Search Results (325)

The 2021 WHO classification of brain tumours revolutionised the oncological field by emphasising the role of molecular, genetic and pathogenetic advances in classifying brain tumours. In this context, incidental gliomas have been increasingly identified due to the widespread performance of standard and advanced MRI sequences and represent a diagnostic and therapeutic challenge. The impactful decision to perform a surgical procedure deeply relies on the non-invasive identification of features or parameters that may correlate with brain tumour genetic profile and grading. Therefore, it is paramount to reach an early and proper diagnosis through neuroradiological techniques, such as MRI. Standard MRI sequences are the cornerstone of diagnosis, while consolidated and emerging roles have been awarded to advanced sequences such as Diffusion-Weighted Imaging/Apparent Diffusion Coefficient (DWI/ADC), Perfusion-Weighted Imaging (PWI), Magnetic Resonance Spectroscopy (MRS), Diffusion Tensor Imaging (DTI) and functional MRI (fMRI). The current novelty relies on the application of AI in brain neuro-oncology, mainly based on radiomics and radiogenomics models, which enhance standard and advanced MRI sequences in predicting glioma genetic status by identifying the mutation of multiple key biomarkers deeply impacting patients’ diagnosis, prognosis and treatment, such as IDH, EGFR, TERT, MGMT promoter, p53, H3-K27M, ATRX, Ki67 and 1p19. AI-driven models demonstrated high accuracy in glioma detection, grading, prognostication, and pre-surgical planning and appear to be a promising frontier in the neuroradiological field. On the other hand, standardisation challenges in image acquisition, segmentation and feature extraction variability, data scarcity and single-omics analysis, model reproducibility and generalizability, the black box nature and interpretability concerns, as well as ethical and privacy challenges remain key issues to address. Future directions, rooted in enhanced standardisation and multi-institutional validation, advancements in multi-omics integration, and explainable AI and federated learning, may effectively overcome these challenges and promote efficient AI-based models in glioma management. The aims of our multidisciplinary review are to: (1) extensively present the role of standard and advanced MRI sequences in the differential diagnosis of iLGGs as compared to HGGs (High-Grade Gliomas); (2) give an overview of the current and main applications of AI tools in the differential diagnosis of iLGGs as compared to HGGs (High-Grade Gliomas); (3) show the role of MRI, radiomics and radiogenomics in unravelling glioma genetic profiles. Standard and advanced MRI, radiomics and radiogenomics are key to unveiling the grading and genetic profile of gliomas and supporting the pre-operative planning, with significant impact on patients’ differential diagnosis, prognosis prediction and treatment strategies. Today, neuroradiologists are called to efficiently use AI tools for the in vivo, non-invasive, and comprehensive assessment of gliomas in the path towards patients’ personalised medicine. Full article

Circadian rhythms are intrinsic 24 h cycles that regulate metabolic processes across multiple tissues, with skeletal muscle emerging as a central node in this temporal network. Muscle clocks govern gene expression, fuel utilisation, mitochondrial function, and insulin sensitivity, thereby maintaining systemic energy homeostasis. However, circadian misalignment, whether due to behavioural disruption, nutrient excess, or metabolic disease, impairs these rhythms and contributes to insulin resistance, and the development of obesity, and type 2 diabetes mellitus. Notably, the muscle clock remains responsive to non-photic cues, particularly exercise, which can reset and amplify circadian rhythms even in metabolically impaired states. This work synthesises multi-level evidence from rodent models, human trials, and in vitro studies to elucidate the role of skeletal muscle clocks in circadian metabolic health. It explores how exercise entrains the muscle clock via molecular pathways involving AMPK, SIRT1, and PGC-1α, and highlights the time-of-day dependency of these effects. Emerging data demonstrate that optimally timed exercise enhances glucose uptake, mitochondrial biogenesis, and circadian gene expression more effectively than time-agnostic training, especially in individuals with metabolic dysfunction. Finally, findings are integrated from multi-omic approaches that have uncovered dynamic, time-dependent molecular signatures that underpin circadian regulation and its disruption in obesity. These technologies are uncovering biomarkers and signalling nodes that may inform personalised, temporally targeted interventions. By combining mechanistic insights with translational implications, this review positions skeletal muscle clocks as both regulators and therapeutic targets in metabolic disease. It offers a conceptual framework for chrono-exercise strategies and highlights the promise of multi-omics in developing precision chrono-medicine approaches aimed at restoring circadian alignment and improving metabolic health outcomes. Full article

