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1.
Theory Biosci ; 143(2): 107-122, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38460025

RESUMO

We consider the standard neural field equation with an exponential temporal kernel. We analyze the time-independent (static) and time-dependent (dynamic) bifurcations of the equilibrium solution and the emerging spatiotemporal wave patterns. We show that an exponential temporal kernel does not allow static bifurcations such as saddle-node, pitchfork, and in particular, static Turing bifurcations. However, the exponential temporal kernel possesses the important property that it takes into account the finite memory of past activities of neurons, which Green's function does not. Through a dynamic bifurcation analysis, we give explicit bifurcation conditions. Hopf bifurcations lead to temporally non-constant, but spatially constant solutions, but Turing-Hopf bifurcations generate spatially and temporally non-constant solutions, in particular, traveling waves. Bifurcation parameters are the coefficient of the exponential temporal kernel, the transmission speed of neural signals, the time delay rate of synapses, and the ratio of excitatory to inhibitory synaptic weights.


Assuntos
Modelos Neurológicos , Neurônios , Sinapses , Neurônios/fisiologia , Sinapses/fisiologia , Algoritmos , Transmissão Sináptica , Animais , Humanos , Simulação por Computador , Fatores de Tempo , Rede Nervosa/fisiologia , Potenciais de Ação/fisiologia
2.
Int J Infect Dis ; 138: 63-72, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-37956899

RESUMO

OBJECTIVES: We investigated the impact of school reopening on SARS-CoV-2 transmission in Italy, Germany, and Portugal in autumn 2022 when the Omicron variant was prevalent. METHODS: A prospective international study was conducted using the case reproduction number (Rc) calculated with the time parametrization of Omicron. For Germany and Italy, staggered difference-in-differences analysis was employed to explore the causal relationship between school reopening and Rc changes, accounting for varying reopening dates. In Portugal, interrupted time series analysis was used due to simultaneous school reopenings. Multivariable models were adopted to adjust for confounders. RESULTS: In Italy and Germany, post-reopening Rc estimates were significantly lower compared to those from regions/states that had not yet reopened at the same time points, both in the student population (overall average treatment effect for the treated subpopulation [O-ATT]: -0.80 [95% CI: -0.94;-0.66] for Italy; O-ATT-0.30 [95% CI: -0.36;-0.23] for Germany) and the adult population (O-ATT: -0.04 [95% CI: -0.07;-0.01] for Italy; O-ATT: -0.07 [95% CI: -0.11;-0.03] for Germany). In Portugal, there was a significant decreasing trend in Rc following school reopenings compared to the pre-reopening period (sustained effect: -0.03 [95% CI: -0.04; -0.03] in students; -0.02 [95% CI: -0.03; -0.02] in adults). CONCLUSIONS: We found no evidence of a causal relationship between school reopenings in autumn 2022 and Omicron SARS-CoV-2 transmission.


Assuntos
COVID-19 , Adulto , Humanos , Portugal/epidemiologia , COVID-19/epidemiologia , Estudos Prospectivos , SARS-CoV-2 , Alemanha/epidemiologia , Itália/epidemiologia , Instituições Acadêmicas
3.
BMC Infect Dis ; 23(1): 684, 2023 Oct 13.
Artigo em Inglês | MEDLINE | ID: mdl-37833640

RESUMO

BACKGROUND: Post-COVID-19 condition refers to persistent or new onset symptoms occurring three months after acute COVID-19, which are unrelated to alternative diagnoses. Symptoms include fatigue, breathlessness, palpitations, pain, concentration difficulties ("brain fog"), sleep disorders, and anxiety/depression. The prevalence of post-COVID-19 condition ranges widely across studies, affecting 10-20% of patients and reaching 50-60% in certain cohorts, while the associated risk factors remain poorly understood. METHODS: This multicentre cohort study, both retrospective and prospective, aims to assess the incidence and risk factors of post-COVID-19 condition in a cohort of recovered patients. Secondary objectives include evaluating the association between circulating SARS-CoV-2 variants and the risk of post-COVID-19 condition, as well as assessing long-term residual organ damage (lung, heart, central nervous system, peripheral nervous system) in relation to patient characteristics and virology (variant and viral load during the acute phase). Participants will include hospitalised and outpatient COVID-19 patients diagnosed between 01/03/2020 and 01/02/2025 from 8 participating centres. A control group will consist of hospitalised patients with respiratory infections other than COVID-19 during the same period. Patients will be followed up at the post-COVID-19 clinic of each centre at 2-3, 6-9, and 12-15 months after clinical recovery. Routine blood exams will be conducted, and patients will complete questionnaires to assess persisting symptoms, fatigue, dyspnoea, quality of life, disability, anxiety and depression, and post-traumatic stress disorders. DISCUSSION: This study aims to understand post-COVID-19 syndrome's incidence and predictors by comparing pandemic waves, utilising retrospective and prospective data. Gender association, especially the potential higher prevalence in females, will be investigated. Symptom tracking via questionnaires and scales will monitor duration and evolution. Questionnaires will also collect data on vaccination, reinfections, and new health issues. Biological samples will enable future studies on post-COVID-19 sequelae mechanisms, including inflammation, immune dysregulation, and viral reservoirs. TRIAL REGISTRATION: This study has been registered with ClinicalTrials.gov under the identifier NCT05531773.


