bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive Genome Based Analysis ofVibrio parahaemolyticusfor Identifying Novel Drug and Vaccine Molecules: Subtractive Proteomics and Vaccinomics Approach
Authors: Hasan Mahmudul , Azim Kazi Faizul , Imran Abdus Shukur , Chowdhury Ishtiak Malique , Akhter Urme Shah Rucksana , Parvez Md Sorwer Alam , Uddin Md Bashir , Uddin Ahmed Syed Sayeem 
Published: April 2020

AbstractMultidrug-resistantVibrio parahaemolyticushas become a significant threat to human health as well as aquaculture, prioritizing the development of effective drug and vaccine candidates. Hence, the study was designed to identify novel therapeutics using a comprehensive genome-based analysis ofV. parahaemolyticus.FromV. parahaemolyticusproteome, a total of 4822 proteins were investigated in order to find out effective drug and vaccine targets. A range of diverse subtractive proteomics approaches – namely, identification of human non-homologous and pathogen-specific essential proteins, druggability and ‘anti-target’ analysis, prediction of subcellular localization, human microbiome non-homology screening, analysis of virulence factors, protein-protein interactions studies. Among 16 novel cytoplasmic proteins, ‘VIBPA Type II secretion system protein L’ and ‘VIBPA Putative fimbrial protein Z’ were allowed to molecular docking with 350 human metabolites, which revealed that Eliglustat, Simvastatin and Hydroxocobalamin were the top drug molecules considering free binding energy. On the contrary, ‘Sensor histidine protein kinase UhpB’ and ‘Flagellar hook-associated protein of 25 novel membrane proteins were subjected to T and B cell epitope prediction, antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking were adopted to generate the most immunogenic epitopes. Three subunit vaccines were constructed by the combination of highly antigenic epitopes along with suitable adjuvant, PADRE sequence and linkers. The designed vaccine constructs (V1, V2, V3) were analyzed by their physiochemical properties and molecular docking with MHC molecules that suggested the superiority of construct V1. Besides, the binding affinity of human TLR1/2 heterodimer and construct V1 was also biologically significant. The vaccine-receptor complex exhibited deformability at a minimum level that also strengthened our prediction. The optimized codons of the designed construct was cloned into pET28a(+) vector ofE. colistrain K12. However, the predicted drug molecules and vaccine constructs could be further studied to combatV. parahaemolyticusassociated infections.
Blocking antibodies against SARS-CoV-2 RBD isolated from a phage display antibody library using a competitive biopanning strategy
Authors: Zeng Xin , Li Lingfang , Lin Jing , Li Xinlei , Liu Bin , Kong Yang , Zeng Shunze , Du Jianhua , Xiao Huahong , Zhang Tao , Zhang Shelin , Liu Jianghai 
Published: April 2020

AbstractThe infection of the novel coronavirus SARS-CoV-2 have caused more than 150,000 deaths, but no vaccine or specific therapeutic antibody is currently available. SARS-CoV-2 relies on its spike protein, in particular the receptor binding domain (RBD), to bind human cell receptor angiotensin-converting enzyme 2 (ACE2) for viral entry, and thus targeting RBD holds the promise for preventing SARS-CoV-2 infection. In this work, a competitive biopanning strategy of a phage display antibody library was applied to screen blocking antibodies against RBD. High-affinity antibodies were enriched after the first round using a standard panning process in which RBD-His recombinant protein was immobilized as a bait. At the next two rounds, immobilized ACE2-Fc and free RBD-His proteins were mixed with the enriched phage antibodies. Antibodies binding to RBD at epitopes different from ACE2-binding site were captured by the immobilized ACE2-Fc, forming a “sandwich” complex. Only antibodies competed with ACE2 for recognizing RBD at the same or similar epitopes can bind to the free RBD-His in the supernatant and be subsequently separated by the Ni-NTA magnetic beads. Top 1 lead from the competitive biopanning of a synthetic antibody library, Lib AB1, was produced as the full-length IgG1 format. It was proved to competitively block the binding of RBD to ACE2 protein, and potently inhibit SARS-CoV-2 pseudovirus infection of ACE2-overexpressing Hela cells with IC50 values of 12nM. Nevertheless, top 1 lead from the standard biopanning of Lib AB1, can only bind to RBDin vitrobut not have the blocking or neutralization activity. Our strategy can efficiently isolate the blocking antibodies of RBD, and it would speed up the discovery of neutralizing antibodies against SARS-CoV-2.
A refined method to monitor arousal from hibernation in the European hamster
Authors: Markussen Fredrik A. S. , Melum Vebjørn J. , Bothorel Béatrice , Hazlerigg David G. , Simonneaux Valérie , Wood Shona H. 
Published: April 2020

