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Introduction: The fermentation of CO-rich gases by carboxidotrophic microbes is a promising way to produce valuable organic compounds. Propionate is a value-added compound with numerous industrial applications, e.g. as an antifungal agent in food and feed, and as a building block to produce plastics and herbicides. Propionate is currently produced by petrochemical processes, but it can be produced from ethanol and acetate by some propionogenic bacteria. Ethanol and acetate are usually formed by acetogenic bacteria from CO-rich gases. Accordingly, propionate can be indirectly produced from CO-rich gases, representing a new approach on the realm of microbial CO conversion. Methodology: Four distinct synthetic co-cultures were constructed, consisting of: Acetobacterium wieringae (DSM 1911T) and Pelobacter propionicus (DSM 2379T); A. wieringae (DSM 1911T) and Anaerotignum neopropionicum (DSM 3847T); A. wieringae strain JM and P. propionicus (DSM 2379T); A. wieringae strain JM and A. neopropionicum (DSM 3847T). The physiology of CO conversion to propionate was accessed and a proteogenomic analysis was performed in the best performing co-culture to get insight into the involved biochemical pathways and microbial interactions within the synthetic consortium. Results: Propionate was produced by all the co-cultures, with the highest titer (~24 mM) measured in the co-culture composed of A. wieringae strain JM + A. neopropionicum, which also produced isovalerate (~4 mM), butyrate (~1 mM), and isobutyrate (~0.3 mM). In this synthetic consortium, A. wieringae strain JM converts CO to a acetate and ethanol via the Wood-Ljungdahl pathway; acetate can also be converted to ethanol through the action of aldehyde oxidoreductase (AOR); A. neopropionicum converts ethanol to propionate via the acrylate pathway. In addition, proteins related to amino acid metabolism and stress response were highly abundant during co-cultivation, which raises the hypothesis that amino acids are exchanged by the two microorganisms, and this results in isovalerate and isobutyrate production. Conclusions: This synthetic co-culture represents a new bioprocess for the microbial production of propionate from carbon monoxide, that couples the Wood-Ljungdahl and acrylate pathways. Furthermore, this symbiosis engages an interesting perspective on how C1-fixing and C3-producing microorganisms can be used to expand the product scope of gas fermentation., Portuguese Foundation for Science and Technology (FCT): POCI-01-0145-FEDER-031377; strategic funding of UIDB/04469/2020 unit; BioTecNorte operation (NORTE-01-0145-FEDER-000004); FCT doctoral grants PD/BD/128030/2016 and PD/BD/150583/2020. Netherlands Science Foundation (NWO): Project NWO-GK-07; Perspectief Programma P16-10; Gravitation Grant, Project 024.002.002., info:eu-repo/semantics/publishedVersion

Gas fermentation is a promising way to convert CO-rich gases to chemicals. In this work we aimed to develop an electrotransformation protocol for the promising gas-converting Acetobacterium wieringae strain JM (sJM) [1], to further implement heterologous pathways for the production of new compounds from gas streams. In this matter, Clostridial species are the most genetic manipulated homoacetogens, and within the Acetobacterium genus, only A. woodii has been used. Therefore, there is a strong need and opportunity to expand the molecular toolkit for sJM and other Acetobacterium species. To achieve this, we tested reported electrotransformation procedures for A. woodii, using available molecular tools from Clostridial species, namely the plasmid vectors pMTL82151, pMTL83151, pMTL84151, and pMTL84151 containing the Gram-positive replicons pBP1, pCB102, pCD6, and pIM13 with the thiamphenicol resistance gene (catP). The utilization reported electrotransformation procedures did not result in sJM transformants. Therefore, we developed a new protocol which we report to be applicable to sJM, A. wieringae DSM 1911 and A. woodii DSM 1030. The most important changes for higher expeditiously and reproducibility were the use of fixed cell density of competent cells resulting in electroporation cell-plasmid ratios of 2 to 3 (OD600.mL/g), the use of an electric field strength of 10 kV/cm, and the selection of transformants in serum anaerobic bottles with molten agar of our optimized basal media. All plasmid vectors were transformed, having pMTL83151 yielded the highest transformation efficiency in all tested Acetobacterium strains, reaching efficiencies up to 5.0 × 102, 2.0 × 103, and 5.1 × 103 transformants g-1 DNA for sJM, A. wieringae DSM 1911 and A. woodii DSM 1030, respectively. Key factors affecting the electrotransformation efficiency include cell-wallweakening using D-threonine, pH of wash buffer, field strength of the electric pulse, plasmid amount, and sucrose osmoprotection. The electrotransformation procedure and tools reported here unlock the genetic manipulation of this biotechnologically relevant sJM strain, which will be directed towards the expansion of the product portfolio of gas fermentation, which is currently limited to mainly acetate and ethanol., Portuguese Foundation for Science and Technology (FCT): POCI-01-0145-FEDER-031377; strategic funding of UIDB/04469/2020 unit; BioTecNorte operation (NORTE-01-0145-FEDER-000004); FCT doctoral grant PD/BD/150583/2020., info:eu-repo/semantics/publishedVersion

