dataesr/scientific-paragraphs-categorization huggingface dataset:
Efficacy and safety were analysed in randomly allocated patients who received one or more doses of study drug. This study is registered with ClinicalTrials. gov, NCT03566238. Findings Between June 21, 2018, and Feb 10, 2020, 62 patients (median age 3•2 [range 0•5-15•9] years) were randomly allocated to placebo (n=20), odevixibat 40 µg/kg per day (n=23), or odevixibat 120 µg/kg per day (n=19). Model-adjusted (least squares) mean proportion of PPAs was significantly higher with odevixibat versus placebo (55% [SE 8] in the combined odevixibat group [58% in the 40 μg/kg per day group and 52% in the 120 μg/kg per day group] vs 30% [SE 9] in the placebo group; model-adjusted mean difference 25•0% [95% CI 8•5-41•5]; p=0•0038). The percentage of patients with serum bile acid response was also significantly higher with odevixibat versus placebo (14 [33%] of 42 patients in the combined odevixibat group [10 in the 40 μg/kg per day group and four in the 120 μg/kg per day group] vs none of 20 in the placebo group; adjusting for stratification factor [PFIC type], the proportion difference was 30•7% [95% CI 12•6-48•8; p=0•0030]).
The ileal bile acid transporter (IBAT), also known as the apical sodium-dependent bile acid transporter (ASBT), is a critical regulator of the enterohepatic circulation of bile acids, taking up bile acids in the distal intestine for return to the liver via the portal circulation. Small-molecule inhibition of IBAT has been investigated as a therapeutic approach to treat a number of disease states, including cholestatic liver diseases. We searched ClinicalTrials. gov from database inception to April 6, 2021, for interventional studies categorised by "cholestasis" as the condition or disease and one of the following other terms: "IBAT inhibitor", "ASBT inhibitor", "odevixibat", "maralixibat", "volixibat", "GSK2330672", or "elobixibat". This search revealed four IBAT inhibitors in clinical development for cholestatic diseases such as PFIC, primary biliary cholangitis, Alagille syndrome, biliary atresia, intrahepatic cholestasis of pregnancy, and primary sclerosing cholangitis.
The ClinicalTrials. gov identifiers of the studies found in the initial search (n=20) were then cross-referenced with published articles indexed on PubMed. There was no language or date restriction for the search. Of articles identified on PubMed, only one published manuscript included data from the patient population of interest (ie, those with PFIC). This was a phase 2 study of the IBAT inhibitor odevixibat that enrolled paediatric patients with cholestatic liver diseases including PFIC and who had pruritus. In addition, some phase 2 study results of the IBAT inhibitors odevixibat or maralixibat in patients with PFIC have been presented as congress proceedings. Published and presented results of phase 2 studies of IBAT inhibitors in PFIC have shown evidence of improvement in key features of PFIC, such as reduced serum bile acid concentrations and pruritus, but these studies had no placebo controls.
Procedures Two on-site screening visits occurred: the first took place during the window of time from days 56 to 35 before the first dose of study drug and the second occurred during the window of time from days 28 to 7 before the first dose of study drug. Randomisation occurred on day 0, and patients took their first dose of study drug at home on day 1. Patients returned to the clinic for planned clinic visits on weeks 4, 8, 12, 18, 22, and 24, with one telephone call at week 2 between the randomisation and week 4 visits. The double-blind treatment period lasted 24 weeks. Patients who completed the treatment period either attended a follow-up visit 28 days after the last dose of study drug, or they could choose to continue into an optional 72-week open-label extension study (PEDFIC 2; ClinicalTrials.
gov NCT03659916), in which all patients received odevixibat 120 μg/kg per day. Initially patients could withdraw from PEDFIC 1 due to intolerable symptoms after 12 or more weeks of treatment and enroll early into PEDFIC 2; however, this provision was removed with the last PEDFIC 1 protocol amendment on June 24, 2019. From March 10, 2020, to Aug 28, 2020, study procedures for patients were affected by the COVID-19 pandemic due to missed or altered on-site study visits (eg, sites were closed per institutional or national guidelines, travel was restricted due to risk of infection). Several contingency measures were implemented during this time including frequent outreach to monitor safety, use of local laboratories, direct-to-patient shipment of study drug, and possible extension of the 24-week period to ensure that patients could attend an on-site end-of-treatment visit.
