Multi-Omics Approaches for Freshness Estimation and Detection of Illicit Conservation Treatments in Sea Bass (Dicentrarchus Labrax): Data Fusion Applications.

Fish freshness consists of complex endogenous and exogenous processes; therefore, the use of a few parameters to unravel illicit practices could be insufficient. Moreover, the development of strategies for the identification of such practices based on additives known to prevent and/or delay fish spoilage is still limited. The paper deals with the identification of the effect played by a Cafodos solution on the conservation state of sea bass at both short-term (3 h) and long-term (24 h). Controls and treated samples were characterized by a multi-omic approach involving proteomics, lipidomics, metabolomics, and metagenomics. Different parts of the fish samples were studied (muscle, skin, eye, and gills) and sampled through a non-invasive procedure based on EVA strips functionalized by ionic exchange resins. Data fusion methods were then applied to build models able to discriminate between controls and treated samples and identify the possible markers of the applied treatment. The approach was effective in the identification of the effect played by Cafodos that proved to be different in the short- and long-term and complex, involving proteins, lipids, and small molecules to a different extent.

Solar photodegradation of irinotecan in water: optimization and robustness studies by experimental design.

Irinotecan, a widely prescribed anticancer drug, is an emerging contaminant of concern that has been detected in various aquatic environments due to ineffective removal by traditional wastewater treatment systems. Solar photodegradation is a viable approach that can effectively eradicate the drug from aqueous systems. In this study, we used the design of experiment (DOE) approach to explore the robustness of irinotecan photodegradation under simulated solar irradiation. A full factorial design, including a star design, was applied to study the effects of three parameters: initial concentration of irinotecan (1.0-9.0 mg/L), pH (5.0-9.0), and irradiance (450-750 W/m2). A high-performance liquid chromatography coupled with a high-resolution mass spectrometry (HPLC-HRMS) system was used to determine irinotecan and identify transformation products. The photodegradation of irinotecan followed a pseudo-first order kinetics. In the best-fitted linear model determined by the stepwise model fitting approach, pH was found to have about 100-fold greater effect than either irinotecan concentration or solar irradiance. Under optimal conditions (irradiance of 750 W/m2, 1.0 mg/L irinotecan concentration, and pH 9.0), more than 98% of irinotecan was degraded in 60 min. With respect to irradiance and irinotecan concentration, the degradation process was robust in the studied range, implying that it may be effectively applied in locations and/or seasons with solar irradiance as low as 450 W/m2. However, pH needs to be strictly controlled and kept between 7.0 and 9.0 to maintain the degradation process robust. Considerations about the behavior of degradation products were also drawn.

Prolonged exposure to simulated microgravity promotes stemness impairing morphological, metabolic and migratory profile of pancreatic cancer cells: a comprehensive proteomic, lipidomic and transcriptomic analysis.

BACKGROUND: The impact of the absence of gravity on cancer cells is of great interest, especially today that space is more accessible than ever. Despite advances, few and contradictory data are available mainly due to different setup, experimental design and time point analyzed. METHODS: Exploiting a Random Positioning Machine, we dissected the effects of long-term exposure to simulated microgravity (SMG) on pancreatic cancer cells performing proteomic, lipidomic and transcriptomic analysis at 1, 7 and 9 days. RESULTS: Our results indicated that SMG affects cellular morphology through a time-dependent activation of Actin-based motility via Rho and Cdc42 pathways leading to actin rearrangement, formation of 3D spheroids and enhancement of epithelial-to-mesenchymal transition. Bioinformatic analysis reveals that SMG may activates ERK5/NF-κB/IL-8 axis that triggers the expansion of cancer stem cells with an increased migratory capability. These cells, to remediate energy stress and apoptosis activation, undergo a metabolic reprogramming orchestrated by HIF-1α and PI3K/Akt pathways that upregulate glycolysis and impair ß-oxidation, suggesting a de novo synthesis of triglycerides for the membrane lipid bilayer formation. CONCLUSIONS: SMG revolutionizes tumor cell behavior and metabolism leading to the acquisition of an aggressive and metastatic stem cell-like phenotype. These results dissect the time-dependent cellular alterations induced by SMG and pave the base for altered gravity conditions as new anti-cancer technology.

