A case study of using natural language processing to extract consumer insights from tweets in American cities for public health crises.

BACKGROUND: The COVID-19 pandemic was a "wake up" call for public health agencies. Often, these agencies are ill-prepared to communicate with target audiences clearly and effectively for community-level activations and safety operations. The obstacle is a lack of data-driven approaches to obtaining insights from local community stakeholders. Thus, this study suggests a focus on listening at local levels given the abundance of geo-marked data and presents a methodological solution to extracting consumer insights from unstructured text data for health communication. METHODS: This study demonstrates how to combine human and Natural Language Processing (NLP) machine analyses to reliably extract meaningful consumer insights from tweets about COVID and the vaccine. This case study employed Latent Dirichlet Allocation (LDA) topic modeling, Bidirectional Encoder Representations from Transformers (BERT) emotion analysis, and human textual analysis and examined 180,128 tweets scraped by Twitter Application Programming Interface's (API) keyword function from January 2020 to June 2021. The samples came from four medium-sized American cities with larger populations of people of color. RESULTS: The NLP method discovered four topic trends: "COVID Vaccines," "Politics," "Mitigation Measures," and "Community/Local Issues," and emotion changes over time. The human textual analysis profiled the discussions in the selected four markets to add some depth to our understanding of the uniqueness of the different challenges experienced. CONCLUSIONS: This study ultimately demonstrates that our method used here could efficiently reduce a large amount of community feedback (e.g., tweets, social media data) by NLP and ensure contextualization and richness with human interpretation. Recommendations on communicating vaccination are offered based on the findings: (1) the strategic objective should be empowering the public; (2) the message should have local relevance; and, (3) communication needs to be timely.

Establishment and validation of the autophagy-related ceRNA network in irreversible pulpitis.

BACKGROUND: The molecular mechanisms underlying the onset and progression of irreversible pulpitis have been studied for decades. Many studies have indicated a potential correlation between autophagy and this disease. Against the background of the competing endogenous RNA (ceRNA) theory, protein-coding RNA functions are linked with long noncoding RNAs (lncRNAs) and microRNAs (miRNAs). This mechanism has been widely studied in various fields but has rarely been reported in the context of irreversible pulpitis. The hub genes selected under this theory may represent the key to the interaction between autophagy and irreversible pulpitis. RESULTS: Filtering and differential expression analyses of the GSE92681 dataset, which contains data from 7 inflamed and 5 healthy pulp tissue samples, were conducted. The results were intersected with autophagy-related genes (ARGs), and 36 differentially expressed ARGs (DE-ARGs) were identified. Functional enrichment analysis and construction of the protein‒protein interaction (PPI) network of DE-ARGs were performed. Coexpression analysis was conducted between differentially expressed lncRNAs (DElncRNAs) and DE-ARGs, and 151 downregulated and 59 upregulated autophagy-related DElncRNAs (AR-DElncRNAs) were identified. StarBase and multiMiR were then used to predict related microRNAs of AR-DElncRNAs and DE-ARGs, respectively. We established ceRNA networks including 9 hub lncRNAs (HCP5 and AC112496.1 ↑; FENDRR, AC099850.1, ZSWIM8-AS1, DLX6-AS1, LAMTOR5-AS1, TMEM161B-AS1 and AC145207.5 ↓), which were validated by a qRT‒PCR analysis of pulp tissue from patients with irreversible pulpitis. CONCLUSION: We constructed two networks consisting of 9 hub lncRNAs based on the comprehensive identification of autophagy-related ceRNAs. This study may provide novel insights into the interactive relationship between autophagy and irreversible pulpitis and identifies several lncRNAs that may serve as potential biological markers.

Effect of hyperglycemia on the immune function of COVID-19 patients with type 2 diabetes mellitus: a retrospective study.

