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There is a complex transition phenomenon in the flow field of a typical hypersonic vehicle, which has a significant impact on the performance of the vehicle. The effects of Mach number and wall temperature on the transition of HyTRV were studied by numerical simulation methods. The self-developed software of the research group was used to carry out numerical calculations. The range of Mach number was 3~8, and the range of wall temperature was 150~900 K. Firstly, the hypersonic corrections of the γ-$\mathop R\limits^ \sim $eθt transition model and the SST turbulence model were carried out. The pressure gradient coefficient correction and the high-speed cross-flow correction were introduced into the γ-$\mathop R\limits^ \sim $eθt transition model, and the compressibility corrections of the closure coefficients β* and β of the SST turbulence model were carried out. Then, the grid independence verification was carried out, and the modified numerical method and software platform were confirmed by comparing with experimental results. Finally, the effects of Mach number and wall temperature on the transition law of the HyTRV boundary layer were studied. The results show that the transition area is mainly concentrated on both sides of the upper surface and the center line of the lower surface. With the increase of the incoming Mach number, the starting position of transition on the upper and lower surfaces is greatly backward, and the turbulent zone is greatly reduced, but it still exists. At the same time, the friction coefficient of the laminar flow zone on the upper surface increases continuously, and the friction coefficient of the turbulent zone on the lower surface decreases. As the wall temperature increases, the starting position of transition on the upper and lower surfaces shifts forward, then rapidly shifts backward, and finally the turbulent zone almost disappears.

Abstract The phenomenon of wind abandoned caused by fault of transmission lines has occurred frequently. Since fault current output by wind turbine after fault may induce the frequency variation of the fundamental frequency, fault location based on the fundamental resistance is easily invalid. In order to locate fault accurately and rapidly after wind farm transmission line faults, a time‐domain‐based novel fault location method for transmission line of wind farm is introduced in this paper. The main idea of the proposed scheme is to discretise the distributed‐parameter model of transmission line that is given in the form of partial differential equations by using the finite‐difference time‐domain. In addition, the phase current and voltage at both ends of lines are regarded as boundary conditions. Then, the variational iteration method is utilised to calculate transmission line equations to obtain line length function. At last, fault location function is constructed by a minimised objective function. This paper builds wind power transmission line system simulation model and carries out simulation experiments on PSCAD/EMTDC. To verify the performance of the algorithm, several factors are taken into account for simulation including different fault distances, different fault types, different fault resistances, and different fault inception angles. Simulation results reveal the performance of the proposed method to locate fault for transmission lines connected to wind farm with high accuracy.

Abstract Background Lung squamous cell carcinoma (LUSC) is prone to metastasis and likely to develop resistance to chemotherapeutic drugs. DNA repair has been reported to be involved in the progression and chemoresistance of LUSC. However, the relationship between LUSC patient prognosis and DNA damage repair genes is still unclear. Methods The clinical information of LUSC patients and tumour gene expression level data were downloaded from the TCGA database. Unsupervised clustering and Cox regression were performed to obtain molecular subtypes and prognosis-related significant genes based on a list including 150 DNA damage repair genes downloaded from the GSEA database. The coefficients determined by the multivariate Cox regression analysis and the expression level of prognosis-related DNA damage repair genes were employed to calculate the risk score, which divided LUSC patients into two groups: the high-risk group and the low-risk group. Immune viability, overall survival, and anticarcinogen sensitivity analyses of the two groups of LUSC patients were performed by Kaplan–Meier analysis with the log rank test, ssGSEA and the pRRophetic package in R software. A time-dependent ROC curve was applied to compare the survival prediction ability of the risk score, which was used to construct a survival prediction model by multivariate Cox regression. The prediction model was used to build a nomogram, the discriminative ability of which was confirmed by C-index assessment, and its calibration was validated by calibration curve analysis. Differentially expressed DNA damage repair genes in LUSC patient tissues were retrieved by the Wilcoxon test and validated by qRT–PCR and IHC. Result LUSC patients were separated into two clusters based on molecular subtypes, of which Cluster 2 was associated with worse overall survival. A prognostic prediction model for LUSC patients was constructed and validated, and a risk score calculated based on the expression levels of ten DNA damage repair genes was employed. The clinical utility was evaluated by drug sensitivity and immune filtration analyses. Thirteen-one genes were upregulated in LUSC patient samples, and we selected the top four genes that were validated by RT–PCR and IHC. Conclusion We established a novel prognostic model based on DNA damage repair gene expression that can be used to predict therapeutic efficacy in LUSC patients.

