dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Analyses Results are presented as a median ± standard deviation. SigmaPlot (version 12. 5, Systat Software Inc. , San Jose, CA, USA) was used to perform the statistical analyses. The Shapiro-Wilk normality test preceded all analyses. The T-test and Mann-Whitney test were used to compare two groups of continuous variables following Gaussian and non-Gaussian distributions, respectively. The Chi-square and Fisher Exact test were used for qualitative variables. Correlations between two variables were assessed using the Spearman test. The association between miR-574-5p and TAA in the serum cohort was evaluated using the ROC (receiver operating characteristic) curve analysis.
Funding: This research was funded by: A. B. is funded by the  National Research Fund of Luxembourg  (grant #  AFR 8832104 ). C. L. L. is supported by the  Fredman Fellowship , the  Toomey Fund for Aortic Dissection Research , and the  Hassenfeld Fellowship. A. C. is funded by the  Aneurysmal Pathology Foundation. M. E. L. is supported by the  National Institutes of Health  (grant # HL130113 ) and the  Toomey Fund for Aortic Dissection Research. Y. D. is supported by the  National Research Fund  and the  Ministry of Higher Education and Research of Luxembourg. R. S. R. and S. D. are supported by the  National Heart, Lung, and Blood Institute (NHLBI)  grant  RO1-HL22547. S. N. is supported by the " Fonds pour la chirurgie cardiaque, ASBL ", by the  European Program   FP7  "Fighting aneurysmal diseases" no.
There is some evidence of differential impacts of shift work on mental health by sex  22 23  although the evidence is inconsistent across studies. Finally, self-selection of individuals in to and out of jobs with non-standard work hours (the 'healthy worker effect') can bias results towards underestimated effects and is particularly problematic when past exposures are not accounted for. To address these challenges, the present study used data from the Swedish Longitudinal Occupational Survey of Health (SLOSH). 24 This large national survey collected detailed information on workplace, demographic and social characteristics, and can be linked to national health registries in Sweden. We examined the prospective effect of work schedule (using detailed categories that considered prior night work history) on antidepressant prescription rates (using objective measures obtained via linkage to a national health registry), in females and in males, over a 2-year period.
Data on antidepressant medication prescriptions were obtained from the Swedish National Prescribed Drug Register. This register contains information on all prescribed drugs dispensed from Swedish pharmacies since July 2005 (except for those given in hospitals or nursing homes). These data were anonymously linked to survey respondents through registered personal identification numbers. All Drug Register prescriptions coded N06A according to the Anatomical Therapeutic Chemical System  28  were extracted for the analyses. A dichotomous variable ('yes' or 'no' was created to describe any antidepressant prescriptions registered between 17 June 2008 and 31 December 2010, representing a period of approximately 2. 5 years following the 2008 survey wave; 17 June 2008 represents the date on which 75% of responses were received from the 2008 SLOSH wave participants.
Acknowledgements The authors thank  Viktor Persson  for his assistance with SLOSH data extraction and linkage. Contributors CL participated in Swedish Longitudinal Occupational Survey of Health (SLOSH) data collection. ALH, GK and PT conceptualised the current study design; ALH performed statistical analyses and drafted the manuscript. All authors participated in interpreting the data and revising the manuscript. Funding The project was supported by the  Swedish Research Council for Health, Working Life and Welfare  (grant number  2016-07150 ) which provided support for PT, CL and GK, and for the costs of publication. At the time of analyses and writing, ALH was supported by  WorkSafeBC 's  Research Training Award Program  and a postdoctoral fellowship from the  International Agency for Research on Cancer.
Despite the quantitative difference, the AS2 promoter and the endogenous gene have similar expression domains. Domain-specific expression of HF-RPL18 can efficiently incorporate epitope tags into polysomes for immunopurification of translating cellular mRNAs from target domains  3, 5. To isolate translating mRNA from target domains, we immunopurified polysomes from seedlings from which roots had been removed at 7 days after germination (DAG). Then, we used deep sequencing to map and quantify these mRNA samples (Supplementary Fig. 2 ). In subsequent analysis, we also combined leaf boundary and whole leaf gene expression datasets, which were defined by the LATERAL SUPPRESSOR (LAS) and AS1 promoters, obtained from an earlier study using identical protocols  16. Taken together, these domains represent many of the key domains of the SAM and developing leaves.
