IoT-Based Epidemic Monitoring via Improved Gated Recurrent Unit Model

During the Coronavirus Disease 2019 (COVID-19) pandemic, non-contact health monitoring and human activity detection by various sensors have attracted tremendous attention. Robot monitoring will result in minimizing the life threat to health providers during the COVID-19 pandemic period. How to improve the performance and generalization of the monitoring model is a critical but challenging task. This paper constructs an epidemic monitoring architecture based on multi-sensor information fusion and applies it in medical robots’ services, such as patient-care, disinfection, garbage disposal, etc. We propose a gated recurrent unit model based on a genetic algorithm (GA-GRU)to realize the effective feature selection and improve the effectiveness and accuracy of the localization, navigation, and activity monitoring for indoor wireless sensor networks (WSNs). By using two GRU layers in the GA-GRU, we improve the generalization capability in multiple WSNs. All these advantages of GA-GRU make it outperform other representative algorithms in a variety of evaluation metrics. The experiments on the WSNs verify that the proposed GA-GRU leads to successful runs and provides optimal performances. These results suggest the GA-GRU method may be preferable for epidemic monitoring in medicine and allied areas with particular relation to the control of the epidemic or pandemic such as COVID-19 pandemic.

Ultrabright nanoparticle-labeled lateral flow immunoassay for detection of anti-SARS-CoV-2 neutralizing antibodies in human serum.

The level of anti-SARS-CoV-2 neutralizing antibodies (NAb) is an indispensable reference for evaluating the acquired protective immunity against SARS-CoV-2. Here, we established an ultrabright nanoparticles-based lateral flow immunoassay (LFIA) for one-step rapid semi-quantitative detection of anti-SARS-CoV-2 NAb in vaccinee's serum. Once embedded in polystyrene (PS) nanoparticles, the aggregation-induced emission (AIE) luminogen, AIE490, exhibited ultrabright fluorescence due to the rigidity of PS and severe inhibition of intramolecular motions. The ultrabright AIE490-PS nanoparticle was used as a fluorescent marker of LFIA. Upon optimized conditions including incubation time, concentrations of coated proteins and conjugated nanoparticles, amounts of antigens modified on the surface of nanoparticles, dilution rate of serum samples, and so on, the ultrabright nanoparticles-based LFIA could accurately identify 70 negative samples and 63 positive samples from human serum (p < 0.0001). The intra- and inter-assay precisions of the established method are above 13% and 16%, respectively. The established LFIA has tremendous practical value of generalization as a rapid semi-quantitative detection method of anti-SARS-CoV-2 NAb. Meanwhile, the AIE490-PS nanoparticle is also promising to detect many other analytes by altering the protein on the surface.

Novel skewed usage of B-cell receptors in COVID-19 patients with various clinical presentations.

B cell-mediated immune responses play important roles in controlling SARS-CoV infection. Here, we performed the single-cell B cell receptor sequencing (scBCR-seq) of the PBMC samples from eleven healthy controls, five asymptomatic subjects and 33 symptomatic COVID-19 patients with various clinical presentations, and subsequently analyzed the abundance and diversity of the BCR repertoires in different groups, respectively. We revealed the skewed usage of the IGHV, IGLV and IGKV genes and identified a number of heavy or light chain VDJ gene pairs and combinational preference in each group, such as IGKV3-7 and IGKV2-24 enriched in the asymptomatic subjects, whereas IGHV3-13, IGHV3-23-IGHJ4, IGHV1-18-IGLV3-19, IGHV1-18-IGLV3-21, and IGHV1-18-IGLV3-25 enriched in the recovery patients with severe diseases. We also observed the differential expression of IGHV3-23 in various B cell clusters by analysis of the scRNA-seq data. Additional dock analysis indicated that IGHV3-13 could bind to the spike protein of SARS-CoV-2. These findings may advance our understanding of the humoral immune responses in COVID-19 patients and help develop novel vaccine candidates as well as therapeutical antibodies against SASR-CoV-2 infections.

Identification of TCR repertoires in asymptomatic COVID-19 patients by single-cell T-cell receptor sequencing.