Online ahead of print, In recent years, various drug nano-delivery platforms have emerged to enhance drug effectiveness in cancer treatment. However, their successful translation to clinics have been hampered by unwanted side effects, as well as associated toxicity. Therefore, there is an imperative need for drug delivery vehicles capable of surpassing cellular barriers and also efficiently transfer therapeutic payloads to tumor cells. Exosomes, a class of small extracellular vesicles naturally released from all cells, have been exploited as a favorable delivery vehicle due to their natural role in intracellular communication and biocompatibility. In this review, information on exosome biogenesis, contents, forms of isolation and their natural functions is discussed, further complemented with the various successful methodologies for therapeutic payloads encapsulation, including distinct loading approaches. In addition, grafting of molecules to improve pharmacokinetics, tumor homing-ligands, as well as stimuli-responsive elements to enhance cell specificity are also debated. In the end, the current status of clinical-grade exosome-based therapies is outlined., This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and projects POCI-01-0145-FEDER-016390 (CancelStem), CENTRO-01-0145-FEDER-000012-HealthyAging2020, and CIBB (FCT reference UIDB/04539/2020). Débora Ferreira (DF) is recipient of a fellowship supported by a doctoral advanced training (call NORTE-69-2015-15) funded by the European Social Fund under the scope of Norte2020 - Programa Operacional Regional do Norte., info:eu-repo/semantics/publishedVersion

[Excerpt] Introduction: Breast cancer is a major public health problem worldwide being the most diagnosed cancer in women [1] . Triple negative breast cancer (TNBC) represents 10-20% of all breast cancers and is characterized by the absence of hormone receptors (progesterone and estrogen) and lack of expression of epidermal growth factor receptor 2. Furthermore, it is also described to have poor prognosis due to its propensity to metastasize to visceral organs early in the clinical course [2–4] . In accordance with the lack of recurrently altered targets at the genomic level, there is a shortage of approved targeted agents for TNBC, remaining cytotoxic chemotherapy the mainstay of treatment. [...], This work was supported by by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2020 unit. Débora Ferreira is recipient of a fellowship supported by a doctoral advanced training (call NORTE-69-2015-15) funded by the European Social Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. Débora Ferreira also acknowledges “Liga Portuguesa contra o cancro - Núcleo Regional do Norte (LPCC-NRN) “for her current fellowship., info:eu-repo/semantics/publishedVersion

Computer games are complex software systems, which means that their development requires some level of programming skills. However, their design also involves the creation of game objects (characters, scenarios, etc.), animations and story lines, which are designed by game domain experts, who in general have minimal (or no) programming skills. Game engines have been developed to facilitate game development by reducing programming efforts and enhancing productivity, but we observed that most of these engines still require programming skills in order to be used. In this paper, we discuss how Model-Driven Engineering technologies, particularly metamodelling and model transformations, can be used to facilitate game development. We define a Domain Specific Language called UGameFeature to be used by game designers to define games that can be automatically transformed into scripts that can be executed by the Unity game engine. In order to facilitate the code generation step, we defined an intermediate metamodel, so that structural differences between the UGameFeature metamodel and the Unity engine scripts can be accommodated by an intermediate model-to-model transformation. We claim that with this approach we could define a streamlined process to go from game design to game implementation, in this way surpassing the benefits already offered by game engines. We also discuss some practical obstacles of applying MDE techniques and give recommendations to practitioners who want to apply them in their projects.

