Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.

Purpose: The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guiding the treatments of ovarian cancer (OC). We tried to develop a model to predict the FIGO stage of OC through machine learning algorithms with patients' pretreatment clinical, positron emission tomography scan (PET/CT) metabolic, and radiomics features.

Methods: We enrolled OC patients who underwent PET/CT scans and divided them into two cohorts according to their FIGO stage.

In-Depth Analysis of Soil Microbial Community Succession Model Construction under Microplastics Stress.

Although microplastics (MPs) toxicity to soil microorganisms has been preliminarily explored, the underlying reasons affecting the direction of microbial community succession are unclear. This study aimed to investigate the impacts of MPs infer community assembly mechanisms through phylogenetic bin-based null model analysis, network models, and protein function prediction in five typical Northeast China five typical soils. The results show that microbial communities in soils with high organic matter exhibit a stronger response to MPs, with enhanced protein functionality, network regulation, and assembly processes.

Removal of tetracycline by biochar synergistic with ferrate: Influencing mechanism on precursor biomass components.

Biochar can serve as an activator for potassium ferrate, significantly enhancing the treatment efficiency to antibiotics. However, the mechanism by which biochar activated potassium ferrate remained unclear, necessitating further investigation. Cellulose biochar (CBC) and lignin biochar (LBC) derived by two model compounds which were the highest proportion of content in biomass were adopted to be study object, to investigate the removal efficiency of tetracycline (TC) by ferrate synergetic with CBC and LBC, respectively for the first time, and thoroughly analyzed the adsorption and degradation processes within the reaction system.

Synergistically piezocatalytic and Fenton-like activation of HO by a ferroelectric Bi(BiFe)O catalyst to boost degradation of polyethylene terephthalate microplastic (PET-MPs).

Pollution of microplastics (MPs) has been drastically threating human health, however, whose elimination from the environment by current approaches is inefficient due to their high molecular weight, stronghydrophobicity and stable covalent bonds. Herein, we report a novel and highly-efficient route to degrade MPs contaminants through synergistically piezocatalytic and Fenton-like activation of HO by a ferroelectric Bi(BiFe)O catalyst under ultrasound treatment. For 10 g/L polyethylene terephthalate microplastics (PET-MPs), the synergistic strategy reached a 28.

GV-971 prevents severe acute pancreatitis by remodeling the microbiota-metabolic-immune axis.

Despite recent advances, severe acute pancreatitis (SAP) remains a lethal inflammation with limited treatment options. Here, we provide compelling evidence of GV-971 (sodium oligomannate), an anti-Alzheimer's medication, as being a protective agent in various male mouse SAP models. Microbiome sequencing, along with intestinal microbiota transplantation and mass cytometry technology, unveil that GV-971 reshapes the gut microbiota, increasing Faecalibacterium populations and modulating both peripheral and intestinal immune systems.

Maternal linoleic acid-rich diet ameliorates bilirubin neurotoxicity in offspring mice.

Hyperbilirubinaemia is a prevalent condition during the neonatal period, and if not promptly and effectively managed, it can lead to severe bilirubin-induced neurotoxicity. Sunflower seeds are a nutrient-rich food source, particularly abundant in linoleic acid. Here, we provide compelling evidence that lactating maternal mice fed a sunflower seed diet experience enhanced neurological outcomes and increased survival rates in hyperbilirubinemic offspring.

Tracing the vertical migration of exogenous cadmium in soil by seasonal freeze-thaw event using rare earth elements.

Environmental behaviors of heavy metal in soil are strongly influenced by seasonal freeze-thaw events at the mid-high altitudes. However, the potential impact mechanisms of freeze-thaw cycles on the vertical migration of heavy metal are still poor understood. This study aimed to explore how exogenous cadmium (Cd) migrated and remained in soil during the in-situ seasonal freeze-thaw action using rare earth elements (REEs) as tracers.

Methylation of microRNA genes and its effect on secondary xylem development of stem in poplar.

MicroRNAs (miRNAs) and DNA methylation are both vital regulators of gene expression. DNA methylation can affect the transcription of miRNAs, just like coding genes, through methylating the CpG islands in the gene regions of miRNAs. Although previous studies have shown that DNA methylation and miRNAs can each be involved in the process of wood formation, the relationship between the two has been relatively little studied in plant wood formation.

Identification of the prognostic value of LACTB2 and its correlation with immune infiltrates in ovarian cancer by integrated bioinformatics analyses.

Ovarian cancer (OC) is one of the most common reproductive tumors in women, whereas current treatment options are limited. β-lactamase-like-protein 2 (LACTB2) has been observed to be associated with various cancers, but its function in OC is unknown. Therefore, we evaluate the prognostic value and the underlying function of LACTB2 in OC.

Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer.

Purpose: Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features.

Methods: We screened age and 33 blood features from 331 OC patients.

Multitask prediction models for serous ovarian cancer by preoperative CT image assessments based on radiomics.

Objective: High-grade serous ovarian cancer (HGSOC) has the highest mortality rate among female reproductive system tumors. Accurate preoperative assessment is crucial for treatment planning. This study aims to develop multitask prediction models for HGSOC using radiomics analysis based on preoperative CT images.

Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer.

Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples.

CSGALNACT2 restricts ovarian cancer migration and invasion by modulating MAPK/ERK pathway through DUSP1.

Purpose: Ovarian cancer is one of the leading causes of cancer-related death among women. CSGALNACT2 is a vital Golgi transferase and is related to a variety of human diseases. However, its expression pattern and function in ovarian cancer remain uncertain.

