**2. Proposed Finite-Element-Analysis-Based Inspection Interval Optimization Approach**

Figure 1 shows the proposed FEA-based inspection interval optimization approach. The developed methodology consisted of the following five phases:

Phase 3.The uncertainty of mechanical parameters was included, and the design of experiments was created based on Latin hypercube sampling (LHS) scenarios.

Phase 4.A Monte Carlo simulation was performed by building a response surface model.

Phase 5. Risk assessment and inspection interval optimization of the tail wing structure were undertaken.

#### *2.1. Development of the Finite Element Model*

Modern aircraft structures, such as the wings and fuselage, utilize FRCPs. The composite laminates are highly susceptible to delamination, which is considered one of the major damage mechanisms in composites among all other types of damage. The delamination propagation can occur under the fatigue loading, thus causing stiffness and gradual strength degradation and leading to catastrophic failure of composite structures. Therefore, the characterization of the fatigue delamination resistance in composite materials is necessary for their damage tolerance design and reliability assessment. In aircraft composite structures, stringers are joined to the skin via adhesive bonding. During the flight, cyclic fatigue causes separation between the skin and stringer, which may result in delamination failure. Therefore, it is important to predict fatigue delamination initiation and propagation so that these composite panels do not fail prematurely. To enhance the fatigue life and reliability of composite structures, several researchers have investigated the delamination growth in composites under fatigue loading. A variety of models are proposed in the literature for the prediction of fatigue delamination growth at the coupon level. However, the prediction of fatigue delamination in complex geometries, such as aircraft wing structures, is still an open issue. The most popular approach for the characterization of fatigue crack

growth is Paris' law [17–19]. Paris' law relates the fatigue crack growth rate to the stress intensity factor and energy release rate. Equation (1) shows the basic form of Paris' law [20]:

$$dA/dN = \mathbb{C}f(G)^m\tag{1}$$

where *C* and m represent the fitting parameters and *f*(*G*) is a function of the energy release rate (*G*). In metals, the stress intensity factor variation (ΔK) is usually adopted for fatigue crack growth. On the other hand, in composite laminated structures, the energy release rate (Δ*G*) variation seems to provide a better description of experimental results, as shown in Equation (2):

$$\frac{dA}{dN} = \mathbb{C}(\Delta G)^{\mathfrak{m}} = \mathbb{C}(\mathbb{G}\_{\max} - \mathbb{G}\_{\min})\tag{2}$$

**Figure 1.** Schematic of the proposed FE-based inspection interval optimization approach.

The FE model implemented in this study and included in the FE code ABAQUS [21] was built on Equation (2) to estimate the fatigue crack growth rate.

In a numerical model, delamination is usually modeled using a damage mechanics or fracture mechanics approach in combination with Paris' law. Different approaches are found in the literature in the context of damage mechanics. Among these, the cohesive zone modeling approach [22–24] received considerable attention for delamination modeling. This approach provides good results in combination with Paris' law for simple geometries and test specimens. However, this approach is not suitable for complex geometries. On the other hand, the virtual crack closure technique (VCCT) [9,25] derived from fracture mechanics is found built into several commercial FE codes. This approach is suitable for implementation in complex geometries and can simulate fatigue delamination growth in

combination with Paris' law. The fatigue crack growth in an ABAQUS simulation employs VCCT criteria to compute the energy release rate. The crack propagation starts when the criterion based on Equation (3) is satisfied:

$$f = \frac{N}{c\_1 \Delta G^{\circ 2}} \ge G\_{\text{max}} > G\_{th} \tag{3}$$

where *N* is the current cycle number and *c*1 and *c*2 are fitting parameters that are experimentally determined. Once the onset criterion is satisfied, the fatigue delamination growth rate is governed by Paris' law, which is shown in Equation (4):

$$\frac{dA}{dN} = c\_3 (\Delta G)^{c\_4} \tag{4}$$

where *c*3 and *c*4 are fitting parameters.

The fatigue delamination finite element was first implemented for the double cantilever beam (DCB) composite specimen. The results of the numerical model were compared with the benchmark experimental study [23,26]. The composite specimen had a length of 254 mm and a width of 25 mm. The thickness of each arm was 3 mm. The initial delamination was induced in the specimen with a length of 51 mm and was located in the center of the plies, as shown in Figure 2. The specimen consisted of a T300/1076 carbon fiber epoxy composite with 24 unidirectional plies.

**Figure 2.** DCB specimen geometry with initial delamination.

The material properties used in the numerical model were taken from [26] and are shown in Table 1.

Continuum shell elements (SC8R) were used for the modeling of the DCB specimen. A single element is used throughout the thickness of each arm. The refined mesh was used in the damage propagation zone and the remaining region consisted of a coarse mesh. First, the load–displacement curve was computed for quasi-static loading. The simulation curve was computed and compared with the experimental benchmark case study result, as shown in Figure 3. The numerical model showed a linear response and a good correlation was found, both in terms of the initial stiffness and peak load between the numerical model results and the experimental benchmark case study.

**Figure 3.** Load vs. displacement curve of the DCB specimen [26].

For the fatigue crack propagation analysis, the triangular load cycle as applied in the experimental benchmark case study [23,26] was applied as a fatigue loading cycle. As expected, the delamination length increased rapidly at the start of the loading cycles. The delamination stopped propagating at around 3.7 million cycles. The numerical results computed in ABAQUS showed good agreement with the experimental benchmark results, as shown in Figure 4.

Once the fatigue delamination crack propagation model was established, the model was extended from the composite specimen to the KT-100 aircraft tail wing structure. The tail wing is located behind the main lifting surface of the aircraft and provides stability and control. The design of the KT-100 horizontal stabilizer consists of upper and lower skins. The upper and lower skins of the sandwich structure act as a spur structure. The upper and lower skins are bonded and tightened to make a box-shaped structure. Three ribs exist inside the box structure. Skin debonding from the rib is the most critical damage that can occur in an aircraft tail wing structure. Figure 5 shows skin-debonding damage. Therefore, in this study, skin/rib-debonding damage was modeled using the fatigue progressive damage model.

The geometry of the tail wing was provided by the Korean Airforce and imported from the 3D model in ABAQUS. To simplify the model, bolts and rivets were not considered in the geometry. Initial delamination of 32 mm was introduced between the middle rib and upper skin, as shown in Figure 6a. To avoid the loss of computational power, shell elements (S4R) were used to model the tail wing structure with 49,209 total elements. The mesh was kept refined in the crack propagation region and coarse in the remaining regions, as shown in Figure 6b.

**Figure 4.** Comparison of the numerical and experimental fatigue delamination propagation curve [23,26].

**Figure 5.** Skin-debonding damage in aircraft tail wing structure.

**Figure 6.** (**a**) Geometry of a tail wing with initial delamination and (**b**) the mesh configuration of the model.

The loads and boundary conditions are used as in an actual flight scenario. One side of the wing was kept fixed, and the shear forces were applied at the other end with the flight loading spectrum as a fatigue cycle provided by the Korean Airforce. Figure 7 shows the flight operating loading spectrum with a normalized amplitude.

