Search Results (1,474)

In the era of precision medicine, managing non-small cell lung cancer (NSCLC) requires pathological confirmation, accurate nodal staging, and comprehensive biomarker profiling performed rapidly and concurrently. In the 9th edition of the TNM classification, the N2 category is subdivided into single-station (N2a) and multistation (N2b) subcategories, highlighting the clinical importance of precise mediastinal staging. This refinement necessitates systematic nodal evaluation using minimally invasive modalities such as endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) to appropriately stratify patients for surgery, neoadjuvant therapy, and definitive chemoradiotherapy. Concurrently, although N1 has not been formally subclassified because of the lack of standardized clinical diagnostic criteria, the increasing use of sublobar resection for early-stage NSCLC requires more precise hilar and intrapulmonary nodal assessments, which can potentially be facilitated by emerging technologies such as thin convex-probe EBUS. Concurrently, adequate tissue acquisition is essential for timely biomarker testing. Before administering neoadjuvant immune checkpoint inhibitors, actionable driver alterations, such as epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements, must be identified to select appropriate treatment and prevent severe sequential toxicities associated with subsequent targeted therapies. This review highlights the indispensable role of endoscopic nodal staging and multidisciplinary collaboration in adapting to the updated TNM classification and optimizing personalized treatment strategies for patients with NSCLC. Full article

Medulloblastoma is a heterogeneous solid tumor, and its molecular characteristics are the most important prognostic factors for this neoplasm. Unfortunately, the molecular classification of MB-G3 and MB-G-4 medulloblastoma is very complex because of molecular similarity. Therefore, in this work, through unsupervised machine learning-based gene expression profiling, we identified a low molecular profile associated with four molecular groups of medulloblastoma. We performed medulloblastoma expression microarray data mining via the Partek Genomics Suite and Transcriptome Analysis Console (TAC), and we included a total of 25 fresh medulloblastoma tumors that were obtained and hybridized into HG U133 Plus 2.0 Array microarrays. To identify the molecular groups of the 25 patients, we compared them against classified patients, which were obtained from free repositories, and through data mining based on gene expression, compared the expression profiles of our patients. To do so, we performed an analysis via the least squares method via PCA. The molecular groups MB-WNT and MB-SHH were confirmed via immunohistochemistry via β-catenin, YAP1 and GAB1 antibodies in tissue fixed in formalin and embedded in paraffin, and another tissue section was placed on a Visium Spatial slide to perform spatial RNA-seq via Illumina NextSeq 2000 platform sequencers. The data obtained were analyzed with R. We identified the expression profiles associated with the four molecular groups and formed a reference set. Through unsupervised analysis via the least squares method, we assigned the molecular profiles of 25 patients with medulloblastoma, via the integration of bulk and spatial tumor molecular gene expression profiling analysis and with immunohistochemical findings, this strategy was fast and accurate. We observed correlations in three of the trials carried out and, in part, in one study, a patient who presented two tumor strains and two molecular signatures (SHH and G4), which led us to believe that this patient presented mixed phenotypic characteristics. Multigene expression profile analysis of medulloblastoma represents a significant advance in precision medicine; integrating different layers of transcriptomic information allows us to demonstrate underlying molecular changes in the four molecular groups that are essential for personalized therapy. Full article

Surface-enhanced Raman spectroscopy (SERS) has emerged as a transformative tool in biomedical diagnostics, offering a highly sensitive and non-invasive method for detecting molecular biomarkers at exceptionally low concentrations. This approach takes advantage of the plasmonic characteristics of customized metallic nanostructures that produce intense localized electromagnetic fields via localized surface plasmon resonance and facilitate electron transfer reactions that notoriously enhance the intrinsically weak Raman scattering signals of molecular entities which reside on or next to their surfaces. SERS-based assays have shown remarkable potential in detecting cancer biomarkers, circulating tumor DNA (ctDNA), and proteins at early stages, enabling timely and targeted intervention. Additionally, the combination of SERS with AI-driven data analysis has facilitated real-time diagnostics, enhancing the precision and efficiency of point-of-care testing. Despite its promising capabilities, challenges such as substrate fouling, signal degradation, and the need for better biocompatibility remain. Nevertheless, ongoing research in substrate development, coupled with advances in AI, positions SERS as a leading technology for future diagnostic tools. This paper explores the current state of SERS in biomedical applications, highlighting its potential to revolutionize diagnostics and personalized medicine while addressing the existing limitations and future research directions. Full article

