Targeting Key Risk Factors for Cardiovascular Disease in At-Risk Individuals: Developing a Digital, Personalized, and Real-Time Intervention to Facilitate Smoking Cessation and Physical Activity.

Health care is under pressure due to an aging population with an increasing prevalence of chronic diseases, including cardiovascular disease. Smoking and physical inactivity are 2 key preventable risk factors for cardiovascular disease. Yet, as with most health behaviors, they are difficult to change.

Investigating eHealth Lifestyle Interventions for Vulnerable Pregnant Women: Scoping Review of Facilitators and Barriers.

Background: The maintenance of a healthy lifestyle significantly influences pregnancy outcomes. Certain pregnant women are more at risk of engaging in unhealthy behaviors due to factors such as having a low socioeconomic position and low social capital. eHealth interventions tailored to pregnant women affected by these vulnerability factors can provide support and motivation for healthier choices.

Understanding microbial syngas fermentation rates.

Syngas fermentation to ethanol has reached industrial production. Further improvement of this process would be aided by quantitative understanding of the influence of imposed reaction conditions on the fermentation performance. That requires a reliable model of the microbial kinetics.

autoMEA: machine learning-based burst detection for multi-electrode array datasets.

Neuronal activity in the highly organized networks of the central nervous system is the vital basis for various functional processes, such as perception, motor control, and cognition. Understanding interneuronal connectivity and how activity is regulated in the neuronal circuits is crucial for interpreting how the brain works. Multi-electrode arrays (MEAs) are particularly useful for studying the dynamics of neuronal network activity and their development as they allow for real-time, high-throughput measurements of neural activity.

Exploring the metabolic potential of to utilise the carbohydrate polymer chitin.

Members of the genus are commonly found in natural aquatic ecosystems. However, they are also frequently present in non-chlorinated drinking water distribution systems. High densities of these bacteria indicate favorable conditions for microbial regrowth, which is considered undesirable.

The Impact of Bridging Additives on Wellbore Strengthening in Shallow Unconsolidated Formations.

Drilling wells in unconsolidated formations is commonly undertaken to extract drinking water and other applications, such as aquifer thermal energy storage (ATES). To increase the efficiency of an ATES system, the drilling campaigns are targeting greater depths and enlarging the wellbore diameter in the production section to enhance the flow rates. In these cases, wells are more susceptible to collapse.

An open source autoregulation-based neuromonitoring algorithm shows PRx and optimal CPP association with pediatric traumatic brain injury.

This study aimed to develop an open-source algorithm for the pressure-reactivity index (PRx) to monitor cerebral autoregulation (CA) in pediatric severe traumatic brain injury (sTBI) and compared derived optimal cerebral perfusion pressure (CPPopt) with real-time CPP in relation to long-term outcome. Retrospective study in children (< 18 years) with sTBI admitted to the pediatric intensive care unit (PICU) for intracranial pressure (ICP) monitoring between 2016 and 2023. ICP was analyzed on an insult basis and correlated with outcome.

Ferrocene-decorated graphene nanosheets built by edge-to-face π-π interaction for room temperature ppb-level NO sensing.

The development of materials toward ppb-level nitric oxide (NO) sensing at room temperature remains in high demand for the monitoring of respiratory inflammatory diseases. In order to find an iron-containing molecule without steric hindrance to combine with graphene for room temperature NO gas sensing, here a supramolecular assembly of ferrocene (Fc) and reduced graphene oxide (rGO) was designed and prepared for NO sensing. The assembly of Fc/rGO was characterized using FT-IR, TEM, and XPS measurements.

A handheld fiber-optic tissue sensing device for spine surgery.

The demographic shift has increased the demand for surgical interventions to address age-related degenerative diseases, such as spinal fusion. Accurate placement of pedicle screws, crucial for successful spinal fusion, varies widely with physician experience. Integrating tissue sensing into spine surgical instruments allows intraoperative examination of tissue properties, providing surgeons with additional information to prevent screw misplacement.

A curved compliant spinal bone anchor to enhance fixation strength.

Pedicle screws have long been established as the gold standard for spinal bone fixation. However, their fixation strength can be compromised in cases of low bone density, particularly in osteoporotic bone, due to the reliance on a micro-shape lock between the screw thread and the surrounding bone. To address this challenge, we propose augmenting conventional pedicles screws with a curved compliant anchor.

Exploring shape changes in healthy bone growth through 3D spatiotemporal statistical shape models: A scoping review.

Objective: Analyzing population trends of bone shape variation can provide valuable insights into growth processes. This review aims to overview state-of-the-art spatiotemporal statistical shape modeling techniques, emphasizing their application to 3D skeletal structures during healthy growth.

Methods: We searched PubMed and Scopus for articles on statistical shape modeling using a pediatric spatiotemporal dataset of 3D healthy bone models.

Advanced 3D-Printed Flexible Composite Electrodes of Diamond, Carbon Nanotubes, and Thermoplastic Polyurethane.

In this work, we pioneered the preparation of diamond-containing flexible electrodes using 3D printing technology. The herein developed procedure involves a unique integration of boron-doped diamond (BDD) microparticles and multi-walled carbon nanotubes (CNTs) within a flexible polymer, thermoplastic polyurethane (TPU). Initially, the process for the preparation of homogeneous filaments with optimal printability was addressed, leading to the development of two TPU/CNT/BDD composite electrodes with different CNT:BDD weight ratios (1:1 and 1:2), which were benchmarked against a TPU/CNT electrode.

Enhancing Magnetic Hyperthermia Efficiency in Pd/Fe-Oxide Hybrid Nanoparticles through Mn-Doping.

Multifunctional, biocompatible magnetic materials, such as iron oxide nanoparticles (IONPs), hold great potential for biomedical applications including diagnostics (e.g., MRI) and cancer therapy.

