Fuzzy Optimization for Identifying Antiviral Targets for Treating SARS-CoV-2 Infection in the Heart (preprint)

In this paper, a fuzzy hierarchical optimization framework is proposed for identifying potential antiviral targets for treating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the heart. The proposed framework comprises four objectives for evaluating the elimination of viral biomass growth and the minimization of side effects during treatment. In the application of the framework, Dulbecco’s Modified Eagle Medium (DMEM) and Ham’s medium were used as uptake nutrients on an antiviral target discovery platform. The prediction results from the framework reveal that most of the antiviral enzymes in the aforementioned media are involved in fatty acid metabolism and amino acid metabolism. However, six enzymes involved in cholesterol biosynthesis in Ham’s medium and three enzymes involved in glycolysis in DMEM are unable to eliminate the growth of the SARS-CoV-2 biomass. Three enzymes involved in glycolysis, namely BPGM, GAPDH, and ENO1, in DMEM combine with the supplemental uptake of L-cysteine to increase the cell viability grade and metabolic deviation grade. Moreover, six enzymes involved in cholesterol biosynthesis reduce and fail to reduce viral biomass growth in a culture medium if a cholesterol uptake reaction does not occur and occurs in this medium, respectively.

In vitro and in vivo effects of 3-indoleacetonitrile-A potential new broad-spectrum therapeutic agent for SARS-CoV-2 infection.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak has resulted in significant global morbidity, mortality, and societal disruption. Currently, effective antiviral drugs for the treatment of SARS-CoV-2 infection are limited. Therefore, safe and effective antiviral drugs to combat COVID-19 are urgently required. In previous studies, we showed that 3-indoleacetonitrile, a plant growth hormone produced by cruciferous (Brassica) vegetables, is effective in treating influenza A virus infection. However, the molecular mechanisms underlying these effects remain unclear. Herein, we demonstrated that 3-indoleacetonitrile exhibits broad-spectrum antiviral activity and is effective against HSV-1 and VSV infections in vitro. This phenomenon prompted us to study its role in the anti-SARS-CoV-2 process. Interestingly, 3-indoleacetonitrile exhibited antiviral activity against SARS-CoV-2 in vitro. Importantly, tail vein injection of 3-indoleacetonitrile resulted in good antiviral activity in mouse models infected with WBP-1 (a mouse adaptation of the SARS-CoV-2 strain). Mechanistically, 3-indoleacetonitrile promoted the host interferon signalling pathway response and inhibited autophagic flux. Furthermore, we demonstrated that 3-indoleacetonitrile induced an increase in mitochondrial antiviral-signalling (MAVS) protein levels, which might be attributed to its inhibition of the interaction between MAVS and the selective autophagy receptor SQSTM1. Overall, our results demonstrate that 3-indoleacetonitrile is potently active against SARS-CoV-2 in vitro and in vivo, which may provide a foundation for further clinical testing for the treatment of COVID-19. In addition, considering its broad-spectrum antiviral effect, it should be explored whether it also has an effect on other viruses that threaten human health.

Pretreatment Methods for Human Nasopharyngeal Swabs to Increase the Signal to Noise Ratio of High Sensitivity Immunoassays.

Mucous samples collected through nasopharyngeal (NP) swabs are considered gold standard specimens for the detection of respiratory pathogens. Matrices of these highly viscous samples often cause significant background noises in immunoassays, especially immunoassays with high sensitivity. We demonstrated such nonspecific background signals in both a chemiluminescence enzyme-linked immunosorbent assay (ELISA) and a novel highly sensitive immunoassay called Microbubbling SARS-CoV-2 Antigen Assay (MSAA). We developed and demonstrated the effectiveness of two quick sample pretreatment methods, filtration and preadsorption, to decrease nonspecific signals and increase the signal-to-noise ratio (SNR). Using these pretreatment methods, the SNR (at 3.6 × 104 copies/mL of inactivated SARS-CoV-2) was increased by 42.4-fold (95% CI 41.0-43.8) and 67.1-fold (95% CI 57.9-76.3) in the MSAA, and 1.3-fold (95% CI 0.9-1.7) and 1.8-fold (95% CI 1.6-2.0) in the chemiluminescence ELISA assay. Sample pretreatment methods developed in this study are broadly adaptable for the development of immunoassays for highly viscous samples.

