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1.
Hum Vaccin Immunother ; : 1-11, 2022 Jan 21.
Article in English | MEDLINE | ID: covidwho-1642249

ABSTRACT

Genetic optimization of Nucleic Acid immunogens is important for potentially improving their immune potency. A COVID-19 DNA vaccine is in phase III clinical trial which is based on a promising highly developable technology platform. Here, we show optimization in mice generating a pGX-9501 DNA vaccine encoding full-length spike protein, which results in induction of potent humoral and cellular immune responses, including neutralizing antibodies, that block hACE2-RBD binding of live CoV2 virus in vitro. Optimization resulted in improved induction of cellular immunity by pGX-9501 as demonstrated by increased IFN-γ expression in both CD8+ and CD4 + T cells and this was associated with more robust antiviral CTL responses compared to unoptimized constructs. Vaccination with pGX-9501 induced subsequent protection against virus challenge in a rigorous hACE2 transgenic mouse model. Overall, pGX-9501 is a promising optimized COVID-19 DNA vaccine candidate inducing humoral and cellular immunity contributing to the vaccine's protective effects.

2.
Int J Biol Macromol ; 200: 487-497, 2022 Jan 20.
Article in English | MEDLINE | ID: covidwho-1634879

ABSTRACT

Virus-like particles (VLPs) are nano-scale particles that are morphologically similar to a live virus but which lack a genetic component. Since the pandemic spread of COVID-19, much focus has been placed on coronavirus (CoV)-related VLPs. CoVs contain four structural proteins, though the minimum requirement for VLP formation differs among virus species. CoV VLPs are commonly produced in mammalian and insect cell systems, sometimes in the form of chimeric VLPs that enable surface display of CoV epitopes. VLPs are an ideal model for virological research and have been applied as vaccines and diagnostic reagents to aid in clinical disease control. This review summarizes and updates the research progress on the characteristics of VLPs from different known CoVs, mainly focusing on assembly, in vitro expression systems for VLP generation, VLP chimerism, protein-based nanoparticles and their applications in basic research and clinical settings, which may aid in development of novel VLP vaccines against emerging coronavirus diseases such as SARS-CoV-2.

3.
Psychol Med ; : 1-6, 2021 Aug 10.
Article in English | MEDLINE | ID: covidwho-1599105

ABSTRACT

BACKGROUND: Self-efficacy is a pivotal factor in the etiology and prognosis of major depression. However, longitudinal studies on the relationship between self-efficacy and major depressive disorder (MDD) are scarce. The objectives were to investigate: (1) the associations between self-efficacy and the 1-year and 2-year risks of first onset of MDD and (2) the associations between self-efficacy and the 1-year and 2-year risks of the persistence/recurrence of MDD, in a sample of first-year university students. METHODS: We followed 8079 first-year university students for 2 years from April 2018 to October 2020. MDD was ascertained by the Chinese version of the Composite International Diagnostic Interview (CIDI-3.0) based on self-report. Self-efficacy was measured by the 10-item General Self-efficacy (GSE) scale. Random effect logistic regression modeling was used to estimate the associations. RESULTS: Among participants without a lifetime MDD, the data showed that participants with high baseline GSE scores were associated with a higher risk of first onset of MDD over 2 years [odds ratio (OR) 1.04, 95% confidence interval (CI) 1.01-1.08]. Among those with a lifetime MDD, participants with high baseline GSE scores were less likely to have had a MDD over 2 years (OR 0.93, 95% CI 0.88-0.99) compared to others. CONCLUSIONS: A high level of GSE may be protective of the risk of persistent or recurrent MDD. More longitudinal studies in university students are needed to further investigate the impact of GSE on the first onset of MDD.

