dataesr/scientific-paragraphs-categorization huggingface dataset:
Enriched peptides were subjected to secondary digest with trypsin and second STAGE tip prior to LC-MS/MS analysis. Replicate injections of each sample were run non-sequentially for each enrichment. Peptides were eluted using a 90-min or 150-min linear gradient of acetonitrile in 0. 125% formic acid delivered at 280 nL/min. Tandem mass spectra were collected in a data-dependent manner with a Thermo Orbitrap QExactive or Fusion™ Lumos™ Tribrid™ mass spectrometer using a top-twenty MS/MS method, a dynamic repeat count of one, and a repeat duration of 30 s. Real-time recalibration of mass error was performed using lock mass  79  with a singly charged polysiloxane ion m/z = 371. 101237. MS/MS spectra were evaluated using SEQUEST and the Core platform from Harvard University  [80] [81] [82]. Files were searched against the most recent update of the UniProt mus musculus FASTA database.
A mass accuracy of ±5 ppm was used for precursor ions and 0. 02 Da for product ions. Enzyme specificity was limited to trypsin, with at least one tryptic (K-or R-containing) terminus required per peptide and up to four mis-cleavages allowed. Cysteine carboxamidomethylation was specified as a static modification, oxidation of methionine and phosphorylation on serine, threonine, or tyrosine residues were allowed as variable modifications. Reverse decoy databases were included for all searches to estimate false discovery rates, and filtered using a 2. 5% FDR in the Linear Discriminant module of Core. Peptides were also manually filtered using a ±5 ppm mass error range and presence of a phosphorylated residue (IMAC) or phosphorylated residue within an RXX(s/t) motif (Akt Substrate Motif antibodies).
Acknowledgements We are grateful to  Arnaud Echard ,  Manuel Thery , and the members of  INSERM-U1151  for support, critically reading the manuscript and helpful discussions. We thank the histology, imaging, metabolomics, and viral vector facilities at the  SFR Necker  for the technical help. We thank  Marine Largeau  and  Veronique Cussin  from the  Biological Resources Center and Tumor Bank Platform of Georges Pompidou European Hospital  for technical support ( BB-0033-00063 ) for providing biological samples. This work was supported by grants from the  European Research Council, Inserm Agemed , ASTB patient association and InCa to M. P. , and  ARC  to M. P. , B. D. , and V. V.
Data availability Material and correspondence: All data are available from the corresponding author upon reasonable request. The information and requests for resources and materials should be directed to Dr. Mario Pende (mario. pende@inserm. fr). The source data for the phosphoproteome has been deposited to the ProteomeXchange Pride database with accession PXD014832. The source data underlying Figs. f, h, e, g, 5d , 7a-g, 8b-d, and 9b, and Supplementary Figs. 3b, c , 4a, b, 5b, 6a-d, 7b, 9a, 10a-c, 11a, b, d, f, g, and 12c are provided as a Source Data file.
Stage 1: Systematic reviews of the literature We will conduct four systematic reviews to identify and assess the available literature on stakeholder engagement in guideline development. This protocol will yield four distinct but related systematic reviews that will inform the overall protocol output. To improve efficiency, we will conduct an integrated literature search, screening, and data extraction process. Once included, articles will be tagged for their relevance to a review(s). Analyses and reports will be conducted separately for each review. Given the qualitative and multi-stage nature of this study, we believe the GRIPP2 checklist is more suitable for reporting the conduct of this project. The systematic review stage will be developed following the PRISMA-P checklist (Additional file 4) Below, we briefly describe the objectives of each review and the methods common to all reviews.
g. , cohort studies, before and after studies, cross-sectional studies), qualitative studies, theoretical and ethical papers, process evaluation studies, policy analysis studies, case studies, and mixed-methods studies. We will exclude editorials, commentaries, proposals, and conference abstracts. Studies without a clear methods section will be excluded. Search strategy We will develop one comprehensive search strategy to identify relevant studies for the four reviews. We will search the following databases: MED-LINE (OVID), CINAHL (EBSCO), EMBASE (OVID), PsycInfo (OVID), AMED (OVID), and SCOPUS. We will not place limits on language, date, or study design. In addition, we will perform both backward and forward citation tracking to identify further eligible studies. A draft of the search strategy is provided (see Additional file 5).
