Reevaluating the risk minimization utility of Islamic stocks and bonds (Sukuk) in international financial markets

We examine the risk minimization utility of Islamic stock and Sukuk (bond) indices by studying their linkages against traditional global counterparts. We first employ an asymmetric power ARCH-based ADCC model on an extended dataset employed by Kenourgios et al. (2016). Our sample ranges from July 2007 to June 2021 covering the Global Financial Crisis (GFC), the European Sovereign Debt Crisis (ESDC), and the COVID-19 pandemic. Econometric tests suggest strong evidence of coupling in the bulk of Islamic equity indices. A handful of emerging market indices constitute exceptions. Qualitatively similar results emerge from time–frequency analysis via wavelet tools, revealing pervasive coupling in both returns and volatility series. The linkages are scale-dependent in only a few pairs. In contrast, Sukuk indices are uncoupled from their global fixed income counterparts and relevant risky debt portfolios. In sum, the risk-return characteristics of Islamic equities (especially in developed economies) remain coupled to major global benchmarks and therefore are unlikely to appeal as safe haven candidates. The converse applies to Sukuk, which promises potential portfolio diversification benefits and safe haven status in ‘normal' and crisis periods.

Comprehensive Bioinformatics analysis of angiotensin-converting enzyme 2 (ACE2) (preprint)

ACE2, a member of the angiotensin converting enzyme family, plays an irreplaceable role in the renin-angiotensin system. And the variations of ACE2 are regarded as the key factor to human diseases such as the novel coronavirus pneumonia, cardiovascular disease, and tumors. Here, we summarized the mutation, expression, modification and function of the human ACE2 based on comprehensive bioinformatics analysis. Especially, the relationship between ACE2 expression and diseases, especially tumor was further discussed. ACE2 is highly conserved in different genera and families. We explored the correlation between ACE2 and disease based on the datasets of GCBI and GEO (Gene expression omnibus), and found the expression of ACE2 is related to heart failure. High prevalence of ACE2 mutations is observed in diffuse large B-cell lymphoma, uterine carcinosarcoma (UCS), and stomach adenocarcinoma (STAD). We first identified that highly expressed of ACE2 was linked to poor prognosis of overall survival for tumors of brain lower grade glioma (LGG). Specially, the expression level of ACE2 in kidney-related tumor tissues is much higher than that of normal kidney tissues. ACE2 is negatively correlated with the infiltration level of cancer-associated fibroblasts in most kinds of cancers, such as uterine corpus endometrial carcinoma (UCEC), esophageal carcinoma (ESCA), ovarian serous cystadenocarcinoma (OV) and kidney renal clear cell carcinoma (KIRC); positively correlation in testicular germ cell tumors (TGCT). The different phosphorylation sites of ACE2 were analyzed in CPTAC dataset, and the DNA methylation of ACE2 in colon adenocarcinoma (COAD), kidney renal papillary cell carcinoma (KIRP), and rectum adenocarcinoma (READ) was lower than that of normal control by using SMART database. Moreover, we summarized the interaction proteins and targeted miRNAs of ACE2 through bioinformatics. Then we found the endocrine process and the regulation of systemic arterial blood pressure were involved in the functional mechanisms of ACE2 by using KEGG and GO analysis. Our study offers a relatively comprehensive understanding of ACE2.

End-to-End Stochastic Optimization with Energy-Based Model (preprint)

Decision-focused learning (DFL) was recently proposed for stochastic optimization problems that involve unknown parameters. By integrating predictive modeling with an implicitly differentiable optimization layer, DFL has shown superior performance to the standard two-stage predict-then-optimize pipeline. However, most existing DFL methods are only applicable to convex problems or a subset of nonconvex problems that can be easily relaxed to convex ones. Further, they can be inefficient in training due to the requirement of solving and differentiating through the optimization problem in every training iteration. We propose SO-EBM, a general and efficient DFL method for stochastic optimization using energy-based models. Instead of relying on KKT conditions to induce an implicit optimization layer, SO-EBM explicitly parameterizes the original optimization problem using a differentiable optimization layer based on energy functions. To better approximate the optimization landscape, we propose a coupled training objective that uses a maximum likelihood loss to capture the optimum location and a distribution-based regularizer to capture the overall energy landscape. Finally, we propose an efficient training procedure for SO-EBM with a self-normalized importance sampler based on a Gaussian mixture proposal. We evaluate SO-EBM in three applications: power scheduling, COVID-19 resource allocation, and non-convex adversarial security game, demonstrating the effectiveness and efficiency of SO-EBM.

