Exercise training reverses myocardial dysfunction induced by CaMKIIδC overexpression by restoring Ca2+-homeostasis

Several conditions of heart disease, including heart failure and diabetic cardiomyopathy, are associated with upregulation of cytosolic Ca2+/calmodulin-dependent protein kinase II (CaMKIIδC) activity. In the heart, CaMKIIδC isoform targets several proteins involved in intracellular Ca2+ homeostasis. We hypothesized that high-intensity endurance training activates mechanisms that enable a rescue of dysfunctional cardiomyocyte Ca2+ handling and thereby ameliorate cardiac dysfunction despite continuous and chronic elevated levels of CaMKIIδC. CaMKIIδC transgenic (TG) and wild-type (WT) mice performed aerobic interval exercise training over 6 wk. Cardiac function was measured by echocardiography in vivo, and cardiomyocyte shortening and intracellular Ca2+ handling were measured in vitro. TG mice had reduced global cardiac function, cardiomyocyte shortening (47% reduced compared with WT, P < 0.01), and impaired Ca2+ homeostasis. Despite no change in the chronic elevated levels of CaMKIIδC, exercise improved global cardiac function, restored cardiomyocyte shortening, and reestablished Ca2+ homeostasis to values not different from WT. The key features to explain restored Ca2+ homeostasis after exercise training were increased L-type Ca2+ current density and flux by 79 and 85%, respectively (P < 0.01), increased sarcoplasmic reticulum (SR) Ca2+-ATPase (SERCA2a) function by 50% (P < 0.01), and reduced diastolic SR Ca2+ leak by 73% (P < 0.01), compared with sedentary TG mice. In conclusion, exercise training improves global cardiac function as well as cardiomyocyte function in the presence of a maintained high CaMKII activity. The main mechanisms of exercise-induced improvements in TG CaMKIIδC mice are mediated via increased L-type Ca2+ channel currents and improved SR Ca2+ handling by restoration of SERCA2a function in addition to reduced diastolic SR Ca2+ leak

Liver Injury Indicating Fatty Liver but Not Serologic NASH Marker Improves under Metformin Treatment in Polycystic Ovary Syndrome

Objective. Polycystic ovary syndrome (PCOS) is associated with obesity and insulin resistance (IR), key features of nonalcoholic steatohepatitis (NASH). Cytokeratin 18 fragments (M30) have been established as a serum marker for NASH. The insulin sensitizer metformin improves hepatic IR. This study evaluates the influence of MF on serologic NASH (sNASH) in patients with PCOS. Patients and Methods. In 89 patients, metabolic parameters, liver injury indicating fatty liver (LIFL), and M30 were assessed at baseline and after metformin treatment. Patients with initial IR were subdivided into dissolved (PCOS-exIR) and persistent IR (PCOS-PIR) after treatment and compared to an initially insulin sensitive PCOS group (PCOS-C). Results. Improvement of LIFL prevalence could be seen in PCOS-C and PCOS-exIR compared to PCOS-PIR (−19.4, resp., −12.0% versus 7.2%, Chi2 = 29.5, P<0.001) without change in sNASH prevalence. In PCOS-PIR, ALT levels increased significantly accompanied by a nominal, nonsignificant M30 increase. Conclusions. Metformin improves LIFL in subgroups of patients with PCOS without influencing sNASH. This could either indicate a missing effect of metformin on NAFLD or slowed disease progression. Further studies are needed to elucidate NAFLD in the context of PCOS and potential therapeutic options

Patterns of Resilience during Socioeconomic Crises among Households in Europe (RESCuE): Concept, Objectives and Work. Packages of an EU FP 7 Project

