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The incidence of laryngeal carcinoma accounts for 1 to 5% of systemic malignancies and ranks second among head and neck malignancies. Screening more effective targets are meaningful for the treatment of laryngeal carcinoma. The purpose was to research the action of miR-21-5p in the occurrence of laryngeal carcinoma. Genecards combined with g:profiler was used for cluster analysis to predict gene-related miRNAs. Q-PCR assay was performed for measuring the level of miR-21-5p and Kruppel-like factor 6 (KLF6). miR-21-5p-mimic, miR-21-5p-inhibitor and sh-KLF6 were transfected using LipofectamineTM 2000. Both CCK-8 and EdU experiments were undertaken to detect cell proliferation ability. Western blot was used to detect apoptosis and epithelial–mesenchymal transition (EMT) related proteins. Wound healing assay and transwell assay were undertaken for migration and invasion, respectively. Three online software (ENCORI, miRWalk, and miRDB) were applied to screen the downstream of miR-21-5p. At the same time, a dual-luciferase reporter experiment was processed to verify the binding. Finally, a rescue experiment was applied to reveal the mediating role of miR-21-5p and KLF6. MiR-21-5p expressed highly in laryngeal carcinoma tissues and cell lines. Knockdown of miR-21-5p reduced the EMT, while enhancing apoptosis of laryngeal carcinoma cell lines. MiR-21-5p targeted KLF6 with negative relationships. The rescue assay results confirmed that sh-KLF6 rescued the action of miR-21-5p knockdown in developing laryngeal carcinoma cells. MiR-21-5p promotes the occurrence and development of laryngeal cancer by targeting KLF6. This finding may provide new insights into miRNA as a biomarker for diagnosing and treating laryngeal carcinoma in the future. [ABSTRACT FROM AUTHOR]

Background: Small-cell lung cancer (SCLC) remains an aggressive cancer with short-term survival due to limited therapeutic options. Apatinib is a small-molecule tyrosine kinase inhibitor that selectively inhibits vascular endothelial growth factor receptor-2. This study aimed to investigate the efficacy and safety of apatinib in patients with extensive-stage (EC) SCLC who had progressed after two or three previous therapies.Methods: Eligible patients were histologically confirmed ES-SCLC after two or three previous treatments, including a platinum-based regimen. Patients received apatinib at an initial dose of 500 mg once daily. The primary endpoint was the objective response rate.Results: Forty patients were enrolled. At the data cut-off time (November 15, 2018), the median follow-up was 7.4 months; no patients remained on treatment, and five were still in follow-up. An objective response was achieved in 7 of 40 patients (17.5%) in the intention-to-treat population, and 7 of 38 patients (18.4%) in the per-protocol population. The median progression-free survival and overall survival were 3.0 months and 5·8 months, respectively. The most commonly observed grade 3 or greater treatment-related adverse events were hypertension, hand-foot syndrome, increased L-gamma-glutamyltransferase.Conclusions: Apatinib exhibited efficacy and an acceptable safety profile in previously heavily-treated ES-SCLC patients. Further exploration of apatinib in phase III trials is warranted.Trial Registration: NCT02945852. [ABSTRACT FROM AUTHOR]

The peak shear strength of discontinuities between two different rock types is essential to evaluate the stability of a rock slope with interlayered rocks. However, current research has paid little attention to shear strength parameters of discontinuities with different joint wall compressive strength (DDJCS). In this paper, a neural network methodology was used to predict the peak shear strength of DDJCS considering the effect of joint wall strength combination, normal stress and joint roughness. The database was developed by laboratory direct shear tests on artificial joint specimens with seven different joint wall strength combinations, four designed joint surface topographies and six types of normal stresses. A part of the experimental data was used to train a back-propagation neural network model with a single-hidden layer. The remaining experimental data was used to validate the trained neural network model. The best geometry of the neural network model was determined by the trial-and-error method. For the same data, multivariate regression analysis was also conducted to predict the peak shear strength of DDJCS. Prediction precision of the neural network model and multivariate regression model was evaluated by comparing the predicted peak shear strength of DDJCS with experimental data. The results showed that the capability of the developed neural network model was strong and better than the multivariate regression model. Finally, the established neural network model was applied in the stability evaluation of a typical rock slope with DDJCS as the critical surface in the Badong formation of China. [ABSTRACT FROM AUTHOR]

