dataesr/scientific-paragraphs-categorization huggingface dataset:
Flow Cytometry Analysis The Annexin V-FITC Apoptosis Detection Kit was used to determine the cell death produced by compounds as previously described  [50]. SH-SY5Y cells were seeded in 12-well plates at 1 × 10 6 per well and incubated for 24 h with laxaphycins. Then, cells were washed with PBS and resuspended in Annexin binding buffer containing Annexin V-FITC and PI. Cells were incubated for 15 min at room temperature, resuspended in PBS and filtered. The fluorescence was determined by flow cytometry using the ImageStreamMKII (Amnis Corporation, Luminex Corp, Austin, TX, USA). 10,000 events were analyzed with IDEAS Application 6. 0 software (Amnis Corporation, Luminex Corp, Austin, TX, USA). STS (Sigma Aldrich) at 0. 01 µM was used as control in this assay.
Evaluation of Caspase 3 Activity The detection of caspase 3 activity was carried out with the EnzCheck ® Caspase-3 Assay Kit. Neuroblastoma cells were cultured in 12-well plates at 1 × 10 6 cells per well and treated with compounds. After 24 h, cells were lysed and an aliquot was collected to quantify protein concentration by the Bradford method. Then, the assay was performed following manufacturer's instructions. Briefly, 50 µL of each sample were mixed with equal volume of Z-DEVD-AMC substrate and incubated for 30 min at room temperature. Then, fluorescence at 342 nm excitation and 441 nm emission was measured. Caspase 3 activity data were corrected by protein concentration values. STS (0. 01 µM) was used as positive control.
Samples containing 15 µg were used for electrophoresis, resolved in 4-20% sodium dodecyl sulphate polyacrylamide gel (Biorad, Madrid, Spain). Proteins were transferred to PVDF membranes (Merck Millipore) with a Trans-Blot ® semi-dry transfer cell (Biorad). Membrane blocking and antibody incubation was performed in Snap i. d. system (Merck Millipore). Protein bands were detected with Supersignal West Pico Luminiscent Substrate and Supersignal West Femto Maximum Sensitivity Substrate (Thermo Fisher Scientific). Chemiluminiscence was determined with Diversity GeneSnap system and software (Syngene)  [51]. LC3 II/I was detected with the primary antibody anti-LC3 II/I (1:1000, Abcam), the primary antibody anti-pmTOR (Ser2448) (1:1000, Merck Millipore) was used to recognize phospho-mTOR and the total levels of the kinase were determined with anti-mTOR antibody (1:10000, Abcam), beclin-1 was detected with anti-beclin-1 primary antibody (1:1000, Merck Millipore), p62 was quantified with anti-p62 antibody (1:1000, Merck Millipore), anti-phospho-p70 S6 kinase (Thr389) (1:1000, Merck Millipore) was used to detect phospho-p70 and the total levels were quantified using anti-p70 S6 kinase antibody (1:1000, Merck Millipore), anti-phospho-AMPK (Thr172) (1:500, Merck Millipore) was used to recognize the phosphorylated state of the kinase, and the total expression of the enzyme was detected with anti-AMPK antibody (1:500, Merck Millipore).
Acknowledgments: The research leading to these results has received funding from the following FEDER cofunded-grants. From  Consellería de Cultura, Educación e Ordenación Universitaria, Xunta de Galicia ,  2017 GRC GI-1682  ( ED431C 2017/01 ). From  CDTI and Technological Funds , supported by  Ministerio de Economía, Industria y Competitividad ,  AGL2016-78728-R (AEI/FEDER, UE), ISCIII/PI16/01830  and  RTC-2016-5507-2 ,  ITC-20161072. From  European Union   POCTEP 0161-Nanoeaters -1-E-1 ,  Interreg  AlertoxNet  EAPA-317-2016 ,  Interreg Agritox   EAPA-998-2018 , and  H2020 778069-EMERTOX. We thank  Olivier Thomas  and  Stephane Greff  for HRMS facilities and  Christian Roumestand  for NMR measurements.
