Intelligent operation, maintenance, and control system for public building: towards infection risk mitigation and energy efficiency

During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control system by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different number of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% with number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.

Intelligent operation, maintenance, and control system for public building: Towards infection risk mitigation and energy efficiency.

During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control systems by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% when number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.

Tissue- and cell-expression of druggable host proteins provide insights into repurposing drugs for COVID-19.

Several human host proteins play important roles in the lifecycle of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Many drugs targeting these host proteins have been investigated as potential therapeutics for coronavirus disease 2019 (COVID-19). The tissue-specific expressions of selected host proteins were summarized using proteomics data retrieved from the Human Protein Atlas, ProteomicsDB, Human Proteome Map databases, and a clinical COVID-19 study. Protein expression features in different cell lines were summarized based on recent proteomics studies. The half-maximal effective concentration or half-maximal inhibitory concentration values were collected from in vitro studies. The pharmacokinetic data were mainly from studies in healthy subjects or non-COVID-19 patients. Considerable tissue-specific expression patterns were observed for several host proteins. ACE2 expression in the lungs was significantly lower than in many other tissues (e.g., the kidneys and intestines); TMPRSS2 expression in the lungs was significantly lower than in other tissues (e.g., the prostate and intestines). The expression levels of endocytosis-associated proteins CTSL, CLTC, NPC1, and PIKfyve in the lungs were comparable to or higher than most other tissues. TMPRSS2 expression was markedly different between cell lines, which could be associated with the cell-dependent antiviral activities of several drugs. Drug delivery receptor ICAM1 and CTSB were expressed at a higher level in the lungs than in other tissues. In conclusion, the cell- and tissue-specific proteomics data could help interpret the in vitro antiviral activities of host-directed drugs in various cells and aid the transition of the in vitro findings to clinical research to develop safe and effective therapeutics for COVID-19.

Ventilation Strategies for Mitigation of Infection Disease Transmission in an Indoor Environment: A Case Study in Office

During the normalization phase of the COVID-19 epidemic, society has gradually reverted to using building space, especially for public buildings, e.g., offices. Prevention of airborne pollutants has emerged as a major challenge. Ventilation strategies can contribute to mitigating the spread of airborne disease in an indoor environment, including increasing supply air rate, modifying ventilation mode, etc. The larger ventilation rate can inevitably lead to high energy consumption, which may be also ineffective in reducing infection risk. As a critical factor affecting the spread of viral contaminant, the potential of ventilation modes for control of COVID-19 should be explored. This study compared several ventilation strategies in the office, including mixing ventilation (MV), zone ventilation (ZV), stratum ventilation (SV) and displacement ventilation (DV), through analyzing ventilation performance and infection risk for the optimal one. By using ANSYS Fluent, the distributions of airflow and pollutant were simulated under various ventilation modes and infected occupants. The SV showed greater performance in mitigating infection disease spread than MV, ZV and DV, with an air distribution performance index (ADPI) of 90.5% and minimum infection risk of 13%. This work can provide a reference for development of ventilation strategies in public space oriented the prevention of COVID-19.

Comparative Analysis of the Therapeutic Effects of Amniotic Membrane and Umbilical Cord Derived Mesenchymal Stem Cells for the Treatment of Type 2 Diabetes.

Type 2 diabetes mellitus (T2DM), one of the most common carbohydrate metabolism disorders, is characterized by chronic hyperglycemia and insulin resistance (IR), and has become an urgent global health challenge. Mesenchymal stem cells (MSCs) originating from perinatal tissues such as umbilical cord (UC) and amniotic membrane (AM) serve as ideal candidates for the treatment of T2DM due to their great advantages in terms of abundant source, proliferation capacity, immunomodulation and plasticity for insulin-producing cell differentiation. However, the optimally perinatal MSC source to treat T2DM remains elusive. This study aims to compare the therapeutic efficacy of MSCs derived from AM and UC (AMMSCs and UCMSCs) of the same donor in the alleviation of T2DM symptoms and explore the underlying mechanisms. Our results showed that AMMSCs and UCMSCs displayed indistinguishable immunophenotype and multi-lineage differentiation potential, but UCMSCs had a much higher expansion capacity than AMMSCs. Moreover, we uncovered that single-dose intravenous injection of either AMMSCs or UCMSCs could comparably reduce hyperglycemia and improve IR in T2DM db/db mice. Mechanistic investigations revealed that either AMMSC or UCMSC infusion could greatly improve glycolipid metabolism in the liver of db/db mice, which was evidenced by decreased liver to body weight ratio, reduced lipid accumulation, upregulated glycogen synthesis, and increased Akt phosphorylation. Taken together, these data indicate that the same donor-derived AMMSCs and UCMSCs possessed comparable effects and shared a similar hepatoprotective mechanism on the alleviation of T2DM symptoms.

