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Lung cancer is the top reason for cancer-related deaths worldwide. The 5-year overall survival rate of lung cancer is approximately 20 % due to the delayed diagnosis and low response rate to regular treatments. Microbiota, both host-microbiota and alien pathogenic microbiota, have been investigated to be involved in a complicated and contradictory relationship with lung cancer initiation, treatments, and prognosis. Disorders of certain host-microbiota and pathogen infection are associated with the risk of lung cancers based on epidemiological evidence, and antibiotics (ATBs) could dramatically impair anti-cancer treatment efficacy, including chemotherapy and immunotherapy. Moreover, probiotics and microbe-mediated drugs are potential approaches to enhance regular anti-tumor treatments. Therefore, the knowledge of the complex dual effect of microbes on lung cancer is beneficial to take their essence and remove their dross. This review offers insight into the current trends and advancements in microbiota or microbial components related to lung cancer.

Hydrogen fueling stations (HFSs) with onsite hydrogen production systems, which are usually composed of electrolyzers, hydrogen storage tanks and fuel cells, not only supply hydrogen for hydrogen-powered vehicles but also serve as a dispatchable technology that can bid in electricity markets. Except participating in energy market, joining in reserve market can compensate the cost in energy market and increase the total revenue of HFS. This paper proposes a multi-stage stochastic programming model to find the optimal offering strategy of the HFS in energy, reserve markets taking into account a series of uncertainties: day-ahead price, secondary reserve price, system imbalance price and hydrogen demand. Nonanticipativity constraints are employed to guarantee the decisions are made according to the realized uncertainty information up to the present stage. Compared with traditional stochastic programming model, the proposed model adequately considers the sequential bidding decisions with the gradual revealing of the uncertainty over time. Numerical experiments based on one case study indicate that the participation of reserve market greatly increase the revenue of HFS. In addition, the proposed multi-stage stochastic programming model is effective in characterizing the sequential decision.

Although there have been many studies on the factors influencing university innovation, few studies have focused on the causal relationship between government innovative support and the innovation ability of universities (IAU). To fill this research gap, based on the quasi-natural experiment perspective of the pilot policy of innovation and entrepreneurship demonstration-bases (IEDB), this study uses the difference-in-differences spatial-autocorrelation model and the mediating-effect model to study the influence mechanism of the government innovation support on IAU, based on Project 211’s panel data consisting of 104 universities and provinces and ministries in China, from 2009 to 2018. The results showed that: (1) the pilot policy of IEDB has a significantly positive effect on IAU, and its robustness is verified; (2) the university–industry cooperation (UIC) intensity has a partial mediating effect on the relationship between the pilot policy of IEDB and IAU; and (3) the pilot policy of IEDB shows a more significant positive impact on the IAU of research-oriented than on non-research-oriented universities.

BACKGROUND: Interventional bronchoscopy exhibits substantial effects for patients with malignant airway obstruction (MAO), while little information is available regarding the potential prognostic factors for these patients. METHODS: Between October 31, 2016, and July 31, 2019, a total of 150 patients undergoing interventional bronchoscopy and histologically-confirmed MAO were collected, in which 112 eligible participants formed the cohort for survival study. External validation cohort from another independent institution comprised 33 MAO patients with therapeutic bronchoscopy. The least absolute shrinkage and selection operator regression (LASSO) was applied to the model development dataset for selecting features correlated with MAO survival for inclusion in the Cox regression from which we elaborated the risk score system. A nomogram algorithm was also utilized. RESULTS: In our study, we observed a significant decline of stenosis rate after interventional bronchoscopy from 71.7%±2.1% to 36.6%±2.7% (P

Objective This review was conducted to systematically summarize the progress made by artificial intelligence technology in early screening based medical imaging, pathological diagnosis, genomics inspection, prognostic evaluation, and individual treatment of lung cancer. Background Lung cancer has a high mortality rate in China, which is closely related to the fact that most lung cancer patients are not diagnosed until the malignancy is advanced. Challenges remain in the early detection, accurate diagnosis, monitoring and individual treatment of lung cancers. Artificial intelligence has developed to process large amounts of data, from clinical presentations to physiological images, which is essential for solving the complex issues with clinical medicine. Increasing evidence has suggested that artificial intelligence technology provides novel, promising strategies for the diagnosis and treatment of lung cancer. Methods A review of literature was conducted in PubMed, EMBASE and Cochrane to identify the latest research on artificial intelligence and lung cancer, and ultimately to generate a narrative review. Conclusions Artificial intelligence plays an important role in the imaging inspection, histopathology examination and genomics inspection of lung cancer. In addition, artificial intelligence has the ability to detect a small number of biomarkers, which is conducive to lung cancer monitoring. Moreover, the intelligent treatment of lung cancer has gradually become the trend of future development, whether in internal medicine or surgical treatment. It is believed that artificial intelligence could improve the early diagnosis of lung cancer and assist doctors in treating lung cancer patients individually.

