dataesr/scientific-paragraphs-categorization huggingface dataset:
TYPE MATERIAL The type materials were deposited in the collection of the Institute of Systematics and Evolution of Animals of the Polish Academy of Sciences (ISEA), Cracow, Poland, and in the collection of the State Museum of Natural History (SMNH) of the National Academy of Sciences of Ukraine, L'viv, Ukraine. HOLOTYPE 1 female (ISEA 6647) USA: Indiana, Oakland City, Hugh Boyd, Patoka River National Wildlife Refuge and Management Area, 9-V-2008, latitude 38. 3539°N, longitude 87. 3156°E, elevation 133 m, deciduous growth with dominant black locust tree (Robinia pseudoacacia L. ; Fabaceae) and red oak, sample of litter and rhizosphere, collected by J. Tajovský & J. Frouz. PARATYPES 2 females (ISEA 6648, SMNH 89. 1), data same as holotype. Table  1. List of investigated proturans and accession numbers of gene sequences used in the phylogenetic analysis (a dash indicates that the gene sequence was not available).
noeli and Andinentulus rapoporti (2 different specimens); 28S rDNA D3-D6: A. charrieri (2 different specimens), A. noeli (2 different specimens), A. pyreneicus, and Andinentulus rapoporti. The se-quences were deposited in BOLD under accession numbers ABPE002-17-ABPE011-17 (see Table  1 ). The concatenated data (COI, 18S rRNA, 28S rDNA D1-D2, and 28S rDNA D3-D6) consist of a total alignment length of 4,438 bp for 55 terminal taxa (27 species). The ML inference and direct optimization parsimony phylogenies all showed consistent agreement among topologies. The only real difference is the position of Nosekiella+Huashanentulus sister group of Acerella in the ML analysis and sister group of the rest of Acerentominae in parsimony. Here we show the ML tree (Fig. 41 ).
Acknowledgments We thank the anonymous reviewers for their helpful comments. We are thankful to  K. Tajovský  and  J. Frouz  for collection of proturan material in the  Patoka River National Wildlife Refuge, Indiana, USA , and to  E. C. Bernard  for collection of A. confinis material in Tennessee,  USA , and for his correction of English. Field collection (2008) was supported by  CaFoTrop  (www. cafotrop. com). The laboratory work was done in the  D'Haese's BoEM laboratory. This research received support from the  SYNTHESYS  Project (http://www. SYNTHESYS. Info/), which is financed by  European Community Research Infrastructure Action  under the  FP7 Integrating Activities Programme and  from the  Ministry of Education, Youth , and Sports, project no. ME08019.
Tree-ring widths were measured, then visually cross-dated using the list method  (Yamaguchi, 1991). We used the computer program COFECHA, which uses segmented time-series correlation techniques, to statistically confirm our visual cross-dating  (Holmes, 1983; Grissino-Mayer, 2001). Cross-dated treering time series were then standardized by fitting a 67 % cubic smoothing spline with a 50 % cutoff frequency to remove non-climatic trends related to the age, size and the effects of stand dynamics using the ARSTAN program  (Cook, 1985; Cook et al. , 1990a). These detrended series were then pre-whitened with low-order autoregressive models to produce time series with a strong common signal and without biological persistence. These series may be more suitable to understand the effect of climate on tree growth, even if any persistence due to climate might be removed by pre-whitening.
Identifying relationships between tree-ring width and climate We extracted high-resolution monthly temperature and precipitation records from the climate dataset CRU TS 3. 23 gridded at 0. 5 First, the climate-growth relationships were investigated with response function analysis (RFA;  Fritts, 1976)  for biological year from the previous October to current October using the DENDROCLIM2002 program  (Biondi and Waikul, 2004). This analysis is done to determine the months during which the tree growth is the most responsive to temperature. RFA results showed that precipitation from May to August and temperature in March and April have dominant control on tree-ring formation in the area. Second, we produced correlation maps showing correlation coefficients between tree-ring chronologies and the climate factors most important for tree growth, which are May-August precipitation and March-April temperature, to find the spatial structure of radial growth-climate relationship  (St.
