Multi-objective optimization of mechanical ventilation with the aid of purifiers in two scenarios: Regular operation and mitigating the spread of respiratory infectious diseases.

COVID-19 and its impact on society have raised concerns about scaling up mechanical ventilation (MV) systems and the energy consequences. This paper attempted to combine MV and portable air cleaners (PACs) to achieve acceptable indoor air quality (IAQ) and energy reduction in two scenarios: regular operation and mitigating the spread of respiratory infectious diseases (RIDs). We proposed a multi-objective optimization method that combined the NSGA-II and TOPSIS techniques to determine the total equivalent ventilation rate of the MV-PAC system in both scenarios. The concentrations of PM2.5 and CO2 were primary indicators for IAQ. The modified Wells-Riley equation was adopted to predict RID transmissions. An open office with an MV-PAC system was used to demonstrate the method's applicability. Meanwhile, a field study was conducted to validate the method and evaluate occupants' perceptions of the MV-PAC system. Results showed that optimal solutions of the combined system can be obtained based on various IAQ requirements, seasons, outdoor conditions, etc. For regular operation, PACs were generally prioritized to maintain IAQ while reducing energy consumption even when outdoor PM2.5 concentration was high. MV can remain constant or be reduced at low occupancies. In RID scenarios, it is possible to mitigate transmissions when the quanta were < 48 h-1. No significant difference was found in the subjective perception of the MV and PACs. Moreover, the effects of infiltration on the optimal solution can be substantial. Nonetheless, our results suggested that an MV-PAC system can replace the MV system for offices for daily use and RID mitigation. Electronic Supplementary Material ESM: The Appendix is available in the online version of this article at 10.1007/s12273-023-0999-z.

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion.

Background: The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown. Methods: We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (C r ). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (R t ). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses. Results: (1) The overall level of R t in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, R t decreased rapidly, and the overall R t level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage. Conclusion: Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion

Background The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown. Methods We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (Cr). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (Rt). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses. Results (1) The overall level of Rt in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, Rt decreased rapidly, and the overall Rt level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage. Conclusion Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

Ubiquitin variants potently inhibit SARS-CoV-2 PLpro and viral replication via a novel site distal to the protease active site.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has made it clear that combating coronavirus outbreaks benefits from a combination of vaccines and therapeutics. A promising drug target common to all coronaviruses-including SARS-CoV, MERS-CoV, and SARS-CoV-2-is the papain-like protease (PLpro). PLpro cleaves part of the viral replicase polyproteins into non-structural protein subunits, which are essential to the viral replication cycle. Additionally, PLpro can cleave both ubiquitin and the ubiquitin-like protein ISG15 from host cell substrates as a mechanism to evade innate immune responses during infection. These roles make PLpro an attractive antiviral drug target. Here we demonstrate that ubiquitin variants (UbVs) can be selected from a phage-displayed library and used to specifically and potently block SARS-CoV-2 PLpro activity. A crystal structure of SARS-CoV-2 PLpro in complex with a representative UbV reveals a dimeric UbV bound to PLpro at a site distal to the catalytic site. Yet, the UbV inhibits the essential cleavage activities of the protease in vitro and in cells, and it reduces viral replication in cell culture by almost five orders of magnitude.

Using machine learning models to predict the duration of the recovery of COVID-19 patients hospitalized in Fangcang shelter hospital during the Omicron BA. 2.2 pandemic.

