dataesr/scientific-paragraphs-categorization huggingface dataset:
Resvega Alters the Level of Autophagy Markers p62 and LC3 ARPE-19 cells were treated with Resvega for 6 h, 12 h, and 48 h. Protein levels of autophagy markers p62 and LC3 were analyzed at each time point to study the activation of autophagy. Western blot data showed a mild increase in p62 content after Resvega treatment for 6 h and 12 h, the p62 level being significantly higher after Resvega treatment for 48 h (approximately nine-fold increase vs. control) (Figure  1A ). The LC3-II protein level showed slight increase after 6 h of Resvega treatment, but decreased to baseline levels at 12 h and 48 h (Figure  1B ). The protein expression of LC3-I was also decreased by Resvega treatment at 12 h, possibly due to the conversion of LC3-I to LC3-II in the autophagosome maturation (Figure  1B ). The levels of LC3-I remained unchanged at 6 h and 48 h.
Acknowledgments: The authors would like to thank  Anne Seppänen  for technical assistance. This work was supported by a grant from  University of Eastern Finland  spearhead project " Changing Climate and Biological Interactions Related to Forests, CABI ", the  Finnish Cultural Foundation-North-Savo , the  Finnish Eye Foundation  and the  Kuopio University Hospital   VTR grant  ( 5503743 ). Goran Petrovski  and his Group are funded by the  National Brain Research Program  ( KTIA_NAP_13-A_III/9 ) in Hungary.
, 2014; R Core Team, 2015). Full code in R for simulations, figures and calculation of context-specific repeatabilities and cross-environmental correlations is given in the supplementary material. another. See supplementary material for code in R to simulate Fig. 1  and calculate both R context and across-context correlations. Currently, across-context correlations and R context are available for only a handful of studies on fish  (Biro and Adriaenssens, 2013; Harrison et al. , 2015)  but are likely to provide a powerful tool for future field studies in which environmental variables (e. g. temperature) can be measured as a continuous variable. Indeed, researchers have used a wide variety of metrics to measure individual consistency and often do this under the same heading of 'repeatability'.
Curves are shown in black for 10 randomly selected individuals to enhance clarity of how each scenario affects crossing of individual curves, whereas remaining curves are plotted in light grey. All simulations and models were fitted using the package lme4 in R (Bates et al. , 2014; R Core Team, 2015). Full code in R for simulations, figures and calculation of context-specific repeatabilities and cross-environmental correlations is given in the supplementary material.
Acknowledgements Inspiration for this manuscript came during workshop sessions at the European Cooperation in Science and Technology Action FA1004 4th Conference on Conservation Physiology of  Marine Fishes , Thessaloniki, Greece, 2014. We thank all those in attendance for their input in these discussions. We thank two anonymous reviewers for their comments on the manuscript. We also thank  Natalie Sopinka ,  Jake Brownscombe ,  Phil Harrison  and  Alex Wilson  for input on the manuscript.
whose EA was assessed at or above age 30. A uniform set of quality-control (QC) procedures was applied to the cohort-level summary statistics. In our GWAS meta-analysis of ∼9. 3M SNPs from the 1000 Genomes Project, we used sample-size weighting and applied a single round of genomic control at the cohort level. Our meta-analysis identified 74 approximately independent genome-wide significant loci. For each locus, we define the "lead SNP" as the SNP in the genomic region that has the smallest P-value (Supplementary Information section 1. 6. 1). Fig. 1  shows a Manhattan plot with the lead SNPs highlighted. This includes the three SNPs that reached genome-wide significance in the discovery stage of our previous GWAS meta-analysis of EA  1. The quantile-quantile (Q-Q) plot of the meta-analysis (Extended Data Fig.
3b ). To further test the robustness of our findings, we examined the within-sample and out-ofsample replicability of SNPs reaching genome-wide significance (Supplementary Information sections 1. 7-1. 8). We found that SNPs identified in the previous EA metaanalysis replicated in the new cohorts included here, and conversely, that SNPs reaching genome-wide significance in the new cohorts replicated in the old cohorts. For the out-ofsample replication analyses of our 74 lead SNPs, we used the interim release of the U. K. Biobank 5 (UKB) (N = 111,349). As shown in Extended Data Fig. 4 , 72 out of the 74 lead SNPs have a consistent sign (P = 1. 47×10 -19 ), 52 are significant at the 5% level (P = 2. 68×10 -50 ), and 7 reach genome-wide significance in the U. K. Biobank dataset (P = 1. 41×10 -42 ).
