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It has been known for several decades that defects are largely responsible for the catalytically active sites on metal and semiconductor surfaces. However, it is difficult to directly probe these active sites because the defects associated with them are often relatively rare with respect to the stoichiometric crystalline surface. In the work presented here, we demonstrate a method to selectively probe defect-mediated photocatalysis through differential alternating current (ac) photocurrent (PC) measurements. In this approach, electrons are photoexcited from the valence band to a relatively narrow distribution of subband gap states in TiO2 and then subsequently to the ions in solution. Because of their limited number, these defect states fill up quickly, resulting in Pauli blocking, and are thereby undetectable under direct current or continuous wave excitation. In the method demonstrated here, the incident light is modulated with an optical chopper, whereas the PC is measured with a lock-in amplifier. Thin (5 nm) films of TiO2 deposited by atomic layer deposition on various metal films, including Au, Cu, and Al, exhibit the same wavelength-dependent PC spectra, with a broad peak centered around 2.0 eV corresponding to the band-to-defect transition associated with the hydrogen evolution reaction (HER). While the UV-vis absorption spectra of these films show no features at 2.0 eV, photoluminescence (PL) spectra of these photoelectrodes show a similar wavelength dependence with a peak of around 2.0 eV, corresponding to the subband gap emission associated with these defect sites. As a control, alumina (Al2O3) films exhibit no PL or PC over the visible wavelength range. The ac PC plotted as a function of electrode potential shows a peak of around -0.4 to -0.1 V versus normal hydrogen electrode, as the monoenergetic defect states are tuned through a resonance with the HER potential. This approach enables the direct photoexcitation of catalytically active defect sites to be studied selectively without the interference of the continuum interband transitions or the effects of Pauli blocking, which is limited by the slow turnover time of the catalytically active sites, typically on the order of 1 μs. We believe that this general approach provides an important new way to study the role of defects in catalysis in an area where selective spectroscopic studies of these are few.

Objectives: Plasma bile acid (BA) has been widely studied as pathophysiological factors in chronic liver disease. But the changes of plasma BA level in lean metabolic dysfunction-associated fatty liver disease (MAFLD) remains unclear. Here, we clarified the BA metabolic characteristics of lean MAFLD and explored its significance and mechanism as a marker. Methods: We employed ultra-performance liquid chromatography tandem mass spectrometry based on BA metabonomics to characterize circulating bile acid in lean MAFLD patients. Explore its significance as serum biomarkers by further cluster analysis, functional enrichment analysis, and serum concentration change analysis of differential BAs. Evaluation of diagnostic value of differential BAs by ROC analysis. Results: A total of 65 BAs were detected and 17 BAs were identified which showed different expression in the lean-MAFLD group compared with the normal group. Functional annotation and enrichment analysis of KEGG and HMDB showed that differential BAs were mainly related to bile acid biosynthesis, bile secretion, cholesterol metabolism, and familial hypercholangitis, involving diseases including but not limited to cirrhosis, hepatocellular carcinoma, chronic active hepatitis, colorectal cancer, acute liver failure, and portal vein obstruction. ROC analysis displayed that the 6 BA metabolites (GCDCA-3S, GUDCA-3S, CDCA-3S, NCA, TCDCA, and HDCA) exhibited well differential diagnostic ability in discriminating between lean MAFLD patients and normal individuals with an area under the curve (AUC) ⩾0.85. Conclusions: We delineated the characteristics of BA level in patients with lean MAFLD, and identified 6 potential plasma BA biomarkers of lean MAFLD. Plain Language Summary: Analysis of serum bile acid profile characteristics and identification of new biomarkers in fatty liver disease accompanied by metabolic abnormalities in people with normal weight based on the technology of high-resolution mass spectrometry Objectives: The physique of lean MAFLD patient is normal or even leaner. They often does not pay enough attention to the onset of fatty liver disease. Plasma bile acids (BAs) have been extensively studied as pathophysiological actors in chronic liver disease. But the changes of plasma BA level in fatty liver disease accompanied by metabolic abnormalities in people with normal weight remains unclear. Here, we clarified the BA metabolic characteristics of lean MAFLD and explored its significance and mechanism as a marker. Methods: we employed an advanced mass spectrometry technology to characterize circulating bile acid in lean lean MAFLD patients. To explore its significance as a marker by bioinformatics methods, such as cluster analysis, functional enrichment analysis, and relative content change analysis of differential BAs. Evaluation diagnostic accuracy and determine threshold points of BAs by Receiver Operating Characteristic analysis. Results: A total of 65 BAs were detected and 17 BAs were identified which showed different expression in the lean MAFLD group compared with the normal group. Bioinformatics analysis showed that differential BAs were mainly related to bile acid biosynthesis, bile secretion, cholesterol metabolism, and familial hypercholangitis, involving diseases including but not limited to cirrhosis, hepatocellular carcinoma, chronic active hepatitis, colorectal cancer, acute liver failure, and portal vein obstruction. ROC analysis displayed that the six BA metabolites (GCDCA-3S, GUDCA-3S, CDCA-3S, NCA, TCDCA and HDCA) exhibited well differential diagnostic ability in discriminating between lean MAFLD patients and normal individuals with an area under the curve (AUC) ≥ 0.85. Conclusions: We delineated the characteristics of BA level in patients with lean MAFLD, and identified six potential plasma BA biomarkers of lean MAFLD. This strategy provided broad clinical application prospects for disease assessment. [ABSTRACT FROM AUTHOR]

