Canine mesenchymal stem cell-derived exosomes attenuate renal ischemia-reperfusion injury through miR-146a-regulated macrophage polarization.

Introduction: The most common factor leading to renal failure or death is renal IR (ischemia-reperfusion). Studies have shown that mesenchymal stem cells (MSCs) and their exosomes have potential therapeutic effects for IR injury by inhibiting M1 macrophage polarization and inflammation. In this study, the protective effect and anti-inflammatory mechanism of adipose-derived mesenchymal stem cell-derived exosomes (ADMSC-Exos) after renal IR were investigated.

Development and validation of a nomogram for predicting occurrence of severe case in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era.

Background: The significant rebound of influenza A (H1N1) virus activity, particularly among children, with rapidly growing number of hospitalized cases is of major concern in the post-COVID-19 era. The present study was performed to establish a prediction model of severe case in pediatric patients hospitalized with H1N1 infection during the post-COVID-19 era.

Methods: This is a multicenter retrospective study across nine public tertiary hospitals in Yunnan, China, recruiting pediatric H1N1 inpatients hospitalized at five of these centers between February 1 and July 1, 2023, into the development dataset.

A novel combined nomogram for predicting severe acute lower respiratory tract infection in children hospitalized for RSV infection during the post-COVID-19 period.

Introduction: Off-season upsurge of respiratory syncytial virus (RSV) infection with changed characteristics and heightened clinical severity during the post-COVID-19 era are raising serious concerns. This study aimed to develop and validate a nomogram for predicting the risk of severe acute lower respiratory tract infection (SALRTI) in children hospitalized for RSV infection during the post-COVID-19 era using machine learning techniques.

Methods: A multicenter retrospective study was performed in nine tertiary hospitals in Yunnan, China, enrolling children hospitalized for RSV infection at seven of the nine participating hospitals during January-December 2023 into the development dataset.

Clinical Analysis and Imaging Study of Lateral Lumbar Intervertebral Fusion in the Treatment of Degenerative Lumbar Scoliosis.

Objective: As the population ages and technology advances, lateral lumbar intervertebral fusion (LLIF) is gaining popularity for the treatment of degenerative lumbar scoliosis (DLS). This study investigated the feasibility, minimally invasive concept, and benefits of LLIF for the treatment of DLS by observing and assessing the clinical efficacy, imaging changes, and complications following the procedure.

Methods: A retrospective analysis was performed for 52 DLS patients (12 men and 40 women, aged 65.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

Background: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection.

Methods: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group.

Multiparametric MRI-based intratumoral and peritumoral radiomics for predicting the pathological differentiation of hepatocellular carcinoma.

Purpose: To explore the predictive potential of intratumoral and multiregion peritumoral radiomics features extracted from multiparametric MRI for predicting pathological differentiation in hepatocellular carcinoma (HCC) patients.

Methods: A total of 265 patients with 277 HCCs (training cohort n = 193, validation cohort n = 84) who underwent preoperative MRI were retrospectively analyzed. The risk factors identified through stepwise regression analysis were utilized to construct a clinical model.

Prognostic nomogram model for selecting between transarterial chemoembolization plus lenvatinib, with and without PD-1 inhibitor in unresectable hepatocellular carcinoma.

Objectives: To establish and verify a prognostic nomogram model for selecting in unresectable hepatocellular carcinoma (uHCC) treated by transarterial chemoembolization plus lenvatinib (TACE-L) with or without PD-1 inhibitor.

Methods: Data of 241 uHCC patients who underwent TACE-L (n = 128) and TACE-L plus PD-1 inhibitor (TACE-L-P, n = 113) were retrospectively reviewed. The differences in tumour responses, progression-free survival (PFS), overall survival (OS), and adverse events (AEs) between two groups were compared, and a prognostic nomogram model was established based on independent clinical-radiologic factors and confirmed by Cox regression analysis for predicting PFS and OS.

CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning.

Rationale And Objectives: To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on contrast-enhanced magnetic resonance imaging (CEMRI) and validate its efficiency for predicting microvascular invasion (MVI) and pathological differentiation in hepatocellular carcinoma (HCC).

Methods: CEMRI images were retrospectively obtained from 277 HCCs in 265 patients. Habitat analysis and DL features were extracted from the CEMRI images and selected with the least absolute shrinkage and selection operator approach to develop ITH and DL models, respectively, and these robust features were then integrated to design a fusion model for predicting MVI and poorly differentiated HCC (pHCC).

Machine Learning-Based CEMRI Radiomics Integrating LI-RADS Features Achieves Optimal Evaluation of Hepatocellular Carcinoma Differentiation.

Purpose: To develop and compare various machine learning (ML) classifiers that employ radiomics extracted from contrast-enhanced magnetic resonance imaging (CEMRI) for diagnosing pathological differentiation of hepatocellular carcinoma (HCC), and validate the performance of the best model.

