dataesr/scientific-paragraphs-categorization huggingface dataset:
OxA Induced an Increase in ATF3 and Cleaved PARP in Gemcitabine-and Nab-Paclitaxel-Resistant Tumors To determine whether OxA induced tumor growth inhibition via OX1R expression in gemcitabine-or Nab-paclitaxel-resistant tumors or/and modified the expression of proteins involved in the resistance processes, a transcriptomic analysis of expression of various proteins related to drug resistance in PDAC was carried out. Transcripts specifically regulated in gemcitabine-or Nabpaclitaxel-resistant tumors treated or not by OxA were identified by RNA-seq and analyzed by functional enrichment using GSEA software and WEB-based GEne SeT AnaLysis Toolkit (WebGeSTAT)  (22). As shown in Figure  7A , few transcripts were impacted by OxA in gemcitabine-or Nab-paclitaxel-resistant tumors. These transcripts mainly represent pseudogene and long non-coding RNA (lncRNA).
Nevertheless, OxA was able to increase the expression of HRK coding for harakiri protein, which promoted apoptosis by interaction with Bcl-2 and Bcl-XL  (24). Moreover, functional enrichment analysis using WikiPathway cancer database showed that differential expression of transcripts associated with OxA treatment in AsPC-1 cells resistant to gemcitabine or Nab-paclitaxel were related to apoptosis, Wnt signaling in cancer, olfactory transduction, and insulin or chemokine signaling pathways (Figure  7B ). These results indicated that OxA treatment of gemcitabine-or Nab-paclitaxel-resistant tumors had very small impact on transcriptome excepted for HRK, which displayed proapoptotic properties. The expression of various proteins expressed in PDAC and participating in tumoral drug resistance including cell stress proteins (Nrf2, p-eIF2a, ATF3, and ATF4), DNA reparation proteins (PolQ and PARP), oncogenic protein (FoxM1), and anti-apoptotic protein (Bcl2) were analyzed in gemcitabine-or Nab-paclitaxel-resistant tumors treated or not by OxA.
ACKNOWLEDGMENTS We thank the  CyBio, Genom'IC and Animal care core facilities of Cochin Institute (Paris, France). We are grateful to  Evelyne Bloch-Gallego  for critical reading of the manuscript and  So-ichiro Fukada  for technical expertise. SHG images acquisition and analysis were performed at the  IMAG'IC Facility , supported by the  National Infrastructure France BioImaging  (grant  ANR-10-INBS-04 ) and IBISA consortium. Financial support to this work was provided by the  Association Francaise contre les Myopathies  (n  22365  and  22776 ),  IdEx Emergence Universitede Paris  ( IP 2019-030 ) the  Agence Nationale de la Recherche  ( Myolinc ,  ANR-R17062KK ), the  Institut National de la Santeet de la Recherche Medicale (INSERM)  and the  Centre National de la Recherche Scientifique (CNRS).
These features together with the cells following the metastatic pattern of ILC recapitulate the characteristics of lobular cells. Examining the cancer genome atlas (TCGA) patient dataset identified lysyl oxidase like 1 (LOXL1), a collagen modifying enzyme, as being highly expressed in lobular carcinomas. Using the ILC intraductal model, described above, he demonstrated that mice dosed with BAPN, a LOX inhibitor, exhibited disrupted extracellular structures and decreased ER signalling, which subsequently led to decreased invasion, growth and metastasis of the tumours and opened new therapeutic strategies for ILC  [14]. Along a similar theme, Jos Jonkers from Netherlands Cancer Institute (Amsterdam, Netherlands) presented a different strategy to investigate ILC using genetically engineered mouse models (GEMMs).
NMR Assignment of Tau PRR2* and Tau R2* All NMR experiments were recorded at 10 • C for R2* and 4 • C for PRR2* on a Bruker 800 MHz spectrometer equipped with a cryogenic probe. All spectra were processed with topspin 3. 5pl7 (Bruker) and NMRPipe/NMRDraw. The assignment of tau PRR2* and R2* was based on a series of 3D spectra using a uniformly 15 N, 13 C-labeled sample including HNCACB, CBCA(CO)NH, HNCO, and HN(CA)CO. 1 H- 15 N HSQC experiments were recorded with 8 scans, a recycle delay of 1. 0 s, 3072 (t 2 ) × 200 (t 1 ) complex data points, and a spectral width of 16 ppm in the 1 H dimension and 22 ppm in the 15 N dimension. HNCACB and CBCACONH were recorded with 8 scans, 3072 (t 3 ) × 75 (t 1 ) × 256 (t 2 ) data points, and a spectral width of 10 ppm in the 1 H dimension, 22 ppm in the 15 N dimension, and 60 ppm in the 13 C dimension.
