Poster Session 4: Therapeutics: Preclinical and Early Clinical Development
Bibliographic record
Abstract
AASLD ABSTRACTS1305A NASH, 25 HC).The data are presented as median (Q1, Q3) for non-normal and mean (SD) for normal continuous variables.Groups were compared using Wilcoxon rank-sum tests and t-tests.Spearman correlation coefficients were used to examine association between variables.Results: NAFLD patients were older than HC and had significantly higher BMI, liver enzymes (AST, ALT), insulin resistance (HOMA-IR), hemoglobin A1c, and blood triglycerides (p<0.05).Fecal choline was higher in NAFLD vs HC: 16.6 (8.9, 28.8) mM vs 9.4 (0, 17.9) mM (p=0.02), as well as fecal TMA: 22.7 (0, 28.2) mM vs 0 (0, 10.6) mM (p=0.02).Both parameters were also associated with increased BMI: fecal choline was correlated to BMI in HC and NAFLD (r=0.46 p=0.01 in HC and r=0.37 p=0.02 in NAFLD) and TMA was correlated to BMI in HC only (r=0.71, p<0.001).Serum choline levels were not different between the groups, but were negatively correlated with percent of steatosis within the HC (4 healthy patients were found to have mild signs of steatosis) and the NAFLD group: r=-0.53,p=0.03 and r=-0.40 p=0.2, respectively.Serum, fecal, and dietary choline were not correlated.Conclusions: These preliminarily results provide evidence that bacterial interference in choline metabolism is related to NAFLD.BMI might also play a role in this complex relationship.Further investigations, including serum TMA levels and the characterization of the intestinal microbiota are in progress and should clarify the relationship.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.210 | 0.124 |
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".