Spatio-Temporal Super-Resolution Data Assimilation (SRDA) Utilizing Deep Neural Networks with Domain Generalization

Deep learning has recently gained attention in the atmospheric and oceanic sciences for its potential to improve the accuracy of numerical simulations or to reduce computational costs. Super-resolution is one such technique for high-resolution inference from low-resolution data. This paper proposes a new scheme, called four-dimensional super-resolution data assimilation (4D-SRDA). This framework calculates the time evolution of a system from low-resolution simulations using a physics-based model, while a trained neural network simultaneously performs data assimilation and spatio-temporal super-resolution. The use of low-resolution simulations without ensemble members reduces the computational cost of obtaining inferences at high spatio-temporal resolution. In 4D-SRDA, physics-based simulations and neural-network inferences are performed alternately, possibly causing a domain shift, i.e., a statistical difference between the training and test data, especially in offline training. Domain shifts can reduce the accuracy of inference. To mitigate this risk, we developed super-resolution mixup (SR-mixup)--a data augmentation method for domain generalization. SR-mixup creates a linear combination of randomly sampled inputs, resulting in synthetic data with a different distribution from the original data. The proposed methods were validated using an idealized barotropic ocean jet with supervised learning. The results suggest that the combination of 4D-SRDA and SR-mixup is effective for robust inference cycles. This study highlights the potential of super-resolution and domain-generalization techniques, in the field of data assimilation, especially for the integration of physics-based and data-driven models

Super-Resolution of Three-Dimensional Temperature and Velocity for Building-Resolving Urban Micrometeorology Using Physics-Guided Convolutional Neural Networks with Image Inpainting Techniques

Atmospheric simulations for urban cities can be computationally intensive because of the need for high spatial resolution, such as a few meters, to accurately represent buildings and streets. Deep learning has recently gained attention across various physical sciences for its potential to reduce computational cost. Super-resolution is one such technique that enhances the resolution of data. This paper proposes a convolutional neural network (CNN) that super-resolves instantaneous snapshots of three-dimensional air temperature and wind velocity fields for urban micrometeorology. This super-resolution process requires not only an increase in spatial resolution but also the restoration of missing data caused by the difference in the building shapes that depend on the resolution. The proposed CNN incorporates gated convolution, which is an image inpainting technique that infers missing pixels. The CNN performance has been verified via supervised learning utilizing building-resolving micrometeorological simulations around Tokyo Station in Japan. The CNN successfully reconstructed the temperature and velocity fields around the high-resolution buildings, despite the missing data at lower altitudes due to the coarseness of the low-resolution buildings. This result implies that near-surface flows can be inferred from flows above buildings. This hypothesis was assessed via numerical experiments where all input values below a certain height were made missing. This research suggests the possibility that building-resolving micrometeorological simulations become more practical for urban cities with the aid of neural networks that enhance computational efficiency

Three-Dimensional Super-Resolution of Passive-Scalar and Velocity Distributions Using Neural Networks for Real-Time Prediction of Urban Micrometeorology

In future cities, micrometeorological predictions will be essential to various services such as drone operations. However, the real-time prediction is difficult even by using a super-computer. To reduce the computation cost, super-resolution (SR) techniques can be utilized, which infer high-resolution images from low-resolution ones. The present paper confirms the validity of three-dimensional (3D) SR for micrometeorology prediction in an urban city. A new neural network is proposed to simultaneously super-resolve 3D temperature and velocity fields. The network is trained using the micrometeorology simulations that incorporate the buildings and 3D radiative transfer. The error of the 3D SR is sufficiently small: 0.14 K for temperature and 0.38 m s-1for velocity. The computation time of the 3D SR is negligible, implying the feasibility of real-time predictions for the urban micrometeorology

Optimal duration of antibiotic treatment for community-acquired pneumonia in adults: a systematic review and duration-effect meta-analysis.

