bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large-scale Integrative Analysis of Juvenile Idiopathic Arthritis for New Insight into Its Pathogenesis
Authors: Kim Daeun , Song Jaeseung , Mancuso Nicholas , Mangul Serghei , Ahn Chul Woo , Jung Junghyun , Jang Wonhee 
Published: April 2023

AbstractObjectivesJuvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear. We conducted a comprehensive integrative analysis to gain new insights into the etiology of JIA.MethodsTo prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand genetic architecture JIA, we systematically analyzed single nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Finally, we performed HLA typing using multi-ancestry RNA sequencing data and analyzed the T cell receptor (TCR) repertoire at a single-cell level to investigate the associations between immunity and JIA risk.ResultsWe have identified 19 TWAS genes and two PWAS proteins that are associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions, and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, includingCXCL13+BHLHE40+THcells which are significantly associated with JIA risks.ConclusionsOur findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA
Autoantibody production is enhanced after mild SARS-CoV-2 infection despite vaccination in individuals with and without long COVID
Authors: Visvabharathy L , Zhu C , Orban ZS , Yarnoff K , Palacio N , Jimenez M , Lim PH , Penaloza-MacMaster P , Koralnik IJ 
Published: April 2023

AbstractLong COVID patients who experienced severe acute SARS-CoV-2 infection can present with humoral autoimmunity. However, whether mild SARS-CoV-2 infection increases autoantibody responses and whether vaccination can decrease autoimmunity in long COVID patients is unknown. Here, we demonstrate that mild SARS-CoV-2 infection increases autoantibodies associated with systemic lupus erythematosus (SLE) and inflammatory myopathies in long COVID patients with persistent neurologic symptoms to a greater extent than COVID convalescent controls at 8 months post-infection. Furthermore, high titers of SLE-associated autoantibodies in long COVID patients are associated with impaired cognitive performance and greater symptom severity, and subsequent vaccination/booster does not decrease autoantibody titers. In summary, we found that mild SARS-CoV-2 infection can induce persistent humoral autoimmunity in both long COVID patients and healthy COVID convalescents, suggesting that a reappraisal of vaccination and mitigation strategies is warranted.
A simulation-based method to inform serosurvey designs for estimating dengue force of infection using existing blood samples
Authors: Vicco Anna , McCormack Clare , Pedrique Belen , Amuasi John H. , Awuah Anthony Afum-Adjei , Obirikorang Christian , Struck Nicole S. , Lorenz Eva , May Jürgen , Ribeiro Isabela , Malavige Gathsaurie Neelika , Donnelly Christl A. , Dorigatti Ilaria 
Published: April 2023

AbstractThe extent to which dengue virus has been circulating in Africa is largely unknown. Testing available blood samples from previous cross-sectional serological surveys offers a convenient strategy to investigate past dengue infections, as such serosurveys provide the ideal data to reconstruct the age-dependent immunity profile of the population and to estimate the average per-capita annual risk of infection; the force of infection (FOI), which is a fundamental measure of transmission intensity.In this study, we present a novel methodological approach to inform the size and age distribution of blood samples to test when samples are acquired from previous surveys. The method was used to inform a dengue seroprevalence survey which is currently being conducted in Ghana by the Drug for Neglected disease initiative, utilizing samples previously collected for a SARS-CoV-2 serosurvey.The method described in this paper can be employed to determine sample sizes and testing strategies for different diseases and transmission settings.Author summaryThe historical circulation of dengue virus in Africa is still poorly understood, and age-stratified seroprevalence surveys can provide the data to quantify population exposure to dengue and its transmission intensity.In this work, we developed a simulation-based method that can be used to identify the sample sizes and age-distribution of the samples needed to obtain informative estimates of dengue force of infection from existing blood samples. We apply this method to data obtained from a SARS-CoV-2 serological survey, previously conducted in three cities in Ghana.The proposed method can be used to design serological surveys for other pathogens when using existing blood samples with accompanying age and location are available.
Metagenomics reveals novel microbial signatures of farm exposures in house dust
Authors: Wang Ziyue , Dalton Kathryn R. , Lee Mikyeong , Parks Christine G. , Beane Freeman Laura E. , Zhu Qiyun , González Antonio , Knight Rob , Zhao Shanshan , Motsinger-Reif Alison A , London Stephanie J. 
Published: April 2023

AbstractIndoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole genome shotgun sequencing (WGS) can detect novel associations between environmental exposures and the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). This study aimed to better depict indoor dust microbial communities using WGS to investigate novel associations with environmental risk factors from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phylaActinobacteria, Bacteroidetes, Firmicutes, andProteobacteria. The identification of novel differential taxa associated with farming at the genera level, includingRhodococcus, Bifidobacterium, Corynebacterium, andPseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota, and should be an important consideration in designing future studies in environmental health.
Cortical microstructural associations with CSF amyloid and pTau
Authors: Nir Talia M. , Villalón-Reina Julio E. , Salminen Lauren , Haddad Elizabeth , Zheng Hong , Thomopoulos Sophia I. , Jack Clifford R. , Weiner Michael W. , Thompson Paul M. , Jahanshad Neda ,   the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Published: April 2023

AbstractDiffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer’s disease (AD) pathology. Few studies have evaluated multi-shell dMRI models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI, in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181and Aβ1–42burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8±6.2 years) from the Alzheimer’s Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1–42and higher pTau181were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures were more widely associated with Aβ1–42than pTau181and better distinguished Aβ+ from Aβ-participants than pTau+/- participants. Conversely, cortical thickness was more tightly linked with pTau181. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI measures sensitive to early AD pathogenesis and microstructural damage may elucidate mechanisms underlying cognitive decline.
Factors associated with differential seropositivity toLeptospira interrogansandLeptospira kirschneriin a high transmission urban setting for leptospirosis in Brazil
Authors: de Oliveira Daiana , Khalil Hussein , Almerinda G. Palma Fabiana , Santana Roberta , Nery Nivison , Quintero-Vélez Juan C. , Zeppelini Caio Graco , do Sacramento Gielson Almeida , Cruz Jaqueline , Lustosa Ricardo , Ferreira Igor Santana , Carvalho-Pereira Ticiana , Diggle Peter J , Wunder Elsio A. , Ko Albert I. , Lopez Yeimi Alzate , Begon Mike , Reis Mitermayer G. , Costa Federico 
Published: April 2023

AbstractBackgroundLeptospirosis is a zoonosis caused by pathogenic species of bacteria belonging to the genusLeptospira. Most studies infer the epidemiological patterns of a single serogroup or aggregate all serogroups to estimate overall seropositivity, thus not exploring the risks of exposure to distinct serogroups. The present study aims to delineate the demographic, socioeconomic and environmental factors associated with seropositivity ofLeptospiraserogroup Icterohaemorraghiae and serogroup Cynopteri in an urban high transmission setting for leptospirosis in Brazil.Methods/Principal FindingsWe performed a cross-sectional serological study in five urban informal communities in the city of Salvador, Brazil. During the years 2018, 2020 2021, we recruited 2.808 residents and collected blood samples for serological analysis using microagglutination assays. We used a mixed-effect multinomial logistic regression model to identify risk factors associated with seropositivity for each serogroup. Seropositivity to Cynopteri increased with age in years (OR 1.03; 95% CI 1.01-1.06) and was higher in those living in houses with unplaster walls (exposed brick) (OR 1.68; 95% CI 1.09-2.59) and where cats were present near the household (OR 2.00; 95% CI 1.03-3.88). Seropositivity to Icterohaemorrhagiae also increased with age in years (OR 1.02; 95% CI 1.01-1.03) but was higher in males (OR 1.51; 95% CI 1.09-2.10), in those with work-related exposures (OR 1.71; 95% CI 1.10-2.66) or who had contact with sewage (OR 1.42; 95% CI 1.00-2.03). Spatial analysis showed differences in distribution of seropositivity to serogroups Icterohaemorrhagiae and Cynopteri within the five districts where study communities were situated.Conclusions/SignificanceOur data suggests distinct epidemiological patterns associated with serogroups Icterohaemorrhagiae and Cynopteri within the high-risk urban environment for leptospirosis and with differences of spatial niches. Future studies must identify the different pathogenic serogroups circulating in low-income areas, and further evaluate the potential role of cats in the transmission of the serogroup Cynopteri in urban settings.
Computational ranking-assisted identification of Plexin-B2 in homotypic and heterotypic clustering of circulating tumor cells in breast cancer metastasis
Authors: Schuster Emma , Dashzeveg Nurmaa , Jia Yuzhi , Golam Kibria , Zhang Tong , Hoffman Andrew , Zhang Youbin , Zheng Chunlei , Ramos Erika , Taftaf Rokana , Shennawy Lamiaa El- , Scholten David , Kitata Reta B. , Adorno-Cruz Valery , Reduzzi Carolina , Spahija Sabina , Xu Rong , Siziopikou Kalliopi P. , Platanias Leonidas C. , Shah Ami , Gradishar William J. , Cristofanilli Massimo , Tsai Chia-Feng , Shi Tujin , Liu Huiping 
Published: April 2023

