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| 1 | In vitro and in vivo evaluation of cucurbitacin E on rat hepatic CYP2C11 expression and activity using LC-MS/MS显示文摘This study explored the effects of cucurbitacin E(Cu E), a bioactive compound from Cucurbitaceae, on the metabolism/ pharmacokinetic of tolbutamide, a model CYP2C9/11 probe substrate, and hepatic CYP2C11 expression in rats. Liquid chromatography-(tandem) mass spectrometry(LC-MS/MS) assay was used to detect tolbutamide as well as 4-hydroxytolbutamide, and then successfully applied to the pharmacokinetic study of tolbutamide in rats. The effect of Cu E on CYP2C11 expression was determined by western blot. Cu E(1.25–100 μmol L-1) competitively inhibited tolbutamide 4-hydroxylation(CYP2C11) activity only in concentration-dependent manner with a Ki value of 55.5 μmol L-1 in vitro. In whole animal studies, no significant difference in metabolism/pharmacokinetic of tolbutamide was found for the single pretreatment groups. In contrast, multiple pretreatments of Cu E(200 μg kg-1 d-1, 3 d, i.p.) significantly decreased tolbutamide clearance(CL) by 25% and prolonged plasma half-time(T1/2) by 37%. Moreover, Cu E treatment(50–200 μg kg-1 d-1, i.p.) for 3 d did not affect CYP2C11 expression. These findings demonstrated that CuE competitively inhibited the metabolism of CYP2C11 substrates but had no effect on rat CYP2C11 expression. This study may provide a useful reference for the reasonable and safe use of herbal or natural products containing Cu E to avoid unnecessary drug-drug interactions. | Jian Lu Tonggui Ding Xuan Qin Mingyao Liu Xin Wang | 2017 | Science China(Life Sciences)2017，60，2： | 2 |
| 2 | 温带森林演替加剧了氮限制:来自叶片化学计量和养分重吸收的证据显示文摘森林生产力和碳汇功能在很大程度上取决于土壤氮和磷的有效性。然而,迄今为止,养分限制随森林演替的时间变化仍存在争议。叶片化学计量和养分重吸收是预测植物生长养分限制的重要指标。基于此,本研究测定了温带森林4个演替阶段所有木本植物叶片和调落叶中氮和磷的含量,并分析了演替过程中非生物因子和生物因子如何影响叶片化学计量和养分重吸收。研究结果表明,在个体尺度上,叶片氮磷含量在演替末期显著增加,而叶片氮磷比无显著变化氮的重吸收效率随演替显著增加,然而磷的重吸收效率先增加后减少:氮重吸收效率与磷重吸收效率的比值仅在演替末期显著增加。此外,植物氮素循环对土壤养分的响应比磷素循环更弱。在群落尺度上,叶片氮磷含量随森林演替呈现先降低后升高的趋势,主要受香农-维纳多样性指数和物种丰富度的影响:叶片氮磷比随演替而显著变化,主要由胸径的群落加权平均值决定:氮的重吸收效率增加,主要受物种丰富度和胸径的影响,而磷的重吸收效率相对稳定。因此,氮重吸收效率与磷重吸收效率的比值显著增加,表明随着温带森林演替,氮限制加剧。这些结果可能反映了较高生物多样性群落中物种间对有限资源的激烈竞争,强调了生物因子在驱动森林生态系统养分循环中的重要性,为中国温带和北方森林可持续经营的施肥管理提供了参考。 | Peng Zhang Xiao-Tao Lu Mai-He Li Tonggui Wu Guangze Jin | 2022 | Journal of Plant Ecology2022，15，5： | 1 |
| 3 | Leaf nitrogen and phosphorus stoichiometry of Quercus species across China显示文摘 | Tonggui Wu Yi Dong Mukui Yu G. Geoff Wang De-Hui Zeng | 2012 | Forest Ecology and Management2012，，： | 1 |
| 4 | Relationship of serum GDF11 levels with bone mineral density and bone turnover markers in postmenopausal Chinese women显示文摘Growth differentiation factor 11(GDF11) is an important circulating factor that regulates aging.However,the role of GDF11 in bone metabolism remains unclear.The present study was undertaken to investigate the relationship between serum GDF11 level,bone mass,and bone turnover markers in postmenopausal Chinese women.Serum GDF11 level,bone turnover biochemical markers,and bone mineral density(BMD) were determined in 169 postmenopausal Chinese women(47–78 years old).GDF11 serum levels increased with aging.There were negative correlations between GDF11 and BMD at the various skeletal sites.After adjusting for age and body mass index(BMI),the correlations remained statistically significant.In the multiple linear stepwise regression analysis,age or years since menopause,BMI,GDF11,and estradiol were independent predictors of BMD.A significant negative correlation between GDF11 and bone alkaline phosphatase(BAP) was identified and remained significant after adjusting for age and BMI.No significant correlation was noted between cross-linked N-telopeptides of type I collagen(NTX) and GDF11.In conclusion,GDF11 is an independent negative predictor of BMD and correlates with a biomarker of bone formation,BAP,in postmenopausal Chinese women.GDF11 potentially exerts a negative effect on bone mass by regulating bone formation. | Yusi Chen Qi Guo Min Zhang Shumin Song Tonggui Quan Tiepeng Zhao Hongliang Li Lijuan Guo Tiejian Jiang Guangwei Wang | 2016 | Bone Research2016，4，1： | 1 |