AbstractBackgroundHibernation is a physiological and behavioural adaptation that permits survival during periods of reduced food availability and extreme environmental temperatures. This is achieved through cycles of metabolic depression and reduced body temperature (torpor) and rewarming (arousal). Rewarming from torpor is achieved through the activation of brown adipose tissue (BAT) associated with a rapid increase in ventilation frequency. Here, we studied the rate of rewarming in the European hamster (Cricetus cricetus) by measuring both BAT temperature, core body temperature and ventilation frequency.ResultsTemperature was monitored in parallel in the BAT (IPTT tags) and peritoneal cavity (iButtons) during hibernation torpor-arousal cycling. We found that increases in brown fat temperature preceded core body temperature rises by about 48 min, with a maximum re-warming rate of 20.9°C*h−1. Re-warming was accompanied by a significant increase in ventilation frequency. The rate of rewarming was slowed by the presence of a spontaneous thoracic mass in one of our animals. Core body temperature re-warming was reduced by 6.2°C*h−1and BAT rewarming by 12°C*h−1. Ventilation frequency was increased by 77% during re-warming in the affected animal compared to a healthy animal. Inspection of the position and size of the mass indicated it was obstructing the lungs and heart.ConclusionsWe have used a minimally invasive method to monitor BAT temperature during arousal from hibernation illustrating BAT re-warming significantly precedes core body temperature re-warming, informing future study design on arousal from hibernation. We also showed compromised re-warming from hibernation in an animal with a mass obstructing the lungs and heart, likely leading to inefficient ventilation and circulation.
A shared neural substrate for action verbs and observed actions in human posterior parietal cortex
Authors: Aflalo T. , Zhang C. , Rosario E.R. , Pouratian N. , Orban G.A. , Andersen R.A. 
Published: April 2020

AbstractHigh-level sensory and motor cortical areas are activated when processing the meaning of language, but it is unknown whether, and how, words share a neural substrate with corresponding sensorimotor representations. We recorded from single neurons in human posterior parietal cortex (PPC) while participants viewed action verbs and corresponding action videos from multiple views. We find that PPC neurons exhibit a common neural substrate for action verbs and observed actions. Further, videos were encoded with mixtures of invariant and idiosyncratic responses across views. Action verbs elicited selective responses from a fraction of these invariant and idiosyncratic neurons, without preference, thus associating with a statistical sampling of the diverse sensory representations related to the corresponding action concept. Controls indicated the results are not the product of visual imagery nor arbitrary learned associations. Our results suggest that language may activate the consolidated visual experience of the reader.
Studies on CRMP2 SUMOylation-deficient transgenic mice identify sex-specific NaV1.7 regulation in the pathogenesis of chronic neuropathic pain
Authors: Moutal Aubin , Cai Song , Yu Jie , Stratton Harrison J. , Chefdeville Aude , Gomez Kimberly , Ran Dongzhi , Madura Cynthia L. , Boinon Lisa , Soto Maira , Zhou Yuan , Shan Zhiming , Chew Lindsey A. , Rodgers Kathleen E. , Khanna Rajesh 
Published: April 2020

