bluuebunny/crossref_metadata_2025_split huggingface dataset:
Read or skip privacy policies when installing apps on wearable devices: the roles of perceived necessity and threat clues
Authors: Pan Yu , Ruan Yiyin , Chang Mengyi , Lyu Dong , Li Yuhao 
Published: May 2024

AbstractWearable devices are increasingly integral to our daily lives but raise significant concerns about the security of personal data. In contrast, users often skip reading privacy policies when installing apps on wearable devices. This gap between the concerns and behaviors has spurred disputes regarding business ethics between app providers and users when private information is leaked. While much research has explored the reasons underlying users’ skipping behaviors on mobile phones or tablets, there has been limited attention given to wearable devices despite their prevalence. Unlike mobile phones or tablets, wearable devices often have limited capabilities, necessitating users to install essential apps and perceive a strong sense of necessity. This research, using both eye tracking and self-report methods, investigates how this perceived necessity affects users’ attention to privacy policies on wearable devices during app installations and how it interacts with the presence of threat clues – a key factor that influences behaviors toward privacy policies. In Study 1, eye tracking technology is applied to observe the variation in users’ attention toward privacy policies. Results indicate that when users perceive a high (vs. low) necessity for an app, they pay less attention to its privacy policy. This effect is amplified when there are strong threat clues present. In Study 2, based on the process-dissociation procedure (PDP), the cognitive mechanisms underlying user reading behavior are uncovered. The findings show that users with high perceived necessity are less inclined to engage in analytical processing when reading privacy policies, and this tendency is further strengthened by strong threat clues. This research supplements the existing literature on users’ behaviors toward privacy policies on wearable devices, and it also provides practical insights for prompting users to pay more attention to privacy policies and enjoy a secure digital experience.
The susceptibility of rare and threatened NSW species to the root-rot pathogen Phytophthora cinnamomi: 2. The identification of species requiring protection or further research
Authors: McDougall Keith L. , Liew Edward C. Y. 
Published: May 2024

Context The response of most native plant species in New South Wales (NSW) to infection by the oomycete pathogen Phytophthora cinnamomi Rands is unknown, which makes decisions about disease management difficult. Aims We aim to improve knowledge about the potential threat from P. cinnamomi by testing a further 32 threatened species for their response to the pathogen and developing a method for prioritising management and susceptibility testing. Methods Susceptibility to infection and host response were evaluated in glasshouse experiments where the pathogen was introduced to pots containing the threatened species, and the results were compared with control uninoculated pots. Our prioritisation used modelled habitat suitability for P. cinnamomi, proximity to known P. cinnamomi occurrences, and numbers of plant species populations at least 1 km apart to rank 928 rare and threatened plant species native to NSW for either management or susceptibility testing. Key results Phytophthora cinnamomi was re-isolated from the roots of 10 of the 32 species assessed, most of which also showed significant mortality or disease symptoms. Darwinia peduncularis B.G.Briggs, Hibbertia circinata K.L.McDougall & G.T.Wright, Isopogon fletcheri F.Muell., Phebalium speciosum I.Telford, Pultenaea baeuerlenii F.Muell. and Pultenaea parrisiae J.D.Briggs & Crisp were the most severely affected species. The effect of P. cinnamomi is known for only 63 rare and threatened species in NSW. The Greater Sydney region is a hotspot for rare and threatened plant species with a high priority for susceptibility testing. Conclusions The prognosis in the wild for rare and threatened plant species affected by P. cinnamomi depends on (1) habitat suitability for the pathogen, with subalpine and arid-zone species unlikely to be affected, (2) the number of unaffected populations, with two severely affected species that occur only on infested sites (Hibbertia circinata and Prostanthera marifolia R.Br.) facing extinction in the near future and (3) climate, with some species (e.g. Pomaderris delicata N.G.Walsh & Coates) apparently affected only in unusually wet years. Further susceptibility testing of rare and threatened species is required. This should be supported by taxonomic studies of genera (e.g. Hibbertia, Pultenaea) commonly affected by the pathogen. Implications Many more plant species in NSW are likely to be severely affected by P. cinnamomi than currently known, and may require active management of the disease for their long-term survival.
Childhood adversity and time to pregnancy in a preconception cohort
Authors: Lovett Sharonda M , Orta Olivia R , Boynton-Jarrett Renée , Wesselink Amelia K , Ncube Collette N , Nillni Yael I , Hatch Elizabeth E , Wise Lauren A 
Published: May 2024