Virofree, an Herbal Medicine-Based Formula, Interrupts the Viral Infection of Delta and Omicron Variants of SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) remains a threat with the emergence of new variants, especially Delta and Omicron, without specific effective therapeutic drugs. The infection causes dysregulation of the immune system with a cytokine storm that eventually leads to fatal acute respiratory distress syndrome (ARDS) and further irreversible pulmonary fibrosis. Therefore, the promising way to inhibit infection is to disrupt the binding and fusion between the viral spike and the host ACE2 receptor. A transcriptome-based drug screening platform has been developed for COVID-19 to explore the possibility and potential of the long-established drugs or herbal medicines to reverse the unique genetic signature of COVID-19. In silico analysis showed that Virofree, an herbal medicine, reversed the genetic signature of COVID-19 and ARDS. Biochemical validations showed that Virofree could disrupt the binding of wild-type and Delta-variant spike proteins to ACE2 and its syncytial formation via cell-based pseudo-typed viral assays, as well as suppress binding between several variant recombinant spikes to ACE2, especially Delta and Omicron. Additionally, Virofree elevated miR-148b-5p levels, inhibited the main protease of SARS-CoV-2 (Mpro), and reduced LPS-induced TNF-α release. Virofree also prevented cellular iron accumulation leading to ferroptosis which occurs in SARS-CoV-2 patients. Furthermore, Virofree was able to reduce pulmonary fibrosis-related protein expression levels in vitro. In conclusion, Virofree was repurposed as a potential herbal medicine to combat COVID-19. This study highlights the inhibitory effect of Virofree on the entry of Delta and Omicron variants of SARS-CoV-2, which have not had any effective treatments during the emergence of the new variants spreading.

Immunogenicity and protective efficacy of a DNA vaccine inducing optimal expression of the SARS-CoV-2 S gene in hACE2 mice.

The wide spread of coronavirus disease 2019 (COVID-19) has significantly threatened public health. Human herd immunity induced by vaccination is essential to fight the epidemic. Therefore, highly immunogenic and safe vaccines are necessary to control SARS-CoV-2, whose S protein is the antigenic determinant responsible for eliciting antibodies that prevent viral entry and fusion. In this study, we developed a SARS-CoV-2 DNA vaccine expressing the S protein, named pVAX-S-OP, which was optimized according to the human-origin codon preference and using polyinosinic-polycytidylic acid as an adjuvant. pVAX-S-OP induced specific antibodies and neutralizing antibodies in BALB/c and hACE2 transgenic mice. Furthermore, we observed 1.43-fold higher antibody titers in mice receiving pVAX-S-OP plus adjuvant than in those receiving pVAX-S-OP alone. Interferon gamma production in the pVAX-S-OP-immunized group was 1.58 times (CD3+CD4+IFN-gamma+) and 2.29 times (CD3+CD8+IFN-gamma+) lower than that in the pVAX-S-OP plus adjuvant group but higher than that in the control group. The pVAX-S-OP vaccine was also observed to stimulate a Th1-type immune response. When, hACE2 transgenic mice were challenged with SARS-CoV-2, qPCR detection of N and E genes showed that the viral RNA loads in pVAX-S-OP-immunized mice lung tissues were 104 times and 106 times lower than those of the PBS control group, which shows that the vaccine could reduce the amount of live virus in the lungs of hACE2 mice. In addition, pathological sections showed less lung damage in the pVAX-S-OP-immunized group. Taken together, our results demonstrated that pVAX-S-OP has significant immunogenicity, which provides support for developing SARS-CoV-2 DNA candidate vaccines.