(1) Background: The global prevalence of myopia has increased substantially in recent decades. Myopia development is influenced by both environmental factors and a complex genetic architecture involving more than 400 susceptibility loci. The interaction between genetic predisposition and environmental exposures plays a critical role in myopia onset and progression. Unequal access to preventive strategies and eye care services continue to limit effective global myopia control. (2) Methods: This structured narrative review synthesizes evidence identified through systematic database searches, manual reference screening, prospective cohort studies, randomized controlled trials, mechanistic investigations, and genetic analyses identified through the literature search. (3) Results: Environmental factors such as limited outdoor activity, intensive near-work, and academic pressure contribute to myopia progression. Key biometric indicators, such as AL, AL/CR ratio, and choroidal thinning, are strong predictors. Molecular and cellular mechanisms also contribute significantly to myopia progression. Genetics also plays a significant role, with both syndromic and polygenic pathways involved. (4) Conclusions: As precision medicine evolves, individualized therapeutic strategies are becoming important in myopia management. In the treatment of myopia, biomarkers, genetic profiling, and artificial intelligence may support personalized risk assessment and treatment decisions. Full article

Inflammatory bowel diseases (IBD), including Crohn’s disease and ulcerative colitis, are characterized by marked heterogeneity, challenging disease monitoring and individualized treatment. Despite advances in treat-to-target strategies, unmet needs persist, particularly in assessing transmural healing and optimizing therapeutic decisions. This narrative review evaluates the role of intestinal ultrasound (IUS) as a key tool for precision medicine in IBD. IUS is a non-invasive, repeatable, and cost-effective imaging modality with diagnostic accuracy comparable to endoscopy and magnetic resonance enterography, with reported sensitivities and specificities frequently exceeding 80–90% for detecting active disease. It enables real-time assessment of transmural inflammation and complications, while parameters such as bowel wall thickness and Doppler vascularity support prognostic stratification. Early reductions in bowel wall thickness (≥25–30%) have been associated with improved treatment response, allowing identification of responders within weeks of therapy initiation. IUS informs therapeutic decision-making, including initiation, optimization, and de-escalation of advanced therapies, and may reduce reliance on invasive procedures. Integration into routine care has been associated with improved disease control and cost-effectiveness. Standardization of protocols, operator training, and prospective validation are required to establish IUS as a cornerstone of precision medicine in IBD. Full article

Theranostics is a novel approach that integrates diagnostic and therapeutic efficacy on a single platform, holding great promise for precision medicine by enabling real-time monitoring of disease progression and therapeutic response. Despite significant advances, the successful development and delivery of theranostic systems are critically limited by multiple biological barriers present at systemic, tissue, cellular, anatomical, and immunological levels. These barriers restrict bioavailability, target accessibility, and therapeutic efficacy, while often increasing off-target accumulation and adverse effects. This review provides a comprehensive overview of the major biological barriers encountered in theranostic development, including physiological barriers such as plasma protein binding, renal clearance, and hepatic metabolism; anatomical barriers like endothelial linings, the blood–brain barrier (BBB), and the tumor microenvironment; cellular barriers involving membrane permeability, intracellular trafficking, and endo-lysosomal entrapment; and immunological barriers such as immune recognition, inflammatory responses, and complement activation. Special emphasis is placed on the BBB, highlighting its structural complexity, transport mechanisms, and strategies such as molecular Trojan-horse technology, receptor-mediated and adsorptive-mediated transcytosis, and nanocarrier-based approaches to enhance central nervous system delivery. The review further discusses targeted delivery challenges, including receptor heterogeneity and multidrug resistance, and critically evaluates current strategies to overcome these barriers through surface functionalization, stimuli-responsive systems, biomimetic carriers, and controlled-release mechanisms. Finally, recent advances, clinical challenges, and future perspectives—including personalized theranostics, artificial intelligence—assisted design, and next-generation barrier-penetrating systems—are explored. Overall, this review aims to provide a structured understanding of biological barriers in theranostics and highlight innovative approaches to improve their translational potential. Full article

Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor remains the cornerstone of antithrombotic management after myocardial revascularization. However, the traditional “one-size-fits-all” approach to DAPT duration and intensity fails to account for marked interindividual variability in drug response—driven by genetic polymorphisms, notably CYP2C19 variants like CYP2C19*2, which reach a frequency of up to 75% in specific groups like the Melanesian population—comorbidities such as diabetes and chronic kidney disease, and dynamic clinical factors including age and concomitant medications. We examine the current landscape of precision medicine tools for individualizing DAPT, including platelet function testing, point-of-care genotyping, validated clinical risk scores, and emerging artificial intelligence (AI)–based predictive models. Evidence from landmark trials is synthesized to evaluate escalation, de-escalation, and duration-tailoring strategies within the ischemic–bleeding trade-off framework. Special populations requiring individualized approaches are reviewed, including patients with atrial fibrillation, the elderly, and those requiring urgent noncardiac surgery with perioperative bridging. Future directions, including multi-omics integration, novel antiplatelet agents, and AI-driven clinical decision support systems, are also explored. As a narrative review, conclusions should be interpreted as reflective of current evidence synthesis rather than systematic-review-grade evidence, given the absence of formal risk-of-bias scoring or meta-analytic pooling. Personalized DAPT guided by complementary genetic and phenotypic testing, integrated with dynamic risk stratification, offers a paradigm shift from empiric therapy toward precision-guided antithrombotic management with the potential to simultaneously reduce ischemic and bleeding complications. Full article

Background/Objectives: With the increasing incidence of drug counterfeiting and the emergence of personalized medicine, the need for unique marking of solid dosage forms, e.g., tablets, has attracted considerable interest in the current research and development landscape. Besides traditional printing methods, laser marking offers several advantages, as it eliminates the need for organic solvents and enables the generation of precise patterns. However, laser exposure may raise safety concerns regarding the stability of photosensitive drugs in the irradiated dosage forms. Therefore, the aim of the present study was to test the photoprotective effect of titanium dioxide (TiO₂) and its various alternatives, e.g., talc, calcium carbonate (CaCO₃), zinc oxide (ZnO), and black iron oxide (Fe₃O₄), alongside a ready-to-use reference formulation, Opadry^® Brown, which contains TiO₂ (titanium-containing, TC) on nifedipine, a light-sensitive model drug. Methods: Laser marking or short-term laser ablation at different wavelengths (193 nm, 248 nm, 532 nm, and 781 nm) was applied to different coating formulations. As a positive control, prolonged exposure to daylight was applied. The properties and photostability of these formulations were evaluated using several analytical methods (i.e., surface profilometry, Raman spectroscopy, and high-performance liquid chromatography (HPLC)). Results: The TiO₂, ZnO, Fe₃O₄, and Opadry^® TC Brown coatings maintained their color during the long-term study under all conditions. Furthermore, the prepared formulations exhibited different ablation depths and morphological changes depending on the coating and laser type. HPLC measurements confirmed significant differences in the protective ability of various pigments against sunlight and different types of lasers. Nevertheless, the obtained Raman spectra were not in complete agreement with HPLC results, which can be attributed to spectral overlap between key nifedipine degradation markers and excipient signals in the tablet core. Conclusions: Overall, laser treatment of tablets containing photosensitive drugs may induce API decomposition; however, this effect can be minimized or avoided by careful selection of the appropriate combination of laser type and photoprotective pigment. Under the applied experimental conditions, Ti:Sa laser treatment was associated with the lowest degree of nifedipine degradation among all formulations, while ZnO-containing coatings demonstrated the most consistent photoprotective performance against the majority of the tested laser types, while Fe₃O₄-containing coatings provided superior protection during prolonged sunlight exposure and Nd:YAG laser irradiation. Full article

