External validation and performance analysis of a deep learning-based model for the detection of intracranial hemorrhage.

Purpose: We aimed to investigate the external validation and performance of an FDA-approved deep learning model in labeling intracranial hemorrhage (ICH) cases on a real-world heterogeneous clinical dataset. Furthermore, we delved deeper into evaluating how patients' risk factors influenced the model's performance and gathered feedback on satisfaction from radiologists of varying ranks.

Methods: This prospective IRB approved study included 5600 non-contrast CT scans of the head in various clinical settings, that is, emergency, inpatient, and outpatient units.

Stable self-assembled oral metformin-bridged nanocochleates against hepatocellular carcinoma.

Despite its established anti-diabetic activity, Metformin hydrochloride (MET) has been repurposed for the management of hepatocellular carcinoma (HCC). Owing to MET high aqueous solubility and poor oral permeability, a novel nanoplatform is sought to overcome the current challenges of traditional formulations. In this study, we developed MET-bridged nanocochleates (MET-CO) using a direct bridging method followed by optimization and assessment using various in-vitro and in-vivo pharmacokinetic methods.

Antimicrobial Sub-MIC induces Staphylococcus aureus biofilm formation without affecting the bacterial count.

Background: Biofilm formation is an essential virulence factor that creates a highly protected growth mode for Staphylococcus aureus (S. aureus) to survive in any hostile environment. Antibiotic sub-minimal inhibitory concentration (sub-MIC) may modulate the biofilm formation ability of bacterial pathogens, thereby affecting bacterial pathogenesis and infection outcomes.

Dielectric properties of epitaxially grown lattice-mismatched GaAs/p-Si heterojunction diode.

The current work presents the possibility of tuning the dielectric parameters by changing the temperature, voltage, and frequency. The unusual behavior of some parameters was attributed to the lattice mismatch constant between gallium arsenide (GaAs) and silicon (Si) and the crystal defects between them. In this article, a thin GaAs film has been grown on Si substrates by liquid phase epitaxial (LPE) as n-GaAs/p-Si heterostructure.