bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of Leading Pedestrian Intervals for Pedestrian Safety in New York City
Authors: Zadey Siddhesh , Roberts Leah E. , Bushover Brady , Gobaud Ariana N. , Mehranbod Christina A. , Fish Carolyn S. , Eschliman Evan L. , Gao Xiang , Goin Dana E. , Morrison Christopher N. 
Published: May 2024

AbstractRoad traffic crashes are a leading cause of morbidity and mortality in large cities. Cities including New York City (NYC) in the United States (US) have implemented a suite of interventions to reduce road traffic crashes. Leading pedestrian intervals (LPIs) are a low-cost physical environmental intervention premised to reduce vehicle-pedestrian crashes by providing pedestrians a head-start over the turning vehicular traffic. Using a spatial ecological panel design, we assessed the impact of LPIs on the risk of total, non-fatal, and fatal pedestrian injuries in NYC from January 2013 to December 2018. For the 36,102 intersection-years studied and 6,017 intersections (2,883 LPI-treated) included in the study, there were 26,033 total injuries of which 291 were fatal. Significant reductions were observed for total (19.4% [95% CI: 11.8%, 26.4%]) and non-fatal injuries (19.6% [11.9%, 26.5%]) but not for fatal injuries. Multiple sensitivity analyses ensured robustness of findings. LPIs may prove to be an effective intervention to improve pedestrian safety outcomes across cities.
Assessing the Knowledge, Attitudes, and Practices (KAP) of Dengue Fever in Thailand: A Systematic Review and Meta-Analysis
Authors: Crowley Julia , Liu Bowen , Jan Hanan 
Published: May 2024

AbstractDengue fever cases are on the rise in Thailand with increases in flooding events. Studies pertaining to public knowledge, attitudes, and practices (KAP) of dengue prevention have frequently been used to better understand the publics’ needs towards dengue. This study conducted a systematic review and meta-analysis of past dengue KAP studies in Thailand. Criteria were developed to determine eligibility, and reviewers independently applied these criteria to identify the 9 eligible studies for the systematic review and the 3 eligible studies for the meta-analysis. Results suggest that the majority of the studies included in the systematic review reported overall low knowledge levels towards dengue prevention in Thailand. This finding was affirmed by the meta-analysis, which concluded that the overall estimate of the proportion of participants with high knowledge of dengue prevention is only 35% (95% CI: 14%-59%). Most of the studies included in the systematic review reported positive attitudes towards dengue prevention, and this finding was also affirmed by the meta-analysis, which concluded that the pooled estimate of the proportion of positive attitudes towards dengue prevention is 61% (95% CI: 43%-77%). Lastly, the majority of studies in the systematic review reported overall poor practices towards dengue prevention. Similarly, the meta-analysis found that the pooled estimate of the proportion of good practices for preventing dengue infection is only 25% (95% CI: 22%-27%).
Exploring and accounting for genetically driven effect heterogeneity in Mendelian Randomization
Authors: Jaitner Annika , Tsaneva-Atanasova Krasimira , Freathy Rachel M. , Bowden Jack 
Published: May 2024

AbstractMendelian randomization uses genetic variants as instrumental variables to estimate the causal effect of a modifiable health exposure or drug target on a downstream outcome. A crucial assumption for accurate estimation of the average causal effect in MR, termed Homogeneity, is that the causal effect does not vary across levels of any instrument used in the analysis. In contrast, the science of pharmacogenetics seeks to actively uncover and exploit genetically driven effect heterogeneity for precision medicine. In this paper we consider a recently proposed method for performing pharmacogenetic analysis on observational data (The Triangulation WIthin a STudy (TWIST) framework), and explore how it can be combined with traditional MR approaches to properly characterise average and causal effects and genetically driven effect heterogeneity. We propose two new methods which not only estimate the genetically driven effect heterogeneity but also enable the estimation of a causal effect in the genetic group with and without the risk allele separately. Both methods utilise homogeneity-respecting and homogeneity-violating genetic variants and rely on a different set of assumptions. Using data from the ALSPAC study, we apply our new method to estimate the causal effect of smoking before and during pregnancy on offspring birth weight in mothers whose genetics mean they find it (relatively) easier or harder to quit.
Epigenetic mechanisms of osteoarthritis risk in human skeletal development
Authors: McDonnell Euan , Orr Sarah E , Barter Matthew J , Rux Danielle , Brumwell Abby , Wrobel Nicola , Murphy Lee , Overmann Lynne M , Sorial Antony K , Young David A , Soul Jamie , Rice Sarah J 
Published: May 2024

