Sex differences in energy balance, body composition, and metabolic and endocrine markers during prolonged arduous military training

Energy deficits are common in military training and can result in endocrine and metabolic disturbances. This study provides first investigation of sex differences in energy balance, body composition, and endocrine and metabolic markers in response to prolonged and arduous military training. Men experienced greater energy deficits than women due to higher energy expenditure, which was not compensated for by increased energy intake. These energy deficits were not associated with decreases in fat or lean mass or metabolic or endocrine function

Characterization of the mouse Dazap1 gene encoding an RNA-binding protein that interacts with infertility factors DAZ and DAZL

BACKGROUND: DAZAP1 (DAZ Associated Protein 1) was originally identified by a yeast two-hybrid system through its interaction with a putative male infertility factor, DAZ (Deleted in Azoospermia). In vitro, DAZAP1 interacts with both the Y chromosome-encoded DAZ and an autosome-encoded DAZ-like protein, DAZL. DAZAP1 contains two RNA-binding domains (RBDs) and a proline-rich C-terminal portion, and is expressed most abundantly in the testis. To understand the biological function of DAZAP1 and the significance of its interaction with DAZ and DAZL, we isolated and characterized the mouse Dazap1 gene, and studied its expression and the subcellular localization of its protein product. RESULTS: The human and mouse genes have similar genomic structures and map to syntenic chromosomal regions. The mouse and human DAZAP1 proteins share 98% identity and their sequences are highly similar to the Xenopus orthologue Prrp, especially in the RBDs. Dazap1 is expressed throughout testis development. Western blot detects a single 45 kD DAZAP1 protein that is most abundant in the testis. Although a majority of DAZAP1 is present in the cytoplasmic fraction, they are not associated with polyribosomes. CONCLUSIONS: DAZAP1 is evolutionarily highly conserved. Its predominant expression in testes suggests a role in spermatogenesis. Its subcellular localization indicates that it is not directly involved in mRNA translation

Evaluation of clustering algorithms for gene expression data

BACKGROUND: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped together according to their expression profiles using one of numerous clustering algorithms that exist in the statistics and machine learning literature. A closely related problem is that of selecting a clustering algorithm that is "optimal" in some sense from a rather impressive list of clustering algorithms that currently exist. RESULTS: In this paper, we propose two validation measures each with two parts: one measuring the statistical consistency (stability) of the clusters produced and the other representing their biological functional congruence. Smaller values of these indices indicate better performance for a clustering algorithm. We illustrate this approach using two case studies with publicly available gene expression data sets: one involving a SAGE data of breast cancer patients and the other involving a time course cDNA microarray data on yeast. Six well known clustering algorithms UPGMA, K-Means, Diana, Fanny, Model-Based and SOM were evaluated. CONCLUSION: No single clustering algorithm may be best suited for clustering genes into functional groups via expression profiles for all data sets. The validation measures introduced in this paper can aid in the selection of an optimal algorithm, for a given data set, from a collection of available clustering algorithms

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60–80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

Does green tea affect postprandial glucose, insulin and satiety in healthy subjects: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Results of epidemiological studies have suggested that consumption of green tea could lower the risk of type 2 diabetes. Intervention studies show that green tea may decrease blood glucose levels, and also increase satiety. This study was conducted to examine the postprandial effects of green tea on glucose levels, glycemic index, insulin levels and satiety in healthy individuals after the consumption of a meal including green tea.</p> <p>Methods</p> <p>The study was conducted on 14 healthy volunteers, with a crossover design. Participants were randomized to either 300 ml of green tea or water. This was consumed together with a breakfast consisting of white bread and sliced turkey. Blood samples were drawn at 0, 15, 30, 45, 60, 90, and 120 minutes. Participants completed several different satiety score scales at the same times.</p> <p>Results</p> <p>Plasma glucose levels were higher 120 min after ingestion of the meal with green tea than after the ingestion of the meal with water. No significant differences were found in serum insulin levels, or the area under the curve for glucose or insulin. Subjects reported significantly higher satiety, having a less strong desire to eat their favorite food and finding it less pleasant to eat another mouthful of the same food after drinking green tea compared to water.</p> <p>Conclusions</p> <p>Green tea showed no glucose or insulin-lowering effect. However, increased satiety and fullness were reported by the participants after the consumption of green tea.</p> <p>Trial registration number</p> <p>NCT01086189</p

New Zealand Blackcurrant Extract Improves Cycling Performance and Fat Oxidation in Cyclists

