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Abstract Azvudine and nirmatrelvir-ritonavir (Paxlovid) were widely used to treat patients with COVID-19 in China during the Omicron wave. However, the efficacy and safety of azvudine versus Paxlovid are poorly established. This study included 40,876 hospitalized patients with COVID-19 from eleven hospitals in Henan and Xinjiang Provinces, China. Clinical outcomes were compared between the two drugs via Kaplan–Meier analysis and Cox regression models. Additionally, in vitro and in vivo experiments were used to evaluate the antitumor effects and safety of both drugs. Single-cell RNA sequencing was performed to elucidate the tumor immune landscape after azvudine treatment. After propensity score matching, 2404 azvudine and 1202 Paxlovid recipients from Henan Province were included. Cox regression revealed that azvudine was related to an 18% lower risk of all-cause death than Paxlovid (95% CI: 0.676–0.987), was not obviously different in composite disease progression. The robustness of the findings was verified by the Xinjiang cohort and three sensitivity analyses. Fewer adverse events were observed in the azvudine group. Subgroup analysis revealed that azvudine provided greater benefits for patients with malignant tumors, significantly reducing both all-cause death (hazard ratio [HR]: 0.33, 95% CI: 0.20−0.54) and composite disease progression (HR: 0.54, 95% CI: 0.33−0.88). Furthermore, azvudine can suppress the growth of hepatocellular carcinoma (HCC) by regulating CD4+ T and CD8+ T cells in vivo. These findings suggest that azvudine therapy is not inferior to Paxlovid in hospitalized COVID-19 patients and has fewer adverse effects. Notably, azvudine may offer greater clinical benefit for patients with HCC.

BackgroundGestational diabetes mellitus (GDM) is a common metabolic disorder with important health implications for both mother and offspring. This study aims to assess the relationship between the Triglyceride Glucose (TyG) index and GDM and explore its clinical significance.MethodsA retrospective cohort study included 631 singleton pregnant women. The study collected data on the TyG index, glucose levels, and clinical outcomes from all participants. Research objectives were validated using logistic regression analysis and Receiver Operating Characteristic curves.ResultsWe found an independent correlation between TyG index and increased risk of GDM, with an odds ratio (OR) of 3.11 (95% confidence interval (CI): 2.09-4.63, P

The assessment of freeze desalination (FD) efficiency is lagging behind due to the lack of an effective means of determining ice total dissolved solid (TDS). In this paper, an ice TDS prediction model was constructed by utilizing the law of conservation of matter (LCMat) and conservation of mass (LCMas) in the icing process. It was concluded that the average TDS ice crystals in any icing process was correlated with the TDS of the raw (concentrated) water at the starting of freezing, the salt mass change rate of the concentrate water, and the volume of ice crystals. A one-way FD test was carried out using the saltwater from South Xinjiang, and the exponential equation model and linear equation model of LCMat-LCMas were derived, and the simulation accuracy of LCMat-LCMas was verified by using the test data. The results show that the model has high prediction accuracy. The exponential equation model is suitable for predicting the ice TDS for ice with thickness within 15 cm, and the linear equation is suitable for predicting the ice crystal TDS for ice thicker than 15 cm. Further validation of the model accuracy is needed for larger cooled areas and icing thicknesses, and multidirectional icing processes.

BackgroundThe etiology of recurrent spontaneous abortion (RSA) remains elusive despite specific investigations affirming the association between RSA and thyroid autoimmunity (TAI). This study explores the immunological and metabolic profiles of RSA patients exhibiting positive thyroid antibodies and their connection with the rates of first-trimester miscarriage and live births. The aim is to provide further guidance for clinical interventions.MethodsA retrospective analysis included 478 women with RSA. Thyroid profile, thyroid peroxidase antibodies, and anti-thyroglobulin antibodies were measured in all participants. The clinical characteristics and pregnancy outcomes of RSA women were compared between thyroid autoimmunity (TAI)-positive and TAI-negative patients. Significant factors associated with adverse pregnancy outcomes and risk prediction models were explored in TAI-positive patients. Correlation analysis was used to identify specific metabolic or immune biomarkers associated with thyroid autoantibodies.ResultsThe prevalence of TAI was 18.6%. Compared with women without TAI, the thyroid-stimulating hormone (TSH) concentration of TAI-positive RSA was significantly higher (2.80 ± 2.98 vs 1.89 ± 1.17, p=0.006). After 28 weeks, the live birth rate of the TAI-positive group was lower than that of the TAI-negative group, with statistical significance (p