To evaluate their reactivity for bioreductive activation, the levels of free radicals under aerobic conditions were quantified. Direct ESR evidence of formation was provided. The data suggest that good levels of free radicals are generated in the HL-60 (e. g. , the HL-60 myeloid leukemia) and MCF-7 cells (e. g. , the MCF-7 breast carcinoma) by compound B. Group B compounds showed good redox cycling in both cell lines (HL-60 and MCF-7 cells). They were cytotoxic in the MCF-7 cell at concentrations down to 10 µM (Figure  7 ).
The ESI-HRMS was a microTOFQ TM (Bruker Daltonics, Bruker, Bremen, Germany) apparatus. The LC coupled with high-resolution mass spectrometry (ESI/QTOF, Bruker Daltonics, Bruker, Bremen, Germany) was used in order to determine the accuracy mass of compounds in the sample extracts. The identification of compounds was performed by comparing the measured molecular mass with the calculated values ± 10 mDa. The analysis was performed in positive mode, and the compound was confirmed by auto-MSMS experiment when the intensity was higher than 1 × 10 4. This system was able to detect the compounds in amounts lower than 1 µg/mL. We used a compass for the otof series 1. 7 software (Bruker Daltonics, Bruker, Bremen, Germany, 2013), including otof Control 3. 4, for acquisition and DataAnalysis 4. 2 for data processing.
To quantify, we used an LC Systeme Advance TM (Bruker Daltonics, Bruker, Bremen, Germany) coupled with an ESI-TQ Evoq TM (Bruker Daltonics, Bruker, Bremen, Germany). The analytical column used was an InfinityLab Poroshell 120 EC-C18 column (50 mm × 30 mm) and eluted at a flow rate of 800 µL/min, using a gradient ranging from 5% solvent B to 99% solvent B in a time span of 40 min. Solvent A consisted of water with 1% of formic acid, and solvent B consisted of pure acetonitrile. Kuwanon G was detected by MRM mode at 20 eV with one quantifying transition 693 > 203 and two qualifying transitions 693 > 355 and 693 > 421. LCMS control and data processing was performed by MS Workstation 8. 2. 1. (Bruker Daltonics, Bruker, Bremen, Germany, 2016).
Morphological analysis The surface morphology of MS was investigated by two different methodologies. For the first analysis, the samples were coated with gold under argon atmosphere and observed in a scanning electron microscope (Quanta) under two magnifications (×500 or ×1000). The second analysis was carried out using a fluorescence microscope (Axio observer 7, Carl Zeiss, Germany) with software Zenblue. The fluorescence was evaluated with DAPI and/or GFP filters with 25% of light source and 70 to 6000 μs of exposure time. For these analyses, the MS samples were dispersed in water (1%, w/v).
Solubility properties of polymeric systems The solubility properties experiments were performed using an inverted microscope (Axio observer 7, Carl Zeiss, Germany). The dry powder of MS (MS-EE-80 or MS-EH-80) was placed into a Petri dish (32 mm) and 1. 5 ml of ultrapure water or a 20% (v/v) ethanol aqueous solution was added. Just after the contact of samples with water a picture was captured (time 0) and another was taken of the same particles after 12 hours. The diameter of 50 particles was determined by software ZenBlue (Carl Zeiss, Germany). The solubility was assessed by the analysing the difference between the diameter at time 0 and after 12 h.
Determination of yield, drug content and entrapment efficiency The product yield was determined by dividing the practical weight of MS into the total amount of drug and polymers used in the preparation of these particles times 100. To evaluate the drug content and entrapment efficiency, 10 mg of MS were added in a 5 ml volumetric flask containing 200 μl of methanol to disrupt the microparticles and extract the MB. After 10 min under ultrasound, the dispersion was filtered, and the absorbance was measured using a UV-VIS double beam spectrophotometer (UV 18000 PC, Shimadzu, Tokyo, Japan) at a wavelength of 664 nm. For the blank solution, the sample was composed of blank-MS. The data were analysed by using a calibration curve obtained from a spectrophotometric method that was previously developed and validated  [35].
