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Objective: To predict the active components and action targets of Wuyao (Linderae Radix) in the treatment of chronic pelvic inflammatory disease (CPID) based on network pharmacology, explore possible mechanisms of the treatment through animal experiments, and provide a scientific basis for clinical applications of Wuyao (Linderae Radix). Methods: Possible active components and targets of Wuyao (Linderae Radix) in the treatment of CPID were obtained applying network pharmacology and molecular docking technology. CPID rat models were established using the mixed Escherichia coli, Staphylococcus aureus, and Ureaplasma urealyticum plus the performance of mechanical injury. Hematoxylin-eosin (HE) staining was applied to observe the pathological changes in the uterus, fallopian tube, and spleens of rat models. The contents of nitric oxide (NO), superoxide dismutase (SOD), and malondialdehyde (MDA) in the serum of rats were determined with the use of corresponding detection kits. Enzyme-linked immunosorbent assay (ELISA) test was used to measure the expression of interleukin (IL)-6 and IL-10 in the serum of rat models. Flow cytometry was used to determine the percentage of CD4+ and CD8a+ T cells as well as CD4+ CD25+ regulatory T cells (Tregs) in the spleen of rat models. Results: A total of nine potential active components and four core therapeutic targets related to inflammatory response in Wuyao (Linderae Radix) were obtained. The animal experiments showed that Wuyao (Linderae Radix) markedly inhibited uterus swelling, regulated morphological changes in the fallopian tube and spleen, effectively reduced inflammatory infiltration and injuries in the uterus and fallopian tube, and improved spleen functions in CPID rats. Moreover, Wuyao (Linderae Radix) markedly reduced the levels of NO, IL-6, and MDA, and increased the levels of IL-10 and SOD in the serum of rats. Wuyao (Linderae Radix) also elevated the percentage of CD4+ T cells and the CD4+ T/CD8a+ T cell ratio, reduced the percentage of CD8a+ T cells, and raised the percentage of CD4+ CD25+ Tregs that had been abnormally decreased in rat models (P < 0.05). Conclusion: Wuyao (Linderae Radix) could have therapeutic effects on CPID rats by relieving oxidative stress, mitigating inflammatory levels, and regulating the immuno-function of T cell subgroups to improve the pathological changes in CPID rats. It is a medicinal herb worth being further explored for its clinical values.

Recently, two-dimensional magnetic materials (2DMMs) have become a focused research direction in a broad range of two-dimensional materials, due to their underlying significance in fundamental research, as well as in technologically relevant applications for future spintronics, magnonics, quantum information and data storage. The rich toolbox of 2DMMs and their diverse tunability have enabled the unprecedented research concerning the two-dimensional magnetic order down to single atomic layer of materials, much beyond the classical thin film magnetism, showing an extremely promising avenue towards electronics, magneto-optics and photonics. Among various degrees of freedoms, the interaction between spin and phonon (i.e., quanta of lattice vibration), hence the so-called spin-phonon coupling, serves as an important tuning knob to explore the two-dimensional magnetism, creates new types of quasiparticles and controls the magnetic order. This review overviews the latest developments in spin-phonon coupling investigations in 2DMMs. Various techniques utilizing spin-phonon coupling to investigate two-dimensional magnetism are discussed. Recent progress in tuning two-dimensional magnetic order based on spin-phonon coupling is also summarized, with a focus to understand the new functionalities. Furthermore, device developments and concepts based on spin-phonon coupling are briefly discussed. This review will provide our perspectives on the existing challenges and future directions in spin-phonon coupling research in 2DMMs and their functional devices.

Biological crusts (BC) are an organic complex, composed of bacteria, cyanobacteria, diatoms, green algae, tiny fungi, ground jackets, and moss plants, as well as other related organisms. BC is distributed about 40% in arid areas, which is one of the important surface landscapes in the intertwined area between oasis and desert. The relationship between BC and drought is close, which can be used to monitor desertification and water resources in remote sensing. However, the current monitoring of BC uses a simple BC index composed of multi-spectrum to extract its area distribution in remote sensing, which makes it difficult to accurately detect its area. This study considers the characteristic bands in the hyper-spectrum cure and designs a hyperspectral index of BS, i.e., HBCI. The HBCI is used, and we successfully estimated the area of biological soil crusts (Kappa=0.86) in the PRISMA image. This finding has help for the regional climate change research.

