Scaling of cardiac morphology is interrupted by birth in the developing sheep Ovis aries.

Scaling of the heart across development can reveal the degree to which variation in cardiac morphology depends on body mass. In this study, we assessed the scaling of heart mass, left and right ventricular masses, and ventricular mass ratio, as a function of eviscerated body mass across fetal and postnatal development in Horro sheep Ovis aries (~50-fold body mass range; N = 21). Whole hearts were extracted from carcasses, cleaned, dissected into chambers and weighed. We found a biphasic relationship when heart mass was scaled against body mass, with a conspicuous 'breakpoint' around the time of birth, manifest not by a change in the scaling exponent (slope), but rather a jump in the elevation. Fetal heart mass (g) increased with eviscerated body mass (Mb , kg) according to the power equation 4.90 Mb0.88 ± 0.26 (± 95%CI) , whereas postnatal heart mass increased according to 10.0 Mb0.88 ± 0.10 . While the fetal and postnatal scaling exponents are identical (0.88) and reveal a clear dependence of heart mass on body mass, only the postnatal exponent is significantly less than 1.0, indicating the postnatal heart becomes a smaller component of body mass as the body grows, which is a pattern found frequently with postnatal cardiac development among mammals. The rapid doubling in heart mass around the time of birth is independent of any increase in body mass and is consistent with the normalization of wall stress in response to abrupt changes in volume loading and pressure loading at parturition. We discuss variation in scaling patterns of heart mass across development among mammals, and suggest that the variation results from a complex interplay between hard-wired genetics and epigenetic influences

MAP4 Mechanism that Stabilizes Mitochondrial Permeability Transition in Hypoxia: Microtubule Enhancement and DYNLT1 Interaction with VDAC1

Mitochondrial membrane permeability has received considerable attention recently because of its key role in apoptosis and necrosis induced by physiological events such as hypoxia. The manner in which mitochondria interact with other molecules to regulate mitochondrial permeability and cell destiny remains elusive. Previously we verified that hypoxia-induced phosphorylation of microtubule-associated protein 4 (MAP4) could lead to microtubules (MTs) disruption. In this study, we established the hypoxic (1% O2) cell models of rat cardiomyocytes, H9c2 and HeLa cells to further test MAP4 function. We demonstrated that increase in the pool of MAP4 could promote the stabilization of MT networks by increasing the synthesis and polymerization of tubulin in hypoxia. Results showed MAP4 overexpression could enhance cell viability and ATP content under hypoxic conditions. Subsequently we employed a yeast two-hybrid system to tag a protein interacting with mitochondria, dynein light chain Tctex-type 1 (DYNLT1), by hVDAC1 bait. We confirmed that DYNLT1 had protein-protein interactions with voltage-dependent anion channel 1 (VDAC1) using co-immunoprecipitation; and immunofluorescence technique showed that DYNLT1 was closely associated with MTs and VDAC1. Furthermore, DYNLT1 interactions with MAP4 were explored using a knockdown technique. We thus propose two possible mechanisms triggered by MAP4: (1) stabilization of MT networks, (2) DYNLT1 modulation, which is connected with VDAC1, and inhibition of hypoxia-induced mitochondrial permeabilization

Weight loss in individuals with metabolic syndrome given DASH diet counseling when provided a low sodium vegetable juice: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Metabolic syndrome, a constellation of metabolic risk factors for type 2 diabetes and cardiovascular disease, is one of the fastest growing disease entities in the world. Weight loss is thought to be a key to improving all aspects of metabolic syndrome. Research studies have suggested benefits from diets rich in vegetables and fruits in helping individuals reach and achieve healthy weights.</p> <p>Objective</p> <p>To evaluate the effects of a ready to serve vegetable juice as part of a calorie-appropriate Dietary Approaches to Stop Hypertension (DASH) diet in an ethnically diverse population of people with Metabolic Syndrome on weight loss and their ability to meet vegetable intake recommendations, and on their clinical characteristics of metabolic syndrome (waist circumference, triglycerides, HDL, fasting blood glucose and blood pressure).</p> <p>A secondary goal was to examine the impact of the vegetable juice on associated parameters, including leptin, vascular adhesion markers, and markers of the oxidative defense system and of oxidative stress.</p> <p>Methods</p> <p>A prospective 12 week, 3 group (0, 8, or 16 fluid ounces of low sodium vegetable juice) parallel arm randomized controlled trial. Participants were requested to limit their calorie intake to 1600 kcals for women and 1800 kcals for men and were educated on the DASH diet. A total of 81 (22 men & 59 women) participants with Metabolic Syndrome were enrolled into the study. Dietary nutrient and vegetable intake, weight, height, leptin, metabolic syndrome clinical characteristics and related markers of endothelial and cardiovascular health were measured at baseline, 6-, and 12-weeks.</p> <p>Results</p> <p>There were significant group by time interactions when aggregating both groups consuming vegetable juice (8 or 16 fluid ounces daily). Those consuming juice lost more weight, consumed more Vitamin C, potassium, and dietary vegetables than individuals who were in the group that only received diet counseling (p < 0.05).</p> <p>Conclusion</p> <p>The incorporation of vegetable juice into the daily diet can be a simple and effective way to increase the number of daily vegetable servings. Data from this study also suggest the potential of using a low sodium vegetable juice in conjunction with a calorie restricted diet to aid in weight loss in overweight individuals with metabolic syndrome.</p

