- Last 7 days
-
haond.hashnode.dev haond.hashnode.dev
-
Mức điểm 2: Gia sư sử dụng các hình ảnh gợi ý và đồ vật để kiểm tra sự hiểu biết của học sinh. Mức điểm 3: Gia sư sử dụng đa dạng phương pháp (cử chỉ, ngôn ngữ cơ thể, hình ảnh và đồ vật) để giúp học sinh giao tiếp. Mức điểm 4: Gia sư ghi nhận và mở rộng những chia sẻ của học sinh dựa trên nhận thức và kinh nghiệm của học sinh/giáo viên.
Hiện tại em đang ở mức điểm 2 – em có sử dụng hình ảnh và đồ vật để hỗ trợ học sinh giao tiếp. Tuy nhiên, em gặp một số khó khăn để tiến xa hơn:
🔍 Kết nối sâu sắc là điều không dễ: Ngay cả với giáo viên là người Việt như em, việc thiết lập những kết nối sáng tạo và thực sự sâu sắc với học sinh là điều rất khó, vì bị giới hạn bởi cả ngôn ngữ, văn hóa lẫn bối cảnh lớp học.
🙁 Câu hỏi mở thường không có “mở”: Những dạng câu hỏi như “Do you like...?” hoặc “What do you do after school?” về lý thuyết là "câu hỏi mở", nhưng trên thực tế chỉ dẫn đến những câu trả lời ngắn, không tạo được đà tương tác.
**🔤 Năng lực ngôn ngữ là rào cản đôi chiều: ** Học sinh có vốn tiếng Anh còn hạn chế, nên dù có động lực chia sẻ, các em cũng khó diễn đạt.
Giáo viên cũng không thể “vượt ngôn ngữ” để dẫn dắt sâu, trừ khi có kỹ thuật hỗ trợ cực kỳ cụ thể và phù hợp với trình độ.
🧠 Khái niệm “hỗ trợ phát triển ngôn ngữ” rất mơ hồ nếu không được làm rõ: Việc kỳ vọng giáo viên "phản hồi và mở rộng trải nghiệm học sinh" cần có mô hình, ví dụ minh họa cụ thể. Nếu không, giáo viên rất dễ rơi vào tình trạng “biết nên làm gì, nhưng không biết làm sao”.
📌 Em nghĩ rằng ngay cả đội học liệu cũng sẽ gặp khó khăn trong việc clarify (làm rõ) yêu cầu này nếu không tiếp cận một cách hệ thống:
🎯 Kỳ vọng của em: Em không mong hướng dẫn hoàn hảo, nhưng rất cần những chỉ dẫn đủ cụ thể – đơn giản – hiệu quả để:
Vượt qua sự mơ hồ
Làm được điều nhỏ trước, rồi mới đến sáng tạo sâuHiện tại em đang ở mức điểm 2 – em có sử dụng hình ảnh và đồ vật để hỗ trợ học sinh giao tiếp. Tuy nhiên, em gặp một số khó khăn để tiến xa hơn, cụ thể:
🔍 Khó kết nối sâu sắc: Ngay cả với giáo viên là người Việt như em, việc kết nối sáng tạo và sâu sắc với học sinh vẫn là một thách thức.
🙁 Câu hỏi qua loa không hiệu quả: Các câu hỏi như “Do you like...?”, “What do you do after school?” thường chỉ nhận lại phản hồi ngắn (Yes/No) và không tạo được động lực cho học sinh nói thêm.
🔤 Học sinh hạn chế ngôn ngữ: Trình độ tiếng Anh của học sinh còn thấp khiến việc chia sẻ sâu hoặc trò chuyện tự nhiên gặp nhiều rào cản.
🧑🏫 Vai trò của giáo viên Việt: Em hiểu vai trò của mình không phải là “hóa thân thành người bản xứ” mà là người dẫn dắt thông qua kỹ thuật sư phạm phù hợp với trình độ và văn hóa học sinh.
🎯 Em mong muốn được hướng dẫn thêm về các kỹ thuật cụ thể, dễ áp dụng, để giúp học sinh vừa cảm thấy thoải mái giao tiếp, vừa phát triển ngôn ngữ một cách tự nhiên và hiệu quả hơn.
-
Mức điểm 1: Gia sư nhận biết được trình độ của từng học sinh trong lớp và sử dụng các tài nguyên trong học liệu phù hợp cho mỗi học sinh. Mức điểm 2: Gia sư sử dụng học liệu đã được cấp nhưng đưa ra các nhiệm vụ khác nhau cho các nhóm học sinh khác nhau dựa trên khả năng, sở trường và tính cách của mỗi học sinh. Mức điểm 3: Gia sư lồng ghép linh hoạt giữa tài liệu được cung cấp và tài liệu bổ sung bên ngoài cho các nhóm học sinh khác nhau dựa trên khả năng, sở trường và tính cách của mỗi học sinh.
Một lần nữa là cần đầu tư nghiên cứu 🙃. Hiện tại em chỉ đáp ứng được mức 1 — nhận biết được trình độ học sinh để chọn phần học liệu phù hợp. Các mức cao hơn cần chuẩn bị kỹ và học hỏi thêm ạ.
-
Mức điểm 1: Từ vựng HOẶC cấu trúc câu được dạy trong ngữ cảnh. Mức điểm 2: Cả từ vựng và cấu trúc câu đều được dạy trong ngữ cảnh. Mức điểm 3: Cả từ vựng và cấu trúc câu được dạy trong ngữ cảnh và liên hệ với kiến thức học sinh đã có nhằm giúp học sinh hiểu một cách dễ dàng và áp dụng hiệu quả.
Em nghĩ cách dạy hiện tại của mình đang nghiêng về mức 1, vì em thường giới thiệu từ vựng kèm hình ảnh để học sinh phát âm, sau đó cho học sinh ghép từ với hình ảnh. Với phần ngữ pháp, em cung cấp trực tiếp quy tắc và ví dụ, rồi cho học sinh làm bài tập áp dụng.
Cách tiếp cận của em mang tính suy diễn (deductive reasoning) – nghĩa là học sinh được tiếp cận kiến thức rõ ràng ngay từ đầu trước khi luyện tập – thay vì khám phá ngữ pháp qua ví dụ (inductive). Tuy về hình thức có vẻ thụ động, nhưng em cho rằng đây là cách đơn giản, hiệu quả và phù hợp với nhiều học sinh trình độ cơ bản.
🧠 Lập luận so sánh: Deductive vs. Inductive reasoning (trong dạy ngữ pháp cho EFL learners) Tiêu chí Deductive reasoning Inductive reasoning Cách tiếp cận Cung cấp quy tắc rõ ràng → học sinh luyện tập áp dụng. Đưa ví dụ → học sinh tự khám phá quy tắc ngữ pháp. Thời gian & sự rõ ràng Hiểu nhanh, tiết kiệm thời gian – đặc biệt hữu ích trong lớp học có thời lượng hạn chế. Tốn thời gian hơn, học sinh dễ rơi vào suy đoán sai nếu thiếu vốn từ/ngữ cảnh. Phù hợp với trình độ nào Rất phù hợp với học sinh trình độ thấp – vốn từ và ngữ cảm chưa đủ để tự rút quy tắc. Thường chỉ phù hợp với học sinh có vốn tiếng Anh phong phú, thường xuyên tiếp xúc với ngôn ngữ (như người bản ngữ). Tính khả thi trong lớp học EFL Cao – giáo viên chủ động điều tiết nội dung, học sinh dễ theo dõi và luyện tập. Thấp – yêu cầu thời gian, kỹ năng ngôn ngữ nền tốt, khó áp dụng đồng đều cho cả lớp.
📌 Lý do chính: Học sinh EFL không được "expose" (tiếp xúc tự nhiên) với ngôn ngữ như người bản ngữ, nên việc tự suy luận ngữ pháp từ ví dụ thường gây nhiễu hoặc hiểu sai.
Trong khi đó, phương pháp deductive cung cấp khung ngữ pháp rõ ràng, giúp học sinh dễ dàng kết nối với bài tập, kiểm tra và củng cố kiến thức ngay trong buổi học.
-
Mức điểm 2: Gia sư đặt những câu hỏi liên quan để liên hệ kiến thức nền của học sinh với các khái niệm chính của bài học. Mức điểm 3: Gia sư vận dụng những phương pháp sáng tạo (video/ câu truyện) để tạo cơ hội liên hệ kiến thức nền và trải nghiệm của học sinh với các khái niệm chính của bài học. Mức điểm 4: Gia sư tạo cơ hội cho học sinh thảo luận theo cặp/nhóm để liên hệ kiến thức nền và trải nghiệm của học sinh với bài học.
Hiện tại, em mới đạt được mức 2 – em có thể đặt các câu hỏi liên quan để liên hệ kiến thức nền của học sinh với bài học. Tuy nhiên, để đạt được mức 3 và 4, em nhận thấy cần đầu tư thêm thời gian cho việc chuẩn bị bài giảng (tìm kiếm video, hình ảnh, tình huống, hoạt động phù hợp...). Em hy vọng bên học liệu có thể hỗ trợ thiết kế sẵn các ý tưởng khởi động sáng tạo hoặc hoạt động liên hệ trải nghiệm để giảm tải phần chuẩn bị cho giáo viên ạ.
-
Mức điểm 0: Học sinh không có cơ hội làm việc theo cặp/nhóm. Mức điểm 1: Học sinh được khuyến khích đặt câu hỏi và chia sẻ quan điểm của mình với bạn bè. Mức điểm 2: Gia sư có tổ chức các hoạt động theo cặp/nhóm đã được thiết kế theo học liệu.
Em nghĩ mình hiện đang ở mức 0 hoặc mức 1. Trong giờ học, nếu học liệu có phần đóng vai hoặc hỏi – đáp, học sinh sẽ có cơ hội tương tác với nhau. Tuy nhiên, mức độ tương tác này vẫn còn đơn giản và khá hạn chế, chủ yếu do rào cản về năng lực ngôn ngữ. Học sinh cần có đủ vốn từ vựng và cấu trúc câu thì mới có thể thực sự tham gia giao tiếp hiệu quả. Với các lớp nhỏ tuổi hoặc trình độ thấp, các em thường chỉ dừng lại ở việc lặp lại mẫu câu.
Tuy vậy, trong thời gian tới, em sẽ đầu tư thêm vào việc nghiên cứu và ứng dụng các hình thức tương tác đơn giản nhưng hiệu quả, cụ thể theo hai hướng sau:
-
Tăng cường tương tác hỏi – đáp giữa học sinh thông qua các trò chơi hoặc hoạt động đóng vai ngắn + fill in the blank
-
Tổ chức linh hoạt các hoạt động cặp/nhóm từ học liệu để học sinh có cơ hội lắng nghe và phản hồi lẫn nhau nhiều hơn.
VD: 🎯 Gợi ý trò chơi: Find Someone Who...
✅ Mục tiêu: Giúp học sinh luyện mẫu câu hỏi và trả lời, đồng thời khuyến khích di chuyển và tương tác trong lớp học.
🧩 Cách triển khai phù hợp với học sinh trình độ thấp: Ví dụ: Luyện mẫu câu “Do you like...?”
Giáo viên chuẩn bị bảng câu hỏi:
Find someone who... Tên ...likes cats.<br /> ...likes apples. <br /> ...likes dancing. <br /> ...likes ice cream.
Học sinh sẽ đi hỏi bạn bè trong lớp: → “Do you like cats?” → Nếu bạn trả lời “Yes, I do.” thì ghi tên bạn đó vào ô tương ứng.
⏱ Sau 5 phút: Cả lớp ngồi lại và chia sẻ: → “I found Linh. She likes cats!”
✏️ Mẫu câu cần luyện trước khi chơi:
Hỏi: “Do you like ___?”
Trả lời: “Yes, I do.” / “No, I don’t.”
👉 Em hy vọng trong tương lai, bên học liệu cũng sẽ thiết kế thêm nhiều hoạt động tương tác như vậy để em được “nhàn hơn” mà lớp vẫn vui ạ!
-
-
Mức điểm 3: Gia sư ghi nhận nỗ lực phát biểu của học sinh và khuyến khích học sinh phát biểu thêm (VD: thank you, very good, great idea, keep it up...)
Em đạt được mức 3 trong tiêu chí này nên cảm thấy khá vui 😃 và có thêm động lực. Em luôn cố gắng ghi nhận nỗ lực phát biểu của học sinh bằng lời khen cụ thể như “Good job!”, “Great idea!”, hoặc “Keep going!”, để khuyến khích các em tiếp tục tham gia. Trong thời gian tới, em sẽ tiếp tục rèn thêm kỹ năng đặt câu hỏi mở và tạo điều kiện để học sinh chủ động hơn trong việc tương tác.
-
Mức điểm 0: Gia sư không dạy đầy đủ toàn bộ nội dung của học liệu.
Em thường Freestyle nên hay bị điểm 0. 😖
Em có xu hướng dạy linh hoạt vì em coi mỗi giờ học là một trải nghiệm mới, và em tin rằng học sinh có học được gì đi chăng nữa đều là điều đáng quý. Vì vậy, em không quá rập khuôn về thời gian phân bổ cho từng phần, mà điều chỉnh theo tình hình thực tế.
Tuy nhiên, em vẫn luôn đảm bảo dạy đầy đủ và theo đúng trình tự các phần trong học liệu. Em chỉ linh hoạt trong cách triển khai để mỗi buổi học diễn ra tự nhiên, phù hợp với học sinh và tạo được sự thoải mái, hứng thú khi học tập.
-
Mức điểm 2: Gia sư sử dụng ngôn ngữ (tiếng Anh/ tiếng Việt) phù hợp với trình độ của học sinh và có vận dụng ngôn ngữ cơ thể một cách hiệu quả để đảm bảo học sinh hiểu. Mức điểm 3: Gia sư tạo môi trường tương tác giữa học sinh (Học sinh - Gia sư, Học sinh - Học sinh) trong lớp để khích lệ học sinh sử dụng tiếng Anh một cách hiệu quả và tạo sáng tạo hơn.
Em đang ở mức điểm 2. Em đã sử dụng ngôn ngữ phù hợp với trình độ học sinh, kết hợp linh hoạt tiếng Anh – tiếng Việt giúp các em hiểu bài tốt hơn.
Em hy vọng tình hình sẽ cải thiện khi em làm tốt ở Tiêu chí 3 – Môi trường tương tác giữa các học sinh, vì nếu học sinh có thể tương tác với nhau bằng tiếng Anh nhiều hơn thì khả năng sử dụng ngôn ngữ của cả lớp sẽ được nâng cao một cách tự nhiên.
