RRID:AB_2619605
DOI: 10.1016/j.celrep.2025.115590
Resource: (DSHB Cat# PMY-2A4, RRID:AB_2619605)
Curator: @scibot
SciCrunch record: RRID:AB_2619605
RRID:AB_2619605
DOI: 10.1016/j.celrep.2025.115590
Resource: (DSHB Cat# PMY-2A4, RRID:AB_2619605)
Curator: @scibot
SciCrunch record: RRID:AB_2619605
RRID:AB_303402
DOI: 10.1016/j.celrep.2025.115590
Resource: (Abcam Cat# ab2907, RRID:AB_303402)
Curator: @scibot
SciCrunch record: RRID:AB_303402
RRID:AB_2097934
DOI: 10.1016/j.celrep.2025.115590
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2097934
RRID:Addgene_22036
DOI: 10.1016/j.celrep.2025.115590
Resource: RRID:Addgene_22036
Curator: @scibot
SciCrunch record: RRID:Addgene_22036
RRID:Addgene_21809
DOI: 10.1016/j.celrep.2025.115590
Resource: RRID:Addgene_21809
Curator: @scibot
SciCrunch record: RRID:Addgene_21809
RRID:Addgene_12259
DOI: 10.1016/j.celrep.2025.115590
Resource: RRID:Addgene_12259
Curator: @scibot
SciCrunch record: RRID:Addgene_12259
RRID:Addgene_21807
DOI: 10.1016/j.celrep.2025.115590
Resource: RRID:Addgene_21807
Curator: @scibot
SciCrunch record: RRID:Addgene_21807
RRID:CVCL_0019
DOI: 10.1016/j.celrep.2025.115590
Resource: (BCRJ Cat# 0223, RRID:CVCL_0019)
Curator: @scibot
SciCrunch record: RRID:CVCL_0019
RRID:CVCL_5555
DOI: 10.1016/j.celrep.2025.115590
Resource: (RRID:CVCL_5555)
Curator: @scibot
SciCrunch record: RRID:CVCL_5555
RRID:CVCL_0062
DOI: 10.1016/j.celrep.2025.115590
Resource: (RRID:CVCL_0062)
Curator: @scibot
SciCrunch record: RRID:CVCL_0062
RRID:CVCL_0598
DOI: 10.1016/j.celrep.2025.115590
Resource: (ATCC Cat# CRL-10317, RRID:CVCL_0598)
Curator: @scibot
SciCrunch record: RRID:CVCL_0598
RRID:CVCL_0030
DOI: 10.1016/j.celrep.2025.115590
Resource: (ICLC Cat# HTL95023, RRID:CVCL_0030)
Curator: @scibot
SciCrunch record: RRID:CVCL_0030
RRID:AB_10015289
DOI: 10.1016/j.celrep.2025.115590
Resource: (Yeasen Biotech Cat# 33201ES60, RRID:AB_10015289)
Curator: @scibot
SciCrunch record: RRID:AB_10015289
RRID:Addgene_15108
DOI: 10.1016/j.celrep.2025.115590
Resource: RRID:Addgene_15108
Curator: @scibot
SciCrunch record: RRID:Addgene_15108
BDSC:54591
DOI: 10.1016/j.celrep.2020.107841
Resource: RRID:BDSC_54591
Curator: @scibot
SciCrunch record: RRID:BDSC_54591
Addgene_62208
DOI: 10.1016/j.celrep.2020.107841
Resource: RRID:Addgene_62208
Curator: @scibot
SciCrunch record: RRID:Addgene_62208
RRID:AB_2936298
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab300421, RRID:AB_2936298)
Curator: @scibot
SciCrunch record: RRID:AB_2936298
RRID:AB_2891049
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab222699, RRID:AB_2891049)
Curator: @scibot
SciCrunch record: RRID:AB_2891049
RRID:AB_1523910
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab64693, RRID:AB_1523910)
Curator: @scibot
SciCrunch record: RRID:AB_1523910
RRID:AB_2758917
DOI: 10.1016/j.cell.2025.09.029
Resource: (ABclonal Cat# A1199, RRID:AB_2758917)
Curator: @scibot
SciCrunch record: RRID:AB_2758917
RRID:AB_300798
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab13970, RRID:AB_300798)
Curator: @scibot
SciCrunch record: RRID:AB_300798
RRID:AB_306047
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab7753, RRID:AB_306047)
Curator: @scibot
SciCrunch record: RRID:AB_306047
RRID:AB_2307313
DOI: 10.1016/j.cell.2025.09.029
Resource: (Aves Labs Cat# GFP-1010, RRID:AB_2307313)
Curator: @scibot
SciCrunch record: RRID:AB_2307313
RRID:AB_2616025
DOI: 10.1016/j.cell.2025.09.029
Resource: (Cell Signaling Technology Cat# 11815, RRID:AB_2616025)
Curator: @scibot
SciCrunch record: RRID:AB_2616025
RRID:AB_2876881
DOI: 10.1016/j.cell.2025.09.029
Resource: (Proteintech Cat# 26765-1-AP, RRID:AB_2876881)
Curator: @scibot
SciCrunch record: RRID:AB_2876881
RRID:AB_2620141
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab134166, RRID:AB_2620141)
Curator: @scibot
SciCrunch record: RRID:AB_2620141
RRID:AB_2801637
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab213363, RRID:AB_2801637)
Curator: @scibot
SciCrunch record: RRID:AB_2801637
RRID:AB_1107780
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0090, RRID:AB_1107780)
Curator: @scibot
SciCrunch record: RRID:AB_1107780
RRID:AB_2256751
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab78078, RRID:AB_2256751)
Curator: @scibot
SciCrunch record: RRID:AB_2256751
RRID:AB_1107769
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0089, RRID:AB_1107769)
Curator: @scibot
SciCrunch record: RRID:AB_1107769
RRID:AB_2798662
DOI: 10.1016/j.cell.2025.09.029
Resource: (Cell Signaling Technology Cat# 14959, RRID:AB_2798662)
Curator: @scibot
SciCrunch record: RRID:AB_2798662
RRID:AB_10949073
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0101, RRID:AB_10949073)
Curator: @scibot
SciCrunch record: RRID:AB_10949073
RRID:AB_1107771
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0085, RRID:AB_1107771)
Curator: @scibot
SciCrunch record: RRID:AB_1107771
RRID:AB_1107737
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0036, RRID:AB_1107737)
Curator: @scibot
SciCrunch record: RRID:AB_1107737
RRID:AB_2209009
DOI: 10.1016/j.cell.2025.09.029
Resource: (Abcam Cat# ab3487, RRID:AB_2209009)
Curator: @scibot
SciCrunch record: RRID:AB_2209009
RRID:AB_2563926
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 362509, RRID:AB_2563926)
Curator: @scibot
SciCrunch record: RRID:AB_2563926
RRID:AB_10950382
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0119, RRID:AB_10950382)
Curator: @scibot
SciCrunch record: RRID:AB_10950382
RRID:AB_493578
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 301610, RRID:AB_493578)
Curator: @scibot
SciCrunch record: RRID:AB_493578
RRID:AB_2687699
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0213, RRID:AB_2687699)
Curator: @scibot
SciCrunch record: RRID:AB_2687699
RRID:AB_2904367
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 344769, RRID:AB_2904367)
Curator: @scibot
SciCrunch record: RRID:AB_2904367
RRID:AB_2566388
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 327017, RRID:AB_2566388)
Curator: @scibot
SciCrunch record: RRID:AB_2566388
RRID:AB_2564139
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 302056, RRID:AB_2564139)
Curator: @scibot
SciCrunch record: RRID:AB_2564139
RRID:AB_1125541
DOI: 10.1016/j.cell.2025.09.029
Resource: (Bio X Cell Cat# BE0061, RRID:AB_1125541)
Curator: @scibot
SciCrunch record: RRID:AB_1125541
RRID:AB_2295770
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 505826, RRID:AB_2295770)
Curator: @scibot
SciCrunch record: RRID:AB_2295770
RRID:AB_2721360
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 367130, RRID:AB_2721360)
Curator: @scibot
SciCrunch record: RRID:AB_2721360
RRID:AB_2783136
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 156504, RRID:AB_2783136)
Curator: @scibot
SciCrunch record: RRID:AB_2783136
RRID:AB_493691
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 300320, RRID:AB_493691)
Curator: @scibot
SciCrunch record: RRID:AB_493691
RRID:AB_2924601
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 396423, RRID:AB_2924601)
Curator: @scibot
SciCrunch record: RRID:AB_2924601
RRID:AB_2561357
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 304032, RRID:AB_2561357)
Curator: @scibot
SciCrunch record: RRID:AB_2561357
RRID:AB_439783
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 105014, RRID:AB_439783)
Curator: @scibot
SciCrunch record: RRID:AB_439783
RRID:AB_2860777
DOI: 10.1016/j.cell.2025.09.029
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2860777
RRID:AB_313777
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 117308, RRID:AB_313777)
Curator: @scibot
SciCrunch record: RRID:AB_313777
RRID:AB_312695
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 100410, RRID:AB_312695)
Curator: @scibot
SciCrunch record: RRID:AB_312695
RRID:AB_493523
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 107616, RRID:AB_493523)
Curator: @scibot
SciCrunch record: RRID:AB_493523
RRID:AB_2562248
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 141720, RRID:AB_2562248)
Curator: @scibot
SciCrunch record: RRID:AB_2562248
RRID:AB_893482
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 123112, RRID:AB_893482)
Curator: @scibot
SciCrunch record: RRID:AB_893482
RRID:AB_313775
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 117306, RRID:AB_313775)
Curator: @scibot
SciCrunch record: RRID:AB_313775
RRID:AB_313151
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 105008, RRID:AB_313151)
Curator: @scibot
SciCrunch record: RRID:AB_313151
RRID:AB_313133
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 104712 (also 104711), RRID:AB_313133)
Curator: @scibot
SciCrunch record: RRID:AB_313133
RRID:AB_312975
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 103110, RRID:AB_312975)
Curator: @scibot
SciCrunch record: RRID:AB_312975
RRID:AB_312789
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 101206, RRID:AB_312789)
Curator: @scibot
SciCrunch record: RRID:AB_312789
RRID:AB_312663
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 100206, RRID:AB_312663)
Curator: @scibot
SciCrunch record: RRID:AB_312663
RRID:AB_11204423
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 118124, RRID:AB_11204423)
Curator: @scibot
SciCrunch record: RRID:AB_11204423
RRID:AB_312661
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 100204, RRID:AB_312661)
Curator: @scibot
SciCrunch record: RRID:AB_312661
RRID:AB_312749
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 100710, RRID:AB_312749)
Curator: @scibot
SciCrunch record: RRID:AB_312749
RRID:AB_312791
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 101208, RRID:AB_312791)
Curator: @scibot
SciCrunch record: RRID:AB_312791
RRID:AB_2915935
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4450017, RRID:AB_2915935)
Curator: @scibot
SciCrunch record: RRID:AB_2915935
RRID:AB_2935889
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4450050, RRID:AB_2935889)
Curator: @scibot
SciCrunch record: RRID:AB_2935889
RRID:AB_3094497
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4450096, RRID:AB_3094497)
Curator: @scibot
SciCrunch record: RRID:AB_3094497
RRID:AB_3094500