Domain-specific expression patterns. To further ensure the quality and reliability of our data, we compared our translatome dataset with published data, such as in situ hybridization results. We used 20 genes with well-characterized domain-enriched expression in the SAM and/or leaves, and analyzed the enrichment levels of their encoded RNAs based on our translatome dataset. As shown in Fig. 1b , Supplementary Fig. 5  and Supplementary Data 1, we detected the expected enrichment and depletion for all transcripts, which validates the domain-specific translatome profiling data. It should be noted that UFO has higher enrichment in the WUS and CLV3 domains in the translatome data, due to the expansion of the UFO' domain. There is a large number of AS1 domain-enriched genes, which is likely due to temporal difference among AS1, AS2, and FIL promoters.
Domain-specific alternative splicing and lncRNA expression. Alternative splicing (AS) contributes to the diversity of the transcriptome and the proteome. Studies have identified that over 60% of intron-containing genes may have AS during different developmental stages and under stress  32. Recent studies have shown that AS events can be domain specific  33, 34. Compared with transcriptome profiling, translatome profiling provides a better estimation of the contribution of AS to proteome diversity  3, 35. In our translatome dataset, we observed substantial domain-specific AS events. A total of 4261 genes have more than one TAIR (The Arabidopsis Information Resource)-annotated isoform expressed (RPKM ≥ 1). Although splicing isoforms of the same gene generally show similar domain expression, we identified 751 genes whose isoforms showed domain-specific enrichment (z-score ≥ 2).
Ribosome-bound lncRNAs were also found in animals and Arabidopsis  [38] [39] [40]. Using recent expression-based lncRNA annotations  34, 41  , as well as de novo assembly based on our own data, we analyzed domain-specific lncRNA distribution in the translatome dataset. Together, we detected 242 lncRNAs in one or more domains (Supplementary Data 5). Among them, 13 are previously unknown lncRNAs, and 21 overlap with but extend previous annotations at the 5' or/and the 3' ends. We found 117 lncRNAs (48. 3% of all expressed ones) were enriched in one domain (Fig. 3c ), which is substantially higher than the proportion for mRNAs. The WUS domain and leaf domains share distinct sets of enriched lncRNAs, suggesting possible involvement of lncRNAs in development. Besides lncRNAs, we also found 125 pseudogenes with moderate expression levels in the translatome datasets.
A gene with a CS score above 0. 3 was denoted to be cell-type specifically expressed. Gene ontology enrichment and promoter motif analysis. GO term enrichment analysis was performed using agriGO with the Singular Enrichment Analysis method  71  and summarized using REVIGO  72. For the enrichment analysis of leaf abaxial differential genes, BiNGO  73  was carried out and the result was displayed by Cytoscape  74. Lists of the phytohormone-responsive genes (Supplementary Data 12) and transcription factor classification (Supplementary Data 13) were given  16. The gene enrichment analysis was quantified by log 2 odds ratio (LR)  3. Briefly, to determine which categories of hormone-responsive genes or transcription factor genes (HT) are enriched with domain characteristic (DC) genes, the number of DC genes contained in each HT category was counted.
Histograms of expression dynamics were produced using R packages. Hierarchical clustering analysis for marker gene and domain-enriched genes were performed in Cluster 3. 0 and shown with Treeview  76. The complete hierarchical clustering analysis for all expressed genes in each library was carried out by hclust and principal component analysis of domainspecific genes was performed by prcomp within R packages. Co-expression network analysis. Co-expression network analysis was performed to identify modules of highly correlated genes using a R package WGCNA  42, 43. Genes with low coefficient of variation among domains (CV = STD/Mean, CV < 0. 7) were filtered out. Finally, log 2 transformed RPKM values of 7085 genes were used to construct the network. The soft threshold power was set to 9, according to assessment of scale-free topology and a dynamic tree cutoff 0.
