dataesr/scientific-paragraphs-categorization huggingface dataset:
Analysis of spot and dendrite distances: The structure of the dendritic tree, as well as the position of the puncta, were further analyzed using custom python scripts. The dendritic tree was reconstructed with the center of the soma as its root using the python NetworkX package. Fluorescence puncta were considered to arise from the labeled dendrite if they were located within a maximal distance from the center of the dendrite. This distance was taken as the dendritic radius, estimated from IMARIS, plus 200 nm (~HWHM of the PSF810). The estimation of local radius was made from IMARIS binary masks using a threshold of the local contrast (DiameterContrastThreshold) set at three times the standard deviation above the background fluorescence noise. The diameter is then calculated using the Shortest Distance from Distance Map algorithm, which estimates the diameter as the distance from the center of the dendrite to the closest part of the surface determined by the above threshold.
The average dendritic radius, using this approach, was found to be 0. 66 ± 0. 28 (SD) µm for adult, and 0. 72 ± 0. 27 (SD) µm for immature mice. As this value was larger than that estimated from single-photon confocal imaging, it was only used as a part of the criteria for assigning a fluorescence puncta to a reconstructed dendrite. For each dendritic branch, the number of PSD95 puncta and their distance to the soma surface were calculated. As the data points of the dendrite structure obtained from IMARIS are not homogeneously spaced, the dendritic structure was resampled in 100 nm intervals with the distance for each segment recalculated with respect to the starting point of each corresponding branch from the soma surface (estimated using the binary mask as for the dendrites). Histograms for the distribution of PSD95 puncta and the number of dendritic segments at a given distance from the soma were then generated in 10µm bins and used to estimate the puncta density along the dendritic tree.
Electrophysiology analysis Data analysis was performed using the Neuromatic analysis package  (Rothman and Silver, 2018)  written within the Igor Pro environment (WaveMetrics, Lake Oswego, OR, USA). mEPSCs were detected with a threshold detection method and mEPSC population average is calculated from the mean EPSC response calculated for each SC. All EPSC were baseline subtracted using a 1 ms window before the stimulation artifact. Peak amplitudes were measured as the difference between the baseline level immediately preceding the stimulation artifact, and the mean amplitude over a 100 μs window centered on the peak of the response. EPSC decay kinetics were assessed either as the width of the EPSC at the amplitude one-half of the peak (half-width in ms) or as the weighted time constant of decay (decay) calculated from the integral of the current from the peak, according to: where tpeak is the time of the EPSC peak, t is the time at which the current had returned to the pre-event baseline, and Ipeak the peak amplitude of the EPSC.
Acknowledgements: This study was supported by the  Centre National de la Recherche Scientifique  and the  Agence Nationale de la Recherche  ( ANR-13-BSV4-00166 , to LC and DAD). TA was supported by fellowships from the  Fondation pour la Recherche Medicale  and the  Swedish Research Council. We thank  Dmitry Ershov  from the  Image Analysis Hub of the Institut Pasteur ,  Elodie Le Monnier ,  Elena Hollergschwandtner ,  Vanessa Zheden  and  Corinne Nantet  for technical support and  Haining Zhong  for providing the Venus-tagged PSD95 mouse line. We would like to thank  Alberto Bacci ,  Ann Lohof  and  Nelson Rebola  for comments on the manuscript.
Data Management Data management and statistical analysis were performed independently of the sponsor and investigators by the clinical research unit (Unité de Recherche Clinique, Hôpital Ambroise Paré, Boulogne, France) and by the Center of Clinical Epidemiology (Centre d'épidémiologie clinique, Hotel-Dieu, Paris, France), respectively. Data entry occurred at enrolling sites by the investigator using a web-based data entry system. An e-CRF (electronic Clinical Report Form) was developed by the clinical research unit using dedicated software (CleanWeb) to facilitate data control and monitoring. Each patient was assigned a unique ID that was used to index the e-CRF and related study documents. All information required by the protocol had to be entered into the e-CRF. Data were recorded in the e-CRF as and when they were obtained.
Management of the treatments used Visits to pharmacies were also carried out in a way that verified compliance with the pharmaceutical circuit. Baseline characteristics, eligibility criteria, primary outcome, and serious adverse events reported in the CRF were systematically checked against the original chart for all research participants by the CRA. In addition, for one-third of the study population, all data reported in the CRF were validated against the patient's original chart. Serious adverse events and major protocol violations were reported to the DRRC, Agence Nationale de la Sécurité du Médicament (ANSM), and Comité de protection des personnes (CPP). At the end of the study, after clarification of discrepancies (data cleaning) and data validation, the database was frozen and transmitted to the statistician following procedures established by the promoter.
