Toshiyuki Imasawa
email: imasawa@nifty.com

Stéphane Claverol
email: stephane.claverol@u-bordeaux.fr

Didier Lacombe
email: didier.lacombe@chu-bordeaux.fr

Nivea Dias

Rodrigue Rossignol
email: rodrigue.rossignol@u-bordeaux.fr

Proteomic Study of Low-Birth-Weight Nephropathy in Rats

Keywords: low birth weight, nephropathy, proteomics, kidney, mitochondria

The hyperfiltration theory has been used to explain the mechanism of low birth weight (LBW)-related nephropathy. However, the molecular changes in the kidney proteome have not been defined in this disease, and early biomarkers are lacking. We investigated the molecular pathogenesis of LBW rats obtained by intraperitoneal injection of dexamethasone into pregnant animals. Normal-birth-weight (NBW) rats were used as controls. When the rats were four weeks old, the left kidneys were removed and used for comprehensive label-free proteomic studies. Following uninephrectomy, all rats were fed a high-salt diet until 9 weeks of age. Differences in the molecular composition of the kidney cortex were observed at the early step of LBW nephropathy pathogenesis. Untargeted quantitative proteomics showed that proteins involved in energy metabolism, such as oxidative phosphorylation (OXPHOS), the TCA cycle, and glycolysis, were specifically downregulated in the kidneys of LBW rats at four weeks. No pathological changes were detected at this early stage. Pathway analysis identified NEFL2 (NRF2) and RICTOR as potential upstream regulators. The search for biomarkers identified components of the mitochondrial respiratory chain, namely, ubiquinol-cytochrome c reductase complex subunits (UQCR7/11) and ATP5I/L, two components of mitochondrial F 1 F O -ATP synthase. These findings were further validated by immunohistology. At later stages of the disease process, the right kidneys revealed an increased frequency of focal segmental glomerulosclerosis lesions, interstitial fibrosis and tubular atrophy. Our findings revealed proteome changes in LBW rat kidneys and revealed a strong downregulation of specific mitochondrial respiratory chain proteins, such as UQCR7.

Introduction

Infants born at less than 2500 g are designated with a low birth weight (LBW). LBW individuals have an increased risk of heart disease, diabetes mellitus, and kidney disease. In particular, LBW is associated with an increased risk of chronic kidney disease (CKD) [START_REF] Hirano | Association between low birth weight and childhood-onset chronic kidney disease in Japan: A combined analysis of a nationwide survey for paediatric chronic kidney disease and the National Vital Statistics Report[END_REF][START_REF] Esmeijer | Low Birth Weight and Kidney Function in Middle-Aged Men and Women: The Netherlands Epidemiology of Obesity Study[END_REF] or end-stage renal disease [START_REF] Vikse | Low birth weight increases risk for end-stage renal disease[END_REF][START_REF] Ruggajo | Low Birth Weight and Risk of Progression to End Stage Renal Disease in IgA Nephropathy-A Retrospective Registry-Based Cohort Study[END_REF] and has become a global concern [START_REF] Luyckx | Birth weight, malnutrition and kidney-associated outcomes-A global concern[END_REF]. LBW is also significantly associated with a decreased number of nephrons in both humans and animals [START_REF] Hughson | Glomerular number and size in autopsy kidneys: The relationship to birth weight[END_REF][START_REF] Vehaskari | Prenatal programming of adult hypertension in the rat[END_REF][START_REF] Koike | Glomerular Density and Volume in Renal Biopsy Specimens of Children with Proteinuria Relative to Preterm Birth and Gestational Age[END_REF]. The molecular mechanism(s) underlying the deterioration of kidney function in LBW individuals remain unclear and no association with familial factors could be observed in a national registry composed of 1,852,080 individuals [START_REF] Ruggajo | Familial Factors, Low Birth Weight, and Development of ESRD: A Nationwide Registry Study[END_REF]. The current paradigm for LBW pathogenesis reflects Brenner's theory (also known as the glomerular hyperfiltration theory), where adaptive mechanisms are activated in response to nephron loss and a subsequent increase in capillary pressure [START_REF] Brenner | The hyperfiltration theory: A paradigm shift in nephrology[END_REF]. Such adaptation results in a vicious cycle promoting further progression of chronic kidney disease (CKD). Until now, the developmental origins of health and diseases (DOHaD) in the kidney have been preferentially explained by this mechanism [START_REF] Bagby | Developmental origins of renal disease: Should nephron protection begin at birth?[END_REF][START_REF] Gurusinghe | Developmental Origins and Nephron Endowment in Hypertension[END_REF], although the molecular pathogenetic mechanisms remain unclear [START_REF] Eriksson | In Reply to "Low Birth Weight: Intrauterine Growth Restriction or Prematurity?[END_REF].

The most characteristic glomerular change in LBW individuals is focal segmental glomerulosclerosis (FSGS) [START_REF] Hodgin | Very low birth weight is a risk factor for secondary focal segmental glomerulosclerosis[END_REF]. We previously reported that the pathological findings of human kidney biopsy specimens were similar between patients with mitochondrial DNA (mtDNA) mutations and those with LBW-related nephropathy [START_REF] Imasawa | Pathological similarities between low birth weight-related nephropathy and nephropathy associated with mitochondrial cytopathy[END_REF]. Therefore, we hypothesized that mitochondrial defects could participate in LBW-related kidney disease. Using untargeted and powerful analytic methods as proteomics, we recently unraveled the molecular alterations in human podocytes challenged with hyperglycemia and discovered a specific program of metabolic pathway reprogramming regulated by MEF2C and MYF5 [START_REF] Imasawa | High glucose repatterns human podocyte energy metabolism during differentiation and diabetic nephropathy[END_REF]. Likewise, a large-scale untargeted quantitative and comprehensive analysis of the molecular alterations in the kidney proteome could provide a dataset of shared interest for understanding the mechanisms underlying the development of LBW-related nephropathy. However, the omics of LBW kidneys remain unknown, and no dataset is available for performing pathway and biomarker analyses. In particular, the bioinformatic study of proteome changes could allow for prediction of the putative transcription factors, kinases or microRNAs involved in the observed changes based on the detailed knowledge of their targets and directionality of the expected changes in target expression. We recently used this predictive strategy to discover the role of various genetic regulators in different disease contexts [START_REF] Imasawa | High glucose repatterns human podocyte energy metabolism during differentiation and diabetic nephropathy[END_REF][START_REF] Szelechowski | Metabolic Reprogramming in Amyotrophic Lateral Sclerosis[END_REF][START_REF] Esteves | Nuclear control of lung cancer cells migration, invasion and bioenergetics by eukaryotic translation initiation factor 3F[END_REF][START_REF] Amoedo | Targeting the mitochondrial trifunctional protein restrains tumor growth in oxidative lung carcinomas[END_REF]. Of note, a clearer understanding of the molecular basis of diabetic nephropathy was obtained using large-scale characterization proteomics, and innovative therapeutic approaches can be derived from this knowledge [START_REF] Papale | Proteomics and diabetic nephropathy: What have we learned from a decade of clinical proteomics studies?[END_REF][START_REF] Joanna | Applying Proteomics and Integrative "Omics" Strategies to Decipher the Chronic Kidney Disease-Related Atherosclerosis[END_REF]. Therefore, similar approaches could be tested for LBW nephropathy.

To investigate molecular candidates involved in LBW-related nephropathy, we developed a rat model of human LBW-related nephropathy and performed a comprehensive untargeted proteomic study of the kidneys between LBW and NBW rats at a young age, when neither group had any pathological changes. These studies could reveal the early pathological factors underlying LBW-related nephropathy.

Results

Clinical and Histopathological Characteristics of LBW Rats

We generated a rat model of LBW as previously described [START_REF] Benediktsson | Glucocorticoid exposure in utero: New model for adult hypertension[END_REF] and summarized in (Figure 1A) to study early molecular alterations of the kidney. As shown in (Table 1), we compared rats in the two different body weight groups: NBW (n = 7) vs. LBW (n = 7). The body weights of LBW rats were consistently and significantly less than those of NBW rats at birth and remained lower at 4 and 9 weeks of age. The kidney weights of the LBW rats were also significantly less than those of NBW rats at 4 weeks of age. Clinical pathology examination revealed that the glomerular numbers per section of the LBW rats were significantly fewer than those of NBW rats at 4 weeks of age (Table 1). The product of glomerular number per section and kidney weight should be proportional to the total glomerular number. These products of LBW rats at 4 weeks old were significantly lower than those of NBW rats at 4 weeks old (Table 1), which should indicate that the total nephron numbers in LBW rats are lower than those in NBW rats as previously reported [START_REF] Hughson | Glomerular number and size in autopsy kidneys: The relationship to birth weight[END_REF][START_REF] Vehaskari | Prenatal programming of adult hypertension in the rat[END_REF][START_REF] Koike | Glomerular Density and Volume in Renal Biopsy Specimens of Children with Proteinuria Relative to Preterm Birth and Gestational Age[END_REF]. In addition, although glomerular sizes of LBW rats were significantly lower than those of the NBW group at 4 weeks old, the sizes became compatible between LBW rats and NBW rats at 9 weeks old (Table 1). These results suggested that the glomeruli with originally small sizes in LBW rats were enlarged with body growth, which should be due to glomerular hyperfiltration by intraglomerular hypertension. The molecular mechanisms underpinning the above-described changes in kidney physiology remain unclear and will be investigated in what follows. There were no sclerotic lesions or any other pathological changes in glomeruli and tubules of either the LBW or NBW rats at 4 weeks of age (Figure 1). However, although glomeruli in 9-week-old NBW rats appeared almost normal (Figure 2a-d), FSGS with a predominance of perihilar lesions of sclerosis was apparently formed in 9-week-old LBW rats (Figure 2e-h). At 9 weeks of age, FSGS lesions were observed in 7.43% of the glomeruli in LBW rats but in only 0.48% of the NBW rats (Table 1). The incidence of interstitial fibrosis and tubular atrophy (IFTA) was also higher in LBW rats than in NBW rats at 9 weeks of age (Table 1). Furthermore, such histological damage was associated with an increase in serum creatinine levels in LBW rats (Table 1). The serum creatinine levels of the 9-week-old LBW rats were greater than those of the same age NBW rats, which indicated that the LBW rats also had worse kidney function accompanied by histological damage (Table 1).

