Search Results (113)

As people with cystic fibrosis (PwCF) live longer, kidney disease is emerging as a significant comorbidity that is increasingly linked to cardiovascular complications and progression to end-stage kidney disease. In our recent review, we proposed the unifying term CF-related kidney disease (CFKD) to encompass the spectrum of kidney dysfunction observed in this population. Early detection of kidney injury is critical for improving long-term outcomes, yet remains challenging due to the limited sensitivity of conventional laboratory tests, particularly in individuals with altered muscle mass and unique CF pathophysiology. Emerging approaches, including novel blood and urinary biomarkers, urinary extracellular vesicles, and genetic risk profiling, offer promising avenues for identifying subclinical kidney damage. When integrated with machine learning algorithms, these tools may enable the development of personalized risk stratification models and targeted therapeutic strategies. This precision medicine approach has the potential to transform kidney disease management in PwCF, shifting care from reactive treatment of late-stage disease to proactive monitoring and early intervention. Full article

Massively parallel or next-generation sequencing (NGS) has enabled the genetic characterization of cancer patients, allowing the identification of somatic and germline variants associated with their diagnosis, tumor classification, and therapy response. Despite its benefits, NGS testing is not yet available in the Chilean public health system, rendering it both costly and time-consuming for patients and clinicians. Using a retrospective cohort of 67 formalin-fixed, paraffin-embedded (FFPE) colorectal cancer (CRC) samples, we aimed to implement the identification, annotation, and prioritization of relevant actionable tumor somatic variants in our laboratory, as part of the public health system. We compared two different library preparation methodologies (amplicon-based and capture-based) and different bioinformatics pipelines for sequencing analysis to assess advantages and disadvantages of each one. We obtained 80.5% concordance between actionable variants detected in our analysis and those obtained in the Cancer Genomics Laboratory from the Universidad de Chile (62 out of 77 variants), a validated laboratory for this methodology. Notably, 98.4% (61 out of 62) of variants detected previously by the validated laboratory were also identified in our analysis. Then, comparing the hybridization capture-based library preparation methodology with the amplicon-based strategy, we found ~94% concordance between identified actionable variants across the 15 shared genes, analyzed by the TumorSec^TM bioinformatics pipeline, developed by the Cancer Genomics Laboratory. Our results demonstrate that it is entirely viable to implement an NGS-based analysis of actionable variant identification and prioritization in cancer samples in our laboratory, being part of the Chilean public health system and paving the way to improve the access to such analyses. Considering the economic realities of most Latin American countries, using a small NGS panel, such as TumorSec^TM, focused on relevant variants of the Chilean and Latin American population is a cost-effective approach to extensive global NGS panels. Furthermore, the incorporation of automated bioinformatics analysis in this streamlined assay holds the potential of facilitating the implementation of precision medicine in this geographic region, which aims to greatly support personalized treatment of cancer patients in Chile. Full article

Parkinson’s disease (PD), a progressive neurodegenerative disorder, imposes growing clinical and socioeconomic burdens worldwide. Despite landmark discoveries in dopamine biology and α-synuclein pathology, translating mechanistic insights into effective, personalized interventions remains elusive. Recent advances in molecular profiling, neuroimaging, and computational modeling have broadened the understanding of PD as a multifactorial systems disorder rather than a purely dopaminergic condition. However, critical gaps persist in diagnostic precision, biomarker standardization, and the translation of bench side findings into clinically meaningful therapies. This review critically examines the current landscape of PD research, identifying conceptual blind spots and methodological shortfalls across pathophysiology, clinical evaluation, trial design, and translational readiness. By synthesizing evidence from molecular neuroscience, data science, and global health, the review proposes strategic directions to recalibrate the research agenda toward precision neurology. Here I highlight the urgent need for interdisciplinary, globally inclusive, and biomarker-driven frameworks to overcome the fragmented progression of PD research. Grounded in the Accelerating Medicines Partnership-Parkinson’s Disease (AMP-PD) and the Parkinson’s Progression Markers Initiative (PPMI), this review maps shared biomarkers, open data, and patient-driven tools to faster personalized treatment. In doing so, it offers actionable insights for researchers, clinicians, and policymakers working at the intersection of biology, technology, and healthcare delivery. As the field pivots from symptomatic relief to disease modification, the road forward must be cohesive, collaborative, and rigorously translational, ensuring that laboratory discoveries systematically progress to clinical application. Full article