Purpose: To analyze the clinical characteristics and immune function parameters and to explore the effect of hyperglycemia on the immune function in patients with Corona Virus Disease 2019 (COVID-19) with type 2 diabetes mellitus (T2DM). Methods: This retrospective study included patients with COVID-19 with T2DM hospitalized in Renmin Hospital of Wuhan University between January 31, 2020, and February 10, 2020. The clinical data were collected and patients were divided into a well-controlled group (blood glucose 3.9-10.0 mmol/L) and a poorly-controlled group (blood glucose >10.0 mmol/L). The differences in routine blood tests, peripheral lymphocyte subsets, humoral immune components, C-reactive protein (CRP) level, and cytokines were compared, and the correlation between blood glucose and immune parameters as well as the severity of the disease was analyzed. Results: A total of 65 patients with COVID-19 and T2DM were included in the final analysis. Compared with the well-controlled group, patients in the poorly-controlled group had decreased lymphocytes, CD16+ 56+ NK cells, CD3+ T cells, CD8+ T cells and increased neutrophil percentage, IL-6 levels, CRP levels and serum concentration of IgA. Blood glucose was inversely correlated with CD16+ 56+ NK cells, CD3+ T cells, CD4+ T cells, and CD8+ T cells and positively correlated with IL-6 and CRP levels. There was a positive correlation between blood glucose and the severity of the COVID-19. Conclusion: Hyperglycemia will aggravate the immune dysfunction of COVID-19 patients with T2DM and affect the severity of COVID-19.

Impact of coronavirus disease 2019 on lung cancer patients: A meta-analysis.

Background: The coronavirus disease 2019 (COVID-19) pandemic poses a great challenge to the treatment of lung cancer patients. Materials and methods: The PubMed, Embase, and Web of Science databases were searched for studies published before March 15, 2022, and Stata 14.0 software was used to perform a meta-analysis with a random-effects model. The odds ratio (OR) along with the corresponding 95% confidence interval (CI) was reported. Results: Our meta-analysis included 80 articles with 318,352 patients involved. The proportion of lung cancer patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was 2.4% (95% CI: 0.02-0.03) prior to the Omicron variant outbreak. Among COVID-19 patients, those with lung cancer showed a higher mortality rate than those with other types of malignant solid tumors (OR = 1.82, 95% CI: 1.61-2.06) and non-cancer patients (OR = 4.67, 95% CI: 3.61-6.05); however, no significant difference was observed in the mortality rate between patients with lung cancer and those with hematologic malignancies (OR = 1.07, 95% CI: 0.85-1.33). SARS-CoV-2 infection significantly increased the mortality rate in lung cancer patients (OR = 8.94, 95% CI: 6.50-12.31). By contrast, the all-cause mortality rate in lung cancer patients (OR = 1.04, 95% CI: 0.69-1.57) and the proportion of patients diagnosed with advanced lung cancer (OR = 1.04, 95% CI: 0.85-1.27) did not significantly change before and after the pandemic. Conclusions: More attention should be paid on improving the health of lung cancer patients during the COVID-19 pandemic.

Single-walled carbon nanotubes-based RNA protection and extraction improves RT-qPCR sensitivity for SARS-CoV-2 detection.

The false-negative result of nucleic acid testing is an important cause of continued spread of COVID-19, while SARS-CoV-2 RNA degradation during transportation and nucleic acid extraction can lead to false-negative results. Here, we investigated that single-walled carbon nanotubes (SCNTs) could protect RNA from degradation for at least 4 days at room temperature. By constructing magnetism-functionalized SCNTs (MSCNTs), we developed a method that enabled protection and simple extraction of SARS-CoV-2 RNA, and the RNA-bound MSCNTs can be directly used for reverse transcription polymerase chain reaction (RT-qPCR) detection. The experimental results showed that 1 µg of MSCNTs adsorbed up to 24 ng of RNA. Notably, the MSCNTs-based method for extracting SARS-CoV-2 RNA from simulated nasopharyngeal swabs and saliva samples with mean recovery rates of 103% and 106% improved the sensitivity of RT-qPCR detection by 8-32 fold in comparison to current common methods. This improvement was largely attributable to the protection of RNA, enabling increased RNA load for downstream assays.

Exploration of the Potential Link, Hub Genes, and Potential Drugs for Coronavirus Disease 2019 and Lung Cancer Based on Bioinformatics Analysis.

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has a huge influence on global public health and the economy. Lung cancer is one of the high-risk factors of COVID-19, but the molecular mechanism of lung cancer and COVID-19 is still unclear, and further research is needed. Therefore, we used the transcriptome information of the public database and adopted bioinformatics methods to identify the common pathways and molecular biomarkers of lung cancer and COVID-19 to further understand the connection between them. The two RNA-seq data sets in this study-GSE147507 (COVID-19) and GSE33532 (lung cancer)-were both derived from the Gene Expression Omnibus (GEO) database and identified differentially expressed genes (DEGs) for lung cancer and COVID-19 patients. We conducted Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis and found some common features between lung cancer and COVID-19. We also performed TFs-gene, miRNAs-gene, and gene-drug analyses. In total, 32 DEGs were found. A protein-protein interaction (PPI) network was constructed by DEGs, and 10 hub genes were screened. Finally, the identified drugs may be helpful for COVID-19 treatment.

