bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Molecular Picture of the Local Environment in a Stable Model Coacervate
Authors: Baksi Atanu , Zerze Hasan , Agrawal Aman , Karim Alamgir , Zerze Gül H. 
Published: January 2024

Polymers with electric charge, known as polyelectrolytes, are well known to form complex coacervates, which have vital implications in various biological processes and beyond. While significant advancements have been made in comprehending the molecular interactions thatdrivecomplex coacervation, the interactions thatstabilizethe coacervates against coalescence present an intricate experimental challenge and remain a subject of ongoing investigation. In a recent experimental study, polydiallyldimethylammonium chloride polycationic (PDDA) and anionic adenosine triphosphate (ATP) coacervates have been shown to stabilize upon transferring them to deionized water. Here, we perform molecular dynamics simulations of PDDA-ATP coacervates both in supernatant and in DI water, to understand the ion dynamics and structure within stable coacervates. We produced and analyzed an aggregated sum of 63μssimulation data of PDDA-ATP coacervates in explicit water when they are in supernatant and deionized (DI) water. We found that discarding the supernatant and transferring the coacervates to DI water causes an immediate ejection of a significant amount (more than 50%) of small ions (Na+andCl−) from the coacervates to the bulk solution. Subsequently, the DI water environment alters the ionic density profiles in coacervates and the surface ion dynamics. We calculated a notable slowdown for the coacervate ions when they were transferred to the DI water. These results suggest that the initial ejection of the ions from the coacervates in DI water potentially brings the outer layer of the coacervates to a physically bound state that prevents or slows down the further mobility of ions.Significance StatementComplex coacervates are promising agents for encapsulating and delivering various materials in living organisms, however, they are often prone to coalesce, limiting the range of their applications. Recently, these coacervates have been stabilized by transferring them to deionized water. However, a molecular understanding of this stability against coalescence remained elusive. This study utilizes computer simulations to model a stable coacervate system previously probed experimentally. When the coacervates were transferred to deionized water, a significant portion of the ions were immediately ejected into the solution, modifying the coacervates’ total charge and facilitating formation of possible surface crust. These molecular insights into the stable coacervates will enable their controllable design for encapsulation and delivery applications.
Pharmacological validation of an attention bias test for conventional broiler chickens
Authors: Lourenço da Silva Marconi Italo , Ulans Alexandra , Jacobs Leonie 
Published: January 2024

AbstractFear and anxiety are considered concerns for animal welfare as they are associated with negative affective states. This study aimed to pharmacologically validate an attention bias test (ABT) for broiler chickens (Gallus gallus domesticus) as a cognitive bias test to determine anxiety. Two-hundred-and-four male Ross 708 broiler chickens were arbitrarily allocated to either the anxiogenic or control treatment at day 25 of age, resulting in 102 birds per treatment. Birds from the anxiogenic group were administered with 2.5 mg/kg of β-CCM (β-carboline-3-carboxylic acid-N-methylamide [FG 7142]) through an intraperitoneal injection at a volume of 0.1 ml/100 g of body weight. Birds from the control group were administered with 9 mg/kg of a saline solution. During ABT, birds were tested in groups of three (n = 34 groups of three birds/treatment) with commercial feed and mealworms as positive stimuli and a conspecific alarm call as a negative stimulus. Control birds were 45 s faster to begin feeding than anxiogenic birds. Birds from the control group vocalized 40 s later and stepped 57 s later than birds from the anxiogenic group. The occurrence of vigilance behaviors did not differ between treatments. This study was successful in pharmacologically validating an attention bias test for fast-growing broiler chickens, testing three birds simultaneously. Our findings showed that latencies to begin feeding, first vocalization, and first step were valid measures to quantify anxiety.
2018-2019 human seasonal H3N2 influenza A virus spillovers into swine with demonstrated virus transmission in pigs were not sustained in the pig population
Authors: Powell Joshua D. , Thomas Megan N. , Anderson Tavis K. , Zeller Michael A. , Gauger Phillip C. , Baker Amy L. Vincent 
Published: January 2024

