Are There More Human Cancer Viruses Left to Be Found?

Of the thousands of viruses infecting humans, only seven cause cancer in the general population. Tumor sequencing is now a common cancer medicine procedure, and so it seems likely that more human cancer viruses already would have been found if they exist. Here, we review cancer characteristics that can inform a dedicated search for new cancer viruses, focusing on Kaposi sarcoma herpesvirus and Merkel cell polyomavirus as the most recent examples of successful genomic and transcriptomic searches. We emphasize the importance of epidemiology in determining which cancers to examine and describe approaches to virus discovery. Barriers to virus discovery, such as novel genomes and viral suppression of messenger RNA expression, may exist that prevent virus discovery using existing approaches. Optimally virus hunting should be performed in such a way that if no virus is found, the tumor can be reasonably excluded from having an infectious etiology and new information about the biology of the tumor can be found.

Multi-adductomics: Advancing mass spectrometry techniques for comprehensive exposome characterization.

Adductomics, an emerging field within the 'omics sciences, focuses on the formation and prevalence of DNA, RNA, and protein adducts induced by endogenous and exogenous agents in biological systems. These modifications often result from exposure to environmental pollutants, dietary components, and xenobiotics, impacting cellular functions and potentially leading to diseases such as cancer. This review highlights advances in mass spectrometry (MS) that enhance the detection of these critical modifications and discusses current and emerging trends in adductomics, including developments in MS instrument use, screening techniques, and the study of various biomolecular modifications from mono-adducts to complex hybrid crosslinks between different types of biomolecules. The review also considers challenges, including the need for specialized MS spectra databases and multi-omics integration, while emphasizing techniques to distinguish between exogenous and endogenous modifications. The future of adductomics possesses significant potential for enhancing our understanding of health in relation to environmental exposures and precision medicine.

MiR-125a-5p regulates the radiosensitivity of laryngeal squamous cell carcinoma via HK2 targeting through the DDR pathway.

Objective: To determine the function of miR-125a-5p in laryngeal squamous cell carcinoma (LSCC), its correlation with radiation sensitivity, and the underlying regulatory mechanism. Materials and methods: We conducted the analysis on the correlation between miR-125a-5p and head and neck squamous cell carcinoma (HNSCC) using data obtained from The Cancer Genome Atlas (TCGA). The putative gene targeted by miR-125a-5p has been identified as HK2, while the expression levels of miR-125a-5p and HK2 were measured in laryngeal cancer tissues and cells using RT-PCR. MiR-125a-5p and HK2 were introduced into the lentiviral vector and the vector was used to transfect AMC-HN-8 cells. The roles of miR-125a-5p and HK2 in LSCC and on radiosensitivity were determined by evaluating cell growth, examining colony formation, analyzing flow cytometry, and utilizing the single hit multi-target model. Western blotting was used to measure H2AX and rH2AX levels in the DNA damage response (DDR) pathway. The validation of the interaction between miR-125a-5p and HK2 was conducted through the dual-luciferase assay. To further confirm the association between miR-125a-5p and HK2, as well as its influence on radiosensitivity, rescue experiments were performed. Results: The expression of miR-125a-5p is downregulated in LSCC, while upregulating its expression could suppress cell growth, induce apoptosis, and enhance radiosensitivity. Additionally, HK2 exhibited high expression in LSCC and the biological function was opposite to miR-125a-5p. Western blotting analysis revealed that miR-125a-5p increased rH2AX levels and decreased H2AX levels, conversely, HK2 had the opposite effect on miR-125a-5p. These findings suggested that HK2 may serve as the target gene of miR-125a-5p. The double luciferase assay confirmed the binding of HK2 to miR-125a-5p, and rescue trials confirmed the role of miR-125a-5p in regulating the effects and radiation sensitivity of LSCC by targeting HK2 via the DDR pathway. Conclusion: By targeting HK2 and impacting the DDR pathway, miR-125a-5p has been found to inhibit cellular proliferation, enhance apoptosis, and heighten radiosensitivity in LSCC.