Early Kidney Proteome Remodeling in LBW Rats

To unravel the early changes in LBW rats before pathological changes occurred in the kidney, we performed quantitative proteomic analyses on kidney cortices taken at 4 weeks of age, when the rats in both groups exhibited no pathological changes. A total of 1200 proteins were found in the rat kidney and 437 proteins were detected as differentially expressed (p < 0.05) between LBW and NBW rats at this time point (Table S1A). Further analysis of the proteomic dataset using a multiple comparison method with Benjamini-Hochberg correction allowed us to calculate the adjusted p-value (q value; Table S1B). The threshold for the false discovery rate (FDR) was set at q = 0.01. The dataset is available to the community through the public repository PRIDE using the accession number PXD018948. The volcano plot of the comparative proteomics data (using the q value) is shown in Figure 3A, and the top 10 proteins are listed in Table 2. The volcano plot showed that a large number of proteins were downregulated in the LBW kidney (top left quadrant). Several mitochondrial proteins responsible for energy transduction, such as different F 1 F O -ATP synthase subunits or complex III subunits, were strongly reduced in LBW kidneys (blue dots on the volcano plot), as shown in (Figure 3B). In contrast, the upregulated proteins revealed an increase in specific regulators of the cell proteome, such as Meprin A subunits α and β in the LBW kidney cortex or activator protein 1 (AP-1), among others. Lastly, several proteins belonging to the functional networks 'cellular assembly and organization' were identified (Figure S1), suggesting a perturbation of plasma membrane homeostasis in the LBW kidney cortex. The Y-axis indicates the significance of the changes in protein content, expressed as -Log(q value). The significance threshold of p = 0.05 (-Log(q value) = 1.3) was selected on the graph. The reduced proteins (in the LBW group) belonging to the

Metabolic and Signaling Pathways Altered in LBW Kidney

Analysis of the above-described proteomic data was performed using Ingenuity Pathway Analysis (IPA) software version July 2021. The LBW rat kidney differential proteome composed of 1183 proteins was compared to the IPA Knowledge database to detect enrichment in specific pathways using the 'core analysis' module. The results revealed that the main four pathways (ranked by log 10 p-value with Z > 1 and -logP < 3) altered in the LBW rat kidneys were EIF2 signaling, oxidative phosphorylation (OXPHOS; Z-score -1.9), TCA cycle, and sirtuin signaling (Figure 4A; Table S2). Glycolysis and gluconeogenesis were also reduced, with 48% of the pathway components downregulateded in LBW kidney. These findings indicate that the main machinery required for energy transduction was inhibited in LBW kidneys, suggesting a reduction in energy metabolism. Intermediate metabolism pathways involved in catabolism and energy metabolism were also altered in the LBW kidney proteome, as shown for fatty acid oxidation (Figure 4B). A significant modulation of two pathways involved in protein translation was also observed: 'EIF2 signaling' (-logp-value = 19.8) and 'Eif4 and P70S6K signaling' (-logp-value = 11.4). Lastly, the catabolism of branched chain amino acids (BCAAs) was strongly altered in the LBW kidneys (valine degradation, -logp-value = 11.1).

Predicted Genetic Regulators Involved in LBW Kidney Remodeling

Analysis of the proteins with altered content (p < 0.05) in the LBW kidney allowed us to predict putative transcription factors, kinases, proteases, or even microRNAs involved in the observed changes based on the knowledge of the targets associated with specific regulators and the directionality of the expected changes. Such a bioinformatic predictive analysis was performed on the LBW kidney proteome. The results (Table S2) identified a series of regulators potentially involved in LBW kidney proteome reprogramming, indicating that LBW kidney remodeling impacts different signaling pathways. The top two regulators (Z-score and p-value) were rapamycin-insensitive companion of mTOR (RICTOR) and NFE2L2 (NRF2), as a large number of their respective targets were found in the LBW differential proteome dataset (Table 3). These predictive findings unravel the complexity of the early molecules occurring in LBW kidneys and identify different signaling path-

Mitochondrial Biomarkers of LBW Kidney Remodeling

The above-described proteomic investigation of the molecular changes occurring in LBW kidney cortices revealed the top alterations in mitochondrial proteins (Table 2). To validate these findings, we performed immunohistological analyses on kidney tissues obtained from 4-week-old LBW rats. The top downregulated protein was UQCR7, a subunit of the respiratory chain complex III (Table 2, Figure 3B). UQCR7 staining showed a positive signal in glomerular tufts, in vascular smooth muscle cells of arterioles, and along the apical membrane of distal tubular cells in NBW rats (Figure 5a-c,e-g). UQCR7 expression was significantly decreased in LBW rats compared with NBW rats (Figure 5i-k). Furthermore, proteomics revealed that key catalytic components of complex V, the F 1 F O -ATP synthase responsible for ATP synthesis, were also reduced in the cortex of LBW rats (Table 2, Figure 3B). Accordingly, immunohistology analysis demonstrated that 'e' subunit (Atp5I) expression was strongly markedly suppressed in tubular cells of LBW rats in contrast with NBW rats (Figure 5d,h,l). These findings indicate that UQCR7 and Atp5I are two mitochondrial proteins indicative of early kidney proteome alteration in LBW rats.

was significantly decreased in LBW rats compared with NBW rats (Figure 5i-k). Furthermore, proteomics revealed that key catalytic components of complex V, the F1FO-ATP synthase responsible for ATP synthesis, were also reduced in the cortex of LBW rats (Table 2, Figure 3B). Accordingly, immunohistology analysis demonstrated that 'e' subunit (Atp5I) expression was strongly markedly suppressed in tubular cells of LBW rats in contrast with NBW rats (Figure 5d,h,l). These findings indicate that UQCR7 and Atp5I are two mitochondrial proteins indicative of early kidney proteome alteration in LBW rats. (a-c). On the other hand, UQCR expression was markedly decreased in LBW rats (e-g). Atp5I was positive in tubular cells in NBW rats (d). Atp5I expression was weakened in LBW rats (h). The numbers of UQCR7-positive tufts per glomerulus (i), semiquantitative scoring of the UQCR7 staining intensity in the glomerular vascular pole (j), the rates of UQCR-positive cells in distal tubular cells on their apical membrane (k), and the percentages of Atp5I-positive tubular cells (l) were statistically analyzed. * p < 0.05 by unpaired t-test. ** p < 0.01 by unpaired t-test.

Discussion

In this study, we investigated the early molecular changes in the kidney proteome in a rat model of LBW-related nephropathy. We considered the hypothesis of fetal programming proposed by Brenner and colleagues [START_REF] Luyckx | Birth weight, malnutrition and kidney-associated outcomes-A global concern[END_REF][START_REF] Hershkovitz | Fetal programming of adult kidney disease: Cellular and molecular mechanisms[END_REF] and searched for proteomic differences between the kidney cortices from rats with a low vs. normal birth weight. We first generated a rat model of LBW-related nephropathy using glucocorticoid treatment and validated several aspects of the previously described LBW-related kidney disease [START_REF] Hughson | Glomerular number and size in autopsy kidneys: The relationship to birth weight[END_REF][START_REF] Hodgin | Very low birth weight is a risk factor for secondary focal segmental glomerulosclerosis[END_REF]. Several animal models for fetal programming of adult disease have been developed using nutrition, surgery, hypoxia, pharmacology, and stress [START_REF] Vuguin | Animal models for small for gestational age and fetal programming of adult disease[END_REF]. The antenatal glucocorticoid (a-c). On the other hand, UQCR expression was markedly decreased in LBW rats (e-g). Atp5I was positive in tubular cells in NBW rats (d). Atp5I expression was weakened in LBW rats (h). The numbers of UQCR7-positive tufts per glomerulus (i), semiquantitative scoring of the UQCR7 staining intensity in the glomerular vascular pole (j), the rates of UQCR-positive cells in distal tubular cells on their apical membrane (k), and the percentages of Atp5I-positive tubular cells (l) were statistically analyzed. * p < 0.05 by unpaired t-test. ** p < 0.01 by unpaired t-test.

Discussion

In this study, we investigated the early molecular changes in the kidney proteome in a rat model of LBW-related nephropathy. We considered the hypothesis of fetal programming proposed by Brenner and colleagues [START_REF] Luyckx | Birth weight, malnutrition and kidney-associated outcomes-A global concern[END_REF][START_REF] Hershkovitz | Fetal programming of adult kidney disease: Cellular and molecular mechanisms[END_REF] and searched for proteomic differences between the kidney cortices from rats with a low vs. normal birth weight. We first generated a rat model of LBW-related nephropathy using glucocorticoid treatment and validated several aspects of the previously described LBW-related kidney disease [START_REF] Hughson | Glomerular number and size in autopsy kidneys: The relationship to birth weight[END_REF][START_REF] Hodgin | Very low birth weight is a risk factor for secondary focal segmental glomerulosclerosis[END_REF]. Several animal models for fetal programming of adult disease have been developed using nutrition, surgery, hypoxia, pharmacology, and stress [START_REF] Vuguin | Animal models for small for gestational age and fetal programming of adult disease[END_REF]. The antenatal glucocorticoid treatment used for intrauterine growth retardation was validated in previous studies, showing a consistent reduction in glomerular number and filtration rate, increased apoptosis, and altered plasma sodium concentration [START_REF] Celsi | Prenatal dexamethasone causes oligonephronia, sodium retention, and higher blood pressure in the offspring[END_REF][START_REF] Martins | Renal function in adult rats subjected to prenatal dexamethasone[END_REF][START_REF] Schreuder | Glomerular number and function are influenced by spontaneous and induced low birth weight in rats[END_REF]. However, when the rats were 9 weeks old, there was no significant difference in glomerular size between LBW rats and NBW rats. This finding suggests that glomerular hyperfiltration might occur in LBW rats and suggest the rat model used in our work is suitable, from the pathophysiology and histology standpoints, for investigating the pathogenesis of LBW-related nephropathy.

At 4 weeks of age, there were no pathological abnormalities in the kidneys of either LBW rats or NBW rats. Therefore, prospective and untargeted quantitative proteomic analyses were performed using kidney samples from 4-week-old rats to identify intrinsic factors potentially linked with the pathogenesis of LBW-related nephropathy. The proteomic analysis extensively described in our work revealed that the molecular pathways involved in energy transduction, such as oxidative phosphorylation, the TCA cycle, and glycolysis, were specifically downregulated in the kidneys of LBW rats at early time points of the disease. This observation suggests that alteration in energy metabolism is an early and intrinsic determinant of LBW kidney dysfunction. In particular, the content of respiratory chain complex III and complex V subunits was strongly reduced, as verified by immunohistology. More precisely, the expression of UQCR7, UQCR11, and Atp5I and ATP5L in tubular cells was markedly decreased in the kidneys of 4-week-old LBW rats. UQCR7 expression was markedly decreased not only in glomerular tufts but also in vascular smooth muscle cells, particularly in those of the afferent arterioles. As previously reported, the characteristic pathological change in LBW individuals is FSGS with a predominance of perihilar lesions of sclerosis, probably due to disturbance of intraglomerular hemodynamic status [START_REF] Hodgin | Very low birth weight is a risk factor for secondary focal segmental glomerulosclerosis[END_REF][START_REF] Imasawa | Pathological similarities between low birth weight-related nephropathy and nephropathy associated with mitochondrial cytopathy[END_REF]. Therefore, dysfunction of OXPHOS in afferent arterioles of LBW rat glomeruli could result in autoregulation failure of intraglomerular pressure, which eventually should develop FSGS lesions. Although analyses using newborn rat kidneys are the most suitable for the pathogenesis of DOHaD in the kidney, the cortex volumes of kidneys at birth are not sufficient for molecular investigations. As we used kidneys from 4-week-old rats when no pathological abnormalities were observed, the results of proteomic and immunohistological analyses may not be the end result but could participate in the cause of nephropathy in adulthood. Our results are in agreement with previous reports that showed tubular dysfunction in LBW individuals [START_REF] Lee | Incidence and outcomes of acute kidney injury in extremely-low-birth-weight infants[END_REF][START_REF] Matsumura | Tubular dysfunction in extremely low birth weight survivors[END_REF]. The discovery of altered mitochondrial proteostasis in an LBW nephropathy rat model is in agreement with previous studies showing that mitochondria play important roles in renal pathophysiology [START_REF] Imasawa | Pathological similarities between low birth weight-related nephropathy and nephropathy associated with mitochondrial cytopathy[END_REF][START_REF] Hall | The not so "mighty chondrion": Emergence of renal diseases due to mitochondrial dysfunction[END_REF][START_REF] Weinberg | Mitochondrial biogenesis in kidney disease[END_REF][START_REF] Zhan | Mitochondrial dynamics: Regulatory mechanisms and emerging role in renal pathophysiology[END_REF][START_REF] Che | Mitochondrial dysfunction in the pathophysiology of renal diseases[END_REF][START_REF] Sharma | Metabolomics reveals signature of mitochondrial dysfunction in diabetic kidney disease[END_REF][START_REF] Stangenberg | Fetal programming of chronic kidney disease: The role of maternal smoking, mitochondrial dysfunction, and epigenetic modfification[END_REF][START_REF] Imasawa | Podocyte energy metabolism and glomerular diseases[END_REF][START_REF] Miyazaki | FP827 the impact of pathological findings of mitochondrial disorders in low birth weight infants[END_REF]. The pathological similarities between low-birth-weight-related nephropathy and nephropathy associated with mitochondrial cytopathy were further discussed in our previous report [START_REF] Imasawa | Pathological similarities between low birth weight-related nephropathy and nephropathy associated with mitochondrial cytopathy[END_REF].

