bluuebunny/crossref_metadata_2025_split huggingface dataset:
The relationship between Cyberchondria and Health Literacy among first year Nursing Students: the mediating effect of health anxiety.
Authors: Mohammed Manal Saeed , Hendawi Nourhan Essam Hendawi , El-Ashry Ayman Mohamed , Ali Samira Saad 
Published: July 2024

Abstract

Background First-year nursing students are at a critical juncture in their education. They are transitioning from laypersons to healthcare professionals, students are frequently exposed to medical information both in academic settings and through personal research. This exposure can sometimes lead to cyberchondria, improving health literacy and managing health anxiety are key strategies in reducing the incidence of cyberchondria.Aim Investigate the mediating effect of health anxiety between Cyberchondria and Health Literacy among first year Nursing Students.Methods A descriptive correlational research design following STROBE guidelines used in this study. The study was conducted with 475 students in October 2023 during the first semester of the academic year 2023–2024.Results Cyberchondria and health literacy levels were both moderate. In addition, the degree of health anxiety among first year Nursing Students was moderate too. The results showed that the association between Cyberchondria and Health Literacy and cyberchondria is partially mediated by health anxiety .Conclusion This study highlights the sophisticated relationship between cyberchondria, health literacy, and health anxiety among first-year nursing students. It demonstrates that lower health literacy can lead to increased health anxiety, which in turn exacerbates cyberchondria. To mitigate these issues, it is essential to enhance health literacy and provide support for managing health anxiety within nursing education programs. By doing so, we can help nursing students effectively navigate online health information and reduce unnecessary health-related anxieties, promoting better educational outcomes and overall well-being.
Interactions between sexual signaling and body size drive ecology and evolution of wing colors in Odonata
Authors: Idec Jacob , Bybee Seth , Ware Jessica , Abbott John , Ferreira Rhainer Guillermo , Suvorov Anton , Kohli Manpreet , Eppel Louis , Kuhn William , Belitz Michael , Guralnick Robert 
Published: July 2024

Abstract

Insect coloration has evolved in response to multiple pressures, and in Odonata (dragonflies and damselflies) a body of work supports a role of wing color in a variety of visual signals and potentially in thermoregulation. Previous efforts have focused primarily on melanistic coloration even though wings are often multicolored, and there has yet to be comprehensive comparative analyses of wing color across broad geographic regions and phylogenetic groups. Percher vs. flier flight-style, a trait with thermoregulatory and signaling consequences, has not yet been studied with regard to color. We used a new color clustering approach to quantify color across a dataset of over 8,000 odonate wing images representing 343 Nearctic species. We then utilized phylogenetically informed Bayesian zero-inflated mixture models to test how color varies with mean ambient temperature, body size, sex and flight-style. We found that wing coloration clustered into two groups across all specimens - light brown-yellow and black-dark brown - with black-dark brown being a much more cohesive grouping. Male perchers have a greater proportion of black-dark brown color on their wings as do species with longer wings. In colder climates, odonates were more likely to have black-dark brown color present, but we found no relationship between the proportion of black and temperature. Light brown-yellow showed similar scaling with wing length, but no relationship with temperature. Our results suggest that black-dark brown coloration may have a limited role in thermoregulation, while light brown-yellow does not have such a role. We also find that the odonate sexes are divergent in wing color in percher species only, suggesting a strong role for color in signaling in more territorial males. Our research contributes to an understanding of complex interactions driving ecological and evolutionary dynamics of color in animals.
A telomere-related gene panel predicts the prognosis and Immune Status in gastric cancer
Authors: Zhang Dai , Song Dingli , Li Yiche , He Fenfen , Hao Qian , Deng Yujiao , Yang Si , Wang Hui , Chen Jianghao , Wang Ting 
Published: July 2024

