Search results for "Personalized medicine"
showing 10 items of 90 documents
Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data
2020
The statistical analysis of the information generated by medical follow-up is a very important challenge in the field of personalized medicine. As the evolutionary course of a patient's disease progresses, his/her medical follow-up generates more and more information that should be processed immediately in order to review and update his/her prognosis and treatment. Hence, we focus on this update process through sequential inference methods for joint models of longitudinal and time-to-event data from a Bayesian perspective. More specifically, we propose the use of sequential Monte Carlo (SMC) methods for static parameter joint models with the intention of reducing computational time in each…
RNA-Seq Atlas—a reference database for gene expression profiling in normal tissue by next-generation sequencing
2012
Abstract Motivation: Next-generation sequencing technology enables an entirely new perspective for clinical research and will speed up personalized medicine. In contrast to microarray-based approaches, RNA-Seq analysis provides a much more comprehensive and unbiased view of gene expression. Although the perspective is clear and the long-term success of this new technology obvious, bioinformatics resources making these data easily available especially to the biomedical research community are still evolving. Results: We have generated RNA-Seq Atlas, a web-based repository of RNA-Seq gene expression profiles and query tools. The website offers open and easy access to RNA-Seq gene expression pr…
Use of Machine Learning and Artificial Intelligence to Drive Personalized Medicine Approaches for Spine Care
2020
Personalized medicine is a new paradigm of healthcare in which interventions are based on individual patient characteristics rather than on “one-size-fits-all” guidelines. As epidemiological datasets continue to burgeon in size and complexity, powerful methods such as statistical machine learning and artificial intelligence (AI) become necessary to interpret and develop prognostic models from underlying data. Through such analysis, machine learning can be used to facilitate personalized medicine via its precise predictions. Additionally, other AI tools, such as natural language processing and computer vision, can play an instrumental part in personalizing the care provided to patients with …
Defining new biotypes in Prostate Cancer for diagnosis, prognosis and therapeutic intervention
2015
El cáncer de próstata (CaP) es el segundo tumor más frecuente en hombres y la sexta causa de muerte por cáncer. Así pues, esta enfermedad constituye un problema socio-sanitario prioritario para el sistema de Salud Pública. Actualmente, las herramientas para orientar el diagnóstico en CaP (PSA y DRE) no son cáncer específicas y presentan distintas limitaciones tales como el alto número de falsos positivos (aproximadamente un 70% en un rango de PSA de 4-10 ng/ml) que dan lugar a complicaciones asociadas con el proceso de biopsia. Además, un gran número de los CaP diagnosticados son tumores de bajo grado implicando un sobre-diagnóstico y sobre-tratamiento de esta enfermedad. Sin embargo, otros…
Molecular Pathways Implicated in Radioresistance of Glioblastoma Multiforme: What Is the Role of Extracellular Vesicles?
2023
Glioblastoma multiforme (GBM) is a primary brain tumor that is very aggressive, resistant to treatment, and characterized by a high degree of anaplasia and proliferation. Routine treatment includes ablative surgery, chemotherapy, and radiotherapy. However, GMB rapidly relapses and develops radioresistance. Here, we briefly review the mechanisms underpinning radioresistance and discuss research to stop it and install anti-tumor defenses. Factors that participate in radioresistance are varied and include stem cells, tumor heterogeneity, tumor microenvironment, hypoxia, metabolic reprogramming, the chaperone system, non-coding RNAs, DNA repair, and extracellular vesicles (EVs). We direct our a…
Air Pollution: Role of Extracellular Vesicles-Derived Non-Coding RNAs in Environmental Stress Response
2023
Air pollution has increased over the years, causing a negative impact on society due to the many health-related problems it can contribute to. Although the type and extent of air pollutants are known, the molecular mechanisms underlying the induction of negative effects on the human body remain unclear. Emerging evidence suggests the crucial involvement of different molecular mediators in inflammation and oxidative stress in air pollution-induced disorders. Among these, non-coding RNAs (ncRNAs) carried by extracellular vesicles (EVs) may play an essential role in gene regulation of the cell stress response in pollutant-induced multiorgan disorders. This review highlights EV-transported ncRN…
Biomarkers in reproductive medicine: the quest for new answers.
2015
Personalized medicine in assisted reproductive technologies (ART) is still in its infancy. Precision medicine, based on objective molecular tools added, to clinical medicine is well-accepted and developed in oncology and other potent medical disciplines. The impact of personalized medicine in cancer is broad, from screening to diagnosis, with the stratification of patients into cancer subgroup categories, facilitating individualized therapies that impact treatment effectiveness and disease recurrence (Diamandis et al., 2010; Hamburg and Collins, 2010). In reproductive medicine many ‘unknown black boxes’ still exist. These will only be unraveled with the timely application of novel technolog…
Is Structured Exercise Performed with Supplemental Oxygen a Promising Method of Personalized Medicine in the Therapy of Chronic Diseases?
2020
Aim: This systematic review aimed to explore the literature to identify in which types of chronic diseases exercise with supplemental oxygen has previously been utilized and whether this type of personalized therapy leads to superior effects in physical fitness and well-being. Methods: Databases (PubMed/MEDLINE, CINHAL, EMBASE, Web of knowledge and Cochrane Library) were searched in accordance with PRISMA. Eligibility criteria included adult patients diagnosed with any type of chronic diseases engaging in supervised exercise training with supplemental oxygen compared to normoxia. A random-effects model was used to pool effect sizes by standardized mean differences (SMD). Results: Out of the…
Clinical Development of Mepolizumab for the Treatment of Severe Eosinophilic Asthma: On the Path to Personalized Medicine.
2021
The development of mepolizumab, an anti-IL-5 monoclonal antibody for the treatment of severe eosinophilic asthma, is an example of a clinical development program that evolved over time based on sound, basic scientific principles. Initial clinical data on the effects of mepolizumab on lung function in a general asthmatic population were disappointing. However, it became clear that mepolizumab may be more effective against other clinical endpoints, particularly asthma exacerbations, in patients with more severe disease. Furthermore, a developing understanding of asthma disease pathobiology led to the identification of an appropriate target population and predictive biomarker for mepolizumab t…
Immunologic microenvironment and personalized treatment in multiple myeloma.
2013
Introduction: Multiple myeloma (MM) is characterized by generalized immune suppression and increased susceptibility to infections and secondary malignancies. Malignant plasma cells (PCs) modulate the bone marrow microenvironment to favor their own survival and proliferation. These events lead to a severe deregulation of immune effectors. Extensive studies have been conducted to unveil the mechanisms through which MM cells negatively modulate immunity and to develop therapeutical approaches for restoring an efficient anti-MM immune response. Areas covered: This review article covers both the immunosuppressive effects exerted by MM and the immunomodulatory potential of novel anti-MM agents. A…