Search Results (98)

Cryotherapy involves flash freezing of tissue and removing unwanted tissue. Mechanism of injury is causing cell membrane rupture by rapid multiple freeze–thaw cycles, while reserving tissue architecture and the collagen matrix. This promotes favorable wound healing. In recent years, it has gained increasing attention as a treatment option for upper gastrointestinal diseases (Barrett’s Esophagus and early cancer). Currently, two FDA-approved delivery methods are available in the GI tract: Cryoballoon and spray cryotherapy, which will be discussed. In this review, we also propose to examine the expanding role of cryotherapy in gastrointestinal practice, drawing from both clinical studies and illustrative vignettes. In addition, we will highlight its established role in eradicating Barrett’s with low and high-grade dysplasia and compare its outcomes and safety profile with radiofrequency ablation (RFA). We will also discuss the application and safety of spray cryotherapy in the palliation of malignant esophageal strictures when compared with Esophageal stent placement. Cryotherapy may have immunological potential, and it may shrink both primary and metastatic diseases. Ongoing research in this field of Cryo-immunology will be highlighted. Beyond esophageal neoplasia, cryotherapy is increasingly utilized in other upper gastrointestinal precancerous conditions. Through this synthesis, our goal is to provide a timely and comprehensive overview of advancements in cryotherapy and its potential to reshape novel therapeutic approaches in upper gastrointestinal cancers. Finally, we highlight the evolution of a novel platform using nitrous oxide delivered by a handheld device, a contact balloon, and a small replaceable cartridge. This approach may make delivery of cryogen application favorable and a first-line approach in the management of Barrett’s esophagus and early cancer. In addition, Cryoballoon therapy for dysphagia palliation for malignant esophageal strictures may become a preferred approach as more data evolves. Full article

Chronic atrophic gastritis (CAG) is a precancerous gastric condition with limited therapeutic interventions, and the mechanisms underlying the benefits of Coptis chinensis Franch. (CCF) remain insufficiently defined. This study employed an integrated computational strategy to clarify the molecular basis of CCF activity against CAG. Network pharmacology was used to identify potential targets of the major CCF constituents berberine, coptisine, and palmatine, followed by molecular docking, machine learning-based IC₅₀ prediction, and molecular dynamics simulations. Fifty-eight overlapping targets between CCF compounds and CAG-related genes were identified, highlighting SRC, STAT3, MAPK1, and NFKB1 as central nodes enriched in inflammatory and immune pathways, including TNF and MAPK signaling. Docking analyses revealed strong interactions between all three compounds and SRC kinase, and machine learning models predicted IC₅₀ values in the low micromolar range (1.38–1.82 μM). Molecular dynamics simulations further suggest that berberine may stabilize the crucial regulatory regions of SRC, specifically the activation loop. It is hypothesized that this stabilization maintains the inactive conformation of the kinase domain and potentially shields Tyr416 from phosphorylation, thus potentially influencing kinase activation. These findings suggest that CCF may modulate key inflammatory and immune pathways implicated in CAG progression, with SRC emerging as a central node for further investigation. Full article

Background: Lichen planus (LP) is a common inflammatory disease affecting skin, mucous membranes, hairs, and nails, with an unpredictable course involving remissions and relapses. LP is a Type-I-Inflammation disease involving IFN-γ and IL-17 as key inflammatory mediators. Materials and Methods: We searched PubMed/MEDLINE and Google Scholar search engines for studies on the esophageal manifestation of lichen planus over an unlimited time frame. Articles were searched with combinations of Medical Subject Heading (MeSH) terms. Given the limited number of publications, no exclusion criteria were applied. Results: Esophageal lichen planus (ELP) is an underreported manifestation of LP that primarily affects middle-aged women. Its prevalence among LP patients remains to be defined. Though potentially clinically silent, ELP can significantly impact patient wellbeing and serve as a precursor to esophageal squamous cell carcinoma. While dysphagia is the primary symptom, the condition may also remain subclinical. The endoscopic hallmarks of ELP are mucosal denudation and tearing, trachealization, and hyperkeratosis. Chronic disease progression may lead to scarring esophageal stenosis. Histologically, ELP shows mucosal detachment, T-lymphocytic infiltrations, epithelial cell apoptosis (Civatte bodies), dyskeratosis, and hyperkeratosis. Fibrinogen deposits along the basement membrane zone distinguish ELP from various immunological esophageal diseases. There is currently no standardized therapy available. Topical steroids lead to symptomatic and histologic improvements in two-thirds of patients. Severe or refractory cases require immunosuppressive therapy, whereas JAK-inhibitors represent a promising emerging option. Endoscopic dilation helps symptomatic stenosis. Considering ELP’s precancerous potential, timely diagnosis and treatment are crucial in preventing complications, such as stenosis or invasive esophageal squamous cell carcinoma. Conclusions: ELP is an underdiagnosed and underreported manifestation of LP. While it may remain clinically silent, it can nevertheless significantly affect patients’ wellbeing and life expectancy. This narrative review aims to initiate multidisciplinary cooperation among gastroenterologists, dermatologists, oral health professionals, and histopathologists to support clinical diagnosis and management. Full article

