bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of ZnO nanoparticles on biofilm formation and gene expression of the toxin-antitoxin system in clinical isolates of Pseudomonas aeruginosa
Authors: Valadbeigi Hassan , Sadeghifard Nourkhoda , Kaviar Vahab Hassan , Haddadi Mohammad Hossein , Ghafourian Sobhan , Maleki Abbas 
Published: October 2023

Abstract
Background
Biofilm formation by Pseudomonas aeruginosa (P. aeruginosa) is known to be characteristic of this organism. This bacterium is considered one of the most life-threatening bacteria and has been identified as a priority pathogen for research by WHO. Biofilm-producing P. aeruginosa is a concern in many parts of the world due to antibiotic resistance. Alginate also plays an important role in the biofilm formation of P. aeruginosa as well as the emergence of antibiotic resistance in biofilms. In addition, the systems of toxin-antitoxin( TA) play an important role in biofilm formation. Metal nanoparticle(NP) such as zinc oxide (ZnO) also have extensive biological properties, especially anti-biofilm properties. Therefore, this study was conducted in relation to the importance of zinc oxide nanoparticles (ZnO NPs) in biofilm formation and also the correlation of gene expression of TA systems in clinical isolates of P. aeruginosa.

Methods
A total of 52 P. aeruginosa isolates were collected from burns (n = 15), UTI (n = 31), and trachea (n = 6) in hospitals in Ilam between May 2020 and October 2020. Biofilm formation was assessed using a microtiter plate assay. MIC and sub-MIC concentrations of ZnO NPs (10–30 nm with purity greater than 99.8%) in P. aeruginosa were determined. Subsequently, biofilm formation was investigated using sub-MIC concentrations of ZnO NPs. Finally, total RNA was extracted and RT- qPCR was used to determine the expression levels of genes of mazEF, mqsRA, and higBA of TA systems.

Results
Six isolates of P. aeruginosa were found to form strong biofilms. The results showed that ZnO NPs were able to inhibit biofilm formation. In our experiments, we found that the sub-MIC concentration of ZnO NPs increased the gene expression of antitoxins mazE and mqsA and toxin higB of TA systems treated with ZnO NPs.

Conclusions
In the present study, ZnO NPs were shown to effectively inhibit biofilm formation in P. aeruginosa. Our results support the relationship between TA systems and ZnO NPs in biofilm formation in P. aeruginosa. Importantly, the expression of antitoxins mazE and mqsA was high after treatment with ZnO NPs, but not that of antitoxin higA.
Naloxone prescriptions among patients with a substance use disorder and a positive fentanyl urine drug screen presenting to the emergency department
Authors: Ali Shawkut Amaan , Shell Jasmine , Harris Raymond , Bedder Marshall 
Published: October 2023

Abstract
Background
Over 109,000 people in the USA died from a drug overdose in 2022. More alarming is the amount of drug overdose deaths involving synthetic opioids other than methadone (SOOM), primarily fentanyl. From 2015 to 2020, the number of drug overdose deaths from SOOM increased 5.9-fold. SOOM are commonly being found in many other drugs without the user's knowledge. Given the alarming number of overdose deaths from illicit drugs with SOOM, naloxone should be prescribed for all persons using illicit drugs regardless of if they knowingly use opioids. How often providers prescribe naloxone for these patients remains unknown.
The aim of this study is to determine the rate of naloxone prescriptions given to patients with any substance use disorder, including when the patient has a urine drug screen positive for fentanyl. Secondary aims include determining what patient factors are associated with receiving a naloxone prescription.

Methods
The design was a single-center retrospective cohort study on patients that presented to the Augusta University Medical Center emergency department between 2019 through 2021 and had an ICD-10 diagnosis of a substance use disorder. Analyses were conducted by logistic regression and t-test or Welch’s t-test.

Results
A total of 10,510 emergency department visits were by 6787 patients. Naloxone was prescribed in 16.3% of visits with an opioid-related discharge diagnosis and 8.4% of visits with a non-opioid substance use-related discharge diagnosis and a urine drug screen positive for fentanyl. Patients with a fentanyl positive urine drug screen had higher odds of receiving a naloxone prescription (aOR 5.80, 95% CI 2.76–12.20, p < 0.001). Patients with a psychiatric diagnosis had lower odds of being prescribed naloxone (aOR 0.51, p = 0.03). Patients who received naloxone had a lower number of visits (mean 1.23 vs. 1.55, p < 0.001). Patients with a urine drug screen positive for cocaine had higher odds of frequent visits (aOR 3.07, p = 0.01).

