Preoperative prediction of the Lauren classification in gastric cancer using automated nnU-Net and radiomics: a multicenter study.

Objectives: To develop and validate a deep learning model based on nnU-Net combined with radiomics to achieve autosegmentation of gastric cancer (GC) and preoperative prediction via the Lauren classification.

Methods: Patients with a pathological diagnosis of GC were retrospectively enrolled in three medical centers. The nnU-Net autosegmentation model was developed using manually segmented datasets and evaluated by the Dice similarity coefficient (DSC).

Dynamic Peptide Nanoframework-Guided Protein Coassembly: Advancing Adhesion Performance with Hierarchical Structures.

Hierarchical structures are essential in natural adhesion systems. Replicating these in synthetic adhesives is challenging due to intricate molecular mechanisms and multiscale processes. Here, we report three phosphorylated peptides featuring a hydrophobic self-assembly motif linked to a hydrophilic phosphorylated sequence (pSGSS), forming peptide fibril nanoframeworks.

Deep Learning-Based Automatic Segmentation Combined with Radiomics to Predict Post-TACE Liver Failure in HCC Patients.

Objective: To develop and validate a deep learning-based automatic segmentation model and combine with radiomics to predict post-TACE liver failure (PTLF) in hepatocellular carcinoma (HCC) patients.

Methods: This was a retrospective study enrolled 210 TACE-trated HCC patients. Automatic segmentation model based on nnU-Net neural network was developed to segment medical images and assessed by the Dice similarity coefficient (DSC).

Predicting overall survival and prophylactic cranial irradiation benefit in small cell lung cancer patients: a multicenter cohort study.

Background: To construct a CT-based radiomics nomogram, enabling the estimation of overall survival (OS) in small cell lung cancer (SCLC) patients and facilitating the identification of prophylactic cranial irradiation (PCI) beneficiaries through risk stratification using the radiomics score (RS).

Methods: A retrospective recruitment of 375 patients with pathologically confirmed SCLC was conducted across three medical centers, followed by their division into different cohorts. To generate the RS, a series of analyses were performed, including Pearson correlation analysis, univariate Cox analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis.

Computed tomography enterography-based deep learning radiomics to predict stratified healing in patients with Crohn's disease: a multicenter study.

Objectives: This study developed a deep learning radiomics (DLR) model utilizing baseline computed tomography enterography (CTE) to non-invasively predict stratified healing in Crohn's disease (CD) patients following infliximab (IFX) treatment.

Methods: The study included 246 CD patients diagnosed at three hospitals. From the first two hospitals, 202 patients were randomly divided into a training cohort (n = 141) and a testing cohort (n = 61) in a 7:3 ratio.

Osteopontin/SPP1: a potential mediator between immune cells and vascular calcification.

Vascular calcification (VC) is considered a common pathological process in various vascular diseases. Accumulating studies have confirmed that VC is involved in the inflammatory response in heart disease, and SPP1+ macrophages play an important role in this process. In VC, studies have focused on the physiological and pathological functions of macrophages, such as pro-inflammatory or anti-inflammatory cytokines and pro-fibrotic vesicles.

Self-assembled branched polypeptides as amelogenin mimics for enamel repair.

The regeneration of demineralized enamel holds great significance in the treatment of dental caries. Amelogenin (Ame), an essential protein for mediating natural enamel growth, is no longer secreted after enamel has fully matured in childhood. Although biomimetic mineralization based on peptides or proteins has made significant progress, easily accessible, low-cost, biocompatible and highly effective Ame mimics are still lacking.

Predicting overall survival and prophylactic cranial irradiation benefit in small-cell lung cancer with CT-based deep learning: A retrospective multicenter study.

Background And Purpose: To develop a computed tomography (CT)-based deep learning model to predict overall survival (OS) among small-cell lung cancer (SCLC) patients and identify patients who could benefit from prophylactic cranial irradiation (PCI) based on OS signature risk stratification.

Materials And Methods: This study retrospectively included 556 SCLC patients from three medical centers. The training, internal validation, and external validation cohorts comprised 309, 133, and 114 patients, respectively.

Evaluation of Mucosal Healing in Crohn's Disease: Radiomics Models of Intestinal Wall and Mesenteric Fat Based on Dual-Energy CT.

This study aims to assess the effectiveness of radiomics signatures obtained from dual-energy computed tomography enterography (DECTE) in the evaluation of mucosal healing (MH) in patients diagnosed with Crohn's disease (CD). In this study, 106 CD patients with a total of 221 diseased intestinal segments (79 with MH and 142 non-MH) from two medical centers were included and randomly divided into training and testing cohorts at a ratio of 7:3. Radiomics features were extracted from the enteric phase iodine maps and 40-kev and 70-kev virtual monoenergetic images (VMIs) of the diseased intestinal segments, as well as from mesenteric fat.

Inactivation of antibiotic resistant bacteria by FeO @MoS activated persulfate and control of antibiotic resistance dissemination risk.