INTRODUCTION Epilepsy requires a rapid and effective treatment, targeting the brain. In this area, the intranasal administration of lipid nanosystems, such as nanostructured lipid carriers (NLC) was suggested as a promising strategy. This route allows drug passage directly from the nose to the brain, bypassing the blood-brain barrier [1]. However, nasal administration faces some physiological barriers, such as the mucociliary clearance, which decreases the residence time of the formulation in the nasal cavity, reducing drug absorption. To circumvent this limitation, the use of ion sensitive polymers, such as pectin, which interacts with the calcium ions of the nasal mucus, increases the residence time of the NLC formulation within the nasal cavity [2]. The aim of this work was to develop an ion sensitive in situ hydrogel containing an optimized diazepam- loaded NLC formulation and to study its nasal deposition using a 3D nasal cavity model. The experiments started with the determination of the in situ hydrogel gelation time and the spray cone angle, using two types of pectin, at different concentrations. Subsequently, the nasal deposition in a 3D nasal cavity model was evaluated at with an airflow of 0 L/min and different administration angles. EXPERIMENTAL Preparation and characterization of in situ hydrogels containing diazepam-loaded NLC Costa et al. [3] previously optimized the diazepam-loaded NLC composition and preparation method. For the in situ hydrogels preparation, pectin CF005 and pectin CF025 were added at concentrations of 0.6% and 1.2% to the aqueous phase of the diazepam-loaded NLC, under continuous stirring, at 20.0±0.5ºC. Evaluation of the gelation time The gelation time of the in situ hydrogels was determined by the oscillatory gelation time test (Modular Compact Rheometer 102, Anton Paar GmbH, Austria) after mixing the diazepam-loaded NLC suspension containing pectin with simulated nasal fluid, in a volume ratio of 1:1. For this test, changes in the storage modulus (G´) and loss modulus (G´´) were recorded. The experiment was performed at 34ºC, using a parallel plate 50 (PP50) measuring system. The defined measuring position was 0.5 mm and the angular frequency was fixed at 6.28 rad s-1. Three replicate measurements were conducted for each formulation and the results are presented as mean values ± standard deviation (SD). Spray cone angle determination The spray cone angle was measured using a virtual protractor, after spraying the formulation against a dark background. The formulation was first placed in a Spray Pump 3K (Aeropump, Germany) and sprayed three times. A camera recorded the emitted plume and the spray cone angle was analyzed for each sample. Evaluation of the formulation deposition profile in a 3D nasal cavity model The 3D nasal cavity model was carried out using a computed tomography (CT) scan of a 62-year old patient with healthy nasal passages airways, obtained from the database of University Hospital Center “Sestre milosrdnice” (Ethics Committees approval codes: EP-9941/19-3 class: 003-06/21- 02/001, registry number:251-29- 11/1-21-01-1 ; PEER class: 643-02/21-03/01, registry number 251-62-03- 21-8) [4]. The nasal model is divided in (Figure 1): anterior region, turbinate region with detachable olfactory part, septum with detachable olfactory part, and nasopharynx. For the nasal deposition profile, the 3D nasal model was covered with Sar-gel®, which turns purple in contact with water and has calcium ions that induce pectin gelation. The administration of the formulations was performed on the right nostril of the 3D model. The fractional spray deposition pattern was determined weighting the amount of deposited formulation in all the nasal regions. Three replicates were conducted for each formulation and the results are presented as mean values ± SD. RESULTS Evaluation of the gelation time For both concentrations of pectin CF025, the G´ was higher than G´´ during the entire measuring period, which indicates that the gelation occurred immediately after the contact with the nasal fluid. The same was not observed with the formulations with pectin CF005. For this reason, further experiments were only performed with pectin CF025. Spray cone angle determination The spray cone angle of the in situ hydrogels was 34.3±0.2º and 16.3±0.4º for the formulation with 0.6% and 1.2% of pectin, respectively, which shows that spray cone angle decreased with the increase of pectin concentration. It was reported that narrow cone angles could increase the drug deposition on the olfactory region. However, if the angle is too narrow, the impact of the sprayed jet might cause patient discomfort. For this reason, only the formulation with 0.6% pectin was chosen for the nasal deposition studies [5]. Evaluation of the formulation deposition profile in a 3D nasal cavity model The deposition in the olfactory region (olfactory part of septum + olfactory part of turbinates) at different administration angles, from the vertical plane (0 and 20º) and horizontal plane (60 and 75º) are shown in Table 1. Table 1. Deposition profile of the in situ hydrogels containing diazepam-loaded NLC in the 3D nasal cavity model, administered at angles of 0 and 20° from the vertical plane and 60 and 75° from the horizontal plane. AHP: angle from horizontal plane ; AVP: angle from vertical plane OS: olfactory part of septum ; OT: olfactory part of turbinates ; R: recovery. Based on the results of Table 1, it was concluded that the angles of administration from the horizontal and vertical planes affect the nasal deposition in the olfactory region. The highest olfactory deposition was obtained for the administration angles of 75º from the horizontal plane and 0º from the vertical plane, with 28.10% of the formulation found in the olfactory region (Figure 2). In addition, it was observed that olfactory deposition increases with the increase of the administration angle from the horizontal plane and with the decrease of administration angle from the vertical plane. CONCLUSION The in situ hydrogel containing diazepam-loaded NLC with 0.6% of pectin CF025 presented an adequate gelation time and provided a suitable spray cone angle. About 28% of the formulation was deposited in the olfactory region, which is considered high. From the results of this study, we conclude that angles of administration from horizontal and vertical planes have impact on olfactory deposition. Currently, more factors that may also interfere, including the presence of airflow and the use of different nasal devices, are being studied by our research group. ACKNOWLEDGEMENTS This work was supported by Fundação para a Ciência e a Tecnologia (FCT) (SFRH/136177/2018, Portugal), by the Applied Molecular Bio-sciences Unit-UCIBIO, which is financed by national funds from FCT (UIDP/04378/2020 and UIDB/04378/2020) and CIBB (FCT reference: UIDB/04539/2020). Also, this work has been supported in part by Croatian Science Foundation under the project UIP-2017-05-4592". REFERENCES 1. Costa, C. et al. Nose-to-brain delivery of lipid-based nanosystems for epileptic seizures and anxiety crisis, Journal of Controlled Release. 187-200 (2019). 2. Nižić, L. et al. Innovative sprayable in situ gelling fluticasone suspension: Development and optimization of nasal deposition. International Journal of Pharmaceutics. 563, 445-456 (2019). 3. Costa, C.P. et al. Quality by design (QbD) optimization of diazepam-loaded nanostructured lipid carriers (NLC) for nose-to-brain delivery: Toxicological effect of surface charge on human neuronal cells. International Journal of Pharmaceutics. 607, 120933 (2021). 4. Nižić Nodilo, L. et al. A Dry Powder Platform for Nose-to-Brain Delivery of Dexamethasone: Formulation Development and Nasal Deposition Studies. Pharmaceutics. 13, 795 (2021). 5. Maaz, A. et al. In Vitro Evaluation of Nasal Aerosol Depositions: An Insight for Direct Nose to Brain Drug Delivery. Pharmaceutics. 13, 1079 (2021).