Acceptance of coronavirus disease 2019 (COVID-19) vaccines among healthcare workers: A meta-analysis

Background The coronavirus disease 2019 (COVID-19) pandemic has posed increasing challenges to global health systems. Vaccination against COVID-19 can effectively prevent the public, particularly healthcare workers (HCWs), from being infected by this disease. Objectives We aim to understand the factors influencing HCWs' acceptance of COVID-19 vaccines. Methods We searched PubMed, Embase and Web of Science to collect literature published before May 15, 2022, about HCWs' acceptance of COVID-19 vaccines. The Newcastle–Ottawa quality assessment scale was used to assess the risk of bias and the quality of the included studies. We utilized Stata 14.0 software for this meta-analysis with a random-effects model, and odds ratios (ORs) with 95% confidence intervals (CIs) were reported. This meta-analysis was conducted in alignment with the preferred reporting items for systematic review and meta-analysis (PRISMA) guideline. Results Our meta-analysis included 71 articles with 93,508 HCWs involved. The research showed that the acceptance of vaccines had significantly increased among HCWs compared to non-HCWs (OR = 1.91, 95% CI: 1.16–3.12). A willingness to undergo COVID-19 vaccination was observed in 66% (95% CI: 0.61–0.67) of HCWs. Among the HCWs involved, doctors showed a generally increased intention to be vaccinated compared with nurses (OR = 2.22, 95% CI: 1.71–2.89). Additionally, males were found to hold more positive attitudes toward vaccination than females (OR = 1.81, 95% CI: 1.55–2.12). When the effectiveness of COVID-19 vaccines was improved, the vaccination acceptance of HCWs was greatly increased accordingly (OR = 5.03, 95% CI: 2.77–9.11). The HCWs who were willing to vaccinate against seasonal influenza showed an increased acceptance of COVID-19 vaccines (OR = 3.52, 95% CI: 2.34–5.28). Our study also showed that HCWs who were willing to be vaccinated against COVID-19 experienced a reduced rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (OR = 0.78, 95% CI: 0.66–0.92). Conclusions Our analysis revealed that the five factors of occupation, gender, vaccine effectiveness, seasonal influenza vaccines, and SARS-CoV-2 infection presumably affected the acceptance of COVID-19 vaccines among HCWs. It is essential to boost the confidence of HCWs in COVID-19 vaccines for the containment of the epidemic.

Management model of mass vaccination of COVID-19 vaccine

OBJECTIVE: To explore the role of systematic vaccination management model in mass vaccination of COVID-19 vaccine. METHODS: According to the mass vaccination plan formulated by the Day Clinic of the Fifth Medical Center of Chinese PLA General Hospital, the vaccination work was fully deployed before vaccination;and the temporary specification of mass vaccination sites were set up according to the requirements of the temporary vaccination site for the new coronavirus vaccine in Beijing;the vaccine management systems was strictly implemented, the doctor group, nursing group and guarantee group performed the responsibilities of their own to ensure smooth and orderly vaccination work. RESULTS: The medical center has participated in more than 30 mass vaccinations of COVID-19, no vaccination error-related reactions and psychogenic reactions occurred at the vaccination site, and no adverse events that were caused by problems in the process link occurred. CONCLUSION: The detailed work plan for mass vaccination may facilitate the safe and orderly mass vaccination, and the vaccination work is unanimously recognized by the recipients.

In Silico Screening of Novel TMPRSS2 Inhibitors for Treatment of COVID-19.

COVID-19, a pandemic caused by the virus SARS-CoV-2, has spread globally, necessitating the search for antiviral compounds. Transmembrane protease serine 2 (TMPRSS2) is a cell surface protease that plays an essential role in SARS-CoV-2 infection. Therefore, researchers are searching for TMPRSS2 inhibitors that can be used for the treatment of COVID-19. As such, in this study, based on the crystal structure, we targeted the active site of TMPRSS2 for virtual screening of compounds in the FDA database. Then, we screened lumacaftor and ergotamine, which showed strong binding ability, using 100 ns molecular dynamics simulations to study the stability of the protein-ligand binding process, the flexibility of amino acid residues, and the formation of hydrogen bonds. Subsequently, we calculated the binding free energy of the protein-ligand complex by the MM-PBSA method. The results show that lumacaftor and ergotamine interact with residues around the TMPRSS2 active site, and reached equilibrium in the 100 ns molecular dynamics simulations. We think that lumacaftor and ergotamine, which we screened through in silico studies, can effectively inhibit the activity of TMPRSS2. Our findings provide a basis for subsequent in vitro experiments, having important implications for the development of effective anti-COVID-19 drugs.