Another finding of our study concerned the catabolism of branched chain amino acids (BCAAs), which was strongly altered in the LBW kidneys (17 proteins). Abnormal BCAA metabolism can result in BCAA depletion in the plasma, but this has not been verified in the blood of LBW patients. However, a prospective study performed on 15 patients with early stages of chronic kidney disease showed a significant decrease in plasma valine and leucine levels compared with controls [START_REF] Kumar | Branched chain amino acid profile in early chronic kidney disease[END_REF]. BCAAs can also stimulate mitochondrial biogenesis [START_REF] Valerio | Branched-chain amino acids, mitochondrial biogenesis, and healthspan: An evolutionary perspective[END_REF], suggesting that the reduction in 97 mitochondrial proteins observed in LBW kidneys could be linked to reduced BCAA metabolism. The survey of the top ten proteomic changes revealed a significant increase in the expression of Meprin A (two subunits) in the kidney cortex of LBW rats. This protein is a protease that cleaves a large number of targets in the kidney, including extracellular matrix (ECM) proteins, modulators of inflammation, and proteins involved in the protein kinase A (PKA) and PKC signaling pathways [START_REF] Gooding | Meprin β metalloproteases associated with differential metabolite profiles in the plasma and urine of mice with type 1 diabetes and diabetic nephropathy[END_REF]. Meprins have been implicated in the pathophysiology of diabetic nephropathy (DN), acute kidney injury (AKI), and fibrosis-associated kidney disease. Studies in diabetic mouse models suggested that Meprin A plays a protective role in the kidney [START_REF] Bylander | Meprin Metalloprotease Deficiency Associated with Higher Mortality Rates and More Severe Diabetic Kidney Injury in Mice with STZ-Induced Type 1 Diabetes[END_REF], raising the need to evaluate in more detail the implication of Meprin A in LBW nephropathy progression or protection.

Computer analysis of the untargeted proteomic dataset generated in our work also predicted the alteration of mTOR signaling in LBW. Accordingly, a considerable number of studies have shown the involvement of mTOR and RICTOR in nephropathies [START_REF] Gödel | Role of mTOR in podocyte function and diabetic nephropathy in humans and mice[END_REF][START_REF] Inoki | mTORC1 activation in podocytes is a critical step in the development of diabetic nephropathy in mice[END_REF]. Mitochondrial biogenesis and mTOR are two actionable pathways using pharmacological drugs such as bezafibrate and resveratrol for the former [START_REF] Augustyniak | Bezafibrate Upregulates Mitochondrial Biogenesis and Influence Neural Differentiation of Human-Induced Pluripotent Stem Cells[END_REF][START_REF] Chuang | Resveratrol Promotes Mitochondrial Biogenesis and Protects against Seizure-Induced Neuronal Cell Damage in the Hippocampus Following Status Epilepticus by Activation of the PGC-1α Signaling Pathway[END_REF] and rapamycin or evelorimus for the latter [START_REF] Kajiwara | Role of mTOR Inhibitors in Kidney Disease[END_REF]. In addition, treatments to restore kidney bioenergetics might provide therapeutic benefits. In support of this claim, recent studies using mitochondrial protective drugs showed improved renal function in swine with atherosclerotic renovascular disease, renal ischemia, and atherosclerotic renal artery stenosis [START_REF] Eirin | Mitochondrial protection restores renal function in swine atherosclerotic renovascular disease[END_REF][START_REF] Liu | Novel cardiolipin therapeutic protects endothelial mitochondria during renal ischemia and mitigates microvascular rarefaction, inflammation, and fibrosis[END_REF][START_REF] Eirin | A mitochondrial permeability transition pore inhibitor improves renal outcomes after revascularization in experimental atherosclerotic renal artery stenosis[END_REF]. Moreover, the predictive analysis of the LBW differential proteomic data identified NFE2L2 (NRF2) signaling as the main inhibited pathway. NRF2 not only protects mitochondria as a major antioxidant orchestrator but also regulates mitochondrial biogenesis [START_REF] Ryoo | Regulatory crosstalk between the oxidative stress-related transcription factor Nfe2l2/Nrf2 and mitochondria[END_REF][START_REF] Vomund | Nrf2, the Master Regulator of Anti-Oxidative Responses[END_REF]. Therefore, the reduction in respiratory chain protein levels in LBW kidneys could also be explained by the observed inhibition of NRF2. Therefore, NRF2 activators might also be interesting candidates for the prevention of LBW-related nephropathy, as considered in other nephropathies [START_REF] Chin | Bardoxolone Methyl Improves Kidney Function in Patients with Chronic Kidney Disease Stage 4 and Type 2 Diabetes: Post-Hoc Analyses from Bardoxolone Methyl Evaluation in Patients with Chronic Kidney Disease and Type 2 Diabetes Study[END_REF][START_REF] De Zeeuw | Bardoxolone methyl in type 2 diabetes and stage 4 chronic kidney disease[END_REF][START_REF] Nagasu | Bardoxolone methyl analog attenuates proteinuria-induced tubular damage by modulating mitochondrial function[END_REF].

To conclude, the proteomic and histopathology study of an LBW rat model generated a unique dataset of interest for generating novel hypotheses on the pathogenesis of LBW nephropathy. We unraveled changes in proteins such as Meprin A, UQCR7/11 and Atp5I/L that occurred early in the disease process, suggesting that these elements are potential players in the molecular determinants of this disorder. However, our findings remain limited to the rat model used. Technical and methodological limitations also exist in our study, as only 1200 proteins were found in the rat kidney proteome. This number is low as compared to the reference rat proteome dataset although a recent analysis found a similar number of distinct proteins (1290) in rat kidney [START_REF] Hariri | Proteome profiling in the aorta and kidney of type 1 diabetic rats[END_REF]. Therefore, our findings might have considered only the most abundant proteins of rat kidney. Our study might therefore indicate a new mechanism of DOHaD in kidney diseases other than hyperfiltration theory.

Methods

Rats

The rats were treated in accordance with the guidelines of the Committee on Ethical Animal Care and Use of the National Hospital Organization Chiba-Higashi National Hospital. Eight pregnant rats were fed standard chow ad libitum. By intraperitoneally injecting dexamethasone (DEXA) (0.2 mg/kg) into pregnant rats (n = 5) consecutively at 15 and 16 days of gestation, LBW rats were born at high rates, as shown in previous reports [START_REF] Benediktsson | Glucocorticoid exposure in utero: New model for adult hypertension[END_REF]. For controls, we injected the same volume of saline (n = 3). Only newborn male rats were selected for this experiment. We first measured body weights of the normal newborn male rats (n = 22), with a mean ± SD of 6.44 ± 0.47 g. We then selected seven rats weighing less than 5.51 g (under the mean-2 SD of NBW) from 38 newborn male rats obtained from DEXA-injected mothers. As normal controls, we selected seven rats weighing > 6.4 g. Consequently, the means ± SE of body weights of the rats used for the subsequent experiments were 5.01 ± 0.11 and 6.93 ± 0.10 in the LBW (n = 7) and NBW (n = 7) rat groups, respectively (p < 0.001, Table 1).

Newborn rats remained with their dams until they were 4 weeks old, at which point they were removed from the cages and provided standard chow ad libitum. When the rats were 4 weeks old, the left kidneys were removed. These extracted kidneys were separated for histological and proteomic analyses. The kidneys were horizontally cut, and specimens from the center were used for light microscopic analysis. For the light microscopy studies, kidney specimens were fixed in 10% neutral-buffered formalin followed by paraffin embedding and routine staining with Masson's trichrome stain, or periodic acid-methenamine-silver (PAM) with hematoxylin and eosin (HE) (PAM-HE) stain. PAM-HE-stained images of paraffin-embedded kidney sections were imported into a vertical slide system. The glomerular size was automatically calculated by manually outlining the glomerular tuft area on the display. The kidney specimens used for the proteomics studies were only obtained from the cortex area. After separating the cortex from the medulla, the isolated cortex specimens were immediately frozen in liquid nitrogen and stored at -80 • C until further analysis. After uninephrectomy, all rats were fed a high-salt diet consisting of 8% NaCl until they were 9 weeks old. After sacrifice, the right kidneys were removed and separated for histological analyses in the same way as those at 4 weeks of age.

Immunohistochemical Analysis

Primary antibodies were anti-UQCR polyclonal antibody (14793-1-AP; Proteintech) and anti-ATP5I polyclonal antibody (ab122241; Abcam). Antigen retrieval was performed according to the manufacturer's instructions. Numbers of UQCR7-positive tufts per glomerulus were counted in more than ten glomeruli per kidney section. The relative amounts of UQCR7 staining in vascular poles of glomeruli were also scored semiquantitatively in more than ten glomeruli per kidney section as follows: 0 = negative staining, 1 = positive in less than 50% of the circumference of vascular pole, 2 = positive in

Figure 1 .

 1 Figure 1. LBW rat model generation protocol and study. (A) Schematic representation of the LBW rat model generation protocol used in our study. Details on kidney sampling, clinical pathology, and molecular investigations are given in the methods. (B) Representative photographs of NBW (a,b) and LBW (c,d) rat kidney sections at 4 weeks of age. (a,c) are lowmagnification images of Masson trichrome staining. (b,d) are photos of PAM-HE staining. Scale bars are provided in each figure. There were no pathological abnormalities in either group. Glomerular sizes in LBW rats appeared to be smaller than those in NBW rats.

