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Changqiang Chen,1,* Pu Li,1,* Jiuming Chen,1,* Chunxiao Liu,2 Xiaodan Wang,3 Jialin Cai,4 Enfei Xiang,4 Zhidong Gu,1,5 Peizhan Chen4 1Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Department of Pediatrics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 3Department of Neurology & Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 4Clinical Research Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 5Department of Laboratory Medicine, Ruijin-Hainan Hospital, Shanghai Jiao Tong University School of Medicine (Hainan Boao Research Hospital), Hainan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Peizhan Chen, Clinical Research Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201821, People’s Republic of China, Tel +86 13918550745, Email pzchen@me.com Zhidong Gu, Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201821, People’s Republic of China, Tel +86 13801653534, Email guzhidongruijin@163.comPurpose: Vitamin D, an essential nutrient and a pleiotropic steroid hormone, has been reported to be associated with the risk and severity in patients infected with Coronavirus Disease-2019 (COVID-19). The role of vitamin D in predicting clinical outcome for COVID-19 patients is unknown. Here, we aimed to determine the prognostic value of plasma 25(OH)D level in COVID-19 patients.Patients and Methods: A total of 158 patients infected with novel COVID-19 Omicron variants in Shanghai were recruited in this study and were categorized into three groups by the tertile levels of plasma 25(OH)D. Plasma 25(OH)D level was determined along with routine blood tests related to liver and renal functions in newly diagnosed COVID-19 patients at admission. The nucleic acid negative conversion time of throat swab samples was evaluated as the primary clinical outcome. The prognostic value of clinical characteristics and plasma 25(OH)D level was assessed using the Kaplan–Meier plot and Cox proportional hazards regression tests.Results: Higher level of plasma 25(OH)D level in COVID-19 patients was independently associated with shorter nucleic acid negative conversion time from COVID-19 infection (multivariate adjusted HR: 0.54, 95%CI: 0.35– 0.82, P=0.004, tertile 2 vs 1; multivariate adjusted HR: 0.60, 95%CI: 0.39– 0.90, P=0.014, tertile 3 vs 1).Conclusion: Plasma 25(OH)D level may serve as an independent prognostic factor in COVID-19 patient. Our findings indicate the protective roles of vitamin D supplementation in the regiment of patients with COVID-19.Keywords: SARS-CoV-2, COVID-19, plasma 25(OH)D level, nucleic acid negative conversion time

This study was designed to prepare a cattle bone-derived collagen peptide-calcium chelate by the ultrasound method (CP-Ca-US), and its structure, stability, and bioactivity on MC3T3-E1 cells were characterized. Single-factor experiments optimized the preparation conditions: ultrasound power 90 W, ultrasound time 40 min, CaCl2/peptides ratio 1/2, pH 7. Under these conditions, the calcium-chelating ability reached 39.48 μg mg−1. The result of Fourier transform-infrared spectroscopy indicated that carboxyl oxygen and amino nitrogen atoms were chelation sites. Morphological analysis indicated that CP-Ca-US was characterized by a porous surface and large particles. Stability analysis demonstrated that CP-Ca-US was stable in the thermal environment and under intestinal digestion. CP-Ca-US showed more stability in gastric juice than the chelate prepared by the hydrothermal method. Cell experiments indicated that CP-Ca-US increased osteoblast proliferation (proliferation rate 153% at a concentration of 300 μg mL−1) and altered the cell cycle. Significantly, CP-Ca-US enhanced calcium absorption by interacting with calcium-sensing receptors and promoted the mineralization of MC3T3-E1 cells. This study provides the scientific basis for applying the ultrasound method to prepare peptide-calcium chelates and clarifies the positive role of chelates in bone building.

