bluuebunny/crossref_metadata_2025_split huggingface dataset:
Open Educational Resources: Equitable and Affordable Nursing Education
Authors: Friday Vivienne Evet , Hunt Cynthia 
Published: August 2023

Abstract
This research report describes findings from a study conducted to learn students’ experiences using open educational resources (OER) in an online nursing research course. Twenty-three students participated in a pilot study in which traditional textbooks were replaced with OER as the primary course material. Data were collected by administering open-ended and closed-ended questions about students’ experiences and demographic characteristics. Findings indicated that OER were cost-effective, accessible, easy to navigate, and interesting. The resources were adequate to meet student learning outcomes. Challenges experienced were related to poor Internet access for a few students.
Laparoscopic Oblique Rectus Abdominis Myocutaneous Flap Harvest for Perineal Reconstruction After Abdominoperineal Resection
Authors: Devriendt Stefanie , Van Praet Laura , Bislenghi Gabriele , D’Hoore André J. L. , Wolthuis Albert M. 
Published: August 2023

BACKGROUND:
Treatment of perineal defects after abdominoperineal resection or salvage surgery for either locally advanced rectal cancer or anal carcinoma can be challenging. Myocutaneous flap reconstruction has proven to reduce perineal morbidity and abscess formation in the pelvis; however, it is associated with significant donor-site morbidity. To our knowledge, this is the first report of a laparoscopic oblique rectus abdominis myocutaneous flap harvesting for perineal reconstruction. This technical note aimed to demonstrate the feasibility of the technique.

IMPACT OF INNOVATION:
Introduction of a laparoscopic technique in harvesting of this flap can potentially further reduce morbidity associated with this flap creation by minimizing abdominal wall trauma and obviating the need for laparotomy for tunneling of the flap intra-abdominally.

TECHNOLOGY, MATERIALS, AND METHODS:
This report describes a technique using a 6-port laparoscopy, in which the harvesting of the myocutaneous flap was performed after a standardized abdominoperineal resection. The flap itself is passed through the rectus sheath toward the pelvis with the help of a retractor.

PRELIMINARY RESULTS:
Two patients successfully underwent a laparoscopic oblique rectus abdominis flap reconstruction after abdominoperineal resection.

CONCLUSION AND FUTURE DIRECTIONS:
This report describes our initial experience with laparoscopic harvesting of an oblique rectus abdominis flap for perineal reconstruction after abdominoperineal resection. We believe the technique is easy and reproducible for laparoscopic surgeons and can reduce donor-site morbidity. However, further studies will be needed to confirm this observation.
A global action agenda for turning the tide on fatty liver disease
Authors: Lazarus Jeffrey V. , Mark Henry E. , Allen Alina M. , Arab Juan Pablo , Carrieri Patrizia , Noureddin Mazen , Alazawi William , Alkhouri Naim , Alqahtani Saleh A. , Anstee Quentin M. , Arrese Marco , Bataller Ramon , Berg Thomas , Brennan Paul N. , Burra Patrizia , Castro-Narro Graciela E. , Cortez-Pinto Helena , Cusi Kenneth , Dedes Nikos , Duseja Ajay , Francque Sven M. , Gastaldelli Amalia , Hagström Hannes , Huang Terry T.K. , Ivancovsky Wajcman Dana , Kautz Achim , Kopka Christopher J. , Krag Aleksander , Newsome Philip N. , Rinella Mary E. , Romero Diana , Sarin Shiv Kumar , Silva Marcelo , Spearman C. Wendy , Terrault Norah A. , Tsochatzis Emmanuel A. , Valenti Luca , Villota-Rivas Marcela , Zelber-Sagi Shira , Schattenberg Jörn M. , Wong Vincent Wai-Sun , Younossi Zobair M. ,   on behalf of the Healthy Livers, Healthy Lives Collaborators
Published: August 2023