[Excerpt] Background: Triple negative breast cancer (TNBC) represents 10-20% of all breast cancer cases and is characterized by an aggressive progression with metastatic nature and high rates of relapse [1]. Due to a lack of known specific molecular biomarkers for this breast cancer subtype, there are no targeted therapies available, which results in the worst prognosis of all breast cancer subtypes. Hence, the identification of novel tumor-homing ligands, such as peptides, for this particular type of breast cancer is highly important for the development of novel targeted therapies. Over the past few years, exosomes have increasingly earned attention as candidate drug delivery platforms due to their distinctive features. The exosome natural role as a transporter of functional molecules is one of the main characteristics that drive their use as drug delivery vehicles [2,3]. Furthermore, their therapeutic potential can be greatly improved by lipid, protein or even nucleic acid content engineering. Based on this rationale, we hypothesized that the decoration of exosomes with TNBC-specific peptides could lead to an increased uptake. [...], info:eu-repo/semantics/publishedVersion

Human Activity Recognition is a machine learning task for the classification of human physical activities. Applications for that task have been extensively researched in recent literature, specially due to the benefits of improving quality of life. Since wearable technologies and smartphones have become more ubiquitous, a large amount of information about a person’s life has become available. However, since each person has a unique way of performing physical activities, a Human Activity Recognition system needs to be adapted to the characteristics of a person in order to maintain or improve accuracy. Additionally, when smartphones devices are used to collect data, it is necessary to manage its limited resources, so the system can efficiently work for long periods of time. In this paper, we present a semi-supervised ensemble algorithm and an extensive study of the influence of hyperparameter configuration in classification accuracy. We also investigate how the classification accuracy is affected by the person and the activities performed. Experimental results show that it is possible to maintain classification accuracy by adjusting hyperparameters, like window size and window overlap, depending on the person and activity performed. These results motivate the development of a system able to automatically adapt hyperparameter settings for the activity performed by each person.

