Active biopolymer coating based on sodium caseinate: Physical characterization and antioxidant activity

The objective of this work was to investigate the effect of sodium caseinate concentration on physical-chemical properties of coating solutions and films obtained by casting as a starting point for the development of an active coating for minimally processed fruits or vegetables. Sodium caseinate solutions at different concentrations (4%, 8%, 10%, 12%, 14%) were used as a coating system. The coating viscosity and desorption kinetic were characterized. Minimally processed fennels were coated by dipping and the liquid and dry coating thickness were estimated by assessing the amount of coating on fennel during draining as a function of solution properties (concentration and viscosity). Film obtained by casting were also characterized in terms of equilibrium moisture content, color, and water vapor permeability. The potential of using the sodium caseinate solution to obtain active coating was investigated by adding gallic acid or rosemary oil to sodium caseinate solution at 4%. The antioxidant capacity of the coating was evaluated by DPPH test. Results show that sodium caseinate solutions follow a Newtonian behavior in the range of concentration investigated and the viscosity increased as solids concentration increased, following a power law. The drying rate was in the range 0.0063-0.00107 mgH2O•mgsolids-1•min-1•m-2 as a function of sodium caseinate concentration. The average liquid and dry coating thickness on fennels were in the range 20-70 and 0.7-6.4 μm, respectively. The water vapor permeability slightly decreased as the solid concentration increased. Active coating showed good antioxidant properties

Polymerizable deep eutectic solvents: Convenient reactive dispersion media for the preparation of novel multi-walled carbon nanotubes-based functional materials

A new straightforward and green approach for the covalent functionalization of multi-walled carbon nanotubes (MWCNTs) was developed. This carbon nanostructure was efficiently derivatized by polymerizing proper deep eutectic monomers (DEM), a subclass of deep eutectic solvents (DES), based on a series of mono- and bis-vinyl imidazolium salts endowed with different functional groups (–OH, –NH2, –NH3+Br–) in the side chain or in the spacer. Herein, DEM systems played a triple role as convenient dispersion media for MWCNTs, efficient reactive systems, and also as structure-directing agents for the radical-initiated polymerization process onto the surface of MWCNTs. In addition, the new methodology allowed obtaining highly functionalized hybrid materials, as shown by thermogravimetric analyses, in short reaction times (<1h). Transmission electron microscopy (TEM) revealed that the polymeric network orderly develops along the surface of the nanotubes, which act as templating agent for both mono- and bis-vinyl imidazolium salts, despite the random nature of the polymerization process for the latter species. This new functionalization strategy of MWCNTs stands out for its environmentally friendly and time-saving nature leading to the formation of materials with significant potential for applications in a plethora of research fields. As a proof of their possible application, we tested these new hybrid materials as recoverable and recyclable catalysts for the conversion of CO2 into cyclic carbonates under solvent-free conditions, showing good catalytic performances, even in the absence of additional co-catalysts

Towards a reliable calculation of relic radiation from primordial gravitational waves

Inflationary gravitational waves, behaving as additional radiation in the Early Universe, can increase the effective number of relativistic species (Neff) by a further correction that depends on the integrated energy-density in gravitational waves over all scales. This effect is typically used to constrain (blue-tilted) models of inflation in light of the bounds resulting from the big bang nucleosynthesis. In this paper, we recompute this contribution, discussing some caveats of the state-of-the-art analyses. Through a parametric investigation, we first demonstrate that the calculation is dominated by the ultraviolet frequencies of the integral and therefore by the behaviour of the tensor spectrum on scales corresponding to modes that cross the horizon very close to the end of inflation, when the slow-roll dynamics breaks down and the production of gravitational waves becomes strongly model dependent. Motivated by these results, we realize a theoretical Monte Carlo and, working within the framework of the Effective Field Theory of inflation, we investigate the observable predictions of a very broad class of models. For each model, we solve a system of coupled differential equations whose solution completely specifies the evolution of the spectrum up to the end of inflation. We prove the calculation of ΔNGWeff to be remarkably model dependent and therefore conclude that accurate analyses are needed to infer reliable information on the inflationary Universe

Exploring the growth index γL: Insights from different CMB dataset combinations and approaches

In this study we investigate the growth index γL, which characterizes the growth of linear matter perturbations, while analysing different cosmological datasets. We compare the approaches implemented by two different patches of the cosmological solver CAMB: MGCAMB and CAMB_GAMMAPRIME_GROWTH. In our analysis we uncover a deviation of the growth index from its expected ΛCDM value of 0.55 when utilizing the Planck dataset, both in the MGCAMB case and in the CAMB_GAMMAPRIME_GROWTH case, but in opposite directions. This deviation is accompanied by a change in the direction of correlations with derived cosmological parameters. However, the incorporation of cosmic microwave background lensing data helps reconcile γL with its Λ-cold dark matter value in both cases. Conversely, the alternative ground-based telescopes Atacama Cosmology Telescope and South Pole Telescope consistently yield growth index values in agreement with γL ¼ 0.55. We conclude that the presence of the Alens problem in the Planck dataset contributes to the observed deviations, underscoring the importance of additional datasets in resolving these discrepancies

Effects of SARS-CoV-2 on Pulmonary Function and Muscle Strength Testing in Military Subjects According to the Period of Infection: Cross-Sectional Study

