A 173-point genetic linkage map of cucumber (Cucumis sativus L.), consisting of 116 SRAPs, 33 RAPDs, 11 SSRs, 9 SCARs, 3 ISSRs, and 1 STS, was constructed using 130 F 2 progeny derived from a narrow cross between line S94 (Northern China open-field type) and line S06 (greenhouse European type). The seven linkage groups spanned 1016 cM with a mean marker interval of 5.9 cM. Using the F 2 population and its F 3 derived families, a total of 38 QTLs were detected on five linkage groups with an LOD threshold of 3.0 for nine fruit-related traits: fruit weight, length, and diameter, fruit flesh thickness, seed-cavity diameter, fruit-stalk length, fruit pedicel length, length/diameter and length/stalk ratio. Of the identified QTLs, fsl4.3 for fruit-stalk length explained the largest portion of phenotypic variation (r 2 ¼ 30%). Several QTLs were detected in the same linkage region in different generations and different seasons. Additionally, several QTLs for various fruit traits were mapped to the same or neighbouring marker intervals, suggesting they are possible character associations for controlling cucumber fruit development.

To identify cellular and molecular changes that driver pediatric low grade glioma (PLGG) progression, we analyzed putative cancer stem cells (CSCs) and evaluated key biological changes in a novel and progressive patient-derived orthotopic xenograft (PDOX) mouse model. Flow cytometric analysis of 22 PLGGs detected CD133+ (<1.5%) and CD15+ (20.7 ± 28.9%) cells, and direct intra-cranial implantation of 25 PLGGs led to the development of 1 PDOX model from a grade II pleomorphic xanthoastrocytoma (PXA). While CSC levels did not correlate with patient tumor progression, neurosphere formation and in vivo tumorigenicity, the PDOX model, IC-3635PXA, reproduced key histological features of the original tumor. Similar to the patient tumor that progressed and recurred, IC-3635PXA also progressed during serial in vivo subtransplantations (4 passages), exhibiting increased tumor take rate, elevated proliferation, loss of mature glial marker (GFAP), accumulation of GFAP−/Vimentin+ cells, enhanced local invasion, distant perivascular migration, and prominent reactive gliosis in normal mouse brains. Molecularly, xenograft cells with homozygous deletion of CDKN2A shifted from disomy chromosome 9 to trisomy chromosome 9; and BRAF V600E mutation allele frequency increased (from 28% in patient tumor to 67% in passage III xenografts). In vitro drug screening identified 2/7 BRAF V600E inhibitors and 2/9 BRAF inhibitors that suppressed cell proliferation. In summary, we showed that PLGG tumorigenicity was low despite the presence of putative CSCs, and our data supported GFAP−/Vimentin+ cells, CDKN2A homozygous deletion in trisomy chromosome 9 cells, and BRAF V600E mutation as candidate drivers of tumor progression in the PXA xenografts.

To improve the efficiency of breeding cucumber in China, we previously mapped QTL for most fruit-and flower-related traits of this species. Here, we mapped QTLs for six plant architecture traits including lateral branch number (LBN), lateral branch total length (LBTL), main-stem length (MSL), internode length (INL), main-stem diameter (MSD), and petiole length (PL) were detected in greenhouse environments. In total, 14 QTLs were identified for the six traits (LBN, 3; LBTL, 2; MSL, 3; INL, 2; MSD, 2; and PL, 2) with additive heritability of individual QTL ranging from 1.6% to 29.5%. Five QTLs for four traits (LBN, LBTL, MSL, and INL) were observed to have significant (P ≤ 0.05) QTL × environment interaction effects. The broadsense heritability for the six traits ranged from 8.5% to 47.0%. The QTL information presented in this research, together with the data in our previous study on the fruit-and flower-related traits, will facilitate the breeding of elite cucumber cultivars by marker-assisted selection in China.

In this paper, a miniature low-power Electrocardiogram (ECG) signal processing application specific integrated circuit (ASIC) chip is proposed. This chip provides multiple critical functions for ECG analysis using a systematic wavelet transform algorithm and a novel SRAM-based ASIC architecture, while achieves low cost and high performance. Using 0.18 µm CMOS technology and 1 V power supply, this ASIC chip consumes only 29 µW and occupies an area of 3 mm(2). This on-chip ECG processor is highly suitable for reliable real-time cardiac status monitoring applications.