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Record W6884299512 · doi:10.1002/jex2

Guidelines for the purification and characterization of extracellular vesicles of parasites

2023· article· en· W6884299512 on OpenAlexfundno aff

Bibliographic record

VenueRepository of Digital Objects for Teaching Research and Culture (University of Valencia) · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaGeneralitat de CatalunyaMinisterio de Ciencia e InnovaciónConselho Nacional de Desenvolvimento Científico e TecnológicoGeneralitat ValencianaInstituto de Salud Carlos IIIUniversity of Texas at El PasoNational Institutes of HealthCanadian Institutes of Health ResearchFundació la Marató de TV3Centres de Recerca de CatalunyaAgencia Estatal de InvestigaciónFundação para a Ciência e a TecnologiaFundação de Amparo à Pesquisa do Estado de São PauloCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsExtracellular vesiclesIsolation (microbiology)Intracellular parasiteHost (biology)DiseaseExtracellularDrug resistanceDrug

Abstract

fetched live from OpenAlex

Parasites are responsible for the most neglected tropical diseases, affecting over a billion people worldwide (WHO, 2015) and accounting for billions of cases a year and responsible for several millions of deaths. Research on extracellular vesicles (EVs) has increased in recent years and demonstrated that EVs shed by pathogenic parasites interact with host cells playing an important role in the parasite's survival, such as facilitation of infection, immunomodulation, parasite adaptation to the host environment and the transfer of drug resistance factors. Thus, EVs released by parasites mediate parasite-parasite and parasite-host intercellular communication. In addition, they are being explored as biomarkers of asymptomatic infections and disease prognosis after drug treatment. However, most current protocols used for the isolation, size determination, quantification and characterization of molecular cargo of EVs lack greater rigor, standardization, and adequate quality controls to certify the enrichment or purity of the ensuing bioproducts.We are now initiating major guidelines based on the evolution of collective knowledge in recent years. The main points covered in this position paper aremethods for the isolation and molecular characterization of EVs obtained from parasite-infected cell cultures, experimental animals, and patients. The guideline also includes a discussion of suggested protocols and functional assays in host cells

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.051
GPT teacher head0.318
Teacher spread0.267 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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