dataesr/scientific-paragraphs-categorization huggingface dataset:
We also drawn a "parallel cohort" from a sample of non-participants for whom we will prospectively collect data on social and demographic characteristics (sex, age, work status, social category), through the CNAV database, as well as information about health and health-care utilization from two other national databases covering the whole French population: the Système d'information de l'assurance maladie (SNIIR-AM), the National Health Insurance Information System  [32]  and the National Death Registry managed by the Centre d'épidémiologie des causes de décès (CepiDc)  [33]. As we have data from the SNIIR-AM, CNAV and National Death Registry files.
THE CONSTANCES COHORT for both the participants and the sample of non-participants, we are able to estimate the probabilities of participation in CONSTANCES using logistic regression models and to compute weights for correcting unit nonresponse, and to estimate adjusted prevalences of questionnaire variables. As in epidemiological surveys health and social data are usually not available for non-respondents, this approach has rarely been used to correct the prevalence estimates for nonresponse bias, with few exceptions  [29]. We can assume that almost none of the people included in CONSTANCES will be permanently lost to follow-up, since the participants will be followed "passively" (so-called because this follow-up will not require the subjects' participation) through the SNIIR-AM, CNAV and National Death Registry files.
There will nonetheless be attrition due to the failure to return the annual questionnaire. Thus, adjustment for attrition is necessary if the analyses from the questionnaires variables are to be valid. Inclusion in CONSTANCES will take place over a 5-year period (see below). For wave 1, we will distinguish the participants who returned the self-administered questionnaire in year 2, that is, the year following their inclusion (which is year 1), from those who did not. We will have the data collected at inclusion in CONSTANCES (year 1) for all participants as well as the SNIIR-AM and CNAV data corresponding to year 1 or to year 0 (the year before inclusion). The coefficients of adjustment for attrition in year 2 can thus be calculated by a method similar to the one used to calculate the coefficient of adjustment for non-participation.
For the following years, we will again distinguish the participants who returned the self-administered questionnaire from those who did not. Thus, the longitudinal follow-up of participants in the SNIIR-AM and CNAV databases, whether or not they drop out of the cohort by not returning the annual questionnaire, will make it possible to update the coefficients of adjustment for attritioFor descriptive purposes, each year we will adjust the cohort data on the reference population. The first year, a sample of CNAMTS members in the CONSTANCES districts aged 18 to 69 years was randomly drawn from the CNAV files. The second year, and respectively the third, fourth and fifth years, this sample of randomly drawn individuals will include people aged 18 to 70 years, then 18 to 71 years, 18 to 72 years and 18 to 73 years.
Procedures for longitudinal follow-up An annual self-administered questionnaire will be completed by the subjects at home, using either a paper questionnaire or internet. Post office procedures make it possible to obtain regular updates of participants' postal addresses. Maximizing their personal participation rate is essential. Accordingly, regular contact with participants includes a CONSTANCES Cohort Journal, which will e 8 9 2 1 -6 present results, nested projects, etc. , and will be sent regularly to participants. A website was also created ( www. constances. fr). The subjects included in CONSTANCES are also followed up passively for social and work-related events and health data by regular linkage with the national databases. The CNAV databases are essential for access to social and work-related data  [30].
This agency's role is to ensure the rights to pension payments after retirement for every individual in France who had health insurance from CNAMTS at least once during his or her life. It has therefore set up a system that allows it to collect social data from different organisms and schemes that manage various forms of insurance and other social protection. The CNAV regularly receives for its databases employers' annual reports, and information about periods of employment and unemployment from social welfare organizations (e. g. , sick leave, maternity leave, unemployment, and diverse social benefits). Access to the SNIIR-AM  [32] , which covers the entire French population, is an efficient method of obtaining information about health events. The SNIIR-AM contains individual medical data from different sources, structured and coded in a standardized manner: reimbursement data (doctors and other health professionals visits, prescribed drugs, medical devices); so-called "long-term diseases" (serious chronic diseases exempt from co-payments and user fees, coded according to the International Classification of Diseases 10 th revision -ICD 10  [34] ); hospital discharge records, including principal and associated diagnoses for each hospitalization, also coded according to ICD 10.
