Laparoscopic Ultrasound-Guided Transcystic Approach for the Treatment of Common Bile Duct Stones.

Background: The treatment of choledocholithiasis with nondilated common bile duct (CBD) is a challenge for surgeons who often choose endoscopic retrograde cholangiopancreatography with laparoscopic cholecystectomy (LC) staging surgery instead of simultaneous laparoscopic CBD exploration with LC because of the small CBD diameter. This study aims to introduce and assess the clinical applicability of a technique we developed to identify and extract CBD stones using laparoscopic ultrasound (LUS). Methods: We retrospectively reviewed surgical procedures and clinical data of 13 patients who underwent LC and CBD exploration using LUS between May 2022 and August 2023. The cystic duct was used for CBD stone removal. Results: Ten patients were successfully treated; 2 patients with residual stones were treated with ursodeoxycholic acid, whereas 1 patient required a microincision near the CBD and choledochoscopy because of stone incarceration in the duodenal papilla. The CBD diameter was 6 mm (5-9 mm). There were less than three CBD stones, with diameters of 2-6 mm; the median operative time was 105 minutes (range, 52-155 minutes). One patient developed postoperative cholangitis. The median postoperative hospital stay was 6 days (3-8 days). The stone clearance rate was 76.9%, and the CBD stone detection rate was 100%. No intraoperative complications, postoperative bile leakage, and mortality occurred. Conclusions: CBD exploration and transcystic stone extraction under LUS guidance are safe and effective approaches for patients with choledocholithiasis; strict control over surgical indications is necessary. This study could provide new strategies for effectively treating choledocholithiasis.

Exploring the dynamics of antibiotic resistome on plastic debris traveling from the river to the sea along a representative estuary based on field sequential transfer incubations.

The environmental risks arising from ubiquitous microplastics or plastic debris (PD) acting as carriers of antibiotic resistance genes (ARGs) have attracted widespread attention. Enormous amounts of plastic waste are transported by rivers and traverse estuaries into the sea every year. However, changes in the antibiotic resistome within the plastisphere (the biofilms formed on PD) as PD travels through estuaries are largely unknown. In this study, we performed sequential migration incubations for PD along Haihe Estuary to simulate the natural process of PD floating from rivers to the ocean. Metagenomic sequencing and analysis techniques were used to track microbial communities and antibiotic resistome on migrating PD and in seawater representing the marine environment. The total relative gene copies of ARGs on traveling PD remained stable. As migration between greatly varied waters, additional ARG subtypes were recruited to the plastisphere. Above 80 % ARG subtypes identified in the plastisphere were persistent throughout the migration, and over 30 % of these persistent ARGs were undetected in seawater. The bacterial hosts composition of ARGs on PD progressively altered as transported downstream. Human pathogenic bacteria carrying ARGs (HPBs-ARG) exhibited decreasing trends in abundance and species number during transfer. Individual HPBs-ARG persisted on transferred PD and were absent in seawater samples, comprising Enterobacter cloacae, Klebsiella pneumoniae, Mycobacterium tuberculosis, and Vibrio parahaemolyticus. Based on all detected ARGs and HPBs-ARG, the Projection Pursuit model was applied to synthetically evaluate the potential risks of antibiotic resistance on migrating PD. Diminished risks on PD were observed upon the river-to-sea journey but consistently remained significantly higher than in seawater. The potential risks posed to marine environments by drifting PD as dispersal vectors for antibiotic resistance deserve greater attention. Our results provide initial insights into the dynamics or stability of antibiotic resistome on PD crossing distinct aquatic systems in field estuaries.

Computational identification and clinical validation of a novel risk signature based on coagulation-related lncRNAs for predicting prognosis, immunotherapy response, and chemosensitivity in colorectal cancer patients.

