The Magnaporthe oryzae effector Avr-PikD suppresses rice immunity by inhibiting an LSD1-like transcriptional activator

Avirulence effectors(Avrs),encoded by plant pathogens,can be recognized by plants harboring the corresponding resistance proteins,thereby initiating effector-triggered immunity(ETI).In susceptible plants,however,Avrs can function as effectors,facilitating infection via effector-triggered susceptibility(ETS).Mechanisms of Avr-mediated ETS remain largely unexplored.Here we report that the Magnaporthe oryzae effector Avr-PikD enters rice cells via the canonical cytoplasmic secretion pathway and suppresses rice basal defense.Avr-PikD interacts with an LSD1-like transcriptional activator AKIP30 of rice,and AKIP30 is also a positive regulator of rice immunity,whereas Avr-PikD impedes its nuclear localization and suppresses its transcriptional activity.In summary,M.oryzae delivers Avr-PikD into rice cells to facilitate ETS by inhibiting AKIP30-mediated transcriptional regulation of immune response against M.oryzae.

Effects of interleukin-10 treated macrophages on bone marrow mesenchymal stem cells via signal transducer and activator of transcription 3 pathway

BACKGROUND Alveolar bone defects caused by inflammation are an urgent issue in oral implant surgery that must be solved.Regulating the various phenotypes of macrophages to enhance the inflammatory environment can significantly affect the progression of diseases and tissue engineering repair process.AIM To assess the influence of interleukin-10(IL-10)on the osteogenic differentiation of bone marrow mesenchymal stem cells(BMSCs)following their interaction with macrophages in an inflammatory environment.METHODS IL-10 modulates the differentiation of peritoneal macrophages in Wistar rats in an inflammatory environment.In this study,we investigated its impact on the proliferation,migration,and osteogenesis of BMSCs.The expression levels of signal transducer and activator of transcription 3(STAT3)and its activated form,phos-phorylated-STAT3,were examined in IL-10-stimulated macrophages.Subsequently,a specific STAT3 signaling inhibitor was used to impede STAT3 signal activation to further investigate the role of STAT3 signaling.RESULTS IL-10-stimulated macrophages underwent polarization to the M2 type through substitution,and these M2 macrophages actively facilitated the osteogenic differentiation of BMSCs.Mechanistically,STAT3 signaling plays a crucial role in the process by which IL-10 influences macrophages.Specifically,IL-10 stimulated the activation of the STAT3 signaling pathway and reduced the macrophage inflammatory response,as evidenced by its diminished impact on the osteogenic differentiation of BMSCs.CONCLUSION Stimulating macrophages with IL-10 proved effective in improving the inflammatory environment and promoting the osteogenic differentiation of BMSCs.The IL-10/STAT3 signaling pathway has emerged as a key regulator in the macrophage-mediated control of BMSCs’osteogenic differentiation.

TransTM:A device-free method based on time-streaming multiscale transformer for human activity recognition

RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy protection.Existing RFID-based HAR methods use modeling,CNN,or LSTM to extract features effectively.Still,they have shortcomings:1)requiring complex hand-crafted data cleaning processes and 2)only addressing single-person activity recognition based on specific RF signals.To solve these problems,this paper proposes a novel device-free method based on Time-streaming Multiscale Transformer called TransTM.This model leverages the Transformer's powerful data fitting capabilities to take raw RFID RSSI data as input without pre-processing.Concretely,we propose a multiscale convolutional hybrid Transformer to capture behavioral features that recognizes singlehuman activities and human-to-human interactions.Compared with existing CNN-and LSTM-based methods,the Transformer-based method has more data fitting power,generalization,and scalability.Furthermore,using RF signals,our method achieves an excellent classification effect on human behaviorbased classification tasks.Experimental results on the actual RFID datasets show that this model achieves a high average recognition accuracy(99.1%).The dataset we collected for detecting RFID-based indoor human activities will be published.