As a special deep learning algorithm, the multilayer extreme learning machine (ML-ELM) has been extensively studied to solve practical problems in recent years. The ML-ELM is constructed from the extreme learning machine autoencoder (ELM-AE), and its generalization performance is affected by the representation learning of the ELM-AE. However, given label information, the unsupervised learning of the ELM-AE is difficult to build the discriminative feature space for classification tasks. To address this problem, a novel Fisher extreme learning machine autoencoder (FELM-AE) is proposed and is used as the component for the multilayer Fisher extreme leaning machine (ML-FELM). The FELM-AE introduces the Fisher criterion into the ELM-AE by adding the Fisher regularization term to the objective function, aiming to maximize the between-class distance and minimize the within-class distance of abstract feature. Different from the ELM-AE, the FELM-AE requires class labels to calculate the Fisher regularization loss, so that the learned abstract feature contains sufficient category information to complete classification tasks. The ML-FELM stacks the FELM-AE to extract feature and adopts the extreme leaning machine (ELM) to classify samples. Experiments on benchmark datasets show that the abstract feature extracted by the FELM-AE is more discriminative than the ELM-AE, and the classification results of the ML-FELM are more competitive and robust in comparison with the ELM, one-dimensional convolutional neural network (1D-CNN), ML-ELM, denoising multilayer extreme learning machine (D-ML-ELM), multilayer generalized extreme learning machine (ML-GELM), and hierarchical extreme learning machine with L21‑norm loss and regularization (H-LR21-ELM).

There is a class-imbalance problem that the number of minority class samples is significantly lower than that of majority class samples in common network traffic datasets. Class-imbalance phenomenon will affect the performance of the classifier and reduce the robustness of the classifier to detect unknown anomaly detection. And the distribution of the continuous features in the dataset does not follow the Gaussian distribution, which will bring great difficulties to intrusion detection. We propose Conditional Wasserstein Variational Autoencoders with Generative Adversarial Network (CWVAEGAN) to solve the class-imbalance phenomenon, CWVAEGAN transform the original dataset through data preprocessing, and then use the improved VAEGAN to generate minority class samples. According to the CWVAEGAN model, an intrusion detection system based on CWVAEGAN and One-dimensional convolutional neural networks (1DCNN), namely CWVAEGAN-1DCNN, is established. By using the examples generated by CWVAEGAN, the problem of intrusion detection on class unbalanced data is solved. Specifically, CWVAEGAN-1DCNN consists of three modules: data preprocessing module, CWVAEGAN, and deep neural network. We evaluate the performance of CWVAEGAN-1DCNN on two benchmark datasets and compared it with the other 16 methods. Experiment results suggest that the performance of CWVAEGAN-1DCNN is better than class-balancing methods, and other advanced methods.

Structural degradation and surface chemical instability are dominant issues of Ni-rich layered cathodes, which trigger capacity fading and safety concerns, hindering the extensive application of Ni-rich cathodes toward high-energy, long-life lithium-ion batteries. Here, by combining trace Ta doping and an ultrathin Zr-Y mixed oxide coating, an integrated modification strategy significantly improves the cycling and thermal stability of Ni-rich LiNi

Purpose To cope with climate change and achieve the dual carbon goal, China has actively promoted the implementation of carbon trading pilot policy, among which the power industry plays an important role in China’s carbon emission reduction work. The purpose of this paper is to study the influence of carbon trading policy on the energy efficiency of power industry and achieve the comprehensive goal of carbon emission reduction, carbon peak and carbon neutralization. Design/methodology/approach This paper constructs the difference-in-differences model based on 2012–2019 provincial data to study the impact of carbon trading policy on energy efficiency in the power industry and its effect path. Heterogeneity analysis was conducted to compare the effects of carbon trading policy in eastern, central and western regions as well as at different levels of power structures. Findings Carbon trading policy can significantly improve the energy efficiency of the power industry, and the policy effect is more significant in eastern and western regions and areas with high power structure. Mechanism analysis shows that carbon trading policy mainly influences the energy efficiency of power industry by environmental protection investment, power consumption demand and industrial structure. Originality/value This paper uses provincial panel data to deeply study the influence of carbon trading policy on energy efficiency of the power industry and its effect path. By constructing the difference-in-differences model, this paper empirically analyzes the governance effect of carbon trading policy. Meanwhile, it controls individual and time effects to solve the endogeneity problem prevalent in previous literature.

Background: CD82/KAI-1 which is a member of the tetraspanin superfamily, has been proposed to exert its activity via the Tetraspanin Web. However, the mechanism of CD82 palmitoylation in this web has not been fully elucidated. The purpose of this study is to investigate cell migration and apoptosis by mutation of tetraspanin CD82 palmitoylation. Methods: This study elucidated the impact of various palmitoylation site mutations on apoptosis in breast cancer cells through a comprehensive approach involving RT-PCR, Western blotting, TUNEL assay, immunofluorescence, and tumor formation assay in athymic nude mice model. Results: We found that the mutation of CD82 palmitoylation at cys74 and cys83 or cys5 and cys74 and cys83 simultaneously increased apoptosis in breast cancer. However, the other forms of mutation of CD82 palmitoylation showed no effects on apoptosis. Conclusion: The study strongly implicate that CD82 palmitoylation at cys74 and cys83 are both closely related to maintain biological function.

