Simulation of Wood Polymer Composites with Finite Element Analysis.

Wood is a cellulosic material that is most abundantly available in nature. Wood has been extensively used as reinforcement in polymer composite materials. Wood polymer composite (WPC) is an environmentally friendly and sustainable material exploited in building and construction within the marine, packaging, housewares, aerospace, and automotive industries. However, the precision of testing equipment for finding the properties of WPCs becomes less feasible compared to experimental analysis due to a high degree of differences in the measurement of properties such as stress, strain and deformation. Thus, evaluating the mechanical properties of WPCs using finite element analysis (FEA) can aid in overcoming the inadequacies in measuring physical properties prior to experimental analyses. Furthermore, the prediction of mechanical properties using simulation tools has evolved to analyze novel material performance under various conditions. The current study aimed to examine the mechanical properties of saw dust-reinforced recycled polypropylene (rPP) through experimentation and FEA. A model was developed using SolidWorks, and simulation was performed in ANSYS to predict the mechanical properties of the WPCs. To validate the obtained results, the simulated static tension test results were confirmed with experimental tension tests, and both assessments were well in accordance with each other. Using FEA to predict material properties could be a cost-effective technique in studying new materials under varied load conditions.

Peracid Oxidation of Unactivated sp3 C-H Bonds: An Important Solvent Effect.

The peracid oxidation of hydrocarbons in chlorinated solvents is a low yielding and poorly selective process. Through a combination of DFT calculations, spectroscopic studies, and kinetic measurement it is shown that the origin of this is electronic in nature and can be influenced through the addition of hydrogen bond donors (HBD) and hydrogen bond acceptors (HBA). Performing the reaction of a cycloalkane with mCPBA in a fluorinated alcohol solvent such as nonafluoro-tert-butanol (NFTB) or hexafluoroisopropanol (HFIP), which act as strong HBD and poor HBA, leads to significantly higher yields and selectivities being observed for the alcohol product. Application of the optimised reaction conditions allows for the selective oxidation of both cyclic and linear alkane substrates delivering the corresponding alcohol in up to 86 % yield. The transformation shows selectivity for tertiary centres over secondary centres and the oxidation of secondary centres is strongly influenced by stereoelectronic effects. Primary centres are not oxidised by this method. A simple computational model developed to understand this transformation provides a powerful tool to reliably predict the influence of substitution and functionality on reaction outcome.

Identification and Optimization of a Ligand-Efficient Benzoazepinone Bromodomain and Extra Terminal (BET) Family Acetyl-Lysine Mimetic into the Oral Candidate Quality Molecule I-BET432.

The bromodomain and extra terminal (BET) family of proteins are an integral part of human epigenome regulation, the dysregulation of which is implicated in multiple oncology and inflammatory diseases. Disrupting the BET family bromodomain acetyl-lysine (KAc) histone protein-protein interaction with small-molecule KAc mimetics has proven to be a disease-relevant mechanism of action, and multiple molecules are currently undergoing oncology clinical trials. This work describes an efficiency analysis of published GSK pan-BET bromodomain inhibitors, which drove a strategic choice to focus on the identification of a ligand-efficient KAc mimetic with the hypothesis that lipophilic efficiency could be drastically improved during optimization. This focus drove the discovery of the highly ligand-efficient and structurally distinct benzoazepinone KAc mimetic. Following crystallography to identify suitable growth vectors, the benzoazepinone core was optimized through an explore-exploit structure-activity relationship (SAR) approach while carefully monitoring lipophilic efficiency to deliver I-BET432 (41) as an oral candidate quality molecule.

Development of Biodegradable Composites Using Polycaprolactone and Bamboo Powder.

