Search Results (9,039)

Hodgkin’s Lymphoma (HL) affects approximately 8500 individuals annually in the United States. The 5-year relative survival rate has improved to 88.5%, driven by transformative advances in immunotherapy and precision oncology. The integration of Brentuximab vedotin (BV) and immune checkpoint inhibitors (ICIs) has redefined treatment paradigms. The phase III SWOG S1826 trial established nivolumab plus doxorubicin, vinblastine, and dacarbazine (N + AVD) as an emerging new standard for advanced-stage HL, achieving a 2-year progression-free survival (PFS) of 92% compared to 83% for BV plus AVD (HR 0.48, 95% CI: 0.33–0.70), with superior safety, particularly in patients over 60. In relapsed/refractory HL, pembrolizumab outperforms BV, with a median PFS of 13.2 versus 8.3 months (HR 0.65, 95% CI: 0.48–0.88), as demonstrated in the KEYNOTE-204 trial. Emerging strategies, including novel ICI combinations, minimal residual disease (MRD) monitoring via circulating tumor DNA (ctDNA), and artificial intelligence (AI)-driven diagnostics, promise to further personalize therapy. This review synthesizes HL’s epidemiology, pathogenesis, diagnostic innovations, and therapeutic advances, highlighting the role of precision medicine in addressing unmet needs and disparities in HL care. Full article

Pediatric asthma is a multifactorial and heterogeneous disease determined by the dynamic interplay of genetic susceptibility, environmental exposures, and immune dysregulation. Recent advances have highlighted the pivotal role of epigenetic mechanisms, in particular, DNA methylation, histone modifications, and non-coding RNAs, in the regulation of inflammatory pathways contributing to asthma phenotypes and endotypes. This review examines the role of respiratory viruses such as respiratory syncytial virus (RSV), rhinovirus (RV), and other bacterial and fungal infections that are mediators of infection-induced epithelial inflammation that drive epithelial homeostatic imbalance and induce persistent epigenetic alterations. These alterations lead to immune dysregulation, remodeling of the airways, and resistance to corticosteroids. A focused analysis of T2-high and T2-low asthma endotypes highlights unique epigenetic landscapes directing cytokines and cellular recruitment and thereby supports phenotype-specific aspects of disease pathogenesis. Additionally, this review also considers the role of miRNAs in the control of post-transcriptional networks that are pivotal in asthma exacerbation and the severity of the disease. We discuss novel and emerging epigenetic therapies, such as DNA methyltransferase inhibitors, histone deacetylase inhibitors, miRNA-based treatments, and immunomodulatory probiotics, that are in preclinical or early clinical development and may support precision medicine in asthma. Collectively, the current findings highlight the translational relevance of including pathogen-related biomarkers and epigenomic data for stratifying pediatric asthma patients and for the personalization of therapeutic regimens. Epigenetic dysregulation has emerged as a novel and potentially transformative approach for mitigating chronic inflammation and long-term morbidity in children with asthma. Full article

The advancement of artificial intelligence (AI), deep learning, and radiomics has introduced novel methodologies for the detection, classification, prognosis, and treatment evaluation of pancreatic ductal adenocarcinoma (PDAC). As the integration of AI into medical imaging continues to evolve, its potential to enhance early detection, refine diagnostic precision, and optimize treatment strategies becomes increasingly evident. However, despite significant progress, various challenges remain, particularly in terms of clinical applicability, generalizability, interpretability, and integration into routine practice. Understanding the current state of research is crucial for identifying gaps in the literature and exploring opportunities for future advancements. This literature review aims to provide a comprehensive overview of the existing studies on AI applications in PDAC, with a focus on disease detection, classification, survival prediction, treatment response assessment, and radiogenomics. By analyzing the methodologies, findings, and limitations of these studies, we aim to highlight the strengths of AI-driven approaches while addressing critical gaps that hinder their clinical translation. Furthermore, this review aims to discuss future directions in the field, emphasizing the need for multi-institutional collaborations, explainable AI models, and the integration of multi-modal data to advance the role of AI in personalized medicine for PDAC. Full article

