CO2 dissociation activated through electron attachment on reduced rutile TiO2(110)-1x1 surface

Converting CO$_2$ to useful compounds through the solar photocatalytic reduction has been one of the most promising strategies for artificial carbon recycling. The highly relevant photocatalytic substrate for CO$_2$ conversion has been the popular TiO$_2$ surfaces. However, the lack of accurate fundamental parameters that determine the CO$_2$ reduction on TiO$_2$ has limited our ability to control these complicated photocatalysis processes. We have systematically studied the reduction of CO2 at specific sites of the rutile TiO$_2$(110)-1x1 surface using scanning tunneling microscopy at 80 K. The dissociation of CO2 molecules is found to be activated by one electron attachment process and its energy threshold, corresponding to the CO$_2^{\dot-}$/CO$_2$ redox potential, is unambiguously determined to be 2.3 eV higher than the onset of the TiO$_2$ conduction band. The dissociation rate as a function of electron injection energy is also provided. Such information can be used as practical guidelines for the design of effective catalysts for CO$_2$ photoreduction

Fiber-Optic Axial-Strain Sensor with Sensitivity Enhancement and Temperature Compensation

In this paper, we report a tapered thin-core fiber based in-line Mach-Zehnder interferometer to improve the response of axial-strain. With the varied diameters of taper waist, the light field distributions are studied by beam propagation method, and the structures are fabricated by arc-discharged lateral offset splicing and tapering techniques. The comprehensive tests are then conducted and compared in terms of axial-strain and temperature. The experimental results show that, by reducing the diameter of taper waist, more than 400% enhancement of wavelength sensitivity can be gained, and the maximum reaches 4.07 pm/µε with the measured error of 3.6%. Moreover, owing to high consistency of temperature response, the near-zero crosstalk is presented by differential compensation method. Furthermore, owing to the merit of high repeatability and stability, our sensor is very practical and promising in the high-precision measurement and engineering monitoring

Niosome-Assisted Delivery of DNA Fluorescent Probe with Optimized Strand Displacement for Intracellular MicroRNA21 Imaging

MicroRNAs play a vital role in cancer development and are considered as potential biomarkers for early prognostic assessment. Here, we propose a novel biosensing system to achieve fluorescence imaging of miRNA21 (miR21) in cancer cells. This system consists of two components: an optimized “off-on” double-stranded DNA (dsDNA) fluorescent for miR21 sensing by efficient strand-displacement reaction and a potent carrier vesicle, termed niosome (SPN), to facilitate the efficient intracellular delivery of the dsDNA probe. A series of dsDNA probes based on fluorescence energy resonance transfer (FRET) was assembled to target miR21. By optimizing the appropriate length of the reporter strand in the dsDNA probe, high accuracy and sensitivity for miR21 recognition are ensured. To overcome the cellular barrier, we synthesized SPN with the main components of a nonionic surfactant Span 80 and a cationic lipid DOTAP, which could efficiently load dsDNA probes via electrostatic interactions and potently deliver the dsDNA probes into cells with good biosafety. The SPN/dsDNA achieved efficient miR21 fluorescent imaging in living cells, and could discriminate cancer cells (MCF-7) from normal cells (L-02). Therefore, the proposed SPN/dsDNA system provides a powerful tool for intracellular miRNA biosensing, which holds great promise for early cancer diagnosis

Ultra-Sensitive Intensity Modulated Strain Sensor by Tapered Thin-Core Fiber Based Modal Interferometer

In this paper, to enhance practicality, a novel tapered thin-core fiber (t-TCF) based modal interferometer is proposed and demonstrated experimentally. The light field distribution of t-TCF structure is investigated by a beam propagation method, and the quantitative relationship is gained between light intensity loss and waist diameter. Under ~30 μm waist diameter, multiple t-TCF based sensor heads are fabricated by arc-discharged splicing and taper techniques, and comprehensive tests are performed with respects to axial strain and temperature. The experimental results show that, with near-zero wavelength shift, obvious intensity strain response is exhibited and negative-proportional to the reduced length of TCF. Thus, the maximum sensitivity reaches 0.119 dB/με when the TCF length is equal to 15 mm, and a sub-micro-strain detection resolution (about 0.084 με) is obtained. Besides, owing to the flat red-shifted temperature response, the calculated cross-sensitivity of our sensor is compressed within 0.32 με/°C, which is promising for high precision strain related engineering applications

Communication-Efficient Federated Learning for Power Load Forecasting in Electric IoTs

With the construction of the modern power system, power load forecasting is significant to keep the electric Internet of Things in operation. However, it usually needs to collect massive power load data on the server and may face the problem of privacy leakage of raw data. Federated learning can enhance the privacy of the raw power load data of clients by frequently transmitting model updates. Concerning the increasing communication burden of resource-heterogeneous clients resulting from frequent communication with the server, a communication-efficient federated learning algorithm based on Compressed Model Updates and Lazy uploAd (CMULA-FL) was proposed to reduce the communication cost. CMULA-FL also integrates the error compensation strategy to improve the model utility. First, the compression operator is used to compress the transmitted model updates, of which large norms are uploaded to reduce the communication cost of each epoch and transmission frequency. Second, by measuring the error of compression and lazy upload, the error is accumulated to the next epoch to improve the model utility. Finally, based on simulation experiments on the benchmark power load data, the results show that the communication cost decreases at least 60% with controlled loss of model prediction compared with baseline

