bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic signatures of lipid droplets as new markers to quantify cellular metabolic changes
Authors: Zhang Chi , Boppart Stephen A. 
Published: July 2020

AbstractThe metabolic properties of live cells are very susceptible to intra- or extra-cellular perturbations, making their measurements challenging tasks. We show that the dynamics of lipid droplets (LDs) carry information to measure the lipid metabolism of live cells. Coherent anti-Stokes Raman scattering microscopy was used to statistically quantify LD dynamics in living cells in a label-free manner. We introduce dynamic signatures of cells derived from the LD displacement, speed, travel length, and directionality, which allows for the detection of cellular changes induced by stimuli such as fluorescent labeling, temperature change, starvation, and chemical treatment. Histogram fittings of the dynamic signatures using lognormal distribution functions provide quantification of changes in cellular metabolic states. The LD dynamics also enable separation of subpopulations of LDs correlated with different functions. We demonstrate that LD dynamics are new markers to quantify the metabolic changes in live cells.
Mapping the Functional Landscape of the Receptor Binding Domain of T7 Bacteriophage by Deep Mutational Scanning
Authors: Huss Phil , Meger Anthony , Leander Megan , Nishikawa Kyle , Raman Srivatsan 
Published: July 2020

AbstractThe interaction between a bacteriophage and its host is mediated by the phage’s receptor binding protein (RBP). Despite its fundamental role in governing phage activity and host range, the molecular rules of RBP function remain a mystery. Here, we systematically dissect the functional role of every residue in the tip domain of T7 phage RBP using a novel phage genome engineering method called ORACLE (OptimizedRecombination,Accumulation andLibraryExpression). ORACLE is a high-throughput, locus-specific, sequence-programmable method to create a large, unbiased library of phage variants at a targeted gene locus. Using ORACLE, we generated all single amino acid substitutions at every site (1660 variants) of the tip domain to quantify the functional role of all variants on multiple bacterial hosts. This rich dataset allowed us to cross compare functional profiles of each host to precisely identify regions of functional importance, many which were previously unknown. Host-specific substitution patterns displayed differences in site specificity and physicochemical properties of mutations indicating exquisite adaptation to individual hosts. Comparison of enriched variants across hosts also revealed a tradeoff between activity and host range. We discovered gain-of-function variants effective against resistant hosts and host-constricting variants that selectively eliminated certain hosts. We demonstrate therapeutic utility against uropathogenicE. coliby engineering a highly active T7 variants to avert emergence of spontaneous resistance of the pathogen. Our approach presents a generalized framework for systematic and comprehensive characterization of sequence-function relationships in phages on an unprecedented scale.
The surface of lipid droplets constitutes a barrier for endoplasmic reticulum residential integral membrane spanning proteins
Authors: Khaddaj Rasha , Mari Muriel , Cottier Stéphanie , Reggiori Fulvio , Schneiter Roger 
Published: July 2020

AbstractLipid droplets (LDs) are globular subcellular structures that mainly serve to store energy in form of neutral lipids, particularly triacylglycerols and steryl esters. LDs are closely associated with the membrane of the endoplasmic reticulum (ER), and are limited by a monolayer membrane of phospholipids harboring a specific set of proteins. Most of these proteins associate with LDs through either an amphipathic helix or a membrane-embedded hairpin motif. Here we address the question whether integral membrane spanning proteins could localize to the surface of LDs. To test this, we fused perilipin 3 (PLIN3), a mammalian LD-targeted protein, to ER resident proteins, such as Wbp1 (a N-glycosyl transferase complex subunit), Sec61 (a translocon subunit), and Pmt1 (a protein O-mannosyltransferase). The resulting fusion proteins localize to the periphery of LDs in both yeast and mammalian cells. This peripheral LD localization of the fusion proteins, however, is due to redistribution of the ER around LDs, as revealed by bimolecular fluorescence complementation between ER- and LD-localized partners in cells coexpressing the membrane-anchored perilipin. A LD-tethering function of PLIN3-containing membrane proteins was confirmed by fusing PLIN3 to the cytoplasmic domain of OM14, an outer mitochondrial membrane protein. Expression of OM14-PLIN3 resulted in close apposition of mitochondria and LDs. Taken together, these data indicate that the LD surface constitutes a barrier for ER-localized integral membrane spanning proteins.
Mind reading of the proteins: Deep-learning to forecast molecular dynamics
Authors: Gupta Chitrak , Cava John Kevin , Sarkar Daipayan , Wilson Eric , Vant John , Murray Steven , Singharoy Abhishek , Karmaker Shubhra Kanti 
Published: July 2020