4.
Journal of Transportation Safety & Security ; : 1-21, 2021.
Article in English | Taylor & Francis | ID: covidwho-1585296
5.
Mol Biomed ; 2(1): 29, 2021 Sep 27.
Article in English | MEDLINE | ID: covidwho-1515465

ABSTRACT

In the face of the emerging variants of SARS-CoV-2, there is an urgent need to develop a vaccine that can induce fast, effective, long-lasting and broad protective immunity against SARS-CoV-2. Here, we developed a trimeric SARS-CoV-2 S protein vaccine candidate adjuvanted by PIKA, which can induce robust cellular and humoral immune responses. The results showed a high level of neutralizing antibodies induced by the vaccine was maintained for at least 400 days. In the study of non-human primates, PIKA adjuvanted S-trimer induced high SARS-CoV-2 neutralization titers and protected from virus replication in the lung following SARS-CoV-2 challenge. In addition, the long-term neutralizing antibody response induced by S-trimer vaccine adjuvanted by PIKA could neutralize multiple SARS-CoV-2 variants and there is no obvious different among the SARS- CoV-2 variants of interest or concern, including B.1.351, B.1.1.7, P.1, B.1.617.1 and B.1.617.2 variants. These data support the utility of S-trimer protein adjuvanted by PIKA as a potential vaccine candidate against SARS-CoV-2 infection.

6.
Signal Transduct Target Ther ; 6(1): 387, 2021 11 09.
Article in English | MEDLINE | ID: covidwho-1510581

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). To halt the pandemic, multiple SARS-CoV-2 vaccines have been developed and several have been allowed for emergency use and rollout worldwide. With novel SARS-CoV-2 variants emerging and circulating widely, whether the original vaccines that were designed based on the wild-type SARS-CoV-2 were effective against these variants has been a contentious discussion. Moreover, some studies revealed the long-term changes of immune responses post SARS-CoV-2 infection or vaccination and the factors that might impact the vaccine-induced immunity. Thus, in this review, we have summarized the influence of mutational hotspots on the vaccine efficacy and characteristics of variants of interest and concern. We have also discussed the reasons that might result in discrepancies in the efficacy of different vaccines estimated in different trials. Furthermore, we provided an overview of the duration of immune responses after natural infection or vaccination and shed light on the factors that may affect the immunity induced by the vaccines, such as special disease conditions, sex, and pre-existing immunity, with the aim of aiding in combating COVID-19 and distributing SARS-CoV-2 vaccines under the prevalence of diverse SARS-CoV-2 variants.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , Humans , Immunogenicity, Vaccine , Pandemics , SARS-CoV-2/genetics , Vaccination
7.
Front Pharmacol ; 12: 770125, 2021.
Article in English | MEDLINE | ID: covidwho-1512052

ABSTRACT

[This corrects the article DOI: 10.3389/fphar.2021.668407.].

8.
Signal Transduct Target Ther ; 6(1): 290, 2021 Aug 02.
Article in English | MEDLINE | ID: covidwho-1344903

ABSTRACT

Emerging evidence suggests that liquid-liquid phase separation (LLPS) represents a vital and ubiquitous phenomenon underlying the formation of membraneless organelles in eukaryotic cells (also known as biomolecular condensates or droplets). Recent studies have revealed evidences that indicate that LLPS plays a vital role in human health and diseases. In this review, we describe our current understanding of LLPS and summarize its physiological functions. We further describe the role of LLPS in the development of human diseases. Additionally, we review the recently developed methods for studying LLPS. Although LLPS research is in its infancy-but is fast-growing-it is clear that LLPS plays an essential role in the development of pathophysiological conditions. This highlights the need for an overview of the recent advances in the field to translate our current knowledge regarding LLPS into therapeutic discoveries.

