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Long non-coding RNAs (lncRNAs) may play a role in oxidative stress by altering the tumor microenvironment, thereby affecting pancreatic cancer progression. There is currently limited information on oxidative stress-related lncRNAs as novel prognostic markers of pancreatic cancer. Gene expression and clinical data of patients with pancreatic cancer were downloaded from The Cancer Genome Atlas (TCGA-PAAD) and the International Cancer Genome Consortium (ICGC-PACA) database. A weighted gene co-expression network analysis (WGCNA) was constructed to identify genes that were differentially expressed between normal and tumor samples. Based on the TCGA-PAAD cohort, a prediction model was established using lasso regression and Cox regression. The TCGA-PAAD and ICGC-PACA cohorts were used for internal and external validation, respectively. Furthermore, a nomogram based on clinical characteristics was used to predict mortality of patients. Differences in mutational status and tumor-infiltrating immune cells between risk subgroups were also explored and model-based lncRNAs were analyzed for potential immune-related therapeutic drugs. A prediction model for 6-lncRNA was established using lasso regression and Cox regression. Kaplan–Meier survival curves and receiver operating characteristic (ROC) curves indicated that patients with lower risk scores had a better prognosis. Combined with Cox regression analysis of clinical features, risk score was an independent factor predicting overall survival of patients with pancreatic cancer in both the TCGA-PAAD and ICGC-PACA cohorts. Mutation status and immune-related analysis indicated that the high-risk group had a significantly higher gene mutation rate and a higher possibility of immune escape, respectively. Furthermore, the model genes showed a strong correlation with immune-related therapeutic drugs. A pancreatic cancer prediction model based on oxidative stress-related lncRNA was established, which may be used as a biomarker related to the prognosis of pancreatic cancer to evaluate the prognosis of pancreatic cancer patients.

N(6)-methyladenosine (m6A)-modified microRNAs (miRNAs) are relevant to cancer progression. Also, although the involvement of miR-380-3p in regulating cancer progression in bladder cancer and neuroblastoma has been preliminarily explored, its role in other types of cancer, such as pancreatic cancer (PC), has not been studied. Thus, this study aimed to investigate the role of miR-380-3p in regulating PC progression. Here, through performing Real-Time qPCR, we evidenced that miR-380-3p was significantly upregulated in the clinical pancreatic cancer tissues and cells compared to their normal counterparts. Interestingly, miR-380-3p was enriched with m6A modifications, and elimination of m6A modifications by deleting METTL3 and METTL14 synergistically suppressed miR-380-3p expressions in PC cells. Next, the gain and loss-of-function experiments verified that knockdown of miR-380-3p suppressed cell proliferation, epithelial-mesenchymal transition (EMT), and tumorigenesis in PC cells

A major tool for curtailing the spread of COVID-19 pandemic in China was a nationwide lockdown, which led to significant reductions in anthropogenic emissions and fine particulate matter (PM2.5). However, the lockdown measures did not prevent high PM2.5 pollution episodes (EPs). Three severe EPs were identified in the Beijing-Tianjin-Hebei (BTH) region during the lockdown. The integrated process rate (IPR) analysis tool in the Community Multiscale Air Quality (CMAQ) model was employed to quantify the contributions of individual atmospheric processes to PM2.5 formation during the lockdown in the BTH region. The IPR results showed that emissions and aerosol processes were the dominant sources of net surface PM2.5 in Beijing and Tianjin, constituting a total of 86.2% and 92.9%, respectively, while emissions, horizontal transport, and aerosol processes dominated the net surface PM2.5 in Shijiazhuang and Baoding. In addition, the EPs in Beijing and Tianjin were primarily driven by local emissions, while the EPs in Shijiazhuang and Baoding were attributed to combined local emissions and regional transport. The reductions in PM2.5 in Case 2 relative to Case 1 were attributed to the weaker PM2.5 formation from emissions and aerosol processes. However, the EPs were enhanced by low planetary boundary layer heights, low vertical export of PM2.5 from the boundary layer to the free troposphere, and substantial horizontal import, especially in Shijiazhuang and Baoding. This study improves the understanding of buildup of PM2.5 during the EPs, and the results provide insights for designing more effective emissions control strategies to mitigate future PM2.5 episodes.

