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Realized niche shift associated with Galinsoga quadriradiata(Asteraceae)invasion in China 被引量:3
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作者 Wengang Zhang Xiaoyan Chen +6 位作者 Ruiling Liu Xingjiang Song Gang Liu Jiabin Zou Zengqiang Qian Zhihong Zhu Langjun Cui 《Journal of Plant Ecology》 SCIE CSCD 2022年第3期538-548,共11页
Shifts in the realized niches of exotic species may play an important role in their invasion.Galinsoga quadriradiata has invaded China widely and occupied many climate zones that are different from its native range.We... Shifts in the realized niches of exotic species may play an important role in their invasion.Galinsoga quadriradiata has invaded China widely and occupied many climate zones that are different from its native range.We addressed the climatic niche shift of G.quadriradiata and evaluated how this could contribute to its invasion in China.We used the Maxent model to predict the potential distribution of G.quadriradiata using its native and invaded range occurrences and climatic variables.Principal component analysis was conducted to measure climatic niche shifts of G.quadriradiata during its invasion in China.The models revealed only 32.7%niche overlap between the native and invasive populations.The niche similarity of the two populations was significantly low(Schoener’s D=0.093,P<0.005),suggesting the occurrence of a niche shift.The envelop and center of the realized climatic niche in China has shifted to lower temperature and less precipitation compared to that in its native range.The majority of invaded areas in southern China are in the stabilizing zone,whereas the colonization and adaptation zones are predicted to be at the leading edge of G.quadriradiata invasion in northern China.This suggests that the regional distribution of G.quadriradiata may be in a quasi-equilibrium state,and that the species continues to invade environmentally suitable areas.Alterations in G.quadriradiata’s niche would help to explain why this species is so invasive in China. 展开更多
关键词 ecological niche modeling invasive species niche shift niche contraction invasion stage
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Identification of TWIST-interacting genes in prostate cancer 被引量:2
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作者 Peng Lyu Shu-Dong Zhang +4 位作者 Hiu-Fung Yuen Cian M.McCrudden Qing Wen Kwok-Wah Chan Hang Fai Kwok 《Science China(Life Sciences)》 SCIE CAS CSCD 2017年第4期386-396,共11页
Prostate cancer is one of the most common cancers in men worldwide, and the number of diagnosed patients has dramatically increased in recent years. Currently, the clinical parameters used to diagnose prostate cancer,... Prostate cancer is one of the most common cancers in men worldwide, and the number of diagnosed patients has dramatically increased in recent years. Currently, the clinical parameters used to diagnose prostate cancer, such as Gleason score, pathological tumor staging, and prostate-specific antigen(PSA) expression level, are considered insufficient to inform recommendation to guide clinical practice. Thus, identification of a novel biomarker is necessary. TWIST is one of the well-studied targets and is correlated with cancer invasion and metastasis in several human cancers. We have investigated two largest prostate cancer patient cohorts available in GEO database and found that TWIST expression is positive correlated with Gleason score and associated with poorer survival. By using a prostate cancer cohort and a prostate cancer cell line dataset, we have identified three potential downstream targets of TWIST, PPM1 A, SRP72 and TBCB. TWIST's prognostic capacity is lost when the gene is mutated. Further investigation in the prostate cancer cohort revealed that gene expression of SERPINA, STX7, PDIA2, FMP5, GP1 BB, VGLL4,KCNMA1, SHMT2, SAA4 and DIDO1 influence the prognostic significance of TWIST and vice versa. Importantly, eight out of these ten genes are prognostic indicator by itself. In conclusion, our study has further confirmed that TWIST is a prognostic marker in prostate cancer, identified its potential downstream targets and genes that could possibly give additional prognostic value to predict TWIST-mediated prostate cancer progression. 展开更多
关键词 Gleason prognostic staging cohort progression invasion downstream metastasis biomarker interacting
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