dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The authors are grateful to  Katie Heath ,  Joseph Feduska ,  KaLia Burnette , and  Miranda Chavez  for critical reading of the manuscript. Research reported in this publication was supported by the  University of Alabama at Birmingham Heflin Center Genomics Core  ( P30 CA013148 ). This work was supported by the following  NIH  grant awards:  R01 DK099550  (to HMT),  R01 DK127497  (to HMT),  R56 DK126456  (to HMT),  DP3 DK097605  (to AMG and YGC),  R01 DK107541  (to YGC),  R01 DK121747  (to YGC),  T32 GM109780  (to SIB),  T32 AI007051  (to SIB),  F31 DK130551  (to SIB),  T32 GM109780  (to JMB),  T32 GM008111  (to JMB), and  T32 AI007051  (to JPT). Parts of this article were presented in abstract form at the 7th Annual Southeastern Immunology Symposium, Birmingham, Alabama, USA June 2018; the Immunology of Diabetes Society Congress, Westminster, London, United Kingdom, October 2018; the American Association of Immunology, San Diego, California, USA, May 2019 and virtually 2021; the 79th Scientific Sessions of the American Diabetes Association, San Francisco, California, USA, June 2019; and the 80th Scientific Sessions of the American Diabetes Association, June 2020, and the 81st Scientific Sessions of the American Diabetes Association, June 2021.
Proteins were resolved by SDS-PAGE (Invitrogen mini gels system) and transferred onto nitrocellulose membranes (Invitrogen iBlot 2) before blocking with 10% evaporated milk in PBS 0. 2% Tween and incubation with the corresponding primary and HRP-conjugated secondary antibodies, all diluted in PBS 0. 2% Tween 10% evaporated milk at concentrations recommended by manufacturer. Signals were visualized using the Amersham ECL, Pierce ECL Plus or SuperSignal West Pico Plus ECL detection reagents and imaged using Invitrogen iBright CL1500 imager. Red Ponceau staining was used before immunoblotting to check for transfer efficiency. All blots were probed for β-actin as a loading control. When indicated, Western Blot quantification was performed using Fiji/ImageJ software. Antibodies. For Western blots, primary and HRP-conjugated secondary antibodies were obtained 1) from Cell Signaling Technology: anti-β-Actin (4970), anti-Akt (2920), anti-Phospho-Akt S473 (4060), anti-AMPK (2793), anti-Phospho-AMPK T172 (50081), anti-Cofilin S3 (5175), anti-Phospho-Cofilin (3313), anti-p70 S6K (34475), anti-Phospho-S6K T389 (9205), anti-mTOR (2972), anti-Phospho-mTOR S2448 (2971), anti-α-Smooth Muscle Actin (SMA; 56856), anti-STAT3 (12640), anti-Phospho-STAT3 Y705 (9145), anti-Phospho-STAT5 Y694 (4322), HRP-conjugated anti-Rabbit IgG (7074), and HRPconjugated anti-Mouse IgG (7076); 2) from Sigma Aldrich: anti-ROCK1 (HPA007567) and anti-ROCK2 (HPA007459); or 3) from eBioscience: CD185 (CXCR5) (12-1859-42), CD279 (PD-1) (11-9969-42), Foxp3 (12-4777-42), CD4 (11-0049-42) and Fixable Viability Dye (65-0866-14).
Participants The study was preregistered on ClinicalTrials. gov (Identifier: NCT03505437). Female participants with a fear of spiders and cockroaches were recruited via various advertisements (e. g. , social media groups and online bulletin boards). Participants with a history of a mental disorder, other than a specific fear for spiders and cockroaches, were not invited to the study. Other exclusion criteria involved the presence of neurological and/or endocrine disorders, pregnancy, current pharmacological treatment, and current smoking (> than five cigarettes per month). Finally, participants with a body mass index (BMI) greater than 27 or smaller than 19 kg/m 2 and shift-workers were excluded. A total of 104 individuals took part in a pre-experimental telephone screening to check for inclusion/exclusion criteria.
