Hepatosplenic T-Cell Lymphoma of αβ Lineage in a 16-Year-Old Boy Presenting With Hemolytic Anemia and Thrombocytopenia
Bibliographic record
Abstract
The authors report an unusual case of peripheral T-cell lymphoma in a 16-year-old boy who presented initially with jaundice, splenomegaly, anemia, and thrombocytopenia. A lymphoma was found subsequently in the spleen, which was infiltrated extensively in the red pulp by medium-sized, blastic-appearing lymphoma cells. Immunologic characterization of these cells revealed positivity for CD3, CD5, CD45RO, CD56, and T-cell intracellular antigen (TIA), and negativity for CD2, CD3, CD4, CD8, CD57, CD34, and terminal deoxynucleotidyl transferase (TdT). Conventional cytogenetic studies revealed the presence of isochromosome 7q. On follow up, this patient deteriorated rapidly, with evidence of liver and bone marrow involvement. Although the overall clinical and pathologic features of this disease were characteristic of hepatosplenic gammadelta T-cell lymphoma, the T-cell receptor of this tumor showed an immunophenotype of alphabeta not gammadelta lineage. Using the Southern blot technique, the authors demonstrated monoclonal gene rearrangement of the T-cell receptor beta-chain. Thus, they confirmed the existence of hepatosplenic alphabeta T-cell lymphoma. In view of its overall similarity to hepatosplenic gammadelta T-cell lymphoma, this unusual entity probably represents a slight biologic variation of the same disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".