Conclusions
Findings should remind providers to prescribe naloxone to all patients with a substance use disorder, especially those with a positive fentanyl urine drug screen or a co-occurring psychiatric condition. Results also show that cocaine use continues to increase healthcare utilization.
L-Fucose promotes enteric nervous system regeneration in type 1 diabetic mice by inhibiting SMAD2 signaling pathway in enteric neural precursor cells
Authors: Yao Hailing , Shi Huiying , Jiang Chen , Fan Mengke , Zhang Yurui , Qian Wei , Lin Rong 
Published: October 2023

Abstract
Background
Diabetes can lead to extensive damage to the enteric nervous system (ENS), causing gastrointestinal motility disorders. However, there is currently a lack of effective treatments for diabetes-induced ENS damage. Enteric neural precursor cells (ENPCs) closely regulate the structural and functional integrity of the ENS. L-Fucose, is a dietary sugar that has been showed to effectively ameliorate central nervous system injuries, but its potential for ameliorating ENS damage and the involvement of ENPCs in this process remains uncertain.

Methods
Genetically engineered mice were generated for lineage tracing of ENPCs in vivo. Using diabetic mice in vivo and high glucose-treated primary ENPCs in vitro, the effects of L-Fucose on the injured ENS and ENPCs was evaluated by assessing gastrointestinal motility, ENS structure, and the differentiation of ENPCs. The key signaling pathways in regulating neurogenesis and neural precursor cells properties, transforming growth factor-β (TGF-β) and its downstream signaling pathways were further examined to clarify the potential mechanism of L-Fucose on the injured ENS and ENPCs.

Results
L-Fucose improved gastrointestinal motility in diabetic mice, including increased defecation frequency (p < 0.05), reduced total gastrointestinal transmission time (p < 0.001) and bead expulsion time (p < 0.05), as well as enhanced spontaneous contractility and electric field stimulation-induced contraction response in isolated colonic muscle strips (p < 0.001). The decrease in the number of neurons and glial cells in the ENS of diabetic mice were reversed by L-Fucose treatment. More importantly, L-Fucose treatment significantly promoted the proportion of ENPCs differentiated into neurons and glial cells both in vitro and in vivo, accompanied by inhibiting SMAD2 phosphorylation.

Conclusions
L-Fucose could promote neurogenesis and gliogenesis derived from ENPCs by inhibiting the SMAD2 signaling, thus facilitating ENS regeneration and gastrointestinal motility recovery in type 1 diabetic mice.
Antibody against apolipoprotein-A1, non-alcoholic fatty liver disease and cardiovascular risk: a translational study
Authors: Pagano Sabrina , Bakker Stephan J. L. , Juillard Catherine , Vossio Stefania , Moreau Dimitri , Brandt Karim J. , Mach François , Dullaart Robin P. F. , Vuilleumier Nicolas 
Published: October 2023

Abstract
Background
Non-alcoholic fatty liver disease (NAFLD) is a common liver disease increasing cardiovascular disease (CVD) morbidity and mortality. Autoantibodies against apolipoprotein A-1 (AAA-1) are a possible novel CVD risk factor promoting inflammation and disrupting cellular lipid homeostasis, two prominent pathogenic features of NAFLD. We explored the role of AAA-1 in NAFLD and their association with CVD risk.

Methods
HepaRG cells and liver sections from ApoE−/− mice exposed to AAA-1 were used for lipid quantification and conditional protein expression. Randomly selected sera from 312 subjects of the Prevention of Renal and Vascular End-stage Disease (PREVEND) general population cohort were used to measure AAA-1. A Fatty Liver Index (FLI) ≥ 60 and a 10-year Framingham Risk Score (FRS) ≥ 20% were used as proxy of NAFLD and high CVD risk, respectively.