AbstractMolecular dynamics (MD) simulations have emerged to become the back-bone of today’s computational biophysics. Simulation tools such as, NAMD, AMBER and GROMACS have accumulated more than 100,000 users. Despite this remarkable success, now also bolstered by compatibility with graphics processor units (GPUs) and exascale computers, even the most scalable simulations cannot access biologically relevant timescales - the number of numerical integration steps necessary for solving differential equations in a million-to-billion-dimensional space is computationally in-tractable. Recent advancements in Deep Learning has made it such that patterns can be found in high dimensional data. In addition, Deep Learning have also been used for simulating physical dynamics. Here, we utilize LSTMs in order to predict future molecular dynamics from current and previous timesteps, and examine how this physics-guided learning can benefit researchers in computational biophysics. In particular, we test fully connected Feed-forward Neural Networks, Recurrent Neural Networks with LSTM / GRU memory cells with TensorFlow and PyTorch frame-works trained on data from NAMD simulations to predict conformational transitions on two different biological systems. We find that non-equilibrium MD is easier to train and performance improves under the assumption that each atom is independent of all other atoms in the system. Our study represents a case study for high-dimensional data that switches stochastically between fast and slow regimes. Applications of resolving these sets will allow real-world applications in the interpretation of data from Atomic Force Microscopy experiments.
Fast cortical dynamics encode tactile grating orientation during active touch
Authors: Harrell Evan R. , Renard Anthony , Bathellier Brice 
Published: July 2020

AbstractTouch-based object recognition relies on perception of compositional tactile features like roughness, shape, and surface orientation. However, besides roughness, it remains unclear how these different tactile features are encoded to guide perception. Here, we establish a barrel cortex-dependent perceptual task in which mice discriminate tactile gratings based on orientation using only their whiskers. Multi-electrode recordings in barrel cortex reveal weak orientation tuning in average firing rates during grating exploration despite high levels of cortical activity. Just before decision, orientation information extracted from fast cortical dynamics more closely resembles concurrent psychophysical measurements than single neuron orientation tuning curves. This temporal code conveys both stimulus and choice-related information, suggesting that fast cortical dynamics during exploration of a tactile object both reflect the physical stimulus and impact the upcoming perceptual decision of the animal.
Wavefront-sensorless adaptive optics with a laser-free spinning disk confocal microscope
Authors: Hussain Syed Asad , Kubo Toshiki , Hall Nicholas , Gala Dalia , Hampson Karen , Parton Richard , Phillips Mick A. , Wincott Matthew , Fujita Katsumasa , Davis Ilan , Dobbie Ian , Booth Martin J. 
Published: July 2020

AbstractAdaptive optics is being applied widely to a range of microscopies in order to improve imaging quality in the presence of specimen-induced aberrations. We present here the first implementation of wavefront-sensorless adaptive optics for a laser-free, aperture correlation, spinning disk microscope. This widefield method provides confocal-like optical sectioning through use of a patterned disk in the illumination and detection paths. Like other high-resolution microscopes, its operation is compromised by aberrations due to refractive index mismatch and variations within the specimen. Correction of such aberrations shows improved signal level, contrast and resolution.
Co-circulation of multiple influenza A variants in swine harboring genes from seasonal human and swine influenza viruses
Authors: Ryt-Hansen Pia , Krog Jesper Schak , Østergaard Breum Solvej , Hjulsager Charlotte Kristiane , Pedersen Anders Gorm , Trebbien Ramona , Larsen Lars Erik 
Published: July 2020

AbstractSince the influenza pandemic in 2009, there has been an increased focus on swine influenza A virus (swIAV) surveillance. This paper describes the results of the surveillance of swIAV in Danish swine from 2011 to 2018.In total, 3800 submissions were received with a steady increase in swIAV positive submissions, reaching 56% in 2018. Ten different swIAV subtypes were detected. Full genome sequences were obtained from 129 swIAV positive samples. Altogether, 17 different circulating genotypes were identified including novel reassortants and subtypes harboring human seasonal IAV gene segments. The phylogenetic analysis revealed substantial genetic drift and also evidence of positive selection occurring mainly in antigenic sites of the hemagglutinin protein and confirmed the presence of a swine divergent cluster among the H1pdm09Nx viruses.The results provide essential data for the control of swIAV in pigs and for early detection of novel swIAV strains with zoonotic potential.
Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions
Authors: Griffis Joseph C. , Metcalf Nicholas V. , Corbetta Maurizio , Shulman Gordon L. 
Published: July 2020

AbstractLesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain’s structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.
Drug Screening with Zebrafish Visual Behavior Identifies Carvedilol as a Potential Treatment for Retinitis Pigmentosa
Authors: Ganzen Logan , Ko MeeJung , Zhang Mengrui , Xie Rui , Chen Yongkai , Zhang Liyun , James Rebecca , Mumm Jeff , van Rijn Richard , Zhong Wenxuan , Pang Chi Pui , Zhang Mingzhi , Tsujikawa Motokazu , Leung Yuk Fai 
Published: July 2020

AbstractRetinitis Pigmentosa (RP) is an incurable inherited retinal degeneration affecting approximately 1 in 4,000 individuals globally. The goal of this work was to identify drugs that can help patients suffering from the disease. To accomplish this, we screened drugs on a zebrafish RP model. This model expresses a truncated humanrhodopsintransgene (Tg(rho:Hsa.RH1_Q344X)) causing significant rod degeneration by 7 days post-fertilization (dpf). Consequently, the larvae displayed a deficit in visual motor response (VMR) under scotopic condition. The diminished VMR was leveraged to screen an ENZO SCREEN-WELL® REDOX library since oxidative stress is postulated to play a role in RP progression. Our screening identified a beta-blocker, carvedilol, that ameliorated the deficient VMR of the RP larvae and increased their rod number. Carvedilol can act directly on rods as it affected the adrenergic pathway in a rod-like human Y79 cell line. Since carvedilol is an FDA-approved drug, our findings suggest that carvedilol can potentially be repurposed to treat RP patients.Summary StatementThis paper presents the utilization of zebrafish visual behavior, a novel paradigm to screen and identify drugs to treat retinitis pigmentosa, an incurable retinal-degenerative disease.
Crystal structure reveals the full Ras:Raf interface and advances mechanistic understanding of Raf activation
Authors: Cookis Trinity , Mattos Carla 
Published: July 2020

AbstractThe interaction between Ras and Raf-kinase through the Ras-binding (RBD) and cysteine-rich domains (CRD) of Raf is essential for signaling through the mitogen-activated protein kinase (MAPK) pathway, yet the molecular mechanism leading to Raf activation has remained elusive. We present the 2.8 Å crystal structure of the HRas/CRaf-RBD_CRD complex showing the Ras/Raf interface as a continuous surface on Ras. In the Ras dimer, with helices roughly perpendicular to the membrane, the CRD is located between the two Ras protomers and far from the membrane, where its dynamic nature in the Ras binding pocket is expected to accommodate BRaf and CRaf heterodimers. Our structure and its analysis by MD simulations, combined with work in the literature, result in a molecular model in which Ras binding is involved in the release of Raf autoinhibition while the Ras/Raf complex dimerizes to promote a platform for signal amplification, with Raf-CRD poised to have direct and allosteric effects on both the Ras active site and the dimerization interface.
Paracoccidioides HSP90 can be found in the cell surface and is a target for antibodies with therapeutic potential
Authors: Moura Ágata Nogueira D’Áurea , de Oliveira Diane Sthefany Lima , Paredes Verenice , Rocha Letícia Barboza , Casadevall Arturo , Albuquerque Patrícia , Felipe Maria Sueli Soares , Piazza Roxane Maria Fontes , Nicola André Moraes 
Published: July 2020

AbstractParacoccidioidomycosis (PCM) is one of the most frequent systemic mycoses in Latin America. It affects mainly male rural workers in impoverished regions, and the therapy can last up to two years or use drugs that are very toxic. Given the need for novel safe and effective approaches to treat PCM, we have been developing monoclonal antibodies (mAbs) that could be used not only to block specific fungal targets, but also modulate the host’s antifungal immunity. In this work we show the generation of and promising results with a mAb against HSP90, a molecular chaperone that is an important virulence factor in fungi. Using recombinantParacoccidioides lutzii(Pb01) andP. brasiliensis(Pb18) HSP90 proteins produced inE. coli, we immunized mice and generated polyclonal antibodies and an IgG1 hybridoma mAb. The proteins were very immunogenic and both the polyclonal serum and mAb were used in immunofluorescence experiments, which showed binding of antibodies to the yeast cell surface. The mAb successfully opsonizedP. lutziiandP. brasiliensiscells in co-incubations with J774.16 macrophage-like cells. Our results suggest that this mAb could serve as the basis for new immunotherapy regimens for PCM.Author summaryParacoccidioidomycosis (PCM) is a severe disease caused by fungi, common in Latin America. It is treatable, but some of the drugs that are available are very toxic or not very effective, and the treatment can take as long as two years to clear the infection. To address the need for improved therapeutic alternatives, we have been developing drug candidates based on antibody technologies againstParacoccidioides brasiliensisandP. lutzii, which cause PCM. In this work, we produced monoclonal antibodies (mAbs) that bind to the fungal protein HSP90, which is essential for fungal cells to survive. One mAb, 4D11, recognized the HSP90 target on the surface of fungal cells. These antibody-covered cells were ingested more efficiently by immune cells called macrophages, suggesting they could improve the host resistance to infection byParacoccidioides. Future improvements on these antibodies could thus lead to more effective and safer PCM treatments.
Variation in relaxation of non-photochemical quenching in a soybean nested association mapping panel as a potential source for breeding improved photosynthesis
Authors: Burgess Steven J. , de Becker Elsa , Cullum Stephanie , Causon Isla , Floristeanu Iulia , Chan Kher Xing , Moore Caitlin E. , Diers Brian W. , Long Stephen P. 
Published: July 2020

