Impact of High, Low, and Non-Optimum Temperatures On Chronic Kidney Disease in a Changing Climate, 1990-2019: a Global analysis

BACKGROUND: Although a few studies have reported the relationship between high and low temperatures and chronic kidney disease (CKD), the global burden of CKD attributable to extreme heat and cold in recent decades remains unknown. METHODS: Based on the Global Burden of Disease Study (GBD) 2019, we obtained data on age-standardized mortality rates (ASMR) and age-standardized rates of disability-adjusted life years (ASDR) per 100 000 population of the CKD attributable to non-optimum temperatures from 1990 to 2019. The annual mean temperature of each country was used to divide each country into five climate zones (tropical, subtropical, warm-temperate, cool-temperate, and boreal). The locally weighted regression model was used to estimate the burden for different climate zones and Socio-demographic index (SDI) regions. RESULTS: In 1990, the ASMR and ASDR due to high temperature estimated -0.01 (95% UI, -0.74 to 0.44) and -0.32 (-21.66 to 12.66) per 100 000 population, respectively. In 2019, the ASMR and ASDR reached 0.10 (-0.28 to 0.38) and 2.71 (-8.07 to 10.46), respectively. The high-temperature burden increased most rapidly in tropical and low SDI regions. There were 0.99 (0.59 to 1.39) ASMR attributable to low-temperature in 1990, which increased to 1.05 (0.61-1.49) in 2019. While the ASDR due to low temperature declined from 22.03 (12.66 to 30.64) in 1990 to 20.43 (11.30 to 29.26) in 2019. Overall, the burden of CKD attributable to non-optimal temperatures has increased from 1990 to 2019. CKD due to hypertension and diabetes mellitus were the primary causes of CKD death attributable to non-optimum temperatures in 2019 with males and older adults being more susceptible to these temperatures. CONCLUSIONS: The CKD burden due to high, low, and non-optimum temperatures varies considerably by regions and countries. The burden of CKD attributable to high temperature has been increasing since 1990

The association between endocrine disrupting chemicals and MAFLD: Evidence from NHANES survey

Previous studies on the association of endocrine-disrupting chemicals (EDCs) with metabolic dysfunction-associated fatty liver disease (MAFLD) are very limited. This study analyzed the association of EDCs exposure with MAFLD among 5073 American adults from the 2017–2018 National Health and Nutrition Examination Survey. The results showed that increased exposure to 3 EDCs metabolites (namely As, DiNP and PFOA) were significantly associated with MAFLD, the odds ratio of which were 1.819 (95% CI: 1.224, 2.702), 1.959 (95% CI: 1.224, 3.136) and 2.148 (95% CI: 1.036, 4.456), respectively. Further, the bayesian kernel machine regression model also revealed that phthalates exposure was strongly connected with the MAFLD, particularly in females and the elderly over 65. Moderating effect analysis suggested that higher body mass index (BMI) and inflammatory diet habit (indicated by dietary inflammatory index) strengthened the association between EDCs and MAFLD, whereas population with higher level of insulin sensitivity showed lower risk. In conclusion, our results suggest that either single or combined exposure to EDCs metabolites is link to MAFLD. Our findings also encourage people to sustain a healthy diet, normal levels of insulin sensitivity and BMI, which may help to alleviate the association of MAFLD risk in exposure to EDCs. These results also help us to better understand the association of EDCs and MAFLD and provide effective evidences for preventing MAFLD from the EDCs exposure aspect

A Knowledge-Driven Geospatially Enabled Framework for Geological Big Data

Geologic survey procedures accumulate large volumes of structured and unstructured data. Fully exploiting the knowledge and information that are included in geological big data and improving the accessibility of large volumes of data are important endeavors. In this paper, which is based on the architecture of the geological survey information cloud-computing platform (GSICCP) and big-data-related technologies, we split geologic unstructured data into fragments and extract multi-dimensional features via geological domain ontology. These fragments are reorganized into a NoSQL (Not Only SQL) database, and then associations between the fragments are added. A specific class of geological questions was analyzed and transformed into workflow tasks according to the predefined rules and associations between fragments to identify spatial information and unstructured content. We establish a knowledge-driven geologic survey information smart-service platform (GSISSP) based on previous work, and we detail a study case for our research. The study case shows that all the content that has known relationships or semantic associations can be mined with the assistance of multiple ontologies, thereby improving the accuracy and comprehensiveness of geological information discovery

Mechanism of Filling and Feeding of Thin-Walled Structures during Gravity Casting

The filling and feeding of thin-walled structures in metal castings pose significant difficulties in manufacturing aerospace structural materials. Samples containing 2 mm and 5 mm thin-walled structures were designed to study the kinetics of filling. The microstructural evolution of the solidification of thin-walled structures was studied with synchrotron X-radiation imaging. The formation of dendritic networks and the isotherm profiles of samples of different thickness were examined. The experimental results showed solidification microstructures of 2 mm and 5 mm thin-walled parts containing elongated equiaxed grains and normal equiaxed grains, respectively. The filling and feeding abilities of thin-walled parts were found to depend more on the wall thickness than on the pouring temperature