bluuebunny/crossref_metadata_2025_split huggingface dataset:
Local computational methods to improve the interpretability and analysis of cryo-EM maps
Authors: Kaur Satinder , Gomez-Blanco Josue , Khalifa Ahmad A. Z. , Adinarayanan Swathi , Sanchez-Garcia Ruben , Wrapp Daniel , McLellan Jason S. , Bui Khanh Huy , Vargas Javier 
Published: February 2021

AbstractCryo-electron microscopy (cryo-EM) maps usually show heterogeneous distributions of B-factors and electron density occupancies and are typically B-factor sharpened to improve their contrast and interpretability at high-resolutions. However, ‘over-sharpening’ due to the application of a single global B-factor can distort processed maps causing connected densities to appear broken and disconnected. This issue limits the interpretability of cryo-EM maps, i.e. ab initio modelling. In this work, we propose 1) approaches to enhance high-resolution features of cryo-EM maps, while preventing map distortions and 2) methods to obtain local B-factors and electron density occupancy maps. These algorithms have as common link the use of the spiral phase transformation and are called LocSpiral, LocBSharpen, LocBFactor and LocOccupancy. Our results, which include improved maps of recent SARS-CoV-2 structures, show that our methods can improve the interpretability and analysis of obtained reconstructions.
An ESCRT-dependent step in fatty acid transfer from lipid droplets to mitochondria through VPS13D−TSG101 interactions
Authors: Wang Jingru , Fang Na , Xiong Juan , Du Yuanjiao , Cao Yue , Ji Wei-Ke 
Published: February 2021

AbstractUpon starvation, cells rewire their metabolism, switching from glucose-based metabolism to mitochondrial oxidation of fatty acids, which require the transfer of FAs from lipid droplets (LDs) to mitochondria at mitochondria−LD membrane contact sites (MCSs). However, factors responsible for FA transfer at these MCSs remain uncharacterized. Here, we demonstrate that vacuolar protein sorting-associated protein 13D (VPS13D), loss-of-function mutations of which cause spastic ataxia, coordinates FA trafficking in conjunction with the endosomal sorting complex required for transport (ESCRT) protein tumor susceptibility 101 (TSG101). The VPS13 adaptor-binding domain of VPS13D and TSG101 directly remodels LD membranes in a cooperative manner. The lipid transfer domain of human VPS13D binds glycerophospholipids and FAs in vitro. Depletion of VPS13D, TSG101, or ESCRT-III proteins inhibits FA trafficking from LDs to mitochondria. Our findings suggest that VPS13D mediates the ESCRT-dependent remodeling of LD membranes to facilitate FA transfer at mitochondria-LD contacts.
The DecNef collection, fMRI data from closed-loop decoded neurofeedback experiments
Authors: Cortese Aurelio , Tanaka Saori C. , Amano Kaoru , Koizumi Ai , Lau Hakwan , Sasaki Yuka , Shibata Kazuhisa , Taschereau-Dumouchel Vincent , Watanabe Takeo , Kawato Mitsuo 
Published: February 2021

AbstractDecoded neurofeedback (DecNef) is a form of closed-loop functional magnetic resonance imaging (fMRI) combined with machine learning approaches, which holds some promises for clinical applications. Yet, currently only a few research groups have had the opportunity to run such experiments; furthermore, there is no existing public dataset for scientists to analyse and investigate some of the factors enabling the manipulation of brain dynamics. We release here the data from published DecNef studies, consisting of 5 separate fMRI datasets, each with multiple sessions recorded per participant. For each participant the data consists of a session that was used in the main experiment to train the machine learning decoder, and several (from 3 to 10) closed-loop fMRI neural reinforcement sessions. The large dataset, currently comprising more than 60 participants, will be useful to the fMRI community at large and to researchers trying to understand the mechanisms underlying non-invasive modulation of brain dynamics. Finally, the data collection size will increase over time as data from newly run DecNef studies will be added.
Observational study on wearable biosensors and machine learning-based remote monitoring of COVID-19 patients
Authors: Un Ka-Chun , Wong Chun-Ka , Lau Yuk-Ming , Lee Jeffrey Chun-Yin , Tam Frankie Chor-Cheung , Lai Wing-Hon , Lau Yee-Man , Chen Hao , Wibowo Sandi , Zhang Xiaozhu , Yan Minghao , Wu Esther , Chan Soon-Chee , Lee Sze-Ming , Chow Augustine , Tong Raymond Cheuk-Fung , Majmudar Maulik D. , Rajput Kuldeep Singh , Hung Ivan Fan-Ngai , Siu Chung-Wah 
Published: February 2021

