Facile preparation of concentrated silver and copper heat transfer nanocolloids

Concentrated, yet stable silver- and copper-in-water nanocolloids are prepared using a novel method combining formation of a metal ammine complex and use of a strong NaBH4 reductant. Maximum solid contents of the stable silver and copper nanofluids are 2000 and 5000 ppm (reported as mass fractions), respectively. The metallic nanoparticles are reduced in micellar microreactors, favoring formation of small nanoparticles. Use of stable metal ammine complexes ([Ag(NH3)2]+ and [Cu(NH3)4(H2O)2]2+) as metal ion sources prevent the formation of sparingly-soluble metal salts and thus, aid the nanocolloid synthesis. Several different stabilizers and combinations of them are tested for nanofluid synthesis: anionic sodium dodecyl sulfate, polymeric polyvinylpyrrolidone, sodium citrate, nonionic sorbitan trioleate and polysorbate 20. The particle sizes and size distributions are studied using dynamic laser scattering and transmission electron microscopy. Stability of the nanofluids is assessed by zeta potential measurements, repetitive particle size measurements and visual observations. The average particle sizes of the silver and copper nanofluids with optimized surfactants are < 20 nm and ~40 nm, respectively, and the fluids with optimized stabilizer compositions are stable over the storing period of a month. Specific heat and thermal conductivities of the fluids are measured using differential scanning calorimetry and modified transient plane source technique (TCi Thermal conductivity analyzer), respectively. In addition, the nanofluid viscosities are measured in order to assess the usability of the nanofluids in convective heat transfer. The chemistry of stabilizers is found to have a significant impact on the viscosity of nanofluids. Commonly used polymeric polyvinylpyrrolidone stabilizer produces viscous fluids, whereas the viscosities of the fluids stabilized with small size surfactants are close to that of water.Papers presented to the 12th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Costa de Sol, Spain on 11-13 July 2016

Sequential MyD88-Independent and -Dependent Activation of Innate Immune Responses to Intracellular Bacterial Infection

AbstractMicrobial infections induce chemokine and cytokine cascades that coordinate innate immune defenses. Infection with the intracellular bacterial pathogen Listeria monocytogenes induces CCR2-dependent monocyte recruitment and activation, an essential response for host survival. Herein we show that invasive L. monocytogenes, but not killed or noninvasive bacteria, induce secretion of MCP-1, the requisite chemokine for monocyte recruitment. Induction of MCP-1, but not TNF or IL-12, following L. monocytogenes infection is MyD88 independent. Consistent with these results, MyD88 deficiency does not impair monocyte recruitment to L. monocytogenes infected spleens, but prevents monocyte activation. Our results indicate that distinct microbial signals activate innate immune responses in an ordered, step-wise fashion, providing a mechanism to specify and modulate antimicrobial effector functions

Prospects of breeding high-quality rice using post-genomic tools

The holistic understanding derived from integrating grain quality and sensory research outcomes in breeding high-quality rice in the light of post-genomics resources has been synthesized

Introgression of a functional epigenetic OsSPL14WFP allele into elite indica rice genomes greatly improved panicle traits and grain yield

Rice yield potential has been stagnant since the Green Revolution in the late 1960s, especially in tropical rice cultivars. We evaluated the effect of two major genes that regulate grain number, Gn1a/OsCKX2 and IPA1/WFP/OsSPL14, in elite indica cultivar backgrounds. The yield-positive Gn1a-type 3 and OsSPL14WFP alleles were introgressed respectively through marker-assisted selection (MAS). The grain numbers per panicle (GNPP) were compared between the recipient allele and the donor allele groups using segregating plants in BC3F2 and BC3F3 generations. There was no significant difference in GNPP between the two Gn1a alleles, suggesting that the Gn1a-type 3 allele was not effective in indica cultivars. However, the OsSPL14WFP allele dramatically increased GNPP by 10.6–59.3% in all four different backgrounds across cropping seasons and generations, indicating that this allele provides strong genetic gain to elite indica cultivars. Eventually, five high-yielding breeding lines were bred using the OsSPL14WFP allele by MAS with a conventional breeding approach that showed increased grain yield by 28.4–83.5% (7.87–12.89 t/ha) vis-à-vis the recipient cultivars and exhibited higher yield (~64.7%) than the top-yielding check cultivar, IRRI 156 (7.82 t/ha). We demonstrated a strong possibility to increase the genetic yield potential of indica rice varieties through allele mining and its application

Additional file 8: Table S4. of Development and validation of allele-specific SNP/indel markers for eight yield-enhancing genes using whole-genome sequencing strategy to increase yield potential of rice, Oryza sativa L.