Acknowledgments The authors are grateful to  CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior/Coordination for the Improvement of Higher Education of Brazil ; grant number  88887. 205259/2018-00 ), CAPES/ COFECUB  (grant number  917/2018 ) and  CNPq  ( Conselho Nacional de Desenvolvimento Científico e Tecnológico/National Counsel of Technological and Scientific Development of Brazil) , and  FINEP (Financiadora de Estudos e Projetos/Financier of Studies and Projects of Brazil). The authors acknowledge the  State University of Maringá (Brazil)  and  Centre de Recherches sur les Macromolécules Végétales (France)  for supporting the project.
Adsorption isotherms Adsorption isotherms were studied to describe the interactive behavior between the adsorbate (DFC) and the adsorbent (polymer). Isotherm data analysis is important for estimating the adsorption capacity and for describing the adsorbent surface properties and affinity. 15 The Freundlich isotherm model is most frequently employed to describe  adsorption onto heterogeneous surfaces from aqueous solution and reversible adsorption, which is not restricted to monolayer formations. It can be expressed in linear form by the following equation Log q log K 1 n log C e F e = + / where K F and 1/n are the Freundlich constants related, respectively, to the adsorption capacity and the adsorption intensity of the adsorbent. A favorable adsorption is expected when 1 < n < 10, which is even very favorable when 1/n < 1.
Our data showed also two compounds with the same exact mass (m/z 400. 168) but with two different retention time (RT: 4. 9 and 5. 6 min) (Fig. 1b ). According to literature data, m/z 400. 168 could correspond to 7-hydroxyquetiapine (m/z 400. 168) or quetiapine sulfoxide (m/z 400. 168))  6. These nodes are linked to quetiapine (m/z 384. 173) with a mass shift of + 15. 994, corresponding to oxidation reaction. We found also mass shifts which could correspond to two desalkylation (-44. 026 Da), giving rise to m/z 296. 121 compound (Fig. 1b ). In order to find where the biotransformation took place, we used MZMine software chromatogram profile analysis and MS 2 fragmentation trees analysis using SIRIUS 4. 0. 1 software  25. Briefly, chromatogram profile analysis allows us to ensure that all nodes contained in the cluster of interest are not artefact.
SIRIUS 4. 0. 1 software provides us a molecular formula for each detected fragment, allowing us to orientate towards a structural formula. Figure  2  displays the example of two m/z 400. 168 isomers (RT 4. 9 and 5. 6 min). We found that both isomers presented m/z 158. 12 and m/z 269. 07 fragments, which could correspond to the same alkyl chain of quetiapine and an oxidized tricycle, respectively. Thus, we concluded that oxidation reaction took place on the quetiapine tricycle. In addition, we found that m/z 237. 10 and m/z 221. 10 fragments correspond to an oxidized tricycle without sulfur and an unoxidized tricycle without sulfur, respectively (Fig. 2 ). These results suggest that m/z 400. 168 (RT: 4. 9 min) and m/z 400. 168 (RT: 5. 6 min) correspond to 7-OH-quetiapine and quetiapine sulfoxide, respectively.
Cytochrome inhibitors enable quetiapine metabolic pathway inhibition in differentiated HepaRG and primary Human hepatocytes (pHH). Cells were incubated with quetiapine (13 µM) with or without CYPs inhibitors (ketoconazole 10 µM as a CYP3A4/5 inhibitor in grey; quinidine 10 µM as a CYP2D6 inhibitor in red) in (a) differentiated HepaRG cells or (b) pHH. Quetiapine concentration was measured at H0, H3, H6, H8 and H24 using high-resolution liquid-chromatography and expressed relative to the value determined at H0 (set arbitrarily to 100%). The data are quoted as the mean ± SEM from one experiment performed in triplicate. Statistics (unpaired student's t-test): ***p < 0. 01 and *p < 0. 05 for cultures exposed to quetiapine + CYP inhibitor (ketoconazole or quinidine) compared with quetiapine alone at different times.
