The polypharmacy reduction potential of cinnamic acids and some related compounds in pre- and post-onset management of type 2 diabetes mellitus
Bibliographic record
Abstract
OBJECTIVES: This review assesses the polypharmacy reduction potential of cinnamic acids (CAs) and some related compounds in managing three or more of the cluster of seven, pre- and post-type 2 diabetes mellitus (T2DM)-related features (central obesity, hyperglycemia, hypertension, dyslipidemia, pro-thrombosis, oxidation, and inflammation). METHODS: Google scholar and Pubmed were searched for cinnam*, chlorogenic acid, ferulic acid, and caffeic acid in conjunction with each of pre- and post-onset T2DM, central obesity, hyperglycemia, hypertension, dyslipidemia, pro-thrombosis, oxidation, and inflammation. The study was divided into an introduction followed by findings on the impacts of each of the CAs including trans-CA acid, the E isomer of a CA-based thiazolidinedione and a metabolite of that isomer, as well as p-methoxy CA, various cinnamic amides and some other CA-related compounds (chlorogenic acid, cinnamaldehyde, ferulic and caffeic acid). RESULTS: Trans-CA has a potential to manage three, while each of chlorogenic acid, cinnamalde-hyde, caffeic acid and ferulic acid has a potential to manage all seven members of the cluster. Other CA-related compounds identified may manage only one or two of the cluster of seven. CONCLUSIONS: Much of the work has been done in animal models of pre- and post-onset T2DM and non-pre- or post-onset T2DM humans and animals, along with some cell culture and in vitro work. Very little work has been done with human pre- and post-onset T2DM. While there is potential for managing 3 or more members of the cluster with many of these compounds, a definitive answer awaits large pre- and post-T2DM onset clinical trials with humans.
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 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) | 0.001 | 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".