dataesr/scientific-paragraphs-categorization huggingface dataset:
Method All articulatory data in this section was collected in the UC Berkeley PhonLab in April and May of 2016. All records are of the second author. Video of the speaker's face was collected using a Canon XF100 HD camcorder. The lingual ultrasound records shown in this section are still frames from videos taken from the approximate acoustic midpoint of the segments examined. Ultrasound video was recorded at a frame rate of 107 Hz using an Ultrasonix SonixTablet and a C9-5/10 microconvex transducer. The transducer was held in place under the chin and approximately perpendicular to the speaker's occlusal plane by an Articulate Instruments stabilization headset  (Scobbie, Wrench & van der Linden 2008). Tongue surface contours were extracted from the ultrasound data using EdgeTrak  (Li, Kambhamettu & Stone 2005) ; comparisons among segments are carried out below using smoothing-spline analysis of variance (SSANOVA) calculated using polar coordinates  (Davidson 2006 , Mielke 2015) , which models the typical position of the tongue surface contour based on multiple input contours (here, in excess of 20 tokens per vowel or consonant type).
Acknowledgements Thanks go to  Keith Johnson  and  Pat Keating , as well as the editor and two anonymous reviewers, for their thoughtful comments. This research was supported by funds made available to the second author by the  Fulbright Visiting Scholar Program ; we gratefully acknowledge  Larry Hyman 's roles as host and organizer of the resulting collaboration. We would also like to thank  Christian DiCanio ,  Jeff Good , and  Malte Münster  for their generous assistance as we worked to make our supplemental recordings.
Hepatic steatosis is associated with poor cardiometabolic health, with de novo lipogenesis (DNL) contributing to hepatic steatosis and subsequent insulin resistance. Hepatic saturated fatty acids (SFA) may be a marker of DNL and are suggested to be most detrimental in contributing to insulin resistance. Here, we show in a cross-sectional study design (ClinicalTrials. gov ID: NCT03211299) that we are able to distinguish the fractions of hepatic SFA, mono-and polyunsaturated fatty acids in healthy and metabolically compromised volunteers using proton magnetic resonance spectroscopy ( 1 H-MRS). DNL is positively associated with SFA fraction and is elevated in patients with non-alcoholic fatty liver and type 2 diabetes. Intriguingly, SFA fraction shows a strong, negative correlation with hepatic insulin sensitivity.
Methods Clinical study design. The study was conducted at Maastricht University Medical Center, the Netherlands, between August 2017 and June 2018, and was approved by the Medical Ethical Committee of Maastricht University Medical Center. Research was performed in accordance with relevant ethical regulations regarding human research participants. The study was registered at clinicaltrials. gov with identifier NCT03211299. Participants. All participants recruited for this study provided written informed consent. Twenty-two healthy overweight/obese participants (BMI 27-35 kg/m 2 ), aged 45-70 years with a large range in liver fat content (0. 9-38. 4%) were recruited for this study. Female study participants were postmenopausal. Exclusion criteria were engagement in exercise for more than 2 h per week, unstable body weight (weight loss or gain more than 3 kg in 3 months preceding enrollment), alcohol consumption more than 2 units per day, smoking more than 5 cigarettes per day, contra-indication for MRI, use of anti-coagulants, use of other medication known to interfere with the outcome parameters, diabetes, or other active disease.
All 1 H-MRS experiments were performed on a 3T MR system (Achieva 3T-X Philips Healthcare, Best, Netherlands) by using a 32-channel sense cardiac/torso coil (Philips Healthcare, Best, Netherlands). All spectra were obtained by using a STEAM sequence  29  with the following parameters; repetition time (TR) 4500 ms/echo time (TE) 20 ms/mixing time (TM) 16 ms, spectral bandwidth 2000 Hz and data points 2048. For the in vivo hepatic lipid spectra VAPOR water suppression  30  was applied and an additional water reference scan was obtained. The number of averages was 16 for the phantom experiments and in adipose tissue and 128 for the in vivo hepatic spectra. We used a voxel size of 30 × 30 × 30 mm for the hepatic and 15 × 15 × 15 mm for the adipose tissue measurements. All obtained lipid spectra were post-processed in a home-written MATLAB (MATLAB 2014b, The MathWorks, Inc.
