Patterns of gene expression in schistosomes: localization by whole mount<i>in situ</i>hybridization
Bibliographic record
Abstract
As a consequence of comprehensive transcriptome analysis followed by sequencing and draft assembly of the genome, the emphasis of schistosome research is shifting from the identification of genes to the characterization of their functions and interactions. Developmental biologists have long used whole mount in situ hybridization (WISH) to determine gene expression patterns, as a vital tool for formulating and testing hypotheses about function. This paper describes the application of WISH to the study of gene expression in larval and adult schistosomes. Fixed worms were permeablized by proteinase K treatment for hybridization with digoxygenin-labelled RNA probes, with binding being detected by alkaline phosphatase-coupled anti-digoxygenin antibodies, and BM Purple substrate. Discrete staining patterns for the transcripts of the molecules Sm29, cathepsin L, antigen 10.3 and chorion were observed in the tegument cell bodies, gut epithelium, oesophageal gland and vitelline lobules, respectively, of adult worms. Transcripts of the molecules SGTP4, GP18-22 and cathepsin L were localized to tegument cell bodies and embryonic gut, respectively, of lung schistosomula. We also showed that Fast Red TR fluorescent substrate can refine the pattern of localization permitting use of confocal microscopy. We believe that method of WISH will find broad application, in synergy with other emerging post-genomic techniques, such as RNA interference, to studies focused at increasing our molecular understanding of schistosomes.
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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 | 0.001 |
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".