Elevated myocardial and lymphocyte GRK2 expression and activity in human heart failure.

The G protein-coupled receptor kinase-2 (GRK2 or beta-ARK1) regulates beta-adrenergic receptors (beta-ARs) in the heart, and its cardiac expression is elevated in human heart failure (HF). We sought to determine whether myocardial levels and activity of GRK2 could be monitored using white blood cells, which have been used to study cardiac beta-ARs. Moreover, we were interested in determining whether GRK2 levels in myocardium and lymphocytes may be associated with beta-AR dysfunction and HF severity.In myocardial biopsies from explanted failing human hearts, GRK activity was inversely correlated with beta-AR-mediated cAMP production (R(2)=-0.215, P<0.05, n=24). Multiple regression analysis confirmed that GRK activity participates with beta-AR density to regulate catecholamine-sensitive cAMP responses. Importantly, there was a direct correlation between myocardial and lymphocytes GRK2 activity (R(2)=0.5686, P<0.05, n=10). Lymphocyte GRK activity was assessed in HF patients with various ejection fractions (EFs) (n=33), and kinase activity was significantly higher in patients with lower EFs and was higher with increasing NYHA class (P<0.001).Myocardial GRK2 expression and activity are mirrored by lymphocyte levels of this kinase, and its elevation in HF is associated with the loss of beta-AR responsiveness and appears to increase with disease severity. Therefore, lymphocytes may provide a surrogate for monitoring cardiac GRK2 in human HF

Natural Occurrence of Ochratoxin A in Blood and Milk Samples from Jennies and Their Foals after Delivery

An assessment of the natural ochratoxin A (OTA) exposure of seven Martina Franca jennies was carried out by analyzing blood and milk samples collected close to and after delivery. A total of 41 and 34 blood samples were collected from jennies and foals, respectively, and analyzed by ELISA. A total of 33 milk samples were collected from jennies and analyzed by the HPLC/FLD method based on IAC clean-up. Furthermore, 53 feed samples were collected from January to September and analyzed by a reference method (AOAC Official Method No. 2000.03) for OTA content. Feed samples showed OTA levels up to 2.7 ng/g with an incidence of 32%, while the OTA incidence rate in jennies' blood samples was 73%, with a median value of 97 ng/L and concentrations ranging fro

External Validation Of Equations To Estimate Resting Energy Expenditure In 14952 Adults With Overweight And Obesity And 1948 Adults With Normal Weight From Italy

Background & aims: We cross-validated 28 equations to estimate resting energy expenditure (REE) in a very large sample of adults with overweight or obesity. Methods: 14952 Caucasian men and women with overweight or obesity and 1498 with normal weight were studied. REE was measured using indirect calorimetry and estimated using two meta-regression equations and 26 other equations. The correct classification fraction (CCF) was defined as the fraction of subjects whose estimated REE was within 10% of measured REE. Results: The highest CCF was 79%, 80%, 72%, 64%, and 63% in subjects with normal weight, overweight, class 1 obesity, class 2 obesity, and class 3 obesity, respectively. The Henry weight and height and Mifflin equations performed equally well with CCFs of 77% vs. 77% for subjects with normal weight, 80% vs. 80% for those with overweight, 72% vs. 72% for those with class 1 obesity, 64% vs. 63% for those with class 2 obesity, and 61% vs. 60% for those with class 3 obesity. The Sabounchi meta-regression equations offered an improvement over the above equations only for class 3 obesity (63%). Conclusions: The accuracy of REE equations decreases with increasing values of body mass index. The Henry weight & height and Mifflin equations are similarly accurate and the Sabounchi equations offer an improvement only in subjects with class 3 obesity

Evaluation of Different Adiposity Indices and Association with Metabolic Syndrome Risk in Obese Children: Is there a Winner?

Body shape index (ABSI) and triponderal mass index (TMI) have been recently associated with cardiovascular risk in adults. A cross-sectional study was conducted to evaluate the relationship between different anthropometric adiposity indexes and metabolic syndrome (MetS) in Caucasian obese children and adolescents. Consecutive obese children aged 657 years have been enrolled. Anthropometric parameters, body composition (by bioelectrical impedance), and systolic and diastolic blood pressure have been measured. Fasting blood samples have been analyzed for lipids, insulin, glucose. A multivariate logistic regression analyses, with body mass index z-score, waist to height ratio, ABSI z-score, TMI, conicity index as predictors for MetS (IDEFICS and IDF criteria according to age) has been performed. Four hundred and three (179 boys and 224 girls) obese children, aged 7\u201320 years, have been evaluated. When we explored the joint contribution of each anthropometric and adiposity index of interest and BMIz on the risk of MetS, we found that the inclusion of ABSIz improved the prediction of MetS compared to BMIz alone. ABSI-BMI can be a useful index for evaluating the relative contribution of central obesity to cardiometabolic risk in clinical management of obese children and adolescents

