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BackgroundTuberculosis (TB) is a leading cause of death worldwide from a single infectious agent. In China the most common extra-pulmonary TB (EPTB) is pleural tuberculosis (PLTB). An important clinical feature of PLTB is that the lymphocytes associated with TB will accumulate in the pleural fluid. The adaptive immune repertoires play important roles in Mycobacterium tuberculosis (Mtb) infection.MethodsIn this study, 10 PLTB patients were enrolled, and their Peripheral Blood Mononuclear Cells(PBMCs) and Pleural Effusion Mononuclear Cells(PEMCs) were collected. After T cells were purified from PBMCs and PEMCs, high-throughput immunosequencing of the TCRβ chain (TRB), TCRγ chain(TRG), and B cell receptor(BCR) immunoglobulin heavy chain (IGH) were conducted on these samples.ResultsThe TRB, TRG, and BCR IGH repertoires were characterized between the pleural effusion and blood in PLTB patients, and the shared clones were analyzed and collected. The binding activity of antibodies in plasma and pleural effusion to Mtb antigens was tested which indicates that different antibodies responses to Mtb antigens in plasma and pleural effusion in PLTB patients. Moreover, GLIPH2 was used to identify the specificity groups of TRB clusters and Mtb-specific TRB sequences were analyzed and collected by VJ mapping.ConclusionWe characterize the adaptive immune repertoires and identify the shared clones and Mtb-specific clones in pleural effusion and blood in PLTB patients which can give important clues for TB diagnosis, treatment, and vaccine development.

This study explored the effect of sesamol on the stability of walnut oil based on the changes of endogenous characteristics in the oxidation process, which provided a theoretical reference for the application of natural antioxidants in walnut oil. A total of 300 mg/kg sesamol (SP), compound antioxidant AC (sesamol 353.62 mg/kg, citric acid 149.60 mg/kg, and BHA 76.33 mg/kg) and 35% sesame oil (35%-SO) were added to walnut oil respectively; in addition, 200 mg/kg t-butylhydroquinone (TBHQ), butylated hydroxyanisole (BHA), and citric acid were used as controls and blank walnut oil to study their effects on peroxide value, acid value, carbonyl compounds, conjugated olefins, phenols, flavonoids, sterols, vitamin E, β-carotene, and 51 fatty acids of walnut oil and their correlation between endogenous antioxidant components. The results showed that the addition of SP, 35%-SO, and AC could inhibit the increase of peroxide value, acid value, and carbonyl compounds in walnut oil, and could inhibit the decrease of β-carotene, total phenols, total sterols, and vitamin E. SP and 35%-SO could inhibit the decrease of total flavonoids, and several antioxidants could inhibit the decrease of endogenous antioxidant components in walnut oil. At the same time, it can better inhibit the change of unsaturated fatty acids in walnut oil. By the end of oxidation, the unsaturated fatty acids of blank walnut oil decreased by 10.31%, but AC, SP, and 35%-SO treatment groups increased by 10.90, 5.09 and 4.13%, respectively. Indicating that it had a certain protective effect on unsaturated fatty acids in walnut oil. There was a certain correlation between the endogenous substances of walnut oil. so the addition of several antioxidants can enhance the endogenous antioxidants of walnut oil, inhibit the oxidation of unsaturated fatty acids, and inhibit the increase of carbonyl compounds, codienes, acid value, and peroxide value. SP and AC have better antioxidant effects on walnut oil and improve the stability of walnut oil.

Underwater navigation practice shows that the long baseline survey has the characteristics of coplanar configuration, flat geometry, and large refraction error, which brings challenges to underwater positioning. To address this challenge, this paper proposes a high-precision real-time range-difference location algorithm based on underwater long baseline measurement. Firstly, the system error sources of long baseline positioning are analyzed in detail, the propagation models of different system errors are constructed, and the effects of system error sources on the rangefinder are described. Secondly, the limitations of traditional range iterative location algorithms and geometric analytic location algorithms in long baseline locations are analyzed. Then, using the strategy of converting the long baseline range information into the distance difference information, a high-precision real-time distance difference location algorithm based on long baseline measurement is presented. Finally, the feasibility of the algorithm is analyzed from the perspective of precision analysis. Numerical simulation results show that compared with the two traditional long-baseline positioning algorithms, the proposed algorithm has higher positioning accuracy and potential application value in the field of underwater real-time positioning.

The task of named entity recognition (NER) is to identify entities in the text and predict their categories. In real-life scenarios, the context of the text is often complex, and there may exist nested entities within an entity. This kind of entity is called a nested entity, and the task of recognizing entities with nested structures is referred to as nested named entity recognition. Most existing NER models can only handle flat entities, and there has been limited research progress in Chinese nested named entity recognition, resulting in relatively few models in this direction. General NER models have limited semantic extraction capabilities and cannot capture deep semantic information between nested entities in the text. To address these issues, this paper proposes a model that uses the GlobalPointer module to identify nested entities in the text and constructs the IDCNNLR semantic extraction module to extract deep semantic information. Furthermore, multiple-head self-attention mechanisms are incorporated into the model at multiple positions to achieve data denoising, enhancing the quality of semantic features. The proposed model considers each possible entity boundary through the GlobalPointer module, and the IDCNNLR semantic extraction module and multi-position attention mechanism are introduced to enhance the model’s semantic extraction capability. Experimental results demonstrate that the proposed model achieves F1 scores of 69.617% and 79.285% on the CMeEE Chinese nested entity recognition dataset and CLUENER2020 Chinese fine-grained entity recognition dataset, respectively. The model exhibits improvement compared to baseline models, and each innovation point shows effective performance enhancement in ablative experiments.

