Inhibitive effect of triptolide on invasiveness of human fibrosarcoma cells by downregulating matrix metalloproteinase—9 expression

AbstractObjectiveTo explore the molecular mechanisms of antitumor properties of triptolide, a bioactive component isolated from the Chinese herb Tripterygium wolfordii Hook F.MethodsHuman fibrosarcoma HT-1080 cells were treated with different doses of triptolide for 72 h. Then the expression and activity of matrix metalloproteinase (MMP)-2 and -9 were measured and the invasiveness of triptolide-treated HT-1080 cells was compared with that of anti-MMP-9-treated HT-1080 cells.Results18 nmol/L triptolide inhibited the gene expression and activity of MMP-9, but not those of MMP-2, in HT-1080 cells. In addition, both 18 nmol/L triptolide and 3 μg/mL anti-MMP-9 significantly reduced the invasive potential of HT-1080 cells, by about 50% and 35%, respectively, compared with the control. Whereas there was no significant difference between the effect of 18 nmol/L triptolide and that of anti-MMP-9 on invasive potential of HT-1080 cells.ConclusionsThese data suggest that triptolide inhibits tumor cell invasion partly by reducing MMP-9 gene expression and activity

Competition, markups, and gains from trade: A quantitative analysis of China between 1995 and 2004

Sing Lun Fellowship of Singapore Management Universit

Competition and Gains from Trade: A Quantitative Analysis of China Between 1995 and 2004

SMU Economics and Statistics Working Paper Series, Paper No. 13-2015</p

Molecular and serological investigations of Batai virus in cattle and goats in the border area of Yunnan, China (2021–2022)

IntroductionBatai virus (BATV), a zoonotic pathogen transmitted by mosquitoes, infects vertebrates, including livestock, birds, and humans. Although BATV has been detected and isolated in mosquitoes in Yunnan Province, China, there have been no reports of livestock infection. Thus, we conducted a molecular and serological investigation of BATV in cattle and goat sera collected in spring and autumn from 2021 to 2022 in Honghe Prefecture, Yunnan Province, on the China-Vietnam border.MethodsWe used indirect enzyme-linked immunosorbent assays and reverse transcription real-time PCR (RT-qPCR) to test 929 cattle and 973 goat serum samples.ResultsBATV antibodies were detected in 262/929 (28.2%) cattle and 263/973 (27.0%) goat serum samples. RT-qPCR did not detect BATV RNA.DiscussionThe positive rate of BATV serum antibodies in cattle and goats in Luxi County was higher compared with other areas, and it was also higher in autumn compared with spring, which may be related to climate, temperature, and mosquito density. Although our findings indicated the presence of BATV infection in livestock in the region, RT-qPCR did not detect BATV RNA. Therefore, BATV monitoring in cattle and goats should be heightened in autumn, and the scope of host monitoring should be expanded to clarify the hosts and vectors of BATV infection

Classificação de uso e cobertura da terra na Amazônia brasileira por meio de imagens de satélite

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.A classificação de uso e cobertura da terra é uma das principais aplicações do sensoriamento remoto. Contudo, a precisão no mapeamento da distribuição espacial do uso/cobertura da terra é um desafio, principalmente em regiões tropicais úmidas, em razão do complexo ambiente biofísico e das limitações dos dados de sensoriamento remoto per se. Este trabalho revisa experimentos relacionados à classificação do uso/cobertura da terra na Amazônia brasileira, durante uma década. A partir de análise compreensiva dos resultados de classificação, conclui-se que a informação espacial, em dados de sensoriamento remoto, tem papel fundamental na melhoria da classificação de uso/cobertura da terra. A incorporação de imagens textura, em bandas multiespectrais, e o uso de método baseado em segmentação são formas importantes de melhorar a  classificação, especialmente para imagens de alta resolução espacial. A fusão de dados de imagens de resolução múltipla dentro de dados do sensor ótico é vital para a interpretação visual, mas pode não melhorar o desempenho da classificação. Em contraste, a integração de dados ópticos e de radar melhorou o desempenho da classificação, quando o método adequado de fusão de dados foi utilizado. Entre os algoritmos de classificação disponíveis, o classificador de máxima verossimilhança ainda é importante para se obter precisão razoável, mas algoritmos não paramétricos, como a análise por árvore de decisão, podem promover melhores resultados. Porém, algoritmos não paramétricos geralmente demandam mais tempo para obtenção da parametrização otimizada. O uso adequado de métodos baseados em hierarquia é fundamental para a precisão na classificação de uso/cobertura da terra, sobretudo em dados de sensoriamento remoto antigos

