Search Results (10,031)

Pain management in multiple trauma patients presents a complex clinical challenge due to competing priorities such as hemodynamic instability, polypharmacy, coagulopathy, and the urgency of life-saving interventions. In this context, peripheral nerve blocks (PNBs) are increasingly recognized as a valuable asset for their role in managing pain in patients with multiple traumatic injuries. By reducing reliance on systemic opioids, PNBs support effective pain control and facilitate early mobilization, aligning with enhanced recovery principles. This narrative review summarizes current evidence on the use of PNBs in the context of polytrauma, focusing on their analgesic efficacy, integration within multimodal analgesia protocols, and contribution to improved functional outcomes. Despite these advantages, clinical application is limited by specific concerns, including the potential to mask compartment syndrome, the risk of nerve injury or local anesthetic systemic toxicity (LAST), and logistical barriers in acute trauma settings. Emerging directions in the field include the refinement of ultrasound-guided PNB techniques, the expanded use of continuous catheter systems, and the incorporation of fascial plane blocks for anatomically complex or multisite trauma. Parallel efforts are focusing on the development of decision-making algorithms, improved risk stratification tools, and integration into multimodal analgesic pathways. There is also growing emphasis on standardized clinical protocols, simulation-based training, and patient education to enhance safety and consistency in practice. As evidence continues to evolve, the long-term impact of PNBs on functional recovery, quality of life, and healthcare utilization must be further explored. With thoughtful implementation, structured training, and institutional support, PNBs may evolve into a cornerstone of modern trauma analgesia. Full article

(1) Background: Early palliative care (EPC) is increasingly recognized as a key component of comprehensive cancer management, with evidence supporting improvements in quality of life, symptom control, and clinical outcomes in advanced malignancies. (2) Methods: This systematic review followed PRISMA 2020 guidelines and was prospectively registered in PROSPERO (CRD42024623219). We searched PubMed, Embase, and the Cochrane CENTRAL Library for randomized controlled trials (RCTs) evaluating EPC in adults with advanced, incurable, or metastatic cancer. Eligible studies reported on at least one of the following: overall quality of life, symptom burden, or disease progression indicators. (3) Results: Forty-one RCTs met inclusion criteria. Despite heterogeneity in timing and structure, EPC consistently improved quality of life and reduced symptom burden in advanced cancer patients, with 32 trials demonstrating significant clinical benefit. Some studies also reported slowed disease progression. However, several RCTs showed no significant effects, highlighting variation in outcomes, possible subgroup effects, and challenges in implementation. Definitions and delivery of EPC varied widely, particularly in timing, frequency, and integration into oncology care. (4) Conclusions: These findings support the integration of EPC alongside disease-directed treatments, challenging the misconception that palliative care is only appropriate at the end of life and reinforcing its role early in the cancer care continuum. Full article

Atherosclerosis is a progressive, multifactorial disease driven by the interplay of lipid dysregulation, chronic inflammation, oxidative stress, and maladaptive vascular remodeling. Despite advances in systemic lipid-lowering and anti-inflammatory therapies, residual cardiovascular risk persists, highlighting the need for more precise interventions. Targeted drug delivery represents a transformative strategy, offering the potential to modulate key pathogenic processes within atherosclerotic plaques while minimizing systemic exposure and off-target effects. Recent innovations span a diverse array of platforms, including nanoparticles, liposomes, exosomes, polymeric carriers, and metal–organic frameworks (MOFs), engineered to engage distinct pathological features such as inflamed endothelium, dysfunctional macrophages, oxidative microenvironments, and aberrant lipid metabolism. Ligand-based, biomimetic, and stimuli-responsive delivery systems further enhance spatial and temporal precision. In parallel, advances in in-silico modeling and imaging-guided approaches are accelerating the rational design of multifunctional nanotherapeutics with theranostic capabilities. Beyond targeting lipids and inflammation, emerging strategies seek to modulate immune checkpoints, restore endothelial homeostasis, and reprogram plaque-resident macrophages. This review provides an integrated overview of the mechanistic underpinnings of atherogenesis and highlights state-of-the-art targeted delivery systems under preclinical and clinical investigation. By synthesizing recent advances, we aim to elucidate how precision-guided drug delivery is reshaping the therapeutic landscape of atherosclerosis and to chart future directions toward clinical translation and personalized vascular medicine. Full article

