dataesr/scientific-paragraphs-categorization huggingface dataset:
(g) ASD patients' nasal OSCs produce higher levels of ROS, at baseline and 1 h after staurosporine treatment. Data are represented as mean ± s. d. *Po0. 05. n = 80-100 animals per group. Experiments were run in triplicate. MOCOS +/+ control lines were differentiated into (Figure  4h ). The synaptic compartment being an important element for neurotransmission, we analyzed the number of synaptic buttons in iPSCs-derived neurons (Figure  4h ). Of utmost importance, and even though we did not observe difference in their capacity to generate TUJ1-expressing neurons, those derived from MOCOS +/ - iPSCs displayed a lower number of SYNAPSIN+ synaptic buttons (Figures  4i  and j ). These results confirm that MOCOS is a newly identified molecule having a role during neurodevelopment and DISCUSSION Together, our results highlight MOCOS as a new candidate molecule implicated in ASD physiopathogeny and unveil novel biological functions associated with MOCOS, including roles in stress response and neurotransmission.
ACKNOWLEDGMENTS We thank  Dr Mani Sahebjam  ( Edouard Toulouse Hospital, Marseille ),  Dr Claude Guinard  ( Valvert Hospital, Marseille ) and  Dr Rémy Defer  ( Montperrin Hospital, Aix-en-Provence ) for their help in recruiting the participants in this study. We are also thankful to  Claudine Rumeau  for magnetic resonance imaging analyses,  Kevin Baranger  for providing neuronal culture as well as  Stéphanie Frecourt ,  Rim Yamani  and  Rupa Devi Soligalla  for technical assistance. We thank the  C. elegans Gene Knockout Consortium ,  S Mitani  and the  National Bioresource Project  and  J Kaplan  and  L Bianchi  for generously providing strains. Other strains used in this study were provided by the  Caenorhabditis Genetics Center , which is funded by  NIH Office of Research Infrastructure Programs  ( P40 OD010440 ).
Epidemiological Data The epidemiological line list has already been described in detail elsewhere  [1]. In short, a standard case investigation form was used to collect clinical and demographic data for all confirmed, probable, and suspected EVD cases identified through contact tracing and clinical care in Guinea. The following variables were used for our analyses: age, gender, EVD status (confirmed/probable/suspected), prefecture of residence, date of symptom onset, outcome (dead/ discharged alive), hospitalization status (hospitalized/not hospitalized), date of hospitalization (if any), date of death (if any), and date of sample collection.
o. , children: 5-14 y. o. , adults: 15-44 y. o. , older adults: 45 y. o. ) and time from symptom onset to sample collection in three classes (<4, 4-7, >7 d). Using this model, it was possible to investigate whether the observed temporal variations in CFR could be explained by changes in the distribution of viremia over time. For each case, we computed the probability of death according to viremia, patient age, and time from symptom onset to sample collection. We then averaged these probabilities by month and compared these with the observed monthly CFRs. We explored the consistency of our results when only a subset of cases was used to inform the model. We estimated monthly CFRs using a model that was trained on cases that were hospitalized between 1 March 2014 and 30 September 2014 only and compared the results to when the whole dataset was used.
Finally, as with all assays, the measurement of viremia (viral load) is not without uncertainty. It has been estimated that the standard deviation of the assay is around 0. 48 C t  [15]. To explore the impact of assay uncertainty on our results, we randomly added measurement uncertainty to each viremia measurement and recalculated the relationship between viremia and probability of death over repeated simulations. Details of the simulation study can be found in Section 6 of S1 Appendix. An aggregated dataset is available in S1 Dataset.
Mean viremia was comparable in males and females (Fig  3B ; p = 0. 95). It was significantly higher in young children (10 4. 84 ; 95% CI 10 4. 27 -10 5. 40 ) than in other age groups (10 4. 13 ; 95% CI 10 4. 00 -10 4. 26 ; p = 0. 02) (Fig  3C). We restricted the univariable analysis of viremia and outcome to the 548 (78%) patients whose samples were collected within 7 d of symptom onset, a time period when viremia appeared to be stable (Fig  3A ). Among these patients, there were a total of 261 deaths (48%). The probability of death was best explained by a logistic regression model with (log 10 V) 2 as a single explanatory variable (see Section 3 of S1 Appendix). The odds ratio (OR) for a unit increase in (log 10 V) 2 was 1. 12 (95% CI 1. 10-1. 14). This simple model provided an excellent fit to the data (Fig  3D ).