In a second setup step, we acquired spectra from the different oils on our clinical 3T scanner. Eddy current correction was applied based on an additional water reference scan with an identical experimental setup. The oil spectra were fitted with the developed Matlab algorithm. To this end, using the basis set from the HR spectra, the time domain signal was simulated. The amplitudes and relative frequency shifts of the individual peaks were updated iteratively. In each step the difference between the simulated spectrum and the acquired spectrum was minimized in the frequency domain. Next to these individual parameters, also the Gaussian line broadening, the Lorentzian line broadening, the zero order phase, an overall frequency shift and the baseline offset were automatically updated, affecting all the peaks in an identical fashion.
The nanointerface of the mass spectrometer was heated to 60 °C and the measurements was made using a scan speed of 200 Da/s. The neutral loss scans were cycled and in total 50 cycles were acquired for each neutral loss scan (one neutral loss for each fatty acid). The data was processed using the LipidView 1. 2 software (Sciex, Concord, Canada) and the most abundant signal intensities from the most commonly found triglyceride species were used to calculate the abundance and composition of the different triglycerides (Supplementary Tables  2  and 3 ). Quantification was made using a one point calibration against glyceryl-d 5 -hexadecanoate (CDN isotopes, Quebec, Canada), which was added to the infusion solvent. Hyperinsulinemic-euglycemic clamp. A two-step hyperinsulinemic-euglycemic clamp was performed to assess hepatic IS using the low-dose phase (10 mU/m 2 / min) (healthy overweight/obese participants: n = 21).
Results are expressed as mean ± SEM for group comparisons. Population characteristics are expressed as mean ± SD. Continuous variables were tested for normality. Two-sided Pearson correlation was performed to identify correlations between variables. For non-normally distributed data two-sided Spearman correlation was performed. Group comparisons were assessed by oneway ANOVA. For non-normally distributed data Kruskal-Wallis analyses was performed to compare groups. In case of significant group differences in the group comparisons, post-hoc analyses were performed using Bonferroni correction to test which groups were significantly different. A p-value < 0. 05 was considered statistically significant. Statistical analyses were performed using SPSS 23. 0 for Mac OS.
Acknowledgements This research was in part financed by the  Ministry of Economic Affairs and Climate Policy  by means of the PPP Allowance made available by the  Top Sector Life Sciences & Health  to stimulate public-private partnerships and by  Unilever R&D Wageningen. We acknowledge the support from the  Netherlands Cardiovascular Research Initiative : an initiative with support of the  Dutch Heart Foundation  ( CVON2014-02 ENERGISE ). L. L. is a recipient of a veni grant from  ZonMW  ( 016. veni. 188. 036 ) and a junior fellowship ( 2017. 81. 004 ) from the  Diabetes Fonds (Dutch Diabetes Research Foundation ). B. S. is a recipient of an  Advanced ERC Grant  ( 694717 ). V. B. S. -H. is a recipient of an  ERC starting grant  (grant no. 759161  'MRS in diabetes').
Selected miRNAs were evaluated in a cohort of WT mice (n > 20 per group) to assess sex influence in intestinal miRNAs expression in the small intestine in response to dietary lipids. A large variability was found when intestinal miRNAs expression data was analysed without gender separation (data not shown). However, when the analysis was divided by gender, a third of miRNAs (miR-218-2-3p, -544-3p, -129-2-3p and -138-1-3p) showed statistically significant differences of expression between male and female controls (Fig. 2b ). In addition, significant differences were seen for miR-218-2-3p, -208b-3p, -129-2-3p and -138-1-3p in female mice fed with a HFD compared to controls, whereas miRNAs levels were not significantly affected in males. Overall, results suggest that, in response to a HFD, intestinal miRNAs levels are influenced by animal gender and that the changes in the expression of certain miRNAs are enhanced in females.