OBJECTIVES To find the optimal treatment duration with antibiotics for community-acquired pneumonia (CAP) in adults. DESIGN Systematic review and duration-effect meta-analysis. DATA SOURCES MEDLINE, Embase and CENTRAL through 25 August 2021. ELIGIBILITY CRITERIA All randomised controlled trials comparing the same antibiotics used at the same daily dosage but for different durations for CAP in adults. Both outpatients and inpatients were included but not those admitted to intensive care units. We imposed no date, language or publication status restriction. DATA EXTRACTION AND SYNTHESIS Data extraction by two independent reviewers. We conducted a random-effects, one-stage duration-effect meta-analysis with restricted cubic splines. We tested the non-inferiority with the prespecified non-inferiority margin of 10% examined against 10 days . The primary outcome was clinical improvement on day 15 (range 7-45 days). SECONDARY OUTCOMES all-cause mortality, serious adverse events and clinical improvement on day 30 (15-60 days). RESULTS We included nine trials (2399 patients with a mean (SD) age of 61.2 (22.1); 39% women). The duration-effect curve was monotonic with longer duration leading to a lower probability of improvement, and shorter treatment duration (3-9 days) was likely to be non-inferior to 10-day treatment. Harmful outcome curves indicated no association. The weighted average percentage of the primary outcome in the 10-day treatment arms was 68%. Using that average, the absolute clinical improvement rates of the following durations were: 3-day treatment 75% (95% CI: 68% to 81%), 5-day treatment 72% (95% CI: 66% to 78%) and 7-day treatment 69% (95% CI: 61% to 76%). CONCLUSIONS Shorter treatment duration (3-5 days) probably offers the optimal balance between efficacy and treatment burden for treating CAP in adults if they achieved clinical stability. However, the small number of included studies and the overall moderate-to-high risk of bias may compromise the certainty of the results. Further research on the shorter duration range is required. PROSPERO REGISTRATION NUMBER CRD 42021273357

アミノ酸トランスポーターによる中枢神経系機能制御の解明に関する研究

13301甲第4898号博士(薬学)金沢大学博士論文要旨Abstract 要約Outline 以下に掲載：FEBS open bio 9(2) pp.241-247 2019. Wiley. 共著者：Yuki Onishi, Manami Hiraiwa, Hikari Kamada, Takashi Iezaki, Takanori Yamada, Katsuyuki Kaneda, Eiichi Hino

ATP and its metabolite adenosine cooperatively upregulate the antigen-presenting molecules on dendritic cells leading to IFN-gamma production by T cells

Dendritic cells (DCs) present foreign antigens to T cells via the major histocompatibility complex (MHC), thereby inducing acquired immune responses. ATP accumulates at sites of inflammation or in tumor tissues, which triggers local inflammatory responses. However, it remains to be clarified how ATP modulates the functions of DCs. In this study, we investigated the effects of extracellular ATP on mouse bone marrow- derived dendritic cells (BMDCs) as well as the potential for subsequent T cell activation. We found that high concentrations of ATP (1 mM) upregulated the cell surface expression levels of MHC-I, MHC-II, and co-stimulatory molecules CD80 and CD86 but not those of co-inhibitory molecules PD-L1 and PD-L2 in BMDCs. Increased surface expression of MHC-I, MHC-II, CD80, and CD86 was inhibited by a pan-P2 receptor antagonist. In addition, the upregulation of MHC-I and MHC-II expression was inhibited by an adenosine P1 receptor antagonist and by inhibitors of CD39 and CD73, which metabolize ATP to adenosine. These results suggest that adenosine is required for the ATP-induced upregulation of MHC-I and MHC-II. In the mixed leukocyte reaction assay, ATP-stimulated BMDCs activated CD4 and CD8T cells and induced interferon-gamma (IFN-gamma) production by these T cells. Collectively, these results suggest that high concentrations of extracellular ATP upregulate the expression of antigenpresenting and co-stimulatory molecules but not that of coinhibitory molecules in BMDCs. Cooperative stimulation of ATP and its metabolite adenosine was required for the upregulation of MHC-I and MHC-II. These ATP-stimulated BMDCs induced the activation of IFN-gamma-producing T cells upon antigen presentation

Daily intake of β-cryptoxanthin prevents bone loss by preferential disturbance of osteoclastic activation in ovariectomized mice

