Immunological and neuroanatomic markers of the clinical dynamics of MCI and pre-MCI
Bibliographic record
Abstract
Objective. To study the relationship of the parameters of immunity and systemic inflammation with the structural magnetic resonance imaging (MRI) parameters in patients with mild cognitive impairment (MCI) and pre-MCI undergoing neurocognitive rehabilitation to search for candidate markers of its effectiveness. Material and methods. The main group included 49 patients, aged ≥60 years, with MCI and pre-MCI with memory impairment, who underwent a course of neurorehabilitation for 5 weeks. The control group included 19 volunteers of similar age with a total MoCA score of ≥25, who did not have cognitive impairment and immuno-inflammatory disorders. The parameters of cellular and humoral immunity and markers of inflammation were studied, and structural MRI was performed. Results. The content of activated natural killer cells (NK-cells) was increased in MCI and pre-MCI (0.63±0.12% vs. 0.22±0.07% in the control group, p=2.2·10–7). The level of immunoglobulin G (IgG) <12.5 g/l in patients with MCI and pre-MCI with the Montreal Cognitive Assessment Scale (MoCA) score <22 was associated with a decrease in the volume of the right nucleus accumbens (376±35 mm3 in patients with IgG <12.5 g/l (p=0.0013) and 480±44 mm3 at IgG <12.5 g/l, 480±44 mm3 in the control group), as well as with a decrease of the thickness and volume of a number of other cortical zones. A logistic regression model including the level of immunoglobulin G, NK cells, CD8+ NK cells and right amygdala volume was constructed to predict the number of MoCA scores 6 months after the course of rehabilitation (R2=0.57; p<1·10–5; standard error of estimate: 2.93). Conclusion. As a result of this work, the perspectives of assessing the immunological parameters in combination with socio-demographic data and morphometric changes of the brain as potential prognostic markers of the dynamics of cognitive impairment in patients with MCI and pre-MCI after neurorehabilitation has been shown.
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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 | 0.000 |
| 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".