AbstractMetastasis is the cause of over 90% of all deaths associated with breast cancer, yet the strategies to predict cancer spreading based on primary tumor profiles and therefore prevent metastasis are egregiously limited. As rare precursor cells to metastasis, circulating tumor cells (CTCs) in multicellular clusters in the blood are 20-50 times more likely to produce viable metastasis than single CTCs. However, the molecular mechanisms underlying various CTC clusters, such as homotypic tumor cell clusters and heterotypic tumor-immune cell clusters, are yet to be fully elucidated. Combining machine learning-assisted computational ranking with experimental demonstration to assess cell adhesion candidates, we identified a transmembrane protein Plexin- B2 (PB2) as a new therapeutic target that drives the formation of both homotypic and heterotypic CTC clusters. High PB2 expression in human primary tumors predicts an unfavorable distant metastasis-free survival and is enriched in CTC clusters compared to single CTCs in advanced breast cancers. Loss of PB2 reduces formation of homotypic tumor cell clusters as well as heterotypic tumor-myeloid cell clusters in triple-negative breast cancer. Interactions between PB2 and its ligand Sema4C on tumor cells promote homotypic cluster formation, and PB2 binding with Sema4A on myeloid cells (monocytes) drives heterotypic CTC cluster formation, suggesting that metastasizing tumor cells hijack the PB2/Sema family axis to promote lung metastasis in breast cancer. Additionally, using a global proteomic analysis, we identified novel downstream effectors of the PB2 pathway associated with cancer stemness, cell cycling, and tumor cell clustering in breast cancer. Thus, PB2 is a novel therapeutic target for preventing new metastasis.
An active traveling wave of Eda/NF-kB signaling controls the timing and hexagonal pattern of skin appendages in zebrafish
Authors: Evanitsky Maya N. , Di Talia Stefano 
Published: April 2023

AbstractPeriodic patterns make up a variety of tissues, including skin appendages such as feathers and scales. Skin appendages serve important and diverse functions across vertebrates, yet the mechanisms that regulate their patterning are not fully understood. Here, we have used live imaging to investigate dynamic signals regulating the ontogeny of zebrafish scales. Scales are bony skin appendages which develop sequentially along the anterior-posterior and dorsal-ventral axes to cover the fish in a hexagonal array. We have found that scale development requires cell-cell communication and is coordinated through an active wave mechanism. Using a live transcriptional reporter, we show that a wave of Eda/NF-κB activity precedes scale initiation and is required for scale formation. Experiments decoupling the propagation of the wave from dermal placode formation and osteoblast differentiation demonstrate that the Eda/NF-kB activity wavefront times the sequential patterning of scales. Moreover, this decoupling resulted in defects in scale size and significant deviations in the hexagonal patterning of scales. Thus, our results demonstrate that a biochemical traveling wave coordinates scale initiation and proper hexagonal patterning across the fish body.
A zero-agnostic model for copy number evolution in cancer
Authors: Schmidt Henri , Sashittal Palash , Raphael Benjamin J. 
Published: April 2023

AbstractMotivationNew low-coverage single-cell DNA sequencing technologies enable the measurement of copy number profiles from thousands of individual cells within tumors. From this data, one can infer the evolutionary history of the tumor by modeling transformations of the genome via copy number aberrations. A widely used model to infer suchcopy number phylogeniesis thecopy number transformation(CNT) model in which a genome is represented by an integer vector and a copy number aberration is an event that either increases or decreases the number of copies of a contiguous segment of the genome. The CNT distance between a pair of copy number profiles is the minimum number of events required to transform one profile to another. While this distance can be computed efficiently, no efficient algorithm has been developed to find the most parsimonious phylogeny under the CNT model.ResultsWe introduce thezero-agnostic copy number transformation(ZCNT) model, a simplification of the CNT model that allows the amplification or deletion of regions with zero copies. We derive a closed form expression for the ZCNT distance between two copy number profiles and show that, unlike the CNT distance, the ZCNT distance forms a metric. We leverage the closed-form expression for the ZCNT distance and an alternative characterization of copy number profiles to derive polynomial time algorithms for two natural relaxations of the small parsimony problem on copy number profiles. While the alteration of zero copy number regions allowed under the ZCNT model is not biologically realistic, we show on both simulated and real datasets that the ZCNT distance is a close approximation to the CNT distance. Extending our polynomial time algorithm for the ZCNT small parsimony problem, we develop an algorithm,Lazac, for solving the large parsimony problem on copy number profiles. We demonstrate thatLazacoutperforms existing methods for inferring copy number phylogenies on both simulated and real data.AvailabilityLazacis implemented in C++17 and is freely available at:github.com/raphaelgroup/lazac-copy-number.
A molecular arm: the molecular bending-unbending mechanism of integrin
Authors: Li Zhenhai 
Published: April 2023

