Real-world systemic sequential therapy with regorafenib for recurrent hepatocellular carcinoma: analysis of 93 cases from a single center.

BACKGROUND: Regorafenib is an oral multikinase inhibitor and became the first second-line systemic treatment for hepatocellular carcinoma (HCC) following the phase III RESORCE trial. This single-center study retrospectively analyzed the clinical data and follow-up results of patients with recurrent HCC treated with regorafenib and discussed the prognostic factors to provide guidance for clinical treatment. METHODS: Ninety-three recurrent HCC patients were enrolled in the research and follow up from December 2017 to December 2020. Clinical and pathological data were collected. SPSS software v26.0 was used (Chicago, IL, USA) for statistical analysis. A two-sided P < 0.05 was considered statistically significant. RESULTS: The patients included 81 males and 12 females with a median age of 57 years. Eighty-seven patients had hepatitis B virus (HBV) infection. The objective response rate (ORR) was 14.0%, and the disease control rate (DCR) was 62.4%. The median overall survival (mOS) and median time to progression (mTTP) were 15.9 and 5.0 months. Multivariate analysis showed that Child-Pugh classification, the Eastern Cooperative Oncology Group performance status (ECOG PS), the neutrophil-to-lymphocyte ratio (NLR), combined treatment, and the time from first diagnosis of HCC to second-line treatment were independent factors affecting the prognosis of recurrent HCC patients. CONCLUSIONS: This real-world study demonstrated similar findings to those of the RESORCE trial. Regorafenib could effectively improve the prognosis of patients after first-line treatment failure. Combination therapy under multidisciplinary treatment (MDT) team guidance could be effective in impeding tumor progression and improving the prognosis of recurrent HCC patients.

Renal denervation ameliorates cardiac metabolic remodeling in diabetic cardiomyopathy rats by suppressing renal SGLT2 expression.

This study aimed to investigate the effects of renal denervation (RDN) on diabetic cardiomyopathy (DCM) and explore the related mechanisms. Male Sprague-Dawley rats were fed high-fat chow and injected with low-dose streptozotocin to establish a DCM model. Six rats served as controls. The surviving rats were divided into three groups: control group, DCM group and DCM + RDN group. RDN surgery was performed in the fifth week. At the end of the experiment, all rats were subjected to 18F-FDG PET/CT and metabolic cage studies. Cardiac function and structure were evaluated by echocardiography and histology. Myocardial substrate metabolism and mitochondrial function were assessed by multiple methods. In the 13th week, the DCM rats exhibited cardiac hypertrophy and interstitial fibrosis accompanied by diastolic dysfunction. RDN ameliorated DCM-induced cardiac dysfunction (E/A ratio: RDN 1.07 ± 0.18 vs. DCM 0.93 ± 0.12, P < 0.05; E/E' ratio: RDN 10.74 ± 2.48 vs. DCM 13.25 ± 1.99, P < 0.05) and pathological remodeling (collagen volume fraction: RDN 5.05 ± 2.05% vs. DCM 10.62 ± 2.68%, P < 0.05). Abnormal myocardial metabolism in DCM rats was characterized by suppressed glucose metabolism and elevated lipid metabolism. RDN increased myocardial glucose uptake and oxidation while reducing the absorption and utilization of fatty acids. Meanwhile, DCM decreased mitochondrial ATP content, depolarized the membrane potential and inhibited the activity of respiratory chain complexes, but RDN attenuated this mitochondrial damage (ATP: RDN 30.98 ± 7.33 µmol/gprot vs. DCM 22.89 ± 5.90 µmol/gprot, P < 0.05; complexes I, III and IV activity: RDN vs. DCM, P < 0.05). Furthermore, both SGLT2 inhibitor and the combination treatment produced similar effects as RDN alone. Thus, RDN prevented DCM-induced cardiac dysfunction and pathological remodeling, which is related to the improvement of metabolic disorders and mitochondrial dysfunction.

Metabolism reprogramming signature associated with stromal cells abundance in tumor microenvironment improve prognostic risk classification for gastric cancer.

