bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research trends on acupuncture for neuropathic pain: A bibliometric analysis from 1979 to 2023
Authors: Li Tao , Yan Qilu , Huang Wei 
Published: May 2024

Background:Acupuncture has drawn increasing attention as a complementary and alternative therapy for neuropathic pain (NP). The present study aimed to summarize the current status and research trends on acupuncture for NP over the past several decades.Methods:The publications on acupuncture for NP in the database of Web of Science Core Collection from 1979 to 2023 were searched. VOSviewer (1.6.15) and CiteSpace software (5.5.R2) were applied to identify active authors, journals, countries and institutions, co-cited references and hot keywords.Results:A total of 642 publications were finally included, and the quantitative trend of annual publications on acupuncture for NP have shown overall upward from 1979 to 2023. Peoples R China was the most productive and influential country, while Kyung Hee University from South Korea was both the first in publications and citations. Fang JQ ranked the first productive author and Han JS was the first 1 among the co-cited authors. The first productive journal was Evidence-based Complementary and Alternative Medicine, while the first co-cited journal was Pain. The high-frequency keywords were divided into 9 clusters, and the frontier topic focused on “Chronic pain”.Conclusion:This present study visually showed the research status and trends of acupuncture for NP from 1979 to 2023 on the basis of bibliometric analysis, which may in some way help researcher discovery and explore some new research directions and ideas in the future.
Evaluating the Quality of Postpartum Hemorrhage Nursing Care Plans Generated by Artificial Intelligence Models
Authors: Karacan Emine 
Published: May 2024

Background:
With the rapidly advancing technological landscape of health care, evaluating the potential use of artificial intelligence (AI) models to prepare nursing care plans is of great importance.

Purpose:
The purpose of this study was to evaluate the quality of nursing care plans created by AI for the management of postpartum hemorrhage (PPH).

Methods:
This cross-sectional exploratory study involved creating a scenario for an imaginary patient with PPH. Information was put into 3 AI platforms (GPT-4, LaMDA, Med-PaLM) on consecutive days without prior conversation. Care plans were evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) scale.

Results:
Med-PaLM exhibited superior quality in developing the care plan compared with LaMDA (Z = 4.354; P = .000) and GPT-4 (Z = 3.126; P = .029).

Conclusions:
Our findings suggest that despite the strong performance of Med-PaLM, AI, in its current state, is unsuitable for use with real patients.
An Exploration of Nurses’ Attitudes and Beliefs on Reporting Medication Errors
Authors: Schuermann Andrea A. , Arkin Laura , Loerzel Victoria 
Published: May 2024

Background:Medication errors in health care are prevalent. Nurses play an important role in reporting; however errors remain underreported in incident reporting systems. Understanding the perspective of nurses will inform strategies to improve reporting and build systems to reduce errors.Purpose:The purpose of this study was to explore nurses’ perceptions and attitudes of medication error reporting practices.Methods:This qualitative study used direct content analysis to analyze interview sessions with 21 total nurses.Results:Participant’s description of medication error reporting practices fell into 2 themes. Internal factors described circumstances within nurses themselves that affect reporting. External factors described outside influences from processes or places.Conclusions:Medication error reporting is a multidimensional phenomenon with internal and external factors impacting nurses’ attitudes and willingness to report errors. Nurses need support from leadership to understand that reporting medication errors can improve practice and impact patient outcomes.
Plasmacytoma and Amyloid Lymphadenopathy, FDG, and Fluorocholine
Authors: Kaya Gursan , Akin Serkan , Tuncel Murat , Kiratli Pinar 
Published: May 2024

Abstract
A 56-year-old man with thoracal mass suspected of solitary plasmacytoma was referred for 18F-FDG PET-CT scan. His PET-CT revealed FDG-avid rib mass and cervical lesion at level 2. He also underwent 18F-fluorocholine (FCH) PET-CT to evaluate possible metastatic spread of the disease. FCH PET-CT showed increased uptake at the rib mass, while the cervical lesion was not FCH-avid. Biopsies confirmed rib lesion was a solitary plasmacytoma; however, the cervical lesion was an amyloid deposited lymph node. This case showed FCH PET-CT is a valuable companion of FDG scan for the evaluation of plasma cell dyscrasias with a better specificity.
Radiomics Analysis of Pericoronary Adipose Tissue From Baseline Coronary Computed Tomography Angiography Enables Prediction of Coronary Plaque Progression
Authors: Chen Rui , Li Xiaohu , Jia Han , Feng Changjing , Dong Siting , Liu Wangyan , Lin Shushen , Zhu Xiaomei , Xu Yi , Zhu Yinsu 
Published: May 2024

