bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mucosal antibody response to SARS-CoV-2 in paediatric and adult patients: a longitudinal study
Authors: Chan Renee WY , Chan Kate CC , Lui Grace CY , Tsun Joseph GS , Chan Kathy YY , Yip Jasmine SK , Liu Shaojun , Yu Michelle WL , Ng Rita WY , Chong Kelvin KL , Wang Maggie H , Chan Paul KS , Li Albert M , Lam Hugh S 
Published: September 2021

AbstractConjunctival and nasal mucosal antibody responses in thirty-four paediatric and forty-seven adult COVID-19 patients were measured. The mucosal antibody was IgA dominant. In the nasal epithelial lining fluid (NELF) of asymptomatic paediatric patients, SARS-CoV-2 spike protein 1 (S1) specific immunoglobulin A (IgA) was induced early. Their plasma S1-specific IgG levels were higher than symptomatic patients. More adult with mild disease had NELF S1-specific IgA than those with severe/critical illness. Within the first week of diagnosis, higher S1-specific antibodies in NELF and plasma and lower vial loads were detected in paediatric than adult patients with mild disease. The IgA and IgG levels correlated positively with the surrogate neutralization readout. The detectable NELF ‘neutralizing’ S1-specific IgA in the first week after diagnosis correlated with a rapid decline in viral load. This study highlights the effect of nasal IgA in limiting the SARS-CoV-2 replication and provides complementary information to the serum antibody measurements.
Cis-regulatory changes in locomotor genes are associated with the evolution of burrowing behavior
Authors: Hu Caroline K. , York Ryan A. , Metz Hillery C. , Bedford Nicole L. , Fraser Hunter B. , Hoekstra Hopi E. 
Published: September 2021

SummaryHow evolution modifies complex, innate behaviors is largely unknown. Divergence in many morphological traits has been linked, at least in part, to cis-regulatory changes in gene expression, a pattern also observed in some behaviors of recently diverged populations. Given this, we compared the gene expression in the brains of two interfertile sister species of Peromyscus mice, including allele-specific expression (ASE) of their F1 hybrids, that show large and heritable differences in burrowing behavior. Because cis-regulation may contribute to constitutive as well as activity-dependent gene expression, we also captured a molecular signature of burrowing circuit divergence by quantifying gene expression in mice shortly after burrowing. We found that several thousand genes were differentially expressed between the two sister species regardless of behavioral context, with several thousand more showing behavior-dependent differences. Allele-specific expression in F1 hybrids showed a similar pattern, suggesting that much of the differential expression is driven by cis-regulatory divergence. Genes related to locomotor coordination showed the strongest signals of lineage-specific selection on burrowing-induced cis-regulatory changes. By comparing these candidate genes to independent quantitative trait locus (QTL) mapping data, we found that the closest QTL markers to these candidate genes are associated with variation in burrow shape, demonstrating an enrichment for candidate locomotor genes near segregating causal loci. Together, our results provide insight into how cis-regulated gene expression can depend on behavioral context as well as how this dynamic regulatory divergence between species can be integrated with forward genetics to enrich our understanding of the genetic basis of behavioral evolution.
Machine learning modeling of protein-intrinsic features predicts tractability of targeted protein degradation
Authors: Zhang Wubing , Roy Burman Shourya S. , Chen Jiaye , Donovan Katherine A. , Cao Yang , Zhang Boning , Zeng Zexian , Zhang Yi , Li Dian , Fischer Eric S. , Tokheim Collin , Liu X. Shirley 
Published: September 2021

AbstractTargeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell’s endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by TPD approaches, termed “degradability”, is largely unknown. Recent systematic studies to map the degradable kinome have shown differences in degradation between kinases with similar drug-target engagement, suggesting yet unknown factors influencing degradability. We therefore developed a machine learning model, MAPD (Model-based Analysis of Protein Degradability), to predict degradability from protein features that encompass post-translational modifications, protein stability, protein expression and protein-protein interactions. MAPD shows accurate performance in predicting kinases that are degradable by TPD compounds (auPRC=0.759) and is likely generalizable to independent non-kinase proteins. We found five features with statistical significance to achieve optimal prediction, with ubiquitination potential being the most predictive. By structural modeling, we found that E2-accessible ubiquitination sites, but not lysine residues in general, are particularly associated with kinase degradability. Finally, we extended MAPD predictions to the entire proteome to find 964 disease-causing proteins, including 278 cancer genes, that may be tractable to TPD drug development.
A Mechanism for the Rare Fluctuation that Powers Protein Conformational Change
Authors: Wu Shanshan , Ma Ao 
Published: September 2021

