Diabetes is a strong risk factor for premature and severe stroke. The GLP-1R (glucagon-like peptide-1 receptor) agonist Ex-4 (exendin-4) is a drug for the treatment of T2D (Type 2 diabetes) that may also have neuroprotective effects. The aim of the present study was to determine the efficacy of Ex-4 against stroke in diabetes by using a diabetic animal model, a drug administration paradigm and a dose that mimics a diabetic patient on Ex-4 therapy. Furthermore, we investigated inflammation and neurogenesis as potential cellular mechanisms underlying the Ex-4 efficacy. A total of seven 9-month-old Type 2 diabetic Goto–Kakizaki rats were treated peripherally for 4 weeks with Ex-4 at 0.1, 1 or 5 μg/kg of body weight before inducing stroke by transient middle cerebral artery occlusion and for 2–4 weeks thereafter. The severity of ischaemic damage was measured by evaluation of stroke volume and by stereological counting of neurons in the striatum and cortex. We also quantitatively evaluated stroke-induced inflammation, stem cell proliferation and neurogenesis. We show a profound anti-stroke efficacy of the clinical dose of Ex-4 in diabetic rats, an arrested microglia infiltration and an increase of stroke-induced neural stem cell proliferation and neuroblast formation, while stroke-induced neurogenesis was not affected by Ex-4. The results show a pronounced anti-stroke, neuroprotective and anti-inflammatory effect of peripheral and chronic Ex-4 treatment in middle-aged diabetic animals in a preclinical setting that has the potential to mimic the clinical treatment. Our results should provide strong impetus to further investigate GLP-1R agonists for their neuroprotective action in diabetes, and for their possible use as anti-stroke medication in non-diabetic conditions.

BackgroundGreen tea was suggested as a therapeutic agent for the treatment of diabetes more than 70 years ago, but the mechanisms behind its antidiabetic effect remains elusive. In this work, we address this issue by feeding a green tea extract (TEAVIGO™) with a high content of epigallocatechin gallate (EGCG) or the thiazolidinedione PPAR-γ agonist rosiglitazone, as positive control, to db/db mice, an animal model for diabetes.MethodsYoung (7 week-old) db/db mice were randomized and assigned to receive diets supplemented with or without EGCG or rosiglitazone for 10 weeks. Fasting blood glucose, body weight and food intake was measured along the treatment. Glucose and insulin levels were determined during an oral glucose tolerance test after 10 weeks of treatment. Pancreata were sampled at the end of the study for blinded histomorphometric analysis. Islets were isolated and their mRNA expression analyzed by quantitative RT-PCR.ResultsThe results show that, in db/db mice, EGCG improves glucose tolerance and increases glucose-stimulated insulin secretion. EGCG supplementation reduces the number of pathologically changed islets of Langerhans, increases the number and the size of islets, and heightens pancreatic endocrine area. These effects occurred in parallel with a reduction in islet endoplasmic reticulum stress markers, possibly linked to the antioxidative capacity of EGCG.ConclusionsThis study shows that the green tea extract EGCG markedly preserves islet structure and enhances glucose tolerance in genetically diabetic mice. Dietary supplementation with EGCG could potentially contribute to nutritional strategies for the prevention and treatment of type 2 diabetes.

Background:The roles of PP5 in normal biology are poorly understood. Results: To help evaluate the biological actions of PP5, a Cre/loxP-conditional mouse line was generated. Conclusion: In response to UV light, PP5 regulates the phosphorylation of Chk1 at Ser-345. Significance: Understanding the biological roles for phosphatases is critical for understanding the role of reversible phosphorylation in the control of signaling networks.

