BackgroundMetabolic 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 characterize the progression toward type 2 diabetes and atherosclerosis. Here we report the discovery and initial characterization of an atypical new biomarker that detects these early conditions with just one measurement.MethodsWater T2, measured in a few minutes using benchtop nuclear magnetic resonance relaxometry, is exquisitely 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.ResultsPlasma and serum water T2 exhibited strong bivariate correlations with markers of insulin, lipids, inflammation, 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.ConclusionsWater T2 detects a constellation of early abnormalities associated with metabolic syndrome, providing 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.Electronic supplementary materialThe online version of this article (10.1186/s12967-017-1359-5) contains supplementary material, which is available to authorized users.

BackgroundThe ability to use frozen biobanked samples from cohort studies and clinical trials is critically important for biomarker discovery and validation. Here we investigated whether plasma and serum water transverse relaxation times (T2) from frozen biobanked samples could be used as biomarkers for metabolic syndrome (MetS) and its underlying conditions, specifically insulin resistance, dyslipidemia, and subclinical inflammation.MethodsPlasma and serum aliquots from 44 asymptomatic, non-diabetic human subjects were biobanked at –80°C for 7–9 months. Water T2 measurements were recorded at 37°C on 50 µL of unmodified plasma or serum using benchtop nuclear magnetic resonance relaxometry. The T2 values for freshly drawn and once-frozen-thawed (“frozen”) samples were compared using Huber M-values (M), Lin concordance correlation coefficients (ρc), and Bland–Altman plots. Water T2 values from frozen plasma and serum samples were compared with >130 metabolic biomarkers and analyzed using multi-variable linear/logistic regression and ROC curves.ResultsFrozen plasma water T2 values were highly correlated with fresh (M=0.94, 95% CI 0.89, 0.97) but showed a lower level of agreement (ρc=0.74, 95% CI 0.62, 0.82) because of an average offset of −5.6% (−7.1% for serum). Despite the offset, frozen plasma water T2 was strongly correlated with markers of hyperinsulinemia, dyslipidemia, and inflammation and detected these conditions with 89% sensitivity and 91% specificity (100%/63% for serum). Using optimized cut points, frozen plasma and serum water T2 detected hyperinsulinemia, dyslipidemia, and inflammation in 23 of 44 subjects, including nine with an early stage of metabolic dysregulation that did not meet the clinical thresholds for prediabetes or MetS.ConclusionPlasma and serum water T2 values from once-frozen-thawed biobanked samples detect metabolic dysregulation with high sensitivity and specificity. However, the cut points for frozen biobanked samples must be calibrated independent of those for freshly drawn plasma and serum.

No abstract

BackgroundMetabolic syndrome is a cluster of abnormalities that increases the risk for type 2 diabetes and atherosclerosis. Plasma and serum water T2 from benchtop nuclear magnetic resonance relaxometry are early, global and practical biomarkers for metabolic syndrome and its underlying abnormalities. In a prior study, water T2 was analyzed against ~ 130 strategically selected proteins and metabolites to identify associations with insulin resistance, inflammation and dyslipidemia. In the current study, the analysis was broadened ten-fold using a modified aptamer (SOMAmer) library, enabling an unbiased search for new proteins correlated with water T2 and thus, metabolic health.MethodsWater T2 measurements were recorded using fasting plasma and serum from non-diabetic human subjects. In parallel, plasma samples were analyzed using a SOMAscan assay that employed modified DNA aptamers to determine the relative concentrations of 1310 proteins. A multi-step statistical analysis was performed to identify the biomarkers most predictive of water T2. The steps included Spearman rank correlation, followed by principal components analysis with variable clustering, random forests for biomarker selection, and regression trees for biomarker ranking.ResultsThe multi-step analysis unveiled five new proteins most predictive of water T2: hepatocyte growth factor, receptor tyrosine kinase FLT3, bone sialoprotein 2, glucokinase regulatory protein and endothelial cell-specific molecule 1. Three of the five strongest predictors of water T2 have been previously implicated in cardiometabolic diseases. Hepatocyte growth factor has been associated with incident type 2 diabetes, and endothelial cell specific molecule 1, with atherosclerosis in subjects with diabetes. Glucokinase regulatory protein plays a critical role in hepatic glucose uptake and metabolism and is a drug target for type 2 diabetes. By contrast, receptor tyrosine kinase FLT3 and bone sialoprotein 2 have not been previously associated with metabolic conditions. In addition to the five most predictive biomarkers, the analysis unveiled other strong correlates of water T2 that would not have been identified in a hypothesis-driven biomarker search.ConclusionsThe identification of new proteins associated with water T2 demonstrates the value of this approach to biomarker discovery. It provides new insights into the metabolic significance of water T2 and the pathophysiology of metabolic syndrome.Electronic supplementary materialThe online version of this article (10.1186/s40364-018-0143-x) contains supplementary material, which is available to authorized users.