Background: Coagulation is critically involved in the tumor microenvironment, cancer progression, and prognosis assessment. Nevertheless, the roles of coagulation-related long noncoding RNAs (CRLs) in colorectal cancer (CRC) remain unclear. In this study, an integrated computational framework was constructed to develop a novel coagulation-related lncRNA signature (CRLncSig) to stratify the prognosis of CRC patients, predict response to immunotherapy and chemotherapy in CRC, and explore the potential molecular mechanism. Methods: CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the substantial bulk or single-cell RNA transcriptomics from Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR (RT-qPCR) data from CRC cell lines and paired frozen tissues were used for validation. We performed unsupervised consensus clustering of CRLs to classify patients into distinct molecular subtypes. We then used stepwise regression to establish the CRLncSig risk model, which stratified patients into high- and low-risk groups. Subsequently, diversified bioinformatics algorithms were used to explore prognosis, biological pathway alteration, immune microenvironment, immunotherapy response, and drug sensitivity across patient subgroups. In addition, weighted gene coexpression network analysis was used to construct an lncRNA-miRNA-mRNA competitive endogenous network. Expression levels of CRLncSig, immune checkpoints, and immunosuppressors were determined using RT-qPCR. Results: We identified two coagulation subclusters and constructed a risk score model using CRLncSig in CRC, where the patients in cluster 2 and the low-risk group had a better prognosis. The cluster and CRLncSig were confirmed as the independent risk factors, and a CRLncSig-based nomogram exhibited a robust prognostic performance. Notably, the cluster and CRLncSig were identified as the indicators of immune cell infiltration, immunoreactivity phenotype, and immunotherapy efficiency. In addition, we identified a new endogenous network of competing CRLs with microRNA/mRNA, which will provide a foundation for future mechanistic studies of CRLs in the malignant progression of CRC. Moreover, CRLncSig strongly correlated with drug susceptibility. Conclusion: We developed a reliable CRLncSig to predict the prognosis, immune landscape, immunotherapy response, and drug sensitivity in patients with CRC, which might facilitate optimizing risk stratification, guiding the applications of immunotherapy, and individualized treatments for CRC.

Construction of a non-negative matrix factorization model of immunogenic cell death-related genes in lung adenocarcinoma and analysis of survival prognosis.

Purpose: To explore the effectiveness of the model based on non-negative matrix factorization (NMF), analyze the tumor microenvironment and immune microenvironment for evaluating the prognosis of lung adenocarcinoma, establish a risk model, and screen independent prognostic factors. Methods: Downloading the transcription data files and clinical information files of lung adenocarcinoma from TCGA database and GO database, the R software was used to establish the NMF cluster model, and then the survival analysis between groups, tumor microenvironment analysis, and immune microenvironment analysis was performed according to the NMF cluster result. R software was used to construct prognostic models and calculate risk scores. Survival analysis was used to compare survival differences between different risk score groups. Results: Two ICD subgroups were established according to the NMF model. The survival of the ICD low-expression subgroup was better than that of the ICD high-expression subgroup. Univariate COX analysis screened out HSP90AA1, IL1, and NT5E as prognostic genes, and the prognostic model established on this basis has clinical guiding significance. Conclusion: The model based on NMF has the prognostic ability for lung adenocarcinoma, and the prognostic model of ICD-related genes has a certain guiding significance for survival.

Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer.

