Search Results (23)

Seronegative sicca syndrome encompasses patients who present with xerostomia and/or keratoconjunctivitis sicca but lack anti-SSA/SSB antibodies and do not fulfill current classification criteria for primary Sjögren’s syndrome (pSS). Despite symptom overlap with pSS, these individuals remain diagnostically and therapeutically unclassified. This review studies the clinical, immunological, and pathological spectrum of seronegative sicca, highlighting its heterogeneity and the limitations of antibody-centric diagnostic frameworks. Histopathologic findings in some seronegative patients—including focal lymphocytic sialadenitis—mirror those seen in pSS, suggesting underlying immune-mediated glandular damage. In others, nonspecific or normal biopsy findings suggest non-immune mechanisms. New evidence of immune activity, such as elevated cytokines (BAFF, IFN-α), and novel autoantibodies (SP-1, CA-VI), further supports the concept of subclinical autoimmunity in a subset of these patients. Clinically, they often face significant burden, including dryness, fatigue, and pain, yet remain excluded from most research cohorts, therapeutic trials, and clinical guidelines. Their management is often individualized, relying on symptomatic therapies rather than immunomodulatory agents. The lack of validated diagnostic criteria and prognostic markers compounds the uncertainty surrounding disease evolution, as some patients may later seroconvert or develop systemic features. To address these gaps, a paradigm shift is needed—one that embraces the spectrum of sicca syndromes, incorporates advanced immunophenotyping, and allows inclusion of seronegative patients in research and care algorithms. Full article

Background: Cervical dystonia (CD) is a chronic neurological disorder characterized by involuntary neck muscle contractions, leading to abnormal head postures, pain, and functional impairment. Botulinum toxin type A (BoNT-A) remains the treatment of choice, but its efficacy is highly dependent on injection accuracy. Various techniques, including palpation-guided, ultrasound-guided, and electromyography-guided (EMG), have been developed to optimize delivery, each with distinct advantages and limitations. Methods: A systematic search of PubMed and Scopus was conducted up until 30 December 2024, using defined keywords related to BoNT-A, CD, and injection techniques. Studies were included if they reported clinical outcomes of BoNT-A injection methods in adult CD patients. Data on efficacy, safety, accuracy, and muscle targeting were extracted and synthesized. Results: Seven studies comprising 239 patients were included: two randomized controlled trials, one retrospective study, one cohort study, one systematic review, one literature review, and one cadaveric study. The most common CD subtype was torticollis/torticaput (49.79%). Frequently targeted muscles included the trapezius (56.9%), levator scapulae (51.7%), and splenius capitis (48.3%). Ultrasound guidance consistently demonstrated superior injection accuracy and reduced adverse effects due to real-time anatomical visualization. EMG-guided techniques showed advantages in identifying dystonic muscles, especially when anatomy was unclear. In contrast, palpation-guided injections were less accurate and suitable only for superficial muscles. Dosing varied by product, with mean doses of 117–118 units for onabotulinumtoxinA and incobotulinumtoxinA, and 405 units for abobotulinumtoxinA. Adverse events were generally mild, including local discomfort, dysphagia, and transient muscle weakness. Conclusions: Ultrasound- and EMG-guided injections enhance the precision, safety, and efficacy of BoNT-A therapy for CD compared to anatomy-guided techniques. While ultrasound guidance improves anatomical accuracy, EMG remains valuable for functionally identifying dystonic muscles. Integration of both may offer optimal outcomes. However, further high-quality, standardized trials are needed to definitively establish best practices. Full article