On the Traceability of the Hazelnut Production Chain by Means of Trace Elements.

The production chain of hazelnuts has been studied by analyzing three sets of samples produced in purity from three different pools of hazelnuts of cultivar "Tonda Gentile Trilobata", "Tonda Gentile Romana" and "Mortarella", all cultivated in Italy. From each pool, five processed products were obtained: roasted hazelnuts, hazelnut paste, hazelnut cream, Gianduja paste and Gianduiotto paste. After pre-treatment by means of dry ashing, all samples from each cultivar, including raw hazelnuts, were then analyzed by means of Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). A good discrimination was obtained among the different chain stages according to the distribution of the trace elements, as expected. More interesting was the discrimination among the different cultivars: it was possible to distinguish the samples produced from the respective cultivar by means of specific chemical markers, particularly Mo and Ni.

Sialylated isoforms of apolipoprotein C-III and plasma lipids in subjects with coronary artery disease.

BACKGROUND: Apolipoprotein C-III (ApoC-III), a key regulator of plasma triglyceride (TG), is present in three isoforms, i.e. non-sialylated (ApoC-III0), monosialylated (ApoC-III1) and disialylated (ApoC-III2). We aimed at quantifying the distribution of the ApoC-III glycoforms in patients with angiographically demonstrated coronary artery disease (CAD) according to levels of total ApoC-III plasma concentration. METHODS: ApoC-III glycoforms were quantified by a specifically developed, high-resolution, mass spectrometry method in unrelated CAD patients. Lipoprotein lipase (LPL) activity was estimated by a fluorescence-based method. RESULTS: In 101 statin-treated CAD patients, the absolute concentrations of the three glycoforms similarly increased across ApoC-III quartiles, but the proportion of ApoC-III1 rose whereas that of ApoC-III0 decreased progressively by increasing total ApoC-III concentrations. The proportion of ApoC-III2 was quite constant throughout the whole range of total ApoC-III. A higher proportion of ApoC-III1 reflected an unfavorable lipid profile characterized by high levels of TG, total and low density lipoprotein cholesterol, ApoE and reduced ApoA-I. The correlations between ApoC-III glycoforms and TG were confirmed in 50 statin-free CAD patients. High concentration of total ApoC-III was associated with low LPL activity, while no correlation was found for the relative proportion of glycoforms. CONCLUSIONS: Specific patterns of ApoC-III glycoforms are present across different total ApoC-III concentrations in CAD patients. The inhibitory effect of ApoC-III on LPL appears related to total ApoC-III concentration, but not to the relative proportion of ApoC-III glycoforms.

Method for Noninvasive Analysis of Proteins and Small Molecules from Ancient Objects.

Proteins and small molecules from ancient objects and cultural heritage can provide key information and contribute to study the context of objects and artists. However, all present-day protocols and strategies for the analysis of ancient samples are often invasive and require microsampling. Here, we present a new method for the noninvasive analysis of proteins and small molecules: the technique uses a special ethyl-vinyl acetate film functionalized with strong cation/anion exchange and C8 resins, for interacting with both proteins and small molecules present on the surface of the objects, followed by LC-MS/MS analysis. The new method was fully validated for the determination of both proteins and small molecules on several types of supports, showing excellent analytical performances such as, for example, R2 of the calibration curve of 0.98 and 0.99 for proteins and small molecules, low but very repeatable recoveries, particularly adequate for investigations on precious ancient samples that must not be altered by the analytical procedure. ESEM images and LED multispectral imaging confirmed that no damages or alterations occurred onto the support surfaces and no residues were left from the extractive film. Finally, the new method was applied for the characterization of the binders of a historical fresco of the XVI century from the Flemish painter Paul Brill and of a recently discovered fresco from Isidoro Bianchi (XVII century). Moreover the method was employed for the identification of the colorant used by Pietro Gallo (XIV century) on a wood panel. The method here reported can be easily applied to any other research on ancient precious objects and cultural heritage, since it does not require microsampling and the proteins/small molecules extraction can be performed directly in situ, leaving the object unchanged and intact.

IEF peptide fractionation method combined to shotgun proteomics enhances the exploration of rice milk proteome.

