Proliferation and apoptosis in subcutaneous adipose tissue of lactating cows with different genetic merit for milk yield

Tissue and Cell 49 (2017) 72–77

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Proliferation and apoptosis in subcutaneous adipose tissue of lactating cows with different genetic merit for milk yield ´ c, ´ Bruno Stefanon Monica Colitti ∗ , Nataliya Poˇsci Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle Scienze, 206, 33100 Udine, Italy

a r t i c l e

i n f o

Article history: Received 1 September 2016 Received in revised form 22 November 2016 Accepted 22 November 2016 Available online 24 November 2016 Keyword: Adipocytes Genetic merit Lactation Cattle

a b s t r a c t The aim of this study was to investigate the adipocyte size and fate in subcutaneous fat (scAT) of cows diverging for genetic merit at mid lactation stage, when anabolic activity increases and animals are in a state of positive energy balance. Twenty mid lactation cows (180 ± 20 days in milk) grouped according to the Estimated Breeding Values (EBV) for milk yield in plus (EBVp) and minus (EBVm) variants were selected. Average of adipocytes area, proliferation and apoptotic labelling index as well as DLK-1 expression, a marker of pre-adipocytes, were immunohistochemically evaluated in scAT biopsies. In EBVp cows, the BCS was lower (P < 0.01) whereas milk yield, protein, fat yield (P < 0.001) and plasma free fatty acid concentration (P < 0.05) were higher. The scAT of EBVp cows showed a significantly (P < 0.001) higher frequency between 500 and 3000 ␮m2 classes in comparison to EBVm cows, that showed a significantly (P < 0.01) higher apoptotic labeling index. The immunohistochemical reaction showed DLK-1 positivity in scAT of EBVp cows. Taking together, the data indicate a link between milk yield genetic merit of cows, scAT morphology and function, suggesting greater dynamics and metabolic flexibility in EBVp cows. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction Adipose tissue (AT) is a tissue that changes its mass during the adult life. The cellular development and dynamics of AT is a result of proliferation of cell number (hyperplasia) and of an increase of cell size (hypertrophy) (Hausman et al., 2001). Although mature adipocytes should not have the capacity to divide, there are studies that reported the replication of mature adipocytes in vitro (Loffler et al., 1994). Also partially differentiated cells, such as pre-adipocytes, are able to duplicate prior to differentiation (Prins and O’Rahilly, 1997). Proliferation is under hormonal, nervous and paracrine control (Hausman et al., 2001) and it has been also demonstrated that region-specific differences in fat cell precursors could contribute to differential adipose tissue growth (Dijan et al., 1983). Delta-like 1 homolog (DLK-1) is a well-established marker of pre-adipocytes (Sul, 2009). DLK-1 is a transmembrane glycoprotein with epidermal growth factor (EGF)-like repeats in the extracellular domain (Sul, 2009). Membrane-bound DLK-1 acts as an inhibitor of in vitro pre-adipocyte differentiation and inhibits pre-adipocyte proliferation by regulating their entry into the G1/S-phase of the cell cycle (Mortensen et al., 2012). The membrane tethered DLK1

∗ Corresponding author. E-mail address: [email protected] (M. Colitti). http://dx.doi.org/10.1016/j.tice.2016.11.008 0040-8166/© 2016 Elsevier Ltd. All rights reserved.

can be cleaved by tumor necrosis ␣ converting enzyme (TACE), generating a biologically active soluble form (Hudak and Sul, 2013) that maintains proliferating cells in an undifferentiated state during development (Wang et al., 2010). Instead, apoptosis, in human AT, has been considered as a result of macrophage recruitment in visceral AT of obese patients (Aron-Wisnewsky et al., 2009), although about 20% apoptosis was observed also in in vitro differentiating human visceral pre-adipocytes (Pomari et al., 2015; Colitti and Stefanon, 2016). In subcutaneous and visceral fat of cows at early lactation, only marginal infiltration of these inflammatory cells was reported (Akter et al., 2012). Considering the peculiar fat metabolism in dairy cows, it is likely that other regulatory mechanisms are involved in cell death of adipocytes in cattle. A large body of research has been devoted to the study of fat metabolism and its implication to physiological regulation and healthy or pathologically conditions of dairy cows (Summer et al., 2005; Graugnard et al., 2012; Rocco and McNamara, 2013). The energy deficit during early lactation in high yielding dairy cows is accompanied by fat mobilization from AT. In a condition of negative energy balance (NEB), reduced lipogenesis and increased lipolysis is described in discrete AT depots (McNamara and Hillers, 1986). When the energy balance reaches positive values, the energy is stored in AT depots, which are increasingly refilled by means of lipogenesis and by adipogenesis, thus preparing the organism for