Superstructure and Correlated Na⁺ Hopping in a Layered Mg-Substituted Sodium Manganate Battery Cathode are Driven by Local Electroneutrality

Publication status: PublishedIn this work, we present a variable-temperature 23Na NMR and variable-temperature and variable-frequency EPR analysis of the local structure of a layered P2 NIB cathode material, Na0.67[Mg0.28Mn0.72]O2 (NMMO). For the first time, we elucidate the superstructure in this material using synchrotron X-ray diffraction and total neutron scattering and show that this superstructure is consistent with NMR and EPR spectra. To complement our experimental data, we carry out ab initio calculations of the quadrupolar and hyperfine 23Na NMR shifts, the Na+ ion hopping energy barriers and the EPR g-tensors. We also describe an in-house simulation script for modelling the effects of ionic mobility on variable-temperature NMR spectra and use our simulations to interpret the experimental spectra, available upon request. We find long-zig-zag-type Na ordering with two different types of Na sites, one with high mobility and the other low mobility, and reconcile the tendency towards Na+/vacancy ordering to the preservation of local electroneutrality. The combined magnetic resonance methodology for studying local paramagnetic environments from the perspective of electron and nuclear spins will be useful for examining the local structures of materials for devices.E.N.B. acknowledges funding from the Engineering Physical Sciences Research Council (EPSRC) via the National Productivity Interest Fund (NPIF) 2018 (EP/S515334/1). J.D.B. acknowledges funding from the Faraday Institution (EP/S003053/1, FIRG016). We also thank the Science and Technology Facilities Council (STFC) and ISIS Neutron and Muon source for neutron data (experiment no.: RB2010350). Additional thanks are given to the staff scientists at beamline I11 of the Diamond Light Source for synchrotron data using block allocation group time under proposal CY34243. This work also utilised the ARCHER UK National Supercomputing Service via our membership in the UK’s HEC Materials Chemistry Consortium, funded by the EPSRC (EP/L000202). Research was also carried out at the Center for Functional Nanomaterials, Brookhaven National Laboratory, through the U.S. Department of Energy, Office of Basic Energy Sciences, Contract DE-AC02-98CH10866. E.N.B. would also like to thank A. Van der Ven and M.A. Jones for illuminating discussions

A Radiotherapy Dose Map-Guided Deep Learning Method for Predicting Pathological Complete Response in Esophageal Cancer Patients after Neoadjuvant Chemoradiotherapy Followed by Surgery

Esophageal cancer is a deadly disease, and neoadjuvant chemoradiotherapy can improve patient survival, particularly for patients achieving a pathological complete response (ypCR). However, existing imaging methods struggle to accurately predict ypCR. This study explores computer-aided detection methods, considering both imaging data and radiotherapy dose variations to enhance prediction accuracy. It involved patients with node-positive esophageal squamous cell carcinoma undergoing neoadjuvant chemoradiotherapy and surgery, with data collected from 2014 to 2017, randomly split into five subsets for 5-fold cross-validation. The algorithm DCRNet, an advanced version of OCRNet, integrates RT dose distribution into dose contextual representations (DCR), combining dose and pixel representation with ten soft regions. Among the 80 enrolled patients (mean age 55.68 years, primarily male, with stage III disease and middle-part lesions), the ypCR rate was 28.75%, showing no significant demographic or disease differences between the ypCR and non-ypCR groups. Among the three summarization methods, the maximum value across the CTV method produced the best results with an AUC of 0.928. The HRNetV2p model with DCR performed the best among the four backbone models tested, with an AUC of 0.928 (95% CI, 0.884–0.972) based on 5-fold cross-validation, showing significant improvement compared to other models. This underscores DCR-equipped models’ superior AUC outcomes. The study highlights the potential of dose-guided deep learning in ypCR prediction, necessitating larger, multicenter studies to validate the results