Abstract
SARS-CoV-2 vaccination has been launched worldwide to build effective population-level immunity to curb the spread of this virus. The effectiveness and duration of protective immunity is a ...critical factor for public health. Here, we report the kinetics of the SARS-CoV-2 specific immune response in 204 individuals up to 1-year after recovery from COVID-19. RBD-IgG and full-length spike-IgG concentrations and serum neutralizing capacity decreases during the first 6-months, but is maintained stably up to 1-year after hospital discharge. Even individuals who had generated high IgG levels during early convalescent stages had IgG levels that had decreased to a similar level one year later. Notably, the RBD-IgG level positively correlates with serum neutralizing capacity, suggesting the representative role of RBD-IgG in predicting serum protection. Moreover, viral-specific cellular immune protection, including spike and nucleoprotein specific, persisted between 6 months and 12 months. Altogether, our study supports the persistence of viral-specific protective immunity over 1 year.
Photocatalytic green hydrogen (H
) production through water electrolysis is deemed as green, efficient, and renewable fuel or energy carrier due to its great energy density and zero greenhouse ...emissions. However, developing efficient and low-cost noble-metal-free photocatalysts remains one of the daunting challenges in low-cost H
production. Porous graphitic carbon nitride (gCN) nanostructures have drawn broad multidisciplinary attention as metal-free photocatalysts in the arena of H
production and other environmental remediation. This is due to their impressive catalytic/photocatalytic properties (i.e., high surface area, narrow bandgap, and visible light absorption), unique physicochemical durability, tunable electronic properties, and feasibility to synthesize in high yield from inexpensive and earth-abundant resources. The physicochemical and photocatalytic properties of porous gCNs can be easily optimized via the integration of earth-abundant heteroatoms. Although there are various reviews on porous gCN-based photocatalysts for various applications, to the best of our knowledge, there are no reviews on heteroatom-doped porous gCN nanostructures for the photocatalytic H
evolution reaction (HER). It is essential to provide timely updates in this research area to highlight the research related to fabrication of novel gCNs for large-scale applications and address the current barriers in this field. This review emphasizes a panorama of recent advances in the rational design of heteroatom (i.e., P, O, S, N, and B)-doped porous gCN nanostructures including mono, binary, and ternary dopants for photocatalytic HERs and their optimized parameters. This is in addition to H
energy storage, non-metal configuration, HER fundamental, mechanism, and calculations. This review is expected to inspire a new research entryway to the fabrication of porous gCN-based photocatalysts with ameliorated activity and durability for practical H
production.
With success of convolutional neural networks (CNNs) in computer vision, the CNN has attracted great attention in hyperspectral classification. Many deep learning-based algorithms have been focused ...on deep feature extraction for classification improvement. In this letter, a novel deep learning framework for hyperspectral classification based on a fully CNN is proposed. Through convolution, deconvolution, and pooling layers, the deep features of hyperspectral data are enhanced. After feature enhancement, the optimized extreme learning machine (ELM) is utilized for classification. The proposed framework outperforms the existing CNN and other traditional classification algorithms by including deconvolution layers and an optimized ELM. Experimental results demonstrate that it can achieve outstanding hyperspectral classification performance.
With success of Deep Belief Networks (DBNs) in computer vision, DBN has attracted great attention in hyperspectral classification. Many deep learning based algorithms have been focused on deep ...feature extraction for classification improvement. Multi-features, such as texture feature, are widely utilized in classification process to enhance classification accuracy greatly. In this paper, a novel hyperspectral classification framework based on an optimal DBN and a novel texture feature enhancement (TFE) is proposed. Through band grouping, sample band selection and guided filtering, the texture features of hyperspectral data are improved. After TFE, the optimal DBN is employed on the hyperspectral reconstructed data for feature extraction and classification. Experimental results demonstrate that the proposed classification framework outperforms some state-of-the-art classification algorithms, and it can achieve outstanding hyperspectral classification performance. Furthermore, our proposed TFE method can play a significant role in improving classification accuracy.
