The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis.

BACKGROUND AND OBJECTIVES: This review aims to delve into the role of artificial intelligence in medicine. Ulcerative colitis (UC) is a chronic, inflammatory bowel disease (IBD) characterized by superficial mucosal inflammation, rectal bleeding, diarrhoea and abdominal pain. By identifying the challenges inherent in UC diagnosis, we seek to highlight the potential impact of artificial intelligence on enhancing both diagnosis and treatment methodologies for this condition. METHOD: A targeted, non-systematic review of literature relating to ulcerative colitis was undertaken. The PubMed and Scopus databases were searched to categorize a well-rounded understanding of the field of artificial intelligence and its developing role in the diagnosis and treatment of ulcerative colitis. Articles that were thought to be relevant were included. This paper only included articles published in English. RESULTS: Artificial intelligence (AI) refers to computer algorithms capable of learning, problem solving and decision-making. Throughout our review, we highlighted the role and importance of artificial intelligence in modern medicine, emphasizing its role in diagnosis through AI-assisted endoscopies and histology analysis and its enhancements in the treatment of ulcerative colitis. Despite these advances, AI is still hindered due to its current lack of adaptability to real-world scenarios and its difficulty in widespread data availability, which hinders the growth of AI-led data analysis. CONCLUSIONS: When considering the potential of artificial intelligence, its ability to enhance patient care from a diagnostic and therapeutic perspective shows signs of promise. For the true utilization of artificial intelligence, some roadblocks must be addressed. The datasets available to AI may not truly reflect the real-world, which would prevent its impact in all clinical scenarios when dealing with a spectrum of patients with different backgrounds and presenting factors. Considering this, the shift in medical diagnostics and therapeutics is coinciding with evolving technology. With a continuous advancement in artificial intelligence programming and a perpetual surge in patient datasets, these networks can be further enhanced and supplemented with a greater cohort, enabling better outcomes and prediction models for the future of modern medicine.

Ecdysterone and Turkesterone-Compounds with Prominent Potential in Sport and Healthy Nutrition.

The naturally occurring compounds ecdysterone and turkesterone, which are present in plants, including Rhaponticum carthamoides Willd. (Iljin), Spinacia oleracea L., Chenopodium quinoa Willd., and Ajuga turkestanica (Regel) Briq, are widely recognized due to their possible advantages for both general health and athletic performance. The current review investigates the beneficial biological effects of ecdysterone and turkesterone in nutrition, highlighting their roles not only in enhancing athletic performance but also in the management of various health problems. Plant-based diets, associated with various health benefits and environmental sustainability, often include sources rich in phytoecdysteroids. However, the therapeutic potential of phytoecdysteroid-rich extracts extends beyond sports nutrition, with promising applications in treating chronic fatigue, cardiovascular diseases, and neurodegenerative disorders.

Development and validation of a high-performance thin-layer chromatography method for detection of sibutramine in dietary supplements.

INTRODUCTION: In the period between 1997 and 2010, sibutramine-containing drugs were widely prescribed for obesity and over-weight management. Due to safety concerns, in 2010 all medicines containing sibutramine were urgently withdrawn from the USA and European pharmaceutical market. Although sibutramine is no longer available in pharmaceutical products, there have been numerous reports of mislabeled weight-loss dietary supplements containing sibutramine.

Coexistence of ankylosing spondylitis and Behçet's disease: Successful treatment with upadacitinib.

BACKGROUND: Ankylosing spondylitis (AS) and Behçet's disease (BD) are distinct inflammatory disorders, but their coexistence is a rare clinical entity. This case sheds light on managing this complex scenario with Janus kinase (JAK) inhibitors. CASE PRESENTATION: A 42-year-old woman presented with a decade-long history of lower back pain, nocturnal spinal discomfort, recurrent eye issues, oral and genital ulcers, hearing loss, pus formation in the left eye, and abdominal pain. Multidisciplinary consultations and diagnostic tests confirmed AS (HLA-B27 positivity and sacroiliitis) and BD (HLA-B51). Elevated acute-phase markers were observed. CONCLUSION: This case fulfills diagnostic criteria for both AS and BD, emphasizing their coexistence. Notably, treatment with upadacitinib exhibited promising efficacy, underscoring its potential as a therapeutic option in patients with contraindications for conventional treatments. Our findings illuminate the intricate management of patients presenting with these two diverse systemic conditions and advocate for further exploration of JAK inhibitors in similar cases.

Rare case of enteric type of urachal adenocarcinoma: A case report.

Urachal adenocarcinomas, constituting 10 % of bladder adenocarcinomas, pose a significant challenge with limited literature. A 43-year-old male presented with haematuria and abdominal pain, leading to surgical intervention for a 13 cm pelvic tumor. Histopathology identified an intestinal-type primary urachal adenocarcinoma, staged as IIIA, no recurrence on follow-up. Early detection is crucial for improved outcomes in these rare malignancies. While surgery remains the primary treatment, outcomes vary, emphasizing the need for research on standardized protocols. Enhanced awareness and interdisciplinary collaboration are vital for effective management. Comprehensive guidelines are essential for optimizing patient prognoses in urachal adenocarcinomas.

Aerobic Microbiological Spectrum and Antibiotic Resistance in Children Operated for Anorectal Abscesses.