Inverse design of copolymers including stoichiometry and chain architecture.

The demand for innovative synthetic polymers with improved properties is high, but their structural complexity and vast design space hinder rapid discovery. Machine learning-guided molecular design is a promising approach to accelerate polymer discovery. However, the scarcity of labeled polymer data and the complex hierarchical structure of synthetic polymers make generative design particularly challenging.

Feasibility of relaxation along a fictitious field in the 2nd rotating frame (T) mapping in the human myocardium at 3 T.

Purpose: Evaluate the feasibility of quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame (RAFF2) relaxation times in the human myocardium at 3 T.

Methods: mapping was performed using a breath-held ECG-gated acquisition of five images: one without preparation, three preceded by RAFF2 trains of varying duration, and one preceded by a saturation prepulse. Pixel-wise maps were obtained after three-parameter exponential fitting.

Reactive vapor-phase dealloying-alloying turns oxides into sustainable bulk nano-structured porous alloys.

For millennia, alloying has been the greatest gift from metallurgy to humankind: a process of mixing elements, propelling our society from the Bronze Age to the Space Age. Dealloying, by contrast, acts like a penalty: a corrosive counteracting process of selectively removing elements from alloys or compounds, degrading their structural integrity over time. We show that when these two opposite metallurgical processes meet in a reactive vapor environment, profound sustainable alloy design opportunities become accessible, enabling bulk nanostructured porous alloys directly from oxides, with zero carbon footprint.

Development of a standard set of key work-related outcomes for use in practice for patients with cardiovascular disease: a modified Delphi study.

Background: To facilitate the maintenance or resumption of participation in work for patients with cardiovascular disease (CVD), there is a need for high-quality work-focused healthcare. According to the concept of value-based healthcare, quality of care can be enhanced by understanding the outcomes that matter most to patients. However, a major challenge in assessing quality of work-focused healthcare in practice is the lack of consensus on which work-related outcomes should be measured.

Automated noise modelling using a triangulated terrain model.

Noise simulations are an important part of noise studies that investigate the impact of noise sources on the environment. In noise simulation, noise levels at receiver points are calculated based on the noise propagation paths between the receiver and source points. These paths are derived from the height of the terrain.

Effects of antibiotic growth promoter and its natural alternative on poultry cecum ecosystem: an integrated analysis of gut microbiota and host expression.

Background: In-feed antibiotic growth promoters (AGPs) have been a cornerstone in the livestock industry due to their role in enhancing growth and feed efficiency. However, concerns over antibiotic resistance have driven a shift away from AGPs toward natural alternatives. Despite the widespread use, the exact mechanisms of AGPs and alternatives are not fully understood.

Vector-flow imaging of slowly moving blood with photoacoustics and pulse-echo ultrasound.

We present a technique called photoacoustic vector-flow (PAVF) to quantify the speed and direction of flowing optical absorbers at each pixel from acoustic-resolution PA images. By varying the receiving angle at each pixel in post-processing, we obtain multiple estimates of the phase difference between consecutive frames. These are used to solve the overdetermined photoacoustic Doppler equation with a least-squares approach to estimate a velocity vector at each pixel.

A dataset to train intrusion detection systems based on machine learning models for electrical substations.

The growing integration of Information and Communication Technology into Operational Technology environments in electrical substations exposes them to new cybersecurity threats. This paper presents a comprehensive dataset of substation traffic, aimed at improving the training and benchmarking of Intrusion Detection Systems (IDS) installed in these facilities that are based on machine learning techniques. The dataset includes raw network captures and flows from real substations, filtered and anonymized to ensure privacy.

AI-Guided Inverse Design and Discovery of Recyclable Vitrimeric Polymers.

Vitrimer is a new, exciting class of sustainable polymers with healing abilities due to their dynamic covalent adaptive networks. However, a limited choice of constituent molecules restricts their property space and potential applications. To overcome this challenge, an innovative approach coupling molecular dynamics (MD) simulations and a novel graph variational autoencoder (VAE) model for inverse design of vitrimer chemistries with desired glass transition temperature (T) is presented.

Viscoelastic Behavior of Cellular Biomaterials Based on Octet-Truss and Tetrahedron Topologies.

Cellular biomaterials offer unique properties for diverse biomedical applications. However, their complex viscoelastic behavior requires careful consideration for design optimization. This study explores the effective viscoelastic response of two promising unit cell designs (tetrahedron-based and octet-truss) suitable for high porosity and strong mechanics.

Order-Disorder Balance in Silk-Elastin-like Polypeptides Determines Their Self-Assembly into Hydrogel Networks.

The biofabrication of recombinant structural proteins with a range of mechanical or structural features usually relies on the generation of protein libraries displaying variations in terms of amino acid composition, block structure, molecular weight, or physical/chemical cross-linking sites. This approach, while highly successful in generating a wealth of knowledge regarding the links between design features and material properties, has some inherent limitations related to its low throughput. This slows down the pace of the development of recombinant structural proteins.

2D Carbon Phosphide for Trapping Sulfur in Rechargeable Li-S Batteries: Structure Design and Interfacial Chemistry.

Rechargeable lithium-sulfur batteries (LiSBs) assembled with earth-abundant and safe Li anodes are less prone to form dendrites on the surface, and sulfur-containing cathodes offer considerable potential for achieving high energy densities. Nevertheless, suitable sulfur host materials and their interaction with electrolytes are at present key factors that retard the commercial introduction of these batteries. Here we propose a two-dimensional metallic carbon phosphorus framework, namely, 2D CP, as a promising sulfur host material for inhibiting the shuttle effect and improving electronic conductivity in high-performance Li-S batteries.