The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. This paper presents a systematic review of the scientific literature published between 1 January 2020 and 31 May 2025. The paper is based on the applicability of ML techniques in the field of geriatrics. The study is conducted using the Web of Science database for a detailed discussion. The most studied algorithms in research articles are Random Forest, Extreme Gradient Boosting, and support vector machines. They are preferred due to their performance in processing incomplete clinical data. The performance metrics reported in the analyzed papers include the accuracy, sensitivity, F1-score, and Area under the Receiver Operating Characteristic Curve. Nine search categories are investigated through four databases: WOS, PubMed, Scopus, and IEEE. A comparative analysis shows that the field of geriatrics, through an ML approach in the context of elderly nutrition, is insufficiently explored, as evidenced by the 61 articles analyzed from the four databases. The analysis highlights gaps regarding the explainability of the models used, the transparency of cross-sectional datasets, and the validity of the data in real clinical contexts. The paper highlights the potential of ML models in transforming geriatrics within the context of personalized predictive care and outlines a series of future research directions, recommending the development of standardized databases, the integration of algorithmic explanations, the promotion of interdisciplinary collaborations, and the implementation of ethical norms of artificial intelligence in geriatric medical practice. Full article

Liquid biopsy has emerged as a valuable tool for the detection and monitoring of colorectal cancer (CRC), providing minimally invasive insights into tumor biology through circulating biomarkers such as circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Additional biomarkers, including tumor-educated platelets (TEPs) and exosomal RNAs, offer further potential for early detection and prognostic role, although ongoing clinical validation is still needed. This review summarizes the current evidence on the diagnostic, prognostic, and predictive capabilities of liquid biopsy in both metastatic and non-metastatic CRC. In the non-metastatic setting, liquid biopsy is gaining traction in early detection through screening and in identifying minimal residual disease (MRD), potentially guiding adjuvant treatment and reducing overtreatment. In contrast, liquid biopsy is more established in metastatic CRC for monitoring treatment responses, clonal evolution, and mechanisms of resistance. The integration of ctDNA-guided treatment algorithms into clinical practice could optimize therapeutic strategies and minimize unnecessary interventions. Despite promising advances, challenges remain in assay standardization, early-stage sensitivity, and the integration of multi-omic data for comprehensive tumor profiling. Future efforts should focus on enhancing the sensitivity of liquid biopsy platforms, validating emerging biomarkers, and expanding multi-omic approaches to support more targeted and personalized treatment strategies across CRC stages. Full article

Cystic fibrosis (CF), the most common hereditary lung disease in Caucasians, is caused by dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR). We evaluated CFTR function using a newly developed Ussing chamber system, the Multi Trans Epithelial Current Clamp (MTECC), in an in vitro model of human airway epithelia. Air–liquid interface (ALI) cultures were established from nasal brushings of healthy controls (HC) and CF patients with biallelic CFTR variants. ALI layer thickness was similar between groups (HC: 62 ± 13 µm; CF: 55 ± 9 µm). Immunofluorescence showed apical CFTR expression in HC, but reduced or absent signal in CF cultures. MTECC enabled continuous measurement of transepithelial resistance (Rt), potential difference (PD), and conductance (G_t). G_t was significantly reduced in CF cultures compared to HC (0.825 ± 0.024 vs. −0.054 ± 0.016 mS/cm²), indicating impaired cAMP-inducible ion transport by CFTR. Treatment of CF cultures with elexacaftor, tezacaftor, and ivacaftor (Trikafta^®) increased G_t, reflecting partial restoration of CFTR function. These findings demonstrate the utility of MTECC in detecting functional differences in CFTR activity and support its use as a platform for evaluating CFTR-modulating therapies. Our model may contribute to the development of personalized treatment strategies for CF patients. Full article

