RESUMEN
Several trace metals, including iron, copper, manganese and zinc are essential for normal function of the nervous system. Both deficiency and excessive accumulation of these metals trigger neuropathological developments. The central nervous system (CNS) is in possession of dedicated homeostatic system that removes, accumulates, stores and releases these metals to fulfil nervous tissue demand. This system is mainly associated with astrocytes that act as dynamic reservoirs for trace metals, these being a part of a global system of CNS ionostasis. Here we overview physiological and pathophysiological aspects of astrocyte-cantered trace metals regulation.
Asunto(s)
Astrocitos , Oligoelementos , Cobre , Hierro , ZincRESUMEN
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairments, and behavioral changes. The presence of abnormal beta-amyloid plaques and tau protein tangles in the brain is known to be associated with AD. However, current limitations of imaging technology hinder the direct detection of these substances. Consequently, researchers are exploring alternative approaches, such as indirect assessments involving monitoring brain signals, cognitive decline levels, and blood biomarkers. Recent studies have highlighted the potential of integrating genetic information into these approaches to enhance early detection and diagnosis, offering a more comprehensive understanding of AD pathology beyond the constraints of existing imaging methods. Our study utilized electroencephalography (EEG) signals, genotypes, and polygenic risk scores (PRSs) as features for machine learning models. We compared the performance of gradient boosting (XGB), random forest (RF), and support vector machine (SVM) to determine the optimal model. Statistical analysis revealed significant correlations between EEG signals and clinical manifestations, demonstrating the ability to distinguish the complexity of AD from other diseases by using genetic information. By integrating EEG with genetic data in an SVM model, we achieved exceptional classification performance, with an accuracy of 0.920 and an area under the curve of 0.916. This study presents a novel approach of utilizing real-time EEG data and genetic background information for multimodal machine learning. The experimental results validate the effectiveness of this concept, providing deeper insights into the actual condition of patients with AD and overcoming the limitations associated with single-oriented data.
Asunto(s)
Enfermedad de Alzheimer , Electroencefalografía , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/fisiopatología , Humanos , Electroencefalografía/métodos , Femenino , Masculino , Aprendizaje Automático , Máquina de Vectores de Soporte , Anciano , Procesamiento de Señales Asistido por Computador , AlgoritmosRESUMEN
Worldwide, the incidence of major depressive disorder (MDD) is increasing annually, resulting in greater economic and social burdens. Moreover, the pathological mechanisms of MDD and the mechanisms underlying the effects of pharmacological treatments for MDD are complex and unclear, and additional diagnostic and therapeutic strategies for MDD still are needed. The currently widely accepted theories of MDD pathogenesis include the neurotransmitter and receptor hypothesis, hypothalamic-pituitary-adrenal (HPA) axis hypothesis, cytokine hypothesis, neuroplasticity hypothesis and systemic influence hypothesis, but these hypothesis cannot completely explain the pathological mechanism of MDD. Even it is still hard to adopt only one hypothesis to completely reveal the pathogenesis of MDD, thus in recent years, great progress has been made in elucidating the roles of multiple organ interactions in the pathogenesis MDD and identifying novel therapeutic approaches and multitarget modulatory strategies, further revealing the disease features of MDD. Furthermore, some newly discovered potential pharmacological targets and newly studied antidepressants have attracted widespread attention, some reagents have even been approved for clinical treatment and some novel therapeutic methods such as phototherapy and acupuncture have been discovered to have effective improvement for the depressive symptoms. In this work, we comprehensively summarize the latest research on the pathogenesis and diagnosis of MDD, preventive approaches and therapeutic medicines, as well as the related clinical trials.
Asunto(s)
Trastorno Depresivo Mayor , Humanos , Trastorno Depresivo Mayor/tratamiento farmacológico , Trastorno Depresivo Mayor/genética , Trastorno Depresivo Mayor/prevención & control , Sistema Hipotálamo-Hipofisario , Sistema Hipófiso-SuprarrenalRESUMEN
SUMMARY OBJECTIVE: We describe the case of a diabetic patient who developed vertebral osteomyelitis and bilateral psoas abscess with gas formation due to klebsiella pneumoniae. METHODS: A 64-year-old woman with a 4-year history of type-2 diabetes mellitus was admitted to the Emergency Department. The subject had a 2-day history of high-grade fever associated with chills and a 5-hour history of consciousness. She received empirical treatment with febrifuge, after which her fever decreased. RESULTS: Her fever recurred after an interval of three hours. A computed tomography scan of the abdomen revealed vertebral osteomyelitis and bilateral psoas muscle abscess with gas formation. Blood culture and purulent fluid described the growth of the Klebsiella pneumoniae. The patient received antibiotic therapy and bilateral drainage therapy after the drainage catheter was placed into the abscess cavity by CT-guidance. Due to the serious damage to the vertebral column and permanent pain, the patient underwent minimally invasive internal spinal fixation and recovered successfully. CONCLUSION: A case of vertebral osteomyelitis and bilateral psoas abscess with gas formation caused by Klebsiella pneumoniae in a diabetic patient. Antibiotic therapy, drainage, and minimally invasive internal spinal fixation were performed, which enabled a good outcome.
RESUMO OBJETIVO: Descrever o caso de uma paciente diabética que desenvolveu osteomielite vertebral e abcesso bilateral do psoas com formação de gás causada por klebsiella pneumoniae. MÉTODOS: Uma mulher de 64 anos de idade, com 4 anos de histórico de diabetes mellitus tipo 2, foi admitida no Serviço de Emergência. A paciente apresentava um quadro de dias de febre alta acompanhada de calafrios e um histórico de 5 horas de consciência. Ela recebeu tratamento empírico com antitérmico, após o qual a febre diminuiu. RESULTADOS: A febre retornou após um intervalo de três horas. Uma tomografia computadorizada do abdome revelou osteomielite vertebral e abcesso bilateral do músculo psoas com formação de gás. A cultura do sangue e o fluido purulento revelaram o crescimento de Klebsiella pneumoniae. A paciente recebeu antibióticos e terapia de drenagem bilateral após o cateter de drenagem ser posicionado na cavidade do abscesso com auxílio de TC. Devido a sérios danos à coluna vertebral e a dor permanente, a paciente foi submetida à fixação vertebral interna minimamente invasiva e recuperou-se com sucesso. CONCLUSÃO: Um caso de osteomielite vertebral e abscesso do psoas bilateral com a formação de gás causada por Klebsiella pneumoniae em uma paciente diabética. Antibioticoterapia, drenagem e fixação vertebral interna minimamente invasiva foram realizadas, o que permitiu um bom resultado.