Potential role of costimulatory pathways in immune dysfunction in hemodialysis patients
Bibliographic record
Abstract
Potential role of costimulatory pathways in immune dysfunction in hemodialysis patientsTo the Editor:We read with interest the paper by Mathew et al. who investigated the role of T-regulatory cells in the immune response to HBV vaccination in patients undergoing hemodialysis (HD). 1 This is a very important topic, since response to vaccines is commonly considered an expression of immune status in HD.The authors, in agreement with previous reports, demonstrated that in HD there is a low rate of response to vaccine, but they did not find any significant difference in T-regulatory cell number between healthy controls and HD subjects.We think that this negative result could depend by the fact that immune dysfunction in HD patients involves alterations of various types of immune cells, including polymorphonuclear leukocytes, monocytes, natural killer cells, B and T lymphocytes 2,3 and probably the simple study of the number of T-regulatory cells and their subtypes is not sufficient to describe this condition.Indeed, in this complex picture T cell dysfunction can occur at different levels.In this regards, in the last years, many studies have demonstrated that co-stimulatory signal alterations may play a role in determining immunodeficiency in HD.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.008 | 0.006 |
| 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".