Background: Long non-coding RNAs (lncRNAs) may play a role in oxidative stress by altering the tumor microenvironment, thereby affecting pancreatic cancer progression. There is currently limited information on oxidative stress-related lncRNAs as novel prognostic markers of pancreatic cancer. Materials and Methods: Gene expression and clinical data of patients with pancreatic cancer were downloaded from The Cancer Genome Atlas (TCGA-PAAD) and the International Cancer Genome Consortium (ICGC-PACA) database. A weighted gene co-expression network analysis (WGCNA) was constructed to identify genes that were differentially expressed between normal and tumor samples. Based on the TCGA-PAAD cohort, a prediction model was established using lasso regression and Cox regression. The TCGA-PAAD and ICGC-PACA cohorts were used for internal and external validation, respectively. Furthermore, a nomogram based on clinical characteristics was used to predict mortality of patients. Differences in mutational status and tumor-infiltrating immune cells between risk subgroups were also explored and model-based lncRNAs were analyzed for potential immune-related therapeutic drugs. Results: A prediction model for 6-lncRNA was established using lasso regression and Cox regression. Kaplan–Meier survival curves and receiver operating characteristic (ROC) curves indicated that patients with lower risk scores had a better prognosis. Combined with Cox regression analysis of clinical features, risk score was an independent factor predicting overall survival of patients with pancreatic cancer in both the TCGA-PAAD and ICGC-PACA cohorts. Mutation status and immune-related analysis indicated that the high-risk group had a significantly higher gene mutation rate and a higher possibility of immune escape, respectively. Furthermore, the model genes showed a strong correlation with immune-related therapeutic drugs. Conclusion: Based on oxidative stress-related lncRNAs, this study demonstrated that using WGCNA to identify prognosis-related genes and combining Cox and lasso regression analysis facilitated the establishment of a new signature that may more accurately and effectively predict the prognosis of patients with pancreatic cancer.

The change detection of urban buildings is currently a hotspot in the research area of remote sensing, which plays a vital role in urban planning, disaster assessments and surface dynamic monitoring. SAR images have unique characteristics compared with traditional optical images, mainly including abundant image information and large data volume. However, the majority of currently used SAR images for the detection of changes in buildings have the problems of missing the detection of small buildings and poor edge segmentation. Therefore, this paper proposes a new approach based on deep learning for changing building detection, which we called CD-TransUNet. It should be noted that CD-TransUNet is an end-to-end encoding–decoding hybrid Transformer model that combines the UNet and Transformer. Additionally, to enhance the precision of feature extraction and to reduce the computational complexity, the CD-TransUNet integrates coordinate attention (CA), atrous spatial pyramid pooling (ASPP) and depthwise separable convolution (DSC). In addition, by sending the differential images to the input layer, the CD-TransUNet can focus more on building changes over a large scale while ignoring the changes in other land types. At last, we verify the effectiveness of the proposed method using a pair of ALOS-2(L-band) acquisitions, and the comparative experimental results obtained from other baseline models show that the precision of the CD-TransUNet is much higher and the Kappa value can reach 0.795. Furthermore, the low missed alarms and the accurate building edge reflect that the proposed method is more appropriate for building changing detection tasks.

Background Hepatocellular carcinoma (HCC) remains one of the most common human cancers, the death cases induced by HCC are increasing these years. Endoplasmic reticulum stress (ERS) occurs when misfolded proteins can't be disposed properly. It’s reported that ERS plays a crucial role in the pathogenesis of human malignant tumors. Results In our study, we established an ERS-related gene signature to predict the overall survival (OS) of HCC patients. The TCGA-LIHC cohort was used as train set while the ICGC-LIRI-JP cohort was used as validation set. A 9-genes ERS-related signature was constructed and the Riskscore was calculated according to it. The results of receiver operating characteristic curve (ROC) showed that the area under the curve (AUC) were 0.784 at 1 year, 0.780 at 2 years, 0.793 at 3 years in train set, this index in validation set were 0.694 at 1 year, 0.622 at 2 years, 0.613 at 3 years respectively. The cases in train set were grouped into high-risk group and low risk group based on the median value of Riskscore. The analysis of immune status revealed an immunosuppressive microenvironment in the high-risk group. The analysis of tumor mutation burden (TMB) and copy number variants (CNV) analysis revealed that the high-risk group patients had a higher genomic mutation frequency in low-risk group had a better prognosis than the high-risk group patients. In Univariate Cox regression analysis, the hazard ratio of Riskscore to the OS was 2.718 (95% CI: 2.173–3.399). In Multivariate Cox regression analysis, the hazard ratio of Riskscore was 2.422 (95% CI:1.805–3.25). At last, we established a nomogram according to the Riskscore and Eastern Cooperative Oncology Group (ECOG) performance status. The AUCs of the nomogram were 0.851 at 1 year, 0.860 at 2 years, 0.866 at 3 years. Conclusion In our study, a novel ERS-related gene signature was constructed to forecast the overall survival of HCC patients. This study maybe provide a new understanding of the tumorigenesis and new therapeutic targets for HCC.

