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- Ning, Yujie, et al.
(författare)
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Comparative analysis of the gut microbiota composition between knee osteoarthritis and Kashin-Beck disease in Northwest China
- 2022
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Ingår i: Arthritis Research & Therapy. - : BioMed Central. - 1478-6362. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Osteoarthritis (OA) and Kashin-Beck disease (KBD) both are two severe osteochondral disorders. In this study, we aimed to compare the gut microbiota structure between OA and KBD patients.Methods: Fecal samples collected from OA and KBD patients were used to characterize the gut microbiota using 16S rDNA gene sequencing. To identify whether gut microbial changes at the species level are associated with the genes or functions of the gut bacteria between OA and KBD groups, metagenomic sequencing of fecal samples from OA and KBD subjects was performed.Results: The OA group was characterized by elevated Epsilonbacteraeota and Firmicutes levels. A total of 52 genera were identified to be significantly differentially abundant between the two groups. The genera Raoultella, Citrobacter, Flavonifractor, g__Lachnospiraceae_UCG-004, and Burkholderia-Caballeronia-Paraburkholderia were more abundant in the OA group. The KBD group was characterized by higher Prevotella_9, Lactobacillus, Coprococcus_2, Senegalimassilia, and Holdemanella. The metagenomic sequencing showed that the Subdoligranulum_sp._APC924/74, Streptococcus_parasanguinis, and Streptococcus_salivarius were significantly increased in abundance in the OA group compared to those in the KBD group, and the species Prevotella_copri, Prevotella_sp._CAG:386, and Prevotella_stercorea were significantly decreased in abundance in the OA group compared to those in the KBD group by using metagenomic sequencing.Conclusion: Our study provides a comprehensive landscape of the gut microbiota between OA and KBD patients and provides clues for better understanding the mechanisms underlying the pathogenesis of OA and KBD.
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| 2. |
- Ning, Yujie, et al.
(författare)
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Genetic Variants and Protein Alterations of Selenium- and T-2 Toxin-Responsive Genes Are Associated With Chondrocytic Damage in Endemic Osteoarthropathy
- 2022
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Ingår i: Frontiers in Genetics. - : Frontiers Media S.A.. - 1664-8021. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- The mechanism of environmental factors in Kashin-Beck disease (KBD) remains unknown. We aimed to identify single nucleotide polymorphisms (SNPs) and protein alterations of selenium- and T-2 toxin-responsive genes to provide new evidence of chondrocytic damage in KBD. This study sampled the cubital venous blood of 258 subjects including 129 sex-matched KBD patients and 129 healthy controls for SNP detection. We applied an additive model, a dominant model, and a recessive model to identify significant SNPs. We then used the Comparative Toxicogenomics Database (CTD) to select selenium- and T-2 toxin-responsive genes with the candidate SNP loci. Finally, immunohistochemistry was applied to verify the protein expression of candidate genes in knee cartilage obtained from 15 subjects including 5 KBD, 5 osteoarthritis (OA), and 5 healthy controls. Forty-nine SNPs were genotyped in the current study. The C allele of rs6494629 was less frequent in KBD than in the controls (OR = 0.63, p = 0.011). Based on the CTD database, PPARG, ADAM12, IL6, SMAD3, and TIMP2 were identified to interact with selenium, sodium selenite, and T-2 toxin. KBD was found to be significantly associated with rs12629751 of PPARG (additive model: OR = 0.46, p = 0.012; dominant model: OR = 0.45, p = 0.049; recessive model: OR = 0.18, p = 0.018), rs1871054 of ADAM12 (dominant model: OR = 2.19, p = 0.022), rs1800796 of IL6 (dominant model: OR = 0.30, p = 0.003), rs6494629 of SMAD3 (additive model: OR = 0.65, p = 0.019; dominant model: OR = 0.52, p = 0.012), and rs4789936 of TIMP2 (recessive model: OR = 5.90, p = 0.024). Immunohistochemistry verified significantly upregulated PPARG, ADAM12, SMAD3, and TIMP2 in KBD compared with OA and normal controls (p < 0.05). Genetic polymorphisms of PPARG, ADAM12, SMAD3, and TIMP2 may contribute to the risk of KBD. These genes could promote the pathogenesis of KBD by disturbing ECM homeostasis.
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| 3. |
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| 4. |
- Chen, Sijie, et al.