Abstract

Telomeres play a crucial role in the development and progression of cancers. However, the impact of telomere-related genes (TRGs) on the prognosis and tumor immune microenvironment (TIME) of gastric cancer (GC) remains unclear. Therefore, a comprehensive investigation of the association between TRGs and GC is necessary. The TRG risk panel was constructed by combining differentially expressed gene analysis, weighted gene co-expression network analyses, the Least Absolute Shrinkage and Selection Operator regression, and stepwise regression analysis in the TCGA cohort and has been validated in a GEO cohort. The major impacts of the signature on the TIME and immunotherapy response were also evaluated. The prognosis model comprised 9 TRGs (CABP2, CALML6, CFAP58, DST, ELOVL2, HIST1H3G, MYF6, PDE1B and TOP3B), stratifying patients into two risk groups. Individuals with low-risk scores exhibited superior prognoses than those with high-risk scores (P < 0.001). The prognostic signature was found to be an independent factor with good predictive power for overall survival. The high-risk group tended to have higher TME scores and an inert immune status with a higher infiltration proportion of Treg cells, M2 macrophages, resting dendritic cells and resting NK cells. Additionally, the low-risk group had higher TMB, lower TIDE and a higher immunotherapy response rate. Additionally, we confirmed the expression of the nine genes in GC tissues using RT-qPCR. Our TRG-based panel has a significant role in the prognosis, TIME, and immunotherapy response. This may suggest that the TRG panel could be a powerful tool for guiding clinical treatment decisions.
Green synthesis of ZnO NPs from Melon by-products (Cucumis Melo L.) extract: antioxidant activity and total phenolic content
Authors: Kahraman Yusuf Sezai , Altınkeser Tuğçe , BOZKURT Rabia Nur , Kaba İbrahim 
Published: July 2024

Abstract

In this study, zinc oxide nanoparticles (ZnO NPs) were synthesized using melon by-products (Cucumis Melo L.) extract. Nanoparticles were characterized using different techniques such as X-ray Diffraction (XRD), Fourier Transform Infrared (FTIR), Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray Diffraction (EDX), Transmission Electron Microscopy (TEM), Ultraviolet-Visible Spectrophotometry (UV-Vis), Ultraviolet-Visible Diffuse Reflection Spectroscopy (UV- DRS), Dynamic light scattering (DLS) analysis and Zetasizer. SEM and TEM analyzes were used to show that the material is relatively spherical in shape and nanosized. It is shown in the UV absorption peaks that ZnO NPs peak at 368 nm. XRD and additionally EDX confirmed the purity of the material, and FTIR spectra confirmed the functional group of ZnO NPs. Melon byproducts were evaluated for total phenolic and DPPH activity with different solvent concentrations. ZnO NPs synthesized using melon by-product extract rich in polyphenols were also evaluated in terms of total phenolic and DPPH activity. Nanoparticles exhibited antioxidant activity. It was understood that secondary metabolites from the extract were used as capping agents.
Electric Motor Health Monitoring Using a Deep Variational Autoencoder (D-VAE)
Authors: Dehghani Adnan , Rahim Sharafiz , Rez Khairil Anas Md , Abidin Abdul Murad Zainal , Mohd Azahar , KHALID SITI NOR AZILA , YUNUS MOHAMAD FIKRI MOHAMAD , RASHID ZAMIL HISHAM ABDUL 
Published: July 2024

Abstract

The integration of the Industrial Internet of Things (IoT) and machine learning techniques in condition-based maintenance (CBM) systems represents a significant advancement in the monitoring and maintenance of electromotors, particularly those used in elevator systems. This study explores the effectiveness of a Condition Based Maintenance (CBM) framework utilizing Arduino microcontrollers and Microelectromechanical Systems (MEMS) sensors for real-time vibration data collection, coupled with the analysis through a Deep Variational Auto-Encoder (D-VAE) model for anomaly detection in electromotor operation particularly in the elevator system. Traditional methods such as Isolation Forest and K-means clustering, enhanced by Principal Component Analysis (PCA), are also implemented for comparative analysis. The performance of these models is evaluated using unsupervised learning metrics, including the silhouette score, Davies-Bouldin Index, and Calinski-Harabasz score, to assess their efficacy in detecting anomalies within vibration data indicative of potential electromotor malfunctions. Our findings suggest the superior capability of the D-VAE model in discerning between normal and faulty operational states through detailed clustering, despite some limitations under problematic conditions. This study underscores the potential of data-driven approaches and IoT technologies in enhancing operational efficiency, reliability, and safety in elevator systems through predictive maintenance strategies.
Health-related quality of life of people with depression: pre-post intervention compared with age-matched general population in Vietnam
Authors: Hoa Truong Thi My , Ngan Tran Thu , Mai Vu Quynh , Minh Hoang Van , Thu Nguyen Khac , Nhu Tran Kieu 
Published: July 2024

