dataesr/scientific-paragraphs-categorization huggingface dataset:
For all the 24 novel and 29 known SNPs, the difference between the SNP effect on eGFRcrea in the diabetes versus the non-diabetes groups was assessed by means of a two-sample t-test for correlated data at a significance level of 0. 05. We used the following twosample t-test for correlated data: t ¼ b DM À b nonDM ð Þ s:e: b DM ð Þ 2 þ s:e: b nonDM ð Þ 2 À 2Âr b DM ; b nonDM ð Þ Â s:e: b DM ð ÞÂs:e: b nonDM ð Þ È É 0:5 ; where b DM and b nonDM represent the SNP effects on log(eGFRcrea) in the two groups, s. e. is the standard error of the estimate and r(. ) indicates the correlation between effects in the two groups, which was estimated as 0. 044 by sampling 100,000 independent SNPs from our DM and nonDM GWAS, after removing known and novel loci associated with eGFRcrea. For a large sample size, as in our case, t follows a standard normal distribution.
All replicated SNPs, as well as SNPs in LD (r 2 40. 2) within ±1 MB distance were checked for their association with other traits according to the NHGRI GWAS catalog  40  (accessed April 14, 2014). SNP assessments in other ethnic groups. We performed cross-ethnicity SNP evaluations in participants of African ancestry from a meta-analysis of African ancestry individuals and from participants of Asian descent from the AGEN consortium  11. African ancestry meta-analysis. We performed fixed-effect meta-analysis of the genome-wide association data from 12 African ancestry studies (Supplementary Table  8 ) with imputation to HapMap reference panel, based on inverse-variance weighting using METAL. Only SNPs with MAF Z0. 01 and imputation quality r 2 Z0. 3 were considered for the meta-analysis. After meta-analysis, we removed SNPs with MAF o0.
05 and which were available in o50% of the studies. Statistical significance was assessed at the standard threshold of 5. 0 Â 10 À 8. Genomic control correction was applied at both the individual study level before metaanalysis and after the meta-analysis. Transethnic meta-analysis. We performed a trans-ethnic meta-analysis of GWAS data from cohorts of different ethnic backgrounds using MANTRA (Meta-Analysis of Trans-ethnic Association studies) software  22. We combined the 48 European ancestry studies that contributed eGFRcrea, which were included in stage 1 discovery meta-analysis, and the 12 African ancestry studies mentioned above for a total sample size of 150,253 samples. We limited our analysis to biallelic SNPs with MAF Z0. 01 and imputation quality r 2 Z0. 3. Relatedness between the 60 studies was estimated using default settings from up to 5.
Expression quantitative trait loci analysis. We identified alias rsIDs and proxies (r 2 40. 8) for our index SNPs using SNAP software across 4 HapMap builds. SNP rsIDs and aliases were searched for primary SNPs and LD proxies against a collected database of expression SNP (eSNP) results. The collected eSNP results met criteria for statistical thresholds for association with gene transcript levels in their respective original analyses (for references see Supplementary Table  11 ). Correlation of selected eSNPs to the best eSNPs per transcript per expression quantitative trait loci (eQTL) data set were assessed by pairwise LD. All results are reported in Supplementary Table  11. DEPICT analysis. In this work, we first used PLINK  42  to identify independently associated SNPs using all SNPs with eGFRcrea association P values o10 À 5 (HapMap release 27 CEU data  43  ; LD r 2 threshold ¼ 0.
01; physical kb threshold ¼ 1,000). We then used the DEPICT method  23  to construct associated regions by mapping genes to independently associated SNPs if they overlapped or resided within LD (r 2 40. 5) distance of a given associated SNP. After merging overlapping regions and discarding regions that mapped within the major histocompatibility complex locus (chromosome 6, base pairs 20,000,000-40,000,000), 124 nonoverlapping regions remained that covered a total of 320 genes. Finally, we ran the DEPICT software program on the 124 regions to prioritize genes that may represent promising candidates for experimental follow up studies, identify reconstituted gene sets that are enriched in genes from associated regions and therefore may provide insight into general kidney function biology, and identify tissue and cell-type annotations in which genes from associated regions are highly expressed.