8×10  -8  ). We also found positive, statistically significant, but very small, genetic correlations with height (P = 5. 2×10  -15  ) and risk of schizophrenia (P = 3. 2×10 -4 ). Second, we examined whether our 74 lead SNPs are jointly associated with each phenotype (Extended Data Fig. 5  and Supplementary Information section 3. 3. 1). We reject the null hypothesis of no enrichment at P < 0. 05 for 10 of the 14 phenotypes (all the exceptions are subcortical brain structures). Third, for each phenotype, we tested (in the published GWAS results) each of our 74 lead SNPs or proxy for association at a significance threshold of 0. 05/74. We found a total of 25 SNPs meeting this threshold for any of these phenotypes, but only one reaching genomewide significance. While these results provide suggestive evidence that some of these SNPs may be associated with other phenotypes, further testing of these associations in independent cohorts is required (Supplementary Tables 3.
Annotations were derived from ENCODE and a number of other data sources. Plotted are the base-2 logarithms of the enrichments and their 95% confidence intervals. Multiple instances of the same annotation correspond to independent replicates of the same experiment. b, The results of combining multiple annotations and applying model selection and cross-validation. Although the maximum-likelihood estimates are plotted, model selection was performed with penalized likelihood. c, Reweighting of GWAS loci. Each point represents an LD-defined region of the genome, and shown are the regional posterior probabilities of association (PPAs). The x-axis give the PPA calculated from the GWAS summary statistics alone, whereas the y-axis gives the PPA upon reweighting on the basis of the annotations in b.
The orange points represent genomic regions where the PPA is equivalent to the standard GWAS significance threshold only upon reweighting. Extended Data Figure  8. Tissue-level biological annotation a, The enrichment factor for a given tissue type is the ratio of variance explained by SNPs in that group to the overall fraction of SNPs in that group. To benchmark the estimates for EduYears, we compare the enrichment factors to those obtained when we use the largest GWAS conducted to date on body mass index, height, and waist-to-hip ratio adjusted for BMI. The estimates were produced with the LDSC python software, using the LD Scores and functional annotations introduced in Finucane et al. (  2015 ) and the HapMap3 SNPs with MAF > 0. 05. Each of the 10 enrichment calculations for a particular cell type is performed independently, while each controlling for the 52 functional annotation categories in the full baseline model.
The error bars show the 95% confidence intervals. b, We took measurements of gene expression by the Genotype-Tissue Expression (GTEx) Consortium and determined whether the genes overlapping EduYears-associated loci are significantly overexpressed (relative to genes in random sets of loci matched by gene density) in each of 37 tissue types. These types are grouped in the panel by organ. The colored bars corresponding to tissues where there is significant overexpression. The y-axis is the significance on a -log 10 scale. Extended Data Figure  9. Gene-level biological annotation a, The DEPICT-prioritized genes for EduYears measured in the BrainSpan Developmental Transcriptome data (red curve) are more strongly expressed in the brain prenatally rather than postnatally. The DEPICT-prioritized genes exhibit similar gene-expression levels across different brain regions (gray lines).
Acknowledgments This research was carried out under the auspices of the  Social Science Genetic Association Consortium  (SSGAC). The SSGAC seeks to facilitate studies that investigate the influence of genes on human behavior, well-being, and social-scientific outcomes using large genome-wide association study meta-analyses. The SSGAC also provides opportunities for replication and promotes the collection of accurately measured, harmonized phenotypes across cohorts. The SSGAC operates as a working group within the  CHARGE consortium. This research has also been conducted using the  UK Biobank Resource. This study was supported by funding from the  Ragnar Söderberg Foundation  ( E9/11 ), the  Swedish Research Council  ( 421-2013-1061 ), The Jan Wallander and  Tom Hedelius Foundation , an  ERC Consolidator Grant  ( 647648 EdGe ), the  Pershing Square Fund of the Foundations of Human Behavior , and the  NIA/NIH  through grants  P01-AG005842 ,  P01-AG005842-20S2 ,  P30-AG012810 , and  T32-AG000186-23  to NBER, and  R01-AG042568  to USC.