The influence of professional identity, job satisfaction, burnout on turnover intention among village public health service providers in China in the context of COVID-19: A cross-sectional study

Background In China, COVID-19 has undoubtedly posed a huge challenge to the capacity of rural public health services. Village public health service providers are responsible for reporting and dealing with infectious diseases and public health emergencies. However, the turnover of village public health service providers is gravely threatening the stability of rural primary health system step by step. This study systematically evaluated the effects of professional identity, job satisfaction, burnout on turnover intention of village public health service providers, and further measured the mediating effect of job satisfaction and burnout between professional identity and turnover intention. Methods From May to June 2019, 1,244 village public health service providers in Shandong Province were selected as the research objects. Sociodemographic characteristics, professional identity, job satisfaction, burnout and turnover intention were quantitated by self-completed questionnaire and measured by Likert 5–7 scale. Person correlation analysis, One-way ANOVA, and Structural Equation Modeling (SEM) were used for statistical analysis and mediating effect evaluation. Results Five hundred and sixty-four (45.3%) village public health providers had high turnover intension. Professional identity had a direct positive effect on job satisfaction (β = 0.146, p < 0.001), job satisfaction had a direct negative effect on burnout (β = 0.263, p < 0.001), and turnover intension (β = −0.453, p < 0.001), while burnout had a direct positive effect on turnover intension (β = 0.242, p < 0.001). Between professional identity and turnover intention, job satisfaction 95%CI: (−0.289)–(−0.11) had significant mediating effects. Job satisfaction 95%CI: (−0.216)–(−0.077) also had significant mediating effects between professional identity and burnout, and burnout had significant mediating effects between job satisfaction and turnover intension, 95%CI: (−0.116)–(−0.052). These results strongly confirm that professional identity, job satisfaction, and burnout are early and powerful predicators of turnover intention. Conclusion According to the results, medical administration and management departments should pay attention to improve the professional attraction of public health services by improving the public's understanding of the profession, reducing work intensity, timely granting of subsidy funds, improving old-age security, ensuring the income level, increasing the new force and so on, so as to reduce turnover intension and ensure the health equity of village residents.

Spatial–Temporal Urban Mobility Pattern Analysis During COVID-19 Pandemic

In response to the repeated outbreaks of the COVID-19, many countries implement the region-specific, multilevel epidemic prevention and control policies. To fully understand the impact of these interventions on urban mobility, it is urgent to analyze spatial-temporal mobility pattern at the neighborhood level and structural changes in urban mobility networks. Here, we construct urban mobility networks among points of interest (POIs), using large-scale anonymous mobility data from de-identified mobile phone users. We comprehensively investigate the changes of urban mobility networks during two waves of the COVID-19 pandemic in Beijing from both graph and subgraph perspectives. Beyond an overall mobility reduction in Beijing, we find that the mobility change is spatially and temporally heterogeneous among different urban regions. We uncover a disproportionately large reduction in long-distance, nighttime, and non-essential travel. This results in a more geographically fragmented, local, and regional network in the pandemic. We demonstrate that these structural changes slow down the spatial spread of the COVID-19 in the mobility network.

Therapeutic Benefits of Mesenchymal Stem Cells in Acute Respiratory Distress Syndrome: Potential Mechanisms and Challenges

Acute respiratory distress syndrome (ARDS) presents as a form of acute respiratory failure resulting from non-cardiogenic pulmonary edema due to excessive alveolocapillary permeability, which may be pulmonary or systemic in origin. In the last 3 years, the coronavirus disease 2019 pandemic has resulted in an increase in ARDS cases and highlighted the challenges associated with this syndrome, as well as the unacceptably high mortality rates and lack of effective treatments. Currently, clinical treatment remains primarily supportive, including mechanical ventilation and drug-based therapy. Mesenchymal stem cell (MSC) therapies are emerging as a promising intervention in patients with ARDS and have promising therapeutic effects and safety. The therapeutic mechanisms include modifying the immune response and assisting with tissue repair. This review provides an overview of the general properties of MSCs and outlines their role in mitigating lung injury and promoting tissue repair in ARDS. Finally, we summarize the current challenges in the study of translational MSC research and identify avenues by which the discipline may progress in the coming years.

