Western World maps In the 17 th and 18 th c.

READING CULTURE

Flood of knowledge and information from outside into Korean society Economic development and social changes

Confucian and sino-centric dogma challenged Resistance to social system • At the beginning :

-Book with practical aims and manual for learning -Principal consumers : people of middle or lower class capable of reading written Chinese

• From the middle-19 th c. :

novels -Clients : men from lower class or women from middle and lower class

Cultural roles

• Manual for learning of written chinese for children • Books on history • à Extension of literate population • Certain publication only in panggakpon • à Appropriation by peuple (intermediary of lower class) of the culture of the higher class 1. Worldviews -3 kinds of map 2. New passions, studies and reading culture 3. Dissolution of cultural monopoly :

•

  An ancient vision of the universe • Correspondence between earth and heaven • To see ourselves placed in the universe • Mention about immortality 천하도 ( ) "Imago mundi" • To see themselves placed in the universe • Mention about immortality à interest in longevity and afterlife 2018, Daeyeol KIM, INALCO (Paris)

•

  his tastes in things, he finally looses his wills" 2018, Daeyeol KIM, INALCO (Paris) In the 18 th c.: Curiosity, passion, mania "The man without mania is useless" (박제가) 벽(癖, mania) and 치(痴, crazy) : cultural distinction and privilege 2018, Daeyeol KIM, INALCO (Paris) "It is only maniacs who can have an original mind and understand a particular technique. Ah! These cowardly people who spoil the major business but who themselves did not suspect anything, they have to be wary of themselves in reading this book !" 2018, Daeyeol KIM, INALCO (Paris) Collection and ordering mania • Curiosity and knowledge mania à Gathered and sorted informations à Compilation & edition • 이서구 (李書九 1754-1825) : 녹앵무경 (綠鸚鵡經 The Classic on Parrot) • 유득공 (柳得恭 1749-1807) : 발합경 ( 經 The Classic on Dove) • 이옥 (李鈺 1760-1812) : 연경 (烟經 The Classic on Tobacco) De la lecture lente, intensive à la lecture rapide, extensive • De l'exégèse au compte-rendu • De la bibliothèque simple à la bibliothèque de dix mille ouvrages 2018, Daeyeol KIM, INALCO (Paris) out of illegitimate birth • Higher officials in technical or specialized fields -Medical doctors 의원 (醫院 ) -Interpreter 역관 (譯官 ) -Expert in calendar 일관 (日官 ) -Accountant 계사 (計士 ) -Jurist 율관 ( ) Middle people's cultural roles • Educated people • Economic power in the Capital • Artistic activities • Educational activity • Bidirectional role Women's culture • To educate their children • To attend the literary activities of their husbands • To develop their own writing talent 2018, Daeyeol KIM, INALCO (Paris) Women's writings • A variety of genre • With Korean alphabet in most cases • In some cases : in a mixed style of Korean and classical Chinese or purely in classical Chinese ⇢ their education in Chinese classics.

  Printing and distribution of books by the State à negative effect on commercial publication -Woodblock printing in the private sector• From the 18 th c. :

	• 金浩然齋 (김호연재, 1681-1722), (자경편) • (풍양조씨, 1772-1825), 자기록 or Autobiographical memoirs • 金三宜堂 (김삼의당, 1769-1823), (삼의당고) • 任允 堂 (임윤지당 1721-1793), (윤지당유고) Female talent behind male work • First draft in Korean by female member • Transcription in classical Chinese by male member • Trace of women's lives through women's care • Division of work 2018, Daeyeol KIM, INALCO (Paris) Autobiographies • (혜경궁 홍씨, 1735-1816), (한중록) or The Memoire of Lady Hyegyŏng • (풍양조씨, 1772-1825), 자기록 or Autobiographical memoirs • 烈女傳 (열녀전) Biographies of women who sacrifice their lives for marital fidelity 2018, Daeyeol KIM, INALCO (Paris) Extended literature • 憑虛閣 (빙허각 이씨, 1759-1824), (규합총서) ou Collections of gynaecium • Poetry and prose • Translation of Chinese texts in Korean 2018, Daeyeol KIM, INALCO (Paris) Book trade • Previously : -Development of market and growing social demande -Circulation of knowledge integrates into the commercial economy • Book brokers 서쾌 (書 ) or 책쾌 -imported chinese books, reproduction by hand copies • Bookstore : -rental -popular books and learning materials -pharmacy-bookstore 약계책사 藥契冊肆 2018, Daeyeol KIM, INALCO (Paris) Diffusion in 2 nd half of Chosŏn -women's clubs of higher society in Seoul

-2018, Daeyeol KIM, INALCO (Paris)

2018, Daeyeol KIM, INALCO (Paris)

"Middle people" Women 2018, Daeyeol KIM, INALCO (Paris)

Prints in low quality and small format With blue paper cover 2018, Daeyeol KIM, INALCO (Paris)

"Middle people"

Women's writings. 4. Book trade -Korean « bibliothèque bleue » 2018, Daeyeol KIM, INALCO (Paris)

Political or ritual debates


Y Lebrini

A Ayerdi Gotor

PERFORMANCE OF REMOTE SENSING DATA AND MACHINE LEARNING FOR WHEAT DISEASE DETECTION

The evolution of remote sensing applications in precision agriculture may lead to a reduction in phytochemical use. The development of data processing techniques allows speeding up the treatment of the information then making it possible to apply the right amount of chemical at the right place and time. In this study, the use of spectral information from remote sensing data using camera sensors coupled with artificial intelligence techniques at the field scale to detect wheat diseases is evaluated. In this study a Region based Convolutional Neural Network (R-CNN) model was evaluated for wheat disease detection. Besides, the methodology considered environmental variability during data collection to simulate real conditions during data acquisition in the field. The preliminary results of the model show a mean average precision of 0.45 and a precision between 0.2 to 0.6 for each image. Considering limitations in terms of data annotations for training the model, these results look promising on the way to consider further improvement of the model to reach higher accuracies and precisions. Furthermore, the study aims to develop a methodology for treatments reduction based on the enhanced version of the R-CNN model. Therefore, wheat disease detection and localized treatment in the field have a strong potential to reduce the use of chemicals. The developed methodology will optimize the costs and the use of chemicals over agricultural fields.

INTRODUCTION

French agriculture has reached high yield levels in many field crops. However, to reach them, it has required an intensive use of plant protection products (PPP) during the last decades. This intensive use of PPP situates France as one of the first users within the European countries (Eurostat, 2022). Since 2008 European and national policies have been trying to reduce the use of PPP to develop a more sustainable agriculture (European Parliament 2009). The development of precision agriculture may have an important impact on the reduction of PPP application, especially with the spot application technique (e.g., only when and where it is necessary), which reduces the use of PPP. Major progress has been made in weed detection and herbicides localized application [START_REF] Nikolić | Site-and time-specific early weed control is able to reduce herbicide use in maize -a case study[END_REF] with the development of sprayers or weeders carrying cameras to detect weeds. On the contrary, the reduction of fungicides used to control diseases in plants has been the object of less studies, because of cumulated difficulties encountered in the implementation process. The first step has been to discriminate leaves with symptoms of diseases from healthy leaves [START_REF] Sujatha | Performance of deep learning vs machine learning in plant leaf disease detection[END_REF], here the main difficulty was the diversity of symptoms within the diseases and along the development of the disease on the leaves. The second step has been to discriminate different plant diseases [START_REF] Martinelli | Advanced methods of plant disease detection. A review[END_REF], to treat with more efficient treatment. Next difficulty will be to find diseased leaves on a field crop at different growing stages of the crop. The last step will be to be able to modulate the fungicides doses in function of the disease pressure or to make localized applications that may be able to stop or slow down the progression of the disease. For these reasons, this study will discuss the possibilities of wheat disease detection based on camera sensors and machine learning algorithms to identify diseased areas and variable rate application of treatment.

MATERIALS AND METHODS

In France there are decision support systems for farmers to alert the risk of diseases on the crops based on rainfall events, presences of spores, soil type, rotation and the level of resistance of the variety to each disease. This study discusses the possibility, once there is a disease risk in a field, to implement a modulation of the dose of fungicides to be applied based on direct identification of the presence of the disease [START_REF] Colbach | Influence of Crop Management on Take-All Development and Disease Cycles on Winter Wheat[END_REF].

The wheat diseases considered in this study are the Septoria leaf blotch (Mycosphaerella graminicola) and the yellow rust (Puccinia striiformis f.sp. tritici). These two diseases affect the wheat leaves and cause important reductions in yields. Many sensor types have been used in literature for plant disease detection [START_REF] Fahey | Active and passive electro-optical sensors for health assessment in food crops[END_REF]. However, the use of sensors for spot application of fungicide was reported in limited studies [START_REF] Esau | Machine vision smart sprayer for spot-application of agrochemical in wild blueberry fields[END_REF][START_REF] Hussain | Design and development of a smart variable rate sprayer using deep learning[END_REF]). The methodology discussed here is based on the use of an RGB sensor from a Sony camera which will be mounted on a support and tilted to 45° degrees to simulate the position of sensors on the sprayer boom (Figure 1).