AHP + AHPL The MATLAB EKF-SLAM toolbox  [44]  was extended with the heterogeneous functionality to perform the simulations. Figure  10a  shows the simulation environment. It consists of a house conformed by 23 lines and an array of 16 points distributed uniformly among the walls. The robot performs two different trajectories. The first one is a circular path of 5 m in diameter, with a pose step of 8 cm and 0. 09 •. The second is a motion of 70 steps of 4 cm, each taken towards the scene. The linear noise is 0. 5 cm and the angular noise 0. 05 •. Besides the heterogeneous landmark capability of the toolbox, the transparency of the objects in the scene was also considered. By default, objects in the simulation environment of the toolbox are transparent, so landmarks are visible on almost every image frame.
[25, 29]  for points and lines. The use of simulated data has shown how the choice of the landmark representation has an impact on the accuracy of the map. The best ones, considering the construction of a map with heterogeneous landmarks, are anchored homogeneous points and anchored homogeneous points lines. These parametrizations were used in a complete heterogeneous SLAM experiment that produced better results than the classic point-based case, by reducing the camera position estimation error. Another contribution of this paper is a method proposed for a segment-based SLAM front-end. This method relies on the line segment active-search process presented in this article and on state-of-the-art line detection and matching processes. The methods that compose the developed front-end that resulted were discussed, recalling, first, their theoretical background and, then, presenting some experimental evaluations on image sequences that show the stability of the process.
Acknowledgments: This study was performed during a long-term stay of  Jorge Othón Esparza-Jiménez, PhD  student in  Tecnológico de Monterrey, Mexico, in the Robot, Action and Perception team of LAAS-CNRS in France. The authors would like to thank  Mexico's National Council of Science and Technology (Consejo Nacional de Ciencia y Tecnología (CONACyT)) , the  Focus Group on Robotics at Tecnológico de Monterrey  and the  Laboratorio de Robótica del Área Noreste y Centro de México (Robotics Laboratory of Northeastern and Central Mexico)  founded by  CONACyT-Tecnológico de Monterrey , for supporting this research. This study contributes to the  French FUI  project  AIR-COBOT. The authors also acknowledge  Susan Fortenbaugh  for the English language revision of the paper.
Participants Nine pairs of healthy volunteers took part in this experiment. In order to generate a more robust self-other face merging illusory effect, we tested same-sexed pairs of participants. We excluded the data from four participants because of bad recording conditions during the IVS-phase (for more details, see Poststimulation Test). For the final analysis, we included, thus, the data from the remaining fourteen participants (six women, eight men; aged 19-32 years; mean ± SD 22. 1 ± 3). All participants were right-handed according to the Edinburgh handedness inventory  (Oldfield, 1971). All participants had normal vision, i. e. , without correction. Thus, individuals with eyeglasses for vision correction or contact lens were systematically excluded from participation. None reported history of neurological or psychiatric disorders.
To prevent Self-and Other-recognition biases, participants wore black long sleeve shirts and had removed all personal belonging (such as jewelry, scarf, watch, etc. ). Participants with long hair were instructed to tie back their hair with an elastic band. We manually adjusted the stool's height of each participant so that the reflections of the participants' eyes were at the same level and merged in the mirror. This was done while the two LED sets were simultaneously on (without flickering). Using hypoallergenic and transparent Band-Aid TM , we placed two markers light, emitting green light, symmetrically on the participants' left and right temples (Figure  2C ). These marker lights were controlled with a PC using E-Prime software. Because we used FIGURE 2 | Experimental setup and procedures.
The flicker frequency was determined in the handling procedures before the recording of the Interpersonal Visual Stimulation phase started. We here also report the frequency data for the four participants who were finally excluded from the final data analysis. with respect to the vertical but not horizontal axis. Before the recording session started, participants were, thus, again instructed to position their face so that the reflection of their eyes matches with that of their partner in the mirror and to maintain this position. Furthermore, they were explicitly instructed not to move, i. e. , not to perform lateral movements of their trunk or face but also not to perform contractions of their facial muscles. In the IVS phase, green flashes appeared randomly either on the face of one or the other participant and either on the left or right temple.
