Anisotropy in the dielectric spectrum of hydration water and its relation to water dynamics

Proteins, molecules, and macromolecular assemblies in water are surrounded by a nanometer-sized hydration layer with properties very different from bulk water. Here, we use classical molecular dynamics simulations to study the dielectric response of hydration water next to hydrophobic and hydrophilic planar surfaces. We find the interfacial dielectricabsorption of water to be strongly anisotropic: compared to bulk water, which shows a broad dielectricabsorption maximum around 15 GHz in the imaginary part of the dielectric function, the absorption for electric fields parallel to the surface is of similar strength and shows a slight redshift, while for perpendicular electric fields it is strongly attenuated and blueshifted. This anisotropy is generic for hydrophobic and hydrophilic surfaces. From our spatially resolved dielectric functions and a modified Maxwell-Garnett theory that accounts for anisotropic hydration layers around spherical particles, the dielectricabsorption of solutions of organic molecules and micelles is derived to exhibit the experimentally known attenuation in combination with a redshift. These two features are traced back to the subtle interplay of interfacial depolarization effects and the dielectricanisotropy in the hydration layer. By a detailed analysis of the individual water molecule dynamics the perpendicular blueshift is shown not to be linked to accelerated water reorientation, but rather to dielectric boundary effects. Carefully conducted angularly resolved experiments at planar aqueous interfaces will be able to resolve this dielectricanisotropy and thus to confirm the subtle connection between spectralabsorption features and the molecular water dynamics in hydration layers

Challenges Enrolling Children Into Traumatic Brain Injury Trials: An Observational Study

ObjectivesIn preparation for a clinical trial of therapeutic agents for children with moderate‐to‐severe blunt traumatic brain injuries (TBIs) in emergency departments (EDs), we conducted this feasibility study to (1) determine the number and clinical characteristics of eligible children, (2) determine the timing of patient and guardian arrival to the ED, and (3) describe the heterogeneity of TBIs on computed tomography (CT) scans.MethodsWe conducted a prospective observational study at 16 EDs of children ≤ 18 years of age presenting with blunt head trauma and Glasgow Coma Scale scores of 3–12. We documented the number of potentially eligible patients, timing of patient and guardian arrival, patient demographics and clinical characteristics, severity of injuries, and cranial CT findings.ResultsWe enrolled 295 eligible children at the 16 sites over 6 consecutive months. Cardiac arrest and nonsurvivable injuries were the most common characteristics that would exclude patients from a future trial. Most children arrived within 2 hours of injury, but most guardians did not arrive until 2–3 hours after the injury. There was a substantial range in types of TBIs, with subdural hemorrhages being the most common.ConclusionEnrolling children with moderate‐to‐severe TBI into time‐sensitive clinical trials will require large numbers of sites and meticulous preparation and coordination and will prove challenging to obtain informed consent given the timing of patient and guardian arrival. The Federal Exception from Informed Consent for Emergency Research will be an important consideration for enrolling these children.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135996/1/acem13085_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135996/2/acem13085.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135996/3/acem13085-sup-0001-DataSupplementS1.pd

Predicting and elucidating the etiology of fatty liver disease : A machine learning modeling and validation study in the IMI DIRECT cohorts

Background Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. Methods and findings We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n= 795) or at high risk of developing the disease (n= 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (= 5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86;p = 5%) rather than a continuous one. Conclusions In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see:) and made it available to the community.Peer reviewe

Efficient nanoscale photonic devices and monolithic electronic-photonic subsystems in sub-100 nm SOI CMOS

We demonstrate efficient photonic devices that rely on sub-100nm features in unmodified 45nm SOI CMOS, including photonic crystals, array-antenna grating couplers, and modulators. We then show monolithically integrated electronicphotonic systems comprising millions of transistors and thousands of photonic devices, including a complete chip-to-chip photonic link

Genome-Wide and Abdominal MRI-Imaging Data Provides Evidence that a Genetically Determined Favourable Adiposity Phenotype is Characterized by Lower Ectopic Liver Fat and Lower Risk of Type 2 Diabetes, Heart Disease and Hypertension

Recent genetic studies have identified alleles associated with opposite effects on adiposity and risk of type 2 diabetes. We aimed to identify more of these variants and test the hypothesis that such favorable adiposity alleles are associated with higher subcutaneous fat and lower ectopic fat. We combined MRI data with genome-wide association studies of body fat percentage (%) and metabolic traits. We report 14 alleles, including 7 newly characterized alleles, associated with higher adiposity but a favorable metabolic profile. Consistent with previous studies, individuals carrying more favorable adiposity alleles had higher body fat % and higher BMI but lower risk of type 2 diabetes, heart disease, and hypertension. These individuals also had higher subcutaneous fat but lower liver fat and a lower visceral-to-subcutaneous adipose tissue ratio. Individual alleles associated with higher body fat % but lower liver fat and lower risk of type 2 diabetes included those in PPARG, GRB14, and IRS1, whereas the allele in ANKRD55 was paradoxically associated with higher visceral fat but lower risk of type 2 diabetes. Most identified favorable adiposity alleles are associated with higher subcutaneous and lower liver fat, a mechanism consistent with the beneficial effects of storing excess triglycerides in metabolically low-risk depots.</p

Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials

Background: In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. We therefore aimed to identify genetic variants associated with glycaemic response to GLP-1 receptor agonist treatment. Methods: In this genome-wide analysis we included adults (aged ≥18 years) with type 2 diabetes treated with GLP-1 receptor agonists with baseline HbA1c of 7% or more (53 mmol/mol) from four prospective observational cohorts (DIRECT, PRIBA, PROMASTER, and GoDARTS) and two randomised clinical trials (HARMONY phase 3 and AWARD). The primary endpoint was HbA1c reduction at 6 months after starting GLP-1 receptor agonists. We evaluated variants in GLP1R, then did a genome-wide association study and gene-based burden tests. Findings: 4571 adults were included in our analysis, of these, 3339 (73%) were White European, 449 (10%) Hispanic, 312 (7%) American Indian or Alaskan Native, and 471 (10%) were other, and around 2140 (47%) of the participants were women. Variation in HbA1c reduction with GLP-1 receptor agonists treatment was associated with rs6923761G→A (Gly168Ser) in the GLP1R (0·08% [95% CI 0·04–0·12] or 0·9 mmol/mol lower reduction in HbA1c per serine, p=6·0 × 10−5) and low frequency variants in ARRB1 (optimal sequence kernel association test p=6·7 × 10−8), largely driven by rs140226575G→A (Thr370Met; 0·25% [SE 0·06] or 2·7 mmol/mol [SE 0·7] greater HbA1c reduction per methionine, p=5·2 × 10−6). A similar effect size for the ARRB1 Thr370Met was seen in Hispanic and American Indian or Alaska Native populations who have a higher frequency of this variant (6–11%) than in White European populations. Combining these two genes identified 4% of the population who had a 30% greater reduction in HbA1c than the 9% of the population with the worse response. Interpretation: This genome-wide pharmacogenomic study of GLP-1 receptor agonists provides novel biological and clinical insights. Clinically, when genotype is routinely available at the point of prescribing, individuals with ARRB1 variants might benefit from earlier initiation of GLP-1 receptor agonists. Funding: Innovative Medicines Initiative and the Wellcome Trus

The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study.

AIMS/HYPOTHESIS: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). METHODS: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. RESULTS: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. CONCLUSIONS/INTERPRETATION: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.S.Bra. was funded by the UK Medical Research Council [MC_UU_12015/3]