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Record W2805051878 · doi:10.1038/s41598-018-25468-8

Multiple aspects of male germ cell development and interactions with Sertoli cells require inositol hexakisphosphate kinase-1

2018· article· en· W2805051878 on OpenAlexfundno aff
Chenglai Fu, Tomás Rojas, Alfred C. Chin, Weiwei Cheng, Isaac A. Bernstein, Lauren Albacarys, William W. Wright, Solomon H. Snyder

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsnot available
FundersNational Institute of Mental HealthUniversity of British ColumbiaJohns Hopkins Bloomberg School of Public HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseU.S. Public Health ServiceUniversity of Illinois at Urbana-ChampaignJohns Hopkins University
KeywordsSertoli cellGerm cellCell biologyBiologyEpididymisSpermBlood–testis barrierInositolSpermatogenesisGermEndocrinologyGeneticsGeneReceptor

Abstract

fetched live from OpenAlex

Inositol hexakisphosphate kinase-1 (IP6K1) is required for male fertility, but the underlying mechanisms have been elusive. Here, we report that IP6K1 is required for multiple aspects of male germ cell development. This development requires selective interactions between germ cells and Sertoli cells, namely apical ectoplasmic specialization. Spermiation (sperm release) requires tubulobulbar complexes. We found that the apical ectoplasmic specialization and tubulobulbar complexes were poorly formed or disrupted in IP6K1 KOs. Deletion of IP6K1 elicited several aberrations, including: 1, sloughing off of round germ cells; 2, disorientation and malformation of elongating/elongated spermatids; 3, degeneration of acrosomes; 4, defects in germ-Sertoli cell interactions and 5, failure of spermiation. Eventually the sperm cells were not released but phagocytosed by Sertoli cells leading to an absence of sperm in the epididymis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.239
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2018
Admission routes1
Has abstractyes

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