Hematologic reference intervals for <i>Xenopus tropicalis</i> with partial use of automatic counting methods and reliability of long‐term stored samples
Bibliographic record
Abstract
BACKGROUND: The African frog, Xenopus tropicalis, is widely used in biomedical and toxicologic research. Reference intervals (RI) for hematologic variables, valuable to research and health status assessment, have not been established. OBJECTIVES: The purpose of the study was to determine hematologic RI of X tropicalis, and establish whether automated cell counting can facilitate routine hematologic assessment in frogs. METHODS: Blood from 41 adult healthy X tropicalis was collected via cardiac puncture, and diluted in Natt-Herrick solution. Complete WBC, RBC, and thrombocyte counts (hemocytometry), differential WBC counts (Wright-Giemsa-stained smears), PCV (centrifugation), total protein (refractometry), and automated total cell counts (WBC + RBC + thrombocytes, Sysmex particle counting) were determined. Concordance correlation coefficients calculated the agreement between total cell counts obtained by hemocytometry and automated particle counting, and between total cell counts at collection and after 2 years of storage. RESULTS: Leukocyte morphology was similar to other amphibians and mammals. PCV was similar to other frogs; RBC counts were higher, and MCV was lower than in other frog species. Neutrophils were the most numerous WBC. Agreement was good between hemocytometry and automated cell counts. Subtracting the hemocytometer WBC and thrombocyte counts from the automated total cell count reliably yielded the RBC count. Cellular integrity evaluated 2 years post collection was good, and automated counts were not clinically different from counts at collection. CONCLUSION: We provide hematologic RI for X tropicalis, suggest how automated cell counts may facilitate hematologic assessments of frogs, and establish that blood in Natt-Herrick solution is stable 2 years post collection.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".