dataesr/scientific-paragraphs-categorization huggingface dataset:
DAtA AnD MethODs Data sources and patients We used two data sources for our study. In order to identify trends in the average number of US examinations per pregnancy, we used the national claims database: the Système National d'Information Inter-Régimes de l'Assurance Maladie. 9 Our data source was the Echantillon Généraliste des Bénéficiaires, a permanent representative sample of 1/97 of the individuals covered by the French Health Insurance System. 10 This representative sample, however, does not allow region-specific analyses. We used data for all women who had delivered between 2006 and 2014 in France. The claims database identifies each episode of care by a code. Codes used to identify US examinations performed during the pregnancy inform on the indication. We included scans for the detection of fetal anomalies (systematic first, second and third trimester US examinations) or scans for the monitoring of a known fetal anomaly, fetal echocardiography.
To assess the trends in the probability of prenatal detection of congenital anomalies, we used data from three French regional registries of birth defects. These public organisations identify cases with congenital anomalies over a predefined area (usually an administrative region). We included three registries-Auvergne, Paris and La Reunion, all members of EUROCAT, the European network for registries of birth defects  11  -and used the standards recommended for this purpose. We included the population of women who gave birth (live birth or fetal loss after 20 WG) or following a TOFPA in the areas covered by these three registries during the study period (2006-2014). We excluded women who were not residents of those areas. A case was defined as a fetus with at least one abnormality whatever the pregnancy outcome was.
Fetal anomalies were the ones listed by EUROCAT (which excludes some minor abnormalities with very low medical or aesthetic impact). 12 In each case, we systematically extracted the time (prenatal or postnatal) of detection and the type of procedure which led to the detection (US examination, first trimester screening for fetal aneuploidy using maternal blood test, invasive procedures). As the aim of our study was to identify the contribution of US examination on detection of fetal anomalies, other modalities leading to a prenatal diagnosis of fetal anomalies, that is, specific Down's syndrome screening, were excluded (estimated risk ≥1/250). ] [15]  Pooling the data of the three registries, the overall detection rate was defined as the ratio of the number of cases detected prenatally (positive screening) to the total number of cases per year.
The detection rate for cases without chromosomal anomalies ranged from 48. 2% to 53. 4%, and was higher in cases of multiple anomalies (70. 4%) than in cases with an isolated anomaly (47. 8%). The logistic regression found a decreasing trend for the overall prenatal detection rate during the study period (OR=0. 985, 95% CI 0. 972 to 0. 997, p=0. 015). Figure  1  represents this trend using moving averages (2-year period). resources leveraged for the us screening for fetal anomalies In the 1/97 sample of the national claims database, we identified between 5888 and 6882 deliveries per year (0. 7%-0. 8% of the total national number of deliveries). The mean maternal age in our sample was similar to the age observed in the national database (source: INSEE  16  ). In 2014, an average of 4. 08 US examinations were performed per pregnancy, for screening and other indications, compared with 3.
2% between 2010 and 2014, considering all categories of US examinations. Additionally, in the French National Perinatal Survey, the proportion of women on whom more than six US examinations were performed during their pregnancy increased from 15. 8% in 1995 to 35. 9% in 2016. In parallel, the proportion of pregnant women with three US examinations decreased from 40. 4% in 2003 to 24. 3% in 2016. This survey is based on self-reported data, which makes it almost impossible to know what kind of US examination was performed. In our study, the database only contained codes used by care providers to record US examinations, and no other clinical information or the precise indications for these examinations. ] [20] [21] [22] [23] [24]  One of our strengths is that we combined data from different registries to estimate the global prenatal detection rate in France.
These papers have confirmed their hypotheses, while the present paper aims at obtaining an equivalent circuit of the PEM EL to emulate during hydrogen production. This approach is similar to the one described in  [14]  that has been carried out for a proton exchange membrane fuel cell (PEMFC); here the model is derived in a suitable current interval to consider its parameters as constants. Only recently, several PEM EL models have been reported in the literature  [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29]. However, the major part of the proposed models is static and does not take into consideration the dynamic behavior of the EL, which is particularly interesting to investigate for power electronics applications. In  [22] , Yigit and Selamet have proposed a dynamic mathematical model developed in a Matlab Simulink environment.