Optimize data-driven multi-agent simulation for COVID-19 transmission.

BACKGROUND: Multi-Agent Simulation is an essential technique for exploring complex systems. In research of contagious diseases, it is widely exploited to analyze their spread mechanisms, especially for preventing COVID-19. Nowadays, transmission dynamics and interventions of COVID-19 have been elaborately established by this method, but its computation performance is seldomly concerned. As it usually suffers from inadequate CPU utilization and poor data locality, optimizing the performance is challenging and important for real-time analyzing its spreading. RESULTS: This paper explores approaches to optimize multi-agent simulation for COVID-19 disease. The focus of this work is on the algorithm and data structure designs for improving performance, as well as its parallelization strategies. We propose two successive methods to optimize the computation. We construct a case-focused iteration algorithm to improve data locality, and propose a fast data-mapping scheme called hierarchical hash table to accelerate hash operations. As a result, The case-focused method degrades [Formula: see text] cache references and achieves [Formula: see text] speedup. Hierarchical hash table can further boost computation speed by 47%. And parallel implementation with 20 threads on CPU achieves [Formula: see text] speedup consequently. CONCLUSIONS: In this work, we propose optimizations for multi-agent simulation of COVID-19 transmission from aspects of algorithm and data structure. Benefit from improvement of locality and multi-thread implementation, our methods can significantly accelerate the simulation computation. It is promising in supporting real-time prevention of COVID-19 and other infectious diseases in the future.

Virofree, an Herbal Medicine-Based Formula, Interrupts the Viral Infection of Delta and Omicron Variants of SARS-CoV-2

Coronavirus disease 2019 (COVID-19) remains a threat with the emergence of new variants, especially Delta and Omicron, without specific effective therapeutic drugs. The infection causes dysregulation of the immune system with a cytokine storm that eventually leads to fatal acute respiratory distress syndrome (ARDS) and further irreversible pulmonary fibrosis. Therefore, the promising way to inhibit infection is to disrupt the binding and fusion between the viral spike and the host ACE2 receptor. A transcriptome-based drug screening platform has been developed for COVID-19 to explore the possibility and potential of the long-established drugs or herbal medicines to reverse the unique genetic signature of COVID-19. In silico analysis showed that Virofree, an herbal medicine, reversed the genetic signature of COVID-19 and ARDS. Biochemical validations showed that Virofree could disrupt the binding of wild-type and Delta-variant spike proteins to ACE2 and its syncytial formation via cell-based pseudo-typed viral assays, as well as suppress binding between several variant recombinant spikes to ACE2, especially Delta and Omicron. Additionally, Virofree elevated miR-148b-5p levels, inhibited the main protease of SARS-CoV-2 (Mpro), and reduced LPS-induced TNF-α release. Virofree also prevented cellular iron accumulation leading to ferroptosis which occurs in SARS-CoV-2 patients. Furthermore, Virofree was able to reduce pulmonary fibrosis-related protein expression levels in vitro. In conclusion, Virofree was repurposed as a potential herbal medicine to combat COVID-19. This study highlights the inhibitory effect of Virofree on the entry of Delta and Omicron variants of SARS-CoV-2, which have not had any effective treatments during the emergence of the new variants spreading.

Effect of Combining Conventional and Telehealth Methods on Managing Peritoneal Dialysis Patients: A Retrospective Single-Center Study