The task of fine-grained named entity recognition is to locate entities in text and classify them into predefined fine-grained categories. At present, Chinese fine-grained NER only uses the pretrained language model to encode the characters in the sentence and lacks the ability to extract the deep semantic, sequence, and position information. The sequence annotation method is character-based and lacks the processing of entity boundaries. Fine-grained entity categories have a high degree of similarity, which makes it difficult to distinguish similar categories. To solve the above problems, this paper constructs the BILTAR deep semantic extraction module and adds the GlobalPointer module to improve the accuracy of Chinese fine-grained named entity recognition. The BILTAR module is used to extract deep semantic features from the coding information of pretrained language models and use higher-quality features to improve the model performance. In the GlobalPointer module, the model first adds the rotation position encoding information to the feature vector, using the position information to achieve data enhancement. Finally, the model considers all possible entity boundaries through the GlobalPointer module and calculates the scores for all possible entity boundaries in each category. In this paper, all possible entity boundaries in the text are considered by the above method, and the accuracy of entity recognition is improved. In this paper, the corresponding experiments were carried out on CLUENER 2020 and the micro Chinese fine-grained NER dataset, and the F1 scores of the model in this paper reached 80.848% and 75.751%, respectively. In ablation experiments, the proposed method outperforms the most advanced baseline model and improves the performance of the basic model.

BackgroundRemarkably, the anti-cancer efficacy of immunotherapy in lung adenocarcinoma (LUAD) has been demonstrated. However, predicting the beneficiaries of this expensive treatment is still a challenge.Materials and methodsA group of patients (N = 250) diagnosed with LUAD and receiving immunotherapy were retrospectively studied. They were randomly divided into a training dataset (80%) and a test dataset (20%). The training dataset was utilized to train neural network models to predict patients’ objective response rate (ORR), disease control rate (DCR), responders (progression-free survival time > 6 months), and overall survival (OS) possibility, which were validated by both the training and test datasets and packaged into a tool later.ResultsIn the training dataset, the tool scored 0.9016 area under the receiver operating characteristic (AUC) curve on ORR judgment, 0.8570 on DCR, and 0.8395 on responder prediction. In the test dataset, the tool scored 0.8173 AUC on ORR, 0.8244 on DCR, and 0.8214 on responder determination. As for OS prediction, the tool scored 0.6627 AUC in the training dataset and 0.6357 in the test dataset.ConclusionsThis immunotherapy efficacy predictive tool for LUAD patients based on neural networks could predict their ORR, DCR, and responder well.

IntroductionInflammation play important roles in the initiation and progression of acute lung injury (ALI), acute respiratory distress syndrome (ARDS), septic shock, clotting dysfunction, or even death associated with SARS-CoV-2 infection. However, the pathogenic mechanisms underlying SARS-CoV-2-induced hyperinflammation are still largely unknown.MethodsThe animal model of septic shock and ALI was established after LPS intraperitoneal injection or intratracheal instillation. Bone marrow-derived macrophages (BMDMs) from WT and BPOZ-2 KO mouse strains were harvested from the femurs and tibias of mice. Immunohistology staining, ELISA assay, coimmunoprecipitation, and immunoblot analysis were used to detect the histopathological changes of lung tissues and the expression of inflammatory factors and protein interaction.Results and conclusionsWe show a distinct mechanism by which the SARS-CoV-2 N (SARS-2-N) protein targets Bood POZ-containing gene type 2 (BPOZ-2), a scaffold protein for the E3 ubiquitin ligase Cullin 3 that we identified as a negative regulator of inflammatory responses, to promote NLRP3 inflammasome activation. We first demonstrated that BPOZ-2 knockout (BPOZ-2 KO) mice were more susceptible to lipopolysaccharide (LPS)-induced septic shock and ALI and showed increased serum IL-1β levels. In addition, BMDMs isolated from BPOZ-2 KO mice showed increased IL-1β production in response to NLRP3 stimuli. Mechanistically, BPOZ-2 interacted with NLRP3 and mediated its degradation by recruiting Cullin 3. In particular, the expression of BPOZ-2 was significantly reduced in lung tissues from mice infected with SARS-CoV-2 and in cells overexpressing SARS-2-N. Importantly, proinflammatory responses triggered by the SARS-2-N were significantly blocked by BPOZ-2 reintroduction. Thus, we concluded that BPOZ-2 is a negative regulator of the NLPR3 inflammasome that likely contributes to SARS-CoV-2-induced hyperinflammation.

Background/ObjectiveThe third-generation epidermal growth factor receptor (EGFR) -tyrosine kinase inhibitor (TKIs), such as osimertinib, designed for targeting the acquired drug-resistant mutation of EGFR T790M, was approved as the first-line therapy for advanced EGFR-mutated non-small cell lung cancer (NSCLC). Thus, detection of the EGFR T790M mutation for NSCLC is crucial. However, tissue samples are often difficult to obtain, especially in patients at advanced stages. This study assessed the performances of droplet digital polymerase chain reaction (ddPCR) and next-generation sequencing (NGS) in detecting EGFR T790M status and abundance in the plasma ctDNA samples of patients with NSCLC. We also explored the association between T790M status and abundance and the response to third-generation EGFR-TKIs.MethodsA total of 201 plasma samples with matched tissues, 821 plasma samples, and 56 patients who received third-generation EGFR-TKIs with response evaluation were included in this study. ddPCR and NGS were used to detect the mutation status and abundance of T790M in the tissues and/or blood samples.ResultsThe results showed that the sensitivity and the specificity of EGFR T790M mutation status detected by ddPCR in plasma samples were 81.82% and 91.85%, respectively, compared with the tissue samples, with a consistency coefficient of 0.740. Among the 821 plasma samples, the positive rates of EGFR T790M detected by ddPCR and NGS were 34.2% (281/821) and 22.5% (185/821), respectively. With NGS results as the reference, the sensitivity and the specificity of ddPCR were 100% and 84.91%, respectively, and the consistency coefficient of the two methods was 0.717. In addition, we found that a higher EGFR T790M abundance was linked to a higher treatment response rate to the third-generation EGFR-TKIs regardless of the classification of the median value of 0.43% (P = 0.016) or average value of 3.16% (P = 0.010).ConclusionTaking these data together, this study reveals that ddPCR is an alternatively potent method for the detection of EGFR T790M in the plasma samples of NSCLC patients.