Obesity is a progressive, chronic disease, which can be caused by long-term miscommunication between organs. It remains challenging to understand how chronic dysfunction in a particular tissue remotely impairs other organs to eventually imbalance organismal energy homeostasis. Here we introduce RNAi Pulse Induction (RiPI) mediated by short hairpin RNA (shRiPI) or double-stranded RNA (dsRiPI) to generate chronic, organ-specific gene knockdown in the adult Drosophila fat tissue. We show that organ-restricted RiPI targeting Stromal interaction molecule (Stim), an essential factor of store-operated calcium entry (SOCE), results in progressive fat accumulation in fly adipose tissue. Chronic SOCE-dependent adipose tissue dysfunction manifests in considerable changes of the fat cell transcriptome profile, and in resistance to the glucagon-like Adipokinetic hormone (Akh) signaling. Remotely, the adipose tissue dysfunction promotes hyperphagia likely via increased secretion of Akh from the neuroendocrine system. Collectively, our study presents a novel in vivo paradigm in the fly, which is widely applicable to model and functionally analyze inter-organ communication processes in chronic diseases. [ABSTRACT FROM AUTHOR]

Worldwide, Lung cancer is the leading cause of cancer-related death and poses a direct health threat, non-small cell lung cancer (NSCLC) is the most common type. In this study, we demonstrated that centrosomal protein 20 (CEP20) is upregulated in NSCLC tissues and associated with cancer invasion metastasis. Notably, CEP20 depletion inhibited NSCLC cell proliferation, migration, and microtubule polymerization. Mechanistically, we discovered that CEP20 is critical in the development of NSCLC by regulating microtubule dynamics and cell adhesion-related signaling pathways. Furthermore, the knockdown or overexpression of CEP20 affects microtubule polymerization in A549 cell lines. Our research provides a promising therapeutic target for the diagnosis and treatment of lung cancer, as well as a theoretical and experimental basis for clinical application. [ABSTRACT FROM AUTHOR]

Worldwide, Lung cancer is the leading cause of cancer-related death and poses a direct health threat, non-small cell lung cancer (NSCLC) is the most common type. In this study, we demonstrated that centrosomal protein 20 (CEP20) is upregulated in NSCLC tissues and associated with cancer invasion metastasis. Notably, CEP20 depletion inhibited NSCLC cell proliferation, migration, and microtubule polymerization. Mechanistically, we discovered that CEP20 is critical in the development of NSCLC by regulating microtubule dynamics and cell adhesion-related signaling pathways. Furthermore, the knockdown or overexpression of CEP20 affects microtubule polymerization in A549 cell lines. Our research provides a promising therapeutic target for the diagnosis and treatment of lung cancer, as well as a theoretical and experimental basis for clinical application. [ABSTRACT FROM AUTHOR]

EGFR-TKIs and radiation therapy (RT) are the principal treatment for patients with brain metastases (BM) and EGFR mutant NSCLC. However, the optimal use of brain RT for patients with asymptomatic BM remains undefined. A total of 152 patients were identified. 58 patients were excluded. Of the remaining 97 patients, 56 patients received upfront RT followed by icotinib, including WBRT or SRS. 41 patients received icotinib therapy alone. The mOS from diagnosis of BM was 27.0 months for the whole cohort (95% CI, 23.9-30.1 months). There was no difference in OS between the RT followed by icotinib group and the icotinib alone group (31.9 vs. 27.9 months, P = 0.237), and similar results were found in the SRS subgroup (35.5 vs. 27.9 months, P = 0.12). Patients with the EGFR Del19 mutation had a longer OS than patients with the exon 21 L858R mutation (32.7 vs. 27.4, P = 0.037). Intracranial progression-free survival (PFS) was improved in the patients who received RT followed by icotinib compared to those receiving icotinib alone (22.4 vs. 13.9 months, P = 0.043). Patients with EGFR-mutant adenocarcinoma and BM treated with icotinib exhibited prolonged survival. A longer duration of intracranial control was observed with brain RT. [ABSTRACT FROM AUTHOR]

The identification of disease-related metabolites is important for a better understanding of metabolite pathological processes in order to improve human medicine. Metabolites, which are the terminal products of cellular regulatory process, can be affected by multi-omic processes. In this work, we propose a powerful method, MetPriCNet, to predict and prioritize disease candidate metabolites based on integrated multi-omics information. MetPriCNet prioritized candidate metabolites based on their global distance similarity with seed nodes in a composite network, which integrated multi-omics information from the genome, phenome, metabolome and interactome. After performing cross-validation on 87 phenotypes with a total of 602 metabolites, MetPriCNet achieved a high AUC value of up to 0.918. We also assessed the performance of MetPriCNet on 18 disease classes and found that 4 disease classes achieved an AUC value over 0.95. Notably, MetPriCNet can also predict disease metabolites without known disease metabolite knowledge. Some new high-risk metabolites of breast cancer were predicted, although there is a lack of known disease metabolite information. A predicted disease metabolic landscape was constructed and analyzed based on the results of MetPriCNet for 87 phenotypes to help us understand the genetic and metabolic mechanism of disease from a global view. [ABSTRACT FROM AUTHOR]

