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Dietary cholesterol has been implicated to promote lung cancer. Lung adenocarcinoma (LAC) is a main type of lung cancer, whereas the functional mechanism of cholesterol in LAC remained largely unknown. In the present study, we evidenced that cholesterol promoted cell proliferation and invasion of LAC in vitro as well as LAC metastasis in vivo. Cyp27A1 knockdown reduced the cholesterol-induced LAC cells proliferation and invasion. In contrast, Cyp7B1 knockdown enhanced the effect of cholesterol on LAC cells proliferation and invasion. Furthermore, Cyp27A1 deficiency remarkably reduced high cholesterol-induced LAC metastasis in vivo. Mechanism investigation demonstrated that exposure of LAC cells to 27-hydroxycholesterol induced the phosphorylation of AKT and NFκB p65, and promoted the expression of peptidylprolyl isomerase B (PPIB), especially in the coculture with THP1-derived macrophage. Meanwhile, 27-hydroxycholesterol induced the secretion of FGF2 and IL-6, which contributed to the expression of snail and vimentin. Luciferase report assay and ChIP assay confirmed that NFκB p65 controlled the transcription of PPIB. Inhibiting NFκB p65 activation reduced PPIB expression. PPIB inhibition reduced 27-hydroxycholesterol-induced expression of snail and vimentin. These results indicated that 27-hydroxycholesterol linked high cholesterol and LAC metastasis by regulating NFκB/PPIB axis and the secretion of FGF2 and IL-6.

Lung adenocarcinoma is the main type of lung cancer in women. Our previous findings have evidenced that 25-hydroxycholesterol (25-HC) promotes migration and invasion of lung adenocarcinoma cells (LAC), during which LXR as a 25-HC receptor plays an important role. Estrogen receptor beta (ERβ) is a receptor of 27-hydroxycholesterol that is structurally analogous to 25-HC, but its role in the functional actions of 25-HC remained largely unknown. In this study, we demonstrated that 25-HC treatment triggered ERβ expression in LAC. Knockdown of ERβ inhibited 25-HC-mediated proliferation, migration and invasion, and reduced 25-HC-induced LAC metastasis in vivo. Further investigation revealed that ERβ knockdown restrained the expression of TNFRSF17 (BCMA). In vivo experiments also confirmed that ERβ knockdown blocked 25-HC-induced TNFRSF17 expression. TNFRSF17 knockdown also restrained 25-HC-induced proliferation, migration and invasion. Bioinformatic analysis showed that the levels of ERβ and TNFRSF17 were elevated in lung adenocarcinoma, and were closely related to tumor stages and nodal metastasis status. These results suggested that 25-HC promoted the proliferation and metastasis of LAC by regulating ERβ/TNFRSF17 axis.

Cholesterol disorder has been implicated in the progression of lung cancer, the mechanism of which remains largely unknown. In this study, we evidenced that cholesterol promoted the proliferation, migration and invasion of lung adenocarcinoma cells (LAC) in vitro, and enhanced LAC metastasis in vivo. Further investigation demonstrated that cholesterol treatment induced the expression of MYADM. Cholesterol-induced interaction between MYADM and Rac1 triggered AKT phosphorylation and c-Myc expression. c-Myc positively regulated the transcriptions of MCT1 and MYADM. MYADM knockdown notably inhibited the expression of Rac1, phosphorylated AKT, c-Myc and MCT1 despite in the presence of cholesterol. Blocking AKT phosphorylation restrained cholesterol-induced the expression of MYADM, Rac1 and c-Myc while AKT activation elevated the levels of MYADM, Rac1 and c-Myc. In addition, MYADM knockdown promoted E-Cadherin expression, and inhibited the expression of β-Catenin, MMP2, MMP9 and vimentin. As expected, inhibiting MYADM significantly attenuated cholesterol-induced proliferation, migration and invasion of LAC in vitro, and reduced high cholesterol diet-induced LAC metastasis in vivo. Intriguingly, MYADM knockdown remarkably decreased the levels of lactate in serum and tumors, confirming the positive regulator of MYADM in MCT1 expression. These results suggested that cholesterol should induce the proliferation and metastasis of LAC by regulating MYADM/Rac1/AKT/c-Myc/MCT1 axis.

