bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robust and sensitive detection of SARS-CoV-2 using PCR based methods
Authors: Park Changwoo , Lee Jina , Hassan Zohaib ul , Ku Keun Bon , Kim Seong Jun , Kim Hong Gi , Park Edmond Changkyun , Park Gun-Soo , Park Daeui , Baek Seung-Hwa , Park Dongju , Lee Jihye , Jeon Sangeun , Kim Seungtaek , Lee Chang-Seop , Yoo Hee Min , Kim Seil 
Published: July 2020

AbstractThe World Health Organization (WHO) has declared the Coronavirus disease 2019 (COVID-19) as an international health emergency. Current diagnostic tests are based on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method, the gold standard test that involves the amplification of viral RNA. However, the RT-qPCR assay has limitations in terms of sensitivity and quantification. In this study, we tested both qPCR and droplet digital PCR (ddPCR) to detect low amounts of viral RNA. The cycle threshold (CT) of viral RNA by RT-PCR significantly varied according to the sequence of primer and probe sets with in vitro transcript (IVT) RNA or viral RNA as templates, whereas the copy number of viral RNA by ddPCR was effectively quantified with IVT RNA, cultured viral RNA, and RNA from clinical samples. Furthermore, the clinical samples were assayed via both methods, and the sensitivity of the ddPCR was determined to be significantly higher than RT-qPCR. These findings suggest that ddPCR could be used as a highly sensitive and compatible diagnostic method for viral RNA detection.
Volatile organic compounds from entomopathogenic and nematophagous fungi, repel banana black weevil (Cosmopolites sordidus)
Authors: Lozano-Soria Ana , Picciotti Ugo , Lopez-Moya Federico , Lopez-Cepero Javier , Porcelli Francesco , Lopez-Llorca Luis Vicente 
Published: July 2020

AbstractFungal Volatile Organic Compounds (VOCs) repel banana black weevil (BW),Cosmopolites sordidus(Germar, 1824), the key-pest of banana (Musaspp.). The entomopathogensBeauveria bassiana(Bb1TS11) andMetarhizium robertsii(Mr4TS04) were isolated from banana plantation soils using an insect bait. Bb1TS11 and Mr4TS04 were pathogenic to BW adults. Bb1TS11, Bb203 (from infected palm weevils), Mr4TS04 and the nematophagous fungusPochonia clamydosporia(Pc123), were tested for VOCs production. VOCs were identified by Gas Chromatography/Mass Spectrometry - Solid-Phase Micro Extraction (GC/MS-SPME). GC/MS-SPME identified a total of 97 VOCs in all strains tested. Seven VOCs (C1 – C7) were selected for their abundance or previous record as insect repellents. BW starved adults in the dark showed the highest mobility to banana corm in olfactometry bioassays. C7, produced by all fungal strains, is the best BW repellent (p<0.05), followed by C5. The rest of VOCs have a milder repellency to BW. C1 and C2 (known to repel palm weevil) block the attraction of banana corm and BW pheromone to BW adults in bioassays. Therefore, VOCs from biocontrol fungi can be used in future studies for biomanagement of BW in the field.
Topographic gradients of intrinsic dynamics across neocortex
Authors: Shafiei Golia , Markello Ross D. , de Wael Reinder Vos , Bernhardt Boris C. , Fulcher Ben D. , Misic Bratislav 
Published: July 2020

AbstractThe intrinsic dynamics of neuronal populations are shaped by both macroscale connectome architecture and microscale attributes. Neural activity arising from the interplay of these local and global factors therefore varies from moment to moment, with rich temporal patterns. Here we comprehensively characterize intrinsic dynamics throughout the human brain. Applying massive temporal feature extraction to regional haemodynamic activity, we estimate over 6,000 statistical properties of individual brain regions’ time series across the neocortex. We identify two robust topographic gradients of intrinsic dynamics, one spanning a ventromedial-dorsolateral axis and the other spanning a unimodal-transmodal axis. These gradients are distinct in terms of their temporal composition and reflect spatial patterns of microarray gene expression, intracortical myelin and cortical thickness, as well as structural and functional network embedding. Importantly, these gradients are closely correlated with patterns of functional activation, differentiating cognitiveversusaffective processing and sensoryversushigher-order cognitive processing. Altogether, these findings demonstrate a link between microscale and macroscale architecture, intrinsic dynamics, and cognition.
Modulation of triple artemisinin-based combination therapy pharmacodynamics byPlasmodium falciparumgenotype
Authors: Ansbro Megan R. , Itkin Zina , Chen Lu , Zahoranszky-Kohalmi Gergely , Amaratunga Chanaki , Miotto Olivo , Peryea Tyler , Hobbs Charlotte V. , Suon Seila , Sá Juliana M. , Dondorp Arjen M. , van der Pluijm Rob W. , Wellems Thomas E. , Simeonov Anton , Eastman Richard T. 
Published: July 2020

