Objectives: To compare the performance of patients with complex partial epilepsy with the normal controls in the subtests of an instrument used to assess intelligence function.
Method: Fifty epileptic patients, whose ages ranged from 19 to 49 years and 20 normal controls without any neuropsychiatric disorders. The Wechsler-Bellevue adult intelligence test was applied in groups, epileptic patients and control subjects. This test is composed of several subtests that assess specific cognitive functions. A statistical analysis was performed using non-parametric tests.
Results: All the Wechsler-Bellevue subtests revealed that the intelligence functions of the patients were significantly inferior to that of the controls (p<0.05). This performance was supported by the patient's complaints in relation to their cognitive performance.
Conclusion: Patients with complex partial epilepsy presented poorer results in the intelligence test when compared with individuals without neuropsychiatric disorders.
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http://dx.doi.org/10.1590/s0004-282x2004000600010 | DOI Listing |
Stem Cell Res Ther
January 2025
Organoid Innovation Center, Suzhou Institute of Nanotech and Nano-bionics, Chinese Academy of Sciences, 398 Ruoshui Rd, Suzhou, Jiangsu, 215123, China.
The lack of in vivo accurate human liver models hinders the investigation of liver-related diseases, injuries, and drug-related toxicity, posing challenges for both basic research and clinical applications. Traditional cellular and animal models, while widely used, have significant limitations in replicating the liver's complex responses to various stressors. Liver organoids derived from human pluripotent stem cells, adult stem cells primary cells, or tissues can mimic diverse liver cell types, major physiological functions, and architectural features.
View Article and Find Full Text PDFJ Comput Chem
January 2025
RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
QCforever is a wrapper designed to automatically and simultaneously calculate various physical quantities using quantum chemical (QC) calculation software for blackbox optimization in chemical space. We have updated it to QCforever2 to search the conformation and optimize density functional parameters for a more accurate and reliable evaluation of an input molecule. In blackbox optimization, QCforever2 can work as compactly arranged surrogate models for costly chemical experiments.
View Article and Find Full Text PDFStem Cell Res Ther
January 2025
Department of Medicine, Veterans Affairs Medical Center, Washington, DC, USA.
Introduction: Effects of Dapagliflozin (Dapa) and Dapagliflozin-Saxagliptin combination (Combo) was examined on peripheral blood derived CD34 + Hematopoetic Stem Cells (HSCs) as a cellular CVD biomarker. Both Dapa (a sodium-glucose co-transporter 2 or SGLT2, receptor inhibitor) and Saxagliptin (a Di-peptydl-peptidase-4 or DPP4 enzyme inhibitor) are commonly used type 2 diabetes mellitus or T2DM medications, however the benefit of using the combination has not been evaluated for cardio-renal risk assessment, in a real-life practice setting, compared to a placebo.
Hypothesis: We hypothesized that Dapa will improve the outcomes when compared to placebo and the Combo maybe even more beneficial.
Sci Rep
January 2025
School of Transportation and Geometics Engineering, Yangling Vocational & Technical College, Yangling, 712100, Shaanxi, China.
This work aims to improve the accuracy and efficiency of flood disaster monitoring, including monitoring before, during, and after the flood, to achieve accurate extraction of flood disaster change information. A modified U-Net network model, incorporating the Transformer multi-head attention mechanism (TM), is developed specifically for the characteristics of Synthetic Aperture Radar (SAR) images. By integrating the TM, the model effectively prioritizes image regions relevant to flood disasters.
View Article and Find Full Text PDFNat Commun
January 2025
Key Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing, 21189, China.
Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties.
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