bluuebunny/crossref_metadata_2025_split huggingface dataset:
It’s about time: moving away from statistical analysis of ecotoxicity data
Authors: Jager Tjalling 
Published: January 2025

Abstract
Environmental risk assessment (ERA) of chemicals relies on single-species laboratory testing to establish the toxic properties of a compound. However, ERA is not concerned with toxicity under laboratory conditions: it needs to assess the impacts of the compound in the real world. Data-driven statistical analyses (e.g., hypothesis testing and interpolation) are the common approaches for analyzing toxicity data, but such approaches are the wrong tool for the job at hand. Environmental risk assessment does not need a statistical description of the effects in the toxicity test (at the end of the standardized test duration); it needs to extrapolate from the laboratory test to longer and time-varying exposure. Such extrapolation requires mechanistic process models, providing a simplified representation of the mechanisms underlying toxicity. Any useful model for the toxicity process should explicitly consider both dose (e.g., exposure concentration) and time. In the history of effects analysis for ERA, the factor of time does not get as much attention as the dose, hence the common use of the term “dose-response analysis.” However, this is a historical oversight: time is a crucial factor for understanding toxicity and thereby essential for meaningful extrapolation from laboratory to field. Mechanistic models for ecotoxicity, considering both dose and time, have been around for quite some time and are classified as toxicokinetic-toxicodynamic (TKTD) models. Toxicokinetic-toxicodynamic models are starting to find their way into pesticide ERA in Europe next to the classical statistical approaches. In this opinion paper, I argue that it is about time to leave statistical analysis of toxicity data behind us. Statistics remains important for ERA effects assessment, but its role lies in the definition of appropriate “error models,” explaining the deviations between model output and observations, which is essential for parameter estimation, uncertainty quantification, and error propagation. The “process model,” essential for extrapolation, firmly belongs to TKTD modeling.
Using space technology approach to improve quality in emergency departments in India: a quality improvement program
Authors: Kumar Saravana , Vikneswaran G , Suryavamshi Jitendra , Kumar Srinath , Shaik Manzoor , Reshma GK , Suresh MR , Sigamani Alben , Shanmuganandan VC , Thomas Alexander , Venkatesh AN , Subhan Imron , Rajadurai M , Kailasam Sateesh Kumar , Nivetha B , Shameem KU , Sangtam TSarangpi 
Published: January 2025

Abstract
Introduction
Human errors are a leading cause of disability and death among hospitalized patients. Globally, various strategies have been employed to reduce errors and to improve the quality of patient care. One such novel effort never attempted before is the Health-QUEST (Quality Upgradation Enabled by Space Technology) initiative which aims at translating the best quality and safety practices of the Indian Space Research Organization (ISRO) into the realm of emergency care. The objective of this quality improvement initiative was to understand the performance of ED across India using key performance indicators (KPI) specified in HQ (Health Quest) document, adoptability of HQ based practices in hospitals and their effect on KPI.
Methods
A pre- and post-intervention study design was used where each hospital served as its own control. Preintervention phase captured the time-based key performance indicators based on their existing practice, followed by implementation and training on QUEST recommendations and the post intervention phase assessed any improvement in the KPIs.
Data was collected in real-time using REDCap mobile application by scanning the patient wrist bands. The time based KPIs include Door to triage time, Door to doctor time, Door to needle time, Door to pain assessment time, Door to ordering of investigation time, Time from ordering to first review of investigation, Door to discharge/disposition time.
Results
Seventeen hospitals were invited to participate in this quality improvement initiative, with 14 hospitals completing pilot training for real time data collection. Among them, 10 hospitals participated in the pre and post intervention data collection contributing to 10,332 patients (5296 patients during the pre-intervention and 5036 during the post intervention phase). All the hospitals had a median triage time of less than 5 minutes. Nine out of the ten hospitals recorded a baseline median discharge time of around 2 hours.
The most significant reductions in time (mean difference between pre- and post-intervention) were observed in triage time (11 minutes, p &lt; 0.05), door-to-pain assessment time (23 minutes, p &lt; 0.05), time from ordering to first review of investigation (26 hours, p &lt; 0.05), and disposition time (1 hour and 30 minutes, p &lt; 0.05)
Conclusion
This study evaluated real-time, time-based KPIs in patient management across emergency departments in India. The Health-QUEST program proved to be a straightforward and effective model, achieving significant improvements in multiple time-based KPIs across participating EDs.
Population structure varies among 4 western North American bumble bee species
Authors: Sakulich Elizabeth M , Koch Jonathan B Uhuad , Strange James P 
Published: January 2025

