dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Analysis The data were analyzed using the SPSS 20. 0 statistical package. The sample was characterized using descriptive statistics, namely central tendency (mean) and dispersion (standard deviation) measures. The Shapiro-Wilk and Levene tests were used to verify sample normality and homogeneity of variances, respectively  [21]. Pearson's correlation was applied to determine the association between PAL and the parameters of mental health and quality of life. A p-value < 0. 05 was considered significant.
Structural model of the isolated AC domain SAXS data from the free AC protein were initially modeled, starting from the atomic coordinates of AC extracted from the Protein Data Bank (pdb) dataset 1YRU of the crystal structure of AC in complex with the C-CaM  [7]. Using AllosModFoxs  [11] , we adjusted the calculated scattering profile against experimental SAXS data by refining the proposed position of the missing residues in 1YRU (residues 226-232, defined as the Hom-loop, and the first six N-terminal residues), while keeping the AC structure unchanged. An example of one of the fits (χ 2 = 2. 57) obtained in this way is shown in  other hand, appears poorly structured: the few regions exhibiting dynamic HDX-MS behavior cover the I-and J/J 0 -helices and the second beta-sheet of the T18 fragment (T18b2) region, respectively.
The helical content of AC was estimated from the SR-CD spectrum (S2 Fig)  using  the BestSel software  [12]  and compared to that of the crystal structure using the Dictionary of Secondary Structure of Proteins (DSSP) algorithm  [13, 14]  (S2-S4 Tables  and S2 Data ). The analysis of SR-CD data indicate that 27% of all residues are part of helical secondary structures, a value significantly lower than the 36% value derived from the X-ray structure using DSSP. However, the SR-CD value favorably compares with HDX-MS results, in which the region corresponding to F-, G-, H-and H 0 -helices and the T18b1 appear to be disordered in solution (Fig  2A ). Taking into account these results from HDX-MS and far-UV SR-CD, the residues from 200-270 were released and allowed to move in SAXS modeling to obtain a new set of models and associated fits, an example of which is shown in  ).
Ten thousand conformations were generated by the Ranch program, starting from the structures of each Ca 2+ -bound domain determined in solution from NMR data by Chou and colleagues (pdb files 1J7O and 1J7P for N-and C-terminal domains, respectively  [23] ). Residues in the center of the inter-domain helix were described as dummy residues with variable positions. These dummy residues were substituted by a full-atom description using the program PD2  [24]. At this point, the Gajoe program was used to select ensembles of conformations, the average scattering pattern of them being fitted against our experimental data using a genetic algorithm. Fig  3D  shows a typical ensemble of conformations that yields a good fit to the experimental data (χ 2 = 2. 15, red curve). This ensemble of conformations illustrates that CaM is made of two folded lobes connected by a highly flexible hinge.
AC-CaM complex in solution Reciprocally, we examined the consequences of AC binding for CaM structural dynamics. HDX-MS data show that AC binding induces a strong stabilization of C-CaM, as evidenced by the dramatic reduction in accessibility imposed by the wrapping of C-CaM helices around the H-helix region of AC  (Fig 4B and S6 Fig). The loop between the first two helices, H5 and H6, of C-CaM is also significantly stabilized, likely via interactions with the J/J 0 -helices and the Cterminal loop of AC. The involvement, beyond the CBS-containing H-helix, of various regions of AC in CaM stabilization is best illustrated by the "difference of uptake differences" plot (Fig  4C ). In contrast, the majority of N-CaM is unaffected, besides peptide 38-48, which covers the loop connecting helices H2 and H3.
Moreover, these residues are not predicted to adopt a helical conformation by secondary structure predictions. Accordingly, we assumed that the two helices are strongly stabilized within the crystal but may only transiently exist in solution. Therefore, we released the position of residues 200-234 of AC so that this stretch was also variable during the refinement process. Thirty runs of the program BUNCH yielded models similar to that shown in S7 The high flexibility of the central CaM linker suggests that a better description of the complex would make use of an ensemble of conformations (as opposed to a unique structural model). Accordingly, we undertook a second round of complex modeling using the program.
