Continual Exposure to Cigarette Smoke Extracts Induces Tumor-Like Transformation of Human Nontumor Bronchial Epithelial Cells in a Microfluidic Chip

IntroductionHeavy cigarette smoking-related chronic obstructive pulmonary disease is an independent risk factor for lung squamous carcinoma. However, the mechanisms underlying the malignant transformation of bronchial epithelial cells are unclear.MethodsIn our study, human tumor-adjacent bronchial epithelial cells were obtained from 10 cases with smoking-related chronic obstructive pulmonary disease and lung squamous carcinoma and cultured in an established microfluidic chip for continual exposure to cigarette smoke extracts (CSE) to investigate the potential tumor-like transformation and mechanisms. The integrated microfluidic chip included upstream concentration gradient generator and downstream cell culture chambers supplied by flowing medium containing different concentrations of CSE.ResultsOur results showed that continual exposure to low doses of CSE promoted cell proliferation whereas to high doses of CSE triggered cell apoptosis. Continual exposure to CSE promoted reactive oxygen species production in human epithelial cells in a dose-dependent manner. More importantly, continual exposure to low dose of CSE promoted the epithelial-to-mesenchymal transition process and anchorage-independent growth, and increased chromosome instability in bronchial epithelial cells, accompanied by activating the GRP78, NF-κB, and PI3K pathways.ConclusionsThe established microfluidic chip is suitable for primary culture of human tumor-adjacent bronchial epithelial cells to investigate the malignant transformation. Continual exposure to low doses of CSE promoted tumor-like transformation of human nontumor bronchial epithelial cells by inducing reactive oxygen species production and activating the relevant signaling

Landscape composition and configuration relatively affect invasive pest and its associator across multiple spatial scales

Landscape structures affect pests, depending on compositional heterogeneity (the number and proportions of different habitats), configurational heterogeneity (spatial arrangement of habitats), and spatial scales. However, there is limited information on the relative effects of compositional and configurational heterogeneity on invasive pests and their associates (species that can benefit from invasive pests), and how they vary across spatial scales. In this study, we assayed the invasive pest Bactrocera dorsalis (Hendel) and its associated fly Drosophila melanogaster in 15 landscapes centered on mango orchards. We calculated landscape composition (forest percentage, mango percentage, and Shannon's diversity) and configuration (edge density) using two methods: spatial distance scales and combined scales. Spatial distance scales included buffer rings with radii of 0.5, 1.0, and 1.5 km, and combined scales referred to cutting or not cutting a smaller ring from larger ones. Our results shown that compositional heterogeneity positively affected B. dorsalis and D. melanogaster due to forest cover percentage, whereas configurational heterogeneity with high edge density negative effect on B. dorsalis. Forest cover had less of an effect on B. dorsalis than configurational heterogeneity, but the opposite effect was observed for D. melanogaster. Importantly, the direction and strength of forest cover and configurational heterogeneity to species did not vary with spatial distance scales or spatial combined scales. Thus, compositional and configurational heterogeneity exhibit differential effects on this invasive pest and its associator, and revealed that the relative effects of landscape structures are consistent across multiple scales. These results provide new insights into landscape effects on interconnected species using a diverse spatial-scale approach

Heredity and cardiometabolic risk: naturally occurring polymorphisms in the human neuropeptide Y2 receptor promoter disrupt multiple transcriptional response motifs

The neuropeptide Y2 G-protein-coupled receptor (NPY2R) relays signals from PYY or neuropeptide Y toward satiety and control of body mass. Targeted ablation of the NPY2R locus in mice yields obesity, and studies of NPY2R promoter genetic variation in more than 10 000 human participants indicate its involvement in control of obesity and BMI. Here we searched for genetic variation across the human NPY2R locus and probed its functional effects, especially in the proximal promoter

Transient Receptor Potential V Channels Are Essential for Glucose Sensing by Aldolase and AMPK

Fructose-1,6-bisphosphate (FBP) aldolase links sensing of declining glucose availability to AMPK activation via the lysosomal pathway. However, how aldolase transmits lack of occupancy by FBP to AMPK activation remains unclear. Here, we show that FBP-unoccupied aldolase interacts with and inhibits endoplasmic reticulum (ER)-localized transient receptor potential channel subfamily V, inhibiting calcium release in low glucose. The decrease of calcium at contact sites between ER and lysosome renders the inhibited TRPV accessible to bind the lysosomal v-ATPase that then recruits AXIN:LKB1 to activate AMPK independently of AMP. Genetic depletion of TRPVs blocks glucose starvation-induced AMPK activation in cells and liver of mice, and in nematodes, indicative of physical requirement of TRPVs. Pharmacological inhibition of TRPVs activates AMPK and elevates NAD(+) levels in aged muscles, rejuvenating the animals' running capacity. Our study elucidates that TRPVs relay the FBP-free status of aldolase to the reconfiguration of v-ATPase, leading to AMPK activation in low glucose