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the upcoming energy deficit in the subsequent lactation (Hausman et al., 2001; McNamara, 1995). Adipose tissue responds to biochemical and nervous signals and it plays an active role during lactation through the secretion of signaling molecules (Colitti, 2015; Hovey and Aimo, 2010). Diet composition and plan of nutrition, parity and milk yield strongly influence the extent of AT accumulation and losses and it has been observed that also genetic merit of the cow can influence the mobilization of fat depots (Sgorlon et al., 2015a). Adipose tissue mass is determined by balancing lipolysis, lipogenesis, and adipocyte proliferation (Della-Fera et al., 2001) and it is likely that genetic make-up of the animal regulates the nutrient fluxes among tissues and modulates the expression of genes which orchestrate the metabolism and the fate of adipose cells (Khan et al., 2013; Rocco and McNamara, 2013). In this study, size, cell proliferation and apoptosis were measured in subcutaneous adipose tissue (scAT) of dairy cows in the mid stage of lactation to evaluate if the genetic merit for milk yield can be related to variations of adipocyte functions.

2. Material and methods 2.1. Animals and sampling Twenty mid lactation and pregnant Simmental cows (180 ± 20 days in milk, DIM) from a commercial farm were selected from a herd of 280 lactating cows. Cows were housed in the farm in free-stall barn, had free access to fresh water and fed ad libitum a total mixed ration (TMR) regularly twice a day, at around 07.00 a.m. and 17.00 p.m. Diets were formulated to cover the nutrient requirements for lactation (NRC, 2001) and further details can be found in Sgorlon et al. (2015b). All animals included in the study were clinically healthy, at parity 3, had somatic cell count in the milk lower than 200,000/ml and a body condition score (BCS; Edmonson et al., 1989) between 2.75–3.25. Moreover, cows were selected according to their Estimated Breeding Values for milk yield (EBV), provided by Italian Simmental (ANAPRI; www. anapri.eu) breed association. The EBV is an approximation of the genetic merit of a cow for a defined phenotype and is estimated by animal model using data records and kinships. The genetic merit is simply the additive effect of an individual’s genotype on the trait expressed relative to the population mean phenotype. (Wilson et al., 2011). Ten animals with the extreme positive and 10 animals with the extreme negative EBV values for milk, fat and protein yields were included in the study (Table 1). The selected animals were in the plus or minus 10% of the population. On the day of official milk recording, during morning milking (from 5.00 a.m. to 6.00 a.m.), 50 ml of milk from each cow was sampled into a tube with preservative (Bronopol, 0.02% w/v). Milk protein, fat, lactose contents as well as somatic cell count were predicted using the mid infrared spectroscopy method (Fourier Transform Instrument, FT6000, Foss Electric, Hillerød, Denmark). After milking right before the morning meal, blood was sampled from the coccygeal vein in 10 ml vacuum tubes with lithium heparin or K3-EDTA (Venoject, Terumo Europe N.V., Leuven, Belgium). The blood was centrifuged within 1 h at 3000 RPM for 10 min at 20 ◦ C and the plasma samples were stored at −20 ◦ C until further analysis. The analyses of glucose (mmol/L), urea (mmol/L) and cholesterol ® (mmol/L) were performed using a Roche Cobas 6000 analyzer and proprietary kits (Hoffmann-La Roche AG, Basel Switzerland). Free fatty acids (FFA, mmol/L) and beta-hydroxy-butyrate acid (BHBA, mmol/L) were measured with Randox kits (Randox Laboratories Limited, Crumlin UK). Biopsies of subcutaneous adipose tissue (scAT) were collected from the dorsal pelvic region as described by McNamara and Hillers