The T cell-mediated immune responses associated with asymptomatic infection (AS) of SARS-CoV-2 remain largely unknown. The diversity of T-cell receptor (TCR) repertoire is essential for generating effective immunity against viral infections in T cell response. Here, we performed the single-cell TCR sequencing of the PBMC samples from five AS subjects, 33 symptomatic COVID-19 patients and eleven healthy controls to investigate the size and the diversity of TCR repertoire. We subsequently analyzed the TCR repertoire diversity, the V and J gene segment deference, and the dominant combination of αß VJ gene pairing among these three study groups. Notably, we revealed significant TCR preference in the AS group, including the skewed usage of TRAV1-2-J33-TRBV6-4-J2-2 and TRAV1-2-J33-TRBV6-1-J2-3. Our findings may shed new light on understanding the immunopathogenesis of COVID-19 and help identify optimal TCRs for development of novel therapeutic strategies against SARS-CoV-2 infection.

Identification of Distinct Immune Cell Subsets Associated With Asymptomatic Infection, Disease Severity, and Viral Persistence in COVID-19 Patients.

The cell-mediated protective and pathogenic immune responses to SARS-CoV-2 infection remain largely elusive. Here we identified 76 distinct cell subsets in the PBMC samples that were associated with various clinical presentations of COVID-19 using scRNA-seq technology coupled with a deep and comprehensive analysis of unique cell surface markers and differentially expressed genes. We revealed that (TRAV1-2+CD8+)MAIT cells and (NCAM1hiCD160+)NK cells significantly enriched in the asymptomatic subjects whereas (LAG3+CD160+CD8+)NKT cells increased in the symptomatic patients. We also observed that (CD68-CSF1R-IL1BhiCD14+)classical monocytes were positively correlated with the disease severity. Moreover, (CD33-HLA-DMA-CD14+)classical monocytes and (CLEC10A-S100A9lo)pDC were associated with the viral persistence. The GO and KEGG analyses identified enriched pathways related to immune responses, inflammation, and apoptosis. These findings may enhance our understanding of the immunopathogenesis of COVID-19 and help develop novel strategies against SARS-CoV-2 infection.

Distinct miRNAs associated with various clinical presentations of SARS-CoV-2 infection.

MicroRNAs (miRNAs) have been shown to play important roles in viral infections, but their associations with SARS-CoV-2 infection remain poorly understood. Here, we detected 85 differentially expressed miRNAs (DE-miRNAs) from 2,336 known and 361 novel miRNAs that were identified in 233 plasma samples from 61 healthy controls and 116 patients with COVID-19 using the high-throughput sequencing and computational analysis. These DE-miRNAs were associated with SASR-CoV-2 infection, disease severity, and viral persistence in the patients with COVID-19, respectively. Gene ontology and KEGG pathway analyses of the DE-miRNAs revealed their connections to viral infections, immune responses, and lung diseases. Finally, we established a machine learning model using the DE-miRNAs between various groups for classification of COVID-19 cases with different clinical presentations. Our findings may help understand the contribution of miRNAs to the pathogenesis of COVID-19 and identify potential biomarkers and molecular targets for diagnosis and treatment of SARS-CoV-2 infection.

Government Performance Evaluation in the Context of Carbon Neutrality: Energy-Saving of New Residential Building Projects

The government’s supervision of new residential building projects’ (NRBPs) energy-saving can promote carbon neutrality policies within its jurisdiction. A scientific and systematic evaluation of NRBPs energy-saving reflects a government’s management performance. However, achieving accurate and reasonable results with unitary evaluation standards without considering regional characteristics is not easy. This study proposes an evaluation method of intelligently evaluating the effectiveness of government energy-saving supervision with regional characteristics weighted in. Consequently, these evaluation indicators can reveal the key issues in carrying out local energy-saving policies and provide concrete guidance for local governments to manage the energy-saving of NRBPs better. The method was tested with ten projects and found to be effective.

Inflammation-related adverse reactions following vaccination potentially indicate a stronger immune response.

Concerns about vaccine safety are an important reason for vaccine hesitancy, however, limited information is available on whether common adverse reactions following vaccination affect the immune response. Data from three clinical trials of recombinant vaccines were used in this post hoc analysis to assess the correlation between inflammation-related solicited adverse reactions (ISARs, including local pain, redness, swelling or induration and systematic fever) and immune responses after vaccination. In the phase III trial of the bivalent HPV-16/18 vaccine (Cecolin®), the geometric mean concentrations (GMCs) for IgG anti-HPV-16 and -18 (P<0.001) were significantly higher in participants with any ISAR following vaccination than in those without an ISAR. Local pain, induration, swelling and systemic fever were significantly correlated with higher GMCs for IgG anti-HPV-16 and/or anti-HPV-18, respectively. Furthermore, the analyses of the immunogenicity bridging study of Cecolin® and the phase III trial of a hepatitis E vaccine yielded similar results. Based on these results, we built a scoring model to quantify the inflammation reactions and found that the high score of ISAR indicates the strong vaccine-induced antibody level. In conclusion, this study suggests inflammation-related adverse reactions following vaccination potentially indicate a stronger immune response.