Since 2008, Europe has been shaken by an ongoing crisis. If relevant parts of populations are exposed to socioeconomic risks, it is a distinctive characteristic of European political ethics that they must not be left alone, but should be subject to support and solidarity by budget support policy, economic development policies and social policy at different levels. But, in analogy with medical and psychological findings, some parts of the vulnerable population, although experiencing the same living conditions as others, are developing resilience, which in our context means that they perform social, economic and cultural practices and habits which protect them from suffer and harm and support sustainable patterns of coping and adaption. This resilience to socioeconomic crises at household levels is the focus of the project. It can consist of identity patterns, knowledge, family or community relations, cultural and social as well as economic practices, be they formal or informal. Welfare states, labour markets and economic policies at both macro or meso level form the context or ‘environment’ of those resilience patterns. For reasons of coping with the crisis without leaving the common ground of the implicit European social model (or the unwritten confession to the welfare state) under extremely bad monetary conditions in many countries, and for reasons of maintaining quality of life and improving social policy, it is a highly interesting perspective to learn from emergent processes of resilience development and their preconditions. Thus, the main questions are directed at understanding patterns and dimensions of resilience at micro-/household level in different types of European member and neighbour states accounting for regional varieties, relevant internal and external conditions and resources as well as influences on these patterns by social, economic or labour market policy as well as legal regulations

Cross-Sectional and Longitudinal MRI Brain Scans Reveal Accelerated Brain Aging in Multiple Sclerosis

Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By combining longitudinal MRI-based brain morphometry and brain age estimation using machine learning, we tested the hypothesis that MS patients have higher brain age relative to chronological age than healthy controls (HC) and that longitudinal rate of brain aging in MS patients is associated with clinical course and severity. Seventy-six MS patients [71% females, mean age 34.8 years (range 21–49) at inclusion] were examined with brain MRI at three time points with a mean total follow up period of 4.4 years (±0.4 years). We used additional cross-sectional MRI data from 235 HC for case-control comparison. We applied a machine learning model trained on an independent set of 3,208 HC to estimate individual brain age and to calculate the difference between estimated and chronological age, termed brain age gap (BAG). We also assessed the longitudinal change rate in BAG in individuals with MS. MS patients showed significantly higher BAG (4.4 ± 6.6 years) compared to HC (Cohen's D = 0.69, p = 4.0 × 10−6). Longitudinal estimates of BAG in MS patients showed high reliability and suggested an accelerated rate of brain aging corresponding to an annual increase of 0.41 (SE = 0.15) years compared to chronological aging (p = 0.008). Multiple regression analyses revealed higher rate of brain aging in patients with more brain atrophy (Cohen's D = 0.86, p = 4.3 × 10−15) and increased white matter lesion load (WMLL) (Cohen's D = 0.55, p = 0.015). On average, patients with MS had significantly higher BAG compared to HC. Progressive brain aging in patients with MS was related to brain atrophy and increased WMLL. No significant clinical associations were found in our sample, future studies are warranted on this matter. Brain age estimation is a promising method for evaluation of subtle brain changes in MS, which is important for predicting clinical outcome and guide choice of intervention

Novel algorithm for non-invasive assessment of fibrosis in NAFLD.

IntroductionVarious conditions of liver disease and the downsides of liver biopsy call for a non-invasive option to assess liver fibrosis. A non-invasive score would be especially useful to identify patients with slow advancing fibrotic processes, as in Non-Alcoholic Fatty Liver Disease (NAFLD), which should undergo histological examination for fibrosis.Patients/methodsClassic liver serum parameters, hyaluronic acid (HA) and cell death markers of 126 patients undergoing bariatric surgery for morbid obesity were analyzed by machine learning techniques (logistic regression, k-nearest neighbors, linear support vector machines, rule-based systems, decision trees and random forest (RF)). Specificity, sensitivity and accuracy of the evaluated datasets to predict fibrosis were assessed.ResultsNone of the single parameters (ALT, AST, M30, M60, HA) did differ significantly between patients with a fibrosis score 1 or 2. However, combining these parameters using RFs reached 79% accuracy in fibrosis prediction with a sensitivity of more than 60% and specificity of 77%. Moreover, RFs identified the cell death markers M30 and M65 as more important for the decision than the classic liver parameters.ConclusionOn the basis of serum parameters the generation of a fibrosis scoring system seems feasible, even when only marginally fibrotic tissue is available. Prospective evaluation of novel markers, i.e. cell death parameters, should be performed to identify an optimal set of fibrosis predictors