Background: Gastric cancer (GC) is the fifth most common malignancy worldwide. Early detection of precancerous conditions—atrophic gastritis (AG), intestinal metaplasia (IM), and dysplasia—is vital for surveillance. Objectives: To assess the accuracy of single high-quality endoscopy (HQE) in detecting advanced GPCs and to identify risk factors for AG, IM, and dysplasia. Methods: A retrospective review of 442 gastroscopies (2017–2022) at a single center. Endoscopic findings were compared with histology, including OLGA/OLGIM staging, dysplasia, and Helicobacter pylori (H. pylori) status. Results: The study population comprised 319 women (72.17%) and 123 men (27.83%), with a mean age of 59 years (SD: 12.53). AG, as defined by OLGA and OLGIM staging, was identified in 90 patients (20.36%) and 50 patients (11.31%), respectively. A total of 44 cases of de novo gastric dysplasia were observed, while HP infection was confirmed in 37 individuals (8.37%). We observed similar low sensitivity for detection of advanced OLGA (32.5%), OLGIM (40%), and dysplasia (19.7%) with relatively high specificity (~89%). Advanced AG and IM peaked at ages 51–53. Risk factors for advanced OLGIM included male sex (OR 2.26; p < 0.001) and presence of dysplasia (OR 2.09; p = 0.02). Dysplasia was positively associated with AG (OR 2.03; p < 0.001) and IM (OR 2.21; p < 0.001) but inversely associated with a family history of GC (OR 0.44; p < 0.001). Conclusions: A single HQE can help exclude advanced GPCs, but due to low sensitivity, gastric mapping biopsies remain crucial. Males are at increased risk of extensive IM. Family history of GC was linked to lower OLGA/OLGIM stages. Full article

Background: Skin cancer represents one of the most prevalent malignancies worldwide, with melanoma accounting for approximately 75% of skin cancer-related deaths despite comprising fewer than 5% of cases. Early detection dramatically improves survival rates from 14% to over 99%, highlighting the urgent need for accurate and accessible diagnostic tools. While deep learning has shown promise in dermatological diagnosis, existing approaches lack clinical explainability and deployable interfaces that bridge the gap between research innovation and practical healthcare applications. Methods: This study implemented a comprehensive multimodal deep learning framework using the HAM10000 dataset (10,015 dermatoscopic images across seven diagnostic categories). Three CNN architectures (DenseNet-121, EfficientNet-B3, ResNet-50) were systematically compared, integrating patient metadata, including age, sex, and anatomical location, with dermatoscopic image analysis. The first implementation of XRAI (eXplanation with Region-based Attribution for Images) explainability for skin lesion classification was developed, providing spatially coherent explanations aligned with clinical reasoning patterns. A deployable web-based clinical interface was created, featuring real-time inference, comprehensive safety protocols, risk stratification, and evidence-based cosmetic recommendations for benign conditions. Results: EfficientNet-B3 achieved superior performance with 89.09% test accuracy and 90.08% validation accuracy, significantly outperforming DenseNet-121 (82.83%) and ResNet-50 (78.78%). Test-time augmentation improved performance by 1.00 percentage point to 90.09%. The model demonstrated excellent performance for critical malignant conditions: melanoma (81.6% confidence), basal cell carcinoma (82.1% confidence), and actinic keratoses (88% confidence). XRAI analysis revealed clinically meaningful attention patterns focusing on irregular pigmentation for melanoma, ulcerated borders for basal cell carcinoma, and surface irregularities for precancerous lesions. Error analysis showed that misclassifications occurred primarily in visually ambiguous cases with high correlation (0.855–0.968) between model attention and ideal features. The web application successfully validated real-time diagnostic capabilities with appropriate emergency protocols for malignant conditions and comprehensive cosmetic guidance for benign lesions. Conclusions: This research successfully developed the first clinically deployable skin lesion classification system combining diagnostic accuracy with explainable AI and practical patient guidance. The integration of XRAI explainability provides essential transparency for clinical acceptance, while the web-based deployment democratizes access to advanced dermatological AI capabilities. Comprehensive validation establishes readiness for controlled clinical trials and potential integration into healthcare workflows, particularly benefiting underserved regions with limited specialist availability. This work bridges the critical gap between research-grade AI models and practical clinical utility, establishing a foundation for responsible AI integration in dermatological practice. Full article

