Modified photoanode by in situ growth of covalent organic frameworks on BiVO4 for oxygen evolution reaction.

The development of efficient oxygen evolution reaction (OER) catalysts is of great significance because the water oxidation reaction at the photoanode is the rate-determining step in photoelectrocatalytic (PEC) water splitting. Herein, two hybrid photoanodes named BiVO4/COF-Azo and BiVO4/COF-Ben were prepared by in situ solvothermal growth on a modified BiVO4 photoanode. Characterization results revealed that the Azo and Ben COFs could match with BiVO4 well to form heterojunctions, which could effectively enhance the separation efficiency of photogenerated carriers. Also, the smaller impedance of the composite photoanodes and faster kinetics of the water oxidation reaction promoted the charge transmission and enhanced the reaction efficiency of the surface-reaching holes, respectively. As a result, the composite photoanodes exhibited a larger photocurrent and more negative onset potential compared to the pristine BiVO4. This work not only provides a new strategy to construct efficient hybrid photoanodes, but also expands the applications of COFs.

Interfacial engineering of POM-stabilized Ni quantum dots on porous titanium mesh for high-rate and stable alkaline hydrogen production.

The development of low-cost, high-efficiency, and stable electrocatalysts for the alkaline hydrogen evolution reaction (HER) is a key challenge because the alkaline HER kinetics is slowed by an additional water dissociation step. Herein, we report an interfacial engineering strategy for polyoxometalate (POM)-stabilized nickel (Ni) quantum dots decorated on the surface of porous titanium mesh (POMs-Ni@PTM) for high-rate and stable alkaline hydrogen production. Benefiting from the strong interfacial interactions among POMs, Ni atoms, and PTM substrates, as well as unique POM-Ni quantum dot structures, the optimized POMs-Ni@PTM electrocatalyst exhibits a remarkable alkaline HER performance with an overpotential (η10) of 30.1 mV to reach a current density of 10 mA cm-2, which is much better than those of bare Ni decorated porous titanium mesh (Ni@PTM) (η10 = 171.1 mV) and POM decorated porous titanium mesh (POMs@PTM) electrocatalysts (η10 = 493.6 mV), comparable to that of the commercial 20 wt% platinum/carbon (20% Pt/C) electrocatalyst (η10 = 20 mV). Moreover, the optimized POMs-Ni@PTM electrocatalyst demonstrates excellent stability under continuous alkaline water-splitting at a current density of ∼100 mA cm-2 for 100 h, demonstrating great potential for its practical application.

Towards generalizable Graph Contrastive Learning: An information theory perspective.

Graph Contrastive Learning (GCL) is increasingly employed in graph representation learning with the primary aim of learning node/graph representations from a predefined pretext task that can generalize to various downstream tasks. Meanwhile, the transition from a specific pretext task to diverse and unpredictable downstream tasks poses a significant challenge for GCL's generalization ability. Most existing GCL approaches maximize mutual information between two views derived from the original graph, either randomly or heuristically. However, the generalization ability of GCL and its theoretical principles are still less studied. In this paper, we introduce a novel metric GCL-GE, to quantify the generalization gap between predefined pretext and agnostic downstream tasks. Given the inherent intractability of GCL-GE, we leverage concepts from information theory to derive a mutual information upper bound that is independent of the downstream tasks, thus enabling the metric's optimization despite the variability in downstream tasks. Based on the theoretical insight, we propose InfoAdv, a GCL framework to directly enhance generalization by jointly optimizing GCL-GE and InfoMax. Extensive experiments validate the capability of InfoAdv to enhance performance across a wide variety of downstream tasks, demonstrating its effectiveness in improving the generalizability of GCL.

Hydroxy-Rich Covalent Organic Framework for the Efficient Catalysis of the Cycloaddition of CO2.

