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.

Advancements in microneedle technology: current status and next-generation innovations.

Microneedle technology is a pivotal component of third-generation transdermal drug delivery systems featuring tiny needles that create temporary microscopic channels in the stratum corneum which facilitate drug penetration in the dermis. This review offers a detailed examination of the current types of microneedles, including solid, coated, dissolving, hollow, and swelling microneedles, along with their preparation techniques as well as their benefits and challenges. Use of 3D printing technology is especially gaining significant attention due to its ability to achieve the high dimensional accuracy required for precise fabrication.

Organo Chalcogenone-Triggered Luminescent Copper(I) Clusters for Light Emitting Applications.

A novel organo sulfur and selenium-controlled emission behavior in discrete copper(I) clusters has been demonstrated for the first time. The pentanuclear [CuBr()] (), trinuclear [CuBr()] (), dinuclear [CuI()] (), and tetranuclear [CuI()CHCN] () copper(I) discrete clusters have been synthesized from the reaction between [ = 1-isopropyl-3-(pyridin-2-yl)-imidazol-2-thione] or [ = 1-isopropyl-3-(pyridin-2-yl)-imidazol-2-selone] chelating ligands and corresponding copper(I) halide salts. These new clusters have been characterized by FT-IR, UV-visible, thermogravimetric analysis, and fluorescence spectroscopy techniques.

AI-Enabled Materials Design of Non-Periodic 3D Architectures With Predictable Direction-Dependent Elastic Properties.

Natural porous materials have exceptional properties-for example, light weight, mechanical resilience, and multi-functionality. Efforts to imitate their properties in engineered structures have limited success. This, in part, is caused by the complexity of multi-phase materials composites and by the lack of quantified understanding of each component's role in overall hierarchy.

Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling.

The rise of machine learning has fueled the discovery of new materials and, especially, metamaterials-truss lattices being their most prominent class. While their tailorable properties have been explored extensively, the design of truss-based metamaterials has remained highly limited and often heuristic, due to the vast, discrete design space and the lack of a comprehensive parameterization. We here present a graph-based deep learning generative framework, which combines a variational autoencoder and a property predictor, to construct a reduced, continuous latent representation covering an enormous range of trusses.

Inverting the structure-property map of truss metamaterials by deep learning.

Inspired by crystallography, the periodic assembly of trusses into architected materials has enjoyed popularity for more than a decade and produced countless cellular structures with beneficial mechanical properties. Despite the successful and steady enrichment of the truss design space, the inverse design has remained a challenge: While predicting effective truss properties is now commonplace, efficiently identifying architectures that have homogeneous or spatially varying target properties has remained a roadblock to applications from lightweight structures to biomimetic implants. To overcome this gap, we propose a deep-learning framework, which combines neural networks with enforced physical constraints, to predict truss architectures with fully tailored anisotropic stiffness.

Nottingham Hip Fracture Score: Does It Predict Mortality in Distal Femoral Fracture Patients?

Background Patients with distal femur fractures are associated with mortality rates comparable to neck of femur fractures. Identifying high-risk patients is crucial in terms of orthogeriatric input, pre-operative medical optimisation and risk stratification for anaesthetics. The Nottingham Hip Fracture Score (NHFS) is a validated predictor of 30-day mortality in neck of femur fracture patients.

A gold(I) 1,2,3-triazolylidene complex featuring the interaction between gold and methine hydrogen.

A mesoionic N-heterocyclic carbene-gold(I) complex with a unique Au⋯H-C(methine) intramolecular hydrogen bonding interaction has been investigated in the solid state. The structure of this new neutral gold(I)-carbene was characterized by FT-IR and NMR spectroscopy, TGA, and X-ray diffraction techniques. Density functional theory (DFT) and atoms-in-molecule (AIM) analysis revealed that the gold-hydrogen bonding situation is more favored.

Clinical Outcomes Following Re-Operations for Intracranial Meningioma.

The outcomes following re-operation for meningioma are poorly described. The aim of this study was to identify risk factors for a performance status outcome following a second operation for a recurrent meningioma. A retrospective, comparative cohort study was conducted.

Volumetric growth of residual meningioma - A systematic review.

Surgical resection of meningioma leaves residual solid tumour in over 25% of patients. Selection for further treatment and follow-up strategy may benefit from knowledge of volumetric growth and factors associated with re-growth. The aim of this review was to evaluate volumetric growth and variables associated with growth in patients that underwent incomplete resection of a meningioma without the use of adjuvant radiotherapy.

The growth rate and clinical outcomes of radiation induced meningioma undergoing treatment or active monitoring.

Introduction: Radiation induced meningioma (RIM) incidence is increasing in line with improved childhood cancer survival. No optimal management strategy consensus exists. This study aimed to delineate meningioma growth rates from tumor discovery and correlate with clinical outcomes.

Carbamoylated chitosan hydrogels with improved viscoelastic properties and stability for potential 3D cell culture applications.

We demonstrate a benign and straightforward method to modify the chitosan (CH) by carbamoylation. The free amines on CH are converted into carbamyl functionalities by reacting with potassium cyanate (KCNO). One wt% CH solution, when reacted with KCNO ⩾ 0.

The Current Management of Cardiac Tumours: a Comprehensive Literature Review.

Objective: To understand the current evidence and guidelines behind the appropriate management of cardiac tumours.

Methods: A comprehensive electronic literature search has been performed in major databases - PubMed, Embase, Scopus, Ovid, and Google Scholar. All articles that discussed all different forms of cardiac tumours, their clinical presentation, diagnosis, and management methods have been critically appraised in this narrative review.

Implications of Physiology-Sensitive Gait Exercise on the Lower Limb Electromyographic Activity of Hemiplegic Post-Stroke Patients: A Feasibility Study in Low Resource Settings.

Unlabelled: Stroke is one of the leading causes of disability with ~80% of post-stroke survivors suffering from gait-related deficits. Conventional gait rehabilitation settings are labor-intensive and need rigorous involvement of clinicians (who use their expertise to decide the dosage of exercise intensity based on patient's capability). This demands a technology-assisted individualized exercise platform that can offer varying dosage of exercise intensity based on one's capability.