9.
JAMA Netw Open ; 4(9): e2127403, 2021 09 01.
Article in English | MEDLINE | ID: covidwho-1441917

ABSTRACT

Importance: The long-term health outcomes and symptom burden of COVID-19 remain largely unclear. Objective: To evaluate health outcomes of COVID-19 survivors 1 year after hospital discharge and to identify associated risk factors. Design, Setting, and Participants: This retrospective, multicenter cohort study was conducted at 2 designated hospitals, Huoshenshan Hospital and Taikang Tongji Hospital, both in Wuhan, China. All adult patients with COVID-19 discharged between February 12 and April 10, 2020, were screened for eligibility. Of a consecutive sample of 3988 discharged patients, 1555 were excluded (796 declined to participate and 759 were unable to be contacted) and the remaining 2433 patients were enrolled. All patients were interviewed via telephone from March 1 to March 20, 2021. Statistical analysis was performed from March 28 to April 18, 2021. Exposures: COVID-19. Main Outcomes and Measures: All patients participated in telephone interviews using a series of questionnaires for evaluation of symptoms, along with a chronic obstructive pulmonary disease (COPD) assessment test (CAT). Logistic regression models were used to evaluate risk factors for fatigue, dyspnea, symptom burden, or higher CAT scores. Results: Of 2433 patients at 1-year follow-up, 1205 (49.5%) were men and 680 (27.9%) were categorized into the severe disease group as defined by the World Health Organization guideline; the median (IQR) age was 60.0 (49.0-68.0) years. In total, 1095 patients (45.0%) reported at least 1 symptom. The most common symptoms included fatigue, sweating, chest tightness, anxiety, and myalgia. Older age (odds ratio [OR], 1.02; 95% CI, 1.01-1.02; P < .001), female sex (OR, 1.27; 95% CI, 1.06-1.52; P = .008), and severe disease during hospital stay (OR, 1.43; 95% CI, 1.18-1.74; P < .001) were associated with higher risks of fatigue. Older age (OR, 1.02; 95% CI, 1.01-1.03; P < .001) and severe disease (OR, 1.51; 95% CI, 1.14-1.99; P = .004) were associated with higher risks of having at least 3 symptoms. The median (IQR) CAT score was 2 (0-4), and a total of 161 patients (6.6%) had a CAT score of at least 10. Severe disease (OR, 1.84; 95% CI, 1.31-2.58; P < .001) and coexisting cerebrovascular diseases (OR, 1.95; 95% CI, 1.07-3.54; P = .03) were independent risk factors for CAT scores of at least 10. Conclusions and Relevance: This study found that patients with COVID-19 with severe disease during hospitalization had more postinfection symptoms and higher CAT scores.


Subject(s)
COVID-19/complications , Hospitals , Patient Discharge , Pulmonary Disease, Chronic Obstructive/etiology , Severity of Illness Index , Survivors , Aged , Anxiety/etiology , China , Cities , Dyspnea/etiology , Fatigue/etiology , Female , Hospitalization , Humans , Logistic Models , Male , Middle Aged , Myalgia/etiology , Pandemics , Retrospective Studies , SARS-CoV-2 , Surveys and Questionnaires
10.
BMC Infect Dis ; 21(1): 1012, 2021 Sep 27.
Article in English | MEDLINE | ID: covidwho-1440914

ABSTRACT

BACKGROUND: The receptor of severe respiratory syndrome coronavirus 2 (SARS-CoV-2), angiotensin-converting enzyme 2, is more abundant in kidney than in lung tissue, suggesting that kidney might be another important target organ for SARS-CoV-2. However, our understanding of kidney injury caused by Coronavirus Disease 2019 (COVID-19) is limited. This study aimed to explore the association between kidney injury and disease progression in patients with COVID-19. METHODS: A retrospective cohort study was designed by including 2630 patients with confirmed COVID-19 from Huoshenshan Hospital (Wuhan, China) from 1 February to 13 April 2020. Kidney function indexes and other clinical information were extracted from the electronic medical record system. Associations between kidney function indexes and disease progression were analyzed using Cox proportional-hazards regression and generalized linear mixed model. RESULTS: We found that estimated glomerular filtration rate (eGFR) and creatinine clearance (Ccr) decreased in 22.0% and 24.0% of patients with COVID-19, respectively. Proteinuria was detected in 15.0% patients and hematuria was detected in 8.1% of patients. Hematuria (HR 2.38, 95% CI 1.50-3.78), proteinuria (HR 2.16, 95% CI 1.33-3.51), elevated baseline serum creatinine (HR 2.84, 95% CI 1.92-4.21) and blood urea nitrogen (HR 3.54, 95% CI 2.36-5.31), and decrease baseline eGFR (HR 1.58, 95% CI 1.07-2.34) were found to be independent risk factors for disease progression after adjusted confounders. Generalized linear mixed model analysis showed that the dynamic trajectories of uric acid was significantly related to disease progression. CONCLUSION: There was a high proportion of early kidney function injury in COVID-19 patients on admission. Early kidney injury could help clinicians to identify patients with poor prognosis at an early stage.