The positive predictive effect of children's problem behaviors on parenting stress has been verified to some extent, but research on parents of children with special needs remains insufficient. Moreover, the role of parental personality traits in the relationship between children's problem behaviors and parenting stress, and whether it differs from before the COVID-19 pandemic, remains unclear. Accordingly, in this study, online questionnaires were used to survey parents of children with autism and intellectual disabilities in China - 337 parents before and 604 during the COVID-19 pandemic - to explore the relationship between problem behaviors in the children and parenting stress as well as the moderating effect of parents' personality. The results showed that problem behaviors of children with autism and intellectual disabilities had a positive predictive effect on parenting stress. However, there was no significant difference in this effect before and during the pandemic. In addition, the relationship between children's problem behaviors and parenting stress was moderated by the Agreeableness and Neuroticism of the parents, but only during COVID-19 pandemic. The research results suggest that, during the pandemic when facing problem behaviors of children with autism or intellectual disabilities, positive personality characteristics such as Agreeableness have a protective effect on parenting stress. By contrast, negative personality characteristics such as Neuroticism are risk factors. The study results provide evidence from special groups regarding the role of parents' personalities in the parent - child interaction and the parenting stress models.

Despite the previous evidence showing that SHC adaptor protein 1 (SHC1) could encode three distinct isoforms (p46SHC, p52SHC and p66SHC) that function in different activities such as regulating life span and Ras activation, the precise underlying role of SHC1 in lung cancer also remains obscure. In this study, we firstly found that SHC1 expression was up‐regulated both in lung adenocarcinoma (LUAD) and in lung squamous cell carcinoma (LUSC) tissues. Furthermore, compared to patients with lower SHC1 expression, LUAD patients with higher expression of SHC1 had poorer overall survival (OS). Moreover, higher expression of SHC1 was also associated with worse OS in patients with stages 1 and 2 but not stage 3 lung cancer. Significantly, the analysis showed that SHC1 methylation level was associated with OS in lung cancer patients. It seemed that the methylation level at specific probes within SHC1 showed negative correlations with SHC1 expression both in LUAD and in LUSC tissues. The LUAD and LUSC patients with hypermethylated SHC1 at cg12473916 and cg19356022 probes had a longer OS. Therefore, it is reasonable to conclude that SHC1 has a potential clinical significance in LUAD and LUSC patients.

Purpose Long noncoding RNAs (lncRNAs) are emerging as gene regulators to drive many important cancer phenotypes through interaction with microRNAs. There have been numerous data about upregulation of H19 and its strong oncogenic function in progression of cancers. However, the function and detailed mechanisms of H19 on small cell lung cancer (SCLC) are still unclear. Methods In this study, we investigated H19 expression in SCLC and para-carcinoma tissues. We also explored the function and detailed mechanisms of H19 on SCLC cells via RT-PCR, transwell assay, Western blot, dual-luciferase report assay and RNA pull-down experiments. Results In this study, we observed that H19 was upregulated in SCLC compared with para-carcinoma tissues or NSCLC tissues. We also uncovered that H19 could promote proliferation and migration of SCLC cells. Functional investigation illustrated that H19 acted as a sponge for miR-140-5p to regulate its expression in SCLC. Interestingly, we further found that H19 upregulated FGF9 expression to promote SCLC progression via sponging miR-140-5p. H19 and FGF9 were also revealed to have similar expression patterns in clinical SCLC samples. Conclusion These data demonstrated that H19 might be a promising prognostic and therapeutic target for SCLC.

