Prenatal arsenic exposure induces immunometabolic alteration and renal injury in rats
Bibliographic record
Abstract
Arsenic (As) exposure is progressively associated with chronic kidney disease (CKD), a leading public health concern present worldwide. The adverse effect of As exposure on the kidneys of people living in As endemic areas have not been extensively studied. Furthermore, the impact of only prenatal exposure to As on the progression of CKD also has not been fully characterized. In the present study, we examined the effect of prenatal exposure to low doses of As 0.04 and 0.4 mg/kg body weight (0.04 and 0.4 ppm, respectively) on the progression of CKD in male offspring using a Wistar rat model. Interestingly, only prenatal As exposure was sufficient to elevate the expression of profibrotic (TGF-β1) and proinflammatory (IL-1α, MIP-2α, RANTES, and TNF-α) cytokines at 2-day, 12- and 38-week time points in the exposed progeny. Further, alteration in adipogenic factors (ghrelin, leptin, and glucagon) was also observed in 12- and 38-week old male offspring prenatally exposed to As. An altered level of these factors coincides with impaired glucose metabolism and homeostasis accompanied by progressive kidney damage. We observed a significant increase in the deposition of extracellular matrix components and glomerular and tubular damage in the kidneys of 38-week-old male offspring prenatally exposed to As. Furthermore, the overexpression of TGF-β1 in kidneys corresponds with hypermethylation of the TGF-β1 gene-body, indicating a possible involvement of prenatal As exposure-driven epigenetic modulations of TGF-β1 expression. Our study provides evidence that prenatal As exposure to males can adversely affect the immunometabolism of offspring which can promote kidney damage later in life.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".