The bond stat plot (crack propagation plot) output in ABAQUS represents the fatigue crack propagation. The blue color represents the unbonded region, while the red color represents the bonded region. Figure 8 represents the BDSTAT plot for the tail wing structure. The BDSTAT plot was computed between the upper skin and the middle rib of the composite structure.

**Figure 8.** BDSTAT plot representing the cracked region between the upper skin and the middle.

Different case simulations were carried out for the different values of the applied loading scenarios by using the flight operating load spectrum. The simulation was run for 8000 flight hours (FHs), and the crack propagation plots are analyzed. The first case scenario represented the actual loading condition with the magnitude of shear forces. The other three case scenarios were simulated to observe the fatigue crack propagation. Table 2 shows the case simulation scenarios.

**Table 2.** Case simulation scenarios.

The first case simulation consisted of the applied load of 1.849 KN (actual flight loading scenario) for the applied operating load spectrum. The simulation was carried out for 8000 FHs, and it was observed that the crack did not propagate. As the case represents a real loading scenario, it is customary that the crack propagation was slow, and it took more than 8000 FHs to propagate the crack. As the applied load was increased, the crack propagation region increased, as shown in Figure 9. Therefore, it was concluded that to observe the crack propagation, the applied loading must be increased to more than the real flight loading scenario.

**Figure 9.** Crack propagation plot for the different applied loading conditions.

Figure 10a shows the fatigue cracks propagation plot measured as a function of the number of cycles for case simulation 5. The cracks started to propagate around 153 flight times, and increase rapidly until 1436 FHs. From the 14,336 cycles over 3692 FHs, the crack propagation occurred linearly with a low crack propagation rate, while after 4692 cycles, the crack propagation increased rapidly up to 4783 cycles until it reached the defined crack threshold length of 10 mm. The graph trend of the current model results was compared with the crack propagation curve in the literature [27] for a composite. It was found that compared with the composite crack propagation trend in the literature, the current numerical model showed a similar trend of crack propagation.

**Figure 10.** (**a**) Crack propagation plot of the current numerical model and (**b**) a comparison with the literature trend of the composite fatigue crack propagation curve [27].

#### *2.2. Sensitivity Analysis and Design of Experiments (DOE)*

FRCPs subjected to cyclic loading are most likely to fail with fatigue delamination crack growth. Many factors can affect the fatigue delamination growth, such as the constituent material parameters, geometry, and environmental conditions. However, the most common practice is to check the effect of mechanical parameters on the fatigue delamination behavior of composite laminates. For this purpose, sensitivity analysis [28] was undertaken to assess the sensitivity of crack growth to uncertain mechanical parameters. Sensitivity analysis can be used as a tool to understand how uncertain inputs can affect a model's performance. Sensitivity analysis is a systematic assessment method that is generally performed to assess the impact of individual input uncertain parameters on the model output response. It is an essential part of every risk assessment analysis that seeks to learn things such as how the model outputs change with the change in inputs and how it affects the model output decisions. The sensitivity analysis enhances the overall confidence in the risk assessment. Further, it improves the prediction of the model by studying the model response to the change in input variables and by analyzing the interaction between the variables. The knowledge of these sensitive parameters can help to better comprehend the fatigue delamination behavior and can pinpoint the direction of an optimal composite design. In this study, the effect of varying the mechanical properties was studied to examine the fatigue delamination behavior. Table 1 shows that a total of eight mechanical properties and two fatigue parameters were considered to examine the effect of fatigue delamination behavior. The parameters were varied by +2% of the mean value, and the model output fatigue delamination growth was computed. It was observed that E1 and G23 showed the most sensitive behavior compared with the other parameters. Figure 11 shows the relative error plot.

After pinpointing the most sensitive mechanical inputs, the design of experiments (DOE) was carried out by using Latin hypercube sampling (LHS) [29]. For the generation of DOE scenarios, input factors should be defined. In the case of fatigue crack propagation in the tail wing structure, two input factors (E1 and G23) were chosen. The error variation of +2% was kept for random sampling for the generation of thirty DOE samples, as shown in Table A1 of Appendix A. Figure 12 shows the fatigue crack propagation curves combined into a single plot. It was observed that for a crack delamination length threshold of 10 mm, the number of flight times range from approximately 2500 to 4600.

**Figure 11.** Sensitivity analysis plot representing the relative error of each parameter with respect to the exact simulation parameters fatigue behavior.

**Figure 12.** Fatigue delamination behavior of DOE data generation scenarios.


*Supporting open minds since 2005*

Zeolites - New Challenges http://dx.doi.org/10.5772/intechopen.77482 Edited by Karmen Margeta and Anamarija Farkaš

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Nandini Das, Jugal Kishore Das, Peng Wu, Hao Xu, Adalgisa Tavolaro, Silvia Catalano, Palmira Tavolaro, Jacques Fraissard, Mykhaylo Petryk, Mykola Ivanchov, Daniel Canet, Sebastien Leclerc, Yashonath Subramanian, Shubhadeep Nag, Camelia Tulcan, Simona Marc, Karmen Margeta, Anamarija Farkaš

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**Peripheral Blood Mononuclear Cell Metabolism Acutely Adapted to Postprandial Transition and Mainly Reflected Metabolic Adipose Tissue Adaptations to a High-Fat Diet in Minipigs**

#### **Yuchun Zeng, Jérémie David, Didier Rémond, Dominique Dardevet, Isabelle Savary-Auzeloux and Sergio Polakof \***

INRA, UNH, Unité de Nutrition Humaine, CRNH Auvergne, Université Clermont Auvergne, F-63000 Clermont-Ferrand, France<EMAIL_ADDRESS>(Y.Z<EMAIL_ADDRESS>(J.D<EMAIL_ADDRESS>(D.R<EMAIL_ADDRESS>(D.D<EMAIL_ADDRESS>(I.S.-A.) **\*** Correspondence<EMAIL_ADDRESS>Tel.: +33-(0)-473-624-895; Fax: +33-(0)-473-624-638

Received: 29 September 2018; Accepted: 15 November 2018; Published: 21 November 2018

**Abstract:** Although peripheral blood mononuclear cells (PBMCs) are widely used as a valuable tool able to provide biomarkers of health and diseases, little is known about PBMC functional (biochemistry-based) metabolism, particularly following short-term nutritional challenges. In the present study, the metabolic capacity of minipig PBMCs to respond to nutritional challenges was explored at the biochemical and molecular levels. The changes observed in enzyme activities following a control test meal revealed that PBMC metabolism is highly reactive to the arrival of nutrients and hormones in the circulation. The consumption, for the first time, of a high fat–high sucrose (HFHS) meal delayed or sharply reduced most of the observed postprandial metabolic features. In a second experiment, minipigs were subjected to two-month HFHS feeding. The time-course follow-up of metabolic changes in PBMCs showed that most of the adaptations to the new diet took place during the first week. By comparing metabolic (biochemical and molecular) PMBC profiles to those of the liver, skeletal muscle, and adipose tissue, we concluded that although PBMCs conserved common features with all of them, their response to the HFHS diet was closely related to that of the adipose tissue. As a whole, our results show that PBMC metabolism, particularly during short-term (postprandial) challenges, could be used to evaluate the whole-body metabolic status of an individual. This could be particularly interesting for early diagnosis of metabolic disease installation, when fasting clinical analyses fail to diagnose the path towards the pathology.