The screening for intestinal miRNAs regulated by dietary lipid challenges was performed using miRNome panels (641 mature miRNAs) Version 3 (Exiqon). Relative expression was calculated using GenEx software (https ://multi d. se/genex /, MultiD Analyses) for data pre-processing and analysis. The common miRNAs among the different experimental studies were represented in a Venn diagram  57. Relative quantification of selected miRNAs was performed using specific primer for each miRNA (Isogen). Mature miRNA primer sequences were obtained from the miRBase (www. mirba se. org). Relative expression levels were calculated with the 2 -ΔΔCt method 58 using RNU1A1, RNU6 and RNU43 to normalization. Lipid analysis. Plasma lipid and lipoprotein profiles. Total plasma triglycerides and cholesterol concentrations were analyzed with a microtiter assay using Triglycerides-LQ GPO-POD and Cholesterol-LQ CHOD-POD (Spinreact) commercial kits.
Statistical analysis. Results were expressed as mean ± standard error of the mean and statistically significant differences between groups were assessed using student's T-test, one-way ANOVA or two-way ANOVA depending on the experimental setting. p < 0. 05 was considered as statistically significant. All statistical analyses were performed using GraphPad Prism software (V. 7, GraphPad Software Inc, San Diego, https ://www. graph pad. com/scien tific -softw are/prism /), except for the screening assay (GenEx software). Bioinformatic approach. To predict miRNA targets, the list of 12 selected miRNAs was imported into the miRWalk database  62, 63. Then, the validated interactions with an entry in miRTarBase (results from 3UTR and binding probability > 0. 95) were selected for a total of 180 different genes.
Acknowledgements This research was funded by grants from the  Spanish "Agencia Estatal de Investigación" and European FEDER Funds  to AD, MJL and OB ( AGL2016-78922-R ); by the  Fundación Ramón Areces  ( CIVP18A3888 ) to AD,  JG-Z, JTC, MCC. Also supported by  CIBER de Fisiopatología de la Obesidad y Nutrición (CIBERObn)  and  RTI2018-098113-B-100  ( Plan Estatal de Investigación Cientifica y Tecnica y de Innovación 2017-2020 ,  Ministerio de Ciencia, Innovación y Universidades, Spain , and the  European Development Regional Fund (ERDF) ) to DGC. CIBERObn is an initiative of ISCIII, Spain. MCLH, LdPA and MBRR were recipients of contracts from the  Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid ,  Fondo Social Europeo , and  Iniciativa de Empleo Juvenil YEI  ( PEJD-2016/BIO-2781 ,  PEJD-2017-PRE/BIO-5100  and  PEJD-2018-POST/ BIO-8933 , respectively).
txt, parameters-ESP. txt, parameters-HIR. txt, and parameters-ESP. txt. Initial configuration i. e. , coordinates of M-Lanr and water molecules are also provided in the xyz. txt file. Usually, partial charges of the AMBER force-field correspond to the averages obtained from quantum calculations based on reference molecules to obtain the "universal" parameters. Nowadays, computational resources allow us to carry out more accurate quantum calculations to extract more realistic charges. In this work, partial charges have been recalculated using DFT calculations, whereas the Lennard-Jones and the intramolecular AMBER parameters were conserved. Four methods have been compared, the CHELPG approach (CHarges from ELectrostatic Potentials using a grid-based method)  32  from Gaussian 33 software, the ESP (electrostatic potential fitting),  34  the Hirshfeld  35  and the Mulliken  36  methods from the Dmol3 quantum package.
Face-toface interviews were conducted with trained staff (mainly physicians and psychologists). With the aim of standardization, the interviewers were trained (including a theoretically grounded instruction, coaching, supervised practice, and ongoing supervision) to conduct interviews via members of the study team. Further details have been published elsewhere  [17]. Among the 3327 individuals, n = 544 individuals participated in FU wave 9 and provided data on both driving behavior and HRQOL. The most important reasons for drop off were that patients died or refused participation. The AgeCoDe as well as the AgeQualiDe study have been approved by the ethics committees of all participating study centers and comply with the ethical standards of the Declaration of Helsinki. Prior to participation, all participants gave written informed consent.