This study presents signatures of seismo-ionospheric perturbations possibly related to the 14 July 2019 \begin{document}$ {M}_{w} $\end{document}7.2 Laiwui earthquake, detected by a cross-validation analysis of total electron content (TEC) data of the global ionospheric map (GIM) from GPS and plasma parameter data recorded by the China Seismo-Electromagnetic Satellite (CSES). After separating pre-seismic ionospheric phenomena from the ionospheric disturbances due to the magnetospheric and solar activities, we have identified three positive temporal anomalies, around the epicenter, at 1 day, 3 days and 8 days before the earthquake (14 July 2019), along with a negative anomaly 6 days after the earthquake. These results agree well with the TEC spatial variations in latitude–longitude–time (LLT) maps. To confirm these anomalies further, we employed the moving mean method (MMM) to analyze ionospheric plasma parameters (electron, \begin{document}$ {\mathrm{O}}^{+} $\end{document}and \begin{document}$ {\mathrm{H}\mathrm{e}}^{+} $\end{document}densities) recorded by the Langmuir probe (LAP) and Plasma Analyzer Package (PAP) onboard the CSES. The analysis detected on, on Day Two, Day Four, and Day Seven before the earthquake, remarkable enhancements along the orbits around when in proximity to the epicenter. To make the investigations still more convincing, we compared the orbits on which anomalous readings were recorded to their corresponding four nearest revisiting orbits; the comparison did indeed indicate the existence of plasma parameter anomalies that appear to be associated with the Laiwui earthquake. All these results illustrate that the unusual ionospheric perturbations detected through GPS and CSES data are possibly associated with the \begin{document}$ {M}_{w}7.2 $\end{document} Laiwui earthquake, which suggests that at least some earthquakes may be predicted by alertness to pre-seismic ionospheric anomalies over regions known to be at seismic risk. This case study also contributes additional information of value to our understanding of lithosphere–atmosphere–ionosphere coupling.

Abstract During the lifetime of females, mammary epithelial cells undergo cyclical expansion and proliferation depending on the cyclical activation of mammary gland stem/progenitor cells (MaSCs) in response to the change of hormone level. The structural shrink of mammary duct tree and the functional loss of mammary gland occur along with inactivation of MaSCs in old females, even leading to breast cancer occasionally. However, the gene expression signature in MaSCs across the lifespan remains unclear. Herein, we tested the tissue regeneration ability of CD24+CD49fhigh MaSCs over six time points from neonatal (4-day-old) to aged mice (360-day-old). Further RNA-seq analyses identified four clusters of gene signatures based on the gene expression patterns. A subset of stemness-related genes was identified, showing the highest level at day 4 of the neonatal age, and the lowest level at the old age. We also identified an aging-related gene signature showing significant change in the old mice, in which an association between aging process and stemness loss was indicated. The aging-related gene signature showed regulation of cancer signaling pathways, as well as aging-related diseases including Huntington disease, Parkinson disease, and Alzheimer disease. Moreover, 425, 1056, 418, and 1107 gene variants were identified at D20, D40, D90, and D180, respectively, which were mostly reported to associated with tumorigenesis and metastasis in cancer. In summary, the current study is the first to demonstrate the gene expression shift in MaSCs from neonatal to aging, which leads to stemness loss, aging, aging-related diseases, and even breast cancer in old mice.

