Microsatellites to enhance characterization, conservation and breeding value of Capsicum germplasm

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Distinguishing Increased Adiposity and/or Aerobic Deconditioning as Moderators of Low VO2peak in Obese Men

Peak oxygen uptake (V̇O2peak) in a cardiopulmonary exercise test (CPET) is a strong predictor of morbidity, mortality, and quality of life. V̇O2peak in obese individuals is typically below the lower limit of normal (2 transport and utilization, i.e. aerobic deconditioning; or both. We hypothesized a modified CPET, to measure the fraction of maximum isokinetic power that can be supported by aerobic metabolism, will distinguish between adiposity and deconditioning effects on V̇O2peak. PURPOSE: To compare V̇O2peak and isokinetic neuromuscular performance in obese vs non-obese men. METHODS: A modified CPET with maximal (3 s) isokinetic cycling power at baseline and the limit of ramp-incremental (RI) exercise was used to calculate: A) baseline maximum isokinetic power (Piso); B) tolerance index (TI), % of Piso at V̇O2peak; C) fatigue index (FI), % reduction in Piso per RI-watt at V̇O2peak; D) power reserve (PR), isokinetic power available at V̇O2peak expressed as % RI-wattpeak. The FRIEND nomogram was used to predict V̇O2peak. Data are mean(SD) and were assessed by t-test. RESULTS: Compared to controls (n=24), obese men (n=20) were older (32(5) vs 26(7) yr), had greater BMI (38(6) vs 23(2) kg/m2), but were not different in stature (177(5) vs 180(7) cm) or predicted V̇O2peak (3.49(0.49) vs 3.58(0.36) L/min). Obese men had lower V̇O2peak (2.84(0.42) vs 3.71(0.45) L/min, p2peak (82(15) vs 104(12) %, pIndependent of body mass, obese men had preserved leg strength (normal Piso), but the fraction of maximum isokinetic power supported by aerobic metabolism at RI intolerance was reduced (low TI) with greater fatigability (high FI); each consistent with aerobic deconditioning. A modified CPET with maximal isokinetic power measurements can distinguish the effects of increased adiposity from aerobic deconditioning on V̇O2peak in obese men

The Accuracy of Recalled versus Measured Pre-Pregnancy Weight for the Calculation of Pre-Pregnancy Body Mass Index

Background: In 2009, the Institute of Medicine (IOM) published gestational weight gain (GWG) guidelines with the goal of optimizing maternal and fetal outcomes. GWG recommendations are specific to pre-pregnancy body mass index (BMI): 28-40 lbs for underweight (UW; BMI2), 25-35 lbs for normal weight (NW; 18.5≤BMI/m2), 15-25 lbs for overweight (OW; 25 ≤BMI/m2), and 11-20 lbs for obese (OB; BMI≥30 kg/m2) women. With upwards of 50% of pregnancies in the U.S. unplanned, measured pre-pregnancy weight is often unavailable in clinical and research settings. Evaluating the accuracy of recalled pre-pregnancy weight early in prenatal care is important in order to establish accuracy of pre-pregnancy BMI calculations in order to counsel about GWG accurately. Objective: To examine differences in recalled versus measured pre-pregnancy weight and to examine factors associated with accuracy of recalled weights. Methods: Medical record review of 1,998 randomly selected pregnancies. Eligible women received prenatal care in faculty and resident clinics at UMass Memorial Health Care (UMMHC), delivered between January 2007 and December 2012, and had available both: (1) a measured weight within one year of conception and (2) a pre-pregnancy weight self-reported at first prenatal visit. Data were obtained from the UMMHC paper or electronic prenatal record and the Allscripts EMR. We calculated the difference in weights as recalled pre-pregnancy weight minus most recent measured weight within one year of conception. Subjects were excluded if they received care at a non-faculty or non-resident practice, charts not available after three separate retrieval attempts, both weights of interest not available, or if measured weight occurred at a prenatal visit for a prior pregnancy. For women with more than one pregnancy during the study time frame, one was randomly selected for inclusion in the analytic data set. Results: Of the 1,998 pregnancy charts reviewed, 400 records met eligibility criteria and were included in this analysis. Women were mean age 29.7 (SD: 6.2) years, 69.3% multigravida, 64.4% non-Hispanic white, 65.2% married, and 62.4% had a college or greater education. Based on recalled weight, 3.3% of women were underweight, 46.6% were normal weight, 25.9% overweight, and 24.2% obese. 63% received care in the faculty obstetric clinic. Recorded recalled weights were mean 2.4 (SD: 11.1) pounds lower than measured pre-pregnancy weight. This difference did not differ by age, location of care, pre-pregnancy BMI, marital status, race/ethnicity, primary language, gravity, education, or time between measured weight and conception, in unadjusted and adjusted models. For 88.7% of women, calculating pre-pregnancy BMI based on weight measured up to a year prior to conception or based on recalled pre-pregnancy weight reported at the first prenatal visit resulted in the same classification of pre-pregnancy BMI. Conclusion: Prenatal care providers may calculate pre-pregnancy BMIs using recalled pre-pregnancy weights early in prenatal care and use such calculated BMIs to accurately provide GWG recommendations regardless of demographic variables, gravity, or location of care

