Age-Related Retinal Layer Thickness Changes Measured by OCT in APPNL-F/NL-F Mice: Implications for Alzheimer's Disease.

In Alzheimer's disease (AD), transgenic mouse models have established links between abnormalities in the retina and those in the brain. APPNL-F/NL-F is a murine, humanized AD model that replicates several pathological features observed in patients with AD. Research has focused on obtaining quantitative parameters from optical coherence tomography (OCT) in AD. The aim of this study was to analyze, in a transversal case-control study using manual retinal segmentation via SD-OCT, the changes occurring in the retinal layers of the APPNL/F-NF/L AD model in comparison to C57BL/6J mice (WT) at 6, 9, 12, 15, 17, and 20 months of age. The analysis focused on retinal thickness in RNFL-GCL, IPL, INL, OPL, and ONL based on the Early Treatment Diabetic Retinopathy Study (ETDRS) sectors. Both APPNL-F/NL-F-model and WT animals exhibited thickness changes at the time points studied. While WT showed significant changes in INL, OPL, and ONL, the AD model showed changes in all retinal layers analyzed. The APPNL-F/NL-F displayed significant thickness variations in the analyzed layers except for the IPL compared to related WT. These thickness changes closely resembled those found in humans during preclinical stages, as well as during mild and moderate AD stages, making this AD model behave more similarly to the disease in humans.

Retinal Vascular and Structural Changes in the Murine Alzheimer's APPNL-F/NL-F Model from 6 to 20 Months.

Alzheimer's disease (AD) may manifest retinal changes preceding brain pathology. A transversal case-control study utilized spectral-domain OCT angiography (SD-OCTA) and Angio-Tool software 0.6a to assess retinal vascular structures and OCT for inner and outer retina thickness in the APPNL-F/NL-F AD model at 6, 9, 12, 15, 17, and 20 months old. Comparisons to age-matched wild type (WT) were performed. The analysis focused on the three vascular plexuses using AngiooTool and on retinal thickness, which was represented with the Early Treatment Diabetic Retinopathy Study (ETDRS) sectors. Compared to WT, the APPNL-F/NL-F group exhibited both vascular and structural changes as early as 6 months persisting and evolving at 15, 17, and 20 months. Significant vascular alterations, principally in the superficial vascular complex (SVC), were observed. There was a significant decrease in the vessel area and the total vessel length in SVC, intermediate, and deep capillary plexus. The inner retina in the APPNL-F/NL-F group predominantly decreased in thickness while the outer retina showed increased thickness in most analyzed time points compared to the control group. There are early vascular and structural retinal changes that precede the cognitive changes, which appear at later stages. Therefore, the natural history of the APPNL-F/NL-F model may be more similar to human AD than other transgenic models.

Endogenous CO2 Overpressure Effect on Higher Alcohols Metabolism during Sparkling Wine Production.

Higher alcohols produced by yeast during the fermentation of sparkling wine must have the greatest impact on the smell and taste of wine. At present, the metabolic response to methanol and higher alcohols formation of Saccharomyces cerevisiae under endogenous CO2 overpressure has not been fully elucidated. In this work, a proteomics and metabolomics approach using a OFFGEL fractionator and the LTQ Orbitrap for the protein identification, followed by a metabolomic study for the detection and quantification of both higher alcohols (GC-FID and SBSE-TD-GC-MS) and amino acids (HPLC), was carried out to investigate the proteomic and metabolomic changes of S. cerevisiae in relation to higher alcohols formation under a CO2 overpressure condition in a closed bottle. The control condition was without CO2 overpressure in an open bottle. Methanol and six higher alcohols were detected in both conditions, and we have been able to relate to a total of 22 proteins: 15 proteins in the CO2 overpressure condition and 22 proteins in the control condition. As for the precursors of higher alcohols, 18 amino acids were identified in both conditions. The metabolic and proteomic profiles obtained in both conditions were different, so CO2 overpressure could be affecting the metabolism of higher alcohols. Furthermore, it was not possible to establish direct correlations in the condition under CO2 overpressure; however, in the condition without pressure it was possible to establish relationships. The data presented here can be considered as a platform that serves as a basis for the S. cerevisiae metabolome-proteome with the aim of understanding the behavior of yeast under conditions of second fermentation in the production of sparkling wines.

Phase angle and rectus femoris cross-sectional area as predictors of severe malnutrition and their relationship with complications in outpatients with post-critical SARS-CoV2 disease.