Responses of runoff to changes in climate and human activities in the Liuhe River Basin, China

Since the 1950s,numerous soil and water conservation measures have been implemented to control severe soil erosion in the Liuhe River Basin(LRB),China.While these measures have protected the upstream soil and water ecological environment,they have led to a sharp reduction in the downstream flow and the deterioration of the river ecological environment.Therefore,it is important to evaluate the impact of soil and water conservation measures on hydrological processes to assess long-term runoff changes.Using the Soil and Water Assessment Tool(SWAT)models and sensitivity analyses based on the Budyko hypothesis,this study quantitatively evaluated the effects of climate change,direct water withdrawal,and soil and water conservation measures on runoff in the LRB during different periods,including different responses to runoff discharge,hydrological regime,and flood processes.The runoff series were divided into a baseline period(1956-1969)and two altered periods,i.e.,period 1(1970-1999)and period 2(2000-2020).Human activities were the main cause of the decrease in runoff during the altered periods,contributing 86.03%(-29.61 mm),while the contribution of climate change was only 13.70%(-4.70 mm).The impact of climate change manifests as a decrease in flood volume caused by a reduction in precipitation during the flood season.Analysis of two flood cases indicated a 66.00%-84.00%reduction in basin runoff capacity due to soil and water conservation measures in the upstream area.Soil and water conservation measures reduced the peak flow and total flood volume in the upstream runoff area by 77.98%and 55.16%,respectively,even with nearly double the precipitation.The runoff coefficient in the reservoir area without soil and water conservation measures was 4.0 times that in the conservation area.These results contribute to the re-evaluation of soil and water conservation hydrological effects and provide important guidance for water resource planning and water conservation policy formulation in the LRB.

Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners:A Recommendation System

Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases.Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not.Typically,smartphones and their associated sensing devices operate in distributed and unstable environments.Therefore,collecting their data and extracting useful information is a significant challenge.In this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical activities.Using the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical activities.This system is based on the calculation of calories burned by each user during physical activities.In this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical workouts.To identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional LSTM.Since human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information simultaneously.While Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal data.The results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and uncertainty.To overcome this constraint and improve performance(96%),we proposed to use the fusion mechanisms.The last combines deep learning classifiers tomodel non-accurate and ambiguous data to obtain synthetic information to aid in decision-making.The Voting and Dempster-Shafer(DS)approaches are employed.The results showed that fused classifiers based on DS theory outperformed individual classifiers(96%)with the highest accuracy level of 98%.Also,the findings disclosed that participants engaging in physical activities are healthy,showcasing a disparity in the distribution of physical activities between men and women.

Centennial Analysis of Human Activity Intensity and Associated Historical Events in Heilongjiang River Sino-Russo Watershed

Human activities in a transborder watershed are complex under the influence of domestic policies,international relations,and global events.Understanding the forces driving human activity change is important for the development of transborder watershed.In this study,we used global historical land cover data,the hemeroby index model,and synthesized major historical events to analyze how human activity intensity changed in the Heilongjiang River(Amur River in Russia)watershed(HLRW).The results showed that there was a strong spatial heterogeneity in the variation of human activity intensity in the HLRW over the past century(1900-2016).On the Chinese side,the human activity intensity change shifted from the plain areas for agricultural reclamation to the mountainous areas for timber extraction.On the Russian side,human activity intensity changes mostly concentrated along the Trans-Siberian Railway and the Baikal-Amur Mainline.Localized variation of human activity intensity tended to respond to regional events while regionalized variation tends to reflect national policy change or broad international events.The similarities and differences between China and Russia in policies and positions in international events resulted in synchronous and asynchronous changes in human activity intensity.Meanwhile,policy shifts were often confined by the natural features of the watershed.These results reveal the historical origins and fundamental connotations of watershed development and contribute to formulating regional management policies that coordinate population,eco-nomic,social,and environmental activities.