AbstractThe sodium channel NaV1.7 is a master regulator of nociceptive neuronal firing. Mutations in this channel can result in painful conditions as well as produce insensitivity to pain. Despite being recognized as a “poster child” for nociceptive signaling and human pain, targeting NaV1.7 has not yet produced a clinical drug. Recent work has illuminated the NaV1.7 interactome, offering insights into the regulation of these channels and identifying potentially new druggable targets. Amongst the regulators of NaV1.7 is the cytosolic collapsin response mediator protein 2 (CRMP2). CRMP2, modified at Lysine 374 (K374) by addition of a small ubiquitin-like modifier (SUMO), bound NaV1.7 to regulate its membrane localization and function. Corollary to this, preventing CRMP2 SUMOylation was sufficient to reverse mechanical allodynia in rats with neuropathic pain. Notably, loss of CRMP2 SUMOylation did not compromise other innate functions of CRMP2. To further elucidate thein vivorole of CRMP2 SUMOylation in pain, we generated CRMP2 K374A knock-in (CRMP2K374A/K374A) mice in which Lys374 was replaced with Ala. CRMP2K374A/K374Amice had reduced NaV1.7 membrane localization and function in female, but not male, sensory neurons. Behavioral appraisal of CRMP2K374A/K374Amice demonstrated no changes in depressive or repetitive, compulsive-like behaviors, and a decrease in noxious thermal sensitivity. No changes were observed in CRMP2K374A/K374Amice to inflammatory, acute, or visceral pain. In contrast, in a neuropathic model, CRMP2K374A/K374Amice failed to develop persistent mechanical allodynia. Our study suggests that CRMP2 SUMOylation-dependent control of peripheral NaV1.7 is a hallmark of chronic, but not physiological, neuropathic pain.
PyRice: a Python package for queryingOryza Sativadatabases
Authors: Do Quan , Hai Ho Bich , Larmande Pierre 
Published: April 2020

AbstractSummaryCurrently, gene information available forOryza sativaspecies is located in various online heterogeneous data sources. Moreover, methods of access are also diverse, mostly web-based and sometimes query APIs, which might not always be straightforward for domain experts. The challenge is to collect information quickly from these applications and combine it logically, to facilitate scientific research. We developed a Python package named PyRice, a unified programming API to access all supported databases at the same time with consistent output. PyRice design is modular and implements a smart query system which fits the computing resources to optimize the query speed. As a result, PyRice is easy to use and produces intuitive results.Availability and implementationhttps://github.com/SouthGreenPlatform/PyRiceDocumentationhttps://pyrice.readthedocs.ioContactpierre.larmande@ird.frLicence informationMITSupplementary informationSupplementary data are available online.
Ecosystem Entanglement and the Propagation of Nutrient-Driven Instability
Authors: McCann Kevin S. , MacDougall A.S , Fussmann G.F. , Bieg C. , Cazelles K. , Cristescu M.E. , Fryxell J.M. , Gellner G. , Lapointe B. , Gonzalez A. 
Published: April 2020

ABSTRACTAlmost 50 years ago, Michael Rosenzweig pointed out that nutrient addition can destabilize food webs, leading to loss of species and reduced ecosystem function through the paradox of enrichment. Around the same time, David Tilman demonstrated that increased nutrient loading would also be expected to cause competitive exclusion leading to deleterious changes in food web diversity. While both concepts have greatly illuminated general diversity-stability theory, we currently lack a coherent framework to predict how nutrients influence food web stability across a landscape. This is a vitally important gap in our understanding, given mounting evidence of serious ecological disruption arising from anthropogenic displacement of resources and organisms. Here, we combine contemporary theory on food webs and meta-ecosystems to show that nutrient additions are indeed expected to drive loss in stability and function in human-impacted regions. However, this loss in stability occurs not just from wild oscillations in population abundance, but more frequently from the complete loss of an equilibrium due to edible plant species being competitively excluded. In highly modified landscapes, spatial nutrient transport theory suggests that such instabilities can be amplified over vast distances from the sites of nutrient addition. Consistent with this theoretical synthesis, the empirical frequency of these distant propagating ecosystem imbalances appears to be growing. This synthesis of theory and empirical data suggests that human modification of the Earth’s ecological connectivity is “entangling” once distantly separated ecosystems, causing rapid, expansive, and costly nutrient-driven instabilities over vast areas of the planet. The corollary to this spatial nutrient theory, though -- akin to weak interaction theory from food web networks -- is that slow spatial nutrient pathways can be potent stabilizers by moderating flows across a landscape.
Deep learning model can predict water binding sites on the surface of proteins using limited-resolution data
Authors: Zaucha Jan , Softley Charlotte A. , Sattler Michael , Popowicz Grzegorz M. 
Published: April 2020