Variations in Sulfur and Nitrogen Oxidation Rates in Summer Aerosols from 2014 to 2020 in Wuhan, China

To date, research regarding the changes of the sulfur and nitrogen rates in Wuhan during the summer is limited. In this study, we analyzed the air quality in Wuhan, China, using water-soluble ion, gaseous precursor, and weather data. A Spearman correlation analysis was then performed to investigate the temporal changes in air quality characteristics and their driving factors to provide a reference for air pollution control in Wuhan. The results indicate that SO2 in the atmosphere at Wuhan undergoes secondary conversion and photo-oxidation, and the conversion degree of SO2 is higher than that of NO2. During the summers of 2016 and 2017, secondary inorganic atmospheric pollution was more severe than during other years. The fewest oxidation days occurred in summer 2020 (11 days), followed by the summers of 2017 and 2014 (25 and 27 days, respectively). During the study period, ion neutralization was the strongest in summer 2015 and the weakest in August 2020. The aerosols in Wuhan were mostly acidic and NH4+ was an important neutralizing component. The neutralization factors of all cations showed little change in 2015. K+, Mg2+, and Ca2+ level changes were the highest in 2017 and 2020. At low temperature, high humidity, and low wind speed conditions, SO2 and NO2 were more easily converted into SO42− and NO3−.

Corporate philanthropic giving and nature of stock market reaction: Evidence from China: MDE

This study examines whether enterprises can obtain abnormal returns through philanthropic giving during public health emergencies, such as the COVID‐19 crisis, by using an event study approach to conduct an empirical analysis. The results show that if enterprises participate in philanthropic giving during the COVID‐19 crisis, they can obtain abnormal returns in the stock market. The extent of this market reaction is directly proportional to the level of philanthropic giving, and it is more significant for private enterprises, enterprises in regions that are more affected by the epidemic, enterprises in social responsibility sensitive industries, and enterprises with more timely donations.

Synthetic Biology-Powered Biosensors Based on CRISPR/Cas Mediated Cascade Signal Amplification for Precise RNA Detection

Synthetic biology enabling technologies have been harnessed to create new diagnostic technologies. However, most strategies involve error-prone amplification steps and limitations of accuracy in RNA detection. Here, a cell-free synthetic biology-powered biosensing strategy, termed as SHARK (Synthetic Enzyme Shift RNA Signal Amplifier Related Cas13a Knockdown Reaction), could efficiently and accurately amplify RNA signal by leveraging the collateral cleavage of activated Cas13a to regulate cell-free enzyme synthesis. Based on cascade amplification and tailored enzyme output, SHARK behaves broad compatibility in different scenarios. The portable device based on SHARK was successfully used as SARS-CoV-2 biosensors with high sensitivity and selectivity, and the results were highly consistent with Ct values of qRT-PCR. In addition, when combined with machine learning, SHARK performs bio-computations and thus for cancer diagnosis and staging based on 64 clinical samples. SHARK shows characteristics of precise recognition, cascade amplification and tailored signal outputting comparisons with established assays, presenting significant potential in developing next-generation RNA detection technology.

Pulmonary and Renal Long COVID at Two-year Revisit (preprint)

More than 450 million individuals have recovered from COVID-19, but little is known about the host responses to long COVID. We performed proteomic and metabolomic analyses of 991 blood and urine specimens from 144 COVID-19 patients with comprehensive clinical data and up to 763 days of follow up. Our data showed that the lungs and kidneys are the most vulnerable organs in long COVID patients. Pulmonary and renal long COVID of one-year revisit can be predicted by a machine learning model based on clinical and multi-omics data collected during the first month from the disease onset with an ACC of 87.5%. Serum protein SFTPB and ATR were associated with pulmonary long COVID and might be potential therapeutic targets. Notably, our data show that all the patients with persistent pulmonary ground glass opacity or patchy opacity lesions developed into pulmonary fibrosis at two-year revisit. Together, this study depicts the longitudinal clinical and molecular landscape of COVID-19 with up to two-year follow-up and presents a method to predict pulmonary and renal long COVID.

An mRNA vaccine candidate for the SARS-CoV-2 Omicron variant (preprint)

The newly emerged Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contains more than 30 mutations on the spike protein, 15 of which are located within the receptor binding domain (RBD). Consequently, Omicron is able to extensively escape existing neutralizing antibodies and may therefore compromise the efficacy of current vaccines based on the original strain, highlighting the importance and urgency of developing effective vaccines against Omicron. Here we report the rapid generation and evaluation of an mRNA vaccine candidate specific to Omicron. This mRNA vaccine encodes the RBD of Omicron (designated RBD-O) and is formulated with lipid nanoparticle. Two doses of the RBD-O mRNA vaccine efficiently induce neutralizing antibodies in mice; however, the antisera are effective only on the Omicron variant but not on the wildtype and Delta strains, indicating a narrow neutralization spectrum. It is noted that the neutralization profile of the RBD-O mRNA vaccine is opposite to that observed for the mRNA vaccine expressing the wildtype RBD (RBD-WT). Our work demonstrates the feasibility and potency of an RBD-based mRNA vaccine specific to Omicron, providing important information for further development of bivalent or multivalent SARS-CoV-2 vaccines with broad-spectrum efficacy.

