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Wet deposition significantly impacts the basin ecosystem and water quality of the Qinling Mountains (QMs). However, few research focused on the difference in wet deposition between the northern (QN) and southern (QS) foothills due to the barrier effect of the QMs. This two-year investigation studied nutrient and organic matter deposition in QN and QS during summer and autumn. Results showed higher concentrations of nitrogen (N), phosphorus (P), dissolved organic carbon (DOC), and permanganate index (CODMn) in QN's rainwater, particularly in autumn. The CODMn in QN ranged 0.59–7.67 mg/L, and DOC ranged 0.64–4.45 mg/L. For QS, the CODMn ranged 0.71–3.25 mg/L, and DOC ranged 0.28–2.62 mg/L. Backward trajectory analysis revealed the accumulation of pollutants in QN originating from Northern China, intensified by autumn heating and straw burning. Tyrosine-like and humic-like components in rainwater DOM suggested that they primarily originated from autochthonous sources. Rainwater N:P mass ratios range from 39:1 to 145:1, highlighting a higher N input than P in QMs' wet deposition. The findings underscore the importance of atmospheric wet deposition in nutrient and organic matter input to the QMs and establish a foundation for exploring the ecological effects of wet deposition. HIGHLIGHTS Concentration of rainwater contaminant showed spatiotemporal variations.; The dilution effect significantly impacted volume-weighted mean concentration.; Higher rainwater pollutant concentrations due to higher atmospheric pollutant levels.; The proportion of N transported to the watershed was higher than that of C and P.;

Abstract Background Investigating immune cell infiltration in the brain post-ischemia-reperfusion (I/R) injury is crucial for understanding and managing the resultant inflammatory responses. This study aims to unravel the role of the RPS27A-mediated PSMD12/NF-κB axis in controlling immune cell infiltration in the context of cerebral I/R injury. Methods To identify genes associated with cerebral I/R injury, high-throughput sequencing was employed. The potential downstream genes were further analyzed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) analyses. For experimental models, primary microglia and neurons were extracted from the cortical tissues of mouse brains. An in vitro cerebral I/R injury model was established in microglia using the oxygen-glucose deprivation/reoxygenation (OGD/R) technique. In vivo models involved inducing cerebral I/R injury in mice through the middle cerebral artery occlusion (MCAO) method. These models were used to assess neurological function, immune cell infiltration, and inflammatory factor release. Results The study identified RPS27A as a key player in cerebral I/R injury, with PSMD12 likely acting as its downstream regulator. Silencing RPS27A in OGD/R-induced microglia decreased the release of inflammatory factors and reduced neuron apoptosis. Additionally, RPS27A silencing in cerebral cortex tissues mediated the PSMD12/NF-κB axis, resulting in decreased inflammatory factor release, reduced neutrophil infiltration, and improved cerebral injury outcomes in I/R-injured mice. Conclusion RPS27A regulates the expression of the PSMD12/NF-κB signaling axis, leading to the induction of inflammatory factors in microglial cells, promoting immune cell infiltration in brain tissue, and exacerbating brain damage in I/R mice. This study introduces novel insights and theoretical foundations for the treatment of nerve damage caused by I/R, suggesting that targeting the RPS27A and downstream PSMD12/NF-κB signaling axis for drug development could represent a new direction in I/R therapy.

Abstract It is very challenging to accurately segment smoke images because smoke has some adverse vision characteristics, such as anomalous shapes, blurred edges, and translucency. Existing methods cannot fully focus on the texture details of anomalous shapes and blurred edges simultaneously. To solve these problems, a Dense Multi‐scale context and Asymmetric pooling Embedding Network (DMAENet) is proposed to model the smoke edge details and anomalous shapes for smoke segmentation. To capture the feature information from different scales, a Dense Multi‐scale Context Module (DMCM) is proposed to further enhance the feature representation capability of our network under the help of asymmetric convolutions. To efficiently extract features for long‐shaped objects, the authors use asymmetric pooling to propose an Asymmetric Pooling Enhancement Module (APEM). The vertical and horizontal pooling methods are responsible for enhancing features of irregular objects. Finally, a Feature Fusion Module (FFM) is designed, which accepts three inputs for improving performance. Low and high‐level features are fused by pixel‐wise summing, and then the summed feature maps are further enhanced in an attention manner. Experimental results on synthetic and real smoke datasets validate that all these modules can improve performance, and the proposed DMAENet obviously outperforms existing state‐of‐the‐art methods.