Background: Currently, a very small number of patients with colorectal cancer (CRC) respond to immune checkpoint inhibitor (ICI) treatment. Therefore, there is an urgent need to investigate effective biomarkers to determine the responsiveness to ICI treatment. Recently, aberrant 5-methylcytosine (m5C) RNA modification has emerged as a key player in the pathogenesis of cancer. Thus, we aimed to explore the predictive signature based on m5C regulator-related genes for characterizing the immune landscapes and predicting the prognosis and response to therapies. Methods: The Cancer Genome Atlas (TCGA) cohort was used as the training set, while GEO data sets, real-time quantitative PCR (RT-qPCR) analysis from paired frozen tissues, and immunohistochemistry (IHC) data from tissue microarray (TMA) were used for validation. We constructed a novel signature based on three m5C regulator-related genes in patients with rectal adenocarcinoma (READ) using a least absolute shrinkage and selection operator (LASSO)-Cox regression and unsupervised consensus clustering analyses. Additionally, we correlated the three-gene signature risk model with the tumor immune microenvironment, immunotherapy efficiency, and potential applicable drugs. Results: The m5C methylation-based signature was an independent prognostic factor, where low-risk patients showed a stronger immunoreactivity phenotype and a superior response to ICI therapy. Conversely, the high-risk patients had enriched pathways of cancer hallmarks and presented immune-suppressive state, which demonstrated that they are more insensitive to immunotherapy. Additionally, the signature markedly correlated with drug susceptibility. Conclusions: We developed a reliable m5C regulator-based risk model to predict the prognosis, clarify the molecular and tumor microenvironment status, and identify patients who would benefit from immunotherapy or chemotherapy. Our study could provide vital guidance to improve prognostic stratification and optimize personalized therapeutic strategies for patients with rectal cancer.

Caudodorsal approach combined with in situ split for laparoscopic right posterior sectionectomy.

BACKGROUND: Laparoscopic right posterior sectionectomy (LRPS) was technically challenging and lack of standardization. There were some approaches for LRPS, such as caudal approach and dorsal approach. During our practice, we initiated pure LRPS using the caudodorsal approach with in situ split and present several advantages of this method. METHODS: From April 2018 to December 2021, consecutive patients who underwent pure LRPS using the caudodorsal approach with in situ split at our institution entered into this retrospective study. The key point of the caudodorsal approach was that the right hepatic vein was exposed from peripheral branches toward the root and the parenchyma was transected from the dorsal side to ventral side. Specially, the right perihepatic ligaments were not divided to keep the right liver in situ before parenchymal dissection for each case. RESULTS: 11 patients underwent pure LRPS using the caudodorsal approach with in situ split. There were 9 hepatocellular carcinoma, 1 sarcomatoid hepatocellular carcinoma, and 1 hepatic hemangioma. Five patients had mild cirrhosis and 1 had moderate cirrhosis. All the procedures were successfully completed laparoscopically. The median operative time was 375 min (range of 290-505 min) and the median blood loss was 300 ml (range of 100-1000 ml). Five patients received perioperative blood transfusion, of which 1 patient received autologous blood transfusion and 2 patients received blood transfusion due to preoperative moderate anemia. No procedure was converted to open surgery. Two patients who suffered from postoperative complications, improved after conservative treatments. The median postoperative stay was 11 days (range of 7-25 days). No postoperative bleeding, hepatic failure, and mortality occurred. CONCLUSION: The preliminary clinical effect of the caudodorsal approach with in situ split for LRPS was satisfactory. Our method was feasible and expected to provide ideas for the standardization of LRPS. Further researches are required due to some limitations of this study.

Characterization of sialylation-related long noncoding RNAs to develop a novel signature for predicting prognosis, immune landscape, and chemotherapy response in colorectal cancer.