The cycloaddition of CO2 with epoxides to cyclic carbonates is one of the most promising and green pathways for CO2 utilization, and the development of highly efficient catalysts remains a challenge. In this work, a novel hydroxy-rich covalent organic framework (TFPB-DHBD-COF) was synthesized, and it served as an efficient heterogeneous catalyst for the reaction of CO2 with 1,2-epoxybutane under mild conditions, providing the desired products in 90% conversion. The abundant hydroxy groups in the pore channels of TFPB-DHBD-COF could not only activate epoxides and CO2 via hydrogen bonding but also obviously enhance its stability through intramolecular five-membered ring hydrogen bonding. Thus, this COF also exhibited outstanding stability and tolerance for diverse substrates. Undoubtedly, this work has enriched the application of tailored COFs in the activation and utilization of CO2.

UniSKGRep: A unified representation learning framework of social network and knowledge graph.

The human-oriented applications aim to exploit behaviors of people, which impose challenges on user modeling of integrating social network (SN) with knowledge graph (KG), and jointly analyzing two types of graph data. However, existing graph representation learning methods merely represent one of two graphs alone, and hence are unable to comprehensively consider features of both SN and KG with profiling the correlation between them, resulting in unsatisfied performance in downstream tasks. Considering the diverse gap of features and the difficulty of associating of the two graph data, we introduce a Unified Social Knowledge Graph Representation learning framework (UniSKGRep), with the goal to leverage the multi-view information inherent in the SN and KG for improving the downstream tasks of user modeling. To the best of our knowledge, we are the first to present a unified representation learning framework for SN and KG. Concretely, the SN and KG are organized as the Social Knowledge Graph (SKG), a unified representation of SN and KG. For the representation learning of SKG, first, two separate encoders in the Intra-graph model capture both the social-view and knowledge-view in two embedding spaces, respectively. Then the Inter-graph model is learned to associate the two separate spaces via bridging the semantics of overlapping node pairs. In addition, the overlapping node enhancement module is designed to effectively align two spaces with the consideration of a relatively small number of overlapping nodes. The two spaces are gradually unified by continuously iterating the joint training procedure. Extensive experiments on two real-world SKG datasets have proved the effectiveness of UniSKGRep in yielding general and substantial performance improvement compared with the strong baselines in various downstream tasks.

User Identity Linkage across Social Networks with the Enhancement of Knowledge Graph and Time Decay Function.

Users participate in multiple social networks for different services. User identity linkage aims to predict whether users across different social networks refer to the same person, and it has received significant attention for downstream tasks such as recommendation and user profiling. Recently, researchers proposed measuring the relevance of user-generated content to predict identity linkages of users. However, there are two challenging problems with existing content-based methods: first, barely considering the word similarities of texts is insufficient where the semantical correlations of named entities in the texts are ignored; second, most methods use time discretization technology, where the texts are divided into different time slices, resulting in failure of relevance modeling. To address these issues, we propose a user identity linkage model with the enhancement of a knowledge graph and continuous time decay functions that are designed for mitigating the influence of time discretization. Apart from modeling the correlations of the words, we extract the named entities in the texts and link them into the knowledge graph to capture the correlations of named entities. The semantics of texts are enhanced through the external knowledge of the named entities in the knowledge graph, and the similarity discrimination of the texts is also improved. Furthermore, we propose continuous time decay functions to capture the closeness of the posting time of texts instead of time discretization to avoid the matching error of texts. We conduct experiments on two real public datasets, and the experimental results show that the proposed method outperforms state-of-the-art methods.

[Porcine circovirus type 2 induces apoptosis by exosomal miR-125a-5p targeting Bcl-2 in porcine lymphocytes].

