Modulating the Reaction Configuration by Breaking the Structural Symmetry of Active Sites for Efficient Photocatalytic Reduction of Low-concentration CO2.

Photocatalytic conversion of low-concentration CO2 is considered as a promising way to simultaneously mitigate the environmental and energy issues. However, the weak CO2 adsorption and tough CO2 activation process seriously compromise the CO production, due to the chemical inertness of CO2 molecule and the formed fragile metal-C/O bond. Herein, we designed and fabricated oxygen vacancy contained Co3 O4 hollow nanoparticles on ordered macroporous N-doped carbon framework (Vo-HCo3 O4 /OMNC) towards photoreduction of low-concentration CO2 . In situ spectra and ab initio molecular dynamics simulations reveal that the constructed oxygen vacancy is able to break the local structural symmetry of Co-O-Co sites. The formation of asymmetric active site switches the CO2 configuration from a single-site linear model to a multiple-sites bending one with a highly stable configuration, enhancing the binding and structural polarization of CO2 molecules. As a result, Vo-HCo3 O4 /OMNC shows unprecedent activity in the photocatalytic conversion of low-concentration CO2 (10 % CO2 /Ar) under laboratory light source or even natural sunlight, affording a syngas yield of 337.8 or 95.2 mmol g-1 h-1 , respectively, with an apparent quantum yield up to 4.2 %.

A Tandem Strategy for Enhancing Electrochemical CO2 Reduction Activity of Single-Atom Cu-S1 N3 Catalysts via Integration with Cu Nanoclusters.

We developed a tandem electrocatalyst for CO2 -to-CO conversion comprising the single Cu site co-coordinated with N and S anchored carbon matrix (Cu-S1 N3 ) and atomically dispersed Cu clusters (Cux ), denoted as Cu-S1 N3 /Cux . The as-prepared Cu-S1 N3 /Cux composite presents a 100 % Faradaic efficiency towards CO generation (FECO ) at -0.65 V vs. RHE and high FECO over 90 % from -0.55 to -0.75 V, outperforming the analogues with Cu-N4 (FECO only 54 % at -0.7 V) and Cu-S1 N3 (FECO 70 % at -0.7 V) configurations. The unsymmetrical Cu-S1 N3 atomic interface in the carbon basal plane possesses an optimized binding energy for the key intermediate *COOH compared with Cu-N4 site. At the same time, the adjacent Cux effectively promotes the protonation of *CO2 - by accelerating water dissociation and offering *H to the Cu-S1 N3 active sites. This work provides a tandem strategy for facilitating proton-coupled electron transfer over the atomic-level catalytic sites.

Upregulated circular RNA circ_0007534 indicates an unfavorable prognosis in pancreatic ductal adenocarcinoma and regulates cell proliferation, apoptosis, and invasion by sponging miR-625 and miR-892b.

Circular RNAs (circRNAs) have been regarded as critical regulators of human diseases and biological markers in some types of malignancies, including pancreatic ductal adenocarcinoma (PDAC). Recently, circ_0007534 has been identified as a novel cancer-related circRNA. Nevertheless, its clinical relevance, functional roles, and mechanism have not been studied in PDAC. In the current study, real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of circ_0007534 in 60-paired PDAC tissue samples and different cell lines. Loss-of-function and gain-of-function assays were performed to detect cell proliferation, apoptosis, and metastatic properties affected by circ_0007534. An animal study was also carried out. The luciferase reporter assay was performed to uncover the underlying mechanism of circ_0007534. As a result, circ_0007534 was overexpressed not only in PDAC tissues but also in a panel of PDAC cell lines, and this overexpression is closely associated with advanced tumor stage and positive lymph node invasion. In addition, circ_0007534 may be regarded as an independent prognostic factor for patients with PDAC. For the part of functional assays, circ_0007534 significantly increased cell proliferation, migratory, and invasive potential of PDAC cells. Circ_0007534 could inhibit cell apoptosis partly via a Bcl-2/caspase-3 pathway. The xenograft study further confirmed the cell growth promoting the role of circ_0007534. Mechanistically, miR-625 and miR-892b were sponged by circ_0007534. The oncogenic functions of circ_0007534 is partly dependent on its regulation of miR-625 and miR-892b. In conclusion, our study illuminates a novel circRNA that confers an oncogenic function in PDAC.

Creating Hybrid Coordination Environment in Fe-Based Single Atom Catalyst for Efficient Oxygen Reduction.

Tailoring the local chemistry environment to optimize the geometric and electronic properties of single atom catalysts has received much attention recently. Yet, most efforts have been devoted to establishing the preferable binding between the solid support and the single metal atom. In this work, a hybrid coordination environment was created for Fe-based single atom catalysts, comprising inorganic anchoring site from the support and organic ligands from the precursor. Using N,S co-doped graphene oxide as the support, Fe phthalocyanine was selectively anchored by the N/S sites, creating the unique N/S-Fe-N4 active sites as evidenced by extended X-ray absorption fine structure and Mössbauer spectrometry. Compared with other analogues with different metal centers or support, N/S-Fe-N4 showed much improved activity in oxygen reduction reaction, delivering onset and half-wave potentials of 1.02 and 0.94 V. This was superior over the state-of-the-art 20 wt % Pt/C and the classic Fe-N4 carbon catalysts. Density functional theory calculations revealed that the interaction between phthalocyanine ligands and heteroatom dopant from the support pushed electrons of Fe site to para-position, facilitating O2 adsorption and activation. This work shows the exciting opportunities of creating a hybrid coordination environment in single atom catalysts and paves a new avenue of improving their catalytic performance.

