dataesr/scientific-paragraphs-categorization huggingface dataset:
Problems with P values and CIs are an ongoing topic for debate  (33) (34) (35) , but for this study CIs rather than P values were favored  (33)  for presentation and interpretation of findings. P values, however, are also provided for information regarding results from the regression analysis. Both P values and CIs should be interpreted bearing in mind that there was no adjustment for multiple comparisons. HbA 1c data were collected and analyzed for the study using percentage values but converted to International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) values in mmol/mol are also cited for key values reported in the text and tables. RESULTSdOf the 7,760 participants for whom any forms were returned to the coordinating center, 63 were excluded because the eligibility criteria had not been met (n = 25), the information needed to assess eligibility was incomplete (n = 35), or the data collection form was missing (n = 3).
Usable combined data therefore were available for 7,597 participants; 5,599 (73. 7%) of these were recruited from primary care and 1,998 (26. 3%) were recruited from specialist care. Recruitment from Sweden was well below target (550 cases) because of logistical problems linked to changes in the organization of care at the time of the study; the range of cases from the other participating countries was 950-1,056. Participants in the overall sample (Table  1 ) had a mean age of 66. 5 years (SD, 10. 8), 56% were male, and mean HbA 1c was 7. 1% (SD, 1. 1; 54 mmol/mol), with a between-country range of 6. 7% (50 mmol/mol) for the Netherlands to 7. 5% (58 mmol/mol) for Italy and the United Kingdom. Treatment patterns varied between countries, including rates of prescribing of insulin and more recently introduced therapies such as glucagon-like peptide 1 analogs; statistically significant variations included proportions prescribed any insulin when comparing countries where recruitment was predominantly or exclusively from primary care, for example, 16.
Therefore, the difference between statistically and clinically significant differences needs to be borne in mind. The GUIDANCE study has contributed to filling a gap in the literature   (22, 23) , and in one of these studies only two of the seven contributing countries (England and Scotland) were from Europe  (22). Findings from a sample of. 7,000 cases based on data from the late 1990s (  24 ) are useful but cannot be assumed to reflect recent quality of care and a more recent study using data from 2006 to 2007 was focused mainly on hypoglycemia  (25). A study involving 12 European countries provided limited data from a small pilotlevel sample  (26). The study has the advantages of a large sample size and data collection from a range of countries. Data for a high number of variables were collected using both self-report and medical records review, resulting in a rich overall dataset.
It is also likely that physicians with a particular interest in diabetes would have been more likely to agree to participate in this study and that the patients included in our dataset therefore were benefiting from enhanced management. These limitations are frequently applicable to datasets collected from prospectively recruited patients, but the use of routine data sources also may present problems relating to availability, accuracy, and completeness  (36). The need for realistic targets that are appropriate for individual patients with diabetes is not a new concept  (37) , but the limitations of using rigid targets for outcomes such as HbA 1c have been strongly re-emphasized in a recent joint position statement from the American Diabetes Association and the European Association for the Study of Diabetes  (12, 38).
AcknowledgmentsdThe GUIDANCE study was funded by the European Association for the Study of Diabetes from a grant from Merck & Co. (Whitehouse Station, NJ). Merck scientists participated in the initial conceptualization and protocol development but were not involved in the conduct of the study or in the analysis and interpretation of the data collected. No other potential conflicts of interest relevant to this article were reported. M. A. S. was involved in the conduct of the study in the United Kingdom, contributed to interpretation of findings, and wrote the paper. G. C. contributed to the conception and design of the study, was involved in the conduct of the study in France, and critically reviewed the manuscript, including interpretation of findings. K. D. was involved in the conduct of the study in Belgium and critically reviewed the manuscript, including interpretation of findings.
