dataesr/scientific-paragraphs-categorization huggingface dataset:
Heritability of Cerebral Cortical Anatomical Asymmetries. In the GOBS dataset, the overall hemispheric asymmetries of both cortical thickness and surface area showed low but statistically significant heritabilities (cortical thickness asymmetry: h 2 = 0. 10, P = 0. 005; surface area asymmetry: h 2 = 0. 17, P = 0. 00024). The most heritable asymmetries in regional cortical thickness were found in the isthmus (h 2 = 0. 17) and caudal anterior cingulate gyrus (h 2 = 0. 13), the superior (h 2 = 0. 13) and rostral middle frontal gyrus (h 2 = 0. 18), the parahippocampal gyrus (h 2 = 0. 15), and the lateral occipital gyrus (h 2 = 0. 16) (P < 0. 05, Bonferroni corrected; Table  1 ). The most heritable asymmetries in regional surface area were found in the entorhinal cortex (h 2 = 0. 24), the superior temporal gyrus (h 2 = 0.
19), the inferior parietal gyrus (h 2 = 0. 19), and the isthmus cingulate gyrus (h 2 = 0. 17) (P < 0. 05, Bonferroni corrected; Table  1 ). For each of these regions, we also estimated the genetic correlation between the measures of the left and right structures. While these correlations were high (indicating high pleiotropy), all were significantly different from 1 (Table  1 ). These results indicate that most genetic effects on structural variation are shared bilaterally, but some independent genetic effects exist on each hemisphere, which constitute the heritable contributions to structural asymmetry. Finally, we found that the heritability of most of these regions was validated in the HCP dataset. For more details, see Dataset S7.
Discussion In the largest-ever analysis of asymmetry of cerebral cortical structure, we applied a meta-analytic approach to brain MRI data from 17,141 healthy individuals from datasets across the world. The findings revealed substantial interhemispheric differences in both regional cortical thickness and surface area and linked some of these asymmetries to sex, age, and ICV. Handedness was not significantly associated with cortical asymmetries. While previous findings are based on low hundreds of participants and different methodological approaches, this study of >17,000 participants is a major step forward in achieving a more accurate description of the typical asymmetries of the human brain, as well as variation in these asymmetries and some key individual differences factors which affect them.
Moreover, with two independent pedigree datasets (i. e. , GOBS and HCP), we revealed that several regions showed significant heritability of asymmetry measures. Cortical Thickness. Regions with significant leftward asymmetry in thickness (i. e. , left > right) were identified mainly in the frontal cortex, as well as the primary sensory, superior parietal, and medial temporal cortices, while rightward asymmetry was prominent in the posterior cortex, including lateral and medial parts of the temporal, parietal, and occipital cortices. This striking asymmetry pattern along the fronto-occipital axis is similar to that reported by Plessen et al. (40)  and may be related to the Yakovlevian torque, i. e. , the frontal/occipital bending in the human brain  (28). Specifically, the torque refers to the phenomenon of crossing of the interhemispheric fissure by one hemisphere into the domain of the other.
In terms of age effects, when limiting our analysis to only the datasets with an age range >20 y, we found a significant correlation between age and the overall hemispheric asymmetry in cortical thickness (i. e. , increasing age correlated with more pronounced leftward asymmetry), which was mainly contributed by the superior temporal gyrus. This finding is consistent with previous studies  (40, 41) , although we did not detect age effects in other regions reported by Plessen et al. (40). Brain size is another factor that can affect functional organization  (63). In the present study, we found a significant effect of ICV on the overall asymmetry in cortical thickness, such that the leftward asymmetry in cortical thickness increases in larger brains. This effect was the most pronounced in the inferior parietal gyrus and the insula.
We also found that males, on average, showed more rightward asymmetry in overall surface area, compared with females, which is consistent with Koelkebeck et al. (38). We additionally observed a number of regionally specific effects, among which surface area asymmetry in the superior frontal gyrus showed the strongest relation to sex (i. e. , males showed more leftward asymmetry in surface area in this region compared with females). In terms of age, when including only those datasets with an age range of >20 y, we found a weak positive correlation between age and the asymmetry of surface area of the entorhinal cortex-that is, the leftward asymmetry of this region was slightly greater in older participants. As far as we are aware, no previous studies have reported possible age effects on the asymmetries of surface area, except one that showed no significant results in 101 participants  (38).