BACKGROUND: Stromal cells play an important role in the process of tumor progression, but the relationship between stromal cells and metabolic reprogramming is not very clear in gastric cancer (GC). METHODS: Metabolism-related genes associated with stromal cells were identified in The Cancer Genome Atlas (TCGA) and GSE84437 datasets, and the two datasets with 804 GC patients were integrated into a training cohort to establish the prognostic signature. Univariate Cox regression analysis was used to screen for prognosis-related genes. A risk score was constructed by LASSO regression analysis combined with multivariate Cox regression analysis. The patients were classified into groups with high and low risk according to the median value. Two independent cohorts, GSE62254 (n = 300) and GSE15459 (n = 191), were used to externally verify the risk score performance. The CIBERSORT method was applied to quantify the immune cell infiltration of all included samples. RESULTS: A risk score consisting of 24 metabolic genes showed good performance in predicting the overall survival (OS) of GC patients in both the training (TCGA and GSE84437) and testing cohorts (GSE62254 and GSE15459). As the risk score increased, the patients' risk of death increased. The risk score was an independent prognostic indicator in both the training and testing cohorts suggested by the univariate and multivariate Cox regression analyses. The patients were clustered into four subtypes according to the quantification of 22 kinds of immune cell infiltration (ICI). The proportion of ICI Cluster C with the best prognosis in the low-risk group was approximately twice as high as that in the high-risk group, and the risk score of ICI Cluster C was significantly lower than that of the other three subtypes. CONCLUSION: Our study proposed the first scheme for prognostic risk classification of GC from the perspective of tumor stromal cells and metabolic reprogramming, which may contribute to the development of therapeutic strategies for GC.

Integrated analysis of 1804 samples of six centers to construct and validate a robust immune-related prognostic signature associated with stromal cell abundance in tumor microenvironment for gastric cancer.

BACKGROUND: Stromal cells in tumor microenvironment could promote immune escape through a variety of mechanisms, but there are lacking research in the field of gastric cancer (GC). METHODS: We identified differential expressed immune-related genes (DEIRGs) between the high- and low-stromal cell abundance GC samples in The Cancer Genome Atlas and GSE84437 datasets. A risk score was constructed basing on univariate cox regression analysis, LASSO regression analysis, and multivariate cox regression analysis in the training cohort (n=772). The median value of the risk score was used to classify patients into groups with high and low risk. We conducted external validation of the prognostic signature in four independent cohorts (GSE26253, n=432; GSE62254, n=300; GSE15459, n=191; GSE26901, n=109) from the Gene Expression Omnibus (GEO) database. The immune cell infiltration was quantified by the CIBERSORT method. RESULTS: The risk score contained 6 genes (AKT3, APOD, FAM19A5, LTBP3, NOV, and NOX4) showed good performance in predicting 5-year overall survival (OS) rate and 5-year recurrence-free survival (RFS) rate of GC patients. The risk death and recurrence of GC patients growing with the increasing risk score. The patients were clustered into three subtypes according to the infiltration of 22 kinds of immune cells quantified by the CIBERSORT method. The proportion of cluster A with the worst prognosis in the high-risk group was significantly higher than that in the low-risk group; the risk score of cluster C subtype with the best prognosis was significantly lower than that of the other two subtypes. CONCLUSION: This study established and validated a robust prognostic model for gastric cancer by integrated analysis 1804 samples of six centers, and its mechanism was explored in combination with immune cell infiltration characterization.

Development and validation of a CTNNB1-associated metabolic prognostic model for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy closely related to metabolic reprogramming. We investigated how CTNNB1 mutation regulates the HCC metabolic phenotype and thus affects the prognosis of HCC. We obtained the mRNA expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA), the International Cancer Genomics Consortium (ICGC) and the Gene Expression Omnibus database (GSE14520 and GSE116174). We conducted gene set enrichment analysis on HCC patients with and without mutant CTNNB1 through TCGA dataset. The Kaplan-Meier analysis and univariate Cox regression analysis assisted in screening metabolic genes related to prognosis, and the prognosis model was constructed using the Lasso and multivariate Cox regression analysis. The prognostic model showed good prediction performance in both the training cohort (TCGA) and the validation cohorts (ICGC, GSE14520, GSE116174), and the high-risk group presented obviously poorer overall survival compared with low-risk group. Cox regression analysis indicated that the risk score can be used as an independent predictor for the overall survival of HCC. The immune infiltration in different risk groups was also evaluated in this study to explore underlying mechanisms. This study is also the first to describe an metabolic prognostic model associated with CTNNB1 mutations and could be implemented for determining the prognoses of individual patients in clinical practice.