Figure 1 .

 1 Figure 1. LBW rat model generation protocol and study. (A) Schematic representation of the LBW rat model generation protocol used in our study. Details on kidney sampling, clinical pathology, and molecular investigations are given in the methods. (B) Representative photographs of NBW (a,b) and LBW (c,d) rat kidney sections at 4 weeks of age. (a,c) are low-magnification images of Masson trichrome staining. (b,d) are photos of PAM-HE staining. Scale bars are provided in each figure. There were no pathological abnormalities in either group. Glomerular sizes in LBW rats appeared to be smaller than those in NBW rats.

17 Figure 2 .

 172 Figure 2. Sclerotic lesions in LBW kidney sections at 9 weeks of age. There were no pathological abnormalities in glomeruli of the NBW rats (a-c: Masson trichrome, d: PAM-HE). However, in LBW rats, sclerotic lesions were observed predominantly in the perihilar area (indicated by arrows) (e-g: Masson trichrome, h: PAM-HE).

Figure 2 .

 2 Figure 2. Sclerotic lesions in LBW kidney sections at 9 weeks of age. There were no pathological abnormalities in glomeruli of the NBW rats (a-c: Masson trichrome, d: PAM-HE). However, in LBW rats, sclerotic lesions were observed predominantly in the perihilar area (indicated by arrows) (e-g: Masson trichrome, h: PAM-HE).

Figure 3 .

 3 Figure 3. Comprehensive label-free proteomic analysis of LBW nephropathy. (A) Scatter plot (volcano plot) of the differential proteomic study between LBW and NBW kidney cortices at 4 weeks. The X-axis shows the difference in protein expression between the LBW and NBW groups (expressed as the absolute difference in protein normalized abundance).The Y-axis indicates the significance of the changes in protein content, expressed as -Log(q value). The significance threshold of p = 0.05 (-Log(q value) = 1.3) was selected on the graph. The reduced proteins (in the LBW group) belonging to the

Figure 3 .

 3 Figure 3. Comprehensive label-free proteomic analysis of LBW nephropathy. (A) Scatter plot (volcano plot) of the differential proteomic study between LBW and NBW kidney cortices at 4 weeks. The X-axis shows the difference in protein expression between the LBW and NBW groups (expressed as the absolute difference in protein normalized abundance). The Y-axis indicates the significance of the changes in protein content, expressed as -Log(q value). The significance threshold of p = 0.05 (-Log(q value) = 1.3) was selected on the graph. The reduced proteins (in the LBW group) belonging to the oxidative phosphorylation machinery are shown as blue dots on the left quadrant. (B) The changes in mitochondrial respiratory chain proteins are shown in a schematic representation. Each respiratory chain complex is depicted, and the subunits detected in the differential proteomic analysis are shown in green (repressed in LBW kidney) or pink (increased in LBW kidney).

  ways and regulators potentially involved in the LBW kidney gene expression program and signature. Int. J. Mol. Sci. 2021, 22, 10294 9 of 17

Figure 4 .

 4 Figure 4. Pathway analysis of LBW kidney proteome remodeling. (A) The proteomic data were analyzed using IPA software to identify changes in signaling and metabolic pathways altered in the LBW group (core analysis; Qiagen). The

Figure 4 .

 4 Figure 4. Pathway analysis of LBW kidney proteome remodeling. (A) The proteomic data were analyzed using IPA software to identify changes in signaling and metabolic pathways altered in the LBW group (core analysis; Qiagen). The background gene-set for 'core analysis' was set to 'Ingenuity Knowledgebase'. The IPA canonical pathways altered in the LBW kidney were ranked by p-value and colored according to the Z-score (blue = pathway inhibited and orange = pathway activated). The dotted yellow lines indicate the threshold for p-value set at 0.05. The ratio line (orange) indicates the number of proteins altered in the dataset as compared to the number of proteins described in the IPA pathway. (B) Detail of the fatty acid oxidation pathway inhibited in LBW kidney. Repressed proteins are shown as green symbols, while overexpressed proteins shown pink. The dotted blue lines indicate a consistent observation between a predicted inhibition of the target and the actual decreased content of the protein. The lines in yellow indicate that the findings are inconsistent with the prediction. Lines in gray indicate that the effect was not predicted.

Figure 5 .

 5 Figure 5. Reduced content of UQCR and Atp5 measured by IHC in LBW kidney. Immunohistochemistry (IHC) analyses of NBW and LBW kidney sections obtained from 4-week-old rats. UQCR7 was expressed in glomerular tufts (blue arrows), in arterioles (mainly by vascular smooth muscle cells) (yellow arrows), and along the apical membrane of distal tubules (red arrows)(a-c). On the other hand, UQCR expression was markedly decreased in LBW rats (e-g). Atp5I was positive in tubular cells in NBW rats (d). Atp5I expression was weakened in LBW rats (h). The numbers of UQCR7-positive tufts per glomerulus (i), semiquantitative scoring of the UQCR7 staining intensity in the glomerular vascular pole (j), the rates of UQCR-positive cells in distal tubular cells on their apical membrane (k), and the percentages of Atp5I-positive tubular cells (l) were statistically analyzed. * p < 0.05 by unpaired t-test. ** p < 0.01 by unpaired t-test.

Figure 5 .

 5 Figure 5. Reduced content of UQCR and Atp5 measured by IHC in LBW kidney. Immunohistochemistry (IHC) analyses of NBW and LBW kidney sections obtained from 4-week-old rats. UQCR7 was expressed in glomerular tufts (blue arrows), in arterioles (mainly by vascular smooth muscle cells) (yellow arrows), and along the apical membrane of distal tubules (red arrows)(a-c). On the other hand, UQCR expression was markedly decreased in LBW rats (e-g). Atp5I was positive in tubular cells in NBW rats (d). Atp5I expression was weakened in LBW rats (h). The numbers of UQCR7-positive tufts per glomerulus (i), semiquantitative scoring of the UQCR7 staining intensity in the glomerular vascular pole (j), the rates of UQCR-positive cells in distal tubular cells on their apical membrane (k), and the percentages of Atp5I-positive tubular cells (l) were statistically analyzed. * p < 0.05 by unpaired t-test. ** p < 0.01 by unpaired t-test.

Table 1 .

 1 Basic characteristics and data from histological analysis of the rats. NBW (n = 7): group of rats born with a normal birth weight, LBW (n = 7): group of rats born with a low birth weight. Data represent mean ± SE. * The unpaired t-test is used for the comparison of two groups. BW, body weight; KW, kidney weight; IFTA, interstitial fibrosis and tubular atrophy. 'na' means not applicable.

	NBW	LBW	p *

Table 2 .

 2 Top 10 changes in the kidney proteome in LBW rats at 4 weeks. Top ten increased and top ten decreased proteins are shown (p < 0.05).

	Accession	ANOVA (p)	LBW/NBW Ratio	Description
	P15800	1.54 × 10 -3	3.03	Laminin subunit beta-2
	O35077	2.59 × 10 -3	2.87	Glycerol-3-phosphate dehydrogenase [NAD(+)], cytoplasmic
	P02770	3.54 × 10 -5	2.78	Serum albumin
	D4A994	2.12 × 10 -2	2.62	Protein Emc1
	D3ZTX4	5.90 × 10 -4	2.60	Uncharacterized protein
	Q6IFW6	5.04 × 10 -3	2.39	Keratin, type I cytoskeletal 10
	Q64230	1.47 × 10 -4	2.28	Meprin A subunit alpha
	P28826	3.94 × 10 -4	2.23	Meprin A subunit beta
	G3V8X5	2.63 × 10 -3	2.18	Protein Slc5a10
	P01048	3.68 × 10 -4	2.13	T-kininogen 1
	P62898	1.41 × 10 -4	0.42	Cytochrome c, somatic
	P11517	4.97 × 10 -4	0.41	Hemoglobin subunit beta-2
	P05765	4.84 × 10 -3	0.40	40S ribosomal protein S21
	B2RYS2	8.74 × 10 -5	0.39	Cytochrome b-c1 complex subunit 7
	Q9JI66	2.10 × 10 -2	0.36	Electrogenic sodium bicarbonate cotransporter 1
	P61459	1.89 × 10 -3	0.36	Pterin-4-alpha-carbinolamine dehydratase
	Q6PDU7	2.15 × 10 -4	0.35	ATP synthase subunit g, mitochondrial
	P70623	8.68 × 10 -4	0.34	Fatty acid-binding protein, adipocyte
	A2VD16	4.75 × 10 -3	0.32	Aldo-keto reductase family 1, member C12-like 1
	P29419	1.69 × 10 -5	0.30	ATP synthase subunit e, mitochondrial

Table 3 .

 3 Top two regulators of the observed LBW kidney proteome reprogramming and their targets predicted by Ingenuity Pathway Analysis.

	Upstream Regulator	Activation Z-Score	p-Value	Target Molecules in LBW Dataset
					ATP5F1A, ATP5F1B, ATP5F1C, ATP5MF, ATP5MG, ATP5PB, ATP5PD,
					ATP5PF, ATP5PO, ATP6AP1, ATP6V0A4, ATP6V0D1, ATP6V1A,
					ATP6V1B2, ATP6V1C1, ATP6V1C2, ATP6V1E1, ATP6V1F, BSG, COX5A,
					NDUFA10, NDUFA6, NDUFB5, NDUFS1, NDUFS2, NDUFS3, NDUFS8,
	RICTOR	Activated	3.842	6.28 × 10 -36	NDUFV1, PPA2, PSMA1, PSMA5, PSMA6, PSMB1, PSMB3, PSMB5, PSMB7, PSMD1, PSMD11, PSMD12, PSMD2, PSMD3, PSMD6, PSMD7, PSME2,
					RPL10, RPL10A, RPL13A, RPL14, RPL17, RPL23, RPL26, Rpl34 (includes
					others), RPL4, RPL6, RPL7A, RPS10, RPS11, RPS18, RPS19, RPS2, RPS21,
					RPS24, RPS29, RPS3, Rps3a1, RPS6, RPS8, SDHA, SDHB, SDHC, SDHD,
					Uba52, UQCR7, UQCRC1, UQCRC2, UQCRQ
					AKR1A1, AKR1B10, AKR7A2, ALDOA, ARF1, ATP1A1, CALB1, CAT,
					CCT3, CCT7, CTSD, Cyp4a14, CYP4A22, DAD1, DDX39B, DNAJB11,
					DNAJC3, EIF2S1, EIF3E, EIF3G, ENTPD5, EPHX1, ERP29, ESD, FABP4,
					FMO1, FN1, FTL, G6PD, GCLC, GCLM, GNAI2, GPX1, GSR, GSS, Gsta1,
					GSTA3, GSTA5, GSTM1, GSTP1, HPRT1, HSP90AA1, HSP90AB1, HSP90B1,
	NFE2L2	Inhibited	-4.341	7.29 × 10 -36	HSPA9, HYOU1, IDE, IDH1, INMT, LMNA, ME1, MGLL, NCKAP1, OAT,
					PAFAH1B1, PDIA3, PDIA4, PDIA6, PFN2, PGD, PPIB, PRDX1, PSAT1,
					PSMA1, PSMA5, PSMA6, PSMB1, PSMB3, PSMB5, PSMD1, PSMD11,
					PSMD12, PSMD3, PSMD7, RACK1, RAN, RARS, RPS16, RYR3, SEC23A,
					SLC16A2, SLC3A1, SLC7A8, SOD1, SOD2, TALDO1, TCN2, TKT, Tpm1,
					TTR, TUB, TXNRD1, UGDH, UGT1A1, VCP

Acknowledgments:

We thank Mori Tachibana and Keiko Tanaka for the technical and administrative assistance.

