Comparative Analysis of Body Composition and Reference Values of Visceral Adipose Tissues in Various American Collegiate Sports

Background: Currently, body composition (BC) assessment is usually performed to diagnose disease states and accurately estimate certain types of tissues. In athletes, performing BC assessments helps gauge training and nutrition programs to see if they are adequately meeting the athlete’s needs to improve performance. Annual Dual Energy X-ray Absorptiometry (DXA) scans before the start of an athlete’s season can help identify an athlete’s preparedness or health before training begins. Objective: To assess the preseason BC of four collegiate sports: Men’s basketball, men’s baseball, women’s volleyball, and women’s soccer, for Fat Mass (FM), bone mineral density BMD), Fat-Free Mass (FFM), and visceral adipose tissue (VAT). Methods: DXA (Lunar iDXA, GE Healthcare) scans were performed before the start of pre-season training for Men’s Basketball, Baseball, Women’s Volleyball, and Women’s Soccer. End-season DXA scans were performed after the end of the regular season for Men’s Basketball and Baseball athletes. Visceral Adipose Tissue was measured using CoreScan software provided by GE and Fat Mass Index (FMI) and Fat-Free Mass Index (FFMI) were calculated from scanned values. Results: Between the various sports, there were several significant differences that were apparent. Height and percentage of Fat Mass (%BF) were significantly different between all sports except Women’s Volleyball and Women’s Soccer. BMI, VAT, and FFMI were significantly different between males and females. Changes over a season showed increased BMD in Men’s Basketball (2.79 to 2.99 Z-score, pre to end of season scan respectively; p \u3c 0.001). No other observations were noticed to be significant. Conclusions: Sports-specific training and sex have large influences on the body composition of athletes. FMI and FFMI are two indices that may have a stronger indication to health than parameters considered for those who are sedentary and non-active. Female athletes have little to no amounts of VAT and this warrants further investigation

Deep RNA-Seq profile reveals biodiversity, plant-microbe interactions and a large family of NBS-LRR resistance genes in walnut (Juglans regia) tissues.

Deep RNA-Seq profiling, a revolutionary method used for quantifying transcriptional levels, often includes non-specific transcripts from other co-existing organisms in spite of stringent protocols. Using the recently published walnut genome sequence as a filter, we present a broad analysis of the RNA-Seq derived transcriptome profiles obtained from twenty different tissues to extract the biodiversity and possible plant-microbe interactions in the walnut ecosystem in California. Since the residual nature of the transcripts being analyzed does not provide sufficient information to identify the exact strain, inferences made are constrained to the genus level. The presence of the pathogenic oomycete Phytophthora was detected in the root through the presence of a glyceraldehyde-3-phosphate dehydrogenase. Cryptococcus, the causal agent of cryptococcosis, was found in the catkins and vegetative buds, corroborating previous work indicating that the plant surface supported the sexual cycle of this human pathogen. The RNA-Seq profile revealed several species of the endophytic nitrogen fixing Actinobacteria. Another bacterial species implicated in aerobic biodegradation of methyl tert-butyl ether (Methylibium petroleiphilum) is also found in the root. RNA encoding proteins from the pea aphid were found in the leaves and vegetative buds, while a serine protease from mosquito with significant homology to a female reproductive tract protease from Drosophila mojavensis in the vegetative bud suggests egg-laying activities. The comprehensive analysis of RNA-seq data present also unraveled detailed, tissue-specific information of ~400 transcripts encoded by the largest family of resistance (R) genes (NBS-LRR), which possibly rationalizes the resistance of the specific walnut plant to the pathogens detected. Thus, we elucidate the biodiversity and possible plant-microbe interactions in several walnut (Juglans regia) tissues in California using deep RNA-Seq profiling

Sugar metabolism and accumulation in the fruit of transgenic apple trees with decreased sorbitol synthesis.

Both sorbitol and sucrose are synthesized in source leaves and transported to fruit for supporting fruit growth in tree fruit species of the Rosaceae family. In apple (Malus domestica), antisense suppression of aldose-6-phosphate reductase, the key enzyme for sorbitol synthesis, significantly decreased the sorbitol concentration but increased the sucrose concentration in leaves, leading to a lower sorbitol but a higher sucrose supply to fruit in these plants. In response to this altered carbon supply, the transgenic fruit had lower concentration of sorbitol and much higher concentration of glucose but similar levels of fructose, sucrose, and starch throughout fruit development relative to the untransformed control. Activities of sorbitol dehydrogenase, fructokinase, and sucrose phosphate synthase were lower, whereas activities of neutral invertase, sucrose synthase, and hexokinase were higher in the transgenic fruit during fruit development. Transcript levels of MdSOT1, MdSDHs, MdFK2, and MdSPS3/6 were downregulated, whereas transcript levels of MdSUC1/4, MdSUSY1-3, MdNIV1/3, MdHKs, and MdTMT1 were upregulated in the transgenic fruit. These findings suggest that the Sucrose cycle and the sugar transport system are very effective in maintaining the level of fructose and provide insights into the roles of sorbitol and sucrose in regulating sugar metabolism and accumulation in sorbitol-synthesizing species