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4450095, RRID:AB_3094500)
Curator: @scibot
SciCrunch record: RRID:AB_3094500
RRID:AB_3094499
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4550112, RRID:AB_3094499)
Curator: @scibot
SciCrunch record: RRID:AB_3094499
RRID:AB_3094498
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4450094, RRID:AB_3094498)
Curator: @scibot
SciCrunch record: RRID:AB_3094498
RRID:AB_2936080
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4550119, RRID:AB_2936080)
Curator: @scibot
SciCrunch record: RRID:AB_2936080
RRID:AB_3662772
DOI: 10.1016/j.cell.2025.09.029
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3662772
RRID:AB_2562559
DOI: 10.1016/j.cell.2025.09.029
Resource: (BioLegend Cat# 103134, RRID:AB_2562559)
Curator: @scibot
SciCrunch record: RRID:AB_2562559
RRID:AB_3096409
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4550058, RRID:AB_3096409)
Curator: @scibot
SciCrunch record: RRID:AB_3096409
RRID:AB_2935894
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4550113, RRID:AB_2935894)
Curator: @scibot
SciCrunch record: RRID:AB_2935894
RRID:AB_3662765
DOI: 10.1016/j.cell.2025.09.029
Resource: Akoya Biosciences Cat# 4250099, RRID:AB_3662765
Curator: @scibot
SciCrunch record: RRID:AB_3662765
RRID:AB_3662766
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4550127, RRID:AB_3662766)
Curator: @scibot
SciCrunch record: RRID:AB_3662766
RRID:AB_2915960
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4250012, RRID:AB_2915960)
Curator: @scibot
SciCrunch record: RRID:AB_2915960
RRID:AB_3083459
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4550114, RRID:AB_3083459)
Curator: @scibot
SciCrunch record: RRID:AB_3083459
RRID:AB_2927679
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4550071, RRID:AB_2927679)
Curator: @scibot
SciCrunch record: RRID:AB_2927679
RRID:AB_3082979
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4250094, RRID:AB_3082979)
Curator: @scibot
SciCrunch record: RRID:AB_3082979
RRID:AB_2935895
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4250079, RRID:AB_2935895)
Curator: @scibot
SciCrunch record: RRID:AB_2935895
RRID:AB_3476455
DOI: 10.1016/j.cell.2025.09.029
Resource: Akoya Biosciences Cat# 4250062, RRID:AB_3476455
Curator: @scibot
SciCrunch record: RRID:AB_3476455
RRID:AB_2927678
DOI: 10.1016/j.cell.2025.09.029
Resource: (Akoya Biosciences Cat# 4250083, RRID:AB_2927678)
Curator: @scibot
SciCrunch record: RRID:AB_2927678
RRID:CVCL_0063
DOI: 10.1016/j.cell.2025.09.026
Resource: (RRID:CVCL_0063)
Curator: @scibot
SciCrunch record: RRID:CVCL_0063
CVCL_0059
DOI: 10.1016/j.cell.2025.09.026
Resource: (IZSLER Cat# BS CL 86, RRID:CVCL_0059)
Curator: @scibot
SciCrunch record: RRID:CVCL_0059
RRID:AB_330288
DOI: 10.1016/j.cell.2025.09.026
Resource: (Cell Signaling Technology Cat# 4967, RRID:AB_330288)
Curator: @scibot
SciCrunch record: RRID:AB_330288
RRID:AB_11134144
DOI: 10.1016/j.cell.2025.09.026
Resource: (LSBio (LifeSpan) Cat# LS-B6572-50, RRID:AB_11134144)
Curator: @scibot
SciCrunch record: RRID:AB_11134144
RRID:SCR_015058
DOI: 10.1016/j.cell.2025.09.025
Resource: bcl2fastq (RRID:SCR_015058)
Curator: @scibot
SciCrunch record: RRID:SCR_015058
RRID:SCR_013672
DOI: 10.1016/j.cell.2025.09.025
Resource: ZEISS ZEN Microscopy Software (RRID:SCR_013672)
Curator: @scibot
SciCrunch record: RRID:SCR_013672
RRID:AB_2338000
DOI: 10.1016/j.cell.2025.09.025
Resource: (Jackson ImmunoResearch Labs Cat# 111-165-003, RRID:AB_2338000)
Curator: @scibot
SciCrunch record: RRID:AB_2338000
RRID:AB_2338690
DOI: 10.1016/j.cell.2025.09.025
Resource: (Jackson ImmunoResearch Labs Cat# 115-165-146, RRID:AB_2338690)
Curator: @scibot
SciCrunch record: RRID:AB_2338690
RRID:SCR_018673
DOI: 10.1016/j.cell.2025.09.025
Resource: Harvard Center for Biological Imaging Core Facility (RRID:SCR_018673)
Curator: @scibot
SciCrunch record: RRID:SCR_018673
RRID:AB_2792314
DOI: 10.1016/j.cell.2025.09.025
Resource: (Thermo Fisher Scientific Cat# PA5-85167, RRID:AB_2792314)
Curator: @scibot
SciCrunch record: RRID:AB_2792314
RRID:AB_916156
DOI: 10.1016/j.cell.2025.09.025
Resource: (Cell Signaling Technology Cat# 4858, RRID:AB_916156)
Curator: @scibot
SciCrunch record: RRID:AB_916156
RRID:AB_2338046
DOI: 10.1016/j.cell.2025.09.025
Resource: (Jackson ImmunoResearch Labs Cat# 111-545-003, RRID:AB_2338046)
Curator: @scibot
SciCrunch record: RRID:AB_2338046
RRID:SCR_017202
DOI: 10.1016/j.cccb.2025.100401
Resource: BZ X-710 fluorescent microscope (RRID:SCR_017202)
Curator: @scibot
SciCrunch record: RRID:SCR_017202
RRID:SCR_023864
DOI: 10.1007/s10886-025-01647-6
Resource: Pennsylvania State University Huck Institutes of Life Sciences Metabolomics Core Facility (RRID:SCR_023864)
Curator: @scibot
SciCrunch record: RRID:SCR_023864
RRID:AB_2741287
DOI: 10.1007/s10238-025-01897-4
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2741287
RRID:AB_1257142
DOI: 10.1007/s10238-025-01897-4
Resource: (Thermo Fisher Scientific Cat# 25-0629-42, RRID:AB_1257142)
Curator: @scibot
SciCrunch record: RRID:AB_1257142
RRID:AB_493257
DOI: 10.1007/s10238-025-01897-4
Resource: (BioLegend Cat# 301910, RRID:AB_493257)
Curator: @scibot
SciCrunch record: RRID:AB_493257
RRID:AB_395799
DOI: 10.1007/s10238-025-01897-4
Resource: (BD Biosciences Cat# 555398, RRID:AB_395799)
Curator: @scibot
SciCrunch record: RRID:AB_395799
RRID:AB_2016659
DOI: 10.1007/s10238-025-01897-4
Resource: (Thermo Fisher Scientific Cat# 17-0118-42, RRID:AB_2016659)
Curator: @scibot
SciCrunch record: RRID:AB_2016659
RRID:CVCL_0063
DOI: 10.1007/s00018-025-05915-2
Resource: (RRID:CVCL_0063)
Curator: @scibot
SciCrunch record: RRID:CVCL_0063
RRID:CVCL_QX51
DOI: 10.1007/s00018-025-05915-2
Resource: (RRID:CVCL_QX51)
Curator: @scibot
SciCrunch record: RRID:CVCL_QX51
RRID:CVCL_0303
DOI: 10.1007/s00018-025-05915-2
Resource: (Millipore Cat# SCC065, RRID:CVCL_0303)
Curator: @scibot
SciCrunch record: RRID:CVCL_0303
RRID:AB_10857310
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sharding
partitioning
quick takeaway
Partitioning = performance tuning (single node)
Sharding = scaling out (multiple nodes)
Replication = redundancy or read scaling (same data copied)
so, 3 separate ideas:
partition = split table
shard = split dataset across DBs
replica = copy dataset across DBs
consistency
before vs after transaction, db is in valid state.. and still all external parts linking to db data is valid ( lilke triggers, indexes, foreign keys )
read uncommitted: can read dirty data• read committed: only committed data, no dirty reads• repeatable read: same reads during txn, may allow phantom rows• serializable: strictest, prevents all anomalies, lowest concurrency
read uncommitted
dirty reads, non repeatable reads, phantom reads
read committed
non repeatable reads, phantom reads and no dirty reads
repeatable reads
phantom reads and not nonrepeatable reads, no dirty reads
serializable :
no phantom, nonrepeatable, dirty reads
covering index
engine skips main table read → serves result right from index.
indexing
primary - data stored in index order - 1step lookup - main access key
secondary - points to primary index fields - 2 step lookup - extra filters / sorts
covered - stores full needed cols - 1 step lookup - readheavy endpoints
flexibility
no strict schema
Aldabra
Native American girls' dolls * Ka'aton'ya * Tamaya
for - US Republican governance failure - blue states provide welfare to red states - youtube - Dave Pakman - blue states vs red states - The US survives Trump's mismanagement because the US is a welfare state in which the blue states, with far better social policies is forced to bail out the tax-friendly red states - The red states keep choosing the same dysfunctional policies, and keep having to get bailed out by the blue states - In this sense, the federal government is being exploited to keep red states doing the same thing
Failure to perform or respond to friendship-maintenance tasks can lead to the deterioration and eventual dissolution of friendships. Causes of dissolution may be voluntary (termination due to conflict), involuntary (death of friendship partner), external (increased family or work commitments), or internal (decreased liking due to perceived lack of support) (Bleiszner & Adams, 1992).
Sometimes friendships can also deteriorate due to internal conflict on one side, or personal issues, I've had reasons to end relationships, while I also have been the one who has been theoretically "dumped" in a relationship.
The number of friends we have at any given point is a situational factor that also affects whether or not we are actually looking to add new friends.
I think this also is affected by the situation you're in as well, I currently feel incredibly lonely because I struggle to get to the point where I feel comfortable or ready to hang out with someone or be 'real' friends as I say, instead of just acquaintances.
friendship may develop between two people who work out at the same gym. They may spend time with each other in this setting a few days a week for months or years, but their friendship might end if the gym closes or one person’s schedule changes.
I feel like this is a situational friend, like if you go to class with someone and you go to study group for that class, but after the class ends we part ways.
overrideデコレ
よさそう
型エイリアスの書き方
良さそう
Self
これも説明してほしい
assert_never()関数
これはよさそう
*kwargs引数にTypedDictの型を付
その手前で、そもそもTypedDictで必須とかオプションとか指定できるようになったので、この話をする必要があるかなと
Circumscribing
creating a boundary is good, but not always, it can mean that someone has recognized something they are uncomfortable with about their situation, and want to create space but aren't sure how, which could also relate to avoiding.
Intensifying
A lot of the time, or maybe just with me, I can see myself rushing into this stage to get to the integrating stage, but usually it's because i'm so excited to be around the person and to have a 'someone.' which reminds me of how a happy dog is so excited for you to be homme they run up to you and jump on you at the door, and you're so overwhelmed you push them away.