NMR Titration of Tau PRR2* and Tau R2* with Arixtra and Heparin The NMR spectra of tau PRR2* were acquired at 4 • C and tau R2* at 10 • C on a Bruker 800 MHz NMR spectrometer equipped with a cryogenic probe. Aggregation did not occur at this low temperature. NMR data were processed and analyzed using Topspin 4. 2pl7 and Sparky. 15 N-labled tau PRR2* and R2* were dissolved in 100 mM of NaCl, 10 mM of Na 2 HPO 4 , and 4 mM of DTT at pH 6. 5 in 90/10% H 2 O/D 2 O. A series of separate 1 H- 15 N HSQC spectroscopy experiments were performed on a 0. 08 mM tau R2* or 0. 120 mM PRR2* sample by adding increasing amounts of Arixtra. Normalized chemical shift perturbation (CSP) of tau for amide 1 H and 15 N chemical shifts upon Arixtra addition: CSP = √ 100 × ∆H 2 + ∆N 2 , where ∆H and ∆N are the differences between the chemical shifts of the free and bound forms of tau, respectively.
In other words, the sound of round is spectrally low and temporally smooth. Surprisingly, while these simple acoustic properties have recently been mentioned for possibly being at the origin of the bouba-kiki effect  12  , they have never been tested. Predicting the bouba-kiki effect from spectral balance and temporal continuity. In this section, we combined a meta-analysis with a computational modelling approach to quantitatively assess the possibility to predict the bouba-kiki effect from spectral balance and temporal continuity parameters. Thanks to their authors, we gathered data and speech stimuli from 8 publications (10 experiments, total of 394 participants, 1086 speech stimuli, five languages) on the bouba-kiki effect (see Table  2  in "Methods" for more details). In spite of the large dataset variability in terms of languages, linguistic contents and stimuli, we opted for a simple and single computational phenomenological model to extract spectral balance and temporal continuity parameters from the acoustic speech stimuli.
The goal was to capture the trends shared by the entire dataset, even though it would likely be sub-optimal for each individual experiment. The phenomenological Balance x Continuity model is displayed in Fig. 1  and described in details in "Methods". For each speech stimulus, it performs basic acoustic analyses resulting in the computation of two parameters: the spectral balance between low and high frequencies (Balance parameter) and the temporal continuity between minimum and maximum amplitude (Continuity parameter). It then predicts a round (over spiky) score from these two parameters only. To measure how well the Balance x Continuity model could predict the bouba-kiki effect, we conducted separate linear regressions for each experiment between the model's round score predictions (Model) and the experimental round score (Data).
For each experiment, we also computed experimental round score percentage of variance r 2 explained by the model. These analyses were conducted using R  27  and the work package "lm". Their results are displayed in Fig. 2  and detailed in Table  1. All linear regressions were significant (alpha level: 0. 05, see Table  1 ), explaining quite large percentages of variance (mean r 2 = 60%, range: 26-94%, see Fig. 2 ). In other words, predictions of the Balance x Continuity model were very accurate for the entire bouba-kiki effect dataset (see also the Supplementary Information for more discussion). Importantly, we tested whether the Balance x Continuity model could also efficiently predict, for non-speech stimuli, similar sound-shape associations as in the bouba-kiki effect with speech stimuli.
Participants had to match each sound to one of the two ball images. Results are displayed in Fig. 5c. Data coding and pre-processing were the same as in the Noise Band Experiment. We then used a mixed-effects model to analyze these non-averaged data with R 27 and the "lme4" package  28  (alpha level: 0. 05, two-tailed). The data for the original sounds and the synthetically modified sounds were analyzed separately. For the original sounds, Ball Shape (Round, Spiky) was the single within-participant fixed factor. For the synthetically modified sounds, Acoustic Envelope (Smooth from the round ball, Sharp from the spiky ball) and Spectral Balance (Low-Frequency from the round ball, High-Frequency from the spiky ball) were within-participant fixed factors. Initially, rolling Surface Material (wood, plastic) was also declared as a random factor, but it did not significantly increase the variance accounted for and was thus excluded from the final models.