Predictive fat mass equations for spinal muscular atrophy type I children: Development and internal validation

BACKGROUND: Body composition assessment is paramount for spinal muscular atrophy type I (SMA I) patients, as weight and BMI have proven to be misleading for these patients. Despite its importance, no disease-specific field method is currently available, and the assessment of body composition of SMA I patients requires reference methods available only in specialized settings. OBJECTIVE: To develop predictive fat mass equations for SMA I children based on simple measurements, and compare existing equations to the new disease-specific equations. DESIGN: Demographic, clinical and anthropometric data were examined as potential predictors of the best candidate response variable and non-linear relations were taken into account by transforming continuous predictors with restricted cubic splines. Alternative models were fitted including all the dimensions revealed by cluster analysis of the predictors. The best models were then internally validated, quantifying optimism of the obtained performance measures. The contribution of nusinersen treatment to the unexplained variability of the final models was also tested. RESULTS: A total of 153 SMA I patients were included in the study, as part of a longitudinal observational study in SMA children conducted at the International Center for the Assessment of Nutritional Status (ICANS), University of Milan. The sample equally represented both sexes (56% females) and a wide age range (from 3 months to 12 years, median 1.2 years). Four alternative models performed equally in predicting fat mass fraction (fat mass/body weight). The most convenient was selected and further presented. The selected model uses as predictors sex, age, calf circumference and the sum of triceps, suprailiac and calf skinfold thicknesses. The model showed high predictive ability (optimism corrected coefficient of determination, R2 = 0.72) and internal validation indicated little optimism both in performance measures and model calibration. The addition of nusinersen as a predictor variable did not improve the prediction. The disease-specific equation was more accurate than the available fat mass equations. CONCLUSIONS: The developed prediction model allows the assessment of body composition in SMA I children with simple and widely available measures and with reasonable accuracy

Prediction of Resting Energy Expenditure in Children: May Artificial Neural Networks Improve Our Accuracy?

The inaccuracy of resting energy expenditure (REE) prediction formulae to calculate energy metabolism in children may lead to either under- or overestimated real caloric needs with clinical consequences. The aim of this paper was to apply artificial neural networks algorithms (ANNs) to REE prediction. We enrolled 561 healthy children (2-17 years). Nutritional status was classified according to World Health Organization (WHO) criteria, and 113 were obese. REE was measured using indirect calorimetry and estimated with WHO, Harris-Benedict, Schofield, and Oxford formulae. The ANNs considered specific anthropometric data to model REE. The mean absolute error (mean \ub1 SD) of the prediction was 95.8 \ub1 80.8 and was strongly correlated with REE values (R2 = 0.88). The performance of ANNs was higher in the subgroup of obese children (101 \ub1 91.8) with a lower grade of imprecision (5.4%). ANNs as a novel approach may give valuable information regarding energy requirements and weight management in children

Predictive energy equations for spinal muscular atrophy type I children

BACKGROUND: Knowledge on resting energy expenditure (REE) in spinal muscular atrophy type I (SMAI) is still limited. The lack of a population-specific REE equation has led to poor nutritional support and impairment of nutritional status. OBJECTIVE: To identify the best predictors of measured REE (mREE) among simple bedside parameters, to include these predictors in population-specific equations, and to compare such models with the common predictive equations. METHODS: Demographic, clinical, anthropometric, and treatment variables were examined as potential predictors of mREE by indirect calorimetry (IC) in 122 SMAI children consecutively enrolled in an ongoing longitudinal observational study. Parameters predicting REE were identified, and prespecified linear regression models adjusted for nusinersen treatment (discrete: 0 = no; 1 = yes) were used to develop predictive equations, separately in spontaneously breathing and mechanically ventilated patients. RESULTS: In na\uefve patients, the median (25th, 75th percentile) mREE was 480 (412, 575) compared with 394 (281, 554) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.009).In nusinersen-treated patients, the median (25th, 75th percentile) mREE was 609 (592, 702) compared with 639 (479, 723) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.949).Both in spontaneously breathing and mechanically ventilated patients, the best prediction of REE was obtained from 3 models, all using as predictors: 1 body size related measurement and nusinersen treatment status. Nusinersen treatment was correlated with higher REE both in spontaneously breathing and mechanically ventilated patients. The population-specific equations showed a lower interindividual variability of the bias than the other equation tested, however, they showed a high root mean squared error. CONCLUSIONS: We demonstrated that ventilatory status, nusinersen treatment, demographic, and anthropometric characteristics determine energy requirements in SMAI. Our SMAI-specific equations include variables available in clinical practice and were generally more accurate than previously published equations. At the individual level, however, IC is strongly recommended for assessing energy requirements. Further research is needed to externally validate these predictive equations

