New insights into Chlamydia pathogenesis: Role of leukemia inhibitory factor
Bibliographic record
Abstract
Chlamydia trachomatis (Ct)is the leading cause of bacterial sexually transmitted infections worldwide. Since the symptoms ofCtinfection are often subtle or absent, most people are unaware of their infection until they are tested or develop severe complications such as infertility. It is believed that the primary culprit ofCt-associated tissue damage is unresolved chronic inflammation, resulting in aberrant production of cytokines, chemokines, and growth factors, as well as dysregulated tissue influx of innate and adaptive immune cells. A member of the IL-6 cytokine family, leukemia inhibitory factor (LIF), is one of the cytokines induced byCtinfection but its role inCtpathogenesis is unclear. In this article, we review the biology of LIF and LIF receptor (LIFR)-mediated signaling pathways, summarize the physiological role of LIF in the reproductive system, and discuss the impact of LIF in chronic inflammatory conditions and its implication inCtpathogenesis. Under normal circumstances, LIF is produced to maintain epithelial homeostasis and tissue repair, including the aftermath ofCtinfection. However, LIF/LIFR-mediated signaling – particularly prolonged strong signaling – can gradually transform the microenvironment of the fallopian tube by altering the fate of epithelial cells and the cellular composition of epithelium. This harmful transformation of epithelium may be a key process that leads to an enhanced risk of infertility, ectopic pregnancy and cancer followingCtinfection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".