Abstract Objective The aim of this study was to assess the efficacy and safety of intrapleural perfusion with hyperthermic chemotherapy (IPHC) in treating malignant pleural effusion (MPE) compared to normothermic chemoperfusion of the pleural cavity (NCPC), and to investigate the better treatment to control MPE. Methods Malignant pleural effusion patients were enrolled in the study and treated with NCPC or IPHC under video‐assisted thoracoscopic surgery (VATS). The chest drainage duration, clinical characteristics, and recurrence time of pleural effusion of patients were collected for statistical analysis. The chi‐squared test and the Fisher's exact test were applied to compare the distribution differences in categorical variables. Progression‐free survival (PFS) was estimated by the Kaplan–Meier method and was compared by the log‐rank test. The survival analysis was performed using the Cox proportional hazards method. Results A total of 37 MPE patients were enrolled in this study. Twenty‐seven patients received NCPC and 10 patients received IPHC under VATS. Significant differences were found in pathological types (p = 0.011), chest drainage duration (p = 0.005), and remission rate (p = 0.009) between two different treatment groups. The chest drainage duration of IPHC under VATS was shorter than the NCPC group (t = 2.969, p = 0.005). The remission rate of MPE in IPHC group was better than the NCPC one (OR = 0.031, 95% CI: 0.002–0.507, p = 0.015). The result of the Kaplan–Meier method showed that IPHC group could significantly prolong the PFS of patients with MPE compared to NCPC group (log‐rank p = 0.002). Univariate cox regression analysis showed that patients with MPE in the IPHC group presented significant longer PFS than the NCPC group (HR = 0.264, 95% CI: 0.098–0.713, p = 0.009). Multivariate cox regression analysis further verified this conclusion (HR = 0.268, 95% CI: 0.096–0.753, p = 0.012). Conclusion Compared to the NCPC, the IPHC under VATS presents a better control effect on MPE, shorter tube placement time, and longer complete remission time. For this reason, we recommend IPHC under VATS as the first‐line treatment for patients with MPE those who can tolerate minimally invasive surgery.

This study presents three distributed beamforming algorithms to address the challenges of positioning and signal phase errors in unmanned aerial vehicle (UAV) arrays that hinder effective beamforming. Firstly, the array’s received signal phase error model was analyzed under near-field conditions. In the absence of navigation data, a beamforming algorithm based on the Extended Kalman Filter (EKF) was proposed. In cases where navigation data were available, Taylor expansion was utilized to simplify the model, the non-Gaussian noise of the compensated received signal phase was approximated to Gaussian noise, and the noise covariance matrix in the Kalman Filter (KF) was estimated. Then, a beamforming algorithm based on KF was developed. To further estimate the Gaussian noise distribution of the received signal phase, the noise covariance matrix was iteratively estimated using unscented transformation (UT), and here, a beamforming algorithm based on the Unscented Kalman Filter (UKF) was proposed. The proposed algorithms were validated through simulations, illustrating their ability to suppress the malign effects of errors on near-field UAV array beamforming. This study provides a reference for the implementation of UAV array beamforming under varying conditions.

Abstract Background Periprosthetic joint infection is a grievous complication after arthroplasty that greatly affects the quality of life of patients. Rapid establishment of infection diagnosis is essential, but great challenges still exist. Methods We conducted research in the PubMed, Embase, and Cochrane databases to evaluate the diagnostic accuracy of D-lactate for PJI. Data extraction and quality assessment were completed independently by two reviewers. The pooled sensitivity, specificity, likelihood ratios, diagnostic odds ratio (DOR), summarized receiver operating characteristic curve (sROC), and area under the sROC curve (AUC) were constructed using the bivariate meta-analysis framework. Results Five eligible studies were included in the quantitative analysis. The pooled sensitivity and specificity of D-lactate for the diagnosis of PJI were 0.82 (95% CI 0.70–0.89) and 0.76 (95% CI 0.69–0.82), respectively. The value of the pooled diagnostic odds ratio (DOR) of D-lactate for PJI was 14.18 (95% CI 6.17–32.58), and the area under the curve (AUC) was 0.84 (95% CI 0.80–0.87). Conclusions According to the results of our meta-analysis, D-lactate is a valuable synovial fluid marker for recognizing PJI, with high sensitivity and specificity.