To elucidate the clinicopathological characteristics and oncological outcomes of clinical T1aN0M0 (c-T1N0M0) lung cancer based on the newest 8th TNM classification. A total of 257 patients with c-T1aN0M0 lung cancer were retrospectively included in this study. According to the solid component size manifesting on the high-resolution computed tomography (HRCT), all lesions were classified as the pure ground-glass nodule (pure-GGN) with a diameter > 3 cm (n = 19), part-solid (n = 174), and pure-solid (n = 64) groups. We evaluated the prognostic impact of clinicopathologic variables including radiological presentations by establishing Cox proportional hazards model. When we evaluated the prognostic impact based on the radiological subtypes, the 5-year recurrence-free survival (RFS) and overall survival (OS) were significantly different among pure-GGN, part-solid, and pure-solid groups (RFS: 100% versus 95.4% versus 76.6%, p < 0.0001; OS: 100% versus 98.9% versus 87.5%, p < 0.0001). Cox regression analysis revealed the preoperative carcinoembryonic antigen (CEA) level and consolidation tumor ratio (CTR) were independently significant prognosticators related to RFS and OS. Furthermore, a receiver operating characteristic (ROC) verified the CTR (area under ROC [AUC] 0.784, 95%CI 0.697–0.869) was equipped with good performance to predict the postoperative recurrence with a cutoff point at 0.5. Lung cancer with higher CTR tended to be associated with lower survival in the c-T1aN0M0 stage. For the c-T1aN0M0 lung cancer, pulmonary nodules manifested as the pure-GGN and part-solid subtypes had an excellent prognosis and may be considered as the “early-stage” cancer, whereas those with pure-solid appearance were associated with the high risk of recurrence despite the sub-centimeter size. • Radiological subtypes could further stratify the risk of lung cancer in cT1a. • Sub-solid nodule has a favorable survival in c-T1a lung cancer, whereas pure-solid nodule is not always “early-stage” lung cancer and is relatively prone to postoperative recurrence despite the sub-centimeter size. • The preoperative CEA level and CTR are valuable prognosticators to predict the recurrence in c-T1a lung cancer.

To overcome the topographic limitations of pumped hydro storage (PHS) system, novel gravity energy storage (GES) technologies are developing. In this paper, a pioneering work on the modeling and scheduling of a GES system is conducted. The GES system stores and releases energy by lifting and lowering concrete bricks. Since the working principle of the GES system is similar to that of a PHS plant, a double-tower based model of the GES system is established. In addition, a day-ahead scheduling model of the GES system is proposed to test the operation of such system. Specifically, the uncertainty of market price is considered with a data-driven distributionally robust optimization method. Some linearization and reformulation techniques are presented to transform the problem into a mixed integer linear programming (MILP) problem which can be solved easily. Numerical experiments indicate that the proposed model can effectively characterize the operation of the GES system. Concrete bricks are lifted up during low-price period and descend under gravity during high-price period to gain benefits. Additionally, the round trip efficiency considerably influences the total profits.

The role of government support in sustainable urban development has always been a research topic of scholars, but research focusing on the relationship between government innovation support and urban green sustainable development is still relatively rare. This article uses China’s innovative city pilot policy (ICPP) to represent the innovation support provided by the government and address the interaction mechanism and the spatial spillover effect of China’s innovative city pilot policy (ICPP), green technology innovation (GTI), and green sustainable development performance (GSDP) with the support of the mediating effect model and the spatial econometric model. Based on panel data of 24 cities in the Yangtze River Delta urban agglomeration from 2001 to 2020, this paper establishes an evaluation index system of green sustainable development performance (GSDP), measuring with the SBM directional distance function based on the undesired output. This paper adopts the spatial difference-in-difference model (SDID) to study the impact mechanism of the ICPP on the GSDP in the Yangtze River Delta. The results show that (i) there is a positive spatial spillover effect of GSDP in the urban agglomeration of the Yangtze River Delta urban agglomeration; (ii) ICPP has a significantly positive effect on GSDP, as verified by several robustness checks; (iii) green technology innovation plays a partial mediating effect in the relationship of the ICPP and GSDP.