Binding Behavior of Human Hepatoma-Derived Growth Factor on SMYD1.

The protein-induced fluorescence change technique was employed to investigate the interactions between proteins and their DNA substrates modified with the Cy3 fluorophore. It has been reported that the human hepatoma-derived growth factor (HDGF), containing the chromatin-associated N-terminal proline-tryptophan-tryptophan-proline (PWWP) domain (the N-terminal 100 amino acids of HDGF) capable of binding the SMYD1 promoter, participates in various cellular processes and is involved in human cancer. This project investigated the specific binding behavior of HDGF, the PWWP domain, and the C140 domain (the C-terminal 140 amino acids of HDGF) sequentially using protein-induced fluorescence change. We found that the binding of HDGF and its related proteins on Cy3-labeled 15 bp SMYD1 dsDNA will cause a significant decrease in the recorded Cy3 fluorophore intensity, indicating the occurrence of protein-induced fluorescence quenching. The dissociation equilibrium constant was determined by fitting the bound fraction curve to a binding model. An approximate 10-time weaker SMYD1 binding affinity of the PWWP domain was found in comparison to HDGF. Moreover, the PWWP domain is required for DNA binding, and the C140 domain can enhance the DNA binding affinity. Furthermore, we found that the C140 domain can regulate the sequence-specific binding capability of HDGF on SMYD1.

Development and validation of an artificial intelligence model for predicting de novo distant bone metastasis in breast cancer: a dual-center study.

OBJECTIVE: Breast cancer has become the most prevalent malignant tumor in women, and the occurrence of distant metastasis signifies a poor prognosis. Utilizing predictive models to forecast distant metastasis in breast cancer presents a novel approach. This study aims to utilize readily available clinical data and advanced machine learning algorithms to establish an accurate clinical prediction model. The overall objective is to provide effective decision support for clinicians. METHODS: Data from 239 patients from two centers were analyzed, focusing on clinical blood biomarkers (tumor markers, liver and kidney function, lipid profile, cardiovascular markers). Spearman correlation and the least absolute shrinkage and selection operator regression were employed for feature dimension reduction. A predictive model was built using LightGBM and validated in training, testing, and external validation cohorts. Feature importance correlation analysis was conducted on the clinical model and the comprehensive model, followed by univariate and multivariate regression analysis of these features. RESULTS: Through internal and external validation, we constructed a LightGBM model to predict de novo bone metastasis in newly diagnosed breast cancer patients. The area under the receiver operating characteristic curve values of this model in the training, internal validation test, and external validation test1 cohorts were 0.945, 0.892, and 0.908, respectively. Our validation results indicate that the model exhibits high sensitivity, specificity, and accuracy, making it the most accurate model for predicting bone metastasis in breast cancer patients. Carcinoembryonic Antigen, creatine kinase, albumin-globulin ratio, Apolipoprotein B, and Cancer Antigen 153 (CA153) play crucial roles in the model's predictions. Lipoprotein a, CA153, gamma-glutamyl transferase, α-Hydroxybutyrate dehydrogenase, alkaline phosphatase, and creatine kinase are positively correlated with breast cancer bone metastasis, while white blood cell ratio and total cholesterol are negatively correlated. CONCLUSION: This study successfully utilized clinical blood biomarkers to construct an artificial intelligence model for predicting distant metastasis in breast cancer, demonstrating high accuracy. This suggests potential clinical utility in predicting and identifying distant metastasis in breast cancer. These findings underscore the potential prospect of developing economically efficient and readily accessible predictive tools in clinical oncology.

3D/2D-Bismuth Oxybromide Spheres with Selenium-Doped Graphitic Carbon Nitride Sheets: An Efficient Electrocatalyst for the Detection of Arsenic Drug Roxarsone.

