Context: Neuro-cognitive functions have not been extensively studied among young bipolar disorder patients. Researchers have found cognitive deficits in bipolar disorder and many have found such deficits even in euthymic states of the disorder but results are still inconclusive.
Aim: To study sustained attention and executive functioning in remitted adolescents with bipolar disorder.
Settings And Design: Present study was a hospital-based cross-sectional study.
Materials And Methods: Twenty adolescents, aged 14-17 years with bipolar disorder, were selected for the study. Subjects were euthymic for at least 2 months. The performance of patients was matched with normal controls. Sustained attention was primarily measured by Letter Cancellation Test (LCT) and Wisconsin Card Sorting Test (WCST), Trail Making Test (TMT) and Stroop Colour Word Test were used to assess executive functions. Two groups differed significantly on level of education and thus multivariate linear model was used and education was put as a covariate.
Results: Results revealed that patients preformed less well than control. Significant poor performance was reported on LCT (omission scores), TMT, Stroop and WCST.
Conclusion: The study confirmed previous findings stating that cognitive deficits like sustained attention and executive functions continue to be present in adolescent bipolar patients even in euthymic states.
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http://dx.doi.org/10.4103/0253-7176.162955 | DOI Listing |
PLoS One
December 2024
MedStar Georgetown University Hospital, Washington, DC, United States of America.
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December 2024
Amrita School for Sustainable Futures, Amrita Vishwa Vidyapeetham, Amritapuri, 690525, Kerala, India.
The 'Third Pole', home to numerous glaciers, serves as vital water reserves for a significant portion of the Asian population and has garnered global attention within the context of climate change due to their highly vulnerable nature. While a general decline in global glacial extent has been observed in recent decades, the pronounced regional imbalances across the Third Pole present a perplexing anomaly. To assess the impact of glacier mass changes in the Gangotri basin, we conducted a comprehensive analysis using remote sensing data to estimate spatially resolved mass changes from 2000 to 2023.
View Article and Find Full Text PDFBioprocess Biosyst Eng
December 2024
Chemical Sciences, Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong, BE 1410, Brunei Darussalam.
In recent years, zinc oxide nanoparticles (ZnO NPs) have gained much attention in biomedical applications because of their distinctive physicochemical features such as low toxicity and biocompatible properties. Traditional methods to produce ZnO NPs sometimes include harmful substances and considerable energy consumption, causing environmental issues and potential health risks. Nowadays, the concern of ZnO production has moved toward environmentally friendly and sustainable synthesis methods, using natural extracts or plant-based precursors.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Grassland and Natural Landscape Sciences, Poznań University of Life Sciences, 11 Dojazd St, 60- 632, Poznań, Poland.
Grasslands, being vital ecosystems with significant ecological and socio-economic importance, have been the subject of increasing attention due to their role in biodiversity conservation, carbon sequestration, and agricultural productivity. However, accurately classifying grassland management intensity, namely extensive and intensive practices, remains challenging, especially across large spatial extents. This research article presents a comprehensive investigation into the classification of grassland management intensity in two distinct regions of Poland, NUTS2 - namely Podlaskie (PL84) and Wielkopolskie (PL41), by integrating data from Sentinel-1 and Sentinel-2 satellite imagery.
View Article and Find Full Text PDFNat Commun
December 2024
School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Per- and polyfluoroalkyl substances (PFASs) have recently garnered considerable concerns regarding their impacts on human and ecological health. Despite the important roles of polyamide membranes in remediating PFASs-contaminated water, the governing factors influencing PFAS transport across these membranes remain elusive. In this study, we investigate PFAS rejection by polyamide membranes using two machine learning (ML) models, namely XGBoost and multimodal transformer models.
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