20 was employed to merge similar trees (Supplement Fig. 14 ). The statistical significances of enrichment of domain enriched genes in each module were assessed by hypergeometric distribution. Co-expression networks were displayed using Cytoscape  74. lncRNA and pseudogene expression analysis. We combined previous expression-based lncRNA annotations, including those obtained from TAIR10 and RepTAS databases, as known lncRNAs  34, 41, 77. We also identified novel lncRNAs based on our expression data following published protocols  34, 41. In brief, we employed Cufflinks (v2. 2. 1)  78  and Stringtie (v1. 3. 5)  79 to assemble putative transcripts for each biological replicate. Meta-assemblies were performed with Cuffmerge (v1. 0. 0) to construct a final unified set of transcripts. Transcripts that overlapped with annotated genes were removed.
Those overlapped with known lncRNAs either with extended 5' or 3' end were classified as known (Supplementary Data 5). The remaining assembled transcripts were considered novel lncRNAs if they fit the following criteria  34, 41  : (1) longer than 200 bp; (2) 500 bp away from protein coding genes; (3) do not overlap with transposons; and (4) containing no ORF (predicted by webAUGUSTUS) longer than 300 bp. Pseudogene annotation was following TAIR10. The expression of lncRNAs and pseudogenes were also assessed and summarized in RPKM with edgeR. The differential expression patterns were identified by z-score as for protein coding genes. Optical and scanning electron microscopy. For immunolocalization, shoot apices were fixed in fresh FAA solution (3. 7% formaldehyde, 50% ethanol, and 5% acetic acid) under vacuum and embedded in Steedman's wax composed of polyethylene glycol 400 distearate and 1-hexadecanol (Sigma-Aldrich).
Acknowledgements We thank  Drs. Yuval Eshed ,  Tengbo Huang ,  Thomas Laux ,  David Smyth , and  Hirokazu Tsukaya  for seeds. This work was supported by  National Natural Science Foundation of China (NSFC)  Grants  31430010 ,  31825002 ,  31861143021 , and  31861130355 ,  National Basic Research Program of China  ( 973 Program ) Grant  2014CB943500 , and a  Royal Society Newton Advanced Fellowship  (award  NAF/R1/180125 ) to Y. J. , by the  National Transgenic Science and Technology Program  Grant  2016ZX08010-002 ,  NSFC  Grant  31770311 , and  Youth Innovation Promotion Association of CAS  ( 2017139 ) to C. T. , by  NSFC  Grant  31871245 ,  University of CAS  (Grant  110601M206 ), and the  Beijing NOVA Program  ( Z161100004916107 ) to Y. W. , and by the  US NSF   2010  Project Grant  MCB-0929349  to E.
Data availability TRAP-seq data have been deposited in the NCBI Short Read Archive with accession number SRP145572. The expression patterns of different domains were implemented in a web based genome browser available at http://bar. utoronto. ca/ efp_arabidopsis/cgi-bin/efpWeb. cgi?dataSource=Shoot_Apex. The source data underlying Figs. 1c-d, 2a , 3b, Supplementary Figs. 5, 7a , and Supplementary Data 1, 2, 4-6, 9-11 are provided as a Source Data file. The authors declare that all other data supporting the findings of this study are available within the manuscript and its Supplementary files or are available from the corresponding author upon request.
Methods The FPC was built with the sampling of all pregnant women included in the French Echantillon generaliste des beneficiaires (EGB), which is a 1/97 th representative sample of the population covered by the French health insurance. The EGB includes anonymized information on the socio-demographic and medical characteristics of beneficiaries, and the health care services they have received such as diagnoses and procedure codes as well as data on filled reimbursed medication; EGB also includes data on hospital stays in all public and private French health facilities. Each filled prescription record contains information on drug brand and generic names, date of prescription and date of dispensing, quantity dispensed, mode of administration, duration of prescription, dosage, and prescribing physician specialty.
FPC includes data on all pregnancies of women in the EGB (2010-2013). Date of entry in the FPC is the first day of pregnancy regardless of pregnancy outcome (spontaneous abortions or planned abortions (with or without medical reasons), deliveries), and data on women are collected retrospectively for a period of one year before pregnancy, and prospectively during pregnancy, and up to one year after delivery. The prevalence of prescribed medications before, during and after pregnancy was compared; comparison was also done between trimesters. Pregnancy outcomes are described and include spontaneous and planned abortions, livebirths, and stillbirths.