Dissolved oxygen (DO) is strongly linked to the origin and transformation of dissolved organic matter (DOM) in reservoirs. During metalimnetic oxygen minimum (MOM), the reservoir is divided into four regions: surface oxygen-rich (SOR), middle anoxic (MA), middle oxygen (MO), and bottom anoxic (BA). This article focuses on the link between DOM and disinfection by-product (DBP) precursors and DO in reservoirs. The DOM in SOR was characterized by the highest proportion of protein-like components, lowest humification and aromaticity, which was indicated mainly affected by algae blooms. The DOM in MO was affected by terrestrial, with the highest ratio of humic and fulvic-like fluorescent and the highest extent of humification and aromaticity. The humification and aromaticity in MA and BA were between MO and SOR water. Moreover, according to redundancy analysis, the dominant DBPs, including trichloromethane and haloacetic acid precursors, mainly originate from a high degree of humification and aromaticity in DOM, suggesting that the terrestrial-derived DOM was a dominant source of DBP precursors. This study provides the distribution in DOM characteristics and its driven DBPs in the Sanhekou Reservoir during the MOM, which is of great significance for selecting appropriate water intake regions for subsequent water treatment. HIGHLIGHTS This article describes in detail the distribution of dissolved organic matter (DOM) and disinfection by-product (DBP) precursors in deep reservoirs. It examines the effect of different sources on DOM characteristics and DBP precursors.; The relationship between DOM characteristics and the yields of DBPs.;

Accurate cloud detection is an important step to improve the utilization rate of remote sensing (RS). However, existing cloud detection algorithms have difficulty in identifying edge clouds and broken clouds. Therefore, based on the channel data of the Himawari-8 satellite, this work proposes a method that combines the feature enhancement module with the Gaussian mixture model (GMM). First, statistical analysis using the probability density functions (PDFs) of spectral data from clouds and underlying surface pixels was conducted, selecting cluster features suitable for daytime and nighttime. Then, in this work, the Laplacian operator is introduced to enhance the spectral features of cloud edges and broken clouds. Additionally, enhanced spectral features are input into the debugged GMM model for cloud detection. Validation against visual interpretation shows promising consistency, with the proposed algorithm outperforming other methods such as RF, KNN and GMM in accuracy metrics, demonstrating its potential for high-precision cloud detection in RS images.

Abstract Background The simplified 3-grade system for measuring fat infiltration in the paraspinal muscles is widely utilized. In comparing our proposed 4-grade system to the existing 3-grade system, we evaluated its impact on results and particularly its ability to predict disc herniation, ultimately highlighting deficiencies in the latter. The objective of this investigation was to validate the efficacy of our newly proposed semi-quantitative simplified 4-grade system for assessing fat infiltration, as compared to the existing literature-based simplified 3-grade system, in terms of their predictive value for lumbar disc herniation. Methods Infiltration of the right and left lumbar multifidus and erector spinae muscles were assessed using a semi-quantitative 3- and 4-grade fat infiltration system on axial magnetic resonance imaging sections at the L3-S1 level in all subjects, with comparison of results between groups. The correlation between these grading systems and lumbar disc herniation was investigated. Results The simplified 3-degree system for measuring fat infiltration was not effective in predicting lumbar disc herniation (p > 0.05), while the 4-degree system proved to be useful in predicting it (p

Abstract Super-resolution structured illumination microscopy (SR-SIM) has become a widely used nanoscopy technique for rapid, long-term, and multi-color imaging of live cells. Precise but troublesome determination of the illumination pattern parameters is a prerequisite for Wiener-deconvolution-based SR-SIM image reconstruction. Here, we present a direct reconstruction SIM algorithm (direct-SIM) with an initial spatial-domain reconstruction followed by frequency-domain spectrum optimization. Without any prior knowledge of illumination patterns and bypassing the artifact-sensitive Wiener deconvolution procedures, resolution-doubled SR images could be reconstructed by direct-SIM free of common artifacts, even for the raw images with large pattern variance in the field of view (FOV). Direct-SIM can be applied to previously difficult scenarios such as very sparse samples, periodic samples, very small FOV imaging, and stitched large FOV imaging.