**Keywords:** peripheral blood mononuclear cells; postprandial metabolism; high fat–high sugar diet; minipig; adipose tissue; biomarkers

#### **1. Introduction**

Peripheral blood mononuclear cells (PBMCs) have been widely used for more than 10 years now as a valuable tool to provide reliable biomarkers of health and diseases [1–3]. Although very recent studies have approached PBMC metabolism from a more functional point of view, such as metabolomics studies [4,5], most of them are based on transcriptomics analyses only [1,6,7]. Very little is actually known about the functional, i.e., biochemical-level, metabolism of PBMCs following nutrition-related interventions. Previous studies showed for specific individual white cell populations (such as lymphocytes and macrophages), these rapidly dividing cells had all the necessary biochemical machinery to utilise the most abundant energy substrates, such as glucose, lipids, and some amino acids, particularly glutamine [8]. More recent studies based on enzyme activities carried out on dogs, cats, and cattle confirm that PBMCs have an active metabolism that could be similar to that

of other organs [9–11]. However, very little is known about PBMC metabolism in minipigs, as most of the studies are focused on immunological approaches. Only a few papers have explored the pig PBMC transcriptomic response to diverse conditions, such as mitogenic stimulation, [12], growth performance [13], stress [14], or leptin administration [15]. Thus, functional metabolic studies are lacking in minipigs, especially with respect to nutritionally-related metabolic diseases.

An aspect of interest in PBMCs is that they circulate permanently and through all body parts in the blood stream, being subjected to any variation of this fluid composition, including those related to fluctuations in circulating nutrients, substrates, and hormones [16]. All these molecules can then potentially impact PBMC metabolism and deeply modify their gene expression profile. On chronic exposure to a modified nutritional environment, PBMC transcriptomics have been used to discover valuable biomarkers of many metabolism-related diseases, such as diabetes [17], obesity [3], or insulin resistance [18]. Despite the current knowledge about the capacity of PBMCs to be imprinted at the long-term molecular level by altered nutritional conditions, it is not clear whether PBMC metabolism could be representative of nutritionally-induced short-term and rapid modifications in blood or tissue metabolites and metabolic activity. The postprandial phase (i.e., the period that follows meal intake) represents one of the most challenging phenomena in whole-body metabolism taking place in healthy conditions; it occurs every day, several times a day. Following meal intake, body metabolism must adapt to major changes in blood composition: the increased levels of circulating nutrients could be harmful remain elevated for a long time, and on the other hand, levels of several hormones increase for just few minutes after the nutrient arrival. As do all the other organs, PBMCs must adapt to these changes [19]. More importantly, while the contact of most of the organs with circulating nutrients and hormones will depend on vascularisation and changes in blood circulation, PBMCs are directly and permanently affected by the blood, as they are surrounded by the fluid. Changes in blood composition may be then particularly sharp for PBMCs, forcing them to rapidly adapt to these changes as suggested in transcriptomic-based postprandial studies [20,21]. For example, this has been demonstrated in studies on humans [22] and rats [16] during fasting, at least at the gene expression level. Whether this flexibility to adapt to a meal is compromised in PBMCs as has been shown for the whole body and individual organs during the onset of many metabolic diseases, such as diabetes or obesity [23,24], remains to be elucidated.

The main objective of the present study was to determine if PBMC metabolism at the biochemical and molecular levels could adapt to different nutritional conditions known to alter the profile of circulating metabolites and hormones, and to induce major changes in whole body metabolism. We submitted Yucatan minipigs to different nutritional challenges, including a meal test (a meal regular or high in fat and sugar, HFHS) and long-term HFHS feeding. In the first case, we aimed at determining whether PBMCs were able to adapt rapidly to changes occurring after meal intake and if their metabolic adaptive capacity might provide information about the capacity of the individual to handle the meal. In the second case we aimed at studying the long-term metabolic footprint of HFHS feeding on PBMC metabolism and to compare it to the metabolism of other tissues, including the liver, skeletal muscle, and adipose tissue (AT). For the postprandial challenges, the biochemical approach (enzyme activities) was chosen to explore the short-term adaptation (hours). For the long-term trial (months), both enzyme activities and mRNA levels were assessed to explore the metabolic adaptations installed in the fasting state during HFHS feeding.

#### **2. Materials and Methods**

#### *2.1. Animals*

The study involved 10 female adult (6 month-old) Yucatan mini-pigs (30 ± 1 kg). They were housed in subject pens (1 × 1.5 m) in a ventilated room with controlled temperature (21 ◦C) and regular light cycle (L12:D12). They were fed once daily with 400 g/day of a concentrate feed containing 17.5% proteins, 3.2% fat, 4.3% cellulose, and 5.2% ash (Porcyprima; Sanders Centre Auvergne, Aigueperse, France) and had free access to tap water. All procedures were in accordance with the guidelines formulated by the European Community for the use of experimental animals (L358-86/609/EEC, Council Directive, 1986).

#### *2.2. Experimental Procedure*

#### 2.2.1. Postprandial Meal Test

The postprandial meal test trial consisted in the ingestion of 400 g of a regular (control) or a high fat-high sugar (HFHS) meal after an overnight fasting period. Five animals were involved in the trial, consuming first the control diet, and after one week of wash-out, the HFHS diet.  Animals ingested the whole mixture in no more than 10 min. Blood was collected though an arterial catheter before (T0) and then 2, 4, and 7 h after the meal.

#### 2.2.2. High Fat–High Sucrose Long-Term Trial

The HFHS trial consisted in the ingestion of an obesogenic diet during two months. Five animals were involved in the trial and were fed twice a day (500 g). Arterial blood was sampled through a permanent catheter after a fast of 24 h (day 0) and after 7, 14, 30, and 60 days of diet consumption also at the fasting state. Liver, skeletal muscle and AT samples were collected during the catheter surgery procedure (before the trial) and by the end of the 60 days. In both cases, minipigs were under deep anaesthesia and samples were immediately frozen at −80 ◦C for further analyses.

#### *2.3. Analytical Procedures*

#### 2.3.1. Blood Treatment and PBMC Collection

At each point, 10 mL of blood were collected on a dry syringe (without anticoagulant) and then gently transferred to a tube CPT™ tube (BD vacutainer) containing a polyester gel and a density gradient liquid (FICOLL™ Hypaque™ solution). This filter allows cell separation during a single centrifugation step. Briefly, blood was centrifuged at 1650 g during 20 min at 20 ◦C. After centrifugation, the plasma was collected and quickly stored at −80 ◦C until further analyses. The layer containing the PBMC was collected (buffy coat), washed twice with PBS solution and centrifuged at 300 g during 15 min at 20 ◦C. After washing, the PBMC were pelleted, the PBS discarded and cells suspended on RNLater™ (for further mRNA analysis) or a lysis solution.