Description of the Experimental Set-Up Once the physical model has been assessed, there is need to acquire experimental data to identify the parameters R1, R2, Rint, C1, C2 and Vint. This was done using a suitable test bench. The developed experimental set-up to analyze the dynamic behavior of the PEM EL and to validate the equivalent dynamic electrical model is shown in Figure  3. It is composed of a DC power supply, a PEM EL, low-pressure metal hydride storage hydrogen tanks and a PC to control the DC power supply. Pure water was supplied to the PEM EL by a pure water tank from (SGWATER, Berlin, Germany). The water flow rate was controlled by a liquid mass flow controller from (HELIOCENTRIS, Berlin, Germany). The range included was between 0 and 7. 5 liters per minute. The water flow rate was controlled automatically according to the operation of the EL.
Description of the Experimental Set-Up Once the physical model has been assessed, there is need to acquire experimental data to identify the parameters R 1 , R 2 , R int , C 1 , C 2 and V int. This was done using a suitable test bench. The developed experimental set-up to analyze the dynamic behavior of the PEM EL and to validate the equivalent dynamic electrical model is shown in Figure  3. It is composed of a DC power supply, a PEM EL, low-pressure metal hydride storage hydrogen tanks and a PC to control the DC power supply. Pure water was supplied to the PEM EL by a pure water tank from (SGWATER, Berlin, Germany). The water flow rate was controlled by a liquid mass flow controller from (HELIOCENTRIS, Berlin, Germany). The range included was between 0 and 7. 5 L per minute. The water flow rate was controlled automatically according to the operation of the EL.
The PEM EL under investigation is the NMH2 1000 from HELIOCENTRIS (HELIOCENTRIS, Berlin, Germany). Although the HELIOCENTRIS NMH2 1000 system includes several ancillary devices (e. g. , power converters), only the stack (and the data acquisition system) has been used in this research. The main characteristics of the PEM EL are provided in Table  1 , while the components of the experimental set up are described in Table  2. During the test, the DC power supply gave a step current to the PEM EL. It was sampled, together with the voltage at the stack terminals, by the digital oscilloscope; data were memorized and elaborated on by the (dSPACE, Bièvres, France) platform to obtain the value of the circuit parameters by the algorithms described in the following section. The PEM EL under investigation is the NMH2 1000 from HELIOCENTRIS (HELIOCENTRIS, Berlin, Germany).
Experimental Test Using the experimental set-up described in the previous section, some tests were performed to obtain a database from which information on the dynamic behavior of the EL could be collected. Specifically, the PEM EL was supplied with step current transients. An example of the voltage and current measured on the EL terminals is shown in Figure  6. In this test, after the power was turned on, the current was increased from 2. 34 A to 4 A at t = 20 s; the duration of the test was equal to 100 s waiting for the end of the transient. Different steps of current were considered for supplying the PEM EL. Energies 2018, 11, x FOR PEER REVIEW 8 of 18 were obtained: Vint = 4. 38 V, Rtot = 0. 441 Ω. From the waveform of Figure  6 , the following considerations can be made: The characteristic resistances Rint can be calculated considering the response after and before the step current and at the end of the transients.
Data collection and variables The following data were collected prospectively by the physician in charge, and recorded on a case report form or on the ORUMIP secured website: demographic data; risk factors (i. e. family history of cardiovascular disease [CVD], smoking, hypertension, diabetes or dyslipidaemia); personal history of CVD (i. e. coronary disease, ischaemic cerebral stroke or distal arteriopathy); clinical data; electrocardiogram; and care timeline. The chosen treatments, reperfusion strategies and adjunctive treatments implemented by the emergency physician were also recorded. For patients admitted to a CICU, the results of coronary angiography and angioplasty, and data on clinical outcomes occurring during hospitalization in the CICU were collected by the cardiologist in charge.
A research assistant checked that case report form data were collected thoroughly. Patients were categorized according to whether they called an MDC or not. Patients who called an MDC were also categorized according to whether or not an MICU intervened. The optimal pathway was confirmed when a patient called an MDC and had an MICU as first medical contact (Fig. 1 ). The other pathways were deemed nonoptimal. The study was conducted by the ORUMIP, in accordance with the principles outlined in the Declaration of Helsinki. This study received the authorization of the French Data Protection Authority (CNIL) (registered number 914329).