Systematic review and meta-analysis of tocilizumab in persons with coronavirus disease-2019 (COVID-19).

We performed a meta-analysis to determine safety and efficacy of tocilizumab in persons with coronavirus disease-2019 (COVID-19). We searched PubMed, Web of Science and Medline using Boolean operators for studies with the terms coronavirus OR COVID-19 OR 2019-nCoV OR SARS-CoV-2 AND tocilizumab. Review Manager 5.4 was used to analyze data and the modified Newcastle-Ottawa and Jadad scales for quality assessment. We identified 32 studies in 11,487 subjects including three randomized trials and 29 cohort studies with a comparator cohort, including historical controls (N = 5), a matched cohort (N = 12), or concurrent controls (N = 12). Overall, tocilizumab decreased risk of death (Relative Risk [RR] = 0.74; 95% confidence interval [CI], 0.59, 0.93; P = 0.008; I2 = 80%) but not of surrogate endpoints including ICU admission (RR = 1.40 [0.64,3.06]; P = 0.4; I2 = 88%), invasive mechanical ventilation (RR = 0.83 [0.57,1.22]; P = 0.34; I2 = 65%) or secondary infections (RR = 1.30 [0.97,1.74]; P = 0.08; I2 = 65%) and increased interval of hospitalization of subjects discharged alive(mean difference [MD] = 2 days [<1, 4 days]; P = 0.006; I2 = 0). RRs of death in studies with historical controls (RR = 0.28 [0.16,0.49; P < 0.001]; I2 = 62%) or a matched cohort (RR = 0.68 [0.53, 0.87]; P = 0.002; I2 = 42%) were decreased. In contrast, RRs of death in studies with a concurrent control (RR = 1.10 [0.77, 1.56]; P = 0.60; I2 = 85%) or randomized (RR = 1.18 [0.57,2.44]; P = 0.66; I2 = 0) were not decreased. A reduced risk of death was not confirmed in our analyses which questions safety and efficacy of tocilizumab in persons with COVID-19.

Association of serum uric acid levels with COVID-19 severity.

AIMS: Hyperuricemia has attracted increasing attention. However, limited concern has been paid to the potential dangers of lowering serum uric acid (SUA). We observed lower levels of SUA in patients with COVID-19. Therefore, we aim to explore whether patients with COVID-19 had SUA lower than normal and the relationship of SUA and the severity of COVID-19. METHODS: This was a case-control study based on 91 cases with COVID-19 and 273 age- and sex-matched healthy control subjects. We first compared SUA levels and uric acid/creatinine (UA/Cr) ratio between patients with COVID-19 and the healthy controls. Then, we examined the association of SUA levels and UA/Cr ratios with COVID-19 severity in COVID-19 cases only, defined according to the fifth edition of China's Diagnosis and Treatment Guidelines of COVID-19. RESULTS: SUA levels in patients with COVID-19 were 2.59% lower, UA/Cr ratios 6.06% lower at admission compared with healthy controls. In sex stratified analysis, levels of SUA and UA/Cr were lower in male patients with COVID-19 while only level of SUA was lower in female patients with COVID-19. Moreover, SUA and UA/Cr values were 4.27 and 8.23% lower in the severe group than that in the moderate group among male COVID-19 patients. Bivariate and partial correlations analysis showed negative correlations between SUA or UA/Cr ratio and COVID-19 after adjusting for age, sex, BMI and eGFR. A multiple linear regression analysis showed that SARS-CoV-2 infection and male sex were independent risk factors associated with lower SUA levels. Male patients with COVID-19 accompanied by low SUA levels had higher risk of developing severe symptoms than those with high SUA levels (incidence rate ratio: 4.05; 95% CI:1.11, 14.72) at admission. Comparing SUA and UA/Cr ratio at three time points (admission, discharge, and follow-up), we found that male patients experienced severe symptoms had lower SUA and UA/Cr ratio levels comparing to moderate patients, but no significant difference between three time points. On the contrary, female patients had lower SUA and UA/Cr ratio at discharge than those at admission, but no significant difference of SUA and UA/Cr ratio between moderate and severe group. CONCLUSION: Patients with COVID-19 had SUA and UA/Cr values lower than normal at admission. Male COVID-19 patients with low SUA levels had a significantly higher crude risk of developing severe symptoms than those with high SUA levels. During disease aggravation, the level of SUA gradually decreased until discharge. At the follow-up exam, the level of SUA was similar to the levels at admission.