After field data collection, the preprocessing steps will be conducted to make data ready for implementing in the machine learning algorithm. The first preprocessing step consists of soil background removal using the CIVE index. The formula used for CIVE computing is indicated below: 𝐶𝐼𝑉𝐸 = 0.441 ⋅ 𝑅 -0.811 ⋅ 𝐺 + 0.385 ⋅ 𝐵 + 18.787 (Eq 1)

Where R, G and B represent spectral bands in red, green, and blue, respectively. Mask-RCNN model was employed in this study to automatically segment and classify the diseased areas of wheat fields. The Mask-RCNN is based on two stages which are object detection and segmentation. It consists of four parts mainly a backbone, Feature Pyramid Network (FPN), Region Proposal Network RPN, and feature branches [START_REF] Su | Automatic evaluation of wheat resistance to fusarium head blight using dual mask-RCNN deep learning frameworks in computer vision[END_REF]. A Residual Neural Network (ResNet) model with 101 layers (ResNet-101) was employed in this study. Model training was carried out using a limited number of annotated images.

RESULTS AND DISCUSSION

Figure 2 presents the result of diseases detection using Mask-RCNN model. The predictions were performed on validation dataset. The confidence values of detected objects vary between 0.3 and 0.65. The average precisions of the model for each image were relatively low and were between 0.2 to 0.6. In addition, the mean average precision (mAP) is about 0.43. Regarding the results obtained and precisions of the model, we can conclude that the model did not perform well for detecting diseased leaves. These raised errors could be originated from many issues that should be reviewed for the next application of the model. The intense presence of wheat heads in the images is the main source of errors during segmentation and identification of objects, as during the labeling step wheat heads were not labeled as a separate class to avoid mismatching with other classes. Moreover, related to some scheduling constraints the field data collection was performed during a late stage of phenological development where most leaves reach the senescence phase which makes the identification of leaves more difficult.

Different data acquisition platforms for plant disease detection were reported in previous studies, by using satellites, UAVs, land robots or handheld sensors [START_REF] Mahlein | Plant disease detection by imaging sensors-parallels and specific demands for precision agriculture and plant phenotyping[END_REF] which allowed unequal diseases detection and time required for data acquisition and treatment. In this study, a handled sensor was chosen to provide accurate acquisition of images and simulate the configuration of sensors on the engine boom. Some studies have used images to detect disease on wheat crops [START_REF] Bohnenkamp | In-field detection of yellow rust in wheat on the ground canopy and UAV scale[END_REF][START_REF] Deng | Applying convolutional neural networks for detecting wheat stripe rust transmission centers under complex field conditions using RGB-based high spatial resolution images from UAVs[END_REF]. However, the use of drones is usually related to technical limitations, such as flight planification for data acquisition, limitations related to weather conditions and the time needed from data acquisition to action release at the field.

Machine learning algorithms for identification of wheat disease using images from sensors, especially deep learning, have provided significant advances to accurately identify and monitor diseased plants. Recently, Convolutional Neural Networks (CNNs), a subset of machine learning techniques, have gained popularity as a flexible tool for operating on large and diverse amounts of data and producing accurate predictions of difficult and complex problems [START_REF] Su | Automatic evaluation of wheat resistance to fusarium head blight using dual mask-RCNN deep learning frameworks in computer vision[END_REF]). Besides, many datasets have contributed to the training of algorithms to enhance predictions, such as Plant Village (PV) [START_REF] Martinelli | Advanced methods of plant disease detection. A review[END_REF], Global Wheat Head Detection dataset (GWHD) [START_REF] David | Global wheat head detection 2021: an improved dataset for benchmarking wheat head detection methods[END_REF], and IPM and Bing datasets [START_REF] Ahmad | A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools[END_REF].

These preliminary results obtained during this study and made with a limited number of images are promising to use machine learning to detect disease and spray localized chemicals on the high yield compromised section of the field.

CONCLUSION

The use of machine learning techniques and data from sensors for plant disease detection combine the expertise and knowledge of agronomists and data scientists for better decision making and the understanding of the plant's behavior during phenological cycle. These kinds of applications are encouraged especially for transitioning towards a rational use of chemicals and adapting new strategies for yield enhancement and preserving soil and human health in a climate changing situation.

Figure 1 :

 1 Figure 1: General methodology for wheat disease detection. a) data collection using field camera with a 45° tilt, b) methodology of background removal based on the Color Index of Vegetation Extraction (CIVE) vegetation index, c) general machine learning steps to perform wheat disease detection.

Figure 2 :

 2 Figure 2: Result of wheat disease detection using the validation dataset with the Mask-RCNN model.


Gaïa Lépine

Jean-François Huneau

Didier Rémond

Véronique Mathé

Jérémie David

Dominique Hermier

Laetitia Guérin-Deremaux

Catherine Lefranc-Millot

Nathalie Poupin

François Mariotti

Sergio Polakof
email: sergio.polakof@inrae.fr.

Hélène Fouillet
email: helene.fouillet@agroparistech.fr

Compared with Milk Protein, a Wheat and Pea Protein Blend Reduces High-Fat, High-Sucrose Induced Metabolic Dysregulations while Similarly Supporting Tissue Protein Anabolism in Rats

Keywords: absolute synthesis rate, AA: amino acids, AP: animal protein, ACLY: ATP-citrate lyase, BCAA: branched-chain amino acids, CHO: carbohydrate, DNL: de novo lipogenesis protein and amino acid metabolism, protein synthesis/turnover, natural isotopic abundance, metabolic tracer, de novo lipogenesis

Background: Plant proteins (PP) have been associated with better cardiovascular health than animal proteins (AP) in epidemiological studies. However, the underlying metabolic mechanisms remain mostly unknown.

Objective: Using a combination of cutting-edge isotopic methods, we aimed at better characterizing the differences in protein and energy metabolisms induced by dietary protein sources (PP vs AP), in a prudent or western dietary context.

Methods: Male Wistar rats (n=44, 8 weeks old) were fed for 4.5 months with isoproteic diets differing in their protein isolate sources, either AP (100% milk) or PP (50%:50% pea: wheat), and being normal (NSF) or high (HFS) in sucrose (6 or 15%kcal, respectively) and saturated fat (7 or 20%kcal, respectively). We measured body weight and composition, hepatic enzyme activities and lipid content, and plasma metabolites. In the intestine, liver, adipose tissues and skeletal muscles, we concomitantly assessed the extent of amino acid (AA) trafficking using a 15 N natural abundance method, the rates of macronutrient routing to dispensable AA using a 13 C natural abundance method, and the metabolic fluxes of protein synthesis (PS) and de novo lipogenesis (DNL) using a 2 H labelling method. Data were analyzed using ANOVA and mixed models.

Results: At the whole-body level, PP limited HFS-induced insulin resistance (-27% in HOMA-IR between HFS groups, P<0.05). In the liver, PP induced lower lipid content (-17%, P<0.01) and DNL (-24%, P<0.05). In the different tissues studied, PP induced higher AA transamination accompanied by higher routings of dietary carbohydrate and lipid towards dispensable AA synthesis by glycolysis and β-oxidation, resulting in similar tissue PS and protein mass.

Conclusions:

In growing rats, compared to AP, a balanced blend of PP similarly supports protein anabolism while better limiting whole-body and tissue metabolic dysregulations, through mechanisms related to their less optimal AA profile for direct channeling to PS.

Introduction

Diets in high-income countries are high in animal products, refined carbohydrate (CHO) and saturated fats. A shift toward more plant-based diets is actively promoted to achieve more sustainable diets, better for both planetary and human health. The partial replacement of animal protein (AP) by plant protein (PP) sources is a key element of this transition, as the relative proportions of AP and PP produced and consumed both have considerable environmental impacts and broad public health implications (1,2). Regarding human health, although PP are considered to be less efficient than AP to sustain overall protein anabolism and muscle function (3,4), there is growing evidence that PP sources are better for cardiometabolic health (5)(6)(7)(8).

Indeed, substituting AP with PP, while accounting for dietary cofounders, was associated with lower cardiovascular and all-cause mortality (9,10). Conversely, high AP intake has been associated with metabolic syndrome features, such as dyslipidemia and insulin resistance (IR) (11,12), and with increased risk of cardiovascular diseases (13) and type 2 diabetes (T2D) (14,[START_REF] Zhao | Dietary protein intake and risk of type 2 diabetes: a dose-response meta-analysis of prospective studies[END_REF]. The differential effects of AP or PP intake on cardiometabolic features could be mediated by a better overall lifestyle, including diet which differs greatly depending on the predominant dietary protein sources [START_REF] De Gavelle | Patterns of Protein Food Intake Are Associated with Nutrient Adequacy in the General French Adult Population[END_REF][START_REF] Phillips | Commonly consumed protein foods contribute to nutrient intake, diet quality, and nutrient adequacy[END_REF][START_REF] Aggarwal | Plant-and animal-protein diets in relation to sociodemographic drivers, quality, and cost: findings from the Seattle Obesity Study[END_REF], and/or by other nutrients and bioactive compounds present in the food matrix (7).

