Elevated Urinary AD7c-NTP Levels in Older Adults with Hypertension and Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Hypertension, a common chronic disease, is associated with cognitive impairment. Cognitive impairment, especially Alzheimer's disease (AD), seriously affects older adults' quality of life and aggravates the burden of disease on society and families. Elevated Alzheimer-associated neuronal thread protein (AD7c-NTP) has been observed in the urine of patients with AD and mild cognitive impairment; however, it is not clear whether this protein can be used as a biomarker for cognitive impairment in older hypertensive patients. OBJECTIVE: To explore the value of urinary AD7c-NTP, and the association of urinary AD7c-NTP with cognitive function in older hypertensive patients. METHODS: This was a cross-sectional study. In total, 134 hypertensive patients aged ≥60 years were divided into two groups: Lower Cognitive Function group (LCF group, n = 89) and Normal Control group (NC group, n = 45) based on the Montreal Cognitive Assessment (MoCA). Urinary AD7c-NTP, blood glucose, serum insulin, superoxide dismutase (SOD) and malondialdehyde (MDA) levels were measured. RESULTS: Urinary AD7c-NTP level was significantly higher in the LCF group than in the NC group [0.48 (0.21-1.00) versus 0.25 (0.04-0.44) ng/ml, p < 0.001]. The LCF group had lower SOD level [(43.07±23.74) versus (53.12±25.80) U/ml, p = 0.026] and higher homeostasis model assessment of insulin resistance (HOMA-IR) [7.17 (3.74-13.94) versus 6.01 (3.78-7.43), p = 0.033] than the NC group. Urinary AD7c-NTP level was associated with MoCA score and HOMA-IR but not with SOD, MDA, blood glucose, and insulin. CONCLUSION: The level of urinary AD7c-NTP is elevated in older hypertensive patients with lower cognitive function, and insulin resistance may be involved in the process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".