Background: Factors that may influence the recovery of patients with confirmed SARS-CoV-2 infection hospitalized in the Fangcang shelter were explored, and machine learning models were constructed to predict the duration of recovery during the Omicron BA. 2.2 pandemic. Methods: A retrospective study was conducted at Hongqiao National Exhibition and Convention Center Fangcang shelter (Shanghai, China) from April 9, 2022 to April 25, 2022. The demographics, clinical data, inoculation history, and recovery information of the 13,162 enrolled participants were collected. A multivariable logistic regression model was used to identify independent factors associated with 7-day recovery and 14-day recovery. Machine learning algorithms (DT, SVM, RF, DT/AdaBoost, AdaBoost, SMOTEENN/DT, SMOTEENN/SVM, SMOTEENN/RF, SMOTEENN+DT/AdaBoost, and SMOTEENN/AdaBoost) were used to build models for predicting 7-day and 14-day recovery. Results: Of the 13,162 patients in the study, the median duration of recovery was 8 days (interquartile range IQR, 6-10 d), 41.31% recovered within 7 days, and 94.83% recovered within 14 days. Univariate analysis showed that the administrative region, age, cough medicine, comorbidities, diabetes, coronary artery disease (CAD), hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were associated with a duration of recovery within 7 days. Age, gender, vaccination dose, cough medicine, comorbidities, diabetes, CAD, hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were related to a duration of recovery within 14 days. In the multivariable analysis, the receipt of two doses of the vaccination vs. unvaccinated (OR = 1.118, 95% CI = 1.003-1.248; p = 0.045), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.114, 95% CI = 1.004-1.236; p = 0.043), diabetes (OR = 0.383, 95% CI = 0.194-0.749; p = 0.005), CAD (OR = 0.107, 95% CI = 0.016-0.421; p = 0.005), hypertension (OR = 0.371, 95% CI = 0.202-0.674; p = 0.001), and ratio of N/IC (OR = 3.686, 95% CI = 2.939-4.629; p < 0.001) were significantly and independently associated with a duration of recovery within 7 days. Gender (OR = 0.736, 95% CI = 0.63-0.861; p < 0.001), age (30-70) (OR = 0.738, 95% CI = 0.594-0.911; p < 0.001), age (>70) (OR = 0.38, 95% CI = 0292-0.494; p < 0.001), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.391, 95% CI = 1.12-1.719; p = 0.0033), cough medicine (OR = 1.509, 95% CI = 1.075-2.19; p = 0.023), and symptoms (OR = 1.619, 95% CI = 1.306-2.028; p < 0.001) were significantly and independently associated with a duration of recovery within 14 days. The SMOTEEN/RF algorithm performed best, with an accuracy of 90.32%, sensitivity of 92.22%, specificity of 88.31%, F1 score of 90.71%, and AUC of 89.75% for the 7-day recovery prediction; and an accuracy of 93.81%, sensitivity of 93.40%, specificity of 93.81%, F1 score of 93.42%, and AUC of 93.53% for the 14-day recovery prediction. Conclusion: Age and vaccination dose were factors robustly associated with accelerated recovery both on day 7 and day 14 from the onset of disease during the Omicron BA. 2.2 wave. The results suggest that the SMOTEEN/RF-based model could be used to predict the probability of 7-day and 14-day recovery from the Omicron variant of SARS-CoV-2 infection for COVID-19 prevention and control policy in other regions or countries. This may also help to generate external validation for the model.

Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission.

With the recent prevalence of COVID-19, cryptic transmission is worthy of attention and research. Early perception of the occurrence and development risk of cryptic transmission is an important part of controlling the spread of COVID-19. Previous relevant studies have limited data sources, and no effective analysis has been carried out on the occurrence and development of cryptic transmission. Hence, we collect Internet multisource big data (including retrieval, migration, and media data) and propose comprehensive and relative application strategies to eliminate the impact of national and media data. We use statistical classification and regression to construct an early warning model for occurrence and development. Under the guidance of the improved coronavirus herd immunity optimizer (ICHIO), we construct a "sampling-feature-hyperparameter-weight" synchronous optimization strategy. In occurrence warning, we propose an undersampling synchronous evolutionary ensemble (USEE); in development warning, we propose a bootstrap-sampling synchronous evolutionary ensemble (BSEE). Regarding the internal training data (Heilongjiang Province), the ROC-AUC of USEE3 incorporating multisource data is 0.9553, the PR-AUC is 0.8327, and the R2 of BSEE2 fused by the "nonlinear + linear" method is 0.8698. Regarding the external validation data (Shaanxi Province), the ROC-AUC and PR-AUC values of USEE3 were 0.9680 and 0.9548, respectively, and the R2 of BSEE2 was 0.8255. Our method has good accuracy and generalization and can be flexibly used in the prediction of cryptic transmission in various regions. We propose strategy research that integrates multiple early warning tasks based on multisource Internet big data and combines multiple ensemble models. It is an extension of the research in the field of traditional infectious disease monitoring and has important practical significance and innovative theoretical value.

