M13-phage-based star-shaped particles with internal flexibility

We report on the construction and the dynamics of monodisperse star-shaped particles, mimicking, at the mesoscale, star polymers. Such multi-arm star-like particles result from the self-assembly of gold nanoparticles, forming the core, with tip-linked filamentous viruses - M13 bacteriophages - acting as spines in a sea urchin-like structure. By combining fluorescence and dark-field microscopy with dynamic light scattering, we investigate the diffusion of these hybrid spiny particles. We reveal the internal dynamics of the star particles by probing their central metallic core, which exhibits a hindered motion that can be described as a Brownian particle trapped in a harmonic potential. We therefore show that the filamentous viruses and specifically their tip proteins behave as entropic springs, extending the relevance of the study of such hybrid mesoscopic analogs of star polymers to phage biotechnology.Comment: To be published in ACS Nan

Smectic blue phases: layered systems with high intrinsic curvature

We report on a construction for smectic blue phases, which have quasi-long range smectic translational order as well as three dimensional crystalline order. Our proposed structures fill space by adding layers on top of a minimal surface, introducing either curvature or edge defects as necessary. We find that for the right range of material parameters, the favorable saddle-splay energy of these structures can stabilize them against uniform layered structures. We also consider the nature of curvature frustration between mean curvature and saddle-splay.Comment: 15 pages, 11 figure

Skyrmion Lattice in a Chiral Magnet

Skyrmions represent topologically stable field configurations with particle-like properties. We used neutron scattering to observe the spontaneous formation of a two-dimensional lattice of skyrmion lines, a type of magnetic vortices, in the chiral itinerant-electron magnet MnSi. The skyrmion lattice stabilizes at the border between paramagnetism and long-range helimagnetic order perpendicular to a small applied magnetic field regardless of the direction of the magnetic field relative to the atomic lattice. Our study experimentally establishes magnetic materials lacking inversion symmetry as an arena for new forms of crystalline order composed of topologically stable spin states

Nitrogen storage and remobilization by trees : ecophysiological relevance in a changing world

Peer reviewedPreprin

Body and milk traits as indicators of dairy cow energy status in early lactation

The inclusion of feed intake and efficiency traits in dairy cow breeding goals can lead to increased risk of metabolic stress. An easy and inexpensive way to monitor postpartum energy status (ES) of cows is therefore needed. Cows' ES can be estimated by calculating the energy balance from energy intake and output and predicted by indicator traits such as change in body weight (Delta BW), change in body condition score (Delta BCS), milk fat:protein ratio (FPR), or milk fatty acid (FA) composition. In this study, we used blood plasma nonesterified fatty acids (NEFA) concentration as a biomarker for ES. We determined associations between NEFA concentration and ES indicators and evaluated the usefulness of body and milk traits alone, or together, in predicting ES of the cow. Data were collected from 2 research herds during 2013 to 2016 and included 137 Nordic Red dairy cows, all of which had a first lactation and 59 of which also had a second lactation. The data included daily body weight, milk yield, and feed intake and monthly BCS. Plasma samples for NEFA were collected twice in lactation wk 2 and 3 and once in wk 20. Milk samples for analysis of fat, protein, lactose, and FA concentrations were taken on the blood sampling days. Plasma NEFA concentration was higher in lactation wk 2 and 3 than in wk 20 (0.56 +/- 0.30, 0.43 +/- 0.22, and 0.13 +/- 0.06 mmol/L, respectively; all means +/- standard deviation). Among individual indicators, C18:1 cis-9 and the sum of C18:1 in milk had the highest correlations (r = 0.73) with NEFA. Seven multiple linear regression models for NEFA prediction were developed using stepwise selection. Of the models that included milk traits (other than milk FA) as well as body traits, the best fit was achieved by a model with milk yield, FPR, Delta BW, Delta BCS, FPR x Delta BW, and days in milk. The model resulted in a cross-validation coefficient of determination (R(2)cv) of 0.51 and a root mean squared error (RMSE) of 0.196 mmol/L. When only milk FA concentrations were considered in the model, NEFA prediction was more accurate using measurements from evening milk than from morning milk (R(2)cv = 0.61 vs. 0.53). The best model with milk traits contained FPR, C10:0, C14:0, C18:1 cis-9, C18:1 cis-9 x C14:0, and days in milk (R(2)cv = 0.62; RMSE = 0.177 mmol/L). The most advanced model using both milk and body traits gave a slightly better fit than the model with only milk traits (R(2)cv = 0.63; RMSE = 0.176 mmol/L). Our findings indicate that ES of cows in early lactation can be monitored with moderately high accuracy by routine milk measurements.Peer reviewe

Numerical calculations of the phase diagram of cubic blue phases in cholesteric liquid crystals

We study the static properties of cubic blue phases by numerically minimising the three-dimensional, Landau-de Gennes free energy for a cholesteric liquid crystal close to the isotropic-cholesteric phase transition. Thus we are able to refine the powerful but approximate, semi-analytic frameworks that have been used previously. We obtain the equilibrium phase diagram and discuss it in relation to previous results. We find that the value of the chirality above which blue phases appear is shifted by 20% (towards experimentally more accessible regions) with respect to previous estimates. We also find that the region of stability of the O5 structure -- which has not been observed experimentally -- shrinks, while that of BP I (O8-) increases thus giving the correct order of appearance of blue phases at small chirality. We also study the approach to equilibrium starting from the infinite chirality solutions and we find that in some cases the disclination network has to assemble during the equilibration. In these situations disclinations are formed via the merging of isolated aligned defects.Comment: 16 pages, 5 figures. Accepted for publication in Phys. Rev.

