Genome Sequence of Three Siphoviruses in the EE, GA and EA5 Actinobacteriophage Clusters: Biscayne, Bush and GreenIvy.

Bacteriophages Biscayne, Bush and GreenIvy were isolated from soil samples in Miami, FL using NRRL B-24224 as host. Transmission electron microscopy shows siphoviral morphologies for all three phages. Based on gene content similarity to other actinobacteriophages, they are assigned to the EE, GA and EA5 clusters, respectively.

An Analysis of the Prevalence and Trends in Drug-Related Lyrics on Twitter (X): Quantitative Approach.

Background: The pervasiveness of drug culture has become evident in popular music and social media. Previous research has examined drug abuse content in both social media and popular music; however, to our knowledge, the intersection of drug abuse content in these 2 domains has not been explored. To address the ongoing drug epidemic, we analyzed drug-related content on Twitter (subsequently rebranded X), with a specific focus on lyrics.

Detection of decline in estimated glomerular filtration rate in patients with type 2 diabetes by cystatin C-based equations.

Background: Aging population is a significant issue in Viet Nam and across the globe. Elderly individuals are at higher risk of chronic kidney disease (CKD), especially those with diabetes. Several studies found that the estimated glomerular filtration rate (eGFR) determined using creatinine-based equations was not as accurate as that determined using cystatin C-based equations.

Comparative analysis of stomatal pore instance segmentation: Mask R-CNN vs. YOLOv8 on Phenomics Stomatal dataset.

This study conducts a rigorous comparative analysis between two cutting-edge instance segmentation methods, Mask R-CNN and YOLOv8, focusing on stomata pore analysis. A novel dataset specifically tailored for stomata pore instance segmentation, named PhenomicsStomata, was introduced. This dataset posed challenges such as low resolution and image imperfections, prompting the application of advanced preprocessing techniques, including image enhancement using the Lucy-Richardson Algorithm.

Evaluation of meniscal injury on magnetic resonance imaging and knee arthroscopy in patient with anterior cruciate ligament tear.

Introduction: Meniscal injuries often occur in association with anterior cruciate ligament (ACL) injury. Failure to detect meniscal tears in patients with ACL injuries can lead to more complex tears and make them more difficult to repair.

Objective: To determine the degree of correlation between magnetic resonance imaging (MRI) and knee arthroscopy in diagnosing meniscal injuries in patients with ACL tears.