Organic fluorescent materials with red/near‐infrared (NIR) emission are highly promising for use in biotechnology due to their exceptional advantages. However, traditional red/NIR fluorophores often exhibit weak emission at high concentrations or in an aggregated state due to the aggregate‐caused quenching effect, which severely limits their applicability in biological imaging. To address this challenge, we developed a series of cyanostyrene derivatives with aggregation‐induced emission characteristics, including 2,3‐Bis‐(4‐styryl‐phenyl)‐but‐2‐enedinitrile (DPB), 2,3‐Bis‐{4‐[2‐(4‐methoxy‐ phenyl)‐vinyl]‐phenyl}‐but‐2‐enedinitrile (DOB), 2,3‐Bis‐{4‐[2‐(4‐diphenylamino‐ phenyl)‐vinyl]‐phenyl}‐but‐2‐enedinitrile (DTB), and 2,3‐Bis‐[4‐(2‐{4‐[phenyl‐ (4‐triphenylvinyl‐phenyl)‐amino]‐phenyl}‐vinyl)‐ phenyl]‐but‐2‐enedinitrile (DTTB). Notably, these compounds exhibited intense solid state fluorescence owing to AIE effect, especially DTTB shows NIR emission with high solid state quantum efficiency (712 nm, ΦF=14.2 %). Then we prepared DTTB@PS‐PEG NPs nanoparticles by encapsulating DTTB with the amphiphilic polymer polystyrene‐polyethylene glycol (PS‐PEG). Importantly, DTTB@PS‐PEG NPs exhibited highly efficient NIR luminescence (ΦF=28.7 %) and a large two‐photon absorption cross‐section (1900 GM) under 800 nm laser excitation. The bright two‐photon fluorescence of DTTB@PS‐PEG indicated that it can be a highly promising candidate for two‐photon fluorescence probe. Therefore, this work provides valuable insights for the design of highly efficient and NIR‐emitting two‐photon fluorescent probes. [ABSTRACT FROM AUTHOR]

The strain technology is accelerating the progress on the CMOS compatible Ge-on-Si laser source. Here, we report a monolithically integrated microbridge-based emitting-detecting configuration, equipped with lateral p–i–n junctions, waveguide and gratings. The operating wavelength range of the emitting bridge and the detecting bridge are matched through the designed same dimensions of the two microbridges, as well as the strain. Strain-enhanced spontaneous emission and the effect of spectra red-shifting on low-loss transmission of on-chip light are discussed. Temperature dependence experiments reveal that in devices with highly strain-enhanced structure, the strain variation can offset the effect of electron thermalization, so that the performance of the device remains stable when temperature changes around room temperature.