| 5 | Temperature biases in modeled polar climate and adoption of physical parameterization schemes显示文摘An annual cycle of atmospheric variations for 1989 in the Arctic has been simulated with the Weather Research and Forecasting (WRF) model. A severe cold bias was found around a cold center in surface air temperature over the Arctic Ocean, compared with results from ERA-Interim reanalysis. Four successive numerical experiments have been carried out to find out the reasons for this. The results show that the sea ice albedo scheme has the biggest influence in summer, and the effect of the cloud microphysics scheme is significant in both summer and winter. The effect of phase transition between ice and water has the biggest influence over the region near the sea ice edge in summer, and contributes little to improvement of the severe cold bias. The original crude albedo parameterization in the surface process scheme is the main reason for the large simulated cold bias of the cold center in summer. With a different land surface scheme than in the control run, cold biases of simulated surface air temperature over the Arctic Ocean are greatly reduced, by as much as 10 K, implying that the land surface scheme is critical for polar climate simulation. | LIU Xiying ZHAO Jiahua XIAHuasheng BAI Tonggui ZHANG Tao | 2012 | Advances in Polar Science2012，23，1： | 1 |
| 6 | Leaf nitrogen and phosphorus stoichiometry of quercus species across China 显示文摘 | Wu Tonggui Dong Yi Yu Mukui | 2012 | Forest Ecology and Management2012，284，1： | 1 |
| 7 | Solar radiation effects on leaf nitrogen and phosphorus stoichiometry of Chinese fir across subtropical China显示文摘Background:Solar radiation(SR)plays critical roles in plant physiological processes and ecosystems functions.However,the exploration of SR influences on the biogeochemical cycles of forest ecosystems is still in a slow progress,and has important implications for the understanding of plant adaption strategy under future environmental changes.Herein,this research was aimed to explore the influences of SR on plant nutrient characteristics,and provided theoretical basis for introducing SR into the establishment of biochemical models of forest ecosystems in the future researches.Methods:We measured leaf nitrogen(N)and phosphorus(P)stoichiometry in 19 Chinese fir plantations across subtropical China by a field investigation.The direct and indirect effects of SR,including global radiation(Global R),direct radiation(Direct R)and diffuse radiation(Diffuse R)on the leaf N and P stoichiometry were investigated.Results:The linear regression analysis showed that leaf N concentration had no association with SR,while leaf P concentration and N:P ratio were negatively and positively related to SR,respectively.Partial least squares path model(PLS-PM)demonstrated that SR(e.g.Direct R and Diffuse R),as a latent variable,exhibited direct correlations with leaf N and P stoichiometry as well as the indirect correlation mediated by soil P content.The direct associations(path coefficient=−0.518)were markedly greater than indirect associations(path coefficient=−0.087).The covariance-based structural equation modeling(CB-SEM)indicated that SR had direct effects on leaf P concentration(path coefficient=−0.481),and weak effects on leaf N concentration.The high SR level elevated two temperature indexes(mean annual temperature,MAT;≥10°C annual accumulated temperature,≥10℃ AAT)and one hydrological index(mean annual evapotranspiration,MAE),but lowered the soil P content.MAT,MAE and soil P content could affect the leaf P concentration,which cause the indirect effect of SR on leaf P concentration(path coefficient=0.004).Soil