Those health effects could also be mediated by the intrinsic amino acid (AA) composition of AP and PP sources (7,8). Thus, AP are richer in indispensable AA such as branched-chain AA (BCAA) and aromatic AA, while PP are richer in dispensable AA such as glycine, glutamine, cysteine and arginine, with most of these AA already reported to be implicated in cardiometabolic health [START_REF] Wu | Amino acids: metabolism, functions, and nutrition[END_REF]. In addition to individual AA, the whole dietary AA pattern, accounting for potential interactions between AA, could also contribute to the health effects of protein sources. However, little is known regarding the health effects of specific AA intake patterns, and few studies have investigated associations with cardiovascular endpoints [START_REF] Tharrey | Patterns of amino acids intake are strongly associated with cardiovascular mortality, independently of the sources of protein[END_REF][START_REF] Teymoori | Dietary amino acids and incidence of hypertension: A principle component analysis approach[END_REF][START_REF] Jennings | Amino Acid Intakes Are Inversely Associated with Arterial Stiffness and Central Blood Pressure in Women[END_REF]. Interestingly, AA intake patterns have been shown to be strongly associated with cardiovascular mortality: negatively for some of the dispensable AA (more abundant in PP) and positively for some of the indispensable AA (more abundant in AP) [START_REF] Tharrey | Patterns of amino acids intake are strongly associated with cardiovascular mortality, independently of the sources of protein[END_REF].

In rodents, the specific effects of some protein sources or dietary AA on cardiometabolic features have been studied and seem to be dependent on the dietary context [START_REF] Macarthur | Total protein, not amino acid composition, differs in plantbased versus omnivorous dietary patterns and determines metabolic health effects in mice[END_REF][START_REF] Lamming | Short-term consumption of a plant protein diet does not improve glucose homeostasis of young C57BL/6J mice[END_REF][START_REF] Chen | The Effect of Vegan Protein-Based Diets on Metabolic Parameters, Expressions of Adiponectin and Its Receptors in Wistar Rats[END_REF][START_REF] Watanabe | Dietary Mung Bean Protein Reduces Hepatic Steatosis, Fibrosis, and Inflammation in Male Mice with Diet-Induced, Nonalcoholic Fatty Liver Disease[END_REF][START_REF] Hernandez-Velazquez | Black bean protein concentrate ameliorates hepatic steatosis by decreasing lipogenesis and increasing fatty acid oxidation in rats fed a high fat-sucrose diet[END_REF][START_REF] Solon-Biet | Meta-analysis links dietary branched-chain amino acids to metabolic health in rodents[END_REF]. For instance, while fasting or postprandial glycemia after a glucose tolerance test were reported to be similar between AP and PP sources when fed within a prudent energy context [START_REF] Macarthur | Total protein, not amino acid composition, differs in plantbased versus omnivorous dietary patterns and determines metabolic health effects in mice[END_REF][START_REF] Lamming | Short-term consumption of a plant protein diet does not improve glucose homeostasis of young C57BL/6J mice[END_REF][START_REF] Chen | The Effect of Vegan Protein-Based Diets on Metabolic Parameters, Expressions of Adiponectin and Its Receptors in Wistar Rats[END_REF], PP were reported to lower hepatic triglyceride accumulation and lipogenic gene expression in a high fat dietary context [START_REF] Watanabe | Dietary Mung Bean Protein Reduces Hepatic Steatosis, Fibrosis, and Inflammation in Male Mice with Diet-Induced, Nonalcoholic Fatty Liver Disease[END_REF][START_REF] Hernandez-Velazquez | Black bean protein concentrate ameliorates hepatic steatosis by decreasing lipogenesis and increasing fatty acid oxidation in rats fed a high fat-sucrose diet[END_REF]. We hypothesized that the differential effects of AP and PP on cardiometabolic health could relate to the fact that their AA profiles differentially modulate protein metabolism on one hand, and other pathways connected to intermediary metabolism on the other hand, with potentially higher differences in a western than a prudent dietary context.

To date, no single study has explored the interrelated changes in protein, fat and CHO metabolisms between dietary protein sources in the different organs concomitantly. Thus, exploring the specific and concomitant tissue responses to protein sources on protein and energy metabolisms in different dietary energy contexts may contribute to explain the differential effects of AP and PP on cardiometabolic health.

In this study, we aimed at characterizing, at both the systemic and tissue levels, the various metabolic orientations specifically related to the dietary protein source (PP vs AP) within a prudent or western dietary pattern. This multi-pathway metabolic study was endeavored by using a combination of cutting-edge isotopic methods at both natural ( 15 N and 13 C) and enriched abundance levels ( 2 H), to respectively estimate the extent of AA metabolic trafficking, the rates of macronutrients routing to dispensable AA and the fluxes of protein synthesis (PS) and de novo lipogenesis (DNL) in tissues.

Materials and methods

Animals, diets and experimental procedures

Male Wistar rats (n=44) of 8 weeks of age and weighing 272.8g (SEM ± 1.5g) (Janvier), were kept on their breeding diet and adapted to the individual housing conditions (12-h light-dark cycle, 20°C) for 3 weeks. Then, the animals were randomly divided into 4 groups (n=11) and fed ad libitum for 4.5 months with 4 experimental diets (Table 1) differing in their energy level, either normal (NFS) or made high (HFS) by enrichment in dietary fat and sucrose content, and in their protein source, either AP or PP. AP consisted of total milk protein isolate (PRODIET 90, Ingredia) and PP on a 50:50 blend of wheat: pea protein isolates (NUTRALYS® W and NUTRALYS® S85 PLUS for wheat and pea respectively, Roquette Frères). All diets contained the same protein proportion relative to dietary energy content (15%) and met the requirements for rodent growth regarding indispensable AA [START_REF] Reeves | AIN-93 Purified Diets for Laboratory Rodents: Final Report of the American Institute of Nutrition Ad Hoc Writing Committee on the Reformulation of the AIN-76A Rodent Diet[END_REF]. The difference in AA composition between AP and PP sources was calculated based on protein isolate AA compositions, as provided by suppliers (Supplemental Figure S1). Mixing cereal and legume protein sources with a 50:50 ratio resulted in a PP blend with a well-balanced AA composition, since wheat and pea protein compensated each other for low contents in lysine and sulfur AA, respectively, while presenting very good digestibility of individual AA [START_REF] Guillin | Multi-criteria assessment of pea protein quality in rats: a comparison between casein, gluten and pea protein alone or supplemented with methionine[END_REF]. In comparison to AP, the AA content of the PP blend was lower in indispensable AA, such as BCAA (-20%), and higher in dispensable AA like glycine (+81%), arginine (+89%) and cysteine (+131%). All the experiments were performed in accordance with the guidelines formulated by the European Community for the use of experimental animals (L358-86/609/EEC, Council Directive, 1986) and authorized by the Regional Ethics Committee (agreement no.12050-2017103015435153V4).

Food intake was recorded weekly and body composition was assessed by MRI (EchoMRITM-700) at 0, 1, 2, 3, 4 and 4.5 months. Blood was collected from the tail vein with heparinized syringes at 0, 2 and 4 months after an overnight fast. After centrifugation (3000 × g, 10 min, 4°C), plasma was rapidly collected, frozen in liquid nitrogen and stored at -80°C until further analyses. Two days before euthanasia (at 4.5 months), rats received a bolus of 2 H2O saline solution (20 mL/kg of body weight at 99.9%, Sigma) intraperitoneally under light anesthesia in order to measure PS and DNL [START_REF] Belloto | Determination of protein replacement rates by deuterated water: validation of underlying assumptions[END_REF][START_REF] Busch | Measurement of protein turnover rates by heavy water labeling of nonessential amino acids[END_REF][START_REF] Gasier | The application of 2H2O to measure skeletal muscle protein synthesis[END_REF][START_REF] Konrad | Use of deuterium oxide to measure de novo fatty acid synthesis in normal subjects consuming different dietary fatty acid composition1Published in part in abstract form[END_REF] concomitantly. The dose was set to result in ~3% enrichment in 2 H of body water, which was then maintained until euthanasia by providing access to 3% 2 H drinking water. Then, after an overnight fast, rats were euthanized under isoflurane anesthesia. Blood was withdrawn from the abdominal aorta and handled as above.

The liver, small intestine, a sample of epididymal adipose tissue and skeletal gastrocnemius and tibialis anterior muscles were rapidly collected, weighed, freeze-clamped in liquid nitrogen, and stored at -80°C for further analyses.

Analytical procedures

Plasma metabolites and insulin levels

At 4.5 months, plasma non-esterified fatty acids (NEFA), glucose, lactate, urea, uric acid, creatinine, triglycerides (TG), total cholesterol, HDL-cholesterol and LDL-cholesterol levels were measured using a commercial kit (NEFA-HR(2), Fujifilm Wako) and a microplate reader or different kits on an ABX Pentra C400 analyzer (Horiba Medical). At 0, 2 and 4 months, plasma glucose levels were as above and plasma insulin levels were assayed using a commercial ELISA kit (10-1250-01, Mercodia). The homeostasis model for the assessment of insulin resistance (HOMA-IR) was calculated as the product of insulin (μU/ml) and glucose (mg/dl) concentrations.