Research on Sentiment Classification of Online Travel Review Text

In recent years, the number of review texts on online travel review sites has increased dramatically, which has provided a novel source of data for travel research. Sentiment analysis is a process that can extract tourists’ sentiments regarding travel destinations from online travel review texts. The results of sentiment analysis form an important basis for tourism decision making. Thus far, there has been minimal concern as to how sentiment analysis methods can be effectively applied to improve the effect of sentiment analysis. However, online travel review texts are largely short texts characterized by uneven sentiment distribution, which makes it difficult to obtain accurate sentiment analysis results. Accordingly, in order to improve the sentiment classification accuracy of online travel review texts, this study transformed sentiment analysis into a multi-classification problem based on machine learning methods, and further designed a keyword semantic expansion method based on a knowledge graph. Our proposed method extracts keywords from online travel review texts and obtains the concept list of keywords through Microsoft Knowledge Graph. This list is then added to the review text to facilitate the construction of semantically expanded classification data. Our proposed method increases the number of classification features used for short text by employing the huge corpus of information associated with the knowledge graph. In addition, this article introduces online travel review text preprocessing, keyword extraction, text representation, sampling, establishment classification labeling, and the selection and application of machine learning-based sentiment classification methods in order to build an effective sentiment classification model for online travel review text. Experiments were implemented and evaluated based on the English review texts of four famous attractions in four countries on the TripAdvisor website. Our experimental results demonstrate that the method proposed in this paper can be used to effectively improve the accuracy of the sentiment classification of online travel review texts. Our research attempts to emphasize and improve the methodological relevance and applicability of sentiment analysis for future travel research

Species–size networks elucidate the effects of biodiversity on aboveground biomass in tropical forests

Although biodiversity has been shown to profoundly affect ecosystem function in forests, the processes which it impacts are limited understood. Various plant species with diverse sizes interact to form complex networks to complete resource use processes, but little is known about the role of species-size networks in influencing ecosystem function and biodiversity-ecosystem function relationships. Using a dataset encompassing 423 species and 32,067 individuals, we constructed species–tree diameter and species–tree height networks for two sampling areas (0.04 and 0.09 ha), and then calculated the network modularity for species and size interlinked specialization and nestedness, species or sizes with relatively few links are a subset of those with more network links. We analyzed the relationships between modularity, nestedness, and the aboveground biomass. The direct and indirect effects of species abundance and richness on the aboveground biomass through network structures were explored using structural equation modelling. Regardless of the species–tree diameter or height network, modularity was positively associated with the aboveground biomass, independent of the sampling area, while nestedness was negatively associated. Species abundance negatively affected the modularity, but positively affected nestedness, whereas species richness had the opposite effect. Species abundance and richness affected the aboveground biomass indirectly through modularity and nestedness, but the effect of modularity was greater than that of nestedness. Our study confirms that the importance of species–size networks in the context of the aboveground biomass has similar effects on species–diameter and height networks across sampling areas. It clarifies that modularity from interactions between species and individuals is a useful indicator to reveal the mechanism by which plant diversity acquires resources for biomass production. These results provide new insights into biodiversity–ecosystem function relationships from a network perspective

Simultaneous Qualitation and Quantitation of Chlorogenic Acids in Kuding Tea Using Ultra-High-Performance Liquid Chromatography–Diode Array Detection Coupled with Linear Ion Trap–Orbitrap Mass Spectrometer

Kuding tea, the leaves of Ilex Kudingcha C.J. Tseng, has been applied for treating obesity, hypertension, cardiovascular disease, hyperlipidemia, and so on. The chlorogenic acids (CGAs) in Kuding tea have shown excellent antioxidative, antiobesity, anti-atherosclerotic and anticancer activities. Nevertheless, the chemical profiles of CGAs in Kuding tea have not been comprehensively studied yet, which hinders further quality control. In the present study, a sensitive ultra-high-performance liquid chromatography-diode array detection coupled with a linear ion trap-Orbitrap (UHPLC-DAD-LTQ-Orbitrap) method was established to screen and identify CGAs in Kuding tea. Six CGA standards were first analyzed in negative ion mode with a CID-MS/MS experiment and then the diagnostic product ions (DPIs) were summarized. According to the retention behavior in the RP-ODS column, accurate mass measurement, DPIs and relevant bibliography data, a total of 68 CGA candidates attributed to 12 categories were unambiguously or preliminarily screened and characterized within 18 min of chromatographic time. This was the first systematic report on the distribution of CGAs in Kuding tea. Meanwhile, the contents of 6 major CGAs in Kuding tea were also determined by the UHPLC-DAD method. All the results indicated that the established analytical method could be employed as an effective technique for the comprehensive and systematic characterization of CGAs and quality control of the botanic extracts or Chinese medicinal formulas that contain various CGAs

P‑Arylation of Dialkyl Phosphites and Secondary Phosphine Oxides with Arynes

The novel P-arylation of dialkyl phosphites and secondary phosphine oxides with arynes has been achieved. The reactions produce dialkyl arylphosphonates in 71–99% yield and tertiary phosphine oxides in 68–92% yield under mild conditions