Open-Access Data and Toolbox for Tracking COVID-19 Impact on Power Systems

Intervention policies against COVID-19 have caused large-scale disruptions globally, and led to a series of pattern changes in the power system operation. Analyzing these pandemic-induced patterns is imperative to identify the potential risks and impacts of this extreme event. For this purpose, we developed an open-access data hub (COVID-EMDA+), an open-source toolbox (CoVEMDA), and a few evaluation methods to explore what the U.S. power systems are experiencing during COVID-19. These resources could be broadly used for research, public policy, and educational purposes. Technically, our data hub harmonizes a variety of raw data such as generation mix, demand profiles, electricity price, weather observations, mobility, confirmed cases and deaths. Typical methods are reformulated and standardized in our toolbox, including baseline estimation, regression analysis, and scientific visualization. Here the fluctuation index and probabilistic baseline are proposed for the first time to consider data fluctuation and estimation uncertainty. Furthermore, we conduct three empirical studies on the U.S. power systems, and share new solutions and findings to address several issues of public concerns. This conveys a more complete picture of the COVID-19 impact and also opens up several attractive topics for future work. Python, Matlab source codes, and user manuals are all publicly shared on a Github repository.

Monocytic HLA-DR Expression in Immune Responses of Acute Pancreatitis and COVID-19.

Acute pancreatitis is a common gastrointestinal disease with increasing incidence worldwide. COVID-19 is a potentially life-threatening contagious disease spread throughout the world, caused by severe acute respiratory syndrome coronavirus 2. More severe forms of both diseases exhibit commonalities with dysregulated immune responses resulting in amplified inflammation and susceptibility to infection. Human leucocyte antigen (HLA)-DR, expressed on antigen-presenting cells, acts as an indicator of immune function. Research advances have highlighted the predictive values of monocytic HLA-DR (mHLA-DR) expression for disease severity and infectious complications in both acute pancreatitis and COVID-19 patients. While the regulatory mechanism of altered mHLA-DR expression remains unclear, HLA-DR-/low monocytic myeloid-derived suppressor cells are potent drivers of immunosuppression and poor outcomes in these diseases. Future studies with mHLA-DR-guided enrollment or targeted immunotherapy are warranted in more severe cases of patients with acute pancreatitis and COVID-19.

Anti-Inflammatory Effects and Molecular Mechanisms of Shenmai Injection in Treating Acute Pancreatitis: Network Pharmacology Analysis and Experimental Verification.

Background: Acute pancreatitis (AP) is an inflammatory disorder of the exocrine pancreas without specific treatment. Shenmai injection (SMI) was reported to eliminate the severity of experimental AP. This study aimed to explore the mechanisms underlying the synergistic protective effects of SMI on AP based on network pharmacology and experimental validation. Methods: Network pharmacology analysis and molecular docking based on identified components were performed to construct the potential therapeutic targets and pathways. The principal components of SMI were detected via ultra-high-performance liquid chromatography-coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS). Effect of SMI and the identified components on cellular injury and IL6/STAT3 signaling was assessed on mouse pancreatic acinar cell line 266-6 cells. Finally, 4% sodium taurocholate (NaT) was used to induce AP model to assess the effects of SMI in treating AP and validate the potential molecular mechanisms. Results: By searching the TCMSP and ETCM databases, 119 candidate components of SMI were obtained. UHPLC-QTOF/MS analysis successfully determined the representative components of SMI: ginsenoside Rb1, ginsenoside Rg1, ginsenoside Re, and ophiopogonin D. Fifteen hub targets and eight related pathways were obtained to establish the main pharmacology network. Subnetwork analysis and molecular docking indicated that the effects of these four main SMI components were mostly related to the interleukin (IL) 6/STAT3 pathway. In vitro, SMI, ginsenoside Rb1, ginsenoside Rg1, ginsenoside Re, and ophiopogonin D increased the cell viability of NaT-stimulated mouse pancreatic acinar 266-6 cells and decreased IL6 and STAT3 expression. In vivo, 10 mL/kg SMI significantly alleviated the pancreatic histopathological changes and the expression of IL6 and STAT3 in the AP mice. Conclusion: This study demonstrated SMI may exert anti-inflammatory effects against AP by suppressing IL6/STAT3 activation, thus providing a basis for its potential use in clinical practice and further study in treating AP.

Recapitulating influenza virus infection and facilitating antiviral and neuroprotective screening in tractable brain organoids.