Coupling Analysis of Multiple Machine Learning Models for Human Activity Recognition

Artificial intelligence(AI)technology has become integral in the realm of medicine and healthcare,particularly in human activity recognition(HAR)applications such as fitness and rehabilitation tracking.This study introduces a robust coupling analysis framework that integrates four AI-enabled models,combining both machine learning(ML)and deep learning(DL)approaches to evaluate their effectiveness in HAR.The analytical dataset comprises 561 features sourced from the UCI-HAR database,forming the foundation for training the models.Additionally,the MHEALTH database is employed to replicate the modeling process for comparative purposes,while inclusion of the WISDM database,renowned for its challenging features,supports the framework’s resilience and adaptability.The ML-based models employ the methodologies including adaptive neuro-fuzzy inference system(ANFIS),support vector machine(SVM),and random forest(RF),for data training.In contrast,a DL-based model utilizes one-dimensional convolution neural network(1dCNN)to automate feature extraction.Furthermore,the recursive feature elimination(RFE)algorithm,which drives an ML-based estimator to eliminate low-participation features,helps identify the optimal features for enhancing model performance.The best accuracies of the ANFIS,SVM,RF,and 1dCNN models with meticulous featuring process achieve around 90%,96%,91%,and 93%,respectively.Comparative analysis using the MHEALTH dataset showcases the 1dCNN model’s remarkable perfect accuracy(100%),while the RF,SVM,and ANFIS models equipped with selected features achieve accuracies of 99.8%,99.7%,and 96.5%,respectively.Finally,when applied to the WISDM dataset,the DL-based and ML-based models attain accuracies of 91.4%and 87.3%,respectively,aligning with prior research findings.In conclusion,the proposed framework yields HAR models with commendable performance metrics,exhibiting its suitability for integration into the healthcare services system through AI-driven applications.

Impacts of climate change and human activities on vegetation dynamics on the Mongolian Plateau, East Asia from 2000 to 2023

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world.Under the impacts of climate change and human activities,desertification is becoming increasingly severe on the Mongolian Plateau.Understanding the vegetation dynamics in this region can better characterize its ecological changes.In this study,based on Moderate Resolution Imaging Spectroradiometer(MODIS)images,we calculated the kernel normalized difference vegetation index(kNDVI)on the Mongolian Plateau from 2000 to 2023,and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test.We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis,and quantified the effects of climate change and human activities on kNDVI change by residual analysis.The results showed that kNDVI on the Mongolian Plateau was increasing overall,and the vegetation recovery area in the southern region was significantly larger than that in the northern region.About 50.99%of the plateau showed dominant climate-driven effects of temperature,precipitation,and wind speed on kNDVI change.Residual analysis showed that climate change and human activities together contributed to 94.79%of the areas with vegetation improvement.Appropriate human activities promoted the recovery of local vegetation,and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau.This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Impacts of Human Activities and Season on Species Diversity and Abundance of Butterflies in Mpanga Kipengere Game Reserve and Surrounding Farmlands, Tanzania

Maintaining natural habitats is crucial for the preservation of insects and other species that indicate environmental changes. However, the Mpanga/Kipengere Game Reserve and its surrounding farmlands are facing disturbance due to human activities, which is putting many wildlife species, particularly larger mammals, at risk. To determine the impact of human activities on butterfly species diversity and abundance in the reserve and its surrounding areas, we conducted a study from November 2021 to October 2023. We collected butterfly data using transect walks and baited traps in two habitat types. Our study yielded 2799 butterfly Individuals ranging in 124 species divided into five families habitat, season, and anthropogenic factors are significant environmental variables influencing species diversity and abundance of butterflies. Therefore, it’s important to protect habitat and dry-season water for the conservation of invertebrates such as butterflies. Our study findings provide essential information for ecological monitoring and future assessment of the Mpanga/Kipengere Game Reserve ecosystem health.

