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Cortical function, including sensory processing, is surprisingly resilient to neuron loss during aging and neurodegeneration. In this Article, we used the mouse auditory cortex to investigate how homeostatic mechanisms protect the representational map of sounds after neuron loss. We combined two-photon calcium imaging with targeted microablation of 30-40 sound-responsive neurons in layer 2/3. Microablation led to a temporary disturbance of the representational map, but it recovered in the following days. Recovery was primarily driven by neurons that were initially unresponsive to sounds but gained responsiveness and strengthened the network's correlation structure. By contrast, selective microablation of inhibitory neurons caused prolonged disturbance, characterized by destabilized sound responses. Our results link individual neuron tuning and plasticity to the stability of the population-level representational map, highlighting homeostatic mechanisms that safeguard sensory processing in the neocortex.
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http://dx.doi.org/10.1038/s41593-025-01982-7 | DOI Listing |
PLoS One
September 2025
Department of Smart Manufacturing, Industrial Perception and Intelligent Manufacturing Equipment Engineering Research Center of Jiangsu Province, Nanjing Vocational University of Industry Technology, Nanjing, Jiangsu, China.
In the field of quality control, metal surface defect detection is an important yet challenging task. Although YOLO models perform well in most object detection scenarios, metal surface images under operational conditions often exhibit coexisting high-frequency noise components and spectral aliasing background textures, and defect targets typically exhibit characteristics such as small scale, weak contrast, and multi-class coexistence, posing challenges for automatic defect detection systems. To address this, we introduce concepts including wavelet decomposition, cross-attention, and U-shaped dilated convolution into the YOLO framework, proposing the YOLOv11-WBD model to enhance feature representation capability and semantic mining effectiveness.
View Article and Find Full Text PDFPLOS Glob Public Health
September 2025
Department of International Health, Center for Humanitarian Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Humanitarian crises, particularly in conflict zones, create cascading disruptions that impact every aspect of daily life, including health and disease outcomes. While international humanitarian frameworks categorize these crises into discrete operational clusters, affected populations experience them as interwoven, systemic failures. This study examines how conflict-induced disruptions transform a preventable and typically self-limiting disease-Hepatitis A-into a fatal outcome.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
Accurate vascular segmentation is essential for coronary visualization and the diagnosis of coronary heart disease. This task involves the extraction of sparse tree-like vascular branches from volumetric space. However, existing methods have faced significant challenges due to discontinuous vascular segmentation and missing endpoints.
View Article and Find Full Text PDFJMIR Res Protoc
September 2025
Division of Physical Therapy and Rehabilitation Science, Department of Family Medicine and Community Health, Medical School, University of Minnesota-Twin Cities, Minneapolis, MN, United States.
Background: Approximately 69% of Americans with spinal cord injury (SCI) have neuropathic pain. Research suggests that impairments in mental body representations (MBRs; ie, representations of the body in the brain) likely contribute to neuropathic pain. Clinical trials in adults with SCI, focused on restoring MBR, led to improvements in sensation and movement as well as neuropathic pain relief.
View Article and Find Full Text PDFBrief Bioinform
August 2025
School of Information and Artificial Intelligence, Anhui Agricultural University, 130 Changjiang Road, Shushan District, Hefei, Anhui 230036, China.
Protein-nucleic acid binding sites play a crucial role in biological processes such as gene expression, signal transduction, replication, and transcription. In recent years, with the development of artificial intelligence, protein language models, graph neural networks, and transformer architectures have been adopted to develop both structure-based and sequence-based predictive models. Structure-based methods benefit from the spatial relationship between residues and have shown promising performance.
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