ABSTRACTThe surfaces of proteins are generally hydrophilic but there have been reports of sites that exhibit an exceptionally high affinity for individual water molecules. Not only do such molecules often fulfil critical biological functions, but also, they may alter the binding of newly designed drugs. In crystal structures, sites consistently occupied in each unit cell yield electron density clouds that represent water molecule presence. These are recorded in virtually all high-resolution structures obtained through X-ray diffraction. In this work, we utilized the wealth of data from the RCSB Protein Data Bank to train a residual deep learning model named ‘hotWater’ to identify sites on the surface of proteins that are most likely to bind water, the so-called water hot spots. The model can be used to score existing water molecules from a PDB file to provide their ranking according to the predicted binding strength or to scan the surface of a protein to determine the most likely water hot-spotsde novo. This is computationally much more efficient than currently used molecular dynamics simulations. Based on testing the model on three example proteins, which have been resolved using both high-resolution X-ray crystallography (providing accurate positions of trapped waters) as well as low-resolution X-ray diffraction, NMR or CryoEM (where structure refinement does not yield water positions), we were able to show that the hotWater method is able to recover in the “water-free” structures many water binding sites known from the high-resolution structures. A blind test on a newly solved protein structure with waters removed from the PDB also showed good prediction of the crystal water positions. This was compared to two known algorithms that use electron density and was shown to have higher recall at resolutions >2.6 Å. We also show that the algorithm can be applied to novel proteins such as the RNA polymerase complex from SARS-CoV-2, which could be of use in drug discovery. The hotWater model is freely available at (https://pypi.org/project/hotWater/).
Cold adaptation drives population genomic divergence in the ecological specialist,Drosophila montana
Authors: Wiberg R. A. W. , Tyukmaeva V. , Hoikkala A. , Ritchie M. G. , Kankare M. 
Published: April 2020

ABSTRACTDetecting signatures of ecological adaptation in comparative genomics is challenging, but analysing population samples with characterised geographic distributions, such as clinal variation, can help identify genes showing covariation with important ecological variation. Here we analysed patterns of geographic variation in the cold-adapted speciesDrosophila montanaacross phenotypes, genotypes and environmental conditions and tested for signatures of cold adaptation in population genomic divergence. We first derived the climatic variables associated with the geographic distribution of 24 populations across two continents to trace the scale of environmental variation experienced by the species, and measured variation in the cold tolerance of the flies of six populations from different geographic contexts. We then performed pooled whole genome sequencing of these six populations, and used Bayesian methods to identify SNPs where genetic differentiation is associated with both climatic variables and the population phenotypic measurements, while controlling for effects of demography and population structure. The top candidate SNPs were enriched on the X and 4thchromosomes, and they also lay near genes implicated in other studies of cold tolerance and population divergence in this species and its close relatives. We conclude that ecological adaptation has contributed to the divergence ofD. montanapopulations throughout the genome and in particular on the X and 4thchromosomes, which also showed highest interpopulation FST. This study demonstrates that ecological selection can drive genomic divergence at different scales, from candidate genes to chromosome-wide effects.
Efficacy and safety of decompressive craniectomy with non-suture duraplasty in patients with traumatic brain injury
Authors: Jeong Tae Seok , Yee Gi Taek , Lim Tae Gyu , Kim Woo Kyung , Yoo Chan Jong 
Published: April 2020

AbstractBackgroundDecompressive craniectomy is an important surgical treatment for patients with severe traumatic brain injury (TBI). Several reports have been published on the efficacy of non-watertight sutures in duraplasty performed in decompressive craniectomy. This study aims to evaluate the effectiveness of dura closure without sutures (non-suture duraplasty) in decompressive craniectomy for TBI.MethodsOne hundred and six patients were enrolled at a single trauma center between January 2017 and December 2018. We retrospectively collected the data and classified the patients into non-suture and suture duraplasty craniectomy groups. We compared the characteristics of patients and their intra/post- operative findings such as operative time, blood loss, imaging findings, complications, and Glasgow outcome scale.ResultsThere were 37 patients in the non-suture group and 69 in the suture craniectomy group. There were no significant differences between the two groups with regard to general characteristics. The operative time was 205 min for the suture duraplasty group and 150 min for the non-suture duraplasty group, and that for the non-suture duraplasty group was significantly lesser (p=0.002). Blood loss was significantly lesser in the non-suture duraplasty group (1000 mL) than in the suture duraplasty group (1500 mL, p=0.028). There were no other significant differences.ConclusionNon-suture duraplasty involved shorter operative time and lesser blood loss when compared to suture duraplasty. Other complications and prognosis were similar in both groups. Therefore, it can be concluded that decompressive craniectomy with non-suture duraplasty is a safe and useful surgical technique in patients with TBI.
Naringenin downregulates inflammation-mediated nitric oxide overproduction and potentiates endogenous antioxidant status during hyperglycemia
Authors: Rehman Kanwal , Khan Ikram Ilahee , Akash Muhammad Sajid Hamid , Jabeen Komal , Haider Kamran , Tariq Muhammad 
Published: April 2020