N content had positive effect on the leaf N concentration,which was positively and negatively regulated by MAP and≥10℃ AAT,respectively.Conclusions:These results confirmed that SR had negatively direct and indirect impacts on plant nutrient status of Chinese fir based on a regional investigation,and the direct associations were greater than the indirect associations.Such findings shed light on the guideline of taking SR into account for the establishment of global biogeochemical models of forest ecosystems in the future studies. | Ran Tong Yini Cao Zhihong Zhu Chenyang Lou Benzhi Zhou Tonggui Wu | 2021 | Forest Ecosystems2021，8，4： | 0 |
| 8 | Root nutrient capture and leaf resorption efficiency modulated by different influential factors jointly alleviated P limitation in Quercus acutissima across the North–South Transect of Eastern China显示文摘Soil and climatic conditions are known to have close associations with plant morphological and stoichiometric traits at a regional scale along latitudinal gradients;however,how latitude drives biotic and abiotic factors affecting plant nutrient acquisition to accommodate environmental nutrient deficiency remains unclear.We quantified soil,root,leaf,and leaf litter nitrogen(N)and phosphorus(P)concentrations to determine the potentially limiting nutrient and the simultaneous responses of root capture and leaf resorption to nutrient deficiency in seven Quercus acutissima forests across the North–South Transect of Eastern China.The results showed that the mean leaf and root N:P ratios in Q.acutissima were 21.58 and 20.23,respectively,which markedly exceeded the P limitation threshold of 16 for terrestrial plants.The mean leaf litter N and P were 10.63 mg/g and 0.51 mg/g,respectively,indicating that P resorption proficiency was relatively higher than N resorption proficiency.N displayed higher stoichiometric homeostasis than P in the leaf.The leaf and root N:P ratios showed a quadratic variation that first decreased and then increased as latitude increased,whereas the phosphorus resorption efficiency and root-soil accumulation factor of P displayed the opposite trend.Partial least square path modeling(PLS-PM)analysis demonstrated that root nutrient capture and leaf nutrient resorption were regulated by different influential factors.Overall,these findings provide new insights into plant strategies to adapt to environmental nutrient deficiency,as well as the scientific basis for predicting the spatial and temporal patterns of nutrient acquisition in the context of climate change. | Ran Tong Yuxiang Wen Jingyuan Wang Chenyang Lou Cong Ma Nianfu Zhu Wenwen Yuan GGeoff Wang Tonggui Wu | 2022 | Forestry Research2022，2，1： | 0 |
| 9 | Forestry development to reduce poverty and improve the environment显示文摘Poverty reduction is a world-wide concern.At the end of 2017,according to the rural poverty standard in China,there were 30.46 million poor in China.However,complete poverty alleviation by the end of 2020 had been achieved.This is significant and complicated,especially as poverty-stricken areas and ecologically fragile areas overlap.During the process of poverty alleviation,the development of forestry projects was not only conducive to improving the environment but also an important way to reduce poverty.Therefore,based on an analysis of the causes of poverty-stricken areas,this study examined successful cases in different regions and proposed ways to promote economic growth:providing state subsidies for tree planting and forest maintenance;developing undergrowth economy;and/or initiating an industrial chain.It also introduces principles to promote forestry progress,according to local conditions,keeping a balance between economic development and the environment.This study provides effective ways to promote forestry development and rural poverty alleviation. | Rongjia Wang Jianfeng Zhang Tonggui Wu Shiyong Sun Zongtai Li Deshun Zhang | 2022 | Journal of Forestry Research2022，33，6： | 0 |