Growth patterns in children with spinal muscular atrophy

Background: Spinal muscular atrophy (SMA) is a neuromuscular disorder characterized by muscle atrophy and weakness. SMA type 1 (SMA1) is the most severe form: affected infants are unable to sit unaided; SMA type 2 (SMA2) children can sit, but are not able to walk independently. The Standards of Care has improved quality of life and the increasing availability of disease-modifying treatments is progressively changing the natural history; so, the clinical assessment of nutritional status has become even more crucial. Aims of this multicenter study were to present the growth pattern of treatment-naïve SMA1 and SMA2, and to compare it with the general growth standards. Results: Body Weight (BW, kg) and Supine Length (SL, cm) were collected using a published standardized procedure. SMA-specific growth percentiles curves were developed and compared to the WHO reference data. We recruited 133 SMA1 and 82 SMA2 (48.8% females). Mean ages were 0.6 (0.4–1.6) and 4.1 (2.1–6.7) years, respectively. We present here a set of disease-specific percentiles curves of BW, SL, and BMI-for-age for girls and boys with SMA1 and SMA2. These curves show that BW is significantly lower in SMA than healthy peers, while SL is more variable. BMI is also typically lower in both sexes and at all ages. Conclusions: These data on treatment-naïve patients point toward a better understanding of growth in SMA and could be useful to improve the clinical management and to assess the efficacy of the available and forthcoming therapies not only on motor function, but also on growth

Spinal muscular atrophy, types I and II : what are the differences in&#160;body composition and resting energy expenditure?

Background & aims: Different neuromuscular functional domains in types I and II Spinal Muscular Atrophy (SMAI and SMAII) could lead to differences in body composition (BC) and resting energy expenditure (REE). Their identification could provide the key to defining appropriate strategies in clinical dietary management, but data comparing SMAI and SMAII in terms of BC and REE are not yet available. We measured total and regional fat (FM), lean (LBM), mineral (BMC) masses, body water (total, intra- and extra-cellular, TBW, ICW, ECW) and REE in a sample of SMAI and II children, matched for age and sex, and also adjusting for body size to compare these features of the two SMA phenotypes. Methods: 15 SMAI and 15 SMAII children, (M/F = 9/6 vs 9/6, age 3.6 \ub1 1.9 vs 3.5 \ub1 1.8 years, p = 0.99), confirmed genetically, were measured as follows: Anthropometric measurements [Body Weight (BW), Supine Length (SL), Arm Length (AL), Femur Length (FL), Tibia Length (TL)], Dual x-ray Energy Absorptiometry (DEXA) [total and segmental FM, LBM, FFM, and BMC], Bioelectrical impedance (BIA) [TBW, ICW, ECW] and Indirect Calorimetry (REE, respiratory quotients) were collected by the same trained dietician. BW, SL and Body Mass Index (BMI) Z-scores were calculated according to CDC Growth Charts (2000). Results: SMA children had high percentages of FM and a lower percentage of TBW and ECW compared to the respective reference values for sex and age, whereas the BMC percentages did not differ, even splitting the two phenotypes. SMA I children had a lower BW and BMI-Z score compared to children with SMA II, but similar total and segmental FM. On the contrary, total FFM and LBM were significantly lower in SMAI (7290.0 \ub1 1729.1 g vs 8410.1 \ub1 1508.4 g; 6971.8 \ub1 1637.1 g vs 8041.7 \ub1 1427.7 g, p = 0.039, p = 0.037, respectively), particularly at the trunk level. Arm BMC also resulted significantly lower in SMAI. The measured REE values were similar (684 \ub1 143 kcal/day vs 703 \ub1 122 Kcal/day p = 0.707) whereas REE per FFM unit was higher in SMA I children than in SMA II (95 \ub1 12 kcal/FFMkg vs 84 \ub1 11 kcal/FFMkg p = 0.017). Conclusions: This study has shown that BW and BMI Z-score measurements alone can be misleading in assessing nutritional status, particularly in SMAI. The differences between SMAI and II in total and regional BC are related only to FFM, LBM and BMC, and seem to be more linked to the magnitude of neurofunctional impairment rather than to the nutritional status derangement. SMA I and SMA II children can have different energy requirements in relation to their specific BC and hypermetabolism of FFM. Based on these results, our recommendation is to use direct BC and REE measurements in the nutritional care process until SMA-specific predictive equations become available

Anthropometric measurement standardization for a multicenter nutrition survey in children with spinal muscular atrophy

Spinal muscular atrophy (SMA) is a neuromuscular disease associated with nutritional status derangement and altered body composition. New drugs are changing the natural history of the disease, so now more than ever is important to focus on the correct assessment of nutritional status in SMA. We implemented a standardization process for the anthropometric measurement as part of our ongoing longitudinal study of growth patterns in SMA patients. It features a procedural manual, included in this communication, observers training and reliability assessment, of which we publish the values obtained in our pilot study. The standardization process was able to produce inter-observer reliability values in agreement with the literature and a procedure manual is now available for multicentre studies of nutritional status and body composition in SMA and possibly other pediatric neuromuscular disorders