Impact of Chronic Sleep Disturbance for People Living With T1 Diabetes.

AIM: The aim was to explore personal experiences and to determine the impact of impaired sleep on well-being and diabetes-related activities/decision making among a cohort of people living with T1D. METHOD: Adults with T1D over the age of 18 and parents/carers of children with T1D were invited to complete an online questionnaire about their quality and quantity of sleep. Questions included impact of sleep on diabetes-related decision making, effective calculation of bolus doses, important aspects of psychosocial functioning, and frequency of waking. Diasend download data were used to objectively determine frequency of nocturnal blood glucose testing in children. RESULTS: A total of 258 parent/carer participants (n = 221 female, 85.6%) and 192 adults with T1D (n = 145, 75.5% female, age range 19 to 89 years) took part. In all, 239 parents/carers and 160 adults believed waking in the night has an impact on their usual daily functioning. Of these, 236 parents/carers and 151 (64%) adults reported the impact as negative. Chronic sleep interruption was associated with detrimental impact on mood, work, family relationships, ability to exercise regularly, ability to eat healthily, and happiness. CONCLUSION: Chronic sleep interruption is highly prevalent in adults with T1D and parents/carers of children with T1D with negative effects on daily functioning and well-being. Appropriate interventions are required to alleviate this burden of T1D, address modifiable risk factors for nocturnal hypoglycemia, and reduce the (perceived) need for nocturnal waking

Influence of C02 enrichment and nitrogen fertilization on tissue chemistry and carbon allocation in longleaf pine seedlings

One-year old, nursery-grown longleaf pine (Pinus palustris Mill.) seedlings were grown in 45-L pots containing a coarse sandy medium and were exposed to two concentrations of atmospheric CO2 (365 or 720 µmol?1) and two levels of nitrogen (N) fertility (40 or 400 kg N ha?1 yr?1) within open top chambers for 20 months. At harvest, needles, stems, coarse roots, and fine roots were separated and weighed. Subsamples of each tissue were frozen in liquid N, lyophilized at ?50 ?C, and ground to pass a 0.2 mm sieve. Tissue samples were analyzed for carbon (C), N, nonpolar extractives (fats, waxes, and oils = FWO), nonstructural carbohydrates (total sugars and starch), and structural carbohydrates (cellulose, lignin, and tannins). Increased dry weights of each tissue were observed under elevated CO2 and with high N; however, main effects of CO2 were significant only on belowground tissues. The high N fertility tended to result in increased partitioning of biomass aboveground, resulting in significantly lower root to shoot ratios. Elevated CO2 did not affect biomass allocation among tissues. Both atmospheric CO2 and N fertility tended to affect concentration of C compounds in belowground, more than aboveground, tissues. Elevated CO2 resulted in lower concentrations of starch, cellulose, and lignin, but increased concentrations of FWO in root tissues. High N fertility increased the concentration of starch, cellulose, and tannins, but resulted in lower concentrations of lignin and FWO in roots. Differences between CO2 concentrations tended to occur only with high N fertility. Atmospheric CO2 did not affect allocation patterns for any compound; however the high N treatment tended to result in a lower percentage of sugars, cellulose, and lignin belowgroun

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models

One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (V-c,V-max) and maximum electron transport rate supporting RuBP regeneration (J(max)), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate V-c,V-max and J(max) based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for V-c,V-max (R-2 = 0.70) and J(max) (R-2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral propertiesThe authors would like to thank the technical help during the experiment of Mr. Robert Icenogle, Barry Dorman (USDA-ARS), Seth Johnston, and Mary Durstock (Crop Physiology Laboratory, Auburn University). The authors also would like to thank to Dr. Jose A. Jimenez Berni for statistical support to analyze the data. This research was supported by the Action CA17134 SENSECO (Optical Synergies for Spatiotemporal Sensing of Scalable Ecophysiological Traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu).This research was also supported by Auburn University and Alabama Agricultural Experimental Station Seed Grant

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models

One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties

Innervation of the receptors present at the various joints of the pereiopods and third maxilliped of Homarus gammarus (L.) and other macruran decapods (crustacea)