-
Mức điểm 1: Gia sư đưa ra các hướng dẫn bằng ngôn từ một cách rõ ràng trong mỗi hoạt động giảng dạy. Mức điểm 2: Gia sư sử dụng hiệu quả bộ câu hỏi kiểm tra hướng dẫn (Instruction Checking Questions - ICQs) để kiểm tra mức độ hiểu của học sinh về các chỉ dẫn. Mức điểm 3: Giáo viên đưa hướng dẫn một cách hiệu quả bằng cách sử dụng lời nói và ngôn ngữ cơ thể để giúp học sinh hiểu rõ những gì họ cần làm trong một hoạt động. Mức điểm 4: Học sinh có thể hiểu và thực hành được ít nhất 80% hoạt động trong lớp theo hướng dẫn của Gia sư trong các hoạt động/nhiệm vụ.
Em đang ở mức điểm 1. Trong giờ học, em thường đưa ra hướng dẫn bằng lời một cách rõ ràng, sau đó kiểm tra sự hiểu của học sinh bằng cách quan sát hành vi thực tế đúng/sai (true/false behaviour checking) – ví dụ như học sinh có làm đúng yêu cầu không – thay vì sử dụng các câu hỏi kiểm tra chỉ dẫn (ICQs). Em thấy đây là cách nhanh và hiệu quả trong bối cảnh lớp học hiện tại.
Ngoài ra, em rất ấn tượng với cách sử dụng ngôn ngữ cơ thể của một số giáo viên để tăng sự rõ ràng và sinh động. Tuy nhiên, em chưa dành thời gian luyện tập kỹ năng này, nên vẫn chưa áp dụng được nhiều. Em mong muốn sẽ cải thiện điều này trong thời gian tới.
-
Mức điểm 2: Gia sư luôn ra hiệu cho học sinh trước khi chuyển sang hoạt động tiếp theo. (VD: Now, we're gonna learn about vocabulary/Let's move on to grammar). Mức điểm 3: Gia sư kết hợp các kỹ thuật chuyển hoạt động một cách có chủ đích và hiệu quả trong giờ học. (VD: bài hát, câu hát, nhịp điệu, vỗ tay, vv + let's move on to...)
Các phần đề mục trong buổi học thường theo một khung cố định và được lặp lại qua nhiều buổi, nên em ưu tiên chuyển hoạt động một cách ngắn gọn, rõ ràng, chủ yếu mang tính thông báo nhằm tiết kiệm thời gian và đảm bảo sự liền mạch của tiết học. Vì vậy, em hiện chưa áp dụng các kỹ thuật chuyển hoạt động mang tính sáng tạo như bài hát, vỗ tay hay trò chơi nhỏ.
Trừ khi hoạt động tiếp theo là phần nội dung trọng tâm, em mới dành thời gian dẫn dắt kỹ hơn để học sinh hiểu rõ mục tiêu và chuẩn bị tinh thần.
Tóm lại, em tin rằng sự nhất quán và đơn giản trong cách chuyển hoạt động, nếu được sử dụng phù hợp với đặc điểm lớp học, vẫn có thể giúp học sinh duy trì được nhịp lớp và tập trung vào nội dung chính một cách hiệu quả.
-
-
mijn.bsl.nl mijn.bsl.nl
-
Hier, neem deze folder maar mee, dan kunt u het thuis nog eens op uw gemak nalezen.
Buyurun, bu broşürü yanınıza alın, böylece evde rahatça tekrar okuyabilirsiniz.
-
Ik zou me geen raad weten!
Aklım durur vallahi!
-
We hebben er natuurlijk niks aan als u straks in het ziekenhuis ligt.
Sonuçta sizin birazdan hastaneye düşmenizin bize bir faydası olmaz.
-
Ik ben een en al oor, zegt u het maar.
tüm kulağım sizde, anlatın.
-
-
hypothes.is hypothes.is
-
8???? # ??????? 9 ??? ????/ # )l?+?? ?%- .//???? j0q-R-??????? ?? ??ª?? )n??? ?? £ ? <} )Q %?." .Q ?? ?75? ³07 9?3U?? KL?3?O-??O?? ?? 6?}?? # ?)- )'U?? < < )? »? ?q? ?? <', M?
?W. ¼ k? Ty? !? ??^%* J??q ?? ?6?4,Q ??½ T< ? %-Q U* ?!??? 6?X #?$¤? " ??+,?{j?+" ??" )?%! ?? 2?! ? . 3U+?? # ??'?? ? Z?¾ 6?4,]? K75?j5 : "??c ??? ??%?? ? ? ??? ??³
??? T<???? M?, / ?? # <??4??" =Q )3???? ?? Z??? ?- 4, - ¿?}?'?)#%?~be5( )???q (??? ?75 ?!u # ) ? £ ?? ?.s ? /%4 . ?+3? T 5?3!?? # 2?! ̄! (??? ?<^ ?<}?\a~8. ?" n?3???? ?'
??? ???????? .<+??" ? 4 ?? ?75 ?< F ? B # KcdQ ?? A5Q ?? ? ??? -j?????? ?!??? 6?X # T< ? %-Q .? ) ' ??<^? ?+3? T 5?!?? # I?]\ab8 .?"T< ? %-Q ????, ?,? ?5??? ??- ,? ????? %" ?+3? T 5?3!?? # ?<^? ?\a8. ?"6%^]? $?% /".?%-???+?? <4 <? ? <?? =] ?. ?" T 3À # ?3??!??4S?" ?+? U? ?A&?m? ?- ????? ?\aa\8. 6?4,Q ??½ T< ? %-Q U ?; ?? 6?X #? .? A?3?S? <', < ̈Q ?%0<?? 8?3, )3C 73+? ?3; ?? Q<- )Q Á"? ?T< ? %-Q 6?4,Q # R"?'?? $Q ???`,\ae~ ±?%" ? 4??? ?8f? μ?L < - ?+? T U,. ??? ?'!S? K75 #?–? ?+ - % T<, ??4?? ?3?"?+?? <0??? ?Z?C ?? ??????? ??????? ?+4? ?? PÂ?%F? ?? ??4? ?? ® Z?C ?.a ?T<3 ? %-Q ? ?? ?? 6?4,]? A5Q $Q ? 0q /?? ? '? ? n? ?? )??; ? ???????? ??????? # R¾ ?Q (?0 0 # // )Ã? J? C?[} U??? ??'0 6?4,Q.\b ?]? ??3+? ???'+C]? ??H??? ?? < < ?? ?! $?0 )Q T< ? %-Q ?, ¶ ,? ?3??? ? c??d?????? ???* ??????%???? ??+?????0 ?g<!?? ??H??? -? ?????????? ???'?. (?0 ?,%4X .???4? ?? ?@?? ??& ? D @EF @*G ???@? ?-?? PC ? ?\a. { ?-???? PC ??{. a ?-???? PC ??\b{. \b ?-???? PC ??\a.
-
-
www.spacemacs.org www.spacemacs.org
-
Why Spacemacs?
Because vim bindings are Greb
-
-
www.biorxiv.org www.biorxiv.org
-
eLife Assessment
This study reports important negative results by showing that genetic removal of the RNA-binding protein PTBP1 in astrocytes is not sufficient to induce their conversion into neurons, challenging prior claims in the field. It also provides a systematic and insightful analysis of the role of PTBP1 in regulating astrocyte-specific splicing. The evidence is convincing, as the experiments are technically robust, rigorously controlled, and supported by both imaging and transcriptomic analyses.
-
Reviewer #1 (Public review):
Summary:
Zhang et al. used a conditional knockout mouse model to re-examine the role of the RNA-binding protein PTBP1 in the transdifferentiation of astroglial cells into neurons. Several earlier studies reported that PTBP1 knockdown can efficiently induce the transdifferentiation of rodent glial cells into neurons, suggesting potential therapeutic applications for neurodegenerative diseases. However, these findings have been contested by subsequent studies, which in turn have been challenged by more recent publications. In their current work, Zhang et al. deleted exon 2 of the Ptbp1 gene using an astrocyte-specific, tamoxifen-inducible Cre line and investigated, using fluorescence imaging and bulk and single-cell RNA-sequencing, whether this manipulation promotes the transdifferentiation of astrocytes into neurons across various brain regions. The data strongly indicate that genetic ablation of PTBP1 is not sufficient to drive efficient conversion of astrocytes into neurons. Interestingly, while PTBP1 loss alters splicing patterns in numerous genes, these changes do not shift the astroglial transcriptome toward a neuronal profile.
Strengths:
Although this is not the first report of PTBP1 ablation in mouse astrocytes in vivo, this study utilizes a distinct knockout strategy and provides novel insights into PTBP1-regulated splicing events in astrocytes. The manuscript is well written, and the experiments are technically sound and properly controlled. I believe this study will be of considerable interest to a broad readership.
Weaknesses:
(1) The primary point that needs to be addressed is a better understanding of the effect of exon 2 deletion on PTBP1 expression. Figure 4D shows successful deletion of exon 2 in knockout astrocytes. However, assuming that the coverage plots are CPM-normalized, the overall PTBP1 mRNA expression level appears unchanged. Figure 6A further supports this observation. This is surprising, as one would expect that the loss of exon 2 would shift the open reading frame and trigger nonsense-mediated decay of the PTBP1 transcript. Given this uncertainty, the authors should confirm the successful elimination of PTBP1 protein in cKO astrocytes using an orthogonal approach, such as Western blotting, in addition to immunofluorescence. They should also discuss possible reasons why PTBP1 mRNA abundance is not detectably affected by the frameshift.
(2) The authors should analyze PTBP1 expression in WT and cKO substantia nigra samples shown in Figure 3 or justify why this analysis is not necessary.
(3) Lines 236-238 and Figure 4E: The authors report an enrichment of CU-rich sequences near PTBP1-regulated exons. To better compare this with previous studies on position-specific splicing regulation by PTBP1, it would be helpful to assess whether the position of such motifs differs between PTBP1-activated and PTBP1-repressed exons.
(4) The analyses in Figure 5 and its supplement strongly suggest that the splicing changes in PTBP1-depleted astrocytes are distinct from those occurring during neuronal differentiation. However, the authors should ensure that these comparisons are not confounded by transcriptome-wide differences in gene expression levels between astrocytes and developing neurons. One way to address this concern would be to compare the new PTBP1 cKO data with publicly available RNA-seq datasets of astrocytes induced to transdifferentiate into neurons using proneural transcription factors (e.g., PMID: 38956165).
-
Reviewer #2 (Public review):
Summary:
The manuscript by Zhang and colleagues describes a study that investigated whether the deletion of PTBP1 in adult astrocytes in mice led to an astrocyte-to-neuron conversion. The study revisited the hypothesis that reduced PTBP1 expression reprogrammed astrocytes to neurons. More than 10 studies have been published on this subject, with contradicting results. Half of the studies supported the hypothesis while the other half did not. The question being addressed is an important one because if the hypothesis is correct, it can lead to exciting therapeutic applications for treating neurodegenerative diseases such as Parkinson's disease.
In this study, Zhang and colleagues conducted a conditional mouse knockout study to address the question. They used the Cre-LoxP system to specifically delete PTBP1 in adult astrocytes. Through a series of carefully controlled experiments, including cell lineage tracing, the authors found no evidence for the astrocyte-to-neuron conversion.
The authors then carried out a key experiment that none of the previous studies on the subject did: investigating alternative splicing pattern changes in PTBP1-depleted cells using RNA-seq analysis. The idea is to compare the splicing pattern change caused by PTBP1 deletion in astrocytes to what occurs during neurodevelopment. This is an important experiment that will help illuminate whether the astrocyte-to-neuron transition occurred in the system. The result was consistent with that of the cell staining experiments: no significant transition was detected.
These experiments demonstrate that, in this experimental setting, PTBT1 deletion in adult astrocytes did not convert the cells to neurons.
Strengths:
This is a well-designed, elegantly conducted, and clearly described study that addresses an important question. The conclusions provide important information to the field.<br /> To this reviewer, this study provided convincing and solid experimental evidence to support the authors' conclusions.
Weaknesses:
The Discussion in this manuscript is short and can be expanded. Can the authors speculate what led to the contradictory results in the published studies? The current study, in combination with the study published in Cell in 2021 by Wang and colleagues, suggests that observed difference is not caused by the difference of knockdown vs. knockout. Is it possible that other glial cell types are responsible for the transition? If so, what cells? Oligodendrocytes?
-
Author response:
Reviewer #1 (Public review):
Summary:
This study investigates how mice make defensive decisions when exposed to visual threats and how those decisions are influenced by reward value and social hierarchy. Using a naturalistic foraging setup and looming stimuli, the authors show that higher threat leads to faster escape, while lower threat allows mice to weigh reward value. Dominant mice behave more cautiously, showing higher vigilance. The behavioral findings are further supported by a computational model aimed at capturing how different factors shape decisions.
Strengths:
(1) The behavioral paradigm is well-designed and ethologically relevant, capturing instinctive responses in a controlled setting.
(2) The paper addresses an important question: how defensive behaviors are influenced by social and value-based factors.
(3) The classification of behavioral responses using machine learning is a solid methodological choice that improves reproducibility.
Weaknesses:
(1) Key parts of the methods are hard to follow, especially how trials are selected and whether learning across trials is fully controlled for. For example, it is unclear whether animals are in the nest during the looming stimulus presentations. The main text and methods should clarify whether multiple mice are in the nest simultaneously and whether only one mouse is in the arena during looming exposure. From the description, it seems that all mice may be freely exploring during some phases, but only one is allowed in the arena at a time during stimulus presentation. This point is important for understanding the social context and potential interactions, and should be clearly explained in both the main text and methods.
When the door system operated normally, only one mouse was allowed in the arena at a time. Specifically, when all mice were in the nest, the door between the nest and the tunnel was left open, while the door between the tunnel and the arena remained closed. When a single mouse entered the tunnel, as detected by the OpenMV camera, the door to the nest closed and the door to the arena opened, allowing only that mouse to enter the arena.
All mice were habituated to the behavioral platform for two days before the looming test. On the first day, five mice from the same home cage were placed in the nest for 30 minutes with all doors closed. Then, under normal door operation, each mouse was allowed to explore the arena individually for at least 10 minutes and access the reward at least twice. Afterward, all five mice were returned to the nest, and all doors were opened to allow free exploration of the arena for two hours. This phase ensured that each mouse learned that a reward was available at the end of the linear arena. On the second day, each mouse was given one hour to explore the arena individually under normal door operation.
On the third day, mice were exposed to the looming stimuli under normal door operation. The stimulus was triggered when the mouse’s position was detected within 20 cm of the reward port located at the end of the arena.
We will clarify these details in the main text and Methods section.
