Does foreign equity investment impact the spillover effect of industries in China?

This study aims to systematically investigate the impact of foreign equity investment on the spillover across industries in China, both in terms of the contagion path and persistence of shocks and the performance during the COVID-19 pandemic. We use daily data on returns covering 2014 to 2022 and apply linear and non-linear causality tests and spillover framework. Our findings show that the two proxies of foreign investment, net buying and Δ Net Buying, significantly shock the spillover across 11 industry indexes of China's stock market, particularly the spillover output and long-term spillover received of sectors. During the COVID-19 pandemic, international investors are bullish on China's economy reflected in the continuous inflow of northbound trading, and the short-run influence on China's stock market is weakened, while the long-run impact remains. Moreover, financial networks suggest that the path of movement international capital movement to accomplish overall contagion through shock in certain specific industries. Overall, this study evidence that the northbound trading generally overlooked by researchers is indeed an important channel of financial contagion to China's stock market.

Stability of SARS-CoV-2 in cold-chain transportation environments and the efficacy of disinfection measures.

Background: Low temperature is conducive to the survival of COVID-19. Some studies suggest that cold-chain environment may prolong the survival of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and increase the risk of transmission. However, the effect of cold-chain environmental factors and packaging materials on SARS-CoV-2 stability remains unclear. Methods: This study aimed to reveal cold-chain environmental factors that preserve the stability of SARS-CoV-2 and further explore effective disinfection measures for SARS-CoV-2 in the cold-chain environment. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, on various types of packaging material surfaces, i.e., polyethylene plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of visible light (wavelength 450 nm-780 nm) and airflow on the stability of SARS-CoV-2 pseudovirus at -18°C was subsequently assessed. Results: Experimental data show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surfaces than on nonporous surfaces, including polyethylene (PE) plastic, stainless steel, and Teflon. Compared with that at 25°C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperatures. Seawater preserved viral stability both at -18°C and with repeated freeze-thaw cycles compared with that in deionized water. Visible light from light-emitting diode (LED) illumination and airflow at -18°C reduced SARS-CoV-2 pseudovirus stability. Conclusion: Our studies indicate that temperature and seawater in the cold chain are risk factors for SARS-CoV-2 transmission, and LED visible light irradiation and increased airflow may be used as disinfection measures for SARS-CoV-2 in the cold-chain environment.

Market sentiment to COVID‐19 and the Chinese stock market

We classify the market sentiment to COVID‐19 into expected and unexpected components and then examine their particular impacts on the stock market. We find that unexpected sentiment causes fluctuations in the stock market more than expected sentiment does. However, unexpected sentiment cannot affect stock market informativeness despite the remarkable informational effect of expected sentiment. Moreover, the relation between expected sentiment and stock market fluctuation or informativeness is one‐way, whereas there exists a two‐way interaction between unexpected sentiment and stock market fluctuation. This further confirms that expected sentiment is informational, whereas unexpected sentiment is quite noisy and informationally harmful.

Evaluation of [18F]Favipiravir in Rodents and Nonhuman Primates (NHP) with Positron Emission Tomography.

The COVID-19 pandemic has posed a significant challenge to global public health. In response, the search for specific antiviral drugs that can effectively treat the disease caused by the SARS-CoV-2 virus has become a priority. While significant progress has been made in this regard, much work remains to address this ongoing crisis effectively. Favipiravir is an antiviral drug initially developed for the treatment of influenza and has received approval for emergency use for COVID-19 in many countries. A better understanding of the biodistribution and pharmacokinetics of Favipiravir in vivo would facilitate the development and translation of clinical antiviral drugs for COVID-19. Herein, we report the evaluation of [18F]Favipiravir in naive mice, transgenic mice models of Alzheimer's disease, and nonhuman primates (NHP) with positron emission tomography (PET). The [18F]Favipiravir was obtained in an overall decay-corrected radiochemical yield of 29% with a molar activity of 25 GBq/µmol at the end of synthesis (EOS). PET imaging in naive mice, transgenic mice models of Alzheimer's disease, and nonhuman primates revealed a low initial brain uptake, followed by a slow washout of [18F]Favipiravir in vivo. The [18F]Favipiravir was eliminated by a combination of hepatobiliary and urinary excretion. The low brain uptake was probably attributed to the low lipophilicity and low passive permeability of the drug. We hope this proof-of-concept study will provide a unique feature to study antiviral drugs using their corresponding isotopologues by PET.

Suramin Disturbs the Association of the N-Terminal Domain of SARS-CoV-2 Nucleocapsid Protein with RNA.