Abstract Background This study aimed to explore the potential regulatory mechanisms of brain metastasis and to identify novel underlying targets of lung cancer with brain metastasis. Methods Exosomes were isolated from the plasma of lung cancer patients with or without brain metastasis and low or high metastatic lung cancer cells, and small RNA from plasma-derived exosomes were sequenced. Differentially expressed miRNAs (DE-miRNAs) were identified. Human brain microvascular endothelial cells (HBMECs) were transfected with miR-550a-3-5p mimics or inhibitors and exosomes. Cell viability, migration, and apoptosis/cycle were determined using Cell Counting Kit-8 (CCK-8), Transwell, and flow cytometry, respectively. Western blotting was used to measure the expression of the associated proteins. Finally, a dual-luciferase reporter gene assay was performed to confirm the miR-550a-3-5p target. Results Transmission electron microscopy, NanoSight, and western blotting showed that exosomes were successfully isolated and cell-derived exosomes could be taken up by HBMECs. Sequencing identified 22 DE-miRNAs which were enriched in the MAPK, chemokine, PPAR, and Wnt signaling pathways. MiR-550a-3-5p was significantly enriched in brain metastatic exosomes. Cellular experiments showed that miR-550a-3-5p and exosome enrichment significantly inhibited cell viability and migration, promoted apoptosis, and regulated the cell cycle of HBMECs compared with the controls (P

Background: Many biological clocks related to aging have been linked to the development of cancer. A recent study has identified that the inflammatory aging clock was an excellent indicator to track multiple diseases. However, the role of the inflammatory aging clock in glioblastoma (GBM) remains to be explored. This study aimed to investigate the expression patterns and the prognostic values of inflammatory aging (iAge) in GBM, and its relations with stem cells.Methods: Inflammation-related genes (IRG) and their relations with chronological age in normal samples from the Cancer Genome Atlas (TCGA) were identified by the Spearman correlation analysis. Then, we calculated the iAge and computed their correlations with chronological age in 168 patients with GBM. Next, iAge was applied to classify the patients into high- and low-iAge subtypes. Next, the survival analysis was performed. In addition, the correlations between iAge and stem cell indexes were evaluated. Finally, the results were validated in an external cohort.Results: Thirty-eight IRG were significantly associated with chronological age (|coefficient| > 0.5), and were used to calculate the iAge. Correlation analysis showed that iAge was positively correlated with chronological age. Enrichment analysis demonstrated that iAge was highly associated with immune cells and inflammatory activities. Survival analysis showed the patients in the low-iAge subtype had significantly better overall survival (OS) than those in the high-iAge subtype (p < 0.001). In addition, iAge outperformed the chronological age in revealing the correlations with stem cell stemness. External validation demonstrated that iAge was an excellent method to classify cancer subtypes and predict survival in patients with GBM.Conclusions: Inflammatory aging clock may be involved in the GBM via potential influences on immune-related activities. iAge could be used as biomarkers for predicting the OS and monitoring the stem cell.