(2) It is often unclear whether the data shown (especially in the main summary figures) come from the first trial or are averages across several exposures. When is the cut-off for trials of each animal? How do we know how many trial presentations were considered, and how learning at different rates between individuals is taken into account when plotting all animals together? This is important because the looming stimulus is learned to be harmless very quickly, so the trial number strongly affects interpretation.
Because the probability of defensive responses decreased from nearly 100% to ~70% over the first five trials and then remained relatively stable through the 10th trial, the data shown in Figures 3, 4 and 5 were taken from the first 10 trials. To account for individual differences in learning rate, we will validate our findings using only the first trials and incorporate individual-level analyses of learning rates and decision patterns in the revised manuscript.
(3) The reward-related effects are difficult to interpret without a clearer separation of learning vs first responses.
As noted above, we will re-analyze reward-related data using only the first trials to separate reward effects from learning.
(4) The model reproduces observed patterns but adds limited explanatory or predictive power. It does not integrate major findings like social hierarchy. Its impact would be greatly improved if the authors used it to predict outcomes under novel or intermediate conditions.
We will expand the model to incorporate the effects of social hierarchy on decision-making and predict outcomes under novel conditions.
(5) Some conclusions (e.g., about vigilance increasing with reward) are counterintuitive and need stronger support or alternative explanations. Regarding the interpretation of social differences in area coverage, it's also possible that the observed behavioral differences reflect access to the nesting space. Dominant mice may control the nest, forcing subordinates to remain in the open arena even during or after looming stimuli. In this case, subordinates may be choosing between the threat of the dominant mouse and the external visual threat. The current data do not distinguish between these possibilities, and the authors do not provide evidence to support one interpretation over the other. Including this alternative explanation or providing data that addresses it would strengthen the conclusions.
We compared differences in total arena visit duration between dominant and subordinate mice across three phases: before, during, and after looming exposure (Figure 4C). Subordinates spent significantly more time in the arena prior to looming exposure, suggesting that subordinates perceived a threat from dominant conspecifics in the absence of external visual threat. However, this difference disappeared during and after looming exposure, indicating that the social threat relationship may be altered by the presence of an external threat, and that subordinates adapt to the conspecific threat under such conditions. To further validate this shift in their relationship, we will analyze their behaviors in the nest as suggested.
(6) While potential neural circuits are mentioned in the discussion, an earlier introduction of candidate brain regions and their relevance to threat and value processing would help ground the study in existing systems neuroscience.
We will revise the Introduction to incorporate relevant brain regions and neural circuits involved in threat and value processing.
(7) Some figures are difficult to interpret without clearer trial/mouse labeling, and a few claims in the text are stronger than what the data fully support. Figure 3H is done for low contrast, but the interesting findings will be to do this experiment with high contrast. Figure 4H - I don't understand this part. If the amount of time in the center after the loom changes for subordinate mice, how does this lead to the conclusion that they spend most of their time in the reward zone?. Figure 3A - The example shown does not seem representative of the claim that high contrast stimuli are more likely to trigger escape. In particular, the 10% sucrose condition appears to show more arena visits under low contrast than high contrast, which seems to contradict that interpretation. Also, the plot currently uses trials on the Y-axis, but it would be more informative to show one line per animal, using only the first trial for each. This would help separate initial threat responses from learning effects and clarify individual variability.
Figure 3H includes data from both low- and high-contrast conditions. We will clarify this in the figure legend.
Regarding Figure 4H, we are not entirely certain about the concern. In this panel, we measured time spent in the reward zone, not the center of the arena, during looming exposure. Subordinate mice spent significantly more time in the reward zone than dominant mice.
In Figure 3A, under high-contrast conditions, animals were more likely to escape to the nest with shorter latency and spent less time in the reward zone, which was especially evident in the 10% sucrose condition. To better separate initial threat responses from learning effects and to highlight individual variability, we will re-plot Figure 3A using only the first trials for each mouse and include this as a supplementary figure.
(8) The analysis does not explore individual variability in behavior, which could be an important source of structure in the data. Without this, it is difficult to know whether social hierarchy alone explains behavioral differences or if other stable traits (e.g., anxiety level, prior experiences) also contribute.
To attribute the observed behavioral differences specifically to social hierarchy rather than other individual traits, we will conduct paired comparisons between dominant and subordinate mice and incorporate analyses of individual variability.
(9) The study shows robust looming responses in group-housed animals, which contrasts with other studies that often require single housing to elicit reliable defensive responses. It would be valuable for the authors to discuss why their results differ in this regard and whether housing conditions might interact with social rank or habituation.
Looming exposure elicits robust defensive behaviors in both group- and single-housed mice (Yilmaz and Meister, 2013, Lenzi et al., 2022), with group-housed animals habituating more quickly to the stimulus (Lenzi et al., 2022). We will discuss this in the revised Discussion, including potential interactions between housing, rank, and habituation.
Reviewer #2 (Public review):
Zhe Li and colleagues investigate how mice exposed to visual threats and rewards balance their decisions in favour of consuming rewards or engaging in defensive actions. By varying threat intensity and reward value, they first confirm previous findings showing that defensive responses increase with threat intensity and that there is habituation to the threat stimulus. They then find that water-deprived mice have a reduced probability of escaping from low contrast visual looming stimuli when water or sucrose are offered in the environment, but that when the stimulus contrast is high, the presence of sucrose or water increases the probability of escape. By analysing behaviour metrics such as the latency to flee from the threat stimulus, they suggest that this increase in threat sensitivity is due to increased vigilance. Analysis of this behaviour as a function of social hierarchy shows that dominant mice have higher threat sensitivity, which is also interpreted as being due to increased vigilance. These results are captured by a drift diffusion model variant that incorporates threat intensity and reward value.
The main contribution of this work is to quantify how the presence of water or sucrose in water-deprived mice affects escape behaviour. The differential effects of reward between the low and high contrast conditions are intriguing, but I find the interpretation that vigilance plays a major role in this process is not supported by the data. The idea that reward value exerts some form of graded modulation of the escape response is also not supported by the data. In addition, there is very limited methodological information, which makes assessing the quality of some of the analyses difficult, and there is no quantification of the quality of the model fits.
(1) The main measure of vigilance in this work is reaction time. While reaction time can indeed be affected by vigilance, reaction times can vary as a function of many variables, and be different for the same level of vigilance. For example, a primate performing the random dot motion task exhibits differences in reaction times that can be explained entirely by the stimulus strength. Reaction time is therefore not a sound measure of vigilance, and if a goal of this work is to investigate this parameter, then it should be measured. There is some attempt at doing this for a subset of the data in Figure 3H, by looking at differences in the action of monitoring the visual field (presumably a rearing motion, though this is not described) between the first and second trials in the presence of sucrose. I find this an extremely contrived measure. What is the rationale for analysing only the difference between the first and second trials? Also, the results are only statistically significant because the first trial in the sucrose condition happens to have zero up action bouts, in contrast to all other conditions. I am afraid that the statistics are not solid here. When analysing the effects of dominance, a vigilance metric is the time spent in the reward zone. Why is this a measure of vigilance? More generally, measuring vigilance of threats in mice requires monitoring the position of the eyes, which previous work has shown is biased to the upper visual field, consistent with the threat ecology of rodents.
We agree that reaction time can be influenced by multiple factors, including stimulus strength. Consistent with this, reaction times (i.e. latencies to flee) were substantially shorter under high-contrast conditions (Figure 3E). However, even under the same high-contrast condition, reaction times were significantly shorter in the water condition compared to the no-reward condition, suggesting that other factors such as vigilance may contribute.
Upward-directed attention includes rearing, up-stretching, and upward head orientation, which will be clarified in the Method section. To address concerns about statistical validity, we will quantify these behaviors across the first 10 trials rather than limiting the analysis to the first two.
As for the dominance-related results, we interpret them as reflecting both enhanced vigilance and reduced reward-seeking behavior. Time spent in the reward zone is not a measure of vigilance but an indicator of reward-seeking motivation. We will clarify this in the revised manuscript.
(2) In both low and high contrast conditions, there are differences in escape behaviour between no reward and water or sucrose presence, but no statistically significant differences between water and sucrose (eg, Figure 3B). I therefore find that statements about reward value are not supported by the data, which only show differences between the presence or absence of reward. Furthermore, there is a confound in these experiments, because according to the methods, mice in the no-reward condition were not water deprived. It is thus possible that the differences in behaviour arise from differences in the underlying state.
In Figure 3B, the difference between water and sucrose conditions did not reach statistical significance (p = 0.08). We plan to collect additional data to determine whether this is due to limited statistical power. It is also possible that some behavioral readouts are more sensitive to the differences between water and sucrose conditions. For example, Figure 3F shows that escape speed was significantly higher in the sucrose than in the water condition under high-contrast stimulation.
Thank you for pointing this out. To control for the potential confounds related to internal state, mice were not water-deprived under any of the three conditions in Figures 3A-3H. We will clarify this in the main text and Methods. For Figures 3I-3M, which compare decision-making under no-reward and water conditions, we will conduct additional experiments using non-deprived mice in the water condition.
(3) There is very little methodological information on behavioural quantification. For example, what is hiding latency? Is this the same are reaction time? Time to reach the safe zone? What exactly is distance fled? I don't understand how this can vary between 20 and 100cm. Presumably, the 20cm flights don't reach the safe place, since the threat is roughly at the same location for each trial? How is the end of a flight determined? How is duration measured in reward zone measures, e.g., from when to when? How is fleeing onset determined?
Hiding latency was defined as the time from stimulus onset to the animal’s arrival at the safe zone. Reaction time was quantified as the latency to flee, measured from stimulus onset to the initiation of the first flight state. The flight state was defined as locomotion exceeding 10 cm at a speed greater than 10 cm/s. Distance fled was defined as the distance covered between stimulus onset and offset for all trials. However, in trials classified as no reaction or freezing, this measure does not accurately reflect escape behavior. We will therefore rename it as distance under threat to better capture its meaning. The reward zone was defined as the region within 15 cm of the reward port at the end of the arena. Duration in the reward zone was measured as the time spent within this region during the 20 seconds following stimulus onset. In Figure 4E, the percentage of time spent in the reward zone was calculated relative to the total time the mouse remained in the arena during the 2-hour social session.
All definitions and additional details on behavioral quantification will be included in the revised Methods section.
(4) There is little methodological information on how the model was fit (for example, it is surprising that in the no reward condition, the r parameter is exactly 0. What this constrained in any way), and none of the fit parameters have uncertainty measures so it is not possible to assess whether there are actually any differences in parameters that are statistically significant.
We appreciate the comment and agree that further clarification is needed. We will provide a more detailed description of the model fitting procedure in the revised Methods section. Specifically, the drift rate parameter (r), which reflects the perceived reward value, was constrained to zero in the no-reward condition. To enable statistical comparison across conditions, we will report uncertainty measures for all fit parameters.
Reviewer #3 (Public review):
Male mice were tested in a classic behavioral "flee the looming stimulus" paradigm. This is a purely behavioral study; no neural analyses were done. Mice were housed socially, but faced the looming stimulus individually. Drift-diffusion modeling found that reward-level interacted with threat level such that at low-threat levels, reward contrasted with threat as classically expected (high reward overwhelms low threat, low threat overwhelms low reward), but that reward aligned with threat at higher threat levels.
Note that they define threat level by the darkness of the looming stimulus. I am not sure that darker stimuli are more threatening to mice. But maybe. Figure 3 shows that mice react more quickly to high contrast looming stimuli, but can the authors distinguish between the ability to detect the visual signal from considering it a more dangerous threat? (The fact that vigilance makes a difference in the high contrast condition, not the low contrast condition, actually supports the author's hypotheses here.)
We thank the reviewer for raising the important point regarding the interpretation of contrast as a proxy for threat level. While increased escape probability and faster reaction times under high-contrast stimuli are consistent with prior work (Evans et al., 2018), they could reflect either improved detection or heightened threat perception.
To disentangle these possibilities, we analyzed not only latency to flee but also distance fled and peak speed, which reflect the intensity of the escape response. If contrast only affected detection, we would expect differences in latency but not in distance or speed. However, all three metrics differed significantly across contrast conditions, supporting the interpretation that high-contrast stimuli are perceived as more threatening, not merely more detectable.
To further clarify this distinction, we will manually examine no-reaction trials to determine whether mice detected the stimulus. In trials classified as “not-threatened”, mice may orient to the stimulus without fleeing; in “not-seen” cases, behavior is unrelated to stimulus onset. If the differece comes from detection, we would expect a higher number of “not-seeen” trials under low-contrast conditions. Conversely, if it reflects threat perception, the difference should be observed in the number of ‘non-threatened’ cases.
The drift-diffusion model (DDM) is fine. I note that the authors included a "leakage rate", which is not a standard DDM parameter (although I like including it). I would have liked to see more about the parameters. What were the distributions? What did the parameters correlate with behaviorally? I would have liked to see distributions of the parameters under the different conditions and different animals. Figure 2C shows the progression of learning. How do the fit parameters change over time as mice shift from choice to choice? How do the parameters change over mice? How do the parameters change over distance to the threat/distance to safety (as per Fanselow and Lester 1988)? They did a supplemental experiment where the threat arrived halfway along the corridor - we could get a lot more detail about that experiment - how did it change the modeling?
We appreciate the reviewer’s comments regarding the modeling. In the revised manuscript, we will include the distribution of model parameters across different conditions and individual animals, along with additional analyses examining how specific parameters relate to behavioral metrics. To better capture individual variability and learning effects, we also plan to fit model parameters across trials for each mouse.
Regarding the influence of distance to safety, our data indicate that it did not significantly affect defensive responses (Figure S2). One possible explanation is that, once a threat is detected, animals prioritize escape over evaluating the proximity to safety. To test this further, we plan to introduce barriers that lengthen the return path to the safe zone, allowing us to assess whether increased distance alters behavior. We will include quantitative analyses, as well as new figures and videos, to support these findings.
We did not examine the effect of distance to threat in our paradigm, as aerial predators typically descend rapidly, giving prey little opportunity to detect and react to the threat at varying distances. This contrasts with terrestrial predator contexts, such as those described in Fanselow and Lester (1988), where prey can observe an approaching threat from a distance and adjust their defensive strategies accordingly.
Overall, this is a reasonable study showing mostly unsurprising results. I think the authors could do more to connect the vigilance question to their results (which seems somewhat new to me).
Thank you for this suggestion. We will expand our analyses to better link vigilance to behavioral outputs.
Although the data appear generally fine and the modeling reasonable, the authors do not do the necessary work to set themselves within the extensive literature on decision-making in mice retreating from threats.
