Search

Uncovering the risk factors of pulmonary hypertension and its mechanisms is crucial for the prevention and treatment of the disease. In the current study, we showed that experimental periodontitis, which was established by ligation of molars followed by orally smearing subgingival plaques from patients with periodontitis, exacerbated hypoxia-induced pulmonary hypertension in mice. Mechanistically, periodontitis dysregulated the pulmonary microbiota by promoting ectopic colonization and enrichment of oral bacteria in the lungs, contributing to pulmonary infiltration of interferon gamma positive (IFNγ+) T cells and aggravating the progression of pulmonary hypertension. In addition, we identified Prevotella zoogleoformansas the critical periodontitis-associated bacterium driving the exacerbation of pulmonary hypertension by periodontitis, and the exacerbation was potently ameliorated by both cervical lymph node excision and IFNγ neutralizing antibodies. Our study suggests a proof of concept that the combined prevention and treatment of periodontitis and pulmonary hypertension are necessary.

Supramolecular polymers are fascinating materials due to their strikingly self-healing capabilities empowered by reversible bonds. However, due to the lack of knowledge about the molecular structure evolution at the fractured interfaces, there is no existing theory to explain and predict the diverse healing times of different supramolecular materials observed in experiments. Here, we systematically study the self-adhesion of both unentangled and entangled supramolecular polymer networks through molecular simulations. We find that the recovery of macroscopic interfacial strength almost linearly depends on the microscopic molecular formations at fractured interfaces of supramolecular polymers, including reversible bonds and entanglements (entangled systems only). More importantly, we place the healing time into the context of intrinsic relaxation timescales of supramolecular polymer networks. It is found that the intrinsic sticky Rouse time features the self-adhesion process of all fractured supramolecular polymers, representing the full recovery of interfacial strength. At this critical timescale, two things happened to guarantee the full recovery of fractured systems: (i) polymer chains have diffused across the fractured interface with a displacement comparable to their sizes; (ii) the crossed stickers and polymer chains have updated their reversible bonds and entanglements (entangled systems only), respectively. The clear molecular description and suggested characteristic self-adhesion time will help the molecular design of supramolecular polymers.

To understand the potential cytotoxicity of perfluoroalkyl substances (PFAS), we study their interactions with a model phospholipid bilayer membrane using molecular dynamics (MD) simulations. Four typical PFAS molecules are investigated, including perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorooctanesulfonic acid (PFOS), and perfluorohexane sulfonate (PFHxS). All of these PFAS molecules are found to spontaneously penetrate the lipid bilayer within a short simulation time (a few nanoseconds). During the penetration process, further free-energy analysis reveals that a PFAS molecule encounters an energy barrier at the bilayer/water interface. To overcome this free-energy barrier, the PFAS molecule flips itself at the interface. We further investigate the influence of embedded PFAS molecules on the membrane properties. All of the embedded PFAS molecules are found to produce a cholesterol-like condensing effect on the lipid bilayer, which includes increases of the order parameters of lipid tails and the thickness of the lipid bilayer and a decrease of area per lipid. Moreover, the PFAS molecules are found to form hydrogen bonds with oxygen atoms at three different positions of a lipid molecule. Our work reveals the penetration pathway of PFAS molecules entering into a lipid bilayer. In addition, the cholesterol-like condensing effect induced by embedded PFAS molecules on model membranes is systematically investigated and discussed. Our simulations can help understand the physical mechanisms of PFAS cytotoxicity.

Nanomaterials have been widely used in the design of drug delivery platforms. This work computationally explores the vascular dynamics of nanoworms as drug carriers within blood flow by considering the effects of nanoworm length, stiffness, and local physiological conditions such as hematocrit. We found that nanoworms with length of 8 μm and moderate stiffness are the optimal choice as drug carriers for circulating within normal vascular network due to their lower near wall margination. Compared to those of spherical rigid particles, these nanoworms demonstrate significant demargination behaviors at hematocrit 20%, induced by the local hydrodynamic interactions. Specifically, the interactions between nanoworms and red blood cells create asymmetrical local flow fields, resulting in the demargination of nanoworms. In addition, the flexibility of nanoworms enables them to conform to the deformed shape of red blood cells under shear flow, leading to their high concentration within the core region of vessels. Therefore, the long blood circulation time of nanoworms can be partially attributed to their demargination behaviors and intertwinement with red blood cells. According to these simulation results, tuning the length and stiffness of nanoworms is the key to design drug carries with reduced near wall margination within normal vascular networks and extend their blood circulation time.