More than 170 years after causing the potato famine in Ireland, late blight is still considered one of the most devastating crop diseases. Commercial potato breeding efforts depend on natural sources of resistance to protect crops from the rapidly evolving late blight pathogen,Phytophthora infestans. We have identified and mapped a novel broad-spectrum disease resistance gene effective againstP. infestansfrom the wild, diploid potato speciesSolanum bulbocastanum. Diagnostic resistance gene enrichment sequencing (dRenSeq) was used to confirm the uniqueness of the identified resistance. RenSeq and GenSeq-based mapping of the resistance, referred to asRpi-blb4, alongside recombinant screening, positioned the locus responsible for the resistance to potato Chromosome 5. The interval spans approximately 2.3 MB and corresponds to the DM reference genome positions of 11.25 and 13.56 Mb.

This research evaluated the protective effect of vitamin A (VA) on the adverse effect of fish oil (FO) substitution with palm oil (PO) in an economical crab Eriocheir sinensis. Three diets of FO, PO, and PO + 8000 IU / kg VA as the main lipid sources were fed to crabs, respectively, for 8 weeks. Compared to crabs fed FO diet, crabs fed PO diet showed reduced hemolymph VA concentration, feed utilization efficiency, and growth performance. Besides, crabs fed PO diet showed elevated lipid content in hepatopancreas and body and triglyceride content in hepatopancreas, leading to decreased antioxidant enzyme and immune parameters activities from biochemical analysis, enzymatic determination, and quantitative polymerase chain reaction. In contrast, compared to crabs fed PO only, VA supplementation in PO improved the growth performance and utilization of fatty acids and reduced lipid deposition in the hepatopancreas. In addition, VA supplementation suppressed gene expression related to triglyceride synthesis (dgat1) and positively affected gene expression related to lipid catabolism (cpt1a, cpt1b, cpt2, and caat). Furthermore, VA supplementation upregulated antioxidant genes (CuZnSOD and CAT) through downregulating gene expression of upstream regulator Keap1. Furthermore, VA supplementation upregulated immune genes (Lzm and proPO) expression and reduced proinflammatory genes (LITAF, ADAM17, and IL-16) expression related to Toll2/MyD88/Relish signaling pathway. This study shows the necessity of VA addition in the feed with FO totally replaced by PO because it can relieve PO’s adverse effects and improve the growth of crabs.

Long-flame coal is a bituminous coal with the lowest metamorphic degree, accounting for 16.1% of China's coal reserves. With increases in mining depths and intensities, mine gas disasters related to the mining of long-flame coal are becoming increasingly serious. Therefore, the exploration of the effect of moisture on the adsorption of methane in coal can provide support for popularizing the application of hydraulic measures in long-flame coal mining areas. In this paper, a molecular structure model of long-flame coal was established by molecular dynamics and the Monte Carlo method. The adsorption characteristics of methane in long-flame coal structures under different pressures were simulated, and the effects of different amounts of water on the methane adsorption and adsorption heat were explored. The results show that, under the same adsorption equilibrium pressure, the methane adsorption rate decreases with increasing water content, and with increasing adsorption equilibrium pressure, the adsorption capacity of methane increases gradually; this increasing trend is in agreement with the Langmuir equation. The water adsorption of coal is greater than the methane adsorption of coal. With the increase in the number of water molecules, when coal-based molecules adsorb methane and then adsorb water molecules, the adsorption heat of methane is reduced, and the desorption of methane molecules is promoted.

The preparation of two-dimensional magnetic materials is a key process to their applications and the study of their structure and morphology plays an important role in the growth of high-quality thin films. Here, the growth, structure, and morphology of Cr1+δTe2 films grown by molecular beam epitaxy on mica with variations of Te/Cr flux ratio, growth temperature, and film thickness have been systematically investigated by scanning tunneling microscopy, reflection high-energy electron diffraction, scanning electron microscope, and X-ray photoelectron spectroscopy. We find that a structural change from multiple phases to a single phase occurs with the increase in growth temperature, irrespective of the Cr/Te flux ratios, which is attributed to the desorption difference of Te atoms at different temperatures, and that the surface morphology of the films grown at relatively high growth temperatures (≥ 300 °C) exhibits a quasi-hexagonal mesh-like structure, which consists of nano-islands with bending surface induced by the screw dislocations, as well as that the films would undergo a growth-mode change from 2D at the initial stage in a small film thickness (2 nm) to 3D at the later stage in thick thicknesses (12 nm and 24 nm). This work provides a general model for the study of pseudo-layered materials grown on flexible layered substrates.

