Ursolic acid enhances macrophage autophagy and attenuates atherogenesis

Macrophage autophagy has been shown to be protective against atherosclerosis. We previously discovered that ursolic acid (UA) promoted cancer cell autophagy. In the present study, we aimed to examine whether UA enhances macrophage autophagy in the context of atherogenesis. Cell culture study showed that UA enhanced autophagy of macrophages by increasing the expression of Atg5 and Atg16l1, which led to altered macrophage function. UA reduced pro-interleukin (IL)-1β protein levels and mature IL-1β secretion in macrophages in response to lipopolysaccharide (LPS), without reducing IL-1β mRNA expression. Confocal microscopy showed that in LPS-treated macrophages, UA increased LC3 protein levels and LC3 appeared to colocalize with IL-1β. In cholesterol-loaded macrophages, UA increased cholesterol efflux to apoAI, although it did not alter mRNA or protein levels of ABCA1 and ABCG1. Electron microscopy showed that UA induced lipophagy in acetylated LDL-loaded macrophages, which may result in increased cholesterol ester hydrolysis in autophagolysosomes and presentation of free cholesterol to the cell membrane. In LDLR(−/−) mice fed a Western diet to induce atherogenesis, UA treatment significantly reduced atherosclerotic lesion size, accompanied by increased macrophage autophagy. In conclusion, the data suggest that UA promotes macrophage autophagy and, thereby, suppresses IL-1β secretion, promotes cholesterol efflux, and attenuates atherosclerosis in mice

The Combined Signatures of Hypoxia and Cellular Landscape Provides a Prognostic and Therapeutic Biomarker in HBV-Related Hepatocellular Carcinoma

Prognosis and treatment options of HBV-related hepatocellular carcinoma (HBV-HCC) are generally based on tumor burden and liver function. Yet, tumor growth and therapeutic resistance of HBV-HCC are strongly influenced by intratumoral hypoxia and cells infiltrating the tumor microenvironment (TME). We, therefore, studied whether linking parameters associated with hypoxia and TME cells could have a better prediction of prognosis and therapeutic responses. Quantification of 109 hypoxia-related genes and 64 TME cells was performed in 452 HBV-HCC tumors. Prognostic hypoxia and TME cells signatures were determined based on Cox regression and meta-analysis for generating the Hypoxia-TME classifier. Thereafter, the prognosis, tumor, and immune characteristics as well as the benefit of therapies in Hypoxia-TME defined subgroups were analyzed. Patients in the Hypoxialow /TMEhigh subgroup showed a better prognosis and therapeutic responses than any other subgroups, which can be well elucidated based on the differences in terms of immune-related molecules, tumor somatic mutations, and cancer cellular signaling pathways. Notably, our analysis furthermore demonstrated the synergistic influence of hypoxia and TME on tumor metabolism and proliferation. Besides, the classifier allowed a further subdivision of patients with early- and late-HCC stages. In addition, the Hypoxia-TME classifier was validated in another independent HBV-HCC cohort (n=144) and several pan-cancer cohorts. Overall, the Hypoxia-TME classifier showed a pretreatment predictive value for prognosis and therapeutic responses, which might provide new directions for strategizing patients with optimal therapies. This article is protected by copyright. All rights reserved

Global Behavior of a Discrete Survival Model with Several Delays

The difference equation yn+1−yn=−αyn+∑j=1mβje−γjyn−kj is studied and some sufficient conditions which guarantee that all solutions of the equation are oscillatory, or that the positive equilibrium of the equation is globally asymptotically stable, are obtained

A prediction-based forward-looking vehicle dispatching strategy for dynamic ride-pooling

For on-demand dynamic ride-pooling services, e.g., Uber Pool and Didi Pinche, a well-designed vehicle dispatching strategy is crucial for platform profitability and passenger experience. Most existing dispatching strategies overlook incoming pairing opportunities, therefore suffer from short-sighted limitations. In this paper, we propose a forward-looking vehicle dispatching strategy, which first predicts the expected distance saving that could be brought about by future orders and then solves a bipartite matching problem based on the prediction to match passengers with partially occupied or vacant vehicles or keep passengers waiting for next rounds of matching. To demonstrate the performance of the proposed strategy, a number of simulation experiments and comparisons are conducted based on the real-world road network and historical trip data from Haikou, China. Results show that the proposed strategy outperform the baseline strategies by generating approximately 31\% more distance saving and 18\% less average passenger detour distance. It indicates the significant benefits of considering future pairing opportunities in dispatching, and highlights the effectiveness of our innovative forward-looking vehicle dispatching strategy in improving system efficiency and user experience for dynamic ride-pooling services

Liver fatty acid composition in mice with or without nonalcoholic fatty liver disease

