Cohesive/Adhesive strengths of CsOH-chemisorbed SS304 surfaces

During the Fukushima Daiichi Nuclear Power Plant (1F) accident, volatile radioactive fission products (FPs) such as Cs-137 were released, which significantly influenced mid- to long-term decommissioning strategies. A substantial amount of the remaining cesium in the pressure vessel may have deposited onto the 304 stainless steel (SS304) steam separators and dryers. This deposited cesium presents a safety hazard during 1F’s decommissioning, as it can generate radioactive dust and complicate waste storage. However, the cohesive and adhesive strengths of CsOH-chemisorbed oxide scales, crucial for understanding the release of cesium-bearing particles from SS304 surfaces, remain undefined. In this study, we explore how CsOH chemisorption affects the cohesive and adhesive strengths between oxide scales and SS304 substrates using a scratch tester. Our tests revealed that cracks formed at approximately the same load, but the overall cohesive strength of the oxide scales decreased following CsOH chemisorption. Furthermore, the transition from cracks to bulk separation occurred more rapidly in CsOH-chemisorbed SS304 substrates, especially those with lower silicon content. Finally, we found that adhesive failure could not be achieved even at 70 N, suggesting that the deposited cesium cannot be completely removed from SS304 during the decommissioning of 1F.</p

Solution-Synthesized In₄SnSe₄ Semiconductor Microwires with a Direct Band Gap

Semiconductor materials having direct band gaps that overlap well with the solar spectrum are important for a variety of applications in solar energy conversion and optoelectronics. Here, we identify the ternary chalcogenide In₄SnSe₄ as a direct band gap semiconductor having a band gap of approximately 1.6 eV. In₄SnSe₄, which contains isolated tetrahedral [SnIn₄]⁸⁺ clusters embedded in an In–Se framework, was synthesized by precipitation from solution at 300 °C. The In₄SnSe₄ product consists of microwires having lengths of approximately 5–20 μm and widths of approximately 100–400 nm. Band structure calculations predict a direct electronic band gap of approximately 2.0 eV. Diffuse reflectance UV–visible spectroscopy qualitatively validates the predicted direct band gap, yielding an observed optical band gap of 1.6 eV

Interleukin-6 Levels in Women with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis

<div><p>Background</p><p>The change of serum interleukin-6(IL-6) levels in women with polycystic ovary syndrome (PCOS), as well as the relations between IL-6 levels and body mass index (BMI), insulin resistance(IR) and androgen status of PCOS patients, are not fully understood.</p><p>Methods</p><p>A literature search was performed in October 2015 using PubMed, Embase and the Cochrane Library databases to identify studies. Random-effects model was used to estimate the standardized mean differences (SMDs) with 95% confidence intervals (CIs).</p><p>Results</p><p>Twenty articles with 25 case-control studies included 1618 women (922 PCOS patients and 696 controls) were included in this study. IL-6 levels in controls were significantly lower than that of PCOS patients (SMD = 0.78, 95%CI = 0.41–1.16, P<0.001), with significant heterogeneity across studies (<i>I</i>^<i>2</i> = 91% and P<0.001). Meta-regression analysis model indicated IR status was the main source of heterogeneity (<i>P</i> = 0.005). Results from group analysis suggested that high IL-6 levels in PCOS were significantly associated with Homeostasis Model Assessment of Insulin Resistance (HOMA2-IR) ratio and total testosterone ratio (T ratio), and was found in both lean and obese women with PCOS. Cumulative meta-analysis results indicated the total effect size (SMD) had tend to be stable since 2012(0.79 to 0.92).</p><p>Conclusions</p><p>A high IL-6 level is not an intrinsic characteristic of PCOS, but may be a useful monitoring biomarker for the treatment of PCOS.</p></div

Association between High Serum Homocysteine Levels and Biochemical Characteristics in Women with Polycystic Ovarian Syndrome: A Systematic Review and Meta-Analysis

<div><p>Background</p><p>Elevated homocysteine levels have been observed in previous studies of PCOS; however, the nature of the associations between high homocysteine levels and the biochemical characteristics of polycystic ovarian syndrome (PCOS)—such as obesity, insulin resistance (IR), and androgen levels—is still uncertain.</p><p>Methods</p><p>A systematic search was conducted electronically up to December 28, 2015 using specific eligibility criteria. Standardized mean difference (SMD) and the corresponding 95% confidence intervals (95% CIs) were used as a measure of effect size.</p><p>Results</p><p>A total of 34 studies (with 1,718 cases and 1,399 controls) of homocysteine levels in PCOS were pooled in this meta-analysis. Significantly lower homocysteine levels were found in controls than in PCOS patients (SMD = 0.895, 95% CI = 0.643–1.146, <i>P</i><0.001; <i>I</i>^<i>2</i> = 90.4% and <i>P</i><0.001 for heterogeneity), regardless of the degree of obesity, IR, or androgen levels. Homocysteine levels in non-IR PCOS patients were significantly lower than those of PCOS patients with IR (SMD = 0.69, 95% CI = 0.37–1.01, <i>P</i><0.01; <i>I</i>^<i>2</i> = 0% and <i>P</i> = 0.50 for heterogeneity). However, metformin treatment did not appear to cause any significant change in the homocysteine levels of PCOS patients (SMD = –0.17, 95% CI = –1.10–0.75, <i>P</i> = 0.71; <i>I</i>^<i>2</i> = 92% and <i>P</i><0.01 for heterogeneity).</p><p>Conclusions</p><p>High homocysteine levels in women with PCOS are not related to degree of obesity, IR, or androgen levels. Metformin treatment cannot decrease the homocysteine levels in PCOS patients.</p></div

Forest plot of the pooled quantitative synthesis and subgroup analysis stratified by HOMA-IR ratio.

<p>Forest plot of the pooled quantitative synthesis and subgroup analysis stratified by HOMA-IR ratio.</p

Univariate meta-regression analysis for the potential variables between studies.

<p>Univariate meta-regression analysis for the potential variables between studies.</p

Characteristics of included studies in meta-analysis.

<p>Characteristics of included studies in meta-analysis.</p

Forest plot of the influence of IR on homocysteine levels.

<p>A: PCOS patients with IR were compared with non-IR patients. B: Influence of metformin treatment on homocysteine levels.</p

Characteristics of studies included in the meta-analysis.

<p>Characteristics of studies included in the meta-analysis.</p

Cumulative meta-analysis.

<p>Cumulative meta-analysis.</p