The ability to combine individual concepts of objects, properties, and actions into complex representations of the world is often associated with language. Yet combinatorial event-level representations can also be constructed from nonverbal input, such as visual scenes. Here, we test whether the language network in the human brain is involved in and necessary for semantic processing of events presented nonverbally. In Experiment 1, we scanned participants with fMRI while they performed a semantic plausibility judgment task versus a difficult perceptual control task on sentences and line drawings that describe/depict simple agent-patient interactions. We found that the language network responded robustly during the semantic task performed on both sentences and pictures (although its response to sentences was stronger). Thus, language regions in healthy adults are engaged during a semantic task performed on pictorial depictions of events. But is this engagement necessary? In Experiment 2, we tested two individuals with global aphasia, who have sustained massive damage to perisylvian language areas and display severe language difficulties, against a group of age-matched control participants. Individuals with aphasia were severely impaired on the task of matching sentences to pictures. However, they performed close to controls in assessing the plausibility of pictorial depictions of agent-patient interactions. Overall, our results indicate that the left frontotemporal language network is recruited but not necessary for semantic processing of nonverbally presented events.
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http://dx.doi.org/10.1162/nol_a_00030 | DOI Listing |
Bioinformatics
January 2025
Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, 1004, Philippines.
Motivation: Recent computational approaches for predicting phage-host interaction have explored the use of sequence-only protein language models to produce embeddings of phage proteins without manual feature engineering. However, these embeddings do not directly capture protein structure information and structure-informed signals related to host specificity.
Results: We present PHIStruct, a multilayer perceptron that takes in structure-aware embeddings of receptor-binding proteins, generated via the structure-aware protein language model SaProt, and then predicts the host from among the ESKAPEE genera.
Taiwan J Ophthalmol
November 2024
Sirindhorn International Institute of Technology, Thammasat University, Bangkok, Thailand.
Recent advances of artificial intelligence (AI) in retinal imaging found its application in two major categories: discriminative and generative AI. For discriminative tasks, conventional convolutional neural networks (CNNs) are still major AI techniques. Vision transformers (ViT), inspired by the transformer architecture in natural language processing, has emerged as useful techniques for discriminating retinal images.
View Article and Find Full Text PDFEClinicalMedicine
January 2025
School of Physical Therapy, Faculty of Health Science, Western University, London, Ontario, Canada.
Background: Given the chronic immune activation and inflammatory milieu associated with Long COVID and HIV, we assessed the prevalence of Long COVID in adults living with HIV; and investigated whether adults living with HIV were associated with increased chance of developing Long COVID compared to adults living without HIV.
Methods: In this systematic review and meta-analysis, we searched Medline, EMBASE, CINHAL, PubMed and CENTRAL from inception until June 14th, 2024, for observational studies that measured the prevalence of Long COVID in adults living with HIV and the odds of developing Long COVID following a SARS-CoV-2 infection in people living with HIV compared to people living without HIV. Reviews, case reports, randomised control trials and editorials were excluded.
Global Spine J
January 2025
Combined Neurosurgical and Orthopedic Spine Program, Department of Orthopedics Surgery, University of British Columbia, Vancouver, BC, Canada.
Study Design: Narrative Literature review.
Objective: To provide a general overview of important molecular markers and targeted therapies for the most common neoplasms (lung, breast, prostate and melanoma) that metastasize to the spine and offer guidance on how to best incorporate them in the clinical setting.
Methods: A narrative review of the literature was performed using PubMed, Google Scholar, Medline databases, as well as the histology-specific National Comprehensive Cancer Network guidelines to identify relevant articles limited to the English language.
World J Microbiol Biotechnol
January 2025
CSIR-National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, India.
Plants and microorganisms coexist within complex ecosystems, significantly influencing agricultural productivity. Depending on the interaction between the plant and microbes, this interaction can either help or harm plant health. Microbes interact with plants by secreting proteins that influence plant cells, producing bioactive compounds like antibiotics or toxins, and releasing molecules such as N-acyl homoserine lactones to coordinate their behaviour.
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