dataesr/scientific-paragraphs-categorization huggingface dataset:
3B ) around gper1 in all the studied species. In Xenopus ("Xtr"), chicken ("Gga") and the non-teleost fish spotted gar   S1  for Accession numbers of the sequences from Ensembl and NCBI databases. S1  for all accession numbers and scientific names. The alignment was edited in Genedoc with shading in group configuration mode and shows fully conserved residues boxed in black, residues conserved in some of the species in grey and non-conserved residues in white. Gaps introduced to optimize the alignment are shown with dashes. The transmembrane domains (TM1-7) predicted by comparison to mammalian and fish Gpers are indicated with solid lines above the MSA. The cysteine residues typically conserved in Gpers are indicated by an asterisk above the alignment. The characteristic DRY residues are enclosed by a rectangle.
Acknowledgements This research was supported by the  ANR  financed project  ETaT  ( ANR-15-CE32-0014 ), the  Spanish MCIN /AEI/10. 13039/ 501100011033/  and by  ERDF  a way of making Europe ( AGL2015-67477-C2-1-R ,  PID2021-122929OB-C32 ) and the  Portuguese Foundation for Science and Technology (FCT)  through projects  UIDB/04326/ 2020 ,  UIDP/04326/2020  and  LA/P/0101/2020 , and researcher contract to PP under the " Norma Transitória ",  DL57/2016/CP1361/ CT0015. This work was partially supported by the " PHC PESSOA" program  (project number:  44642RM ), funded by the  French Ministry for Europe and Foreign Affairs , the  French Ministry for Higher Education and Research  and the  Portuguese Foundation for Science and Technology.
Acknowledgments We thank  Zacaria Essaidi  for fruitful discussions of in-line holography and  Francesco Pedaci  for insightful comments on this manuscript. We thank  Patrick Nepveu  from  VM2  for the loan of a Photron FASTCAM NOVA 4K R5 camera, as well as  Constant Taindjis  from  Ametek France  for the loan of a Phantom V2640 camera from Vision Research. We thank  Christian Ligoure  from  Laboratoire Charles Coulomb  for the loan of a Phantom VEO 1310 camera from Vision research as well as the TSI droplet generator.
Funding This research has been supported by the  French National Research Agency (ANR) , grants  ANR-22-CE30-0034  and  ANR-21-CO15-0004 , as well as by the  LabEx NUMEV  ( ANR-10-LABX-0020 ) within the  I-Site MUSE  ( ANR-16-IDEX-0006 ). The CBS is a member of the  France-BioImaging (FBI)  and the  French Infrastructure for   Integrated Structural Biology (FRISBI) , 2 national infrastructures supported by the  French National Research Agency  ( ANR-10-INBS-04-01  and  ANR-10-INBS-05 , respectively).
We previously demonstrated in a comparative longitudinal study that PreHab was beneficial in addition to a stan-dard ERAS program in terms of postoperative metrics and health-related costs  [3]. The involvement of RARP patients in this PreHab scheme also led to better short-term functional outcomes, with a shorter delay to strict continence recovery after surgery even after controlling for age, body mass index, prostate volume, nerve-sparing surgery, and lymph node dissection  [5]. We assessed the impact of this program on global hospital endpoints at 5 yr after its initiation and compared the results to French nationwide data (2017-2022 Programme de Médicalisations des Systèmes d'Informations data). During the study period, all 694 consecutive RARP patients treated in our center were included.
2% after PreHab initiation. The overall hospitalization costs per patient (calculated from the daily national hospital costs for surgery wards) decreased from €1026 to €376, representing a cost reduction of 63% for our center and of 73% in comparison to the national RARP average. When taking into account the readmission rate, we found a 3. 8-d difference regarding the number of days out of the hospital within 30 d after surgery (24. 5 vs 27. 8) between our results and national data. Despite these advantages for patients, surgeons, and hospitals, our experience taught us that maintenance of this program its diffusion to other interested centers could be challenging, mainly because of motivational issues for care teams, the absence of financial and incentive support for such programs, and the lack of human resources in health care systems.
We faced some issues during our experience. Owing to organizational constraints and to the intense turnover of RARP patients, PreHab could not be applied to all patients, as the program was limited to 1 d and four patients per week. The most illustrative example is the COVID-19 outbreak, which led to discontinuation of the PreHab for several months and resulted in a trend towards worse annual outcomes (Fig. 1 ). Our experience suggests that optimization of the patient perioperative pathway provides significant patient and hospital benefits. However, multiple constraints related to financial support, team motivation, and caregiver resources may limit the widespread diffusion of such programs. The development of a digital, easy-to-use, validated tool can help in overcoming these limitations.
