Influence of spin fluctuations on the superconducting transition temperature and resistivity in the t-J model at large N

Spin fluctuations enter the calculation of the superconducting transition temperature T$_c$ only in the next-to-leading order (i.e., in O(1/N$^2$) of the 1/N expansion of the t-J model. We have calculated these terms and show that they have only little influence on the value of T$_c$ obtained in the leading order O(1/N) in the optimal and overdoped region, i.e., for dopings larger than the instability towards a flux phase. This result disagrees with recent spin-fluctuation mediated pairing theories. The discrepancies can be traced back to the fact that in our case the coupling between electrons and spins is determined by the t-J model and not adjusted and that the spin susceptibility is rather broad and structureless and not strongly peaked at low energies as in spin-fluctuation models. Relating T$_c$ and transport we show that the effective interactions in the particle-particle and particle-hole channels are not simply related within the 1/N expansion by different Fermi surface averages of the same interactin as in the case of phonons or spin fluctuations. As a result, we find that large values for T$_c$ and rather small scattering rates in the normal state as found in the experiments can easily be reconciled with each other. We also show that correlation effects heavily suppress transport relaxation rates relative to quasiparticle relaxation rates in the case of phonons but not in the case of spin fluctuations.Comment: 16 pages, 10 figures, will appear in Phys. Rev.

Selection of Reference Genes for RT-qPCR Studies in Different Organs of Rice Cultivar BRS AG Submitted to Recurrent Saline Stress.

Quantitative real-time polymerase chain reactions (RT-qPCR) have become one of the most widely used methods for analyzing gene expression, provided suitable reference genes are available to normalize the data. RNA was isolated from leaves, grain, rachises and sheaths of rice (Oryza sativa L. cv. BRS AG) submitted to different saline stress events for seven days, and expression analysis was carried out by RT-qPCR. Expression levels of ten candidate reference genes were assessed, actin11 (ACT11), ubiquitin conjugating enzyme E2 (UBC-E2), eukaryotic elongation factor1-a (Eef-1a), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), B-tubulin (B-Tub), eukaryotic initiation factor 4a (Eif-4-a), ubiquitin10 (UBQ10), ubiquitin5 (UBQ5), aquaporin TIP41 (TIP41-like). Gene expression stability was calculated using the common statistical algorithms geNorm, BestKeeper and ?Ct method, NormFinder and RefFinder. The most stably expressed genes were UBC2E and GAPDH for leaves, UBQ5 and UBQ10 for sheaths, TIP41 and UBQ10 for rachises, and TIP41 and cyclophilin for grain. Gene expression of triose phosphate translocator (TPT1), ADP-glucose transporter (BT1-1), choline monooxygenase (CMO) was used to validate the selected reference genes. The results highlighted the importance of using suitable reference gene to normalize gene expression data in rice plants

DNA Methods to Identify Missing Persons

Human identification by DNA analysis in missing person cases typically involves comparison of two categories of sample: a reference sample, which could be obtained from intimate items of the person in question or from family members, and the questioned sample from the unknown person-usually derived from the bones, teeth, or soft tissues of human remains. Exceptions include the analysis of archived tissues, such as those held by hospital pathology departments, and the analysis of samples relating to missing, but living persons. DNA is extracted from the questioned and reference samples and well-characterized regions of the genetic code are amplified from each source using the Polymerase Chain Reaction (PCR), which generates sufficient copies of the target region for visualization and comparison of the genetic sequences obtained from each sample. If the DNA sequences of the questioned and reference samples differ, this is normally sufficient for the questioned DNA to be excluded as having come from the same source. If the sequences are identical, statistical analysis is necessary to determine the probability that the match is a consequence of the questioned sequence coming from the same individual who provided the reference sample or from a randomly occurring individual in the general population. Match probabilities that are currently achievable are frequently greater than 1 in 1 billion, allowing identity to be assigned with considerable confidence in many cases