Search Results (428)

Background and Clinical Significance: Triosephosphate isomerase (TPI) deficiency is a rare autosomal recessive metabolic disorder caused by a pathogenic variant in the TPI1 gene. It is characterised by chronic haemolytic anaemia, progressive neuromuscular dysfunction, and reduced life expectancy. Patients typically present with symptoms in the first few months of life, including muscle weakness, ataxia, and recurrent respiratory infections. Diagnosis is confirmed by genetic testing, and management is generally symptomatic as no treatment is available. Case Presentation: We describe the case of an infant diagnosed with TPI deficiency in the context of haemolytic anaemia with progressive neurological deterioration and respiratory failure. Conclusions: This case illustrates the complexity of the disease and highlights the importance of early diagnosis and contributes to the limited literature by providing a detailed clinical description and highlighting the diagnostic challenges associated with this condition. Beyond its clinical relevance, this report emphasises the potential role of personalised medicine in the management of TPI deficiency. Early identification of specific genotypes may inform prognosis and guide individualised supportive strategies. As knowledge of the molecular underpinnings of TPI deficiency expands, opportunities may emerge for targeted therapeutic approaches tailored to patient-specific characteristics. Full article

Objectives: Connective tissue diseases (CTDs) include a diverse group of systemic autoimmune conditions, among which interstitial lung disease (ILD) is acknowledged as a major determinant of prognosis. High-resolution computed tomography (HRCT) is the gold standard for ILD assessment. The distribution of HRCT patterns across CTDs remain incompletely defined. The objective of this systematic review is to synthesize available evidence regarding the prevalence of specific radiological patterns within CTD-ILDs and to assess whether specific patterns occur at different frequencies among individual CTDs. Methods: The inclusion criteria encompassed original human studies published in English between 2015 and 2024, involving adult participants (≥18 years) with CTD-ILDs assessed primarily by HRCT and designed as retrospective, prospective, or cross-sectional trials with extractable data. We systematically searched PubMed, Scopus, and Web of Science (January 2025). Risk of bias was evaluated using the Newcastle–Ottawa Scale (NOS) for cohort and case–control studies, and the JBI Critical Appraisal Checklist for cross-sectional studies. Data were extracted and categorized by HRCT pattern for each CTD, and then summarized descriptively and statistically. Results: We analyzed 23 studies published between 2015 and 2024, which included 2020 patients with CTD-ILDs. The analysis revealed non-specific interstitial pneumonia (NSIP) as the most prevalent pattern overall (36.5%), followed by definite usual interstitial pneumonia (UIP) (24.8%), organizing pneumonia (OP) (9.8%) and lymphoid interstitial pneumonia (LIP) (1.25%). HRCT distribution varied by CTD: NSIP predominated in systemic sclerosis, idiopathic inflammatory myopathies, and mixed connective tissue disease; UIP was most frequent in rheumatoid arthritis; LIP was more common in Sjögren’s syndrome. While global differences were statistically significant, pairwise comparisons often lacked significance, likely due to sample size constraints. Discussion: Limitations include varying risk of bias across study designs, heterogeneity in HRCT reporting, small sample sizes, and inconsistent follow-up, which may reduce precision and generalizability. In addition to the quantitative synthesis, this review offers a detailed description of each radiologic pattern mentioned above, illustrated by representative examples to support the recognition in clinical settings. Furthermore, it includes a brief overview of the major CTDs associated with ILD, summarizing their epidemiological data, risk factors for ILD and clinical presentation and diagnostic recommendations. Conclusions: NSIP emerged as the most common HRCT pattern across CTD-ILDs, with UIP predominating in RA. Although inter-disease differences were observed, statistical significance was limited, likely reflecting sample size constraints. These findings emphasize the diagnostic and prognostic relevance of HRCT pattern recognition and highlight the need for larger, standardized studies. Full article

Objectives: Although 3D-printing has been identified as a promising technique for personalised medicine manufacturing, developing complex formulations that are suitable for the process can be challenging. This study evaluates the use of a mixture design for the targeted development of an optimised formulation designed for the 3D-printing of oral dosage forms containing the drug sertraline hydrochloride featuring immediate-release drug dissolution. Methods: The polymers Eudragit E PO, Kollidon 17 PF and hydroxypropyl cellulose were compared in simple screening experiments regarding their extrudability, printability and disintegration. A combination of Eudragit E PO and Kollidon 17 PF proved superior and therefore served as the basis for the mixture design. The resulting blends were processed via hot melt extrusion to produce filaments, which were then measured for bending stress using a 3-point-bending-test, and 3D-printed sample plates were used to determine the crystallinity index of sertraline hydrochloride using X-ray diffraction in a previously identified range with low interference from the other components. The formulation was optimised using statistically based models with the aim of minimising the bending stress to obtain flexible, process-robust filaments and simultaneously minimising the crystallinity index with the intention of improving the solubility of the drug by maximising its amorphous content. Results: The filaments made from the optimised formulation could be reliably printed, and the amorphous state of the active ingredient therein was confirmed. The oral dosage forms produced from these showed immediate release characteristics in an acidic medium. Conclusions: This study demonstrates the advantages of a mixture design for optimising complex formulations in a time- and resource-efficient way and could serve as a basis for other research groups to develop innovative, customisable drug delivery systems more effectively. Full article