Demographic Characteristics Associated with the Presence of Recalled and Measured Prepregnancy Weights

Background: Gestational weight gain within prepregnancy BMI-specific Institute of Medicine (IOM) recommended ranges are associated with good outcomes for both mother and baby. Availability of measured prepregnancy weight, recalled prepregnancy weight or measured weight at first prenatal visit if the former two weights are not available, influences the accuracy of provider recommendations for gestational weight gain. Objective: The purpose of this study is to examine demographic characteristics associated with the presence of recalled prepregnancy weight and measured prepregnancy weight in the prenatal care medical record. Methods: Medical record review of 1,998 randomly selected pregnancies, of which 1,911 met inclusion criteria of delivery between January 2007 and December 2012 and receipt of prenatal care in faculty and resident clinic sites at UMass Memorial Health Care (UMMHC). Subjects\u27 paper prenatal chart and electronic record (AllScripts and QS prenatal EMR) were fully abstracted if available and contained both: (1) a recorded measured weight within one year of conception, and (2) a self-reported prepregnancy weight obtained at first prenatal visit. Additionally, exclusion criteria included those pregnancies with only prenatal weights recorded one year prior to conception for index pregnancy. For women with multiple pregnancies during the study time period, one pregnancy was randomly selected for inclusion in study analyses. Demographic data was abstracted for all available charts regardless of presence or absence of weights of interest. Demographic characteristics considered were age (15-29, 20-24, 25-29, 30-34, 35+ years), prepregnancy BMI calculated based on recalled height and weight (underweight: BMI2, normal weight: 18.5≤ BMI/m2, overweight: 25≤BMI/m2, and obese: 30 kg/m2≤BMI), race/ethnicity (non-Hispanic white vs. other race/ethnicity), marital status (not married vs. married), primary language (non-English vs. English), gravidity (1, 2, 3+), education (high school diploma or less, some college, 4 year college or more) and prenatal care site (faculty vs. resident obstetric clinic). Logistic regressions were performed to calculate crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) and adjusted analyses controlled for demographics. Results: Of the 1911 pregnancies meeting initial inclusion criteria, 1711 (89.5%) had charts available for abstraction; fifty-three subjects had multiple pregnancies of which only one was included in analyses resulting in an analytic sample of 1656 pregnancies. Of these, 511 (30.9%) were missing a recalled prepregnancy weight at first prenatal visit, 711 (42.9%) had the recalled prepregnancy weight but did not have a measured weight; and only 434 (26.2%) had both weights of interest. Overweight women had decreased odds of having a recalled weight compared to women of normal weight (aOR 0.75; 95% CI 0.56-1.00). Additionally, women with ≥4 years of college compared to those with ≤ high school diploma (aOR 0.54; 95% CI 0.40-0.73), and those receiving care in the faculty compared to the resident clinics (aOR 0.48; 95% CI 0.35-0.65) had decreased odds of having a recalled weight available in the chart. Among women with available recalled prepregnancy weight (n=1101), 390 (35.4%) also had a documented measured weight within one year of conception and 711 (64.6%) did not. Women who were not married (aOR 0.54; 95% 0.39-0.76) had decreased odds of having a measured weight, whereas those receiving care in the faculty compared to resident clinics had greater odds (aOR 1.79; 95% CI 1.26-2.53) of having a measured weight within one year of conception available in their charts. Conclusions: Our results suggest that approximately 25% of women have both recalled weight at first prenatal visit and at least one weight measured within one year of conception in their medical records. Prepregnancy BMI, education, and prenatal care site were associated with presence or absence of recalled weight. Similarly, amongst those with recalled weight, martial status and prenatal care in faculty practice where associated with decreased and increased odds respectively of having a measured weight within one year of conception. We can use this information to help practitioners target women for which greater efforts are needed to provide accurate IOM-recommended BMI-specific gestational weight gain guidelines. This may be utilized to discern patterns of health care access in this patient population

Prepregnancy weight, gestational weight gain, and risk of growth affected neonates