Control over Electrochemical CO2 Reduction Selectivity by Coordination Engineering of Tin Single-Atom Catalysts.

Carbon-based single-atom catalysts (SACs) with well-defined and homogeneously dispersed metal-N4 moieties provide a great opportunity for CO2 reduction. However, controlling the binding strength of various reactive intermediates on catalyst surface is necessary to enhance the selectivity to a desired product, and it is still a challenge. In this work, the authors prepared Sn SACs consisting of atomically dispersed SnN3 O1 active sites supported on N-rich carbon matrix (Sn-NOC) for efficient electrochemical CO2 reduction. Contrary to the classic Sn-N4 configuration which gives HCOOH and H2 as the predominant products, Sn-NOC with asymmetric atomic interface of SnN3 O1 gives CO as the exclusive product. Experimental results and density functional theory calculations show that the atomic arrangement of SnN3 O1 reduces the activation energy for *COO and *COOH formation, while increasing energy barrier for HCOO* formation significantly, thereby facilitating CO2 -to-CO conversion and suppressing HCOOH production. This work provides a new way for enhancing the selectivity to a specific product by controlling individually the binding strength of each reactive intermediate on catalyst surface.

Expression of inflammatory factors and oxidative stress markers in serum of patients with coronary heart disease and correlation with coronary artery calcium score.

Expression characteristics of inflammatory factors interleukin-23 and interleukin-35; oxidative stress markers of malondialdehyde, which is a final product of lipid peroxidation; superoxide dismutase; microRNA-126 and microRNA-146a in serum of patients with coronary heart disease were investigated. Correlation between these biomarkers and CACS (calcification score), as well as the underlying clinical significance were evaluated. A total of 192 patients diagnosed with coronary heart disease were recruited as the observation group, and 69 healthy adults who provided their blood samples were selected as the control group. Enzyme linked immunosorbent assay was carried out to measure the levels of inflammatory factors interleukin-23 and interleukin-35, and the levels of oxidative stress markers of malondialdehyde and superoxide dismutase in serum of the patients and healthy subjects. Real-time fluorescence-based quantitative PCR was performed to measure the expression levels of microRNA-126 and microRNA-146a in serum. The differences in expression of these biomarkers were analyzed, and correlation between these biomarkers and coronary artery calcium score were assessed. The differences in expression levels of interleukin-23, interleukin-35, malondialdehyde, superoxide dismutase, microRNA-126 and microRNA-146a were statistically significant in both groups. The expression levels of interleukin-23, interleukin-35, malondialdehyde, superoxide dismutase, microRNA-126 and microRNA-146a in the observation group were closely associated with severity of the disease. There were positive correlations between coronary artery calcium score and interleukin-23, interleukin-35, malondialdehyde, microRNA-126 and microRNA-146a, respectively; while a negative correlation existed between coronary artery calcium score and superoxide dismutase in the observation group. In conclusion, biomarkers interleukin-23, interleukin-35, malondialdehyde, superoxide dismutase, microRNA-126 and microRNA-146a were abnormally expressed in serum of patients with coronary heart disease, implicating their association with onset and progression of the disease. The biomarkers were found to be correlated with coronary artery calcium score. Detection of changes of related biomarkers in serum may have certain value in diagnosis of disease formation, as well as assessment of disease severity.

Robust object tracking via online dynamic spatial bias appearance models.

This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a human vision system during object tracking, we propose to partition an object into regions with different confidences and track the object using a dynamic spatial bias appearance model (DSBAM) estimated from region confidences. The confidence of a region is estimated to re ect the discriminative power of the region in a feature space, and the probability of occlusion. We propose a novel hierarchical Monte Carlo (HAMC) algorithm to learn region confidences dynamically in every frame. The algorithm consists of two levels of Monte Carlo processes implemented using two particle filtering procedures at each level and can efficiently extract high confidence regions through video frames by exploiting the temporal consistency of region confidences. A dynamic spatial bias map is then generated from the high confidence regions, and is employed to adapt the appearance model of the object and to guide a tracking algorithm in searching for correspondences in adjacent frames of video images. We demonstrate feasibility of the proposed method in video surveillance applications. The proposed method can be combined with many other existing tracking systems to enhance the robustness of these systems.

Recognition of aggressive human behavior using binary local motion descriptors.

Video surveillance is an alternative approach to staff or self-reporting that has the potential to detect and monitor aggressive behaviors more accurately. In this paper, we propose an automatic algorithm capable of recognizing aggressive behaviors from video records using local binary motion descriptors. The proposed algorithm may increase the accuracy for retrieving aggressive behaviors from video records, and thereby facilitates scientific inquiry into this low frequency but high impact phenomenon that eludes other measurement approaches.

Intelligent video monitoring to improve safety of older persons.

This paper presents the application of computer vision and machine learning technologies to a clinical task of paramount importance, improving safety of older persons. We propose an intelligent monitoring system equipped with a camera network and an automatic elopement detection algorithm to reduce the risks of un-witnessed elopements from a dementia unit in order to avoid their potential catastrophic consequences. The camera network employs 23 cameras to record daily activities in our test bed, which includes 15 residents, 4 registered and licensed practical nurses and a number of certified nursing assistants. An elopement detector is then built by using computer vision algorithms and a machine learning algorithm to automatically detect elopements and alert caregivers. The experiments demonstrate that the proposed system leverages the advantages of monitoring from multiple cameras and is able to detect elopements with almost 100% accuracy.