We obtained a very sharp PCR band that could be directly sequenced (Figure  1B , lanes 14 and 15). The 59 end of the atpH/F/A mRNAs maps at positions 245 upstream to the atpH AUG (Figure  3A , bottom panel) and the 39 end maps at position +448 downstream to the atpA stop codon (g in Figure  3A ). No sRNAs were found close to the +448 position  [3]. However, the upstream 50 nucleotides can fold in a very stable stem loop structure with a predicted DG of 229. 49 kcal/mol (using the MFOLD 3. 2 program, http://mobyle. pasteur. fr/cgibin/portal. py?#forms) (Figure  3B , right panel). These data suggest that the 39 end of the tri-cistronic atpH/F/A mRNAs is stabilized by a secondary structure rather than by a protein barrier. Finally, we analyzed the atpI/H/F/A co-transcripts. Long transcripts of the expected size (around 4600 nucleotides) could be detected in Northern blot analyses exclusively with the atpI probe (Figure  2A  and B , probe 1, star).
The genomic-relatedness-matrix restricted maximum likelihood (GREML) technique  15  uses all of the genotypic data from SNP arrays to estimate, for each pair of participants in a dataset, their degree of genetic similarity (relatedness), and then correlates genetic relatedness with phenotypic similarity across all of the pairs. Note that this technique does not require the participants to be related in the conventional genealogical sense of being siblings or cousins. It exploits the fact that all individuals within a population are distantly related, and that the level of relatedness varies considerably among pairs of people. For example, Davies et al. reported a GREML analysis with about 550,000 common SNPs and 3000 subjects in which about 45% of the variance in general cognitive ability could be directly explained by the SNP variation;  16  Chabris et al.
Thus, each of our 419 participants was tested individually in a laboratory session lasting an average of 3. 5 hours. To preview the results: Despite an adequate sample size for detecting large effects and despite high-precision measurements, we found few associations between SNPs and traits at an appropriately stringent significance threshold. Since many of our measured phenotypes (including our behavioral phenotypes) are known to be heritable,  28  the absence of strong associations in our data indicates that-aside from pigmentation-both physical and behavioral traits are mainly affected by numerous genes with small effects. After presenting the results, we discuss their implications for future genetic association studies of behavioral traits, which are likely to become ever more common as the cost of genotyping and sequencing declines.
Methods Participants were recruited, and data and samples were collected, at two sites: Harvard University in Cambridge, MA, and Union College in Schenectady, NY. Efforts were made to recruit from the surrounding communities a more representative sample than the typical college student population: Paper fliers were posted at various public locations, advertisements were placed in free newspapers and on Craigslist, and the study was made available to the Psychology Department Study Pool at Harvard. Participants first completed an online screening questionnaire that included items regarding age, medical history, and grandparental ethnicity. Participants who were younger than 18 or older than 45, or who reported a history of bipolar disorder, schizophrenia, or severe head trauma were excluded.
To help control for ancestral confounding of genotypes and trait levels,  29  we recruited a sample of predominantly Western European ancestry, which was ascertained at the screening process by asking potential participants to list the country of origin or ancestry for each of their biological grandparents. A total of 419 participants provided complete, usable genetic and phenotypic data. Eligible participants were invited to either the Harvard or Union lab for a data collection session lasting typically from three to four hours. Participants gave informed consent after the nature of the procedure had been fully explained to them. A diverse set of cognitive, personality, economic, attitude, demographic, and physical phenotypes were collected via computerized tasks, paper-and-pencil surveys, and face-to-face interaction.
DNA was collected via two mouthwash samples in the lab, and then extracted and genotyped elsewhere. Population stratification was investigated and controlled for in all genetic analyses reported here. We used the program PLINK for genotypic data cleaning and analyses. 30 (See for a complete list of phenotypes, descriptions of select phenotypes, and details of DNA collection, extraction, genotyping, and analysis of population stratification. ) Linear regression was performed to test for purely additive association between SNPs and all polytomous and continuous traits. Logistic regression was performed for dichotomous traits. We chose the standard genome-wide significance threshold of 5×10 -8 for declaring a SNP-trait association to be statistically significant. 31 Under a frequentist approach aiming to minimize the chance that even a single declared "hit" is a false positive, the large number of examined traits would require an even more stringent threshold.