The French Pregnancy Cohort (FPC) FPC is a representative sample of all French pregnant women with longitudinal follow-up data. The Echantillon généraliste des bénéficiaires (EGB) is a 1/97 th representative sample of the population covered by the French health insurance and includes data from two administrative databases, the SNIIRAM (reimbursement claims in ambulatory care), and the Programme de Médicalisation des Systèmes Informatiques (PMSI, national hospital discharge summaries)  [15]. It contains anonymous information on the socio-demographic and medical characteristics of beneficiaries, and the health care services they have received such as diagnoses and procedure codes, data on filled reimbursed medications, and specialty of the prescribers. Each prescription record contains information on drug brand and generic names, date of prescription and date of dispensing, quantity dispensed, mode of administration, duration of prescription, dosage, and prescribing physician specialty.
All drugs are classified according to their drug identification number (DIN) code, and the Anatomical Therapeutic Chemical (ATC) code. Over-the-counter (OTC) drugs and vitamins are not included in the EGB database if they are not prescribed or reimbursed; drugs administered during hospitalizations are also not included. Data on medications recorded in the EGB are based on prospective fillings. 1/97 th of people insured by the French social security were randomly sampled and form the EGB. The number of people protected by the general scheme in the EGB was 46,891,934 in 2008, and breakdown per age and sex is very similar to that of the overall French population  [15]. The Programme de Médicalisation des Systèmes Informatiques (PMSI) included in EGB includes data on short stays in public and private French health facilities since 1996.
It is a national database where each patient's stay is documented with personal information (age, sex, postal code of the area of residence), health medical data (diagnostic code according to the international classification of diseases, 10 th edition (ICD-10), medical procedure codes according to the French 'Classification des Actes Medicaux', and medical department of stay). For each calendar year studied, using data from the PMSI, an extraction of deliveries, spontaneous or induced/planned abortions was performed using an algorithm developed specifically for the FPC, which used data from medical and hospital visits/stays and procedures as well as diagnostic codes (ICD-10 codes) (Appendix A in S1 File). Hence, from the medical and hospitalisation visits data, pregnancies that were registered to the health insurance were identified and extracted using date of beginning of pregnancy listed in the standardized declaration of pregnancy form ('first prenatal medical examination').
These extractions constitute a set of pregnancies for which the ultrasound was performed in the first, second or third trimester of pregnancy. Gestational age, the date of the declaration of pregnancy, dates of the ultrasounds, and date of the pregnancy outcome (delivery, spontaneous or induced/planned abortions) were used for the estimation of the date of the beginning and end of pregnancy as well as the dates of the three trimesters. Although minimal compared to deliveries performed in hospital settings, data on deliveries occurring outside hospitals were also identified. The medicated induced/planned abortions were identified using the CCAM code JNP001 or with a procedure for evacuation of a pregnant uterus in the first trimester (CCAM code JNJD002) and from the benefits codes  (1981, 2411, 2419, 2422, 2423, 2425, 3329 ) (Appendix B in S1 File).
The unit of analysis was a pregnancy. In the FPC, women were prospectively followed from at least the year before pregnancy, during pregnancy until the end of pregnancy (induced/planned or spontaneous abortion, or delivery, whichever occurs first), and at least up to 1-year post-partum. Women were treated and followed prospectively as part of the usual health care management in France before, during and after pregnancy. In France, once having a positive pregnancy test, the woman may be checked with the same gynecologist throughout her pregnancy, including 3 ultrasound scans (1 st at 12 weeks, 2 nd at 22-24 weeks, and 3 rd at 30-35 weeks of pregnancy, respectively)  [16] [17] [18] [19]. Specifically, from the EGB, we selected data on all the variables that characterized a pregnant woman (age, insurance, government financial support, geographic code) as well as the variables that described the physician visits (date in day/month/year, prescriber, diagnosis, procedure).