Background: Autophagy plays a vital role in cancer development. However, the prognostic value of autophagy-related genes (ARGs) in low-grade gliomas (LGG) is unclear. This research aimed to investigate whether ARGs correlated with overall survival (OS) in LGG patients.Methods: RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA) TARGET GTEx database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of ARGs were performed by the “clusterprofile” R package. Cox regression with the wald χ2 test was employed to identify prognostic significant ARGs. Next, the receiver operator characteristic curves were established to evaluate the feasibility of risk score (riskscore=h0(t)exp(∑j=1nCoefj×Xj)) and other clinical risk factors to predict prognosis. A nomogram was constructed. Correlations between clinical features and ARGs were further verified by a t-test or Kruskal–Wallis test. In addition, the correlations between autophagy and immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA) and tumor immune estimation resource database. Last, the prediction model was verified by LGG data downloaded from the Chinese Glioma Genome Atlas (CGGA) database.Results: Overall, 35 DE-ARGs were identified. Functional enrichment analysis showed that these genes were mainly related to oxidative stress and regulation of autophagy. Nine ARGs (BAX, BIRC5, CFLAR, DIRAS3, GRID2, MAPK9, MYC, PTK6, and TP53) were significantly associated with OS. Age (Hazard ratio (HR) = 1.063, 95% CI: 1.046–1.080), grade (HR = 3.412, 95% CI: 2.164–5.379), histological type (HR = 0.556, 95% CI: 0.346–0.893), and risk score (HR = 1.135, 95% CI: 1.104–1.167) were independent prognostic risk factors (all p < 0.05). In addition, BIRC5, CFLAR, DIRAS3, TP53, and risk scores were found to correlate significantly with age and tumor grade (all p < 0.05). Immune cell enrichment analysis demonstrated that the types of immune cells and their expression levels in the high-risk group were significantly different from those in the low-risk group (all p < 0.05). A prognostic nomogram was constructed to predict 1-, 3-, and 5-year survival, and the prognostic value of sorted ARGs were verified in the CGGA database and clinical samples.Conclusion: Our findings suggest that the 9 DE-ARGs’ risk score model could serve as diagnostic and prognostic biomarkers. The prognostic nomograms could be useful for individualized survival prediction and improved treatment strategies.

Abstract Background Ferroptosis is a recently recognized non-apoptotic cell death that is distinct from the apoptosis, necroptosis and pyroptosis. Considerable studies have demonstrated ferroptosis is involved in the biological process of various cancers. However, the role of ferroptosis in esophageal adenocarcinoma (EAC) remains unclear. This study aims to explore the ferroptosis-related genes (FRG) expression profiles and their prognostic values in EAC. Methods The FRG data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regressions were used to identify the prognostic FRG, and the predictive ROC model was established using the independent risk factors. GO and KEGG enrichment analyses were performed to investigate the bioinformatics functions of significantly different genes (SDG) of ferroptosis. Additionally, the correlations of ferroptosis and immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA) and TIMER database. Finally, SDG were verified in clinical EAC specimens and normal esophageal mucosal tissues. Results Twenty-eight significantly different FRG were screened from 78 EAC and 9 normal tissues. Enrichment analyses showed these SDG were mainly related to the iron-related pathways and metabolisms of ferroptosis. Gene network demonstrated the TP53, G6PD, NFE2L2 and PTGS2 were the hub genes in the biology of ferroptosis. Cox regression analyses demonstrated four FRG (CARS1, GCLM, GLS2 and EMC2) had prognostic values for overall survival (OS) (all P

Turbulent convective heat-transfer characteristics in a concentric annular channel with both walls heated are theoretically modeled and numerically computed in this article. Generalized algebraic predictive models and equations for heating over a single wall are first reviewed by summarizing the well-known methods in the literature. These methods are then scrutinized according to the most recent investigations such that new viewpoints and corrections are introduced accordingly. Moreover, the application of superposition in temperature is used in the current work instead of the Nusselt number as seen in the literature. The numerical integration method is applied to the generalized equations to obtain the solutions, which are found to be in decent agreement with the direct numerical simulation (DNS) data in the literature. The results in this work also indicate that the wall heat flux density ratio and the annular radius ratio are two key factors that have a great influence on the heat-transfer characteristics of the case with both walls heated.