Conflicts of Interest:

The authors declare no conflict of interest.

Data Availability Statement:

The proteomic dataset is available to the community through the public repository PRIDE using the accession number PXD018948.

equal to or more than 50% of the circumference 3 = positive in whole circumference. In addition, percentages of UQCR7-positive cells in distal tubular cells were calculated by counting more than fifty distal tubular cells per section. Positive rates of Atp5I in tubular cells were evaluated.

Proteomics

Sample preparation and protein digestion, nLC-MS/MS analysis, and database search and results processing were performed as described in [START_REF] Amoedo | Targeting the mitochondrial trifunctional protein restrains tumor growth in oxidative lung carcinomas[END_REF].

Label-Free Quantitative Data Analysis

Raw LC-MS/MS data were imported into the Progenesis LC-MS 4.0 software program (Nonlinear Dynamics Ltd., Newcastle, UK). The data processing included the following steps: (i) feature detection, (ii) feature alignment across the samples, (iii) volume integration for two to six charge-state ions, (iv) normalization to the total protein abundance, (v) import of sequence information, (vi) ANOVA procedure at the peptide level, and filtering for features with values of p-value < 0.05, (vii) calculation of protein abundance (sum of corresponding peptide volume), and (viii) ANOVA testing with Benjamini-Hochberg correction for multiple testing at the protein level and filtering for features with values of Adj. p < 0.05. Of note, only nonconflicting features and unique peptides were considered for calculation at the protein level. Additionally, Progenesis performs an arcsinh correction of data before ANOVA calculation. Quantitative data were considered for proteins quantified by a minimum of two peptides. Protein abundance was normalized to the total protein content determined for each sample using in-gel densitometry methods (SDS-PAGE). MS data were also normalized in Progenesis based on feature median ratio. Furthermore, we selected proteins that showed a statistically significant > 20% change in expression levels (Adj. p-value < 0.05) for differences between two groups (n = 7 in each group). A global analysis of the data was performed using the computer platform Ingenuity Pathway Analysis (IPA; Qiagen). We used the 'core analysis' package to identify relationships, mechanisms, functions, and pathways relevant to the dataset of interest. We also used the 'regulators' package to identify predicted regulators of the proteomic changes.

Supplementary Materials:

The following are available online at https://www.mdpi.com/article/10 .3390/ijms221910294/s1.

Institutional Review Board Statement:

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board of Chiba Hospital (approval number approval number H22-5).

Informed Consent Statement:

Not applicable as the study did not involve humans.


Gabriel Kerbart

Christelle Harnois

Sylvain Marinel

Charles Manière

Modeling the sintering trajectories of MgAl 2 O 4 Spinel

Keywords: Sintering, Sintering trajectory, Grain growth, Transparent Ceramics, MgAl 2 O 4

Controlling microstructure and density of MgAl 2 O 4 spinel is a crucial step in the elaboration of industrial ceramics products. Understanding the sintering characteristics is a key issue to optimize the mechanical and optical properties. In this paper, Olevsky's sintering model is used to simulate the sintering trajectories of spinel. The densification and grain growth behaviors were identified via ramping and interrupted isothermal cycles highlighting the final stage sintering mechanisms change. The sintering trajectory model is intended to be a powerful numerical tool for sintering optimizations.

The transparent spinel ceramic MgAl 2 O 4 is an important material for a wide range of applications, such as jewelry, spacecraft windows, or protective transparent materials for military applications [1]. This interest is motivated by the excellent thermo-mechanical properties of spinel from room to high temperature (>1000°C), as well as its high hardness and fracture toughness, and the low cost of materials [START_REF] Petit | Conf. SPIE Def. + Secur[END_REF]. Furthermore, the spinel isotropic structure makes it very advantageous for the production of transparent ceramics thanks to the absence of birefringence. This material is consequently less sensitive to the optical transmission degradation due to the grain size effect.

Nevertheless, the properties of MgAl 2 O 4 spinel are intrinsically linked to the microstructure of the material [START_REF] Salem | [END_REF][4][5]. Controlling final stage sintering of spinel is therefore a key issue for ensuring optimal mechanical-optical properties. Numerous researches focus on the importance of the presintering powder preparation [6,7] and on the influence of additives for reaching high densities [8][9][10]. The optimization of the sintering cycle is generally done by an experimental dilatometric study. The latter consists of trial and error methods to identify the right temperature and holding time to ensure full densification while retaining a small average grain size [11,12]. Two steps sintering strategies [13] are also investigated to achieve these objectives [14,15]. However, the experimental optimization of the sintering trajectory via the thermal cycle can be a time-consuming process. Indeed, each iteration step requires several hours of cycle, with long holding times, to reach interesting microstructures by free sintering [16][17][18]. The sintering trajectory modeling will therefore be of great interest for allowing an optimization study by computational approaches, after a previous experimental identification of the sintering model parameters. In this work, we will develop a comprehensive model to predict the sintering trajectory (evolution of grain size and densification) of MgAl 2 O 4 spinel. Such a modeling is possible by a careful identification of the intermediate/final stage sintering behaviors and by the coupling of densification/grain growth models [19]. Similar approaches have been used for alumina [20], Zpex smile Tosoh zirconia [18], and also applied to spark plasma sintering with a relevant model [21]. This model will take into account the transition of grain growth mechanism from surface diffusion for high porosity content, to lattice diffusion for low porosity, as previously shown for this material [22]. Furthermore, it will be shown that the final stage grain growth mechanism transition is accompanied by a densification behavior transition. These final stage phenomena will be compared to previous results obtained by a two-stages master sintering curve on the same material [23]. Finally, the sintering trajectory model will be compared to the experimental microstructural data for validation.

The densification/grain growth coupling has a great impact on the final stage sintering of ceramics. The sintering densification affected by grain growth has been formulated in Olevsky's model by the equation below [18]:

𝜃 ̇= -6𝛼(1 -𝜃) 3 𝐺 𝑚+1 𝐺 0 𝑚 𝜂 0 𝑇𝜓𝑒𝑥𝑝( 𝑄 𝑅𝑇 ) (1)
With θ the porosity, 𝜃 ̇ the porosity elimination rate (s -1 ), T the absolute temperature, R the gas constant (J mol -1 K -1 ), G and G 0 respectively the actual grain size and initial grain size (m), α the surface energy (J m -2 ), η 0 the viscosity pre-exponential factor (Pa s), ψ the bulk modulus, Q the sintering activation energy (J mol -1 ) and m the grain size exponent of the sintering behavior (m = 2 for lattice diffusion, and m = 3 for grain boundary diffusion [START_REF] Rahaman | Sintering of Ceramics[END_REF]).

Assuming theoretical functions of ψ and the sintering stress [START_REF] Skorohod | [END_REF]26], the linear regression of Equation ( 1) is used to determine the densification activation energy 𝑄 and the pre-exponential constant ratio 𝜂 0 𝛼 (Eq. 2) [27].

𝑄 𝑅𝑇 + 𝑙𝑛 ( 𝜂 0 𝛼 ) = 𝑙𝑛 (- 6(1 -𝜃) 3 𝐺 𝑚+1 𝐺 0 𝑚 𝑇𝜓𝜃 ̇) (2)
In the sintering region where grain growth is inactive (initial and intermediate stages), the right term of equation ( 2) can be simplified as

𝐺 𝑚+1
𝐺 0 𝑚 ~𝐺0 . However, in this work, the grain growth parameters (see Equation (3) originated from ref [28]) are known as they were determined in our previous study ref [22].

Ġ = 𝐾 0 exp ( -𝑄 𝐺 𝑅𝑇 ) 𝐺 𝑝 ( 𝜃 𝑐 𝜃 + 𝜃 𝑐 ) 𝑛 (3)
θ c and n are fitting constants required to adjust the porosity influence on the grain growth kinetics. K 0 is a pre-exponential factor, Q G the grain growth activation energy and p the grain growth exponent (p=2 for pore control lattice diffusion and p=3 for pore control surface diffusion [START_REF] Rahaman | Sintering of Ceramics[END_REF]).

Therefore, in the present study, the grain growth is considered in equation ( 2) right regression term (later noted Y). The latter is plotted vs 1/RT based on the dilatometry data and the grain growth model data.

Combining equations ( 1) and ( 3), the sintering trajectory can be modeled.

Samples are shaped by cold isostatic pressing (CIP) at 300 MPa of a commercial S30CR Baikowski spinel powder. This powder presents a specific surface area between 25 and 28 m² g -1 (BET surface area), a material purity over 99 % and d50 between 0.15 and 0.3 µm. The determination of the sintering behavior is based on dilatometry experiments (setsys 16/18, SETARAM), up to 1773 K, with three different heating ramps of 1, 2 and 5 K min -1 (Figure 1. a). Final relative density (RD f ) has been measured by Archimedes' method in ethanol and the actual relative density (RD t ) curve has been calculated from the specimen height (h t ) assuming isotropic shrinkage via RD t =RD f h f 3 /h t 3 (see 𝛼 can be identified using equation ( 2) and assuming that densification is governed by the grain boundary diffusion mechanism (m=3). This first identification will be named "step 1". The activation energy from equation ( 2) direct method may be influenced by the 𝜓 and Laplace stress porosity function from Skorohod's sintering theory [START_REF] Skorohod | [END_REF]26]. This direct method is then compared with the master sintering curve (MSC) that has been done in a previous paper [23].

In order to explore the grain growth behaviors in isothermal regime, twelves interrupted experiments at 1673, 1773, 1873 K (Figure 1. d,e,f) were conducted in a previous study [22]. In this work, these data will be employed as final validation of the experimental/modeled sintering trajectories and for adjusting the model parameters. Latter validation step will be referred as "step 2". the interruptions [22]), e) porosity evolution during sintering, f) grain size evolution with dwelling time.

The linear regression curves of the identification "step 1" are reported on Figure 2. Figure 2a points out two phenomena: first of all, a mismatch is observed between the curves corresponding to the different heating rates, especially at low temperature, where the porosity is still important. This mismatch implies dissimilar intercepts, i.e. different pre-exponential viscosities (  Secondly, whatever the heating rates, a change in the activation energy of densification appears systematically at the of grain growth (above 1600 K, see also figure 1c).