AbstractIntegrin conformational change is the key to transmitting signals across the cell membrane. The integrin on the cell surface undergoes bending-unbending cycles while sensing and responding to the mechanical environment. Mechanical force triggers the unbending of integrin. However, how an integrin stably extends and how an extended integrin spontaneously bends back are unclear. I performed molecular dynamics simulations on integrin and its subunits to reveal the bending-unbending mechanism of integrin at the atomic level. According to the simulations, the integrin structure works like a human arm. The integrin α subunit serves as the bones, while the β leg serves as the bicep. Thus, the integrin extension results in the stretching of the β leg, and the extended integrin spontaneously bends as a consequence of the contraction of the β leg. This study provides new insights into the mechanism of how the integrin secures in the bent inactivated state and sheds light on the mechanism of how the integrin could achieve the stable extended state.Author summaryAs a mechanosensitive protein, the integrin is a molecular machine, which converts the mechano-signal to others, or in the opposite way. The reversible conformational change of integrin is the key to the mechanosensing function. It is straightforward that the integrin would extend while it senses pulling force. However, how integrin bends back after releasing the force is not clear. The ability to bend back guarantees that the integrin can be reused in the bending-unbending cycles. With molecular dynamics simulations, this study shows the integrin works as a molecular arm in the bending-unbending working cycles, which answers how the integrin spontaneously bends back. Meanwhile, based on this study, several hypothesized mechanisms for integrin to be stably extended are proposed.
Physiological accuracy in simulating refractory cardiac tissue: the volume-averaged bidomain model vs. the cell-based EMI model
Authors: Reimer Joyce , Domínguez-Rivera Sebastián A. , Sundnes Joakim , Spiteri Raymond J. 
Published: April 2023

AbstractThe refractory period of cardiac tissue can be quantitatively described using strength-interval (SI) curves. The information captured in SI curves is pertinent to the design of anti-arrhythmic devices including pacemakers and implantable cardioverter defibrillators. As computational cardiac modelling becomes more prevalent, it is feasible to consider the generation of computationally derived SI curves as a supplement or precursor to curves that are experimentally derived. It is beneficial, therefore, to examine the profiles of the SI curves produced by different cardiac tissue models to determine whether some models capture the refractory period more accurately than others. In this study, we compare the unipolar SI curves of two tissue models: the current state-of-the-art bidomain model and the recently developed extracellular-membrane-intracellular (EMI) model. The EMI model’s resolution of individual cell structure makes it a more detailed model than the bidomain model, which forgoes the structure of individual cardiac cells in favour of treating them homogeneously as a continuum. We find that the resulting SI curves elucidate differences between the models, including that the behaviour of the EMI model is noticeably closer to the refractory behaviour of experimental data compared to that of the bidomain model. These results hold implications for future computational pacemaker simulations and shed light on the predicted refractory properties of cardiac tissue from each model.Author summaryMathematical modelling and computational simulation of cardiac activity have the potential to greatly enhance our understanding of heart function and improve the precision of cardiac medicine. The current state-of-the-art model is the bidomain model, which considers a volume average of cardiac activity. Although the bidomain model has had success in several applications, in other situations, its approach may obscure critical details of heart function. The extracellular-membrane-intracellular (EMI) model is a recently developed model of cardiac tissue that addresses this limitation. It models cardiac cells individually; therefore, it offers significantly greater physiological accuracy than bidomain simulations. This increase in accuracy comes at a higher computational cost, however. To explore the benefits of one model over the other, here we compare the performance of the bidomain and EMI models in a pacing study of cardiac tissue often employed in pacemaker design. We find that the behaviour of the EMI model is noticeably closer to experimental data than the behaviour of the bidomain model.These results hold implications for future pacemaker design and improve our understanding of the two models in relation to one another.