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

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

Leptin and high glucose stimulate cell proliferation in MCF-7 human breast cancer cells: reciprocal involvement of PKC-α and PPAR expression

AbstractGlucose concentration may be an important factor in breast cancer cell proliferation, and the prevalence of breast cancer is high in diabetic patients. Leptin may also be an important factor since plasma levels of leptin correlated with TNM staging for breast cancer patients. The effects of glucose and leptin on breast cancer cell proliferation were evaluated by examining cell doubling time, DNA synthesis, levels of cell cycle related proteins, protein kinase C (PKC) isozyme expression, and peroxisome proliferator-activated receptor (PPAR) subtypes were determined following glucose exposure at normal (5.5 mM) and high (25 mM) concentrations with/without leptin in MCF-7 human breast cancer cells. In MCF-7 cells, leptin and high glucose stimulated cell proliferation as demonstrated by the increases in DNA synthesis and expression of cdk2 and cyclin D1. PKC-α, PPARγ, and PPARα protein levels were up-regulated following leptin and high glucose treatment in drug-sensitive MCF-7 cells. However, there was no significant effect of leptin and high glucose on cell proliferation, DNA synthesis, levels of cell cycle proteins, PKC isozymes, or PPAR subtypes in multidrug-resistant human breast cancer NCI/ADR-RES cells. These results suggested that hyperglycemia and hyperleptinemia increase breast cancer cell proliferation through accelerated cell cycle progression with up-regulation of cdk2 and cyclin D1 levels. This suggests the involvement of PKC-α, PPARα, and PPARγ

Zinc homeostasis and signaling in health and diseases: Zinc signaling

The essential trace element zinc (Zn) is widely required in cellular functions, and abnormal Zn homeostasis causes a variety of health problems that include growth retardation, immunodeficiency, hypogonadism, and neuronal and sensory dysfunctions. Zn homeostasis is regulated through Zn transporters, permeable channels, and metallothioneins. Recent studies highlight Zn’s dynamic activity and its role as a signaling mediator. Zn acts as an intracellular signaling molecule, capable of communicating between cells, converting extracellular stimuli to intracellular signals, and controlling intracellular events. We have proposed that intracellular Zn signaling falls into two classes, early and late Zn signaling. This review addresses recent findings regarding Zn signaling and its role in physiological processes and pathogenesis

Combined Predictive Value of Extracellular Fluid/Intracellular Fluid Ratio and the Geriatric Nutritional Risk Index for Mortality in Patients Undergoing Hemodialysis

The ratio of extracellular fluid (ECF) to intracellular fluid (ICF) may be associated with mortality in patients undergoing hemodialysis, possibly associated with protein-energy wasting. We therefore investigated the relationship of the ECF/ICF ratio and the geriatric nutritional risk index (GNRI) with the all-cause and cardiovascular-specific mortality in 234 patients undergoing hemodialysis. Bioimpedance analysis of the ECF and ICF was performed and the ECF/ICF ratio was independently associated with GNRI (β = −0.247, p < 0.0001). During a median follow-up of 2.8 years, 72 patients died, of which 29 were cardiovascular. All-cause mortality was independently associated with a lower GNRI (adjusted hazard ratio [aHR] 3.48, 95% confidence interval [CI] 2.01–6.25) and a higher ECF/ICF ratio (aHR 11.38, 95%CI 5.29–27.89). Next, we divided patients into four groups: group 1 (G1), higher GNRI and lower ECF/ICF ratio; G2, lower GNRI and lower ECF/ICF ratio; G3, higher GNRI and higher ECF/ICF ratio; and G4, lower GNRI and higher ECF/ICF ratio. Analysis of these groups revealed 10-year survival rates of 91.2%, 67.2%, 0%, and 0% in G1, G2, G3, and G4, respectively. The aHR for G4 versus G1 was 43.4 (95%CI 12.2–279.8). Adding the GNRI alone, the ECF/ICF ratio alone, or both to the established risk model improved the net reclassification improvement by 0.444, 0.793 and 0.920, respectively. Similar results were obtained for cardiovascular mortality. In conclusion, the ECF/ICF ratio was independently associated with GNRI and could predict mortality in patients undergoing hemodialysis. Combining the GNRI and ECF/ICF ratio could improve mortality predictions

The Impact of Abdominal Fat Levels on All-Cause Mortality Risk in Patients Undergoing Hemodialysis

