bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of appearance-related cyberbullying on the desire to alter physical appearance among adolescent females
Authors: Prince Taliah , Mulgrew Kate , Driver Christina , Mills Lia , Loza Jehan , Hermens Daniel 
Published: June 2024

Abstract

Cyberbullying is associated with various mental health concerns in adolescents including body dissatisfaction and disordered eating behaviours. However, there is a significant research gap concerning the unique effects of appearance-related cyberbullying (ARC) on adolescent mental health. This study examined the prevalence and psychological consequences of ARC among middle to late adolescent females (aged 14–19 years, Mage= 15.98, N = 336). Participants completed an online survey regarding their experiences of ARC, body image variables, and eating disorder symptomology. Findings indicate the widespread occurrence of ARC among adolescent females, with body shape and size emerging as predominant targets. Experiences of ARC-victimisation positively correlated with increased concerns about body shape, body shame, and eating disorder symptomology. Conversely, experiences of ARC-victimisation were negatively correlated with body esteem and body appreciation. Finally, appearance-related cybervictimisation was a significant predictor of adolescent females’ desire to pursue appearance alterations through methods such as dieting and exercising, altering self-presentation, and undergoing cosmetic procedures. These findings highlight the necessity for developing comprehensive strategies aimed at protecting the mental well-being of adolescent females by reducing the effects of ARC.
Prevalence of Typical and Atypical Pain Sites of Coronary Artery Disease: A Cross-Sectional Study
Authors: Abdullatef Mayar , Omran Maya , Bitar Anas , Alsaid Bayan 
Published: June 2024

Abstract

Study Objective
This study aims to assess the prevalence of both typical and atypical pain in patients with ischemic heart disease, emphasizing the importance of recognizing and not disregarding atypical symptoms.
Methods
This cross-sectional study was conducted on patients diagnosed with coronary artery disease (CAD) who were admitted to two major hospitals in Damascus, Syria, from 2021 to 2023. Patients were asked to mark the sites of their pain on an anatomic illustration. Typical pain was identified as pain located in the precordial area, with or without radiating to the left shoulder or the left arm. Any other distribution of pain was considered atypical. Patients’ demographics and previous medical history were documented to investigate any potential associations with atypical pain.
Results
Among the 100 patients, 64% (64) had atypical pain, while 36% (36) had typical symptoms. Referred pain to areas like the left shoulder and left arm was reported by 81.9% of patients, with 47% and 41% of the sample mentioning discomfort in these regions, respectively. We found that smoking and previous heart disease were associated with atypical pain, with 73% of patients who experienced atypical pain being smokers.
Conclusion
The study found that atypical pain is common, affecting 64% of individuals primarily in the right shoulder, right arm, and back. This type of pain is associated with smoking and prior heart disease. Misdiagnosing coronary artery disease (CAD) can have serious consequences, as patients with atypical symptoms may miss important pre-hospital procedures like ECG.
Small-sample short-term photovoltaic output prediction model based on GRA-SSA-GNNM method
Authors: Wang Qi , Mutailipu Meiheriayi , Jing Jiaheng , Jing Xuehui , Yang Yande 
Published: June 2024

Abstract

The precision of photovoltaic (PV) output forecasting results is crucial to the reliability of the intelligent distribution network and multi-energy supplementary system. This work aims to address problems of insufficient research related to the short-term prediction of small-sample PV power generation and the low prediction accuracy in the previous research. A hybrid prediction model based on grey relation analysis (GRA) combined by sparrow search algorithm (SSA), and grey neural network model (GNNM) is proposed. In this paper, GRA is utilized to reduce the dimension of meteorological features of the samples. Then, a high-precision day-ahead short-term PV production forecast based on the SSA-GNNM model is established. The GNNM is used to perform regression analysis on the input features after reducing the dimension of meteorological features of the samples, and the parameters of the GNNM are optimised via SSA. The prediction results agrees well with the data from PV power plant in Xinjiang, indicating that the GRA-SSA-GNNM model developed in this work effectively achieves a high precision estimation in short-term PV power generation output prediction and has a promising application in this field.
Optimizing UAV Photography: Strategies in Flight Control and Image Capture
Authors: zheng ting , li shangze , xiao zhensheng , zhang luyan 
Published: June 2024