SARS-CoV-2 Spike Stem Protein Nanoparticles Elicited Broad ADCC and Robust Neutralization against Variants in Mice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the global pandemic. The virus is rapidly evolving, characterized by the emergence of several major variants. Stable prefusion spike protein (Pre) is the immunogen in current vaccines but is limited in protecting against different variants. Here, the immune responses induced by the relatively conserved stem subunit (S2) of spike protein versus Pre are investigated. Pre generates the most robust neutralization responses against SARS-CoV-2 variants in vesicular stomatitis virus pseudovirus-based assessment but elicits less antibody-dependent cellular cytotoxicity (ADCC) activity than S2. By contrast, S2 induces the most balanced immunoglobulin G (IgG) antibodies with potent and broad ADCC activity although produces weaker neutralization. The immunogenicity of S2 and Pre improves by incorporating the two proteins into double-layered protein nanoparticles. The resulting protein nanoparticles Pre/S2 elicit higher neutralizing antibodies than Pre alone, and stronger ADCC than S2 alone. Moreover, nanoparticles produce more potent and balanced serum IgG antibodies than the corresponding soluble protein mixture, and the immune responses are sustained for at least four months after the immunization. Thus, the double-layered protein nanoparticles have the potential to be developed into broader SARS-CoV-2 vaccines with excellent safety profiles.

Prevalence and Differences of Depression, Anxiety, and Substance Use Between Chinese College-Age Students Studying in China and America During the Coronavirus Disease 2019 Pandemic.

Introduction: The coronavirus disease (COVID-19) swept the globe and harmfully influenced the mental health and behaviors of the college student population. This study aims to examine the prevalence and difference of mental health and the substance use problems of the Chinese college-age students studying in China and America (CSA) during the COVID-19 pandemic. Methods: One thousand five hundred four students participated in this study. A total of 42.12% of students are enrolled in Chinese colleges, and 57.78% of students are enrolled in American colleges, aged 17-23 years ( x ¯ ± s = 19.90 ± 1.50). Binary logistic regression and independent t-test were used in this study to find the predictor variables and association among mental health, substance use problems, and student population. Results: The two student groups had a statistical difference in General Anxiety Disorder-7 scale, alcohol, medicines, drinks, drugs and cigarettes (p < 0.01). The students suffering depression problems from the two groups have statistical significance with drinks (odds ratio = 0.89, 95% confidence interval = 0.81-0.97, p < 0.05; odds ratio = 1.11, 95% confidence interval = 1.04-1.19, p < 0.01). CSA experiencing anxiety problem had a significant association with alcohol, drinks, cigarette, and desserts (p < 0.05). Conclusion: This is the first cross-sectional study focusing on the comparison of the Chinese college-age students' mental health and substance use problems who are studying in China and America during the pandemic. Our study revealed severe mental health and substance use problems in both student groups, particularly in the CSA during the COVID-19 pandemic. The findings of our study also highlight the evidence to find more interventions and preventions to solve the different mental health and substance use problems for college students.

RNA G-quadruplex in TMPRSS2 reduces SARS-CoV-2 infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues to have devastating consequences worldwide. Recently, great efforts have been made to identify SARS-CoV-2 host factors, but the regulatory mechanisms of these host molecules, as well as the virus per se, remain elusive. Here we report a role of RNA G-quadruplex (RG4) in SARS-CoV-2 infection. Combining bioinformatics, biochemical and biophysical assays, we demonstrate the presence of RG4s in both SARS-CoV-2 genome and host factors. The biological and pathological importance of these RG4s is then exemplified by a canonical 3-quartet RG4 within Tmprss2, which can inhibit Tmprss2 translation and prevent SARS-CoV-2 entry. Intriguingly, G-quadruplex (G4)-specific stabilizers attenuate SARS-CoV-2 infection in pseudovirus cell systems and mouse models. Consistently, the protein level of TMPRSS2 is increased in lungs of COVID-19 patients. Our findings reveal a previously unknown mechanism underlying SARS-CoV-2 infection and suggest RG4 as a potential target for COVID-19 prevention and treatment.