Objective This study aimed to explore follow-up mode changes for peritoneal dialysis (PD) patients and their effects on PD quality during the COVID-19 pandemic. Methods A retrospective single-center study was conducted. All patients who received PD treatment at the Second Affiliated Hospital of Soochow University between January 2018 and March 2020 were enrolled in this study. Patient data during the first quarter of 2018 (Q1-2018), the first quarter of 2019 (Q1-2019), and the first quarter of 2020 (Q1-2020) were collected. Results No significant differences were observed for any serum examinations in different follow-up periods (P > 0.05). A significantly reduced outpatient follow-up rate was observed in Q1-2020 compared with Q1-2018 and Q1-2019 (71.6% Vs 78.9% Vs 84.7%, P < 0.001), accompanied by a significantly increased remote follow-up rate (28.4% Vs 21.1% Vs 15.3%, P < 0.001). Compared with Q1-2018 and Q1-2019, the hospitalization rate (27.7% Vs 30.9% Vs 15.7%, P < 0.001) and the incidence of peritonitis (0.162 Vs 0.186 Vs 0.08 per patient-year, P < 0.001) decreased significantly in Q1-2020. PD patients had a significant decline in the drop-out rate for Q1-2020 compared with Q1-2019 (4.4% Vs 7.3% Vs 2.2%, P < 0.001). No differences in the incidence of catheter-related infections were observed. No significant differences were observed for any peritoneal dialysis key performance indicators (KPIs) between outpatient follow-up and remote follow-up patients. Conclusion During the COVID-19 pandemic (Q1-2020), our center practiced more remote follow-up procedures in PD patients. The hospitalization rate and peritonitis incidence were significantly decreased compared with the same time in previous years. No statistical differences were observed in other KPIs for peritoneal dialysis. This study shows that telehealth methods are a reasonable alternative to in-person care in the care/management of PD patients.

Human/SARS-CoV-2 genome-scale metabolic modeling to discover potential antiviral targets for COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a substantial increase in mortality and economic and social disruption. The absence of US Food and Drug Administration-approved drugs for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) highlights the need for new therapeutic drugs to combat COVID-19. METHODS: The present study proposed a fuzzy hierarchical optimization framework for identifying potential antiviral targets for COVID-19. The objectives in the decision-making problem were not only to evaluate the elimination of the virus growth, but also to minimize side effects causing treatment. The identified candidate targets could promote processes of drug discovery and development. SIGNIFICANT FINDINGS: Our gene-centric method revealed that dihydroorotate dehydrogenase (DHODH) inhibition could reduce viral biomass growth and metabolic deviation by 99.4% and 65.6%, respectively, and increase cell viability by 70.4%. We also identified two-target combinations that could completely block viral biomass growth and more effectively prevent metabolic deviation. We also discovered that the inhibition of two antiviral metabolites, cytidine triphosphate (CTP) and uridine-5'-triphosphate (UTP), exhibits effects similar to those of molnupiravir, which is undergoing phase III clinical trials. Our predictions also indicate that CTP and UTP inhibition blocks viral RNA replication through a similar mechanism to that of molnupiravir.

Debulking SARS-CoV-2 in saliva using angiotensin converting enzyme 2 in chewing gum to decrease oral virus transmission and infection.

To advance a novel concept of debulking virus in the oral cavity, the primary site of viral replication, virus-trapping proteins CTB-ACE2 were expressed in chloroplasts and clinical-grade plant material was developed to meet FDA requirements. Chewing gum (2 g) containing plant cells expressed CTB-ACE2 up to 17.2 mg ACE2/g dry weight (11.7% leaf protein), have physical characteristics and taste/flavor like conventional gums, and no protein was lost during gum compression. CTB-ACE2 gum efficiently (>95%) inhibited entry of lentivirus spike or VSV-spike pseudovirus into Vero/CHO cells when quantified by luciferase or red fluorescence. Incubation of CTB-ACE2 microparticles reduced SARS-CoV-2 virus count in COVID-19 swab/saliva samples by >95% when evaluated by microbubbles (femtomolar concentration) or qPCR, demonstrating both virus trapping and blocking of cellular entry. COVID-19 saliva samples showed low or undetectable ACE2 activity when compared with healthy individuals (2,582 versus 50,126 ΔRFU; 27 versus 225 enzyme units), confirming greater susceptibility of infected patients for viral entry. CTB-ACE2 activity was completely inhibited by pre-incubation with SARS-CoV-2 receptor-binding domain, offering an explanation for reduced saliva ACE2 activity among COVID-19 patients. Chewing gum with virus-trapping proteins offers a general affordable strategy to protect patients from most oral virus re-infections through debulking or minimizing transmission to others.