BACKGROUND: In 2009, the Institute of Medicine published revised gestational weight gain (GWG) guidelines with changes notable for altered body mass index (BMI) categorization as per World Health Organization criteria and a stated range of recommended gain (11-20 pounds) for obese women. The goal of this study was to evaluate associations between maternal BMI-specific GWG adherence in the context of these new guidelines and risk of small for gestational age (SGA) and large for gestational age (LGA) neonates. METHODS: Subjects were a retrospective cohort of 11,203 live birth singletons delivered at 22-44 weeks at a Massachusetts tertiary care center between April 2006 and March 2010. Primary exposure was GWG adherence (inadequate, appropriate, or excessive) based on BMI-specific recommendations. SGA and LGA were defined as /=90th percentiles of U.S. population growth curves, respectively. The association between GWG adherence and SGA and LGA was examined in polytomous logistic regression models that estimated adjusted odds ratios (AOR) stratified by prepregnancy weight status, controlling for potential confounders. RESULTS: Before pregnancy, 3.8% of women were underweight, 50.9% were normal weight, 24.6% were overweight, and 20.6% were obese. Seventeen percent had inadequate GWG, and 57.2% had excessive GWG. Neonates were 9.6% SGA and 8.7% LGA. Inadequate GWG was associated with increased odds of SGA (AOR 2.51, 95% confidence interval [CI] 1.31-4.78 for underweight and AOR 1.78, 95% CI 1.42-2.24 for normal weight women) and decreased odds of LGA (AOR 0.5, 95% CI 0.47-0.73 for normal weight and AOR 0.56, 95% CI 0.34-0.90 for obese women). Excessive GWG was associated with decreased odds of SGA (AOR 0.59, 95% CI 0.47-0.73 for normal weight and AOR 0.64, 95% CI 0.47-0.89 for overweight women) and increased odds of LGA (AOR 1.76, 95% CI 1.38-2.24 for normal weight, AOR 2.99, 95% CI 1.92-4.65 for overweight, and AOR 1.55, 95% CI 1.10-2.19 for obese women). CONCLUSIONS: Efforts to optimize GWG are essential to reducing the proportion of SGA and LGA neonates, regardless of prepregnancy BMI

A study of elective genome sequencing and pharmacogenetic testing in an unselected population

BACKGROUND: Genome sequencing (GS) of individuals without a medical indication, known as elective GS, is now available at a number of centers around the United States. Here we report the results of elective GS and pharmacogenetic panel testing in 52 individuals at a private genomics clinic in Alabama. METHODS: Individuals seeking elective genomic testing and pharmacogenetic testing were recruited through a private genomics clinic in Huntsville, AL. Individuals underwent clinical genome sequencing with a separate pharmacogenetic testing panel. RESULTS: Six participants (11.5%) had pathogenic or likely pathogenic variants that may explain one or more aspects of their medical history. Ten participants (19%) had variants that altered the risk of disease in the future, including two individuals with clonal hematopoiesis of indeterminate potential. Forty-four participants (85%) were carriers of a recessive or X-linked disorder. All individuals with pharmacogenetic testing had variants that affected current and/or future medications. CONCLUSION: Our study highlights the importance of collecting detailed phenotype information to interpret results in elective GS

Glycosylated superparamagnetic nanoparticle gradients for osteochondral tissue engineering

In developmental biology, gradients of bioactive signals direct the formation of structural transitions in tissue that are key to physiological function. Failure to reproduce these native features in an in vitro setting can severely limit the success of bioengineered tissue constructs. In this report, we introduce a facile and rapid platform that uses magnetic field alignment of glycosylated superparamagnetic iron oxide nanoparticles, pre-loaded with growth factors, to pattern biochemical gradients into a range of biomaterial systems. Gradients of bone morphogenetic protein 2 in agarose hydrogels were used to spatially direct the osteogenesis of human mesenchymal stem cells and generate robust osteochondral tissue constructs exhibiting a clear mineral transition from bone to cartilage. Interestingly, the smooth gradients in growth factor concentration gave rise to biologically-relevant, emergent structural features, including a tidemark transition demarcating mineralized and non-mineralized tissue and an osteochondral interface rich in hypertrophic chondrocytes. This platform technology offers great versatility and provides an exciting new opportunity for overcoming a range of interfacial tissue engineering challenges

Availability of Food Preparation Supplies among Pregnant Women: Preliminary Results from the Decision Making, Eating, and Weight Gain during Pregnancy (DEW) Study

