bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of Frailty With Health Care Utilization for Patients Over One Year Following Surgical Evaluation
Authors: Flinn Stephen J. , Silver David S. , Hodges Jacob , Bilderback Andrew L. , Buchanan Dan , Ludwig Justin M. , Schuster James , Hall Daniel E. 
Published: January 2024

Objective:
Characterize the distribution of health care utilization associated with preoperative frailty in the year following evaluation by a surgeon.

Background:
Frailty is associated with increased morbidity, mortality, and costs for surgical patients. However, the total financial burden for frail patients beyond the index surgery and inpatient stay remains unknown.

Methods:
Prospective cohort assembled from February 2016 to December 2020 within a multihospital integrated health care delivery and finance system, from patients evaluated with the Risk Analysis Index of frailty. Inclusion criteria: age greater than 18 years, valid Risk Analysis Index, and membership in the integrated health care delivery and finance system health plan. Data were stratified by frailty and surgical status.

Results:
The mean (SD) age was 54.7 (16.1) years and 58.2% females of the cohort (n=86,572). For all patients with reimbursement for surgery (n=53,856), frail and very frail patients incurred respective increases of 8% (P=0.027) and 29% (P<0.001) in utilization relative to the normal group. Robust patients saw a 52% (P<0.001) decrease. This pattern was more pronounced in the cohort without surgery (n=32,716). The increase over normal utilization for frail and very frail patients increased to 23% (P=0.004) and 68% (P<0.001), respectively. Utilization among robust patients decreased by 62% (P<0.001). Increases among the frail were primarily due to increased inpatient medical and postacute care services (all P<0.001).

Conclusions:
Patient frailty is associated with increased total health care utilization, primarily via increased inpatient medical and postacute care following surgery. Quantifying these frailty-related financial burdens may inform clinical decision-making as well as the design of value-based reimbursement strategies.
Numerical direct scattering transform for breathers
Authors: Mullyadzhanov I. I. , Gudko A. S. , Mullyadzhanov R. I. , Gelash A. A. 
Published: January 2024

We consider the model of the focusing one-dimensional nonlinear Schrödinger equation (fNLSE) in the presence of an unstable constant background, which exhibits coherent solitary wave structures—breathers. Within the inverse scattering transform (IST) method, we study the problem of the scattering data numerical computation for a broad class of breathers localized in space. Such a direct scattering transform (DST) procedure requires a numerical solution of the auxiliary Zakharov–Shabat system with boundary conditions corresponding to the background. To find the solution, we compute the transfer matrix using the second-order Boffetta–Osborne approach and recently developed high-order numerical schemes based on the Magnus expansion. To recover the scattering data of breathers, we derive analytical relations between the scattering coefficients and the transfer matrix elements. Then we construct localized single- and multi-breather solutions and verify the developed numerical approach by recovering the complete set of scattering data with the built-in accuracy providing the information about the amplitude, velocity, phase and position of each breather. To combine the conventional IST approach with the efficient dressing method for multi-breather solutions, we derive the exact relation between the parameters of breathers in these two frameworks.
MicroFisher: Fungal taxonomic classification for metatranscriptomic and metagenomic data using multiple short hypervariable markers
Authors: Wang Haihua , Wu Steven , Zhang Kaile , Chen Ko-Hsuan , Vilgalys Rytas , Liao Hui-Ling 
Published: January 2024