Principal data to be collected from different sources Here we summarize the main data to be collected from different sources (selfquestionnaires, medical examination, national health and social databases), at each stage of the study; the detailed list of data can be downloaded from CONSTANCES' website  [35]. When possible, we selected variables already used in other surveys, both because they are validated measures and because it will thus be possible to have reference data for some analyses. Whenever it was possible and pertinent, we used scales already published in the literature, for which the psychometric properties are already established. Social and demographic characteristics: social position, educational and income level, employment and marital status, household composition, socioeconomic status of parents and spouse, and material living conditions (type of housing, household income, etc.
Periodicity of follow-up The periodicity of follow-up varies according to the sources. A mail questionnaire will be sent annually, thus allowing close follow-up, by collecting numerous data without asking subjects for too much work each year. At the same time, it will facilitate rapid response for setting up new studies and establish a sense of loyalty in the participants; too long a delay between two questionnaires is a factor that promotes dropping out  [22] ). Some data will be collected annually (health status and reported morbidity, life events and characteristics of place of residence, smoking, alcohol, etc. ), while others will be collected at longer intervals, according to a planned calendar (health scales and questionnaires for a specific health area or specific risk factors). Self-administered questionnaires will be staggered over the year to take seasonal variations into account, since they are important for some topics (in particular, morbidity, drug use, and working conditions).
Pilot A field pilot took place in seven of the participating HSCs from May 2009 to May 2010 for a four-to five-month period in each center. About 3 500 subjects were included (women and men in almost equal numbers). The preliminary analysis of the data showed that this sample was close to the general population of adults in France regarding sex, age and socioeconomic status. There was quite a diverse distribution of occupations and working conditions, lifestyle factors. The prevalence rates of various diseases and symptoms were close to those from other available French surveys (Figure  2 ). Regarding cognitive and physical functioning, there was also a very good variability in the tests results, in spite of the  THE CONSTANCES COHORT relatively young age of this sample (Figure  3 ). Finally, the field pilot showed that the procedures for invitation of selected subjects, for data collection and medical examination were quite satisfactory, and that only some marginal adaptations of the protocol were necessary; these are currently being implemented.
More detailed results of the field pilot can be found on the CONSTANCES website  [35]. We also verified that the use of auxiliary data from national databases on both respondents and non-respondents for correcting unit nonresponse and to estimate adjusted prevalences of questionnaire variables was efficient. As shown in Table  2 , reweighting techniques proved to meaningfully improve the estimates of prevalences in the population of different conditions related to health and behaviors, showing that adjusting only on "classical" parameters (age, sex and socioeconomic status) as it is usually done in health surveys, is not sufficient if not completely misleading.
legal requirements According to the French regulations, the CONSTANCES Cohort project has obtained the authorization of the National Data Protection Authority (Commission nationale de l'informatique et des libertés-CNIL). CNIL verified that before inclusion, clear information is provided to the eligible subjects (presentation of CONSTANCES, type of data to be collected, ability to refuse to participate, informed consent, etc. ). Concrete procedures for setting up the two cohorts (participants and non-participants) ensure the confidentiality of the data at every point in its circulation as well as the anonymity of the cohort of non-participants. In addition, CONSTANCES was approved by the National Council for Statistical Information (Conseil national de l'information statistique-CNIS), the National Medical Council (Conseil national de l'Ordre des médecins-CNOM), the Institutional Review Board of the National Institute for Medical Research-INSERM and.
concluSionS Considering its large size, the extensive coverage of the French adult population, the wealth of data collected from different sources, and its openness to the scientific community, the CONSTANCES Cohort should constitute a powerful tool for public health information and epidemiologic research in many different fields. The inclusion of cohort participants started in 2012 and it is planned to have the full 200 000 subjects cohort completed by the end of 2017. CONSTANCES has several strengths. It was designed both to provide public health information needed by the health authorities and to help answer research questions in diverse areas; to facilitate this goal, we devised a specific sampling scheme (including a nonparticipants cohort) and developed complex statistical procedures in order to take into account selection effects at inception as well as during the follow-up of the cohort.