Data from two recent studies have indeed indicated that the asymmetry measures of cortical thickness and surface area are relatively independent at the overall hemispheric level  (38, 39). With our larger sample size in the present study [including the BIL&GIN dataset used in Maingault et al. (39) ], we confirmed a lack of correlation across regions between the asymmetries of thickness and surface areas, which further supports their independent natures. Moreover, by including data on participants' sex, age, handedness, and ICV, our findings further elaborated the largely independent nature of regional area vs. thickness variability (SI Appendix, SI Results). Note that, when zooming in on some individual regions, there may be identifiable relations between thickness and surface area asymmetries, such as reported for the fusiform gyrus and the cingulate cortex  (38, 39, 43) , although further investigation is needed.
In future studies of cortical asymmetry, the simultaneous investigation of both cortical thickness and surface area will be important. For example, this may be necessary to approach the genetics of brain asymmetry  (26)  and its links with functional lateralization (e. g. , language lateralization)  (74). With the pedigree datasets from the GOBS and HCP, we revealed that several regions showed significant heritability of their asymmetry measures. These data on heritability will be useful in targeting future studies of brain laterality with, for example, genome-wide association scanning aimed at identifying genes involved. Interestingly, cortical asymmetry of the human brain may also be associated with interhemispheric differences in gene expression  (75, 76). Our data revealed extensive variability in cortical asymmetry across participants and samples.
Future studies using continuous handedness measures, when available in very large samples, may provide more information. In addition, it is interesting to note that paleoneurologists have attempted to use skull endocasts to assess cerebral asymmetries and to infer the evolution of handedness in hominins  (81). Since we found no significant association between brain anatomical asymmetries and handedness, our analysis does not support the use of indirect measures of brain anatomy to infer the handedness of individuals. Limitations and Future Directions. This study has several limitations that could be overcome in future studies. First, for age effects, as most datasets included a wide age range, our meta-analysisbased approach cannot rule out that age effects might differ across different age groups.
Given the important roles of development and aging on cortical structures, this issue should be investigated in future research using datasets which are individually very large. In addition, the cross-sectional study design limits the interpretation of results. Longitudinal studies should ideally be performed to support the findings. Second, when combining already collected data across worldwide samples, data-collection protocols are not prospectively harmonized. Imaging acquisition protocols and handedness assessments therefore differed across studies, which resulted in possible sources of heterogeneity. On the other hand, this heterogeneity can be taken as an advantage of our approach, in the sense that our findings are representative of the real-world diversity of MRI acquisition currently in use in the field and not limited to a single laboratory-specific protocol.
Third, we note that variability of asymmetry in surface area across samples was relatively lower than that of asymmetry in cortical thickness, at both the global hemispheric and regional levels. The relatively consistent asymmetry in regional surface area across datasets might be, to an extent, driven by the same parcellation scheme (i. e. , Desikan-Killiany atlas) having been used across all samples. The potential impact of parcellation dependence will be an important topic for future studies. In addition, we applied a region-based approach, rather than a vertex-wise approach. The key idea of the region-based approach is that if we define the regions of interest in each hemisphere based on each hemisphere's own particular features such as its sulcal and gyral geometry, we can then obtain the corresponding relationships between hemispheres.
To this end, we applied an automated labeling program from Free-Surfer for subdividing the human cerebral cortex from MRI scans. The labeling system incorporates hemisphere-specific information about sulcal and gyral geometry with spatial information regarding the locations of brain structures and shows a high accuracy when comparing with manual labeling results  (69). Thus, reliable measures of each region can be extracted for each subject and regional asymmetries then accurately assessed. Moreover, compared with a vertex-wise approach, the region-based approach is a more feasible solution for largescale, collaborative, meta-analysis-based projects. Nonetheless, the region-based approach is necessarily limited in terms of spatial resolution, related to the number of cortical regions defined.