All these considerations led us to develop a free mobile app, which can be downloaded from the usual app stores by every patient, that integrates checklists, remote monitoring, and multiple PreHab/rehabilitation educational materials, including a specific module for RARP (https:// app. betty. care/appstores). The patient app includes checklists before key events (anesthesiologist visit, admission, discharge, postoperative visit), alerts for starting or stopping activities (medications, physical activity, stockings, diet, work), and educational materials (podcasts, videos, articles) to improve access to patient information and each patient's condition before surgery, including physiotherapy exercises adapted to RARP. ePatient-reported outcome and experience measures are also available for prospective collection of data on patient satisfaction, experiences, and specific outcomes related to RARP such as continence and sexual function using validated questionnaires.
Between 2019 and 2020, the Gambier lagoon was instrumented over a period of 9 months with a large array of autonomous oceanographic instruments measuring temperature, pressure and current. Two deployments were conducted, respectively from June 2019 to October 2019 (Leg1) and from late October 2019 to late February 2020 (Leg2). A total of sixteen instrumented locations were spread across the lagoon and on the forereef. Physical parameters were measured to characterize the wave climate, tide and surges, lagoonal circulation, and spatial and vertical temperature variabilities. Those observations were part of the ANR-funded MANA project (2017-2022) and its derivatives that aimed to improve knowledge of processes influencing the spat collection of Pinctada margaritifera oysters that are used for black pearl farming and production.
Acknowledgements The authors acknowledge the  Direction des Ressources Marines (DRM) of French Polynesia  for their financial support and for providing oceanographic instruments. The additional scientific staff that helped during the field operation described here include  David Varillon ,  Bertrand Bourgeois ,  John Butscher ,  Manui Tanetoa  and  Teranui Ebb. We also thank the boat drivers and local population for their support and welcome.
Financial support This study was funded by a grant  ANR16CE320004 MANA  ( Management of Atolls  project). For  Takapoto Atoll  surveys were also funded by the  Direction des Ressources Marines (DRM)  through grant  7518/VP/DRM  to IRD. Instruments were provided by the  Direction des Ressources Marines , OTI project,  Contrat de Projet France French Polynesia ,  Program 123, Action 2 ,  2015-2020.
Study population We used data from two weight loss interventions, the Reach for Health (RfH) and the Metabolic, Exercise, and Nutrition at University of California San Diego (MENU) studies. These interventions were conducted on women living in Southern California who were at risk for breast cancer or breast cancer recurrence. Both randomized controlled trials were as part of the NCI-funded Transdisciplinary Research and Energetics in Cancer Center and have identical data collection procedures, including data collection of biomarkers and GPS/accelerometer recorded physical activity and location. The full protocol and eligibility criteria have been described elsewhere  (Patterson et al. , 2016; Le et al. , 2016; Rock et al. , 2016). Briefly, RfH is a randomized trial using a 2 × 2 factorial design to compare the degree to which weight loss, metformin, or both, influence biomarkers associated with breast cancer risk.
Eligible participants were overweight or obese women with a history of early-stage postmenopausal breast cancer within the past 10 years (n = 333). Women were randomized to placebo, metformin, weight-loss intervention and placebo, or weight-loss intervention and metformin. MENU is a weight loss intervention in non-diabetic overweight/obese women (n = 245) randomly assigned to 3 dietary intervention arms: a lower fat, higher carbohydrate diet; a lower carbohydrate, higher fat diet; or a walnutrich, higher fat, lower carbohydrate diet. Overall, combining data from these two studies, 578 overweight or obese women were enrolled at baseline between 2011 and 2016. The Human Research Protections Program at University of California San Diego approved both studies (protocols 101977 and 110876). All participants provided written informed consent.
GPS-GIS environmental measures In both studies, participants wore an ActiGraph GT3X and a Qstarz GPS device around their waist for at least 4 days at baseline and 6 months. The data from the two devices data were stitched together and processed by the Personal Activity and Location Measurement System (PALMS) to remove scattering signals and then missing GPS data imputed using the mean center of GPS points before the lapses. Study days with at least 10 h of overlapping accelerometer and GPS wear time were considered as valid days for analysis. This resulted in the creation of the final dataset of an average 12. 58 valid days among participants and a mean daily valid GPS wear time of 822. 87 min. For each participant, all daily GPS points were combined to generate a daily Kernel Density Estimates (KDE) surface with a 200 m bandwidth and the quartic kernel function  (Silverman, 1986) , representing daily activity space.