#### 2.3.2. Plasma Insulin and Metabolite Determination

Glucose, triacylglycerol (TG), lactate, and urea levels were enzymatically measured using commercial kits on an automotive ABX Pentra 400 (Horiba Medical, Grabels, France) test system. Plasma insulin levels were assessed using a commercial ELISA kit (Mercodia, Uppsala, Sweden). Branched-chain amino acids (BCAA) were assessed enzymatically as described in Polakof et al. 2017 [25].

#### 2.3.3. Measurements of Enzyme Activities

For enzyme activities, PBMC were immediately homogenized on the lysis solution (20 mM Tris, pH 7.4, 250 mM sucrose, 2 mM EDTA, 10 mM β-mercaptoethanol, 100 mM NaF, 0.5 mM EDTA). The homogenate was centrifuged for 20 min at 10,000× *g* and the supernatant immediately used. Enzyme activities were determined by spectrophotometry using a microplate reader (Infinite® 200 PRO NanoQuant, Tecan, Grödig, Austria), based on mini-pigs methods adapted to PBMC [23,25,26], including hexokinase (HK), pyruvate kinase (PK), glucose-6-phosphate dehydrogenase (G6PD), malate dehydrogenase (MDH), lactate dehydrogenase (LDH), glutamate dehydrogenase (GDH), glutaminase

P-dependent, branched-chain amino acid aminotransferase (BCAT) and aspartate aminotransferase (AspAT).

#### 2.3.4. Western Blot Analyses

Samples were homogenized as described above and for each sample, total protein lysates (4 μg) were subjected to SDS-PAGE, electrotransferred on a PVDF membrane and probed with the indicated antibodies: total serine/threonine kinase protein kinase B (AKT) and phospho AKT at serine 473 (pAKT) and total eEF2-α and phosphor eEF2-α at threonine 56 (peEF2-α) (Cell Signaling Technology, Ozyme, St Quentin-en-Yvelines, France). After washing, membranes were incubated with an IRDye infrared secondary antibody (LI-COR Biotechnology, Lincoln, NE, USA). Bands were visualized by infrared fluorescence using the Odyssey imaging system (LI-COR Inc. Biotechnology, Lincoln, NE, USA) and quantified by Odyssey infrared imaging system software (version 1.2).

#### 2.3.5. PCR Analyses

Total RNA was extracted using RNEasy Mini Kit® (Qiagen) and mRNA levels were determined by RT-PCR. RNA quality was verified on 1% agarose ethidium-bromide stained gel. cDNA was generated from 500 ng RNA using the High Capacity cDNA Reverse Transcription Kit (Life Technologies, Villebon-sur-Yvette, France). Real-time PCR was performed in the CFX96 Touch™ Real-Time PCR Detection System (BIO-RAD, Hercules, CA, USA) as in [23]. Primers were designed so that they are overlapping an intron (Primer3 software; Whitehead Institute for Biomedical Research/MIT Center, Cambridge, MA, USA) using known sequences in nucleotide databases. Primers sequences are available in [26].

#### *2.4. Statistical Analyses*

Data from the postprandial challenges were analysed using a repeated measures two-way ANOVA test (time and diet as variables). The PBMC and plasma parameters from the HFHS trial were analysed using a one-way ANOVA test followed by post-hoc Holm-Sidak. The *p*-value significance threshold for all factors was set to 0.05.

The differences between the D0 and D60 HFHS trial in liver, skeletal muscle and AT enzyme activities and mRNA levels were analysed using a Mann–Whitney nonparametric test using for the post hoc analysis the Student–Newman–Keuls test (SigmaPlot 12, Systat Software, San Jose, CA, USA). The *p*-value significance threshold for all factors and ions was set to 0.05. *p*-values between 0.05.

#### **3. Results**

#### *3.1. Short-Term Control vs HFHS Postprandial Trial*

Glucose (insulin, glucose, lactate), lipid (TG), and nitrogen (urea, BCAA) metabolism were evaluated before and after the control and the HFHS meal based on plasma hormone and metabolite assessment in order to evaluate the postprandial metabolic phenotype of minipig followings the meal (Figure 1). Plasma glucose levels increased (between 2 and 4 h after the meal) after the control meal intake, recovering to basal level 7 h after the meal. No changes with time were observed following the HFHS meal, although plasma glucose levels were lower between 2 and 4 h than after the control meal. Plasma insulin levels showed a very important variability among individuals to put in evidence a time effect. However, 2 h after the meal, a tendency (*p* < 0.081) to have higher levels than before the meal was observed, which is in agreement with the changes observed in the plasma glucose profile. No differences were found among the animals consuming the different meals. Lactate plasma levels, a good indicator of glucose utilisation at the whole body level, increased significantly after both meal tests. However, the increase observed in the control group was more important, at least 2 h after the meal. Plasma TG levels increased also after the control and HFHS meals, but the maximum values were different among the groups. For the control group the peak was observed 2 h after the meal (+355%), while for the HFHS group it was delayed up to 4 h (+281%), most likely reflecting differences in the meal digestion and absorption. Postprandial urea plasma levels (indicative amino acid catabolism at the whole body level) showed different patterns: while in the control group levels steadily increased up to 151% at 4 h when compared to the fasting point, in the HFHS group no changes were observed. While BCAA levels after the control meal slightly increased (+12%), following the HFHS meal, their concentration was reduced up to 25% 7 h after the meal intake, suggesting their withdrawal from the blood compartment exceeded their appearance following the digestion process.

**Figure 1.** Plasma parameters in Yucatan mini-pigs fed either a control or a high fat–high sucrose (HFHS) test meals. Results are expressed as means + SEM (*n* = 5) and were analysed using a repeated measures 2-way ANOVA test. Different letters indicate significant differences between sampling points for a given meal test. \* Significant different for a given sampling point between the control and the HFHS meals (*p* < 0.05). BCAA: branched-chain amino acids.

Enzyme activities involved in glucose and amino acids metabolism in PBMC (Figure 2) were assessed in order to determine if they were affected by the meal (postprandial period) and its composition (regular vs. HFHS). We aimed also to explore if such changes could be related to the circulating metabolites and hormones described above. Two opposite profiles were observed: enzymes which activity increased after the control meal, including those participating in the glucose phosphorylation (HK, +300%), glycolysis (PK +400-600%, LDH, +150%), pentose phosphate pathway (G6PD, +200%), and amino acid catabolism (BCAT +125%, GDH, +140%); and enzymes for which activity was inhibited by the meal, such as those participating in amino acids metabolism, including glutaminase (−50%) and AspAT (−50%). For all of them, the response to the meal was further

blunted when the HFHS test was performed. MDH activity (enzyme involved in the Krebs cycle) was not modified by the regular meal, but it was inhibited (−75% at 2 h) following the HFHS test, suggesting that those changes were meal-specific. Finally, we also explored the insulin (Akt) and protein synthesis (eEF2α) signalling pathways in order to evaluate the capacity of PBMC to transduce the nutritional stimuli from the meal into intracellular information able to regulate the glucose and protein metabolisms (Figure 3). In both cases, their phosphorylation statuses increased following the control meal (about +200% for both proteins), but no changes were observed after the HFHS test.

