P-248 Futility and utility of two-stage hepatectomy

Meeting abstract in the European-Society-for-Medical-Oncology (ESMO) 21st World Congress on Gastrointestinal Cancer.info:eu-repo/semantics/publishedVersio

Identification of clinical phenotypes in knee osteoarthritis: a systematic review of the literature

Background: Knee Osteoarthritis (KOA) is a heterogeneous pathology characterized by a complex and multifactorial nature. It has been hypothesised that these differences are due to the existence of underlying phenotypes representing different mechanisms of the disease.Methods: The aim of this study is to identify the current evidence for the existence of groups of variables which point towards the existence of distinct clinical phenotypes in the KOA population. A systematic literature search in PubMed was conducted. Only original articles were selected if they aimed to identify phenotypes of patients aged 18 years or older with KOA. The methodological quality of the studies was independently assessed by two reviewers and qualitative synthesis of the evidence was performed. Strong evidence for existence of specific phenotypes was considered present if the phenotype was supported by at least two high-quality studies.Results: A total of 24 studies were included. Through qualitative synthesis of evidence, six main sets of variables proposing the existence of six phenotypes were identified: 1) chronic pain in which central mechanisms (e.g. central sensitisation) are prominent; 2) inflammatory (high levels of inflammatory biomarkers); 3) metabolic syndrome (high prevalence of obesity, diabetes and other metabolic disturbances); 4) Bone and cartilage metabolism (alteration in local tissue metabolism); 5) mechanical overload characterised primarily by varus malalignment and medial compartment disease; and 6) minimal joint disease characterised as minor clinical symptoms with slow progression over time.Conclusions: This study identified six distinct groups of variables which should be explored in attempts to better define clinical phenotypes in the KOA population

Dynamic models of brain imaging data and their Bayesian inversion

This work is about understanding the dynamics of neuronal systems, in particular with respect to brain connectivity. It addresses complex neuronal systems by looking at neuronal interactions and their causal relations. These systems are characterized using a generic approach to dynamical system analysis of brain signals - dynamic causal modelling (DCM). DCM is a technique for inferring directed connectivity among brain regions, which distinguishes between a neuronal and an observation level. DCM is a natural extension of the convolution models used in the standard analysis of neuroimaging data. This thesis develops biologically constrained and plausible models, informed by anatomic and physiological principles. Within this framework, it uses mathematical formalisms of neural mass, mean-field and ensemble dynamic causal models as generative models for observed neuronal activity. These models allow for the evaluation of intrinsic neuronal connections and high-order statistics of neuronal states, using Bayesian estimation and inference. Critically it employs Bayesian model selection (BMS) to discover the best among several equally plausible models. In the first part of this thesis, a two-state DCM for functional magnetic resonance imaging (fMRI) is described, where each region can model selective changes in both extrinsic and intrinsic connectivity. The second part is concerned with how the sigmoid activation function of neural-mass models (NMM) can be understood in terms of the variance or dispersion of neuronal states. The third part presents a mean-field model (MFM) for neuronal dynamics as observed with magneto- and electroencephalographic data (M/EEG). In the final part, the MFM is used as a generative model in a DCM for M/EEG and compared to the NMM using Bayesian model selection

Polyhydroxyalkanoates Production by Mixed Microbial Culture under High Salinity

PTDC/BTA-BTA/30902/2017 UIDP/04378/2020 UIDB/04378/2020 LA/P/0140/2020The fishing industry produces vast amounts of saline organic side streams that require adequate treatment and disposal. The bioconversion of saline resources into value-added products, such as biodegradable polyhydroxyalkanoates (PHAs), has not yet been fully explored. This study investigated PHA production by mixed microbial cultures under 30 gNaCl/L, the highest NaCl concentration reported for the acclimatization of a PHA-accumulating mixed microbial culture (MMC). The operational conditions used during the culture-selection stage resulted in an enriched PHA-accumulating culture dominated by the Rhodobacteraceae family (95.2%) and capable of storing PHAs up to 84.1% wt. (volatile suspended solids (VSS) basis) for the highest organic loading rate (OLR) applied (120 Cmmol/(L.d)). This culture presented a higher preference for the consumption of valeric acid (0.23 ± 0.03 CmolHVal/(CmolX.h)), and the 3HV monomer polymerization (0.33 ± 0.04 CmmolHV/(CmmolX.h) was higher as well. As result, a P(3HB-co-3HV)) with high HV content (63% wt.) was produced in the accumulation tests conducted at higher OLRs and with 30 gNaCl/L. A global volumetric PHA productivity of 0.77 gPHA/(L.h) and a specific PHA productivity of 0.21 gPHA/(gX.h) were achieved. These results suggested the significant potential of the bioconversion of saline resources into value-added products, such as PHAs.publishersversionpublishe

Pontine and Extrapontine Myelinolysis

Introdução: A mielinólise define-se como uma doença desmielinizante aguda, associada a um quadro clínico de tetraplegia flácida e a incapacidade na fala e na deglutição. A patogenia em geral está associada a perturbações electrolíticas, particularmente hiponatrémia profunda e sua rápida correcção. A confirmação imagiológica do diagnóstico pode ser feita recorrendo à Ressonância Magnética Nuclear. Objectivo: Os autores fazem a descrição do caso clínico, evidenciando a sua evolução e programa de reabilitação instituído, realçando os ganhos da funcionalidade. São descritas também as intercorrências clínicas relevantes no atraso do diagnóstico. Caso clínico: Apresenta-se uma doente com antecedentes psiquiátricos e polidipsia, internada na sequência de um quadro convulsivo resistente à medicação, tendo sido identificada hiponatrémia e feita a sua correcção. Após a correcção a doente desenvolveu um quadro de tetraplegia e hipotonia generalizada, tendo realizado uma Ressonância Magnética compatível com o diagnóstico de mielinólise centropôntica e extrapôntica