Statistical analysis The statistical analysis plan was finalised before database lock and analysis. For the primary endpoint related to pruritus, the individual null hypothesis was that the average proportion of positive assessments would be the same between the active and placebo groups; the alternative hypothesis was that the average proportion would be larger in the active group. For the primary endpoint related to serum bile acids, the individual null hypothesis was that the odds ratio of the response in an active group versus placebo would be 1; the alternative hypothesis was that the odds ratio would be greater than 1. Since each active group was to be compared with placebo, there were two individual null hypotheses for each endpoint. For each primary endpoint, simulations with 5000 iterations using 20 patients per group were conducted to estimate power after multiplicity adjustment based on a closed-testing procedure to control the one-sided overall type I error rate for two treatment comparisons versus placebo at the 0•025 level.
This one patient whose liver findings worsened had a clinically significant worsening in echogenicity pattern (from smooth homogeneous at baseline to heterogeneous at week 24). He was aged 1 year at baseline, had PFIC2 and a history of vitamin deficiency, and received concomitant treatments including ursodeoxycholic acid and vitamin supplementation during the study. Despite the worsened liver ultrasound finding, this patient was a serum bile acid responder at the end of treatment, and the patient's pruritus score changed from 3•00 at baseline to 2•02 at weeks 21-24. Splenomegaly was noted at baseline in 35% of patients (13 of 37 with data available) in the overall odevixibat group and in 25% of patients (five of 20 patients) in the placebo group. At week 24, most patients with data available (ten of 19) had no change in spleen size.
Mapping ancient milk use To build a more comprehensive picture of prehistoric milk use and examine how well it explains selection on LP, we compiled all published instances of the occurrence of milk fat residues detected in pottery containers from 366 archaeological sites in Europe and southwest Asia. To improve spatiotemporal coverage we added newly generated organic residues data from 188 sites from various regions and periods. Overall, we used 6,899 animal fat residues derived from 13,181 potsherds from 826 phases from 554 sites, with associated georeferences and phase chronology including more than 1,000 radiocarbon dates. These data were used to generate time series depicting the frequency of milk use across prehistoric continental Europe from 7000 bc to ad 1500 (Fig. 1 ) and regional time series (Fig.
Health impacts of milk consumption Our analysis of potsherd lipid residue and ancient LP allele data suggest that intensity of milk usage-beyond its mere presence-did not drive selection on LP. To explore other explanations for LP selection we first turned to contemporary data. The UK Biobank 4,5 includes genotypic and phenotypic data from about 500,000 people aged between 37 and 73 years, recruited between 2006 and 2010 (http://biobank. ndph. ox. ac. uk/showcase). In a subset of approximately 337,000 unrelated participants who classified themselves as 'white, British' and have similar genetic ancestry, LP genotypes were out of Hardy-Weinberg equilibrium (Extended Data Table  2 ), which could reflect genotype-related assortative mating  51  (for which there is weak evidence for LP; Extended Data Table  3 ), selection into a study or population structure, amongst other influences  52.
These findings bring into question the widely held belief that selection against LNP was the result of detrimental effects of milk consumption in otherwise healthy individuals-for example, through inducing stomach cramps, diarrhoea and flatulence  40, 41, [55] [56] [57]. One possible explanation for the small effect of LNP on milk intake in contemporary data is the use of mealtime lactase supplements that reduce symptoms of lactose intolerance. However, these have only become widely available recently and UK Biobank participants would not have had access to them for most of their lives. We examined phenotypic associations of genetically predicted LP (Fig. 4 ) to investigate potential pathways through which selection could have occurred. The related calcium assimilation and vitamin D hypotheses  32  would anticipate LP to be associated with higher vitamin D concentration and bone mineral density due to its positive relationship with milk consumption  [58] [59] [60].