Background and Aims:Fatty liver disease is a major public health threat due to its very high prevalence and related morbidity and mortality. Focused and dedicated interventions are urgently needed to target disease prevention, treatment, and care.Approach and Results:We developed an aligned, prioritized action agenda for the global fatty liver disease community of practice. Following a Delphi methodology over 2 rounds, a large panel (R1 n = 344, R2 n = 288) reviewed the action priorities using Qualtrics XM, indicating agreement using a 4-point Likert-scale and providing written feedback. Priorities were revised between rounds, and in R2, panelists also ranked the priorities within 6 domains: epidemiology, treatment and care, models of care, education and awareness, patient and community perspectives, and leadership and public health policy. The consensus fatty liver disease action agenda encompasses 29 priorities. In R2, the mean percentage of “agree” responses was 82.4%, with all individual priorities having at least a super-majority of agreement (> 66.7% “agree”). The highest-ranked action priorities included collaboration between liver specialists and primary care doctors on early diagnosis, action to address the needs of people living with multiple morbidities, and the incorporation of fatty liver disease into relevant non-communicable disease strategies and guidance.Conclusions:This consensus-driven multidisciplinary fatty liver disease action agenda developed by care providers, clinical researchers, and public health and policy experts provides a path to reduce the prevalence of fatty liver disease and improve health outcomes. To implement this agenda, concerted efforts will be needed at the global, regional, and national levels.
Host genetic variation guides hepacivirus clearance, chronicity, and liver fibrosis in mice
Authors: Brown Ariane J. , Won John J. , Wolfisberg Raphael , Fahnøe Ulrik , Catanzaro Nicholas , West Ande , Moreira Fernando R. , Nogueira Batista Mariana , Ferris Martin T. , Linnertz Colton L. , Leist Sarah R. , Nguyen Cameron , De la Cruz Gabriela , Midkiff Bentley R. , Xia Yongjuan , Evangelista Mia D. , Montgomery Stephanie A. , Billerbeck Eva , Bukh Jens , Scheel Troels K.H. , Rice Charles M. , Sheahan Timothy P. 
Published: August 2023

Background & Aims:
Human genetic variation is thought to guide the outcome of HCV infection, but model systems within which to dissect these host genetic mechanisms are limited. Norway rat hepacivirus, closely related to HCV, causes chronic liver infection in rats but causes acute self-limiting hepatitis in typical strains of laboratory mice, which resolves in 2 weeks. The Collaborative Cross (CC) is a robust mouse genetics resource comprised of a panel of recombinant inbred strains, which model the complexity of the human genome and provide a system within which to understand diseases driven by complex allelic variation.

Approach & Results:
We infected a panel of CC strains with Norway rat hepacivirus and identified several that failed to clear the virus after 4 weeks. Strains displayed an array of virologic phenotypes ranging from delayed clearance (CC046) to chronicity (CC071, CC080) with viremia for at least 10 months. Body weight loss, hepatocyte infection frequency, viral evolution, T-cell recruitment to the liver, liver inflammation, and the capacity to develop liver fibrosis varied among infected CC strains.

Conclusions:
These models recapitulate many aspects of HCV infection in humans and demonstrate that host genetic variation affects a multitude of viruses and host phenotypes. These models can be used to better understand the molecular mechanisms that drive hepacivirus clearance and chronicity, the virus and host interactions that promote chronic disease manifestations like liver fibrosis, therapeutic and vaccine performance, and how these factors are affected by host genetic variation.
Legislative Advocacy on Capitol Hill
Authors: Jagger Kaeser Jennifer G. , Farley Cindy L. , Bradford Heather M. , Heitzler Ella T. , McDevitt Katie , Gutterman Zoe 
Published: August 2023

Background:
Policies, regulations, and laws influence all aspects of health care, including the education of health care professionals, independent practice, and patient access to care. Health equity and social justice are mediated through policy.