Acknowledgements We want to thank both all participating patients and their general practitioners for their good collaboration. Members of the  AgeCoDe & AgeQualiDe Study Group :  Wolfgang Maier  (Principal Investigator),  Martin Scherer  (Principal Investigator),  Steffi G. Riedel-Heller  (Principal Investigator),  Heinz-Harald Abholz ,  Christian Brettschneider ,  Cadja Bachmann ,  Horst Bickel ,  Wolfgang Blank ,  Hendrik van den Bussche ,  Sandra Eifflaender-Gorfer ,  Marion Eisele ,  Annette Ernst ,  Angela Fuchs ,  André Hajek ,  Kathrin Heser ,  Frank Jessen ,  Hanna Kaduszkiewicz ,  Teresa Kaufeler ,  Mirjam Köhler ,  Hans-Helmut König ,  Alexander Koppara ,  Diana Lubisch ,  Tobias Luck ,  Dagmar Lühmann ,  Melanie Luppa ,  Tina Mallon ,  Manfred Mayer ,  Edelgard Mösch ,  Michael Pentzek ,  Jana Prokein ,  Alfredo Ramirez ,  Susanne Röhr ,  Anna Schumacher ,  Janine Stein ,  Susanne Steinmann ,  Franziska Tebarth ,  Hendrik van den Bussche  (Principal Investigator 2002-2011),  Carolin van der Leeden ,  Michael Wagner ,  Klaus Weckbecker ,  Dagmar Weeg ,  Jochen Werle ,  Siegfried Weyerer ,  Birgitt Wiese ,  Steffen Wolfsgruber , and  Thomas Zimmermann.
Measure of in vivo GFP fluorescence During the exposure, female fish from each condition were anesthetized with 200 mg/L MS222 (Sigma-Aldrich, Lyon, France, CAS 886-86-2) and then photographed using an IVIS Lumina II fluorescence imaging system (Perkin Elmer, Courtaboeuf, France). All the pictures taken were made under identical conditions (fish orientation, zoom, binning, excitation filter (465 nm) and emission filters (520, 540, 560, 580 nm)). The Living Image software (Caliper Life Sciences, Hopkinton, USA) was used to apply spectral unmixing on the images captured. This enabled the discrimination between spectral signatures and the extraction of the GFP signal from the tissue autofluorescence. GFP fluorescence quantification was then expressed as the Total Radiant Efficiency (number of photons per seconde normalized by the excitation light intensity, [p/s]/[µW/cm 2 ]) divided by the gonad area (cm 2 ).
The reaction was stopped with the addition of 37. 5 µL of 1M phosphoric acid after 30 min. The plates were then read at 450 nm on a Synergy™ H4 Hybrid Multi-Mode Microplate Reader (Biotek™, USA). The raw data were analyzed on the BioTek™ GEN5 software. For the whole blood samples, this ELISA exerted limits of detection and quantification of 75 ng/ml and 155 ng/ml respectively.
3. 1. PCZ concentrations in water To determine the actual concentrations to which zebrafish were exposed, PCZ concentrations were measured by LC/MS/MS in water of aquaria and in the water delivered to the aquaria by the flow-through system of exposure. The measured data are reported in Table  1. No PCZ was quantified in the control conditions. Table  1 : Nominal and measured concentrations of PCZ in water at different sampling times of the exposure. Data are mean ± SEM. n=2 for each condition. LOQ: Limit of quantification (9 ng/L). "Needle" indicates the water sampled at the outlet of the needle supplying the aquarium with water.
