Contribution of electronic structure to the large thermoelectric power in layered cobalt oxides

With a strong help of high-resolution photoemission spectroscopy we demonstrate in this paper that the large thermoelectric power observed in the layered cobalt oxides, such as Ca_3Co_4O_9, Na_0.6CoO_2, and Bi_2Sr_2Co_2O_9, can be well accounted for with the Boltzmann-type metallic electrical conduction. An intense peak with 1.5–2 eV in width was observed in the photoemission spectra with its center at 1.0 eV below the Fermi level E_F in these compounds. The density of states at E_F is finite but negligibly small at room temperature, because E_F is located near the high-energy edge of this narrow band. We calculated thermoelectric power S using the Boltzmann transport equation with the electronic structure near E_F determined by the photoemission measurement. The calculated S shows fairly good consistency with the measured value both in its magnitude and the temperature dependence.journal articl

ゲンチョ チトクローム P4501A1 イデンシ タケイ ノ キツエン シュウカン オヨビ ケツエキガクテキ ケンサ ショケン ニ アタエル エイキョウ

予防医学上重要な領域である喫煙対策において,個々の素因に適合した1次予防の方策を探ることを目的とし,肺癌発生と関連があるとされる CYP1A1遺伝子型が,喫煙習慣や血液学的検査所見にどのような影響を及ほしているかを某製造業事業部の男性社員391名を対象に検討を行い,以下の結果を得た。(1) CYP1A1遺伝子型と喫煙習慣には,統計学的に有意な関連はみられなかった。(2) 喫煙者においてVal対立遺伝子をもつ個体の白血球数はVal対立遺伝子をもたない個体の白血球数に比べて有意に増加していた。(3) 重回帰分析において,喫煙者の白血球数に CYP1A1遺伝子型および1日喫煙本数が有意に影響を与えていた。また,CYP1A1遺伝子型と赤血球数,ヘモグロビン量,ヘマトクリット値,MCV,MCH,MCHCに有意な影響を与えていなかった。 CYP1A1遺伝子型と血液学的検査所見の関連を検討した報告はみあたらず,今回の結果および白血球数増加者に癌や心疾患が多いという疫学的報告や,喫煙者の白血球数増加と呼吸機能低下が関連している報告等と考えあわせると,白血球数をマーカーにすることによって,これらの疾患に対する予防に寄与する可能性があると考えられる。journal articl

Clinical Features in Intrahepatic Cholestasis : Especially in Cases of Acute Types

Article信州医学雑誌 18(2): 388-397(1969)journal articl

Improved measurement of CP-violation parameters sin⁡2ϕ1 and |λ|, B meson lifetimes, and B0-B̅0 mixing parameter Δmd

journal articl

Strongest functional effectors in RNAi screens.

‡<p>GWAS listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s008" target="_blank">Table S1</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s009" target="_blank">S2</a>.</p>*<p>blood levels of LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglycerides; TC, total cholesterol; CAD, coronary artery disease; MI, myocardial infarction.</p>†<p>Strongest effector siRNAs (upregulators, red; downregulators, blue) in the two functional assays analyzed. For complete results, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s011" target="_blank">Table S4</a>.</p>#<p>adapted from <a href="http://www.genecards.org" target="_blank">www.genecards.org</a>.</p

Selected results of secondary assays.^*

*<p>Summarized results from secondary assays for 29 exemplary effector genes. For full datasets, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s014" target="_blank">Table S7</a>. For RNAi-screens, + (increase) and − (decrease) denote genes validated by two independent siRNAs, (+) and (−) genes scoring with 1 siRNA, and (−/+) genes where one siRNA scored in opposite directions each. n.s., not significant; n.d., not determined.</p

RNAi–Based Functional Profiling of Loci from Blood Lipid Genome-Wide Association Studies Identifies Genes with Cholesterol-Regulatory Function

<div><p>Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease. However, GWAS only rarely reveal information on the exact genetic elements and pathogenic events underlying an association. In order to extract functional information from genomic data, strategies for systematic follow-up studies on a phenotypic level are required. Here we address these limitations by applying RNA interference (RNAi) to analyze 133 candidate genes within 56 loci identified by GWAS as associated with blood lipid levels, coronary artery disease, and/or myocardial infarction for a function in regulating cholesterol levels in cells. Knockdown of a surprisingly high number (41%) of trait-associated genes affected low-density lipoprotein (LDL) internalization and/or cellular levels of free cholesterol. Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions. Using a set of secondary assays we demonstrate for a number of genes without previously known lipid-regulatory roles (e.g. CXCL12, FAM174A, PAFAH1B1, SEZ6L, TBL2, WDR12) that knockdown correlates with altered LDL–receptor levels and/or that overexpression as GFP–tagged fusion proteins inversely modifies cellular cholesterol levels. By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.</p> </div

Comparison of multiparametric datasets for neighboring genes within lipid-trait-associated loci.

<p>Shown are parameters “total cellular intensity” (“total”) of the two strongest effector siRNAs/gene and relative genomic position of lead SNPs (arrowheads) for seven (A–G) selected lipid-trait/CAD/MI loci in which multiple neighboring candidate genes (±50 kB up-/downstream of lead SNP) were functionally analyzed (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s002" target="_blank">Figure S2</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s011" target="_blank">Table S4</a> for comprehensive datasets). Phenotypes (red, increasing; blue, decreasing) meeting statistical criteria as described in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#s3" target="_blank">Materials and Methods</a> are framed in orange.</p

Functional profiling of lipid-trait/CAD/MI associated genes by cell-based RNAi.

<p>(A) Workflow of this study. (B,C) Profiling of lipid-trait associated genes for a cholesterol-regulating function in cells was performed by monitoring LDL-uptake (upper panels) and free perinuclear cholesterol (FC; lower panels) in siRNA-knockdown cells (for details, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338-Bartz1" target="_blank">[30]</a>). Shown are automatically acquired images of Hela-Kyoto cells cultured and reverse siRNA transfected on cell microarrays for 48 h with control siRNAs (B) or indicated siRNAs targeting selected candidate genes increasing (red) or decreasing (blue) typical cellular phenotypes (C; see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen-1003338-g002" target="_blank">Figure 2</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#s3" target="_blank">Materials and Methods</a> for details). Arrows denote selected compartments representative for respective heatmaps (see text). Bars = 20 µm.</p

Multiparametric analysis and clustering of functional effector genes.

<p>(A) Functional consequences upon knockdown of each candidate gene (using 3–5 different siRNAs/gene) were quantified from microscopic images with regard to seven phenotypic parameters: total cellular LDL-signal; LDL concentration and number of cellular structures; total free cholesterol (FC) signal; and FC concentration, area and number of cellular structures. Shown are heatmaps for 37 out of 55 most pronounced functional effector genes that according to parameter “total cellular intensity” (“total”) of the two strongest effector siRNAs/gene were clustered into five distinct functional groups (B–F) (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s002" target="_blank">Figure S2</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#pgen.1003338.s011" target="_blank">Table S4</a> for comprehensive datasets). Phenotypes (red, increasing; blue, decreasing) meeting statistical criteria as described in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003338#s3" target="_blank">Materials and Methods</a> are framed in orange.</p