#### *3.2. Long-Term HFHS Trial*

After two months of HFHS feeding minipigs developed an obesity-like phenotype, with a significant increase in body weight (from 31.5 ± 1.4 kg to 44.7 ± 1.7 kg), most likely as the consequence of fat deposition at the visceral and subcutaneous adipose tissue [23]. The main metabolic features associated to this phenotype are described in Table 1. No changes were observed in glucose and lactate levels, while TG concentrations slightly increased between day 7 and 14. Insulin levels increased significantly from day 7 (about three times from day 0), and remained elevated up to the end of trial. In contrast, urea plasma levels were reduced from day 7 onwards (about 1.5 times) up to day 60. Finally, the inflammation status of minipigs was evaluated by assessing the CRP circulating levels at the beginning and at the end of the trial. CRP levels increased significantly from 0.52 ± 0.10 up to 0.99 ± 0.21 mg/L following the two months of HFHS feeding.

**Figure 2.** Hexokinase (HK), pyruvate kinase (PK), lactate dehydrogenase (LDH), glucose 6-phosphate dehydrogenase (G6PD), malate dehydrogenase (MDH), branched chain amino-acid transaminase (BCAT), glutaminase P-dependent, aspartate aminotransferase (AspAT) and glutamate dehydrogenase (GDH) alanine transaminase activities in PBMCs from Yucatan mini-pigs fed either a control or a high fat–high sucrose (HFHS) test meals. Enzyme activity units (mU) are defined as nmol of substrate converted to product, per min, at 37 ◦C and per mg protein. Results are expressed as means + SEM (*n* = 5) and were analysed using a repeated measures two-way ANOVA test. Different letters indicate significant differences between sampling points for a given meal test. \* Significantly different for a given sampling point between the control and the HFHS meals (*p* < 0.05). PMBC: peripheral blood mononuclear cell.

**Figure 3.** Phosphorylation levels of Akt Ser473 and eEF2-α Thr56 in PBMCs and S6 Ser235/236 from Yucatan mini-pigs fed either a control or a high fat–high sucrose (HFHS) test meals. Analysis was made by Western blot and levels of phosphorylated protein were normalized to the levels of the respective total protein (Akt Ser473 and eEF2-α). Results are expressed as means + SEM (*n* = 5) and were analysed using a repeated measures two-way ANOVA test. Different letters indicate significant differences between sampling points for a given meal test. \*Significant different for a given sampling point between the control and the HFHS meals (*p* < 0.05).

**Table 1.** Plasma fasting metabolites in Yucatan minipigs fed a high fat–high sucrose diet (HFHS) over 2 months.

Results are expressed as means + SEM (*n* = 5) and were analysed using a one-way ANOVA test followed by post-hoc Holm-Sidak. Different letters indicate significant differences between the sampling points (*p* < 0.05).

Once the metabolic phenotype of minipigs evaluated during the 2 months of HFHS feeding, we aimed at determining if the PBMC metabolism was able to respond to the modifications induced by the diet at the circulating level. We explored the PBMC metabolism at both, the enzyme activity and mRNA levels, as shown in Figures 4 and 5, respectively. Overall, most of the explored enzymes increased their activities from day 7, recovering progressively their basal levels after 2 months of feeding. Only glutaminase and AspAT activities were reduced by the HFHS feeding (−50%), also from day 7. The tendency was conserved up to the end of the trial. Concerning the molecular analyses, several genes resulted up-regulated by the long-term HFHS feeding, including *acox, fasn, bckdhb* and *bckdk*, for which levels increased progressively with time. Only *dld* mRNA levels increased at day 7 and remained stable up to the end of the trial. *Bcat* and *bckdhb* mRNA levels were down-regulated by the HFHS consumption, while no changes were observed on *srebpf2* levels. Finally, *srebpf1* levels were transiently reduced between day 7 and 30 (−40%) but recovered the initial levels at day 60.

The third objective of the present study was to compare PBMC metabolic potential to those of other organs, such as the liver, the skeletal muscle and the AT. We therefore explored the metabolism of those tissues before and 2 months after HFHS feeding. As for the PBMCs, we choose a double approach, including biochemical (glycogen levels, enzyme activities) and molecular (mRNA levels) targets as presented in Figures 6 and 7, as well as in Table 2, respectively. At the hepatic level, the HFHS feeding resulted in increased glycogen levels (+24-fold), and in enzymes participating at the gluconeogenesis (FBPase, +3-fold), lipogenesis (FAS, +5-fold), lipid oxidation (Acox, +2.5-fold) and amino acids catabolism (GDH, +3-fold). Other enzyme activities were inhibited by the HFHS feeding, including those participating at the glycolysis (HK, PK, about −4-fold), the pentose phosphate pathway (G6PD, −1.8-fod), and amino acid transamination (AspAT, −1.3-fod). Except for the AspAT activity (which was inhibited (−2-fold)), all the explored enzymes were up-regulated in the adipose tissue, including HK (+5-fold), G6PD (+3-fold) and GDH (+2-fold). At the muscle level, glycogen levels increased by 2-fold after 2 months of HFHS feeding, while HK, GDH, and AspAT activities were reduced.

Concerning the mRNA levels of proteins involved in glucose, lipids and amino acids metabolism are at the hepatic level, the general tendency was the reduction of expression induced by the HFHS feeding including those genes involved in glucose metabolism such as *hk1* (−1.5-fold) and *g6pc* (−2-fold), or in lipid oxidation like *cptl* (−5-fold) or lipogenesis (*acly*; −1.3-fod). The only exception was another gene involved in lipogenesis, *fasn*, which mRNA levels were dramatically (+23-fold) increased by the HFHS diet intake. Only minor changes were observed in the skeletal muscle, with a 50% reduction it the mRNA levels of the *cptm*, involved in β-oxidation. Several genes were up-regulated by the HFHS feeding in the AT, including those participating at the glucose transport, like *slc2a4* (+6-fold), *hk1* (+1.4-fold), or lipogenesis, like *acly* (+10-fold) and *fasn* (+9-fold). In contrast, the hepatic isoform of CPT (*cptl*) was down-regulated (−5-fold) the HFHS feeding.

**Figure 4.** Hexokinase (HK), pyruvate kinase (PK), lactate dehydrogenase (LDH), glucose 6-phosphate dehydrogenase (G6PD), malate dehydrogenase (MDH), branched chain amino-acid transaminase (BCAT), glutaminase P-dependent, aspartate aminotransferase (AspAT), and glutamate dehydrogenase (GDH) alanine transaminase activities in PBMC from Yucatan mini-pigs fed a high fat-high sucrose (HFHS) diet for 2 months. Samples were obtained after an overnight fast period before (0) and 7, 14, 30, and 60 days after HFHS feeding. Enzyme activity units (mU) are defined as nmol of substrate converted to product, per min, at 37 ◦C and per mg protein. Results are expressed as means + SEM (*n* = 5) and were analysed using a one-way ANOVA test followed by post-hoc Holm-Sidak. Different letters indicate significant differences between the sampling points (*p* < 0.05).

