Development and Validation of a Pathomics-Based Prognostic Model for Patients with Lung Adenocarcinoma Undergoing First-Line EGFR-TKI Therapy.

Background: Accurate prognostic prediction is crucial for personalized treatment of patients with lung adenocarcinoma (LUAD) receiving epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). This study aims to develop and validate a pathomics-based prognostic model for EGFR-TKI-treated patients with LUAD.

Patients And Methods: Data from 122 patients with LUAD who underwent first-line EGFR-TKI therapy were retrospectively analyzed.

A Novel Model for Predicting Microsatellite Instability in Endometrial Cancer: Integrating Deep Learning-Pathomics and MRI-Based Radiomics.

Rationale And Objectives: To develop and validate a novel model based on multiparametric MRI (mpMRI) and whole slide images (WSIs) for predicting microsatellite instability (MSI) status in endometrial cancer (EC) patients.

Materials And Methods: A total of 136 surgically confirmed EC patients were included in this retrospective study. Patients were randomly divided into a training set (96 patients) and a validation set (40 patients) in a 7:3 ratio.

Triptonide stabilizes BIM to enhance oxaliplatin-induced ferroptosis and apoptosis in colorectal cancer.

Oxaliplatin (OXA) is a common chemotherapeutic agent for advanced colorectal cancer. However, its effectiveness is limited by drug resistance, highlighting the need for combination therapies. In this study, Triptonide (TN), a diterpenoid compound is used to enhance the sensitivity of OXA, and the underlying mechanisms are investigated.

Astragalin induces immunogenic cell death in liver cancer by targeting NQO2 to promote ROS-mediated endoplasmic reticulum stress pathway.

Astragalin (ASG), a natural flavonoid glycoside, is known for its multiple pharmacological effects. In this study, we explored the antitumor effects of ASG and its underlying mechanism. Specifically, the growth inhibitory effects of ASG were assessed.

Identifying key psychological characteristics among Chinese individuals with eating disorders: an exploratory graph and network analysis.

Background: Interventions targeting core characteristics of eating disorders (EDs) can effectively alleviate symptoms. However, it remains unclear whether these characteristics exhibit cultural specificity within the Chinese population. This study combines exploratory graph analysis (EGA) and network analysis to identify key psychological characteristics in Chinese patients with EDs.

Cardiovascular safety of propranolol oral solution in infantile hemangiomas: a disproportionality analysis based on the FAERS database.

This study aims to explore the potential association between propranolol and cardiovascular adverse events (AEs) through real-world evidence. Reports from the FDA Adverse Event Reporting System (FAERS) database spanning from January 2014 to September 2024, identifying propranolol oral solution as the primary suspected (PS) drug, were analyzed. Disproportionality analysis employed four key metrics: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma-Poisson Shrinkage (MGPS) to identify positive signals of cardiovascular AEs potentially associated with propranolol oral solution.

Magnesium microspheres for enhanced transarterial chemoembolization therapy of hepatocellular carcinoma: From animal models to a pilot clinical study.

Transarterial chemoembolization (TACE) has been extensively used in clinic to treat unresectable hepatocellular carcinoma (HCC). Herein, magnesium microspheres (Mg MSs) were used as embolic devices to enhance lipiodol-mediated TACE. After being dispersed in lipiodol and injected into tumors, Mg MSs would continuously generate hydrogen and magnesium hydroxide, which could neutralize the acidic tumor microenvironment, restore exhausted CD8 T cells, reverse immunosuppression, and trigger specific T cell-mediated antitumor responses, synergistically resulting in inhibited tumor growth.

Vesicular Stomatitis Virus Glycoprotein- and Lentiviral RNA-Based Robust Approach for Rapid and Accurate Quantification of Viable Lentiviral Vectors.

Chimeric antigen receptor (CAR)-T cell (CAR-T) therapy is often used for treating malignant tumors, including leukemia and lymphoma. Lentiviral vectors (LVs) and their dosages are the key determinants of efficient and stable CAR-T cell preparation, cell quality, and treatment costs. However, the rapid quantification of viable LVs remains challenging because of difficulties in determining LV's viability.

Immune-activated microspheres for enhanced chemoembolization of hepatocellular carcinoma by blocking the adenosine A2A receptor.

Transcatheter arterial chemoembolization (TACE) stands as the frontline strategy for unresectable hepatocellular carcinoma (HCC), effectively eliminating cancer cells through direct cytotoxicity and immunogenic cell death (ICD). However, TACE triggers rapid tumor apoptosis, which promotes the release of intracellular ATP into the extracellular space. This ATP is sequentially hydrolyzed to adenosine (ADO) by ectonucleotidases (CD39 and CD73) overexpressed in the tumor microenvironment (TME), resulting in ADO accumulation.