Abstract Background Several studies have demonstrated autophagy was involved in the process of esophageal adenocarcinoma (EAC). The aim of this study was to explore autophagy-related genes (ARGs) correlated with overall survival (OS) in EAC patients. Methods Expressions of ARGs in EAC and normal samples were downloaded from TCGA database. GO and KEGG enrichment analyses were used to investigate the ARGs bioinformatics functions. Univariate and multivariate cox regressions were performed to identify prognostic ARGs and the independent risk factors. ROC curve was established to evaluate the feasibility to predict the prognosis. Finally, the correlations between ARGs and clinical features were further explored. In addition, significantly different ARGs were verified in EAC specimens and normal esophageal mucosal tissues. Results Thirty significantly different ARGs were selected from EAC and normal tissues. Functional enrichments showed these ARGs were mainly related apoptosis. Multivariate cox regression analyses demonstrated eight ARGs were significantly associated with OS. Among these eight genes, BECN1 (HR = 0.321, P = 0.046), DAPK1 (HR = 0.636, P = 0.025) and CAPN1 (HR = 0.395, P = 0.004) played protective roles in survival. Gender (HR = 0.225, P = 0.032), stage (HR = 5.841, P = 0.008) and risk score (HR = 1.131, P < 0.001) were independent prognostic risk factors. ROC curves showed better efficacy to predict survival using the risk score. Additionally, we found BECN1, DAPK1, VAMP7 and SIRT1 genes were correlated significantly with survival status, gender, primary tumor and tumor stage (all P < 0.05). The experimental results confirmed the BIRC5 was overexpressed and the ITPR1, PRKN were downregulated in the EAC tissues compared with the normal esophageal mucosal tissues (all P < 0.05). Conclusion Our findings suggested that autophagy was involved in the process of EAC. Several ARGs probably could serve as diagnostic and prognostic biomarkers and may help facilitate therapeutic targets in EAC patients.

Abstract Pulmonary fibrosis is a chronic, progressive lung disease associated with lung damage and scarring. The pathological mechanism causing pulmonary fibrosis remains unknown. Emerging evidence suggests prominent roles of epithelial–mesenchymal transition (EMT) of alveolar epithelial cells (AECs) in myofibroblast formation and progressive pulmonary fibrosis. Our previous work has demonstrated the regulation of YY1 in idiopathic pulmonary fibrosis and pathogenesis of fibroid lung. However, the specific function of YY1 in AECs during the pathogenesis of pulmonary fibrosis is yet to be determined. Herein, we found the higher level of YY1 in primary fibroblasts than that in primary epithelial cells from the lung of mouse. A549 and BEAS-2B cells, serving as models for type II alveolar pulmonary epithelium in vitro, were used to determine the function of YY1 during EMT of AECs. TGF-β-induced activation of the pro-fibrotic program was applied to determine the role YY1 may play in pro-fibrogenesis of type II alveolar epithelial cells. Upregulation of YY1 was associated with EMT and pro-fibrotic phenotype induced by TGF-β treatment. Targeted knockdown of YY1 abrogated the EMT induction by TGF-β treatment. Enforced expression of YY1 can partly mimic the TGF-β-induced pro-fibrotic change in either A549 cell line or primary alveolar epithelial cells, indicating the induction of YY1 expression may mediate the TGF-β-induced EMT and pro-fibrosis. In addition, the translocation of NF-κB p65 from the cytoplasm to the nucleus was demonstrated in A549 cells after TGF-β treatment and/or YY1 overexpression, suggesting that NF-κB-YY1 signaling pathway regulates pulmonary fibrotic progression in lung epithelial cells. These findings will shed light on the better understanding of mechanisms regulating pro-fibrogenesis in AECs and pathogenesis of lung fibrosis.

The target of an unmanned aerial vehicle swarm will present near-field characteristics when it is integrated as an array, and the existence of the unmanned aerial vehicle swarm motion error will greatly deteriorate the beam pattern formed by the array. To solve these problems, a near-field array beamforming model with array element position error is constructed, and the Taylor expansion of the phase difference function is used to approximately simplify the model. The improved Newton maximum entropy algorithm is proposed to estimate and compensate for the phase errors. The maximum entropy objective function is established, and the Newton iterative algorithm is used to estimate the phase error iteratively. To select the proper Newton iteration initial value, based on a single reference source signal, the initial value of the phase error is estimated through the phase gradient information of the received array signal. Beamforming is carried out after phase error compensation regarding the array. In order to assess the mismatch of the phase error compensation function based on the proposed method, when the beam is scanning, the effectively compensated spatial area of the array beamforming is divided, which lays a foundation for subsequent spatial region division and unmanned aerial vehicle swarm path planning. The simulation results show that the beam formed by the method proposed in this paper has a lower sidelobe level, and as the signal-to-noise ratio changes, the robustness of the proposed method is better validated. The proposed algorithm can effectively suppress the adverse influence of array element position error on array beamforming, and when the beam is scanning, the effectively compensated area of the phase error compensation function is divided, based on the proposed method.

