Leveraging survival analysis and machine learning for accurate prediction of breast cancer recurrence and metastasis.

Breast cancer, with its high incidence and mortality globally, necessitates early prediction of local and distant recurrence to improve treatment outcomes. This study develops and validates predictive models for breast cancer recurrence and metastasis using Recurrence-Free Survival Analysis and machine learning techniques. We merged datasets from the Molecular Taxonomy of Breast Cancer International Consortium, Memorial Sloan Kettering Cancer Center, Duke University, and the SEER program, creating a comprehensive dataset of 272, 252 rows and 23 columns.

Optimizing dental implant identification using deep learning leveraging artificial data.

This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using panoramic X-ray images. To supplement an existing dataset of 7,946 in vivo dental implant images, a three-dimensional scanner was employed to create implant surface models. Subsequently, implant surface models were used to generate two-dimensional X-ray images, which were compiled along with original images to create a comprehensive dataset.

Understanding Burnout among Surgical residents: a mixed method study.

Burnout is a complex condition that can strangely affect individuals in healthcare professions, such as surgeons and surgical residents. This study aimed to assess burnout and better explain the concept of burnout in surgical residents and the clarification strategies they take with this phenomenon to solve this problem. This mixed methods study was conducted at Shiraz University of Medical Sciences in 2022-2023 with two quantitative and qualitative phases.

Dynamic simulation of breast behaviour during different activities based on finite element modelling of multiple components of breast.

This study presents an advanced dynamic finite element (FE) model of multiple components of the breast to examine the biomechanical impact of different types of physical activities and activity intensity on the breast tissues. Using 4D scanning and motion capture technologies, dynamic data are collected during different activities. The accuracy of the FE model is verified based on relative mean absolute error (RMAE), and optimal material parameters are identified by using a validated stepwise grid search method.

A clinical narrative corpus on nut allergy: annotation schema, guidelines and use case.

This article describes a dataset on nut allergy extracted from Spanish clinical records provided by the Hospital Universitario Fundación de Alcorcón (HUFA) in Madrid, Spain, in collaboration with its Allergology Unit and Information Systems and Technologies Department. There are few publicly available clinical texts in Spanish and having more is essential as a valuable resource to train and test information extraction systems. In total, 828 clinical notes in Spanish were employed and several experts participated in the annotation process by categorizing the annotated entities into medical semantic groups related to allergies.

A guidance to intelligent metamaterials and metamaterials intelligence.

The bidirectional interactions between metamaterials and artificial intelligence have recently attracted immense interest to motivate scientists to revisit respective communities, giving rise to the proliferation of intelligent metamaterials and metamaterials intelligence. Owning to the strong nonlinear fitting and generalization ability, artificial intelligence is poised to serve as a materials-savvy surrogate electromagnetic simulator and a high-speed computing nucleus that drives numerous self-driving metamaterial applications, such as invisibility cloak, imaging, detection, and wireless communication. In turn, metamaterials create a versatile electromagnetic manipulator for wave-based analogue computing to be complementary with conventional electronic computing.

Remote sensing image dehazing using a wavelet-based generative adversarial networks.

Remote sensing images often suffer from the degradation effects of atmospheric haze, which can significantly impair the quality and utility of the acquired data. A novel dehazing method leveraging generative adversarial networks is proposed to address this challenge. It integrates a generator network, designed to enhance the clarity and detail of hazy images, with a discriminator network that distinguishes between dehazed and real clear images.

The compositional behavior of the human T cell receptor repertoire in ovarian cancer compared to healthy donors.

The distinctive characteristics of an individual's T cell receptor repertoire are crucial in recognizing and responding to a diverse array of antigens, contributing to immune specificity and adaptability. The repertoire, famously vast due to a series of cellular mechanisms, can be quantified using repertoire sequencing. In this study, we sampled the repertoire of 85 women: ovarian cancer patients (OC) and healthy donors (HD), generating a dataset of T cell clones and their abundance.

Comparison of mNGS with conventional methods for diagnosis of cryptococcal meningitis: a retrospective study.

The application of metagenomic next-generation sequencing (mNGS) in the diagnosis of cryptococcal meningitis is relatively under characterized. Here, we retrospectively evaluated data from cryptococcal meningitis patients who were tested using mNGS and/or routine testing, including fungal culture, India ink staining, and cryptococcal antigen (CrAg) testing. The performance of mNGS was then assessed.

CODE-ACCORD: A Corpus of building regulatory data for rule generation towards automatic compliance checking.

Automatic Compliance Checking (ACC) within the Architecture, Engineering, and Construction (AEC) sector necessitates automating the interpretation of building regulations to achieve its full potential. Converting textual rules into machine-readable formats is challenging due to the complexities of natural language and the scarcity of resources for advanced Machine Learning (ML). Addressing these challenges, we introduce CODE-ACCORD, a dataset of 862 sentences from the building regulations of England and Finland.

The mycobacterial ABC transporter IrtAB employs a membrane-facing crevice for siderophore-mediated iron uptake.

The mycobacterial ABC transporter IrtAB features an ABC exporter fold, yet it imports iron-charged siderophores called mycobactins. Here, we present extensive cryo-EM analyses and DEER measurements, revealing that IrtAB alternates between an inward-facing and an outward-occluded conformation, but does not sample an outward-facing conformation. When IrtAB is locked in its outward-occluded conformation in nanodiscs, mycobactin is bound in the middle of the lipid bilayer at a membrane-facing crevice opening at the heterodimeric interface.

Genetically-encoded targeted protein degradation technology to remove endogenous condensation-prone proteins and improve crop performance.