The soy beverage is a healthy product rich in plant protein; however, its unpleasant flavor affects consumer acceptance. The aim of this study was to determine the feasibility of using

Glycogen branching enzyme (GBE1) is a critical gene that participates in regulating glycogen metabolism. However, the correlations between GBE1 expression and the prognosis and tumor-associated macrophages in lung adenocarcinoma (LUAD) also remain unclear. Herein, we firstly analyzed the expression level of GBE1 in LUAD tissues and adjacent lung tissues

BackgroundCD8+ T cells are one of the central effector cells in the immune microenvironment. CD8+ T cells play a vital role in the development and progression of lung adenocarcinoma (LUAD). This study aimed to explore the key genes related to CD8+ T-cell infiltration in LUAD and to develop a novel prognosis model based on these genes.MethodsWith the use of the LUAD dataset from The Cancer Genome Atlas (TCGA), the differentially expressed genes (DEGs) were analyzed, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Combined with the CIBERSORT algorithm, the gene module in WGCNA, which was the most significantly correlated with CD8+ T cells, was selected for the subsequent analyses. Key genes were then identified by co-expression network analysis, protein–protein interactions network analysis, and least absolute shrinkage and selection operator (Lasso)-penalized Cox regression analysis. A risk assessment model was built based on these key genes and then validated by the dataset from the Gene Expression Omnibus (GEO) database and multiple fluorescence in situ hybridization experiments of a tissue microarray.ResultsFive key genes (MZT2A, ALG3, ATIC, GPI, and GAPDH) related to prognosis and CD8+ T-cell infiltration were identified, and a risk assessment model was established based on them. We found that the risk score could well predict the prognosis of LUAD, and the risk score was negatively related to CD8+ T-cell infiltration and correlated with the advanced tumor stage. The results of the GEO database and tissue microarray were consistent with those of TCGA. Furthermore, the risk score was higher significantly in tumor tissues than in adjacent lung tissues and was correlated with the advanced tumor stage.ConclusionsThis study may provide a novel risk assessment model for prognosis prediction and a new perspective to explore the mechanism of tumor immune microenvironment related to CD8+ T-cell infiltration in LUAD.

Long noncoding RNAs (lncRNAs) have emerged as regulators of gene expression and play critical regulatory roles in diverse biological functions and diseases, including cancer. In this study, we report the downregulation of LINC01089 in non-small cell lung cancer (NSCLC) samples, relative to adjacent non-tumor tissues, and demonstrate its role in the inhibition of proliferation, migration, and epithelial–mesenchymal transition (EMT) of NSCLC cells. Mechanistic analysis indicates that LINC01089 acts as a sponge for miR-27a, regulating its expression in NSCLC. Interestingly, LINC01089 mediated the upregulation of SFRP1 expression by inhibiting the Wnt/β-catenin–EMT pathway and inhibiting the epithelial–mesenchymal transition of NSCLC via sponging miR-27a. Overall, our findings highlight LINC01089’s tumorigenic role and regulatory mechanism in NSCLC, thereby suggesting its potential as a therapeutic target for managing NSCLC.

27-Hydroxycholesterol (27-HC) has been implicated in the pathological process of estrogen receptor positive breast cancer. However, the role of 27-HC in lung adenocarcinoma is still unclear. Because bone metastasis is a main reason for the high mortality of lung adenocarcinoma, this study aimed to investigate the effect of 27-HC on osteoclastogenesis in lung adenocarcinoma microenvironment. The results showed that the conditioned media (CM) from lung adenocarcinoma cells cocultured with macrophages promoted osteoclast differentiation, which was enhanced by 27-HC. Further investigation showed that CM inhibited miR-139 expression and promoted c-Fos expression. Luciferase reporter assay identified c-Fos as a direct target of miR-139. CM also induced the expression and nuclear translocation of NFATc1 and STAT3 phosphorylation, which was enlarged by 27-HC but was attenuated by miR-139. Coimmunoprecipitation assay demonstrated that 27-HC increased the interaction between NFATc1 and phosphorylated STAT3, which was restricted by miR-139. Chromatin immunoprecipitation assay showed that pSTAT3 could bind to the promoter of c-Fos, c-Fos could bind to the promoter of NFATc1, and both pSTAT3 and NFATc1 could bind to the promoter of Oscar, which were enlarged by 27-HC but were blocked by miR-139. Knockdown of c-Fos mimicked the effect of miR-139. These results suggested that CM, especially containing 27-HC, promoted osteoclastogenesis by inhibiting miR-139 expression and activating the STAT3/c-Fos/NFATc1 pathway.