Abstract
Bumble bees (Hymenoptera: Apidae, Bombus Latreille, 1802) are critical pollinators—providing the necessary ecological services for food and crop production. In western North America, species-rich bumble bee communities inhabit mountain ranges. However, as climate change increases temperatures, montane populations are restricted to higher elevations, and their ability to disperse and maintain genetic diversity decreases as suitable habitat connecting populations decreases. This genetic isolation could lead to the extirpation of local pollinator populations and a loss of genetic diversity for pollinator species. We analyzed the genetic diversity of 4 broadly sympatric species of bumble bees with differing elevational niches—Bombus flavifrons, B. melanopygus, B. mixtus, and B. sylvicola—across the Rocky and Cascade Mountains of western North America to assess range-wide population genetic structure. We used microsatellite markers to assess genetic differentiation among populations (FST) and performed Bayesian clustering analyses to identify genetic groups within each study species. Further, we investigated if observed genetic differentiation within study species was better explained by isolation by distance (IBD) or isolation by resistance (IBR) by incorporating habitat suitability models (HSMs) into population structure analyses. Although we expected range-wide genetic differentiation for species with more narrow niche requirements, we found evidence of this differentiation for all 4 study species, with western populations experiencing significant genetic structure relative to inland populations. Additionally, IBR predicted genetic structure better than IBD for B. flavifrons and B. mixtus. Our results suggest that considering habitat connectivity across the geographic range of montane bumble bee species is important for understanding their population structures.
Oral switch antibiotic therapy in uncomplicated Enterococcus faecalis bloodstream infection
Authors: Al Mansi Sarah , Pokalsky Margaret , Turnley Katherine , Freeman Andrew , Bookstaver P Brandon , Kohn Joseph , Winders Hana R , Withers Sarah , Al-Hasan Majdi N 
Published: January 2025

Abstract

Background
The role of oral switch antibiotic therapy in uncomplicated Enterococcus faecalis bloodstream infection (BSI) remains unclear. This retrospective cohort study examines the effectiveness of oral switch compared with standard intravenous antibiotic therapy in uncomplicated E. faecalis BSI.

Methods
Adults with first episodes of uncomplicated monomicrobial E. faecalis BSI were admitted to 10 Prisma Health hospitals in South Carolina from January 2021 to June 2023 were included. Deaths within 7 days were excluded to mitigate immortal time bias. Multivariate Cox proportional hazards regression examined the risk of treatment failure (all-cause mortality or recurrence) within 90 days after adjustment for the propensity of transitioning to oral switch therapy.

Results
Of 476 screened patients, 131 with uncomplicated E. faecalis BSI were included in the analysis. The median age was 70 years, 84 (64%) were men, and 46 (35%) had a urinary source of infection. Eighty-seven patients (66%) received standard intravenous therapy and 44 (34%) were transitioned to oral switch therapy. Aminopenicillins were the most commonly used antibiotics for oral switch therapy (33/44; 75%). There was no increased risk of treatment failure with oral switch therapy compared with standard intravenous therapy (hazard ratio 0.77, 95% CIs 0.23–2.57, P = 0.67). Hospital length of stay (HLOS) was 7 and 11 days in the oral switch and standard intravenous groups, respectively (P &lt; 0.001).