BackgroundAt present, immunotherapy is a very promising treatment method for lung cancer patients, while the factors affecting response are still controversial. It is crucial to predict the efficacy of lung squamous carcinoma patients who received immunotherapy.MethodsIn our retrospective study, we enrolled lung squamous carcinoma patients who received immunotherapy at Beijing Chest Hospital from January 2017 to November 2021. All patients were grouped into two cohorts randomly, the training cohort (80% of the total) and the test cohort (20% of the total). The training cohort was used to build neural network models to assess the efficacy and outcome of immunotherapy in lung squamous carcinoma based on clinical information. The main outcome was the disease control rate (DCR), and then the secondary outcomes were objective response rate (ORR), progression-free survival (PFS), and overall survival (OS).ResultsA total of 289 patients were included in this study. The DCR model had area under the receiver operating characteristic curve (AUC) value of 0.9526 (95%CI, 0.9088–0.9879) in internal validation and 0.9491 (95%CI, 0.8704–1.0000) in external validation. The ORR model had AUC of 0.8030 (95%CI, 0.7437–0.8545) in internal validation and 0.7040 (95%CI, 0.5457–0.8379) in external validation. The PFS model had AUC of 0.8531 (95%CI, 0.8024–0.8975) in internal validation and 0.7602 (95%CI, 0.6236–0.8733) in external validation. The OS model had AUC of 0.8006 (95%CI, 0.7995–0.8017) in internal validation and 0.7382 (95%CI, 0.7366–0.7398) in external validation.ConclusionsThe neural network models show benefits in the efficacy evaluation of immunotherapy to lung squamous carcinoma patients, especially the DCR and ORR models. In our retrospective study, we found that neoadjuvant and adjuvant immunotherapy may bring greater efficacy benefits to patients.

Considering the complexity of entity pair relations and the information contained in the target neighborhood in few-shot knowledge graphs (KG), existing few-shot KG completion methods generally suffer from insufficient relation representation learning capabilities and neglecting the contextual semantics of entities. To tackle the above problems, we propose a Few-shot Relation Learning-based Knowledge Graph Completion model (FRL-KGC). First, a gating mechanism is introduced during the aggregation of higher-order neighborhoods of entities in formation, enriching the central entity representation while reducing the adverse effects of noisy neighbors. Second, during the relation representation learning stage, a more accurate relation representation is learned by using the correlation between entity pairs in the reference set. Finally, an LSTM structure is incorporated into the Transformer learner to enhance its ability to learn the contextual semantics of entities and relations and predict new factual knowledge. We conducted comparative experiments on the publicly available NELL-One and Wiki-One datasets, comparing FRL-KGC with six few-shot knowledge graph completion models and five traditional knowledge graph completion models for five-shot link prediction. The results showed that FRL-KGC outperformed all comparison models in terms of MRR, Hits@10, Hits@5, and Hits@1 metrics.

Link prediction is a crucial problem in the analysis of graph-structured data, and graph neural networks (GNNs) have proven to be effective in addressing this problem. However, the computational and temporal costs associated with large-scale graphs remain a concern. This study introduces a novel method for link prediction called Sparse Subgraph Prediction Based on Adaptive Attention (SSP-AA). The method generates sparse subgraphs and utilizes Graph SAmple and aggreGatE (GraphSAGE) for prediction, aiming to reduce computation and time costs while providing a foundation for future exploration of large-scale graphs. Certain key issues in GraphSAGE are addressed by integrating an adaptive attention mechanism and a jumping knowledge module into the model. To address the issue of adaptive weight distribution in GraphSAGE, an aggregation function is employed, which is based on the attention mechanism. This modification enables the model to distribute weights adaptively among neighboring nodes, significantly improving its ability to capture node relationships. Furthermore, to tackle the common issue of over-smoothing in GNNs, a jumping knowledge module is integrated, enabling information sharing across different layers and providing the model with the flexibility to select the appropriate representation depth based on the specific situation. By enhancing the quality of node representations, SSP-AA further boosts the performance of GraphSAGE in various prediction tasks involving graph-structured data.

The present study examined whether and how early cognitive flexibility, metalinguistic awareness, including phonological awareness (PA) and morphological awareness (MA), Chinese word reading (CWR), and listening comprehension (LC) influenced Chinese children's later reading comprehension. In total, 153 Chinese children were recruited. Path analysis showed that cognitive flexibility measured when the children were in Grade 1 (M[subscript age] = 85.92 months, SD = 4.36) significantly explained the variance of later reading comprehension at Grade 3 (M[subscript age] = 103.03 months, SD = 3.80) and all concurrent domain-specific precursors of reading comprehension, except LC. Multiple mediation analyses further demonstrated that MA and CWR partially mediated the effect of cognitive flexibility on reading comprehension. Also, the effect of cognitive flexibility on reading comprehension was mediated partially by two two-mediator paths, PA-LC and MA-CWR. These findings demonstrated that cognitive flexibility could be related to reading comprehension directly and indirectly through multiple pathways involving metalinguistic awareness, word reading, and language comprehension. These findings particularly highlighted the roles of MA and word reading in the association between Chinese readers' cognitive flexibility and their reading comprehension.