Materials and Methods The primary datasets used in this study for large-scale meta-analysis were from members of the Lateralization Working Group within the ENIGMA Consortium  (51). There were 99 independent samples with MRI data, including 17,141 healthy participants from diverse ethnic backgrounds. Samples were drawn from the general population or were healthy controls from clinical studies. All local institutional review boards permitted the use of extracted measures of the completely anonymized data. The present study mainly focused on the asymmetry in cortical thickness and surface area and its variability related to sex, age, handedness, and ICV. The asymmetry index was defined as (L -R)/((L + R)/2)). Image processing and effect size estimations were conducted at each participating site, and then we combined the output statistics from each dataset using random-effect meta-analysis with the R package metafor  (84).
Two additional datasets with MRI data were used to estimate heritability of asymmetry measures, i. e. , the GOBS and HCP datasets. GOBS is a family study comprising 1,443 individuals with MRI data (836 females), aged between 18 and 85 y at the time of scanning  (85). The HCP is a large-scale project comprising 1,113 individuals (twins and nontwin siblings; 606 females, age range 22-37 y at the time of scanning) (https://www. humanconnectome. org/). The complete statistics from the meta-analyses are included in SI Datasets S1-S7 and the query tool (conxz. net/neurohemi/). Scripts are also available from the query tool (conxz. net/neurohemi/). Materials and methods are described in detail in SI Appendix, SI Materials and Methods.
During previous surveys conducted between 2004 and 2011, we identified several SIVgor infected gorillas in the Campo Ma'an National Park in southwest Cameroon  (Neel et al. , 2010). We demonstrated the feasibility of long-term monitoring of SIVgor infection in nonhabituated gorillas and we showed for the first time that it is possible to re-sample gorillas in a noninvasive way and to characterize SIVgor diversity  (Etienne et al. , 2012). Here we included additional 4 years of follow-up, inferred groups of gorillas using geo-referenced data over time and performed genetic and phylogenetic analyses using state-of-the-art approaches. We sought to advance our understanding of SIVgor transmission and evolution among gorillas in the Campo-Ma'an National Park and to further validate a noninvasive approach to better monitor and inform the conservation of this critically endangered and elusive species.
| Study site and sample collection The Campo-Ma'an National Park is located in the South Western corner of Cameroon, bordering on Equatorial Guinea to the south and the Atlantic Ocean to the west covering an area of approximately 2,640 km 2. This study was conducted in an area of approximately 200 km 2 at the center of the park where we previously characterized SIVgor infected gorillas  (Etienne et al. , 2012). Opportunistic collection of fecal samples occurred between 07:00 and 17:00 hr. Field data included sample's GPS coordinates, location type (nest, feeding site or directly on track), estimated time of fecal deposition and, since 2012, the hour of collection. About 20 g of fecal material was collected in a 50-ml tube, containing 20 mL of RNAlater ™ (Ambion, Austin, TX, USA), and kept at ambient temperature, for a maximum of 2 weeks, and then stored frozen.
Seven additional microsatellite loci  (vWF, D7s817, D7s2204, D16s2624, D8s1106, D10s1432, and D1s550)  were obtained from at least one nucleic acids extract of each gorilla to improve the estimation of relatedness and relationship among the different individuals. Genetic diversity was quantified by estimating observed and expected heterozygosis. Test for Hardy-Weinberg equilibrium (HWE) for each locus and test for linkage disequilibrium between loci were performed using the package adegenet  (Jombart, 2008; Jombart & Ahmed, 2011). A Minimum Spanning Network (MSN) of microsatellite haplotypes was constructed using the Prevosti  (Prevosti, Ocana, & Alonso, 1975)  and the Bruvo's distance  (Bruvo, Michiels, D'Souza, & Schulenburg, 2004)  for its ability to handle missing data and that were included in the package  (Kamvar, Brooks, & Grunwald, 2015; Kamvar, Tabima, & Grunwald, 2014).