First of all, this is not a new paradigm; variants of this paradigm have been used since at least the 1980s. There is an ‘extensive’ literature on this, including extensive theoretical work on the relation of fear and other motivational factors. I recommend starting with the classic Fanselow and Lester 1988 paper (which they cite, but only in passing), and the reviews by Dean Mobbs and Jeansok Kim, and by Denis Paré and Greg Quirk, which have explicit theoretical proposals that the authors can compare their results to. I would also recommend that the authors look into the "active avoidance" literature. Moreover, to talk about a mouse running from a looming stimulus without addressing the other "flee the predator" tasks is to miss a huge space for understanding their results. Again, I would start with the reviews above, but also strongly urge the authors to look at the Robogator task (work by June-Seek Choi and Jeansok Kim, work by Denis Paré, and others).
We agree that integrating prior literature will strengthen the manuscript. We will revise the Introduction and Discussion to incorporate relevant theories, studies on active avoidance, and other “flee the predator” paradigms, including the Robogator task.
Similarly, in their anatomical review, they do not mention the amygdala. Given the extensive literature on the role of the amygdala in retreating from danger, both in terms of active avoidance and in terms of encoding the danger itself, it would surprise me greatly if this behavior does not involve amygdala processing. (If there is evidence that the amygdala does not play a role here, but that the superior colliculus does, then that would be a *very* important result that needs to be folded into our understanding of decision-making systems and neural computational processing.)
Thank you for highlighting this important point. We will revise the Discussion to address the roles of amygdala and superior colliculus in threat processing.
Second, there is an extensive economic literature on non-human animals in general and on rodents in particular. Again, the authors seem unaware of this work, which would provide them with important data and theories to broaden the impact of their results (by placing them within the literature). First, there are explicit economic literatures in terms of positively-valenced conflicts (e.g., neuroeconomics within the primate literature, sequential foraging and delay-discounting tasks within the rodent literature), but also there is a long history within the rodent conditioning world, such as the classic work by Len Green and Peter Shizgal. I would strongly urge the authors to explore the motivational conflict literature by people like Gavin McNally, Greg Quirk, and Mark Andermann. Again, putting their results into this literature will increase the impact of their experiment and modeling.
We appreciate this valuable recommendation. We will incorporate relevant work from the fields of neuroeconomics, including sequantial foraging and delay-discounting tasks, and studies on motivational conflict in rodents. Integrating these perspectives will help us better frame our task within broader frameworks of decision-making under conflict.
-
-
www.biorxiv.org www.biorxiv.org
-
eLife Assessment
This manuscript presents a valuable methodological approach for investigating context-dependent activity of cis-regulatory elements within defined genomic loci. The authors combine a locus-specific massively parallel reporter assay, enabling unbiased and high-coverage profiling of enhancer activity across large genomic regions, with a degenerate reporter assay to identify nucleotides critical for enhancer function. The data supporting the conclusions are solid, highlighted by the successful identification and characterization of both previously known and new regulatory elements across multiple developmental stages, cell types, and species; however, concerns regarding assay sensitivity, statistical rigor in distinguishing active regions, and limitations inherent to the design of the reporter assays remain to be addressed. With strengthened quantitative analysis, statistical validation, and additional functional experiments to directly establish regulatory element-gene relationships, this study will be of broad interest to researchers investigating gene regulation mechanisms in development and disease.
-
Reviewer #1 (Public review):
MPRAs are a high-throughput and powerful tool for assaying the regulatory potential of genomic sequences. However, linking MPRA-nominated regulatory sequences to their endogenous target genes and identifying the more specific functional regions within these sequences can be challenging. MPRAs that tile a genomic region, and saturation mutagenesis-based MPRAs, can help to address these challenges. In this work, Tulloch et al. describe a streamlined MPRA system for the identification and investigation of the regulatory elements surrounding a gene of interest with high resolution. The use of BACs covering a locus of interest to generate MPRA libraries allows for an unbiased and high-coverage assessment of a particular region. Follow-up degenerate MPRAs, where each nucleotide in the nominated sequences is systematically mutated, can then point to key motifs driving their regulatory activity. The authors present this MPRA platform as straightforward, easily customizable, and less time- and resource-intensive than traditional MPRA designs. They demonstrate the utility of their design in the context of the developing mouse retina, where they first use the LS-MPRA to identify active regulatory elements for select retinal genes, followed by d-MPRA, which allowed them to dissect the functional regions within those elements and nominate important regulatory motifs. These assays were able to recapitulate some previously known cis-regulatory modules (CRMs), as well as identify some new potential regulatory regions. Follow-up experiments assessing co-localization of the gene of interest with the CRM-linked GFP reporter in the target cells, and CUT&RUN assays to confirm transcription factor binding to nominated motifs, provided support linking these CRMs to the genes of interest. Overall, this method appears flexible and could be an easy-to-implement tool for other investigators aiming to study their locus of interest with high resolution.
Strengths:
(1) The method of fragmenting BACs allows for high, overlapping coverage of the region of interest.
(2) The d-MPRA method was an efficient way to identify key functional transcription factor motifs and nominate specific transcription factor-driven regulatory pathways that could be studied further.
(3) Additional assays like co-expression analyses using the endogenous gene promoter, and use of the Notch inhibitor in the case of Olig2, helped correlate the activity of the CRMs to the expression of the gene of interest, and distinguish false positives from the initial MPRA.
(4) The use of these assays across different time points, tissues, and even species demonstrated that they can be used across many contexts to identify both common and divergent regulatory mechanisms for the same gene.
Weaknesses:
The LS-MPRA assay most strongly identified promoters, which are not usually novel regulatory elements you would try to discover, and the signal-to-noise ratio for more TSS-distal, non-promoter regulatory elements was usually high, making it difficult to discriminate lower activity CRMs, like enhancers, from the background. For example, NR2 and NR3 in Figure 3 have very minimal activity peaks (NR3 seems non-existent). The ex vivo data in Figure 2 are similarly noisy. Is there a particular metric or calculation that was or could be used to quantitatively or statistically call a peak above the background? The authors mention in the discussion some adjustments that could reduce the noise, such as increased sequencing depth, which I think is needed to make these initial LS-MPRA results and the benchmarking of this assay more convincing and impactful.
-
Reviewer #2 (Public review):
Summary:
In this study, Tulloch et al. developed two modified massively parallel reporter assays (MPRAs) and applied them to identify cis-regulatory modules (CRMs) - genomic regions that activate gene expression, controlling retinal gene expression. These CRMs usually function at specific developmental stages and in distinct cell types to orchestrate retinal development. Studying them provides insights into how retinal progenitor cells give rise to various retinal cell types.
The first assay, named locus-specific MPRA (LS-MPRA), tests all genomic regions within 150-300 kb of the gene of interest, rather than relying on previously predicted candidate regulatory elements. This approach reduces potential bias introduced during candidate selection, lowers the cost of synthesizing a library of candidate sequences, and simplifies library preparation. The LS-MPRA libraries were electroporated into mouse retinas in vivo or ex vivo. To benchmark the method, the authors first applied LS-MPRA near stably expressed retinal genes (e.g., Rho, Cabp5, Grm6, and Vsx2), and successfully identified both known and novel CRMs. They then used LS-MPRA to identify CRMs in embryonic mouse retinas, near Olig2 and Ngn2, genes expressed in subsets of retinal progenitor cells. Similar experiments were conducted in chick retinas and postnatal mouse retinas, revealing some CRMs with conserved activity across species and developmental stages.
Although the study identified CRMs with robust reporter activity in Olig2+ or Ngn2+ cells, the data do not provide sufficient evidence to support the claims that these CRMs regulate Olig2 or Ngn2, rather than other nearby genes, in a cell-type-specific manner. For example, the authors propose that three regions (NR1/2/3) regulate Olig2 specifically in retinal progenitor cells based on: (1) the three regions are close to Olig2, (2) increased Olig2 expression and NR1/2/3 activity upon Notch inhibition, and (3) reporter activity observed in Olig2+ cells (though also present in many Olig2- cells). While these are promising findings, they do not directly support the claims.
The second assay, called degenerate MPRA (d-MPRA), introduces random point mutations into CRMs via error-prone PCR to assess the impact of sequence variations on regulatory activity. This approach was used on NR1/2/3 to identify mutations that alter CRM activity, potentially by influencing transcription factor binding. The authors inferred candidate transcription factors, such as Mybl1 and Otx2, through motif analysis, co-expression with Olig2 (based on single-cell RNA-seq), and CUR&RUN profiling. While some transcription factors identified in this way overlapped with the d-MPRA results, others did not. This raises questions about how well d-MPRA complements other methods for identifying transcriptional regulators.
Strengths:
(1) The study introduces two technically robust MPRA protocols that offer advantages over standard methods, such as avoiding reliance on predefined candidate regions, reducing cost and labor, and minimizing selection bias.
(2) The identified regulatory elements and transcription factors contribute to our understanding of gene regulation in retinal development and may have translational potential for cell-type-specific gene delivery into developing retinas.
Weaknesses:
(1) The claims for gene-specific and cell type-specific CRMs would benefit from further validation using complementary approaches, such as CRISPR interference or Prime editing.
-
Reviewer #3 (Public review):
Summary:
Use of reporter assays to understand the regulatory mechanisms controlling gene expression moves beyond simple correlations of cis-regulatory sequence accessibility, evolutionary sequence conservation, and epigenetic status with gene expression, instead quantifying regulatory sequence activity for individual elements. Tulloch et al., provide a systematic characterization of two new reporter assay techniques (LS-MPRA and d-MPRA) to comprehensively identify cis-regulatory sequences contained within genomic loci of interest during retinal development. The authors then apply LS-MPRA and d-MPRA to identify putative cis-regulatory sequences controlling Olig2 and Ngn2 expression, including potential regulatory motifs that known retinal transcription factors may bind. Transcription factor binding to regulatory sequences is then assessed via CUT&RUN. The broader utility of the techniques is then highlighted by performing the assays across development, across species, and across tissues.
Strengths:
(1) The authors validate the reporter assays on retinal loci for which the regulatory sequences are known (Rho, Vsx2, Grm6, Cabp5) mostly confirming known regulatory sequence activity but highlighting either limitations of the current technology or discrepancies of previous reporter assays and known biology. The techniques are then applied to loci of interest (Olig2 and Ngn2) to better understand the regulatory sequences driving expression of these transcription factors across retinal development within subsets of retinal progenitor cells, identifying novel regulatory sequences through comprehensive profiling of the region.
(2) LS-MPRA provides broad coverage of loci of interest.
(3) d-MPRA identifies sequence features that are important for cis-regulatory sequence activity.
(4) The authors take into account transcript and protein stability when determining the correlation of putative enhancer sequence activity with target gene expression.
Weaknesses:
(1) In its current form, the many important controls that are standard for other MPRA experiments are not shown or not performed, limiting the interpretations of the utility of the techniques. This includes limited controls for basal-promoter activity, limited information about sequence saturation and reproducibility of individual fragments across different barcode sequences, limitations in cloning and assay delivery, and sequencing requirements. Additional quantitative metrics, including locus coverage and number of barcodes/fragments, would be beneficial throughout the manuscript.
(2) There are no statistical metrics for calling a region/sequence 'active'. This is especially important given that NR3 for Olig2 seems to have a small 'peak' and has non-significant activity in Figure 4.
(3) The authors present correlational data for identified cis-regulatory sequences with target gene expression. Additionally, the significance of transcription factor binding to the putative regulatory sequences is not currently tested, only correlated based on previous single-cell RNA-sequencing data. While putative regulatory sequences with potential mechanisms of regulation are identified/proposed, the lack of validation (and discrepancies with previous literature) makes it hard to decipher the utility of the techniques.
(4) While the interpretations that Olig2 mRNA/protein expression is dynamically regulated improved the proportions of cells that co-expressed CRM-regulated GFP and Olig2, alternate explanations (some noted) are just as likely. First, the electroporation isn't specific to Olig2+ progenitors. Also, the tested, short CRM fragments may have activating signals outside of Olig2 neurogenic cells because chromatin conformation, histone modifications, and DNA methylation are not present on plasmids to precisely control plasmid activity. Alternatively, repressive elements that control Olig2 expression are not contained in the reporter vectors.
(5) It is unclear as to why the d-MPRA uses a different barcoding strategy, placing a second copy of the cis-regulatory sequence in the 3' UTR. As acknowledged by the author, this will change the transcript stability by changing the 3' UTR sequence. Because of this, comparisons of sequence activity between the LS-MPRA and d-MPRA should not be performed as the experiments are not equivalent.
(6) Furthermore, details of the mutational burden in d-MPRA experiments are not provided, limiting the interpretations of these results.
(7) Many figures are IGV screenshots that suffer from low resolution. Many figures could be consolidated.
-
-
news.stanford.edu news.stanford.edu
-
One of the first papers to directly examine the risks of microplastics exposure in humans, published in The New England Journal of Medicine in March 2024, studied patients undergoing surgery to remove plaque from their arteries. More than two years after the procedure, those who had microplastics in their plaque had a higher risk of heart attack, stroke, and death than those who didn’t.
Study examining the risk of mp exposure
-
By the late 1960s, experts began warning about the dangers of plastic pollution, including islands of debris clogging the oceans.