AbstractThe epigenome, including the methylation of cytosine bases at CG dinucleotides, is intrinsically linked to transcriptional regulation. The tight regulation of gene expression during skeletal development is essential, with ∼1/500 individuals born with skeletal abnormalities. Furthermore, increasing evidence is emerging to link age-associated complex genetic musculoskeletal diseases, including osteoarthritis (OA), to developmental factors including joint shape. Multiple studies have shown a functional role for DNA methylation in the genetic mechanisms of OA risk using articular cartilage samples taken from aged patients. Despite this, our knowledge of temporal changes to the methylome during human cartilage development has been limited.We quantified DNA methylation at ∼700,000 individual CpGs across the epigenome of developing human articular cartilage in 72 samples ranging from 7-21 post-conception weeks, a time period that includes cavitation of the developing knee joint. We identified significant changes in 8% of all CpGs, and >9400 developmental differentially methylated regions (dDMRs). The largest hypermethylated dDMRs mapped to transcriptional regulators of early skeletal patterning includingMEIS1andIRX1. Conversely, the largest hypomethylated dDMRs mapped to genes encoding extracellular matrix proteins includingSPON2andTNXBand were enriched in chondrocyte enhancers. Significant correlations were identified between the expression of these genes and methylation within the hypomethylated dDMRs. We further identified 811 CpGs at which significant dimorphism was present between the male and female samples, with the majority (68%) being hypermethylated in female samples.Following imputation, we captured the genotype of these samples at >5 million variants and performed epigenome-wide methylation quantitative trait locus (mQTL) analysis. Colocalization analysis identified 26 loci at which genetic variants exhibited shared impacts upon methylation and OA genetic risk. This included loci which have been previously reported to harbour OA-mQTLs (includingGDF5andALDH1A2), yet the majority (73%) were novel (including those mapping toCHST3, FGF1andTEAD1).To our knowledge, this is the first extensive study of DNA methylation across human articular cartilage development. We identify considerable methylomic plasticity within the development of knee cartilage and report active epigenomic mediators of OA risk operating in prenatal joint tissues.
Enhancing Sweat Rate for In-Hospital and Home-Based Decongestive Therapy
Authors: Aronson Doron , Nitzan Yaacov , Petcherski Sirouch , Shaul Aviv , Abraham William T. , Burkhoff Daniel , Ben Gal Tuvia 
Published: May 2024

AbstractBackgroundMany patients admitted for acutely decompensated heart failure (ADHF) are discharged with persistent congestion. Furthermore, the early post-discharge period carries a particularly high risk of readmission and is known as the ‘vulnerable phase’.MethodsWe used a device designed to enhance fluid and salt expulsion via the eccrine sweat glands for decongestion of patients admitted for ADHF. Patients were treated for 1-6 days in the hospital. Following discharge, home therapy continued for 30-60 days at a rate of 1-4 treatments/week. The primary efficacy endpoint for the in-hospital phase was fluid loss of ≥500 mL per ≥4h treatment. Secondary performance endpoints including fluid loss, changes in congestion score, and changes in NT-pro-BNP levels were evaluated for each phase separately.ResultsWe studied 15 patients, 12 completing both the hospital and home phases. During the in-hospital and home phases, median weight change due to device therapy was 2.4 Kg [IQR 2.20–3.77] and 3.1Kg [IQR 7.4–0.6 Kg] respectively, and the primary endpoint was met in 86% of patients. During the home treatment, median weight loss was 3.1 Kg [IQR 7.4–0.6 Kg]. Congestion score declined from 6 [IQR 6 to 7] to 4 [IQR 3–6] during the hospital phase (P=0.0007) and to 1 [IQR 1–1.5] at the end of home therapy (P=0.002). Median NT-proBNP levels decreased from 7732 [IQR 4694– 9746] to 4984 pg/mL [IQR 3559–8950](P=0.01) during the hospital phase and to 3596 ng/mL [IQR 1640–5742](P=0.02) at the end of home therapy. Renal function remained stable.ConclusionThe AquaPass device is useful in enhancing decongestion in hospitalized ADHF patients. Following hospital discharge, device therapy was associated with additional improvement in decongestion without worsening of renal function.
Improving Privacy and Utility in Aggregate Data: A Hybrid Approach
Authors: Kofie Samuel Nartey , Min-Zhang Ivy , Chen Kai , Percy Wei 
Published: May 2024