Improving antibody affinity through in vitro mutagenesis in complementarity determining regions.

High-affinity antibodies are widely used in diagnostics and for the treatment of human diseases. However, most antibodies are isolated from semi-synthetic libraries by phage display and do not possess in vivo affinity maturation, which is triggered by antigen immunization. It is therefore necessary to engineer the affinity of these antibodies by way of in vitro assaying. In this study, we optimized the affinity of two human monoclonal antibodies which were isolated by phage display in a previous related study. For the 42A1 antibody, which targets the liver cancer antigen glypican-3, the variant T57H in the second complementarity-determining region of the heavy chain (CDR-H2) exhibited a 2.6-fold improvement in affinity, as well as enhanced cell-binding activity. For the I4A3 antibody to severe acute respiratory syndrome coronavirus 2, beneficial single mutations in CDR-H2 and CDR-H3 were randomly combined to select the best synergistic mutations. Among these, the mutation S53P-S98T improved binding affinity (about 3.7 fold) and the neutralizing activity (about 12 fold) compared to the parent antibody. Taken together, single mutations of key residues in antibody CDRs were enough to increase binding affinity with improved antibody functions. The mutagenic combination of key residues in different CDRs creates additive enhancements. Therefore, this study provides a safe and effective in vitro strategy for optimizing antibody affinity.

Tetravalent SARS-CoV-2 Neutralizing Antibodies Show Enhanced Potency and Resistance to Escape Mutations.

Neutralizing antibodies (nAbs) hold promise as therapeutics against COVID-19. Here, we describe protein engineering and modular design principles that have led to the development of synthetic bivalent and tetravalent nAbs against SARS-CoV-2. The best nAb targets the host receptor binding site of the viral S-protein and tetravalent versions block entry with a potency exceeding bivalent nAbs by an order of magnitude. Structural studies show that both the bivalent and tetravalent nAbs can make multivalent interactions with a single S-protein trimer, consistent with the avidity and potency of these molecules. Significantly, we show that the tetravalent nAbs show increased tolerance to potential virus escape mutants and an emerging variant of concern. Bivalent and tetravalent nAbs can be produced at large-scale and are as stable and specific as approved antibody drugs. Our results provide a general framework for enhancing antiviral therapies against COVID-19 and related viral threats, and our strategy can be applied to virtually any antibody drug.

Temporal lung changes on thin-section CT in patients with COVID-19 pneumonia.

We examined characteristics of chest CT across different time periods for patients with COVID-19 pneumonia in Huizhou, China. This study included 56 COVID-19 patients with abnormal CT acquired between January 22 and March 3, 2020. The 141 scans of 56 patients were classified into four groups (Groups 1-4) based on dates on which scans were obtained at the 1st, 2nd, 3rd week or longer than three weeks after illness onset. Forty-five patients with follow-up scans were categorized into four groups (Groups A-D) according to extent that lesions reduced (≥ 75%, 50-75%, 25-50% and < 25%). Ground-glass opacities (GGO) was prevalent in Groups 1-4 (58.1-82.6%), while percentages of consolidation ranged between 9.7% in Group 4 and 26.2% in Group 2. The highest frequency of fibrous stripes occurred in Group 3 (46.7%). Total CT scores were on average higher in Groups 2-3. Among 45 follow-up patients, 11 (24.4%) of them recovered with lesions reducing ≥ 75%, with the lowest median age and total CT scores on admission. There are temporal patterns of lung abnormalities in COVID-19 patients, with higher extent of lesion involvement occurring in the 2nd and 3rd week. Persisting lung changes indicate some patients may need isolation after discharge from hospital.

Declined serum high density lipoprotein cholesterol is associated with the severity of COVID-19 infection.

