ResTransUnet: An effective network combined with Transformer and U-Net for liver segmentation in CT scans.

Liver segmentation is a fundamental prerequisite for the diagnosis and surgical planning of hepatocellular carcinoma. Traditionally, the liver contour is drawn manually by radiologists using a slice-by-slice method. However, this process is time-consuming and error-prone, depending on the radiologist's experience. In this paper, we propose a new end-to-end automatic liver segmentation framework, named ResTransUNet, which exploits the transformer's ability to capture global context for remote interactions and spatial relationships, as well as the excellent performance of the original U-Net architecture. The main contribution of this paper lies in proposing a novel fusion network that combines Unet and Transformer architectures. In the encoding structure, a dual-path approach is utilized, where features are extracted separately using both convolutional neural networks (CNNs) and Transformer networks. Additionally, an effective feature enhancement unit is designed to transfer the global features extracted by the Transformer network to the CNN for feature enhancement. This model aims to address the drawbacks of traditional Unet-based methods, such as feature loss during encoding and poor capture of global features. Moreover, it avoids the disadvantages of pure Transformer models, which suffer from large parameter sizes and high computational complexity. The experimental results on the LiTS2017 dataset demonstrate remarkable performance for our proposed model, with Dice coefficients, volumetric overlap error (VOE), and relative volume difference (RVD) values for liver segmentation reaching 0.9535, 0.0804, and -0.0007, respectively. Furthermore, to further validate the model's generalization capability, we conducted tests on the 3Dircadb, Chaos, and Sliver07 datasets. The experimental results demonstrate that the proposed method outperforms other closely related models with higher liver segmentation accuracy. In addition, significant improvements can be achieved by applying our method when handling liver segmentation with small and discontinuous liver regions, as well as blurred liver boundaries. The code is available at the website: https://github.com/Jouiry/ResTransUNet.

RMAU-Net: Residual Multi-Scale Attention U-Net For liver and tumor segmentation in CT images.

Liver cancer is one of the leading causes of cancer-related deaths worldwide. Automatic liver and tumor segmentation are of great value in clinical practice as they can reduce surgeons' workload and increase the probability of success in surgery. Liver and tumor segmentation is a challenging task because of the different sizes, shapes, blurred boundaries of livers and lesions, and low-intensity contrast between organs within patients. To address the problem of fuzzy livers and small tumors, we propose a novel Residual Multi-scale Attention U-Net (RMAU-Net) for liver and tumor segmentation by introducing two modules, i.e., Res-SE-Block and MAB. The Res-SE-Block can mitigate the problem of gradient disappearance by residual connection and enhance the quality of representations by explicitly modeling the interdependencies and feature recalibration between the channels of features. The MAB can exploit rich multi-scale feature information and capture inter-channel and inter-spatial relationships of features simultaneously. In addition, a hybrid loss function, that combines focal loss and dice loss, is designed to improve segmentation accuracy and speed up convergence. We evaluated the proposed method on two publicly available datasets, i.e., LiTS and 3D-IRCADb. Our proposed method achieved better performance than the other state-of-the-art methods, with dice scores of 0.9552 and 0.9697 for LiTS and 3D-IRCABb liver segmentation, and dice scores of 0.7616 and 0.8307 for LiTS and 3D-IRCABb liver tumor segmentation.

Highly selective monoclonal antibody-based fluorescence immunochromatographic assay for the detection of fenpropathrin in vegetable and fruit samples.

Fenpropathrin (FPT) is a typical pyrethroid pesticide that can cause chronic toxicity to humans. Herein, an anti-FPT monoclonal antibody (mAb) was elicited via a novel hapten synthesized by introducing a carboxyl-containing spacer arm in the cyclopropane moiety of FPT. Characterized by enzyme-linked immunosorbent assay (ELISA), the mAb exhibited high affinity and selectivity to FPT with a half-maximal inhibitory concentration of 31.05 µg/L and negligible cross-reactivities with analogs of pyrethroids. Based on the mAb, a fluorescence immunochromatographic assay (FICA) for FPT detection was firstly developed. The detection limit of the FICA is 0.012 mg/kg which is much lower than the maximum residue limit of FPT for food samples. The average recoveries of FPT from spiked food samples by the FICA were 85.0-105.0%, and the obtained results were in good agreement with those of gas chromatography-tandem mass spectrometry. Overall, this work provided a reliable tool suitable for the detection of FPT residue for large-scale samples in a rapid and cost-effective manner.