Methods: A total of 251 patients with HCCs (n = 262) were assigned to a training (n = 200) cohort and a validation (n = 62) cohort. A collection of 5502 radiomics signatures were extracted from the CEMRI images for each HCC nodule.

[Measures for waste and by-product recycling and circular economy of whole industry chain of traditional Chinese medicine resources facing carbon peak and carbon neutrality (dual carbon) goals].

It has become a common consensus that resource conservation and intensive recycling for improving resource utilization efficiency is an important way to achieve carbon peak and carbon neutrality(dual carbon). Traditonal Chinese medicine(TCM)resources as national strategic resources are the material basis and fundamental guarantee for the development of TCM industry and health services. However, the rapid growth of China's TCM industry and the continuous expansion and extension of the industrial chain have exposed the low efficiency of TCM resources.

Doubly Screened Coulomb Correction Approach for Strongly Correlated Systems.

Strongly correlated systems containing d/f electrons present a challenge to conventional density functional theory such as the local density approximation or generalized gradient approximation. We developed a doubly screened Coulomb correction (DSCC) approach to perform on-site Coulomb interaction correction for strongly correlated materials. The on-site Coulomb interaction between localized d/f electrons is self-consistently determined from a model dielectric function that includes both the static dielectric and Thomas-Fermi screening.

[Progress on the impact of adjacent vertebral arch after single open door laminoplasty].

Single-door laminoplasty has been widely used in the treatment of multisegment cervical myelopathy, with the clinical advantages of decompression of the spinal cord, relieving preoperative neurological symptoms or signs, and maintaining cervical mobility. However, in clinical work, patients with limited cervical spine activity after single open door laminoplasty are often encountered, and the direct contact with the adjacent vertebral arch can be observed in the postoperative X-ray of the anterior and lateral cervical spine, which is called the adjacent vertebral arch bone impact, which is one of the important causes of the limited cervical spine movement. In recent years, there have been many reports on the prevention of bone impact, although the short-term clinical effect is significant, but long-term clinical efficacy to be further study, and the cause and the pathogenesis of bone impact is no consensus, this paper on the surgery of adjacent vertebral arch impact epidemiology, biomechanics, clinical performance, surgical effect and improvement.

Virulence gene detection and antimicrobial resistance analysis of Enterococcus faecium in captive giant pandas (Ailuropoda melanoleuca) in China.

Background: The emergence of multidrug resistance among enterococci makes effective treatment of enterococcal infections more challenging. Giant pandas (Ailuropoda melanoleuca) are vulnerable to oral trauma and lesions as they feast on bamboo. Enterococci may contaminate such oral lesions and cause infection necessitating treatment with antibiotics.

A nomogram model integrating LI-RADS features and radiomics based on contrast-enhanced magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma falling the Milan criteria.

Purpose: To establish and validate a nomogram model incorporating both liver imaging reporting and data system (LI-RADS) features and contrast enhanced magnetic resonance imaging (CEMRI)-based radiomics for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) falling the Milan criteria.

Methods: In total, 161 patients with 165 HCCs diagnosed with MVI (n = 99) or without MVI (n = 66) were assigned to a training and a test group. MRI LI-RADS characteristics and radiomics features selected by the LASSO algorithm were used to establish the MRI and Rad-score models, respectively, and the independent features were integrated to develop the nomogram model.

Preoperative Nomogram Incorporating Clinical Factors, Serological Markers and LI-RADS MRI Features to Predict Early Recurrence of Hepatocellular Carcinoma Treated with Transarterial Chemoembolization.

Purpose: To develop and validate a preoperative nomogram model that incorporates clinical factors, serological markers and liver imaging reporting and data system (LI-RADS v2018) MRI features for predicting early recurrence (ER) of hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE).

Methods: One hundred and fourteen patients with HCC who underwent MRI scanning before TACE were enrolled retrospectively and divided into a training cohort (n=80) and a test cohort (n=34). The clinical factors, serological markers and LI-RADS v2018 MRI features associated with ER were determined by univariable and multivariable analyses.

Identification of potential hub genes of gastric cancer.

Background: Gastric cancer (GC) is a malignant tumor originated from gastric mucosa epithelium. It is the third leading cause of cancer mortality in China. The early symptoms are not obvious.

Simultaneous liver steatosis, fibrosis and iron deposition quantification with mDixon quant based on radiomics analysis in a rabbit model.

Purpose: To evaluate the feasibility of simultaneous quantification of liver fibrosis, liver steatosis and abnormal iron deposition using mDixon Quant based on radiomics analysis, and to eliminate the interference among different histopathologic features.

Methods: One hundred and twenty rabbits that were administered CCl4 for 4-16 weeks and a cholesterol rich diet for the initial 4 weeks in the experimental group and 20 rabbits in the control group were examined using mDixon. Radiomics features of the whole liver were extracted from PDFF and R2* and radiomics models for discriminating steatosis: S0-S1 vs.