dataesr/scientific-paragraphs-categorization huggingface dataset:
The data set was accessed from the GlioVis web server (http://gliovis. bioinfo. cnio. es/) and mRNA levels retrieved using the correlation tool. After plotting the mRNA level of PRKDC against MB21D1, we applied a filter cutoff to determine low and high expression allowing the definition of 4 populations: PRKDC low /MB21D1 low ; PRKDC low / MB21D1 high ; PRKDC high /MB21D1 low ; PRKDC high /MB21D1 high. mRNA levels of genes of interest were plotted based on these populations. One-way ANOVA with Tukey's multiple comparisons test was used to compare gene expression among populations in glioblastoma dataset.
Acknowledgements We thank  P. Pourquier  for the HCT116 cell lines,  N. Bonnefoy  for the parental CFPAC cell line,  Soren Paludan  for THP-1 cell lines,  C. Vanpouille-Box  for the GL261 CTRL and GL261 cGAS-/-cell lines and  E. Chevet  for the gift of parental GL261 cells. We thank  C. Goujon  for the parental T98G cell line and CRISPR/ Cas9 gRNA sequences. We thank  C. Langevin  and all members of the molecular basis of inflammation laboratory for discussions. We thank  N. Dupuis  and A. Blömeke-Eiben  for technical assistance. We acknowledge iExplore-RAM animal facility, the  MRI imaging facility , member of the national infrastructure France-BioImaging infrastructure supported by the  French National Research Agency  ( ANR-10-INBS-04 , " Investments for the future ") and the  SIRIC Montpellier Cancer  ( INCa_Inserm_DGOS_12553 ).
Work in NL's laboratory was funded by the  European Research Council  ( ERC-Stg CrIC :  637763 ,  ERC-PoC DIM-CrIC: 893772 ),  LA LIGUE pour la recherche contre le cancer ,  Agence Nationale de Recherche sur le SIDA et les  H epatites virales (ANRS:  ECTZ117448 ),  La R egion Languedoc Roussillon , and the  CNRS. CT was supported by the  Merck Sharp and Dohme Avenir  ( MSD-Avenir-GnoSTic) program  and  ANRS  ( ECTZ119088 ). HC was supported by  LA LIGUE pour la recherche contre le  cancer. SG was supported by a  LabMuse EpiGenMed. ALCV was supported by  ERC -Stg CrIC :  637763 , and  MSD-Avenir. KP was supported by the  Laboratoire d'Excellence EpiGenMed. IKV was supported by  ERC -Stg CrIC :  637763 , followed by  Fondation pour la Recherche M edicale  (FRM:  ARF20170938586  " Prix Roger PROPICE pour la recherche sur le cancer du pancreas ").
JM was supported by an " Agence Nationale de Recherche Technologie" (ANRT). Work in NB laboratory was funded by  Fondation de France  (JJ),  Fondation ARC contre le Cancer  (PJA to JG and NB),  Institut National du Cancer  ( INCa   PAIR-CEREB lNCa_16285 ),  Ligue nationale contre le cancer  (Equipe labellis ee) et comit es de Loire- Atlantique ,  Maine et Loire , Vend ee, Ille-et-Vilaine (JG, NB). CM received a fellowship from  Ligue R egionale contre le Cancer  and R  egion Pays-de-la-Loire. Work in MSS laboratory is funded by grants from  National Institutes of Health  ( CA196740 ,  CA258100 ) and  Department of Defense  ( W81XWH-20-1-0379 ). Work in CVB laboratory is funded by grants from the  Uncle Kory Foundation , the  StacheStrong Foundation  and the  St. Baldrick's Foundation. MDM is supported by a  2022-SITC Nektar Therapeutics Equity  and  Inclusion in Cancer Immunotherapy fellowship.
P-values were determined by Student's t-test. ns: not significant. *P < 0. 05, **P < 0. 01, ****P < 0. 0001. Mann-Withney test was performed to analyze macrophage recruitment in zebrafish. Source data are available online for this figure. 10 of 22 The EMBO Journal 42: e111961 | 2023 Ó 2022 The Authors The EMBO Journal Clara Taffoni et al (Fig 6A).
