Refinement of Light-Responsive Transcript Lists Using Rice Oligonucleotide Arrays: Evaluation of Gene-Redundancy

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics

Retrospective analyses of cisplatin-based doublet combination chemotherapy in patients with advanced gastric cancer

<p>Abstract</p> <p>Backgrounds</p> <p>Cisplatin-based chemotherapy, in combination with fluoropyrimidines or taxanes, have demonstrated efficacy against advanced gastric cancer (AGC). This retrospective study was performed with the data obtained from our cancer chemotherapy registry and eight another cancer centers.</p> <p>Methods</p> <p>In 2008, a total of 283 AGC patients were treated with cisplatin-based doublet chemotherapy in the first-line setting: capecitabine plus cisplatin (XP, n = 77), S-1 plus cisplatin (SP, n = 97), taxanes (docetaxel, paclitaxel) plus cisplatin (TP, n = 72), and 5-fluorouracil plus platinum (FP, n = 37). The primary endpoint of this study was overall survival (OS) and the secondary endpoints were safety, response rate and progression-free survival (PFS).</p> <p>Results</p> <p>The median age was 54 years with a range of 28-78 years and median delivered number of chemotherapy cycles were XP: 4, SP: 5, TP: 5 and FP: 5, respectively. Objective tumor responses (38%; 95% CI, 32-43%) were 40% for XP, 42% for SP, 36% for DP, and 24% for FP. The estimated median PFS was 4.5 months (95% CI, 3.6-5.4 months) and the median OS was 12.3 months (95% CI, 10.8-13.7 months). No statistically significant difference was found between each regimen used as first-line chemotherapy. At multivariate analysis, independent prognostic parameters for OS were prior gastrectomy, peritoneal dissemination, performance status and hemoglobin level</p> <p>Conclusion</p> <p>All of the cisplatin-based doublet chemotherapy regimens appear to be active as first-line chemotherapy for AGC. With better patient selection according to clinical parameters and molecular markers, clinical outcomes of AGC patients in first-line setting can be improved.</p

Identification and Functional Analysis of Light-Responsive Unique Genes and Gene Family Members in Rice

Functional redundancy limits detailed analysis of genes in many organisms. Here, we report a method to efficiently overcome this obstacle by combining gene expression data with analysis of gene-indexed mutants. Using a rice NSF45K oligo-microarray to compare 2-week-old light- and dark-grown rice leaf tissue, we identified 365 genes that showed significant 8-fold or greater induction in the light relative to dark conditions. We then screened collections of rice T-DNA insertional mutants to identify rice lines with mutations in the strongly light-induced genes. From this analysis, we identified 74 different lines comprising two independent mutant lines for each of 37 light-induced genes. This list was further refined by mining gene expression data to exclude genes that had potential functional redundancy due to co-expressed family members (12 genes) and genes that had inconsistent light responses across other publicly available microarray datasets (five genes). We next characterized the phenotypes of rice lines carrying mutations in ten of the remaining candidate genes and then carried out co-expression analysis associated with these genes. This analysis effectively provided candidate functions for two genes of previously unknown function and for one gene not directly linked to the tested biochemical pathways. These data demonstrate the efficiency of combining gene family-based expression profiles with analyses of insertional mutants to identify novel genes and their functions, even among members of multi-gene families

Engineering Thermal Transport across Layered Graphene-MoS2 Superlattices.

Layering two-dimensional van der Waals materials provides a high degree of control over atomic placement, which could enable tailoring of vibrational spectra and heat flow at the sub-nanometer scale. Here, using spatially resolved ultrafast thermoreflectance and spectroscopy, we uncover the design rules governing cross-plane heat transport in superlattices assembled from monolayers of graphene (G) and MoS2 (M). Using a combinatorial experimental approach, we probe nine different stacking sequences, G, GG, MG, GGG, GMG, GGMG, GMGG, GMMG, and GMGMG, and identify the effects of vibrational mismatch, interlayer adhesion, and junction asymmetry on thermal transport. Pure G sequences display evidence of quasi-ballistic transport, whereas adding even a single M layer strongly disrupts heat conduction. The experimental data are described well by molecular dynamics simulations, which include thermal expansion, accounting for the effect of finite temperature on the interlayer spacing. The simulations show that an increase of ∼2.4% in the layer separation of GMGMG, relative to its value at 300 K, can lead to a doubling of the thermal resistance. Using these design rules, we experimentally demonstrate a five-layer GMGMG superlattice "thermal metamaterial" with an ultralow effective cross-plane thermal conductivity comparable to that of air

Engineering Thermal Transport across Layered Graphene-MoS2 Superlattices.

Layering two-dimensional van der Waals materials provides a high degree of control over atomic placement, which could enable tailoring of vibrational spectra and heat flow at the sub-nanometer scale. Here, using spatially resolved ultrafast thermoreflectance and spectroscopy, we uncover the design rules governing cross-plane heat transport in superlattices assembled from monolayers of graphene (G) and MoS2 (M). Using a combinatorial experimental approach, we probe nine different stacking sequences, G, GG, MG, GGG, GMG, GGMG, GMGG, GMMG, and GMGMG, and identify the effects of vibrational mismatch, interlayer adhesion, and junction asymmetry on thermal transport. Pure G sequences display evidence of quasi-ballistic transport, whereas adding even a single M layer strongly disrupts heat conduction. The experimental data are described well by molecular dynamics simulations, which include thermal expansion, accounting for the effect of finite temperature on the interlayer spacing. The simulations show that an increase of ∼2.4% in the layer separation of GMGMG, relative to its value at 300 K, can lead to a doubling of the thermal resistance. Using these design rules, we experimentally demonstrate a five-layer GMGMG superlattice "thermal metamaterial" with an ultralow effective cross-plane thermal conductivity comparable to that of air