bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sotagliflozin, a dual SGLT1/2 inhibitor, improves cardiac outcomes in a mouse model of early heart failure without diabetes
Authors: Young Sophia L , Ryan Lydia , Mullins Thomas P , Flint Melanie , Steane Sarah E , Walton Sarah L , Bielefeldt-Ohmann Helle , Carter David A , Reichelt Melissa E , Gallo Linda A 
Published: August 2020

AbstractAimsSelective SGLT2 inhibition reduces the risk of worsening heart failure and cardiovascular death in patients with existing heart failure, irrespective of diabetic status. We aimed to investigate the effects of dual SGLT1/2 inhibition, using sotagliflozin, on cardiac outcomes in non-diabetic and diabetic mice with cardiac pressure overload.Methods and ResultsFive-week old male C57BL/6J mice were randomized to receive a high fat diet (HFD; 60% of calories from fat) to induce diabetes or remain on normal diet (ND) for 12 weeks. Transverse aortic constriction (TAC) was then employed to induce cardiac pressure-overload (50% increase in right:left carotid pressure versus sham surgery), resulting in features representative of heart failure with preserved ejection fraction. At five weeks into the dietary protocol, mice were treated for seven weeks by oral gavage once daily with sotagliflozin (10mg/kg body weight) or vehicle (0.1% tween 80). In ND non-diabetic mice, treatment with sotagliflozin attenuated cardiac hypertrophy and histological markers of cardiac fibrosis induced by TAC. These benefits were associated with profound diuresis and glucosuria, without shifts toward whole-body fatty acid utilisation nor increased cardiac ketolysis. In HFD diabetic mice, sotagliflozin did not attenuate cardiac injury induced by TAC. HFD mice had vacuolation of proximal tubular cells, associated with less profound diuresis and glucosuria, which may have compromised drug action and subsequent cardio-protection.ConclusionWe demonstrate the utility of dual SGLT1/2 inhibition in treating heart failure risk factors in the non-diabetic state. Its efficacy in high fat-induced diabetes with proximal tubular damage requires further study.
Predicting future regional tau accumulation in asymptomatic and early Alzheimer’s disease
Authors: Giorgio Joseph , Jagust William J , Baker Suzanne , Landau Susan M. , Tino Peter , Kourtzi Zoe ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: August 2020

AbstractThe earliest stages of Alzheimer’s disease (AD) involve interactions between multiple pathophysiological processes. Although these processes are well studied, we still lack robust tools to predict individualised trajectories of disease progression. Here, we employ a robust and interpretable machine learning approach to combine multimodal biological data and predict future tau accumulation, translating predictive information from deep phenotyping cohorts at early stages of AD to cognitively normal individuals. In particular, we use machine learning to quantify interactions between key pathological markers (β-amyloid, medial temporal atrophy, tau and APOE 4) at early and asymptomatic stages of AD. We next derive a predictive index that stratifies individuals based on future pathological tau accumulation, highlighting two critical features for optimal clinical trial design. First, future tau accumulation provides a better outcome measure compared to changes in cognition. Second, stratification based on multimodal data compared to β-amyloid alone reduces the sample size required to detect a clinically meaningful change in tau accumulation. Further, we extend our machine learning approach to derive individualised trajectories of future pathological tau accumulation in early AD patients and accurately predict regional future rate of tau accumulation in an independent sample of cognitively unimpaired individuals. Our results propose a robust approach for fine scale stratification and prognostication with translation impact for clinical trial design at asymptomatic and early stages of AD.One Sentence SummaryOur machine learning approach combines baseline multimodal data to make individualised predictions of future pathological tau accumulation at prodromal and asymptomatic stages of Alzheimer’s disease with high accuracy and regional specificity.
Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson’s disease heterogeneity
Authors: Hill Emily J. , Grant Mangleburg C. , Alfradique-Dunham Isabel , Ripperger Brittany , Stillwell Amanda , Saade Hiba , Rao Sindhu , Fagbongbe Oluwafunmiso , Coelln Rainer von , Tarakad Arjun , Hunter Christine , Dawe Robert J. , Jankovic Joseph , Shulman Lisa M. , Buchman Aron S. , Shulman Joshua M. 
Published: August 2020

