NLRX1 does not play a role in diabetes nor the development of diabetic nephropathy induced by multiple low doses of streptozotocin
Bibliographic record
Abstract
Diabetic nephropathy (DN) is a microvascular complication of diabetes mellitus that results in both tubular and glomerular injury. Low-grade inflammation and oxidative stress are two mechanisms known to drive the progression of DN. Nucleotide-binding leucine-rich repeat containing family member X1 (NLRX1) is an innate immune receptor, uniquely located in mitochondria, that has been found to regulate inflammatory responses and to dampen renal oxidative stress by regulating oxidative phosphorylation. For this reason, we investigated the role of NLRX1 in the development of DN in a Type 1 Diabetes mouse model. We analyzed the effect of NLRX1 deficiency on diabetes development and the accompanied renal damage, inflammation, and fibrosis. We found that multiple low doses of streptozotocin induced body weight loss, polydipsia, hyperglycemia, glycosuria, and a mild DN phenotype in wildtype and NLRX1-deficient mice, without significant differences between these mouse strains. Despite increased NLRX1 expression in diabetic wildtype mice, NLRX1 deficiency did not affect the diabetic phenotype induced by streptozotocin treatment, as reflected by similar levels of polyuria, microalbuminuria, and increased renal markers of oxidative stress and inflammation in wildtype and NLRX1-deficient mice. The present findings show that NLRX1 does not mediate the development of streptozotocin-induced diabetes and diabetic-induced nephropathy in mice after multiple low doses of streptozotocin. This data implies that, while NLRX1 can be triggered by cellular stress, its regulatory and functional effects may be dependent on the specific physiological conditions. In the case of DN, NLRX1 may be neither helpful nor harmful, but rather a marker of metabolic stress.
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 | 0.001 |
| 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".