Background and Purpose: Coronavirus disease 2019 (COVID-19) has been associated with an increased incidence of thrombotic events, including stroke. However, characteristics and outcomes of COVID-19 patients with stroke are not well known. Methods: We conducted a retrospective observational study of risk factors, stroke characteristics, and short-term outcomes in a large health system in New York City. We included consecutively admitted patients with acute cerebrovascular events from March 1, 2020 through April 30, 2020. Data were stratified by COVID-19 status, and demographic variables, medical comorbidities, stroke characteristics, imaging results, and in-hospital outcomes were examined. Among COVID-19-positive patients, we also summarized laboratory test results. Results: Of 277 patients with stroke, 105 (38.0%) were COVID-19-positive. Compared with COVID-19-negative patients, COVID-19-positive patients were more likely to have a cryptogenic (51.8% versus 22.3%, P <0.0001) stroke cause and were more likely to suffer ischemic stroke in the temporal ( P =0.02), parietal ( P =0.002), occipital ( P =0.002), and cerebellar ( P =0.028) regions. In COVID-19-positive patients, mean coagulation markers were slightly elevated (prothrombin time 15.4±3.6 seconds, partial thromboplastin time 38.6±24.5 seconds, and international normalized ratio 1.4±1.3). Outcomes were worse among COVID-19-positive patients, including longer length of stay ( P <0.0001), greater percentage requiring intensive care unit care ( P =0.017), and greater rate of neurological worsening during admission ( P <0.0001); additionally, more COVID-19-positive patients suffered in-hospital death (33% versus 12.9%, P <0.0001). Conclusions: Baseline characteristics in patients with stroke were similar comparing those with and without COVID-19. However, COVID-19-positive patients were more likely to experience stroke in a lobar location, more commonly had a cryptogenic cause, and had worse outcomes.

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Gene expression is a fundamental cellular process by which proteins are synthesized based on the information coded in the genes. The two major steps of this process are the transcription of the DNA segment corresponding to a gene to mRNA molecules and the translation of the mRNA molecules to proteins by the ribosome. Thus, understanding, modeling and engineering the different stages of this process have both important biotechnological applications and contributions to basic life science. In previous studies we have introduced the Homogenous Ribosome Flow Model (HRFM) and demonstrated its advantages in analyses of the translation process. In this study we introduce the RNA Polymerase Flow Model (RPFM), a non trivial extension of the HRFM, which also includes a backward flow and can be used for modeling transcription and maybe other similar processes. We compare the HRFM and the RPFM in the three regimes of the transcription process: rate limiting initiation, rate limiting elongation and rate limiting termination via a simulative and analytical analysis. In addition, based on experimental data, we show that RPFM is a better choice for modeling transcription process.

Background: Injury is a major global health problem, causing >5,800,000 deaths annually and widespread disability largely attributable to neurotrauma. 89% of trauma deaths occur in low- and middle-income countries (LMICs), however data on neurotrauma epidemiology in LMICs is lacking. In order to support neurotrauma surveillance efforts, we present a review and analysis of data dictionaries from national registries in LMICs. Methods: We performed a scoping review to identify existing national trauma registries for all LMICs. Inclusion/exclusion criteria included articles published since 1991 describing national registry neurotrauma data capture methods in LMICs. Data sources included PubMed and Google Scholar using the terms "trauma/neurotrauma registry" and country name. Resulting registries were analyzed for neurotrauma-specific data dictionaries. These findings were augmented by data from direct contact of neurotrauma organizations, health ministries, and key informants from a convenience sample. These data were then compared to the WHO minimum dataset for injury (MDI) from the international registry for trauma and emergency care. Results: We identified 15 LMICs with 16 total national trauma registries tracking neurotrauma-specific data elements. Among these, Cameroon had the highest concordance with the MDI, followed by Colombia, Iran, Myanmar and Thailand. The MDI elements least often found in the data dictionaries included helmet use, and alcohol level. Data dictionaries differed significantly among LMICs. Common elements included Glasgow Coma Score, mechanism of injury, anatomical site of injury and injury severity scores. Limitations included low response rate in direct contact methods. Conclusion: Significant heterogeneity was observed between the neurotrauma data dictionaries, as well as a spectrum of concordance or discordance with the MDI. Findings offer a contextually relevant menu of possible neurotrauma data elements that LMICs can consider tracking nationally to enhance neurotrauma surveillance and care systems. Standardization of nationwide neurotrauma data collection can facilitate international comparisons and bidirectional learning among health care governments.