As mentioned above, a visit was defined as a consultation for prenatal ultrasound, an obstetrical procedure, or any intervention performed by a midwife (including childbirth preparation). Ultrasound could be performed by a general practitioner (GP), a gynecologist, an obstetrician, an imaging center, or a midwife. The FPC includes data on all pregnancies between 2010-2013 included in the EGB-data on 39,364 pregnant women.
Baseline characteristics and prevalence of prescribed medication use before pregnancy and during the perinatal period Baseline data on FPC are presented here for the study period 2010-2013. Characteristics of women were assessed on the first day of gestation (1DG); defined as the first day of the last menstrual period. Medication exposures included all filled reimbursed medications by the Caisse National d'Assurance Maladie (CNAM) obtained by prescription and dispensed by a pharmacist. Prevalences of prescribed medication exposures are presented according to the 3 following time-windows of interest: 1) before pregnancy (12 months before the 1DG), 2) during pregnancy (1DG until the end of pregnancy (spontaneous or planned abortions, or delivery)), and after pregnancy (12 months after the end of pregnancy).
Statistical analyses Characteristics of pregnant women are presented as proportions for categorical variables and means with standard deviations (SD) for continuous variables. Prevalences of exposure to prescribed medications are presented as proportions of pregnancies exposed for all prescribed medications combined and by class for each time-window interval. Prevalences of prescribed medications are compared between intervals using generalized equations models (GEE). Prevalences of pregnancy outcomes are also presented as proportions. All analyses were conducted using the SAS System V9. 4 (SAS Institute Inc. , North Carolina, USA). Table  1  describes the characteristics of pregnancies included in the FPC. Overall, the FPC includes data on equal numbers of pregnancies by calendar year of the cohort (approximately 25% in each of the 4 calendar years studied).
Maternal depression was the most frequent maternal comorbidity (20%); post-partum depression was present in 12. 0%-38. 8% of women depending on whether they had a spontaneous or induced/planned abortion, stillborn or liveborn. FPC's maternal characteristics were comparable to the overall French population of pregnant women. Indeed, using the 2016 National French perinatal survey [20], we were able to determine that our prevalence of singleton livebirths was comparable to the national estimate (98% in FPC vs. 98. 2% in the national survey); stillbirths occurred in 0. 7% of pregnancies in FPC versus 0. 6% of pregnancies in the survey; the majority of pregnant women was between 20-35 years of age (76. 2% in FPC, 76. 6% in the survey, and 77. 5% in the overall PMSI database); prematurity was 6.
Using the overall duration of gestation to calculate medication exposure prevalence, the FPC is comparable to the Quebec Pregnancy Cohort, which reports 26. 5% prevalence of use for antibiotics  [29]. The FPC has a higher prevalence of antidepressant use compared to elsewhere in the world (8. 7% in FPC vs. 4. 9% in the QPC)  [3, 30] , and other French studies  [31, 32]. The variation between study estimates could partly be explained by, as mentioned above, the differences in definitions of measurement of medication exposure during pregnancy between the different databases. Finally, 12. 0-38. 8% of pregnant women in the FPC had post-partum depression disorders diagnosed in the year following the end of pregnancy. Post-partum depression was highest for those who delivered a stillborn infant (38.
8%), and lowest in those who delivered a liveborn (12. 0%). This is comparable to studies which reported rates of postnatal depression disorders of 10. 4% at 6-months postpartum in deliveries with liverborns  [33]. The FPC gives the opportunity to assess post-partum depression among all pregnant women regardless of pregnancy outcome, which is important given the varying prevalence among groups. Although there has been an increase in the assembly of cohorts of pregnant women over the past years, the FPC offers an interesting range of variables, and is one of a few that focuses on maternal health in addition of giving valid gestational age, which is essential in perinatal pharmacoepidemiologic studies. The FPC is a representative sample of French pregnant women followed within the universal health care system in France, built with data from the French administrative database (EGB), which includes information from routine billing data and hospital database (PMSI), and includes physician-based prospective diagnoses and procedure codes, data on prescription fillings including date of filling, duration of prescription and dosage, and has data on maternal comorbidities during pregnancy, and pregnancy outcomes.