Image segmentation methods usually fuse shallow and deep features to locate object boundaries, but it is difficult to improve the accuracy of smoke segmentation by conventional fusion methods. It is a very difficult vision task to perform semantic segmentation of smoke images, because the translucency and irregular shapes of smoke lead to extremely complicated mixtures with background that are adverse to segmentation. To improve the segmentation accuracy of smoke scenes, we propose a Boundary Enhancement and Pixel Alignment based smoke segmentation Network for fire alarms. For the shallow features of the network, an attention mechanism is adopted to capture spatially details of smoke for improving boundary precision. For the deep layers, the Pyramid Pooling Module is used to extract local features and abstract semantic ones simultaneously. Finally, to efficiently merge shallow and deep features, a Pixel Alignment Module is adopted to model the relationship between pixel locations. The experimental results show that the mean Intersection over Union of the proposed method on the three synthetic smoke test datasets is 78.61%, 77.63% and 77.30%, respectively, and it outperforms most of the existing methods. In addition, our method obtains satisfying results on inconspicuous smoke and smoke-like images.

Post-collisional alkaline intrusive rocks from the Dabie orogen were studied for their whole-rock major-trace elements and Sr-Nd-Hf-Pb isotopes, as well as zircon U-Pb ages and Hf-O isotopes. The results provide geochemical constraints on the nature of their mantle sources and thus insight into crust-mantle interaction in the continental collision zone. The alkaline intrusive rocks are composed of syenite and nepheline syenite. Syn-magmatic zircon U-Pb dating by LA-ICP-MS for them yielded Early Cretaceous ages of 131.3 ± 1.4 Ma to 122.6 ± 0.6 Ma, coeval with the post-collisional magmatism in the Dabie orogen. One relict zircon with U-Pb age of 211 Ma is consistent with the timing of metamorphism for the ultrahigh-pressure (UHP) metamorphic rocks in this orogen. They have arc-like trace element distribution patterns, such as enrichment in LILE (large ion lithophile element) and LREE (light rare earth element) but depletion in HFSE (high field strength element), and enriched whole-rock Sr-Nd-Hf isotope compositions with high (87Sr/86Sr)i ratios of 0.7077–0.7131 but negative εNd(t) values of −16.0 to −9.4 and εHf(t) values of −17.5 to −12.7. Their syn-magmatic zircons have three groups of Hf-O isotope compositions comparable to those of UHP metamorphic rocks in Central-South Dabie and North Dabie, which represent the upper and middle continental crust of the subducted South China Block, respectively. In this regard, slab–mantle interaction is evident during the Triassic continental collision. We suggest that the melts derived from the subducted South China Block reacted with the lithospheric mantle wedge of the North China Block, resulting in phlogopite-bearing metasomatites, whose partial melting would generate the post-collisional alkaline intrusive rocks during the Early Cretaceous.

Approaching the peak year of the 25th solar activity cycle, the frequency of strong geomagnetic storms is gradually increasing, which seriously affects the navigation and positioning performance of GNSS. Based on the globally distributed GNSS station data and FORMOSAT-7/COSMIC-2 occultation data, this paper explores for the first time the effects of the G4-class geomagnetic storm that occurred on 23–24 April 2023 on the global ionosphere, especially the ionospheric equatorial anomalies and F-layer perturbations. It reveals the precise point positioning (PPP) accuracy degradation during a geomagnetic storm. The results show that the ionospheric rate of total electron content index (ROTI) and near high latitude GNSS phase scintillations index have varying levels of perturbation during geomagnetic storms, with the maximum ROTI and phase scintillations index exceeding 0.5 TECU/min and 0.8, respectively. The equatorial ionization anomaly (EIA) shows an enhanced state (positive ionospheric storms) during geomagnetic storms, and the cause of this phenomenon is most likely the equatorward neutral wind. The variation of the S4 index of the FORMOSAT-7/COSMIC-2 satellite reveals the uplift of the F-layer during geomagnetic storms. During geomagnetic storms, the PPP accuracy degrades most seriously at high latitudes, the maximum MAE exceeds 2.3 m, and the RMS in the three-dimensional (3D) direction exceeds 2.0 m. These investigations can provide case support for space weather and GNSS studies of the impact of geomagnetic storms during peak solar activity years.

Early smoke detection using Digital Image Processing technology is an important research field, which has great applications in reducing fire hazards and protecting the ecological environment. Due to the complex changes of color, shape and size of smoke with time, it is challenging to accurately recognize smoke from a given image. In addition, limited by domain shift, the trained detector is difficult to adapt to the smoke in real scenes, resulting in a sharp drop in detection performance. In order to solve this problem, an unsupervised domain adaptive smoke detection algorithm rely on Multilevel feature Cooperative Alignment and Fusion (MCAF) was proposed in this paper. Firstly, the cooperative domain alignment is performed on the features of different scales obtained by the feature extraction network to reduce the domain difference and enhance the generalization ability of the model. Secondly, multilevel feature fusion modules were embedded at different depths of the network to enhance the representation ability of small targets. The proposed method is evaluated on multiple datasets, and the results show the effectiveness of the method.