The Ka'ba in the Masjid Al-Haram in Mecca, during the 2018 Hajj season.Muhammad's revelations continued and were written down in what became the Qur'an. The focus on social justice, submission (islam) to god, and monotheism echoed elements of Judaism and Christianity, and Muhammad's followers described their new faith as a continuation of a tradition that began with Abraham and accepted the Hebrew prophets, including Jesus.
I just learned about The Ba'ba. It is called "The Holiest of Holies." It was built during the Old Testament times when God told them exactly how to build it. They have had to rebuild it, but it has real gold, and the doors (covered in the cloth) are pure gold.
Gothic and Byzantine battle in Italy
This picture shows so much detail of what happened or what may have happened.
The lack of imperial endorsement weakened Theodoric's daughter and her son, and in 535, Justinian invaded Italy
This is so soon after Theodoric died. Many times, in history when there is a new ruler(s) they get weakened down and invaded.
Theodoric advanced into Italy between 489 and 493,
This is a long time ago. It is interesting to see that historians try to find out how long-ago things took place.
Emperor Wen and his son, Emperor Yang, ruled until 618 and set the stage for the Tang Dynasty
Random thought but I feel like there are many emperors in China that rule for very long periods of time.
On the Similarities Between the SGI Doctrinal Text and Professor Miyata’s Paper
Issue 1.
Lately, on social media, there have been discussions suggesting that The Book on the Doctrinal Foundation of the SGI, published immediately after President Daisaku Ikeda’s passing, closely resembles several papers written by Professor Koichi Miyata. I also share this impression.
Mr. Suda, former Vice Leader of the SGI Study Department, makes the following claim in his Letter to President Harada regarding the “Teaching Outline”: “I have heard that the main individuals behind the creation of the Teaching Outline were Mr. Miyata and Mr. Kanno, both professors emeritus at Soka University. From their standpoint as researchers, however, they have shown a marked tendency to defer to the Minobu sect of Nichiren Buddhism, which represents the mainstream of academic Nichiren studies, seemingly out of fear of criticism from that sect. As a result, the entire Teaching Outline can be seen as having been assimilated to the doctrines of the Minobu sect.” On the other hand, the SGI Men’s Division Doctrinal Office officially denied any involvement of Professors Miyata and Kanno, stating on the Seikyo Shimbun website that “this claim is factually incorrect, and neither Professor Miyata nor Professor Kanno were members of the publication committee.” (Reference: Seikyo Online) In response, I conducted a careful comparative analysis of The Book on the Doctrinal Foundation of the SGI and Professor Miyata’s papers, employing not only a close textual reading but also the analytical functions of a natural language processing AI (ChatGPT) to ensure objectivity. The results revealed a level of similarity far beyond my expectations—one that can hardly be overlooked.
SGI is a large religious organization with approximately twelve million members in Japan and around the world, and The Book on the Doctrinal Foundation of the SGI appears to have become the organization’s core doctrinal text following President Ikeda’s passing. In this regard, Suda, in his Letter to President Harada regarding the “Teaching Outline”, points out that “Even now, it seems that the ‘Teaching Outline’ is being followed in articles in the Soka Shimpo and Seikyo Shimbun newspapers, as well as in the commentary on The Object of Devotion for Observing the Mind, and I think that this is a dangerous situation.” Therefore, this issue is of considerable importance for the future of the SGI’s doctrinal study.
At the same time, it should be emphasized that the purpose of this paper is not to criticize any individual personally, but rather to ensure the accuracy and scholarly transparency of doctrinal materials.To maintain the credibility of SGI’s doctrinal studies, it is increasingly necessary to clarify bibliographical sources and secure philosophical consistency in future publications.
Professor Koichi Miyata, “The Structure and Issues of Udana Nichiko’s Honzon Ryakuben” (2017–2018, pp. 38–39)
“The passage ‘The doctrine of three thousand realms in a single moment of life is found in only one place, hidden in the depths of the “Life Span” chapter of the essential teaching of the Lotus Sutra’ (WND I: 30) can be interpreted, from the overall context, to mean that the doctrine of the true “three thousand realms in a single moment of life” is hidden in the text of the “Life Span” chapter—that is, in the passage revealing enlightenment countless kalpas ago.” The Book on the Doctrinal Foundation of the SGI (Kyōgaku Yōkō, 2023, p. 70) “The great sage Nichiren states in The Opening of the Eyes, ‘The doctrine of three thousand realms in a single moment of life is found in only one place, hidden in the depths of the “Life Span” chapter of the essential teaching of the Lotus Sutra’ (WND I: 30). He perceived that, at the very depths of the chapter The Life Span of the Thus Come One, which expounds enlightenment countless kalpas ago, the essential doctrine of three thousand realms in a single moment of life in the Lotus Sutra is revealed.” Commentary The Book on the Doctrinal Foundation of the SGI makes no reference to Miyata’s paper. Yet both the book and Miyata’s interpretation share a distinctive view: that the passage describing “enlightenment countless kalpas ago” conceals the doctrine of three thousand realms in a single moment of life. In the Book on the Doctrinal Foundation of the SGI, this interpretation is presented as if it were Nichiren’s own insight, raising serious concerns regarding the proper attribution of scholarly authority. In this respect, the book may be seen as raising a significant issue of academic integrity. Incidentally, the traditional SGI interpretation—found in the third President Daisaku Ikeda’s works such as The Lecture on the Orally Transmitted Teachings II (pp. 32–33)—is that this doctrine is concealed in the passage “Originally I practiced the bodhisattva way” (Burton Watson, The Lotus Sutra, p. 268) in the Life Span chapter. From this perspective, The Book on the Doctrinal Foundation represents a problematic departure from that established tradition.
In this respect, Suda, former Vice Leader of the SGI Study Department (2024, p. 53), criticizes this book, stating that “Although The Book on the Doctrinal Foundation was published immediately after Ikeda’s passing and claims to have been supervised by him, its content significantly deviates from Ikeda’s ideological framework during his lifetime. Thus, the assertion that the book was under Ikeda’s supervision can be seen as an attempt to misuse his name rather than a genuine reflection of his doctrinal stance.”
Furthermore, in his paper, Professor Miyata rejects the traditional interpretation that locates the doctrine in the passage “Originally I practiced the bodhisattva way” (Burton Watson, The Lotus Sutra, p. 268) and offers his own alternative view. The following section examines the possibility that this reinterpretation found its way into The Book on the Doctrinal Foundation of the SGI.
Reference
Ikeda, D. (1968) Gogikuden Kōgi [Lecture on the Oral Transmission of the Teachings, vol. 2]. Tokyo: Soka Gakkai.
Miyata, K. (2017–2018). The Structure and Issues of Udana Nichiko’s Honzon Ryakuben. Available at: http://hw001.spaaqs.ne.jp/miya33x/honzonryakuben.pdf [Accessed 24 October 2025].
Nakamura, M. (2025) Kyôgaku Yōkō to Moto Sōka Daigaku Kyōju no Ronbun no Hikaku Kensō [A Comparative Examination of the Book on the Doctrinal Foundation of SGI and Papers by Former Soka University Professors]. Available at: https://jikatsu.net/wp-content/uploads/2025/10/4f92b9e0e1e7f83a456ee2c6d262748b.pdf [Accessed 24 October 2025].
Soka Gakkai. (1999). The Writing of Nichiren Daishonin. Tokyo: Soka Gakkai.
Soka Gakkai (2023) Kyōgaku Yōkō [The Book on the Doctrinal Foundation of SGI]. Tokyo: Soka Gakkai. Available at: https://www.amazon.co.jp/dp/4412017028 (Accessed: 24 October 2025).
SGI Study Department (2024). “The Teaching Outline” is the Culmination of the Soka Renaissance. Available at: https://www.seikyoonline.com/article/603E8EF7E9B96D20AF2920005F5C1C6B [Accessed 10 October 2025].
Suda, H. (2024). Letter to President Harada regarding the “Teaching Outline”, 12 September 2024. file_20240930-185744.pdf [Accessed 24 October 2025].
Suda, H. (2024). A Critique of the Book on Doctrinal Foundation of Soka Gakkai from the Perspective of Buddhist History: In Light of Nichiren Buddhism as the Global Religion Taught by SGI President Daisaku Ikeda. Available at: https://jikatsu.net/download/1st-english-edition-a-critique-of-the-book-on-doctrinal-foundation-of-soka-gakkai-from-the-perspective-of-buddhist-history/
Watson, B. (1993). The Lotus Sutra. New York: Columbia University Press.
Gutenberg
Test
In this image, the “dog” is on the left side, and the “cat” is on the right side.
Figure 1.2.3 does not have the "dog" on the left side, and the "cat" on the right side. Which feels like an ironic typo given the subject matter of the text.
V duchu postmoderného myslenia je jeho strata väčším hriechom, než jeho korekcia.
Proč si autorstvo myslí, že postmoderní myšlení implikuje toto relativní hodnocení ztráty a korekce názoru?
špecializovaných povolaní
Napadá mě jen "logoterapeut" a "filosofický poradce". Odhadl jsem správně, jaká povolání mělo na mysli autorstvo? Jaká povolání napadla nebo napadají vás?
dôstojnosť jednotlivca netkvie v plnom bruchu, ale v jeho integrite
Autorstvo zde, zdá se, předpokládá, že filosofování vede ke kladnému hodnocení integrity; k určité "křesťanské" (pro momentální neschopnost najít vhodnější označení) etice. Rád bych souhlasil a zároveň doufám, že směr etického snažení navržený tímto manifestem by měl smysl i v případě, že by filosofování mohlo vést i k méně obvyklým etickým závěrům. Jinými slovy, nepovažuji filosofování za samospásné. Podobně riskantní, mimochodem, mi připadá spoléhat se na evoluční výhody "křesťanské" etiky.
S výnimkou akademickej pôdy (kde debatné súboje aj tak často označujeme za neužitočnú zábavku neužitočných ľudí) a úzko špecializovaných povolaní (ktoré sú napádané podobným spôsobom)
Praktická filosofie (sokratovské rozhovory atp.) je další takovou výjimkou.
Bieganie częściowo naprawia to, co psują fast foody
Duzentos anos atrás, antes do advento do capitalismo, o status social de um homem permanecia inalterado do princípio ao fim de sua existência: era herdado dos seus ancestrais e nunca mudava. Se nascesse pobre, pobre seria para sempre; se rico – lorde ou duque –, manteria seu ducado, e a propriedade que o acompanhava, pelo resto dos seus dias
If you are writing a research paper about reality television shows, you will need to use some reality shows as a primary source, but secondary sources, such as a reviewer’s critique, are also important.
What kinds of sources, from which perspective, you need.
Leaving aside the question of whether exercises and worksheets are satisfying for children, it is the case that these are solitary activities, and much of the time in schools children are expected to engage in these activities on their own, neither receiving nor providing help that is similar to how children often engage in chores in middle-class families.