Conclusions
Transitioning patients with uncomplicated E. faecalis BSI from intravenous to oral switch antibiotic therapy appears to be a promising strategy with shorter HLOS and no significant increase in the risk of treatment failure.
Antibiotic resistance in the Middle East and Southern Asia: a systematic review and meta-analysis
Authors: Mathu Rachel , Diago-Navarro Elizabeth , Lynch Emily , Degail Marie-Amélie , Ousley Janet , Kanapathipillai Rupa , Michel Justine , Gastellu-Etchegorry Marc , Malou Nada 
Published: January 2025

Abstract

Introduction
Despite global surveillance efforts, antibiotic resistance (ABR) is difficult to address in low- and middle-income countries (LMICs). In the absence of country-wide ABR surveillance data, peer-reviewed literature is the next most significant source of publicly available ABR data. Médecins Sans Frontières conducted this review in hopes of using the pooled findings to inform treatment choices in the studied countries where sufficient local ABR data are unavailable.

Methods
A systematic literature review reporting ABR rates for six infection sites in nine countries in the Middle East and Southern Asia was conducted. PubMed was used to identify literature published between January 2012 and August 2022. A meta-analysis of the included studies (n = 694) was conducted, of which 224 are reviewed in this paper. The JBI critical appraisal tool was used to evaluate risk of bias for included studies.

Results
This paper focuses on sepsis, burns and wound infections, specifically, with the largest number of papers describing data from Iran, Türkiye and Pakistan. High (&gt;30%) resistance to recommended first-line antibiotics was found. Gram-negative resistance to ceftriaxone, aminoglycosides and carbapenems was high in burn-related infections; colistin resistance among Klebsiella pneumoniae isolates in Pakistan was alarmingly high (81%).

Conclusions
High-quality data on ABR in LMIC settings remain difficult to obtain. While peer-reviewed literature is a source of publicly available ABR data, it is of inconsistent quality; the field also lacks agreed reporting standards, limiting the capacity to pool findings. Nonetheless, high resistance to first-line antibiotics underscores the need for improved localized surveillance and stewardship.
A meta-analysis of genome-wide association studies to identify candidate genes associated with feed efficiency traits in pigs
Authors: Silva Maria Rita Gonçalves da , Veroneze Renata , Marques Daniele B D , Silva Delvan A da , Machado Inaê I , Brito Luiz F , Lopes Paulo S 
Published: January 2025

Abstract
Pig production is an agricultural sector of great economic and social relevance to Brazil and global markets. Feed efficiency traits directly influence the sustainability of pig production due to the economic impact of feed costs on the production system and the environmental footprint of the industry. Therefore, breeding for improved feed efficiency has been a target of worldwide pig breeding programs. Genome-wide association studies (GWAS) enable the assessment of the genetic background of complex traits, which contributes to a better understanding of the biological mechanisms regulating their phenotypic expression. In this context, the primary objective of this study was to identify and validate genomic regions and candidate genes associated with feed conversion ratio (FCR) and residual feed intake (RFI) in pigs based on a comprehensive systematic review and meta-analysis of GWAS. The METAL software was used to implement the meta-analysis and the Bonferroni multiple testing correction considering a significance threshold 0.05. The significant single nucleotide polymorphisms (SNPs) in the meta-analysis were used to identify candidate genes, followed by a functional genomic enrichment analysis. The systematic review identified 13 studies, of which 7 evaluated FCR, 3 evaluated RFI, and 3 studies investigated both traits, with 160 and 96 SNPs identified for FCR and RFI, respectively. After the meta-analysis, 145 markers were significantly associated with FCR and 90 with RFI. The gene annotation process resulted in 105 and 114 genes for FCR and RFI, respectively. The enrichment analysis for FCR resulted in 16 significant gene ontology (GO) terms, while 6 terms were identified for RFI. The main GO terms were actin cytoskeleton (GO_BP:0030036), membrane (GO_CC:0016020), integral components of the peroxisomal membrane (GO_CC:0005779), and carbohydrate-binding (GO_MF:0030246). The main candidate genes identified were MED18, PHACTR4, ABCC2, TRHDE, FRS2, FAR2 and FIS1 for FCR, and ADGRL2, ASGR1, ASGR2, and MAN2B1 for RFI. These findings contribute to a better understanding of the genetic mechanisms associated with feed efficiency traits in pigs, providing a foundation for future improvements in pig breeding programs.
A novel fractional order partial grey model for forecasting short-term traffic flow
Authors: Wang Qiong , Li Chenghang , Zhan Guoping , Zhu Wei 
Published: January 2025

