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Caracterización de proteínas de fase aguda asociadas con un brote de virus de diarrea epidémica porcina en lechones y cerdas lactantes en México

2018· article· es· W2789453918 on OpenAlexaff
Elein Hernández, Dan Bolaños-López, R Beltrán, Rosa Elena Sarmiento‐Silva, Noé Orlando Juárez López, María Elena Trujillo Ortega

Bibliographic record

VenueTIP Revista Especializada en Ciencias Químico-Biológicas · 2018
Typearticle
Languagees
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHumanitiesChemistryPhilosophy

Abstract

fetched live from OpenAlex

El objetivo de este estudio fue determinar la relación entre cuatro diferentes proteínas de fases aguda (APP) y los efectos patológicos causados por el virus de la diarrea epidémica porcina (PEDV) en lechones y cerdas. El diagnóstico en laboratorio (prueba PCR) del PEDV fue determinado a partir de muestras de heces de animales enfermos; posteriormente, los cerdos fueron clasificados en relación a la presencia o ausencia de signos entéricos (ES) característicos de la enfermedad: vómitos y diarrea. Los grupos fueron: (I) Lechones sin ES (n = 7), (II) Lechones con ES (n = 8), (III) Cerdas sin ES (n = 6) y (IV) Cerdas con ES (n = 6). La cuantificación en sangre de las APP fue a partir de ensayo ELISA (no específico) para Amiloide sérico A (SAA) y haptoglobina (HAP); en cambio, la Proteína C reactiva (CRP) y PIGMAP fueron cuantificados mediante un ensayo ELISA (sándwich) de anticuerpos monoclonales. Finalmente, no se encontraron diferencias significativas (P>0.05) en las concentraciones de las diferentes APP entre lechones y cerdas con y sin ES. La supervivencia de los lechones está relacionada con el grado de deshidratación durante la diarrea; PEDV provoca signos entéricos severos antes de la inducción de citoquinas pro-inflamatorias, sin embargo esta inducción patológica sigue sin tener respuesta.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.324
Teacher spread0.306 · 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 designObservational
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

Citations2
Published2018
Admission routes1
Has abstractyes

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