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1.
  • Kattge, Jens, et al. (författare)
  • TRY plant trait database - enhanced coverage and open access
  • 2020
  • Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
  • Tidskriftsartikel (refereegranskat)abstract
    • Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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2.
  • Amaral, Rita, et al. (författare)
  • Profiling Persistent Asthma Phenotypes in Adolescents : A Longitudinal Diagnostic Evaluation from the INSPIRERS Studies
  • 2021
  • Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 18:3
  • Tidskriftsartikel (refereegranskat)abstract
    • We aimed to identify persistent asthma phenotypes among adolescents and to evaluate longitudinally asthma-related outcomes across phenotypes. Adolescents (13-17 years) from the prospective, observational, and multicenter INSPIRERS studies, conducted in Portugal and Spain, were included (n = 162). Latent class analysis was applied to demographic, environmental, and clinical variables, collected at a baseline medical visit. Longitudinal differences in clinical variables were assessed at a 4-month follow-up telephone contact (n = 128). Three classes/phenotypes of persistent asthma were identified. Adolescents in class 1 (n = 87) were highly symptomatic at baseline and presented the highest number of unscheduled healthcare visits per month and exacerbations per month, both at baseline and follow-up. Class 2 (n = 32) was characterized by female predominance, more frequent obesity, and uncontrolled upper/lower airways symptoms at baseline. At follow-up, there was a significant increase in the proportion of controlled lower airway symptoms (p < 0.001). Class 3 (n = 43) included mostly males with controlled lower airways symptoms; at follow-up, while keeping symptom control, there was a significant increase in exacerbations/month (p = 0.015). We have identified distinct phenotypes of persistent asthma in adolescents with different patterns in longitudinal asthma-related outcomes, supporting the importance of profiling asthma phenotypes in predicting disease outcomes that might inform targeted interventions and reduce future risk.
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3.
  • Bernal, Ximena E., et al. (författare)
  • Empowering Latina scientists
  • 2019
  • Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 363:6429, s. 825-826
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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5.
  • Jacome, Cristina, et al. (författare)
  • Feasibility and Acceptability of an Asthma App to Monitor Medication Adherence : Mixed Methods Study
  • 2021
  • Ingår i: JMIR mhealth and uhealth. - : JMIR Publications. - 2291-5222. ; 9:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Poor medication adherence is a major challenge in asthma, and objective assessment of inhaler adherence is needed. The InspirerMundi app aims to monitor adherence while providing a positive experience through gamification and social support. Objective: This study aimed to evaluate the feasibility and acceptability of the InspirerMundi app to monitor medication adherence in adolescents and adults with persistent asthma (treated with daily inhaled medication). Methods: A 1-month mixed method multicenter observational study was conducted in 26 secondary care centers from Portugal and Spain. During an initial face-to-face visit, physicians reported patients' asthma therapeutic plan in a structured questionnaire. During the visits, patients were invited to use the app daily to register their asthma medication intakes. A scheduled intake was considered taken when patients registered the intake (inhaler, blister, or other drug formulation) by using the image-based medication detection tool. At 1 month, patients were interviewed by phone, and app satisfaction was assessed on a 1 (low) to 5 (high) scale. Patients were also asked to point out the most and least preferred app features and make suggestions for future app improvements. Results: A total of 107 patients (median 27 [P25-P75 14-40] years) were invited, 92.5% (99/107) installed the app, and 73.8% (79/107) completed the 1-month interview. Patients interacted with the app a median of 9 (P25-P75 1-24) days. At least one medication was registered in the app by 78% (77/99) of patients. A total of 53% (52/99) of participants registered all prescribed inhalers, and 34% (34/99) registered the complete asthma therapeutic plan. Median medication adherence was 75% (P25-P75 25%-90%) for inhalers and 82% (P25-P75 50%-94%) for other drug formulations. Patients were globally satisfied with the app, with 75% (59/79) scoring >= 4,; adherence monitoring, symptom monitoring, and gamification features being the most highly scored components; and the medication detection tool among the lowest scored. A total of 53% (42/79) of the patients stated that the app had motivated them to improve adherence to inhaled medication and 77% (61/79) would recommend the app to other patients. Patient feedback was reflected in 4 major themes: medication-related features (67/79, 85%), gamification and social network (33/79, 42%), symptom monitoring and physician communication (21/79, 27%), and other aspects (16/79, 20%). Conclusions: The InspirerMundi app was feasible and acceptable to monitor medication adherence in patients with asthma. Based on patient feedback and to increase the registering of medications, the therapeutic plan registration and medication detection tool were redesigned. Our results highlight the importance of patient participation to produce a patient-centered and engaging mHealth asthma app.