Automatic 2D vision-based defect detection on sealing nail (SealN) surfaces is challenging due to interference of complex backgrounds with non-homogeneous and low contrast between foreground and background. Inspired by an interesting observation that the albedo domain recovered by the uncalibrated photometric stereo (UPS) shows obvious differences and significant abruptness between defects’ and non-defects’ regions, we develop a novel semantic-guided variational model (SGVM) to conditional extract structural defects from albedo map. Specifically, SGVM utilizes one developed global regularized label indicator to semantically guide one local regularized relative Gaussian filter (RGF) for achieving large-scale structures (i.e., defects) preservation and small-scale textures (i.e., background) suppression. Furthermore, defects can be efficiently extracted by thresholding the structure map within the label indicator. Additionally, experimental results on numerous challenging defect images reveal that the proposed SGVM outperforms the existing advanced 2D methods in terms of defect extraction.

Abstract Ferredoxin (Fdx) is regarded as the main electron carrier in biological electron transfer and acts as an electron donor in metabolic pathways of many organisms. Here, we screened a self-sufficient P450-derived reductase PRF with promising production yield of 9OHAD (9α-hydroxy4-androstene-3,17-dione) from AD, and further proved the importance of [2Fe–2S] clusters of ferredoxin-oxidoreductase in transferring electrons in steroidal conversion. The results of truncated Fdx domain in all oxidoreductases and mutagenesis data elucidated the indispensable role of [2Fe–2S] clusters in the electron transfer process. By adding the independent plant-type Fdx to the reaction system, the AD (4-androstene-3,17-dione) conversion rate have been significantly improved. A novel efficient electron transfer pathway of PRF + Fdx + KshA (KshA, Rieske-type oxygenase of 3-ketosteroid-9-hydroxylase) in the reaction system rather than KshAB complex system was proposed based on analysis of protein–protein interactions and redox potential measurement. Adding free Fdx created a new conduit for electrons to travel from reductase to oxygenase. This electron transfer pathway provides new insight for the development of efficient exogenous Fdx as an electron carrier. Graphical Abstract

The reflection phenomenon exhibited by highly reflective surfaces considerably affects the quality of captured images, thereby rendering the task of structured light (SL) 3D reconstruction. In this paper, a polarized SL method is proposed to address the reconstruction issues on high-reflectance surfaces. The SL system we build in this paper involves a four-channel polarizing camera and a digital light processing (DLP) projector equipped with a polarizer in the lens. The built system enables the simultaneous acquisition of four groups of fringe images, each with different brightness differences. Then, a binary time-multiplexing SL method is adopted to obtain four distinct point clouds. Additionally, a fusion algorithm is proposed to merge the four point clouds into a single, precise, and complete point cloud. Several experiments have been conducted to demonstrate that the proposed method is capable of achieving excellent reconstruction outcomes on highly reflective surfaces.

Spatial structured light (SL) can achieve three-dimensional measurements with a single shot. As an important branch in the field of dynamic reconstruction, its accuracy, robustness, and density are of vital importance. Currently, there is a wide performance gap of spatial SL between dense reconstruction (but less accurate, e.g., speckle-based SL) and accurate reconstruction (but often sparser, e.g., shape-coded SL). The central problem lies in the coding strategy and the designed coding features. This paper aims to improve the density and quantity of reconstructed point clouds by spatial SL whilst also maintaining a high accuracy. Firstly, a new pseudo-2D pattern generation strategy was developed, which can improve the coding capacity of shape-coded SL greatly. Then, to extract the dense feature points robustly and accurately, an end-to-end corner detection method based on deep learning was developed. Finally, the pseudo-2D pattern was decoded with the aid of the epipolar constraint. Experimental results validated the effectiveness of the proposed system.

