bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kindlin2-mediated phase separation underlies integrin adhesion formation
Authors: Li Yujie , Zhang Ting , Li Huadong , Yang Haibin , Lin Ruihong , Sun Kang , Wang Lei , Zhang Jing , Wei Zhiyi , Yu Cong 
Published: July 2020

AbstractFormation of cell-extracellular matrix adhesion requires assembly of the transmembrane receptor integrins and their intracellular activators, kindlin and talin proteins in minutes. The mechanisms governing the rapid formation and dynamics of the adhesion remain enigmatic. Here, we reported that the dimerized-kindlin2 underwent phase separation with clustered-integrin in solution and on lipid bilayer. The kindlin2/integrin condensate can further enrich other components for the adhesion complex assembly. The full-length structure of kindlin2 was solved and revealed that the kindlin2 dimers can further pack with each other to form a higher oligomer. Disrupting the intermolecular interaction between the kindlin2 dimer inhibits the phase formation on 2D membrane in vitro and impaired the adhesion formation, integrin activation, and cell spreading in cultured cells. We also determined the full-length structure of kindlin2 in its monomeric conformation. Structural analysis and biochemical characterization indicate that the interdomain interaction control the monomer-dimer transition of kindlin2, providing a regulation mechanism of the kindlin2-mediated phase separation. Our findings not only provide a mechanistic explanation for the formation and dynamic regulation of the integrin-based adhesion, but also shed light on understanding of how the clustered receptors participate in assembly of the functional membrane domains via phase separation.
Identification of parallel pH- and zeaxanthin-dependent quenching of excess energy in LHCSR3 in Chlamydomonas reinhardtii
Authors: Troiano Julianne M. , Perozeni Federico , Moya Raymundo , Zuliani Luca , Baek Kwangryul , Jin EonSeon , Cazzaniga Stefano , Ballottari Matteo , Schlau-Cohen Gabriela S. 
Published: July 2020

AbstractUnder high light conditions, oxygenic photosynthetic organisms avoid photodamage by thermally dissipating excess absorbed energy, which is called non-photochemical quenching (NPQ). In green algae, a chlorophyll and carotenoid-binding protein, light-harvesting complex stress-related (LHCSR3), detects excess energy via pH and serves as a quenching site. However, the mechanisms by which LHCSR3 functions have not been determined. Using a combined in vivo and in vitro approach, we identify two parallel yet distinct quenching processes, individually controlled by pH and carotenoid composition, and their likely molecular origin within LHCSR3 from Chlamydomonas reinhardtii. The pH-controlled quenching is removed within a mutant LHCSR3 that lacks the protonable residues responsible for sensing pH. Constitutive quenching in zeaxanthin-enriched systems demonstrates zeaxanthin-controlled quenching, which may be shared with other light-harvesting complexes. We show that both quenching processes prevent the formation of damaging reactive oxygen species, and thus provide distinct timescales and mechanisms of protection in a changing environment.
Allosteric modulation of GABAAreceptors in rat basolateral amygdala blocks stress-enhanced reacquisition of nicotine self-administration
Authors: Sharp Burt M , Jiang Qin , Simone Xenia , Scholze Petra 
Published: July 2020

AbstractStress is a major determinant of relapse to smoked tobacco. In a rat model, repeated stress during abstinence from nicotine self-administration (SA) results in enhanced reacquisition of nicotine SA, which is dependent on the basolateral amygdala (BLA). We postulate that repeated stress during abstinence causes hyperexcitability of BLA principal output neurons (PN) due to disinhibition of PN from reduced inhibitory regulation by local GABAergic interneurons. To determine if enhanced GABAergic regulation of BLA PNs can lessen the effects of stress on nicotine intake, positive allosteric modulators (PAMs) of GABAAreceptors were infused into the BLA immediately prior to reacquisition of nicotine SA. Three selective PAMs (e.g., NS 16085, DCUK-OEt, DS2) with varied GABAAsubunit specificities abolished the stress-induced amplification of nicotine taking during reacquisition. These studies indicate that highly selective PAMS targeting α3 or δ subunit-containing GABAAin BLA may be effective in ameliorating the stress-induced relapse to smoked tobacco during abstinence from cigarettes.
Improved characterisation of clinical text through ontology-based vocabulary expansion
Authors: Slater Luke T , Bradlow William , Ball Simon , Hoehndorf Robert , Gkoutos Georgios V 
Published: July 2020