Preparation of atomic reconstructions and tracking its dynamic-evolutionary pathways for some polar surfaces of ionic crystals are essential in surface science but remain a formidable challenge. Mainly by scanning tunneling microscopy, we investigate various reconstructions as well as their dynamic-evolutionary pathways on ZnO(0001) surface as a prototypical ionic crystal, which have been successfully prepared by introducing Ga surface segregation. We observe three complex pathways from an initial disorder to finally well-ordered surface with (2×8) reconstruction undergoing complicated atom desorption, missing and moving dynamic processes, one of which is “disorder → [disorder + (√3 × √3)R30°] → [(2 × 2)] → zigzag arrangement → [(2 × 8)]”. The atomic reconstructions are proposed to originate from the modification of empty states of dangling bonds of the surface by surface segregation. Our findings provide a general model for preparing plentifully atomic reconstructions and revealing dynamic-evolutionary pathways on complex polar surfaces of ionic crystals.

Deoxynivalenol (DON) is a mycotoxin that commonly contaminates cereals worldwide. Dietary exposure to DON is a subject of great public health concern, but studies on the health effects of chronic exposure to DON are not available. In this study, we investigated the connection between DNA methylation levels and DON exposure in children. The DNA methylation status of white blood cells from 32 children aged 2~15 years old in Henan, China, was profiled. A total of 378 differentially methylated CpGs were identified between the high and low DON exposure groups, and 8 KEGG pathways were found to be significantly enriched among the differentially methylated genes. In addition, the quantitative methylation of EIF2AK4, EMID2 and GNASAS was analysed using the Sequenom MassARRAY platform. The results showed that the methylation level of EIF2AK4 was significantly different between the two groups, and the methylation levels were associated with exposure to DON. Conclusively, our study found that chronic exposure to DON during childhood could affect DNA methylation levels.

Objective. Repair of cartilage defects, a common condition resulting from many factors, is still a great challenge. Based on their chondrogenic differentiation ability, mesenchymal stem cell- (MSC-) based cartilage regeneration is a promising approach for cartilage defect repair. However, MSC differentiation into chondroblasts or related cell lineages is elaborately controlled by stem cell differentiation stage factors and affected by an array of bioactive elements, which may impede the efficient production of target cells. Thus, identifying a single transcription factor to promote chondrogenic differentiation is critical. Herein, we explored the mechanism by which scrapie-responsive gene 1 (SCRG1), a candidate gene for cartilage regeneration promotion, regulates chondrogenic differentiation of MSCs. Methods. Expression of SCRG1 was detected in umbilical cord-derived MSCs (UCMSCs) by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunohistochemical analysis during chondrogenic differentiation. The function of SCRG1 in chondrogenic potential was evaluated after gene knockdown or overexpression by lentiviral vectors. Finally, a rabbit cartilage defect model was established to evaluate the effect of SCRG1 on cartilage repair in vivo. Results. Expression of SCRG1 was upregulated during in vitro chondrogenic differentiation of UCMSCs. SCRG1 knockdown inhibited chondrogenic differentiation of UCMSCs, while SCRG1 overexpression promoted chondrogenic differentiation of UCMSCs in vitro. In addition, UCMSC overexpressing SCRG1 promoted cartilage repair in vivo. Mechanistically, SCRG1 promoted chondrogenic differentiation via upregulation of Wnt5a expression and subsequent inhibition of β-catenin. Conclusion. Our results showed that SCRG1 promotes chondrogenic differentiation of UCMSCs by inhibiting canonical Wnt/β-catenin signaling through Wnt5a. Our findings provide a future target for chondrogenic differentiation and cartilage regeneration.

