A low carbohydrate diet high in fish oil and soy protein delays inflammation, hematopoietic stem cell depletion, and mortality in miR-146a knock-out mice
Bibliographic record
Abstract
Since our previous studies found a low carbohydrate (CHO) diet containing soy protein and fish oil (15%Amylose/Soy/FO) significantly reduced lung and breast cancer in mice we asked herein if this low CHO diet could also delay the onset of myeloid malignancies. To test this we employed a miR-146a knock-out (KO) mouse model and found the 15%Amylose/Soy/FO diet increased their median lifespan by 8.5 month, compared to these mice on a Western diet. This was associated with increased lymphocytes and reduced monocytes, granulocytes, blood glucose and insulin levels. Inflammatory cytokine/chemokine studies carried out with 6-month-old mice, before any signs of illness, revealed the 15%Amylose/Soy/FO diet significantly reduced pro-inflammatory cytokines. This low CHO diet also led to an increase in plasma β-hydroxybutyrate and in liver fatty acid synthase levels. This, together with higher liver carnitine palmitoyltransferase I levels suggested that the 15%Amylose/Soy/FO diet was causing a systemic metabolic shift from glucose to fatty acids as an energy source. Lastly, we found the 15%Amylose/Soy/FO diet resulted in significantly higher numbers of primitive hematopoietic stem cells (HSCs) in the bone marrow of 6-month-old mice than those fed a Western diet. Taken together, these results suggest a 15%Amylose/Soy/FO diet reduces chronic inflammation and increases fatty acid oxidation and that this, in turn, may prevent HSC proliferation and exhaustion, thereby delaying myeloid malignancy-induced death of miR-146a KO mice. We suggest a low CHO diet containing soy protein and fish oil could be beneficial in reducing the risk of myeloid malignancies in patients with low miR-146a levels.
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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 | 0.000 | 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 | 0.000 |
| 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".