AbstractIntroductionEmerging technologies show promise for enhanced characterization of Parkinson’s Disease (PD) motor manifestations. We evaluated quantitative mobility measures from a wearable device compared to the conventional motor assessment, the Movement Disorders Society-Unified PD Rating Scale part III (motor MDS-UPDRS).MethodsWe evaluated 176 subjects with PD (mean age 65, 65% male, 66% H&Y stage 2) at the time of routine clinic visits using the motor MDS-UPDRS and a structured 10-minute motor protocol, which included a 32-ft walk, Timed Up and Go (TUG), and standing posture with eyes closed, while wearing a body-fixed sensor (DynaPort MT, McRoberts BV). Regression models examined 12 quantitative mobility measures for associations with (i) motor MDS-UPDRS, (ii) motor subtype (tremor dominant vs. postural instability/gait difficulty), (iii) Montreal Cognitive Assessment (MoCA), and (iv) physical functioning disability (PROMIS-29). All analyses included age, gender, and disease duration as covariates. Models iii-iv were secondarily adjusted for motor MDS-UPDRS.ResultsQuantitative mobility measures from gait, TUG transitions, turning, and posture were significantly associated with motor MDS-UPDRS (7 of 12 measures, p< 0.05) and subtype (6 of 12 measures, p< 0.05). Compared with motor MDS-UPDRS, several quantitative mobility measures accounted for ∼1.5-fold increased variance in either cognition or physical functioning disability. Among minimally-impaired subjects within the bottom quartile of motor MDS-UPDRS, including subjects with normal gait exam, the measures captured substantial residual motor heterogeneity.ConclusionClinic-based quantitative mobility assessments using a wearable sensor captured features of motor performance beyond those obtained with the motor MDS-UPDRS and may offer enhanced characterization of disease heterogeneity.
GIS-based spatial modeling to identify factors affecting COVID-19 incidence rates in Bangladesh
Authors: Rahman Md. Hamidur , Zafri Niaz Mahmud , Ashik Fajle Rabbi , Waliullah Md 
Published: August 2020

AbstractThe outbreak of the COVID-19 pandemic is an unprecedented shock throughout the world which leads to generate a massive social, human, and economic crisis. However, there is a lack of research on geographic modeling of COVID-19 as well as identification of contributory factors affecting the COVID-19 in the context of developing countries. To fulfill the gap, this study aimed to identify the potential factors affecting the COVID-19 incidence rates at the district-level in Bangladesh using spatial regression model (SRM). Therefore, data related to 32 demographic, economic, weather, built environment, health, and facilities related factors were collected and analyzed to explain the spatial variability of this disease incidence. Three global (Ordinary least squares (OLS), spatial lag model (SLM) and spatial error model (SEM)) and one local (geographically weighted regression (GWR)) SRMs were developed in this study. The results of the models showed that four factors significantly affected the COVID-19 incidence rates in Bangladesh. Those four factors are urban population percentage, monthly consumption, number of health workers, and distance from the capital. Among the four developed models, the GWR model performed the best in explaining the variation of COVID-19 incidence rates across Bangladesh with aR2value of 78.6%. Findings from this research offer a better insight into the COVID-19 situation and would help to develop policies aimed to prevent the future epidemic crisis.
Consensus-based somatic variant-calling method correlatesFBXW7mutations with poor prognosis in canine B-cell lymphoma
Authors: White ME , Hayward JJ , Hertafeld SR , Castelhano MG , Leung W , Dave SS , Bhinder BH , Elemento OL , Boyko AR , Richards KL , Suter SE 
Published: August 2020

