Asiatic acid alleviates vascular remodeling in BAPN-induced aortic dissection through inhibiting NF-κB p65/CX3CL1 signaling.

Inflammation assumes a pivotal role in the aortic remodeling of aortic dissection (AD). Asiatic acid (AA), a triterpene compound, is recognized for its strong anti-inflammatory properties. Yet, its effects on ß-aminopropionitrile (BAPN)-triggered AD have not been clearly established. The objective is to determine whether AA attenuates adverse aortic remodeling in BAPN-induced AD and clarify potential molecular mechanisms. In vitro studies, RAW264.7 cells pretreated with AA were challenged with lipopolysaccharide (LPS), and then the vascular smooth muscle cells (VSMCs)-macrophage coculture system was established to explore intercellular interactions. To induce AD, male C57BL/6J mice at three weeks of age were administered BAPN at a dosage of 1 g/kg/d for four weeks. To decipher the mechanism underlying the effects of AA, RNA sequencing analysis was conducted, with subsequent validation of these pathways through cellular experiments. AA exhibited significant suppression of M1 macrophage polarization. In the cell coculture system, AA facilitated the transformation of VSMCs into a contractile phenotype. In the mouse model of AD, AA strikingly prevented the BAPN-induced increases in inflammation cell infiltration and extracellular matrix degradation. Mechanistically, RNA sequencing analysis revealed a substantial upregulation of CX3CL1 expression in BAPN group but downregulation in AA-treated group. Additionally, it was observed that the upregulation of CX3CL1 negated the beneficial impact of AA on the polarization of macrophages and the phenotypic transformation of VSMCs. Crucially, our findings revealed that AA is capable of downregulating CX3CL1 expression, accomplishing this by obstructing the nuclear translocation of NF-κB p65. The findings indicate that AA holds promise as a prospective treatment for adverse aortic remodeling by suppressing the activity of NF-κB p65/CX3CL1 signaling pathway.

Chlorine-Coordinated Pd Single Atom Enhanced the Chlorine Resistance for Volatile Organic Compound Degradation: Mechanism Study.

The development of catalysts with high chlorine resistance for volatile organic compound (VOC) degradation is of great significance to achieve air purification. Herein, Pd@ZrO2 catalysts with monodispersed Pd atoms coordinated with Cl were prepared using an in situ grown Zr-based metal-organic framework (MOF) as the sacrifice templates to enhance the chlorine resistance for VOC elimination. The residual Cl species from the Zr-MOF coordinated with Pd, forming Pd1-Cl species during the pyrolysis. Meanwhile, abundant oxygen vacancies (VO) were generated, which enhanced the adsorption and activation of gaseous oxygen molecules, accelerating the degradation of VOCs. In addition, the Pd@ZrO2 catalysts exhibited satisfactory water resistance, long-term stability, and great resistance to CO and dichloromethane (DCM) for VOC elimination. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) results elucidated that the generation of Pd1-Cl species in Pd@ZrO2 suppressed the absorption of DCM, releasing more active sites for toluene and its intermediate adsorption. Simultaneously, the monodispersed Pd atoms and VO improved the reactivity of gaseous oxygen molecule adsorption and dissociation, boosting the deep decomposition of toluene and its intermediates. This work may provide a new strategy for rationally designing high-chlorine resistance catalysts for VOC elimination to improve the atmospheric environment.

Universitetet i Oslo-67 (UiO-67)/graphite oxide composites with high capacities of toluene: Synthesis strategy and adsorption mechanism insight.