AbstractThe first-line treatments for uncomplicatedPlasmodium falciparummalaria are artemisinin-based combination therapies (ACTs), consisting of an artemisinin derivative combined with a longer acting partner drug. However, the spread ofP. falciparumwith decreased susceptibility to artemisinin and partner drugs presents a significant challenge to malaria control efforts. To stem the spread of drug resistant parasites, novel chemotherapeutic strategies are being evaluated, including the implementation of triple artemisinin-based combination therapies (TACTs). Currently, there is limited knowledge on the pharmacodynamics and pharmacogenetic interactions of proposed TACT drug combinations. To evaluate these interactions, we established anin vitrohigh-throughput process for measuring the drug dose-response to three distinct antimalarial drugs present in a TACT. Sixteen different TACT combinations were screened against fifteen parasite lines from Cambodia, with a focus on parasites with differential susceptibilities to piperaquine and artemisinins. Analysis revealed drug-drug interactions unique to specific genetic backgrounds, including antagonism between piperaquine and pyronaridine associated with gene amplification ofplasmepsin II/III, two aspartic proteases that localize to the parasite digestive vacuole. From this initial study, we identified parasite genotypes with decreased susceptibility to specific TACTs, as well as potential TACTs that display antagonism in a genotype-dependent manner. Our assay and analysis platform can be further leveraged to inform drug implementation decisions and evaluate next-generation TACTs.One Sentence SummaryIn vitroprocess to evaluate triple-drug combinations for prioritizing antimalarial combinations forin vivoevaluation.
Neural correlates of modal displacement and discourse-updating under (un)certainty
Authors: Tulling Maxime , Law Ryan , Cournane Ailís , Pylkkänen Liina 
Published: July 2020

ABSTRACTA hallmark of human thought is the ability to think about not just the actual world, but also about alternative ways the world could be. One way to study this contrast is through language. Language has grammatical devices for expressing possibilities and necessities, such as the wordsmightormust. With these devices, called “modal expressions,” we can study the actual vs. possible contrast in a highly controlled way. While factual utterances such as “There is a monster under my bed” update thehere-and-nowof a discourse model, a modal version of this sentence, “There might be a monster under my bed,” displaces from thehere-and-nowand merely postulates a possibility. We used magnetoencephalography (MEG) to test whether the processes of discourse updating and modal displacement dissociate in the brain. Factual and modal utterances were embedded in short narratives, and across two experiments, factual expressions increased the measured activity over modal expressions. However, the localization of the increase appeared to depend on perspective: signal localizing in right temporo-parietal areas increased when updating others’ beliefs, while frontal medial areas seem sensitive to updating one’s own beliefs. The presence of modal displacement did not elevate MEG signal strength in any of our analyses. In sum, this study identifies potential neural signatures of the process by which facts get added to our mental representation of the world.
Class A Penicillin-Binding Protein-mediated cell wall synthesis promotes structural integrity during peptidoglycan endopeptidase insufficiency
Authors: Murphy Shannon G. , Murtha Andrew N. , Zhao Ziyi , Alvarez Laura , Diebold Peter , Shin Jung-Ho , VanNieuwenhze Michael S. , Cava Felipe , Dörr Tobias 
Published: July 2020