Markers for Fluidigm SNP genotyping platform. (DOC 36 kb

Additional file 3: Figure S3. of Development and validation of allele-specific SNP/indel markers for eight yield-enhancing genes using whole-genome sequencing strategy to increase yield potential of rice, Oryza sativa L.

Screening of ST12-specific DNA variation in the OsSPL14 promoter region through WGS data analysis. Note that the OsSPL14 gene lay on the opposite strand of the reference sequence. The reference genome sequence was shown at the bottom of the image. Screen-captured image of IGV software showed an ST12-specific SNP located at the Chr 8: 25282790 nucleotide position (IRGSP-1.0). (DOC 77 kb

Additional file 2: Figure S2. of Development and validation of allele-specific SNP/indel markers for eight yield-enhancing genes using whole-genome sequencing strategy to increase yield potential of rice, Oryza sativa L.

Marker designing schemes for SNP-type polymorphisms. (A) Schematic presentation of the tetra-primer PCR method for designing Gn1a-17SNP marker. The target SNPs, G and A, are highlighted in each genome and its surrounding sequences are represented with the allele-specific primers (pink, G allele-specific primer; green, A allele-specific primer). Actually, the SNP is determined by the last nucleotide (filled triangle) of the allele-specific primer. Proper annealing of the last nucleotide of the primer (the 3’ end) is very important for PCR amplification because Taq DNA polymerase start polymerization at that nucleotide through adding dNTP. For instance, the A allele-specific primer (green) can be annealed to the G allele genome but the efficiency of DNA polymerization will be very low because of no annealing of the 3’ end of the primer, resulting in no PCR band or a very weak band. To increase allele specificity, we gave an artificial mismatched nucleotide near the 3’ end (second or third nucleotide from the 3’ end) of the allele-specific primer (lowercase with underlined nucleotide in Figure). Primer combination of the Gn1a-17SNP marker, its predicted band size, and deduced gel image depending on genotypes were presented. (B) Schematic presentation of the separated allele-specific PCR method for designing the SPIKE-01SNP marker. To discriminate G/A SNP, the SPIKE-01SNP marker consisted of two PCRs (PCR #1, SPIKE-01SNP-GF/R; PCR #2, SPIKE-01SNP-AF/R). Between the G allele-specific primer (pink) and A allele-specific primer (green), only the last nucleotide of each allele-specific primer (filled triangle) is different. To increase allele specificity, the artificial mismatched nucleotide near the 3’ end was given in the allele-specific primer. PCRs were performed with each allele-specific primer and common reverse primer. Primer combinations of the SPIKE-01SNP marker, its predicted band size, and deduced gel image depending on genotypes were presented. (C) The effect of artificial mismatched nucleotide near the 3’ end of the allele-specific primer. As an example, the SPIKE-01SNP marker was designed without the artificial mismatched nucleotide in allele-specific primers that were shown on the gel image. Non-allele-specific PCR amplifications were obtained with these primers. Using artificial mismatch, we obtained allele-specific PCR amplifications (Fig. 6a). (DOC 240 kb

Additional file 5: Table S1. of Development and validation of allele-specific SNP/indel markers for eight yield-enhancing genes using whole-genome sequencing strategy to increase yield potential of rice, Oryza sativa L.

Summary of Fluidigm SNP genotyping results. (DOC 90 kb

Additional file 8: Table S4. of Development and validation of allele-specific SNP/indel markers for eight yield-enhancing genes using whole-genome sequencing strategy to increase yield potential of rice, Oryza sativa L.

Markers for Fluidigm SNP genotyping platform. (DOC 36 kb

Additional file 1: Figure S1. of Development and validation of allele-specific SNP/indel markers for eight yield-enhancing genes using whole-genome sequencing strategy to increase yield potential of rice, Oryza sativa L.

Screening of DNA polymorphisms in the Gn1a gene using WGS data. Sequencing reads were aligned to the reference genome sequence (IRGSP-1.0). Note that the Gn1a gene lay on the opposite strand of the reference sequence. Screen-captured images of IGV software showed nucleotide variations that were used for marker development. (A) Three SNPs located in the Gn1a promoter region were shown with their genomic location on chromosome 1. Chr1: 5276405, Chr1: 5276521, and Chr1: 5276591 SNPs were used for Gn1a-17SNP/Gn1a-17SNP-FD, Gn1a-18SNP-FD, and Gn1a-19SNP-FD markers, respectively. (B) About a 70-bp deletion (red circles) near the 3’ UTR of Gn1a was found in varieties NSIC Rc158 and NSIC Rc238. This indel was used for designing the Gn1a-indel3 marker. (DOC 178 kb