Human pluripotent stem cell derived brain organoids offer an unprecedented opportunity for various applications as in vitro model. Currently, human brain organoids as models have been used to understand virus-induced neurotoxicity. Methods: The brain organoids were separately challenged by multiple viruses including influenza viruses (H1N1-WSN and H3N2-HKT68), Enteroviruses (EV68 and EV71) and Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) to investigate the impaired effect of these viruses on human brain development. Results: The brain organoids challenged by influenza viruses had decreased overall organoid size, while enteroviruses infected brain organoids displayed the opposite result. Then, we found WSN preferentially infected MAP2+ neurons compared to SOX2+ neural stem cells (NSCs) and GFAP+ astrocytes in brain organoids, and induced apoptosis of NSCs and neurons, and released inflammatory factors (TNF-α, INF-γ, and IL-6), facilitating brain damage. Furthermore, transcriptional profiling revealed several co-upregulated genes (CSAG3 and OAS2) and co-downregulated genes (CDC20B, KCNJ13, OTX2-AS1) after WSN infection for 24 hpi and 96 hpi, implicating target for antiviral drugs development. Finally, we explored compound PYC-12 could significantly suppress virus infection, apoptosis, and inflammatory responses. Conclusions: Collectively, we established a tractable experimental model to investigate the impact and mechanism of virus infection on human brain development.

An Integrative Analysis of the Immune Features of Inactivated SARS-CoV-2 Vaccine (CoronaVac).

Currently, an inactivated vaccine has been widely used with encouraging results as a prophylactic agent against COVID-19 infection, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants. However, in vitro SARS-CoV-2 vaccine-specific immune features remain elusive, hindering the promotion of a third dose of the vaccine. Here, we present a detailed in vitro immune cellular response and large-scale multi-omics analysis for peripheral blood mononuclear cells (PBMCs) from participants vaccinated with CoronaVac (Sinovac Life Sciences, Beijing, China) and recovered participants from COVID-19. The mean titers of SARS-CoV-2 serum-neutralizing antibodies were significantly increased after the boosting immunization (Day 45) compared to the unimmunized state. We observed that type-1 helper T cells (Th1) tended to dominate after the first dose of vaccine, while humoral immune responses became dominant after the second dose due to the activation of type-2 helper T cell (Th2), memory B cells, and plasmablasts. T follicular helper cells (Tfh) involved in antibody production were activated after the first dose and were maintained for the observed time points. Single-cell RNA sequencing of PBMCs revealed specific changes in cell compositions and gene expression in immunized participants. Multi-omics analysis also demonstrated that CoronaVac-specific serum proteins, plasma metabolites, and plasma lipid changes were skewed to those changes in convalescent patients. Collectively, we provide a comprehensive understanding of CoronaVac-specific in vitro immune features.

Evaluation of Product Innovation Practice of Chinese Internet Companies Based on DANP Model

Purpose. Internet companies have played an important supporting role in China’s economic growth and social resource allocation in the advent of an exogenous shock: the coronavirus disease (COVID-19) pandemic. This is owing to their digital, networked, and platform-based characteristics amidst an environment of intensified competition and stagnation of innovation activities due to the pandemic shock. Thus, based on the social network theory and resource-based theory, this study combines the DANP model with corporate innovation to build a product innovation performance evaluation framework for Chinese Internet companies. From a value network perspective, this study considers the different performance aspects of network embeddedness, knowledge management, environmental triggering, and organizational effectiveness. Methodology. The performance of Internet enterprise product innovation may be considered a complex multicriteria decision-making problem. This study used the decision-making trial and evaluation laboratory-based analytic network algorithms to analyze the complex influencing relationship among the factors and calculate their weights. Preference ranking organization method for enrichment evaluation was used for selecting the final solution of multiobjective optimization. Three representative and influential Internet companies in China were selected for empirical analysis and practical evaluation, to find the gap between product innovation performance and expectations and present development suggestions. Findings. The study results reveal that relational embeddedness, knowledge sharing degree, cognitive embeddedness, structural embeddedness, knowledge absorptive capacity, and corporate strategic orientation are important to Chinese Internet enterprise product innovation performance. Practical Implications. This Internet enterprise product innovation performance evaluation framework can be used by Internet business operators to assess product innovation performance and identify areas of improvement. This study provides new product innovation ideas for Chinese Internet companies during an epidemic situation. Originality/Value. This study contributes to the present body of knowledge by using the DANP model to conduct empirical analysis, considering value network-related performance aspects to evaluate the product innovation performance of Internet enterprise in China.

Healthcare resource utilisation and predictors for critical care unit admissions after primary bariatric surgery in an Australian public hospital setting: an exploratory study using a mixed-methods approach.

