Effects of Noise Exposure on Systemic and Tissue-Level Markers of Glucose Homeostasis and Insulin Resistance in Male Mice
Bibliographic record
Abstract
BACKGROUND: Epidemiological studies have indicated that noise exposure is associated with an increased risk of type 2 diabetes mellitus (T2DM). However, the nature of the connection between noise exposure and T2DM remains to be explored. OBJECTIVES: We explored whether and how noise exposure affects glucose homeostasis in mice as the initial step toward T2DM development. METHODS: Male ICR mice were randomly assigned to one of four groups: the control group and three noise groups (N20D, N10D, and N1D), in which the animals were exposed to white noise at 95 decibel sound pressure level (dB SPL) for 4 hr per day for 20 successive days, 10 successive days, or 1 day, respectively. Glucose tolerance and insulin sensitivity were evaluated 1 day, 1 week, and 1 month after the final noise exposure (1DPN, 1WPN, and 1MPN). Standard immunoblots, immunohistochemical methods, and enzyme-linked immunosorbent assays (ELISA) were performed to assess insulin signaling in skeletal muscle, the morphology of β cells, and plasma corticosterone levels. RESULTS: Noise exposure for 1 day caused transient glucose intolerance and insulin resistance, whereas noise exposure for 10 and 20 days had no effect on glucose tolerance but did cause prolonged insulin resistance and an increased insulin response to glucose challenge. Akt phosphorylation and GLUT4 translocation in response to exogenous insulin were decreased in the skeletal muscle of noise-exposed animals. CONCLUSIONS: Noise exposure at 95 dB SPL caused insulin resistance in male ICR mice, which was prolonged with longer noise exposure and was likely related to the observed blunted insulin signaling in skeletal muscle. CITATION: Liu L, Wang F, Lu H, Cao S, Du Z, Wang Y, Feng X, Gao Y, Zha M, Guo M, Sun Z, Wang J. 2016. Effects of noise exposure on systemic and tissue-level markers of glucose homeostasis and insulin resistance in male mice. Environ Health Perspect 124:1390-1398; http://dx.doi.org/10.1289/EHP162.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".