Introduction: Bioinformatics is a relatively recent multidisciplinary research field continuously offering novel opportunities. Although many researchers are actively working in/with bioinformatics, some research centers still face difficulties in hiring bioinformaticians and establishing the appropriate (first) bioinformatics infrastructures and computational resources. In our research center, we started from scratch and established initial bioinformatics infrastructures for common use and also for the specific case of precision/personalized medicine. Case description: Here, we report a case study reflecting our specific needs and circumstances during the implementation of a novel bioinformatics laboratory. This involved the preparation of rooms, computer networks, computational resources novel designs, and upgrades to existing designs. Moreover, this work involved people from diverse areas and institutions, such as companies, institutional projects, informatics, and technical infrastructures services. Discussion and evaluation: The work resulted in the implementation of four novel designs dedicated to genomic medicine and in the adaptation of two existing designs dedicated to common use located in the dry-lab room. This is not an accurate and objective work, as it often depends on the available computer hardware and the target bioinformatics field(s). The four novel designs offered substantial improvements when compared to the upgraded designs, additionally corroborated by performance evaluations, which resulted in an overall highest performance of the novel designs. Conclusions: We present work that was developed over two years until completion with functioning infrastructure. This project enabled us to learn many novel aspects not only related to redundant disk technologies, but also related to computer networks, hardware, storage-management operating systems, file systems, performance evaluation, and also in the management of services. Moreover, additional equipment will be important to maintain and expand the potential and reliability of the bioinformatics laboratory. We hope that this work can be helpful for other researchers seeking to design their bioinformatics equipment or laboratories. Full article

Advancements in biosensing technologies have introduced opportunities for non-invasive, real-time monitoring of salivary biomarkers, enabling progress in fields ranging from personalized medicine to public health. Identifying and prioritizing the most critical analytes to measure in saliva is essential for estimating physiological status and forecasting performance in applied contexts. This study examined the value of 12 salivary analytes, including hormones, metabolites, and enzymes, for predicting cognitive and physical performance outcomes in military personnel (N = 115) engaged in stressful laboratory and field tasks. We calculated a series of features to quantify time-series analyte data and applied multiple regression techniques, including Elastic Net, Partial Least Squares, and Random Forest regression, to evaluate their predictive utility for five outcomes of interest: the ability to move, shoot, communicate, navigate, and sustain performance under stress. Predictive performance was poor across all models, with R-squared values near zero and limited evidence that salivary analytes provided stable or meaningful performance predictions. While certain features (e.g., post-peak slopes and variance metrics) appeared more frequently than others, no individual analyte emerged as a reliable predictor. These results suggest that salivary biomarkers alone are unlikely to provide robust insights into cognitive and physical performance outcomes. Future research may benefit from combining salivary and other biosensor data with contextual variables to improve predictive accuracy in real-world settings. Full article

Hemophilia, an X-linked bleeding disorder, is characterized by a deficiency in coagulation factors. It manifests as spontaneous bleeding, leading to severe complications if not properly managed. In contrast, acquired hemophilia is an autoimmune condition marked by the development of inhibitory antibodies against coagulation factors. Both forms present significant diagnostic and therapeutic challenges, highlighting the need for advanced genetic, molecular, laboratory, and clinical assessments. Recent advances in artificial intelligence have opened new avenues for the management of hemophilia. Machine learning and deep learning technologies enhance the ability to predict bleeding risks, optimize treatment regimens, and monitor disease progression with greater precision. Artificial intelligence-driven applications in medical imaging have also improved the detection of joint damage and hemarthrosis, ensuring timely interventions and better clinical outcomes. Moreover, the integration of artificial intelligence into clinical practice holds the potential to transform hemophilia care through predictive analytics and personalized medicine, promising not only faster and more accurate diagnoses but also a reduction in long-term complications. However, ethical considerations and the need for data standardization remain critical for its widespread adoption. The application of artificial intelligence in hemophilia represents a paradigm shift towards precision medicine, with the promise of significantly improving patient outcomes and quality of life. Full article