Background: Pulmonary function can be impaired as a long-term consequence of SARS-CoV-2 infection. The aim of this study was to evaluate the effect of SARS-CoV-2 infection on pulmonary function, exercise tolerance, and muscle strength in healthy middle-aged military outpatients according during the period of infection. Methods: A cross-sectional study was carried out from March 2020 to November 2022 at the Military Hospital "Celio" (Rome, Italy). If someone had a diagnosis of SARS-CoV-2 infection certified by molecular nasal swab and if they performed pulmonary function tests, diffusion of carbon monoxide (DL'co), a six Minute Walk Test (6MWT), a Handgrip (HG) Test, and a One Minute Sit to Stand Test (1 ' STST). The included subjects were divided into two groups, A and B, according to the period of infection: A) from March 2020 to August 2021 and B) from September 2021 to October 2022. Results: One hundred fifty-three subjects were included in the study: 79 in Group A and 74 in Group B. Although the values were within the normal range, Group A had smaller FVC, FEV1, and DL'co compared to Group B. Group A also walked a shorter distance at the 6MWT and performed fewer repetitions in the 1 ' STS test compared to Group B. In both groups, the DL'co (%predicted) correlated with the 6MWT distance (R-2 = 0.107, p < 0.001), the number of repetitions of the 1'STST (R-2 = 0.086, p = 0.001), and the strength at the HG test (R-2 = 0.08, p < 0.001). Conclusions: This study shows that the SARS-CoV-2 infection in healthy middle-aged military outpatients was more severe in the first waves than in the later ones and that, in healthy and physically fit individuals, even a marginal reduction in resting respiratory test values can have a major impact on exercise tolerance and muscles strength. Moreover, it shows that those infected more recently had symptoms related to the upper respiratory tract infection compared to those of the first waves

Strain gauge properties of Pd+-ion-implanted polymer:

Pd+ ions (90 keV) were implanted at normal incidence and at room temperature in different highly insulating (>200 GΩ) thermoplastic polymers (poly(methyl methacrylate), polypropylene, polyethylene terephthalate glycol-modified, and polycarbonate). At high fluence and optimized process parameters, the ion implantation gives rise to the formation of a nanocomposite thin surface layer constituted by Pd nanoclusters and carbonaceous material (nanographite/amorphous carbon). The morphological, microstructural, and microanalytical properties of the nanocomposite layers were investigated by He-ion microscopy, glancing incidence X-ray diffraction, and Raman scattering, respectively. The electrical properties were characterized by resistance, van der Pauw, and Hall measurements. We performed accurate simultaneous deformation/bending experiments and electrical resistance measurements. We show that the electrical resistance varies linearly with the mechanical deformation (beam deflection) applied. The experimental results are interpreted by "hopping conductivity" model considering the nanostructure configuration of the nanocomposite layers. A gauge factor in the range between 4 and 8, depending on the ion-implanted polymer, was obtained for prototype strain gauge devices

Mutant p53 improves cancer cells\u2019 resistance to endoplasmic reticulum stress by sustaining activation of the UPR regulator ATF6

Missense mutations in the TP53 gene are frequent in human cancers, giving rise to mutant p53 proteins that can acquire oncogenic properties. Gain of function mutant p53 proteins can enhance tumour aggressiveness by promoting cell invasion, metastasis and chemoresistance. Accumulating evidences indicate that mutant p53 proteins can also modulate cell homeostatic processes, suggesting that missense p53 mutation may increase resistance of tumour cells to intrinsic and extrinsic cancer-related stress conditions, thus offering a selective advantage. Here we provide evidence that mutant p53 proteins can modulate the Unfolded Protein Response (UPR) to increase cell survival upon Endoplasmic Reticulum (ER) stress, a condition to which cancer cells are exposed during tumour formation and progression, as well as during therapy. Mechanistically, this action of mutant p53 is due to enhanced activation of the pro-survival UPR effector ATF6, coordinated with inhibition of the pro-apoptotic UPR effectors JNK and CHOP. In a triple-negative breast cancer cell model with missense TP53 mutation, we found that ATF6 activity is necessary for viability and invasion phenotypes. Together, these findings suggest that ATF6 inhibitors might be combined with mutant p53-targeting drugs to specifically sensitise cancer cells to endogenous or chemotherapy-induced ER stress

Tracking the multifield dynamics with cosmological data: a Monte Carlo approach

We introduce a numerical method specifically designed for investigating generic multifield models of inflation where a number of scalar fields ϕK are minimally coupled to gravity and live in a field space with a non-trivial metric Script G>IJ(ϕK). Our algorithm consists of three main parts. Firstly, we solve the field equations through the entire inflationary period, deriving predictions for observable quantities such as the spectrum of scalar perturbations, primordial gravitational waves, and isocurvature modes. We also incorporate the transfer matrix formalism to track the behavior of adiabatic and isocurvature modes on super-horizon scales and the transfer of entropy to scalar modes after the horizon crossing. Secondly, we interface our algorithm with Boltzmann integrator codes to compute the subsequent full cosmology, including the cosmic microwave background anisotropies and polarization angular power spectra. Finally, we develop a novel sampling algorithm able to efficiently explore a large volume of the parameter space and identify a sub-region where theoretical predictions agree with observations. In this way, sampling over the initial conditions of the fields and the free parameters of the models, we enable Monte Carlo analysis of multifield scenarios. We test all the features of our approach by analyzing a specific model and deriving constraints on its free parameters. Our methodology provides a robust framework for studying multifield inflation, opening new avenues for future research in the field