| 1 | Multi-reservoir joint operating rule in inter-basin water transfer-supply project显示文摘The joint operation of inter-basin water transfer-supply(IBWTS)project can be more complex when there is joint water demand in multi-reservoir system and multi-importing reservoirs simultaneously transferring water from exporting reservoir.In this study,a joint operating rule is proposed for the purpose of solving such complex operation problem.This rule is composed of a set of sub-rules,including hedging rule curves of virtual aggregation reservoir(i.e.equivalent reservoir)and other individual reservoirs,water-transfer rule curves of each individual reservoir,as well as some of important assisted rules.These assisted rules refer to allocation models for water transfer-supply.In the proposed rule,an equivalent reservoir is established to determine under what condition the water supply should be reduced and specify the total supplied water for joint water demand(i.e.aggregation method).Allocation models are developed to distribute the total transferred water into each importing reservoir and determine the water releases for joint water demand by each member reservoir of the aggregation system(i.e.decomposition method).And these models are integrated with a set of influence factors such as hydrologic characteristics,reservoir storage or vacant storage,regulating ability,water-supply pressure,and so on.The aggregation of multi-reservoirs and the disaggregation of water quantities are taken into a whole consideration to reduce the complexity in reallocation of water target storage or water release.Finally,the proposed rule is applied to the North-line IBWTS Project in Liaoning Province,China.The results indicate that the proposed rule can take full advantage of hydrologic compensation in basins and capacity compensation in reservoirs.Thus it can improve the utilization efficiency of water resources in system. | PENG AnBang PENG Yong ZHOU HuiCheng ZHANG Chi | 2015 | Science China(Technological Sciences)2015，58，1： | 8 |
| 2 | Definition and verification of novel metastasis and recurrence related signatures of ccRCC: A multicohort study显示文摘Background:Cancer metastasis and recurrence remain major challenges in renal carcinoma patient management.There are limited biomarkers to predict the metastatic probability of renal cancer,especially in the early-stage subgroup.Here,our study applied robust machine-learning algorithms to identify metastatic and recurrence-related signatures across multiple renal cancer cohorts,which reached high accuracy in both training and testing cohorts.Methods:Clear cell renal cell carcinoma(ccRCC)patients with primary or metastatic site sequencing information from eight cohorts,including one outhouse cohort,were enrolled in this study.Three robust machine-learning algorithms were applied to identify metastatic signatures.Then,two distinct metastatic-related subtypes were identified and verified;matrix remodeling associated 5(MXRA5),as a promising diagnostic and therapeutic target,was investigated in vivo and in vitro.Results:We identified five stable metastasis-related signatures(renin,integrin subunit beta-like 1,MXRA5,mesenchyme homeobox 2,and anoctamin 3)from multicenter cohorts.Additionally,we verified the specificity and sensibility of these signatures in external and out-house cohorts,which displayed a satisfactory consistency.According to these metastatic signatures,patients were grouped into two distinct and heterogeneous ccRCC subtypes named metastatic cancer subtype 1(MTCS1)and type 2(MTCS2).MTCS2 exhibited poorer clinical outcomes and metastatic tendencies than MTCS1.In addition,MTCS2 showed higher immune cell infiltration and immune signature expression but a lower response rate to immune blockade therapy than MTCS1.The MTCS2 subgroup was more sensitive to saracatinib,sunitinib,and several molecular targeted drugs.In addition,MTCS2 displayed a higher genome mutation burden and instability.Furthermore,we constructed a prognosis model based on subtype biomarkers,which performed well in training and validation cohorts.Finally,MXRA5,as a promising biomarker,significantly suppressed malignant ability,including the cell migration and proliferation of ccRCC cell lines in vitro and in vivo.Conclusions:This study identified five robust metastatic signatures and proposed two metastatic probability clusters with stratified prognoses,multiomics landscapes,and treatment options.The current work not only provided new insight into the heterogeneity of renal cancer but also shed light on optimizing decision‐making in immunotherapy and chemotherapy. | Aimin Jiang Qingyang Pang Xinxin Gan Anbang Wang Zhenjie Wu Bing Liu Peng Luo Le Qu Linhui Wang | 2022 | Cancer Innovation2022，1，2： | 0 |
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