Objectives The aim of this exploratory study was to investigate resource use and predictors associated with critical care unit (CCU) admission after primary bariatric surgery within the Tasmanian public healthcare system. Methods Patients undergoing primary bariatric surgery in the Tasmanian Health Service (THS) public hospital system between 7 July 2013 and 30 June 2019 were eligible for inclusion in this study. The THS provides two levels of CCU support, an intensive care unit (ICU) and a high dependency unit (HDU). A mixed-methods approach was performed to examine the resource use and predictors associated with overall CCU admission, as well as levels of HDU and ICU admission. Results There were 254 patients in the study. Of these, 44 (17.3%) required 54 postoperative CCU admissions, with 43% requiring HDU support and 57% requiring more resource-demanding ICU support. Overall, CCU patients were more likely to have higher preoperative body mass index and multimorbidity and to undergo sleeve gastrectomy or gastric bypass. Patients undergoing gastric banding were more likely to require HDU rather than ICU support. Total hospital stays and median healthcare costs were higher for CCU (particularly ICU) patients than non-CCU patients. Conclusions Bariatric surgery patients often have significant comorbidities. This study demonstrates that patients with higher levels of morbidity are more likely to require critical care postoperatively. Because this is elective surgery, being able to identify patients who are at increased risk is important to plan either the availability of critical care or even interventions to improve patients' preoperative risk. Further work is required to refine the pre-existing conditions that contribute most to the requirement for critical care management (particularly in the ICU setting) in the perioperative period. What is known about the topic? Few studies (both Australian and international) have investigated the use of CCUs after bariatric surgery. Those that report CCU admission rates are disparate across the contemporaneous literature, reflecting the different healthcare systems and their associated incentives. In Australia, the incidence and utilisation of CCUs (consisting of HDUs and ICUs) after bariatric surgery have only been reported using Western Australian administrative data. What does the paper add? CCU patients were more likely to have a higher preoperative body mass index and multimorbidity and to undergo a sleeve gastrectomy or gastric bypass procedure. Just over half (57%) of these patients were managed in the ICU. Sleeve gastrectomy patients had a higher incidence of peri- and postoperative complications that resulted in an unplanned ICU admission. Hospital length of stay and aggregated costs were higher for CCU (particularly ICU) patients. What are the implications for practitioners? The association of increased CCU (particularly ICU) use with multimorbidity and peri- and postoperative complications could enable earlier recognition of patients that are more likely to require CCU and ICU support, therefore allowing improved planning when faced with increasing rates of bariatric surgery. We suggest streamlined clinical guidelines that anticipate CCU support for people with severe and morbid obesity who undergo bariatric surgery should be considered from a national perspective.

Prognostic Potential of Liver Enzymes in Patients With COVID-19 at the Leishenshan Hospital in Wuhan.

Background: Coronavirus disease 2019 (COVID-19) has evolved into a pandemic. We hypothesized that biochemical indicators of liver function may help determine the prognosis of COVID-19 patients. Methods: Patient information was collected from the Wuhan-Leishenshan hospital. Logistic and Cox regression analyses, Kaplan-Meier curves, and Curve fitting were used to determine the correlation between elevated levels of aspartate transaminase (AST), alanine transaminase (ALT), and AST/ALT and severity of disease/mortality. Results: Logistic and Cox regression analyses and Kaplan-Meier survival curves showed that COVID-19 progression correlated with elevated levels of AST and AST/ALT. The odds ratios for elevated levels of AST and AST/ALT in patients were 0.818 (95% confidence interval [CI]: 0.274-2.441, P = 0.035) and 2.055 (95% CI: 1.269-3.327, P = 0.003), respectively; the hazard ratios were 4.195 (95% CI: 1.219-14.422, P = 0.023) and 3.348 (95% CI: 1.57-7.139, P = 0.002), respectively. The Kaplan-Meier survival curves demonstrated that patients with elevated AST and AST/ALT levels had a higher risk of developing severe COVID-19. Conclusion: Elevated AST and AST/ALT levels correlated with severity of COVID-19 and mortality. Liver function tests may help clinicians in determining the prognosis of patients undergoing treatment for COVID-19.

Critical roles of cytokine storm and secondary bacterial infection in acute kidney injury development in COVID-19: A multi-center retrospective cohort study.

