Explainable machine learning for predicting recurrence-free survival in endometrial carcinosarcoma patients.

Objectives: Endometrial carcinosarcoma is a rare, aggressive high-grade endometrial cancer, accounting for about 5% of all uterine cancers and 15% of deaths from uterine cancers. The treatment can be complex, and the prognosis is poor. Its increasing incidence underscores the urgent requirement for personalized approaches in managing such challenging diseases.

Species sensitivity distribution of rare earth elements: A full overview.

Rare earth elements (REEs) encompass 15 lanthanides and play a crucial role in modern technology. Despite their essential uses, REEs are emerging environmental contaminants due to their growing presence in industrial, agricultural, and medical applications. For the first time, the species sensitivity distribution (SSD) approach was applied to REEs considering 58 papers including toxicity about Ce, Dy, Er, Gd, La, Lu, Nd, Pr, Sm, and Y.

Disinfection of dental root canals by cold atmospheric plasma: a systematic review and meta-analysis of dental biofilm.

Aim: The intricate structure of the tooth root canals has a role in the colonization and biofilm formation in hidden areas that are hardly reached by standard endodontic treatments. This review aims at summarizing data from and studies for a better understanding of the application of cold atmospheric plasma (CAP) for the disinfection of dental root canals.

Methods: PubMed, Scopus, and Web of Science databases were screened.

Guided Bone Regeneration: CGF and PRF Combined With Various Types of Scaffolds-A Systematic Review.

Bone regeneration plays a pivotal role in modern oral surgery, particularly in facilitating successful implant-prosthetic rehabilitation. This systematic review explores the regenerative potential of growth factors, such as platelet-rich fibrin (PRF) and concentrated growth factors (CGFs), when combined with various types of scaffolds in bone augmentation procedures, including guided bone regeneration, split crest, sinus lift (SL), and alveolar ridge preservation. A comprehensive search strategy yielded 18 relevant studies, which were analyzed for bone formation and stabilization outcomes.

Clinical and genomic profiling of a patient with a de novo ring chromosome 18: a case report highlighting autoimmune and neurological implications.

Ring chromosome 18 (r(18)) is a rare chromosomal abnormality characterized by the circular rearrangement of chromosome 18, which presents significant challenges in genotype-phenotype correlations due to variability in deletions across the 18p and 18q arms. We report the case of a pediatric patient with a de novo ring chromosome 18, diagnosed by karyotype analysis and confirmed by high-resolution SNP arrays. The patient exhibited pathogenic copy number variants (CNVs) in the 18p11.

SIGMAP: an explainable artificial intelligence tool for SIGMA-1 receptor affinity prediction.

Developing sigma-1 receptor (S1R) modulators is considered a valuable therapeutic strategy to counteract neurodegeneration, cancer progression, and viral infections, including COVID-19. In this context, tools capable of accurately predicting S1R affinity are highly desirable. Herein, we present a panel of 25 classifiers trained on a curated dataset of high-quality bioactivity data of small molecules, experimentally tested as potential S1R modulators.

Demonstrating the Efficacy of Core-Shell Silica Catalyst in Depolymerizing Polycarbonate.

Polycarbonate (PC) is a highly versatile plastic material that is extensively utilized across various industries due to its superior properties, including high impact strength and heat resistance. However, its durability presents significant challenges for recycling and waste management. Polycarbonate is a thermoplastic polymer representative of the class of condensation reaction polymers obtained from the reaction of bisphenol A (BPA) and a carbonyl source, such as phosgene or alkyl and aryl carbonate.

Mineral states and sequestration processes involving soil biogenic components in various soils and desert sands of Inner Mongolia.

Soil biogenic components are subject to continuous sequestration, and export from soils into the surrounding air and water environments. However, the processes involving the stability or lability of their mineral states remain still unclear. To assess these issues, we have measured various biogenic components in a number of agricultural, forest, grassland, and deep soils, as well as desert sands from Inner Mongolia, both in the solid state and liquid extracts.

Electric Field Cycling of Physisorbed Antibodies Reduces Biolayer Polarization Dispersion.

The electric dipoles of proteins in a biolayer determine their dielectric properties through the polarization density P. Hence, its reproducibility is crucial for applications, particularly in bioelectronics. Biolayers encompassing capturing antibodies covalently bound at a biosensing interface are generally preferred for their assumed higher stability.

[Thrombosis in Hemodialysis Tunnelled Central Venous Catheters: From Pathogenesis to Therapeutic Strategies].

Central venous catheter-related thrombosis is a frequent non-infectious complication, typically associated with catheter dysfunction and hemodialysis inadequacy. Central venous catheters (CVCs) are categorized into non-tunnelled and tunnelled types, wherein the choice depends on patient's clinical conditions and the diagnostic and therapeutic workup. Tunnelled CVCs (tCVCs) are sought whenever an arteriovenous fistula is unfeasible or as primary access in patients with poor prognosis.

Integrating Epoxidation, High-Resolution Mass Spectrometry and Ultraviolet Spectroscopy to Unravel the Complex Profile of Boswellic Acids and Related Compounds in the Gum Resin Extract.

The chemical characterization of natural products is often a complex task that demands powerful analytical techniques. Liquid chromatography with high-resolution tandem mass spectrometry (HRMS/MS) is often employed, yet it can face hard challenges when isomeric species are present, and reference standards are lacking. In such cases, the confidence level in compound identification can be significantly improved by the collection of orthogonal information on target analytes.

