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Simple Summary: Device-assisted enteroscopy is the only diagnostic and therapeutic exam capable of exploring the entire gastrointestinal tract. However, the diagnostic yield of this procedure is not sufficient enough to assure a cost-effective panendoscopy, and there is significant interobserver variability during the exam. Artificial intelligence tools have been proved to be beneficial in several areas of medicine, namely in Gastroenterology, with a strong image component. However, the development of deep learning models for application in device-assisted enteroscopy is still in an embryonic phase. The authors herein aimed to develop a multidevice convolutional neural network based on 338 exams performed in two renowned centers. The present model was able to accurately identify multiple clinically relevant lesions across the entire gastrointestinal tract, with an image processing time that favors its clinical applicability. The first worldwide panendoscopic model showed the potential of artificial intelligence in augmenting the accuracy and cost-effectiveness of device-assisted enteroscopy. Device-assisted enteroscopy (DAE) is capable of evaluating the entire gastrointestinal tract, identifying multiple lesions. Nevertheless, DAE's diagnostic yield is suboptimal. Convolutional neural networks (CNN) are multi-layer architecture artificial intelligence models suitable for image analysis, but there is a lack of studies about their application in DAE. Our group aimed to develop a multidevice CNN for panendoscopic detection of clinically relevant lesions during DAE. In total, 338 exams performed in two specialized centers were retrospectively evaluated, with 152 single-balloon enteroscopies (Fujifilm®, Porto, Portugal), 172 double-balloon enteroscopies (Olympus®, Porto, Portugal) and 14 motorized spiral enteroscopies (Olympus®, Porto, Portugal); then, 40,655 images were divided in a training dataset (90% of the images, n = 36,599) and testing dataset (10% of the images, n = 4066) used to evaluate the model. The CNN's output was compared to an expert consensus classification. The model was evaluated by its sensitivity, specificity, positive (PPV) and negative predictive values (NPV), accuracy and area under the precision recall curve (AUC-PR). The CNN had an 88.9% sensitivity, 98.9% specificity, 95.8% PPV, 97.1% NPV, 96.8% accuracy and an AUC-PR of 0.97. Our group developed the first multidevice CNN for panendoscopic detection of clinically relevant lesions during DAE. The development of accurate deep learning models is of utmost importance for increasing the diagnostic yield of DAE-based panendoscopy. [ABSTRACT FROM AUTHOR]

Simple Summary: Diagnosis and characterization of biliary strictures is challenging, even after the introduction of digital single-operator cholangioscopy (D-SOC). The endoscopist's visual impression has a suboptimal accuracy and there is a significant interobserver variability. Artificial intelligence tools for image analysis have presented important contributions in several fields of gastroenterology. Convolutional neural networks are highly efficient multi-layered deep neural networks for image analysis, with great results in several fields of medicine. Nevertheless, the role of these deep learning models in digital cholangioscopy is still in a premature phase. With this bicentric international study, the authors aimed to create a deep learning-based algorithm for digital cholangioscopy capable of distinguishing benign from malignant biliary lesions. The present model accurately detected malignant biliary lesions with an image processing rate that favors its clinical applicability. The authors believe that the use of an AI-based model may change the landscape in the digital cholangioscopy diagnostic yield. Digital single-operator cholangioscopy (D-SOC) has enhanced the ability to diagnose indeterminate biliary strictures (BSs). Pilot studies using artificial intelligence (AI) models in D-SOC demonstrated promising results. Our group aimed to develop a convolutional neural network (CNN) for the identification and morphological characterization of malignant BSs in D-SOC. A total of 84,994 images from 129 D-SOC exams in two centers (Portugal and Spain) were used for developing the CNN. Each image was categorized as either a normal/benign finding or as malignant lesion (the latter dependent on histopathological results). Additionally, the CNN was evaluated for the detection of morphologic features, including tumor vessels and papillary projections. The complete dataset was divided into training and validation datasets. The model was evaluated through its sensitivity, specificity, positive and negative predictive values, accuracy and area under the receiver-operating characteristic and precision-recall curves (AUROC and AUPRC, respectively). The model achieved a 82.9% overall accuracy, 83.5% sensitivity and 82.4% specificity, with an AUROC and AUPRC of 0.92 and 0.93, respectively. The developed CNN successfully distinguished benign findings from malignant BSs. The development and application of AI tools to D-SOC has the potential to significantly augment the diagnostic yield of this exam for identifying malignant strictures. [ABSTRACT FROM AUTHOR]