Isotropic-nematic phase transition in suspensions of filamentous virus and the neutral polymer Dextran

We present an experimental study of the isotropic-nematic phase transition in an aqueous mixture of charged semi-flexible rods (fd virus) and neutral polymer (Dextran). A complete phase diagram is measured as a function of ionic strength and polymer molecular weight. At high ionic strength we find that adding polymer widens the isotropic-nematic coexistence region with polymers preferentially partitioning into the isotropic phase, while at low ionic strength the added polymer has no effect on the phase transition. The nematic order parameter is determined from birefringence measurements and is found to be independent of polymer concentration (or equivalently the strength of attraction). The experimental results are compared with the existing theoretical predictions for the isotropic-nematic transition in rods with attractive interactions.Comment: 8 Figures. To be published in Phys. Rev. E. For more information see http://www.elsie.brandeis.ed

Development of a subacute ruminal acidosis risk score and its prediction using milk mid-infrared spectra in early-lactation cows

peer reviewe

Immunological effects of altering the concentrate inclusion level in a grass silage-based diet for early lactation Holstein Friesian cows

Concentrate inclusion levels in dairy cow diets are often adjusted so that the milk yield responses remain economic. While changes in concentrate level on performance is well known, their impact on other biological parameters, including immune function, is less well understood. The objective of this study was to evaluate the effect of concentrate inclusion level in a grass silage-based mixed ration on immune function. Following calving 63 (45 multiparous and 18 primiparous) Holstein Friesian dairy cows were allocated to one of three isonitrogenous diets for the first 70 days of lactation. Diets comprised of a mixture of concentrates and grass silage, with concentrates comprising either a low (30%, LC), medium (50%, MC) or high (70%, HC) proportion of the diet on a dry matter (DM) basis. Daily DM intakes, milk yields and BW were recorded, along with weekly body condition score, milk composition and vaginal mucus scores. Blood biochemistry was measured using a chemistry analyzer, neutrophil phagocytic and oxidative burst assessed using commercial kits and flow cytometry, and interferon-γ production evaluated by ELISA after whole blood stimulation. Over the study period cows on HC had a higher total DM intake, milk yield, fat yield, protein yield, fat+protein yield, protein content, mean BW and mean daily energy balance, and a lower BW loss than cows on MC, whose respective values were higher than cows on LC. Cows on HC and MC had a lower serum non-esterified fatty acid concentration than cows on LC (0.37, 0.37 and 0.50 mmol/l, respectively, P=0.005, SED=0.032), while cows on HC had a lower serum β-hydroxybutyrate concentration than cows on MC and LC (0.42, 0.55 and 0.55 mmol/l, respectively, P=0.002, SED=0.03). Concentrate inclusion level had no effect on vaginal mucus scores. At week 3 postpartum, cows on HC tended to have a higher percentage of oxidative burst positive neutrophils than cows on LC (43.2% and 35.3%, respectively, P=0.078, SED=3.11), although at all other times concentrate inclusion level in the total mixed ration had no effect on neutrophil phagocytic or oxidative burst characteristics, or on interferon-γ production by pokeweed mitogen stimulated whole blood culture. This study demonstrates that for high yielding Holstein Friesian cows managed on a grass silage-based diet, concentrate inclusion levels in early lactation affects performance but has no effect on neutrophil or lymphocyte immune parameters

A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra

peer-reviewedLactoferrin (LF) is a glycoprotein naturally present in milk. Its content varies throughout lactation, but also with mastitis; therefore it is a potential additional indicator of udder health beyond somatic cell count. Condequently, there is an interest in quantifying this biomolecule routinely. First prediction equations proposed in the literature to predict the content in milk using milk mid-infrared spectrometry were built using partial least square regression (PLSR) due to the limited size of the data set. Thanks to a large data set, the current study aimed to test 4 different machine learning algorithms using a large data set comprising 6,619 records collected across different herds, breeds, and countries. The first algorithm was a PLSR, as used in past investigations. The second and third algorithms used partial least square (PLS) factors combined with a linear and polynomial support vector regression (PLS + SVR). The fourth algorithm also used PLS factors, but included in an artificial neural network with 1 hidden layer (PLS + ANN). The training and validation sets comprised 5,541 and 836 records, respectively. Even if the calibration prediction performances were the best for PLS + polynomial SVR, their validation prediction performances were the worst. The 3 other algorithms had similar validation performances. Indeed, the validation root mean squared error (RMSE) ranged between 162.17 and 166.75 mg/L of milk. However, the lower standard deviation of cross-validation RMSE and the better normality of the residual distribution observed for PLS + ANN suggest that this modeling was more suitable to predict the LF content in milk from milk mid-infrared spectra (R2v = 0.60 and validation RMSE = 162.17 mg/L of milk). This PLS +ANN model was then applied to almost 6 million spectral records. The predicted LF showed the expected relationships with milk yield, somatic cell score, somatic cell count, and stage of lactation. The model tended to underestimate high LF values (higher than 600 mg/L of milk). However, if the prediction threshold was set to 500 mg/L, 82% of samples from the validation having a content of LF higher than 600 mg/L were detected. Future research should aim to increase the number of those extremely high LF records in the calibration set