AbstractBackgroundBiomedical ontologies contain a wealth of metadata that constitutes a fundamental infrastructural resource for text mining. For several reasons, redundancies exist in the ontology ecosystem, which lead to the same concepts being described by several terms in the same or similar contexts across several ontologies. While these terms describe the same concepts, they contain different sets of complementary metadata. Linking these definitions to make use of their combined metadata could lead to improved performance in ontology-based information retrieval, extraction, and analysis tasks.ResultsWe develop and present an algorithm that expands the set of labels associated with an ontology class using a combination of strict lexical matching and cross-ontology reasoner-enabled equivalency queries. Across all disease terms in the Disease Ontology, the approach found51,362additional labels, more than tripling the number defined by the ontology itself. Manual validation by a clinical expert on a random sampling of expanded synonyms over the Human Phenotype Ontology yielded a precision of0.912. Furthermore, we found that annotating patient visits in MIMIC-III with an extended set of Disease Ontology labels led to semantic similarity score derived from those labels being a significantly better predictor of matching first diagnosis, with a mean average precision of0.88for the unexpanded set of annotations, and0.913for the expanded set.ConclusionsInter-ontology synonym expansion can lead to a vast increase in the scale of vocabulary available for text mining applications. While the accuracy of the extended vocabulary is not perfect, it nevertheless led to a significantly improved ontology-based characterisation of patients from text in one setting. Furthermore, where run-on error is not acceptable, the technique can be used to provide candidate synonyms which can be checked by a domain expert.
Somatotopic specificity of perceptual and neurophysiological changes associated with visuo-proprioceptive realignment
Authors: Mirdamadi Jasmine L. , Seigel Courtney R. , Husch Stephen D. , Block Hannah J. 
Published: July 2020

AbstractSpatial realignment of visual and proprioceptive estimates of hand position can occur in response to a perturbation. E.g., viewing the hand underwater while washing dishes. This form of multisensory perceptual learning presumably affects perceived hand position, which is used in movement planning. Consistent with this idea, we recently observed changes in motor cortex (M1) index finger representation associated with visuo-proprioceptive misalignment at that fingertip (Munoz-Rubke et al., 2017). In three experiments with healthy human participants, we asked whether these changes are specific to the brain’s representation of the misaligned finger (somatotopically focal), or whether they extend to other parts of the hand and arm that would be needed to move the misaligned finger (somatotopically broad). In Experiments 1 and 2, participants experienced misaligned or veridical visuo-proprioceptive information about the index fingertip. Before and after the perceptual alignment task, we used transcranial magnetic stimulation (TMS) to assess M1 representation of five hand and arm muscles. The index finger representation showed the expected association between M1 excitability and visuo-proprioceptive realignment, as did the pinkie finger representation to a lesser extent. Forearm flexors, forearm extensors, and biceps did not show any such relationship. In Experiment 3, we asked subjects to indicate their proprioceptive estimate of the fingertip, knuckle, wrist, and elbow, before and after misalignment at the fingertip. Proprioceptive realignment at the knuckle, but not the wrist or elbow, was correlated with realignment at the fingertip. These results suggest the effects of perceptual perturbation are somatotopically focal in both sensory and motor domains.Significance StatementMultisensory and motor processing have largely been examined separately, limiting our understanding of how these systems interact. Motor adaptation is thought to affect somatosensory perception and neurophysiology, but the reverse interaction, an effect of perceptual learning on the motor system, has rarely been considered. Here we examine the effect of a somatotopically localized visuo-proprioceptive perturbation on motor neurophysiology and conscious perception. We found somatotopically-focal effects in both domains. This correspondence highlights the tight relationship between sensory and motor systems, but also raises the possibility that perceptual learning may not generalize to other body parts as motor learning does. Rather, it appears to create a localized distortion in the multisensory body representation, with correspondingly local changes in the motor cortex representation.
Visualization of Collagen–Mineral Arrangement using Atom Probe Tomography
Authors: Lee Bryan E.J. , Langelier Brian , Grandfield Kathryn 
Published: July 2020