Heavy metals are crucial carcinogenic agents threatening the environment and living habituates. Among them, arsenic (As) is an important metalloid that is categorized as a group I toxic carcinogen. Roxarsone (RX) is an organoarsenic antibiotic compound primarily used as a veterinarian drug and growth promoter for poultry animals. The extensive usage of RX increased the accumulation of As in living beings and the ecosystem. Therefore, we have prepared an electrochemical sensor based on 3D bismuth oxybromide with 2D selenium-doped graphitic carbon nitride (BOB/SCN) electrocatalyst for the rapid detection of RX. The elemental and structural details were thoroughly investigated with several spectroscopic techniques. The electrochemical properties were measured by impedance and voltammetric measurements. The electrocatalytic behavior toward the RX was estimated with different voltammetric methods. Therefore, our BOB/SCN-based electrochemical sensor demonstrated a low detection limit (2.3 nM), low quantification value (7.7 nM), optimal sensitivity (0.675 µA µM-1 cm-2), and good linear ranges (0.01-77 and 77-857 µM). Additionally, this sensor showed good electrochemical performance and was applied to monitor the RX in various real samples with remarkable recoveries. Based on these results, our BOB/SCN sensor is a promising electrochemical platform for determining RX.

Strategies for arterial graft optimization at the single-cell level.

Common arterial grafts used in coronary artery bypass grafting include internal thoracic artery (ITA), radial artery (RA) and right gastroepiploic artery (RGA) grafts; of these, the ITA has the best clinical outcome. Here, by analyzing the single-cell transcriptome of different arterial grafts, we suggest optimization strategies for the RA and RGA based on the ITA as a reference. Compared with the ITA, the RA had more lipid-handling-related CD36+ endothelial cells. Vascular smooth muscle cells from the RGA were more susceptible to spasm, followed by those from the RA; comparison with the ITA suggested that potassium channel openers may counteract vasospasm. Fibroblasts from the RA and RGA highly expressed GDF10 and CREB5, respectively; both GDF10 and CREB5 are associated with extracellular matrix deposition. Cell-cell communication analysis revealed high levels of macrophage migration inhibitory factor signaling in the RA. Administration of macrophage migration inhibitory factor inhibitor to mice with partial carotid artery ligation blocked neointimal hyperplasia induced by disturbed flow. Modulation of identified targets may have protective effects on arterial grafts.

Andrographolide suppresses the malignancy of pancreatic cancer via alleviating DNMT3B-dependent repression of tumor suppressor gene ZNF382.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer type that urgently requires effective therapeutic strategies. Andrographolide, a labdane diterpenoid compound abundant in Andrographis paniculata, has anticancer effects against various cancer types, but its anticancer activity and mechanism against PDAC remain largely uncharacterized. PURPOSE: This study explores novel drug target(s) and underlying molecular mechanism of andrographolide against PDAC. STUDY DESIGN AND METHODS: The malignant phenotypes of PDAC cells, PANC-1 and MIA PaCa-2 cells, were measured using MTT, clonogenic assays, and Transwell migration assays. A PDAC xenograft animal model was used to evaluate tumor growth in vivo. Western blot, immunofluorescence and immunohistochemistry were used for measuring protein expression. The TCGA database was analyzed to evaluate promoter methylation status, gene expression, and their relationship with patient survival rates. RT-qPCR was used for detecting mRNA expression. Reporter assays were used for detecting signal transduction pathways. Promoter DNA methylation was determined by sodium bisulfite treatment and methylation-specific PCR (MSP). The biological function and role of specific genes involved in drug effects were measured through gene overexpression. RESULTS: Andrographolide treatment suppressed the proliferation and migration of PDAC cells and impaired tumor growth in vivo. Furthermore, andrographolide induced the mRNA and protein expression of zinc finger protein 382 (ZNF382) in PDAC cells. Overexpression of ZNF382 inhibited malignant phenotypes and cancer-associated signaling pathways (AP-1, NF-κB and ß-catenin) and oncogenes (ZEB-1, STAT-3, STAT-5, and HIF-1α). Overexpression of ZNF382 delayed growth of PANC-1 cells in vivo. ZNF382 mRNA and protein expression was lower in tumor tissues than in adjacent normal tissues of pancreatic cancer patients. Analysis of the TCGA database found the ZNF382 promoter is hypermethylated in primary pancreatic tumors which correlates with its low expression. Furthermore, andrographolide inhibited the expression of DNA methyltransferase 3 beta (DNMT3B) and increased the demethylation of the ZNF382 promoter in PDAC cells. Overexpression of DNMT3B attenuated the andrographolide-suppressed proliferation and migration of PDAC cells. CONCLUSION: Our finding revealed that ZNF382 acts as a tumor suppressor gene in pancreatic cancer and andrographolide restores ZNF382 expression to suppress pancreatic cancer, providing a novel molecular target and a promising therapeutic approach for treating pancreatic cancer.