Contrasting Altitudinal Patterns and Composition of Soil Bacterial Communities along Stand Types in <i>Larix principis-rupprechtii</i> Forests in Northern China

Bacterial communities inhabiting the soil of mountain ecosystems perform critical ecological functions. Although several studies have reported the altitudinal distribution patterns of bacterial communities in warm-temperate mountain forests, our understanding of typical zonal vegetation dominated by Larix principis-rupprechtii Mayr (abbreviated as larch hereafter) and the understory elevation distribution patterns of soil bacterial communities is still limited. In this study, the Illumina NovaSeq 6000 sequencing platform was used to investigate the changes of surface and subsurface soil bacterial communities along an altitudinal gradient (from 1720 m to 2250 m) in larch forests in northern China. Altitude significantly affected the relative abundance of Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi (bacterial dominant phylum) and Alphaproteobacteria, Gammaproteobacteria, and Actinobacteria (bacterial dominant classes). The diversity of bacterial communities showed a concomitant increase with altitude. The variations in available nitrogen and soil temperature content at different altitudes were the main factors explaining the bacterial community structures in pure stands and mixed stands, respectively. Altitude and the contents of soil organic carbon and soil organic matter were the main factors explaining the dominant phylum (taxonomy). Our results suggest that stand type has a greater effect on the structure and composition of soil bacterial communities than elevation and soil depth, and bacterial communities show divergent patterns along the altitudes, stand types, and soil profiles

Network pharmacology, molecular docking, combined with experimental verification to explore the role and mechanism of shizhifang decoction in the treatment of hyperuricemia

Ethnopharmacological relevance: Shizhifang Decoction, a traditional Chinese medicine prescription formulated by Professor Zheng Pingdong of Shuguang Hospital, has been widely utilized in clinical settings for the treatment of hyperuricemia due to its proven safety and efficacy. Objective: In this study, we used network pharmacology, molecular docking technology, and experimental validation to elucidate the therapeutic effects and underlying mechanisms of Shizhifang Decoction in managing hyperuricemia. Methods: Quality control and component identification of the freeze-dried powder of Shizhifang Decoction were conducted using ultra-high performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry. Active ingredients and their corresponding targets were obtained from Traditional Chinese Medicine Systems Pharmacology, Traditional Chinese Medicine Information Database, The Encyclopedia of Traditional Chinese Medicine, and other databases. Disease-related targets for hyperuricemia were collected from GeneCards and DisGeNET databases. The Venny platform is used to screen common targets for drug active ingredients and diseases. Subsequently, we constructed an active component-target-disease interaction network using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, create a component disease common target network using Cytoscape 3.9.1 software, from which core targets were selected. Import common targets into the Database for Annotation, Visualization and Integrated Discovery (DAVID) for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis. Molecular docking was then conducted to validate the binding capacity of key active ingredients and their associated targets in Shizhifang Decoction. The theoretical predictions were further confirmed through in vitro and in vivo experiments. Result: A total of 35 active ingredients and 597 action targets were identified, resulting in 890 disease-related targets for hyperuricemia. After comprehensive analysis, 99 common targets were determined. Protein-protein interaction network analysis revealed crucial relationships between these targets and hyperuricemia. Among them, 12 core targets (CASP3, IL1B, IL6, TNF, TP53, GAPDH, PTGS2, MYC, INS, VEGFA, ESR1, PPARG) were identified. Gene Ontology enrichment analysis demonstrated significant associations with the regulation of inflammatory response, cell apoptosis, and the positive regulation of extracellular regulated protein kinases 1 and extracellular regulated protein kinases 2 cascades. Kyoto Encyclopedia of Genes and Genomes pathway analysis highlighted inflammation and apoptosis-related pathways as critical mediators of Shizhifang Decoction's effects on hyperuricemia. Molecular docking studies further supported the interactions between apoptosis-related proteins and active ingredients in the extracellular regulated protein kinases 1/2 signaling pathway. In vitro experiments confirmed the downregulation of apoptosis-related proteins (caspase-3, Bax, Bcl-2) and the inhibition of the extracellular regulated protein kinases 1/2 signaling pathway by Shizhifang Decoction. These findings were also validated in animal models, demonstrating the potential of Shizhifang Decoction to mitigate renal injury induced by hyperuricemia through extracellular regulated protein kinases 1/2-mediated inhibition of renal tubular epithelial cell apoptosis. Conclusion: Our study provides valuable insights into the main mechanism by which Shizhifang Decoction ameliorates hyperuricemia. By targeting the ERK1/2 signaling pathway and modulating cell apoptosis, Shizhifang Decoction exhibits promising therapeutic potential for the treatment of hyperuricemia. These findings support the continued exploration and development of Shizhifang Decoction as a potential herbal remedy for hyperuricemia management