Third, the final reconstruction is based on bootstrap regression  (Till and Guiot, 1990) , a method designed to calculate appropriate confidence intervals for reconstructed values and explained variance even in cases of short time series. It consists in randomly resampling the calibration datasets to produce 1000 calibration equations based on a number of slightly different datasets. The quality of the reconstruction is assessed by a number of standard statistics. The overall quality of fit of reconstruction is evaluated based on the determination coefficient (R 2 ), which expresses the percentage of variance explained by the model and RMSE, which expresses the calibration error. This does not ensure the quality of the extrapolation which needs additional statistics based on independent observations, i.
, 2011; Güner et al. , 2016). Moreover, seemingly innocuous short-term warm events, such as the 1807 event, were recorded across the Mediterranean and in high elevations of the European regions. Casty et al. (2005)   2013 ) temperature record did not capture the 20th century warming trend as found elsewhere  (Wahl et al. , 2010). However, their temperature trend does agree with trend analyses conducted on meteorological data from Turkey and other areas in the eastern Mediterranean region. The warming trend seen during our reconstruction calibration period  was similar to the data shown by  Wahl et al. (2010)  across the region and hemisphere. Further, the warming trends seen in our record agrees with data presented by  Turkes and Sumer (2004) , of which they attributed to increased urbanization in Turkey.
Comparison of instrumental gridded data and spatial reconstructions Spatial correlation analysis revealed that our network-based temperature reconstruction was representative of conditions across Turkey as well as the broader Mediterranean region (Fig. 7 ). During the period 1930-2002, estimated temperature values were highly significant (r range 0. 5-0. 6, p < 0. 01) with instrumental conditions recorded from southern Ukraine to the west across Romania, and from northern areas of Libya and Egypt to the east across Iraq. The strength of the reconstruction model is evident in the broad spatial implications demonstrated by the temperature record. Thus, we interpret warm and cold periods and extreme events within the record with high confidence. We compared our tree-ring-based temperature reconstruction with existing gridded temperature reconstructions for Europe  (Xoplaki et al.
This research was supported by the  Scientific and Technical Research Council of Turkey (TUBITAK) , projects  ÇAYDAG 107Y267  and  YDABAG 102Y063. Nesibe Köse  was supported by the  Council of Higher Education of Turkey. We are grateful to the  Turkish Forest Service  personnel and  Ali Kaya ,  Umut Ç. Kahraman  and  Hüseyin Yurtseven  for their invaluable support during our field studies. We thank  Ufuk Turuncoglu  for his help on spatial analysis. Joel Guiot was supported by the  Labex OT-Med  ( ANR-11-LABEX-0061 ),  French National Research Agency (ANR).
| Diploid male occurrence and male reproduction To estimate diploid male occurrence, molecular analyses were carried out using a multiplex PCR kit with 11 microsatellite molecular markers developed for this species  (Retamal et al. , 2016). If a male was heterozygous at one or more markers, it was considered diploid. This estimation is conservative because diploid males homozygous for all microsatellite markers are erroneously categorized as haploid. The proportion of diploid males among those used for the controlled crossings in the G0 generation (N = 73) and for G1-G4 (N = 249) was estimated based on male origin data (crossing treatment and generation when the male was born). Generation 5 was not included, because only seven males from outbred lines were genotyped. The progeny of females mated with genotyped males was available for 226 crosses.
From this dataset, we determined the proportion of diploid (N = 71) and haploid males (N = 155) siring daughters (an indication of male fertility) under inbred and outbred crosses. Additionally, the number of daughters, number of sons, and total adult offspring in relation to male ploidy, crossing treatment, and generation were noted. Finally, to estimate whether males sired fertile daughters, we verified the proportion of diploid and haploid males siring granddaughters in inbred and outbred lines. This dataset included 12 diploid males and 108 haploid males that sired daughters for which their progeny were followed in the main experiment (i. e. , there was a record of the progeny of the daughters). Note that because in the main experiment only up to two females were followed per line in each generation, the records of only up to two daughters per male were available.
| Data analysis Female life history traits (Hypothesis 1). When data for two females per line per generation were available, only one was chosen at random for the analyses, which resulted in a dataset of the progeny of 266 crosses. Generalized linear models (GLM) with different error distributions and link functions were used to test the effect of crossing treatment (inbred or outbred), generation (1 to 5), and their interaction on life history traits. The best fitted models used a Poisson error distribution (accounting for overdispersion) with a log link function for count data (fecundity and longevity), and binomial error distribution (accounting for overdispersion) with a logit link function for proportional data (offspring survival and parasitism rate). Traits associated with production of diploid males (Hypothesis 2).
