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Metformin

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Comparative study between UHPLC-UV and UPLC-MS/MS methods for determination of alogliptin and metformin in their pharmaceutical combination.

Die Pharmazie
A new UPLC-MS/MS method (method A), for simultaneous determination of alogliptin (ALN) and metformin (MET) in their recently approved pharmaceutical combination Kazano® tablets, was developed and compared to a new UHPLC-UV method (method B). Concerni...

Impact of metformin on serum prostate-specific antigen levels: Data from the national health and nutrition examination survey 2007 to 2008.

Medicine
PURPOSE: A possible association between metformin use and the development of prostate cancer (PCa) has been reported. However, there is limited information on the impact of long-term metformin use on serum prostate-specific antigen (PSA) levels. We i...

Lactate levels and risk of lactic acidosis with metformin in diabetic kidney disease patients.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Metformin as an oral antidiabetic drug (OAD) is not recommended in renal failure due to the presumed risk of lactic acidosis though it has advantages in cardiovascular protection with a low risk of hypoglycemia. Few studies have measured lactic acid ...

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide ex...

Machine Learning Helps Identify New Drug Mechanisms in Triple-Negative Breast Cancer.

IEEE transactions on nanobioscience
This paper demonstrates the ability of mach- ine learning approaches to identify a few genes among the 23,398 genes of the human genome to experiment on in the laboratory to establish new drug mechanisms. As a case study, this paper uses MDA-MB-231 b...

Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes.

Computers in biology and medicine
OBJECTIVE: Metformin is the preferred first-line medication for management of type 2 diabetes and prediabetes. However, over a third of patients experience primary or secondary therapeutic failure. We developed machine learning models to predict whic...

Using Unlabeled Data to Discover Bivariate Causality with Deep Restricted Boltzmann Machines.

IEEE/ACM transactions on computational biology and bioinformatics
An important question in microbiology is whether treatment causes changes in gut flora, and whether it also affects metabolism. The reconstruction of causal relations purely from non-temporal observational data is challenging. We address the problem ...

Predicting diabetes second-line therapy initiation in the Australian population via time span-guided neural attention network.

PloS one
INTRODUCTION: The first line of treatment for people with Diabetes mellitus is metformin. However, over the course of the disease metformin may fail to achieve appropriate glycemic control, and a second-line therapy may become necessary. In this pape...

Simultaneous ultra-trace quantitative colorimetric determination of antidiabetic drugs based on gold nanoparticles aggregation using multivariate calibration and neural network methods.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, a simple and rapid method was investigated for the simultaneous ultra-trace colorimetric determination of Metformin (MET) and Sitagliptin (STG) based on the aggregation of gold nanoparticles (AuNPs). The Morphology and size distributio...