Purpose:
The relationship between plaque progression and pericoronary adipose tissue (PCAT) radiomics has not been comprehensively evaluated. We aim to predict plaque progression with PCAT radiomics features and evaluate their incremental value over quantitative plaque characteristics.

Patients and Methods:
Between January 2009 and December 2020, 500 patients with suspected or known coronary artery disease who underwent serial coronary computed tomography angiography (CCTA) ≥2 years apart were retrospectively analyzed and randomly stratified into a training and testing data set with a ratio of 7:3. Plaque progression was defined with annual change in plaque burden exceeding the median value in the entire cohort. Quantitative plaque characteristics and PCAT radiomics features were extracted from baseline CCTA. Then we built 3 models including quantitative plaque characteristics (model 1), PCAT radiomics features (model 2), and the combined model (model 3) to compare the prediction performance evaluated by area under the curve.

Results:
The quantitative plaque characteristics of the training set showed the values of noncalcified plaque volume (NCPV), fibrous plaque volume, lesion length, and PCAT attenuation were larger in the plaque progression group than in the nonprogression group (P < 0.05 for all). In multivariable logistic analysis, NCPV and PCAT attenuation were independent predictors of coronary plaque progression. PCAT radiomics exhibited significantly superior prediction over quantitative plaque characteristics both in the training (area under the curve: 0.814 vs 0.615, P < 0.001) and testing (0.736 vs 0.594, P = 0.007) data sets.

Conclusions:
NCPV and PCAT attenuation were independent predictors of coronary plaque progression. PCAT radiomics derived from baseline CCTA achieved significantly better prediction than quantitative plaque characteristics.
Comparison of two audit and feedback approaches: descriptive analysis of personal and contextual dynamics
Authors: Pagano Maria , Cappadona Irene , Corallo Francesco , Cardile Davide , Ielo Augusto , D’Aleo Giangaetano , Cola Maria Cristina De , Bramanti Placido , Ciurleo Rosella 
Published: May 2024

ABSTRACT

Introduction:
Audit and feedback (A&F) is a systematic intervention that can be used to improve the quality of health care. The EASY-NET Network Project proposes an innovative A&F model.

Aim:
This study aimed to describe the newly proposed A&F model. An analysis was conducted, examining the participants’ attitudes and their individual and interpersonal mechanisms to understand how they influence the work context and vice versa.

Methods:
Two A&F models were compared, involving emergency and rehabilitation health workers, who were divided into two groups. The classic A&F model was compared with a new model, using a desk audit followed by interactive feedback. Communication training was provided to the audit team by psychologists before commencement of the project. The experimental group underwent psychological screening using two standardized tools (COPE-NVI and ProQoL) to evaluate personal and relational dynamics using the context-mechanism-outcome (CMO) paradigm.

Results:
The exchange of ideas among health professionals is more effective when using face-to-face feedback than written feedback. The COPE-NVI and ProQoL questionnaires highlighted the difficulties experienced by health care professionals in implementing effective coping strategies to deal with stressful events.

Conclusions:
Identifying signs of stress in health care workers is essential for improvement strategies to be implemented and for establishing new, optimal conditions. Remote feedback makes it possible to overcome logistical barriers and, in the future, this method can be used for inter-organizational collaboration.

