Firearm Violence in America: A Growing Health Problem

Firearm injury is a disease that afflicts many individuals in the United States, either directly or indirectly. Trauma and critical care nurses have direct experience with this life-threatening disease and recognize the high lethality and life-altering consequences of these injuries. The magnitude of this health problem requires a focus on primary prevention. We recognize that any focus on firearm injury is often contentious and political; however, nurses bring a ready-made credibility and focus on evidence-based practice to the prevention of this disease

The Rts1 Regulatory Subunit of Protein Phosphatase 2A Is Required for Control of G1 Cyclin Transcription and Nutrient Modulation of Cell Size

The key molecular event that marks entry into the cell cycle is transcription of G1 cyclins, which bind and activate cyclin-dependent kinases. In yeast cells, initiation of G1 cyclin transcription is linked to achievement of a critical cell size, which contributes to cell-size homeostasis. The critical cell size is modulated by nutrients, such that cells growing in poor nutrients are smaller than cells growing in rich nutrients. Nutrient modulation of cell size does not work through known critical regulators of G1 cyclin transcription and is therefore thought to work through a distinct pathway. Here, we report that Rts1, a highly conserved regulatory subunit of protein phosphatase 2A (PP2A), is required for normal control of G1 cyclin transcription. Loss of Rts1 caused delayed initiation of bud growth and delayed and reduced accumulation of G1 cyclins. Expression of the G1 cyclin CLN2 from an inducible promoter rescued the delayed bud growth in rts1Δ cells, indicating that Rts1 acts at the level of transcription. Moreover, loss of Rts1 caused altered regulation of Swi6, a key component of the SBF transcription factor that controls G1 cyclin transcription. Epistasis analysis revealed that Rts1 does not work solely through several known critical upstream regulators of G1 cyclin transcription. Cells lacking Rts1 failed to undergo nutrient modulation of cell size. Together, these observations demonstrate that Rts1 is a key player in pathways that link nutrient availability, cell size, and G1 cyclin transcription. Since Rts1 is highly conserved, it may function in similar pathways in vertebrates

Atypical Prolonged Viral Shedding With Intra-Host SARS-CoV-2 Evolution in a Mildly Affected Symptomatic Patient

International audienceThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is caused by a respiratory virus with a wide range of manifestations, varying from asymptomatic to fatal cases, with a generally short outcome. However, some individuals present long-term viral shedding. We monitored 38 individuals who were mildly affected by the SARS-CoV-2 infection. Out of the total studied population, three (7.9%) showed atypical events regarding the duration of positivity for viral RNA detection. In one of these atypical cases, a previously HIV-positive male patient presented a SARS-CoV-2 RNA shedding and subgenomic RNA (sgRNA) detected from the upper respiratory tract, respectively, for 232 and 224 days after the onset of the symptoms. The SARS-CoV-2 B.1.1.28 lineage, one of the most prevalent in Brazil in 2020, was identified in this patient in three serial samples. Interestingly, the genomic analyses performed throughout the infectious process showed an increase in the genetic diversity of the B.1.1.28 lineage within the host itself, with viral clearance occurring naturally, without any intervention measures to control the infection. Contrasting widely spread current knowledge, our results indicate that potentially infectious SARS-CoV-2 virus might be shed by much longer periods by some infected patients. This data call attention to better adapted non-pharmacological measures and clinical discharge of patients aiming at preventing the spread of SARS-CoV-2 to the population

Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model.

OBJECTIVE. Deep learning applications in radiology often suffer from overfitting, limiting generalization to external centers. The objective of this study was to develop a high-quality prostate segmentation model capable of maintaining a high degree of performance across multiple independent datasets using transfer learning and data augmentation. MATERIALS AND METHODS. A retrospective cohort of 648 patients who underwent prostate MRI between February 2015 and November 2018 at a single center was used for training and validation. A deep learning approach combining 2D and 3D architecture was used for training, which incorporated transfer learning. A data augmentation strategy was used that was specific to the deformations, intensity, and alterations in image quality seen on radiology images. Five independent datasets, four of which were from outside centers, were used for testing, which was conducted with and without fine-tuning of the original model. The Dice similarity coefficient was used to evaluate model performance. RESULTS. When prostate segmentation models utilizing transfer learning were applied to the internal validation cohort, the mean Dice similarity coefficient was 93.1 for whole prostate and 89.0 for transition zone segmentations. When the models were applied to multiple test set cohorts, the improvement in performance achieved using data augmentation alone was 2.2% for the whole prostate models and 3.0% for the transition zone segmentation models. However, the best test-set results were obtained with models fine-tuned on test center data with mean Dice similarity coefficients of 91.5 for whole prostate segmentation and 89.7 for transition zone segmentation. CONCLUSION. Transfer learning allowed for the development of a high-performing prostate segmentation model, and data augmentation and fine-tuning approaches improved performance of a prostate segmentation model when applied to datasets from external centers