Abstract

Background
There is a paucity of health-related quality of life (HRQoL) research on people with depression as well as a lack of evidence on supported self-management (SSM) intervention for depression on HRQoL in Vietnam. This study aimed to compare the HRQoL of people with depression and age-matched people in the Vietnamese population, evaluate the effects of Tele-SSM intervention on HRQoL, and examine the association between the changes in HRQoL score and mental health well-being (depression, anxiety, and stress).
Methods
This study was a pre- and post-study involving Vietnamese adults aged 18–64 who had depression symptoms (score ≥ 5 points in the PHQ-9). Participants (N = 58) completed Tele-SSM - a supported self-management intervention incorporating cognitive behavioral therapy and non-violent communication and using a task-shifting approach. To compare with the general population, we conducted 1-to-1 matching by age with an EQ-5D-5L valuation study with a nationally representative sample of the Vietnamese general population.
Results
HRQoL is significantly impaired in people with depression compared to the age-matched general population. Regarding health profile, participants reported the most difficulties in usual activities, pain/discomfort, and anxiety/depression dimensions. Significant improvements were observed in HRQoL scores post-intervention compared to pre-intervention in both EQ-VAS scores (from 59.84 to 79.48) and utility scores (from 0.79 to 0.09). These results remained lower than the age-matched general population (EQ-VAS score = 83.28, utility score = 0.96). Depression was associated with lower HRQoL while controlling for stress, anxiety symptoms and sociodemographic characteristics.
Conclusions
These results indicate that HRQoL is significantly impaired in people with depression and contribute to providing empirical evidence of Tele-SSM intervention in improving HRQoL. Further randomized controlled trials should be conducted to evaluate effectiveness and cost-effectiveness of the Tele-SSM intervention.
A Unsupervised graph comparison learning-based click-through rate prediction model
Authors: He Mingxiang , Bo Xina , li Guan , Sun Cheng'ai 
Published: July 2024

Abstract

Click-through rate (CTR) prediction refers to the estimation of the probability that a given user will click on a given advertisement, with the objective of displaying items of greater interest to the user. In this paper, we propose a clickthrough rate prediction model based on unsupervised graph comparison learning (USGCL-CTR) to address the issue of a decline in model prediction accuracy due to the neglecting the introduction of noise caused by useless feature interactions in existing CTR prediction models based on GNNs. To facilitate the transformation of the modeling task of feature interactions into the modeling of node interactions on the corresponding graph, the feature domain is visually represented as a graph structure following the embedding layer. Subsequently, noisy edges are removed by a designed feature interaction selection layer based on unsupervised graph comparison learning. In USGCL-CTR, we utilize metric learning to establish an ’anchor graph’, serving as a guide for the optimization of the graph structure. We then apply contrast loss to maximize the interaction information between the anchor graph and the learned structure. By eliminating unproductive feature interactions, the denoised feature map significantly enhances the precision of CTR predictions. Comparative experiments were carried out against eight baseline models on three open-source datasets. The results clearly showed that our proposed USGCL-CTR model surpassed all baseline models in performance.
An unusual case of acute pseudogout in the hand masquerading as cellulitis
Authors: meng yake , zhou lili , wang huang , yao jun , pan Hao 
Published: July 2024

Abstract

Calcium pyrophosphate dihydrate (CPPD) disease is the third most common inflammatory arthritides primarily affecting the elderly. We present a case of acute pseudogout of the hand whose symptoms mimicked cellulitis. Our patient presented with a swollen hand which were initially treated as acute cellulitis with antibiotics but without any improvement. A final diagnosis of acute chondrocalcinosis was made based on multiple intra-articular calcifications.
Brain Tumor and Mood Disorders: A Retrospective Analysis of Anxiety and Depression in Patients with Primary and Metastatic Brain Tumors
Authors: Kang Xiaoman , Ge Yulu , Zhang Xin , Yang Tianrui , Xia Yu , Wang Yaning , Li Junlin , Chen Wenlin , Zhang Kun , Xiao Zhiyuan , Wu Jiaming , Song Yixuan , Cao Yaning , Dong Yijun , Wang Yuekun , Xing Hao , Guo Xiaopeng , Wang Yu , Ma Wenbin 
Published: July 2024

