Causal relationship between gut microbiota and diabetic nephropathy: A bidirectional mendelian randomization study.

In this study, we summarized the key findings and potential implications of association studies investigating the relationship between gut microbiota composition and risks for Diabetic nephropathy (DN). We used Mendelian randomization (MR) analysis to explore the relationship between gut microbiota and DN using two different publicly available DN databases. The results were also summarized using five mainstream MR analysis methods. We controlled for various possible biases in the results. The results showed that specific bacterial genera were associated with increased or decreased risk of DN. These associations can be attributed to a variety of factors, including metabolites produced by certain bacteria. Most of our findings are consistent with the existing research findings, but there are still some differences with the existing results. In addition, we also pointed out that some microbiota that may be associated with DN but remain unnoticed can bring new research directions. Our work made use of MR, a reliable technique for examining causal correlations using genetic data investigating potential processes, carrying out longitudinal studies, looking into intervention options, and using a multi-omics approach may be future research avenues. Further, our findings also point to a few unexplored possible study paths for DN in the future. These initiatives may improve our reconciliation of the internal relationships between the gut microbiota and DN and pave the way for more precise prevention and treatment methods. However, it is also critical to recognize any potential restrictions, such as those caused by sample size, population variety, and analytical techniques.

The influence of dusts on radiation and temperature over the eastern Asia with a regional climate model.

In order to investigate the climate effects of dusts, a regional climate model (RegCM 4.6) with the dust scheme was used to simulate the direct radiative forcing and air temperature response at 2 m near surface of dusts over the eastern Asia. Two sets of experiments were conducted, one with and one without dust aerosols. The experiment covered the main dust occurrence months from March to May for 8 years (2011-2018), and the simulation results were evaluated against ground station, reanalysis and satellite data. The model captured the spatiotemporal distribution of dust AOD and mass loading over the eastern Asia. However, it tended to underestimate the dust AOD and mass loading over the downwind of the dust source region and the Taklimakan Desert, and overestimate them over the north Xinjiang. The direct net radiative forcing including shortwave and longwave was up to -20 W·m-2 at the surface and -10 W·m-2 at the TOA over the dust source region due to the dominant negative shortwave forcing. The only exception of positive forcing at the TOA was observed along the western boundaries of the Tibetan Plateau due to the semi-persistent ice and snow cover. The dusts tended to warm the atmosphere more than 18 W·m-2 and cool the surface locally up to -0.7 °C. Among the 5 sub-areas, the largest averaged regional direct radiative forcing induced by dusts appeared over the central Inner Mongolia in May with the value of -3.0 ± 2.1, -12.2 ± 4.1 and 9.2 ± 4.4 W·m-2 at the TOA, surface and in the atmosphere, respectively. The results indicated that the model simulation for dusts should be further improved and the dust effects should be included in the estimates of climate change over the eastern Asia.

C-arm CT imaging with the extended line-ellipse-line trajectory: first implementation on a state-of-the-art robotic angiography system.

Three-dimensional cone-beam imaging has become valuable in interventional radiology. Currently, this tool, referred to as C-arm CT, employs a circular short-scan for data acquisition, which limits the axial volume coverage and yields unavoidable cone-beam artifacts. To improve flexibility in axial coverage and image quality, there is a critical need for novel data acquisition geometries and related image reconstruction algorithms. For this purpose, we previously introduced the extended line-ellipse-line trajectory, which allows complete scanning of arbitrary volume lengths in the axial direction together with adjustable axial beam collimation, from narrow to wide depending on the targeted application. A first implementation of this trajectory on a state-of-the-art robotic angiography system is reported here. More specifically, an assessment of the quality of this first implementation is presented. The assessment is in terms of geometric fidelity and repeatability, complemented with a first visual inspection of how well the implementation enables imaging an anthropomorphic head phantom. The geometric fidelity analysis shows that the ideal trajectory is closely emulated, with only minor deviations that have no impact on data completeness and clinical practicality. Also, mean backprojection errors over short-term repetitions are shown to be below the detector pixel size at field-of-view center for most views, which indicates repeatability is satisfactory for clinical utilization. These repeatability observations are further supported by values of the Structural Similarity Index Metric above 94% for reconstructions of the FORBILD head phantom from computer-simulated data based on repeated data acquisition geometries. Last, the real data experiment with the anthropomorphic head phantom shows that the high contrast features of the phantom are well reconstructed without distortions as well as without breaks or other disturbing transition zones, which was not obvious given the complexity of the data acquisition geometry and the major variations in axial coverage that occur over the scan.