Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors.

Background: Despite an abundance of information on the risk factors of SARS-CoV-2, there have been few US-wide studies of long-term effects. In this paper we analyzed a large medical claims database of US based individuals to identify common long-term effects as well as their associations with various social and medical risk factors.

Methods: The medical claims database was obtained from a prominent US based claims data processing company, namely Change Healthcare.

The Risk of Hospitalization and Mortality After Breakthrough SARS-CoV-2 Infection by Vaccine Type: Observational Study of Medical Claims Data.

Background: Several risk factors have been identified for severe COVID-19 disease by the scientific community. In this paper, we focus on understanding the risks for severe COVID-19 infections after vaccination (ie, in breakthrough SARS-CoV-2 infections). Studying these risks by vaccine type, age, sex, comorbidities, and any prior SARS-CoV-2 infection is important to policy makers planning further vaccination efforts.

Machine learning-based derivation and external validation of a tool to predict death and development of organ failure in hospitalized patients with COVID-19.

COVID-19 mortality risk stratification tools could improve care, inform accurate and rapid triage decisions, and guide family discussions regarding goals of care. A minority of COVID-19 prognostic tools have been tested in external cohorts. Our objective was to compare machine learning algorithms and develop a tool for predicting subsequent clinical outcomes in COVID-19.

A dual-center cohort study on the association between early deep sedation and clinical outcomes in mechanically ventilated patients during the COVID-19 pandemic: The COVID-SED study.

Background: Mechanically ventilated patients have experienced greater periods of prolonged deep sedation during the coronavirus disease (COVID-19) pandemic. Multiple studies from the pre-COVID era demonstrate that early deep sedation is associated with worse outcome. Despite this, there is a lack of data on sedation depth and its impact on outcome for mechanically ventilated patients during the COVID-19 pandemic.

A Dual-Center Cohort Study on The Association Between Early Deep Sedation and Clinical Outcomes in Mechanically Ventilated Patients During the COVID-19 Pandemic: the COVID-SED Study.

: Mechanically ventilated patients have experienced greater periods of prolonged deep sedation during the coronavirus disease (COVID-19) pandemic. Multiple studies from the pre-COVID era demonstrate that early deep sedation is associated with worse outcome. Despite this, there is a lack of data on sedation depth and its impact on outcome for mechanically ventilated patients during the COVID-19 pandemic.

Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19.

BackgroundCOVID-19 mortality risk stratification tools could improve care, inform accurate and rapid triage decisions, and guide family discussions regarding goals of care. A minority of COVID-19 prognostic tools have been tested in external cohorts. Our objective was to compare machine learning algorithms and develop a tool for predicting subsequent clinical outcomes in COVID-19.

Migration pattern, actin cytoskeleton organization and response to PI3K-, mTOR-, and Hsp90-inhibition of glioblastoma cells with different invasive capacities.

High invasiveness and resistance to chemo- and radiotherapy of glioblastoma multiforme (GBM) make it the most lethal brain tumor. Therefore, new treatment strategies for preventing migration and invasion of GBM cells are needed. Using two different migration assays, Western blotting, conventional and super-resolution (dSTORM) fluorescence microscopy we examine the effects of the dual PI3K/mTOR-inhibitor PI-103 alone and in combination with the Hsp90 inhibitor NVP-AUY922 and/or irradiation on the migration, expression of marker proteins, focal adhesions and F-actin cytoskeleton in two GBM cell lines (DK-MG and SNB19) markedly differing in their invasive capacity.

Self-assembled tunable networks of sticky colloidal particles.

Surfaces decorated with dense arrays of microscopic fibres exhibit unique materials properties, including superhydrophobicity and low friction. Nature relies on 'hairy' surfaces to protect blood capillaries from wear and infection (endothelial glycocalyx). Here we report on the discovery of self-assembled tunable networks of microscopic polymer fibres ranging from wavy colloidal 'fur' to highly interconnected networks.

Multiple Myeloma and lifetime occupation: results from the EPILYMPH study.

Background: The EPILYMPH study applied a detailed occupational exposure assessment approach to a large multi-centre case-control study conducted in six European countries. This paper analysed multiple myeloma (MM) risk associated with level of education, and lifetime occupational history and occupational exposures, based on the EPILYMPH data set.

Methods: 277 MM cases and four matched controls per each case were included.

Effects of Lac operon activation, deletion of the Yhha gene, and the removal of oxygen on the ultra-weak photon emission of Escherichia coli.

We observed a relation between gene activity and ultra-weak photon emission (UPE). By comparing the UPEs of E. coli with the LacI gene present and deleted we found that more gene activity produced higher UPE.