Cardiovascular disease (CVD) remains Europe’s leading cause of mortality, responsible for >45% of deaths. Beyond established risk factors (hypertension, diabetes, dyslipidaemia, smoking, obesity), psychosocial elements—depression, anxiety, financial stress, personality traits, and trauma—significantly influence CVD development and progression. Behavioural Cardiology addresses this connection by systematically incorporating psychosocial factors into prevention and rehabilitation protocols. This review examines the HEARTBEAT model, developed by Greece’s first Behavioural Cardiology Unit, which aligns with current European guidelines. The model serves dual purposes: primary prevention (targeting at-risk individuals) and secondary prevention (treating established CVD patients). It is a personalised medicine approach that integrates psychosocial profiling with traditional risk assessment, utilising tailored evaluation tools, caregiver input, and multidisciplinary collaboration to address personality traits, emotional states, socioeconomic circumstances, and cultural contexts. The model emphasises three critical implementation aspects: (1) digital health integration, (2) cost-effectiveness analysis, and (3) healthcare system adaptability. Compared to international approaches, it highlights research gaps in psychosocial interventions and advocates for culturally sensitive adaptations, particularly in resource-limited settings. Special consideration is given to older populations requiring tailored care strategies. Ultimately, Behavioural Cardiology represents a transformative systems-based approach bridging psychology, lifestyle medicine, and cardiovascular treatment. This integration may prove pivotal for optimising chronic disease management through personalised interventions that address both biological and psychosocial determinants of cardiovascular health. Full article

Diabetic retinopathy (DR) is a progressive, multifactorial complication of diabetes and one of the major global causes of visual impairment. Its pathogenesis involves chronic hyperglycaemia-induced oxidative stress, inflammation, mitochondrial dysfunction, neurodegeneration, and pathological angiogenesis, as well as emerging systemic contributors such as gut microbiota dysregulation. While current treatments, including anti-vascular endothelial growth factor (anti-VEGF) agents, corticosteroids, and laser photocoagulation, have shown clinical efficacy, they are largely limited to advanced stages of DR, require repeated invasive procedures, and do not adequately address early neurovascular and metabolic abnormalities. Resveratrol (RSV), a naturally occurring polyphenol, has emerged as a promising candidate due to its potent antioxidant, anti-inflammatory, neuroprotective, and anti-angiogenic properties. This review provides a comprehensive analysis of the molecular mechanisms by which RSV exerts protective effects in DR, including modulation of oxidative stress pathways, suppression of inflammatory cytokines, enhancement of mitochondrial function, promotion of autophagy, and inhibition of pathological neovascularisation. Despite its promising pharmacological profile, the clinical application of RSV is limited by poor aqueous solubility, rapid systemic metabolism, and low ocular bioavailability. Various routes of administration, including intravitreal injection, topical instillation, and oral and sublingual delivery, have been investigated to enhance its therapeutic potential. Recent advances in drug delivery systems, including nanoformulations, liposomal carriers, and sustained-release intravitreal implants, offer potential strategies to address these challenges. This review also explores RSV’s role in combination therapies, its potential as a disease-modifying agent in early-stage DR, and the relevance of personalised medicine approaches guided by metabolic and genetic factors. Overall, the review highlights the therapeutic potential and the key translational challenges in positioning RSV as a multi-targeted treatment strategy for DR. Full article