ABSTRACTHuman seasonal H3 3C3a clade influenza A viruses (IAV) were detected in four U.S. pigs from commercial swine farms in Michigan, Illinois, and Virginia in 2019. To evaluate the relative risk of this spillover to the pig population, whole genome sequencing and phylogenetic characterization was conducted and revealed all eight viral gene segments were closely related to 2018-2019 H3N2 human seasonal IAV. Next, a series of in vitro viral kinetics, receptor binding, and antigenic characterization studies were performed using a representative A/swine/Virginia/A02478738/2018(H3N2) (SW/VA/19) isolate. Viral replication kinetic studies of SW/VA/19 demonstrated less efficient replication curves than all ten swine H3N2 viruses tested, but higher than three human H3N2 strains. Serial passaging experiments of SW/VA/19 in swine cells did not increase virus replication, but changes at HA amino acid positions 9 and 159 occurred. In swine transmission studies, wild type SW/VA/19 was shed in nasal secretions and transmitted to all indirect contact pigs, whereas the human seasonal strain A/Switzerland/9715293/2013(H3N2) from the same 3C3a clade failed to transmit. SW/VA/19 induced minimal macroscopic and microscopic lung lesions. Collectively these findings demonstrate that these human seasonal H3N2 3C3a-like viruses did not require reassortment with endemic swine IAV gene segments, impacting virus shedding and transmission in pigs. Limited detections in the U.S. pig population in the subsequent period of time suggests a yet unknown restriction factor likely limiting the spread of these viruses in the U.S. pig population.IMPORTANCEInterspecies human-to-swine IAV transmission occurs globally and contributes to increased IAV diversity in pig populations. We present data that a swine isolate from a 2018-2019 human-to-swine transmission event was shed for multiple days in challenged and contact pigs. By characterizing this introduction through bioinformatic, molecular, and animal experimental approaches, these findings better inform animal health practices and in vaccine decision-making. Since wholly human seasonal H3N2 viruses in the U.S. were not previously identified as being transmissible in pigs (i.e. reverse zoonosis), these findings reveal the interspecies barriers for transmission to pigs may not require significant changes to all human seasonal H3N2.
TransMEP: Transfer learning on large protein language models to predict mutation effects of proteins from a small known dataset
Authors: Hoffbauer Tilman , Strodel Birgit 
Published: January 2024

AbstractMachine learning-guided optimization has become a driving force for recent improvements in protein engineering. In addition, new protein language models are learning the grammar of evolutionarily occurring sequences at large scales. This work combines both approaches to make predictions about mutational effects that support protein engineering. To this end, an easy-to-use software tool called TransMEP is developed using transfer learning by feature extraction with Gaussian process regression. A large collection of datasets is used to evaluate its quality, which scales with the size of the training set, and to show its improvements over previous fine-tuning approaches. Wet-lab studies are simulated to evaluate the use of mutation effect prediction models for protein engineering. This showed that TransMEP finds the best performing mutants with a limited study budget by considering the trade-off between exploration and exploitation.Graphical TOC Entry
A user-friendly input–output (IO) curve analysis tool for variable brain stimulation responses, particularly evoked potentials in transcranial magnetic stimulation (TMS)
Authors: Ma Ke , Goetz Stephan M. 
Published: January 2024

AbstractBackgroundMotor-evoked potentials (MEPs) are among the few readily observable direct responses to suprathreshold stimuli administered to the brain. They serve for a variety of applications, often in the form of dose–response curves, also called recruitment or input–output (IO) curves. However, MEPs and thus IO curves demonstrate extreme trial-to-trial variability that can exceed more than two decimal orders of magnitude. Recent studies have identified issues in previous statistical analysis of IO curves and introduced better methods, others could quantitatively separate several widely independent variability sources. However, research has failed providing the field with a user-friendly implementation of the methods for analysing such IO curves statistically sound and separating variability so that they were limited to a few research groups.ObjectiveThis work intends to provide the latest methods for analysing IO curves and extract variability information in an open-source package so that the community can easily use and adapt them to their own needs.MethodsWe implemented recent IO curve methods with a graphical user interface and provided the code as well as compiled versions for Mac, Linux, and Windows.ResultsThe application imports typical IO data of individual stimulus–response sets, guides users step by step through the analysis, and allows exporting of the results including figures for post-hoc analysis and documentation.ConclusionThis graphical application offers a user-friendly environment for analysing the variability of evoked potentials and its various contributions, catering to the needs of clinical and experimental neuroscientists.
Prediction of Post Traumatic Epilepsy using MRI-based Imaging Markers
Authors: Akrami Haleh , Cui Wenhui , Kim Paul E. , Heck Christianne N. , Irimia Andrei , Jebri Karim , Nair Dileep , Leahy Richard M. , Joshi Anand A. 
Published: January 2024

