Refine
Year of publication
- 2014 (1892) (remove)
Document Type
- Article (1253)
- Doctoral Thesis (222)
- Postprint (127)
- Review (65)
- Monograph/Edited Volume (61)
- Preprint (47)
- Conference Proceeding (43)
- Part of Periodical (27)
- Part of a Book (19)
- Other (11)
Language
Keywords
- prevention (25)
- violence (22)
- Gewalt (21)
- Kriminalität (21)
- Nachhaltigkeit (21)
- Prävention (21)
- Rechtsextremismus (21)
- crime (21)
- right-wing extremism (21)
- sustainability (21)
Institute
- Institut für Biochemie und Biologie (251)
- Institut für Physik und Astronomie (239)
- Institut für Geowissenschaften (228)
- Institut für Chemie (189)
- Department Psychologie (92)
- Wirtschaftswissenschaften (62)
- Sozialwissenschaften (59)
- Institut für Ernährungswissenschaft (58)
- Institut für Mathematik (54)
- Department Linguistik (52)
Elucidating the genetic basis of morphological changes in evolution remains a major challenge in biology [1-3]. Repeated independent trait changes are of particular interest because they can indicate adaptation in different lineages or genetic and developmental constraints on generating morphological variation [4-6]. In animals, changes to "hot spot" genes with minimal pleiotropy and large phenotypic effects underlie many cases of repeated morphological transitions [4-8]. By contrast, only few such genes have been identified from plants [8-11], limiting cross-kingdom comparisons of the principles of morphological evolution. Here, we demonstrate that the REDUCED COMPLEXITY (RCO) locus [12] underlies more than one naturally evolved change in leaf shape in the Brassicaceae. We show that the difference in leaf margin dissection between the sister species Capsella rubella and Capsella grandiflora is caused by cis-regulatory variation in the homeobox gene RCO-A, which alters its activity in the developing lobes of the leaf. Population genetic analyses in the ancestral C. grandiflora indicate that the more-active C. rubella haplotype is derived from a now rare or lost C. grandiflora haplotype via additional mutations. In Arabidopsis thaliana, the deletion of the RCO-A and RCO-B genes has contributed to its evolutionarily derived smooth leaf margin [12], suggesting the RCO locus as a candidate for an evolutionary hot spot. We also find that temperature-responsive expression of RCO-A can explain the phenotypic plasticity of leaf shape to ambient temperature in Capsella, suggesting a molecular basis for the well-known negative correlation between temperature and leaf margin dissection.
Polyadenylation of pre-mRNAs by poly(A) polymerase (PAPS) is a critical process in eukaryotic gene expression. As found in vertebrates, plant genomes encode several isoforms of canonical nuclear PAPS enzymes. In Arabidopsis thaliana these isoforms are functionally specialized, with PAPS1 affecting both organ growth and immune response, at least in part by the preferential polyadenylation of subsets of pre-mRNAs. Here, we demonstrate that the opposite effects of PAPS1 on leaf and flower growth reflect the different identities of these organs, and identify a role for PAPS1 in the elusive connection between organ identity and growth patterns. The overgrowth of paps1 mutant petals is due to increased recruitment of founder cells into early organ primordia, and suggests that PAPS1 activity plays unique roles in influencing organ growth. By contrast, the leaf phenotype of paps1 mutants is dominated by a constitutive immune response that leads to increased resistance to the biotrophic oomycete Hyaloperonospora arabidopsidis and reflects activation of the salicylic acid-independent signalling pathway downstream of ENHANCED DISEASE SUSCEPTIBILITY1 (EDS1)/PHYTOALEXIN DEFICIENT4 (PAD4). These findings provide an insight into the developmental and physiological basis of the functional specialization amongst plant PAPS isoforms.
Context: Relations between fibroblast growth factor-23 (FGF-23), soluble alpha-klotho (s-alpha-klotho), and kidney function in chronic kidney disease (CKD) are still unclear. Especially the role of s-alpha-klotho requires further study.
Objectives: Our objectives were to analyze the relation of s-alpha-klotho to estimated glomerular filtration rate (eGFR), FGF-23, and other parameters of calcium-phosphate metabolism and to investigate the response of s-alpha-klotho to cholecalciferol.
