Lentiviral Engineered Fibroblasts Expressing Codon Optimized COL7A1 Restore Anchoring Fibrils in RDEB

Cells therapies, engineered to secrete replacement proteins, are being developed to ameliorate otherwise debilitating diseases. Recessive dystrophic epidermolysis bullosa (RDEB) is caused by defects of type VII collagen (C7), a protein essential for anchoring fibril formation at the dermal-epidermal junction (DEJ). Whilst allogeneic fibroblasts injected directly into the dermis can mediate transient disease modulation, autologous gene-modified fibroblasts should evade immunological rejection and support sustained delivery of C7 at the DEJ. We demonstrate the feasibility of such an approach using a therapeutic grade, self-inactivating-lentiviral vector, encoding codon optimized COL7A1, to transduce RDEB fibroblasts under conditions suitable for clinical application. Expression and secretion of C7 was confirmed, with transduced cells exhibiting supra-normal levels of protein expression and ex vivo migration of fibroblasts was restored in functional assays. Gene modified RDEB fibroblasts also deposited C7 at the DEJ of human RDEB skin xenografts placed on NOD-scid IL2Rgamma(null) recipients, with reconstruction of human epidermal structure and regeneration of anchoring fibrils at the DEJ. Fibroblast mediated restoration of protein and structural defects in this RDEB model strongly supports proposed therapeutic applications in man

Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques

We evaluated the ability of simple and complex surrogate-indices to identify individuals from an overweight/obese cohort with hepatic insulin-resistance (HEP-IR). Five indices, one previously defined and four newly generated through step-wise linear regression, were created against a single-cohort sample of 77 extensively characterised participants with the metabolic syndrome (age 55.6±1.0 years, BMI 31.5±0.4 kg/m2; 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6–62H2] glucose during fasting and euglycemic-hyperinsulinemic clamps and expressed as EGP*fasting plasma insulin. Complex measures were incorporated into the model, including various non-standard biomarkers and the measurement of body-fat distribution and liver-fat, to further improve the predictive capability of the index. Validation was performed against a data set of the same subjects after an isoenergetic dietary intervention (4 arms, diets varying in protein and fiber content versus control). All five indices produced comparable prediction of HEP-IR, explaining 39–56% of the variance, depending on regression variable combination. The validation of the regression equations showed little variation between the different proposed indices (r2 = 27–32%) on a matched dataset. New complex indices encompassing advanced measurement techniques offered an improved correlation (r = 0.75, P<0.001). However, when validated against the alternative dataset all indices performed comparably with the standard homeostasis model assessment for insulin resistance (HOMA-IR) (r = 0.54, P<0.001). Thus, simple estimates of HEP-IR performed comparable to more complex indices and could be an efficient and cost effective approach in large epidemiological investigations

Factors affecting commencement and cessation of smoking behaviour in Malaysian adults

<p>Abstract</p> <p>Background</p> <p>Tobacco consumption peak in developed countries has passed, however, it is on the increase in many developing countries. Apart from cigarettes, consumption of local hand-rolled cigarettes such as <it>bidi </it>and <it>rokok daun </it>are prevalent in specific communities. Although factors associated with smoking initiation and cessation has been investigated elsewhere, the only available data for Malaysia is on prevalence. This study aims to investigate factors associated with smoking initiation and cessation which is imperative in designing intervention programs.</p> <p>Methods</p> <p>Data were collected from 11,697 adults by trained recording clerks on sociodemographic characteristics, practice of other risk habit and details of smoking such as type, duration and frequency. Smoking commencement and cessation were analyzed using the Kaplan-Meier estimates and log-rank tests. Univariate and multivariate Cox proportional hazard regression models were used to calculate the hazard rate ratios.</p> <p>Results</p> <p>Males had a much higher prevalence of the habit (61.7%) as compared to females (5.8%). Cessation was found to be most common among the Chinese and those regularly consuming alcoholic beverages. Kaplan-Meier plot shows that although males are more likely to start smoking, females are found to be less likely to stop. History of betel quid chewing and alcohol consumption significantly increase the likelihood of commencement (p < 0.0001), while cessation was least likely among Indians, current quid chewers and kretek users (p < 0.01).</p> <p>Conclusions</p> <p>Gender, ethnicity, history of quid chewing and alcohol consumption have been found to be important factors in smoking commencement; while ethnicity, betel quid chewing and type of tobacco smoked influences cessation.</p