AbstractPatients infected with SARS-CoV-2 may deteriorate rapidly and therefore continuous monitoring is necessary. We conducted an observational study involving patients with mild COVID-19 to explore the potentials of wearable biosensors and machine learning-based analysis of physiology parameters to detect clinical deterioration. Thirty-four patients (median age: 32 years; male: 52.9%) with mild COVID-19 from Queen Mary Hospital were recruited. The mean National Early Warning Score 2 (NEWS2) were 0.59 ± 0.7. 1231 manual measurement of physiology parameters were performed during hospital stay (median 15 days). Physiology parameters obtained from wearable biosensors correlated well with manual measurement including pulse rate (r = 0.96, p < 0.0001) and oxygen saturation (r = 0.87, p < 0.0001). A machine learning-derived index reflecting overall health status, Biovitals Index (BI), was generated by autonomous analysis of physiology parameters, symptoms, and other medical data. Daily BI was linearly associated with respiratory tract viral load (p < 0.0001) and NEWS2 (r = 0.75, p < 0.001). BI was superior to NEWS2 in predicting clinical worsening events (sensitivity 94.1% and specificity 88.9%) and prolonged hospitalization (sensitivity 66.7% and specificity 72.7%). Wearable biosensors coupled with machine learning-derived health index allowed automated detection of clinical deterioration.
Predictors for blood loss and transfusion frequency to guide blood saving programs in primary knee- and hip-arthroplasty
Authors: Pempe Christina , Werdehausen Robert , Pieroh Philip , Federbusch Martin , Petros Sirak , Henschler Reinhard , Roth Andreas , Pfrepper Christian 
Published: February 2021

AbstractEndoprosthetic surgery can lead to relevant blood loss resulting in red blood cell (RBC) transfusions. This study aimed to identify risk factors for blood loss and RBC transfusion that enable the prediction of an individualized transfusion probability to guide preoperative RBC provision and blood saving programs. A retrospective analysis of patients who underwent primary hip or knee arthroplasty was performed. Risk factors for blood loss and transfusions were identified and transfusion probabilities computed. The number needed to treat (NNT) of a potential correction of preoperative anemia with iron substitution for the prevention of RBC transfusion was calculated. A total of 308 patients were included, of whom 12 (3.9%) received RBC transfusions. Factors influencing the maximum hemoglobin drop were the use of drain, tranexamic acid, duration of surgery, anticoagulation, BMI, ASA status and mechanical heart valves. In multivariate analysis, the use of a drain, low preoperative Hb and mechanical heart valves were predictors for RBC transfusions. The transfusion probability of patients with a hemoglobin of 9.0–10.0 g/dL, 10.0–11.0 g/dL, 11.0–12.0 g/dL and 12.0–13.0 g/dL was 100%, 33.3%, 10% and 5.6%, and the NNT 1.5, 4.3, 22.7 and 17.3, while it was 100%, 50%, 25% and 14.3% with a NNT of 2.0, 4.0, 9.3 and 7.0 in patients with a drain, respectively. Preoperative anemia and the insertion of drains are more predictive for RBC transfusions than the use of tranexamic acid. Based on this, a personalized transfusion probability can be computed, that may help to identify patients who could benefit from blood saving programs.
Evaluating patient perspectives on participating in scientific research and clinical trials for the treatment of spinal cord injury
Authors: Bahsoun Soukaina , Kuiper Jan-Herman , Hulme Charlotte H. , Twigg Angus J. Armstrong , El Masri Wagih , Glass Clive , Soni Bakul , Kumar Naveen , Chowdhury Joy Roy , Osman Aheed , Wright Karina T. 
Published: February 2021

