dataesr/scientific-paragraphs-categorization huggingface dataset:
Pharmacoeconomic Model The model was built in Excel on the basis of a Markovian structure previously developed to assess the cost-effectiveness of empagliflozin in the treatment of HFrEF and adapted for HFpEF. This model has been methodologically accepted by the National Institute for Health and Care Excellence (NICE) as part of a medico-economic evaluation  [13]. Four mutually exclusive health states were defined based on Kansas City Cardiomyopathy Questionnaire-Clinical Summary Score (KCCQ-CSS) quartiles. The KCCQ-CSS score is a patient-reported outcome instrument that allows assessment of the symptoms and physical limitations experienced by the patients. A diminution in the score, therefore, translates into a deterioration of the patient's physical function and a worsening of the symptoms.
Clinical Data For each arm, the transition probabilities between the KCCQ-CSS quartiles were derived from an analysis of the EMPEROR-Preserved trial data for the following time points: months 1 to 3, months 4 to 8, and months 9 and higher (Table  2 ). To estimate the risk of HHF events and the CV and AC mortality over time, a distinct set of survival, for AC death and CV death, and risk equations for HHF were derived. These equations consider a coefficient depending on the KCCQ-CSS quartiles, as a time-varying predictor, and the treatment effect, in the empagliflozin arm. The inclusion of the coefficients was supported by statistical analyses on the EMPEROR trial data and key opinion leaders' (KOL) opinions. There were a total of 12 KOLs, including 1 pharmacist, 2 HF nurse specialists, 2 general practitioners (GP), 3 consultant cardiologists, 1 consultant nephrologist, 1 cardiology professor, 1 metabolic medicine professor, and 1 cardiologist professor and researcher.
The coefficients generated for the survival equation are presented in the Supplementary Material. For treatment discontinuation, a generalized gamma distribution was selected as it was the most conservative model and was the closest fitting to the trial data on visual inspection. In all the regression models, the treatment-specific and time-varying KCCQ-CSS health states were used as predictors of the disease progression. The treatment-specific rates of AEs were derived from the EMPEROR-Preserved trial and included if the difference in event rates between the two comparators was > 1%. The AEs included are presented in Table  1.
Health-Related Quality of Life Health-related quality of life (HrQoL) inputs associated with KCCQ-CSS health states, HHF, and adverse events were obtained from the EMPEROR-Preserved trial. The data were collected using the EQ-5D-5L administered at baseline, at weeks 12, 32, 52, and 100, and/or at treatment discontinuation; and 30 days post completion. A linear mixed model was fit to account for repeated measures on some patients. The model incorporated time-varying indicators for HHF in 0-1 month, 1-2 months, 2-4 months, and 4-12 months prior or not to being hospitalized, as well as time-varying levels of KCCQ-CSS quartiles. The estimates were valued based on the French tariff  [15]. The impact of HHF on quality of life was captured as a one-off QALY loss and calculated based on HRQoL decrements measured at four different time points (0-1 month, 1-2 months, 2-4 months, and 4-12 months), after patients experienced HHF.
Drug Costs Drug costs for empagliflozin 10 mg and SoC therapies were extracted from the French Health Insurance drug and pricing information database. For each of them, the latest price published by the official instance was considered for the indicated dosages, as reported in the Summary of Product Characteristics (SmPC)  [17]. In addition, dispensing fees were accounted for, i. e. , €1. 02 per pack, €0. 51 per prescription, and an additional €1. 58 specific to prescriptions dispensed to individuals aged 70 years and over (the mean age at model entry was 72 years)  [18]. For the SoC, an overall treatment cost was estimated by calculating the average treatment cost weighted by distribution of the patients among the different pharmacologic classes presented in Table  3. It was however assumed that the different drugs among the pharmacological classes were distributed uniformly among the patients.
Disease Management The cost of HFpEF management includes medical consultations, medical examinations, and technical procedures carried out as part of the follow-up of the patient and their disease. The specific medical investigations, procedures, and treatments, and their frequencies, were identified via the national guidelines published by the French Health agency and the FREnch Survey on HF (FRESH)-SNDS study, an observational study using secondary data extracted from the FRESH clinical cohort linked to the French administrative healthcare database (SNDS, Système National des Données de Santé) conducted from 2014 to 2018 (with data available from 2012)  [19]. The average consultation fee (including the patient's out-of-pocket) for each specialist (general practitioner, cardiologist) was calculated by the ratio of the total fees received and the total activity.