Model-Informed Drug Development Approaches to Assist New Drug Development in the COVID-19 Pandemic.

Leveraging limited clinical and nonclinical data through modeling approaches facilitates new drug development and regulatory decision making amid the coronavirus disease 2019 (COVID-19) pandemic. Model-informed drug development (MIDD) is an essential tool to integrate those data and generate evidence to (i) provide support for effectiveness in repurposed or new compounds to combat COVID-19 and dose selection when clinical data are lacking; (ii) assess efficacy under practical situations such as dose reduction to overcome supply issues or emergence of resistant variant strains; (iii) demonstrate applicability of MIDD for full extrapolation to adolescents and sometimes to young pediatric patients; and (iv) evaluate the appropriateness for prolonging a dosing interval to reduce the frequency of hospital visits during the pandemic. Ongoing research activities of MIDD reflect our continuous effort and commitment in bridging knowledge gaps that leads to the availability of effective treatments through innovation. Case examples are presented to illustrate how MIDD has been used in various stages of drug development and has the potential to inform regulatory decision making.

A Smartphone App-Based Application Enabling Remote Assessments of Standing Balance During the COVID-19 Pandemic and Beyond

Assessments of postural control provide important insights into health. We created a smartphone App-based assessment of standing posture—completed with the phone placed in the user’s pocket—to enable remote monitoring of the function while minimizing the need for in-person assessment or contact. We tested the reliability of App-derived postural sway metrics, as well as their sensitivity to age and task conditions. Fifteen older and 15 younger adults completed two separate laboratory visits. They followed multimedia instructions provided by the App to complete three 30-s trials of eyes-open (EO), eyes-closed (EC), and dual-task (DT) standing. Sway data were recorded by the App and a force plate. Participants also used the App to complete the assessment in their homes on three separate days. Sway path length and root-mean square were derived from the angular velocity and acceleration acquired from phone’s internal motion sensor, and from the center-of-pressure signal from force plate. App-derived path length and root-mean-square of acceleration and angular velocity across conditions demonstrated moderate-to-excellent test–retest reliability (intraclass correlation coefficients (ICCs) = 0.69 − 0.97) for both younger and older adults. Reliability was comparable to metrics derived from the force plate (ICCs = 0.44 − 0.93). As expected, App-derived sway outcomes exhibited somewhat greater variability when tested across days at home (ICCs = 0.14 − 0.79). All App-derived metrics were sensitive to age ([Formula Omitted], [Formula Omitted]) and testing condition ([Formula Omitted], [Formula Omitted]) in both laboratory and home settings, revealing that the smartphone App enabled reliable and sensitive assessment of standing posture in both healthy younger and older adults.

Whole Body PBPK Modeling of Remdesivir and Its Metabolites to Aid in Estimating Active Metabolite Exposure in the Lung and Liver in Patients With Organ Dysfunction.

Remdesivir (RDV) is the first drug approved by the US Food and Drug Administration (FDA) for the treatment of coronavirus disease 2019 (COVID-19) in certain patients requiring hospitalization. As a nucleoside analogue prodrug, RDV undergoes intracellular multistep activation to form its pharmacologically active species, GS-443902, which is not detectable in the plasma. A question arises that whether the observed plasma exposure of RDV and its metabolites would correlate with or be informative about the exposure of GS-443902 in tissues. A whole body physiologically-based pharmacokinetic (PBPK) modeling and simulation approach was utilized to elucidate the disposition mechanism of RDV and its metabolites in the lungs and liver and explore the relationship between plasma and tissue pharmacokinetics (PK) of RDV and its metabolites in healthy subjects. In addition, the potential alteration of plasma and tissue PK of RDV and its metabolites in patients with organ dysfunction was explored. Our simulation results indicated that intracellular exposure of GS-443902 was decreased in the liver and increased in the lungs in subjects with hepatic impairment relative to the subjects with normal liver function. In subjects with severe renal impairment, the exposure of GS-443902 in the liver was slightly increased, whereas the lung exposure of GS-443902 was not impacted. These predictions along with the organ impairment study results may be used to support decision making regarding the RDV dosage adjustment in these patient subgroups. The modeling exercise illustrated the potential of whole body PBPK modeling to aid in decision making for nucleotide analogue prodrugs, particularly when the active metabolite exposure in the target tissues is not available.