Statistical analysis was performed using GraphPad Prism version 7. For statistical analysis of in vitro experiments, unpaired Student's ttest was performed as indicated in figure legends. One-way Anova with Tukey's multiple comparisons test was used to analyze gene expression among populations in glioblastoma datasets. One-way ANOVA was used for mice studies. Mann-Whitney test was performed to analyze tumor growth and macrophage recruitment in zebrafish. The number of replicates in each experiment (including number of mice or zebrafish) are indicated in the figure legends. All data are expressed as mean AE SEM. The statistical parameters can be found in the figures and the figure legends. Ns: non-significant. *P < 0. 05, **P < 0. 01, ***P < 0. 001 and ****P < 0. 0001. Figure EV1. DNA-PKcs promotes type I Interferon responses in cancer cells that do not express cGAS.
Secondly, there are few local indicators to predict the large-scale (spatial and temporal) impact of coastal infrastructure construction and development and changes in ocean forcing on coastal morphology  (Hzami et al. , 2021; Tano et al. , 2016). Numerical modelling would undoubtedly enable the derivation of this type of indicators  (Vousdoukas et al. , 2022; Abessolo et al. , 2021; Giardino et al, 2018). Nevertheless, calibration and improving existing models require large databases and better descriptions of nearshore processes. Thirdly, the discordance of actors and responsibilities among African countries, and sometimes even within the same country, has too often prevented the planning of effective and sustainable long-term solutions  (Giardino et al, 2018). There are regional programs that synergize efforts to understand the dynamics of these environments such as the West African Coastal Areas (WACA) Management Program and the West African Coastal Observatory (ORLOA).
) and particularly suited for tropical developing countries and open-wave areas  (Almar et al. , 2014a). Several parameters are estimated from video imagery, such as the shoreline position (e. g. ,  Almar et al. , 2012b , Pianca et al. , 2015) , intertidal topography (e. g. ,  Osorio et   A pilot video camera station was installed at Grand Popo (Benin) in 2013, and the network is currently extending to West and Central Africa (Fig. 2 ). In this paper, we demonstrate how this pilot network can be used to build a database to document African coasts evolution, and how the network can support effective land-use planning policy. We present the main scienti c advances induced by the data collected, and we discuss the bene t of building data and scienti c expertise in the management and planning of the coastal environment in Africa.
New Insights Through Coastal Video Camera Monitoring All-in-one measuring system at the coast: methodological developments Most of the parameters needed to understand the African coastal environments are measured simultaneously in this network: wave's characteristics, water level variations and beach morphology. Several studies have been conducted to investigate these video-based estimates and the results showed in general an overall error below 10% (see results in Table  S2 ). The main characteristics of waves (e. g. , Fig. 3 ) that represent the most important forcing in open coastal environments are determined at wave breaking area where it is di cult to install conventional measuring equipment due to the dissipation of wave energy. For instance, it provides long-term local wave datasets  (Abessolo et al.
Bergsma and Almar (2018) and Thuan et al. (2019) de ned two new error estimators based solely on video processing to assess the accuracy of video-derived bathymetry: the wavelength-related-error proxy and the tide-related-error proxy. These proxies express a reliability rate on bathymetric estimates to identify erroneous data and extract a useful data set when applying a Kalman lter, in the same way as the cBathy method (see  Holman et al. , 2013). Abessolo et al (2020b) tested these two proxies on data collected at Grand Popo. Their results showed that both estimators reduce errors by at least 30%.
Using collocated dataset, tide gauge, and wave buoy,  Abessolo et al. (2022)  showed that this contribution could be estimated from a video camera station, thus highlighting the potential of optimizing the location of coastal observation networks with respect to satellite ground tracks (as expressed in  Marti et al. , 2021). Tidal harmonics were successfully extracted together with long-term sea level rise, and the signature of sea level variations induced by coastal waves, such as Kelvin waves, could well be present in the video data, but this remains to be studied and investigated through more developments and studies.
