An insight into biomolecules for the treatment of skin infectious diseases

In assigning priorities, skin infectious diseases are frequently classified as minor when compared to infectious diseases of high mortality rates, such as tuberculosis or HIV. However, skin infections are amongst the most common and prevalent diseases worldwide. Elderly individuals present an increased susceptibility to skin infections, which may develop atypical signs and symptoms or even complicate pre-existing chronic disorders. When the skin fails to correct or inhibit the action of certain pathogenic microorganisms, biomolecules endowed with antimicrobial features are frequently administered topically or systemically to assist or treat such conditions. (1) Antibiotics, (2) antimicrobial peptides, or (3) natural extracts display important features that can actively inhibit the propagation of these pathogens and prevent the evolution of infectious diseases. This review highlights the properties and mechanisms of action of these biomolecules, emphasizing their effects on the most prevalent and difficult to treat skin infections caused by pathogenic bacteria, fungi, and viruses. The versatility of biomolecules’ actions, their symbiotic effects with skin cells and other inherent antimicrobial components, and their target-directed signatures are also explored hereFoundation for Science and Technology of Portugal (FCT), FEDER via Portugal 2020 Competitive Factors Operational Program (POCI), and the Government of Portugal (OE) for supporting the projects PTDC/CTM-TEX/28074/2017 (POCI-01-0145-FEDER028074) and UID/CTM/00264/202

Frontiers in antimicrobial biomaterials

[Excerpt] Biomaterials can be used as implantable devices or drug delivery platforms, which have significant impacts on the patient’s quality of life. Indeed, every year, a substantial number of new biomaterials and scaffolding systems are engineered and introduced in the biomedical field, with increased health benefits observed, as reported by Spalek et al. [1]. However, their long-term use can be threatened by the adhesion and proliferation of microorganisms, which can interact and form biofilms, or by the formation of fibrosis and consequent triggered cytotoxic responses. Pathogenic microorganisms may cause local infections and lead to implant failures

Laparoscopic versus Robotic gastric cancer surgery: Short-term Outcomes. Systematic Review and Meta-analysis of 25 521 patients