Acute kidney injury (AKI) may develop in patients with coronavirus disease 2019 (COVID-19) and is associated with in-hospital death. We investigated the incidence of AKI in 223 hospitalized COVID-19 patients and analyzed the influence factors of AKI. The incidence of cytokine storm syndrome and its correlation with other clinicopathologic variables were also investigated. We retrospectively enrolled adult patients with virologically confirmed COVID-19 who were hospitalized at three hospitals in Wuhan and Guizhou, China between February 13, 2020, and April 8, 2020. We included 124 patients with moderate COVID-19 and 99 with severe COVID-19. AKI was present in 35 (15.7%) patients. The incidence of AKI was 30.3% for severe COVID-19 and 4.0% for moderate COVID-19 (p < 0.001). Furthermore, cytokine storm was found in 30 (13.5%) patients and only found in the severe group. Kidney injury at admission (odds ratio [OR]: 3.132, 95% confidence interval [CI]: 1.150-8.527; p = 0.025), cytokine storm (OR: 4.234, 95% CI: 1.361-13.171; p = 0.013), and acute respiratory distress syndrome (ARDS) (OR: 7.684, 95% CI: 2.622-22.523; p < 0.001) were influence factors of AKI. Seventeen (48.6%) patients who received invasive mechanical ventilation developed AKI, of whom 64.7% (11/17) died. Up to 86.7% of AKI patients with cytokine storms may develop a secondary bacterial infection. The leukocyte counts were significantly higher in AKI patients with cytokine storm than in those without (13.0 × 109/L, interquartile range [IQR] 11.3 vs. 8.3 × 109/L, IQR 7.5, p = 0.005). Approximately 1/6 patients with COVID-19 eventually develop AKI. Kidney injury at admission, cytokine storm and ARDS are influence factors of AKI. Cytokine storm and secondary bacterial infections may be responsible for AKI development in COVID-19 patients.

Prognostic significance of low TSH concentration in patients with COVID-19 presenting with non-thyroidal illness syndrome.

BACKGROUND: Low free triiodothyronine (FT3) levels are related to a poor prognosis deterioration in patients with COVID-19 presenting with non-thyroidal illness syndrome (NTI). This study was designed to explore whether free thyroxin (FT4) or thyroid stimulating hormone (TSH) levels affected the mortality of patients with COVID-19 presenting with NTI. METHODS: Patients with COVID-19 complicated with NTI who were treated at our hospital were included in this retrospective study. Patients were divided into low TSH and normal TSH groups, as well as low and normal-high FT4 group, according to the reference range of TSH or FT4 levels. The 90-day mortality and critical illness rates were compared among patients with low and normal TSH levels, as well as among patients with low FT4 levels and normal-high FT4 levels; in addition, differences in demographic and laboratory data were compared. A Kaplan-Meier analysis and Cox proportional hazards models were used to assess the associations of TSH and FT4 levels with mortality. RESULTS: One hundred fifty patients with low FT3 levels and without a history of thyroid disease were included, 68% of whom had normal FT4 and TSH levels. Critical illness rates (74.07% VS 37.40%, P = 0.001) and mortality rates (51.85% VS 22.76%, P = 0.002) were significantly higher in the low TSH group than in the normal TSH group. Although no significant difference in the critical illness rate was found (P = 0.296), the mortality rate was significantly higher in the low FT4 group (P = 0.038). Low TSH levels were independently related to 90-day mortality (hazard ratio = 2.78, 95% CI:1.42-5.552, P = 0.003). CONCLUSIONS: Low FT4 and TSH concentrations were associated with mortality in patients with COVID-19 presenting with NTI; moreover, low TSH levels were an independent risk factor for mortality in these patients.

Characteristics of Viral Shedding in Respiratory Samples and Specific Antibodies Production in 564 COVID-19 Patients.

Positive nucleic acid (NA) results have been found in recovered and discharged COVID-19 patients, but the proportion is unclear. This study was designed to analyze the recurrent positive rate of NA results after consecutively negative results, and the relationship between the specific antibody production and positive NA rate. According to Strengthening the Reporting of Observational Studies in Epidemiology guidelines, data of inpatients in Sino-French New City Branch of Tongji Hospital between Jan. 28 and Mar. 6, 2020 were collected. A total of 564 COVID-19 patients over 14 years old who received the examinations of NA and antibodies against SARS-CoV-2 were included. Days of viral shedding and specific antibodies were recorded and assessed. Among NA tests in respiratory samples (throat swabs, nasopharyngeal swabs, sputum and flushing fluid in alveoli), the patients with all-negative NA results accounted for 17.20%, those with single-positive results for 46.63%, and those with multiple-positive results for 36.17% respectively. Besides, the recurrent positive NA results after consecutively negative results appeared in 66 patients (11.70%). For multiple-positive patients, median viral shedding duration was 20 days (range: 1 to 57 days). Of the 205 patients who received 2 or more antibody tests, 141 (68.78%) had decreased IgG and IgM concentrations. IgM decreased to normal range in 24 patients, with a median of 44 days from symptom onset. Viral shedding duration was not significantly correlated with gender, age, disease severity, changes in pulmonary imaging, and antibody concentration. It is concluded that antibody level and antibody change had no significant correlation with the positive rate of NA tests and the conversion rate after continuous negative NA tests. In order to reduce the recurrent positive proportion after discharge, 3 or more consecutive negative NA test results with test interval more than 24 h every time are suggested for the discharge or release from quarantine.