The relatedness value (r d ) was calculated using the Wang estimator  (Wang, 2017; Wang, 2002)  included in the package Demerelate  (Kraemer & Gerlach, 2017) , the Maximum Likelihood (ML) approach implemented in the MLrelate software  (Kalinowski, Wagner, & Taper, 2006) , and Bayesian estimation using the package SOLOMON  (Christie, Tennessen, & Blouin, 2013). The Wang estimator was chosen because it is robust for small samples sizes and applies to any number of alleles per locus and to any allele frequency distribution (J. Wang, 2017; J. L. Wang, 2002). The Bayesian parentage analysis requires the prespecification of adults and offspring genotypes. To account for this, we randomly distributed our data in two groups and then performed the analysis. We repeated this approach ten times and preferred the pairs that were hypothesized as parent-offspring in any of them; a cutoff value of 0.
| SIV Phylogenetic analysis The novel and previous SIVgor genetic sequences were used in reconstruction of phylogenetic trees. When multiple sequence reads from the same individual and the same day were available, consensus sequences were generated and used in time-scaled evolutionary analyses following Markov chain Monte Carlo sampling as implemented in BEAST v1. 8. 3 software package  (Drummond, Suchard, Xie, & Rambaut, 2012). Reconstructions were performed using both genetic regions. Regressions of root-to-tip genetic distance against sampling time for each of the datasets were performed using TempEst v1. 5. 1  (Rambaut, Lam, de Carvalho, & Pybus, 2016)  and trees constructed with maximum-likelihood algorithms in FastTree 2. 1  (Price, Dehal, & Arkin, 2009 , 2010). All datasets exhibited positive correlation between genetic divergence and sampling time and appeared to be suitable for phylogenetic molecular clock analysis (correlation coefficient of 0.
29 and 0. 14 for gp41 and pol, respectively). The datasets were analyzed using a HKY+4Γ  (Hasegawa, Kishino, & Yano, 1985)  nucleotide substitution model plus a demographic coalescent tree prior model (among the parametric constant size, exponential or logistic growth models and the nonparametric Skyride one)  (Drummond, Rambaut, Shapiro, & Pybus, 2005; Minin, Bloomquist, & Suchard, 2008)  and either a molecular strict clock model or a relaxed uncorrelated lognormal one  (Drummond, Ho, Phillips, & Rambaut, 2006). Model comparisons were performed using the path sampling and stepping stone approach (A minimum of 50 steps with the length of each chain being at least one million iterations)  (Baele et al. , 2012). For each dataset, two to four Markov chain Monte Carlo chains of 20-200 million iterations were computed.
ACK N OWLED G M ENTS This work was supported in part by grants from the  National Institute of Health  ( RO1 AI 50529 ), the  Agence Nationale de Recherches sur le SIDA  ( ANRS 12125/12182/12325 ) and  IRD (Institut de Recherche pour le Développement). CJVA was supported by a fellowship from  IRD  and the  Labex EpiGenMed , via the  National Research Agency ,  Programme for Future Investment  " ANR-10-LABX-12-01 " and  University of Montpellier. MD received a PhD grant from the  Brazilian PDSE-CAPES  " Scholarship Program Doctoral Sandwich abroad. "We thank the  Ministries of Health, Research, Environment  and the  National Ethic committee from Cameroon  for permission to perform this study. We thank the staff and SIV team from  Projet PRESICA  ( Innocent Ndong Bass ,  Aime Mebenga ,  Joseph Moudindo ,  Thomas Atemkem ) for the collection of fecal samples and logistical support in Cameroon,  Helene De Nys  for helpful discussions.
Funding information National Institute of Health , Grant/Award Number:  RO1 AI 50529 ;  Agence Nationale de Recherches sur le SIDA , Grant/Award Number:  ANRS 12125/12182/12325 ;  IRD  ( Institut de Recherche pour le Développement) ; the  Labex EpiGenMed , via the  National Research Agency ,  Programme for Future Investment , Grant/Award Number:  ANR-10-LABX-12-01 ;  University of Montpellier.
Statistical Analysis A statistical analysis to examine the consequences of attrition was included. We used descriptive statistics, t tests, logistic regression, and group-based trajectory modeling to analyze the data. A statistical software program (Stata, version 12; StataCorp LP) was used to perform these analyses. Group-based trajectory modeling is designed to identify groups of individuals who are following similar trajectories of a single outcome variable. 33 Multitrajectory modeling extends the basic model by defining trajectory groups in terms of multiple outcome variables. 29 Both the basic model and the multitrajectory generalization are applications of finite mixture modeling. The multitrajectory method applied herein combined the trajectories of physical aggression based on mother ratings (ages 1.