Briefly, proximal tubule cells derived from an adult human kidney were collected and cross-linked with 1% formaldehyde. Subsequently, ChIP-seq was conducted using whole-cell extract from adult kidney tissue as the input (GSM621638) and assessing the following chromatin marks: H3K36me3 (GSM621634), H3K4me1 (GSM670025), H3K4me3 (GSM621648), H3K9ac (GSM772811) and H3K9me3 (GSM621651). The MACS version 1. 4. 1 (model-based analysis of ChIP-Seq) peak-finding algorithm was used to identify regions of ChIP-Seq enrichment  47. A FDR threshold of enrichment of 0. 01 was used for all data sets. The resulting genomic coordinates in bed format were further used in ChromHMM v1. 06 for chromatin annotation  45. For comparison, the same genomic coordinates were investigated in chromatin annotation maps of renal tissue, as well as across nine different cell lines from the ENCODE Project: umbilical vein endothelial cells (HUVEC), mammary epithelial cells (HMEC), normal epidermal keratinocytes (NHEK), B-lymphoblastoid cells (GM12878), erythrocytic leukemia cells (K562), normal lung fibroblasts (NHLF), skeletal muscle myoblasts (HSMM), embryonic stem cells (H1 ES) and hepatocellular carcinoma cells (HepG2).
Baculovirus titration and total particles quantification Baculovirus infectious particles quantification was performed following the MTT assay, as previously described in  Roldão et al. (2009). Baculovirus total particles concentration was assessed by counting the baculovirus particles in a Nanosight NS500 (Nanosight Ltd. , Salisbury, UK), using the Nanoparticle Tracking Analysis (NTA) software. The average size of purified Inf-VLPs samples and baculovirus was identified a priori for the determination of the gates for both particles quantification (data not shown). To exclude minor errors due to counting of cellular debris, exosomes, and other particles that can interfere with the accuracy of the measurements, appropriate controls were performed (supernatant of non-infected cultures at the correspondent cell densities).
Supplements preparation The culture supplements tested, listed in Table  1 , were selected as boosters of the metabolic pathways correlated with IC-BEVS productivity. Supplements concentration was set taking into account the manufacturer instructions and preliminary assays of their impact in the specific productivity and viability of Sf9 cells (data not shown). Supplements were prepared in Sf900II insect culture media (Gibco), and stored according to the manufacturer instructions. Cholesterol supplementation was performed in combination with 0. 4 mg. L -1 albumin (Merck Millipore, Billerica, MA, USA) as a carrier.
We have recently further improved the speed of the TC-FISH technique and analysis in our laboratory with the development of a semi-automated software (TCScore) that is able to detect IR-induced CAs (dicentrics, rings, acentrics with 4, 2, 0 telomeres) with the same efficacy as manual scoring in a fraction of time  (9). This software provides automated analysis of three-channel (RGB) images (red, green, and blue channels containing telomere, centromere, and DAPI DNA staining information, respectively) split into their individual channels by any image processing software (e. g. , Image J) and generates an intuitive and interactive report of CA classes that can be reviewed and corrected in batches by an investigator. This improved, automated approach will open up new horizons for the assessment of genotoxic risk for clinical uses (e.
The photons emitted after traversal of the foil by the accelerated ions were counted, and a correlation at low fluences/doses was established with the real ion tracks measured on CR39 tracks detectors (C12H18O7)n. After exposure to the beam, the ion tracks in the CR39 were chemically etched for 8-12 min in 12 N KOH at 80°C. Several microscope fields were photographed using an Olympus Vanox-S, ×100, equipped with a Cohn Pieper FK-7512-Q video camera. The tracks were then counted using a homemade image analysis application from the Aphelion ® software. X-ray detector doses were also subsequently correlated with the doses measured with an ionizing chamber (Unidos 23332 or 23344, PTW Freiburg, Germany, depending on the ion atomic number and its track length) for further verification of the dose/fluence ratio.
After counterstaining of the DNA with 4′,6-diamidino-2-phenylindole (DAPI), slides were mounted with coverslips with PPD (1 mg/mL p-phenylenediamine-90% glycerol-10% PBS) and stored in a dark box at -4°C until automated image acquisition using the MetaSystems AutoCapt software. Images of metaphase cells were acquired with a charge-coupled device camera (Zeiss, Thornwood, NY, USA) coupled with a Zeiss Axioplan microscope. CAs were scored manually using the MetaSystems ISIS software.