We name this the 'chronic mechanism', which predicts that LP selection pressures would have increased with greater pathogen exposure. Crucially, proxies are available for some of the drivers of these suggested mechanisms, permitting us to explore the extent to which they explain LP selection and so allele frequency trajectories, using our maximum likelihood modelling approach. For the 'crisis mechanism' we use fluctuations in population size (residual fluctuations detrended for overall background growth) as a proxy for malnutrition exposure. For the 'chronic mechanism', we use temporal variation in settlement density as a proxy for pathogen exposure. Both proxies are constructed using an extensive database comprising >110,000  14  C dates from >27,000 sites across the European and Mediterranean area.
Lipid residue analyses Data, lipid extraction and analysis. Our lipid residue analysis draws on our SQL database of 13,181 archaeological potsherds from 554 sites, of which 6,899 sherds have yielded animal fat residues from georeferenced sites and dated phases (826 phases from 554 sites). This analysis represents about 30% new data (Supplementary Table  1 ) and about 70% collated from previously published studies  3, 11, 12, [15] [16] [17] [18] [20] [21] [22] 33,. Lipid residue analyses and interpretations were based on established protocols  160, 161. Lipids were extracted from 1-3 g of cleaned potsherd and analysed using gas chromatography (GC) and GC-mass spectrometry (GC-MS) to determine their molecular composition. Compound-specific δ  13  C values of fatty acids were determined using Agilent Industries 7890A gas chromatograph coupled to an Isoprime 100 isotope ratio mass spectrometer (GC-C-IRMS) for extracts identified as animal fats.
Instrumental precision was 0. 3‰. Data processing was carried out using Ion Vantage software (v. 1. 5. 6. 0, IsoPrime). Δ  13  C proxy for milk exploitation. The δ  13  C values of the C 16:0 and C 18:0 fatty acids from more than 170 modern ruminant adipose and dairy fats taken from animals raised in Europe, Eurasia and Africa, reveal a consistent difference in the δ  13  C values of the C 18:0 fatty acid, which relate to the different biosynthetic origins of this fatty acid in the two fat types  16, 47. The result is that δ  13  C values of the C 18:0 fatty acid in milk are always depleted compared to the C 18:0 fatty acid in ruminant adipose fats by on average 2. 3‰ (ref. 16 ). This difference allows archaeological ruminant fats extracted from pottery to be assigned as either milk or adipose fats.
Chronology. Archaeological sherds are associated in the MySQL database with specific site phases. Each phase is assigned a uniform date range using published start and end dates from archaeological site reports. If unavailable, we used calibrated  162  radiocarbon dates to construct phase models in OxCal  163  and used the mode of each boundary posterior distribution as start and end dates. In cases in which neither of these sources was available (10% of phases), phases 'borrow' their chronology from the geographically closest site phase that has the same associated culture. Date ranges of site phases are reasonably constrained (75% less than 580 years).
UK Biobank analysis Data. UK Biobank 4,5 is a large prospective cohort study of approximately 500,000 UK participants aged 37-73 years at recruitment (2006-2010). The study collected a wide-range of measures including demographics, health status, lifestyle, cognitive function, mental and physical health and molecular data such as genetic and biomarkers. UK Biobank received ethical approval from the Research Ethics Committee (REC reference for UK Biobank is 11/NW/0382). All analyses were performed under application no. 16729. Dairy consumption. Multiple measures of milk consumption were evaluated in this study. Milk servings. Participants were asked: How many glasses/cartons/ 250 ml of milk (excluding milkshakes) did you consume yesterday? (field 100520) and how many glasses/cartons/250 ml of yogurt drinks, flavoured milk or milkshakes did you consume yesterday? (field 100530).
Ancient DNA analyses Data. We collated published BAM files from 2,999 ancient Eurasian individuals  25, 27,  , out of which 1,786 had the European LP single nucleotide polymorphism (SNP) covered at least once (read depth: span 1 to 128-fold, average sevenfold). All gen mes came aligned to the GRCh37/hg19 human reference assembly but for the Tyrolean Iceman (hg18). Relevant geographic and temporal annotation was extracted from D. Reich's aDNA compendium v. 44. 3 (ref. 218  ), see Fig. 3  for a representation of the full dataset. For the joint analyses of genetic and ecological data, we restricted this dataset to those individuals spatiotemporally overlapping the ecological data (four geographic regions: 'British Isles', 'Rhine-Danube axis', 'Mediterranean Europe' and the 'Baltic region'; 8,000-2,500 years bp), leaving 2,162, out of which 1,293 had the lactase locus covered at least once (read depth: span 1-128-fold, average sevenfold).
