Region-level demand forecasting is an essential task in ridehailing services. Accurate ride-hailing demand forecasting can guide vehicle dispatching, improve vehicle utilization, reduce the wait-time, and mitigate traffic congestion. This task is challenging due to the complicated spatiotemporal dependencies among regions. Existing approaches mainly focus on modeling the Euclidean correlations among spatially adjacent regions while we observe that non-Euclidean pair-wise correlations among possibly distant regions are also critical for accurate forecasting. In this paper, we propose the spatiotemporal multi-graph convolution network (ST-MGCN), a novel deep learning model for ride-hailing demand forecasting. We first encode the non-Euclidean pair-wise correlations among regions into multiple graphs and then explicitly model these correlations using multi-graph convolution. To utilize the global contextual information in modeling the temporal correlation, we further propose contextual gated recurrent neural network which augments recurrent neural network with a contextual-aware gating mechanism to re-weights different historical observations. We evaluate the proposed model on two real-world large scale ride-hailing demand datasets and observe consistent improvement of more than 10% over stateof-the-art baselines.

The polyacrylic acid@zeolitic imidazolate framework-8 (PAA@ZIF-8) nanoparticles (NPs) were first fabricated using a facile and simple route. It is worthwhile noting that the as-fabricated PAA@ZIF-8 NPs possessed ultrahigh doxorubicin (DOX) loading capability (1.9 g DOX g(-1) NPs), which were employed as pH-dependent drug delivery vehicles.

A facile, reproducible, and scalable method was explored to construct uniform Au@poly(acrylic acid) (PAA) Janus nanoparticles (JNPs). The as-prepared JNPs were used as templates to preferentially grow a mesoporous silica (mSiO2 ) shell and Au branches separately modified with methoxy-poly(ethylene glycol)-thiol (PEG) to improve their stability, and lactobionic acid (LA) for tumor-specific targeting. The obtained octopus-type PEG-Au-PAA/mSiO2 -LA Janus NPs (PEG-OJNP-LA) possess pH and NIR dual-responsive release properties. Moreover, DOX-loaded PEG-OJNP-LA, upon 808 nm NIR light irradiation, exhibit obviously higher toxicity at the cellular and animal levels compared with chemotherapy or photothermal therapy alone, indicating the PEG-OJNP-LA could be utilized as a multifunctional nanoplatform for in vitro and in vivo actively-targeted and chemo-photothermal cancer therapy.

BackgroundRecently, trimethylamine-N-oxide (TMAO) plasma levels have been proved to be associated with atherosclerosis development. Among the targets aimed to ameliorating atherosclerotic lesions, inducing bile acid synthesis to eliminate excess cholesterol in body is an effective way. Individual bile acid as endogenous ligands for the nuclear receptor has differential effects on regulating bile acid metabolism. It is unclear whether bile acid profiles are mechanistically linked to TMAO-induced development of atherosclerosis.MethodsMale apoE−/− mice were fed with control diet containing 0.3% TMAO for 8 weeks. Aortic lesion development and serum lipid profiles were determined. Bile acid profiles in bile, liver and serum were measured by liquid chromatographic separation and mass spectrometric detection (LC-MS). Real-time PCRs were performed to analyze mRNA expression of genes related to hepatic bile acid metabolism.ResultsThe total plaque areas in the aortas strongly increased 2-fold (P < 0.001) in TMAO administration mice. The levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c) in TMAO group were also significantly increased by 25.5% (P = 0.044), 31.2% (P = 0.006), 28.3% (P = 0.032), respectively. TMAO notably changed bile acid profiles, especially in serum, the most prominent inductions were tauromuricholic acid (TMCA), deoxycholic acid (DCA) and cholic acid (CA). Mechanically, TMAO inhibited hepatic bile acid synthesis by specifically repressing the classical bile acid synthesis pathway, which might be mediated by activation of small heterodimer partner (SHP) and farnesoid X receptor (FXR).ConclusionsThese findings suggested that TMAO accelerated aortic lesion formation in apoE−/− mice by altering bile acid profiles, further activating nuclear receptor FXR and SHP to inhibit bile acid synthesis by reducing Cyp7a1 expression.

A novel synthetic strategy has been developed for fabricating spherical polydopamine/mesoporous calcium phosphate (PDA/mCaP) hollow Janus nanoparticles (H-JNPs).