Eleven immune-gene pairs signature associated with TP53 predicting the overall survival of gastric cancer: a retrospective analysis of large sample and multicenter from public database.

BACKGROUND: Growing attention have been paid to the relationship between TP53 and tumor immunophenotype, but there are still lacking enough search on the field of gastric cancer (GC). MATERIALS AND METHODS: We identified differential expressed immune-related genes (DEIRGs) between the TP53-altered GC samples (n = 183) and without TP53-altered GC samples (n = 192) in The Cancer Genome Atlas and paired them. In the TCGA cohort (n = 350), a risk score was determined through univariate and multivariate cox regression and Lasso regression analysis. Patients were divided into two groups, high-risk and low-risk, based on the median risk score. Four independent cohorts (GSE84437,n = 431; GSE62254, n = 300; GSE15459, n = 191; GSE26901, n = 100) from the Gene Expression Omnibus (GEO) database were used to validate the reliability and universal applicability of the model. RESULTS: The signature contained 11 gene pairs showed good performance in predicting progression-free survival (PFS), disease-free survival (DFS), disease special survival (DSS), and the overall survival (OS) for GC patients in the TCGA cohort. The subgroup analysis showed that the signature was suitable for GC patients with different characteristics. The signature could capable of distinguish GC patients with good prognosis and poor prognosis in all four independent external validation cohorts. The high- and low-risk groups differed significantly in the proportion of several immune cell infiltration, especially for the T cells memory resting, T cells memory activated and follicular helper, and Macrophage M0, which was also related to the prognosis of GC patients. CONCLUSION: The present work proposed an innovative system for evaluating the prognosis of gastric cancer. Considering its stability and general applicability, which may become a widely used tool in clinical practice.

Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma.

BACKGROUND: In recent years, the relationship between tumor-associated macrophages (TAMs) and solid tumors has become a research hotspot. This study aims to explore the close relationship of TAMs with metabolic reprogramming genes in hepatocellular carcinoma (HCC) to provide new methods of treatment for HCC. METHODS: The study selected 343 HCC patients with complete survival information (survival time > = 1 month) in the Cancer Genome Atlas (TCGA) as study subjects. Kaplan-Meier survival analysis assisted in determining the relationship between macrophage infiltration and overall survival (OS), and Pearson correlation tests were used to identify metabolic reprogramming genes (MRGs) associated with tumor macrophage abundance. Lasso regression algorithms were used on prognosis-related MRGs identified by Kaplan-Meier survival analysis and univariate Cox regression analysis to construct a risk score; another independent cohort (including 228 HCC patients) from the International Cancer Genome Consortium (ICGC) was used to verify prognostic signature externally. RESULTS: A risk score composed of 8 metabolic genes could accurately predict the OS of a training cohort (TCGA) and a testing cohort (ICGC). The risk score could be widely used for people with different clinical characteristics, and it is a predictor that is independent of other clinical factors that affect prognosis. As expected, compared with the low-risk group, the high-risk group exhibited an obviously higher macrophage abundance, together with a positive correlation between the risk score and the expression levels of three commonly used immune checkpoints (PD1, PDL1, and CTLA4). CONCLUSION: Our study constructed and validated a novel eight-gene signature for predicting HCC patient OS, which may contribute to clinical treatment decisions.

Chinese college students' ability to recognize facial expressions based on their meaning-in-life profiles: An eye-tracking study.

