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Liquid biopsy of plasma and urinary CfDNA differentiates glioma recurrence from radiation brain necrosis in preclinical models
Analysis and prediction of schizophrenia patients based on high-order graph attention generative adversarial networks
Abstract Generative Adversarial Networks, a popular deep learning method, have achieved excellent performance in both classification and prediction tasks. However, there have been relatively few applications of generative adversarial networks to EEG data. To study the effect of high-order brain functional networks on schizophrenia patients, a high-order graph attention generative adversarial network prediction model is proposed, and the generator of the model utilizes graph attention networks and long short-term memory networks to capture the high-order topological features of persistence images for early diagnosis and prediction of schizophrenia patients. The research results on the five frequency bands of schizophrenia show that the proposed prediction model performs best in the Theta frequency band, with AUC and MAP values reaching 93.5% and 93.0%, respectively, and an average accuracy of 91.5%, both of which are superior to the selected comparison methods. Moreover, the image quality coefficient is used to quantify the realism and clarity of the images generated by the model. the image quality coefficients of schizophrenia patients were significantly correlated with the PANSS total scores in the Gamma and Theta bands, which provided a new idea for generative adversarial networks in the prediction of schizophrenia high-order topological features.
Clinical outcomes and management strategies for moderate aortic regurgitation in patients undergoing rheumatic mitral valve surgery
A virtual-structure-based type-3 fuzzy system for predictive sensor and actuator fault detection, compensation, and control in nonlinear systems
Deep reinforcement learning for resource allocation and scalable numerology in NR-U enabled multi-RAT HetNets
Abstract Leveraging the new radio technology in the unlicensed band (NR-U) can alleviate traffic congestion, enhance network capacity, and help mitigate the diversity in users’ service requests. In this paper, a multiple slice multi-radio access technology (RAT) heterogeneous network (HetNet) is considered, integrating the new radio (NR) technology in the licensed and unlicensed bands. An optimization problem is proposed aiming to maximize users’ satisfaction, defined by maximizing the achievable data rate while maintaining the minimum latency slice requirement. To solve the proposed optimization problem, an iterative framework is introduced that utilizes deep reinforcement learning (DRL) algorithm jointly with the regret learning algorithm (RLA) that efficiently solves users’ association problem considering coexisting Wi-Fi users, allocates radio resources for each slice and determines the optimum scalable numerology value in each slice. The simulation results show that our proposed model improves users’ satisfaction, achieving up to 70% user satisfaction compared with other baseline approaches.
Cold stress impacts cognitive performance in healthy volunteers: results from a randomized, controlled, cross-over study
Impact of hydrotalcite phases on the texture characteristic of OPC and its correlation with compressive strength and gamma Attenuation
Abstract Hydrotalcites (HTs), recognized for their eco-friendly synthesis, layered structure, and exceptional ion-exchange capacity, offer significant potential as functional additives in cementitious systems. Most previous studies used different types of HT based on varying the kinds of di- or tri-valent cations during the preparation process, but they did not change the ratio between them. Accordingly, this study tailored three Mg-Al-CO₃-based HTs with varying Mg: Al ratios (1:1, 2:1, and 3:1, designated HT1, HT2, and HT3) and incorporated them at 1 wt% into ordinary Portland cement (OPC) pastes. The effects of HTs on setting time, workability, and compressive strength were evaluated. Phase composition, textural properties, and microstructure of reference and HT-modified pastes were characterized using XRD, BET/BJH analyses, and SEM/EDX. Additionally, gamma-ray shielding performance against Cs-137 (661.64 keV) was assessed by determining the linear attenuation coefficient (µ) and half-value layer (HVL). Results reveal that HTs accelerate setting, slightly reduce workability, enhance compressive strength, and significantly improve radiation shielding. Among the tailored HTs, HT1 exhibited superior performance, achieving the highest compressive strength (88.8 MPa at 28 days) and greatest shielding efficiency, with µ increased by 112.5% and HVL reduced by 52.9% compared to OPC. These improvements are attributed to HT1’s high surface area, amorphous/mesoporous nature, and its role as a nucleation site and filler, leading to a dense microstructure. Furthermore, incorporating HTs provides an environmentally sustainable approach for producing high-performance cementitious materials with enhanced mechanical and radiological properties, supporting industrial applications in construction and nuclear safety.