Extracting Multi-Scale and Salient Features by MSE Based U-Structure and CBAM for Sleep Staging.

According to the World Health Organization, more and more people in the world are suffering from somnipathy. Automatic sleep staging is critical for assessing sleep quality and assisting in the diagnosis of psychiatric and neurological disorders caused by somnipathy. Many researchers employ deep learning methods for sleep stage classification and have achieved high performance. However, there are still no effective methods to modeling intrinsic characteristics of salient wave in different sleep stages from physiological signals. And transition rules hidden in signals from one to another sleep stage cannot be identified and captured. In addition, class imbalance problem in dataset is not conducive to building a robust classification model. To solve these problems, we construct a deep neural network combining MSE(Multi-Scale Extraction) based U-structure and CBAM (Convolutional Block Attention Module) to extract the multi-scale salient waves from single-channel EEG signals. The U-structured convolutional network with MSE is utilized to extract multi-scale features from raw EEG signals. After that, the CBAM is used to focus more on salient variation and then learn transition rules between successive sleep stages. Further, a class adaptive weight cross entropy loss function is proposed to solve the class imbalance problem. Experiments in three public datasets show that our model greatly outperform the state-of-the-art results compared with existing methods. The overall accuracy and macro F1-score (Sleep-EDF-39: 90.3%-86.2, Sleep-EDF-153: 89.7%-85.2, SHHS: 86.8%-83.5) on three public datasets suggest that the proposed model is very promising to completely take place of human experts for sleep staging.

Copper-Catalyzed Oxidative C-H Annulation of Quinolines with Dichloroethane toward Benzoquinoliziniums Using an In Situ Activation Strategy.

Described herein is a copper-catalyzed oxidative C-H annulation of quinolines with 1,2-chloroethane (DCE), providing a concise synthetic approach to benzoquinoliziniums. In this protocol, DCE not only serves as a solvent and an in situ activation agent of quinoline C2-H but also works as vinyl equivalents to constitute the six-membered azonia ring. Furthermore, the resultant benzoquinolizinium library exhibits good properties of binding to DNA and low cytotoxicity.

Carboxylated fluorescent microsphere based immunochromatographic test strip enabled sensitive and quantitative on-site detection for florfenicol in eggs.

Florfenicol (FF), used popularly in prevention and treatment of virus infections in livestock and poultry, has widely been found in eggs and harmful to human health. In this work, a sensitive and quantitative on-site detecting solution, monoclonal antibody-based carboxylated fluorescent microsphere immunochromatographic test strip assay (FM-ICTS), is design and applied for FF detection. The proposed method can sensitively detect FF in low detection limit of 0.030 ng/g and quantitatively measure its concentration from 0.1 ng/mL to 8.1 ng/mL (R2 = 0.9991) with high repeatability (CV<8.0 %). In addition, the established FM-ICTS method exhibited high measurement accuracy in FF samples as compared with HPLC-MS analysis and demonstrated satisfied recoveries (99.1-101.3 %). More importantly, the quantitative FF test strip demonstrate ultra-high stability, which presents approximately equivalent detection ability to the fresh one after stored at 4 °C for more than one year or stored at 37 °C for 60 days. Therefore, the proposed method is a promising solution for rapidly and sensitively quantitative determination of FF in eggs.

Semi-coherent cation-rich Mn-Cu oxides heterostructures as cathode for novel aqueous potassium dual-ion energy storage devices.

In this work, combining both advantages of aqueous energy storage systems (ESS) and conventional dual-ion ESS, a novel aqueous dual-ion ESS is developed based on K+ and OH- electrochemistry by employing semi-coherent K1.33Mn8O16-CuO (sc-Mn-Cu) cathode. Profting from the elaborate design, the electrolyte and cathode simultaneously act as source of cations. In the novel aqueous dual-ion ESS configuration, the dependence of the performance on the electrolyte salt concentration is reduced and the sc-Mn-Cu cathode can host OH- with lower working potentials by conversion mechanism. Furthermore, based on the sc-Mn-Cu cathode and freestanding V2O3-VC (fs-V2O3-VC) anode, we developed a flexible quasi-solid-state device. Remarkably, it exhibits an ultrahigh energy density of ~39.9 µW h cm-2 together with high power density of carbon-based devices, which outperforms most previously reported flexible storage devices to our knowledge. These results indicating that the unique mechanism of the sc-Mn-Cu cathode opens up a promising direction for low-cost and high-performance novel aqueous ESS.