Abstract

This paper addresses the challenges faced by novice drone operators in mastering flight altitude, speed, and shooting angles. It analyzes strategies for adjusting these parameters to capture satisfactory photographs, focusing on four key questions. Firstly, it examines the geometric relationship between flight altitude and camera coverage area, establishing an optimization model for drone shooting accuracy. Secondly, it independently analyzes the numerical relationship between shooting angles and camera coverage area, identifying optimal shooting angles using a UAV shooting accuracy score optimization model. Thirdly, it develops a small UAV system model and ground target model, employing a recursive target tracking algorithm to continuously adjust shooting angles for target acquisition. Finally, it introduces a novel RRT* algorithm for path planning around obstacles encountered during flight. We use MATLAB to select a reasonable obstacle avoidance strategy, and the global optimal route is obtained by smoothing processing. Simulation results demonstrate model stability and robustness across varying flight conditions.
Subcision with Platelet-Rich Plasma and Microneedling versus Subcision with Saline and Microneedling in Posttraumatic Scars
Authors: Twisy Howida Omar 
Published: June 2024

Abstract

Background: In treating post-traumatic scars, this study compared the safety and effectiveness of combined subcision with saline and microneedling versus combined subcision with platelet-rich plasma and microneedling.
Methods: Subcision with microneedling with either saline or platelet-rich plasma was used to treat 36 consecutive individuals with post-traumatic scarring. The Modified Manchester score was used to assess texture change, pigmentation, and surface distortion changes. Each change was given a score between 1 and 4. A lower score (range: 3–12) indicates a better result. The mean of the three individual scores was determined.
Results: For best outcomes, a patient needed an average of four treatments for each scar, with a one-month follow-up period following the final treatment. The three variables in group B had mean scores of 1.4±0.5, 2±0.8, and 2.2±0.9, respectively, for texture change, pigmentation, and surface distortion. With a mean score of 1.4±0.5, texture change had the best response out of the three variables we evaluated. The investigator determined that the mean improvement score for patients in group B's overall appearance was 5.61±1.19.
Conclusion: The study has shown that the combination of subcision with platelet-rich plasma, and microneedling appears to be a promising treatment for posttraumatic scars due to its low risk and high efficacy. Our findings suggest that this is safe method for treating posttraumatic scars, with few side effects and a low chance of recurrence.
Characteristics of regional lymph node metastasis in breast cancer and construction of a nomogram model based on ultrasonographic Analysis: A Retrospective Study
Authors: Zhu Meidi , Xu Zipeng , Hu Jing , Hua Lingling , Zou Yu , Qin Fei , Chen Chaobo 
Published: June 2024

Abstract

Objective: The ultrasonographic characteristics of lymph node metastasis in breast cancer patients were retrospectively analyzed and a predicted nomogram model was conducted, aiming to provide an imaging basis for better clinical evaluation of lymph node metastasis in breast cancer patients.
Methods:B-mode ultrasound was used to retrospectively analyze the imaging characteristics of regional lymph nodes and tumor. Pathological examination of lymph node metastasis was confirmed in breast cancer patients. Univariable and multivariable logistic regression analyses were performed to analyze the risk factors of lymph node metastasis. LASSO regression analysis was further carried out to screen non-invasive indicators and a nomogram prediction model was conducted for breast cancer patients with lymph node metastasis.
Results: A total of 187 breast cancer patients were included in this study. Of them, 74 patients with lymph node metastasis were assigned to the Positive group, and 113 non-metastases were assigned to the Negative group. Multivariate analysis indicated that pathological type (OR=4.58, 95%CI: 1.44-14.6, p=0.01), tumor diameter (OR=1.37, 95%CI: 1.07-1.74, p=0.012), spiculated margins (OR=7.92, 95%CI:3.03-20.67, p<0.001), mixture echo of the breast tumor (OR=37.09, 95%CI:3.49-394.1, p=0.003) and unclear lymphatic hilum structure (OR=16.07, 95%CI:2.41-107.02, p=0.004) were independent risk factors for lymph node metastasis. A nomogram model was constructed for predicting breast cancer with lymph node metastasis, incorporating three significantly correlated indicators identified through LASSO regression analysis: tumor spiculated margins, cortical thickness of lymph nodes, and unclear lymphatic hilum structure. The receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) for the training set was 0.717 (95% CI, 0.614-0.820) and the validation set was 0.817 (95% CI, 0.738-0.890). The Hosmer Lemeshow test for the training-set and the validation- set was p=0.9148 and p=0.1648, separately. The predicted nomogram has a good diagnostic performance.
Conclusions:B-mode ultrasound is helpful in preoperative assessment of breast cancer with lymph node metastasis. Our predicted nomogram model based on logistic regression and LASSO regression analysisis clinical predictive safe, reliable, and highly practical.
Inhibitory Effect of the Multi-target TKI, Anlotinib, in 5-FU Resistant Colorectal Cancer HCT-8/15 Cells: Down Regulation of Drug Resistance-associated Protein Expression.
Authors: LIU JUAN , SUN HAOLIN , ZHENG XIXI , MA NINA , Liu Xiaoling , Cao Ruizhen , Cao Bangwei , Yang Mudan 
Published: June 2024