Long-distance water transfer projects are important for water allocation. To enhance our understanding of biofilm growth and changes in water quality during raw water transfer, raw water through a long-distance non-full culvert at flow rates of 1.4−2.0 m/s was studied. The results revealed that: (1) the biofilm total cell count (TCC) and heterotrophic plate count (HPC) were the highest at a flow rate of 1.5 m/s, which were 3.7 × 104 cells/cm2 and 1.1 × 103 CFU/cm2, respectively; (2) Proteobacteria had the highest relative abundance (RA) among all samples, and the RA in biofilm (78.85%) was higher than that in water (48%−59%); (3) when the pollutants and biofilm were partially shed, the total phosphorus (TP), permanganate index (CODMn), and dissolved organic carbon (DOC) increased by 0.011, 0.36, and 0.5 mg/L at most, respectively; and (4) dissolved oxygen (DO) was sufficient during non-full flow water transport and nitrification occurred. The highest removal rates of ammonium nitrogen (NH+4-N) and nitrous nitrogen (-N) reached 27.16% and 66.76%, respectively. At the flow rates of 2.0 m/s, the efficiency decreased to 10.47% and 41.25%, respectively, due to the shedding of biofilm. HIGHLIGHTS Raw water flow over a long-distance non-full culvert studied using an experimental model.; Flow rate influenced biofilm biomass, and resulted in different bacterial community structure in bulk water and biofilm.; Nitrification in the long-distance non-full culvert was only 0.54%–1.2% that in the simulation experiment.;

Abstract Structured illumination microscopy (SIM) has become a widely used tool for insight into biomedical challenges due to its rapid, long-term, and super-resolution (SR) imaging. However, artifacts that often appear in SIM images have long brought into question its fidelity, and might cause misinterpretation of biological structures. We present HiFi-SIM, a high-fidelity SIM reconstruction algorithm, by engineering the effective point spread function (PSF) into an ideal form. HiFi-SIM can effectively reduce commonly seen artifacts without loss of fine structures and improve the axial sectioning for samples with strong background. In particular, HiFi-SIM is not sensitive to the commonly used PSF and reconstruction parameters; hence, it lowers the requirements for dedicated PSF calibration and complicated parameter adjustment, thus promoting SIM as a daily imaging tool.

Fungi pollution in water can lead to serious problems, such as turbidity, odor, food pollution, mycotoxin production, and increased opportunistic infections among people with an immune deficiency. Few studies have reported the fungi community composition, quantity of fungi, and origin of fungi in groundwater. To study the change of quantity and community composition of fungi in groundwater at different times of year, this study evaluated the number of fungi and dominant fungi genera in groundwater and the factors affecting fungi quantity. The results showed that 18 genera of fungi were observed in the study area’s groundwater, among which Penicillium (18–27%), Aspergillus (17–26%), Acremonium (12–28%) were the three most dominant. The numbers of dominant fungi genera were as follows: Penicillium (21–62 CFU/100 mL), Aspergillus (18–43 CFU/100 mL), and Acremonium (15–38 CFU/100 mL). The number of fungi in water closely correlates with environmental variables such as pH, dissolved oxygen (DO), turbidity, and total organic carbon (TOC). Various genera of fungi were affected differently by unique environmental variables. The fungi in the water were also affected by components of the external environment, such as rainfall, surface farming, surface water sources, and so on. This study aims to provide meaningful information for understanding fungi pollution in groundwater.

Thermophoresis is of common interest due to its influence on the deposition of particles. Present research on thermophoretic deposition mainly focused on the sub-micron particles, whereas the particle size during the radioactive aerosol monitoring process usually exceeds the range. In order to study the effect of thermophoresis on the deposition characteristics of aerosols ranging from 1 to 10 µm, direct numerical simulation (DNS) and experiments of particle deposition are performed in this paper aiming at still and turbulent flow respectively. The results obtained by DNS coupled with Lagrangian particle tracking (LPT) are validated by the experimental data and the theoretical values. The results indicate that thermophoresis has an influence on the deposition of micron-sized particles, and the effect of thermophoresis on deposition velocity depends on particle size. In the still air, when the temperature gradient is 3000 K/m, the deposition velocity of 1 and 10 µm particles will be increased by 87% and 4.8% respectively when compared with gravitational deposition velocity. In the turbulent flow, the motion of particles is dominated by turbulent motion. In the region near the wall, thermophoresis can increase the deposition rate on the cold wall.