Problem:
While health policy knowledge and skills are recognized as essential competencies within nursing and midwifery curricula, most students graduate with limited or no experience engaging in advocacy efforts to advance legislation that would improve health systems and the delivery of care.

Approach:
An experiential learning activity is described that gives students authentic experience in federal legislative advocacy.

Outcomes:
Students report powerful, positive learning from interacting with their legislators.

Conclusion:
Support of a legislative advocacy experiential learning activity requires ongoing faculty initiative and can promote advancement of health policy bills into law. Opportunities to participate in legislative advocacy need to be expanded within nursing and midwifery education to cultivate leaders who can effect policy change.
PharaohFUN: PHylogenomic Analysis foR plAnt prOtein History and FUNction elucidation
Authors: Ramos-González Marcos , Ramos-González Víctor , Arvanitidou Christina , Hernández-García Jorge , García-González Mercedes , Romero-Campero Francisco José 
Published: August 2023

AbstractMotivationSince DNA sequencing has turned commonplace, the development of efficient methods and tools to explore gene sequences has become indispensable. In particular, despite photosynthetic eukaryotes constituting the largest percentage of terrestrial biomass, computational functional characterization of gene sequences in these organisms still predominantly relies on comparisons withArabidopsis thalianaand other angiosperms. This paper introduces PharaohFUN, a web application designed for the evolutionary and functional analysis of protein sequences in photosynthetic eukaryotes, leveraging orthology relationships between them.ResultsPharaohFUN incorporates a homogeneous representative sampling of key species in this group, bridging clades that have traditionally been studied separately, thus establishing a comprehensive evolutionary framework to draw conclusions about sequence evolution and function. For this purpose, it incorporates modules for exploring gene tree evolutionary history, domain identification, multiple sequence alignments, and functional annotation. The study of the CCA1 protein exemplifies how PharaohFUN unifies results for both land plants and chlorophyte microalgae, accurately tracing the evolutionary history of this protein.Availability and ImplementationPharaohFUN web application is freely available athttps://greennetwork.us.es/AlgaeFUN/and its source code can be freely accessed athttps://github.com/fran-romero-campero/AlgaeFUN.Contactfran@us.es
The pace of mitochondrial molecular evolution varies with seasonal migration distance
Authors: Pegan Teresa M. , Berv Jacob S. , Gulson-Castillo Eric R. , Kimmitt Abigail A. , Winger Benjamin M. 
Published: August 2023

AbstractAnimals that engage in long-distance seasonal migration experience strong selective pressures on their metabolic performance and life history, with potential consequences for molecular evolution. Species with slow life histories typically show lower rates of synonymous substitution (dS) than “fast” species. Previous work has suggested that long-distance seasonal migrants have a slower life history strategy than short-distance migrants, raising the possibility that rates of molecular evolution may covary with migration distance. Additionally, long-distance migrants may face strong selection on metabolically important mitochondrial genes owing to their long-distance flights. Using over 1000 mitochondrial genomes, we assessed the relationship between migration distance and mitochondrial molecular evolution in 39 boreal-breeding migratory bird species. We show that migration distance correlates negatively with dS, suggesting that the slow life history associated with long-distance migration is reflected in rates of molecular evolution. Mitochondrial genes in every study species exhibited evidence of purifying selection, but the strength of selection was greater in short-distance migrants, contrary to our predictions. This result may indicate selection for cold tolerance on mitochondrial evolution among species overwintering at high latitudes. Our study demonstrates that the pervasive correlation between life history and molecular evolutionary rates exists in the context of differential adaptations to seasonality.
From Proteins to Ligands: Decoding Deep Learning Methods for Binding Affinity Prediction
Authors: Gorantla Rohan , Kubincová Ažbeta , Weiße Andrea Y. , Mey Antonia S. J. S. 
Published: August 2023