Background and aims: The diagnosis of malnutrition in post-critical COVID-19 patients is challenging as a result of the high prevalence of obesity, as well as the variability and previously reported inconsistencies across currently available assessment methods. Bioelectrical impedance vector analysis (BIVA) with phase angle (PhA) and nutritional ultrasound (NU®) are emerging techniques that have been proven successful in assessing body composition with high precision in previous studies. Our study aims to determine the performance and usefulness of PhA and rectus femoris cross-sectional area (RF-CSA) measurements in assessing body composition as part of the full routine morphofunctional assessment used in the clinical setting, as well as their capacity to predict severe malnutrition and to assess complications and aggressive therapy requirements during recent intensive care unit (ICU) admission, in a cohort of post-critically ill COVID-19 outpatients. Methods: This prospective observational study included 75 post-critical outpatients who recovered from severe COVID-19 pneumonia after requiring ICU admission. Correlations between all the morphofunctional parameters, complications, and aggressive therapy requirements during admission were analyzed. Multivariate logistic regression analysis and ROC curves were provided to determine the performance of NU® and PhA to predict severe malnutrition. Differences in complications and aggressive therapy requirements using the cutoff points obtained were analyzed. Results: In total, 54.7% of patients were classified by Subjective Global Assessment (SGA) as SGA-B and 45.3% as SGA-C, while 78.7% met the Global Leadership Initiative of Malnutrition (GLIM) criteria. PhA correlates positively with body cell mass/height (BCM/h) (r = 0.74), skeletal muscle index (SMI) (r = 0.29), RF-CSA (r = 0.22), RF-Y axis (r = 0.42), and handgrip strength (HGS) assessed using dynamometry (r = 0.42) and the Barthel scale (r = 0.29) and negatively with ICU stay (r = -0.48), total hospital stay (r = -0.57), need for invasive mechanical ventilation (IMV) (r = -0.39), days of IMV (r = -0.41), need for tracheostomy (r = -0.51), and number of prone maneuvers (r = -0.20). RF-CSA correlates positively with BCM/h (r = 0.41), SMI (r = 0.58), RF-Y axis (r = 0.69), and HGS assessed using dynamometry (r = 0.50) and the Barthel scale (r = 0.15) and negatively with total hospital stay (r = -0.22) and need for IMV (r = -0.28). Cutoff points of PhA < 5.4° and standardized phase angle (SPhA) < -0.79 showed good capacity to predict severe malnutrition according to SGA and revealed differences in ICU stay, total hospital stay, number of prone maneuvers, need for IMV, and need for rehabilitation, with statistical significance (p < 0.05). An RF-CSA/h < 2.52 cm2/m (for men) and <2.21 cm2/m (for women) also showed good performance in predicting severe malnutrition and revealed differences with statistical significance (p < 0.05) in ICU stay and total hospital stay. Conclusion: More than 75% of the post-critical COVID-19 survivors had malnutrition, and approximately half were obese. PhA, SPhA, RF-CSA, and RF-CSA/h, when applied to the assessment of body composition in post-critical COVID-19 patients, showed moderate-to-high correlation with other morphofunctional parameters and good performance to predict severe malnutrition and to assess complications and aggressive therapy requirements during ICU admission. Besides being readily available methods, BIVA and NU® can help improve the morphofunctional assessment of malnutrition in post-critical COVID-19 survivors; however, more studies are needed to assess the performance of these methods in other populations.

The Role of S. cerevisiae Sub1/PC4 in Transcription Elongation Depends on the C-Terminal Region and Is Independent of the ssDNA Binding Domain.

Saccharomyces cerevisiae Sub1 (ScSub1) has been defined as a transcriptional stimulatory protein due to its homology to the ssDNA binding domain (ssDBD) of human PC4 (hPC4). Recently, PC4/Sub1 orthologues have been elucidated in eukaryotes, prokaryotes, and bacteriophages with functions related to DNA metabolism. Additionally, ScSub1 contains a unique carboxyl-terminal region (CT) of unknown function up to date. Specifically, it has been shown that Sub1 is required for transcription activation, as well as other processes, throughout the transcription cycle. Despite the progress that has been made in understanding the mechanism underlying Sub1's functions, some questions remain unanswered. As a case in point: whether Sub1's roles in initiation and elongation are differentially predicated on distinct regions of the protein or how Sub1's functions are regulated. Here, we uncover some residues that are key for DNA-ScSub1 interaction in vivo, localized in the ssDBD, and required for Sub1 recruitment to promoters. Furthermore, using an array of genetic and molecular techniques, we demonstrate that the CT region is required for transcription elongation by RNA polymerase II (RNAPII). Altogether, our data indicate that Sub1 plays a dual role during transcription-in initiation through the ssDBD and in elongation through the CT region.

Biological Processes Highlighted in Saccharomyces cerevisiae during the Sparkling Wines Elaboration.