Introduction: Alkaptonuria is an autosomal-recessive disorder affecting the metabolism of tyrosine and phenylalanine which results in accumulation of homogentisic acid in connective tissues. The joints are most commonly affected, while the most common cardiac damage is aortic valve stenosis. The treatment focuses on reducing the symptoms. Aortic stenosis in alkaptonuria is treated with surgical aortic valve replacement; however, transcatheter aortic valve implantation procedures are increasing in number with excellent outcomes. Case presentation: We report a case of a 67-year-old female with chronic back pain and large-joint arthralgia, who was recently diagnosed with alkaptonuria. She reported a long-known heart murmur and intermittent dark-brown staining of her underwear since childhood. Bilateral dark-brown pigmentation of the sclera and both ear cartilages were visualised. ECG confirmed atrial fibrillation and left ventricular hypertrophy. Cardiac ultrasonography showed severe aortic stenosis, reduced global longitudinal strain and preserved ejection fraction. According to the latest recommendations, the choice between surgical and transcatheter intervention must be based upon careful evaluation of clinical, anatomical and procedural factors by the Heart Team, weighing the risks and benefits of each approach for an individual patient. The advantages and disadvantages of both procedures were explained to the patient. It was emphasised that the genetic disease present has no etiopathogenetic definitive treatment and the pigment may continue to deposit on the biological valve (in transcatheter aortic valve implantation) and less likely on the mechanical valve prosthesis (in Surgical Aortic Valve Replacement), highlighting the fact that in the literature worldwide, there are only single reports of ochronosis and severe aortic stenosis. At this stage of knowledge, it is difficult to give the patient clear guarantees when choosing a methodology for performing a valve correction. Along with the standard therapy the patient underwent transcatheter aortic valve implantation with Boston Scientific prosthesis with a very good post-procedural outcome. Conclusions: There is scarce information on transcatheter aortic valve implantation success rate in patients with alkaptonuria. In the population, transcatheter aortic valve implantation outcome is generally good; however, the individual success in alkaptonuria patients depends on the severity of their heart valve damage and overall health. Full article

Background: Advancements in artificial intelligence (AI) diagnostics for renal cell carcinoma (RCC) provide valuable information for classification and subtyping, which improve treatment options and patient care. RCC diagnoses are most commonly incidental due to a lack of specific characterizations of subtypes, often leading to overtreatment. Accurate diagnosis also allows for personalized patient management. Different diagnostic methods, such as histopathology, multi-omics, imaging, and perioperative diagnostics, show a lot of promise for AI. Objective: This literature review focuses on developments in RCC diagnostics and their outcomes, efficacy, and accuracy in classification. Method: We conducted a non-systematic review of the published literature to explore advancements in the diagnostics of RCC. The PubMed and Google Scholar databases were reviewed to extract relevant information. The literature shows that AI can help distinguish RCC from other kidney lesions and track tumor growth. The integration of radiomic features with clinical metadata further enhances the results. This enables clinicians to implement personalized treatment plans. The application of artificial intelligence in perioperative diagnostics enhances decision-making, improves patient safety, mitigates intraoperative complications, and accelerates recovery. Alongside the advancements in AI-assisted diagnostics, there are problems that need to be addressed, including selection bias, demand for larger and diverse datasets, and reliable validation. Conclusions: Despite the challenges, using AI to help with RCC diagnosis could lead to better patient outcomes, a new standard of care for RCC patients, and more personalized cancer management for each patient. Full article

Objectives: The aim of this study was to establish the etiology of uveitis and to examine its relationship with anatomical localization, age, and gender. Methods: A prospective study on patients with uveitis was conducted over a 13-year period at the Department of Ophthalmology, University Hospital “St. George”, Plovdiv, Bulgaria. Each case was diagnosed based on a comprehensive eye examination, a review of the systems, and additional laboratory and specialized examination methods. Patients were categorized into four groups based on the location of inflammation: anterior uveitis, intermediate uveitis, posterior uveitis, and panuveitis. Results: A total of 606 patients with uveitis were included in the study. The mean age of the study group was 46.5 ± 18.6 years. There was no statistically significant difference in gender distribution (p = 0.329). Anterior uveitis was the most dominant anatomical localization (p < 0.001). Cases with clarified etiology were significantly prevalent (p < 0.001). The most frequently identified etiology was HLA B27-associated uveitis (32.5%), followed by viral uveitis (16.8%). A significant correlation between etiology and anatomical localization was found (p < 0.001). The highest proportion (93%) of cases with clarified etiology was associated with posterior uveitis, while the lowest (39.7%) was linked to intermediate uveitis. Conclusions: We found that anterior uveitis was the most common anatomical localization, followed by intermediate uveitis. The disease is rare in childhood, while in elderly patients, there is an increase in idiopathic and viral uveitis cases. Our results provide valuable information about the most common etiologies of uveitis among the Bulgarian population. Full article