Mitochondria perform critical roles in cellular functions, particularly in metabolism and cell death regulation. Mutations in nuclear and mitochondrial genes can cause mitochondrial dysfunction, leading to classical mitochondrial diseases. Emerging evidence suggests that mitochondrial adaptations in cancer support the high energy demands of proliferating cells and contribute to tumor progression through anti-apoptotic mechanisms, dysregulated mitochondrial quality control (mtQC), and altered mitochondrial DNA (mtDNA) copy numbers. Interestingly, several mitochondrial pathways involved in cancer progression resemble those implicated in mitochondrial diseases. From this perspective, although cancer is not a classical mitochondrial disease, its progression involves mitochondria-associated pathways similar to those in mitochondrial disorders, suggesting that cancer may be considered a mitochondria-related disease in a broader sense. Understanding these shared mechanisms could provide new insights into precision treatment strategies. Furthermore, mitochondrial dysfunction is increasingly recognized in precancerous conditions, suggesting its potential as a target for early intervention. Oral potentially malignant disorders (OPMDs) serve as a valuable model for studying these mitochondria-associated mechanisms, offering a promising avenue for both therapeutic advancements and preventive approaches. Full article

Introduction: Actinic cheilitis (AC) is a common precancerous condition affecting the lips, primarily caused by prolonged ultraviolet radiation exposure. Various treatment options are available. However, the optimal treatment approach remains a subject of debate. Objective: To summarize and compare practice-relevant interventions for AC. Materials and Methods: A pre-defined protocol was registered in PROSPERO (CRD42021225182). Systematic searches in Medline, Embase, and Central, along with manual trial register searches, identified studies reporting participant clearance rates (PCR) or recurrence rates (PRR). Quality assessment for randomized controlled trials (RCTs) was conducted using the Cochrane Risk of Bias tool 2. Uncontrolled studies were evaluated using the tool developed by the National Heart, Lung, and Blood Institute. The generalized linear mixed model was used to pool proportions for uncontrolled studies. A pairwise meta-analysis for RCTs was applied, using the odds ratio (OR) as the effect estimate and the GRADE approach to evaluate the quality of the evidence. Adverse events were analyzed qualitatively. Results: A comprehensive inclusion of 36 studies facilitated an evaluation of 614 participants for PCR, and 430 patients for PRR. Diclofenac showed the lowest PCR (0.53, 95% confidence interval (CI) [0.41; 0.66]), while CO₂ laser showed the highest PCR (0.97, 95% CI [0.90; 0.99]). For PRR, Er:YAG laser showed the highest rates (0.14, 95% CI [0.08; 0.21]), and imiquimod the lowest (0.00, 95% CI [0.00; 0.06]). In a pairwise meta-analysis, the OR indicated a lower recurrence rate for Er:YAG ablative fractional laser (AFL)-primed methyl-aminolevulinate photodynamic therapy (MAL-PDT) (Er:YAG AFL-PDT) compared to methyl-aminolevulinate photodynamic therapy (MAL-PDT) alone (OR = 0.22, 95% CI [0.06; 0.82]). The CO₂ laser showed fewer local side effects than the Er:YAG laser, while PDTs caused more skin reactions. Due to qualitative data, comparability was limited, highlighting the need for individualized treatment. Conclusions: This study provides a complete and up-to-date evidence synthesis of practice-relevant interventions for AC, identifying the CO₂ laser as the most effective treatment and regarding PCR and imiquimod as most effective concerning PRR. Full article

