dataesr/scientific-paragraphs-categorization huggingface dataset:
Funding: This study was supported by research grants for  Dr. Dalel Askri  from the  Tunisian Ministry of Higher Education and Scientific Research , the  Auvergne Rhone-Alpes Region  (grant  N° 16. 007278. 01 )and the  French Embassy in Tunisia-Campus France. The project leading to this publication has also received funding for  Dr. Sylvia G. Lehmann  from  Excellence Initiative of Aix-Marseille University -A*MIDEX, a  French "Investissements d'Avenir" program , through its associated  Labex   SERENADE  project.
1 ms pulse, 300 µA, Suppl. Fig. 7 ). In A1, electrode location was set using sound-evoked field potential in response white noise (Suppl. Fig. 7 ). The reference electrode was positioned in the skull bone above the contralateral cortical hemisphere at 5 mm posterior to the bregma. All electrodes were connected to a miniature socket (PlasticOne, USA) fixed onto the rat's skull by dental cement after the application of a surface activator (Super-Bond C&B, Sun Medical). Two weeks of recovery separated surgery from recordings. After experiments were complete, rats were given an overdose of Pentobarbital. Brains were extracted for histological examination (Suppl. Fig. 7 ). Behavior. Experiments were performed in 50 × 25 × 30 cm size arena (Habitest, Coulbourn, USA) controlled by a computer (GraphicState software, Coulbourn USA).
Rats were connected to the recording device by a tether plugged into the implant connector in one end and a swiveling electrical connector that allowed free movements on the other end. Monopolar activity was acquired using a custom DasyLab (IOTECH, U. S. A) script driving an XCellAmp 64 amplifier (Dipsi, France) coupled with a DaqBoard 3000 USB system (IOTECH, U. S. A). The LFP signals and event markers (nose pokes) were amplified (X 2500), filtered (0. 1-1000 Hz), digitized (sampling frequency, 2000 Hz) and stored on a computer. ′ =                  + -- - ≤. ≤ + -- ≤ <. + -- - -. < ≤ A H F F H F H H F F H F H H F H F F H 3 4 4 (.
Acknowledgements This work received funding from the  IFR 144 NeuroSud-Paris  to C. M. and B. G. ; from the  Agence Nationale de la Recherche  ( ANR-15-CE37-0007 ) to B. G. and from the  French Ministry of Research (MNSER)  to A. G. We thank  Florian Occelli  and  Cédric Esnault  for technical help,  Aurélie Bonilla  for animal care and  Daisy Vargas  for carefully reading the manuscript.
The objective of the present paper was to verify this hypothesis. The kinetics of peptide release was followed during gastro-intestinal digestion of a pool of raw or pasteurized preterm human milk at the preterm newborn stage. Digestion was simulated using an in vitro dynamic model, where digestive enzymes, pH and digestive compartment emptying were continuously controlled. Nature and abundance of peptides were determined by mass spectrometry and data analyzed by multivariate statistics.
01% (v/v) TFA in HPLC gradient grade water] and B [95% (v/v) acetonitrile, 0. 08% (v/v) formic acid and 0. 01% (v/v) TFA in HPLC gradient grade water]. The elution gradient first rose from 5 to 35% solvent B over 87 min, then up to 85% solvent B over 3 min before column reequilibration. The mass spectra were recorded in positive mode using the m/z range 250-2000. The resolution of the mass analyzer for m/z of 200 amu (atomic mass unit) was set in the acquisition method to 70 000 for MS and 17 500 for MS/MS. For each MS scan, the ten most intense ions were selected for MS/MS fragmentation and excluded from fragmentation for 15 s. Peptides were identified from the MS/MS spectra using the X!TandemPipeline software  (Langella, Valot, Balliau, Blein-Nicolas, Bonhomme, & Zivy, 2017)  against a human milk protein database  (Molinari, Casadio, Hartmann, Livk, Bringans, Arthur, et al.
Quantification of peptides Each identified peptide was quantified by label-free MS using the MassChroQ software  (Valot, Langella, Nano, & Zivy, 2011). A m/z width of 10 ppm was used to perform extracted ion chromatograms (XIC) of peptides in time-aligned chromatograms and the area under the curve was then quantified. When a peptide was measured with several charge states, all ion intensities were summed.