Aberrant sialylation plays a key biological role in tumorigenesis and metastasis, including tumor cell survival and invasion, immune evasion, angiogenesis, and resistance to therapy. It has been proposed as a possible cancer biomarker and a potential therapeutic target of tumors. Nevertheless, the prognostic significance and biological features of sialylation-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC) remain unclear. This study aimed to develop a novel sialylation-related lncRNA signature to accurately evaluate the prognosis of patients with CRC and explore the potential molecular mechanisms of the sialylation-related lncRNAs. Here, we identified sialylation-related lncRNAs using the Pearson correlation analysis on The Cancer Genome Atlas (TCGA) dataset. Univariate and stepwise multivariable Cox analysis were used to establish a signature based on seven sialylation-related lncRNAs in the TCGA dataset, and the risk model was validated in the Gene Expression Omnibus dataset. Kaplan-Meier curve analysis revealed that CRC patients in the low-risk subgroup had a better survival outcome than those in the high-risk subgroup in the training set, testing set, and overall set. Multivariate analysis demonstrated that the sialylation-related lncRNA signature was an independent prognostic factor for overall survival, progression-free survival, and disease-specific survival prediction. The sialylation lncRNA signature-based nomogram exhibited a robust prognostic performance. Furthermore, enrichment analysis showed that cancer hallmarks and oncogenic signaling were enriched in the high-risk group, while inflammatory responses and immune-related pathways were enriched in the low-risk group. The comprehensive analysis suggested that low-risk patients had higher activity of immune response pathways, greater immune cell infiltration, and higher expression of immune stimulators. In addition, we determined the sialylation level in normal colonic cells and CRC cell lines by flow cytometry combined with immunofluorescence, and verified the expression levels of seven lncRNAs using real-time quantitative polymerase chain reaction. Finally, combined drug sensitivity analysis using the Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, and Profiling Relative Inhibition Simultaneously in Mixtures indicated that the sialylation-related lncRNA signature could serve as a potential predictor for chemosensitivity. Collectively, this is the first sialylation lncRNA-based signature for predicting the prognosis, immune landscape, and chemotherapeutic response in CRC, and may provide vital guidance to facilitate risk stratification and optimize individualized therapy for CRC patients.

Solvatochromic Cellular Stress Sensors Reveal the Compactness Heterogeneity and Dynamics of Aggregated Proteome.

Deterioration of protein homeostasis (proteostasis) often induces aberrant proteome aggregation. Visualization and dissection of the stressed proteome are of particular interest given their association with numerous degenerative diseases. Recent progress in chemical cellular stress sensors allows for direct visualization of aggregated proteome. Beyond its localization and morphology, the physicochemical nature and the dynamics of the aggregated proteome have been challenging to explore. Herein, we developed a series of solvatochromic fluorene-based D-π-A probes that can selectively and noncovalently bind to a misfolded and aggregated proteome and report on their compactness heterogeneity upon cellular stresses. We achieved this goal by variation of the heterocyclic acceptors to modulate their solvatochromism and binding affinity to amorphous aggregated proteins. The optimized sensor P6 was capable of sensing the polarity differences among different aggregated proteins via its fluorescence emission wavelength. In live cells, P6 revealed the cellular compactness heterogeneity in the aggregated proteome upon cellular stresses. Given the combinative solvatochromic and noncovalent properties, our probe can reversibly monitor the dynamic changes in the aggregated proteome compactness upon stress and after stress recovery, suggesting its potential applications in search of therapeutics to counteract disease-causing proteome stresses.

Prevalence of coal worker's pneumoconiosis: a systematic review and meta-analysis.

Global prevalence trend and regional differences of coal worker's pneumoconiosis (CWP) remain unclear. This study aimed to provide systematic and comprehensive evidence for the global prevalence of CWP. Literature research for studies that reported prevalence of CWP was conducted in PubMed, CNKI, and Web of Science. The identified studies were strictly screened according to predetermined inclusion and exclusion criteria. The pooled prevalence of CWP in different periods and regions was calculated. A total of 37 studies were included after screening, and data from the Coal Workers' Health Surveillance Program was additionally included in the meta-analysis. The global pooled prevalence of CWP decreased from 23.33% (95% confidence interval [CI]: 18.03%, 28.62%) before 1970 to 6.00% (95% CI: 4.11%, 7.90%) in 1981-1990, but indicated a rebound (10.35%, 95% CI: 8.08%, 12.62%) in 1991-2000 and finally dropped to 2.29% (95% CI: 2.06%, 2.51%) in 2011-2020. In the recent 30 years, the top three pooled prevalence of CWP was found in Europe, China, and the USA, respectively. Few articles have reported the prevalence in developing regions, but available evidence indicated that the prevalence in developing regions was much higher than that in developed regions. Higher pooled prevalence was observed in studies which reported larger number of miners in collieries, older average age of miners, underground collieries, and longer dust exposure time. The global prevalence of CWP indicates a rebound in 1990s, but the overall trend is downward in the recent 60 years. The prevention and treatment of CWP should be currently emphasized in developing countries.