In fact, dead cells with Ant-PIm in the nucleus was observed also after our experiments (data not shown). Concerning the light induced toxicity, the initial drop in the Ant-PHEA curve during the first 1-3 min of light exposure (Figure  4 ) is often observed in PDT-cell survival studies  [29]  and, as reported previously, also on a well-studied bladder cancer cell line, AY27, after TPCS 2a -based PDT  [31]. The dark toxicity (0 min of light) recorded for Ant-PIm was initially high (38%) but, together with the blue-light-induced cell death of 0-3 min, the repairing mechanisms work for this short period. The combination of the photosensitizer Ant-PIm and longer illumination periods (more than 3 min) resulted in a cell death that could not be repaired, and the cell survival dropped to almost zero after 20 min of illumination.
After a post incubation period (24 h, 37 • C, 5% CO 2 ) from illumination, the MTT proliferation assay was performed  [36]  as follows: the culture medium was removed and the cells were incubated in MTT-solution (0. 5 mg/mL, 1 h, 37 • C, 5% CO 2 (Sigma-Aldrich, St. Louis, MO, USA) before replacing by isopropanol (2 mL) and placing on a plate shaker (30 min, 80 rpm). The important and modified step, as described by Gederaas et al. [31] , is the removal of dead cells by centrifuging (5 min, 1500 rpm). The absorbance (595 nm) was measured using a Shimadzu UV-1700 spectrophotometer. The obtained data were processed and compared to the untreated cells. The cells were illuminated with blue light from below by using the LumiSource ® from PCI Biotech AS, Oslo, Norway, consisting of 4 Osram tubes (emission maximum = 435 nm, 13 mW/cm 2 ).
Mitotracker deep red was excited using 633 nm (He-Ne laser) and detected with LP 650 filter. The excitation period during the images was about 5 s, with little change for the re-localization of the compound, and the imaging was performed twice in 2-3 biological replicates, recorded at two different occasions. In our experience, the imaging of living cells is safer than confocal studies on fixed cells. All emissions where detected through a 1 Airy Unit pinhole. The laser power, detector gain, and offset were chosen to minimize auto-fluorescence in the control samples where no photosensitizer was added. For further processing, 512 by 512-pixel images with an 8 bit dynamic range was recorded. The procedure for the colocalization assessment of CHO-K1 cells using the chromophores Ant-PIm and Ant-PHEA, together with the markers Lysotracker red, Draq 5, and Mitotracker deep red, was based on the algorithms and software analysis developed in-house using the Matlab (Mathworks) mathematics software package.
YAP is active in human basal breast cancers and predicts patient survival The analysis of human primary patient proteomic data available from Mertins et al. 22  revealed high expression of the YAP signature  40  in basal breast cancer, in contrast to other subgroups of breast cancers (Fig. 6a ). qPCR of YAP target genes CTGF, IGFBP3 and ANKRD1  40  in spheres of human basal breast cancer cell lines BT549, MDA231 and SUM1315 confirmed elevated YAP activity compared to the luminal cell lines MCF7, BT474 and T47D (Fig. 6b , Supplementary Fig. 6a ). Online datasets available from Gene expression-based Outcome for Breast cancer Online (GoBo)  67  confirmed a significantly higher expression of YAP in tumours of human patients with basal breast cancer than in tumours of patients with luminal breast cancer (Supplementary Fig.
Fluorescence-Activated Cell Sorting (FACS) Single cell suspensions from dissociated tumours were re-suspended at 10,000 cells/μl and incubated with conjugated primary antibodies at 4°C for 15mins. Cells were then washed x3 in DPBS and incubated with 7AAD (5μl/10 6 cells) at room temperature for 5 minutes to stain dead/dying cells. Cells were sorted using the FACSAria II or III (BD Biosciences) or analysed using LSRFortessa (BD Biosciences). Compensation and unstained controls were carried out for every FACS experiment as required. Data were analysed using FLowJo Analysis Software.