Abstract

Purpose
Colorectal cancer is the most prevalent gastrointestinal malignancy. Treatment usually includes 5-fluorouracil (5-FU), oxaliplatin, and irinotecan, with 5-FU usually being the first choice. 5-FU treatment failure occurs when cancer cells acquire resistance. Therefore, it is crucial to identify compounds effective against 5-FU-resistant tumors. Herein, we determined the efficacy and mechanism of anlotinib in 5-FU-resistant colon cancer cells.
Materials and methods
Human colon cancer cells (HCT-8/5-FU and HCT-15/5-FU) resistant to 5-FU were subjected to treatment with anlotinib, 5-FU, or both. Cell proliferation was assessed via MTS and clone formation assays. Cell cycle progression was studied using flow cytometry. Through immunoblotting, we evaluated changes in the protein levels of p-AKT and multidrug resistance 1.
Results
MTS assays indicated that HCT-8/5-FU and HCT-15/5-FU cells were sensitive to anlotinib and resistant to 5-FU. At 48 h, HCT-8/5-FU had an IC50 of 2246.5 ± 204.5 µM, while HCT-15/5-FU had an IC50 of 18.49 ± 3.23 mM for 5-FU. The IC50 of anlotinib for HCT-8/5-FU cells was 53.69 ± 8.10µM at 24 h and 17.39 ± 1.98µM at 48 h. The IC50 values for HCT-15/5-FU at 24 and 48 h were 55.03 ± 3.44µM and 8.83 ± 3.02µM, respectively. Anlotinib enhanced 5-FU sensitivity in resistant cells, with low concentrations (IC10) considerably enhancing the antiproliferative effects of 5-FU. Further, anlotinib significantly increased the number of cells in the G0-G1 phase dose-dependently, while the proportion of cells entering S phase decreased. MDR1 and AKT expression decreased with increasing anlotinib concentration.
Conclusion
Anlotinib suppressed the proliferation of 5-FU-resistant colon cancer cells by preventing entry into S phase, thus sensitizing cells to 5-FU. Moreover, anlotinib may reverse the effect of 5-FU on drug-resistant cells by down-regulating the expression of multidrug-resistant proteins, in which the AKT signaling pathway may play an important role.
Developing guidelines for nursing management of epilepsy in Ghanaian schools
Authors: Dzah Seth Selassie , Leech Ronell , Wath Anna Van der 
Published: June 2024