Background/Objectives: In the past two decades, the primary therapeutic use of sildenafil has shifted significantly, from the treatment of angina to managing erectile dysfunction, and since the early 2000s it has been used in the treatment of pulmonary hypertension, particularly pulmonary arterial hypertension. Sildenafil is used as a citrate salt; after oral administration, it presents an absorption of ~90% and an absolute bioavailability of 38%, due to the first-pass effect, such that it belongs to class II of the Biopharmaceutics Classification System. Currently, studies are seeking to obtain new pharmaceutical formulations with an optimized biopharmaceutical profile. In this study, an inclusion complex of sildenafil citrate and 2-hydroxypropyl-beta-cyclodextrin in a molar ratio of 1:1 was obtained and its pharmaceutical compatibility with six pharmaceutical excipients was assessed. For three of these excipients, the presence of chemical interactions with sildenafil citrate has been presented in the literature, and for the other three, compatibility has not been evaluated. Methods: To certify the stoichiometry of the obtained inclusion complex molecular modeling, Job’s method and the Benesi–Hildebrand method were employed. Furthermore, we have described the inclusion complex and the obtained binary mixtures via ATR-FTIR and thermal (TG/DTG and DSC) analysis. Results: The results indicated a lack of chemical interactions between the inclusion complex and the six pharmaceutical excipients at ambient temperature (confirmed by ATR–FTIR investigations) and the presence of chemical interactions between the inclusion complex and three of the excipients when the mixture was heated under non-isothermal conditions (TG/DTG and DSC investigations). Conclusions: This study describes the inclusion complex between sildenafil citrate and 2-hydroxypropyl-beta-cyclodextrin in a molar ratio of 1:1 and its compatibility with several pharmaceutical excipients, results with further applications in the preformulation stage of novel delivery systems. Full article

Background/Objectives: The application of additive manufacturing in medicine, and specifically in personalised medicine, has achieved notable development. This article aims to present the results and benefits of applying a comprehensive methodology to simulate, plan, and manufacture customised three-dimensional medical prosthetic devices for use in surgery to restore bone structures with congenital and acquired malformations. Methods: To digitally reconstruct a bone structure in three dimensions from a medical image, a segmentation process is developed to correlate the anatomical model. Then, this model is filtered using a post-processing step to generate stereolithography (STL) files, which are rendered using specialised software. The segmentation of tomographic images is achieved by the specific intensity selection, facilitating the analysis of compact and soft tissues within the anatomical region of interest. With the help of a thresholding algorithm, a three-dimensional digital model of the anatomical structure is obtained, ready for printing the required structure. Results: The described cases demonstrate that the use of anatomical test models, cutting guides, and customised prostheses reduces surgical time and hospital stay, and achieves better aesthetic and functional results. Using materials such as polylactic acid (PLA) for presurgical models, appropriate resins for cutting guides, and biocompatible materials such as polyether ether ketone (PEEK) or polymethylmethacrylate (PMMA) for prostheses, the described improvements are achieved. Conclusions: The achievements attained demonstrate the feasibility of applying these techniques, their advantages and their accessibility in Ecuador. They also reinforce the ideas of personalised medicine in the search for medical treatments and procedures tailored to the needs of each patient. Full article

Tuberculosis and parasitic infections, including Toxocara, frequently coexist in many regions worldwide, yet their interaction remains poorly understood. Tuberculosis triggers a type 1 immune response characterized by IL-12, IFN-γ, and TNF-α production, while toxocariasis elicits a type 2 response, mediated by cytokines such as IL-4, IL-5, IL-13, and IL-33. The coexistence of these divergent immune pathways can disrupt immune regulation and impair the host’s ability to control both infections, potentially leading to persistent hypereosinophilia. We illustrate this complex interplay through a real-world case involving a heavy smoker in whom Toxocara infection likely reactivated latent tuberculosis, resulting in severe, unexplained hypereosinophilia and late-onset asthma with recurrent exacerbations. After excluding other causes and completing full antituberculosis therapy along with three courses of antiparasitic treatment and systemic corticosteroids, hypereosinophilia persisted. The introduction of benralizumab, a biologic therapy targeting IL-5Rα, led to a rapid reduction in eosinophils to normal ranges and significant clinical improvement. This case underscores the diagnostic and therapeutic challenges posed by the intersection of common infections and highlights that even a neglected parasitic infection such as toxocariasis can underlie severe respiratory complications with eosinophilia, where paradoxically biologic therapy may ultimately provide a very effective intervention. Full article

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

Background: This genetic association study investigated single nucleotide polymorphism (SNP) in interleukin-8 (CXCL8) and opiorphin (OPRPN) genes, as well as psychological characteristics and oral behaviours, between patients with pain-related temporomandibular disorders (TMDp) and healthy controls. The aim was to examine associations and predictive value of these factors for TMDp subtypes: arthralgia and myalgia. Methods: A total of 85 patients with TMDp (arthralgia and/or myalgia) and 85 pain-free controls were included. Diagnoses were established following the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD). All participants completed standardised self-report questionnaires assessing anxiety, depression, and oral behaviours. Buccal swabs were collected for DNA extraction, and SNP genotyping was performed using real-time PCR. Statistical analyses were conducted using dominant and recessive genetic models. Logistic regression models were applied to assess risk factors for each TMDp subtype. Results: Participants homozygous for the minor allele (CC genotype) of rs1387964 in OPRPN were significantly more prevalent in both arthralgia and myalgia groups compared to controls. Age and female sex predicted TMDp-arthralgia. Predictors of TMDp-myalgia included the CC genotype of rs1387964, age, female sex, anxiety, and depression. Conclusions: Genetic background and psychological characteristics were significant predictors of TMDp myalgia, highlighting a multifactorial profile for this TMDp subtype. 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