ABSTRACT
Abstract In recent decades, there have been significant advances in the diagnosis of diffuse gliomas, driven by the integration of novel technologies. These advancements have deepened our understanding of tumor oncogenesis, enabling a more refined stratification of the biological behavior of these neoplasms. This progress culminated in the fifth edition of the WHO classification of central nervous system (CNS) tumors in 2021. This comprehensive review article aims to elucidate these advances within a multidisciplinary framework, contextualized within the backdrop of the new classification. This article will explore morphologic pathology and molecular/genetics techniques (immunohistochemistry, genetic sequencing, and methylation profiling), which are pivotal in diagnosis, besides the correlation of structural neuroimaging radiophenotypes to pathology and genetics. It briefly reviews the usefulness of tractography and functional neuroimaging in surgical planning. Additionally, the article addresses the value of other functional imaging techniques such as perfusion MRI, spectroscopy, and nuclear medicine in distinguishing tumor progression from treatment-related changes. Furthermore, it discusses the advantages of evolving diagnostic techniques in classifying these tumors, as well as their limitations in terms of availability and utilization. Moreover, the expanding domains of data processing, artificial intelligence, radiomics, and radiogenomics hold great promise and may soon exert a substantial influence on glioma diagnosis. These innovative technologies have the potential to revolutionize our approach to these tumors. Ultimately, this review underscores the fundamental importance of multidisciplinary collaboration in employing recent diagnostic advancements, thereby hoping to translate them into improved quality of life and extended survival for glioma patients.
Resumo Nas últimas décadas, houve avanços significativos no diagnóstico de gliomas difusos, impulsionados pela integração de novas tecnologias. Esses avanços aprofundaram nossa compreensão da oncogênese tumoral, permitindo uma estratificação mais refinada do comportamento biológico dessas neoplasias. Esse progresso culminou na quinta edição da classificação da OMS de tumores do sistema nervoso central (SNC) em 2021. Esta revisão abrangente tem como objetivo elucidar esses avanços de forma multidisciplinar, no contexto da nova classificação. Este artigo irá explorar a patologia morfológica e as técnicas moleculares/genéticas (imuno-histoquímica, sequenciamento genético e perfil de metilação), que são fundamentais no diagnóstico, além da correlação dos radiofenótipos da neuroimagem estrutural com a patologia e a genética. Aborda sucintamente a utilidade da tractografia e da neuroimagem funcional no planejamento cirúrgico. Destacaremos o valor de outras técnicas de imagem funcional, como ressonância magnética de perfusão, espectroscopia e medicina nuclear, na distinção entre a progressão do tumor e as alterações relacionadas ao tratamento. Discutiremos as vantagens das diferentes técnicas de diagnóstico na classificação desses tumores, bem como suas limitações em termos de disponibilidade e utilização. Além disso, os crescentes avanços no processamento de dados, inteligência artificial, radiômica e radiogenômica têm grande potencial e podem em breve exercer uma influência substancial no diagnóstico de gliomas. Essas tecnologias inovadoras têm o potencial de revolucionar nossa abordagem a esses tumores. Em última análise, esta revisão destaca a importância fundamental da colaboração multidisciplinar na utilização dos recentes avanços diagnósticos, com a esperança de traduzi-los em uma melhor qualidade de vida e uma maior sobrevida.
ABSTRACT
Abstract Precision medicine has revolutionized the field of neuroimmunology, with innovative approaches that characterize diseases based on their biology, deeper understanding of the factors leading to heterogeneity within the same disease, development of targeted therapies, and strategies to tailor therapies to each patient. This review explores the impact of precision medicine on various neuroimmunological conditions, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), optic neuritis, autoimmune encephalitis, and immune-mediated neuropathies. We discuss advances in disease subtyping, recognition of novel entities, promising biomarkers, and the development of more selective monoclonal antibodies and cutting-edge synthetic cell-based immunotherapies in neuroimmunological disorders. In addition, we analyze the challenges related to affordability and equity in the implementation of these emerging technologies, especially in situations with limited resources.