Background and objective Immune checkpoint inhibitor monotherapy is reported to have little effect in advanced non-small cell lung cancer (NSCLC) patients with driver oncogenes. However, recent studies have shown that some patients with driver genes are still benefit from combination immunotherapy after tyrosine kinase inhibitors (TKIs) drug resistance. The purpose of this study was to analyze the efficacy of posterior line immunotherapy in NSCLC patients with epidermal growth factor (EGFR) sensitive mutation, and to evaluate the value of immunotherapy in posterior line therapy in patients with advanced EGFR mutation. Methods A total of 27 patients with EGFR mutation diagnosed in Beijing Chest Hospital, Capital Medical University from June 2018 to November 2020 were collected. After the progress of targeted therapy, they had received programmed cell death protein 1 (PD-1) checkpoint inhibitor combined with chemotherapy and anti-angiogenic drug therapy. Results Of the 27 advanced NSCLC patients, 19 cases (70.4%) did not have T790M mutation. There were 8 cases (29.6%) with T790M point mutation. The total objective response rate (ORR) was 40.7%. Kaplan-Meier survival analysis showed that there was no statistically significant difference among different EGFR mutations (χ2=4.15, P=0.230). But progression-free survival (PFS) was significantly longer in patients without T790M mutation than in patients with T790M mutation (9.2 mon vs 3.3 mon, χ2=2.808, P=0.041), and the same trend was observed in patients with overall survival treated with the PD-1 inhibitor (12.2 mon vs 7.3 mon, χ2=3.22, P=0.062). ORR of patients without T790M was significantly better than that with T790M (52.63% vs 12.5%, P=0.045). Conclusion Patients with EGFR mutation can benefit from later-line combined immunotherapy. The patients with T790M mutation in the population of EGFR mutation had the worst effect of immunotherapy in the later line. Therefore, the follow-up treatment and whole-course management of these patients need to explore better treatment strategies to improve the benefit.

Passion fruit wine is a popular fruit wine because of its unique aroma. However, the roles of microorganisms in different fermentation methods, particularly their contributions to aroma formation, are poorly understood. Accordingly, the goal of this study is to reveal the contribution of different fermentation methods to the flavor. Purple passion fruit was used as the experimental focus; high-throughput sequencing technology was used to analyze the microbial community of CF (controlled fermentation) and NF (natural fermentation), and the correlations between the microbial community and physicochemical indices, nonvolatile metabolites and flavor substances were analyzed. In NF, totals of eight fungal phyla, 135 fungal genera, 15 bacterial phyla and 130 bacterial genera were identified. Debaryomyces, Meyerozyma, and Wickerhamomyces were the dominant fungal genera, and Paucibacter and Pantoea were the dominant bacterial genera. In CF, totals of 11 fungal phyla, 389 fungal genera, 15 bacterial phyla and 128 bacterial genera were identified. Meyerozyma, Cladosporium, and Saccharomyces were the dominant fungal genera, and Paucibacter, Achromobacter, and Lactobacillus were the dominant bacterial genera. In NF, Wickerhamomyces, Achromobacter, Bifidobacterium and Lactobacillus were positively correlated with flavor substances such as ethylene glycol acetate formate, 2-pentanol, acetate, phenylethyl alcohol and 1-butanol, 3-methyl-. In CF, Saccharomyces, Achromobacter and Lactobacillus were positively correlated with a variety of esters and alcohols such as decanoic acid, ethyl ester, dodecanoic acid, ethyl ester and phenylethyl alcohol. Overall, this study can provide a valuable resource for further developments and improve the aromatic quality of passion fruit wine.

Background and objective Immunotherapy represented by immune checkpoint inhibitors (ICIs) has been widely used in the treatment of lung cancer. There are controversies in clinical practice for patients with advanced non-small cell lung cancer (NSCLC) and high programmed cell death-ligand 1 (PD-L1) expression receiving ICIs monotherapy or combination chemotherapy. Methods This study retrospectively analyzed the clinical data of 49 patients with advanced NSCLC and high PD-L1 expression. Immunohistochemistry was performed with 22C3 antibody, and the expression level of PD-L1 was evaluated according to tumor proportion score (TPS). Objective response rate (ORR) and progression free survival (PFS) were compared by groups of different clinical characteristics. Results ORR of monotherapy and combination therapy group was 47.1% (8/17) and 43.8% (14/32), respectively, without statistical difference (P=0.825). The median PFS of monotherapy and combination therapy group was 8.0 months and 6.8 months, respectively, without statistical difference (P=0.502). Statistical analysis of predictors of immunotherapy for the patients showed first-line immunotherapy had better ORR than subsequent immunotherapy (12/19, 63.2% vs 10/30, 33.3%, P=0.041), however no difference in PFS. And there were no differences in ORR or PFS among groups of age, gender, smoking status, performance status (PS), pathological type, tumor size and tumor-node-metastasis (TNM) stage. Conclusion The therapeutic effect is similar between ICIs monotherapy and combination chemotherapy for patients with advanced NSCLC and high PD-L1 expression. ORR of first-line immunotherapy was better in patients with advanced NSCLC and high PD-L1 expression. The optimal treatment for this population remains further prospective clinical studies.