Results
In-vitro and mouse models showed that AAA-1 increased triglyceride synthesis leading to steatosis, and promoted inflammation and hepatocyte injury. In the 112 PREVEND participants with FLI ≥ 60, AAA-1 were associated with higher FRS, alkaline phosphatase levels, lower HDL cholesterol and tended to display higher FLI values. Univariate linear and logistic regression analyses (LRA) confirmed significant associations between AAA-1, FLI and FRS ≥ 20%, while in adjusted LRA, FLI was the sole independent predictor of FRS ≥ 20% (OR: 1.05, 95%CI 1.01–1.09, P = 0.003). AAA-1 was not an independent FLI predictor.

Conclusions
AAA-1 induce a NAFLD-compatible phenotype in vitro and in mice. Intricate associations exist between AAA-1, CVD risk and FLI in the general population. Further work is required to refine the role of AAA-1 in NAFLD and to determine if the AAA-1 association with CVD is affected by hepatic steatosis.
Association between triglyceride glucose index and severity of diabetic foot ulcers in type 2 diabetes mellitus
Authors: Chen Weihao , Wang Xuedong , Jiang Qilin , Wu Jiyan , Shi Wanyan , Wang Xiaoxiao , Yin Yihu , Zheng Jiayin , Hu Xiang , Lin Cai , Zhang Xingxing 
Published: October 2023

AbstractBackgroundTriglyceride glucose (TyG) index is a good surrogate biomarker to evaluate insulin resistance (IR). The study aimed to investigate whether the TyG index is related to the severity of diabetic foot ulcers (DFUs) in patients with type 2 diabetes mellitus (T2DM).MethodsA total of 1059 T2DM patients were enrolled in this observational, retrospective, single‐center study. TyG index was calculated as ln[fasting triglycerides (mg/dl) × fasting glucose (mg/ dl)/2]. The severity of DFUs was classified into mild‐to‐moderate DFUs (Wagner grade score < 3) and severe DFUs (Wagner grade score ≥ 3) based on Wagner classification. Patients were stratified according to the tertiles of TyG index. Logistic regression models were implemented to explore the association between TyG index and the severity of DFUs. Subgroup analyses were used to verify the reliability of results.ResultsCompared with the reference lowest TyG tertile (T1), the highest tertile (T3) was associated with 0.377‐fold increased risk of prevalence of severe DFUs (odds ratio [OR] 1.377, 95% confidence interval [CI] 1.017–1.865) (P = 0.039). After adjusting for potential confounders, the multivariable‐adjusted OR and 95% CI were 1.506 (1.079–2.103) (P = 0.016) in patients with highest tertile. Moreover, subgroup analyses indicated that the association was stronger among men, patients with age ≥ 65 years, duration of diabetes more than 10 years, or without PAD.ConclusionsElevated TyG index is independently associated with severity of DFUs even after adjusting conventional confounders.
HycDemux: a hybrid unsupervised approach for accurate barcoded sample demultiplexing in nanopore sequencing
Authors: Han Renmin , Qi Junhai , Xue Yang , Sun Xiujuan , Zhang Fa , Gao Xin , Li Guojun 
Published: October 2023

AbstractDNA barcodes enable Oxford Nanopore sequencing to sequence multiple barcoded DNA samples on a single flow cell. DNA sequences with the same barcode need to be grouped together through demultiplexing. As the number of samples increases, accurate demultiplexing becomes difficult. We introduce HycDemux, which incorporates a GPU-parallelized hybrid clustering algorithm that uses nanopore signals and DNA sequences for accurate data clustering, alongside a voting-based module to finalize the demultiplexing results. Comprehensive experiments demonstrate that our approach outperforms unsupervised tools in short sequence fragment clustering and performs more robustly than current state-of-the-art demultiplexing tools for complex multi-sample sequencing data.
The mechanism of dendritic cell-T cell crosstalk in rheumatoid arthritis
Authors: Wang Zhandong , Zhang Jinlong , An Fangyu , Zhang Jie , Meng Xiangrui , Liu Shiqing , Xia Ruoliu , Wang Gang , Yan Chunlu 
Published: October 2023