Immunotherapy has greatly changed the status of cancer treatment, and many patients do not respond or develop acquired resistance. The related research is blocked by lacking of comprehensive resources for researchers to discovery and analysis signatures, then further exploring the mechanisms. Here, we first offered a benchmarking dataset of experimentally supported signatures of cancer immunotherapy by manually curated from published literature works and provided an overview. We then developed CiTSA (http://bio-bigdata.hrbmu.edu.cn/CiTSA/) which stores 878 entries of experimentally supported associations between 412 signatures such as genes, cells, and immunotherapy across 30 cancer types. CiTSA also provides flexible online tools to identify and visualize molecular/cell feature and interaction, to perform function, correlation, and survival analysis, and to execute cell clustering, cluster activity, and cell–cell communication analysis based on single cell and bulk datasets of cancer immunotherapy. In summary, we provided an overview of experimentally supported cancer immunotherapy signatures and developed CiTSA which is a comprehensive and high-quality resource and is helpful for understanding the mechanism of cancer immunity and immunotherapy, developing novel therapeutic targets and promoting precision immunotherapy for cancer. [ABSTRACT FROM AUTHOR]

new method was developed for the determination of fungicides in red wine using ultrasound-assisted ionic liquid dispersive liquid-phase microextraction followed by high-performance liquid chromatography. The ionic liquid, 1-hexyl-3-methylimidazolium hexafluorophosphate (IL) was quickly disrupted by ultrasonication and dispersed in wine as fine droplets. At this stage, the analytes were extracted into the fine droplets of IL. After centrifugation, the concentration of the enriched fungicides in the sedimented phase was determined. Extraction conditions including the type of extraction solvent, the extraction solvent volume, ultrasonication time, centrifugation time and sample pH were optimized. The performance of the method was studied in terms of linearity, precision, and recovery. Quantitative recoveries (>70%) except for pyrimethanil were obtained, and method precision was also satisfactory (RSD < 10%). Enrichment factors range from 100 to 200, and the limits of detection are at the low μg per liter level for most of the target compounds. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Several studies have investigated the associations between diurnal temperature rage (DTR) and mortality, but little evidence has been available regarding the association of DTR with years of life lost (YLL). The aim of this study was to examine the association of DTR with YLL rate, and quantify life loss per death caused by DTR in China. Daily meteorological and death data were collected from 364 locations in China during 2006–2017. First, we calculated daily YLL rate. Then, the distributed lag nonlinear model was applied to estimate the associations of DTR with YLL rate in each location, and multivariable meta-analysis was conducted to pool the location-specific estimates. Finally, we calculated the attributable fractions of DTR on YLL rate and average life loss per death to estimate the mortality burden caused by DTR. Subgroups analyses were conducted by region, age, sex and cause of death. A J-shaped association of DTR with YLL rate was identified in China. The minimum YLL-rate DTR (MYDTR) was 3.7 °C nationwide. The overall AF of DTR in China was 6.40% [95% confidence interval (CI) 3.95–8.86%], and AFs caused by DTR were higher in females, the elderly and south China. An average of 0.96 years (95%CI 0.57–1.35) life loss per death was attributable to DTR nationwide, and life losses per death attributed to DTR were higher in female, young population, and south China. AF and life loss per death caused by DTR were much higher in cold season than that in warm season. Both high DTR and low DTR increased YLL rate in China. Mortality burdens of DTR were much higher in cold season than warm season. The effects of DTR were modified by region, demography and cause of death. Our findings suggest that vulnerable population should be protected when daily temperature change rapidly, especially in cold season. [ABSTRACT FROM AUTHOR]