Hydrogen fueling stations (HFSs) will proliferate in the near future as they are prerequisites for the fast developing hydrogen-powered vehicles (HVs). The HFSs can utilize cheap renewable energy from, e.g., wind turbines (WTs), to generate and store hydrogen on site locally. Conventional studies usually ignore the independence of the WT and HFSs and perform joint operation optimization to them. This article, however, proposes a cooperative operation model for the WT and HFSs considering individual benefit. Nash bargaining theory is employed to deal with the energy trading and benefit sharing problems during the cooperation. In particular, the conditional value-at-risk (CVaR) is used to characterize the risk-preference degree of HFSs against the uncertainties of electricity price. Moreover, an improved benders decomposition (BD) algorithm is proposed to solve the energy trading problem in a distributed manner for privacy concern; while an analytical method is developed to solve the payment bargaining problem. Numerical experiments based on two case studies indicate that the cooperation can greatly reduce the hydrogen production cost for HFSs. In addition, the proposed algorithm outperforms conventional alternating direction method of multipliers (ADMM) algorithm in the case studies.

Objective: To identify the protective and anti-apoptotic role of alpha-crystallin related lncRNAs.Methods: We established stable overexpression of αA- and αB-crystallin in human lens epithelial cells (HLECs). All cells were treated with 0.1 μmol, 1 μmol, 10 μmol and 100 μmol Dex for 12 h, 24 h, 36 h, and 48 h then we detected nine related apoptotic proteins and closely related lncRNAs . Results: Based on western blot results, we determined the most significant exposure factors and cell types and performed long non-coding RNA (lncRNA) and mRNA chip scanning using microchip assay. The results of microchip assay were also verified by real-time PCR. We found that αA- and αB-crystallin had a close relationship with the expression of three anti-apoptotic proteins heat shock protein 60 (HSP60), survivin and P53. However, no significant changes in the expression of cytochrome C, Samc, P65, and Fas were found in HLECs (αA-crystallin overexpressed) and in HLECs (αB-crystallin overexpressed). Following lncRNA and mRNA chip scanning and depth analysis, we found that overexpressed αA-crystallin could increase the expression of lnc-TMPRSS15, TMPRSS15 and related CDH12 and could decrease the expression of HSD11B1, lnc-RNF13-2 and lnc-CDH2-1 which may result in the significantly high expression of anti-apoptotic proteins such as HSP60, survivin and P53. Conclusion: Our results showed that αA-crystallin promoted the expression of some anti-apoptotic proteins. Lnc-TMPRSS15 played a very important role which provides a theoretical basis for the mechanism of glucocorticoid-induced cataract.

BACKGROUND: The hemoglobin (Hgb)/red cell distribution width (RDW) ratio (HRR) is a simple prognostic marker for small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), but no data are available for pulmonary large cell neuroendocrine carcinoma (PLCNEC). This study aimed to assess the potential prognostic role of preoperative HRR in PLCNEC. METHODS: This single-center retrospective study included patients with PLCNEC who underwent surgery at Shanghai Pulmonary Hospital from January 2012 to August 2016. The follow-up was censored in August 2020. The participants were grouped as low/high HRR according to their optimal value calculated using a receiver operating characteristic (ROC) curve. Univariable and multivariable Cox analysis were performed to identify the risk factors for overall survival (OS). RESULTS: A total of 80 patients with PLCNEC were included. The optimal cutoff values were 0.969 for HRR. Compared with the high HRR group, the low HRR group had a lower mean Hgb (12.1 vs. 14.1 g/dL, P