Salient info
-
-
elifesciences.org elifesciences.org
-
ID: 006474
DOI: 10.7554/eLife.107708.1
Resource: (IMSR Cat# JAX_006474,RRID:IMSR_JAX:006474)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:006474
-
RRID:SCR_025044
DOI: 10.7554/eLife.107708.1
Resource: LJPcalc (RRID:SCR_025044)
Curator: @scibot
SciCrunch record: RRID:SCR_025044
-
RRID:Addgene_18917
DOI: 10.7554/eLife.107708.1
Resource: RRID:Addgene_18917
Curator: @scibot
SciCrunch record: RRID:Addgene_18917
-
-
elifesciences.org elifesciences.org
-
#016961
DOI: 10.7554/eLife.105277
Resource: (IMSR Cat# JAX_016961,RRID:IMSR_JAX:016961)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:016961
-
RRID:SCR_018206
DOI: 10.7554/eLife.105277
Resource: University of California San Francisco Parnassus Flow Cytometry Core Facility (RRID:SCR_018206)
Curator: @scibot
SciCrunch record: RRID:SCR_018206
-
RRID:AB_2860113
-
RRID:SCR_016582
DOI: 10.7554/eLife.105277
Resource: kallisto (RRID:SCR_016582)
Curator: @scibot
SciCrunch record: RRID:SCR_016582
-
-
elifesciences.org elifesciences.org
-
RRID:AB_2535718
DOI: 10.7554/eLife.102230
Resource: (Thermo Fisher Scientific Cat# A-21050, RRID:AB_2535718)
Curator: @dhovakimyan1
SciCrunch record: RRID:AB_2535718
-
RRID:AB_2534096
DOI: 10.7554/eLife.102230
Resource: (Thermo Fisher Scientific Cat# A-11039, RRID:AB_2534096)
Curator: @scibot
SciCrunch record: RRID:AB_2534096
-
RRID:BDSC_55138
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_55138
Curator: @scibot
SciCrunch record: RRID:BDSC_55138
-
RRID:BDSC_55139
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_55139
Curator: @scibot
SciCrunch record: RRID:BDSC_55139
-
RRID:BDSC_44277
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_44277
Curator: @scibot
SciCrunch record: RRID:BDSC_44277
-
RRID:BDSC_55137
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_55137
Curator: @scibot
SciCrunch record: RRID:BDSC_55137
-
RRID:BDSC_79603
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_79603
Curator: @scibot
SciCrunch record: RRID:BDSC_79603
-
RRID:AB_2392664
DOI: 10.7554/eLife.102230
Resource: (Creative Diagnostics Cat# DMAB9116MD, RRID:AB_2392664)
Curator: @scibot
SciCrunch record: RRID:AB_2392664
-
RRID:AB_300798
DOI: 10.7554/eLife.102230
Resource: (Abcam Cat# ab13970, RRID:AB_300798)
Curator: @scibot
SciCrunch record: RRID:AB_300798
-
RRID:BDSC_32189
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_32189
Curator: @scibot
SciCrunch record: RRID:BDSC_32189
-
RRID:BDSC_75862
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_75862
Curator: @scibot
SciCrunch record: RRID:BDSC_75862
-
RRID:BDSC_52867
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_52867
Curator: @scibot
SciCrunch record: RRID:BDSC_52867
-
RRID:BDSC_88574
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_88574
Curator: @scibot
SciCrunch record: RRID:BDSC_88574
-
RRID:BDSC_53740
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_53740
Curator: @scibot
SciCrunch record: RRID:BDSC_53740
-
RRID:BDSC_48322
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_48322
Curator: @scibot
SciCrunch record: RRID:BDSC_48322
-
RRID:BDSC_32186
DOI: 10.7554/eLife.102230
Resource: RRID:BDSC_32186
Curator: @scibot
SciCrunch record: RRID:BDSC_32186
-
-
academic.oup.com academic.oup.com
-
Strain no. 005796
DOI: 10.1093/jimmun/vkaf122
Resource: (IMSR Cat# JAX_005796,RRID:IMSR_JAX:005796)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:005796
-
Strain #033076
DOI: 10.1093/jimmun/vkaf122
Resource: RRID:IMSR_JAX:033076
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:033076
-
Strain no. 002014
DOI: 10.1093/jimmun/vkaf122
Resource: (IMSR Cat# JAX_002014,RRID:IMSR_JAX:002014)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:002014
-
Strain no. 000664
DOI: 10.1093/jimmun/vkaf122
Resource: (IMSR Cat# JAX_000664,RRID:IMSR_JAX:000664)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:000664
-
RRID: SCR_022628
DOI: 10.1093/jimmun/vkaf122
Resource: Cincinnati Children's Hospital Confocal Imaging Core Facility (RRID:SCR_022628)
Curator: @dhovakimyan1
SciCrunch record: RRID:SCR_022628
-
-
pubs.acs.org pubs.acs.org
-
RRID:SCR_023230
DOI: 10.1021/acs.nanolett.5c02166
Resource: Stanford Nano Shared Core Facility (RRID:SCR_023230)
Curator: @dhovakimyan1
SciCrunch record: RRID:SCR_023230
-
-
elifesciences.org elifesciences.org
-
RRID:AB_1134159
DOI: 10.7554/eLife.98662
Resource: (BioLegend Cat# 127610, RRID:AB_1134159)
Curator: @scibot
SciCrunch record: RRID:AB_1134159
-
RRID:IMSR_JAX:005582
DOI: 10.7554/eLife.98662
Resource: (IMSR Cat# JAX_005582,RRID:IMSR_JAX:005582)
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:005582
-
RRID:IMSR_JAX:000664
DOI: 10.7554/eLife.98662
Resource: RRID:IMSR_JAX:000664
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:000664
-
-
elifesciences.org elifesciences.org
-
RRID:AB_261889
DOI: 10.7554/eLife.106469
Resource: (Sigma-Aldrich Cat# V8137, RRID:AB_261889)
Curator: @scibot
SciCrunch record: RRID:AB_261889
-
RRID:AB_2535860
DOI: 10.7554/eLife.106469
Resource: (Thermo Fisher Scientific Cat# A-21442, RRID:AB_2535860)
Curator: @scibot
SciCrunch record: RRID:AB_2535860
-
RRID:AB_262044
DOI: 10.7554/eLife.106469
Resource: (Sigma-Aldrich Cat# F1804, RRID:AB_262044)
Curator: @scibot
SciCrunch record: RRID:AB_262044
-
RRID:AB_2534069
DOI: 10.7554/eLife.106469
Resource: (Thermo Fisher Scientific Cat# A-11001, RRID:AB_2534069)
Curator: @scibot
SciCrunch record: RRID:AB_2534069
-
RRID:AB_477583
DOI: 10.7554/eLife.106469
Resource: (Sigma-Aldrich Cat# T6199, RRID:AB_477583)
Curator: @scibot
SciCrunch record: RRID:AB_477583
-
RRID:AB_796202
DOI: 10.7554/eLife.106469
Resource: (Sigma-Aldrich Cat# F2555, RRID:AB_796202)
Curator: @scibot
SciCrunch record: RRID:AB_796202
-
RRID:AB_2637089
DOI: 10.7554/eLife.106469
Resource: (Sigma-Aldrich Cat# M8823, RRID:AB_2637089)
Curator: @scibot
SciCrunch record: RRID:AB_2637089
-
RRID:AB_261888
DOI: 10.7554/eLife.106469
Resource: (Sigma-Aldrich Cat# V8012, RRID:AB_261888)
Curator: @scibot
SciCrunch record: RRID:AB_261888
-
RRID:Addgene_212936
DOI: 10.7554/eLife.106469
Resource: RRID:Addgene_212936
Curator: @scibot
SciCrunch record: RRID:Addgene_212936
-
RRID:AB_302613
DOI: 10.7554/eLife.106469
Resource: (Abcam Cat# ab1791, RRID:AB_302613)
Curator: @scibot
SciCrunch record: RRID:AB_302613
-
RRID:Addgene_32369
-
RRID:CVCL_0060
DOI: 10.7554/eLife.106469
Resource: (NCI-DTP Cat# NCI-H1299, RRID:CVCL_0060)
Curator: @scibot
SciCrunch record: RRID:CVCL_0060
-
RRID:Addgene_16451
DOI: 10.7554/eLife.106469
Resource: RRID:Addgene_16451
Curator: @scibot
SciCrunch record: RRID:Addgene_16451
-
RRID:Addgene_20140
DOI: 10.7554/eLife.106469
Resource: RRID:Addgene_20140
Curator: @scibot
SciCrunch record: RRID:Addgene_20140
-
RRID:Addgene_16591
-
-
iovs.arvojournals.org iovs.arvojournals.org
-
RRID:SCR_017696
DOI: 10.1167/iovs.66.9.53
Resource: University of Delaware Center for Bioinformatics and Computational Biology Core Facility (RRID:SCR_017696)
Curator: @scibot
SciCrunch record: RRID:SCR_017696
Tags
Annotators
URL
-
-
pubs.aip.org pubs.aip.org
-
RRID:SCR_018674
DOI: 10.1063/5.0272809
Resource: Massachusetts Institute of Technology Swanson Biotechnology Center Nanotechnology Materials Core Facility (RRID:SCR_018674)
Curator: @scibot
SciCrunch record: RRID:SCR_018674
-
-
www.iea.org www.iea.org
-
Long-term contracts, together with domestic gas production, typically accounted for 80-90% of the European Union’s natural gas consumption before the 2022 crisis. In the past two years, that share has dropped to around 50%. If no new contracts are signed and existing ones are not renewed, the share of spot gas and flexible LNG in total EU gas supply could increase to around two-thirds by 2030, which could increase exposure to short-term price volatility.
This effectively sounds like a good argument for 24/7 style PPAs which include batteries, because this reduces exposure to the price of power on the spot market.
Given the trend towards higher volatility, the consequences of being on the wrong side a price spike seem greater, and being able to hedge against that sounds increasingly valuable.
-
-
shrewdies.com shrewdies.com
-
Architecture – The Granary became a parking garage (Port Louis, Mauritius)
The post details a visit to The Granary in Port Louis, Mauritius, a historic red brick building originally constructed as a warehouse that now serves as a parking garage. The author reflects on its architectural significance, its history during wartime, and the transformation it has undergone over the years.
-
-
shrewdies.com shrewdies.com
-
Beer Tasting: Bevog Kramah and Deetz
A personal account of attending a rainy Bike & Beer Festival. Highlighting the presence of Bevog Brewery's Kramah IPA and Deetz Golden Ale. Along with recommendations for beer enthusiasts. Despite the weather challenges, the author's enthusiasm for the beers and the event remains evident.
-
-
shrewdies.com shrewdies.com
-
TV Shows That Defined an Era!
The post reflects on the nostalgic impact of popular Nigerian TV shows from the '80s and '90s, such as "Binta and Friends" and "Papa Ajasco." Highlighting how they shaped childhood experiences, provided entertainment, and conveyed valuable life lessons. It emphasizes the cultural significance of these shows in promoting social values and community narratives in Nigeria.
-
-
shrewdies.com shrewdies.com
-
Hive launches borehole water project in Ghana
Hive has successfully launched a borehole water project in Fawoade, Ghana. Providing the community with access to potable water. And marking a significant milestone in its community empowerment initiatives. The project's inauguration, celebrated on April 17th, 2022, was met with joy and gratitude from local residents. Addressing a crucial need for clean water in the region.
-
-
Local file Local file
-
The shaded afterlife of Leonardo’s notebooks – ‘without parallel in theintellectual history of word and image’, as Kemp describes them – stands insharp relief when we light it with the long, powerful burn of Pacioli’sposthumous – albeit near-anonymous – career. There’s no doubt thatLeonardo was the greater thinker, but his creative achievements madescarcely any impression compared to the impact of the universal adoptionof his friend’s Summa.
So much value hiding in da Vinci's notebooks because he failed to publish and share his knowledge
-
up Isabella d’Este’s portrait, complaining of Leonardo’s ‘haphazard andextremely unpredictable’ routine. This frustrating restlessness was, ofcourse, integral to the obsessive creativity. Pacioli had been able to draw aline under a piece of work and consider it done, but for Leonardo thisrepresented a mental hurdle that he frequently failed to clear. He leftpaintings unfinished for decades – Lisa del Giocondo sat for the Mona Lisawhen she was in her early twenties, and was thirty-nine when Leonardodied, still working on it – and he evidently felt similarly about hismanuscripts and notebooks
-
Melzi’s posthumousedition of the Treatise on Painting, for instance, would require collationfrom no fewer than eighteen notebooks.
-
Why did Leonardo not go to Venice to publish when Pacioli did? Had hetidied up the texts in his notebooks, he would have had no difficulty findinga patron and printer, and could have seen several books into print at thesame time as his friend.
Like many, da Vinci didn't publish much from his copious notebooks. He had huge volumes of material, but really not much to show for it in the end.
-
Pacioli’s Summa proved to be one of the most consequential books of alltime.
-
In 1540 a Venetianprinter named Domenico Manzoni excerpted them, without attribution(Pacioli himself had acknowledged most, but not all, of his sources) butusefully adding hundreds of worked examples which illustrated Pacioli’spoints. Tellingly, Manzoni retitled the work Quaderno Doppio, ‘the doubleledger’. Selling even better than Maestro Luca’s original, it went throughsix or seven editions and prompted a wave of adaptations and translations.
-
of the six hundred pagesof the Summa, only twenty-seven covered bookkeeping.
-
that of a centenarian who had died of arteriosclerosis
oops, Allen accidentally spills this note twice!
-
Pacioli completed another equally playful book at about the same time:De Viribus Quantitatis (‘On the powers of numbers’), which compilesnumber games, card tricks, riddles and reasoning problems. It makesfrequent mention of Leonardo, and much of the content overlaps withpuzzles that can be found in the notebooks.
-
‘Alas, this will never get anything done’ is a theme that recurs in severalnotebooks.
-
In February 1498, Maestro Lucacompleted De Divina Proportione, which was illustrated by ‘the graciousleft hand’ of his new friend, as Leonardo showed off his mastery ofperspective and geometry with a set of precise, fenestrated illustrations ofthe six Platonic solids, from the four-faced tetrahedron to the twenty-sidedicosahedron.
-
This habit of drawing engaged one of his most important analyticaltools: analogy. Drawing from nature in detail forces the artist to understandboth underlying structure and surface detail, and this close examination ledLeonardo to make surprising connections, noting the resemblances betweenthe curls of hair and the movement of water, a sprouting seed and thevessels around the human heart, ropes and levers and tendons and bones.These connections would prove distracting – ‘lateral thinking at apathological level’, as Kemp puts it – but the result was that ‘he couldalways see further possibilities’.
-
He analysed the flow of blood around the heart, makingthe world’s first post-mortem diagnosis of arteriosclerosis, and worked outhow the aortic valve manages the turbulence of rushing blood.
-
Over six thousand leaves (which is tosay, thirteen thousand pages) survive, and experts estimate that thisrepresents about a quarter of the original total. This implies that Leonardofilled his notebooks at the rate of about a thousand pages a year, allobsessively covered with drawings, diagrams and idiosyncratic mirrorhandwriting. ‘I worked out at one point that he must have written aboutfifty academic-length books, if you put them all together,’ says Kemp. ‘Hewas never at rest.’
-
The successful artist towhom he was apprenticed in Florence, Andrea del Verrocchio, ran a book-making workshop out of his house on Via Ghibellina, just off the street ofbookshops, where the cartolai clustered
Da Vinci apprenticed to Andrea del Verrocchio who sculpted for the Medici. Verrocchio also ran a book-making workshop out of his house and manufactured zibaldoni to order.
-
Pacioli’s reader, in whose company he would spend most of thefollowing decade, was Leonardo da Vinci.
-
Pacioli was granted copyright inthe work by the Venetian authorities, protecting his work from piracy.
-
Paganino de Paganini
Paganino de Paganini was the publisher of Pacioli's Summa.
-
In short: Book ix of the Summawas the nearest thing to an MBA textbook that the fifteenth century had tooffer. And one of the first lessons that its aspirational readers digested wasthat every business needed at least four blank books – the memoriale, orday book, the giornale, or journal, the quaderno, or general ledger, and abook for correspondence – and maybe even a fifth, the squartofoglia, or
waste book.