Changes of coastline and tidal flat and its implication for ecological protection under human activities: Take China’s Bohai Bay as an example

The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.

A Novel Method for Cross-Subject Human Activity Recognition with Wearable Sensors

Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recognizing activities for specific users, which does not consider the individual differences among users and cannot adapt to new users. In order to improve the generalization ability of HAR model, this paper proposes a novel method that combines the theories in transfer learning and active learning to mitigate the cross-subject issue, so that it can enable lower limb exoskeleton robots being used in more complex scenarios. First, a neural network based on convolutional neural networks (CNN) is designed, which can extract temporal and spatial features from sensor signals collected from different parts of human body. It can recognize human activities with high accuracy after trained by labeled data. Second, in order to improve the cross-subject adaptation ability of the pre-trained model, we design a cross-subject HAR algorithm based on sparse interrogation and label propagation. Through leave-one-subject-out validation on two widely-used public datasets with existing methods, our method achieves average accuracies of 91.77% on DSAD and 80.97% on PAMAP2, respectively. The experimental results demonstrate the potential of implementing cross-subject HAR for lower limb exoskeleton robots.

Evaluating the Impacts of Human Activities on Diversity, Abundance, and Distribution of Large Mammals in Nimule National Park, South Sudan

Globally, human activities have a significant impact on the diversity, abundance, and distribution of large mammals in Protected Areas (PAs). These disturbances increase human pressure on biodiversity and species habitats, highlighting the need for conservation. This study aimed to assess the abundance and distribution of large mammals in different habitat types within Nimule National Park (NNP) and understand the impacts of human activities on them. Data on the abundance and distribution of large mammals and their respective habitat types were collected through line transect surveys. Human activity signs were observed and recorded along the transect lines. To estimate the impacts of human activities on the diversity, abundance, and distribution of large mammal species, as well as to identify any significant differences between them and their habitat types, the study utilized the Kruskal Wallis test, Polynomial multiple regressions, and diversity indices. The findings from the Shannon-Weiner and Simpson indices indicated that large mammal species were more diverse inside the park (H’ = 1.136;D = 0.570) compared to the buffer zone (H’ = 0.413;D = 0.171), with 85% (443 out of 510 samples) recorded within Nimule National Park. The species abundance showed a semi-balanced status (0.58). The diversity results among different habitat types revealed that large mammals were more diverse and highly distributed in both open woodlands (244) and dense woodlands (192), while riverine vegetation had the lowest diversity (8). Statistical tests demonstrated a highly significant difference at a 99% confidence interval (p-value = 0.01) between habitat types and identified species of large mammals. Additionally, the results highlighted the high abundance of Uganda kob (274), baboons (141), and warthog (57) across most habitat types, accounting for at least 75% of their distribution. The most prevalent human activities observed were cattle footprints (27%) and cattle dung (14%). Human footprints and tree cutting combined accounted for 9%, indicating the practice of livestock grazing, poaching, encroachment, and fuelwood collection by local communities. However, these activities did not appear to significantly impact the diversity, abundance, and distribution of large mammals in Nimule National Park. Therefore, it is crucial to foster shared responsibilities and engage relevant stakeholders in the management and conservation of large wildlife species. Regular community awareness programs should be implemented to cultivate a sense of ownership. Moreover, it is recommended that a comprehensive survey be conducted on the population status of all mammal species in Nimule National Park, including its surrounding Buffer Zone. Monitoring the impact of human activities on their behavior and habitats using satellite images should also be carried out at least every five to ten years.

