The concept of healing in medicine has been taking a new form where scientists and researchers are in pursuance of regenerative medicine. Until now, doctors have "reacted" to disease by treating the symptoms; however, modern medicine is transforming toward regeneration rather than reactive treatment, which is where stem cell therapy comes into the play-the concept of replacing damaged cells with brand new cells that perform the same function better. Stem cell treatment is currently being used to treat autoimmune, inflammatory, neurological, orthopedic, and traumatic disorders, with various research being undertaken for a wide range of diseases. It could also be the answer to anti-aging and a disease-free state. Despite the benefits, numerous errors could prevail in treating patients with stem cells. With the advancement of technology and research in the modern period, medicine is beginning to turn to artificial intelligence (AI) to address the complicated errors that could occur in regenerative medicine. For successful treatment, one must achieve precision and accuracy when analyzing healthy and productive stem cells that possess all the properties of a native cell. This review intends to discuss and study the application of AI in stem cell therapy and how it influences how medicine is practiced, thus creating a path to a regenerative future with negligible adverse effects. The following databases were used for a literature search: PubMed, Google Scholar, PubMed Central, and Institute of Electrical and Electronics Engineers (IEEE) Xplore. After a thorough analysis, studies were chosen, keeping in mind the inclusion and exclusion criteria set by the authors of this review, which comprised reports published within the last six years in the English language. The authors also made sure to include studies that sufficed the quality of each report assessed using appropriate quality appraisal tools, after which eight reports were found to be eligible and were included in this review. This research mainly revolves around machine learning, deep neural networks (DNN), and other subclasses of AI encompassed in these categories. While there are concerns and limitations in implementing various mediums of AI in stem cell therapy, the analysis of the eligible studies concluded that artificial intelligence provides significant benefits to the global healthcare ecosystem in numerous ways, such as determining the viability, functionality, biosafety, and bioefficacy of stem cells, as well as appropriate patient selection. Applying AI to this novelty brings out the precision, accuracy, and a revolution in regenerative medicine. In addition, stem cell therapy is not currently FDA approved (except for the blood-forming stem cells) and, to date, is considered experimental with no clear outline of risks and benefits. Given this limitation, studies are conducted regularly around the world in hopes for a concrete conclusion where technological advances such as AI could help in shaping the ...

Lung cancer has been the leading cause of cancer-associated deaths worldwide. While numerous reasons, including tobacco smoking, may lead to lung cancer, the purpose of this article was to explore the association between sarcoidosis, a multisystem granulomatous disorder, and lung neoplasms. A literature search was done on multiple databases with appropriate keywords, and the authors selected case reports where patients were diagnosed with sarcoidosis and lung cancer. These reports were analyzed in detail, and nine reports were included in this study. Each case was evaluated for the presenting symptoms, age, gender, and diagnostic procedures, including a follow-up analysis. After the evaluation, it can be concluded that sarcoidosis and lung cancer can occur simultaneously, despite being rare. Appropriate diagnostic procedures, including histopathological examination of the affected lymph nodes, showed either cancerous or non-cancerous cells (granulomas), thus altering the treatment on a case-by-case basis. Being aware of all possible associations between these two diseases could alter the clinical management, whether curative or palliative, and clinicians must rule out metastatic cancer in individuals with sarcoidosis-like clinical and radiographic features.

Delirium is defined by the DSM-5 as a fluctuating course of disturbance in attention, cognition, and awareness that develops over a short period without any pre-existing neurocognitive disorder. As people age, there is an increased risk of complications that may occur following a surgical procedure and one such acute complication is delirium. Studies are emerging to reduce the incidence of postoperative delirium, and one such preventive measures implemented in recent years include the administration of dexmedetomidine, a high selectivity α-2 adrenoceptor agonist. This study aims to review the efficacy of Dexmedetomidine in the prevention of postoperative delirium in randomized controlled trials in patients older than 18 years of age. The literature was explored in three online databases, namely, PubMed, Science Direct, and Scopus. Appropriate keywords and MesH terms were employed to scrutinize relevant articles that demonstrated the effects of dexmedetomidine in the prevention of postoperative delirium. The data was restricted to randomized controlled trials and clinical trials published from 2017 to 2021 in human patients older than >18 years of age undergoing non-cardiac-related procedures. The randomized clinical trials were critically assessed with the Cochrane risk of bias tool. We proceeded to screen 428 records with the assessment of the PRISMA chart and filtered out 420 papers to obtain a total of eight studies where we identified data such as sample size, types of surgeries in which the patients were involved, the delirium assessment tool, the plan of the administration of dexmedetomidine and the outcomes evaluated in each study. The Confusion Assessment Method (CAM) was the prevailing assessment tool used with the sole purpose to evaluate the incidence of postoperative delirium as the primary outcome, and assessment of inflammatory cytokines, sleep quality, and pain scales were considered as secondary outcomes. The dosage of dexmedetomidine varied among studies, and it displayed varying impacts on postoperative delirium and the secondary outcomes as well. Limitations include varying ages and ethnicities of the population. It was concluded that dexmedetomidine prevents the development of postoperative delirium in elderly patients undergoing non-cardiac surgical interventions by modulating important predisposing factors such as neuroinflammation, pain, and sleep quality. No funding was made for this study.

Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is a rare multisystem autoimmune condition that causes inflammation of small and medium-sized blood vessels and is more commonly seen in the geriatric population. ANCA-associated vasculitis (AAV) is typically characterized as necrotizing vasculitis and includes granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatosis with polyangiitis (EGPA). The mortality rate remains high, with especially cardiovascular disease, infections, and malignancies being the leading causes of death. Existing treatment options depend heavily on the use of glucocorticoids (GCs), often in combination with cyclophosphamide (CYC); however, as the multitude of adverse effects associated with these agents has increased, numerous studies are being conducted to reduce not only these harmful effects but also improve remission rates. Rituximab, avacopan, corticosteroids, including intravenous pulse methylprednisolone, plasma exchange, and immunological targeting are among the emerging treatments. The purpose of this review is to emphasize the pathogenesis and traditional treatment modalities and give insights into the recent advances in managing this disorder in an attempt to spare the adverse effects of conventional therapies while achieving better remission rates with combination therapies as well. The authors explored multiple databases, employing appropriate keywords, satisfying the quality appraisal, after which a total of 14 reports were included in this review. Upon overall analysis, it can be concluded that rituximab and CYC, when used in combination, provided a safer alternative to GCs while exhibiting equal, if not superior, effectiveness and results, thus, paving the way for additional in-depth research in a larger population of interest.

Currently, breast cancer is one of the insidious malignancies that evolves silently, eventually leading to mortality, and has been recorded as one of the leading causes of cancer-related deaths around the globe. It is evident from numerous research studies that the etiology of breast cancer is multifaceted, both on an individual and environmental level. Insulin resistance, commonly known as metabolic syndrome, has been related to a poor breast cancer prognosis. There is presently limited data on the clinical features of insulinresistant breast cancer patients. The purpose of this study is to examine the association between metabolic syndrome and its components impacting the risk and the prognosis of breast cancer, including the clinicopathological variables in patients with newly diagnosed breast cancer with and without already established diabetes. The authors extracted data from PubMed, Google Scholar, Science Direct, and Embase, intending to study the connections between these two entities. Studies from worldwide were selected to analyze the association between breast cancer and insulin resistance, including mammogram screening practices in a region-wise manner. The ultimate objective is to raise awareness of this association among practitioners worldwide. After analyzing several reports that included observational studies, it is to be concluded that insulin resistance impacts breast cancer both in regards to increasing the risk as well as affecting the survival outcome.