Background and objective Targeted therapy for patients with driver genes positive and immunotherapy for patients with driver gene-negative but high programmed death ligand 1 (PD-L1) expression are the standards of first-line treatment for patients with advanced non-small cell lung cancer (NSCLC). The treatment options for patients with driver gene positive and high PD-L1 expression are still worth exploring. Methods The characteristics of 315 patients with NSCLC were identified to analyze the clinicopathological characteristics of patients with driver gene positive and high PD-L1 expression, and the efficacy of targeted therapy. Results Among the 315 patients, the total positive rate of driver genes was 62.2%, and the high PD-L1 expression rate (≥50.0%) was 11.2%. The proportion of patients with driver gene positive and high PD-L1 expression was 10.7%. PD-L1 was highly expressed in patients with epidermal growth factor receptor (EGFR) mutation, KRAS mutation, ALK fusion, BRAF mutation, and MET 14 exon skip mutation, the proportions were 7.8% (11/141), 18.2% (4/22), and 23.1%, (3/13), 50.0% (2/4) and 100.0% (1/1) respectively. EGFR mutation positive with PD-L1 high expression was mainly in patients with stage IV lung adenocarcinoma. KRAS mutation positive with PD-L1 high expression was mainly in patients with a history of smoking. Among them, two patients were followed in detail for targeted therapy, who with ALK fusion-positive and PD-L1 high expression (90.0%), EGFR L858R mutation and PD-L1 high expression (70.0%) respectively. The total OS of the patients was 5 months, 2 months. Conclusion The high PD-L1 expression rate in NSCLC patients with different driver gene mutations was variable, which maybe correlated with distinct clinicopathological characteristics. Patients with sensitive mutations and high PD-L1 expression may be less benefit from targeted therapy and have poor prognosis.

Erianin (Eri) is the extract of Dendrobium chrysotoxum Lindl. The NLRP3 inflammasome is a multiprotein complex that plays key roles in a wide variety of chronic inflammation-driven human diseases. Nevertheless, little is known about the protection of Eri against NLRP3 inflammasome-related diseases. In this study, we demonstrated that Eri inhibited NLRP3 inflammasome activation in vitro and in vivo. Mechanistically, Eri directly interacted with NLRP3, leading to inhibition of NLRP3 inflammasome assembly. Eri associated with the Walker A motif in the NACHT domain and suppressed NLRP3 ATPase activity. In mouse models, Eri had therapeutic effects on peritonitis, gouty arthritis and type 2 diabetes, via NLRP3. More importantly, Eri was active ex vivo for synovial fluid cells and monocytes from patients with IAV infection and gout. Eri may serve as a potential novel therapeutic compound against NLRP3-driven diseases.

PurposeCirculating cell-free DNA (cfDNA) level has been demonstrated to be associated with efficacy in first generation EGFR TKIs in non-small cell lung cancer (NSCLC). However, the role of dynamic cfDNA analysis using next-generation sequencing (NGS) in patients with subsequent third-generation EGFR TKIs remains unclear.MethodsFrom 2016 to 2019, 81 NSCLC patients with EGFR T790M mutation either in tissue or plasma who received third-generation EGFR TKIs treatment were enrolled. CfDNA were sequenced by NGS with a 425-gene panel. The association of clinical characteristics, pretreatment, dynamic cfDNA and T790M level with outcomes in patients treated with the third-generation TKIs were analyzed.ResultsIn univariate analysis, the median PFS of patients with undetectable cfDNA level during treatment was significantly longer than those with detectable cfDNA (16.97 vs. 6.10 months; HR 0.2109; P < 0.0001). The median PFS of patients with undetectable T790M level during treatment was significantly longer than those with detectable T790M (14.1 vs. 4.4 months; HR 0.2192; P < 0.001). Cox hazard proportion model showed that cfDNA clearance was an independent predictor for longer PFS (HR 0.3085; P < 0.001) and longer OS (HR 0.499; P = 0.034). The most common resistant mutations of the third-generation TKIs were EGFR C797S (24%). CDK6 CNV, GRIN2A, BRCA2, EGFR D761N, EGFR Q791H, EGFR V843I, and ERBB4 mutation genes may possibly be new resistant mechanisms.ConclusionsPatients with undetectable cfDNA during the third-generation EGFR TKI treatment have superior clinical outcomes, and dynamic cfDNA analysis by NGS is valuable to explore potential resistant mechanisms.

HER2 mutations have emerged as oncogenic driver gene mutations in non-small cell lung cancer (NSCLC), which have not been described in detail like other driver gene mutations. Here, 295 patients with advanced lung adenocarcinoma were retrospectively screened for HER2 mutations using next-generation sequencing (NGS), and the positive cases were validated by Sanger sequencing. We identified five cases with HER2 exon 20 insertions, representing 1.7% of 295 lung adenocarcinomas. Among them, four different subtypes of HER2 exon 20 insertions were identified, including a rare subtype G778_S779insCPG never reported before with a partial response (PR) to pyrotinib and progression-free survival (PFS) of 12.8 months. Our findings reveal that HER2 exon 20 insertion mutations were detected in a small subset of lung adenocarcinomas. Given the different drug sensitivities, determining the mutation subtype by next-generation sequencing at the time of diagnosis might make sense.

The optical-mechanical system of a space camera is composed of several complex components, and the effects of several factors (weight, gravity, modal frequency, temperature, etc.) on its system performance need to be considered during ground tests, launch, and in-orbit operation. In order to meet the system specifications of the optical camera system, the dimensional parameters of the optical camera structure need to be optimized. There is a highly nonlinear functional relationship between the dimensional parameters of the optical machine structure and the design indexes. The traditional method takes a significant amount of time for finite element calculation and is less efficient. In order to improve the optimization efficiency, a recurrent neural network prediction model based on the Bayesian regularization algorithm is proposed in this paper, and the NSGA-II is used to globally optimize multiple prediction objectives of the prediction model. The reflector of the space camera is used as an example to predict the weight, first-order modal frequency, and gravitational mirror deformation root mean square of the reflector, and to complete the lightweight design. The results show that the prediction model established by BR-RNN-NSGA-II offers high prediction accuracy for the design indexes of the reflector, which all reach over 99.6%, and BR-RNN-NSGA-II can complete the multi-objective optimization search efficiently and accurately. This paper provides a new idea of optimization of optical machine structure, which enriches the theory of complex structure design.