AbstractPost-traumatic Epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Despite the high prevalence of PTE, current methods for predicting its occurrence remain limited. In this study, we aimed to identify imaging-based markers for the prediction of PTE using machine learning. Specifically, we examined three imaging features: lesion volumes and resting-state fMRI-based measures of functional connectivity and amplitude of low-frequency fluctuation (ALFF). We employed three machine learning methods, namely, kernel support vector machine (KSVM), random forest, and a neural network, to develop predictive models. Our results showed that the KSVM classifier, with all three feature types as input, achieved the best prediction accuracy of 0.78 AUC (Area Under the Receiver Operating Characteristic (ROC) curve) using nested cross-validation. Furthermore, we performed voxel-wise and lobe-wise group difference analyses to investigate the specific brain regions and features that the model found to be most helpful in distinguishing PTE from non-PTE populations. Our statistical analysis uncovered significant differences in bilateral temporal lobes and cerebellum between PTE and non-PTE groups. Overall, our findings demonstrate the complementary prognostic value of MR-based markers in PTE prediction and provide new insights into the underlying structural and functional alterations associated with PTE.
Revisiting the invasion paradox: resistance-richness relationship is driven by augmentation and displacement trends
Authors: Zhu Yu , Momeni Babak 
Published: January 2024

AbstractHost-associated resident microbiota can protect their host from pathogen—a community-level trait called colonization resistance. The effect of the diversity of the resident community in previous studies has shown contradictory results, with higher diversity either strengthening or weakening colonization resistance. To control the confounding factors that may lead to such contradictions, we use mathematical simulations that focus on species interactions and their impact on colonization resistance. We use a mediator-explicit model that accounts for metabolite-mediated interactions to performin silicoinvasion experiments. Our results state that colonization resistance often does not have a monotonic relationship with the species richness of the resident community. Instead, colonization outcomes are often the consequence of two underlying trends as the richness of the resident community increases: a decrease in instances of augmentation (invader species added, without driving out resident species) and an increase in instances of displacement (invader species added, driving out some of the resident species). We observe these two underlying trends hold consistently under different parameters, regardless of the number of compounds that mediate interactions between species or the proportion of the facilitative versus inhibitory interactions among species. Our results provide an explanation for the seemingly contradictory trend in the resistance-diversity relationship in previous reports.
Strategic Debulking of the Femoral Stem Promotes Load Sharing Through Controlled Flexural Rigidity of the Implant Wall: Optimization of Design by Finite Element Analysis
Authors: Sunavala-Dossabhoy Gulshan , Saba Brent M. , McCarthy Kevin 
Published: January 2024