DGCR8 regulates multiple processes of transcription coupled nucleotide excision repair
An explanatory composite metric for air cargo network robustness: incorporating pairwise synergistic effects
High tensile strength and transformation-induced plasticity in bulk polycrystalline omega titanium
Differential brain reorganization in chronic cervical spinal cord injury and its relation to motor versus sensory impairments: a preliminary investigation
Correction: Detecting mangrove seedlings from UAV imagery using deep learning for restoration monitoring
Covalent immobilization of Lepidium draba peroxidase on chitosan-coated magnetic nanoparticles and its application in glucose biosensing
Mechanical performance and life cycle assessment of a Persian gum-waste carpet fiber soil composite for landfill bottom liners
Self-efficacy and quality of life mediate self-reported mental health outcomes in visual snow syndrome
Abstract Visual snow syndrome (VSS) is a chronic neurological disorder associated with impaired mental health. While self-efficacy and quality of life (QOL) are known to influence mental health outcomes (depression and suicidal ideation) in clinical populations, their roles in VSS remain unexplored. This study aimed to examine the associations among VSS, self-efficacy, QOL, mental health outcomes and the potential serial mediation roles of self-efficacy and QOL. A cross-sectional study compared 64 VSS patients and 67 healthy controls matched with age, sex and education level. Participants completed validated questionnaires assessing self-efficacy (GSES), QOL (WHOQOL-BREF), depression (CES-D), and suicidal ideation (BSSI, first five items). Analyses included group comparisons, correlation analyses to examine variable relationships, multimodel linear regression and serial mediation modeling to test the hypothesized sequential pathway from VSS through self-efficacy and quality of life to mental health outcomes. Compared with controls, VSS patients demonstrated significantly lower self-efficacy (VSS: 23.6 ± 6.2; Controls: 30.6 ± 6.0; p < 0.001) and QOL (VSS: 62.5 ± 9.5; Controls: 73.6 ± 8.8; p < 0.001), alongside elevated depression (median [IQR]: VSS: 28 [21,34]; Controls: 11 [7, 15]; p < 0.001) and suicidal ideation (VSS: 6 [5, 7]; Controls: 5 [5,6]; p < 0.01). Serial mediation analysis revealed that the effects of VSS on depression and suicidal ideation were mediated through self-efficacy and QOL sequentially. The total indirect effect for depression was 7.73 (95% CI [5.64–9.85]), with QOL accounting for 49.09% of the total effect. For suicidal ideation, the total indirect effect was 0.80 (95% CI [0.39–1.22]). Lower self-efficacy and QOL appear to serially mediate the associations between VSS and mental health impairments. These preliminary, cross-sectional findings indicate that self-efficacy and QOL may serve as modifiable intervention targets that mediate or moderate the risk of depression and suicidal ideation in individuals with VSS. Clinicians should prioritize routine assessments of these factors to guide early intervention strategies, although longitudinal studies are needed to confirm these causal pathways.
Bovine serum albumin nanoparticles improve bacteriophage stability and antimicrobial activity against Pseudomonas aeruginosa
Dose-dependent effects of camel milk on immune function and metabolic health in weaning rats
Abstract Breastfeeding cannot fulfill an infant’s nutritional needs beyond six months, necessitating the introduction of alternative milk sources. Camel milk has emerged as a promising candidate due to its rich profile of nutrients and immunomodulatory properties. This study evaluated the dose-dependent effects of camel milk on general health and immune response in post-weaning rats, with particular attention to sex-specific differences. Male and female rats were divided into: control (GI), and four treatment groups receiving 2.4 mL (GII), 3.4 mL (GIII), 4.4 mL (GIV), or 5.4 mL (GV) of camel milk daily for six weeks. Serum biochemical parameters, including lipid profile, liver and kidney function markers, and immunological responses were assessed before and after immunization with sheep red blood cells. While higher doses (4.4–5.4 mL) significantly enhanced immune response and bone health, they concurrently elevated liver and kidney function parameters. The 3.4 mL dose balanced benefits, showing significant immune enhancement and bone health improvement without adverse metabolic effects. These findings demonstrated that camel milk (3.4 mL for rats/473 mL for infants) safely enhanced immune function, while higher doses risk metabolic stress. The results supported camel milk’s potential as a nutritional supplement during weaning but emphasized the importance of dose regulation.