AbstractA questionnaire was developed to evaluate patients’ perspective on research aimed at improving functions and overcoming complications associated with spinal cord injury (SCI). The first three sections were based on published and validated assessment tools. The final section was developed to assess participant perspectives on research for SCI. One thousand patients were approached, of which 159 participated. Fifty-eight percent of participants were satisfied with their ‘life as a whole’. Two factors could be generated that reflected the variance in the data regarding participants’ life with a SCI: “Psychosocial and physical wellbeing” and “Independent living”. The majority of participants stated they would be involved in research (86%) or clinical trials (77%). However, the likelihood of participation dropped when potential risks of the research/trials were explained. Which participants would be willing to participate in research could not be predicted based on the severity of their injury, their psychosocial and physical wellbeing or their independent living. Despite participant establishment of a life with SCI, our data indicates that individuals strive for improvements in function. Participant willingness to be included in research studies is noteworthy and scientists and clinicians are encouraged to involve more patients in all aspects of their research.
Genome-wide transcriptome reveals mechanisms underlying Rlm1-mediated blackleg resistance on canola
Authors: Zhai Chun , Liu Xunjia , Song Tao , Yu Fengqun , Peng Gary 
Published: February 2021

AbstractGenetic resistance to blackleg (Leptosphaeria maculans, Lm) of canola (Brassica napus, Bn) has been extensively studied, but the mechanisms underlying the host–pathogen interaction are still not well understood. Here, a comparative transcriptome analysis was performed on a resistant doubled haploid Bn line carrying the resistance gene Rlm1 following inoculation with a virulent (avrLm1) or avirulent (AvrLm1) Lm isolate on cotyledons. A total of 6999 and 3015 differentially expressed genes (DEGs) were identified, respectively, in inoculated local tissues with compatible (susceptible) and incompatible (resistant) interactions. Functional enrichment analysis found several biological processes, including protein targeting to membrane, ribosome and negative regulation of programmed cell death, were over-represented exclusively among up-regulated DEGs in the resistant reaction, whereas significant enrichment of salicylic acid (SA) and jasmonic acid (JA) pathways observed for down-regulated DEGs occurred only in the susceptible reaction. A heat-map analysis showed that both biosynthesis and signaling of SA and JA were induced more significantly in the resistant reaction, implying that a threshold level of SA and JA signaling is required for the activation of Rlm1-mediated resistance. Co-expression network analysis revealed close correlation of a gene module with the resistance, involving DEGs regulating pathogen-associated molecular pattern recognition, JA signaling and transcriptional reprogramming. Substantially fewer DEGs were identified in mock-inoculated (control) cotyledons, relative to those in inoculated local tissues, including those involved in SA pathways potentially contributing to systemic acquired resistance (SAR). Pre-inoculation of cotyledon with either an avirulent or virulent Lm isolate, however, failed to induce SAR on remote tissues of same plant despite elevated SA and PR1 protein. This study provides insights into the molecular mechanism of Rlm1-mediated resistance to blackleg.
A model for screen utility to predict the future of printed solar cell metallization
Authors: Tepner Sebastian , Ney Linda , Singler Marius , Preu Ralf , Pospischil Maximilian , Clement Florian 
Published: February 2021

AbstractFine line screen printing for solar cell metallization is one of the most critical steps in the entire production chain of solar cells, facing the challenge of providing a conductive grid with a minimum amount of resource consumption at an ever increasing demand for higher production speeds. The continuous effort of the industrial and scientific community has led to tremendous progress over the last 20 years, demonstrating an average reduction rate for the finger width of approximately 7 µm per year with the latest highlight of achieving widths of 19 µm. However, further reductions will become a major challenge because commonly used metal pastes are not able to penetrate arbitrary small screen opening structures. Therefore, this study introduces the novel dimensionless parameter screen utility index SUI which quantifies the expected printability of any 2-dimensional screen architecture in reference to a given paste. Further, we present a full theoretical derivation of the SUI, a correlation to experimental results and an in-depth simulation over a broad range of screen manufacturing parameters. The analysis of the SUI predicts the point when commonly used wire materials will fail to provide sufficient meshes for future solar cell metallization tasks. Therefore, novel wire materials (e.g. the use of carbon nanotubes) with very high ultimate tensile strengths are discussed and suggested in order to fulfill the SUI requirements for printing contact fingers with widths below 10 µm. We further analyze economic aspects of design choices for screen angles by presenting an analytical solution for the calculation of mesh cutting losses in industrial screen production. Finally, we combine all aspects by presenting a generalized approach for designing a 2-dimensional screen architecture which fulfills the task of printing at a desired finger width.
Polar lipidomic profile shows Chlorococcum amblystomatis as a promising source of value-added lipids
Authors: Conde Tiago A. , Couto Daniela , Melo Tânia , Costa Margarida , Silva Joana , Domingues M. Rosário , Domingues Pedro 
Published: February 2021

