38 research outputs found
The Tendency of Atmospheric Temperature and Precipitation from a Viewpoint of the Climatic Variation Indices
Surface air temperature (AT) and precipitation are important in studying global climate system. AT and precipitation are related with climatic variation indices, such as SOl(Southern oscillation index; Philander, 1990), PDO(Pacific decadal oscillation; Mantua, et al., 1997), AO(Arcticoscillation; Yamakawa, 2005), AAO(Antarctic oscillation; Tompson & Wallace, 2000) and QBO(quasi- biennial oscillation) which are dealt with in this study. Inoue & Yamakawa (2010) analyzed the precipitation of Asia in the warm half year. This research focuses mainly on the relation between teleconnections(Gibntz, et al., 1991) and AT. Multiple regressions are used to determine the relationships between the climatic indices and AT in summer. A multipleregression including QBO should be taken into consideration to improve summer weather forecast
Relationships between Stratospheric Quasi-Biennial Oscillation (QBO) and Precipitation Activities in Asia
The influence of stratospheric quasi-biennial oscillation (QBO) on global precipitation features was studied over a 25-year period. The years from 1980 to 2004 are classified into easterlyand westerly phases of QBO. Composite analyses in Asia reveal noteworthy pluvial anomalies near the Philippines, and inactive front activity and typical drought events due to adiabatic descent over Japan during the easterly phase of QBO. Cool summers and extreme rainfall events in Japan tend to prevail in the westerly phase. In particular, ten Typhoons struck Japan in 2004 accompanied by the westerly phase of QBO
Gradient boosting decision tree becomes more reliable than logistic regression in predicting probability for diabetes with big data
We sought to verify the reliability of machine learning (ML) in developing diabetes prediction models by utilizing big data. To this end, we compared the reliability of gradient boosting decision tree (GBDT) and logistic regression (LR) models using data obtained from the Kokuho-database of the Osaka prefecture, Japan. To develop the models, we focused on 16 predictors from health checkup data from April 2013 to December 2014. A total of 277,651 eligible participants were studied. The prediction models were developed using a light gradient boosting machine (LightGBM), which is an effective GBDT implementation algorithm, and LR. Their reliabilities were measured based on expected calibration error (ECE), negative log-likelihood (Logloss), and reliability diagrams. Similarly, their classification accuracies were measured in the area under the curve (AUC). We further analyzed their reliabilities while changing the sample size for training. Among the 277,651 participants, 15,900 (7978 males and 7922 females) were newly diagnosed with diabetes within 3 years. LightGBM (LR) achieved an ECE of 0.0018 ± 0.00033 (0.0048 ± 0.00058), a Logloss of 0.167 ± 0.00062 (0.172 ± 0.00090), and an AUC of 0.844 ± 0.0025 (0.826 ± 0.0035). From sample size analysis, the reliability of LightGBM became higher than LR when the sample size increased more than 104. Thus, we confirmed that GBDT provides a more reliable model than that of LR in the development of diabetes prediction models using big data. ML could potentially produce a highly reliable diabetes prediction model, a helpful tool for improving lifestyle and preventing diabetes
CNVs in Three Psychiatric Disorders
BACKGROUND: We aimed to determine the similarities and differences in the roles of genic and regulatory copy number variations (CNVs) in bipolar disorder (BD), schizophrenia (SCZ), and autism spectrum disorder (ASD).
METHODS: Based on high-resolution CNV data from 8708 Japanese samples, we performed to our knowledge the largest cross-disorder analysis of genic and regulatory CNVs in BD, SCZ, and ASD.
RESULTS: In genic CNVs, we found an increased burden of smaller (500 kb) exonic CNVs in SCZ/ASD. Pathogenic CNVs linked to neurodevelopmental disorders were significantly associated with the risk for each disorder, but BD and SCZ/ASD differed in terms of the effect size (smaller in BD) and subtype distribution of CNVs linked to neurodevelopmental disorders. We identified 3 synaptic genes (DLG2, PCDH15, and ASTN2) as risk factors for BD. Whereas gene set analysis showed that BD-associated pathways were restricted to chromatin biology, SCZ and ASD involved more extensive and similar pathways. Nevertheless, a correlation analysis of gene set results indicated weak but significant pathway similarities between BD and SCZ or ASD (r = 0.25–0.31). In SCZ and ASD, but not BD, CNVs were significantly enriched in enhancers and promoters in brain tissue.
CONCLUSIONS: BD and SCZ/ASD differ in terms of CNV burden, characteristics of CNVs linked to neurodevelopmental disorders, and regulatory CNVs. On the other hand, they have shared molecular mechanisms, including chromatin biology. The BD risk genes identified here could provide insight into the pathogenesis of BD
Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial
Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials.
Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure.
Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen.
Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049
Bofutsushosan, a Japanese herbal (Kampo) medicine, attenuates progression of nonalcoholic steatohepatitis in mice
Climatological study of cold frontal precipitation in japan
Cold frontal precipitation in Japan has regional and seasonal characteristics. First of all, a cold front and its precipitation have been recognized. The contributing rates of cold frontal precipitation due to various causes have been surveyed at 11 stations. The annual or seasonal occurrence frequencies of precipitation due to cold fronts, classified by equivalent potential temperature (850mb), have been studied at about 140 stations. In addition, on the basis of analyzing the aerological data and meso-scale phenomena, pre-frontal or post-frontal squalls, thunderstorms, upper or lower winds related to them, etc. have been examined. Last of all, various models of the cold frontal system have been illustrated on the basis of the acquired information
Weather systems of winter passing cold front over north japan
A weather system before and after a cold front passage over North Japan is studied from the viewpoint of mesoscale and synoptic scale meteorology. A case study in winter shows the typical synoptic system and distinctive mesoscale phenomena. The temporal and regional features of temperature variations, which are accompanied by the pass of a cold front, are focused on. For example, in Nemuro Plain, the inland of southeastern Hokkaido, temperature rises suddenly and temporarily right after the cold front passage, chiefly because the inversion layers are destroyed by downslope wind on the lee side. This exceptional weather system is worth noting not only in meteorology but also in synoptic climatology