Poster presented at ICTOPEN 2019.

Time to say “Past forward!“ This plenary is going to be a vivid session with contributions from all current and emerging offices to pave the way for future GO FAIR community activities and build on the achievements of the past three years. Let’s take full advantage of the effervescent energy of summer and virtually round up the community to move on with the FAIR shift in research data management. Our panelists from Austria, Brazil, China, Denmark, France, Germany, The Netherlands and the US will share their ongoing activities and jointly paint a picture on the future support for the international GO FAIR community. Enjoy the FAIR road trip around the globe!, panelists from Austria, Brazil, China, Denmark, France, Germany, The Netherlands and the US

[Excerpt] Breast cancer was the leading cause of global cancer incidence in 2020, with an estimated 2.3 million new diagnosed cases among women. Triple negative breast cancer (TNBC) characterized by the absence of hormone receptors, lack of expression of epidermal growth factor receptor-2 and poor prognosis, represents about 10-20% of all breast cancers. Hence, an efficient targeted delivery system is urgently needed for TNBC therapy. Exosomes are natural and nanosized intraluminal vesicles, with a size range of ~30 to 150 nm, released by most cell types. They are present in almost all biological fluids and function as natural transporters of molecules between neighboring and distant cells. Thus, exosomes may serve as endogenous vehicles for drug delivery such as chemotherapeutic agents, short-interfering RNAs (siRNAs) or even microRNAs (miRNAs). Herein, we describe the development of a novel targeted cancer therapeutic platform for TNBC therapy by exosome-mediated delivery of RNAi-based therapeutics. [...], info:eu-repo/semantics/publishedVersion

An early warning system (EWS) is a distributed system that monitors the physical world and issues warnings if it detects abnormal situations. The Internet of Things (IoT) offers opportunities to improve monitoring capabilities of EWS and to realize (near) real-time warning and response. This paper presents the development of an interoperable IoT-based EWS to detect accident risks with trucks that deliver goods at the Valencia port area. Our solution addresses the semantic integration of a variety of data sources with processing in safety-critical applications for effective emergency response. The solution considers existing domain-specific ontologies and standards, along with their serialization formats. Accident risks are assessed by monitoring the drivers’ vital signs with ECG medical wearables and the trucks’ position with speed and accelerometer data. Use cases include the detection of health issues and vehicle collision with dangerous goods. This EWS is developed with the SEMIoTICS framework, which encompasses a model-driven architecture that guides the application of data representations, transformations, and distributed software components. This framework enables an EWS to act as a semantic broker for situation-aware decision support.

In data streams new classes can appear over time due to changes in the data statistical distribution. Consequently, models can become outdated, which requires the use of incremental learning algorithms capable of detecting and learning the changes over time. However, when a single classification model is used for novelty detection, there is a risk that its bias may not be suitable for new data distributions. A solution could be the combination of several models into an ensemble. Besides, because models can only be updated when labeled data arrives, we propose two unsupervised ensemble approaches: one combining clustering partitions using the same clustering technique; and other using different clustering techniques. We compare the performance of the proposed methods with well known novelty detection algorithms. The methods were tested on datasets commonly used in the novelty detection literature. The experimental results show that proposed ensembles have competitive performance for novelty detection in data streams.

