[Expression relationship and significance of NEAT1 and miR-27a-3p in serum and cerebrospinal fluid of patients with Alzheimer disease].
Bibliographic record
Abstract
OBJECTIVE: To explore the expression relationship and significance of long chain non-coding RNA nuclear-enriched abundant transcript 1 (LncRNA NEAT1) and miR-27a-3p in serum and cerebrospinal fluid of patients with Alzheimer disease (AD). METHODS: =25). Another 66 cases of serum and cerebrospinal fluid samples from outpatient physical examination personnel were regarded as the control group. The general information on all subjects was recorded and cognition was assessed; real-time quantitative PCR was performed to measure the expression levels of miR-27a-3p and NEAT1 in serum and cerebrospinal fluid; enzyme-linked immunosorbent assay was performed to measure the protein levels of β-amyloid precursor protein cleaving enzyme 1 (BACE1), β-amyloid (Aβ) 40 and Aβ42 in cerebrospinal fluid; Spearman' s method was performed to analyze the correlation of serum miR-27a-3p and NEAT1 levels with mini-mental state examination (MMSE) and montreal cognitive assessment (MoCA) scores; Pearson method was performed to analyze the correlation between serum miR-27a-3p and NEAT1 levels and Aβ deposition standard uptake value ratio (SUVR) and cerebrospinal fluid miR-27a-3p, NEAT1, BACE1, Aβ42 and Aβ40 levels. RESULTS: < 0.05). CONCLUSION: The expression trends of NEAT1 and miR-27a-3p in the serum and cerebrospinal fluid of AD patients are consistent, the level of NEAT1 is increased, and the level of miR-27a-3p is decreased. The levels of the two are negatively correlated, which is related to the degree of Aβ deposition in the brain of AD patients and is involved in the progression of AD.
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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 | 0.000 | 0.000 |
| 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".