bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computational anti-COVID-19 drug design: progress and challenges
Authors: Wang Jinxian , Zhang Ying , Nie Wenjuan , Luo Yi , Deng Lei 
Published: October 2021

AbstractVaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially the latest delta variant, has brought considerable challenges to human health. Hence, the development of robust therapeutic approaches, such as anti-COVID-19 drug design, could aid in managing the pandemic more efficiently. Some drug design strategies have been successfully applied during the COVID-19 pandemic to create and validate related lead drugs. The computational drug design methods used for COVID-19 can be roughly divided into (i) structure-based approaches and (ii) artificial intelligence (AI)-based approaches. Structure-based approaches investigate different molecular fragments and functional groups through lead drugs and apply relevant tools to produce antiviral drugs. AI-based approaches usually use end-to-end learning to explore a larger biochemical space to design antiviral drugs. This review provides an overview of the two design strategies of anti-COVID-19 drugs, the advantages and disadvantages of these strategies and discussions of future developments.
Multiomics integration-based molecular characterizations of COVID-19
Authors: Li Chuan-Xing , Gao Jing , Zhang Zicheng , Chen Lu , Li Xun , Zhou Meng , Wheelock Åsa M 
Published: October 2021

Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.
Combining power of different methods to detect associations in large data sets
Authors: Li He , Zhang Hangxiao , Jiang Hangjin 
Published: October 2021

AbstractExploring the relationship between factors of interest is a fundamental step for further analysis on various scientific problems such as understanding the genetic mechanism underlying specific disease, brain functional connectivity analysis. There are many methods proposed for association analysis and each has its own advantages, but none of them is suitable for all kinds of situations. This brings difficulties and confusions to practitioner on which one to use when facing a real problem. In this paper, we propose to combine power of different methods to detect associations in large data sets. It goes as combining the weaker to be stronger. Numerical results from simulation study and real data applications show that our new framework is powerful. Importantly, the framework can also be applied to other problems. Availability: The R script is available at https://jiangdata.github.io/resources/DM.zip
Historical controls in clinical trials: a note on linking Pocock’s model with the robust mixture priors
Authors: Callegaro Andrea , Galwey Nicholas , Abellan Juan J 
Published: October 2021

SummarySeveral Bayesian methods have been proposed to borrow information dynamically from historical controls in clinical trials. In this note, we identify key features of the relationship between the first method proposed, the bias–variance method, which is strongly related to the commensurate prior approach, and a more recent and widely used approach called robust mixture priors (RMP). We focus on the two key terms that need to be chosen to define the RMP, namely $w$, the prior probability that the new trial differs systematically from the historical trial, and $s_v^2$, the variance of the vague component of the RMP. The relationship with Pocock’s prior reveals that different combinations of these two terms can express similar prior beliefs about the amount of information provided by the historical data. This demonstrates the value of fixing $s_v^2$, e.g., so the vague component is “worth one subject.” Prior belief about the relevance of the historical data is then driven by a single value, the prespecified weight $w$.
Increased scale-free and aperiodic neural activity during sensorimotor integration—a novel facet in Tourette syndrome
Authors: Adelhöfer Nico , Paulus Theresa , Mückschel Moritz , Bäumer Tobias , Bluschke Annet , Takacs Adam , Tóth-Fáber Eszter , Tárnok Zsanett , Roessner Veit , Weissbach Anne , Münchau Alexander , Beste Christian 
Published: October 2021

AbstractTourette syndrome is a common neurodevelopmental disorder defined by multiple motor and phonic tics. Tics in Tourette syndrome resemble spontaneously occurring movements in healthy controls and are therefore sometimes difficult to distinguish from these. Tics may in fact be mis-interpreted as a meaningful action, i.e. a signal with social content, whereas they lack such information and could be conceived a surplus of action or ‘motor noise’. These and other considerations have led to a ‘neural noise account’ of Tourette syndrome suggesting that the processing of neural noise and adaptation of the signal-to-noise ratio during information processing is relevant for the understanding of Tourette syndrome. So far, there is no direct evidence for this. Here, we tested the ‘neural noise account’ examining 1/f noise, also called scale-free neural activity as well as aperiodic activity, in n = 74 children, adolescents and adults with Tourette syndrome and n = 74 healthy controls during task performance using EEG data recorded during a sensorimotor integration task. In keeping with results of a previous study in adults with Tourette syndrome, behavioural data confirmed that sensorimotor integration was also stronger in this larger Tourette syndrome cohort underscoring the relevance of perceptual-action processes in this disorder. More importantly, we show that 1/f noise and aperiodic activity during sensorimotor processing is increased in patients with Tourette syndrome supporting the ‘neural noise account’. This implies that asynchronous/aperiodic neural activity during sensorimotor integration is stronger in patients with Tourette syndrome compared to healthy controls, which is probably related to abnormalities of GABAergic and dopaminergic transmission in these patients. Differences in 1/f noise and aperiodic activity between patients with Tourette syndrome and healthy controls were driven by high-frequency oscillations and not lower-frequency activity currently discussed to be important in the pathophysiology of tics. This and the fact that Bayesian statistics showed that there is evidence for the absence of a correlation between neural noise and clinical measures of tics, suggest that increased 1/f noise and aperiodic activity are not directly related to tics but rather represents a novel facet of Tourette syndrome.
Aphid Species and Feeding Location on Canola Influences the Impact of Glucosinolates on a Native Lady Beetle Predator
Authors: Cibils-Stewart Ximena , Kliebenstein Daniel J , Li Baohua , Giles Kristopher , McCornack Brian P , Nechols James 
Published: October 2021