Advances in pharmaceutical technology have positioned 3D printing and bioprinting as promising tools for developing personalized drug therapies. These innovations may redefine compounding practices by enabling precise, patient-specific drug formulations. Evaluating pharmacists’ readiness to adopt such technologies is therefore becoming increasingly important. Aim: The aim of this study is to investigate pharmacists’ knowledge, attitudes, and perceived barriers regarding the application of 3D printing and bioprinting technologies, as well as their perspectives on the regulation and implementation of these technologies in the context of personalized pharmacy. Materials and Methods: A custom-designed questionnaire was developed for the purposes of this pilot study, based on a review of the existing literature and informed by expert consultation to ensure conceptual relevance and clarity. The survey was conducted between September and December 2024. The data collection instrument comprises three main sections: (1) sociodemographic and professional characteristics, (2) knowledge regarding the applications of 3D printing and bioprinting in pharmacy, and (3) attitudes toward the regulatory framework and implementation of these technologies. Results: A total of 353 respondents participated, and 65.5% of them (n = 231) correctly distinguished between the concepts of “3D printing” and “bioprinting.” More than 25% (n = 88) were uncertain, and 8.5% (n = 30) were unable to differentiate between the two. Regarding the perceived benefits of personalized pharmacy, 83% (n = 293) of participants identified “the creation of personalized medications tailored to individual needs” as the main advantage, while 66% (n = 233) highlighted the “optimization of drug concentration to enhance therapeutic efficacy and minimize toxicity and adverse effects.” Approximately 60% (n = 210) of the pharmacists surveyed believed that the introduction of 3D-bioprinted pharmaceuticals would have a positive impact on the on-site preparation of customized drug formulations in community and hospital pharmacies. Lack of regulatory guidance and unresolved ethical concerns were identified as primary barriers. Notably, over 40% (n = 142) of respondents expressed concern that patients could be subjected to treatment approaches resembling “laboratory experimentation.” Nearly 90% (n = 317) of participants recognized the need for specialized training and expressed a willingness to engage in such educational initiatives. Conclusions: Three-dimensional printing and bioprinting technologies are considered cutting-edge instruments that may contribute to the advancement of pharmaceutical practice and industry, particularly in the field of personalized medicine. However, respondents’ views suggest that successful integration may require improved pharmacist awareness and targeted educational initiatives, along with the development and adaptation of appropriate regulatory frameworks to accommodate these novel technologies in drug design and compounding. Full article

Background: In systemic sclerosis (SSc), endothelial dysfunction, inflammation, and reduced nitric oxide levels may disrupt circadian blood pressure (BP) regulation. There are studies showing that inflammatory and certain other cells in diseases like SSc exhibit diurnal rhythms. In our study, we examined the effect of SSc on BP. In particular, the frequency of the non-dipper pattern (lack of nighttime BP reduction) in SSc patients has not been adequately investigated. The aim of this study was to evaluate the 24 h BP profile in SSc patients and to compare the frequency of the non-dipper pattern with that of the non-scleroderma group. Additionally, the identification of disrupted circadian BP patterns in SSc patients aims to contribute to the development of personalized, time-sensitive BP monitoring strategies in the future and to support the applicability of personalized medicine in this context. Methods: A total of 31 SSc patients diagnosed according to the 2013 ACR/EULAR classification criteria and 30 age- and sex-matched individuals without SSc were included in this prospective study. BP changes between day and night were evaluated by measuring BP every 30 min with a 24 h ambulatory blood pressure monitoring (ABPM) device. The non-dipper pattern was defined as a decrease in BP of less than 10% during the night compared to the day. To better assess BP fluctuations during the night, nighttime measurements were divided into two time periods: first, 24:00–04:00, and then 04:00–08:00. Additionally, laboratory and clinical parameters and SSc subtypes were compared between the groups. Results: The ABPM findings were compared between the groups with and without SSc. The non-dipper pattern was significantly more common in the SSc group at all time intervals. The non-dipper pattern was observed in 25.8% of the non-SSc group and 83.9% of SSc patients (p < 0.001). In the period between 24:00 and 04:00, the prevalence was 25.8% in the control group and 71.0% in SSc patients (p < 0.001), and between 04:00 and 08:00, it was 35.5% in the control group and 80.6% in SSc patients (p < 0.001). No significant difference was found in non-dipper patterns between individuals with diffuse and limited cutaneous forms of systemic sclerosis. Conclusions: The non-dipper BP pattern is significantly more common in patients with SSc, indicating the disruption of the circadian rhythm affecting BP. Analysis performed by dividing the night into specific time periods revealed that this deterioration continued throughout the night. The findings highlight the importance of circadian BP monitoring in SSc patients and may contribute to future risk stratification and treatment strategies. Circadian BP analysis in SSc may help to develop strategies that are personalized for these patients and tailored to their physiological rhythm. Full article