Fourth, for the analysis of change in lifestyle factors before and after the diagnosis of diabetes, patients who did not change lifestyles before and after diabetes were used as the reference group. All statistical analyses were performed with SAS software, version 9. 4 (SAS Institute Inc). In addition, greater improvements in lifestyle factors from before to after diabetes diagnosis were also significantly associated with a lower risk of neuropathy or total microvascular complications (Table  4 ). Each increment in number of low-risk lifestyle factors was associated with a 6% lower risk for any microvascular complications (RR, 0. 94; 95% CI, 0. 90-0. 98; P =. 01) and a 9% lower risk for diabetic neuropathy (RR, 0. 91; 95% CI, 0. 86-0. 96; P =. 001). Consistent results were observed when analyses were stratified by age at diabetes diagnosis, sex/cohort, or lifestyle factors before diabetes diagnosis, although with reduced power some of the results did not reach statistical significance (eTables 2 and 3 in Supplement 1).
Thunderstorms and long-lasting rainfalls To define a plausible range of precipitation scenarios which could potentially trigger future PPDFs, information on quantity, duration and probability of occurrence of extreme rainfalls is needed for the debris flow initiation zone. Here we used data on hourly and daily sums of extreme point rainfall with varying return periods provided by the Hydrological Atlas of Switzerland (HADES) to define different precipitation scenarios for both thunderstorms and long-lasting rainfalls. The data used represents precipitation levels for rare (return period of 2 to 200 years) heavy precipitation events in today's climate. It comes with a ground resolution of 1 km 2 for entire Switzerland, and was derived by extreme value analysis of precipitation data from a large number of MeteoSwiss weather stations and subsequent spatial interpolation  (Frei and Fukutome, 2022).
Following  Würzer and Jonas (2017) , snow melt intensities were calculated as quotients of the long-lasting rainfall intensities (Table  2 ). No measured data on the spatial distribution of snow depths or snowpack characteristics are available for the cirque of Le Dar Dessus. In close proximity to the debris flow initiation zone, however, continuous seasonal in-situ mass balance measurements are available for Glacier du Sex Rouge since 2012  (Fischer, 2018; GLAMOS, 2021). Based on time series of measured snow depths and density profiles on the glacier, average snow water equivalent (SWE) in the (upper parts of the) cirque of Le Dar Dessus at the time of maximum end-of-winter snow cover was estimated to 2000 mm. This value was adopted here as an upper limit average for late spring to early summer in order to calculate snow cover runoff intensities and clear water discharges for the different ROS scenarios which could potentially trigger debris flows.
Acknowledgements. This study was funded by the  University of Bern, Switzerland. The license and full version of RAMMS-DF was provided by the  Swiss Federal Institute for Forest, Snow and Landscape Research (WSL, Birmensdorf, Switzerland). Many thanks to  Luc Braillard  ( Department of Geosciences, University of Fribourg, Switzerland ), for geological advice and expertise,  Alexander Groos  ( Institute of Geography, Friedrich-Alexander-University Erlangen-Nuremberg  ( FAU), Erlangen, Germany ), for the acquisition of UAV data for the cirque of  Le Dar Dessus  and assistance in the field,  Frédéric Guex  ( B+C Ingénieurs SA, Montreux, Switzerland ), for providing us the photo documentation and practitioners' reports of the 2005 event,  Julien Viquerat  ( Office de l'information sur le territoire, Canton of Vaud, Lausanne, Switzerland) , for supplying us with the high-resolution ALS-DEMs of 2001/02/05 for the Dar catchment, and  Glacier 3000 AG (Les Diablerets, Switzerland) , for free cablecar transportations for fieldwork in the framework of this research project.
5 mL taken from the clear phase of the centrifugated solution was The number of zein (ZN), mg of nitrogen (N) released per 100 g of surfactant solution, is calculated as: ZN = c/10 ( 1 ) Where c is the concentration of N measured spectrophotometrically in ppm (mg/1000 mL). Considering that the density of the testing solution is 1 g mL -1 , c would be finally expressed as mg 1000 g -1. Data are the average of at least two repeats. Two control cases have been implemented for validation, a negative control using deionised water and a positive control using sodium lauryl sulphate (SLS) at 1 % wt. ; SLS is a well-known standard surfactant with high irritant potential (ZN = 536 ± 12).
