Large-scale imaging of neuronal activities is crucial for understanding brain functions. However, it is challenging to analyze large-scale imaging data in real time, preventing closed-loop investigation of neural circuitry. Here we develop a real-time analysis system with a field programmable gate array-graphics processing unit design for an up to 500-megabyte-per-second image stream. Adapted to whole-brain imaging of awake larval zebrafish, the system timely extracts activity from up to 100,000 neurons and enables closed-loop perturbations of neural dynamics.
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http://dx.doi.org/10.1038/s41593-024-01595-6 | DOI Listing |
Microb Genom
January 2025
Department of Laboratory Medicine, Clinical Microbiology, Faculty of Medicine and Health, rebro University, rebro, Sweden.
National epidemiological investigations of microbial infections greatly benefit from the increased information gained by whole-genome sequencing (WGS) in combination with standardized approaches for data sharing and analysis. To evaluate the quality and accuracy of WGS data generated by different laboratories but analysed by joint pipelines to reach a national surveillance approach. A national methicillin-resistant (MRSA) collection of 20 strains was distributed to nine participating laboratories that performed in-house procedures for WGS.
View Article and Find Full Text PDFInt J Surg
January 2025
Carcinoma Department of Traditional Chinese Medicine, Dianjiang People's Hospital of Chongqing, Chongqing, PR China.
The widespread adoption of high-resolution computed tomography (CT) screening has led to increased detection of small pulmonary nodules, necessitating accurate localization techniques for surgical resection. This review examines the evolution, efficacy, and safety of various localization methods for small pulmonary nodules. Studies focusing on localization techniques for pulmonary nodules ≤30 mm in diameter were included, with emphasis on technical success rates and complication profiles.
View Article and Find Full Text PDFACS Sens
January 2025
Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada.
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.
View Article and Find Full Text PDFDrug Saf
January 2025
Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark.
Introduction: Large administrative healthcare databases can be used for near real-time sequential safety surveillance of drugs as an alternative approach to traditional reporting-based pharmacovigilance. The study aims to build and empirically test a prospective drug safety monitoring setup and perform a sequential safety monitoring of rofecoxib use and risk of cardiovascular outcomes.
Methods: We used Danish population-based health registers and performed sequential analysis of rofecoxib use and cardiovascular outcomes using case-time-control and cohort study designs from January 2000 to September 2004.
Mol Biol Rep
January 2025
Medical Sociology and Psychobiology, Department of Health and Physical Activity, University of Potsdam, 14469, Potsdam, Germany.
Background: Depression constitutes a risk factor for osteoporosis, but underlying molecular and cellular mechanisms are not fully understood. MiRNAs influence gene expression and are carried by extracellular vesicles (EV), affecting cell-cell communication.
Aims: (1) Identify the difference in miRNA expression between depressed patients and healthy controls; (2) Analyze associations of these miRNAs with bone turnover markers; (3) Analyze target genes of differentially regulated miRNAs and predict associated pathways regarding depression and bone metabolism.
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