Spanish abstract:

http://links.lww.com/IJEBH/A203
Rapid Assessment of Biomarkers on Single Extracellular Vesicles Using ‘Catch and Display’ on Ultrathin Nanoporous Silicon Nitride Membranes
Authors: Walker Samuel N. , Lucas Kilean , Dewey Marley J. , Badylak Stephen , Hussey George , Flax Jonathan , McGrath James L. 
Published: May 2024

ABSTRACTExtracellular vesicles (EVs) are particles secreted by all cells that carry bioactive cargo and facilitate intercellular communication with roles in normal physiology and disease pathogenesis. EVs have tremendous diagnostic and therapeutic potential and accordingly, the EV field has grown exponentially in recent years. Bulk assays lack the sensitivity to detect rare EV subsets relevant to disease, and while single EV analysis techniques remedy this, they are undermined by complicated detection schemes often coupled with prohibitive instrumentation. To address these issues, we propose a microfluidic technique for EV characterization called ‘catch anddisplay forliquidbiopsy (CAD-LB)’. CAD-LB rapidly captures fluorescently labeled EVs in the similarly-sized pores of an ultrathin silicon nitride membrane. Minimally processed sample is introducedviapipette injection into a simple microfluidic device which is directly imaged using fluorescence microscopy for a rapid assessment of EV number and biomarker colocalization. In this work, nanoparticles were first used to define the accuracy and dynamic range for counting and colocalization by CAD-LB. Following this, the same assessments were made for purified EVs and for unpurified EVs in plasma. Biomarker detection was validated using CD9 in which Western blot analysis confirmed that CAD-LB faithfully recapitulated differing expression levels among samples. We further verified that CAD-LB captured the known increase in EV-associated ICAM-1 following the cytokine stimulation of endothelial cells. Finally, to demonstrate CAD-LB’s clinical potential, we show that EV biomarkers indicative of immunotherapy responsiveness are successfully detected in the plasma of bladder cancer patients undergoing immune checkpoint blockade.
Optimal control of combination immunotherapy for a virtual murine cohort in a glioblastoma-immune dynamics model
Authors: Anderson Hannah G. , Takacs Gregory P. , Harrison Jeffrey K. , Rong Libin , Stepien Tracy L. 
Published: May 2024

AbstractThe immune checkpoint inhibitor anti-PD-1, commonly used in cancer immunotherapy, has not been successful as a monotherapy for the highly aggressive brain cancer glioblastoma. However, when used in conjunction with a CC-chemokine receptor-2 (CCR2) antagonist, anti-PD-1 has shown efficacy in preclinical studies. In this paper, we aim to optimize treatment regimens for this combination immunotherapy using optimal control theory. We extend a treatment-free glioblastoma-immune dynamics ODE model to include interventions with anti-PD-1 and the CCR2 antagonist. An optimized regimen increases the survival of an average mouse from 32 days post-tumor implantation without treatment to 111 days with treatment. We scale this approach to a virtual murine cohort to evaluate mortality and quality of life concerns during treatment, and predict survival, tumor recurrence, or death after treatment. A parameter identifiability analysis identifies five parameters suitable for personalizing treatment within the virtual cohort. Sampling from these five practically identifiable parameters for the virtual murine cohort reveals that personalized, optimized regimens enhance survival: 84% of the virtual mice survive to day 100, compared to 60% survival in a previously studied experimental regimen. Subjects with high tumor growth rates and low T cell kill rates are identified as more likely to die during and after treatment due to their compromised immune systems and more aggressive tumors. Notably, the MDSC death rate emerges as a long-term predictor of either disease-free survival or death.HighlightsA mathematical model of glioma-immune dynamics integrates combination immunotherapy.An optimized regimen extends survival in an average virtual mouse by 79 days.Quality of life and survival outcomes were evaluated for a virtual murine cohort.A high death rate of myeloid-derived suppressor cells predicts long-term survival.
Beyond a diagnostic tool: Validating standardized Mahalanobis distance as a species distribution model for invasive alien species in North America
Authors: Stinziano JR , Charron A , Damus M 
Published: May 2024