AbstractAccuratein silicoprediction of protein-ligand binding affinity is important in the early stages of drug discovery. Deep learning-based methods exist but have yet to overtake more conventional methods such as giga-docking largely due to their lack of generalisability. To improve generalizability we need to understand what these models learn from input protein and ligand data. We systematically investigated a sequence-based deep learning framework to assess the impact of protein and ligand encodings on predicting binding affinities for commonly used kinase data sets. The role of proteins is studied using convolutional neural network-based encodings obtained from sequences and graph neural network-based encodings enriched with structural information from contact maps. Ligand-based encodings are generated from graph-neural networks. We test different ligand perturbations by randomizing node and edge properties. For proteins we make use of 3 different protein contact generation methods (AlphaFold2, Pconsc4, and ESM-1b) and compare these with a random control. Our investigation shows that protein encodings do not substantially impact the binding predictions, with no statistically significant difference in binding affinity for KIBA in the investigated metrics (concordance index, Pearson’s R Spearman’s Rank, and RMSE). Significant differences are seen for ligand encodings with random ligands and random ligand node properties, suggesting a much bigger reliance on ligand data for the learning tasks. Using different ways to combine protein and ligand encodings, did not show a significant change in performance.TOC Graphic
XRN1deletion induces PKR-dependent cell lethality in interferon-activated cancer cells
Authors: Zou Tao , Zhou Meng , Gupta Akansha , Zhuang Patrick , Fishbein Alyssa R. , Wei Hope Y. , Zhang Zhouwei , Cherniack Andrew D. , Meyerson Matthew 
Published: August 2023

SummaryEmerging data suggest that induction of viral mimicry responses through activation of double-stranded RNA (dsRNA) sensors in cancer cells is a promising therapeutic strategy. One approach to induce viral mimicry is to target molecular regulators of dsRNA sensing pathways. Here, we show that the exoribonuclease XRN1 is a negative regulator of the dsRNA sensor protein kinase R (PKR) in cancer cells with high interferon-stimulated gene (ISG) expression.XRN1deletion causes PKR activation and consequent cancer cell lethality. Disruption of interferon signaling with the JAK1/2 inhibitor ruxolitinib can decrease cellular PKR levels and rescue sensitivity toXRN1deletion. Conversely, interferon-β stimulation can increase PKR levels and induce sensitivity toXRN1inactivation. Lastly,XRN1deletion causes accumulation of endogenous complementary sense/anti-sense RNAs, which may represent candidate PKR ligands. Our data demonstrate how XRN1 regulates PKR and nominate XRN1 as a potential therapeutic target in cancer cells with an activated interferon cell state.
Methods for decoding cortical gradients of functional connectivity
Authors: Peraza Julio A. , Salo Taylor , Riedel Michael C. , Bottenhorn Katherine L. , Poline Jean-Baptiste , Dockès Jérôme , Kent James D. , Bartley Jessica E. , Flannery Jessica S. , Hill-Bowen Lauren D. , Lobo Rosario Pintos , Poudel Ranjita , Ray Kimberly L. , Robinson Jennifer L. , Laird Robert W. , Sutherland Matthew T. , de la Vega Alejandro , Laird Angela R. 
Published: August 2023

AbstractMacroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.
Conductive microgel annealed scaffolds enhance myogenic potential of myoblastic cells
Authors: Casella Alena , Lowen Jeremy , Shimamoto Nathan , Griffin Katherine H. , Filler Andrea C. , Panitch Alyssa , Leach J. Kent 
Published: August 2023