**Figure 5.** Hexokinase (*hk1*), acyl-coenzyme A oxidase (*acox*), fatty acid synthase (*fasn*), sterol regulatory element binding protein-1c (*srebf1c*), peroxisome proliferator-activated receptor alpha (*ppara*), sterol regulatory element binding protein-2 (*srebf2*), branched-chain alpha-keto acid dehydrogenase alpha/beta (*bckdha/b*), dihydrolipoyl dehydrogenase (*dld*), and branched chain ketoacid dehydrogenase kinase (*bckdk*) mRNA levels in PBMCs from Yucatan mini-pigs fed on high fat-high sucrose (HFHS) diet for 2 months. Samples were obtained after an overnight fast period before (0) and 7, 14, 30, and 60 days after HFHS feeding. Results are expressed as means + SEM (*n* = 5) and were analysed using a one-way ANOVA test followed by post-hoc Holm-Sidak. Different letters indicate significantdifferencesbetweenthesamplingpoints(*p*<0.05).

**Figure 7.** Glycogen levels, hexokinase (HK), pyruvate kinase (PK), glucose 6-phosphate dehydrogenase (G6PD), aspartate transaminase (AspAT), glutamate dehydrogenase (GDH) activities in adipose tissue and skeletal muscle samples from Yucatan mini-pigs fed a high fat–high sucrose (HFHS) diet for 2 months. Enzyme activity units (mU) are defined as nmol of substrate converted to product, per min, at 37 ◦C and per mg protein. Glycogen levels are expressed in μmol of glycosyl units/g wet tissue. Results are expressed as means + SEM (*n* = 5) and were analysed using a *t*-student test. \*, significantly different from the D0 (*p* < 0.05).

**Table 2.** mRNA levels of proteins involved in glucose and lipid metabolism in the liver, adipose tissue and skeletal muscle samples from Yucatan minipigs fed

and are indicated as fold variation of the control group. \* significantly different from D0 (*p* < 0.05) among groups. *gck*, glucokinase; *pck1*, phosphoenolpyruvate kinase; *g6pc*, glucose6-phosphatase; *acly*, ATP-citrate lyase; *fasn*, fatty acid synthase; *srebf1c*, sterol regulatory element binding protein-1c; *cpt1-l/m*, carnitine palmitoyltransferase-liver/muscle isoform; acyl-coenzyme A oxidase; *ppara*, peroxisome proliferator-activated receptor alpha; *hk-1*, hexokinase 1.

*acox*,

 on a

#### **4. Discussion**

In the present study we show for the first time that the metabolism of mini-pig PBMC can be altered at the biochemical and molecular levels and that it was closely related to the AT profile, at least in the context of a long-term HFHS feeding. Further, we showed that the PBMC metabolism, particularly at the biochemical level, can be modulated at the postprandial level.

#### *4.1. PBMC Metabolism Is Highly Reactive to the Meal, But Its Response Is Blunted by the Intake of a HFHS Meal*

After meal intake, the body must adapt to the greater influx of nutrients in a very short period of time (from minutes to a couple of hours). Although several studies have previously explored the postprandial response of PBMC, they were focussed on transcriptomics analyses only [20,21,27]. Given the very short-term response needed after the meal, we choose to explore the postprandial metabolism at the biochemical and signalling levels rather than at the molecular level, which as far as we are aware has never been done before. The objective was therefore to elucidate if PBMC metabolism could respond in the very short-term to a nutritional stimulus and provide valuable information about changes at the whole body metabolism and metabolic flexibility that could not be visible at the fasting state [16,28]. In our study, PBMC metabolism was indeed highly responsive to the control meal challenge. The glucose phosphorylation potential and further channelling through the glycolysis was strongly increased, highlighting the importance of glucose for fuelling PBMC metabolism [29]. This was further supported by the meal-stimulated phosphorylation of Akt, a major actor on the insulin signalling pathway. Other metabolic processes were also stimulated by the meal, as the NADPH production to support lipogenesis or nucleotide biosynthesis through the pentose phosphate pathway.

PBMCs not only rely on glucose as energy source, as glutamine utilization in these cells can be even greater than that of glucose [8]. In our study glutaminase activity was significantly reduced following the meal, in line with its increased activity in lymphocytes from starved rats [29]. The fact that the AspAT activity followed the same profile than the glutaminase, further confirms that this enzyme rather than GDH is mainly responsible of the glutamate to α-ketoglutarate conversion in PBMCs. However, PBMCs do not only use glutamine for energy purposes, as the production of non-essential amino acids (such as alanine and aspartate) via the transaminases for biosynthetic purposes is of great importance for this kind of highly proliferating cell [8]. Following the meal, when circulating amino acid levels increase, PBMCs would rather rely on them for biosynthesis processes, reducing the demand from transaminases and resulting in an increase in the glutamate channelling through the GDH reaction [30], explaining the increased GDH activity in our study. Finally, the fact that the glucose utilisation was enhanced in response to the meal, whereas glutamine utilisation was reduced, strongly suggests that during the fasted-to-fed transition a metabolic shift allows PBMC to switch from glutamine to glucose utilisation [31].

During the HFHS meal test, we surprisingly found that the PBMC response was often blunted or in some cases delayed when compared to the regular test meal. The postprandial trial aimed at challenging the metabolic response of PBMC, which has been achieved with the control meal. By providing for the first time an HFHS meal to the same animals, our goal was to further alter the PBMC environment in terms of composition and time-course appearance of nutrients and hormones. Thus, the kinetics of most of the plasma parameters were altered following the HFHS meal, most likely due to the impact of the diet on gut physiology (motility, gastric emptying) and hormone release (CCK, PYY, GLP-1) [32]. Thus, despite a higher content of sugar than in the regular meal, the HFHS consumption did not result in a significant postprandial increase in blood glucose levels. Accordingly, the same lack of responsiveness was observed in the insulin signalling pathway, resulting (together with the low glucose available) in a non-stimulated glucose utilisation, and supporting the idea that PBMC strongly depend on circulating substrates, particularly glucose. This could explained in part by a delayed and reduced excursion of glucose and insulin mediated by a slower gastric emptying

and reduced gut hormone secretion, as previously observed in humans subjected to high fat diet tests [33–35].

Unlike after the control meal, following the HFHS intake we did not longer observe the fasting-to-fed transition between glucose and glutamine utilisation. This suggests that PBMC metabolism has adapted to the reduced glucose levels and continue to rely on glutamine, such as during the post-absorptive period. In contrast to other circulating metabolites, BCAA levels following the HFHS meal showed reduced levels during the postprandial period, which resulted in a lower transamination potential as well, likely reducing the flux of ketoacids up to the Krebs cycle. In agreement with this, the phosphorylation status of the protein eEF2α, responsible for determine the end of the translation and sensitive to the leucine signal role, remained unchanged after the HFHS meal. This may represent another sign of the altered response to the meal stimulus. Another symptom of impaired normal metabolic activity after the HFHS meal was the reduction on MDH activity. Since MDH plays crucial roles in the malate–aspartate shuttle, essential for coupling activation of mitochondrial and energy production [36], a decrease in MDH activities may suggest a depression of the transfer of NADH, and less ATP production in mitochondria.