Resumo A medicina de precisão está revolucionando o campo da neuroimunologia, com uma abordagem inovadora caracterizada pela classificação de doenças com base em sua biologia, compreensão mais profunda dos fatores que levam à heterogeneidade dentro da mesma doença, desenvolvimento de terapias com alvos específicos e estratégias para adaptar as terapias a cada paciente. Esta revisão explora o impacto da medicina de precisão em várias condições neuroimunológicas, incluindo esclerose múltipla (EM), distúrbio do espectro da neuromielite óptica (NMOSD), doença associada ao anticorpo anti-glicoproteína da mielina do oligodendrócito (MOGAD), neurites ópticas, encefalites autoimunes e neuropatias imunomediadas. Discutimos avanços na subclassificação de doenças, reconhecimento de novas entidades, biomarcadores promissores e desenvolvimento de anticorpos monoclonais mais seletivos e imunoterapias de ponta baseadas em células sintéticas para as condições acima. Além disso, analisamos os desafios relacionados com acessibilidade e equidade na implementação dessas tecnologias emergentes, especialmente em ambientes com recursos limitados.
ABSTRACT
Resumen ChatGPT es un asistente virtual con inteligencia artificial que utiliza lenguaje natural para comunicarse, es decir, mantiene conversaciones como las que se tendrían con otro humano. Puede aplicarse en educación a todos los niveles, que incluye la educación médica, tanto para la formación, la investigación, la escritura de artículos científicos, la atención clínica y la medicina personalizada. Puede modificar la interacción entre médicos y pacientes para mejorar los estándares de calidad de la atención médica y la seguridad, por ejemplo, al sugerir medidas preventivas en un paciente que en ocasiones no son consideradas por el médico por múltiples causas. Los usos potenciales del ChatGPT en la educación médica, como una herramienta de ayuda en la redacción de artículos científicos, un asistente en la atención para pacientes y médicos para una práctica más personalizada, son algunas de las aplicaciones que se analizan en este artículo. Los aspectos éticos, originalidad, contenido inapropiado o incorrecto, citas incorrectas, ciberseguridad, alucinaciones y plagio son ejemplos de las situaciones a tomar en cuenta al usar las herramientas basadas en inteligencia artificial en medicina.
Abstract ChatGPT is a virtual assistant with artificial intelligence (AI) that uses natural language to communicate, i.e., it holds conversations as those that would take place with another human being. It can be applied at all educational levels, including medical education, where it can impact medical training, research, the writing of scientific articles, clinical care, and personalized medicine. It can modify interactions between physicians and patients and thus improve the standards of healthcare quality and safety, for example, by suggesting preventive measures in a patient that sometimes are not considered by the physician for multiple reasons. ChatGPT potential uses in medical education, as a tool to support the writing of scientific articles, as a medical care assistant for patients and doctors for a more personalized medical approach, are some of the applications discussed in this article. Ethical aspects, originality, inappropriate or incorrect content, incorrect citations, cybersecurity, hallucinations, and plagiarism are some examples of situations to be considered when using AI-based tools in medicine.
ABSTRACT
Resumen La epilepsia es un trastorno neurológico caracterizado por crisis epilépticas recurrentes no provocadas, en el cual la genética tiene un factor etiológico importante. Durante las últimas décadas se ha logrado encontrar genes específicos involucrados en la patogénesis de esta condición. Actualmente existen múltiples exámenes disponibles en la práctica clínica para el diagnóstico genético, siendo los más útiles los paneles multi-genes y la secuenciación del exoma completo por medio de next generation sequencing (NGS). El tener un diagnósti co genético puede mejorar la calidad de vida de cada paciente y su familia, al mismo tiempo que nos ayuda a individualizar el tratamiento haciéndolo más eficaz. Algunos ejemplos en los que el diagnóstico genético puede modificar la conducta terapéutica incluyen el gen SCN1A en que se recomienda no utilizar medicamentos bloqueadores de canales de sodio y el gen SLC2A1 en el que se recomienda el inicio de la dieta cetogénica. El futuro de la investigación en medicina de precisión en epilepsia es muy prometedor, con el objetivo de que cada paciente reciba un tratamiento acorde a su etio logía genética.
