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Mutaciones en los genes PSEN1 y PSEN2 como marcadores moleculares en la Enfermedad de Alzheimer. Revisión Sistemática.

2025· article· es· W4413440199 on OpenAlexaboutno aff
María José Tapia, Carem Prieto

Bibliographic record

VenueMQRInvestigar · 2025
Typearticle
Languagees
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPSEN1BiologyAlzheimer's diseaseMedicineMolecular biologyPresenilinDiseasePathology

Abstract

fetched live from OpenAlex

Introducción: La enfermedad de Alzheimer se considera una de las patologías neurodegenerativas de mayor impacto en la salud pública, con una prevalencia y tasa de mortalidad en incremento. En su forma de inicio temprano, se ha vinculado estrechamente con mutaciones genéticas que alteran el procesamiento de la APP y por ende acumulación de placas Aβ, siendo los genes PSEN1 y PSEN2 los más implicados. Objetivo: Analizar la evidencia disponible sobre mutaciones en los genes PSEN1 y PSEN2 como marcadores moleculares en la enfermedad de Alzheimer. Metodología: Se realizó una revisión sistemática de la literatura, incluyendo estudios publicados entre 2019 y 2024, identificados a través de las bases de datos Scopus, PubMed y Taylor & Francis. La selección de estudios siguió los lineamientos PRISMA, y la calidad metodológica fue evaluada mediante la escala Newcastle-Ottawa (NOS). Resultados: Los estudios incluidos reportaron mutaciones frecuentes en PSEN1 (E280A, M146I, T274K) y en menor medida en PSEN2 (M239T), asociadas con una mayor proporción Aβ42/Aβ40 y un incremento en la acumulación de placas amiloides en tejido cerebral. Conclusiones: Las mutaciones en PSEN1 y PSEN2 se pueden considerar potenciales marcadores moleculares útiles para el diagnóstico temprano y la estratificación del riesgo en pacientes con sospecha de Alzheimer de origen genético.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.334
Teacher spread0.315 · 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.

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
Published2025
Admission routes1
Has abstractyes

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