Orthographic factors together with phonotactic and phonological constraints also play a role in this effect and in sound symbolism Table  2. Presentation of the data and speech stimuli of the 10 published experiments assessed in the computational phenomenological model. The experiment number matches the one from the original publication. The Experimental "Round Score" in the second last column is the one used in all simulations and analyses of the present paper. FCT forced choice task, LRT likert rating task, No Shape Participants judged how each speech stimulus sounded, DV dependent variable, Round Score assessment (averaged across participants) used in each study, ADS adult-directed-speech, IDS infant-directed-speech, Proc. procedure. in general (see  12, 23, 31  for recent overviews). More globally, the bouba-kiki effect may be part of a larger system of sound-to-semantic associations which could involve higher-order factors such as arousal (termed "activity" in  32  ).
2. The pattern of variations of r 2 values with the boundary b across all experimental data sets is further discussed in the Supplementary Information. These analyses were conducted using R  27  and the work package "lm". Experiments. All the experiments in this manuscript including human participants followed the General Data Protection Regulation (GDPR), and was approved by a local ethical committee (CERGA, "Comité d'Ethique pour la Recherche, Grenoble Alpes", Ethical Research Committee Grenoble Alpes n° 2020-07-01-1). This means that methods were performed in accordance with the relevant guidelines and regulations for testing human participants in the European Union. Notably, informed consent was required from all participants before participating in the study. Noise Band Experiment. Participants.
We then recorded the sound produced by these two balls rolling on a hard wood or plastic surface (see Fig. 5a ). This provided 12 original sounds, from two objects (round and spiky balls) x two surface materials (hard wood and hard plastic) and 3 instances per object and surface material per condition (see examples of corresponding envelope fluctuations in Fig. 5b ). To control for differences in frequency spectrum between round vs. spiky objects, we estimated the mean spectrum of all sounds respectively produced by round objects and spiky objects. We used the Praat Speech_Shaped_Noise script  53  to generate two noise stimuli "shaped" by these mean values for round and spiky frequency spectra. We then estimated the acoustic envelope of each of the 12 original stimuli using  54  and we modulated in time the two shaped-noise-spectra stimuli by these 12 envelopes.
Acknowledgements We thank  Radu Horaud  ( INRIA, Grenoble, France ) for his crucial advice on the mathematical work by  Kac. We thank  Eric Guinet  ( LPNC, Grenoble, France ) for his help with the 3D-printing of the balls in the  Rolling Balls Experiment. We thank  Ferran Pons  ( University of Barcelona, Barcelona, Spain ),  Julien Diard  and  Olivier Pascalis  (both from the  LPNC, Grenoble, France ) for their comments on previous versions of this manuscript. We thank the authors of the articles who provided their data and stimuli for the meta-analysis.
Data availability Not all the authors of the experiments included in the meta-analysis shared their data publicly (cf. Table  2 ). Summary of available data, stimuli and script of the model, as well as the data, stimuli and scripts used in the Noise Band, Beating Toys and Rolling Balls Experiments are available in this osf: https:// osf. io/ v9xyd/? view_ only= 2d207 fc228 684f1 d8ac9 6ac97 f5775 9c.
Purpose: This trial aimed to assess the efficacy and safety of olipudase alfa enzyme replacement therapy for non-central nervous system manifestations of acid sphingomyelinase deficiency (ASMD) in adults. Methods: A phase 2/3, 52 week, international, double-blind, placebo-controlled trial (ASCEND; NCT02004691/EudraCT 2015-000371-26) enrolled 36 adults with ASMD randomized 1:1 to receive olipudase alfa or placebo intravenously every 2 weeks with intrapatient dose escalation to 3 mg/kg. Primary efficacy endpoints were percent change from baseline to week 52 in percent predicted diffusing capacity of the lung for carbon monoxide and spleen volume (combined with splenomegaly-related score in the United States). Other outcomes included liver volume/function/sphingomyelin content, pulmonary imaging/function, platelet levels, lipid profiles, and pharmacodynamics.