Study on the performance condition and impact mechanism of tourism system vulnerability under the impact of COVID-19: analysis of tourism data of the Chinese Spring Festival holiday in 2020

In order to study the impact degree of tourism system of the Spring Festival holiday in China under the impact of the COVID-19, this article establishes the concept and theory of performance vulnerability of a system by using the concept of vulnerability in the measurement of the effect degree of a system under the impact of disturbance factors. Combined with AHP and compositive evaluation method, we set up a vulnerability evaluation index system of tourism system to measure the index of performance vulnerability of the tourism system and its subsystems under the impact of the COVID-19, and discuss the impact mechanism model of the COVID-19 on the tourism system during the Spring Festival. The research shows that: the index of performance vulnerability of the tourism system in Spring Festival holiday is 0.6560, which reaches high vulnerability;the index of tourist market system is 0.7250, which reaches high vulnerability;the index of transportation system is 0.6930, which reaches high vulnerability;the index of central tourism enterprise system is 0.8714, which reaches severe vulnerability;the index of destination system is 0.8024, which reaches severe vulnerability;The index of support system is 0.1368, which reaches slight vulnerability.

Habit Formation of Preventive Behaviours during the COVID-19 Pandemic: A Longitudinal Study of Physical Distancing and Hand Washing (preprint)

Introduction: Since the outbreak of the COVID-19 pandemic, physical distancing and hand washing have been used as effective means to reduce virus transmission in the Netherlands. However, they pose a societal challenge as they require people to change their customary behaviours in various contexts. The science of habit formation is potentially useful for informing policy-making in public health, but the current literature largely overlooked the role of habit in predicting and explaining these preventive behaviours. Our research aimed to describe habit formation processes of physical distancing and hand washing and to estimate the influences of habit strength and intention on behavioural adherence. Methods: A longitudinal survey was conducted between July and November 2020 on a representative Dutch sample (n = 800). Respondents reported weekly their intention, habit strength, and actual adherence regarding six context-specific behaviours. Temporal developments of the measured variables were visualized, quantified, and mapped to five distinct phases of the pandemic. Regression models were used to test the effects of intention, habit strength, and their interaction on future adherence. Results: Dutch respondents generally had strong intention to adhere to all preventive measures and their actual adherence rates were between 70% and 90%. They also self-reported to experience their behaviours as more automatic over time, and this increasing trend in habit strength was more evident for physical distancing than hand washing behaviours. For all six behaviours, both intention and habit strength predicted future adherence (all ps < 2e-16). In addition, the predictive power of intention decreased over time and was weaker for respondents with strong habits for physical distancing when visiting supermarket (B = -0.63, p < .0001) and having guests at home (B = -0.54, p < .0001) in the later phases of the study, but not for hand washing. Conclusions: People’s adaptation to physical distancing and hand washing involves both intentional and habitual processes. For public health management, our findings highlight the importance of using contextual cues to promote habit formation, especially for maintaining physical distancing practice. For habit theories, our study provides a unique data set that covers multiple health behaviours in a critical real-world setting.

Molecular basis of SARS-CoV-2 Omicron variant receptor engagement and antibody evasion and neutralization (preprint)

The SARS-CoV-2 Omicron variant exhibits striking immune evasion and is spreading globally at an unprecedented speed. Understanding the underlying structural basis of the high transmissibility and greatly enhanced immune evasion of Omicron is of high importance. Here through cryo-EM analysis, we present both the closed and open states of the Omicron spike, which appear more compact than the counterparts of the G614 strain, potentially related to the Omicron substitution induced enhanced protomer-protomer and S1-S2 interactions. The closed state showing dominant population may indicate a conformational masking mechanism of immune evasion for Omicron spike. Moreover, we capture two states for the Omicron S/ACE2 complex with S binding one or two ACE2s, revealing that the substitutions on the Omicron RBM result in new salt bridges/H-bonds and more favorable electrostatic surface properties, together strengthened interaction with ACE2, in line with the higher ACE2 affinity of the Omicron relative to the G614 strain. Furthermore, we determine cryo-EM structures of the Omicron S/S3H3 Fab, an antibody able to cross-neutralize major variants of concern including Omicron, elucidating the structural basis for S3H3-mediated broad-spectrum neutralization. Our findings shed new lights on the high transmissibility and immune evasion of the Omicron variant and may also inform design of broadly effective vaccines against emerging variants.