Patients, Design, and Setting: Twenty-four CKD (stage 1-5) patients participated in this 8-week randomized controlled trial (vitamin D and chronic renal insufficiency).
Interventions: Interventions included 40 000 IU cholecalciferol or placebo weekly.
Main Outcome Measure: S-alpha-klotho was determined by ELISA with antihuman klotho antibodies 67G3 and 91F1.
Results: For all patients, s-alpha-klotho concentrations did not differ between CKD stages. When patients were subdivided based on FGF-23 concentrations, a positive association of s-alpha-klotho with eGFR became apparent in patients with lower than median FGF-23 concentrations but not in those above median value. Patients with s-alpha-klotho below 204 pg/mL showed higher age, lower phosphate clearance, and lower bone-specific alkaline phosphatase compared with patients with higher s-alpha-klotho. Treatment with cholecalciferol significantly increased 1,25-dihydroxyvitamin D. The increase of FGF-23 had only borderline significance. There was no significant effect of high-dose cholecalciferol administration for 8 weeks on plasma s-alpha-klotho.
Conclusions: CKD patients with s-alpha-klotho below 204 pg/mL had higher age, lower phosphate clearance, and lower bone-specific alkaline phosphatase. An association of s-alpha-klotho with eGFR was observed only in the presence of close to normal, but not high, FGF-23 concentrations. Cholecalciferol treatment did not change s-alpha-klotho concentrations.
Diatom diversity in lakes of northwest Yakutia (Siberia) was investigated by microscopic and genetic analysis of surface and cored lake sediments, to evaluate the use of sedimentary DNA for paleolimnological diatom studies and to identify obscure genetic diversity that cannot be detected by microscopic methods. Two short (76 and 73 bp) and one longer (577 bp) fragments of the ribulose 1,5-bisphosphate carboxylase/oxygenase (rbcL) gene, encoding the large subunit of the rbcL, were used as genetic markers. Diverse morphological assemblages of diatoms, dominated by small benthic fragilarioid taxa, were retrieved from the sediments of each lake. These minute fragilarioid taxa were examined by scanning electron microscopy, revealing diverse morphotypes in Staurosira and Staurosirella from the different lakes. Genetic analyses indicated a dominance of haplotypes that were assigned to fragilarioid taxa and less genetic diversity in other diatom taxa. The long rbcL_577 amplicon identified considerable diversification among haplotypes clustering within the Staurosira/Staurosirella genera, revealing 19 different haplotypes whose spatial distribution appears to be primarily related to the latitude of the lakes, which corresponds to a vegetation and climate gradient. Our rbcL markers are valuable tools for tracking differences between diatom lineages that are not visible in their morphologies. These markers revealed putatively high genetic diversity within the Staurosira/Staurosirella species complex, at a finer scale than is possible to resolve by microscopic determination. The rbcL markers may provide additional reliable information on the diversity of barely distinguishable minute benthic fragilarioids. Environmental sequencing may thus allow the tracking of spatial and temporal diversification in Siberian lakes, especially in the context of diatom responses to recent environmental changes, which remains a matter of controversy.
A modern pollen dataset from China and Mongolia (18-52 degrees N, 74-132 degrees E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables - mean annual precipitation (P-ann): 35-2091 mm, mean annual temperature (T-ann): -12.1-25.8 degrees C, mean temperature in the coldest month (Mt(co).): -33.8-21.7 degrees C, and mean temperature in the warmest month (Mt(wa)): 03-29.8 degrees C. Modern pollen-climate relationships are assessed using canonical correspondence analysis (CCA), Huisman-Olff-Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that P-ann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r(2)) and root mean square error of prediction (RMSEP). Mt(co) and Mt(wa) may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power. (C) 2014 Elsevier B.V. All rights reserved.
AimFossil pollen spectra from lake sediments in central and western Mongolia have been used to interpret past climatic variations, but hitherto no suitable modern pollen-climate calibration set has been available to infer past climate changes quantitatively. We established such a modern pollen dataset and used it to develop a transfer function model that we applied to a fossil pollen record in order to investigate: (1) whether there was a significant moisture response to the Younger Dryas event in north-western Mongolia; and (2) whether the early Holocene was characterized by dry or wet climatic conditions.