Aliquots of 10-20 pmol of protein were withdrawn at each time point and quenched upon mixing of the deuterated sample with ice-cold 0. 5% formic acid solution to achieve a final pH of 2. 5. Quenched samples were immediately snap frozen in liquid nitrogen and stored at -80˚C for approximately 12 h. Undeuterated controls were treated using an identical procedure. All MS-analyses were performed in triplicate for each time point and condition. HDX-MS data acquisition. Prior to MS analysis, samples were rapidly thawed. To minimize back exchange, the LC solvent line, injection valve, columns, and sample loop were maintained at 0˚C. To achieve this, HDX-MS analyses were performed with the aid of a cooled HDX Manager (Waters Corporation, Milford, MA). Labeled samples were digested using an in-house prepared cartridge of immobilized pepsin beads (Thermo Scientific, Rockford, IL) for 2 min at 70 μL/min and 20˚C.
For local-level analysis, unlabeled AC and CaM samples were digested in triplicate to obtain a peptide coverage map of both proteins. HDX-MS data processing. Peptide identification was via the Protein Lynx Global Server (PLGS) 3. 0 (Waters Corporation). Oxidation of methionines and carbamylation of N-terminal and lysine residues were set as variable modifications. The sequence coverage map was plotted using DynamX 3. 0 HDX software (Waters Corporation). D 2 O uptake at the peptide level was extracted and visualized in DynamX; only one charge state was considered per peptide. No adjustment was made for back exchange, and the results were reported as relative deuterium exchange levels expressed in either mass unit or fractional exchange. Fractional exchange data were calculated by dividing the experimentally measured uptake by the theoretically maximum number of exchangeable backbone amide hydrogens that could be replaced within each peptide.
Small angle X-ray scattering Data acquisition. X-ray scattering data were collected at the SWING beamline of the SOLEIL Synchrotron (Saint-Aubin, France). All measurements were performed using a sizeexclusion HPLC column (Agilent BioSEC-3, 300 Å, 4. 6 Ã 300 mm) online with the SAXS measuring cell, a 1. 5-mm diameter quartz capillary contained in an evacuated vessel  [52]. The sample to detector distance was 1,988 mm, allowing useful data collection in the q range 0. 006 Å -1 < q < 0. 5 Å -1 , for which q = 4πsinθ/λ, 2θ is the scattering angle, and λ = 1. 00 Å, the wavelength of the X-rays. We first studied solutions of isolated AC364 and CaM proteins. We then examined solutions of CaM in complex with either H-helix peptide (both 5:1 and 3:1 ratios of peptide:CaM), P MLCK (3:1 ratio of peptide:CaM), or AC364 (1:2 and 1:4 ratios of AC364:CaM).
All proteins were analyzed in Buffer A. Scattering of the elution buffer before void volume was recorded and used as buffer scattering for subtraction from all protein patterns. Successive frames of 1 s were recorded and separated by a 0. 5-s interval. The elution flow of 0. 200 mL/ min ensured that no protein was irradiated for more than 0. 4 s. For each frame, the protein concentration (about 1-2 mg/mL at the top of elution peak) was estimated from UV absorption at 280 and 295 nm using a spectrometer located immediately upstream of the SAXS measuring cell. Data analysis. Scattered intensities were put on an absolute scale using water scattering. SAXS data were normalized to the intensity of the incident beam and background subtracted using the programs FoxTrot (courtesy of SWING beamline) and Primus (https://www.
emblhamburg. de/biosaxs/primus. html) [53]. Identical frames under the main elution peak were selected using Cormap  [54]  and averaged for further analysis. The R g was evaluated using the Guinier approximation  [55]  and also derived from the distance distribution function P(r) calculated by the program GNOM  [56]. Two independent determinations of the molecular mass were obtained using the programs SAXSMow2 and ScÅtter, available at URLs http://saxs. ifsc. usp. br/ and https://bl1231. als. lbl. gov/scatter/, respectively. A third determination was also obtained from the value of I(0)/c, in which c is the protein concentration for the two samples containing AC364. This could not be generated for the CaM, CaM:H-helix, and CaM-P MLCK samples, as CaM does not possess any tryptophan. The molecular mass of the CaM/H-peptide complex derived from the SAXS data was intermediate between that of the 1:1 and that of the 1:2 complex.