The video camera network described in this paper is one of the guarantees for the implementation of a more integrated management policy along the African coasts. Video camera stations serve as a multivariable monitoring platform, with the collection over long periods of real-time estimates of morphological and hydrodynamic variations around the wave breaking zone, where in-situ measurement techniques and other types of remote sensing (e. g. , satellite, drone, Lidar) are either too costly or inadequate. The multiplicity of video camera station sites contributes to the strengthening of the database necessary to study the associated physical phenomena. Moreover, the low nancial cost of establishing a video camera station guarantees the spatial development of this network whose maintenance depends almost only on human resources.
The generated database could serve as a basis for the study of natural processes, the prediction of associated risks, and therefore for the development of a common regional coastal management policy. This includes the identi cation of objectives, priorities, strategies, and timetables common to several countries to achieve them, even if compliance with legal and regulatory frameworks is a challenge that falls under the sovereignty of the States, with of course the consideration of United Nations guidelines at the level of the African Union. In addition, this camera network can be the basis for the development of monitoring systems speci c to the sub-region concerning the management of, for example, the registration of the departure and arrival of artisanal shing boats, which are essential in the region.
The coastal African camera network has the potential to bridge the problem of non-data availability for coastal studies. The video data from the network can provide data and information that will help coastal scientists, investors, managers, and policymakers in improving the spatial planning and management of the African coastal areas. The network can be used to gather data that will be used for studies on ooding, erosion, coastal structures, infrastructure monitoring, oil pollution assessment, over shing, and ecosystem and ecosystem services. It can provide new data and information useful for understanding and managing African coastal environments to the Coastal Observatories such as the World Bank-funded WACA and ORLOA.
Future perspective The coastal camera network is rapidly growing, and it is set to become an African data hub for coastal video imagery. Such a platform could be linked to the World Bank-funded WACA Management Programme; or the ORLOA, an observatory established to develop the Central and West African coastal territories in a sustainable manner, through the promotion, production, and sharing of reliable and homogeneous data using harmonized data collection protocols for decision-making. The ORLOA could be used as a regional centralized repository accessible to all actors (researchers and decision makers). The repository must be made up of generated data and processing algorithms, to promote sharing and integration of all actors. The network is poised to make signi cant progress on coastal environmental issues that have signi cant societal impacts.
Conclusions This paper presents a pilot active network of video camera stations along the African coasts with similar technology, methods, and data sharing between active scienti c communities in these countries. This network ful ls a long-expected need to document African coastal evolution with the objectives of creating an e cient coastal database, implementing targeted research, and promoting a more effective land-use planning policy. The current generated database consists of hydrodynamic (coastal waves, tides, and sea level) and morphologic (shoreline and beach pro le) data collected by an increasing number of video camera stations. These data have led to new methodological developments, student capacity building, and a better understanding of coastal processes, e. g. , tropical beach dynamics, sea level variability, dangerous rip currents or ash rips, and the impact of coastal defences.
The coastal African camera network can help investigate and address societal and environmental challenges (e. g. , engineering, risk mitigation, and prevention). It can also provide key local ground truth that is important for satellite remote sensing techniques and engineering studies, even more, if when coupled with other measurements such as DGPS, unmanned aerial vehicles (UAVs), but also wave, tide and current moorings. The development efforts and lessons learned in each African country can be synergized, enabling more e cient planning through sharing of associated (novel) technologies, data analyses, and results. This network is a real asset for regional programs like the West African Coastal Observatory (ORLOA) or the West Africa Coastal Areas Program (WACA) to target hotspots. This network needs to be perennialized and further extended to answer important questions related to the coastal zone development in Africa.
Data And Methods Several hydrodynamic and morphological parameters can be deduced from video imagery (Fig. 7 ). Hydrodynamic parameters consist of wave characteristics ( , , direction) and water level variations (tide and sea level rise). Morphological parameters consist of shoreline location, intertidal topography, and bathymetry. Figure  3  shows the complete processing scheme and the estimated parameters. On site-processing Grand Popo, James Town, Mbour, and Kribi video camera stations are tted with an on-site local computer that processes the raw images and stores three types of secondary images every 10 or 15 minutes: a snapshot, a time exposure (Timex), and several time-stacks. Timex images are snapshot images averaged every 10 or 15 minutes into a single image  (Holland et al. , 1997).
