Electrocardiographic Features of Left Ventricular Diastolic Dysfunction and Heart Failure With Preserved Ejection Fraction: A Systematic Review

Background: Electrocardiographic features are well-known for heart failure with reduced ejection fraction (HFrEF), but not for left ventricular diastolic dysfunction (LVDD) and heart failure with preserved ejection fraction (HFpEF). As ECG features could help to identify high-risk individuals in primary care, we systematically reviewed the literature for ECG features diagnosing women and men suspected of LVDD and HFpEF. Methods and Results: Among the 7,127 records identified, only 10 studies reported diagnostic measures, of which 9 studied LVDD. For LVDD, the most promising features were T-end-P/(PQ*age), which is the electrocardiographic equivalent of the passive-to-active filling (AUC: 0.91-0.96), and repolarization times (QTc interval ≥ 350 ms, AUC: 0.85). For HFpEF, the Cornell product ≥ 1,800 mm*ms showed poor sensitivity of 40% (AUC: 0.62). No studies presented results stratified by sex. Conclusion: Electrocardiographic features are not widely evaluated in diagnostic studies for LVDD and HFpEF. Only for LVDD, two ECG features related to the diastolic interval, and repolarization measures showed diagnostic potential. To improve diagnosis and care for women and men suspected of heart failure, reporting of sex-specific data on ECG features is encouraged

Myocardial remodeling during pathophysiology: Relevance for cardiac dysfunction

Upon various forms of cardiac damage or disease, such as myocardial infarction, pressure overload or genetic cardiomyopathies, the heart attempts to adapt to its altered circumstances by myocardial remodeling, consisting of electrical, structural and contractile remodeling. Even though myocardial tissue remodeling is a natural rescue process that is initiated to maintain sufficient blood supply to the organs throughout the body, when remodeling is massive and heterogeneous, it aggravates the damage, eventually leading to heart failure. In this thesis, we focused on myocardial remodeling of predominantly the intercalated disc and tissue architecture during various cardiomyopathies such as Dilated Cardiomyopathy, Hypertrophic Cardiomyopathy, Ischemic Cardiomyopathy, and Arrhythmogenic Cardiomyopathy; and upon artificially induced pressure overload in mice, where we studied the effect of fibrosis and inflammation

Heterogeneity of glycaemic phenotypes in type 1 diabetes

International audienceAims/hypothesis: Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes.Methods: In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison.Results: We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes.Conclusions/interpretation: Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management

sPlotOpen - An environmentally balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called 'sPlot', compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Abstract Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co‐occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open‐access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local‐to‐regional datasets to openly release data. We thus present sPlotOpen, the largest open‐access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co‐occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot‐level data also include community‐weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01–40,000 m². Time period and grain 1888–2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot‐level records. Software format Three main matrices (.csv), relationally linked.Agence Nationale de la Recherche http://dx.doi.org/10.13039/501100001665H2020 European Research Council http://dx.doi.org/10.13039/100010663Villum Fonden http://dx.doi.org/10.13039/100008398Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Narodowe Centrum Nauki http://dx.doi.org/10.13039/501100004281Latvia grantNSF http://dx.doi.org/10.13039/100003187Horizon 2020 Framework Programme http://dx.doi.org/10.13039/100010661U.S. National Science Foundation http://dx.doi.org/10.13039/100000001Grantová Agentura České Republiky http://dx.doi.org/10.13039/501100001824German Centre for Integrative Biodiversity Research http://dx.doi.org/10.13039/501100020056Fundación BBVA http://dx.doi.org/10.13039/100007406Akademie Věd České Republiky http://dx.doi.org/10.13039/501100004240Spanish Research Agency http://dx.doi.org/10.13039/501100011033National Research, Development and Innovation Office, Hungar http://dx.doi.org/10.13039/501100018818Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung http://dx.doi.org/10.13039/501100001711Basque Government http://dx.doi.org/10.13039/501100003086Russian Foundation for Basic Research http://dx.doi.org/10.13039/501100002261Brazil’s National Council of Scientific and Technological DevelopmentVolkswagen Foundation http://dx.doi.org/10.13039/50110000166

