Real world utilization of REGEN-COV2 at a community hospital.

INTRODUCTION: Monoclonal antibodies received an Emergency Use Authorization (EUA) from the U.S. Food & Drug Administration for the outpatient treatment of mild to moderate coronavirus disease 2019 (COVID-19). REGN-COV2, casirivimab and imdevimab, has been shown to decrease the viral load and healthcare visits of those with mild to moderate COVID-19 who are treated in the outpatient setting. OBJECTIVE: To determine 7- and 14-day emergency department (ED) and hospitalization rates of adult patients given REGN-COV2 for the outpatient treatment of COVID-19 at a community hospital. METHODS: A convenience sample of consecutive adult patients given REGN-COV2 from January 18, 2021 through March 31, 2021 for the outpatient treatment of mild to moderate COVID-19. Abstracted data included patient demographics, allergic reactions, ED presentations and hospitalizations at 7 and 14 days, and in-hospital mortality. RESULTS: A total of 68 patients with a medain age of 69 years (IQR 57-75.5) and 58.3% being female were given REGEN-COV2 during the study period. No allergic reactions were noted during infusion. Of those infused, 18% (12/68) were infused in the ED and had a median length of stay of 477 min. Following infusion, 10% (7/68) of patients re-presented to the ED and 2% (1/68) were hospitalized for COVID-19 at 14 days. In those aged 65 years or greater, 12% (5/42) of patients re-presented to the ED following infusion. Of those who re-presented to the emergency department, the median age was 72.5 years and the median time from infusion to re-presentation was 2.0 days. No patients suffered in-hospital mortality during the study period. CONCLUSION: There was a significant length of stay associated with REGN-COV2 infusion in the emergency department. Following REGN-COV2 infusion, few patients under the age of 65 re-presented to the emergency department at seven and 14 days. However, a large number of patients aged over 65 years re-presented to the ED following infusion.

A data-driven computational scheme for the nonlinear mechanical properties of cellular mechanical metamaterials under large deformation.

Cellular mechanical metamaterials are a special class of materials whose mechanical properties are primarily determined by their geometry. However, capturing the nonlinear mechanical behavior of these materials, especially those with complex geometries and under large deformation, can be challenging due to inherent computational complexity. In this work, we propose a data-driven multiscale computational scheme as a possible route to resolve this challenge. We use a neural network to approximate the effective strain energy density as a function of cellular geometry and overall deformation. The network is constructed by "learning" from the data generated by finite element calculation of a set of representative volume elements at cellular scales. This effective strain energy density is then used to predict the mechanical responses of cellular materials at larger scales. Compared with direct finite element simulation, the proposed scheme can reduce the computational time up to two orders of magnitude. Potentially, this scheme can facilitate new optimization algorithms for designing cellular materials of highly specific mechanical properties.

Automated particle picking for low-contrast macromolecules in cryo-electron microscopy.

Cryo-electron microscopy is an increasingly popular tool for studying the structure and dynamics of biological macromolecules at high resolution. A crucial step in automating single-particle reconstruction of a biological sample is the selection of particle images from a micrograph. We present a novel algorithm for selecting particle images in low-contrast conditions; it proves more effective than the human eye on close-to-focus micrographs, yielding improved or comparable resolution in reconstructions of two macromolecular complexes.

Joint analysis of expression levels and histological images identifies genes associated with tissue morphology.

Histopathological images are used to characterize complex phenotypes such as tumor stage. Our goal is to associate features of stained tissue images with high-dimensional genomic markers. We use convolutional autoencoders and sparse canonical correlation analysis (CCA) on paired histological images and bulk gene expression to identify subsets of genes whose expression levels in a tissue sample correlate with subsets of morphological features from the corresponding sample image. We apply our approach, ImageCCA, to two TCGA data sets, and find gene sets associated with the structure of the extracellular matrix and cell wall infrastructure, implicating uncharacterized genes in extracellular processes. We find sets of genes associated with specific cell types, including neuronal cells and cells of the immune system. We apply ImageCCA to the GTEx v6 data, and find image features that capture population variation in thyroid and in colon tissues associated with genetic variants (image morphology QTLs, or imQTLs), suggesting that genetic variation regulates population variation in tissue morphological traits.