Metabolomic and Transcriptomic Profiling Identified Significant Genes in Thymic Epithelial Tumor.

Thymomas and thymic carcinomas are malignant thymic epithelial tumors (TETs) with poor outcomes if non-resectable. However, the tumorigenesis, especially the metabolic mechanisms involved, is poorly studied. Untargeted metabolomics analysis was utilized to screen for differential metabolic profiles between thymic cancerous tissues and adjunct noncancerous tissues. Combined with transcriptomic data, we comprehensively evaluated the metabolic patterns of TETs. Metabolic scores were constructed to quantify the metabolic patterns of individual tumors. Subsequent investigation of distinct clinical outcomes and the immune landscape associated with the metabolic scores was conducted. Two distinct metabolic patterns and differential metabolic scores were identified between TETs, which were enriched in a variety of biological pathways and correlated with clinical outcomes. In particular, a high metabolic score was highly associated with poorer survival outcomes and immunosuppressive status. More importantly, the expression of two prognostic genes (ASNS and BLVRA) identified from differential metabolism-related genes was significantly associated with patient survival and may play a key role in the tumorigenesis of TETs. Our findings suggest that differential metabolic patterns in TETs are relevant to tumorigenesis and clinical outcome. Specific transcriptomic alterations in differential metabolism-related genes may serve as predictive biomarkers of survival outcomes and potential targets for the treatment of patients with TETs.

Comprehensive Analysis of a Cancer-Immunity Cycle-Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer.

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle-based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle-related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint-associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle-based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.

Prognostic Values and Underlying Regulatory Network of Cohesin Subunits in Esophageal Carcinoma.

Background: Cohesin is a highly conserved and ubiquitously expressed protein complex. While increasing evidence suggests that cohesin dysregulation is vital in the carcinogenesis of numerous malignancies, little is known about the prognostic values and potential mechanisms of cohesin subunits and direct regulators in esophageal carcinoma (ESCA). Methods: RNA-sequencing data from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression (GTEx) were used. The subunits and regulators of cohesin affecting the prognosis of ESCA were screened by Kaplan-Meier survival analysis; univariate and multivariate Cox regression analyses were performed; and the receiver-operating characteristic (ROC) curve was determined. The ESCA hazard model and nomogram map were constructed by integrating the clinical data. We used functional analysis and protein-protein interaction (PPI) networks to explore underlying pathways. Finally, immunohistochemistry was performed to examine the expression levels of cohesin subunits in tissue microarray (TMA). Results: Transcriptome data from multiple ESCA patient datasets showed cohesin subunits SMC1A, SMC1B, SMC3, STAG1, STAG2, RAD21, and cohesin regulators including ESCO2, NIPBL, MAU2, WAPL, PDS5A and PDS5B were all upregulated in ESCA tissues compared to normal tissues. Survival analysis demonstrated that high STAG2 expression was significantly associated with poorer overall survival (OS) and progression-free survival (PFS) in esophageal adenocarcinoma (EAC). In contrast, high RAD21 expression was significantly correlated with better OS in esophageal squamous cell carcinoma (ESCC). Moreover, STAG2 and RAD21 were identified as independent prognostic factors and predictive biomarkers in EAC and ESCC, respectively. Functional enrichment analysis further revealed that STAG2 and RAD21 were mainly involved in the mitotic nuclear division, DNA repair, angiogenesis, epithelial-mesenchymal transition (EMT), and oncogenic signaling pathways. PPI analysis illustrated that STAG2 and RAD21 could cross-talk through cancer-associated modules and performed the core roles of the whole PPI network. Using TMA, STAG2 protein expression positively correlated with lymph node metastasis and advanced clinical stage of EAC patients, whereas there was a negative correlation between RAD21 protein expression and the malignant clinicopathological parameters in ESCC. Conclusion: These findings suggest that STAG2 and RAD21 can be used as predictive biomarkers for risk assessment and prognostic stratification in ESCA, which provide potential novel insights into molecular targets of ESCA.