LocationCentral and western Mongolia.
MethodsWe analysed pollen data from surface sediments from 90 lakes. A transfer function for mean annual precipitation (P-ann) was developed with weighted averaging partial least squares regression (WA-PLS) and applied to a fossil pollen record from Lake Bayan Nuur (49.98 degrees N, 93.95 degrees E, 932m a.s.l.). Statistical approaches were used to investigate the modern pollen-climate relationships and assess model performance and reconstruction output.
ResultsRedundancy analysis shows that the modern pollen spectra are characteristic of their respective vegetation types and local climate. Spatial autocorrelation and significance tests of environmental variables show that the WA-PLS model for P-ann is the most valid function for our dataset, and possesses the lowest root mean squared error of prediction.
Main conclusionsPrecipitation is the most important predictor of pollen and vegetation distributions in our study area. Our quantitative climate reconstruction indicates a dry Younger Dryas, a relatively dry early Holocene, a wet mid-Holocene and a dry late Holocene.
This study examines the course and driving forces of recent vegetation change in the Mongolian steppe. A sediment core covering the last 55years from a small closed-basin lake in central Mongolia was analyzed for its multi-proxy record at annual resolution. Pollen analysis shows that highest abundances of planted Poaceae and highest vegetation diversity occurred during 1977-1992, reflecting agricultural development in the lake area. A decrease in diversity and an increase in Artemisia abundance after 1992 indicate enhanced vegetation degradation in recent times, most probably because of overgrazing and farmland abandonment. Human impact is the main factor for the vegetation degradation within the past decades as revealed by a series of redundancy analyses, while climate change and soil erosion play subordinate roles. High Pediastrum (a green algae) influx, high atomic total organic carbon/total nitrogen (TOC/TN) ratios, abundant coarse detrital grains, and the decrease of C-13(org) and N-15 since about 1977 but particularly after 1992 indicate that abundant terrestrial organic matter and nutrients were transported into the lake and caused lake eutrophication, presumably because of intensified land use. Thus, we infer that the transition to a market economy in Mongolia since the early 1990s not only caused dramatic vegetation degradation but also affected the lake ecosystem through anthropogenic changes in the catchment area.
Subfossil Cladocera were sampled and examined from the surface sediments of 35 thermokarst lakes along a temperature gradient crossing the tree line in the Anabar-river basin in northwestern Yakutia, northeastern Siberia. The lakes were distributed through three environmental zones: typical tundra, southern tundra and forest tundra. All lakes were situated within the continuous permafrost zone. Our investigation showed that the cladoceran communities in the lakes of the Anabar region are diverse and abundant, as reflected by taxonomic richness, and high diversity and evenness indices (H = 1.89 +/- A 0.51; I = 0.8 +/- A 0.18). CONISS cluster analysis indicated that the cladoceran communities in the three ecological zones (typical tundra, southern tundra and forest-tundra) differed in their taxonomic composition and structure. Differences in the cladoceran assemblages were related to limnological features and geographical position, vegetation type, climate and water chemistry. The constrained redundancy analysis indicated that T-July, water depth and both sulphate (SO4 (2-)) and silica (Si4+) concentrations significantly (p a parts per thousand currency sign 0.05) explained variance in the cladoceran assemblage. T-July featured the highest percentage (17.4 %) of explained variance in the distribution of subfossil Cladocera. One of the most significant changes in the structure of the cladoceran communities in the investigated transect was the replacement of closely related species along the latitudinal and vegetation gradient. The results demonstrate the potential for a regional cladoceran-based temperature model for the Arctic regions of Russia, and for and Yakutia in particular.
Late Holocene glacier variations in westernmost Tibetan Plateau were studied based on the analysis of grain size, magnetic susceptibility, and elements from an 8.3m long distal glaciolacustrine sediment core of Kalakuli Lake. Our results show that there are four glacier expansion episodes occurring in 4200-3700calibrated years (cal years) B.P., 2950-2300cal years B.P., 1700-1070cal years B.P., and 570-100cal years B.P. and four glacier retreat periods of 3700-2950cal years B.P., 2300-1700cal years B.P., 1070-570cal years B.P., and 50cal years B.P.-present. The four glacier expansion episodes are generally in agreement with the glacier activities indicted by the moraines at Muztagh Ata and Kongur Shan, as well as with the late Holocene ice-rafting events in the North Atlantic. Over the last 2000years, our reconstructed glacier variations are in temporal agreement with reconstructed temperature from China and the Northern Hemisphere, indicating that glacier variations at centennial time scales are very sensitive to temperature in western Tibetan Plateau.