SUMMARY: Uncovering the function of phytopathogen effectors is crucial for understanding mechanisms of pathogen pathogenicity and for improving our ability to protect plants from diseases. An increasing number of effectors have been predicted in various plant pathogens. Functional characterization of these effectors has become a major focus in the study of plant–pathogen interactions. In this study, we designed a novel screening system that combines the TMV (tobacco mosaic virus)‐GFP vector and Agrobacterium‐mediated transient expression in the model plant Nicotiana benthamiana. This system enables the rapid identification of effectors that interfere with plant immunity. The biological function of these effectors can be easily evaluated by observing the GFP fluorescence signal using a UV lamp within just a few days. To evaluate the TMV‐GFP system, we initially tested it with well‐described virulence and avirulence type III effectors from the bacterial pathogen Ralstonia solanacearum. After proving the accuracy and efficiency of the TMV‐GFP system, we successfully screened a novel virulence effector, RipS1, using this approach. Furthermore, using the TMV‐GFP system, we reproduced consistent results with previously known cytoplasmic effectors from a diverse array of pathogens. Additionally, we demonstrated the effectiveness of the TMV‐GFP system in identifying apoplastic effectors. The easy operation, time‐saving nature, broad effectiveness, and low technical requirements of the TMV‐GFP system make it a promising approach for high‐throughput screening of effectors with immune interference activity from various pathogens. Significance Statement: The development of a robust high‐throughput functional screening assay for pathogen effectors will facilitate the study in plant‐pathogen interactions. We established a novel screening system using the TMV‐GFP vector, enabling the rapid identification of effectors that interfere with plant immunity by observing GFP fluorescence under a UV lamp within a few days. The TMV‐GFP system is a promising approach for high‐throughput screening of effectors from diverse pathogens. [ABSTRACT FROM AUTHOR]

Industrial control systems (ICSs), as critical national infrastructures, are increasingly susceptible to sophisticated security threats. To address this challenge, our study introduces the CAE-T, a deep convolutional autoencoding transformer network designed for efficient anomaly detection and real-time fault monitoring in ICS. The CAE-T utilizes unsupervised deep learning, employing a convolutional autoencoder for spatial feature extraction from multidimensional time-series data, and combines this with a transformer architecture to capture long-term temporal dependencies. The design of the model facilitates rapid training and inference, while its dual-component approach, utilizing an optimization function based on support vector data description (SVDD), enhances detection accuracy. This integration synergistically combines spatiotemporal feature extraction, significantly improving the robustness and precision of anomaly detection in ICS environments. The CAE-T model demonstrated notable performance enhancements across three industrial control system datasets. Notably, the CAE-T model achieved approximately a 70.8% increase in F1 score and a 9.2% rise in AUC on the WADI dataset. On the SWaT dataset, the model showed improvements of approximately 2.8% in F1 score and 5% in AUC. The power system dataset saw more modest gains, with an approximately 0.1% uptick in F1 score and a 1% increase in AUC. These improvements validate the CAE-T model's efficacy and robustness in anomaly detection across various scenarios. [ABSTRACT FROM AUTHOR]

We report a microscopic study of p-GaAs/TiO2 heterojunctions using cross-sectional high resolution transmission electron microscopy (HRTEM). The photocatalytic performance for both H2 evolution and CO2 reduction of these heterostructures shows a very strong dependence on the thickness of the TiO2 over the range of 0-15 nm. Thinner films (1-10 nm) are amorphous and show enhanced catalytic performance with respect to bare GaAs. HRTEM images and electron energy loss spectroscopy (EELS) maps show that the native oxide of GaAs is removed by the TiCl4 atomic layer deposition (ALD) precursor, which is corrosive. Ti3+ defect states (i.e., O vacancies) in the TiO2 film provide catalytically active sites, which improve the photocatalytic efficiency. Density functional theory (DFT) calculations show that water molecules and CO2 molecules bind stably to these Ti3+ states. Thicker TiO2 films (15 nm) are crystalline and have poor charge transfer due to their insulating nature, while thinner amorphous TiO2 films are conducting.