A new approach to COVID-19 data mining: A deep spatial-temporal prediction model based on tree structure for traffic revitalization index.

The outbreak of the COVID-19 epidemic has had a huge impact on a global scale and its impact has covered almost all human industries. The Chinese government enacted a series of policies to restrict the transportation industry in order to slow the spread of the COVID-19 virus in early 2020. With the gradual control of the COVID-19 epidemic and the reduction of confirmed cases, the Chinese transportation industry has gradually recovered. The traffic revitalization index is the main indicator for evaluating the degree of recovery of the urban transportation industry after being affected by the COVID-19 epidemic. The prediction research of traffic revitalization index can help the relevant government departments to know the state of urban traffic from the macro level and formulate relevant policies. Therefore, this study proposes a deep spatial-temporal prediction model based on tree structure for the traffic revitalization index. The model mainly includes spatial convolution module, temporal convolution module and matrix data fusion module. The spatial convolution module builds a tree convolution process based on the tree structure that can contain directional features and hierarchical features of urban nodes. The temporal convolution module constructs a deep network for capturing temporal dependent features of the data in the multi-layer residual structure. The matrix data fusion module can perform multi-scale fusion of COVID-19 epidemic data and traffic revitalization index data to further improve the prediction effect of the model. In this study, experimental comparisons between our model and multiple baseline models are conducted on real datasets. The experimental results show that our model has an average improvement of 21%, 18%, and 23% in MAE, RMSE and MAPE indicators, respectively.

Rapid Detection of SARS-CoV-2 Spike RBD Protein in Body Fluid: Based on Special Calcium Ion-Mediated Gold Nanoparticles Modified by Bromide Ions.

The receptor-binding domain of the SARS-CoV-2 spike mediates the key to binding the virus to the host receptor, but capturing the molecular signal of this spike RBD remains a formidable challenge. Here, we report a new surface-enhanced Raman spectroscopy (SERS) approach, which used gold nanoparticles prepared by low-speed constant-temperature centrifugation by bromine and calcium ions in two cleaning steps as the enhanced substrate to rapidly and accurately detect spike RBD large protein molecules in body fluids. The detection signal was extremely stable, and the orientation of the spike RBD on the enhanced substrate surface was also determined. This approach was specific in distinguishing different SARS-CoV-2 variants of spike RBD, including Delta, Beta, Gamma, and Omicron. Additionally, the enhanced substrate can identify biologically active or inactive spike RBD. This two-step cleaning enhanced substrate opens up opportunities not only for early diagnostics of SARS-CoV-2 virus but also for developing targeted drugs against viruses.

Implications of NKG2A in immunity and immune-mediated diseases.

In recent studies, NKG2A is revealed to be a key immune checkpoint for both natural killer (NK) cells and CD8+ T cells. It form heterodimer receptors with CD94, and targets the peptide-presenting human leukocyte antigen-E (HLA-E) molecules. Upon crosslinking, NKG2A/CD94 delivers inhibitory signals for NK cells and CD8+ T cells, while blocking NKG2A can effectively unleash functions of these cytotoxic lymphocytes. The interaction between NKG2A and HLA-E contributes to tumor immune escape, and NKG2A-mediated mechanisms are currently being exploited to develop potential antitumor therapeutic strategies. In addition, growing evidence shows that NKG2A also plays important roles in other immune-related diseases including viral infections, autoimmune diseases, inflammatory diseases, parasite infections and transplant rejection. Therefore, the current work focuses on describing the effect of NKG2A on immune regulation and exploring its potential role in immune-mediated disorders.

Risk Factors for Infection of Sutured Maxillofacial Soft Tissue Injuries.

Background: Maxillofacial soft tissue injuries (STIs) are common and frequent in emergency departments. The aim of this study was to analyze factors causing infection of maxillofacial STIs. Patients and Methods: Patients with maxillofacial STIs who received sutures and had complete medical records were evaluated. Gender, age, American Society of Anesthesiologists (ASA) grade, diabetes mellitus, wound age, wound length, wound contamination, wound type, and sites were analyzed using univariable analysis and binary logistic regression. Results: There were 3,276 cases included. In the univariable analysis, there was no significant difference in the infection rate between genders or between the wound age groups. In binary logistic regression, age, wound length, wound type, and physician level were risk factors for infection: age of 18-44 years (odds ratio [OR], 2.2; 95% confidence interval [CI], 1.7-2.9), 44-64 years (OR, 3.1; 95% CI, 2.3-4.3), and ≥65 years (OR, 2.6; 95% CI, 1.7-4.1); wound length of 4-8 cm (OR, 1.7; 95% CI, 1.3-2.2) and >8 cm (OR, 2.4; 95% CI, 1.1-5.1); intra-oral wounds (OR, 1.6; 95% CI, 1.1-2.4) and communicating wounds (OR, 3.2; 95% CI, 2.3-4.4); junior specialists (OR, 1.6; 95% CI, 1.2-2.2); and lip (OR, 3.7; 95% CI, 1.1-12.0) and cheek (OR, 4.7; 95% CI, 2.3-17.1) sites. Wound contamination, ASA grade, and diabetes mellitus were not significantly different from wound infection in binary regression analysis. Conclusions: Age (>18 years old), wound length (>4 cm), intra-oral wounds, communicating wounds, suturing by junior surgeons, and lip or cheek injuries may be risk factors for maxillofacial STI infection. Even if the penetrating wound age exceeds 24 hours, it is meaningful to suture if there is no serious infection. For wounds at high risk of infection, further measures should be considered to reduce the possibility of infection, such as improving the surgical training of junior surgeons and improving the patient's wound care.