Chronic atrophic gastritis and intestinal metaplasia (IM) are gastric precancerous conditions (GPCs) associated with an increased risk of gastric cancer. Early detection and accurate characterization of GPC are therefore crucial for risk stratification and the implementation of preventive strategies. In the absence of clear mucosal changes observed through white-light imaging (WLI) or virtual chromoendoscopy, endocytoscopy can help unveil the presence of GPC by enabling in vivo assessment of nuclear and cellular structures at ultra-high magnification. Endocytoscopy is typically performed using WLI following dye-based staining of the mucosa. In this case, we demonstrate that combining endocytoscopy with the texture and color enhancement imaging (TXI) mode substantially improves the assessment of the gastric mucosa. In a 61-year-old man undergoing esophagogastroduodenoscopy, WLI showed multifocal erythema in the stomach, without clearly visible lesions on either WLI or narrow-band imaging. Conventional endocytoscopy revealed multiple small spots of IM with characteristic changes in glandular structures, which were even more evident when using the TXI mode. Histological analysis of targeted biopsies confirmed small foci of IM in both the antrum and corpus. The patient was enrolled in a surveillance program because of his clinical background. The combination of endocytoscopy with the TXI mode significantly enhances the delineation of mucosal and cellular architecture, supporting a more accurate optical diagnosis. Full article

Background: Vaginal intraepithelial neoplasia (VaIN) is a rare but potentially precancerous condition strongly associated with human papillomavirus (HPV) infection. Despite increased detection rates due to HPV screening and colposcopy, diagnosis and management remain challenging. This study aimed to evaluate the epidemiological characteristics, risk factors, and outcomes of VaIN in patients referred to a tertiary academic center. Methods: We conducted a retrospective analysis of 48 patients who underwent colposcopy-directed vaginal biopsies between January 2019 and June 2024 at the Medical University of Warsaw. Data collected included patient demographics, HPV status, cytology, histopathology, and treatment outcomes. Patients were grouped based on the presence and grade of VaIN (VaIN 1 vs. VaIN 2/3). Statistical analyses were performed using SPSS software. Results: VaIN was diagnosed in 24 patients (50%), VaIN was confirmed in half of the cohort, VaIN 2 in 30%, and VaIN 3 in 18% of cases. HPV infection and prior cervical pathology were significantly associated with VaIN diagnosis (P = 0.03 and P = 0.05, respectively), and high-risk HPV infection correlated with higher-grade lesions (P = 0.04). Among VaIN 2+ cases, most patients required laser ablation or surgical excision, while VaIN 1 often regressed spontaneously. Regression occurred in 11 cases, and high-risk HPV infection was inversely associated with spontaneous regression (P = 0.04). Conclusions: This study confirms the central role of HPV, particularly high-risk subtypes, in VaIN pathogenesis. Conservative management may be appropriate for VaIN 1, while VaIN 2+ requires active intervention. HPV genotyping should be integrated into diagnostic workups, and long-term follow-up is essential due to the risks of persistence and recurrence. Full article

Background: Intestinal metaplasia (IM) is a precancerous gastric condition that requires accurate histopathological diagnosis to enable early intervention and cancer prevention. Traditional evaluation of H&E-stained tissue slides can be labor-intensive and prone to interobserver variability. Recent advances in deep learning, particularly transformer-based models, offer promising tools for improving diagnostic accuracy. Methods: We propose ViSwNeXtNet, a novel patch-wise ensemble framework that integrates three transformer-based architectures—ConvNeXt-Tiny, Swin-Tiny, and ViT-Base—for deep feature extraction. Features from each model (12,288 per model) were concatenated into a 36,864-dimensional vector and refined using iterative neighborhood component analysis (INCA) to select the most discriminative 565 features. A quadratic SVM classifier was trained using these selected features. The model was evaluated on two datasets: (1) a custom-collected dataset consisting of 516 intestinal metaplasia cases and 521 control cases, and (2) the public GasHisSDB dataset, which includes 20,160 normal and 13,124 abnormal H&E-stained image patches of size 160 × 160 pixels. Results: On the collected dataset, the proposed method achieved 94.41% accuracy, 94.63% sensitivity, and 94.40% F1 score. On the GasHisSDB dataset, it reached 99.20% accuracy, 99.39% sensitivity, and 99.16% F1 score, outperforming individual backbone models and demonstrating strong generalizability across datasets. Conclusions: ViSwNeXtNet successfully combines local, regional, and global representations of tissue structure through an ensemble of transformer-based models. The addition of INCA-based feature selection significantly enhances classification performance while reducing dimensionality. These findings suggest the method’s potential for integration into clinical pathology workflows. Future work will focus on multiclass classification, multicenter validation, and integration of explainable AI techniques. Full article