Antimicrobial peptides (AMPs) are attractive antimicrobial agents used to combat bacterial infections, and have been advanced to be one of the most promising alternatives to conventional antibiotics. They stand out for their attractive broad-spectrum activity, unmatched antibacterial mechanism that is not prone to develop drug resistance and diversified topologies, which can be fabricated with manifold amino acid blocks. In this study, using

Attention mechanisms have recently shown strong potential in improving the performance of convolutional neural networks (CNNs). This letter proposes a fully convolutional attention block (FCAB) that can be combined with a CNN to refine important features and suppress unnecessary ones in synthetic aperture radar (SAR) images. The FCAB consists of a channel attention module and a spatial attention module. For the channel attention module, we use average-pooling and max-pooling to learn complementary features, and apply group convolution to aggregate the information of the two types of channels. Global average-pooling is then used to encode the channel-wise importance. For the spatial attention module, the average-pooling and max-pooling along the channel axis are used to generate two spatial feature maps, and then two very lightweight convolutional layers are used to encode the spatial weight map. Experimental results on SAR images demonstrate that our FCAB can focus on important channels and object regions. It uses relatively few parameters and is computationally efficient, while bringing about significant performance gain for SAR recognition.

Common scab (CS) caused by Streptomyces spp. is a significant soilborne potato disease that results in tremendous economic losses globally. Identification of CS-associated species of the genus Streptomyces can enhance understanding of the genetic variation of these bacterial species and is necessary for the control of this epidemic disease. The present study isolated Streptomyces strain 6-2-1(1) from scabby potatoes in Keshan County, Heilongjiang Province, China. PCR analysis confirmed that the strain harbored the characteristic Streptomyces pathogenicity island (PAI) genes (txtA, txtAB, nec1, and tomA). Pathogenicity assays proved that the strain caused typical scab lesions on potato tuber surfaces and necrosis on radish seedlings and potato slices. Subsequently, the strain was systemically characterized at morphological, physiological, biochemical, and phylogenetic levels. Phylogenetic analysis based on 16S rRNA gene sequences revealed that strain 6-2-1(1) shared 99.86% sequence similarity with Streptomyces rhizophilus JR-41T, isolated initially from bamboo in rhizospheric soil in Korea. PCR amplification followed by Sanger sequencing of the 16S rRNA gene of 164 scabby potato samples collected in Heilongjiang Province from 2019 to 2020 demonstrated that approximately 2% of the tested samples were infected with S. rhizophilus. Taken together, these results demonstrate that S. rhizophilus is capable of causing potato CS disease and may pose a potential challenge to potato production in Heilongjiang Province of China.

Background and Aims: Livestock excreta (dung and urine) is one of the significant sources of soil nitrogen (N) and phosphorus (P) nutrients in grazed grasslands, and freezing-thawing cycle (FTC) during non-growing season are considered to complicatedly affect soil N and P dynamics by changing excreta nutrients release, soil physicochemical, and microbial properties. However, the combined effects and functional mechanisms of FTCs and excreta deposition on the availability, transformation, and migration processes of soil N and P nutrients in alpine grasslands need further clarifications. Methods: A 277-day experiment was conducted to investigate the response of dung N and P nutrients release, soil available N and P dynamics, and N transformation process to FTCs at different freezing-thawing periods, including treatments of control (CK), soils respectively treated with yak dung (YD), Tibetan sheep dung (TSD), yak urine (YU), and Tibetan sheep urine (TSU) in an alpine steppe of northern Tibetan Plateau. Results: Enhanced mineralization during the stable freezing period significantly (P < 0.05) increased alpine steppe soil ammonium-N (NH4+-N) and available P (AP) concentrations at 0–5 cm depth. The significant (P < 0.05) increase in soil nitrate-N (NO3--N) concentration at 0−5 and 5−10 cm depths during the thawing period was a response to the improvement in nitrification. The YU and TSU deposition respectively resulted in the 0−5 cm soil NH4+-N concentration reached 127 and 89.4 mg/kg and the corresponding NO3--N concentration reached 90.5 and 29.6 mg/kg, with these peaked values occurred during freezing period significantly (P < 0.05) greater than other freezing–thawing periods. Interactions between excreta treatment and freezing–thawing periods significantly (P < 0.001) affected soil NH4+-N and NO3--N concentrations, and soil AP variation was strongly (P < 0.001) correlated with freezing–thawing periods. Trade-off between NH4+-N and NO3--N was closely related to the influence of nitrification and denitrification, which were affected by frequent FTCs during the winter freezing and spring thawing. Conclusion: Increases in mineral N and AP concentrations during the spring thawing period likely altered the phenological properties of vegetation and the productivity of grassland ecosystems to varying degrees. Our study would provide scientific guidance for optimizing the management mode of livestock excreta during freezing–thawing periods and promoting the sustainable development of alpine grassland ecosystems.