Comprehensive bioinformatics analysis identifies LAPTM5 as a potential blood biomarker for hypertensive patients with left ventricular hypertrophy.

Left ventricular hypertrophy (LVH) is a pivotal manifestation of hypertensive organ damage associated with an increased cardiovascular risk. However, early diagnostic biomarkers for assessing LVH in patients with hypertension (HT) remain indefinite. Here, multiple bioinformatics tools combined with an experimental verification strategy were used to identify blood biomarkers for hypertensive LVH. GSE74144 mRNA expression profiles were downloaded from the Gene Expression Omnibus (GEO) database to screen candidate biomarkers, which were used to perform weighted gene co-expression network analysis (WGCNA) and establish the least absolute shrinkage and selection operator (LASSO) regression model, combined with support vector machine-recursive feature elimination (SVM-RFE) algorithms. Finally, the potential blood biomarkers were verified in an animal model. A total of 142 hub genes in peripheral blood leukocytes were identified between HT with LVH and HT without LVH, which were mainly involved in the ATP metabolic process, oxidative phosphorylation, and mitochondrial structure and function. Notably, lysosomal associated transmembrane protein 5 (LAPTM5) was identified as the potential diagnostic marker of hypertensive LVH, which showed strong correlations with diverse marker sets of reactive oxygen species (ROS) and autophagy. RT-PCR validation of blood samples and cardiac magnetic resonance imaging (CMRI) showed that the expression of LAPTM5 was significantly higher in the HT with LVH model than in normal controls, LAPTM5 demonstrated a positive association with the left ventricle wall thickness as well as electrocardiogram (ECG) parameters widths of the QRS complex and QTc interval. In conclusion, LAPTM5 may be a potential biomarker for the diagnosis of LVH in patients with HT, and it can provide new insights for future studies on the occurrence and the molecular mechanisms of hypertensive LVH.

SEMA6B Overexpression Predicts Poor Prognosis and Correlates With the Tumor Immunosuppressive Microenvironment in Colorectal Cancer.

Background: Semaphorin 6b (SEMA6B) is a member of the semaphorin axon-guidance family and has been demonstrated to both induce and inhibit tumor progression. However, the role of SEMA6B in colorectal cancer (CRC) has remained unclear. This study sought to explore the promising prognostic biomarker for CRC and to understand the expression pattern, clinical significance, immune effects, and biological functions of SEMA6B. Methods: SEMA6B expression in CRC was evaluated via multiple gene and protein expression databases and we identified its prognostic value through The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Correlations between SEMA6B expression and components of the tumor immune microenvironment were analyzed by packages implemented in R, Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), and Tumor-Immune System Interactions database (TISIDB). RNA interference was performed to silence the expression of SEMA6B to explore its biological roles in the colon cancer cell lines HCT116 and LoVo. Results: The messenger RNA (mRNA) level of SEMA6B and the protein expression were higher in CRC tissues than adjacent normal tissues from multiple CRC datasets. High SEMA6B expression was significantly associated with dismal survival. Multivariate Cox regression analysis demonstrated that SEMA6B was an independent prognostic factor for progression-free survival (PFS). The nomogram showed a favorable predictive ability in PFS. Functional enrichment analysis and the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm revealed that the gene cluster associated with the high SEMA6B group were prominently involved in immune responses and inflammatory activities. Notably, SEMA6B expression was positively correlated with infiltrating levels of CD4+ T cells, macrophages, myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), neutrophils, and dendritic cells. Moreover, SEMA6B expression displayed strong correlations with diverse marker sets of immunosuppressive cells in CRC. Integrative analysis revealed that immunosuppressive molecules and immune checkpoints were markedly upregulated in CRC samples with high SEMA6B expression. Furthermore, knockdown of SMEA6B in colon cancer cells significantly inhibited cell proliferation, migration, invasion and reduced the mRNA levels of immunosuppressive molecules. Conclusion: Our findings provide evidence that high SEMA6B expression correlated with adverse prognosis and the tumor immunosuppressive microenvironment in CRC patients. Therefore, SEMA6B may serve as a novel prognostic biomarker for CRC, which offers further insights into developing CRC-targeted immunotherapies.