Biochemical characteristics of the peptides Several biochemical characteristics were determined for each peptide, particularly the amino acids at cleavage sites in positions P1 (C-ter end) and P1' (N-ter end), the number of essential amino acids (histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, valine), the isoelectric point, the molecular weight and the Grand Average of Hydropathy Value (GRAVY) as defined by the ExPASy "ProtParam tool"  (Gasteiger, Hoogland, Gattiker, Duvaud, Wilkins, Appel, et al. , 2005). A positive GRAVY corresponds to a hydrophobic peptide and a negative one to a hydrophilic peptide  (Kyte & Doolittle, 1982). Bioactive peptides were searched within the databases of BIOPEP  (Minkiewicz, Dziuba, Iwaniak, Dziuba, & Darewicz, 2008)  and MBPDB  (Nielsen, Beverly, Qu, & Dallas, 2017)  both accessed on January 2018.
Enzymes predicted to be active in milk before gastrointestinal digestion The peptide sequences as identified in milk before digestion were submitted to the online software Enzyme Predictor (http://bioware. ucd. ie), which examined the cleavage patterns and predicted the enzymes responsible for this profile based on the cleavage specificities of 35 enzymes  (Vijayakumar, Guerrero, Davey, Lebrilla, Shields, & Khaldi, 2012). Enzymes were then ranked according to their likelihood of having being used to generate the hydrolysate thanks to the calculation of an odds ratio (OR). The same human enzymes as those previously considered  (Deglaire, et al. , 2016)  were included. Enzymes presenting only one potential cleavage were not considered. Cleavage sites of cytosol aminopeptidase and carboxypeptidase B2 were examined manually over β-casein, such as performed previously  (Dallas, Smink, Robinson, Tian, Guerrero, Parker, et al.
Clusters 6 and 8 (36% of the peptides) included peptides mainly produced during the gastric phase and showed a lower abundance for PHM than for RHM (Figure  2C ). In cluster 6, leucine (cleavage specificity for pepsin) in position P1 was significantly more represented unlike lysine and arginine (cleavage specificity for plasmin/trypsin) significantly less represented than in the overall dataset; peptides had in average a higher molecular weight than in overall (Table  2 ). Cluster 8 was significantly associated to bile salt-stimulated lipase. Clusters 1 to 3 (20% of the peptides) included peptides mostly produced in the intestinal phase, where the abundance was lower for PHM than for RHM at some digestion time (Figure  2C ). In cluster 1, the proportion of α s1 -casein peptides and of arginine in position P1 was greater than in overall (Table  2 ).
Bioactive peptides The exact matching sequence search over the 1531 peptides resulted in 36 peptides having a predicted antimicrobial activity; they were originating mostly from bile-salt stimulated lipase (39% of them) and lactoferrin (19%) (data not shown). Eight peptides were found to have a proved bioactivity according to the literature, such as indexed by BIOPEP and MBPDB databases. They were all from β-casein, except for one peptide from lactoferrin (Table  3 ). The antimicrobial peptide β-casein(185-211) had an abundance six times lower (P < 0. 05) for PHM prior to digestion but its abundance was then similar (P > 0. 05) between RHM and PHM during the first hour of gastric digestion before being null for both types of milk. Two angiotensin-converting enzyme inhibitor peptides  [β-casein(154-160)  and β-casein(161-166)] were present only in the intestinal phase and had abundances significantly higher (P < 0.
05) for PHM than for RHM. Non-transformed abundances were two times higher for β-casein(154-160) in PHM during the intestinal digestion (except at 60 min) and four times higher for β-casein(161-166) in PHM only at 180 min of digestion. An additional bioactive peptide, not reported within the bioactive peptide databases, was the β-casein(1-18), a caseinophosphopeptide (CPP) homologue  (Wada & Lonnerdal, 2015) , which was present in the human milk prior to digestion in a lower proportion in PHM than in RHM (3 times lower). This difference was maintained along the gastric digestion, while the peptide was hydrolysed rapidly in the intestinal phase.
List of tables and figures Table  1 : Predicted enzymes and cleavage counts for proteolysis of human milk as raw or pasteurized prior to digestion. Table  2. Peptide biochemical characteristics significantly associated (p < 0. 05) with clusters. Table  3. Bioactive peptides identified within the entire peptide dataset (n=1531) using an exact matching search the databases of BIOPEP and MBPDB. Results obtained from the online software Enzyme Predictor. Cleavages from cytosol aminopeptidase and carboxypeptidase B2 were examined manually on β-casein and appear only in supplementatl figure  3. 2 Odds ratio (OR) were calculated on the present enzymes as OR= (a * d) / (b *c), where a is the total number of sites cleaved by enzyme "A" at the peptide termini ("total number of cleavages"), b is the total number of all sites cleaved by all enzymes except "A"; c is the total number of sites enzyme "A" could have cleaved within the current peptides ("number of expected cleavages within peptides"), and d is the number of sites all enzymes, aside from A, could have cleaved within the current peptides.