AbstractProfiling the taxonomic and functional composition of microbes using metagenomic (MG) and metatranscriptomic (MT) sequencing is advancing our understanding of microbial functions. However, the sensitivity and accuracy of microbial classification using genome– or core protein-based approaches, especially the classification of eukaryotic organisms, is limited by the availability of genomes and the resolution of sequence databases. To address this, we propose the MicroFisher, a novel approach that applies multiple hypervariable marker genes to profile fungal communities from MGs and MTs. This approach utilizes the hypervariable regions of ITS and large subunit (LSU) rRNA genes for fungal identification with high sensitivity and resolution. Simultaneously, we propose a computational pipeline (MicroFisher) to optimize and integrate the results from classifications using multiple hypervariable markers. To test the performance of our method, we applied MicroFisher to the synthetic community profiling and found high performance in fungal prediction and abundance estimation. In addition, we also used MGs from forest soil and MTs of root eukaryotic microbes to test our method and the results showed that MicroFisher provided more accurate profiling of environmental microbiomes compared to other classification tools. Overall, MicroFisher serves as a novel pipeline for classification of fungal communities from MGs and MTs.
Burkholderia cenocepaciaepigenetic regulator M.BceJIV simultaneously engages two DNA recognition sequences for methylation
Authors: Quintana-Feliciano Richard , Kottur Jithesh , Ni Mi , Ghosh Rikhia , Salas-Estrada Leslie , Rechkoblit Olga , Filizola Marta , Fang Gang , Aggarwal Aneel K. 
Published: January 2024

AbstractBurkholderia cenocepaciais an opportunistic and infective bacterium containing an orphan DNA methyltransferase (M.BceJIV) with roles in regulating gene expression and motility of the bacterium. M.BceJIV recognizes a GTWWAC motif (where W can be an adenine or a thymine) and methylates the N6 of the adenine at the fifth base position (GTWWAC). Here, we present a high-resolution crystal structure of M.BceJIV/DNA/sinefungin ternary complex and allied biochemical, computational, and thermodynamic analyses. Remarkably, the structure shows not one, but two DNA substrates bound to the M.BceJIV dimer, wherein each monomer contributes to the recognition of two recognition sequences. This unexpected mode of DNA binding and methylation has not been observed previously and sets a new precedent for a DNA methyltransferase. We also show that methylation at two recognition sequences occurs independently, and that GTWWAC motifs are enriched in intergenic regions of a strain ofB. cenocepacia’sgenome. We further computationally assess the interactions underlying the affinities of different ligands (SAM, SAH, and sinefungin) for M.BceJIV, as a step towards developing selective inhibitors for limitingB. cenocepaciainfection.
Freshwater ‘microcroissants’ shed light on a novel higher-level clade within Trebouxiophyceae and reveal the genusChlorolobionas a trebouxiophyte
Authors: Barcytė Dovilė , Hodač Ladislav , Eliáš Marek 
Published: January 2024

AbstractTrebouxiophyceae is a widespread and species-rich green algal class encompassing mostly coccoid algae with a simple ovoid or ellipsoidal outline. However, some poorly-sampled lineages have evolved more elaborate shapes or even complex thalli, adding to the class’s morphological diversity. Led by new and previously established strains, this study additionally uncovered a clade of croissant-like trebouxiophytes. Phylogenetic analyses inferred from nuclear 18S rDNA and chloroplastrbcLsequences confirmed the monophyly of the ‘microcroissant’ clade, which we propose to be classified as a new family, Ragelichloridaceae. This family includes two novel genera,RagelichlorisandNavichloris, and the previously describedThorsmoerkia. The position of Ragelichloridaceae within Trebouxiophyceae stayed unresolved but chloroplast phylogenomics showed that the family belongs to the broaderincertae sedisgroup, which also includesXylochlorisandLeptosira. In addition, our study showed that the microcroissant-like genusChlorolobion, previously classified within Chlorophyceae, is a genuine trebouxiophyte, potentially related to Ragelichloridaceae.HighlightsA new family-level clade uncovered within Trebouxiophyceae.Two new genera described.The genusChlorolobionshown to be a trebouxiophyte.
The blast effector Pwl2 is a virulence factor that modifies the cellular localisation of host protein HIPP43 to suppress immunity
Authors: Were Vincent , Yan Xia , Foster Andrew J. , Sklenar Jan , Langner Thorsten , Gentle Amber , Sahu Neha , Bentham Adam , Zdrzałek Rafał , Ryder Lauren , Kaimenyi Davies , Gomez De La Cruz Diana , Petit-Houdenot Yohan , Eseola Alice Bisola , Smoker Matthew , Bautista Mark Jave , Ma Weibin , Kourelis Jiorgos , Maclean Dan , Banfield Mark J. , Kamoun Sophien , Menke Frank L.H. , Moscou Matthew J. , Talbot Nicholas J. 
Published: January 2024