Introdução: O cancro gástrico possui a terceira maior taxa de mortalidade oncológica a nível mundial. Ainda não existe um consenso relativamente à técnica cirúrgica mais apropriada para realizar a cirurgia de resseção curativa. Objetivo: Comparar as gastrectomias laparoscópica e robótica, tendo em conta os resultados a curto prazo, em doentes com cancro gástrico. Materiais e Métodos: Esta revisão sistemática foi realizada de acordo as Guidelines PRISMA. Pesquisámos os seguintes tópicos: "Gastrectomy", Laparoscopic" e "Robotic Surgical Procedures". Incluímos os estudos que comparavam os resultados a curto prazo entre as gastrectomias laparoscópica e robótica. O risco de viés individual foi analisado através da escala MINORS. Resultados: Não houve diferenças significativas entre a gastrectomia robótica e a gastrectomia laparoscópica no que diz respeito à probabilidade de conversão, probabilidade de reoperação, mortalidade, complicações, deiscência da anastomose, distâncias das margens de resseção distal e proximal e probabilidade de recorrência. Contudo, a média da perda hemática (Diferença de Médias - DM - -19,43 mL, p<0,00001), o tempo de internamento (DM -0,50 dias, p=0,0007), o tempo até à primeira flatulência (DM -0,52 dias, p<0,00001), o tempo até ingestão oral (DM -0,17 dias, p=0,0001), as complicações cirúrgicas com classificação de Clavien-Dindo ≥ III (Risco Relativo - RR - 0,68, p<0,0001) e as complicações pancreáticas (RR 0,51, p=0,007) foram significativamente menores no grupo submetido a cirurgia robótica. O número de nódulos linfáticos removidos foi significativamente maior no grupo submetido a cirurgia robótica. Em contrapartida, a cirurgia robótica apresentou um tempo operatório (DM 41,19 min, p<0,00001) e um custo (DM 3684,27 dólares americanos, p<0,00001) significativamente maiores. Conclusão: Esta meta-análise favorece a escolha da cirurgia robótica no que concerne às complicações cirúrgicas mais relevantes. Contudo, o maior tempo operatório e o seu custo elevado ainda permanecem limitações importantes. Deste modo, são necessários mais ensaios clínicos aleatorizados, com o intuito de evidenciar as vantagens e desvantagens da gastrectomia robótica.Background: Gastric cancer has the third highest cancer-related mortality worldwide. There is no consensus regarding the optimal surgical technique to perform curative resection surgery. Objective: Compare laparoscopic and robotic gastrectomy regarding short-term outcomes in patients with gastric cancer. Materials and Methods: This systematic review was conducted according to the PRISMA guidelines. We searched the following topics: "Gastrectomy", "Laparoscopic" and "Robotic Surgical Procedures". The included studies compared short-term outcomes between laparoscopic and robotic gastrectomy. Individual risk of bias was assessed with the MINORS scale. Results: There were no significant differences between robotic gastrectomy (RG) and laparoscopic gastrectomy (LG) regarding conversion rate, reoperation rate, mortality, overall complications, anastomotic leakage, distal and proximal resection margin distances, and recurrence rate. However, mean blood loss (mean difference - MD - -19.43 mL, p<0.00001), length of stay (MD -0.50 days, p=0.0007), time to first flatus (MD -0.52 days, p<0.00001), time to oral intake (MD -0.17 days, p=0.0001), surgical complications with a Clavien-Dindo grade ≥ III (relative risk - RR - 0.68, p<0.0001), and pancreatic complications (RR 0.51, p=0.007) were significatively lower in the RG group. Furthermore, the number of retrieved lymph nodes was significantly higher in the RG group. Nevertheless, the RG group showed a significantly higher operation time (MD 41.19 min, p<0.00001) and cost (MD 3684.27 US Dollars, p<0.00001). Conclusion: This meta-analysis supports the choice of robotic surgery over laparoscopy concerning relevant surgical complications. However, longer operation time and higher cost remain crucial limitations. Randomized clinical trials are required to clarify the advantages and disadvantages of RG

Green antimicrobials

[Excerpt] In the last couple of years, the awareness of climate change and high pollution levels have raised our sense of ecological responsibility. Pharmaceutical industries play a major role in these issues; as such, alternatives must be found. New environmentally friendly approaches to deal with the growing concern associated with antimicrobial-resistant bacteria are also in great demand. The excessive consumption and misuse of these agents have accelerated the rise of such pathogens responsible for compromising global health—not only the health of humans, but also the health of all living systems.This research was funded by the Portuguese Foundation for Science and Technology (FCT) via grant UID/CTM/00264/2020 of 2C2T Strategic Project 2020–2023. H.P.F. also acknowledges the FCT for Auxiliary Researcher contract 2021.02720.CEECIND