LC-MS settings. Liquid chromatography-mass spectrometry (LC-MS) analyses were carried out using Orbitrap Q Exactive mass spectrometer coupled to an UltiMate 3000 pump (Thermo Scientific, San Jose, CA). A heated electrospray ionization source (HESI-II) was used for the ionization of the target compounds. Data acquisition, calibration and instrument control were performed using Xcalibur 2. 1 (Thermo Scientific, San Jose, CA) software. Samples were maintained at 15 °C in the autosampler and quality controls were injected before each analysis. Quetiapine quantitation assays were performed using a validated LC-HRMS method as already used  13  as follow: The mobile phases were composed of ammonium formiate at 10 mM and formic acid 0. 1% in water (phase A) and acetonitrile and formic acid 0. 1% phase B).
LC was performed on a on a Hypersil Gold column (5 mm × 2. 1 mm, 3 µm) (Thermo Scientific, San Jose, CA). Gradient elution was as follow : initial conditions of 95:5 (A:B) maintained for 1. 5 min, increasing to 70:30 (A:B) for 3. 5 min, increasing to 60:40 (A:B) for 3 min, increasing to 5:95 (A:B) for 1 min, followed by a 1 min plateau with 5:95 (A:B), decreasing to 95:5 (A:B) for 3 min, and return to initial conditions 95:5 (A:B) for equilibration for 3 min. This corresponded to a total chromatographic run of 15 min. The flow rate was 500 μL/ min, the column temperature was maintained at 25 °C, the injection volume was 5 μL. For mass spectrometry, the instrument operated in ESI positive mode, the range for acquisition was 120-700 m/z. Full scan data were acquired at a resolution of 140. 000 FWHM, an AGC target of 1e6 and a maximum injection time of 200 ms.
The flow rate was 500 μL/min, the column temperature was maintained at 40 °C, the injection volume was 10 μL. For mass spectrometry, the instrument operated alternately in ESI positive and negative mode in the same run, the range for acquisition was, respectively, 70-1000 m/z in positive mode and negative mode. Ion precursor selection was performed in the data dependent mode of operation where the most intense ion from the previous scan was selected for fragmentation. Full scan (MS1) data were acquired for each ionization mode at a resolution of 35,000 FWHM, with an AGC target of 1e6 and a maximum injection time of 120 ms. Source parameters were as follows: source voltage + 3. 0 and -4. 0 kV, sheath gas flow 60 units, auxiliary gas flow 10 units, capillary temperature 320 °C, S-Lens RF level 60 units.
MS/MS (MS2) data were acquired at a resolution of 17,500 FWHM with an AGC target of 1e5, maximum injection time was 50 ms, a TopN of 5 in positive mode and 2 in negative mode, an isolation window of 2. 0 m/z. The normalized collision energy (NCE) was stepped at 17. 5, 35 and 52. 5, and the dynamic exclusion time set at 3 s. MN generation. Spectral data allowed us to generate MN using semi-quantitative bioinformatics approach. Data acquisition, processing (i. e. MS data conversion, preprocessing, MS1 annotation, and generation of molecular networks), visualization and network analysis have been described in detail elsewhere  9. Briefly, raw data were converted to an open MS format (. mzXML) with ProteoWizard's MSConvert module  46. The mzXML files were then preprocessed (deconvolution, de-isotoping, alignment, gap-filling) with MZmine 2 software 47.