Abstract
Short-term traffic flow forecasting is an integral part of intelligent transportation systems, and a key foundation for traffic departments and travelers to obtain reliable traffic information. This paper constructs a fractional order partial grey model with a sine function control matrix by combining a partial differential equation. The model is capable of predicting short-term traffic flow with spatiotemporal and oscillatory characteristics. In the new model, the introduction of a fractional order accumulation operator may help reduce random fluctuations in data and enhance the flexibility of the model. Moreover, the model dynamically adjusts its parameters using a sine function control matrix, allowing it to better adapt to data with different oscillation types, thereby improving the versatility of the model. Additionally, the characteristic curve method is used to provide the time response function of the model, and the particle swarm optimization algorithm is employed to optimize the model parameters. To demonstrate the validation of the new model, two different road segments from two different highways were selected as research objects. Compared with two other partial grey models and two other algorithm models, the new model has the highest accuracy in simulation and prediction. Furthermore, this new model is applied to the simulation and prediction of the short-term traffic flow, and the results show that the simulated and predicted data have great similarity with the real data trend, which exhibits good reliability and applicability in solving the short-time traffic flow prediction problem.
ODE-DSN: A surrogate model for dynamic stiffness in microscopic RVE problems under nonuniform time-step strain inputs
Authors: Xie Kai , Huo Yongqing , Li Zhongxin , Wu Zhilin 
Published: January 2025

Abstract
In multiscale finite-element methods, solving macroscopic problems typically requires addressing computationally expensive microscopic representative volume element (RVE) problems. To reduce this computational burden, a data-driven approach using artificial neural networks has been employed to pretrain the strain–stress relationship of the microscopic RVE, bypassing the need for full microscale calculations. Existing research has also explored the use of recurrent neural networks to handle history-dependent materials. Building on this approach, this paper introduces a novel ordinary differential equation-dynamic stiffness network model to capture the dynamic stiffness of time-dependent materials and compute stress. The stiffness-based framework enhances the model’s physical consistency and interpretability, while the ordinary differential equation neural network effectively manages nonuniform time sampling in strain inputs. Examples demonstrate that the model accurately learns material behavior with limited data (around 560 random strain–stress sequences) and effectively handles nonuniform time steps. This method addresses the challenge of handling strain inputs with nonuniform time steps while offering potential advantages in computational efficiency and resource utilization.
Understanding screenshot collection and sharing on messaging platforms: a privacy perspective
Authors: Ingber Alexis Shore 
Published: January 2025

Abstract
Individuals rely on messaging platforms to form and maintain intimate relationships, trusting shared information will remain within intended digital confines. However, the screenshot feature allows people to capture and store pieces of private conversations as a separate file on their device, rendering them shareable with third parties. While usage of this feature can be benign, this study focuses on its ability to breach privacy expectations within messaging platforms, termed within communication privacy management theory as privacy turbulence. This study recognizes the power of both interpersonal dynamics and platform affordances in constraining existing norms around screenshot collection and sharing others’ private messages. Experimental results (n = 302) suggest obscuring received messages upon use of the screenshot feature and stating an explicit privacy rule significantly reduce screenshot collection and sharing, respectively. Implications for communication theory and the future of messaging platform design will be discussed.
Bit by bit: colocation and the death of distance in software developer networks
Authors: Goldbeck Moritz 
Published: January 2025

Abstract
Digital work environments potentially facilitate remote collaboration, thereby decreasing geographic friction in knowledge work. I examine spatial collaboration of 190,637 software developers in the USA on the largest coding platform, GitHub. Using a gravity framework that accounts for cluster size, I find that colocated developers collaborate about nine times more frequently than non-colocated developers. This colocation effect is about two to four times smaller than in less digital settings in inventor or social networks. Increased distance beyond colocation has little impact on collaboration. Heterogeneity analyses demonstrate the colocation effect is smaller within large organizations, among experienced developers, and for sporadic interactions. Results suggest geographic proximity is less important for collaboration in digital knowledge work.
The political effects of (mis)perceived immigration
Authors: Barilari Francesco , Bellucci Davide , Conzo Pierluigi , Zotti Roberto 
Published: January 2025