Background/Objectives: Multifactorial prevention of falls in persons with dementia has minimal or non-significant effects. Personalised prevention is recommended. We have previously shown that gait speed, basic activities of daily living (ADL), and depression (high Cornell scores) were independent predictors of falls in persons with mild and moderate cognitive impairment. This study explored person-specific risks of falls related to physical, mental, and cognitive functions and types of dementia: Alzheimer’s disease (AD), vascular dementia (VD), mixed Alzheimer’s disease/vascular dementia (MixADVD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB). Methods: The study used data from “The Norwegian Registry of Persons Assessed for Cognitive Symptoms” (NorCog). Differences between the dementia groups and predictors of falls, gait speed, ADL, and Cornell scores were analysed. Results: Among study participants, 537/1321 (40.7%) reported a fall in the past year, with significant variations between dementia diagnoses. Fall incidence increased with age, comorbidity/polypharmacy, depression, and MAYO fluctuation score and with reduced physical activity, gait speed, and ADL. Persons with VD and MixADVD had high fall incidences and impaired gait speed and ADL. Training of physical fitness, endurance, muscular strength, coordination, and balance and optimising treatment of comorbidities and medication enhance gait speed. Improving ADL necessitates, in addition, relief of cognitive impairment and fluctuations. Relief of depression and fluctuations by psychological and pharmacological interventions is necessary to reduce the high fall risk in persons with DLB. Conclusions: The fall incidence and fall predictors varied significantly. Personalised interventions presuppose knowledge of each individual’s fall risk factors. Full article

Colorectal cancer (CRC) constitutes a major global health concern, ranking as the third most common cancer and the second leading cause of cancer-related mortality. The current review explores sex-based differences in CRC epidemiology, risk factors, tumor biology, and clinical outcomes. Males exhibit a higher incidence and mortality rate, with left-sided (distal) CRC predominating, while females are more frequently diagnosed with right-sided (proximal) tumors, which tend to be more aggressive and less responsive to conventional chemotherapy. Genetic disparities, including microsatellite instability and X-chromosome tumor suppressor genes, contribute to sex-specific differences in tumor progression and treatment response. Immune variations also influence disease outcomes, with females exhibiting stronger immune surveillance but higher exhaustion markers. Lifestyle factors such as body mass index (BMI), smoking, and hormonal influences further modulate CRC risk. While males are more vulnerable to obesity-related CRC, central obesity (waist-to-hip ratio) emerges as a stronger predictor in females. Additionally, smoking increases CRC risk differentially by tumor location. These findings underscore the importance of sex-specific approaches in CRC prevention, screening, and treatment, advocating for personalized medicine strategies tailored to gender-based biological and clinical distinctions. Full article

Despite significant advances in prostate cancer treatment over the past two decades, metastatic castration-resistant prostate cancer (mCRPC) remains incurable. We present the case of a patient with aggressive prostate cancer diagnosed 20 years ago, underscoring the value of longitudinal genomic profiling and advanced imaging to guide clinical decisions. After multiple treatment failures, genomic analyses of tissue and liquid biopsies revealed dynamic changes in tumor biology and the emergence of resistance mechanisms, particularly AR amplification, identified with a liquid biopsy test and validated by [¹⁸F]-FDHT PET scan. This finding guided treatment with bipolar androgen therapy (BAT), which achieved a dramatic clinical response, reduced AR expression, improved symptoms, and restored sensitivity to enzalutamide. This case exemplifies the utility of serial liquid biopsies in uncovering mechanisms of tumor evolution and resistance, and the crucial role of cutting-edge diagnostics in personalized cancer treatment. Full article

Background: Drug–drug interactions (DDIs) may occur when two or more drugs are taken together, leading to undesired side effects or potential synergistic effects. Most clinical effects of drug combinations have not been assessed in clinical trials. Therefore, predicting DDIs can provide better patient management, avoid drug combinations that can negatively affect patient care, and exploit potential synergistic combinations to improve current therapies in women’s healthcare. Methods: A DDI prediction model was built to describe relevant drug combinations affecting reproductive treatments. Approved drug features (chemical structure of drugs, side effects, targets, enzymes, carriers and transporters, pathways, protein–protein interactions, and interaction profile fingerprints) were obtained. A unified predictive score revealed unknown DDIs between reproductive and commonly used drugs and their associated clinical effects on reproductive health. The performance of the prediction model was validated using known DDIs. Results: This prediction model accurately predicted known interactions (AUROC = 0.9876) and identified 2991 new DDIs between 192 drugs used in different female reproductive conditions and other drugs used to treat unrelated conditions. These DDIs included 836 between drugs used for in vitro fertilization. Most new DDIs involved estradiol, acetaminophen, bupivacaine, risperidone, and follitropin. Follitropin, bupivacaine, and gonadorelin had the highest discovery rate (42%, 32%, and 25%, respectively). Some were expected to improve current therapies (n = 23), while others would cause harmful effects (n = 11). We also predicted twelve DDIs between oral contraceptives and HIV drugs that could compromise their efficacy. Conclusions: These results show the importance of DDI studies aimed at identifying those that might compromise or improve their efficacy, which could lead to personalizing female reproductive therapies. Full article

