In vitro transmission of Chlamydia using naturally infected koala (Phascolarctos cinereus) semen
Bibliographic record
Abstract
Transmission of Chlamydia pecorum infection has generally been assumed to be via the urogenital route and in an attempt to confirm this we investigated an in vitro method of Chlamydia infection using naturally infected koala semen to inoculate a cell line and attempt to estimate C. pecorum infectious load. A total of 57% of 122 koala semen samples had low C. pecorum copy number or no burden, while 18% of semen samples contained >10000 inclusion-forming units/mL, as determined by quantitative polymerase chain reaction. In vitro inoculation of a McCoy cell line resulted in successful infection from 4% of semen samples where C. pecorum burden was >105 inclusion-forming units/mL. Our preliminary study suggests that transmission of C. pecorum infectious dose may be restricted to peak bacterial shedding in semen associated with recent infection. Here, we report venereal transmission of C. pecorum in koala semen is possible; however, we speculate that antimicrobial factors and innate immune function receptors associated with semen may inhibit chlamydial growth. These mechanisms have yet to be reported in marsupial semen.
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".