AbstractMost functional processes of biomolecules are rare events. Key to a rare event is the rare fluctuation that enables the energy activation process, which powers the system across the activation barrier. But the physical nature of this rare fluctuation and how it enables barrier crossing are unknown. With the help of a novel metric, the reaction capacity pC, that rigorously defines the beginning and parameterizes the progress of energy activation, the rare fluctuation was identified as a special phase-space condition that is necessary and sufficient for initiating systematic energy flow from the non-reaction coordinates into the reaction coordinates. The energy activation of a prototype biomolecular isomerization reaction is dominated by kinetic energy transferring into and accumulating in the reaction coordinates, administered by inertial forces alone. The two major reaction coordinates move in precise synergy, with one acting as a gating mechanism on the other. This mechanism is enabled by the structural features of biomolecules and may the cause of their unique functions that are not possible in small molecules.
The architecture of phenotypic flexibility within a complex trait: an empirical case study using avian thermogenic performance
Authors: Stager Maria , Cheviron Zachary A. 
Published: September 2021

ABSTRACTReversible modifications to trait values can allow individuals to match their phenotypes to changing environmental conditions, a phenomenon known as phenotypic flexibility. A system’s capacity for flexibility may be determined by its underlying architecture, and these relationships can have important implications for both organismal adaptation and the evolvability of acclimatization responses. Theory provides two possible alternatives to explain the ways in which lower-level traits respond to environmental challenges and contribute to phenotypic flexibility in complex, whole-organism traits: symmorphosis predicts correspondence between structure and demand across all levels of a physiological system, while the alternative predicts that influence is concentrated in select elements of a physiological network. Here we provide a rich dataset — composed of 20 sub-organismal, physiological traits paired with whole-organism metabolic rates for 106 adult Dark-eyed Juncos (Junco hyemalis) — to explore the mechanistic basis of phenotypic flexibility in complex traits. When exposed to synthetic temperature cues, these individuals have previously been shown to increase their thermogenic capacity (Msum) and enhance their ability to maintain their body temperature in the cold. We show that the relationships among a number of the traits that contribute to Msum varied as the environmental context changed. Moreover, variation in Msum in response to temperature acclimation was correlated with only a handful of subordinate phenotypes. As a result, avian thermogenic flexibility does not appear to be a symmorphotic response. If this is generally true of complex traits, it suggests that simple and reversible modifications can significantly impact whole-organism performance, and thus that the evolution of phenotypic flexibility in a single component part could impart flexibility for the entire system.
A machine vision based frailty index for mice
Authors: Hession Leinani E. , Sabnis Gautam S. , Churchill Gary A. , Kumar Vivek 
Published: September 2021

1AbstractChronological aging is uniform, but biological aging is heterogeneous. Clinically, this heterogeneity manifests itself in health status and mortality, and it distinguishes healthy from unhealthy aging. Frailty indexes (FIs) serve as an important tool in gerontology to capture health status. FIs have been adapted for use in mice and are an effective predictor of mortality risk. To accelerate our understanding of biological aging, high-throughput approaches to pre-clinical studies are necessary. Currently, however, mouse frailty indexing is manual and relies on trained scorers, which imposes limits on scalability and reliability. Here, we introduce a machine learning based visual frailty index (vFI) for mice that operates on video data from an open field assay. We generate a large mouse FI dataset of both male and female mice. From video data on these same mice, we use neural networks to extract morphometric, gait, and other behavioral features that correlate with manual FI score and age. We use these features to train a regression model that accurately predicts the normalized FI score within 0.04 ± 0.002 (mean absolute error). We show that features of biological aging are encoded in open-field video data and can be used to construct a vFI that can complement or replace current manual FI methods. We use the vFI data to examine sex-specific aspects of aging in mice. This vFI provides increased accuracy, reproducibility, and scalability, that will enable large scale mechanistic and interventional studies of aging in mice.
Gigantic Genomes of Salamanders Indicate Body Temperature, not Genome Size, is the Driver of Global Methylation and 5-Methylcytosine Deamination in Vertebrates
Authors: Adams Alexander Nichols , Denton Robert Daniel , Mueller Rachel Lockridge 
Published: September 2021

