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This study presents new fuzzy adaptations of Ostrowski's integral inequalities through a novel class of convex fuzzy-valued mappings defined over a harmonic convex set, avoiding the use of the Sugeno integral. These innovative inequalities generalize the recently developed interval forms of real-valued Ostrowski inequalities. Their formulations incorporate integrability concepts for fuzzy-valued mappings (FVMs), applying the Kaleva integral and a Kulisch–Miranker fuzzy order relation. The fuzzy order relation is constructed via a level-wise approach based on the Kulisch–Miranker order within the fuzzy number space. Additionally, numerical examples illustrate the effectiveness and significance of the proposed theoretical model. Various applications are explored using different means, and some complex cases are derived. [ABSTRACT FROM AUTHOR]

Given the rapid advancement of functional 1,8-Naphthalimide derivatives in anticancer research, we synthesized these two novel naphthalimide derivatives with diverse substituents and investigated the effect on glioblastoma multiforme (GBM) cells. Cytotoxicity, apoptosis, cell cycle, topoisomerase II and Western blotting assays were evaluated for these compounds against GBM in vitro. A human GBM xenograft mouse model established by subcutaneously injecting U87-MG cells and the treatment responses were assessed. Both compounds 3 and 4 exhibited significant antiproliferative activities, inducing apoptosis and cell death. Only compound 3 notably induced G2/M phase cell cycle arrest in the U87-MG GBM cells. Both compounds inhibited DNA topoisomerase II activity, resulting in DNA damage. The in vivo antiproliferative potential of compound 3 was further validated in a U87-MG GBM xenograft mouse model, without any discernible loss of body weight or kidney toxicity noted. This study presents novel findings demonstrating that 1,8-Naphthalimide derivatives exhibited significant GBM cell suppression in vitro and in vivo without causing adverse effects on body weight or kidney function. Further experiments, including investigations into mechanisms and pathways, as well as preclinical studies on the pharmacokinetics and pharmacodynamics, may be instrumental to the development of a new anti-GBM compound. [ABSTRACT FROM AUTHOR]

Mobile technology is developing significantly. Mobile phone technologies have been integrated into the healthcare industry to help medical practitioners. Typically, computer vision models focus on image detection and classification issues. MobileNetV2 is a computer vision model that performs well on mobile devices, but it requires cloud services to process biometric image information and provide predictions to users. This leads to increased latency. Processing biometrics image datasets on mobile devices will make the prediction faster, but mobiles are resource-restricted devices in terms of storage, power, and computational speed. Hence, a model that is small in size, efficient, and has good prediction quality for biometrics image classification problems is required. Quantizing pre-trained CNN (PCNN) MobileNetV2 architecture combined with a Support Vector Machine (SVM) compacts the model representation and reduces the computational cost and memory requirement. This proposed novel approach combines quantized pre-trained CNN (PCNN) MobileNetV2 architecture with a Support Vector Machine (SVM) to represent models efficiently with low computational cost and memory. Our contributions include evaluating three CNN models for ocular disease identification in transfer learning and deep feature plus SVM approaches, showing the superiority of deep features from MobileNetV2 and SVM classification models, comparing traditional methods, exploring six ocular diseases and normal classification with 20,111 images post-data augmentation, and reducing the number of trainable models. The model is trained on ocular disorder retinal fundus image datasets according to the severity of six age-related macular degeneration (AMD), one of the most common eye illnesses, Cataract, Diabetes, Glaucoma, Hypertension, and Myopia with one class Normal. From the experiment outcomes, it is observed that the suggested MobileNetV2-SVM model size is compressed. The testing accuracy for MobileNetV2-SVM, InceptionV3, and MobileNetV2 is 90.11%, 86.88%, and 89.76% respectively while MobileNetV2-SVM, InceptionV3, and MobileNetV2 accuracy are observed to be 92.59%, 83.38%, and 90.16%, respectively. The proposed novel technique can be used to classify all biometric medical image datasets on mobile devices. [ABSTRACT FROM AUTHOR]

Infiltrative non-GBM gliomas are common primary intracranial malignancies, and postoperative adjuvant radiotherapy is recommended for most adult patients diagnosed with this disease to enhance local control and prolong intracranial progression-free survival (PFS). However, RT-related neurocognitive function (NCF) consequences should not be ignored. Early neurocognitive decline principally includes episodic memory, associated significantly with functions of the hippocampus. This prospective study aims to investigate the impact of adjuvant brain irradiation on neurocognitive performances and relevant oncological outcomes. Twenty-five patients with intracranial infiltrative non-GBM gliomas were enrolled when postoperative adjuvant RT was recommended. All recruited patients should receive baseline brain magnetic resonance imaging, and neuropsychological assessments before and 4 months after the RT course. A battery of neuropsychological measures, mainly including executive functions, memory, psychomotor speed and visuoconstructive ability, was used to evaluate NCFs of interest. Analyzing the delta values between post-irradiation and baseline NCF scores, we observed a robust trend reflecting cognitive stabilization rather than deterioration in almost all NCF. Both verbal and visual memory functions exhibited significant differences in the corresponding scaled scores (Z = −2.722, p =.006, regarding verbal memory; Z = −2.246, p =.025, concerning non-verbal memory). Moreover, patients' neuropsychological performances associated with psychomotor speed and executive functions also disclosed a tendency toward stabilization/improvement. This prospective study demonstrated that patients with infiltrative non-GBM exhibited a marked tendency toward neurocognitive stabilization after receiving postoperative adjuvant RT. Clinical trial registration: Trial Registration with ClinicalTrials.gov identifier: NCT03534050 [ABSTRACT FROM AUTHOR]