Whole fat dairy products do not adversely affect adiposity or cardiometabolic risk factors inchildren in the Milky Way study: A double blind randomized controlled pilot study

Background Limited evidence supports the common public health guideline that children \u3e 2 y of age should consume dairy with reduced fat content. Objectives We aimed to investigate the effects of whole-fat compared with reduced-fat dairy intake on measures of adiposity and biomarkers of cardiometabolic risk in healthy 4- to 6-y-old children. Methods The Milky Way Study enrolled 49 children (mean ± SD age: 5.2 ± 0.9 y; 47% girls) who were habitual consumers of whole-fat dairy, then randomly assigned them in a double-blind fashion to remain on whole-fat dairy or switch their dairy consumption to reduced-fat products for 3 mo. Primary endpoints included measures of adiposity, body composition, blood pressure, fasting serum lipids, blood glucose, glycated hemoglobin (HbA1c), and C-reactive protein (CRP) and were assessed at baseline and study end. Pre- and postintervention results were compared using linear mixed models, adjusted for growth, age, and sex. Results Dairy fat intake was reduced by an adjusted (mean ± SEM) 12.9 ± 4.1 g/d in the reduced-fat compared with the whole-fat dairy group (95% CI: –21.2, –4.6 g/d; P = 0.003), whereas dietary energy intakes remained similar (P = 0.936). We found no significant differential changes between dairy groups in any measure of adiposity, body composition, blood pressure, or fasting serum lipids, glucose, HbA1c, and CRP. Conclusions Our results suggest that although changing from whole-fat to reduced-fat dairy products does reduce dairy fat intake, it does not result in changes to markers of adiposity or cardiometabolic disease risk in healthy children

A comprehensive evaluation of colonic mucosal isolates of Sutterella wadsworthensis from inflammatory bowel disease

Peer reviewedPublisher PD

The adaptive designs CONSORT extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design

Abstract: Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised. This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process. The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text. The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites.“To maximise the benefit to society, you need to not just do research but do it well” Douglas G Altma

Testing the magnetar scenario for superluminous supernovae with circular polarimetry

Superluminous supernovae (SLSNe) are at least ∼5 times more luminous than common supernovae (SNe). Especially hydrogen-poor SLSN-I are difficult to explain with conventional powering mechanisms. One possible scenario that might explain such luminosities is that SLSNe-I are powered by an internal engine, such as a magnetar or an accreting black hole. Strong magnetic fields or collimated jets can circularly polarize light. In this work, we measured circular polarization of two SLSNe-I with the FOcal Reducer and low dispersion Spectrograph (FORS2) mounted at the ESO’s Very Large Telescope (VLT). PS17bek, a fast evolving SLSN-I, was observed around peak, while OGLE16dmu, a slowly evolving SLSN-I, was observed 100 days after maximum. Neither SLSN shows evidence of circularly polarized light, however, these non-detections do not rule out the magnetar scenario as the powering engine for SLSNe-I. We calculate the strength of the magnetic field and the expected circular polarization as a function of distance from the magnetar, which decreases very fast. Additionally, we observed no significant linear polarization for PS17bek at four epochs, suggesting that the photosphere near peak is close to spherical symmetry

An ensemble of flexible conformations underlies mechanotransduction by the cadherin-catenin adhesion complex

© 2019 The Authors. Published by National Academy of Sciences. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1073/pnas.1911489116The cadherin–catenin adhesion complex is the central component of the cell–cell adhesion adherens junctions that transmit mechanical stress from cell to cell. We have determined the nanoscale structure of the adherens junction complex formed by the α-catenin•β-catenin•epithelial cadherin cytoplasmic domain (ABE) using negative stain electron microscopy, small-angle X-ray scattering, and selective deuteration/small-angle neutron scattering. The ABE complex is highly pliable and displays a wide spectrum of flexible structures that are facilitated by protein-domain motions in α- and β-catenin. Moreover, the 107-residue intrinsically disordered N-terminal segment of β-catenin forms a flexible “tongue” that is inserted into α-catenin and participates in the assembly of the ABE complex. The unanticipated ensemble of flexible conformations of the ABE complex suggests a dynamic mechanism for sensitivity and reversibility when transducing mechanical signals, in addition to the catch/slip bond behavior displayed by the ABE complex under mechanical tension. Our results provide mechanistic insight into the structural dynamics for the cadherin–catenin adhesion complex in mechanotransduction.This research was funded by NSF Grant MCB-1817684 (to Z.B.) and National Center for Research Resources Grant 2G12 RR003060 (to City College of New York). A portion of the research conducted at Oak Ridge National Laboratory’s Spallation Neutron Source and High Flux Isotope Reactor was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, US Department of Energy (DOE). The Bio-SANS of the Center for Structural Molecular Biology at the High Flux Isotope Reactor is supported by the Office of Biological and Environmental Research of the DOE. Use of the SSRL, Stanford Linear Accelerator Center’s is supported by DOE, Office of Science, Office of Basic Energy Sciences Contract DE-AC02-76SF00515. The SSRL Structural Molecular Biology Program is supported by the DOE Office of Biological and Environmental Research and NIH, National Institute of General Medical Sciences (NIGMS) Grant P41 GM103393.Published versio

