Biological sex, not reproductive cycle, influences peripheral blood immune cell prevalence in mice
Bibliographic record
Abstract
Key points Traditionally the female sex, compared with the male sex, has been perceived as having greater variability in many physiological traits, including within the immune system. We investigated effects of biological sex and the female reproductive cycle on numbers of circulating leukocytes in C57BL/6J mice. We show that biological sex, but not female reproductive cyclicity, has a significant effect on peripheral blood immune cell prevalence and variability, and that sex differences were not consistent amongst common inbred laboratory mouse strains. We found that male C57BL/6J mice, compared with female mice, have greater variability in peripheral blood immunophenotype, and that this was influenced by body weight. We created summary tables for researchers to facilitate experiment planning and sample size calculations for peripheral immune cells that consider the effects of biological sex. Abstract Immunophenotyping (i.e. quantifying the number and types of circulating leukocytes) is used to characterize immune changes during health and disease, and in response to pharmacological and other interventions. Despite the importance of biological sex in immune function, there is considerable uncertainty amongst researchers as to the extent to which biological sex or the female reproductive cycle influence blood immunophenotype. We quantified circulating leukocytes by multicolour flow cytometry in young C57BL/6J mice and assessed the effects of the reproductive cycle, biological sex, and other experimental and biological factors on data variability. We found that there are no significant effects of the female reproductive cycle on the prevalence of peripheral blood B cells, NK cells, CD4+ T cells, CD8+ T cells, monocytes, or neutrophils. Immunophenotype composition and variability do not significantly change between stages of the female reproductive cycle. There are, however, sex‐specific differences in immune cell prevalence, with fewer monocytes, neutrophils, and NK cells in female mice. Surprisingly, immunophenotype is more variable in male mice, and weight is a significant contributing factor. We provide tools for researchers to perform a priori sample size calculations for two‐group and factorial analyses. We show that immunophenotype varies between inbred mouse strains, and that using equal sample sizes of male and female mice is not always appropriate for within‐sex evaluations of immune cell populations in peripheral blood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".