Post-stimulation Test In this test, we computed the total amount and corresponding percentage of correct responses, and associated RTs for each participant in each task, as in the pre-stimulation test. To test for statistical analyses between the Self-and Other-task, we calculated Wilcoxon signed-rank tests on performance (number of correct response) and RTs. Then, to statistically test whether the IVS-phase impacted the egocentered or heterocentered visuo-spatial mechanisms, we computed a 2 × 2 repeated-measures ANOVA with permutation tests on the number of correct response and RTs with time (pre-IVS vs. post-IVS) and tasks (Self-task vs. Other-task) as the factors. We calculated the statistical power which was about 0. 71 (1 -β). As mentioned above (see Participants), we excluded the data from four participants [participants 9 (P9), 10 (P10), 14 (P14), and 17 (P17)] because of bad recording conditions in the IVSphase.
DISCUSSION In the present study, we investigated whether identifying oneself with the face of another individual in the mirror impacts either the egocentered or heterocentered visuo-spatial mechanisms that sustain self-other distinction. For that, self-identification was manipulated by exposing participants to an IVS condition in which the reflection of their own face was merged with that of their facing partner in a semi-transparent double mirror. In the pre-and post-IVS tests, participants performed egocentered visuo-spatial transformations with respect to their own face as reflected in the mirror and heterocentered visuo-spatial transformations with respect to their partner's face seen through the mirror. Our data show that selfother face identification alters the egocentered visuo-spatial mechanisms but preserved the heterocentered coding.
Self-face Identification Contributes to Bodily Self-consciousness In the post-stimulation test, i. e. , after exposure to IVS, participants performed the same Self-task (egocentered visuospatial mechanisms) and Other-task (heterocentered visuospatial mechanisms) as in the pre-stimulation test. Comparable to pre-IVS, participants performed significantly faster in the Self-(∼576 ms) than Other-task (∼680 ms). Interestingly enough, visual comparison of the pre-and post-IVS data suggested that RTs increased after IVS but selectively for the Self-task. This effect was confirmed by statistical comparisons, showing a significant time (pre-IVS vs. post-IVS) × task (Self-task vs. Other-task) interaction that was attributable to a significant difference between the pre-IVS Self-task and the post-IVS Selftask.
Oxygen consumption rate measurements Oxygen consumption rate (OCR) was measured using the real time flux analyser XF-24e (Seahorse Bioscience). For these experiments 6 × 10 4 cells were treated with 1 M Oligomycin, 2 M Carbonyl cyanidep-trifluoromethoxyphenylhydrazone (FCCP), 1 M Rotenone and 1 M Antimycin A (all purchased from Sigma-Aldrich). At the end of the run cells were lysed using RIPA buffer (25 mM Tris-HCl pH 7. 6, 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, 0. 1% SDS). Protein content for each well was measured using BCA kit (Pierce) according to the manufacturer's instructions. OCR was normalised to total protein content. The extent of ATP-linked mitochondrial respiration was obtained by calculating the ratio between OCR in the presence or absence of Oligomycin. Data were obtained from 3 independent experiments and presented as mean ± SEM.
The mass spectrometer was operated in full MS and polarity switching mode. Samples were randomized in order to avoid machine drift and blinded to the operator. The acquired spectra were analysed using XCalibur Qual Browser and XCalibur Quan Browser softwares (Thermo Scientific) by referencing to an internal library of compounds. Integrated metabolites were normalised on total metabolite intensity per sample and statistically significant metabolites were obtained by applying ANOVA and Tukey's post-hoc test between samples (n = 4). Statistical analysis of metabolomic data was carried out with R software (FDR = 0. 05).
We then investigated whether heteroplasmy shift of m. 8993T>G mtDNA is associated with changes in cellular metabolism. To this end we performed Liquid-Chromatography coupled to Mass Spectrometry (LC-MS)based metabolomic analyses of N80, N45 and N10 cells. Principal component analysis based on a matrix of 70 metabolites clearly separated the three cell lineages based on their heteroplasmy level (Figure  4D ), indicating that substantial metabolic changes are associated with genetic correction of m. 8993T>G mtDNA. Univariate analysis of individual metabolites (Supplementary Figure  S9 ) demonstrated that citrate and aconitate, two key mitochondrial metabolites, were among the most increased metabolites in both N45 and N10 compared to N80 (Figure  4E  and Supplementary Figure  S9 ). These data suggested that the defect of mitochondrial function in cells bearing high loads of m.