2007; Judson et al. 2010; Martin et al. 2010 ). Relevant to this paper, these two projects have in common ~ 1,800 chemicals tested in a battery of 18 ER-related assays  (Huang et al. 2014; Judson et al. 2015). This paper describes the results of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP), which was organized by the National Center for Computational Toxicology at the U. S. EPA. The aim of the project was to use ToxCast™/ Tox21 ER HTS assay data to develop and optimize predictive computational models, and to use their predictions to prioritize a large chemical universe of 32,464 unique chemical structures for further testing. Seventeen research groups from the United States and Europe participated in this project. These groups submitted 40 categorical models and 8 continuous models using different QSAR and structure-based approaches.
Available in the U. S. EPA chemical product categories database (CPCat), which is part of the Aggregated Computational Toxicology Resource (ACToR) system  (Dionisio et al. 2015; Judson et al. 2008 Judson et al. , 2012 ; U. S. EPA 2014a). (Gaulton et al. 2012 ). The full data set consisted of > 60,000 entries, including binding, agonist, and antagonist information for ~ 15,000 unique chemical structures. For the purpose of this project, this data set was cleaned and made more consistent by removing in vivo data, cytotoxicity information, and all ambiguous entries (missing values, undefined/nonstandard end points, and unclear units). Only 7,547 chemical structures from the experimental evaluation set that overlapped with the CERAPP prediction set, for a total of 44,641 entries, were kept and made available for download on the U.
2007). The workflow performed a series of curation steps: 1) The original files containing structures in different formats were parsed, checked for valences, and for the integrity of the required structural information to render the molecules. Invalid entries were corrected by retrieving a new structure from online databases using web services  [PubChem (NIH 2015) , ChemSpider (Royal Society of Chemistry 2015)] or removed if ambiguous. 2) The first filter was applied to check for the presence of carbon atoms and remove inorganic compounds. 3) The structures were desalted, and inorganic counterions were removed. 4) The second filter, based on molecular weight, was applied and chemicals exceeding a threshold of 1,000 g/mol were removed to speed up molecular descriptor calculations and model calibration.
" A food reward was used to encourage exploration in the arena. The food reward consisted of a mixture of freeze-dried krill or spirulina flakes that were distributed among all of the grid squares. Fish were introduced individually into an acclimation tube at the safe end nearest to the shoal group since this species of fish is social and this most closely mimics realistic biological conditions. Individuals were acclimated for 2 min before the tube was lifted and the assay began. This arena design allowed us to simultaneously score the time individuals spent in presumptively safe versus risky activities (i. e. , holding vs. exploring) and in safe versus risky locations (near a shoal vs. near a predator). Behaviors were continuously recorded using the JWatcher software (Ver. 1. 0, Macquarie University and UCLA) for 10 min and used to quantify the amount of time required to first leave the release area and begin exploring (lag time), the subsequent amount of time spent swimming around the arena or feeding (exploration time), the percentage of time spent in portion of the arena closest to the shoal (time in safe zone, diagonal dashed area), and the percentage of time in the portion of the arena closest to the predator (time in danger zone, vertical dashed area) (Figure  1 ).
Body size and shape After behavioral assays, individuals were euthanized with a lethal dose of MS-222 (>250 mg L À 1 ), weighed (to 64 mg), and photographed against a grid background with a ruler for scale. Individuals were measured in ImageJ (Ver. 1. 6. 0_20, Rasband and NIH) for total length (mm from tip of snout to tip of caudal fin), and body depth (mm of deepest vertical measure of the body). These 3 different size indexes (mass, length, and depth) were analyzed with MANOVA followed by post hoc t-tests within treatment levels. Shape data were collected from the photographs based on 15 fixed landmarks (Appendix A) adapted from a set used by  Palkovacs et al. (2011) , excluding some spinal and cranial markers, and adding caudal region markers. These landmarks were used for geometric morphometric analyses to summarize overall fish body shape using the program tpsDig2 (Ver.
Acknowledgments We thank  E. P. Palkovacs  for his help in fish collection as well as the  Contra-Costa Mosquito and Vector Control District. We thank  Kevin Simon  for providing friendly review of the manuscript, as well as  Cameron Ghalambor ,  Brian McGill , and others for thoughtful insights. We thank  W. Wright ,  C. Bigos ,  L. Lamb-Wotton , and  R. Lund  for help in the lab.