Background/Objectives: In many parts of the world, pharmacists hold the primary responsibility for providing safe and effective pharmacotherapy. A key aspect is the availability of appropriate medicines for each individual patient. When industrially manufactured medicines are unsuitable or unavailable, pharmacists can prepare tailor-made medicines. While this principle applies globally, practices vary between countries. In the Netherlands, the preparation of medicines in pharmacies is well-established and integrated into routine healthcare. This narrative review explores the role and significance of extemporaneous compounding, pharmacy preparations and related product care in the Netherlands. Methods: Pharmacists involved in pharmacy preparations across various professional sectors, including community and hospital pharmacies, central compounding facilities, academia, and the professional pharmacists’ organisation, provided detailed and expert insights based on the literature and policy documents while also sharing their critical perspectives. Results: We present arguments supporting the need for pharmacy preparations and examine their position and role in community and hospital pharmacies in the Netherlands. Additional topics are discussed, including the regulatory and legal framework, outsourcing, quality assurance, standardisation, education, and international context. Specific pharmacy preparation topics, often with a research component and a strong focus on product care, are highlighted, including paediatric dosage forms, swallowing difficulties and feeding tubes, hospital-at-home care, reconstitution of oncolytic drugs and biologicals, total parenteral nutrition (TPN), advanced therapy medicinal products (ATMPs), radiopharmaceuticals and optical tracers, clinical trial medication, robotisation in reconstitution, and patient-centric solid oral dosage forms. Conclusions: The widespread acceptance of pharmacy preparations in the Netherlands is the result of a unique combination of strict adherence to tailored regulations that ensure quality and safety, and patient-oriented flexibility in design, formulation, and production. This approach is further reinforced by the standardisation of a broad range of formulations and procedures across primary, secondary and tertiary care, as well as by continuous research-driven innovation to develop new medicines, formulations, and production methods. Full article

Introduction: Falls are the leading cause of Emergency Department (ED) presentations among residents from residential aged care facilities (RACFs). While most current studies focus on post-fall evaluations and fall prevention, limited research has been conducted on decision-making in post-fall management. Objective: To develop and internally validate a model that can predict the likelihood of RACF residents being discharged from the ED after being presented for a fall. Methods: The study sample was obtained from a previous study conducted in Shepparton, Victoria, Australia. Consecutive samples were selected from January 2023 to November 2023. Participants aged 65 and over were included in this study. Results: A total of 261 fall presentations were initially identified. One patient with Australasian Triage Scale category 1 was excluded to avoid overfitting, leaving 260 presentations for analysis. Two logistic regression models were developed using prehospital and ED variables. The ED predictor model variables included duration of ED stay, injury severity, and the presence of an advance care directive (ACD). It demonstrated excellent discrimination (AUROC = 0.83; 95% CI: 0.79–0.89) compared to the prehospital model (AUROC = 0.77, 95% CI: 0.72–0.83). A simplified four-variable Discharge Eligibility after Fall in Elderly Residents (DEFER) score was derived from the prehospital model. The score achieved an AUROC of 0.76 (95% CI: 0.71–0.82). At a cut-off score of ≥5, the DEFER score exhibited a sensitivity of 79.7%, a specificity of 60.3%, a diagnostic odds ratio of 5.96, and a positive predictive value of 85.0%. Conclusions: The DEFER score is the first validated discharge prediction model for residents of RACFs who present to the ED after a fall. Importantly, the DEFER score advances personalised medicine in emergency care by integrating patient-specific factors, such as ACDs, to guide individualised discharge decisions for post-fall residents from RACFs. Full article