Characterisation of particle size, concentration, and zeta potential The size and particle concentration of surfactant micelles, nanoparticles, and particles-surfactant complexes were measured by multiangle dynamic light scattering (MADLS) using a Zetasizer Ultra (Malvern Panalytical Ltd. , Malvern, UK). The Zetasizer system is also used to analyse the particle Zeta potential by Electrophoretic Light Scattering (ELS). The instrument settings were optimised automatically by means of the ZS XPLORER software (Malvern Panalytical Ltd. , UK). All experiments were performed at room temperature. Data are the average of at least three repeats. For these measurements, the final concentration of each component, pure or in a mixture, is 1 % wt (section 2. 1). Therefore, depending on the number of substances present in the mixture (one, two, or three), it is necessary to start from the appropriate initial concentration to obtain the final concentration desired for the measurement.
ME THODOLOGY The appointed task force by the European Academy of Neurology (EAN), the European Pain Federation (EFIC) and the Neuropathic Pain Special Interest Group (NeuPSIG) of the IASP defined patient intervention comparison outcome (PICO) questions and performed a systematic literature review, using a standardized review (Appendix S1) and data extraction protocol (unpublished). The full reports of studies published in peer-reviewed journals between January 1966 and December 2020 were identified with searches of PubMed and the Cochrane Library. Additional studies were identified from published reviews and the reference lists of selected papers. We included studies in English, providing information on diagnostic yield. Studies with fewer than 10 participants were excluded. The quality of the studies was assessed with the Quadas-2  [4].
They can also assess patients with two or three pain locations, provided they are administered with specific instructions and successively to the different pain areas. This appears less feasible in patients with multiple pain locations (i. e. , more than three). Thus, screening tools should not be used for diagnostic purposes in patients with widespread pain for both practical and theoretical reasons. Our data collection and analysis included only the most widely used screening questionnaires, namely the Leeds Assessment Neuropathique en 4 Questions (DN4), their self-administered versions (S-LANSS and I-DN4, respectively), and the PainDETECT  [8]. We have therefore excluded the IDPain and Neuropathic Pain Questionnaire  [9, 10] , given that these screening questionnaires found a limited application in studies dealing with diagnostic accuracy  [8].
QUANTITATIVE S EN SORY TE S TING QST uses standardized mechanical and thermal stimuli (e. g. , graded von Frey hairs, pinprick stimuli, light touch, pressure algometers, quantitative thermotesting) to examine the nociceptive and nonnociceptive afferent pathways in peripheral nerves and the central nervous system. QST assesses and quantifies the loss of function (sensory deficits) as well as gain of function (positive signs). The standardized protocol for QST proposed by the German Research Network on Neuropathic Pain  [16]  is widely used for assessing patients with neuropathic pain. This protocol includes 13 parameters gathered from sensory testing procedures. An age-, gender-, and location-matched database for absolute and relative QST reference data, useful for clinical purposes, was established for healthy children, adolescents, and adults  [17, 18].
No data met our criteria concerning the supporting diagnostic value of intravenous injections or sympathetic blocks. Comparators (reference) included the response to surgery in two studies, imaging evidence of compression in two studies, a combination of spine imaging with a neurological examination in one study, and intraoperative findings in one study. In all cases, nerve blocks used local anaesthetics (lidocaine, bupivacaine, mepivacaine, and procaine). Whereas one study found that retroperitoneal genitofemoral nerve block efficacy was relevant to the diagnosis of genitofemoral neuralgia  [54] , other studies have reported a limited or moderate role of nerve blocks, three of them in the diagnosis of lumbar radiculopathy  [55] [56] [57]  and one in the diagnosis of cervical radiculopathy  [58].
| Micro-CT scanning and volume segmentation Both teeth were scanned using the Scanco Medical Micro-CT80 system at the Centro Nacional de Investigaci on sobre la Evoluci on Humana (CENIEH) in Burgos (Spain) using the following parameters: 120 kV, 100 μA, 0. 2 mm copper filter and a voxel size of 18 μm. The resulting dataset was segmented by using semiautomatic threshold-based segmentation in Mimics 10. 0 (Materialize, Louvain, Belgium), following the half-maximum height method  (Coleman & Colbert, 2007; Fajardo et al. , 2002; Spoor et al. , 1993)  assisted by manual corrections. Following segmentation, we obtained the virtual models for the enamel, dentine and pulp cavity. These 3D models for each dental tissue are available at http://doi. org/10. 6084/m9. figshare. 12075477.