Nitrate (NO3−) has been the dominant and the least reduced chemical component of fine particulate matter (PM2.5) since the stringent emission controls implemented in China in 2013. The formation pathways of NO3− vary seasonally and differ substantially in daytime vs. nighttime. They are affected by precursor emissions, atmospheric oxidation capacity, and meteorological conditions. Understanding NO3− formation pathways provides insights for the design of effective emission control strategies to mitigate NO3− pollution. In this study, the Community Multiscale Air Quality (CMAQ) model was applied to investigate the impact of regional transport, predominant physical processes, and different formation pathways to NO3− and total nitrate (TNO3, i.e., HNO3+ NO3−) production in the Yangtze River Delta (YRD) region during the four seasons of 2017. NO3-/PM2.5 and NO3-/TNO3 are the highest in the winter, reaching 21 % and 94 %, respectively. The adjusted gas ratio (adjGR = ([NH3]+ [NO3−])/([HNO3]+ [NO3−])) in the YRD is generally greater than 2 in the four seasons across most areas in the YRD, indicating that YRD is mostly in the NH3-rich regime and that NO3− is limited by HNO3 formation. Local emissions and regional transportation contribute to NO3− concentrations throughout the YRD region by 50 %–62 % and 38 %–50 %, respectively. The majority of the regional transport of NO3− concentrations is contributed by indirect transport (i.e., NO3− formed by transported precursors reacting with local precursors). Aerosol (AERO, including condensation, coagulation, new particle formation, and aerosol growth) processes are the dominant source of NO3− formation. In summer, NO3− formation is dominated by AERO and total transport (TRAN, sum of horizontal and vertical transport) processes. The OH + NO2 pathway contributes to 60 %–83 % of the TNO3 production, and the N2O5 heterogeneous (HET N2O5) pathway contributes to 10 %–36 % in the YRD region. HET N2O5 contribution becomes more important in cold seasons than warm seasons. Within the planetary boundary layer in Shanghai, the TNO3 production is dominated by the OH + NO2 pathway during the day (98 %) in the summer and spring and by the HET N2O5 pathway during the night (61 %) in the winter. Local contributions dominate the OH + NO2 pathway for TNO3 production during the day, while indirect transport dominates the HET N2O5 pathway at night.

During the COVID-19 lockdown period (from January 23 to February 29, 2020), ambient PM2.5 concentrations in the Yangtze River Delta (YRD) region were observed to be much lower, while the maximum daily 8 h average (MDA8) O3 concentrations became much higher compared to those before the lockdown (from January 1 to 22, 2020). Here, we show that emission reduction is the major driving force for the PM2.5 change, contributing to a PM2.5 decrease by 37% to 55% in the four YRD major cities (i.e., Shanghai, Hangzhou, Nanjing, and Hefei), but the MDA8 O3 increase is driven by both emission reduction (29%–52%) and variation in meteorological conditions (17%– 49%). Among all pollutants, reduction in emissions mainly of primary PM contributes to a PM2.5 decrease by 28% to 46%, and NOx emission reduction contributes 7% to 10%. Although NOx emission reduction dominates the MDA8 O3 increase (38%–59%), volatile organic compounds (VOCs) emission reduction lead to a 5% to 9% MDA8 O3 decrease. Increased O3 promotes secondary aerosol formation and partially offsets the decrease of PM2.5 caused by the primary PM emission reductions. The results demonstrate that more coordinated air pollution control strategies are needed in YRD.

