High expression of VTA1 is an adverse prognostic factor in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a common pathological type of non-small cell lung cancer; identifying preferable biomarkers has become one of the current challenges. Given that VTA1 has been reported associated with tumor progression in various human solid cancers but rarely reported in LUAD, herein, RNA sequencing data from TCGA and GTEx were obtained for analysis of VTA1 expression and differentially expressed gene (DEG). Furthermore, functional enrichment analysis of VTA1-related DEGs was performed by GO/KEGG, GSEA, immune cell infiltration analysis, and protein-protein interaction (PPI) network. In addition, the clinical significance of VTA1 in LUAD was figured out by Kaplan-Meier Cox regression and prognostic nomogram model. R package was used to analyze incorporated studies. As a result, VTA1 was highly expressed in various malignancies, including LUAD, compared with normal samples. Moreover, high expression of VTA1 was associated with poor prognosis in 533 LUAD samples, as well as T stage T2&T3&T4, N stage N1&N2&N3, M stage M1, pathologic stage II&III&IV, and residual tumor R1&R2, et al. (P < 0.05). High VTA1 was an independent prognostic factor in Cox regression analysis; Age and cytogenetics risk were included in the nomogram prognostic model. Furthermore, a total of 4232 DEGs were identified between the high- and the low-expression group, of which 736 genes were up-regulated and 3496 genes were down-regulated. Collectively, high expression of VTA1 is a potential biomarker for adverse outcomes in LUAD. The DEGs and pathways recognized in the study provide a preliminary grasp of the underlying molecular mechanisms of LUAD carcinogenesis and progression.

Gastrodia elata Blume: A review of its mechanisms and functions on cardiovascular systems.

Gastrodia elata Blume (GEB), commonly called Tianma in Chinese, is a valuable and extensively used herbal Traditional Chinese Medicine with a wide range of clinical applications. It has been used to treat headaches, dizziness, stroke, epilepsy, amnesia, spasm, and other disorders since ancient times. Hundreds of compounds, including phenols, glycosides, polysaccharides, steroids, organic acids, and others, have been isolated and identified from this plant. Modern pharmacological studies have shown that its active ingredients possess many pharmacological effects, such as neuroprotective, analgesic, sedation and hypnosis, anti-anxiety, anti-depressant, anti-convulsant, anti-dizziness, blood pressure lowering, blood lipids lowering, liver protection, anti-tumor, and immunity enhancement effects. The present review discusses the pharmacological actions and mechanisms of various components of GEB in cardiovascular diseases to provide a reference for further study of GEB.

Germacrane Sesquiterpene Dilactones from Mikania micrantha and Their Antibacterial and Cytotoxic Activity.

Four new germacrane sesquiterpene dilactones, 2ß-hydroxyl-11ß,13-dihydrodeoxymikanolide (1), 3ß-hydroxyl-11ß,13-dihydrodeoxymikanolide (2), 1α,3ß-dihydroxy-4,9-germacradiene-12,8:15,6-diolide (3), and (11ß,13-dihydrodeoxymikanolide-13-yl)-adenine (4), together with five known ones (5-9) were isolated from the aerial parts of Mikania micrantha. Their structures were elucidated on the basis of extensive spectroscopic analysis. Compound 4 is featured with an adenine moiety in the molecule, which is the first nitrogen-containing sesquiterpenoid so far isolated from this plant species. These compounds were evaluated for their in vitro antibacterial activity against four Gram-(+) bacteria of Staphyloccocus aureus (SA), methicillin-resistant Staphylococcus aureus (MRSA), Bacillus cereus (BC) and Curtobacterium. flaccumfaciens (CF), and three Gram-(-) bacteria of Escherichia coli (EC), Salmonella. typhimurium (SA), and Pseudomonas Solanacearum (PS). Compounds 4 and 7-9 were found to show strong in vitro antibacterial activity toward all the tested bacteria with the MIC values ranging from 1.56 to 12.5 µg/mL. Notably, compounds 4 and 9 showed significant antibacterial activity against the drug-resistant bacterium of MRSA with MIC value 6.25 µg/mL, which was close to reference compound vancomycin (MIC 3.125 µg/mL). Compounds 4 and 7-9 were further revealed to show in vitro cytotoxic activity toward human tumor A549, HepG2, MCF-7, and HeLa cell lines, with IC50 values ranging from 8.97 to 27.39 µM. No antibacterial and cytotoxic activity were displayed for the other compounds. The present research provided new data to support that M. micrantha is rich in structurally diverse bioactive compounds worthy of further development for pharmaceutical applications and for crop protection in agricultural fields.