AbstractINTRODUCTIONCanine Lymphoma (CL) is the most commonly diagnosed malignancy in the domestic dog, with estimates reaching 80,000 new cases per year in the United States. Understanding of genetic factors involved in development and progression of canine B-Cell Lymphoma (cBCL), the most common of the two major subtypes of CL, can help guide efforts to prevent, diagnose, and treat disease in dogs. Such findings also have implications for human Non-Hodgkin Lymphoma (NHL), as pet dogs have recently emerged as an important translational model due to the many shared histopathological, biological, and clinical characteristics between cBCL and NHL.OBJECTIVESWe aimed to identify potential driver mutations in cBCL and detect associations between affected genes and differential clinical outcomes.METHODSUsing exome sequencing of paired normal and tumor tissues from 71 dogs of various breeds with cBCL, we identified somatic variants with a consensus approach: keeping variants called by both MuTect2 and with high-confidence by VarScan 2. We predicted effects of these variants using SnpEff then measured associations between mutated genes and survival times from clinical data available for 62 cohort dogs using a multivariate Cox Proportional Hazards Model.RESULTSMutations inFBXW7, a gene commonly mutated in both human and canine cancers including lymphoma, were associated with shorter overall survival (OS; p=0.01, HR 3.3 [1.4-7.6]). The two most frequently mutated codons ofFBXW7in our cohort correspond to the most frequently mutated codons in human cancers.CONCLUSIONSOur findings show that exome sequencing results can be combined with clinical data to identify key mutations associated with prognosis in cBCL. These results may have implications for precision medicine in dogs and also allow subsets of dogs to serve as models for specific subtypes of human lymphoma.Translational RelevanceIdentifying tumor biomarkers associated with clinical outcomes has been a major driver in improved success in treating many types of human cancers, including Non-Hodgkin lymphoma (NHL). Since canine B-cell Lymphoma (cBCL) shares many clinically identifiable characteristics with NHL, our detection of recurring mutations in certain genes in cBCL and their association with clinical outcomes stands to benefit both humans and dogs. If common canine lymphoma subtypes show mutational similarity to certain human subtypes, then therapies found to be effective for a subtype in one species may be more likely to improve treatment response in the analogous subtype in the other.
A comparative study of stress responses elicited by misfolded proteins targeted by bipartite or matrix-targeting signal sequences to yeast mitochondria
Authors: Rao Kannan Boosi Narayana , Pandey Pratima , Sarkar Rajasri , Ghosh Asmita , Mansuri Shemin , Ali Mudassar , Majumder Priyanka , Kumar K. Ranjith , Ray Arjun , Raychaudhuri Swasti , Mapa Koyeli 
Published: August 2020

AbstractThe double-membrane-bound architecture of mitochondria, essential for ATP production, sub-divides the organelle into inter-membrane space (IMS) and matrix. IMS and matrix possess contrasting oxido-reductive environments and distinct protein quality control (PQC) machineries resulting different protein folding environments. To understand the nature of stress response elicited by equivalent proteotoxic stress to sub-mitochondrial compartments, we fused well-described bipartite or matrix-targeting signal sequences to misfolding and aggregation-prone stressor proteins to target and impart stress to yeast mitochondrial IMS or matrix. We show, mitochondrial proteotoxicity leads to growth arrest of yeast cells of varying degrees depending on nature of stressor proteins and the intra-mitochondrial location of stress. Next, using transcriptomics and proteomics, we report a comprehensive stress response elicited by two types of targeting signal-fused stressor proteins. Among global responses by mitochondria-targeted stressors by both types of signal sequences, an adaptive response of abrogated mitochondrial respiration and concomitant upregulation of glycolysis is uncovered. Beyond shared stress responses, specific signatures due to stress within mitochondrial sub-compartments are also revealed. We report that bipartite signal sequence-fused stressor proteins eliciting stress to IMS, leads to specific upregulation of IMS-chaperones and TOM complex components. In contrast, matrix-targeted stressors lead to specific upregulation of matrix-chaperones and cytosolic PQC components. Finally, by systematic genetic interaction using deletion strains of differentially upregulated genes, we found prominent modulatory role of TOM complex components during IMS-stress response. In contrast, VMS1 markedly modulates the stress response originated from matrix.
Cortical volume-to-surface and -to-white matter volume relations are explained by uniform cortical architecture in mammals
Authors: de Lussanet Marc H E , Boström Kim J , Wagner Heiko 
Published: August 2020