In order to investigate the apoptosis triggered by porcine circovirus type 2 (PCV2) in lymphocytes and the underlying mechanism, the levels of apoptosis and the expression levels of miRNA were examined by flow cytometry, Western blotting and real-time PCR (qPCR). The mimics or inhibitors of miR-125a-5p, an apoptosis-related miRNA, were transfected into PK-15 cells, and the apoptosis rate was examined upon overexpression or inhibition of mir-125a-5p. The target gene of mir-125a-5p was predicted by bioinformatics method, and the regulation of mir-125a-5p on the target gene was analyzed by luciferase reporter assay. The expressions of Bcl-2, Bax, cytochrome C and caspase-3 were detected by Western blotting. The results showed that exosomes secreted by PK-15 cells infected with PCV2 significantly increased the lymphocyte apoptosis rate, which was dose-dependent in certain concentration range. The expression of miR-125a-5p was dramatically increased. The apoptosis rate was increased significantly in the cells transfected with miR-125a-5p. It was predicted that there were binding sites of miR-125a-5p at Bcl-2 3'UTR by TargetScan. The luciferase activity of wild-type pmir-Bcl-2 3'UTR was inhibited significantly by miR-125a-5p mimics, but that of mutant pmir-Bcl-2 3'UTR was not changed. By Western blotting, Bcl-2 was reduced significantly, while Bax, cytochrome C and caspase-3 increased significantly, and the ratio of Bcl-2/Bax was significantly decreased. These results showed that PCV2 up-regulated the expression of miR-125a-5p through exosomes, then inhibited the expression of Bcl-2 at both mRNA and protein level, activated mitochondrial apoptosis pathway and induced apoptosis in lymphocytes.

Location-aware convolutional neural networks for graph classification.

Graph patterns play a critical role in various graph classification tasks, e.g., chemical patterns often determine the properties of molecular graphs. Researchers devote themselves to adapting Convolutional Neural Networks (CNNs) to graph classification due to their powerful capability in pattern learning. The varying numbers of neighbor nodes and the lack of canonical order of nodes on graphs pose challenges in constructing receptive fields for CNNs. Existing methods generally follow a heuristic ranking-based framework, which constructs receptive fields by selecting a fixed number of nodes and dropping the others according to predetermined rules. However, such methods may lose important structure information through dropping nodes, and they also cannot learn task-oriented graph patterns. In this paper, we propose a Location learning-based Convolutional Neural Networks (LCNN) for graph classification. LCNN constructs receptive fields by learning the location of each node according to its embedding that contains structures and features information, then standard CNNs are applied to capture graph patterns. Such a location learning mechanism not only retains the information of all nodes, but also provides the ability for task-oriented pattern learning. Experimental results show the effectiveness of the proposed LCNN, and visualization results further illustrate the valid pattern learning ability of our method for graph classification.

A Target-Feedback Rolling-Cleavage signal amplifier for ultrasensitive electrochemical detection of miRNA with Self-Assembled CeO2@Ag hybrid nanoflowers.

Currently, developing an effective and easy-to-operate signal amplification assay to detect the trace-amount miRNAs in serum remains a significant challenge. Herein, an ultrasensitive CeO2@Ag hybrid nanoflower (CeO2@Ag HNF)-labeled electrochemical biosensor was developed for sensing miRNA, based on a target-feedback rolling-cleavage (TFRC) signal amplifier. CeO2@Ag HNFs possessing a unique three-dimensional layered structure were synthesized without any complex reaction conditions, such as heating and vacuum. The bimetallic nanoflowers provided a large surface area and excellent CAT-like activity, thereby enhancing electrochemical performance. Based on the principle of branched catalytic hairpin assembly, target miRNA could continuously trigger the assembly of branched junctions with ends composed of DNAzyme. The activated DNAzyme was able to cleave the hairpin substrate efficiently and release to capture more CeO2@Ag HNFs label. The process combining target-driven branched catalytic hairpin assembly and DNAzyme-assisted rolling cleavage were defined as TFRC signal amplification. This sensitive electrochemical biosensor exhibited good linear relationship of 1 fM - 1 nM with a detection limit down to 0.89 fM. The proposed method is expected to have a promising application in the miRNA-associated fundamental research and clinical diagnosis.

The prediction of fluctuation in the order-driven financial market.

Risk prediction is one of the important issues that draws much attention from academia and industry. And the fluctuation-absolute value of the change of price, is one of the indexes of risk. In this paper, we focus on the relationship between fluctuation and order volume. Based on the observation that the price would move when the volume of order changes, the prediction of price fluctuation can be converted into the prediction of order volume. Modelling the trader's behaviours-order placement and order cancellation, we propose an order-based fluctuation prediction model. And our model outperforms better than baseline in OKCoin and BTC-e datasets.

Novel cytosensor for accurate detection of circulating tumor cells based on a dual-recognition strategy and BSA@Ag@Ir metallic-organic nanoclusters.