Impact of climate change and human activities on the spatiotemporal dynamics of surface water area in Gansu Province, China

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas.This study took Gansu Province,China,a typical area with complex terrain and variable climate,as the research subject.Based on Google Earth Engine,we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022,and quantitatively analyzed the main causes of regional differences in surface water area.The findings revealed that surface water area in Gansu Province expanded by 406.88 km2 from 1985 to 2022.Seasonal surface water area exhibited significant fluctuations,while permanent surface water area showed a steady increase.Notably,terrestrial water storage exhibited a trend of first decreasing and then increasing,correlated with the dynamics of surface water area.Climate change and human activities jointly affected surface hydrological processes,with the impact of climate change being slightly higher than that of human activities.Spatially,climate change affected the'source'of surface water to a greater extent,while human activities tended to affect the'destination'of surface water.Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted.Therefore,we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water'supply-demand'balance strategies.The study not only sheds light on the dynamics of surface water area in Gansu Province,but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

Influence of Human Activity Intensity on Habitat Quality in Hainan Tropical Rainforest National Park,China

Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.

18β-glycyrrhetinic acid promotes gastric cancer cell autophagy and inhibits proliferation by regulating miR-328-3p/signal transducer and activator of transcription 3

BACKGROUND Gastric cancer(GC)is one of the most common cancer types worldwide,and its prevention and treatment methods have garnered much attention.As the active ingredient of licorice,18β-glycyrrhetinic acid(18β-GRA)has a variety of pharmacological effects.The aim of this study was to explore the effective target of 18β-GRA in the treatment of GC,in order to provide effective ideas for the clinical prevention and treatment of GC.AIM To investigate the mechanism of 18β-GRA in inhibiting cell proliferation and promoting autophagy flux in GC cells.METHODS Whole transcriptomic analyses were used to analyze and screen differentially expressed microRNAs(miRNAs)in GC cells after 18β-GRA intervention.Lentivirus-transfected GC cells and the Cell Counting Kit-8 were used to detect cell proliferation ability,cell colony formation ability was detected by the clone formation assay,and flow cytometry was used to detect the cell cycle and apoptosis.A nude mouse transplantation tumor model of GC cells was constructed to verify the effect of miR-328-3p overexpression on the tumorigenicity of GC cells.Tumor tissue morphology was observed by hematoxylin and eosin staining,and microtubule-associated protein light chain 3(LC3)expression was detected by immunohistochemistry.TransmiR,STRING,and miRWalk databases were used to predict the relationship between miR-328-3p and signal transducer and activator of transcription 3(STAT3)-related information.Expression of STAT3 mRNA and miR-328-3p was detected by quantitative polymerase chain reaction(qPCR)and the expression levels of STAT3,phosphorylated STAT3(p-STAT3),and LC3 were detected by western blot analysis.The targeted relationship between miR-328-3p and STAT3 was detected using the dual-luciferase reporter gene system.AGS cells were infected with monomeric red fluorescent protein-green fluorescent protein-LC3 adenovirus double label.LC3 was labeled and autophagy flow was observed under a confocal laser microscope.RESULTS The expression of miR-328-3p was significantly upregulated after 18β-GRA intervention in AGS cells(P=4.51E-06).Overexpression of miR-328-3p inhibited GC cell proliferation and colony formation ability,arrested the cell cycle in the G0/G1 phase,promoted cell apoptosis,and inhibited the growth of subcutaneous tumors in BALB/c nude mice(P<0.01).No obvious necrosis was observed in the tumor tissue in the negative control group(no drug intervention or lentivirus transfection)and vector group(the blank vector for lentivirus transfection),and more cells were loose and necrotic in the miR-328-3p group.Bioinformatics tools predicted that miR-328-3p has a targeting relationship with STAT3,and STAT3 was closely related to autophagy markers such as p62.After overexpressing miR-328-3p,the expression level of STAT3 mRNA was significantly decreased(P<0.01)and p-STAT3 was downregulated(P<0.05).The dual-luciferase reporter gene assay showed that the luciferase activity of miR-328-3p and STAT33’untranslated regions of the wild-type reporter vector group was significantly decreased(P<0.001).Overexpressed miR-328-3p combined with bafilomycin A1(Baf A1)was used to detect the expression of LC3 II.Compared with the vector group,the expression level of LC3 II in the overexpressed miR-328-3p group was downregulated(P<0.05),and compared with the Baf A1 group,the expression level of LC3 II in the overexpressed miR-328-3p+Baf A1 group was upregulated(P<0.01).The expression of LC3 II was detected after intervention of 18β-GRA in GC cells,and the results were consistent with the results of miR-328-3p overexpression(P<0.05).Additional studies showed that 18β-GRA promoted autophagy flow by promoting autophagosome synthesis(P<0.001).qPCR showed that the expression of STAT3 mRNA was downregulated after drug intervention(P<0.05).Western blot analysis showed that the expression levels of STAT3 and p-STAT3 were significantly downregulated after drug intervention(P<0.05).CONCLUSION 18β-GRA promotes the synthesis of autophagosomes and inhibits GC cell proliferation by regulating the miR-328-3p/STAT3 signaling pathway.