Suramin was originally used as an antiparasitic drug in clinics. Here, we demonstrate that suramin can bind to the N-terminal domain of SARS-CoV-2 nucleocapsid protein (N-NTD) and disturb its interaction with RNA. The BLI experiments showed that N-NTD interacts suramin with a dissociate constant (Kd = 2.74 µM) stronger than that of N-NTD with ssRNA-16 (Kd = 8.37 µM). Furthermore, both NMR titration experiments and molecular docking analysis suggested that suramin mainly binds to the positively charged cavity between the finger and the palm subdomains of N-NTD, and residues R88, R92, R93, I94, R95, K102 and A156 are crucial for N-NTD capturing suramin. Besides, NMR dynamics experiments showed that suramin-bound N-NTD adopts a more rigid structure, and the loop between ß2-ß3 exhibits fast motion on the ps-ns timescale, potentially facilitating suramin binding. Our findings not only reveal the molecular basis of suramin disturbing the association of SARS-CoV-2 N-NTD with RNA but also provide valuable structural information for the development of drugs against SARS-CoV-2.

What impacts foreign capital flows to China's stock markets? Evidence from financial risk spillover networks

This study investigates the spillover effects between foreign capital in China's stock market and 11 other financial assets (e.g., major stock markets, financial products, and interest rates). Employing the Diebold–Yilmaz framework (VAR– and QVAR based) and a complex network approach, we found that China's stock market foreign capital is significantly connected to international markets;the U.S., Hong Kong, and the U.K. were the top net risk transmitters. Moreover, money flows were subject to global instability and emergencies, including Brexit, the Sino-US trade war, and the COVID-19 pandemic. The operation of the Northward Fund is sometimes ahead of many developed markets, indicating that capital movement was somehow "Smart Money”. Our study provides a new idea for risk warning and systematic risk prevention.

Trends in operating room-based glaucoma procedures at a single eye center from 2016-2020.

AIM: To evaluate trends in glaucoma procedures at the Peking University Eye Center in 2016-2020. METHODS: A retrospective search of all glaucoma procedures performed at our institution were performed. Data were analyzed by calculating the absolute numbers and relative weightage of each procedure per year. RESULTS: The average age of glaucoma patients undergoing surgical procedures was 62.33±17.87y, and 55% were women. From 2016 to 2019, the number of surgical procedures performed in glaucoma patients showed an overall upward trend from 749 to 1460, although it decreased slightly in 2020 (n=1393), probably due to the COVID-19 pandemic. The number of trabeculectomies did not change significantly in 2016 (n=161) to 2018 (n=164) but decreased in 2019 (n=139) to 2020 (n=121), indicating a reduction in its relative weightage among glaucoma procedures (from 21.50% to 8.69%). The number of glaucoma drainage device implantations and minimally invasive glaucoma surgeries both increased (50 and 58 respectively in 2019), except in 2020. The number of transscleral cyclophotocoagulation procedures was relatively stable, increasing until 2017 (n=218) and then decreasing. Cataract surgeries with or without glaucoma procedures accounted for a large number of the total surgeries, increasing from 247 (32.97%) in 2016 to 967 (69.42%), among which cataract extraction combined with goniosynechialysis was the most frequent. CONCLUSION: The overall increase in the number of operating room-based surgical procedures is significant. Trabeculectomy is one of the most commonly performed procedures, despite the relative decline in its weightage. Other procedures, including use of glaucoma drainage devices and mini shunts and minimally invasive glaucoma surgeries, are gaining greater acceptance. Notably, lens-related surgery plays an important role in glaucoma management.

Stress load of Chinese nurses in Fangcang Shelter Hospitals during the COVID-19 pandemic: A latent profile analysis.

The Omicron wave of the COVID-19 pandemic significantly affected Shanghai, China, from March to June 2022. Numbers of Fangcang Shelter Hospitals (FSHs) were conversed from stadiums and exhibition centers to tackle the pandemic. This study aimed to identify the stress load profiles of nurses working in FSHs and explore the characteristics and factors influencing stress load profiles. Totally, 609 out of 700 FSH nurses (with an effective response rate of 87%) participated in an online survey investigating their socio-demographic information, work-related stressors, and stress load. Results of the latent profile analysis identified four classes of stress load, which were labeled as the low (Class 1), mild (Class 2), moderate (Class 3), and high (Class 4) stress load class. Maternity status and self-perceived health condition were significantly different between the four stress load classes by comparisons using the Chi-square test and the Kruskal-Wallis test. The contributors to the stress load profiles were determined by the multinomial logistic regression analysis, including age, education, maternity status, self-perceived health condition, working time in FSHs, and the four dimensions of work-related stressors. Participants who were less healthy (OR = 0.045, 95% CI:0.012,0.171), worked longer time in FSHs (OR = 40.483, 95% CI: 12.103,135.410), faced with more workload (OR = 3.664, 95% CI: 1.047,12.815), and worse working environment (OR = 12.274, 95% CI: 3.029,49.729) were more likely to be classified to the high stress load class. The task arrangement and working environment for FSH nurses should be optimized, and psychological training should be conducted routinely.

Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms

The ability to estimate current GDP growth before official data are released, known as "nowcasting”, is crucial for the Chinese government to effectively implement economic policy and manage economic uncertainties;however, there is limited research on nowcasting China's GDP in a data-rich environment. We evaluate the performance of various machine learning algorithms, dynamic factor models, static factor models, and MIDAS regressions in nowcasting the Chinese annualised real GDP growth rate in pseudo out-of-sample exercise, using 89 macroeconomic variables from years 1995 to 2020. We find that some machine learning methods outperform the benchmark dynamic factor model. The machine learning method that deserves more attention is ridge regression, which dominates all other models not only in terms of nowcast error but also in effective recognition of the impacts of the Global Financial Crisis and Covid-19 shocks. Policy-wise, our study guides practitioners in selecting appropriate nowcasting models for China's macroeconomy.

Stress load of Chinese nurses in Fangcang Shelter Hospitals during the COVID-19 pandemic: A latent profile analysis

The Omicron wave of the COVID-19 pandemic significantly affected Shanghai, China, from March to June 2022. Numbers of Fangcang Shelter Hospitals (FSHs) were conversed from stadiums and exhibition centers to tackle the pandemic. This study aimed to identify the stress load profiles of nurses working in FSHs and explore the characteristics and factors influencing stress load profiles. Totally, 609 out of 700 FSH nurses (with an effective response rate of 87%) participated in an online survey investigating their socio-demographic information, work-related stressors, and stress load. Results of the latent profile analysis identified four classes of stress load, which were labeled as the low (Class 1), mild (Class 2), moderate (Class 3), and high (Class 4) stress load class. Maternity status and self-perceived health condition were significantly different between the four stress load classes by comparisons using the Chi-square test and the Kruskal–Wallis test. The contributors to the stress load profiles were determined by the multinomial logistic regression analysis, including age, education, maternity status, self-perceived health condition, working time in FSHs, and the four dimensions of work-related stressors. Participants who were less healthy (OR = 0.045, 95% CI:0.012,0.171), worked longer time in FSHs (OR = 40.483, 95% CI: 12.103,135.410), faced with more workload (OR = 3.664, 95% CI: 1.047,12.815), and worse working environment (OR = 12.274, 95% CI: 3.029,49.729) were more likely to be classified to the high stress load class. The task arrangement and working environment for FSH nurses should be optimized, and psychological training should be conducted routinely.

Transformer for one stop interpretable cell type annotation.

Consistent annotation transfer from reference dataset to query dataset is fundamental to the development and reproducibility of single-cell research. Compared with traditional annotation methods, deep learning based methods are faster and more automated. A series of useful single cell analysis tools based on autoencoder architecture have been developed but these struggle to strike a balance between depth and interpretability. Here, we present TOSICA, a multi-head self-attention deep learning model based on Transformer that enables interpretable cell type annotation using biologically understandable entities, such as pathways or regulons. We show that TOSICA achieves fast and accurate one-stop annotation and batch-insensitive integration while providing biologically interpretable insights for understanding cellular behavior during development and disease progressions. We demonstrate TOSICA's advantages by applying it to scRNA-seq data of tumor-infiltrating immune cells, and CD14+ monocytes in COVID-19 to reveal rare cell types, heterogeneity and dynamic trajectories associated with disease progression and severity.

