Gender differences in expression of the human caspase-12 long variant determines susceptibility to <i>Listeria monocytogenes</i> infection
Bibliographic record
Abstract
Inflammatory caspases are important effectors of innate immunity. Caspase-12, of the inflammatory caspase subfamily, is expressed in all mammals tested to date, but has acquired deleterious mutation in humans. A single-nucleotide polymorphism introduces a premature stop codon in caspase-12 in the majority of the population. However, in 20% of African descendants, caspase-12 is expressed and sensitizes to infections and sepsis. Here, we examined the modalities by which human caspase-12 confers susceptibility to infection. We have generated a fully humanized mouse that expresses the human caspase-12 rare variant (Csp-12L) in a mouse casp-12(-/-) background. Characterization of the humanized mouse uncovered sex differences in Csp-12L expression and gender disparity in innate immunity to Listeria monocytogenes infection. The Csp-12L transgene completely reversed the knockout resistance-to-infection phenotype in casp-12(-/-) males. In contrast, it had a marginal effect on the response of female mice. We found that estrogen levels modulated the expression of caspase-12. Csp-12L was expressed in male mice but its expression was repressed in female mice. Administration of 17-beta-estradiol (E2) to humanized male mice had a direct suppressive effect on Csp-12L expression and conferred relative resistance to infection. Chromatin immunoprecipitation experiments revealed that caspase-12 is a direct transcriptional target of the estrogen receptor alpha (ERalpha) and mapped the estrogen response element (ERE) to intron 7 of the gene. We propose that estrogen-mediated inhibition of Csp-12L expression is a built-in mechanism that has evolved to protect females from infection.
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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 | 0.000 | 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".