3D Lung Nodule Classification in Computed Tomography Images

Lung cancer is the leading cause of cancer death worldwide. One of the reasons is the absence of symptoms at an early stage, which means that it is only discovered at a later stage, where the treatment is more difficult [1]. Furthermore, when making a diagnosis, frequently done by reading computed tomographies (CT's), it is regularly allied with errors. One of the reasons is the variation of the opinion of the doctors regarding the diagnosis of the same nodule [2,3].The use of CADx, Computer-Aided Diagnosis, systems can be a great help for this problem by assisting doctors in diagnosis with a second opinion. Although its efficiency has already been proven [4], it often ends up not being used because doctors can not understand the "how and why" of CADx diagnostic results, and ultimately do not trust the system [5]. To increase the radiologists' confidence in the CADx system it is proposed that along with the results of malignancy prediction, there are also results with evidence that explains those malignancy results.There are some visible features in lung nodules that are correlated with malignancy. Since humans are able to visually identify these characteristics and correlate them with nodule malignancy, one way to present those evidence is to make predictions of those characteristics. To have these predictions it is proposed to use deep learning approaches. Convolutional neural networks had shown to outperform the state of the art results in medical image analysis [6]. To predict the characteristics and malignancy in CADx system, the architecture HSCNN, a deep hierarchical semantic convolutional neural network, proposed by Shen et al. [7], will be used.The Lung Image Database Consortium image collection (LIDC-IDRI) public dataset is frequently used as input for lung cancer CADx systems. The LIDC-IDRI consists of thoracic CT scans, presenting a lot of data's quantity and variability. In most of the nodules, this dataset has doctor's evaluations for 9 different characteristics. A recurrent problem in those evaluations is the subjectivity of the doctors' interpretation in what each characteristic is. In some characteristics, it can result in a great divergence in evaluations regarding the same nodule, which makes the inclusion of those evaluations as an input in CADx systems not useful as it could be. To reduce this subjectivity, it is proposed the creation of a metric that makes the characteristics classification more objective. For this, it is planned bibliographic and LIDC-IDRI dataset reviews. With that, taking into account this new metric, validated after by doctors from Hospital de São João, will be made a reclassification in LIDC-IDRI dataset. This way it could be possible to use as input all the relevant characteristics. The principal objective of this dissertation is to develop a lung nodule CADx system methodology which promotes the confidence of specialists in its use. This will be made classifying lung nodules according to relevant characteristics to diagnosis and malignancy. The reclassified LIDC-IDRI dataset will be used as an input for CADx system and the architecture used for predicting the characteristics and malignancy results will be the HSCNN. To measure the classification evaluation will be used sensitivity, sensibility, and area under the Receiver Operating Characteristic (ROC), curve. The proposed solution may be used for improving a CADx system, LNDetector, currently in development by the Center for Biomedical Engineering Research (C-BER) group from INESC-TEC in which this work will be developed.[1] - S. Sone M. Hasegawa and S. Takashima. Growth rate of small lung cancels detected on mass ct screening. Tire British Journal of Radiology, pages 1252-1259[2] - D. J. Bell S. E. Marley P. Guo H. Mann M. L. Scott L. H. Schwartz D. C. Ghiorghiu B. Zhao, Y. Tan. Exploring intra-and inter-reader variability in uni-dimensional, bi-dimensional, and volumetric measurements of solid tumors on ct scans reconstructed at different slice intervals. European journal of radiology 82, page 959-968, 2013[3] - H.T Winer-Muram. The solitary pulmonary nodule 1. Radiology, 239, pages 39-49, 2006.[4] - R. Yan J. Lee L. C. Chu C. T. Lin A. Hussien J. Rathmell B. Thomas C. Chen et al. P. Huang, S. Park. Added value of computer-aided ct image features for early lung cancer diagnosis with small pulmonary nodules: A matched case-control study. Radiology 286, page 286-295, 2017[5] - W Jorritsma, Fokie Cnossen, and Peter Van Ooijen. Improving the radiologist-cad interaction: Designing for appropriate trust. Clinical Radiology, 70, 10 2014.[6] - Tom Brosch, Youngjin Yoo, David Li, Anthony Traboulsee, and Roger Tam. Modeling the variability in brain morphology and lesion distribution in multiple sclerosis by deep learning. Volume 17, 09 2014.[7] - Simon Aberle Deni A. T. Bui Alex Hsu Willliam Shen, Shiwen X. Han. An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification. june 201

