Microbiological and chemical profiles of dairy farm red smear cheese made from pasteurized and un-pasteurized milk

A red-smear soft cheese was produced four times during a year at an organic dairy farm using pasteurized and un-pasteurized milk, respectively, from the same milking. A commercial starter culture was added. The cheeses were characterized microbiologically and chemically in order to study how heat treatment and season affected their characteristics during cheese making and ripening. Large variations between the different lots of cheeses characterized the production. However, the cheeses made from un-pasteurized milk generally had a higher lactic acid bacteria count except in cases, where the pasteurized milk was recontaminated or if acidification failure took place. Delays in acidification caused a more pronounced increase in numbers of E.coli, Enterobacteriaceae and staphylococci, as well as an increase in the plasmin and plasminogen-derived activities. A number of pre-milking and process steps were identified as important for the microbiological contamination and development in the cheeses

Detailed milk fatty acid profiling of the Danish dairy cattle population

Abstract Milk fatty acid (FA) composition can be manipulated through feeding, and especially effects of grazing have been shown to promote a healthier milk FA profile due to increasing contents of beneficial FAs, like conjugated linoleic acid (CLA) and α-linolenic acid (C18:3, the main n3 FA in milk). In addition to diet-based manipulations, selective breeding for specific FA could also be a strategy for altering the FA profile as milk FA display low to moderate heritabilites (0.07-0.34 in Danish Holstein). Since 2015, milk samples from all Danish dairy cows under yield control have been analyzed using mid infrared spectroscopy. The FOSS Application Note 64 has subsequently been used to predict content of seven FA groups (short-chain FA (SCFA), medium-chain FA (MCFA), long-chain FA (LCFA), saturated FA (SFA), mono-unsaturated FA (MUFA), poly-unsaturated FA (PUFA), and trans FA (TFA)) together with four individual FA (myristic acid (C14:0), palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1)). This access to millions of FA profiles in milk enables large-scale in depth analyses of factors affecting FA profile of milk and accurate genetic parameter estimation. Initially, more than 3.5 million milk samples from three Danish dairy breeds (Holstein, Jersey, Red) and crossbred cows have been analyzed from May 2015 to October 2016. The results showed significant (P ≤ 0.05) effects of cow breed. As reported earlier, Jersey cows have a higher de novo synthesis, resulting in higher proportions of SFA, MCFA, SCFA and C16:0 compared to the other breeds. For parity (only checked in Holstein), the proportion of SFA and SCFA increased with increasing lactation number, whereas the proportion of MUFA and C16:0 decreased. PUFA had the lowest proportion in 2nd parity and the highest in 1st parity. Also, significant effects of production system (organic vs. conventional) was found, as organic dairy cows due to legislation have to be on pasture during summer. In months, where cows were fed fresh grass, the proportion of unsaturated FA increased, whereas the proportion of saturated FA decreased. This was seen in both organic, and to a lesser extent, in conventional milk. A healthier FA profile can be obtained by increasing MUFA and PUFA in milk. However, health aspects in relation to SFA are more complex, but there seems to be a general agreement that most SFA have neutral or even slightly positive effects, whereas palmitic acid exerts a negative effect on human health due to its role in increased LDL cholesterol. Thus from a consumers perspective, our results suggest that organic summer milk from 1st parity Holstein or Red cows are preferred during the grass season, whereas conventional milk may have a healthier FA profile during winter. To explore specific seasonal effect in relation to pasture-based diets in more details, milk samples from 160 cows from eight herds are collected to investigate whether bulls with extreme SFA% breeding values are reflected in the FA milk profile from their daughters. The collected milk samples will be analyzed by AN64 MIR, as well as by gas chromatography, to provide additional information e.g. in relation to CLA and C18:3 and the n3/n6 ratio. So far, milk samples have been collected prior to summer grazing and will be collected again in June 2017, where most cows in the experiment will be on pasture. In conclusion, this study has shown that the choice of breed, parity, lactation stage, season, production system and genetics affect the FA composition of milk. Different strategies may therefore be applied to alter the FA profile, but generally, which could be exploited for product differentiation for e.g. new healthier innovative dairy products