Abstract Epilepsy is a neurological disorder characterized by recurrent unprovoked seizures. It is known that genetics play an important etiology roll. During the last decades it has been possible to find specific genes involved in the pathogenesis of this condition. There are currently multiple studies available in clinical practice for genetic diagnosis, the most useful being the next generation se quencing (NGS) techniques with multi-gene panels and whole exome sequencing. Having a genetic diagnosis can help improve the quality of life of each patient and their family, while it helps us to individualize the treatment, making it more effective. Some examples in which ge netic diagnosis can modify therapeutic conduct include the SCN1A gene, in which it is recommended not to use drugs that block Sodium channels, and the SLC2A1 gene, in which starting ketogenic diet is recommended. The future of precision medicine research in epilepsy is very promising, with the goal that each patient receives treatment according to their genetic etiology.
ABSTRACT
A pesquisa em telemedicina possibilitou a captação de medidas fisiológicas para encontrar biomarcadores do comportamento humano durante o uso de smartphones chamados fenótipos digitais. A identificação e avaliação desses biomarcadores para diagnóstico da saúde fornece subsídios a uma área afim da telemedicina, a medicina de precisão. Foi desenvolvido um aplicativo para celular chamado Neuropesquisa, que possui recursos voltados a encontrar esses biomarcadores enquanto os usuários preenchem escalas psicológicas para saúde mental. O objetivo foi correlacionar mindfulness, ansiedade e tempo de reação e rastrear possíveis fenótipos digitais dessas pessoas. Realizou-se um estudo observacional, de delineamento correlacional, transversal e remoto com 364 adultos pelo Neuropesquisa. Foram encontradas correlações positivas e significativas entre mindfulness e tempo de reação, e negativas e significativas para ansiedade e tempo de reação. Concluiu-se que Neuropesquisa foi capaz de identificar fenótipos digitais dentre os constructos avaliados, de relevante importância para medicina de precisão e saúde mental.
Research in telemedicine has made it possible to capture regulatory measures to find biomarkers of human behavior during smartphone use called digital phenotypes. The identification and evaluation of these biomarkers for health diagnosis provide gains for an area related to telemedicine, precision medicine. It was developed a mobile application called Neuropesquisa, which has features to find these biomarkers while users complete psychological scales for mental health. The aim was to correlate mindfulness, anxiety and reaction time, and track possible digital phenotypes of users. This was an observational study, with a cross-sectional, correlational, and remote design with 364 adults, through Neuropesquisa. There were positive correlations between mindfulness and reaction time, and negative correlations between anxiety and reaction time. It was concluded that Neuropesquisa was able to identify digital phenotypes among the considered constructs, of relevant importance for precision medicine and mental health.
ABSTRACT
Corneal refractive surgery is widely used to correct myopia and astigmatism because of its safety, effectiveness and stability.Precision medicine is the future direction of development, and the demands for accuracy in corneal refractive surgery are also increasing, which has a direct impact on patient satisfaction.Nomogram, as a key design in refractive surgery, needs to be combined with several important predictors to quantify individual risk.Different surgical methods need different nomograms.In this paper, the effects of corneal surface surgery, lamellar surgery, modeling algorithm and possible factors such as patient's sex, age, expected correction, corneal curvature, preoperative spherical equivalent, etc.on the predicted values were discussed.At the same time, the application of nomograms in corneal refractive surgery at home and abroad in recent years and the research progress of nomogram influencing factors were explored, in order to provide more and more accurate reference for clinical practice, to improve the accuracy of corneal refractive surgery and help patients achieve satisfactory postoperative visual quality.
ABSTRACT
@#Artificial intelligence (AI) has developed rapidly in the twentieth century, and has substantialy changed the modern way of life.At the same time, AI has greatly contributed to the development of the pharmaceutical industry, playing a key role in precision medicine, intelligent diagnosis, computer-aided drug design, and clinical trial decision-making, and has also greatly developed itself through its integration with the pharmaceutical industry.This paper outlines the key issues in research, describes the key applications of AI in the health and pharmaceutical industries, and finally analyzes the opportunities and challenges of AI in the health pharmaceutical industry to provide reference for the development of AI in the health and pharmaceutical fields.