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Table 1 Mean (± standard error, SE) of body condition score (BCS), days in milk (DIM), milk yield, milk composition and hematological variables in the two groups of cows diverging for estimated breeding value (EBV) for milk yield. Ten cows with the highest EBV (EBVp) and 10 cows with lowest EBV (EBVm) were selected within the herd. Item

EBVp mean ± SE

EBVm mean ± SE

P value

BCS DIM EBV milk yield EBV fat yield EBV protein yield

2.81 ± 0.11 175.6 ± 6.96 1077.4 ± 26.33 34.5 ± 1.39 33.7 ± 0.66

3.25 ± 0.05 162.8 ± 7.06 −492.7 ± 23.99 −17.7 ± 1.01 −16.0 ± 0.95

** n.s. *** *** ***

Milk Yield (Kg) Fat (%) Protein (%) Fat yield (kg/d) Protein yield (kg/d)

31.02 ± 1.39 3.79 ± 0.15 3.71 ± 0.09 1.16 ± 0.05 1.15 ± 0.05

19.84 ± 1.88 3.89 ± 0.21 3.72 ± 0.15 0.75 ± 0.06 0.74 ± 0.07

** n.s. n.s. *** ***

Plasma Glucose (mmol/L) Cholesterol (mmol/L) Urea (mmol/L) FFA (mmol/L) BHBA (mmol/L)

3.92 ± 0.06 6.04 ± 0.52 6.00 ± 0.46 0.14 ± 0.03 0.71 ± 0.09

3.98 ± 0.11 5.37 ± 0.75 6.55 ± 0.31 0.08 ± 0.01 0.63 ± 0.08

n.s. n.s. n.s. * n.s.

n.s. = not significant; * = P < 0.05; ** = P < 0.01; ***P < 0.001. FFA: Free Fatty Acids. BHBA: Beta Hydroxy Butyrate Acid.

(1986), using a 20 gauge biopsy needle. Tissue samples were fixed in 10% (w/v) neutral formalin for 24 h at room temperature, processed for paraffin embedding and cut at a thickness of 5–7 ␮m. Sections meant for a morphometric analysis were stained with haematoxylin-eosin, observed and photographed at 20× under Leica DM750 microscope equipped with Leica ICC50 HD (Leica Microsystems, Milan, Italy). The study complies with the national regulation on the use of animals in research and was approved by the bioethical committee of University of Udine. 2.2. Histomorphology Adipocytes Tool, a macro of ImageJ1.50b software (http://rsb. info.nih.gov/ij/), was used to measure adipocyte area (in ␮m2 ) (Baecker, 2012). After running the macro, the scale was settled for magnification and the global checkbox on the set scale dialog was chosen. The options in the ‘p’ and ‘s’ buttons of macro were settled and measurements were checked by the roi manager. The areas of the adipocytes were measured on ten different field for each sample slide. Cell area of 490.2 ± 62.7 (mean ± se) cells was measured in EBVp group and 413.0 ± 86.2 (mean ± se) cells was measured in EBVm group. To label macrophages sections were stained with periodic acidSchiff (PAS) according to standard protocol (Sigma, Milan, Italy). 2.3. Immunohistochemistry analyses Immunohistochemical investigations were performed as described more fully by Colitti (2015). The avidin-biotinperoxidase complex (ABC) method was performed using the Vectastain ABC kit (PK-4000, Vector Laboratories, Burlingame, CA, USA). Primary antisera were horse anti-Ki-67 (Novocastra, U.K.) and rabbit anti-DLK (Abcam, Cambridge UK). Ki-67 and DLK were visualized using the 3,30-diaminobenzidine tetrachloride (DAB solution, Vector Laboratories, Burlingame, CA) as a chromogen. In the control sections, blocking solution was substituted for the primary antibody. Lymph node and adrenal gland were used as positive controls for Ki-67 and DLK reactions respectively.

