In this article, we formally present the (ISCA). This model brings together the cognitive-perceptual and social-communication features of autism under a single explanatory framework. Specifically, ISCA proposes that the social-communication features that are related to theory of mind dysfunction emerge from the cognitive-perceptual features related to enhanced perceptual functioning and weak central coherence, and proposes that they are linked by dysfunction in the self-categorization process. We present the assumptions on which the model is based, and from these, we derive a set of precise, testable hypotheses, including a set of novel hypotheses that do not emerge from any existing models of autism. We then provide evidence that supports the model, derived from a number of direct tests of the hypotheses that it generates. We conclude by discussing the implications of the model for understanding autism and for intervention to improve the lives of autistic people, as well as future directions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1037/rev0000385 | DOI Listing |
Soft comput
July 2024
Computer Science and Engineering, KL University, Guntur, Andra Pradesh India.
[This retracts the article DOI: 10.1007/s00500-022-06943-x.].
View Article and Find Full Text PDFAnn Med
December 2025
Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, PR China.
Objective: This study aims to explore the role of exosome-related genes in breast cancer (BRCA) metastasis by integrating RNA-seq and single-cell RNA-seq (scRNA-seq) data from BRCA samples and to develop a reliable prognostic model.
Methods: Initially, a comprehensive analysis was conducted on exosome-related genes from the BRCA cohort in The Cancer Genome Atlas (TCGA) database. Three prognostic genes (JUP, CAPZA1 and ARVCF) were identified through univariate Cox regression and Lasso-Cox regression analyses, and a metastasis-related risk score model was established based on these genes.
Proc Natl Acad Sci U S A
January 2025
Department of Statistics and Data Science, College of Science, Southern University of Science and Technology, Shenzhen 518055, China.
Social media is profoundly changing our society with its unprecedented spreading power. Due to the complexity of human behaviors and the diversity of massive messages, the information-spreading dynamics are complicated, and the reported mechanisms are different and even controversial. Based on data from mainstream social media platforms, including WeChat, Weibo, and Twitter, cumulatively encompassing a total of 7.
View Article and Find Full Text PDFSmall
January 2025
Institute of Biomass and Function Materials & National Demonstration Centre for Experimental Light Chemistry Engineering Education, College of Bioresources Chemistry and Materials Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, P. R. China.
As skin bioelectronics advances, hydrogel wearable devices have broadened perspectives in environment sensing and health monitoring. However, their application is severely hampered by poor mechanical and self-healing properties, environmental sensitivity, and limited sensory functions. Herein, inspired by the hierarchical structure and unique cross-linking mechanism of hagfish slime, a self-powered supramolecular hydrogel is hereby reported, featuring high stretchability (>2800% strain), ultrafast autonomous self-healing capabilities (electrical healing time: 0.
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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!