Liver enzyme activities

Hepatic activities of enzymes involved in glucose, AA and lipid metabolisms were assessed on liver homogenates as previously described [START_REF] Polakof | Resistant starch intake partly restores metabolic and inflammatory alterations in the liver of high-fat-diet-fed rats[END_REF][START_REF] Dardevet | Fructose Feeding during the Postabsorptive State Alters Body Composition and Spares Nitrogen in Protein-Energy-Restricted Old Rats[END_REF], including ATP-citrate lyase (ACLY), fatty acid synthase (FAS), glucose-6-phosphate dehydrogenase (G6PDH), malic enzyme (ME), glucokinase (GK), pyruvate kinase (PK), glucose-6-phosphatase (G6Pase), glutamic oxaloacetic transaminase (GOT) and glutamine-pyruvate transaminase (GPT). Measurements were performed at 37 °C using an Infinite M200Pro spectrophotometer (Tecan) by monitoring the oxidation rate of NAD(P)H. Activities were expressed in mU/mg protein.

Tissue protein masses and synthesis fluxes

Protein masses and synthesis fluxes were measured in the liver, the intestine and muscles as previously described [START_REF] Mantha | Differential changes to splanchnic and peripheral protein metabolism during the diet-induced development of metabolic syndrome in rats[END_REF]. Briefly, for each tissue, the protein mass (mg N) was determined from the tissue weight, the protein content per mg fresh tissue, and the percentage nitrogen content in protein measured using elemental analysis (Vario Micro Cube; Elementar). PS was measured using the precursor-product 2 H labeling method, with 2 H enrichment measured in the free and protein-bound alanine of liver, intestine and muscles by GC-MS after ~2 days of 2 H2O exposure before euthanasia. Enrichments were calculated on the basis of a standard curve of known enrichments corrected for variations in abundance, as previously described [START_REF] Mantha | Differential changes to splanchnic and peripheral protein metabolism during the diet-induced development of metabolic syndrome in rats[END_REF]. As explained in Supplemental Text S1, in each sampled tissue (intestine, liver and muscles), the net fluxes of protein synthesized and stored in situ during the last ~2d before euthanasia were calculated as:

𝑇𝑖𝑠𝑠𝑢𝑒 𝑝𝑟𝑜𝑡𝑒𝑖𝑛 𝐹𝑆𝑅 (% 𝑑 ⁄ ) = 100 𝑡 (𝑑) × 𝑙𝑛 [ 𝐸 𝐴𝐴 -𝐸 𝑃0 𝐸 𝐴𝐴 -𝐸 𝑃 ] [1]
𝑇𝑖𝑠𝑠𝑢𝑒 𝑝𝑟𝑜𝑡𝑒𝑖𝑛 𝐴𝑆𝑅 (𝑚𝑔 𝑁 𝑑 ⁄ ) = 𝐹𝑆𝑅 (%/𝑑) 100 × 𝑡𝑖𝑠𝑠𝑢𝑒 𝑝𝑟𝑜𝑡𝑒𝑖𝑛𝑠 (𝑚𝑔 𝑁) [2] where t (d) is the period of 2 H labeling from 2 H2O injection to tissue sampling, EAA (%) is the 2 H enrichment of tissue free alanine, EP and EP0 (%) are the 2 H enrichments of protein-bound alanine at the end of the labeling period and before 2 H2O administration, respectively (with EP0 measured in 4 rats from the same batch that were euthanized at baseline). FSR (%/d) and ASR (mg/d) are the fractional and absolute synthesis rates, respectively.

Tissue lipid content and de novo lipogenesis (DNL) fluxes

Lipid masses and DNL fluxes were measured in the liver and epididymal adipose tissue. Neutral lipids (mostly exclusively triglycerides) were extracted quantitatively by the Soxhlet procedure [START_REF] Smedes | Determination of total lipid using non-chlorinated solvents[END_REF], for calculating tissue lipid content and mass. The lipid mass in whole-body adipose tissues was calculated as the product of the percentage of lipid in epididymal adipose tissue by the total fat mass measured by echo-MRI. DNL was estimated using the precursor-product 2 H labeling method, with 2 H enrichment measured in the precursor (with plasma used as a proxy) and product (tissue neutral lipids) by EA-IRMS and GC-MS, respectively. As explained in Supplemental Text S1, in the liver and total adipose tissues, the net fluxes of lipids synthesized by DNL and stored in situ during the last ~2d before euthanasia were calculated as:

𝑇𝑖𝑠𝑠𝑢𝑒 𝐷𝑁𝐿(%/𝑑) = 100 𝑡 (𝑑) × 𝑙𝑛 [ 0.48 * 𝐸 𝐵𝑊 -𝐸 𝐿𝑖𝑝0 0.48 * 𝐸 𝐵𝑊 -𝐸 𝐿𝑖𝑝 ] [3]
𝑇𝑖𝑠𝑠𝑢𝑒 𝐷𝑁𝐿 (𝑚𝑔 𝑙𝑖𝑝𝑖𝑑𝑠/𝑑) = 𝐹𝑆𝑅 (%/𝑑) 100 × 𝑡𝑖𝑠𝑠𝑢𝑒 𝑙𝑖𝑝𝑖𝑑𝑠 (𝑚𝑔) [4] where t (days) is the period of 2 H labeling from 2 H2O injection to tissue sampling, EBW (%) is the 2 H enrichment of body water (with 0.48*EBW taken as a proxy of the DNL precursor enrichment (34)), ELip and ELip0 (%) are the 2 H enrichments of the tissue neutral lipids at the end of the labeling period and before 2 H2O administration, respectively (with ELip0 measured in 4 rats from the same batch that were euthanized at baseline), and tissue lipids are the lipid masses in the liver or adipose tissues.

Finally, whole-body DNL was calculated as the sum of DNL in the liver and adipose tissues and expressed as the % of CHO intake for comparisons with findings in the literature (with glucose-to-fat conversion calculated as 2.8 g glucose/g fatty acids):

𝑊ℎ𝑜𝑙𝑒-𝑏𝑜𝑑𝑦 𝐷𝑁𝐿 (% 𝐶𝐻𝑂 𝑖𝑛𝑡𝑎𝑘𝑒) = 100×2.8 × [ 𝐿𝑖𝑣𝑒𝑟+ 𝑎𝑑𝑖𝑝𝑜𝑠𝑒 𝑡𝑖𝑠𝑠𝑢𝑒𝑠 𝐷𝑁𝐿 (𝑚𝑔 𝑙𝑖𝑝𝑖𝑑𝑠/𝑑𝑎𝑦) ] 𝐶𝐻𝑂 𝑖𝑛𝑡𝑎𝑘𝑒 (𝑚𝑔/𝑑𝑎𝑦) [5]

Natural abundances of stable N and C isotopes in tissue proteins

Natural abundances of N and C stable isotopes were measured in the proteins of the different tissues sampled and in dietary proteins, CHO and lipids, and expressed relative to standards (atmospheric N2 for 15 N/ 14 N and Vienna Pee Dee Belemnite for 13 C/ 12 C, respectively) using the delta notation:

𝛿(‰) = (𝑅𝑅 𝑠𝑎𝑚𝑝𝑙𝑒 -𝑅 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 ) / 𝑅 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 [6]
where  is the parts-per-thousand difference in the ratio of heavy to light isotopes ( 15 N/ 14 N and 13 C/ 12 C) in the samples (Rsample) and standards (Rstandard, 0.0112372 for C and 0.0036765 for N).

Isotopic measurements were performed with an isotope-ratio mass spectrometer (Isoprime; VG Instruments) coupled to an elemental analyzer (EA Vario Micro Cube; Elementar). Tyrosine was used for calibration and drift correction. δ 15 N values for tissue proteins were expressed relative to the δ-value of dietary proteins using the capital delta notation (∆tissue proteins = δtissue proteins -δdietary proteins).

As previously explained [START_REF] Mantha | Differential changes to splanchnic and peripheral protein metabolism during the diet-induced development of metabolic syndrome in rats[END_REF], the natural 15 N and 13 C fingerprints in tissue proteins were respectively used to assess the extent of tissue AA metabolic trafficking and catabolism (relative to PS), and the relative use of the different macronutrients for tissue AA synthesis.

Indeed, while tissue AA mainly originate from dietary proteins, dietary lipids and CHO are also used for the synthesis of dispensable AA via ß-oxidation and glycolysis that produce different AA precursors. Details on reasoning and equations are given in Supplemental Text S2. Briefly, during between-group comparisons, higher Δ 15 N values in tissue proteins were interpreted as indicative of increased AA metabolic trafficking and catabolism relative to PS in the tissue considered, in the light of our previous results [START_REF] Poupin | Natural Isotopic Signatures of Variations in Body Nitrogen Fluxes: A Compartmental Model Analysis[END_REF][START_REF] Cantalapiedra-Hijar | Dietanimal fractionation of nitrogen stable isotopes reflects the efficiency of nitrogen assimilation in ruminants[END_REF][START_REF] Huneau | Natural Isotope Abundances of Carbon and Nitrogen in Tissue Proteins and Amino Acids as Biomarkers of the Decreased Carbohydrate Oxidation and Increased Amino Acid Oxidation Induced by Caloric Restriction under a Maintained Protein Intake in Obese Rats[END_REF]. In addition, using the tissue protein δ 13 C values and assuming that dietary protein routing to tissue AA was affected only by the protein source (and not the energy level), we assessed the impact of the protein source on the contribution of each nutrient to tissue AA synthesis [START_REF] Mantha | Differential changes to splanchnic and peripheral protein metabolism during the diet-induced development of metabolic syndrome in rats[END_REF][START_REF] Mantha | Early changes in tissue amino acid metabolism and nutrient routing in rats fed a high-fat diet: evidence from natural isotope abundances of nitrogen and carbon in tissue proteins[END_REF].

