Effect of synbiotic bread containing lactic acid on blood lipids and apolipoproteins in patients with type 2 diabetes: A randomized controlled trial
Bibliographic record
Abstract
Abstract Recently, the use of synbiotics for managing various diseases has dramatically increased. Synbiotics have been shown to be a good approach to influence the composition of the gut microbiota with positive health effects. Management of type 2 diabetes mellitus (T2DM) complications is one of the reasons for the ingestion of synbiotics and so the aim of the current study was to determine the effects of synbiotic bread intake on markers of lipid profile in T2DM patients. One hundred T2DM patients (age between 20 and 60 years) were randomly assigned to four groups to consume different types of synbiotic bread, three times/day, for 8 weeks: “synbiotic + lactic acid” (n = 25; IV), “synbiotic” (n = 25; III), “lactic acid brad” (n = 25; II), or “control” (n = 25; I). The measured outcomes included anthropometric characteristics, glycemic control parameters, blood lipids, and apolipoproteins. The consumption of “synbiotic + lactic acid bread” (group IV) and “lactic acid bread” (group II) led to a significant decrease in total cholesterol (TC) and glycated hemoglobin (HbA1c) compared to the “control bread.” The HbA1c levels were also significantly lower when compared to group II. Additionally, apolipoprotein A (Apo A1) levels were significantly decreased in group IV, compared to control and other groups (post hoc analysis). No significant differences between groups were observed for triglyceride (TG), high‐density lipoprotein (HDL), low‐density lipoprotein (LDL), and apolipoprotein B100 (Apo B100) levels. The observed results show that the synbiotic bread (with or without lactic acid) promoted a decrease in total cholesterol (TC) and Apo A1 in diabetic patients when consumed daily for 8 weeks.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".