Elevated baseline expression of seven virulence factor RNA transcripts in visceralizing species of <i>Leishmania</i> : a preliminary quantitative PCR study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Leishmaniasis is a neglected tropical disease that manifests as three major disease phenotypes: cutaneous, mucocutaneous, and visceral. In this preliminary study, we quantified virulence factor (VF) RNA transcript expression in Leishmania species, stratified by geographic origin and propensity for specific disease phenotypes. Methods: Cultured promastigotes of 19 Leishmania clinical and ATCC isolates were extracted for total cellular RNA, cDNA was reverse transcribed, and qPCR assays were performed to quantify VF RNA transcript expression for hsp23, hsp70, hsp83, hsp100, mpi, cpb, and gp63. Results: Comparison of visceralizing species (Leishmania donovani, Leishmania chagasi, and Leishmania infantum) versus non-visceralizing species [Leishmania (Viannia) spp., Leishmania tropica, Leishmania major, Leishmania mexicana, and Leishmania amazonensis] revealed a significantly greater pooled transcript expression for visceralizing species (p = 0.0032). Similarly, Old World species demonstrated significantly higher VF RNA transcript expression than New World species (p = 0.0015). On a per-gene basis, species with a propensity to visceralize ubiquitously expressed higher levels of gp63 (p = 0.005), cpb (p = 0.0032), mpi (p = 0.0032), hsp23 (p = 0.0039), hsp70 (p = 0.0032), hsp83 (p = 0.0032), and hsp100 (p = 0.0032). Conclusion: Here, we provide quantitative, preliminary evidence of elevated VF RNA transcript expression driven largely by the visceralizing causative species of Leishmania. This work highlights the extensive heterogeneity in pathogenicity mechanisms between Leishmania species, which may partly underpin the fatal progression of visceral leishmaniasis.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it