Although confrontation naming deficits have been observed in dominant temporal lobe epilepsy (DTLE), the relative contribution of impoverished phonologic word retrieval and/or semantic knowledge remains unclear. Analysis of verbal-semantic, phonemic-literal, and combination paraphasias produced during confrontation naming by participants with seizure disorders (52 DTLE; 47 nondominant temporal lobe epilepsy [NDTLE]; 54 psychogenic nonepileptic seizures [PNES]) indicated that the frequency of: (a) verbal-semantic paraphasias was similar across groups, (b) phonemic-literal paraphasias was highest in DTLE, and (c) combination paraphasias was lowest in PNES. Confrontation naming ability was most strongly related to phonemic-literal paraphasia frequency in DTLE and to verbal IQ in both NDTLE and PNES. Greater confrontation naming deficits in DTLE may be attributed to impairments in phonological processing.
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http://dx.doi.org/10.1037/0894-4105.19.5.603 | DOI Listing |
Neural Netw
January 2025
School of Big Data & Software Engineering, Chongqing University, Chongqing, 401331, China. Electronic address:
Recent progress in Graph Convolutional Networks (GCNs) has facilitated their extensive application in recommendation, yielding notable performance gains. Nevertheless, existing GCN-based recommendation approaches are confronted with several challenges: (1) how to effectively leverage multi-order graph connectivity to derive meaningful node embeddings; (2) faced with sparse raw data, how to augment supervision signals without relying on auxiliary information; (3) given that GCNs necessitate the aggregation of neighborhood nodes, and the sparsity of these nodes can exacerbate the impact of noise data, how to mitigate the noise problem inherent in the raw data. For tackling aforementioned challenges, we devise a new hybrid propagation GCN-based method named S3HGN, incorporating a simplified self-supervised learning paradigm for recommendation.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Population and Health, College of Humanities and Legal Studies, University of Cape Coast, Cape Coast, Ghana.
Background: Teenage childbirth is an issue of social and public health concern in Ghana, with high prevalence in some regions, including the Central Region. There is a dire need to understand the experiences of teenagers beyond pregnancies to facilitate comprehensive sexual and reproductive health information and service provision. We explored the postnatal experiences of teenage mothers in five communities in the Central Region of Ghana.
View Article and Find Full Text PDFAppl Microbiol Biotechnol
January 2025
Department of Microbiology and Biochemistry, Hochschule Geisenheim University, Von-Lade-Straße 1, 65366, Geisenheim, Germany.
Improving ale or lager yeasts by conventional breeding is a non-trivial task. Domestication of lager yeasts, which are hybrids between Saccharomyces cerevisiae and Saccharomyces eubayanus, has led to evolved strains with severely reduced or abolished sexual reproduction capabilities, due to, e.g.
View Article and Find Full Text PDFHum Brain Mapp
February 2025
Université libre de Bruxelles (ULB), UNI - ULB Neuroscience Institute, Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN2T), Brussels, Belgium.
Language control processes allow for the flexible manipulation and access to context-appropriate verbal representations. Functional magnetic resonance imaging (fMRI) studies have localized the brain regions involved in language control processes usually by comparing high vs. low lexical-semantic control conditions during verbal tasks.
View Article and Find Full Text PDFFront Bioeng Biotechnol
January 2025
Department of Rheumatology and Immunology, Beijing Hospital, National Centre of Gerontology, Beijing, China.
Background: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of osteoarthritis confronts challenges such as reduced sensitivity, subjective interpretation, and heightened misdiagnosis rates. The objective of this investigation is to enhance the validation and optimization of accuracy and efficiency in KOA assessment by utilizing fusion deep learning techniques.
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