Comparing the performance of artificial intelligence learning models to medical students in solving histology and embryology multiple choice questions.

INTRODUCTION: The appearance of artificial intelligence language models (AI LMs) in the form of chatbots has gained a lot of popularity worldwide, potentially interfering with different aspects of education, including medical education as well. The present study aims to assess the accuracy and consistency of different AI LMs regarding the histology and embryology knowledge obtained during the 1st year of medical studies. METHODS: Five different chatbots (ChatGPT, Bing AI, Bard AI, Perplexity AI, and ChatSonic) were given two sets of multiple-choice questions (MCQs). AI LMs test results were compared to the same test results obtained from 1st year medical students. Chatbots were instructed to use revised Bloom's taxonomy when classifying questions depending on hierarchical cognitive domains. Simultaneously, two histology teachers independently rated the questions applying the same criteria, followed by the comparison between chatbots' and teachers' question classification. The consistency of chatbots' answers was explored by giving the chatbots the same tests two months apart. RESULTS: AI LMs successfully and correctly solved MCQs regarding histology and embryology material. All five chatbots showed better results than the 1st year medical students on both histology and embryology tests. Chatbots showed poor results when asked to classify the questions according to revised Bloom's cognitive taxonomy compared to teachers. There was an inverse correlation between the difficulty of questions and their correct classification by the chatbots. Retesting the chatbots after two months showed a lack of consistency concerning both MCQs answers and question classification according to revised Bloom's taxonomy learning stage. CONCLUSION: Despite the ability of certain chatbots to provide correct answers to the majority of diverse and heterogeneous questions, a lack of consistency in answers over time warrants their careful use as a medical education tool.

Small Interfering Ribonucleic Acid as Lipid-Lowering Therapy: Inclisiran in Focus.

The PCSK9 (Proprotein Convertase Subtilisin/Kexin type 9) enzyme interferes with the metabolism of low-density lipoprotein (LDL) cholesterol. Inhibition of PCSK9 results in lower LDL cholesterol levels, which can be achieved by different molecular pathways. Monoclonal antibodies targeting circulating PCSK9 have shown strong and persistent effects on lowering the LDL cholesterol level, while reducing the risk of future cardiovascular events. However, this therapy requires once- or twice-monthly administration in the form of subcutaneous injection. This dosing regimen might impact the therapy adherence in cardiovascular patients who often require multiple drugs with different dosing intervals. Small interfering ribonucleic acid (siRNA) represents a promising therapy approach for patients with elevated LDL cholesterol level despite optimized background statin therapy. Inclisiran is a synthesized siRNA which inhibits PCSK9 synthesis in the liver and provides sustained and durable lowering of LDL cholesterol with twice-yearly application and a good tolerability profile. Herein, we present an overview of the current available data and critical review of the major clinical trials which assessed safety and efficacy of inclisiran in different groups of patients with elevated LDL cholesterol level.

Differentiation of Amyloid Plaques Between Alzheimer's Disease and Non-Alzheimer's Disease Individuals Based on Gray-Level Co-occurrence Matrix Texture Analysis.

Amyloid plaques, one of the main hallmarks of Alzheimer's disease (AD), are classified into diffuse (associated with cognitive impairment) and dense-core types (a common finding in brains of people without Alzheimer's disease (non-AD) and without impaired cognitive function) based on their morphology. We tried to determine the usability of gray-level co-occurrence matrix (GLCM) texture parameters of homogeneity and heterogeneity for the differentiation of amyloid plaque images obtained from AD and non-AD individuals. Images of amyloid-ß (Aß) immunostained brain tissue samples were obtained from the Aging, Dementia and Traumatic Brain Injury Project. A total of 1,039 plaques were isolated from different brain regions of 69 AD and non-AD individuals and used for further GLCM analysis. Images of Aß stained plaques show higher values of heterogeneity parameters and lower values of homogeneity parameters in AD patients, and vice versa in non-AD patients. Additionally, GLCM analysis shows differences in Aß plaque texture between different brain regions in non-AD patients and correlates with variables that characterize patient's dementia status. The present study shows that GLCM texture analysis is an efficient method to discriminate between different types of amyloid plaques based on their morphology and thus can prove as a valuable tool in the neuropathological investigation of dementia.

Proteolytic activation of the essential parasitophorous vacuole cysteine protease SERA6 accompanies malaria parasite egress from its host erythrocyte.

The malaria parasite replicates within an intraerythrocytic parasitophorous vacuole (PV). The PV and host cell membranes eventually rupture, releasing merozoites in a process called egress. Certain inhibitors of serine and cysteine proteases block egress, indicating a crucial role for proteases. The Plasmodium falciparum genome encodes nine serine-repeat antigens (SERAs), each of which contains a central domain homologous to the papain-like (clan CA, family C1) protease family. SERA5 and SERA6 are indispensable in blood-stage parasites, but the function of neither is known. Here we show that SERA6 localizes to the PV where it is precisely cleaved just prior to egress by an essential serine protease called PfSUB1. Mutations that replace the predicted catalytic Cys of SERA6, or that block SERA6 processing by PfSUB1, could not be stably introduced into the parasite genomic sera6 locus, indicating that SERA6 is an essential enzyme and that processing is important for its function. We demonstrate that cleavage of SERA6 by PfSUB1 converts it to an active cysteine protease. Our observations reveal a proteolytic activation step in the malarial PV that may be required for release of the parasite from its host erythrocyte.