Confidentiality As for any clinical research supported by the AP-HP, processing of personal data complied with the methodological recommendations of the MR001 reference established by the French Data Protection Authority (Commission Nationale de l'Informatique et des libertés) in January 2006 for biomedical research. During and after the clinical research, all data collected concerning the participants and sent to the sponsor by the investigators (or any other specialized collaborators) are rendered nonidentifying. Under no circumstances shall the names and addresses of the participants involved be shown. Only the participant's initials are recorded, accompanied by an encoded number specific to the study indicating the order of enrollment. Moreover, all nominal data were erased on the copies of the source files that were used for documentation of the research.
Methods in Analysis to Handle Protocol Nonadherence and Any Statistical Methods to Handle Missing Data Statistical analysis will be performed according to the intent-to-treat principle, after all patients have completed the 90-day follow-up. Accordingly, all patients will be analyzed in the arm they were allocated to, regardless of the protocol deviations. In addition, missing outcome data will be imputed. Before data analysis, a detailed statistical analysis plan will be issued by the study statistician. A comprehensive report of the statistical analysis will be issued, following the Consolidated Standards of Reporting Trials (CONSORT) statement recommendations. Any change in the analysis plan will be justified in this final report. Although no missing data are expected for the primary outcome, the maximum bias method will be used for the analysis of the primary outcome, replacing missing data with a success in the control arm and by a failure in the experimental arm.
Adverse Event Reporting and Harms A centralized phone and email center answered participating centers questions regarding patient eligibility or management and declaration of any adverse event during the trial period. A newsletter was sent monthly, informing participating centers on the number of patients included, main study constraints, and any protocol modifications. Baseline characteristics, eligibility criteria, primary outcome, and serious adverse events reported in the CRF were systematically checked against the original chart for all research participants. In addition, for one-third of the study population, all data reported in the CRF were validated against the patient's original chart. Serious adverse events and major protocol violations were reported for DRRC, ANSM, and CPP.
Study Follow-Up The DSMB met five times. The DRRC organized data monitoring and quality audits. Baseline characteristics, eligibility criteria, primary outcome, and serious adverse events reported in the CRF were systematically checked against the original chart for all research participants. In addition, for one-third of the study population, all data reported in the CRF were validated against the patient's original chart. Serious adverse events and major protocol violations were reported for DRRC, ANSM, and CPP. The study coordinator had quarterly face-to-face meetings with the DRRC, AP-HP, and independent pharmacists to monitor trial conduct according to the highest standard for protection of research participants. All randomized patients completed follow-up for the primary outcome and 180-day mortality data.
Acknowledgments The authors thank  Naima Sghiouar ,  Chanez Lazizi ,  Nawal Derridj-Ait-Younes , and  Yasmine Domingo  of the  Center for Clinical Epidemiology. The authors also thank all families and staff at participating sites who have agreed to participate in the VALSE study, and all members of the Trial Steering Committee and Independent Data and Safety Monitoring Committee. This study was funded by the  Clinical Research Hospital Program in 2010 , and the  Ministry of Health  confirmed funding under contract number  AOM10268. The study funder and cosponsors play no part in study design, data collection or analysis, writing of the report, or the decision to submit for publication; the responsibility for these activities lies with the Trial Management Group. The authors are grateful to the investigators of all participating centers:  Laurent Argaud  ( service de Médecine intensive-reanimation, Hôpital Edouard Herriot, Lyon ),  Pierre Asfar  ( Réanimation Médicale, Centre hospitalo-universitaire, Angers, France), Eric Azabou (Service d'Explorations Fonctionnelles, Hôpital Raymond Poincaré, Garches, France ),  Omar Ben Hadj  ( Réanimation Médico-Chirurgicale, Centre Hospitalier Intercommunal Poissy Saint-Germaine-en-Laye, Poissy, France ),  Pascal Blanc  ( Réanimation Médico-Chirurgicale, Centre Hospitalier René-Dubos, Pontoise, France ),  Pierre-Edouard Bollaert  ( Réanimation Médicale, Hôpital Central, Nancy, France ),  Francis Bolgert  ( Réanimation Neurologique, Hôpital Pitié-Salpêtrière, Paris, France ),  Patrick Chillet  ( Réanimation Polyvalente, Châlons-en-Champagne, France ),  Bernard Clair  ( Réanimation Médico-Chirurgicale, Hôpital Raymond Poincaré, Garches, France ),  Gwenhaël Colin  ( Réanimation Polyvalente, Centre Hospitalier Départemental de Vendée, France), Philippe Corne (Réanimation, Hôpital Lapeyronnie, Montpellier, France ),  Jean Dellamonica  ( Réanimation Médicale, Centre Hospitalo-Universitaire de Nice, Nice, France ),  Sophie Demeret  ( Réanimation Neurologique, Hôpital Pitié-SalpêtrièreParis, France ),  Marie-Line Harley  ( Réanimation Médicale, Strasbourg, France ),  Julien Jabot  ( Réanimation Polyvalente, Hôpital Félix GuyonSaint Denis, France ),  Nicholas Heming  ( Réanimation Médico-Chirurgicale, Hôpital Raymond.