AbstractBone is a complex, hierarchical structure comprised of two distinct phases: the organic, collagen– rich phase and the inorganic mineral–rich phase. This collagen–mineral arrangement has implications for bone function, aging, and disease. However, strategies to extract a single mineralized collagen fibril to investigate the interplay between components with sufficient resolution have been mostly confined toin vitrosystems that only approximate the biological environment or transmission electron microscopy studies with lower spatial and chemical resolution. Therefore, there is extensive debate over the location of mineral with respect to collagen inin vivomineralized tissues as visualization and quantification of the mineral in a living system is difficult or impossible. Herein, we have developed an approach to artificially extract a single mineralized collagen fibril from bone to analyze its composition and structure atom-by-atom with 3D resolution and sub-nanometer accuracy using atom probe tomography. This enables, for the first time, a method to probe fibril-level mineralization and collagen–mineral arrangement from anin vivosystem with both the spatial and chemical precision required to comment on collagen– mineral arrangement. Using atom probe tomography, 4D (spatial + chemical) reconstructed volumes of leporine bone were generated with accuracy from correlative scanning electron microscopy. Distinct, winding collagen fibrils were identified with mineralized deposits both encapsulating and incorporated into the collagenous structures. This work demonstrates a novel fibril-level detection method that can be used to probe structural and chemical changes of bone and contribute new insights to the debate on collagen–mineral arrangement in mineralized tissues such as bones, and teeth.
Extensive hybridization reveals multiple coloration genes underlying a complex plumage phenotype
Authors: Aguillon Stepfanie M. , Walsh Jennifer , Lovette Irby J. 
Published: July 2020

ABSTRACTColoration is an important target of both natural and sexual selection. Discovering the genetic basis of color differences can help us to understand how this visually striking phenotype evolves. Hybridizing taxa with both clear color differences and shallow genomic divergences are unusually tractable for associating coloration phenotypes with their causal genotypes. Here, we leverage the extensive admixture between two common North American woodpeckers—yellow-shafted and red-shafted flickers—to identify the genomic bases of six distinct plumage patches involving both melanin and carotenoid pigments. Comparisons between flickers across ~8.5 million genome-wide SNPs show that these two forms differ at only a small proportion of the genome (meanFST= 0.007). Within the few highly differentiated genomic regions, we identify 408 SNPs significantly associated with four of the six plumage patches. These SNPs are linked to multiple genes known to be involved in melanin and carotenoid pigmentation. For example, a gene (CYP2J19) known to cause yellow to red color transitions in other birds is strongly associated with the yellow versus red differences in the wings and tail feathers of these flickers. Additionally, our analyses suggest novel links between known melanin genes and carotenoid coloration. Our finding of patch-specific control of plumage coloration adds to the growing body of literature suggesting color diversity in animals could be created through selection acting on novel combinations of coloration genes.
Plate reader microrheology
Authors: Hawkins Robert F. , Duncan Gregg A. 
Published: July 2020

