Purpose: This study aims to determine the siege and related factors of nurses working in psychiatric clinics. Method: This study was conducted as a related description design. The sample of the study consisted of 204 nurses working in psychiatric clinics. The data was collected using questionnaires generated by researchers from literature and workplace psychological abuse scales. Descriptive statistics (frequency and percentage) and chi-square independence test are used to determine whether there is a significant relationship between variables. Results: The conditions for more frequent siege behaviors are that nurses have graduate education, work at night, are dissatisfied with work methods and institutions, have been besieged before, and have an understanding of the number of legal persons and consulting services related to Go. Conclusion: The nursing service management department of the hospital should effectively organize the types of employment and develop strategies that can improve nurse satisfaction. It is believed that raising nurses’ awareness of siege will effectively reduce psychological violence in high-risk wards.

Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to its asymptomatic nature in early stages and consequent late diagnosis. The development of reliable, non-invasive biomarkers for early detection is critical to improving prognosis and survival rates. Recent advances in omics technologies and liquid biopsy have led to the identification of novel biomarkers, including circulating tumor DNA (ctDNA), microRNAs (miRNAs), exosomes, and protein signatures. These biomarkers show promise in enhancing diagnostic accuracy, risk stratification, and monitoring of disease progression. This review highlights the current landscape of emerging biomarkers for early lung cancer detection, evaluates their clinical utility, and discusses the challenges in their translation to routine clinical practice. Integration of these biomarkers with imaging and artificial intelligence-based diagnostic tools may offer a transformative approach for early lung cancer diagnosis.

Purpose: The primary motive of this study was to examine advantages of allometry scaling strategies for correct prediction of pharmacokinetics of Baricitinib in human from preclinical species. Baricitinib is basically Janus kinase (JAK) inhibitor used for the treatment of rheumatoid arthritis. Currently approved by FDA in combination with remdesivir for treatment of COVID-19 hospitalized patient. Methods: The literature published pharmacokinetic parameters (Cl and Vd) of preclinical species (Rat, Dog and monkey) were utilized for the allometry scaling of Baricitinib. The connection among the primary pharmacokinetic parameters [Volume of distribution (Vd) and clearance (Cl)] and body weight (BW) were studied across three preclinical species, we used the double logarithmic plots for prediction of the human pharmacokinetic parameters i.e. Cl and Vd with use of simple allometry and with additional correction factors for better prediction. The dose extrapolation of baricitinib was carried out by FDA guidelines. Results: By application of the allometric scaling methods and principles correlation was found to be satisfactory for the prediction of intravenous human Cl and Vd for baricitinib. The volume of distribution (Vd) predicted by simple allometry (65.3 L) was found to be in agreement with the reported value (75.5 L); clearance (Cl) prediction by simple allometry was found to be at least 1.06 -closer to the reported value (245 mL/min); CF were used to predict the clearance. Both brain weight (B.W) and maximum life span potential (MLP) predicted the Cl with 0.52- and 0.61 -fold difference. The application of monkey liver blood flow predicted Cl with 0.81 fold which was also in close agreement with reported value. The Cl prediction was also extrapolated using LBF (Liver blood flow) method and observed that the higher species (Dog and Monkey) have predicted Cl with better accuracy than rat. Conclusions: Overall, the simple allometry (SA), monkey liver blood flow (MLBF) and application of liver blood flow (LBF) methods showed excellent correlation with human. The time vs. plasma concentration simulated graph also showed the similar closeness with human profile. The inclusion of plasma protein binding factor didn’t improve the prediction accuracy. The FIH dose extrapolation were showed that PK guided approach and exponent for BSA based approach was found closer to actual human dose of 4.0 mg/Kg.

AI Publications is an open access peer review international journal to publish the article in the field of Agriculture, Horticulture, Food science, Rural Development, Environment and Health Research, Chemistry, Mathematics,Physics.

AI Publications is an open access peer review international journal to publish the article in the field of Agriculture, Horticulture, Food science, Rural Development, Environment and Health Research, Chemistry, Mathematics,Physics.