With the above dataset, we also used GLM to test for the effect of crossing treatment and generation on number of daughters (Poisson error distribution accounting for overdispersion with a log link function), offspring sex ratio (binomial error distribution accounting for overdispersion, logit link function), and proportion of diploid males (binomial error distribution, logit link function). Diploid male fertility (Hypothesis 3). For this analysis, we used the data from all available genotyped males (N = 226) to increase representation of diploid males in inbred and outbred lines and generations. This included 157 crosses of the above dataset plus 69 from those not chosen for the female life history trait analysis. Similarly, we used GLM to test for the effect of male ploidy, crossing treatment, and generation on number of daughters, number of sons, and total offspring (Poisson error distribution accounting for overdispersion with a log link function), and the effect of male ploidy and crossing treatment on proportion of males siring daughters (binomial error distribution with a logit link function).
ACKNOWLEDGEMENTS This work was financed by the  Chilean Government through Fondecyt 1131145. Additional funding was received by the  European Union Seventh Framework Program FP7  (grant agreement  FP7-PEOPLE-IRSES # 612 , 566  " BIOMODICS "). We thank  Nick Mills  ( University of California at Berkeley ) for reviewing and earlier version of this manuscript and two anonymous reviewers. Alda Romero ,  Ivan Osorio , and many students help in the maintenance of the insect colonies for the experiment.
Results Anaerobically grown E. coli REL4536 has a higher spontaneous mutation rate than aerobically grown E. coli Escherichia coli REL4536 has been aerobically adapted to a minimal glucose medium  [15] , and was used to establish MA lineages on minimal glucose agar plates. Fifty lineages per growth regime were propagated daily aerobically, and every three days anaerobically, for 4,500 and 3,456 generations respectively, representing 180 and 144 single colony bottlenecks, respectively. Mutations were detected in evolved lineages, 24 per treatment, through whole genome re-sequencing by directly mapping sequence reads to the reference sequence to detect small mutations, and de-novo assembly and alignment of contigs to the reference genome for detection of SVs (S1 Dataset). A total of 282 mutations were detected (Fig 1A ), with 124 and 158 mutations identified in the aerobically and anaerobically grown cells, respectively (S2 Dataset).
Of these, 147 mutations were BPSs (74 and 73 in the aerobically and anaerobically grown cells, respectively), 98 were SVs (33 and 65) and 37 were indels (17 and 20) (S2 Dataset). Based on these data, the estimated spontaneous mutation rate of 1. 90 × 10 -3 mutations per genome per generation for anaerobically grown cells was 1. 7-fold greater [Mann-Whitney (MW) U = 196, p = 0. 029] than that of the aerobically grown cells, at 1. 15 × 10 -3 mutations per genome per generation (Table  1 ). Despite differences in the bacterial strain and media used, and when SVs were excluded from the analysis, the aerobic mutation rate calculated in this study is within the range of previous genome-based estimates for E. coli  [6]  that do not account for SV mutations. Furthermore, independent estimates of mutation rates were assessed by Luria-Delbru ¨ck fluctuation assays  [26]  using a nalidixic acid marker (S1 Table ).
SV and indel analyses SVs comprised 34. 8% of the mutations detected in this study (S2 Dataset). These were predominated by IS element mediated mutations (96%), though 2% of the SVs were mediated by other repeat-sequences, such as rhs elements. Two SVs were not associated with repeated sequences, suggesting a different mechanistic origin to IS element and repeat-mediated mutations. SVs were mainly detected in anaerobically grown cells, at a rate of 1. 74 × 10 -10 mutations per nucleotide per generation (Fig 1 ); 2. 6-fold greater than that of aerobically grown cells (6. 78 × 10 -11 mutations per nucleotide per generation; MW U = 146. 5, p = 0. 002). Analysis of the IS element-mediated mutations revealed that IS insertions were the most frequently observed type of SV  (Fig 4). The aerobic IS insertion rate (4.