Real World Utilization of Bamlanivimab at a Rural Community Hospital.

Introduction Although there were several proposed treatments for patients that were hospitalized with COVID-19, outpatient treatments for those with mild to moderate illness were limited prior to the emergency use authorization (EUA) of virus-neutralizing monoclonal antibodies. To assess the efficacy of outpatient monoclonal therapy, the investigators assessed the seven, 14, and 28-day emergency department and hospitalization rates of adult patients given bamlanivimab for the treatment of COVID-19 at a community hospital. Methods A retrospective chart review was performed of all adult patients given bamlanivimab within the emergency department or an outpatient infusion center from December 2, 2020 through January 8, 2021 for the treatment of mild to moderate COVID-19. Patients were compared to a set of controls who would have qualified for bamlanivimab treatment prior to its authorization in reverse temporal order from November 30, 2020 through August 1, 2020. Abstracted data included patient demographics, allergic reactions, emergency department presentations, and hospitalizations at seven, 14, and 28 days post-infusion due to COVID-19 and any in-hospital mortality in those admitted with a COVID-19 complication.  Results A total of 136 patients received bamlanivimab during the study period with none having an allergic reaction during infusion. In those who received bamlanivimab, 84 (61.8%) patients included were aged 65 years or older. At 28 days, there was a statistically significant reduction in emergency department visits in those who received bamlanivimab (20 vs 36 patients; p = 0.03) but not at seven days (12 vs 20 patients; p = 0.18) or 14 days (17 vs 28 patients; p = 0.11). No statistically significant difference in emergency department returns was noted in those aged 65 years or older at seven (eight vs eight patients; p = 0.70), 14 (11 vs 10 patients; p = 0.83), or 28 days (13 vs 14 patients, p = 0.46). A total of six (4.4%) patients were hospitalized at 28 days following the bamlanivimab infusion with five (83.3%) being aged 65 or older. No statistical difference was noted for decreased hospitalizations at seven (four vs five patients; p = 0.79), 14 (five vs nine patients; p = 0.32), or 28 days (six vs nine patients; p = 0.49) post-infusion. No patients suffered from in-hospital mortality after infusion with bamlanivimab. Conclusion Outpatient infusion of bamlanivimab reduced the incidence of those with mild to moderate COVID-19 requiring subsequent care through the emergency department at 28 days but not hospitalizations within this time frame. No statistical difference was noted in either emergency department visits or hospitalizations in those aged 65 or greater who were treated as an outpatient with bamlanivimab for mild to moderate COVID-19.

Optimisation of recovery protocols for double-base smokeless powder residues analysed by total vaporisation (TV) SPME/GC-MS.

The investigation of explosive events requires appropriate evidential protocols to recover and preserve residues from the scene. In this study, a central composite design was used to determine statistically validated optimum recovery parameters for double-base smokeless powder residues on steel, analysed using total vaporisation (TV) SPME/GC-MS. It was found that maximum recovery was obtained using isopropanol-wetted swabs stored under refrigerated conditions, then extracted for 15min into acetone on the same day as sample collection. These parameters were applied to the recovery of post-blast residues deposited on steel witness surfaces following a PVC pipe bomb detonation, resulting in detection of all target components across the majority of samples. Higher overall recoveries were obtained from plates facing the sides of the device, consistent with the point of first failure occurring in the pipe body as observed in previous studies. The methodology employed here may be readily applied to a variety of other explosive compounds, and thus assist in establishing 'best practice' procedures for explosive investigations.

Gila monster bite.

A 29-year-old man was bitten on the forearm by a wild Gila monster. Radiographs demonstrated subcutaneous air. During a period of observation, erythema and edema progressed from the forearm to the axilla and he developed a significant leukocytosis. No purulence was found upon surgical evaluation. We hypothesize that air was introduced into the wound by the "pulsing," chewing-like action that the Gila monster made while it was attached to the man's forearm.