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6.
  • Jacome, Cristina, et al. (författare)
  • Monitoring Adherence to Asthma Inhalers Using the InspirerMundi App : Analysis of Real-World, Medium-Term Feasibility Studies
  • 2021
  • Ingår i: Frontiers in Medical Technology. - : Frontiers Media S.A.. - 2673-3129. ; 3
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Poor medication adherence is a major challenge in asthma and objective assessment of inhaler adherence is needed. InspirerMundi app aims to monitor inhaler adherence while turning it into a positive experience through gamification and social support.Objective: We assessed the medium-term feasibility of the InspirerMundi app to monitor inhaler adherence in real-world patients with persistent asthma (treated with daily inhaled medication). In addition, we attempted to identify the characteristics of the patients related to higher app use.Methods: Two real-world multicenter observational studies, with one initial face-to-face visit and a 4-month telephone interview, were conducted in 29 secondary care centers from Portugal. During an initial face-to-face visit, patients were invited to use the app daily to register their asthma medication intakes. A scheduled intake was considered taken when patients took a photo of the medication (inhaler, blister, or others) using the image-based medication detection tool. Medication adherence was calculated as the number of doses taken as a percentage of the number scheduled. Interacting with the app =30 days was used as the cut-off for higher app use.Results: A total of 114 patients {median 20 [percentile 25 to percentile 75 (P25-P75) 16-36] years, 62% adults} were invited, 107 (94%) installed the app and 83 (73%) completed the 4-month interview. Patients interacted with the app for a median of 18 [3-45] days, translated on a median use rate of 15 [3-38]%. Median inhaler adherence assessed through the app was 34 [4-73]% when considering all scheduled inhalations for the study period. Inhaler adherence assessed was not significantly correlated with self-reported estimates. Median adherence for oral and other medication was 41 [6-83]% and 43 [3-73]%, respectively. Patients with higher app use were slightly older (p = 0.012), more frequently taking medication for other health conditions (p = 0.040), and more frequently prescribed long-acting muscarinic antagonists (LAMA, p = 0.024). After 4 months, Control of Allergic Rhinitis and Asthma Test (CARAT) scores improved (p < 0.001), but no differences between patients interacting with the app for 30 days or less were seen.Conclusions: The InspirerMundi app was feasible to monitor inhaler adherence in patients with persistent asthma. The persistent use of this mHealth technology varies widely. A better understanding of characteristics related to higher app use is still needed before effectiveness studies are undertaken.
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7.
  • Neves, Ana Luisa, et al. (författare)
  • Determinants of the Use of Health and Fitness Mobile Apps by Patients With Asthma : Secondary Analysis of Observational Studies
  • 2021
  • Ingår i: Journal of Medical Internet Research. - : JMIR Publications. - 1438-8871. ; 23:9
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Health and fitness apps have potential benefits to improve self-management and disease control among patients with asthma. However, inconsistent use rates have been reported across studies, regions, and health systems. A better understanding of the characteristics of users and nonusers is critical to design solutions that are effectively integrated in patients' daily lives, and to ensure that these equitably reach out to different groups of patients, thus improving rather than entrenching health inequities. Objective: This study aimed to evaluate the use of general health and fitness apps by patients with asthma and to identify determinants of usage. Methods: A secondary analysis of the INSPIRERS observational studies was conducted using data from face-to-face visits. Patients with a diagnosis of asthma were included between November 2017 and August 2020. Individual-level data were collected, including age, gender, marital status, educational level, health status, presence of anxiety and depression, postcode, socioeconomic level, digital literacy, use of health services, and use of health and fitness apps. Multivariate logistic regression was used to model the probability of being a health and fitness app user. Statistical analysis was performed in R. Results: A total of 526 patients attended a face-to-face visit in the 49 recruiting centers and 514 had complete data. Most participants were <= 40 years old (66.4%), had at least 10 years of education (57.4%), and were in the 3 higher quintiles of the socioeconomic deprivation index (70.1%). The majority reported an overall good health status (visual analogue scale [VAS] score>70 in 93.1%) and the prevalence of anxiety and depression was 34.3% and 11.9%, respectively. The proportion of participants who reported using health and fitness mobile apps was 41.1% (n=211). Multivariate models revealed that single individuals and those with more than 10 years of education are more likely to use health and fitness mobile apps (adjusted odds ratio [aOR] 2.22, 95%CI 1.05-4.75 and aOR 1.95, 95%CI 1.12-3.45, respectively). Higher digital literacy scores were also associated with higher odds of being a user of health and fitness apps, with participants in the second, third, and fourth quartiles reporting aORs of 6.74 (95%CI 2.90-17.40), 10.30 (95%CI 4.28-27.56), and 11.52 (95%CI 4.78-30.87), respectively. Participants with depression symptoms had lower odds of using health and fitness apps (aOR 0.32, 95%CI 0.12-0.83). Conclusions: A better understanding of the barriers and enhancers of app use among patients with lower education, lower digital literacy, or depressive symptoms is key to design tailored interventions to ensure a sustained and equitable use of these technologies. Future studies should also assess users' general health-seeking behavior and their interest and concerns specifically about digital tools. These factors may impact both initial engagement and sustained use.