Study design and participants This phase 2/3 randomized, placebo-controlled, doubleblind study in adults with ASMD (ASCEND/ NCT02004691/EudraCT 2015-000371-26) was conducted in 13 countries between December 18, 2015 and October 17, 2019 (52-week primary analysis period). Institutional Review Boards approved the protocol, and patients provided written informed consent. Adults diagnosed with ASMD by enzymatic assay and/or genotyping with DL CO ≤70% of predicted normal value, spleen volume ≥6 multiples of normal (MN), and splenomegaly-related score (SRS) ≥5 were eligible. ASMD types B and A/B were not differentiated. Exclusion criteria included mean platelet counts <60 × 10 9 /L, alanine aminotransferase (ALT) or aspartate aminotransferase >250 IU/L, or total bilirubin >1. 5 mg/dL at screening (except for patients with Gilbert syndrome).
All treated patients were included in safety and efficacy analyses. Demographic and disease characteristics were summarized using descriptive statistics. The percentage change from baseline to week 52 for primary and secondary endpoints was analyzed using the mixed model for repeated measures with baseline values, baseline age, treatment arm, study visit, and study visit × treatment arm interaction as covariates. Comparisons between treatment groups were made using least square (LS) mean contrasts at the week 52 visit. SRS information collected by eDiary over 7 consecutive days was averaged for respondents with data for at least 4 of 7 days.
Patient-reported outcomes Baseline scores for Brief Fatigue Inventory, Brief Pain Inventory, 36-Item Short Form Health Survey, and EQ-5D-5L reflected moderate impairment, and scores improved in both groups. Changes from baseline were not different between the olipudase alfa and placebo groups for any instrument (data not shown). FACIT-Dyspnea symptom scale scores were largely unrelated to predicted DL CO at baseline and were not significantly associated with the patient's global evaluation of shortness of breath; changes from baseline did not differ between groups (data not shown).
10 Olipudase alfa treatment led to a reduction in spleen volume accompanied by increases in platelet counts, reflecting correction of secondary hypersplenism. 35 SRS was used to collect data on symptoms related to splenomegaly and was adapted for use in the ASCEND trial from a PRO tool used in patients with myeloproliferative diseases. 21 Although myelofibrosis disease pathology is different from ASMD, splenomegaly in both diseases is correlated with increased morbidity and mortality and is a clinically relevant treatment endpoint in clinical trials. 10, 21, 36 owever, the validity, reliability, and sensitivity to change of SRS has not been established in patients with ASMD. SRS improved in both the placebo and olipudase alfa groups without a statistically significant difference between groups, and scores did not correlate with baseline spleen volume.
Acknowledgments The authors thank patients, families, and research facility clinical staff. The study was sponsored and funded by  Sanofi Genzyme. Medical writing support funded by  Sanofi Genzyme ,  United States  was provided by  Patrice C. Ferriola  ( KZE PharmAssociates ); critical manuscript review and editing were provided by  Lisa Underhill (Sanofi). Sanofi Genzyme  was involved in the design of the study, data collection, data analysis, interpretation of data, and collaboration with authors on the writing of the manuscript. All authors had full access to the trial data and are responsible for data accuracy and interpretation of the results. The corresponding author had final responsibility for submission of the manuscript.
Calibration with experimental data In principle, our model can describe search movements of any central place forager. Here we explored its properties focusing on a model species for which we had access to high-quality experimental data: the buff-tailed bumblebee Bombus terrestris. We used the dataset of Pasquaretta et al. (39)  in which the authors used a harmonic radar to track 2D exploratory flight trajectories of bees in the field. Bees carrying a transponder were released from a colony nest box located in the middle of a large and flat open field, and performed exploration flights without any spatial limitation. The radar recorded the location of the bees every 3. 3s over a distance of ca. 800 m (Fig  1C ). In these experiments the bees were tested until they found artificial flowers randomly scattered in the field.
Analysis of experimental data We used the dataset of Pasquaretta et al. (39)  in which the authors tracked exploratory flight trajectories of bumblebees in the field with a harmonic radar. Bees carrying a transponder were released from a colony nest box located in the middle of a large and flat open field, and performed exploration flights without any spatial limitation. The radar recorded the location of the bees every 3. 3s over a distance of ca. 800 m, and with an accuracy of approximately 2 m (  14 ). The bees were tested until they found one of three 20-cm artificial flowers randomly scattered in the field. The position of these flowers was changed whenever one of them was found to prevent the bees from learning their location, but their presence may still affect the bees' trajectories.
We first attempted to control for this factor by removing all trajectories where bees passed near an artificial flower, but this introduced a significant bias towards short trajectories, because bees are less likely to find a flower when they stay near the nest. Therefore, we used the full dataset, and in order to remove the effect of the bees hovering around and exploiting the artificial flowers, we summarized all the points detected in an area within 6 m of an artificial flower as a single point at the location of the flower. This threshold of 6 m was derived from a 4 m perception distance corresponding to 20 cm flowers, plus 2 m to account for the experimental noise. All trajectories are given in S2-section V.
