Objective Adiposity rebound (AR) or BMI (body mass index) rebound refers to the increase in BMI following the minimum BMI in early childhood. Early AR (before age 5) is predictive of adult obesity. ...To determine how 4 domains – demographics, maternal BMI, food security, and behavioral characteristics – may affect timing of AR. Study design A total of 248 children, ages 2.5-3.5 years, in Latino farmworker families in North Carolina were examined at baseline and every 3 months for 2 years. BMI was plotted serially for each child and the onset of BMI rebound was determined by visual inspection of the graphs. Given the ages of the children, all rebounds were detected before age 5 years and were deemed “early,” whereas other children were classified as “nonrebounders.” Classes were then compared in terms of the 4 domains with the use of bivariate analyses and linear mixed models. Results A total of 131 children demonstrated early rebound, 59 children were nonrebounders, and a further 35 had inconclusive data. Parents of early rebounders were less likely to have documentation permitting legal residence in the US. Mothers of early rebounders were on average 3 BMI units heavier. Sex, household food security, diet quality, caloric intake, and daily activity did not differ between classes. In multivariable analysis, female sex, limited maternal education, increased maternal BMI, and increased caloric intake were significant predictors of early rebound. Conclusion High maternal BMI was the strongest predictor of early BMI rebound, but increased caloric intake also was significant. Limiting excess calories could delay premature AR and lower the risk of future obesity.
In a retrospective review to assess neuroanatomical targets of radiation-induced cognitive decline, dose volume histogram (DVH) analyses of specific brain regions of interest (ROI) are correlated to ...neurocognitive performance in 57 primary brain tumor survivors.
Neurocognitive assessment at baseline included Trail Making Tests A/B, a modified Rey-Osterreith Complex Figure, California or Hopkins Verbal Learning Test, Digit Span, and Controlled Oral Word Association. DVH analysis was performed for multiple neuroanatomical targets considered to be involved in cognition. The %v10 (percent of ROI receiving 10 Gy), %v40, and %v60 were calculated for each ROI. Factor analysis was used to estimate global cognition based on a summary of performance on individual cognitive tests. Stepwise regression was used to determine which dose volume predicted performance on global factors and individual neurocognitive tests for each ROI.
Regions that predicted global cognitive outcomes at doses <60 Gy included the corpus callosum, left frontal white matter, right temporal lobe, bilateral hippocampi, subventricular zone, and cerebellum. Regions of adult neurogenesis primarily predicted cognition at %v40 except for the right hippocampus which predicted at %v10. Regions that did not predict global cognitive outcomes at any dose include total brain volume, frontal pole, anterior cingulate, right frontal white matter, and the right precentral gyrus.
Modeling of radiation-induced cognitive decline using neuroanatomical target theory appears to be feasible. A prospective trial is necessary to validate these data.
This trial investigated whether an intensive lifestyle intervention to produce weight loss and increased fitness would slow loss of mobility among obese patients with type 2 diabetes. Both weight ...loss and improved fitness were associated with a decline in the rate of mobility loss.
The growing prevalence of type 2 diabetes mellitus is an ominous health threat in the United States
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,
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and globally.
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Surveillance data from the Centers for Disease Control and Prevention cite type 2 diabetes as largely a disease of aging,
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and its prevalence may escalate as the population gets older.
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,
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An insidious consequence of aging in persons with type 2 diabetes is physical disability,
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particularly the loss of mobility.
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Reduced mobility puts patients at risk for loss of independence,
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leads to muscle loss (which compromises glucose storage and clearance),
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and compromises the quality of life.
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With increasing age in . . .
Abstract Context Identification of cancer patients with similar symptom profiles may facilitate targeted symptom management. Objectives To identify subgroups of breast cancer survivors based on ...differential experience of symptoms, examine change in subgroup membership over time, and identify relevant characteristics and quality of life (QOL) among subgroups. Methods Secondary analyses of data from 653 breast cancer survivors recruited within eight months of diagnosis who completed questionnaires at five time points. Hidden Markov modeling was used to 1) formulate symptom profiles based on prevalence and severity of eight symptoms commonly associated with breast cancer and 2) estimate probabilities of changing subgroup membership over 18 months of follow-up. Ordinal repeated measures were used to 3) identify patient characteristics related to subgroup membership and 4) evaluate the relationship between symptom subgroup and QOL. Results A seven-subgroup model provided the best fit: 1) low symptom burden, 2) mild fatigue, 3) mild fatigue and mild pain, 4) moderate fatigue and moderate pain, 5) moderate fatigue and moderate psychological, 6) moderate fatigue, mild pain, mild psychological, and 7) high symptom burden. Seventy percent of survivors remained in the same subgroup over time. In multivariable analyses, chemotherapy and greater illness intrusiveness were significantly related to greater symptom burden, while not being married or partnered, no difficulty paying for basics, and greater social support were protective. Higher symptom burden was associated with lower QOL. Survivors who reported psychological symptoms had significantly lower QOL than did survivors with pain symptoms. Conclusion Cancer survivors can be differentiated by their symptom profiles.