We conducted a proteomics study in order to detect the proteomic method which provides the most complete characterization of the proteins of rice milk. In particular, we compared the results obtained from LC-MS/MS after protein precipitation with acetone or TCA, as well as the results obtained from LC-MS/MS after protein prefractionation based on SDS-PAGE (GeLC-MS/MS) or ProteoMiner™ technology (ProteoMiner-LC-MS/MS), and after peptide prefractionation based on IEF (pIEF-LC-MS/MS). A total of 158 protein species have been detect in rice milk. The physical-chemical analysis and classification of the identified proteins were also reported. In particular, we showed that pIEF-LC-MS/MS method led to a significant increase in the proteome coverage, allowing the identification of a total of 96 proteins of milk rice. This study demonstrates the utility of a prefractionation step based on pIEF before the shotgun proteomic analysis and offers an in-depth insight into the rice milk proteome.

Blood transcriptomics of drug-naïve sporadic Parkinson's disease patients.

BACKGROUND: Parkinson's disease (PD) is a chronic progressive neurodegenerative disorder that is clinically defined in terms of motor symptoms. These are preceded by prodromal non-motor manifestations that prove the systemic nature of the disease. Identifying genes and pathways altered in living patients provide new information on the diagnosis and pathogenesis of sporadic PD. METHODS: Changes in gene expression in the blood of 40 sporadic PD patients and 20 healthy controls ("Discovery set") were analyzed by taking advantage of the Affymetrix platform. Patients were at the onset of motor symptoms and before initiating any pharmacological treatment. Data analysis was performed by applying Ranking-Principal Component Analysis, PUMA and Significance Analysis of Microarrays. Functional annotations were assigned using GO, DAVID, GSEA to unveil significant enriched biological processes in the differentially expressed genes. The expressions of selected genes were validated using RT-qPCR and samples from an independent cohort of 12 patients and controls ("Validation set"). RESULTS: Gene expression profiling of blood samples discriminates PD patients from healthy controls and identifies differentially expressed genes in blood. The majority of these are also present in dopaminergic neurons of the Substantia Nigra, the key site of neurodegeneration. Together with neuronal apoptosis, lymphocyte activation and mitochondrial dysfunction, already found in previous analysis of PD blood and post-mortem brains, we unveiled transcriptome changes enriched in biological terms related to epigenetic modifications including chromatin remodeling and methylation. Candidate transcripts as CBX5, TCF3, MAN1C1 and DOCK10 were validated by RT-qPCR. CONCLUSIONS: Our data support the use of blood transcriptomics to study neurodegenerative diseases. It identifies changes in crucial components of chromatin remodeling and methylation machineries as early events in sporadic PD suggesting epigenetics as target for therapeutic intervention.

Bio-physical pre-treatments in anaerobic digestion of organic fraction of municipal solid waste to optimize biogas production and digestate quality for agricultural use.

This study optimized the anaerobic digestion (AD) of separated collected organic fractions of municipal solid waste (OFMSW) to produce energy and digestate as biofertilizer. Due to OFMSW's partial recalcitrance to degradation, enzymatic (UPP2, MCPS, USC4, USE2, A. niger) and physical (mechanical blending, heating, hydrodynamic cavitation) pre-treatments were tested. Experimental and modeling approaches were used to compare AD performance regarding energy sustainability and digestate quality. Digestate was separated into solid and liquid fractions, and then chemically and physically characterized by investigating the nutrient release mechanisms. Principal Component Analysis was applied, equally weighing energy and digestate productions. Unlike previous studies focusing only on biogas, this study evaluated the effects of pre-treatments on both biogas and digestate production, viewing AD as a biorefinery process for urban waste valorization. Results showed that all pre-treatments were energetically sustainable, but enzymatic pre-treatments yielded digestates richer in nutrients (increase of 80% N, 200% P and 150% K as compared to OFMSW) and with greater organic matter degradation compared to physical pre-treatments. The liquid fraction of digestate from enzymatic pre-treatments had higher nutrient concentrations, while those from physical pre-treatments had more balanced nutrient content, making them more suitable for fertigation.

Identification of Illicit Conservation Treatments in Fresh Fish by Micro-Raman Spectroscopy and Chemometric Methods.