AbstractBioelectricity is an understudied phenomenon to guide tissue homeostasis and regeneration. Conductive biomaterials may capture native or exogenous bioelectric signaling, but incorporation of conductive moieties is limited by cytotoxicity, poor injectability, or insufficient stimulation. Microgel annealed scaffolds are promising as hydrogel-based materials due to their inherent void space that facilitates cell migration and proliferation better than nanoporous bulk hydrogels. We generated conductive microgels from poly(ethylene) glycol and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) to explore the interplay of void volume and conductivity on myogenic differentiation. PEDOT:PSS increased microgel conductivity over 2-fold while maintaining stiffness, annealing strength, and viability of associated myoblastic cells. C2C12 myoblasts exhibited increases in the late-stage differentiation marker myosin heavy chain as a function of both porosity and conductivity. Myogenin, an earlier marker, was influenced only by porosity. Human skeletal muscle derived cells exhibited increasedMyod1, IGF-1, and IGFBP-2 at earlier timepoints on conductive microgel scaffolds compared to non-conductive scaffolds. They also secreted higher levels of VEGF at early timepoints and expressed factors that led to macrophage polarization patterns observed during muscle repair. These data indicate that conductivity aids myogenic differentiation of myogenic cell lines and primary cells, motivating the need for future translational studies to promote muscle repair.
R2ROC: An efficient method of comparing two or more correlated AUC from out-of-sample prediction using polygenic scores
Authors: Momin Md. Moksedul , Wray Naomi R , Lee S. Hong 
Published: August 2023

AbstractPolygenic risk scores (PRSs) enable early prediction of disease risk. Evaluating PRS performance for binary traits commonly relies on the area under the receiver operating characteristic curve (AUC). However, the widely used DeLong’s method for comparative significance tests suffer from limitations, including computational time and the lack of a one-to-one mapping between test statistics based on AUC andR2. To overcome these limitations, we propose a novel approach that leverages the Delta method to derive the variance and covariance of AUC values, enabling a comprehensive and efficient comparative significance test. Our approach offers notable advantages over DeLong’s method, including reduced computation time (up to 150-fold), making it suitable for large-scale analyses and ideal for integration into machine learning frameworks. Furthermore, our method allows for a direct one-to-one mapping between AUC andR2values for comparative significance tests, providing enhanced insights into the relationship between these measures and facilitating their interpretation. We validated our proposed approach through simulations and applied it to real data comparing PRSs for diabetes and coronary artery disease (CAD) prediction in a cohort of 28,880 European individuals. The PRSs were derived using genome-wide association study summary statistics from two distinct sources. Our approach enabled a comprehensive and informative comparison of the PRSs, shedding light on their respective predictive abilities for diabetes and CAD. This advancement contributes to the assessment of genetic risk factors and personalized disease prediction, supporting better healthcare decision-making.
Continuous lifelong learning for modeling of gene regulation from single cell multiome data by leveraging atlas-scale external data
Authors: Yuan Qiuyue , Duren Zhana 
Published: August 2023

AbstractAccurate context-specific Gene Regulatory Networks (GRNs) inference from genomics data is a crucial task in computational biology. However, existing methods face limitations, such as reliance on gene expression data alone, lower resolution from bulk data, and data scarcity for specific cellular systems. Despite recent technological advancements, including single-cell sequencing and the integration of ATAC-seq and RNA-seq data, learning such complex mechanisms from limited independent data points still presents a daunting challenge, impeding GRN inference accuracy. To overcome this challenge, we present LINGER (LIfelong neural Network for GEne Regulation), a novel deep learning-based method to infer GRNs from single-cell multiome data with paired gene expression and chromatin accessibility data from the same cell. LINGER incorporates both 1) atlas-scale external bulk data across diverse cellular contexts and 2) the knowledge of transcription factor (TF) motif matching tocis-regulatory elements as a manifold regularization to address the challenge of limited data and extensive parameter space in GRN inference. Our results demonstrate that LINGER achieves 2-3 fold higher accuracy over existing methods. LINGER reveals a complex regulatory landscape of genome-wide association studies, enabling enhanced interpretation of disease-associated variants and genes. Additionally, following the GRN inference from a reference sc-multiome data, LINGER allows for the estimation of TF activity solely from bulk or single-cell gene expression data, leveraging the abundance of available gene expression data to identify driver regulators from case-control studies. Overall, LINGER provides a comprehensive tool for robust gene regulation inference from genomics data, empowering deeper insights into cellular mechanisms.