Activation of Tenofovir Alafenamide and Sofosbuvir in the Human Lung and Its Implications in the Development of Nucleoside/Nucleotide Prodrugs for Treating SARS-CoV-2 Pulmonary Infection.

ProTide technology is a powerful tool for the design of nucleoside/nucleotide analog prodrugs. ProTide prodrug design improves cell permeability and enhances intracellular activation. The hydrolysis of the ester bond of a ProTide is a determinant of the intracellular activation efficiency and final antiviral efficacy of the prodrug. The hydrolysis is dictated by the catalytic activity and abundance of activating enzymes. The antiviral agents tenofovir alafenamide (TAF) and sofosbuvir (SBV) are typical ProTides. Both TAF and SBV have also been proposed to treat patients with COVID-19. However, the mechanisms underlying the activation of the two prodrugs in the lung remain inconclusive. In the present study, we profiled the catalytic activity of serine hydrolases in human lung S9 fractions using an activity-based protein profiling assay. We evaluated the hydrolysis of TAF and SBV using human lung and liver S9 fractions and purified enzymes. The results showed that CatA and CES1 were involved in the hydrolysis of the two prodrugs in the human lung. More specifically, CatA exhibited a nearly 4-fold higher hydrolytic activity towards TAF than SBV, whereas the CES1 activity on hydrolyzing TAF was slightly lower than that for SBV. Overall, TAF had a nearly 4-fold higher hydrolysis rate in human lung S9 than SBV. We further analyzed protein expression levels of CatA and CES1 in the human lung, liver, and primary cells of the two tissues using proteomics data extracted from the literature. The relative protein abundance of CatA to CES1 was considerably higher in the human lung and primary human airway epithelial cells than in the human liver and primary human hepatocytes. The findings demonstrated that the high susceptivity of TAF to CatA-mediated hydrolysis resulted in efficient TAF hydrolysis in the human lung, suggesting that CatA could be utilized as a target activating enzyme when designing antiviral ester prodrugs for the treatment of respiratory virus infection.

D-Limonene Is a Potential Monoterpene to Inhibit PI3K/Akt/IKK-α/NF-κB p65 Signaling Pathway in Coronavirus Disease 2019 Pulmonary Fibrosis.

At the time of the prevalence of coronavirus disease 2019 (COVID-19), pulmonary fibrosis (PF) related to COVID-19 has become the main sequela. However, the mechanism of PF related to COVID (COVID-PF) is unknown. This study aimed to explore the key targets in the development of COVID-PF and the mechanism of d-limonene in the COVID-PF treatment. The differentially expressed genes of COVID-PF were downloaded from the GeneCards database, and their pathways were analyzed. d-Limonene was molecularly docked with related proteins to screen its pharmacological targets, and a rat lung fibrosis model was established to verify d-limonene's effect on COVID-PF-related targets. The results showed that the imbalance between collagen breakdown and metabolism, inflammatory response, and angiogenesis are the core processes of COVID-PF; and PI3K/AKT signaling pathways are the key targets of the treatment of COVID-PF. The ability of d-limonene to protect against PF induced by bleomycin in rats was reported. The mechanism is related to the binding of PI3K and NF-κB p65, and the inhibition of PI3K/Akt/IKK-α/NF-κB p65 signaling pathway expression and phosphorylation. These results confirmed the relationship between the PI3K-Akt signaling pathway and COVID-PF, showing that d-limonene has a potential therapeutic value for COVID-PF.

Anti-SARS-CoV-2 Repurposing Drug Database: Clinical Pharmacology Considerations.

A critical step to evaluate the potential in vivo antiviral activity of a drug is to connect the in vivo exposure to its in vitro antiviral activity. The Anti-SARS-CoV-2 Repurposing Drug Database is a database that includes both in vitro anti-SARS-CoV-2 activity and in vivo pharmacokinetic data to facilitate the extrapolation from in vitro antiviral activity to potential in vivo antiviral activity for a large set of drugs/compounds. In addition to serving as a data source for in vitro anti-SARS-CoV-2 activity and in vivo pharmacokinetic information, the database is also a calculation tool that can be used to compare the in vitro antiviral activity with in vivo drug exposure to identify potential anti-SARS-CoV-2 drugs. Continuous development and expansion are feasible with the public availability of this database.