The process of KDE and exposure calculations were implemented in Python 3. 8 with the ArcPy package. The daily GPS-GIS exposure values were averaged for each participant at baseline and 6-month follow-up and transformed into z-scores. To ensure that an increase in the unit of environmental factors corresponded to an improvement in environmental exposure (i. e. , a positive change), PM 2. 5 and NO 2 levels were inverted to represent a reduction in air pollution levels. To ensure robustness of results and sensitivity due to definition of dynamic exposure, in supplementary analyses the dynamic daily exposure values were assessed using Density Ranking (DR) as the activity space measurement. DR is another time-weighted activity space measurement that utilizes probability-like density ranking function ordering of KDE outputs from lowest to highest  (Chen and Dobra, 2020).
Results Among the 578 women with overweight or obesity who were included at baseline from both the RfH (333 participants) and MENU (245 participants) studies, we restricted our analyses to participants who had completed a 6-month follow-up and who had GPS-GIS environmental data. Ultimately, 464 participants had complete information on covariates (i. e. , study, age, race/ethnicity, education, intervention, and ADI), and 462 had HOMA-IR, glucose, and CRP data (see Fig. S2 ). The analyses were performed on complete cases, thus the study sample varied according to the outcome and exposure studied. The average age of the 464 women with complete data for covariates was 58. 2 years (SD 9. 8) (refer to Table  1 ). On average, these women had a BMI of 31. 3 (SD 4. 8). The majority of women were non-Hispanic white (77.
Discussion We utilized data from two weight loss trials, the RfH and MENU studies, which included ~460 overweight/obese women residing in Southern California. To assess their daily-life environmental exposures, we used dynamic exposure based on GPS data. In the whole sample, no association was found between a 6-month improvement in environmental exposures (i. e. , exposure to a healthier environment) and a reduction in metabolic biomarkers levels, such as insulin resistance, glucose, and CRP. Similarly, we found no association between the levels of NDVI, walkability, NO 2 , and PM 2. 5 exposures and the levels of these biomarkers at baseline. However, using DR measures, we found that a more recreational environment was associated with a lower level of CRP at baseline. When stratifying the analyses according to the level of environmental exposures at baseline, we found significant association between an exposure to greener environments and reduced CRP concentrations between baseline and 6-month time points.
The differential expression analysis of the filtered data was performed using the edgeR package of R and the limma-trend method described in  (Law et al. 2016  https://doi. org/10. 12688%2Ff1000research. 9005. 3). For each experimental setting Differentially Expressed Genes (DEGs) were further analyzed for all the available enrichments. Enrichment analysis and visualization of the DEGs were performed using the clusterProfiler R package  (Wu, et al. 2021   FIGURE LEGENDS d if f + T G F B 1 mRNA expression normalized to PPIA MYOGENIN 0,0 0,5 1,0 1,5 2,0 2,5 p r o l if d if f d if f + T G F B 1 mRNA expression normalized to PPIA MYOD1 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 1,6 1,8 p r o l if d if f d if f + T G F B 1 mRNA expression normalized to PPIA SERPINE1 D.
ACKNOWLEDGEMENTS We thank members of the  Ait-Si-Ali lab and Epigenetics and Cell Fate department  for helpful discussions during the group and department meetings and critical reading of the manuscript. We thank  Dr Vincent Mouly  from the  Institute of Myology and MyoBank  for generous sharing of biological material as well as  Dr Frédérique Magdinier. We warmly thank  Dr Capucine Trollet ,  Dr Elisa Negroni  and  Dr Anne Bigot  for their advice, generous sharing of biological material, technical and critical help. We also thank  Myriame Mohamed  for her precious help and expertise. We warmly thank  Anna Moles  for NGS data thanks to the "Project  CTN01_00177_888744  for the creation of a multiregional infrastructure ( Italian regenerative medicine infrastructure IRMI) for the development of advanced therapies aimed at organ and tissue regeneration ".