(1) Background: Anorectal abscesses are a relatively rare pathology in childhood. Most often, male children under 1 year of age are affected. The importance of microbiological examination for the diagnosis and treatment of such patients remains debatable among surgeons, resulting in scarce data being available in the literature. We aimed to identify the aerobic microbiological spectrum and antibiotic resistance of isolates in children undergoing operation to treat anorectal abscesses. (2) Methods: We performed a case series of 102 children diagnosed and operated for anorectal abscesses over a period of 10 years (2010-2019). Purulent wound exudate was used for microbiological evaluation, which was subsequently cultured on 5% sheep-blood agar and eosin-methylene blue agar. For microbiological identification, conventional biochemical tests and semi-automated (API 20, bioMerieux, Marcy-l'Étoile, France) tests were used, as well as automated systems (Vitek-2 Compact, bioMerieux, France). Antimicrobial susceptibility testing was performed by the disk diffusion method of Bauer-Kirby and by determining the minimal inhibitory concentrations for glycopeptides. The results were interpreted according to the EUCAST standard for the corresponding year. (3) Results: Microbiological testing in children operated for anorectal abscesses mainly identified the gut commensals that normally reside in the rectal mucosa. Monocultures were found in just over half of the cases. Escherichia coli, Klebsiella pneumoniae complex, and Proteus mirabilis were the most frequently isolated. In addition, Staphylococcus aureus was found in 7% of patients. In Gram-negative bacteria, antibiotic resistance was most often observed in penicillins, cephalosporins, sulfonamides, and fluoroquinolones. (4) Conclusions: The increasing rates of antimicrobial resistance impose the need for the local monitoring of circulating commensal bacteria associated with anorectal abscesses in children to guide antibiotic therapy when indicated.

Artificial Intelligence in the Diagnosis of Colorectal Cancer: A Literature Review.

BACKGROUND: The aim of this review is to explore the role of artificial intelligence in the diagnosis of colorectal cancer, how it impacts CRC morbidity and mortality, and why its role in clinical medicine is limited. METHODS: A targeted, non-systematic review of the published literature relating to colorectal cancer diagnosis was performed with PubMed databases that were scouted to help provide a more defined understanding of the recent advances regarding artificial intelligence and their impact on colorectal-related morbidity and mortality. Articles were included if deemed relevant and including information associated with the keywords. RESULTS: The advancements in artificial intelligence have been significant in facilitating an earlier diagnosis of CRC. In this review, we focused on evaluating genomic biomarkers, the integration of instruments with artificial intelligence, MR and hyperspectral imaging, and the architecture of neural networks. We found that these neural networks seem practical and yield positive results in initial testing. Furthermore, we explored the use of deep-learning-based majority voting methods, such as bag of words and PAHLI, in improving diagnostic accuracy in colorectal cancer detection. Alongside this, the autonomous and expansive learning ability of artificial intelligence, coupled with its ability to extract increasingly complex features from images or videos without human reliance, highlight its impact in the diagnostic sector. Despite this, as most of the research involves a small sample of patients, a diversification of patient data is needed to enhance cohort stratification for a more sensitive and specific neural model. We also examined the successful application of artificial intelligence in predicting microsatellite instability, showcasing its potential in stratifying patients for targeted therapies. CONCLUSIONS: Since its commencement in colorectal cancer, artificial intelligence has revealed a multitude of functionalities and augmentations in the diagnostic sector of CRC. Given its early implementation, its clinical application remains a fair way away, but with steady research dedicated to improving neural architecture and expanding its applicational range, there is hope that these advanced neural software could directly impact the early diagnosis of CRC. The true promise of artificial intelligence, extending beyond the medical sector, lies in its potential to significantly influence the future landscape of CRC's morbidity and mortality.

Comprehensive Exploration of Antinuclear Antibodies (ANAs): Unveiling Clinical Significance, Associations with Cancer, and the Nuances of Differential Diagnosis in Positive ANA Patients.

This comprehensive review delves into the complex realm of antinuclear antibodies (ANAs), expanding beyond their traditional involvement in autoimmune rheumatic disorders. By digging into historical changes, diagnostic complexity, and clinical significance, the debate reveals the shifting relationships between ANAs, particularly with cancer. Specialized studies provide practical insights on ANA testing processes, standardization, and upcoming challenges. Examining prevalence trends in the United States provides a time dimension to ANA dynamics, linking autoimmune and oncological considerations. The debate delves into the complexity of lupus erythematosus, emphasizing ANAs' diverse presentations and their potential as flexible diagnostic and prognostic indicators. The complex relationship between ANAs and cancer is highlighted, demonstrating their potential as early markers or indicators of malignancies. Looking ahead, this synthesis anticipates advances in personalized medicine and collaborative research, putting ANAs at the forefront of advanced diagnostics and treatments for autoimmune disorders and cancer. This synthesis envisions a future for ANA research in which these antibodies play a critical role in promoting personalized treatment, enhancing diagnostics, and fostering collaborative initiatives that cross traditional boundaries. As ANAs grow more prominent at the junction of autoimmune illnesses and cancer, this synthesis lays the path for further research and novel advances in understanding, diagnosing, and treating complicated medical conditions.