Objective Through the summary and analysis of large samples, the characteristic imaging manifestations of intrapulmonary lymph nodes (IPLNs) were quantified, and two corresponding rating tables were developed. These rating tables could be used to distinguish the IPLNs from primary lung cancer, so as to improve the diagnostic accuracy and help clinicians make correct judgments and decisions. Methods A total of 82 patients with 110 IPLNs and 35 patients with primary lung cancer lesions were collected from June 2017 to December 2018. All lesions were solid nodules of less than 12 mm in diameter, which were confirmed by pathology. Observation indicators included location, size, shape, density, border and internal vacuoles of nodules, linear high-density shadow around the nodules, distance from the pleura, pleural indentation, and so on. Results There were statistically significant differences in the location, size, shape, internal vacuole of the nodules, and distance from the pleura (p Conclusion For the pulmonary solid nodules of less than 12 mm in diameter and unknown nature, the evaluation in accordance with the Score Table and the Risk Level Table of this study can be more accurate and faster than the original judgment, which will help clinicians in diagnosis and treatment decisions.

Chylothorax is a rare and challenging complication of thoracic surgery. Whereas most current studies focus on postoperative treatment and preventative measures for esophageal cancer surgery, the current study investigates the impact of prophylactic ligation of the thoracic duct branch on postoperative chylothorax after pulmonary resection for right lung cancer. The subjects of this retrospective study were 1165 patients who underwent right pulmonary resection and mediastinal lymph-node dissection in our department between January 2015 and August 2019. Those who underwent prophylactic ligation of the thoracic duct branch after 4R lymph-node dissection were assigned to group A (n = 475), and those who did not were assigned to group B (n = 690). The incidence of postoperative chylothorax, the success rate of conservative treatment, the postoperative hospital stay, and the chest drainage volume were recorded and compared statistically between the two groups. The incidence of postoperative chylothorax was significantly lower in group A than in group B (0.84% vs. 2.90%, p = 0.015). Patients who had a chylothorax in group A had a significantly shorter postoperative hospital stay, less mean drainage volume per day, and less total drainage than those in group B (7.25 ± 0.50 days vs. 11.00 ± 2.81 days, p = 0.003; 0.64 ± 0.04 L vs. 0.80 ± 0.09 L, p = 0.003; 4.64 ± 0.40 L vs. 8.82 ± 2.84 L; p = 0.002). The success rate of conservative treatment was higher in group A than in group B, but the difference was not significant (100% vs. 75.0%, p = 0.544). Performing prophylactic ligation of the thoracic duct branch during right pulmonary resection and mediastinal lymph-node dissection is an effective and safe method of preventing postoperative chylothorax.

Modern geo-position system (GPS) enabled smart phones are generating an increasing volume of information about their users, including geo-located search, movement, and transaction data. While this kind of data is increasingly rich and offers many grand opportunities to identify patterns and predict behaviour of groups and individuals, it is not immediately obvious how to develop a framework for extracting plausible inferences from these data. In our case, we have access to a large volume (more than half a billion individual records) of real user data from the Point smart phone application, and we have developed a generic and layered system architecture to incrementally find aggregate items of interest within that data. "Interest" is based on the semantics of the data, so include time and space correlations, e.g., Are people searching for dinner and a movie, distributions of usage patterns and platforms, e.g., Geographic distribution of Android, Apple, and Black-Berry users, and clustering to identify interesting and relatively complex search and movement patterns, e.g., Consumer trajectories from key word searches. Our integration of visualization tools is thus guided top-down, by semantic concepts in the application domain, rather than by bottom-up tool development. Our presentation here is preliminary in that we provide sketches of case-studies that demonstrate an application specific integration of the three major components of modern visual analytics: visualization, analytics, and interaction (VAI). Our case-study sketches show how an interactive system for visual data exploration can be used to alternate between exploratory search -- looking for ideas and new hypothesis in data -- and explanatory search -- looking for evidence to support a hypothesis. While we have not yet formulated experiments to directly measure the cognitive efficacy of our experimental system, we believe that our semantically-driven VAI workflows and the integration of visual methods and interaction provides some useful ideas about how to extend current frameworks for visual analytics systems.