The upcoming wave of personalized medicine, driven by genomic diagnostics and artificial intelligence, demands clearly defined pre-laboratory and laboratory procedures to ensure the acquisition of DNA and RNA of sufficient quantity and quality. In prostate cancer oncogenetics, diagnostic and prognostic assessments increasingly rely on personalized approaches, including Comprehensive Genomic Profiling (CGP). In this pilot study, we aimed to establish optimal pre-analytical and analytical conditions for selected genetic diagnostic methods using tissue samples acquired through multiparametric MRI-guided biopsy. Tissue specimens from thirteen patients were processed for DNA isolation, fluorescence in situ hybridization (FISH), and next-generation sequencing (NGS). Comparative analyses were performed on DNA derived from both fresh and formalin-fixed, paraffin-embedded (FFPE) samples. Sequencing quality metrics demonstrated markedly superior performance in fresh tissue compared to FFPE. These results highlight the importance of standardized tissue collection and processing protocols to enable reliable molecular diagnostics in prostate cancer. Our findings support the feasibility of integrating high-quality genomic testing into routine biopsy workflows and emphasize the need for further large-scale validation. Full article

Liposome-based drug delivery systems have revolutionized modern pharmaceutics, offering unparalleled versatility and precision in therapeutic delivery. These lipid vesicles, capable of encapsulating hydrophilic, hydrophobic, and amphiphilic drugs, have demonstrated significant potential in addressing pharmacokinetic challenges such as poor solubility, systemic toxicity, and rapid clearance. This review provides a comprehensive exploration of the evolution of liposomes from laboratory models to clinically approved therapeutics, highlighting their structural adaptability, functional tunability, and transformative impact on modern medicine. We discuss pivotal laboratory-scale preparation techniques, including thin-film hydration, ethanol injection, and reverse-phase evaporation, along with their inherent advantages and limitations. The challenges of transitioning to industrial-scale production are examined, with emphasis on achieving batch-to-batch consistency, scalability, regulatory compliance, and cost-effectiveness. Innovative strategies, such as the incorporation of microfluidic systems and advanced process optimization, are explored to address these hurdles. The clinical success of Food and Drug Administration (FDA)-approved liposomal formulations such as Doxil^® and AmBisome^® underscores their efficacy in treating conditions ranging from cancer to fungal infections. Furthermore, this review delves into emerging trends, including stimuli-responsive and hybrid liposomes, as well as their integration with nanotechnology for enhanced therapeutic precision. As liposomes continue to expand their role in gene therapy, theranostics, and personalized medicine, this review highlights their potential to redefine pharmaceutical applications. Despite existing challenges, ongoing advancements in formulation techniques and scalability underscore the bright future of liposome-based therapeutics in addressing unmet medical needs. Full article

Background: Although antibiotic resistance is a well-known issue in veterinary medicine, studies proposing real-time therapeutic monitoring (TDM) are lacking. The objective of the present study was to develop a simple and rapid protocol for the real-time therapeutic monitoring of antibiotics in horses and dogs. Methods: A reliable TDM protocol should encompass guidelines for the definition of plasma/serum collection time points, sample management by the clinical staff, transportation to the laboratory, and the availability of robust and swift analytical technologies. Ampicillin and sulbactam were quantified using liquid chromatography–tandem mass spectrometry (LC-MS/MS) in the plasma or serum of animals treated with ampicillin alone or combined with sulbactam. Results: The method was successfully applied to samples collected from animals hospitalized in our veterinary hospital and proved helpful in understanding the pharmacokinetics of this antibiotic in critically ill patients. Conclusions: Combined with minimum inhibitory concentration (MIC) data, this approach enables PK/PD evaluations to support the development of personalized therapeutic strategies and optimized dosing regimens for animals. Full article

The application of whole-exome sequencing (WES) for diagnostic purposes has the potential to unravel secondary findings unrelated with the primary reason of testing. Some of those might be of high clinical utility and comprise disease-causing variants in genes, related to life-threatening and clinically actionable diseases. Clarifying the allelic frequencies of such variants in specific populations is a crucial step for the large-scale deployment of genomic medicine. We analysed medically relevant variants in the 81 genes from the American College of Medical Genetics and Genomics (ACMG) v3.2 list of actionable loci, using WES data from a diagnostic laboratory cohort of 3972 persons, tentatively resampled to represent the Portuguese population geographic distribution. We identified medically actionable variants in 6.2% of our cohort, distributed across several disease domains: cardiovascular disorders (3.0%), cancer predisposition (2.0%), miscellaneous disorders (1.1%), and metabolic disorders (0.1%). Additionally, we estimated a frequency of heterozygotes for recessive disease alleles of 11.1%. Overall, our results suggest that medically actionable findings can be identified in approximately 6.2% of persons from our population. This is the first study estimating medically actionable findings in Portugal. These results provide valuable insight for patients, healthcare providers, and policymakers involved in advancing genomic medicine at the national and international level. Full article