In the field of food control for fresh products, the identification of foods subjected to illicit conservation treatments to extend their shelf life is fundamental. Fresh fish products are particularly subjected to this type of fraud due to their high commercial value and the fact that they often have to be transported over a long distance, keeping their organoleptic characteristics unaltered. Treatments of this type involve, e.g., the bleaching of the meat and/or the momentary abatement of the microbial load, while the degradation process continues. It is therefore important to find rapid methods that allow the identification of illicit treatments. The study presented here was performed on 24 sea bass samples divided into four groups: 12 controls (stored on ice in the fridge for 3 or 24 h), and 12 treated with a Cafodos-like solution for 3 or 24 h. Muscle and skin samples were then characterized using micro-Raman spectroscopy. The data were pre-processed by smoothing and taking the first derivative and then PLS-DA models were built to identify short- and long- term effects on the fish's muscle and skin. All the models provided the perfect classification of the samples both in fitting and cross-validation and an analysis of the bands responsible for the effects was also reported. To the best of the authors' knowledge, this is the first time Raman spectroscopy has been applied for the identification of a Cafodos-like illicit treatment, focusing on both fish muscle and skin evaluation. The procedure could pave the way for a future application directly on the market through the use of a portable device.

Distinct Signatures of Tumor-Associated Microbiota and Metabolome in Low-Grade vs. High-Grade Dysplastic Colon Polyps: Inference of Their Role in Tumor Initiation and Progression.

According to the driver-passenger model for colorectal cancer (CRC), the tumor-associated microbiota is a dynamic ecosystem of bacterial species where bacteria with carcinogenic features linked to CRC initiation are defined as "drivers", while opportunistic bacteria colonizing more advanced tumor stages are known as "passengers". We reasoned that also gut microbiota-associated metabolites may be differentially enriched according to tumor stage, and be potential determinants of CRC development. Thus, we characterized the mucosa- and lumen-associated microbiota (MAM and LAM, respectively) and mucosa-associated metabolites in low- vs. high-grade dysplastic colon polyps from 78 patients. We show that MAM, obtained with a new biopsy-preserving approach, and LAM differ in composition and α/ß-diversity. By stratifying patients for polyp histology, we found that bacteria proposed as passengers by previous studies colonized high-grade dysplastic adenomas, whereas driver taxa were enriched in low-grade polyps. Furthermore, we report altered "mucosa-associated metabolite" levels in low- vs. high-grade groups. Integrated microbiota-metabolome analysis suggests the involvement of the gut microbiota in the production and consumption of these metabolites. Altogether, our findings support the involvement of bacterial species and associated metabolites in CRC mucosal homeostasis in a tumor-stage-specific manner. These distinct signatures may be used to distinguish low-grade from high-grade dysplastic polyps.

Effects of nickel, chlorpyrifos and their mixture on the Dictyostelium discoideum proteome.

Mixtures of chemicals can have additive, synergistic or antagonistic interactions. We investigated the effects of the exposure to nickel, the organophosphate insecticide chlorpyrifos at effect concentrations (EC) of 25% and 50% and their binary mixture (Ec25 + EC25) on Dictyostelium discoideum amoebae based on lysosomal membrane stability (LMS). We treated D. discoideum with these compounds under controlled laboratory conditions and evaluated the changes in protein levels using a two-dimensional gel electrophoresis (2DE) proteomic approach. Nickel treatment at EC25 induced changes in 14 protein spots, 12 of which were down-regulated. Treatment with nickel at EC50 resulted in changes in 15 spots, 10 of which were down-regulated. Treatment with chlorpyrifos at EC25 induced changes in six spots, all of which were down-regulated; treatment with chlorpyrifos at EC50 induced changes in 13 spots, five of which were down-regulated. The mixture corresponding to EC25 of each compound induced changes in 19 spots, 13 of which were down-regulated. The data together reveal that a different protein expression signature exists for each treatment, and that only a few proteins are modulated in multiple different treatments. For a simple binary mixture, the proteomic response does not allow for the identification of each toxicant. The protein spots that showed significant differences were identified by mass spectrometry, which revealed modulations of proteins involved in metal detoxification, stress adaptation, the oxidative stress response and other cellular processes.

A Fully Automated Online SPE-LC-MS/MS Method for the Determination of 10 Pharmaceuticals in Wastewater Samples.