This will remain an important complement to volunteer-and consumer-driven approaches. Recall that Chabris et al. consulted three population-based studies and found that only one out of 12 published genetic associations with general intelligence could be replicated within them, and that one only one out of three times. 11 One explanation is that the original associations came from small convenience samples similar to the one we studied here. There is, however, a tradeoff inherent in using large population-based studies for gene discovery. Most of these projects are directed towards medical outcomes rather than socialscience traits (with some notable exceptions, such as the Health and Retirement Study, the Wisconsin Longitudinal Study, and the English Longitudinal Study of Aging; the first of these now has GWAS data available, and the others may soon).
3. If there are two ways to measure a trait-a high-reliability measure that can be performed only on a small sample because of the required time, effort, and resources, versus a lower-reliability brief measure that can be administered to a large sample-power analyses suggest that using the lower-reliability measure with the larger sample size is likely to be the best strategy. Researchers interested in the genetic architecture of behavioral traits should therefore consider working with large-scale survey datasets such as the HRS, WLS, and ELSA, as well as medicalgenetic studies that are willing to conduct social science surveys among their participants. 4. Genetic associations with behavioral traits have proven notoriously difficult to replicate. This is not because the relevant traits are not heritable or the original studies were poorly designed or knowingly underpowered; researchers at the time lacked the resources for conducting more genotyping and assembling larger samples, and they were hoping to find common alleles with large effect size.
Our discussion of Fisher's model, and the empirical experience accumulated in the first fifteen years of social science genetics, suggest that individual gene effect sizes for traits not under strong selection are likely to be extremely small, and therefore require extremely large datasets to be detected. The fact that faster, cheaper, and more powerful methods of genotyping have led to fewer, smaller, and less reliable findings on the connection between genes and behavior, despite the near-certainty that such connections exist, stands as one of the disappointments of 21st century science. To make progress, we should shift away from the traditional model of epidemiology via statistical significance testing, in which large significant correlations are the standards of success and worthy of newspaper headlines, while negative results are considered a failure and destined for the file drawer.
Risk aversion 54% Income (20-year average) Benjamin et al. 4  Men 58% Women 46% * Estimated from genome-wide SNP data from twin and sibling pairs in Australia. Notes: Estimates are averages of male and female heritabilities except when heritabilities are provided separately for both sexes (these are cases in which heritability differs by a large amount between males and females). Except in the third section, heritability estimates are not adjusted for differences in measurement error, longitudinal stability, or test-retest reliability of the phenotypes. 07.
Acknowledgments We thank  Stephen M. Kosslyn  for his support. Brian Atwood ,  Chris Eur ,  Kathleen Huber ,  Sara Igoe ,  Minji K. Lee ,  Melissa Liebert ,  Jaclyn Mandart ,  Ben Orlin ,  Mike Puempel ,  Esther Snyder ,  Martha Widger ,  Linda Yao , and  Chelsea Zhang  provided research assistance. Funding was provided by research funds of the authors, as well as  NIA  grant  T32-AG00186  to the  National Bureau of Economic Research. The study reported here was approved by the  Institutional Review Boards of Harvard University and Union College.
PyroSuite This program (available upon request) was developed to combine algorithms from several packages in order to (i) compute indices and rarefaction curves to determine whether the data set is representative of the sample biodiversity (http://www. mothur. org/); (ii) compare the sampled sequences against a local dedicated bank for automated identification (Blastn http://blast. ncbi. nlm. nih. gov or Blat http://genome. ucsc. edu); and (iii) study their clusterization in terms of relative abundance and annotated phylogenetic trees (Phylip (http://www. phylip. com/ )). PyroSuite includes several subroutines, of which the following are the two most important.
PyroSeqToAlignedSeq This handles the Mothur Software  (Schloss 2009) , reading the commercial sequence fasta file, selecting a valid subset of the sequence stretches and producing an alignment fasta file through several algorithms described in the "Costello stool analysis"  (Costello et al. 2009). Reads from commercial files were shortened when more than two undetermined bases (N) were found and Phred quality scores were Q 30. Sequences with more than eight repeats or smaller than 100 bp were eliminated, as well as primer sequences with mismatches. Sequence boundaries were chosen and SILVA  (Pruesse et al. 2007 ) was used as the reference alignment in the process according to the analyzed amplicons data set (Bacteria, Archae, Eukarya, or Universal). The subroutine also computes rarefaction curves.
