dataesr/scientific-paragraphs-categorization huggingface dataset:
20 in a multivariate logistic regression model. We performed backwards stepwise selection for the final variable selection. The final measure of associations presented is the adjusted odds ratio (aOR) and its 95% CIs and P-value. We assessed risk factors for stillbirth (>28WG) and early neonatal death, but not for late and extended neonatal death due to an insufficient number of events. Prematurity status was not available in BIRDY1, so we used low birth weight (<2500g) as a proxy for prematurity in these analyses. Overall, we determined that 1% of data were missing due to non-random reasons (i. e. , due to greater omission among sex and birth weight variables in stillborn/dead babies). We handled this missing data using multiple imputations  [13]  for 63 cases following the procedure described by Von Hippel  [14].
This is particularly important for settings like Madagascar, where nearly 40% of women delivered outside of health facilities. We estimated stillbirth incidences at 11 per 1000 total births in Cambodia, 15 per 1000 in Madagascar and 12 per 1000 in Senegal. Between 30% and 62% of stillbirths were intrapartum. These results are in line with data from recent population-based surveys, which have estimated the incidence of stillbirth to be 6 per 1000 in Cambodia (2014), 14 per 1000 in Madagascar (2008), and 18 per 1000 in Senegal (2018)  [15] [16] [17]. Although estimated antepartum stillbirth rates in our study are high, they may nonetheless be underestimated: we included 33% of mothers after 37 WG, so antepartum stillbirths that occurred before potential enrolment were not documented. Earlier systematic recruitment may improve the accuracy of stillbirth incidence estimates (e.
g. , with preconception cohorts). This type of study has previously been implemented in Benin, with gestational age at recruitment of approximately 7 WG, but with a high rate of loss to follow-up that limits the reliability of the data  [18]. We estimated neonatal mortality at 18 per 1000 live births in Cambodia, 24 per 1000 in Madagascar and 23 per 1000 in Senegal. These results are also in line with the most recently available population-based surveys (18 per 1000 in Cambodia, 25 per 1000 in Madagascar, and 21 per 1000 in Senegal) [2,6,12]. Comparatively low incidence in Cambodia reflects that this country has had one of the greatest declines in neonatal mortality recorded globally over the past two decades, reported as the result of improvements in the quality of prenatal care provided by trained health professionals, the introduction of tetanus toxoid injections during pregnancy, an increase in women's use of contraception resulting in an increase in the proportion of long-interval births, and a decrease in the proportion of women carrying children at risky ages  [19].
Acknowledgements: We are grateful to all mothers and their newborns for their participation. We thank all the physicians, laboratory staff, field investigators and community workers for their participation in this project, as well as all the BIRDY project collaborators. We thank David R. M. Smith for his critical review of the article and for proofreading the English. Data availability: Data cannot be shared publicly because data privacy is subject to French, Cambodian, Senegalese and Malagasy regulations. Data are available from the Ethics Committee (contact via irb@pasteur. fr) for researchers who meet the criteria for access to confidential data. Funding: The present work was supported by internal resources from Paris-Sud University.
The software for analysis was PDXL2 coming together with the XRD device. The peaks were identified using International Centre for Diffraction Data ICDD (PDF-4 + 2023). The pH pzc of the biochars was determined by adding 20. 00 mL of 0. 050 mol/L NaCl with a previously adjusted initial pH (the initial pH (pH i ). The pH of NaCl solution was adjusted from 2. 0 to 10. 0 by adding 0. 10 mol/L of HCl and NaOH to several 50. 0 mL falcon tubes containing 50. 0 mg of biochars (Biochar and Se-Biochar in separate tubes). The suspensions were shaken in an acclimatized shaker at 298 K and allowed to equilibrate for 48 h. The suspensions were then centrifuged at 10,000 rpm for 10 min to separate the biochars from the  aqueous solution. The pH i of the solutions was accurately measured using the solutions that had no contact with the solid adsorbents; the final pH (pH f ) values of the supernatant after contact with the solid were recorded.