An analysis model of diagnosis and treatment for COVID-19 pandemic based on medical information fusion.

Exploring the complicated relationships underlying the clinical information is essential for the diagnosis and treatment of the Coronavirus Disease 2019 (COVID-19). Currently, few approaches are mature enough to show operational impact. Based on electronic medical records (EMRs) of 570 COVID-19 inpatients, we proposed an analysis model of diagnosis and treatment for COVID-19 based on the machine learning algorithms and complex networks. Introducing the medical information fusion, we constructed the heterogeneous information network to discover the complex relationships among the syndromes, symptoms, and medicines. We generated the numerical symptom (medicine) embeddings and divided them into seven communities (syndromes) using the combination of Skip-Gram model and Spectral Clustering (SC) algorithm. After analyzing the symptoms and medicine networks, we identified the key factors using six evaluation metrics of node centrality. The experimental results indicate that the proposed analysis model is capable of discovering the critical symptoms and symptom distribution for diagnosis; the key medicines and medicine combinations for treatment. Based on the latest COVID-19 clinical guidelines, this model could result in the higher accuracy results than the other representative clustering algorithms. Furthermore, the proposed model is able to provide tremendously valuable guidance and help the physicians to combat the COVID-19.

Joint Detection of Serum IgM/IgG Antibody Is an Important Key to Clinical Diagnosis of SARS-CoV-2 Infection.

BACKGROUND: This study was aimed to investigate the application of SARS-CoV-2 IgM and IgG antibodies in diagnosis of COVID-19 infection. METHOD: This study enrolled a total of 178 patients at Huangshi Central Hospital from January to February 2020. Among them, 68 patients were SARS-CoV-2 infected, confirmed with nucleic acid test (NAT) and CT imaging. Nine patients were in the suspected group (NAT negative) with fever and other respiratory symptoms. 101 patients were in the control group with other diseases and negative to SARS-CoV-2 infection. After serum samples were collected, SARS-CoV-2 IgG and IgM antibodies were tested by chemiluminescence immunoassay (CLIA) for all patients. RESULTS: The specificity of serum IgM and IgG antibodies to SARS-CoV-2 was 99.01% (100/101) and 96.04% (97/101), respectively, and the sensitivity was 88.24% (60/68) and 97.06% (66/68), respectively. The combined detection rate of SARS-CoV-2 IgM and IgG antibodies was 98.53% (67/68). CONCLUSION: Combined detection of serum SARS-CoV-2 IgM and IgG antibodies had better sensitivity compared with single IgM or IgG antibody testing, which can be used as an important diagnostic tool for SARS-CoV-2 infection and a screening tool of potential SARS-CoV-2 carriers in clinics, hospitals, and accredited scientific laboratories.

Development and multicenter performance evaluation of fully automated SARS-CoV-2 IgM and IgG immunoassays.

Objectives: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread globally. The laboratory diagnosis of SARS-CoV-2 infection has relied on nucleic acid testing; however, it has some limitations, such as low throughput and high rates of false negatives. Tests of higher sensitivity are needed to effectively identify infected patients. Methods: This study has developed fully automated chemiluminescent immunoassays to determine IgM and IgG antibodies to SARS-CoV-2 in human serum. The assay performance has been evaluated at 10 hospitals. Clinical specificity was evaluated by measuring 972 hospitalized patients and 586 donors of a normal population. Clinical sensitivity was assessed on 513 confirmed cases of SARS-CoV-2 by RT-PCR. Results: The assays demonstrated satisfied assay precision with coefficient of variation of less than 4.45%. Inactivation of specimen did not affect assay measurement. SARS-CoV-2 IgM showed clinical specificity of 97.33 and 99.49% for hospitalized patients and the normal population respectively, and SARS-CoV-2 IgG showed clinical specificity of 97.43 and 99.15% respectively. SARS-CoV-2 IgM showed clinical sensitivity of 82.54, 92.93, and 84.62% before 7 days, 7-14 days, and after 14 days respectively, since onset of symptoms, and SARS-CoV-2 IgG showed clinical sensitivity of 80.95, 97.98, and 99.15% respectively at the same time points above. Conclusions: We have developed fully automated immunoassays for detecting SARS-CoV-2 IgM and IgG antibodies in human serum. The assays demonstrated high clinical specificity and sensitivity, and add great value to nucleic acid testing in fighting against the global pandemic of the SARS-CoV-2 infection.