Due to the perishable nature of tourist products, which impacts supply and demand, the possibility of analysing the relationship between customers' satisfaction and service quality can contribute to increased revenues. Machine learning techniques allow the analysis of how these services can be improved or developed and how to reach new markets, and look for the emergence of ideas to innovate and improve interaction with the customer. This paper presents a decision-support system for analysing consumer satisfaction, based on consumer feedback from the customer's experience when transported by a transfer company, in the present case working in the Algarve region, Portugal. The results show how tourists perceive the service and which factors influence their level of satisfaction and sentiment. One of the results revealed that the first impression associated with good news is what creates the most value in the experience, i.e., "first impressions matter". [ABSTRACT FROM AUTHOR]

Background The Iberian Peninsula is a diverse region that contains several different bioclimatic areas within one confined space, leading to high biodiversity. Portugal distinguishes itself in this regard by having a high count of spider species (829) and a remarkable number of endemic spider species (42) for its size (approximately 88,890 km2). However, only one non-endemic species (Macrothele calpeiana) is currently protected by the Natura 2000 network and no endemic spider species (aside from Anapistula ataecina) has been assessed according to the IUCN Red List criteria. The objective of this paper is to assess all non-assessed endemic species (41) as well as M. calpeiana. New information The 43 assessed species belong to 15 families, the richest being Zodariidae, Dysderidae, Linyphiidae and Gnaphosidae. In general and despite the lack of information on more than half the species, general patterns and trends could be found. Only 18 species (including M. calpeiana and A. ataecina) had enough data to allow their EOO (extent of occurrence) and AOO (area of occurrence) to be quantified. Of these, we modelled the distribution of 14 epigean species, eight of which were found to be widespread. The remaining six fulfilled at least one of the criteria for threatened species. Four species are troglobiont, all of which meet the EOO and AOO thresholds for threatened species. The remaining 25 Portuguese endemics had no reliable information on their range. Only nine species out of the 43 are estimated to be in decline and 11 are stable, with the majority of species having no information on trends (23 species). Forest areas, sand dunes, shrublands and caves host the majority of species. As such, the threats to Portuguese endemics reflect the diversity of habitats they occupy. Urbanisation and climate change seem to be the most important threats to these species, although other factors are also important and represented across the data. A considerable proportion of the currently known Portuguese endemic species can be found in national protected areas, with higher prominence to the Serras de Aire e Candeeiros, Douro Internacional, Vale do Guadiana, Sudoeste Alentejano e Costa Vicentina and Arrábida Natural Parks. These correspond mostly to areas that have been particularly well sampled during the last two decades. [ABSTRACT FROM AUTHOR]

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Multinationals have operating problems due to the multiple contexts in which they operate. One of the greatest challenges for these organizations is the management of the cultural diversity of their human resources, in the sense of creating a collective of work capable of meeting the goals of the new economy. In Portugal, of the most represented countries at the level of their multinationals, Germany is the one that has a more antagonistic culture when compared with Portuguese culture, not preventing a multiplicity of successful cases. This paper firstly aims to characterize the HRM practices used in the Portuguese subsidiaries of the German multinationals and to see if there is a pattern in these same practices, trying to find out the "how" German companies manage with productivity the Portuguese human capital. The results dictated the existence of a pattern used in practices and a clear focus on human resources, identified by a clear approach to HRM soft model, without neglecting the importance of achieving the goals, improving empowerment, knowledge, skills and motivation. [ABSTRACT FROM AUTHOR]

Motivation in work teams has a key role to play for the survival and competitiveness of businesses in the harsh environment of economic recession. This paper characterizes motivation in small and medium-sized construction companies in Portugal. It draws on data collected from in-person surveys which were carried out to employees of 32 companies. Results reveal the presence of some motivating factors specific to the profession such as the fact that the work requires a wide range of skills and is not very routine. Also, although employees in general feel a sense of equity and recognize that managers provide constant feedback, results show the need for improvement in motivation's management, particularly in regard to more autonomy and participation in setting goals. [ABSTRACT FROM AUTHOR]