Acknowledgments Dr. dos Reis thanks Bio4Energy -a  Strategic Research Environment  appointed by the  Swedish government  and the  Swedish University of Agricultural Sciences , for the funding support. Dr. Alejandro Grimm  acknowledges financial support from the  Swedish Research Council FORMAS  ( 2021-00877 ). The authors are grateful to the  Distinguished Scientist Fellowship Program (DSFP)  from  King Saud University, Riyadh ,  Saudi Arabia , for the financial support. E. C. Lima  thanks to  CNPq and FINEP  for financial support. The FT-IR and Raman measurements were performed at the  Vibrational Spectroscopy Core Facility (ViSp), Chemical Biological Centre (KBC) ,  Umeå University.
Phase 3 comprised an online quantitative survey, designed to take no longer than 30 min, that was completed by HCPs involved in the management of adult patients with chronic IF across these 12 European countries. The survey design and questions were developed with the assistance of the ATLAS steering committee based on outcomes from the Phase 2 interviews (see Supplementary File 1 for full survey). Data from Phase 3 were collected between November 2020 and January 2021 and are the focus of this paper.
Data collection In Phase 2, audio-recorded interviews were transcribed, and deidentified transcripts were uploaded into the Atlas. ti online research tool (https://atlasti. com/) to facilitate the organisation and analysis of qualitative data. In Phase 3, quantitative anonymised data were collected using a closed-ended, online survey instrument hosted on the Qualtrics platform operating system for experience management. The survey was developed in English and translated into the language(s) of each selected country, as required. Data security was fully compliant with the European Union's General Data Protection Regulation.
Mineralogical and microscopic characterization of water-saturated bentonite microcosms and selenium nanoparticles (SeNPs) Se-treated microcosm samples were analyzed by Variable Pressure Field Emission Scanning Electron Microscopy (VP-FESEM) ZeissSupra 40VP equipped with secondary electron (SE) and backscattered electron (BSE) detectors. This microscope is coupled with a microanalysis system (Aztec 2. 2) to deliver elemental composition data by Energy Dispersive X-ray (EDX) and equipped with Raman spectrometer Renishaw In Via fitted with a Nd:YAG 532 nm laser and a near-infrared diode 785 nm laser, with 500 mW and 100 mW as maximum powers, respectively  (Guerra and Cardell, 2015). Additional ultrastructural features on the SeNPs and water-saturated bentonite were determined using Scanning Transmission Electron Microscope (STEM; FEI TITAN G2 80-300) equipped with an EDX spectrometer working at 300 kV and a High-Angle Annular Dark Field (HAADF) detector.
X-ray Absorption Spectroscopy (XAS) analysis of the Se-bentonite samples For XAS experiments the supernatant layers of the Se(IV)-amended bentonites microcosmos samples were collected, dried, and powdered. The powdered samples were prepared by spreading and pressing them onto 10 mm × 3 mm area of Kapton tape, which was sealed between additional layers. Selenium references (sodium selenate (Se VI ), sodium selenite (Se IV ) and Se 0 foil) were prepared as it was described in  Ruiz--Fresneda et al. (2020). Their XAS data were collected in transmission mode. Se K-edge XAS of the studied samples were collected at the MARS beamline at the SOLEIL synchrotron facility, which is the French bending magnet beamline dedicated to Multi Analyses on radioactive materials  (Sitaud et al. , 2012). For the experiment, the ring was operated at 2.
75 GeV in 8-bunch mode (100 mA). The optics consisted on a double-crystal monochromator with horizontal dynamical focusing set to the Si (220) crystals, and -coated mirrors for vertical focusing and rejection of higher harmonics set to the Si strips  (Solari et al. , 2009). Spectra were collected in fluorescence mode using a 13-element Ge detector (EG & G ORTEC, USA). Data were processed following standard procedures by using the Athena codes  (Ravel and Newville, 2005). Background removal was performed by means of a pre-edge linear function. Atomic absorption was simulated with a square-spline function. The theoretical phase and amplitude functions used in data analysis were calculated with FEFF8  (Ankudinov et al. , 1998)  using the trigonal Se as atomic model. The amplitude reduction factor (S0 2 ) was held constant at 1.
