Urinary cadmium concentration is associated with the severity and clinical outcomes of COVID-19: a bicenter observational cohort study (preprint)

Background Cadmium exposure can cause oxidative stress, induce inflammation, inhibit immune function, and therefore has significant impacts on the pathogenesis and severity of many diseases. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can also provoke oxidative stress and the dysregulation of inflammatory and immune responses. This study aimed to assess the potential associations of cadmium exposure with the severity and clinical outcomes of patients with coronavirus disease 2019 (COVID-19).Methods We performed a retrospective, observational, bicenter cohort analysis of patients with SARS-CoV-2 infection in Taiwan between June 2022 and July 2023. Cadmium concentrations in blood and urine were measured within 3 days of the diagnosis of acute SARS-CoV-2 infection, and the severity and clinical outcomes of patients with COVID-19 were analyzed.Results A total of 574 patients were analyzed and divided into a severe COVID-19 group (hospitalized patients) (n = 252; 43.9%), and non-severe COVID-19 group (n = 322; 56.1%). The overall in-hospital mortality rate was 11.8% (n = 68), and 149 patients (26%) required invasive mechanical ventilation. The severe COVID-19 patients were older, had significantly more comorbidities, and significantly higher neutrophil/lymphocyte ratio, C-reactive protein, and interleukin-6 than the non-severe COVID-19 patients (all p < 0.05). Both blood and urine cadmium concentrations were significantly higher in the severe COVID-19 patients than in the non-severe COVID-19 patients. Among the severe COVID-19 patients, those in higher urine cadmium/creatinine quartiles had a significantly higher risk of organ failure (i.e., higher APACHE II and SOFA scores), higher neutrophil/lymphocyte ratio, lower PaO2/FiO2 requiring higher invasive mechanical ventilation support, higher risk of acute respiratory distress syndrome, and higher 60-, 90-day, and all-cause hospital mortality (all p < 0.05). Multivariate logistic regression models revealed that urine cadmium/creatinine was independently associated with severe COVID-19 (adjusted OR 1.648 [95% CI 1.064–2.552], p = 0.025), and that a urine cadmium/creatinine value > 2.05 µg/g had the highest predictive value (adjusted OR 5.391, [95% CI 1.127–25.794], p = 0.035).Conclusions Urine cadmium concentration in the early course of COVID-19 could predict the severity and clinical outcomes of patients and was independently associated with the risk of severe COVID-19.

Oil price shocks, economic policy uncertainty, and green finance: a case of China

This study investigates the long- and short-run effects of crude oil price (COP) and economic policy uncertainty (EPU) on China's green bond index (GBI) using the quantile autoregressive distributed lag model. The empirical results show that COP and EPU produce a significant positive and negative influence on GBI in the long-run across most quantiles, respectively, but their short-run counterparts are opposite direction and only significant in higher quantiles. Thus, major contributions are made accordingly and shown in the following aspects. The findings emphasise the importance of understanding how COP and EPU affect China's green bond market for the first time. In addition, both the long- and short-run effects are captured, but long-run shocks primarily drive the green bond market. Finally, time- and quantile-varying analyses are adopted to explain the nexus between COP and EPU to GBI, which considers not only different states of the bond market but also events that occur in different time periods. Some detailed policies, such as a unified and effective green bond market, an early warning mechanism of oil price fluctuation, and prudent economic policy adjustments, are beneficial for stabilising the green finance market.

Continuous Wavelet Transform of Time-Frequency Analysis Technique to Capture the Dynamic Hedging Ability of Precious Metals

Exploring the hedging ability of precious metals through a novel perspective is crucial for better investment. This investigation applies the wavelet technique to study the complicated correlation between global economic policy uncertainty (GEPU) and the prices of precious metals. The empirical outcomes suggest that GEPU exerts positive influences on the prices of precious metals, indicating that precious metals could hedge against global economic policy uncertainty, which is supported by the inter-temporal capital asset pricing model (ICAPM). Among them, gold is better for long-term investment than silver, which is more suitable for the short run in recent years, while platinum's hedging ability is virtually non-existent after the global trade wars. Conversely, the positive influences from gold price on GEPU underline that the gold market plays a prospective role in the situation of economic policies worldwide, which does not exist in the silver market. Besides, the effects of platinum price on GEPU change from positive to negative, suggesting that the underlying cause of its forward-looking effect on GEPU alters from the investment value to the industrial one. In the context of the increasing instability of global economic policies, the above conclusions could offer significant lessons to both investors and governments.