I see my own students more engaged when they are in groups and we are working together. I have put two big tables together in my classroom and started getting away from the solitary exercises because my special education students are already behind in social skills and understanding roles in group activities. I do this because their peers are so far ahead of them academically that they can not engage or contribute to their group the same and then the groups accuse the students of cheating when really they just cannot comprehend what the class is doing. I am trying to help the students learn social cues and academics with the activities that are centered around group work.
. There are therefore parallels between the solitary chores children were often asked to do at home and the solitary exercises they engaged in at school.
This really hit home for me because at home during my childhood everything was done in solitary, from getting ready for the day to chores and even meals. We as a family never ate together except on special occasions. If I got all of my chores, homework or whatever it might need to be taken care of done as soon as possible so I could go to my friends’ homes where we had dinner together and family engagement. I did not mind if I needed to help the family with more work.
The case demonstrates the significance ofcontinuously seeking new tools and techniques to enhance musicpublishing. Practitioners can benefit from Diana’s approach of experi-menting with different AI tools and incorporating them selectively tomaintain a unique sound and efficient business operations.
Artists can decide how many tools and which tools they wish to use, depending on their skills, priorities, and amount of time available.
connection in music, even when integrating advanced technologieslike AI. Students should understand that while AI can enhance effi-ciency, the authenticity and originality of content are crucial for audi-ence engagement (Wei et al., 2022).2. Strategic Use of AI: Diana’s selective use of AI tools for specific tasks,such as data management and analytics, illustrates the importance ofstrategically adopting technology to enhance workflow without com-promising creative integrity. This teaches students to critically evaluatethe tools they use and ensure they align with their creative goals(Hampe & Schwabe 2001).3. Adaptability and Continuous Learning: Diana’s approach high-lights the need for continuous learning and adaptability in therapidly evolving field of music publishing. Students should beprepared to stay updated with the latest technological advancementsand be willing to experiment and learn from their experiences
While AI tools are being widely integrated in industries such as music, it is very important not to overuse them, otherwise the human element and critical thinking skills required for these complex tasks are completely lost.
The evolving capabilities of AI in natural language pro-cessing and automated content generation might open new avenues forinnovative music marketing and fan engagement strategies. Diana plans tointegrate AI more deeply into her operations through advanced tools forpredictive analytics and automated content management systems, increasingefficiency and scaling her operations to reach a global audience effectively.
AI makes promotion of music through analytics and social media easier than ever.
Ensuring that AI does not compromise the emotional authenticity of musicremains a critical challenge, and Diana emphasizes the importance of usingAI to support rather than overshadow human creativity.
The age of balanced AI use like Diana's is already coming to an end, as AI tools continually get implemented everywhere.
Diana faced challenges in aligning AI toolswith existing workflows and ensuring compatibility. However, throughtargeted training and continuous learning, these challenges were addressed.The initial investment in AI systems was a hurdle, but the long-term benefitsof increased efficiency and reduced errors justified the expenditure.
These AI tools are difficult to learn with a steep learning curve, but the efficiency boost outweighs this.
Diana’s success with AI tools under-scores the importance of balancing technological advancements with main-taining the emotional and artistic integrity of music. Her work serves as anexample of how AI can be used to support rather than replace humancreativity in the music industry
Diana's use of AI does not undermine the human aspect of it; rather, it makes the process more efficient and keeps the balance between technological assistance and human input.
providing adequate trainingand resources is essential for fostering intrinsic motivation and ensuring thatusers feel competent and capable of using new tools. This approach notonly enhances proficiency but also builds confidence in using AI technolo-gies (Ezinwa et al. 2024). The continuous upgrading of IT infrastructure tosupport the latest AI technologies is another crucial aspect of developingthe ability to use AI tools effectively.
This chapter does not mention energy use or environmental impact at all.
AI’s capacity to provide real-time analytics aligns with the findings ofWatson and Leyshon (2022), who emphasize the importance of timely andaccurate data in the music industry. Real-time analytics allow for agiledecision- making, enabling music publishers like Diana to adjust their strate-gies based on current market performance and trends. This capability isparticularly valuable in a fast-paced industry where timing can significantlyimpact the success of promotional campaigns.
The music industry is very fast-paced, so AI tools are able to help artists like Diana adapt fast to new market trends.
AI tools have opened up significant opportunities for Diana, particularly indata management and analytics. These tools enable her to access real-timeanalytics on how songs are performing globally, allowing her to make quickdecisions on promotional strategies. AI also provides the capability tomanage artists’ portfolios and rights across different countries and legalenvironments seamlessly
AI tools also have access to global analytics that weren't previously easily accessible or centralized in one place.
Diana highlighted her motivation by saying:My primary driver is the desire to streamline the complex pro-cesses of music publishing and rights management to ensure thatartists receive their fair share of earnings. AI tools enable us toautomate many of the labour-intensive tasks involved, from track-ing song plays across digital platforms to managing royalties andrights distributions efficiently.
The way that Diana uses AI for music production is very ethical, simply making complex processes more efficient, and ensuring fair royalty splits.
AI-driven financial tools provide significant benefits in terms of optimiz-ing revenue streams and ensuring timely royalty payments (Barata &Coelho, 2021). The ability to analyze market trends and consumer prefer-ences using AI aligns with Diana’s strategies for maximizing revenue andenhancing the commercial success of her music projects
AI financial tools also ensure maximum revenue by analyzing market trends.
Boomplay’s analytics features have providedinsights into popular songs, influencing the release strategy for albums andsingles. By leveraging AI tools for data analysis, Diana ensures that hermarketing efforts are targeted and effective, resulting in higher streamingnumbers and increased revenue.
An AI tool called Boomplay reveals analytics of popular songs, with the ability to provide a playbook of what release strategies made it successful, so that it can be used for releasing your own music.
On the publishing front, AI tools help track music plays acrossdifferent platforms, ensuring accurate royalty collection and distribution.AI- driven analytics have also provided predictive insights that guide produc-tion decisions, enhancing the commercial success of her projects
Additionally, AI tools track music plays across all platforms, helping to distribute royalties fairly. AI analytics also help guide decisions and help musicians like Dians remain successful in today's industry.
AI tools have significantly impacted Diana’s music production and publish-ing processes. A pivotal moment was the training session conducted byVladimir Philippov, CEO of Heaven 11, which enhanced her team’s capabili-ties in using AI tailored for the music industry. The Heaven 11 platformoffers features for music distribution and rights management, crucial forartists aiming to earn from their creativity and have their music distributedglobally
Heaven 11 is an AI platform that includes tools for music distribution and copyright management, a pivotal part to solving the problem of copyright management with music generated by AI.
The adoption of AI tools in Diana’s operations reflects broader trends inthe music industry, where AI is used to enhance various business processes.AI technologies like those used by Diana streamline administrative tasksand financial management, which are crucial for maintaining operationalefficiency. This trend is consistent with findings in Chapter 2, where theimpact of AI on the music industry is discussed extensively in a literaturereview.
Adoption of AI tools is becoming widespread in all industries, for people like Diana, these tools free up time and allow her to focus on her music more.
Diana Hopeson integrates AI tools extensively in her operations as both anartist and a music publisher. She utilizes Google’s business tools for manag-ing interactions and tracking engagements, which streamlines administrativetasks and enhances efficiency. The Oze app is pivotal for her accountingprocesses, simplifying financial transactions and client interactions.
AI has allowed Diana to work more efficiently and better understand the business metrics of her music.
She also attended a needs assess-ment class at the Ghana Institute of Management and Public Administrationand graduated with a master’s degree in philosophy from the University ofEducation, Winneba, in 2019. Diana’s dedication to her craft and continuouslearning have been pivotal in her journey, allowing her to adapt to theevolving music industry and maintain her relevance over the decades.
She continued her education, getting a master's degree decades later into her career. Her dedication has allowed her to grow and adapt through the decades.
In March 2021, she was named among the Top30 Most Influential Women in Music by the 3Music Awards Women’sBrunch.In addition to her music career, Diana has played an instrumental role inshaping the music industry in Ghana. She served as the president of theMusicians Union of Ghana (MUSIGA
She is a very influential figure in the music industry.
Diana Hopeson, also known as Diana Akiwumi, has been a significantfigure in the Ghanaian music industry since 1991. With 11 albums and 15singles released, she has made a name for herself as a gospel artist and apioneering music publisher.
She is a well-established artist who has been in the industry for several decades.
C'est dit ! Il n'y a plus que la fédération et les pays n'ont plus rien à dire. Ni l'Italie, ni la France, ni l'Allemagne. L'ex de Goldman Sachs a parlé.
Cette Europe là doit mourir et le plus tôt sera le mieux. Vae victis.
44 percent
more than half of poorer students could be left behind?
Brazil is divided into 26 states and a Federal District. The Federal District andfive states were part of the study, including three of the most populous and devel-oped states (São Paulo, Minas Gerais, and Rio de Janeiro), and two states (Cearáand Tocantins) that represent less developed areas of Brazil.
most developed states, so maybe it is a certain type of students. maybe they have more opp to experiment w monetary investments and decisions, maybe they have seen recently started earning good amounts so they are curious and have the means to try out things. maybe students in poorer areas would be more cautious and disciplined due to diff financial goals?
This is how the synthetic knowledge crisis unfolds. Not through outright falsehoods, but through a gradual weakening of the criteria that distinguish knowing from appearing to know.
How do we identify the folks who are just faking it until the make it with synthetic knowledge.
my personal experience, which is that whenever I write what I think about a subject, it always turns out that my thoughts do not hold up on paper? No matter how confident I am in my thoughts, they reveal themselves on the page as little but logical holes, contradictions, and non sequiturs.
Pre-emptive note: it seems logical that the very next paragraph references Paul Graham directly; my very next move was going to be to connect the writer's self-reported experiences here with Graham on writing, had it not been the case that that job was already done.
As I've said before: I'm not in the same boat with Graham on the writing-is-thinking stance. The difficulty with seeing my own thoughts fixed in words after an initial pass is not in their inadequacy or their being a source of illusory and fleeting comfort with said illusion now made stark for everyone to see, but a mixture of (a) a lack of "punch", and/or (b) the places where a dishonest broker could exploit the yet-to-be shored up wording to suggest/assert the presence of some weakness in thought regarding the thing being argued for, where such purported weakness would be the real illusion.
The lack of satisfaction I feel when trying to capture my thoughts in English (my first language) isn't too far off from the lack of satisfaction at being able to comprehensively express a simple declarative in another language only because of the fact that don't know, say, the right word for the noun in that language. It doesn't lead me to agonize about how well-supported my observations about a backhoe are just because I've never been introduced to the word for backhoe in that language.
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Manuscript number: RC-2025-03130
Corresponding author(s): Ellie S. Heckscher
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We thank all three reviewers for their feedback on the paper. Reviewers stated that the paper was of broad interest to developmental biologists and neurobiologists. However, we want to ensure that our two key conceptual contributions are clear. We clarify in the following paragraph and include a revised abstract. We will update the introduction and paper to better reflect these advances. We also attach a supplemental table 1, which was inadvertently omitted from the previous submission due to our error.