Modeling Ab initio shape determination. Regarding CaM and its complexes with H-helix and P MLCK peptides, the structural effect of peptide binding was investigated by determining the shape or envelope of each scattering particle. For all three systems, 20 shapes were determined using the ab initio program DAMMIF  [20]  and compared using the DAMAVER suite of routines based on the calculation of the normalized spatial discrepancy (NSD), which is lower than 0. 7 if all 20 models are similar. The final envelope is obtained using DAMMIN  [57] , which uses the envelope of all superimposed DAMMIF models (the union of all models) as initial volume. Rigid-body modeling. All scattering patterns calculated from atomic coordinates were obtained using CRYSOL  [58]. AC alone was first modeled using its crystal structure in complex with C-CaM  [7].
The scattering pattern was calculated using AllosModFoxs  [11] , which refines the position of missing residues. For the sake of consistency, the scattering intensities of the resulting models were recalculated using CRYSOL. The complex of AC with CaM was modeled using the BUNCH program  [59]. Starting from the crystal structure of AC:C-CaM (1YRU), the program refines the position of the N-CaM domain by modifying the position of the central linker residues so as to fit the data. Modifications to 1YRU were authorized in the 200-234 stretch of AC (helices F and G), a region that appears to be essentially disordered in HDX-MS studies. Ensemble of conformations. Finally, CaM and AC:CaM were modeled in terms of an ensemble of conformations using the program EOM  [22]. The routine Ranch first creates a large pool of 10,000 conformations by varying the conformation of the central linker of CaM (hence, the position of the N-CaM domain) and that of the stretch 200-234 of AC (in the case of the complex).
(F) Comparison of experimental data (black dots) to the scattering pattern of the crystal structure of CaM: P MLCK (pdb 2K0F shown in the inset) calculated using Crysol (blue line). The P MLCK peptide is shown in purple. CaM, calmodulin; EOM, Ensemble Optimization Method; pdb, Protein Data Bank; P MLCK , myosin light-chain kinase peptide; SAXS, small-angle X-ray scattering. https://doi. org/10. 1371/journal. pbio. 2004486. g003.
Funding: Fondation pour la Recherche Medicale (FRM) https://www. frm. org/(grant number DBS Received By DOB, AV, MD, DL, and AC. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Agence Nationale de la Recherche  (grant number  CACSICE Equipex   ANR-11-EQPX-0008 ). DOB, AV, VH, MD, JCR, SB, DL, and AC. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Region Ile de France  (grant number  DIM MalInf 2016 ). AV and AC. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CNRS. DOB, DD, AV, VH, MD, JCR, PV, SB, DL, and AC. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
+H2O2 ×[H 2 O 2 ]×[Target rd ]), and the rate of reduction is set to k switchoff ×[Target ox ], with k switchoff being a pseudo first-order rate constant. The differential equation is built, simplified by dividing by the total concentration of target [Target tot ], and solved with a software like Maxima [24]. The resulting solution describes the time course of the target in terms of its molar fraction in the reduced state (Target rd ), thus avoiding the utilization of absolute concentrations, a measure that is difficult to measure experimentally.
Data collection All patients included in the study underwent comprehensive ophthalmologic examination including best-corrected visual acuity (BCVA) measurement on ETDRS scale, slit-lamp biomicroscopic and fundus examination, Spectral-Domain Optical Coherence Tomography (volume mode of 49 B-scans, centered on the fovea), macular 30 degree MultiColor retinography (Spectralis HRA + OCT; Heidelberg Engineering, Heidelberg, Germany) as well as ETDRS 35 degree 7-standard fields color retinal photographs (Topcon TRC; Topcon, Tokyo, Japan) for retinal assessment, Swept-Source Optical Coherence Tomography (DRI OCT-1 Atlantis; Topcon, Tokyo, Japan) for choroidal thickness assessment, and Optical Coherence Tomography Angiography (Optovue RTVue XR Avanti; Optovue Inc, Fremont, California) for macular retinal vascularization assessment.
Diabetic retinopathy was graded according to the International Diabetic Retinopathy Severity Scale, as previously described. [12] emographic data (age, gender), general medical history (smoking, high blood pressure, hyperlipidemia, cerebral vascular accident, myocardial infarction, and amputation), diabetic medical history (type of diabetes, disease duration, most recent level of glycated hemoglobin, oral diabetes medication, and insulin therapy), and ophthalmologic history (cataract surgery, intravitreal antivascular endothelium growth factor injections) were also collected.