3D facial expression dataset plays an essential role in computer vision and computer graphics, especially to the data-driven machine learning algorithms like deep-learning etc. In contrast with traditional low-resolution and low-accuracy 3D face related datasets, an accurate and dense facial expression database was introduced in this paper. During the period from January to June 2019, we have collected 8,000 3D facial expression models and 32,000 texture images from 500 subjects. The 3D facial capture device works based on structured light principle. The procedure of 3D face capture and property of 3D samples are introduced in details. The proposed high-accuracy 3D face dataset can be used in many 3D applications, like recognition, animation, and 3D facial expression simulations.

3D vision technology has been gradually applied to intelligent terminals ever since Apple Inc. introduced structured light on iPhoneX. At present, time-of-flight (TOF) and laser speckle-based structured light (SL) are two mainstream technologies applied to intelligent terminals, both of which are widely regarded as efficient dynamic technologies, but with low accuracy. This paper explores a new approach to achieve accurate depth recovery by fusing TOF and our previous work—dot-coded SL (DCSL). TOF can obtain high-density depth information, but its results may be deformed due to multi-path interference (MPI) and reflectivity-related deviations. In contrast, DCSL can provide high-accuracy and noise-clean results, yet only a limited number of encoded points can be reconstructed. This inspired our idea to fuse them to obtain better results. In this method, the sparse result provided by DCSL can work as accurate “anchor points” to keep the correctness of the target scene’s structure, meanwhile, the dense result from TOF can guarantee full-range measurement. Experimental results show that by fusion, the MPI errors of TOF can be eliminated effectively. Dense and accurate results can be obtained successfully, which has great potential for application in the 3D vision task of intelligent terminals in the future.

A novel gill cell line from pearl gentian grouper (Epinephelus lanceolatus♂×Epinephelus fuscoguttatus♀, PGGG cell line) was established, its application in cadmium (Cd) toxicology was demonstrated in this study. Primary cultures and PGGG subcultures were carried out at 25 °C in Dulbecco’s Modified Eagle medium/F12 medium (1:1; pH 7.2) supplemented with 15% fetal bovine serum (FBS). Primary PGGG cells were spindle-shaped, proliferated into a confluent monolayer within two weeks and were continuously subcultured over passage 60. The growth of cells at passages 20, 40, and 60 was examined. Chromosome analysis revealed that the chromosomal number of normal PGGG cells was 48, but the number of cells with the normal chromosomes number decreased during the passaging process. Cadmium is one of the most toxic metals in aquatic systems and has been associated with multiple animal and human health problems. To interpret the cytotoxicity and related mechanisms of cadmium, PGGG cells were used as an in vitro model. After treatment with cadmium at concentrations ranging from 1 µM to 500 µM, PGGG cells demonstrated dose- and time-dependent cytotoxicity, manifested as morphological abnormalities and a viability decline. Further, it was found that the reactive oxygen species (ROS) and malondialdehyde (MDA) levels were elevated following cadmium exposure, and related genes involved in the antioxidant system, including those encoding catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), glutathione reductase (GR), and Kelch-like- ECH-associated protein 1 (Keap1), were regulated differently. In addition, PGGG cells treated with cadmium had the typical features associated with apoptosis, including phosphatidylserine (PS) externalization; upregulated expression of caspase-3, −8, and −9; and apoptotic body formation. In general, the PGGG cell line may serve as a useful tool for studying the toxic mechanisms of cadmium or other toxicants or for toxicity testing and environment monitoring.

Steroid hormones that serve as vital compounds are necessary for the development and metabolism of a variety of organisms. The neverland (NVD) family genes encode the conserved Rieske-type oxygenases, which are accountable for the dehydrogenation during the synthesis and regulation of steroid hormones. However, the His-tagged NVD protein from Caenorhabditis elegans expresses as inclusion bodies in Escherichia coli BL21 (DE3). This bottleneck can be solved through refolding by urea or the introduction of a maltose-binding protein (MBP) tag at the N-terminus. Through further research on purification after the introduction of a MBP tag at the N-terminus, the CD measurement and fluorescence-based thermal shift assay indicated that MBP was favorable for the NVD proteins’ solubility and stability, which may be beneficial for the large-scale manufacture of NVD protein for further research. The structural model contained the Rieske [2Fe–2S] domain and non-heme iron-binding motif, which were similar to 3-ketosteroid 9 α-hydroxylase.