AbstractThe bacterial cell wall is composed primarily of peptidoglycan (PG), a poly-aminosugar that is essential to sustain cell shape, growth and structural integrity. PG is synthesized by two different types of synthase complexes (class A Penicillin-binding Proteins [PBP]s/Lpos and Shape, Elongation, Division, Sporulation [SEDS]/class B PBP pairs) and degraded by ‘autolytic’ enzymes to accommodate growth processes. It is thought that autolsyin activity (and particulary the activity of endopeptidases, EPs) is required for PG synthesis and incorporation by creating gaps that are patched and paved by PG synthases, but the exact relationship between autolysins and the separate synthesis machineries remains incompletely understood. Here, we have probed the consequences of EP depletion for PG synthesis in the diarrheal pathogenVibrio cholerae. We found that EP depletion resulted in severe morphological defects, increased cell mass, a decline in viability, and continuing (yet aberrant) incorporation of cell wall material. Mass increase and cell wall incorporation proceeded in the presence of Rod system inhibitors, but was abolished upon inhibition of aPBPs. However, the Rod system remained functional (i.e., exhibited sustained directed motion) even after prolonged EP depletion, without effectively promoting cell elongation. Lastly, heterologous expression of an EP fromNeisseria gonorrhoeaecould fully complement growth and morphology of an EP-insufficientV. cholerae. Overall, our findings suggest that inV. cholerae, the Rod system requires endopeptidase activity (but not necessarily direct interaction with EPs) to promote cell expansion and substantial PG incorporation, whereas aPBPs are able to engage in sacculus construction even during severe EP insufficiency.ImportanceSynthesis and turnover of the bacterial cell wall must be tightly co-ordinated to avoid structural integrity failure and cell death. Details of this coordination are poorly understood, particularly if and how cell wall turnover enzymes are required for the activity of the different cell wall synthesis machines. Our results suggest that inVibrio cholerae, one class of turnover enzymes, the endopeptidases, are required only for substantial PG incorporation mediated by the Rod system, while the aPBPs maintain structural integrity during endopeptidase insufficiency. Our results suggest that aPBPs are more versatile than the Rod system in their ability to recognize cell wall gaps formed by autolysins other than the major endopeptidases, adding to our understanding of the co-ordination between autolysins and cell wall synthases. A detailed understanding of autolysin biology may promote the development of antibiotics that target these essential turnover processes.
MicroRNA-based cancer mortality risk scoring system and hTERT expression linked with risk-adjusted treatment strategy in early-stage oral squamous cell carcinoma
Authors: Yoon Angela J. , Santella Regina M. , Wang Shuang , Kutler David I. , Carvajal Richard D. , Philipone Elizabeth , Wang Tian , Peters Scott M. , Stewart Claire R. , Momen-Heravi Fatemeh , Troob Scott , Levin Matt , AkhavanAghdam Zohreh , Shackelford Austin J. , Canterbury Carleigh R. , Shimonosono Masataka , Nakagawa Hiroshi 
Published: July 2020

ABSTRACTWe have developed and validated a novel microRNA (miRNA)-based prognostic model to predict survival outcome in oral squamous cell carcinoma (OSCC) patients who are already categorized into ‘early-stage’ by the TNM system. A total of 836 early-stage OSCC patients were assigned the mortality risk scores. We evaluated the efficacy of various treatment regimens in terms of survival benefit compared to surgery only in patients stratified into high and low mortality risk categories. Within the high-risk group, surgery with neck dissection significantly improved the 5-year survival to 75% from 46% (p<0.001) with surgery only. A Cox proportional hazard model on time-to-death suggests a hazard ratio of 0.37 when comparing surgery with neck dissection to surgery only (95% CI: 0.2-0.6; p=0.0005). For the low-risk group, surgery only without neck dissection was the most beneficial treatment modality, as opposed to the high-risk group, in which surgery with neck dissection significantly improved 5-year survival. Regardless of treatment selected, those with risk score ≥1 may benefit from additional therapy to prevent cancer relapse. Based on functional analysis of the prognostic miRNAs, we identified hTERT (human telomerase reverse transcriptase) as a promising drug target to prevent cancer relapse, thereby improving cancer-free survival. We also established a functional platform for patient-derived organoid-based drug testing in an effort to link prognostic marker-based mortality risk assessment with appropriate risk-adjusted therapy to improve overall survival.
Fungal microbiomes are determined by host phylogeny and exhibit widespread associations with the bacterial microbiome
Authors: Harrison Xavier A. , McDevitt Allan D. , Dunn Jenny C. , Griffiths Sarah , Benvenuto Chiara , Birtles Richard , Boubli Jean P. , Bown Kevin , Bridson Calum , Brooks Darren , Browett Samuel S. , Carden Ruth F. , Chantrey Julian , Clever Friederike , Coscia Ilaria , Edwards Katie L. , Ferry Natalie , Goodhead Ian , Highlands Andrew , Hopper Jane , Jackson Joseph , Jehle Robert , da Cruz Kaizer Mariane , King Tony , Lea Jessica M. D. , Lenka Jessica L. , McCubbin Alexandra , McKenzie Jack , de Moraes Bárbara Lins Caldas , O’Meara Denise B. , Pescod Poppy , Preziosi Richard F. , Rowntree Jennifer K. , Shultz Susanne , Silk Matthew J. , Stockdale Jennifer E. , Symondson William O. C. , de la Pena Mariana Villalba , Walker Susan L. , Wood Michael D. , Antwis Rachael E. 
Published: July 2020