The first advance is that serially homologous neuroblasts follow a multimodal production model: In principle, stem cells can divide any number of times, from once to throughout the entire lifetime of the animal. And, on each division, a stem cell can generate either a proliferative daughter cell or a post-mitotic neuron. Together, therefore, there is a vast potential number of neurons any given stem cell could produce. From the literature on the vertebrate neocortex, we had the following models: (1) "random production" model, in which any number of neurons could be made by a stem cell; or (2) "unitary production" model, in which the same number of neurons (~eight) is produced by a stem cell regardless of context. Our data revealed an entirely new "multi-modal production" model, which could not have been predicted by prior literature. In the context of serially homologous neuroblasts arrayed along the Drosophila larval body axis, sets of five to seven neurons are produced in increments of one, two, or four. These increments correspond to units called temporal cohorts. Temporal cohorts are lineage fragments, or small set of neurons that share synaptic partners, making them lineage-based units of circuit assembly. Thus, in a multimodal production model, serially homologous stem cells produce different numbers of temporal cohorts depending on location. Our data advance the field by showing that stem cells produce circuit-relevant sets of neurons by adding or omitting temporal cohorts from a region, to meet regional needs.
Key to understanding the second advance is that there are multiple types of temporal cohorts: early-born Notch OFF, early-born Notch ON, late-born Notch OFF, and late-born Notch ON. One temporal cohort type, the early-born Notch OFF, is found in every segment, which we term the "ubiquitous" temporal cohort. The other temporal cohort types can be produced in various combinations depending on the stem cell division pattern and segmental location. In a result that could not have been predicted, we found that the ubiquitous temporal cohorts are refined both in terms of the number of neurons and their connectivity, depending on body region. In contrast, when other temporal cohort types are produced, they are not refined to the same degree.
The impact of this work is to advance how we think about stem cell-based circuit assembly.
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
*Summary: The study by Vasudevan et al intends to address how serially homologous neural progenitors generate different numbers and types of neurons depending on their location along the body axis. *
Investigation of full repertoire of neurogenesis for these progenitors necessitates a precise ability to track the fates of both progenitors and their neuronal progeny making it extremely difficult in vertebrate paradigm. The authors used NB3-3 in the developing fly embryo as a model to investigate the full extent of the flexibility in neurogenesis from a single type of serially homologous stem cell. Previous work showed NB3-3 generates neurons including lateral interneurons that can be positively labeled by Even-skipped, but detailed characterization of the NB3-3 lineage mainly focused on 3 segments during embryogenesis. The authors defined the number of EL neurons in all segments of the central nervous system in early larvae after the completion of circuit formation and carried out clonal analyses to determine the proliferation pattern of NB3-3. They described the failure to express Eve in Notch OFF/B neurons as a new mechanism for controlling the number of EL neurons and PCD limits EL neurons in terminal segments.
*Major comments: The authors performed careful analyses of the NB3-3 lineage using EL neurons. My main concerns are limited applicability of their findings and lack of mechanisms as how NB3-3 generate various numbers of EL neurons. Their findings are exclusively relevant to the NB3-3 lineage despite their effort in highlighting that other NB lineages also generate temporal cohorts of EL neurons. *
Thank you for raising these points. First, to clarify, as Reviewer 4 also mentioned, NB3-3 is the only lineage to produce EL neurons. We will ensure that this is clearly stated in the revised text.
We agree that our findings might not apply beyond the NB3-3 lineage. However, as this is the first study of its kind, it is impossible to know a priori to what extent the concepts surfaced here are generalizable. In our opinion, this speaks to the novelty and impact of the study. A contribution is to motivate a need for future studies. We will make this explicit in our updated manuscript in the Discussion section.
Our manuscript provides cell biological mechanisms that explain how stem cells give rise to different numbers of EL neurons in different regions, including stem cell division duration and type, neural cell death, identity gene expression, and differentiation state. If the reviewer is interested in genetic or molecular mechanisms, this is an interesting point. Several prior studies using NB3-3 as a model (e.g., Tsuji et al., 2008, Birkholz et al., 2013, Baumgardt et al., 2014) have elucidated the genetic regulation of specific cell biological processes. However, these studies provided fragmentary insight with regard to serially homologous stem cell development along the body axis. A comprehensive understanding of how the NB3-3 lineage, or any other serially homologous lineage, develops was missing. This is what makes our study both novel and needed. Without an analysis that both examines every segment and assays multiple cell biological processes, we would have missed key insights: that there is a ubiquitous type of temporal cohort, and that neurons within the ubiquitous temporal cohort are selectively refined post-mitotically (See General Statements for more details).
*I disagreed with their conclusion that failure to express Eve as a mechanism for controlling EL neuron numbers when Eve serves as the marker for these neurons. Are there any other strategy to assess the fates and functions of these cells beside relying solely on Eve expression? I am not familiar with the significance of Eve expression on the functions of these neurons. Is it possible to perform clonal analyses of NB3-3 mutant for Eve and see if these neurons adopt different functionalities/identities? *
*If NB3-3 in the SEZ continually generate GMCs based on the interpretation of clonal analyses and depicted in Fig. 2A, why is the percent of clones that are 1:0 virtually at or near 100% from division 6-11 shown in 2G? *
Admittedly, the ts-MARCM heat-shock-based lineage tracing experiments are inherently messy. This is part of the reason why we included the G-TRACE lineage tracing experiments in Figure 3. In Figure 3E, one can see that the number of Notch ON/A neurons in SEZ3 is equal to the number of ELs in that segment (Figure 1E). This is a second independent method that supports the assertion that in SEZ, NB3-3 stem cells continually generate GMCs. Given this independent observation, it leads us to believe that this question is most likely explained by technical issues inherent in ts-MARCM. These issues include but are not limited to: cell-type specific accessibility/success of heat-shock induced recombination; variably effective RNAi; and idiosyncrasies of the EL-GAL4 line used to detect recombination events. If the question is why the data is only reported for division 6-11, the answer is that the ts-MARCM dataset, which included SEZ clones only used later heat-shock time points (line from the paper "for the SEZ-containing dataset, inductions started at NB3-3's 5th division"). Along with this revision plan, we will include Supplemental Table 1, which was inadvertently omitted from the previous submission due to our error. This table shows all of the clonal data. We will include a section in the discussion to describe limitations in ts-MARCM.
The authors also indicate that NB3-3 in the abdomen directly generate Notch OFF/B cells that assume EL neuronal identity. In this scenario, shouldn't the percent of 1:0 clones be 100% in later divisions in Fig. 2G? Based on the number of clones in abdomen shown in Fig. 2E, I cannot seem to understand how the authors come to the percent of 1:0 clones shown in Fig. 2G
We agree that one might expect the 12th division to be 100% 1:0 clones in the abdomen. Unfortunately, we didn't sample that late in our dataset, and even when we sampled the inferred 11th division, we had a small sample size (Figure 2E). Other studies suggest that NB3-3 in the abdomen directly generates Notch OFF/B neurons (Baumgardt et al., 2014), which served as our starting point. We will revise the text to make this clearer. As you can see from Figure 3E, there is only one NB3-3 Notch ON/ A neuron produced in each abdominal segment in comparison to the number of NB3-3 Notch OFF/B/EL neurons (Figure 1E). According to two independent assessments, Figure 3 and Baumgardt et al., 2014, the data support the conclusion that NB3-3 in the abdomen directly generates Notch OFF/B cells that assume EL identity for all but one of their divisions. Again, we believe technical issues make the ts-MARCM dataset messy. We will include a section in the discussion to describe limitations in ts-MARCM.
*There are many potentially interesting questions related to this study that can significantly broaden the impact of this study. For example, are other NB lineages that also generate distinct temporal cohorts of EL neurons display similar proliferation patterns (type 1 division in SEZ, early termination of cell division in thoracic segments and type 0 division in abdomen)? *
*Why does NB3-3 in the thoracic segment become quiescence so much sooner than SEZ and abdominal segments? *
The authors' observations suggest that NB3-3 in SEZ and abdomen generate a similar number of EL neurons despite the difference in their division patterns (type 1 vs type 0). Are the mechanisms that promote EL neuron generate in NB3-3 in SEZ and abdomen the same? Anything else is known beside Notch OFF?
Minor commentsThe authors' writing style is highly unusual especially in the result section. There is an overwhelming large amount of background information in the result section but very thin description on their observations. The background information portion also includes previously published observations. Since the nature of this study is not hypothesis-driven, it is very confusing to read in many places and difficult to distinguish their original observations from previously published results and making. One easily achievable improvement is to insert relevant figure numbers into the text more often.
Thank you for this comment. It is invaluable. In the revision, we will expand the background into a more comprehensive introduction and present the results more clearly. We will certainly insert relevant figure numbers. In responding to the reviewer's comments above, we can see where our writing lacked clarity and will improve these areas. Thank you again.
Reviewer #1 (Significance (Required)):
The study by Vasudevan et al intends to address how serially homologous neural progenitors generate different numbers and types of neurons depending on their location along the body axis. Investigation of full repertoire of neurogenesis for these progenitors necessitates a precise ability to track the fates of both progenitors and their neuronal progeny making it extremely difficult in vertebrate paradigm. The authors used NB3-3 in the developing fly embryo as a model to investigate the full extent of the flexibility in neurogenesis from a single type of serially homologous stem cell. Previous work showed NB3-3 generates neurons including lateral interneurons that can be positively labeled by Even-skipped, but detailed characterization of the NB3-3 lineage mainly focused on 3 segments during embryogenesis. The authors defined the number of EL neurons in all segments of the central nervous system in early larvae after the completion of circuit formation and carried out clonal analyses to determine the proliferation pattern of NB3-3. They described the failure to express Eve in Notch OFF/B neurons as a new mechanism for controlling the number of EL neurons and PCD limits EL neurons in terminal segments.
Because this text is the same as the summary, please see our response to that section.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
In this manuscript, Vasudevan et al provide a detailed characterisation of the different numbers and temporal birthdates of Even-skipped Lateral (EL) neurons produced at in different segments from the same neuroblast, NB3-3. The work highlights the differences in EL neuronal generation across segments is achieved through a combination of different division patterns, failure to upregulate EL marker Eve and segment-specific program cell death. For neurons born within the same window and segment, the authors describe additional heterogeneity in their circuit formation. The work underscores the large diversity that the same neuroblast can generate across segments.
Thank you!
Major comments:
- Based on the ts-MARCM 1:0 clones representing 100% of the SEZ clones at any given inferred cell division, the authors conclude "NB3-3 neuroblasts generate proliferative daughter GMCs in the SEZ and thorax on most divisions". Figure 2G does not have any data for SEZ before inferred division 5, whereas there is data in other regions. The authors also state "In the SEZ and abdomen, ELs were labelled regardless of induction time." In reference to Fig 2F, which seems inaccurate given there are no SEZ clones before inferred division 5. There is no comment on this fact, which is surprising give their focus on temporal cohorts. The authors should explain this discrepancy, if known, or modify their statements to reflect the data.
- The temporal cohort (early-born vs late-born) identity is exclusively examined based on markers. Given the absence of SEZ clones from early NB3-3 divisions, a time course showing that the SEZ generate early-born Els or some other complementary method would be desirable.