Herein, based on a dual-recognition strategy and BSA@Ag@Ir metallic-organic nanoclusters (BSA@Ag@Ir MONs), a highly specific and sensitive cytosensor was developed for detecting circulating tumor cells (CTCs). To amplify current signal, novel BSA@Ag@Ir MONs with outstanding catalytic activity and huge specific surface area were synthesized, and conjugated with hairpin DNA strands as signal probes. Orion carbon black 40 (Ocb40)//AuNPs were firstly used to modify electrode to increase its conductivity and surface area. Moreover, the dual recognition strategy based on DNA proximity effect was designed to improve the specificity of cytosensor. When two capture probes respectively bound to two adjacent membrane markers of target cells, the probes could form the associative toehold through the proximity effect to capture the signal probes. Only CTCs simultaneously expressing two membrane markers could be captured and generate current responses. The developed cytosensor could detect CTCs in the range of 3 - 3 × 106 cells mL-1 with a detection limit of 1 cell mL-1. Notably, the cytosensor could accurately identify CTCs even in whole blood. Therefore, this cytosensor has great potential for application in biological science, biomedical engineering and personalized medicine.

A dual recognition strategy for accurate detection of CTCs based on novel branched PtAuRh trimetallic nanospheres.

Accurate detection of circulating tumor cells (CTCs) has a pivotal role in the metastasis monitoring and prognosis of tumor. In this work, an ultrasensitive electrochemical cytosensor was developed based on excellent electrocatalytic materials and a dual recognition strategy. Herein, novel branched PtAuRh trimetallic nanospheres (b-PtAuRh TNS) were synthesized for the first time by a facile one-pot method, which had a huge specific surface area and outstanding catalytic activity. B-PtAuRh TNS linked with aptamers targeting mucin1 (MUC1) were served as signal tags to amplify the signal. As electrode modified material, the nanocomposites of Cabot carbon black (BP2000) and AuNPs were used to improve the electron transfer efficiency of electrode. In addition to using b-PtAuRh TNS labeled anti-MUC1 aptamers as signal probes, anti-EpCAM antibodies were worked as capture probes to achieve dual recognition of target cells. In other words, only cells expressing both MUC1 and EpCAM could produce electrochemical signal. The constructed cytosensor presented a wide linear range (5 - 1 × 106 cells mL-1) and a low detection limit (1 cell mL-1). It was worth noting that the proposed cytosensor could detect CTCs in clinical blood samples. To sum up, the developed cytosensor might become a promising detection platform for cancer diagnosis and tumor metastasis.

Factors affecting the success of fallopian tube recanalization in treatment of tubal obstructive infertility.

OBJECTIVE: To examine potential risk factors associated with the success rate following fallopian tube recanalization (FTR) in infertile women with obstruction of the proximal fallopian tube. METHODS: We retrospectively studied patients who underwent FTR for tubal obstructive infertility between January 2016 and December 2018 at the Third Affiliated Hospital of Guangzhou Medical University. FTR was performed using a catheter and guidewire system to clear tubal obstruction. Predictive factors potentially associated with the success rate were assessed by logistic regression. RESULTS: A total of 762 patients were included. Multivariable analysis showed that age (odds ratio [OR] = 2.38, 95% confidence interval [CI]: 1.24-4.58), infertility type (OR = 2.82, 95% CI: 1.36-6.21), history of ectopic pregnancy (OR = 7.87, 95% CI: 4.05-15.81), history of abdominal surgery (OR = 4.30, 95% CI: 2.22-8.60), history of artificial abortion curettage (OR = 4.08, 95% CI: 2.12-8.03), and duration of infertility (OR = 2.03, 95% CI: 1.06-3.85) were independently associated with postoperative tubal patency. CONCLUSIONS: Our findings suggest that risk factors, such as age ≥35 years, secondary infertility, duration of infertility ≥5 years, and histories of ectopic pregnancy, abdominal surgery, and artificial abortion curettage, affect the success rate of FTR. These factors may also predict surgical success in treating tubal obstructive infertility.

Modified sandwich embolization technique for postpartum hemorrhage caused by uterine artery pseudoaneurysm: a case series.