Abstract
Aphids that attack canola (Brassica napus L.) exhibit feeding preferences for different parts of canola plants, which may be associated with brassica-specific glucosinolates. However, this idea remains untested. Furthermore, canola aphid species employ different strategies for tolerating glucosinolates. While the green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), excretes glucosinolates, the cabbage aphid Brevicoryne brassicae (L.) (Hemiptera: Aphididae) sequesters them. Given the different detoxification mechanisms, we predicted that both aphid species and aphid feeding location would affect prey suitability for larvae of the predator, Hippodamia convergens (Guérin-Méneville) (Coleoptera: Coccinellidae). We hypothesized that aphids, specifically glucosinolate-sequestering cabbage aphid, reared on reproductive structures that harbor higher glucosinolates concentrations would have greater negative effects on predators than those reared on vegetative structures which have lower levels of glucosinolates, and that the impact of aphid feeding location would vary depending on the prey detoxification mechanism. To test these predictions, we conducted experiments to compare 1) glucosinolates profiles between B. brassicae and M. persicae reared on reproductive and vegetative canola structures, 2) aphid population growth on each structure, and 3) their subsequent impact on fitness traits of H. convergens. Results indicate that the population growth of both aphids was greater on reproductive structures, with B. brassicae having the highest population growth. B. brassicae reared on reproductive structures had the highest concentrations of glucosinolates, and the greatest adverse effects on H. convergens. These findings suggest that both aphid-prey species and feeding location on canola could influence populations of this predator and, thus, its potential for biological control of canola aphids.
Trends in aortic valve replacement for aortic stenosis: a French nationwide study
Authors: Nguyen Virginia , Willner Nadav , Eltchaninoff Helene , Burwash Ian G , Michel Morgane , Durand Eric , Gilard Martine , Dindorf Christel , Iung Bernard , Cribier Alain , Vahanian Alec , Chevreul Karine , Messika-Zeitoun David 
Published: October 2021

Abstract

Aims
Transcatheter aortic valve replacement (TAVR) as an alternative to surgical aortic valve replacement (SAVR) has profoundly changed the management of patients with aortic valve stenosis (AS). Large unbiased nationwide data regarding TAVR implementation, impact on SAVR and their respective outcomes are scarce.

Methods and results
Based on a French administrative hospital-discharge database, we collected data on all consecutive aortic valve replacements (AVRs) performed in France for AS between 2007 and 2019 [106 253 isolated SAVR (49%), 46 514 combined SAVR (21%), and 65 651 TAVR (30%)]. The number of AVR linearly increased between 2007 and 2019 (from 10 892 to 23 109, P for trend &lt; 0.0001) due to a marked increase in TAVR (from 253 to 13 030, P for trend &lt; 0.0001), while SAVR increased up to 2013 and then declined (10 892 in 2007, 12 699 in 2013, and 10 079 in 2019). The Charlson index decreased linearly for TAVR, but in two steps for SAVR (2011 and 2017). In-hospital mortality rates of both SAVR and TAVR declined (both P for trend &lt; 0.0001) and were similar or lower for TAVR than for isolated SAVR in patients 75 years or above in the last 3 years (2017–19). Complication rates of TAVR also declined but permanent pacemaker rates remained high and length of stay substantial (16.7% and median 6 days, respectively, in 2017–19).

