- 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).

Audiometric results of tympanoplasty with stapedectomy and synthetic total ossicular replacement prosthesis: A STROBE analysis.

Aim: To evaluate the audiometric results of tympanoplasty with stapedectomy and insertion of a synthetic total ossicular replacement prosthesis (TORP).

Material And Methods: Retrospective observational study conducted on a cohort of 15 patients (16 ears) aged 10 to 58 years (mean: 36 years) with chronic otitis media (COM) and tympanosclerosis (n=9), stapediovestibular ankylosis (n=3), minor aplasia (n=3) or post-traumatic ossicular dislocation (n=1). Treatment consisted in tympanoplasty with stapedectomy and TORP placement by the same operator, between December 1, 2012 and January 30, 2023, in a French university hospital department, with follow-up ranging from 2 to 92 months (mean: 24 months).

Evaluation of balloon and self-expandable stents for common femoral artery stenosis.

Background: Endovascular treatment of the common femoral artery (CFA) and its bifurcation is currently recommended for patients with hostile groin (prior femoral bifurcation open surgery, history of radiotherapy) or severe comorbidities (advanced age, frailty, obesity). Preliminary results have shown favorable outcomes. Among the different endovascular techniques (atherectomy, intravascular lithotripsy, plain balloon angioplasty, drug-coated balloon angioplasty, stenting), stents are mainly used but the best type of stent to use is still debated.

Automatic Classification of Nodules from 2D Ultrasound Images Using Deep Learning Networks.

Objective: In clinical practice, thyroid nodules are typically visually evaluated by expert physicians using 2D ultrasound images. Based on their assessment, a fine needle aspiration (FNA) may be recommended. However, visually classifying thyroid nodules from ultrasound images may lead to unnecessary fine needle aspirations for patients.

Pharmacological induction of the hypoxia response pathway in Huh7 hepatoma cells limits proliferation but increases resilience under metabolic stress.

The hypoxia response pathway enables adaptation to oxygen deprivation. It is mediated by hypoxia-inducible factors (HIF), which promote metabolic reprogramming, erythropoiesis, angiogenesis and tissue remodeling. This led to the successful development of HIF-inducing drugs for treating anemia and some of these molecules are now in clinic.

Serum ARGS-aggrecan in a phase 2 clinical trial targeting osteoarthritis.

Objective: To monitor serum concentrations of the aggrecan alanine-arginine-glycine-serine (ARGS) neoepitope in a clinical trial of a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)-5 inhibition as disease-modifying therapy of knee osteoarthritis, and to investigate relationships between reduction in ARGS and change in cartilage thickness, knee-related pain and function.

Design: ROCCELLA trial participants received once-daily oral S201086 75, 150 or 300 mg, or placebo, for 52 weeks. Serum was collected at baseline, 4, 12, 28 and 52 weeks, and 2 weeks post-treatment with ARGS measured by an in-house immunoassay.

Evaluating Patient Experience with Food in a Hospital-Wide Survey.

Patient dissatisfaction with hospital food is an important driver of poor food intake in hospitals. The objective of this study was to examine patient satisfaction with current menu offerings and explore patient preferences and values, in order to inform a patient-centred menu redesign. Between July and September 2021, a cross-sectional survey was distributed to inpatients receiving a lunch tray at Vancouver General Hospital, a large tertiary care centre in Vancouver, Canada.

Improving staff wellness via an after-hours healthy sustainable meals program: A general surgery residency pilot.

Healthcare worker wellness is foundational to delivering quality care. Yet, healthcare facilities often lack access to healthy and sustainable food overnight and on weekends. Healthy, low-carbon meals were provided free of charge after hours to on-call General Surgery residents at the University of British Columbia and the impact on resident well-being assessed using pre- and post-intervention surveys.

The low-density lipoprotein receptor and apolipoprotein E associated with CCHFV particles mediate CCHFV entry into cells.

The Crimean-Congo hemorrhagic fever virus (CCHFV) is an emerging pathogen of the Orthonairovirus genus that can cause severe and often lethal hemorrhagic diseases in humans. CCHFV has a broad tropism and can infect a variety of species and tissues. Here, by using gene silencing, blocking antibodies or soluble receptor fragments, we identify the low-density lipoprotein receptor (LDL-R) as a CCHFV entry factor.

The PACS-2 protein and trafficking motifs in CCHFV Gn and Gc cytoplasmic domains govern CCHFV assembly.

The Crimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne bunyavirus that causes high mortality in humans. This enveloped virus harbors two surface glycoproteins (GP), Gn and Gc, that are released by processing of a glycoprotein precursor complex whose maturation takes place in the ER and is completed through the secretion pathway. Here, we characterized the trafficking network exploited by CCHFV GPs during viral assembly, envelopment, and/or egress.

Carbon savings potential of virtual care in obstructive sleep apnea and otitis media with effusion.

Objective: To determine the carbon savings potential of incorporating virtual care into surgical care pathways for pediatric patients with obstructive sleep apnea or otitis media with effusion.

Methods: Pediatric patients with obstructive sleep apnea or otitis media with effusion were not enrolled, instead, a modeling cohort study design was used. This study utilized the British Columbia healthcare system and geography to model emissions.