About 2.1 million new diagnosed breast cancer cases among women were estimated for 2018. Triple negative breast cancer (TNBC), characterized by the absence of hormone receptors (estrogen and progesterone), lack of expression of epidermal growth factor receptor-2 and poor prognosis, represents 10-20% of all breast cancers. Hence, the identification of novel biomarkers for this type of breast cancer is highly relevant for an early diagnosis. Additionally, TNBC peptide ligands can be used to design powerful drug delivery systems that specifically target this type of breast cancer. Therefore, the following study aimed to select and characterize novel peptides for a triple negative breast cancer murine mammary carcinoma cell line 4T1. Using phage display, 7 and 12 amino acid random peptide libraries were screened against the 4T1 cell line. A total of four rounds, plus a counter-selection round using the 3T3 murine fibroblast cell line, was performed. The enriched selective peptides were characterized and their binding capacity towards 4T1 tissue samples was confirmed by immunofluorescence and flow cytometry analysis. The selected peptides (4T1pep1 CPTASNTSC and 4T1pep2EVQSSKFPAHVS) were enriched over few rounds of selection and exhibited specific binding to the 4T1 cell line. Exosomes derived from BJ cells were isolated by differential centrifugation and further characterized by nanoparticle tracking analysis, transmission electron microscopy (TEM), flow cytometry and western blot. Cell-derived exosomes were efficiently uptake by different TNBC cell lines (MDA-MB-231, MDA-MB-453, MDA-MB-157 and Hs 578T). Moreover, in vivo circulation times and biodistribuition experiments were accomplished to assess performance. The ultimate goal is to develop multifunctional exosomes decorated with the previously selected peptides to achieve a drug delivery system with increased affinity/selectivity for triple negative breast cancer cells. Targeted exosomes have led to a completely new paradigm for the therapeutic delivery of drug molecules to specific targets, opening the door for new treatments of diseases caused by aberrant gene expression as cancer., info:eu-repo/semantics/publishedVersion

Background: The number of health-related publications has been exponential in the recent decade. Indeed, cardiovascular area includes more than 670k papers published at MEDLINE [((cardiovascular) NOT ((("Animals"[Mesh] NOT ("Animals"[Mesh] AND "Humans"[Mesh])))], of which, more than 20k are related to coronary artery bypass grafting (CABG). We are witnessing a 6% increase in publications per year. The growth in potential information content is a challenge to manage; one way to leverage the evidence level using such a vast amount of information is using systematic reviews and meta-analysis. These approaches allow health professionals to quickly synthesize and efficiently be up to date regarding their specific topics of interest and, eventually, identify major gaps in the evidence. Meta-analysis of randomized controlled trials (RCTs) is considered one of the highest levels of evidence since pooling the data of individual studies provide higher statistical power to detect differences even in low-frequency events(1, 2). Besides the common pitfalls of all systematic reviews, such as overlapping data, publication bias, the limited number of databases searched, low quality, and heterogeneity of the original studies included(2), the lack of easy access to data is a severe limitation to leverage the potential information present in many studies. Also, an overwhelming number of authors do not reply to the reviewers or community queries for delivering access to papers’ data, implying their exclusion from quantitative analysis due to the lack of information, impacting the growth of the evidence building negatively. However, the publication of figures that provide relevant information is not an uncommon practice. More specifically, Kaplan-Meier curves to estimate cumulative survival differences between studies groups are usually provided, but occasionally without the association measure, hazard ratio (HR), which is of high relevance for evidence assessment. For the cases where the HR is not provided, the incidence rate ratio (IRR) calculation could be an option since the number of deaths within each group is provided (IRR=((nr events exposed group)/(total patients in risk exposed group×follow-up time))/((nr events control group)/(total patients in risk control group ×follow-up time))). For RCTs this is not a constraining factor, but for observational studies, it is likely to be a source of bias since the results should be adjusted for potential confounding or unbalanced covariates. In these cases, the crude number of deaths within each group and IRR calculation would provide an unadjusted and inconclusive analysis of data. Adjusted HR or HR provided from previously matched (balanced) groups are the best estimations to pool within observational studies. Guyot et al(3) developed an algorithm to reconstruct and analyse Kaplan-Meier curves, providing survival statistics. It also delivers HR, but the authors pointed out that this was not the primary purpose of their algorithm. Indeed, their validation exercise resulted in excellent reproducibility and accuracy for reconstruction of survival statistics, such as median survival and probability of survival, while HR reproducibility and accuracy was less good mostly when less information about number at risk and number of events were available. The reason pointed by the authors for the lower accuracy of HR comparing with the other statistics is that the HR is a weighted average of ratios along the curve, while the other statistics are simple points estimates. Our aim was to assess and validate, with our data, Guyot et al. algorithm for HR computation, for long-term survival outcome, and to estimate the precision of this method according to different levels of provided data. Methods: Using GetData Graph Digitizer 2.26 (http://getdata-graph-digitizer.com/), we imported one survival curve from our cohort study (n=2414 patients) that compared long-term survival between a bilateral internal mammary artery (BIMA) and single internal mammary artery (SIMA) CABG surgery. A careful delineation of each curve after limiting X and Y axes was done, and two ASCII (text) files, one per group, were exported with all the supplied coordinates: time (X) and cumulative survival (Y) for each point. Three event tables were built: 1) the number of patients at risk provided for every single year (from 0 to 10 – 10 points); 2) the number at risk was provided only every two years (5 points); 3) the number at risk only at three distinct points: beginning, median and end of follow-up (3 points). Those data files were then imported by an R script that reads the number at risk at each time point, produce vectors and calculates approximations of number of censored on each interval, i; adjusts the total number at risk and number of events within each i according to Kaplan-Meier (K-M) estimates read from curves. Then it obtains the individual patient data (IPD) from the reconstructed Kaplan-Meier data including time, event and respective arm. Finally, it reads those K-M and coxph formula could be applied. Those results were compared with Cox regression data derived directly from our dataset. Results: We included 2414 patients(4), of which 1478 were subject to SIMA and 936 were subject to BIMA. During the follow-up, median of 5.5 years for a maximum of 12 years, 391 deaths were registered (20% SIMA vs. 10% BIMA). Kaplan-Meier curves marked an evident statistical difference between those groups as well as the Cox regression (HR for BIMA: 0.6046, CI 95%: 0.4771 – 0.7663). From the 3 methods we stated above we got the following HR [95% CI]: 1) 0.5994 [0.4735 – 0.7587]; 2) 0.6021 [0.4761 – 0.7614]; and 3) 0.5921 [0.4663 – 0.7518]. Conclusion: Even though the authors who provided the algorithm for reconstruction of Kaplan-Meier curves question its ability to compute HR, our own experience shows otherwise, corroborating with Saluja and colleagues who compared four methods developed to estimate HR from Kaplan-Meier curves and recommended the Guyot method(5). This algorithm has high potential and could be used to extract data from papers where quantitative data is absent. We recently used it to extract data from 9 studies avoiding to exclude them from a meta-analysis of RCTs and propensity score studies(6)., Journal of Statistics on Health Decision, vol. 2 n.º 2 (2020): Special Issue - Statistics on Health Decision Making: clinical trials