This regime transition could be understood by different phenomena such as, a regime change in defects formation at high temperature [29,[START_REF] Ball | Computer Simulation of Disorder in Ceramic Materials[END_REF], the segregation of impurities at grain boundary, grain boundaries complexion [START_REF] Cantwell | [END_REF]32] or a competition between the grain growth/densification diffusional mechanisms. In particular, we observed an exaggerated grain growth at to the specimen surfaces (see figure 2c andd) which seems to point out a high sensitivity to oxygen at high temperatures. In a previous study dedicated to MSC affected by grain growth [23], a similar difference in activation energy for sintering was observed from 400 kJ mol -1 below 1600 K to 700 kJ mol -1 above. In the literature, 750 kJ mol -1 were found for the same spinel powder grade formulated with a binder [33] and shaped by uniaxial pressing and CIP [START_REF] Yamalaç | Sintering, Co-Sintering and Microstructure Control of Oxide Based Materials : Zirconia, Alumina, Spinel, Alumina-Zirconia and Spinel-Alumina[END_REF]; 530 kJ mol -1 was also reported by Tailimian et al [START_REF] Talimian | [END_REF] after milling of the same spinel grade. A similar transition regime was observed in an MSC study of zirconia [36].

Concerning the dissimilar densification behavior(≠𝜂 0 ), one hypothesis to explain this difference may come Skorohod [START_REF] Skorohod | [END_REF]26] theoretical bulk modulus function 𝜓 = 2 3

(1-𝜃) 3 𝜃 . The latter modulus is based on an hypothesis which does not take into account the initial stage, where particle contacts imply a high sintering reactivity and a bulk modulus value close to zero [37]. The initial stage porous skeleton high reactivity can be considered by introducing a critical porosity 𝜃 𝑐𝑑 [38] inspired by Abouaf's moduli 𝜓 = 2 3 (𝜃 𝑐𝑑 -𝜃) 3 𝜃 [START_REF] Abouaf | Modélisation de La Compaction de Poudres Métalliques Frittées[END_REF]40]. This critical porosity represents a porosity close to the green porosity leading the bulk modulus to tend towards zero. By adjusting 𝜃 𝑐𝑑 close to the green porosity, the bulk modulus has been corrected to obtain a unique densification sintering behavior (see figure 2b) accompanied by a flatter overall linearization. A 𝜃 𝑐𝑑 of 0.54 was obtained (a value close to the green porosity of 0.5). To take into account the abrupt change of activation energy during sintering, a sigmoidal step function has been implemented in the model (see Appendix). We exposed on Fig. 3 the validation (stage 2) of grain growth/densification modeling on isothermal tests. Two main comments can be made.

(i)

We can see on Fig. 3.a-b) that the model closely follows the experiments for both grain growth and density at lower temperature (1673 and 1773 K). However, there is a slight deviation at high temperature (1873 K). This deviation is imputable to the multiple changes in sintering energy activation and grain growth mechanisms at high temperatures. The important grain size difference between 1773-1873 K may be explained by the start of exaggerated grain growth as it was observed for spinel [4] and in figure 2c andd. We focus on the improvement of the model on the temperatures 1673 and 1773 K which are very important for the sintering optimization. (ii)

Concerning the sintering trajectory at 1673 K( Fig. 3.c), the experimental points and the model exhibit higher grain sizes than the main trend of the other trajectory curves. This indicates that a holding at low temperature favors the coarsening rather than densification. The pore surface diffusion seems high for this material against grain boundary diffusion. Consequently, low temperature holding should be avoided to reduce this coarsening zone. We have established a simple method in two steps for the identification of the sintering densification parameters of ceramics. This model (applied to MgAl 2 O 4 spinel) reveals a regime transition of the densification parameters at the onset of grain growth. Furthermore, a dissimilar densification behavior has been highlighted especially before the onset of grain growth. However, we have shown that this apparent dissimilarity is caused by the bulk modulus function that should include the high sintering reactivity of the initial stage. Finally, the low temperature trajectories seem to indicate a highly active pore coarsening phenomenon. The latter may limit the densification if uncontrolled.

Hence, sintering at this temperature (1673 K) should be avoided favoring thermal cycles like the two steps sintering where a rapid heating is employed to close the porosity with a minimum of coarsening. To conclude, we have determined the sintering parameters of MgAl 2 O 4 spinel for both densification and grain growth, and we developed a predictive model for the sintering trajectory. This powerful numerical tool can be used to conduct sintering cycle optimizations for obtaining fine grained ceramics.

Figure 1 .

 1 Figure 1. b). The corresponding dilatometry grain size evolution was determined from equation (3) (see Figure 1. c) and previously determined parameters (see appendix). With these data, the sintering parameters 𝑄and 𝜂 0

Figure 1 a

 1 Figure 1 a) Heating ramp for dilatometry experiments, b) density during dilatometry experiments, c) grain size during dilatometry experiments, d) heating cycles used to determine the grain growth model (the red spots arethe interruptions[22]), e) porosity evolution during sintering, f) grain size evolution with dwelling time.

Figure 2 a

 2 Figure 2 a) Determination of the sintering parameters without considering critical porosity, b) determination of the sintering parameters considering critical porosity, with below the corresponding sigmoidal functions used for the regime transition (c,d) center/edge microstructures at 1600°C showing the sensitivity of the microstructure close to the surface (air) at high temperatures.

Figure 3 a

 3 Figure 3 a) Grain growth modelisation results, b) sintering modelisation results, c) sintering trajectory modelisation results.

Figure 1 a

 1 Figures captions

Acknowledgements

The authors thank Jérôme Lecourt and Christelle Bilot for their help in the progress of this study. We would like to thank the French ministery of research for PhD subvention of Gabriel Kerbart.

Appendix

The simulation of grain growth requires Olevsky's porosity function of the following form:

The values used in this model for 𝜃 𝑐 and n are 0.001 and 0.25 respectively. Furthermore, the grain growth exponent was found to vary with the sintering temperature, as follows [22]:

The value used for the activation energy Q G and K 0 are 1515kJ mol -1 and 6.014.10 18 m s -1 respectively.

In order to take into account the low temperature (LT)/ high temperature (HT) jump in activation energy and pre-exponential factor, a sigmoidal function has been added in the code via the following form:

Considering this function, the activation energy is expressed by:

With Q HT =750 kJ mol -1 and Q LT =437 kJ mol -1 . Similarly, the pre-exponential term is expressed by:


Florent Sevely
email: fsevely@laas.fr

Lionel Seguier

Tao Wu

Fabien Mesnilgrente

Sylvain Pelloquin

Carole Rossi
email: rossi@laas.fr

Development of a Chip-Level Ultimate Security Device Using Reactive Composites

Keywords: anti-tamper, anti-revere engineering, antihacking, energetic materials, nanothermite, PyroMEMS, circuit breaker, Al/CuO

We developed an Ultimate Security Device (USD) that can, in case of intrusion or external attack, blow up a safetycritical component such as memory device. The device consists of two active parts (1) a pyroMEMS ignites in a fraction of millisecond (2) a mass of reactive composite, both encapsulated into a printed hermetic cap and placed over the sensitive component to be protected. After the presentation of the design and integration of the USD, we demonstrated that 400 mg of reactive composite permits to irreversibly destroy the silicon chips (~118 mm 3 ) in less than 10 ms. This ultimate security device provides a speedy and automatic response and can be programmed for tunable actions (generation of pressure burst, heat, chemical species) to implement relevant emergency safety responses.

I. INTRODUCTION

Infrastructures are moving towards more heterogeneous, intelligent, connected, user-centric and collaborative electronic systems. This evolution has also brought rapid growth of criminal activity that threatens citizens, businesses, and governments. Typically, software attack and hardware intrusion such as reverse engineering which intends to clone, pirate, or counterfeit a design, to develop an attack pose a great threat to national security and must be actively addressed. Anti-tamper technologies are as old as the economy but requires constant adaptation to new extremely complex topologies and to reverse engineering technique being constantly evolving [START_REF] Mcloughlin | Secure Embedded Systems: The Threat of Reverse Engineering[END_REF]- [START_REF] Atallah | A Survey of Anti-Tamper Technologies[END_REF]. The simplest anti-tamper and anti-reverse engineering solutions are based on cryptographic keys or software [START_REF] Ozsoyoglu | Anti-Tamper Databases[END_REF], security fuses [START_REF] Rossi | Nano-Engineering of Al/CuO Multilayers: Bridging the Gap Between Research and Applications[END_REF] to prevent non-authorized access, reinforcement of the components' coating and encapsulation [START_REF] Li | Design of anti-key leakage camouflage gate circuit for reverse engineering based on dummy vias[END_REF]- [START_REF] Guo | Investigation of obfuscation-based anti-reverse engineering for printed circuit boards[END_REF] to avoid housing opening. More sophisticated solutions may include anti-tamper sensors able to detect the type of tampering such as Hall-effect switches [START_REF] Patnaik | Advancing hardware security using polymorphic and stochastic spin-hall effect devices[END_REF]. And, often, especially for safetycritical components in order to ensure an efficient protection, several different anti-tamper protections are integrated [START_REF] Atallah | A Survey of Anti-Tamper Technologies[END_REF], [START_REF] Koemmerling | Design Principles for Tamper-Resistant Smartcard Processors[END_REF]. All these anti-tamper technologies, while being effective and in constant evolution, can be cracked or bypassed. That is why, to prevent the reverse engineering or tampering of a safety-critical system, upon the detection of intrusion, an ultimate action must be quickly taken before. Possible response includes the shut down or disable the device [START_REF] Nicollet | Fast circuit breaker based on integration of Al/CuO nanothermites[END_REF], [START_REF] Pennarun | Design, fabrication and characterization of a MEMS safe pyrotechnical igniter integrating arming, disarming and sterilization functions[END_REF], erase critical parts of memory and physically destroy the device [START_REF] Fleck | Controlled Substrate Destruction Using Nanothermite[END_REF]- [START_REF] Brailovski | Temporal characteristics of shape memory linear actuators and their application to circuit breakers[END_REF]. In this work, we exploit the high-pressurization capability of Al/CuO nanothermites based composites [START_REF] Song | A comparative study of thermal kinetics and combustion performance of Al/CuO, Al/Fe2O3 and Al/MnO2 nanothermites[END_REF]- [START_REF] Wu | Unexpected Enhanced Reactivity of Aluminized Nanothermites by Accelerated Aging[END_REF] to design and fabricate a miniature ultimate security device ideally suited to protect sensitive data or hardware against reverse engineering or hacking. A threat is detected, the so called, ultimate security device (USD) remains in sleeping-mode until the threat occurs or simply a risk is imminent. It is then triggered in less than 100 µs by an electrical command and destroy irreversibly the sensible component against hacking, attempt or misuse. A nanothermite based reactive composite was chosen as they are the only attractive sources of reliable and "dormant" energy, exhibiting long shelf life (decades) and able to very quickly deliver gas, heat through a selfsustained redox reaction. For context, the decomposition of thermites can produce ~4 MJ/kg, which approaches the combustion of hydrocarbon materials (~50 MJ/kg), whereas a modern chemical lithium-ion battery stores only 0.5 MJ/kg.

