Testosterone‐dependent sex differences in red blood cell hemolysis in storage, stress, and disease
Bibliographic record
Abstract
BACKGROUND: Red blood cell (RBC) hemolysis represents an intrinsic mechanism for human vascular disease. Intravascular hemolysis releases hemoglobin and other metabolites that inhibit nitric oxide signaling and drive oxidative and inflammatory stress. Although these pathways are important in disease pathogenesis, genetic and population modifiers of hemolysis, including sex, have not been established. STUDY DESIGN AND METHODS: We studied sex differences in storage or stress-induced hemolysis in RBC units from the United States and Canada in 22 inbred mouse strains and in patients with sickle cell disease (SCD) using measures of hemolysis in 315 patients who had homozygous SS hemoglobin from the Walk-PHASST cohort. A mouse model also was used to evaluate posttransfusion recovery of stored RBCs, and gonadectomy was used to determine the mechanisms related to sex hormones. RESULTS: An analysis of predisposition to hemolysis based on sex revealed that male RBCs consistently exhibit increased susceptibility to hemolysis compared with females in response to routine cold storage, under osmotic or oxidative stress, after transfusion in mice, and in patients with SCD. The sex difference is intrinsic to the RBC and is not mediated by plasmatic factors or female sex hormones. Importantly, orchiectomy in mice improves RBC storage stability and posttransfusion recovery, whereas testosterone repletion therapy exacerbates hemolytic response to osmotic or oxidative stress. CONCLUSION: Our findings suggest that testosterone increases susceptibility to hemolysis across human diseases, suggesting that male sex may modulate clinical outcomes in blood storage and SCD and establishing a role for donor genetic variables in the viability of stored RBCs and in human hemolytic diseases.
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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 | 0.000 |
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".