The regional distribution of resident immune cells shapes distinct immunological environments along the murine epididymis
Bibliographic record
Abstract
The epididymis functions as transition zone for post-testicular sperm maturation and storage and faces contrasting immunological challenges, i.e. tolerance towards spermatozoa vs. reactivity against pathogens. Thus, normal organ function and integrity relies heavily on a tightly controlled immune balance. Previous studies described inflammation-associated tissue damage solely in the distal regions (corpus, cauda), but not in the proximal regions (initial segment, caput). To understand the observed region-specific immunity along the epididymal duct, we have used an acute bacterial epididymitis mouse model and analyzed the disease progression. Whole transcriptome analysis using RNAseq 10 days post infection showed a pro-inflammatory environment within the cauda, while the caput exhibited only minor transcriptional changes. High-dimensional flow cytometry analyses revealed drastic changes in the immune cell composition upon infection with uropathogenic Escherichia coli . A massive influx of neutrophils and monocytes was observed exclusively in distal regions and was associated with bacterial appearance and tissue alterations. In order to clarify the reasons for the region-specific differences in the intensity of immune responses, we investigated the heterogeneity of resident immune cell populations under physiological conditions by scRNASeq analysis of extravascular CD45+ cells. Twelve distinct immune cell subsets were identified, displaying substantial differences in distribution along the epididymis as further assessed by flow cytometry and immunofluorescence staining. Macrophages constituted the majority of resident immune cells and were further separated in distinct subgroups based on their transcriptional profile, tissue location and monocyte-dependence. Crucially, the proximal and distal regions showed striking differences in their immunological landscapes. These findings indicate that resident immune cells are strategically positioned along the epididymal duct, potentially providing different immunological environments required for addressing the contrasting immunological challenges and thus, preserving tissue integrity and organ function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".