A light-promoted Ni-catalyzed cyanation of aryl halides employing 1,4-dicyanobenzene as a cyanating agent is reported. A broad array of aryl bromides, chlorides, and druglike molecules could be converted into their corresponding nitriles (65 examples). Mechanistic studies suggest that upon irradiation, the oxidative addition product Ni(II)(dtbbpy)(

Reliable emission estimate of non-methane volatile organic compounds (NMVOCs) is important for understanding the atmospheric chemistry and formulating control policy of ozone (O

The atmospheric oxidizing capacity (AOC), reflecting the self-cleansing capacity of the atmosphere, plays an important role in the chemical evolution of secondary fine particulate matter (PM

Epidemiological studies have shown that fine particulate matter (PM2.5) has adverse impacts on human health. However, limited studies have investigated the effects of short-term exposure to PM2.5 and its constituents on mortality in China. This study used the generalized linear model (GLM) to investigate the effects of PM2.5 and its constituents, including organic carbon (OC), element carbon (EC), ammonium (NH4+), nitrate (NO3−), sulfate (SO42−), on different causes of mortality in Shanghai from January 1, 2013 to December 31, 2015. The single-day lagged model and the moving average lagged model were used to examine the lagging effects of pollutants on mortality. At lag0 day, PM2.5 had a significant effect on all-cause mortality, and a 10 μg/m3 increase leads to 0.68% increase in all-cause mortality (RR 1.0068, 95%CI 1.0013–1.0123). Among the five constituents, EC had the greatest impact on all-cause mortality in Shanghai, with 10.48% increase of mortality (RR 1.1048, 95%CI 1.0266–1.1891) per 10 μg/m3 increase of concentrations, followed by OC (RR 1.0577, 95%CI 1.0277–1.0886), NH4+ (RR 1.0272, 95%CI 1.0028–1.0522) and SO42− (RR 1.0104, 95%CI 1.0003–1.0206). For respiratory diseases mortality, EC, OC, NO3− and NH4+ had significant impacts and caused an increase of mortality by 44.99% (RR 1.4499, 95%CI 1.1813–1.7794), 10.40% (RR 1.1040, 95%CI 1.0260–1.1880), 5.338% (RR 1.0533, 95%CI 1.0097–1.0989) and 7.34% (RR 1.0734, 95%CI 1.0015–1.1505) per 10 μg/m3 increase of concentrations, respectively. The cumulative effect of PM2.5 on mortality was significant in Shanghai. Except for SO42−, the RR value of the single-day lagged model was smaller than the moving average lagged model.

The North China Plain and the Yangtze River Delta are the two of the most heavily polluted regions in China. Observational studies revealed that ‘explosive’ PM2.5 mass concentration growths frequently occurred in the two regions. This study analyzed all the PM2.5 mass concentration growth processes from clean condition (i.e., 150 μg m−3) in Beijing (BJ) and Shanghai (SH), two representative cities of the two regions, using hourly monitored PM2.5 concentrations during 2013–2016. 173 and 76 growth processes were identified in BJ and SH, respectively. PM2.5 rising rates (PMRR) and dynamic growth durations were calculated to illustrate the characteristics of the growth processes. Hourly particulate chemical composition data and meteorological data in BJ and SH were further analyzed. The 4-year averaged PMRR of PM2.5 total mass were similarly of 7.11 ± 9.82 μg m−3 h−1 in BJ and 6.71 ± 6.89 μg m−3 h−1 in SH. A decreasing trend was found for the PM2.5 growth processes in two cities from 2013 to 2016, reflecting the effectiveness of emission controls implemented in the past years. The contributions of particulate components to the PM2.5 total mass growth were different in BJ and SH. Average PMRR value of PM1 organic aerosols (OA), SO42−, NO3−, and NH4+ in BJ was 1.90, 0.95, 0.82, and 0.53 μg m−3 h−1, respectively. Average PMRR of PM2.5 OA, SO42−, NO3−, and NH4+ in SH was 1.70, 1.18, 1.99 and 1.14 μg m−3 h−1, respectively. Based on the contributions of different components, the PM2.5 mass concentration growth processes in BJ and SH were proposed to be classified into ‘other components-dominant growth processes’, ‘all components-contributing growth processes’, ‘one or more explosive secondary components-dominant growth processes’, and ‘mixed-factor growth processes’. Potential source contribution function analysis and the meteorological condition analysis showed that source origins and prevailing wind for the two cities during different categories of growth processes had substantial difference. The important source areas included Hebei and Shandong for BJ, and Jiangsu and Anhui for SH. The dominant wind directions during growth processes were northeast, south and southwest in BJ, and were west to north in SH. The results suggested the contributing components, the prevailing wind conditions, and the formation processes were substantially different in the two cities, despite the similar PMRR of PM2.5 total mass during the growth processes between BJ and SH. Future research is needed to study the detailed formation mechanisms of the different PM2.5 mass concentration growth processes in the two cities.