The rapid evolution of micro- and nano-architectures is revolutionizing biomedical engineering, particularly in the fields of therapeutic and diagnostic micromechanics. This review explores the recent innovations in micro- and nanostructured materials and their transformative impact on healthcare applications, ranging from drug delivery and tissue engineering to biosensing and diagnostics. Key advances in fabrication techniques, such as lithography, 3D printing, and self-assembly, have enabled unprecedented control over material properties and functionalities at microscopic scales. These engineered architectures offer enhanced precision in targeting and controlled release in drug delivery, foster cellular interactions in tissue engineering, and improve sensitivity and specificity in diagnostic devices. We examine critical design parameters, including biocompatibility, mechanical resilience, and scalability, which influence their clinical efficacy and long-term stability. This review also highlights the translational potential and current limitations in bringing these materials from the laboratory research to practical applications. By providing a comprehensive overview of the current trends, challenges, and future perspectives, this article aims to inform and inspire further development in micro- and nano-architectures that hold promise for advancing personalized and precision medicine. Full article

The analysis of human gait is a cornerstone in diagnosing and monitoring a variety of neuromuscular and orthopedic conditions. Recent technological advancements have paved the way for innovative methodologies that combine multimodal neuroimaging and eXtended Reality (XR) technologies to enhance the precision and applicability of gait analysis. This review explores the state-of-the-art solutions of an advanced gait analysis approach, a multidisciplinary concept that integrates neuroimaging, extended reality technologies, and sensor-based methods to study human locomotion. Several wearable neuroimaging modalities such as functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), commonly used to monitor and analyze brain activity during walking and to explore the neural mechanisms underlying motor control, balance, and gait adaptation, were considered. XR technologies, including virtual, augmented, and mixed reality, enable the creation of immersive environments for gait analysis, real-time simulation, and movement visualization, facilitating a comprehensive assessment of locomotion and its neural and biomechanical dynamics. This advanced gait analysis approach enhances the understanding of gait by examining both cerebral and biomechanical aspects, offering insights into brain–musculoskeletal coordination. We highlight its potential to provide real-time, high-resolution data and immersive visualization, facilitating improved clinical decision-making and rehabilitation strategies. Additionally, we address the challenges of integrating these technologies, such as data fusion, computational demands, and scalability. The review concludes by proposing future research directions that leverage artificial intelligence to further optimize multimodal imaging and XR applications in gait analysis, ultimately driving their translation from laboratory settings to clinical practice. This synthesis underscores the transformative potential of these approaches for personalized medicine and patient outcomes. Full article

Medical laboratories (MLs) are vital in global healthcare delivery, enhancing diagnostic accuracy and supporting clinical decision-making. This systematic review examines the multifaceted contributions of ML, emphasizing their importance in pandemic preparedness, disease surveillance, and the integration of innovative technologies such as artificial intelligence (AI). Medical laboratories are equally crucial to clinical practices, offering essential diagnostic services to identify diseases like infections, metabolic disorders, and malignancies. They monitor treatment effectiveness by analyzing patient samples, enabling healthcare providers to optimize therapies. Additionally, they support personalized medicine by tailoring treatments based on genetic and molecular data and ensure test accuracy through strict quality control measures, thereby enhancing patient care. The methodology for this systematic review follows the PRISMA-ScR guidelines to systematically map evidence and identify key concepts, theories, sources, and knowledge gaps related to the roles and impact of MLs in public health delivery. This review involved systematic searching and filtering of literature from various databases, focusing on studies from 2010 to 2024, primarily in Africa, Asia, and Europe. The selected studies were analyzed to assess their outcomes, strengths, and limitations regarding MLS roles, impacts, and integration within healthcare systems. The goal was to provide comprehensive insights and recommendations based on the gathered data. The article highlights the challenges that laboratories face, especially in low- and middle-income countries (LMICs), where resource constraints hinder effective healthcare delivery. It discusses the potential of AI to improve diagnostic processes and patient outcomes while addressing ethical and infrastructural challenges. This review underscores the necessity for collaborative efforts among stakeholders to enhance laboratory services, ensuring that they are accessible, efficient, and capable of meeting the evolving demands of healthcare systems. Overall, the findings advocate for strengthened laboratory infrastructures and the adoption of advanced technologies to improve health outcomes globally. Full article