Multiparametric MRI-based radiomics and clinical nomogram predicts the recurrence of hepatocellular carcinoma after postoperative adjuvant transarterial chemoembolization.

Background: This study was undertaken to develop and validate a radiomics model based on multiparametric magnetic resonance imaging (MRI) for predicting recurrence in patients with hepatocellular carcinoma (HCC) following postoperative adjuvant transarterial chemoembolization (PA-TACE).

Methods: In this retrospective study, 149 HCC patients (81 for training, 36 for internal validation, 32 for external validation) treated with PA-TACE were included in two medical centers. Multiparametric radiomics features were extracted from three MRI sequences.

The evolving landscape of biomarkers for systemic therapy in advanced hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains one of the most prevalent and deadliest cancers. With the approval of multiple first- and second-line agents, especially the combination therapies based on immune checkpoint inhibitor (ICI) regimens, the landscape of systemic therapy for advanced HCC (aHCC) is more diverse than ever before. The efficacy of current systemic therapies shows great heterogeneity in patients with aHCC, thereby identifying biomarkers for response prediction and patient stratification has become an urgent need.

Fibrosis-4plus score: a novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): an international multicenter study.

Background/aims: A large percentage of patients undergoing esophagogastroduodenoscopy (EGD) screening do not have esophageal varices (EV) or have only small EV. We evaluated a large, international, multicenter cohort to develop a novel score, termed FIB-4plus, by combining the fibrosis-4 (FIB-4) score, liver stiffness measurement (LSM), and spleen stiffness measurement (SSM) to identify high-risk EV (HRV) in compensated cirrhosis.

Methods: This international cohort study involved patients with compensated cirrhosis from 17 Chinese hospitals and one Croatian institution (NCT04546360).

MELK prevents radiofrequency ablation-induced immunogenic cell death and antitumor immune response by stabilizing FABP5 in hepatocellular malignancies.

Background: Radiofrequency ablation (RFA) is an efficient treatment with unlimited potential for liver cancer that can effectively reduce patient mortality. Understanding the biological process related with RFA treatment is important for improving treatment strategy. This study aimed to identify the critical targets for regulating the efficacy of RFA.

Predicting early recurrence in locally advanced gastric cancer after gastrectomy using CT-based deep learning model: a multicenter study.

Background: Early recurrence in patients with locally advanced gastric cancer (LAGC) portends aggressive biological characteristics and a dismal prognosis. Predicting early recurrence may help determine treatment strategies for LAGC. The goal is to develop a deep learning model for early recurrence prediction (DLER) based on preoperative multiphase computed tomography (CT) images and to further explore the underlying biological basis of the proposed model.

CRISPR-Cas9 screening identified novel subtypes of cutaneous melanoma based on essential cancer genes.

Our primary objective was to identify genes critical for cutaneous melanoma (CM) and related typing, based on essential genes, to generate novel insights for clinical management and immunotherapy of patients with CM. We analyzed RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and sequencing data of 29 CM cell line from Cancer Cell Line Encyclopedia (CCLE) databases. Combined with DepMap database, 406 CM essential cancer genes were finally obtained.

Polydopamine-Based Targeted Nanosystem for Chemo/Photothermal Therapy of Retinoblastoma in a Mouse Orthotopic Model.

Background: At present, the few photothermal/chemotherapy studies about retinoblastoma that have been reported are mainly restricted to ectopic models involving subcutaneous implantation. However, eyeball is unique physiological structure, the blood-retina barrier (BRB) hinders the absorption of drug molecules through the systemic route. Moreover, the abundant blood circulation in the fundus accelerates drug metabolism.

Microneedle fractional radiofrequency associated with drug delivery for facial atrophic acne scars and skin rejuvenation.

Microneedle fractional radiofrequency (MFRF) has been used to improve photoaging and scars. This study aimed to evaluate the efficacy and safety of MFRF with basic fibroblast growth factor (bFGF) for facial atrophic acne scars and skin rejuvenation by blinded visual evaluation, self-report, and reflective confocal microscopy (RCM). Fifteen subjects were randomized to the MFRF with bFGF group and fifteen to the MFRF group.

Utilizing multicompartmental restriction spectrum magnetic resonance imaging for liver fibrosis characterization in a mouse model.

Background: Currently, an advanced imaging method may be necessary for magnetic resonance imaging (MRI) to diagnosis and quantify liver fibrosis (LF).

Purpose: To evaluate the feasibility of the multicompartmental restriction spectrum imaging (RSI) model to characterize LF in a mouse model.

Methods: Thirty mice with carbon tetrachloride (CCl)-induced LF and eight control mice were investigated using multi-b-value (ranging from 0 to 2000 s/mm) diffusion-weighted imaging (DWI) on a 3T scanner.