Effects of milk heat treatment and solvent composition on physicochemical and selected functional characteristics of milk protein concentrate

peer-reviewedMilk protein concentrate (MPC) powders (∼81% protein) were made from skim milk that was heat treated at 72°C for 15 s (LHMPC) or 85°C for 30 s (MHMPC). The MPC powder was manufactured by ultrafiltration and diafiltration of skim milk at 50°C followed by spray drying. The MPC dispersions (4.02% true protein) were prepared by reconstituting the LHMPC and MHMPC powders in distilled water (LHMPCw and MHMPCw, respectively) or milk permeate (LHMPCp and MHMPCp, respectively). Increasing milk heat treatment increased the level of whey protein denaturation (from ∼5 to 47% of total whey protein) and reduced the concentrations of serum protein, serum calcium, and ionic calcium. These changes were paralleled by impaired rennet-induced coagulability of the MHMPCw and MHMPCp dispersions and a reduction in the pH of maximum heat stability of MHMPCp from pH 6.9 to 6.8. For both the LHMPC and MHMPC dispersions, the use of permeate instead of water enhanced ethanol stability at pH 6.6 to 7.0, impaired rennet gelation, and changed the heat coagulation time and pH profile from type A to type B. Increasing the severity of milk heat treatment during MPC manufacture and the use of permeate instead of water led to significant reductions in the viscosity of stirred yogurt prepared by starter-induced acidification of the MPC dispersions. The current study clearly highlights how the functionality of protein dispersions prepared by reconstitution of high-protein MPC powders may be modulated by the heat treatment of the skim milk during manufacture of the MPC and the composition of the solvent used for reconstitution

Low birth weight male guinea pig offspring display increased visceral adiposity in early adulthood.

Uteroplacental insufficiency (UPI)-induced intrauterine growth restriction (IUGR) predisposes individuals to adult visceral obesity. We postulated that low birth weight (LBW) offspring, from UPI-induced IUGR pregnancies, would display a visceral adipose lipogenic molecular signature involving altered gene expression, phosphorylation status of proteins of the lipid synthesis pathway and microRNA (miR) expression profile, occurring in association with increased visceral adiposity. Normal birth weight (NBW) and LBW (obtained by uterine artery ablation) male guinea pig pups were fed a control diet from weaning to 145 days and sacrificed. Despite being lighter at birth, LBW pups displayed body weights similar to NBW offspring at 145 days. At this age, which represents young adulthood, the relative weights of LBW epididymal white adipose tissue (EWAT) and lipid content were increased; which was consistent with adipocyte hypertrophy in the LBW offspring. Additionally, the mRNA expression of lipid synthesis-related genes including acetyl-CoA carboxylase 1 (ACC1), diglyceride acyltransferase 2 (DGAT2) and peroxisome proliferator-activated receptor gamma 1 (PPARγ1), was increased in LBW EWAT. Further, LBW EWAT displayed decreased phospho-ACC (Ser79) and phospho-PPARγ (Ser273) proteins. Moreover, the mRNA expression of hormone-sensitive lipase (HSL) and fatty acid binding protein 4 (FABP4), both involved in promoting adipose lipid storage, was increased in LBW EWAT. Finally, miR-24 and miR-103-2, miRs related to adipocyte development, were both increased in LBW EWAT. These findings indicate that, following an adverse in utero environment, lipid synthesis-related genes and miR expression, along with phosphorylation status of key regulators of lipid synthesis, appear to be chronically altered and occur in association with increased visceral adiposity in young adult IUGR male offspring

Cross-correlation Weak Lensing of SDSS Galaxy Clusters I: Measurements

This is the first in a series of papers on the weak lensing effect caused by clusters of galaxies in Sloan Digital Sky Survey. The photometrically selected cluster sample, known as MaxBCG, includes ~130,000 objects between redshift 0.1 and 0.3, ranging in size from small groups to massive clusters. We split the clusters into bins of richness and luminosity and stack the surface density contrast to produce mean radial profiles. The mean profiles are detected over a range of scales, from the inner halo (25 kpc/h) well into the surrounding large scale structure (30 Mpc/h), with a significance of 15 to 20 in each bin. The signal over this large range of scales is best interpreted in terms of the cluster-mass cross-correlation function. We pay careful attention to sources of systematic error, correcting for them where possible. The resulting signals are calibrated to the ~10% level, with the dominant remaining uncertainty being the redshift distribution of the background sources. We find that the profiles scale strongly with richness and luminosity. We find the signal within a given richness bin depends upon luminosity, suggesting that luminosity is more closely correlated with mass than galaxy counts. We split the samples by redshift but detect no significant evolution. The profiles are not well described by power laws. In a subsequent series of papers we invert the profiles to three-dimensional mass profiles, show that they are well fit by a halo model description, measure mass-to-light ratios and provide a cosmological interpretation.Comment: Paper I in a series; v2.0 includes ApJ referee's suggestion

The SOAR Gravitational Arc Survey - I: Survey overview and photometric catalogs

We present the first results of the SOAR (Southern Astrophysical Research) Gravitational Arc Survey (SOGRAS). The survey imaged 47 clusters in two redshift intervals centered at $z=0.27$ and $z=0.55$, targeting the richest clusters in each interval. Images were obtained in the $g'$, $r'$ and $i'$ bands using the SOAR Optical Imager (SOI), with a median seeing of 0.83, 0.76 and 0.71 arcsec, respectively, in these filters. Most of the survey clusters are located within the Sloan Digital Sky Survey (SDSS) Stripe 82 region and all of them are in the SDSS footprint. Photometric calibration was therefore performed using SDSS stars located in our SOI fields. We reached for galaxies in all fields the detection limits of $g \sim 23.5$, $r \sim 23$ and $i \sim 22.5$ for a signal-to-noise ratio (S/N) = 3. As a by-product of the image processing, we generated a source catalogue with 19760 entries, the vast majority of which are galaxies, where we list their positions, magnitudes and shape parameters. We compared our galaxy shape measurements to those of local galaxies and concluded that they were not strongly affected by seeing. From the catalogue data, we are able to identify a red sequence of galaxies in most clusters in the lower $z$ range. We found 16 gravitational arc candidates around 8 clusters in our sample. They tend to be bluer than the central galaxies in the lensing cluster. A preliminary analysis indicates that $\sim 10$ of the clusters have arcs around them, with a possible indication of a larger efficiency associated to the high-$z$ systems when compared to the low-$z$ ones. Deeper follow-up images with Gemini strengthen the case for the strong lensing nature of the candidates found in this survey.Comment: 17 pages, 11 figures (most of them multi-panel) MNRAS (2013

Tailoring Capture-Recapture Methods to Estimate Registry-Based Case Counts Based on Error-Prone Diagnostic Signals

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database

Fast non-negative deconvolution for spike train inference from population calcium imaging

Calcium imaging for observing spiking activity from large populations of neurons are quickly gaining popularity. While the raw data are fluorescence movies, the underlying spike trains are of interest. This work presents a fast non-negative deconvolution filter to infer the approximately most likely spike train for each neuron, given the fluorescence observations. This algorithm outperforms optimal linear deconvolution (Wiener filtering) on both simulated and biological data. The performance gains come from restricting the inferred spike trains to be positive (using an interior-point method), unlike the Wiener filter. The algorithm is fast enough that even when imaging over 100 neurons, inference can be performed on the set of all observed traces faster than real-time. Performing optimal spatial filtering on the images further refines the estimates. Importantly, all the parameters required to perform the inference can be estimated using only the fluorescence data, obviating the need to perform joint electrophysiological and imaging calibration experiments.Comment: 22 pages, 10 figure