Repurposing flubendazole for glioblastoma ferroptosis by affecting xCT and TFRC proteins.

New uses of old drugs hold great promise for clinical translation. Flubendazole, an FDA-approved antiparasitic drug, has been shown to target p53 and promote apoptosis in glioblastoma (GBM) cells. However, its damaging mechanism in GBM remains elusive.

Cell death pathways: molecular mechanisms and therapeutic targets for cancer.

Cell death regulation is essential for tissue homeostasis and its dysregulation often underlies cancer development. Understanding the different pathways of cell death can provide novel therapeutic strategies for battling cancer. This review explores several key cell death mechanisms of apoptosis, necroptosis, autophagic cell death, ferroptosis, and pyroptosis.

Epimedin A inhibits the PI3K/AKT/NF-κB signalling axis and osteoclast differentiation by negatively regulating TRAF6 expression.

Background: Epimedin A (EA) has been shown to suppress extensive osteoclastogenesis and bone resorption, but the effects of EA remain incompletely understood. The aim of our study was to investigate the effects of EA on osteoclastogenesis and bone resorption to explore the corresponding signalling pathways.

Methods: Rats were randomly assigned to the sham operation or ovariectomy group, and alendronate was used for the positive control group.

The Bayesian Regularized Quantile Varying Coefficient Model.

The quantile varying coefficient (VC) model can flexibly capture dynamical patterns of regression coefficients. In addition, due to the quantile check loss function, it is robust against outliers and heavy-tailed distributions of the response variable, and can provide a more comprehensive picture of modeling via exploring the conditional quantiles of the response variable. Although extensive studies have been conducted to examine variable selection for the high-dimensional quantile varying coefficient models, the Bayesian analysis has been rarely developed.

Elevated triglyceride-glucose-body mass index associated with lower probability of future regression to normoglycemia in Chinese adults with prediabetes: a 5-year cohort study.

Objective: Despite the clear association of TyG-BMI with prediabetes and the progression of diabetes, no study to date has examined the relationship between TyG-BMI and the reversal of prediabetes to normoglycemia.

Methods: 25,279 participants with prediabetes who had physical examinations between 2010 and 2016 were enrolled in this retrospective cohort study. The relationship between baseline TyG-BMI and regression to normoglycemia from prediabetes was examined using the Cox proportional hazards regression model in this study.

ZLDI-8 suppresses angiogenesis and vasculogenic mimicry in drug-resistant NSCLC in vitro and in vivo.

Aims: The chemotherapy drugs for NSCLC often face the consequences of treatment failure due to acquired drug resistance. Tumor chemotherapy resistance is often accompanied by angiogenesis. Here, we aimed to investigate the effect and underlying mechanisms of ADAM-17 inhibitor ZLDI-8 we found before on angiogenesis and vasculogenic mimicry(VM) in drug-resistant NSCLC.

Springer: An R package for bi-level variable selection of high-dimensional longitudinal data.

In high-dimensional data analysis, the bi-level (or the sparse group) variable selection can simultaneously conduct penalization on the group level and within groups, which has been developed for continuous, binary, and survival responses in the literature. Zhou et al. (2022) (PMID: 35766061) has further extended it under the longitudinal response by proposing a quadratic inference function-based penalization method in gene-environment interaction studies.

PSME2 identifies immune-hot tumors in breast cancer and associates with well therapeutic response to immunotherapy.

Breast cancer (BrCa) is a heterogeneous disease, which leads to unsatisfactory prognosis in females worldwide. Previous studies have proved that tumor immune microenvironment (TIME) plays crucial roles in oncogenesis, progression, and therapeutic resistance in Breast cancer. However, biomarkers related to TIME features have not been fully discovered.

Construction of a novel prognostic signature based on the composition of tumor-infiltrating immune cells in clear cell renal cell carcinoma.

Emerging evidence has uncovered that tumor-infiltrating immune cells (TIICs) play significant roles in regulating the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the exact composition of TIICs and their prognostic values in ccRCC have not been well defined. A total of 534 ccRCC samples with survival information and TIIC data from The Cancer Genome Atlas (TCGA) dataset were included in our research.

Sparse group variable selection for gene-environment interactions in the longitudinal study.

Penalized variable selection for high-dimensional longitudinal data has received much attention as it can account for the correlation among repeated measurements while providing additional and essential information for improved identification and prediction performance. Despite the success, in longitudinal studies, the potential of penalization methods is far from fully understood for accommodating structured sparsity. In this article, we develop a sparse group penalization method to conduct the bi-level gene-environment (G   E) interaction study under the repeatedly measured phenotype.

Robust Bayesian variable selection for gene-environment interactions.