Acknowledgments The authors thank  Frederic Carrière  and  GERME SA  for providing rabbit gastric extract. The authors also thank the volunteer mothers for their donations of breast milk samples as well as  Emelyne Dirson  and her colleagues from the bank milk of the  Rennes University Hospital Center  for their involvement in the project. This work was supported by  INRA  ( French National Institute for Agricultural Research ) as well as by  CNPq (Brazilian National Council for Scientific and Technological Development ) by funding a Ph. D. scholarship for the author S. D. O. Most authors were participants of the  Food and Agriculture COST (European Cooperation in Science and Technology) Action   FA1005  "Improving health properties of food by sharing our knowledge on the digestive process (INFOGEST).
Although no signal was detected over 3000 m/z, data were acquired over the m/z range of 500-5000 for 2 min. Helium flow rate of 30 ml min -1 and nitrogen flow rate of 25 ml min -1 were used for TWIMS experiments, with 250 m s -1 for wave velocity and 8. 0 V for wave height. Calibration of the experimental arrival time to determine collision cross section (ΩD) values was performed following previously reported methods  65, 66  using ubiquitin and cytochrome c as calibrants. The raw data were processed using Mass Lynx v4. 1 software (Waters). The reported data are the average of three independent experiments. The ESI-IM-MS data were assigned to specific Aβ oligomers on the following basis: (i) First, ion mobility is often described as proportional to collision cross section-to-charge ratio (Ω/z).
Virtual images were acquired using a Mirax Digital Slide Scanner (Zeiss), and image analysis was performed using the Definiens analysis software package v1. 5. Regions of interest (ROIs) were manually delineated in accordance with Franklin and Paxinos atlas, and for each ROI, the percentage of DAB-labelled area was calculated. Measurement of PDK1 activity. PDK1 activity was measured in cell extracts using a fluorescently labeled PDK1 substrate (5FAM-ARKRERTYSFGHHA-COOH, Caliper Life Sciences, Hanover, MD, USA)  74. The relative amounts of substrate peptide and product phospho-peptide were determined using a Caliper EZ-reader (Caliper Life Sciences, Hanover, MD, USA). Data analysis. An analysis of variance of the cell/animal response group was performed using the Kaleidagraph software (Synergy Software, Reading, PA, USA) and the GraphPad Prism software (San Diego, CA, USA).
Acknowledgements We thank  V. Mutel ,  G. Zürcher ,  E. Borroni ,  Z. Lam ,  M. Bühler ,  N. Pierron , and  R. Hochköppler  for providing skillful methodological assistance for all data acquisition and statistical analyses. We acknowledge  M. Briley  for helpful discussions and critical reading of the manuscript. This work was supported by the  French Agence Nationale de la Recherche  ( TargetingPDK1inAD ,  n°ANR-16-CE16-0021-01 ), the  European Joint Program on Neurodegenerative Diseases and Agence Nationale de la Recherche  (PrP C  &PDK1 , n°ANR- 14-JPCD-0003-01 ), the  foundation Vaincre ALZHEIMER  (grant n°FR-15033) and INSERM. JE is funded by  Domaine D'Intérêt Majeur -Cerveau&-Pensée -Région Ile de France. ZAA is a post-doctoral fellow funded by the  ANR PrP C &PDK1 European project  and the  ANR   TargetingPDK1inAD program.
Observational study of nutritional status in French critically ill children We conducted a prospective observational multicenter point prevalence study in France in 2014 (nutritional status assessment), following ethical approval (CPP Sud-Méditerranée IV). This study was registered on Clini-calTrial. gov (NCT02293434). Thirty-one French PICUs affiliated with the French-speaking PICU scientific society (GFRUP) participated in this study. Participating French units, who admitted children aged 1 month to 18 years, consecutively recruited children over three different, one-week time periods in 2014 (February, June, October), to avoid any seasonal recruitment bias. These units were a mixture of standalone PICUs or mixed (pediatric and adult or neonatology) intensive care units. Children whose parents did not understand French or refused to participate were not included.