AbstractIn this work, we report the development of a simplified microrheological method that can be used to rapidly study soft materials. This approach uses fluorescence polarization and a plate reader format to measure the rotational diffusion of nanoparticles within a sample of interest. We show that this measurement is sensitive to viscosity-dependent changes in polymeric soft materials and is correlated with particle tracking microrheology, a previously validated measure of microrheology. Using these fluorescence polarization-based measurements, we describe formalism that enables reasonable estimation of viscosity in polymeric materials after accounting for length-scale dependent effects of the polymer environment on the nanoparticle rotational diffusion. The use of a plate reader format allows this approach to be higher throughput, less technically challenging, and more widely accessible than standard macro- and microrheological methods, making it available to non-experts. This approach has potential applications in academic and industry settings where conventional rheological equipment may not be available, as well as in clinical settings to rapidly characterize human clinical samples.
InpherNet provides attractive monogenic disease gene hypotheses using patient genes indirect neighbors
Authors: Yoo Boyoung , Birgmeier Johannes , Bernstein Jonathan A. , Bejerano Gill 
Published: July 2020

AbstractClose to 70% of patients suspected to have a Mendelian disease remain undiagnosed after genome sequencing, partly because our current knowledge about disease-causing genes is incomplete. Although hundreds of new diseases-causing genes are discovered every year, the discovery rate has been constant for over a decade. Generating an attractive novel disease gene hypothesis from patient data can be time-consuming as each patient’s genome can contain dozens to hundreds of rare, possibly pathogenic variants. To generate the most plausible hypothesis, many sources of indirect evidence about each candidate variant may be considered. We introduce InpherNet, a network-based machine learning approach to accelerate this process. InpherNet ranks candidate genes based on gene neighbors from 4 graphs, of orthologs, paralogs, functional pathway members, and co-localized interaction partners. As such InpherNet can be used to both prioritize potentially novel disease genes and also help reveal known disease genes where their direct annotation is missing, or partial. InpherNet is applied to over 100 patient cases for whom the causative gene is incorrectly given low priority by two clinical gene ranking methods that rely exclusively on human patient-derived evidence. It correctly ranks the causative gene among its top 5 candidates in 68% of the cases, compared to 9-44% using comparable tools including Phevor, Phive and hiPhive.
Community prevalence of SARS-CoV-2 virus in England during May 2020: REACT study
Authors:   REACT Study Investigators, Riley Steven , Ainslie Kylie E. C. , Eales Oliver , Jeffrey Benjamin , Walters Caroline E. , Atchison Christina , Diggle Peter J. , Ashby Deborah , Donnelly Christl A. , Cooke Graham , Barclay Wendy , Ward Helen , Taylor Graham , Darzi Ara , Elliott Paul 
Published: July 2020

AbstractBackgroundEngland has experienced one of the highest rates of confirmed COVID-19 mortality in the world. SARS-CoV-2 virus has circulated in hospitals, care homes and the community since January 2020. Our current epidemiological knowledge is largely informed by clinical cases with far less understanding of community transmission.MethodsThe REal-time Assessment of Community Transmission (REACT) study is a nationally representative prevalence survey of SARS-CoV-2 virus swab-positivity in the community in England. We recruited participants regardless of symptom status.ResultsWe found 159 positives from 120,610 swabs giving an average prevalence of 0.13% (95% CI: 0.11%,0.15%) from 1st May to 1st June 2020. We showed decreasing prevalence with a halving time of 8.6 (6.2, 13.6) days, implying an overall reproduction number R of 0.57 (0.45, 0.72). Adults aged 18 to 24 yrs had the highest swab-positivity rates, while those >64 yrs had the lowest. Of the 126 participants who tested positive with known symptom status in the week prior to their swab, 39 reported symptoms while 87 did not, giving an estimate that 69% (61%,76%) of people were symptom-free for the 7 days prior testing positive in our community sample. Symptoms strongly associated with swab-positivity were: nausea and/or vomiting, diarrhoea, blocked nose, loss of smell, loss of taste, headache, chills and severe fatigue. Recent contact with a known COVID-19 case was associated with odds of 24 (16, 38) for swab-positivity. Compared with non-key workers, odds of swab-positivity were 7.7 (2.4, 25) among care home (long-term care facilities) workers and 5.2 (2.9, 9.3) among health care workers. However, some of the excess risk associated with key worker status was explained by recent contact with COVID-19 cases. We found no strong evidence for geographical variability in positive swab results.ConclusionOur results provide a reliable baseline against which the impact of subsequent relaxation of lockdown can be assessed to inform future public health efforts to control transmission.
A neural network model for UAV propulsion system
Authors: Işık Gültekin , Ekici Selçuk , Şahin Gökhan 
Published: July 2020

