Spatial performance in a group of young Fragile-X syndrome males with FMR-1 full mutation was compared to a learning disabled control group comprising young Down's syndrome males and two control groups of mainstream schoolchildren. Performance was assessed across a wide range of spatial tasks including visuo-construction, visuo-spatial memory, visuo-motor, and visuo-perception. The findings indicate a task-specific rather than global deficit in spatial performance in Fragile-X males with visuo-constructive and visuo-motor skills most vulnerable. Molecular analysis of the lymphocyte DNA found minimal evidence for a correlation between CGG expansion size and spatial performance, although tasks with a visuo-perceptual component correlated negatively with expansion size indicating that the further away the number of repeats are from the 200 threshold the poorer the performance.
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http://dx.doi.org/10.1016/s0010-9452(08)70799-8 | DOI Listing |
Neuro Oncol
January 2025
Department of Neurosurgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg.
Background: Peripheral nerve sheath tumors (PNSTs) encompass entities with different cellular differentiation and degrees of malignancy. Spatial heterogeneity complicates diagnosis and grading of PNSTs in some cases. In malignant PNST (MPNST) for example, single cell sequencing data has shown dissimilar differentiation states of tumor cells.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
Artificial Intelligence Lab, School of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500046, India.
The generalization of deep learning (DL) models is critical for accurate lesion segmentation in breast ultrasound (BUS) images. Traditional DL models often struggle to generalize well due to the high frequency and scale variations inherent in BUS images. Moreover, conventional loss functions used in these models frequently result in imbalanced optimization, either prioritizing region overlap or boundary accuracy, which leads to suboptimal segmentation performance.
View Article and Find Full Text PDFDalton Trans
January 2025
College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, P. R. China.
Efficient separation of photogenerated charge carriers is essential for maximizing the photocatalytic efficiency of semiconductor materials in oxygen evolution reactions (OER). This study presents a novel trimetallic photocatalyst, MIL-100(Fe)/TiO/CoO, synthesized through a facile microwave-assisted hydrothermal method followed by atomic layer deposition (ALD). The porous MIL-100(Fe) serves as a support for the sequential deposition of TiO and CoO layers ALD, which enhances electron-hole pair separation and minimizes their recombination.
View Article and Find Full Text PDFJ Acoust Soc Am
January 2025
Department of Informatics, University of Oslo, 0316 Oslo, Norway.
In adaptive beamforming, the array signal processing adjusts its sensor delays and weights based on the incoming data. In conventional beamforming, these parameters are instead given from a predefined model. Adaptive beamformers can improve measurement precision by dynamically rejecting spatial interference.
View Article and Find Full Text PDFIET Syst Biol
January 2025
School of Computer, University of South China, Hengyang, Hunan, China.
Spatially resolved transcriptomics technologies potentially provide the extra spatial position information and tissue image to better infer spatial cell-cell interactions (CCIs) in processes such as tissue homeostasis, development, and disease progression. However, methods for effectively integrating spatial multimodal data to infer CCIs are still lacking. Here, the authors propose a deep learning method for integrating features through co-convolution, called SpaGraphCCI, to effectively integrate data from different modalities of SRT by projecting gene expression and image feature into a low-dimensional space.
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