# DEQ20160334922); Agence Nationale de la Recherche (ANR, « MuSIC » grant # ANR-17-CE12-0010-01), Université Paris Diderot (now Université Paris Cité) and the "Who Am I?" Laboratory of Excellence, # ANR-11-LABX-0071, funded by the French Government through its "Investments for the Future" program, operated by the ANR under grant #ANR-11-IDEX-0005-01. A. G. was supported by a 4-years Prix LINE POMARET DELALANDE PhD fellowship managed by the Fondation pour la Recherche Médicale. M. Z. was supported by a French government PhD fellowship (PLP201910009924 and FDT20224014764). R. R. has been supported by a DIM Biotherapies -Paris and LABEX "Who am I?" (Université Paris Cité, ex Université Paris Diderot) fellowships. A. G. and M. Z. are PhD students at the BioSPC doctoral school (UPC).
Introduction Protein-protein interactions (PPIs) play a pivotal role in regulating biological processes, particularly cellular and signaling pathways  [1]. Abbreviations: ARE, antioxidant response element; DSF, differential scanning fluorimetry; IPTG, isopropyl β-D-thiogalactopyranoside; ITC, isothermal titration calorimetry; K D , dissociation constant; Keap1, Kelch-like ECH-associated protein 1; MS, mass spectrometry; Neh, Nrf2-ECH homology; NMR, nuclear magnetic resonance; Nrf2, nuclear factor erythroid-2 related factor 2; NTA, nitrilotriacetic acid; PDB, protein data bank; PPI, protein-protein interaction; Rbx1, RING box protein 1; RU, resonance unit; SPR, surface plasmon resonance; STD, saturation transfer difference; TCEP, Tris (2-carboxyethyl) phosphine; Tm, melting temperature; UbcH5c, human ubiquitin-conjugating enzyme H5c; Ube1, ubiquitin-activating enzyme E1; WT, wild-type.
The Neh2 domain at the Nrf2 N-terminus binds to the Keap1 Kelch domain  [12]. The Neh2 domain contains DLG and ETGE motifs, which are essential for the interactions with Keap1. Both the higher affinity ETGE peptide motif (protein data bank [PDB]: 2FLU) and the lower affinity DLG peptide motif (PDB: 2DYH) bind in the central cavity of the Kelch domain and interact with serine, arginine, and tyrosine side chains  [13, 14]. In particular, Arg 380, 415, and 483 in the substrate binding pocket of Keap1 could be hot spots identified in previous alanine scanning and computational hot spot mapping studies  [15, 16]. We focused on three hot spot arginine residues (Arg380, Arg415, and Arg483) to discover novel small molecule inhibitors of Keap1-Nrf2 interaction and screened the Japan Tobacco (JT) library of carboxylic acid compounds that could be expected to bind to arginine residues in differential scanning fluorimetry (DSF) assays.
4, 150 mM NaCl, 3 µM EDTA, 0. 05% Tween 20 containing 5% DMSO). The peptides were injected with a 1 min association time and a 3 min dissociation time at a flow rate of 30 µL/min. The obtained screening data were solvent corrected, reference subtracted, quality controlled, and globally fitted to a 1:1 binding model using Biacore 4000 evaluation software.
SPR direct binding assay for hit validation SPR experiments for hit validation were carried out on a Biacore 4000 or Biacore S51 instrument in the format used in hot spot residue analysis. DSF hit compounds were prepared as 10 mM stock solution, diluted in the running buffer, and injected at 50 µM. Every 24 cycles, KK-16mer ETGE peptide was injected at 30 µM to monitor the amount of active Keap1 Kelch domain. All binding level data were calculated by adjusting them to molecular weight and protein activity levels as measured by the amount of KK-16mer ETGE peptide bound to the Keap1 Kelch domain (%R max ). The maximum of binding activity (R max ) can be calculated using Eq. (2). R max = MW compound MW protein × immobilized protein amount (2) where MW compound is molecular weight of compound and MW protein is molecular weight of protein.
Compounds with above 15% R max and without ill-behavior (very slow dissociation, nonspecific adsorption to reference spots, discontinuous sensorgram, etc. ) or superstoichiometry (>300% R max ) were identified as binders  [21, 22]. To confirm the affinity of the compounds that were obtained at a single concentration, they were tested for binding to the target protein in dose-response format. Compounds were diluted in the running buffer to 100 µM, and serially diluted with running buffer. The compounds were injected with a 1 min association time and a 1-3 min dissociation time at a flow rate of 30 µL/min. The dissociation constant (K D ) values were determined using the Biacore 4000 or Biacore S51 evaluation software.