11 iven the influence of DED on QoL and healthcare costs, and the minimal published data in the UK, this study was performed to document the burden of DED among adults in the UK. We conducted an online survey and compared the demographics and overall QoL between those with and without DED; evaluated the severity of symptoms and their impact on vision-related QoL and work productivity; assessed the behaviours for seeking care and adhering to treatment and assessed the use of medications for DED.
Open access These items were part of the development of the NEI VFQ and, thus, have been validated. 12 The DED survey included the following assessments: symptom severity/ frequency Visual Analogue Scale (VAS), Ocular Comfort Index (OCI), Work Productivity and Activity Impairment (WPAI) questionnaire, treatment and resource utilisation, treatment satisfaction and treatment compliance and discontinuation. In addition, participants assigned to survey A completed the Impact of Dry Eye on Everyday Life (IDEEL) questionnaire, and those assigned to survey B completed the 5-item Dry Eye Questionnaire (DEQ-5) and the Standardised Patient Evaluation of Eye Dryness (SPEED) questionnaire. Participants had to complete all questions; missing data were not allowed. Participants were compensated by the marketing agency that recruited them and fielded the survey; the costs were reimbursed by the study sponsor.
Open access Identifiable participant data were anonymised prior to analysis. Analyses included descriptions of the following: (1) sociodemographic, diagnosis and medical history data for participants with and without DED, (2) VFQ-28R items with domain scores and EQ-5D-5L for participants with and without DED and (3) overall DED-related burden items and scores from surveys A and B and by EDS severity. No hypothesis was formulated; therefore, no inferential statistics were performed.
Acknowledgements We acknowledge  Ipek Özer Stillman , from  Takeda , for her assistance with survey conceptualisation and development, interpretation of the data and study operations; and  Patrick Marquis  from  Modus Outcomes  for his assistance with survey conceptualisation and development. We thank  Lisa O'Brien, PharmD , of  Excel Scientific Solutions , who provided medical writing assistance, supported by  Takeda  and  Novartis.
Quantitative real-time PCR Total RNA was extracted using TRIzol reagent (Invitrogen) and cDNA was reverse transcribed using Pri-meScript RT Reagent Kit with gDNA Eraser (TaKaRa). qRT-PCR was performed using TB Green Premix Ex Taq II (TaKaRa). mRNA levels were expressed as fold change after normalization to βactin levels (used as internal control), and data were analyzed by means of the 2 -△△Ct method. The primer pairs had the following sequences: LINGO-1: CTTT CCCCTTCGACATCAAGAC (forward), CAGCAGCA CCAGGCAGAA (reverse); Wnt5a: CAACTGGCAG GACTTTCTCAA (forward), CATCTCC GATGCCGG AACT (reverse).
Statistical analysis Data were expressed as the mean ± SD and analyzed using SPSS software (version 20. 0 IBM, Chicago, IL). Significant differences between two groups were calculated by means of the Student t-test. BMS and BMS subscores at different timepoints were analyzed by means of repeated measures analysis of variance (rmANOVA). A post hoc analysis with Bonferroni's adjustment was conducted for further multiple comparisons. The level of significance for all comparisons was set at P < 0. 05.