Background and objective Non-small cell lung cancer (NSCLC) has been transformed from the treatment according to histological type to genotype treatment model. The epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) genes are the most important drivers in lung cancer. The aim of this study is to explore the clinical characteristics and prognostic factors of patients with advanced NSCLC with different genotypes. Methods We retrospectively reviewed the clinical data of 553 advanced NSCLC patients with EGFR mutations and ALK positive who were hospitalized in the Beijing Chest Hospital from July 2004 to December 2015, and the independent prognostic factors of patients were analyzed by Cox proportional hazards regression model. Results The clinical data of 553 patients (227 with EGFR mutations, 58 with ALK positive, 2 with EGFR and ALK co-mutation and 266 with wild-type) with advanced NSCLC were enrolled in this study. The median survival time of 227 patients with EGFR mutations was 28.7 mo (95%CI: 22.160-35.240), and the performance status (PS) score (0-1) (HR=4.451; 95%CI: 2.112-9.382; P

Seven steady-state temperature profiles are logged in the Harbin Area, Northeast China. The temperature data illustrate high conductive thermal gradients with a mean value of 4.78°C/100 m. Temperature maps at depths of 1000, 1500, and 1800 m are represented. The present temperature field is cooling southeastward, with the highest thermal gradients being observed at the junction zone between the Central Depression and the Southeast Uplift of the Songliao Basin. The recoverable heat is calculated using a volumetric method and Monte Carlo simulation. The mean value for recoverable heat from the detailed exploration area around the Harbin Area is 1.052 × 10 19 J (3.59 × 10 11 t standard coal). Geological controls on the present temperature fields are discussed.

Background and objective There is no high-level evidence for the time of whole brain radiotherapy (WBRT) for patients with epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) and brain metastases. The aim of this study is to assess the appropriate timing of WBRT for patients with EGFR-mutated NSCLC and brain metastases (BM). Methods There were 78 patients diagnosed with EGFR-mutated NSCLC and BM in Beijing Chest Hospital between August 2009 and May 2015. 48 untreated patients who received both WBRT and EGFR-tyrosine kinase inhibitors (TKIs) therapy. Prognostic factors of intracranial progression-free survival (PFS) and overall survival (OS) were identified by Cox proportional hazards modeling. Results Intracranial objective response rate was 81.3% and disease control rate was 93.8%. Median intracranial PFS was 10 months. Median OS was 18 months. Multivariate analysis of intracranial PFS revealed that Eastern Cooperative Oncology Group (ECOG) performance status (PS) 0-1 (HR=30.436, 95%CI: 4.721-196.211, P

Background and objective Anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC) is an important subtype of lung cancer. The standard modality of ALK-positive NSCLC with brain metastases remains uncertain. Methods We collected data on clinical characteristics and treatment of patients with ALK-positive NSCLC and brain metastases between March 2013 and March 2016 and retrospectively analyzed patient outcomes. Results In 84 ALK-positive patients with advanced NSCLC, 22 (26.2%) had brain metastases during the initial diagnosis of lung cancer, among which 3 patients with EGFR mutation were excluded, and 19 patients were analyzed. Median intracranial progression-free survival (PFS) was 12.0 months. PFS for patients who received first-line local brain therapy (P=0.021) and crizotinib therapy (P=0.030) was superior to PFS for patients without such therapies. PFS for patients who received first-line crizotinib combined with local brain therapy was 27.0 months and only 4.2 months for those who received crizotinib alone. Conclusion First-line crizotinib therapy combined with local brain treatment can improve intracranial PFS for ALK-positive NSCLC with brain metastases. This finding should be confirmed further through multicenter, prospective clinical trials with large sample size.

Background and objective Kirsten rat sarcoma viral oncogene (KRAS) mutation is one of the major driver genes of non-small cell lung cancer (NSCLC). KRAS is a resistant predictor of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), which raises controversy because of its role in chemotherapy sensitivity and prognosis. The aim of this study is to accumulate clinical experience in treating NSCLC patients harboring KRAS mutation. Methods A total of 107 NSCLC patients harboring KRAS mutation were analyzed retrospectively. The efficacy was analyzed in terms of first-line chemotherapy or EGFR-TKIs therapy. Results The objective response rate (ORR) to first-line chemotherapy of 52 patients with advanced disease harboring KRAS mutation was 9.6%. The disease control rate (DCR) was 53.8%, and the median progression-free survival (PFS) was 3 months. The ORR to EGFR-TKIs therapy in 21 patients harboring KRAS mutation and EGFR/KRAS co-mutation was 9.5%; the DCR was 23.8%, and the median PFS was 1 month. The ORR and DCR to EGFR-TKIs therapy of patients with EGFR/KRAS co-mutation were significantly higher than those of patients with KRAS mutation (50% vs 0, P=0.029; 75% vs 11.8%, P=0.043); the median PFS was also significantly longer (3 months vs 1 month, P=0.004). Conclusion The efficacy to first-line chemotherapy and EGFR-TKIs therapy in NSCLC patients harboring KRAS mutation was poor; thus, new drugs should be developed. Furthermore, the existence of EGFR/KRAS co-mutation was confirmed. Hence, EGFR-TKIs therapy should be administered to patients with EGFR/KRAS co-mutation.