SPR solution competition assay Biotin-labeled LC-LC-16mer ETGE peptide was immobilized at a concentration of 10 nM for 5 min on a Series S SA sensor chip. Solution competition assays were performed under the same conditions at a Keap1 Kelch domain concentration of 30 nM in the presence of varying concentrations of compounds or the KK-16mer ETGE peptide. Concentration-response data were fitted to the Eq. (  3 ) using Spotfire (TIBCO software): % inhibition = max -min 1 + 10 (Log IC50-Log[comp])×Hill + min (3) In this equation, parameter min equals the baseline of 100% inhibition, max the plateau of 100% activity. IC 50 gives the transition center. The Hill slope (Hill) determines the slope of the curve at the transition center.
Native-MS binding assay All the data have been acquired on an ESI-TOF mass spectrometer (Micro mass LCT) in positive mode using a Triversa Nanomate as infusion robot. For denaturing mass spectrometry analysis, acquisitions and calibration were performed on the m/z range 500-5000 using a 2 µM myoglobin solution as external calibrant. For native mass spectrometry analysis, acquisitions and calibration were performed on the m/z range 500-5000 using a 2 g/L cesium iodide in 2-propanol/water (50/50 v/v) as external calibrant. Native mass spectra were recorded at Vc 50 V and Pi = 5 mBar. The purified Keap1 Kelch domain was buffer exchanged against 50 mM ammonium acetate buffer, pH 7. 5, using NAP5 desalting columns (Cytiva). Analysis under denaturing conditions in 50% water/ 50% acetonitrile/0. 5% formic acid revealed a major species with mass 35,204.
6 Da, which was attributed to intact Keap1 Kelch domain (theoretical mass: 35,205. 6 Da). Characterization of compound binding to the Kelch domain under non-denaturing conditions was then performed in 50 mM ammonium acetate pH 7. 5. In Native-MS conditions, the main species showed a + 64-65 Da mass shift regarding the expected mass which could be explained by a potential non-covalent binding of an endogenous zinc molecule. For the Native-MS binding experiment, Keap1 and compound 4 were incubated at 50 µM at a 1:5 molar ratio and analyzed at Vc = 50 V, Pi = 5 mbar. Data interpretation was performed using MassLynx v4. 1 software (Waters) and masses were calculated using the peak picking method.
ITC binding assay ITC titration experiments were performed at 25 • C on an Auto-iTC 200 system (Malvern Instrument). All samples were in 10 mM HEPES, pH 7. 4, 150 mM NaCl, 3 µM EDTA, 0. 05% Tween 20 containing 5% DMSO. In a typical experiment, 100 µM KK-16mer ETGE peptide or 500 µM compound was titrated in the sample cell containing 10 µM Keap1 Kelch. Each titration consisted of a preliminary 5 µL injection followed by 18 or 36 subsequent 13 µL additions. Binding data were analyzed using the computer program Origin 7 supplied by Malvern Instrument.
X-ray protein structure determination Each compound was dissolved in the precipitant solution to reach a final concentration of 1 mM for soaking. The apo crystal in 0. 1 M sodium acetate, pH 5. 0, 1. 5 M di-ammonium sulfate was transferred into the soaking drop and left for 4 h at 4 • C. Crystals were cryoprotected with ammonium sulfate and flash-frozen in liquid nitrogen. The crystallographic experiments were performed on the Proxima-1 beamline at Soleil Synchrotron, Paris, France. The structure has been deposited in the Protein Data Bank database (PDB: 8IVG)  [17].
X-ray analysis of compound 4 The structure of human Keap1 with Compound 4 (PDB: 8IVG) was solved at 1. 79 Å resolution with a packing similar to the packing described for mouse Keap1 (PDB: 1X2J)  [15, 17]. Human Keap1 had a cylindrical-shaped structure with a typical β propeller topology. Interactions between Compound 4 and Keap1 included four direct electrostatic interactions and one indirect electrostatic interaction as well as hydrophobic contacts (Fig. 6 ). The carbonyl oxygen of the amide of Compound 4 formed a hydrogen bond with the side chain of Ser555. The carbonic acid of Compound 4 formed a salt bridge with the side chain of Arg483, and hydrogen bonds with Ser508 and Arg415 via a water molecule. In addition, the p-tolyl moiety was immersed deeply in the hydrophobic region at the center of the β-propeller tunnel.