Sparkling wines elaboration has been studied by several research groups, but this is the first report on analysis of biological processes according to the Gene Ontology terms (GO terms) and related to proteins expressed by yeast cells during the second fermentation of sparkling wines. This work provides a comprehensive study of the most relevant biological processes in Saccharomyces cerevisiae P29, a sparkling wine strain, during the second fermentation under two conditions (without and with endogenous CO2 overpressure) in the middle and the end of second fermentation. Consequently, a proteomic analysis with the OFFGEL fractionator and protein identification with LTQ Orbitrap XL coupled to HPLC were performed. The classification of biological processes was carried out using the tools provided by the Saccharomyces Genome Database. Results indicate that a greater number of biological processes were identified under condition without CO2 overpressure and in the middle of the fermentation versus the end of the second fermentation. The biological processes highlighted under condition without CO2 overpressure in the middle of the fermentation were involved in the carbohydrate and lipid metabolic processes and catabolic and biosynthetic processes. However, under CO2 overpressure, specific protein expression in response to stress, transport, translation, and chromosome organization and specific processes were not found. At the end of fermentation, there were higher specific processes under condition without CO2 overpressure; most were related to cell division, growth, biosynthetic process, and gene transcription resulting in increased cell viability in this condition. Under CO2 overpressure condition, the most representative processes were related to translation as tRNA metabolic process, chromosome organization, mRNA processing, ribosome biogenesis, and ribonucleoprotein complex assembly, probably in response to the stress caused by the hard fermentation conditions. Therefore, a broader knowledge of the adaptation of the yeast, and its behavior under typical conditions to produce sparkling wine, might improve and favor the wine industry and the selection of yeast for obtaining a high-quality wine.

Autophagic Proteome in Two Saccharomyces cerevisiae Strains During Second Fermentation for Sparkling Wine Elaboration.

A correlation between autophagy and autolysis has been proposed in order to acceleratethe acquisition of wine organoleptic properties during sparkling wine elaboration. In this context, aproteomic analysis was carried out in two industrial Saccharomyces cerevisiae strains (P29,conventional sparkling wine strain and G1, implicated in sherry wine elaboration) with the aim ofstudying the autophagy-related proteome and comparing the effect of CO2 overpressure duringsparkling wine elaboration. In general, a detrimental effect of pressure and second fermentationdevelopment on autophagy-related proteome was observed in both strains, although it was morepronounced in flor yeast strain G1. Proteins mainly involved in autophagy regulation andautophagosome formation in flor yeast G1, and those required for vesicle nucleation and expansionin P29 strain, highlighted in sealed bottle. Proteins Sec2 and Sec18 were detected 3-fold underpressure conditions in P29 and G1 strains, respectively. Moreover, 'fingerprinting' obtained frommultivariate data analysis established differences in autophagy-related proteome between strainsand conditions. Further research is needed to achieve more solid conclusions and design strategiesto promote autophagy for an accelerated autolysis, thus reducing cost and time production, as wellas acquisition of good organoleptic properties.

Comparative Study of the Proteins Involved in the Fermentation-Derived Compounds in Two Strains of Saccharomyces cerevisiae during Sparkling Wine Second Fermentation.

Sparkling wine is a distinctive wine. Saccharomyces cerevisiae flor yeasts is innovative and ideal for the sparkling wine industry due to the yeasts' resistance to high ethanol concentrations, surface adhesion properties that ease wine clarification, and the ability to provide a characteristic volatilome and odorant profile. The objective of this work is to study the proteins in a flor yeast and a conventional yeast that are responsible for the production of the volatile compounds released during sparkling wine elaboration. The proteins were identified using the OFFGEL fractionator and LTQ Orbitrap. We identified 50 and 43 proteins in the flor yeast and the conventional yeast, respectively. Proteomic profiles did not show remarkable differences between strains except for Adh1p, Fba1p, Tdh1p, Tdh2p, Tdh3p, and Pgk1p, which showed higher concentrations in the flor yeast versus the conventional yeast. The higher concentration of these proteins could explain the fuller body in less alcoholic wines obtained when using flor yeasts. The data presented here can be thought of as a proteomic map for either flor or conventional yeasts which can be useful to understand how these strains metabolize the sugars and release pleasant volatiles under sparkling wine elaboration conditions.

Differential Analysis of Proteins Involved in Ester Metabolism in two Saccharomyces cerevisiae Strains during the Second Fermentation in Sparkling Wine Elaboration.

The aromatic metabolites derived from yeast metabolism determine the characteristics of aroma and taste in wines, so they are considered of great industrial interest. Volatile esters represent the most important group and therefore, their presence is extremely important for the flavor profile of the wine. In this work, we use and compare two Saccharomyces cerevisiae yeast strains: P29, typical of sparkling wines resulting of second fermentation in a closed bottle; G1, a flor yeast responsible for the biological aging of Sherry wines. We aimed to analyze and compare the effect of endogenous CO2 overpressure on esters metabolism with the proteins related in these yeast strains, to understand the yeast fermentation process in sparkling wines. For this purpose, protein identification was carried out using the OFFGEL fractionator and the LTQ Orbitrap, following the detection and quantification of esters with gas chromatograph coupled to flame ionization detector (GC-FID) and stir-bar sorptive extraction, followed by thermal desorption and gas chromatography-mass spectrometry (SBSE-TD-GC-MS). Six acetate esters, fourteen ethyl esters, and five proteins involved in esters metabolism were identified. Moreover, significant correlations were established between esters and proteins. Both strains showed similar behavior. According to these results, the use of this flor yeast may be proposed for the sparkling wine production and enhance the diversity and the typicity of sparkling wine yeasts.