Automated inspection using unmanned aerial vehicles (UAVs) is an essential means to ensure safe operations of the power grid. Defect detection for antivibration hammers on transmission lines in inspection imagery is one of the critical tasks for automated UAV inspection. It needs a machine interpretation system to automatically detect numerous inspection images. In this paper, a high-efficiency model based on Cascade RCNN (region-convolutional neural network) is proposed to detect antivibration hammer defects with reduced costs and speedier response, which applies in energy-efficient transmission line inspection systems. Firstly, to reduce computational costs, this study modifies the Cascade RCNN with a probabilistic interpretation to achieve the best trade-off between the inference time and average precision. Secondly, an antivibration hammer defect detector (AVHDD) model is proposed that uses a deep layer aggregation-based feature extraction network and a highly effective weighted bidirectional feature fusion network to replace the original ResNet and FPN on the modified Cascade RCNN to further enhance the model performance. Finally, a fine classification (FC) scheme for the types of antivibration hammer defects is proposed based on defect features to rationalize the model. The AVHDD reached an experimental mAP of 97.24% when IoU = 0.75, which is 2.93% higher than the original Cascade RCNN, and the defect recall was 98.9% while also significantly improving the inference speed. Moreover, the experimental results indicate that the overall performance of the proposed model is superior to typical models, confirming its suitability for energy-efficient transmission line inspection systems.

Exceeding the permitted manganese (Mn2+) and ammonium (NH4+-N) levels is a frequent seasonal occurrence in a water treatment plant in south China. An iron Fe–Mn complex oxide film was found capable of removing more than 95% of Mn2+ and NH4+-N at a water temperature of 20 °C and an alkalinity level of 30 mg/L. It could remove up to 5.5 mg/L of Mn2+ and up to 3.5 mg/L of NH4+-N in a stable manner. Alkalinity is a crucial factor in the removal process. The morphology, elemental composition, and micro-structure of the oxide film were investigated using a scanning electron microscope, an energy-dispersive spectrometer, a Brunauer–Emmett–Teller specific surface-area analyzer, an X-ray diffractometer, and a Fourier-transform infrared spectrometer. The capacity of the Fe–Mn complex oxide film on the surface of the filter medium increased appreciably as its content and specific surface area increased. This research, which provides a theoretical basis for simultaneous manganese and NH4+-N removal by catalytic oxidation, demonstrates an engineering reference value.

In this paper, we provide a comprehensive survey of the recent advances in abnormality detection in smart grids using multimodal image data, which include visible light, infrared, and optical satellite images. The applications in visible light and infrared images, enabling abnormality detection at short range, further include several typical applications in intelligent sensors deployed in smart grids, while optical satellite image data focus on abnormality detection from a large distance. Moreover, the literature in each aspect is organized according to the considered techniques. In addition, several key methodologies and conditions for applying these techniques to abnormality detection are identified to help determine whether to use deep learning and which kind of learning techniques to use. Traditional approaches are also summarized together with their performance comparison with deep-learning-based approaches, based on which the necessity, seen in the surveyed literature, of adopting image-data-based abnormality detection is clarified. Overall, this comprehensive survey categorizes and carefully summarizes insights from representative papers in this field, which will widely benefit practitioners and academic researchers.

Structured illumination microscope (SIM) can double the spatial resolution by using fringed pattern illumination. However, for samples with large intra-scene dynamic ranges, such as clustered objects, SIM fails to reconstruct high-quality images and often exhibits strong artifacts. Herein, we present a high dynamic range SIM (HDR-SIM) method using a multi-exposure acquisition strategy. With HDR-SIM, individual and clustered microspheres and vesicles with 420 times intensity differences can be visualized in the same scene while the delicate structures of the sample were preserved effectively.

