Anti-inflammatory actions of Pentosan polysulfate sodium in a mouse model of influenza virus A/PR8/34-induced pulmonary inflammation.

Introduction: There is an unmet medical need for effective anti-inflammatory agents for the treatment of acute and post-acute lung inflammation caused by respiratory viruses. The semi-synthetic polysaccharide, Pentosan polysulfate sodium (PPS), an inhibitor of NF-kB activation, was investigated for its systemic and local anti-inflammatory effects in a mouse model of influenza virus A/PR8/1934 (PR8 strain) mediated infection. Methods: Immunocompetent C57BL/6J mice were infected intranasally with a sublethal dose of PR8 and treated subcutaneously with 3 or 6 mg/kg PPS or vehicle. Disease was monitored and tissues were collected at the acute (8 days post-infection; dpi) or post-acute (21 dpi) phase of disease to assess the effect of PPS on PR8-induced pathology. Results: In the acute phase of PR8 infection, PPS treatment was associated with a reduction in weight loss and improvement in oxygen saturation when compared to vehicle-treated mice. Associated with these clinical improvements, PPS treatment showed a significant retention in the numbers of protective SiglecF+ resident alveolar macrophages, despite uneventful changes in pulmonary leukocyte infiltrates assessed by flow cytometry. PPS treatment in PR8- infected mice showed significant reductions systemically but not locally of the inflammatory molecules, IL-6, IFN-g, TNF-a, IL-12p70 and CCL2. In the post-acute phase of infection, PPS demonstrated a reduction in the pulmonary fibrotic biomarkers, sICAM-1 and complement factor C5b9. Discussion: The systemic and local anti-inflammatory actions of PPS may regulate acute and post-acute pulmonary inflammation and tissue remodeling mediated by PR8 infection, which warrants further investigation.

Enhancing Supply Chain Resilience: A Machine Learning Approach for Predicting Product Availability Dates Under Disruption (preprint)

The COVID 19 pandemic and ongoing political and regional conflicts have a highly detrimental impact on the global supply chain, causing significant delays in logistics operations and international shipments. One of the most pressing concerns is the uncertainty surrounding the availability dates of products, which is critical information for companies to generate effective logistics and shipment plans. Therefore, accurately predicting availability dates plays a pivotal role in executing successful logistics operations, ultimately minimizing total transportation and inventory costs. We investigate the prediction of product availability dates for General Electric (GE) Gas Power's inbound shipments for gas and steam turbine service and manufacturing operations, utilizing both numerical and categorical features. We evaluate several regression models, including Simple Regression, Lasso Regression, Ridge Regression, Elastic Net, Random Forest (RF), Gradient Boosting Machine (GBM), and Neural Network models. Based on real world data, our experiments demonstrate that the tree based algorithms (i.e., RF and GBM) provide the best generalization error and outperforms all other regression models tested. We anticipate that our prediction models will assist companies in managing supply chain disruptions and reducing supply chain risks on a broader scale.

Pentosan Polysulfate Inhibits Attachment and Infection by SARS-CoV-2 In Vitro: Insights into Structural Requirements for Binding.

Two years since the outbreak of the novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic, there remain few clinically effective drugs to complement vaccines. One is the anticoagulant, heparin, which in 2004 was found able to inhibit invasion of SARS-CoV (CoV-1) and which has been employed during the current pandemic to prevent thromboembolic complications and moderate potentially damaging inflammation. Heparin has also been shown experimentally to inhibit SARS-CoV-2 attachment and infection in susceptible cells. At high therapeutic doses however, heparin increases the risk of bleeding and prolonged use can cause heparin-induced thrombocytopenia, a serious side effect. One alternative, with structural similarities to heparin, is the plant-derived, semi-synthetic polysaccharide, pentosan polysulfate (PPS). PPS is an established drug for the oral treatment of interstitial cystitis, is well-tolerated, and exhibits weaker anticoagulant effects than heparin. In an established Vero cell model, PPS and its fractions of varying molecular weights inhibited invasion by SARS-CoV-2. Intact PPS and its size-defined fractions were characterized by molecular weight distribution and chemical structure using nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry, then employed to explore the structural basis of interactions with SARS-CoV-2 spike protein receptor-binding domain (S1 RBD) and the inhibition of Vero cell invasion. PPS was as effective as unfractionated heparin, but more effective in inhibiting cell infection than low-molecular-weight heparin (on a weight/volume basis). Isothermal titration calorimetry and viral plaque-forming assays demonstrated size-dependent binding to S1 RBD and inhibition of Vero cell invasion, suggesting the potential application of PPS as a novel inhibitor of SARS-CoV-2 infection.

Use of geographic information systems web mapping application to support active case search to guide public health and social measures in the context of COVID-19 in Zimbabwe: a preliminary report to guide replication of methods in similar resource settings.

INTRODUCTION: the new coronavirus (COVID-19) that emerged from Wuhan, Hubei Province of China in December 2019, causing severe acute respiratory syndrome (SARS) has fast spread across the entire globe, with most countries struggling to slow and reduce the spread of the virus through rapid screening, testing, isolation, case management, contact tracing, implementing social distancing and lockdowns. This has been shown to be a major factor in countries that have been successful in containing COVID-19 transmission. Early detection of cases is important, and the use of geospatial technology can support to detect and easily identify potential hotspots that will require timely response. The use of spatial analysis with geographic information systems (GIS) had proved to be effective in providing timely and effective solutions in supporting epidemic response and pandemics over the years. It has developed and evolved rapidly with a complete technological tool for representing data, model construction, visualization and platform construction among others. METHODS: we conducted a geospatial analysis to develop a web mapping application using ArcMap and ArcGIS online to guide and support active case search of potential COVID-19 cases, within 500m radius of COVID-19 confirmed cases to improve detection and testing of suspected cases. RESULTS: the web mapping application tool guides the active case search teams in the field, with clear boundaries on the houses to be visited within 500-meter radius of confirmed positive cases, to conduct active case search of all cases of severe acute respiratory illnesses (SARI), acute respiratory illnesses (ARI), pneumonia etc, to detect and test for COVID-19 towards containing the pandemic. CONCLUSION: the use of GIS and spatial statistical tools have become an important and valuable tool in decision-making and, more importantly, guiding health care professional and other stakeholders in the response being carried out in a more coherent and easy manner. It has proven to be effective in supporting the active case search process to rapidly detect, test and isolate cases during the process, towards containing the COVID-19 pandemic.