Multiple attention-based encoder-decoder networks for gas meter character recognition.

Factories swiftly and precisely grasp the real-time data of the production instrumentation, which is the foundation for the development and progress of industrial intelligence in industrial production. Weather, light, angle, and other unknown circumstances, on the other hand, impair the image quality of meter dials in natural environments, resulting in poor dial image quality. The remote meter reading system has trouble recognizing dial pictures in extreme settings, challenging it to meet industrial production demands. This paper provides multiple attention and encoder-decoder-based gas meter recognition networks (MAEDR) for this problem. First, from the acquired dial photos, the dial images with extreme conditions such as overexposure, artifacts, blurring, incomplete display of characters, and occlusion are chosen to generate the gas meter dataset. Then, a new character recognition network is proposed utilizing multiple attention and an encoder-decoder structure. Convolutional neural networks (CNN) extract visual features from dial images, encode visual features employing multi-head self-attention and position information, and facilitate feature alignment using the connectionist temporal classification (CTC) method. A novel two-step attention decoder is presented to improve the accuracy of recognition results. convolutional block attention module (CBAM) reweights the visual features from the CNN and the semantic features computed by the encoder to improve model performance; long short-term memory attention (LSTM attention) focuses on the relationship between feature sequences. According to experimental data, our system can effectively and efficiently identify industrial gas meter picture digits with 91.1% identification accuracy, faster inference speed, and higher accuracy than standard algorithms. The accuracy and practicality of the recognition can fulfill the needs of instrument data detection and recognition in industrial production, and it has a wide range of applications.

Integrated Gut-Heart Axis and Network Pharmacology to Reveal the Mechanisms of the Huoxue Wentong Formula Against Myocardial Ischemia.

Background: Myocardial ischemia (MI) is a major public health problem with high mortality and morbidity worldwide. Huoxue Wentong formula (HX), a traditional Chinese medicine (TCM) formula, exhibits unambiguous effects on treating MI and preventing cardiovascular diseases. However, the molecular mechanism of the therapeutic effects of HX on MI remains largely unknown. Objective: This study combined microbiology, metabolomics, and network pharmacology to explore the relationship between the gut microbiota and its metabolites in MI rats and the efficacy of HX. Methods: First, the MI rat model was established by ligation of left anterior descending. Echocardiography, Masson's staining, and hematoxylin and eosin staining were used to evaluate the effect of HX on MI. Then, fecal metabolomics and 16S rRNA sequencing were used to obtain the microbial and metabolic characteristics of HX on MI. After that, network pharmacology was used to predict the target and action pathway of HX in treating MI. Finally, the relationship between fecal metabolites and target was explored through bioinformatics. Results: HX can improve the cardiac function and ameliorated myocardial fibrosis in MI rats. Moreover, HX can affect the gut microbiota community and metabolites of MI rats, especially Bacteroides, Deferribacteres, Ruminococcus_sp._zagget7, Acidobacteria, daidzein, L-lactic acid, and malate. Network pharmacology found that HX can function through tumor necrosis factor (TNF), tumor protein p53 (TP53), interleukin 6 (IL6), vascular endothelial growth factor A (VEGFA), fos proto-oncogene (FOS), bcl2-associated X (BAX), myeloperoxidase (MPO), PI3K-Akt signaling pathways, and HIF-1 signaling pathway. The mechanism study showed that the anti-MI effect of HX was related to valine, leucine, and isoleucine biosynthesis, fatty acid biosynthesis, and arachidonic acid metabolism. Conclusion: This study demonstrates that HX treated MI rats in a multitarget and multipathway manner. Its mechanism is related to the change of gut microbiota and the regulation of valine, leucine and isoleucine biosynthesis, fatty acid biosynthesis, and arachidonic acid metabolism.