ABSTRACT
The incidence of bladder cancer is increasing annually, and the gold standard for its diagnosis relies on histopathological biopsy. Whole-slide digitization technology can produce thousands of high-resolution captured pathological images and has greatly promoted the development of digital pathology. Deep learning, as a new method of artificial intelligence, has achieved remarkable results in the analysis of pathological images for tumor diagnosis, molecular typing, and prediction of prognosis and recurrence of bladder cancer. Traditional pathology relies heavily on the professional level and experience of pathologists; as such, it is highly subjective and has poor reproducibility. Deep learning can automatically extract image features. It can also improve diagnostic efficiency and repeatability and reduce missed and misdiagnosed rates when used to assist pathologists in making decisions. This technology cannot only alleviate the pressure of the current shortage of skilled workforce and uneven medical resources but also promote the development of precision medicine. This article reviews the latest research progress and prospects of deep learning in pathological image analysis of bladder cancer.
ABSTRACT
Lung cancer remains to have the highest morbidity and mortality rates in China among known malignant tumors. Novel drugs and regimens have been sought because of the limited efficiency of traditional chemotherapy and radiotherapy in lung cancer treatment. In the last 20 years, rapid developments in molecular targeted therapy and immunotherapy have increased clinical efficacy and benefitted patients with cancer. Treatments for lung cancer are the most rapidly developed among treatments for solid tumors, pioneering tumor precision medicine. This manuscript reviews the evolution and development of targeted therapy and immunotherapy and discusses existing problems and future directions in the precision therapy of lung cancer.
ABSTRACT
The aging society has led to a substantial increase in the number of clinical comorbidities. To meet the needs of comorbidity treatment, polypharmacy is widely used in clinical practice. However, polypharmacy has drawbacks such as treatment conflict. Same treatment of different diseases refers to treating different diseases with same treatment. Therefore, the principle of same treatment of different diseases can alleviate the problems caused by polypharmacy. Under the research background of precision medicine, it becomes possible to explore the mechanism of same treatment of different diseases and achieve its clinical application. However, drugs successfully developed in the past have revealed shortcomings in clinical use. To better interpret the mechanism of precision medicine for same treatment of different diseases, under the multi-dimensional attributes including dynamic space and time, omics was performed, and a new strategy of tensor decomposition was proposed. With the characteristics of complete data, tensor decomposition is advantageous in data mining and can fully grasp the connotation of precision treatment of different diseases with same treatment under dynamic spatiotemporal changes. This method is used for drug repositioning in some biocomputations. By taking advantage of the dimensionality reduction of tensor decomposition and integrating the dual influences of time and space, this study achieved accurate target prediction of same treatment of different diseases at each stage, and discovered the mechanism of precision medicine of same treatment for different diseases, providing scientific support for precision prescription and treatment of different diseases with same treatment in clinical practice. This study thus conducted preliminary exploration of the pharmacological mechanism of precision Chinese medicine treatment.
Subject(s)
Humans , Data Mining , Medicine, East Asian Traditional , Precision MedicineABSTRACT
Knowledge of an underlying genetic predisposition to cancer allows the use of personalised prognostic, preventive and therapeutic strategies for the patient and carries clinical implications for family members. Despite great progress, we identified six challenging areas in the management of patients with hereditary cancer predisposition syndromes and suggest recommendations to aid in their resolution. These include the potential for finding unexpected germline variants through somatic tumour testing, optimal risk management of patients with hereditary conditions involving moderate-penetrance genes, role of polygenic risk score in an under-represented Asian population, management of variants of uncertain significance, clinical trials in patients with germline pathogenic variants and technology in genetic counselling. Addressing these barriers will aid the next step forward in precision medicine in Singapore. All stakeholders in healthcare should be empowered with genetic knowledge to fully leverage the potential of novel genomic insights and implement them to provide better care for our patients.
