Blood Characteristics of Adults With Type 2 Diabetes and Response of Their Peripheral Blood Mononuclear Cells to Inhibitors of the NLRP3 Inflammasome and Caspase-1
Bibliographic record
Abstract
OBJECTIVES: Obesity and aging are associated with increased activity of the innate immune system. This chronic systemic inflammation contributes to the development of type 2 diabetes and long-term complications and is partly driven by the activation of the NLRP3 inflammasome. METHODS: We conducted a comparative analysis of clinical parameters, nonesterified fatty acid(s) (NEFA) profiles, immune cell subsets, and inflammatory responses of peripheral blood mononuclear cells (PBMCs) obtained from both healthy individuals and those diagnosed with type 2 diabetes. RESULTS: Plasma NEFA profiling revealed a dysregulation in patients with type 2 diabetes, indicating potential modulation of immune cell responses by lipids, along with leukocytosis, elevated serum levels of inflammatory cytokines, the inflammasome-related protein apoptosis-associated speck-like protein with a caspase recruitment domain, interleukin (IL)-1 receptor antagonist, and IL-18 binding protein. Surprisingly, functional assessments demonstrated comparable NLRP3 inflammasome activity in PBMCs from both groups, suggesting that systemic inflammation in type 2 diabetes is driven by elevated leukocyte numbers or resident tissue macrophages. Treatment of PBMCs with NLRP3 and caspase-1 inhibitors attenuated the release of pro-inflammatory cytokines ex vivo. CONCLUSIONS: Inhibition of inflammasome activation has emerged as a promising therapeutic strategy for management of diabetes-related complications.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".