Enzymes in the cytochrome P450 4 (CYP4) family are involved in the metabolism of fatty acids, xenobiotics, therapeutic drugs, and signaling molecules, including eicosanoids, leukotrienes, and prostanoids. As CYP4 enzymes play a role in the maintenance of fatty acids and fatty-acid-derived bioactive molecules within a normal range, they have been implicated in various biological functions, including inflammation, skin barrier, eye function, cardiovascular health, and cancer. Numerous studies have indicated that genetic variants of CYP4 genes cause inter-individual variations in metabolism and disease susceptibility. Genetic variants of CYP4A11, 4F2 genes are associated with cardiovascular diseases. Mutations of CYP4B1, CYP4Z1, and other CYP4 genes that generate 20-HETE are a potential risk for cancer. CYP4V2 gene variants are associated with ocular disease, while those of CYP4F22 are linked to skin disease and CYP4F3B is associated with the inflammatory response. The present study comprehensively collected research to provide an updated view of the molecular functionality of CYP4 genes and their associations with human diseases. Functional analysis of CYP4 genes with clinical implications is necessary to understand inter-individual variations in disease susceptibility and for the development of alternative treatment strategies.

UDP-glucuronosyltransferases (UGTs) are phase II drug-metabolizing enzymes that metabolize endogenous fatty acids such as arachidonic acid metabolites, as well as many prescription drugs, such as opioids, antiepileptics, and antiviral drugs. The UGT1A and 2B genes are highly polymorphic, and their genetic variants may affect the pharmacokinetics and hence the responses of many drugs and fatty acids. This study collected data and updated the current view of the molecular functionality of genetic variants on UGT genes that impact drug responses and the susceptibility to human diseases. The functional information of UGT genetic variants with clinical associations are essential to understand the inter-individual variation in drug responses and susceptibility to toxicity.

Background: Artificial intelligence (AI) programs generate responses to input text, showcasing their innovative capabilities in education and demonstrating various potential benefits, particularly in the field of medical education. The current knowledge of health profession students about AI programs has still not been assessed in Jordan and the West Bank of Palestine (WBP). Aim: This study aimed to assess students’ awareness and practice of AI programs in medicine and pharmacy in Jordan and the WBP. Methods: This study was in the form of an observational, cross-sectional survey. A questionnaire was electronically distributed among students of medicine and pharmacy at An-Najah National University (WBP), Al-Isra University (Jordan), and Al-Balqa Applied University (Jordan). The questionnaire consisted of three main categories: sociodemographic characteristics of the participants, practice of AI programs, and perceptions of AI programs, including ChatGPT. Results: A total of 321 students responded to the distributed questionnaire, and 261 participants (81.3%) stated that they had heard about AI programs. In addition, 135 participants had used AI programs before (42.1%), while less than half the participants used them in their university studies (44.2%): for drug information (44.5%), homework (38.9%), and writing research articles (39.3%). There was significantly (48.3%, P< 0.005) more conviction in the use of AI programs for writing research articles among pharmacy students from Palestine compared to Jordan. Lastly, there was significantly more (53.8%, P< 0.05) AI program use among medicine students than pharmacy students. Conclusion: While most medicine and pharmacy students had heard about AI programs, only a small proportion of the participants had used them in their medical study. In addition, attitudes and practice related to AI programs in their education differs between medicine and pharmacy students and between WBP and Jordan.