-
He supplemented the commercial arithmetic with instruction in goodpractice in letter-writing, record-keeping, filing – and even that staple of theworkplace notebook, the things-to-do list
-
And buried deep inside,Book ix of the Summa presents a concise and surprisingly readable coursein double-entry bookkeeping, spelling out exactly how a business should berun – and why the Florentine-Venetian system of double entry was the bestway to do it. ‘Without double entry, businessmen would not sleep easily atnight’, he writes. ‘Their minds would keep them awake with worry.’
-
An ambitious synthesis of all the mathematical knowledge he could find,Pacioli’s Summa de arithmetica, geometria, proportioni et proportionalitais a baggy monster of a book. Six hundred and fifteen pages long, nearlyhalf a million words, full folio in size, closely printed on fine paper, itcomprehensively sums up the state of European mathematical knowledge,and was intended for a wide audience – Fra Luca wrote informally, inTuscan, not Latin, making it accessible to anyone with a basic education.The book combines a general treatise on theoretical and practical arithmetic– including the Liber Abaci of the then little-known Fibonacci, whichPacioli had discovered on a monastery bookshelf – with an introduction toalgebra, currency conversions, multiplication tables, weights and measuresof the Italian states, a summary of Euclidean geometry, and accounts ofArchimedes, Euclid and Piero della Francesca.
-
At one point he was forced to move on, when in 1491 he wasforbidden from teaching young men in Sansepolcro, presumably for somekind of sexual impropriety.
-
Leon Battista Alberti, who, as artist-architect-cryptographer-philosopher-poet-athlete, was perhaps the most Renaissanceof all Renaissance men.* Forty-three years older than Pacioli, he hadworked out the mathematics that underpinned perspective some thirty yearsbefore, completing his book De Pictura (‘On Painting’) in 1435.
-
Luca Pacioli
-
To conjure the devil, play a C and an F# together, or listen to the intro toJimi Hendrix’s ‘Purple Haze’.
-
But LHD 244 is unique in how it captures an art form evolving overa long period, and shows how it was transmitted from musician tomusician. This formal study of musical theory shows us how classicalmusic evolved out of liturgical chanting and towards the harmonicsophistication that Bach, Mozart and Beethoven would master
-
while avoidingaccidentally landing on the tritone, an interval so abrasive that it wasnamed diabolus in musica (‘the devil in music’).
-
It documents the English harmonic innovation known as the gymel,in which two or more voices singing a part in unison suddenly split intopolyphonic harmony, producing rich, textured chords before returning tothe melody in unison.
-
Allen, Roland. The Notebook: A History of Thinking on Paper. United Kingdom: Profile Books, 2023. https://uk.bookshop.org/p/books/the-notebook-rolad-allen/6331084.
Tags
- notes per day
- post-mortem diagnosis
- The Notebook: A History of Thinking on Paper
- tipping of the zettelkasten
- piracy
- idea links
- number games
- accounting
- music
- productivity
- duplication
- Piero della Francesca
- Summa de arithmetica, geometria, proportioni et proportionalita
- card tricks
- Euclid
- Venice
- perspective
- Catholic Church
- zibaldoni
- 1494
- day book (memoriale)
- De Pictura (On Painting)
- evolution
- cardiology
- finishing
- general ledger (quaderno)
- quotes
- Domenico Manzioni
- Fibonacci
- notebooks
- copyright
- logic problems
- art
- note reuse
- analogy
- Andrea del Verrocchio
- LHD 244
- mathematics
- Ludovico Sforza
- publishing
- Catholic sex abuse crisis
- Paganino de Paganini
- gymel
- notebooks as vaults
- intellectual history
- note taking methods
- sexual impropriety
- 1498
- arteriosclerosis
- influential books
- to do lists
- math
- Liber Abaci
- writing output
- textbooks
- knowledge dispersal
- procrastination
- diagnoses
- Francisco Melzi
- 1540
- Lisa del Giocondo
- De Divina Proportione
- cultural influence
- lateral thinking
- Jimmy Hendrix
- De Viribus Quantitatis (On the powers of numbers)
- double entry bookkeeping
- zettelkasten output
- posthumous publication
- Mona Lisa
- Franciscans
- Archimedes
- Isabella d'Este
- 1435
- Dan Allosso Book Club 2025-07-19
- waste books
- creativity
- Leon Battista Alberti
- journal (giornale)
- firsts
- Luca Pacioli
- blood flow
- puzzles
- References
- perfection as the enemy of the good
- Roland Allen
- homosexuality
- Purple Haze
- squartofoglia
- Quaderno Doppio (The Double Ledger)
- Getting Things Done (GTD)
- diabolus in musica
- tritone
- Treatise on Painting
- illustrations
- Leonardo da Vinci
Annotators
-
-
shrewdies.com shrewdies.com
-
Beer Tasting: Tuborg Gold
The post reviews Tuborg Gold, a lager brewed in Serbia. Highlighting its smooth taste and balanced bitterness. While the author also shares excitement about an upcoming trip to the coast. The piece is a celebration of beer culture, inviting readers to join the #BeerSaturday community.
-
-
shrewdies.com shrewdies.com
-
Real-world Impact: Hive's Story on News Networks
Highlights the positive impact of Hive's recent borehole project in Kanvili Kukuo, Ghana. Emphasizing the importance of media coverage in raising awareness about Hive's contributions to community development. And dispelling misconceptions about cryptocurrency. By utilizing various media channels, Hive aims to educate a broader audience on its transformative efforts and promote global adoption.
-
-
shrewdies.com shrewdies.com
-
Beer Tasting: Loo-Blah-Nah APA
The author shares a beer tasting experience of Loo-Blah-Nah APA, a well-balanced American Pale Ale from Slovenia, enjoyed during a late lunch featuring limited pizza. The author describes the beer's cloudy appearance, delightful hop bitterness, and fruity aromas. Emphasizing its drinkability and satisfaction despite having only one bottle.
-
-
shrewdies.com shrewdies.com
-
Splinterlands You Need More Power! What to do next!
Emphasizes the importance of acquiring and managing "Power" in Splinterlands. Which is essential for claiming seasonal rewards. And is derived from owning or renting cards. This article provides tips on calculating power values and cautions against burning cards without good reason. While also highlighting resources for players to maximize their gameplay.
-
-
-
Virtual Bank Apps In Nigeria: An Experience Of Gamification
Gamification strategies employed by virtual banks in Nigeria. Highlighting how these financial apps use reward systems and interactive features to enhance user engagement and retention. It emphasizes the significant role of gamification in reshaping the fintech landscape and creating a compelling business model.
-
-
learn.scu.edu.au learn.scu.edu.auDocument1
-
style
In the figure can we please change Normal to usual
-
-
github.com github.com
-
Mathematics
Functional Analysis
Optimization by Vector Space Methods<br /> Lectures and exercises on functional Analysis<br /> Convex Functional Analysis<br /> Functional Analysis for Probability and Stochastic Processes<br /> Abstract Calculus A Categorical Approach <br /> Banach-Hilbert Spaces, Vector Measures and Group Representations
Differential Geometry
Clifford algebra, geometric algebra, and applications<br /> Mathematical Structures From Linear Algebra over Rings to Geometry with Sheaves<br /> Diffeology<br /> Global Calculus<br /> Manifolds, Tensor Analysis, and Applications<br /> Manifolds, Sheaves, and Cohomology
Algebra
Basic algebra groups, rings and fields<br /> Further Algebra and Application<br /> Abstract Algebra - Paul Garrett.
Linear Algebra
Algebra An Approach via Module Theory<br /> Linear Algebra via Exterior Products<br /> Rings, Modules, and Linear Algebra<br /> Modules and Homological Algebra<br /> Module theory an approach to linear algebra<br /> 代数学方法I
Measure, Probability and Statistics
A Basic Course in Probability Theory<br /> Probability Theory An Analytic View<br /> Probability and Stochastics<br /> Measure-Theoretic Probability<br /> Measure-Theoretic Calculus in Abstract Spaces<br /> Plane Answers to Complex Questions<br /> Mathematical Statistics<br /> Time Series Theory and Methods<br /> The Coordinate-Free Approach to Linear Models<br /> Multivariate Statistics A Vector Space Approach<br /> hypo
Logic Category Type
THE OPEN LOGIC TEXT<br /> Categorical Logic and Type Theory
Algebraic Topology
Fundamentals of Algebraic Topology<br /> Algebraic Topology - A Structural Introduction<br /> Homology, Cohomology, and Sheaf<br /> Combinatorial Algebraic Topology<br /> Algebraic Foundations for Applied Topology and Data Analysis<br /> Topology A Categorical Approach<br /> hypo
Combinatorics and Discrete
Introduction to the Theory of Species of Structures<br /> Discrete Calculus Methods for Counting<br /> Combinatorics the rota way
-
CS
PLType
Lecture Notes on Type Theory Type Theory and Functional Programming.pdf<br /> The Hitchhiker's Guide to Logic.pdf<br /> Foundations for Programming Languages.pdf<br /> Formal syntax and semantics of programming languages<br /> Formal Reasoning About Programs<br /> Computation and reasoning A type theory for computer science
Language, Parse and Compile
Language Server Protocol & Implementation <br /> Crafting Interpreters<br /> Introduction to Compilers and and Language Design<br /> Techniques for Searching, Parsing, and Matching.pdf
LLM, ML, Data
Deep Learning Architectures<br /> Probability and Statistics for Machine Learning<br /> Machine Learning A Probabilistic Perspective<br /> Large Language Models A Deep Dive<br /> Foundations of Machine Learning<br /> Data Science for Mathematicians <br /> Transformers for Machine Learning
-
Programming
Programming Languages
What I Wish I Knew When Learning Haskell<br /> JavaScript the Definitive Guide<br /> Beginning C++23.pdf<br /> Programming Rust<br /> The Well-Grounded Rubyist<br /> Mathematica programming an advanced introduction<br /> Advanced R<br /> TypeScript Basics<br /> SQL Query Design Patterns and Best Practices<br /> SQL必知必会<br /> hypo
Web
CSS in Depth<br /> Vue.js 3 Design Patterns and Best Practices<br /> React in Depth <br /> Modern Full-Stack Development Using TypeScript, React, Node.js, Webpack, and Docker <br /> Fullstack Web Components<br /> Fullstack Vue 3<br /> Fullstack Rust<br /> Frameworkless Front-End Development<br />
Penetration
Black Hat Ruby<br /> Understanding Network Hacks<br /> Metasploit The Penetration Tester‘s Guide<br /> RubyFu
Tags
Annotators
URL
-
-
learn.scu.edu.au learn.scu.edu.auDocument2
-
a
delete a
-
amendable
typo should be amenable
-
-
learn.scu.edu.au learn.scu.edu.auDocument1
-
delete the section Bipolar
-
-
learn.scu.edu.au learn.scu.edu.auDocument1
-
Tthe Uniteds States
typo should be the United States
-
-
learn.scu.edu.au learn.scu.edu.auDocument1
-
mind.
After the sentence finishing with theory of mind is a new paragraph that did not get loaded but is in the original doc. Please load The creator of the first online community has written of his experience and why he no longer identifies as being part of the movement and attributes much of the issues to challenges with social communication attributable to the neurotype (Dekker, 2019).
-
-
beeswap.dcity.io beeswap.dcity.io
-
BRO
No Liquidity Pool
-
DOOK
No Liquidity Pool
-
VKBT
No Liquidity Pool
-
ALIVE
No Liquidity Pool
-
CTP
No Liquidity Pool
-
STEM
No Liquidity Pool
-
GROWTH
No Liquidity Pool
-
CCC
CCC:PHOTO CCC:MUSIC
-
CURE
No Liquidity Pool
-
SLOTHBUZZ
No Liquidity Pool
-
ARCHON
Liquidity Pool APR low
-
NEOXAG
No Liquidity Pool
-
DUO
No Liquidity Pool
-
CTPSB
No Liquidity Pool
-
-
learn.scu.edu.au learn.scu.edu.auDocument1
-
waiting for information
this section can be deleted
-
-
learn.scu.edu.au learn.scu.edu.auDocument1
-
hese resources will introduce and reinforce core anatomy and physiology concepts each week.
All references to anatomy and physiology in this section need to be deleted.
-
-
chem.libretexts.org chem.libretexts.org
-
books.byui.edu books.byui.edu
-
“Culture eats strategy for breakfast.”
-
-
news.ycombinator.com news.ycombinator.com
-
I use a jekyll/CI/static hosting workflow, and even though I make a zillion git commits a day, somehow branching, editing, PRing, and merging one to my website seems like friction.
This is at the root of the infamous "Blogging vs. blog setups" comic https://rakhim.org/honestly-undefined/19/.
The fact that this is true is also the entire basis for wikis. It is reasonable to find it irksome that people, perversely, refer to Git repos full of Markdown documentation as "wikis"—which they aren't. They are fully the opposite.
Tags
Annotators
URL
-
-
www.biorxiv.org www.biorxiv.org
-
eLife Assessment
In this valuable study, the authors show the physiological response and molecular pathway mediating the effect of quinofumelin, a developed fungicide with an unknown mechanism. The authors present convincing data suggesting the involvement of the uridine/uracil biosynthesis pathway, by combining in vivo microbiology characterization as well as in vitro biochemical binding results.
-
Reviewer #2 (Public review):
Summary:
In the current study, the authors aim to identify the mode of action/molecular mechanism of characterized a fungicide, quinofumelin, and its biological impact on transcriptomics and metabolomics in Fusarium graminearum and other Fusarium species. Two sets of data were generated between quinofumelin and no treatment group, and differentially abundant transcripts and metabolites were identified, suggesting a potential role of pyrimidine biosynthesis. Upon studying the genetic mutants of the uridine/uracil biosynthesis pathway with quinofumelin treatment and metabolite supplementation, combining in vitro biochemical assay of quinofumelin and F.graminearum dihydroorotate dehydrogenase protein, the authors identified that quinofumelin inhibits the dihydroorotate dehydrogenase and blocks downstream metabolite biosynthesis, limiting fungal metabolism and growth.
Strengths:
Omics datasets were leveraged to understand the physiological impact of quinofumelin, showing the intracellular impact of the fungicide. The characterization of FgDHODHII deletion strains with supplemented metabolites clearly showed the impact of the enzyme on fungal growth. Corroborating in vitro and in vivo data revealed the direct interaction of quinofumelin with Fusarium protein target.
Potential Impact:
Understanding this new mechanism could facilitate rational design or screen for molecules targeting the same pathway, or improve binding affinity and inhibitor potency. Confirming the target of quinofumelin may also help understand its resistance mechanism, and further development of other inhibitory molecules against the target.