AbstractMethylation of cytosines at CpG dinucleotide sites silences transposable elements (TEs), sequences that replicate and move throughout genomes. TE abundance drives differences in genome size, but TE silencing variation across genomes of different sizes remains largely unexplored. Salamanders include most of the largest C-values — 9 to 120 Gb. We measured CpG methylation levels in salamanders with genomes ranging from 2N = ~58 Gb to 4N = ~116 Gb. We compared these levels to results from endo- and ectothermic vertebrates with more typical genomes. Salamander methylation levels are ~90%, higher than all endotherms. However, salamander methylation does not differ from the other ectotherms, despite a ~100-fold difference in nuclear DNA content. Because methylation affects the nucleotide compositional landscape through 5-methylcytosine deamination to thymine, we quantified salamander CpG dinucleotide levels and compared them to other vertebrates. Salamanders have comparable CpG levels to other ectotherms, and ectotherm levels are higher than endotherms. These data show no shift in global methylation at the base of salamanders, despite a dramatic increase in TE load and genome size. This result is reconcilable with previous studies by considering endothermy and ectothermy, which may be more important drivers of methylation in vertebrates than genome size.
Lip movements enhance speech representations and effective connectivity in speech dorsal stream and its relationship with neurite architecture
Authors: Zhang Lei , Du Yi 
Published: September 2021

AbstractLip movements facilitate speech comprehension, especially under adverse listening conditions, but the neural mechanisms of this perceptual benefit at the phonemic and feature levels remain unclear. This fMRI study addresses this question by quantifying regional multivariate representation and network organization underlying audiovisual speech-in-noise perception. We found that valid lip movements enhanced neural representations of phoneme, place of articulation, or voicing feature of speech differentially in dorsal stream regions, including frontal speech motor areas and supramarginal gyrus. Such local changes were accompanied by strengthened dorsal stream effective connectivity. Moreover, the neurite orientation dispersion of left arcuate fasciculus, a structural basis of speech dorsal stream, predicted the visual enhancements of neural representations and effective connectivity. Our findings provide novel insight to speech science that lip movements promote both local phonemic and feature encoding and network connectivity in speech dorsal pathway and the functional enhancement is mediated by the microstructural architecture of the circuit.
Phylodynamics Of A Regional, Sars-Cov-2 Rapid Spreading Event In Colorado
Authors: Wade Kristen J. , Tisa Samantha , Barrington Chloe , Crooks Kristy R. , Gignoux Chris R. , Almand Austin T. , Steel J. Jordan , Sitko John C. , Rohrer Joseph W. , Wickert Douglas P. , Almand Erin A. , Pollock David D. , Rissland Olivia S. 
Published: September 2021

