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Record W4391577046 · doi:10.1128/cmr.00098-23

Beyond schistosomiasis: unraveling co-infections and altered immunity

2024· review· en· W4391577046 on OpenAlexafffund
Dilhan J. Perera, Cal Koger-Pease, Kayla Paulini, Mohamed Daoudi, Momar Ndao

Bibliographic record

VenueClinical Microbiology Reviews · 2024
Typereview
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéPublic Health Agency of CanadaGovernment of CanadaFonds de recherche du QuébecCanadian Institutes of Health ResearchMcGill University Health CentrePublic Health Agency
KeywordsSchistosomaSchistosomiasisSchistosoma mansoniBiologyImmunologyHelminthiasisHelminthsProtozoaTropical diseaseImmunityImmune systemDiseaseMicrobiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

SUMMARY Schistosomiasis is a neglected tropical disease caused by the helminth Schistosoma spp. and has the second highest global impact of all parasites. Schistosoma are transmitted through contact with contaminated fresh water predominantly in Africa, Asia, the Middle East, and South America. Due to the widespread prevalence of Schistosoma , co-infection with other infectious agents is common but often poorly described. Herein, we review recent literature describing the impact of Schistosoma co-infection between species and Schistosoma co-infection with blood-borne protozoa, soil-transmitted helminths, various intestinal protozoa, Mycobacterium , Salmonella , various urinary tract infection-causing agents, and viral pathogens. In each case, disease severity and, of particular interest, the immune landscape, are altered as a consequence of co-infection. Understanding the impact of schistosomiasis co-infections will be important when considering treatment strategies and vaccine development moving forward.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.140
GPT teacher head0.474
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations22
Published2024
Admission routes2
Has abstractyes

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