Background and objective Mutations in epidermal growth factor receptor (EGFR) and KRAS are important markers in non-small cell lung cancer, which are closely related to the clinical therapeutic effect. To analysis the EGFR and KRAS gene mutation rate and its relationship with clinical features in patients with lung adenocarcinoma. Methods 395 patients with treatment naïve lung adenocarcinoma, tumor tissue samples were available for testing. Tumor sample EGFR and KRAS mutation status were detected using mutant enriched liquidchip. Results 395 cases of lung adenocarcinoma, EGFR mutations were detected in 192 cases (48.9%), KRAS mutations were detected in 29 cases (7.8%), and the presence of EGFR and KRAS mutation were detected in 1 case (0.3%). EGFR mutations were found to occur significantly more often in female than in male patients (62.0% vs 37.1%, P0.05) in each clinical factors, only occurred in the wild type EGFR gene in patients (13.5%, 27/200) was significantly higher than that of patients with EGFR mutation (1.0%, 2/192), the difference was statistically significant (P

Background and objective Activating mutations in epidermal growth factor receptor (EGFR) and KRAS are important markers in non-small cell lung cancer. However, EGFR and KRAS gene mutations in lung squamous cell carcinoma are rarely reported. The aim of this study was to analyze EGFR and KRAS gene mutation rate and their relationship with clinical features in patients with lung squamous cell carcinomas. Methods A total of 139 patients undergoing treatment for naïve lung squamous cell carcinomas with tumor tissue samples available for testing were recruited. EGFR and KRAS mutation statuses of the tumor samples were detected using a mutant enriched liquid chip. Results Of the 139 cases of lung squamous cell carcinoma, EGFR mutations were detected in 25 cases (18%), KRAS mutations were detected in 7 cases (5%), and the presence of both EGFR and KRAS mutations was detected in 1 case (0.7%). EGFR mutations occurred more often in females than in males (33.3% vs 16.5%) and in patients that never smoked than in those who smoke (29.6% vs 16.1%). However, the difference did not reach statistical significance (P>0.05). No significant differences were observed in age, stage, and different biopsy type. KRAS mutations occurred more often in males than in females (5.5% vs 0%), but the difference did not reach statistical significance (P>0.05). No significant differences were observed in age, stage, different biopsy type, and smoking status (P>0.05). Conclusion EGFR and KRAS mutations were low in lung squamous cell carcinomas, and had no significant correlation with clinical features. Before using tyrosine kinase inhibitor targeted therapy, EGFR and KRAS mutations should be detected in patients with lung squamous cell carcinomas.

Background and objective Status of epidermal growth factor receptor (EGFR) gene is a predictor of response to EGFR tyrosine kinase inhibitor (TKI). However, little is know about the relationship between EGFR status and response to chemotherapy. We evaluated the prediction value of EGFR mutation status on response to first-line chemotherapy in patients with advanced non-small-cell lung cancer (NSCLC). Methods The data of 181 patients with stage IIIb/IV NSCLC who diagnosed by histopathology from January 10, 2006 to December 20, 2013 in Beijing Chest Hospital, Capital Medical University were collected. The relationships between EGFR gene status, clinical characteristics and response and progression-free survival (PFS) were analyzed. Results All of the 181 patients’ EGFR statuses were determined. 75 (41.4%) patients harbored EGFR-activating mutations and 106 (58.6%) patients were EGFR wild-type. All patients received first-line chemotherapy. The objective response rate (ORR) was 26.0% and disease control rate (DCR) was 70.2%. Patients with EGFR-activating mutations had a higher DCR than patients with EGFR wild-type (84.0% vs 60.4%, P=0.001) did. Subgroup analysis showed that the ORR and DCR in patients with EGFR exon 19 deletions were remarkably higher than those with EGFR wild-type (P = 0.049, 0.002, respectively). The DCR in patients with EGFR exon 21 L858R mutation was significantly higher than that in patients with EGFR wild-type (P=0.010). 168 patients were available for response evaluation in all of 181 patients and median PFS was 4.3 mo. The PFS of patients with adenocarcinoma was significantly higher than that patients with squamous cell carcinoma (4.7 mo vs 3.0 mo, P=0.036). The PFS in patients harbored EGFR-activating mutations was significantly higher than that in the patients with EGFR wild-type (6.3 mo vs 3.0 mo, P=0.002). The PFS of patients with a performance status (PS) of 0-1 was significantly higher than that in patients with a PS of 2 (4.4 months vs. 0.7 months, P= 0.016). Cox multivariate analysis indicates the EGFR-activating mutation is an independent factor affecting PFS (HR=0.654, 95%CI: 0.470-0.909, P=0.012). Conclusion EGFR-activating mutation is a predictor for PFS of first-line chemotherapy in advanced NSCLC patients.

BACKGROUND:Peroxisome proliferator-activated receptor gamma (PPARG) plays an important role in the pathogenesis and maintenance of essential hypertension (EH). It has been suggested that polymorphisms of PPARG are associated with the risk of EH. However, findings to date remain controversial. To elucidate the associations between the PPARG Pro12Ala and C161T polymorphisms and EH risk, a meta-analysis was carried out. METHODS:A comprehensive literature search of PubMed, Embase, CNKI (Chinese National Knowledge Infrastructure), VIP and Wanfang databases was conducted. The pooled odds ratios (ORs) and 95% confidence interval (CI) were calculated to estimate the size of the effect using the random-effects model. At the same time, the pooled standardized mean difference (SMD) with 95% CI was used for the meta-analysis of the PPARG Pro12Ala polymorphism and blood pressure. RESULTS:Finally, Fifteen papers (seventeen studies) including 4,151 cases and 4,997 controls to evaluate the association of the PPARGPro12Ala polymorphism and EH risk, were included in this study. Overall, the results suggested that Ala allele was associated with the decreased EH risk (for allelic model, OR = 0.757, 95%CI: 0.624-0.918, P = 0.005; for dominant model, OR = 0.771, 95%CI: 0.627-0.946, P = 0.013). The subgroup analysis stratified by ethnicity showed that the significant association between the PPARG Pro12Ala polymorphism and EH was only detected in the Asian subgroup. There was no difference in blood pressure values between Ala carriers and non-carriers. For the C161T polymorphism, only 5 studies comprising 1,118 cases and 1,357 controls met the inclusion criteria. The overall results showed that the PPARG C161T polymorphism was not associated with the risk of EH. But in the subgroup analysis, we found that the PPARG C161T polymorphism significantly associated with the risk of EH in the Asian subgroup (for allelic model, OR = 0.719, 95% CI: 0.537-0.963, P = 0.027; for dominant model, OR = 0.653, 95% CI: 0.439-0.972, P = 0.036). CONCLUSION:Our meta-analysis suggested that the PPARG polymorphisms might be associated with the risk of EH.