ObjectiveRenal conservation (retention) of fluid might affect the outcome of hospital care and can be indicated by increased urinary concentrations of metabolic waste products. We obtained a reference material for further studies by exploring the prevalence of fluid retention in a healthy population.MethodsSpot urine sampling was performed in 300 healthy hospital workers. A previously validated algorithm summarized the urine-specific gravity, osmolality, creatinine, and color to a fluid retention index (FRI), where 4.0 is the cut-off for fluid retention consistent with dehydration. In 50 of the volunteers, we also studied the relationships between FRI, plasma osmolality, and water-retaining hormones.ResultsThe cut-off for fluid retention (FRI ≥ 4.0) was reached by 38% of the population. No correlation was found between the FRI and the time of the day of urine sample collection, and the FRI was only marginally correlated with the time period spent without fluid intake. Volunteers with fluid retention were younger, generally men, and more often had albuminuria (88% vs. 34%, P < 0.001). Plasma osmolality and plasma sodium were somewhat higher in those with a high FRI (mean 294.8 vs. 293.4 mosmol/kg and 140.3 vs. 139.9 mmol/l). Plasma vasopressin was consistently below the limit of detection, and the plasma cortisol, aldosterone, and renin concentrations were similar in subjects with a high or low FRI. The very highest FRI values (≥ 5.0, N = 61) were always accompanied by albuminuria.ConclusionFluid retention consistent with moderate dehydration is common in healthy staff working in a Swedish hospital.

Aims/hypothesis During the development of type 2 diabetes mellitus, beta cells are often exposed to a high glucose/ hyperlipidaemic environment, in which the levels of reactive oxygen species (ROS) are elevated. In turn, ROS can trigger an apoptotic response leading to beta cell death, by activating mitogen-activated protein kinase (MAPK) signalling cascades. Here we test the hypothesis that serine/threonine protein phosphatase 5 (PP5) acts to suppress proapoptotic c-Jun N-terminal kinase (JNK) signalling in beta cells. Methods Ppp5c−/− and Ppp5c +/+ mice were subjected to intraperitoneal glucose (IPGTT)

Accurate measurements of metabolic fluxes in living cells are central to metabolism research and metabolic engineering. The gold standard method is model-based metabolic flux analysis (MFA), where fluxes are estimated indirectly from mass isotopomer data with the use of a mathematical model of the metabolic network. A critical step in MFA is model selection: choosing what compartments, metabolites, and reactions to include in the metabolic network model. Model selection is often done informally during the modelling process, based on the same data that is used for model fitting (estimation data). This can lead to either overly complex models (overfitting) or too simple ones (underfitting), in both cases resulting in poor flux estimates. Here, we propose a method for model selection based on independent validation data. We demonstrate in simulation studies that this method consistently chooses the correct model in a way that is independent on errors in measurement uncertainty. This independence is beneficial, since estimating the true magnitude of these errors can be difficult. In contrast, commonly used model selection methods based on the χ2-test choose different model structures depending on the believed measurement uncertainty; this can lead to errors in flux estimates, especially when the magnitude of the error is substantially off. We present a new approach for quantification of prediction uncertainty of mass isotopomer distributions in other labelling experiments, to check for problems with too much or too little novelty in the validation data. Finally, in an isotope tracing study on human mammary epithelial cells, the validation-based model selection method identified pyruvate carboxylase as a key model component. Our results argue that validation-based model selection should be an integral part of MFA model development.

The role of serine/threonine protein phosphatase 5 (PP5) in the development of obesity and insulin resistance associated with high-fat diet-feeding (HFD) was examined using PP5-deficient mice (Ppp5c(-/-)). Despite similar caloric intake, Ppp5c(-/-) mice on HFD gained markedly less weight and did not accumulate visceral fat compared to wild-type littermates (Ppp5c(+/+)). On a control diet, Ppp5c(-/-) mice had markedly improved glucose control compared to Ppp5c(+/+) mice, an effect diminished by HFD. However, even after 10 weeks of HFD glucose control in Ppp5c(-/-) mice was similar to that observed in Ppp5c(+/+) mice on the control diet. Thus, PP5 deficiency confers protection against HFD-induced weight gain in mice.

Summary Studying metabolic activities in living cells is crucial for understanding human metabolism, but facile methods for profiling metabolic activities in an unbiased, hypothesis-free manner are still lacking. To address this need, we here introduce the deep labeling method, which combines a custom 13C medium with high-resolution mass spectrometry. A proof-of-principle study on human cancer cells demonstrates that deep labeling can identify hundreds of endogenous metabolites as well as active and inactive pathways. For example, protein and nucleic acids were almost exclusively de novo synthesized, while lipids were partly derived from serum; synthesis of cysteine, carnitine and creatine was absent, suggesting metabolic dependencies; and branched-chain keto acids (BCKA) were formed and metabolized to short-chain acylcarnitines, but did not enter the TCA cycle. Remarkably, BCKA could substitute for essential amino acids to support growth. The deep labeling method may prove useful to map metabolic phenotypes across a range of cell types and conditions.