Serotoninomics is an expanding field that focuses on the comprehensive study of the serotoninergic system, including serotonin’s biosynthesis, metabolism, and regulation, as well as related scientific methodologies 5-hydroxytryptamine (5-HT). This field explores serotonin’s complex roles in various physiological and pathological contexts. The essential amino acid tryptophan (Trp) is a precursor for several metabolic and catabolic pathways, with the kynurenine (KYN) pathway being particularly significant, representing about 95% of Trp metabolism. In contrast, only a small portion (1–2%) of dietary Trp enters the serotonin pathway. Anthranilic acid (AA), a metabolite in the KYN pathway, has emerged as a potential biomarker and therapeutic target for schizophrenia. Elevated serum AA levels in patients with schizophrenia have been associated with neurotoxic effects and disruptions in neurotransmission, suggesting AA’s critical role in the disorder’s pathophysiology. Furthermore, the 5-HT_2A receptor’s involvement is particularly noteworthy, especially in relation to schizophrenia’s positive symptoms. Recent findings indicate that 5-HT_2A receptor hyperactivity is linked to positive symptoms of schizophrenia, such as hallucinations and delusions. This study investigates serotoninomics’ implications for neuropsychiatric disorders, focusing on AA in schizophrenia and analysing recent research on serotonin signalling pathways and AA’s neurochemical effects. Understanding the roles of the 5-HT_2A receptor and AA in neuropsychiatric disorders could lead to the development of more precise and less invasive diagnostic tools, specific therapeutic strategies, and improved clinical outcomes. Ongoing research is essential to uncover these pathways’ exact mechanisms and therapeutic potential, thereby advancing personalised medicine and innovative treatments in neuropsychiatry. Full article

Cardiovascular disease (CVD) remains the foremost global cause of mortality, driven significantly by modifiable lifestyle factors. This study employs a data-driven approach to identify and evaluate these risk factors using advanced machine learning techniques. Analysing a large publicly available dataset of over 300,000 adult health records containing lifestyle behaviours, clinical risk factors, and self-reported health indicators, this research implemented traditional classifiers, ensemble methods, and deep learning architectures to examine the impact of behaviours such as smoking, diet, physical activity, and alcohol consumption on CVD risk. The Random Forest model demonstrated superior performance, achieving high accuracy, recall, and ROC-AUC scores. To demonstrate real-world utility, the model was deployed as an interactive Streamlit web application. This tool allows individuals to input lifestyle and health data to receive real-time CVD risk predictions, offering a novel, user-friendly prototype that bridges machine learning insights with personalised digital health engagement. This tool can facilitate personalised health monitoring and supports early detection by providing actionable insights. The findings underscore the efficacy of predictive modelling in informing targeted interventions and public health strategies. By bridging advanced analytics with practical applications, this research offers a scalable framework for reducing CVD burden, paving the way for precision medicine and improved population health outcomes through data-driven decision-making. Full article

In the era of precision medicine, effective data visualisation plays a pivotal role in supporting clinical decision-making by translating complex, multidimensional datasets into intuitive and actionable insights. This paper explores the foundational principles of visual perception, with a specific focus on pre-attentive attributes such as colour, shape, size, orientation, and spatial position, which are processed automatically by the human visual system. Drawing from cognitive psychology and perceptual science, we demonstrate how these attributes can enhance the clarity and usability of medical visualisations, reducing cognitive load and improving interpretive speed in high-stakes clinical environments. Through detailed case studies and visual examples, particularly within the field of oncology, we highlight best practices and common pitfalls in the design of dashboards, nomograms, and interactive platforms. We further examine the integration of advanced tools—such as genomic heatmaps and temporal timelines—into multidisciplinary workflows to support personalised care. Our findings underscore that visually intelligent design is not merely an aesthetic concern but a critical factor in clinical safety, efficiency, and communication, advocating for user-centred and evidence-based approaches in the development of health data interfaces. Full article