AbstractThe rice blast fungusMagnaporthe oryzaesecretes a battery of effector proteins to facilitate host infection. Among these effectors, Pwl2 was first identified as a host specificity determinant for infection of weeping lovegrass (Eragrostis curvula) and is also recognised by the barley Mla3 resistance gene. However, its biological activity is not known. Here we show thatPWL2expression is regulated by the Pmk1 MAP kinase during cell-to-cell movement byM. oryzaeat plasmodesmata (PD)-containing pit field sites. Consistent with its regulation, we provide evidence that Pwl2 binds to a barley heavy metal-binding isoprenylated protein HIPP43, which results in its displacement from plasmodesmata. Transgenic barley lines overexpressing eitherPWL2or HIPP43 exhibit attenuated immune responses and increased disease susceptibility. By contrast, a Pwl2SNDEYWYmutant that does not interact with HIPP43, fails to alter the PD localisation of HIPP43. Targeted deletion of three copies ofPWL2inM. oryzaeresults in aΔpwl2mutant showing gain-of-virulence to weeping lovegrass and barley Mla3 lines, but also a reduction in severity of blast disease on susceptible host plants. Taken together, our results provide evidence that Pwl2 is a virulence factor that acts by suppressing host immunity through perturbing the plasmodesmatal deployment of HIPP43.
Deregulation of multiple mechanisms shapes the onset ofLAMA2-congenital muscular dystrophy
Authors: Martins Susana G , Ribeiro Vanessa , Melo Catarina , Paulino-Cavaco Cláudia , Antonini Dario , Naidu Sharadha Dayalan , Murtinheira Fernanda , Fonseca Inês , Saget Bérénice , Pita Mafalda , Fernandes Diogo R , dos Santos Pedro G , Rodrigues Gabriela , Zilhão Rita , Herrera Federico , Dinkova-Kostova Albena T , Carlos Ana Rita , Thorsteinsdóttir Sólveig 
Published: January 2024

ABSTRACTLAMA2-congenital muscular dystrophy (LAMA2-CMD) is the most common congenital muscular dystrophy. This often-lethal disease is triggered by mutations inLAMA2, coding for laminin-α2 chain, a key extracellular matrix (ECM) component, prevalent in the skeletal muscle. Several phenotypes have been associated with LAMA2-CMD, however, it is not yet known what mechanisms are faulty, right at disease onsetin utero. Using thedyWmouse model of LAMA2-CMD we showed that the disease onset is characterized by a profound downregulation of gene expression, with a marked effect on cytoskeletal organization, myoblast differentiation and fusion and altered DNA repair and oxidative stress responses. Concordantly, we found thatLama2-deficient myoblast cells displayed proliferation and differentiation defects, increased oxidative stress and DNA damage. Together, our findings provide unique insights into the processes dependent on laminin-α2 chain during muscle development, revealing its critical importance to maintain muscle cell homeostasis already at fetal stages.
Understanding and predicting ligand efficacy in the mu-opioid receptor through quantitative dynamical analysis of complex structures
Authors: Galdino Gabriel Tiago , Mailhot Olivier , Najmanovich Rafael 
Published: January 2024

AbstractTheµ-opioid receptor (MOR) is a G-protein coupled receptor involved in nociception and is the primary target of opioid drugs. Understanding the relationships between ligand structure, receptor dynamics, and efficacy in activating MOR is crucial for drug discovery and development. Here, we use coarse-grained normal mode analysis to predict ligand-induced changes in receptor dynamics with the Quantitative Dynamics Activity Relationships (QDAR) DynaSig-ML methodology, training a LASSO regression model on the entropic signatures (ES) computed from ligand-receptor complexes. We train and validate the methodology using a dataset of 179 MOR ligands with experimentally measured efficacies split into strickly chemically different cross-validation sets. By analyzing the coefficients of the ES LASSO model, we identified key residues involved in MOR activation, several of which have mutational data supporting their role in MOR activation. Additionally, we explored a contacts-only LASSO model based on ligand-protein interactions. While the model showed predictive power, it failed at predicting efficacy for ligands with low structural similarity to the training set, emphasizing the importance of receptor dynamics for predicting ligand-induced receptor activation. Moreover, the low computational cost of our approach, at 3 CPU seconds per ligand-receptor complex, opens the door to its application in large-scale virtual screening contexts. Our work contributes to a better understanding of dynamics-function relationships in theµ-opioid receptor and provides a framework for predicting ligand efficacy based on ligand-induced changes in receptor dynamics.Contactrafael.najmanovich@umontreal.ca
Temperature-mediated dynamics: unraveling the impact of temperature on cuticular hydrocarbon profiles, mating behavior, and life history traits in threeDrosophilaspecies
Authors: Baleba Steve B. S. , Jiang Nan-Ji , Hansson Bill S. 
Published: January 2024