BACKGROUND: Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare clinical subtype of lung cancer which has a poor prognosis for patients. This study aimed to explore the relationship between blood-based inflammatory markers, namely neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), and the prognosis for pulmonary LCNEC. METHODS: Peripheral leukocyte and platelet counts of 106 LCNEC patients were measured within the week leading up to their surgery. Serum neuron specific enolase (NSE) was detected by ELISA. Overall survival (OS) was analyzed by Kaplan-Meier method and compared by log-rank test. RESULTS: The NLR and PLR cut-off values based on survival receiver operating characteristic curve (ROC) were 2.52 and 133.6, respectively. A correlation was found between dichotomized NLR and tumor size (P=0.006), and PLR and NLR were significantly correlated with each other (P

We develop a new cross-sample entropy, namely the multiscale cross-trend sample entropy (MCTSE), to investigate the synchronism of dynamical structure regarding two series with potential trends. It incorporates symbolic representation and polynomial fitting trend. Numerical tests illustrated that the newly proposed MCTSE can address the series with various trends well and detect asynchrony between two series more sensitively. The MCTSE is used to analyze the asynchrony between air quality index (AQI) series of Beijing, Changsha and Zhuhai and the series of six air quality impact factors (PM2.5, PM10, $$\hbox {SO}_2$$, CO, $$\hbox {NO}_2$$ and $$\hbox {O}_3$$). We find that the consistency between the AQI series and the two fine particulates series of PM2.5 and PM10 is obviously higher than other four factors series. Comparing the entropy values of these pollution factors between every two cities, we also found that the pollutants in Changsha and Zhuhai are similar in quality, but they are quite different from those in Beijing. These findings help to further explore the similarities and differences in dynamic structure of the AQI series and identify the main pollutant. This has certain reference value for the reduction and control of similar pollutants.

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

CLLC converter is widely used due to its bidirectional symmetry, high efficiency, and low reactive power. In the resonant network, the design of the inductance ratio (resonant inductance L r /magnetizing inductance L m ) determines ZVS realization, circulation loss, and dv/dt. The existing L r /L m method only considers the realization of ZVS. And it can’t give the precise boundary of ZVS because there are too many assumptions. As a result, the existing design method cannot give an optimal value. This paper proposes an optimal design method for L r /L m based on CLLC resonant converter. It can reduce circulation loss and dv/dt while ensuring soft-switching. And this method gives a precise boundary of ZVS by establishing a dead zone model. By using this, an optimal region of L r /L m can be given. Finally, a 4kW, 500kHz bidirectional CLLC platform is designed based on GaN Hemts devices. The experiment verifies the precision of the proposed optimal design method.

Hao Wang,1,2 Shanhao Chen,1 Die Meng,1,2 Chunyan Wu,3 Junjie Zhu,4 Minlin Jiang,1,2 Jing Ning,1,2 Shengyu Wu,1,2 Lijia Wu,5 Jingjie Li,5 Bin Chen,1 Sha Zhao,1 Wei Li,1 Jia Yu,1,2 Qiyu Fang,1,2 Jun Zhu,1,2 Wencheng Zhao,1,2 Yayi He,1 Caicun Zhou1 1Department of Medical Oncology, Shanghai Pulmonary Hospital, Shanghai, 200433, People’s Republic of China; 2Medical School, Tongji University, Shanghai, 200433, People’s Republic of China; 3Pathology Department, Shanghai Pulmonary Hospital, Shanghai, 200433, People’s Republic of China; 4Surgery Department, Shanghai Pulmonary Hospital, Shanghai, 200433, People’s Republic of China; 5Genecast Biotechnology Co., Ltd, Wuxi City, Jiangsu, 214104, People’s Republic of ChinaCorrespondence: Yayi He; Caicun ZhouDepartment of Medical Oncology, Shanghai Pulmonary Hospital, No. 507 Zhengmin Road, Shanghai, People’s Republic of ChinaTel +86 13818828623; Tel +86 13818828623Email 2250601@qq.com; caicunzhoudr@126.comIntroduction: Nowadays, immune checkpoint blockades (ICBs) have been extensively applied in non-small cell lung cancer (NSCLC) treatment. However, the outcome of anti-program death-1/program death ligand-1 (anti-PD-1/PD-L1) therapy is not satisfying in EGFR-mutant lung adenocarcinoma (LUAD) patients and its exact mechanisms have not been fully understood. Since tumor mutation burden (TMB) and tumor immune phenotype had been thought as potential predictors for efficacy of ICBs, we further studied the TMB and immune phenotype in LUAD patients to explore potential mechanisms for poor efficacy of ICBs in EGFR positive mutated patients and to find possible factors that could impact the tumor immune phenotype which might uncover some new therapeutic strategies or combination therapies.Methods: We enrolled 223 LUAD patients who underwent surgery in our hospital. We evaluated TMB through targeted panel sequencing. The tumor immune phenotype, which could be divided into non-inflamed, intermediate and inflamed, was determined through immunohistochemistry using formalin-fixed paraffin-embedded samples. Enumeration data were analyzed by Chi-square test or Fisher exact test and shown as number (proportion). Logistic regression model was employed for univariate and multivariate analysis of the association between TMB levels and clinical characteristics.Results: The median TMB level was 4.0445 mutations/Mb. Multivariate analysis showed the TMB level was significantly associated with age (P=0.026), gender (P=0.041) and EGFR mutation status (P=0.015), and in EGFR-mutant patients we found a lower proportion of patients with mutated KRAS and BRCA2. Furthermore, we found patients with or without metastatic lesions would have different immune phenotype (P=0.007). And the mutational frequencies of ALK, CDKN2A, MAP2K1, IDH2 and PTEN were significantly different among three immune phenotypes.Conclusion: Low TMB level could be the reason for the poor efficacy of ICBs in patients having EGFR mutation. And mutational frequencies of KRAS and BRCA2 were lower in EGFR-mutant patients. Furthermore, ALK, CDKN2A, MAP2K1, IDH2 and PTEN might involve in the formation of immune phenotypes.Keywords: lung adenocarcinoma, EGFR mutation, tumor mutation burden, immune phenotype, immune checkpoint blockade