Development and Performance verification of colloidal gold labeled SARS-CoV-2 antigen detection method for routine popular screening of COVID-19 with clinical samples in Poland and China (preprint)

In this research, we have constructed and optimized the colloidal gold labeled lateral flow strip (LFS) for rapid detection of antigen of SARS-CoV-2 and rapid screening of COVID-19. Based on the constructed and optimized colloidal gold lateral flow strip, the parameters of the LFS have been well evaluated with the clinical samples in the professional labs. The screening performance have also been evaluated from the aspects including the CT values, age distribution and onset of symptoms. Finally, based on the detection results of 420 clinical samples, the LFS can achieve the screening of COVID-19 with the positive percentage agreement (PPA, sensitivity), negative percent agreement (NPA, specificity), the positive predictive value (PPV) and the negative predictive value (NPV) of 96.8%, 100%, 100% and 96.6%, respectively, indicating the powerful potential for practical screening applications in pandemic control. Of great significance, this developed SARS-CoV-2 antigen detection method has also been successfully utilized for screening of delta-variant of SARS-CoV-2.

The impact of COVID-19 epidemic on the control of important parasitic diseases

The spread of COVID-19 has increased the risk of contact transmission between people, and imposes challenges and opportunities for the prevention and control of important parasitic diseases. There may be risks of COVID-19 infection during the implementation of the virus control, including in field investigation and intervention, contacting with fecal samples, or with asymptomatic infected people. Therefore, corresponding prevention and control measures should be taken before and during field investigation, and in sample transportation and detection to prevent the risks effectively. In this paper, the risks and corresponding countermeasures in the above processes are discussed in detail, and the opportunities that COVID-19 brought to the disease control system are also analyzed.

Human Mesenchymal Stem Cells Treatment for Severe COVID-19: 1-Year Follow-Up Results of a Randomized, Double-Blind, Placebo-Controlled Trial (preprint)

Background The long-term consequences of human umbilical cord-derived mesenchymal stem cell (UC-MSC) treatment for COVID-19 patients are yet to be reported. This study assessed the 1-year outcomes in patients with severe COVID-19, who were recruited in our previous UC-MSC clinical trial.Methods: In this prospective, longitudinal, cohort study, 100 patients enrolled in our phase 2 trial were prospectively followed up at 3-month intervals for 1 year to evaluate the long-term safety and effectiveness of UC-MSC treatment. The primary endpoint was an altered proportion of whole-lung lesion volumes measured by high-resolution CT. Other imaging outcomes, 6-minute walking distance (6-MWD), lung function, plasma biomarkers, and adverse events were also recorded and analyzed. This trial was registered with ClinicalTrials.gov (NCT04288102).Findings: Within 3 months, MSC administration exerted numerical improvement in whole-lung lesion volume compared with the placebo, leading to a significant difference of −10.82% (95% CI: −20.69%, −1.46%, P=0.030) on day 10. MSC also reduced the proportion of solid component lesion volume compared with the placebo at each follow-up point, with a significant difference of − 9.02% (95%CI: − 17.44%, − 0.10%, P=0.045) at month 9. More interestingly, 17.86% (10/56) of patients in the MSC group had normal CT images at month 12 ( P= 0.013), but none in the placebo group. The incidence of symptoms was lower in the MSC group than in the placebo group at each follow-up time, particularly sleep difficulties at month 3 (OR 0.19, 95% CI 0.07,0.50; P=0.001), and usual activity at month 12 (OR 0.15, 95% CI 0.03,0.79; P=0.018). Neutralizing antibodies were all positive, with a similar median inhibition rate (61.6% vs. 67.55%) in both groups at month 12. No difference in adverse events at the 1-year follow-up and tumor markers at month 12 were observed between the two groups.Interpretation: UC-MSC administration achieves a long-term benefit in the recovery of lung lesions and symptoms in COVID-19 patients.Trial Registration: This trial was registered with ClinicalTrials.gov (NCT04288102).Funding The National Key R&D Program of China, the Innovation Groups of the National Natural Science Foundation of China, and the National Science and Technology Major Project.Declaration of Interest: None to declare. Ethical Approval: This study was approved by the Ethics Committee of the Fifth Medical Center, Chinese PLA General Hospital (2020-013-D).

Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection. (preprint)

We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection ( ACE2, TMPRSS2, DPP4 , and LY6E ). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2 , we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2 , we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.