Abstract
We examined the association between childhood adversity and fecundability (the per-cycle probability of conception), and the extent to which childhood social support modified this association. We used data from 6318 female participants aged 21-45 years in Pregnancy Study Online (PRESTO), a North American prospective preconception cohort study (2013-2022). Participants completed a baseline questionnaire, bimonthly follow-up questionnaires (until pregnancy or a censoring event), and a supplemental questionnaire on experiences across the life course including adverse childhood experiences (ACEs) and social support (using the modified Berkman-Syme Social Network Index [SNI]). We used proportional probabilities regression models to compute fecundability ratios (FRs) and 95% CIs, adjusting for potential confounders and precision variables. Adjusted FRs for ACE scores 1-3 and ≥4 vs 0 were 0.91 (95% CI, 0.85-0.97) and 0.84 (95% CI, 0.77-0.91), respectively. The FRs for ACE scores ≥4 vs 0 were 0.86 (95% CI, 0.78-0.94) among participants reporting high childhood social support (SNI ≥4) and 0.78 (95% CI, 0.56-1.07) among participants reporting low childhood social support (SNI &lt;4). Our findings confirm results from 2 previous studies and indicate that high childhood social support slightly buffered the effects of childhood adversity on fecundability.
Clinical Effect of Dermatologic Trephination Combined With Radiotherapy in the Treatment of Keloids
Authors: Chen Liang , Qin Xiao Ming , Wang Lin Qi , Wang Qiu Yu , Yang Kong Chao 
Published: May 2024

Abstract

Background
Keloids are excessive formations of scar tissue that develop at the site of a skin injury. Due to their invasive nature, they have a negative impact on the skin's appearance and are prone to recurrence, making them a challenging condition to treat with regard to skin aesthetics.

Objectives
The objective of this article was to compare the long-term effects of dermatologic trephination with nonsurgical treatments for scars and evaluate the clinical value of the treatments.

Methods
A retrospective analysis was conducted of 48 patients who received keloid treatment in the Department of Dermatology and Department of Thoracic Surgery at our hospital from January 2021 to October 2023. Twenty-four patients received dermatologic trephination, and 24 patients received nonsurgical treatment. Outcome measures included scar appearance, scar healing time, pain and itching levels, and patient satisfaction.

Results
The healing time of patients receiving dermatologic trephination was significantly shorter than that of patients in the nonsurgical group. The degree of itching in patients undergoing dermatologic trephination was significantly lower than that of patients in the nonsurgical group. The satisfaction of patients who received dermatologic trephination was significantly higher than that of patients in the nonsurgical group.

Conclusions
In this study we demonstrated that trephination achieves better long-term results in keloid revision, including improved keloid appearance, itching symptoms, and patient satisfaction.

Level of Evidence: 3
RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data
Authors: Singh Sandeep , Shi Xinrui , Haddox Samuel , Elfman Justin , Ahmad Syed Basil , Lynch Sarah , Manley Tommy , Piczak Claire , Phung Christopher , Sun Yunan , Sharma Aadi , Li Hui 
Published: May 2024

