Synthetic coevolution reveals adaptive mutational trajectories of neutralizing antibodies and SARS-CoV-2 (preprint)

The Covid-19 pandemic showcases a coevolutionary race between the human immune system and SARS-CoV-2, mirroring the Red Queen hypothesis of evolutionary biology. The immune system generates neutralizing antibodies targeting the SARS-CoV-2 spike protein's receptor binding domain (RBD), crucial for host cell invasion, while the virus evolves to evade antibody recognition. Here, we establish a synthetic coevolution system combining high-throughput screening of antibody and RBD variant libraries with protein mutagenesis, surface display, and deep sequencing. Additionally, we train a protein language machine learning model that predicts antibody escape to RBD variants. Synthetic coevolution reveals antagonistic and compensatory mutational trajectories of neutralizing antibodies and SARS-CoV-2 variants, enhancing the understanding of this evolutionary conflict.

Pandemic and the Administrative Rationality: Understanding the Administrative Response to the Pandemic

The outbreak of the Corona Virus Disease 2019 or COVID 19 pandemic has literally dashed our enlightened scientific rationality. It has claimed more than six million lives around the globe. The struggling humanity has adopted a series of strict legal-administrative protocols like lockdown, quarantine, isolation, to contain the spread of the virus. However, the strict adherence to the above-mentioned protocols has brought several collateral damages like the disruption of normal socio-economic activities;suspension of political and civic engagements of the people. The situation gets further complicated as endless suggestions and opinions have been offered by several experts. The scientific community, till today, is grappling with the possible antidote of the virus in the form of vaccines. Several research laboratories across the globe have been actively engaged in devising full-proof vaccines of which, some have already started manufacturing commercially. Despite the tall claims of these companies, the efficacy of these vaccines is still not very clear. Moreover, the modality of administering these vaccines is another difficult issue, involving delicate distributive management that requires something more than mere scientific rationality. Further, given the nature of neoliberal governance, where delivery of services is a collective venture of all the stakeholders like state, civil society, market, and community, administrative rationality is perhaps the most important means. Drawing on the existing literature, the paper intends to explore the administrative responses to the pandemic of COVID-19 through the lens of administrative rationality. Finally, the paper with an optimistic note concludes that the administrative rationality of the bureaucracy has the potential to devise a bailout programme for all the stakeholders concerned. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022, corrected publication 2022.

Interactive Communication Robot Handling Crowd Management and Content Delivery in Museums Employing Crowd Counting

Through the last decade, and particularly after the Covid period (2020 - 2022), crowd counting and localization have attracted much attention of AI researchers due to its potential applicability in crowd monitoring and control, public safety, space design, interactive content delivery etc. Once delivery objectives for a system are envisaged and the premises are fixed, we can always construct manifold technology architecture that delivers the set goals. However, in the Indian context a solution of choice needs to be optimized on frugality and ease of adaptability. In this paper we report an economic and replicable application of crowd counting and interactive content delivery in museums through unbiased knowledge systems embedded in robotic museum assistants. We intend to demonstrate a robotic system that can deliver any gallery content to groups of visitors keeping special focus on the exhibits that are popular choices. Crowd counting is used here to enable the content presentation to a group of choice in an interactive way. There are some market-ready solutions available for interactive gallery demonstration by moveable robots but they require not only huge capital investment but are also of limited use within controlled environments. Our proposed design is to multiplex an existing infrastructure of surveillance system as a smart crowd counting and gallery demonstration system along with crowd management with minimum additional hardware infusion. © 2023 IEEE.