potential of membrane cholesterol in non-inflamed primary dermal human fibroblasts is z À2.3 kBT relative to crystalline cholesterol. Treating these cells with tumor necrosis factor (TNF-a) for 72 hr results in an increase of the chemical potential. This increase occurs in a dose-dependent manner: modest for 10 ng/ml TNF-a, about 0.8 kBT greater for 20 ng/ml, and only slightly greater for 40 ng/ml. Simultaneous treatment with TNF-a and 50 nM of the antiinflammatory agent dexamethasone abolishes the increase in the chemical potential of cholesterol caused by TNF-a alone. Using 5 ng/ml of interleukin-1b, instead of TNF-a, as a pro-inflammatory agent also resulted in a rise of chemical potential. But the effect was less than that induced by TNF-a; the increase was z 0.5 kBT. These results indicate a possible causative relation between cell inflammation and the chemical potential of plasma membrane cholesterol. Supported by R01 GM101539.

Introduction: The metabolic abnormalities that precede type 2 diabetes progress slowly and in stages. Current evidence-based diabetes prevention programs target individuals in Stage 2 (impaired glucose tolerance or prediabetes). However, by that stage, 70% of pancreatic beta-cell insulin secretory capacity has been lost irreversibly. Thus, it is imperative to identify individuals in Stage I (early insulin resistance syndrome) in order to preserve pancreatic insulin secretion and prevent both diabetes and prediabetes. Early insulin resistance syndrome is characterized by compensatory hyperinsulinemia, dyslipidemia, sub-clinical inflammation and acid-base abnormalities. The nature of the association between these elements is unclear, and different subtypes of insulin resistance syndrome may exist. Hypothesis: We have developed two novel and unconventional biomarkers for characterizing insulin resistance in non-diabetic subjects. One approach is based on dynamic light scattering (DLS) of human serum. The second approach measures the T 2 relaxation time of water in human plasma using compact time-domain NMR relaxometry (TD-NMR). We hypothesize that these methods can detect subtypes, i.e. , insulin resistance with or without inflammation, hypercholesterolemia, or acid-base abnormalities. Methods: Seventy-two asymptomatic non-diabetic human subjects were recruited through an IRB-approved biomarker discovery protocol. Medical histories, anthropomorphic measurements and fasting blood samples were obtained, and over 1300 blood biomarkers were measured on each subject along with DLS and TD-NMR parameters. Bi-variate correlation analyses and multiple regression models were used to analyze continuous variables, and categorical variables were established for insulin resistance, inflammation, acid-base abnormalities and lipid abnormalities. Multiple means comparisons were performed using one-way ANOVA and Tukey-Kramer testing. Results: Plasma water T 2 from TD-NMR was strongly correlated with markers of early insulin resistance syndrome. Multiple regression analysis showed independent contributions from markers of hyperinsulinemia, hypercholesterolemia and inflammation. Multiple means comparisons showed significant differences for insulin resistance with and without inflammation. By contrast, DLS parameters were strongly correlated with insulin markers, but could not distinguish the inflammatory subtypes. Conclusions: Both TD-NMR and DLS are able to detect early insulin resistance in individuals who do not meet the criteria for prediabetes or metabolic syndrome. However, TD-NMR has the unique ability to distinguish inflammatory vs. non-inflammatory subtypes of insulin resistance. Subtyping and risk stratification are important for the design of personalized interventions to prevent diabetes, prediabetes and cardiovascular disease.

Current proteomic strategies exploit the measurement of hundreds-to-thousands of potential biomarkers to establish profiles of disease risk. We propose an alternative strategy - inverse proteomics - which utilizes just one marker to monitor the status of many biomolecules all at once. Water is an attractive surveillance system, as it forms hydrogen bonds with virtually every protein, lipoprotein and metabolite in human blood. Here we show that the mobility of water in plasma and serum samples from apparently healthy human subjects correlates with known markers of inflammation, insulin resistance, dyslipidemia and possibly, oxidative stress. Water mobility is assessed in a six-minute experiment that requires no sample manipulations or chemical reactions. Rather, the spin-spin relaxation time constant (T 2 ) is measured non-invasively using benchtop time-domain nuclear magnetic resonance. The current discovery provides a framework for developing a simple blood test that could identify individuals with hidden risk for diabetes, atherosclerosis and Alzheimer’s disease.

Oral prolonged release systems are manufactured to release the drug in-vivo with privies to enhance bioavailability, diminish untoward effectsand enhance effectiveness of drugs. Microballoons or hollow microspheres are anticipated to persist buoyant in a permanent way upon the gastricingredients. The various formulations comprise unfilled microspheres, powders, capsules, tablets and laminated films. Micro-balloons aredistinctly attaining attention due to their immense significance in the drug targeting to the stomach. These floating micro-balloons have theconvenience that they stay buoyant and circulate uniformly over the gastric ingredients to refrain the variations of gastric emptying and releasethe drug for extended period of time. Multiparticulate particles of low density can efficiently prolong the gastric retention time of drugs. Thisarticle provides an insight of fabrication and methods of evaluation of micro-balloons.