Modern geo-positioning system (GPS) enabled smart phones are generating an increasing volume of information about their users, including geo-located search, movement, and transaction data. While this kind of data is increasingly rich and offers many grand opportunities to identify patterns and predict behaviour of groups and individuals, it is not immediately obvious how to develop a framework for extracting plausible inferences from these data. In our case, we have access to a large volume of real user data from the Point smart phone application, and we have developed a generic and layered system architecture to incrementally find aggregate items of interest within that data. This includes time and space correlations, e.g., are people searching for dinner and a movie, distributions of usage patterns and platforms, e.g., geographic distribution of Android, Apple, and BlackBerry users, and clustering to identify relatively complex search and movement patterns we call "consumer trajectories." Our pursuit of these kinds of patterns has helped guide our development of information extraction, machine learning, and visualization methods that provide systematic tools for investigating the geo-located data, and for the development of both conceptual tools and visualization tools in aid of finding both interesting and useful patterns in that data. Included in our system architecture is the ability to consider the difference between exploratory and explanatory hypotheses on data patterns, as well as the deployment of multiple visualization methods that can provide alternatives to help expose interesting patterns. In our introduction to our framework here, we provide examples of formulating hypotheses on geo-located behaviour, and how a variety of methods including those from machine learning and visualization, can help confirm or deny the value of such hypotheses as they emerge. In this particular case, we provide an initial basis for identifying semantically motivated data artifacts we call geo-located consumer trajectories. We investigate their plausibility with a variety of time and space series clustering and visualization models.

Aiming at the weight degeneracy phenomena in particle filter algorithm, the improved particle filtering algorithm based on neural network was presented. BP neural network and generalized regression neural network (GRNN) are adapted to improve resampling algorithm and importance probability density function. This algorithm utilizes the nonlinear mapping function of BP neural network. First of all, to sample from the importance density function of particle weight division, the weighted particle is splitted into two small weight particles. Then, abandon the weight of very small particles, and adjust the particles with smaller weight by using the neural network. This algorithm optimizes the sample from importance density function by generalized regression neural network. Through GRNN, the samples are adjusted. The samples are more nearer to the posterior probability density. Simulation results show that the particle filter algorithm based on neural network can improve the diversity of particle samples, increase the effective particle number, reduce the mean square error, and the filtering performance is improved. It is proved that this particle filter algorithm based on neural network is available and effective.

Because of the different precision of the satellite-ground and inter-satellite observations, how to correctly determine the weight of the two kinds of observations is still a key technique in integrated orbit determination. According to the ground stations and different kinds of the inter-satellite cross-link of the Chinese COMPASS satellite navigation system, the weight of the two kinds of observations was determined by the Helmert method of variance components estimate, and then the new weight was used in the integrated orbit determination. The results show that this method could reasonably determine the weight of satellite-ground and inter-satellite observations and improve the precision of integrated orbit determination. For the integrated orbit determination based on the Satellite-Ground and Inter-Satellite cross-link fixed antenna data, the orbit accuracies improve from 0.15 to 0.04 m after use the Helmert estimation weight to replace the priori. And the result is 0.06–0.03 m for the Satellite-Ground and Inter-Satellite cross-link UHF antenna data.