Computational processing of the bacterial diversity and biostatistical analyses Analyses of all FastaQ files were achieved using dada2 package in R (www. r-project. org) resulting in a unique table containing the sequence reads and abundances of all microcosms samples. Normalization was performed using the "phyloseq" package returning 354 phylotypes. Sequence reads were assigned to a taxonomic affiliation based on the Bayesian classification, establishing 80% pseudo-bootstrap threshold. Relative abundances of phylum, class, order, family and genus were obtained by Explicet 2. 10. 5 software  (Robertson et al. , 2013). Alpha diversity was calculated to the lowest sample size (1006) and bootstrapped 100 times. Specific differences in the bacterial community structure were further visualized in a heatmap using the heatmap.
2 function in the R gplots v. 3. 0. 1. 1 package  (Warnes et al. , 2019)  including only taxa at ≥ 1% relative abundance in at least one sample. At the genus level, microbial community composition was analyzed using PAST3 v. 3. 18 and the output was visualized with Principal Components Analysis (PCA) and Principal Coordinate Analysis (PCoA). Significant differences in taxa relative abundance (p < 0. 05) between the different samples were determined using a one-way ANOVA test. In addition, a Tukey posthoc test was used to test for significant differences in relative taxa abundance (p < 0. 05) between treatments for the total community.
Changes in microbial diversity of saturated-bentonite microcosms induced by sodium selenite Total DNA of water-saturated bentonite microcosms was sequenced obtaining large diversity data of the microbial communities. Sterile bentonite samples (Bs) failed in the PCR amplification. A total of 355 OTUs were classified at phylum (97. 9%), class (92%), order (91. 1%), family (87. 1%) and genus (79. 5%) levels. Richness (S), evenness and diversity of all the sequenced samples at each phylotype level were calculated using diversity indices (Shannon, Shannon's evenness, and Simpson) indicating a high bacterial diversity (ShannonD and SimpsonD) and a highly uniform distribution of OTUs (ShannonE) among the microcosms' microbial communities (Supplementary Fig. S5 , Supplementary Table  S2 ). Sequences belonging to Archaea and Bacteria were identified.
Acknowledgments This work was supported by grant  RTI2018. 101548. B. I00  to M. L. M. We acknowledge the assistance of  Concepción Hernández-Castillo  for the preparation of samples for microscopic analyses, and members of  Centro de Instrumentación Científica (University of Granada, Spain ). AL and RVV are supported by the funds of  European Commission  through the " European funds for regional development" (EFRE ) as well as by the  regional Ministry of Economy ,  Science and Digitalization of Saxony-Anhalt as part of the "Autonomy in old Age" (AiA) research group for "LiLife" Project (Project ID :  ZS/2018/11/95324 ). Funding for open access charge:  Universidad de Granada / CBUA.
Study design The GPS Registry (NCT05027685) is a multicenter, single-arm, observational study (Fig. 1 ). Up to 200 study centers from areas where the Paradise System (Recor Medical, Palo Alto, USA) is available will enroll patients, including but not limited to the European Union, the United Kingdom, Switzerland and Monaco. Additional locations may be added to the GPS Registry over time. Monitoring of study sites will be performed during the registry to assess continued adherence to the protocol and applicable regulations. The recommended follow-up is 5 years. All national and local approvals will be obtained prior to beginning the study. Any additional requirements imposed by the institutional review board/ethics committee (IRB/EC) or regulatory authority will be followed where appropriate.
Study population Based on the international guidelines that have been recently published, patients qualifying for renal denervation should have been unsuccessful in controlling their blood pressure with lifestyle changes and antihypertensive medications. Patients selected for uRDN with the Paradise System as per routine clinical practice on patient selection for renal denervation can be enrolled in the registry. The goal of the study is to collect real-world data on current clinical practices at each participating site. Full details of the study inclusion and exclusion criteria are shown in Table  1. For prospectively enrolled patients, the uRDN procedure is to be scheduled within 30 days of registry enrollment, while retrospectively enrolled patients need to have undergone uRDN within the previous 6 months.