Background: Lack of cooking supplies may be a potential barrier to preparing healthy meals at home. We examined the availability of food preparation supplies among pregnant women in relation to sociodemographic characteristics. Methods: We used preliminary data (N=59) from an ongoing study which enrolled English-speaking women aged 18+ years, pregnant with singleton gestation \u3c36\u3eweeks, pre-pregnancy BMI 18.5-40 kg/m2, and planning to deliver at UMMHC. Women completed the Food Preparation Checklist (FPC) at home. The FPC asks women if 41 specific food preparation items; scores reflect number of items present in the home. Other variables were self-reported. Pearson’s correlation, t-tests, and ANOVAs provided comparisons. We constructed an adjusted linear regression model to explore FPC by sociodemographic characteristics. Results: Women were aged 30.3 (SD=4.1) years, 64.4% were non-Hispanic White, 84.8% were married or living with a partner, and 30.5% reported difficulty paying for basic expenses. Women were enrolled at 22.7 (SD=5.6) weeks gestation; 30.5% were primigravid. Mean pre-pregnancy BMI was 25.0 (SD=4.6) kg/m2; 25.4% were overweight and 17.0% obese. Average FPC score was 32.3 (SD=6.1; range:14-39). FPC scores were higher among Non-Hispanic White women (34.6±3.5 vs. 28.1±7.5, p\u3c0.0001), those with higher education (28.3±7.0 high school/GED or less, 31.0±6.2 some/college degree, vs. 34.7±4.6 some/degree graduate, p\u3c0.01), those married or living with a partner (33.3±5.7 vs. 26.9±5.7, p\u3c0.01), with lower pre-pregnancy BMI (r=-0.38, p\u3c0.01), and who had no difficulty paying for basic expenses (34.0±5.0 vs. 28.4±6.6, p\u3c0.001). In a model that additionally adjusted for pre-pregnancy BMI, non-Hispanic White women had on average 5.7 more food preparation items (95% CI: 3.2, 8.3) and those reporting difficulty paying for basic expenses 3.8 fewer items (95% CI: -6.8, -0.9). Conclusions: Understanding the food preparation supplies available to pregnant women may be useful when designing interventions to improve diet quality and promote healthy weight gain during pregnancy

Evening Snacking in Relation to Self-reported Declines in Sleep Quality during Pregnancy: Preliminary Results from the Decision-Making, Eating, and Weight Gain During Pregnancy (DEW) Study

Background: Poor sleep in non-pregnant adults has been associated with increased evening snacking, which may contribute to weight gain. Sleep disturbances are common during pregnancy. Objective: To examine the association between changes in sleep quality from pre-pregnancy and evening snacking. Methods: In an ongoing prospective cohort study, pregnant women were recruited from UMMHC obstetric practices and the community. Participants are 18+ years, with singleton gestationweeks, pre-pregnancy BMI 18.5-40 kg/m2, English-speaking, and with plans to deliver at UMMHC. Participants were asked “compared to the three months before you became pregnant, how is your sleep quality now?”; we combined responses of “about the same”/“a little better”/“a lot better” versus “a little worse”/“much worse”. Participants completed three 24-hour dietary recalls (2 weekdays, 1 weekend day). Evening snacks were defined as eating occasions after dinner but before bedtime during which food items other than water was consumed. Fisher’s Exact tests and t-tests provided comparisons for evening snacking (yes/no), number of snacks, and energy intake. Results: Women with complete data (n=55) were 58% non-Hispanic White and aged 30.0 (SD:4.3) years; gestational age at study visit was 23.0 (SD:5.9) weeks. Of 866 meals reported, 94 were evening snacks. 71% (n=39) reported that their current sleep quality was worse than before pregnancy. Evening snacks were reported by 90% of women reporting worse sleep and 69% same/better (p=0.1028). While the number of snacks among snackers did not differ by change in sleep quality (M[SD]: 2.2[1.2] versus 1.6[0.8], p=0.2372), energy intake from these snacks was higher among women whose sleep quality had declined (M[SD]: 630[488] versus 309[331] kcal, p=0.0480). Conclusions: Declines in sleep quality during pregnancy may be linked to evening snacking. More research is needed to understand the role of sleep quality, eating behavior, and weight gain during pregnancy

Glycolytic requirement for NK cell cytotoxicity and cytomegalovirus control

NK cell activation has been shown to be metabolically regulated in vitro; however, the role of metabolism during in vivo NK cell responses to infection is unknown. We examined the role of glycolysis in NK cell function during murine cytomegalovirus (MCMV) infection and the ability of IL-15 to prime NK cells during CMV infection. The glucose metabolism inhibitor 2-deoxy-ᴅ-glucose (2DG) impaired both mouse and human NK cell cytotoxicity following priming in vitro. Similarly, MCMV-infected mice treated with 2DG had impaired clearance of NK-specific targets in vivo, which was associated with higher viral burden and susceptibility to infection on the C57BL/6 background. IL-15 priming is known to alter NK cell metabolism and metabolic requirements for activation. Treatment with the IL-15 superagonist ALT-803 rescued mice from otherwise lethal infection in an NK-dependent manner. Consistent with this, treatment of a patient with ALT-803 for recurrent CMV reactivation after hematopoietic cell transplant was associated with clearance of viremia. These studies demonstrate that NK cell-mediated control of viral infection requires glucose metabolism and that IL-15 treatment in vivo can reduce this requirement and may be effective as an antiviral therapy