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2.4. TUNEL assay

3. Results

Apoptosis assay was performed using Terminal Transferase and Biotin-16-dUTP (TUNEL Enzyme Method) as previously described in Pomari et al. (2015). Slides were deparaffinised, rehydrated through graded concentrations of alcohol to distilled water, and submitted to pre-treatment using proteinase K digestion method (20 ␮g/ml) 20 min in PBS at room temperature. After two washes in PBST, tissue slides were blocked for endogenous peroxidase in 3% H2 O2 in PBS for 10 min, rinsed in PBST and pre-incubated at RT in the TdT Reaction Buffer containing 1 mM cobalt chloride in 0.2 M sodium cacodylate, 25 mM Tris HCl and 0.25 mg/ml bovine serum albumin pH 6.6. Further the specimens were exposed to the TUNEL labeling mix, containing 400 U/␮l calf thymus terminal deoxynucleotidyl transferase (TdT) (Roche Diagnostic, Monza Italy) and 0.5 nmol Biotin-16-Dutp (Roche Diagnostic, Monza Italy) in TdT reaction buffer, followed by 1 h incubation in a moist chamber at 37 ◦ C. The reaction was stopped with 300 mM NaCl, 30 mM sodium citrate and the specimens were further incubated with streptavidin-HRP (Sigma, Milan, Italy) in PBS for 20 min at RT. The detection was performed by incubation with 3,3 -diaminobenzidine tetrahydrochloride (DAB solution, Vector Laboratories, Burlingame, CA) as a chromogen. Specimens were counterstained with Gill’s hematoxylin, washed in running tap water, dehydrated by passing through graded ethanol cleared in xylene and, finally, mounted with Diamount medium (Diapath, Martinengo BG, Italy) for light microscopy. Tissue of mammary gland at involution was used as positive control. Image analysis of Ki-67 and TUNEL sections was performed using ImmunoRatio, a plugin of ImageJ 1.50b software (Tuominen et al., 2010). ImmunoRatio uses a colour deconvolution algorithm, which separates 3,3 -diaminobenzidene tetrahydrochloride (DAB) from hematoxylin-counterstain nuclei by adaptive thresholding to allow nuclear segmentation. This software allowed to assess the percentage of positively stained nuclei over the total nuclear area (termed Labelling Index (LI)). Briefly, the threshold values for hematoxylin (0) and DAB (−85) were adjusted; image analysis settings were kept the same after the light exposure and thresholds were considered good. An average of three blank field images was taken and used as blank field correction image for every image session to balance uneven illuminations in the final digital images. Eleven different image fields were captured as digital images (TIFF format, resolution 2048 × 1536). The outcome of the analysis was presented as a pseudocolour image, giving an opportunity to check that only positive nuclei were included in the analysis.

3.1. Productive and metabolic features

2.5. Statistical analysis Data of milk yield and composition, BCS, blood variables, average of adipocytes area, proliferation and apoptotic LIs were submitted to analysis of variance using the ANOVA model to assess significant differences between EBV groups (SPSS Inc., 1997). The data were reported as a mean ± SE. Furthermore, the frequency distribution of adipocytes was calculated. Cell that fall below an area of 500 ␮m2 were removed from the analysis, as these cells may be a mixture of adipocytes and stromal vascular cells. The frequency function in Excel (=frequency(data array, bins array)) was used to classify adipocyte size within each animal with an array bin of 500 increments from 500 to 8000 ␮m2 . The generalized linear model (GENLIN) of the SPSS package (1997) was used to assess the fixed effects of EBV groups and size of adipocyte on the frequency distribution, including in the model the linear effect of the total number of adipocytes.