The Local Origin of the Tibetan Pig and Additional Insights into the Origin of Asian Pigs

BACKGROUND: The domestic pig currently indigenous to the Tibetan highlands is supposed to have been introduced during a continuous period of colonization by the ancestors of modern Tibetans. However, there is no direct genetic evidence of either the local origin or exotic migration of the Tibetan pig. METHODS AND FINDINGS: We analyzed mtDNA hypervariable segment I (HVI) variation of 218 individuals from seven Tibetan pig populations and 1,737 reported mtDNA sequences from domestic pigs and wild boars across Asia. The Bayesian consensus tree revealed a main haplogroup M and twelve minor haplogroups, which suggested a large number of small scale in situ domestication episodes. In particular, haplogroups D1 and D6 represented two highly divergent lineages in the Tibetan highlands and Island Southeastern Asia, respectively. Network analysis of haplogroup M further revealed one main subhaplogroup M1 and two minor subhaplogroups M2 and M3. Intriguingly, M2 was mainly distributed in Southeastern Asia, suggesting for a local origin. Similar with haplogroup D6, M3 was mainly restricted in Island Southeastern Asia. This pattern suggested that Island Southeastern Asia, but not Southeastern Asia, might be the center of domestication of the so-called Pacific clade (M3 and D6 here) described in previous studies. Diversity gradient analysis of major subhaplogroup M1 suggested three local origins in Southeastern Asia, the middle and downstream regions of the Yangtze River, and the Tibetan highlands, respectively. CONCLUSIONS: We identified two new origin centers for domestic pigs in the Tibetan highlands and in the Island Southeastern Asian region

A comparative analysis of modeling approaches and canopy height-based data sources for mapping forest growing stock volume in a northern subtropical ecosystem of China

Lidar has been regarded as the most accurate data source for forest-growing stock volume (FGSV) estimation, but inconsistent acquisition dates of lidar data with field survey often result in poor FGSV estimation accuracy. Spaceborne stereo imagery is captured at regular intervals, providing new opportunities for mapping and updating FGSV spatial distributions. Digital Surface Model derived from spaceborne stereo imagery and Digital Terrain Model (DTM) derived from airborne lidar can be used together to produce a canopy height model (CHM) (LS-CHM), which can then be used to predict FGSV spatial distributions, but this methodology has yet to be explored. Our research attempts to compare the performance of LS-CHM and lidar-CHM (L-CHM) for FGSV modeling and to explore the advantages of using the hierarchical Bayesian approach (HBA) over traditional linear regression and random forest modeling approaches when sample size is small. Considering different forest types and topographical conditions, as well as the number of sample plots for each forest type, HBA is used to develop the FGSV estimation model, and the results are compared with those from linear regression and random forest approaches. The research results in a northern subtropical forest ecosystem indicate that overall, L-CHM provides better predictions than LS-CHM using the same modeling approaches, and L-CHM is especially valuable when FGSV is small or large, but when FGSV falls within 100–200 m3/ha, LS-CHM–based variables produce better modeling accuracy than L-CHM–based variables using linear regression or HBA. The HBA based on stratification of both forest type and slope aspect provides the best FGSV estimation, using either L-CHM or LS-CHM, and solves the modeling problem due to limited sample sizes for forest types. Our research provides new insights to using the combination of satellite stereo images and lidar-derived DTM for mapping and updating FGSV in a large area

Effect Analysis of Excavation and Unloading of Deep Foundation Pit in Soft Soil Stratum on Pile Foundation of Underground Station

Objective In the excavation process of deep foundation pit of underground station in deep soft soil stratum, excavation and unloading of the overlying soil in the pit will obviously impact the previously constructed superlong pile foundation in the pit, threatening the structure stability and engineering safety. In order to explore the effects of large-scale deep foundation pit excavation and unloading on the pile group at the station foundation pit bottom, it is necessary to analyze the deformation law of the superlong pile under pressure. Method A numerical analysis software Midas GTS NX is used to establish a finite element numerical calculation model for the underground station S2 east end well and make the excavation simulation analysis. Based on a comparison of the on-site actual monitored data and the numerical calculation results, the deformation law of the pile group at the pit bottom affected by the foundation pit excavation is discussed. Result & Conclusion The results show that the pile area under tension increases with the deepening of excavation，both the maximum tension and the maximum pressure of the end well pile foundation are greater than the standard range. The vertical displacement of the pile foundation at the pit bottom continuously increases in the process of excavation. The largest pile displacement occurs at the farthest distance from the edge of the end well. In the later stage of excavation, as the incremental uplift of the pile foundation increases significantly, the vertical displacement of the pile top needs to be monitored in real time to prevent engineering accidents