To identify grey literature, we will search the websites of agencies who actively engage stakeholder groups such as the AHRQ, Canadian Institute of Health Research (CIHR) Strategy for Patient-Oriented Research (SPOR), INVOLVE, the National Institute for Health and Care Excellence (NICE), and the PCORI. We will also search the websites of guideline-producing agencies, such as the American Academy of Pediatrics, Australia's National Health Medical Research Council (NHMRC), and the WHO. We will invite members of the team to suggest grey literature sources, and we plan to broaden the search by soliciting suggestions via social media, such as Twitter (https://twitter. com/CochraneEquity). Study selection Titles and abstracts of the studies identified by the search strategy and the full texts of those assessed as potentially relevant will be screened independently, in duplicate using Covidence software  [38].
Data extraction The data extraction form will be pretested and will include (as applicable) factors related to the population, intervention, comparison, and outcomes. Extracted data common to all reviews include information on study characteristics (e. g. , year of publication, authors, type of publication), stakeholders included, stakeholder roles, and stakeholder characteristics. The data will be extracted independently in duplicate by two reviewers and will be piloted on ten articles. Disagreements on extractions will be resolved by discussion and with a third member of the research team when necessary. Where necessary, the corresponding author of eligible studies will be contacted for additional information We will use the 18 steps of the guideline development process as a framework for data extraction and will map the existing guidance, barriers and facilitators, conflicts of interest, and impacts discussed in our included studies to one or more of the steps of this framework  [7].
We are not including language or date restrictions on our search strategy. A potential limitation of these reviews is that we are including papers regardless of their methodological quality. This will allow us to collect and synthesize qualitative data that we may miss if standard methodological criteria are applied. We will discuss limitations further in the full review. These reviews will contribute to the literature by identifying existing guidance, barriers and facilitators, potential impacts, and possible conflict of interest issues related to engagement of stakeholders from many stakeholder groups in guideline development and implementation. The results of the four reviews will inform the development of draft guidance. Once drafted, we will gather opinions and priorities on the guidance items from a wide range of purposefully selected stakeholders external to the MuSE consortium, including representation from low-and middle-income countries through an anonymous, online survey.
Funding This work has been funded by the  Canadian Institutes of Health Research  ( PJT-155970 ; Application number: 391110). AS is supported by a  National Health and Medical Research Council   Postgraduate Scholarship  ( GNT 1132803 ). SVK is funded by a  NRS   Senior Clinical Fellowship  ( SCAF/15/02 ), the  Medical Research Council  ( MRC_UU_12017/13 & MRC_UU_12017/15 ), and the  Scottish Government Chief Scientist Office  ( SPHSU13 & SPHSU15 ). PC and AP are employed by the  Nursing, Midwifery and Allied Health Professions Research Unit , which is funded by the  Chief Scientist Office in Scotland. IDG is a recipient of a  Canadian Institutes of Health Research Foundation  Grant (FDN#  143237 ). The funders had no role in study design, preparation of manuscript, or the decision to publish.
0001; UCMS microbiota-recipient mice vs UCMS microbiota-recipient mice + AA, P = 0. 0113; UCMS microbiota-recipient mice vs UCMS microbiota-recipient mice + Lp WJL , P = 0. 0394). g 16S rDNA of the fecal microbiota of donor mice at the end of the 8 weeks UCMS protocol (n = 4/group, top) or recipients mice after 8 weeks in isolators (n = 4/group, bottom) was sequenced and analyzed by principal component analysis (PCA) at the level of bacterial families for the relative abundance of bacterial families. Data are represented as boxplots, with median, minima, and maxima. Statistical significance was calculated using Mann-Whitney test (top, Ruminococcaceae, P = 0. 0571; Porphyromonadaceae, P = 0. 0571; Lactobacillaceae, P = 0. 0286; bottom, Lactobacillaceae, P = 0. 0286, two tailed). h Alpha diversity for donors (P = 0.
16S data analysis. Sequences were clustered into OTUs (Operational Taxonomic Units) and annotated with the MASQUE pipeline (https://github. com/aghozlane/ masque) as described  72. OTU representative sequences were assigned to the different taxonomic levels using RDP Seqmatch (RDP database, release 11, update 1)  73. Relative abundance of each OTU and other taxonomic levels was calculated for each sample in order to consider different sampling levels across multiple individuals. After trimming, numbers of sequences clustered within each OTU (or other taxonomic levels) were converted to relative abundances. All the analysis were performed blinded to experimental conditions. Statistical analyses were performed with SHAMAN (shaman. c3bi. pasteur. fr) as described  74. Briefly, the normalization of OTU counts was performed at the OTU level using the DESeq2 normalization method.