Assuntos
COVID-19 , SARS-CoV-2 , Feminino , Humanos , Estudos de Coortes , COVID-19/epidemiologia , Fadiga/epidemiologia , Fadiga/etiologia , Síndrome de COVID-19 Pós-Aguda , Estudos Prospectivos , Qualidade de Vida , Estudos Retrospectivos , Masculino
4.
Clin Nutr ESPEN ; 43: 442-447, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-34024553

RESUMO

BACKGROUNDS: Coronary artery disease (CAD) is the major cause of mortality and morbidity globally. Diet is known to contribute to CAD risk, and the dietary intake of specific macro- or micro-nutrients might be potential predictors of CAD risk. Machine learning methods may be helpful in the analysis of the contribution of several parameters in dietary including macro- and micro-nutrients to CAD risk. Here we aimed to determine the most important dietary factors for predicting CAD. METHODS: A total of 273 cases with more than 50% obstruction in at least one coronary artery and 443 healthy controls who completed a food frequency questionnaire (FFQ) were entered into the study. All dietary intakes were adjusted for energy intake. The QUEST method was applied to determine the diagnosis pattern of CAD. RESULTS: A total of 34 dietary variables obtained from the FFQ were entered into the initial study analysis, of these variables 23 were significantly associated with CAD according to t-tests. Of these 23 dietary input variables, adjusted protein, manganese, biotin, zinc and cholesterol remained in the model. According to our tree, only protein intake could identify the patients with coronary artery stenosis according to angiography from healthy participant up to 80%. The dietary intake of manganese was the second most important variable. The accuracy of the tree was 84.36% for the training dataset and 82.94% for the testing dataset. CONCLUSION: Among several dietary macro- and micro-nutrients, a combination of protein, manganese, biotin, zinc and cholesterol could predict the presence of CAD in individuals undergoing angiography.


Assuntos
Doença da Artéria Coronariana , Doença da Artéria Coronariana/diagnóstico , Doença da Artéria Coronariana/epidemiologia , Mineração de Dados , Proteínas Alimentares , Ingestão de Energia , Humanos , Fatores de Risco
5.
Genomics ; 112(6): 3871-3882, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32619574

RESUMO

The present study aimed to identify the genes associated with the involvement of adjunct lymph nodes of patients with prostate cancer (PCa) and to provide valuable information for the identification of potential diagnostic biomarkers and pathological genes in PCa metastasis. The most important candidate genes were identified through several machine learning approaches including K-means clustering, neural network, Naïve Bayesian classifications and PCA with or without downsampling. In total, 21 genes associated with lymph nodes involvement were identified. Among them, nine genes have been identified in metastatic prostate cancer, six have been found in the other metastatic cancers and four in other local cancers. The amplification of the candidate genes was evaluated in the other PCa datasets. Besides, we identified a validated set of genes involved in the PCa metastasis. The amplification of SPAG1 and PLEKHF2 genes were associated with decreased survival in patients with PCa.


Assuntos
Antígenos de Superfície/genética , Biologia Computacional/métodos , Proteínas de Ligação ao GTP/genética , Metástase Linfática/genética , Neoplasias da Próstata/patologia , Aprendizado de Máquina Supervisionado , Aprendizado de Máquina não Supervisionado , Proteínas de Transporte Vesicular/genética , Análise por Conglomerados , Conjuntos de Dados como Assunto , Humanos , Masculino , Neoplasias da Próstata/genética
6.
Theory Biosci ; 135(4): 217-230, 2016 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-27488866

RESUMO

In this paper, we consider a four dimensional model of the human immunodeficiency virus-1 (HIV-1) with delay, which is an extension of some three dimensional models. We approach the treatment problem by adding two controllers to the system for inhibiting viral production. The optimal controller [Formula: see text] is considered for vaccine and [Formula: see text] for the drug. The Pontryagin maximum principle with delay is used to characterize these optimal controls. At the end, numerical results are presented to illustrate the optimal solutions. The validity of the model was confirmed by proper semi-quantitative simulation of some clinical data. The model was used to predict the possible beneficial effects of vaccine and anti-retroviral drug administration in HIV-1 disease.


Assuntos
Infecções por HIV/prevenção & controle , HIV-1/patogenicidade , Algoritmos , Linfócitos T CD4-Positivos/virologia , Simulação por Computador , Infecções por HIV/terapia , Humanos , Modelos Teóricos , Reprodutibilidade dos Testes , Vacinação
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