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Record W4388578607

Correlation Analysis of Serum 3-NT, NPASDP-4, and S100β Protein Levels with Cognitive Function in Patients Diagnosed with Cerebral Infarction.

2024· article· en· W4388578607 on OpenAlexaboutno aff
Zuhao Xu, Xiaorong Weng, Liping Cao, Disai Liang, Fengshan Zeng, Shaolan Chen, Yi Zhang, Haiwen Huang, Min Gao

Bibliographic record

VenuePubMed · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineCerebral infarctionCognitionMontreal Cognitive AssessmentLogistic regressionInfarctionCohortCardiologyMyocardial infarctionCognitive impairmentDiseaseIschemiaPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objective: To observe the levels of serum 3-nitrotyrosine (3-NT), neuronal PAS domain protein 4 (NPASDP-4), and S100β protein in patients diagnosed with cerebral infarction and analyze their correlation with cognitive dysfunction in these patients. Methods: The study included a cohort of 158 patients suffering from cerebral infarction who were admitted to the Liwan District Hospital of Traditional Chinese Medicine between January 2021 and December 2022. After stabilizing vital signs, all patients underwent the Montreal Cognitive Assessment (MoCA) to assess their cognitive function. Based on the assessment results, they were divided into two groups: the cognitive dysfunction group (121 cases) and the normal cognitive function group (37 cases). The baseline characteristics and serum levels of 3-NT, neuronal PAS domain protein 4 (NPASDP-4), and S100β protein were compared in the patient cohorts. Furthermore, the correlation between these three indicators and cognitive function in patients suffering from cerebral infarction was analyzed. A logistic regression model was constructed to analyze how serum levels of 3-NT, NPASDP-4, and S100β protein levels affected cognitive function in patients suffering from cerebral infarction. ROC curve analysis was conducted to assess the predictive value of serum 3-NT, NPASDP-4, and S100β protein levels for cognitive function in patients suffering from cerebral infarction. Results: Among the 158 patients with cerebral infarction, 121 (76.58%) had cognitive dysfunction, while 37 (23.42%) had normal cognitive function. The levels of 3-NT, NPASDP-4, and S100β protein were found to be significantly higher in the cognitive dysfunction group compared to the normal cognitive function group (t = 5.788, 7.774, 6.460; P = .000, .000, .000). The point-biserial correlation analysis results showed a positive correlation between serum levels of 3-NT, NPASDP-4, and S100β protein and the occurrence of cognitive dysfunction in patients suffering from cerebral infarction (r=0.420, 0.529, 0.424; P = .000, .000, .000). The logistic regression model demonstrated that serum levels of 3-NT(95%CI: 1.299-2.603), NPASDP-4(95%CI: 1.487-3.386), and S100β protein(95%CI: 1.153-8.746) were risk factors for cognitive dysfunction in patients suffering from cerebral infarction (OR=1.839, 2.244, 1.429; P = .001, .000, .240). ROC curve analysis demonstrated that serum 3-NT, NPASDP-4, and S100β protein levels exhibited a certain predictive value for cognitive function in patients with cerebral infarction (AUC = 0.789, 0.881, 0.820). Conclusion: Serum levels of 3-NT, NPASDP-4, and S100β protein are closely related to the cognitive function of patients with cerebral infarction, and abnormal changes in these levels may exacerbate cognitive dysfunction in these patients.

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)0.001
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.208
Teacher spread0.188 · 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".

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Citations2
Published2024
Admission routes1
Has abstractyes

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