sPlot - A new tool for global vegetation analyses

Dengler, Jurgen/0000-0003-3221-660X; Chytry, Milan/0000-0002-8122-3075; de Gasper, Andre Luis/0000-0002-1940-9581; Marceno, Corrado/0000-0003-4361-5200; Swacha, Grzegorz/0000-0002-6380-2954; He, Tianhua/0000-0002-0924-3637; Haider, Sylvia/0000-0002-2966-0534; Kuhn, Ingolf/0000-0003-1691-8249; Svenning, Jens-Christian/0000-0002-3415-0862; Jansen, Florian/0000-0002-0331-5185; Casella, Laura/0000-0003-2550-3010; Schmidt, Marco/0000-0001-6087-6117; Chepinoga, Victor/0000-0003-3809-7453; Petrik, Petr/0000-0001-8518-6737; Willner, Wolfgang/0000-0003-1591-8386; Jansen, Steven/0000-0002-4476-5334; De Sanctis, Michele/0000-0002-7280-6199; Niinemets, Ulo/0000-0002-3078-2192; Pauchard, Anibal/0000-0003-1284-3163; Vibrans, Alexander C./0000-0002-8789-5833; Biurrun, Idoia/0000-0002-1454-0433; De Patta Pillar, Valerio/0000-0001-6408-2891; Phillips, Oliver L/0000-0002-8993-6168; Sibik, Jozef/0000-0002-5949-862X; Lenoir, Jonathan/0000-0003-0638-9582; Venanzoni, Roberto/0000-0002-7768-0468; Gutierrez, Alvaro G./0000-0001-8928-3198; Cayuela, Luis/0000-0003-3562-2662; Nobis, Marcin/0000-0002-1594-2418; Agrillo, Emiliano/0000-0003-2346-8346; Manning, Peter/0000-0002-7940-2023; Venanzoni, Roberto/0000-0002-7768-0468; Virtanen, Risto/0000-0002-8295-8217; Higuchi, Pedro/0000-0002-3855-555X; Sopotlieva, Desislava/0000-0002-9281-7039; Kuzemko, Anna/0000-0002-9425-2756; Hatim, Mohamed/0000-0002-0872-5108; Mencuccini, Maurizio/0000-0003-0840-1477; Enquist, Brian J./0000-0002-6124-7096; De Bie, Els/0000-0001-7679-743X; Samimi, Cyrus/0000-0001-7001-7893; Nowak, Arkadiusz/0000-0001-8638-0208; Jimenez-Alfaro, Borja/0000-0001-6601-9597; Font, Xavier/0000-0002-7253-8905; Levesley, Aurora/0000-0002-7999-5519; Acic, Svetlana/0000-0001-6553-3797; Kattge, Jens/0000-0002-1022-8469; Silc, Urban/0000-0002-3052-699X; Arnst, Elise/0000-0003-2388-7428; Moretti, Marco/0000-0002-5845-3198; Kozub, Lukasz/0000-0002-6591-8045; Kacki, Zygmunt/0000-0002-2241-1631; Fagundez, Jaime/0000-0001-6605-7278; Purschke, Oliver/0000-0003-0444-0882; Martynenko, Vasiliy/0000-0002-9071-3789; Jandt, Ute/0000-0002-3177-3669; Peyre, Gwendolyn/0000-0002-1977-7181; SABATINI, FRANCESCO MARIA/0000-0002-7202-7697; Bruelheide, Helge/0000-0003-3135-0356; Wohlgemuth, Thomas/0000-0002-4623-0894; Onyshchenko, Viktor/0000-0001-9079-7241; Kuzmic, Filip/0000-0002-3894-7115; Ejrnaes, Rasmus/0000-0003-2538-8606; Jirousek, Martin/0000-0002-4293-478X; Noroozi, Jalil/0000-0003-4124-2359; Curran, Michael/0000-0002-1858-5612; Baraloto, Christopher/0000-0001-7322-8581; Ozinga, Wim/0000-0002-6369-7859WOS: 000466421500001Aims Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.German Research FoundationGerman Research Foundation (DFG) [DFG FZT 118]; TRY initiative on plant traitsWe are grateful to thousands of vegetation scientists who sampled vegetation plots in the field or digitized them into regional, national or international databases. We also appreciate the support of the German Research Foundation for funding sPlot as one of the iDiv (DFG FZT 118) research platforms, and the organization of three workshops through the sDiv calls. We acknowledge this support with naming the database "sPlot", where the "s" refers to the sDiv synthesis workshops. The study was supported by the TRY initiative on plant traits (http://www.try-db.org). For all further acknowledgements see Appendix S10. We thank Meelis Partel for his very fast and constructive feedback on an earlier version of this manuscript

