Recent Discoveries in the Pathogenesis and Immune Response Toward <i>Entamoeba Histolytica</i>
Bibliographic record
Abstract
Entamoeba histolytica is an enteric dwelling human protozoan parasite that causes the disease amoebiasis, which is endemic in the developing world. Over the past four decades, considerable effort has been made to understand the parasite and the disease. Improved diagnostics can now differentiate pathogenic E. histolytica from that of the related but nonpathogenic Entamoeba dispar, thus minimizing screening errors. Classically, the triad of Gal-lectin, cysteine proteinases and amoebapores of the parasite were thought to be the major proteins involved in the pathogenesis of amoebiasis. However, other amoebic molecules such as lipophosphopeptidoglycan, perioxiredoxin, arginase, and lysine and glutamic acid-rich proteins are also implicated. Recently, the genome of E. histolytica has been sequenced, which has widened our scope to study additional virulence factors. E. histolytica genome-based approaches have now confirmed the presence of Golgi apparatus-like vesicles and the machinery for glycosylation, thus improving the chances of identifying potential drug targets for chemotherapeutic intervention. Apart from Gal-lectin-based vaccines, promising vaccine targets such as serine-rich E. histolytica protein have yielded encouraging results. Considerable efforts have also been made to skew vaccination responses towards appropriate T-helper cell immunity that could augment the efficacy of vaccine candidates under study. Thus, ongoing efforts mining the information made available with the sequencing of the E. histolytica genome will no doubt identify and characterize other important potential vaccine/drug targets and lead to effective immunologic strategies for the control of amoebiasis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".