Use of polyethyleneimine polymer in cell culture as attachment factor and lipofection enhancer

Background  

Several cell lines and primary cultures benefit from the use of positively charged extracellular matrix proteins or polymers that enhance their ability to attach to culture plates. Polyethyleneimine is a positively charged polymer that has gained recent attention as a transfection reagent. A less known use of this cationic polymer as an attachment factor was explored with several cell lines.     

Impact of aging on myocardial metabolic response to dobutamine

In humans, under resting conditions there is an age-related decrease in myocardial fatty acid utilization (MFAU) and oxidation (MFAO) and a relative increase in myocardial glucose utilization (MGU). The impact of age on an individual's myocardial metabolic response to catecholamines is not well defined. Sixteen younger (mean age, 26 +/- 5 yr) and 14 older (mean age, 69 +/- 4 yr) volunteers underwent positron emission tomography to measure myocardial blood flow, myocardial oxygen consumption (M.VO2), MFAU, MFAO, and MGU both under resting conditions and during dobutamine infusion. In response to dobutamine administration, the rate-pressure product, myocardial blood flow, and M.VO2 measurements increased by similar amounts in both groups. No age-related differences were noted in the responses of plasma insulin, glucose, fatty acid, or lactate levels to dobutamine. With dobutamine infusion, MFAU and MFAO increased by a similar extent in both younger and older volunteers (age/dobutamine interactions, P = 0.62 and 0.75, respectively). In contrast, MGU increased with dobutamine administration in the younger (from 149 +/- 71 to 209 +/- 78 nmol.g(-1).min(-1); P = 0.04) but not in the older (from 235 +/- 147 to 176 +/- 84 nmol.g(-1).min(-1); P = 0.23; age/dobutamine interaction, P = 0.03) group. With dobutamine infusion, hearts in both younger and older volunteers responded by increasing their MFAU and MFAO values. Whereas younger hearts also responded with an increase in MGU, older hearts did not. Although the clinical significance of these findings awaits further study, these results may partially explain the impaired contractile reserve and the increased incidence of cardiovascular disease in older individuals.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.     

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains

Background

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers.

Results

The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping.We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population.

Conclusion

The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R package for QTL studies. Pheno2Geno is freely available on CRAN under “GNU GPL v3”. The Pheno2Geno package as well as the tutorial can also be found at: http://pheno2geno.nl.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0475-6) contains supplementary material, which is available to authorized users.     

Rodent cell transformation assays-a brief historical perspective

In vitro cell transformation is a process characterized by a series of progressive distinctive events that often emulate manifestations occurring in vivo and which are associated with neoplasia. Attendant cellular and sub-cellular alterations include, among others: cellular immortality, phenotypic changes, aneuploidy, genetic variability, cellular disarray, anchorage-independent growth, and tumorigenicity in vivo. Early chemically induced neoplastic transformation studies involved the use of normal diploid (Syrian) hamster embryo (SHE) cells and monitored the formation of morphologically altered colonies. Later investigations employed primarily two established mouse cell lines, i.e. the BALB/c 3T3 A31 cell line and the C3H 10T 1/2 cell line, and monitored the induction of morphologically aberrant foci. In either case, such transformed cellular clusters (colonies and foci) could induce tumors upon inoculation in vivo. Some subsequent noteworthy advancements using these systems included pH adjustments, metabolic supplementation, amplification of expression of formerly latent transformed foci, concurrent detection of mutagenesis and transformation, and use of a Bhas 42 cell line (v-Ha-ras transfected BALB/c 3T3 cells) to detect both tumor initiators and promoters. Over time, such transformation assay systems have been found useful in academic, industry and regulatory laboratories, generally for research purposes, but also occasionally as screening tools for potential chemical carcinogens. Nevertheless, to date, use of these assays for decision-making purposes in the regulatory arena remains elusive and will require comprehensive validation to gain universal acceptance.     

Influence of weekend lifestyle patterns on body weight

Objective: To determine whether alterations in diet and/or activity patterns during weekends contribute to weight gain or hinder weight loss. Methods and Procedures: Randomized, controlled trial comparing 1 year of caloric restriction (CR) with 1 year of daily exercise (EX). Subjects included 48 healthy adults (30F, 18M) aged 50–60 years with BMI 23.5–29.9 kg/m². Body weight was measured on 7 consecutive mornings for a total of 165 weeks at baseline and 437 weeks during the 1‐year interventions. Daily weight changes were calculated for weekends (Friday to Monday) and weekdays (Monday to Friday). Daily energy intake was estimated using food diaries; daily physical activity was measured using accelerometers. Both measures were validated against doubly labeled water (DLW). Results: At baseline, participants consistently gained weight on weekend days (+0.06 ± 0.03 kg/day, (mean ± s.e.), P = 0.02), but not on weekdays (?0.02 ± 0.02 kg/day, P = 0.18). This was attributable to higher dietary intake on Saturdays and lower physical activity on Sundays relative to weekdays (both P < 0.05). During the interventions, both CR and EX participants were in negative energy balance on weekdays (P < 0.005). On weekends, however, CR participants stopped losing weight, and EX participants gained weight (+0.08 ± 0.03 kg/day, P < 0.0001) due to higher dietary intakes on weekends. This helps to explain the slower‐than‐expected rate of weight loss during the interventions. Discussion: Alterations in lifestyle behaviors on weekends contribute to weight gain or cessation of weight loss on weekends. These results provide one explanation for the relatively slow rates of weight loss observed in many studies, and the difficulty with maintaining significant weight loss.