Abstract

Background The absence of guidelines for the nursing management of individuals living with epilepsy, who are students in Ghana, has resulted in the high dropout rates of such students. It is our hope, that in the near future, these individuals living with epilepsy will receive the needed attention, experience less stigmatization and discrimination. This, we expect, will result in better retention of such students in schools, improved academic performance and successful graduation. To achieve this, there is the need to develop appropriate guidelines and implement same for their benefit. In line with this, the study aims to develop guidelines for nurses to manage individuals living with epilepsy in Ghanaian schools.Methodology Qualitative approach will be adopted to conduct this study in two phases. In the first phase, a case study design will be deployed in the Twifo/Atti-Morkwa District of the Central Region of Ghana. The case is the nursing management of individuals living with epilepsy within the school context, and the sources of information will be the general nurses, psychiatric, or community psychiatric nurses working at the schools. Within the context of the case, parents or guardians of individuals living with epilepsy in the schools as well as their teachers will be included in the study. Data will be collected through individual interviews for nurses and parents while focus group discussions will be used for the teachers. Thematic analysis will be used to analyze the data. In the second phase, guidelines will be developed using the e-Delphi Technique. The study will be piloted in the Komenda-Edina-Eguafo-Abrem Municipality of the Central Region of Ghana. Ethics approval for this study has been obtained from the Ethical Review Committee of the University of Pretoria in South Africa. Additionally, Administrative approvals have been obtained from the Ghana Education Service.Discussion The guidelines developed will form the basis for nursing management of individuals living with epilepsy in Ghanaian schools. This will help to improve educational outcomes for the individuals living with epilepsy.
Altered expression and localization of nuclear envelope proteins in a prostate cancer cell system
Authors: Sandoval Ariana , Garrido Efrain , Camacho Javier , Magaña Jonathan Javier , Cisneros Bulmaro 
Published: June 2024

Abstract

Background. The nuclear envelope (NE), which is composed of the outer and inner nuclear membranes, the nuclear pore complex and the nuclear lamina, regulates a plethora of cellular processes, including those that restrict cancer development (genomic stability, cell cycle regulation, and cell migration). Thus, impaired NE is functionally related to tumorigenesis, and monitoring of NE alterations is used to diagnose cancer. However, the chronology of NE changes occurring during cancer evolution and the connection between them remained to be precisely defined, due to the lack of appropriate cell models. Methods. The expression and subcellular localization of NE proteins (lamins A/C and B1 and the inner nuclear membrane proteins emerin and β-dystroglycan [β-DG]) during prostate cancer progression were analyzed, using confocal microscopy and western blot assays, and a prostate cancer cell system comprising RWPE-1 epithelial prostate cells and several prostate cancer cell lines with different invasiveness. Results. Deformed nuclei and the mislocalization and low expression of lamin A/C, lamin B1, and emerin became more prominent as the invasiveness of the prostate cancer lines increased. Suppression of lamin A/C expression was an early event during prostate cancer evolution, while a more extensive deregulation of NE proteins, including β-DG, occurred in metastatic prostate cells. Conclusion. The RWPE-1 cell line-based system was found to be suitable for the correlation of NE impairment with prostate cancer invasiveness and determination of the chronology of NE alterations during prostate carcinogenesis. Further study of this cell system would help to identify biomarkers for prostate cancer prognosis and diagnosis.
Integrated miRNA and mRNA Analysis Provides New Insight into Mechanism of dermal papilla in Androgenetic Alopecia
Authors: Liu Xiaomin , Ye Maijiayi , Tao Guogui , Sun Xiaoqing , Zuo Tiantian , Wu Wanhong , Jin Jinghui , Hu Zhiqi 
Published: June 2024

Abstract

Background
Androgenetic alopecia (AGA) is a generally progressive type of hair loss, characterized by hair cycle abnormalities and hair miniaturization, with genetic predisposition and androgen-dependence. Although microRNAs (miRNAs) play indispensable roles in the control of many biological processes in hair follicle (HF), the miRNA-based regulation in the hair follicular mesenchyme remains utterly unknown so far. For this reason, we constructed a miRNA-mRNA interaction network by integrating analysis of miRNA and mRNA expression from balding and non-balding dermal papilla cells (DPCs) to study the underlying mechanism of AGA.
Methods
The mRNA and the miRNA expression profiles were downloaded from previously studies. Among all different mRNAs, top 10 hub genes, MYC, KRAS, RAF1, CCND1, FOS, MAPK3, STAT1, IL6, ETS1 and AKT1 were identified form PPI network. Then, the up-regulated miRNAs and the down-regulated mRNAs were integrated to construct a miRNA-mRNA interaction network.
Results
Pathway analysis revealed that the miRNA-mRNA network mainly involved MAPK signaling pathway, Ras signaling pathway, Rap1 signaling pathway, FoxO signaling pathway, P13K-Akt signaling pathway and Apoptosis.
Conclusions
These findings highlight the top 10 hub genes which may play significant roles in pathology of AGA. Meanwhile, miRNA-mRNA network pathway analysis offers a novel insight into potential etiology and mechanism of AGA.
Precise Firing Methods for Small-caliber Unmanned Intelligent Firearms Based on BP Neural Network and Model Predictive Control
Authors: Gao Yunlong , Wang Yongjuan 
Published: June 2024