AI models predicting breast cancer distant metastasis using LightGBM with clinical blood markers and ultrasound maximum diameter.

Breast cancer metastasis significantly impacts women's health globally. This study aimed to construct predictive models using clinical blood markers and ultrasound data to predict distant metastasis in breast cancer patients, ensuring clinical applicability, cost-effectiveness, relative non-invasiveness, and accessibility of these models. Analysis was conducted on data from 416 patients across two centers, focusing on clinical blood markers (tumor markers, liver and kidney function indicators, blood lipid markers, cardiovascular biomarkers) and maximum lesion diameter from ultrasound. Feature reduction was performed using Spearman correlation and LASSO regression. Two models were built using LightGBM: a clinical model (using clinical blood markers) and a combined model (incorporating clinical blood markers and ultrasound features), validated in training, internal test, and external validation (test1) cohorts. Feature importance analysis was conducted for both models, followed by univariate and multivariate regression analyses of these features. The AUC values of the clinical model in the training, internal test, and external validation (test1) cohorts were 0.950, 0.795, and 0.883, respectively. The combined model showed AUC values of 0.955, 0.835, and 0.918 in the training, internal test, and external validation (test1) cohorts, respectively. Clinical utility curve analysis indicated the combined model's superior net benefit in identifying breast cancer with distant metastasis across all cohorts. This suggests the combined model's superior discriminatory ability and strong generalization performance. Creatine kinase isoenzyme (CK-MB), CEA, CA153, albumin, creatine kinase, and maximum lesion diameter from ultrasound played significant roles in model prediction. CA153, CK-MB, lipoprotein (a), and maximum lesion diameter from ultrasound positively correlated with breast cancer distant metastasis, while indirect bilirubin and magnesium ions showed negative correlations. This study successfully utilized clinical blood markers and ultrasound data to develop AI models for predicting distant metastasis in breast cancer. The combined model, incorporating clinical blood markers and ultrasound features, exhibited higher accuracy, suggesting its potential clinical utility in predicting and identifying breast cancer distant metastasis. These findings highlight the potential prospects of developing cost-effective and accessible predictive tools in clinical oncology.

Development and validation of AI models using LR and LightGBM for predicting distant metastasis in breast cancer: a dual-center study.

Objective: This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients. Methods: Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models. Results: The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase. Conclusion: This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.

Select gene mutations associated with survival outcomes in ER-positive ERBB2-negative early-stage invasive breast cancer: A single-institutional tissue bank study.