OBJECTIVE: People can be categorized into one of four meaning-in-life profiles: High Presence High Search (HPHS), High Presence Low Search (HPLS), Low Presence High Search (LPHS), and Low Presence Low Search (LPLS).The main goal of this study is to provide a theoretical explanation for why Chinese people with different meaning-in-life profiles have different mental health levels than Western people, based on their emotional-cognitive-processing ability. METHOD: We adopted eye-movement analysis and recognition-judgment experimental paradigm concerning absolute-recognition judgment and relative-recognition judgment in our study. Moreover, we applied a multifactor and multilevel mixed-experimental design. We selected 118 participants for the experiments from the 788 Chinese college students who responded. RESULTS: Our results showed that HPHS individuals preferred positive-emotion pictures, LPLS individuals preferred negative-emotion pictures, HPLS individuals preferred positive- and neutral-emotion pictures, and LPHS individuals preferred neutral-emotion pictures. Moreover, HPHS individuals were better at accurately processing facial expression from pictures, while LPLS individuals lacked such ability. The fine-processing ability of HPLS and LPHS individuals was lower than that of HPHS yet higher than that of LPLS individuals. Moreover, the features of HPLS individuals were closer to HPHS, while those of LPHS individuals were closer to LPLS. CONCLUSIONS: Our findings support the hypothesis that meaning-in-life profiles have different immediate processing abilities and preferences regarding facial expression recognition and different emotional-cognitive-processing ability.

Identification and validation of a five-gene prognostic signature for hepatocellular carcinoma.

BACKGROUND: ARID1A is a commonly mutated tumor suppressor gene found in all human cancer types, but its clinical significance, oncogenic functions, and relevant mechanisms in hepatocellular carcinoma (HCC) are not well understood. OBJECTIVE: We aimed to improving the prognosis risk classification of HCC from the perspective of ARID1A mutations. MATERIALS AND METHODS: We examined the interaction between ARID1A mutations and the overall survival via Kaplan-Meier survival analysis. We used gene set enrichment analysis (GSEA) to elucidate the influence of ARID1A mutations on signaling pathways. A prognostic model was constructed using LASSO and multivariate Cox regression analyses. A receiver operating characteristic (ROC) curve was used to estimate the performance and accuracy of the model. RESULTS: HCC patients with ARID1A mutations presented poor prognosis. By GSEA, we showed that genes upregulated by reactive oxygen species (ROS) and regulated by MYC were positively correlated with ARID1A mutations. A prognostic signature consisting of 5 genes (SRXN1, LDHA, TFDP1, PPM1G, and EIF2S1) was constructed in our research. The signature showed good performance in predicting overall survival (OS) for HCC patients by internal and external validation. CONCLUSION: Our research proposed a novel and robust approach for the prognostic risk classification of HCC patients, and this approach may provide new insights to improve the treatment strategy of HCC.

Beneficial Effects of Sacubitril/Valsartan at Low Doses in an Asian Real-World Heart Failure Population.

This study aimed at analyzing the clinical profile of real-world patients with heart failure with reduced ejection fraction (HFrEF) and evaluating the safety and efficacy of sacubitril/valsartan among Asian patients in daily practice. We conducted a single-center prospective observational cohort study of HFrEF patients treated with sacubitril/valsartan from September 2017 to September 2018 with a follow-up of 6 months. The mean (SD) age of the 110 patients enrolled was 59.7 ± 13.3, 85 (77.3%) were men and 41 (37.3%) had ischemic cardiomyopathy. Thirty-one (27.2%) patients with low systolic blood pressure initiated sacubitril/valsartan on a tiny dose of 12/13 mg. Despite the low mean daily dose achieved in real world mainly because of hypotension, left ventricular ejection fraction increased significantly from 35.4 ± 8.9% at baseline to 43.0 ± 12.2% after 6-month follow-up (P < 0.001). We also observed a significant improvement in a 6-minute walk test (6-MWT) distance and N-terminal pro-B-type natriuretic peptide (NT-proBNP) concentration reduction. No severe adverse event was recorded. Low dose sacubitril/valsartan induces beneficial cardiac reverse remodeling and improves clinical functional performance in real-world HFrEF patients without severe adverse effect. A tiny initial dose may enhance tolerability and reduce discontinuation rate by minimizing hypotension events in patients with low systolic blood pressure. These data further support using low-dose sacubitril/valsartan among eligible patients with HFrEF in Asia.

Development and Validation of a Novel Immune-Gene Pairs Prognostic Model Associated with CTNNB1 Alteration in Hepatocellular Carcinoma.