AbstractImproving the efficiency of crop photosynthesis has the potential to increase yields. Genetic manipulation showed photosynthesis can be improved in Tobacco by speeding up relaxation of photoprotective mechanisms, known as non-photochemical quenching (NPQ), during high to low light transitions. However, it is unclear if natural variation in NPQ relaxation can be exploited in crop breeding programs. To address this issue, we measured NPQ relaxation in the 41 parents of a soybean NAM population in field experiments in Illinois during 2018 and 2019. There was significant variation in amount and rate of fast, energy dependent quenching (qE) between genotypes. However, strong environmental effects led to a lack of correlation between values measured over the two growing season, and low broad-sense heritability estimates (< 0.3). These data suggest that either improvements in screening techniques, or transgenic manipulation, will be required to unlock the potential for improving the efficiency of NPQ relaxation in soybean.Table of Abbreviations
Early Clinical Factors Predicting the Development of Critical Disease in Japanese Patients with COVID-19: A Single-Center Retrospective, Observational Study
Authors: Higuchi Takatoshi , Nishida Tsutomu , Iwahashi Hiromi , Morimura Osamu , Otani Yasushi , Okauchi Yukiyoshi , Yokoe Masaru , Suzuki Norihiro , Inada Masami , Abe Kinya 
Published: July 2020

ABSTRACTBackgroundInsufficient evidence of factors predicting the COVID-19 progression from mild to moderate to critical has been established. We retrospectively evaluated risk factors for critical progression in Japanese COVID-19 patients.MethodSeventy-four laboratory-confirmed COVID-19 patients were hospitalized in our hospital between February 20, 2020, and June 10, 2020. We excluded asymptomatic, non-Japanese, and child patients. We divided patients into the stable group (SG) and the progression group (PG) (patients requiring mechanical ventilation). We compared the clinical factors in both groups. We established the cutoff values (COVs) for significantly different factors via receiver operating characteristic (ROC) curve analysis and evaluated risk factors by univariate regression.ResultsWe enrolled 57 COVID-19 patients (median age 52 years, 56.1% male). The median progression time from symptom onset was eight days. Seven patients developed critical disease (PG: 12.2%), two (3.5%) of whom died; 50 had stable disease. Univariate logistic analysis identified elevated lactate dehydrogenase (LDH) (COV: 309 U/l), decreased estimated glomerular filtration rate (eGFR) (COV: 68 ml/min), lymphocytopenia (COV: 980/μl), and statin use as significantly associated with disease progression. However, in Cox proportional hazards analysis, lymphocytopenia at symptom onset was not significant.ConclusionsWe identified three candidate risk factors for adult Japanese patients with mild to moderate COVID-19: statin use, elevated LDH level, and decreased eGFR.
Model stability of COVID-19 mortality prediction with biomarkers
Authors: Huang Chenyan , Long Xi , Zhan Zhuozhao , van den Heuvel Edwin 
Published: July 2020

AbstractCoronavirus disease 2019 (COVID-19) is an unprecedented and fast evolving pandemic, which has caused a large number of critically ill patients and deaths globally. It is an acute public health crisis leading to overloaded critical care capacity. Timely prediction of the clinical outcome (death/survival) of hospital-admitted COVID-19 patients can provide early warnings to clinicians, allowing improved allocation of medical resources. In a recently published paper, an interpretable machine learning model was presented to predict the mortality of COVID-19 patients with blood biomarkers, where the model was trained and tested on relatively small data sets. However, the model or performance stability was not explored and assessed. By re-analyzing the data, we reveal that the reported mortality prediction performance was likely over-optimistic and its uncertainty was underestimated or overlooked, with a large variability in predicting deaths.