Conclusion
The number of AVR has doubled in a decade and TAVR has become the dominant form of AVR in 2018. The improvement in patient profiles seems to have anticipated the demonstrated benefit of TAVR in intermediate and low-risk patients. In patients 75 years or older, TAVR should be considered as the first option. We also highlight two important areas for improvement, the high permanent pacemaker rates, and the long length of stay even in the contemporary era. Our results may have major implications for clinical practice and policymakers.
Tracing the Evolution of Human Gene Regulation and Its Association with Shifts in Environment
Authors: Colbran Laura L , Johnson Maya R , Mathieson Iain , Capra John A 
Published: October 2021

Abstract
As humans populated the world, they adapted to many varying environmental factors, including climate, diet, and pathogens. Because many of these adaptations were mediated by multiple noncoding variants with small effects on gene regulation, it has been difficult to link genomic signals of selection to specific genes, and to describe the regulatory response to selection. To overcome this challenge, we adapted PrediXcan, a machine learning method for imputing gene regulation from genotype data, to analyze low-coverage ancient human DNA (aDNA). First, we used simulated genomes to benchmark strategies for adapting PrediXcan to increase robustness to incomplete data. Applying the resulting models to 490 ancient Eurasians, we found that genes with the strongest divergent regulation among ancient populations with hunter-gatherer, pastoralist, and agricultural lifestyles are enriched for metabolic and immune functions. Next, we explored the contribution of divergent gene regulation to two traits with strong evidence of recent adaptation: dietary metabolism and skin pigmentation. We found enrichment for divergent regulation among genes proposed to be involved in diet-related local adaptation, and the predicted effects on regulation often suggest explanations for known signals of selection, for example, at FADS1, GPX1, and LEPR. In contrast, skin pigmentation genes show little regulatory change over a 38,000-year time series of 2,999 ancient Europeans, suggesting that adaptation mainly involved large-effect coding variants. This work demonstrates that combining aDNA with present-day genomes is informative about the biological differences among ancient populations, the role of gene regulation in adaptation, and the relationship between genetic diversity and complex traits.
Gender Differences in Physical Activity Engagement Among Adolescents With Congenital Heart Disease
Authors: Jackson Jamie L , Fox Kristen R , Swenski Taylor N , Neville Steven P , Marousis Noelle C , Korth Christina X , Rausch Joseph R , Cua Clifford L , Garg Vidu , Vannatta Kathryn 
Published: October 2021

Abstract

Objective
The current study aimed to (a) describe moderate-to-vigorous physical activity (MVPA), sedentary behavior (SB), and cardiorespiratory fitness (VO2Peak) via objective assessment among adolescents with congenital heart disease (CHD), (b) examine gender differences on MVPA, SB, VO2Peak, and the Theory of Planned Behavior elements, and (c) identify whether gender moderates the relationships between the Theory of Planned Behavior elements and MVPA, SB, and VO2Peak.

Methods
Adolescent CHD survivors (N = 86; ages 15–18 years) wore an accelerometer to assess MVPA and SB, underwent an exercise stress test to assess VO2Peak, and completed a survey of the Theory of Planned Behavior elements as measured by perceived benefits (attitudes), family/friend support and perceived norms (social norms), and self-efficacy and barriers (perceived behavioral control) to engaging in physical activity.

Results
On average, CHD survivors engaged in 22.3 min (SD = 15.3) of MVPA/day and 9 hr of SB/day (M = 565.8, SD = 102.5 min). Females engaged in less MVPA but not more SB had a lower mean VO2Peak, reported lower self-efficacy, and perceived greater barriers than males. In a regression model, barriers explained unique variance in MVPA and VO2Peak, but the relationship between barriers and MVPA/VO2Peak did not vary by gender. Self-efficacy did not explain unique variance in MVPA and VO2Peak when included in a model with gender and barriers.

Conclusions
Family/friend support for physical activity engagement may be an important consideration when developing physical activity interventions for adolescent CHD survivors. The role of gender differences in self-efficacy and perceived barriers on physical activity engagement warrants further investigation.
Rescued from oblivion: detailed analysis of archival Spitzer data of SN 1993J
Authors: Zsíros Szanna , Nagy Andrea P , Szalai Tamás 
Published: October 2021

ABSTRACT
We present an extensive analysis of the late-time mid-infrared (mid-IR) evolution of the Type IIb SN 1993J from 10–26 yr post-explosion based on archival – mostly previously unpublished – photometric data from the Spitzer Space Telescope in conjunction with an archival InfraRed Spectrograph spectrum. SN 1993J is one of the best-studied supernovae (SNe) with an extensive decade-long multiwavelength data set published in various papers; however, its detailed late-time mid-IR analysis is still missing from the literature. Mid-IR data follow not just the continuously cooling SN ejecta but also late-time dust-formation and circumstellar-interaction processes. We provide evidence that the observed late-time mid-IR excess of SN 1993J can be described by the presence of two-component local dust with a dust mass of ∼(3.5–6.0) × 10−3 M⊙ in the case of a partly silicate-based dust composition. The source of these components could be either newly formed dust grains or heating of pre-existing dust via ongoing circumstellar matter interaction also detected at other wavelengths. If it is newly formed, the dust is assumed to be located both in the unshocked inner ejecta and in the outer cold dense shell, just as in the Cassiopeia A remnant and also assumed in other dust-forming SNe a few years after explosion.
The fast radio burst population evolves, consistent with the star formation rate
Authors: James C W , Prochaska J X , Macquart J-P , North-Hickey F O , Bannister K W , Dunning A 
Published: October 2021