AbstractThe increasing need to protect individual privacy in data releases has led to significant advancements in privacy-preserving technologies. Differential Privacy (DP) offers robust privacy guarantees but often at the expense of data utility. On the other hand, data pooling, while improving utility, lacks formal privacy assurances. Our study introduces a novel hybrid method, termed PoolDiv, which combines differential privacy with data pooling to enhance both privacy guarantees and data utility. Through extensive simulations and real data analysis, we assess the performance of synthetic datasets generated via traditional DP methods, data pooling, and our proposed PoolDiv method, demonstrating the advantages of our hybrid approach in maintaining data utility while ensuring privacy.
Noncoding de novo mutations inSCN2Aare associated with autism spectrum disorders
Authors: Zhang Yuan , Ahsan Mian Umair , Wang Kai 
Published: May 2024

AbstractCodingde novomutations (DNMs) contribute to the risk for autism spectrum disorders (ASD), but the contribution of noncoding DNMs remains relatively unexplored. Here we use whole genome sequencing (WGS) data of 12,411 individuals (including 3,508 probands and 2,218 unaffected siblings) from 3,357 families collected in Simons Foundation Powering Autism Research for Knowledge (SPARK) to detect DNMs associated with ASD, while examining Simons Simplex Collection (SSC) with 6383 individuals from 2274 families to replicate the results. For coding DNMs,SCN2Areached exome-wide significance (p=2.06×10−11) in SPARK. The 618 known dominant ASD genes as a group are strongly enriched for coding DNMs in cases than sibling controls (fold change=1.51,p=1.13×10−5for SPARK; fold change=1.86,p=2.06×10−9for SSC). For noncoding DNMs, we used two methods to assess statistical significance: a point-based test that analyzes sites with a Combined Annotation Dependent Depletion (CADD) score ≥15, and a segment-based test that analyzes 1kb genomic segments with segment-specific background mutation rates (inferred from expected rare mutations in Gnocchi genome constraint scores). The point-based test identifiedSCN2Aas marginally significant (p=6.12×10−4) in SPARK, yet segment-based test identifiedCSMD1,RBFOX1andCHD13as exome-wide significant. We did not identify significant enrichment of noncoding DNMs (in all 1kb segments or those with Gnocchi>4) in the 618 known ASD genes as a group in cases than sibling controls. When combining evidence from both coding and noncoding DNMs, we found thatSCN2Awith 11 coding and 5 noncoding DNMs exhibited the strongest significance (p=4.15×10−13). In summary, we identified both coding and noncoding DNMs inSCN2Aassociated with ASD, while nominating additional candidates for further examination in future studies.
Single-cell characterization of menstrual fluid at homeostasis and in endometriosis
Authors: Schwalie Petra C. , Bafligil Cemsel , Russeil Julie , Zachara Magda , Biocanin Marjan , Alpern Daniel , Aasna Evelin , Deplancke Bart , Canny Geraldine , Goncalves Angela 
Published: May 2024

AbstractProgress in detecting and understanding endometrial conditions in women of fertile age, such as endometriosis, has been hampered by the invasiveness of the sample collection procedure. Menstrual fluid (MF) can be sampled non-invasively and could provide a unique opportunity to study the physiological state of tissues in the reproductive system. Despite this potential, the use of MF for diagnostics and research has been limited. Here we establish protocols and assess the feasibility of collecting and processing MF in an outpatient setting. We characterize the cellular contents of MF from 15 healthy women using flow cytometry and single-cell RNA-sequencing, and demonstrate the ability to recover millions of live cells from the different cellular fractions of interest (epithelial, stromal, endothelial, perivascular and blood). Through computational integration of MF with endometrial samples we show that MF sampling is a good surrogate for endometrial biopsy. In a proof-of-principle case-control study, we collect MF from a further 7 women with a diagnosis of endometriosis and 11 healthy controls. Through RNA sequencing of 93 MF samples from these women we highlight important differences betweenex vivoand cultured cells, identify impaired decidualisation, low apoptosis, high proliferation, and both higher and lower inflammatory activity in different subsets of immune cells as distinguishing features of endometriosis patients. Finally, we identify potential novel pan-cell-type biomarkers for this neglected condition.
Epigenetic age deviation and mental health in childhood and adolescence: A systematic review and meta-analysis
Authors: Moyakhe L.B. , Dalvie S. , Chalumbila T.C. , Stein D.J. , Koen N. 
Published: May 2024