Thank you for raising this point. We show early-born versus late-born identity using markers in Figure 5. We conducted the time-course experiment as suggested and can confirm that there are early-born ELs in the SEZ at stage 13. We will include a new Supplemental Figure that includes a time course of EL number at stages 11, 13, 15, and 17 for segments SEZ3 to Te2 in the revision. See figure below.
- The authors repeatedly refer to their work as showing how a stem cell type can have "flexibility". Flexibility would imply that NB3-3 from one segment could adopt a different behaviour (different division pattern, or cell death or connectivity) if it were placed in a different segment. This is not what is being shown. In my opinion, "heterogeneity" of the same neuroblast across different segments would be more appropriate.
Minor comments:
- Figure 2A depicts a combination of known data and conclusions from their own (mainly SEZ). The authors might consider editing the figure to highlight what is new. A possibility would be for figure A to be a diagram of the experimental design and their summary division pattern to be shown after the new data instead of being panel A.
Thank you for this suggestion. We will make the suggested change.
- The authors state that they combined published ts-MARCM with their new one, which differed in a number ways that they list, but they don't specify which limitations are associated with the published vs new dataset. Could the authors please clarify?
We now include Supplemental Table 1, which shows the complete combined datasets. In the first dataset, experiments a-h, the CNS was imaged at high resolution, but in a smaller region. The limitation is that the SEZ is missing. In the second dataset, i-k, inductions started at NB3-3's 5th division. The limitation is that we fail to sample early time points. This was a strategic decision. There were two possible scenarios: (1) in the SEZ, NB3-3 divided early, made GMCs, but both daughters expressed Eve. (2) in the SEZ, NB3-3 divided for the entirety of the embryonic neurogenesis, making GMCs, with only the Notch OFF daughters expressing Eve-our data support (2). Only late heat shocks were needed to distinguish between these possibilities. As these experiments are labor-intensive, we focused our efforts on the later time points. We will make this clearer in our revised text.
- The title refers exclusively to "temporal cohorts", which in the manuscript are defined quite narrowly and do not seem to apply to all segments.
- Several cited references are missing from the Reference list at the end. Could the authors please double check this? (e.g. Matsushita, 1997; Sweeney et al., 2018)
- Legend for figure 2 is a bit confusing, there is a "(A)" within the legend for (D), which indicates that segments A1-A7 are shown (this seems inaccurate, as it only goes to A6).
Thank you, we will remedy this!
Reviewer #3 (Significance (Required)):
This study provides a comprehensive analysis of different cell biological scenarios for a neuroblast to generate distinct progeny across repeating axial units. The strength is the detailed and systematic approach across segments and possible scenarios: different division patterns, cell death, molecular marker expression. While it focuses on one specific neuroblast of the ventral nerve cord of Drosophila, the authors have done extensive work to place their findings and interpretation in the context of other cell types and across model organisms both in the introduction and discussion. This makes the work of interest for developmental biologists in general, neurodevelopment research in particular and those interested in circuit assembly, beyond their specialised community. This point of view comes from someone working in vertebrate CNS development.
Thank you!
Reviewer #4 (Evidence, reproducibility and clarity (Required)):
Summary
This manuscript addresses the question of how the number of neurons produced by each progenitor in the nervous system is determined. To address this question the authors use the Drosophila embryo model. They focus on a single type of neural stem cell (neuroblast), with homologues in each hemisegment along the anterior-posterior axis.
Using a combination of clonal labelling, antibody stainings, and blockade of programmed cell death, they provide a detailed description of segment-specific differences in the proliferation patterns of these neuroblasts, as well as in the fate and survival of their neuronal progeny.
Furthermore, by employing trans-synaptic labelling, they demonstrate that neurons derived from the same progenitor type receive distinct patterns of synaptic input depending on their segmental origin, in part due to their temporal window origin.
Overall this work shows that different mechanisms contribute to the final number and identity of the neuronal progeny arising from a single progenitor, even within homologous progenitors along the anterior posterior body axis.
Thank you!
Major Comments
I would suggest adding line numbers to the text for future submissions, this massively helps providing comments.
Thank you for this comment. We will definitely add line numbers to the revised manuscript. We also thank you for providing comments despite this oversight on our part. We appreciate your time, and did not mean to make extra work.
*The authors propose that all neuroblasts produce the same type of temporal cohort (early born) and that, by changing the pattern of cell division, different temporal cohorts can be added. The way this this presented in the abstract sounds like an obvious thing, what would be the alternative scenario/s? *
Thank you for raising the point that the abstract should be updated. We have included a revised abstract. The things that are obvious are: (1) changing a neuroblast's division pattern will change the number of neurons produced, and (2) if you have late-born neurons, the stem cell must at some point, have made early-born neurons. However, within those bounds is an extremely large parameter space. Each stem cell can choose to divide or not, and it can also choose to produce a proliferative daughter or not. The stem cell must navigate these choices at every division. The field had two models for what a stem cell might do - a "random production" model and a "unitary production" model. Our data support a third "multimodal production" model, which could not have been predicted based on prior literature or data.
We had raised these points in the discussion as follows-
"Under a null model, the durations and types of proliferation would vary stochastically across segments, resulting in a continuous and unstructured distribution of neuron numbers (Llorca et al., 2019). In a unitary production model, based on the vertebrate neocortex, there is a fixed neurogenic output of ~8-9 neurons per progenitor (Gao et al., 2014). However, our data support a third model, a multimodal production model. In a multimodal model, serially homologous neuroblasts generate different numbers of neurons depending on the segment."
We will now update the text to address this concern.
Here it's the late born neurons that lack in thoracic segments because of early NB quiescence, but it cannot be excluded that different neuroblast types adopt a different strategy.
I found the ts-MARCM results confusing for 2 reasons:
1- It's not clear to me why there are so many single cell clones in div 3 and 4 in abdominal segments. This is not compatible with the division model depicted for abdominal segments, unless GMCs are produced in those division window and the MARCM hits the GMC, as also mentioned in the legend for G. This aspect is important because, either the previous model by Baumgardt et al. - please correct cit. currently Gunnar et al. 2026 - is wrong, or something strange happens in this experiment, or the relative temporal order is incorrect.
Thank you for raising this point. Having multiple single-cell (i.e., 1:0) clones in divisions 3 and 4 is not precisely what would be predicted by the model in Figure 2C. In part because heat-shock-based recombination methods in fly are stochastic and inherently "messy", we also conducted a second set of lineage tracing experiments, as shown in Figure 3, using G-TRACE. Figure 3E shows one Notch ON/A neuron in each abdominal segment, suggesting there is only one GMC present during lineage progression. But Figure 3E's result does not localize the GMC to any particular division. One possibility is that the GMC is generated once, but randomly throughout lineage progression. This possibility is consistent with the idea that the relative temporal order is incorrect and suggests that Baumgardt is erroneous. However, the Baumgardt data are strong, so we do not favor this idea. A second possibility, which we favor, is that something strange happened in this experiment. Here is how we envision the strange occurrence: heterogeneity in the EL driver. Ts-MARCM's recombination timing dictates the upper limit for the number of cells within a clone. However, recombination is detected by GAL4. So, if the GAL4 driver for some reason detects fewer cells than one expects, then one would see unusually small clones as is the case in question. To detect Ts-MARCM recombination in Figure 2, we used the EL-GAL4 driver. The EL-GAL4 driver is an enhancer fragment, ~400KB, meaning that it does not capture the full regulatory context of the eve locus. In our experience (e.g., Manning et al., 2012), drivers using small enhancers tend to give highly-specific, but somewhat variable expression, and this is the case for EL-GAL4 in our experience. We will update the discussion to discuss the ts-MARCM dataset and its limitations. And, we will correct the citation to Baumgardt et al., 2014, not Gunnar. Thank you!
2- In segments other than abdomen, it is quite rare to hit proper clones, it appears that only GMCs are hit by recombination, with very few exceptions. Could the author please provide an explanation for this or at least mention this aspect?
It is also unclear whether in F the graph includes all types of clones (including 1:0 clones). This is important, because the timing of division for NBs and GMCs is different, and inclusion of 1:0 might lead to a wrong estimate of the NB proliferation window (longer than it actually is because GMCs divide for longer). This is particularly important for the SEZ, where most clones in normalised division 10 and 11 are with ratio 1:0, thus compatible with both terminal division as well as GMC division.
To obtain an estimate of the timing of division, the authors normalise clone size to the size of the bigger clone in the abdomen. What happened to those samples where no abdominal clones were hit? Were they simply excluded from the analysis?
From the analysis in Figure 2, we excluded the clones that were SEZ, thorax, or terminus only. They were rare. They are shown in Supplemental Table 1, which will now be added in our revision plan.
It is proposed that in the thorax late temporal cohort neurons are not produced, yet the ts-MARCM experiment detects some 1:0 clones. What is the fate of these cells? Are they all derived from GMC division and therefore decoupled from the temporal identity window? Or is this a re-activation of division?
Figure 2F shows at the inferred 11th NB3-3 division, 100% of thoracic clones are of the 1:0 type. This is an n=1 observation (Supplemental Table 1, row f-Jan20-2). When we look at the morphology of this thoracic EL, we can see that it is a fully differentiated neuron that crosses the midline and ascends to the CNS, which is similar to EL morphologies in A1, so we don't think it's a whole new cell type. We have no way of determining whether this neuron was derived from a GMC division. It is also possible that this is an infrequent event or a technical anomaly. To address the question of reactivation of the thoracic NB3-3 division, we plan to include a Supplemental Figure of EL number over developmental time (stages 11, 13, 15, 17) for segments SEZ3 to Te2. This is the same data that we mentioned to Reviewer 3. This will reveal the extent to which the thorax produces late-born ELs.
*"in A1, a majority of segments had one Notch OFF/B neuron that failed to label with Eve" does "the majority" in this sentence mean that there were cases where all B neurons were labelled with Eve? If yes, where would this stochasticity come from? *
Additionally, there is no evidence that it's the first born NotchOFF neuron in A1 that does not express Eve. The authors should clarify where this speculation comes from.
When discussing trends shared with other phyla:
A- "In the mammalian spinal cord, more neurons are present in regions that control limbs (Francius et al., 2013). Analogously, EL numbers do not smoothly taper from anterior to posterior; instead, the largest number of ELs is found in two non-adjacent regions, SEZ and the abdomen." It's unclear what is the link between the figure in the mammalian spinal cord and the Drosophila embryo. The embryo doesn't even have limbs and the number of neurons measured here refer only to a single lineage, while there could be (and in fact there are) lineage-to-lineage differences that could depict a different scenario.
Thank you for this comment. We will rewrite this sentence, "in the mammalian spinal cord, more neurons are present in regions that control limbs (Francius et al., 2013)" to more accurately reflect the data in the Francius paper, and make the parallel more explicit. We will say "the size of columns of V3, V1, V2a, V2b, and V0v neurons differ at brachial compared to lumbar levels in the developing spinal cord." This removes the confusion about limbs and somewhat mitigates the concern about lineage-to-lineage differences, at least from the perspective of the spinal cord.
B- The parallelism between V1 mouse neurons and EL Drosophila neurons is also unclear to me. The similarity in fold change across segments could be a pure coincidence and, from what I understand, the two cell types are not functionally linked.