The use of biodegradable polymers in daily life is increasing to reduce environmental hazards. In line with this, the present study aimed to develop a fully biodegradable polymer composite that was environmentally friendly and exhibited promising mechanical and thermal properties. Bamboo powder (BP)-reinforced polycaprolactone (PCL) composites were prepared using the solvent casting method. The influence of BP content on the morphology, wettability, and mechanical and thermal properties of the neat matrix was evaluated. In addition, the degradation properties of the composites were analysed through soil burial and acidic degradation tests. It was revealed that BP contents had an evident influence on the properties of the composites. The increase in the BP content has significantly improved the tensile strength of the PCL matrix. A similar trend is observed for thermal stability. Scanning electron micrographs demonstrated uniform dispersion of the BP in the PCL matrix. The degradation tests revealed that the biocomposites with 40 wt·% of BP degraded by more than 20% within 4 weeks in the acidic degradation test and more than 5% in the soil burial degradation test. It was noticed that there was a considerable difference in the degradation between the PCL matrix and the biocomposites of PCL and BP. These results suggest that biodegradable composites could be a promising alternative material to the existing synthetic polymer composites.

Retrospective analysis of a clinical exome sequencing cohort reveals the mutational spectrum and identifies candidate disease-associated loci for BAFopathies.

PURPOSE: BRG1/BRM-associated factor (BAF) complex is a chromatin remodeling complex that plays a critical role in gene regulation. Defects in the genes encoding BAF subunits lead to BAFopathies, a group of neurodevelopmental disorders with extensive locus and phenotypic heterogeneity. METHODS: We retrospectively analyzed data from 16,243 patients referred for clinical exome sequencing (ES) with a focus on the BAF complex. We applied a genotype-first approach, combining predicted genic constraints to propose candidate BAFopathy genes. RESULTS: We identified 127 patients carrying pathogenic variants, likely pathogenic variants, or de novo variants of unknown clinical significance in 11 known BAFopathy genes. Those include 34 patients molecularly diagnosed using ES reanalysis with new gene-disease evidence (n = 21) or variant reclassifications in known BAFopathy genes (n = 13). We also identified de novo or predicted loss-of-function variants in 4 candidate BAFopathy genes, including ACTL6A, BICRA (implicated in Coffin-Siris syndrome during this study), PBRM1, and SMARCC1. CONCLUSION: We report the mutational spectrum of BAFopathies in an ES cohort. A genotype-driven and pathway-based reanalysis of ES data identified new evidence for candidate genes involved in BAFopathies. Further mechanistic and phenotypic characterization of additional patients are warranted to confirm their roles in human disease and to delineate their associated phenotypic spectrums.

Discovery of GSK251: A Highly Potent, Highly Selective, Orally Bioavailable Inhibitor of PI3Kδ with a Novel Binding Mode.

Optimization of a previously reported lead series of PI3Kδ inhibitors with a novel binding mode led to the identification of a clinical candidate compound 31 (GSK251). Removal of an embedded Ames-positive heteroaromatic amine by reversing a sulfonamide followed by locating an interaction with Trp760 led to a highly selective compound 9. Further optimization to avoid glutathione trapping, to enhance potency and selectivity, and to optimize an oral pharmacokinetic profile led to the discovery of compound 31 (GSK215) that had a low predicted daily dose (45 mg, b.i.d) and a rat toxicity profile suitable for further development.

Acetylation of the Catalytic Lysine Inhibits Kinase Activity in PI3Kδ.

Covalent inhibition is a powerful strategy to develop potent and selective small molecule kinase inhibitors. Targeting the conserved catalytic lysine is an attractive method for selective kinase inactivation. We have developed novel, selective inhibitors of phosphoinositide 3-kinase δ (PI3Kδ) which acylate the catalytic lysine, Lys779, using activated esters as the reactive electrophiles. The acylating agents were prepared by adding the activated ester motif to a known selective dihydroisobenzofuran PI3Kδ inhibitor. Three esters were designed, including an acetate ester which was the smallest lysine modification evaluated in this work. Covalent binding to the enzyme was characterized by intact protein mass spectrometry of the PI3Kδ-ester adducts. An enzymatic digest coupled with tandem mass spectrometry identified Lys779 as the covalent binding site, and a biochemical activity assay confirmed that PI3Kδ inhibition was a direct result of covalent lysine acylation. These results indicate that a simple chemical modification such as lysine acetylation is sufficient to inhibit kinase activity. The selectivity of the compounds was evaluated against lipid kinases in cell lysates using a chemoproteomic binding assay. Due to the conserved nature of the catalytic lysine across the kinome, we believe the covalent inhibition strategy presented here could be applicable to a broad range of clinically relevant targets.

