PSX-9 Gonadectomy Is Not Correlated with Altered T-Lymphocyte Populations in Senior Labrador Retrievers
Bibliographic record
Abstract
Abstract Retrospective studies have suggested that gonadectomies, such as the spays and neuters common in companion animal populations, may be correlated with the development of autoimmune conditions later in the life of an animale. This study investigated the potential influences of gonadectomy on peripheral blood lymphocyte populations through flow cytometry. Twenty senior Labrador Retrievers (10 males and 10 females) were randomly selected from Four Rivers Kennel’s existing research colony according to their intact or altered status. Groups were balanced by age and body weight (average 11.4 y/o and 64.5 kg) as both have been previously shown to alter lymphocyte populations. A single blood collection was performed and stained with canine cross-reactive conjugated antibodies CD3-FITC, CD4-Superbright 600, CD8-Superbright 702, and a fixable lime viability stain (Invitrogen, Waltham MA). Samples were processed through a whole blood based lyse no-wash method and analyzed on an Attune NXT Flow Cytometer equipped with blue and violet lasers (ThermoFisher Waltham, MA). Measurement of cell populations was completed on a defined volume of each sample, and all subsets were gated to live, singlet lymphocytes. Statistical significance was determined through one-way ANOVAs on JMP Pro 16 (Cary, NC). There were no significant differences in CD4+/CD8+ ratio between groups (P = 0.56), or total lymphocyte populations (P = 0.34). Additionally, there were no significant differences between groups regarding CD3+ MFI (P = 0.25), CD8+ MFI (P = 0.70), or CD4+ MFI (P = 0.43). Overall, in age and body weight balanced senior Labrador Retrievers, spay or neuter status did not significantly influence T-cell populations. This suggests that previous gonadectomy does not influence the adaptive immune system as an animal ages. Further research is needed to clarify the relationship between gonadectomy and the later development of autoimmune disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".