Statistical analysis Statistical analyses were conducted using STATA software, release  14   We proposed a two-step analysis to identify factors associated with an optimal care pathway (Fig. 1 ). First, we identified factors associated with calling the MDC when presenting chest pain (binary We used multilevel logistic models  [11] , i. e. generalized linear mixed models with random intercepts, to allow the probability of calling an MDC (analysis 1) or of sending an MICU (analysis 2) to vary between the different MDCs. Indeed, each MDC belongs to a limited geographic area, with its own characteristics in terms of MICU availability and territory. We estimated the intraclass correlation coefficient (ICC), to assess the contribution of the between-MDC variance to the whole variance of the variable response.
Simulated Fault Scenario TRNsys (simulation software) with interface TRNBuild and TRNsys Simulation Studio (graphical front-end) have been used to simulate the building faults. TRNBuild interface allows adding the non-geometrical properties such as wall and layer material properties, window and door properties, thermal conductivity and different gains etc. In the present work, these values are taken from the French building code. Table  4  and Figure  6  show the simulated fault scenario over a data set, namely Batch 1, Batch 2, and Batch 3, for a 24-hour duration. Faults are simulated by adding or tuning different parameters in the fault model. The detail of simulated faults is given below: • open window: using a TRNsys model • unplanned occupancy: considered to be abnormal occupancy, i. e.
Symptoms Analysis for CECP Building This section demonstrates the experimental validation of the proposed diagnosis methodology. The tests were performed for the different building zones which include several offices and meeting rooms. Tests are derived from the one-week data collection from the CECP building. To make a concise explanation only the first 24-hours i. e. , one day with three different scenarios and data set (Batch 1,2 &3), are accounted for in the fault analysis. Table  5  represents the test results in three different scenarios. Conclusions from Table  5  are: • there is no inconsistency between the hours 0 and 5 which confirms the normal building operation. Hour Test1 ( Equation  1 ) Test3 ( Equation  3 ) Conclusion (Test1) Conclusion (Test3) 0-1 K = 0, V = 0 K = 0, V = 0 consistent consistent 1-2 K = 0, V = 0 K = 0, V = 0 consistent consistent 2-3 K = 0, V = 0 K = 0, V = 0 consistent consistent 3-4 K = 0, V = 0 K = 0, V = 0 consistent consistent 4-5 K = 0, V = 0 K = 0, V = 0 consistent consistent 5-6 K = 0, V = 0 K = 0, V = 0 consistent inconsistent 6-7 K = 0, V = 0 K = 0, V = 0 no conclusion inconsistent 7-8 K = 0, V = 0 K = 0, V = 0 no conclusion inconsistent 8-9 K = 0, V = 0 K = 0, V = 0 no conclusion inconsistent 9-10 K = 0, V = 0 K = 0, V = 0 no conclusion inconsistent 10-11 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 11-12 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 12-13 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 13-14 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 14-15 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 15-16 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 16-17 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 17-18 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 18-19 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 19-20 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 20-21 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 21-22 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 22-23 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent 23-24 K = 0, V = 0 K = 0, V = 0 inconsistent inconsistent.
Genetic distance matrix among all genotypes including Ethiopian accessions was estimated by the Jaccard's (1998) coefficient  (Link et al. 1995). Clustering analysis was performed using the matrix distance based on the complement of Jaccard's coefficient employing the Neighbor-joining method. Bootstrap analysis  (Felsenstein 1985)  was performed to evaluate the tree topology reliability for 1000 simulations using FAMD software (Fingerprint Analysis with Missing Data 1. 31)  (Schlüter and Harris 2006). The tree was done in MEGA software (Molecular Evolutionary Genetics Analysis 6. 06)  (Tamura et al. 2013). Analysis of Molecular Variance (AMOVA) was performed to estimate variation within and among genetic groups using SSR polymorphic loci. The analysis was performed using Arlequin 3. 11 software  (Excoffier et al.
Population structure analysis The SSR profile for each genotype was used to perform the principal coordinate analysis (PCoA) and dissimilarity index between C. arabica genotypes in relation to C. canephora and C. eugenioides species. This analyses was performed using GenAlex software version 6. 5  (Peakall and Smouse 2006). Population structure was also estimated using Bayesian clustering method implemented in STRU CTU RE software version 2. 3. 4  (Pritchard et al. 2000). Allele frequencies in each of the K groups (from 2 to 10) were estimated. We used a 10 5 burn-in period and 10 5 interactions MCMC (Markov Chain Monte Carlo), as these parameters resulted in relative stability of the results with 10 runs per K value. The most probable number of populations was estimated based on ΔK values  (Evanno et al.