Abstract
Read-through chimeric RNAs are being recognized as a means to expand the functional transcriptome and contribute to cancer tumorigenesis when mis-regulated. However, current software tools often fail to predict them. We have developed RTCpredictor, utilizing a fast ripgrep tool to search for all possible exon-exon combinations of parental gene pairs. We also added exonic variants allowing searches containing common SNPs. To our knowledge, it is the first read-through chimeric RNA specific prediction method that also provides breakpoint coordinates. Compared with 10 other popular tools, RTCpredictor achieved high sensitivity on a simulated and three real datasets. In addition, RTCpredictor has less memory requirements and faster execution time, making it ideal for applying on large datasets.
Using deep learning and large protein language models to predict protein–membrane interfaces of peripheral membrane proteins
Authors: Paranou Dimitra , Chatzigoulas Alexios , Cournia Zoe 
Published: May 2024

Abstract

Motivation
Characterizing interactions at the protein–membrane interface is crucial as abnormal peripheral protein–membrane attachment is involved in the onset of many diseases. However, a limiting factor in studying and understanding protein–membrane interactions is that the membrane-binding domains of peripheral membrane proteins (PMPs) are typically unknown. By applying artificial intelligence techniques in the context of natural language processing (NLP), the accuracy and prediction time for protein–membrane interface analysis can be significantly improved compared to existing methods. Here, we assess whether NLP and protein language models (pLMs) can be used to predict membrane-interacting amino acids for PMPs.

Results
We utilize available experimental data and generate protein embeddings from two pLMs (ProtTrans and ESM) to train classifier models. Overall, the results demonstrate the first proof of concept study and the promising potential of using deep learning and pLMs to predict protein–membrane interfaces for PMPs faster, with similar accuracy, and without the need for 3D structural data compared to existing tools.

Availability and implementation
The code is available at https://github.com/zoecournia/pLM-PMI. All data are available in the Supplementary material.
Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation
Authors: Duan Ziheng , Riffle Dylan , Li Ren , Liu Junhao , Min Martin Renqiang , Zhang Jing 
Published: May 2024

Abstract

Motivation
Recent advances in spatial transcriptomics allow spatially resolved gene expression measurements with cellular or even sub-cellular resolution, directly characterizing the complex spatiotemporal gene expression landscape and cell-to-cell interactions in their native microenvironments. Due to technology limitations, most spatial transcriptomic technologies still yield incomplete expression measurements with excessive missing values. Therefore, gene imputation is critical to filling in missing data, enhancing resolution, and improving overall interpretability. However, existing methods either require additional matched single-cell RNA-seq data, which is rarely available, or ignore spatial proximity or expression similarity information.

Results
To address these issues, we introduce Impeller, a path-based heterogeneous graph learning method for spatial transcriptomic data imputation. Impeller has two unique characteristics distinct from existing approaches. First, it builds a heterogeneous graph with two types of edges representing spatial proximity and expression similarity. Therefore, Impeller can simultaneously model smooth gene expression changes across spatial dimensions and capture similar gene expression signatures of faraway cells from the same type. Moreover, Impeller incorporates both short- and long-range cell-to-cell interactions (e.g. via paracrine and endocrine) by stacking multiple GNN layers. We use a learnable path operator in Impeller to avoid the over-smoothing issue of the traditional Laplacian matrices. Extensive experiments on diverse datasets from three popular platforms and two species demonstrate the superiority of Impeller over various state-of-the-art imputation methods.

Availability and implementation
The code and preprocessed data used in this study are available at https://github.com/aicb-ZhangLabs/Impeller and https://zenodo.org/records/11212604.
SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models
Authors: Gjoni Ketrin , Pollard Katherine S 
Published: May 2024

Abstract

Summary
The increasing development of sequence-based machine learning models has raised the demand for manipulating sequences for this application. However, existing approaches to edit and evaluate genome sequences using models have limitations, such as incompatibility with structural variants, challenges in identifying responsible sequence perturbations, and the need for vcf file inputs and phased data. To address these bottlenecks, we present Sequence Mutator for Predictive Models (SuPreMo), a scalable and comprehensive tool for performing and supporting in silico mutagenesis experiments. We then demonstrate how pairs of reference and perturbed sequences can be used with machine learning models to prioritize pathogenic variants or discover new functional sequences.

