A novel film based on a cellulose/sodium alginate/gelatin composite activated with an ethanolic fraction of Boswellia sacra oleo gum resin

Boswellia sacra and its derivatives exhibit notable bioactive properties, which have been the subject of extensive scientific research; however, their potential applications in food packaging remain largely untapped. In the current study, cellulose, sodium alginate, and gelatin composite edible films were fabricated with the addition of different concentrations (0.2% and 0.3%) of the ethanolic fraction of Boswellia sacra oleo gum resin (BSOR). The resultant films were examined for their physical, chemical, mechanical, barrier, optical, and antioxidant properties. Moreover, the films were characterized using Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) to study the impact of incorporating BSOR on the morphological, crystalline, and chemical properties of the films. The addition of BSOR increased the film thickness (0.026-0.08 mm), water vapor permeability (0.210-0.619 (g.mm)/(m2.h.kPa), and the intensity of the yellow color (3.01-7.20) while reducing the values of both tensile strength (6.67-1.03 MPa) and elongation at break (83.50%-48.81%). SEM and FTIR analysis confirmed the interaction between the BSOR and film-forming components. The antioxidant properties of the edible films were significantly increased with the addition of BSOR. The comprehensive findings of the study demonstrated that BSOR possesses the potential to serve as an efficient natural antioxidant agent in the fabrication of edible films.

Spastic paraplegia preceding PSEN1-related familial Alzheimer's disease

INTRODUCTION

We investigated the frequency, neuropathology, and phenotypic characteristics of spastic paraplegia (SP) that precedes dementia in presenilin 1 (PSEN1) related familial Alzheimer's disease (AD).

METHODS

We performed whole exome sequencing (WES) in 60 probands with hereditary spastic paraplegia (HSP) phenotype that was negative for variants in known HSP-related genes. Where PSEN1 mutation was identified, brain biopsy was performed. We investigated the link between HSP and AD with PSEN1 in silico pathway analysis and measured in vivo the stability of PSEN1 mutant γ-secretase.

RESULTS

We identified a PSEN1 variant (p.Thr291Pro) in an individual presenting with pure SP at 30 years of age. Three years later, SP was associated with severe, fast cognitive decline and amyloid deposition with diffuse cortical plaques on brain biopsy. Biochemical analysis of p.Thr291Pro PSEN1 revealed that although the mutation does not alter active γ-secretase reconstitution, it destabilizes γ-secretase-amyloid precursor protein (APP)/amyloid beta (Aβn) interactions during proteolysis, enhancing the production of longer Aβ peptides. We then extended our analysis to all 226 PSEN1 pathogenic variants reported and show that 7.5% were associated with pure SP onset followed by cognitive decline later in the disease. We found that PSEN1 cases manifesting initially as SP have a later age of onset, are associated with mutations located beyond codon 200, and showed larger diffuse, cored plaques, amyloid-ring arteries, and severe CAA.

DISCUSSION

We show that pure SP can precede dementia onset in PSEN1-related familial AD. We recommend PSEN1 genetic testing in patients presenting with SP with no variants in known HSP-related genes, particularly when associated with a family history of cognitive decline.

Robust Fourier transformed infrared spectroscopy coupled with multivariate methods for detection and quantification of urea adulteration in fresh milk samples

Urea is added as an adulterant to give milk whiteness and increase its consistency for improving the solid not fat percentage, but the excessive amount of urea in milk causes overburden and kidney damages. Here, an innovative sensitive methodology based on near-infrared spectroscopy coupled with multivariate analysis has been proposed for the robust detection and quantification of urea adulteration in fresh milk samples. In this study, 162 fresh milk samples were used, those consisting 20 nonadulterated samples (without urea) and 142 with urea adulterant. Eight different percentage levels of urea adulterant, that is, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, and 1.70%, were prepared, each of them prepared in triplicates. A Frontier NIR spectrophotometer (BSEN60825-1:2007) by Perkin Elmer was used for scanning the absorption of each sample in the wavenumber range of 10,000-4,000 cm-1, using 0.2 mm path length CaF2 sealed cell at resolution of 2 cm-1. Principal components analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and partial least-squares regressions (PLSR) methods were applied for the multivariate analysis of the NIR spectral data collected. PCA was used to reduce the dimensionality of the spectral data and to explore the similarities and differences among the fresh milk samples and the adulterated ones. PLS-DA also showed the discrimination between the nonadulterated and adulterated milk samples. The R-square and root mean square error (RMSE) values obtained for the PLS-DA model were 0.9680 and 0.08%, respectively. Furthermore, PLSR model was also built using the training set of NIR spectral data to make a regression model. For this PLSR model, leave-one-out cross-validation procedure was used as an internal cross-validation criteria and the R-square and the root mean square error (RMSE) values for the PLSR model were found as 0.9800 and 0.56%, respectively. The PLSR model was then externally validated using a test set. The root means square error of prediction (RMSEP) obtained was 0.48%. The present proposed study was intended to contribute toward the development of a robust, sensitive, and reproducible method to detect and determine the urea adulterant concentration in fresh milk samples.