BACKGROUND Immunotherapy is one of the research hotspots in the field of hepatocellular carcinoma (HCC). Successive clinical trials have shown that patients with CTNNB1 mutations are resistant to immunotherapy, but the mechanism is still unclear. MATERIAL AND METHODS We identified differentially expressed immune genes (DEIGs) in patients with and without CTNNB1 mutations in the Cancer Genome Atlas (TCGA) database and then paired them to explore any correlation with prognosis. Univariate Cox regression analysis and Lasso regression analysis were used to develop the prognostic model. We first divided the TCGA cohort into 29 subgroups for internal validation and then used the International Cancer Genome Consortium (ICGC) cohort to conduct external validation. We also used a CIBERSORT algorithm to quantify immune infiltration of the different risk groups. RESULTS The novel prognostic model consisted of 45 immune-gene pairs with general applicability. It was more accurate than the traditional prognostic signature, which is based on gene expression by comparison of area under the receiver operating characteristic curve (AUC) values. The infiltration proportion of B cells, CD8 T lymphocytes, activated natural killer cells, and M1 macrophages in the low-risk group was greater in the high-risk group, while the infiltration proportion of M0 and M2 macrophages was greater in the high-risk group. CONCLUSIONS In this study, a novel approach was proposed for evaluating HCC prognosis, which may be useful in evaluatingthe intensity of the immune response in the HCC microenvironment.

Identification of biomarkers correlated with hypertrophic cardiomyopathy with co-expression analysis.

Hypertrophic cardiomyopathy (HCM) is reported to be the most common genetic heart disease. To identify key module and candidate biomarkers correlated with clinical prognosis of patients with HCM, we carried out this study with co-expression analysis. To construct a co-expression network of hub genes correlated with HCM, the Weighted Gene Co-expression Network Analysis (WGCNA) was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network analysis of central genes was performed to recognize the interactions of central genes. Gene set enrichment analyses were carried out to discover the possible mechanisms involved in the pathways promoted by hub genes. To validate the hub genes, quantitative real-time polymerase chain reaction (RT-PCR) was performed. Based on the results of topological overlap measure based clustering, 2,351 differentially expressed genes (DEGs) were identified. Those genes were included in six different modules. Of these modules, the yellow and the blue modules showed a pivotal correlation with HCM. DEGs were enriched in immune system procedure associated GO terms and KEGG pathways. We identified nine hub genes (TYROBP, STAT3, CSF1R, ITGAM, SYK, ITGB2, LILRB2, LYN, and HCK) affected the immune system significantly. Among the genes we validated with RT-PCR, TYROBP, CSF1R, and SYK showed significant increasing expression levels in model HCM rats. In conclusion, we identified two modules and nine hub genes, which were prominently associated with HCM. We found that immune system may play a crucial role in the HCM. Accordingly, those genes and pathways might become therapeutic targets with clinical usefulness in the future.

Effects of Angiotensin Receptor Neprilysin Inhibitors on Inducibility of Ventricular Arrhythmias in Rats with Ischemic Cardiomyopathy.

The aims of the present study were to investigate the effects of angiotensin receptor neprilysin inhibitors (ARNi) on the susceptibility of ventricular arrhythmias (VAs) in rats with myocardial infarction (MI) and to explore the related mechanisms.A total of 32 adult male Sprague-Dawley rats were divided into 3 groups: a control group, MI group, and MI+ARNi group. MI was generated by ligation of the left anterior descending coronary artery. ARNi was given at 68 mg/kg/day for 4 weeks after MI surgery. At 4 weeks after MI, electrical programmed stimulation (EPS) was performed in all groups for the evaluation of VAs, and echocardiography was used to evaluate cardiac function. Indicators of sympathetic neural remodeling and cardiac remodeling were detected to further explore the related mechanisms.Four weeks after MI, rats in the ARNi group exhibited low susceptibility of VAs in comparison with that in the MI group, which was coincident with the attenuation of sympathetic nerve remodeling, amelioration of cardiac fibrosis, and regulation of Cx43 expression.ARNi is effective in reducing VAs in rats with ischemic cardiomyopathy, which is associated with attenuating sympathetic nerve remodeling and myocardial fibrosis.

Activated CD4 T cells/Tregs derived immune-metabolism signature provide precise prognosis assessment for gastric cancer and beneficial for treatment option.