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM

Taking Jinjiang Wudian City Tourism Cultural and Creative Industrial Park as the research object, we use the case study method to explore the intelligent management system design scheme of the tourism cultural and creative industrial park, and through field interviews, data collection, data coding and result analysis, we deeply analyze the tourism cultural and creative industrial park in Jinjiang Wudian City. Through the methods of field interviews, data collection, coding and result analysis, we analyze the management subjects and components of the management mode of Wudian City Tourism and Creative Industry Park in Jinjiang and identify its existing management mode. On this basis, it embeds technical elements of wisdom tourism, subdivides wisdom management composition modules of tourism cultural and creative industrial park, and finally forms a complete wisdom tourism management system of tourism cultural and creative industrial park.

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM2.5) and ozone (O3) has important scientific significance and provides valuable information for future emission control strategies. Exposure data are particularly vital but may cause great uncertainty in health burden assessments. This study, for the first time, used six methods to generate the concentration data of PM2.5 and O3 in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM2.5 and O3 using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM2.5-related premature mortality in China decreases by 263 (95% confidence interval (CI95): 142-159) to 308 (CI95: 213-241) thousands from 2014 to 2018 by using different concentration data, while O3-related premature mortality increases by 67 (CI95: 26-104) to 103 (CI95: 40-163) thousands. The estimated mean changes are up to 40% different for the PM2.5-related mortality, and up to 30% for the O3-related mortality if different exposure data are chosen. The most significant difference due to the exposure data is found in the areas with a population density of around 103 people/km2, mostly located in Central China, for both PM2.5 and O3. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.

PM2.5 and O3 controls are traditionally considered separately because PM2.5 is usually high in winter while O3 is generally high in summer. In this study, we explore the opportunity of controlling the two pollutants simultaneously through a better understanding of their intra-seasonal correlation and chemical-coupling behaviors under different meteorological conditions during the late summer and early fall (August–September) episodes in the San Joaquin Valley (SJV), California. A correlation analysis is first used to identify the temporal correlations between O3 and PM2.5 and their underlying physical and chemical drivers. Sensitivity analysis is then applied to determine the chemical coupling between PM2.5 and O3 and subsequent multipollutant control opportunities under two contrasting meteorological conditions using the Community Multi-Scale Air Quality (CMAQ) model. We find that O3 and PM2.5 are positively correlated on the daily timescale because both are sensitive to atmospheric stagnation. However, O3 and PM2.5 are negatively correlated on the hourly timescale determined by the negative correlation between hourly NO3− and O3, which is mainly due to the opposite effects of T and RH on the diurnal variations of NO3− and O3. Reducing NOx on average lead to O3 increase, but it can facilitate reducing O3 at higher O3 (>75 ppb) locations under the more stagnant conditions. NOx emission control could become beneficial for both O3 and PM2.5 when the NOx emissions in 2005 are further reduced by 15% under the more stagnant meteorological conditions and by 30% under the more ventilated meteorological conditions.

China has been suffering serious particulate matter (PM) pollution in recent decades. Local emission and regional transport both contribute to PM pollution. Determining the contributions of local emissions vs. regional transport to PM concentrations is crucial in making effective PM control policies. This paper reviews the recent research on the contributions of regional transport to PM pollution in four regions in China, i.e., the northern China, eastern China, southern China, and the western China, respectively. The major findings include (1) HYSPLIT is the most popular methods in studies in all regions and often is used in combination with the CA, PSCF, and CWT techniques to investigate the transport pathways and source origins; (2) during the relatively polluted period, transport contributes over 50% of the PM concentrations in Beijing, Shanghai, Hangzhou, Guangzhou, Hong Kong, and Chengdu. Regional transport is important for PM pollution in major cities of China; and (3) regional transport exhibits clear seasonal variations and long term trends. The findings have important implication for emission control programs in these regions.