Immunofluorescence staining and quantification demonstrated that D, E Tuj1+/GFP+ neurons increased significantly, while F, G GFAP+/GFP+ astrocytes decreased in LINGO-1 shRNA-treated sp-NSPCs. Enlarged areas show that astrocytes in the LINGO-1shRNA group appeared more mature (arrowheads) than those in the control group (arrows) (bar = 100 μm), * P < 0. 05. Results are expressed as the mean ± SD. All of the analysis was calculated based on three biological replicates miR-143-3p, miR-101a-3p, miR-135a-5p), findings which were consistent with the miRNA-seq data (Fig. 5D ). Wnt5a is a non-canonical WNT molecule which plays an important role during cell differentiation and proliferation  [11]. To investigate the signaling pathway that is activated by Wnt5a, we measured JNK and phosphor-JNK protein expression levels, since they are key molecules in the non-canonical Wnt signaling pathway.
Water analysis Dissolved major species were analyzed at the analytical platform of the Indo-French Cell for Water Sciences (Indian Institute of Science, Bengaluru) following the protocol described in  Riotte et al. (2014 Riotte et al. ( , 2021)). Conductivity and pH were determined with a WTW metre, anions (F, Cl, NO 3 , SO 4 ) and cations (Na, K, Ca, Mg) with a Metrohm 561 ion chromatograph, alkalinity with a Mettler Toledo DL50Gx titrator, DOC with a Shimadzu TOC 500 and silica by colorimetry (blue method). The quality of the major ion data was checked using reference materials ION-96. 4 and PERADE, and by calculating the inorganic charge balance. This latter was better than 3% for both samples. Trace element concentrations, including metals, were determined with an ICP-MS Agilent 7700x at BSIP, Lucknow, with detection limits ranging from 10 ng/L for light trace elements to 1 ng/L for the heavy ones.
Appropriate biotinylated secondary antibodies (Vector Laboratories) were used, the antibody was visualised using 3,3 ′ -diamino-benzidine (DAB; Sigma-Aldrich Company) and sections were counterstained with Nissl. Where intensity of immunostaining is reported it was calculated by densitometric analysis using the NIH ImageJ software (Fiji, NIH). Optical density was calculated from grayscale images standardised to the photomicrograph background as previously described  (Fleiss et al. , 2012b; Rangon et al. , 2018). In brief, for each animal, four measurements in each region (4 fields of view) were made across four sections. For cell counts, the number of cells per field under 10x or 20x magnification were performed. Results are expressed as cell counts per field. The different areas of the brain analysed are shown in Appendix C.
Acknowledgements This study was supported by grants from  Inserm  :  Institut National de la Santé et de la Recherche Médicale (INSERM, France) ,  Université de Paris ,  Fondation Grace de Monaco (Monaco)  and  Indo-French Center for the Promotion of Advanced Research (CEFIPRA)   IFC/4903-2  to PG and SM, from the  Cerebral Palsy Alliance (Australia)  to SM, JR, LR, BF and PG and from  Agence Nationale de la Recherche  ( ANR, France )  ANR-16-CE03-0006  to LR. The  Kabini Critical Zone Observatory  (Indian sites of the SNO M-TROPICS) from which water samples and analyses were provided is supported by the  French Institute of Research for Development (IRD, France) ,  Institut National des Sciences de l'Univers (CNRS-INSU, France)  and the  Toulouse University. We also thank the  International Atomic Energy Agency (IAEA, Vienna)  for funding the pesticide analysis through the  Coordinated Research  Project  D15018  " Multiple Isotope Fingerprints to Identify Sources and Transport of Agro-.
Density of mature, immature and transitory OSNs Few studies have been devoted to evaluate the density of OSNs, yet this data is important for the analysis and understanding of olfactory dysfunction. In 1981, Hinds et al. calculated the density of OSNs using electron microscopy, based on the count of olfactory knobs on a section passing through the middle of the rat's septal OE. They estimated the density of all OSNs between 60,000 and 120,000/mm²  32. In 1989, Meisami et al. calculated the density of total OSNs from cross-sections of OE by counting the number of non-speci cally counterstained nuclei. They estimated the OSNs cell density at 94170 ± 3950/mm 2 in 25-day-old rats  33. In 1996, Loo et al. described a count of mature and immature OSNs based on the immunostaining technique on atmounted olfactory mucosa  24.