One-Step Synthesis of Photoaffinity Probes for Live-Cell MS-Based Proteomics.

We present a one-step Ugi reaction protocol for the expedient synthesis of photoaffinity probes for live-cell MS-based proteomics. The reaction couples an amine affinity function with commonly used photoreactive groups, and a variety of handle functionalities. Using this technology, a series of pan-BET (BET: bromodomain and extra-terminal domain) selective bromodomain photoaffinity probes were obtained by parallel synthesis. Studies on the effects of photoreactive group, linker length and irradiation wavelength on photocrosslinking efficiency provide valuable insights into photoaffinity probe design. Optimal probes were progressed to MS-based proteomics to capture the BET family of proteins from live cells and reveal their potential on- and off-target profiles.

Differential recognition of HIV-stimulated IL-1ß and IL-18 secretion through NLR and NAIP signalling in monocyte-derived macrophages.

Macrophages are important drivers of pathogenesis and progression to AIDS in HIV infection. The virus in the later phases of the infection is often predominantly macrophage-tropic and this tropism contributes to a chronic inflammatory and immune activation state that is observed in HIV patients. Pattern recognition receptors of the innate immune system are the key molecules that recognise HIV and mount the inflammatory responses in macrophages. The innate immune response against HIV-1 is potent and elicits caspase-1-dependent pro-inflammatory cytokine production of IL-1ß and IL-18. Although, NLRP3 has been reported as an inflammasome sensor dictating this response little is known about the pattern recognition receptors that trigger the "priming" signal for inflammasome activation, the NLRs involved or the HIV components that trigger the response. Using a combination of siRNA knockdowns in monocyte derived macrophages (MDMs) of different TLRs and NLRs as well as chemical inhibition, it was demonstrated that HIV Vpu could trigger inflammasome activation via TLR4/NLRP3 leading to IL-1ß/IL-18 secretion. The priming signal is triggered via TLR4, whereas the activation signal is triggered by direct effects on Kv1.3 channels, causing K+ efflux. In contrast, HIV gp41 could trigger IL-18 production via NAIP/NLRC4, independently of priming, as a one-step inflammasome activation. NAIP binds directly to the cytoplasmic tail of HIV envelope protein gp41 and represents the first non-bacterial ligand for the NAIP/NLRC4 inflammasome. These divergent pathways represent novel targets to resolve specific inflammatory pathologies associated with HIV-1 infection in macrophages.

A Turing Test for Molecular Generators.

Machine learning approaches promise to accelerate and improve success rates in medicinal chemistry programs by more effectively leveraging available data to guide a molecular design. A key step of an automated computational design algorithm is molecule generation, where the machine is required to design high-quality, drug-like molecules within the appropriate chemical space. Many algorithms have been proposed for molecular generation; however, a challenge is how to assess the validity of the resulting molecules. Here, we report three Turing-inspired tests designed to evaluate the performance of molecular generators. Profound differences were observed between the performance of molecule generators in these tests, highlighting the importance of selection of the appropriate design algorithms for specific circumstances. One molecule generator, based on match molecular pairs, performed excellently against all tests and thus provides a valuable component for machine-driven medicinal chemistry design workflows.

A Photoaffinity-Based Fragment-Screening Platform for Efficient Identification of Protein Ligands.

Advances in genomic analyses enable the identification of new proteins that are associated with disease. To validate these targets, tool molecules are required to demonstrate that a ligand can have a disease-modifying effect. Currently, as tools are reported for only a fraction of the proteome, platforms for ligand discovery are essential to leverage insights from genomic analyses. Fragment screening offers an efficient approach to explore chemical space. Presented here is a fragment-screening platform, termed PhABits (PhotoAffinity Bits), which utilizes a library of photoreactive fragments to covalently capture fragment-protein interactions. Hits can be profiled to determine potency and the site of crosslinking, and subsequently developed as reporters in a competitive displacement assay to identify novel hit matter. The PhABit platform is envisioned to be widely applicable to novel protein targets, identifying starting points in the development of therapeutics.