AbstractAlthough β-cryptoxanthin, a xanthophyll carotenoid, has been shown to exert an anabolic effect on bone calcification, little attention has been paid thus far to the precise mechanism of bone remodeling. Daily oral administration of β-cryptoxanthin significantly inhibited osteoclastic activation as well as reduction of bone volume in ovariectomized mice. In vitro studies revealed that β-cryptoxanthin inhibited differentiation and maturation of osteoclasts by repression of the nuclear factor-κB-dependent transcriptional pathway. Our results suggest that supplementation with β-cryptoxanthin would be beneficial for prophylaxis and for therapy of metabolic bone diseases associated with abnormal osteoclast activation

叙景、叙事、叙情の歌 : オペラの受容と日本語音楽劇の近代

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 菅原 克也, 東京大学教授 ゴチェフスキ ヘルマン, 東京大学教授 長木 誠司, 東京大学准教授 前島 志保, 早稲田大学教授 児玉 竜一University of Tokyo(東京大学

Clinical impact of aortic valve replacement in patients with moderate mixed aortic valve disease

BackgroundInformation is scarce regarding the clinical implications of aortic valve replacement (AVR) for patients suffering from moderate mixed aortic valve disease (MAVD), characterized by a combination of moderate aortic stenosis (AS) and regurgitation (AR). The objective of this retrospective study was to explore the clinical effects of AVR in individuals with moderate MAVD.MethodsWe examined the clinical data from patients with moderate MAVD and preserved left ventricular ejection fraction, who had undergone echocardiography in the period spanning from 2010 to 2018. Moderate AS was defined as aortic valve area index of 0.60–0.85 cm2/m2 and peak velocity of 3.0–4.0 m/s. Moderate AR was defined as a vena contracta width of 3.0–6.0 mm. The primary endpoint was a composite of all-cause death and heart failure hospitalization.ResultsAmong 88 patients (mean age, 74.4 ± 6.8 years; 48.9%, men), 44 (50.0%) required AVR during a median follow-up period of 3.3 years (interquartile range, 0.5–4.9). Mean values of specific aortic valve variables are as follows: aortic valve area index, 0.64 ± 0.04 cm2/m2; peak velocity, 3.40 ± 0.30 m/s; and vena contracta width, 4.1 ± 0.7 mm. The primary endpoint occurred in 32 (36.4%) patients during a median follow-up duration of 5.3 years (interquartile range, 3.2–8.0). Multivariable analysis revealed that AVR was significantly associated with the endpoint (hazard ratio, 0.248; 95% confidence interval, 0.107–0.579; p = 0.001) after adjusting for age, B-type natriuretic peptide, and the Charlson comorbidity index. Patients who underwent AVR during follow-up had significantly lower incidence rates of the endpoint than those managed with medical treatment (10.2% vs. 44.1% at 5 years; p < 0.001).ConclusionsApproximately half of the patients diagnosed with moderate MAVD eventually necessitated AVR throughout the period of observation, leading to positive clinical results. Vigilant tracking of these patients and watchful monitoring for signs requiring AVR during this time frame are essential

18FDG-PET at 1-Month Intervals Is a Better Predictive Marker for GISTs That Are Difficult to Be Diagnosed Histopathologically: A Case Report

Imatinib mesylate is a tyrosine kinase inhibitor of c-KIT and PDGFRA. Imatinib mesylate is an effective drug that can be used as a first-choice agent for treatment of GISTs. Prior to treatment, molecular diagnosis of c-KIT or PDGFRA is necessary; however, in some types of GISTs, it is impossible to obtain a sufficient amount of specimen for diagnosis. An inoperable or marginally resectable GIST in a 79-year-old female was difficult to be diagnosed at a molecular pathological level, and hence, exploratory treatment was initiated using imatinib combined with 18FDG-PET evaluation at 1-month intervals. PET imaging indicated a positive response, and so we continued imatinib treatment in an NAC setting for 4 months. As a result, curative resection of the entire tumor was successfully performed with organ preservation and minimally invasive surgery. 18FDG-PET evaluation at 1-month intervals is beneficial for GISTs that are difficult to be diagnosed histopathologically