Diminished Sphingolipid Metabolism, a Hallmark of Future Type 2 Diabetes Pathogenesis, Is Linked to Pancreatic β Cell Dysfunction.

Gestational diabetes mellitus (GDM) is the top risk factor for future type 2 diabetes (T2D) development. Ethnicity profoundly influences who will transition from GDM to T2D, with high risk observed in Hispanic women. To better understand this risk, a nested 1:1 pair-matched, Hispanic-specific, case-control design was applied to a prospective cohort with GDM history.

The magnesium transporter NIPAL1 is a pancreatic islet-expressed protein that conditionally impacts insulin secretion.

Type 2 diabetes is a chronic metabolic disease characterized by pancreatic β-cell dysfunction and peripheral insulin resistance. Among individuals with type 2 diabetes, ∼30% exhibit hypomagnesemia. Hypomagnesemia has been linked to insulin resistance through reduced tyrosine kinase activity of the insulin receptor; however, its impact on pancreatic β-cell function is unknown.

Isoniazid and host immune system interactions: A proposal for a novel comprehensive mode of action.

The known mode of action of isoniazid (INH) is to inhibit bacterial cell wall synthesis following activation by the bacterial catalase-peroxidase enzyme KatG in Mycobacterium tuberculosis (Mtb). This simplistic model fails to explain (a) how isoniazid penetrates waxy granulomas with its very low lipophilicity, (b) how isoniazid kills latent Mtb lacking a typical cell wall, and (c) why isoniazid treatment time is remarkably long in contrast to most other antibiotics. To address these questions, a novel comprehensive mode of action of isoniazid has been proposed here.

Unbiased data analytic strategies to improve biomarker discovery in precision medicine.

Omics technologies promised improved biomarker discovery for precision medicine. The foremost problem of discovered biomarkers is irreproducibility between patient cohorts. From a data analytics perspective, the main reason for these failures is bias in statistical approaches and overfitting resulting from batch effects and confounding factors.

Correction to: The discovery of novel predictive biomarkers and early-stage pathophysiology for the transition from gestational diabetes to type 2 diabetes.

Unfortunately, the graph in Fig. 5f became misaligned during typesetting.

The discovery of novel predictive biomarkers and early-stage pathophysiology for the transition from gestational diabetes to type 2 diabetes.

Aims/hypothesis: Gestational diabetes mellitus (GDM) affects up to 20% of pregnancies, and almost half of the women affected progress to type 2 diabetes later in life, making GDM the most significant risk factor for the development of future type 2 diabetes. An accurate prediction of future type 2 diabetes risk in the early postpartum period after GDM would allow for timely interventions to prevent or delay type 2 diabetes. In addition, new targets for interventions may be revealed by understanding the underlying pathophysiology of the transition from GDM to type 2 diabetes.