Although an increased body mass index is associated with lower mortality in patients undergoing hemodialysis (HD), known as the “obesity paradox,” the relationship of abdominal fat levels with all-cause mortality has rarely been studied. We investigated the impact of computed-tomography-measured abdominal fat levels (visceral fat area (VFA) and subcutaneous fat area (SFA)) on all-cause mortality in this population. A total of 201 patients undergoing HD were enrolled and cross-classified by VFA and SFA levels according to each cutoff point, VFA of 78.7 cm2 and SFA of 93.2 cm2, based on the receiver operator characteristic (ROC) curve as following; group 1 (G1): lower VFA and lower SFA, G2: higher VFA and lower SFA, G3: lower VFA and higher SFA, G4: higher VFA and higher SFA. During a median follow-up of 4.3 years, 67 patients died. Kaplan–Meier analysis revealed 10-year survival rates of 29.0%, 50.0%, 62.6%, and 72.4% in G1, G2, G3, and G4 (p < 0.0001), respectively. The adjusted hazard ratio was 0.30 (95% confidence interval [CI] 0.05–1.09, p = 0.070) for G2 vs. G1, 0.37 (95% CI 0.18–0.76, p = 0.0065) for G3 vs. G1, and 0.21 (95% CI 0.07–0.62, p = 0.0035) for G4 vs. G1, respectively. In conclusion, combined SFA and VFA levels were negatively associated with risks for all-cause mortality in patients undergoing HD. These results are a manifestation of the “obesity paradox.

Muscle hematoma: A critically important complication of alcoholic liver cirrhosis

An iliopsoas hematoma can occur either spontaneously or secondary to trauma or bleeding tendency due to hemophilia and anticoagulant therapy. Although liver cirrhosis is commonly associated with coagulopathy, iliopsoas hematoma is very rare. We herein, present a case of bilateral iliopsoas hematoma in a patient with alcoholic cirrhosis, and review the literature on muscle hematoma associated with cirrhosis. A 56-year-old man with alcoholic cirrhosis was admitted in a state of shock with anemia. The cause of anemia could not be detected, and the patient was treated conservatively. The site of bleeding was not detected with either gastroduodenal endoscopy or upper abdominal computed tomography, the latter of which did not include the iliopsoas muscle. He died on the 10th day of admission and bilateral iliopsoas hematomas were found on autopsy. An iron stain was positive in the iliopsoas muscle. Eight cases of muscle hematoma associated with cirrhosis, including the present case, were found in a review of the literature. Four of these cases involved the rectus abdominis muscle, 3 involved the iliopsoas muscle and 1 involved combined muscles. Alcoholic cirrhosis accounted for 75% of the cases. One case (12.5%) was associated with virus-related cirrhosis, and another with combined virus- and alcohol-related cirrhosis. The mortality rate was 75% despite early diagnosis and low risk scores for cirrhosis. Muscle hematoma in patients with cirrhosis is closely related to alcoholism, and the mortality rate of the condition is extremely high. In conclusion, muscle hematoma should be recognized as an important complication of cirrhosis

The associations of fat tissue and muscle mass indices with all-cause mortality in patients undergoing hemodialysis.

Protein-energy wasting, which involves loss of fat and muscle mass, is prevalent and is associated with mortality in hemodialysis (HD) patients. We investigated the associations of fat tissue and muscle mass indices with all-cause mortality in HD patients. The study included 162 patients undergoing HD. The fat tissue index (FTI) and skeletal muscle mass index (SMI), which represent respective tissue masses normalized to height squared, were measured by bioimpedance analysis after dialysis. Patients were divided into the following four groups according to the medians of FTI and SMI values: group 1 (G1), lower FTI and lower SMI; G2, higher FTI and lower SMI; G3, lower FTI and higher SMI; and G4, higher FTI and higher SMI. The associations of the FTI, SMI, and body mass index (BMI) with all-cause mortality were evaluated. During a median follow-up of 2.5 years, 29 patients died. The 5-year survival rates were 48.6%, 76.1%, 95.7%, and 87.4% in the G1, G2, G3, and G4 groups, respectively (P = 0.0002). The adjusted hazard ratio values were 0.34 (95% confidence interval [CI] 0.10-0.95, P = 0.040) for G2 vs. G1, 0.13 (95%CI 0.01-0.69, P = 0.013) for G3 vs. G1, and 0.25 (95%CI 0.07-0.72, P = 0.0092) for G4 vs. G1, respectively. With regard to model discrimination, on adding both FTI and SMI to a model with established risk factors, the C-index increased significantly when compared with the value for a model with BMI (0.763 vs. 0.740, P = 0.016). Higher FTI and/or higher SMI values were independently associated with reduced risks of all-cause mortality in HD patients. Moreover, the combination of the FTI and SMI may more accurately predict all-cause mortality when compared with BMI. Therefore, these body composition indicators should be evaluated simultaneously in this population