AbstractThere is a growing trend to explore microalgae as an alternative resource for the food, feed, pharmaceutical, cosmetic and fuel industry. Moreover, the polar lipidome of microalgae is interesting because of the reports of bioactive polar lipids which could foster new applications for microalgae. In this work, we identified for the first time the Chlorococcum amblystomatis lipidome using hydrophilic interaction liquid chromatography-high resolution electrospray ionization- tandem mass spectrometry (HILIC–HR–ESI–MS/MS). The Chlorococcum amblystomatis strain had a lipid content of 20.77% and the fatty acid profile, determined by gas chromatography-mass spectrometry, has shown that this microalga contains high amounts of omega-3 polyunsaturated fatty acids (PUFAs). The lipidome identified included 245 molecular ions and 350 lipid species comprising 15 different classes of glycolipids (6), phospholipids (7) and betaine lipids (2). Of these, 157 lipid species and the main lipid species of each class were esterified with omega-3 PUFAs. The lipid extract has shown antioxidant activity and anti-inflammatory potential. Lipid extracts also had low values of atherogenic (0.54) and thrombogenic index (0.27). In conclusion, the lipid extracts of Chlorococcum amblystomatis have been found to be a source of lipids rich in omega-3 PUFAs for of great value for the food, feed, cosmetic, nutraceutical and pharmaceutical industries.
Computational learning of features for automated colonic polyp classification
Authors: Bora Kangkana , Bhuyan M. K. , Kasugai Kunio , Mallik Saurav , Zhao Zhongming 
Published: February 2021

AbstractShape, texture, and color are critical features for assessing the degree of dysplasia in colonic polyps. A comprehensive analysis of these features is presented in this paper. Shape features are extracted using generic Fourier descriptor. The nonsubsampled contourlet transform is used as texture and color feature descriptor, with different combinations of filters. Analysis of variance (ANOVA) is applied to measure statistical significance of the contribution of different descriptors between two colonic polyps: non-neoplastic and neoplastic. Final descriptors selected after ANOVA are optimized using the fuzzy entropy-based feature ranking algorithm. Finally, classification is performed using Least Square Support Vector Machine and Multi-layer Perceptron with five-fold cross-validation to avoid overfitting. Evaluation of our analytical approach using two datasets suggested that the feature descriptors could efficiently designate a colonic polyp, which subsequently can help the early detection of colorectal carcinoma. Based on the comparison with four deep learning models, we demonstrate that the proposed approach out-performs the existing feature-based methods of colonic polyp identification.
Using transcranial Direct Current Stimulation (tDCS) to investigate why faces are and are not special
Authors: Civile Ciro , Quaglia Samantha , Waguri Emika , Ward Maddy , McLaren Rossy , McLaren I. P. L. 
Published: February 2021

AbstractWe believe we are now in a position to answer the question, "Are faces special?" inasmuch as this applies to the face inversion effect (better performance for upright vs inverted faces). Using a double-blind, between-subject design, in two experiments (n = 96) we applied a specific tDCS procedure targeting the Fp3 area while participants performed a matching-task with faces (Experiment 1a) or checkerboards from a familiar prototype-defined category (Experiment 1b). Anodal tDCS eliminated the checkerboard inversion effect reliably obtained in the sham group, but only reduced it for faces (although the reduction was significant). Thus, there is a component to the face inversion effect that we are not affecting with a tDCS procedure that can eliminate the checkerboard inversion effect. We suggest that the reduction reflects the loss of an expertise-based component in the face inversion effect, and the residual is due to a face-specific component of that effect.
Scaling of contact networks for epidemic spreading in urban transit systems
Authors: Qian Xinwu , Sun Lijun , Ukkusuri Satish V. 
Published: February 2021