However, IS150-mediated mutations were the most abundant overall, and ~10-fold more insertions per generation were detected from anaerobically, as compared to aerobically, grown cells (MW U = 75, p < 0. 001). A strong positive correlation between the copy number of each IS element type (S3 Table) and its aerobic  ). This was mainly driven by the large difference in IS150-mediated mutations between the two environments. To further investigate why IS150 was more active during anaerobic growth, consideration of IS element differences, their genomic contexts and expression levels were investigated and are discussed further below. Indels accounted for 13. 1% of all mutations identified in this study. The majority (51. 4%) of indels were slippage events in regions of repetitive DNA (S2 Dataset).
Within the REL4536 reference genome, IS150 was the largest IS element at a length of 1446 bp. Therefore, to ensure that all IS element meditated SV mutations could be detected, DNA was sequenced with 2 kb mate-pair inserts on the Illumina HiSeq 2000 platform (BGI). Paired-end sequencing with 90 bp reads resulted in over 98% genome coverage with the mean read depth ± standard deviation was 127. 6 ± 11. 1 and 64. 0 ± 24. 8 for the aerobic, and anaerobic genomes, respectively (S1 Dataset). The DNA sequences for the MA lines are deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive, BioProject PRJNA315479.
Mutation detection The E. coli REL4536 reference genome was manually annotated using information provided by Barrick et al. [15]  and the E. coli REL606 GenBank file (NCBI Reference Sequence NC_012967. 1). Sequence data from BGI had been filtered to remove reads containing ! 10% unreadable bases, ! 20% low quality ( Q20) bases, adapter contamination or duplicate readpairs and FastQC  [86]  was used to check the quality of the sequence data before analysis. BPSs, indels and MGE movement were identified using breseq  [87, 88]  with default parameters. To detect SVs, genomes were assembled de novo using SPAdes 3. 0. 0 [89]  with default parameters. Assemblies were aligned to the reference E. coli REL4536 genome using the NUCmer pipeline in MUMmer  [90]  and Mauve  [91]  with default parameters to identify SV breakpoints.
In this study, an increase in IS element copy number, as well as a change in the location of an IS element, were both counted as IS insertions. Spontaneous mutation rates for aerobically and anaerobically grown E. coli lineages were calculated with the equation μ = m/(L Ã N Ã T), where μ is the mutation rate per genome per generation, m is the total number of observed mutations, L is the number of MA lineages, N is the number of generations between bottlenecks and T is the number of bottlenecks (180 for aerobic lineages and 144 for anaerobic lineages). To obtain the mutation rate per nucleotide per generation, the equation μ/G was used, where G is the size of the genome that was sequenced (S1 Dataset). To obtain the mutation rate per genome per day, the equation μ' = m/(L Ã D) was used, where μ' is the mutation rate per genome per day, m is the total number of observed mutations, L is the number of MA lineages and D is the number of days of evolution (180 for aerobic lineages and 432 for anaerobic lineages).
Bowtie 2  [93]  was used with default parameters, to remove any sequence reads aligning to ribosomal RNA, transfer RNA and non-coding RNA sequences. EDGE-pro (Estimated Degree of Gene Expression in PROkaryotes)  [94]  and DESeq2  [95]  were used on the remaining reads to identify differential expression between aerobic and anaerobic environments. The RNA sequence data is available at NCBI GEO accession GSE80451.
Introduction The World Health Organization estimated that 47 million cases dementia existed worldwide in 2015 and predicted that this may triple by 2050 owing to ageing of the population. 1  In the absence of a cure, prevention studies are important to identify modifiable risk factors and protective factors to delay the onset or reduce the risk of dementia. 2 [14] [15]  Dementia is a progressive disorder involving changes over a long preclinical period,  16  which might include alterations in physical activity. Thus, studies with short follow-up times, typically less than 10 years, cannot distinguish causal effects from those due to preclinical changes (that is, reverse causation). ] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20]  To uncover the role of physical activity, we used data spanning nearly three decades to investigate the association between physical activity and cognitive function at ages 50, 60, 70, and 80 years; examine the association of physical activity with subsequent 15 year cognitive decline; assess the association between midlife physical activity and the risk of dementia; and model changes in physical activity over 28 years before diagnosis of dementia by using a backwards timescale anchored to year of diagnosis.