Availability and implementation
SuPreMo was written in Python, and can be run using only one line of code to generate both sequences and 3D genome disruption scores. The codebase, instructions for installation and use, and tutorials are on the GitHub page: https://github.com/ketringjoni/SuPreMo.
Digital Technology in Children’s Safeguarding Social Work Practice in the 21st Century: A Scoping Review
Authors: Behan-Devlin Josh 
Published: May 2024

Abstract
Digital technology plays an increasing role in children’s safeguarding social work practice, where there is a renewed emphasis on the recording and interpretation of data via digital technology, as well as the use of technology to communicate with families and colleagues, particularly since Covid-19. This scoping review delineated extant research investigating uses of digital technology in children’s safeguarding social work practice since 2000 in order to contextualise current emerging practices. The methodology used accounted for the heterogeneity of study designs whilst maintaining a rigorous approach to searching, selection and analysis. Literature searches were conducted in August and September 2022 identifying forty-three studies. Descriptive quantitative and qualitative analyses were undertaken to outline date, location, methodology, aspect of technology investigated, and key findings of included studies. The review generated two descriptive categories which reflect the included studies: electronic information systems and digital communications. These categories subsume a range of distinct platforms and applications whilst highlighting a tendency of the included studies to separate out their focus between these specific aspects of digital technology, with limited discourse between categories. Families’ perspectives are also missing from most research identified in the review.
Embedding Learning as a Practice of Value: Learning from the Experiences of Early Career Social Workers in Scotland
Authors: McCulloch Trish , Grant Scott , Daly Maura , Sen Robin , Ferguson Gillian 
Published: May 2024

Abstract
Across the Global North, professional learning for social workers has become a matter of concern. Efforts to ‘fix’ the problem have focused narrowly on formal methods of learning and show limited connect with recent research. In this article, we report on findings from a mixed-method longitudinal cohort study, which examined early career social workers experiences of learning over the first five years of professional practice. Drawing on a repeat-measure annual online survey, our findings provide an inside-view of how early career social workers in Scotland experience work-based learning over time and how professional learning for social workers can be enhanced. Quantitative and qualitative data were analysed using descriptive statistical analysis and reflexive thematic analysis respectively and integrated using a convergence coding matrix to identify meta-themes. Our findings support an integrative, developmental and ecological approach to professional learning, embedded in a value-led understanding of social work as practice. We invite the profession to embrace and embed learning as a ‘practice of value’, both as an antidote to managerial approaches to practice and learning and as a way of valuing the extraordinary work that social workers do.
Spatiotemporal variation in ecophysiological traits align with high resolution niche modelling in the short-range banded ironstone endemicAluta quadrata
Authors: Lewandrowski Wolfgang , Tudor Emily P , Ajduk Hayden , Tomlinson Sean , Stevens Jason C 
Published: May 2024