Medical Diagnosis and Identification of Covid -19 by Intelligent IoT System and Resnet 18 Bilinear Deep Greedy Network

An international health crisis has been caused by the widespread COVID-19 epidemic. COVID-19 patient diagnoses are made using deep learning, although this necessitates a massive radiography data collection in order to efficiently deliver an optimum result. This paper presents a novel Intelligent System with IoT sensors for covid 19 and "Bilinear Resnet 18 Deep Greedy Network,"which is effective with a limited amount of datasets. Despite peculiarities brought on by a small dataset, the suggested approach could successfully combat the anomalies of over fitting and under fitting. The suggested architecture ensures a successful conclusion when the trained model is correctly evaluated using the provided X-ray datasets of COVID-19 cases. The recommended model offers accuracy of 97%, which is superior to existing methodologies. Better precision, recall, and F1 score are provided;which are 98%, 96%, and 96.94% respectively, which is better than other existing methodology. © 2022 IEEE.

Structural insights into protection against a SARS-CoV-2 spike variant by T cell receptor diversity.

T cells play a crucial role in combatting SARS-CoV-2 and forming long-term memory responses to this coronavirus. The emergence of SARS-CoV-2 variants that can evade T cell immunity has raised concerns about vaccine efficacy and the risk of reinfection. Some SARS-CoV-2 T cell epitopes elicit clonally restricted CD8+ T cell responses characterized by T cell receptors (TCRs) that lack structural diversity. Mutations in such epitopes can lead to loss of recognition by most T cells specific for that epitope, facilitating viral escape. Here, we studied an HLA-A2-restricted spike protein epitope (RLQ) that elicits CD8+ T cell responses in COVID-19 convalescent patients characterized by highly diverse TCRs. We previously reported the structure of an RLQ-specific TCR (RLQ3) with greatly reduced recognition of the most common natural variant of the RLQ epitope (T1006I). Opposite to RLQ3, TCR RLQ7 recognizes T1006I with even higher functional avidity than the WT epitope. To explain the ability of RLQ7, but not RLQ3, to tolerate the T1006I mutation, we determined structures of RLQ7 bound to RLQ-HLA-A2 and T1006I-HLA-A2. These complexes show that there are multiple structural solutions to recognizing RLQ and thereby generating a clonally diverse T cell response to this epitope that assures protection against viral escape and T cell clonal loss.

Structure-Based Design of Potent Iminosugar Inhibitors of Endoplasmic Reticulum α-Glucosidase I with Anti-SARS-CoV-2 Activity.

Enveloped viruses depend on the host endoplasmic reticulum (ER) quality control (QC) machinery for proper glycoprotein folding. The endoplasmic reticulum quality control (ERQC) enzyme α-glucosidase I (α-GluI) is an attractive target for developing broad-spectrum antivirals. We synthesized 28 inhibitors designed to interact with all four subsites of the α-GluI active site. These inhibitors are derivatives of the iminosugars 1-deoxynojirimycin (1-DNJ) and valiolamine. Crystal structures of ER α-GluI bound to 25 1-DNJ and three valiolamine derivatives revealed the basis for inhibitory potency. We established the structure-activity relationship (SAR) and used the Site Identification by Ligand Competitive Saturation (SILCS) method to develop a model for predicting α-GluI inhibition. We screened the compounds against SARS-CoV-2 in vitro to identify those with greater antiviral activity than the benchmark α-glucosidase inhibitor UV-4. These host-targeting compounds are candidates for investigation in animal models of SARS-CoV-2 and for testing against other viruses that rely on ERQC for correct glycoprotein folding.

Monoclonal Antibodies Specific for SARS-CoV-2 Spike Protein Suitable for Multiple Applications for Current Variants of Concern.

The global coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spawned an ongoing demand for new research reagents and interventions. Herein we describe a panel of monoclonal antibodies raised against SARS-CoV-2. One antibody showed excellent utility for immunohistochemistry, clearly staining infected cells in formalin-fixed and paraffin embedded lungs and brains of mice infected with the original and the omicron variants of SARS-CoV-2. We demonstrate the reactivity to multiple variants of concern using ELISAs and describe the use of the antibodies in indirect immunofluorescence assays, Western blots, and rapid antigen tests. Finally, we illustrate the ability of two antibodies to reduce significantly viral tissue titers in K18-hACE2 transgenic mice infected with the original and an omicron isolate of SARS-CoV-2.