The probability of death increased with viremia, from 21% (95% CI 16%-27%; 51 deaths out of 243 individuals) in patients with low viremia (V < 10 4. 4 ) to 53% (95% CI 44%-61%; 70 deaths out of 133 individuals) in those with intermediate viremia (10 4. 4  V < 10 5. 2 ) and 81% (95% CI 75%-87%; 140 deaths out of 172 individuals) in those with high viremia (V 10 5. 2 ) (Fig  3D ). The proportion of patients in the low, intermediate, and high viremia groups was 44% (95% CI 40%-49%; n = 243), 24% (95% CI 21%-28%; n = 133), and 31% (95% CI 28%-35%; n = 172), respectively. Our results were found to be robust to the level of measurement error expected from the viral load assay (see Section 6 in S1 Appendix). We performed a multivariable analysis incorporating (log 10 V) 2 , age, and time from symptom onset to sample collection using data from all 699 EVD patients.
Discussion Here, we analyzed a large dataset of laboratory results for 699 EVD patients in order to characterize how the probability of death changed with viremia, while adjusting for age and time between symptom onset and sample collection. We found that viremia was a strong predictor of outcome for individual EVD patients, with the probability of death increasing from 21% in those with low viremia to 81% in those with high viremia. This is important because it confirms the significance of viremia as a predictor of EVD outcome suggested in small case series  [16, 17]  and it provides an important potential measure of risk adjustment in clinical evaluations of Ebola-specific treatments. Important variations in the CFR of the study population (namely, a 14% increase from the first to the second epidemic wave) coincided with an order of magnitude increase in mean viremia (Fig  4B ).
This study has some limitations. Our analysis was conducted on a retrospective cohort using data collected as part of routine case management, with no active follow-up of patients who were discharged. We considered individuals discharged from hospital as having recovered; however, it is possible that some died at a later date. This would result in increases in the CFRs reported here, although any differences are likely to be minor. Further, we used data only on hospitalized cases. Our results may not be generalizable to community cases, as the distribution of viremia may be different in these individuals, for example if they represent cases that died before they could seek care or that had only minor symptoms. The route of infection, which is unknown in our cases, may be linked with differential mortality risk  [21].
What Did the Researchers Do and Find? The researchers used laboratory and epidemiological data (for example, patient age and date of symptom onset and death; epidemiology is the study of disease patterns in populations) to investigate the relationship between viremia and CFR among 699 patients with confirmed EVD hospitalized in the Conakry area of Guinea between March 2014 and February 2015. In the week following symptom onset, mean (average) viremia remained stable, and the CFR among the patients increased with the level of viremia. Thus, the CFRs for patients with low, intermediate, and high viremia (defined by the number of virus copies per milliliter of blood) were 21%, 53%, and 81%, respectively. Compared to adults aged 15-44 years, young children (aged less than five years) and older adults had a higher CFR, but children aged 5-14 years had a lower CFR.
August, p < 0. 01). Our multivariable logistic regression model performed well in predicting individual outcomes (area under the curve [AUC] of 0. 81; see Section 5 of S1 Appendix), and it showed a similar trend in CFR (Fig 4A). A simpler univariable logistic regression model that relied only on viremia showed similar performance (Fig 4A). Finally, a model informed using data from March to September 2014 only (29% of all the data) performed similarly to one trained on the entire dataset (Section 5 of S1 Appendix).
Acknowledgments We thank the  Coordination Nationale de Lutte contre la Maladie à Virus Ebola (CNLEB) ,  Médecins Sans Frontières ,  WHO , surveillance teams from various partners involved in EVD outbreak responses and control,  Barré Soropogui ,  Hadja Aissatou Bah ,  Amadou Doré ,  Fodé Kourouma ,  Moussa Condé ,  Eugène Kolié ,  Mamadou Lamine Keita , and  Alpha Mamadou Baldé  for excellent technical expertise.