Acknowledgements This study was financed in part by the  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brazil (CAPES) -Finance Code 001 , and by  CAPES -Agropolis Foundation  under the reference ID  1203-001  through the  "Investissements d'avenir" program  ( Labex Agro :  ANR-10-LABX-0001-01 ). We especially thank the  Brazilian Coffee Research Consortium and INCT Café  for supporting this study. DSD and LFPP acknowledge  CNPq  for the research fellowship. BSRS acknowledge  CAPES and Brazilian Coffee Research Consortium  for fellowships.
0625 g/ml to 2 g/ml. MGIT tubes were each inoculated with 0. 5 ml of a fresh bacterial inoculum suspension prepared from a liquid subculture. Tubes were mixed well and loaded into the MGIT instrument. Growth was monitored by automated fluorometric detection of oxygen consumption and compared with drug-free control tubes containing a 1:100 dilution of the investigated culture suspension. Incubation was stopped when the growth control reached a growth unit (GU) value of 400. At that point, GU values of drug-containing tubes were retrieved from the MGIT instrument software and results were interpreted as follows. If the GU of the drug-containing tube was more than 100 when the GU of the growth control was 400, the result was defined as resistant. If the GU value was equal to or less than 100, the result was considered susceptible.
Determination of intracellular pH using the BCECF-AM dye The effects of inhibitors on ⌬pH were determined using BCECF, a pH-sensitive fluorescent dye activated inside cells via esterase-mediated hydrolysis of BCECF-AM  (46). First, a standard curve was generated as follows. Briefly, M. smegmatis ⌬mmpL3 attB::mmpL3-tb spheroplasts (A 600 ϭ 0. 8) in 1ϫ SMM buffers at various pH levels (6. 0 -8. 0) were incubated with 20 M BCECF-AM at 37 °C for 30 min in the presence of 20 M nigericin. Nigericin is a proton uncoupler and serves to allow equilibration of protons (pH) across the membrane. The buffers also contained 100 mM KCl to ensure a steady membrane potential (⌬). Fluorescence emission ( em 525 nm) intensities of intracellular BCECF were measured following excitation at ex 488 and 440 nm in a SPECTRAmax 250 microplate spectrophotometer equipped with SOFTmax PRO software (Molecular Devices).
Membrane potential measurements in M. smegmatis ⌬mmpL3 attB::mmpL3-tb spheroplasts The effects of inhibitors on ⌬ were determined using the membrane potential-sensitive DiSC3(5) dye  (47). DiSC3(5) binds to energized membranes and becomes quenched. When ⌬ is disrupted, the dye leaves the membrane, resulting in an increase in fluorescence. 1. 5 ml M. smegmatis ⌬mmpL3 attB::mmpL3-tb spheroplasts (A 600 ϭ 0. 8) were used in 1ϫ SMM buffer containing 10 mM glucose and 1 M nigericin (added to remove the effects of ⌬pH). DiSC3(5) was then added to samples to get a final concentration of 5 M and equilibrated for 10 min at room temperature. From this point, fluorescence was continuously monitored with a SPECTRAmax 250 microplate spectrophotometer equipped with SOFTmax PRO software (Molecular Devices), employing an excitation wavelength of 643 nm and an emission wavelength of 666 nm.
3D modeling of MmpL3 and docking studies The MmpL3 three-dimensional homology models of M. tuberculosis (Rv0206) and M. abscessus (MAB_4508) were generated using the Phyre2 server  (48)  and the crystal structure of M. smegmatis MmpL3 as a template (PDB code: 6ajj)  (30). The model geometry was further optimized using the Phenix package  (49). In silico docking of PIPD1 was performed with the PyRx software  (50)  running AutoDock Vina  (51).
This work was supported by  Fondation pour la Recherche Médicale  Grant  DEQ20150331719  (to L. K. ),  French National Research Agency MyCat  Grant  ANR-15-CE18-0007-02  (to L. K. and Y. G. ) and  MyTraM  Grant  ANR-17-CE11-0008-01  (to M. B. ), funds from the  Joachim Herz Foundation  (to F. P. M. ), and a  Singapore Ministry of Education Tier 1 grant  ( National University of Singapore-CNRS Collaborative Track ; to S. S. C. ). The authors declare that they have no conflicts of interest with the contents of this article.