Data-driven approach for incident management in a smart city

Buildings in Lisbon are often the victim of several types of events (such as accidents, fires, collapses, etc.). This study aims to apply a data-driven approach towards knowledge extraction from past incident data, nowadays available in the context of a Smart City. We apply a Cross Industry Standard Process for Data Mining (CRISP-DM) approach to perform incident management of the city of Lisbon. From this data-driven process, a descriptive and predictive analysis of an events dataset provided by the Lisbon Municipality was possible, together with other data obtained from the public domain, such as the temperature and humidity on the day of the events. The dataset provided contains events from 2011 to 2018 for the municipality of Lisbon. This data mining approach over past data identified patterns that provide useful knowledge for city incident managers. Additionally, the forecasts can be used for better city planning, and data correlations of variables can provide information about the most important variables towards those incidents. This approach is fundamental in the context of smart cities, where sensors and data can be used to improve citizens’ quality of life. Smart Cities allow the collecting of data from different systems, and for the case of disruptive events, these data allow us to understand them and their cascading effects better.info:eu-repo/semantics/publishedVersio

Portuguese Cucurbita spp. and Citrullus lanatus: conservation, evaluation and breeding

Cucurbitaceae is one of the most important families of vascular plants. This family includes 118 genera and 825 species. The five major cucurbit crops are Citrullus lanatus Thumb Mansf. (watermelon), Cucurbita maxima Duchesne (pumpkin), Cucurbita pepo L. (squash), Cucumis sativus L. (cucumber) and Cucumis melo L. (melon). Citrullus lanatus and Cucurbita spp. are very important in the Portuguese agro-ecosystems, associated with maize, beans and cabbage. Due to the importance of Citrullus and Cucurbita spp., the Portuguese National Genebank (BPGV) has done systematic collecting missions in Portugal (Mainland and Madeira Island). Since 2001, BPGV in partnership with other National Institutions, Escola Superior Agraria de Santarem, Direccao Regional de Agricultura e Pescas do Algarve and Universidade do Algarve, has been carrying out activities related to preservation, characterization, evaluation and pre-breeding. In Portugal, in BPGV, the Curcubitaceae collection preserved in ex situ conditions (medium and long term) totals 573 accessions. The collection of Citrullus lanatus and Cucurbita spp. has a total of 355 accessions, representing 62% of the whole collection: (37 of Citrullus lanatus, 19 of Cucurbita ficifolia, 74 of Cucurbita maxima and 224 of Cucurbita pepo). Based upon the diagnosis of the preserved collection, further germplasm collecting missions were recommended in Algarve Region. AFLP and RAPDs markers were used to check the assignment of accessions to Cucurbita species: C. pepo, C. maxima and C. moshata. The morphological characterization followed the Curcubita spp. and Citrullus descriptors, elaborated by Bioversity International, integrated in the European Cooperative Program for Genetic Resources, Cucurbits Working Group. Characterization data are reported herein. Departing from the most homogeneous accessions of Citrullus lanatus, Cucurbita maxima and C. moschata, three cultivars, one of each species, have already been selected and registered in the National Catalogue of Varieties

Pilot-scale valorisation of salmon peptone into polyhydroxyalkanoates by mixed microbial cultures under conditions of high ammonia concentration

publishedVersio

Multidisciplinary Development and Initial Validation of a Clinical Knowledge Base on Chronic Respiratory Diseases for mHealth Decision Support Systems

Most mobile health (mHealth) decision support systems currently available for chronic obstructive respiratory diseases (CORDs) are not supported by clinical evidence or lack clinical validation. The development of the knowledge base that will feed the clinical decision support system is a crucial step that involves the collection and systematization of clinical knowledge from relevant scientific sources and its representation in a human-understandable and computer-interpretable way. This work describes the development and initial validation of a clinical knowledge base that can be integrated into mHealth decision support systems developed for patients with CORDs. A multidisciplinary team of health care professionals with clinical experience in respiratory diseases, together with data science and IT professionals, defined a new framework that can be used in other evidence-based systems. The knowledge base development began with a thorough review of the relevant scientific sources (eg, disease guidelines) to identify the recommendations to be implemented in the decision support system based on a consensus process. Recommendations were selected according to predefined inclusion criteria: (1) applicable to individuals with CORDs or to prevent CORDs, (2) directed toward patient self-management, (3) targeting adults, and (4) within the scope of the knowledge domains and subdomains defined. Then, the selected recommendations were prioritized according to (1) a harmonized level of evidence (reconciled from different sources); (2) the scope of the source document (international was preferred); (3) the entity that issued the source document; (4) the operability of the recommendation; and (5) health care professionals' perceptions of the relevance, potential impact, and reach of the recommendation. A total of 358 recommendations were selected. Next, the variables required to trigger those recommendations were defined (n=116) and operationalized into logical rules using Boolean logical operators (n=405). Finally, the knowledge base was implemented in an intelligent individualized coaching component and pretested with an asthma use case. Initial validation of the knowledge base was conducted internally using data from a population-based observational study of individuals with or without asthma or rhinitis. External validation of the appropriateness of the recommendations with the highest priority level was conducted independently by 4 physicians. In addition, a strategy for knowledge base updates, including an easy-to-use rules editor, was defined. Using this process, based on consensus and iterative improvement, we developed and conducted preliminary validation of a clinical knowledge base for CORDs that translates disease guidelines into personalized patient recommendations. The knowledge base can be used as part of mHealth decision support systems. This process could be replicated in other clinical areas.info:eu-repo/semantics/publishedVersio