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Depression symptom severity and behavioral impairment in school-going adolescents in Uganda.
BMC Psychiatry
January 2025
Division of Epidemiology and Social Sciences, Institute for Health and Equity, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
Background: During adolescence, a critical developmental phase, cognitive, psychological, and social states interact with the environment to influence behaviors like decision-making and social interactions. Depressive symptoms are more prevalent in adolescents than in other age groups which may affect socio-emotional and behavioral development including academic achievement. Here, we determined the association between depression symptom severity and behavioral impairment among adolescents enrolled in secondary schools of Eastern and Central Uganda.
View Article and Find Full Text PDFSynergistic anticancer effects of cisplatin and phenolic aglycones of the aerial part of Rumex dentatus L. in tongue squamous cell carcinoma: insights from network pharmacology and biological verification.
BMC Complement Med Ther
January 2025
Department of Biochemistry, Faculty of Pharmacy, Tanta University, Tanta, 31527, Egypt.
Background: Oral squamous cell carcinoma (OSCC) ranks as the sixth most common malignancy globally. Cisplatin is the standard chemotherapy for OSCC, but resistance often reduces its efficacy, necessitating new treatments with fewer side effects. Rumex dentatus L.
View Article and Find Full Text PDFA machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness.
Sci Rep
January 2025
College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, 321004, China.
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them.
View Article and Find Full Text PDFA quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.
Sci Rep
January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
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