Construction of Cationic Azahelicenes: Regioselective Three-Component Annulation Using In Situ Activation Strategy.

Described herein is a strategy to construct cationic azahelicenes through the three-component annulation reaction of isoquinoline, indole, and 1,2-dichloroethane (DCE), in which DCE serves as an in situ activating agent for C1-H activation of isoquinoline, a vinyl equivalent, and a solvent. This in situ activation annulation reaction features a facile one-step synthesis and complete regioselectivity. The complete regioselectivity of C1 over C3 for the isoquinoline ring paves a path to the helical structure in a highly ordered sequence. One of the synthesized ionic [5]azahelicenium fluorophores exhibits the potential to serve as a mitochondria-targeted biomarker with good photostability and low cytotoxicity.

Robustness of heat transfer in confined inclined convection at high Prandtl number.

We investigate the dependency of the magnitude of heat transfer in a convection cell as a function of its inclination by means of experiments and simulations. The study is performed with a working fluid of large Prandtl number, Pr≃480, and at Rayleigh numbers Ra≃10^{8} and Ra≃5×10^{8} in a quasi-two-dimensional rectangular cell with unit aspect ratio. By changing the inclination angle (ß) of the convection cell, the character of the flow can be changed from moderately turbulent, for ß=0^{∘}, to laminar and steady at ß=90^{∘}. The global heat transfer is found to be insensitive to the drastic reduction of turbulent intensity, with maximal relative variations of the order of 20% at Ra≃10^{8} and 10% at Ra≃5×10^{8}, while the Reynolds number, based on the global root-mean-square velocity, is strongly affected with a decay of more than 85% occurring in the laminar regime. We show that the intensity of the heat flux in the turbulent regime can be only weakly enhanced by establishing a large-scale circulation flow by means of small inclinations. However, in the laminar regime the heat is transported solely by a slow large-scale circulation flow which exhibits large correlations between the velocity and temperature fields. For inclination angles close to the transition regime in-between the turbulentlike and laminar state, a quasiperiodic heat-flow bursting phenomenon is observed.

Rhodium-catalyzed ortho-heteroarylation of phenols: directing group-enabled switching of the electronic bias for heteroaromatic coupling partner.

The directed oxidative C-H/C-H cross-coupling reactions between a functionalized arene and a heteroarene typically exhibit an electronic bias for the heteroaromatic coupling partner. Disclosed herein is a conception of directing group enabled-switching of the electronic bias for coupling partner from the electron-deficient to electron-rich heteroarene, demonstrating that the modification of the directing group may match the latent reactivity of heteroarene substrates caused by the distinctly different electronic nature. In this work, we develop a Rh(iii)-catalyzed ortho-heteroarylation of phenols with greatly important electron-rich heteroarenes such as benzothiophene, benzofuran, thiophene, furan and pyrrole via two-fold C-H activation, which presents broad substrate scopes of both phenols and electron-rich heteroarenes and shows the advantage of tolerance of reactive functional groups, especially halogen. This work also provides a new strategy for the construction of π-conjugated furan-fused heteroacenes prevalent in materials science in dramatically simplified procedures, which makes the protocol highly applicable.

Pd-Catalyzed Direct C-H Functionalization/Annulation of BODIPYs with Alkynes to Access Unsymmetrical Benzo[ b]-Fused BODIPYs: Discovery of Lysosome-Targeted Turn-On Fluorescent Probes.

A highly efficient palladium-catalyzed direct C-H functionalization/annulation of BODIPYs with alkynes has been developed for the first time to construct a series of unsymmetrical benzo[ b]-fused BODIPYs from readily available starting materials. These unsymmetrical benzo[ b]-fused BODIPYs exhibit remarkably red-shifted emissions and larger Stokes shifts than classical BODIPY dyes. Cell imaging experiments and cytotoxicity assays demonstrate that BODIPYs 4c and 4d have specific lysosome-labeling capacities, turn-on fluorescence emissions in cells, and low cytotoxicity.