The single. mgf output file was then loaded on the Global Natural Products Social networking (GNPS) web-based platform in order to generate the multi-matrix molecular network 8. To the use of high resolution data, the basic parameters were modified to m/z 0. 02 for the mass tolerance of precursor and fragment ions used for MS/MS spectral library searching, and m/z 0. 02 for the mass tolerance of fragment ions used for MN. The minimum cluster size was set to 1. In addition, links between nodes were created when the cosine score was greater than 0. 70, and the minimum number of common fragment ions shared by two MS/MS spectra was 6. Links between two nodes were only kept in the network if each node was in the top 10 most similar nodes. Full data processed through the GNPS platform are accessible through these links: • https ://gnps.
ucsd. edu/Prote oSAFe /statu s. jsp?task=028be ffa24 9c495 dbe8c 9c94d fbc3e 49 (Fig. 1 : in vitro quetiapine metabolism kinetic); • https ://gnps. ucsd. edu/Prote oSAFe /statu s. jsp?task=cfabff d4f1 cf4fb b8571 bb039 040ab 75 (Fig. 4 : in vitro quetiapine metabolism pathway inhibition in differentiated HepaRG cells); • https ://gnps. ucsd. edu/Prote oSAFe /statu s. jsp?task=dfe75 ac427 3d49b 69b83 2bbe3 c2c5e f5 (Fig. 5 : in vitro versus in vivo quetiapine metabolism); • https ://gnps. ucsd. edu/Prote oSAFe /statu s. jsp?task=8f00f 95fd3 ca4ea 99fc6 477ba 1a55c af (Supplementary Fig. 1 : in vitro quetiapine metabolism pathway inhibition in pHH). The molecular network was visualized using Cytoscape 3. 5. 1 software  48. The nodes were annotated by comparison with reference standards, by spectral matching with the curated GNPS, mzCloud online mass spectral libraries and information propagation  49.
Data processing The resulting OTUs were assigned using MetaGX, a home-made software pipeline developed with the start-up XeGen (http://xegen. eu/) based on QIIME  [35]  and using BLAST  [39]  for taxonomic assignment and SILVA  [40, 41]  as a reference dictionary (See the supplemental material). For taxonomic assignments, we applied at least 20 reads per OTU. The OTUs were then searched against each database using BLASTN  [39]. The best match of ≥ 97% identity and 100% coverage for each of the OTUs was extracted from the reference database, and taxonomy was assigned up to the species level.
Statistical analysis The data were entered into the Microsoft O ce Excel template, then imported and analyzed in the statistical software SPSS, version 20 (IBM Corp. , Armonk, NY) using bilateral uncorrected chi-square test (χ2), with a signi cance level at P ≤ 0. 05. In vitro proof-of concept of antagonistic activity against Treponema sp. In order to con rm the predicted antagonists detected in silico, we performed in vitro tests using the antibiotic discovery method  [43]. This method reveals antibacterial effects, based on the principle that a bacterium inoculated into a solid medium [8] or a substance produced this bacterium diffusing into the solid culture medium can inhibit a target strain subsequently inoculated onto the medium. In this work we used Treponema denticola CSURP 7640, isolated in our laboratory from the oral cavity against which top ranking predicted antagonists were tested.
This systematic review aims to investigate the role of the oral microbiome in the pathophysiology of mental health disorders and to appraise the methodological quality of research of the oral-brain axis which is a growing interest area. The PRISMA guideline was adopted, to carry out an electronic search through the MEDLINE database, to identify studies that have explored the role of the oral microbiome in the pathophysiology of mental health disorders published from 2000 up to June 2020. The search resulted in 140 records; after exclusions, a total of 22 papers were included in the present review. In accordance with the role of the oral microbiome in the pathophysiology of mental disorders, four mental disorders were identified: Alzheimer's disease, dementia, and cognitive disorders; autism spectrum disorder; Down's syndrome and mental retardation; and Bipolar disorders.