Background: Thyroid eye disease (TED) is a rare autoimmune orbital disorder predominantly associated with Graves’ disease. It is characterized by orbital inflammation, tissue remodeling, and potential visual morbidity. Conventional therapies, particularly systemic glucocorticoids, offer only partial symptomatic relief, failing to reverse chronic structural changes such as proptosis and diplopia, and are associated with substantial adverse effects. This review aims to synthesize recent developments in understandings of TED pathogenesis and to critically evaluate emerging therapeutic strategies. Methods: A systematic literature review was conducted using MEDLINE, Embase, and international clinical trial registries focusing on pivotal clinical trials and investigational therapies targeting core molecular pathways involved in TED. Results: Current evidence suggests that TED pathogenesis is primarily driven by the autoimmune activation of orbital fibroblasts (OFs) through thyrotropin receptor (TSH-R) and insulin-like growth factor-1 receptor (IGF-1R) signaling. Teprotumumab, a monoclonal IGF-1R inhibitor and the first therapy approved by the U.S. Food and Drug Administration for TED, has demonstrated substantial clinical benefit, including improvements in proptosis, diplopia, and quality of life. However, concerns remain regarding relapse rates and treatment-associated adverse events, particularly hearing impairment. Investigational therapies, including next-generation IGF-1R inhibitors, small-molecule antagonists, TSH-R inhibitors, neonatal Fc receptor (FcRn) blockers, cytokine-targeting agents, and gene-based interventions, are under development. These novel approaches aim to address both inflammatory and fibrotic components of TED. Conclusions: Teprotumumab has changed TED management but sustained control and toxicity reduction remain challenges. Future therapies should focus on targeted, mechanism-based, personalized approaches to improve long-term outcomes and patient quality of life. Full article

The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling continuous patient monitoring, early diagnosis, and personalized treatments. However, the het-erogeneity of IoMT devices and the lack of standardized protocols introduce serious security vulnerabilities. To address these challenges, we propose a hybrid BiLSTM-DNN intrusion detection system, named HBiLD-IDS, that combines Bidirectional Long Short-Term Memory (BiLSTM) networks with Deep Neural Networks (DNNs), leveraging both temporal dependencies in network traffic and hierarchical feature extraction. The model is trained and evaluated on the CICIoMT2024 dataset, which accurately reflects the diversity of devices and attack vectors encountered in connected healthcare environments. The dataset undergoes rigorous preprocessing, including data cleaning, feature selection through correlation analysis and recursive elimination, and feature normalization. Compared to existing IDS models, our approach significantly enhances detection accuracy and generalization capacity in the face of complex and evolving attack patterns. Experimental results show that the proposed IDS model achieves a classification accuracy of 98.81% across 19 attack types confirming its robustness and scalability. This approach represents a promising solution for strengthening the security posture of IoMT networks against emerging cyber threats. Full article