Antibiotic resistance poses a global environmental challenge that jeopardizes human health and ecosystem stability. Antibiotic resistant bacteria (ARB) significantly promote the spreading and diffusion of antibiotic resistance. This study investigated the efficiency and mechanism of inactivating tetracycline-resistant Escherichia coli (TR E.

Inflammatory predictors (eosinophil, C-RP and IL-6) and effectiveness of oral Azvudine tablets treatment in COVID-19 hospitalized patients: A retrospective, self-controlled study.

Background: Although vaccinations and antiviral drugs are widely used in the clinical treatment worldwide, there is little investigation on the clinical outcomes and effectiveness of oral Azvudine tablets (FNC) treatment in COVID-19 hospitalized patients. The previous data showed Azvudine treatment was closely related to reduced virus shedding time, but the potential role of Azvudine on inflammatory response is scarce. Thus, this study is to investigate inflammatory predictors and effectiveness of oral Azvudine tablets treatment in COVID-19 hospitalized patients.

Automatic Segmentation and Radiomics for Identification and Activity Assessment of CTE Lesions in Crohn's Disease.

Background: The purpose of this article is to develop a deep learning automatic segmentation model for the segmentation of Crohn's disease (CD) lesions in computed tomography enterography (CTE) images. Additionally, the radiomics features extracted from the segmented CD lesions will be analyzed and multiple machine learning classifiers will be built to distinguish CD activity.

Methods: This was a retrospective study with 2 sets of CTE image data.

A multifunctional hydrogel dressing with high tensile and adhesive strength for infected skin wound healing in joint regions.

Most hydrogel dressings are designed for skin wounds in flat areas, and few are focused on the joint skin regions which undergo frequent movement. The mismatch of mechanical properties and poor fit between a hydrogel dressing and a wound in joint skin results in hydrogel shedding, bacterial infection and delayed healing. Therefore, it is of great significance to design and prepare a multifunctional hydrogel with high tensile and tissue-adhesive strength as well as other therapeutic effects for the treatment of joint skin wounds.

Correction: Ren et al. Injectable and Antioxidative HT/QGA Hydrogel for Potential Application in Wound Healing. 2021, , 204.

In the original publication [...

PMN-incorporated multifunctional chitosan hydrogel for postoperative synergistic photothermal melanoma therapy and skin regeneration.

Melanoma excision surgery is usually accompanied by neoplasm residual, tissue defect, and bacterial infection, resulting in high tumor recurrence and chronic wound. Nanocomposite hydrogels can satisfy the twin requirements of avoiding tumor recurrence and skin wound healing following skin melanoma surgery due to their photothermal anti-tumor and anti-bacterial activities. In this study, carboxymethyl chitosan, oxidized fucoidan and polyphenol-metal nanoparticle (PMN) of tannic acid capped gold nanoparticles were used to fabricate multifunctional nanocomposite hydrogels through Schiff base reaction.

Photocatalytic Degradation of Acetaminophen in Aqueous Environments: A Mini Review.

Over the past few decades, acetaminophen (ACT), a typical nonsteroidal anti-inflammatory drug (NSAID), has gained global usage, positioning itself as one of the most extensively consumed medications. However, the incomplete metabolism of ACT leads to a substantial discharge into the environment, classifying it as an environmental contaminant with detrimental effects on non-target organisms. Various wastewater treatment technologies have been developed for ACT removal to mitigate its potential environmental risk.

Heterogeneous Photocatalytic C-H Functionalization of Indoles with Diazo Compounds Enabled by Carbon Nitride.

Herein, we reported the heterogeneous photocatalytic C-H alkylation of indoles with diazo compounds using graphitic carbon nitride (g-CN) as the photocatalyst. The reaction was carried out under a simple operation and mild conditions. In addition, the catalyst was found to be stable and reusable after five reaction cycles.

CTE-Based Radiomics Models Can Identify Mucosal Healing in Patients with Crohn's Disease.

Rationale And Objectives: To develop computed tomography enterography (CTE)-based radiomics models to assess mucosal healing (MH) in patients with Crohn's disease (CD).

Materials And Methods: CTE images were retrospectively collected from 92 confirmed cases of CD at the post-treatment review. Patients were randomly divided into developing (n = 73) and testing (n = 19) groups.

Ultra-stretchable, tissue-adhesive, shape-adaptive, self-healing, on-demand removable hydrogel dressings with multiple functions for infected wound healing in regions of high mobility.

Bacterial infection in the most mobile area usually leads to delayed healing and functional restriction, which has been a long-term challenge in clinic. Developing hydrogel-based dressings with mechanical flexibly, high adhesive and anti-bacterial properties, will contribute to the healing and therapeutic effects especially for this typical skin wound. In this work, composite hydrogel named PBOF through multi-reversible bonds between polyvinyl alcohol, borax, oligomeric procyanidin and ferric ion demonstrated a 100 times ultra-stretch ability, 24 kPa of highly tissue-adhesive, rapid shape-adaptability within 2 min and self-healing feature within 40 s, was designed as the multifunctional wound dressing for the Staphylococcus aureus-infected skin wound in the mice nape model.