Catalytic chemical vapor deposition synthesis of carbon nanotubes from methane on SiO supported Fe and Fe−Ni catalysts

Influences of operating conditions on the production of carbon nanotubes (CNTs) were studied using Fe and Fe-Ni bimetallic catalysts supported on silicon monoxide (SiO). The catalysts were prepared in three steps: (1) impregnation of SiO powders with ferric nitride or combinations of ferric and nickel nitrides, (2) oxidation of nitrides in an air stream, and (3) grinding the powders obtained. CNTs were successfully synthesized by catalytic CVD using NH₃/CH₄ mixtures in a horizontal tubular flow reactor. The following process parameters were varied to investigate their effects on the growth rates of CNTs. The morphologies of catalysts and product CNTs were observed by scanning electron microscope (SEM). • The particle size of SiO, • metal composition, • metal loading, • temperature for catalyst oxidation, • extent of grinding of catalysts, • NH₃ pretreatment time, • reaction temperature for CNT growth, • reaction time, and • NH₃/CH₄ feed ratio. Two different average sizes of SiO particles, 8 μm and 44 μm, were compared based on the growth of CNTs in 5 min. Catalysts supported on 44 μm average sized SiO particles demonstrated higher yields when they were not pretreated in an NH₃ stream. When 1 wt% Fe was loaded, aligned CNTs were formed, and a highest growth rate per unit mass of catalyst was observed. The range of oxidation temperature to achieve highest catalyst activities depended on metals and metal contents: 600 - 750°C for 1 wt% Fe, 450 - 600°C for 3 wt% Fe, and 750 - 900°C for Fe-Ni. Grinding catalysts for at least 3 minutes increased the growth rate of CNTs by approximately 40 percent. The growth of CNTs was enhanced when no NH₃ pretreatment of catalysts was carried out, regardless of metals and metal contents. However, CNTs did not grow appreciably from methane without ammonia. An NH₃/CH₄ feed ratio of 0.15 - 0.25 was observed to yield highest growth rates. The reaction temperature to achieve highest CNT growth rates was found to be in the range between 990 and 1000 °C. The growth of CNTs was not linear but decreased with reaction time

Heme-dependent autophosphorylation of a heme sensor kinase, ChrS, from Corynebacterium diphtheriae reconstituted in proteoliposomes

AbstractCorynebacterium diphteriae employs the response regulator, ChrA, and the sensor kinase, ChrS, of a two-component signal transduction system to utilize host heme iron. Although ChrS is predicted to encode a heme sensor, the sensing mechanism remains to be characterized. In this report, ChrS expressed in Eshcherichia coli membranes was solubilized and purified using decylmaltoside. ChrS protein incorporated into proteoliposomes catalyzed heme-dependent autophosphorylation by ATP. Other metalloporphyrins and iron did not stimulate kinase activity. The UV–Vis spectrum of hemin in the ChrS–proteoliposomes indicated that heme directly interacts with ChrS. This is the first functional reconstitution of a bacterial heme-sensing protein

Antidepressant Response and Stress Resilience Are Promoted by CART Peptides in GABAergic Neurons of the Anterior Cingulate Cortex

[Background] A key challenge in the understanding and treatment of depression is identifying cell types and molecular mechanisms that mediate behavioral responses to antidepressant drugs. Because treatment responses in clinical depression are heterogeneous, it is crucial to examine treatment responders and nonresponders in preclinical studies. [Methods] We used the large variance in behavioral responses to long-term treatment with multiple classes of antidepressant drugs in different inbred mouse strains and classified the mice into responders and nonresponders based on their response in the forced swim test. Medial prefrontal cortex tissues were subjected to RNA sequencing to identify molecules that are consistently associated across antidepressant responders. We developed and used virus-mediated gene transfer to induce the gene of interest in specific cell types and performed forced swim, sucrose preference, social interaction, and open field tests to investigate antidepressant-like and anxiety-like behaviors. [Results] Cartpt expression was consistently upregulated in responders to four types of antidepressants but not in nonresponders in different mice strains. Responder mice given a single dose of ketamine, a fast-acting non–monoamine-based antidepressant, exhibited high CART peptide expression. CART peptide overexpression in the GABAergic (gamma-aminobutyric acidergic) neurons of the anterior cingulate cortex led to antidepressant-like behavior and drove chronic stress resiliency independently of mouse genetic background. [Conclusions] These data demonstrate that activation of CART peptide signaling in GABAergic neurons of the anterior cingulate cortex is a common molecular mechanism across antidepressant responders and that this pathway also drives stress resilience

Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells

Deep LearningとALS iPS細胞を用いた疾患予測テクノロジー --人工知能のALS検知・診断への応用--. 京都大学プレスリリース. 2021-02-24.Deep learning amyotrophic lateral sclerosis by taking pictures. 京都大学プレスリリース. 2021-02-24.In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence‐based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research. ANN NEUROL 202

Deep Learning and ALS

In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research

急性心不全における退院時の尿素窒素分画排泄率の予後判定への有用性

Background Maintaining euvolemia is crucial for improving prognosis in acute decompensated heart failure (ADHF). Although fractional excretion of urea nitrogen (FEUN) is used as a body fluid volume index in patients with acute kidney injury, the clinical impact of FEUN in patients with ADHF remains unclear. This study aimed to investigate whether FEUN can determine the long-term prognosis in patients with ADHF. Methods and Results We retrospectively identified 466 patients with ADHF who had FEUN measured at discharge between April 2011 and December 2018. The primary endpoint was post-discharge all-cause death. Patients were divided into two groups according to a FEUN cut-off value of 35%, commonly used in pre-renal failure. The FEUN <35% (low-FEUN) group included 224 patients (48.1%), and the all-cause mortality rate for the total cohort was 37.1%. The log-rank test revealed that the low-FEUN group had a significantly higher rate of all-cause death compared to the FEUN equal to or greater than 35% (high-FEUN) group (P<0.001). Multivariate Cox proportional hazards model analysis revealed that low-FEUN was associated with post-discharge all-cause death, independently of other heart failure risk factors (hazard ratio, 1.467; 95% CI, 1.030-2.088, P=0.033). The risk of low-FEUN compared to high-FEUN in post-discharge all-cause death was consistent across all subgroups; however, the effects tended to be modified by renal function (threshold: 60 mL/min/1.73 m2, interaction P=0.069). Conclusions Our study suggests that FEUN may be a novel surrogate marker of volume status in patients with ADHF requiring diuretics.博士（医学）・甲第814号・令和4年3月15日Copyright © 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License(https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made

タンパク質酸化を指標とした茶飲料の抗酸化および酸化促進作用

The ready-to-drink tea beverages from the market were examined to assess their pro-oxidant activities by incubating with bovine serum albumin in the presence of 10 mM 2,2'-azobis (2-amidinopropane) dihydrochloride (AAPH), a water-soluble free radical initiator, or 0.1 mM CuC12 in sodium phosphate buffer (pH 7.4) at 37°C for 90 mM. Protein carbonyl was measured as an index of protein oxidation. In the presence of AAPH, several green tea beverages reduced the formation of protein carbonyl possibly by scavenging free radicals, whereas oolong tea and black tea enhanced the protein carbonyl formation. In the presence of Cu^2+ ions, all tea beverages examined in this study largely increased protein carbonyl content. Additionally catechins oxidized by tyrosinase increased the protein carbonyl formation. These results indicate that oxidized catechins and their derivatives, which are rich in oolong tea and black tea, may be responsible for the protein carbonyl formatio

Characterisation of Ppy-lineage cells clarifies the functional heterogeneity of pancreatic beta cells in mice

Aims/hypothesis Pancreatic polypeptide (PP) cells, which secrete PP (encoded by the Ppy gene), are a minor population of pancreatic endocrine cells. Although it has been reported that the loss of beta cell identity might be associated with beta-to-PP cell-fate conversion, at present, little is known regarding the characteristics of Ppy-lineage cells. Methods We used Ppy-Cre driver mice and a PP-specific monoclonal antibody to investigate the association between Ppy-lineage cells and beta cells. The molecular profiles of endocrine cells were investigated by single-cell transcriptome analysis and the glucose responsiveness of beta cells was assessed by Ca2+ imaging. Diabetic conditions were experimentally induced in mice by either streptozotocin or diphtheria toxin. Results Ppy-lineage cells were found to contribute to the four major types of endocrine cells, including beta cells. Ppy-lineage beta cells are a minor subpopulation, accounting for 12–15% of total beta cells, and are mostly (81.2%) localised at the islet periphery. Unbiased single-cell analysis with a Ppy-lineage tracer demonstrated that beta cells are composed of seven clusters, which are categorised into two groups (i.e. Ppy-lineage and non-Ppy-lineage beta cells). These subpopulations of beta cells demonstrated distinct characteristics regarding their functionality and gene expression profiles. Ppy-lineage beta cells had a reduced glucose-stimulated Ca2+ signalling response and were increased in number in experimental diabetes models. Conclusions/interpretation Our results indicate that an unexpected degree of beta cell heterogeneity is defined by Ppy gene activation, providing valuable insight into the homeostatic regulation of pancreatic islets and future therapeutic strategies against diabetes