Statistical analyses

Results are expressed as means and SEM. P-values < 0.05 were considered to be significant.

P-values close to the significance threshold (0.05≤P<0.1) were also reported. Analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). For data obtained at a single time point at the end of the experiment (natural δ 15 N abundances, PS and DNL measured by ²H labelling, hepatic lipid content, enzyme activities and some plasma biochemical values), the effects of the protein source, the energy level and their interaction were assessed using ANOVA (PROC GLM). No statistical analysis could be conducted on the nutrient routing results because the equations used to estimate the routing coefficients from the δ13C data did not provide a separate estimate for each rat but a single estimate for each group or protein source (see Supplementary Text S2). TG and G6PDH values were log transformed before analysis to meet normality. The 4-month kinetics of food intake, body weight, body composition, glucose and insulin levels were analyzed using a mixed model (PROC MIXED) with time as the repeated factor, and protein source and energy level as between-group factors. Interactions between protein source, energy level and time were also tested on the whole kinetics and at the final time. Finally, the differences between PP and AP were tested as preplanned comparisons at each level of energy, using ad hoc contrast in the ANOVA and MIXED models.

Results

Macronutrient intake, body weight and composition

Protein intake did not differ between groups while, as expected, lipids and CHO intake differed between HFS and NFS groups (125% higher lipid intake and ~50% lower CHO intake in HFS, P < 0.0001), but not between the PA and PP groups. For all groups, body weight, fat and lean masses increased with time (Figure 1). The increase observed in body weight was higher in the HFS groups than in the NFS groups, due to the higher fat mass gain and similar lean mass gain.

The protein source had no effect on body weight or composition.

Evolution of glucose homeostasis and insulin sensitivity

The post-absorptive levels of plasma glucose, insulin and HOMA-IR increased with time (Figure 2). At 4 months, the energy level (i.e., the fat and sucrose dietary contents) impacted glucose and insulin levels and HOMA-IR, which were systematically greater in the HFS groups than in the NFS groups. In contrast, the protein source affected only glucose levels, which were lower in the PP groups than in the AP groups. However, as shown by the significant interactions between the protein source and the energy level, the differences between protein sources in all these parameters were greater within the HFS context.

End point metabolite levels

To further characterize the metabolic status of the animals by the end of the study, we measured the plasma concentration of various metabolites related to lipid, nitrogen and glucose metabolisms (Figure 3). Urea and lactate concentrations were lower in the PP groups than in the AP groups while NEFA concentrations were higher. Regarding lactate, while the protein source effect was significant (P < 0.05) on all energy levels, it was only a trend (P < 0.1) at each energy level. TG levels were also lower in the PP groups than in the AP groups, but only in the NFS context (P-interaction = 0.012). No differences were found for total, HDL-and LDL-cholesterol, uric acid and creatinine concentrations.

Liver lipid content and liver and whole-body DNL fluxes

Liver lipid content and DNL were affected by both the energy level and the protein source, with values higher by 41% and 49% respectively (P < 0.001) in the HFS groups than in the NFS groups and values lower by 17% and 24% (P < 0.05) in the PP groups than in the AP groups (Figure 4). Regarding liver DNL, while the protein source effect was significant (P < 0.05) on all energy levels, it was only a trend (P < 0.1) at each energy level. Adipose tissue DNL (data not shown) and whole-body DNL were affected only by the energy level, with higher levels in the HFS groups than in the NFS groups (P < 0.001).

Protein synthesis and macronutrient contribution to AA synthesis and routing to tissue proteins

Protein synthesis was affected only in two organs (see Table 2). Compared to NFS, HFS groups had higher protein mass and ASR in the liver but lower protein FSR and ASR in the gastrocnemius muscle. The results obtained for macronutrient routing to tissue proteins are presented in Figure 5. Only the effect of the protein source was explored, as the energy level effect on the routing of dietary protein to tissue protein was assumed to be comparatively negligible (Supplemental Text 2). Compared to AP, PP groups had a lower direct contribution of dietary protein-bound AA to tissue protein-bound AA in all the sampled tissues (up to a ~3% absolute decrease in liver, where protein routing dropped from 79% in AP to 76% in PP groups).

In contrast, in PP vs AP groups, dietary CHO and lipids contributed slightly more to tissue deposition of dispensable AA via glycolysis and ß-oxidation (up to 1.5% and 1% absolute increases in liver for CHO and lipid routings, respectively, on average for both energy levels but with the same trend for each).

Extent of AA metabolic trafficking in tissues

The tissue protein ∆ 15 N values (i.e., the natural nitrogen isotopic distance between tissue proteins and dietary proteins, or trophic step) reflect the intensity of AA trafficking by transamination and deamination relative to their direct use for protein anabolism and turn-over, as these metabolic pathways are fractionating processes that amplify the ∆ 15 N trophic step [START_REF] Mantha | Differential changes to splanchnic and peripheral protein metabolism during the diet-induced development of metabolic syndrome in rats[END_REF][START_REF] Poupin | Natural Isotopic Signatures of Variations in Body Nitrogen Fluxes: A Compartmental Model Analysis[END_REF][START_REF] Cantalapiedra-Hijar | Dietanimal fractionation of nitrogen stable isotopes reflects the efficiency of nitrogen assimilation in ruminants[END_REF][START_REF] Huneau | Natural Isotope Abundances of Carbon and Nitrogen in Tissue Proteins and Amino Acids as Biomarkers of the Decreased Carbohydrate Oxidation and Increased Amino Acid Oxidation Induced by Caloric Restriction under a Maintained Protein Intake in Obese Rats[END_REF][START_REF] Mantha | Early changes in tissue amino acid metabolism and nutrient routing in rats fed a high-fat diet: evidence from natural isotope abundances of nitrogen and carbon in tissue proteins[END_REF]. ∆ 15 N values measured in the protein of the intestine, liver and muscles are presented in Figure 6. Compared to AP, the PP groups had higher ∆ 15 N values and thus higher rates of AA metabolic trafficking in all tissues. In addition, in all tissues except gastrocnemius muscle, there was a significant interaction (a trend in tibialis anterior muscle) between protein source and energy level, showing smaller differences between protein sources in the HFS context.

Hepatic enzyme activities

The activity levels of limiting hepatic enzymes related to DNL, glucose and AA metabolism are presented in Figure 7. Regarding DNL, FAS and G6PDH (which contribute to the NADPH production) activities were lower in the HFS groups than in the NFS groups. Regarding the protein effect, the activity levels were lower in the PP groups than the AP groups for ACL and G6PDH irrespectively of the energy context, while for FAS this reduction was visible in the NFS context only (P-interaction = 0.040). ME, another NADPH producer, had similar activities across groups. GK and PK, both key enzymes of glycolysis, were down-regulated in HFS vs NFS groups, and GK activity was also lower in the PP groups than in the AP groups. The activity of G6Pase, involved in the glucose export into the blood stream, was similar across diets. Regarding AA metabolism, the GPT activity was higher in the PP and HFS groups compared to the AP and NFS groups. GOT activity was not modified by experimental diets.

Discussion

We have shown that compared to the standard AP used in reference rodent diets (milk protein), a balanced blend of PP (50:50 wheat:pea) similarly supports the lean mass gain and tissue protein turnover in growing rats, while protecting against metabolic dysregulations induced by excessive intakes of saturated fat and sucrose. Thus, in such a western dietary context, dietary PP limit whole-body IR and fat deposition in the liver, with lower hepatic lipid storage and DNL and higher rates of nutrient oxidation in the intestine, liver and muscles. We evidenced a higher routing of dietary lipids and CHO oxidation products towards PS after PP feeding than AP feeding, accompanying and possibly compensating for the higher AA trafficking by transamination and deamination. Since, in the present study, differences between the AP and PP diets specifically lie in their protein isolate fraction, in the next sections we discuss these metabolic differences in the light of the distinct AA profiles of AP and PP.

Protein source effects on protein and AA metabolism in tissues

Dietary AP and PP (when provided as a well-balanced 50:50 wheat:pea blend) had an equivalent ability to support lean mass growth and tissue PS in growing rats fed ad libitum.

These results, in line with other findings in the rodent literature [START_REF] Berrazaga | Anabolic Properties of Mixed Wheat-Legume Pasta Products in Old Rats: Impact on Whole-Body Protein Retention and Skeletal Muscle Protein Synthesis[END_REF], support the idea that the balanced AA profile of wheat and legume protein blends are equivalent to the reference AP for sustaining protein anabolism.