One-Year Trajectory of Cognitive Changes in Older Survivors of COVID-19 in Wuhan, China: A Longitudinal Cohort Study.

Importance: Determining the long-term impact of COVID-19 on cognition is important to inform immediate steps in COVID-19 research and health policy. Objective: To investigate the 1-year trajectory of cognitive changes in older COVID-19 survivors. Design, Setting, and Participants: This cohort study recruited 3233 COVID-19 survivors 60 years and older who were discharged from 3 COVID-19-designated hospitals in Wuhan, China, from February 10 to April 10, 2020. Their uninfected spouses (N = 466) were recruited as a control population. Participants with preinfection cognitive impairment, a concomitant neurological disorder, or a family history of dementia were excluded, as well as those with severe cardiac, hepatic, or kidney disease or any kind of tumor. Follow-up monitoring cognitive functioning and decline took place at 6 and 12 months. A total of 1438 COVID-19 survivors and 438 control individuals were included in the final follow-up. COVID-19 was categorized as severe or nonsevere following the American Thoracic Society guidelines. Main Outcomes and Measures: The main outcome was change in cognition 1 year after patient discharge. Cognitive changes during the first and second 6-month follow-up periods were assessed using the Informant Questionnaire on Cognitive Decline in the Elderly and the Telephone Interview of Cognitive Status-40, respectively. Based on the cognitive changes observed during the 2 periods, cognitive trajectories were classified into 4 categories: stable cognition, early-onset cognitive decline, late-onset cognitive decline, and progressive cognitive decline. Multinomial and conditional logistical regression models were used to identify factors associated with risk of cognitive decline. Results: Among the 3233 COVID-19 survivors and 1317 uninfected spouses screened, 1438 participants who were treated for COVID-19 (691 male [48.05%] and 747 female [51.95%]; median [IQR] age, 69 [66-74] years) and 438 uninfected control individuals (222 male [50.68%] and 216 female [49.32%]; median [IQR] age, 67 [66-74] years) completed the 12-month follow-up. The incidence of cognitive impairment in survivors 12 months after discharge was 12.45%. Individuals with severe cases had lower Telephone Interview of Cognitive Status-40 scores than those with nonsevere cases and control individuals at 12 months (median [IQR]: severe, 22.50 [16.00-28.00]; nonsevere, 30.00 [26.00-33.00]; control, 31.00 [26.00-33.00]). Severe COVID-19 was associated with a higher risk of early-onset cognitive decline (odds ratio [OR], 4.87; 95% CI, 3.30-7.20), late-onset cognitive decline (OR, 7.58; 95% CI, 3.58-16.03), and progressive cognitive decline (OR, 19.00; 95% CI, 9.14-39.51), while nonsevere COVID-19 was associated with a higher risk of early-onset cognitive decline (OR, 1.71; 95% CI, 1.30-2.27) when adjusting for age, sex, education level, body mass index, and comorbidities. Conclusions and Relevance: In this cohort study, COVID-19 survival was associated with an increase in risk of longitudinal cognitive decline, highlighting the importance of immediate measures to deal with this challenge.

Identification of a novel coronavirus causing severe pneumonia in human: a descriptive study.

BACKGROUND: Human infections with zoonotic coronaviruses (CoVs), including severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have raised great public health concern globally. Here, we report a novel bat-origin CoV causing severe and fatal pneumonia in humans. METHODS: We collected clinical data and bronchoalveolar lavage (BAL) specimens from five patients with severe pneumonia from Wuhan Jinyintan Hospital, Hubei province, China. Nucleic acids of the BAL were extracted and subjected to next-generation sequencing. Virus isolation was carried out, and maximum-likelihood phylogenetic trees were constructed. RESULTS: Five patients hospitalized from December 18 to December 29, 2019 presented with fever, cough, and dyspnea accompanied by complications of acute respiratory distress syndrome. Chest radiography revealed diffuse opacities and consolidation. One of these patients died. Sequence results revealed the presence of a previously unknown ß-CoV strain in all five patients, with 99.8% to 99.9% nucleotide identities among the isolates. These isolates showed 79.0% nucleotide identity with the sequence of SARS-CoV (GenBank NC_004718) and 51.8% identity with the sequence of MERS-CoV (GenBank NC_019843). The virus is phylogenetically closest to a bat SARS-like CoV (SL-ZC45, GenBank MG772933) with 87.6% to 87.7% nucleotide identity, but is in a separate clade. Moreover, these viruses have a single intact open reading frame gene 8, as a further indicator of bat-origin CoVs. However, the amino acid sequence of the tentative receptor-binding domain resembles that of SARS-CoV, indicating that these viruses might use the same receptor. CONCLUSION: A novel bat-borne CoV was identified that is associated with severe and fatal respiratory disease in humans.