ABSTRACTInteractions between hosts and their resident microbial communities are a fundamental component of fitness for both agents. Though recent research has highlighted the importance of interactions between animals and their bacterial communities, comparative evidence for fungi is lacking, especially in natural populations. Using data from 49 species, we present novel evidence of strong covariation between fungal and bacterial communities across the host phylogeny, indicative of recruitment by hosts for specific suites of microbes. Using co-occurrence networks, we demonstrate that fungi form critical components of putative microbial interaction networks, where the strength and frequency of interactions varies with host taxonomy. Host phylogeny drives differences in overall richness of bacterial and fungal communities, but the effect of diet on richness was only evident in mammals and for the bacterial microbiome. Collectively these data indicate fungal microbiomes may play a key role in host fitness and suggest an urgent need to study multiple agents of the animal microbiome to accurately determine the strength and ecological significance of host-microbe interactions.SIGNIFICANCE STATEMENTMicrobes perform vital metabolic functions that shape the physiology of their hosts. However, almost all research to date in wild animals has focused exclusively on the bacterial microbiota, to the exclusion of other microbial groups. Although likely to be critical components of the host microbiome, we have limited knowledge of the drivers of fungal composition across host species. Here we show that fungal community composition is determined by host species identity and phylogeny, and that fungi form extensive interaction networks with bacteria in the microbiome of a diverse range of animal species. This highlights the importance of microbial interactions as mediators of microbiome-health relationships in the wild.
Towards the design of multiepitope-based peptide vaccine candidate against SARS-CoV-2
Authors: Odhar Hasanain Abdulhameed , Ahjel Salam Waheed , Humadi Suhad Sami 
Published: July 2020

AbstractCoronavirus disease 2019 is a current pandemic health threat especially for elderly patients with comorbidities. This respiratory disease is caused by a beta coronavirus known as severe acute respiratory syndrome coronavirus 2. The disease can progress into acute respiratory distress syndrome that can be fatal. Currently, no specific drug or vaccine are available to combat this pandemic outbreak. Social distancing and lockdown have been enforced in many places worldwide. The spike protein of coronavirus 2 is essential for viral entry into host target cells via interaction with angiotensin converting enzyme 2. This viral protein is considered a potential target for design and development of a drug or vaccine. Previously, we have reported several potential epitopes on coronavirus 2 spike protein with high antigenicity, low allergenicity and good stability against specified proteases. In the current study, we have constructed and evaluated a peptide vaccine from these potential epitopes by using in silico approach. This construct is predicted to have a protective immunogenicity, low allergenicity and good stability with minor structural flaws in model build. The population coverage of the used T-cells epitopes is believed to be high according to the employed restricted alleles. The vaccine construct can elicit efficient and long-lasting immune response as appeared through simulation analysis. This multiepitope-based peptide vaccine may represent a potential candidate against coronavirus 2. However, further in vitro and in vivo verification are required.
ConnecTF: A platform to build gene networks by integrating transcription factor-target gene interactions
Authors: Brooks M.D. , Juang C.-L. , Katari M.S. , Alvarez J.M. , Pasquino A.V. , Shih H.-J. , Huang J. , Shanks C. , Cirrone J. , Coruzzi G.M. 
Published: July 2020

