From the beginning of 2002 and 2012, severe respiratory syndrome coronavirus (SARS‐CoV) and Middle East respiratory syndrome coronavirus (MERS‐CoV) crossed the species barriers to infect humans, ...causing thousands of infections and hundreds of deaths, respectively. Currently, a novel coronavirus (SARS‐CoV‐2), which has become the cause of the outbreak of Coronavirus Disease 2019 (COVID‐19), was discovered. Until 18 February 2020, there were 72 533 confirmed COVID‐19 cases (including 10 644 severe cases) and 1872 deaths in China. SARS‐CoV‐2 is spreading among the public and causing substantial burden due to its human‐to‐human transmission. However, the intermediate host of SARS‐CoV‐2 is still unclear. Finding the possible intermediate host of SARS‐CoV‐2 is imperative to prevent further spread of the epidemic. In this study, we used systematic comparison and analysis to predict the interaction between the receptor‐binding domain (RBD) of coronavirus spike protein and the host receptor, angiotensin‐converting enzyme 2 (ACE2). The interaction between the key amino acids of S protein RBD and ACE2 indicated that, other than pangolins and snakes, as previously suggested, turtles (Chrysemys picta bellii, Chelonia mydas, and Pelodiscus sinensis) may act as the potential intermediate hosts transmitting SARS‐CoV‐2 to humans.
Highlights
The critical residues of S protein RBD binding with ACE2 indicated the potential intermediate hosts transmitting SARS‐CoV‐2 to humans.
Complicated weather conditions lead to intermittent, random and volatility in photovoltaic (PV) systems, which makes PV predictions difficult. A recurrent neural network (RNN) is considered to be an ...effective tool for time-series data prediction. However, when the weather changes intensely, the long-term sequence of multivariate may cause gradient vanishing (exploding) during the training of RNN, leading the prediction results to local optimum. Long short-term memory (LSTM) network is the deep structure of RNN. Due to its special hidden layer unit structure, it can preserve the trend information contained in the long-term sequence, which is allowed to solve the problems of RNN and improve performance. An LSTM-based approach is applied for short-term predictions in this study based on a timescale that encompasses global horizontal irradiance (GHI) one hour in advance and one day in advance. Inaccurate forecasts usually occur on cloudy days, and the results of ANN and SVR in the literature prove this. To improve prediction accuracy on cloudy days, the clearness-index was introduced as an input data for the LSTM model and to classify the type of weather by k-means during the data processing, where cloudy days are classified as the cloudy and the mixed(partially cloudy). NN models are established to compare the accuracy of different approaches and the cross-regional study is to prove whether the method can be generalizable. From the results of hourly forecast, the R 2 coefficient of LSTM on cloudy days and mixed days is exceeding 0.9, while the R 2 of RNN is only 0.70 and 0.79 in Atlanta and Hawaii. From the results of daily forecast, All R 2 on cloudy days is about 0.85. However, the LSTM is still very effective in improving of RNN and more accurate than other models.
Bladder cancer (BC) is a common urological malignancy that still lacks effective treatments. Abietic acid (AA) is an abietane diterpene that possesses various biological activities, including ...antitumor activity. This study aimed at evaluating the effects of AA on BC cells.
The 3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) assay was used to assess the effects of AA on the viability of BC cells. Annexin-V and FITC staining was used to assess cellular death. The type of cell death was determined by the administration of various specific cell death inhibitors. Commercial kits were used to measure the levels of reactive oxygen species (ROS), intracellular iron, malondialdehyde (MDA), and glutathione (GSH). Real-time polymerase chain reaction (RT-PCR) and western blot analysis were used to assay mRNA and protein levels, respectively. The role of glutathione peroxidase 4 (GPX4) in the antitumor effects of AA was evaluated using the forced expression of GPX4 in BC cells. The impact of HO-1 on the antitumor effects of AA was examined by gene silencing and pharmacological inhibition of the protein. Finally, the antitumor effects of AA were evaluated in xenograft models.
AA selectively inhibited the viability of BC cells but not normal cells. AA-induced ferroptosis in BC cells was evidenced by the upregulation of ROS, intracellular iron, and MDA. AA treatment led to the downregulation of GPX4 and the upregulation of HO-1 in BC cells. Forced expression of GPX4 or inhibition of HO-1 resulted in decreased ferroptosis triggered by AA in BC cells. AA also showed synergistic effects with various chemotherapeutic agents against BC and inhibited the growth of BC cells in vivo.