Subject(s)
Humans , Singapore , Genotype , Neoplasms/therapy , Risk Factors , FamilyABSTRACT
RESUMEN El artículo se interroga por los alcances y los límites del paradigma de la medicina de precisión y su relación con el enfoque de la salud colectiva. Para ello, se toma la evaluación genética preimplantatoria o PGT (preimplantation genetic testing) dado que constituye un ejemplo paradigmático de tecnologías que apuntan a la "individualización" de los procesos de salud. En esta dirección, se revisan las características y los fundamentos científico-normativos acerca de las tecnologías PGT en Argentina, y el camino que queda por recorrer para su análisis bioético. De manera más específica, se visibilizan algunas de las condiciones de posibilidad para su implementación desde la perspectiva norte-sur. Como síntesis del análisis, proponemos tres ejes o nudos problemáticos relacionados con los sesgos en la producción de conocimiento, los valores e intereses subyacentes a sus usos y los presupuestos epistemológicos que operan en la base de estas tecnologías. A lo largo de este trabajo, presentamos estos dilemas y sugerimos algunas recomendaciones para ser tenidas en cuenta en futuras investigaciones.
ABSTRACT This article examines the scope and limitations of the precision medicine paradigm and its relationship with the collective health approach. To that end, it takes preimplantation genetic testing (PGT) as a paradigmatic example of technologies aimed at the "individualization" of health processes. In this regard, we review the characteristics and scientific and regulatory foundations of PGT technologies in Argentina, and discuss the next steps for their bioethical analysis. More specifically, we shed light on some of the conditions for their implementation from a north-south perspective. We propose three themes or problematic aspects as a synthesis of our analysis, related to biases in the production of knowledge, the values and interests underlying its uses, and the underlying epistemological assumptions of these technologies. Throughout the article, we review these dilemmas and suggest some issues that should be taken into account in future research.
ABSTRACT
Recientes investigaciones han relacionado la microbiota intestinal con la salud humana en múltiples aspectos. La evolución de los estilos de vida ha determinado un cambio en la composición de las bacterias intestinales, así como la implicación que la comunidad de estas ejerce sobre la salud. Actualmente, se conoce que la mayoría de las bacterias presentes en el sistema gastrointestinal pertenecen principalmente a los fila Firmicutes y Bacterioidetes, aunque también se encuentran otros grupos tales como proteobacterias y actinobacterias. A medida que se avanza en el tracto gastrointestinal predominan algunos géneros de bacterias. Los efectos de la microbiota pueden ser directos e indirectos, además, dependen de muchos factores tales como la edad de la persona, el grupo etario, la genética del individuo, la dieta y el estilo de vida. Durante los últimos años, la accesibilidad a tecnologías de secuenciación ha permitido tener un acercamiento más estrecho a la microbiota intestinal. Esto, sumado a herramientas bioinformáticas, ha permitido establecer relaciones microbiales entre la cantidad y estructura poblacional y las manifestaciones clínicas en el ser humano. Algunas de las afecciones estudiadas y que tienen relación con la microbiota intestinal son: la obesidad, la diabetes, el cáncer, las enfermedades relacionadas con el cerebro, las enfermedades cardiovasculares y las enfermedades gastrointestinales. De acuerdo con lo mencionado, se hizo una recopilación de información de carácter científico en cuanto a estudios relevantes que describen la relación microbiota-salud humana y casos donde se observa compromiso del organismo, al mismo tiempo que se describen opciones terapéuticas propuestas y un abordaje de perspectivas futuras.
Recent research has linked gut microbiota to human health in multiple ways. The evolution of lifestyles has determined a change in the composition of intestinal bacteria, as well as the implications that they exert on health. Currently, it is known that most of the bacteria present in the gastrointestinal sector belong mainly to the phylum Firmicutes and Bacterioidetes, although there are also other groups such as proteobacteria and actinobacteria. As it progresses through the gastrointestinal tract, some genera of bacteria and species predominate. The effects of the microbiota can be direct and indirect, and also depend on many factors such as the age of the person, the age group, the individual's genetics, diet, and lifestyle. In recent years, accessibility to sequencing technologies has allowed for a closer approach to the intestinal microbiota. This, added to bioinformatic tools has allowed establishing microbial relationships in terms of quantity and population structure with clinical manifestations in humans. Some of the pathologies studied that are related to intestinal microbiota are obesity, diabetes, cancer, brain-related diseases, cardiovascular diseases, and gastrointestinal diseases. A compilation of scientific information is made regarding relevant studies that describe the microbiota-human health relationship, cases where the organism is affected, as well as proposed therapeutic options and an approach to future perspectives
Subject(s)
Gastrointestinal Microbiome , Probiotics , Prebiotics , MultiomicsABSTRACT
ABSTRACT Objective: To develop a Web App from a predictive model to estimate the risk of Intensive Care Unit (ICU) admission for patients with covid-19. Methods: An applied technological production research was carried out with the development of Streamlit using Python, considering the decision tree model that presented the best performance (AUC 0.668). Results: Based on the variables associated with Precision Nursing, Streamlit stratifies patients admitted to clinical units who are most likely to be admitted to the Intensive Care Unit, serving as a decision-making support tool for healthcare professionals. Final considerations: The performance of the model may have been influenced by the start of vaccination during the data collection period, however, the Web App via Streamlit proved to be a feasible tool for presenting research results, due to the ease of understanding by nurses and its potential for supporting clinical decision-making.