Assessments and data collection Follow-up visits are scheduled at 3, 6, and 12 months after the uRDN procedure and every 12 months thereafter. Each visit will include medical review, measurement of office BP, medication name and dose). Ambulatory BP data (mean values, heart rate, standard deviation) obtained during routine clinical practice at study centers (including daytime, nighttime and 24-h BP) will be recorded and assigned to the nearest follow-up visit. Other data collected during routine clinical practice will also be reviewed as part of patient follow-up, including any of the following: physical parameters including body weight, HR, seated and standing office BP; smoking status during follow-up, socioeconomic, and healthcare resource use parameters; electrocardiogram; non-invasive cardiac imaging; urinalysis including micro/macroalbuminuria; blood chemistry (serum creatinine, electrolytes, blood glucose and HbA1c, blood lipids); non-invasive renal artery imaging; any other cardiovascular procedures and treatments including glucose-and cholesterol-lowering drugs and antiplatelet/ anticoagulant use, and the occurrence of any cardiovascular/ cerebrovascular event (MI, HF, AF, etc.
Home blood pressure All clinical sites will be provided with validated, commercially available, validated telemetric home BP monitoring (HBPM) devices BPM Connect Pro, WITHING, Issy-les-Moulineaux, France)  [19]. The collection of home blood pressure with this WITHING device is specific to the execution of the study and is not currently part of the sites' routine clinical practice. Prospectively enrolled subjects who elect to be part of HBPM data collection will be provided with a device and will be instructed to record their home BP according to the American Heart Association and American Medical Assocation  [20]  for seven consecutive days prior to the uRDN procedure. Over this period, subjects will take two measurements in the morning and two measurements in the evening. Consistent with current recommendations  [20, 21] , patients will be instructed to avoid smoking, caffeinated beverages, or exercise in the 30 min prior to home BP measurement, to take readings in a quiet room after sitting quietly for 5 min, to sit with their back straight and supported and feet flat on the floor with the arm supported on a flat surface and the upper arm at heart level.
The same arm with the highest BP determined previously will be used for all home BP measurements, and at least two measurements should be taken 1-2 min apart before taking medications in the morning, and before taking medications and before dinner in the evening. All home BP measurements will be transmitted automatically via cellular or wifi signal by the HBPM device to a dedicated secured cloud-based platform (Study Pal; DELVE; www. delve health. com), which is GDPR 2016/679 compliant. The use of this integrated Global System for Mobile communication functionality removes the need and burden for participants to record home BP measurements in a diary. Subjects will be reminded by automatic text message to measure their home BP if their home BP assessment is incomplete. Ideally seven-but a minimum of 3-day HBPM data (at least twelve valid measurements) are recommended prior to the procedure.
Patients participating in home BP data collection will measure their home BP every 3 months during follow-up, ideally over 7 days of measurements with four readings per day prior each visit at the study site. If insufficient baseline home BP data are collected, no additional home BP data will be collected for that patient. Subjects who are unwilling and/or unable to comply with HBPM requirements will not take part in HBPM data collection but will continue to be part of the registry. Retrospectively enrolled subjects will not be provided with a HBPM device, and any available BP data (office, HBP, ABPM) from prior to the uRDN procedure will be collected retrospectively.
Data collection and storage Subject data will be collected into an electronic data capture system. The data will be monitored and audited for data collection to assess continued compliance with the protocol and applicable regulations to ensure the integrity of the data. Data processing will be performed in compliance with the European Union General Data Protection Regulation (GDPR) 2016/679, and all applicable national laws to ensure data governance policies and guidelines, including data ownership, data access, data sharing, and data use agreements are managed properly.
Sample size The sample size for the Registry is based on the intent to characterize the safety and effectiveness data in a real-world patient population. The target is to enroll up to 3000 patients at up to 200 sites globally and follow them up to 5 years after enrollment. This sample size should provide a high degree of statistical precision on home and office blood pressure changes and a high probability of observing rare safety events; with a sample size of 3000 subjects, there is a 95% probability of observing events that occur at a population rate as low as 0. 1%.
Statistical analysis Every effort will be made to minimize the amount of missing data. Statistical analyses will be descriptive. Continuous variables will be summarized as mean ± standard deviations and median (range) with interquartile range. Categorical variables will be summarized as frequencies and percentages. Analysis of clinical effectiveness and safety (Table  2 ) data will be performed on the total study population and in clinically relevant participant subgroups (e. g. , based on age, history of chronic kidney disease, heart failure, atrial fibrillation, sleep apnea, diabetes mellitus, etc. ). An additional analysis will determine whether BP parameters can help predict patients that may be more likely to respond to uRDN. Subgroup analyses and multivariable analyses will be performed.