Effective modulation of gene expression in plants is achievable through tools like CRISPR and RNA interference, yet methods for directly modifying endogenous proteins remain lacking. Here, we identify the E3 ubiquitin ligase E3TCD1 and develope a Targeted Condensation-prone-protein Degradation (TCD) strategy. The X-E3TCD1 fusion protein acts as a genetically engineered degrader, selectively targeting endogenous proteins prone to condensation.

Multi-modal framework for battery state of health evaluation using open-source electric vehicle data.

Accurate, practical, and robust evaluation of the battery state of health is crucial to the efficient and reliable operation of electric vehicles. However, the limited availability of large-scale, high-quality field data hinders the development of the battery management system for state of health estimation, lifetime prediction, and fault detection in various applications. In this work, to gain insights into underlying factors limiting battery management system performance in real-world vehicles, we analyze the operational data of 300 diverse electric vehicles over three years to understand the disparities between field data and laboratory battery test data and their effect on state of health estimation.

Diffusion-driven transient hydrogenation in metal superhydrides at extreme conditions.

In recent years, metal hydride research has become one of the driving forces of the high-pressure community, as it is believed to hold the key to superconductivity close to ambient temperature. While numerous novel metal hydride compounds have been reported and extensively investigated for their superconducting properties, little attention has been focused on the atomic and electronic states of hydrogen, the main ingredient in these novel compounds. Here, we present combined H- and La-NMR data on lanthanum superhydrides, LaH, (x = 10.

Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data.

In the analysis of spatially resolved transcriptomics data, detecting spatially variable genes (SVGs) is crucial. Numerous computational methods exist, but varying SVG definitions and methodologies lead to incomparable results. We review 34 state-of-the-art methods, classifying SVGs into three categories: overall, cell-type-specific, and spatial-domain-marker SVGs.

Chromosome-level genome assembly of the sweet potato rot nematode Ditylenchus destructor.

Ditylenchus destructor, commonly known as the potato rot nematode, is a significant plant-parasitic pathogen affecting over 120 plant species globally. Effective control measures for D. destructor are limited, underscoring the need a high-quality reference genome to understand its pathogenic mechanisms.

Scoring Conformational Metastability of Macrocyclic Peptides with Binding Pose Metadynamics.

Potency optimization of macrocyclic peptides can include both modifying intermolecular interactions and modifying the conformational stability of the bioactive conformation. However, the number of possible modifications is vast. To identify modifications that enhance the stability of the binding conformations in a cost-effective manner, there is a need for a high-throughput in-silico method that scores the conformational stability of these modified molecules.

Examining the impact of clinical features and built environment on risk of hospital onset infection.

Objective: Environmental features of a patient's room depend on the patient's level of acuity and their clinical manifestations upon admission and during their hospital stay. In this study, we wish to apply statistical methodology to explore the association between room features and hospital onset infections caused by (HO-CDI) while accounting for room assignment.

Method: We conducted a nested case-control study using retrospective electronic health record (EHR) data of patients hospitalized at the Ohio State University Wexner Medical Center (OSUWMC) between January 2019 and April 2021.

Effectiveness and safety of adalimumab biosimilar in patients with inflammatory bowel disease.

Background: Adalimumab biosimilar MSB11022 (Idacio®) has been approved for the same indications as its originator (Humira®), based on findings from clinical trials in plaque psoriasis. Data on its efficacy and safety in inflammatory bowel disease, however, are scarce.

Methods: Retrospective, observational study of 44 patients with inflammatory bowel disease: 30 were treated with originator adalimumab, five were directly started on MSB11022, and nine switched from originator to biosimilar adalimumab.

Development and Validation of an Ultrasound-Based Clinical Radiomics Nomogram for Diagnosing Gouty Arthritis.

Objective: This study aimed to develop and validate a diagnostic model for gouty arthritis by integrating ultrasonographic radiomic features with clinical parameters.

Methods: A total of 604 patients suspected of having gouty arthritis were enrolled and randomly divided into a training set (n = 483) and a validation set (n = 121) in a 4:1 ratio. Univariate and multivariate analyses were conducted on the clinical data to identify statistically significant clinical features for constructing an initial diagnostic model.

Impact of pulmonary artery catheterization in patients with acute myocardial infarction cardiogenic shock.

Acute myocardial infarction (AMI) remains one of the most common causes for cardiogenic shock (CS), with high inpatient mortality (40-50 %). Studies have reported the use of pulmonary artery catheters (PACs) in decompensated heart failure, but contemporary data on their use to guide management of AMI-CS and in different SCAI stages of CS are lacking. We investigated the association of PACs and clinical outcomes in AMI-CS.

Temporary mechanical circulatory support utilization and outcomes in cardiogenic shock phenotypes: A comparative analysis of heart failure and acute myocardial infarction.

Introduction: Cardiogenic shock (CS) is marked by substantial morbidity and mortality. The two major CS etiologies include heart failure (HF) and acute myocardial infarction (AMI). The utilization trends of mechanical circulatory support (MCS) and their clinical outcomes are not well described.

A robust output-feedback control scheme based on composite nonlinear feedback in singular uncertain delayed models.

Relying on composite nonlinear feedback, an output-feedback controller is robustly addressed in the singular models with uncertainties, disturbances and time-delays. For this purpose, an observer-based compensator is utilized to realize the purpose. In the presence of disturbance and uncertainty, it is demonstrated that the tracking error and the states of the overall system are ultimately bounded.

Male sexual and reproductive health in cystic fibrosis: A concept mapping study.

Background: Males with cystic fibrosis (MwCF) face general and disease-specific sexual and reproductive health (SRH) concerns. Using concept mapping (CM), this study identified the SRH topics valued by members of the CF community.

Methods: MwCF 18 years and older, parents and partners of MwCF, and healthcare providers participated in an online CM study.