Like most maximum likelihood models, multitrajectory modeling assumes that data are missing at random. Under this assumption, there is no constraint on the number of missing observations that individuals may have to be included in the estimation sample. Therefore, we included a condition requiring individuals to have at least 10 observations across the 16 observations to be included in the estimation sample. In addition, we checked using single-trajectory modeling whether the attrition at later periods of data collection was systematically different for a given type of physical aggression trajectory or was equally distributed. We estimated the posterior probability or group membership for each period for mother ratings and performed a cross-tabulation between group membership at each period, with nonresponse or participating category at the last 2 periods (ages 12 and 13 years).
Assessment of computational cost For the estimation of the computational cost, we needed larger series and numerous dyads. Therefore, we simulated 1000 dyads with trajectories following a Brownian motion, each one composed of 100 fixes. Table  3  shows the summary statistics for the CPU time for computing Green, red and blue correspond to case scenarios of same, independent and opposite direction. For each category, the solid circle corresponds to the median, the solid wide bar contains values from the first to the third quartiles, while the dashed line joins the minimum to the maximum values. The green and blue boxplots are shifted to the left and right, respectively, to distinguish them better in case of overlap. each metric for one dyad. In all cases, it took less than a second per dyad; but the small differences may become relevant for large datasets.
work has received funding from French region Pays de la Loire and the research project COSELMAR, the French research network PathTIS and the European Union's Horizon 2020 research and innovation program under grant agreement No 633680, Discardless. The authors would like to warmly thank Mathieu Basille for his constructive comments to the manuscript, Angela Blanchard for proofreading and Criscely Lujan for help with github. [55] Van Strien, A. J. , Soldaat, L. L. , and Gregory, R. D. (2012). Desirable mathematical properties of indicators for biodiversity change. Ecological Indicators, 14(1):202-208. [56] VanDerWal, J. , Falconi, L. , Januchowski, S. , Shoo, L. , and Storlie, C. (2014). SDMTools:.
work has received funding from French region Pays de la Loire and the research project COSELMAR, the French research network PathTIS and the European Union's Horizon 2020 research and innovation program under grant agreement No 633680, Discardless. The authors would like to warmly thank Mathieu Basille for his constructive comments to the manuscript, Angela Blanchard for proofreading and Criscely Lujan for help with github. [55] Van Strien, A. J. , Soldaat, L. L. , and Gregory, R. D. (2012). Desirable mathematical properties of indicators for biodiversity change. Ecological Indicators, 14(1):202-208. [56] VanDerWal, J. , Falconi, L. , Januchowski, S. , Shoo, L. , and Storlie, C. (2014). SDMTools: Species Distribution Modelling Tools: Tools for processing data associated with species distribution modelling exercises.
Most patients were medication-free for considerably longer; of eight patients previously treated with antidepressants, seven were drug-free >6 months at entry into the study. After inclusion in the study, the patients were randomly assigned (using a block randomization design with blocks of 4) to receive CBT or sertraline treatment for a period of 12 weeks. OCD symptom severity, assessed using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS), and depressive symptoms, estimated with the Beck Depression Inventory (BDI), were recorded by a clinician blind to the patient's PET data approximately every 2 weeks during treatment, beginning at baseline (week 0). Following completion of the 12-week treatment study, patients in both groups were offered further treatment as clinically indicated. All participants provided written, informed consent.
Acknowledgements This study was supported by funding from  Fonds de la Recherche du Quebec -Sante (FRQS). We thank  Rick Fukusawa ,  Gary Sauchuk ,  DEC ,  Dean Jolly ,  Shadreck Mzengeza, PhD ,  Mirjana Kovacevic , and  Gail Rauw, PhD  ( McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University ), for their excellent technical assistance. We are grateful to the  Department of Mathematics, UC Davis , for providing an office so that  Dr. Nordahl  may more directly participate in mathematical activity now that he is Professor Emeritus of the  Department of Psychiatry and Behavioral Sciences.