RWD161 Pharmacological Treatment Disruption in Women With Post-Partum Depression (PPD) During COVID-19: A Retrospective Cohort Study Using Claim Data

Objectives: Postpartum depression (PPD) has been described as "the thief that steals motherhood" by depriving women of the anticipated joy of a new infant. Through this study, we intend to see the incidence, treatment rates (TR), relative-treatment rate (TRR), absolute treatment rate (ATR), and number needed to treat (NNT) pre- and post-COVID-19 on treatment of women with PPD. Method(s): This retrospective cohort study included newly diagnosed patients with PPD in 2019 (1st Jan - 31st Dec [pre-pandemic]) and 2020 (1st Jan - 31st Dec [pandemic]) using ICD-10-CM codes from Optum's de-identified Clinformatics Data Mart. Only the patients having continuous eligibility between 12 months before (baseline period) to 12-months post (follow-up period) the first diagnosis of PPD (index date) were included in study. During the follow-up period, patients were then checked for pharmacological treatment received (SSRI, SNRI's and other anti-depressants) using NDC codes. To measure effects, percentages of patients getting treatment, TRR (TR in pandemic/TR in pre-pandemic), ATR (TR in pre-pandemic - TR in a pandemic), and NNT (1/ATR) were calculated before and during COVID. The significance of categorical variables was examined using the Chi-square test. Result(s): We observed 39% increase in incidence of PPD patients during pandemic (n=16,095) vs pre-pandemic (n=11,565). Only 51% TR (risk ratio) was observed during pandemic vs 60% TR (risk ratio) in pre-pandemic with any SSRI, SNRI, and anti-depressants (p<.01). Compared to patients receiving treatment during pandemic vs pre-pandemic: TRR was found to be 85% (relative risk) and ATR was 9% (absolute risk reduction). The NNT comparing pre- and during pandemic was 11. Conclusion(s): The results of the study demonstrated that treatment of women with PPD was impacted during pandemic vs pre-pandemic (9% women did not receive treatment during pandemic). Alternative methods or non-pharmacological treatments may be required to further alleviate non-treated patients and improve their condition. Copyright © 2022

RWD128 Exploring the Burden of COVID-19 on Post-Traumatic Stress Disorder (PTSD) in Pre- and During-COVID-19 Pandemic Using Real-World Data

Objectives: This study aimed to explore the impact of COVID-19 on patients with PTSD and the burden of resource utilization in the pre- and during the COVID-19 pandemic. Method(s): This retrospective observational study included patients diagnosed with PTSD between 1st January 2018 to 31st December 2020 using ICD-10-CM codes from Optum's de-identified Clinformatics Data Mart database. In the study duration, distinct patients were identified and further classified by age, gender, and location of service. To determine the influence in pre- and during COVID-19 for each of the stratification variables, a year-wise comparison was done. Chi-square was performed as test of significance for categorical variables. Result(s): Overall we observed the number of PTSD patients increased by 7% (n=206,741) during the pandemic (1st January 2020 - 31st December 2020) vs pre-pandemic (1st January 2019 - 31st December 2019). A significant increase was seen across all age groups (p<.05). In the case of teenagers, PTSD was found to have increased by 22% whereas in adults and the elderly an 8% and 3% increase was seen respectively. When broken down by gender, a significant increase was observed. Females (+9% [n=143,032]) were seen to have been affected more compared to males (+4% [n=63,625]) during the pandemic vs pre-pandemic. In healthcare resources utilization overall, there was an observed 24% increase. For both inpatients and office, PTSD decreased significantly (-3% and -4% respectively) (p<.05);while ER visits, increased only by 1% (p<.05). A significant increase in outpatient and telehealth services was observed (122% and 454% respectively) (p<.05). Conclusion(s): An increased exacerbation in PTSD was observed during the pandemic with respect to burden across various stratification and resource utilization;especially in outpatient and telehealth services. Better treatment, psychotherapy and alternative care programs may be required to curb this impact and decrease the overall burden across various care setting. Copyright © 2022