Eye and hand motor interactions with the Symbol Digit Modalities Test in early multiple sclerosis

Purpose Eye and hand motor dysfunction may be present early in the disease course of relapsing-remitting multiple sclerosis (RRMS), and can affect the results on visual and written cognitive tests. We aimed to test for differences in saccadic initiation time (SI time) between RRMS patients and healthy controls, and whether SI time and hand motor speed interacted with the written version of the Symbol Digit Modalities Test (wSDMT). Methods Patients with RRMS (N=44, age 35.1±7.3 years), time since diagnosis <3 years and matched controls (N=41, age 33.2±6.8 years) were examined with ophthalmological, neurological and neuropsychological tests, as well as structural MRI (white matter lesion load (WMLL) and brainstem lesions), visual evoked potentials (VEP) and eye-tracker examinations of saccades. Results SI time was longer in RRMS than controls (p<0.05). SI time was not related to the Paced Auditory Serial Addition Test (PASAT), WMLL or to the presence of brainstem lesions. 9 hole peg test (9HP) correlated significantly with WMLL (r=0.58, p<0.01). Both SI time and 9HP correlated negatively with the results of wSDMT (r=−0.32, p<0.05, r=−0.47, p<0.01), but none correlated with the results of PASAT. Conclusions RRMS patients have an increased SI time compared to controls. Cognitive tests results, exemplified by the wSDMT, may be confounded by eye and hand motor function

Clinical Study Liver Injury Indicating Fatty Liver but Not Serologic NASH Marker Improves under Metformin Treatment in Polycystic Ovary Syndrome

Objective. Polycystic ovary syndrome (PCOS) is associated with obesity and insulin resistance (IR), key features of nonalcoholic steatohepatitis (NASH). Cytokeratin 18 fragments (M30) have been established as a serum marker for NASH. The insulin sensitizer metformin improves hepatic IR. This study evaluates the influence of MF on serologic NASH (sNASH) in patients with PCOS. Patients and Methods. In 89 patients, metabolic parameters, liver injury indicating fatty liver (LIFL), and M30 were assessed at baseline and after metformin treatment. Patients with initial IR were subdivided into dissolved (PCOS-exIR) and persistent IR (PCOS-PIR) after treatment and compared to an initially insulin sensitive PCOS group (PCOS-C). Results. Improvement of LIFL prevalence could be seen in PCOS-C and PCOS-exIR compared to PCOS-PIR (−19.4, resp., −12.0% versus 7.2%, Chi 2 = 29.5, &lt; 0.001) without change in sNASH prevalence. In PCOS-PIR, ALT levels increased significantly accompanied by a nominal, nonsignificant M30 increase. Conclusions. Metformin improves LIFL in subgroups of patients with PCOS without influencing sNASH. This could either indicate a missing effect of metformin on NAFLD or slowed disease progression. Further studies are needed to elucidate NAFLD in the context of PCOS and potential therapeutic options

Decision Tree.

<p>The decision tree (DT) focuses on the parameters M30, M65 and AST (GOT), which is in partial agreement with the RFs. At the first level, the DT focuses on M30. If the M30 value for a given sample is less than 472.7, it is assigned to the negative class (0). If the M30 value is greater than 472.7, it is transferred to the next level that uses M65. If the M65 value for the given sample is greater than 462.1, it is assigned to the negative class, otherwise it is transferred to the last level. The last level in the DT focuses on GOT. If the GOT value for the given sample is less than 27.5, the sample is assigned as negative, otherwise as a positive sample (1).</p