INTRODUCTION: The prognostic capability of targeted sequencing of primary tumors in patients with estrogen receptor-positive, human epidermal growth factor receptor-2-negative early-stage invasive breast cancer (EBC) in a real-world setting is uncertain. Therefore, we aimed to determine the correlation between a 22-gene mutational profile and long-term survival outcomes in patients with ER+/ERBB2- EBC. PATIENTS AND METHODS: A total of 73 women diagnosed with ER+/ERBB2- EBC between January 10, 2004, and June 2, 2008, were followed up until December 31, 2022. Univariate and multivariate Cox models were constructed to plot the relapse-free survival (RFS) and overall survival (OS). The log-rank test derived p-value was obtained. For external validation, we performed a survival analysis of 1163 comparable patients retrieved from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset. RESULTS: At follow-up, 16 (21.9%) patients had relapsed, while 21 (nearly 29%) harbored mutant genes. Thirty-three missense mutations were detected in 14 genes. The median ages were 51 and 46 years in patients with and without mutations, respectively. Patients with any mutation had a 1.85-fold higher risk of relapse (hazard ratio [HR]: 1.85, 95% confidence interval [CI]: 0.60-5.69) compared to those without any mutation. Patients who harbored any of the six genes (MAP2K4, FGFR3, APC, KIT, RB1, and PTEN) had a nearly 6-fold increase in the risk of relapse (HR: 5.82, 95% CI: 1.31-18.56; p = 0.0069). Multivariate Cox models revealed that the adjusted HR for RFS and OS were 6.67 (95% CI: 1.32-27.57) and 8.31 (p = 0.0443), respectively. METABRIC analysis also demonstrated a trend to significantly worse RFS (p = 0.0576) in the subcohort grouped by having a mutation in any of the six genes. CONCLUSIONS: Our single-institution tissue bank study of Taiwanese women with ER+/ERBB2- EBC suggests that a novel combination of six gene mutations might have prognostic capability for survival outcomes.

Overexpression of ATP5F1A in Cardiomyocytes Promotes Cardiac Reverse Remodeling.

BACKGROUND: The mechanism of cardiac reverse remodeling (CRR) mediated by the left ventricular assist device remains unclear. This study aims to identify the specific cell type responsible for CRR and develop the therapeutic target that promotes CRR. METHODS: The nuclei were extracted from the left ventricular tissue of 4 normal controls, 4 CRR patients, and 4 no cardiac reverse remodeling patients and then subjected to single-nucleus RNA sequencing for identifying key cell types responsible for CRR. Gene overexpression in transverse aortic constriction and dilated cardiomyopathy heart failure mouse model (C57BL/6J background) and pathological staining were performed to validate the results of single-nucleus RNA sequencing. RESULTS: Ten cell types were identified among 126 156 nuclei. Cardiomyocytes in CRR patients expressed higher levels of ATP5F1A than the other 2 groups. The macrophages in CRR patients expressed more anti-inflammatory genes and functioned in angiogenesis. Endothelial cells that elevated in no cardiac reverse remodeling patients were involved in the inflammatory response. Echocardiography showed that overexpressing ATP5F1A through cardiomyocyte-specific adeno-associated virus 9 demonstrated an ability to improve heart function and morphology. Pathological staining showed that overexpressing ATP5F1A could reduce fibrosis and cardiomyocyte size in the heart failure mouse model. CONCLUSIONS: The present results of single-nucleus RNA sequencing and heart failure mouse model indicated that ATP5F1A could mediate CRR and supported the development of therapeutics for overexpressing ATP5F1A in promoting CRR.

RAD51 Expression as a Biomarker to Predict Efficacy of Platinum-Based Chemotherapy and PD-L1 Blockade for Muscle-Invasive Bladder Cancer.

RAD51, a key recombinase that catalyzes homologous recombination (HR), is commonly overexpressed in multiple cancers. It is curial for DNA damage repair (DDR) to maintain genomic integrity which could further determine the therapeutic response. Herein, we attempt to explore the clinical value of RAD51 in therapeutic guidance in muscle-invasive bladder cancer (MIBC). In this retrospective study, a total of 823 patients with MIBC were included. Zhongshan hospital (ZSHS) cohort (n=134) and The Cancer Genome Atlas-Bladder Cancer (TCGA-BLCA) cohort (n=391) were included for the investigation of chemotherapeutic response. The IMvigor210 cohort (n=298) was utilized to interrogate the predictive efficacy of RAD51 status to programmed cell death ligand-1 (PD-L1) blockade. In addition, the association of RAD51 with genomic instability and tumor immune contexture was investigated. Patients with RAD51 overexpression were more likely to benefit from both platinum-based chemotherapy and immunotherapy rather than RAD51-low patients. The TMB high PD-L1 high RAD51 high subgroup possessed the best clinical benefits from PD-L1 blockade. RAD51-high tumors featured by genomic instability were correlated to highly inflamed and immunogenic contexture with activated immunotherapeutic pathway in MIBC. RAD51 could serve as a prognosticator for treatment response to platinum-based chemotherapy and PD-L1 inhibitor in MIBC patients. Besides, it could also improve the predictive efficacy of TMB and PD-L1.