#### *4.2. Time-Course Changes in PBMC Metabolism during Long-Term High Fat Feeding*

The second goal of our study was to evaluate if the metabolism of PBMC could be modified by a long-term nutritional change, such as HFHS feeding-induced obesity. As in our previous study focused on tissue/organ metabolism [23], we observed in the present study that the same major metabolic changes occurred also in PBMC after only one week of HFHS feeding. However, unlike during the short-term stimulation (postprandial period) PBMC do not seem to rely on available circulating metabolites during the long-term HFHS imprinting. Thus, despite the lack of changes in post-absorptive blood glucose levels, PBMC glucose metabolism was enhanced, as previously shown in a PBMC transcriptome-based study comparing lean vs. obese subjects [20]. It is known that alterations in postprandial glucose kinetic precedes those at the fasting state in the insulin resistance installation [37]. The increased glucose metabolism at the fasting state observed in the circulating PBMC may be the result of a long-term important glucose postprandial excursions (as supported by the hyperinsulinemia), exposing the circulating cells to elevated postprandial glucose levels. If our results are further investigated in future studies, alterations in these enzyme activities could constitute early events signalling the beginning of glucose alterations leading to insulin resistance, even when fasting blood glucose levels remain unchanged.

PBMCs seem to also have very active lipid metabolism [22]. Thus, genes involved in lipid catabolism, such as *acox* and *ppara*, were up-regulated by the long-term HFHS feeding, suggesting that minipig PBMC metabolism adapted to the increased dietary lipids, as previously observed in PBMCs from obese rats fed on cafeteria diets [2,38]. On the other hand, markers of lipogenesis (*fasn, srebpf1*) also resulted up-regulated. A recent study showed that lipogenesis was active in PBMCs and that was highly dependent on glucose [39], a strong activator of lipogenic genes [40]. This effect of glucose on de novo lipid synthesis represents a common feature for lipogenic organs, such as the liver or the AT from HFHS-fed animals [28,41,42].

As far as we are aware, the metabolism of amino acids has never been explored on PBMC from obese animals. After two months of HFHS feeding, both glutaminase and AspAT activities resulted rapidly (one week) down-regulated, suggesting that amino acids use for energy was reduced in detriment of other alternative fuels like glucose and lipids [23]. BCAA related-enzyme activities and mRNA levels were also reduced by the end of the trial, supporting the idea of a progressively reduction of BCAA catabolism from obese minipigs. We and other have shown that in obese and insulin resistant animal models, BCAA circulating levels increased with time [25,43]. Interestingly, the increased transamination potential during the first weeks of HFHS feeding could be the consequence of a metabolic adaptation to the progressively increase in BCAA levels. However, by the end of the trial, the potential to catabolise BCAA was blunted, in agreement with a defective oxidative deamination observed in the adipose tissue of HFHS-fed minipigs [25].

#### *4.3. The PBMC Metabolism Rather Resembled that of the Adipose Tissue*

As explained above, PBMC metabolism is different from any other organ, as these cells are actually permanently stimulated by changes in circulating blood metabolites and hormones. Despite this, we demonstrated that their metabolism has many common features with several major organs of the body. The second objective of the present study was therefore to compare PBMC response to the long-term HFHS meal to that of the liver, skeletal muscle and the AT.

We observed that an adaptive strategy was settled at the hepatic level in order to handle the excess of nutrients and energy brought by the HFHS diet. Thus, those pathways involved in glucose utilisation, such as glycolysis and pentose phosphate pathway were reduced, while lipid oxidation potential increased, illustrating a metabolic switch aiming at giving the priority to the more abundant energy substrates available. In accordance with this, we observed that the liver increased its capacity to store the excess of energy in the form of lipids (lipogenesis) and glycogen. Of note, the increased FBPase activity and reduced G6Pase potential strongly suggests that the glucose produced via the gluconeogenesis was further stored as glycogen rather than being exported into the blood stream. Unlike the liver, the overall metabolic features observed in the skeletal muscle and the AT suggest that both organs enhanced the uptake, utilisation, and storage of glucose. Two other catabolic features were also different from those of the liver, including lipids and amino acids oxidation pathways, that were reduced in the muscle and the AT. As for the liver, lipogenesis potential was strongly up-regulated in the AT. The integrative view of the HFHS minipig physiology suggests therefore that at the whole-body level, inflammation was settled. Despite this, the metabolism seemed flexible enough to adapt and kept blood glucose levels into within the physiological range. This was achieved through a coordinated increased in glucose uptake, utilisation and storage from all the explored organs in order to remove as much as possible glucose from the blood circulation. Further, the liver and the AT increased also their potential of other highly consuming glucose pathways, such as *de novo* lipogenesis. Finally, the lipid handling seemed to be organ-dependent, as the liver increased the oxidation potential of lipids, while the muscle and the adipose tissue showed an opposite trend.

When compared to the results discussed above, the metabolic response observed in the PBMCs in the obese minipig at the fasting state seems to be coherent with the adaptations reported in the major organs involved in the intermediary metabolism. As in a previous study in hamsters [44] our results show that PBMC metabolism does not reflect that of the liver. In contrast, the metabolic profile of PBMC evaluated at the molecular and biochemical levels was particularly close to the one observed in the AT. This is in line with similar conclusions draws in several studies in humans [45] and laboratory animals [16,44], specially concerning lipid metabolism [46]. In contrast to this, other metabolic features, like pentose phosphate potential seems to have a PBMC-specific behaviour, with a strong dependence on glucose uptake and phosphorylation and a lower induction capacity when compared to the AT. The responsiveness of PBMCs, particularly at the biochemical level could be then potentially used to explore the whole body metabolism in response to different dietary interventions or to evaluate the functional metabolic status of an individual with a single blood sample.

#### **5. Conclusions**

As a whole, the evaluation of the metabolic response to a control test meal of PBMC showed for the first time at the biochemical level that these cells were able to modify and adapt in a very short period (often < 3 h) their metabolic activity under the influence of circulating nutrient and hormones. Most of the changes recorded showed that PBMCs relayed glutamine metabolism during the post-absorptive period, and that they switched to glucose when quantity of carbohydrates from the diet increased in the circulation. Interestingly, we showed that major and fast changes in the PBMC environment induced by the HFHS during the postprandial period were able to trigger in PBMCs

the necessary metabolic changes to adapt to this challenge. Finally, the exploration of the PBMC metabolism in long-term HFHS feeding confirmed that the regulation pattern observed in PBMCs fits with that expected in tissues involved in energy balance. It would be therefore reasonable to use them to evaluate whole-body metabolism without the need to perform invasive organs biopsies, as they can act as metabolic sentinels of nutritional-related changes. The common features observed between the PBMC and AT metabolism in HFHS minipigs make these cells particularly attractive for exploring metabolism and looking for biomarkers of dysregulation in obesity-related conditions.