This study has received funding from the  French Government 's  Investissement d'Avenir program ,  Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases " (grant n  °ANR-10-LABX-62-IBEID ), the  NIGMS MIDAS initiative , the  AXA Research Fund  and the  European Union Seventh Framework Programme  ( FP7/2007-2013 ) under Grant Agreement number  278433-95% CI 1. supported by a personnel award from the  Heart and Stroke Foundation ,  Ontario Provincial Office. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
after August, p < 0. 01). Our multivariable logistic regression model performed well in predicting individual outcomes (area under the curve [AUC] of 0. 81; see Section 5 of S1 Appendix), and it showed a similar trend in CFR (Fig 4A). A simpler univariable logistic regression model that relied only on viremia showed similar performance (Fig 4A). Finally, a model informed using data from March to September 2014 only (29% of all the data) performed similarly to one trained on the entire dataset (Section 5 of S1 Appendix).
The updated inventory of the Latin American Pollen Database (LAPD) offers a wide range of new insights. This paper presents a systematic compilation of palynological research in Latin America. A comprehensive inventory of publications in peer-reviewed and grey literature shows a major expansion of studies over the last decades. The inventory includes 1379 cores and sections with paleoecological data and more than 4800 modern samples from throughout the continent. Through the years, pollen datasets extend over increasing spans of time and show improved taxonomic and temporal resolution. Currently, these datasets are from 12 modern biomes and 30 countries, covering an altitudinal range of 0 to 6300 m asl. The most densely sampled regions are the Colombian Andes, the southeast coast of Brazil, and Patagonia.
Underrepresented biomes are the warm temperate mixed forest (3%), dry forests (3%), and warm temperate rainforest (1%); whereas steppe, tropical rainforest, and cool grass shrublands, such as the páramos, are generally well represented (all N17%). There are 126 records that span the late Pleistocene to the Last Glacial Maximum transition (21,000 cal yr BP), and N 20% of the records cover the Younger Dryas interval and the Pleistocene/Holocene transition. Reanalysis of numerous sites using multiproxy tools emphasize the informative value of this approach in paleoenvironmental reconstruction. We make suggestions for several pollen sites and regions to be visited again; similarly we identify some key research questions that have yet to be answered. The updated LAPD now provides the platform to support an exciting new phase of global palynological research in which multi-site data are being integrated to address current cuttingedge research questions.
Global pollen databases Although analyses of individual sites remain crucially important and are the basis of all integrative studies, pollen analysis is moving from an emphasis on single-site analyses to multisite integrative analyses and the generation of spatial summaries of ecosystem dynamics  (Bradshaw, 2013). Integration of multi-site and multiproxy data facilitates investigation of a range of key research questions, such as response lags  (Seppä and Bennett, 2003) , the direction and rates of species migration and population expansions and contractions  (Blois et al. , 2011) , acclimation and eventual microevolutionary adaptation  (Feeley et al. , 2012) , ecological resilience  (Willis et al. , 2010) , asynchronous ecosystem responses to (abrupt) climate change  (Kohfeld and Harrison, 2000) , microrefugia  (Rull, 2009; Mosblech et al.
, 2011; Collins et al. , 2013) , and no-analog ecosystem formation  (Williams and Jackson, 2007; Correa-Metrio et al. , 2012). Furthermore, a continent-wide overview of sites highlights available data for both generating and answering research questions  (Seddon et al. , 2014). Therefore, global databases of environmental data from the past and present will become increasingly important for enabling new research directions, to facilitate large accessible archives and collaborative thinking between research groups.
Regional pollen database of Latin America The lack of a comprehensive inventory of pollen sites from "Latin America" (Caribbean region, México, and Central and South America) has inhibited synoptic studies of the region and has caused an unawareness of the spatial and temporal coverage potentially available for global-scale assessments  (Kohfeld and Harrison, 2000; Gajewski, 2008; Bartlein et al. , 2011). After the Latin American Pollen Database (LAPD) was initiated in 1994, it passed through several institutions, to finally reappear again without new updates in 2007, when it was incorporated into the Neotoma Paleoecology Database (www. neotomadb. org;  Grimm et al. , 2013). Beginning in 2014, new data contributed by individual investigators was added to LAPD/Neotoma; however most of the LAPD data in Neotoma are from a 2002 version of LAPD.