IdentifySeq This subroutine uses different information sources: taxonomic files (GenBank), a dedicated annotated databank fasta file extracted from the updated archive of Genbank, EMBL, and DDBJ, and a subset of the alignment fasta file produced by PyroSeqToAlignedSeq. The sequences of this last file were processed with BLAST or BLAT against the annotated bank for identification, producing two files containing the BLAST result and ID of each sequence. Also produced are two files, which can identify and calculate the relative importance of redundant sequences.
This technology is a powerful method for investigating the diversity of complex ecosystems compared to conventional cloning analyses whereas not exempted of some bias or limitations  (Tedersoo et al. 2010; Pinto and Raskin 2012). As every recent technologies, improvement will be done, notably with the arrival of ~3000-base single-molecule reads of Pacific Biosciences  (Eid et al. 2009; Ribeiro et al. 2012). To detect most of the organisms in this ecosystem, we used several primer pairs, either universal or specific for prokaryotic, eukaryotic, and archaeal cells, which targeted the ribosomal DNA gene region, owing to the richness of the corresponding databases. The number of sequences recovered by each primer pair was highly variable and illustrates the wellknown amplification bias introduced by primer selection  (Polz and Cavanaugh 1998; Baker et al.
The presence in our samples of Rhodoferax, which are able to degrade phenoxyherbicides  (Ehrig et al. 1997) , suggests that these communities could have been previously in contact with such pollutants. Potential human pathogens were also identified in all samples by culture (data not shown), mostly Enterobacteriaceae (Klebsiella and Enterobacter), Aeromonas, and Pseudomonas. Most of these isolates were resistant to antibiotics, with 75% of them producing cephalosporinases and 48% showing resistance to quinolones (data not shown). It is likely that sewage treatment processes are unable to avoid the dissemination of such resistant bacteria into the environment, resulting therefore in their contact with water-or soil-borne microorganisms. In this study, no member of the domain Archaea was detected, although 144 sequences were initially retrieved using primer pairs designed to detect archaea.
The cross section is defined as a single-inclusive cross section, i. e. several high-p T hadrons per muon-scattering event are counted for the hadron yield N h. The experimental data were recorded in 2004 with the COMPASS spectrometer at CERN. In the experiment a naturally-polarized 160 GeV/c µ + -beam scatters off a polarized, isoscalar target that consists of granulated 6 LiD immersed in liquid helium. The small admixtures of H, 3 He, and 7 Li lead to an excess of neutrons of about 0. 1%. The target is arranged in two oppositely polarized 60 cm long cells. The unpolarized cross section is obtained by averaging over the target polarizations. Since the azimuthal angles of the produced hadrons are integrated over, the cross section does not depend on the beam polarization. The integrated luminosity is determined via the direct measurement of the rate of beam muons crossing the target and is found to be equal to 142 pb -1 ± 10%(syst.
Acknowledgments We thank  W. Vogelsang  and  M. Pfeuffer  for many useful discussions and for providing the pQCD calculations, and  A. Afanasev  for estimating the QED radiative corrections. We acknowledge the support of the CERN management and staff, as well as the skills and efforts of the technicians of the collaborating institutions. Special thanks go to  V. Anosov  and  V. Pesaro  for their technical support during the installation and the running of this experiment. This work was made possible thanks to the financial support of our funding agencies.
