Thermoperiodic Control of Hypocotyl Elongation Depends on Auxin-Induced Ethylene Signaling That Controls Downstream PHYTOCHROME INTERACTING FACTOR3 Activity

<p>We show that antiphase light-temperature cycles (negative day-night temperature difference [2DIF]) inhibit hypocotyl growth in Arabidopsis (Arabidopsis thaliana). This is caused by reduced cell elongation during the cold photoperiod. Cell elongation in the basal part of the hypocotyl under 2DIF was restored by both 1-aminocyclopropane-1-carboxylic acid (ACC; ethylene precursor) and auxin, indicating limited auxin and ethylene signaling under 2DIF. Both auxin biosynthesis and auxin signaling were reduced during 2DIF. In addition, expression of several ACC Synthase was reduced under 2DIF but could be restored by auxin application. In contrast, the reduced hypocotyl elongation of ethylene biosynthesis and signaling mutants could not be complemented by auxin, indicating that auxin functions upstream of ethylene. The PHYTOCHROME INTERACTING FACTORS (PIFs) PIF3, PIF4, and PIF5 were previously shown to be important regulators of hypocotyl elongation. We now show that, in contrast to pif4 and pif5 mutants, the reduced hypocotyl length in pif3 cannot be rescued by either ACC or auxin. In line with this, treatment with ethylene or auxin inhibitors reduced hypocotyl elongation in PIF4 overexpressor (PIF4ox) and PIF5ox but not PIF3ox plants. PIF3 promoter activity was strongly reduced under 2DIF but could be restored by auxin application in an ACC Synthase-dependent manner. Combined, these results show that PIF3 regulates hypocotyl length downstream, whereas PIF4 and PIF5 regulate hypocotyl length upstream of an auxin and ethylene cascade. We show that, under 2DIF, lower auxin biosynthesis activity limits the signaling in this pathway, resulting in low activity of PIF3 and short hypocotyls.</p

Factors associated with first return to work and sick leave durations in workers with common mental disorders

Background: Associations are examined between socio-demographic, medical, work-related and organizational factors and the moment of first return to work (RTW) (within or after 6 weeks of sick leave) and total sick leave duration in sick leave spells due to common mental disorders. Methods: Data are derived from a Dutch database, build to provide reference data for sick leave duration for various medical conditions. The cases in this study were entered in 2004 and 2005 by specially trained occupational health physicians, based on the physician's assessment of medical and other factors. Odds ratios for first RTW and sick leave durations are calculated in logistic regression models. Results: Burnout, depression and anxiety disorder are associated with longer sick leave duration. Similar, but weaker associations were found for female sex, being a teacher, small company size and moderate or high psychosocial hazard. Distress is associated with shorter sick leave duration. Medical factors, psychosocial hazard and company size are also and analogously associated with first RTW. Part-time work is associated with delayed first RTW. The strength of the associations varies for various factors and for different sick leave durations. Conclusion: The medical diagnosis has a strong relation with the moment of first RTW and the duration of sick leave spells in mental disorders, but the influence of demographic and work-related factors should not be neglected

Analysis of long-term terrestrial water storage variations in the Yangtze River basin

In this study, we analyze 32 yr of terrestrial water storage (TWS) data obtained from the Interim Reanalysis Data (ERA-Interim) and Noah model from the Global Land Data Assimilation System (GLDAS-Noah) for the period 1979 to 2010. The accuracy of these datasets is validated using 26 yr (1979–2004) of runoff data from the Yichang gauging station and comparing them with 32 yr of independent precipitation data obtained from the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA's PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin has decreased significantly since the year 1998. The driest period in the basin occurred between 2005 and 2010, and particularly in the middle and lower Yangtze reaches. The TWS figures changed abruptly to persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. The year 2006 is identified as major inflection point, at which the system starts exhibiting a persistent decrease in TWS. Comparing these TWS trends with independent precipitation datasets shows that the recent decrease in TWS can be attributed mainly to a decrease in the amount of precipitation. Our findings are based on observations and modeling datasets and confirm previous results based on gauging station datasets

Scanning Imaging Absorption Spectrometer for Atmospheric Chartography carbon monoxide total columns: Statistical evaluation and comparison with chemistry transport model results

This paper presents a detailed statistical analysis of one year (September 2003 to August 2004) of global Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) carbon monoxide (CO) total column retrievals from the Iterative Maximum Likelihood Method (IMLM) algorithm, version 6.3. SCIAMACHY provides the first solar reflectance measurements of CO and is uniquely sensitive down to the boundary layer. SCIAMACHY measurements and chemistry transport model (CTM) results are compared and jointly evaluated. Significant improvements in agreement occur, especially close to biomass burning emission regions, when the new Global Fire Emissions Database version 2 (GFEDv2) is used with the CTM. Globally, the seasonal variation of the model is very similar to that of the SCIAMACHY measurements. For certain locations, significant differences were found, which are likely related to modeling errors due to CO emission uncertainties. Statistical analysis shows that differences between single SCIAMACHY CO total column measurements and corresponding model results are primarily explained by random instrument noise errors. This strongly suggests that the random instrument noise errors are a good diagnostic for the precision of the measurements. The analysis also indicates that noise in single SCIAMACHY CO measurements is generally greater than actual variations in total columns. It is thus required to average SCIAMACHY data over larger temporal and spatial scales to obtain valuable information. Analyses of monthly averaged SCIAMACHY measurements over 3° × 2° geographical regions indicates that they are of sufficient accuracy to reveal valuable information about spatial and temporal variations in CO columns and provide an important tool for model validation. A large spatial and temporal variation in instrument noise errors exists which shows a close correspondence with the spatial distribution of surface albedo and cloud cover. This large spatial variability is important for the use of monthly and annual mean SCIAMACHY CO total column measurements. The smallest instrument noise errors of monthly mean 3° × 2° SCIAMACHY CO total columns measurements are 0.01 × 1018 molecules/cm2 for high surface albedo areas over the Sahara. Errors in SCIAMACHY CO total column retrievals due to errors other than instrument noise, like cloud cover, calibration, retrieval uncertainties and averaging kernels are estimated to be about 0.05–0.1 × 1018 molecules/cm2 in total. The bias found between model and observations is around 0.05–0.1 1018 molecules/cm2 (or about 5%) which also includes model errors. This thus provides a best estimate of the currently achievable measurement accuracy for SCIAMACHY CO monthly mean averages

Light signal perception in Arabidopsis rosettes

Light signals are important signals for future and present competition. We used an architectural model of Arabidopsis development to show that vertical growth of neighboring vegetation is more important than proximity for early detection of competition. Self-signaling is greatly enhanced when own organs grow more vertically, and signal strength differs between signal perception at the apex compared to the leaves