dataesr/scientific-paragraphs-categorization huggingface dataset:
Introduction The development of white biotechnology is underpinned by advances in enzyme discovery and engineering, areas that are being driven by metagenomics and in vitro directed enzyme evolution. These techniques procure massive discovery or creation of new enzyme-encoding sequences, filling up databases with a wealth of information. However, while resolving an early step in the discovery pipeline, these techniques progressively create a new bottleneck regarding enzyme characterization. Therefore, there is a pressing need to extend the enzymologist's toolbox, providing informationally rich high-throughput screens that can not only attribute an activity to putative enzymes, but also procure some qualitative details on enzyme properties. In this respect, the availability of easy to use chromogenic substrates that can provide both qualitative and quantitative assays and be compatible with automatized protocols is a crucial issue.
Acknowledgments The NMR work carried out in this work at  TBI  (Toulouse, France) was performed with the equipment of  Meta-Toul (Metabolomics & Fluxomics Facitilies, Toulouse, France , www. metatoul. fr). MetaToul is part of the national infrastructure MetaboHUB (The French National infrastructure for metabolomicsand fluxomics, www. metabohub. fr) and is supported by grants from the  Région Midi-Pyrénées , the  European Regional Development Fund , SICOVAL,  IBiSa-France ,  CNRS  and  INRAE. We thank the  ICEO facility  dedicated to enzyme screening and discovery, and part of the  Integrated Screening Platform of Toulouse (PICT, IBiSA)  for providing access to its equipment. The authors wish to acknowledge the support from the  ICMG Chemistry Nanobio Platform (Grenoble, France ) for HRMS analyses.
Funding This work was supported by the  European Union's Seventh Programme for Research, Technological Development and Demonstration  under Grant Agreement No  613868 ,  OPTIBIOCAT  project (to O. G. and J. D. ), by the  French National Research Agency , grant  ANR-05-PNRB-002 , project  SPPECABBE  (to M. R. ) and the  Région Midi-Pyrénées  grants  DAER-Recherche 07009817 (to F. F. ).
2017; Nishio et al. 2018; Nunziata et al. 2020; Sun et al. 2020) , no SNP assays have been designed and optimized for the mentioned applications. We identi ed SNPs in the nuclear genome of chestnuts using restriction-site associated DNA sequencing  (Miller et al. 2007 ). We used three samples from the INRAE chestnut germplasm collection, one C. mollissima (Ca 737), one C. crenata (Ca 04) and one C. sativa (Ca 577). We also included SNPs originating from C. mollissima CCall_Unigene_V2 assembly data and from C. dentata AC454_Unigene_V3 contig data  (Santos et al. 2017 ; http://www. hardwoodgenomics. org/). We rst tested the markers on a set of 95 samples including the three sequenced parents, the descendants of two interspeci c crosses (Ca 577 x Ca 737 and Ca 577 x Ca 04) and nine French cultivars.
0, Agena Bioscience, San Diego, USA) of up to 40 loci. Data analysis relied on MassARRAY Typer Analyzer 4. 0. 26. 75 (Agena Biosciences). We excluded all monomorphic SNPs, loci with weak or ambiguous signal (i. e. , displaying more than three genotypes clusters or with unclear cluster delimitation) and loci with >10% missing data. Out of the 343 loci tested, 237 were validated (Larue 2021, File 1). We combined the best markers in two new multiplexes of 40 and 39 loci (Larue 2021, File 2) and used them to genotype the second set of 95 individuals. All 79 loci were polymorphic. Extensive testing with Mismatch nder (https://github. com/jschoete/mismatch nder, Supplementary 2) of over 3000 progeny identi ed 68 markers segregating according to Mendelian expectations that worked well on all species.
This paper is part of the PhD of CL. The work was supported by ANRt funding under CIFRE PhD program to CL. Financial support to Invenio for this project was provided by the Conseil Régional d'Aquitaine for CL PhD work, as part of the REGINA project, and for BL work (Grant Number 2018-1R20204 project DIGIE "chestnut dieback: vulnerability and genetic determinism of ink disease resistance"). SNP development and genotyping were performed at the Genome Transcriptome Facility of Bordeaux (grants from the Conseil Régional d'Aquitaine no. 20030304002FA and 20040305003FA, from the European Union FEDER no. 2003227 and from Investissements d'Avenir ANR-10-EQPX-16-01).