Data collection Data were collected from consulting patients' medical records and the electronic databases of the ICU and the Department of Medical Biochemistry at our institution. They comprised baseline demographic characteristics, type of admission, severity of illness and comorbidity score, amine and mechanical ventilation use, baseline serum creatinine, starting and cessation dates of RRT in the ICU, weaning date in the ICU, and diuretic use. Baseline serum creatinine was defined as the lowest serum creatinine value in the year before RRT initiation. Baseline glomerular filtration rate (GFR) was estimated according to the Modified Diet in Renal Disease equation  [22]. Severity of illness at ICU admission was assessed on the basis of the Simplified Acute Physiology Score II and Sequential Organ Failure Assessment (SOFA) score.
Statistical analysis Statistical analysis was performed with Stata 13 software (StataCorp, College Station, TX, USA). The tests were two-sided, with a type I error set at α = 0. 05. Variables were presented as medians (interquartile range) for continuous data and as the number of patients and associated percentages for categorical parameters. Comparisons between the weaned and unweaned groups were made by using χ 2 or Fisher's exact tests for categorical variables and Student's t test or the Mann-Whitney U test for quantitative parameters. Assumption of normality was assessed by using the Shapiro-Wilk test, and homoscedasticity was verified by using the Fisher-Snedecor test. To identify independent predictors of IHD weaning, a multivariate logistic regression analysis was performed with IHD weaning as the dependent variable.
In their study, the urine output on the day following the last session was significantly greater in weaned patients (1435 ml/24 h vs. Adjusted for diuretic use 598 ml/24 h). In a post hoc analysis of 529 patients from the BEST study, urine output was the main predictor of successful RRT cessation  [17]. In this analysis, the AUROC of patients without diuretics was 0. 845 and the best threshold was 436 ml/24 h, but the AUROC decreased to 0. 671 with the best threshold at 2330 ml/24 h in patients with diuretics  [17]. In our study, we determined one urine output threshold, which was intermediate (8. 5 ml/kg/24 h or 826 ml/24 h), because 90 % of the patients received no diuretics. However, the physiological data show that the predictive ability of urine output for recovery of renal function is poor.
Furthermore, there was no difference between the patient groups in the percentage of IHD with hypotension requiring fluid challenge or an increase in vasoactive drug use. These data suggest an association between weaned patients and continuous RRT and are consistent with other results that show a beneficial association between continuous RRT and renal recovery  [28] [29] [30]. Our study has a number of limitations. First, the study design was retrospective. However, data analysis from real clinical practice is the first step in finding new and relevant markers. The collection of data was exhaustive, with multiple screening of patients from several different databases. Hence, the possibility of overlooking a patient meeting the inclusion criteria was very low. Although our data collection was exhaustive and the statistical analysis robust, further prospective studies are needed to assess whether our findings can be used to make clinical decisions.
Ab initio calculations Electronic structure calculations were performed using the ORCA 3. 0. 3 soware package and MOLCAS 8. 0. 18 Energies, wavefunctions and spin-Hamiltonian parameters for full and model complexes were calculated by the CASSCF methodology. The spin-orbit effects were included in both programs using quasi-degenerate perturbation theory (QDPT) in ORCA and restricted active space state interaction (RASSI) approach with MOLCAS program. The def2-TZVP basis set 19a,b and ANO-RCC 19c,d basis were employed with ORCA and MOLCAS, respectively. Such methods comprise two steps: (i) a CASSCF calculation is performed to obtain the non-relativistic states and energies of the system and (ii) state mixing by the Spin-Orbit Coupling (SOC) operator. Dynamical correlation was introduced by the N-electron valence perturbation theory (NEVPT2).
As expected, the theoretical cT vs. T data calculated using MOLCAS code 18 (blue line in Fig. 5 ) compare qualitatively very well with the experimental data (it is worth noting that the higher theoretical cT value is due to the larger calculated g av value; see Electronic structure calculations section). At lower temperatures and as already detected by EPR (vide supra), the marked decrease of the cT product reveals the presence of antiferromagnetic interactions between Mn(IV) complexes. These intermolecular interactions were evaluated at À0. 6(1) K (zJ/k B ) by simulating the experimental data in the frame of the Fig. 4  High-resolution Mn 2p spectra of (a) PhB(MesIm) 3 Mn^N (2) and (c) PhB(MesIm) 3 MnCl (1). The black line represents the experimental data, the red line shows the fit, and the blue and green lines represent Mn 2p 3/2 and Mn 2p 1/2 components, respectively, while the brown line represents shake-up satellites.