Lemon Peel Water Extract: A Novel Material for Retinal Health, Protecting Retinal Pigment Epithelial Cells against Dynamin-Related Protein 1-Mediated Mitochondrial Fission by Blocking ROS-Stimulated Mitogen-Activated Protein Kinase/Extracellular Signal-Regulated Kinase Pathway.

Previous studies showed that NaIO3 can induce oxidative stress-mediated retinal pigment epithelium (RPE) damage to simulate age-related macular degeneration (AMD). Lemon peel is rich in antioxidants and components that can penetrate the blood-retinal barrier, but their role in retinal oxidative damage remains unexplored. Here, we explore the protection of lemon peel ultrasonic-assisted water extract (LUWE), containing large amounts of flavonoids and polyphenols, against NaIO3-induced retinal degeneration. We initially demonstrated that LUWE, orally administered, prevented retinal distortion and thinning on the inner and outer nuclei layers, downregulating cleaved caspase-3 protein expression in RPE cells in NaIO3-induced mice. The effect of LUWE was achieved through the suppression of apoptosis and the associated proteins, such as cleaved PARP and cleaved caspase-3, as suggested by NaIO3-induced ARPE-19 cell models. This is because LUWE reduced reactive oxygen species-mediated mitochondrial fission via regulating p-Drp-1 and Fis1 expression. We further confirmed that LUWE suppresses the expression of p-MEK-1/2 and p-ERK-1/2 in NaIO3-induced ARPE-19 cells, thereby providing the protection described above, which was confirmed using PD98059 and U0126. These results indicated that LUWE prevents mitochondrial oxidative stress-mediated RPE damage via the MEK/ERK pathway. Elucidation of the molecular mechanism may provide a new protective strategy against retinal degeneration.

FK228 suppress the growth of human malignant pleural mesothelioma tumor independent to epithelioid or non-epithelioid histology.

Human malignant pleural mesothelioma (hMPM) is an aggressive, rare disease with a poor prognosis. Histologically, MPM is categorized into epithelioid, biphasic, and sarcomatoid subtypes, with the epithelioid subtype generally displaying a better response to treatment. Conversely, effective therapies for the non-epithelioid subtypes are limited. This study aimed to investigate the potential role of FK228, a histone deacetylase inhibitor, in the suppression of hMPM tumor growth. We conducted a comprehensive analysis of the histological and molecular characteristics of two MPM cell lines, CRL-5820 (epithelioid) and CRL-5946 (non-epithelioid). CRL-5946 cells and non-epithelioid patient-derived xenografted mice exhibited heightened growth rates compared to those with epithelioid MPM. Both CRL-5946 cells and non-epithelioid mice displayed a poor response to cisplatin. However, FK228 markedly inhibited the growth of both epithelioid and non-epithelioid tumor cells in vitro and in vivo. Cell cycle analysis revealed FK228-induced G1/S and mitotic arrest in MPM cells. Caspase inhibitor experiments demonstrated that FK228-triggered apoptosis occurred via a caspase-dependent pathway in CRL-5946 but not in CRL-5820 cells. Additionally, a cytokine array analysis showed that FK228 reduced the release of growth factors, including platelet-derived and vascular endothelial growth factors, specifically in CRL-5946 cells. These results indicate that FK228 exhibits therapeutic potential in MPM by inducing cytotoxicity and modulating the tumor microenvironment, potentially benefiting both epithelioid and non-epithelioid subtypes.

Single-Cell Transcriptomic Analysis Reveals Myocardial Fibrosis Mechanism of Doxorubicin-Induced Cardiotoxicity.