BackgroundImmunotherapies may prolong the survival of patients with small-cell lung cancer (SCLC) to some extent. The role of forkhead box protein P3 (FOXP3) in tumor microenvironment (TME) remains controversial. We aimed to examine FOXP3-related expression characteristics and prognostic values and to develop a clinically relevant predictive system for SCLC.MethodsWe enrolled 102 patients with histologically confirmed SCLC at stages I–III. Through immunohistochemistry, we determined the expression pattern of FOXP3 and its association with other immune biomarkers. By machine learning and statistical analysis, we constructed effective immune risk score models. Furthermore, we examined FOXP3-related enrichment pathways and TME traits in distinct cohorts.ResultsIn SCLC, FOXP3 level was significantly associated with status of programmed death-ligand 1 (PD-L1), programmed cell death protein 1 (PD-1), CD4, CD8, and CD3 (p=0.002, p=0.001, p=0.002, p=0.030, and pCD28, basic excision repair genes MUTYH, POLD1, POLD2, and oxidative phosphorylation related gene cytochrome c oxidase subunit 8A with FOXP3 expression were revealed. Moreover, we found low-immune risk score group had statistically higher activated CD4+ memory T cells (p=0.014) and plasma cells (p=0.049) than the high-risk group. The heterogeneity of tumor-infiltrating immune cells might represent a promising feature for risk prediction in SCLC.ConclusionFOXP3 interacts closely with immune biomarkers on tumor-infiltrating cells in TME. This study highlighted the crucial prognostic value and promising clinical applications of FOXP3 in SCLC.

Checkpoint-based immunotherapies, such as programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) inhibitors, have shown promising clinical outcomes in many types of cancers. Unfortunately, the response rate of immune checkpoint inhibitors is low. It is very important to discover novel therapeutic targets and prognostic biomarkers. Cholesterol metabolism has been demonstrated to be related to the occurrence and development of a variety of tumors and may provide a new breakthrough in the development of immunotherapy. First of all, cholesterol metabolism in the tumor microenvironment affects the function of tumor-infiltrating immune cells. In addition, intracellular cholesterol homeostasis is an important regulator of immune cell function. Furthermore, drugs that act on cholesterol metabolism affect the efficacy of immunotherapy. What is more, peripheral blood cholesterol level can be a biomarker to predict the efficacy of immunotherapy. In this review, we aimed to explore the potential role of cholesterol metabolism on immunotherapy. By summarizing the major findings of recent preclinical and clinical studies on cholesterol metabolism in immunotherapy, we suggested that cholesterol metabolism could be a potential therapeutic target and a prognostic biomarker for immunotherapy.