Cognitive function The cognitive test battery, introduced to the study in 1997-99 and repeated using the same tests at all subsequent assessments, allowed analysis using four waves of data between 1997 (age of participants 45-69 years) and 2013 (age 60-84 years). 31 The tests have good test-retest reliability (range 0. 6-0. 9), assessed in 556 participants and retested within three months in 1997-99. The cognitive domains assessed were as follows. Memory was assessed using a 20 word free recall test. Participants were presented a list of one or two syllable words at two second intervals and were then asked to recall in writing as many of the words as possible in any order with two minutes to do so. Executive function was assessed with the Alice Heim 4-I test, which is composed of a series of 65 verbal and mathematical reasoning items of increasing difficulty.
32 It tests inductive reasoning, measuring the ability to identify patterns and infer principles and rules. Participants had 10 minutes to do this section. Fluency was assessed using measures of phonemic and semantic fluency. 33 Participants were asked to recall in writing as many words beginning with "s" (phonemic fluency) and as many animal names (semantic fluency) as they could. One minute was allowed for each test. In addition to three cognitive domains, we created a global cognitive score incorporating all tests described above by firstly using the distribution of the first wave of cognitive data (1997-99) to standardise the raw scores for each domain to z scores (mean=0; standard deviation=1). We summed these z scores and restandardised them to yield the global score, an approach that minimises measurement error inherent in individual tests.
Dementia We used comprehensive tracing of electronic health records for ascertainment of dementia in three databases: the national Hospital Episode Statistics database, the Mental Health Services Data Set (MHSDS), and the mortality register. Record linkage until 31 March 2015, using ICD-10 (international classification of diseases 10th edition) codes F00, F01, F02, F03, F05. 1, G30, G31. 0, G31. 1, and G31. 8 identified cases of dementia. The NHS in the UK (England, Scotland, and Wales) provides most of the healthcare, including outpatient and inpatient care; private medical insurance, held by around 12% of the UK population (1997 figures),  35  is mainly used for elective surgery rather than chronic conditions such as dementia. MHSDS is a national database that contains information for people in contact with mental health services in hospitals, outpatient clinics, and the community.
Mortality data came from the British national mortality register (NHS Central Registry). The tracing exercise used the unique NHS identification number given to each resident in the UK. We set date of dementia at the first record of a diagnosis of dementia in any of the three databases used for ascertainment. The validity of dementia cases in our study is supported by modelling changes in the global cognitive score over 18 years before diagnosis of dementia. These results show accelerated decline in global cognitive score in the 8-10 years before diagnosis of dementia (supplementary figure A), as has been shown in studies that use a "gold standard" dementia ascertainment procedure. 36.
Association between physical activity and cognitive function These analyses were based on 7424 participants with data on cognitive function (added to the study protocol only in 1997-99). We first examined whether the association between physical activity over the follow-up (from 1997-99 to 2012-13) and cognitive function (time varying from 1997-99 onwards) changed with age by using linear mixed effect models with age as timescale and time varying physical activity and cognitive function. This model also included age (centred at mean age (65 years) over the follow-up period), age 2 , five year birth cohort, sociodemographic factors, health behaviours, and interaction terms of age and age 2 with both time varying physical activity categories and time invariant variables (sex, education, ethnicity); see equation 1 in supplementary methods.
com/subscribe dementia variable (no dementia, dementia with cardiovascular disease history, and without cardiovascular disease history) allowed us to examine changes in physical activity in relation to these subtypes of dementia. To determine whether poor sensitivity of our method of dementia ascertainment affected the results, we simulated scenarios with differential misclassification-that is, the hypothesis that the probability of dementia misclassification depends on physical activity-by using an SAS macro provided by Fox et al. 40  We allowed the sensitivity to vary between 50% and 80% and specificity between 97% and 100% with a trapezoidal probability density function. We simulated two scenarios: one in which the correlation between the sensitivity distribution in people following recommendations and the sensitivity distribution in all others was 0.