Objectives: This prospective trial was performed to verify whether microwave ablation (MWA) in combination with chemotherapy could provide superior survival benefit compared with chemotherapy alone.Materials and Methods: From March 1, 2015, to June 20, 2017, treatment-naïve patients with pathologically verified advanced or recurrent non-small cell lung cancer (NSCLC) were randomly assigned to MWA plus chemotherapy group or chemotherapy group. The primary endpoint was progression-free survival (PFS), while the secondary endpoints included overall survival (OS), time to local progression (TTLP), and objective response rate (ORR). The complications and adverse events were also reported.Results: A total of 293 patients were randomly assigned into the two groups. One hundred forty-eight patients with 117 stage IV tumors were included in the MWA plus chemotherapy group. One hundred forty-five patients with 113 stage IV tumors were included in the chemotherapy group. The median follow-up period was 13.1 months and 12.4 months, respectively. Median PFS was 10.3 months (95% CI 8.0-13.0) in the MWA plus chemotherapy group and 4.9 months (95% CI 4.2-5.7) in the chemotherapy group (HR = 0.44, 95% CI 0.28-0.53; p < 0.0001). Median OS was not reached in the MWA plus chemotherapy group and 12.6 months (95% CI 10.6-14.6) in the chemotherapy group (HR = 0.38, 95% CI 0.27-0.53; p < 0.0001) using Kaplan-Meier analyses with log-rank test. The median TTLP was 24.5 months, and the ORR was 32% in both groups. The adverse event rate was not significantly different in the two groups.Conclusions: In patients with advanced NSCLC, longer PFS and OS can be achieved with the treatment of combined MWA and chemotherapy than chemotherapy alone.Key Points: • Patients treated with MWA plus chemotherapy had superior PFS and OS over those treated with chemotherapy alone. • The ORR of patients treated with MWA plus chemotherapy was similar to that of those treated with chemotherapy alone. • Complications associated with MWA were common but tolerable and manageable. [ABSTRACT FROM AUTHOR]

Data from in situ monitoring of displacement is of fundamental importance, not only in hazard assessments, but also for understanding the deformation mechanisms of landslides. However, acquiring reliable and continuous displacement data from complex landslides is often a problem because of the high cost of instruments and maintenance. Among more than 250 dangerous landslides monitored in the Chinese Three Gorges reservoir area, the most systematic and complete monitoring data have been obtained from the Shuping landslide. A ten-year record of GPS displacements measured in eight different locations, plus rainfall and reservoir level data, are utilised to identify the movement characteristics and causal factors of the Shuping landslide. The cumulative displacement curves show a series of abrupt increases that occur every year and are separated by periods of steady, slower deformations. The maximum cumulative displacement that occurred during the ten-year monitoring period was 4.7 m at site SP-2. The maximum displacement rate was 35 mm/day, which was observed on June 13, 2012 at site ZG86. Causal factors of the Shuping landslide are identified through qualitative comparisons of the monitoring data and cross-examined by grey correlation degree analysis. The results show that reservoir water level drawdown is the main factor accelerating the movement of the Shuping landslide, with heavy rainfall playing a subordinate role. The proposed use of field data and analytical methods has the potential for providing procedures and solutions for the interpretation of landslide monitoring data. [ABSTRACT FROM AUTHOR]

Purpose: Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) is the standard therapy for advanced lung adenocarcinomas with common EGFR mutations. However, the efficacy of EGFR-TKIs in patients with uncommon EGFR mutations (other than exon 19 deletions or exon 21 L858R mutation) remains undetermined.Methods: Seven hundred and fifty-five non-small cell lung cancer (NSCLC) patients with EGFR mutation analyses for TKI therapy were identified between October 2010 and December 2015 in East of China. And 66 patients bearing uncommon EGFR mutations were included to collect data from TKI response and prognosis. We categorised EGFR uncommon mutations as: sensitizing rare mutations (group 1: G719X, L861Q, S768I); Ex20 ins (group 2), or complex mutations (G719X + L861Q, G719X + S768I, 19 del + T790M, 19 del + L858R, L858R + S768I, and L858R + T790M; group 3).Results: Of 66 patients given EGFR-TKI treatment, rare sensitive mutations, Ex20 ins, and complex mutations were identified in 37 (56.1%), 9 (13.6%), and 20 (33.3%) cases, respectively. TKI efficacy in patients harboring uncommon EGFR mutations exhibited a tumor response rate of 28.8% and a median progression-free survival (PFS) of 4.8 months. Additionally, patients with complex EGFR mutations had significantly longer PFS when compared with the remaining sensitizing rare mutations or Ex20 ins cases (8.6 vs. 4.1 vs. 3.1 months; p = 0.041). Importantly, complex EGFR mutations were independent predictors of increased overall survival (Hazard Ratios = 0.31; 95% confidence intervals: 0.11-0.90; p = 0.031). Among them, patients harboring Del-19 combined with L858R mutations showed a tendency to have higher response rate (RR) and improved PFS than those with other complex mutation patterns (RR: 66.7 vs. 14.3%, p = 0.021; PFS: 10.1 vs. 8.6 months, p = 0.232).Conclusions: Personalized treatment should be evolving in different types of uncommon EGFR mutations. Clinical benefit from EGFR-TKIs was higher in NSCLC patients with complex EGFR mutations than those with other uncommon EGFR mutation types. [ABSTRACT FROM AUTHOR]