After the presentation of the USD concept and design, the fabrication of the miniature (0.4 cm 3 ) USD device is presented in detail. The testing achieved on several mounted USD on SD memories cards demonstrates 100 % success of data destruction when 400 mg of reactive composite are integrated into the USD. Results also show that the reaction time and efficiency highly depend on the reactive material loading, e.g. the mass of nanothermites deposited onto the pyroMEMS [START_REF] Pouchairet | PyroMEMS as Future Technological Building Blocks for Advanced Microenergetic Systems[END_REF]- [START_REF] Salvagnac | Layered Al/CuO Thin Films for Tunable Ignition and Actuations[END_REF]. The USD presented in this paper offers important advantages for safety-critical components such as the use of harmless material or substance for human and the tunability of the response which depends on the mass and nature of reactive composite integrated into the device.

II. USD OPERATION PRINCIPLE AND DESIGN

Fig. 1 represents a schematic diagram of the proposed USD and the operational principle for destroying a memory containing sensitive and critical informations. As shown in Fig. 1(a), the USD is made of two stacked main active parts:

• one microscale electric initiators, pyroMEMS. It consists of a thin thermite layer deposited on a thinfilm resistive layer. When a current is applied to the resistance, the nanothermite is ignited by the Joule effect and reacts to produce a spark.

• one mass of reactive composite made of a mixture of Al/CuO nanothermite with copper complex (Cu(NH3)4(NO3)2, labelled CuC) which is deposited in a 3D printed reservoir.

Fig. 1(b) shows the operational principle of the device. The USD is placed onto a memory card to be protected (Fig. 1b (2)) and remains in sleeping mode for years until a threat is detected. When a threat is confirmed (Fig. 1b (3)), the pyroMEMS is ignited in less than 100 µs and further ignite the reactive composite (Fig. 1b (4)). The combustion of the reactive composite generates a heat and pressure burst that mechanically destroy the silicon memory chip (Fig. 1b (5)).

Figure 1. Conceptual illustration of the USD operation principle. (a) Exploded view of the device, composed of a 2 stacked parts (a pyroMEMS and reactive composite printed in a reservoir). (b)

Operating mechanism for utilizing the USD as a protecting device against the …. Of data contained in a memory.

III. FABRICATION AND ASSEMBLY

PyroMEMS fabrication

A 500-µm thick 4-inch glass substrate is cleaned with oxygen plasma at 800 W for 5 min to remove surface contaminations.

Next negative nLof photoresist (AZ nLof 2035, MicroChem Corporation, USA) is then spin coated and patterned using photolithography. Subsequently, 350-nm thick titanium and 300-nm thick gold layers are evaporated onto the surface and then patterned to define the Ti electrical resistor and Au electrical pads. Finally 13.9 mm² Al/CuO multilayer films are sputter deposited as described in [START_REF] Rossi | Nano-Engineering of Al/CuO Multilayers: Bridging the Gap Between Research and Applications[END_REF], [START_REF] Zapata | Self-propagating combustion of sputter-deposited Al/CuO nanolaminates[END_REF]- [START_REF] Nicollet | Investigation of Al/CuO multilayered thermite ignition[END_REF] on the microinitiator directly in contact with the Ti electrical resistance (Fig. 2a).

Reactive composite formulation and printing

4.83 g (0.02 mol) of copper nitrate trihydrate is dissolved in 10 mL of distilled water followed by addition of 15 mL of 25% aqueous ammonia solution (0.24 mol). The final product (powder) [START_REF] Wu | New coordination complexes-based gas-generating energetic composites[END_REF] is separated via vacuum filtration and dried in an oven (Carbolite Gero, England) at 70 °C. The assynthesized CuC powders are milled using a Retsch CryoMill machine using alumina grinding balls (diameter: 25 mm).

Milling parameters are: frequency of 30 Hz (30/s) for 10 min while equipped with liquid N2 cooling. In parallel, 91 mg of aluminum nanopowders (Al, average particle size: 80 nm, purity: 69 % purchased from Novacentrix, USA) and 203 mg of copper oxide (CuO, average particle size: 100 nm purchased from Merck, Germany) are mixed with 86 mg of milled CuC powder and dispersed in 20 mg of polymer polyvinylpyrrolidone (PVP) and ethanol (4 ml) and then stirred 45 minutes in a sonication bath cooled by ice. It has to be noted that the equivalence ratio for the CuC over Al/CuO nanopowder is 25%. PVP enables a good dispersion and stabilization of the nanoparticles [START_REF] Sevely | Effect of Process Parameters on the Properties of Direct Written Gas-Generating Reactive Layers[END_REF] (Fig. 2b). The reactive composite is then deposited into the USD reservoir using a volumetrically controlled dispenser: the precision of the deposition is 6 µL, e.g. 1.14 mg.

Reservoir and external packaging fabrication

The USD packaging is made in two parts:

• The external packaging which is a rectangular cap in dimensions adapted to fit on the component to be protected. At its bottom, a trench is designed to host and electrically connect the pyroMEMS.

• The second part is a rectangular reservoir with two functions: block the pyroMEMS in its trench and store the reactive composite.

On the side of both parts, holes let the pyroMEMS electrical contact to go through the packaging and to the printed circuit board (PCB) described in next section. Both parts were printed in Nylon (Z-NYLON, Zortrax, Poland) using a 3D printer (Zortrax M300plus). Photos are given in Fig. 2c. 3D printing technology were chosen because it offers a good resolution (±0.09 mm) while being low cost and fast for prototyping. Nylon offers a good compromise between cost and thermal and mechanical resistance.

Printed circuit board (PCB)

The circuitry (Fig. 2e) is a basic capacitive discharge circuit that is able to initiate the pyroMEMS in less than 100 µs.

Assembly

For the demonstrations, we chose a commercial Transcend SDHC memory Card 8GB, so called SD card (Transcend, Taiwan) It offers the advantage to be easily readable and programmable with a computer. Its packaging made in Epoxy resist reinforced with silica, making the packaging is resistant to heat and pressure. Therefore, we first open a 4 × 10 mm² squared window into the packaging to access to the Si memory, taking care to not destroy the internal wires bonding and electrical connexions, nor the passive components and the silicon chip that constitutes the memory. This step is done by chemical etching using nitric acid, HNO3. The prepared SD card is then checked, programmed and mounted and connected on the printed circuit board shown in Fig. 2e. In a second step, the electronic components are welded on the PCB. At last, the USD is assembled with the PyroMEMS, filled with the reactive material then sealed with cellophane.

After its preparation, the USD is mounted on the SD, soldered and attach to the printed PCB.

A photo of the USD mounted on the SD is shown in Fig. 2f.

IV. CHARACTERIZATION

Several demonstrators was prepared and tested with 5 different masses of reactive composite, corresponding to different compaction rates expressed in % TMD (1) : 100 mg (TMD% = 11%), 200 mg (TMD% 21.26%); 300 mg (%TMD = 32%); 400 mg (%TMD = 43%); 600 mg (%TMD = 64%).

After the ignition and reaction of the reactive material, the demonstrators were opened and SD cards observed visually and using a Microscope Hirox RX-100 with a ×20 and ×140 magnification (Fig. 6 iii). All pictures were taken using a multi-focus technique allowing us to see rifts / trenches in a full reconstituted picture without any blur. Results are summarized in Fig. 6 for configurations 200 mg, 300 mg, 400mg and 600 mg. Results are given in the form of photos of the SD cards after the tests: (i) a non-magnified, (ii) magnification ×20, (iii) and (iv) ×140 magnification. photo 100 mg configuration was not given as the SD card remains intact after the test. %TMD = mass of reactive composite TMD × volume of the reservoir ×100

Where TMD is the theoretical density of the reactive composite, calculated equal to 3.51 g/cm 3 and the volume of the reservoir is 268 mm 3 .

Figure 3. Photos of the SD cards after the tests.

It was observed that with 600 mg, the SD card became fully destroyed: a part of the packaging was torn out and most of the silicon chip was pulverised. When not pulverised, the silicon features rifts and holes (Fig. 3d (iii) and (iv)). This result therefore confirmed the feasibility of our concept as we destroyed the silicon component with all the data in it. With 400 mg, some parts of the silicon chip were pulverized and rifts run across the chip. Although the damages are less intense than using 600 mg of reactive composite, the SD was enough damaged and the data totally destroyed. With 300 mg we observe some cracks into the silicon chip and some shard have been torn off (Fig. 3b (iii) and (iv)). The silicon surface is covered by superficial scratch but the SD card remain unbroken and data can be read. The test has failed. With 300 mg, the SD remain totally intact and therefore tests have failed. These tests not only validated the allowed us to determine the minimum amount of energetic material needed to destroy a silicon chip and to make it unreadable. With only 400 mg of reactive material we archived our goal.

V. CONCLUSION

The concept of a chip-level ultimate security device based on nanothermite composite has been demonstrated: we successfully destroy in ~5 ms a memory card and its containing data. The fabricated made to measure device is 29 mm wide & 34 mm long and simply mounted onto the safetycritical component. 400 mg of reactive composite permits to destroy physically all the silicon chip, but the energetic response can be adapted by tuning the mass of reactive powder depending on the level of destruction desired and the type of component to neutralize.

VI. ACKOWLEDGEMENTS

  It is composed of 3 transistor MOS (MOSFET, Canal-N, 20 A 60 V TO-220AB, 3 pins, ON Semiconductor, Malaysia & MOSFET, Canal-P, 14 A 100 V TO-220AB, 3 pins, Infineon, Germany) and a10 µF chemical capacitor (Capacitor RS PRO, 10μF, 63V c.c., Taiwan). This circuit is powered by a lab. power supply (Agilent U8031A, Agilent technologies, Malaysia) and driven by an Arduino prototyping board.

Figure 2 .

 2 Figure 2. Photo of (a) the pyroMEMS, (b) the reactive composite reserved in a vial, (c) the packaging and reservoir fabricated in Nylon by 3D printing, (d) the prepared SD card memory, (e) Printed circuit board with the electrical schema, (f) On-Chip Ultimate Security Device fully assembled on a memory card for demonstration.

The authors acknowledge support from the European Research Council (H2020 Excellent Science) Researcher Award (grant 832889 -PyroSafe). This work was also supported by LAAS-CNRS technology platform, a member of Renatech network. We acknowledge the French Defense Agency DGA which partially funds F.S. scholarship.