Statistical analyses Statistical analyses were performed with SPSS Statistics for Macintosh, Version 27. 0 (Armonk, NY: IBM Corp. ). Pre-exposure participant characteristics and stress ratings were compared using a series of two-way ANOVAs with the between-subjects factors "Stress" (Stress vs. No-Stress) and "OC" (OC vs. FC). Blood pressure as well as salivary cortisol were analyzed with ANOVAs with the within-subjects factor "Time" (salivary cortisol: baseline vs. 25 min after SECPT; blood pressure: measurements at baseline, during stress induction vs. after the SECPT) and the between-subjects factors "Stress" and "OC". Exposureinduced changes in outcome measures (i. e. , BAT score, subjective fear during the BAT, questionnaires) were also analyzed with two-way ANOVAs with three levels of the within-subjects factor "Time" (Day 1 Pre, Day 2 Post, vs.
Acknowledgements The study was supported by grants from the  Deutsche Forschungsgemeinschaft (German Research Foundation ;  SFB 874 , project  A1  to M. T. ; SFB 1280  Extinction Learning  project  SFB1280  -project number  316803389 , Project  A13  awarded to A. Z. and J. M. , project  A09  to C. J. M. and O. T. W. ; Heisenberg Grant  ZL 59 4-1  and  ZL 59 5-1  awarded to A. Z. ). The funders had no role in study design, data collection and analysis, preparation of the manuscript and decision to publish.
BH3 profiling data To uncover any potential effects of Opa1 perturbations on the apoptosis pathway, we used BH3 profiling to compare mitochondrial responses to pro-apoptotic stimuli across the cell lines. BH3 profiling quantifies the percentage of cells that release cytochrome c from their mitochondria, the key commitment to WT controls as indicated by decreased sensitivity to the BIM BH3 peptide, which can inhibit all prosurvival BCL-2 family proteins and also directly activate BAX and BAK (Fig. 5a ). We also used a chemosensitivity assay to measure apoptotic sensitivity by quantifying markers of apoptosis (in this case, Annexin V positivity) after treatment of cultured cells with common apoptosis-inducing drugs. Equal doses of the BIM BH3 peptide induced less cytochrome c release from mitochondria in Opa1-KO MEFs than WT MEFs, indicated that stronger pro-death stimuli are required to induce apoptosis in cells lacking Opa1 (Fig.
Cryo-electron tomography All imaging was performed on a FEI Titan Krios (TFS) transmission electron microscope operated at 300KeV equipped with a Gatan BioQuantum K3 energy filter (20eV zero-loss filtering and a Gatan K3 direct electron detector. Prior acquisition, a full K3 gain reference was acquired, and ZLP and BioQuantum energy filter were finely tuned. The nominal magnification for data collection was 33,000x giving a calibrated 4K pixel size of 2. 758. Data collection was performed in nanoprobe mode using SerialEM  (Mastronarde, 2003)  or TFS Tomography 6 software. The tilt range varied depending on the lamella, but generally was from -70 to 70 in 2 steps following the dose-symmetric scheme (Hagen et al,.
Acknowledgments We are grateful to  Phat Vinh Dip , and  Edward Brignole  at the  MIT. nano cryo-EM facility  and  Kang Song  and  Chen Xu  at the  University of Massachusetts cryo-EM facility  for providing access to the cryo-EM microscopes and for all their help, advice, and maintenance of cryo-EM equipment. Electron microscopy was performed in the Microscopy Core of the  Center for Systems Biology/Program in Membrane Biology , which is partially supported by an  Inflammatory Bowel Disease Grant   DK043351  and a  Boston Area Diabetes and Endocrinology Research Center (BADERC)  Award  DK057521. We thank  Connor Tou  for assistance cloning guide RNAs. Grants/funding: P. P. N. was supported by the  Swiss National Science Foundation (SNF)   Early Postdoc. Mobility   P2BSP3_188112  and  Postdoc.