RESUMEN Objetivo: Desarrollar una Web App a partir de un modelo predictivo para estimar el riesgo de ingreso a la Unidad de Cuidados Intensivos (UCI) para pacientes con covid-19. Métodos: Se realizó una investigación de producción tecnológica aplicada con el desarrollo de Streamlit utilizando Python, considerando el modelo de árbol de decisiones que presentó el mejor rendimiento (AUC 0.668). Resultados: Basado en las variables asociadas con la Enfermería de Precisión, Streamlit estratifica a los pacientes ingresados en unidades clínicas que tienen más probabilidades de ser admitidos en la Unidad de Cuidados Intensivos, sirviendo como una herramienta de apoyo para la toma de decisiones para los profesionales de la salud. Consideraciones finales: El rendimiento del modelo puede haber sido influenciado por el inicio de la vacunación durante el período de recolección de datos. La Web App a través de Streamlit demostró ser una herramienta factible para presentar los resultados, debido a la facilidad de comprensión y su potencial para apoyar la toma de decisiones clínicas.
RESUMO Objetivo: Desenvolver um Web App a partir de um modelo preditivo para estimar o risco de internação de pacientes com covid-19 em UTI. Métodos: Realizou-se uma pesquisa aplicada de produção tecnológica com o desenvolvimento do Streamlit a partir do Python, considerando o modelo de árvore de decisão que apresentou o melhor desempenho (AUC 0.668). Resultados: A partir das variáveis associadas à Enfermagem de Precisão, o Streamlit estratifica os pacientes internados nas unidades clínicas com maior probabilidade de internação em Unidade de Terapia Intensiva, funcionando como uma ferramenta de apoio à tomada de decisão dos profissionais de saúde. Considerações finais: A performance do modelo pode ter sido influenciada pelo início da vacinação no período de coleta de dados, no entanto, o Web App via Streamlit mostrou-se uma ferramenta viável para a apresentação dos resultados de pesquisa, devido à facilidade de entendimento por parte dos enfermeiros e pelo potencial de apoio à decisão clínica.
ABSTRACT
@#Rare diseases, also known as "orphan diseases", refer to diseases with very low incidence. Countries and regions define rare diseases according to epidemiological standards, economic standards of rare drugs and disease severity. The World Health Organization (WHO) has suggested the prevalence rate of less than 6.5 to 10 per 10 000 people to define rare diseases. In May 2018, "China's First List of Rare Diseases" was released, including 121 rare diseases. Most rare diseases are hereditary diseases with early onset, severe disease, and poor prognosis. About 75% of rare genetic diseases occur in the neonatal period or childhood, which are important part of human birth defects and brings a huge burden to society and families. The effective prevention and treatment of rare diseases is one of the important goals of building a "Healthy China". With the development of molecular biology technology and the continuous research and development of advanced medical products in the field of gene therapy, the level of clinical diagnosis and treatment of rare diseases has risen to a new level, which provides a possibility for the cure of some rare diseases. In China, most rare diseases rely on imported drugs, which cost a lot and bring heavy economic burden to patients. Improving the medical insurance system for rare diseases has become a difficult point in the current medical reform. This paper mainly discusses the definition of rare diseases, the research status, efforts and future development direction of rare diseases in China, in order to deepen the understanding and response of medical workers and the whole society to rare diseases.
