Concomitant Presence of Mandibular Mucormycosis in a COVID Positive Patient: Report of A Rare Case

Reports of COVID-19 associated mucormycosis has exponentially increased in recent times, especially in patients with uncontrolled diabetes. It is reported to be associated with high mortality and morbidity rates and hence has emerged as a public health crisis. Covid-19 associated mucormycosis poses a diagnostic challenge for the Dentists as the clinical and radiological featuresare largely non-specific. The most common variant of mucormycosis in general is rhino-orbital and involvement of mandible is a rather uncommon presentation. Here we document a rare case of mucormycosis affecting the mandible with the concomitant presence of COVID19 infection in a diabetic patient.

Association of COVID-19 with Comorbidities: An Update.

Coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) which was identified in Wuhan, China in December 2019 and jeopardized human lives. It spreads at an unprecedented rate worldwide, with serious and still-unfolding health conditions and economic ramifications. Based on the clinical investigations, the severity of COVID-19 appears to be highly variable, ranging from mild to severe infections including the death of an infected individual. To add to this, patients with comorbid conditions such as age or concomitant illnesses are significant predictors of the disease's severity and progression. SARS-CoV-2 enters inside the host cells through ACE2 (angiotensin converting enzyme2) receptor expression; therefore, comorbidities associated with higher ACE2 expression may enhance the virus entry and the severity of COVID-19 infection. It has already been recognized that age-related comorbidities such as Parkinson's disease, cancer, diabetes, and cardiovascular diseases may lead to life-threatening illnesses in COVID-19-infected patients. COVID-19 infection results in the excessive release of cytokines, called "cytokine storm", which causes the worsening of comorbid disease conditions. Different mechanisms of COVID-19 infections leading to intensive care unit (ICU) admissions or deaths have been hypothesized. This review provides insights into the relationship between various comorbidities and COVID-19 infection. We further discuss the potential pathophysiological correlation between COVID-19 disease and comorbidities with the medical interventions for comorbid patients. Toward the end, different therapeutic options have been discussed for COVID-19-infected comorbid patients.

Age and Comorbidities Predict COVID-19 Outcome, Regardless of Innate Immune Response Severity: A Single Institutional Cohort Study

OBJECTIVES: The COVID-19 pandemic has claimed over eight hundred thousand lives in the United States alone, with older individuals and those with comorbidities being at higher risk of severe disease and death. Although severe acute respiratory syndrome coronavirus 2–induced hyperinflammation is one of the mechanisms underlying the high mortality, the association between age and innate immune responses in COVID-19 mortality remains unclear. DESIGN: Flow cytometry of fresh blood and multiplexed inflammatory chemokine measurements of sera were performed on samples collected longitudinally from our cohort. Aggregate impact of comorbid conditions was calculated with the Charlson Comorbidity Index, and association between patient factors and outcomes was calculated via Cox proportional hazard analysis and repeated measures analysis of variance. SETTING: A cohort of severely ill COVID-19 patients requiring ICU admission was followed prospectively. PATIENTS: In total, 67 patients (46 male, age 59 ± 14 yr) were included in the study. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Mortality in our cohort was 41.8%. We identified older age (hazard ratio [HR] 1.09 [95% CI 1.07–1.11];p = 0.001), higher comorbidity index (HR 1.24 [95% CI 1.14–1.35];p = 0.039), and hyponatremia (HR 0.90 [95% CI 0.82–0.99];p = 0.026) to each independently increase risk for death in COVID-19. We also found that neutrophilia (R = 0.2;p = 0.017), chemokine C-C motif ligand (CCL) 2 (R = 0.3;p = 0.043), and C-X-C motif chemokine ligand 9 (CXCL9) (R = 0.3;p = 0.050) were weakly but significantly correlated with mortality. Older age was associated with lower monocyte (R = –0.2;p = 0.006) and cluster of differentiation (CD) 16+ cell counts (R = –0.2;p = 0.002) and increased CCL11 concentration (R = 0.3;p = 0.050). Similarly, younger patients (< 65 yr) demonstrated a rise in CD4 (b-coefficient = 0.02;p = 0.036) and CD8 (0.01;p = 0.001) counts, as well as CCL20 (b-coefficient = 6.8;p = 0.036) during their ICU stay. This CD8 count rise was also associated with survival (b-coefficient = 0.01;p = 0.023). CONCLUSIONS: Age, comorbidities, and hyponatremia independently predict mortality in severe COVID-19. Neutrophilia and higher CCL2 and CXCL9 levels are also associated with higher mortality, while independent of age.

Using Computer Vision to Detect Violation of Social Distancing in Queues

On March of 2020, World Health Organization (WHO) declared COVID-19 as a global pandemic after months of infecting and claiming many victims. There are some ways by which we can safeguard ourselves against the virus and thereby controlling the spread of the virus. They are following proper sanitization by washing hands with soap regularly, wearing masks and following social distancing, while being present in public places. Social distancing refers to maintaining at least 6 feet of distance between other people. But the main problem is that most of the people ignore these rules and hence the spread of the virus can not be controlled. The project uses computer vision in order to ensure that social distancing is being followed properly, thus helping to reduce the number of victims that the virus may claim. Computer vision is a field of computer science that deals with how computers can gather knowledge and learn from images and videos. It is a rapidly growing field of science thanks to the many advancements in technology over the past few years such as increase in processing power of computers and the exponential increase in data being available nowadays. The system works by taking input from CCTV or other similar image source and then processing the input to find out if any people violate the rules of social distancing and if any violations are detected, the system will consist of an alert module which will alert the respective authorities regarding the violation so that they can do the needful. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Small World Student Network at the University of Texas at Dallas in Times of Social Distancing (preprint)

