The role of amylin, a gut–brain axis hormone, in metabolic and neurological disorders
Bibliographic record
Abstract
cell peptide hormone involved in satiation and control food intake. It is also produced in smaller quantities by neurons, the gastrointestinal tract, and spinal ganglia. Numerous studies have revealed that patients with type 2 diabetes mellitus (T2DM) and cognitive deficits exhibit IAPP deposits in the pancreas, brain, and blood vessels. IAPP has also been shown to exert neuroprotective effects against Alzheimer's disease (AD) and cognitive impairments. The objective of this review paper is to provide recent information about the pathophysiological roles of IAPP in metabolic and in neurological disorders, and its potential as a druggable target. We have reviewed preclinical and clinical human and animal research studies of IAPP. We discuss the IAPP structure, its receptors, and its physiological functions in metabolism, satiation, adiposity, obesity, and in the brain. Then we discuss its role in metabolic and neurological disorders like diabetes, obesity, bone disorder, neurodegeneration, cerebrovascular disorders, depression, alcohol use disorder, epilepsy, and in ovarian cysts. Overall, this review provides information on the progress of research into the roles of IAPP and its receptor in food intake, energy homeostasis, glucose regulation, satiation, and its role in metabolic and neurological disorders making it a potential target for therapeutic approaches. This review also suggests that the utilization of rodents overexpressing human IAPP in neurodegeneration models may unearth some significant therapeutic potentials for neurological disorders.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".