Efecto de un calentamiento con estiramientos estáticos y dinámicos sobre el salto horizontal y la capacidad para repetir esprint con cambio de dirección = Effect of warm-up with static and dynamic stretching on the horizontal jump and repeated sprint ability with changes of direction

P. 26-38El objetivo de este trabajo ha sido comparar el efecto de tres calentamientos diferentes (calentamiento aeróbico de baja intensidad, estiramiento estático y estiramiento dinámico) sobre el salto horizontal y la capacidad de repetir esprint con cambios de dirección. Diecisiete practicantes de deportes de equipo de 20.8±1.1 años realizaron 3 tipos de calentamiento (10 min): ejercicio aeróbico sin estiramiento (CAE), con estiramiento estático (CAES) y con estiramiento dinámico (CAED). Se estudió el efecto agudo de cada calentamiento sobre el rendimiento en una prueba de salto horizontal (SH) y un test de repetición de esprint con cambio de dirección (RSCOD). No se obtuvieron diferencias significativas (p>0.05) en ninguna de las variables en función del calentamiento realizado. El tamaño del efecto (TE) indicó que probablemente el RSCODmejor sea más sensible al CAE que al CAES (TE: 0.52) y al CAED (TE: 0.44). El escaso efecto de los estiramientos estáticos sobre el rendimiento en SH y RSCOD puede ser debido a la dosis, la intensidad y el tiempo de recuperación empleado. Los estiramientos dinámicos no mejoraron el rendimiento en SH y RSCODS

The BTB transcription factors ZBTB11 and ZFP131 maintain pluripotency by repressing pro-differentiation genes

In pluripotent cells, a delicate activation-repression balance maintains pro-differentiation genes ready for rapid activation. The identity of transcription factors (TFs) that specifically repress pro-differentiation genes remains obscure. By targeting ∼1,700 TFs with CRISPR loss-of-function screen, we found that ZBTB11 and ZFP131 are required for embryonic stem cell (ESC) pluripotency. ESCs without ZBTB11 or ZFP131 lose colony morphology, reduce proliferation rate, and upregulate transcription of genes associated with three germ layers. ZBTB11 and ZFP131 bind proximally to pro-differentiation genes. ZBTB11 or ZFP131 loss leads to an increase in H3K4me3, negative elongation factor (NELF) complex release, and concomitant transcription at associated genes. Together, our results suggest that ZBTB11 and ZFP131 maintain pluripotency by preventing premature expression of pro-differentiation genes and present a generalizable framework to maintain cellular potency

TRY plant trait database - enhanced coverage and open access

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

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

TRY plant trait database – enhanced coverage and open access

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

TRY plant trait database - enhanced coverage and open access

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

TRY plant trait database – enhanced coverage and open access

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

Efecto de un calentamiento con estiramientos estáticos y dinámicos sobre el salto horizontal y la capacidad para repetir esprint con cambio de dirección. [Effect of warm-up with static and dynamic stretching on the horizontal jump and repeated sprint ability with changes of direction].

El objetivo de este trabajo ha sido comparar el efecto de tres calentamientos diferentes (calentamiento aeróbico de baja intensidad, estiramiento estático y estiramiento dinámico) sobre el salto horizontal y la capacidad de repetir esprint con cambios de dirección. Diecisiete practicantes de deportes de equipo de 20.8±1.1 años realizaron 3 tipos de calentamiento (10 min): ejercicio aeróbico sin estiramiento (CAE), con estiramiento estático (CAES) y con estiramiento dinámico (CAED). Se estudió el efecto agudo de cada calentamiento sobre el rendimiento en una prueba de salto horizontal (SH) y un test de repetición de esprint con cambio de dirección (RSCOD). No se obtuvieron diferencias significativas (p>0,05) en ninguna de las variables en función del calentamiento realizado. El tamaño del efecto (TE) indicó que probablemente el RSCODmejor sea más sensible al CAE que al CAES (TE: 0,52) y al CAED (TE: 0,44). El escaso efecto de los estiramientos estáticos sobre el rendimiento en SH y RSCOD puede ser debido a la dosis, la intensidad y el tiempo de recuperación empleado. Los estiramientos dinámicos no mejoraron el rendimiento en SH y RSCOD.AbstractThe purpose of this study was to compare the effect of three different warm-ups (low intensity aerobic warm-up, static stretching and dynamic stretching) on the horizontal jump and repeated sprint ability with changes of direction. Seventeen players of team sports whose age was 20.8±1.1 years old performed three types of warm up (10 minutes): aerobic exercise without stretching (WU), with static stretching (WUSS) and with dynamic stretching (WUDS). The acute effect of each warming over performance was studied in a test of horizontal jump (HJ) and repeat sprint test with change of direction (RSCD). No significant differences were obtained (p>0.05) in any of the variables studied according to the warming developed. 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Análise comparativa da captação de 18 fluordesoxiglicose por câmara de cintilação e sistema de coincidência e a ecocardiografia de estresse pela dobutamina na detecção de viabilidade miocárdica Comparative study of 18 F-fluorodeoxyglucose imaging with a dual-head coincidence gamma camera with dobutamine stress echocardiography for the assessment of myocardial viability

OBJETIVO: Comparar a câmara de cintilação e sistema de coincidência (CC) com a ecocardiografia de estresse pela dobutamina (EED) na detecção de viabilidade miocárdica, utilizando-se a recuperação funcional como padrão de referência. MÉTODOS: Vinte e um pacientes com doença arterial coronária e disfunção grave do ventrículo esquerdo foram estudados prospectivamente, submetidos a EED e CC, antes da cirurgia de revascularização do miocárdio (RM), e a EED, três meses após. RESULTADOS: De 290 segmentos analisados, 83% encontravam-se acinéticos, 15%, hipocinéticos, e 2, discinéticos ao repouso. A EED identificou 68% destes segmentos como não-viáveis. A CC identificou 56% destes segmentos como normais (contratilidade alterada com metabolismo e perfusão preservada), 30% como viáveis (perfusão reduzida e metabolismo preservado) e 14%, como não-viáveis (ausência de metabolismo e perfusão). Entre os não-viáveis pela EED, a CC classificou 80% como normais ou viáveis e 19,9%, como não viáveis (pOBJECTIVE: To compare Dual-Head coincidence gamma camera (DCD-AC) with dobutamine stress echocardiography (DSE) in viability assessment, using functional recovery as the gold standard. METHODS: Twenty-one patients were prospectively studied, with coronary artery disease and severe left ventricular dysfunction undergoing DSE and DCD-AC at baseline and DSE three months after revascularization. RESULTS: Of the 290 segments analyzed, 83% were akinetic, 15% hypokinetic and 2% dyskinetic at rest. DSE identified 68% of these segments as non-viable. DCD-AC identified 56% of these segments as normal (dysfunctional segments with preserved metabolism and perfusion), 30% as viable (preserved metabolism and reduced perfusion) and 14% as non-viable (reduced perfusion and metabolism). Of the DSE non-viable segments, DCD-AC identified 80% as normal or viable and 19.9% as non-viable (p<0.001). In hypokinetic segments viability and normal segments were detected in a higher proportion by both methods (p<0.001). DSE sensibility and specificity were 48.3% and 78.1% respectively. DCD-AC sensibility and specificity was 92.2% and 20.0%. DCD-AC identifies a higher incidence of function improvement in normal segments than in viable and non-viable. CONCLUSION: DCD-AC classified as normal or viable most of the non-viable DSE segments. In assessment of functional recovery segments after three months, DCD-AC showed a high sensibility but low specificity