The GPS Registry will provide the unique opportunity to assess teletransmitted home BP every 3 months with a dedicated telemetric device. Out-of-office home BP measurements are more reproducible than office measurements and are more closely associated with hypertension mediated organ damage (HMOD) and the risk of cardiovascular events and are thus recommended by several hypertension management guidelines  [6, 8, 20]. Furthermore, the use of HBPM will facilitate increased data collection in patients over time to see how their BP evolves following uRDN. It will also permit ongoing data collection in the GPS Registry even in the event of further outbreaks of the COVID-19 or other pandemic  [29]. As has been shown, one of the biggest limitations of a registry is losing subjects to follow-up. A benefit of collecting home BP is that the data will be automatically uploaded to the cloud, which will enable better long-term follow-up of patients regardless of attendance for office visits and it will allow for the collection of BP between the visits.
Literature review and studies included The PubMed database was searched until March 2022. We included the following articles: randomized controlled trials (RCTs), prospective studies (uncontrolled or observational) irrespective of number of patients, and retrospective studies including more than 5 cases, and registry data, all restricted to human studies in English, as summarized in Tables 1 and 2  [1-3, 5, 24-37].
Acknowledgements This work was supported by members (JB, DH, CPS, JVD, BR) of the  European Reference Network for Rare Kidney Diseases (ERK-Net ). The authors also acknowledge the valuable contributions of two experts in neonatology and neonatal intensive care,  Pr Silvia Iacobelli (MD, PhD ,  CHU La Réunion, Site Sud, Saint Pierre, France ) and  Pr Helmut Küster (MD, Clinic for Paediatric Cardiology, Intensive Care and Neonatology, University Medical Center Göttingen, Germany)  in the reviewing of the manuscript. The authors also acknowledge the valuable contributions of the expert panel who participated in the Delphi technique.
2-3 Data collection The questionnaire was designed and entered into the KoboCollect application (KoBoToolbox™, Cambridge, USA). It included sociodemographic data (age, gender, living area, education level, marital status, main activity, household size, monthly income and source of income), disease status (cancer, diabetes, hypertension, cardiovascular disease, tuberculosis, asthma, epilepsy and HIV infection) and the number of drugs taken, and these information's were obtained from statements, and we checked health records to ensure the information provided. Blood pressure was measured using an electronic upper-arm blood pressure monitor (Omron™ Paris, France and M3-HEM 7131-E™ Kyoto Japan). Three measurements were taken for each arm and the mean was then calculated. Hypertension was determined as a systolic pressure ≥ 140 mmHg and/or a diastolic pressure ≥ 90 mmHg  10.
2-4 Statistical analysis Data were analysed using SPSS software version 26 (SPSS, Chicago, USA). Continuous variables were expressed as means and standard deviations (SD) and categorical variables as numbers and percentages (n/%). Normality was tested using the Shapiro-Wilk test. Anova and Kruskal-Wallis tests were used to compare quantitative variables and the Chi-squared test to compare categorical variables. Multivariate analyses were performed to determine the associations between the nutritional status and possible associated factors (socio-demographic and medical variables). The dependent variable (undernutrition, normal/overweight and obesity) was categorised using multinomial logistic regression analysis  15. Variables with p < 0. 25 calculated by univariate analysis were included in the multivariate initial model and a step-by-step descending procedure was used.
The release of 19 discriminant aroma compounds whose MH + masses ranged from m/z 49. 011 (methanethiol) to m/z 143. 145 (nonanal) was followed and 6 predefined sensory attributes ('fruity', 'dry fruit', 'roasted', 'woody', 'cocoa', 'spicy') were evaluated as dominant sensations (TDS) or citable attributes (TCATA). The three chocolate samples were clearly distinguished at the nosespace and sensory levels, whatever the temporal sensory method used  [53]. CA of AWD indices calculated for each sensory method allowed to draw the same conclusions as previously stated. The links between ions and dominant sensations (TDS) or cited attributes (TCATA) displayed various combinatorial codes of aromas that could explain the different perceptions, allowing samples differentiation  [53]. However, a multiblock analysis of the paired aroma release and sensory temporal data revealed that the chocolates discrimination obtained with TDS was more similar to the discrimination displayed in nosespace than the TCATA one  [136].