CONSTANCES will be a large cohort, including persons living and working in diverse settings, from large cities to small villages in different regions of France, with a broad range of socioeconomic status and trades. Numerous data will be collected at inception, including an extensive medical, physiological and biological examination, and a large biobank will be set up. The follow-up will be very extensive, relying both on active participation of the volunteers through annual questionnaires and regular visits to the HSCs, and on passive methods through the regular linkage to health and socioeconomic national exhaustive databases. Of particular importance is the high frequency of measurements from many different sources, allowing for analyses of life course trajectories of health in relation to personal, social, occupational factors and major life events.
Specific efforts were put into the quality of data collection and the validation of main outcomes in order to provide a highly phenotyped cohort. A unique feature of CONSTANCES is also to include a comprehensive set of cognitive and physical tests starting as young as 45 years, which is earlier in the life course than most available studies on ageing. The CONSTANCES has also some limitations. Due to the voluntary participation of cohort members, there will probably be an underrepresentation of hard-to-reach subjects, such as heavy drinkers or socially excluded persons. Comparisons between participants and non-participants at inclusion and during the follow-up through the "non-participants cohort" should allow assessment of potential biases due to selection effects, but lack of sufficient numbers in some categories might be a problem.
Even more importantly,  THE CONSTANCES COHORT CONSTANCES will not offer sufficient power to study rare outcomes or exposures despite its large size. Simulations under several hypotheses regarding the prevalence of exposure and expected relative risk and duration of followup since inception, showed that in most of the situations where the relative risk is below 2, especially when interactions have to be taken into account, power will be satisfactory after at least 5 years of follow-up for situations where the incidence of the outcome is over 10/100,000 and the prevalence of exposure over 10% (data not shown). This limit is common to all longitudinal cohorts, and we are currently working with colleagues from other countries on a consortium for networking of prospective studies in Europe where several large-scale prospective cohorts already exist, or are currently under construction.
Competing interests: none. aCknowledgements: the Authors want to express their thanks to the Constances team and to all the many project partners. Quality control procedures are taken in charge by ClinSearch for the data collected in the HSCs, and by Asqualab and EuroCell for the biological data. We also gratefully acknowledge the major contribution to the protocol of numerous colleagues, in France and abroad, who helped in the general design of the cohort, and of the participating HSCs. The authors express also their thanks to Dominique Polton, Yvon Merlière, Laurent Duchet and Alain Weill from the CNAMTS for their help regarding the CNAMTS database, and to Christophe Albert and Joël Brulard for the drawing of eligible persons and the access to the CNAV database. support: the CONSTANCES Cohort is supported by the Caisse Nationale d'Assurance Maladie des travailleurs salariés-CNAMTS, and was funded in its pilot phase by the Institut de Recherche en Santé Publique / Institut Thématique Santé Publique, and the following sponsors : Ministère de la santé et des sports, Ministère délégué à la recherche, Institut national de la santé et de la recherche médicale, Institut national du cancer et Caisse nationale de solidarité pour l'autonomie.
Our results showed that deposition of callose was significantly reduced in Atcoilin-1 when compared with WT plants after 24 h flg22 treatment (Figure  2 , C and D). Since PTI is associated with transcriptional reprogramming, we investigated the role of AtCOILIN in PAMPtriggered transcriptional response by RT-qPCR analysis. Under normal conditions, the basal transcript levels of WRKY29 and FLS2 in Atcoilin-1 were significantly lower and Pst DC3000 hrcC -treatment did not induce the expression of these defense marker genes compared to WT plants (Figure  2E ). Taken together, these data suggest that AtCOILIN positively regulates defense-related responses. Four-week-old plants were spray-inoculated with bacterial suspensions of optical density (OD) 600 = 0. 2. Bacterial titers were determined 3 and 72 hpi.