Subject(s)
Acute Kidney Injury , COVID-19 , Cohort Studies , Disease Progression , Humans , Kidney , Retrospective Studies , Risk Factors , SARS-CoV-2
11.
Industrial and Organizational Psychology ; 14(3):404-408, 2021.
Article in English | ProQuest Central | ID: covidwho-1434018

ABSTRACT

[...]the authors theoretically separated technology experiences from technology-use behaviors, which in our opinion will constrain our understanding of ICT-related constructs. [...]although the authors draw on a work design perspective to discuss the literature, they overlook the more powerful role of work design theory for understanding ICT-related phenomena in the workplace. [...]the effects of non-work-related ICT use on performance and well-being are jointly influenced by use intensity and functions of ICT use. [...]the widespread use of advanced ICTs in communication makes the invasion of work-related issues into personal life possible, resulting in the demand for constant availability (Mazmanian, 2013). [...]as a consequence of workplace ICT use, constant availability is conceptually different from other long-existing constructs, such as work demands (e.g., workload).

12.
Diabetes Res Clin Pract ; 180: 109041, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1401412

ABSTRACT

AIMS: We aimed to investigate the role of Fasting Plasma Glucose (FPG) and glucose fluctuation in the prognosis of COVID-19 patients stratified by pre-existing diabetes. METHODS: The associations of FPG and glucose fluctuation indexes with prognosis of COVID-19 in 2,642 patients were investigated by multivariate Cox regression analysis. The primary outcome was in-hospital mortality; the secondary outcome was disease progression. The longitudinal changes of FPG over time were analyzed by the latent growth curve model in COVID-19 patients stratified by diabetes and severity of COVID-19. RESULTS: We found FPG as an independent prognostic factor of overall survival after adjustment for age, sex, diabetes and severity of COVID-19 at admission (HR: 1.15, 95% CI: 1.06-1.25, P = 1.02 × 10-3). Multivariate logistic regression analysis indicated that the standard deviation of blood glucose (SDBG) and largest amplitude of glycemic excursions (LAGE) were also independent risk factors of COVID-19 progression (P = 0.03 and 0.04, respectively). The growth trajectory of FPG over the first 3 days of hospitalization was steeper in patients with critical COVID-19 in comparison to moderate patients. CONCLUSIONS: Hyperglycemia and glucose fluctuation were adverse prognostic factors of COVID-19 regardless of pre-existing diabetes. This stresses the importance of glycemic control in addition to other therapeutic management.


Subject(s)
COVID-19 , Diabetes Mellitus , Blood Glucose , Diabetes Mellitus/epidemiology , Fasting , Glucose , Humans , Prognosis , Retrospective Studies , Risk Factors , SARS-CoV-2
13.
BMC Infect Dis ; 21(1): 760, 2021 Aug 05.
Article in English | MEDLINE | ID: covidwho-1403220

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) has spread around the world. This retrospective study aims to analyze the clinical features of COVID-19 patients with cancer and identify death outcome related risk factors. METHODS: From February 10th to April 15th, 2020, 103 COVID-19 patients with cancer were enrolled. Difference analyses were performed between severe and non-severe patients. A propensity score matching (PSM) analysis was performed, including 103 COVID-19 patients with cancer and 206 matched non-cancer COVID-19 patients. Next, we identified death related risk factors and developed a nomogram for predicting the probability. RESULTS: In 103 COVID-19 patients with cancer, the main cancer categories were breast cancer, lung cancer and bladder cancer. Compared to non-severe patients, severe patients had a higher median age, and a higher proportion of smokers, diabetes, heart disease and dyspnea. In addition, most of the laboratory results between two groups were significantly different. PSM analysis found that the proportion of dyspnea was much higher in COVID-19 patients with cancer. The severity incidence in two groups were similar, while a much higher mortality was found in COVID-19 patients with cancer compared to that in COVID-19 patients without cancer (11.7% vs. 4.4%, P = 0.028). Furthermore, we found that neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) were related to death outcome. And a nomogram based on the factors was developed. CONCLUSION: In COVID-19 patients with cancer, the clinical features and laboratory results between severe group and non-severe group were significantly different. NLR and CRP were the risk factors that could predict death outcome.