PURPOSE: Uterine artery pseudoaneurysm (UAP) is rare but can cause life-threatening postpartum hemorrhage (PPH). To evaluate a novel sandwich embolization technique as a treatment for PPH caused by UAP. METHODS: This retrospective study included 10 patients with PPH caused by UAP who were treated using a modified sandwich embolization technique at the Radiology Department, Third Affiliated Hospital of Guangzhou Medical University between April 2009 and September 2018. Baseline clinical characteristics, intraoperative data (including treatment effectiveness) and postoperative data (including re-bleeding events and complications) were extracted from the medical records. RESULTS: Uterine arterial angiography showed cystic shadowing of the vascular wall during the arterial phase in all patients. Spraying of contrast agent into the pseudoaneurysm was observed for large UAPs, and the pseudoaneurysm disappeared in the venous phase. The pseudoaneurysm blood supply was from the uterine artery in 9 patients (90%) and the uterine, superior vesical, internal pudendal and nameless little arteries in 1 patient (10%). Bleeding symptoms were completely relieved in all patients after sandwich embolization. Eight patients experienced painful contractions in the perioperative period, but there were no other postoperative complications. During the 1-year postoperative follow-up, 9 patients (90%) had no re-bleeding symptoms/signs. One patient (10%), who had a pseudoaneurysm supplied by the uterine, superior vesical, internal pudendal and nameless little arteries, experienced re-bleeding 20 days after surgery and was treated by hysterectomy. CONCLUSION: Modified sandwich embolization is an effective treatment for PPH caused by UAP.

Ultrasensitive aptasensor for isolation and detection of circulating tumor cells based on CeO2@Ir nanorods and DNA walker.

Herein, based on dual signal amplification by CeO2@Ir nanorods (Ce@IrNRs) and enzyme-free DNA walker, a novel electrochemical aptasensor was developed for simultaneous isolation and detection of circulating tumor cells (CTCs). A membrane protein MUC1-targeting aptamer was used to specifically recognize and capture MCF-7 cells. Uracil DNA glycosylase could hydrolyze deoxyuracils of the aptamer to isolate the captured cells. Novel Ce@IrNRs with large surface area and high peroxidase activity were synthesized to amplify the signal, and the enzyme-free DNA walker was applied to release more signal probes combined with Ce@IrNRs. Furthermore, to reduce steric hindrance by cells, the signal probes rather than the target cells, were directly combined with the electrode. The aptasensor could detect CTCs in the range of 2 to 2 × 106 cells mL-1 with a limit of detection 1 cell mL-1. The developed aptasensor, which can simultaneously isolate and detect CTCs, has great application potential in the early monitoring of tumor metastasis and in individualized treatment.

PdIrBP mesoporous nanospheres combined with superconductive carbon black for the electrochemical determination and collection of circulating tumor cells.

An integrated electrochemical immunoassay is described for the determination of circulating tumor cells (CTCs). For the first time, Ketjen black (KB), which is a superconductive carbon material, was incorporated with Au nanoparticles (AuNPs) and used to modify the surface of gold electrodes. A cocktail of anti-epithelial cell adhesion molecules (EpCAM) and anti-vimentin antibodies was chosen to capture the CTCs. Palladium-iridium-boron-phosphorus alloy-modified mesoporous nanospheres (PdIrBPMNS) served as a catalytic tag to amplify the current signal. Glycine-HCl (Gly-HCl) was used as an antibody eluent to release and collect the captured CTCs from the electrodes for further clinical research without compromising cell viability. The response of the method increased linearly from 10 to 1 × 106 cells mL-1 CTCs, while the detection limit was calculated to be as low as 2 cells mL-1. This method was successfully used to determine CTCs in spiked blood samples and demonstrated good recovery. Graphical abstractKetjen black/AuNPs was incorporated in the electrochemical platform to enhance the electron transfer ability of the electrode surface. PdIrBP mesoporous nanospheres were used to amplify DPV signal in this assay. The introduction of Gly-HCl realized nondestructive recovery of circulating tumor cells.

Anomaly detection in Bitcoin market via price return analysis.