The "en face" image was then automatically segmented with an inner boundary 3 mm beneath the internal limiting membrane and an outer boundary 15 mm beneath the inner plexiform layer (IPL) to obtain images of the superficial capillary plexus. The segmentation was carried out with an inner boundary 15 mm beneath the IPL and an outer boundary 70 mm beneath the IPL in order to obtain deep capillary plexus images. [13] 5. Superficial and deep capillary plexus image analysis Each superficial capillary plexus image was analyzed using ImageJ 1. 48 software (NIH, Bethesda, MD). [13]  We manually traced FAZ contours in order to assess its different parameters. After setting the image scale to 3 Â 3 mm in the software parameters, we were able to automatically obtain measurement of the perimeter and area of the FAZ.
Statistical analysis Statistical analysis was performed with SAS software, version 9. 3 (SAS Institute Inc, Cary NC). Qualitative variables are presented as number and percentage. Quantitative variables are presented as means and standard deviations. Nonparametric ANOVA comparing the 3 NPDR groups used the nonparametric Kruskal-Wallis test. Qualitative variables were compared by Fisher exact test. Univariate analysis of FAZ parameters was based on Spearman rank correlation coefficient when relating to quantitative variables and Mann-Whitney nonparametric test when relating to qualitative factors. Multivariate analysis used linear covariance analyses for each FAZ parameters. Covariates were entered in the analysis on a P-value less than 0. 20 from the univariate analysis, then a backward elimination procedure retained only independently significant variables.
Participants Participants were workers potentially exposed to urinary tract occupational carcinogens, in France and mainly in the Auvergne region. Follow-up was assessed by their occupational physician. Their occupational physician recorded sociodemographic and occupational data such as gender, birthdate, occupational sector, date of first and last occupational exposure and thus the duration of exposure. Occupational exposure could have started any time prior to the first screening provided by physicians (ie, before the beginning of the follow-up). Women and current smokers at time of study were excluded. We included 2020 workers over a period of 20 years, from 1993 to 2013. All included participants were men and non-smokers. Occupational sectors were rubber manufacturing for 606 workers, metal processing for 692 workers, chemical industry for 245 workers and roadwork and building industry for 477 workers.
All rubber manufacturing workers were employed in the tyre sector. Metal processing workers included those within metalworking fluid and foundries. The chemical industry workers mainly included pharmaceutical manufacturers, who worked with dyes, adhesives or synthetic resins or in biological laboratories. Workers from roadwork and building industry were mainly exposed to asphalt and bitumen. The ethics committee from the University Hospital of Clermont-Ferrand (CHU), France, concluded that there was no need for ethics approval when data collected for secondary analyses were unidentifiable and part of daily clinical practice (2015CE/101). Therefore, workers did not provide consent. urine collection and analysis Urine samples were collected on site, after several consecutive days of work. Urine samples were sent by post in refrigerated packages to the Center of Occupational Diseases of the University Hospital of Clermont-Ferrand (CHU), France.
Acknowledgements We express our sincere gratitude to  Martine Lafaure ,  Gisèle Vernet ,  Françoise Chamoux ,  Béatrice Olagnier  and  Sarah De Saint Vincent  who analysed the urine cytology. We also express our sincere gratitude to  Professor Pierre Catilina  who created the laboratory of occupational medicine to analyse urine cytology and follow occupation exposures. Contributors FD and AC contributed to the study design. FD and AC were responsible for data collection. FD and AM were responsible of data processing. FD was responsible for the overall supervision. FD and LR wrote the first draft. GN, LF, MD-C and FM revised the manuscript. All authors read, contributed towards and approved of the final manuscript.
The Ocean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400-1020 nm. The OLCI is important to the expansion of remote sensing monitoring of inland waters using water color satellite data. In this study, we developed a dual band ratio algorithm for the downwelling diffuse attenuation coefficient at 490 nm (K d (  490 )) for the waters of Lake Taihu, a large shallow lake in China, based on data measured during seven surveys conducted between 2008 and 2017 in combination with Sentinel-3A-OLCI data. The results show that: (1) Compared to the available K d (490) estimation algorithms, the dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm developed in this study had a higher estimation accuracy (N = 26, coefficient of determination (R 2 ) = 0.
