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Record W4313238711 · doi:10.3390/ani13010128

Long-Term In Vitro Maintenance of Piglet Testicular Tissue: Effects of Tissue Fragment Size, Preparation Method, and Serum Source

2022· article· en· W4313238711 on OpenAlexafffund
Fahar Ibtisham, Tat-Chuan Cham, Mohammad Amin Fayaz, Ali Honaramooz

Bibliographic record

VenueAnimals · 2022
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaServierUniversity of Saskatchewan
KeywordsGonocyteAndrologyBiologyIn vitroFetusInternal medicineEndocrinologySpermatogenesisBiochemistryPregnancyMedicineSertoli cell

Abstract

fetched live from OpenAlex

Long-term culture of testicular tissue has important applications, including the preservation of fertility potential of prepubertal boys undergoing gonadotoxic cancer treatment. This study was designed to define optimal conditions for the long-term culture of neonatal porcine testicular tissue as an animal model for preadolescent individuals. Testes from 1 wk old donor piglets were used to examine the effects of tissue fragment size (~2, 4, 6, or 8 mg), preparation method (intact, semi-digested, or physically dispersed fragments), and serum source in the media (fetal bovine serum—FBS—or knockout serum replacement—KSR). Testicular fragments were examined weekly for 4 weeks for tissue integrity, seminiferous cord density and morphology, and gonocyte counts. Testicular tissue integrity was dependent on fragment size and preparation method, where the smallest size (2 mg, p < 0.05) and intact preparation method were advantageous (p < 0.05). Seminiferous cord density decreased over the culture period (p < 0.05). Although the relative number of gonocytes decreased over time for all sizes and methods (p < 0.01), smaller intact fragments (2 and 4 mg) had greater numbers of gonocytes (p < 0.05). Our findings suggest that intact or physically dispersed testicular fragments of the smallest size (2 mg) cultured in KSR-supplemented media could be effectively maintained in vitro for the duration of 4 weeks.

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)0.001
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 score0.338
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.008
GPT teacher head0.286
Teacher spread0.278 · 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

Citations12
Published2022
Admission routes2
Has abstractyes

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