AbstractImproved mobility not only contributes to more intensive human activities but also facilitates the spread of communicable disease, thus constituting a major threat to billions of urban commuters. In this study, we present a multi-city investigation of communicable diseases percolating among metro travelers. We use smart card data from three megacities in China to construct individual-level contact networks, based on which the spread of disease is modeled and studied. We observe that, though differing in urban forms, network layouts, and mobility patterns, the metro systems of the three cities share similar contact network structures. This motivates us to develop a universal generation model that captures the distributions of the number of contacts as well as the contact duration among individual travelers. This model explains how the structural properties of the metro contact network are associated with the risk level of communicable diseases. Our results highlight the vulnerability of urban mass transit systems during disease outbreaks and suggest important planning and operation strategies for mitigating the risk of communicable diseases.
Diagnosis, clinical characteristics, and outcomes of COVID-19 patients from a large healthcare system in northern New Jersey
Authors: Zhao Yanan , Cunningham Marcus H. , Mediavilla Jose R. , Park Steven , Fitzgerald Sean , Ahn Hee Sang , Li Xiangyang , Zhan Caixin , Hong Tao , Munk Gary , Chow Kar Fai , Perlin David S. 
Published: February 2021

AbstractNew Jersey was an early epicenter for the COVID-19 pandemic in the United States, yet information on hospitalized COVID-19 patients from this area is scarce. This study aimed to provide data on demographics and clinical features of a hospitalized patient population who were confirmed with infection by our in-house (CDI) real-time reverse-transcription polymerase chain reaction (RT-PCR) test. We included consecutive patients who were admitted to Hackensack Meridian Health system hospitals with laboratory-confirmed diagnoses of COVID-19 at Hackensack University Medical Center by the CDI virus test between March 12, 2020, and April 8, 2020. Clinical data and viral testing results were collected and analyzed for characteristics associated with outcomes, as well as the correlation with viral load. A total of 722 patients were included in the study, with a median age of 63 (interquartile range (IQR), 51–75) and 272 (37.7%) females. Mortality of this case series was 25.8%, with a statistically significant linear increase observed from age 40 to ≥ 80 by 10-year intervals. Viral load, as indicated by the cycle of threshold (Ct) values from the RT-PCR test, was significantly higher in the oldest patient group (≥ 80), and inversely correlated with survival. This is the first report to describe the clinical characteristics and outcomes in a large hospitalized COVID-19 patient series from New Jersey. Findings from this study are valuable to the ongoing response of both nationwide healthcare networks and the medical research community.
Altitude conditions seem to determine the evolution of COVID-19 in Brazil
Authors: Fernandes José Sebastião Cunha , da Silva Ricardo Siqueira , Silva Alexandre Christófaro , Villela Daniel Campos , Mendonça Vanessa Amaral , Lacerda Ana Cristina Rodrigues 
Published: February 2021

AbstractCOVID-19 is spreading rapidly in Brazil, a country of continental dimensions, but the incidence of the disease is showing to be very heterogeneous, affecting cities and regions differently. Thus, there is a gap regarding what factors would contribute to accentuate the differences in the incidence of COVID-19 among Brazilian cities. This work aimed to evaluate the effect of altitude on the incidence of COVID-19 in Brazilian cities. We analyzed the relative incidence (RI), the relative death rate (RDR) of COVID-19, and air relative humidity (RH) in all 154 cities in Brazil with a population above 200 thousand inhabitants, located between 5 and 1135 m in altitude. Pearson's correlation analysis was performed to compare a relationship between altitude with RI and RDR, and between RH with RI and RDR. Altitudes were classified into three classes [low (altitude ≤ 97 m a. s. l), middle (97 < altitude ≤ 795 m a. s. l), high (795 < altitude ≤ 1135 m a. s. l)] for the RI, RDR, and RH variables. To compare the three classes of altitude, analysis of variance (ANOVA) and Tukey test were used to compare averages (p < 0.05). Our epidemiological analysis found that the RI, RDR, and RH were lower in cities located in high altitudes (795 < altitude ≤ 1135 m a. s. l) when compared to the middle (97 < altitude ≤ 795 m a. s. l) and low (altitude ≤ 97 m a. s. l) cities altitudes. Furthermore, our study shows that there is a negative correlation between the incidence of COVID-19 with altitude and a positive correlation with RH in the cities analyzed. Brazilian cities with high altitude and low RH have lower RI and RDR from COVID-19. Thus, high altitude cities may be favorable to shelter people at risk. This study may be useful for understanding the behavior of SARS-CoV2, and start point for future studies to establish causality of environmental conditions with SARS-CoV2 contributing to the implementation of measures to prevent and control the spread of COVID-19.