Revealing the progenitor of SN 2021zby through analysis of the TESSTESS shock-cooling light curve

We present early observations and analysis of the double-peaked Type IIb supernova (SN IIb) 2021zby. $TESS$ captured the prominent early shock cooling peak of SN 2021zby within the first $\sim$10 days after explosion with a 30-minute cadence. We present optical and near-infrared spectral series of SN 2021zby, including three spectra during the shock cooling phase. Using a multi-band model fit, we find that the inferred properties of its progenitor are consistent with a red supergiant or yellow supergiant, with an envelope mass of $\sim$0.3-3.0 M$_\odot$ and an envelope radius of $\sim$50-350$R_\odot$. These inferred progenitor properties are similar to those of other SNe IIb with double-peak feature, such as SNe 1993J, 2011dh, 2016gkg and 2017jgh. This study further validates the importance of the high cadence and early coverage in resolving the shape of the shock cooling light curve, while the multi-band observations, especially UV, is also necessary to fully constrain the progenitor properties.Comment: 12 pages, 5 figures, 2 tables, submitted to ApJ

Association of latent class analysis-derived multimorbidity clusters with adverse health outcomes in patients with multiple long-term conditions: Comparative results across three UK cohorts

Background It remains unclear how to meaningfully classify people living with multimorbidity (multiple long-term conditions (MLTCs)), beyond counting the number of conditions. This paper aims to identify clusters of MLTCs in different age groups and associated risks of adverse health outcomes and service use. Methods Latent class analysis was used to identify MLTCs clusters in different age groups in three cohorts: Secure Anonymised Information Linkage Databank (SAIL) (n = 1,825,289), UK Biobank (n = 502,363), and the UK Household Longitudinal Study (UKHLS) (n = 49,186). Incidence rate ratios (IRR) for MLTC clusters were computed for: all-cause mortality, hospitalisations, and general practice (GP) use over 10 years, using <2 MLTCs as reference. Information on health outcomes and service use were extracted for a ten year follow up period (between 01st Jan 2010 and 31st Dec 2019 for UK Biobank and UKHLS, and between 01st Jan 2011 and 31st Dec 2020 for SAIL). Findings Clustering MLTCs produced largely similar results across different age groups and cohorts. MLTC clusters had distinct associations with health outcomes and service use after accounting for LTC counts, in fully adjusted models. The largest associations with mortality, hospitalisations and GP use in SAIL were observed for the “Pain+” cluster in the age-group 18–36 years (mortality IRR = 4.47, hospitalisation IRR = 1.84; GP use IRR = 2.87) and the “Hypertension, Diabetes & Heart disease” cluster in the age-group 37–54 years (mortality IRR = 4.52, hospitalisation IRR = 1.53, GP use IRR = 2.36). In UK Biobank, the “Cancer, Thyroid disease & Rheumatoid arthritis” cluster in the age group 37–54 years had the largest association with mortality (IRR = 2.47). Cardiometabolic clusters across all age groups, pain/mental health clusters in younger groups, and cancer and pulmonary related clusters in older age groups had higher risk for all outcomes. In UKHLS, MLTC clusters were not significantly associated with higher risk of adverse outcomes, except for the hospitalisation in the age-group 18–36 years. Interpretation Personalising care around MLTC clusters that have higher risk of adverse outcomes may have important implications for practice (in relation to secondary prevention), policy (with allocation of health care resources), and research (intervention development and targeting), for people living with MLTCs. Funding This study was funded by the National Institute for Health and Care Research (NIHR; Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (multimorbidity)—NIHR202020)

Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix

<p>Abstract</p> <p>Background</p> <p>Using routinely collected patient data we explore the utility of multilevel latent class (MLLC) models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs).</p> <p>Methods</p> <p>Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640). Patient age, sex, stage-at-diagnosis (Dukes), and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared.</p> <p>Results</p> <p>Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years), and one with better prognosis (39.3% died within 3 years). In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs.</p> <p>Conclusions</p> <p>A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments) and factors associated with the processes of healthcare delivery (e.g. delays). Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.</p