Transcriptomics and differential gene expression in <i>Whitmania pigra</i> (Annelida: Clitellata: Hirudinida: Hirudinidae): Contrasting feeding and fasting modes
Bibliographic record
Abstract
Abstract The medicinal utility of leeches has been demonstrated through decades of use in modern hospital settings, mainly as relievers of venous congestion following flap or digit replantation surgery. In the present study, we sequence and annotate (through BLAST‐ and Gene Ontology‐based approaches) the salivary transcriptome of the nonblood feeding hirudinid Whitmania pigra and assess the differential gene expression of anticoagulation factors (through both quantitative real‐time PCR [qRT‐PCR] and in silico‐based methods) during feeding and fasting conditions. This was done in order to evince the diversity of putative anticoagulation factors, as well as estimate the levels of upregulation of genes immediately after feeding. In total, we found sequences with demonstrated orthology (via both phylogenetic analyses and BLAST‐based approaches) to seven different proteins that have previously been linked to anticoagulatory capabilities—eglin C, bdellin, granulin, guamerin, hyaluronidase, destabilase I, and lipocalin. All of these were recovered from leeches both in the fasting and in the feeding conditions, but all show signs of upregulation in the feeding leeches. Interestingly, our RNA‐seq effort, coupled with a hypergeometric test, indicated that the differentially expressed genes were disproportionately involved in three main immunological pathways (endocytosis, peroxisome regulation, and lysosome regulation). The results and implications of the finding of anticoagulants in this nonblood feeding leech and the putative upregulation of anticoagulation factors after feeding are briefly discussed in an evolutionary context.
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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) | 0.000 | 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".