Abstract
Several studies document that exposure to actual immigration affects political outcomes. This article examines, instead, the influence of expected immigration, using data from local elections in Italy. We develop an index of potential exposure to pre-electoral sea arrivals, which varies over time and space depending on immigrants’ nationality. We find that such potential exposure causes a decrease in turnout and an increase in protest votes, shifting valid votes toward extreme-right parties. Support for populist and anti-immigration parties increased in highly exposed municipalities, where voters believed that the new inflow of refugees would increase the local stock of immigrants. However, Twitter data show that these expectations do not reflect actual immigration trends; immigration salience rises mainly during the election period, while most arrivals occur months later. This suggests that, around elections, informal media can bias people’s expectations and, consequently, influence voting behavior.
Precise motif and cross-presentation of coronavirus peptides by feline MHC class I: implications for the mild infection of SARS-CoV-2
Authors: Qiao Peiwen , Yue Can , Peng Weiyu , Liu Kefang , Huo Shuting , Zhang Di , Chai Yan , Qi Jianxun , Sun Zeyu , Gao George F , Wu Guizhen , Liu Jun 
Published: January 2025

Abstract
As one of the earliest identified susceptible animals for the SARS-CoV-2, cats are also the vulnerable hosts for feline coronaviruses, ie feline enteric coronavirus (FECV). Here, to understand the cross-presentation of coronavirus-derived peptides by cat major histocompatibility complex molecule feline leucocyte antigen (FLA) class I, unpredictable natural peptide motifs presented by FLA-K*00701 and FLA-E*00301 were identified through peptide elution and further confirmed by the structural determination of the 2 FLA class I molecules. Based on these precise motifs of FLA class I peptides, the atlas of cross-presenting peptides from different coronaviruses in cats were sketched with 3 hotspots in C-terminal half of ORF1ab protein. The possibility of cross-presentation is further supported by the similar conformation of the corresponding peptides KP-CoV-9 (RSFIEDLLF) and KM-FECV-9 (RSAVEDLLF) from the 2 coronaviruses presented by FLA-K*00701. Our findings provide insights into the understanding of the cross-presentation of peptides from SARS-CoV-2 and feline coronaviruses FECV and the development of universal vaccine for coronaviruses.
Plasmacytoid dendritic cell sensing of African swine fever virus–infected macrophages results in STING-dependent robust interferon-α production
Authors: Sánchez-Carvajal José María , Godel Aurélie , Husson Nolwen , Summerfield Artur , García-Nicolás Obdulio 
Published: January 2025

Abstract
While several African swine fever virus (ASFV)–encoded proteins potently interfere with the cGAS-STING (cyclic GMP-AMP synthetase–stimulator of interferon genes) pathway at different levels to suppress interferon (IFN) type I production in infected macrophages, systemic IFN-α is induced during the early stages of AFSV infection in pigs. The present study elucidates a mechanism by which such responses can be triggered, at least in vitro. We demonstrate that infection of monocyte-derived macrophages (MDMs) by ASFV genotype 2 strains is highly efficient but immunologically silent with respect to IFN type I, IFN-stimulated gene induction, and tumor necrosis factor production. Additionally, ASFV does not directly activate plasmacytoid dendritic cells (pDCs). However, coculturing pDCs with ASFV-infected MDMs results in a strong pDC response characterized by high levels of IFN-α and tumor necrosis factor. IFN type I, in turn, promoted interleukin-1 receptor antagonist production by macrophages. Similar to the sensing of infected cells by other viruses, pDC activation required integrin-mediated cognate interactions with ASFV-infected MDMs to form an interferogenic synapse. Inhibitor studies indicated that the activation of pDCs requires the STING pathway and the formation of gap junctions. While IL-4–polarized macrophages showed increased susceptibility, IFN-γ–polarized ASFV-infected macrophages induced higher pDC activation. Pretreatment of pDCs with IFN-β and IFN-γ also enhanced IFN-α production in response to ASFV-infected macrophages, highlighting the influence of the immunological microenvironment. These findings suggest that the IFN-α detected during ASFV infection in pigs may be a result of pDC sensing ASFV-infected macrophages.