Formulation and Bioequivalence of Two Valsartan Tablets After a Single Oral Administration

The aim of this study is to assess the quality of Valzan® tablet (160 mg, valsartan immediate release test formulation) by comparing its pharmacokinetic parameters with Diovan® tablet (160 mg, valsartan reference formulation). Valzan® tablets were prepared according to a dry granulation method (roll compaction). To assess the bioequivalence of Valzan® tablets a randomized, two-way, crossover, bioequivalence study was performed in 24 healthy male volunteers. The selected volunteers were divided into two groups of 12 subjects. One group was treated with the reference formulation (Diovan®) and the other one with the generic Valzan®, with a cross-over after the drug washout period of 14 days. Blood samples were collected at fixed time intervals and valsartan concentrations were determined by a validated HPLC assay method. The pharmacokinetic parameters AUC0–48, AUC0–∞, Cmax, Tmax, Ke and T1/2 were determined for both the tablets and were compared statistically to evaluate the bioequivalence between the two brands of valsartan, using the statistical model recommended by the FDA. The analysis of variance (ANOVA) did not show any significant difference between the two formulations and 90% confidence intervals (CI) fell within the acceptable range for bioequivalence. Based on this statistical evaluation it was concluded that the test tablets (Valzan®) is well formulated, since it exhibits pharmacokinetic profile comparable to the reference brand Diovan®

Exploring Knowledge, Attitudes, and Practices Towards Artificial Intelligence among Health Professions’ Students in Jordan

The integration of Artificial Intelligence (AI) in medical education and practice is a significant development. This study examined the Knowledge, Attitudes, and Practices (KAP) of health professions' students in Jordan concerning AI, providing insights into their preparedness and perceptions. An online questionnaire was distributed to 483 Jordanian health professions' students via social media. Demographic data, AI-related KAP, and barriers were collected. Quantile regression models analyzed associations between variables and KAP scores. Moderate AI knowledge was observed among participants, with specific understanding of data requirements and barriers. Attitudes varied, combining skepticism about AI replacing human teachers with recognition of its value. While AI tools were used for specific tasks, broader integration in medical education and practice was limited. Barriers included lack of knowledge, access, time constraints, and curriculum gaps. This study highlights the need to enhance medical education with AI topics and address barriers. Students need to be better prepared for AI integration, in order to enable medical education to harness AI's potential for improved patient care and training. [Abstract copyright: © 2023. The Author(s).

Genome-wide association mapping in a diverse spring barley collection reveals the presence of QTL hotspots and candidate genes for root and shoot architecture traits at seedling stage

Figure S1. Examples of scanned root images from individual plants. Figure S2. Concatenated split network tree for the collection of 233 accessions based on 6019 SNP markers. Figure S3. LD pattern along the individual chromosomes of barley. Figure S4. Schematic representation of the eight re-sequenced candidate genes models. (DOCX 3427 kb

Stone-walled terraces restoration: conserving biodiversity and promoting economic functions of farmlands in Lebanon

Dry stone-walled terraces are peculiar features of Mediterranean farmland, representing typical examples of social-ecological systems combining ecological functionality and ecosystem services provision. In the Shouf Biosphere Reserve (Lebanon) a program of restoration of abandoned terraces applying Forest Landscape Restoration (FLR) principles is ongoing from 2016, combined with biodiversity monitoring activities. This study illustrates preliminary results of the plant monitoring, with the aim to (1) draft a checklist of the plants found in the terraces, (2) compare plant diversity and evaluate consistency of species assemblages observed among 3 different terrace managements (abandoned, restored and intensively-cultivated) and (3) compare ecological and ecosystem service value of the plant communities in the 3 types of terraces. Overall, 332 species were observed, with significantly higher diversity found in abandoned and restored terraces compared to intensively farmed terraces. Similarly, species assemblages of restored terraces were closely related to abandoned and distantly related to intensively-managed terraces. According to the study, restored terraces provide the same ecological value and ecosystem services functions as abandoned terraces, significantly higher than intensively-managed terraces. This study showcases the effectiveness of FLR programmes in restoring economic and social functions of terraced Mediterranean farmland while maintaining ecological functionality

Hospital adoption of antimicrobial stewardship programmes in Gulf Cooperation Council countries: A review of existing evidence

© 2018 International Society for Chemotherapy of Infection and Cancer Antimicrobial resistance is increasing at an alarming rate in the Gulf Cooperation Council (GCC) owing to the overuse and misuse of antimicrobials. Novel and rare multidrug-resistant strains can spread globally since the region is host to the largest expatriate population in the world as well as a pilgrimage destination for more than 4 million people annually. Adoption of antimicrobial stewardship programmes (ASPs) could improve the use of antimicrobials and reduce antimicrobial resistance in the region. However, despite the established benefits of these interventions, little is known about the level of their adoption in the region and the impact of these programmes on antimicrobial use and resistance. This study aimed to review existing evidence on the level of adoption of ASPs, the facilitators and barriers to their adoption, and outcomes of their adoption in GCC hospitals

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Automatic Arabic Domain-Relevant Term Extraction

Term extraction from text corpus is an important step in knowledge acquisition and it is the first step in many Natural Language Processing (NLP) methods and computer lingual systems. In Arabic language there are some works in the field of term extraction and few of them try to extract domain-relevant terms. In this research a model for automatic Arabic domain-relevant term extraction from text corpus was proposed. The proposed model uses a hybrid approach composed of linguistic and statistical methods to extract terms relevant to specific domains depending on prevalence and tendency term ranking mechanism. In order to realize the proposed model a multi domain corpus separated into 10 domains (Economic, History, Education and family, Religious and Fatwa's, Sport, Health, Astronomy, Low, Stories, and Cooking recipes) was used. Then this corpus preprocessed by removing non Arabic letters, punctuations, diacritics, and stop words. Then a candidate terms vector was extracted using a sliding window with variant length dropping the windows that contain a stop word. Candidate terms have been ranked using Termhood method as a statistical method that measures the distributional behavior of candidate terms within the domain and across the rest of the corpus. Then Candidate terms have been distributed over the domains depending on the higher rank result for the extracted terms constructing a domain term matrix. This matrix has been used in a simple classifier that classifies the testing corpus. The final step gives us a confusion matrix that indicates that the domain term matrix worked as a best classifier achieving an accuracy rate of 100% for some domains and very good in others. The total accuracy of the classifier was 95%. This is a highly accurate classifier

Application of Adobe® Photoshop® CC 2018 for identifying color laser printer source of Xerox® brand

Abstract Background In a field of digital forensic science, we have struggled to prove and keep any evidence in its most original form. The seized source of color laser printers in forgery crimes has been still an awkward issue today in digital forensic labs for identification. Till now no any scientific method has reported at all over the world that could be applied to make a success in an investigation for identifying the source of color laser printers with accuracy ratio 100%. Method We have explored an advanced security feature that has embedded in the color laser printouts of Xerox® brand. Adobe® Photoshop® CC 2018 has used as an indirect and nondestructive tool for our work. Results In this study, we could detect the hidden information (steganalysis) embedded in the color laser printouts of Xerox® brand candidate. Therefore, we could extract the clear precise machine identification code pattern corresponding to each color laser printer of Xerox® brand selected. Conclusion Via Adobe® Photoshop® CC 2018, we could successfully track all active security features characteristic of the color laser printers of Xerox® brand. Moreover, we could detect the identity and uniqueness of each color laser printer which had studied with an accuracy ratio reached to a hundred percent