Effects of different national standards and driving conditions on pollutants and persistent free radicals in diesel engine exhaust particles.

Exhaust pollutants from diesel vehicles constitute an important portion of air pollution. In addition to conventional pollutants such as carbon and nitrogen oxides, persistent free radicals (PFRs) exist on exhaust particles could also pose a health risk by inducing oxidative stress. However, recently there is a dearth of comprehensive studies addressing this concern.

Clinical significance and immune infiltration analyses of a novel coagulation-related signature in ovarian cancer.

Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn't been determined yet.

Endoplasmic Reticulum Stress-Related Ten-Biomarker Risk Classifier for Survival Evaluation in Epithelial Ovarian Cancer and : A Potential Therapeutic Target of Ovarian Cancer.

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignant tumor. Endoplasmic reticulum (ER) stress plays an important role in the malignant behaviors of several tumors. In this study, we established a risk classifier based on 10 differentially expressed genes related to ER stress to evaluate the prognosis of patients and help to develop novel medical decision-making for EOC cases.

The dual effect of disodium anthraquinone-2,6-disulfonate (AQDS) on the Cr(VI) removal by biochar: The enhanced electron transfer and the inhibited adsorption.

Due to large specific surface area, abundant surface functional groups, and stable chemical structure, biochar has been widely used in many environmental fields, including the remediation of Cr pollution. Alternatively, electrochemically active organic matter (e-OM), which is prevalent in both natural environments and industrial wastewater, exerts an inevitable influence on the mechanisms underlying Cr(VI) removal by biochar. The synergistic interplay between biochar and e-OM in the context of Cr(VI) remediation remains to be fully elucidated.

Regulation of friction pair to promote conversion of mechanical energy to chemical energy on BiWO and realization of enhanced tribocatalytic activity to degrade different pollutants.

Recently, friction-induced tribocatalysis has received tremendous attention through converting mechanical energy to chemical energy. However, its efficiency is much lower than those of photocatalysis and piezocatalysis, and its environmental application is limited in dye degradation. Herein, we developed a facile approach to improve the tribocatalytic activity of BiWO via adding trace polymer powders to form friction pairs with BiWO.

A novel autophagy-related gene signature associated with prognosis and immune microenvironment in ovarian cancer.

Ovarian cancer (OV), the most fatal gynecological malignance worldwide, has high recurrence rates and poor prognosis. Recently, emerging evidence supports that autophagy, a highly regulated multi-step self-digestive process, plays an essential role in OV progression. Accordingly, we filtered 52 potential autophagy-related genes (ATGs) among the 6197 differentially expressed genes (DEGs) identified in TCGA-OV samples (n = 372) and normal controls (n = 180).

DiffSeer: Difference-Based Dynamic Weighted Graph Visualization.

Existing dynamic weighted graph visualization approaches rely on users' mental comparison to perceive temporal evolution of dynamic weighted graphs, hindering users from effectively analyzing changes across multiple timeslices. We propose DiffSeer, a novel approach for dynamic weighted graph visualization by explicitly visualizing the differences of graph structures (e.g.

Exploring prognostic indicators in the pathological images of ovarian cancer based on a deep survival network.

Tumor pathology can assess patient prognosis based on a morphological deviation of tumor tissue from normal. Digitizing whole slide images (WSIs) of tissue enables the use of deep learning (DL) techniques in pathology, which may shed light on prognostic indicators of cancers, and avoid biases introduced by human experience. We aim to explore new prognostic indicators of ovarian cancer (OC) patients using the DL framework on WSIs, and provide a valuable approach for OC risk stratification.

Artificial intelligence-based preoperative prediction system for diagnosis and prognosis in epithelial ovarian cancer: A multicenter study.

Background: Ovarian cancer (OC) is the most lethal gynecological malignancy, with limited early screening methods and poor prognosis. Artificial intelligence technology has made a great breakthrough in cancer diagnosis.

Purpose: We aim to develop a specific interpretable machine learning (ML) prediction model for the diagnosis and prognosis of epithelial ovarian cancer (EOC) based on a variety of biomarkers.

Single-Step Fabrication of Longtail Glasswing Butterfly-Inspired Omnidirectional Antireflective Structures.

Most bio-inspired antireflective nanostructures are extremely vulnerable and suffer from complicated lithography-based fabrication procedures. To address the issues, we report a scalable and simple non-lithography-based approach to engineer robust antireflective structures, inspired by the longtail glasswing butterfly, in a single step. The resulting two-dimensional randomly arranged 80/130/180 nm silica colloids, partially embedded in a polymeric matrix, generate a gradual refractive index transition at the air/substrate interface to suppress light reflection.

Tribocatalysis of homogeneous material with multi-size granular distribution for degradation of organic pollutants.

Recently, tribocatalysis driven by mechanical energy has been developed by rubbing two kinds of different materials. In this work, we firstly demonstrated that the friction of the single material also could initiate the tribocatalysis for degrading organic dyes. Under magnetic stirring, the multi-size granular polytetrafluoroethylene (PTFE) particles were triboelectrically charged, among which the collision between large and small particles would cause high energy electrons on large particles to transfer to small ones.

Omnidirectional / Unidirectional Antireflection-Switchable Structures Inspired by Dragonfly Wings.

Randomly arranged irregular inclined conical structure-covered dragonfly wings, distinguished from periodic conical structure-covered cicada wings, are with high optical transparency for wide viewing angles. Bioinspired by the antireflective structures, we develop a colloidal lithography approach for engineering randomly arranged irregular conical structures with shape memory polymer-based tips. The structures establish a gradual refractive index transition to suppresses optical reflection in the visible spectrum.