Discovery of a Bromodomain and Extraterminal Inhibitor with a Low Predicted Human Dose through Synergistic Use of Encoded Library Technology and Fragment Screening.

The bromodomain and extraterminal (BET) family of bromodomain-containing proteins are important regulators of the epigenome through their ability to recognize N-acetyl lysine (KAc) post-translational modifications on histone tails. These interactions have been implicated in various disease states and, consequently, disruption of BET-KAc binding has emerged as an attractive therapeutic strategy with a number of small molecule inhibitors now under investigation in the clinic. However, until the utility of these advanced candidates is fully assessed by these trials, there remains scope for the discovery of inhibitors from new chemotypes with alternative physicochemical, pharmacokinetic, and pharmacodynamic profiles. Herein, we describe the discovery of a candidate-quality dimethylpyridone benzimidazole compound which originated from the hybridization of a dimethylphenol benzimidazole series, identified using encoded library technology, with an N-methyl pyridone series identified through fragment screening. Optimization via structure- and property-based design led to I-BET469, which possesses favorable oral pharmacokinetic properties, displays activity in vivo, and is projected to have a low human efficacious dose.

Radiofrequency Ablation, Where It Stands in Interventional Radiology Today.

Radiofrequency ablation (RFA) is one of the first developed minimally invasive definitive cancer therapies. The safety and efficacy of RFA is well documented and has led to its incorporation into multiple international societal guidelines. By expanding on the body of knowledge acquired during the clinical use of RFA, alternative ablative technologies have emerged and are successfully competing for locoregional therapy market share. The adaption of newer ablative technologies is leading to a rapid decline in the utilization of RFA by interventional radiologists despite the lack of proven superiority. In their 2010 article, Hong and Georgiades stated "… RFA is likely to remain the mainstay of ablations for small tumors until sufficient experience emerges for the widespread acceptance for alternative ablative modalities." Within a decade of this publication, has this time arrived?

Validation Studies for Single Circulating Trophoblast Genetic Testing as a Form of Noninvasive Prenatal Diagnosis.

It has long been appreciated that genetic analysis of fetal or trophoblast cells in maternal blood could revolutionize prenatal diagnosis. We implemented a protocol for single circulating trophoblast (SCT) testing using positive selection by magnetic-activated cell sorting and single-cell low-coverage whole-genome sequencing to detect fetal aneuploidies and copy-number variants (CNVs) at ∼1 Mb resolution. In 95 validation cases, we identified on average 0.20 putative trophoblasts/mL, of which 55% were of high quality and scorable for both aneuploidy and CNVs. We emphasize the importance of analyzing individual cells because some cells are apoptotic, in S-phase, or otherwise of poor quality. When two or more high-quality trophoblast cells were available for singleton pregnancies, there was complete concordance between all trophoblasts unless there was evidence of confined placental mosaicism. SCT results were highly concordant with available clinical data from chorionic villus sampling (CVS) or amniocentesis procedures. Although determining the exact sensitivity and specificity will require more data, this study further supports the potential for SCT testing to become a diagnostic prenatal test.

Clinical exome sequencing reveals locus heterogeneity and phenotypic variability of cohesinopathies.

PURPOSE: Defects in the cohesin pathway are associated with cohesinopathies, notably Cornelia de Lange syndrome (CdLS). We aimed to delineate pathogenic variants in known and candidate cohesinopathy genes from a clinical exome perspective. METHODS: We retrospectively studied patients referred for clinical exome sequencing (CES, N = 10,698). Patients with causative variants in novel or recently described cohesinopathy genes were enrolled for phenotypic characterization. RESULTS: Pathogenic or likely pathogenic single-nucleotide and insertion/deletion variants (SNVs/indels) were identified in established disease genes including NIPBL (N = 5), SMC1A (N = 14), SMC3 (N = 4), RAD21 (N = 2), and HDAC8 (N = 8). The phenotypes in this genetically defined cohort skew towards the mild end of CdLS spectrum as compared with phenotype-driven cohorts. Candidate or recently reported cohesinopathy genes were supported by de novo SNVs/indels in STAG1 (N = 3), STAG2 (N = 5), PDS5A (N = 1), and WAPL (N = 1), and one inherited SNV in PDS5A. We also identified copy-number deletions affecting STAG1 (two de novo, one of unknown inheritance) and STAG2 (one of unknown inheritance). Patients with STAG1 and STAG2 variants presented with overlapping features yet without characteristic facial features of CdLS. CONCLUSION: CES effectively identified disease-causing alleles at the mild end of the cohensinopathy spectrum and enabled characterization of candidate disease genes.

