Background: The present study examined the effect of intermittent fasting (IF) on bone mineral content (BMC) and bone mineral density (BMD) and the markers of bone remodeling in a glucocorticoid-induced osteoporosis (GIO) rat model.Methods: Forty male rats were allocated to 4 groups (N=10 per group): control group of normal rats; control+IF group (normal rats subjected to IF for 16-18 hr daily for 90 days); dexamethasone (DEX) group: (DEX [0.5 mg i.p.] for 90 days); and DEX+IF group (DEX and IF for 90 days). By the end of the experiment, BMD and BMC in the right tibia were measured. Serum levels of the following were measured: glucose; insulin; triglycerides (TGs); total cholesterol; parathyroid hormone (PTH); osteoprotegerin (OPG); receptor activator of nuclear factor-κB (RANK); bone-resorbing cytokines, including bone deoxypyridinoline (DPD), N-terminal telopeptide of collagen type I (NTX-1), and tartrate-resistant acid phosphatase 5b (TRAP-5b); and bone-forming cytokines, including alkaline phosphatase (ALP) and osteocalcin (OC).Results: DEX administration for 90 days resulted in significantly increased serum levels of glucose, insulin, TGs, cholesterol, PTH, OPG, DPD, NTX-1, and TRAP-5b and significantly decreased BMD, BMC, and serum levels of RANK, OC, and ALP (all P<0.05). IF for 90 days significantly improved all these parameters (all P<0.05).Conclusions: IF corrected GIO in rats by inhibiting osteoclastogenesis and PTH secretion and stimulating osteoblast activity.

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PurposeExam blueprinting achieves valid assessment of students by defining exactly what is intended to be measured in which learning domain and defines what level of competence is required. We aimed to detect the impact of newly applied method for blueprinting that depends on total course credit hours and relate the results with item analysis reports for students’ performance.Participants and methodsA new method for blueprint construction was created. This method utilizes course credit hours for blueprint creation. Survey analysis was conducted for two groups of students (n=80); one utilized our new method (credit hours based) for blueprinting and the other used traditional method depending on exam duration and time for individual test items.ResultsResults of both methods were related to item analysis of students’ achievements. No significant difference was found between both groups in terms related to test difficulty, discrimination, or reliability indices. Both achieved close degrees of test validity and reliability measures.ConclusionWe concluded that our method using credit hours system for blueprinting could be considered easy and feasible and may eventually be utilized for blueprint construction and implementation.

BackgroundOval cells, specific liver progenitors, are activated in response to injury. The human umbilical cord blood (hUCB) is a possible source of transplantable hepatic progenitors and can be used in cases of severe liver injury. We detected the effect of hUCB stem cell transplantation on natural response of oval cells to injury.MethodsTwenty-four female albino rats were randomly divided into three groups: (A) control, (B) liver injury with hepatocyte block, and (C) hUCB transplanted group. Hepatocyte block was performed by administration of 2-acetylaminofluorene (2-AAF) for 12 days. CCL4 was administrated at day 5 from experiment start. Animals were sacrificed at 9 days post CCL4 administration, and samples were collected for biochemical and histopathological analysis. Oval cell response to injury was evaluated by the percentage of oval cells in the liver tissue and frequency of cells incorporated into new ducts.ResultsImmunohistochemical analysis of oval cell response to injury was performed. There was significant deviation in the hUCB-transplanted (4.9 ± 1.4) and liver injury groups (2.4 ± 0.9) as compared to control (0.89 ± 0.4) 9 days post injury. Detection of oval cell response was dependant on OV-6 immunoreactivity. For mere localization of cells with human origin, CD34 antihuman immunoreactivity was performed. There was no significant difference in endogenous OV-6 immunoreactivity following stem cell transplantation as compared to the liver injury group.ConclusionsIn vivo transplantation of cord blood stem cells (hUCB) does not interfere with natural oval cell response to liver injury.

Anatomy is taught in the early years of an undergraduate medical curriculum. The subject is volatile and of voluminous content, given the complex nature of the human body. Students frequently face learning constraints in these fledgling years of medical education, often resulting in a spiraling dwindling academic performance. Hence, there have been continued efforts directed at developing new curricula and incorporating new methods of teaching, learning and assessment that are aimed at logical learning and long-term retention of anatomical knowledge, which is a mainstay of all medical practice. In recent years, artificial intelligence (AI) has gained in popularity. AI uses machine learning models to store, compute, analyze and even augment huge amounts of data to be retrieved when needed, while simultaneously the machine itself can be programmed for deep learning, improving its own efficiency through complex neural networks. There are numerous specific benefits to incorporating AI in education, which include in-depth learning, storage of large electronic data, teaching from remote locations, engagement of fewer personnel in teaching, quick feedback from responders, innovative assessment methods and user-friendly alternatives. AI has long been a part of medical diagnostics and treatment planning. Extensive literature is available on uses of AI in clinical settings, e.g., in Radiology, but to the best of our knowledge there is a paucity of published data on AI used for teaching, learning and assessment in anatomy. In the present review, we highlight recent novel and advanced AI techniques such as Artificial Neural Networks (ANN), or more complex Convoluted Neural Networks (CNN) and Bayesian U-Net, which are used for teaching anatomy. We also address the main advantages and limitations of the use of AI in medical education and lessons learnt from AI application during the COVID-19 pandemic. In the future, studies with AI in anatomy education could be advantageous for both students to develop professional expertise and for instructors to develop improved teaching methods for this vast and complex subject, especially with the increasing paucity of cadavers in many medical schools. We also suggest some novel examples of how AI could be incorporated to deliver augmented reality experiences, especially with reference to complex regions in the human body, such as neural pathways in the brain, complex developmental processes in the embryo or in complicated miniature regions such as the middle and inner ear. AI can change the face of assessment techniques and broaden their dimensions to suit individual learners.