AbstractRheumatoid arthritis (RA) is a chronic inflammatory disease characterised by joint pain and swelling, synovial hyperplasia, cartilage damage, and bone destruction. The mechanisms of dendritic cell (DC) and T cell-mediated crosstalk have gradually become a focus of attention. DCs regulate the proliferation and differentiation of CD4+ T cell subtypes through different cytokines, surface molecules, and antigen presentation. DC-T cell crosstalk also blocks antigen presentation by DCs, ultimately maintaining immune tolerance. DC-T cell crosstalk mainly involves chemokines, surface molecules (TonEBP, NFATc1), the PD-L1/PD-1 signalling axis, and the TGF-β signalling axis. In addition, DC-T cell crosstalk in RA is affected by glycolysis, reactive oxygen species, vitamin D, and other factors. These factors lead to the formation of an extremely complex regulatory network involving various mechanisms. This article reviews the key immune targets of DC-T cell crosstalk and elucidates the mechanism of DC-T cell crosstalk in RA to provide a basis for the treatment of patients with RA.
Organisational benefits of undertaking research in healthcare: an approach to uncover impact
Authors: Holliday Judith , Jones Natalie , Cooke Jo 
Published: October 2023

AbstractThere is increasing focus to review the societal impact of research through assessment and research excellence frameworks. These often link to financial and reputational incentives within the academic community. However, timeframes to demonstrate impact using these approaches are often long and are not designed to show benefit to service collaborators who require evidence of improvement and change to their services more immediately. Impacts that are measured this way may also miss out on unintended and positive impacts that occur as by-products of research, or through the ‘ripple effect’ that research may have on practice. Importantly, demonstrating how research makes a difference can improve the research culture in services, and motivations in service partners to become, and stay involved in research. This article describes, and provides access to, a tool called VICTOR (making Visible the ImpaCT Of Research) that was developed by a community of practice involving 12 NHS organisations through blending evidence from the literature, practice and service users. We describe the types of impact that have been collected by VICTOR and explore how collecting impact in this way might help research-practice partnerships and inform research methodologies and may be useful to show impacts alongside, and shortly after the research process.
Cognitive impairment indicator for the neuropsychological test batteries in the Canadian Longitudinal Study on Aging: definition and evidence for validity
Authors: O’Connell Megan E. , Kadlec Helena , Griffith Lauren E. , Wolfson Christina , Maimon Geva , Taler Vanessa , Kirkland Susan , Raina Parminder 
Published: October 2023

Abstract
Background
Prevalence of overall cognitive impairment based on each participant’s performance across a neuropsychological battery is challenging; consequently, we define and validate a dichotomous cognitive impairment/no cognitive indicator (CII) using a neuropsychological battery administered in a population-based study. This CII approximates the clinical practice of interpretation across a neuropsychological battery and can be applied to any neuropsychological dataset.

Methods
Using data from participants aged 45–85 in the Canadian Longitudinal Study on Aging receiving a telephone-administered neuropsychological battery (Tracking, N = 21,241) or a longer in-person battery (Comprehensive, N = 30,097), impairment was determined for each neuropsychological test based on comparison with normative data. We adjusted for the joint probability of abnormally low scores on multiple neuropsychological tests using baserates of low scores demonstrated in the normative samples and created a dichotomous CII (i.e., cognitive impairment vs no cognitive impairment). Convergent and discriminant validity of the CII were assessed with logistic regression analyses.

Results
Using the CII, the prevalence of cognitive impairment was 4.3% in the Tracking and 5.0% in the Comprehensive cohorts. The CII demonstrated strong convergent and discriminant validity.

Conclusions
The approach for the CII is a feasible method to identify participants who demonstrate cognitive impairment on a battery of tests. These methods can be applied in other epidemiological studies that use neuropsychological batteries.
RETRACTED ARTICLE: Enhancing throughput using channel access priorities in frequency hopping network using federated learning
Authors: Han Yu , Zhu Xiaowei 
Published: October 2023