Acknowledgments We thank  J. Schoeters  for developing MISMATCHFINDER software,  C. Lalanne  for DNA isolation protocol development and  L. Dubois ,  C. Boury  and  C. Mouden  for SNP identi cation and genotyping. We thank  INRAE experimental unit Vigne Bordeaux (UEVB) in Villenave d'Ornon , and  INRAE experimental unit Forêt Pierroton (UEFP) for their continuous support for chestnut orchards management.
Funding This paper is part of the PhD of CL. The work was supported by ANRt funding under CIFRE PhD program to CL. Financial support to Invenio for this project was provided by the Conseil Régional d'Aquitaine for CL PhD work, as part of the REGINA project, and for BL work (Grant Number 2018-1R20204 project DIGIE "chestnut dieback: vulnerability and genetic determinism of ink disease resistance"). SNP development and genotyping were performed at the Genome Transcriptome Facility of Bordeaux (grants from the Conseil Régional d'Aquitaine no. 20030304002FA and 20040305003FA, from the European Union FEDER no. 2003227 and from Investissements d'Avenir ANR-10-EQPX-16-01).
Another objective would be to accumulate data from a range of contexts and profiles of patients to define the optimal discharge criteria for SAM treatment, typically through Receiver Operating Characteristics (ROC) curves analysis. Of note, although being discharged with a WHZ≥-2 appeared as a strong protective factor, there were still 20 % of relapse as SAM among those children. Since WHZ as a continuous variable displayed a strong association with the risk of relapse, the question arises whether a higher WHZ cut-off should be defined to keep relapse risk minimal. Optimal MUAC discharge cut-offs by age group should also be further investigated. Importantly, such investigations on relapse should fully assess the anthropometry of children upon discharge and during follow-up. They should also use a complete definition rather than a restricted MUAC-only definition of relapse.
Statistical analysis Before using parametric analyses, all data were checked for normality and homogeneity of variance with Shapio-Wilk W test and Levene's test, respectively. All data were analyzed by one-way ANOVA using SPSS Statistics 22 (IBM® SPSS® Statistics, New York, NY, USA) and GraphPad Prism 6. 0 (GraphPad Inc. , La Jolla, CA, USA; figures). Then multiple comparison by DUNCAN analysis (Tukey's multiple range test were used in all figures) were used to determine statistical differences between groups. The results are presented as mean ± SE. P < 0. 05 was considered as a statistically significant difference. A trend was assumed at 0. 05 ≤ P < 0. 1.
In vitro evaluation of SPF and UVA-PF were calculated using the following equations  [29]  :  () 10 - 0 ()  ()  (1)  where Eλ is the erythema action spectrum at wavelength λ, Iλ is the spectral irradiance of the UV source at wavelength λ, A0(λ) is the mean monochromatic absorbance measurements per plate of the test product layer after UV exposure at wavelength λ and dλ is the wavelength step (1 nm). 𝑆𝑃𝐹 𝑖𝑛 𝑣𝑖𝑡𝑟𝑜 = ∫ 𝐸 (𝜆) 𝐼 (𝜆) 𝑑 (𝜆) Each sample was exposed to the UV exposure dose, which is the initial UVA-PF (UVA-PF0)  [29]  value multiplied by a factor 1. 2 (J/cm 2 ). - = ∫  ()  ()  () 400 320 ∫  () 400 320 𝐼 (𝜆) 10 -𝐴 𝑒 (𝜆)𝐶 𝑑 (𝜆) ( 2 ) where Pλ is the PPD action spectrum, Ae is the mean monochromatic absorbance measurements plate of the test product after UV exposure and C is the coefficient adjustment determined using the SPF label (SPF in vitro adj  [29] ) generated by the UV-2000's software.
Mechanical properties The mechanical properties of samples were evaluated by compression testing (bending and needle probe penetration tests) or tension-compression tests (cycle count test). Samples were kept at 25 and 45°C for 24h before testing. Visual inspection and measurements were taken at day 1, 2 weeks, 4 weeks, and 8 weeks using a texture analyser (Ta. XT+; Texture Technologies Corp. , Hamilton, MA / Stable Microsystems, Godalming, Surrey, UK). All samples had an inner diameter of 9 mm and a height of 35 mm. All measurements were carried out with six lipsticks of each type. The data (force, distance) were recorded using Exponent Stable Micro Systems software (version 8). The maximum force value, which provides the hardness of the sample, is the force required to bend the sample until it broke off at the base and for a defined distance and give an indication of the brittleness of the sample.
