Multivariate curve resolution of time course microarray data

BACKGROUND: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), independent component analysis (ICA), or other methods. Such methods do not generally yield factors with a clear biological interpretation. Moreover, implicit assumptions about the measurement errors often limit the application of these methods to log-transformed data, destroying linear structure in the untransformed expression data. RESULTS: In this work, a method for the linear decomposition of gene expression data by multivariate curve resolution (MCR) is introduced. The MCR method is based on an alternating least-squares (ALS) algorithm implemented with a weighted least squares approach. The new method, MCR-WALS, extracts a small number of basis functions from untransformed microarray data using only non-negativity constraints. Measurement error information can be incorporated into the modeling process and missing data can be imputed. The utility of the method is demonstrated through its application to yeast cell cycle data. CONCLUSION: Profiles extracted by MCR-WALS exhibit a strong correlation with cell cycle-associated genes, but also suggest new insights into the regulation of those genes. The unique features of the MCR-WALS algorithm are its freedom from assumptions about the underlying linear model other than the non-negativity of gene expression, its ability to analyze non-log-transformed data, and its use of measurement error information to obtain a weighted model and accommodate missing measurements

Phosphofructo-2-kinase/Fructose-2,6-bisphosphatase Modulates Oscillations of Pancreatic Islet Metabolism

Pulses of insulin from pancreatic beta-cells help maintain blood glucose in a narrow range, although the source of these pulses is unclear. It has been proposed that a positive feedback circuit exists within the glycolytic pathway, the autocatalytic activation of phosphofructokinase-1 (PFK1), which endows pancreatic beta-cells with the ability to generate oscillations in metabolism. Flux through PFK1 is controlled by the bifunctional enzyme PFK2/FBPase2 (6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase) in two ways: via (1) production/degradation of fructose-2,6-bisphosphate (Fru2,6-BP), a potent allosteric activator of PFK1, as well as (2) direct activation of glucokinase due to a protein-protein interaction. In this study, we used a combination of live-cell imaging and mathematical modeling to examine the effects of inducibly-expressed PFK2/FBPase2 mutants on glucose-induced Ca2+ pulsatility in mouse islets. Irrespective of the ability to bind glucokinase, mutants of PFK2/FBPase2 that increased the kinase:phosphatase ratio reduced the period and amplitude of Ca2+ oscillations. Mutants which reduced the kinase:phosphatase ratio had the opposite effect. These results indicate that the main effect of the bifunctional enzyme on islet pulsatility is due to Fru2,6-BP alteration of the threshold for autocatalytic activation of PFK1 by Fru1,6-BP. Using computational models based on PFK1-generated islet oscillations, we then illustrated how moderate elevation of Fru-2,6-BP can increase the frequency of glycolytic oscillations while reducing their amplitude, with sufficiently high activation resulting in termination of slow oscillations. The concordance we observed between PFK2/FBPase2-induced modulation of islet oscillations and the models of PFK1-driven oscillations furthermore suggests that metabolic oscillations, like those found in yeast and skeletal muscle, are shaped early in glycolysis

Severe Exercise and Exercise Training Exert Opposite Effects on Human Neutrophil Apoptosis via Altering the Redox Status

Neutrophil spontaneous apoptosis, a process crucial for immune regulation, is mainly controlled by alterations in reactive oxygen species (ROS) and mitochondria integrity. Exercise has been proposed to be a physiological way to modulate immunity; while acute severe exercise (ASE) usually impedes immunity, chronic moderate exercise (CME) improves it. This study aimed to investigate whether and how ASE and CME oppositely regulate human neutrophil apoptosis. Thirteen sedentary young males underwent an initial ASE and were subsequently divided into exercise and control groups. The exercise group (n = 8) underwent 2 months of CME followed by 2 months of detraining. Additional ASE paradigms were performed at the end of each month. Neutrophils were isolated from blood specimens drawn at rest and immediately after each ASE for assaying neutrophil spontaneous apoptosis (annexin-V binding on the outer surface) along with redox-related parameters and mitochondria-related parameters. Our results showed that i) the initial ASE immediately increased the oxidative stress (cytosolic ROS and glutathione oxidation), and sequentially accelerated the reduction of mitochondrial membrane potential, the surface binding of annexin-V, and the generation of mitochondrial ROS; ii) CME upregulated glutathione level, retarded spontaneous apoptosis and delayed mitochondria deterioration; iii) most effects of CME were unchanged after detraining; and iv) CME blocked ASE effects and this capability remained intact even after detraining. Furthermore, the ASE effects on neutrophil spontaneous apoptosis were mimicked by adding exogenous H2O2, but not by suppressing mitochondrial membrane potential. In conclusion, while ASE induced an oxidative state and resulted in acceleration of human neutrophil apoptosis, CME delayed neutrophil apoptosis by maintaining a reduced state for long periods of time even after detraining