ABSTRACT
Fast radio bursts (FRBs) are extremely powerful sources of radio waves observed at cosmological distances. We use a sophisticated model of FRB observations – presented in detail in a companion paper – to fit FRB population parameters using large samples of FRBs detected by ASKAP and Parkes, including seven sources with confirmed host galaxies. Our fitted parameters demonstrate that the FRB population evolves with redshift in a manner consistent with, or faster than, the star formation rate (SFR), ruling out a non-evolving population at better than 98 per cent CL (depending on modelling uncertainties). Our estimated maximum FRB energy is $\log _{10} E_{\rm max} [{\rm erg}] = 41.70_{-0.06}^{+0.53}$ (68 per cent CL) assuming a 1 GHz emission bandwidth, with slope of the cumulative luminosity distribution $\gamma =-1.09_{-0.10}^{+0.14}$. We find a log-mean host DM contribution of $129_{-48}^{+66}$ pc cm−3 on top of a typical local (interstellar medium and halo) contribution of ∼80 pc cm−3, which is higher than most literature values. These results are insensitive to assumptions of the FRB spectral index, and are consistent with the model of FRBs arising as the high-energy limit of magnetar bursts, but allow for FRB progenitors that evolve faster than the SFR.
Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes
Authors: Andreopoulos William B , Geller Alexander M , Lucke Miriam , Balewski Jan , Clum Alicia , Ivanova Natalia N , Levy Asaf 
Published: October 2021

AbstractPlasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC–ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.
ONQUADRO: a database of experimentally determined quadruplex structures
Authors: Zok Tomasz , Kraszewska Natalia , Miskiewicz Joanna , Pielacinska Paulina , Zurkowski Michal , Szachniuk Marta 
Published: October 2021

Abstract
ONQUADRO is an advanced database system that supports the study of the structures of canonical and non-canonical quadruplexes. It combines a relational database that collects comprehensive information on tetrads, quadruplexes, and G4-helices; programs to compute structure parameters and visualise the data; scripts for statistical analysis; automatic updates and newsletter modules; and a web application that provides a user interface. The database is a self-updating resource, with new information arriving once a week. The preliminary data are downloaded from the Protein Data Bank, processed, annotated, and completed. As of August 2021, ONQUADRO contains 1,661 tetrads, 518 quadruplexes, and 30 G4-helices found in 467 experimentally determined 3D structures of nucleic acids. Users can view and download their description: sequence, secondary structure (dot-bracket, classical diagram, arc diagram), tertiary structure (ball-and-stick, surface or vdw-ball model, layer diagram), planarity, twist, rise, chi angle (value and type), loop characteristics, strand directionality, metal ions, ONZ, and Webba da Silva classification (the latter by loop topology and tetrad combination), origin structure ID, assembly ID, experimental method, and molecule type. The database is freely available at https://onquadro.cs.put.poznan.pl/. It can be used on both desktop computers and mobile devices.
Contemporary adaptive evolution in fragmenting river landscapes: evidence from the native waterflea Ceriodaphnia cornuta
Authors: Zhang Haoran , He Yuanwen , Yang Jiashen , Mao Hongzhen , Jiang Xiaodong 
Published: October 2021

Abstract
The hypothesis that adaptive evolution in cities can occur on both contemporary and microgeographic scales was tested by investigating morphological, genetic and life history traits of waterflea Ceriodaphnia cornuta in an urbanized river. After the partial isolation from the Yingtao River by urban construction 16 years ago, the population of C. cornuta in the Shangyi Pond showed a different pattern of genotypic composition. Nuclear microsatellite markers revealed significant population genetic structure of C. cornuta among the Shangyi Pond, the Yingtao River and the Dianshan Lake in the upstream area. Migration analyses demonstrated little gene flow among different waters. In a common garden experiment, the changes in multivariate reaction norms provided evidence of local adaptation to dietary cyanobacteria in the river and lake populations. The results indicated that fragmenting river landscapes with urbanization resulted in the significant genetic differentiation and subsequent adaptive evolution in zooplankton populations on a short temporal and geographical scale.