To limit the spread of the novel coronavirus on college campuses, a common strategy for the Fall 2020 and Spring 2021 terms has been to offer instruction weighted toward hybrid or fully online modalities. Colleges are now considering whether and how to expand hybrid or fully in-person instruction for future terms, and learn lessons from this experience for future use. Our paper uses Fall 2019 enrollment data for a medium-sized public American university to analyze whether some student groupings by class standing or course level are more susceptible to the spread of infectious disease through academic enrollment networks. Replicating Weeden and Cornwell [8], we find that enrollment networks at the institution are "small worlds" characterized by high clustering, short average path lengths, and multiple independent connections. Connectivity decreases as class standing (graduate vs. undergraduate; senior vs. freshman) and course level increase; as students move from generalized to specialized course loads, networks cluster by major. Holding other factors constant, policies focusing on in-person instruction for lower division students conflict with the greater risk of infectious spread through a lower division network in the absence of additional steps to minimize academic connectivity. There are academic and financial incentives for emphasizing the freshman experience, including concerns about student attrition from the first to second academic year and recouping costs of infrastructure investments in dormitories. Possible solutions could include (i) restricting face-to-face or hybrid instruction to courses in students' academic majors, which would disrupt larger networks into smaller ones and thus restrict the spread of infection across majors, and (ii) take a "scalpel" approach to instruction modes by moving online courses most likely to facilitate epidemic spread.

An ultrapotent synthetic nanobody neutralizes SARS-CoV-2 by stabilizing inactive Spike.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells via an interaction between its Spike protein and the host cell receptor angiotensin-converting enzyme 2 (ACE2). By screening a yeast surface-displayed library of synthetic nanobody sequences, we developed nanobodies that disrupt the interaction between Spike and ACE2. Cryo-electron microscopy (cryo-EM) revealed that one nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains locked into their inaccessible down state, incapable of binding ACE2. Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for Spike and picomolar neutralization of SARS-CoV-2 infection. mNb6-tri retains function after aerosolization, lyophilization, and heat treatment, which enables aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia.

Prognostic Impact of Prior Heart Failure in Patients Hospitalized With COVID-19.

BACKGROUND: Patients with pre-existing heart failure (HF) are likely at higher risk for adverse outcomes in coronavirus disease-2019 (COVID-19), but data on this population are sparse. OBJECTIVES: This study described the clinical profile and associated outcomes among patients with HF hospitalized with COVID-19. METHODS: This study conducted a retrospective analysis of 6,439 patients admitted for COVID-19 at 1 of 5 Mount Sinai Health System hospitals in New York City between February 27 and June 26, 2020. Clinical characteristics and outcomes (length of stay, need for intensive care unit, mechanical ventilation, and in-hospital mortality) were captured from electronic health records. For patients identified as having a history of HF by International Classification of Diseases-9th and/or 10th Revisions codes, manual chart abstraction informed etiology, functional class, and left ventricular ejection fraction (LVEF). RESULTS: Mean age was 63.5 years, and 45% were women. Compared with patients without HF, those with previous HF experienced longer length of stay (8 days vs. 6 days; p < 0.001), increased risk of mechanical ventilation (22.8% vs. 11.9%; adjusted odds ratio: 3.64; 95% confidence interval: 2.56 to 5.16; p < 0.001), and mortality (40.0% vs. 24.9%; adjusted odds ratio: 1.88; 95% confidence interval: 1.27 to 2.78; p = 0.002). Outcomes among patients with HF were similar, regardless of LVEF or renin-angiotensin-aldosterone inhibitor use. CONCLUSIONS: History of HF was associated with higher risk of mechanical ventilation and mortality among patients hospitalized for COVID-19, regardless of LVEF.

An ultra-high affinity synthetic nanobody blocks SARS-CoV-2 infection by locking Spike into an inactive conformation (preprint)

Without an effective prophylactic solution, infections from SARS-CoV-2 continue to rise worldwide with devastating health and economic costs. SARS-CoV-2 gains entry into host cells via an interaction between its Spike protein and the host cell receptor angiotensin converting enzyme 2 (ACE2). Disruption of this interaction confers potent neutralization of viral entry, providing an avenue for vaccine design and for therapeutic antibodies. Here, we develop single-domain antibodies (nanobodies) that potently disrupt the interaction between the SARS-CoV-2 Spike and ACE2. By screening a yeast surface-displayed library of synthetic nanobody sequences, we identified a panel of nanobodies that bind to multiple epitopes on Spike and block ACE2 interaction via two distinct mechanisms. Cryogenic electron microscopy (cryo-EM) revealed that one exceptionally stable nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains (RBDs) locked into their inaccessible down-state, incapable of binding ACE2. Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for SARS-CoV-2 Spike and picomolar neutralization of SARS-CoV-2 infection. mNb6-tri retains stability and function after aerosolization, lyophilization, and heat treatment. These properties may enable aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia, promising to yield a widely deployable, patient-friendly prophylactic and/or early infection therapeutic agent to stem the worst pandemic in a century.