Eye movements during reading proverbs and regular sentences: the incoming word predictability effect
(2014)
Humans typically read at incredibly fast rates, because they predict likely occurring words from a given context. Here, we used functional near-infrared spectroscopy (fNIRS) to track the ultra-rapid hemodynamic responses of words presented every 280 ms in a naturally paced sentence context. We found a lower occipital deoxygenation to unpredictable than to predictable words. The greater hemodynamic responses to unexpected words suggest that the visual features of expected words have been pre-activated previous to stimulus presentation. Second, we tested opposing theoretical proposals about the role of the medial orbitofrontal cortex (OFC): Either OFC may respond to the breach of expectation; or OFC is activated when the present stimulus matches the prediction. A significant interaction between word frequency and predictability indicated OFC responses to breaches of expectation for low- but not for high-frequency words: OFC is sensitive to both, bottom-up processing as mediated by word frequency, as well as top-down predictions. Particularly, when a rare word is unpredictable, OFC becomes active. Finally, we discuss how a high temporal resolution can help future studies to disentangle the hemodynamic responses of single trials in such an ultra-rapid event succession as naturally paced reading. (C) 2014 Elsevier Inc. All rights reserved.
Unterschiedliche Verfahren zur Ermittlung von Georadar-Wellengeschwindigkeiten wurden entwickelt und erfolgreich angewendet. Für die Verfahren wurden statistische Methoden und Schwarmintelligenz-Algorithmen benutzt. Es wurde gezeigt, dass die neuen Verfahren schneller, präziser und besser reproduzierbare Ergebnisse für Georadar-Wellengeschwindigkeit erzielen als herkömmliche Verfahren.
Mit verbesserten Werten der Georadar-Wellengeschwindigkeit lassen sich die verzerrten dreidimensionalen Abbilder der obersten zehn Meter des Untergrundes, welche sich mit Georadar-Daten erzeugen lassen, korrigieren. In diesen korrigierten Abbildern sind dann realistische Tiefen von Schichten oder Objekten im Untergrund besser messbar. Außerdem verbessern präzisere Wellengeschwindigkeiten die Bestimmung von Bodenparametern, wie Wassergehalt oder Tonanteil. Die präsentierten Verfahren erlauben eine quantitative Angabe von Fehlern der bestimmten Wellengeschwindigkeit und der daraus folgenden Tiefen und Bodenparametern im Untergrund. Die Vorteile dieser neu entwickelten Verfahren zur Charakterisierung des Untergrundes der oberen Meter wurde an Feldbeispielen demonstriert.
For a detailed characterization of near-surface environments, geophysical techniques are increasingly used to support more conventional point-based techniques such as borehole and direct-push logging. Because the underlying parameter relations are often complex, site-specific, or even poorly understood, a remaining challenging task is to link the geophysical parameter models to the actual geotechnical target parameters measured only at selected points. We propose a workflow based on nonparametric regression to establish functional relationships between jointly inverted geophysical parameters and selected geotechnical parameters as measured, for example, by different borehole and direct-push tools. To illustrate our workflow, we present field data collected to characterize a near-surface sedimentary environment Our field data base includes crosshole ground penetrating radar (GPR), seismic P-, and S-wave data sets collected between 25 m deep boreholes penetrating sand- and gravel dominated sediments. Furthermore, different typical borehole and direct-push logs are available. We perform a global joint inversion of traveltimes extracted from the crosshole geophysical data using a recently proposed approach based on particle swarm optimization. Our inversion strategy allows for generating consistent models of GPR, P-wave, and S-wave velocities including an appraisal of uncertainties. We analyze the observed complex relationships between geophysical velocities and target parameter logs using the alternating conditional expectation (ACE) algorithm. This nonparametric statistical tool allows us to perform multivariate regression analysis without assuming a specific functional relation between the variables. We are able to explain selected target parameters such as characteristic grain size values or natural gamma activity by our inverted geophysical data and to extrapolate these parameters to the inter-borehole plane covered by our crosshole experiments. We conclude that the ACE algorithm is a powerful tool to analyze a multivariate petrophysical data base and to develop an understanding of how a multi-parameter geophysical model can be linked and translated to selected geotechnical parameters.