AbstractSpecies distribution models (SDMs) are useful tools for predicting where new invasive species can establish within a country, supporting both preparatory and response activities. National Plant Protection Organizations use SDMs to inform risk assessment and surveillance activities for emerging plant pests. However, SDMs face multiple and difficult statistical challenges, including multi-collinearity of input variables, correlation structures in climate variables that vary through time and space, limited species observation data, and they often lack formal tests of model performance.We have implemented a previously-reported extrapolation-detection tool as an SDM, rather than a diagnostic tool of SDMs. This method characterizes the observed multivariate climate envelope by using Mahalanobis distance to take advantage of the correlation between climate variables, and identifies areas where the climatic conditions are outside the range of the observed climate envelope. Model outputs include climate suitability maps, and most-important covariate analyses to identify the environmental drivers of the results while assisting in variable reduction. We performed a formal test to assess the ability of the SDM to identify areas invaded by invasive plant pests in North America.Using a list of 23 species from the Canadian Food Inspection Agency’s regulated plant pest list, we demonstrate that this method achieves a high level of accuracy (> 85%) for determining climate suitability for North American plant pest invasions, especially when combined with most-important covariate-guided variable reduction. This suggests that the model is suitable for identifying areas of North America that are susceptible to future invasions. We show that many of the errors occur at the edge of climate suitable areas, where we would expect greater uncertainty in model predictions due to potential over-constraining and geospatial averaging. We present additional analyses to support recommendations on the use and limitations of this SDM in a regulatory context.
Dataset of emerging contaminants in surface water, bottom water, porewater, and sediment: Urban and aquaculture impacts in the central and southern coast of Chile
Authors: Inostroza Pedro A. , Soriano Yolanda , Carmona Eric , Krauss Martin , Brack Werner , Backhaus Thomas , Quiñones Renato A. 
Published: May 2024

AbstractSynthetic organic chemicals, including pesticides, pharmaceuticals, and industrial compounds, pose a growing threat to marine ecosystems as they enter through a variety of pathways, including direct discharges of wastewater (untreated or treated) from industrial, agricultural, and urban sources. Additionally, runoff from residential and agricultural land, as well as inland waterways, transport these chemicals to coastal zones. Despite their potential impact, data on the co-occurrence of these contaminants in the marine environment remains limited. Such information is critical for assessing coastal chemical status, establishing environmental quality benchmarks, and conducting comprehensive environmental risk assessments. In this study, we describe a multifaceted monitoring campaign targeting pesticides, pharmaceuticals, and industrial chemicals along the central-south coast and in northern Patagonia, Chile. Surface water, bottom water, porewater, and adjacent sediment samples were collected for analysis. Our results show the detection of up to 83 chemicals in surface water, 71 in bottom water, 101 in porewater, and 244 in sediments. To enhance data utility, we provide valuable information on the mode of action and molecular targets of the identified chemicals. This comprehensive dataset contributes to defining pollution fingerprints in coastal areas of the Global South, including remote regions in Patagonia. It serves as a critical resource for future research, policymaking, and the advancement of environmental protection in these regions.
Fusarium Protein Toolkit: AI-powered tools to combat fungal threats to agriculture
Authors: Kim Hye-Seon , Haley Olivia C. , Portwood John L. , Harding Stephen , Proctor Robert H. , Woodhouse Margaret R. , Sen Taner Z. , Andorf Carson M. 
Published: May 2024

AbstractBackgroundThe fungal genusFusariumposes significant threats to food security and safety worldwide because it consists of numerous species that cause destructive diseases in crops, as well as mycotoxin contamination. The adverse effects of climate change are exacerbating some existing threats and causing new problems. These challenges highlight the need for innovative solutions, including the development of advanced tools to identify targets to control crop diseases and mycotoxin contamination incited byFusarium.DescriptionIn response to these challenges, we developed the Fusarium Protein Toolkit (FPT,https://fusarium.maizegdb.org/), a web-based tool that allows users to interrogate the structural and variant landscape within theFusariumpan-genome. FPT offers a comprehensive approach to understanding and mitigating the detrimental effects ofFusariumon agriculture. The tool displays both AlphaFold and ESMFold-generated protein structure models from sixFusariumspecies. The structures are accessible through a user-friendly web portal and facilitate comparative analysis, functional annotation inference, and identification of related protein structures. Using a protein language model, FPT predicts the impact of over 270 million coding variants in two of the most agriculturally important species,Fusarium graminearum, which causes Fusarium head blight and trichothecene mycotoxin contamination of cereals, andF. verticillioides, which causes ear rot and fumonisin mycotoxin contamination of maize. To facilitate the assessment of naturally occurring genetic variation, FPT provides variant effect scores for proteins in aFusariumpan-genome constructed from 22 diverse species. The scores indicate potential functional consequences of amino acid substitutions and are displayed as intuitive heatmaps using the PanEffect framework.ConclusionFPT fills a knowledge gap by providing previously unavailable tools to assess structural and missense variation in proteins produced byFusarium, the most agriculturally important group of mycotoxin-producing plant pathogens. FPT will deepen our understanding of pathogenic mechanisms inFusarium, and aid the identification of genetic targets that can be used to develop control strategies that reduce crop diseases and mycotoxin contamination. Such targets are vital to solving the agricultural problems incited byFusarium, particularly evolving threats affected by climate change. By providing a novel approach to interrogateFusarium-induced crop diseases, FPT is a crucial step toward safeguarding food security and safety worldwide.
PlasEval: a framework for comparing and evaluating plasmid detection tools
Authors: Mane Aniket , Sanderson Haley , White Aaron P. , Zaheer Rahat , Beiko Robert G. , Chauve Cedric 
Published: May 2024