In contrast with the tissue protein accretion and turnover, the metabolic trafficking of AA in tissues differed between the dietary protein sources studied. Compared to AP, PP induced higher AA transamination and/or deamination in tissues, as shown by the higher natural nitrogen isotopic distances between tissue and dietary proteins (∆ 15 N). This evidences an enhancement of such fractionating processes [START_REF] Mantha | Differential changes to splanchnic and peripheral protein metabolism during the diet-induced development of metabolic syndrome in rats[END_REF][START_REF] Poupin | Natural Isotopic Signatures of Variations in Body Nitrogen Fluxes: A Compartmental Model Analysis[END_REF], in line with previous ∆ 15 N findings in rats fed with other PP and AP [START_REF] Poupin | The Nature of the Dietary Protein Impacts the Tissue-to-Diet 15N Discrimination Factors in Laboratory Rats[END_REF]. Here, higher ∆ 15 N values with PP more likely reflect increased transamination than increased deamination, as supported by the higher activity of hepatic GPT and lower plasma urea levels. Of note, the lower plasma urea levels in the PP-fed rats may not only result from lower urea production, but also from higher enterohepatic urea hydrolysis and nitrogen salvage, in line with our previous findings showing the increase in both urea production and urea recycling with PP [START_REF] Fouillet | Urea-nitrogen production and salvage are modulated by protein intake in fed humans: results of an oral stableisotope-tracer protocol and compartmental modeling[END_REF]. Furthermore, we found that dispensable AA supply for tissue PS relied less on dietary AA with PP than AP, while dietary CHO and lipids contributed more through enhanced glycolysis and ß-oxidation, as evidenced by the natural carbon isotopic distances between tissue and dietary proteins (∆ 13 C). Overall, the observed metabolic differences between PP and AP reflected specific responses to their distinct AA profiles, given that AA intake from AP better matches metabolic tissue demands and requires less metabolic trafficking prior to incorporation into tissue proteins (4). The AA profile of PP not only enhances AA transamination but also glycolysis and lipolysis, which sustains the routing of AA toward PS in tissues. In contrast, the AA profile of AP could increase urea production to dispose AA in excess to the metabolic demand and/or decrease urea recycling when nitrogen salvage is useless [START_REF] Fouillet | Urea-nitrogen production and salvage are modulated by protein intake in fed humans: results of an oral stableisotope-tracer protocol and compartmental modeling[END_REF].

Protein source effects on insulin sensitivity

In our study, the long-term intake of PP compared to that of AP resulted in lower fasting plasma glucose and insulin levels, as well as reduced HOMA-IR (the latter two in the HFS context only). In the rodent literature, PP blends have often been compared to AP in a NFS dietary context, which may explain the lack of effects, or only small, effects on glucose homeostasis [START_REF] Macarthur | Total protein, not amino acid composition, differs in plantbased versus omnivorous dietary patterns and determines metabolic health effects in mice[END_REF][START_REF] Lamming | Short-term consumption of a plant protein diet does not improve glucose homeostasis of young C57BL/6J mice[END_REF][START_REF] Chen | The Effect of Vegan Protein-Based Diets on Metabolic Parameters, Expressions of Adiponectin and Its Receptors in Wistar Rats[END_REF]. Similarly, in short-term clinical interventions, no specific effects of the protein source on glucose homeostasis were observed [START_REF] González-Salazar | Effect of the intake of dietary protein on insulin resistance in subjects with obesity: a randomized controlled clinical trial[END_REF][START_REF] Hill | Type and amount of dietary protein in the treatment of metabolic syndrome: a randomized controlled trial[END_REF][START_REF] Li | Effects of Dietary Protein Source and Quantity during Weight Loss on Appetite, Energy Expenditure, and Cardio-Metabolic Responses[END_REF]. These contrasted findings could be related to the duration of the dietary exposure, shorter in both animal studies and human clinical trials than in our experiment (4 months), when accounting for the differences in life expectancy.

Indeed, when long-term exposures were considered in human observational studies, AP intake was rather positively associated with IR (12) and T2D (14,[START_REF] Zhao | Dietary protein intake and risk of type 2 diabetes: a dose-response meta-analysis of prospective studies[END_REF], in line with the current study.

In this sense, because our study consisted in a long-term dietary exposure with highly controlled protein sources in a HFS dietary context, our findings add an important line of evidence in comparison to noisier human interventions, by highlighting the beneficial effects of PP-feeding on insulin sensitivity.

Interestingly, we also reported lower plasma lactate in PP, compared to AP. To the best of our knowledge, this is the first time that this metabolite, whose elevated levels are often associated with obesity and TD2 [START_REF] Adeva-Andany | Comprehensive review on lactate metabolism in human health[END_REF], has been related to protein sources. Therefore, the role of this particular pathway deserves further exploration in future studies.

Protein source effects on lipid metabolism

Compared to AP, long-term PP intake favored liver homeostasis with a lower lipid accumulation and DNL, whatever the dietary energy level. In particular, we found that the metabolic machinery of the liver better responded to HFS exposure when the protein source was PP, with coordinated changes in intermediary metabolism resulting in limiting DNL and lipid accumulation. These changes consisted in direct changes on DNL, like lower ACL activity, but also indirect adaptations like reduced CHO influx via glycolysis (lower GK activity) ultimately feeding DNL, or restricted pentose phosphate cycle limiting the availability of NADPH donors (lower G6PD activity) to DNL. These results are in line with other studies in rodents involving PP like soy [START_REF] Torres | Regulation of lipid metabolism by soy protein and its implication in diseases mediated by lipid disorders[END_REF][START_REF] Tovar | The role of dietary protein on lipotoxicity[END_REF][START_REF] Xiao | Effect of soy proteins and isoflavones on lipid metabolism and involved gene expression[END_REF] or beans [START_REF] Watanabe | Dietary Mung Bean Protein Reduces Hepatic Steatosis, Fibrosis, and Inflammation in Male Mice with Diet-Induced, Nonalcoholic Fatty Liver Disease[END_REF][START_REF] Hernandez-Velazquez | Black bean protein concentrate ameliorates hepatic steatosis by decreasing lipogenesis and increasing fatty acid oxidation in rats fed a high fat-sucrose diet[END_REF], and are also supported by the positive association found in humans between AP intake and non-alcoholic fatty liver disease in humans [START_REF] Alferink | Association of dietary macronutrient composition and non-alcoholic fatty liver disease in an ageing population: the Rotterdam Study[END_REF].

In conjunction with lower hepatic lipid storage and DNL, we observed better insulin sensitivity following PP feeding than AP. There are two possible intertwined explanations for these concomitant findings. On the one hand, hepatic lipid accumulation is known to suppress signaling through the insulin pathway, thereby promoting IR. On the other hand, IR favors DNL and lipid storage, which in turn promotes further IR in a vicious cycle [START_REF] Sanders | De novo lipogenesis in the liver in health and disease: more than just a shunting yard for glucose[END_REF]. In addition, the glycolytic potential was lower after PP than AP intake, while oxidation products of dietary CHO and lipids from both glycolysis and lipolysis were routed more to PS. These metabolic shifts could also contribute to a lower substrate availability for DNL and thus restrain lipid accumulation.

Causal role of distinct protein source AA profiles

The differences in AA composition between protein sources provide mechanistic hypotheses for their metabolic effects evidenced here, as AP are richer in indispensable (BCAA) and PP in dispensable AA (cysteine, arginine and glycine), which have been positively and negatively linked to cardiometabolic risk, respectively [START_REF] Lépine | A Scoping Review: Metabolomics Signatures Associated with Animal and Plant Protein Intake and Their Potential Relation with Cardiometabolic Risk[END_REF].

Regarding BCAA, dietary restriction in rodents was reported to improve glucose homeostasis [START_REF] Cummings | Restoration of metabolic health by decreased consumption of branched-chain amino acids[END_REF][START_REF] Fontana | Decreased Consumption of Branched-Chain Amino Acids Improves Metabolic Health[END_REF][START_REF] White | Branched-chain amino acid restriction in Zucker-fatty rats improves muscle insulin sensitivity by enhancing efficiency of fatty acid oxidation and acylglycine export[END_REF], while BCAA or leucine supplementation in a high fat context either promoted IR [START_REF] Newgard | A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance[END_REF] or preserved insulin sensitivity [START_REF] Roquetto | Moderate intake of BCAA-rich protein improves glucose homeostasis in high-fat-fed mice[END_REF][START_REF] Macotela | Dietary Leucine -An Environmental Modifier of Insulin Resistance Acting on Multiple Levels of Metabolism[END_REF]. These contrasted findings could be related to differences in background diets, as suggested by a recent meta-analysis of the rodent literature [START_REF] Solon-Biet | Meta-analysis links dietary branched-chain amino acids to metabolic health in rodents[END_REF]. In humans, BCAA intake has generally been associated with impaired glucose homeostasis [START_REF] Zheng | Cumulative consumption of branched-chain amino acids and incidence of type 2 diabetes[END_REF][START_REF] Karusheva | Short-term dietary reduction of branched-chain amino acids reduces meal-induced insulin secretion and modifies microbiome composition in type 2 diabetes: a randomized controlled crossover trial[END_REF]. On the other hand, glycine, cysteine and arginine intake have been associated with improved glucose homeostasis (64-66). In rodents, supplementation studies with these AA have reported reduced oxidative stress, a potential explanatory mechanism for preserved insulin sensitivity [START_REF] El-Hafidi | Glycine Increases Insulin Sensitivity and Glutathione Biosynthesis and Protects against Oxidative Stress in a Model of Sucrose-Induced Insulin Resistance[END_REF][START_REF] Blouet | Dietary cysteine alleviates sucrose-induced oxidative stress and insulin resistance[END_REF][START_REF] Hong | Watermelon and l-arginine consumption improve serum lipid profile and reduce inflammation and oxidative stress by altering gene expression in rats fed an atherogenic diet[END_REF][START_REF] Kim | Effects of exercise and L-arginine intake on inflammation in aorta of high-fat diet induced obese rats[END_REF]. Beneficial effects of glycine and arginine supplementation on insulin sensitivity have been also reported in humans [START_REF] Gannon | The metabolic response to ingested glycine[END_REF][START_REF] Monti | l-Arginine enriched biscuits improve endothelial function and glucose metabolism: A pilot study in healthy subjects and a cross-over study in subjects with impaired glucose tolerance and metabolic syndrome[END_REF], their respective circulating concentrations being rather low in T2D [START_REF] Alves | Glycine Metabolism and Its Alterations in Obesity and Metabolic Diseases[END_REF][START_REF] Yu | Changes in Arginine are Inversely Associated with Type 2 Diabetes: A Case-Cohort Study in the PREDIMED Trial[END_REF], often in conjunction with elevated BCAA levels regarding glycine [START_REF] White | Insulin action, type 2 diabetes, and branched-chain amino acids: A two-way street[END_REF].