Senescence Detection in ECFCs The SA-β-gal is an enzyme which hydrolyzes the glycosylic bonds in X-Gal, producing an easily recognizable blue reaction product. Its optimum activity is reached at pH 6. 0, which is a characteristic of senescent cells. The SA-β-gal activity was evaluated in the CTRL ± R (n = 4) and IUGR ± R (n = 4) ECFCs using a senescence detection kit (Cell Signaling Technology, Danvers, MA, USA) according to the manufacturer's instructions. The SA-β-gal-positive cells (blue staining) were normalized as a percentage of the total number of cells. Each experiment was performed in duplicate. Using an inverted microscope (Eclipse Ti2 Series), the pictures at ×20 magnification were blindly acquired and analyzed with ImageJ software (Java 1. 8. 0_112) by the same examiner (E. G. )  [10, 11].
The incubations with anti-mouse or anti-rabbit secondary antibodies (1/2000; Cell Signaling) were performed for 2 h at room temperature in TBS-tween 1%-BSA 3%. The antibodies were visualized using an enhanced chemiluminescence Western blotting substrate (Life Technologies). A G-BOX Imaging System (GeneSys, Syngene, Cambridge, UK) was used to detect specific bands, and the optical density of each band was measured using specific software (GeneTools 4. 03. 05. 0, Syngene) for all blots. For technical reasons, it was not possible to load the CTRL and IUGR on the same blot. For IUGR-ECFCs, we conducted the Western blotting for Sirtuin-1 and Cu/Zn SOD on the same membrane to reduce the biological material consumption.
Acknowledgments: We are grateful to  Jean-Pierre Guignard  and  AIRG-Switzerland  for their financial support. We also extend our gratitude for the technical assistance to the students from the  School of Health Sciences (HESAV; Lausanne, Switzerland ),  Steeve Menétrey  from the  Neonatal Research Laboratory (University of Lausanne, Switzerland ), and especially  John Prior  and  David Viertl  from the  Department of Nuclear Medicine and Molecular Imaging  ( University of Lausanne, Switzerland ) for their unfailing support. We would like to extend our warmest thanks to  Umberto Simeoni  ( University of Lausanne ) for his invaluable support over the years we have spent together, and we dedicate this manuscript to him.
Typical minimum detection limits are 0. 1, 1. 6, 0. 1, 8. 5, 2. 3, 1. 8, 0. 8, 0. 6, 0. 05, 0. 3, 0. 07, and 0. 03 µg/g for Li, Na, Mg, P, K, Cr, Mn, Zn, Sr, Ba, Pb, and U, respectively. Internal instrumental errors are close to 0. 2, 160, 1030, 30, 5, 0. 7, 0. 4, 0. 4, 90, 0. 4,0. 05, and 0. 02 µg/g, respectively. The mean calcium abundance measured by EMP for a series of coral samples was used as an internal standard. A typical signal acquisition consisted of collecting a background signal for 30 s followed by laser firing for 70 s. Trace-element reductions were made with the Glitter software  (van Achterbergh et al. , 2001). The long firing time (70 s) allowed to check (1) the stability of the signal during the measure (flat plateau) and (  2 ) the presence of voids or inclusions during firing.
Four out of 38 analyses performed have Li contents slightly lower than 3 µg/g, two analyses have lower U content than 0. 08 µg/g, and there is no analysis with both Li and U lower than the above-mentioned critical values (Li < 3 µg/g; U < 0. 08 µg/g). As a complementary processing of the data, a PCA analysis was performed, combining the  Vielzeuf et al. (2018)  dataset and our measurements. These results further indicate that the chemical compositions of the 3-4-year-old  skeletons that we analyzed do not correspond to compositions characteristic of the annular zone (see Supplementary Material 1).