A profiling analysis on the receptor ACE2 expression reveals the potential risk of different type of cancers vulnerable to SARS-CoV-2 infection.

BACKGROUND: The new coronavirus pneumonia (NCP) is now causing a severe public health emergency. The novel coronavirus 2019 (2019-nCoV) infected individuals by binding human angiotensin converting enzyme II (ACE2) receptor. ACE2 is widely expressed in multiple organs including respiratory, cardiovascular, digestive and urinary systems in healthy individuals. These tissues with high expression level of ACE2 seemed to be more vulnerable to SARS-CoV-2 infection. Recently, it has been reported that patients with tumors were likely to be more susceptible to SARS-CoV-2 infection and indicated poor prognosis. METHODS: The tissue atlas database and the blood atlas were used to analyze the distribution of ACE2 in human tissues or organs of cancers and normal samples. Starbase dataset was applied to predict the prognosis of cancers according to expression level of ACE2. RESULTS: In this study, we demonstrated a landscape profiling analysis on expression level of ACE2 in pan-cancers and showed the risky of different type of cancers to SARS-CoV-2 according to the expression level of ACE2. In addition, we found that ACE2 was both differential expression and related to the prognosis only in liver hepatocellular carcinoma (LIHC). Relative high expression of ACE2 indicated a favorable prognosis in LIHC, but they might be more susceptible to SARS-CoV-2. CONCLUSIONS: We indeed emphasized that LIHC patients with high expression level of ACE2 should be more cautious of the virus infection. Our study might provide a potential clue for preventing infection of SARS-CoV-2 in cancers.

Impact of corticosteroid therapy on outcomes of persons with SARS-CoV-2, SARS-CoV, or MERS-CoV infection: a systematic review and meta-analysis.

We performed a meta-analysis to determine safety and efficacy of corticosteroids in SARS-CoV-2, SARS-CoV, and MERS-CoV infections. We searched PubMed, Web of Science, Medline, WanFang Chinese database, and ZhiWang Chinese database using Boolean operators and search terms covering SARS-CoV-2, SARS-CoV, OR MERS-CoV AND corticosteroids to find appropriate studies. Review Manager 5.3 was used to analyze results of meta-analysis. Observational studies were analyzed for quality using the modified Newcastle-Ottawa scale and randomized clinical trials, using the Jadad scale. Subjects were divided into those with severe-only and other (severe and not severe) cohorts based on published criteria. Efficacy endpoints studied included mortality, hospitalization duration, rates of intensive care unit (ICU) admission, use of mechanical ventilation, and a composite endpoint (death, ICU admission, or mechanical ventilation). We included 11 reports including 10 cohort studies and 1 randomized clinical trial involving 5249 subjects (2003-2020). Two discussed the association of corticosteroids and virus clearing and 10 explored how corticosteroids impacted mortality, hospitalization duration, use of mechanical ventilation, and a composite endpoint. Corticosteroid use was associated with delayed virus clearing with a mean difference (MD) = 3.78 days (95% confidence Interval [CI] = 1.16, 6.41 days; I2 = 0%). There was no significant reduction in deaths with relative Risk Ratio (RR) = 1.07 (90% CI = 0.81; 1.42; I2 = 80%). Hospitalization duration was prolonged and use of mechanical ventilation increased. In conclusion, corticosteroid use in subjects with SARS-CoV-2, SARS-CoV, and MERS-CoV infections delayed virus clearing and did not convincingly improve survival, reduce hospitalization duration or ICU admission rate and/or use of mechanical ventilation. There were several adverse effects. Because of a preponderance of observational studies in the dataset and selection and publication biases our conclusions, especially regarding SARS-CoV-2, need confirmation in a randomized clinical trial. In the interim we suggest caution using corticosteroids in persons with COVID-19.