Enhancement of Recombinant Protein Production in Transgenic Nicotiana benthamiana Plant Cell Suspension Cultures with Co-Cultivation of Agrobacterium Containing Silencing Suppressors.

We have previously demonstrated that the inducible plant viral vector (CMViva) in transgenic plant cell cultures can significantly improve the productivity of extracellular functional recombinant human alpha-1-antiryspin (rAAT) compared with either a common plant constitutive promoter (Cauliflower mosaic virus (CaMV) 35S) or a chemically inducible promoter (estrogen receptor-based XVE) system. For a transgenic plant host system, however, viral or transgene-induced post-transcriptional gene silencing (PTGS) has been identified as a host response mechanism that may dramatically reduce the expression of a foreign gene. Previous studies have suggested that viral gene silencing suppressors encoded by a virus can block or interfere with the pathways of transgene-induced PTGS in plant cells. In this study, the capability of nine different viral gene silencing suppressors were evaluated for improving the production of rAAT protein in transgenic plant cell cultures (CMViva, XVE or 35S system) using an Agrobacterium-mediated transient expression co-cultivation process in which transgenic plant cells and recombinant Agrobacterium carrying the viral gene silencing suppressor were grown together in suspension cultures. Through the co-cultivation process, the impacts of gene silencing suppressors on the rAAT production were elucidated, and promising gene silencing suppressors were identified. Furthermore, the combinations of gene silencing suppressors were optimized using design of experiments methodology. The results have shown that in transgenic CMViva cell cultures, the functional rAAT as a percentage of total soluble protein is increased 5.7 fold with the expression of P19, and 17.2 fold with the co-expression of CP, P19 and P24

The electrostatic profile of consecutive Cβ atoms applied to protein structure quality assessment.

The structure of a protein provides insight into its physiological interactions with other components of the cellular soup. Methods that predict putative structures from sequences typically yield multiple, closely-ranked possibilities. A critical component in the process is the model quality assessing program (MQAP), which selects the best candidate from this pool of structures. Here, we present a novel MQAP based on the physical properties of sidechain atoms. We propose a method for assessing the quality of protein structures based on the electrostatic potential difference (EPD) of Cβ atoms in consecutive residues. We demonstrate that the EPDs of Cβ atoms on consecutive residues provide unique signatures of the amino acid types. The EPD of Cβ atoms are learnt from a set of 1000 non-homologous protein structures with a resolution cuto of 1.6 Å obtained from the PISCES database. Based on the Boltzmann hypothesis that lower energy conformations are proportionately sampled more, and on Annsen's thermodynamic hypothesis that the native structure of a protein is the minimum free energy state, we hypothesize that the deviation of observed EPD values from the mean values obtained in the learning phase is minimized in the native structure. We achieved an average specificity of 0.91, 0.94 and 0.93 on hg_structal, 4state_reduced and ig_structal decoy sets, respectively, taken from the Decoys `R' Us database. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134

Genetic mechanisms of the devious intruder Candidatus Liberibacter in citrus

HLB symptom progression may result from three types of dysfunction occurring in Ca.L.-infected citrus: (1) a carbohydrate disorder linked to disruption of the source-sink relationship, (2) perturbation of hormonal crosstalk involved in plant immune responses (JA-SA signaling crosstalk), and (3) changes in the rapid activation of detoxifying pathways (particularly GSTs). The development of innovative short- or long-term biotechnological tools that allow beneficial modulation of these three pathways will help increase Citrus tolerance to this devastating disease

Synthetic sequence generator for recommender systems - memory biased random walk on sequence multilayer network

Personalized recommender systems rely on each user's personal usage data in the system, in order to assist in decision making. However, privacy policies protecting users' rights prevent these highly personal data from being publicly available to a wider researcher audience. In this work, we propose a memory biased random walk model on multilayer sequence network, as a generator of synthetic sequential data for recommender systems. We demonstrate the applicability of the synthetic data in training recommender system models for cases when privacy policies restrict clickstream publishing.Comment: The new updated version of the pape