Chronic pancreatitis (CP) is a progressive condition that is associated with severe complications. Diagnosis of late CP is easy due to characteristic clinical presentation and pathognomonic imaging findings, such as pancreatic calcifications. Early changes, such as lobularity and a dilated main pancreatic duct, are very subtle and challenging to detect with ultrasonography (US) or even computed tomography (CT). Data were accumulating on the usefulness of EUS in the early diagnosis of CP. The sensitivity values for detecting early CP (ECP) by US, MRI, and EUS were 67–69%, 77–78%, and 81–84%, respectively. The specificity values for detecting ECP by US, MRI, and EUS were 90–98%, 83–96%, and 90–100%, respectively. Pancreatic cancer (PDAC) is one of the leading cancers worldwide, with increasing morbidity. Due to its poor prognosis and survival, early diagnosis is crucial. For this indication, EUS also shows better outcomes compared to other imaging methods, especially in tumors < 2 cm. The sensitivity and specificity for diagnosing PDAC with MRI and EUS were 52.3–93%, 77.1–89%, 72–100%, and 90%, respectively. In addition, EUS can detect precancerous conditions that are associated with a higher risk of PDAC. EUS-assisted new techniques, like elastography and contrast enhancement, facilitate the diagnosis of pancreatic lesions and make it even more accurate. Early PDAC changes, such as main pancreatic duct dilatation or irregular margins of pancreatic solid masses, may be detected with EUS. This review describes the efficacy of different imaging techniques in the early detection of CP and PDAC. In addition, we describe the useful interventions made possible by early diagnosis of PDAC and CP. Full article

Background: Prostate cancer (PCa) remains one of the most prevalent malignancies in men, with diagnostic challenges arising from the limited specificity of current biomarkers, like PSA. Improved stratification tools are essential to reduce overdiagnosis and guide personalized patient management. Objective: This study aimed to identify and validate clinical and hematological biomarkers capable of differentiating PCa from benign prostatic hyperplasia (BPH) and precancerous lesions (PL) using univariate and multivariate statistical methods. Methods: In a cohort of 514 patients with suspected PCa, we performed a univariate analysis (Kruskal–Wallis and ANOVA) with preprocessing via adaptive Box–Cox transformation and missing value imputation through probabilistic principal component analysis (PPCA). LASSO regression was used for variable selection and classification. An ROC curve analysis assessed diagnostic performance. Results: Five variables—age, PSA, Index %, hemoglobin (HGB), and the International Index of Erectile Function (IIEF)—were consistently significant across univariate and multivariate analyses. The LASSO regression achieved a classification accuracy of 70% and an AUC of 0.74. Biplot and post-hoc analyses confirmed partial separation between PCa and benign conditions. Conclusions: The integration of multivariate modeling with reconstructed clinical data enabled the identification of blood-based biomarkers with strong diagnostic potential. These routinely available, cost-effective indicators may support early PCa diagnosis and patient stratification, reducing unnecessary invasive procedures. Full article