Background: Clinical assessment of balance and postural disorders is usually carried out through several common practices including tests such as the Subjective Visual Vertical (SVV) and Limit of Stability (LOS). Nowadays, several cutting-edge technologies have been proposed as supporting tools for stability evaluation. Extended Reality (XR) emerges as a powerful instrument. This proof-of-concept study aims to assess the feasibility and potential clinical utility of a novel MR-based framework integrating HoloLens 2, Wii Balance Board, and Azure Kinect for multimodal balance assessment. An innovative test is also introduced, the Innovative Dynamic Balance Assessment (IDBA), alongside an MR version of the SVV test and the evaluation of their performance in a cohort of healthy individuals. Results: All participants reported SVV deviations within the clinically accepted ±2° range. The IDBA results revealed consistent sway and angular profiles across participants, with statistically significant differences in posture control between opposing target directions. System outputs were consistent, with integrated parameters offering a comprehensive representation of postural strategies. Conclusions: The MR-based framework successfully delivers integrated, multimodal measurements of postural control in healthy individuals. These findings support its potential use in future clinical applications for balance disorder assessment and personalized rehabilitation. Full article

The epidermal growth factor receptor (EGFR) is a key target for both cancer diagnosis and therapeutic interventions. Assessing EGFR expression before therapy has become routine in clinical practice, yet current methods like biopsy and immunohistochemistry (IHC) have significant limitations, including invasiveness, limited repeatability, and lack of real-time, whole-body data. EGFR-targeted imaging has emerged as a promising alternative. EGFR-targeting peptides, owing to their favorable physicochemical properties and versatility, are increasingly being explored for a variety of applications, including molecular imaging, drug delivery, and targeted therapy. Recent advances have demonstrated the potential of EGFR-targeting peptides conjugated to imaging probes for non-invasive, real-time in vivo tumor detection, precision therapy, and surgical guidance. Here, we provide a comprehensive overview of the latest progress in EGFR-targeting peptides development, with a particular focus on their application in the development of molecular imaging agents, including fluorescence imaging, PET/CT, magnetic resonance imaging, and multimodal imaging. Furthermore, we examine the challenges and future directions concerning the development and clinical application of EGFR-targeting peptide-based imaging probes. Finally, we highlight emerging technologies such as artificial intelligence, mutation-specific peptides, and multimodal imaging platforms, which offer significant potential for advancing the diagnosis and treatment of EGFR-targeted cancers. Full article

Epileptic seizure prediction remains a critical challenge in neuroscience and healthcare, with profound implications for enhancing patient safety and quality of life. In this paper, we introduce a novel seizure prediction method that leverages electroencephalogram (EEG) data, combining discrete wavelet transform (DWT)-based time–frequency analysis, advanced feature extraction, and deep learning using Fourier neural networks (FNNs). The proposed approach extracts essential features from EEG signals—including entropy, power, frequency, and amplitude—to effectively capture the brain’s complex and nonstationary dynamics. We measure the method based on the broadly used CHB-MIT EEG dataset, ensuring direct comparability with prior research. Experimental results demonstrate that our DWT-FS-FNN model achieves a prediction accuracy of 98.96 with a zero false positive rate, outperforming several state-of-the-art methods. These findings underscore the potential of integrating advanced signal processing and deep learning methods for reliable, real-time seizure prediction. Future work will focus on optimizing the model for real-world clinical deployment and expanding it to incorporate multimodal physiological data, further enhancing its applicability in clinical practice. Full article

Osteosarcoma (OS) is the most common primary bone malignancy in children and adolescents, which is also considered an aggressive disease due to its rapid growth rate, ability to metastasize early, and complex and heterogeneous tumor microenvironment (TME). Although we are developing improved surgical and chemotherapeutic approaches, the presence of metastatic or recurrent disease is still detrimental to the patient’s outcome. Major advances in understanding the molecular mechanisms of OS are needed to substantially improve outcomes for patients being treated for OS. This review integrates new data on the molecular biology, pathophysiology, and immune landscape of OS, as well as introducing salient areas of tumorigenesis underpinning these findings, such as chromothripsis; kataegis; cancer stem cell dynamics; and updated genetic, epigenetic, and glycosylation modifiers. In addition, we review promising biomarkers, diagnostic platforms, and treatments, including immunotherapy, targeted small molecule inhibitors, and nanomedicine. Using genomic techniques, we have defined OS for its significant genomic instability due to TP53 and RB1 mutations, chromosomal rearrangements, and aberrant glycosylation. The TME is also characterized as immunosuppressive and populated by tumor-associated macrophages, myeloid-derived suppressor cells, and regulatory T cells, ultimately inhibiting immune checkpoint inhibitors. Emerging fields such as glycomics and epigenetics, as well as stem cell biology, have defined promising biomarkers and targets. Preclinical studies have identified that glycan-directed CAR therapies could be possible, as well as metabolic inhibitors and 3D tumor models, which presented some preclinical success and could allow for tumoral specificity and enhanced efficacy. OS is a biologically and clinically complex disease; however, advances in exploring the molecular and immunologic landscape of OS present new opportunities in biomarkers and the development of new treatment options with adjunctive care. Successful treatments in the future will require personalized, multi-targeted approaches to account for tumor heterogeneity and immune evasion. This will help us turn the corner in providing improved outcomes for patients with this resilient malignancy. Full article