High estimation errors are exclusively found when few derived alleles are simulated, as the latter are responsible for important likelihood differences between models with appreciable LP allele frequencies. The number of derived alleles in our dataset seems to be high enough to estimate s with high accuracy and a at least with intermediate accuracy. Besides the estimation of actual model parameters, we quantified the power to select a model with milk as a driver over a constant selection model. For the same set of simulations underlying Supplementary Fig. 3 , we show the likelihood differences between a model of constant selection and one in which milk exploitation drives selection strength on the derived LP allele in Supplementary Fig. 4. With less than 30 derived alleles, which is the number we observe in the actual data, only 20% of the likelihood differences pass the significance threshold, compared to 81% for simulations with at least the same number of derived alleles (51% overall), in which we restricted the set of simulations only to those with an estimated parameter a above 0.
Ecological proxy variables We generate five ecological variables as proxies for suggested drivers of LP selection. Each variable is generated for four geographic polygons which overlap spatially and temporally with our ancient genetic data ('British Isles', 'Baltic region', 'Rhine-Danube axis' and 'Mediterranean Europe'). We make no assumption about the direction of the possible relationship between each variable (V) and the selection coefficient (that is, if they are positively or negatively correlated). Therefore, we also generate a set of inverse variables, which can be notionally considered as a reflection; for example, a variable that ranges between 0 and 1 will have an inverse variable between 1 and 0. Radiocarbon dates. Two of the five ecological variables (residential density and fluctuations in population levels) were constructed directly by using an extensive database comprising >110,000  14  C dates which we compiled from over 1,000 published sources including CalPal  225  , BANADORA  226  , RADON  227  , EUROEVOL  228  , Wales and Borders radiocarbon database  229  , Scottish Radiocarbon Database  230  , ref.
Residential density (clustering). Under the assumption that dwelling proximity increases the potential for the spread of disease in a population, our 'chronic' mechanism proposes that periods and regions of greater residential density would tend to suffer more from diseases, providing greater selection on LP. We construct a residential density statistic (RDS) from the site locations of our radiocarbon database. The RDS is influenced neither by the number of archaeological sites (which is heavily biased by differential sampling and a general increase through the Neolithic period from population growth) nor by geographic structure in the site locations (caused by features such as islands and mountains). Instead, our RDS uses the distribution of pairwise distances between all sites in a region as a null expectation and then calculates how the distribution of pairwise distances in each time slice deviates from this expected distribution.
Animal exploitation. Fluctuations between domestic and wild animal exploitation for meat have the potential to inform on various economic, social and food production changes. For example, we might expect an increase in the proportion of domesticates to be associated with greater animal husbandry and increased contact with animals could lead to a greater probability of zoonotic diseases and therefore greater selection. Conversely, we might expect periods of famine from failure of agriculture to result in a return to exploiting wild resources, thus a decrease in domestic animals might correlate with periods (and regions) with greater selection. We extract NISP counts of the main meat-bearing taxa for domestic (Bos taurus, Sus scrofa domesticus, Ovis aries, Capra hircus, Equus caballus) and wild (Bos primigenius, Sus scrofa scrofa, Cervus elaphus, Alces alces, Rupicapra rupicapra, Cervidae, Oryctolagus cuniculus, Lepus europaeus, Lagomorpha, Equus ferus) from the EUROEVOL  71  and OSSK  49  databases.
Therefore, for a given time slice the 'domesticates' and 'wild' NISP counts are used to calculate a proportion of domesticates. Fluctuations in population levels. We use our radiocarbon database and the R package ADMUR to directly model the underlying broadscale population dynamics as the combination of exponential population growth with power law taphonomic loss. An SPD was also generated and the residual difference between the short-term fluctuations of the SPD and the long-term trend of the model was used as the detrended proxy for short-term fluctuations in human presence through time. This was achieved independently for each of the four geographic polygons, after all radiocarbon dates were calibrated through the intcal20 curve  162  Finally, we normalize these residuals to a range between 0 and 1 globally, by scaling each variable by the smallest and largest values found across all polygons.