Background: The prognostic significance of the ratio of activated CD4 T cells to Tregs infiltrating tumor tissues in gastric cancer (GC) remains unknown. Materials and methods: For the quantification of infiltration of immune cells, the ssGSEA algorithm, which is a single sample gene set enrichment analysis, was utilized. Group A was defined as having activated CD4 T cells/Tregs >1, while group B was defined as having activated CD4 T cells/Tregs <1. To compare the overall survival (OS) of the two groups, the Kaplan-Meier survival analysis was employed. The R package 'limma' was used to identify the immune and metabolism related genes that were expressed differentially between the two groups, with a false discovery rate (FDR) less than 0.05. The risk score (RS) was constructed by combining univariate Cox regression analysis, LASSO penalized Cox regression analysis, and multivariate Cox regression analysis. The median RS was used to classify high-risk (HR) and low-risk (LR) groups. Results: A predicted unfavorable outcome of GC was observed when the ratio of activated CD4 T cells to Tregs was less than 1. Our proposed RS was utilized for prognostic risk categorization in ten distinct independent cohorts (TCGA-STAD, n = 371; GSE84437, n = 433; GSE26253, n = 432; GSE13861, n = 65; GSE15459, n = 192; GSE26899, n = 93; GSE26901, n = 109; GSE28541, n = 40; GSE34942, n = 56; GSE62254, n = 300) and exhibited exceptional precision. In terms of tumor microenvironment (TME) and treatment strategies, compared to the LR group, the HR group was characterized by a higher infiltration levels of stromal cells, Tregs, macrophages, Tfh, mast cells, and NK cells, inclined to activated CD4 T cells/Tregs <1, and exhibited insensitivity to immunotherapy and multiple chemotherapy drugs. In relation to the potential molecular mechanism, the excessive activation of oncogenic pathways such as MAPK, hedgehog, WNT, calcium, and TGF-ß signaling pathways may accelerate the malignant progression of GC by stimulating angiogenesis, promoting EMT, and altering ECM. Conversely, the overactivation of the P53 pathway is likely to inhibit tumor proliferation by regulating the cell cycle. Conclusion: The immune-metabolism signature associated with the ratio of activated CD4 T cells and Tregs could be used to assess prognosis, TME, and treatment strategies in GC patients.

Comprehensive analysis of metabolic pathway activity subtypes derived prognostic signature in hepatocellular carcinoma.

OBJECTIVE: Metabolic reprogramming is one of the hallmarks of cancer, but metabolic pathway activity-related subtypes of hepatocellular carcinoma (HCC) have not been identified. METHODS: Based on the quantification results of 41 metabolic pathway activities by gene set variation analysis, the training cohort (n = 609, merged by TCGA and GSE14520) was clustered into three subtypes (C1, C2, and C3) with the nonnegative matrix factorization method. Totally 1371 differentially expressed genes among C1, C2, and C3 were identified, and an 8-gene risk score was established by univariable Cox regression analysis, least absolute shrinkage and selection operator method, and multivariable Cox regression analysis. RESULTS: C1 had the strongest metabolic activity, good prognosis, the highest CTNNB1 mutation rate, with massive infiltration of eosinophils and natural killer cells. C2 had the weakest metabolic activity, poor prognosis, was younger, was inclined to vascular invasion and advanced stage, had the highest TP53 mutation rate, exhibited a higher expression level of immune checkpoints, accompanied by massive infiltration of regulatory T cells. C3 had moderate metabolic activity and prognosis, the highest LRP1B mutation rate, and a higher infiltration level of neutrophils and macrophages. Internal cohorts (TCGA, n = 370; GSE14520, n = 239), external cohorts (ICGC, n = 231; GSE116174, n = 64), and clinical subgroup validation showed that the risk score was applicable for patients with diverse clinical features and was effective in predicting the prognosis and malignant progression of patients with HCC. Compared with the low-risk group, the high-risk group had a poor prognosis, enhanced cancer stem cell characteristics, activated DNA damage repair, weakened metabolic activity, cytolytic activity, and interferon response. CONCLUSION: We identified HCC subtypes from the perspective of metabolism-related pathway activity and proposed a robust prognostic signature for HCC.

Immunotherapy Efficacy-related Risk Classifier Differentiate Prognostic Characteristics of Gastric Cancer-A Large-scale Retrospective Study.

