Modification in Biotic Potential of Insects surviving exposure to an Insecticide

殺虫剤で処理して生き残つた昆虫の其の後の繁殖能力,特に1雌の産卵数,性比,卵より成虫までの間の生育率及び体重がどの様に変動するかをアズキゾウムシCallosobruchus chinensisに対するエンドリン乳剤の効果によつて実験的に確かめた. (1)処理された成虫の1雌の産卵数は対照に比して1般に少ない.然し処理された雄を正常の雌に配した場合では逆に多い. (2)処理された雌雄から生まれたF1の卵から成虫までの間の生育率は対照と余り差がないが正常な雌に処理された雄を配した場合のそれは低い. (3)上記F1の性比は0.45以下であつて雄の割合が多い. (4)その1雌当り産卵数は25%増加する.又その体重も重い. (5)F1代に於いて産卵数が多く,性比が雄の割合が多く,成虫の体重が重いという状態はF2以下では消失する

Statistical hypothesis test of factor loading in principal component analysis and its application to metabolite set enrichment analysis

Principal component analysis (PCA) has been widely used to visualize high-dimensional metabolomic data in a two- or three-dimensional subspace. In metabolomics, some metabolites (e.g. top 10 metabolites) have been subjectively selected when using factor loading in PCA, and biological inferences for these metabolites are made. However, this approach is possible to lead biased biological inferences because these metabolites are not objectively selected by statistical criterion. We proposed a statistical procedure to pick up metabolites by statistical hypothesis test of factor loading in PCA and make biological inferences by metabolite set enrichment analysis (MSEA) for these significant metabolites. This procedure depends on the fact that the eigenvector in PCA for autoscaled data is proportional to the correlation coefficient between PC score and each metabolite levels. We applied this approach for two metabolomic data of mice liver samples. 136 of 282 metabolites in first case study and 66 of 275 metabolites in second case study were statistically significant. This result suggests that to set the previously-determined number of metabolites is not appropriate because the number of significant metabolites is different in each study when using factor loading in PCA. Moreover, MSEA was performed for these significant metabolites and significant metabolic pathways can be detected. These results are acceptable when compared with previous biological knowledge. It is essential to select metabolites statistically for making unbiased biological inferences from metabolome data, when using factor loading in PCA. We proposed a statistical procedure to pick up metabolites by statistical hypothesis test of factor loading in PCA and make biological inferences by MSEA for these significant metabolites. We developed an R package mseapca to perform this approach. The “mseapca” package is publicity available on CRAN website

Statistical hypothesis testing of factor loading in principal component analysis and its application to metabolite set enrichment analysis

BACKGROUND: Principal component analysis (PCA) has been widely used to visualize high-dimensional metabolomic data in a two- or three-dimensional subspace. In metabolomics, some metabolites (e.g., the top 10 metabolites) have been subjectively selected when using factor loading in PCA, and biological inferences are made for these metabolites. However, this approach may lead to biased biological inferences because these metabolites are not objectively selected with statistical criteria. RESULTS: We propose a statistical procedure that selects metabolites with statistical hypothesis testing of the factor loading in PCA and makes biological inferences about these significant metabolites with a metabolite set enrichment analysis (MSEA). This procedure depends on the fact that the eigenvector in PCA for autoscaled data is proportional to the correlation coefficient between the PC score and each metabolite level. We applied this approach to two sets of metabolomic data from mouse liver samples: 136 of 282 metabolites in the first case study and 66 of 275 metabolites in the second case study were statistically significant. This result suggests that to set the number of metabolites before the analysis is inappropriate because the number of significant metabolites differs in each study when factor loading is used in PCA. Moreover, when an MSEA of these significant metabolites was performed, significant metabolic pathways were detected, which were acceptable in terms of previous biological knowledge. CONCLUSIONS: It is essential to select metabolites statistically to make unbiased biological inferences from metabolomic data when using factor loading in PCA. We propose a statistical procedure to select metabolites with statistical hypothesis testing of the factor loading in PCA, and to draw biological inferences about these significant metabolites with MSEA. We have developed an R package “mseapca” to facilitate this approach. The “mseapca” package is publicly available at the CRAN website