Quantitative assessment of U.S. bulk power systems and market operations during the COVID-19 pandemic.

Starting in early 2020, the novel coronavirus disease (COVID-19) severely attached the U.S., causing substantial changes in the operations of bulk power systems and electricity markets. In this paper, we develop a data-driven analysis to substantiate the pandemic's impacts from the perspectives of power system security, electric power generation, electric power demand and electricity prices. Our results suggest that both electric power demand and electricity prices have discernibly dropped during the COVID-19 pandemic. Geographically diverse impacts are observed and quantified, while the bulk power systems and markets in the northeast region are most severely affected. All the data sources, assessment criteria, and analysis codes reported in this paper are available on a GitHub repository.

Correlation analysis between disease severity and inflammation-related parameters in patients with COVID-19: a retrospective study.

BACKGROUND: COVID-19 is highly contagious, and the crude mortality rate could reach 49% in critical patients. Inflammation concerns on disease progression. This study analyzed blood inflammation indicators among mild, severe and critical patients, helping to identify severe or critical patients early. METHODS: In this cross-sectional study, 100 patients were included and divided into mild, severe or critical groups according to disease condition. Correlation of peripheral blood inflammation-related indicators with disease criticality was analyzed. Cut-off values for critically ill patients were speculated through the ROC curve. RESULTS: Significantly, disease severity was associated with age (R = -0.564, P < 0.001), interleukin-2 receptor (IL2R) (R = -0.534, P < 0.001), interleukin-6 (IL-6) (R = -0.535, P < 0.001), interleukin-8 (IL-8) (R = -0.308, P < 0.001), interleukin-10 (IL-10) (R = -0.422, P < 0.001), tumor necrosis factor α (TNFα) (R = -0.322, P < 0.001), C-reactive protein (CRP) (R = -0.604, P < 0.001), ferroprotein (R = -0.508, P < 0.001), procalcitonin (R = -0.650, P < 0.001), white cell counts (WBC) (R = -0.54, P < 0.001), lymphocyte counts (LC) (R = 0.56, P < 0.001), neutrophil count (NC) (R = -0.585, P < 0.001) and eosinophil counts (EC) (R = 0.299, P < 0.001). With IL2R > 793.5 U/mL or CRP > 30.7 ng/mL, the progress of COVID-19 to critical stage should be closely observed and possibly prevented. CONCLUSIONS: Inflammation is closely related to severity of COVID-19, and IL-6 and TNFα might be promising therapeutic targets.

Evolutionary Analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Reveals Genomic Divergence with Implications for Universal Vaccine Efficacy.

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the pressing contemporary public health challenges. Investigations into the genomic structure of SARS-CoV-2 may inform ongoing vaccine development efforts and/or provide insights into vaccine efficacy to fight against COVID-19. Evolutionary analysis of 540 genomes spanning 20 different countries/territories was conducted and revealed an increase in the genomic divergence across successive generations. The ancestor of the phylogeny was found to be the isolate from the 2019/2020 Wuhan outbreak. Its transmission was outlined across 20 countries/territories as per genomic similarity. Our results demonstrate faster evolving variations in the genomic structure of SARS-CoV-2 when compared to the isolates from early stages of the pandemic. Genomic alterations were predominantly located and mapped onto the reported vaccine candidates of structural genes, which are the main targets for vaccine candidates. S protein showed 34, N protein 25, E protein 2, and M protein 3 amino acid variations in 246 genomes among 540. Among identified mutations, 23 in S protein, 1 in E, 2 from M, and 7 from N protein were mapped with the reported vaccine candidates explaining the possible implications on universal vaccines. Hence, potential target regions for vaccines would be ideally chosen from the structural regions of the genome that lack high variation. The increasing variations in the genome of SARS-CoV-2 together with our observations in structural genes have important implications for the efficacy of a successful universal vaccine against SARS-CoV-2.