Pediatric drug therapy remains fundamentally challenged by profound interindividual variability driven by dynamic development, genetic, and environmental factors. Although dosing strategies based on age, body weight, or body surface area remain important starting points in pediatric pharmacotherapy, they may not fully capture ontogeny-dependent variability in drug disposition and response. Consequently, clinically relevant differences in efficacy and toxicity may still occur among children receiving similar weight-adjusted doses. Pharmacogenomics offers a promising framework for individualized therapy; however, its clinical translation in pediatrics is limited by developmental variability in gene expression and enzyme activity. Emerging evidence highlights the pivotal role of epigenetic regulation, including DNA methylation, histone modifications, and microRNAs, in modulating pharmacogenetic expression across developmental stages, thereby reshaping drug response trajectories. Concurrently, advances in artificial intelligence and next-generation sequencing enable integration of multidimensional datasets, facilitating predictive modeling of drug efficacy and toxicity. This narrative review provides a comprehensive synthesis of developmental pharmacology, pharmacogenomics, and epigenetic mechanisms, while critically evaluating current translational gaps and implementation challenges. Importantly, it proposes an integrative precision framework that incorporates genetic, epigenetic, and computational insights to optimize pediatric pharmacotherapy. By bridging mechanistic biology with emerging digital health technologies, this work advances a paradigm shift from empirical prescribing toward predictive, adaptive, and individualized therapeutic strategies. The proposed approach holds significant potential to enhance clinical outcomes, minimize adverse effects, and accelerate the realization of precision medicine in pediatric populations. Full article

Background: Digital twins and patient-specific computational models are emerging technologies in healthcare, enabling predictive, personalized, and adaptive interventions. Their integration with artificial intelligence (AI) facilitates the simulation of clinical scenarios, optimization of treatment strategies, and advancement of precision medicine. Despite growing interest, the evidence base is still evolving, highlighting the need for a comprehensive synthesis to identify current trends, applications, and gaps. Methods: A narrative review was conducted using PubMed, Web of Science, and Scopus to identify relevant literature on digital twins in healthcare. Priority was given to systematic reviews and meta-analyses in the selection process. From this process, 28 studies were selected for in-depth analysis, and their findings were complemented by primary research and conceptual, and synthesized evidence to capture emerging trends and real-world applications. Results and Discussion: The analysis revealed that digital twins are increasingly applied for patient-specific monitoring, predictive simulations, and adaptive interventions. Integration with AI enhances their ability to model complex clinical scenarios and support precision medicine. While the selected systematic reviews provide consolidated evidence of established applications, the complementary analysis indicates that these studies actively contribute to stabilizing clinical evidence, consolidating knowledge, and enabling the development of more robust patient-specific strategies. Conclusions: Digital twins are progressively shaping patient-centered healthcare by combining AI-driven simulations with clinical insights. Current research is not only consolidating existing evidence but also exploring novel applications, underscoring the potential of digital twins to enhance precision medicine. Further studies are required to fully integrate these technologies into routine clinical practice. Full article

Inflammation plays a central role in the pathogenesis and progression of cardiovascular diseases, including atherosclerosis, myocardial infarction and heart failure. Despite advances in conventional diagnostic and therapeutic strategies, limitations in sensitivity, specificity and targeted drug delivery still remain. Nanomedicine has emerged as a promising yet underexplored approach to address these challenges by enabling precise molecular imaging and site-specific therapeutic interventions. This review summarizes current and emerging nanotechnology-based approaches for the diagnosis and treatment of cardiovascular inflammation, highlighting their potential in clinical practice and remaining challenges. In addition, recent advances, including the development of biomimetic nanoplatforms, are discussed, along with future perspectives and the potential integration of artificial intelligence to further enhance precision in cardiovascular medicine. Full article