B, ROS burst response in Col-0 and coilin-1 mutant after treatment with 1-lM flg22. ROS production was quantified for 40 min using a luminescence microplate reader. The experiments were repeated at least 3 times with similar results. C and D, Flg22-induced callose deposition in 14-day-old WT and coilin-1 seedlings. After treating the seedlings with 1-lM flg22 for 24 h, seedlings were stained with aniline blue and examined with UV fluorescence microscope. The callose deposits were quantified with ImageJ. E, Relative transcript levels of PTI-related genes in response to Pst DC3000 hrcC -in 14-day-old WT and coilin-1 plants. Transcript levels of candidate genes determined by RT-qPCR were normalized to the levels of ACTIN and UBQ10 relative to the WT (set as 1). In all experiments, three biological replicates are carried out and each biological replicate is composed of three technical repeats.
5% (164 genes) were downregulated (Figure  3A ). AS events between WT and Atcoilin-1 were identified using the program rMATS, version 3. 2. 5  (Shen et al. , 2012; Park et al. , 2013; Shen et al. , 2014). Five different splicing event types were identified using this tool. We used a cutoff parameter of -c 0. 0001 and events that have FDR 4 0. 05 (or 5%) were filtered out. After comparing all the confident junctions to the annotated genes, we identified all significant AS events: these comprised 1,791 alternative 3'-splice sites (A3SSs), 786 alternative 5 0 -splice sites (A5SSs), 361 skipped exons (SE), 14 mutually exclusive (MXE), and 3,467 intron retention (IR) events in Atcoilin-1 (Figure  3B ). IR events were the most predominant AS events. This is consistent with the observation that IR events constitute the majority of the AS events in Arabidopsis  (Staiger and Brown, 2013).
, 2012)  (Figure  4A ). In addition, cyclin-dependent kinaseactivating kinase (AT4G30820) was also found among the intron retained transcripts (Figure  4A ). Disease-resistance gene (CC-NBS-LRR class) family (AT5G48620) was found among the A3SSs events. Binding partner of ACD11 1-BP1 (AT5G16840) has a role in fungal and ROS-mediated defense responses and was found among the A3SSs events (Figure  4B )  (Li et al. , 2019). Defense protein-like protein (A5G48657) and disease-resistance protein (CC-NBS-LRR class) family (AT5G35450) were found among the alternative 5 0 -SSs events (Figure  4C ). For all the above different AS events, visualization of AS events by the Integrative Genomics Viewer (IGV) program screenshot is shown as well as the validation by RT-qPCR and RT-PCR (Figure  4, A-C ). These results suggest that a subset of transcription factors involved in defense-related genes are regulated post-transcriptionally by AtCOILIN.
Since some long noncoding RNAs (lncRNAs) are known to be involved in plant responses to pathogens  (Sharma et al. , 2022) , we analyzed the transcriptome data to identify lncRNAs that are differentially expressed in Atcoilin mutant plants. From the total of 33,557 assembled unique transcripts, 27,416 protein coding transcripts and 965 small noncoding transcripts (miRNA, rRNA, snoRNA, snRNA, and tRNA) were subjected to filter for transcripts 4200 bp. Remaining 5,221 non-coding transcripts were further checked for their coding potential by Pfam match via HMMER's utility "hmmscan"  (Bateman et al. , 2004 ) and subsequently by CPC2 calculator  (Kang et al. , 2017)  with score 40 as putative non-coding transcripts resulting in a total of 5,173 lncRNAs. Looking at the GO enrichment of the differentially expressed lncRNAs, we found enrichment of terms related to microRNA, hormone metabolism, stress, protein synthesis, nucleotide transport, and secondary metabolism (Supplemental Figure  S3 ;  Sun et al.
Quantitative proteomics of Atcoilin-1 mutant To evaluate the changes at the protein level, we performed data-independent acquisition-mass spectrometry (DIA-MS) analysis of Arabidopsis 14-day-old WT and Atcoilin-1 seedlings. Samples from three independent biological experiments were collected for protein extraction, and DIA-MS analysis was carried out. A total of 6,392 protein groups were quantified out of 15,514 identified (PXD014032) with low number of missing values between replicates using Arabidopsis spectral library generated using Fusion LUMOS MS (Figure  5A ). The number of proteins identified by DIA represents 41. 2% of the Arabidopsis spectral library used for the analysis. The median coefficient of variation for protein quantities within the experiment for all runs was 515%, indicating high reproducibility and high quantitation accuracy (Supplemental Figure  S4 ).
