In this paper, a versatile multi-body dynamic algorithm is developed to integrate an incompressible fluid flow with a bio-inspired multibody dynamic system. Of particular interest to the biomimetic application, the algorithm is developed via four properly selected benchmark verifications. The present tool has shown its powerful capability for solving a variety of biomechanics fish swimming problems, including self-propelled multiple degrees of freedom with a rigid undulatory body, multiple deformable fins and an integrated system with both undulatory fish body and flexible fins. The established tool has paved the way for future investigation on more complex bio-inspired robots and live fish, for either propulsion or manoeuvring purposes.
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http://dx.doi.org/10.1088/1748-3190/aacd60 | DOI Listing |
Genome Med
January 2025
Blizard Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK.
Background: Senescence classification is an acknowledged challenge within the field, as markers are cell-type and context dependent. Currently, multiple morphological and immunofluorescence markers are required. However, emerging scRNA-seq datasets have enabled an increased understanding of senescent cell heterogeneity.
View Article and Find Full Text PDFCancer Cell Int
January 2025
Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510080, China.
Background: Patients with lung adenocarcinoma (LUAD) receiving drug treatment often have an unpredictive response and there is a lack of effective methods to predict treatment outcome for patients. Dendritic cells (DCs) play a significant role in the tumor microenvironment and the DCs-related gene signature may be used to predict treatment outcome. Here, we screened for DC-related genes to construct a prognostic signature to predict prognosis and response to immunotherapy in LUAD patients.
View Article and Find Full Text PDFJ Transl Med
January 2025
School of Information and Communication Engineering, Dalian University of Technology, No. 2 Linggong Road, 116024, Dalian, China.
Background: Parkinson's Disease (PD) is a neurodegenerative disorder, and eye movement abnormalities are a significant symptom of its diagnosis. In this paper, we developed a multi-task driven by eye movement in a virtual reality (VR) environment to elicit PD-specific eye movement abnormalities. The abnormal features were subsequently modeled by using the proposed deep learning algorithm to achieve an auxiliary diagnosis of PD.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Department of Pharmacy, Hangzhou Third People's Hospital, Hangzhou Third Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Background: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is not well understood, and there is no targeted therapy available for AA. METHODS: In this study, differential gene expression analysis, immune status assessment, weighted correlation network analysis (WGCNA), and functional enrichment analysis were performed to identify shared genes associated with both immunological response and AA.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Pediatric Dentistry Department, Faculty of Dentistry, Başkent University, 06490, Ankara, Turkey.
Background: Hypodontia is the absence of one or more teeth in the primary or permanent dentition during development, and radiographic imaging is the most common method of diagnosis. However, in recent years, artificial intelligence-based decision support systems have been employed to make highly accurate diagnoses. The aim of this study was to classify single premolar agenesis, multiple premolar agenesis, and without tooth agenesis using various artificial intelligence approaches.
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