Cerebral Venous Thrombosis and Venous Infarction: Case Report of a Rare Initial Presentation of Smoker's Polycythemia

Introduction: Cerebral venous thrombosis is a rare initial presentation of polycythemia. If diagnosed early, treatment can reduce mortality and morbidity significantly. Often it may present with headache as the only complaint, and thus the diagnosis is likely to be missed. Case Presentation: A medically stable 31-year-old male, a chronic smoker with a ∼17 pack-year history of smoking, was admitted to the emergency room with a 2-week history of gradually worsening, severe, throbbing headache in the occipital region sensitive to light. Initial neurological examination was positive only for some involuntary motor tics of the left leg. Initial laboratory workup showed hemoglobin of 20 g/dl and hematocrit of 56.5%. The carboxyhemoglobin level was normal, but the oxygen dissociation curve was shifted to the left. Further evaluation by MRI and MRA of the brain suggested extensive and complete thrombosis of the superior sagittal sinus, right transverse sinus and right sigmoid sinus with a small venous infarct in the right parafrontal region. Given that the patient first presented with a thrombotic event, workup for primary polycythemia and hypercoagulable disorders was carried out, including JAK2 mutation evaluation, which was negative. This left us with smoking as the only risk factor and possible cause for secondary polycythemia. He improved significantly with phlebotomy and anticoagulation treatment. Conclusion: This case illustrates a rare but severe complication of secondary polycythemia stressing the importance of being aware of the risk of developing cerebral thrombosis in patients with chronic smoking exposure

Yttrium-90 Radioembolization of Hepatic Metastases from Colorectal Cancer

Liver metastases from colorectal cancer (CRC) result in substantial morbidity and mortality. The primary treatment is systemic chemotherapy, and in selected patients, surgical resection; however, for patients who are not surgical candidates and/or fail systemic chemotherapy, liver-directed therapies are increasingly being utilized. Yttrium-90 (Y-90) microsphere therapy, also known as selective internal radiation therapy (SIRT) or radioembolization, has proven to be effective in terms of extending time to progression of disease and also providing survival benefit. This review focuses on the use of Y-90 microsphere therapy in the treatment of liver metastases from CRC, including a comprehensive review of published clinical trials and prospective studies conducted thus far. We review the methodology, outcomes, and side effects of Y-90 microsphere therapy for metastatic CRC

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

This article contains supporting information online at http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2113561119/-/DCSupplemental.Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Integrative Biolog

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Studies on Optimization of the Crystal Habit and Improvement on Processing and Pharmacokinetic Parameters of Selected Active Pharmaceutical Ingredients

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<i>In vitro</i> cystein protease inhibitory activity of selected Indian antimalarial plants

476-481In this study few plants having antimalarial activity (leaves of Nyctanthes arbor-tristis L., Caesalpinia crista L., Ailanthus&nbsp;excelsa&nbsp;Roxb., Bauhinia variegate L., seed of Balanites aegyptiaca Delile, entire plant of Enicostema littorale Blume, fruits of Momordica charantia L.) were screened for cystein protease inhibitory activity. Cysteine protease inhibitory activity was done by papain inhibition assay. Water and methanol extracts of all selected plants were screened for in vitro enzyme inhibition assay. Percentage inhibition of papain was measured and IC50 for all the extracts were calculated. Comparative study of above selected medicinal plants methanolic and water extract showed the maximum inhibition in leaves of N. arbor-tristis, 87.8051 %, IC50 &ndash; 13.03 &micro;g/ml and 85.6189 %, IC50 - 16.54 &micro;g/ml, respectively. The present study has provided scientific validity to leaves of N. arbor-tristis against cysteine protease inhibition activity and it is concluded that protease inhibitor of N. arbor-tristis leaves are an indicator of wide range of pharmacological activities such as anticancer, antimalarial, osteoarthritis, osteoporosis, etc., isolation of cysteine protease inhibitors may provide a lead compound for development of novel therapeutic agents in the above areas

Formulation and development of a self-nanoemulsifying drug delivery system of irbesartan

Irbesartan (IRB) is an angiotensin II receptor blocker antihypertensive agent. The aim of the present investigation was to develop a self-nanoemulsifying drug delivery system (SNEDDS) to enhance the oral bioavailability of poorly water-soluble IRB. The solubility of IRB in various oils was determined to identify the oil phase of SNEDDS. Various surfactants and co-surfactants were screened for their ability to emulsify the selected oil. Pseudoternary phase diagrams were constructed to identify the efficient self-emulsifying region. The optimized SNEDDS formulation contained IRB (75 mg), Cremophor® EL (43.33%), Carbitol® (21.67%) and Capryol® 90 (32%). SNEDDS was further evaluated for its percentage transmittance, emulsification time, drug content, phase separation, dilution, droplet size and zeta potential. The optimized formulation of IRB-loaded SNEDDS exhibited complete in vitro drug release in 15 min as compared with the plain drug, which had a limited dissolution rate. It was also compared with the pure drug solution by oral administration in male Wister rats. The in vivo study exhibited a 7.5-fold increase in the oral bioavailability of IRB from SNEDDS compared with the pure drug solution. These results suggest the potential use of SNEDDS to improve dissolution and oral bioavailability of poorly water-soluble IRB