BackgroundMore information on genetic variation can be obtained by exon sequencing for the diagnosis of nuclear age-related cataract (NARC). MethodsIn our present study, genomes of 12 DNA samples were sequenced. The average effective depth was 10× when using Illumina sequencing. After conducting whole-exon sequencing, we further performed depth analysis and spectrum analysis to determine the gene polymorphism sites closely associated with NARC. ResultsIn genes showing single nucleotide polymorphism (SNP), there were 18,699 synonymous mutations and 17,975 missense mutations in the coding region. A total of 4,944 insertions and deletions (indels) were found. Among them, 1329 indels exhibited polymorphism and were further analyzed. Whole-exon sequencing previously showed polymorphism associated with ARC and known pathways associated with protein synthesis and metabolism. Following depth analysis (GO and KEGG analysis), we identified 20 promising candidate genes that were closely related to NARC. We further performed spectrum analysis for 26 polymorphism sites and found that ZNF573 (rs3095726, SNP), ZNF862 (rs62621204, SNP), SYNE3 (rs76499929, indel), and GAS2L2 (rs78557458, SNP) had statistically significant relationship with NARC. The 3D protein structure showed obvious changes for ZNF573 (rs3095726, SNP) and GAS2L2 (rs78557458, SNP). ConclusionsOur findings provide the basis for further studies and discovery of key genes associated with NARC.

Background Platinum-based chemotherapy remains the essential therapy for small cell lung cancer (SCLC). Here, we conducted a statistical analysis to explore whether the curative efficacy of 2-cycle platinum-based chemotherapy can predict the survival of patients with SCLC. Methods Fifty-six SCLC patients who had each received 2 cycles of platinum-based chemotherapy were enrolled. The curative efficacy of the chemotherapy was evaluated, mainly by chest computed tomography, and the treatment response was categorized according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. Patients were continuously followed up for progression-free survival (PFS) and overall survival. The 55 patients were separated into 2 groups by the curative efficacy of the 2-cycle first-line platinum-based chemotherapy. All statistical analyses were performed with SPSS software (version 17.0; SPSS, Inc.; Chicago, IL, USA). Results Patients who responded to 2-cycle chemotherapy (partial response, PR) had significantly better survival than others who did not (stable disease, SD or progressive disease, PD). The median progression-free survival (mPFS) in the PR group was 6.330 months, which was significantly longer than the 2.870 months seen in SD+PD group (95% CI: 4.631-8.029 vs. 0.000-5.790, P=0.022). The median overall survival (mOS) was 10.870 months in the PR group, which was remarkably longer than the 8.970 months observed in the SD+PD group (95% CI: 9.546-12.194 vs. 6.517-11.423, P=0.028). Curative efficacy had no correlation with clinical features. Conclusions The curative efficacy of 2-cycle first-line platinum-based chemotherapy was significantly correlated with PFS and OS, and showed prognostic value in SCLC patients. Patients who were sensitive to chemotherapy had superior survival to those who were chemotherapy insensitive.

The imbalance of helper T (Th) 17 and regulatory T (Treg) cells plays an important role in the pathogenesis of pneumonia. This study aims to investigate the role and mechanism of long non-coding RNA growth arrest-specific 5 (GAS5) in the differentiation of Th17 cells and Tregs in childhood pneumonia. Expression of GAS5, miR-217, signal transducer and activator of transcription-5 (STAT5), receptor-related orphan receptor γt (RORγt), and transcription factor Forkhead box P3 (Foxp3) were examined by qRT-PCR and western blot. The percentage of Th17 cells and Tregs in CD4+ T cells were measured by flow cytometry. The interaction between miR-217 and GAS5 or STAT5 was analyzed by luciferase reporter assay. Downregulated GAS5 expression and Treg cell percentage, and upregulated Th17 cell percentage were observed in pneumonia patients when compared with the healthy controls. Furthermore, GAS5 overexpression corrected the imbalanced Th17/Treg in peripheral blood CD4+ T cells derived from pneumonia patients, and this effect was reversed by miR-217 mimic and STAT5 silencing. Mechanistically, GAS5 acted as a sponge of miR-217 to reduce binding of miR-217 to its target STAT5, leading to upregulation of STAT5 expression. Taken together, GAS5 corrects the Treg/Th17 imbalance by targeting the miR-217/STAT5 axis in childhood pneumonia.