Background/Objectives: Curcumin (CUR) is well known for its therapeutic properties, particularly attributed to its antioxidant and anti-inflammatory effects in managing chronic diseases such as arthritis. While CUR application for biomedical purposes is well known, the phytochemical has several restrictions given its poor water solubility, physicochemical instability, and low bioavailability. These limitations have led to innovative formulations, with nanocarriers emerging as a promising alternative. For this reason, this study aimed to address the potential advantages of associating CUR with nanocarrier systems in managing arthritis through a scoping review. Methods: A systematic literature search of preclinical (in vivo) and clinical studies was performed in PubMed, Scopus, and Web of Science (December 2024). General inclusion criteria include using CUR or natural derivatives in nano-based formulations for arthritis treatment. These elements lead to the question: “What is the impact of the association of CUR or derivatives in nanocarriers in treating arthritis?”. Results: From an initial 536 articles, 34 were selected for further analysis (31 preclinical investigations and three randomized clinical trials). Most studies used pure CUR (25/34), associated with organic (30/34) nanocarrier systems. Remarkably, nanoparticles (16/34) and nanoemulsions (5/34) were emphasized. The formulations were primarily presented in liquid form (23/34) and were generally administered to animal models through intra-articular injection (11/31). Complete Freund’s Adjuvant (CFA) was the most frequently utilized among the various models to induce arthritis-like joint damage. The findings indicate that associating CUR or its derivatives with nanocarrier systems enhances its pharmacological efficacy through controlled release and enhanced solubility, bioavailability, and stability. Moreover, the encapsulation of CUR showed better results in most cases than in its free form. Nonetheless, most studies were restricted to the preclinical model, not providing direct evidence in humans. Additionally, inadequate information and clarity presented considerable challenges for preclinical evidence, which was confirmed by SYRCLE’s bias detection tools. Conclusions: Hence, this scoping review highlights the anti-arthritic effects of CUR nanocarriers as a promising alternative for improved treatment. 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

Prostate cancer (PC) remains a leading cause of malignancy in men worldwide, with current diagnostic methods such as prostate-specific antigen (PSA) testing and tissue biopsies facing limitations in specificity, invasiveness, and ability to capture tumor heterogeneity. Liquid biopsy, especially analysis of circulating tumor DNA (ctDNA), has emerged as a transformative tool for non-invasive detection, real-time monitoring, and treatment selection for PC. This review examines the role of ctDNA in both localized and metastatic PCs, focusing on its utility in early detection, risk stratification, therapy selection, and post-treatment monitoring. In localized PC, ctDNA-based biomarkers, including ctDNA fraction, methylation patterns, fragmentation profiles, and mutations, demonstrate promise in improving diagnostic accuracy and predicting disease recurrence. For metastatic PC, ctDNA analysis provides insights into tumor burden, genomic alterations, and resistance mechanisms, enabling immediate assessment of treatment response and guiding therapeutic decisions. Despite challenges such as the low ctDNA abundance in early-stage disease and the need for standardized protocols, advances in sequencing technologies and multimodal approaches enhance the clinical applicability of ctDNA. Integrating ctDNA with imaging and traditional biomarkers offers a pathway to precision oncology, ultimately improving outcomes. This review underscores the potential of ctDNA to redefine PC management while addressing current limitations and future directions for research and clinical implementation. 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