A randomized, controlled, feasibility study of RD-X19 in subjects with mild-to-moderate COVID-19 in the outpatient setting.

The RD-X19 is an investigational, handheld medical device precisely engineered to emit blue light through the oral cavity to target the oropharynx and surrounding tissues. At doses shown to be noncytotoxic in an in vitro three-dimensional human epithelial tissue model, the monochromatic visible light delivered by RD-X19 results in light-initiated expression of immune stimulating cytokines IL-1α and IL-1ß, with corresponding inhibition of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) replication. A single exposure of 425 nm blue light at 60 J/cm2 led to greater than 99% reductions against all SARS-CoV-2 strains tested in vitro, including the more transmissible (Alpha) and immune evasive (Beta) variants. These preclinical findings along with other studies led to a randomized, double-blind, sham-controlled early feasibility study using the investigational device as a treatment for outpatients with mild to moderate coronavirus disease 2019 (COVID-19). The study enrolled 31 subjects with a positive SARS-CoV-2 antigen test and at least two moderate COVID-19 signs and symptoms at baseline. Subjects were randomized 2:1 (RD-X19: sham) and treated twice daily for 4 days. Efficacy outcome measures included assessments of SARS-CoV-2 saliva viral load and clinical assessments of COVID-19. There were no local application site reactions and no device-related adverse events. At the end of the study (day 8), the mean change in log10 viral load was -3.29 for RD-X19 and -1.81 for sham, demonstrating a treatment benefit of -1.48 logs (95% confidence internal, -2.88 to -0.071, nominal p = 0.040). Among the clinical outcome measures, differences between RD-X19 and sham were also observed, with a 57-h reduction of median time to sustained resolution of COVID-19 signs and symptoms (log rank test, nominal p = 0.044).

Fractional-Order Discrete-Time SIR Epidemic Model with Vaccination: Chaos and Complexity

This research presents a new fractional-order discrete-time susceptible-infected-recovered (SIR) epidemic model with vaccination. The dynamical behavior of the suggested model is examined analytically and numerically. Through using phase attractors, bifurcation diagrams, maximum Lyapunov exponent and the 0−1 test, it is verified that the newly introduced fractional discrete SIR epidemic model vaccination with both commensurate and incommensurate fractional orders has chaotic behavior. The discrete fractional model gives more complex dynamics for incommensurate fractional orders compared to commensurate fractional orders. The reasonable range of commensurate fractional orders is between γ = 0.8712 and γ = 1, while the reasonable range of incommensurate fractional orders is between γ2 = 0.77 and γ2 = 1. Furthermore, the complexity analysis is performed using approximate entropy (ApEn) and C0 complexity to confirm the existence of chaos. Finally, simulations were carried out on MATLAB to verify the efficacy of the given findings.

Efficacy and Safety of Anticoagulation Treatment in COVID-19 Patient Subgroups Identified by Clinical-Based Stratification and Unsupervised Machine Learning: A Matched Cohort Study.