PSTCNN: Explainable COVID-19 diagnosis using PSO-guided self-tuning CNN

Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rapidly worldwide, posing an unignorable threat to the global economy and human health. It is a disease caused by severe acute respiratory syndrome coronavirus 2, a single-stranded RNA virus of the genus Betacoronavirus. This virus is highly infectious and relies on its angiotensin-converting enzyme 2-receptor to enter cells. With the increase in the number of confirmed COVID-19 diagnoses, the difficulty of diagnosis due to the lack of global healthcare resources becomes increasingly apparent. Deep learning-based computer-aided diagnosis models with high generalisability can effectively alleviate this pressure. Hyperparameter tuning is essential in training such models and significantly impacts their final performance and training speed. However, traditional hyperparameter tuning methods are usually time-consuming and unstable. To solve this issue, we introduce Particle Swarm Optimisation to build a PSO-guided Self-Tuning Convolution Neural Network (PSTCNN), allowing the model to tune hyperparameters automatically. Therefore, the proposed approach can reduce human involvement. Also, the optimisation algorithm can select the combination of hyperparameters in a targeted manner, thus stably achieving a solution closer to the global optimum. Experimentally, the PSTCNN can obtain quite excellent results, with a sensitivity of 93.65% ± 1.86%, a specificity of 94.32% ± 2.07%, a precision of 94.30% ± 2.04%, an accuracy of 93.99% ± 1.78%, an F1-score of 93.97% ± 1.78%, Matthews Correlation Coefficient of 87.99% ± 3.56%, and Fowlkes-Mallows Index of 93.97% ± 1.78%. Our experiments demonstrate that compared to traditional methods, hyperparameter tuning of the model using an optimisation algorithm is faster and more effective. [ FROM AUTHOR]

Nitrogen-rich based conjugated microporous polymers for highly efficient adsorption and removal of COVID-19 antiviral drug chloroquine phosphate from environmental waters

Chloroquine phosphate (CQP) has been suggested as an important and effective clinical reliever medication for the 2019 coronavirus (COVID-19). Nevertheless, its excessive use will inevitably cause irreparable damage to the entire ecosystem, thereby posing a considerable environmental safety concern. Hence, the development of highly-efficient methods of removing CQP from water pollution sources, e.g., effluents from hospitals and pharmaceutical factories is significant. This study reported the fabrication of novel CN bond linked conjugated microporous polymers (CMPs) (BPT–DMB–CMP) with multiple nitrogen-rich anchoring sites for the quick and efficient removal of CQP from aqueous solutions. The irreversible covalent CN bond linked in the internal framework of BPT–DMB–CMP endowed it with good chemical stability and excellent adsorbent regeneration. With its predesigned functional groups (i.e., rich NH bonds, triazine rings, and benzene rings) and large area surface (1,019.89 m2·g−1), BPT–DMB–CMP demonstrated rapid adsorption kinetics (25 min) and an extraordinary adsorption capacity (334.70 mg·g−1) for CQP, which is relatively higher than that of other adsorbents. The adsorption behavior of CQP on BPT–DMB–CMP corresponded with Liu model and mixed-order model. Based on the density functional theory (DFT) calculations, X-ray photoelectron spectroscopy (XPS), and adsorption comparisons test, the halogen bonding, and hydrogen bonding cooperates with π − π, C  H···π interactions and size-matching effect in the CQP adsorption system on BPT–DMB–CMP. The excellent practicability for the removal of CQP from real wastewater samples verified the prospect of practical application of BPT–DMB–CMP. BPT–DMB–CMP exhibited the application potentials for the adsorption of other antiviral drugs. This work opens up an efficient, simple, and high adsorption capacity way for removal CQP.

CRISPR/Cas12a-based SARS-CoV-2 Rapid Visual Detection and Clinical Application (preprint)

Background: Currently, rapid and widespread testing is essential to promote early intervention and curb the ongoing COVID-19 pandemic. The reverse transcription-polymerase chain reaction (RT-PCR) for detecting novel coronavirus (SARS-CoV-2) is restricted to professional laboratories and well-trained personnel, thus, limiting its widespread use in in resource-limited conditions. Methods: To overcome these challenges, we developed a rapid and convenient assay using recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR) technology for the rapid detection SARS-CoV-2, which was named as Visual Detection of RPA-amplified Products (VDAP). The reaction conditions of the VDAP were optimized and selected using pure SARS-CoV-2 RNA standards and the sensitivity and specificity of the VDAP were further determined. Finally, the VDAP was verified on clinical specimens. Results: The VDAP was performed at 37 °C for 15 min, and the result was visible by the naked eye. The limits of detection (LODs) of the VDAP for the target ORF1ab and N genes are 70 and 500 copies, respectively. No cross-reactivity was observed with the RNA standard samples of four respiratory viruses or clinical samples of common respiratory viral infections. These results confirmed that the assay was highly specific. Thirty SARS-CoV-2 positive and 30 SARS-CoV-2 negative patient specimens were analyzed. We compared these results to RT-PCR, the overall sensitivity and specificity of the VDAP compared to RT-PCR for detection SARS-CoV-2 were 93.3% and 100.0%, respectively. Conclusions: The VDAP is a simple, highly specific, and convenient assay for the detection of SARS-CoV-2 in resource-limited conditions