Prognostic signatures related to the efficacy of immunotherapy have not been determined in gastric cancer (GC). We identified the differentially expressed genes between the CR/PR and SD/PD groups with the R package "limma" (false discovery rate <0.05) in the IMvigor210 data set. The GSE13861 (n=65), GSE15459 (n=192), GSE26899 (n=93), GSE26901 (n=109), GSE28541 (n=40), GSE34942 (n=56), and GSE62254 (n=300) cohorts were merged into a training cohort (n=855). Univariate Cox regression analysis, LASSO penalized Cox regression analysis, and multivariate Cox regression analysis were jointly applied to construct the prognostic model. The Cancer Genome Atlas (TCGA)-STAD (n=371), GSE84437 (n=433), GSE26253 (n=432), and IMvigor210 (n=348) cohorts were utilized for external validation. The GC patients were divided into 16 subgroups according to clinical features for universal applicability validation. Repeated validation confirmed that the overall survival of the high-risk (HR) group was significantly reduced compared with that of the low-risk (LR) group. The HR group showed a higher infiltration abundance of regulatory T cells, macrophages, T follicular helper cells, and natural killer T cells, whereas the infiltration levels of activated CD4 T cells and monocytes were upregulated in the LR group. The calcium, TGF-ß, MAPK, Hedgehog, and KRAS signaling pathways were overactivated in the HR group, while the hallmarks related to DNA damage repair and metabolism were enriched in the LR group. In addition, the LR group had high tumor mutation burden, FLG, and OBSCN mutations. A prognostic risk classifier for GC patients was identified and validated by carrying out a multicenter retrospective study.

Usability of curved keyboard design on the large smartphone: An empirical study.

The curved design is ubiquitous, with a vast user base due to its similarity with in shape to human physiological structure. The curved QWERTY keyboard layout was proposed for one-handed usage on smartphones with ambiguous effects. This study evaluated whether the curved QWERTY could optimize the user experience and input performance on large smartphones better than the traditional straight QWERTY layout. Eight measurements were used to evaluate the usability of each design, six suggesting curved QWERTY failed to achieve outstanding typing performance or subjective user experience, while the other two indicators showed that curved QWERTY had advantages in touch dispersion and touching offset, indicating the possible higher usability it could reach. The results also investigated the potential application of curved designs and provided insights into the optimization methods.

Removal performance, biotransformation pathways and products of sulfamethoxazole in vertical subsurface flow constructed wetlands with different substrates.

For decades, sulfamethoxazole (SMX) has been frequently detected in the aquatic environments due to its high usage and refractory to degradation. Constructed wetland (CW) is regarded as an efficient advanced wastewater technology to eliminate organic pollutants including SMX. In CW system, substrate adsorption and further biodegradation are extremely important in SMX removal; however, the removal performance of SMX by CWs with different substrates varies greatly, and the biotransformation pathways, products, and mechanisms of SMX remain unclear. To address this, we constructed a CW with conventional substrate (CS, gravel) as control (C-CW) and three CWs with emerging substrates (ES, biochar, zeolite and pyrite for B-CW, Z-CW and P-CW, respectively), and explored the performance and mechanisms of SMX removal in CWs. Results illustrated that the removal performance of SMX in CWs with ES reached 94.89-99.35%, and significantly higher than that with CS of 89.50% (p < 0.05). Biodegradation contributed >90% SMX removal in all CWs. The microbial compositions and functions differed among CWs at the middle layer (mixed layer), which shaped diverse resistance pattern and metabolism pathways of microbiomes under SMX stress: P-CW and B-CW cope with SMX stress by enhancing material and energy metabolism, whereas Z-CW does that by enhancing metabolism and exocytosis of xenobiotics. Additionally, nine transformation pathways with 15 transformation products were detected in this study. A reversible process of desamino-SMX being reconverted to SMX might exist in P-CW, which caused a lower SMX removal efficiency in P-CW. This study provided a comprehensive insight into the processes and mechanisms of SMX removal in CWs with different substrates, which would be a useful guidance for substrate selection in CWs in terms of enhanced micropollutants removal.

Empagliflozin ameliorates cardiac dysfunction in heart failure mice via regulating mitochondrial dynamics.