Rapid Improvement after Starting Elexacaftor–Tezacaftor–Ivacaftor in Patients with Cystic Fibrosis and Advanced Pulmonary Disease

International audienceRationale: Elexacaftor-tezacaftor-ivacaftor is a CFTR (cystic fibrosis [CF] transmembrane conductance regulator) modulator combination, developed for patients with CF with at least one Phe508del mutation. Objectives: To evaluate the effects of elexacaftor-tezacaftor- ivacaftor in patients with CF and advanced respiratory disease. Methods: A prospective observational study, including all patients aged ⩾12 years and with a percent-predicted FEV1 (ppFEV1) <40 who initiated elexacaftor-tezacaftor-ivacaftor from December 2019 to August 2020 in France was conducted. Clinical characteristics were collected at initiation and at 1 and 3 months. Safety and effectiveness were evaluated by September 2020. National-level transplantation and mortality figures for 2020 were obtained from the French CF and transplant centers and registries. Measurements and Main Results: Elexacaftor-tezacaftor- ivacaftor was initiated in 245 patients with a median (interquartile range) ppFEV1 = 29 (24-34). The mean (95% confidence interval) absolute increase in the ppFEV1 was +15.1 (+13.8 to +16.4; P < 0.0001), and the mean (95% confidence interval) in weight was +4.2 kg (+3.9 to +4.6; P < 0.0001). The number of patients requiring long-term oxygen, noninvasive ventilation, and/or enteral tube feeding decreased by 50%, 30%, and 50%, respectively (P < 0.01). Although 16 patients were on the transplant waiting list and 37 were undergoing transplantation evaluation at treatment initiation, only 2 received a transplant, and 1 died. By September 2020, only five patients were still on the transplantation path. Compared with the previous 2 years, a twofold decrease in the number of lung transplantations in patients with CF was observed in 2020, whereas the number of deaths without transplantation remained stable. Conclusions: In patients with advanced disease, elexacaftor-tezacaftor-ivacaftor is associated with rapid clinical improvement, often leading to the indication for lung transplantation being suspended

sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots

Abstract Motivation: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01–40,000 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measurement: 42,677 vascular plant taxa, plot-level records. Software format: Three main matrices (.csv), relationally linked

sPlot:a new tool for global vegetation analyses

Abstract Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale

Impact of COVID-19 infection on lung function and nutritional status amongst individuals with cystic fibrosis: A global cohort study

International audienceBackground: Factors associated with severe COVID-19 infection have been identified; however, the impact of infection on longer-term outcomes is unclear. The objective of this study was to examine the impact of COVID-19 infection on the trajectory of lung function and nutritional status in people with cystic fibrosis (pwCF).Methods: This is a retrospective global cohort study of pwCF who had confirmed COVID-19 infection diagnosed between January 1, 2020 and December 31, 2021. Forced expiratory volume in one second percent predicted (ppFEV 1 ) and body mass index (BMI) twelve months prior to and following a diagnosis of COVID-19 were recorded. Change in mean ppFEV 1 and BMI were compared using a t-test. A linear mixed-effects model was used to estimate change over time and to compare the rate of change before and after infection.Results: A total of 6,500 cases of COVID-19 in pwCF from 33 countries were included for analysis. The mean difference in ppFEV 1 pre-and post-infection was 1.4 %, (95 % CI 1.1, 1.7). In those not on modulators, the difference in rate of change pre-and post-infection was 1.34 %, (95 % CI -0.88, 3.56) per year (p = 0.24) and -0.74 % (-1.89, 0.41) per year (p = 0.21) for those on elexacaftor/tezacaftor/ivacaftor. No clinically significant change was noted in BMI or BMI percentile before and after COVID-19 infection.Conclusions: No clinically meaningful impact on lung function and BMI trajectory in the year following infection with COVID-19 was identified. This work highlights the ability of the global CF community to unify and address critical issues facing pwCF