This study revealed AA-induced ferroptosis in BC cells both in vitro and in vivo. AA might be applied as a promising agent for the treatment of BC.
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•Abietic acid selectively inhibits the proliferation of bladder cancer cells but spare the normal cell.•Abietic acid induced ferroptosis relied on the inhibition of GPX4 in bladder cancer cells.•Abietic acid reduced the expression of GPX4 dependent on HO-1 pathway.•Abietic acid inhibited the tumorigenesis of bladder cancer cells in vivo.
The rare earth extraction process has significant time delay characteristics, making it challenging to identify the time delay and establish an accurate mathematical model. This paper proposes a ...multi-delay identification method based on improved time-correlation analysis. Firstly, the data are preprocessed by grey relational analysis, and the time delay sequence and time-correlation data matrix are constructed. The time-correlation analysis matrix is defined, and the H∞ norm quantifies the correlation degree of the data sequence. Thus the multi-delay identification problem is transformed into an integer optimization problem. Secondly, an improved discrete state transition algorithm is used for optimization to obtain multi-delay. Finally, based on an Neodymium (Nd) component content model constructed by a wavelet neural network, the performance of the proposed method is compared with the unimproved time delay identification method and the model without an identification method. The results show that the proposed algorithm improves optimization accuracy, convergence speed, and stability. The performance of the component content model after time delay identification is significantly improved using the proposed method, which verifies its effectiveness in the time delay identification of the rare earth extraction process.
Abstract
Digital twin can be defined as a digital equivalent of an object of which it can mirror its behavior and status or virtual replicas of real physical entities in Cyberspace. To an extent, it ...also can simulate and predict the states of equipment or systems through smart algorithms and massive data. Hence, the digital twin is emerging used in intelligent manufacturing Systems in real-time and predicting system failure and also has introduced into a variety of traditional industries such as construction, Agriculture. Rare earth production is a typical process industry, and its Extraction Process enjoys the top priority in the industry. However, the extraction process is usually characterized by nonlinear behavior, large time delays, and strong coupling of various process variables. In case of failures happened in the process, the whole line would be shut down. Therefore, the digital twin is introduced into the design of process simulation to promote the efficiency and intelligent level of the Extraction Process. This paper proposes the techniques to build the rare earth digital twin such as soft measurement of component content, component content process simulation, control optimization strategy, and virtual workshop, etc. At the end, the validity of the model is verified, and a case study is conducted to verify the feasibility of the whole Digital twin framework.
Cr
C
-modified NiCr-TiC composite coatings were prepared using the plasma spraying technique for different Cr
C
contents on the microstructure and the properties of the Ni-based TiC cladding layer ...were investigated. The microstructures of the coatings were characterized using scanning electron microscopy, and the friction and wear performance of the coating was evaluated by the wear tests. The results revealed that the surfaces of the Cr
C
-modified NiCr-TiC composite coatings with varying Cr
C
contents were dense and smooth. TiC was uniformly distributed throughout the entire coating, forming a gradient interface between the binder phase of the Ni-based alloy and the hard phase of TiC. At high temperatures, Cr
C
decomposes, with some chromium diffusing and forming complex carbides around TiC, some chromium solubilizes with Fe, Ni, and other elements. An increase in chromium carbide content leads to an upward trend in hardness. The measured hardness of the coatings ranged from 600 to 850 HV3 and tended to increase with increasing Cr
C
content. When the mass fraction of Cr
C
reached 30%, the hardness increased to 850 HV3, and the cracks and defects were observed in the coating, resulting in a wear resistance decline.
Nearly 30% of clear cell renal cell carcinoma (ccRCC) patients present with metastasis at the time of diagnosis, and the prognosis for these patients is poor. Therefore, novel potential prognostic ...biomarkers and therapeutic targets for ccRCC could be helpful. Emerging evidence indicates that lncRNAs play important roles in cancer tumorigenesis and could be used as potential biomarkers or therapeutic targets. PANDAR (promoter of CDKN1A antisense DNA damage activated RNA) is a relatively novel lncRNA that plays an important role in the development of multiple cancers. However, the clinical significance and molecular mechanism of PANDAR in ccRCC are still elusive. In the present study, we attempted to elucidate the role of PANDAR in ccRCC.