Subject(s)
COVID-19 , Neoplasms , Adult , Aged , Aged, 80 and over , C-Reactive Protein/analysis , COVID-19/complications , COVID-19/mortality , Female , Humans , Lymphocytes/cytology , Male , Middle Aged , Neoplasms/complications , Neoplasms/mortality , Neutrophils/cytology , Nomograms , Retrospective Studies , Risk Factors , Young Adult
14.
Agricultural & Forest Meteorology ; 308:N.PAG-N.PAG, 2021.
Article in English | Academic Search Complete | ID: covidwho-1397128

ABSTRACT

• Develop a within-growing season yield forecast system with random forest model. • Random forest model performs well in predicting grain yield in China. • We identified the most important stage-specific predictors determining crop yield. • The most important variable influencing yields varied with crop types. Accurate and timely crop yield forecasts can provide essential information to make conclusive agricultural policies and to conduct investments. Recent studies have used different machine learning techniques to develop such yield forecast systems for single crops at regional scales. However, no study has used multiple sources of environmental predictors (climate, soil, and vegetation) to forecast yields for three major crops in China. In this study, we adopted 7-year observed crop yield data (2013–2019) for three major grain crops (wheat, maize, and rice) across China, and three major data sets including climate, vegetation indices, and soil properties were used to develop a dynamic yield forecasting system based on the random forest (RF) model. The RF model showed good performance for estimating yields of all three crops with correlation coefficient (r) higher than 0.75 and normalized root means square errors (nRMSE) lower than 18.0%. Our results also showed that crop yields can be satisfactorily forecasted at one to three months prior to harvest. The optimum lead time for yield forecasting depended on crop types. In addition, we found the major predictors influencing crop yield varied between crops. In general, solar radiation and vegetation indices (especially during jointing to milk development stages) were identified as the main predictor for winter wheat;vegetation indices (throughout the growing season) and drought (especially during emergence to tasseling stages) were the most important predictors for spring maize;soil moisture (throughout the growing season) was the dominant predictor for summer maize, late rice, and mid rice;precipitation (especially during booting to heading stages) was the main predictor for early rice. Our study provides insights into practical crop yield forecasting and the understanding of yield response to environmental conditions at a large scale across China. The methods undertaken in this research can be easily implemented in other countries with available information on climate, soil, and vegetation conditions. [ABSTRACT FROM AUTHOR] Copyright of Agricultural & Forest Meteorology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

16.
BMC Infect Dis ; 21(1): 783, 2021 Aug 09.
Article in English | MEDLINE | ID: covidwho-1350140

ABSTRACT

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death. METHODS: A total of 2169 adult COVID-19 patients were enrolled from Wuhan, China, from February 10th to April 15th, 2020. Difference analyses of medical records were performed between severe and non-severe groups, as well as between survivors and non-survivors. In addition, we developed a decision tree model to predict death outcome in severe patients. RESULTS: Of the 2169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed as severe illness, and 75 patients died. An older median age and a higher proportion of male patients were found in severe group or non-survivors compared to their counterparts. Significant differences in clinical characteristics and laboratory examinations were found between severe and non-severe groups, as well as between survivors and non-survivors. A decision tree, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in training and test datasets. The accuracy of this model were 0.98 in both datasets. CONCLUSION: We performed a comprehensive analysis of COVID-19 patients from the outbreak in Wuhan, China, and proposed a simple and clinically operable decision tree to help clinicians rapidly identify COVID-19 patients at high risk of death, to whom priority treatment and intensive care should be given.


