We analyze the coupling of CP-even and CP-odd Higgs bosons to a photon and a Z boson in extensions of the Standard Model. In particular, we study in detail the effect of charged Higgs bosons in two-Higgs doublet models, and the contribution of SUSY particle loops in the minimal supersymmetric extension of the Standard Model. The Higgs-γZ coupling can be measured in the decay Z → γ+Higgs at e + e − colliders running on the Z resonance, or in the reverse process Higgs → Zγ with the Higgs boson produced at LHC. We show that a measurement of this coupling with a precision at the percent level, which could be the case at future e + e − colliders, would allow to distinguish between the lightest SUSY and standard Higgs bosons in large areas of the parameter space.

Recently, the isolation of new health-related bioactive molecules derived from agro-food industrial by-products by means of environment-friendly extraction processes has become of particular interest. In the present study, a protein by-product from the rice starch industry was hydrolysed with five commercial proteolytic enzymes, avoiding the use of solvents or chemicals. The digestion processes were optimised, and the digestates were separated in fractions with four different molecular weight ranges by using a cross-flow membrane filtration technique. Total hydrolysates and fractions were tested in vitro for a wide range of biological activities. For the first time rice-derived peptides were assayed for anti-tyrosinase, anti-inflammatory, cytotoxicity and irritation capacities. Antioxidant and anti-hypertensive activities were also evaluated. Protamex, Alcalase and Neutrase treatments produced peptide fractions with valuable bioactivities without resulting cytotoxic or irritant. Highest levels of bioactivity were detected in Protamex-derived samples, followed by samples treated with Alcalase. Based on the present results, a future direct exploitation of isolated peptide fractions in the nutraceutical, functional food and cosmetic industrial fields may be foreseen.

Pooling decisions in preparative liquid chromatography for protein purification are usually based on univariate UV absorption measurements that are not able to differentiate between product and co-eluting contaminants. This can result in inconsistent pool purities or yields, if there is a batch-to-batch variability of the feedstock. To overcome this analytical bottleneck, a tool for selective inline quantification of co-eluting model proteins using mid-UV absorption spectra and Partial Least Squares Regression (PLS) was presented in a previous study and applied for real-time pooling decisions. In this paper, a process-data-based method for the PLS model calibration will be introduced that allows the application of the tool towards chromatography steps of real-life processes. The process-data-based calibration method uses recorded inline mid-UV absorption spectra that are correlated with offline fraction analytics to calibrate PLS models. In order to generate average spectra from the inline data, a Visual Basic for Application macro was successfully developed. The process-data-based model calibration was established using a ternary model protein system. Afterwards, it was successfully demonstrated in two case studies that the calibration method is applicable towards real-life separation issues. The calibrated PLS models allowed a successful quantification of the co-eluting species in a cation-exchange-based aggregate and fraction removal during the purification of monoclonal antibodies and of co-eluting serum proteins in an anion-exchange-based purification of Cohn supernatant I. Consequently, the presented process-data-based PLS model calibration in combination with the tool for selective inline quantification has a great potential for the monitoring of future chromatography steps and may contribute to manage batch-to-batch variability by real-time pooling decisions.

No abstract

No abstract