Chimeric mRNA based COVID-19 vaccine elicits potent neutralizing antibodies and protection against Omicron and Delta (preprint)

The emerging SARS-CoV-2 variants of concern (VOCs) exhibit enhanced transmission and immune escape, reducing the efficacy and effectiveness of the two FDA-approved mRNA vaccines currently in use. Here, we explored various strategies to develop mRNA vaccines that offer potentially safer and wider coverage of VOCs. The initial mouse vaccination results showed that the individual VOC mRNAs carrying furin cleavage mutation induced the generation of neutralizing antibody in a VOC-specific manner. Moreover, we discovered that the antibodies produced from mice immunized with Beta-Furin and Washington (WA)-Furin mRNAs cross-reacted with other VOCs. The broad spectrum of generated nAb was further confirmed when vaccinated mice were challenged with the respective live viruses. However, neither WA-Furin nor Beta-Furin mRNA elicited potent neutralizing activity against the omicron variant. Interestingly, in a mix-and-match booster experiment, omicron-Furin and WA-Furin mRNA elicited comparable protection against omicron. Finally, we tested the concept of bivalent vaccine by introducing the RBD of Delta strain into the intact S antigen of Omicron. The chimeric mRNA induces potent and broadly acting nAb against Omicron and Delta, which paves the way to develop vaccine candidate to target emerging variants in the future.

Urban spatial epidemic simulation model: A case study of the second COVID‐19 outbreak in Beijing, China

The second COVID‐19 outbreak in Beijing was controlled by non‐pharmaceutical interventions, which avoided a second pandemic. Until mass vaccination achieves herd immunity, cities are at risk of similar outbreaks. It is vital to quantify and simulate Beijing's non‐pharmaceutical interventions to find effective intervention policies for the second outbreak. Few models have achieved accurate intra‐city spatio‐temporal epidemic spread simulation, and most modeling studies focused on the initial pandemic. We built a dynamic module of infected case movement within the city, and established an urban spatially epidemic simulation model (USESM), using mobile phone signaling data to create scenarios to assess the impact of interventions. We found that: (1) USESM simulated the transmission process of the epidemic within Beijing;(2) USESM showed the epidemic curve and presented the spatial distribution of epidemic spread on a map;and (3) to balance resources, interventions, and economic development, nucleic acid testing intensity could be increased and restrictions on human mobility in non‐epidemic areas eased.

Health Resources and Well-Being in Optimal Aging: The Mediating Role of Selection, Optimization, and Compensation Strategies

Aging and health issues continue to receive attention, especially under the global health challenge of achieving the Sustainable Development Goals. It is important to understand how people adapt their lifespan development to face the gains and losses of resources. The purpose of this study was to test the relationships between health resources, selection, optimization, and compensation (SOC) strategies and well-being with aging;to examine the impact of SOC strategies on health resources and well-being, and the link between health resources and well-being. Using structural equation modeling to analyze our hypotheses, a sample survey of 372 adults was conducted. The results showed that health resources were positively and significantly related to SOC and well-being. SOC strategies were positively and significantly related to well-being and SOC strategies partially mediated the link between health resources and well-being. The findings contribute to the literature by establishing a model and providing practical implications for individual behavior, as well as better understanding of the theoretical and practical implications of aging and health. A friendly community and organization may help people’s well-being in terms of physiology, psychology, society, and environment.