Rapid detection of viruses: Based on silver nanoparticles modified with bromine ions and acetonitrile.

Nearly 200 million people have been diagnosed with COVID-19 since the outbreak in 2019, and this disease has claimed more than 5 million lives worldwide. Currently, researchers are focusing on vaccine development and the search for an effective strategy to control the infection source. This work designed a detection platform based on Surface-Enhanced Raman Spectroscopy (SERS) by introducing acetonitrile and calcium ions into the silver nanoparticle reinforced substrate system to realize the rapid detection of novel coronavirus. Acetonitrile may amplify the calcium-induced hot spots of silver nanoparticles and significantly enhanced the stability of silver nanoparticles. It also elicited highly sensitive SERS signals of the virus. This approach allowed us to capture the characteristic SERS signals of SARS-CoV-2, Human Adenovirus 3, and H1N1 influenza virus molecules at a concentration of 100 copies/test (PFU/test) with upstanding reproduction and signal-to-noise ratio. Machine learning recognition technology was employed to qualitatively distinguish the three virus molecules with 1000 groups of spectra of each virus. Acetonitrile is a potent internal marker in regulating the signal intensity of virus molecules in saliva and serum. Thus, we used the SERS peak intensity to quantify the virus content in saliva and serum. The results demonstrated a satisfactory linear relationship between peak intensity and protein concentration. Collectively, this rapid detection method has a broad application prospect in clinical diagnosis of viruses, management of emergent viral infectious diseases, and exploration of the interaction between viruses and host cells.

A novel enhanced substrate for label-free detection of SARS-CoV-2 based on surface-enhanced Raman scattering.

Accurate and sensitive detection of SARS-CoV-2 is an effective strategy for preventing the COVID-19 pandemic in the current absence of specific drug therapy. This study presents a novel enhanced substrate for label-free detection of respiratory viruses using surface-enhanced Raman Scattering. Sodium borohydride reduces silver ions to clustered silver nanoparticles to eliminate the disorganized peak signal of the traditional citrate reducing agent. Meanwhile, the study obtained the fingerprints and concentration-dependent curves of many respiratory viruses, including SARS-CoV-2, human adenovirus type 7, and H1N1 virus, with good linear relationships. The three viruses were also identified in serum and saliva within two minutes, combined with linear discriminant diagnostic analysis. Therefore, establishing this enhanced substrate is greatly valuable for the global response to the COVID-19 pandemic.

Exploring the treatment of COVID-19 with Yinqiao powder based on network pharmacology.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In China, Yinqiao powder is widely used to prevent and treat COVID-19 patients with Weifen syndrome. In this study, the screening and verification of active ingredients, target selection and DisGeNET scoring, drug-ingredient-gene network construction, protein-protein interaction network construction, molecular docking and surface plasmon resonance (SPR) analysis, gene ontology (GO) functional analysis, gene tissue analysis, and kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were used to explore the active ingredients, targets, and potential mechanisms of Yinqiao powder in the treatment of COVID-19. We also predicted the therapeutic effect of Yinqiao powder using TCM anti-COVID-19 (TCMATCOV). Yinqiao powder has a certain therapeutic effect on COVID-19, with an intervention score of 20.16. Hesperetin, eriodictyol, luteolin, quercetin, and naringenin were the potentially effective active ingredients against COVID-19. The hub-proteins were interleukin-6 (IL-6), mitogen-activated protein kinase 3 (MAPK3), tumor necrosis factor (TNF), and tumor protein P53 (TP53). The potential mechanisms of Yinqiao powder in the treatment of COVID-19 are the TNF signaling pathway, T-cell receptor signaling pathway, Toll-like receptor signaling pathway, and MAPK signaling pathway. This study provides a new perspective for discovering potential drugs and mechanisms of COVID-19.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown.

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing "pandemic haze," raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

A Case of 2019 Novel Coronavirus in a Pregnant Woman With Preterm Delivery.

We present a case of a 30-week pregnant woman with the 2019 novel coronavirus (COVID-19) delivering a healthy infant with no evidence of COVID-19.