AbstractIn a world grappling with climate change, understanding the enduring impact of changes in temperature on insect adult traits is crucial. Here, we explored the intricate dynamics of exposure to different temperatures in threeDrosophilaspecies:Drosophila ezoanaoriginating in Arctic regions,D. novamexicanain arid, hot environments, and in the cosmopolitan speciesD. virilis. Rearing these flies at 15, 20, 25, and 30°C revealed striking variations in their cuticular hydrocarbon (CHC) profiles, known to mediate mate recognition and prevent water loss in insects. The cold-adaptedD. ezoanaconsistently exhibited reduced CHC levels with increasing temperatures, while the warm-adaptedD. novamexicanaand the cosmopolitanD. virilisdisplayed more nuanced responses. Additionally, we observed a significant influence of rearing temperature on the mating behavior of these flies, where those reared at the extreme tempreatures, 15 and 30°C, exhibiting reduced mating success. Consequently, this led to a decrease in the production of adult offspring. Also these adult offspring underwent notable alterations in life history traits, reaching adulthood more rapidly at 25 and 30°C but with lower weight and reduced longevity. Furthermore, among these offspring, those produced by the cold-adaptedD. ezoanawere more vulnerable to desiccation and starvation compared to those from the warm-adaptedD. novamexicanaand the cosmopolitanD. virilis. In summary, our research underscores the intricate interplay between temperature, ecological adaptation and various life history traits inDrosophilaspecies from distinct agro-ecological regions. The observed variations in CHC profiles, mating behavior, fertility and responses to environmental stressors collectively provide valuable insights into how environmental conditions shape the biology and ecology of insects.
Effects of mineral addition on the establishment of grazing lawns in a nutrient poor savanna
Authors: Schroder Bradley , Langevelde Frank Van , Schroder Nicola-Anne Hawkins , Prins Herbert H. T. 
Published: January 2024

AbstractNutrient poor savannas are often characterized by inedible or rarely palatable grasses, which generally provide poor nutrition for mammalian grazers. So-called grazing lawns, with short, stoloniferous edible grasses, could provide high-quality food for grazers, but these lawn grasses are rare in nutrient poor savannas. We tested whether we could use mineral addition to establish grazing lawns in a nutrient poor African savanna, in order to achieve a switch from tall, nutritionally poor to short, highly nutritional grass species. The key finding is that phosphorus and lime, nitrogen and nitrogen and lime supplementation resulted in shift from tall to short grasses within three years, with a higher overall nutrient concentration in the grass leaf, than without supplementation. When grazed, the cover of lawn grasses was higher compared to the other grasses when not grazed, demonstrating the role of grazers in maintaining and expanding lawn grass patches. We conclude that local fertilisation in nutrient poor savannas is a viable method of increasing mineral levels in the soil and grass leaf. We also concluded that grazing results in an increase in lawn grass cover and a combination of fertilisation and grazing can improve forage quality to ensure higher nutrient availability to herbivores.
A novel zebrafish-basedin vivomodel of Zika virus infection unveils NS4A as a key viral determinant of neuropathogenesis
Authors: Sow Aïssatou Aïcha , Jamadagni Priyanka , Scaturro Pietro , Patten Shunmoogum A. , Chatel-Chaix Laurent 
Published: January 2024

