Browsing by Author "Pinto, Pedro"
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- Boosting additive circular economy ecosystems using blockchain: An exploratory case studyPublication . Ferreira, Inês A.; Godina, Radu; Pinto, António; Pinto, Pedro; Carvalho, HelenaThe role of new technologies such as additive manufacturing and blockchain technology in designing and implementing circular economy ecosystems is not a trivial issue. This study aimed to understand if blockchain technology can be an enabler tool for developing additive symbiotic networks. A real case study was developed regarding a circular economy ecosystem in which a fused granular fabrication 3D printer is used to valorize polycarbonate waste. The industrial symbiosis network comprised four stakeholders: a manufacturing company that produces polycarbonate waste, a municipality service responsible for the city waste management, a start-up holding the 3D printer, and a non-profit store. It was identified a set of six requirements to adopt the blockchain technology in an additive symbiotic network, bearing in mind the need to have a database to keep track of the properties of the input material for the 3D printer during the exchanges, in addition to the inexistence of mechanisms of trust or cooperation between well-established industries and the additive manufacturing industry. The findings suggested a permissioned blockchain to support the implementation of the additive symbiotic network, namely, to enable the physical transactions (quantity and quality of waste material PC sheets) and monitoring and reporting (additive manufacturing technology knowledge and final product’s quantity and price). Future research venues include developing blockchain-based systems that enhance the development of additive symbiotic networks.
- Combined germline and tumor mutation signature testing identifies new families with NTHL1 tumor syndromePublication . Pinto, Carla; Guerra, Joana; Pinheiro, Manuela; Escudeiro, Carla; Santos, Catarina; Pinto, Pedro; Porto, Miguel; Bartosch, Carla; Silva, João; Peixoto, Ana; Teixeira, Manuel R.NTHL1 tumor syndrome is an autosomal recessive rare disease caused by biallelic inactivating variants in the NTHL1 gene and which presents a broad tumor spectrum. To contribute to the characterization of the phenotype of this syndrome, we studied 467 index patients by KASP assay or next-generation sequencing, including 228 patients with colorectal polyposis and 239 patients with familial/personal history of multiple tumors (excluding multiple breast/ovarian/polyposis). Three NTHL1 tumor syndrome families were identified in the group of patients with polyposis and none in patients with familial/personal history of multiple tumors. Altogether, we identified nine affected patients with polyposis (two of them diagnosed after initiating colorectal cancer surveillance) with biallelic pathogenic or likely pathogenic NTHL1 variants, as well as two index patients with one pathogenic or likely pathogenic NTHL1 variant in concomitance with a missense variant of uncertain significance. Here we identified a novel inframe deletion classified as likely pathogenic using the ACMG criteria, supported also by tumor mutational signature analysis. Our findings indicate that the NTHL1 tumor syndrome is a multi-tumor syndrome strongly associated with polyposis and not with multiple tumors without polyposis.
- Cross-Layer Admission Control to Enhance the Support of Real-Time Applications in WSNPublication . Pinto, Pedro; Pinto, António; Ricardo, ManuelReal-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.
- Frequency of CDH1, CTNNA1 and CTNND1 germline variants in families with diffuse and mixed gastric cancerPublication . Guerra, Joana; Pinto, Carla; Pinto, Pedro; Pinheiro, Manuela; Santos, Catarina; Peixoto, Ana; Escudeiro, Carla; Barbosa, Ana; Porto, Miguel; Francisco, Inês; Lopes, Paula; Isidoro, Ana Raquel; Cunha, Ana Luísa; Albuquerque, Cristina; Claro, Isabel; Oliveira, Carla; Silva, João; Teixeira, Manuel R.Hereditary diffuse gastric cancer (HDGC) is caused by germline pathogenic variants in the CDH1 and CTNNA1 genes and is characterized by a high prevalence of diffuse gastric cancer and lobular breast cancer. We aimed to evaluate the contribution of CTNNA1 and CTNND1 germline variants to HDGC, as well as to compare the frequencies of CDH1 and CTNNA1 (and eventually CTNND1) germline variants between patients with diffuse and mixed gastric carcinomas. In this study, we report a deleterious CTNNA1 germline variant and four CDH1 pathogenic variants in patients with criteria for genetic testing. None of the cases with mixed gastric cancer carried pathogenic variants in either the CDH1 or the CTNNA1 genes, so there is no evidence to use this tumor type in testing criteria.
- Improving genetic diagnostics for patients with negative exome sequencing using AI- powered genome analysisPublication . Ribeiro, Joana; Faria, Brígida Mónica; Pinto, Pedro; Sá, Joaquim; Faria, Brigida MonicaNext-generation sequencing (NGS) can be performed using several different platforms. Detecting DNA alterations that affect human health is now possible because of NGS technologies [1]. Despite the advancements in NGS, challenges persist, particularly in cases where traditional exome sequencing yields negative results. Sequencing of the entire genome provides global information about exons and introns, which can reveal the regulatory components of genes, such as promoters, enhancers, and intronic regulators, and structural variants, like copy number variants, inversions, and translocations [2],[3]. As with any technology, DNA sequencing has its limitations. Despite these limitations, DNA sequencing technology has revolutionised our understanding of cellular physiology in health and disease [1]. Although these steps do not directly involve bioinformatics per se, they may have downstream consequences on the bioinformatics algorithms used. This study focuses on the analysis and performance of genome sequencing in patients with negative exome results. Leveraging AI technology, our study explores both non-coding and coding regions of the genome, aiming to unlock hidden insights. For this project, the data were collected from patients with a negative result for Whole Exome sequencing (WES) and who were resequenced for the Whole Genome Sequencing (WGS) approach. After, the raw data was treated by Emedgene (AI- algorithm-based software) and afterwards the results between techniques were compared and statistically treated using SPSS software. The results were based on 16 selected cases with a negative exome diagnosis but with a diagnosis result from other complementary techniques. The first analysis appreciation shows that at least in 80% of the cases, the diagnosis could be assumed with WGS using this specific AI- algorithm. The implications of AI genome analysis, showcase the potential to provide more accurate and conclusive genetic diagnoses, improving patient care and treatment decisions. Bridging the gap left by traditional exome sequencing offers a promising avenue for precision medicine and personalized healthcare.
- MEC vs MCC: análise do desempenho de aplicações interativas e de tempo realPublication . Soares, Micael; Pinto, Pedro; Mamede, JorgeA evolução das redes de telecomunicações tem promovido o desenvolvimento de novas aplicações para dispositivos móveis. Algumas destas aplicações exigem requisitos computacionais e energéticos que vão para além das capacidades dos dispositivos móveis. Neste contexto, pode ser utilizada a arquitetura Mobile Cloud Computing (MCC), que permite executar as aplicações em datacenters na cloud e aliviar o processamento nos dispositivos móveis. No entanto, algumas aplicações mais exigentes, e.g. interativas e de tempo real, são mais sensíveis ao atraso no processamento e comunicação da informação. Para estas aplicações, a arquitetura Mobile Edge Computing (MEC) pode ser utilizada como uma tecnologia intermédia que disponibiliza recursos computacionais e de armazenamento a partir da periferia da rede. Este artigo apresenta um estudo que avalia o desempenho das arquiteturas MCC e MEC na execução de duas aplicações tomadas como representativas do espectro das aplicações interativas, de tempo real e de processamento intensivo: o Fluid e o FaceSwap. São apresentados resultados que permitem quantificar o desempenho destas arquiteturas em diferentes circunstâncias.