Does ambient air quality standard contribute to green innovation of enterprises in China? Implications for environmental protection and public health

In the post-COVID-19 era, environmental pollution has been a serious threat to public health. Enterprises are in urgent need of enhancing green technology innovation as the main source of pollutant emissions, and it is necessary for governments to support green innovation of enterprises to reduce pollutant emissions and promote public health. In this context, this paper investigates whether the Ambient Air Quality Standard (AAQS) implemented in 2012 in China contributes to green innovation of enterprises, to provide implications for environmental protection and public health. By using panel data of Chinese A-share listed companies from 2008 to 2020, this study adopts the difference-in-difference model to analyze the policy impact of environmental regulation on green innovation of enterprises and its internal mechanism. The results show that AAQS has significantly improved the green innovation of enterprises. Furthermore, AAQS affects the green innovation of enterprises by virtue of two mechanism paths: compliance cost effect and innovation offset effect. On the one hand, AAQS leads to an increase in production costs of enterprises, thus inhibiting green innovation activities of enterprises. On the other hand, AAQS encourages enterprises to increase R&D investment in green technology, thus enhancing their green innovation. In addition, the impact of AAQS on firms' green innovation has heterogeneous characteristics. Our findings not only enrich the studies of environmental regulation and green innovation of enterprises but also provide policymakers in China and other developing countries with implications for environmental protection and public health improvement.

Current Status of Phage Therapy against Infectious Diseases and Potential Application beyond Infectious Diseases.

Intestinal microbiota plays a key role in regulating the pathogenesis of human disease and maintaining health. Many diseases, mainly induced by bacteria, are on the rise due to the emergence of antibiotic-resistant strains. Intestinal microorganisms include organisms such as bacteria, viruses, and fungi. They play an important role in maintaining human health. Among these microorganisms, phages are the main members of intestinal viromes. In particular, the viral fraction, composed essentially of phages, affects homeostasis by exerting selective pressure on bacterial communities living in the intestinal tract. In recent years, with the widespread use and even abuse of antibacterial drugs, more and more drug-resistant bacteria have been found, and they show a trend of high drug resistance and multidrug resistance. Therefore, it has also become increasingly difficult to treat serious bacterial infections. Phages, a natural antibacterial agent with strong specificity and rapid proliferation, have come back to the field of vision of clinicians and scholars. In this study, the current state of research on intestinal phages was discussed, with an exploration of the impact of phage therapy against infectious diseases, as well as potential application beyond infectious diseases.

Market sentiment to COVID ‐19 and the Chinese stock market

We classify the market sentiment to COVID-19 into expected and unexpected components and then examine their particular impacts on the stock market. We find that unexpected sentiment causes fluctuations in the stock market more than expected sentiment does. However, unexpected sentiment cannot affect stock market informativeness despite the remarkable informational effect of expected sentiment. Moreover, the relation between expected sentiment and stock market fluctuation or informativeness is one-way, whereas there exists a two-way interaction between unexpected sentiment and stock market fluctuation. This further confirms that expected sentiment is informational, whereas unexpected sentiment is quite noisy and informationally harmful.

An ultra-sensitive and specific nanoplasmonic-enhanced isothermal amplification platform for the ultrafast point-of-care testing of SARS-CoV-2.

The novel mutations attributed by the high mutagenicity of the SARS-CoV-2 makes its prevention and treatment challenging. Developing an ultra-fast, point-of-care-test (POCT) protocol is critical for responding to large-scale spread of SARS-CoV-2 in public places and in resource-poor remote areas. Here, we developed a nanoplasmonic enhanced isothermal amplification (NanoPEIA) strategy that combines a nanoplasmonic sensor with isothermal amplification. The novel strategy provides an ideal easy-to operate detection platform for obtaining accurate, ultra-fast and high-throughput (96 samples can be tested together) data. For clinical samples with viral detection at Ct value <25, the entire process (including sample preparation, virus lysis, detection, and data analysis) can be completed within six minutes. The method is also appropriate for detection of SARS-CoV-2 γ-coronavirus mutants. The NanoPEIA method was validated using clinical samples from 21 patients with SARS-CoV-2 infection and 31 healthy individuals. The detection result on the 52 clinical samples for SARS-CoV-2 showed that the NanoPEIA platform had a 100% sensitivity for N and orf1ab genes, which was higher than those obtained using RT-qPCR (88.9% and 90.0%, respectively). The specificities of 31 clinical negative samples were 92.3% and 91.7% for the N gene and the orf1ab gene, respectively. The limits of detection (LoD) of the clinical samples were 28.3 copies/mL and 23.3 copies/mL for the N gene and the orf1ab gene, respectively. The efficient NanoPEIA detection strategy facilitates real-time detection and visualization within ultrashort durations and can be applied for POCT diagnosis in resource-poor and highly populated areas.

The impact of COVID-19 on commodity options market: Evidence from China.