Chromatographic analysis is completed using Agilent's MassHunter Qualitative Analysis (Version B. 08. 00) integration and quantification performed with Quantitative Analysis (Version B. 09. 00) software. Internal standard mixture was added to each sample to determine the absolute concentration of each FA detected in these samples following calibration curves determined for all major FAs. The list of different studied fatty acids with common manes and formula is provided in Table  A7  in Supplementary data.
The mobile phase consisted of (A) 30/40 hexane/isopropanol v/v and (B) 30/40/7 hexane/isopropanol/water with 5 mM ammonium acetate with a flow rate of 200 μl/min. The stationary phase was a normal phase silica column (Supelco Ascentis 5 μ Si, 100 Å pore size, 150 × 2. 1 mm). Mass spectrometric analyses were performed in the negative ion mode for precursors of m/z 327 for DHA and m/z 288 for the internal standards and positive ion precursors of m/z 184 scanning from m/z 450-900. Results were analyzed using MultiQuant software (SCIEX) and all detected PC species containing DHA are reported as the ratio between the integrated area of each analyte and the integrated area of the corresponding internal standard for PC class (PC-C15:0/[ 2 H 7 ]18:1). The internal standard LPC C18:1/[ 2 H 7 ] was used for determining the LPC ratios.
Acknowledgments The authors thank  Stefan Haugen  for his technical assistance. Targeted lipidomic analyses in plasma and placental tissue were provided by the  Mass Spectrometry Lipidomics Core Facility of Dr. Robert Murphy  at the  University of Colorado Anschutz Medical Campus, Aurora, Colorado. Quantification of acyl-carnitine metabolites was performed in placental tissue in the department of Pharmaceutical Sciences at the  University of Colorado Anschutz Medical Campus, Aurora, CO, USA. We also thank  Jenny Neira  for graphic illustration.
Single-nutrient approaches The effects of omega-3 polyunsaturated fatty acids (PUFA) on fighting inflammation and oxidative stress are well stablished in literature  (1, 2). Docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), mainly, have been shown to have neuroprotective abilities through both vascular and neuronal mechanisms  (3, 4) , being associated with reduced white matter hyperintensities (WMH) accumulation and delayed neurodegeneration  (5, 6). In this sense, trials based on omega-3 PUFA supplementation have been developed. The doubleblind, placebo-controlled PUFA Trial (NCT01953705) provided marine omega-3 PUFA to North-American adults free of dementia but with suboptimum plasma omega-3 (<110μg/mL) and magnetic resonance imaging (MRI)-derived WMH burden (≥5cm3), aged 75 years and older, for 3 years  (7).
Participants took daily doses of 1,650mg of omega-3 PUFA (975mg of EPA and 675mg of DHA) or placebo. Data presented in CTAD 2020 showed that WMH progression was slowed over 3 years among participants that adhered to study protocol, while no effects were observed among the modified intention to treat (mITT) cohort presenting at least one followup MRI. No differences were seen in medial temporal lobe, total brain or ventricular volume changes, nor in executive function Z-score though. The given dose and duration appeared to be safe, since no differences in adverse events between active group and placebo were observed  (8). Another study testing the effects of omega-3 PUFA supplementation on cognitive function among community-dwelling older adults is the multicenter, randomized, double-blind controlled Multidomain Alzheimer Preventive Trial (MAPT) (NCT01513252), performed in France and Monaco with subjects aged 70 years or more reporting subjective memory complaints.
In addition to these clinically detectable benefits, the multinutrient drink presented a good safety profile and high compliance throughout this study  (21, 22). The NOLAN Study (NCT03080675) has also tested the effectiveness of a multi-nutrient oral supplement on cognitive function and brain volume of communitydwelling older adults, as also on erythrocyte omega-3 and plasma homocysteine (biomarkers with a capacity to underlie an attenuation in cognitive decline during aging  (23) (24) (25) ). The nutritional blend was composed by two soft capsules and a powdered drink mix to be solved in cold water, containing omega-3 PUFA (DHA and EPA), choline, vitamins B1, B2, B3, B5, B6, B7, B9, B12, E, C, D, selenium and citrulline, and offered daily for one year to participants presenting subjective memory complaints.