Myocardial fibrosis is a pathological feature of doxorubicin-induced chronic cardiotoxicity that severely affects the prognosis of oncology patients. However, the specific cellular and molecular mediators driving doxorubicin-induced cardiac fibrosis, and the relative impact of different cell populations on cardiac fibrosis, remain unclear.This study aimed to explore the mechanism of doxorubicin-induced cardiotoxicity and myocardial fibrosis and to find potential therapeutic targets. Single-cell RNA sequencing was used to analyze the transcriptome of non-cardiomyocytes from normal and doxorubicin-induced chronic cardiotoxicity in mouse model heart tissue.We established a mouse model of doxorubicin-induced cardiotoxicity with a well-defined fibrotic phenotype. Analysis of single-cell sequencing results showed that fibroblasts were the major origin of extracellular matrix in doxorubicin-induced myocardial fibrosis. Further resolution of fibroblast subclusters showed that resting fibroblasts were converted to matrifibrocytes and then to myofibroblasts to participate in the myocardial remodeling process in response to doxorubicin treatment. Ctsb expression was significantly upregulated in fibroblasts after doxorubicin-induced.This study provides a comprehensive map of the non-cardiomyocyte landscape at high resolution, reveals multiple cell populations contributing to pathological remodeling of the cardiac extracellular matrix, and identifies major cellular sources of myofibroblasts and dynamic gene-expression changes in fibroblast activation. Finally, we used this strategy to detect potential therapeutic targets and identified Ctsb as a specific target for fibroblasts in doxorubicin-induced myocardial fibrosis.

Upregulated dual oxidase 1-induced oxidative stress and caspase-1-dependent pyroptosis reflect the etiologies of heart failure.

BACKGROUND: Oxidative stress is implicated in the pathogenesis of heart failure. Dual oxidase 1 (DUOX1) might be important in heart failure development through its mediating role in oxidative stress. This study was designed to evaluate the potential role of DUOX1 in heart failure. MATERIALS AND METHODS: AC16 cells were treated with 2 µmol/L of doxorubicin (DOX) for 12, 24, and 48 h to construct a heart failure model. DUOX1 overexpression and silencing in AC16 cell were established. DUOX1 expression was detected by Quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Pyroptosis and reactive oxygen species (ROS) production were measured by flow cytometry. RESULTS: Increased DUOX1 expression levels were observed after DOX treatment for 24 h in AC16 cells. DUOX1 silencing inhibited DOX-induced pyroptosis and ROS production. The release of IL-1ß, IL-18, and lactate dehydrogenase (LDH), and expression levels of pyroptosis-related proteins were also decreased. DUOX1 overexpression increased pyroptosis, ROS production, IL-1ß, IL-18, and LDH release, and pyroptosis-related protein expression. N-acetyl-cysteine (NAC) significantly reversed DUOX1-induced pyroptosis, ROS, and related factors. CONCLUSION: These results suggest that DUOX1-derived genotoxicity could promote heart failure development. In the process, oxidative stress and pyroptosis may be involved in the regulation of DUOX1 in heart failure.

Advances in preclinical surgical therapy of cardiovascular diseases.

Cardiovascular disease is the most common cause of death worldwide, resulting in millions of deaths annually. Currently, there are still some deficiencies in the treatment of cardiovascular diseases. Innovative surgical treatments are currently being developed and tested in response to this situation. Large animal models, which are similar to humans in terms of anatomy, physiology, and genetics, play a crucial role in connecting basic research and clinical applications. This article reviews recent preclinical studies and the latest clinical advancements in cardiovascular disease based on large animal models, with a focus on targeted delivery, neural regulation, cardiac remodeling, and hemodynamic regulation. It provides new perspectives and ideas for clinical translation and offers new methods for clinical treatment.

Comparative study of Scleromitrion diffusum and Oldenlandia corymbosa: Microscopy, TLC, HPLC, and antioxidant activity.

