Bibliographic record
Abstract
Metabolic pathways which extract energy from carbon compounds are essential for an organism's survival.Therefore, inhibition of enzymes in these pathways represents a potential therapeutic strategy to combat parasitic infections.However, the high degree of similarity between host and parasite enzymes makes this strategy potentially difficult.Nevertheless, several existing drugs to treat infections by parasitic helminths (worms) target metabolic enzymes.These include the trivalent antimonials which target phosphofructokinase and Clorsulon which targets phosphoglycerate mutase and phosphoglycerate kinase.Glycolytic enzymes from a variety of helminths have been characterised biochemically, and some inhibitors identified.To date none of these inhibitors have been developed into therapies.Many of these enzymes are externalised from the parasite and so are also of interest in the development of potential vaccines.Less work has been done on tricarboxylic acid cycle enzymes and oxidative phosphorylation complexes.Again, while some inhibitors have been identified none have been developed into drug-like molecules.Barriers to the development of novel drugs targeting metabolic enzymes include the lack of experimentally determined structures of helminth enzymes, lack of direct proof that the enzymes are vital in the parasites and lack of cell culture systems for many helminth species.Nevertheless, the success of Clorsulon (which discriminates between highly similar host and parasite enzymes) should inspire us to consider making serious efforts to discover novel anthelminthics which target metabolic enzymes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".