This study investigates the effects of cathepsins on the gel strength and water-holding capacity (WHC) of myofibrillar protein gels from bighead carp (Aristichthys nobilis) under a hydroxyl radical-generation oxidizing system. The myofibrillar proteins were divided into control group (with cathepsins) and E64 group (without cathepsins). The changes of cathepsin B and cathepsin L activities, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), protein oxidation (total sulfhydryl and carbonyl contents), and chemical interactions (nonspecific association, ionic bonds, hydrogen bonds, hydrophobic interactions, and disulfides) of myofibrillar protein and gels, as well as the gel strength and WHC of two groups under 0–100 mM H2O2, were measured. The results indicated that mild oxidation (10 mM H2O2) made a better gel strength and WHC. Cathepsin B and L activities decreased with increasing H2O2 concentrations but their effects on myofibrillar protein degradation still existed during 0.1–50 mM H2O2, which was expressed by higher carbonyl contents and ionic bonds at 0.1 and 50 mM H2O2, higher total sulfhydryl contents at 0 mM H2O2, and a lower intensity of MHC and actin of the control group than the E64 group. Besides more protein degradation, cathepsin proteolysis also resulted in lower gel strength and WHC in control gels than E64 gels under mild oxidation, which could be explained by lower hydrophobic interaction and moderate disulfides bonds between gel protein molecules of control gels.

The O3/PMS system has appeared as an effective wastewater treatment method because of the simultaneous generation of hydroxyl radicals (•OH) and sulfate radicals (SO4•−). Many research achievements have been made on the degradation of micropollutants and the reaction mechanism of the O3/PMS system. However, an integral understanding of the O3/PMS system is lacking, which limits the development of safe and effective AOP-based water treatment schemes. Therefore, in this review, the degradation effects, toxicity changes, and reaction mechanisms of various micropollutants in the O3/PMS system are reviewed. The formation of oxidation by-products (OBPs) is an important issue that affects the practical application of O3/PMS systems. The formation mechanism and control methods of OBPs in the O3/PMS system are overviewed. In addition, the influence of different reaction conditions on the O3/PMS system are comprehensively evaluated. Finally, future research needs are proposed based on the limited understanding of O3/PMS systems in the degradation of micropollutants and formation of OBPs. Specifically, the formation rules of several kinds of OBPs during the O3/PMS system are not completely clear yet. Furthermore, pilot-scale research, the operational costs, sustainability, and general feasibility of the O3/PMS system also need to be studied. This review can offer a comprehensive assessment on the O3/PMS system to fill the knowledge gap and provide guidance for the future research and engineering applications of the O3/PMS system. Through this effort, the O3/PMS system can be better developed and turned towards practical applications.

Structured illumination microscopy (SIM) is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly used fluorescent labeling methods. Structured illumination can be obtained by either laser interference or projection of fringe patterns. Here, we proposed a fringe projector composed of a compact multi-wavelength LEDs module and a digital micromirror device (DMD) which can be directly attached to most commercial inverted fluorescent microscopes and update it into a SIM system. The effects of the period and duty cycle of fringe patterns on the modulation depth of the structured light field were studied. With the optimized fringe pattern, 1.6× resolution improvement could be obtained with high-end oil objectives. Multicolor imaging and dynamics of subcellular organelles in live cells were also demonstrated. Our method provides a low-cost solution for SIM setup to expand its wide range of applications to most research labs in the field of life science and medicine.

A useful method for the synthesis of 2-acylamino-1,3,4-oxadiazoles was developed. By using potassium iodate as an oxidant in water at 60 °C, a wide range of 2-acylamino-1,3,4-oxadiazoles were afforded in moderate to excellent yields within two hours. This method could provide a facile shortcut to generate a series of 2-acylamino-1,3,4-oxadiazoles in medicinal chemistry. Interestingly, some highly potent antibiotic compounds were found through this synthetic method, and some of them displayed a significant improvement in activity compared with the corresponding 1,4-diacylthiosemicarbazides. Compound 2n was the most active against Staphylococcus aureus with MIC (minimum inhibitory concentration) of 1.56 mg/mL, and compounds 2m and 2q were the most active against Bacillus subtilis with MIC of 0.78 mg/mL. The preliminary cytotoxic activities of the most potent compounds 2m, 2n, and 2q against the androgen-independent (PC-3) prostate cancer cell line were more than 30 μM (IC50 > 30 μM).

We have developed a new method to prepare 4-acetoxy substituted 5(4H)-oxazolones by direct oxidation of N-benzoyl amino-acids using hypervalent iodine. The method is efficient, economical and easy to perform for the synthesis of quaternary substituted amino acid derivatives. We used online FTIR monitoring techniques to analyze the reaction, and gave a plausible reaction mechanism.