Purpose
Determining the performance parameters of the propulsion systems of the aircraft, which is the key product of the aviation industry, plays a critical role in reducing adverse environmental impacts. Therefore, the purpose of this paper is to present a temperature performance template for turbojet engines at the design stage using a neural network model that defines the relationship between the performance parameters obtained from ground tests of a turbojet engine used in unmanned aerial vehicles (UAV).

Design/methodology/approach
The main parameters of the flow passing through the engine of the UAV propulsion system, where ground tests were performed, were obtained through the data acquisition system and injected into a neural network model created. Fifteen sensors were mounted on the engine – six temperature sensors, six pressure sensors, two flow meters and one load cell were connected to the data acquisition system to make sense of this physical environment. Subsequently, the artificial neural network (ANN) model as a complement to the approach was used. Thus, the predicted model relationship with the experimental data was created.

Findings
Fuel flow and thrust parameters were estimated using these components as inputs in the feed-forward neural network. In the network experiments to estimate fuel flow parameter, r-square and mean absolute error were calculated as 0.994 and 0.02, respectively. Similarly, for thrust parameter, these metrics were calculated as 0.994 and 1.42, respectively. In addition, the correlation between fuel flow, thrust parameters and each input parameters was examined. According to this, air compressor inlet (ACinlet,temp) and outlet (ACoutlet,temp) temperatures and combustion chamber (CCinlet,temp, CCoutlet,temp) temperature parameters were determined to affect the output the most. The proposed ANN model is applicable to any turbojet engines to model its behavior.

Practical implications
Today, deep neural networks are the driving force of artificial intelligence studies. In this study, the behavior of a UAV is modeled with neural networks. Neural networks are used here as a regressor. A neural network model has been developed that predicts fuel flow and thrust parameters using the real parameters of a UAV turbojet engine. As a result, satisfactory findings were obtained. In this regard, fuel flow and thrust values of any turbojet engine can be estimated using the neural network hyperparameters proposed in this study. Python codes of the study can be accessed from https://github.com/tekinonlayn/turbojet.

Originality/value
The originality of the study is that it reports the relationships between turbojet engine performance parameters obtained from ground tests using the neural network application with open source Python code. Thus, small-scale unmanned aerial propulsion system provides designers with a template showing the relationship between engine performance parameters.
The role of technology readiness in individuals' intention to use health and fitness applications: a comparison between users and non-users
Authors: Chiu Weisheng , Cho Heetae 
Published: July 2020

PurposeThe purpose of this study is to examine individuals' decisions to use health and fitness apps by applying the extended technology readiness and acceptance model (TRAM), which combines technology readiness (TR), the technology acceptance model (TAM) and perceived enjoyment (PEN). Moreover, this study explores the differences between users and non-users regarding their intentions to use health and fitness apps.Design/methodology/approachData collection (n = 206) was conducted using convenience sampling from four large universities in South Korea. The data were analysed by partial least squares structural equation modelling (PLS-SEM) using SmartPLS 3.0.FindingsThe results revealed that positive TR positively affects perceived ease of use (PEOU), perceived usefulness (PU) and PEN, while negative TR had a negative impact only on PEN. Furthermore, the significant relationships between PEOU, PU and PEN were identified. In addition, multigroup analyses indicated that the relationships between positive TR and PEN, between PEN and PEOU, between PEOU and PU, and between PU and behavioural intention were positively stronger for app users.Originality/valueThis study initially applied the TRAM to understand individuals' behavioural intentions to use health and fitness apps. Moreover, this study identified the distinct roles of positive and negative TR affecting individuals' cognition regarding using health and fitness apps. The differences in the psychological processes between app users and non-users offer insights and implications for practitioners.