Subject(s)
COVID-19 , Adult , China/epidemiology , Decision Trees , Humans , Infant, Newborn , Male , Retrospective Studies , Risk Factors , SARS-CoV-2
17.
Front Pharmacol ; 12: 668407, 2021.
Article in English | MEDLINE | ID: covidwho-1337662

ABSTRACT

Coronavirus disease 2019 (COVID-19) is an emergent infectious pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is highly contagious and pathogenic. COVID-19 has rapidly swept across the world since it was first discovered in December 2019 and has drawn significant attention worldwide. During the early stages of the outbreak in China, traditional Chinese medicines (TCMs) were involved in the whole treatment process. As an indispensable part of TCM, Chinese patent medicines (CPMs) played an irreplaceable role in the prevention and treatment of this epidemic. Their use has achieved remarkable therapeutic efficacy during the period of medical observation and clinical treatment of mild, moderate, severe, and critical cases and during convalescence. In order to better propagate and make full use of the benefits of TCM in the treatment of COVID-19, this review will summarize the potential target of SARS-CoV-2 as well as the theoretical basis and clinical efficacy of recommended 22 CPMs by the National Health Commission and the Administration of TCM and local provinces or cities in the treatment of COVID-19. Additionally, the study will further analyze the drug composition, potential active ingredients, potential targets, regulated signaling pathways, and possible mechanisms for COVID-19 through anti-inflammatory and immunoregulation, antiviral, improve lung injury, antipyretic and organ protection to provide meaningful information about the clinical application of CPMs.

18.
Adv Mater ; 32(42): e2002940, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-743232

ABSTRACT

Recent years have seen enormous advances in nanovaccines for both prophylactic and therapeutic applications, but most of these technologies employ chemical or hybrid semi-biosynthetic production methods. Thus, production of nanovaccines has to date failed to exploit biology-only processes like complex sequential post-translational biochemical modifications and scalability, limiting the realization of the initial promise for offering major performance advantages and improved therapeutic outcomes over conventional vaccines. A Nano-B5 platform for in vivo production of fully protein-based, self-assembling, stable nanovaccines bearing diverse antigens including peptides and polysaccharides is presented here. Combined with the self-assembly capacities of pentamer domains from the bacterial AB5 toxin and unnatural trimer peptides, diverse nanovaccine structures can be produced in common Escherichia coli strains and in attenuated pathogenic strains. Notably, the chassis of these nanovaccines functions as an immunostimulant. After showing excellent lymph node targeting and immunoresponse elicitation and safety performance in both mouse and monkey models, the strong prophylactic effects of these nanovaccines against infection, as well as their efficient therapeutic effects against tumors are further demonstrated. Thus, the Nano-B5 platform can efficiently combine diverse modular components and antigen cargos to efficiently generate a potentially very large diversity of nanovaccine structures using many bacterial species.


Subject(s)
Nanoparticles , Proteins/chemistry , Proteins/immunology , Vaccination , Antigens/immunology , Proteins/metabolism
19.
Environmental Research Letters ; 16(7), 2021.
Article in English | ProQuest Central | ID: covidwho-1317875

ABSTRACT

Coronavirus disease 2019 (COVID-19) pandemic has led to a rare reduction in human activities. In such a background, data from ground-based environmental stations, satellites, and reanalysis materials are utilized to conduct a comprehensive analysis of the global air quality changes during the COVID-19 outbreak. The results showed that under the impact of the COVID-19 outbreak, a significant decrease in particulate matter (PM x ) and nitrogen dioxide (NO2) occurred in more than 40% of the world’s land area, with NO2 (PM x ) decreasing by ∼30% (∼20%). The mobility, meteorological factors, and the response speed to COVID-19 outbreaks were examined. It was further found that in quick-response cities, lockdowns produced a sharp decline in mobility and had a dominant impact on air quality. In contrast, in slow-response cities, mobility dropped gradually since the confirmation of the first COVID-19 case (FCC) and he impact of the FCC, lockdowns, and meteorological factors were comparable.

20.
Discrete Dynamics in Nature and Society ; 2021, 2021.
Article in English | ProQuest Central | ID: covidwho-1305515

ABSTRACT

This paper analyzed the influence of dollar on crude oil and gold based on the multifractal detrended partial cross-correlation analysis method. It showed that affected by the dollar, the crude oil and gold markets have a partial cross-correlation relationship which is stronger than their own cross-correlation. The partial cross-correlation is long-term and has multifractal characteristics. Through shuffled and Fourier-phase randomization, it is found that this multifractal feature is caused by the combined effect of the long-term cross-correlation between the returns and the fluctuation fat-tailed distribution, where the influence of the fat-tailed distribution is slightly greater than that of the long-term cross-correlation between the returns.

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