Thank you for this comment. We believe this is the sentence in question (sorry about no line numbers). "(3) In the mouse spinal cord, ~10-fold differences in molecular subtypes for V1 neurons (Sweeney et al., 2018). In *Drosophila*, NB3-3 neuroblasts show differences in EL number, depending on region, with similar fold changes, suggesting this trait is shared across phyla." The emphasis was intended to be on the fold-changes, not cell types. Coincidence or not, it is parallel. We will update the sentence to say "(3) In the mouse spinal cord, ~10-fold differences in molecular subtypes for V1 neurons (Sweeney et al., 2018). Although V1 neurons are not direct homologs of EL neurons, the number also varies ~10-fold depending on the region. One possibility is that this trait is shared across phyla." And, we will remove the final part of the paragraph, which distracts from the point "Thus, for this study and future research, NB3-3 development now offers a uniquely tractable, detailed, and comprehensive model for studying how stem cells flexibly produce neurons."
Minor comments:
I found the manuscript somewhat difficult to follow, even though I am familiar with both the model and the topic. For non-specialist readers, I expect it will be even more challenging. The presentation of the results often feels fragmented, at times resembling a sequence of brief statements rather than a continuous narrative. I would encourage the authors to provide more synthesis and interpretation, for example by summarising key findings, rather than listing in detail the number of neurons labelled in each segment for every experiment. This would make the results more accessible and easier to digest.
From the way the MS is written it's not clear from the beginning that the work focuses exclusively on embryonic-born neurons. Since in Drosophila neuronal stem cells undergo two rounds of neurogenesis, one in the embryo and one in the larva, this omission could lead to confusion.
Thank you for this comment. We will mention this in the abstract, introduction and discussion.
In the abstract, what would be the other temporal cohorts generated in specific regions? (ref to: "In specific regions, NB3-3 neuroblasts produce additional types of temporal cohorts, including but not limited to the late-born EL temporal cohort.")
In this manuscript, we use lineage tracing to identify four types of temporal cohorts- early-born Notch ON, early-born Notch OFF, late-born Notch ON, and late-born Notch OFF. This is now reflected in the revised abstract. ELs are early-born Notch OFF and/or late-born Notch OFF.
This sentence in the introduction is inaccurate: "The Drosophila CNS is
organized into an anterior hindbrain-like subesophageal zone (SEZ) and a posterior spinal cord-like nerve cord". The anterior hindbrain-like portion of the CNS is in fact the supraesophageal ganglion (or cerebrum), while the SEZ is a posterior-like region.
Thank you. We will change this sentence to: "The *Drosophila* CNS is
organized into a hindbrain-like subesophageal zone (SEZ) and a spinal cord-like nerve cord".
Fig 1E: the encoding of the significance is not immediately clear. In the legend the 4 stars could also be arranged in the same way for clarity.
Fig 2E legend: it is mentioned that B corresponds to a 1:4 clone, however the MARCM example is shown for C and it's a 1:5.
Thank you. We will fix this.
The occurrence of "undifferentiated" neurons in Th segments is in less than 10% of the clones, I wonder if this a stochastic or deterministic event and to what extent small cell bodies could just be the consequence of local differences in tissue architecture.
Fig 2I: it's unclear what the purple means (I suppose it might be Eve expression) and why in J there should be one purple cell not labelled by the ts-MARCM when this is not present in H and I.
Purple is Eve. We will add labels for stains used in H and I, and remove the extra purple cell from the illustration in J.
"When synapses do occur, they are numerically similar from segment to segment". It's unclear where the evidence for this statement comes from, please clarify or remove the sentence.
We calibrated our trans-Tango data against available connectomic data using segment A1 as a reference. We learned that the trans-tango method only identifies strongly (>15 synapses) connected neurons.
"First, we calibrated trans-Tango for use in larval Drosophila, focusing on segment A1, where connectome data are available (Wang et al., 2022). In the connectome, of the five early-born ELs in A1, three are strongly connected to CHOs (>15 synapses), two are weakly connected (15 synapses) connected to somatosensory neurons."
We will modify this sentence to say "when synapses do occur they are of similar strengths from segment to segment"
"In SEZ2, NB3-3 divides 10 times (Figure 2F)". Figure 2F does not support this statement and Figure 7 shows 12 divisions. Possibly SEZ2 and 3 have been inverted in this statement, please clarify.
Thank you for pointing this out. We will correct it!
**Referees cross-commenting**
I agree with most of the comments/suggestions provided by the other two reviewers.
In particular:
I agree with reviewer #1's comment about failure to express Eve being a mechanism for controlling neurons number, as this is a circular argument.
I agree with reviewer #2's concern about the use of the word "flexibility"; "heterogeneity" would be a more appropriate term, as I would associate the word "flexibility" to the ability of a single neuroblast in a single segment to produce neurons with different fates under, for example, unusual growth conditions. Here no genetic/epigenetic manipulations were performed to address flexibility and the observed (stereotypical) differences result from axial patterning.
*As a note, Reviewer #1 asks about other temporal cohorts of EL neurons produced by other lineages, but these neurons are specifically generated from NB3-3. *
To generalise the observations reported in this study, the authors would need to focus on other molecularly defined temporal cohorts or, more generally, on other lineages, which, however, are likely to adopt different combinations of mecahnisms to tune progeny number across segments.
Reviewer #4 (Significance (Required)):
In Drosophila melanogaster, the relationship between neural progenitors and their neuronal progeny has been studied in great detail. This work has provided a comprehensive description of the number of progenitors present in each embryonic segment, their molecular identities, the number of neurons they produce, and the temporal transcriptional cascades that couple progenitor temporal identity to neuronal fate.
This work adds to the existing knowledge a detailed characterisation of intersegmental differences in the pattern of proliferation of a single type of neuronal progenitor as well as in post-divisional fate depending on anterior-posterior position in the body axis (i.e. programmed cell death and Notch signalling activation). This is a first step towards understanding the cellular and molecular mechanisms underlying such differences, but it's not disclosing them.
We have disclosed the cellular mechanisms- stem cell division duration and type, neural cell death, identity gene expression, and differentiation state -unless something else is envisaged by this comment. The molecular mechanisms are beyond the scope of this paper.
That homologous neuroblasts can generate variable numbers of progeny neurons depending on their segmental position has been established previously. What this manuscript adds is the demonstration that these differences arise through a combination of altered division patterns and differential programmed cell death, thereby revealing a more complex and less predictable scenario than could have been anticipated from existing knowledge in other contexts. The advance provided by this study is therefore incremental, refining rather than overturning our understanding of how segmental diversity in neuroblast lineages is achieved.
The key conceptual advances provided by this study are described in the General Statements section above. We don't overturn, but we advance the field.
By touching on the general question of how progenitors generate diversity, this work could be of broad interest to developmental neuroscientists beyond the fly field. However, the way it is currently written does not make it very accessible to non-specialists.
Thank you for this comment. We will endeavor to make it more accessible in the revised manuscript. Reviewer 3, an expert in vertebrate neurobiology, agreed that our work was of broad interest.
My expertise: Drosophila neurodevelopment, nerve cord, cell types specification
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With this Revision Plan, we submit a revised abstract, and a supplemental table 1. We plan to address every point raised by the reviewers.
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Summary
This manuscript addresses the question of how the number of neurons produced by each progenitor in the nervous system is determined. To address this question the authors use the Drosophila embryo model. They focus on a single type of neural stem cell (neuroblast), with homologues in each hemisegment along the anterior-posterior axis.
Using a combination of clonal labelling, antibody stainings, and blockade of programmed cell death, they provide a detailed description of segment-specific differences in the proliferation patterns of these neuroblasts, as well as in the fate and survival of their neuronal progeny. Furthermore, by employing trans-synaptic labelling, they demonstrate that neurons derived from the same progenitor type receive distinct patterns of synaptic input depending on their segmental origin, in part due to their temporal window origin. Overall this work shows that different mechanisms contribute to the final number and identity of the neuronal progeny arising from a single progenitor, even within homologous progenitors along the anterior posterior body axis.
Major Comments
I would suggest adding line numbers to the text for future submissions, this massively helps providing comments.
The authors propose that all neuroblasts produce the same type of temporal cohort (early born) and that, by changing the pattern of cell division, different temporal cohorts can be added. The way this this presented in the abstract sounds like an obvious thing, what would be the alternative scenario/s? Here it's the late born neurons that lack in thoracic segments because of early NB quiescence, but it cannot be excluded that different neuroblast types adopt a different strategy.
I found the ts-MARCM results confusing for 2 reasons:
To obtain an estimate of the timing of division, the authors normalise clone size to the size of the bigger clone in the abdomen. What happened to those samples where no abdominal clones were hit? Were they simply excluded from the analysis?
It is proposed that in the thorax late temporal cohort neurons are not produced, yet the ts-MARCM experiment detects some 1:0 clones. What is the fate of these cells? Are they all derived from GMC division and therefore decoupled from the temporal identity window? Or is this a re-activation of division?
"in A1, a majority of segments had one Notch OFF/B neuron that failed to label with Eve" does "the majority" in this sentence mean that there were cases where all B neurons were labelled with Eve? If yes, where would this stochasticity come from? Additionally, there is no evidence that it's the first born NotchOFF neuron in A1 that does not express Eve. The authors should clarify where this speculation comes from. When discussing trends shared with other phyla:
A- "In the mammalian spinal cord, more neurons are present in regions that control limbs (Francius et al., 2013). Analogously, EL numbers do not smoothly taper from anterior to posterior; instead, the largest number of ELs is found in two non-adjacent regions, SEZ and the abdomen." It's unclear what is the link between the figure in the mammalian spinal cord and the Drosophila embryo. The embryo doesn't even have limbs and the number of neurons measured here refer only to a single lineage, while there could be (and in fact there are) lineage-to-lineage differences that could depict a different scenario.
B- The parallelism between V1 mouse neurons and EL Drosophila neurons is also unclear to me. The similarity in fold change across segments could be a pure coincidence and, from what I understand, the two cell types are not functionally linked.
Minor comments:
I found the manuscript somewhat difficult to follow, even though I am familiar with both the model and the topic. For non-specialist readers, I expect it will be even more challenging. The presentation of the results often feels fragmented, at times resembling a sequence of brief statements rather than a continuous narrative. I would encourage the authors to provide more synthesis and interpretation, for example by summarising key findings, rather than listing in detail the number of neurons labelled in each segment for every experiment. This would make the results more accessible and easier to digest.
From the way the MS is written it's not clear from the beginning that the work focuses exclusively on embryonic-born neurons. Since in Drosophila neuronal stem cells undergo two rounds of neurogenesis, one in the embryo and one in the larva, this omission could lead to confusion.
In the abstract, what would be the other temporal cohorts generated in specific regions? (ref to: "In specific regions, NB3-3 neuroblasts produce additional types of temporal cohorts, including but not limited to the late-born EL temporal cohort.")
This sentence in the introduction is inaccurate: "The Drosophila CNS is organized into an anterior hindbrain-like subesophageal zone (SEZ) and a posterior spinal cord-like nerve cord". The anterior hindbrain-like portion of the CNS is in fact the supraesophageal ganglion (or cerebrum), while the SEZ is a posterior-like region.