Light Transport Refocusing for Unknown Scattering Medium

2014 22nd International Conference on Pattern Recognition,Stockholm, Sweden,24-28 Aug. 2014In this paper we propose a new light transport refocusing method for depth estimation as well as for investigation inside scattering media with unknown scattering properties. Propagated visible light rays through scattering media are utilized in our proposed refocusing method. We use 2D light source to illuminate the scattering media and 2D image sensor for capturing transported rays. The proposed method that uses 4D light transport can clearly visualize shallow depth, as well as deep depth plane of the medium. We apply our light transport refocusing method for depth estimation using conventional depth-from-focus method and for clear visualization by descattering the light rays passing through the medium. To evaluate the effectiveness we have done experiments using acrylic and milk-water type scattering medium in various optical and geometrical conditions. Finally, we show up the results of depth estimation and clear visualization, as well as with numeric evaluation

Development of a Vertex Finding Algorithm using Recurrent Neural Network

Deep learning is a rapidly-evolving technology with possibility to significantly improve physics reach of collider experiments. In this study we developed a novel algorithm of vertex finding for future lepton colliders such as the International Linear Collider. We deploy two networks; one is simple fully-connected layers to look for vertex seeds from track pairs, and the other is a customized Recurrent Neural Network with an attention mechanism and an encoder-decoder structure to associate tracks to the vertex seeds. The performance of the vertex finder is compared with the standard ILC reconstruction algorithm.Comment: 8 pages, 8 figures, preliminary version currently under review by IL

Reconstructive Surgery of Poliomyelitic Disabled Hand and Arm with particular Reference to Opponens Plasty

The purpose of this report is to give light on problems concerning surgical reconstruction of the hand and arm disabled by poliomyelitis. Before any surgical intervention, too much attention cannot be placed to the over-all gain sought for the patient. With regard to opponens plasty, it must be emphasized that there are inherent obstacles against the complete reconstruction of poliomyelitic thumb. Authors have come to conclude that no stereotyped measure can be made for any weak thumb

Functional Analysis of Free Fatty Acid Receptor GPR120 in Human Eosinophils: Implications in Metabolic Homeostasis

Recent evidence has shown that eosinophils play an important role in metabolic homeostasis through Th2 cytokine production. GPR120 (FFA4) is a G protein-coupled receptor (GPCR) for long-chain fatty acids that functions as a regulator of physiological energy metabolism. In the present study, we aimed to investigate whether human eosinophils express GPR120 and, if present, whether it possesses a functional capacity on eosinophils. Eosinophils isolated from peripheral venous blood expressed GPR120 at both the mRNA and protein levels. Stimulation with a synthetic GPR120 agonist, GW9508, induced rapid down-regulation of cell surface expression of GPR120, suggesting ligand-dependent receptor internalization. Although GPR120 activation did not induce eosinophil chemotactic response and degranulation, we found that GW9508 inhibited eosinophil spontaneous apoptosis and Fas receptor expression. The anti-apoptotic effect was attenuated by phosphoinositide 3-kinase (PI3K) inhibitors and was associated with inhibition of caspase-3 activity. Eosinophil response investigated using ELISpot assay indicated that stimulation with a GPR120 agonist induced IL-4 secretion. These findings demonstrate the novel functional properties of fatty acid sensor GPR120 on human eosinophils and indicate the previously unrecognized link between nutrient metabolism and the immune system

『宣教卿記』天正三年六月〜一二月記

departmental bulletin pape

Infiltration of M1, but not M2, macrophages is impaired after unilateral ureter obstruction in Nrf2-deficient mice

Chronic inflammation can be a major driver of the failure of a variety of organs, including chronic kidney disease (CKD). The NLR family pyrin domain-containing 3 (NLRP3) inflammasome has been shown to play a pivotal role in inflammation in a mouse kidney disease model. Nuclear factor erythroid 2-related factor 2 (Nrf2), the master transcription factor for anti-oxidant responses, has also been implicated in inflammasome activation under physiological conditions. However, the mechanism underlying inflammasome activation in CKD remains elusive. Here, we show that the loss of Nrf2 suppresses fibrosis and inflammation in a unilateral ureter obstruction (UUO) model of CKD in mice. We consistently observed decreased expression of inflammation-related genes NLRP3 and IL-1β in Nrf2-deficient kidneys after UUO. Increased infiltration of M1, but not M2, macrophages appears to mediate the suppression of UUO-induced CKD symptoms. Furthermore, we found that activation of the NLRP3 inflammasome is attenuated in Nrf2-deficient bone marrow–derived macrophages. These results demonstrate that Nrf2-related inflammasome activation can promote CKD symptoms via infiltration of M1 macrophages. Thus, we have identified the Nrf2 pathway as a promising therapeutic target for CKD