Using coarse-grained molecular dynamics simulations, we systematically investigate the receptor-mediated endocytosis of elastic nanoparticles (NPs) with different sizes, ranging from 25 to 100 nm, and shapes, including sphere-like, oblate-like, and prolate-like. Simulation results provide clear evidence that the membrane wrapping efficiency of NPs during endocytosis is a result of competition between receptor diffusion kinetics and thermodynamic driving force. The receptor diffusion kinetics refer to the kinetics of receptor recruitment that are affected by the contact edge length between the NP and membrane. The thermodynamic driving force represents the amount of required free energy to drive NPs into a cell. Under the volume constraint of elastic NPs, the soft spherical NPs are found to have similar contact edge lengths to rigid ones and to less efficiently be fully wrapped due to their elastic deformation. Moreover, the difference in wrapping efficiency between soft and rigid spherical NPs increases with their sizes, due to the increment of their elastic energy change. Furthermore, because of its prominent large contact edge length, the oblate ellipsoid is found to be the least sensitive geometry to the variation in NP’s elasticity among the spherical, prolate, and oblate shapes during the membrane wrapping. In addition, simulation results indicate that conflicting experimental observations on the efficiency of cellular uptake of elastic NPs could be caused by their different mechanical properties. Our simulations provide a detailed mechanistic understanding about the influence of NPs’ size, shape, and elasticity on their membrane wrapping efficiency, which serves as a rational guidance for the design of NP-based drug carriers.

Query refinement is essential for information retrieval. In this study, a fuzzy-related thesaurus based query refinement mechanism is proposed. This thesaurus can be dynamically generated during the retrieval process for a document collection that is classified by an unsupervised neural network, the self-organising map. In contrast with general relational thesaurus, the fuzzy-related thesaurus is more effective and efficient. The relationships between the terms are based on the classification of a document collection, and thus, the generated thesaurus naturally has more power to enhance retrieval quality. The recognition of the relationships can be done automatically without human involvement, which significantly reduces the cost associated with the construction of the thesaurus. An evaluation on the query refinement mechanism based on the fuzzy-related thesaurus has conducted and the preliminary result is promising. A significant improvement on retrieval performance was observed when a fuzzy-related thesaurus was used for query refinement for a software document collection.

The self-organizing map (SOM) can classify documents by learning about their interrelationships from its input data. The dimensionality of the SOM input data space based on a document collection is generally high. As the computational complexity of the SOM increases in proportion to the dimension of its input space, high dimensionality not only lowers the efficiency of the initial learning process but also lowers the efficiencies of the subsequent retrieval and the relearning process whenever the input data is updated. A new method called feature competitive algorithm(FCA) is proposed to overcome this problem. The FCA can capture the most significant features that characterize the underlying interrelationships of the entities in the input space to form a dimensionally reduced input space without excessively losing of essential information about the interrelationships. The proposed method was applied to a document collection, consisting of 97 UNIX command manual pages, to test its feasibility and effectiveness. The test results are encouraging. Further discussions on several crucial issues about the FCA are also presented.

Due to the lack of therapeutics and vaccines, diagnostics of COVID-19 emerges as one of the primary tools for controlling the spread of SARS-COV-2. Here we aim to develop a theoretical model to study the detection process of SARS-COV-2 in lateral flow device (LFD), which can achieve rapid antigen diagnostic tests. The LFD is modeled as the adhesion of a spherical nanoparticle (NP) coated with ligands on the surface, mimicking the SARS-COV-2, on an infinite substrate distributed with receptors under a simple shear flow. The adhesive behaviors of NPs in the LFD are governed by the ligand–receptor binding (LRB) and local hydrodynamics. Through energy balance analysis, three types of motion are predicted: (i) firm-adhesion (FA); (ii) adhesive-rolling (AR); and (iii) free-rolling (FR), which correspond to LRB-dominated, LRB-hydrodynamics-competed, and hydrodynamics-dominated regimes, respectively. The transitions of FA-to-AR and AR-to-FR are found to be triggered by overcoming LRB barrier and saturation of LRB torque, respectively. Most importantly, in the AR regime, the smaller NPs can move faster than their larger counterparts, induced by the LRB effect that depends on the radius Rof NPs. In addition, a scaling law is found in the AR regime that v∝γ̇Rα(rolling velocity vand shear rate γ̇), with an approximate scaling factor α∼−0.2±0.05identified through fitting both theoretical and numerical results. The scaling factor emerges from the energy-based stochastic LRB model, and is confirmed to be universal by examining selections of different LRB model parameters. This size-dependent rolling behavior under the control of flow strength may provide the theoretical guidance for designing efficient LFD in detecting infectious disease.