Ludovic Saint-Bauzel

Ozer Unluhisarcikli

Constantinos Mavroidis

Phase-dependent knee

come

INTRODUCTION

Rehabilitation robotics that has seen great growth during the last years can be classified into end-effector devices and wearable exoskeleton devices. The end effector design approach is both applied on upper limb (e.g. MIT Manus [START_REF] Hogan | Robot and Human Communication[END_REF],Handle Device [START_REF] Khanicheh | Rehabilitation Robotics[END_REF])) and on lower limb rehabilitation (Haptic Walker [START_REF] Schmidt | [END_REF]). Similarly, exoskeleton devices could be used on upper limb (Able [START_REF] Garrec | Intelligent Robots and Systems[END_REF], 2RobotArm [START_REF] Culmer | Rehabilitation Robotics[END_REF]) and lower limb (Lokomat [START_REF] Bernhardt | Rehabilitation Robotics[END_REF],PAM-POGO [START_REF] Aoyagi | [END_REF], KneeDevice [START_REF] Weinberg | IEEE International Conference[END_REF]). In both types of rehabilitation devices the controllers are similar. However due to the additional safety concerns when wearing a an exoskeleton, its controller should guarantee safe operation of the device.. In general, the main control aims of a rehabilitation robotic devices are that the controller should be able to a) implement accurately the prescribed rehabilitation treatment protocol and b) eliminate unwanted (e.g. hazardous) effects on the subject. In order for the controller to be able to achieve these aims, it should be able to take into account the changing dynamics of the human body and its environment using a dynamic model. One way to develop a dynamic model of the human body interacting with its environment for use in the control of a rehabilitation device, is to use a global model that takes into account the whole body. However, This global modeling leads to a very large number of parameters to be identified using experimental data and a complex identification process [4,5 or 6] It is also computationally very expensive that makes its real time implementation on the device almost impossible. [14], [15] and [16]. But this bio-mechanical models that aim to understand and present a realistic model of the joint. In our case we want to represent properties during defined motion. As describe below the walking lead to non-linearities when the foot impact the ground, many unwanted motion are appearing because of the robot attachment. So the issue is that one don't know if the knee properties while walking motion can be presented as a linear parameter variable system. So this paper will evaluate if it is accurate to represent the knee mechanical properties as a LPV system and present a ensemble data method to identify the parameters. It will be applied on knee motion equipped of ANDROS Device that present the property to be a one DOF exoskeleton and is therefor a good experimental tool to apply the method.

System Overview -ANDROS V1

ANdROS V1 is designed as a wearable and portable assistive tool for gait rehabilitation and monitoring. The exoskeleton frame consists of two braces: an actuated brace attached to the impaired leg via rigid straps, and a sensorized brace attached to the healthy leg via elastic straps (Figures 1 &2). The power and torque specifications of ANdROS were determined based on the reference trajectories obtained from tests conducted on 70 adult healthy subjects at Spaulding Rehabilitation Hospital in Boston, MA. The specifications obtained from these tests are summarized in Table 1.

The actuated brace is driven by a brushless DC motor (MCG IB23000-E1) coupled to a gearbox (Anaheim Automation GBPH-0602-NP-040, 40:1 gear ratio) which is located next to the pelvis, to reduce the moving mass and keep the center of mass (CM) of the exoskeleton close to the wearer's CM. The motor has been selected to provide at least 50% assistance. The peak torque at the gearbox output is 22.88 Nm and rated power is 179 W. The torque generated by the motor is transferred to the knee joint by means of a push bar that features a quick disengagement mechanism. By disengaging the lower part of the exoskeleton from the power train, easy adjustment during donning/doffing is possible. The push bar mechanism of ANdROS is basically a four bar linkage. Kinematic analysis has been carried out to convert the torque at the motor shaft to the torque at the knee, but has been excluded herein due to space limitations.

A load cell at the end of the push bar measures the interaction forces. The load cell is located proximal to the knee joint to maximize the amount of mass between the motor and itself, whose apparent inertia is reduced by force-feedback. An incremental encoder and a rotary potentiometer are placed on either side of the knee joint, where the potentiometer is used to initialize the incremental encoder's position. The rotary encoder provides high accuracy (0.088°) and noise free measurement of the knee angle, which are critical properties in calculating digital derivative for velocity estimation. An exoskeleton should be attached to the body so that there is minimal play (migration) with respect to the human tissue, yet still be comfortable to wear. The actuated brace of ANdROS is attached to the user's body at four locations (i.e. hip, thigh, shank, and ankle) to prevent the migration effect. The weight of the exoskeleton and the user is transferred to the ground through an AFO. The 3 symmetrical structure of the actuated brace applies torque to the knee from both medial and lateral sides of the leg, thus eliminating the twisting effect which would occur in a single-sided design.

The brace worn on the unimpaired leg measures the knee and hip flexion/extension angles via high precision potentiometers.

Models

Phases of Gait Cycle

Figure 3 shows the four phases in a gait cycle. The stance is supposed to begin when the foot is close to leave the ground. During Phase-1 (from 0 to 20% of the gait cycle) one can see that the right foot is in the air. Then Phase-2 is a high torque phase corresponding to the ground hitting pick (between 20 to 40% of the gait cycle). Then a second opposite pick is observed corresponding to the main knee action to move the other leg in Phase-3 (40-60% of the gait cycle). The last phase, Phase-4, is more or less a constant part of the walking motion for the knee. It is when the leg is straight and turns around the ankle while the other foot is in the air and goes to the front of the subject.

Mechanical Models of the Knee

The biomechanical model of the knee shown in Figure 4 leads to Equation (1).

(1) where , and are respectively the torque coming from the leg muscle, the robot actuator and the gravity on the leg, is the inertia of the Representation of the Leg system. But one hypothesis is that the actuators are not perfect so they have some impedance (where represents spring parameter and stands for damper actions) in the motion. U is the initial torque. Consequently and will be written a impedance torques :

(2)

(3) So the previous equation becomes : [START_REF] Garrec | Intelligent Robots and Systems[END_REF] where is the global orientation of the shin, is the angle between the shin and the thigh. And is decompose of inertia property of the shin and inertia of the robot . One can notice that these equation are representing the dynamics of the leg without external forces coming from the ground during the walking motion. As a reminder, time varying parameters are identified in this equation. In this paper one would like to represent this ground action as a part of time varying impedance. So as a time varying impedance, it has been added to the previous equation and is called . The idea of this work is to represent walking motion as a time varying impedance. So it seems that we may have to represent as a function of time and . The problem is that a big part of walking motion is done with close to a blocked position (during the swing of the other Leg). And the action of the robot could be useful during this motion. So the proposed solution is to include Hip angle ( ) in the time varying model of the walking motion. So the time varying of dynamics of walking can be presented as follow :

(5)

where will be considered as a time varying wanted torque. Having an identification of the human joint mechanical parameters is not the aim of this paper. The aim is to have a model of the leg connected to the robot. Consequently knowing the and parameters for themself is not relevant. In this paper, it will be added in (6) as follow : [START_REF] Bernhardt | Rehabilitation Robotics[END_REF] Consequently, the parameters that are dependent to and its differentiates can be aggregated and will be called :

(7), (8)

Phase-dependent representation

In this paper, the idea is to take advantage of periodicity of walking motion. So an hypothesis of this work is that there is some periodicity in the properties of the leg between each stance. Thanks to this property, the time varying parameters will be considered as phase-dependent parameter. So one can introduce a new parameter that represents the phase of the motion. This parameter is only a position of the phase. It is a real scalar value between 0 and 1 that represents a percent of the phase. The difficulty is that this numerical representations are not representing the proximity between a parameter close to 0 and a parameter close to 1. In order to obtain a realistic relation, it has been decided to use a lookup table that represent a piece of data centered on the percent presented by and a time window of . As for example, is computed with every data at time where are every moment that are in position of the stance motion, is the duration of the stance and W is a percent of this duration. Consequently, and continuity is kept. Another property of this notation is one can represent a fixed in time parameter as robot parameters for example: , , From equation ( 1) with impedance parameters (k for spring action, b for damper action parameter), Inertia matrices decomposed by their origin , the system can therefore be rewritten as follow : [START_REF] Jarrasse | Robotics and Automation[END_REF] where all the dependent parameters, k and b robot parameters and are unknown and are the parameters that are aimed to be identified in this paper.

The idea behind this variable model is to take a small set of data around the working point and to find the best model parameters by converging to the local minimum. The data selection is phase dependent and is collected as explained before for the parameters and as presented in Figure 5. This approach is also a way to reduce inter-trial variations, and as far as time evolutions is not modified it is respecting dynamics properties of the motion.

Results & Discussion

Experimental setup

The comparison is done between a model with constant parameters and the model with phase varying parameters is called

Results

If one compares the proposed models as they estimate the knee torque applied by the human when walking with AKROD, we can observe that the phase varying parameter model is closer to the constant parameter model. As presented in Fig. 6, the black line that represent the phase model torque evaluation seems closer to grey line than green dashed line, the most relevant parts are around sample 200. and around the sample 100. A better way to evaluate the accuracy of the phase varying model is to look at the measured quadratic error along the stance as it is done in Fig. 7. According to this graphic, the phase varying model is always under the constant model, It means that the errors between model predicted torque and measured torque.

Discussion

This study shows a phase-dependent model that fits to a human leg with good accuracy. The methodology based on random noise is an interesting approach in obtaining a dynamic model. However, as explained in the introduction, one of the goals of this work is to create a model of the patient. Obviously, introducing random noise to the patient while he/she is in motion can be a problem. Therefore, one limitation of this method is the patient being subjected to perturbations as he/she walks during the identification process. This method is also interesting in showing the different fields of accuracy of the proposed model. Since this is a phase dependent algorithm, it is possible to propose more accurate models in some parts of the motion. It should be noted that this study is conducted on a single subject. This is a proof of concept that must be confirmed with statistical analysis on multiple subjects. However, this larger study will have to pay attention to the subjectdependency of this method.

2

 2

Figure 1 :

 1 Figure 1 : ANdROS V1: The new Active Knee Rehabilitation Orthotic System.

Figure 2 :

 2 Figure 2: Close-Up View of ANdROS V1 and its Components.

Figure 3 :

 3 Figure 3: One Stance Cycle Schematic Representation.

Figure 4 :

 4 Figure 4: Mechanical Impedance Representation of the Leg

Figure 5

 5 Figure 5 : with and

  Figure 7: Comparison Phase dependent model ) vs global model ( ) error along motion

Figure 6 :

 6 Figure 6: Model(-,1) (green and dashed line), Model (Black line), and Measured data(grey line) of Knee Torque during one stance.



  This work was supported in part by the U.S. National Science Foundation under Grant CBET-0828772. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.

	PHASE-DEPENDENT KNEE MODEL IDENTIFICATION IN GAIT MOTION USING AN
	ACTIVE KNEE REHABILITATION ORTHOTIC DEVICE
	Ludovic Saint-Bauzel , Ozer Unluhisarcikli Student Member, IEEE, and Constantinos Mavroidis,
	Member, IEEE
	:
	(+33)144-276-210; fax: (+33)144-275-145; e-mail: saintbauzel@isir.upmc.fr).
	O. Unluhisarcikli and C. Mavroidis are with the Department of Mechanical and Industrial
	Engineering, Northeastern University, Boston MA 02115 USA (phone: 617-373-4121; fax: 617-373-
	2921; e-mail: mavro@coe.neu.edu).
	Corresponding authors: L. Saint-Bauzel and C. Mavroidis
	1

L. Saint-Bauzel is with the Université Pierre et Marie Curie-UPMC "Institut des Systèmes Intelligents etde Robotique" ISIR, Paris, F-75014 France (corresponding author to provide phone

TABLE 1

 1

		: TECHNICAL SPECIFICATIONS
		10% of Gait Cycle	90% of Gait Cycle
	Torque a (Nm)	54 (peak)	27
	Velocity (rad/sec)	2	7 (peak)
	Power (W)	108	189
	a The torque values are calculated for a 135 kg individual