// Xing Chen 1 , Geng Liu 1 , Kaiqiang Wang 1 , Guodong Chen 1 and Jinjin Sun 1 1 Department of Hepatopancreatobiliary Surgery, The Second Hospital of Tianjin Medical University, Tianjin, China Correspondence to: Jinjin Sun, email: jsun02@tmu.edu.cn Keywords: LAPC, neoadjuvant radiation, resection, CSS, SEER Received: February 24, 2017 Accepted: April 07, 2017 Published: May 23, 2017 ABSTRACT Background and aim: To compare cancer-specific survival (CSS) between patients who received neoadjuvant radiation followed by resection (NRR) and those who received upfront resection (UR) for locally advanced pancreatic cancer (LAPC). Methods: A total of 772 LAPC patients who underwent curative-intent surgical resection with or without neoadjuvant radiation from 2004 to 2013 were identified from the Surveillance, Epidemiology, and End Result (SEER) database. Propensity score matching (PSM) was conducted to eliminate possible bias. Kaplan-Meier method was used to analyze long-term outcome. Independent risk factors of CSS were predicted by Cox proportional hazards model. Subgroup analyses were done according to 5 variables. Results: The propensity score model matched 196 patients from the whole cohort. Neoadjuvant radiation was an independent predictor of CSS no matter before or after PSM. After PSM, the 1-, 3-, 5-year CSS rates of NRR group were 82.7%, 39.2% and 17.1%, while 64.3%, 19.9% and 12.4% for UR group. The median CSS for NRR group was 25 months, while 17 months for UR group. In subgroup analyses, CSS rates or median CSS of NRR group were still superior to those of UR group in married, unmarried, pancreatic adenocarcinoma, G1+G2, G3+G4, N0 stage, N1 stage and M0 stage subgroups, but no differences were found in other histological types and M1 stage subgroups. Other predictors of CSS included histological type, tumor grade and marital status. Conclusions: Neoadjuvant radiation followed by resection has a significant survival benefit compared with upfront resection in LAPC patients. Therapeutic strategy for LAPC patients should be further explored.

Epidemiological studies have shown that fine particulate matter (PM

Star-branched amphiphilic copolymer nanocarriers with high-density zwitterionic shell show great promise in drug delivery due to their controllable small size and excellent anti-biofouling properties. This gives the hydrophobic cargo with high stability and long blood circulation in vivo . In the present study, star-branched polylactic acid and poly(2-methacryloyloxyethyl phosphorylcholine) copolymers with (AB 3 ) 3 –type architecture (PLA- b -PMPC 3 ) 3 were conceived as drug vectors, and the copolymers were synthesized by an “arm-first” approach via the combination of ring opening polymerization (ROP), atom transfer radical polymerization (ATRP) and the click reaction. The self-assembled star-branched copolymer micelles (sCPM) had an average diameter of about 64.5 nm and exhibited an ultra-hydrophilic surface with an ultralow water contact angle of about 12.7°, which efficiently suppressed the adhesion of serum proteins. In vivo experiments showed that the sCPM loading strongly enhanced the blood circulation time of DiI and the plasma half-life of DiI in sCPM was 19.3 h. The relative accumulation concentration in tumor of DiI delivered by sCPM was 2.37-fold higher than that of PLA-PEG, at 4 h after intravenous injection. These results demonstrated that the star-branched copolymer (PLA- b -PMPC 3 ) 3 is a promising alternative carrier material for intravenous delivery versus classic PEG-modified strategies.