Actos Now for the prevention of diabetes (ACT NOW) study

Abstract Background Impaired glucose tolerance (IGT) is a prediabetic state. If IGT can be prevented from progressing to overt diabetes, hyperglycemia-related complications can be avoided. The purpose of the present study was to examine whether pioglitazone (ACTOS®) can prevent progression of IGT to type 2 diabetes mellitus (T2DM) in a prospective randomized, double blind, placebo controlled trial. Methods/Design 602 IGT subjects were identified with OGTT (2-hour plasma glucose = 140–199 mg/dl). In addition, IGT subjects were required to have FPG = 95–125 mg/dl and at least one other high risk characteristic. Prior to randomization all subjects had measurement of ankle-arm blood pressure, systolic/diastolic blood pressure, HbA1C, lipid profile and a subset had frequently sampled intravenous glucose tolerance test (FSIVGTT), DEXA, and ultrasound determination of carotid intima-media thickness (IMT). Following this, subjects were randomized to receive pioglitazone (45 mg/day) or placebo, and returned every 2–3 months for FPG determination and annually for OGTT. Repeat carotid IMT measurement was performed at 18 months and study end. Recruitment took place over 24 months, and subjects were followed for an additional 24 months. At study end (48 months) or at time of diagnosis of diabetes the OGTT, FSIVGTT, DEXA, carotid IMT, and all other measurements were repeated. Primary endpoint is conversion of IGT to T2DM based upon FPG ≥ 126 or 2-hour PG ≥ 200 mg/dl. Secondary endpoints include whether pioglitazone can: (i) improve glycemic control (ii) enhance insulin sensitivity, (iii) augment beta cell function, (iv) improve risk factors for cardiovascular disease, (v) cause regression/slow progression of carotid IMT, (vi) revert newly diagnosed diabetes to normal glucose tolerance. Conclusion ACT NOW is designed to determine if pioglitazone can prevent/delay progression to diabetes in high risk IGT subjects, and to define the mechanisms (improved insulin sensitivity and/or enhanced beta cell function) via which pioglitazone exerts its beneficial effect on glucose metabolism to prevent/delay onset of T2DM. Trial Registration clinical trials.gov identifier: NCT0022096

Insulin resistance, lipotoxicity, type 2 diabetes and atherosclerosis: the missing links. The Claude Bernard Lecture 2009

Insulin resistance is a hallmark of type 2 diabetes mellitus and is associated with a metabolic and cardiovascular cluster of disorders (dyslipidaemia, hypertension, obesity [especially visceral], glucose intolerance, endothelial dysfunction), each of which is an independent risk factor for cardiovascular disease (CVD). Multiple prospective studies have documented an association between insulin resistance and accelerated CVD in patients with type 2 diabetes, as well as in non-diabetic individuals. The molecular causes of insulin resistance, i.e. impaired insulin signalling through the phosphoinositol-3 kinase pathway with intact signalling through the mitogen-activated protein kinase pathway, are responsible for the impairment in insulin-stimulated glucose metabolism and contribute to the accelerated rate of CVD in type 2 diabetes patients. The current epidemic of diabetes is being driven by the obesity epidemic, which represents a state of tissue fat overload. Accumulation of toxic lipid metabolites (fatty acyl CoA, diacylglycerol, ceramide) in muscle, liver, adipocytes, beta cells and arterial tissues contributes to insulin resistance, beta cell dysfunction and accelerated atherosclerosis, respectively, in type 2 diabetes. Treatment with thiazolidinediones mobilises fat out of tissues, leading to enhanced insulin sensitivity, improved beta cell function and decreased atherogenesis. Insulin resistance and lipotoxicity represent the missing links (beyond the classical cardiovascular risk factors) that help explain the accelerated rate of CVD in type 2 diabetic patients

A Novel High Throughput Assay for Anthelmintic Drug Screening and Resistance Diagnosis by Real-Time Monitoring of Parasite Motility

Parasitic worms cause untold morbidity and mortality on billions of people and livestock. Drugs are available but resistance is problematic in livestock parasites and is a looming threat for human helminths. Currently, new drug discovery and resistance monitoring is hindered as drug efficacy is assessed by observing motility or development of parasites using laborious, subjective, low-throughput methods evaluated by eye using microscopy. Here we describe a novel application for a cell monitoring device (xCELLigence) that can simply and objectively assess real time anti-parasite efficacy of drugs on eggs, larvae and adults in a fully automated, label-free, high-throughput fashion. This technique overcomes the current low-throughput bottleneck in anthelmintic drug development and resistance detection pipelines. The widespread use of this device to screen for new therapeutics or emerging drug resistance will be an invaluable asset in the fight against human, animal and plant parasitic helminths and other pathogens that plague our planet

Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics

[EN] Complexity analysis of glucose time series with Detrended Fluctuation Analysis (DFA) has been proved to be useful for the prediction of type 2 diabetes mellitus (T2DM) development. We propose a modified DFA algorithm, review some of its characteristics and compare it with other metrics derived from continuous glucose monitorization in this setting. Several issues of the DFA algorithm were evaluated: (1) Time windowing: the best predictive value was obtained including all time-windows from 15 minutes to 24 hours. (2) Influence of circadian rhythms: for 48-hour glucometries, DFA alpha scaling exponent was calculated on 24hour sliding segments (1-hour gap, 23-hour overlap), with a median coefficient of variation of 3.2%, which suggests that analysing time series of at least 24-hour length avoids the influence of circadian rhythms. (3) Influence of pretreatment of the time series through integration: DFA without integration was more sensitive to the introduction of white noise and it showed significant predictive power to forecast the development of T2DM, while the pretreated time series did not. (4) Robustness of an interpolation algorithm for missing values: The modified DFA algorithm evaluates the percentage of missing values in a time series. Establishing a 2% error threshold, we estimated the number and length of missing segments that could be admitted to consider a time series as suitable for DFA analysis. For comparison with other metrics, a Principal Component Analysis was performed and the results neatly tease out four different components. The first vector carries information concerned with variability, the second represents mainly DFA alpha exponent, while the third and fourth vectors carry essentially information related to the two "pre-diabetic behaviours" (impaired fasting glucose and impaired glucose tolerance). The scaling exponent obtained with the modified DFA algorithm proposed has significant predictive power for the development of T2DM in a high-risk population compared with other variability metrics or with the standard DFA algorithm.This study has been funded by Instituto de Salud Carlos III through the project PI17/00856 (Co-funded by the European Regional Development Fund, A way to make Europe). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Colás, A.; Vigil, L.; Vargas, B.; Cuesta Frau, D.; Varela, M. (2019). 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Water T2 as an early, global and practical biomarker for metabolic syndrome: an observational cross-sectional study

Background: Metabolic syndrome (MetS) is a highly prevalent condition that identifies individuals at risk for type 2 diabetes mellitus and atherosclerotic cardiovascular disease. Prevention of these diseases relies on early detection and intervention in order to preserve pancreatic β-cells and arterial wall integrity. Yet, the clinical criteria for MetS are insensitive to the early-stage insulin resistance, inflammation, cholesterol and clotting factor abnormalities that char- acterize the progression toward type 2 diabetes and atherosclerosis. Here we report the discovery and initial charac- terization of an atypical new biomarker that detects these early conditions with just one measurement. Methods: Water T2, measured in a few minutes using benchtop nuclear magnetic resonance relaxometry, is exqui- sitely sensitive to metabolic shifts in the blood proteome. In an observational cross-sectional study of 72 non-diabetic human subjects, the association of plasma and serum water T2 values with over 130 blood biomarkers was analyzed using bivariate, multivariate and logistic regression. Results: Plasma and serum water T2 exhibited strong bivariate correlations with markers of insulin, lipids, inflamma- tion, coagulation and electrolyte balance. After correcting for confounders, low water T2 values were independently and additively associated with fasting hyperinsulinemia, dyslipidemia and subclinical inflammation. Plasma water T2 exhibited 100% sensitivity and 87% specificity for detecting early insulin resistance in normoglycemic subjects, as defined by the McAuley Index. Sixteen normoglycemic subjects with early metabolic abnormalities (22% of the study population) were identified by low water T2 values. Thirteen of the 16 did not meet the harmonized clinical criteria for metabolic syndrome and would have been missed by conventional screening for diabetes risk. Low water T2 values were associated with increases in the mean concentrations of 6 of the 16 most abundant acute phase proteins and lipoproteins in plasma. Conclusions: Water T2 detects a constellation of early abnormalities associated with metabolic syndrome, provid- ing a global view of an individual’s metabolic health. It circumvents the pitfalls associated with fasting glucose and hemoglobin A1c and the limitations of the current clinical criteria for metabolic syndrome. Water T2 shows promise as an early, global and practical screening tool for the identification of individuals at risk for diabetes and atherosclerosis

A Functional Variant of the Dimethylarginine Dimethylaminohydrolase-2 Gene Is Associated with Insulin Sensitivity

Background: Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of endothelial nitric oxide synthase, which was associated with insulin resistance. Dimethylarginine dimethylaminohydrolase (DDAH) is the major determinant of plasma ADMA. Examining data from the DIAGRAM+ (Diabetes Genetics Replication And Meta-analysis), we identified a variant (rs9267551) in the DDAH2 gene nominally associated with type 2 diabetes (P =3610 25). Methodology/Principal Findings: initially, we assessed the functional impact of rs9267551 in human endothelial cells (HUVECs), observing that the G allele had a lower transcriptional activity resulting in reduced expression of DDAH2 and decreased NO production in primary HUVECs naturally carrying it. We then proceeded to investigate whether this variant is associated with insulin sensitivity in vivo. To this end, two cohorts of nondiabetic subjects of European ancestry were studied. In sample 1 (n = 958) insulin sensitivity was determined by the insulin sensitivity index (ISI), while in sample 2 (n = 527) it was measured with a euglycemic-hyperinsulinemic clamp. In sample 1, carriers of the GG genotype had lower ISI than carriers of the C allele (67633 vs.79644; P = 0.003 after adjusting for age, gender, and BMI). ADMA levels were higher in subjects carrying the GG genotype than in carriers of the C allele (0.6860.14 vs. 0.5760.14 mmol/l; P = 0.04). In sample 2, glucose disposal was lower in GG carriers as compared with C carriers (9.364.1 vs. 11.064.2 mg6Kg 21 free fat mass6min 21; P = 0.009)