In this paper, a simple solvothermal synthesis method was proposed for the preparation of metal organic framework/graphene oxide hybrid nanocomposite (UiO-67/GO). A series of UiO-67/GO composites were prepared by varying the addition forms and amounts of GO, and the optimal synthesis conditions were screened. The composites were characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR), transmission Electron Microscope (TEM), scanning electron microscopy (SEM), X-ray photoelectron spectroscopic (XPS), water contact angles (CA) and thermogravimetric analysis (TGA). The adsorption capacity and the adsorption process of toluene were investigated by dynamic adsorption and adsorption kinetics, respectively. The results indicated that 67/GO-0.5% reached the maximum adsorption capacity (876 mg g-1), which far exceeded the other adsorbents. Kinetic model and the Weber-Morris model correlated satisfactorily to the experimental data. The improved adsorption performance was attributed to GO, which enhanced π-π interaction, promoted defect generation and provided more adsorption sites. Finally, the excellent regeneration performance of the adsorbent was verified by temperature programmed desorption (TPD) and cyclic adsorption-desorption experiments. Moreover, the adsorption mechanism was further revealed. Combined with the related adsorption experiments and the density functional theory (DFT) analysis, the efficient removal of toluene by UiO-67/GO was attributed to the cooperation of defects, π-π interaction and hydrogen bonding.

Anomalously slow attrition times for asymmetric populations with internal group dynamics.

The many-body dynamics exhibited by living objects include group formation within a population and the nonequilibrium process of attrition between two opposing populations due to competition or conflict. We show analytically and numerically that the combination of these two dynamical processes generates an attrition duration T whose nonlinear dependence on population asymmetry x is in stark contrast to standard mass-action theories. A minority population experiences a longer survival time than two equally balanced populations, irrespective of whether or not the majority population adopts such an internal grouping. Adding a third population with predefined group sizes allows T(x) to be tailored. Our findings compare favorably to real-world observations.

Human group formation in online guilds and offline gangs driven by a common team dynamic.

Quantifying human group dynamics represents a unique challenge. Unlike animals and other biological systems, humans form groups in both real (offline) and virtual (online) spaces-from potentially dangerous street gangs populated mostly by disaffected male youths to the massive global guilds in online role-playing games for which membership currently exceeds tens of millions of people from all possible backgrounds, age groups, and genders. We have compiled and analyzed data for these two seemingly unrelated offline and online human activities and have uncovered an unexpected quantitative link between them. Although their overall dynamics differ visibly, we find that a common team-based model can accurately reproduce the quantitative features of each simply by adjusting the average tolerance level and attribute range for each population. By contrast, we find no evidence to support a version of the model based on like-seeking-like (i.e., kinship or "homophily").

Model for in vivo progression of tumors based on co-evolving cell population and vasculature.

With countless biological details emerging from cancer experiments, there is a growing need for minimal mathematical models which simultaneously advance our understanding of single tumors and metastasis, provide patient-personalized predictions, whilst avoiding excessive hard-to-measure input parameters which complicate simulation, analysis and interpretation. Here we present a model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in a murine mammary cell line EMT6-HER2 model in BALB/c mice and with clinical metastasis data. Seeding data about the tumor and its vasculature from in vivo images, our model predicts corridors of future tumor growth behavior and intervention response. A scaling relation enables the estimation of a tumor's most likely evolution and pinpoints specific target sites to control growth. Our findings suggest that the clinically separate phenomena of individual tumor growth and metastasis can be viewed as mathematical copies of each other differentiated only by network structure.

Effect of social group dynamics on contagion.

Despite the many works on contagion phenomena in both well-mixed systems and heterogeneous networks, there is still a lack of understanding of the intermediate regime where social group structures evolve on a similar time scale to individual-level transmission. We address this question by considering the process of transmission through a model population comprising social groups which follow simple dynamical rules for growth and breakup. Despite the simplicity of our model, the profiles produced bear a striking resemblance to a wide variety of real-world examples--in particular, empirical data that we have obtained for social (i.e., YouTube), financial (i.e., currency markets), and biological (i.e., colds in schools) systems. The observation of multiple resurgent peaks and abnormal decay times is qualitatively reproduced within the model simply by varying the time scales for group coalescence and fragmentation. We provide an approximate analytic treatment of the system and highlight a novel transition which arises as a result of the social group dynamics.