The increasing use of pharmaceuticals, their presence in the aquatic environment, and the associated toxic effects, have raised concerns in recent years. In this work, a new multi-residue analytical method was developed and validated for the determination of 10 pharmaceuticals in wastewaters using online solid-phase extraction (online SPE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The compounds included in the method were antineoplastics (cabazitaxel, docetaxel, doxorubicin, etoposide, irinotecan, methotrexate, paclitaxel, and topotecan), renin inhibitors (aliskiren), and antidepressants (maprotiline). The method was developed through several experiments on four online SPE cartridges, three reversed phase chromatography columns, and four combinations of mobile phase components. Under optimal conditions, very low limits of detection (LODs) of 1.30 to 10.6 ng L-1 were obtained. The method was repeatable, with relative standard deviations (RSD, %) for intraday and interday precisions ranged from 1.6 to 7.8 and from 3.3 to 13.2, respectively. Recovery values ranged from 78.4 to 111.4%, indicating the reproducibility of the method. Matrix effects were mainly presented as signal suppression, with topotecan and doxorubicin being the two most affected compounds (31.0% signal suppression). The proposed method was successfully applied to hospital effluents, detecting methotrexate (4.7-9.3 ng L-1) and maprotiline (11.2-23.1 ng L-1). Due to the shorter overall run time of 15 min, including sample preparation, and reduced sample volume (0.9 mL), this on-line SPE-LC-MS/MS method was extremely convenient and efficient in comparison to the classical off-line SPE method. The proposed method was also highly sensitive and can be used for ultratrace quantification of the studied pharmaceuticals in wastewaters, providing useful data for effective environmental monitoring.

Transcriptional Biomarkers and Immunohistochemistry for Detection of Illicit Dexamethasone Administration in Veal Calves.

Corticosteroids such as Dexamethasone (DEX) are commonly licensed for therapy in meat animals due to their known pharmacological properties. However, their misuse aimed to achieve anabolic effects is often found by National Residues Control Plans. The setup of a complementary "biomarker based" methods to unveil such illicit practices is encouraged by current European legislation. In this study, the combined use of molecular and histological quantitative techniques was applied on formalin fixed paraffin embedded (FFPE) muscle samples to assess the effects of illicit DEX treatment on veal calves. A PCR array, including 28 transcriptional biomarkers related to DEX exposure, was combined with a histochemical analysis of muscle fiber. An analysis based on unsupervised (PCA) and supervised (PLS-DA and Kohonen's SOM) methods, was applied in order to define multivariate models able to classify animals suspected of illicit treatment by DEX. According to the conventional univariate approach, a not-significant reduction in type I fibres was recorded in the DEX-treated group, and only 12 out of 28 targeted genes maintained their expected differential expression, confirming the technical limitations of a quantitative analysis on FFPE samples. However, the multivariate models developed highlighted the possibility to establish complementary screening strategies, particularly when based on transcriptional biomarkers characterised by low expression profiles.

Proteins involved in biotic and abiotic stress responses as the most significant biomarkers in the ripening of Pinot Noir skins.

We propose an integrated approach, obtained by the combination of multivariate statistics and proteomics, useful to isolate candidate biomarkers for the evaluation of grape ripening. We carried out a comparative 2-DE analysis of grape skins collected in three moments of ripening and analyzed the spot volume dataset through the application of principal component analysis followed by forward stepwise-linear discriminant analysis. This technique allowed to discriminate véraison, quite mature and mature samples, and to sort the matched spots according to their significance. We identified 36 spots showing high discriminating coefficients through liquid chromatography - electrospray ionization - tandem mass spectrometry (LC-ESI-MS/MS). Most of them were involved in biotic and abiotic stress responses indicating these enzymes as good candidate markers of berry ripening. These evidences hint at a likely developmental role of these proteins, in addition to their reported activity in stress events. Restricting the same statistical analysis to the samples belonging to the two last stages, it was indicated that this approach can clearly distinguish these close and similar phases of berry development. Taken all together, these results bear out that the employment of the combination of 2-DE and multivariate statistics is a reliable tool in the identification of new protein markers for describing the ripening phases and to assess the overall quality of the fruit.

Technique based on LED multispectral imaging and multivariate analysis for monitoring the conservation state of the Dead Sea Scrolls.

