- a large-scale dataset of 3D medical shapes for computer vision.

Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models).

Discovering Influenza Virus Neuraminidase Inhibitors via Computational and Experimental Studies.

Influenza A and B viruses spread out worldwide, causing several global concerns. Discovering neuraminidase inhibitors to prevent influenza A and B viruses is thus of great interest. In this work, a machine learning model was trained and tested to evaluate the ligand-binding affinity to neuraminidase.

Re-identification of anonymised MRI head images with publicly available software: investigation of the current risk to patient privacy.

Background: Facial recognition software (FRS) has historically been perceived as lacking the capability to identify individuals from cross-sectional medical images. Utilising such data for identification purposes was considered infeasible due to the substantial computational power and specialised technical expertise it would require. However, recent advancements in accessible artificial intelligence-based (AI-based) software and open-source tools have made these applications widely available and easy to use, raising new privacy concerns.

Fear and Impact of COVID-19 Among Post-Infected Adults: Types and Associations with Quality of Life and Post-Traumatic Stress Symptoms.

Survivors of COVID-19 are susceptible to diminished health-related quality of life (HRQoL) and adverse psychological health, which may be exacerbated by their experiences of fear and the impact of the pandemic itself. This study aims to identify distinct fear and impact patterns related to the COVID-19 pandemic among survivors through latent profile analysis (LPA) and examine the associations of fear and impact patterns with post-traumatic stress symptoms (PTSS) and HRQoL. A total of 5,890 Vietnamese COVID-19 survivors completed the COVID-19 Impact Battery- Disability Scale (CIB-D), the Fear of COVID-19 Scale (FCoV-19 S), the Impact of Event Scale-Revised for PTSS, and the 36-Item Short Form Survey (SF-36) for HRQoL.

Transmembrane E3 ligase RNF128 regulates N-glycosylation by promoting ribophorin I ubiquitination and degradation.

Ring finger protein 128 (RNF128) is a transmembrane E3 ubiquitin ligase mainly localized in to the endoplasmic reticulum that is involved in various processes, including T cell anergy and tumor progression. However, the biological function of RNF128 in N-glycosylation remains unexplored. To investigate the functional role of RNF128, we used the proximity-directed biotin labeling method, and identified ribophorin I (RPN1) as a novel RNF128 substrate, demonstrating that RNF128 ubiquitinated RPN1 and promoted its degradation.