Quality control of herbal medicines is crucial, especially the role of herbal drug identification. This is essential for preventing the misuse of herbs, which can affect efficacy or cause toxicity. Scleromitrion diffusum is a common herb, yet it is often mistaken for Oldenlandia corymbosa. This study analyzed the morphology, microscopy, thin-layer chromatography (TLC), and high-pressure liquid chromatography (HPLC) using two markers, asperuloside and scandoside methyl ester, to distinguish between S. diffusum and O. corymbosa with the analysis included 10 samples of S. diffusum and 10 samples of O. corymbosa collected from the Taiwan market. By quantifying the total polyphenols and flavonoids, we investigated the antioxidant activity, including the 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging effect, 2,2'-azino-bis 3-ethylbenzothiazoline-6-sulfonic acid (ABTS•+) scavenging effect, and reducing power to further elucidate the biological effects of the two herbs. The results of this study revealed notable differences in microscopy and suggested a TLC method for distinguishing between the two herbs in the market. In HPLC, the ratios of asperuloside and scandoside methyl ester differed between the two herbs. S. diffusum contained a higher asperuloside content. In contrast, O. corymbosa contained higher concentrations of scandoside methyl esters. With more total polyphenols and flavonoids in S. diffusum than those in O. corymbosa, the antioxidant activity of S. diffusum was superior to that of O. corymbosa. This study provides a comprehensive understanding for the identification and quality evaluation of S. diffusum in the market. RESEARCH HIGHLIGHTS: The study consolidates and clarifies the morphological and microscopic differences between Scleromitrion diffusum and Oldenlandia corymbosa - a common adulterant species of S. diffusum on the Taiwan markets. Using Asperuloside and Scandoside methyl ester as two chemical markers, the study proposes a TLC method for rapidly testing S. diffusum and O. corymbosa on the market. Through HPLC analysis, our results showed that S. diffusum and O. corymbosa had a clear difference in the ratio of two markers, Asperuloside and Scandoside methyl ester: Asperuloside/Scandoside methyl ester in S. diffusum is higher than that in O. corymbosa. Through phytochemicals contents, including total phenols content, flavonoids content, and antioxidant activity, including DPPH, ABTS•+ scavenging activity, and reducing power, S. diffusum showed slightly higher levels of phenols and flavonoids as well as a better antioxidant activity than O. corymbosa.

A retrospective analysis of comorbidities in patients with psoriasis at a single centre.

Introduction: Psoriasis is a chronic inflammatory disease occurring worldwide. It is currently considered a multi-system disease, which is associated with several comorbidities. Aim: To deeply understand the clinical characteristics of psoriasis comorbidities and explore the relationship between psoriasis comorbidities, different subtypes and related influencing factors. Material and methods: This retrospective study analysed data from the electronic inpatient medical record system of dermatology and non-dermatology departments at a tertiary hospital in China. We collected relevant demographic data and clinical features of all patients diagnosed with psoriasis from January 2013 to September 2023. Results: This study ultimately included a total of 1097 patients with psoriasis. Psoriasis vulgaris was the most common among the subtypes of psoriasis, with 957 (87.2%) cases. The sample consisted of 65.6% of males and 34.4% of females, with an average age of 53.5 ±15.2 years. Common comorbidities of psoriasis included hypertension (38.2%), hyperlipidaemia (29.4%), type 2 diabetes mellitus (24.6%), fatty liver disease (21.4%), coronary heart disease (21.0%), tumours (15.5%), gastroduodenal disease (14.4%), osteoarthropathy (11.8%), and cerebrovascular disease (10.8%). The incidence of hypertension (p = 0.015), hyperuricemia (p < 0.001), osteoarthropathy (p < 0.001), and autoimmune disease (p = 0.003) among different subtypes of psoriasis showed statistically significant differences. In addition, gender, smoking and alcohol consumption all have significant impacts on the distribution of comorbidities. Conclusions: The distribution of psoriasis comorbidities and complications varies among different subtypes of psoriasis. Lifestyles such as smoking and alcohol abuse, as well as gender, are also associated with the occurrence of psoriasis comorbidities.