(författare)
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Inverse Estimation of Soil Hydraulic Parameters in a Landslide Deposit Based on a DE-MC Approach
- 2022
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Ingår i: Water. - : MDPI AG. - 2073-4441. ; 14:22
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Tidskriftsartikel (refereegranskat)abstract
- Extreme rainfall is a common triggering factor of landslide disasters, for infiltration and pore water pressure propagation can reduce suction stress and shear strength at the slip surface. The subsurface hydrological model is an essential component in the early-warning system of rainfall-triggered landslides, whereas soil moisture and pore water pressure simulated by the Darcy–Richards equation could be significantly affected by uncertainties in soil hydraulic parameters. This study conducted an inverse analysis of in situ measured soil moisture in an earthquake-induced landslide deposit, and the soil hydraulic parameters were optimized with the Differential Evolution Markov chain Monte Carlo method (DE-MC). The DE-MC approach was initially validated with a synthetic numerical experiment to demonstrate its effectiveness in finding the true soil hydraulic parameters. Besides, the soil water characteristic curve (SWCC) and hydraulic conductivity function (HCF) described with optimized soil hydraulic parameter sets had similar shapes despite the fact that soil hydraulic parameters may be different. Such equifinality phenomenon in inversely estimated soil hydraulic parameters, however, did not affect the performance of simulated soil moisture dynamics in the synthetic numerical experiment. The application of DE-MC to a real case study of a landslide deposit also indicated satisfying model performance in terms of accurate match between the in situ measured soil moisture content and ensemble of simulations. In conclusion, based on the satisfying performance of simulated soil moisture and the posterior probability density function (PDF) of parameter sets, the DE-MC approach can significantly reduce uncertainties in specified prior soil hydraulic parameters. This study suggested the integration of the DE-MC approach with the Darcy–Richards equation for an accurate quantification of unsaturated soil hydrology, which can be an essential modeling strategy to support the early-warning of rainfall-triggered landslides.
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| 5. |
- Shao, Wei, et al.
(författare)
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Reduce uncertainty in soil hydrological modeling : A comparison of soil hydraulic parameters generated by random sampling and pedotransfer function
- 2023
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Ingår i: Journal of Hydrology. - 0022-1694 .- 1879-2707. ; 623
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Tidskriftsartikel (refereegranskat)abstract
- Numerical simulation of unsaturated soil hydrology relies on calibrated soil hydraulic parameters, which are subject to uncertainty due to imperfect information during the inverse modelling. This study investigates the effectiveness of reducing parameter uncertainty using the recently developed Rosetta 3 pedotransfer function. The GLUE method was employed for numerical modeling using the Darcy-Richards equation under two strategies for sampling Mualem-van Genuchten (MvG) parameters: the first uses conventional random generation of MvG parameters (GLUE-random), while the second adopts Rosetta 3 to transfer soil particle composition to MvG parameter (GLUE-Rosetta). Both approaches were used for inverse modeling of 9 typical soils, each with a recommended parameter set defined as true values and associated soil moisture dynamics as observations. The posterior parameters selected with both GLUE-random and GLUE-Rosetta show an equifinality phenomenon. GLUE-random fails to provide well-constrained posterior parameters to recover the pre-defined true values, and its posterior results of soil water characteristic curve (SWCC) and soil hydraulic conductivity function (HCF) are poorly constrained. In contrast, GLUE-Rosetta significantly improves the accuracy of the inversely-estimated soil hydraulic parameters, and the ensemble of posterior SWCC and HCF also encompasses the predefined true curves. The results demonstrate the effectiveness of using Rosetta 3 to reduce the dimensionality of the optimization problem, which results in reliable estimation of soil hydraulic parameters and soil particle compositions. Moreover, GLUE-Rosetta outperforms GLUE-random in predicting soil moisture dynamics under different rainfall intensities. Overall, it is recommended to integrate Rosetta 3 with existing optimization tools to reduce the uncertainty of soil parameters and support more reliable modeling of unsaturated soil hydrology.
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| 6. |
- Shao, Wei, et al.
(författare)
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Reducing uncertainties in hydromechanical modeling with a recently developed Rosetta 3 podeotransfer function
- 2023
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Ingår i: Engineering Geology. - 0013-7952 .- 1872-6917. ; 324
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Tidskriftsartikel (refereegranskat)abstract
- Stability analysis of unsaturated landslide deposits requires reliable estimates of soil moisture and pore water pressure. However, modeled soil moisture and pore water pressure contain substantial uncertainties due to imperfect information on soil hydraulic properties. Due to the relatively high dimensionality, commonly used parameter optimization strategies can be significantly affected by equifinality problems. This study investigates the effectiveness of reducing parameter estimation dimensionality using soil pedo-transfer functions. Specifically, we first estimated soil hydraulic parameters using the traditional Generalized Likelihood Uncertainty Estimation (GLUE) method, with parameters randomly drawn from the entire space (refer to as GLUE-random). In a second strategy, we use the Rosetta 3 pedotransfer function to constrain soil hydraulic parameters (refer to as GLUE-Rosetta). The two methods were tested in a typical landslide deposit with in-situ measured soil moisture dynamics for inverse modeling. The GLUE-random estimated soil hydraulic parameters contained substantial uncertainties –resulting in poorly constrained soil water retention curves (SWCC) and hydraulic conductivity functions (HCF). As a result, the uncertainty bands of pore water pressure and slope stability can cross values with several orders of magnitudes. In contrast, GLUE-Rosetta provided well-constrained SWCC and HCF, which significantly reduce the uncertainties in pore water pressure and slope stability estimates. These results suggest that the Rosetta 3 pedotransfer function can significantly improve the reliability of soil hydraulic parameters by reducing the dimensionality of the optimization problem and high-quality prior information of soil hydraulic properties. In conclusion, Rosetta 3 can enhance the reliability of soil parameters estimates and the reliability of subsurface hydrology, which may benefit the development of landslide early-warning systems.
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