This paper gives a full account of the number and structure of the chordotonal organs present at all joints between the coxopodite and dactylopodite of the pereiopods and 3rd maxilliped of the macruran Homarus gammarus L. ( H. vulgaris M. Ed.). Some comparative data is supplied for other macruran decapods. As the form of the receptors depends to some degree upon the structure of the joint we have included details of musculature, planes of movement and degrees of freedom at each of the joints.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47101/1/359_2004_Article_BF00297736.pd

Fine root chemistry and decomposition in model communities of north-temperate tree species show little response to elevated atmospheric CO 2 and varying soil resource availability

Rising atmospheric [CO 2 ] has the potential to alter soil carbon (C) cycling by increasing the content of recalcitrant constituents in plant litter, thereby decreasing rates of decomposition. Because fine root turnover constitutes a large fraction of annual NPP, changes in fine root decomposition are especially important. These responses will likely be affected by soil resource availability and the life history characteristics of the dominant tree species. We evaluated the effects of elevated atmospheric [CO 2 ] and soil resource availability on the production and chemistry, mycorrhizal colonization, and decomposition of fine roots in an early- and late-successional tree species that are economically and ecologically important in north temperate forests. Open-top chambers were used to expose young trembling aspen ( Populus tremuloides ) and sugar maple ( Acer saccharum ) trees to ambient (36 Pa) and elevated (56 Pa) atmospheric CO 2 . Soil resource availability was composed of two treatments that bracketed the range found in the Upper Lake States, USA. After 2.5 years of growth, sugar maple had greater fine root standing crop due to relatively greater allocation to fine roots (30% of total root biomass) relative to aspen (7% total root biomass). Relative to the low soil resources treatment, aspen fine root biomass increased 76% with increased soil resource availability, but only under elevated [CO 2 ]. Sugar maple fine root biomass increased 26% with increased soil resource availability (relative to the low soil resources treatment), and showed little response to elevated [CO 2 ]. Concentrations of N and soluble phenolics, and C/N ratio in roots were similar for the two species, but aspen had slightly higher lignin and lower condensed tannins contents compared to sugar maple. As predicted by source-sink models of carbon allocation, pooled constituents (C/N ratio, soluble phenolics) increased in response to increased relative carbon availability (elevated [CO 2 ]/low soil resource availability), however, biosynthetically distinct compounds (lignin, starch, condensed tannins) did not always respond as predicted. We found that mycorrhizal colonization of fine roots was not strongly affected by atmospheric [CO 2 ] or soil resource availability, as indicated by root ergosterol contents. Overall, absolute changes in root chemical composition in response to increases in C and soil resource availability were small and had no effect on soil fungal biomass or specific rates of fine root decomposition. We conclude that root contributions to soil carbon cycling will mainly be influenced by fine root production and turnover responses to rising atmospheric [CO 2 ], rather than changes in substrate chemistry.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47710/1/442_2005_Article_191.pd

Effects of Atmospheric CO2 Enrichment on Crop Nutrient Dynamics under No-Till Conditions

Increasing atmospheric CO2 concentration could increase crop productivity and alter crop nutrient dynamics. This study was conducted (3 yrs) with two crops ([Glycine max (L.) Merr.] and grain sorghum [Sorghum bicolor (L.) Moench.]) grown under two CO2 levels (ambient and twice ambient) using open top field chambers on a Blanton loamy sand under no-tillage. Macronutrient and micronutrient concentrations and contents were determined for grain, stover, and roots. Although elevated CO2 tended to reduce nutrient concentrations, high CO2 consistently increased nutrient content especially in grain tissue; this response pattern was more notable with macronutrients. The CO2 effect was observed primarily in soybean. The consistent CO2-induced increases in grain macronutrient contents favors reliable predictions of system outputs, however, predictions of crop nutrient inputs (i.e., stover and root contents) to the soil are less robust due to observed variability. Again, this is particularly true in regards to micronutrient dynamics in CO2-enriched cropping systems