Fig 1E: the encoding of the significance is not immediately clear. In the legend the 4 stars could also be arranged in the same way for clarity.
Fig 2E legend: it is mentioned that B corresponds to a 1:4 clone, however the MARCM example is shown for C and it's a 1:5.
The occurrence of "undifferentiated" neurons in Th segments is in less than 10% of the clones, I wonder if this a stochastic or deterministic event and to what extent small cell bodies could just be the consequence of local differences in tissue architecture.
Fig 2I: it's unclear what the purple means (I suppose it might be Eve expression) and why in J there should be one purple cell not labelled by the ts-MARCM when this is not present in H and I.
"When synapses do occur, they are numerically similar from segment to segment". It's unclear where the evidence for this statement comes from, please clarify or remove the sentence.
"In SEZ2, NB3-3 divides 10 times (Figure 2F)". Figure 2F does not support this statement and Figure 7 shows 12 divisions. Possibly SEZ2 and 3 have been inverted in this statement, please clarify.
Referees cross-commenting
I agree with most of the comments/suggestions provided by the other two reviewers. In particular: I agree with reviewer #1's comment about failure to express Eve being a mechanism for controlling neurons number, as this is a circular argument. I agree with reviewer #2's concern about the use of the word "flexibility"; "heterogeneity" would be a more appropriate term, as I would associate the word "flexibility" to the ability of a single neuroblast in a single segment to produce neurons with different fates under, for example, unusual growth conditions. Here no genetic/epigenetic manipulations were performed to address flexibility and the observed (stereotypical) differences result from axial patterning. As a note, Reviewer #1 asks about other temporal cohorts of EL neurons produced by other lineages, but these neurons are specifically generated from NB3-3. To generalise the observations reported in this study, the authors would need to focus on other molecularly defined temporal cohorts or, more generally, on other lineages, which, however, are likely to adopt different combinations of mecahnisms to tune progeny number across segments.
In Drosophila melanogaster, the relationship between neural progenitors and their neuronal progeny has been studied in great detail. This work has provided a comprehensive description of the number of progenitors present in each embryonic segment, their molecular identities, the number of neurons they produce, and the temporal transcriptional cascades that couple progenitor temporal identity to neuronal fate. This work adds to the existing knowledge a detailed characterisation of intersegmental differences in the pattern of proliferation of a single type of neuronal progenitor as well as in post-divisional fate depending on anterior-posterior position in the body axis (i.e. programmed cell death and Notch signalling activation). This is a first step towards understanding the cellular and molecular mechanisms underlying such differences, but it's not disclosing them.
That homologous neuroblasts can generate variable numbers of progeny neurons depending on their segmental position has been established previously. What this manuscript adds is the demonstration that these differences arise through a combination of altered division patterns and differential programmed cell death, thereby revealing a more complex and less predictable scenario than could have been anticipated from existing knowledge in other contexts. The advance provided by this study is therefore incremental, refining rather than overturning our understanding of how segmental diversity in neuroblast lineages is achieved. By touching on the general question of how progenitors generate diversity, this work could be of broad interest to developmental neuroscientists beyond the fly field. However, the way it is currently written does not make it very accessible to non-specialists.
My expertise: Drosophila neurodevelopment, nerve cord, cell types specification
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In this manuscript, Vasudevan et al provide a detailed characterisation of the different numbers and temporal birthdates of Even-skipped Lateral (EL) neurons produced at in different segments from the same neuroblast, NB3-3. The work highlights the differences in EL neuronal generation across segments is achieved through a combination of different division patterns, failure to upregulate EL marker Eve and segment-specific program cell death. For neurons born within the same window and segment, the authors describe additional heterogeneity in their circuit formation. The work underscores the large diversity that the same neuroblast can generate across segments.
Major comments:
Minor comments:
This study provides a comprehensive analysis of different cell biological scenarios for a neuroblast to generate distinct progeny across repeating axial units. The strength is the detailed and systematic approach across segments and possible scenarios: different division patterns, cell death, molecular marker expression. While it focuses on one specific neuroblast of the ventral nerve cord of Drosophila, the authors have done extensive work to place their findings and interpretation in the context of other cell types and across model organisms both in the introduction and discussion. This makes the work of interest for developmental biologists in general, neurodevelopment research in particular and those interested in circuit assembly, beyond their specialised community. This point of view comes from someone working in vertebrate CNS development.
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Summary: The study by Vasudevan et al intends to address how serially homologous neural progenitors generate different numbers and types of neurons depending on their location along the body axis. Investigation of full repertoire of neurogenesis for these progenitors necessitates a precise ability to track the fates of both progenitors and their neuronal progeny making it extremely difficult in vertebrate paradigm. The authors used NB3-3 in the developing fly embryo as a model to investigate the full extent of the flexibility in neurogenesis from a single type of serially homologous stem cell. Previous work showed NB3-3 generates neurons including lateral interneurons that can be positively labeled by Even-skipped, but detailed characterization of the NB3-3 lineage mainly focused on 3 segments during embryogenesis. The authors defined the number of EL neurons in all segments of the central nervous system in early larvae after the completion of circuit formation and carried out clonal analyses to determine the proliferation pattern of NB3-3. They described the failure to express Eve in Notch OFF/B neurons as a new mechanism for controlling the number of EL neurons and PCD limits EL neurons in terminal segments.
Major comments: The authors performed careful analyses of the NB3-3 lineage using EL neurons. My main concerns are limited applicability of their findings and lack of mechanisms as how NB3-3 generate various numbers of EL neurons. Their findings are exclusively relevant to the NB3-3 lineage despite their effort in highlighting that other NB lineages also generate temporal cohorts of EL neurons. I disagreed with their conclusion that failure to express Eve as a mechanism for controlling EL neuron numbers when Eve serves as the marker for these neurons. Are there any other strategy to assess the fates and functions of these cells beside relying solely on Eve expression? I am not familiar with the significance of Eve expression on the functions of these neurons. Is it possible to perform clonal analyses of NB3-3 mutant for Eve and see if these neurons adopt different functionalities/identities? If NB3-3 in the SEZ continually generate GMCs based on the interpretation of clonal analyses and depicted in Fig. 2A, why is the percent of clones that are 1:0 virtually at or near 100% from division 6-11 shown in 2G? The authors also indicate that NB3-3 in the abdomen directly generate Notch OFF/B cells that assume EL neuronal identity. In this scenario, shouldn't the percent of 1:0 clones be 100% in later divisions in Fig. 2G? Based on the number of clones in abdomen shown in Fig. 2E, I cannot seem to understand how the authors come to the percent of 1:0 clones shown in Fig. 2G
There are many potentially interesting questions related to this study that can significantly broaden the impact of this study. For example, are other NB lineages that also generate distinct temporal cohorts of EL neurons display similar proliferation patterns (type 1 division in SEZ, early termination of cell division in thoracic segments and type 0 division in abdomen)? Why does NB3-3 in the thoracic segment become quiescence so much sooner than SEZ and abdominal segments? The authors' observations suggest that NB3-3 in SEZ and abdomen generate a similar number of EL neurons despite the difference in their division patterns (type 1 vs type 0). Are the mechanisms that promote EL neuron generate in NB3-3 in SEZ and abdomen the same? Anything else is known beside Notch OFF?
Minor comments:
The authors' writing style is highly unusual especially in the result section. There is an overwhelming large amount of background information in the result section but very thin description on their observations. The background information portion also includes previously published observations. Since the nature of this study is not hypothesis-driven, it is very confusing to read in many places and difficult to distinguish their original observations from previously published results and making. One easily achievable improvement is to insert relevant figure numbers into the text more often.
The study by Vasudevan et al intends to address how serially homologous neural progenitors generate different numbers and types of neurons depending on their location along the body axis. Investigation of full repertoire of neurogenesis for these progenitors necessitates a precise ability to track the fates of both progenitors and their neuronal progeny making it extremely difficult in vertebrate paradigm. The authors used NB3-3 in the developing fly embryo as a model to investigate the full extent of the flexibility in neurogenesis from a single type of serially homologous stem cell. Previous work showed NB3-3 generates neurons including lateral interneurons that can be positively labeled by Even-skipped, but detailed characterization of the NB3-3 lineage mainly focused on 3 segments during embryogenesis. The authors defined the number of EL neurons in all segments of the central nervous system in early larvae after the completion of circuit formation and carried out clonal analyses to determine the proliferation pattern of NB3-3. They described the failure to express Eve in Notch OFF/B neurons as a new mechanism for controlling the number of EL neurons and PCD limits EL neurons in terminal segments.
The word “way” is the Greek word hodos. It forms, for example, the word “exodus” which means “the way out.” The word hodos means “a path, road, or journey from one place to another, a course at sea.”
What is the source for this? The word "way" forms the word "exodus"?
Oh, I found it. Exodus is from the Greek word ἔξοδος (éxodos), which means "a going out" or "departure". It is a compound word from ἐξ (ex), meaning "out of," and ὁδός (hodos)
Notice the three uses of "the" (Greek definite article "he"), which is crucial to comprehend. Jesus is saying with each use of "the" that He is the definitive way, the definitive truth and the definitive life. The clear implication is that there is absolutely NO OTHER way, truth or life! Jesus Christ not only states the truth; he is the truth.
Interesting point about paying attention to the "the". Normally we skip over "the". But here, "the" has sigficiant meaning.
Table of Contents
You can insert a TOC using the Reference Tab in MS Word.
Emailed them at this address in 9/2025 and got no response. Emailed again with no response in 10/2025. Called and was given yet another email address. Not sure why businesses don't update their emails on their websites anymore. Phone meetings are dumb.
"playful actions are not directed to something else." But it is a requisite of virtue that the agent in choosing should "direct his action to something else,"
I am a bit confused on how to interpret this. From looking at the link, the "Philosopher" he refers to is Plato, and the quote I am guessing, from the citations, is from Plato's ethics. Plato lists several virtues: courage, moderation, piety, and justice (Scavone 2023). I'd like to read the original by Plato before making real conclusions, but I believe the author's argument is appealing to both the virtues of moderation and piety. We've established already that among the differing medieval attitudes around games, one of the conclusions was moderation was key, such as this passage selected from the textbook, which was originally by John Salisbury, "'There are, however, times when, viewed from a certain aspect, games of chance are permissible. For example, if without evil consequences they alleviate the strain of heavy responsibilities and if without harming character they introduce an agreeable period of relaxation. Liberty to do as one pleases is justified if moderation controls the act'" (Milliman, 587), and so it's easy to see how, say, dice games would contradict Plato's virtue of moderation from a more severe perspective, since they can become addictive and make a gambler of a person. There is also a contradiction to the virtue of piety that the author may be appealing to, that since a person should "direct his action to something else" he means, potentially, that games distract a person from both their other responsibilities (both religion and justice if you were to look at it under the lens of Plato's virtues) and from the worship of God, not because a person should be spending every second of their time on these things, but because they have the capacity to steer a person the wrong way and tempt them away from keeping to the virtues.
I've left a link to the article I looked at here, it is by Daniel C. Scavone.