The Heavy Photon Search test detector

The Heavy Photon Search (HPS), an experiment to search for a hidden sector photon in fixed target electroproduction, is preparing for installation at the Thomas Jefferson National Accelerator Facility (JLab) in the Fall of 2014. As the first stage of this project, the HPS Test Run apparatus was constructed and operated in 2012 to demonstrate the experiment׳s technical feasibility and to confirm that the trigger rates and occupancies are as expected. This paper describes the HPS Test Run apparatus and readout electronics and its performance. In this setting, a heavy photon can be identified as a narrow peak in the e+e− invariant mass spectrum above the trident background or as a narrow invariant mass peak with a decay vertex displaced from the production target, so charged particle tracking and vertexing are needed for its detection. In the HPS Test Run, charged particles are measured with a compact forward silicon microstrip tracker inside a dipole magnet. Electromagnetic showers are detected in a PbW04 crystal calorimeter situated behind the magnet, and are used to trigger the experiment and identify electrons and positrons. Both detectors are placed close to the beam line and split top-bottom. This arrangement provides sensitivity to low-mass heavy photons, allows clear passage of the unscattered beam, and avoids the spray of degraded electrons coming from the target. The discrimination between prompt and displaced e+e− pairs requires the first layer of silicon sensors be placed only 10 cm downstream of the target. The expected signal is small, and the trident background huge, so the experiment requires very large statistics. Accordingly, the HPS Test Run utilizes high-rate readout and data acquisition electronics and a fast trigger to exploit the essentially 100% duty cycle of the CEBAF accelerator at JLab

LC-IMPACT: a regionalized life cycle damage assessment method

Life cycle impact assessment (LCIA) is a lively field of research, and data and models are continuously improved in terms of impact pathways covered, reliability, and spatial detail. However, many of these advancements are scattered throughout the scientific literature, making it difficult for practitioners to apply the new models. Here, we present the LC-IMPACT method that provides characterization factors at the damage level for 11 impact categories related to three areas of protection (human health, ecosystem quality, natural resources). Human health damage is quantified as disability adjusted life years, damage to ecosystem quality as global species extinction equivalents (based on potentially disappeared fraction of species), and damage to mineral resources as kilogram of extra ore extracted. Seven of the impact categories include spatial differentiation at various levels of spatial scale. The influence of value choices related to the time horizon and the level of scientific evidence of the impacts considered is quantified with four distinct sets of characterization factors. We demonstrate the applicability of the proposed method with an illustrative life cycle assessment example of different fuel options in Europe (petrol or biofuel). Differences between generic and regionalized impacts vary up to two orders of magnitude for some of the selected impact categories, highlighting the importance of spatial detail in LCIA. This article met the requirements for a gold - gold JIE data openness badge described at .Industrial Ecolog

Truncating SRCAP variants outside the Floating-Harbor syndrome locus cause a distinct neurodevelopmental disorder with a specific DNA methylation signature

Truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein (SRCAP) gene cause the neurodevelopmental disorder (NDD) Floating-Harbor syndrome (FLHS), characterized by short stature, speech delay, and facial dysmorphism. Here, we present a cohort of 33 individuals with clinical features distinct from FLHS and truncating (mostly de novo) SRCAP variants either proximal (n = 28) or distal (n = 5) to the FLHS locus. Detailed clinical characterization of the proximal SRCAP individuals identified shared characteristics: developmental delay with or without intellectual disability, behavioral and psychiatric problems, non-specific facial features, musculoskeletal issues, and hypotonia. Because FLHS is known to be associated with a unique set of DNA methylation (DNAm) changes in blood, a DNAm signature, we investigated whether there was a distinct signature associated with our affected individuals. A machine-learning model, based on the FLHS DNAm signature, negatively classified all our tested subjects. Comparing proximal variants with typically developing controls, we identified a DNAm signature distinct from the FLHS signature. Based on the DNAm and clinical data, we refer to the condition as "non-FLHS SRCAP-related NDD.'' All five distal variants classified negatively using the FLHS DNAm model while two classified positively using the proximal model. This suggests divergent pathogenicity of these variants, though clinically the distal group presented with NDD, similar to the proximal SRCAP group. In summary, for SRCAP, there is a clear relationship between variant location, DNAm profile, and clinical phenotype. These results highlight the power of combined epigenetic, molecular, and clinical studies to identify and characterize genotype-epigenotype-phenotype correlations.Genetics of disease, diagnosis and treatmen