Search Strategy An electronic search was conducted through the MEDLINE (PubMed) database to identify publications that met the inclusion criteria. High-throughput sequencing techniques for genetic material developed in the 2000s have led to a better understanding of the nature of host-microbiota interactions, the interactions of microorganisms with each other, and their impact on health  [42]. That is why the search was performed from 2000 up to June 2020, in order to identify the studies that explore the role of the oral microbiome in the pathophysiology of mental health disorders, using the following search terms and keywords alone or in combination with the Boolean operator "AND"/ "OR" according to the following equation [Mouth/microbiology [Mesh]) OR "Mouth Diseases/microbiology"[Mesh]) OR "Saliva/microbiology"[Mesh:NoExp]) OR "Mouth Diseases/immunology"[Mesh]) AND "Mental Disorders"[Mesh]].
Study Selection The initial studies retrieved from the databases were first selected, and studies that met the eligibility criteria were reviewed and analysed. From 140 studies, 19 were selected. The complementary detection resulted in the selection of three additional articles. Taken together, a total of 22 articles were included in the analysis (Figure  1 ). Each study that met the inclusion criteria was analysed from several aspects, such as authors, date of publication, the time when the study was conducted, study design, objectives, results, and limitations. Of the 22 studies included in the analysis (Table  1 ), four distinct themes in mental health disorders emerged: Alzheimer's disease (AD), dementia, and cognitive disorders  [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] ; autism spectrum disorder (ASD)  [61] [62] [63] ; Down's syndrome (DS) and mental retardation  [64] [65] [66] [67] [68] ; and bipolar disorders  [69].
Micro-CT imaging Each sample was scanned using X-ray micro-CT (microtomography) (Figure  1 ) with the Nanotom S Phoenix X-ray (Baker Hughes GE, Boston, Massachusetts, USA, 180 kV -150 µA, 25 W) at maximum accuracy according to the size of the sample. Before starting experiments, a blank of detector noise was recorded, then subtracted of radiography data set. Samples were placed frozen in the micro-CT to be thawed in ambient air atmosphere (constant temperature during micro-CT acquisition, approximately 20°C) and put on a polyethylene rod holder with a polystyrene home-made holder stuck on it, to avoid samples movement during the acquisition process. Scanning in air affords the highest contrast between the specimen and surrounding medium  (Bouxsein et al. , 2010). Total scan time was 144 minutes per sample (0.
25° step, 1440 images, 6 second exposure, 80 KVp, 6. 5W, microfocus beam 2 µm). The distance between the detector and the source was set to 200 mm and sample-source distance was set to 20 mm, with a constant magnification factor of 13. 3. No dilatation was observed during experiments. Voxel size was 3. 75 µm in each dimension (isometric) for "lowporosity" bone (LPB) and 5 µm for "high-porosity" bone (HPB). For 3D-imaging reconstruction, the cone-beam algorithm of Feldkamp was applied using Phoenix datos|x software (GE, Boston, Massachusetts, USA). The 3D qualitative representation of the porosity (LPB or HPB, see Figure  1 ) was obtained by importing the ". raw" file (16 bits) in the 3D software (VGStudio Max 3. 3 material package, Volume graphics, Heidelberg, Germany). To accurately distinguish voids from bone material, some filters were applied (adaptive gauss and opacity mapping filters) on each volume.
Spherical depth-sensing nanoindentation An ultra nanoindenter (UNHT³ Bio) from ANTON-PAAR, Peseux, Switzerland (Figure  2 ) was used. This system enables testing at penetration depths varying from just a few nanometers to 100 µm, using loads of up to 20 mN. The depth resolution was 0. 006 nm and the load resolution 0. 001 µN. The radius of the spherical indenter (diamond tip) was 100µm. The contact surface disc generated by indentations did not exceed a radius of 30 μm. The load and unload speeds were intentionally kept low (40 mN/min), enabling us to generate bone elasticity as well as reversible deformations, avoiding any interference from neighboring indentations. The tool was adapted to enable testing on biological materials in liquid medium. Raw data curves were obtained using OriginPro 9 software (OriginLab, Northampton, Massachusetts, USA).