PURPOSE: Blackcurrant intake increases peripheral blood flow in humans, potentially by anthocyanin-induced vasodilation which may affect substrate delivery and exercise performance. We examined the effects of New Zealand blackcurrant (NZBC) extract on substrate oxidation, cycling time-trial performance and plasma lactate responses following the time-trial in trained cyclists. METHODS: Using a randomized, double-blind, crossover design, fourteen healthy men (age: 38 ± 13 years, height: 178 ± 4 cm, body mass: 77 ± 9 kg, V?O2max: 53 ± 6 ml·kg-1·min-1, mean ± SD) ingested NZBC extract (300 mg?day-1 CurraNZ™ containing 105 mg anthocyanin) or placebo (PL, 300 mg microcrystalline cellulose M102) for 7-days (washout 14-days). On day 7, participants performed 30 min of cycling (3x10 min at 45, 55 and 65% V?O2max), followed by a 16.1 km time-trial with lactate sampling during a 20-minute passive recovery. RESULTS: NZBC extract increased fat oxidation at 65% V?O2max by 27% (P < 0.05) and improved 16.1 km time-trial performance by 2.4% (NZBC: 1678 ± 108 s, PL: 1722 ± 131 s, P < 0.05). Plasma lactate was higher with NZBC extract immediately following the time-trial (NZBC: 7.06 ± 1.73 mmol?L-1, PL: 5.92 ± 1.58 mmol?L-1 P < 0.01). CONCLUSIONS: Seven days intake of New Zealand blackcurrant extract improves 16.1 km cycling time-trial performance and increases fat oxidation during moderate intensity cycling

Impact of the frequency of online verifications on the patient set-up accuracy and set-up margins

<p>Abstract</p> <p>Purpose</p> <p>The purpose of the study was to evaluate the patient set-up error of different anatomical sites, to estimate the effect of different frequencies of online verifications on the patient set-up accuracy, and to calculate margins to accommodate for the patient set-up error (ICRU set-up margin, SM).</p> <p>Methods and materials</p> <p>Alignment data of 148 patients treated with inversed planned intensity modulated radiotherapy (IMRT) or three-dimensional conformal radiotherapy (3D-CRT) of the head and neck (n = 31), chest (n = 72), abdomen (n = 15), and pelvis (n = 30) were evaluated. The patient set-up accuracy was assessed using orthogonal megavoltage electronic portal images of 2328 fractions of 173 planning target volumes (PTV). In 25 patients, two PTVs were analyzed where the PTVs were located in different anatomical sites and treated in two different radiotherapy courses. The patient set-up error and the corresponding SM were retrospectively determined assuming no online verification, online verification once a week and online verification every other day.</p> <p>Results</p> <p>The SM could be effectively reduced with increasing frequency of online verifications. However, a significant frequency of relevant set-up errors remained even after online verification every other day. For example, residual set-up errors larger than 5 mm were observed on average in 18% to 27% of all fractions of patients treated in the chest, abdomen and pelvis, and in 10% of fractions of patients treated in the head and neck after online verification every other day.</p> <p>Conclusion</p> <p>In patients where high set-up accuracy is desired, daily online verification is highly recommended.</p

Reduced expression of lamin A/C correlates with poor histological differentiation and prognosis in primary gastric carcinoma

<p>Abstract</p> <p>Background</p> <p>Lamin A/C is very important in DNA replication, RNA dependent transcription and nuclear stabilization. Reduced or absent lamin A/C expression has been found to be a common feature of a variety of different cancers. To investigate the role of lamin A/C in gastric carcinoma (GC) pathogenesis, we analyzed the correlations between the lamin A/C expression level and clinicopathological factors and studied its prognostic role in primary GC.</p> <p>Methods</p> <p>The expression of lamin A/C at mRNA level was detected by the reverse transcription-polymerase chain reaction (RT-PCR) and real time RT-PCR, and western blot was used to examine the protein expression. Lamin A/C expression and its prognostic significance were investigated by performing immunohistochemical analysis on a total of 126 GC clinical tissue samples.</p> <p>Results</p> <p>Both lamin A/C mRNA and protein expression were downregulated in the majority of tumours compared with corresponding normal gastric tissues (<it>p </it>= 0.011 and <it>p </it>= 0.036, respectively). Real time RT-PCR further validated that downregulation of lamin A/C is associated with poor histological differentiation (r = 0.438, <it>p </it>= 0.025). The immunohistochemical staining showed an evident decrease of lamin A/C expression in 55.6% (70/126) GC cases. Importantly, the negative lamin A/C expression correlated strongly with histological classification (r = 0.361, <it>p </it>= 0.034). Survival analysis revealed that patients with lamin A/C downregulation have a poorer prognosis (<it>p </it>= 0.034). In addition, lamin A/C expression was found to be an independent prognostic factor by multivariate analysis.</p> <p>Conclusion</p> <p>Data of this study suggest that lamin A/C is involved in the pathogenesis of GC, and it may serve as a valuable biomarker for assessing the prognosis for primary GC.</p