Search for: All records

Claudin-15 (CLDN15) molecules form channels that directly regulate cation and water transport. In the gastrointestinal tract, this transport indirectly impacts nutrient absorption. However, the mechanisms governing ion transport through these channels remain poorly understood. We addressed this question by building on our previous cell culture studies and all atom molecular dynamic simulation model of CLDN15. By mutating D55 to a bulkier glutamic acid (E) or neutral amino acid asparagine (N), our in vitro measurements showed that the D55E mutation decreased charge selectivity and favored small ion permeability, while the D55N mutation led to reduced charge selectivity without markedly altering size selectivity. By establishing a simplified (reduced) CLDN15 molecular dynamics model that excludes non-essential transmembrane regions, we were able to probe how D55 modified cation dehydration, charge interaction, and permeability. These results provide novel insight into organization of the CLDN15 selectivity filter and suggests that D55 plays a dual role in shaping both electrostatic and steric properties of the pore, but its electrostatic role is more prominent in determining CLDN15 cation permeability. This knowledge can be used toward the development of effective strategies to modulate CLDN15 function. The experimental approach established can be further extended to study the function of other claudin channels. Together, these advancements will help us to modulate tight junctions to promote human health. 

Recent advancements in large language models (LLMs) have achieved promising performances across various applications. Nonetheless, the ongoing challenge of integrating long-tail knowledge continues to impede the seamless adoption of LLMs in specialized domains. In this work, we introduce DALK, a.k.a. Dynamic Co-Augmentation of LLMs and KG, to address this limitation and demonstrate its ability on studying Alzheimer's Disease (AD), a specialized sub-field in biomedicine and a global health priority. With a synergized framework of LLM and KG mutually enhancing each other, we first leverage LLM to construct an evolving AD-specific knowledge graph (KG) sourced from AD-related scientific literature, and then we utilize a coarse-to-fine sampling method with a novel self-aware knowledge retrieval approach to select appropriate knowledge from the KG to augment LLM inference capabilities. The experimental results, conducted on our constructed AD question answering (ADQA) benchmark, underscore the efficacy of DALK. Additionally, we perform a series of detailed analyses that can offer valuable insights and guidelines for the emerging topic of mutually enhancing KG and LLM. 

Abstract Hyporheic exchange leads to the transfer of gases, solutes, and fine particles across the sediment‐water interface, playing a critical role in biogeochemical cycles and pollutant transport in aquatic environments. While in‐channel vegetation has been recognized to enhance hyporheic exchange, the mechanisms remain poorly understood. Here, we investigated how an emergent vegetation canopy impacts hyporheic exchange using refractive index‐matched flume experiments and coupled numerical simulations. Our results show that at the same mean surface flow velocity, vegetation increases the hyporheic exchange velocity by four times compared to the non‐vegetated channel. However, the hyporheic exchange velocity does not increase further with increasing vegetation density. In addition, our results show that the hyporheic exchange velocity scales with the square root of sediment permeability. Our findings provide a predictive framework for hyporheic exchange in vegetated channels with varying vegetation densities and sediment permeabilities and could guide the future design of environmental management and restoration projects using vegetation. 

We develop a consistent adaptive framework in a multilevel collocated grid layout for simulating two-phase flows with adaptive mesh refinement (AMR). The conservative mo-mentum equations and the mass equation are solved in the present consistent framework. This consistent mass and momentum transport treatment greatly improves the accuracy and robustness for simulating two-phase flows with a high density ratio and high Reynolds number. The interface capturing level set method is coupled with the conservative form of the Navier–Stokes equations, and the multilevel reinitialization technique is applied for mass conservation. This adaptive framework allows us to advance all variables level by level using either the subcycling or the non-subcycling method to decouple the data ad-vancement on each level. The accuracy and robustness of the framework are validated by a variety of canonical two-phase flow problems. We demonstrate that the consistent scheme results in a numerically stable solution in flows with high density ratios(up to 106) and high Reynolds numbers(up to 106), while the inconsistent scheme exhibits non-physical fluid behaviors in these tests. Furthermore, it is shown that the subcycling and non-subcycling methods provide consistent results and that both of them can accurately resolve the interfaces of the two-phase flows with surface tension effects. Finally, a 3D breaking wave problem is simulated to show the efficiency and significant speedup of the proposed framework using AMR. 

We develop a consistent adaptive framework in a multilevel collocated grid layout for simulating two-phase flows with adaptive mesh refinement (AMR). The conservative mo-mentum equations and the mass equation are solved in the present consistent framework. This consistent mass and momentum transport treatment greatly improves the accuracy and robustness for simulating two-phase flows with a high density ratio and high Reynolds number. The interface capturing level set method is coupled with the conservative form of the Navier–Stokes equations, and the multilevel reinitialization technique is applied for mass conservation. This adaptive framework allows us to advance all variables level by level using either the subcycling or the non-subcycling method to decouple the data ad-vancement on each level. The accuracy and robustness of the framework are validated by a variety of canonical two-phase flow problems. We demonstrate that the consistent scheme results in a numerically stable solution in flows with high density ratios(up to 106) and high Reynolds numbers(up to 106), while the inconsistent scheme exhibits non-physical fluid behaviors in these tests. Furthermore, it is shown that the subcycling and non-subcycling methods provide consistent results and that both of them can accurately resolve the interfaces of the two-phase flows with surface tension effects. Finally, a 3D breaking wave problem is simulated to show the efficiency and significant speedup of the proposed framework using AMR. 

Abstract By measuring a linear response function directly, such as the dynamic susceptibility, one can understand fundamental material properties. However, a fresh perspective can be offered by studying fluctuations. This can be related back to the dynamic susceptibility through the fluctuation–dissipation theorem, which relates the fluctuations in a system to its response, an alternate route to access the physics of a material. Here, we describe a new X-ray tool for material characterization that will offer an opportunity to uncover new physics in quantum materials using this theorem. We provide details of the method and discuss the requisite analysis techniques in order to capitalize on the potential to explore an uncharted region of phase space. This is followed by recent results on a topological chiral magnet, together with a discussion of current work in progress. We provide a perspective on future measurements planned for work in unconventional superconductivity. Graphical abstract We describe a new X-ray tool for material characterization that will offer an opportunity to uncover new physics in quantum materials using coherent, short-pulsed X-rays. We provide details of the method and discuss the requisite analysis techniques in order to capitalize on the potential to explore an uncharted region of phase space. This is followed by recent results on a topological chiral magnet, together with a discussion of current work in progress. We provide a perspective on future measurements planned for work in unconventional superconductivity.