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Introduction: Investigating CD68+ positive cells in the synovial tissue is crucial for understanding the pathogenesis of psoriatic arthritis (PsA) and developing targeted treatment strategies. The role of CD68+ positive cells in the synovial tissue of patients with PsA for joint destruction has not been fully studied., Objective: The objective of the study was to examine the presence of CD68+ cells in the synovial tissue of patients with PsA, particularly those with high inflammatory activity., Methods: Synovial tissue samples were collected during knee joint replacement surgeries from patients with PsA (16 patients) and gonarthrosis (25 patients). Immunohistochemical methods were employed to detect CD68+ cell expression in the tissue samples. The results were analyzed by histologists, and the staining intensity and percentage of positively stained cells were evaluated. The data were then divided into three groups for statistical analysis: negative, weakly positive, and strongly positive histological samples. Routine indices for disease activity, VAS, DAPSA, PASDAI, and mCPDAI were used to assess PsA activity in all patients and to assess correlations with CD68+ positive cells in the synovial tissue. Statistical analysis was performed using SPSS version 26.0 (SPSS Inc., Chicago, IL, USA)., Results: The expression of CD68+ positive cells was significantly higher in patients with PsA compared to those with activated gonarthrosis (p < 0.001). The indices for disease activity, VAS, DAPSA, PASDAI, mCPDAI, and mCPDAI showed a significant positive relationship with the expression of CD68 + cells on synovial tissue in patients with PsA (p < 0.01) Conclusion: The findings of the study confirm the increased numbers of CD68+ cells in PsA vs. gonathrosis synovium. This suggests the need to explore therapeutic approaches aimed at suppressing or blocking CD68+ cells to potentially mitigate joint damage., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Breast cancer is the most prevalent cancer worldwide, affecting both low- and middle-income countries, with a growing number of cases. In 2024, about 310,720 women in the U.S. are projected to receive an invasive breast cancer diagnosis, alongside 56,500 cases of ductal carcinoma in situ (DCIS). Breast cancer occurs in every country of the world in women at any age after puberty but with increasing rates in later life. About 65% of women with the BRCA1 and 45% with the BRCA2 gene variants develop breast cancer by age 70. While these genes account for 5% of breast cancers, their prevalence is higher in certain populations. Advances in early detection, personalised medicine, and AI-driven diagnostics are improving outcomes by enabling a more precise analysis, reducing recurrence, and minimising treatment side effects. Our paper aims to explore the vast applications of artificial intelligence within the diagnosis and treatment of breast cancer and how these advancements can contribute to elevating patient care as well as discussing the potential drawbacks of such integrations into modern medicine. We structured our paper as a non-systematic review and utilised Google Scholar and PubMed databases to review literature regarding the incorporation of AI in the diagnosis and treatment of non-palpable breast masses. AI is revolutionising breast cancer management by enhancing imaging, pathology, and personalised treatment. In imaging, AI can improve the detection of cancer in mammography, MRIs, and ultrasounds, rivalling expert radiologists in accuracy. In pathology, AI enhances biomarker detection, improving HER2 and Ki67 assessments. Personalised medicine benefits from AI's predictive power, aiding risk stratification and treatment response. AI also shows promise in triple-negative breast cancer management, offering better prognosis and subtype classification. However, challenges include data variability, ethical concerns, and real-world validation. Despite limitations, AI integration offers significant potential in improving breast cancer diagnosis, prognosis, and treatment outcomes.

Aim: This study aimed at identifying factors that worsen the prognosis of diabetic foot, one of the most common complications seen in patients with diabetes., (This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: Hydatidosis is one of the most critical parasitic zoonotic diseases worldwide. Lungs are the second most common site of the disease., (This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The development of the Gleason grading system has proven to be an irreplaceable tool in prostate cancer diagnostics within urology. Despite the advancements and developments in diagnostics, there remains a discrepancy in the grading process among even the most experienced pathologists. AI algorithms have demonstrated potential in detecting cancer and assigning Gleason grades, offering a solution to the issue of significant variability among pathologists' evaluations. Our paper explores the evolving role of AI in prostate cancer histopathology, with a key focus on outcomes and the reliability of various AI algorithms for Gleason pattern assessment. We conducted a non-systematic review of the published literature to examine the role of artificial intelligence in Gleason pattern diagnostics. The PubMed and Google Scholar databases were searched to gather pertinent information about recent advancements in artificial intelligence and their impact on Gleason patterns. We found that AI algorithms are increasingly being used to identify Gleason patterns in prostate cancer, with recent studies showing promising advancements that surpass traditional diagnostic methods. These findings highlight AI's potential to be integrated into clinical practice, enhancing pathologists' workflows and improving patient outcomes. The inter-observer variability in Gleason grading has seen an improvement in efficiency with the implementation of AI. Pathologists using AI have reported successful outcomes, demonstrating its effectiveness as a supplementary tool. While some refinements are still needed before AI can be fully implemented in clinical practice, its positive impact is anticipated soon.

