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Record W4402922272 · doi:10.1038/s41598-024-73843-5

A human-serum-free medium can induce more infectious P. falciparum gametocytes than a conventional human-serum-containing medium

2024· article· en· W4402922272 on OpenAlexaff
Kazutoyo Miura, Bingbing Deng, Ragavan Varadharajan Suresh, Yonas T Gebremicale, Luwen Zhou, Thao Pham, Kyle C. Roche, Ababacar Diouf, Jonathan F. Lovell, Jean‐Philippe Julien, Carole A. Long

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsGametocytePlasmodium falciparumMalariaBiologyVirologyMedicineImmunology

Abstract

fetched live from OpenAlex

Malaria remains a global health problem, and the standard membrane feeding assay (SMFA) is a key functional assay for development of new interventions to stop malaria transmission from human to mosquito. For SMFA, media with ~ 10% of human serum has been used for infectious gametocyte cultures, however, there are multiple challenges to obtain a suitable human serum. Here we show a human-serum-free culture medium (HSF), which was a mixture of two stem cell culture media and AlbuMAX, supported infectious gametocyte growth. Moreover, the HSF-induced gametocytes elicited significantly higher numbers of oocysts compared to gametocytes cultured with conventional human serum medium (Conv). While some caution is required when comparing percent transmission reducing activity data generated from HSF-SMFA and Conv-SMFA, the HSF method can facilitate the establishment of gametocyte cultures or SMFA by bypassing the need for human serum. Thus, this study will support future development of P. falciparum transmission-blocking interventions.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.028
GPT teacher head0.325
Teacher spread0.297 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes1
Has abstractyes

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