AbstractThe size of the mammalian cerebrum spans more than 5 orders of magnitude. The smallest cerebrums have a smooth (lissencephalic) cortical surface, which gets increasingly folded (gyrencephalic) with cerebral size. Further, the proportion of white-to-gray matter volume increases with the total volume. These scaling relations have unusually little variation. Even though a number of theories and models have been proposed, it remains an open question, why this is so. Here, we show that almost all variance is explained by assuming a homogeneous composition of the cortex across mammals. On the basis of this assumption we derive quantitative analytical computational models. The first model predicts the cortical surface area from the gray and white matter volume. A single free parameter, for the height of cortical columns is estimated asλ= 2.9mm (r2= 0.996). The second model predicts the white matter volume as a function of the gray volume and the cerebral size (with parameters for intra- and extra-gyral connectionslint, lext;). The models are validated by predicting the effective cortical thickness and the folding parameterκ. The results accurately predict the human intraspecific variation of the surface relations. As expected, we find a reducedλfor cetaceans, and that preterm human infants do not follow the model. We also find deviations of gray and white matter volume for large cerebrums. Overall, the models thus show how the regular architecture of the cortex shapes the cerebrum. We conclude that the mammalian cerebrum scales in anisomorphic, rather than isometric, manner.
Genomic selection for any dairy breeding program via optimized investment in phenotyping and genotyping
Authors: Obšteter Jana , Jenko Janez , Gorjanc Gregor 
Published: August 2020

AbstractThis paper evaluates the potential of maximizing genetic gain in dairy cattle breeding by optimizing investment into phenotyping and genotyping. Conventional breeding focuses on phenotyping selection candidates or their close relatives to maximize selection accuracy for breeders and quality assurance for producers. Genomic selection decoupled phenotyping and selection and through this increased genetic gain per year compared to the conventional selection. Although genomic selection is established in well-resourced breeding programs, small populations and developing countries still struggle with the implementation. The main issues include the lack of training animals and lack of financial resources. To address this, we simulated a case-study of a small dairy population with a number of scenarios with equal resources yet varied use of resources for phenotyping and genotyping. The conventional progeny testing scenario had 11 phenotype records per lactation. In genomic scenarios, we reduced phenotyping to between 10 and 1 phenotype records per lactation and invested the saved resources into genotyping. We tested these scenarios at different relative prices of phenotyping to genotyping and with or without an initial training population for genomic selection. Reallocating a part of phenotyping resources for repeated milk records to genotyping increased genetic gain compared to the conventional scenario regardless of the amount and relative cost of phenotyping, and the availability of an initial training population. Genetic gain increased by increasing genotyping, despite reduced phenotyping. High-genotyping scenarios even saved resources. Genomic scenarios expectedly increased accuracy for young non-phenotyped male and female candidates, but also cows. This study shows that breeding programs should optimize investment into phenotyping and genotyping to maximise return on investment. Our results suggest that any dairy breeding program using conventional progeny testing with repeated milk records can implement genomic selection without increasing the level of investment.
Bilateral Intracranial Beta Activity during Forced and Spontaneous Movements in a Hemi-PD Rat Model
Authors: Mottaghi Soheil , Kohl Sandra , Biemann Dirk , Liebana Samuel , Montano Ruth , Buchholz Oliver , Wilson Mareike , Klaus Carolin , Uchenik Michelle , Münkel Christian , Schmidt Robert , Hofmann Ulrich G. 
Published: August 2020