Multilabel classification of unstructured data using Crunchbase

Our work compares different methods and models for multilabel text classification using information collected from Crunchbase, a large database that holds information of more than 600000 companies. Each company is labeled with one more categories, from a subset of 46 possible, and the proposed models predict the categories based solely on the company textual description. A number of natural language processing strategies have been tested for feature extraction, including stemming, lemmatization, and Part-of-Speech Tagging. This is a highly unbalanced dataset, where the frequency of each category ranges from 0.7% to 28%. The first experiment, is a Multiclass classification problem that tries to find the most probable category using only one model for all categories, with an overall score of 67% using SVM, Naive Bayes and Fuzzy Fingerprints. The second experiment uses makes use of multiple classifiers, one for each category, and tries to predict the complete set of categories for each company, with an overal score of 73% precision and 47% recall. The resulting models may constitute an important asset for automatic classification of texts, not only consisting of company descriptions, but also other texts, such as web pages, text blogs, news pages, etc.Este trabalho compara diferentes métodos e modelos para classificação de texto utilizando informação proveniente do Crunchbase, uma grande base de dados que contém dados sobre mais de 600000 empresas. Cada empresa está associada a uma ou mais categorias, de 46 possiveis, e os modelos propostos utilizam apenas a descrição de cada empresa para prever a sua categoria. Foram aplicadas várias técnicas de processamento de linguagem natural para extração de informação incluindo "stemming", lematização e "Part-of-Speech Tagging". Este "dataset" é altamente desiquilibrado, a frequência de cada categoria vai desde 0.7% a 28%. A primeira experiência, é um problema multiclasse que tenta encontrar qual a categoria mais provável para uma empresa utilizando apenas um modelo para todas as categorias, obtendo um resultado global de 67% de "accuracy" utilizando SVM, Naive Bayes e Fuzzy Fingerprints. A segunda experiência utiliza vários classificadores, um por cada categoria, para atribuir todas as categorias de uma determinada empresa obtendo resultados de 73% de precisão e 47% de "recall". Os modelos resultantes do nosso trabalho podem ser um ativo importante para a classificação automática de texto, não só para descrições de empresas mas também para outros textos, como páginas de Internet, blogs, notícias, entre outros

Technological Policing: Big data vs real data

Big Data assumes a preponderant role in the intervention in the most diverse areas of intervention, to which the police area is no stranger. This theoretical article seeks to open ways to understand the Big Data phenomenon in police intervention at micro and macro levels, as a tool inserted in police technology. On the other hand, to present the concept aggregated to real data, and its distancing in police intervention. The methodology used for this purpose was literature analysis, in which inclusion and exclusion criteria are presented to consolidate the analysis in question. From the authors’ perspective, it is pointed out that as an instrument of police technology, Big Data provides the necessary information, in terms of volume and quantity, taking into account the different levels of police intervention, and is a resource that increases efficiency in the maintenance of public order.info:eu-repo/semantics/publishedVersio

BNC textile: bacterial nanocellulose as a new and sustainable material for textile yarn