Exosomes are a class of naturally occurring nanoparticles that are secreted endogenously by mammalian cells. Clinical applications for exosomes remain a challenge because of their unsuitable donors, low scalability, and insufficient targeting ability. In this study, we developed a dual-functional exosome-based superparamagnetic nanoparticle cluster as a targeted drug delivery vehicle for cancer therapy. The resulting exosome-based drug delivery vehicle exhibits superparamagnetic behavior at room temperature, with a stronger response to an external magnetic field than individual superparamagnetic nanoparticles. These properties enable exosomes to be separated from the blood and to target diseased cells. In vivo studies using murine hepatoma 22 subcutaneous cancer cells showed that drug-loaded exosome-based vehicle delivery enhanced cancer targeting under an external magnetic field and suppressed tumor growth. Our developments overcome major barriers to the utility of exosomes for cancer application.

As contamination is one of important factors to Panax notoginseng quality and safety. Saponin is one of important compounds with the medicinal values of P. notoginseng. The impact of soil As on production of saponin of P. notoginseng knew very little. This study was performed to determine content and heterogeneity of saponins from P. notoginseng and its mechanisms upon treatments with different concentration levels of As in soil. Plants of P. notoginseng were treated with arsenic [As (V)] at 0, 20, 80, 140, 20 and 260 mg/kg concentration levels which were supplied as sodium arsenate (Na3AsO4). These experimental plants were grown in shade condition in a greenhouse. Plants were harvested at vigorous vegetative growth and fruit ripening stages, separately. Effects of As treatments on saponin content, and heterogeneity of monomers in the mixtures of notoginesenosides and ginsenosides, enzymatic activity and gene expression level of squalene synthetase were determined for rhizome and main root tissues. Results show that：(1) Of all the As treatments from the lowest to the highest concentration levels, the As content in both rhizome and main roots from As-treated plants was within the standard level for superior products derived from P. notoginseng. The content of notoginsenosides from all tissues except the main roots at fruit ripening stage, was 5% higher than the standard level specified in the Chinese Pharmacopoeia; (2) The treatment of As at 20 mg/kg led to an 3.5% - 183.9% increases in total notoginesenosides content in rhizome and main roots, respectively. Treatments with the highest As concentration at 260 mg/kg resulted in a significant decline in total notoginsenosides content, and lower enzymatic activity and gene expression levels of squalene synthetase; (3) Under As treatment conditions, the ratio of Rb1/Rg1 decreased but the ratio of (Rb1 + Rg1)/R1 increased in both rhizomes and main roots. Conclusively, this study demonstrated that low As concentration (20 - 80 mg/kg) treatments resulted in higher notoginsenoside content in P. notoginseng. However, treatments with high As concentrations had an adverse effect. The repression in the synthesis of notoginsenoside and interruption of the conversion process from propanaxadiol into propanaxatriol are responsible for more heterogeneous monomer mixtures and low notoginsenoside content. For plants treated with the highest As concentration of 260 mg/kg, both gene expression and enzymatic activities of squalene synthetase were greatly repressed thus leading to a significantly low saponin content in rhizome and main root tissues.

With the increase of data quantity, people have begun to attach importance to cloud storage, however, traditional single cloud can’t ensure the privacy of users’ data to a certain extent. To solve the security issue, we present a multi-cloud storage system called CloudS which spreads data over multiple cloud storage servers by using a new kind of XOR-based non-systematic erasure codes - Privacy Protecting Codes (PPC). For better user experiences and tradeoffs between security and performance, CloudS provides multiple levels of security by a variety of combinations of compression, encryption and coding schemes. In addition, we also put forward a novel Parallel Cyclic Encryption (PCE) scheme to achieve random secret key protection which attains high security and performance. We implement CloudS as a web application which doesn’t require users to perform complicated operations on local.

The North China Plain and the Yangtze River Delta are the two of the most heavily polluted regions in China. Observational studies revealed that 'explosive' PM

A kind of graphene foam chemical sensor (GFCS) system based on the principal component analysis (PCA) and backpropagation neural network (BPNN) was presented in this paper. Compared with conventional chemical sensors, the GFCS could discriminate various chemical molecules with selectivity without surface modification. The GFCS system consisted of an unmodified graphene foam chemical sensor, an electrical resistance time domain detection system (ERTDS), and a pattern recognition module. The GFCS has been validated via several chemical molecules discrimination including chloroform, acetone, and ether. The experimental results showed that the discrimination accuracy for each molecule exceeded 97% and a single measurement can be achieved in ten minutes. This work may have presented a new strategy for research and application for graphene chemical sensors.