AbstractDefining plant ecophysiological responses across natural distributions enables a greater understanding of the niche that plants occupy. Much of the foundational knowledge of species’ ecology and responses to environmental change across their distribution is often lacking, particularly for rare and threatened species, exacerbating management and conservation challenges. Combining high-resolution species distribution models (SDMs) with ecophysiological monitoring characterized the spatiotemporal variation in both plant traits and their interactions with their surrounding environment for the range-restricted Aluta quadrata Rye & Trudgen, and a common, co-occurring generalist, Eremophila latrobei subsp. glabra (L.S.Sm.) Chinnock., from the semi-arid Pilbara and Gascoyne region in northwest Western Australia. The plants reflected differences in gas exchange, plant health and plant water relations at sites with contrasting suitability from the SDM, with higher performance measured in the SDM-predicted high-suitability site. Seasonal differences demonstrated the highest variation across ecophysiological traits in both species, with higher performance in the austral wet season across all levels of habitat suitability. The results of this study allow us to effectively describe how plant performance in A. quadrata is distributed across the landscape in contrast to a common, widespread co-occurring species and demonstrate a level of confidence in the habitat suitability modelling derived from the SDM in predicting plant function determined through intensive ecophysiology monitoring programmes. In addition, the findings also provide a baseline approach for future conservation actions, as well as to explore the mechanisms underpinning the short-range endemism arid zone systems.
Computational simulation model of transcatheter edge-to-edge mitral valve repair: a proof-of-concept study
Authors: Messika-Zeitoun David , Mousavi Jamal , Pourmoazen Mohammad , Cotte Florian , Dreyfus Julien , Nejjari Mohammed , Attias David , Kloeckner Martin , Ghostine Said , Pierrard Romain , Eker Armand , Levy Franck , Le Dolley Yvan , Houel Remi , Unni Rudy R , Burwash Ian G , Dryden Adam , Hynes Mark , Nicholson Donna , Labinaz Marino , Chan Vincent , Albertini Jean-Noel , Mesana Thierry 
Published: May 2024

Abstract

Aims
As transcatheter mitral valve (MV) interventions are expanding and more device types and sizes become available, a tool supporting operators in pre-procedural planning and the clinical decision-making process is highly desirable. We sought to develop a finite element computational simulation model to predict the results of transcatheter edge-to-edge repair (TEER) interventions.

Methods and results
We prospectively enrolled patients with secondary mitral regurgitation (MR) referred for a clinically indicated TEER. The 3D trans-oesophageal echocardiograms performed at the beginning of the procedure were used to perform the simulation. On the 3D dynamic model of the MV that was first obtained, we simulated the clip implantation using the same clip type, size, number, and implantation location that was used during the intervention. The 3D model of the MV obtained after the simulation of the clip implantation was compared with the clinical results obtained at the end of the intervention. We analysed the degree and location of residual MR and the shape and area of the diastolic MV area. We performed computational simulation on five patients. Overall, the simulated models predicted well the degree and location of the residual regurgitant orifice(s) but tended to underestimate the diastolic mitral orifice area.

Conclusion
In this proof-of-concept study, we present preliminary results on our algorithm simulating clip implantation in five patients with functional MR. We show promising results regarding the feasibility and accuracy in terms of predicting residual MR and the need to improve the estimation of the diastolic MV area.
Bacterial hosts of clinically significant beta-lactamase genes in Croatian wastewaters
Authors: Dekić Rozman Svjetlana , Puljko Ana , Karkman Antti , Virta Marko , Udiković-Kolić Nikolina 
Published: May 2024

Abstract
Wastewater treatment plants (WWTPs) provide a suitable environment for the interaction of antibiotic resistant bacteria and antibiotic-resistance genes (ARGs) from human, animal, and environmental sources. The aim was to study the influent and effluent of two WWTPs in Croatia to identify bacterial hosts of clinically important beta-lactamase genes (blaTEM, blaVIM, blaOXA-48-like) and observe how their composition changes during the treatment process. A culture-independent epicPCR (Emulsion, Paired isolation and Concatenation Polymerase Chain Reaction) was used to identify the ARG hosts, and 16S rRNA amplicon sequencing to study the entire bacterial community. Different wastewater sources contributed to the significant differences in bacterial composition of the wastewater between the two WWTPs studied. A total of 167 genera were detected by epicPCR, with the Arcobacter genus, in which all ARGs studied were present, dominating in both WWTPs. In addition, the clinically important genera Acinetobacter and Aeromonas contained all ARGs examined. The blaOXA-48-like gene had the highest number of hosts, followed by blaVIM, while blaTEM had the narrowest host range. Based on 16S rRNA gene sequencing, ARG hosts were detected in both abundant and rare taxa. The number of hosts carrying investigated ARGs was reduced by wastewater treatment. EpicPCR provided valuable insights into the bacterial hosts of horizontally transmissible beta-lactamase genes in Croatian wastewater.