It is important to present the full extent of the growing palynological efforts in Latin America so that the potential for continental-scale synoptic studies can be assessed and researchers are aware of the available data for inclusion in their research. A comprehensive and updated database would be also useful to better address the origin and temporal evolution of "Latitudinal Diversity Gradients," as well as to analyze the relationships between pollen diversity and vegetation diversity in time and space. Finally, it is important to have identified those areas where sampling effort should be focused in the near future so as to complete the picture of different biotic and climate dynamic changes.
History of LAPD In 1994, Vera Markgraf at the University of Colorado (USA) started an open database of Latin American pollen data. During the period between 1998 and 2003, management of the LAPD was based at the University of Amsterdam, where Robert Marchant served as coordinator. Among numerous papers by Marchant and collaborators two are key for this paper. One was a synthesis of the distribution and ecology of taxa in the LAPD  (Marchant et al. , 2002) , and the other was pollenbased biome reconstructions for Latin America  (Marchant et al. , 2009). The version of the LAPD in Amsterdam ultimately incorporated about 500 pollen sites, including data from cores, archeological, cave and alluvial sites and surface samples and sites from Central America, the Caribbean, and South America. However, this database was never publicly available.
Through the NOAA Paleoclimatology website and several workshops, the idea of sharing data was promoted, especially before data become lost or abandoned over time  (Michener et al. , 1997). Active management of LAPD at Amsterdam ended in 2003, and no further updates were made to the website and related database. Meanwhile, publication of new data from Latin America has accelerated, and the current LAPD is outdated, a common problem of shared databases  (Costello et al. , 2014).
Description of the data compilation As a first step to updating LAPD and for developing a plan for acquisition of new data, we have developed an inventory of existing data for potential incorporation into LAPD. We carried out an exhaustive search for published pollen datasets and compiled the following metadata: site latitude-longitude coordinates and altitude, proxies analyzed, chronological control, and estimated time range covered. The inventory includes both paleodata and modern pollen samples and data from terrestrial and marine environments. Although historically LAPD has focused on the Quaternary period, the new inventory also includes pollen records from the Pliocene and late Miocene, especially long records that also span the Quaternary. Direct access to Colombian universities facilitated the addition of "grey" literature (including Master and Ph.
Spatial metadata The geographical extent of the inventory was confined between latitudes 32°N to 63°S and longitudes 30°W to 116°W. For many sites, especially those published before 1980, accurate locational information is not available, but insofar as possible, the published geographic coordinates were recorded. Significant discrepancies in published descriptive locations and latitude-longitude coordinates were checked, for example sites with coordinates in the wrong country or terrestrial sites with coordinates in the sea. In such cases, other references and Google Earth were consulted where possible to obtain estimated coordinates. Most modern samples have excellent metadata for their location with the advent of Geographical Positioning System (GPS) and online mapping tools such as Google Earth.
Published altitudinal data have not been adjusted even if coordinates were incorrect (a typo in a longitude or latitude coordinate does not necessarily imply an error in altitude). Here again, the pre-GPS altitude assessments were often based on altimeters that could drift in accuracy by N100 m during a day. The temporal coverage of datasets was recorded as published without further evaluation of radiocarbon accuracy. Sites were categorized into broad time bins, including the last glacial cycle (300-50 thousand calibrated years before the Present, here indicated as 300-50 ka), the transition of the Last Glacial Maximum (LGM; 22-20 ka), the Holocene (12-10 ka), and the period of most recent human impact (2-0 ka). The latter time bin is currently of specific interest at a global scale (PAGES-2k Consortium, 2013) and regional scale (http://www.
Geochronologic database of the LAPD Mapped syntheses are critically limited by the accuracy and precision of 14 C ages  (Grimm and Jacobson, 2004; Giesecke et al. , 2012; Flantua et al. , 2015a) , especially for those aimed at assessing the synchrony of change across a region. In this first phase of temporal assessment, we evaluated only the "age control density" for each dataset. This score indicates the density of the geochronologic ages ( 14 C, 210 Pb, Useries, etc) along the total core length and is quantified by dividing the length of time represented by the sedimentary sequence by the number of geochronologic ages. The density of ages was calculated using the original author-reported age controls. Sites (n = 97) with only one geochronologic date were excluded.