Cancer remains a leading global health burden, profoundly affecting patient survival and quality of life. Current treatments—including chemotherapy, radiotherapy, immunotherapy, and surgery—are often limited by toxicity or insufficient specificity. Conventional chemotherapy, for instance, indiscriminately attacks rapidly dividing cells, causing severe side effects. In contrast, peptide-based therapeutics offer a paradigm shift, combining high tumour-targeting precision with minimal off-target effects. Their low immunogenicity, multi-pathway modulation capabilities, and adaptability for diagnostics and therapy make them ideal candidates for advancing oncology care. Innovative peptide platforms now enable three transformative applications: (1) precision molecular diagnostics (e.g., ¹⁸F-PSMA-1007 for prostate cancer detection), (2) targeted therapies (e.g., BT5528 and SAR408701 targeting tumour-specific antigens), and (3) theranostic systems (e.g., RAYZ-8009 and ¹⁷⁷Lu-FAP-2286 integrating imaging and radiotherapy). Despite their promise, peptides face challenges like metabolic instability and short half-lives. Recent advances in structural engineering (e.g., cyclization and D-amino acid incorporation) and delivery systems (e.g., nanoparticles and PEGylation) have significantly enhanced their clinical potential. This review highlights peptide-based agents in development, showcasing their ability to improve early cancer detection, reduce metastasis, and enhance therapeutic efficacy with fewer adverse effects. Examples like CLP002 underscore their role in personalised medicine. By overcoming current limitations, peptide drugs are poised to redefine cancer management, offering safer, more effective alternatives to conventional therapies. Their integration into clinical practice could mark a critical milestone in achieving precision oncology. Full article

Multi-layer cell constructs produced in vitro are an innovative treatment option to support the growing demand for therapy in regenerative medicine. Our research introduces a novel construct integrating organ-derived decellularised extracellular matrix (dECM) hydrogels and 3D-printed biodegradable polymer meshes composed of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and poly(3-hydroxybutyrate-co-4-hydroxybutyrate) (P34HB) to support and maintain multiple layers of different cell types. We achieved that by integrating the mechanical stability of PHBV+P34HB, commonly used in the food storage industry, with a dECM hydrogel, which replicates organ stiffness and supports cellular survival and function. The construct was customised by adjusting the fibre arrangement and pore sizes, making it a suitable candidate for a personalised design. We showed that the polymer is degradable after precoating it with PHB depolymerase (PhaZ), with complete degradation achieved in 3–5 days and delayed by adding the hydrogel to 10 days, enabling tuneable degradation for regenerative medicine applications. Finally, as a proof of concept, we composed a three-layered tissue in vitro; each layer represented a different tissue type: epidermal, vascular, and subcutaneous layers. Possible future applications include wound healing and diabetic ulcer paths, personalised drug delivery systems, and personalised tissue implants. Full article

Obstructive sleep apnoea (OSA) is a prevalent condition characterised by intermittent upper airway obstruction during sleep, resulting in recurrent hypoxia and sleep fragmentation. Emerging evidence highlights the significant impact of OSA on neuro-ophthalmological health, linking it to conditions such as glaucoma, optic neuropathy, papilledema, and visual field defects. These associations emphasise the importance of understanding the mechanisms connecting OSA to neuro-ophthalmological disorders to enhance early diagnosis and management. This review explores the pathophysiological pathways, including hypoxia-induced vascular dysregulation, oxidative stress, inflammation, and intracranial pressure fluctuations, that contribute to ocular and neurological impairments in OSA patients. Advanced diagnostic tools, such as optical coherence tomography and polysomnography, offer promising avenues for detecting subclinical neuro-ophthalmological changes, enabling timely intervention. Management strategies, primarily centred on continuous positive airway pressure therapy, have shown efficacy in mitigating OSA-related neuro-ophthalmological complications. However, surgical and pharmacological interventions and lifestyle modifications remain vital components of a multidisciplinary approach to care. Despite advancements, significant research gaps persist, particularly in understanding the long-term impact of OSA treatment on neuro-ophthalmological outcomes and identifying specific biomarkers for early detection. Future research should prioritise longitudinal studies, interdisciplinary collaborations, and personalised medicine approaches to address these challenges. Recognising and treating neuro-ophthalmological disorders in OSA patients is imperative for improving quality of life and preventing irreversible visual and neurological damage. Full article