Velocity models are essential to process two-and three-dimensional ground-penetrating radar (GPR) data. Furthermore, velocity information aids the interpretation of such data sets because velocity variations reflect important material properties such as water content. In many GPR applications, common midpoint (CMP) surveys are routinely collected to determine one-dimensional velocity models at selected locations. To analyse CMP data gathers, spectral velocity analyses relying on the normal-moveout (NMO) model are commonly employed. Using Dix's formula, the derived NMO velocities can be further converted to interval velocities which are needed for processing and interpretation. Because of the inherent assumptions and limitations of such approaches, we investigate and propose an alternative procedure based on the global inversion of reflection travel-times. We use a finite-difference solver of the Eikonal equation to accurately solve the forward problem in combination with particle swarm optimization (PSO) to find one-dimensional GPR velocity models explaining our data. Because PSO is a robust and efficient global optimization tool, our inversion approach includes generating an ensemble of representative solutions that allows us to analyse uncertainties in the model space. Using synthetic data examples, we test and evaluate our inversion approach to analyse CMP data collected across typical near-surface environments. Application to a field data set recorded at a well-constrained test site including a comparison to independent borehole and direct-push data, further illustrates the potential of the proposed approach, which includes a straightforward and understandable appraisal of non-uniqueness and uncertainty issues, respectively. We conclude that our methodology is a feasible and powerful tool to analyse GPR CMP data and allows practitioners and researchers to evaluate the reliability of CMP derived velocity models.
Vertical radar profiling (VRP) is a single-borehole geophysical technique, in which the receiver antenna is located within a borehole and the transmitter antenna is placed at one or various offsets from the borehole. Today, VRP surveying is primarily used to derive 1D velocity models by inverting the arrival times of direct waves. Using field data collected at a well-constrained test site in Germany, we evaluated a VRP workflow relying on the analysis of direct-arrival traveltimes and amplitudes as well as on imaging reflection events. To invert our VRP traveltime data, we used a global inversion strategy resulting in an ensemble of acceptable velocity models, and thus, it allowed us to appraise uncertainty issues in the estimated velocities as well as in porosity models derived via petrophysical translations. In addition to traveltime inversion, the analysis of direct-wave amplitudes and reflection events provided further valuable information regarding subsurface properties and architecture. The used VRP amplitude preprocessing and inversion procedures were adapted from raybased crosshole ground-penetrating radar (GPR) attenuation tomography and resulted in an attenuation model, which can be used to estimate variations in electrical resistivity. Our VRP reflection imaging approach relied on corridor stacking, which is a well-established processing sequence in vertical seismic profiling. The resulting reflection image outlines bounding layers and can be directly compared to surface-based GPR reflection profiling. Our results of the combined analysis of VRP, traveltimes, amplitudes, and reflections were consistent with independent core and borehole logs as well as GPR reflection profiles, which enabled us to derive a detailed hydro-stratigraphic model as needed, for example, to understand and model groundwater flow and transport.
Geophysical techniques offer the potential to tomographically image physical parameter variations in the ground in two or three dimensions. Due to the limited number and accuracy of the recorded data, geophysical model generation by inversion suffers ambiguity. Linking the model generation process of disparate data by jointly inverting two or more data sets allows for improved model reconstruction. Fully nonlinear inversion using optimization techniques searching the solution space of the inverse problem globally enables quantitative assessment of the ambiguity inherent to the model reconstruction. We used two different multiobjective particle swarm optimization approaches to jointly invert synthetic crosshole tomographic data sets comprising radar and P-wave traveltimes, respectively. Beginning with a nonlinear joint inversion founded on the principle of Pareto optimality and game theoretic concepts, we obtained a set of Pareto-optimal solutions comprising commonly structured radar and P-wave velocity models for low computational costs. However, the efficiency of the approach goes along with some risk of achieving a final model ensemble not adequately illustrating the ambiguity inherent to the model reconstruction process. Taking advantage of the results of the first approach, we inverted the database using a different nonlinear joint-inversion approach reducing the multiobjective optimization problem to a single-objective one. Computational costs were significantly higher, but the final models were obtained mutually independently allowing for objective appraisal of model parameter determination. Despite the high computational effort, the approach was found to be an efficient nonlinear joint-inversion formulation compared to what could be extracted from individual nonlinear inversions of both data sets.