Background: In high-risk and frail patients with multivessel coronary artery disease (MV CAD), guidelines indicated complete revascularization with or without the use of cardiopulmonary bypass (CPB) bears a high morbidity and mortality risk. In cases where catheter interventions were deemed unsuitable and conventional coronary artery bypass grafting (CABG) posed an unacceptable perioperative risk, patients were scheduled for minimally invasive direct coronary artery bypass (MIDCAB) grafting or minimally invasive multivessel coronary artery bypass grafting (MICS-CABG). We called this approach “palliative revascularization.” This study assesses the safety and impact of palliative revascularization on clinical outcomes and overall survival. Methods: A consecutive series of 57 patients undergoing MIDCAB or MICS-CABG as a palliative surgery between 2008 and 2018 was included. The decision for palliative surgery was met in heart team after carefully assessing each case. The patients underwent single or double-vessel revascularization using the left internal thoracic artery and rarely radial artery/saphenous vein segments, both endoscopically harvested. Inpatient data could be completed for all 57 patients. The mean follow-up interval was 4.2 ± 3.7 years, with a follow-up rate of 91.2%. Results: Mean patient age was 79.7 ± 7.4 years. Overall, 46 patients (80.7%) were male, 26 (45.6%) had a history of atrial fibrillation and 25 (43.9%) of chronic kidney disease. In total, 13 patients exhibited a moderate EuroSCORE II, while 27 were classified as high risk, with a EuroSCORE II exceeding 5%. Additionally, 40 patients (70.2%) presented with three-vessel disease, 17 (29.8%) suffered an acute myocardial infarction within three weeks prior to surgery and 50.9% presented an impaired ejection fraction. There were 48 MIDCAB and nine MICS CABG with no conversions either to sternotomy or to CPB. Eight cases were planned as hybrid procedures and only 15 patients (26.3%) were completely revascularized. During the first 30 days, four patients (7%) died. A myocardial infarction occurred in only one case, no patient necessitated immediate reoperation. The one-, three- and five-year survival rates were 83%, 67% and 61%, respectively. Conclusions: MIDCAB and MICS CABG can be successfully conducted as less invasive palliative surgery in high-risk multimorbid patients with MV CAD. The early and mid-term results were better than predicted. A higher rate of hybrid procedures could improve long-term outcome in selected cases. Full article

Acute kidney injury (AKI) is a serious clinical condition that is linked to markedly higher rates of morbidity and mortality in cirrhosis patients. Its diagnosis is challenging due to overlapping clinical and laboratory features among causes such as hepatorenal syndrome (HRS), acute tubular injury (ATI), and prerenal hypovolemia. In order to address the distinct pathophysiology and clinical context of cirrhosis, the definitions and classification of AKI have changed over time, moving from RIFLE and AKIN to KDIGO and ICA-AKI. Because cirrhosis patients have altered muscle mass and fluid retention, traditional markers like serum creatinine (sCr) and urine output have significant limitations. Neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), and cystatin C (CysC) are some of the new biomarkers that have shown promise in early AKI detection and in differentiating structural from functional kidney injury. NGAL and KIM-1 are sensitive indicators of tubular damage with potential prognostic implications. IL-18 reflects inflammatory injury, and CysC offers a more reliable measure of glomerular filtration. Incorporating these markers may improve early diagnosis, risk stratification, and treatment decisions, representing a key direction for future research in managing AKI in cirrhosis. Full article

Objectives: Paratubal cysts (PTCs) are embryological remnants and are potentially hormonally responsive. Since hyperandrogenism (HA) is representative of polycystic ovary syndrome (PCOS), we examined whether biochemical hyperandrogenism is associated with PTCs in women with PCOS and if body mass index (BMI) and insulin resistance (IR) mediate this association. Methods: This retrospective study included 577 women diagnosed with PCOS at a tertiary academic center from 2010 to 2018. Clinical data included age at diagnosis, BMI, and diagnoses of hypertension, non-alcoholic fatty liver disease, and metabolic syndrome. Laboratory measures included total testosterone, sex hormone-binding globulin, anti-Müllerian hormone, luteinizing hormone, fasting glucose, insulin, and triglycerides (TG). Derived indices included a free androgen index (FAI), homeostasis model assessment of insulin resistance (HOMA-IR), and fasting glucose-to-insulin ratio. PTCs were identified through imaging or surgical findings. Structural equation modeling (SEM) assessed direct and indirect relationships between FAI, BMI, HOMA-IR, and PTCs, while adjusting for diagnostic age. Results: PTCs were identified in 2.77% of participants. BMI, FAI, TG, and IR indices were significantly higher for women with PTCs than those without PTCs. SEM revealed significant indirect effects of FAI on PTCs via BMI and HOMA-IR. The direct effect was negative, resulting in a non-significant total effect. A sensitivity model using HOMA-IR as the predictor showed a significant direct effect on PTCs without mediation via FAI. Conclusions: Biochemical HA may influence PTC development in PCOS through metabolic pathways, establishing the need to consider metabolic context when evaluating adnexal cysts in hyperandrogenic women. Full article