Gene-environment (G× E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G× E studies have been commonly encountered, leading to the development of a broad spectrum of robust regularization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies.

Interep: An R Package for High-Dimensional Interaction Analysis of the Repeated Measurement Data.

We introduce , an R package for interaction analysis of repeated measurement data with high-dimensional main and interaction effects. In G × E interaction studies, the forms of environmental factors play a critical role in determining how structured sparsity should be imposed in the high-dimensional scenario to identify important effects. Zhou et al.

Identifying Gene-Environment Interactions With Robust Marginal Bayesian Variable Selection.

In high-throughput genetics studies, an important aim is to identify gene-environment interactions associated with the clinical outcomes. Recently, multiple marginal penalization methods have been developed and shown to be effective in G×E studies. However, within the Bayesian framework, marginal variable selection has not received much attention.

Cervical Cancer Development: Implications of HPV16 E6E7-NFX1-123 Regulated Genes.

High-risk human papillomavirus (HR HPV) causes nearly all cervical cancers, half of which are due to HPV type 16 (HPV16). HPV16 oncoprotein E6 (16E6) binds to NFX1-123, and dysregulates gene expression, but their clinical implications are unknown. Additionally, HPV16 E7's role has not been studied in concert with NFX1-123 and 16E6.

Case Report: Management of Primary Tracheobronchial Light Chain Amyloidosis in a Patient With Biclonal Gammopathy Using a Systemic Bortezomib-Based Regimen.

Primary tracheobronchial light chain (AL) amyloidosis is a rare and heterogeneous disease characterized by the buildup of amyloid deposits in the airway mucosa. Although its treatment remains challenging, the current view is that the localized form can be treated conservatively due to its slow progression. While radiotherapy has proven effective in treating localized form of the disease, some patients do not respond to local treatment and continue to experience poor quality of life, highlighting the need to explore additional treatment strategies.

Development and Validation of a Nomogram for Predicting the Disease Progression of Nonsevere Coronavirus Disease 2019.

Background And Objectives: The majority of coronavirus disease 2019 (COVID-19) cases are nonsevere, but severe cases have high mortality and need early detection and treatment. We aimed to develop a nomogram to predict the disease progression of nonsevere COVID-19 based on simple data that can be easily obtained even in primary medical institutions.

Methods: In this retrospective, multicenter cohort study, we extracted data from initial simple medical evaluations of 495 COVID-19 patients randomized (2:1) into a development cohort and a validation cohort.

Eltrombopag-related renal vein thromboembolism in a patient with immune thrombocytopenia: A case report.

Background: Eltrombopag is an orally administered thrombopoietin receptor agonist linked to a heightened risk of treatment-related thromboembolism. Both venous and arterial thromboses have been documented in the medical literature.

Case Summary: In the absence of nephropathy, a 48-year-old patient receiving eltrombopag for immune thrombocytopenia (ITP) developed renal vein thrombosis and pulmonary embolism.

Recent advances in convex probe endobronchial ultrasound: a narrative review.

Convex probe endobronchial ultrasound (CP-EBUS) has been widely used in the lymph node staging and restaging of lung tumors and the diagnosis of mediastinal diseases. Recent years have seen continuous progress in this technology. For diagnosis, elastography technology can preliminarily distinguish between benign and malignant lesions, so that reduce the number of punctures.

Gene-Environment Interaction: A Variable Selection Perspective.

Gene-environment interactions have important implications for elucidating the genetic basis of complex diseases beyond the joint function of multiple genetic factors and their interactions (or epistasis). In the past, G × E interactions have been mainly conducted within the framework of genetic association studies. The high dimensionality of G × E interactions, due to the complicated form of environmental effects and the presence of a large number of genetic factors including gene expressions and SNPs, has motivated the recent development of penalized variable selection methods for dissecting G × E interactions, which has been ignored in the majority of published reviews on genetic interaction studies.

Integrating Multi-Omics Data for Gene-Environment Interactions.

Gene-environment (G×E) interaction is critical for understanding the genetic basis of complex disease beyond genetic and environment main effects. In addition to existing tools for interaction studies, penalized variable selection emerges as a promising alternative for dissecting G×E interactions. Despite the success, variable selection is limited in terms of accounting for multidimensional measurements.

High Risk α-HPV E6 Impairs Translesion Synthesis by Blocking POLη Induction.

High risk genus α human papillomaviruses (α-HPVs) express two versatile oncogenes (α-HPV E6 and E7) that cause cervical cancer (CaCx) by degrading tumor suppressor proteins (p53 and RB). α-HPV E7 also promotes replication stress and alters DNA damage responses (DDR). The translesion synthesis pathway (TLS) mitigates DNA damage by preventing replication stress from causing replication fork collapse.