Stokes shift, an energy difference between the excitonic absorption and emission, is a property of colloidal quantum dots (CQDs) typically ascribed to splitting between dark and bright excitons. In ...some materials, e.g., PbS, CuInS2, and CdHgTe, a Stokes shift of up to 200 meV is observed, substantially larger than the estimates of dark–bright state splitting or vibronic relaxations. The shift origin remains highly debated because contradictory signatures of both surface and bulk character were reported for the Stokes-shifted electronic state. Here, we show that the energy transfer among CQDs in a polydispersed ensemble in solution suffices to explain the excess Stokes shift. This energy transfer is primarily due to CQD aggregation and can be substantially eliminated by extreme dilution, higher-viscosity solvent, or better-dispersed colloids. Our findings highlight that ensemble polydispersity remains the primary source of the Stokes shift in CQDs in solution, propagating into the Stokes shift in films and the open-circuit voltage deficit in CQD solar cells. Improved synthetic control can bring notable advancements in CQD photovoltaics, and the Stokes shift continues to provide a sensitive and significant metric to monitor ensemble size distribution.
Colloidal quantum dot (CQD) solids are attractive materials for photovoltaic devices due to their low-cost solution-phase processing, high absorption cross sections, and their band gap tunability via ...the quantum size effect. Recent advances in CQD solar cell performance have relied on new surface passivation strategies. Specifically, cadmium cation passivation of surface chalcogen sites in PbS CQDs has been shown to contribute to lowered trap state densities and improved photovoltaic performance. Here we deploy a generalized solution-phase passivation strategy as a means to improving CQD surface management. We connect the effects of the choice of metal cation on solution-phase surface passivation, film-phase trap density of states, minority carrier mobility, and photovoltaic power conversion efficiency. We show that trap passivation and midgap density of states determine photovoltaic device performance and are strongly influenced by the choice of metal cation. Supported by density functional theory simulations, we propose a model for the role of cations, a picture wherein metals offering the shallowest electron affinities and the greatest adaptability in surface bonding configurations eliminate both deep and shallow traps effectively even in submonolayer amounts. This work illustrates the importance of materials choice in designing a flexible passivation strategy for optimum CQD device performance.
The upgrading of CO
/CO feedstocks to higher-value chemicals via energy-efficient electrochemical processes enables carbon utilization and renewable energy storage. Substantial progress has been made ...to improve performance at the cathodic side; whereas less progress has been made on improving anodic electro-oxidation reactions to generate value. Here we report the efficient electroproduction of value-added multi-carbon dimethyl carbonate (DMC) from CO and methanol via oxidative carbonylation. We find that, compared to pure palladium controls, boron-doped palladium (Pd-B) tunes the binding strength of intermediates along this reaction pathway and favors DMC formation. We implement this doping strategy and report the selective electrosynthesis of DMC experimentally. We achieve a DMC Faradaic efficiency of 83 ± 5%, fully a 3x increase in performance compared to the corresponding pure Pd electrocatalyst.
We explore the selective electrocatalytic hydrogenation of lignin monomers to methoxylated chemicals, of particular interest, when powered by renewable electricity. Prior studies, while advancing the ...field rapidly, have so far lacked the needed selectivity: when hydrogenating lignin-derived methoxylated monomers to methoxylated cyclohexanes, the desired methoxy group (−OCH3) has also been reduced. The ternary PtRhAu electrocatalysts developed herein selectively hydrogenate lignin monomers to methoxylated cyclohexanesmolecules with uses in pharmaceutics. Using X-ray absorption spectroscopy and in situ Raman spectroscopy, we find that Rh and Au modulate the electronic structure of Pt and that this modulating steers intermediate energetics on the electrocatalyst surface to facilitate the hydrogenation of lignin monomers and suppress C–OCH3 bond cleavage. As a result, PtRhAu electrocatalysts achieve a record 58% faradaic efficiency (FE) toward 2-methoxycyclohexanol from the lignin monomer guaiacol at 200 mA cm–2, representing a 1.9× advance in FE and a 4× increase in partial current density compared to the highest productivity prior reports. We demonstrate an integrated lignin biorefinery where wood-derived lignin monomers are selectively hydrogenated and funneled to methoxylated 2-methoxy-4-propylcyclohexanol using PtRhAu electrocatalysts. This work offers an opportunity for the sustainable electrocatalytic synthesis of methoxylated pharmaceuticals from renewable biomass.
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