Abstract

The firing accuracy of small-caliber unmanned intelligent weapons has an important impact on killing effectiveness. In order to improve the firing accuracy of small-caliber unmanned intelligent weapons against moving humanoid targets, hit probability estimation and image servo control are investigated in this paper. Firstly, a method to predict the impact points based on supervised learning is proposed. An corrected ballistic trajectory model is applied to generate training samples, and the mapping relationship that expresses the state of the impact points is formed. Then, a bullet dispersion acquisition experiment is carried out, and a model of bullet dispersion based on a two-dimensional Gaussian distribution is established by analyzing the distribution characteristics of the impact points. Meanwhile, the estimation method of hit probability applied to image detection is formed. In addition, an image servo control method based on model predictive control and human key point detection is proposed, which effectively improves the tracking accuracy of moving humanoid targets. Finally, numerical simulation and firing experiment validation are carried out, and the results show that the precision firing method of small-caliber unmanned intelligent weapons proposed in this paper can effectively improve the firing accuracy of small-caliber unmanned intelligent weapons.
Facile Synthesis of new 7-morpholino-6-(Aryl-1,3,4-oxadiazol)-1,8-naphthyridines and, evaluation of Antimicrobial and molecular Docking studies
Authors: Priya Kasaboina Kalyani , Shireesha Kavati , Jella Kumara Swamy 
Published: June 2024

Abstract

The new series of biologically potential antibacterial and anti-fungal agents of 7-morpholino-6-(5-ary-1,3,4-oxadiazol)-1,8-naphthyridine-2-carbonitrile scaffolds successfully synthesised by using the mild catalyst (FeCl3.6H2O) obtained good yields. The structures of the newly synthesized final target molecules established by various techniques IR, 1H NMR, 13C NMR, and Mass data. Activity of In vitro Antimicrobial studies of the new products were investigated against bacterial and fungal strains in compare with the clinical drugs Ampicillin, Grieseofulvin, compounds 7c and 7g demonstrated highest activity against pathogenic strains. Moreover, products were docked against target protein receptor (PDB ID: 8g4d), Docking results displayed that 7c and 7g are excellent binding interactions with the protein.
Enhancing Quantum Approximate Optimization with CNN-CVaR Integration
Authors: Cai Pengnian , Shen Kang , Yang Tao , Hu Yuanming , Lv Bin , Fan Liuhuan , Liu Zeyu , Hu Qi , Zhu Yunlai , Wu Zuheng , Dai Yuehua , Yang Fei , Wang Jun , Xu Zuyu 
Published: June 2024

Abstract

The Quantum Approximate Optimization Algorithm (QAOA) represents a promising approach for tackling combinatorial optimization challenges on near-term quantum devices. Central to QAOA optimization is the minimization of the expectation of the problem Hamiltonian for parameterized trial quantum states, which motivates the exploration of advanced optimization techniques. In this study, we propose a novel combinatorial optimization strategy, CNN-CVaR-QAOA, which integrates a Convolutional Neural Network (CNN) with Conditional Value at Risk (CVaR) to optimize QAOA circuits. By replacing the traditional loss function with CVaR and leveraging CNN for variational quantum parameter optimization, we demonstrate the superior efficacy of CNN-CVaR-QAOA through experimental validation on Erdos-Renyi random graphs. Our results show enhanced approximation ratios across various graph configurations. Furthermore, we investigate the influence of the CVaR parameter ($\alpha$) on algorithm performance, revealing that lower $\alpha$ values lead to smoother objective functions and improved approximation ratios. CNN-CVaR-QAOA offers significant advantages in optimizing QAOA parameters, particularly in the context of small-scale quantum devices, highlighting its potential to enhance QAOA optimization efforts across diverse optimization domains.