In SHAMAN, a generalized linear model was fitted and vectors of contrasts were defined to determine the significance in abundance variation between sample types. The resulting P values were adjusted for multiple testing according to the Benjamini and Hochberg procedure  75. Principal coordinates analysis was performed with the ade4 R package (v. 1. 7. 6) using a Bray-Curtis dissimilarity matrix. Further statistical analysis was conducted using the Prism software (GraphPad, v6, San Diego, USA). Differences between two groups were assessed using Mann-Whitney test for family abundance. Gut permeability test. This examination is based on the intestinal permeability to 4 kD fluorescent-dextran (Sigma-Aldrich). After 4 h of food withdrawal, mice were orally administered with FITC-dextran (0. 6 g/kg body weight).
• Tail suspension test. Mice were suspended by the tail using adhesive tape affixed 1 cm from the origin of the tail, on a metal rod under dim light conditions (~40 lux). The behavior of the animals was recorded by a video camera during a 5-min period and total immobility time was evaluated in a blind manner. • Forced swim test. Mice were placed individually into plastic cylinders (19 cm diameter, 25 cm deep) filled to a depth of 18 cm with water (23-25 °C) under dim light conditions (~40 lux) for 5 min. The behavior of the animals was recorded by a video camera and immobility time was automatically evaluated using the EthoVision XT 5. 1 software (Noldus Information Technology). In both TST and FST, mice face an uncomfortable situation that they confront by attempting to move out of it and eventually surrender to.
Image acquisition and quantification analysis. Immunofluorescence was analyzed using an Apotome microscope (Apotome. 2; Zeiss) with the Zen Imaging software (Zeiss), courtesy of Pr. Peduto. Quantification was performed using the Icy open source platform (http://www. icy. bioimageanalysis. org)  77. The region of interest was defined as the granule cell layer (GCL) of the DG, and automatic detection of Ki67 + and DCX + cells was performed using the spot detector tool. Values are expressed as the mean of total Ki67 + or DCX + cell count per mm 2 in six slices per animal. All imaging and quantification were performed blinded to experimental conditions. For EdU analysis, positive cells were manually counted in the GCL of the DG. Total number was estimated by multiplying the total number of cells every sixth section by six.
Blots were blocked in blocking buffer containing 5% (w/v) milk and 0. 1% (v/v) Tween-20 in Tris-buffered saline (TBS-T) for 1-2 h at room temperature and incubated overnight at 4 °C with antibodies against p-mTOR (S2448) (1:1000, Cell Signaling), mTOR (1:1000, Cell Signaling), p-p70S6K (T389) (1:500, R&D Systems), p-rpS6 (S235/236) (1:500, R&D Systems), or glyceraldehyde 3-phosphate dehydrogenase (1:1000, Cell Signaling) antibodies. Blots were washed 3 times with TBS-T and then probed with anti-rabbit IgG, horseradish peroxidase-linked antibody (1:3000, Cell Signaling) for 1 h at room temperature before being revealed using ECL Prime detection reagent (GE Healthcare) and chemiluminescence reading on a luminescent image analyzer (LAS-4000; Fujifilm). Immunoreactivity of western blots was quantified by densitometry using the ImageJ software (NIH, Bethesda) and the analysis was performed blinded to experimental conditions.
PUFAs and AEA were separated on a SFC (Acquity UPC2, Waters, France) using a Torus 1-Aminoanthracene 100 × 3. 0 mm, 1. 7 μm column (Waters, France) at 60 °C. Mobile phase A containing CO 2 and B containing MeOH and 0. 2% formic acid were used for separation during a running time of 6. 5 min with a flow rate at 1. 8 ml/min. Wash weak and strong weak solutions are composed of Heptane/ Isopropanol (90:10, v/v) and Isopropanol/Methanol/Chloroform (45:45:10, v/v/v) respectively. Finally, the make-up solution is composed of ACN. MS data were acquired in negative ionization mode on a Xevo TQ-MS triple quadrupole mass spectrometer (Waters, USA) controlled by the Masslynx software (version 4. 1) with an ion spray voltage of 2500 V, a source, and a desolvation temperature set to 150 and 450 °C. Cone voltage was set to 30 V for PUFAs C18:2 and C18:3 and 25 V for PUFAs C20:5, C20:4, C22:6, deuterated C18:0 d4 as internal standard, and AEA.