BACKGROUND: COVID-19 infection is epidemic worldwide. We describe the serum lipid profile of the patients with COVID-19 infection. METHODS: In this retrospective study, we collected the first clinical laboratory data of 114 patients on admission, and 80 healthy controls. Meanwhile, we monitored the serum lipid profile, COVID-19 nucleic acid and chest CT scan of a severe patient from the early stage of infection to the recovery period for a total of 80 days. RESULTS: Compared with the healthy controls, the patients had sharply decreased concentrations of total cholesterol, HDL-cholesterol and LDL-cholesterol (P < 0.001). Among the patients, HDL-cholesterol concentration in severe groups was significantly lower than the common groups [1.01 (0.88-1.20) vs 1.21 (1.02-1.48) mmol/l, P < 0.001]. The lipid profile of a severe patient showed that serum cholesterol concentration significantly decreased in the early stage and returned to be normal in the recovery period. Moreover, the change of HDL-cholesterol in this patient was consistent with the results of nucleic acid tests and chest CT scans. In correlation analysis, HDL-cholesterol concentration was negatively correlated with C-reactive protein (CRP, r = -0.396, P < 0.001) and positively correlated with lymphocytes (r = 0.336, P < 0.001). The area under curve (AUC) in receiver operating characteristic (ROC) of HDL-cholesterol was 0.732 (P < 0.001), and, the adjusted odd ratio (OR) of HDL-cholesterol was 0.023 (95% CI 0.002-0.227). CONCLUSIONS: Decreased serum HDL-cholesterol is associated with the severity of COVID-19 infection.

Remdesivir (GS-5734) Impedes Enterovirus Replication Through Viral RNA Synthesis Inhibition.

Human enteroviruses are responsible for diverse diseases, from mild respiratory symptoms to fatal neurological complications. Currently, no registered antivirals have been approved for clinical therapy. Thus, a therapeutic agent for the enterovirus-related disease is urgently needed. Remdesivir (GS-5734) is a novel monophosphoramidate adenosine analog prodrug that exhibits potent antiviral activity against diverse RNA virus families, including positive-sense Coronaviridae and Flaviviridae and negative-sense Filoviridae, Paramyxoviridae, and Pneumoviridae. Currently, remdesivir is under phase 3 clinical development for disease COVID-19 treatment. Here, we found that remdesivir impeded both EV71 viral RNA (vRNA) and complementary (cRNA) synthesis, indicating that EV71 replication is inhibited by the triphosphate (TP) form of remdesivir. Moreover, remdesivir showed potent antiviral activity against diverse enteroviruses. These data extend the remdesivir antiviral activity to enteroviruses and indicate that remdesivir is a promising antiviral treatment for EV71 and other enterovirus infections.

Emergency Responses to Covid-19 Outbreak: Experiences and Lessons from a General Hospital in Nanjing, China.

BACKGROUND: The novel coronavirus 2019 (SARS-CoV-2) has caused wide dissemination across the world. Global health systems are facing the unprecedented challenges. Here we shared the experiences and lessons in emergency responses and management from our hospital, a government-assigned regional anti-Covid-19 general hospital in Nanjing, Jiangsu Province, China. METHODS: Our periodic strategies in dealing with Covid-19 were described in detail. An administrative response including the establishment of Emergency Leadership Committee that was in full charge of management was established. Modifications of infrastructure including the Fever Clinic, inpatient ward, outpatient clinic and operation room were carried out. Special arrangements for outpatient services, hospitalization and surgeries were introduced. Medical personnel training and patient educations were performed. Initiations of Covid-19 researches and application of information technology were introduced. FINDINGS: Since January 16, three cases have been confirmed in our hospital and no healthcare-associated infection was found. During the epidemics, 6.46% staffs suffered depression, 9.87% had anxiety, and 98% were satisfied with the infection control policy. Shortages in staffs and medical consumables, and limitation in space were the obstacles we encountered. INTERPRETATION: As the cost of in-hospital transmission is unbearable, our experiences and lessons suggested that prompt actions should be taken immediately to decrease or eliminate potential in-hospital transmission. Experience shared herein may be useful for those facilities that are and may encounter Covid-19.