Immunological Profile and Markers of Endothelial Dysfunction in Elderly Patients with Cognitive Impairments
Bibliographic record
Abstract
The process of aging is accompanied by a dynamic restructuring of the immune response, a phenomenon known as immunosenescence. Further, damage to the endothelium can be both a cause and a consequence of many diseases, especially in elderly people. The purpose of this study was to carry out immunological and biochemical profiling of elderly people with acute ischemic stroke (AIS), chronic cerebral circulation insufficiency (CCCI), prediabetes or newly diagnosed type II diabetes mellitus (DM), and subcortical ischemic vascular dementia (SIVD). Socio-demographic, lifestyle, and cognitive data were obtained. Biochemical, hematological, and immunological analyses were carried out, and extracellular vesicles (EVs) with endothelial CD markers were assessed. The greatest number of significant deviations from conditionally healthy donors (HDs) of the same age were registered in the SIVD group, a total of 20, of which 12 were specific and six were non-specific but with maximal differences (as compared to the other three groups) from the HDs group. The non-specific deviations were for the MOCA (Montreal Cognitive Impairment Scale), the MMSE (Mini Mental State Examination) and life satisfaction self-assessment scores, a decrease of albumin levels, and ADAMTS13 (a Disintegrin and Metalloproteinase with a Thrombospondin Type 1 motif, member 13) activity, and an increase of the VWF (von Willebrand factor) level. Considering the significant changes in immunological parameters (mostly Th17-like cells) and endothelial CD markers (CD144 and CD34), vascular repair was impaired to the greatest extent in the DM group. The AIS patients showed 12 significant deviations from the HD controls, including three specific to this group. These were high NEFAs (non-esterified fatty acids) and CD31 and CD147 markers of EVs. The lowest number of deviations were registered in the CCCI group, nine in total. There were significant changes from the HD controls with no specifics to this group, and just one non-specific with a maximal difference from the control parameters, which was α1-AGP (alpha 1 acid glycoprotein, orosomucoid). Besides the DM patients, impairments of vascular repair were also registered in the CCCI and AIS patients, with a complete absence of such in patients with dementia (SIVD group). On the other hand, microvascular damage seemed to be maximal in the latter group, considering the biochemical indicators VWF and ADAMTS13. In the DM patients, a maximum immune response was registered, mainly with Th17-like cells. In the CCCI group, the reaction was not as pronounced compared to other groups of patients, which may indicate the initial stages and/or compensatory nature of organic changes (remodeling). At the same time, immunological and biochemical deviations in SIVD patients indicated a persistent remodeling in microvessels, chronic inflammation, and a significant decrease in the anabolic function of the liver and other tissues. The data obtained support two interrelated assumptions. Taking into account the primary biochemical factors that trigger the pathological processes associated with vascular pathology and related diseases, the first assumption is that purine degradation in skeletal muscle may be a major factor in the production of uric acid, followed by its production by non-muscle cells, the main of which are endothelial cells. Another assumption is that therapeutic factors that increase the levels of endothelial progenitor cells may have a therapeutic effect in reducing the risk of cerebrovascular disease and related neurodegenerative diseases.
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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".