RWD95 Exploring the Burden of COVID-19 on Suicides and Suicidal Attempts (SSA) in Pre- and During-COVID-19 Pandemic Using Real-World Data

Objectives: This study aimed to explore the impact of COVID-19 on patients with SSA and the burden of resource utilization in the pre- and during the COVID-19 pandemic. Method(s): This retrospective observational study included patients diagnosed with SSA between 1st January 2019 to 31st December 2020 using ICD-10-CM codes from Optum's de-identified Clinformatics Data Mart. In the study duration, distinct patients were identified and further classified by age, gender, and location of service. To determine the influence in pre- and during COVID-19 for each of the stratification variables, a year-wise comparison was done. Chi-square test was performed to check the significance of categorical variables. Result(s): Overall we observed the number of SSA patients increased by 2% (n=266,329) during the pandemic (1st January 2020 - 31st December 2020). A significant increase was seen across all age groups (p<.01). In the case of teenagers, SSA was found to have increased by 80% whereas in adults and elderly an 15% and 8% increase was seen respectively during pandemic (p<.01). When stratified by gender, a significant increase was observed only in females (+9% [n=174,647]) where in males (-3% [n=91,573]) decrease was observed during pandemic. In healthcare resources utilization overall, there was an observed 12% increase during pandemic. For inpatients, office, and outpatient, SSA decreased significantly (-4%, -8%, and -1% respectively) during pandemic (p<.01). A significant increase in outpatient and telehealth services was observed (34% and 1,299% respectively) (p<.01). Conclusion(s): An increased exacerbation in SSA was observed during the pandemic with telehealth and outpatient services being impacted the highest. This may be attributed to facing near-death scenarios, and the loss of loved ones amongst other factors. With the increase in cases, health care resource utilization across various settings is pressed. Better treatment and programs may be required to curb this impact and decrease the overall burden. Copyright © 2022

RWD29 Use of Telemedicine Services and Health Outcomes in Hypertensive Patients in Pre- and Post-COVID-19 Periods in the United States

Objectives: This study examines use of telemedicine services and health outcomes in patients with hypertension (HTN) in pre- and post-COVID 19 periods in the US. Method(s): A retrospective analysis, using Optum de-identified Electronic Health Record dataset, was done among hypertensive patients on Medicare plans in three different time periods: 1st Jan 2018 - 30th June 2018, 1st Jan - 30th June 2019, and 1st Jan - 30th June 2020 (first two time periods are pre-COVID 19 and the last one is post-COVID 19). The date of first EHR with mention of HTN diagnosis was considered index date. Study participants were categorized into those who used only telemedicine services (Telemedicine group);only other places of service like outpatient, inpatient, or office (Other POS group);and those who used both telemedicine and other places of service (Both POS groups). Patients were followed for 6-months post-index to determine use of anti-HTN medications, resource utilization, and healthcare outcomes. Result(s): Fewer than 100 patients in each study period belonged to Telemedicine group. Majority (55%) patients in 2018 (pre-COVID 19) belonged to Other POS group, but in 2020 (post-COVID 19) majority (61%) patients belonged to Both POS group. About 70% patients in each of three groups were prescribed anti-HTN drugs and adherence was >90%. About ~60% patients in Telemedicine group had 2-6 healthcare encounters while ~80% in Other POS group and ~95% in Both POS groups had >6 healthcare encounters during follow-up period. Significantly more patients in Both POS groups received anti-HTN nutritional counseling as compared to other two groups. Also, blood pressure was controlled in significantly higher percentage of patients in Both POS groups as compared to other two groups. Conclusion(s): Patients who use telemedicine and other places of service are more likely to receive anti-HTN nutritional counseling and have better blood pressure control. Copyright © 2022