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Piwi-interacting RNAs (piRNAs) are regarded as drug targets and biomarkers for the diagnosis and therapy of diseases. However, biological experiments cost substantial time and resources, and the existing computational methods only focus on identifying missing associations between known piRNAs and diseases. With the fast development of biological experiments, more and more piRNAs are detected. Therefore, the identification of piRNA-disease associations of newly detected piRNAs has significant theoretical value and practical significance on pathogenesis of diseases. In this study, the iPiDA-LTR predictor is proposed to identify associations between piRNAs and diseases based on Learning to Rank. The iPiDA-LTR predictor not only identifies the missing associations between known piRNAs and diseases, but also detects diseases associated with newly detected piRNAs. Experimental results demonstrate that iPiDA-LTR effectively predicts piRNA-disease associations outperforming the other related methods. Author summary: Accumulating evidences have indicated that dysfunction and abnormal expression of piRNAs are closely associated with the emergence and development of diseases. Currently, identifying piRNA-disease associations mainly focuses on biological experimental methods and computational methods. However, biological experimental methods take substantial time and resources. Computational methods mainly focused on identifying diseases associated known piRNAs. With the development of biological technology, more and more newly detected piRNAs were detected. Therefore, identifying diseases associated with newly detected piRNAs is more important compared with identifying diseases associated with known piRNAs. Information retrieval (IR)'s goal is to rank documents based on the relevance to certain topics. This task is particularly similar with identification of piRNA-disease associations. Specifically, ranking documents related to previous topics corresponds to identify diseases associated with known piRNAs, and ranking documents related to novel topics is similar to identify diseases associated with newly detected piRNAs. Therefore, we propose a new predictor called iPiDA-LTR to predict associations between piRNAs and diseases based on information retrieval technology. Experimental results indicated that iPiDA-LTR is promising in identifying diseases associated with known piRNAs and newly detected piRNAs. [ABSTRACT FROM AUTHOR]

Lacustrine deposits at the margin of the southeastern Tibetan Plateau (SETP) are sensitive indicators for the evolution of the southwest Asian monsoon (SWAM) during the Quaternary. Thus, they can provide insight into the Quaternary climatic history and their relationship with global climatic changes. The results of the geochemical analysis of the Xiaozhongdian Basin section at the SETP suggest that SiO2 had the highest content of the major elements followed by Al2O3. The order of the abundance of the major elements was generally as follows: SiO2>Al2O3>Fe2O3>CaO>MgO>K2O>TiO2>Na2O>MnO2. The geochemical proxies, such as chemical index of alteration (CIA), the index of compositional variability (ICV) and (CaO+K2O+Na2O)/Al2O3, indicate the weak chemical weathering and the aridification of the margin of the SETP during the Heinrich events. In addition, the aridification of the SETP during the Heinrich events may be closely related to the cold signals transmitted from the high latitudes of the North Atlantic to the TP, and the effect caused the cooling effect to be very strong on the TP as a result of the upper-level westerly jet stream and then reduced the suction action associated with the SWAM, thus accelerating the drying rate of Xiaozhongdian Basin, which was amplifying the degree of drought in Heinrich events. [ABSTRACT FROM AUTHOR]

Sediments from Xinyun Lake in central Yunnan, southwest China, provide a record of environmental history since the Holocene. With the application of multi-proxy indicators (total organic carbon (TOC), total nitrogen (TN), δ13C and δ15N isotopes, C/N ratio, grain size, magnetic susceptibility (MS) and CaCO3 content), as well as accelerator mass spectrometry (AMS) 14C datings, four major climatic stages during the Holocene have been identified in Xingyun′s catchment. A marked increase in lacustrine palaeoproductivity occurred from 11.06 to 9.98 cal. ka BP, which likely resulted from an enhanced Asian southwest monsoon and warm-humid climate. Between 9.98 and 5.93 cal. ka BP, a gradually increased lake level might have reached the optimum water depth, causing a marked decline in coverage by aquatic plants and lake productivity of the lake. This was caused by strong Asian southwest monsoon, and coincided with the global Holocene Optimum. During the period of 5.60–1.35 cal. ka BP, it resulted in a warm and dry climate at this stage, which is comparable to the aridification of India during the mid- and late Holocene. The intensifying human activity and land-use in the lake catchment since the early Tang Dynasty (∼1.35 cal. ka BP) were associated with the ancient Dian culture within Xingyun’s catchment. The extensive deforestation and development of agriculture in the lake catchment caused heavy soil loss. Our study clearly shows that long-term human activities and land-use change have strongly impacted the evolution of the lake environment and therefore modulated the sediment records of the regional climate in central Yunnan for more than one thousand years. [ABSTRACT FROM AUTHOR]