A dynamic nutritional assessment was also requested, and local investigators were asked to record weight loss in the 3 months prior to PICU admission, and faltering growth, defined as a weight-for-age growth chart presenting with a deceleration of > --1 z-score in the previous 3 months. Previous anthropometric measurements were obtained from medical records or from personal medical records. Anonymized anthropometric data further allowed for centralized calculation of nutritional indices (e. g. , body mass index BMI) and cohort nutritional status description. BMI-for-age z-score was used as a continuous variable to describe nutritional status, using both French and World Health Organization (WHO) references to allow for other cohort comparisons  [9]. Undernutrition was defined as a BMI-for-age z-score < -2 SD, as per WHO standards, and overweight as a BMI-for-age z-score > 2 SD.
Nutritional status was further described using other nutritional indices: weight-for-age z-score, weight-forheight z-score, Waterlow index, height/length-for-age z-score, mid-upper arm circumference z-score, midupper arm circumference/head circumference ratio when age ranges were appropriate  [10]. In case of history of prematurity, z-score for age were based on the corrected age. The calculation of nutritional indices was performed using the survey function of WHO software "ANTHRO" and "ANTHROplus, " available online  [36]  and EPINUT software (www. epinu t. fr) an online nutritional assessment tool certified by the French-speaking Society of Clinical Nutrition and Metabolism, for WHO and French references, respectively. These calculations were based on age and gender and anthropometric data collected from the study population, and expressed as z-scores, according to recent recommendations  [10, 35, 36].
Patients' characteristics were compared according to nutritional status (WHO standards for undernutrition) using Wilcoxon or Kruskal-Wallis tests for quantitative variables, and using Chi-squared test for qualitative variables. We used logistic regression model to calculate the adjusted odds ratios and their 95% confidence intervals. Only variable with a p < 0. 2 in univariate analysis was entered in the model. The two-sided significance level set at 0. 05. SAS ® version 9. 4 (SAS Institute, Cary, NC) was used.
The nutritional status of children in French PICUs During the three one-week periods of recruitment, 432 children (from 27/31 French PICUs) were included. Out of 490 eligible patients, 46 were not included because of early death or transfer, or refused parental consent and 12 were excluded because of missing data compromising BMI calculation. Patient characteristics are detailed in Table  3. Weight was measured at admission in 77% of children, and height/length in 60%; they were estimated in remaining children. Thirty-eight percent of children had received nutritional support (enteral or parenteral) before PICU admission. According to WHO BMI z-score definition, 18. 5% of children were diagnosed with undernutrition at PICU admission (Fig. 2 ). In children under 5 years, undernutrition was diagnosed in 19.
[5]  would be required to properly assess nutritional status, including a dynamic assessment, taking into account pathophysiology, etiology, chronicity and the impact of malnutrition. Anthropometric measurements are difficult to perform in the PICU setting: weighing children may be challenging because of PICU equipment (tubes, probes, mechanical ventilation) or considered unsafe; height cannot be measured respecting WHO guidelines in the bedbound child. This may have impacted on measurement accuracy. The diagnosis of faltering growth occurring prior to PICU admission may also be biased by the accuracy and validity of previous anthropometric measurements, performed outside the study. No data regarding outcomes were collected in the study, which did not allow us to assess the nutritional status impact on outcomes.
To study the effects of Prok2 underexpression on metabolic parameters, mice injected in the MOB with the scrambled-shRNA or Prok2-shRNA were placed in calorimetric cage (TSE system, Germany) 3 weeks postsurgery and kept under a 12 h light/12 h dark cycle from 7. 00 am to 7:00 pm in a temperaturecontrolled environment at 22. 5 C with ad libitum access to food and water. Animals were accustomed to daily manipulation. After 48 h of acclimation, feeding behavior, energy expenditure, substrate utilization, and locomotor activity were measured. Ultra structure of meals (meals and bouts number, size and frequency) as defined by Gaetani et al. [21]  was performed using in-house analytic sheet under Excel (Microsoft SA, Issy-les-Moulineaux, France). Raw data (mg of change per second resolution) were obtained from automatic food and drink sensors (TSE, Bad Hamburg, Germany).
Population The D. E. S. I. R. study (Data from an Epidemiological Study on the Insulin-Resistance syndrome) is a prospective study of 5212 participants at inclusion (2,576 men and 2,636 women, aged 30e65 years), recruited from volunteers who were offered periodic health examinations free of charge by the French Social Security system in 10 health examination centers from the western part of France. They were clinically and biologically evaluated every three years, and the final examination was 9 years after inclusion. A detailed description of all clinical and laboratory measurements is reported by Balkau et al. [23]. Dietary intakes were assessed (protein, lipid, carbohydrate, and total energy intake) from a validated questionnaire on eating habits  [24]. The socio-economic status was coded as: 1.
