Effects of tumor necrosis factor α on the structure of brain networks and cognitive functions in patients with chronic cerebral ischemia
Bibliographic record
Abstract
Introduction. The processes of cognitive decline, which are typical for elderly and senile people, as well as for patients with chronic cerebral circulation insufficiency, involve pro-inflammatory cytokines, such as tumor necrosis factor (TNF-), interleukin-6, etc. The aim of this work was to study the association of TNF- with brain network structure and cognitive functions in patients with chronic cerebral ischemia (CCI). Materials and methods. We examined 101 patients with CCI (5085 years old, men and women) who were assessed for the saliva levels of TNF- during cognitive testing. The status of resting-state networks was analyzed in 55 patients using functional magnetic resonance therapy. Results. After cognitive tasks, the saliva level of TNF- increased by 17.6 6.2 pg/mL. Half of the CCI patients older than 60 years showed a significant increase in the level of TNF-. This cytokine correlated with delayed word recall and the ratio of delayed recall to their performance on the Luria Memory Words Test. The change in TNF- saliva levels correlated with the status of the resting-state network, mainly with the salience network. An increase in TNF- levels was associated with a higher frequency of negative correlations than at lower values of TNF- (less than 80 pg/mL). TNF--sensitive connectivities correlated with cognitive tasks, not only memory tests, but also with the Montreal Cognitive Assessment Scale, verbal fluency test scores, etc. Discussion. The study revealed two significant facts: an increase in the TNF- saliva level during cognitive performance and a lower success rate of cognitive performance associated with an increase in the levels of this cytokine. The central mechanism for the implementation of this relationship includes the restructuring of the salience network, namely the additional increase of negative correlations within the connective structure of the salience neural network of the right hemisphere. Conclusions. A change in the saliva level of TNF- affects the connectivity of resting-state networks, mainly the salience network
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".