Head and neck squamous cell carcinoma (HNSCC) remains one of the most aggressive and heterogeneous malignancies worldwide, characterized by high rates of locoregional recurrence, metastatic dissemination, and therapeutic resistance. Angiogenesis plays a central role in tumor progression by supporting vascular remodeling, hypoxia adaptation, invasion, immune evasion, and metastatic spread. In HNSCC, angiogenic activation is regulated through complex interactions involving hypoxia-inducible factors, vascular endothelial growth factor (VEGF) signaling, stromal remodeling, inflammatory pathways, and epigenetic mechanisms within the tumor microenvironment. Recent evidence has also highlighted the role of non-coding RNAs, particularly microRNAs, and exosome-mediated communication in modulating angiogenic and immune-related signaling pathways. Although antiangiogenic therapies, including monoclonal antibodies and tyrosine kinase inhibitors, have demonstrated biological activity in HNSCC, their clinical efficacy remains limited by tumor heterogeneity, adaptive resistance mechanisms, toxicity, and the lack of validated predictive biomarkers. Several emerging therapeutic strategies are under preclinical or early clinical investigation in HNSCC, including miRNA-based approaches, nanoparticle-assisted delivery systems, vascular normalization concepts, and combinations with immune checkpoint inhibitors; however, robust clinical evidence for most of these strategies remains limited, and their translation to routine practice requires further validation. This review provides a comprehensive overview of the molecular mechanisms regulating angiogenesis in HNSCC and critically discusses current and emerging pharmacological strategies targeting these pathways. Particular emphasis is placed on VEGF/VEGFR signaling, the integration of miRNA and exosome biology, resistance mechanisms, and translational perspectives for biomarker-guided personalized therapy. The novelty of this review lies in the systematic integration of miRNA- and exosome-mediated angiogenic regulation, therapeutic resistance pathways, and precision medicine strategies into a unified pharmacological framework, addressing gaps not fully covered by prior reviews focused primarily on VEGF-targeted agents. Full article

Background/Objectives: Alzheimer’s disease (AD) disproportionately affects women, who account for nearly two-thirds of affected individuals worldwide. This sex imbalance cannot be explained by longevity alone and likely reflects complex interactions among biological sex, endocrine aging, genetic susceptibility, and brain-specific mechanisms of vulnerability. Neuroimaging has played a pivotal role in characterizing these sex-related differences in vivo, enabling the assessment of amyloid-β deposition, tau propagation, neurodegeneration, cerebral glucose metabolism, and network reorganization. This invited review examines AD through a rigorously sex-specific neuroimaging perspective, with particular emphasis on implications for women’s brain health. Methods: We integrated evidence from structural MRI, FDG-PET, amyloid-PET, tau-PET, estrogen receptor PET, diffusion MRI, and fluid biomarkers, together with epidemiological, molecular, genetic, and endocrine studies. The review focuses on female-specific trajectories of AD initiation and progression, highlighting the contribution of neuroendocrine aging, menopause, metabolic dysfunction, and sex-modulated genetic risk factors. Results: Available evidence indicates that women exhibit distinct biological and neuroimaging signatures across the AD continuum. Menopause emerges as a critical neuroendocrine transition associated with metabolic decline, altered brain connectivity, increased amyloid and tau vulnerability, and progressive neurodegeneration. Female-specific patterns of tau propagation and sex-dependent interactions with genetic risk factors further contribute to differential disease trajectories. Advanced multimodal neuroimaging approaches have substantially improved the characterization of these mechanisms and their relationship with cognitive decline and clinical progression. Conclusions: A sex-specific neuroimaging framework is essential to improve understanding of AD pathophysiology and to advance precision medicine approaches tailored to women’s brain health. Recognition of endocrine aging and female-specific biological vulnerability may inform earlier identification of at-risk individuals and the development of targeted prevention and treatment strategies. Future research should prioritize sex-aware longitudinal studies and multimodal biomarker integration to optimize personalized interventions in AD. Full article