The antioxidant enzyme peroxiredoxin-2 is depleted in lymphocytes seven days after ultra-endurance exercise

Purpose: Peroxiredoxin-2 (PRDX-2) is an antioxidant and chaperone-like protein critical for cell function. This study examined whether the levels of lymphocyte PRDX-2 are altered over one month following ultra-endurance exercise. Methods: Nine middle-aged men undertook a single-stage, multi-day 233 km (145 mile) ultra-endurance running race. Blood was collected immediately before (PRE), upon completion/retirement (POST), and following the race at DAY 1, DAY 7 and DAY 28. Lymphocyte lysates were examined for PRDX-2 by reducing SDS-PAGE and western blotting. In a sub-group of men who completed the race (n = 4) PRDX-2 oligomeric state (indicative of redox status) was investigated. Results: Ultra-endurance exercise caused significant changes in lymphocyte PRDX-2 (F (4,32) 3.409, p=0.020, ?(2) =0.299): seven-days after the race, PRDX-2 levels in lymphocytes had fallen to 30% of pre-race values (p=0.013) and returned to near-normal levels at DAY 28. Non-reducing gels demonstrated that dimeric PRDX-2 (intracellular reduced PRDX-2 monomers) was increased in 3 of 4 race completers immediately post-race, indicative of an "antioxidant response". Moreover, monomeric PRDX-2 was also increased immediately post-race in 2 of 4 race-completing subjects, indicative of oxidative damage, which was not detectable by DAY 7. Conclusions: Lymphocyte PRDX-2 was decreased below normal levels 7 days after ultra-endurance exercise. Excessive accumulation of reactive oxygen species induced by ultra-endurance exercise may underlie depletion of lymphocyte PRDX-2 by triggering its turnover after oxidation. Low levels of lymphocyte PRDX-2 could influence cell function and might, in part, explain reports of dysregulated immunity following ultra-endurance exercise

E2F1 Regulates Cellular Growth by mTORC1 Signaling

During cell proliferation, growth must occur to maintain homeostatic cell size. Here we show that E2F1 is capable of inducing growth by regulating mTORC1 activity. The activation of cell growth and mTORC1 by E2F1 is dependent on both E2F1's ability to bind DNA and to regulate gene transcription, demonstrating that a gene induction expression program is required in this process. Unlike E2F1, E2F3 is unable to activate mTORC1, suggesting that growth activity could be restricted to individual E2F members. The effect of E2F1 on the activation of mTORC1 does not depend on Akt. Furthermore, over-expression of TSC2 does not interfere with the effect of E2F1, indicating that the E2F1-induced signal pathway can compensate for the inhibitory effect of TSC2 on Rheb. Immunolocalization studies demonstrate that E2F1 induces the translocation of mTORC1 to the late endosome vesicles, in a mechanism dependent of leucine. E2F1 and leucine, or insulin, together affect the activation of S6K stronger than alone suggesting that they are complementary in activating the signal pathway. From these studies, E2F1 emerges as a key protein that integrates cell division and growth, both of which are essential for cell proliferation

Body Adiposity Index Utilization in a Spanish Mediterranean Population: Comparison with the Body Mass Index

BACKGROUND: Body fat content and fat distribution or adiposity are indicators of health risk. Several techniques have been developed and used for assessing and/or determining body fat or adiposity. Recently, the Body Adiposity Index (BAI), which is based on the measurements of hip circumference and height, has been suggested as a new index of adiposity. The aim of the study was to compare BAI and BMI measurements in a Caucasian population from a European Mediterranean area and to assess the usefulness of the BAI in men and women separately. RESEARCH METHODOLOGY/PRINCIPAL FINDINGS: A descriptive cross-sectional study was conducted in a Caucasian population. All participants in the study (1,726 women and 1,474 men, mean age 39.2 years, SD 10.8) were from Mallorca (Spain). Anthropometric data, including percentage of body fat mass obtained by Bioelectrical Impedance Analysis, were determined. Body Mass Index (BMI) and BAI were calculated. BAI and BMI showed a good correlation (r = 0.64, p<0.001). A strong correlation was also found between BAI and the % fat determined using BIA (r = 0.74, p<0.001), which is even stronger than the one between BMI and % fat (r = 0.54, p<0.001). However, the ROC curve analysis showed a higher accuracy for BMI than for the BAI regarding the discriminatory capacity. CONCLUSION: The BAI could be a good tool to measure adiposity due, at least in part, to the advantages over other more complex mechanical or electrical systems. Probably, the most important advantage of BAI over BMI is that weight is not needed. However, in general it seems that the BAI does not overcome the limitations of BMI

Evaluation of receptor and chemical transport models for PM10 source apportionment

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models