AbstractBackgroundEpigenetic age acceleration (EAA, i.e., higher EA relative to chronological age) may be linked to adverse mental health outcomes in children. Previously, EAA has been associated with advanced physical maturation and early pubertal development in adolescents. However, research on epigenomic changes and mental health outcomes in children remains limited. This systematic review aimed to investigate the associations between epigenetic age deviation (greater or lower EA age relative to chronological age) and mental health outcomes in childhood.MethodsThis systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Relevant terms were used to search the PubMed, Scopus, and PsychINFO (via Ebsco host) online databases. The search commenced between February and September 2022. Only full-text studies published in English, involving participants under 18 years of age, and examining associations between epigenetic age deviation and child mental health outcomes were eligible for inclusion.Results and conclusionAmong the 4 studies that met the inclusion criteria for this review, 3 studies independently reported significant associations between EAA and internalising behaviour in children and adolescents (aged 4 to 17 years). However, a meta-analysis (OR=1.14, [95% CI, 0.86-1.49]) incorporating a subset of these studies (n=2) did not confirm this finding, though heterogeneity between studies was observed (I2=81%, p=0.022). While the data are not consistent, the findings of this systematic review suggest that EAA holds promise as a potential biomarker for identifying children and adolescents at risk of internalising problems. Given the limited number of studies and the heterogeneity in effect size measures, further work is warranted to explore these preliminary findings.
New dark matter analysis of milky way dwarf satellite galaxies with madhatv2
Authors: Boddy Kimberly K. , Carter Zachary J. , Kumar Jason , Rufino Luis , Sandick Pearl , Tapia-Arellano Natalia 
Published: May 2024

We obtain bounds on dark matter annihilation using 14 years of publicly available Fermi-LAT data from a set of 54 dwarf spheroidal galaxies, using spectral information from 16 energy bins. We perform this analysis using our updated and publicly available code , which can be used to test a variety of models for dark matter particle physics and astrophysics in an accessible manner. In particular, we note that including Carina III in the analysis strengthens constraints on s-wave annihilation into two-body Standard Model final states by a factor of ∼3 but broadens the error on the constraint due to the large uncertainty of its J-factor. Our findings illustrate the importance of verifying if Carina III is in fact a dwarf spheroidal galaxy and measuring more precisely its J-factor. More generally, they highlight the significance of forthcoming discoveries of nearby ultrafaint dwarfs for dark matter indirect detection.

Published by the American Physical Society
2024
Bell Nonlocality in Classical Systems Coexisting with Other System Types
Authors: Chiribella Giulio , Giannelli Lorenzo , Scandolo Carlo Maria 
Published: May 2024

The realistic interpretation of classical theory assumes that every classical system has well-defined properties, which may be unknown to the observer but are nevertheless part of reality and can, in principle, be revealed by measurements. Here we show that this interpretation can, in principle, be falsified if classical systems coexist with other types of physical systems. To make this point, we construct a toy theory that (i) includes classical theory as a subtheory and (ii) allows classical systems to be entangled with another type of system, called anticlassical. We show that our toy theory allows for the violation of Bell inequalities in two-party scenarios where one of the settings corresponds to a local measurement performed on a classical system alone. Building on this fact, we show that measurement outcomes in classical theory cannot, in general, be regarded as predetermined by the state of an underlying reality.