The mid lactating cows were grouped in plus (EBVp) and minus (EBVm) variants according to the EBV for milk yield; the EBVp cows had a significantly higher values of EBV for fat yield and protein yield, other than for milk yield (P < 0.001) (Table 1). The average days in milk did not differ between groups, while for the EBVp cows the BCS was lower (P < 0.01) and milk yield, protein and fat yields were higher (P < 0.001). Among all metabolites measured in plasma only the concentration of FFA was significantly higher in EBVp cows (P < 0.05). 3.2. Histomorphology Size of adipocytes significantly differed (P < 0.001) between cows with plus and minus EBV. Adipocyte sizes were significantly larger (P < 0.001) in minus variants for EBV (EBVm: 2421.525 ± 53.50 ␮m2 ) than in plus variants for EBV (EBVp: 1661.96 ± 30.64 ␮m2 ). Significant differences in the frequency distribution of the class of adipocyte size between cows with plus and minus EBV were calculated for the classes ranging from 501 to 3000 ␮m2 (Fig. 1). Adipocytes area of EBVp cows showed a significantly higher frequency in 501–1000, 1001–1500, 1501–2000 ␮m2 classes (P < 0.001) and also in 2001–2500 and 2501–3000 ␮m2 classes (P < 0.05) in comparison to the frequency in classes of adipocytes in EBVm cows. Starting from 3501 ␮m2 class the frequency of larger adipocytes increased in EBVm cows, but without significant difference. 3.3. Immunohistochemistry analysis Ki-67 positive cells were observed in adipocytes of all examined groups (Fig. 2A and B). The positivity was comparable with that of positive control and no stain was detected when antibody was omitted. A representative image of TUNEL assay is shown in Fig. 2(C and D), where the apoptotic cells are well identified in brown in the different groups of cows. Fig. 2E reports the quantitative analysis for Ki-67 and TUNEL assessed samples. Proliferation LI between groups was not statistically different (P = 0.668), and was 2.70 ± 0.288% in adipocytes of cows with EBVp and 2.52 ± 0.31% in adipocytes of cows with EBVm. Apoptotic LI reached the level of significance (P = 0.008) and was 0.71 ± 0.56% in adipocytes of cows with EBVp and 1.33 ± 0.167% in adipocytes of cows with EBVm. PAS reaction was used to identify the presence of macrophages and showed a very small number of inflammatory cells. However, PAS staining also identifies glycogen and mucosubstances such as glycoproteins, glycolipids and mucins in tissues. Close to small fat globules a strong reaction was observed in scAT of EBVp cows (Fig. 3A), where also DLK-1 immunostaining was particularly evident (Fig. 3C). In scAT of EBVm cows only few small fat globules were observed, PAS staining was very weak (Fig. 3B), and no DLK-1 positivity was found (Fig. 3D). 4. Discussion This study investigated whether differences in genetic merit of cows for milk yield in mid lactation can influence the adipocyte features. Among the EBVs, we focused the attention on the milk yield, considering that it is the main factor affecting energy metabolism in lactating cows. The EBV for milk yield is the base of quantitative selection and is used in breeding programs to screen animals with

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Fig. 1. Frequency distribution of adipocyte sizes (␮m2 ) of different groups of cows with plus (EBVp) and minus (EBVm) EBV. Data are reported as mean of the percentage ± standard error (SE). P-value < 0.001 double asterisk; P-value < 0.05 single asterisk.

Fig. 2. Representative immunolocalisation of Ki-67 in bovine subcutaneous adipose tissue (A–B) and TUNEL assay (C–D). Ki-67 staining shows proliferating cells. A. Adipocytes of cows with plus EBV. Insert: Very intense immunoreactivity in the germinal center of bovine lymph node, used as positive control. B. Adipocytes of cows with minus EBV. C. Nuclei of apoptotic adipocytes of cows with plus EBV. Insert: Bovine mammary gland at involution used as positive control. D. Apoptotic adipocytes of cows with minus EBV. Gill’s haematoxylin counterstain. E. Graphic appraisal of proliferation and apoptotic labeling indexes reported as mean of the percentage ± standard error (SE). ** = P < 0.01.

higher performances, which are preferentially used for reproduction purposes. Genotype to phenotype genome wide association studies have demonstrated that selecting for EBV leads to a significant changes of the frequency of DNA variants in the progenies, most of them in the regulatory or coding sequence of genome (Capomaccio et al., 2015). Recently, it has also been reported that the variable genetic merit for milk yield can influence the expression of genes also involved in fat metabolism and can produce specific molecular signature (Sandri et al., 2015). Not surprisingly, the productive performances measured in a small number of animals at the time of sampling confirmed that milk yield and compositions reflect the differences of the genetic background of animals. Milk yield was significantly higher in EBVp than in EBVm cows (Table 1). Interestingly, the most

productive cows showed a significantly lower BCS, which is an estimate of the amount of subcutaneous fat (Edmonson et al., 1989), indicating a delay in the recovery of fat depots. The FFA and BHBA concentrations in plasma are markers of energy metabolism at the beginning of lactation (McArt et al., 2013), as in this period a large mobilization of fat stored in the tissues in high yielding cows occurs. These metabolites can be used also in the late phase of lactation as biomarkers of metabolic activity and genetic merit (Sgorlon et al., 2015a,b). The higher FFA plasma concentration observed in EBVp cows (Table 1) indicates that fat mobilization in EBVm cows was lower than in EBVp cows, in agreement with the higher BCS (P < 0.01) and the higher adipocyte size (P < 0.01) revealed for the less productive animals (Fig. 1).