ABSTRACT
Approximately 30%-40% of rare diseases are related to the endocrine and metabolic system, and abnormal metabolism of carbohydrate accounts for a significant proportion among others. Carbohydrate metabolic rare disorders often develop insidiously. The clinical symptoms of these disorders sometimes overlap with common diseases. Therefore, delayed diagnosis, misdiagnosis, and mismanagement happen often. The diagnosis and treatment of carbohydrate metabolic rare disorders is usually difficult in clinical practice. Efficient and practical screening models, identification of specific clinical features and biochemical changes, and genomic sequencing are critical to improve diagnostic efficiency. Most carbohydrate metabolic rare disorders are still lack in effective and targeted therapies. So, the symptomatic treatment is still main practice. The targeted medications and gene therapies based on precision diagnosis are directions for the diagnosis and management of rare disorders of carbohydrate metabolism in the future. In this paper, we classify the carbohydrate metabolic rare disorders based on their causes. We also discuss the current status and prospective of diagnosis and management of those diseases.
ABSTRACT
Deep phenotyping is a precise and comprehensive approach used for the precise analysis and comprehensive assessment of multi-system phenotypes of the patients. The approach uses symptoms, signs, various medical examination and laboratory results, and other relevant medical information. In the clinical diagnosis and medical research of rare bone diseases, deep phenotyping plays a pivotal role. The realization of precision medicine primarily comprises three key dimensions: deep phenotyping, stratified medicine, and targeted therapy. The deep phenotyping is the basis for the latter two. Deep phenotyping not only facilitates fine subtyping of diseases, but also allows for the in-depth understanding of genetic data. The use of deep phenotyping requires stand- ardized terminology and specific procedures. Moreover, deep phenotyping shows substantial potential using the application of artificial intelligence technology particularly when combining with multi-omics techniques.
ABSTRACT
Metabolomics technology played an important role in the field of biomedical research, such as disease diagnosis, pathogenesis analysis, drug target exploration, formulation of treatment guidelines, etc. Due to the systematic and holistic characteristics of metabolomics research, it has shown certain advantages in the analysis of the basis of pharmacodynamic substances of traditional Chinese medicines and the development of new medicines from traditional Chinese medicines. With the continuous innovation of metabolomics research, many advanced technologies have been developed, which make up for the shortcomings of conventional metabolomics studies in searching for disease targets, identifying functional compounds and interpreting biological significance. Furthermore, the rapid development of metabolomics technology has created new opportunities for the diagnosis of diseases and the development of new drugs in traditional Chinese medicine. Herein, different from conventional metabolomics techniques and methods, nine new metabolomics technologies with wide application prospects in the past 10 years were reviewed from the perspective of new tools, new ideas and new samples, with a view to providing new insights on relevant metabolomics research in the biomedical field and providing new motivation for innovation and development of metabolomics technologies.
ABSTRACT
It has been noted for decades that cancer is essentially a genomic disease. Benefiting from the latest development of high-throughput sequencing and bioinformatics technologies, a variety of genetic alterations have been identified for their roles in cancer occurrence and development, giving rise to new opportunities for anti-cancer drug discovery. In particular, the rapid advancement of cancer genomics has paved the way for the precision medicine that has gained compelling achievement in the past years and significantly benefited cancer patients. In this review, we summarize the main types of genomic abnormalities in cancer, the application of functional genomics research in cancer research, and in particular the translational application of cancer genomics in clinical diagnosis, drug discovery and cancer precision medicine. With this review, we hope to better understand cancer genomics research and provide future perspectives for its application in precision medicine.
ABSTRACT
@#The umbrella trial has received increasing attention in the design of clinical trials for oncology drugs in recent years. This trial design categorizes a single disease into multiple sub-types based on predictive biomarkers or other predictive factors, and simultaneously evaluates the efficacy of multiple targeted therapies. When compared with the traditional drug development model of phase Ⅰ, phaseⅡ, and phase Ⅲ randomized controlled trials, umbrella trials are a more scientifically rigorous trial design that can speed up drug evaluation to address the conflict between numerous untested drugs and diseases with a lack of effective treatment options. This article will focus on the concept, main characteristics, eligibility criteria, design and statistical considerations, ethical considerations, and future directions of umbrella trials, with the aim of providing methodological guidance for the design of clinical trials for oncology drugs.