Long-span bridges are susceptible to damage, aging, and deformation in harsh environments for a long time. Therefore, structural health monitoring (SHM) systems need to be used for reasonable ...monitoring and maintenance. Among various indicators, bridge displacement is a crucial parameter reflecting the bridge's health condition. Due to the simultaneous bearing of multiple environmental loads on suspension bridges, determining the impact of different loads on displacement is beneficial for the better understanding of the health conditions of the bridges. Considering the fact that extreme gradient boosting (XGBoost) has higher prediction performance and robustness, the authors of this paper have developed a data-driven approach based on the XGBoost model to quantify the impact between different environmental loads and the displacement of a suspension bridge. Simultaneously, this study combined wavelet threshold (WT) denoising and the variational mode decomposition (VMD) method to conduct a modal decomposition of three-dimensional (3D) displacement, further investigating the interrelationships between different loads and bridge displacements. This model links wind speed, temperature, air pressure, and humidity with the 3D displacement response of the span using the bridge monitoring data provided by the GNSS and Earth Observation for Structural Health Monitoring (GeoSHM) system of the Forth Road Bridge (FRB) in the United Kingdom (UK), thus eliminating the temperature time-lag effect on displacement data. The effects of the different loads on the displacement are quantified individually with partial dependence plots (PDPs). Employing testing, it was found that the XGBoost model has a high predictive effect on the target variable of displacement. The analysis of quantification and correlation reveals that lateral displacement is primarily affected by same-direction wind, showing a clear positive correlation, and vertical displacement is mainly influenced by temperature and exhibits a negative correlation. Longitudinal displacement is jointly influenced by various environmental loads, showing a positive correlation with atmospheric pressure, temperature, and vertical wind and a negative correlation with longitudinal wind, lateral wind, and humidity. The results can guide bridge structural health monitoring in extreme weather to avoid accidents.
Bone tissue engineering (BTE) has received significant attention due to its enormous potential in treating critical‐sized bone defects and related diseases. Traditional materials such as metals, ...ceramics, and polymers have been widely applied as BTE scaffolds; however, their clinical applications have been rather limited due to various considerations. Recently, carbon‐based nanomaterials attract significant interests for their applications as BTE scaffolds due to their superior properties, including excellent mechanical strength, large surface area, tunable surface functionalities, high biocompatibility as well as abundant and inexpensive nature. In this article, recent studies and advancements on the use of carbon‐based nanomaterials with different dimensions such as graphene and its derivatives, carbon nanotubes, and carbon dots, for BTE are reviewed. Current challenges of carbon‐based nanomaterials for BTE and future trends in BTE scaffolds development are also highlighted and discussed.
Carbon‐based nanomaterials demonstrate enormous potential in bone tissue engineering (BTE) to treat critical‐sized bone defects due to their superior properties. Recent advancements of different dimensional carbon‐based nanomaterials (i.e., graphene oxide, carbon nanotubes, and carbon dots) in BTE are presented. Current challenges of BTE applications with carbon‐based nanomaterials and future trends of BTE are also highlighted and discussed.
Ferroptosis is an iron-dependent, non-apoptotic mode of cell death characterized by excessive accumulation of reactive oxygen species (ROS). It plays an important role in the occurrence, development ...and treatment of various cancers, but little is known regarding the role of ferroptosis in hematologic malignancies. This review elaborates the regulatory mechanism of ferroptosis and the treatment opportunities for targeting ferroptosis in hematologic malignancies.
A systematic literature review through PubMed was conducted to summarize the published evidence on the therapeutic potential of targeting ferroptosis in hematological malignant tumors. Literature sources published in English were searched, using the terms ferroptosis, leukemia, myelodysplastic syndrome, lymphoma and multiple myeloma.
More and more small molecules have been found to induce ferroptosis in hematologic malignancies through targeted iron metabolism and lipid peroxidation, and some ferroptosis inducers have been proved to have synergistic effect with other chemotherapeutic drugs.
This paper discusses the significance of ferroptosis in hematologic malignancies and provides a new way for the treatment of hematologic malignancies, and more experimental studies should be conducted in future.