Abstract

Brain tumors are associated with a dismal prognosis, and the diagnosis of intracranial tumors can evoke significant psychological disturbance. However, the evolution of patients' emotional status over the clinical course of brain tumors is less well understood. This study aims to document the prevalence of anxiety and depression in brain tumor patients and examine the risk factors associated with postoperative emotional derangement. Their psychological conditions were assessed using the Hospital Anxiety and Depression Scale (HADS) at various preoperative and postoperative time points. A total of 159 patients who underwent surgery and underwent HADS assessment between May 2018 and November 2020 were included in the analysis, with 112 gliomas and 47 metastatic brain tumors. After surgery, the incidence of anxiety increased for the glioma group (from 3.8–11.2%) and the metastatic brain tumor group (from 8.9–11.1%). Similarly, the prevalence of depression increased among glioma patients (from 8.6–18.4%) and metastatic tumor patients (from 20.0–31.1%). In either the glioma or metastatic group, tumors involving the frontal lobe were associated with a significant increase in postoperative HADS depression score. Univariate analysis among glioma patients indicated that males exhibited a reduced risk of postoperative exacerbation of anxiety, while right-sided tumors were associated with a decreased risk of postoperative worsening of depression. In the metastatic group, a BMI > 24 was a risk factor for postoperative anxiety exacerbation, whereas a temporal-lobe lesion was a protective factor in HADS depression worsening after surgery. The findings from the present research illustrate patient characteristics with a higher risk of psychological disturbance exacerbation postoperatively, aiding in early prevention and improving the quality of life among patients with intracranial tumors.
Uncommon Triple Vessel Spontaneous Coronary Artery Dissection in the Setting of Polyarteritis Nodosa: A Case Report
Authors: Lahmouch Nouhaila , Faraj Raid , Cherkaoui Soukaina , Nafii Omar , Sarsari Mohamed , Kerrouani Oualid , Allalat Idriss , Zarzur Jamila , Cherti Mohamed 
Published: July 2024

Abstract

Spontaneous coronary artery dissection (SCAD) is a rare cause of acute coronary syndromes (ACS) not related to atherosclerosis. It involves the sudden tearing of the coronary artery wall, separating the inner intimal lining from the outer vessel wall, typically affecting a single coronary vessel. In 20% of cases, the cause of SCAD is unknown. The other cases often occur in pregnant or postpartum women, or in individuals with conditions like connective tissue disorders or vasculitis. Here, we describe a case of a 69-year-old female presenting with non-ST-segment elevation myocardial infarction (NSTEMI). Coronary angiography revealed an unusual triple-vessel spontaneous coronary artery dissection (SCAD) affecting peripheral segments, with further investigations suggesting Polyarteritis nodosa (PAN). While triple-vessel SCAD and PAN are individually rare, their coexistence is exceptionally uncommon and presents diagnostic and therapeutic challenges. Clinicians should be alert to vasculitic causes in SCAD patients, especially with atypical clinical features.
Development of a quality indicator set for the optimal acute management of moderate to severe traumatic brain injury in the Australian context
Authors: Jeffcote Toby , Battistuzzo Camila R , Roach Rebecca , Bell Catherine , Bendinelli Cino , Rashford Stephen , Jithoo Ron , Gabbe Belinda J , Flower Oliver , O'Reilly Gerard , Campbell Lewis T , Cooper D James , Balogh Zsolt J , Udy Andrew U 
Published: July 2024

Abstract

Background

The aim of this study was to develop a consensus-based set of indicators of high-quality acute moderate to severe TBI (msTBI) clinical management that can be used to measure structure, process and outcome factors that are likely to influence patient outcomes. This is the first stage of the PRECISION-TBI program which is a prospective cohort study that aims to identify and promote optimal clinical management of msTBI in Australia.

Methods

A preliminary set of 45 quality indicators was developed based on available evidence. An advisory committee of established experts in the field refined the initial indicator set in terms of content coverage, proportional representation, contamination and supporting evidence. The refined indicator set was then distributed to a wider Delphi panel for assessment of each indicator in terms of validity, measurement feasibility, variability and action feasibility. Inclusion in the final indicator set was contingent on pre-specified inclusion scoring.

