Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy.

Reducing electrophysiological (EP) signal noise is essential for diagnosis, mapping, and ablation, yet traditional approaches are suboptimal. This study tests the hypothesis that generative artificial intelligence (AI), specifically Variational Autoencoders (VAEs), can effectively denoise these signals by forming robust internal representations of 'clean' signals. Utilizing a dataset of 5706 time series from 42 patients with ischemic cardiomyopathy at risk of cardiac sudden death, we set out to apply a β-VAE model to denoise and reconstruct intra-ventricular monophasic action potential (MAP) signals, which have verifiable morphology.

The significance of PAX5 in Merkel cell carcinoma.

Merkel cell carcinoma (MCC) is a highly malignant skin cancer that expresses epithelial-, neuroendocrine-, and lymphoid-associated genes. Here, we focused on B-cell differentiation, which is characterised by the coexpression of PAX5 and TdT. PAX5 is the master regulator of B-cell commitment and is expressed in 65% of MCC cases.

Suppression of Fibroblast Growth Factor 23 in UMR106 Osteoblast-Like Cells and MC3T3-E1 Cells by Adipokine Chemerin.

Endocrine fibroblast growth factor 23 (FGF23) derived from bone governs phosphate and vitamin D metabolism. Paracrine FGF23 has additional functions in different organs. Moreover, plasma FGF23 is correlated with outcomes in chronic kidney disease.

AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation.

The primary practice of healthcare artificial intelligence (AI) starts with model development, often using state-of-the-art AI, retrospectively evaluated using metrics lifted from the AI literature like AUROC and DICE score. However, good performance on these metrics may not translate to improved clinical outcomes. Instead, we argue for a better development pipeline constructed by working backward from the end goal of positively impacting clinically relevant outcomes using AI, leading to considerations of causality in model development and validation, and subsequently a better development pipeline.

Paediatric Personalized Research Network Switzerland (SwissPedHealth): a joint paediatric national data stream.

Introduction: Children represent a large and vulnerable patient group. However, the evidence base for most paediatric diagnostic and therapeutic procedures remains limited or is often inferred from adults. There is an urgency to improve paediatric healthcare provision based on real-world evidence generation.

Comparison of 2D and 3D lung lobe quantification with Ventilation/Perfusion Ratio.

In this study, standard 2D lung lobe quantification is compared with two 3D lung lobe quantification software tools to investigate the clinical benefit of a 3D approach. The accuracy of 2D versus 3D lung lobe quantification is evaluated based on the calculated numerical ventilation-perfusion ratio (VQR) using a receiver operating curve (ROC) analysis.A study group of 50 consecutive patients underwent a planar lung scintigraphy (anterior/posterior) as well as ventilation/perfusion single photon emission computed tomography (SPECT/CT) to exclude acute pulmonary embolism.

The art of selecting the ECG input in neural networks to classify heart diseases: a dual focus on maximizing information and reducing redundancy.

Background And Objectives: Accurate diagnosis of cardiovascular diseases often relies on the electrocardiogram (ECG). Since the cardiac vector is located within a three-dimensional space and the standard ECG comprises 12 projections or leads derived from it, redundant information is inherently present. This study aims to quantify this redundancy and its impact on classification tasks using Convolutional Neural Networks (CNNs) in cardiovascular diseases.

Improving quantitative neuromuscular monitoring: an education initiative on stimulating electrode placement.

Quantitative neuromuscular monitoring reduces the incidence of residual neuromuscular block, but broad acceptance of monitoring has been elusive despite recommendations for quantitative monitoring for decades. Acceptance of quantitative monitoring may, in part, be related to the quality of the data from monitoring systems. This evaluation explored proper stimulating electrode positioning for electromyographic (EMG) monitoring, the impact of an educational intervention on electrode positioning and anesthesia provider (anesthesiologist, resident, anesthetist) confidence in the monitoring data from the device.

Train-of-four ratio, counts and post tetanic counts with the Tetragraph electromyograph in comparison to mechanomyography.

Automated EMG devices to detect compound muscle action potentials from the adductor pollicis muscle in response to ulnar nerve stimulation, regardless of hand and thumb position, may serve as a better reference ("gold standard") for clinical assessment of neuromuscular function than traditional mechanomyography (MMG) systems that need custom design and validation in lab settings. This evaluation compared the TetraGraph EMG system against a validated MMG device to investigate the accuracy and repeatability of this quantitative EMG monitor for detecting onset, offset and deep neuromuscular block. Simultaneous muscle action potential recordings from the EMG neuromuscular monitor and muscle contractions from an in-house developed MMG monitor in response to ulnar nerve stimulation were obtained from patients having elective surgery requiring neuromuscular block.

AMP-dependent kinase stimulates the expression of αKlotho.

Renal αKlotho along with fibroblast growth factor 23 regulates phosphate and vitamin D metabolism. Its cleavage yields soluble Klotho controlling intracellular processes. αKlotho has anti-inflammatory and antioxidant effects and is nephro- and cardioprotective.

Computational Decision Support for PE Diagnosis based on Ventilation Perfusion Ratio.

Aim: The aim of this study is to investigate whether computer-aided, semi-automated 3D lung lobe quantification can support decision-making on PE diagnosis based on the ventilation-perfusion ratio in clinical practice.

Methods: A study cohort of 100 patients (39 male, 61 female, age 64.8±15.

European Joint Programme on Rare Diseases workshop: LAMA2-muscular dystrophy: paving the road to therapy March 17-19, 2023, Barcelona, Spain.