Functional Hypergraphs of Stock Markets.

In stock markets, nonlinear interdependencies between various companies result in nontrivial time-varying patterns in stock prices. A network representation of these interdependencies has been successful in identifying and understanding hidden signals before major events like stock market crashes. However, these studies have revolved around the assumption that correlations are mediated in a pairwise manner, whereas, in a system as intricate as this, the interactions need not be limited to pairwise only.

Robust machine learning challenge: An AIFM multicentric competition to spread knowledge, identify common pitfalls and recommend best practice.

Purpose: A novel and unconventional approach to a machine learning challenge was designed to spread knowledge, identify robust methods and highlight potential pitfalls about machine learning within the Medical Physics community.

Methods: A public dataset comprising 41 radiomic features and 535 patients was employed to assess the potential of radiomics in distinguishing between primary lung tumors and metastases. Each participant developed two classification models using: (i) all features (base model); (ii) only robust features (robust model).

Differentiating sensor changes in a composite heart failure ICD monitoring index: clinical correlates and implications.

Background: The HeartLogic algorithm (Boston Scientific, St Paul, MN) integrates data from implantable cardioverter-defibrillator (ICD) sensors to predict heart failure (HF) decompensation: first (S1) and third (S3) heart sounds, intrathoracic impedance, respiration rate, ratio of respiration rate to tidal volume (RSBI), and night heart rate.

Objective: This study assessed the relative changes in ICD sensors at the onset of HeartLogic alerts, their association with patient characteristics, and outcomes.

Methods: The study included 568 patients with HF carrying ICDs (CRT-D, n = 410) across 26 centers, with a median follow-up of 26 months.

Diatoms in Focus: Chemically Doped Biosilica for Customized Nanomaterials.

Diatoms are photosynthetic microalgae widely diffused around the globe and well adapted to thrive in diverse environments. Their success is closely related to the nanostructured biosilica shell (frustule) that serves as exoskeleton. Said structures have attracted great attention, thanks to their hierarchically ordered network of micro- and nanopores.

Crystal Structure and Li-Fe Order in Synthetic MgLiFe(SiO) Olivine Structure.

Olivines are naturally occurring silicates consisting of isolated (SiO) tetrahedra linked through 1O and 2O octahedra. In this study, we report the structural and crystal-chemical characterization of synthetic olivine crystals containing up to 25% Li-Fe synthesized using the flux growth technique. Based on site scattering, <1-O> and <2-O> mean bond lengths, and charge neutrality of the chemical formula, we found a perfect ordering of Li and Fe at the two distinct 1 and 2 sites.

Dynamic changes, cycling and downward fate of dissolved carbon and nitrogen photosynthetically-derived from glaciers in upper Indus river basin.

Glaciers play key roles in capturing, storing, and transforming global carbon and nitrogen, thereby contributing markedly to their cycles. However, an integrated mechanistic approach is still lacking regarding glacier's primary producers (PP), in terms of stable dissolved inorganic carbon isotope (δC-DIC) and its relationship with dissolved carbon and nitrogen transformation d ynamic changes/cycling. Here, we sampled waters from glaciers, streams, tributaries, and the Indus River (IR) mainstream in the Upper IR Basin, Western Himalaya.

Long-term retention rate, adverse event temporal patterns and rescue treatment strategies of mycophenolate mofetil in systemic sclerosis: insights from real-life.

Background: Mycophenolate mofetil (MMF) is a mainstay for the treatment of systemic sclerosis (SSc). The occurrence and implications of MMF-related adverse events on drug retention rates in real life remain poorly defined. We aimed to determine the MMF retention rate and to investigate the causes and patterns of discontinuation, adverse events (AEs) and treatment options used after discontinuation.

A single bout of physical exercise improves 1-hour post-load plasma glucose in healthy young adults.

Purpose: Physical exercise is a key component in the treatment of type 2 diabetes and plays an important role in maintaining a healthy glucose metabolism even in healthy subjects. To date, no studies have investigated the effect of a single bout of aerobic physical exercise on glucose metabolism in young, moderately active, healthy adults.

Methods: We performed an OGTT 7 days before and 24 h after a single bout of physical exercise, to evaluate 1-hour post-load plasma glucose and surrogate indexes of insulin sensitivity and insulin secretion.

An integrated georeferenced dataset of public investments for soil defence in Italy.

The dataset collects and harmonizes financial data about public works in Italy, focusing on soil defence investments. The data are sourced from three distinct platforms: the Italian Ministry of Economics and Finance's open data platform OpenBDAP, the OpenCoesione website, concerned with interventions framed in cohesion policies financed by additional resources from the European and national budgets, and the ReNDiS database, provided by the Italian Institute for Environmental Protection and Research (ISPRA), that exclusively gathers information about public works in soil defence. The data records belonging to these three sources are linked by a unique project code (CUP), ensuring that there is no duplication of data.

TIRESIA and TISBE: Explainable Artificial Intelligence Based Web Platforms for the Transparent Assessment of the Developmental Toxicity of Chemicals and Drugs.

Developmental toxicity is key human health endpoint, especially relevant for safeguarding maternal and child well-being. It is an object of increasing attention from international regulatory bodies such as the US EPA (US Environmental Protection Agency) and ECHA (European CHemicals Agency). In this challenging scenario, non-test methods employing explainable artificial intelligence based techniques can provide a significant help to derive transparent predictive models whose results can be easily interpreted to assess the developmental toxicity of new chemicals at very early stages.