The aim of this project is the development of a noninvasive technique based on LED multispectral imaging (MSI) for monitoring the conservation state of the Dead Sea Scrolls (DSS) collection. It is well-known that changes in the parchment reflectance drive the transition of the scrolls from legible to illegible. Capitalizing on this fact, we will use spectral imaging to detect changes in the reflectance before they become visible to the human eye. The technique uses multivariate analysis and statistical process control theory. The present study was carried out on a "sample" parchment of calfskin. The monitoring of the surface of a commercial modern parchment aged consecutively for 2 h and 6 h at 80 °C and 50% relative humidity (ASTM) was performed at the Imaging Lab of the Library of Congress (Washington, DC, U.S.A.). MSI is here carried out in the vis-NIR range limited to 1 µm, with a number of bands of 13 and bandwidths that range from about 10 nm in UV to 40 nm in IR. Results showed that we could detect and locate changing pixels, on the basis of reflectance changes, after only a few "hours" of aging.

Investigation of the applicability of Zernike moments to the classification of SDS 2D-PAGE maps.

The aim of this work is to investigate the performance of multivariate classification techniques like partial least squares-discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) when using Zernike moments as global image descriptors, in the classification of sodium dodecyl sulphate (SDS) two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) maps affected by different levels of deformation. Synthetic sets of images simulating real SDS 2D-PAGE maps were analysed in controlled conditions to obtain information on the robustness and limits of applicability of the classification techniques operating on the basis of a given image decomposition method.

Two-Dimensional Gel Electrophoresis Image Analysis.

Gel-based proteomics is still quite widespread due to its high-resolution power; the experimental approach is based on differential analysis, where groups of samples (e.g., control vs diseased) are compared to identify panels of potential biomarkers. However, the reliability of the result of the differential analysis is deeply influenced by 2D-PAGE maps image analysis procedures. The analysis of 2D-PAGE images consists of several steps, such as image preprocessing, spot detection and quantitation, image warping and alignment, spot matching. Several approaches are present in literature, and classical or last-generation commercial software packages exploit different algorithms for each step of the analysis. Here, the most widespread approaches and a comparison of the different strategies are presented.

Chemometric Tools for 2D-PAGE Data Analysis.

Two-Dimensional Polyacrylamide Gel Electrophoresis (2D-PAGE) provides two-dimensional maps where proteins appear separated according to their isoelectric point (pI) and molecular weight (MW). Usually these maps are very complex (i.e., hundreds or thousands of spots can be present in each map), and characterized by a low reproducibility, which hinders the possibility to identify reliable biomarkers unless robust methods are applied. The analysis of different sets of 2D-PAGE maps (e.g., control vs. pathological or control vs. drug-treated samples) to identify candidate biomarkers (proteins under- or over-expressed in different conditions) is usually carried out through image analysis systems providing a so-called spot volume dataset where each sample corresponds to a map described by the optical densities of all the detected spots. The identification of candidate biomarkers can be therefore accomplished by comparing different maps by classical monovariate statistical tests applied spotwise, or by multivariate chemometric tools applied to the entire set of spots present on each map. Here, the most exploited multivariate techniques will be considered, ranging from pattern recognition to classification methods.

Kohonen Artificial Neural Network and Multivariate Analysis in the Identification of Proteome Changes during Early and Long Aging of Bovine Longissimus dorsi Muscle Using SWATH Mass Spectrometry.

To study proteomic changes involved in tenderization of Longissimus dorsi, Charolais heifers and bulls muscles were sampled after early and long aging (12 or 26 days). Sensory evaluation and instrumental tenderness measurement were performed. Proteins were analyzed by gel-free proteomics. By pattern recognition (principal component analysis and Kohonen's self-organizing maps) and classification (partial least squares-discriminant analysis) tools, 58 and 86 dysregulated proteins were detected after 12 and 26 days of aging, respectively. Tenderness was positively correlated mainly with metabolic enzymes (PYGM, PGAM2, TPI1, PGK1, and PFKM) and negatively with keratins. Downregulation in hemoglobin subunits and carbonic anhydrase 3 levels was relevant after 12 days of aging, while mimecan and collagen chains levels were reduced after 26 days of aging. Bioinformatics indicated that aging involves a prevalence of metabolic pathways after late and long periods. These findings provide a deeper understanding of changes involved in aging of beef and indicate a powerful method for future proteomics studies.