The Effect of Tofogliflozin Treatment on Postprandial Glucose and Lipid Metabolism in Japanese Men With Type 2 Diabetes: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Postprandial hyperglycemia and hyperlipidemia are highly related to the development of atherosclerosis. Sodium/glucose cotransporter-2 (SGLT2) inhibitors have attracted attention as a new class of anti-diabetic agents for the treatment of type 2 diabetes. We investigated the effect of tofogliflozin on postprandial glucose and lipid metabolism in Japanese male patients with type 2 diabetes. METHODS: Ten Japanese men with type 2 diabetes (average age 66.3 years) were orally administered tofogliflozin (20 mg per day) for 8 weeks followed by a subsequent 8 weeks of washout of the agent. At 0, 8 and 16 weeks, postprandial metabolic parameters were measured at 0, 60 and 120 min after cookie ingestion. RESULTS: There were significant reductions in body weight and body mass index at 8 weeks. There was a reduction in HbA1c at 8 weeks, which returned to pretreatment levels at 16 weeks. Serum insulin levels did not change during the entire study period under either fasting or postprandial state. The area under the curve of plasma glucagon significantly increased at 8 weeks. There were no changes in lipid and lipoprotein levels either in fasting or postprandial state except for tendency toward reduction in postprandial triglycerides at 8 weeks and increase in HDL-C at 16 weeks. CONCLUSIONS: Tofogliflozin treatment causes an improvement of postprandial glucose metabolism but not considerable postprandial lipid metabolism.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".