We found a temporal window of vulnerability (0-2 years), during which C. rubrum's recruits are small, lack a rigid axial skeleton and are not firmly attached to the substrate. This insight will be pivotal in developing active restoration plans based on sexual reproduction. for the technical support and the aquarium system set up, B. Hesse, JC Roca, and the boat crew for the support during SCUBA diving operations. A special thanks to Prof G. Ardizzone for his support during the whole master thesis project. We acknowledge SOLEIL synchrotron for financial support concerning inhouse beamtime. ANATOMIX is an Equipment of Excellence (EQUIPEX) funded by the Investments for the Future program of the French National Research Agency (ANR), project NanoimagesX, grant no. ANR-11-EQPX-0031.
Differential cross-section measurements of Zγ production in association with hadronic jets are presented, using the full 139 fb -1 dataset of √ s = 13 TeV proton-proton collisions collected by the ATLAS detector during Run 2 of the LHC. Distributions are measured using events in which the Z boson decays leptonically and the photon is usually radiated from an initial-state quark. Measurements are made in both one and two observables, including those sensitive to the hard scattering in the event and others which probe additional soft and collinear radiation. Different Standard Model predictions, from both parton-shower Monte Carlo simulation and fixed-order QCD calculations, are compared with the measurements. In general, good agreement is observed between data and predictions from MATRIX and MiNNLO PS , as well as next-to-leading-order predictions from MadGraph5_aMC@NLO and Sherpa.
The measurements are performed differentially in either one or two observables. The analysis uses the full dataset of protonproton (pp) collisions at a centre-of-mass energy of √ s = 13 TeV recorded by the ATLAS detector during Run 2 (2015-2018) of the LHC. The results presented here build upon a previous analysis performed by ATLAS  [14] , which focused on more inclusive observables. The measurements extend the published results by including the hadronic activity associated with the Zγ system and by measuring double-differential cross sections. As in the previous analysis, only Z bosons decaying into pairs of charged leptons ( + -, with = e, µ) are considered. This restriction makes it easier to fully reconstruct the final state with high resolution, and also provides a relatively large cross section with little background.
They are reconstructed and analysed by the same program chain as the data. Table  1  gives an overview of the generators used in this analysis, their precision in QCD, and the PDF set used. Additional signal theory predictions at NNLO matched to the parton shower  [24]  were calculated using Powheg Box  [59]. They provide a prediction consistently matched to the parton shower, including spin correlation, intereference and off-shell effects, using the MiNNLO PS  [23]  approach. These predictions are compared with the data in section 9. Photon infrared-safe predictions were obtained by imposing the same Frixione isolation parameter values as for the Sherpa 2. 2. 11 sample. The central renormalisation and factorisation scales were set to m γ. Events were generated using the NNPDF3. 0nnlo PDF set with the strong coupling constant taken as α s (m Z ) = 0.
118. Fixed-order QCD calculations are also considered by using the program MATRIX  [25, 26] , which relies on OpenLoops  [54]  for all amplitudes up to the one-loop level, and on other dedicated calculations  [55, [60] [61] [62]. The MATRIX predictions are obtained with CT14nnlo PDFs  [63]. Frixione isolation parameter values are the same as for the Sherpa 2. 2. 11 sample. The measurements presented in this paper are obtained at particle level, where leptons are corrected for collinear photon radiation by adding to the four-momentum of the lepton the four-momenta of the photons within ∆R = 0. 1 of given lepton. This procedure is called dressing. The MATRIX predictions are obtained instead at parton level, since no.
Event selection Selected events must have at least one reconstructed vertex with at least two associated tracks with p T > 500 MeV. In events with multiple vertices, the one with the highest p 2 T of associated tracks is selected as the primary vertex. Candidate events must also pass at least one unprescaled single-muon or single-electron trigger  [64, 65]. For data recorded in 2015, the lowest p T threshold was 24 GeV for the electron trigger, and 20 GeV for the muon trigger. For data recorded during the period 2016-2018, these thresholds were both raised to 26 GeV and tighter isolation criteria were applied, to compensate for the increase in instantaneous luminosity. Triggers with a higher p T threshold, but looser isolation, are also used because they increase the total trigger efficiency.