The catabolism of lignin-derived -methoxylated aromatic compounds by RHA1.

Emergent strategies to valorize lignin, an abundant but underutilized aromatic biopolymer, include tandem processes that integrate chemical depolymerization and biological catalysis. To date, aromatic monomers from C-O bond cleavage of lignin have been converted to bioproducts, but the presence of recalcitrant C-C bonds in lignin limits the product yield. A promising chemocatalytic strategy that overcomes this limitation involves phenol methyl protection and autoxidation.

Deep learning application for abdominal organs segmentation on 0.35 T MR-Linac images.

Introduction: Linear accelerator (linac) incorporating a magnetic resonance (MR) imaging device providing enhanced soft tissue contrast is particularly suited for abdominal radiation therapy. In particular, accurate segmentation for abdominal tumors and organs at risk (OARs) required for the treatment planning is becoming possible. Currently, this segmentation is performed manually by radiation oncologists.

Registration of preoperative temporal bone CT-scan to otoendoscopic video for augmented-reality based on convolutional neural networks.

Purpose: Patient-to-image registration is a preliminary step required in surgical navigation based on preoperative images. Human intervention and fiducial markers hamper this task as they are time-consuming and introduce potential errors. We aimed to develop a fully automatic 2D registration system for augmented reality in ear surgery.

A Generative Adversarial Network to Synthesize 3D Magnetohydrodynamic Distortions for Electrocardiogram Analyses Applied to Cardiac Magnetic Resonance Imaging.

Recently, deep learning (DL) models have been increasingly adopted for automatic analyses of medical data, including electrocardiograms (ECGs). Large, available ECG datasets, generally of high quality, often lack specific distortions, which could be helpful for enhancing DL-based algorithms. Synthetic ECG datasets could overcome this limitation.

Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study.

Objectives: To efficiently assess the disease-modifying potential of new osteoarthritis treatments, clinical trials need progression-enriched patient populations. To assess whether the application of machine learning results in patient selection enrichment, we developed a machine learning recruitment strategy targeting progressive patients and validated it in the IMI-APPROACH knee osteoarthritis prospective study.

Design: We designed a two-stage recruitment process supported by machine learning models trained to rank candidates by the likelihood of progression.

Image-to-Patient Registration in Computer-Assisted Surgery of Head and Neck: State-of-the-Art, Perspectives, and Challenges.

Today, image-guided systems play a significant role in improving the outcome of diagnostic and therapeutic interventions. They provide crucial anatomical information during the procedure to decrease the size and the extent of the approach, to reduce intraoperative complications, and to increase accuracy, repeatability, and safety. Image-to-patient registration is the first step in image-guided procedures.

FUTIs: an In-Person or Online Graphing, Bioinformatics, and Scientific Literacy Exercise That Explores the Presence of Antibiotic Resistance in Foodborne Urinary Tract Infections.

We developed a course-based undergraduate research experience (CURE) that gives students an opportunity to practice the process of science in a context that intersects with their everyday lives: purchasing grocery store chicken. Student mastery of concepts was assessed by pre- and postassessment questions and lab report worksheets that guided them through the process of writing a scientific paper. Learning to produce graphs from large data sets and comparing the results with published data emphasized quantitative reasoning, while working as a group and writing helped students practice scientific communication.

Tracking of Blood Vessels Motion from 4D-flow MRI Data.

This paper presents a novel approach to track objects from 4D-flow MRI data. A salient feature of the proposed method is that it fully exploits the geometrical and dynamical nature of the information provided by this imaging modality. The underlying idea consists in formulating the tracking problem as a data assimilation problem, in which both position and velocity observations are extracted from the 4D-flow MRI data series.

Patient, hospital and environmental costs of unnecessary bloodwork: capturing the triple bottom line of inappropriate care in general surgery patients.

Objective: To characterise the extent of unnecessary care in general surgery inpatients using a triple bottom line approach.

Design: Patients with uncomplicated acute surgical conditions were retrospectively evaluated for unnecessary bloodwork according to the triple bottom line, quantifying the impacts on patients, healthcare costs and greenhouse gas emissions. The carbon footprint of common laboratory investigations was estimated using PAS2050 methodology, including emissions generated from the production, transport, processing and disposal of consumable goods and reagents.

Calibration of the Mechanical Boundary Conditions for a Patient-Specific Thoracic Aorta Model Including the Heart Motion Effect.

Objective: We propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect.

Methods: We first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI.

Segmentation of 4D Flow MRI: Comparison between 3D Deep Learning and Velocity-Based Level Sets.

A thoracic aortic aneurysm is an abnormal dilatation of the aorta that can progress and lead to rupture. The decision to conduct surgery is made by considering the maximum diameter, but it is now well known that this metric alone is not completely reliable. The advent of 4D flow magnetic resonance imaging has allowed for the calculation of new biomarkers for the study of aortic diseases, such as wall shear stress.

Biomechanical properties of 3D printable material usable for synthetic personalized healthy human aorta.

With the development of three-dimensional (3D) printing, 3D-printed products have been widely used in medical fields, such as plastic surgery, orthopedics, dentistry, . In cardiovascular research, 3D-printed models are becoming more realistic in shape. However, from a biomechanical point of view, only a few studies have explored printable materials that can represent the properties of the human aorta.