Weight cycling-induced hypothalamic and metabolic tissue immune remodeling is uncoupled from metabolic dysfunctions
Bibliographic record
Abstract
Abstract Background Obesity-induced insulin resistance is associated with white adipose tissue (WAT) and liver inflammation, which are both mitigated by weight loss. However, most individuals undergoing weight loss will regain lost weight, resulting in weight cycling (WC), which may exacerbate metabolic dysfunctions. Here, we studied the immunometabolic impact of WC in mice. Methods C57BL/6J mice were exposed to two cycles of weight gain and weight loss by alternating between low (LFD) and high-fat diet (HFD) feeding. Animals were sacrificed when WC mice were weight stable for 10 weeks upon weight loss (WC-lean) and after a subsequent exposure to weight regain for 10 weeks (WC-obese), and compared to mice persistently fed LFD (LFD-lean) or HFD (HFD-obese). Results Body weight stabilized at a higher level in WC-lean mice after two weight gain/loss cycles compared to LFD-lean controls. While insulin resistance, metabolic tissue inflammation, and hepatic steatosis normalized between the two groups of lean mice, WC-lean mice exhibited features of WAT dysfunction. In the hypothalamus, inflammatory microglia were less abundant in WC-lean mice compared to LFD-lean mice, but mean individual microglial cell volume was larger. WC-obese mice stabilized at slightly lower weight compared with HFD-obese controls. Intriguingly, WC-obese mice exhibited increased WAT macrophages and reduced WAT and liver effector T cells compared to HFD-obese mice, whereas energy intake, body composition, whole-body insulin resistance and hepatic steatosis were similar. Conclusions Our results suggest that WC in mice differently impacts animals in the weight-stable lean and obese states. WC-lean mice display features of a novel body weight settling point, associated with hypothalamic inflammatory changes. However, metabolic dysfunctions were uncoupled from WC-induced metabolic tissue inflammation in WC-obese mice.
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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) | 0.000 | 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) | 0.002 | 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".