AbstractNitric oxide (NO) is a key regulating factor for physiological functions, when elevated during inflammatory conditions can lower endogenous antioxidant levels. Increased NO interacts with oxygen or other ROS to generate peroxynitrite, a potent oxidant which induces oxidative stress. Analgesic effects of naringenin (NRN), a flavanone has been demonstrated by inducing anti-inflammatory effects in O2−•-mediated inflammation. NRN stimulates antioxidant enzymes and also improves glucose uptake. Hence this study was designed to look for therapeutic effects of NRN and in comparison, to metformin (MET) on inflammation-mediated increased NO and decreased antioxidant superoxide dismutase (SOD) in diabetic rat model with compromised glycemic and lipid profile. After single intraperitoneal injection of alloxan (120 mg/kg), the rats were equally divided as Group 1 and 2 which received normal saline and no-treatment respectively while group 3 and 4 received MET 50 mg/kg/day and NRN 50 mg/kg/day respectively. Blood samples were collected at 0, 15thand 30thday of treatment period. Results showed that alloxan significantly increased serum level of glucose (P<0.001), NO (P<0.001) and inflammatory biomarkers (TNF-α, IL-6), however, it expressively decreased serum SOD and insulin level. While, NRN significantly downregulated glucose (P<0.05), lipid profile, TNF-α, IL-6 and normalized level of NO (P<0.01). It also improved SOD level as compared to that of MET-treatment. Histopathology of pancreas also showed significant improvement in morphology after NRN treatment. This work delivers that NRN exerts anti-oxidant effect in part by downregulating the inflammation-mediated NO overproduction and improving level of SOD resulting in potentiation of endogenous antioxidant defense.
Predicting Longitudinal Disease Severity for Individuals with Parkinson’s Disease using Functional MRI and Machine Learning Prognostic Models
Authors: Nguyen Kevin P. , Raval Vyom , Treacher Alex , Mellema Cooper , Yu Frank , Pinho Marco C. , Subramaniam Rathan M. , Dewey Richard B. , Montillo Albert 
Published: April 2020

AbstractParkinson’s disease is the second most common neurodegenerative disorder and is characterized by the loss of ability to control voluntary movements. Predictive biomarkers of progression in Parkinson’s Disease are urgently needed to expedite the development of neuroprotective treatments and facilitate discussions about disease prognosis between clinicians and patients. Resting-state functional magnetic resonance imaging (rs-fMRI) shows promise in predicting progression, with derived measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF), having been previously been associated withcurrentdisease severity. In this work, ReHo and fALFF features from 82 Parkinson’s Disease subjects are used to train machine learning predictors of baseline clinical severity and progression at 1 year, 2 years, and 4 years follow-up as measured by the Movement Disorder Society Unified Depression Rating Scale (MDS-UPDRS) score. This is the first time that rs-fMRI and machine learning have been combined to predictfuturedisease progression. The machine learning models explain up to 30.4% (R2= 0.304) of the variance in baseline MDS-UPDRS scores, 55.8% (R2= 0.558) of the variance in year 1 scores, and 47.1% (R2= 0.471) of the variance in year 2 scores with high statistical significance (p <0.0001). For distinguishing high- and low-progression individuals (MDS-UPDRS score above or below the median), the models achieve positive predictive values of up to 71% and negative predictive values of up to 84%. The models learn patterns of ReHo and fALFF measures that predict better and worse prognoses. Higher ReHo and fALFF in regions of the default motor network predicted lower current severity and lower future progression. The rs-fMRI features in the temporal lobe, limbic system, and motor cortex were also identified as predictors. These results present a potential neuroimaging biomarker that accurately predicts progression, which may be useful as a clinical decision-making tool and in future trials of neuroprotective treatments.