The acquisition of the geometry of general scenes is related to the interplay of surface geometry, material properties and illumination characteristics. Surface texture and non-Lambertian reflectance properties degrade the reconstruction results by structured light technique. Existing structured light techniques focus on different coding strategy and light sources to improve reconstruction accuracy. The hybrid system consisting of a structured light technique and photometric stereo combines the depth value with normal information to refine the reconstruction results. In this paper, we propose a novel hybrid system consisting of stripe-based structured light and photometric stereo. The effect of surface texture and non-Lambertian reflection on stripe detection is first concluded. Contrary to existing fusion strategy, we propose an improved method for stripe detection to reduce the above factor’s effects on accuracy. The reconstruction problem for general scene comes down to using reflectance properties to improve the accuracy of stripe detection. Several objects, including checkerboard, metal-flat plane and free-form objects with complex reflectance properties, were reconstructed to validate our proposed method, which illustrates the effectiveness on improving the reconstruction accuracy of complex objects. The three-step phase-shifting algorithm was implemented and the reconstruction results were given and also compared with ours. In addition, our proposed framework provides a new feasible scheme for solving the ongoing problem of the reconstruction of complex objects with variant reflectance. The problem can be solved by subtracting the non-Lambertian components from the original grey values of stripe to improve the accuracy of stripe detection. In the future, based on stripe structured light technique, more general reflection models can be used to model different types of reflection properties of complex objects.

Structured light (SL) has a trade-off between acquisition time and spatial resolution. Temporally coded SL can produce a 3D reconstruction with high density, yet it is not applicable to dynamic reconstruction. On the contrary, spatially coded SL works with a single shot, but it can only achieve sparse reconstruction. This paper aims to achieve accurate 3D dense and dynamic reconstruction at the same time. A speckle-based SL sensor is presented, which consists of two cameras and a diffractive optical element (DOE) projector. The two cameras record images synchronously. First, a speckle pattern was elaborately designed and projected. Second, a high-accuracy calibration method was proposed to calibrate the system; meanwhile, the stereo images were accurately aligned by developing an optimized epipolar rectification algorithm. Then, an improved semi-global matching (SGM) algorithm was proposed to improve the correctness of the stereo matching, through which a high-quality depth map was achieved. Finally, dense point clouds could be recovered from the depth map. The DOE projector was designed with a size of 8 mm × 8 mm. The baseline between stereo cameras was controlled to be below 50 mm. Experimental results validated the effectiveness of the proposed algorithm. Compared with some other single-shot 3D systems, our system displayed a better performance. At close range, such as 0.4 m, our system could achieve submillimeter accuracy.

Sliding-window based multiclass hand posture detections are often performed by detecting postures of each predefined category using an independent detector, which makes it lack efficiency and results in high postures confusion rates in real-time applications. To tackle such problems, in this work, an efficient cascade detector that integrates multiple softmax-based binary (SftB) models and a softmax-based multiclass (SftM) model is investigated to perform multiclass posture detection in parallel. The SftB models are used to distinguish the predefined postures from the background regions, and the SftM model is applied to discriminate among all the predefined hand posture categories. Another usage of the cascade structure is that it could effectively decompose the complexity of background pattern space and therefore improve the detection accuracy. In addition, to balance the detection accuracy and efficiency, the HOG features of increasing resolutions will be adopted by classifiers of increasing stage-levels in the cascade structure. The experiments are implemented under various scenarios with complicated background and challenging lightings. Results show the superiority of the proposed SftB classifiers over the traditional binary classifiers such as logistic regression, as well as the accuracy and efficiency improvements brought by the softmax-based cascade architecture compared with the noncascade multiclass softmax detectors.