The European Joint Programme on Rare Diseases (EJPRD) funded the workshop "LAMA2-Muscular Dystrophy: Paving the road to therapy", bringing together 40 health-care professionals, researchers, patient-advocacy groups, Early-Career Scientists and other stakeholders from 14 countries. Progress in natural history, pathophysiology, trial readiness, and treatment strategies was discussed together with efforts to increase patient-awareness and strengthen collaborations. Key outcomes were (a) ongoing natural history studies in 7 countries already covered more than 350 patients.

Endothelin receptor B-deficient mice are protected from high-fat diet-induced metabolic syndrome.

Objective: Endothelin receptor B (ETB) together with ETA mediates cellular effects of endothelin 1 (ET-1), an autocrine and endocrine peptide produced by the endothelium and other cells. It regulates vascular tone and controls kidney function. Metabolic syndrome is due to high caloric intake and is characterized by insulin resistance, dyslipidemia, and white adipose tissue (WAT) accumulation.

Blood glucose forecasting from temporal and static information in children with T1D.

Background: The overarching goal of blood glucose forecasting is to assist individuals with type 1 diabetes (T1D) in avoiding hyper- or hypoglycemic conditions. While deep learning approaches have shown promising results for blood glucose forecasting in adults with T1D, it is not known if these results generalize to children. Possible reasons are physical activity (PA), which is often unplanned in children, as well as age and development of a child, which both have an effect on the blood glucose level.

Unveiling Consumer Preferences and Intentions for Cocreated Features of a Combined Diet and Physical Activity App: Cross-Sectional Study in 4 European Countries.

Background: Numerous mobile health apps are marketed globally, and these have specific features including physical activity tracking, motivational feedback, and recipe provision. It is important to understand which features individuals prefer and whether these preferences differ between consumer groups.

Objective: In this study, we aimed to identify consumers' most preferred features and rewards for a mobile app that targets healthy eating and physical activity and to reduce the number of individual mobile health app features to a smaller number of key categories as perceived by consumers.

Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis.

Appendicitis is among the most frequent reasons for pediatric abdominal surgeries. Previous decision support systems for appendicitis have focused on clinical, laboratory, scoring, and computed tomography data and have ignored abdominal ultrasound, despite its noninvasive nature and widespread availability. In this work, we present interpretable machine learning models for predicting the diagnosis, management and severity of suspected appendicitis using ultrasound images.

A mixed-methods approach to understanding barriers and facilitators to healthy eating and exercise from five European countries: highlighting the roles of enjoyment, emotion and social engagement.

Healthy adults are consistently falling below national and international recommendations for physical activity and dietary intake across Europe. This study took a co-creative approach with adult samples from five European countries to qualitatively and quantitatively establish motivators, barriers and sustaining factors for positive health behaviour change. Stage 1 delivered a newly-designed online programme, creating a community who identified challenges, motivators and solutions to sustaining positive healthy eating and physical activity behaviours.

Validating the early phototherapy prediction tool across cohorts.

Background: Hyperbilirubinemia of the newborn infant is a common disease worldwide. However, recognized early and treated appropriately, it typically remains innocuous. We recently developed an early phototherapy prediction tool (EPPT) by means of machine learning (ML) utilizing just one bilirubin measurement and few clinical variables.

PKC regulates αKlotho gene expression in MDCK and NRK-52E cells.

Particularly expressed in the kidney, αKlotho is a transmembrane protein that acts together with bone hormone fibroblast growth factor 23 (FGF23) to regulate renal phosphate and vitamin D homeostasis. Soluble Klotho (sKL) is released from the transmembrane form and controls various cellular functions as a paracrine and endocrine factor. αKlotho deficiency accelerates aging, whereas its overexpression favors longevity.

Machine learning analysis of humoral and cellular responses to SARS-CoV-2 infection in young adults.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces B and T cell responses, contributing to virus neutralization. In a cohort of 2,911 young adults, we identified 65 individuals who had an asymptomatic or mildly symptomatic SARS-CoV-2 infection and characterized their humoral and T cell responses to the Spike (S), Nucleocapsid (N) and Membrane (M) proteins. We found that previous infection induced CD4 T cells that vigorously responded to pools of peptides derived from the S and N proteins.

Co-Culture of Mesenchymal Stem Cells and Ligamentocytes on Triphasic Embroidered Poly(L-lactide-co-ε-caprolactone) and Polylactic Acid Scaffolds for Anterior Cruciate Ligament Enthesis Tissue Engineering.

Successful anterior cruciate ligament (ACL) reconstructions strive for a firm bone-ligament integration. With the aim to establish an enthesis-like construct, embroidered functionalized scaffolds were colonized with spheroids of osteogenically differentiated human mesenchymal stem cells (hMSCs) and lapine (l) ACL fibroblasts in this study. These triphasic poly(L-lactide-co-ε-caprolactone) and polylactic acid (P(LA-CL)/PLA) scaffolds with a bone-, a fibrocartilage transition- and a ligament zone were colonized with spheroids directly after assembly (DC) or with 14-day pre-cultured lACL fibroblast and 14-day osteogenically differentiated hMSCs spheroids (=longer pre-cultivation, LC).

Multimodal Remote Home Monitoring of Lung Transplant Recipients during COVID-19 Vaccinations: Usability Pilot Study of the COVIDA Desk Incorporating Wearable Devices.

: Remote patient monitoring (RPM) of vital signs and symptoms for lung transplant recipients (LTRs) has become increasingly relevant in many situations. Nevertheless, RPM research integrating multisensory home monitoring in LTRs is scarce. We developed a novel multisensory home monitoring device and tested it in the context of COVID-19 vaccinations.