Aim Researchers measuring beta diversity have rarely concerned themselves with the problems of how complete the species lists of studied communities are, and of how the varying degrees of completeness can actually change estimates of beta diversity. No comprehensive assessment has been made regarding the behaviour of most beta diversity indices when applied to incomplete samples, a situation which is more common than usually recognized. Our objective was to assess the behaviour and robustness of a number of beta diversity measures for incidence data from undersampled communities. Location Mainland Portugal and the Azorean archipelago (North Atlantic). Methods Data from intensive sampling of spiders in mainland Portugal and arthropods in Azores were collected. We examined the properties of 15 beta diversity measures developed for incidence data. We simulated varying degrees of completeness, whereas computing beta diversity for selected pairs of samples. The robustness of these beta diversity accumulation curves was assessed for the purpose of finding the best measures for undersampled communities. Results The Harrison et al.β-2 and the Williams β-3 are particularly robust to undersampling. These measures are also insensitive to differences of alpha diversity (species richness) between communities, and therefore to nestedness. Colwell & Coddington βcc and the related Jaccard βj and Gaston et al.βg performed best of the measures sensitive to alpha diversity. They performed poorly, however, when compared communities exhibited very low values of beta diversity. In such cases, the Routledge βr performed the best. Main conclusions No index was found to perform without bias in all circumstances. Overall, β-2, β-3 and βcc (or related measures βj and βg) are recommended as they seem to be the most robust to undersampling. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 pandemic has imposed an unprecedented burden on healthcare systems worldwide, changing the profile of interventional cardiology activity., Objectives: To quantify and compare the number of percutaneous coronary interventions (PCIs) performed for acute and chronic coronary syndromes during the first COVID-19 outbreak with the corresponding period in previous years., Methods: Data on PCI from the prospective multicenter Portuguese Registry on Interventional Cardiology (RNCI) were used to analyze changes in PCI for ST-elevation myocardial infarction (STEMI), non-ST-elevation acute coronary syndromes (NSTE-ACS) and chronic coronary syndromes (CCS). The number of PCIs performed during the initial period of the COVID-19 outbreak in Portugal, from March 1 to May 2, 2020, was compared with the mean frequency of PCIs performed during the corresponding period in the previous three years (2017-2019)., Results: The total number of PCIs procedures was significantly decreased during the initial COVID-19 outbreak in Portugal (-36%, p<0.001). The reduction in PCI procedures for STEMI, NSTE-ACS and CCS was, respectively, -25% (p<0.019), -20% (p<0.068) and -59% (p<0.001)., Conclusions: Compared with the corresponding period in the previous three years, the number of PCI procedures performed for STEMI and CCS decreased markedly during the first wave of the COVID-19 pandemic in Portugal., (Copyright © 2022 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.)

This document was prepared by the College of Orthopedics of the Portuguese Medical Association with the aim of developing the guidelines on the resumption of elective surgical activity in Orthopedics during the COVID-19 pandemic. It sets the criteria that allow the prioritization of surgeries according to the severity of the clinical situation, based on existing and published classifications. Moreover, it provides an organizational model for patient preparation and describes the patient pathways in the preoperative, intraoperative and postoperative periods. It also describes safety rules for elective surgery and a model for monitoring patients after discharge according to scientific evidence.

There are 800 known species of spiders in Portugal. Of these, only two may cause any kind of medical condition: the Mediterranean black-widow (Latrodectus tredecimguttatus) and the violin spider (Loxosceles rufescens). Both are relatively common in the country, the latter inclusively in urban areas. It is frequent in Portugal for some types of necrotic lesión to be attributed to spider bites. However, as in the rest of the world, evidences are often circumstantial. Most probably, some of the reported cases may in fact represent misdiagnoses of serious conditions such as infections by Streptococcus group A or Methicillin resistant Staphylococcus aureus. The correct diagnosis of spider poisoning must always be submitted to the following steps: (1) confirmation or observation of the biting, with verification of medical signs compatible with it; (2) the spider should be captured immediately or right after the bite, dead or alive; (3) identification of the spider by a taxonomist. It is extremely important that the medical community does not associate any necrotic lesion with a spider bite based on merely circumstantial evidence. Doing it is to neglect the real cause of such condition and to delay the effective cure. In reality, given their rarity, spider bite lesions should be relegated to the end of the differential diagnostic list of necrotic skin lesions.