AbstractHip arthroplasty prostheses are often constructed of metal alloys, and the inherent disparity in the modulus of elasticity between the implant and the femur is attributed to the altered stress-strain pattern in adjacent bone. Rigid implants shield surrounding bone from mechanical loading, and the reduction in skeletal stress required to maintain bone mass and density results in accelerated bone loss, the forerunner to implant loosening and implant failure. Femoral stems of various geometric profiles and surface modifications, materials and material distributions for graded functionality, and porous stem structures have been investigated to achieve mechanical properties of stems that are closer to bone to mitigate stress shielding. For improved load transfer from implant to femur, the proposed study investigated a strategic debulking effort to impart controlled flexibility while retaining sufficient strength and endurance properties of the femoral stem. Using an iterative design process, debulked configurations based on an internal skeletal truss framework were evaluated using finite element analysis as outlined in ISO 7206 standards, with implants offset in natural femur or potted in testing cylinders. The commonality across the debulked designs was the minimization of proximal stress shielding compared to conventional solid implants. Stem topography can influence performance, and the truss implants with and without the calcar collar were evaluated. Load sharing was equally effective irrespective of the collar however, the collar was critical to reducing the stresses in the implant. When bonded directly to bone or cemented in the femur, the truss stem was effective at limiting stress shielding. Nevertheless, a localized increase in principal stress at the lateral proximal junction could negatively affect cement integrity and the bonding of cemented implants. The study determined that superior biomechanical performance of the truss implant is realized with a collared stem that is placed in an interference fit. Mechanistically, the controlled accommodation of deformation of the implant wall provides contextual flexibility and load sharing characteristics to the truss implant.
Artificial intelligence–enabled electrocardiogram for mortality and cardiovascular risk estimation: An actionable, explainable and biologically plausible platform
Authors: Sau Arunashis , Pastika Libor , Sieliwonczyk Ewa , Patlatzoglou Konstantinos , Ribeiro Antonio H. , McGurk Kathryn A. , Zeidaabadi Boroumand , Zhang Henry , Macierzanka Krzysztof , Mandic Danilo , Sabino Ester , Giatti Luana , Barreto Sandhi M , do Valle Camelo Lidyane , Tzoulaki Ioanna , O’Regan Declan P. , Peters Nicholas S. , Ware James S. , Ribeiro Antonio Luiz P. , Kramer Daniel B. , Waks Jonathan W. , Ng Fu Siong 
Published: January 2024

AbstractBackground and AimsArtificial intelligence-enhanced electrocardiograms (AI-ECG) can be used to predict risk of future disease and mortality but has not yet been adopted into clinical practice. Existing model predictions lack actionability at an individual patient level, explainability and biological plausibility. We sought to address these limitations of previous AI-ECG approaches by developing the AI-ECG risk estimator (AIRE) platform.Methods and ResultsThe AIRE platform was developed in a secondary care dataset of 1,163,401 ECGs from 189,539 patients, using deep learning with a discrete-time survival model to create a subject-specific survival curve using a single ECG. Therefore, AIRE predicts not only risk of mortality, buttime-to-mortality. AIRE was validated in five diverse, transnational cohorts from the USA, Brazil and the UK, including volunteers, primary care and secondary care subjects. AIRE accurately predicts risk of all-cause mortality (C-index 0.775 (0.773-0.776)), cardiovascular (CV) death 0.832 (0.831-0.834), non-CV death (0.749 (0.747-0.751)), future ventricular arrhythmia (0.760 (0.756-0.763)), future atherosclerotic cardiovascular disease (0.696 (0.694-0.698)) and future heart failure (0.787 (0.785-0.889))). Through phenome- and genome-wide association studies, we identified candidate biological pathways for the prediction of increased risk, including changes in cardiac structure and function, and genes associated with cardiac structure, biological aging and metabolic syndrome.ConclusionAIRE is an actionable, explainable and biologically plausible AI-ECG risk estimation platform that has the potential for use worldwide across a wide range of clinical contexts for short- and long-term risk estimation.Graphical Abstract
Assessing the Incidence of Postoperative Diabetes in Gastric Cancer Patients: A Comparative Study of Roux-en-Y Gastrectomy and Other Surgical Reconstruction Techniques
Authors: Onishi Tatsuki 
Published: January 2024