| 10 | Variations in seed size and seed mass related to tree growth over 5 years for 23 provenances of Quercus acutissima from across China显示文摘The origin of a seed strongly impacts its traits,and both origin and seed traits influence seed germination and seedling development.However,in many instances,this effect on the seedling does not persist into adulthood,and little is known about how seed traits and original environment affect seedling/tree growth over time.In this study,seed size,seed mass,seedling/tree growth and origins were collected and determined for 23 provenances of Quercus acutissima from across China.Origin variables correlated well with seed size and seed mass.In stepwise multiple regressions,a longitudinal aridity index explained 49.2–68.7% of the total variation in seed size and mass,while only seed width was correlated with seedling/tree height(H) and diameter at the ground(D) from seed traits and origins.The total variance in H and D explained by the models decreased over time,for example,the R^2 value of the models for H declined from 0.477 in the first year to 0.224 in the fourth year;no models was significant in the fifth year.These results indicate that seed size,regulated by the longitudinal aridity index strongly impacted seedling and tree growth,but the strength of the influence decreased over time,and disappeared after 4 years. | Hui Zhang Xiuqing Yang Mukui Yu Youzhi Han Tonggui Wu | 2017 | Journal of Forestry Research2017，28，5： | 0 |
| 11 | The Estimation of the Higher Heating Value of Biochar by Data-Driven Modeling显示文摘Biomass is a carbon-neutral renewable energy resource.Biochar produced from biomass pyrolysis exhibits preferable characteristics and potential for fossil fuel substitution.For time-and cost-saving,it is vital to establish predictive models to predict biochar properties.However,limited studies focused on the accurate prediction of HHV of biochar by using proximate and ultimate analysis results of various biochar.Therefore,the multi-linear regression(MLR)and the machine learning(ML)models were developed to predict the measured HHV of biochar from the experiment data of this study.In detail,52 types of biochars were produced by pyrolysis from rice straw,pig manure,soybean straw,wood sawdust,sewage sludge,Chlorella Vulgaris,and their mixtures at the temperature ranging from 300 to 800℃.The results showed that the co-pyrolysis of the mixed biomass provided an alternative method to increase the yield of biochar production.The contents of ash,fixed carbon(FC),and C increased as the incremental pyrolysis temperature for most biochars.The Pearson correlation(r)and relative importance analysis between HHV values and the indicators derived from the proximate and ultimate analysis were carried out,and the measured HHV was used to train and test the MLR and the ML models.Besides,ML algorithms,including gradient boosted regression,random forest,and support vector machine,were also employed to develop more widely applicable models for predicting HHV of biochar from an expanded dataset(total 149 data points,including 97 data collected from the published literature).Results showed HHV had strong correlations(|r|>0.9,p<0.05)with ash,FC,and C.The MLR correlations based on either proximate or ultimate analysis showed acceptable prediction performance with test R2>0.90.The ML models showed better performance with test R^(2)around 0.95(random forest)and 0.97–0.98 before and after adding extra data for model construction,respectively.Feature importance analysis of the ML models showed that ash and C were the most important inputs to predict biochar HHV. | Jiefeng Chen Lisha Ding Pengyu Wang Weijin Zhang Jie Li Badr A.Mohamed Jie Chen Songqi Leng Tonggui Liu Lijian Leng Wenguang Zhou | 2022 | Journal of Renewable Materials2022，10，6： | 0 |
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