AbstractPlasmids play a major role in the transfer of antimicrobial resistance (AMR) genes among bacteria via horizontal gene transfer. The identification of plasmids in short-read assemblies is a challenging problem and a very active research area.Plasmid binningaims at detecting, in a draft genome assembly, groups (bins) of contigs likely to originate from the same plasmid. Several methods for plasmid binning have been developed recently, such as PlasBin-flow, HyAsP, gplas, MOB-suite, and plasmidSPAdes. This motivates the problem of evaluating the performances of plasmid binning methods, either against a given ground truth or between them.We describe PlasEval, a novel method aimed at comparing the results of plasmid binning tools. PlasEval computes a dissimilarity measure between two sets of plasmid bins, that can originate either from two plasmid binning tools, or from a plasmid binning tool and a ground truth set of plasmid bins. The PlasEval dissimilarity accounts for the contig content of plasmid bins, the length of contigs and is repeat-aware. Moreover, the dissimilarity score computed by PlasEval is broken down into several parts, that allows to understand qualitative differences between the compared sets of plasmid bins. We illustrate the use of PlasEval by benchmarking four recently developed plasmid binning tools – PlasBin-flow, HyAsP, gplas, and MOB-recon – on a data set of 54E. colibacterial genomes.PlasEval is freely available athttps://github.com/acme92/PlasEval
Tipping point inα-synuclein–membrane interactions: stable protein-covered vesicles or amyloid aggregation
Authors: Makasewicz Katarzyna , Carlström Göran , Stenström Olof , Bernfur Katja , Fridolf Simon , Akke Mikael , Linse Sara , Sparr Emma 
Published: May 2024

Abstractα-synuclein is a neuronal protein implicated in neurotransmitter release. Its function is thought to critically depend on the dynamic equilibrium between free and membrane-bound protein.α-synuclein amyloid formation implicated in Parkinson’s Disease was also shown to be modulated by lipid membranes. However, it remains elusive whetherα-synuclein-related pathology is due to loss-of-function or gain-of-toxic-function. To help address this question, we studied the coupling of the equilibrium between free and membrane-boundα-synuclein and membrane-induced amyloid formation – phenomena that are usually treated separately. We present a description of the system on a wide range of length scales and timescales for lipid-to-protein ratio conditions where amyloid formation is either accelerated or inhibited by lipid membranes. We find a clear difference between the dynamics and heterogeneity of the protein-covered membrane interface in the two sets of conditions. In aggregation-accelerating conditions, the membrane interface is dynamic and heterogeneous with rapid exchange between free and membrane-bound protein, and disordered protein segments of varying lengths exposed to solution. All these characteristics of the membrane interface are likely to decrease the free energy barrier for amyloid formation. Conversely, the membrane interface is homogeneous and less dynamic in conditions where amyloid formation is inhibited. Importantly, any factors affecting the equilibrium between free and membrane-boundα-synuclein may trigger a change from non-aggregating to aggregating conditions. Altogether, our results highlight a strong coupling of the dynamic equilibrium between the free and membrane-boundα-synuclein and membrane-modulated amyloid formation and thus of the physiological function ofα-synuclein and its aberrant aggregation.