Early detection of metabolic dysregulation using water T2 analysis of biobanked samples.

BACKGROUND: The 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. METHODS: Plasma 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. RESULTS: Frozen 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. CONCLUSION: Plasma 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.

Aptamer-based search for correlates of plasma and serum water T2: implications for early metabolic dysregulation and metabolic syndrome.

BACKGROUND: Metabolic 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. METHODS: Water 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. RESULTS: The 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. CONCLUSIONS: The 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.

Clinical exome sequencing for fetuses with ultrasound abnormalities and a suspected Mendelian disorder.

BACKGROUND: Exome sequencing is now being incorporated into clinical care for pediatric and adult populations, but its integration into prenatal diagnosis has been more limited. One reason for this is the paucity of information about the clinical utility of exome sequencing in the prenatal setting. METHODS: We retrospectively reviewed indications, results, time to results (turnaround time, TAT), and impact of exome results for 146 consecutive "fetal exomes" performed in a clinical diagnostic laboratory between March 2012 and November 2017. We define a fetal exome as one performed on a sample obtained from a fetus or a product of conception with at least one structural anomaly detected by prenatal imaging or autopsy. Statistical comparisons were performed using Fisher's exact test. RESULTS: Prenatal exome yielded an overall molecular diagnostic rate of 32% (n = 46/146). Of the 46 molecular diagnoses, 50% were autosomal dominant disorders (n = 23/46), 41% were autosomal recessive disorders (n = 19/46), and 9% were X-linked disorders (n = 4/46). The molecular diagnostic rate was highest for fetuses with anomalies affecting multiple organ systems and for fetuses with craniofacial anomalies. Out of 146 cases, a prenatal trio exome option designed for ongoing pregnancies was performed on 62 fetal specimens, resulting in a diagnostic yield of 35% with an average TAT of 14 days for initial reporting (excluding tissue culture time). The molecular diagnoses led to refined recurrence risk estimates, altered medical management, and informed reproductive planning for families. CONCLUSION: Exome sequencing is a useful diagnostic tool when fetal structural anomalies suggest a genetic etiology, but other standard prenatal genetic tests did not provide a diagnosis.

De Novo Missense Variants in TRAF7 Cause Developmental Delay, Congenital Anomalies, and Dysmorphic Features.

TRAF7 is a multi-functional protein involved in diverse signaling pathways and cellular processes. The phenotypic consequence of germline TRAF7 variants remains unclear. Here we report missense variants in TRAF7 in seven unrelated individuals referred for clinical exome sequencing. The seven individuals share substantial phenotypic overlap, with developmental delay, congenital heart defects, limb and digital anomalies, and dysmorphic features emerging as key unifying features. The identified variants are de novo in six individuals and comprise four distinct missense changes, including a c.1964G>A (p.Arg655Gln) variant that is recurrent in four individuals. These variants affect evolutionarily conserved amino acids and are located in key functional domains. Gene-specific mutation rate analysis showed that the occurrence of the de novo variants in TRAF7 (p = 2.6 × 10-3) and the recurrent de novo c.1964G>A (p.Arg655Gln) variant (p = 1.9 × 10-8) in our exome cohort was unlikely to have occurred by chance. In vitro analyses of the observed TRAF7 mutations showed reduced ERK1/2 phosphorylation. Our findings suggest that missense mutations in TRAF7 are associated with a multisystem disorder and provide evidence of a role for TRAF7 in human development.

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 ß-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. METHODS: Water 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. RESULTS: Plasma 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. CONCLUSIONS: Water 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.