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Record W4375955915 · doi:10.1080/10253890.2023.2210687

The chronic stress risk phenotype mirrored in the human retina as a neurodegenerative condition

2023· article· en· W4375955915 on OpenAlexfundno aff
Leoné Malan, Roelof van Wyk, Roland von Känel, Tjalf Ziemssen, Walthard Vilser, Peter M. Nilsson, Martin Magnusson, Amra Jujić, Daniel W. Mak, Faans Steyn, Nico T. Malan

Bibliographic record

VenueStress · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsnot available
FundersRoche DiagnosticsLund University Medical Faculty FoundationNorth-West UniversityCrafoordska StiftelsenMedical Research CouncilSouth African Medical Research CouncilKnut och Alice Wallenbergs StiftelseLunds UniversitetNational Research FoundationSouthwest Skanes Diabetes FoundationHeart and Stroke Foundation of Canada
KeywordsMedicineRetinaPathologyIschemiaInternal medicineNeuroscienceBiology

Abstract

fetched live from OpenAlex

The brain is the key organ that orchestrates the stress response which translates to the retina. The retina is an extension of the brain and retinal symptoms in subjects with neurodegenerative diseases substantiated the eye as a window to the brain. The retina is used in this study to determine whether chronic stress reflects neurodegenerative signs indicative of neurodegenerative conditions. A three-year prospective cohort (n = 333; aged 46 ± 9 years) was stratified into stress-phenotype cases (n = 212) and controls (n = 121) by applying the Malan stress-phenotype index. Neurodegenerative risk markers included ischemia (astrocytic S100 calcium-binding protein B/S100B); 24-h blood pressure, proteomics; inflammation (tumor-necrosis-factor-α/TNF-α); neuronal damage (neuron-specific-enolase); anti-apoptosis of retinal-ganglion-cells (beta-nerve-growth-factor), astrocytic activity (glial-fibrillary-acidic-protein); hematocrit (viscosity) and retinal follow-up data [vessels; stress-optic-neuropathy]. Stress-optic-neuropathy risk was calculated from two indices: a newly derived diastolic-ocular-perfusion-pressure cut-point ≥68 mmHg relating to the stress-phenotype; combined with an established cup-to-disk ratio cut-point ≥0.3. Higher stress-optic-neuropathy (39% vs. 17%) and hypertension (73% vs. 16%) prevalence was observed in the stress-phenotype cases vs. controls. Elevated diastolic-ocular-perfusion-pressure, indicating hypoperfusion, was related to arterial narrowing and trend for ischemia increases in the stress-phenotype. Ischemia in the stress-phenotype at baseline, follow-up and three-year changes was related to consistent inflammation (TNF-α and cytokine-interleukin-17-receptor-A), neuron-specific-enolase increases, consistent apoptosis (chitinase-3-like protein 1, low beta-nerve-growth-factor), glial-fibrillary-acidic-protein decreases, elevated viscosity, vein widening as risk marker of endothelial dysfunction in the blood-retinal barrier, lower vein count, and elevated stress-optic-neuropathy. The stress-phenotype and related neurodegenerative signs of ongoing brain ischemia, apoptosis and endothelial dysfunction compromised blood–retinal barrier permeability and optic nerve integrity. In fact, the stress-phenotype could identify persons at high risk of neurodegeneration to indicate a neurodegenerative condition.

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 score0.003
Threshold uncertainty score0.006

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 communication0.0010.000
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 head0.011
GPT teacher head0.289
Teacher spread0.278 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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