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Multiomic analyses direct hypotheses for Creutzfeldt-Jakob disease risk genes.
Brain
January 2025
Medical Research Council Prion Unit, University College London Institute of Prion Diseases, London, W1W 7FF, UK.
Prions are assemblies of misfolded prion protein that cause several fatal and transmissible neurodegenerative diseases, with the most common phenotype in humans being sporadic Creutzfeldt-Jakob disease (sCJD). Aside from variation of the prion protein itself, molecular risk factors are not well understood. Prion and prion-like mechanisms are thought to underpin common neurodegenerative disorders meaning that the elucidation of mechanisms could have broad relevance.
View Article and Find Full Text PDFAdvancing long-read nanopore genome assembly and accurate variant calling for rare disease detection.
Am J Hum Genet
January 2025
UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA. Electronic address:
More than 50% of families with suspected rare monogenic diseases remain unsolved after whole-genome analysis by short-read sequencing (SRS). Long-read sequencing (LRS) could help bridge this diagnostic gap by capturing variants inaccessible to SRS, facilitating long-range mapping and phasing and providing haplotype-resolved methylation profiling. To evaluate LRS's additional diagnostic yield, we sequenced a rare-disease cohort of 98 samples from 41 families, using nanopore sequencing, achieving per sample ∼36× average coverage and 32-kb read N50 from a single flow cell.
View Article and Find Full Text PDFLigand interaction landscape of transcription factors and essential enzymes in E. coli.
Cell
January 2025
Program in Bioinformatics, Boston University, Boston, MA 02215, USA; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Center for Network Systems Biology, Boston University, Boston, MA 02218, USA; Department of Chemistry, Boston University, Boston, MA 02215, USA; Department of Chemical Physiology and Biochemistry, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA. Electronic address:
Knowledge of protein-metabolite interactions can enhance mechanistic understanding and chemical probing of biochemical processes, but the discovery of endogenous ligands remains challenging. Here, we combined rapid affinity purification with precision mass spectrometry and high-resolution molecular docking to precisely map the physical associations of 296 chemically diverse small-molecule metabolite ligands with 69 distinct essential enzymes and 45 transcription factors in the gram-negative bacterium Escherichia coli. We then conducted systematic metabolic pathway integration, pan-microbial evolutionary projections, and independent in-depth biophysical characterization experiments to define the functional significance of ligand interfaces.
View Article and Find Full Text PDFA Vibration Signal-Based Active Noise Control Method for Liquid-Filled Pipelines.
Sensors (Basel)
January 2025
Laboratory of Vibration and Noise, Naval University of Engineering, Wuhan 430033, China.
Pulsation noise in the piping system generated by the excitation of the pump source seriously affects the reliability of the pipeline system and mechanical equipment. The active noise control can effectively suppress the low-frequency noise in the liquid-filled pipeline. Active control methods with intrusive secondary sources generally use dynamic pressure sensors or hydrophones to collect signals, which destroy the structure of the pipe.
View Article and Find Full Text PDFResearch on a Novel Unsupervised-Learning-Based Pipeline Leak Detection Method Based on Temporal Kolmogorov-Arnold Network with Autoencoder Integration.
Sensors (Basel)
January 2025
College of Energy and Power Engineering, Xihua University, Chengdu 610039, China.
Artificial intelligence (AI) technologies have been widely applied to the automated detection of pipeline leaks. However, traditional AI methods still face significant challenges in effectively detecting the complete leak process. Furthermore, the deployment cost of such models has increased substantially due to the use of GPU-trained neural networks in recent years.
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