ABSTRACTInfection of pregnant women by Zika virus (ZIKV) is associated with severe neurodevelopmental defects in newborns through poorly defined mechanisms. Here, we engineered a zebrafishin vivomodel of ZIKV infection to circumvent limitations of existing mammalian models. Leveraging the unique tractability of this system, we gained unprecedented access to the ZIKV-infected brain at early developmental stages. The infection of zebrafish larvae with ZIKV phenocopied the disease in mammals including a reduced head area and neural progenitor cells (NPC) infection and depletion. Moreover, transcriptomic analyses of ZIKV-infected NPCs revealed a distinct dysregulation of genes involved in survival and neuronal differentiation, including downregulation of the expression of the glutamate transportervglut1, resulting in an altered glutamatergic network in the brain. Mechanistically, ectopic expression of ZIKV protein NS4A in the larvae recapitulated the morphological defects observed in infected animals, identifying NS4A as a key determinant of neurovirulence and a promising antiviral target for developing therapies.
Predicting Prolonged Length of Stay For Hospitalized Stroke Patients Using Common Physiological Features
Authors: Murphy Zachary , Ainsworth Michael , Gong Kirby , Zink Elizabeth K. , Greenstein Joseph L. , Winslow Raimond L. , Bahouth Mona N. 
Published: January 2024

ABSTRACTBackground and PurposeStroke is a leading cause of death and disability worldwide. Predicting which patients are at risk for a prolonged length of stay (LOS) could assist in coordination of care and serve as a rough measure of clinical recovery trajectory. During the acute stroke period, there is a disruption in the fidelity of the blood-brain barrier and cerebral autoregulation, and we hypothesize that trends in physiologic parameters early in a patient’s hospital course may be used to predict which patients are increased risk for a prolonged LOS. In this work we sought to create a model to predict prolonged LOS (defined as ≥ 7 days) from patient data available at admission as well as routinely collected physiologic (pulse, blood pressure, respiratory rate, temperature), and other data from the first 24 hours of admission.MethodsThis retrospective cohort study included stroke patients admitted to an urban comprehensive stroke center between 2016-2019. Data included common physiological parameters (pulse, temperature, blood pressure, respirations, and oxygen saturation) as well as demographic and comorbidity data. Raw time series data were transformed into statistical features for modeling. Logistic regression, random forest, and XGBoost models were trained on data collected during the first 24 hours after hospital admission to predict prolonged LOS and evaluated on a held-out test set.ResultsA total of 2,025 patients were included. Using an XGBoost classifier we obtained a ROC AUC of 0.85 and Precision-Recall AUC of 0.77, with the optimal operating point achieving an accuracy of 0.80, sensitivity of 0.78, specificity of 0.81.ConclusionsThe model suggests that prolonged LOS can be predicted with reasonable accuracy using clinical data obtained within the first 24 hours of hospitalization. This approach could provide the basis for development of a risk score and augment the care coordination process.
edgeR v4: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets
Authors: Chen Yunshun , Chen Lizhong , Lun Aaron T. L. , Baldoni Pedro L. , Smyth Gordon K. 
Published: January 2024

AbstractedgeR is an R/Bioconductor software package for differential analyses of sequencing data in the form of read counts for genes or genomic features. Over the past 15 years, edgeR has been a popular choice for statistical analysis of data from sequencing technologies such as RNA-seq or ChIP-seq. edgeR pioneered the use of the negative binomial distribution to model read count data with replicates and the use of generalized linear models to analyse complex experimental designs. edgeR implements empirical Bayes moderation methods to allow reliable inference when the number of replicates is small. This article announces edgeR version 4, which includes new developments across a range of application areas. Infrastructure improvements include support for fractional counts, implementation of model fitting in C, and a new statistical treatment of the quasi-likelihood pipeline that improves accuracy for small counts. The revised package has new functionality for differential methylation analysis, differential transcript expression, differential transcript and exon usage, testing relative to a fold-change threshold and pathway analysis. This article reviews the statistical framework and computational implementation of edgeR, briefly summarizing all the existing features and functionalities but with special attention to new features and those that have not been described previously.