Polydimethylsiloxane loaded capsaicin afflicts membrane integrity, metabolic activity and biofilm formation of nosocomial pathogens.

Biofilms constitute 80% of all nosocomial infections associated with invasive medical devices. Polydimethylsiloxane, a highly elastic, inert, non-reactive, biocompatible silicone polymer is widely used as implant biomaterial due to its non-toxic and low-immunogenic nature. Owing to its hydrophobicity, PDMS suffers from microbial adhesion.

Trabecular meshwork ultrastructural changes in primary and secondary glaucoma.

To examine ultrastructural changes in the trabecular meshwork (TM) in patients with primary and secondary glaucoma using scanning electron microscopy (SEM). This was a qualitative descriptive hospital-based study on the ultrastructure of the TM. Pure TM samples were collected after microincisional trabeculectomy from 26 patients with primary or secondary glaucoma and 10 control samples from eye bank donor corneas.

A comparative study of wavelet families for schizophrenia detection.

Schizophrenia (SZ) is a chronic mental disorder, affecting approximately 1% of the global population, it is believed to result from various environmental factors, with psychological factors potentially influencing its onset and progression. Discrete wavelet transform (DWT)-based approaches are effective in SZ detection. In this report, we aim to investigate the effect of wavelet and decomposition levels in SZ detection.

Multimodality Imaging in the Diagnosis and Staging of Gestational Choriocarcinoma.

Choriocarcinoma is an uncommon, highly invasive malignancy arising from the placental trophoblastic tissue. Though staging is clinical, imaging has significant role in the diagnosis, staging, prognostic risk scoring, and management of choriocarcinomas. The purpose of this article is to review the role of multimodality imaging in the diagnosis, staging, and management of choriocarcinomas in correlation with clinicopathologic findings.

Comparing new tools of artificial intelligence to the authentic intelligence of our global health students.

Introduction: The transformative feature of Artificial Intelligence (AI) is the massive capacity for interpreting and transforming unstructured data into a coherent and meaningful context. In general, the potential that AI will alter traditional approaches to student research and its evaluation appears to be significant. With regard to research in global health, it is important for students and research experts to assess strengths and limitations of GenAI within this space.