ACKNOWLEDGEMENTS We gratefully acknowledge the kind gift of the HHR constructs from the laboratory of  Prof. Beatrix Suess  ( University of Darmstadt, Germany ). All FACS was carried out at the  NIHR BRC Cell Phenotyping Hub, Cambridge , UK by  Chris Bowman ,  Natalia Savinykh ,  Esther Perez ,  Jelena Markovic Djuric ,  Valeria Radjabova  and  Anna Petrunika Harrison  between  07/2013  and  07/2015.
FUNDING Medical Research Council, UK ;  EMBO  Fellowship [ALTF 701-2013 to L. V. H. ]; PhD fellowship from the  Foundation for Science and Technology, Portugal  through the  GABBA Program ,  University of Porto  (to P. R. G. ); Experiments undertaken in the J-PC laboratory were supported by  ANR   Investissement d'Avenir  [ ANR-IIINSB-0014 ] and AFM [18566]. Funding for open access charge:  Medical Research Council, UK.
Study population Data were drawn from the Haguenau cohort, a community-based cohort derived from a maternity registry of the metropolitan area of the city of Haguenau (France) that has the purpose of investigating the longterm consequences of being born SGA. 9  Briefly, the registry included information about all pregnancies and deliveries occurring at the city maternity hospital from 1971 to 1985 with an 80% degree of completeness. SGA and AGA individuals were all singleton births and born between 32 and 42 weeks of gestation. SGA were individuals born with body weight <10th centile with respect to local standard growth curves. AGA individuals were born between the 25th and the 75th centiles for sex and gestational age and were selected as the next full-term singleton after the selection of an SGA individual.
10 Data in the Haguenau cohort were drawn at two time points with a participation rate of 80. 7% at the second visit. 4 The first visit took place when singletons were on average 22 years of age, and participants who agreed to participate were 886 AGA individuals and 734 SGA. 4  Since dietary intake was only inquired at the first visit and on only 536 participants, we included data from those with complete data (n=401 aged in average of 22 years, figure  1 ). Measurement strategy: Details about measurements are available in the previous publication of Meas et al. 10  Cross-sectional analyses are presented in this work. Dietary intake was evaluated using a self-administered questionnaire including 19 components and information on alcohol, water, meat, fish, poultry, eggs, dairy products, bread and sweets consumption.
Statistical analyses Descriptive statistics were performed to provide characteristics of the sample studied and are presented as means ±SD or percentages by type of weight for gestational age. Data from a total of 401 individuals with the complete data set are presented as a function of type (AGA, SGA). A χ 2 test of independence was performed to examine the difference in intake between SGA-born and AGA-born individuals. Multiple correspondence analyses were run in order to determine relationships between components of the Food Frequency Questionnaire in SGA and AGA individuals. The a priori score was divided into quartiles. The SAS Genmod procedure adjusting for age and sex was used to compare relative risk and 95% CIs of belonging to the first quartile versus the other three quartiles in SGA-born versus AGA-born individuals.
DISCUSSION In this study, we examined the differences in dietary intakes of young adults in their early 20s, born either SGA or AGA. We found that SGA-born adults were less likely to consume fish and more likely to eat meat and sweets when compared with their AGA-born counterparts. Fish consumption has been strongly associated with a lesser risk of cardiovascular diseases. 13 Our results suggest that small weight for gestational age might influence food choice and therefore health outcomes in adult years. We also found a difference in desserts intake but not in that of bread. Data from a Brazilian birth cohort  14  showed that women who were born with intrauterine growth restriction had a spontaneous preference for carbohydrate intake instead of proteins and thus had a higher carbohydrate-to-protein ratio, which we find in our study by a higher dessert intake.
GP Data Collection The GPs collected sociodemographic data, the medical history, and zoster symptoms (rash localization and extension and number of vesicles) at initial visit and pain characteristics (allodynia, itching, and paresthesia) at each visit. In the medical history, underlying conditions were categorized as one of three chronic diseases (diabetes, cardiovascular diseases, and respiratory diseases), or as "other relevant diseases. " Where a condition was considered relevant by the GP, but not related to zoster, it was classified as "other relevant diseases," and the GP was invited to provide a description of the condition in free text.