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Projeto de investigação
Center for Mathematics and Applications
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Publicações
Comparing two block estimation procedures for the extremal index: An application
Publication . Gomes, Dora Prata; Neves, Manuela
When extending the analysis of the limiting behaviour of the extreme values from independent and identically distributed
sequences to stationary sequences a key parameter appears, the extremal index θ, whose accurate estimation is not easy and is not
completely solved. Here we focus on the estimation of θ using blocks estimators, that can be constructed by using disjoint or sliding
blocks. Both blocks construction require the choice of a threshold and a block length. The main objective of this work is to revisit
another block estimation procedure that only depends on the block length, although some conditions on the underlying process
need to be verified. An application will be presented for illustrating the proposed procedure
Detection of JCV or BKV viruria and viremia after kidney transplantation is not associated with unfavorable outcomes
Publication . Querido, Sara; Weigert, Andre; Pinto, Iola; Papoila, Ana Luísa; Pessanha, Maria Ana; Gomes, Perpétua; Adragão, Teresa; Paixão, Paulo
Studies analyzing the relationship between BK polyomavirus (BKV) or JC polyomavirus (JCV) infection and kidney transplant (KT) long term clinical outcomes are scarce. Therefore, we evaluated this relationship in a single-center retrospective cohort of 288 KT patients followed for 45.4(27.5; 62.5) months. Detection of BKV viremia in two consecutive analyses led to discontinuation of antimetabolite and initiation of mammalian target of rapamycin inhibitor. Outcome data included de novo BKV and/or JCV viremia and/or viruria after KT, death-censored graft survival and patient survival. BKV viruria and viremia were detected in 42.4% and 22.2% of KT recipients, respectively. BKV viremic patients had higher urinary BKV viral loads at the onset of viruria, when compared to nonviremic patients (7 log10 vs. 4.9 log10 cp/mL, p < 0.001). JCV viruria was identified in 38.5% of KT patients; the 5.9% of KT recipients who developed JCV viremia had higher JCV urinary viral loads at the onset of viruria, when compared to non-viremic patients (5.3 vs. 3.7 log10 cp/mL, p = 0.034). No differences were found in estimated glomerular filtration rate at the end of follow up, when comparing BKV or JCV viruric or viremic patients with nonviremic patients. No association was found between JCV or BKV viruria or viremia and death/graft failure. Therefore, higher BKV urinary viral loads at the onset could serve as an early maker of over immunosuppression. JCV and BKV replication was not associated with inferior clinical outcomes in KT patients with the above-mentioned immunosuppression strategy.
TCox : correlation-based regularization applied to colorectal cancer survival data
Publication . Peixoto, Carolina; Lopes, Marta B.; Martins, Marta; Costa, Luis; Vinga, Susana
Colorectal cancer (CRC) is one of the leading causes of mortality and morbidity in the world. Being a heterogeneous disease, cancer therapy and prognosis represent a significant challenge to medical care. The molecular information improves the accuracy with which patients are classified and treated since similar pathologies may show different clinical outcomes and other responses to treatment. However, the high dimensionality of gene expression data makes the selection of novel genes a problematic task. We propose TCox, a novel penalization function for Cox models, which promotes the selection of genes that have distinct correlation patterns in normal vs. tumor tissues. We compare TCox to other regularized survival models, Elastic Net, HubCox, and OrphanCox. Gene expression and clinical data of CRC and normal (TCGA) patients are used for model evaluation. Each model is tested 100 times. Within a specific run, eighteen of the features selected by TCox are also selected by the other survival regression models tested, therefore undoubtedly being crucial players in the survival of colorectal cancer patients. Moreover, the TCox model exclusively selects genes able to categorize patients into significant risk groups. Our work demonstrates the ability of the proposed weighted regularizer TCox to disclose novel molecular drivers in CRC survival by accounting for correlation-based network information from both tumor and normal tissue. The results presented support the relevance of network information for biomarker identification in high-dimensional gene expression data and foster new directions for the development of network-based feature selection methods in precision oncology.
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Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
6817 - DCRRNI ID
Número da atribuição
UIDB/00297/2020