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8.
  • Dallora Moraes, Ana Luiza, et al. (författare)
  • Bone age assessment with various machine learning techniques : A systematic literature review and meta-analysis
  • 2019
  • Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 14:7
  • Forskningsöversikt (refereegranskat)abstract
    • Background The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal environment in what concerns if an individual is a minor or not when there is a lack of documents. Being a time-consuming activity that can be prone to inter- and intra-rater variability, the use of methods which can automate it, like Machine Learning techniques, is of value. Objective The goal of this paper is to present the state of the art evidence, trends and gaps in the research related to bone age assessment studies that make use of Machine Learning techniques. Method A systematic literature review was carried out, starting with the writing of the protocol, followed by searches on three databases: Pubmed, Scopus and Web of Science to identify the relevant evidence related to bone age assessment using Machine Learning techniques. One round of backward snowballing was performed to find additional studies. A quality assessment was performed on the selected studies to check for bias and low quality studies, which were removed. Data was extracted from the included studies to build summary tables. Lastly, a meta-analysis was performed on the performances of the selected studies. Results 26 studies constituted the final set of included studies. Most of them proposed automatic systems for bone age assessment and investigated methods for bone age assessment based on hand and wrist radiographs. The samples used in the studies were mostly comprehensive or bordered the age of 18, and the data origin was in most of cases from United States and West Europe. Few studies explored ethnic differences. Conclusions There is a clear focus of the research on bone age assessment methods based on radiographs whilst other types of medical imaging without radiation exposure (e.g. magnetic resonance imaging) are not much explored in the literature. Also, socioeconomic and other aspects that could influence in bone age were not addressed in the literature. Finally, studies that make use of more than one region of interest for bone age assessment are scarce. Copyright: © 2019 Dallora et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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9.
  • Marote, Ana, et al. (författare)
  • Cellular Aging Secretes : a Comparison of Bone-Marrow-Derived and Induced Mesenchymal Stem Cells and Their Secretome Over Long-Term Culture
  • 2023
  • Ingår i: Stem Cell Reviews and Reports. - : Springer Science and Business Media LLC. - 2629-3269 .- 2629-3277. ; 19:1, s. 248-263
  • Tidskriftsartikel (refereegranskat)abstract
    • Mesenchymal stem cells (MSCs) hold promising therapeutic potential in several clinical applications, mainly due to their paracrine activity. The implementation of future secretome-based therapeutic strategies requires the use of easily accessible MSCs sources that provide high numbers of cells with homogenous characteristics. MSCs obtained from induced pluripotent stem cells (iMSCs) have been put forward as an advantageous alternative to the gold-standard tissue sources, such as bone marrow (BM-MSCs). In this study, we aimed at comparing the secretome of BM-MSCs and iMSCs over long-term culture. For that, we performed a broad characterization of both sources regarding their identity, proteomic secretome analysis, as well as replicative senescence and associated phenotypes, including its effects on MSCs secretome composition and immunomodulatory action. Our results evidence a rejuvenated phenotype of iMSCs, which is translated into a superior proliferative capacity before the induction of replicative senescence. Despite this significant difference between iMSCs and BM-MSCs proliferation, both untargeted and targeted proteomic analysis revealed a similar secretome composition for both sources in pre-senescent and senescent states. These results suggest that shifting from the use of BM-MSCs to a more advantageous source, like iMSCs, may yield similar therapeutic effects as identified over the past years for this gold-standard MSC source. Graphical Abstract: [Figure not available: see fulltext.].
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