Multiple reaction monitoring (MRM) experiments were performed using parent-parent ion transitions for PUFAs with a collision energy (CE) at 5 eV while AEA analysis was performed by MRM experiment using transition 346 to 259 with a CE set to 15 eV. Following mean normalization, data were analyzed using oneway analysis of variance (ANOVA). All the quantification was performed blinded to experimental conditions. Metabolomics. Blood were collected by cardiac puncture in Microvette ® tubes (Sarstedt, Marnay, France) from behaviorally validated adult mice. The tubes were centrifuged at 10,000 × g for 5 min, at room temperature, to extract the serum. Serum samples were then extracted and analyzed on gas chromatography tandem mass spectrometry (GC/MS), LC/MS, and LC/MS/MS platforms by Metabolon, Inc.
Following log transformation and imputation with minimum observed values for each compound, data were analyzed using two-way ANOVA with contrasts. Statistical analysis. Statistical analysis was performed using the Prism software (GraphPad, v6, San Diego, USA). Principal component analyses and heatmaps were performed using Qlucore Omics Explorer (Qlucore). Data are plotted in the figures as mean ± s. e. m. Differences between two groups were assessed using Mann-Whitney test. Differences among three or more groups were assessed using one-way ANOVA with Tukey's. Significant differences are indicated in the figures by *P < 0. 05, **P < 0. 01, ***P < 0. 001, ****P < 0. 0001. Notable near-significant differences (0. 05 < P < 0. 1) are indicated in the figures. Notable non-significant (and non-near significant) differences are indicated by "n.
Acknowledgements We would like to thank all the members of the  Eberl and Lledo laboratories , as well as members of the  Peduto laboratory  for insightful discussions, and  Pr. Peduto  for access to the Apotome microscope as well as  Giovanni Marsicano  and  Arnaud Busquets  for some advice. A special thanks also to the members of the  Pasteur Animal Facility  who were essential for this project, and in particular  Marion Bérard ,  Martine Jacob ,  Thierry Angelique , and  Eddie Maranghi. This work was supported by the  Major Federating Program  " Microbes & Brain " of the  Institut Pasteur ,  Agence Nationale de la Recherche  Grant  ANR-16-CE15-0021-02-PG-Brain  and a grant from the  Fédération pour la Recherche sur le Cerveau (FRC). Lledo's laboratory is supported by  Agence Nationale de la Recherche  Grants  ANR-16-CE37-0010-ORUPS  and  ANR-15-NEUC-0004-02  " Circuit-OPL," Laboratory for Excellence Programme  " Revive " Grant  ANR-10-LABX-73 , and the  Life Insurance Company AG2R-La Mondiale.
Data availability The metabolomics datasets of mouse serum can be accessed at MetaboLights [https:// www. ebi. ac. uk/metabolights/index] (Project ID: MTBLS121). The metabolomics datasets of mouse hippocampus tissues can also be accessed at MetaboLights [https://www. ebi. ac. uk/metabolights/index] (Project ID: MTBLS2106). All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.
The Binding of the Hit Compounds C6 and C6-3 to HMBS The binding of C6 and C6-3 to HMBS was analyzed by surface plasmon resonance (SPR), measuring the response units from the compound concentration-dependent, steady-state binding response, and analyzed assuming a 1:1 binding model (Figures  2C  and 2D ). C6 showed some unspecific binding by SPR, and an accurate concentration of compound at half-maximal binding (S 0. 5 ) could not be obtained (Figures  2C, S4A,  and S4B ). The binding of C6 to HMBS was therefore also analyzed with the Octet RED96 system with super streptavidin (SSA) biosensors in which data analysis using double reference subtraction accounts for nonspecific binding and minimizes the well-based and sensor variability. For the loading of the sensors, the protein needed to be biotinylated, but no alteration for the buffer conditions was required.
40 With the use of the pocket finder tool fpocket to identify binding sites adequate to accommodate stabilizing small-molecule compounds,  41  the structure of the human HMBS holoenzyme (PDB: 3ECR) revealed two relevant binding pockets other than the active site pocket (Figure  3A ). However, computational protein-ligand docking suggested a favorable binding mode of both C6 (and C6-3; not shown) in only one of these pockets, close to the active site (Figure  3B ). Consequent docking to the holoenzyme provided a topscore binding mode of C6 in which the hydroxyl and aldehyde oxygens of C6 interact with the guanidine group of Arg195, facilitating two hydrogen bonds, whereas the more hydrophobic part can interact with Leu238 and Val38 (Figure  3C ). On the other hand, for C6-3, the oxygens that interact with Arg195 via hydrogen bonds are those in the nitro group (Figure  3D ).