This study has several strengths. With the use of purified isoproteic and isocaloric diets, the observed metabolic effects could be directly attributed to the protein sources, and with the use of protein isolates, even more specifically to their AA profiles. The relatively long experimental duration in rats also represents long-term dietary exposure. With the combined use of cuttingedge isotopic methods and traditional approaches, we obtained an integrative view of the metabolic shifts between PP and AP at both whole-body and tissue levels. Our study has also some limits, like the exclusive nature of the protein source in the diet (100% AP or 100% PP), favoring a straight-forward mechanistical interpretation of the effects, but rather difficult to translate into the classical range of AP:PP consumption ratio in human diets (about 70:30 in western countries ( 76)).

Conclusion

PP intake adequately supported tissue PS and body weight gain in growing rats while limiting whole body and liver metabolic dysregulations induced by HFS diets. These effects could be related to the fact that the AA profile of PP, which is less optimal for direct channelling to protein synthesis than that of AP, stimulated other metabolic pathways like AA transamination, glycolysis and lipolysis while down-regulating others, such as DNL. These combined effects involving highly intertwined metabolic pathways could explain, at least in part, the beneficial effect on cardiometabolic health of PP per se, which could therefore account for some of the beneficial effects of plant-based diets. These metabolic adaptations induced by specific protein sources deserve further exploration at the molecular level using omics approaches and within more realistic dietary settings in human dietary interventions.

Tables Table 1. Composition of experimental diets containing either animal (AP) or plant (PP) proteins and being either normal (NFS) or high (HFS) in fat and sucrose In each sampled tissue, this product synthesis estimate corresponds to its mean value over both the postprandial and postabsorptive states over the labeling period, i.e., over the last ~2d of 2 H labeling before euthanasia (the labeling duration having been chosen to reach reliably detectable 2 H enrichment levels). As during this period, some newly synthesized product may have left the tissue by product degradation or export, this estimate also only represents the net flux of product that was synthesized and stored in the considered tissue over the period. Supplemental Text S2: Assessment of tissue amino acid (AA) trafficking and macronutrients contribution to tissue AA synthesis by natural nitrogen and carbon isotopic distances between tissue proteins and nutrients (Δ 15 N and Δ 13 C), respectively

NFS-AP

HFS-AP

NFS-PP

HFS-PP

Extent of tissue AA metabolic trafficking and catabolism relative to protein synthesis

Although dietary protein N is the sole source of body protein N, body proteins are naturally enriched over dietary protein in the heavier stable N isotope ( 15 N). This 15 N bioaccumulation (Δ 15 N) is globally due to discrimination against this heavy isotope during N waste formation by urea production, with the existence of several isotope effects associated with amino acid (AA) transaminations and deamination (6)(7)(8). Indeed, as variations in the relative orientation of tissue AA towards catabolic or anabolic processes can result in Δ 15 N changes, Δ 15 N values differ between tissues and subjects because of their particular AA metabolism (7,9). Through mechanistic modeling, we have shown that Δ 15 N measurements in tissue proteins represent integrated biomarkers for tissue AA partitioning between oxidation and protein synthesis, and vary as a function of the extent of AA metabolic trafficking and catabolism (7). In the present study, during between-group comparisons, higher Δ 15 N values were interpreted as indicative of increased AA metabolic trafficking and catabolism, in the light of these previous modelling outputs (7) and other consistent experimental results (8,10).

Assessment of macronutrients contribution to AA synthesis and routing to tissue proteins

By contrast, the heavier stable C isotope ( 13 C) bioaccumulates only modestly and its natural abundance in tissues mainly reflects that of the diet and provides information on the dietary origin of tissue AA (11)(12)(13). Even though dietary proteins are preferentially routed to tissue proteins as AA, dietary lipids and CHO are used for the biosynthesis of non-indispensable AA, via ß-oxidation and glycolysis that produce different AA precursors (11), and the extent of each nutrient routing to protein synthesis can vary with the dietary protein source and energy level (5,11,12,14). As the three macronutrients differed in terms of their δ 13 C value, the δ 13 C of tissue proteins represents the sum of macronutrient δ 13 C values weighted by their respective contributions to C in tissue proteins (routing coefficients), plus the difference in δ 13 C between diet and tissue proteins due to isotopic fractionation along metabolic pathways (the trophic step). As previously explained (5,14), we thus derived a system of equations explaining the δ 13 C of tissue proteins by the δ 13 C of macronutrients, where the unknowns were the routing coefficients (p, c and l, representing the proportions of protein, CHO and lipids routed to C in tissue proteins, respectively) and the trophic step (TS). This equation system has to be solved theoretically for each diet, as each parameter (p, c, l and TS) can depend on the dietary protein source and energy level. However for identifiability reasons and as in our previous study (14), p (but not c and l) was assumed to depend only of the dietary protein source (P = AP or PP) and not of the energy level (E = NFS or HFS), which allowed solving the system as: p P = (δ 13 CE NFS -δ 13 CE HFS + δ 13 CT HFS-P -δ 13 CT NFS-P ) / (δ 13 CE NFS -δ 13 CE HFS ) [1] TS P = (δ 13 CT NFS-P -δ 13 CE NFS ) -(δ 13 CE NFS -δ 13 CE HFS + δ 13 CT HFS-P -δ 13 CT NFS-P )*(δ 13 CP Pδ 13 CE NFS )/(δ 13 CE NFS -δ 13 CE HFS ) [2] c E-P = (δ 13 CT E-P -δ 13 CL E -TS P + p P *(δ 13 CL E -δ 13 CP P )) / (δ 13 CC E -δ 13 CL E ) [3] l E-P = 1-p P -c E-P [4] where δ 13 CT E-P , δ 13 CP P , δ 13 CC E , δ 13 CL E and δ 13 CE E , are respectively the δ 13 C values of proteins in a tissue, of dietary proteins, of dietary CHO, of dietary lipids and of dietary nonprotein energy sources (both CHO and lipids) in the diet with the dietary protein source P (P = AP or PP) and the energy level E (E = NFS or HFS); p P , c E-P and l E-P are the proportions of protein, CHO and lipids routed to C in tissue proteins (i.e., the routing coefficients) in the diet with the dietary protein source P and the energy level E, and TS P the trophic step in the diet with the dietary protein source P.

Because of their different CHO and lipid contents, the NFS and HFS diets differed in terms of their δ 13 CE which was calculated as the average δ 13 C of lipids and CHO weighted by their C content and dietary occurrence as follows (11,12): δ 13 CE E = [(%C E *0.444)/(%L E *0.768 + %C E *0.444)]*δ 13 CC E + [(%L E *0.768)/(%L E *0.768 + %C E *0.444)]*δ 13 CL E [5] where %C E and %L E are dietary mass fractions of carbohydrates and lipids in the diet with the dietary energy level E and 0.444 and 0.768 are the reference C mass fractions of CHO and lipids, respectively. Finally, using the mean isotopic data for each diet, we derived one estimate for each protein source (PP and AP) for p, and one estimate for each diet for c and l. In the results (Fig. 5), we presented the protein source effect (PP vs AP) on the nutrient routing coefficients p, c and l calculated as:

Δp PP-AP = p PP -p AP [6] Δc PP-AP = [(c NFS-PP -c NFS-AP ) + (c HFS-PP -c HFS-AP )] / 2 [7] Δl PP-AP = [(l NFS-PP -l NFS-AP ) + (l HFS-PP -l HFS-AP )] / 2 [8] Of note, we here assumed that p depended only of the protein source and not of the energy level of the diet, this simplifying hypothesis being necessary to solve the equation system in our particular context. Nevertheless, in order to a posteriori test the validity of this simplifying hypothesis, we have verified that the individual estimates here obtained for each diet were consistent with those we previously obtained in another rat experiment where no simplifying hypothesis was required because of an isotopic experimental design fully adapted to the estimation of the nutrient routing coefficients (5). The individual estimates obtained here, ranging across diets from 76% to 79% for p values, from 8% to 18% for c values and from 5% to 14% for l values, were indeed fully in line with our previous estimates. Also in line with our hypothesis and results, other findings in the literature have shown that p varies only little under a broad range of dietary conditions, except for diets markedly deficient or excessive in protein (11).