Hepatocellular carcinoma with inferior vena cava and right atrium thrombus: A case report.

BACKGROUND: Hepatocellular carcinoma (HCC) with inferior vena cava and right atrium thrombus is rare, accounting for approximately 1.4%-4.9% of cases. These patients are rarely reported, but the condition is being increasingly discovered with advances in imaging techniques, and their prognosis is extremely pessimistic with no current effective treatment. This condition is further associated with unexpected sudden death by cardiac arrest and acute large area pulmonary embolism. CASE SUMMARY: A 34-year-old man with advanced HCC with a hepatic vein thrombus extending into the right atrium had a long-term, disease-free survival following 5-mo sequential treatment combined with transcatheter arterial chemoembolization and curative liver resection. No severe adverse effects were encountered, such as massive hemorrhage or pulmonary embolism. The proper selection of operative method is an important factor. CONCLUSION: HCC with a tumor thrombus extending into the right atrium has a significant impact on the survival of patients. Thrombectomy combined with adjuvant therapy may be beneficial for these patients.

Lp-PLA2 inhibition prevents Ang II-induced cardiac inflammation and fibrosis by blocking macrophage NLRP3 inflammasome activation.

Macrophage-mediated inflammation plays an important role in hypertensive cardiac remodeling, whereas effective pharmacological treatments targeting cardiac inflammation remain unclear. Lipoprotein-associated phospholipase A2 (Lp-PLA2) contributes to vascular inflammation-related diseases by mediating macrophage migration and activation. Darapladib, the most advanced Lp-PLA2 inhibitor, has been evaluated in phase III trials in atherosclerosis patients. However, the role of darapladib in inhibiting hypertensive cardiac fibrosis remains unknown. Using a murine angiotensin II (Ang II) infusion-induced hypertension model, we found that Pla2g7 (the gene of Lp-PLA2) was the only upregulated PLA2 gene detected in hypertensive cardiac tissue, and it was primarily localized in heart-infiltrating macrophages. As expected, darapladib significantly prevented Ang II-induced cardiac fibrosis, ventricular hypertrophy, and cardiac dysfunction, with potent abatement of macrophage infiltration and inflammatory response. RNA sequencing revealed that darapladib strongly downregulated the expression of genes and signaling pathways related to inflammation, extracellular matrix, and proliferation. Moreover, darapladib substantially reduced the Ang II infusion-induced expression of nucleotide-binding oligomerization domain-like receptor with pyrin domain 3 (NLRP3) and interleukin (IL)-1ß and markedly attenuated caspase-1 activation in cardiac tissues. Furthermore, darapladib ameliorated Ang II-stimulated macrophage migration and IL-1ß secretion in macrophages by blocking NLRP3 inflammasome activation. Darapladib also effectively blocked macrophage-mediated transformation of fibroblasts into myofibroblasts by inhibiting the activation of the NLRP3 inflammasome in macrophages. Overall, our study identifies a novel anti-inflammatory and anti-cardiac fibrosis role of darapladib in Lp-PLA2 inhibition, elucidating the protective effects of suppressing NLRP3 inflammasome activation. Lp-PLA2 inhibition by darapladib represents a novel therapeutic strategy for hypertensive cardiac damage treatment.