Objective: To explore the efficacy of anticoagulation in improving outcomes and safety of Coronavirus disease 2019 (COVID-19) patients in subgroups identified by clinical-based stratification and unsupervised machine learning. Methods: This single-center retrospective cohort study unselectively reviewed 2,272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. The association between AC treatment and outcomes was investigated in the propensity score (PS) matched cohort and the full cohort by inverse probability of treatment weighting (IPTW) analysis. Subgroup analysis, identified by clinical-based stratification or unsupervised machine learning, was used to identify sub-phenotypes with meaningful clinical features and the target patients benefiting most from AC. Results: AC treatment was associated with lower in-hospital death risk either in the PS matched cohort or by IPTW analysis in the full cohort. A higher incidence of clinically relevant non-major bleeding (CRNMB) was observed in the AC group, but not major bleeding. Clinical subgroup analysis showed that, at admission, severe cases of COVID-19 clinical classification, mild acute respiratory distress syndrome (ARDS) cases, and patients with a D-dimer level ≥0.5 µg/mL, may benefit from AC. During the hospital stay, critical cases and severe ARDS cases may benefit from AC. Unsupervised machine learning analysis established a four-class clustering model. Clusters 1 and 2 were non-critical cases and might not benefit from AC, while clusters 3 and 4 were critical patients. Patients in cluster 3 might benefit from AC with no increase in bleeding events. While patients in cluster 4, who were characterized by multiple organ dysfunction (neurologic, circulation, coagulation, kidney and liver dysfunction) and elevated inflammation biomarkers, did not benefit from AC. Conclusions: AC treatment was associated with lower in-hospital death risk, especially in critically ill COVID-19 patients. Unsupervised learning analysis revealed that the most critically ill patients with multiple organ dysfunction and excessive inflammation might not benefit from AC. More attention should be paid to bleeding events (especially CRNMB) when using AC.

Efficacy and Safety of Anticoagulation Treatment in COVID-19 Patient Subgroups Identified by Clinical-Based Stratification and Unsupervised Machine Learning: A Matched Cohort Study

Objective: To explore the efficacy of anticoagulation in improving outcomes and safety of Coronavirus disease 2019 (COVID-19) patients in subgroups identified by clinical-based stratification and unsupervised machine learning. Methods: This single-center retrospective cohort study unselectively reviewed 2,272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. The association between AC treatment and outcomes was investigated in the propensity score (PS) matched cohort and the full cohort by inverse probability of treatment weighting (IPTW) analysis. Subgroup analysis, identified by clinical-based stratification or unsupervised machine learning, was used to identify sub-phenotypes with meaningful clinical features and the target patients benefiting most from AC. Results: AC treatment was associated with lower in-hospital death risk either in the PS matched cohort or by IPTW analysis in the full cohort. A higher incidence of clinically relevant non-major bleeding (CRNMB) was observed in the AC group, but not major bleeding. Clinical subgroup analysis showed that, at admission, severe cases of COVID-19 clinical classification, mild acute respiratory distress syndrome (ARDS) cases, and patients with a D-dimer level ≥0.5 μg/mL, may benefit from AC. During the hospital stay, critical cases and severe ARDS cases may benefit from AC. Unsupervised machine learning analysis established a four-class clustering model. Clusters 1 and 2 were non-critical cases and might not benefit from AC, while clusters 3 and 4 were critical patients. Patients in cluster 3 might benefit from AC with no increase in bleeding events. While patients in cluster 4, who were characterized by multiple organ dysfunction (neurologic, circulation, coagulation, kidney and liver dysfunction) and elevated inflammation biomarkers, did not benefit from AC. Conclusions: AC treatment was associated with lower in-hospital death risk, especially in critically ill COVID-19 patients. Unsupervised learning analysis revealed that the most critically ill patients with multiple organ dysfunction and excessive inflammation might not benefit from AC. More attention should be paid to bleeding events (especially CRNMB) when using AC.

Sub-acute hypersensitive reaction to botulinum toxin type A following Covid-19 vaccination: Case report and literature review.

RATIONALE: Botulinum toxin type A (BTA) is one of the most widely used injectable agents in cosmetic surgery. Corona virus disease 2019 (Covid-19) infection and vaccination, which can induce specific and nonspecific activation of the immune system, has been reported to induce delayed inflammatory reactions to previously injected hyaluronic acid fillers. However, there are no reports about the interaction between BTA and Covid-19. We aimed to report 2 sub-acute cases of allergic reactions to BTA in facial cosmesis following the Covid-19 vaccination. PATIENT CONCERN: A 35-year-old and a 34-year-old female who has several previous BTA injections without any adverse effects experienced facial swelling, flu-like symptoms after BTA treatment following the Covid-19 vaccination. DIAGNOSE: According to the typical clinical manifestation, a hypersensitive reaction to BTA was considered. INTERVENTION: Corticosteroids and antihistamine were administered empirically. OUTCOMES: The flu-like symptoms recovered over the next day, but the facial swelling gradually faded within 1 to 2 weeks. LESSONS: A literature review was also conducted to summarize the hypersensitive actions to cosmesis related to Covid-19. We recommend BTA injection be administered at least 2 to 3 months after Covid-19 vaccination.