Optimal noninvasive brain stimulation parameters for the treatment of negative symptoms of schizophrenia remain unclear. Here, we aimed to investigate the clinical and biological effects of intermittent theta burst transcranial magnetic stimulation (iTBS) in patients with treatment-resistant negative symptoms of schizophrenia (NCT00875498). In a randomized sham-controlled 2-arm study, 22 patients with schizophrenia and treatment-resistant negative symptoms received 20 sessions of either active (n = 12) or sham (n = 10) iTBS. Sessions were delivered twice a day on 10 consecutive working days. Negative symptom severity was assessed 5 times using the Scale for the Assessment of Negative Symptoms (SANS): before iTBS, after iTBS, and 1, 3, and 6 months after iTBS. As a secondary objective, we explored the acute effects of iTBS on functional connectivity of the left dorsolateral prefrontal cortex (DLPFC) using seed-based resting-state functional connectivity MRI (rsFC fMRI) images acquired before and after iTBS.
Tolerability and blinding The intervention was well tolerated, and no seizures or other lifethreatening events occurred. In both groups, mild headaches were reported during the stimulation sessions. There were two serious adverse events during the follow-up period: two patients from the sham group displayed an exacerbation of positive symptoms requiring hospitalization. Treatment conditions were not correctly classified by either the patients (chi  2  (1, N = 22) = 0. 22, p = 0. 64) or the clinical raters (chi  2  (1, N = 22) = 1. 77, p = 0. 18). Effects of iTBS on left DLPFC seed-based rsFC Among the 22 patients, imaging data from 17 patients were available and analyzed (10 in the active group and 7 in the sham group). Between-group analysis showed no significant rsFC difference between the two groups at baseline.
Extrapyramidal symptoms were assessed in each group with the Simpson-Angus Scale (SAS)  46  , a 10-item scale with item scores ranging from 1 to 5, designed to assess the presence and severity of rigidity and bradykinesia. The protocol was reviewed and approved by a local ethics committee (comitéde protection des personnes-CPP Sud Est 6-AFSSAPS n°2008-A00558-47). All subjects gave their written informed consent after a detailed description of the study by the investigators from our Brain Stimulation Unit (CH Le Vinatier, psychiatric hospital, France). Details of the study were registered on ClinicalTrials. gov (identifier NCT00875498) on April 3, 2009.
Functional MRI (fMRI) data acquisition and preprocessing Images were acquired at the CERMEP imaging center of Lyon (France) on a 1. 5 T Magnetom Siemens scanner with a standard 8-channel head coil. The participants underwent 2 resting-state fMRI scans: the first was acquired on the Friday before starting the iTBS sessions, and the second was acquired 1 h after the end of the 20th iTBS session. The fMRI restingstate data were acquired using a gradient-echo T2*-weighted echo-planar imaging (EPI) sequence with the following parameters: 5 min, 120 volumes, 29 transverse slices, TR = 2500 ms, TE = 50 ms, field of view = 220 mm², and voxel size = 3. 438 × 3. 438 × 4 mm. During the resting sequence, the participants remained in a state of wakeful rest; they were instructed to stay awake and to lie still with their eyes open, fixating on a white cross presented at the center of the visual field.
They were instructed to not fall asleep and to think of nothing in particular. All participants wore headphones to attenuate scanner noise. The fMRI resting-state data were preprocessed and analyzed using the CONN toolbox (v18. b, https://www. nitrc. org/projects/conn) in conjunction with SPM12. After the removal of the first 5 volumes, functional images were realigned (motion estimation and correction), unwarped, and slicetime corrected. Outlier detection was conducted using the artifact detection toolbox. The volumes in which the normalized z-scores from global mean signal intensity exceeded 5 or the composite motion was over 0. 9 mm were identified as outliers. Then, functional images were segmented and spatially normalized into the standard MNI space (Montreal Neurological Institute, Canada) and smoothed using an 8-mm full-width half-maximum (FWHM) Gaussian kernel.
UA surgery is often recommended for treating OSA patients who have refused or cannot tolerate CPAP, and the main result achievable by the surgery is UA expansion, and/or stabilization, and/or tissue removal to different UA levels  [8]. The targeted approach to the surgical care of OSA is not a simple algorithm based on only clinical examination or UA evaluation findings. Multiple factors need to be considered, including the patient's OSA physiologic endotype and clinical phenotype. Findings from each of these features must be incorporated into the best available clinical evidence and patient needs and preferences. These data then allow for a more targeted and customized approach  [13]. This paper aims to analyze the data collected from medical history, sleep studies, and clinical examination, which could help an otorhinolaryngologist in detecting the preponderance of anatomical factors in UA collapsibility and its role in apnea events.