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Record W2081967523 · doi:10.4061/2011/686570

The Number of Grafted Fragments Affects the Outcome of Testis Tissue Xenografting from Piglets into Recipient Mice

2010· article· en· W2081967523 on OpenAlex
Sepideh Abbasi, Ali Honaramooz

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueVeterinary Medicine International · 2010
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaSaskatchewan Health Research FoundationUniversity of Saskatchewan
KeywordsAndrologyTestosterone (patch)SpermatogenesisMedicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

To optimize the procedure for testis tissue xenografting, we grafted 2, 4, 8, or 16 small fragments of immature porcine testis tissue under the back skin of immunodeficient castrated mice (n = 10 mice/group). At 8 months post grafting, the graft recovery rate did not differ between groups; however, not only the total but also the average graft weights were higher (by approximately 12-fold and approximately 2.5-fold, resp.) in mice receiving 16 fragments than those receiving 2 fragments (P < .05). The recipient mice with 16 fragments had the largest vesicular glands (indicators of testosterone release by the grafts) compared with those with 2 fragments (P = .007). The grafts in the group of 16 fragments also had more (P < .05) percentage of tubules with round spermatids than those of the group of mice receiving 2 fragments. Therefore, recipient mice can be grafted with at least 16 testis tissue fragments for optimal results.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.027
GPT teacher head0.346
Teacher spread0.319 · 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