Obesogenic diet in aging mice disrupts gut microbe composition and alters neutrophil:lymphocyte ratio leading to inflamed milieu in acute heart failure
Bibliographic record
Abstract
Calorie dense obesogenic diet (OBD) is a prime risk factor for cardiovascular disease in aging. However, increasing age coupled with changes in the diet can affect the interaction of intestinal microbiota impacting immune system that can lead to chronic inflammation. How the age and calorie enriched OBD interact with microbial flora and impacts leukocyte profiling is currently under‐investigated. Here, we tested whether OBD in young and aging mice alters the gut microbe composition and the splenic leukocyte profile in acute heart failure. Young (2 month‐old) and aging (18 month‐old) mice were supplemented with STD‐(standard chow diet ~4% safflower oil diet) and OBD‐(obesogenic diet‐10% safflower oil) diet for 2 months and then subjected to coronary artery ligation to induce myocardial infarction (MI). Fecal samples were collected pre‐ and post‐diet and the microbial flora analyzed using 16S V4 rRNA gene DNA sequencing and QIIME informatics. The STD and OBD in aging mice resulted in an expansion of the genus Allobaculum in the fecal microbiota. However, we found a pathological change of neutrophil: lymphocyte ratio in aging mice in comparison to their young counterparts. Thus, calorie‐enriched OBD dysregulated splenic leukocytes by decreasing immune responsive F4/80+/CD169+ macrophages in aging. OBD programmed neutrophil swarming with an increase in isoprostanes levels with dysregulation of lipoxygenases and cytokines. In summary, calorie dense OBD in aging mice disrupted the composition of the gut microbiota that correlates with the development of integrative and system‐wide non‐resolving inflammation in acute heart failure. Support or Funding Information Authors acknowledge the support from National Institutes of Health (NIH)‐NCCIH (formerly known as NCCAM) AT006704, HL132989‐01 to GVH and American Heart Association postdoctoral fellowship [POST31000008] to V. K. The authors also acknowledge support of Microbiome Resource at the University of Alabama at Birmingham: Comprehensive Cancer Center (P30AR050948), Center for Clinical Translational Science (UL1TR001417), University‐Wide Institutional Core, Heflin Center for Genomic Sciences and Microbiome Center to CM This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".