Published by the American Physical Society
2024
Do nonlinear and interactive effects exist in live-streaming sellers’ disclosure of two-sided product information on consumers’ trust and purchase intention?
Authors: Jia Minjiang 
Published: May 2024

PurposeThis study examines the inverted U-shaped relationship between a live-streaming seller’s disclosure of two-sided product information and consumers’ trust in the seller and product. It also explores the interaction between these two types of information disclosure and their impact on purchase intention in the live-streaming sales context.Design/methodology/approachAn e-questionnaire survey was conducted in China, followed by multiple regression and structural equation modeling analyses.FindingsThe disclosure of both negative and positive product information is positively correlated with consumers’ trust in the seller or product but does not directly affect their purchase intention. Negative information disclosure neither enhances nor diminishes the positive impact of disclosing positive information on consumer trust.Practical implicationsLive-streaming sellers (i.e. retailers or manufacturers) should disclose both positive and negative product information to form consumers’ trust toward them (or products) and enhance sales.Social implicationsLive-streaming sellers often worry about the negative effects of excessive promotions or disclosure of positive or negative product information. However, these negative effects were not statistically significant.Originality/valueSince some researchers have found nonlinear effects of two-sided product information in other contexts, this study is the first to focus on the impact of live-streaming sellers’ disclosure of two-sided product information on consumers’ trust in the live-streaming sales context rather than on the information per se.
Do AI-powered digital assistants influence customer emotions, engagement and loyalty? An empirical investigation
Authors: Maduku Daniel K. , Rana Nripendra P. , Mpinganjira Mercy , Thusi Philile , Mkhize Njabulo Happy-Boy , Ledikwe Aobakwe 
Published: May 2024

PurposeDigital voice assistants (DVAs) are revolutionising consumers’ interactions with technology and businesses. Whilst research on the adoption of these devices is rapidly expanding, few have explored post-adoption behaviour. To fill this gap, we investigate how functionality and human-like features shape customers’ emotions, engagement and loyalty towards DVAs.Design/methodology/approachThe data were collected through a self-administered online survey from 509 DVA users. Structural equation modelling was employed for data analysis.FindingsThe results reveal that distinct human-like and functional factors of DVA independently explain customers’ positive emotions and engagement with DVAs. Positive emotions and engagement significantly impact customer loyalty to DVAs. The study shows that localisation of DVAs has a significant positive moderating influence on the service experience-customer engagement relationship but a negative moderating influence on the anthropomorphism-customer engagement relationship.Originality/valueUnlike previous research, this study contributes to the literature by delving into post-adoption phenomena. It explains how DVAs’ human-like and functional attributes drive customers’ positive emotional responses, engagement and loyalty towards DVAs. The findings not only unveil new insights into the moderating role of localisation but also provide a crucial understanding regarding the boundary conditions of the influence of anthropomorphism and service experience on customer engagement.
Enhancing SMEs resilience through digital innovation: a stage-based analysis
Authors: Wang Xueyuan , Sun Meixia 
Published: May 2024

PurposeThe COVID-19 pandemic has profoundly impacted small and medium-sized enterprises (SMEs), inherently vulnerable entities, prompting a pivotal question of how to enhance SMEs’ organizational resilience (OR) to withstand discontinuous crises. Although digital innovation (DI) is widely acknowledged as a critical antecedent to OR, limited studies have analyzed the configurational effects of DI on OR, particularly stage-based analysis.Design/methodology/approachUnderpinned by the dynamic capabilities view, this study introduces a multi-stage dynamic capabilities framework for OR. Employing Latent Dirichlet Allocation (LDA), digital product innovation (DPI), digital services innovation (DSI) and digital process innovation (DCI) are further deconstructed into six dimensions. Furthermore, we utilized fuzzy-set qualitative comparative analysis (fsQCA) to explore the configuration effects of six DI on OR at different stages, using data from 94 Chinese SMEs.FindingsFirst, OR improvement hinges not on a singular DI but on the interactions among various DIs. Second, multiple equivalent configurations emerge at different stages. Before the crisis, absorptive capability primarily advanced through iterative DPI and predictive DSI. During the crisis, response capability is principally augmented by the iterative DPI, distributed DCI, and integrated DCI. After the crisis, recovery capability is predominantly fortified by the iterative DPI, expanded DPI and experiential DSI. Third, iterative DPI consistently assumes a supportive role in fortifying OR.Originality/valueThis study contributes to the extant literature on DI and OR, offering practical guidance for SMEs to systematically enhance OR by configuring DI across distinct stages.