The combination of body mass index and fasting plasma glucose is associated with type 2 diabetes mellitus in Japan: a secondary retrospective analysis

BackgroundBody mass index (BMI) and fasting plasma glucose (FPG) are known risk factors for type 2 diabetes mellitus (T2DM), but data on the prospective association of the combination of BMI and FPG with T2DM are limited. This study sought to characterize the association of the combination of BMI and FPG (ByG) with T2DM.MethodsThe current study used the NAGALA database. We categorized participants by tertiles of ByG. The association of ByG with T2DM was expressed with hazard ratios (HRs) with 95% confidence intervals (CIs) after adjustment for potential risk factors.ResultsDuring a median follow-up of 6.19 years in the normoglycemia cohort and 5.58 years in the prediabetes cohort, the incidence of T2DM was 0.75% and 7.79%, respectively. Following multivariable adjustments, there were stepwise increases in T2DM with increasing tertiles of ByG. After a similar multivariable adjustment, the risk of T2DM was 2.57 (95% CI 2.26 - 2.92), 1.97 (95% CI 1.53 - 2.54) and 1.50 (95% CI 1.30 - 1.74) for a per-SD change in ByG in all populations, the normoglycemia cohort and the prediabetes cohort, respectively.ConclusionByG was associated with an increased risk of T2DM in Japan. The result reinforced the importance of the combination of BMI and FPG in assessing T2DM risk

Comparison of joint status using ultrasound assessments and Haemophilia Joint Health Score 2.1 in children with haemophilia

IntroductionUltrasound (US) has gained popularity in the evaluation of haemophilic joint diseases because it enables the imaging of soft-tissue lesions in the joints and bone-cartilage lesions. We aimed to determine the correlation between US evaluations and clinical assessments performed using HJHS 2.1 and to evaluate their respective characteristics in assessing early haemophilic arthropathy.MethodsA total of 178 joints (32 knees, 85 elbows, and 61 ankles) in 45 haemophilia A patients (median age, 10 years; range, 6–15) were assessed using US and HJHS 2.1. Ultrasonographic scoring was performed in consensus assessments by one imager by using the US scores.ResultsThe total HJHS 2.1 and US scores showed a strong correlation (rS=0.651, P=0.000, CI: 0.553–0.763), with an excellent correlation for the elbows (rS=0.867, P=0.000, CI: 0.709–0.941) and a substantial correlation for the knees (rS=0.681, P=0.000, CI: 0.527–0.797). The correlation for the ankles was relatively moderate (rS=0.518, P=0.000, CI: 0.308–0.705). Nine subjects (15.5%) without abnormalities, as indicated by HJHS 2.1, showed haemophilic arthropathy in US scoring. All nine joints showed moderate (1/9) to severe (8/9) synovial thickening in the ankle (5/9) and elbow joints (4/9). In contrast, 50 joints (50.5%) showed normal US scores and abnormal changes as indicated by HJHS 2.1. S scores correlated well with HJHS 2.1 for overall and individual joints.DiscussionUS could identify some early pathological changes in joints showing normal clinical findings, but still cannot replace the HJHS; however, it can serve as an imaging examination complementing HJHS 2

A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia

FengYun-3B (FY-3B) soil moisture product, retrieved from passive microwave brightness temperature data based on the Qp model, has rarely been applied at the catchment and region scale. One of the reasons for this is its coarse spatial resolution (25-km). The study in this paper presented a new method to obtain a high spatial resolution soil moisture product by downscaling FY-3B soil moisture product from 25-km to 1-km spatial resolution using the theory of Apparent Thermal Inertia (ATI) under bare surface or sparse vegetation covered land surface. The relationship between soil moisture and ATI was first constructed, and the coefficients were obtained directly from 25-km FY-3B soil moisture product and ATI derived from MODIS data, which is different from previous studies often assuming the same set of coefficients applicable at different spatial resolutions. The method was applied to Naqu area on the Tibetan Plateau to obtain the downscaled 1-km resolution soil moisture product, the latter was validated using ground measurements collected from Soil Moisture/Temperature Monitoring Network on the central Tibetan Plateau (TP-STMNS) in 2012. The downscaled soil moisture showed promising results with a coefficient of determination R2 higher than 0.45 and a root mean-square error (RMSE) less than 0.11 m3/m3 when comparing with the ground measurements at 5 sites out of the 9 selected sites. It was found that the accuracy of downscaled soil moisture was largely influenced by the accuracy of the FY-3B soil moisture product. The proposed method could be applied for both bare soil surface and sparsely vegetated surface