Computer vision has become a powerful tool in the field of biosensing, aiding in the development of innovative and precise systems for the analysis and interpretation of biological data. This interdisciplinary approach harnesses the capabilities of computer vision algorithms and techniques to extract valuable information from various biosensing applications, including medical diagnostics, environmental monitoring, and food health. Despite years of development, there is still significant room for improvement in this area. In this perspective, we outline how computer vision is applied to raw sensor data in biosensors and its advantages to biosensing applications. We then discuss ongoing research and developments in the field and subsequently explore the challenges and opportunities that computer vision faces in biosensor applications. We also suggest directions for future work, ultimately underscoring the significant impact of computer vision on advancing biosensing technologies and their applications.

An aerosol jet printing-enabled dual-function biosensor for the sensitive detection of pathogens using SARS-CoV-2 RNA as an example has been developed. A CRISPR-Cas13:guide-RNA complex is activated in the presence of a target RNA, leading to the collateral trans-cleavage of ssRNA probes that contain a horseradish peroxidase (HRP) tag. This, in turn, catalyzes the oxidation of 3,3,5,5-tetramethylbenzidine (TMB) by HRP, resulting in a color change and electrochemical signal change. The colorimetric and electrochemical sensing protocol does not require complicated target amplification and probe immobilization and exhibits a detection sensitivity in the femtomolar range. Additionally, our biosensor demonstrates a wide dynamic range of 5 orders of magnitude. This low-cost aerosol inkjet printing technique allows for an amplification-free and integrated dual-function biosensor platform, which operates at physiological temperature and is designed for simple, rapid, and accurate point-of-care (POC) diagnostics in either low-resource settings or hospitals.

A novel localized surface plasmon resonance (LSPR) system based on the coupling of gold nanomushrooms (AuNMs) and gold nanoparticles (AuNPs) is developed to enable a significant plasmonic resonant shift. The AuNP size, surface chemistry, and concentration are characterized to maximize the LSPR effect. A 31 nm redshift is achieved when the AuNMs are saturated by the AuNPs. This giant redshift also increases the full width of the spectrum and is explained by the 3D finite-difference time-domain (FDTD) calculation. In addition, this LSPR substrate is packaged in a microfluidic cell and integrated with a CRISPR-Cas13a RNA detection assay for the detection of the SARS-CoV-2 RNA targets. Once activated by the target, the AuNPs are cleaved from linker probes and randomly deposited on the AuNM substrate, demonstrating a large redshift. The novel LSPR chip using AuNP as an indicator is simple, specific, isothermal, and label-free; and thus, provides a new opportunity to achieve the next generation multiplexing and sensitive molecular diagnostic system.

Image classification belongs to the machine learning and computer vision fields, it aims to recognize and classify objects in the image contents. How to apply image classification algorithms to large-scale data in the IoT framework is the focus of current research. Based on Anaconda, this article implement sk-NN, SVM, Softmax and Neural Network algorithms by Python, performs data normalization, random search, HOG and colour histogram feature extraction to enhance the algorithms, experiments on them in CIFAR-10 datasets, then conducts comparison from three aspects of training time, test time and classification accuracy. The experimental results show that: the vectorized implementation of the algorithms is more efficient than the loop implementation; The training time of k-NN is the shortest, SVM and Softmax spend more time, and the training time of Neural Network is the longest; The test time of SVM, Softmax and Neural Network are much shorter than of k-NN; Neural Network gets the highest classification accuracy, SVM and Softmax get lower and approximate accuracies, and k-NN gets the lowest accuracy. The effects of three algorithm improvement methods are obvious.

Superhydrophobic surface-based optofluidics have been introduced to biosensors and unconventional optics with unique advantages, such as low light loss and power consumption. However, most of these platforms were made with planar-like microstructures and nanostructures, which may cause bonding issues and result in significant waveguide loss. Here, we introduce a fully enclosed superhydrophobic-based optofluidics system, enabled by a one-step microstereolithography procedure. Various microstructured cladding designs with a feature size down to 100 μm were studied and a T-type overhang design exhibits the lowest optical loss, regardless of the excitation wavelength. Surprisingly, the optical loss of superhydrophobic-based optofluidics is not solely decided by the solid area fraction at the solid/water/air interface, but also the cross-section shape and the effective cladding layer composition. We show that this fully enclosed optofluidic system can be used for CRISPR-labeled quantum dot quantification, intended for in vitro and in vivo CRISPR therapeutics.