Empagliflozin has cardioprotective effects in patients with heart failure (HF). However, the mechanism by which empagliflozin protects against HF remains controversial. Study aimed to evaluate the effect of empagliflozin on myocardial fibrosis and cardiac function in HF mice and its possible mechanism. C57BL/6 mice were induced with HF by ligation of the left anterior descending coronary artery. At 4 weeks postoperation, mice were randomly given normal saline or empagliflozin for 8 weeks. Echocardiography was used to assess cardiac function. Masson's staining, immunohistochemistry and Western blot analysis were used to detect the degree of myocardial fibrosis. Changes in mitochondria were detected by observing mitochondrial morphology, measuring mitochondrial dynamics-related proteins and analysing the levels of adenosine triphosphate (ATP), adenosine monophosphate (AMP) and adenosine diphosphate (ADP). The mitochondrial fission inhibitor, mdivi1, was used to detect the relationship between mitochondrial dysfunction and cardiac dysfunction in HF mice. HF led to myocardial fibrosis and cardiac dysfunction. However, treatment with empagliflozin reduced these effects. Empagliflozin inhibited mitochondrial fission and improved energy metabolic efficiency in HF mice by regulating the expression of mitochondrial dynamics-related proteins. Similarly, mdivi1 attenuated mitochondrial dysfunction and cardiac dysfunction by inhibiting mitochondrial fission in HF mice. Regulation of mitochondrial dynamics, especially inhibition of mitochondrial fission, may be a potential target for reducing cardiac damage in patients with HF. Empagliflozin improved myocardial fibrosis and cardiac dysfunction by modulating mitochondrial dynamics in HF mice. Thus, the cardiac protective effect of empagliflozin may be related to the normalization of mitochondria and the increase in ATP production.

Pyroptosis, apoptosis, and necroptosis molecular subtype derived prognostic signature universal applicable for gastric cancer-A large sample and multicenter retrospective analysis.

BACKGROUND: Whether pyroptosis, apoptosis, and necroptosis (PAN) molecular subtypes exist in gastric cancer (GC) remains unclear. METHODS: Seven independent cohorts including a total of 1901 GC patients were enrolled in our research. TCGA (n = 371) and GSE84437 (n = 433) were combined into one cohort (n = 804) to screen for prognosis-related PAN genes using a univariate Cox regression analysis. The R package "ConsensusClusterPlus" was applied to conduct a clustering analysis of the combination set based on prognosis-related PAN genes. The R package "limma" was used for the identification of differentially expressed genes (DEGs) between different PAN clusters (FDR <0.05 and |logFC|>1). The combined cohort was randomly divided into a training group (n = 484) and a test group (n = 320) at a ratio of 6:4 to establish and verify the prognostic model. A univariate Cox regression analysis, least absolute shrinkage and selection operator method (LASSO) regression analysis, and multivariate Cox regression analysis were used for the identification of prognostic genes and the construction of risk scores. Another five independent cohorts (GSE62254, n = 300; GSE15459, n = 191; GSE26901, n = 109; GSE26253, n = 432; and GSE13861, n = 65) were used for external validation to verify the accuracy and stability of the prognostic signature. RESULTS: The internal and external validation demonstrated that the 5-gene risk score (LOXL4, SLCO2A1, CST2, PDK4, and MMP11) was an effective instrument for the prognostic risk classification of GC patients. The overall survival (OS) and relapse-free survival (RFS) in the high-risk group were significantly lower than those in the low-risk group and were accompanied by a larger proportion of macrophage and regulatory T cell infiltration. The low-risk group had a good prognosis, with a high tumor mutation burden (TMB), strong cytolytic activity, and a higher proportion of activated CD4 T cell infiltration. In addition, compared with the low-risk group, the cancer-related pathways in the high-risk group were overactivated, and the function of DNA damage repair (DDR) was significantly weakened. Regarding drug sensitivity, the high-risk group was more suitable for targeted drugs, such as axitinib, lapatinib, and nilotinib. The low-risk group was more sensitive to chemotherapy, such as cisplatin, gemcitabine, and vinorelbine. CONCLUSION: A universally applicable prognostic signature of GC is proposed in this research based on pyroptosis, apoptosis, and necroptosis (PAN) molecular subtypes.