Background/Objectives: Embryo implantation is a highly regulated, multistep process requiring precise synchronization between a developmentally competent blastocyst and a receptive endometrium. Despite advances in reproductive medicine, implantation failure remains a major limiting factor in assisted reproductive technology (ART), particularly in cases of recurrent implantation failure (RIF). This review aims to summarize current knowledge on the molecular, cellular, and immunological mechanisms governing embryo–endometrial interaction and to evaluate contemporary strategies for optimizing implantation outcomes. Methods: This narrative review synthesizes the current literature on embryo implantation, including studies addressing uterine receptivity, etiological factors contributing to implantation failure, and emerging diagnostic and therapeutic approaches. The review integrates findings from molecular biology, clinical ART practices, and bioengineering-based models. Key areas include transcriptomic tools such as endometrial receptivity analysis, time-lapse imaging, artificial-intelligence-based embryo selection, and advanced in vitro models (e.g., microfluidic “womb-on-a-chip” systems and three-dimensional embryo–endometrial platforms). The literature was identified through major biomedical databases, following a structured but non-systematic approach. Results: Implantation success is dependent on a complex interplay of hormonal regulation, gene expression, immune modulation, and embryo quality. Disruption of uterine receptivity during the window of implantation is a critical contributor to infertility and RIF. Multiple factors—including genetic abnormalities, maternal age, lifestyle influences, immunological imbalance, uterine pathology, and chronic endometrial conditions—are implicated in implantation failure. Emerging technologies, such as AI-assisted embryo selection, transcriptomic profiling, and advanced in vitro implantation models, provide enhanced insight into implantation dynamics and offer potential for improved clinical outcomes. Conclusions: Advances in understanding embryo implantation and the development of innovative diagnostic and therapeutic technologies hold significant promise for improving reproductive success. However, further research, validation, and standardization are required before these approaches can be fully integrated into routine clinical practice. A more personalized and mechanism-based approach to implantation may ultimately enhance ART outcomes and reduce the burden of infertility. Full article

The emergence and increasing use of artificial intelligence (AI) in healthcare have paved the way for highly personalized and time-saving approaches in the field of precision medicine. It can be applied to determine a prognosis, diagnosis, and recommended treatment, and may also be used for patient monitoring. As AI applications become more widely available, reliable and easy to use, they are rapidly reshaping the traditional roles of professionals and patients in the therapeutic relationship. On the positive side, professionals may have more time to communicate with patients and provide individualized care, whereas patients may become more empowered and autonomous due to AI-facilitated personalized information and monitoring. On the negative side, AI applications threaten to reduce the role of professionals to a mediating one in clinical decision-making, provide patients with misinformation, and lead to misunderstandings that hinder patients’ autonomy. In this narrative review, we examine the main ethical issues related to the AI-induced shift in roles in the therapeutic relationship, within four inter-related themes: the validity of claims that algorithms outperform humans in certain tasks; the ways in which AI saves time for health professionals but also takes time to properly explain and implement; the issues of trust and accountability, especially if AI suggestions lead to patient harm; and what AI’s alleged cost-effectiveness means for professionals’ employment and remuneration. Across the three roles, we find a common pattern: AI tends to absorb the technical and data-processing parts of clinical work while leaving its relational core to humans. Physicians move toward oversight and interpretation, nurses retain the attentiveness and responsiveness that define care, and patients gain tools for self-management that can widen autonomy or, left unguided, erode it. Whether the overall effect is benign depends less on the technology than on how outperformance is evidenced, how the freed time is used, how trust and accountability are anchored in people, and how cost pressures are managed. The article concludes with some suggestions for prudent use of AI in healthcare, indicating the appropriate measures that can be used to harness the power of AI without damaging the traditional cornerstones of the therapeutic relationship. Full article