The management of acute lymphoblastic leukemia (ALL), the most common pediatric malignancy, critically relies on thiopurine therapy, such as 6-mercaptopurine (6-MP), during the maintenance phase. However, significant inter-individual response variety and high risk of myelosuppression often disrupt therapy efficacy. Pharmacogenetics offer crucial strategies to personalized therapy. While thiopurine methyltransferase (TPMT) was initially the primary focus, the discovery of nudix hydrolase 15 (NUDT15) appears as a more comprehensive determinant of thiopurine intolerance. This review aims to consolidate and critically evaluate the advancement achieved in unraveling the biological mechanism and clinical significance of NUDT15 pharmacogenetics in thiopurine therapy. Foundational studies showed the vital role of NUDT15 in the detoxification of active thiopurines, with common genetic variants (for instance, p. Arg139Cys) significantly disrupting its activity, leading to the accumulation of toxic metabolites. Observational studies consistently associated NUDT15 variants with severe myelosuppression, notably in Asian populations. Recent randomized controlled trials (RCTs) confirmed that NUDT15 genotype-guided dosing effectively reduces thiopurine-induced toxicity without interfering with the therapeutic outcome. Despite these advancements, challenges remain present, including the incomplete characterization of rare variants, limited data in the diverse Asian populations, and the need for standardized integration with metabolite monitoring. In conclusion, NUDT15 pharmacogenetics is essential for improving patient safety and thiopurine dosage optimization in the treatment of ALL. For thiopurine tailored medicine to be widely and fairly implemented, future research should focus on increasing genetic data across different populations, improving the dose adjustment algorithm, and harmonizing therapeutic guidelines. Full article

Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal tract. Although the aetiology of IBD remains largely unknown, several studies suggest that an individual’s genetic susceptibility, external environmental factors, intestinal microbial flora, and immune responses are all factors involved in and functionally linked to the pathogenesis of IBD. Beyond the gastrointestinal manifestations, IBD patients frequently suffer from psychiatric comorbidities, particularly depression and anxiety. It remains unclear whether these disorders arise solely from reduced quality of life or whether they share overlapping biological mechanisms with IBD. This review aims to explore the bidirectional relationship between IBD and depressive disorders (DDs), with a focus on four key shared mechanisms: immune dysregulation, genetic susceptibility, alterations in gut microbiota composition, and dysfunction of the hypothalamic–pituitary–adrenal (HPA) axis. By examining recent literature, we highlight how these interconnected systems may contribute to both intestinal inflammation and mood disturbances. Furthermore, we discuss the reciprocal pharmacologic interactions between IBD and DDs: treatments for IBD, such as TNF-alpha and integrin inhibitors, have demonstrated effects on mood and anxiety symptoms, while certain antidepressants appear to exert independent anti-inflammatory properties, potentially reducing the risk or severity of IBD. Overall, this review underscores the need for a multidisciplinary approach to the care of IBD patients, integrating psychological and gastroenterological assessment. A better understanding of the shared pathophysiology may help refine therapeutic strategies and support the development of personalized, gut–brain-targeted interventions. Full article

Sleep disorders and stroke are intricately linked through a complex, bidirectional relationship. Sleep disturbances such as obstructive sleep apnea (OSA), insomnia, and restless legs syndrome (RLS) not only increase the risk of stroke but also frequently emerge as consequences of cerebrovascular events. OSA, in particular, is associated with a two- to three-fold increased risk of incident stroke, primarily through mechanisms involving intermittent hypoxia, systemic inflammation, endothelial dysfunction, and autonomic dysregulation. Conversely, stroke can disrupt sleep architecture and trigger or exacerbate sleep disorders, including insomnia, hypersomnia, circadian rhythm disturbances, and breathing-related sleep disorders. These post-stroke sleep disturbances are common and significantly impair rehabilitation, cognitive recovery, and quality of life, yet they remain underdiagnosed and undertreated. Early identification and management of sleep disorders in stroke patients are essential to optimize recovery and reduce the risk of recurrence. Therapeutic strategies include lifestyle modifications, pharmacological treatments, medical devices such as continuous positive airway pressure (CPAP), and emerging alternatives for CPAP-intolerant individuals. Despite growing awareness, significant knowledge gaps persist, particularly regarding non-OSA sleep disorders and their impact on stroke outcomes. Improved diagnostic tools, broader screening protocols, and greater integration of sleep assessments into stroke care are urgently needed. This narrative review synthesizes current evidence on the interplay between sleep and stroke, emphasizing the importance of personalized, multidisciplinary approaches to diagnosis and treatment. Advancing research in this field holds promise for reducing the global burden of stroke and improving long-term outcomes through targeted sleep interventions. Full article