ABSTRACTSince the initial reported discovery of SARS-CoV-2 in late 2019, genomic surveillance has been an important tool to understand its transmission and evolution. Here, we describe a case study of genomic sequencing of Colorado SARS-CoV-2 samples collected August through November 2020 at the University of Colorado Anschutz Medical campus in Aurora and the United States Air Force Academy in Colorado Springs. We obtained nearly complete sequences for 44 genomes, inferred ancestral sequences shared among these local samples, and used NextStrain variant and clade frequency monitoring in North America to place the Colorado sequences into their continental context. Furthermore, we describe genomic monitoring of a lineage that likely originated in the local Colorado Springs community and expanded rapidly over the course of two months in an outbreak within the well-controlled environment of the United States Air Force Academy. This variant contained a number of amino acid-altering mutations that may have contributed to its spread, but it appears to have been controlled using extensive contact tracing and strict quarantine protocols. The genome sequencing allowed validation of the transmission pathways inferred by the United States Air Force Academy and provides a window into the evolutionary process and transmission dynamics of a potentially dangerous but ultimately contained variant.SIGNIFICANCESARS-CoV-2 spreads and mutates, negatively impacting containment. In this study, we use long-read sequencing to generate 44 SARS-CoV-2 genomes from COVID-19 patients associated with a rapid-spreading event on the USAFA campus, as well as a neighboring community for reference. We reconstruct the genomic and evolutionary signatures of the rapid-spreading event, and pin-point novel, protein-altering mutations that may have impacted viral fitness. These insights into viral evolutionary dynamics, in the context of contact tracing and a rigorous containment program, help to inform response efforts in the future.
A MUC5Bgene polymorphism, rs35705950-T, confers protective effects in COVID-19 infection
Authors: Verma Anurag , Minnier Jessica , Huffman Jennifer E , Wan Emily S , Gao Lina , Joseph Jacob , Ho Yuk-Lam , Wu Wen-Chih , Cho Kelly , Gorman Bryan R , Rajeevan Nallakkandi , Pyarajan Saiju , Garcon Helene , Meigs James B , Sun Yan V , Reaven Peter D , McGeary John E , Suzuki Ayako , Gelernter Joel , Lynch Julie A , Petersen Jeffrey M , Zekavat Seyedeh Maryam , Natarajan Pradeep , Madison Cecelia J , Dalal Sharvari , Jhala Darshana N , Arjomandi Mehrdad , Gatsby Elise , Lynch Kristine E , Bonomo Robert A , Freiberg Mat , Pathak Gita A , Zhou Jin J , Donskey Curtis J , Madduri Ravi K , Wells Quinn S , Huang Rose DL , Polimanti Renato , Chang Kyong-Mi , Liao Katherine P , Tsao Philip S , Wilson Peter W.F. , Hung Adriana , O’Donnell Christopher J , Gaziano John M , Hauger Richard L , Iyengar Sudha K. , Luoh Shiuh-Wen 
Published: September 2021

AbstractRationaleA commonMUC5Bgene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis, but its role in the SARS-CoV-2 infection and disease severity is unclear.ObjectivesTo assess whether rs35705950-T confers differential risk for clinical outcomes associated with COVID-19 infection among participants in the Million Veteran Program (MVP) and COVID-19 Host Genetics Initiative (HGI).MethodsMVP participants were examined for an association between the incidence or severity of COVID-19 and the presence of aMUC5Brs35705950-T allele. Comorbidities and clinical events were extracted from the electronic health records (EHR). The analysis was performed within each ancestry group in the MVP, adjusting for sex, age, age2,and first twenty principal components followed by a trans-ethnic meta-analysis. We then pursued replication and performed a meta-analysis with the trans-ethnic summary statistics from the HGI. A phenome-wide association study (PheWAS) of the rs35705950-T was conducted to explore associated pathophysiologic conditions.Measurements and Main ResultsA COVID-19 severity scale was modified from the World Health Organization criteria, and phenotypes derived from the International Classification of Disease-9/10 were extracted from EHR. Presence of rs35705950-T was associated with fewer hospitalizations (Ncases=25353, Ncontrols=631,024; OR=0.86 [0.80-0.93], p=7.4 × 10−5) in trans-ethnic meta-analysis within MVP and joint meta-analyses with the HGI (N=1641311; OR=0.89 [0.85-0.93], p =1.9 × 10−6). Moreover, individuals of European Ancestry with at least one copy of rs35705950-T had fewer post-COVID-19 pneumonia events (OR=0.85 [0.76-0.96], p =0.008). PheWAS exclusively revealed pulmonary involvement.ConclusionsTheMUC5Bvariant rs35705950-T is protective in COVID-19 infection.
A multivariable Mendelian randomization analysis disentangling the causal relations between abdominal obesity, non-alcoholic fatty liver disease and cardiometabolic diseases
Authors: Pelletier William , Gagnon Éloi , Gobeil Émilie , Bourgault Jérôme , Manikpurage Hasanga D. , Maltais-Payette Ina , Abner Erik , Taba Nele , Esko Tõnu , Mitchell Patricia L. , Ghodsian Nooshin , Després Jean-Pierre , Vohl Marie-Claude , Tchernof André , Thériault Sébastien , Arsenault Benoit J. 
Published: September 2021