, 2011; Macchiarelli et al. , 2008; Zanolli, Pan, et al. , 2018; Zanolli, Martin on-Torres, et al. 2018 ). These proportions were compared to previously published data on Neanderthals and modern humans, including fossil and recent groups  (Bayle et al. , 2017; Martín-Francés et al. , 2018). These samples are available in the NESPOS database (www. nespos. org, 2020) and ESRF database (http://paleo. esrf. eu/, 2020). Adjusted z-scores  (  Maureille et al. , 2001; Scolan et al. , 2012)  were calculated to compare the quantitative variables measured in the Lezetxiki fossils to the comparative samples, including dental dimensions and tissue proportions. This method makes it possible to compare unbalanced samples with an adjustment to include small samples by using the Student's t inverse distribution.
ACKNOWLEDGMENTS We would like to thank  S. San José  ( Gordailua -Provincial Government of Gipuzkoa's Heritage Collection Centre ),  K. Mariezkurrena  and  J. Altuna  for granting access to the Lezetxiki teeth. We are grateful to the  José Miguel de Barandiarán foundation  for granting us access and permission to consult and reproduce the original fieldnotes of the Lezetxiki excavations. This work was funded by the  Direcci on General de Investigaci on of M. E. C , project number  CGL2012-38434-C03-03  and  MICINN PID202-1-122355N-B-C32 ; 2017  SGR 1630 Grup de recerca en Antropologia Biològica  (GREAB), 2017 SGR 1040 Social, cultural and biological  Evolution during the Pleistocene (StEP) , and  2021 SGR 01239  of the  Generalitat de Catalunya ; and  2019 PFR-URV-91  and  22017  Research Groups.
The dose-response semi-logarithmic curves from Figure  4  were fitted using the GraphPad Prism software. The standard deviation values of the three replicates are indicated in brackets. b N: number of replicated calibrations. c LD: limit of detection calculated using the 3σ IUPAC criterion. The recorded current signals at 1. 6 s were used to interpolate the concentration values in the respective calibration curves. The standard deviation values of three replicates are indicated in brackets. These results show that the device unambiguously detected the three biomarkers in real sputum samples and was able to discriminate between healthy individuals and those suffering from the disease. It also points out that the sample pretreatment procedures carried out to extract MPO enzyme on the one hand and IL-8 and TNF-α on the other hand were highly suitable for our purposes.
A cost for the production of small quantities of the transducer and the paper component of 20 € and 5 € per unit was estimated. The device can be controlled by a battery-powered instrumentation that could be connected to a mobile device (not equipment-free). While commercial electronics were used for all of the analytical studies included in this work, compact tailor-made instrumentation has already been fabricated for evaluating the simultaneous performance of up to eight electrochemical cells. It is a portable 85 × 78 × 45-mm 3 amperometer device (Figure  S8 , SI) that shows a measurement range of 0-4 μA and a resolution of 2 nA; it is powered by a battery and easily controlled by a software designed in LabVIEW. Variabilities of less than 5% in the responses of the electrochemical transducer in standard solutions of a representative redox species were recorded compared to those of the commercial electronics.
Laboratory Procedures and Data Preparation We used restriction site-associated DNA sequencing (RADseq) to generate genetic data for the population genetics analyses  [49]. RADseq generates sequence datasets for a large number of sites across the genome and is generally useful for the study of non-model organisms, as no prior genetic information is needed  [50]. DNA was extracted from ear biopsies using a DNeasy Blood & Tissue Kit (Qiagen) following an optimized version of the manufacturer's protocol. DNA concentrations were estimated using the Fluorometer dsDNA HS Assay Kit (Qubit) to select samples of a sufficiently high concentration. We obtained 93 samples of E. myoxinus (n = 77 individuals from ANP, n = 16 individuals from MCF) and 106 samples of R. rattus (n = 49 individuals from ANP, n = 57 individuals from MCF) for RADseq.