Statistical analyses 2. 3. 1. Mice studies GraphPad Prism 5 was used for all representations and statistical analyses. Results are presented as mean AE SEM. Analyses used either Student's t-test when a normal distribution was validated, or one/twoway(s) ANOVA followed by Bonferroni post hoc test when data were not normally distributed. Rhythmicity was assessed using Circwave v1. 4 (free software developed by Roelof A. HUT, University of Groningen, Netherlands). The statistical tests as well as the number of mice used for each experiment are mentioned in the figure caption. Differences between groups were considered significant when P < 0. 05.
To assess the effect of rPROK2 injection in the MOB on olfactory behavior, we performed a buried food test which relies on the animal's natural tendency to use olfactory cues for foraging. The main parameter is the latency to find and uncover a small piece of palatable food, hidden beneath a layer of cage bedding. In control mice, 24 h fast significantly decreased the buried food discovery time by 79% when compared to mice fed ad libitum (Figure  2C ). Interestingly, rPROK2 injection (500 pmol/mouse) into the MOB of fasted mice resulted in a 3. 6-fold increase of the latency to uncover the small piece of buried food compared to the fasted group (Figure  2C ). These data show that PROK2 can be a local MOB regulator of olfactory function participating in food intake. 3. 1. 3. Partial deletion of Prok2 in the MOB has no effect on body weight but alters the food intake microstructure (Figures  3  and 4 ) Injection of the Prok2-shRNA was processed in 8 different locations and restricted to the MOB.
ACKNOWLEDGEMENTS This work was supported by grants from  CORDDIM Ile-de-France ,  Société Francophone du Diabète (SFD , grant  SFD-BD ) and  Fondation pour la Recherche Médicale (FRM , grant  FDT20150532232 ). We also acknowledge the animal core facility " Buffon " of the  University Paris Diderot-Paris 7/Institut Jacques Monod, Paris  for animal husbandry and breeding. We.
Element concentration expressed in µg. g -1 were determined for each of the selected regions. Finally, the elemental content in the three regions of interest (SNpc, SNpr and VTA) was calculated as the mean value of the extracted regions of all the individual scans performed on each region. The number of analyzed animals was 15 for the 6-OHDA group and 12 for the Sham group. Quantitative data treatment of PIXE spectra was performed using the GUPIXWIN software  (Campbell et al. , 2010). This software allows determining the elemental areal mass (µg • cm -2 ). Charge normalization of PIXE data was obtained by fitting RBS spectra with SINMRA software  (Mayer, 1997)  following a methodology described in earlier publications  (Carmona et al. , 2008 (Carmona et al. , , 2017;; Perrin et al. , 2015).
Statistical Analyses Statistical analyses were conducted using open access R software (R Core Team, 2013), R Commander  (Fox and Bouchet-Valat, 2018) , and RStudio  (RStudio Team, 2016). We compared each brain region (SNpc, SNpr, and VTA) and brain side (ContraL and IpsiL) for the two injection conditions (sham and 6-OHDA injured). The normality postulate was not always fulfilled and we considered the regions and brain sides as not paired. Multiples comparison of elemental content were performed using Kruskal Wallis test. Wilcoxon comparison as post hoc test was used to determine, for each element, which zone show significant differences, no method to adjust p-value was used  (Feise, 2002).
Iron Oxidation State Measured by Micro-XANES and XRF Imaging of Fe and Mn Iron can be present in biological tissues in different oxidation states, mainly Fe(II) and Fe(III), which determine the reactivity and potential toxicity of this element. Iron oxidation state was measured in the SNpc and the SNpr and for both brain sides (IpsiL and ContraL) and injection conditions (6-OHDA and sham). Micro-XANES data indicated that Fe is present in form of Fe(III), in all cases, regardless of the injection side or the brain region (Figure  5  and Table  1 ). Micro-XANES spectra for all brain regions show that Fe exhibits very similar shapes and values of the first derivative inflection point as for the ferritin standard, suggesting that iron could be complexed principally to ferritin (Figure  5  and Table  1 ).
ACKNOWLEDGMENTS We are grateful to  AIFIRA Facility at CENBG  for beamtime allocation. We acknowledge SOLEIL for provision of synchrotron radiation facilities. We would like to thank  LUCIA  staff and in particular  Nicolas Trcera  for assistance in using beamline LUCIA. We are very grateful to  Jean Luc Guerquin-Kern  ( Institut Curie, Orsay ) and  Sylvain Bohic  ( Grenoble Institute of Neuroscience ) for helpful discussions and contribution to other parts of the project.