Time-stack images are obtained by stacking successive traces corresponding to 10 or 15 min of snapshots  (Holland and Holman, 1993) , with as many 15 min time-stacks images as traces implemented. Saint Louis, Elmina, Dzita and Assounidé video camera stations are not tted with a local computer. The raw images collected at a frequency of 2 Hz are stored directly on a memory card as a video le since the new versions of the cameras used allow this. This implies that the data must be retrieved before the memory card is full. The full pre-processing is then done in the laboratory.
Acknowledgements The Grand Popo experiments (2013 and 2014) were supported by the  French INSU/CNRS   EC2CO-LEFE/IRD , IRHOB, and  UNESCO Co-Chair ICMPA/UAC. We are indebted to the  'Forces Navales' of Benin at Grand Popo  for their logistic support during the eld experiment and for allowing the installation of the permanent video system on the semaphore. We thank the managers of the  Palm Beach Hotel in Kribi  for allowing the installation of the camera. We also acknowledge the  National Geographic Society and IRD-JEAI  for funding the Coasts-Under-Control and Beachmon Projects to set up video stations in Ghana. The Video camera station at Assounidé was sustained by  IRD-LEGOS  (thanks to  Julien Jouanno  and FORSEA),  JEAI IVOARE-UP , and WACA.
Acknowledgements. The authors thank the referee for the positive and enthusiastic feedback. This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No. 863412 ). Computing resources were provided by  TGCC  and  CINES  under the allocation A0090407669 made by  GENCI. The authors thank  Maïca Clavel ,  Antoine Strugarek ,  Guillaume Dubus  and  Geoffroy Lesur  for fruitful discussions and constructive feedback.
Objective: The aim of this study is to assess the impact of prenatal exposure to serotonergic antidepressants, accounting for maternal mood disturbances, on markers of stress regulation during childhood. Methods: We will follow PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and will search MEDLINE, Embase, CINAHL, PsycINFO, and ClinicalTrials. gov for full-length studies that assessed physiological (eg, cortisol level, heart rate variability, salivary amylase, pupillary size, C-reactive protein) indices of stress regulation in children of pregnant people who were treated with a serotonergic antidepressant at any point during pregnancy. We will assess the quality of observational studies using the Newcastle-Ottawa Scale and the quality of experimental studies using the Cochrane risk-of-bias tool.
Information Sources and Literature Search We developed our search strategy with the consultation of a librarian and will search the literature by population and intervention (Table  1 ). The following databases will be searched: MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCOhost), PsycINFO (EBSCOhost), and ClinicalTrials. gov. We will use both Medical Subject Headings (MeSH) terms and keywords. Our search strategy for the MEDLINE database is outlined in Multimedia Appendix 1. We will adjust the MeSH terms and keywords used to accommodate the different databases' requirements and limitations. We will limit our search to studies published in English or French. We will not limit for year of publication and will include original studies of all study types. We will conduct a manual search of the journals Psychoneuroendocrinology, Early Human Development, Neuroscience, and Neuroscience & Biobehavioral Reviews, as well as a forward and backward citation search through Google Scholar  [47]  on all included papers to locate additional papers that may have been missed in our literature search.
Study Selection Process Using our predetermined selection criteria, two authors (EZZ and AL) will independently screen all retrieved papers at level 1 (title and abstract) for inclusion in the study using Covidence, a screening and data extraction tool for systematic reviews  [48]. Once a list of studies is determined, the selected papers will be reviewed at level 2 (full text) to select a final list of review studies. Screening questions can be found in Multimedia Appendix 2. At any point, authors will meet to discuss discrepancies and a third author (SH) will be consulted if disagreement occurs.
Data Collection Process Two authors (EZZ and AL) will independently extract the following information from all included studies: year of publication, country, sample size, study design, study setting, trimester of pregnancy, drug exposure class, drug exposure generic name, drug dose, cortisol level (diurnal), cortisol level (stress challenge), heart rate variability, salivary amylase, pupillary size, CRP, cytokines, chemokines, lymphokines, IL-6, maternal depression, maternal depression diagnosis method, maternal anxiety, and maternal anxiety diagnosis method. Authors will meet to discuss discrepancies and a third author (SH) will be consulted if disagreement occurs. If needed, we will contact study corresponding authors for unpublished or missing data.