Other dietary approaches Another nutritional approach used in a trial presented at CTAD 2020 was the oral supplementation with ketone bodies. Brain function is mainly fueled by glucose. In the insufficiency of circulating glucose (which occurs after the depletion of glycogen stores caused by a long fasting state), ketones (acetoacetate and beta-hydroxybutyrate) are naturally produced to keep brain functioning  (27). In mild cognitive impairment (MCI) and AD, brain glucose uptake is reduced  (28, 29). In contrast, uptake of ketones has been shown to remain normal in both MCI and mild-moderate AD  (28, 30, 31). Previous research have suggested that endogenous or exogenous sources of ketones may improve energy metabolism in both MCI and AD subjects  (32). To test if such improvement might also benefit cognitive performance, the randomized, placebo-controlled Benefic Trial (NCT02551419) supplemented MCI subjects with an oral nutritional supplement composed of ketogenic medium chain triglycerides (kMCT), and compared them to controls taking placebo for 6 months.
Overall, the consistent plasma ketone response suggested no metabolic adaptation to the oral kMCT drink after 6 months of treatment, with safety and good acceptability from participants  (33, 34). Also using a nutrition-based approach, the Blood Flow Improvement Trial (BFIT) (NCT03117829) was designed to test whether an intervention based on exercise and carbohydrate-restricted diet (CRD) would reduce insulin resistance (IR) and improve cognitive function. The potential relationship between IR and cognitive performance stands on evidence showing that type 2 diabetes is associated with increased risk of cognitive impairment  (35)  and of MCI conversion to dementia  (36, 37) , what is believed to occur through vascular damage and dysfunctions in glucose, insulin and amyloid metabolism  (38).
Hence, to reflect the absence of consensus on coastal erosion induced by sea level rise, neither the surrogate PCR model nor the Bruun rule should be discarded in our uncertainty propagation. To account for the limited knowledge of future sea level and its impact on shoreline change, we construct RSLR and 1/ tan β terms as trapezoidal possibility distributions (see also Sect. 4a and b). As a second step (Fig. 2b ), to propagate the heterogeneous uncertainty nature of the terms in Eq. (  1 ), we used the HYRISK R package  (Rohmer et al. , 2018). HYRISK software is designed to jointly propagate probability and possibility by implementing the hybrid Monte Carlo scheme, named the independent random sampling (IRS) algorithm developed by  Baudrit et al. (2005). The IRS algorithm combines random sampling of the inverse of the cumulative probability distribution functions for random parameters and the α-cuts (intervals associated with a level of confidence of 1 -α) from the possibility distributions.
, 2019a). For the Castellón-Sagunto stretch, the dataset retrieved by CoastSat has been validated against discrete profile surveys at some specific sites. The shoreline evolution over the period 1989-2019 for the profile studied in Chilches is shown in Fig. 4b. Over the 31-year period, 859 shoreline positions (orange time series) were retrieved for this profile, with an average of 25 (70) observational records per year before (after) 2017. The profile shows an average coastline retreat of 0. 6 m yr -1 over the period 1989-2019. In Aquitaine (site 1), topographic and bathymetric surveys recorded nearshore slopes in the range 1. 2 %-1. 5 % that can occasionally be as mild as 1 %  (Bernon et al. , 2016)  and slopes of the upper shoreface that can be as steep as ∼ 10 %  (Bulteau et al. , 2014).
In Castellón, beach slopes have been determined by combining two datasets: a topography dataset from the Spanish Geographic Institute (Instituto Geográfico Nacional, IGN) and a bathymetry dataset from the Spanish Ministry for the Ecological Transition and Demographic Challenge (Ministerio para la Transición Ecológica y el Reto Demográfico, MITERD). Specifically in site 2, a nearshore slope of 3. 1 % was retrieved.
Analysis of past shoreline change Past shoreline changes are investigated first to ensure the validity of the modelling framework. Table  1  summarises how uncertainties of each variable of Eq. (  1 ) are defined (using either probability distributions or possibility distributions as introduced in Sect. 2) to model past shoreline changes in sites 1 and 2, respectively. Over the historical period, mean sea level uncertainty for these two sites is assumed to be well represented by a normal probability distribution. For vertical ground motion (VGM), the sites that are investigated in our study have no statistically significant trends identified. Therefore, uncertainties due to VGM were prescribed as a centred normal distribution with a standard deviation of 2 mm yr -1 , as retrieved by the analysis of trends computed from the permanent coastal GNSS stations in the SONEL (Système d'Observation du Niveau des Eaux Littorales) database  (Wöppelmann and Marcos, 2016).
Acknowledgements. This research takes part in the COasTAUD framework. We thank  Mark Carson  for making available the ICDC sea level data and the modelling groups that participated in the CMIP5 for producing their model output. We also thank SONEL and PSMSL services for providing tide gauges and GPS land motion records. We thank  Bruno Castelle  for providing the shoreline change historical evolution dataset in Aquitaine. We thank the two anonymous reviewers for their constructive comments on our work. Financial support. This research has been supported by the  BRGM, IHCantabria  and the  ERA4CS-ECLISEA  project (grant no. 690462 ). Review statement. This paper was edited by  Ira Didenkulova  and reviewed by two anonymous referees.
