AIMC Topic: Insulin

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Magneto-Responsive Microneedle Robots for Intestinal Macromolecule Delivery.

Advanced materials (Deerfield Beach, Fla.)
Oral administration is the most convenient and commonly used approach for drug delivery, while it is still a challenge to overcome the complicated gastrointestinal barriers and realize efficient macromolecular drug absorption. Here, novel magneto-res...

Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.

Canadian journal of diabetes
OBJECTIVES: Circulating insulin concentrations mediate vascular-inflammatory and prothrombotic factors. However, it is unknown whether interindividual differences in circulating insulin levels are associated with different inflammatory and prothrombo...

Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.

Sensors (Basel, Switzerland)
Type 1 diabetes is a chronic disease caused by the inability of the pancreas to produce insulin. Patients suffering type 1 diabetes depend on the appropriate estimation of the units of insulin they have to use in order to keep blood glucose levels in...

Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study.

Frontiers in endocrinology
BACKGROUND AND OBJECTIVE: Clinical characteristics of obesity are heterogenous, but current classification for diagnosis is simply based on BMI or metabolic healthiness. The purpose of this study was to use machine learning to explore a more precise ...

Screening of a novel free fatty acid receptor 1 (FFAR1) agonist peptide by phage display and machine learning based-amino acid substitution.

Biochemical and biophysical research communications
Free fatty acid receptor 1 (FFAR1 or GPR40) has attracted attention for the treatment of type 2 diabetes mellitus, and various small-molecule agonists have been developed. However, most FFAR1 agonists as well as endogenous ligands, such as linoleic a...

Intelligent automated drug administration and therapy: future of healthcare.

Drug delivery and translational research
In the twenty-first century, the collaboration of control engineering and the healthcare sector has matured to some extent; however, the future will have promising opportunities, vast applications, and some challenges. Due to advancements in processi...

Image-Based Machine Learning Algorithms for Disease Characterization in the Human Type 1 Diabetes Pancreas.

The American journal of pathology
Emerging data suggest that type 1 diabetes affects not only the β-cell-containing islets of Langerhans, but also the surrounding exocrine compartment. Using digital pathology, machine learning algorithms were applied to high-resolution, whole-slide i...

[Leptin sexual dimorphism, insulin resistance, and body composition in normal weight prepubescent].

Revista chilena de pediatria
INTRODUCTION: The prepubertal stage is a critical period of body fat development, in which leptin and insulin re sistance has been associated, however, there are few studies in normal-weight prepubescents. Ob jective: To assess the relationship betwe...

Multi-Hour Blood Glucose Prediction in Type 1 Diabetes: A Patient-Specific Approach Using Shallow Neural Network Models.

Diabetes technology & therapeutics
Considering current insulin action profiles and the nature of glycemic responses to insulin, there is an acute need for longer term, accurate, blood glucose predictions to inform insulin dosing schedules and enable effective decision support for the...

Deep Physiological Model for Blood Glucose Prediction in T1DM Patients.

Sensors (Basel, Switzerland)
Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mellitus (T1DM) patients in order to be able to react on time and avoid hypo and hyper-glycemic episodes. Accurate predictions for blood glucose are the ...