Molecular-glue degraders mediate interactions between target proteins and components of the ubiquitin-proteasome system to cause selective protein degradation. Here, we report a new molecular glue ...HQ461 discovered by high-throughput screening. Using loss-of-function and gain-of-function genetic screening in human cancer cells followed by biochemical reconstitution, we show that HQ461 acts by promoting an interaction between CDK12 and DDB1-CUL4-RBX1 E3 ubiquitin ligase, leading to polyubiquitination and degradation of CDK12-interacting protein Cyclin K (CCNK). Degradation of CCNK mediated by HQ461 compromised CDK12 function, leading to reduced phosphorylation of a CDK12 substrate, downregulation of DNA damage response genes, and cell death. Structure-activity relationship analysis of HQ461 revealed the importance of a 5-methylthiazol-2-amine pharmacophore and resulted in an HQ461 derivate with improved potency. Our studies reveal a new molecular glue that recruits its target protein directly to DDB1 to bypass the requirement of a substrate-specific receptor, presenting a new strategy for targeted protein degradation.
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•Tri-chamber nanofibers in the form of core–shell microstructure embedded on one side of the Janus main structure were designed.•Hydrophilic and pH sensitive polymers were combined ...skillfully in complicated structure nanocomposites.•The tri-chamber nanofibers facilitated the rapid release of quercetin and the delayed and sustained release of tamoxifen citrate.•The tri-chamber nanofibers could result in a synergistic anticancer action of quercetin and tamoxifen citrate.
A tri-fluid electrospinning process was successfully developed to prepare tri-chamber complex nanofibers. The core–shell and Janus structure were combined to form a delicate and complicated architecture for solving the problem of co-administration of quercetin and tamoxifen citrate, improving the oral bioavailability, and enhancing their synergistic anti-breast cancer actions. Scanning electron microscope, transmission electron microscope and confocal fluorescent microscopy images showed the complex structure of the designed nanofibers. Fourier transform infrared and X-ray diffraction analyses verified that the model drugs and the polymeric excipients had good compatibility and were presented in an amorphous state. The in vitro release study certified that the tri-chamber nanofibers facilitated the rapid release of quercetin compared with that of the crude drug (90% versus 38%) and the delayed and sustained release of tamoxifen citrate at the same time interval (decreased by 1.88 times). The in vivo pharmacokinetic and pharmacodynamic analysis verified that the tri-chamber nanofibers could result in increased oral bioavailability and enhanced synergistic anticancer action of quercetin and tamoxifen citrate. The findings proved that a new medicated drug delivery system with advanced dual-, time-, and target-specific drug release profiles was developed using the electrospun complex nanostructure.
The district heating system accounts for 40% energy consumption of the building sector in China and still has tremendous growth potential due to the urbanisation. However, few studies have conducted ...explicit quantification on the drivers and the sustainable development of the district heating energy consumption of the building sector (DHEB) in China, although previous aggregation analysis on whole building energy service could convey implications on the district heating systems. This study investigates the driving factors of the DHEB in China between 2004 and 2016 using a decomposition analysis that incorporates effects of energy mix, heat production technology structure, energy intensity, heating area, and population. The decoupling status between the DHEB and gross domestic product (GDP) in China is then analyzed based on the Tapio decoupling index, along with the contributions of each driving factor to the decoupling. The results show that the effects of district heating area and population dominate the increase in the DHEB, while the heating energy intensity is the strongest factor reducing the DHEB. In addition, the shares of coal and heating boilers positively contribute to the increase in 2004–2008, and have a negative effect in 2008–2016. The complete reverse trend is found in the shares of gas and combined heat and power (CHP) during the same period. These results are largely associated with the implementation of “coal to gas” and the “elimination of old boilers” pushed by the Chinese government. Furthermore, a weak decoupling effect is mainly found between China’s DHEB and GDP from 2004 to 2016. The heating energy intensity is the strongest factor promoting the decoupling, while the growth of the district heating area and population leads to a weak decoupling.
•Decomposition and decoupling analysis focus on China’s district heating system.•Effects of heat production technology and energy mix were investigated.•Acceleration of energy saving from the effects of the shares of coal and boilers after 2008.•The heating energy intensity is the strongest factor promoting the decoupling.
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