Deep Rank-Based Average Pooling Network for Covid-19 Recognition

(Aim) To make a more accurate and precise COVID-19 diagnosis system, this study proposed a novel deep rank-based average pooling network (DRAPNet) model, i.e., deep rank-based average pooling network, for COVID-19 recognition. (Methods) 521 subjects yield 1164 slice images via the slice level selection method. All the 1164 slice images comprise four categories: COVID-19 positive;community-acquired pneumonia;second pulmonary tuberculosis;and healthy control. Our method firstly introduced an improved multiple-way data augmentation. Secondly, an n-conv rank-based average pooling module (NRAPM) was proposed in which rank-based pooling—particularly, rank-based average pooling (RAP)—was employed to avoid overfitting. Third, a novel DRAPNet was proposed based on NRAPM and inspired by the VGG network. Grad-CAM was used to generate heatmaps and gave our AI model an explainable analysis. (Results) Our DRAPNet achieved a micro-averaged F1 score of 95.49% by 10 runs over the test set. The sensitivities of the four classes were 95.44%, 96.07%, 94.41%, and 96.07%, respectively. The precisions of four classes were 96.45%, 95.22%, 95.05%, and 95.28%, respectively. The F1 scores of the four classes were 95.94%, 95.64%, 94.73%, and 95.67%, respectively. Besides, the confusion matrix was given. (Conclusions) The DRAPNet is effective in diagnosing COVID-19 and other chest infectious diseases. The RAP gives better results than four other methods: strided convolution, l2-norm pooling, average pooling, and max pooling.

Design characteristics on the indoor and outdoor environments of the COVID-19 emergency hospital

According to the discussion of the design method and operational effect for Wuhan Huoshenshan Hospital, this paper summarized the design control points of indoor and outdoor environment of COVID-19 emergency hospital. Based on the design of Wuhan Huoshenshan Hospital, this paper analyzed and discussed the site design, building layout, three-zones and two-passages, the design scheme of the ventilation and air conditioning system for negative pressure ward and negative pressure isolation ward, air distribution, as well as some other key designs for COVID-19 emergency hospital. The design points were summarized and refined. The design methods and technology requirements of the COVID-19 emergency hospital were provided in this study, such as ventilation and air conditioning system setting, ventilation quantity of wards, pressure gradient control measures among different areas, upper and lower air distribution, filter setting mode and distance of air inlet and outlet, which could benefit to provide references for the design of similar projects in the future.

Directing an mRNA-LNP vaccine toward lymph nodes improves humoral and cellular immunity against SARS-CoV-2 (preprint)

The exploration and identification of safe and effective vaccines for the SARS-CoV-2 pandemic has captured the worlds attention and remains an ongoing issue in order to protect against emerging variants of concern (VoCs) while generating long lasting immunity. Here, we report the synthesis of a novel messenger ribonucleic acid (mRNA) encoding the spike protein in a lipid nanoparticle formulation (LNP) (STI-7264) that generates robust humoral and cellular immunity following immunization of C57Bl6 mice. In efforts to continually improve immunity, a lymphatic drug delivery device (MuVaxx) was engineered and tested to modulate immune cells at the injection site (epidermis and dermis) and draining lymph node (LN) to elicit adaptive immunity. Using MuVaxx, immune responses were elicited and maintained at a 10-fold dose reduction compared to traditional intramuscular (IM) administration as measured by anti-spike antibodies, cytokine producing CD8 T cells, and neutralizing antibodies against the Washington (Wild Type, WT) and South African (beta) variants. Remarkably, a 4-fold elevated T cell response was observed in MuVaxx administered vaccination as compared to that of IM administered vaccination. Thus, these data support further investigation into STI-7264 and lymphatic mediated delivery using MuVaxx for SARS-CoV-2 and VoCs vaccines.

Therapeutic strategy of traditional Chinese medicine for COVID-19

2019 novel coronavirus pneumonia is an acute infectious pneumonia outbreak at the end of 2019 in Wuhan, Hubei province. It belongs to the category of "epidemic disease" in TCM. Early intervention of traditional Chinese medicine has played an important role in this epidemic situation.In each stage, it has shown the advantages of treatment, accumulated rich experience, and initially formed a set of mechanism of Chinese medicine to prevent and treat acute infectious diseases. This article summarizes the classical prescriptions during each period of the disease, the screening methods of effective prescriptions and the clinical studies that have been carried out. This article can preliminarily showed the active part of traditional Chinese medicine in the treatment of 2019 novel coronavirus pneumonia.

SARS-CoV-2-Triggered Mast Cell Rapid Degranulation Induces Alveolar Epithelial Inflammation and Lung Injury (preprint)

SARS-CoV-2 infection-induced hyper-inflammation links to the acute lung injury and COVID-19 severity. Identifying the primary mediators that initiate the uncontrolled hypercytokinemia is essential for treatments. Mast cells (MCs) are strategically located at the mucosa and beneficially or detrimentally regulate immune inflammations. Here we showed that SARS-CoV-2-triggeed MC degranulation initiated alveolar epithelial inflammation and lung injury. SARS-CoV-2 challenge induced MC degranulation in ACE-2 humanized mice and rhesus macaques, and a rapid MC degranulation could be recapitulated with Spike-RBD binding to ACE2 in cells; MC degranulation alterred various signaling pathways in alveolar epithelial cells, particularly, led to the production of pro-inflammatory factors and consequential disruption of tight junctions. Importantly, the administration of clinical MC stabilizers for blocking degranulation dampened SARS-CoV-2-induced production of pro-inflammatory factors and prevented lung injury. These findings uncover a novel mechanism for SARS-CoV-2 initiating lung inflammation, and suggest an off-label use of MC stabilizer as immunomodulators for COVID-19 treatments.