Femtomolar SARS-CoV-2 Antigen Detection Using the Microbubbling Digital Assay with Smartphone Readout Enables Antigen Burden Quantitation and Tracking.

BACKGROUND: High-sensitivity severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen assays are desirable to mitigate false negative results. Limited data are available to quantify and track SARS-CoV-2 antigen burden in respiratory samples from different populations. METHODS: We developed the Microbubbling SARS-CoV-2 Antigen Assay (MSAA) with smartphone readout, with a limit of detection of 0.5 pg/mL (10.6 fmol/L) nucleocapsid antigen or 4000 copies/mL inactivated SARS-CoV-2 virus in nasopharyngeal (NP) swabs. We developed a computer vision and machine learning-based automatic microbubble image classifier to accurately identify positives and negatives and quantified and tracked antigen dynamics in intensive care unit coronavirus disease 2019 (COVID-19) inpatients and immunocompromised COVID-19 patients. RESULTS: Compared to qualitative reverse transcription-polymerase chain reaction methods, the MSAA demonstrated a positive percentage agreement of 97% (95% CI 92%-99%) and a negative percentage agreement of 97% (95% CI 94%-100%) in a clinical validation study with 372 residual clinical NP swabs. In immunocompetent individuals, the antigen positivity rate in swabs decreased as days-after-symptom-onset increased, despite persistent nucleic acid positivity. Antigen was detected for longer and variable periods of time in immunocompromised patients with hematologic malignancies. Total microbubble volume, a quantitative marker of antigen burden, correlated inversely with cycle threshold values and days-after-symptom-onset. Viral sequence variations were detected in patients with long duration of high antigen burden. CONCLUSIONS: The MSAA enables sensitive and specific detection of acute infections and quantification and tracking of antigen burden and may serve as a screening method in longitudinal studies to identify patients who are likely experiencing active rounds of ongoing replication and warrant close viral sequence monitoring.

Optimization of a modeling platform to predict oncogenes from genome-scale metabolic networks of non-small-cell lung cancers.

Cancer cell dysregulations result in the abnormal regulation of cellular metabolic pathways. By simulating this metabolic reprogramming using constraint-based modeling approaches, oncogenes can be predicted, and this knowledge can be used in prognosis and treatment. We introduced a trilevel optimization problem describing metabolic reprogramming for inferring oncogenes. First, this study used RNA-Seq expression data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) samples and their healthy counterparts to reconstruct tissue-specific genome-scale metabolic models and subsequently build the flux distribution pattern that provided a measure for the oncogene inference optimization problem for determining tumorigenesis. The platform detected 45 genes for LUAD and 84 genes for LUSC that lead to tumorigenesis. A high level of differentially expressed genes was not an essential factor for determining tumorigenesis. The platform indicated that pyruvate kinase (PKM), a well-known oncogene with a low level of differential gene expression in LUAD and LUSC, had the highest fitness among the predicted oncogenes based on computation. By contrast, pyruvate kinase L/R (PKLR), an isozyme of PKM, had a high level of differential gene expression in both cancers. Phosphatidylserine synthase 1 (PTDSS1), an oncogene in LUAD, was inferred to have a low level of differential gene expression, and overexpression could significantly reduce survival probability. According to the factor analysis, PTDSS1 characteristics were close to those of the template, but they were unobvious in LUSC. Angiotensin-converting enzyme 2 (ACE2) has recently garnered widespread interest as the SARS-CoV-2 virus receptor. Moreover, we determined that ACE2 is an oncogene of LUSC but not of LUAD. The platform developed in this study can identify oncogenes with low levels of differential expression and be used to identify potential therapeutic targets for cancer treatment.