5 days, which compares favorably with the MODIS and thus has better prospects for highly variable inland waters. This study examined the temporal and spatial distributions of K d (490) in Lake Taihu, which is a large shallow lake in China, based on data measured during seven surveys conducted between 2008 and 2017 in combination with the Sentinel-3A-OLCI dataset from 2016-2017 to determine the characteristics of the photoecological environment in the waters of Lake Taihu. The main goals were:  (1)  to develop an algorithm for estimating K d (490) for the waters of Lake Taihu based on OLCI sensor data and compare it with a MODIS product of the same type; and (2) to establish a long time-series K d (490) dataset for Lake Taihu and determine the patterns of and driving factors for the temporal and spatial variations of K d (490) in Lake Taihu.
Only the K d (λ) values from regression fits of R 2 ≥ 0. 95 were accepted  [44]. Four to six depths were used in the regressions depending on the penetration depth. Note that before December 2016, measurements were made every 0. 30 m down to the lake bottom, usually at five depths (0. 30, 0. 60, 0. 90, 1. 20, and 1. 50 m); after December 2016, a WH311l liquid level transmitter (Shenzhen Oriental Vanward Instrument Co. , Ltd. , Shenzhen, China) was installed on the TriOS underwater spectroradiometer to obtain more accurate downwelling irradiance profile data (with an interval of ~0. 02 m and usually more than 50 profiles). Significant correlations between the in situ measured K d (490) obtained using the two measurement schemes were observed (r = 0. 98, p < 0. 001).
Satellite Image Acquisition and Pre-Processing Twenty four scenes of Sentinel-3A-OLCI Level-1B data over Lake Taihu from November 2016 to April 2017 with minimal or no cloud cover were chosen and downloaded from the European Space Agency Copernicus Open Access Hub (previously known as the Sentinels Scientific Data Hub; https://scihub. copernicus. eu/). The OLCI Level-1B products include top-of-atmosphere (TOA) radiances for the 21 OLCI spectral bands, geolocation information, meteorological variables (e. g. , total column water vapor and total columnar ozone), geographical information, and angles. Terra-MODIS Level-1A images captured on the same date as the OLCI data were download from the NASA Ocean Color website (http://oceancolor. gsfc. nasa. gov/). Terra-MODIS data were used to take advantage of its near identical transit time over the study area, with respect to Aqua-MODIS, despite its lower-quality (e.
Satellite-in situ comparison: To maximize the number of possible matching pairs between the in situ and satellite observations without compromising quality, the acceptable time interval was relaxed to 6 h instead of the commonly used 3 h time interval. A spatial homogeneity test was then applied to the satellite data [51]; the test required half of the pixels in the 3 × 3 window centered around the in situ stations to have valid data, and the variance limit for these valid pixels was <10%. Note that there are a total of 40 matchups obtained in November 2016, March 2017, and April 2017 according to the strict criteria. Table  1. Water parameters and optical properties of Lake Taihu, China. Chla, SPM, SPOM, and SPIM are chlorophyll a, suspended particle matter, suspended particulate organic matter, and suspended particulate inorganic matter, respectively.
Development and Validation of the Kd(490) Algorithm The simultaneous sampling sites for Kd(490) were divided into two groups. Two thirds of the sampling sites (N = 26) were used to establish an algorithm. To determine the optimal band or combination of bands for deriving Kd(490), a correlation analysis was performed on the in situ measured Kd(490) and different OLCI-derived Rrs bands or combinations of OLCI-derived Rrs bands. The dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm is found to have a high accuracy in estimating Kd(490) (Figure  5 ; R 2 = 0. 81, RMSE = 0. 99 m -1 , RMSErel = 25. 36%, MNB = 2. 81% and NRMS = 25. 73%). The remote sensing-based algorithm for deriving Kd(490) from the OLCI-derived Rrs is as follows:         R R K R R    (3) The remaining one third of the data (N = 14) was used to validate the algorithm (Figure  5 ).