Background: Schnyder corneal dystrophy (SCD) is a rare autosomal dominant disorder characterized by bilateral corneal opacification due to abnormal cholesterol and phospholipid deposition. Mutations in the UBIAD1 gene, identified as causative in 2007, underline the condition, although its exact pathogenesis remains unclear. Case Presentation: A 55-year-old female presented with persistent photophobia, blepharospasm, and corneal discomfort. She also reported joint pain related to rheumatoid arthritis (RA), managed with Ro-Actemra (tocilizumab). The ophthalmological evaluation revealed bilateral corneal stromal deposits resembling snowflakes, with visual acuities of 0.8 (right eye) and 0.7 (left eye). Multimodal imaging confirmed stromal hyperreflective deposits. Based on the clinical findings, SCD was diagnosed, although no genetic testing was performed. Symptomatic management with artificial tears was initiated. Discussion: This case illustrates the diagnostic challenges of SCD, particularly in the absence of corneal crystals, a hallmark feature that is not universally present. Advanced imaging techniques aided diagnosis, and the coexistence of SCD and RA highlights the need for multidisciplinary care. Treatment options remain limited, although emerging therapies targeting oxidative stress and lipid metabolism show promise. Conclusions: This case highlights the importance of integrating ophthalmological and systemic care in SCD management and underscores the need for further research to expand diagnostic and therapeutic strategies for this rare disorder. Full article

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. Full article

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. Full article

Introduction: Descending necrotizing mediastinitis is one of the most lethal forms of acute mediastinitis. It originates from an odontogenic or deep neck infection, which descends to the mediastinum through the fascial planes. It is a rare condition, but mortality rates remain high, especially in the presence of comorbidities or predisposing factors. Delay in diagnosis has been shown to be one of the most important factors for the disease outcome. Therefore, early diagnosis and treatment by a multidisciplinary team are of utmost importance. Case series: Four healthy young males with descending necrotizing mediastinitis were treated at our institution. None of them had any comorbidities, but all of them waited between 3 and 4 days before seeking medical help. Upon their arrival at the hospital, in addition to the presence of a severe neck infection, the presence of mediastinitis was also found. Despite the timely surgical treatment of both the source of the infection and the mediastinitis, three of the four cases had a fatal outcome. Conclusion: We believe that the time factor is of greater importance for the outcome of acute descending mediastinitis than the factors of age and presence of accompanying diseases. Proper and rapid treatment by a multidisciplinary team is essential, even for young and healthy people. Full article

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. Full article

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. Full article

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. Full article

Introduction. Biliary obstruction is a common manifestation of biliopancreatic malignancies, and its relief is an essential part of the treatment algorithm. Currently, there are three techniques to manage malignant biliary obstruction—endoscopic retrograde cholangiopancreatography (ERCP), percutaneous transhepatic biliary drainage (PTBD), and endoscopic ultrasound-guided biliary drainage (EUS-BD). ERCP has been adopted as a first-line treatment modality but EUS-BD is gradually emerging as a viable alternative. The aim of the current article is to assess the clinical outcomes of the three nonsurgical biliary drainage procedures. Materials and methods. A total of 102 consecutive patients with unresectable biliopancreatic malignancy inducing biliary obstruction and subjected to palliative treatment by means of ERCP, EUS-BD, or PTBD were retrospectively included in the study. Results. No difference in clinical and technical success of the procedures was found: ERCP—97.2% technical; 88.9% clinical; PTBD—94.4% technical, 72.2% clinical; EUS-BD—90% technical; 83.3% clinical. Adverse events (AEs) and reinterventions were significantly more common in PTBD (38.9% and 52.8%) and ERCP (27.9% and 25%) compared to EUS-BD (10% and 3.3%). Total duration of hospital stay and number of hospitalizations were lower in the EUS-BD compared to PTBD and ERCP groups. Conclusions. In the presence of adequate expertise, EUS-BD may be superior to PTBD and ERCP in achieving and sustaining biliary drainage in the setting of unresectable malignancy. Full article

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. Full article

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. Full article