Inhibition of signal transducer and activator of transcription 3 expression by RNA interference suppresses invasion through inducing anoikis in human colon cancer cells

AIM:To investigate the roles and mechanism of signal transducer and activator of transcription 3 (STAT3) in invasion of human colon cancer cells by RNA interference. METHODS: Small interfering RNA (siRNA) targeting Signal transducer and activator of transcription 3 (STAT3) was transfected into HT29 colon cancer cells. STAT3 protein level and DNA-binding activity of STAT3 was evaluated by western blotting and electrophoretic mobility shift assay (EMSA), respectively. We studied the anchorage-independent growth using colony formation in soft agar, and invasion using the boyden chamber model, anoikis using DNA fragmentation assay and terminal deoxynucleotidyltransferase-mediated dUTP nick-end labeling (TUNEL), respectively. Western blot assay was used to observe the protein expression of Bcl-xL and survivin in colon cancer HT29 cells. RESULTS: RNA interference (RNAi) mediated by siRNA leads to suppression of STAT3 expression in colon cancer cell lines. Suppression of STAT3 expression by siRNA could inhibit anchorage-independent growth, and invasion ability, and induces anoikis in the colon cancer cell line HT29. It has been shown that knockdown of STAT3 expression by siRNA results in a reduction in expression of Bcl-xL and survivin in HT29 cells. CONCLUSION: These results suggest that STAT3 siRNA can inhibit the invasion ability of colon cancer cells through inducing anoikis, which antiapoptotic genes survivin and Bcl-xL contribute to regulation of anoikis.These studies indicate STAT3 siRNA could be a useful therapeutic tool for the treatment of colon cancer.

Silencing of signal transducer and activator of transcription 3 expression by RNA interference suppresses growth of human hepatocellular carcinoma in tumor-bearing nude mice

AIM： To explore the effect of silencing of signal transducer and activator of transcription 3 （STAT3） expression by RNA interference （RNAi） on growth of human hepatocellular carcinoma （HCC） in tumorbearing nude mice in vivo.METHODS： To construct the recombinant plasmid of pSilencer 3.0-H1-STAT3-siRNA-GFP （pSHI-siRNA- STAT3） and establish the tumor-bearing nude mouse model of the HCC cell line SMMC7721, we used intratumoral injection together with electroblotting to transfect the recombinant plasmid pSHI-siRNA- STAT3 into the transplanted tumor. The weight of the nude mice and tumor volumes were recorded. STAT3 gene transcription was detected by semi-quantitative reverse transcription polymerase chain reaction （RT- PCR）. Level of protein expression and location of STAT3 were determined by Western blotting and immunohistochemical staining. STAT3-related genes such as survivin, c-myc, VEGF, p53 and caspase3 mRNA and protein expression were detected in tumor tissues at the same time. The terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling （TUNEL） assay was used to detect apoptosis of tumor cells.RESULTS： The weight of the treated nude mice increased, and the tumor volume decreased markedly compared with those of the mock-treated and negative control groups （P 〈 0.01）. The results of RT-PCR and Western blotting showed that mRNA and protein levels of STAT3 declined markedly in the treated group. The change in STAT3-related gene expression in tumor tissues at the mRNA and protein level also varied, the expression of survivin, VEGF and c-myc were obviously reduced, and expression of p53 and caspase3 increased （P 〈 0.01）. Most of the tumor tissue ceils in the treated group developed apoptosis that was detected by TUNEL assay.CONCLUSION： Silencing of STAT3 expression by RNAi significantly inhibits expression of STAT3 mRNA and protein, and suppresses growth of human HCC in tumor-bearing nude mice. The mechanism may be related to down-regulation of survivin, VEGF and c-myc and up-regulation of p53 and caspase3 expression. Accordingly, the STAT3 gene may act as an important and effective target in gene therapy of HCC.