Introduction: Osteoarthritis is a prevalent degenerative joint disorder associated with pain and functional impairment. Curcumin, a natural anti-inflammatory compound, has garnered attention for its potential therapeutic benefits in osteoarthritis management., (This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Bouveret's syndrome (BS) represents an exceedingly rare clinical entity characterized by gastric outlet obstruction induced by a gallstone passing through a cholecystoduodenal, cholecystogastric or choledochoduodenal fistula and impacting in the duodenum or pylorus. Endoscopy is the preferred first-line therapy. It has a favorable safety profile, but requires high level of expertise to achieve stone clearance., (This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The ongoing growth of artificial intelligence (AI) involves virtually every aspect of oncologic care in medicine. Although AI is in its infancy, it has shown great promise in the diagnosis of oncologic urological conditions. This paper aims to explore the expanding role of artificial intelligence in the histopathological diagnosis in urological oncology. We conducted a focused review of the literature on AI in urological oncology, searching PubMed and Google Scholar for recent advancements in histopathological diagnosis using AI. Various keyword combinations were used to find relevant sources published before April 2nd, 2024. We approached this article by focusing on the impact of AI on common urological malignancies by incorporating the use of different AI algorithms. We targeted the capabilities of AI's potential in aiding urologists and pathologists in histological cancer diagnosis. Promising results suggest AI can enhance diagnosis and personalized patient care, yet further refinements are needed before widespread hospital adoption. AI is transforming urological oncology by improving histopathological diagnosis and patient care. This review highlights AI's advancements in diagnosing prostate, renal cell, and bladder cancer. It is anticipated that as AI becomes more integrated into clinical practice, it will have a greater influence on diagnosis and improve patient outcomes., (This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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.

Background: A xanthoma is a rare bone condition consisting of a predominant collection of lipid-rich, foamy histiocytes. The central xanthoma of the jaws is a unique benign tumor., Case Report: A 15-year-old Caucasian male has been presented to our department. He had radiological changes in the area of the left mandibular angle, with an area of diffuse osteolysis of 3.0 cm by 2.0 cm. Computed tomography reveals an area of diffuse osteolysis that starts from the distal root of the lower second molar and reaches the ascending process. A bone biopsy was performed, which revealed a benign proliferative process composed of histiocytic cells involving and infiltrating trabecular bone in a background of loose fibrous connective tissue devoid of any other significant inflammatory infiltrate. The size of the formation was 2.9 cm by 2.0 cm. Immunohistochemical staining for CD68 was strongly positive and negative for S-100 and CD1a. From routine blood tests, cholesterol, triglycerides, and blood sugar are within normal values, which excludes systemic metabolic disease. Subsequent to the surgical intervention, the patient underwent postoperative assessments at intervals of 14, 30, 60 days, and a year later, revealing the absence of any discernible complications during the aforementioned observation periods., Conclusion: The diagnosis of primary xanthoma of the mandible is rare and can often be confused with other histiocytic lesions. A differential diagnosis should be made with nonossifying fibroma and Langerhans cell histiocytosis, as in our case. In these cases, immunohistochemistry with CD 68, S-100, and CD1a, as well as blood parameters, are crucial for the diagnosis., (© 2024. The Author(s).)

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.

Aim: This study aimed to construct prognostic mathematical models utilizing multifactorial regression analysis to assess the risk of developing drug-induced neutralizing antibodies in patients with rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis treated with tumor necrosis factor alpha blockers., (This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Tanacetum parthenium L. (Asteraceae) is a perennial herbaceous plant with a long-standing historical use in traditional medicine. Recently Tanacetum parthenium L. essential oil has been associated with a promising potential for future applications in the pharmaceutical industry, in the cosmetics industry, and in agriculture. Investigations on the essential oil (EO) have indicated antimicrobial, antioxidant, and repellent activity. The present study aimed to evaluate the chemical composition of Bulgarian T. parthenium essential oil from two different regions, to compare the results to those reported previously in the literature, and to point out some of its future applications. The essential oils of the air-dried flowering aerial parts were obtained by hydrodistillation using a Clevenger-type apparatus. The chemical composition was evaluated using gas chromatography with mass spectrometry (GC-MS). It was established that the oxygenated monoterpenes were the predominant terpene class, followed by the monoterpene hydrocarbons. Significant qualitative and quantitative differences between both samples were revealed. Camphor (50.90%), camphene (16.12%), and bornyl acetate (6.05%) were the major constituents in the feverfew EO from the western Rhodope Mountains, while in the EO from the central Balkan mountains camphor (45.54%), trans-chrysanthenyl acetate (13.87%), and camphene (13.03%) were the most abundant components.

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., (© 2024 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.)

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.

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.