The relative expression level of lncRNA PANDAR was quantified by real-time qPCR in 62 paired ccRCC tissues and in renal cancer cell lines, and its association with overall survival was assessed by statistical analysis. The biological functions of lncRNA PANDAR on ccRCC cells were determined both in vitro and in vivo.
PANDAR expression was significantly upregulated in tumor tissues and cell lines compared with normal counterparts. Moreover, PANDAR served as an independent predictor of overall survival, and increased PANDAR expression was positively correlated with an advanced TNM stage. Further experiments demonstrated that PANDAR silencing can significantly inhibit cell proliferation and invasion, induce cell cycle arrest in the G1 phase and significantly promote apoptosis in 7860 and Caki-1 cell lines. In addition, in vivo experiments confirmed that downregulation of PANDAR inhibited the tumorigenic ability of 7860 cells in nude mice. Silencing of PANDAR also inhibited the expression of Bcl-2 and Mcl-1 and upregulated the expression of Bax in vivo.
Our results suggest that PANDAR is involved in ccRCC progression and may serve as a potential prognostic biomarker and therapeutic target.
Insufficient color feature extraction can lead to poor prediction performance in rare earth element composition estimation. To address this issue, we propose a one-dimensional convolutional method ...for predicting rare earth element composition. First, images of rare earth element solutions, color space features (HSV and YUV), and spatial texture features are extracted. Because the trend of rare earth element composition is closely related to the extraction stage, we select the corresponding extraction stage of the image as a key feature. A feature selection technique based on Random Forest Recursive Feature Elimination with Cross-Validation (RF-RFECV) is applied to select the most relevant features, with a mixed feature set being obtained. Based on this, a one-dimensional convolutional neural network prediction model with multiple residual attention blocks (MRAB-DNN) is introduced. The proposed model incorporates the Residual Attention Block (RAB) structure, which mitigates the effects of noisy weights, subsequently enhancing both prediction accuracy and the rate of convergence. Experimental assessments on field images utilizing the MRAB-DNN model with an amalgamation of features indicate that our methodology surpasses alternative techniques in thorough image feature extraction. Moreover, it presents dual advantages of speed and precision in predicting the composition of rare earth elements. Such a model holds potential for real-time monitoring of rare earth element composition in extraction production processes.
Lysosome-associated agents have been implicated as possible chemo-sensitizers and immune regulators for cancer chemotherapy. We investigated the potential roles and mechanisms of hydroxychloroquine ...(HCQ) in combination with chemotherapy in lung cancer treatment.
The effects of combined treatment on non-small cell lung cancer (NSCLC) were investigated using cell viability assays and animal models. The influence of HCQ on lysosomal pH was evaluated by lysosomal sensors and confocal microscopy. The effects of HCQ on the tumour immune microenvironment were analysed by flow cytometry.
HCQ elevates the lysosomal pH of cancer cells to inactivate P-gp while increasing drug release from the lysosome into the nucleus. Furthermore, single HCQ therapy inhibits lung cancer by inducing macrophage-modulated anti-tumour CD8
T cell immunity. Moreover, HCQ could promote the transition of M2 tumour-associated macrophages (TAMs) into M1-like macrophages, leading to CD8
T cell infiltration into the tumour microenvironment.
HCQ exerts anti-NSCLC cells effects by reversing the drug sequestration in lysosomes and enhancing the CD8
T cell immune response. These findings suggest that HCQ could act as a promising chemo-sensitizer and immune regulator for lung cancer chemotherapy in the clinic.
Penile shrapnel injuries are an exceedingly rare occurrence and a medical emergency. Herein, we present a case of penile shrapnel wounds in an adolescent male and discuss the management and ...complications associated with penetrating injuries to penile. We reported that an 18-year-old Chinese armed police soldier underwent debridement, shrapnel removal and suturing under spinal anesthesia. Six days postoperatively, he was discharged from the hospital smoothly. The patient reported normal erectile function and urination following discharge. With a follow-up of three months, the patient exhibited no symptoms of dysuria or erectile dysfunction. It is explicitly stated that prompt surgery intervention described in this report resulted in optimal prognosis. Penile shrapnel injury is a rare phenomenon typically associated with emergency drill and military training involving explosive shells. With regard to penetrating penile injury, timely surgical exploration is essential because it avoids penile plaque formation, penile fibrosis and angulation, and accelerates the return to erectile and urination function.
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