At the age of 9 yr and 10 mo, he came to our attention for persistent fever, weight loss, hepatosplenomegaly, and recurrent lymphadenopathies associated with persistent high blood load of EBV (6. 5 × 10 6 copies/ml; Fig. 1 B ). Episodes resolved spontaneously without treatment in a few weeks. High EBV loads were also detected in a liver biopsy (data not shown). Immunohistochemistry of the liver biopsy showed mild portal infiltration with CD3 + CD8 + mononuclear cells (Fig. 1 D ). In situ hybridization with Epstein-Barr encoding region (EBER) probe was mainly positive in CD3 + cells, while most of CD20 + B cells were negative indicative of liver infiltration by EBV-infected T cells. Hydroa vacciniforme-like lesions also contained accumulation of EBVcontaining CD8 + T cells that hybridized with EBER (Fig.
Identification of a homozygous LOF mutation in TNFRSF9 in both siblings with EBV-infected T cells To identify a gene defect responsible for the disease in the patient and his sister, whole-exome sequencing (WES) was performed in all family members. Because of the consanguinity, an autosomal recessive inheritance pattern of the gene defect was applied to filter WES data with a focus on homozygous genetic variations. One significant homozygous variation in TNFRSF9 was identified in exon 4 (NM_001561. 5), corresponding to a frameshift point deletion that results in a premature stop codon (chromosome 1, g. 7998819delC, c. 170delG, p. G57fsX91; Fig. 1 E ). It predicted to remove a large part of the extracellular, transmembrane, and intracytoplasmic domains of the protein. Sanger sequencing confirmed the WES results; only the patient and his sister were homozygous carriers of the mutation, while the parents were heterozygous (Fig.
1 A ). Other siblings had heterozygous or WT genotypes. This mutation was not present in public WES and whole-genome sequencing databases and our own databases at IMAGINE Institute. TNFRSF9 encodes CD137 (also known as 4-1BB), which belongs to the TNF receptor (TNFR) family  (Wortzman et al. , 2013). CD137 is a costimulatory molecule that is only expressed by activated T cells. When engaged by its ligand (CD137L), CD137 enhances antigen-specific T cell responses, including proliferation, IL-2 secretion, survival, and cytolytic activity  (DeBenedette et al. , 1997 (DeBenedette et al. , , 1999;; Shuford et al. , 1997; Wen et al. , 2002; Bukczynski et al. , 2004). As reported, CD137 expression was only detectable on control T cells that were activated with anti-CD3 antibody, anti-CD3/CD28-coated beads, PHA, or PMA + ionomycin, but not on resting T cells (Fig.
We failed to detect any reversion event in PBMCs and PHAactivated T cells from the sister (as well as from the patient) using Sanger and next-generation sequencing (Fig. S3 ). Therefore, WES results were reanalyzed considering the sister as not affected. One significant missense biallelic mutation in PIK3CD was identified in the patient at position 9783218 (rs573872848) on chromosome 1, (NM_005026. 3 c. 2462G>A) in exon 20 that led to a R821H substitution (Fig. 4 A ). In public WES and wholegenome sequencing databases and own databases, the mutation was only found as heterozygous with a frequency of 3. 8 × 10 -5. The mutation was further verified by Sanger sequencing confirming the autosomal recessive inheritance in the kindred (Fig. 4 B ). Both parents were heterozygous carriers of the mutation as well as the sister and one brother, while the other siblings were not mutated.
These results suggest that there is a physiological balance between PLCγ1 and PI3K-dependent pathways in T cells. Indeed, PLCγ1 and PI3Kδ (p110δ) activities share the same substrate, PIP2, and hence are competing to access to it  (Okkenhaug et al. , 2007). We propose that the skewed signaling toward PLC-γ1 resulting from PIK3CD deficiency may provide a permissive with anti-CD25 antibody as an activation marker. Numbers ahead each peak correspond to the number of divisions. Calculated proliferation indexes from FACS data are shown on the right. (F) Intracellular Ca 2+ levels by real time flow cytometry in T cell blasts or PBMCs of Ctrl. (gray) or Pat. (black line) after stimulation with anti-CD3 and a cross-linker. (G) Same as A, with immunoblots of phosphorylated ERK (P-ERK). (H) Normalized densitometry quantifications of P-ERK immunoblots.