05), and a maximum heterozygosity of 0. 7 (max_het = 0. 7), and we retained only one random single nucleotide polymorphism (SNP) per RAD locus (--write_random_snp) in order to avoid linkage disequilibrium in downstream analyses. After filtering, we retained 66 samples of E. myoxinus, 52 from ANP and 14 from MCF (Table  S2 ). We used a similar protocol and parameters for R. rattus whenever possible, but with a reference genome available. In Stacks 2. 5  [51] , we used process_radtags, clone_filter, and kmer_filter to filter out low-quality reads. We then aligned our samples of R. rattus to the reference genome of congener R. norvegicus (Rnor_6. 0, GCA_000001895. 4) using the Burrows-Wheeler alignment (BWA) with BWA-MEM vs. 0. 7. 17  [53]  (https://github. com/ lh3/bwa). We then ran gstacks and removed read pairs of the same length (--rm-PCRduplicates).
We ran populations, retaining only loci found in at least 80% of samples (r = 0. 80), with a minor allele frequency of at least 5% (min_maf = 0. 05) and a maximum heterozygosity of 0. 7 (max_het = 0. 7), and we retained one random single nucleotide polymorphism (SNP) per RADtag (--write_random_snp). After filtering, we retained 81 samples of R. rattus, 43 from ANP and 38 from MCF (Table  S2 ). As a first test to assess if each of the two landscapes contained distinct populations, we ran ADMIXTURE 1. 3. 0  [54]  (http://dalexander. github. io/admixture/). We tested a varying number of ancestral populations (K = 2-10) and calculated cross-validation errors (CV) for each K-value to determine the most likely K. We then used the CLUMPAK program 1. 1  [55]  (http://clumpak. tau. ac. il/) to infer cluster assignments across 20 independent runs of ADMIXTURE 1.
Analyses of Local Movement and Dispersal We calculated a coefficient of genetic relatedness for each dyad for each landscape separately to investigate the distribution of related individuals in space. Distribution of related individuals accurately reflects the dispersal patterns within a species and can be used to detect potential dispersal events  [56]. We generated pairwise relatedness values by multiplying the kinship coefficient from the relatedness2 function in VCFtools 0. 1. 16  [57]  (https://vcftools. github. io/) by two, and assigned dyads into discrete kinship classes based on these r values. Classes were defined as first-order relatives (r ≥ 0. 375), second-order relatives (0. 375 > r ≥ 0. 1875), or distantly related individuals (0. 1875 > r > 0) in congruence with Combs et al. [58] , being aware that these classes represent approximations as we did not directly test for kinship categories but divided continuous relatedness values into three non-overlapping size classes.
amnh. org/open_source/gdmg (accessed on 19 April 2021)). We used these two matrices to create Mantel correlograms using the mantel. correlog function in the Vegan R package 2. 6-4 with 999 permutations  [60]. Mantel correlograms test for spatial autocorrelation between genetic and geographic distances in a predefined set of distance classes. We selected distance classes of 200 m width due to the expectation for short dispersal distances in R. rattus  [61] , and used the same distance classes for E. myoxinus for comparability. Only dyads from individuals of less than half the maximum Euclidean geographic distance were included in this analysis to reduce a potential bias due to individuals from the edges of the sampling space  [62].
Analyses of Connectivity and Genetic Structure on the Landscape Level In order to assess the effect of isolation by distance (IBD) across the entire population in each landscape, we first conducted Mantel tests using the genetic dissimilarity matrix and the geographic distance matrix described above. We ran Mantel tests with 999 permutations on each species and landscape separately using the Vegan R package 2. 6-4  [60]. We used three complementary methods to determine sub-population connectivity and genetic structure within the two landscapes. For all three analyses, we used a slightly reduced dataset with one individual of each closely related dyad being removed (n = 4 individuals removed). First, we ran ADMIXTURE 1. 3. 0  [54]  to assess genetic structure via ancestry estimation across each landscape using the same methods described above on each species and landscape independently.
We pooled population ancestry estimates from ADMIXTURE for all individuals from each forest site into one pie chart to visualize population structure across the landscape. Secondly, we used the Estimating Effective Migration Surfaces (EEMS) software package 0. 0. 0. 9000 (https://github. com/dipetkov/eems) to investigate migration rates and potential barriers to gene flow across each landscape. EEMS uses a stepping-stone model to estimate effective migration rates between adjacent subpopulations (demes) and produces a visual migration surface of estimated genetic barriers and connectivity  [59]. Specifically, the program highlights geographic areas where genetic distance between samples increases more quickly (i. e. , low genetic connectivity) or more slowly than expected (i. e. , high genetic connectivity).