JHEP07(2023)072 modelled by the predictions, except for the last bins in the case of MiNNLO PS , where an underestimation is observed. The MATRIX prediction also shows good agreement, with a small overestimation, although within systematic uncertainties, in the last bins. Figure  8   The ∆φ(jet, γ) distribution is important for PS corrections in QCD predictions in phasespace regions with soft QCD emission  [24]. The measurement shows a preference for events in which the photon and the leading jet are back-to-back. The ∆φ(jet, γ) observable is well modelled by all the predictions, except in the very first bin of the MATRIX prediction. The p γj T observable is well modelled within uncertainties by both Sherpa samples and MadGraph5_aMC@NLO, whereas the MiNNLO PS and MATRIX predictions show some deviation from the data distributions.
The p γj T distributions in different regions of p γ T (figure  12 ) are well modelled by Sherpa and MadGraph5_aMC@NLO, while the MiNNLO PS predictions underestimate the data for p γ T > 75 GeV. The MATRIX prediction exhibits a softer spectrum than the other predictions. In summary, the Sherpa and MadGraph5_aMC@NLO predictions describe the data well, especially for observables involving jets, although Sherpa underestimates the measured total cross section. The MiNNLO PS and MATRIX predictions give an adequate description of the measurements, but some deviations from the data are observed at high jet multiplicity. Error bands on the data points show the statistical uncertainty, while the grey area shows the total uncertainty in the unfolded result. Measured cross sections are compared with SM predictions from event generators at particle level: Sherpa 2.
2. 4, Sherpa 2. 2. 11, MadGraph5_aMC@NLO+Pythia 8 (MG5_aMC+Pythia8 in the legend), and MiNNLO PS. Fixed-order calculation results from MATRIX NNLO are also shown. Dashed bands represent the statistical uncertainty and theoretical uncertainty (PDF and scale variations). The bottom panels show the ratio of the SM prediction to the measured cross section. Error bands on the data points show the statistical uncertainty, while the grey area shows the total uncertainty in the unfolded result. Measured cross sections are compared with SM predictions from event generators at particle level: Sherpa 2. 2. 4, Sherpa 2. 2. 11, MadGraph5_aMC@NLO+Pythia 8 (MG5_aMC+Pythia8 in the legend), and MiNNLO PS. Fixed-order calculation results from MATRIX NNLO are also shown. Dashed bands represent the statistical uncertainty and theoretical uncertainty (PDF and scale variations).
JHEP07(2023)072 10 Conclusion Measurements of several differential cross sections for Zγ production in association with jets are presented, in the final state where the Z boson decays into two opposite-sign sameflavour leptons (e + e -or µ + µ -). The measurements are performed in a fiducial phase space enhanced in ISR photons, where the sum of the invariant mass of the leptons and the invariant mass of the leptons and the photon is greater than twice the mass of the Z boson. The measurements are performed using data collected by the ATLAS detector from LHC pp collisions at √ s = 13 TeV, using a total integrated luminosity of 139 fb -1. Differential cross sections are measured as functions of the kinematics of jets, leptons, and photons. Both one-dimensional and two-dimensional distributions are chosen to enhance the separation of hard-scatter effects from soft collinear radiation.