Synthesis of Included Studies We will pool studies based on their reported outcome and will present the characteristics of included studies both descriptively and in a table. Where possible, we will pool reported levels of cortisol, heart rate variability, salivary amylase, pupillary size, and CRP. We will calculate the Cochrane Q test (chi-square) and Higgins I 2 score to assess the statistical heterogeneity of effect size estimates across our included studies before running a meta-analysis. When meta-analysis is possible, we will calculate pooled mean differences for continuous data and perform a random-effects meta-analysis for dichotomous data  [54]. If meta-analysis is not possible, we will conduct a narrative synthesis of the data. When a sufficient number of studies are found, we will perform subgroup analysis and assess outcomes measured by drug class, dose, trimester of exposure, and child's age and gender.
In most recent surveys, we found that quantitative data are obtained from the questionnaire responses, while qualitative information is obtained from a set of persons who are interviewed separately, and whose responses are analyzed with more detail. Typically, this set of responses, referred to as experts, is used to validate and interpret the responses of the questionnaire. However, expert answers usually point towards a positive attitude to drones, as confirmed during the first CORUS-XUAM stakeholder workshop. This workshop analyzed the most critical elements related to UAS/UAM operations along with possible solutions that could enable a sustainable and accepted expansion of drone operations in and around the European cities. In particular, the fifth day of the workshop was dedicated to the analysis of societal impact of drone operations and possible mitigation measures.
CORUS-XUAM Mitigations Subset As a final step for this work, we selected a subset of mitigation measures, mainly from the operational/ConOps category (but not all) that are applicable to very large (drone flight) demonstrations (VLDs) being prepared within the CORUS-XUAM project. Very-large-scale demonstration (VLD) activities will be at the heart of CORUS-XUAM and will support the integrated operations of UAS/UAM and manned aircraft and the advanced forms of interaction through digital data exchange supported by integrated and advanced U-space services in urban, suburban, and intercity scenarios, as well as in and near ATM-controlled airspace and airports. The VLDs will focus on different types of missions such as passenger transport, delivery, emergency response, and surveillance. The VLDs will use different U-space deployment architectures and state-of-the-art technologies.
The proposed mitigation measures do not only concern drone operators but also regulators, educational bodies, other airspace stakeholders, infrastructure providers, technology and software developers, and research centers. Future work includes the analysis of the application of mitigations in the six very large demonstrations of CORUS-XUAM to understand their impact and to fully consolidate the mitigation list proposed in this paper. It also includes new measures and scientific work to provide more detailed data to some mitigation measures, such as the perception of noise in the ground, which will help to suggest limits on altitude and speed. Future observations are needed to understand the interaction with birds. The analysis of images captured during flights will be useful to estimate threats to privacy.
ACKNOWLEDGMENTS S. M and M. B. thank the  European Research Council (ERC)  advanced grant  SubNano (Grant agreement   832237 ) and the  Centre de Calcul Intensif d'Aix-Marseille. E. V. thanks the  Brazilian agencies CAPES  for funding the grant through the  Capes/PrInt  project (Grant number  88887. 467063/2019-00 ). E. V. and S. A. M. thank the  Brazilian agency CNPq  (Grant Numbers  423112/2018-0 ,  308371/2021-6  and  310123/2020-23 8 ) for support. I. B. thanks the  Brazilian agencies CNPq  (Grant numbers  304148/2018-0  and  409447/2018-8 ) and Faperj (Grant number  E26/201. 197/2021 ) for support. This work was supported by the  Center for Integrated Nanotechnologies  (Project No. 2021BC0076 ), an  Office of Science User Facility operated for the U. S. Department of Energy Office of Science by Los Alamos National Laboratory  (Contract  89233218CNA000001 ) and  Sandia National Laboratories  (Contract  DE-NA-0003525 ).