For analysis, the MaxQuant software package version 1. 6. 10. 43  82, 83  was used. TMT6 reporter ion quantitation was turned on using a PIF setting of 0. 5. Variable modifications included Met-oxidation, acetylated N-termini and deamidation of Asn and Gln for proteomics analysis. For phosphoproteomics analysis, deamidation was replaced by phosphorylation on Ser, Thr and Tyr. An FDR of 0. 01 was applied for peptides, sites and proteins, and the Andromeda search was performed using a mouse Uniprot database (July 2018, including isoforms). Further analysis was done using R and the Protigy package (https://github. com/broadinstitute/protigy). Protein groups were filtered for proteins that have been identified by at least one unique peptide and that had valid TMT reporter ion intensities across all samples.
The phosphoproteome was also filtered for sites containing valid values for all samples. For both analyses, two-sample moderated t-tests (limma package  84 )  comparing the two groups were calculated using the log2-transformed and median-MAD normalised TMT6 corrected reporter ion intensities, followed by a Benjamini-Hochberg (BH) p-value correction. Heatmaps of selected significant proteins or phosphosites according to BH-adjusted p-value were generated using the pheatmap package  85  employing hierarchical clustering based on Euclidean distance. For annotation of gene lists derived from a human proteome, i. e. Zanconato and collegues (2016), genes were converted into mouse orthologs using biomaRt  86  and manual curation.
Nanostring PanCancer Pathways panel was purchased from Nanostring including additional custom gene set for selected YAP and β-catenin target genes. 70ng of RNA was hybridised for 16hours at 65°C. Hybridised RNA was loaded onto and analysed using nCounter SPRINT Profiler. Data were analysed using nSolver software. Heatmaps were generated using nSolver software from normalised data using Pearson Correlation. Genes included were manually filtered using available gene lists  40, 45.
Kaplan-Meier and GOBO analysis Relapse-free survival of breast cancer patients was analysed using Kaplan-Meier Plotter online software (http://kmplot. com). Trichotomization was set to Q1 vs Q4. Expression analysis of YAP in breast cancer cell lines and human datasets were generated using GOBO online software (http://co. bmc. lu. se/gobo). The provided CPTAC dataset was filtered for samples that passed the QC criteria. A two-sample moderated t-test was applied between samples that have been assigned to basal vs. all other subtypes combined. Selected significant proteins from Zanconato et al. 40 Figure Legends C8-A131 BH-A18Q BH-A0AV A2-A0CM AR-A0U4 AO-A0J6 A7-A0CE D8-A142 AN-A0FL AO-A12F AN-A0AL E2-A158 C8-A12V A2-A0D2 C8-A131 C8-A134 AO-A0JL A2-A0YM A2-A0SX AO-A12D AO-A12B C8-A130 C8-A138 E2-A154 C8-A12L A2-A0EX AO-A12D AN-A04A C8-A12T A8-A06Z BH-A18U A2-A0EQ AO-A0J9 AR-A1AP AN-A0FK A7-A13F BH-A0E1 A2-A0YC AO-A0JC A8-A08Z AR-A0TX A8-A076 AO-A126 BH-A0C1 A2-A0EY AR-A1AW AR-A1AV C8-A135 A2-A0EV AN-A0AM BH-A0DG AR-A0TV C8-A12Z AO-A0JJ AO-A0JE AN-A0AJ A7-A0CJ A8-A079 A2-A0T3 A2-A0YD AR-A0TR AO-A03O AO-A12E A8-A06N A2-A0YG BH-A18N A2-A0T6 E2-A15A AO-A0JM C8-A12U AR-A1AS A8-A09G A2-A0YF BH-A0DD BH-A0E9 AR-A0TT AO-A12B A2-A0SW BH-A0BV BH-A0C7.
Acknowledgements We thank  Russ Hodge  of the  MDC  for improving our manuscript style,  Dr. Hans-Peter Rahn  and the  FACS Core Facility of the MDC  for their expertise,  Dr. Anca Margineanu  and the  Confocal Microscopy Core Facility of the MDC  for the support with microscopy, and  Dr. Diana Behrens  at  EPO-Buch  for supervising the in vivo drug treatments.