International audience; Recently, a number of ontology-driven healthcare systems have been leveraged by the Internet-of-Things (IoT) 11 technologies, which offer opportunities to improve abnormal situation detection when integrating medical wearables and cloud 12 infrastructure. Usually, these systems rely on standardised IoT ontologies to represent sensor data observations. The ETSI 13 Smart Applications REFerence ontology (SAREF) is an extensible industry-oriented standard. In this paper, we explain the 14 need for interoperability of IoT healthcare applications and the role of standardised ontologies to achieve semantic 15 interoperability. In particular, we discuss the verbosity problem of SAREF when used for real-time electrocardiography (ECG), 16 emphasizing the requirement of representing time series. We compared the main ontologies in this context, according to 17 quality, message size (payload), IoT-orientation and standardisation. Here we describe the first attempt to extend SAREF for 18 specific e-Health use cases related to ECG data, the SAREF4health extension, which tackles the verbosity problem. Ontology-19 driven conceptual modelling was applied to develop SAREF4health, in which an ECG ontology grounded in the Unified 20 Foundational Ontology (UFO) plays the role of a reference model. The methodology was enhanced by following a 21 standardisation procedure and considering the RDF implementation of the HL7 Fast Healthcare Interoperability Resources 22 (FHIR) standard. The validation of SAREF4health includes the responses to competency questions, as well as the development 23 and tests of an IoT Early Warning System prototype that uses ECG data and collision identification to detect accidents with 24 truck drivers in a port area. This prototype integrates an existing ECG wearable with a cloud infrastructure, demonstrating the 25 performance impact of SAREF4health considering IoT constraints. Our results show that SAREF4health enables the semantic 26 interoperability of IoT solutions that need to deal with frequency-based time series. Design decisions regarding the trade-off 27 between ontology quality and aggregation representation are also discussed.