According to Dooge (1986) intermediate-scale catchments are systems of organized complexity, being too organized and yet too small to be characterized on a statistical/conceptual basis, but too large and too heterogeneous to be characterized in a deterministic manner. A key requirement for building structurally adequate models precisely for this intermediate scale is a better understanding of how different forms of spatial organization affect storage and release of water and energy. Here, we propose that a combination of the concept of hydrological response units (HRUs) and thermodynamics offers several helpful and partly novel perspectives for gaining this improved understanding. Our key idea is to define functional similarity based on similarity of the terrestrial controls of gradients and resistance terms controlling the land surface energy balance, rainfall runoff transformation, and groundwater storage and release. This might imply that functional similarity with respect to these specific forms of water release emerges at different scales, namely the small field scale, the hillslope, and the catchment scale. We thus propose three different types of "functional units" - specialized HRUs, so to speak - which behave similarly with respect to one specific form of water release and with a characteristic extent equal to one of those three scale levels. We furthermore discuss an experimental strategy based on exemplary learning and replicate experiments to identify and delineate these functional units, and as a promising strategy for characterizing the interplay and organization of water and energy fluxes across scales. We believe the thermodynamic perspective to be well suited to unmask equifinality as inherent in the equations governing water, momentum, and energy fluxes: this is because several combinations of gradients and resistance terms yield the same mass or energy flux and the terrestrial controls of gradients and resistance terms are largely independent. We propose that structurally adequate models at this scale should consequently disentangle driving gradients and resistance terms, because this optionally allow sequifinality to be partly reduced by including available observations, e. g., on driving gradients. Most importantly, the thermodynamic perspective yields an energy-centered perspective on rainfall-runoff transformation and evapotranspiration, including fundamental limits for energy fluxes associated with these processes. This might additionally reduce equifinality and opens up opportunities for testing thermodynamic optimality principles within independent predictions of rainfall-runoff or land surface energy exchange. This is pivotal to finding out whether or not spatial organization in catchments is in accordance with a fundamental organizing principle.
Background: The identification of brassinosteroid (BR) deficient and BR insensitive mutants provided conclusive evidence that BR is a potent growth-promoting phytohormone. Arabidopsis mutants are characterized by a compact rosette structure, decreased plant height and reduced root system, delayed development, and reduced fertility. Cell expansion, cell division, and multiple developmental processes depend on BR. The molecular and physiological basis of BR action is diverse. The BR signalling pathway controls the activity of transcription factors, and numerous BR responsive genes have been identified. The analysis of dwarf mutants, however, may to some extent reveal phenotypic changes that are an effect of the altered morphology and physiology. This restriction holds particularly true for the analysis of established organs such as rosette leaves. Results: In this study, the mode of BR action was analysed in established leaves by means of two approaches. First, an inhibitor of BR biosynthesis (brassinazole) was applied to 21-day-old wild-type plants. Secondly, BR complementation of BR deficient plants, namely CPD (constitutive photomorphogenic dwarf)-antisense and cbb1 (cabbage1) mutant plants was stopped after 21 days. BR action in established leaves is associated with stimulated cell expansion, an increase in leaf index, starch accumulation, enhanced CO2 release by the tricarboxylic acid cycle, and increased biomass production. Cell number and protein content were barely affected. Conclusion: Previous analysis of BR promoted growth focused on genomic effects. However, the link between growth and changes in gene expression patterns barely provided clues to the physiological and metabolic basis of growth. Our study analysed comprehensive metabolic data sets of leaves with altered BR levels. The data suggest that BR promoted growth may depend on the increased provision and use of carbohydrates and energy. BR may stimulate both anabolic and catabolic pathways.