Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States.

The rapid spread of the numerous outbreaks of the coronavirus disease 2019 (COVID-19) pandemic has fueled interest in mathematical models designed to understand and predict infectious disease spread, with the ultimate goal of contributing to the decision making of public health authorities. Here, we propose a computational pipeline that dynamically parameterizes a modified SEIRD (susceptible-exposed-infected-recovered-deceased) model using standard daily series of COVID-19 cases and deaths, along with isolated estimates of population-level seroprevalence. We test our pipeline in five heavily impacted states of the US (New York, California, Florida, Illinois, and Texas) between March and August 2020, considering two scenarios with different calibration time horizons to assess the update in model performance as new epidemiologic data become available. Our results show a median normalized root mean squared error (NRMSE) of 2.38% and 4.28% in calibrating cumulative cases and deaths in the first scenario, and 2.41% and 2.30% when new data are assimilated in the second scenario, respectively. Then, 2-week (4-week) forecasts of the calibrated model resulted in median NRMSE of cumulative cases and deaths of 5.85% and 4.68% (8.60% and 17.94%) in the first scenario, and 1.86% and 1.93% (2.21% and 1.45%) in the second. Additionally, we show that our method provides significantly more accurate predictions of cases and deaths than a constant parameterization in the second scenario (p < 0.05). Thus, we posit that our methodology is a promising approach to analyze the dynamics of infectious disease outbreaks, and that our forecasts could contribute to designing effective pandemic-arresting public health policies. Supplementary Information: The online version contains supplementary material available at 10.1007/s00366-023-01816-9.

Autoantibodies are highly prevalent in non-SARS-CoV-2 respiratory infections and critical illness.

The widespread presence of autoantibodies in acute infection with SARS-CoV-2 is increasingly recognized, but the prevalence of autoantibodies in non-SARS-CoV-2 infections and critical illness has not yet been reported. We profiled IgG autoantibodies in 267 patients from 5 independent cohorts with non-SARS-CoV-2 viral, bacterial, and noninfectious critical illness. Serum samples were screened using Luminex arrays that included 58 cytokines and 55 autoantigens, many of which are associated with connective tissue diseases (CTDs). Samples positive for anti-cytokine antibodies were tested for receptor blocking activity using cell-based functional assays. Anti-cytokine antibodies were identified in > 50% of patients across all 5 acutely ill cohorts. In critically ill patients, anti-cytokine antibodies were far more common in infected versus uninfected patients. In cell-based functional assays, 11 of 39 samples positive for select anti-cytokine antibodies displayed receptor blocking activity against surface receptors for Type I IFN, GM-CSF, and IL-6. Autoantibodies against CTD-associated autoantigens were also commonly observed, including newly detected antibodies that emerged in longitudinal samples. These findings demonstrate that anti-cytokine and autoantibodies are common across different viral and nonviral infections and range in severity of illness.

Rhamnan sulfate reduces atherosclerotic plaque formation and vascular inflammation.

OBJECTIVE: While lipid-lowering drugs have become a mainstay of clinical therapy these treatments only slow the progression of the disease and can have side effects. Thus, new treatment options are needed to supplement the effects of lipid lowering therapy for treating atherosclerosis. We examined the use of an inexpensive and widely available marine polysaccharide rhamnan sulfate as an oral therapeutic for limiting vascular inflammation and atherosclerosis. METHODS AND RESULTS: We found rhamnan sulfate enhanced the barrier function of endothelial cells, preventing the deposition of LDL and maintaining barrier function even in the presence of glycocalyx-degrading enzymes. Rhamnan sulfate was also found to bind directly to FGF-2, PDGF-BB and NF-κB subunits with high affinity. In addition, rhamnan sulfate was a potent inhibitor of NF-κB pathway activation in endothelial cells by TNF-α. We treated ApoE-/- mice with a high fat diet for 4 weeks and then an addition 9 weeks of high fat diet with or without rhamnan sulfate. Rhamnan sulfate reduced vascular inflammation and atherosclerosis in both sexes of ApoE-/- mice but had a stronger therapeutic effect in female mice. Oral consumption of rhamnan sulfate induced a significant decrease in cholesterol plasma levels in female mice but not in male mice. In addition, there was a marked reduction in inflammation for female mice in the liver and aortic root in comparison to male mice. CONCLUSIONS: Rhamnan sulfate has beneficial effects in reducing inflammation, binding growth factors and NF-κB, enhancing endothelial barrier function and reducing atherosclerotic plaque formation in ApoE-/- mice.

Mathematical characterization of population dynamics in breast cancer cells treated with doxorubicin.

The development of chemoresistance remains a significant cause of treatment failure in breast cancer. We posit that a mathematical understanding of chemoresistance could assist in developing successful treatment strategies. Towards that end, we have developed a model that describes the cytotoxic effects of the standard chemotherapeutic drug doxorubicin on the MCF-7 breast cancer cell line. We assume that treatment with doxorubicin induces a compartmentalization of the breast cancer cell population into surviving cells, which continue proliferating after treatment, and irreversibly damaged cells, which gradually transition from proliferating to treatment-induced death. The model is fit to experimental data including variations in drug concentration, inter-treatment interval, and number of doses. Our model recapitulates tumor cell dynamics in all these scenarios (as quantified by the concordance correlation coefficient, CCC > 0.95). In particular, superior tumor control is observed with higher doxorubicin concentrations, shorter inter-treatment intervals, and a higher number of doses (p < 0.05). Longer inter-treatment intervals require adapting the model parameterization after each doxorubicin dose, suggesting the promotion of chemoresistance. Additionally, we propose promising empirical formulas to describe the variation of model parameters as functions of doxorubicin concentration (CCC > 0.78). Thus, we conclude that our mathematical model could deepen our understanding of the cytotoxic effects of doxorubicin and could be used to explore practical drug regimens achieving optimal tumor control.

Nanobodies: Next Generation of Cancer Diagnostics and Therapeutics.

The development of targeted medicine has greatly expanded treatment options and spurred new research avenues in cancer therapeutics, with monoclonal antibodies (mAbs) emerging as a prevalent treatment in recent years. With mixed clinical success, mAbs still hold significant shortcomings, as they possess limited tumor penetration, high manufacturing costs, and the potential to develop therapeutic resistance. However, the recent discovery of "nanobodies," the smallest-known functional antibody fragment, has demonstrated significant translational potential in preclinical and clinical studies. This review highlights their various applications in cancer and analyzes their trajectory toward their translation into the clinic.

Algal Polysaccharides as Therapeutic Agents for Atherosclerosis.

Seaweed-derived polysaccharides including agar and alginate, have found widespread applications in biomedical research and medical therapeutic applications including wound healing, drug delivery, and tissue engineering. Given the recent increases in the incidence of diabetes, obesity and hyperlipidemia, there is a pressing need for low cost therapeutics that can economically and effectively slow the progression of atherosclerosis. Marine polysaccharides have been consumed by humans for millennia and are available in large quantities at low cost. Polysaccharides such as fucoidan, laminarin sulfate and ulvan have shown promise in reducing atherosclerosis and its accompanying risk factors in animal models. However, others have been tested in very limited context in scientific studies. In this review, we explore the current state of knowledge for these promising therapeutics and discuss the potential and challenges of using seaweed derived polysaccharides as therapies for atherosclerosis.