OBJECTIVE To explore the role of hypoxic inducible factor-1α (HIF-1 α ) in the proliferation and apoptosis of pancreatic cancer cells under hypoxic conditions. METHODS A cassette encoding small interference RNA (siRNA) targeting HIF-1 α mediated by recombinant adeno-associated virus (rAAV) was constructed, giving rAAV-siHIF. rAAV-siHIF or rAAV-hrGFP was transfected into exponentially growing MiaPaCa2 cells under hypoxic conditions. Then, the expression of HIF-1α mRNA and protein, the proliferation and apoptosis of MiaPaCa2 cells were examined, using real-time PCR, Western Blot, MTT and TUNEL, respectively. RESULTS Under hypoxic conditions, rAAV-siHIF inhibited the expression of HIF-1 α mRNA and protein in MiaPaCa2 cells. At the same time, rAAV-siHIF decreased MiaPaCa2 cell proliferation and induced apoptosis. However, rAAV-hrGFP had no effect on the expression of HIF-1 α as well as the proliferation and apoptosis of MiaPaCa2 cells under hypoxic conditions. CONCLUSION Under hypoxic conditions, HIF-1α plays a key role in the proliferation of MiaPaCa2 cells, and inhibition of HIF-1α expression can lead to MiaPaCa2 cell apoptosis.

With the increase of data quantity, people have begun to attach importance to cloud storage, however, traditional single cloud can’t ensure the privacy of users’ data to a certain extent. To solve the security issue, we present a multi-cloud storage system called CloudS which spreads data over multiple cloud storage servers by using a new kind of XOR-based non-systematic erasure codes - Privacy Protecting Codes (PPC). For better user experiences and tradeoffs between security and performance, CloudS provides multiple levels of security by a variety of combinations of compression, encryption and coding schemes. In addition, we also put forward a novel Parallel Cyclic Encryption (PCE) scheme to achieve random secret key protection which attains high security and performance. We implement CloudS as a web application which doesn’t require users to perform complicated operations on local.

There is small, scattered, weakness and other issues in China’s large-scale airport development process. Refer to this, based on analysis of China’s current airport traffic status and functional position, research of the current collection and distribution profile of the international large hub airport’s ground transportation, ground traffic organization mode. Learned from its advanced experience, this paper proposes a development model suitable for China’s large-scale airport, which is a future direction of China’s large-scale airport’s development that should be combining railway transportation, ground public transportation, airport transportation and urban outbound traffic together as one comprehensive transport hub.

In this information era, we are facing the knowledge explosion, and the information on the Internet is multifarious. It is not convenient enough for us to access to information directly on cell phones due to their limitation. Based on parsing a web page with regarding it as a DOM (document object model) tree, we extract the valuable information with considering three factors: structure, content, and programming habits. For illustration, 28 websites are utilized to show the feasibility of the method in web information extraction, and we design the mobile client to present the web content on the cell phones. The practice has proved that using the web page extraction technology related to this article to browse the corresponding news websites only consumed 8 % of cell phone traffic of the existing mobile phone browser. And the user experience is improved. This method can help people to get rid of costing too much on the cell phone traffic, redundant information, complicated operations, and so on.

In the filamentous fungus Aspergillus nidulans, both microtubules and actin filaments are important for polarized growth at the hyphal tip. Less clear is how different microtubule-based and actin-based motors work together to support this growth. Here we examined the role of myosin-V (MYOV) in hyphal growth. MYOV-depleted cells form elongated hyphae, but the rate of hyphal elongation is significantly reduced. In addition, although wild type cells without microtubules still undergo polarized growth, microtubule disassembly abolishes polarized growth in MYOV-depleted cells. Thus, MYOV is essential for polarized growth in the absence of microtubules. Moreover, while a triple kinesin null mutant lacking kinesin-1 (KINA) and two kinesin-3s (UNCA and UNCB) undergoes hyphal elongation and forms a colony, depleting MYOV in this triple mutant results in lethality due to a severe defect in polarized growth. These results argue that MYOV, through its ability to transport secretory cargo, can support a significant amount of polarized hyphal tip growth in the absence of any microtubule-based transport. Finally, our genetic analyses also indicate that KINA (kinesin-1) rather than UNCA (kinesin-3) is the major kinesin motor that supports polarized growth in the absence of MYOV.