See Table  S3  † for fitting parameters. High-resolution Mn 3s spectra of (b) PhB(MesIm) 3 Mn^N (2) and (d) PhB(MesIm) 3 MnCl (1). The black line represents the experimental data, the red line shows fit, and the blue and green lines represent Mn 3s split components. See Table  S4  † for fitting parameters. mean-eld approximation 29 applied to the scaled (Â0. 88) MOLCAS cT vs. values (red line in Fig. 5 ). The eld dependences of the magnetization below 8 K (inset Fig. 5 ) are also in good agreement with an S ¼ 1/2 species (M ¼ 1. 05 m B at 7 T & 1. 85 K). The t of the experimental data with an S ¼ 1/2 Brillouin function conrms an average g factor around 2. 10(2), which is in perfect agreement with that deduced from EPR (g av ¼ 2. 096, vide supra). The magnetization dynamics of this manganese nitride complex were probed by ac susceptibility measurements.
Electronic structure calculations The magnetic properties of the low-lying states of 2 were further analysed by means of an ab initio multireference methodology. A symmetrized model complex was rst studied to obtain a qualitative description of the ground state nature of 2 and then these conclusions were corroborated by calculations of the full complex. The model complex was constructed from its original geometry, where the aryl groups were replaced with methyl substituents, symmetrizing the structure to the C 3v group. Initial CASSCF (3,5) calculations for the model system using the ORCA code indicate the following orbital sequence (obtained with the AILFT theory, see ab initio calculations section): d xy and d x 2 Ày 2 at a reference energy (i. e. 0. 0 cm À1 ), d z 2 at 31 000 cm À1 and (d xy , d xz ) at 32 500 cm À1 (which is equivalent to the orbital diagram of Fig.
Equivalent CASSCF + RASSI calculations performed with MOLCAS code provide similar values with a rst excited Kramers doublet at 1932 cm À1 (2800 K) and g x ¼ 1. 927, g y ¼ 1. 933 and g z ¼ 2. 790 values (i. e. g av ¼ 2. 217; as mentioned above the calculated g av values is systematically slightly larger than the experimental one, around 2. 1, which explains the difference between experimental and calculated magnetic susceptibility exemplied in Fig. 5 ). This CASSCF + RASSI approach was also used to estimate the possible relaxation mechanisms considering the two lowest Kramers doublets (Fig. 9 inset ). As expected due to their large energy separation, thermally activated mechanisms of relaxation, e. g. Orbach, cannot be relevant at low temperatures. Thus, the magnetic dynamics in 2 should only involve the ground Kramers' doublet, allowing possible quantum tunnelling (QTM), direct and Raman mechanisms.
Acknowledgements M. D. and J. M. S. acknowledge funding from  Indiana University  and the  NSF  ( CHE-1112299 ). R. C. , P. D. and M. R. thank the  University of Bordeaux , the  ANR , the  Conseil Régional d'Aquitaine , and the  CNRS  for nancial support. The XPS was funded by the  NSF  ( DMR MRI-1126394 ). We thank the  IU Nanoscale Characterization Facility  for access to this instrument. Chem-MatCARS Sector 15 is principally supported by the  National Science Foundation/Department of Energy  under grant number  NSF/CHE-0822838. Use of the Advanced Photon Source  was supported by the  U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences , under Contract No. DE-AC02-06CH11357. G. E. C. acknowledges  Prof. Brian M. Hoffman  ( Northwestern University ) for access to instrumentation and funding ( NIH GM111097 ).
Methods This prospective, multicenter, longitudinal, observational study was conducted at 48 sites in metropolitan France from October 2011 to October 2014. The study protocol was approved by an independent scientific committee and by the French National Authority for Health and the study was conducted in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. All patients provided written informed consent prior to study recruitment and enrollment. The study is registered at ClinicalTrials. gov with the identifier NCT01618266.