A gas chromatographic-tandem mass spectrometric method ( GC-MS/MS) has been developed for sensitive and reliable detection of 8 organochlorine pesticide residues in wild L. chuanxiong and chestnut. The target compounds were extracted from both samples and simultaneously rudely cleaned up by water-acetone and dichloromethane. Then, the obtained dichloromethane phase was evaporated to dry, treated with HSO, centrifuged, evaporated and redissolved in 0.5 mL of benzene for GC-MS/MS detection. When spiked from 5 to 500 μg/kg, the average recoveries of organochlorine pesticides in two kinds of sample ranged from 74.2 to 110.9% with the intra-day RSD of 0.1 to 10.1% and the inter-day RSD of 0.7 to 10.5%. The limit of detection of eight compounds varied from 0.13 to 1.2 μg/kg in two kinds of samples. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) have been demonstrated to play essential roles in diverse cellular processes and biological functions. Exploring the functions associated with lncRNAs may help provide insight into their underlying biological mechanisms. The current methods primarily focus on investigating the functions of individual lncRNAs; however, essential biological functions may be affected by the combinatorial effects of multiple lncRNAs. Here, we have developed a novel computational method, LncRNAs2Pathways, to identify the functional pathways influenced by the combinatorial effects of a set of lncRNAs of interest based on a global network propagation algorithm. A new Kolmogorov-Smirnov-like statistical measure weighted by the network propagation score, which considers the expression correlation among lncRNAs and coding genes, was used to evaluate the biological pathways influenced by the lncRNAs of interest. We have described the LncRNAs2Pathways methodology and illustrated its effectiveness by analyzing three lncRNA sets associated with glioma, prostate and pancreatic cancers. We further analyzed the reproducibility and robustness and compared our results with those of two other methods. Based on these analyses, we showed that LncRNAs2Pathways can effectively identify the functional pathways associated with lncRNA sets. Finally, we implemented this method as a freely available R-based tool. [ABSTRACT FROM AUTHOR]

The phytohormone abscisic acid (ABA) plays a crucial role in mediating plant growth and development by recruiting genetically redundant ABA receptors. To overcome its oxidation inactivation, we developed a novel ABA analog named 2′,3′-benzo-iso-ABA (iso-PhABA) and studied its function and structural characterization with A. thaliana ABA receptors. The (+)-iso-PhABA form showed much higher ABA-like activities than (+)-ABA including inhibitory effects on the seed germination of lettuce and A. thaliana, wheat embryo germination and rice seedling elongation. The PP2C (protein phosphatases 2C) activity assay showed that (+)-iso-PhABA acted as a potent and selective ABA receptor agonist, which is preferred to PYL10. In some cases, (−)-iso-PhABA showed moderate to high activity for the PYL protein inhibiting PP2C activity, suggesting different mechanisms of action of iso-PhABA and ABA. The complex crystal structure of iso-PhABA with PYL10 was determined and elucidated successfully, revealing that (+)-iso-PhABA was better coordinated in the same binding pocket compared to (+)-ABA. Moreover, the detailed interaction network of iso-PhABA/PYL10 was disclosed and involves hydrogen bonds and multiple hydrophobic interactions that provide a robust framework for the design of novel ABA receptor agonists/antagonists. [ABSTRACT FROM AUTHOR]

Precise cancer classification is a central challenge in clinical cancer research such as diagnosis, prognosis and metastasis prediction. Most existing cancer classification methods based on gene or metabolite biomarkers were limited to single genomics or metabolomics, and lacked integration and utilization of multiple 'omics' data. The accuracy and robustness of these methods when applied to independent cohorts of patients must be improved. In this study, we propose a directed random walk-based method to evaluate the topological importance of each gene in a reconstructed gene-metabolite graph by integrating information from matched gene expression profiles and metabolomic profiles. The joint use of gene and metabolite information contributes to accurate evaluation of the topological importance of genes and reproducible pathway activities. We constructed classifiers using reproducible pathway activities for precise cancer classification and risk metabolic pathway identification. We applied the proposed method to the classification of prostate cancer. Within-dataset experiments and cross-dataset experiments on three independent datasets demonstrated that the proposed method achieved a more accurate and robust overall performance compared to several existing classification methods. The resulting risk pathways and topologically important differential genes and metabolites provide biologically informative models for prostate cancer prognosis and therapeutic strategies development. [ABSTRACT FROM AUTHOR]

Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). [ABSTRACT FROM AUTHOR]