**Author Contributions:** For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used "Conceptualization, S.P. and I.S.A.; Methodology, Y.Z., D.R. and J.D.; Software, S.P.; Validation, S.P. and Y.Z.; Formal Analysis, Y.Z. and J.D.; Investigation, Y.Z., I.S.A. and S.P.; Resources, S.P.; Data Curation, S.P.; Writing-Original Draft Preparation, S.P.; Writing-Review & Editing, D.D., D.R.; Visualization, Y.Z. and S.P.; Supervision, S.P.; Project Administration, S.P.; Funding Acquisition, S.P.", please turn to the CRediT taxonomy for the term explanation. Authorship must be limited to those who have contributed substantially to the work reported.

#### **Funding:** No external funding received.

**Acknowledgments:** The authors acknowledge D. Durand and the personnel of the Animal Facility (C. de L'Homme, B. Cohade) for technical assistance.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

#### *Article*


**3. Test conditions**

226 Olive Germplasm – The Olive Cultivation, Table Olive and Olive Oil Industry in Italy

(blue or amber-coloured) tasting glass.

gustatory sensitivity.

Sensory analysis is an essential technique to characterize food and investigate consumer preferences. International cooperative studies, supported by the International Olive Oil Council (IOOC) have provided a sensory codified methodology for virgin olive oils, known as the "COI *Panel test*". Such an approach is based on the judgments of a panel of technicians, conducted by a *panel* leader, who has sufficient knowledge and skills to prepare sessions of sensory analysis, motivate judgement, process data, interpret results and draft the report.

The *panel* generally consists of a group of 8 to 12 persons, selected and trained to identify and measure the intensity of the different positive and negative sensations perceived.

Sensory assessment is carried out according to codified rules, in a specific tasting room, using controlled conditions to minimize external influences, using a proper tasting glass and adopting both a specific vocabulary and a profile sheet that includes positive and negative sensory attributes. Collection of the results and statistical elaboration must be standardized. The colour of virgin olive oil, which is not significantly related to its quality, may produce expectations and interferences in the flavour perception phase. In order to eliminate any prejudices that may affect the smelling and tasting phases, *panel* lists use a dark-coloured

The *panel* leader is the person responsible for selecting, training and monitoring tasters to ascertain their level of aptitude according to (IOOC/T.20/Doc.15/rev.3). The number of candidates is generally greater than that needed in order to select people that have a grater sensitivity and discriminatory capability. Screening criteria of candidates are founded on sensory capacity, but also on some personal characteristics of candidates. Given this, the *panel* leader will personally interview a large number of candidates to become familiar with their personality and understand habits, hobbies, and interest in the food field. He uses this information to screen candidates and rejects those who show little interest, who are not

The determination of the detection threshold of the group of candidates for characteristic attributes is necessary because the "threshold concentration" is a point of reference common to a "normal group" and may be used to form homogeneous *panels* on the basis of olfactory-

A selection of tasters is made by the intensity rating method, as described by Gutiérrez Rosales (Gutiérrez Rosales *et al.*, 1984). A series of 12 samples is prepared by diluting a virgin olive oil characterized by a very high intensity of a given attribute in an odourless and tasteless medium (refined oil or paraffin). The *panel* leader sends out the candidate, removes one of the 12 tasting glasses from the series, and places the remaining together; the candidate is called back in the room and is asked to correctly replace the testing glass withdrawn from the series by comparing the intensity of this last with that of the others. The test is carried out for fusty, rancid, winey and bitter attributes to verify the discriminating

The stage training of technicians is necessary to familiarize tasters with the specific sensory methodology, to heighten individual skill in recognizing, identifying and quantifying the sensory attributes and to improve sensitivity and retention with regards to the various

readily available or who are incapable of expressing themselves clearly.

capacity of the candidate on the entire scale of intensities.

The test conditions for tasting are described in COI/T.20/Doc. No. 15/Rev. 3:

"The oil sample for analysis shall be presented in standardised tasting glasses conforming to the standard COI7T.20/Doc. No. 5 (Fig. 2).

**Figure 2.** Tasting glass

The glass shall contain 14-16 ml of oil, or between 12.8 and 14.6 g if the samples are to be weighed, and shall be covered with a watch-glass. Each glass shall be marked with a code made up of digits or a combination of letters and digits chosen at random.

**Figure 3.** Heating the samples when in the glass

The oil samples intended for tasting shall be kept in the glass at 28 °C ± 2 °C throughout the test (Fig. 3).

Sensory Analysis of Virgin Olive Oils 229

booth allotted to them in an orderly, quiet manner;

the concentration and work of their colleagues.

**4. Technique for tasting of virgin olive oil**

shall take a short rest before trying again (Fig. 5).

**Figure 5.** The olfactory test during

panel leader accordingly;

2568/91:

The technique applied for tasting is the one described in annex XXI of (EEC) Reg. N.

"the taster shall pick up the glass (Fig. 2), keeping it covered with the watch glass, and shall

Once this stage is completed, he shall remove the watch-glass and smell the sample taking even, slow deep breaths until he has formed a criterion on the oil under assessment. Smelling shall not exceed 30 seconds. If no conclusion has been reached during this time, he

bend it gently fully in this position so as to wet the inside as much as possible.

This temperature has been chosen because it makes it easier to observe organoleptic differences than at ambient temperature and because at lower temperature the aromatic compounds peculiar to these oils volatilize poorly while higher temperatures lead to the formation of volatile compounds peculiar to heated oils. The test room must be at a temperature between 20 and 25 °C.

The morning is the best time for tasting oils. It has been proved that there are optimum perception periods with regards to taste and smell during the day. Meals are preceded by a period in which olfactory-gustatory sensitivity increases, whereas afterwards this perception decreases. However, this criterion should not be taken to the extreme where hunger may distract the tasters, thus decreasing their discriminatory capacity; therefore, it is recommended to hold the tasting session between 10:00 in the morning and 12:00 noon (Fig. 4).

**Figure 4.** Cabins of the test room

The following recommendations apply to the conduct of the tasters during their work.

When called by the panel leader to participate in an organoleptic test, tasters should be able to attend at the time set beforehand and shall observe the following:

228 Olive Germplasm – The Olive Cultivation, Table Olive and Olive Oil Industry in Italy

test (Fig. 3).

temperature between 20 and 25 °C.

**Figure 4.** Cabins of the test room

the time of the test;

The oil samples intended for tasting shall be kept in the glass at 28 °C ± 2 °C throughout the

This temperature has been chosen because it makes it easier to observe organoleptic differences than at ambient temperature and because at lower temperature the aromatic compounds peculiar to these oils volatilize poorly while higher temperatures lead to the formation of volatile compounds peculiar to heated oils. The test room must be at a

The morning is the best time for tasting oils. It has been proved that there are optimum perception periods with regards to taste and smell during the day. Meals are preceded by a period in which olfactory-gustatory sensitivity increases, whereas afterwards this perception decreases. However, this criterion should not be taken to the extreme where hunger may distract the tasters, thus decreasing their discriminatory capacity; therefore, it is recommended

to hold the tasting session between 10:00 in the morning and 12:00 noon (Fig. 4).

The following recommendations apply to the conduct of the tasters during their work.

to attend at the time set beforehand and shall observe the following:

When called by the panel leader to participate in an organoleptic test, tasters should be able