The Bitcoin market becomes the focus of the economic market since its birth, and it has attracted wide attention from both academia and industry. Due to the absence of regulations in the Bitcoin market, it may be easier to bring some kinds of illegal behaviors. Thus, it raises an interesting question: Is there abnormity or illegal behavior in Bitcoin platforms? To answer this question, we investigate the abnormity in five leading Bitcoin platforms. By analyzing the financial index, i.e. the normalized logarithmic price return, we find that the properties of price return in bitFlyer are completely different from others. To find the possible reasons, we find that the abnormal ask price and bid price appear simultaneously in bitFlyer, which may be potentially linked to either price manipulation or money laundering. It verifies our conjecture that there may be abnormity or price manipulation in Bitcoin platforms. Furthermore, our findings in price return could also provide an innovative and effective method to detect the abnormity in Bitcoin platforms.

Docosahexaenoic acid inhibits bone remodeling and vessel formation in the osteochondral unit in a rat model.

OBJECTIVES: We aimed to determine whether bone remodeling and vessel formation in the osteochondral unit are suppressed by supplementing with docosahexaenoic acid in anterior cruciate ligament transection (ACLT)-induced rats. METHODS: Twelve-week-old male Sprague Dawley rats were randomized to sham-operated, ACLT-operated and treated with vehicle, or ACLT-operated and treated with DHA groups. Micro-architecture and vasculature in the tibial osteochondral unit were examined by micro-CT, as well as by histomorphometry. To evaluate the effects of DHA in vitro, we conducted functional and expressional assays in RAW264.7 cells and HUVECs. Finally, we used OARSI-modified Mankin criteria and histological analyses to assess the status of the cartilage layer. RESULTS: Microstructural parameters in the osteochondral unit showed that bone mass loss and angiogenesis were less in DHA-treated rats than in vehicle-treated rats. Immunofluorescence-positive cells labeled with TRAP, RANKL, CD31, and endomucin agents in the osteochondral unit of ACLT-operated rats were reduced in the DHA-treated group compared with the vehicle-treated group. Furthermore, the number of TRAP-stained cells, areas of bone resorption pits, and mRNA expression of TRAP, CTSK, MITF, and NFATC1 were reduced in RAW264.7 cells treated with RANKL + DHA compared with those treated with only RANKL. Tube formation, proliferation and migration of HUVECs, and VEGF-C mRNA and VEGFR2 protein expression were inhibited by DHA. The decrease in OARSI score, and MMP-13 and collagen X expression suggested that DHA attenuated cartilage degeneration. CONCLUSIONS: DHA has the ability to restrain bone remodeling and vessel formation in the osteochondral unit, which may contribute to protection of cartilage.

Colorimetric determination of BCR/ABL fusion genes using a nanocomposite consisting of Au@Pt nanoparticles covered with a PAMAM dendrimer and acting as a peroxidase mimic.

A colorimetric assay is described for the detection of BCR/ABL fusion genes. Polyamidoamine (PAMAM) dendrimers were placed on peroxidase (POx) mimicking Au@Pt nanoparticles to form a nanocomposite of type Au@Pt-PAMAM. Capture DNA probe is a designed nucleic acid strand that specifically binds target DNA to the surface of the electrode. The capture probe was attached to magnetic beads via biotin and avidin interaction. The hairpin structure of the capture probe can only be opened by the complementary BCR/ABL DNA. This results in a highly specific assay. The POx-mimicking property of the Au@Pt-PAMAM causes the formation of a blue dye by reaction of H2O2 and 3,3,3',3'-tetramethylbenzidine (TMB) which is measured by a microplate reader. Under optimum conditions, the absorbance increases linearly the 1 pM to 100 nM BCR/ABL concentration range, and the detection limit is as low as 190 fM. The method is highly selective and was successfully applied to the determination of fusion genes in spiked real samples. Conceivably, it possesses a large potential in clinical testing of patients suffering from chronic myeloid leukemia. Graphical abstract Au@PtNP, an efficient catalyst, is bound with polyamidoamine (PAMAM) dendrimer to amplify the colorimetric signal. With the introduction of streptavidin-magnetic beads to remove non-specific signals, a novel colorimetric sensor is constructed to detect BCR/ABL fusion genes.