Code availability. HYRISK software, used to design and jointly propagate probability and possibility distributions is a publicly available CRAN R package (https://cran. r-project. org/ web/packages/HYRISK/index. html;  Rohmer et al. , 2021). R code and data needed to reproduce simulations, shoreline reconstructions and projections, and related figures for each case study are publicly available at https://gitlab. brgm. fr/brgm/ shoreline-change-hyrisk (BRGM, 2021a). Data availability. AR5 projections can be downloaded from the Integrated Climate Data Center at the University of Hamburg (https: //icdc. cen. uni-hamburg. de/en/ar5-slr. html; University of Hamburg, 2021). Other projections (i. e. low-end, high-end projections) used in this study are available at https://sealevelrise. brgm. fr/ (BRGM,  2021b).
Statistical Analysis All data are presented as mean ± SEM, n = 7-8 per group from different litters. Body weight, a basic and well-characterized biologically meaningful endpoint, was examined by one-sided t-test in male and female F1 from the control group and was statistically different (p < 0. 001), therefore sexes were analyzed separately. To assess the statistical differences within maternal diet and DHA supplementation groups, data were analyzed using twoway multiple analysis of variance (ANOVA), followed by Tukey test. Corticosterone and leptin concentrations in milk were compared to serum, and Pearson's correlations were calculated. p ≤ 0. 05 was considered significant. Log-transformation was used for skewed and spread data (serum and milk corticosterone, and milk leptin).
Maternal Food Intake during Lactation From lactation day 1-16, maternal food intake in g/day was reduced in MO and MO+DHA groups compared with C and C+DHA, respectively (Figure  1A ). Maternal energy intake per day, as well as average energy intake during lactation, were similar in all groups (Figure  1B, C ). Maternal fat intake was higher, while protein and carbohydrate intake was lower in MO and MO+DHA groups in comparison with C and C+DHA (Figure  1D-F ). relations were calculated. p ≤ 0. 05 was considered significant. Log-transformation was used for skewed and spread data (serum and milk corticosterone, and milk leptin).
Methods and findings Our method relies on a recently-developed log-quadratic model that can predict age-specific mortality by detailed age between 0 and 5. The model's coefficients were derived from a newly constituted database, the Under-5 Mortality Database (U5MD), that represents the mortality experience of countries with high-quality vital registration data. We applied this model to 204 DHS surveys, and compared unadjusted IMR values to IMR values adjusted with the log-quadratic model as well as with the classic model life table approach. Results show that contrary to existing knowledge, age heaping at age 12 months rarely generates a large amount of bias in IMR estimates. In most cases, the unadjusted IMR values were not deviating by more than +/-5% from the adjusted values. The model life table approach, by contrast, introduced an unwarranted, downward bias in adjusted IMR values.
In the last update of 2017, the UN Statistics Division estimated that less than 45% of countries benefited from a coverage of deaths that was above 90%  [1]. In Sub-Saharan Africa, this was the case for only about 5% of countries. Due to this lack of reliable vital registration systems, the estimation of mortality in low-and middle-income countries has depended largely on alternative sources of data such as nationally representative surveys. The Demographic and Health Surveys (DHS) Program, in particular, has constituted one of the most important sources of mortality information when no complete vital registration (VR) system is available. Since the 1980s, the DHS Program has collected and disseminated data on health and population in low-and middle-income countries. The full birth histories collected in these surveys have made it possible to monitor child mortality at relatively regular intervals.
In this paper, we propose to assess the quality of DHS-based IMR estimates by using a new model of under-5 mortality that overcomes the shortcomings of the MLTs. The model, whose details are provided elsewhere  [7] , builds on the log-quad approach initially proposed by Wilmoth et al. [8]  and benefits form the newly constituted Under-5 Mortality Database (U5MD)a data source that includes 22 detailed age groups from 0 to 5 years. Thanks to the granularity of the age breakdown, our assessment has one fundamental change when compared to the MLT approach. The choice of the age pattern of mortality can be directly informed by the data under study rather than by an alternative source of information that could be itself potentially biased by age heaping. Indeed, given the multiplicity of age groups in the model, robust/problematic data points can be selected/discarded around the month 12, as we propose in this paper.