<p>Abstract</p> <p>Background</p> <p>Nonalcoholic fatty liver disease (NAFLD) is one of the most frequent causes of abnormal liver function. Because fatty acids can damage biological membranes, fatty acid accumulation in the liver may be partially responsible for the functional and morphological changes that are observed in nonalcoholic liver disease. The aim of this study was to use gas chromatography-mass spectrometry to evaluate the fatty acid composition of an experimental mouse model of NAFLD induced by high-fat feed and CCl₄and to assess the association between liver fatty acid accumulation and NAFLD. C57BL/6J mice were given high-fat feed for six consecutive weeks to develop experimental NAFLD. Meanwhile, these mice were given subcutaneous injections of a 40% CCl₄-vegetable oil mixture twice per week.</p> <p>Results</p> <p>A pathological examination found that NAFLD had developed in the C57BL/6J mice. High-fat feed and CCl₄led to significant increases in C14:0, C16:0, C18:0 and C20:3 (P < 0.01), and decreases in C15:0, C18:1, C18:2 and C18:3 (P < 0.01) in the mouse liver. The treatment also led to an increase in SFA and decreases in other fatty acids (UFA, PUFA and MUFA). An increase in the ratio of product/precursor n-6 (C20:4/C18:2) and n-3 ([C20:5+C22:6]/C18:3) and a decrease in the ratio of n-6/n-3 (C20:4/[C20:5+C22:6]) were also observed.</p> <p>Conclusion</p> <p>These data are consistent with the hypothesis that fatty acids are deranged in mice with non-alcoholic fatty liver injury induced by high-fat feed and CCl₄, which may be involved in its pathogenesis and/or progression via an unclear mechanism.</p

Intraperitoneal Injection is Not Always a Suitable Alternative to Intravenous Injection for Radiotherapy

Abstract Intraperitoneal (IP) injection is frequently reported to be as effective as intravenous (IV) injection. Because it allows administering a larger volume with more radioactivity, we have investigated this route and the possibility of using it to circumvent the volume constraint we earlier experienced with pretargeting radiotherapy. Using 99mTc as the label, the pharmacokinetics (PK) of the cMORF effector (a DNA analogue) was evaluated after IP or IV injection in normal mice by necropsy and SPECT/CT imaging. In another experiment, nude mice bearing tumors were used and they received MORF-CC49 pretargeting antibody IV 2 days earlier than labeled cMORF IV or IP. Tumor accumulations of cMORF were measured at 6 hours after its injections. The absorbed radiation doses for 188Re or 90Y pretargeting were estimated using the 99mTc data and a self-absorbed model. Although the absorbed radiation doses to other organs were comparable, the dose to intestines after IP injection was 30-fold higher than IV injection due to the slow entry into the circulation. It had reached such a level as high as the dose to the kidneys that cleared the radioactivity and usually were at the highest level. Nevertheless, the slow entry did not reduce the tumor accumulation. In conclusion, using IP in place of IV led to an unacceptably high absorbed radiation dose to the intestines although the tumor accumulation was not compromised. This effect may be applicable to other radiotherapeutic agents as well

Dynamic Transfer Learning across Graphs

Transferring knowledge across graphs plays a pivotal role in many high-stake domains, ranging from transportation networks to e-commerce networks, from neuroscience to finance. To date, the vast majority of existing works assume both source and target domains are sampled from a universal and stationary distribution. However, many real-world systems are intrinsically dynamic, where the underlying domains are evolving over time. To bridge the gap, we propose to shift the problem to the dynamic setting and ask: given the label-rich source graphs and the label-scarce target graphs observed in previous T timestamps, how can we effectively characterize the evolving domain discrepancy and optimize the generalization performance of the target domain at the incoming T+1 timestamp? To answer the question, for the first time, we propose a generalization bound under the setting of dynamic transfer learning across graphs, which implies the generalization performance is dominated by domain evolution and domain discrepancy between source and target domains. Inspired by the theoretical results, we propose a novel generic framework DyTrans to improve knowledge transferability across dynamic graphs. In particular, we start with a transformer-based temporal encoding module to model temporal information of the evolving domains; then, we further design a dynamic domain unification module to efficiently learn domain-invariant representations across the source and target domains. Finally, extensive experiments on various real-world datasets demonstrate the effectiveness of DyTrans in transferring knowledge from dynamic source domains to dynamic target domains

Boosting Nitrate to Ammonia Electroconversion through Hydrogen Gas Evolution over Cu-foam@mesh Catalysts.

The hydrogen evolution reaction (HER) is often considered parasitic to numerous cathodic electro-transformations of high technological interest, including but not limited to metal plating (e.g., for semiconductor processing), the CO2 reduction reaction (CO2RR), the dinitrogen → ammonia conversion (N2RR), and the nitrate reduction reaction (NO3-RR). Herein, we introduce a porous Cu foam material electrodeposited onto a mesh support through the dynamic hydrogen bubble template method as an efficient catalyst for electrochemical nitrate → ammonia conversion. To take advantage of the intrinsically high surface area of this spongy foam material, effective mass transport of the nitrate reactants from the bulk electrolyte solution into its three-dimensional porous structure is critical. At high reaction rates, NO3-RR becomes, however, readily mass transport limited because of the slow nitrate diffusion into the three-dimensional porous catalyst. Herein, we demonstrate that the gas-evolving HER can mitigate the depletion of reactants inside the 3D foam catalyst through opening an additional convective nitrate mass transport pathway provided the NO3-RR becomes already mass transport limited prior to the HER onset. This pathway is achieved through the formation and release of hydrogen bubbles facilitating electrolyte replenishment inside the foam during water/nitrate co-electrolysis. This HER-mediated transport effect "boosts" the effective limiting current of nitrate reduction, as evidenced by potentiostatic electrolyses combined with an operando video inspection of the Cu-foam@mesh catalysts under operating NO3-RR conditions. Depending on the solution pH and the nitrate concentration, NO3-RR partial current densities beyond 1 A cm-2 were achieved