Hourly or 3-hourly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite products and rain gauge records are used to characterize East Asian summer monsoon rainfall, including spatial patterns in June-August (JJA) mean precipitation amount, frequency, and intensity, as well as the diurnal and semidiurnal cycles. The results show that the satellite products are comparable to rain gauge data in revealing the spatial patterns of JJA precipitation amount, frequency, and intensity, with pattern correlation coefficients for five subregions ranging from 0.66 to 0.94. The pattern correlation of rainfall amount is higher than that of frequency and intensity. Relative to PERSIANN, the TRMM product has a better resemblance with rain gauge observations in terms of both the pattern correlation and rootmean-square error. The satellite products overestimate rainfall frequency but underestimate its intensity. The diurnal (24 h) harmonic dominates subdaily variations of precipitation over most of eastern China. A late-afternoon maximum over southeastern and northeastern China and a near-midnight maximum over the eastern periphery of the Tibetan Plateau are seen in the rain gauge data. The diurnal phases of precipitation frequency and intensity are similar to those of rainfall amount in most regions, except for the middle Yangtze River valley. Both frequency and intensity contribute to the diurnal variation of rainfall amount over most of eastern China. The contribution of frequency to the diurnal cycle of rainfall amount is generally overestimated in both satellite products. Both satellite products capture well the nocturnal peak over the eastern periphery of the Tibetan Plateau and the late-afternoon peak in southern and northeastern China. Rain gauge data over the region between the Yangtze and Yellow Rivers show two peaks, with one in the early morning and the other later in the afternoon. The satellite products only capture the major late-afternoon peak.

Using hourly rain gauge data at more than 30,000 automatic weather stations in China, in conjunction with the Climate Precipitation Center Morphing (CMORPH) precipitation product for the 2008-2010 warm seasons (from May through September), we assess the capability of the probability density function-optimal interpolation (PDF-OI) methods in generating the daily, 0.25°× 0.25°and hourly, 0.1°× 0.1°merged precipitation products between gauge observations and the CMORPH product. We find that error correlation, error variances of gauge and satellite data, and matching strategy in the PDF-OI method are dependent on the spatial and temporal resolutions of the used data. Efforts to improve the parameters and matching strategy for the hourly and 0.1°× 0.1°product have been conducted. These improvements are not only suitable to a high-frequency depiction of no-rain events, but accurately describe the error structures of hourly gauge and satellite fields. The successive merged precipitation algorithm or product is called the original PDF-OI (Orig_PDF-OI) and the improved PDF-OI, respectively. The cross-validation results show that the improved method reduces systematic bias and random errors effectively compared with both the CMORPH precipitation and the Orig_PDF-OI. The improved merged precipitation product over China at hourly, 0.1°resolution is generated from 2008 to 2010. Compared with the Orig_PDF-OI, the improved product reduces the underestimation greatly and has smaller bias and root-mean-square error, and higher spatial correlation. The improved product can better capture some varying features of hourly precipitation in heavy weather events.

Purpose Glioma stem cells (GSC) are a critical therapeutic target of glioblastoma multiforme (GBM). Experimental Design The effects of a G-quadruplex ligand, telomestatin, were evaluated using patient-derived GSCs, non-stem tumor cells (non-GSC), and normal fetal neural precursors in vitro and in vivo. The molecular targets of telomestatin were determined by immunofluorescence in situ hybridization (iFISH) and cDNA microarray. The data were then validated by in vitro and in vivo functional assays, as well as by immunohistochemistry against 90 clinical samples. Results Telomestatin impaired the maintenance of GSC stem cell state by inducing apoptosis in vitro and in vivo. The migration potential of GSCs was also impaired by telomestatin treatment. In contrast, both normal neural precursors and non-GSCs were relatively resistant to telomestatin. Treatment of GSC-derived mouse intracranial tumors reduced tumor sizes in vivo without a noticeable cell death in normal brains. iFISH revealed both telomeric and non-telomeric DNA damage by telomestatin in GSCs but not in non-GSCs. cDNA microarray identified a proto-oncogene, c-Myb, as a novel molecular target of telomestatin in GSCs, and pharmacodynamic analysis in telomestatin-treated tumor-bearing mouse brains showed a reduction of c-Myb in tumors in vivo. Knockdown of c-Myb phenocopied telomestatin-treated GSCs both in vitro and in vivo, and restoring c-Myb by overexpression partially rescued the phenotype. Finally, c-Myb expression was markedly elevated in surgical specimens of GBMs compared with normal tissues. Conclusions These data indicate that telomestatin potently eradicates GSCs through telomere disruption and c-Myb inhibition, and this study suggests a novel GSC-directed therapeutic strategy for GBMs.