White Matter Alternation at Corpus Callosum and Stria Terminalis Contributes to the Cognitive Impairment in ESRD via Dysregulating Homeostasis of Calcium
Bibliographic record
Abstract
Background: Cognitive impairment is common in patients with end stage kidney disease (ESRD). White matter alternation is important pathologic change in cognitive impairment, and fixel-based analysis quantifies the fiber loss. The study is to elucidate the white matter alternation in uremic cognitive impairment patients. Methods: The study period was from August 2019 to December2020. The participants were divided into three groups according to the MMSE score and the status with end stage renal disease or not: (1) control (n=16): MMSE>24 without end stage renal disease; (2) group 2 (n=17): end stage renal disease with MMSE 25˜30; (3) group 3 (n=14): end stage renal disease with MMSE10˜24. All participants received magnetic resonance imaging and hematologic and biochemical parameters. Fixel-based analysis was performed to assess the fiber density. Results: The fiber density, the fiber cross section and the summation of the fiber density and cross section were lower in the ESRD patients. The decrease in corpus callosum and fornix/stria terminalis was associated with the decrease in Montreal Cognitive Assessment(p<0.05). The concentration of calcium(8.80± 0.79mg, vs 9.27± 0.29mg for control group, p<0.05) was lower in ESRD patients. The serum concentration of calcium was positive associated with the fiber density in the corpus callosum and fornix/stria terminalis(p<0.05). Conclusions: The white mater density decreased in the ESRD patients, and the decrease was associated with cognitive impairment. Serum calcium positively correlated with the fiber density in corpus callosum and fornix terminalis.The association between imparied fibers and MoCA.The fibers influenced by calcium concentration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".