The question of which turbulence model is better for a given class of applications is always confusing for the CFD researchers and users. Comparative assessments of scale-adaptive simulation (SAS), improved delay detached-eddy simulation (IDDES) and other hybrid RANS/LES models based on eddy-viscosity models (EVMs) are thoroughly investigated. But how well they perform based on a second-moment closure needs to be answered. In this paper, a widely acclaimed Reynolds-stress model (RSM) in aeronautical engineering, SSG/LRR- ω model, is carried out. The relevant test cases include the NACA0012 airfoil stalled flows and turret separated flow. In order to make a more reasonable comparison, a seventh-order scheme WCNS-E8T7 is adopted to reduce the influence of the numerical dissipation and a symmetrical conservative metric method is used to ensure the robustness. By comparing with the relevant experimental data and the solutions by original SSG/LRR- ω model (etc. URANS), it shows that all of the three hybrid methods (SAS, IDDES and hybrid filtering methods) based on the SSG/LRR- ω model have a good ability to simulate unsteady turbulence. Among them, the IDDES correction has the most potential.

Cancer stem cells (CSCs) contribute to the cancer initiation, metastasis and drug resistance in non-small cell lung cancer (NSCLC). Herein, we identified a miR-221/222 cluster as a novel regulator of CSCs in NSCLC. Targeted overexpression or knockdown of miR-221/222 in NSCLC cells revealed the essential roles of miR-221/222 in regulation of lung cancer cell proliferation, mammosphere formation, subpopulation of CD133+ CSCs and the expression of stemness genes including OCT4, NANOG and h-TERT. The in vivo animal study showed that overexpression of miR-221/222 significantly enhanced the capacity of lung cancer cells to develop tumor and grow faster, indicating the importance of miR-221/222 in tumorigenesis and tumor growth. Mechanistically, Reck was found to be a key direct target gene of miR-221/222 in NSCLC. Overexpression of miR-221/222 significantly suppressed Reck expression, activated Notch1 signaling and increased the level of NICD. As an activated form of Notch1, NICD leads to enhanced stemness in NSCLC cells. In addition, knockdown of Reck by siRNA not only mimicked miR-221/222 effects, but also demonstrated involvement of Reck in the miR-221/222-induced activation of Notch1 signaling, verifying the essential roles of the miR-221/222-Reck-Notch1 axis in regulating stemness of NSCLC cells. These findings uncover a novel mechanism by which lung CSCs are significantly manipulated by miR-221/222, and provide a potential therapeutic target for the treatment of NSCLC.

This work is an attempt to critically analyze the correlation between great deep-focus undersea earthquake and possible ionospheric anomalies. The significant TEC (total electron content) temporal and spatial anomalies were detected over the epicenter of 2007 Mw7.5 Jakarta–Java earthquake, and they coincide well with the striking plasma anomalies in the ionosphere in situ observed by the LEO (low Earth orbit) satellite. The localization and synchronization of the disturbances during the earthquake suggest that these ionospheric anomalies are highly related to this large undersea earthquake. In order to identify this correlation, we made efforts to distinguish seismo-associated signals from large electromagnetic noise due to solar and geomagnetic activities, natural non-seismic sources and known artificial signals. Nevertheless, the difficulties of this work should be recognized and approached with caution. This special (deep-focus and undersea) case study here provides us with valuable information on the study of lithosphere–atmosphere–ionosphere (LAI) coupling process and reminds us that deep-focus undersea seismic events need to be treated more carefully and discreetly in the future.

MicroRNAs regulate a wide range of biological processes and being able to inhibit their function could allow the development of therapeutic options. Here the authors describe a ‘small RNA zipper’ that sequesters miRNAs by forming a chain of DNA:RNA duplexes.