Funding AM was supported by a PhD Fellowship from the  French Government. ML was supported by grants of the  Agence Nationale de la Recherche  ( 3DNaviBee ANR-19-CE37-0024 ), and the  European Commission  ( FEDER ECONECT MP0021763 ,  ERC  Cog  BEE-MOVE GA101002644 ). APE acknowledges funding from a  CNRS   Momentum grant  (https://www. cnrs. fr/)and a  Fyssen Foundation  Research grant (https://www. fondationfyssen. fr/en/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Study set-up and subjects Quantitative MRI and  31  P MRS data were obtained annually (between November 2012 and November 2017) for 3 years in 54 patients from two sites: Newcastle, UK (n = 42), and Paris, France (n = 12). These 54 subjects were a sub-cohort of the 201 patients enrolled across 15 sites worldwide in the Jain COS for dysferlinopathy (Supporting Information, Table  S1 ). 8 Patients were included in the global study based on genetic confirmation for dysferlinopathy. 10 Ambulatory status was defined as the ability to walk 10 m with or without walking aids or orthotics. 8, 10 None of the patients were under corticosteroid treatment since at least 6 months before the start of the study. Data were also obtained in 12 age-matched and sex-matched healthy subjects. Results on the 1-year fat fraction (FF) progression in the 12 patients from Paris have previously been reported.
24 ritten informed consent was obtained from patients prior to inclusion, in accordance with the 1964 Declaration of Helsinki and its later amendments. The study registration number was NCT01676077. Healthy control subjects were scanned as part of a methodology MRI/S protocol approved by local ethics committees (Newcastle: United Kingdom National Research Ethics Committee 1417/375/2017; Paris: CPP-Ile de France VI-Groupe Hospitalier Pitié-Salpêtrière, ID RCB: 2012-A01689-34). Informed consent was obtained from all controls.
Quantitative magnetic resonance imaging and phosphorus magnetic resonance spectroscopy data acquisition Data were acquired on one of two 3 T MRI clinical scanners: an Achieva (Philips Healthcare, Amsterdam, Netherlands) in Newcastle and Trio/Prisma (Siemens Healthineers, Erlangen, Germany) in Paris. For MRI, the local system's body RF coil for signal transmission and surface-array coils for signal transmission were used. For 31 P MRS, a flexible 1 H/ 31 P surface RF coil was employed (Newcastle: 14 cm, Philips; Paris: 11 cm, Rapid Biomedical GmbH, Rimpar, Germany). Patients were positioned feet-first supine and all MRI sequences were centred at one-third of the femur from the superior border of the patella and at the widest part of the calf. Quantitative water-fat imaging was performed using a 2D (Newcastle) or 3D (Paris) gradient echo 3-point Dixon sequence.
5 ms in Paris), a TR of 3000 ms, a slice thickness of 10 mm, and a slice gap of 30 mm. 25  For calculating the transmit field (B 1 + ) in each voxel, a B 1 map sequence was run covering the same slices as the MSE sequence. 26 31 P MRS data were obtained in the anterior part of the right leg, unless the muscles were completely replaced by fat, from a non-localized free-induction decay of 64 averages (a TR of 4000 ms, a bandwidth of 3000 Hz, 2048 data points). Total acquisition time for quantitative MRI and 31 P MRS was approximately 40 min.
Magnetic resonance imaging and phosphorus magnetic resonance spectroscopy data processing All quantitative MRI data were processed using in-house written Matlab (MathWorks, Natick, MA, USA) or Python (www. python. org) code (Newcastle, UK, and Paris, France, respectively). Regions of interest (ROIs) were drawn manually on the shortest TE-image of the MSE series, using the free software tool (www. itksnap. org), both left and right sides, in seven leg muscles (extensor digitorum longus, tibialis anterior, tibialis posterior, peroneus longus, soleus, gastrocnemius medialis/lateralis) and nine thigh muscles (vastus lateralis/intermedius/medialis, gracilis, sartorius, adductor magnus, biceps femoris long head, semimembranosus, semitendinosus), for the five central slices of the MSE scan. To determine FF and cross-sectional area (CSA), the boundaries of the ROIs were drawn (by I.