Blended Learning: New Prospects for International Higher Education

Shidong wang (SW): Please share with us the pandemic experience of Peking University and Oxford University. How has your university adapted its education and teaching to COVID-19 conditions?

Implementation of Web-Based Dynamic Assessments as Sustainable Educational Technique for Enhancing Reading Strategies in English Class during the COVID-19 Pandemic

The COVID-19 pandemic has resulted in educational disruption at a global scale. Based on the United Nation’s Sustainable Development Goal 4, “achieving inclusive and quality education for all”, this study designed two feasible learning models for the solution of sustainable learning during the COVID-19 pandemic, GPAM-WATA and Paper-and-Pencil test (PPT). The GPAM-WATA, a web-based dynamic assessment, offers online learning to most of the populations impacted by the COVID-19 pandemic, while PPT makes the vulnerable groups’ access to learning possible with the aid of paper-based delivery. A quasi-experimental design was adopted, and both learning models were applied to a junior high school English reading course in Taiwan. A total of 122 seventh graders were randomly assigned to the GPAM-WATA group and PPT group for self-directed learning. The findings show that the GPAM-WATA is a sustainable educational technique that facilitates a better improvement in English reading performance. The PPT also has a positive effect on English reading performance, although not significantly if compared with the GPAM-WATA. This study suggests that GPAM-WATA is effective for English reading instruction in an online learning environment. The PPT can be an alternative approach for students stuck without access to online delivery during the COVID-19 pandemic.

Occurrence of COVID-19 symptoms during SARS-CoV-2 infection defines waning of humoral immunity (preprint)

Approximately half of the SARS-CoV-2 infections occur without apparent symptoms, raising questions regarding long-term humoral immunity in asymptomatic individuals. Plasma levels of immunoglobulin G (IgG) and M (IgM) against the viral spike or nucleoprotein were determined for 25,091 individuals enrolled in a surveillance program in Wuhan, China. We compared 405 asymptomatic individuals with 459 symptomatic COVID-19 patients. The well-defined duration of the SARS-CoV-2 endemic in Wuhan allowed a side-by-side comparison of antibody responses following symptomatic and asymptomatic infections without subsequent antigen re-exposure. IgM responses rapidly declined in both groups. However, both the prevalence and durability of IgG responses and neutralizing capacities correlated positively with symptoms. Regardless of sex, age, and body weight, asymptomatic individuals lost their SARS-CoV-2-specific IgG antibodies more often and rapidly than symptomatic patients. These findings have important implications for immunity and favour immunization programs including individuals after asymptomatic infections. One-Sentence SummaryPrevalence and durability of SARS-CoV-2-specific IgG responses and neutralizing capacities correlate with COVID-19 symptoms.

A combination regimen by lopinave/litonawe, emtricitabine and tenofovir alafenamide fumarate for treatment of novel coronavirus pneumonia (TARCoV)

Objective: To explore the efficacy of a combination regimen by Lopinave/Litonawe (LPV/r), emtricitabine and tenofovir alafenamide fumarate (FTC/TAF) for the treatment of novel coronavirus pneumonia.

Automated Detection of COVID-19 through Convolutional Neural Network using Chest x-ray images (preprint)

The COVID-19 epidemic appears to have a catastrophic impact on global well-being and public health. More than 10 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, timely and accurate classification of healthy and infected patients is essential to control and treat COVID-19. To this end, in this paper, we aim to develop a deep learning-based system for the persuasive classification and reliable detection of COVID-19 using chest radiography. Firstly, we evaluate the performance of various state-of-the-art convolutional neural networks (CNNs) proposed over recent years for medical image classification. Secondly, we develop and train CNN from scratch. In both cases, we use a recently published public X-Ray dataset for training and validation purposes. For transfer learning, we obtain 100% accuracy for binary classification (i.e., Normal/COVID-19) and 87.50% accuracy for tertiary classification (Normal/COVID-19/Pneumonia). With the CNN trained from scratch, we achieve 93.75% accuracy for tertiary classification. We observe, in the case of transfer learning, the classification accuracy drops with an increased number of classes. Our comprehensive ROC and confusion metric analysis with 10-fold cross-validation strongly underpin our findings.