The X-ray structure of an enzyme intermediate captured in the ES 2 state, with two PBG substrates bound to the covalently linked dipyrromethane (DPM) cofactor (PDB: 5M6R), allowed the prediction of the interaction of the PC candidates with intermediate states of HMBS other than the holoenzyme. 42 Nevertheless, the analysis of this ES 2 -state structure revealed overlapping binding pockets as in the holoenzyme (Figures  S5A  and S5B ). Subsequent docking to the ES 2 -state structure showed potential docking modes for the compounds with similar docking scores as for the holoenzyme-docked structures, with possible interactions with Val38 and Leu238. Hit Compound C6 and Analog C6-3 Decrease ALA and PBG Excretion in Hmbs-Deficient Mice In a second animal trial using Hmbs-deficient T1/T2 À/À mice, denoted trial T1/T2-B, we further investigated the PC potential of C5, C6, and C6-3 at higher concentration (20 mg/kg/day) than in trial T1/T2-A.
The control group is shown in white. (C) HMBS protein levels measured in liver lysates by western blot quantification. Scatterplots with mean representing HMBS protein levels in mice livers treated with C5 (red), C6 (blue), and C6-3 (green). *p < 0. 05 for differences with the corresponding control (10% DMSO without compound; white circles), calculated by unpaired two-tailed t test. Data are presented as mean ± SD. (D) HMBS activity in liver lysates. Scatterplot with mean showing the hepatic HMBS activity after treatment with C6 (blue) and C6-3 (green). **p < 0. 01 and ****p < 0. 0001 for differences with the corresponding control (10% DMSO without compound; white circles), calculated by unpaired two-tailed t test. Data are presented as mean ± SD. (E and F) The relative concentrations of ALA (E) and PBG (F) were measured in liver tissue extracts after treatment with C6 (blue) and C6-3 (green).
K M and V max were determined using an increasing concentration of PBG (3. 125-1,000 mM), and the kinetic parameters were obtained by nonlinear fitting to Michaelis-Menten enzyme kinetics using GraphPad Prism version 8. 2. 0 for Windows (GraphPad Software, La Jolla, California, USA; https://www. graphpad. com/). To assay the HMBS activity in liver lysates, the crude liver homogenates were passed through Zeba spin desalting columns (Thermo Fisher Scientific) using 50 mM HEPES (pH 8. 2) as equilibration buffer. 25 mL filtrated homogenate (400-500 mg total protein) was added to 110 mL sample mix (50 mM HEPES [pH 8. 2], 1% Triton X-100) and incubated for 10 min at 37 C before adding PBG (1 mM). The reaction was stopped after 1 h by adding ice-cooled 100% trichloroacetic acid (TCA) to a final concentration of 25%, incubated at room temperature (RT) for 10 min, and centrifuged at 10,000 g for 10 min.
Limited Proteolysis by Trypsin Limited proteolysis by trypsin was performed at 37 C in 20 mM HEPES, 150 mM NaCl, 2% DMSO (pH 8. 2), with 0. 15 mg/mL HMBS in the absence (DMSO control) or presence of 84 mM compound and 2% DMSO. The proteolysis was initiated by adding 1 mg/mL N-tosyl-L-phenylalanine chloromethyl ketone (TPCK)treated trypsin (Sigma-Aldrich). After 30 min, aliquots were removed and transferred to Laemmli loading buffer containing 2 mg/mL soybean trypsin inhibitor. Samples resolved by SDS-PAGE with 10% Mini-Protean TGX gels (Bio-Rad Laboratories, Hercules, California) were analyzed using the Image Lab software (Bio-Rad). The unpaired t test (two-tailed) was performed using GraphPad Prism.
Octet RED96 Octet RED96 system (FortéBio Biologics by Molecular Devices, San Jose, California) with super streptavidin (SSA) biosensors was used as an additional method for determining the binding affinity of C6. The loading of HMBS to the SSA sensors required biotinylation, which was carried out at room temperature, mixing 1. 5 molar excess of N-hydroxysuccinimide (NHS)-ester biotinylation reagent (EZ-Link NHS-PEG4-Biotin; Thermo Fisher Scientific) to protein. After 30 min, excess of biotin was removed using Zeba spin desalting columns (Thermo Fisher Scientific), and the gel filtration buffer was changed to reaction buffer, PBS-P+ (GE Healthcare), supplemented with 5% DMSO. Sensors were loaded with 5 mg/mL of biotinylated HMBS, reaching 6 nm surface thickness. Triplicates for the concentration series of C6 were measured, and double-reference subtraction was applied for data analysis based on the steady-state kinetics with an equilibrium binding signal (R eq ) using ForteBio Data analysis 9.