Lung cancer remains one of the main causes of cancer-related death globally and a significant global health concern. There is an urgent need for safer and more effective therapeutic alternatives despite notable progress in therapy; issues such as drug resistance, side effects, metastasis, and recurrence still affect patient outcome and quality of life. The aim of this review is to examine recent developments in the application of herbal-drug-loaded nanoparticles as a new strategy for treating lung cancer. A thorough examination of different drug delivery systems based on nanoparticles is provided, highlighting their function in improving the solubility, bioavailability, and targeted delivery of herbal compounds. In addition, the review evaluates the biomarkers used for targeted therapy and examines how new personalised treatment approaches like wearable electronic patches, robotics-assisted interventions, smartphone-enabled therapies, AI-driven diagnostics, and lung-on-a-chip technologies can be integrated to improve the accuracy and effectiveness of lung cancer treatment. In conclusion, the combination of personalised medicine and nanotechnology may lead to revolutionary changes in lung cancer treatment in the future. Full article

Intermittent fasting (IF) is emerging as a heterogeneous neurometabolic intervention with the possibility of changing the course of neurodegenerative diseases. Through the modulation of the gut–brain axis (GBA), cellular bioenergetics (or metabolic) reprogramming, and involvement in preserved stress adaptation pathways, IF influences a range of physiological mechanisms, including mitobiogenesis, autophagy, circadian rhythm alignment, and neuroinflammation. This review critically synthesises current preclinical and early clinical evidence illustrating IF’s capability to supplement synaptic plasticity and integrity, reduce toxic proteins (proteotoxic) burden, and rehabilitate glial and immune homeostasis across models of Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis. The key players behind these effects are bioactive metabolites such as short-chain fatty acids (SCFA) and β-hydroxybutyrate (BHB), and molecular mediators such as brain-derived neurotrophic factor (BDNF). We feature the therapeutic pertinence of IF-induced changes in gut microbiota composition, immune response, and mitochondrial dynamics, and we discuss emerging approaches for merging IF into precision medicine frameworks. Crucial challenges include individual variability, protocol optimisation, safety in cognitively vulnerable populations, and the need for biomarker-guided, ethically grounded clinical trials. Finally, we propose IF as a scalable and flexible intervention that, when personalised and integrated with other modalities, may reframe neurodegeneration from a model of irreversible decline to one of modifiable resilience. Full article

Background/Objectives. Flavonoids are a vast class of phenolic substances. To date, approximately 6000 plant-origin flavonoids have been discovered, with many of them being used in drug therapy. Therapeutic flavonoids are commonly formulated to conventional “one-size-fits-all” dosage forms, such as conventional tablets or hard capsules. However, the current trends in pharmacy and medicine are centred on personalised drug therapy and drug delivery systems (DDSs). Therefore, 3D printing is an interesting technique for designing and preparing novel personalised pharmaceuticals for flavonoids. The aim of the present study was to develop aqueous polyethylene oxide (PEO) gel inks loaded with rutin for semisolid extrusion (SSE) 3D printing. Methods. Rutin (a model substance for therapeutic flavonoids), Tween 80, PEO (MW approx. 900,000), ethanol, and purified water were used in PEO gels at different proportions. The viscosity and homogeneity of the gels were determined. The rutin–PEO gels were printed with a bench-top Hyrel 3D printer into lattices and discs, and their weight and effective surface area were investigated. Results. The key SSE 3D-printing process parameters were established and verified. The results showed the compatibility of rutin as a model flavonoid and PEO as a carrier polymer. The rutin content (%) and content uniformity of the 3D-printed preparations were assayed by UV spectrophotometry and high-performance liquid chromatography (HPLC). Conclusions. The most feasible aqueous PEO gel ink formulation for SSE 3D printing contained rutin 100 mg/mL and Tween 80 50 mg/mL in a 12% aqueous PEO gel. The 3D-printed dosage forms are intended for the oral administration of flavonoids. Full article