j Supported by the  German Bundesministerium für Bildung und Forschung k Supported by Czech Republic MEYS  Grants  ME492  and LA242 l Supported by  SAIL (CSR), Govt. of India m Supported by  CERN-RFBR  Grants  08-02-91009  and  12-02-91500  n Supported by the  Portuguese FCT -Fundacão para a Ciência e Tecnologia, COMPETE  and QREN, Grants  CERN/FP/109323/2009 ,  CERN/FP/116376/2010  and  CERN/FP/123600/2011  o Supported by the  MEXT  and the  JSPS  under the Grants No. 18002006 , No. 20540299  and No. 18540281 ;  Daiko Foundation  and Yamada Foundation p Supported by the  DFG cluster of excellence 'Origin and Structure of the Universe'  (www. universecluster. de)q Supported by  EU   FP7  ( HadronPhysics3 , Grant Agreement number  283286 ) r Supported by the  Israel Science Foundation , founded by the  Israel Academy of Sciences  and Humanities s Supported by the  Polish NCN  Grant  DEC-2011/01/M/ST2/02350  * Deceased.
Introduction Leg ulcers have been previously reported in 25-65% of adult sickle cell patients in Jamaica  [1, 2]  but the incidence is much lower (2-2. 5%) in North America  [2, 3]. Leg ulcers are often refractory to treatment and are prone to recurrence  [1, 2]. While the exact causes of recurrent leg ulcers are unknown  [4] [5] [6] [7] , several studies support a role of hemolysis. Nolan et al  [7]  shown that patients with sickle cell anemia (SCA) and leg ulcers had lower hemoglobin level and higher levels of lactate dehydrogenase (LDH), bilirubin, aspartate transaminase and reticulocyte counts than SCA patients without leg ulcers. Similar observation was made by Taylor et al  [8]  who observed higher frequency of patients with a positive history of leg ulcers in the top quartile of serum LDH level in the NIH database and the Cooperative Study of Sickle Cell Disease database (CSSD).
Statistical analysis Results are presented as means ± SD. Unpaired Student's ttest and chi-square test were used for continuous covariates and for categorical covariates, respectively, to compare biological parameters between the ULC-and ULC+ groups. Principal component analysis was used to derive the hemolytic component. Significance level was defined as p < 0. 05. Analyses were conducted using SPSS (v. 20, IBM SPSS Statistics, Chicago, IL).
Numerical predictions Numerical predictions are carried out with the following conditions: • the mechanical loading consists of tensile cycles in such a way that the uniaxial strain oscillates between 0 and 5 × 10 -4 , which corresponds to a stress variation between 0 and 35 MPa; • a sinusoidal signal shape is considered; • the frequency is set to 3 Hz; • thermophysical properties, issued from the Sciglass database  [14]  are reported in Table  1. Under adiabatic conditions, the frequency does not influence the amplitude of the temperature oscillation. Under non-adiabatic conditions, it affects the temperature variation because of the heat exchanges with the outside. In the experiments presented in Section 3, τ is equal to  130 s. This means that the steady-state regime of the temperature evolution is reached from about 3 or 4 times this duration.
Methods Scopus, Web of Science, and Medline databases were searched to retrieve and analyze published SUPC cases and reports concerning early SUDI, early neonatal sudden unexpected death, SUEND, and early ALTE occurring during the first postnatal days in presumably healthy term and near term newborns. The selection criteria of the published articles were derived from the general guidelines for systematic reviews  [8, 9]. All the terms comprised in "SUPC," "SUDI," "SUEND," "ALTE," and the terms "newborn infant" or "neonate" were used as MesH terms for the research process. All references of retrieved articles were cross-searched. We used the recent definition of a SUPC event established in "The guidelines for the investigation of newborn infants who suffer a sudden and unexpected postnatal collapse"  [7].
We thus included infants born >35 weeks gestational age, with 10 min Apgar of >7, considered healthy who collapsed suddenly and unexpectedly within the first postnatal week  [7, 10, 11]. We excluded cases that occurred after the first week of life and only retained articles in which minimal neonatal data were available. All articles with an English language title were analyzed. Non-English articles in French or Spanish were analyzed with the help of native language scientist in the research group (Drs. Kuhn and Perez, respectively). Unpublished studies were excluded. We then determined which type of study (case report, site, regional study, or population survey) and which inclusion and exclusion criteria (gestational age, postnatal age, underlying conditions, outcome, as well as risk and associated factors) were reported.