Clinical, Laboratory, and Histopathologic Features of Equine Lymphoma
Bibliographic record
Abstract
Clinical, laboratory and tissue findings from 37 horses with lymphoma were investigated. Horses ranged in age from 0.3 to 20.5 years (median 5.0 years) and included 18 females and 19 males. Weight loss (n = 25) and ventral edema (n = 21) were the most common historical and physical abnormalities. The most common laboratory abnormalities were hyperfibrinogenemia (n = 26), hypoalbuminemia (n = 19), anemia (n = 19), leukemia (n = 14), hyperglobulinemia (n = 13), and thrombocytopenia (n = 13). Thirty-four tumors involved multiple lymphoid tissues and abdominal or thoracic organs, and 3 tumors were restricted to cutaneous and subcutaneous sites. Histopathologically, all tumors diffusely effaced normal lymph node architecture. Tumor cell morphology was heterogeneous in 17 tumors, and 8 tumors had marked histiocytic and multinucleated giant cell infiltrates. Extensive necrosis or focal fibrosis was present in 22 and 4 lymphomas, respectively. Staining of tumor sections with antibodies against CD3 and CD79alpha molecules resulted in classification of T-cell (n = 26) or B-cell (n = 7) origin. Four tumors could not be classified. Most T-cell tumors comprised small to medium CD3(+) lymphocytes, whereas 5 of 7 B-cell tumors were infiltrated by numerous small T lymphocytes and classified as T-cell-rich B-cell lymphoma. Neither estrogen nor progesterone receptor expression was consistently identified by immunochemical assessment of tumor tissues. Fresh tumor cells from 6 horses bound antibodies reactive with equine CD4, CD5, CD8, CD21, or major histocompatibility class II molecules, confirming T-cell (n = 5) or B-cell origin (n = 1). These findings suggest that T-cell lymphoma is more common than B-cell lymphoma in horses and that inflammation, possibly from tumor cytokine production, is frequent.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".