AbstractCortico-basal ganglia beta oscillations (13-30Hz) are assumed to be involved in motor impairments in Parkinson’s Disease (PD), especially in bradykinesia and rigidity. Various studies have utilized the unilateral 6-OHDA rat PD model to further investigate PD and test novel treatments. However, a detailed behavioral and electrophysiological characterization of the model, including analyses of popular PD treatments such as DBS, has not been documented in the literature. We hence challenged the 6-OHDA rat PD model with a series of experiments (i.e. cylinder test, open field test and rotarod test) aimed at assessing the motor impairments, analyzing the effects of Deep Brain Stimulation (DBS), and identifying under which conditions excessive beta oscillations occur. We found that hemi-PD rats presented an impaired performance in all experiments compared to the sham group, and DBS could improve their overall performance. Across all the experiments and behaviors, the power in the high beta band was observed to be an important biomarker for PD as it showed differences between healthy and lesioned hemispheres and between PD and sham rats. This all shows that the 6-OHDA PD model accurately represents many of the motor and electrophysiological symptoms of PD and makes it a useful tool for the pre-clinical testing of new treatments and further investigations into this disease.
Howµ-Opioid Receptor Recognizes Fentanyl
Authors: Vo Quynh N. , Mahinthichaichan Paween , Shen Jana , Ellis Christopher R. 
Published: August 2020

AbstractIn 2019, drug overdose has claimed over 70,000 lives in the United States. More than half of the deaths are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, the crystal structures of mOR in complex with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like synthetic opioids remains lacking. Exploiting the X-ray structure of mOR bound to a morphinan ligand and several state-of-the-art simulation techniques, including weighted ensemble and continuous constant pH molecular dynamics, we elucidated the detailed binding mechanism of fentanyl with mOR. Surprisingly, in addition to forming a salt-bridge with Asp1473.32in the orthosteric site common to morphinan opiates, fentanyl can move deeper and bind mOR through hydrogen bonding with a conserved histidine His2976.52, which has been shown to modulate mOR’s ligand affinity and pH dependence in mutagenesis experiments, but its precise role remains unclear. Intriguingly, the secondary binding mode is only accessible when His297 adopts a neutral HID tautomer. Alternative binding modes and involvement of tautomer states may represent general mechanisms in G protein-coupled receptor (GPCR)-ligand recognition. Our work provides a starting point for understanding the molecular basis of mOR activation by fentanyl which has many analogs emerging at a rapid pace. The knowledge may also inform the design of safer analgesics to combat the opioid crisis. Current protein simulation studies employ standard protonation and tautomer states; our work demonstrates the need to move beyond the practice to advance our understanding of protein-ligand recognition.
Dissociating the effects of distraction and proactive interference on object memory through tests of novelty preference
Authors: Landreth K. , Simanaviciute U. , Fletcher J. , Grayson B. , Grant R.A. , Harte M.H. , Gigg J. 
Published: August 2020

AbstractEncoding information into memory is sensitive to distraction whilst retrieving that memory may be compromised by proactive interference from pre-existing memories. These two debilitating effects are common in neuropsychiatric conditions but modelling them preclinically to date is slow as it requires prolonged operant training. A step change would be the validation of functionally equivalent but fast, simple, high-throughput tasks based on spontaneous behaviour. Here, we show that spontaneous object preference testing meets these requirements in the subchronic phencyclidine (scPCP) rat model for cognitive impairments associated with schizophrenia. scPCP rats show clear memory sensitivity to distraction in the standard novel object recognition task (stNOR). However, due to this, stNOR cannot assess proactive interference. Therefore, we compared scPCP performance in stNOR to that using the continuous NOR task (conNOR), which offers minimal distraction, allowing disease-relevant memory deficits to be assessed directly. We first determined that scPCP treatment did not affect whisker movements during object exploration. scPCP rats exhibited the expected distraction stNOR effect but had intact performance on the first conNOR trial, effectively dissociating distraction by using two NOR task variants. In remaining conNOR trials, scPCP rats performed above chance throughout but, importantly, their detection of object novelty was increasingly impaired relative to controls. We attribute this effect to the accumulation of proactive interference. This is the first demonstration that increased sensitivity to distraction and proactive interference, both key cognitive impairments in schizophrenia, can be dissociated in the scPCP rat using two variants of the same fast, simple, spontaneous object memory paradigm.