Dissertação de mestrado integrado em Engenharia BiológicaNeste trabalho, são discutidas tecnologias de produção de fios para aplicações têxteis tendo a celulose como base. São referidas tendências recentes que visam poupar o ambiente de exploração massiva, como o uso de nanocelulose bacteriana, procurando também responder às necessidades crescentes por fibras alternativas obtidas por processos sustentáveis. A avaliação do ciclo de vida de vários métodos de produção de fibras de celulose foi também abordada. O objetivo deste trabalho foi a produção de fios a partir de fibras alternativas às existentes no mercado utilizando a nanocelulose bacteriana como matéria-prima. A nanocelulose bacteriana possui características como elevada resistência mecânica, capacidade de retenção de água, estabilidade dimensional, cristalinidade, biocompatibilidade e biodegradabilidade, o que permite explorar a sua utilização em várias áreas como biomédica, cosmética, alimentar, têxtil e papel. Além disso, a sua produção tem um impacte ambiental menor onde não ocorre a destruição de florestas e a sua produção é feita em apenas algumas semanas, um tempo bastante inferior comparativamente ao análogo vegetal que demora meses ou anos. Foram produzidos filamentos utilizando diferentes concentrações de nanocelulose bacteriana e dois sistemas de dissolução diferentes: o método de dissolução em fase sólida e o método tradicional de produção de Liocel. Pelo primeiro método foi possível obter filamentos com módulo de Young de 20,8 ± 5,4 GPa, resistência à tração de 1201,9 ± 149,2 MPa e alongamento de 11,5 ± 0,1 %. Pelo segundo, foi obtido um módulo de Young de 35,0 ± 17,2 GPa, resistência à tração de 1100,0 ± 480,0 MPa e alongamento de 6,8 ± 4,0 %. De forma a respeitar os critérios de produção de filamentos pelo processo Liocel, foi realizado, posteriormente, um estudo de despolimerização da nanocelulose bacteriana. O grau de polimerização da nanocelulose bacteriana foi reduzido do seu valor original (cerca de 2000) para 602-531, que normalmente é considerado adequado para o processo de Liocel. Métodos alternativos de produção de filamentos sem a dissolução da nanocelulose bacteriana foram também testados – dry-spinning e wet-drawing, obtendo-se resultados semelhantes em ambos os métodos, com um módulo de Young de 5,4 ± 2,2 GPa e 7,9 ± 3,4 GPa, resistência à tração de 194,6 ± 53,2 MPa e 220,2 ± 98,4 MPa , e alongamento de 9,1 ± 6,3 % e 14,3 ± 1,8 %, respetivamente. São necessários mais estudos de forma a perceber se a despolimerização da nanocelulose bacteriana é realmente necessária para o processo de Liocel. A produção de fibras sem solventes também requer um estudo mais aprofundado, sendo estas as formas mais sustentáveis de produção de fibras têxteis.In this work, the technologies for the production of cellulose-based textiles, their surface modification and the recent trends aiming at sparing the forest from massive exploitation are discussed. The life cycle assessment of several cellulose fibre production methods is also addressed. The objective of this work was the production of cellulose filaments using an alternative source of cellulose – bacterial nanocellulose – as raw material. Bacterial nanocellulose has impressive characteristics such as high mechanical strength, water-holding capacity, dimensional stability, crystallinity, biocompatibility and biodegradability, allowing to explore its use in several areas, namely in the biomedical, cosmetic, food, textile and paper areas. Besides that, its production has less impact on the environment as no forests are destroyed and its production is faster. Filaments were produced using different BNC concentrations and two different dissolving systems: the solid-phase dissolution method and the traditional Lyocell production method. From the first method it was possible to obtain filaments with Young’s modulus of 20,8 ± 5,4 GPa, tensile strength of 1201,9 ± 149,2 MPa and elongation of 11,5 ± 0,1 %. Through the second was obtained Youngs’ modulus of 35,0 ± 17,2 GPa, tensile strength of 1100,0 ± 480,0 MPa and elongation of 6,8 ± 4,0 %. In order to meet Lyocell's production criteria, the degree of polymerization of bacterial nanocellulose was lowered from its original value (around 2000) to 602-531, which is normally considered suitable for the Lyocell process. Although it has been possible to achieve the depolymerization of BNC in a simple way using a chemical treatment, it would be preferable to process the original cellulose, without depolymerization. Alternative methods of filament production without dissolution were also tested – dry spinning and wet-drawing. Similar results were obtained for both methods with a Young’s modulus of 5,4 ± 2,2 GPa and 7,9 ± 3,4 GPa, tensile strength of 194,6 ± 53,2 MPa and 220,2 ± 98,4 MPa, and elongation of 9,1 ± 6,3 % and 14,3 ± 1,8 %, respectively. Further study on this subject is needed to understand if BNC depolymerization is really needed on a pilot or commercial scale for the Lyocell process. Fibres without solvents also need to be further studied as they are the more sustainable ways of fibre production and there is a growing need for these types of fibres on market

Police decision-making at major events: a research programme

The Major Events Laboratory (MEL) started functioning in 2011. Its primary objectives are to develop research in what concerns the security of major events and to contribute to modernising police activity and the definition of good practices. One of MEL’s research lines tackles decision-making in police activity. Police decision makers face the limits of the human mind when making choices or solving problems. Facing time pressure, lacking complete knowledge and with information processing capability, they are prone to attaining acceptable and satisficing solutions under challenging and uncertain scenarios. Descriptive studies have been conducted using the naturalistic decision-making approach: on the field — at major political and sports events — at MEL’s simulation room, during traffic control and during monitoring operations. The initial results are presented and implications for the learning and training process are discussed.info:eu-repo/semantics/publishedVersio