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Fig. 3. Representative PAS reaction (A–B) and immunolocalisation of DLK-1 (C–D) in bovine subcutaneous adipose tissue (scAT). A. scAT of cows with plus EBV, massive presence of PAS-positive small fat globules, observed as pink granules, close to mature adipocytes. B. scAT of cows with minus EBV, very few small fat globules with weak PAS reaction, along the border of mature cells. C. scAT of cows with plus EBV; extracellular DLK-1 positive expression in stromal vascular fraction in proximity to small fat globules. Insert: negative control. D. scAT of cows with minus EBV; very faint DLK-1 expression close to small globules. Insert: adrenal gland served as positive control. Gill’s haematoxylin counterstain.

Fat depots are located in defined areas and possess different metabolic functions (Rosen and Spiegelman, 2000). The retroperitoneal AT is the most metabolically active depot in cows (von Soosten et al., 2011; Kenéz et al., 2015), but we focused the attention on scAT, for the easy of sampling. In scAT numerous very small adipocytes are present, infiltration of phagocytic cell barely occurs (Häussler et al., 2013) and minor extents of time-related differences are exhibited (Kenéz et al., 2015). The stain of scAT with Periodic-acid Schiff reagent confirmed a very scarce presence of macrophages (data not shown). In this study, as suggested by Parlee et al. (2014), the frequency distribution rather than the average adipocyte area alone was chosen, as the change in the adipocyte number in addition to the size is present. The frequency of smallest adipocytes until 3500 ␮m2, was significantly higher in scAT of EBVp cows, while the frequency of largest adipocytes was higher in fat of EBVm cows (Fig. 1). The smaller size of adipocytes is consistent with the significantly higher FFA concentration in plasma of EBVp cows and could be related to an increase of fat mobilization. Metabolic improvements are generally associated with a reduction in average fat mass and cell size in mice (Khan et al., 2009) and cows (Akter et al., 2011). According with McNamara (1995), substrates that supply mammary gland during lactation are affected by the differences of nutrients through the adipose tissue, which has a primary role in maintaining lactation and reproduction rather than just a control function. This is particularly interesting at 180 DIM when cows are far from negative energy balance (Vernon, 1980).

The DKL-1 positivity was observed in scAt stroma vascular fraction of EBVp cows and was associated to small fat globules. DKL-1 is a master regulator of repression of pre-adipocyte differentiation and homeostasis of adipose tissue expansion (Traustadottir et al., 2013). It is likely that the presence of DKL-1 positivity limited adipocyte hyperplasia more than hypertrophy, considering that proliferation LI was not significantly different between plus and minus EBV cows. PAS staining in scAt stroma vascular fraction of EBVp cows evidenced a positive reaction for glycogen around small lipid droplets (Fig. 3), suggesting that nearby adipocytes are probably entering in an anabolic process. It has been reported that smaller adipocytes have higher apoptotic rate as a consequence of a loss of function as lipid storage and cell undernourishment (Häussler et al., 2013). However, in mid phase of lactation such as 180 DIM, lower apoptosis, higher PASand DLK-1 positive cells were observed in the smaller adipocytes of EBVp cows, (Fig. 3), indicating a delay in adipocytes replenishment in EBVp cows in comparison to EBVm ones. Indeed, a higher apoptotic LI was calculated in adipocytes of EBVm cows in agreement with the in vitro evidences demonstrating that hypertrophy per se promotes adipocyte death (Cinti et al., 2005). 5. Conclusion Present results suggest that dairy cows with different genetic merit, but at the same phase of mid lactation, differ in milk yield and fat metabolism and that these variations correspond to specific features of scAT. Of note, the size of adipocytes as well as apop-

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