AbstractThe data are sent by the nodes taking part in frequency hopping communications (FHC) utilising carrier frequencies and time slots that are pseudo-randomly assigned. Because of this, a high degree of protection against eavesdropping and anti-interference capabilities is provided. When using FHC in an environment, sharing time and frequency resources, avoiding collisions, and differentiating services are all made more complex as a result of this. A protocol for FHC that is based on dispersed wireless networks is presented by the authors of this research. It is a mechanism for multiple access control, which is prioritised and distributed. The ratio of empty channels metric can be found in the previous sentence. It is possible to provide priority in channel access by assigning different preset ratios of empty channel thresholds to the various traffic classes. Frames from frequency spread segments that have a partial collision are included as well. An analytical model is simulated for the analysis in terms of collision probability, transmission probability, and frame service time in order to carry out a theoretical examination of the performance of FHC. The objective of this inquiry is to determine how well FHC works. The analytical model has been proven correct by the exhaustive simulations as well as the theoretical findings. Cloud platforms are often used in the instruction of the most cutting-edge machine learning techniques of today, such as deep neural networks. This is done in order to take advantage of the cloud's capacity to scale elastically. In order to satisfy the criteria of these sorts of applications, federated learning, has been proposed as a distributed machine learning solution. This is done in order to fulfil the requirements of these kinds of applications. In federated learning (FL), even though everyone who uses the system works together to train a model, nobody ever shares their data with anybody else. Each user trains a local model with their own data, and then communicates the updated models with a FL server so that the data can be aggregated and a global model can be constructed. This process ensures that each user's model is unique. This process is repeated until a global model has been developed. This kind of training not only reduces the amount of network overhead that is necessary to transfer data to a centralised server, but it also safeguards the personal information of the users. Within the framework of this work, we looked at the feasibility of using the FL technique of learning on the many devices that are part of the dispersed network. On a centralised server, we conduct an analysis of the performance of the FL model by comparing its accuracy and the amount of time it takes to train using a range of various parameter value combinations. Additionally, the accuracy of these federated models may be made to reach a level that is comparable to that of the accuracy of central models.
An exploratory factor analysis of entrepreneurship psychological readiness (EPR) instrument
Authors: Farradinna Syarifah , Syafitri Nesi , Herawati Icha , Jayanti Wella 
Published: October 2023

AbstractThe purpose of this study was to develop an instrument for assessing psychological readiness for entrepreneurship. A well-designed measurement of entrepreneurship psychological readiness can provide early warning to policymakers, in this case the government, and provide education and funding to prospective entrepreneurs who must not only be examined physically, but also psychologically. Using Exploratory Factor Analysis (EFA) and reliability analysis, the validity and reliability of the Entrepreneurship Psychological Readiness (EPR) instrument were examined. An Exploratory Factor Analysis (EFA) found that the Entrepreneurship Psychological Readiness (EPR) instrument’s eight-factor model explained 57.44% of the variance among the items. To develop a fit model, it was necessary to exclude 26 items from the questionnaire, leaving 59 items left. The factors name identified by Personal Knowledge, Personal Adversity, Committed Certain Action, Willingness to Learn, Personal Relationship to Others, Personal Growth, Passion Achieved, and Related Person Support. All of the eight-factor models have excellent reliability of 0.96.
Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
Authors: Safrastyan Aram , zu Siederdissen Christian Höner , Wollny Damian 
Published: October 2023

Abstract
Background
Liquid biopsy, particularly cell-free RNA (cfRNA), has emerged as a promising non-invasive diagnostic tool for various diseases, including cancer, due to its accessibility and the wealth of information it provides. A key area of interest is the composition and cellular origin of cfRNA in the blood and the alterations in the cfRNA transcriptomic landscape during carcinogenesis. Investigating these changes can offer insights into the manifestations of tissue alterations in the blood, potentially leading to more effective diagnostic strategies. However, the consistency of these findings across different studies and their clinical utility remains to be fully elucidated, highlighting the need for further research in this area.

Results
In this study, we analyzed over 350 blood samples from four distinct studies, investigating the cell type contributions to the cfRNA transcriptomic landscape in liver cancer. We found that an increase in hepatocyte proportions in the blood is a consistent feature across most studies and can be effectively utilized for classifying cancer and healthy samples. Moreover, our analysis revealed that in addition to hepatocytes, liver endothelial cell signatures are also prominent in the observed changes. By comparing the classification performance of cellular proportions to established markers, we demonstrated that cellular proportions could distinguish cancer from healthy samples as effectively as existing markers and can even enhance classification when used in combination with these markers.

Conclusions
Our comprehensive analysis of liver cell-type composition changes in blood revealed robust effects that help classify cancer from healthy samples. This is especially noteworthy, considering the heterogeneous nature of datasets and the etiological distinctions of samples. Furthermore, the observed differences in results across studies underscore the importance of integrative and comparative approaches in the future research to determine the consistency and robustness of findings. This study contributes to the understanding of cfRNA composition in liver cancer and highlights the potential of cellular deconvolution in liquid biopsy.