-
Reviewer #3 (Public review):
Summary:
The manuscript shows the mechanism of action of quinofumelin, a novel fungicide, against the fungus Fusarium graminearum. Through omics analysis, phenotypic analysis and in silico approaches, the role of quinofumelin in targeting DHODH is uncovered.
Strengths:
The phenotypic analysis and mutant generation are nice data and add to the role of metabolites in bypassing pyrimidine biosynthesis.
Weaknesses:
The role of DHODH in this class of fungicides has been known and this data does not add any further significance to the field.
-
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public review):
Summary:
Phytophathogens including fungal pathogens such as F. graminearum remain a major threat to agriculture and food security. Several agriculturally relevant fungicides including the potent Quinofumelin have been discovered to date, yet the mechanisms of their action and specific targets within the cell remain unclear. This paper sets out to contribute to addressing these outstanding questions.
We appreciate the reviewer's accurate summary of our manuscript.
Strengths:
The paper is generally well-written and provides convincing data to support their claims for the impact of Quinofumelin on fungal growth, the target of the drug, and the potential mechanism. Critically the authors identify an important pyrimidine pathway dihydroorotate dehydrogenase (DHODH) gene FgDHODHII in the pathway or mechanism of the drug from the prominent plant pathogen F. graminearum, confirming it as the target for Quinofumelin. The evidence is supported by transcriptomic, metabolomic as well as MST, SPR, molecular docking/structural biology analyses.
We appreciate the reviewer's recognition of the strengths of our manuscript.
Weaknesses:
Whilst the study adds to our knowledge about this drug, it is, however, worth stating that previous reports (although in different organisms) by Higashimura et al., 2022 https://pmc.ncbi.nlm.nih.gov/articles/PMC9716045/ had already identified DHODH as the target for Quinofumelin and hence this knowledge is not new and hence the authors may want to tone down the claim that they discovered this mechanism and also give sufficient credit to the previous authors work at the start of the write-up in the introduction section rather than in passing as they did with reference 25? other specific recommendations to improve the text are provided in the recommendations for authors section below.
We appreciate the reviewer's suggestion. In the revised manuscript, we have incorporated the reference in the introduction section and expanded the discussion of previous work on quinofumelin by Higashimura et al., 2022 in the discussion section to more effectively contextualize their contributions. Moreover, we have made revisions and provided responses in accordance with the recommendations.
Reviewer #2 (Public review):
Summary:
In the current study, the authors aim to identify the mode of action/molecular mechanism of characterized a fungicide, quinofumelin, and its biological impact on transcriptomics and metabolomics in Fusarium graminearum and other Fusarium species. Two sets of data were generated between quinofumelin and no treatment group, and differentially abundant transcripts and metabolites were identified. The authors further focused on uridine/uracil biosynthesis pathway, considering the significant up- and down-regulation observed in final metabolites and some of the genes in the pathways. Using a deletion mutant of one of the genes and in vitro biochemical assays, the authors concluded that quinofumelin binds to the dihydroorotate dehydrogenase.
We appreciate the reviewer's accurate summary of our manuscript.
Strengths:
Omics datasets were leveraged to understand the physiological impact of quinofumelin, showing the intracellular impact of the fungicide. The characterization of FgDHODHII deletion strains with supplemented metabolites clearly showed the impact of the enzyme on fungal growth.
We appreciate the reviewer's recognition of the strengths of our manuscript.
Weaknesses:
Some interpretation of results is not accurate and some experiments lack controls. The comparison between quinofumelin-treated deletion strains, in the presence of different metabolites didn't suggest the fungicide is FgDHODHII specific. A wild type is required in this experiment.
Potential Impact: Confirming the target of quinofumelin may help understand its resistance mehchanism, and further development of other inhibitory molecules against the target.
The manuscript would benefit more in explaining the study rationale if more background on previous characterization of this fungicide on Fusarium is given.
We appreciate the reviewer's suggestion. Under no treatment with quinofumelin, mycelial growth remains normal and does not require restoration. In the presence of quinofumelin treatment, the supplementation of downstream metabolites in the de novo pyrimidine biosynthesis pathway can restore mycelial growth that is inhibited by quinofumelin. The wild-type control group is illustrated in Figure 4. Figure 5b depicts the phenotypes of the deletion mutants. With respect to the relationship among quinofumelin, FgDHODHII, and other metabolites, quinofumelin specifically targets the key enzyme FgDHODHII in the de novo pyrimidine biosynthesis pathway, disrupting the conversion of dihydroorotate to orotate, which consequently inhibits the synthesis downstream metabolites including uracil. In our previous study, quinofumelin not only exhibited excellent antifungal activity against the mycelial growth and spore germination of F. graminearum, but also inhibited the biosynthesis of deoxynivalenol (DON). We have added this part to the introduction section.
Reviewer #3 (Public review):
Summary:
The manuscript shows the mechanism of action of quinofumelin, a novel fungicide, against the fungus Fusarium graminearum. Through omics analysis, phenotypic analysis, and in silico approaches, the role of quinofumelin in targeting DHODH is uncovered.
We appreciate the reviewer's accurate summary of our manuscript.
Strengths:
The phenotypic analysis and mutant generation are nice data and add to the role of metabolites in bypassing pyrimidine biosynthesis.
We appreciate the reviewer's recognition of the strengths of our manuscript.
Weaknesses:
The role of DHODH in this class of fungicides has been known and this data does not add any further significance to the field. The work of Higashimura et al is not appreciated well enough as they already showed the role of quinofumelin upon DHODH II.
There is no mention of the other fungicide within this class ipflufenoquin, as there is ample data on this molecule.
We appreciate the reviewer's suggestion. We sincerely appreciate the reviewer's insightful comment regarding the work of Higashimura et al. We agree that their investigation into the role of quinofumelin in DHODH II inhibition provides critical foundational insights for this field. In the revised manuscript, we have incorporated the reference in the introduction section and expanded the discussion of their work in the discussion section to more effectively contextualize their contributions. The information regarding action mechanism of ipflufenoquin against filamentous fungi was added in discussion section.
Reviewer #1 (Recommendations for the authors):
(1) Given that the DHODH gene had been identified as a target earlier, could the authors perform blast experiments with this gene instead and let us know the percentage similarity between the FgDHODHII gene and the Pyricularia oryzae class II DHODH gene in the report by Higashimura et al., 2022.
BLAST experiment revealed that the percentage similarity between the FgDHODHII gene and the class II DHODH gene of P. oryzae was 55.41%. We have added the description ‘Additionally, the amino acid sequence of the FgDHODHII exhibits 55.41% similarity to that of DHODHII from Pyricularia oryzae, as previously reported (Higashimura et al., 2022)’ in section Results.
(2) Abstract:
The authors started abbreviating new terms e.g. DEG, DMP, etc but then all of a sudden stopped and introduced UMP with no full meaning of the abbreviation. Please give the full meaning of all abbreviations in the text, UMP, STC, RM, etc.
We have provided the full meaning for all abbreviations as requested.
(3) Introduction section:
The introduction talks very little about the work of other groups on quinofumelin. Perhaps add this information in and reference them including the work of Higashimura et al., 2022 which has done quite significant work on this topic but is not even mentioned in the background
We have added the work of other groups on quinofumelin in section introduction.
(4) General statements:
Please show a model of the pyrimidine pathway that quinofumelin attacks to make it easier for the reader to understand the context. They could just copy this from KEGG
We have added the model (Fig. 7).
(5) Line 186:
The authors did a great job of demonstrating interactions with the Quinofumelin and went to lengths to perform MST, SPR, molecular docking, and structural biology analyses yet in the end provide no details about the specific amino acid residues involved in the interaction. I would suggest that site-directed mutagenesis studies be performed on FgDHODHII to identify specific amino acid residues that interact with Quinofumelin and show that their disruption weakens Quinofumelin interaction with FgDHODHII.
Thank you for this insightful suggestion. We fully agree with the importance of elucidating the interaction mechanism. At present, we are conducting site-directed mutagenesis studies based on interaction sites from docking results and the mutation sites of FgDHODHII from the resistant mutants; however, due to the limitations in the accuracy of existing predictive models, this work remains ongoing. Additionally, we are undertaking co-crystallization experiments of FgDHODHII with quinofumelin to directly and precisely reveal their interaction pattern
(6) Line 76:
What is the reference or evidence for the statement 'In addition, quinofumelin exhibits no cross-resistance to currently extensively used fungicides, indicating its unique action target against phytopathogenic fungi.
If two fungicides share the same mechanism of action, they will exhibit cross resistance. Previous studies have demonstrated that quinofumelin retains effective antifungal activity against fungal strains resistant to commercial fungicides, indicating that quinofumelin does not exhibit cross-resistance with other commercially available fungicides and possesses a novel mechanism of action. Additionally, we have added the relevant inference.
(7) Line 80-82:
Again, considering the work of previous authors, this target is not newly discovered. Please consider toning down this statement 'This newly discovered selective target for antimicrobial agents provides a valuable resource for the design and development of targeted pesticides.'
We have rewritten the description of this sentence.
(8) Line 138: If the authors have identified DHODH in experimental groups (I assume in F. graminearum), what was the exact locus tag or gene name in F. graminearum, and why not just continue with this gene you identified or what is the point of doing a blast again to find the gene if the DHODH gene if it already came up in your transcriptomic or metabolic studies? This unfortunately doesn't make sense but could be explained better.
The information of FgDHODHII (gene ID: FGSG_09678) has been added. We have revised this part.
Reviewer #2 (Recommendations for the authors):
(1) Line 40:
Please add a reference.
We have added the reference
(2) Line 47:
Please add a reference.
We have added the reference.
(3) Line 50:
The lack of target diversity in existing fungicides doesn't necessarily serve as a reason for discovering new targets being more challenging than identifying new fungicides within existing categories, please consider adjusting the argument here. Instead, the authors can consider reasons for the lack of new targets in the field.
We have revised the description.
(4) Line 63:
Please cite your source with the new technology.
We have added the reference.
(5) Line 68:
What are you referring to for "targeted medicine", do you have a reference?
We have revised the description and the reference.
(6) Line 74:
One of the papers referred to "quinoxyfen", what are the similarities and differences between the two? Please elaborate for the readership.
Quinoxyfen, similar to quinofumelin, contains a quinoline ring structure. It inhibits mycelial growth by disrupting the MAP kinase signaling pathway in fungi (https://www.frac.info). In addition, quinoxyfen still exhibits excellent antifungal activity against the quinofumelin-resistant mutants (the findings from our group), indicating that action mechanism for quinofumelin and quinoxyfen differ.
(7) Line 84:
Please introduce why RNA-Seq was designed in the study first. What were the groups compared? How was the experiment set up? Without this background, it is hard to know why and how you did the experiment.
According to your suggestions, we have added the description in Section Results. In addition, the experimental process was described in Section Materials and methods as follows: A total of 20 mL of YEPD medium containing 1 mL of conidia suspension (1×105 conidia/mL) was incubated with shaking (175 rpm/min) at 25°C. After 24 h, the medium was added with quinofumelin at a concentration of 1 μg/mL, while an equal amount of dimethyl sulfoxide was added as the control (CK). The incubation continued for another 48 h, followed by filtration and collection of hyphae. Carry out quantitative expression of genes, and then analyze the differences between groups based on the results of DESeq2 for quantitative expression.
(8) Figures:
The figure labeling is missing (Figures 1,2,3 etc). Please re-order your figure to match the text
The figures have been inserted.
(9) Line. 97:
"Volcano plot" is a common plot to visualize DEGs, you can directly refer to the name.
We have revised the description.
(10) Figure 1d, 1e:
Can you separate down- and up-regulated genes here? Does the count refer to gene number?
The expression information for down- and up-regulated genes is presented in Figure 1a and 1b. However, these bubble plots do not distinguish down- and up-regulated genes. Instead, they only display the significant enrichment of differentially expressed genes in specific metabolic pathways. To more clearly represent the data, we have added the detailed counts of down- and up-regulated genes for each metabolic pathway in Supplementary Table S1 and S2. Here, the term "count" refers to differentially expressed genes that fall within a certain pathway.
(11) Line 111:
Again, no reasoning or description of why and how the experiment was done here.
Based on the results of KEGG enrichment analysis, DEMs are associated with pathways such as thiamine metabolism, tryptophan metabolism, nitrogen metabolism, amino acid sugar and nucleotide sugar metabolism, pantothenic acid and CoA biosynthesis, and nucleotide sugar production compounds synthesis. To specifically investigate the metabolic pathways involved action mechanism of quinofumelin, we performed further metabolomic experiments. Therefore, we have added this description according the reviewer’s suggestions.
(12) Figure 2a:
It seems many more metabolites were reduced than increased. Is this expected? Due to the antifungal activity of this compound, how sick is the fungus upon treatment? A physiological study on F. graminearum (in a dose-dependent manner) should be done prior to the omics study. Why do you think there's a stark difference between positive and negative modes in terms of number of metabolites down- and up-regulated?
Quinofumelin demonstrates exceptional antifungal activity against Fusarium graminearum. The results indicate that the number of reduced metabolites significantly exceeds the number of increased metabolites upon quinofumelin treatment. Mycelial growth is markedly inhibited under quinofumelin exposure. Prior to conducting omics studies, we performed a series of physiological and biochemical experiments (refer to Qian Xiu's dissertation https://paper.njau.edu.cn/openfile?dbid=72&objid=50_49_57_56_49_49&flag=free). Upon quinofumelin treatment, the number of down-regulated metabolites notably surpasses that of up-regulated metabolites compared to the control group. Based on the findings from the down-regulated metabolites, we conducted experiments by exogenously supplementing these metabolites under quinofumelin treatment to investigate whether mycelial growth could be restored. The results revealed that only the exogenous addition of uracil can restore mycelial growth impaired by quinofumelin.
Quinofumelin exhibits an excellent antifungal activity against F. graminearum. At a concentration of 1 μg/mL, quinofumelin inhibits mycelial growth by up to 90%. This inhibitory effect indicates that life activities of F. graminearum are significantly disrupted by quinofumelin. Consequently, there is a marked difference in down- and up-regulated metabolites between quinofumelin-treated group and untreated control group. The detailed results were presented in Figures 1 and 2.
(13) Figure 2e:
This is a good analysis. To help represent the data more clearly, the authors can consider representing the expression using fold change with a p-value for each gene.
To more clearly represent the data, we have incorporated the information on significant differences in metabolites in the de novo pyrimidine biosynthesis pathway, as affected by quinofumelin, in accordance with the reviewer’s suggestions.
(14) Line 142:
Please indicate fold change and p-value for statistical significance. Did you validate this by RT-qPCR?
