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  1. Chong MY, Gu B, Armour CH, Dokos S, Ong ZC, Xu XY, et al.
    Biomech Model Mechanobiol, 2022 Feb;21(1):261-275.
    PMID: 35079931 DOI: 10.1007/s10237-021-01534-5
    False lumen thrombosis (FLT) in type B aortic dissection has been associated with the progression of dissection and treatment outcome. Existing computational models mostly assume rigid wall behavior which ignores the effect of flap motion on flow and thrombus formation within the FL. In this study, we have combined a fully coupled fluid-structure interaction (FSI) approach with a shear-driven thrombosis model described by a series of convection-diffusion reaction equations. The integrated FSI-thrombosis model has been applied to an idealized dissection geometry to investigate the interaction between vessel wall motion and growing thrombus. Our simulation results show that wall compliance and flap motion can influence the progression of FLT. The main difference between the rigid and FSI models is the continuous development of vortices near the tears caused by drastic flap motion up to 4.45 mm. Flap-induced high shear stress and shear rates around tears help to transport activated platelets further to the neighboring region, thus speeding up thrombus formation during the accelerated phase in the FSI models. Reducing flap mobility by increasing the Young's modulus of the flap slows down the thrombus growth. Compared to the rigid model, the predicted thrombus volume is 25% larger using the FSI-thrombosis model with a relatively mobile flap. Furthermore, our FSI-thrombosis model can capture the gradual effect of thrombus growth on the flow field, leading to flow obstruction in the FL, increased blood viscosity and reduced flap motion. This model is a step closer toward simulating realistic thrombus growth in aortic dissection, by taking into account the effect of intimal flap and vessel wall motion.
  2. Chong MY, Gu B, Chan BT, Ong ZC, Xu XY, Lim E
    Int J Numer Method Biomed Eng, 2020 12;36(12):e3399.
    PMID: 32862487 DOI: 10.1002/cnm.3399
    A monolithic, fully coupled fluid-structure interaction (FSI) computational framework was developed to account for dissection flap motion in acute type B aortic dissection (TBAD). Analysis of results included wall deformation, pressure, flow, wall shear stress (WSS), von Mises stress and comparison of hemodynamics between rigid wall and FSI models. Our FSI model mimicked realistic wall deformation that resulted in maximum compression of the distal true lumen (TL) by 21.4%. The substantial movement of intimal flap mostly affected flow conditions in the false lumen (FL). Flap motion facilitated more flow entering the FL at peak systole, with the TL to FL flow split changing from 88:12 in the rigid model to 83:17 in the FSI model. There was more disturbed flow in the FL during systole (5.8% FSI vs 5.2% rigid) and diastole (13.5% FSI vs 9.8% rigid), via a λ2 -criterion. The flap-induced disturbed flow near the tears in the FSI model caused an increase of local WSS by up to 70.0% during diastole. This resulted in a significant reduction in the size of low time-averaged WSS (TAWSS) regions in the FL (113.11 cm2 FSI vs 177.44 cm2 rigid). Moreover, the FSI model predicted lower systolic pressure, higher diastolic pressure, and hence lower pulse pressure. Our results provided new insights into the possible impact of flap motion on flow in aortic dissections, which are particularly important when evaluating hemodynamics of acute TBAD. NOVELTY STATEMENT: Our monolithic fully coupled FSI computational framework is able to reproduce experimentally measured range of flap deformation in aortic dissection, thereby providing novel insights into the influence of physiological flap motion on the flow and pressure distributions. The drastic flap movement increases the flow resistance in the true lumen and causes more disturbed flow in the false lumen, as visualized through the λ2 criterion. The flap-induced luminal pressure is dampened, thereby affecting pressure measures, which may serve as potential prognostic indicators for late complications in acute uncomplicated TBAD patients.
  3. Zhong H, Tang W, Li Z, Sonne C, Lam SS, Zhang X, et al.
    Nat Food, 2024 Apr;5(4):301-311.
    PMID: 38605129 DOI: 10.1038/s43016-024-00954-7
    Contamination of rice by the potent neurotoxin methylmercury (MeHg) originates from microbe-mediated Hg methylation in soils. However, the high diversity of Hg methylating microorganisms in soils hinders the prediction of MeHg formation and challenges the mitigation of MeHg bioaccumulation via regulating soil microbiomes. Here we explored the roles of various cropland microbial communities in MeHg formation in the potentials leading to MeHg accumulation in rice and reveal that Geobacteraceae are the key predictors of MeHg bioaccumulation in paddy soil systems. We characterized Hg methylating microorganisms from 67 cropland ecosystems across 3,600 latitudinal kilometres. The simulations of a rice-paddy biogeochemical model show that MeHg accumulation in rice is 1.3-1.7-fold more sensitive to changes in the relative abundance of Geobacteraceae compared to Hg input, which is recognized as the primary parameter in controlling MeHg exposure. These findings open up a window to predict MeHg formation and accumulation in human food webs, enabling more efficient mitigation of risks to human health through regulations of key soil microbiomes.
  4. Tang W, Bai X, Zhou Y, Sonne C, Wu M, Lam SS, et al.
    Nat Food, 2024 Jan;5(1):72-82.
    PMID: 38177223 DOI: 10.1038/s43016-023-00910-x
    Dietary exposure to methylmercury (MeHg) causes irreversible damage to human cognition and is mitigated by photolysis and microbial demethylation of MeHg. Rice (Oryza sativa L.) has been identified as a major dietary source of MeHg. However, it remains unknown what drives the process within plants for MeHg to make its way from soils to rice and the subsequent human dietary exposure to Hg. Here we report a hidden pathway of MeHg demethylation independent of light and microorganisms in rice plants. This natural pathway is driven by reactive oxygen species generated in vivo, rapidly transforming MeHg to inorganic Hg and then eliminating Hg from plants as gaseous Hg°. MeHg concentrations in rice grains would increase by 2.4- to 4.7-fold without this pathway, which equates to intelligence quotient losses of 0.01-0.51 points per newborn in major rice-consuming countries, corresponding to annual economic losses of US$30.7-84.2 billion globally. This discovered pathway effectively removes Hg from human food webs, playing an important role in exposure mitigation and global Hg cycling.
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