High glucose induces pro‐inflammatory phenotype in human astrocytes and enhances neurotoxicity
Bibliographic record
Abstract
Chronic neuroinflammation caused by activation of microglia and astrocytes in the brain contributes to neuronal loss and disease progression in Alzheimer's disease (AD). High glucose has been shown to increase release of pro‐inflammatory mediators from various immune cells, including microglia. We investigated the effects of glucose (5.5–30.5 mM) on astrocytic cells. High glucose increased expression and secretion of pro‐inflammatory cytokines interleukin (IL)‐6 and IL‐8 (P<0.05) in human primary astrocytes and U‐118 MG astrocytoma cells. This astrocytic proinflammatory response to elevated glucose may involve increased phosphorylation of the signal transducer and activator of transcription (STAT)‐3. High glucose also increased the susceptibility of human SH‐SY5Y neuroblastoma cells to toxicity induced by hydrogen peroxide and Alzheimer amyloid‐β1–42 (P<0.05). We hypothesize that brain hyperglycemia in type 2 diabetes contributes to the observed increased risk of AD by exacerbating astrocyte‐mediated neuroinflammation and neuronal injury caused by disease‐specific agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".