Background. The present study aimed to evaluate the prevalence and prognosis of residual lipid abnormalities in statin-treated acute coronary syndrome (ACS) patients after percutaneous coronary intervention (PCI). Subjects and Methods. A total of 3,047 ACS patients who underwent PCI and received statin therapy were included. Plasma concentrations of LDL-C, HDL-C, and TG were measured. For the follow-up study, major adverse cardiovascular cerebrovascular events (MACCE; including total death, cardiovascular death, myocardial infarction, and revascularization) were documented. Results. A total of 93.14% of all individuals were followed up for 18.1 months (range, 0–29.3 months). Of all 3,047 patients, those with a suboptimal goal were 67.75%, 85.85%, and 33.64% for LDL-C, HDL-C, and TG levels, respectively. Multiple Cox regression analysis revealed there were significant increases in cumulative MACCE of 41% (HR = 1.41, 95% CI [1.09–1.82], p=0.008), and revascularization of 48% (HR = 1.48, 95% CI [1.10–1.99], p=0.01) in low HDL-C patients with ACS after PCI, but not the high TG group at the end of study. Conclusions. Our results showed there is high rate of dyslipidemia in Chinese ACS patients after PCI. Importantly, low HDL-C but not high TG levels are associated with higher MACCE and revascularization rates in ACS patients after PCI.

Background and objectives It has been proven that epigermal growth factor receptor (EGFR) signal pathway plaied an important role in the oncogenesis and development of non-small cell lung cancer (NSCLC). EGFR tyrosine kinase inhibitors (EGFR-TKIs) are currently investigated in the treatment of NSCLC. It was suggested in previous studies that the EGFR gene mutations were correlated with the response to EGFR-TKIs therapy and prognosis of NSCLC. We studied the role of EGFR gene mutations in response to two kinds of TKIs therapy and prognosis of NSCLC in this study. Methods The tissue samples of 59 advanced NSCLC patients (34 patients receiving Gefitinib monotherapy and 25 patients receiving Erlotinib monotherapy) were collected, and patient charts were reviewed. The mutations in exons 19 and 21 of EGFR gene were detected by PCR-PAGE and PCR-RFLP respectively. The sequences of interested fragments were verified by direct sequencing. Relationship between EGFR mutation and response to TKIs therapy was analyzed with X^2 test. Results EGFR gene mutations were identified in 22 of 59 samples (37.3%). EGFR gene mutation rate was significantly higher in female, non-smoker and patients with adenocarcinoma than in others (50% vs 18.9%, P0.05). Conclusions EGFR gene mutation occurs more frequently in female, non-smoker and patients with adenocarcinoma. In patients with advanced NSCLC, EGFR mutation is associated with good response to EGFR-TKIs therapy.

Background and objective Icotinib is the first self-developed small molecular drug in China for targeted therapy of lung cancer. Compared to the other two commercially available epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors, gefitinib and erlotinib, icotinib is similar to them in chemical structure, mechanism of activity and therapeutic effects. To explore the efficacy and side effects of icotinib hydrochloride in the treatment of the advanced non-small cell lung cancer (NSCLC) patients with EGFR mutation and wild-type. Methods Patients with advanced NSCLC who were treated with icotinib hydrochloride in Beijing Chest Hospital were retrospective analyzed from March 2009 to December 2014. Results The clinical data of 124 patients (99 with EGFR mutation and 25 with wild type) with advanced NSCLC were enrolled in this study. The patients’ overall objective response rate (ORR) was 51.6 % and the disease control rate (DCR) was 79.8%; The patients with EGFR mutation, ORR was 63.6%, DCR was 93.9%. The ORR was 4.0% and the DCR was 24.0% in the wild-type patients. Median progression-free survival (PFS) with icotinib treatment in EGFR mutation patients was 10.5 months and 1.0 month in wild-type patients. The major adverse events were mild skin rash (30.6%) and diarrhea (16.1%). Conclusion Monotherapy with icotinib hydrochloride is effective and tolerable for the advanced NSCLC EGFR mutation patients.

Background and objective Erlotinib is a small molecular inhibitor of tyrosine kinase. Multiple foreign and demestic studies have confirmed that it can prolong the median progression-free survival time (PFS) and the overall survival (OS), which could be more significant in the selected population. In this study we retrospectively oberserved the response, the survival and adverse reaction of erlotinib in non-selected non-small cell lung cancer. Methods The retrospective study included seventy non-small-cell lung cancer patients, who were treated with erlotinib from July 2005 to July 2009. Erlotinib was prescribed at a dose of 150 mg daily. Results Sixty-eight patients were evaluated response. Among these patients, CR 0 case, PR 26 cases, RR (CR+PR) 38.2% and SD 24 cases as their best response, disease control rate (DCR=CR+PR+SD) 73.5%, PD 18 cases (26.5%). Sixty-three patients were evaluated PFS. The median PFS was 3.0 months. The median PFS of adenocarcinoma and non-adenocarcinoma was 3.0 months vs 2.6 months. The drug-related adverse reactions were skin rash , diarrhea and interstitial lung disease (ILD)(4.3%). Conclusion Erlotinib is active in non-small cell lung cancer, and it is much more effective in adenocarcinoma and non-smoking patients. There is no difference in response or suvival concerning the sexuality. It is well tolerated in most patients.