Results

The indicator set was structured according to the care pathway of msTBI and included pre-hospital, emergency department, neurosurgical, intensive care, and rehabilitation indicators. Measurement domains included structure indicators, logistic indicators and clinical management indicators. The Delphi panel consisted of 44 participants (84% physician, 12% nursing, 4% primary research) with a median of 15 years of practice. Of the 47 indicators included in the second round of the Delphi, 32 indicators were approved by the Delphi group.

Conclusion

This study identified a set of 32 quality indicators that can be used to structure data collection to drive quality improvement in the clinical management of msTBI. They will also be used to guide feedback to PRECISION-TBI’s participating sites.
Deciphering the Subtypes of Oily Sensitive Skin in Chinese Women: A Comprehensive Classification and Analysis
Authors: Kuang Xinjue , Lin Caini , Fu Yuanyuan , Wang Yuhui , Gong Junhua , Chen Yong , Liu Youting , Yi Fan 
Published: July 2024

Abstract

Background
Oily sensitive skin is complex that requires accurate identification and personalized care. However, the current classification method relies on subjective assessment.
Objectives
This study aimed to create a skin type and subtype classification using objective biophysical parameters to investigate differences in skin characteristics across anatomical and morphological regions.
Methods
This study involved 200 Chinese women. Noninvasive capture of biophysical measures and image analysis yielded 104 parameters. Key classification parameters were identified through mechanisms and characteristics, with thresholds set using statistical methods.
Results
This study identified the optimal ternary value classification method for dividing skin types into dry, neutral, and oily types based on tertiles of biophysical parameters, and further into barrier-sensitive, neurosensitive, and inflammatory-sensitive types. Oily sensitive skin showed increased sebum, pore, redness, dullness, wrinkles, and porphyrins, along with a tendency for oiliness and early acne. Subtypes exhibited specific characteristics: barrier-sensitive was rough with a high pH and was prone to acne; neurosensitive had increased TEWL and sensitivity; and inflammatory-sensitive exhibited a darker tone, with low elasticity and uneven redness.
Conclusions
This study established an objective classification system for skin types and subtypes using noninvasive parameters, clarifying the need for care for oily sensitive skin and supporting personalized skincare.
Heterozygous CELF4 variants in the N-term region crucial for the RNA-binding activity, leads to neurodevelopmental disorder and obesity.
Authors: Bruel Ange-Line , Silfhout Anneke Vulto-van , Bilan Frederic , Guyader Gwenaël Le , Gilbert-Dussardier Brigitte , Horn Xavier Le Guillou , Rondeau Sophie , RIO Marlène , Lee Kristen , Beil Adelyn , Suri Mohnish , Guerin François , Ruault Valentin , Goldenberg Alice , Lecoquierre François , Bertsch Nicole , Anderson Rhonda , Yang Xiao-Ru , Inness Micheil , Rikeros-Orozco Emi , Palomares-Bralo Maria , Hayek Jennifer , Cech Jennifer , Jhuraney Ankita , Kumar Runjun , Mercimek-Andrews Saadet , Ambrose Anastasia , Wakeling Erin , Wentzensen Ingrid , Torti Erin , Gooch Catherine , Faivre Laurence , Philippe Christophe , Duffourd Yannis , Vitobello Antonio , Thauvin-Robinet Christel 
Published: July 2024

Abstract

RNA-binding proteins play a key role in post-transcriptional events, such as mRNA splicing, transport, stability, translation and decay. Dysregulation of RNA life can have dramatic consequences. CELF RNA-binding proteins appear to be essential during embryo development. In this study, we identified fifteen patients with heterozygous missense or loss-of-function variants in the CELF4 gene by exome or genome sequencing. All variants affecting the N-terminus of the protein are essential and sufficient for the RNA-binding and splicing activity or RRM domains. Most patients presented with neurodevelopmental disorders including global developmental delay/intellectual disability (11/14), seizures (9/15), and overweight/obesity (10/14) that began in childhood. Clinical features are similar to the reported celf4-mouse mutant phenotype. This study highlights the essential role of CELF4 in development and its involvement as a novel etiology of neurodevelopmental disorders with obesity.