Acknowledgments We thank  CERN  for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of  ANPCyT , Argentina; YerPhI, Armenia;  ARC, Australia ;  BMWFW  and  FWF , Austria; ANAS, Azerbaijan;  CNPq  and  FAPESP, Brazil ;  NSERC ,  NRC  and  CFI ,  Canada ; CERN;  ANID, Chile ;  CAS ,  MOST  and  NSFC, China ;  Minciencias , Colombia; MEYS CR, Czech Republic; DNRF and  DNSRC, Denmark ;  IN2P3-CNRS  and  CEA-DRF/IRFU , France; SRNSFG, Georgia; BMBF,  HGF  and  MPG , Germany; GSRI, Greece; RGC and  Hong Kong SAR, China ;  ISF and Benoziyo Center, Israel ;  INFN, Italy ;  MEXT  and  JSPS, Japan ; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain;  SRC and Wallenberg Foundation, Sweden ;  SERI ,  SNSF  and  Cantons of Bern and Geneva, Switzerland ; MOST, Taiwan; TENMAK, Türkiye; STFC,  United Kingdom ;  DOE  and  NSF ,  United States of America.
In addition, individual groups and members have received support from  BCKDF ,  CANARIE ,  Compute Canada  and  CRC ,  Canada ;  PRIMUS 21/SCI/017  and  UNCE SCI/013 , Czech Republic; COST,  ERC ,  ERDF ,  Horizon 2020  and  Marie Skłodowska-Curie Actions ,  European Union ;  Investissements d'Avenir Labex , In-.
The Hidradenitis Suppurativa Core Outcomes Set International Collaboration (HiSTORIC) has established the core domain set (what to measure)inHS  8  and has highlighted considerable challenges related to the question of how to measure disease activity reliably. 9 The global assessment represents 1 of 6 HiSTORIC core domains. The Hidradenitis Suppurativa Investigator Global Assessment (HS-IGA) has been proposed as a measure to fulfill the global assessment domain, and to overcome limitations in existing measures used in clinical trials. Recently, HiSTORIC described the development and initial validation of the HS-IGA in measuring disease activity and responsiveness to interventions. 10  The construct was developed using data from 2 replicate phase 3 randomized clinical trials (PIONEER I [NCT01468207] and PIONEER II [NCT01468233])  11  and an iterative process involving input from experts, patient research partners, and methodologists in HiSTORIC over 2 years.
Statistical Analysis Analyses were performed on the full analysis set population consisting of all randomized participants receiving at least 1 dose of the investigative medicinal product and who have a valid measurement of the primary efficacy variable at baseline and at least 1 postbaseline efficacy assessment. Analyses were conducted at the study population level; thus treatment group allocation was not considered in any of the analyses. All statistical analyses involving an association of data between 1 or more measures included only records where data were not missing for all measures. Analysis was conducted from April 2, 2021 to September 30, 2022, using SAS statistical software (version 9. 4, SAS Institute).
These analyses conducted on blinded data from a phase 2 randomized, double-blind, placebo-controlled, active reference arm study to assess the efficacy and safety of bimekizumab in adults with moderate-to-severe HS confirmed the psychometric properties of HS-IGA score. The HS-IGA score demonstrated good convergent validity with IHS4 and HS-PhGA and divergent validity with a general skin disease QoL measure and global pain scales. Importantly, HS-IGA showed very strong test-retest reliability, which suggests that raters may use the measure with accuracy. The HS-IGA also showed responsiveness to change when anchored against HiSCR. For responsiveness, the desire is to maximize true-positive and truenegative results compared with the anchor, while minimizing false-positive and false-negative results.
It then takes on the characteristics of a supersonic mode. The first scale-resolving simulations for wall-bounded flows of a dense gas were performed for the compressible channel flow. Sciacovelli, Cinnella & Gloerfelt (2017)  used DNS for a heavy fluorocarbon (PP11) and bulk Mach and Reynolds numbers between 971 A8-3 1. 5 and 3, and 3000 and 12 000, respectively. They also observed a negligible friction heating and a liquid-like behaviour for the viscosity. Despite the very weak temperature variations, strong density fluctuations are present due to the non-standard thermodynamic behaviour. Density fluctuations are correlated with pressure ones, unlike the perfect gas, where the near-wall streaks correspond directly to high-and low-density fluid. A priori analyses of several RANS models based on these DNS databases was conducted by  Sciacovelli, Cinnella & Gloerfelt (2018).