Screening of T Cell-Related Long Noncoding RNA-MicroRNA-mRNA Regulatory Networks in Non-Small-Cell Lung Cancer.

BACKGROUND: Lung cancer (LC) has the highest mortality rate among all the other types of cancer in the world. T cells are known to be the key factor in inducing the immune response during LC. OBJECTIVE: In this study, we aimed to screen and analyze RNAs associated with CD8(+) T cells and activated memory CD4(+) T cells in lung adenocarcinomas, a subtype of non-small-cell lung cancer (NSCLC-LUAD). METHODS: Gene expression RNA-seq data and clinical data of NSCLC-LUAD were downloaded from the XENA database. The data were divided into low scores and high scores based on the Stromal and Immune scores. Then, all the genes were screened for identifying those specifically associated with CD8(+) T cells and activated memory CD4(+) T cells. The screened genes were used for the construction of the protein-protein interaction (PPI) network and for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis along with prognosis analysis. Based on the results of the prognostic analysis, the prognostic-related genes were used to analyze long noncoding (lnc)RNA-micro(mi)RNA-mRNA networks and to predict small chemical molecules. RESULTS: According to the Immune and Stromal scores, a total of 885 upregulated and 29 downregulated RNAs were identified. A total of 90 differentially expressed genes (DEGs) were found to be related to CD8(+) T immune cells, and 48 DEGs were related to activated memory CD4(+) T cells. GPR174 and CD226 suggested a favorable prognosis. For CD8(+) and activated memory CD4(+) T cells, 112 and 113 PPI edges were obtained, respectively. GPR174 was found to be regulated by hsa-miR-19b-5p and hsa-miR-19b-2-5p, and both of these two miRNAs were regulated by lncRNA PCED1B-AS1. CD226 was regulated by hsa-miR-379-5p, which was in turn regulated by lncRNA RP11-81H14.2. CONCLUSION: Our findings provide a deeper understanding of the T cell-related ceRNA regulatory mechanism in NSCLC-LUAD pathogenesis.

Application of Computer-Aided Tongue Inspection for Preliminary Screening of Esophageal Cancer.

OBJECTIVE: To differentiate patients with esophageal cancer or premalignant lesions from the high-risk population for preliminary screening of esophageal cancer using a feature index determined by a computer-aided tongue information acquisition and processing system (DS01-B). METHODS: Totally, 213 patients diagnosed with esophageal cancer or premalignant lesions and 2,840 normal subjects were collected including primarily screened and reexamined, all of them were confirmed with histological examinations. Their tongue color space values and manifestation features were extracted by DS01-B and analyzed. Firstly, the analysis of variance was performed to differentiate normal subjects from patients with esophageal cancer and premalignant lesions. Secondly, the logistic regression was conducted using 10 features and gender, age to get a predictive equation of the possibility of esophageal cancer or premalignant lesions. Lastly, the equation was tested by subjects undergoing primary screening. RESULTS: Saturation (S) values in the HSV color space showed significant differences between patients with esophageal cancer and normal subjects or those with mild atypical hyperplasia (P<0.05); blue-to-yellow (b) values in the Lab color space showed significant differences between patients with esophageal cancer or premalignant lesions and normal subjects (P<0.05). Logistic regression analysis showed that the computer-aided tongue inspection approach had an accuracy of 72.3% (2008/2776) in identifying patients with esophageal cancer or premalignant lesions for preliminary screening in high-risk population. CONCLUSION: Computer-aided tongue inspection, with descriptive and quantitative profile as described in this study, could be applied as a cost- and timeefficient, non-invasive approach for preliminary screening of esophageal cancer in high-risk population.