AbstractStudy objectiveSleeve gastrectomy is effective in morbid obesity, and it improves glucose homeostasis. In gastric cancer patients with type 2 diabetes mellitus, gastrectomy, including total gastrectomy (TG), is beneficial for glycaemic control. However, the effects of gastrectomy and different reconstructive techniques on the incidence of postoperative diabetes in gastric cancer patients are unclear. This study investigated the development of new-onset diabetes in these patients, focusing on different reconstruction methods.DesignA comparative studySettingElectrical medical recordsPatientsThis study included 715 patients without diabetes who underwent TG at Tokyo Metropolitan Bokutoh Hospital between August 2005 and March 2019.InterventionsPatients underwent reconstruction by Roux-en-Y (RY) or other surgical techniques (OT), with diabetes onset determined by HbA1c levels or medical records.MeasurementsAnalyses included two-sample t-tests, chi-squared tests, and the Kaplan-Meier method with log-rank tests to compare the onset curves between the two groups.Main ResultsStratified data analysis compared the RY and OT reconstruction methods. Log-rank test results (P=0.0217) indicated a statistically significant difference in the incidence of new-onset diabetes between RY and OT groups in gastric cancer patients.ConclusionThis first-of-its-kind study provides insight into how different methods of gastric reconstruction affect postoperative diabetes. The results suggest significant differences in new-onset diabetes mellitus after surgery based on the reconstruction method. This research highlights the need for careful surgical planning to consider potential postoperative diabetes, particularly in patients with a family history of diabetes mellitus. Future studies should investigate the role of gut microbiota and other reconstructive techniques, such as laparoscopic jejunal interposition, in developing postoperative diabetes.
Genome assembly of the milky mangroveExcoecaria agallocha
Authors:   Hong Kong Biodiversity Genomics Consortium,   Project Coordinator and Co-Principal Investigators, Hui Jerome H.L. , Chan Ting Fung , Chan Leo L. , Cheung Siu Gin , Cheang Chi Chiu , Fang James K.H. , Gaitan-Espitia Juan Diego , Lau Stanley C.K. , Sung Yik Hei , Wong Chris K.C. , Yip Kevin Y.L. , Wei Yingying ,   DNA extraction, library preparation and sequencing, Law Sean T.S. , So Wai Lok ,   Genome assembly and gene model prediction, Nong Wenyan ,   Genome analysis and quality control, Nong Wenyan ,   Sample collector and logistics, Lau David T.W. , Law Sean T.S. , Lee Shing Yip , Yip Ho Yin 
Published: January 2024

AbstractThe milky mangroveExcoecaria agallochais a latex-secreting mangrove that are distributed in tropical and subtropical regions. While its poisonous latex is regarded as a potential source of phytochemicals for biomedical applications, the genomic resources ofE. agallocharemains limited. Here, we present a chromosomal level genome ofE. agallocha, assembled from the combination of PacBio long-read sequencing and Omni-C data. The resulting assembly size is 1,332.45 Mb and has high contiguity and completeness with a scaffold N50 of 58.9 Mb and a BUSCO score of 98.4 %. 73,740 protein-coding genes were also predicted. The milky mangrove genome provides a useful resource for further understanding the biosynthesis of phytochemical compounds inE. agallocha.
Spatio-temporal analysis of Vaccinia virus infection and host response dynamics using single-cell transcriptomics and proteomics
Authors: Matía Alejandro , McCarthy Frank , Woosley Hunter , Turon-Lagot Vincent , Platzer Sebastian W. , Liu Jonathan , Lorenzo María M. , Borja Michael , Shetty Kavya , Winkler Juliane , Elias Joshua E. , Blasco Rafael , Arias Carolina , Hein Marco Y. 
Published: January 2024

ABSTRACTPoxviruses are a large group of DNA viruses with exclusively cytoplasmic life cycles and complex gene expression programs. A number of systems-level studies have analyzed bulk transcriptome and proteome changes upon poxvirus infection, but the cell-to-cell heterogeneity of the transcriptomic response, and the subcellular resolution of proteomic changes have remained unexplored.Here, we measured single-cell transcriptomes of Vaccinia virus-infected populations of HeLa cells and immortalized human fibroblasts, resolving the cell-to-cell heterogeneity of infection dynamics and host responses within those cell populations. We further integrated our transcriptomic data with changes in the levels and subcellular localization of the host and viral proteome throughout the course of Vaccinia virus infection.Our findings from single-cell RNA sequencing indicate conserved transcriptome changes independent of the cellular context, including widespread host shutoff, heightened expression of cellular transcripts implicated in stress responses, the rapid accumulation of viral transcripts, and the robust activation of antiviral pathways in bystander cells. While most host factors were co-regulated at the RNA and protein level, we identified a subset of factors where transcript and protein levels were discordant in infected cells; predominantly factors involved in transcriptional and post-transcriptional mRNA regulation. In addition, we detected the relocalization of several host proteins such as TENT4A, NLRC5, and TRIM5, to different cellular compartments in infected cells. Collectively, our comprehensive data provide spatial and temporal resolution of the cellular and viral transcriptomes and proteomes and offer a robust foundation for in-depth exploration of virus-host interactions in poxvirus-infected cells.