Considering the severe economic impact of COVID-19, this study examines COVID-19's influence on the Chinese commodity market. The literature shows that COVID-19's influence in China during its abatement period has not been well investigated. We address this issue by the intraday analysis of the volatility from 16 commodity options contracts in the Chinese commodity options market over the period 2019-2021. We demonstrate that while the pandemic eased in China after its initial outbreak, it still significantly affected the volatility of Chinese agricultural commodities options. In contrast, its impacts on the volatility of options for petrochemicals, ores, and metals are negligible. This pattern reflects the role of pandemic-led supply disruptions affecting agricultural commodity prices as necessities, contributing to higher price volatility relative to non-agricultural commodities, which are less volatile.

Risks factors for virus shedding period of COVID-19 in maintenance hemodialysis patients: a retrospective cohort study (preprint)

Objective This study aimed to describe the clinical features of maintenance hemodialysis (MHD)patients with COVID-19 and potential factors related to the time to return negative RT-PCR in discharged.Methods Retrospective analysis was performed on the clinical data of 90 MHD patients and 134 non-dialysis patients who infected with COVID-19 and admitted to our hospital from 1 April 2022 to 10 June 2022.Results The average age of the MHD patients with COVID-19 was 64.8 ± 12.9 years old and 59.3% patients were males. 12.2% MHD patients with COVID-19 were admitted to ICU and they had higher levels of WBC, neutrophils and procalcitonin(PCT)(P < 0.05) and more symptoms of nausea or vomiting at admission(P = 0.0003). The mean lengths of time from positive to two consecutive negative COVID-19 PCR was 18.15 ± 6.37 days in discharged MHD patients and 11.18 ± 3.52 days in non-dialysis patients(P < 0.0001). Discharged MHD patients with hypertension and DM need obviously longer time to negative than without comorbid disease(21.33 ± 7.03 days vs 16.47 ± 3.6, P = 0.0194). Longer time to negative PCR was associated with lower level of Ct-ORF1ab RNA and Ct-N RNA at admission (R2 = 0.05958, P = 0.0291; R2 = 0.06719, P = 0.0202) in MHD patients.Conclusion MHD patients with COVID-19 had a high probability of admitting to ICU and the level of inflammatory indicators were critical factors. It takes a week longer for MHD patients to return negative PCR than non-dialysis patients. MHD patients combined with hypertension and DM, lower level of Ct- RNA need longer SARS-CoV-2 RNA clearance time than others.

Adaptive consensus building in emergency group decision-making with hesitant fuzzy linguistic information: a perspective based on disappointment theory

In this article, an adaptive consensus model that considers individual disappointment emotion is proposed for emergency multi-attribute group decision-making (MAGDM) problems with hesitant fuzzy linguistic information. Subsequently, it is applied to choose the optimal emergency alternative(s) for the prevention and control of COVID-19 on a college campus. The main innovations and contributions of this article are as follows: (a) Individual modified perceived utility (MPU) based on disappointment theory is integrated into the determination of attribute weights and construction of consensus reaching process (CRP). (b) The MPU-based individual contribution degree and the MPU-based soft group consensus degree are developed. (c) The new emergency CRP mechanism not only considers the rewards and penalties of expert weights but also regards the adaptive updating of attribute weights. Compared with the existing emergency MAGDM models in a hesitant fuzzy linguistic environment, the proposed consensus model has some advantages in improving consensus efficiency and simulating uncertain psychological behavior.

Novel nanostructure-coupled biosensor platform for one-step high-throughput quantification of serum neutralizing antibody after COVID-19 vaccination.

COVID-19 vaccination efficacy depends on serum levels of the neutralizing antibodies (NAs) specific to the receptor-binding domain of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. Therefore, a high-throughput rapid assay capable of measuring the total SARS-CoV-2 NA level is urgently needed for COVID-19 serodiagnosis, convalescent plasma therapy, vaccine development, and assessment. Here, we developed a novel nanoplasmonic immunosorbent assay (NanoPISA) platform for one-step rapid quantification of SARS-CoV-2 NAs in clinical serum samples for high-throughput evaluation of COVID-19 vaccine effectiveness. The NanoPISA platform enhanced by the use of nanoporous hollow gold nanoparticle coupling was able to detect SARS-CoV-2 NAs with a limit of detection of 0.2 pM within 15 min without washing steps. The one-step NanoPISA for SARS-CoV-2 NA detection in clinical specimens yielded good results, comparable with those obtained in the gold-standard seroneutralization test and the surrogate virus-neutralizing enzyme-linked immunosorbent assay. Collectively, the one-step NanoPISA might be a rapid and high-throughput NA-quantification platform for evaluating the effectiveness of COVID-19 vaccines.