Tissue-Specific Proteomics Analysis of Anti-COVID-19 Nucleoside and Nucleotide Prodrug-Activating Enzymes Provides Insights into the Optimization of Prodrug Design and Pharmacotherapy Strategy.

Nucleoside and nucleotide analogs are an essential class of antivirals for COVID-19 treatment. Several nucleoside/nucleotide analogs have shown promising effects against SARS-CoV-2 in vitro; however, their in vivo efficacy is limited. Nucleoside/nucleotide analogs are often formed as ester prodrugs to improve pharmacokinetics (PK) performance. After entering cells, the prodrugs undergo several enzymatic metabolism steps to form the active metabolite triphosphate nucleoside (TP-Nuc); prodrug activation is therefore associated with the abundance and catalytic activity of the corresponding activating enzymes. Having the activation of nucleoside/nucleotide prodrugs occur at the target site of action, such as the lung, is critical for anti-SARS-CoV-2 efficacy. Herein, we conducted an absolute quantitative proteomics study to determine the expression of relevant activating enzymes in human organs related to the PK and antiviral efficacy of nucleoside/nucleotide prodrugs, including the lung, liver, intestine, and kidney. The protein levels of prodrug-activating enzymes differed significantly among the tissues. Using catalytic activity values reported previously for individual enzymes, we calculated prodrug activation profiles in these tissues. The prodrugs evaluated in this study include nine McGuigan phosphoramidate prodrugs, two cyclic monophosphate prodrugs, two l-valyl ester prodrugs, and one octanoate prodrug. Our analysis showed that most orally administered nucleoside/nucleotide prodrugs were primarily activated in the liver, suggesting that parenteral delivery routes such as inhalation and intravenous infusion could be better options when these antiviral prodrugs are used to treat COVID-19. The results also indicated that the l-valyl ester prodrug design can plausibly improve drug bioavailability and enhance effects against SARS-CoV-2 intestinal infections. This study further revealed that an octanoate prodrug could provide a long-acting antiviral effect targeting SARS-CoV-2 infections in the lung. Finally, our molecular docking analysis suggested several prodrug forms of favipiravir and GS-441524 that are likely to exhibit favorable PK features over existing prodrug forms. In sum, this study revealed the activation mechanisms of various nucleoside/nucleotide prodrugs relevant to COVID-19 treatment in different organs and shed light on the development of more effective anti-COVID-19 prodrugs.

The Impact of Social Support on Public Anxiety amidst the COVID-19 Pandemic in China.

The recent coronavirus outbreak has captured worldwide attention. This study investigated the anxiety of the Chinese public and its relationship with social support during the early stage of the COVID-19 pandemic, thereby providing empirical support for interventions on improving the public's mental health. On the basis of an online questionnaire survey conducted on 10-18 February 2020, this study shows that 19.8%, 68.5%, and 11.1% of the respondents suffered mild anxiety, moderate anxiety, and severe anxiety, respectively. Significant differences are reported in state anxiety between people with different household incomes. There are significant differences in trait anxiety and state anxiety between different social support groups. Social support and trait anxiety are negatively correlated. Social support and state anxiety are negatively correlated. Social support affects state anxiety both directly and indirectly (through the mediation of trait anxiety). Therefore, during the COVID-19 pandemic, increasing public support for society can effectively reduce public anxiety.

The changes of the peripheral CD4+ lymphocytes and inflammatory cytokines in Patients with COVID-19.

To investigate the clinical value of changes in the subtypes of peripheral blood lymphocytes and levels of inflammatory cytokines in patients with COVID-19, the total numbers of lymphocytes and CD4+ lymphocytes and the ratio of CD4+/CD8+ lymphocytes were calculated and observed in different groups of patients with COVID-19. The results show that the lymphocytopenia in patients with COVID-19 was mainly manifested by decreases in the CD4+ T lymphocyte number and the CD4+/CD8+ ratio. The decreased number of CD4+ T lymphocytes and the elevated levels of TNF-α and IL-6 were correlated with the severity of COVID-19 disease.