Background/Objectives: Oral health is a complex concept involving physical, psychological, emotional, and social components. A key factor in maintaining oral tissue integrity is redox balance, which is disrupted by oxidative stress (OS) through an imbalance between reactive oxygen species (ROS) and antioxidant defenses. This study examines the contribution of endogenous and exogenous sources to OS and explores the therapeutic potential of medicinal plants from the Asteraceae and Lamiaceae families in restoring redox homeostasis and improving oral health. Methods: A literature review was conducted, analyzing the role of OS in oral diseases and the antioxidant mechanisms of selected Asteraceae species. Special attention was given to their phytochemical contents—polyphenols, flavonoids, and essential oils—and their biological relevance to oral health. Results: OS plays a critical role in the onset and progression of oral conditions such as caries, periodontitis, gingivitis, aphthous ulcers, abscesses, precancerous lesions, and oral cancers. ROS and reactive nitrogen species (RNS) cause inflammation, tissue breakdown, and salivary gland dysfunction. Asteraceae plants like Matricaria chamomilla, Calendula officinalis, Cichorium intybus, Taraxacum officinale, Arctium lappa, Achillea millefolium, and Solidago virgaurea demonstrate notable antioxidant, anti-inflammatory, and antimicrobial properties that help counteract OS and support oral homeostasis. Conclusions: Asteraceae and Lamiaceae species show high therapeutic potential in addressing OS-related oral disorders. Their bioactive compounds aid in restoring redox balance and protecting oral tissues. These findings support the integration of phytotherapeutic agents into oral healthcare and call for further clinical validation of plant-based strategies for disease prevention and management. Full article

Background and Objectives: The relationship between the vaginal microbiota, human papillomavirus infection (HPV), and cervical precancerous lesions is a critical area of research, as it influences both the progression of HPV-related diseases and potential treatment strategies. New evidence suggests that Lactobacillus crispatus dominance in the microbiota may protect against HPV persistence and speed the elimination of HPV. This study aims to explore the relationship between the vaginal microbiota composition and HPV infection, focusing on the impact of these factors on the development of cervical precancerous lesions. Materials and Methods: A comprehensive literature review was conducted using the PubMed database, focusing on studies that analyzed the association between the vaginal microbiota and HPV infection in the context of cervical dysplasia. This study was primarily based on clinical data on HPV integration in women with low-grade squamous intraepithelial lesions (LSILs), high-grade squamous intraepithelial lesions (HSILs), and cervical cancer. Results: Different types of vaginal microbiota communities (CSTs) have different pathogenic or protective potential. Healthy women predominantly exhibited CST I, with Lactobacillus crispatus as the dominant microorganism. CST IV, associated with increased anaerobic bacteria, was most common in HSIL and cervical cancer patients. Statistical analysis revealed that bacterial vaginosis (BV) was significantly associated with HPV persistence, with studies reporting a 1.8–3.4-fold increased risk (p < 0.05) of persistent HR-HPV infection in BV-positive women. Conclusions: Our literature review suggests that the composition of the vaginal microbiota can modulate the local immune response, the expression of viral oncogenes, and the integrity of the epithelial barrier. Furthermore, certain bacterial genes or metabolic pathways can be associated with a favorable or unfavorable outcome of the disease. Analysis of the vaginal microbiota could serve as an additional risk assessment tool, helping to distinguish between regressing and progressive precancerous conditions. Full article

Background/Objectives: Skin lesions, ranging from benign to malignant diseases, are a difficult dermatological condition due to their great diversity and variable severity. Their detection at an early stage and proper classification, particularly between benign Nevus (NV), precancerous Actinic Keratosis (AK), and Squamous Cell Carcinoma (SCC), are crucial for improving the effectiveness of treatment and patient prognosis. The goal of this study was to test deep learning (DL) models to determine the best architecture to use in classifying lesions and create a web-based platform for improved diagnostic and educational availability. Methods: Various DL models, like Xception, DenseNet169, ResNet152V2, InceptionV3, MobileNetV2, EfficientNetV2 Small, and NASNetMobile, were compared for classification accuracy. The top model was incorporated into a web application, allowing users to upload images for automatic classification, thereby offering confidence scores as a measure of the reliability of predictions. The tool also has enhanced visualization capabilities, which allow users to investigate feature maps derived from convolutional layers, enhancing interpretability. Web scraping and summarization techniques were also employed to offer concise, evidence-based dermatological information from established sources. Results: Of the models evaluated, DenseNet169 achieved the best classification accuracy of 85% and was, therefore, chosen as the base architecture for the web application. The application enhances diagnostic clarity by visualizing features and promotes access to trustworthy medical information on dermatological disorders. Conclusions: The developed web application serves as both a diagnostic support system for dermatologists and an educational system for the general public. By using DL-based classification, interpretability techniques, and automatic medical information extraction, it facilitates early intervention and increases awareness regarding skin health. Full article