AbstractBackgroundObservational studies have linked obesity and especially abdominal obesity to non-alcoholic fatty liver disease (NAFLD). These traits are also associated with type 2 diabetes (T2D) and coronary artery disease (CAD) but the causal factor(s) underlying these associations remain unexplored.MethodsWe used a multivariable Mendelian randomization (MVMR) study design to determine whether obesity (defined using body mass index [BMI]) and abdominal obesity (defined using waist circumference) were causally associated with NAFLD using publicly available genome-wide association study (GWAS) summary statistics of the UK Biobank (n>450,000) and a GWAS meta-analysis of NAFLD (8434 cases and 770,180 control). A MVMR study design was also used to determine the respective causal contributions of waist circumference and NAFLD to T2D and CAD using additional GWAS summary statistics of the DIAGRAM (74,124 cases and 824,006 controls) and CARDIoGRAMplusC4D (122,733 cases and 424,528 controls) consortia.ResultsIn univariable Mendelian randomization analyses, both BMI and waist circumference were associated with NAFLD. NAFLD was not associated with obesity or abdominal obesity. In MVMR analyses, waist circumference was associated with NAFLD when accounting for BMI (OR per 1-standard deviation increase = 2.56 95% CI: 1.39-4.69, p=2.4e-03) and BMI was not associated with NAFLD when accounting for waist circumference (0.81 95% CI: 0.5-1.31, p =3.9e-01). In MVMR analyses accounting for NAFLD, waist circumference remained strongly associated with both T2D (3.25 95% CI: 2.87-3.68, p=5.1e-77) and CAD (1.62 95% CI: 1.48-1.76, p=6.5e-28).ConclusionsThese results identified abdominal obesity as a strong, independent and causal contributor to NAFLD, T2D and CAD, suggesting that interventions targeting abdominal obesity rather than body weight per se should be prioritized for the prevention and management of cardiometabolic diseases.
Predicting hospital-onset COVID-19 infections using dynamic networks of patient contacts: an observational study
Authors: Myall Ashleigh , Price James R , Peach Robert L , Abbas Mohamed , Mookerjee Siddharth , Zhu Nina , Ahmad Isa , Ming Damien , Ramzan Farzan , Teixeira Daniel , Graf Christophe , Weiße Andrea Y , Harbarth Stephan , Holmes Alison , Barahona Mauricio 
Published: September 2021

ABSTRACTBackgroundReal-time prediction is key to prevention and control of healthcare-associated infections. Contacts between individuals drive infections, yet most prediction frameworks fail to capture the dynamics of contact. We develop a real-time machine learning framework that incorporates dynamic patient contact networks to predict patient-level hospital-onset COVID-19 infections (HOCIs), which we test and validate on international multi-site datasets spanning epidemic and endemic periods.MethodsOur framework extracts dynamic contact networks from routinely collected hospital data and combines them with patient clinical attributes and background contextual hospital data to forecast the infection status of individual patients. We train and test the HOCI prediction framework using 51,157 hospital patients admitted to a UK (London) National Health Service (NHS) Trust from 01 April 2020 to 01 April 2021, spanning UK COVID-19 surges 1 and 2. We then validate the framework by applying it to data from a non-UK (Geneva) hospital site during an epidemic surge (40,057 total inpatients) and to data from the same London Trust from a subsequent period post surge 2, when COVID-19 had become endemic (43,375 total inpatients).FindingsBased on the training data (London data spanning surges 1 and 2), the framework achieved high predictive performance using all variables (AUC-ROC 0·89 [0·88-0·90]) but was almost as predictive using only contact network variables (AUC-ROC 0·88 [0·86-0·90]), and more so than using only hospital contextual (AUC-ROC 0·82 [0·80-0·84]) or patient clinical (AUC-ROC 0·64 [0·62-0·66]) variables. The top three risk factors we identified consisted of one hospital contextual variable (background hospital COVID-19 prevalence) and two contact network variables (network closeness, and number of direct contacts to infectious patients), and together achieved AUC-ROC 0·85 [0·82-0·88]. Furthermore, the addition of contact network variables improved performance relative to hospital contextual variables on both the non-UK (AUC-ROC increased from 0·84 [0·82–0·86] to 0·88 [0·86–0·90]) and the UK validation datasets (AUC-ROC increased from 0·52 [0·49–0·53] to 0·68 [0·64-0·70]).InterpretationOur results suggest that dynamic patient contact networks can be a robust predictor of respiratory viral infections spreading in hospitals. Their integration in clinical care has the potential to enhance individualised infection prevention and early diagnosis.FundingMedical Research Foundation, World Health Organisation, Engineering and Physical Sciences Research Council, National Institute for Health Research, Swiss National Science Foundation, German Research Foundation.