FiguresFigure 1 :

 1 Figures

Figure 2 :

 2 Figure 2: Changes in plasma glucose (A), plasma insulin (B) and HOMA-IR (C) in rats fed with diets containing either animal (AP) or plant (PP) proteins and being either normal (NFS) or high (HFS) in fat and sucrose. Data are mean + SEM values (n=44) expressed as increase in percentage of their baseline values. † 0.05 <P<0.1; * P<0.05. Effects at the final time of the dietary energy level (Energy), protein source (Protein) and their interaction (Energy x Protein), as tested with ANOVA.

Figure 3 :

 3 Figure 3: Plasma metabolite concentrations at 4.5 months in rats fed with diets containing either animal (AP) or plant (PP) proteins and being either normal (NFS) or high (HFS) in fat and sucrose. Data are mean + SEM values for urea (A, n=43), uric acid (B, n=42), lactate (C, n=42), creatinine (D, n=44), triglycerides (E, n=43), non-esterified fatty acids (F, n=44), total cholesterol (G, n=43), LDL-cholesterol (H, n=43) and HDL-cholesterol (I, n=43) levels. † 0.05 <P<0.1; * P<0.05; ** P<0.01: effects of the dietary energy level (Energy), protein source (Protein) and their interaction (Energy x Protein), as tested with ANOVA.

Figure 4 :

 4 Figure 4: Liver lipid content (A), liver de novo lipogenesis (DNL) (B) and whole-body DNL (C) levels at 4.5 months in rats fed with diets containing either animal (AP) or plant (PP) proteins and being either normal (NFS) or high (HFS) in fat and sucrose. Data are mean + SEM values (n=44). † 0.05 <P<0.1; ** P<0.01: effects of the dietary energy level (Energy), protein source (Protein) and their interaction (Energy x Protein), as tested with ANOVA.

Figure 5 :

 5 Figure 5: Dietary protein source effect on the relative contribution of macronutrients to tissue protein-bound amino acids. Values represent the absolute differences between plant (PP) and animal (AP) protein diets in their dietary protein, CHO and lipid routings to the proteins of intestine, liver and muscles (see Supplemental text 2 for explanations). Data from of tibialis anterior and gastrocnemius muscles were similar and thus merged. n=44

Figure 6 :

 6 Figure 6: Natural nitrogen isotopic distances between tissue and dietary proteins (Δ 15 N) representing the extent of amino acid metabolic trafficking in tissues at 4.5 months in rats fed with diets containing either animal (AP) or plant (PP) proteins and being either normal (NFS) or high (HFS) in fat and sucrose. Data are mean + SEM values for Δ 15 N (‰) in intestine (A), liver (B), tibialis anterior muscle (C) and gastrocnemius muscle (D, n=44). * P<0.05; ** P<0.01; *** P<0.001: effects of the dietary energy level (Energy), protein source (Protein) and their interaction (Energy x Protein), as tested with ANOVA.

Figure 7 :

 7 Figure 7: Hepatic enzyme activities at 4.5 months in rats fed with diets containing either animal (AP) or plant (PP) proteins and being either normal (NFS) or high (HFS) in fat and sucrose. Data are mean + SEM values in mU/mg of protein of fatty acid synthase (FAS) (A, n=37), ATPcitrate lyase (ACL) (B, n=44), glucose-6-phosphate dehydrogenase (G6PDH) (C, n=44), malic enzyme (ME) (D, n=44), glucokinase (GK) (E, n=42), pyruvate kinase (PK) (F, n=44), glucose-6-phosphatase (G6pase) (G, n=44), glutamic oxaloacetic transaminase (GOT) (H, n=44) and glutamine-pyruvate transaminase (GPT) (I, n=44) enzymatic activities. ** P<0.01; * P<0.05: effects of the dietary energy level (Energy), protein source (Protein) and their interaction (Energy x Protein), as tested with ANOVA.

Table 2 :

 2 Fractional synthesis rates (FSR, %/d), absolute synthesis rates (ASR, mg N/d) and masses (mg N) of tissue proteins in intestine, liver and skeletal muscles at 4.5 months in rats fed with diets containing either animal (AP) or plant (PP) proteins and being either normal (NFS) or high (HFS) in fat and sucrose 1 .

			NFS-AP	NFS-PP	HFS-AP	HFS-PP	Effects
		FSR (%/d)	59.4 ± 2.4	50.5 ± 3.4	52.7 ± 3.0	54.9 ± 9.9
	Intestine	ASR (mg N/d) 93.3 ± 6.9	84.6 ± 9.4	94.9 ± 9.0	94.8 ± 6.4
		Mass (mg N) 157.0 ± 10.1 164.9 ± 9.2 179.5 ± 11.6 175.6 ± 9.9
		FSR (%/d)	36.9 ± 1.4	35.3 ± 1.3	35.3 ± 1.2	35.2 ± 1.4
	Liver	ASR (mg N/d) 164.3 ± 8.7 145.2 ± 10.1 183.0 ± 13.0 177.7 ± 13.0	Energy P=0.03 (HFS>NFS)
		Mass (mg N) 446.3 ± 21.8 409.2 ±20.1 518.7 ± 34.9 500.6 ± 22.8	Energy P=0.003 (HFS>NFS)
	Tibialis	FSR (%/d)	4.5 ± 0.3	4.6 ± 0.3	4.3 ± 0.2	4.3 ± 0.3
	anterior	ASR (mg N/d)	1.2 ± 0.1	1.2 ± 0.1	1.1 ± 0.1	1.1 ± 0.1
	muscle	Mass (mg N)	26.9 ± 0.9	27.0 ± 1.3	26.3 ± 0.8	26.4 ± 0.7
							Energy P=0.019
	Gastrocn emius muscle	FSR (%/d) ASR (mg N/d)	3.6 ± 0.2 3.4 ± 0.2	3.9 ± 0.2 3.7 ± 0.2	3.5 ± 0.2 3.2 ± 0.2	3.1 ± 0.2 2.8 ± 0.1	(HFS<NFS) Interaction P=0.071 Energy P=0.018 (HFS<NFS)
		Mass (mg N)	94.0 ± 2.5	93.2 ± 3.9	91.8 ± 1.9	91.4 ± 2.5

Data are mean ± SEM values, n=44. * P<0.05; ** P<0.01: effects of the dietary energy level (Energy), protein source (Protein) and their interaction (Energy x Protein), as tested with ANOVA. No significant difference was observed for all variables in preplanned comparisons (NFS-AP vs NFS-PP and HFS-AP vs HFS-PP).

Acknowledgments H.F, S.P, J-F. H, F.M and D.R designed the research; S.P, H.F, G.L., J.D and V.M conducted the research and analyzed the data. G.L., H.F and S.P wrote the first draft of the manuscript. H.F, S.P, J-F. H, F.M, D.R, D.H, N.P, C. L-M, L. G-D provided critical comments on the manuscript. H.F and S.P had primary responsibility for final content, and all authors have read and approved the final manuscript.

The authors thank the staff of the IEN Animal Facility (P. Lhoste, P. Denis and J. Hermet) for technical assistance.

The French National Research Institute for Agriculture, Food and Environment (INRAE) funded the experimental and analytical costs (Action Prioritaire ProVegOmics). Conflict of interest and funding disclosure: GL PhD grant is funded by INRAE and Roquette, under the scientific supervision of SP and HF. LG-D and CL-M are employees of Roquette Frères. The other authors declare no conflicts of interest.

Supplementary data

Supplemental Figure S1: Relative amino acid composition of animal protein (milk) and plant protein (50% pea : 50% wheat) isolates, expressed as percentage of the animal protein isolate composition and calculated with information provided by protein isolate suppliers

Supplemental Text S1: Protein synthesis and de novo lipogenesis assessments by 2 H precursor-product labeling

In this work, we used the deuterated method to concomitantly estimate protein synthesis and de novo lipogenesis by 2 H labeling of their respective precursors and products (1)(2)(3)(4). Whatever the precursor-product couple considered, the enrichment in the product is known to increase exponentially with time towards its final equilibrium value, i.e., the precursor's enrichment being stable over time, according to the following general equation ( 5):

where t (day) is the labeling period (i.e., the period of 2 H exposure from 2 H2O injection to tissue sampling), Eprecursor (%) is the 2 H enrichment in precursor being stable over the labeling period, Eproduct and Eproduct_baseline (%) are the 2 H enrichments in product at time t and before labeling (i.e., before 2 H2O injection), respectively, and FSR (%/day) is the fractional rate of product synthesis from precursor. The fractional (FSR, %/day) and absolute (ASR, mg/day) rates of product synthesis from precursor can thus be calculated as:

𝐴𝑆𝑅 (𝑚𝑔 𝑑𝑎𝑦 ⁄ ) = 𝐹𝑆𝑅 (%/𝑑𝑎𝑦) 100 × 𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑝𝑜𝑜𝑙 𝑠𝑖𝑧𝑒 (𝑚𝑔) [3]


Mohamed Boutahar

Limiting distribution of the least squares estimates in polynomial regression with long memory noises

Keywords: Fractional Brownian motion, Long memory, Multiple Wiener-Itô integral, Polynomial regression, Stochastic integral

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