We validated the expression level of the DHODH gene under quinofumelin treatment using RT-qPCR. The results indicated that, upon treatment with the EC50 and EC90 concentrations of quinofumelin, the expression of the DHODH gene was significantly reduced by 11.91% and 33.77%, respectively (P<0.05). The corresponding results have been shown in Figure S4.
(15) Line 145:
It looks like uracil is the only metabolite differentially abundant in the samples - how did you conclude this whole pathway was impacted by the treatment?
The experiments involving the exogenous supplementation of uracil revealed that the addition of uracil could restore mycelial growth inhibited by quinofumelin. Consequently, we infer that quinofumelin disrupts the de novo pyrimidine biosynthesis pathway. In addition, as uracil is the end product of the de novo pyrimidine biosynthesis pathway, the disruption of this pathway results in a reduction in uracil levels.
(16) Figure 3:
What sequence was used as the root of the tree? Why were the species chosen? Since the BLAST query was Homo sapiens sequence, would it be good to use that as the root?
FgDHODHII sequence was used as the root of the tree. These selected fungal species represent significant plant-pathogenic fungi in agriculture production. According to your suggestion, we have removed the BLAST query of Homo sapiens in Figure 3.
(17) Figure 4:
How were the concentrations used to test chosen?
Prior to this experiment, we carried out concentration-dependent exogenous supplementation experiments. The results indicated that 50 μg/mL of uracil can fully restore mycelial growth inhibited by quinofumelin. Consequently, we chose 50 μg/mL as the testing concentration.
(18) Line 164:
Why do you hypothesize supplementing dihydroorotate would restore resistance? The metabolite seemed accumulated in the treatment condition, whereas downstream metabolites were comparable or even depleted. The DHODH gene expression was suppressed. Would accumulation of dihydroorotate be associated with growth inhibition by quinofumelin? Please include the hypothesis and rationale for the experimental setup.
DHODH regulates the conversion of dihydroorotate to orotate in the de novo pyrimidine biosynthesis pathway. The inhibition of DHODH by quinofumelin results in the accumulation of dihydroorotate and the depletion of the downstream metabolites, including UMP, uridine and uracil. Consequently, downstream metabolites were considered as positive controls, while upstream metabolite dihydroorotate served as a negative control. This design further demonstrates DHODH as action target of quinofumelin against F. graminearum. In addition, the accumulation of dihydroorotate is not associated with growth inhibition by quinofumelin; however, but the depletion of downstream metabolites in the de novo pyrimidine biosynthesis pathway is closely associated with growth inhibition by quinofumelin.
(19) Line 168:
I'm not sure if this conclusion is valid from your results in Figure 4 showing which metabolites restore growth.
o minimize the potential influence of strain-specific effects, five strains were tested in the experiments shown in Figure 4. For each strain, the first row (first column) corresponds to control condition, while second row (first column) represents treatment with 1 μg/mL of quinofumelin, which completely inhibits mycelial growth. The second row (second column) for each strain represents the supplementation with 50 μg/mL of dihydroorotate fails to restore mycelial growth inhibited by quinofumelin. In contrast, the second row (third column, fourth column, fifth colomns) for each strain demonstrated that the supplementation of 50 μg/mL of UMP, uridine and uracil, respectively, can effectively restore mycelial growth inhibited by quinofumelin.
(20) Figure 5a:
The fact you saw growth of the deletion mutant means it's not lethal. However, the growth was severely inhibited.
Our experimental results indicate that the growth of the deletion mutant is lethal. The mycelial growth observed originates from mycelial plugs that were not exposed to quinofumelin, rather than from the plates amended with quinofumelin.
(21) Figure 5b:
Would you expect different restoration of growth in the presence of quinofumelin vs. no treatment? The wild type control is missing here. Any conclusions about the relationship between quinofumelin, FgDHODHII, and other metabolites in the pathway?
Under no treatment with quinofumelin, mycelial growth remains normal and does not require restoration. In the presence of quinofumelin treatment, the supplementation of downstream metabolites in the de novo pyrimidine biosynthesis pathway can restore mycelial growth that is inhibited by quinofumelin. The wild-type control group is illustrated in Figure 4. Figure 5b depicts the phenotypes of the deletion mutants. With respect to the relationship among quinofumelin, FgDHODHII, and other metabolites, quinofumelin specifically targets the key enzyme FgDHODHII in the de novo pyrimidine biosynthesis pathway, disrupting the conversion of dihydroorotate to orotate, which consequently inhibits the synthesis downstream metabolites including uracil.
(22) Figure 6b:
Lacking positive and negative controls (known binder and non-binder). What does the Kd (in comparison to other interactions) indicate in terms of binding strength?
We tested the antifungal activities of publicly reported DHODH inhibitors (such as leflunomide and teriflunomide) against F. graminearum. The results showed that these inhibitors exhibited no significant inhibitory effects against the strain PH-1. Therefore, we lacked an effective chemical for use as a positive control in subsequent experiments. Biacore experiments offers detailed insights into molecular interactions between quinofumelin and DHODHII. As shown in Figure 6b, the left panel illustrates the time-dependent kinetic curve of quinofumelin binding to DHODHII. Within the first 60 s after quinofumelin was introduced onto the DHODHII surface, it bound to the immobilized DHODHII on the chip surface, with the response value increasing proportionally to the quinofumelin concentration. Following cessation of the injection at 60 s, quinofumelin spontaneously dissociated from the DHODHII surface, leading to a corresponding decrease in the response value. The data fitting curve presented on the right panel indicates that the affinity constant KD of quinofumelin for DHODHII is 6.606×10-6 M, which falls within the typical range of KD values (10-3 ~ 10-6 M) for protein-small molecule interaction patterns. A lower KD value indicates a stronger affinity; thus, quinofumelin exhibits strong binding affinity towards DHODHII.
Reviewer #3 (Recommendations for the authors):
The authors should add information about the other molecule within this class, ipflufenoquin, and what is known about it. There are already published data on its mode of action on DHODH and the role of pyrimidine biosynthesis.
We have added the information regarding action mechanism of ipflufenoquin against filamentous fungi in discussion section.
The work of Higashimura et al is not appreciated well enough as they already showed the role of quinofumelin upon DHODH II.
We sincerely appreciate the reviewer's insightful comment regarding the work of Higashimura et al. We agree that their investigation into the role of quinofumelin in DHODH II inhibition provides critical foundational insights for this field. In the revised manuscript, we have incorporated the reference in the introduction section and expanded the discussion of their work in the discussion section to more effectively contextualize their contributions.
It is unclear how the protein model was established and this should be included. What species is the molecule from and how was it obtained? How are they different from Fusarium?
The three-dimensional structural model of F. graminearum DHODHII protein, as predicted by AlphaFold, was obtained from the UniProt database. Additionally, a detailed description along with appropriate citations has been incorporated in the ‘Manuscript’ file.
-
-
samkriss.substack.com samkriss.substack.com
-
Every day I spawn in. Emerge wriggling out my skibidi bolus of slime. Whence and where? Lol. Idk. Vibes here be mad shady fr. Shit is not aesthetic. Shit is not bussin. Shit is burned-out cars piled in barricades across the street. Shit is THE END IS NIGH scrawled across bridges. Shit is roofs caved in, windows boarded, thin trees already rising out the wreckage, with roots that slip through gaps in the brickwork to return the brief work of man to the senseless rubble that came before. This sus ahh Ohio ahh realm is my crib. Damn, bitch, I live like this
tho you have to see he’s having fun with the lect
-
-
-
deep research couldn’t interact with websites to refine results or access content requiring user authentication
dr 的缺点是无法与网站交互(比如输入搜索)以及访问需要用户身份验证的内容,而这些正式 operator 所擅长的。
-
-
elifesciences.org elifesciences.org
-
ATCCCRL-3216
DOI: 10.7554/eLife.92406
Resource: (RRID:CVCL_0063)
Curator: @areedewitt04
SciCrunch record: RRID:CVCL_0063
Tags
Annotators
URL
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
24623
DOI: 10.7554/eLife.41444
Resource: RRID:BDSC_24623
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_24623
-
43144
DOI: 10.7554/eLife.41444
Resource: RRID:BDSC_43144
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_43144
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
Rps174; RpL141
DOI: 10.7554/eLife.38843
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @bdscstockkeepers
SciCrunch record: RRID:SCR_006457
-
l(3)CL-L1
DOI: 10.7554/eLife.38843
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @bdscstockkeepers
SciCrunch record: RRID:SCR_006457
Tags
Annotators
URL
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
32040
DOI: 10.3389/fgene.2019.00149
Resource: RRID:BDSC_32040
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_32040
-
3605
DOI: 10.3389/fgene.2019.00149
Resource: RRID:BDSC_3605
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_3605
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
011699
DOI: 10.3389/fcell.2025.1571770
Resource: (MMRRC Cat# 011699-UCD,RRID:MMRRC_011699-UCD)
Curator: @AleksanderDrozdz
SciCrunch record: RRID:MMRRC_011699-UCD
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
Dot-Gal4
DOI: 10.1681/ASN.2018080786
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @bdscstockkeepers
SciCrunch record: RRID:SCR_006457
Tags
Annotators
URL
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
4414
DOI: 10.1534/genetics.119.302037
Resource: RRID:BDSC_4414
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_4414
-
9146
DOI: 10.1534/genetics.119.302037
Resource: RRID:BDSC_9146
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_9146
-
3605
DOI: 10.1534/genetics.119.302037
Resource: RRID:BDSC_3605
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_3605
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
BL‐33708
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_33708
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_33708
-
BL‐26308
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_26308
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_26308
-
BL‐28563
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_28563
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_28563
-
BL‐32840
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_32840
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_32840
-
BL‐34665
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_34665
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_34665
-
BL‐51155
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_51155
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_51155
-
BL‐32372
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_32372
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_32372
-
BL‐34919
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_34919
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_34919
-
BL‐35573
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_35573
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_35573
-
BL‐28918
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_28918
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_28918
-
BL‐32845
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_32845
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_32845
-
BL‐31266
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_31266
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_31266
-
BL‐28696
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_28696
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_28696
-
BL‐33745
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_33745
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_33745
-
BL‐31615
DOI: 10.15252/embr.201846944
Resource: RRID:BDSC_31615
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_31615
-
-
journals.plos.org journals.plos.org
-
GraphPad Prism
DOI: 10.1371/journal.pgen.1008253
Resource: GraphPad Prism (RRID:SCR_002798)
Curator: @areedewitt04
SciCrunch record: RRID:SCR_002798
Tags
Annotators
URL
-
-
journals.biologists.com journals.biologists.com
-
ImageJ
DOI: 10.1242/jeb.242792
Resource: ImageJ (RRID:SCR_003070)
Curator: @areedewitt04
SciCrunch record: RRID:SCR_003070
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
Mef2-Gal4.R-3
DOI: 10.1242/jcs.263844
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @bdscstockkeepers
SciCrunch record: RRID:SCR_006457
-
UAS-sktlRNAiJF02796
DOI: 10.1242/jcs.263844
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @bdscstockkeepers
SciCrunch record: RRID:SCR_006457
Tags
Annotators
URL
-
-
journals.biologists.com journals.biologists.com
-
t
DOI: 10.1242/jcs.258601
Resource: (Abcam Cat# ab28379, RRID:AB_2192903)
Curator: @areedewitt04
SciCrunch record: RRID:AB_2192903
-
t
DOI: 10.1242/jcs.258601
Resource: (Abcam Cat# ab76541, RRID:AB_1523334)
Curator: @areedewitt04
SciCrunch record: RRID:AB_1523334
-
o
DOI: 10.1242/jcs.258601
Resource: (Abcam Cat# ab16780, RRID:AB_2259338)
Curator: @areedewitt04
SciCrunch record: RRID:AB_2259338
-
n
DOI: 10.1242/jcs.258601
Resource: (Santa Cruz Biotechnology Cat# sc-271462, RRID:AB_10648902)
Curator: @areedewitt04
SciCrunch record: RRID:AB_10648902
-
A
DOI: 10.1242/jcs.258601
Resource: (Cell Signaling Technology Cat# 2360, RRID:AB_2080320)
Curator: @areedewitt04
SciCrunch record: RRID:AB_2080320
-
n
DOI: 10.1242/jcs.258601
Resource: (Bethyl Cat# A300-110A, RRID:AB_2064794)
Curator: @areedewitt04
SciCrunch record: RRID:AB_2064794
-
a
DOI: 10.1242/jcs.258601
Resource: (Sigma-Aldrich Cat# F1804, RRID:AB_262044)
Curator: @areedewitt04
SciCrunch record: RRID:AB_262044
-
s
DOI: 10.1242/jcs.258601
Resource: (Abcam Cat# ab28364, RRID:AB_726362)
Curator: @areedewitt04
SciCrunch record: RRID:AB_726362
-
d
DOI: 10.1242/jcs.258601
Resource: (Abcam Cat# ab70469, RRID:AB_2229454)
Curator: @areedewitt04
SciCrunch record: RRID:AB_2229454
-
e
DOI: 10.1242/jcs.258601
Resource: (Santa Cruz Biotechnology Cat# sc-56, RRID:AB_628110)
Curator: @areedewitt04
SciCrunch record: RRID:AB_628110
-
o
DOI: 10.1242/jcs.258601
Resource: (Abcam Cat# ab7029, RRID:AB_305706)
Curator: @areedewitt04
SciCrunch record: RRID:AB_305706
-
i
-
b
DOI: 10.1242/jcs.258601
Resource: (Abcam Cat# ab7028, RRID:AB_305705)
Curator: @areedewitt04
SciCrunch record: RRID:AB_305705
-
d
DOI: 10.1242/jcs.258601
Resource: (Santa Cruz Biotechnology Cat# sc-9996, RRID:AB_627695)
Curator: @areedewitt04
SciCrunch record: RRID:AB_627695
-
i
DOI: 10.1242/jcs.258601
Resource: (Santa Cruz Biotechnology Cat# sc-13145, RRID:AB_628254)
Curator: @areedewitt04
SciCrunch record: RRID:AB_628254
-
b
DOI: 10.1242/jcs.258601
Resource: (Santa Cruz Biotechnology Cat# sc-166830, RRID:AB_2260278)
Curator: @areedewitt04
SciCrunch record: RRID:AB_2260278
-
i
-
-
pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
-
25374
DOI: 10.1242/dmm.037325
Resource: RRID:BDSC_25374
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_25374
-
48667
DOI: 10.1242/dmm.037325
Resource: RRID:BDSC_48667
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_48667
-
24650
DOI: 10.1242/dmm.037325
Resource: RRID:BDSC_24650
Curator: @bdscstockkeepers
SciCrunch record: RRID:BDSC_24650
-