CHARACTERIZATION OF <i>HYDROPSYCHE SLOSSONAE</i> (TRICHOPTERA: HYDROPSYCHIDAE) CAPTURE NET POLYPEPTIDES
Bibliographic record
Abstract
Abstract The aim of this study was to characterize polypeptide components of the capture net spun by trichopteran larvae Hydropsyche slossonae (Banks) (Trichoptera: Hydropsychidae). Thirty-one polypeptide bands were identified by SDS – polyacrylamide gel electrophoresis (SDS–PAGE) from extracted net material, with molecular weights ranging from 8500 to 179 000. Comparison with published data on Bombyx mori (L.) (Lepidoptera: Bombycidae) silk, treated under similar denaturing conditions, shows that six low molecular weight polypeptides ranging between 8500 and 18 800 in the silk of H. slossonae are absent from that of B. mori; furthermore, two high molecular weight polypeptides (210 000 and 220 000) detected in the silk of B. mori are not present in that of H. slossonae. Differences between both groups are probably related to their mode of living and to the specific use of silk (in air versus under water). Our findings are consistent with the current trend in the literature that silk spun by aquatic and terrestrial insects, as well as those spun by different species, is apparently made of different biopolymers according to the protein constituents. Hence, the polypeptide characterization of silk, combined with sequence data and (or) antibodies cross-reactivity data, could represent a potential tool for taxonomic classification improvement of aquatic insects. These results could eventually be used to characterize hydropsychid capture net anomalies induced by environmental pollution.
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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 | 0.001 | 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".