Central role of Yes-associated protein and WW-domain-containing transcriptional co-activator with PDZ-binding motif in pancreatic cancer development

Pancreatic ductal adenocarcinoma(PDAC) remains a deadly disease with no efficacious treatment options. PDAC incidence is projected to increase, which may be caused at least partially by the obesity epidemic. Significantly enhanced efforts to prevent or intercept this cancer are clearly warranted. Oncogenic KRAS mutations are recognized initiating events in PDAC development, however, they are not entirely sufficient for the development of fully invasive PDAC.Additional genetic alterations and/or environmental, nutritional, and metabolic signals, as present in obesity, type-2 diabetes mellitus, and inflammation, are required for full PDAC formation. We hypothesize that oncogenic KRAS increases the intensity and duration of the growth-promoting signaling network.Recent exciting studies from different laboratories indicate that the activity of the transcriptional co-activators Yes-associated protein(YAP) and WW-domaincontaining transcriptional co-activator with PDZ-binding motif(TAZ) play a critical role in the promotion and maintenance of PDAC operating as key downstream target of KRAS signaling. While initially thought to be primarily an effector of the tumor-suppressive Hippo pathway, more recent studies revealed that YAP/TAZ subcellular localization and co-transcriptional activity is regulated by multiple upstream signals. Overall, YAP has emerged as a central node of transcriptional convergence in growth-promoting signaling in PDAC cells. Indeed, YAP expression is an independent unfavorable prognostic marker for overall survival of PDAC. In what follows, we will review studies implicating YAP/TAZ in pancreatic cancer development and consider different approaches to target these transcriptional regulators.

Detection for Transcriptional Activity of Alternaria Tenuissim Protein Elicitor in Yeast Two-hybrid System

The peaT1 gene fragment was amplified from pGEM-6p-l-peaT1 by PCR, and recovered target gene was cloned into pLexA vector. After digestion and sequencing, the bait vector pLexA-peaT1 was transformed into yeast strain EGY48 [p8op-lacZ] by PEG/LiAC, and the transcriptional activity of bait vector was detected. The results showed that recombinant bait plasmid pLexA-PEMG1 was constructed, for the two bands of recombinant bait plasmid in agarose gel eleetrophoresis were expected after digesting by restriction endonuclease EcoR I and Xho I. Therefore, the recombinant bait plasmid could be used in yeast two-hybrid system to screen a cDNA library.

Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019

Under the combined influence of climate change and human activities,vegetation ecosystem has undergone profound changes.It can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical periods.Therefore,it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change cycle.Based on the data of climate elements(sunshine hours,precipitation and temperature),human activities(population intensity and GDP intensity)and other natural factors(altitude,slope and aspect),this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method,a trend analysis,and a gravity center model,and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector model.The results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to northwest.During 1981-2019,the temporal variation of vegetation NDVI showed an overall increasing trend.The gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County,Gansu Province,and the center moved northeastwards from 1981 to 2019.During 1981-2000 and 2001-2019,the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the largest.During the study period(1981-2019),the dominant factors influencing vegetation NDVI shifted from natural factors to human activities.These results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.