A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia

FengYun-3B (FY-3B) soil moisture product, retrieved from passive microwave brightness temperature data based on the Qp model, has rarely been applied at the catchment and region scale. One of the reasons for this is its coarse spatial resolution (25-km). The study in this paper presented a new method to obtain a high spatial resolution soil moisture product by downscaling FY-3B soil moisture product from 25-km to 1-km spatial resolution  using the theory of Apparent Thermal Inertia (ATI) under bare surface or sparse vegetation covered land surface. The relationship between soil moisture and ATI was first constructed, and the coefficients were obtained directly from 25-km FY-3B soil moisture product and ATI derived from MODIS data, which is different from previous studies often assuming the same set of coefficients applicable at different spatial resolutions. The method was applied to Naqu area on the Tibetan Plateau to obtain the downscaled 1-km resolution soil moisture product, the latter was validated using ground measurements collected from Soil Moisture/Temperature Monitoring Network on the central Tibetan Plateau (TP-STMNS) in 2012. The downscaled soil moisture showed promising results with a coefficient of determination R2 higher than 0.45 and a root mean-square error (RMSE) less than 0.11 m3/m3 when comparing with the ground measurements at 5 sites out of the 9 selected sites. It was found that the accuracy of downscaled soil moisture was largely influenced by the accuracy of the FY-3B soil moisture product. The proposed method could be applied for both bare soil surface and sparsely vegetated surface

Retrieving high-resolution surface soil moisture by downscaling AMSR-E brightness temperature using MODIS LST and NDVI data

A method to retrieve soil moisture at high spatial resolution is presented in this paper. The method is based on soil moisture retrieval with passive brightness temperature. The method of retrieving land surface temperature with passive microwave is combined with the relationship between the microwave polarization difference index (MPDI) and normalized difference of vegetation index (NDVI) to obtain high-resolution microwave brightness temperature and soil moisture. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) 18.7-GHz brightness temperature at 25-km resolution is downscaled to 1-km using high-resolution MODIS visible/infrared (VIS/IR) data. High-resolution soil moisture is retrieved with the downscaled microwave brightness temperature using a single-channel algorithm (SCA) and the Qp model to deal with the influence of roughness. The method is applied to an area in northwest of China. The downscaled high-resolution soil moisture is tested with ground data collected at three sites within the Maqu monitoring network from July 1, 2008 to June 30, 2009. The trend of the time series of the downscaled soil moisture is similar to the ground measurements during this period with root mean-square error (RMSE) less than 0.12. The results show that the method is more suitable to moderate to drier soil conditions with bare surface or covered by sparse vegetation.</p

A review of recommendation system research based on bipartite graph

The interaction history between users and items is usually stored and displayed in the form of bipartite graphs. Neural network recommendation based on the user-item bipartite graph has a significant effect on alleviating the long-standing data sparseness and cold start of the recommendation system. The whole paper is based on the bipartite graph. An review of the recommendation system of graphs summarizes the three characteristics of graph neural network processing bipartite graph data in the recommendation field: interchangeability, Multi-hop transportability, and strong interpretability. The biggest contribution of the full paper is that it summarizes the general framework of graph neural network processing bipartite graph recommendation from the models with the best recommendation effect in the past three years: embedding layer, propagation update layer, and prediction layer. Although there are subtle differences between different models, they are all this framework can be applied, and different models can be regarded as variants of this general model, that is, other models are fine-tuned on the basis of this framework. At the end of the paper, the latest research progress is introduced, and the main challenges and research priorities that will be faced in the future are pointed out