COVID-19 lesion discrimination and localization network based on multi-receptive field attention module on CT images.

Since discovered in Hubei, China in December 2019, Corona Virus Disease 2019 named COVID-19 has lasted more than one year, and the number of new confirmed cases and confirmed deaths is still at a high level. COVID-19 is an infectious disease caused by SARS-CoV-2. Although RT-PCR is considered the gold standard for detection of COVID-19, CT plays an important role in the diagnosis and evaluation of the therapeutic effect of COVID-19. Diagnosis and localization of COVID-19 on CT images using deep learning can provide quantitative auxiliary information for doctors. This article proposes a novel network with multi-receptive field attention module to diagnose COVID-19 on CT images. This attention module includes three parts, a pyramid convolution module (PCM), a multi-receptive field spatial attention block (SAB), and a multi-receptive field channel attention block (CAB). The PCM can improve the diagnostic ability of the network for lesions of different sizes and shapes. The role of SAB and CAB is to focus the features extracted from the network on the lesion area to improve the ability of COVID-19 discrimination and localization. We verify the effectiveness of the proposed method on two datasets. The accuracy rate of 97.12%, specificity of 96.89%, and sensitivity of 97.21% are achieved by the proposed network on DTDB dataset provided by the Beijing Ditan Hospital Capital Medical University. Compared with other state-of-the-art attention modules, the proposed method achieves better result. As for the public COVID-19 SARS-CoV-2 dataset, 95.16% for accuracy, 95.6% for F1-score and 99.01% for AUC are obtained. The proposed network can effectively assist doctors in the diagnosis of COVID-19 CT images.

Therapeutic Potential of Glutamine Pathway in Lung Cancer.

Cancer cells tend to obtain the substances needed for their development depending on altering metabolic characteristics. Among the reorganized metabolic pathways, Glutamine pathway, reprogrammed to be involved in the physiological process including energy supply, biosynthesis and redox homeostasis, occupies an irreplaceable role in tumor cells and has become a hot topic in recent years. Lung cancer currently maintains a high morbidity and mortality rate among all types of tumors and has been a health challenge that researchers have longed to overcome. Therefore, this study aimed to clarify the essential role of glutamine pathway played in the metabolism of lung cancer and its potential therapeutic value in the interventions of lung cancer.

High SEMA4C expression promotes the epithelial-mesenchymal transition and predicts poor prognosis in colorectal carcinoma.

Semaphorin 4C (SEMA4C), is an important regulator of axonal guidance and aggravates tumor development. However, the roles and prognostic value of SEMA4C in colorectal cancer (CRC) remain unclear. Here, bioinformatics analyses of transcriptome data from multiple CRC patient datasets and immunohistochemical staining of a CRC tissue microarray (TMA) (n=83) showed that SEMA4C mRNA and protein expression were higher in CRC tissues than normal colorectal tissues. SEMA4C mRNA and protein expression correlated with pathologic stage and metastasis in CRC patients. Higher SEMA4C expression was associated with shorter overall survival, consensus molecular subtype 4 (CMS4), and DNA hypomethylation of SEMA4C in CRC patients. Multivariate Cox regression analyses revealed that SEMA4C expression was an independent prognostic predictor in CRC patients. Gene set expression analysis (GSEA) illustrated that SEMA4C expression had remarkable correlations with epithelial-mesenchymal transition (EMT) as well as hedgehog, Wnt/ß-catenin, TGF-ß, and Notch signaling pathways. Receiver operating characteristic (ROC) curve analysis demonstrated that SEMA4C expression accurately distinguished between the CMS4 and CMS1-3 subtypes of CRC patients. By inhibiting EMT, SEMA4C silencing reduced in vitro proliferation, migration, and invasion by CRC cells. These findings suggest that SEMA4C is a CMS4-associated gene that enhances CRC progression by inducing EMT.