AbstractDeciphering gene regulatory networks (GRNs) is both a promise and challenge of systems biology. The promise is identifying key transcription factors (TFs) that enable an organism to react to changes in its environment. The challenge is constructing GRNs that involve hundreds of TFs and hundreds of thousands of interactions with their genome-wide target genes validated by high-throughput sequencing. To address this challenge, we developed ConnecTF, a species-independent web-based platform for constructing validated GRNs and to refine inferred GRNs via combined analysis of genome-wide studies of TF-target gene binding, TF-target regulation and other TF-centric omic data. We demonstrate the functionality of ConnecTF in three case studies, showing how integration within and across TF-target datasets uncovers biological insights. Case study 1 uses integration of TF-target gene regulation and binding datasets to uncover mode-of-action and identify potential TF partners for 14 TFs in abscisic acid signaling. Case study 2 demonstrates how genome-wide TF-target data and automated functions in ConnecTF are used to conduct precision/recall analysis and pruning of an inferred GRN for nitrogen signaling. In case study 3, we use ConnecTF to chart a network path from NLP7, a master TF in nitrogen signaling, to direct secondary TF2s, to its indirect targets, in an approach called Network Walking. The public version of ConnecTF (https://ConnecTF.org) contains 3,738,278 TF-target interactions for 423 TFs in Arabidopsis, and 839,210 TF-target interactions for 139 TFs in maize. The database and tools in ConnecTF should advance the exploration of GRNs in plant systems biology applications for models and crops.
Sequence dependent co-phase separation of RNA-protein mixtures elucidated using molecular simulations
Authors: Regy Roshan Mammen , Dignon Gregory L. , Zheng Wenwei , Kim Young Chan , Mittal Jeetain 
Published: July 2020

ABSTRACTRibonucleoprotein (RNP) granules are membraneless organelles (MLOs) which majorly consist of RNA and RNA-binding proteins and are formed via liquid-liquid phase separation (LLPS). Experimental studies investigating the drivers of LLPS have shown that intrinsically disordered proteins (IDPs) and nucleic acids like RNA play a key role in modulating protein phase separation. There is currently a dearth of modelling techniques which allow one to delve deeper into how RNA plays its role as a modulator/promoter of LLPS in cells using computational methods. Here we present a coarse-grained RNA model developed to fill this gap, which together with our recently developed HPS model for protein LLPS, allows us to capture the factors driving RNA-protein co-phase separation. We explore the capabilities of the modelling framework with the LAF-1 RGG/RNA system which has been well studied in experiments and also with the HPS model previously. Further taking advantage of the fact that the HPS model maintains sequence specificity we explore the role of charge patterning on controlling RNA incorporation into condensates. With increased charge patterning we observe formation of structured or patterned condensates which suggests the possible roles of RNA in not only shifting the phase boundaries but also introducing microscopic organization in MLOs.
Recurrent Neural Network-based Acute Concussion Classifier using Raw Resting State EEG Data
Authors: Thanjavur Karun , Babul Arif , Foran Brandon , Bielecki Maya , Gilchrist Adam , Hristopulos Dionissios T. , Brucar Leyla R. , Virji-Babul Naznin 
Published: July 2020

ABSTRACTConcussion is a global health concern. Despite its high prevalence, a sound understanding of the mechanisms underlying this type of diffuse brain injury remains elusive. It is, however, well established that concussions cause significant functional deficits; that children and youths are disproportionately affected and have longer recovery time than adults; and recovering individuals are more prone to suffer additional concussions, with each successive injury increasing the risk of long term neurological and mental health complications. Currently, concussion management faces two significant challenges: there are no objective, clinically accepted, brain-based approaches for determining (i) whether an athlete has suffered a concussion, and (ii) when the athlete has recovered. Diagnosis is based on clinical testing and self-reporting of symptoms and their severity. Self-reporting is highly subjective and symptoms only indirectly reflect the underlying brain injury. Here, we introduce a deep learning Long Short Term Memory (LSTM)-based recurrent neural network that is able to distinguish between healthy and acute post-concussed adolescent athletes using only a short (i.e. 90 seconds long) sample of resting state EEG data as input. The athletes were neither required to perform a specific task nor subjected to a stimulus during data collection, and the acquired EEG data was neither filtered, cleaned of artefacts, nor subjected to explicit feature extraction. The LSTM network was trained and tested on data from 27 male, adolescent athletes with sports related concussion, bench marked against 35 healthy, adolescent athletes. During rigorous testing, the classifier consistently identified concussions with an accuracy of >90% and its ensemble-median Area Under the Curve (AUC) corresponds to 0.971. This is the first instance of a high-performing classifier that relies only on easy-to-acquire resting state EEG data. It represents a key step towards the development of an easy-to-use, brain-based, automatic classification of concussion at an individual level.