The interpolated surface was masked to coastlines and used the following R libraries: maptools  233  , mapdata (original S code by R. A. Becker and A. R. Wilks; R version by ref. 234  ), raster  235  , rgeos  236  and RColorBrewer 237. We constructed a two-dimensional Gaussian kernel for each site phase, the magnitude of which was weighted by the precision of the estimate, using 1 - 1/ n ( +1) ) for which n is the number of sherds that have yielded animal fats. The frequency of dairy residues at any geographic pointwas then calculated as the average of the proportion of sherds containing dairy fat residues over the total number of sherds yielding residues at a given site phase, weighted by the probability density function of each site phase's kernel at that point. Therefore, the influence each site phase has on any interpolated point on the map depends primarily on its geographic distance from that point but is also influenced by the error on its frequency estimate.
Data availability Data for running the aDNA analyses are available from https://github. com/ydiekmann/Evershed_Nature_2022. KML files, a summary of archaeological milk residue data, ecological proxy variables and a summary of radiocarbon dates are available from https://github. com/ AdrianTimpson/2020-03-03523A. UK Biobank data are available from: https://www. ukbiobank. ac. uk/.
Code availability R code for running the aDNA analyses is available from https://github. com/ydiekmann/Evershed_Nature_2022. Open-source R Code for running the UK Biobank analyses under MIT license are available from https://github. com/MRCIEU/lp-coevolution. R code for the generation of Figs. 1, 2, 3 and Extended Data Fig. 1  are available from https://github. com/AdrianTimpson/2020-03-03523A.
The recent realization of the Gaia Data Release 3 (DR3) catalog extended this dataset to about ∼60 000 asteroids observed in the VIS wavelengths  (Gaia Collaboration 2022; Tanga et al. 2022). On the other hand, multifilter photometry of asteroids still remains a common tool to study asteroid surface properties that is accessible for hundreds of thousands of asteroids from various space-and ground-based surveys. Multiple studies in the past used the scientific potential of large surveys. Zellner et al. (1985)  studied the distribution of asteroid types across the Solar System and in asteroid families using the ECAS photometric data and  Sykes et al. (2000)  did so based on NIR photometry from the Two Micron All Sky Survey (2MASS). A similar study of several asteroid families was performed more recently by  Erasmus et al.
(2020)  using the Asteroid Terrestrial-impact Last Alert System (ATLAS) survey photometry in orange and cyan bands. Data from two other large spectro-photometric sky surveys -the Sloan Digital Sky Survey (SDDS) and the Visible and Infrared Survey telescope for Astronomy (VISTA) -were intensely utilized in asteroid studies. Ivezić et al. (2002)  used the colors derived from SDSS to assign asteroids into broad C, S and, V types and  Parker et al. (2008)  did so to provide implications to the dynamics of asteroid families. Nesvornỳ et al. (2005)  used principal component analysis to distinguish the SDSS data into three main complexes -S, C, and X -and they analyzed space weathering trends. Later on,  Thomas et al. (2012)  and  Carry et al. (2016)  extended this work to asteroid families and Mars crossers.
We use several metrics to compare the results. This allows, for the first time, for a uniform and detailed comparison of taxonomic predictability among large surveys and multiple classification methods. In Sect. 2 we describe the original spectral dataset, cloned spectral data, and the final sample used for each survey. We briefly describe each survey in the same section. In Sect. 3 we report the machine learning methods and evaluation metricises that were applied. In Sect. 4 we discuss the results. Conclusions are provided in Sect. 5.
Simulating photometry from spectra We used the collection of about 6000 spectra of  Mahlke et al. (2022). We trimmed this dataset to 770 spectra of 596 unique asteroids that cover both VIS and NIR wavelength ranges. We further filtered these spectra to only contain the taxonomic types from the Bus-DeMeo taxonomy, resulting in 754 spectra. Lastly, we removed types with only one object, with the resulting set consisting of 752 objects. This limitation is necessary to test taxonomic predictions on the same dataset for all surveys, thus allowing for a direct comparison of their efficiency. We then generated clones of these VIS-NIR spectra, increasing the sample size by a factor of ten. Cloning and sampling has been a common practice to increase the sample size for machine learning algorithms  (Cellino et al.