Additional metadata If the publication named the biome in which the site occurred, that biome was recorded. If no specific biome was named, a biome was assigned as per Table  1  from  Marchant et al. (2009). Datasets were categorized as monoproxy if they included only pollen data or multiproxy if other biological, physical, or chemical data are available. Figures throughout this paper were created using ArcGIS ® software by Esri (2012).
Spatial coverage The density and the spatial distribution of pollen sites over a geographical region are important variables for paleomapping and spatial interpolation. The LAPD inventory comprises datasets from 30 countries, including 4817 modern pollen surface samples (Fig. 1A ) and 1379 paleo-datasets (Fig. 1B ). Surface-sample coverage in terms of density of samples and representation of biomes is especially good from Argentina (21%), Colombia (18%), and Chile (9%) (Table  1 ). A limitation, however, is that although published surface-sample datasets often include a large number of samples, precise geographical coordinates are not always provided, in which case, a number of points may be assigned identical latitude-longitude coordinates and are mapped as single point in Fig. 1 , e. g. in the Cordillera Oriental of Colombia  (Grabandt, 1985) , Venezuelan Andes  (Rull, 2006) , and Tierra del Fuego  (Heusser, 1989).
Differences with previously announced LAPD versions  (Flantua et al. , 2013)  are owing to continuous updates and revisions of literature. The long history of paleoecological research in Latin America contributes to the impressive number of paleo-sites investigated, particularly from Chile (19%), Colombia (18%), Argentina (14%), Brazil (13%), and Mexico (10%). Palynological research at fossil animal middens (n = 88) contributes to the large amount of paleo-sites in Chile. New countries to the database are mainly from the Caribbean (e. g. Cuba and Haiti) and Central America (mainland Honduras and El Salvador). The density of sites is especially high in central and southern Mexico, the Colombian Andes, the region of Lake Titicaca in Peru and Bolivia, the southern pampas of Argentina, and the southern Patagonia of Argentina and Chile.
Spatial distance assessment The nearest neighbor index of the LAPD is b 1 for all time bins, indicating clustering of sites at all times. At 0 BP, mean nearest neighbor distance is 67 km; whereas at 50 ka, the mean distance is 218 km, with only 145 sites available older than 25 ka (Fig. 3A ). Thus, with increasing age, the density of sites decreases, while the degree of uncertainty for paleomapping increases. At the Pleistocene-Holocene transition (11. 6 ka), mean distance is higher in the central regions of Latin America and the Amazon basin compared to the Colombian Andes and Southern Chile and Argentina. Most sites (n N 800) include the last two millennia, while the LGM (n ≅ 120) and Pleistocene-Holocene transition (n ≅ 310) is represented in smaller numbers of datasets (Fig. 3B ). Time control for some datasets is uncertain, however, because of few 14 C or other geochronological control.
, 2005)  and Lake Petén-Itza in Guatemala (Correa-Metrio et al, 2013), 100 ka and 85 ka respectively. The Cariaco record (68 ka,  González et al. , 2008)  is an example of an exceptional regional reference for the palaeoeclimatology of the area, and also as a chronological landmark for its annualy laminated sediments  (Hughen et al. , 2004)  that have been used to calibrate the worldwide 14 C database  (Reimer et al. , 2013).
Temporal assessment of the LAPD The new LAPD inventory contains 5003 chronological controls from 1062 sites (some sites contain multiple records) including tephras (n = 30) and uranium series dates (n = 6). Relative chronologic controls, such as biostratigraphic dates, were not included. During recent years, the number of ages used for stratigraphic age models has trended upwards; since 2010, the mean and median number of dates per published age model is five and three, respectively (Fig. 4 ); however, the number varies widely, between 1 and 50. Wide variation in dating resolution has important implications for paleomapping (Fig. 5 ). Publications report geochronologic metadata inconsistently. Important details are often missing, including material dated, laboratory number, calibration curve and program, and age modeling algorithm.