Despite the low similarity in amino acid sequences, a similar type of domain organization is shared by human and animal COILIN proteins and COILIN-like proteins of various plant species  (Makarov et al. , 2013). Human COILIN was shown to be phosphorylated at several residues with maximum levels at mitosis. The Figure  7  Atcoilin mutants have reduced JA levels and increased susceptibility to B. cinerea. A, Quantification of total ABA, SA, and JA was realized by HPLC using samples extracted from 14-day-old Arabidopsis WT and coilin mutant plants. Data are representative from three independent biological replicates. B, Disease symptoms observed in 4-week-old Arabidopsis WT and coilin-1 leaves that were drop-inoculated with 5 Â 10 5 spores mL -1 B. cinerea. coilin-1 shows susceptibility to the fungal pathogen.
The lesion diameter was measured at 48 hpi using ImageJ. In all experiments, three biological replicates are carried out and each biological replicate is composed of three technical repeats. The center line in the box plot refers to the median, the box limits refer to the upper and lower quartiles and the whiskers denote 1. 5 Â interquartile range. Statistical significance was calculated using the Biorad CFX Software and is indicated in the graphs based on t test ( *** P 5 0. 001, ** P 5 0. 01). NS, not significant. phosphorylation of COILIN at S489 impacted RNAse activity suggesting that it could be the key regulator of coilin activity  (Broome et al. , 2013). We recently showed that AtCOILIN was phosphorylated upon perception of the PAMP flg22. Analysis of the phosphorylation status of AtCOILIN in the PhosPhAt database showed that it is phosphorylated at seven residues in several large scale phosphoproteomic analyses as shown in Table  1.
Assuming that there are equal chances of retaining an intron in both samples, a significant P-value indicates that one of the samples has an IR event. We compared our DEGs and DAS with the dataset of  Kanno et al. (2016)  but only observed a very poor overlap between up and down DEGs. While comparing the splicing events, we found 157 common events between the two datasets. These were enriched for GO terms related to defense response, metabolism, response to stress, and photosynthesis (Supplemental Figure  S6 ). In order to see if there was any association between the changes in the transcriptome and proteome of Atcoilin mutant, we compared the downregulated genes with the downregulated proteins and found a very poor overlap. The result with the upregulated genes and proteins was also similar.
Botrytis infection For inoculation of 4-week-old Arabidopsis plants, B. cinerea spores were collected in Vogel buffer as described previously by  Birkenbihl et al. (2012). Then, 5-lL droplet of a spore suspension (5 Â 10 5 spores mL -1 ) was placed on each rosette leaf (three leaves per plant and six to eight plants per genotype). Inoculated plants were covered with transparent plastic lid to maintain high humidity and returned to the growth chamber. After 72 h, inoculated leaves were photographed, and the developed lesions were measured using the ImageJ image analysis software.
Callose deposition Fourteen-day-old Arabidopsis seedlings were grown on 1/2 MS agar plates and then transferred to 1/2 MS liquid medium in 12 wells plate treated with water as mock or 1-lM flg22 as a PAMP (flg22 peptide was synthesized from Genscript Corp) and kept back in growth chamber for 24 h. After 24 h, six seedlings were fixed in (acetic acid: ethanol (1:3) overnight, rehydrated with 50% ethanol for 1 h, 30% ethanol for 1 h, and rinsed twice with sterilized H 2 O, respectively. Finally, cleared seedlings were stained with aniline blue (0. 01% in 150-mM K 2 HPO 4 ) overnight in the dark. Stained leaves were mounted in 50% glycerol and visualized using a UV microscope (Nikon, Tokyo, Japan). Callose deposits were quantified after processing the images with Photoshop and ImageJ software.