dataesr/scientific-paragraphs-categorization huggingface dataset:
After 5 years of spin-up with climatological surface and lateral boundary forcing, the model is forced with the Drakkar Forcing Set version no. 4. 4 (DFS4. 4; Brodeau et al. , 2009)  from 1958 to 2012. This forcing is a modified version of the CORE dataset  (Large and Yeager, 2004) , with atmospheric parameters derived from ERA40 reanalysis until 2002  (Uppala et al. , 2005)  and ECMWF analysis after 2002 for latent and sensible heat flux computation. Radiative fluxes are taken from the corrected International Satellite Cloud Climatology Project-Flux Dataset (ISCCP-FD) surface radiations  (Zhang et al. , 2004) , while precipitation is specified from a blend of satellite products described in  Large and Yeager (2004). All atmospheric fields are corrected to avoid temporal discontinuities and to remove known biases (see  Brodeau et al.
Physical control of the interannual oxygen variability off the WCI The gaps in the CaTS observational dataset do not allow constructing a reliable time series of interannual upper-ocean oxygen content, to which our model could be validated. However, the data can still provide some estimate of the amplitude of interannual variability, which can be compared to that of our model (the whiskers in Fig. 7b  and c  indicate the amplitude of the variability around the mean seasonal cycle). Despite a slight underestimation in our model, the amplitude of the near-surface oxygen interannual variability is largest during SON, both in the shelf observations and the model. This further corroborates the offshore-shelf connection discussed above. A seasonally shallow OCD combined with a larger interannual variability in fall creates a window of opportunity for the occurrence of coastal anoxic events.
We previously demonstrated a tight relationship between the seasonal variability of OCD and TCD in the eastern Arabian Sea. Figure  8a  exhibits a similar relation in large portions of the northern Indian Ocean for fall interannual OCD and TCD anomalies in the model. A comparison with observations is unfortunately not feasible due to lack of a basin-scale dataset for interannual OCD anomalies. The cor- relation between interannual OCD and TCD anomalies are, in general, slightly weaker than that on seasonal timescales (Fig. 5b ) but remain high in a large part of the Indian Ocean north of 5 • N, generally exceeding 0. 8 in the entire Bay of Bengal and in the eastern Arabian Sea and in particular in the WCI box (∼ 0. 95 correlation, Fig. 8b ). The influence of remote forcing at WCI is further established in Fig.
, 2006; Gutierrez et al. , 2008). As was shown in Figs. 6 and 7b, the model and WOA climatology vertical oxygen distributions agree quite well, both in terms of the oxycline depth and near-surface value. The CaTS data, on the other hand, is representative of what happens much closer to the coast and displays much lower oxygen levels than seen further offshore in WOA and the model. This may of course partially be due to shortcomings in representing physical exchanges between the shelf and open ocean at the current resolution of our model and existing oxygen dataset in the region. But biological processes are also known to be a prominent oxygen consumption factor on the shelf, in particular in the benthic zone where the enhanced concentration of particulate matter above sediments is associated with a high oxygen demand (e.
Acknowledgements. This work is a part of a CSIR-funded  INDIAS IDEA  project. I. Suresh  acknowledges financial support from the  Council of Scientific and Industrial Research, New Delhi , and  INCOIS/MoES  ( HOOFS program ). V. Parvathi is funded by  CSIR  under a  Senior Research Fellowship. We thank the  CSIR-NIO data center and Chemical Oceanography Division  for making the archived cruise and CaTS data available for the present study. We thank the  NEMO-PISCES  modeling team. The simulations were performed on HPC Pravah at  CSIR-NIO. We thank  M. Afroosa  for assistance in data processing. M. Lengaigne ,  C. Ethé ,  J. Vialard , and  M. Levy  benefited from  Institut de Recherche pour le Développement (IRD)  funding for their visits to the  CSIR-NIO. This is NIO contribution number  6008.
Data availability. The (CaTS) data archived at the CSIR-NIO data center and Chemical Oceanography Division have been used in Figs. 1  and 7. These datasets are not publicly available. Hence we do not provide the data or any access link. All other datasets are publicly available: WOA13https://www. nodc. noaa. gov/OC5/woa13/woa13data. html (NOAA,  2015); SLA -http://www. aviso. altimetry. fr/en/data/products/ sea-surface-height-products/global. html (AVISO, 2014); OC-CCI -https://www. oceancolour. org/ (Plymouth Marine Laboratory -PML, 2014); NEMO model source codes are downloadable after registering at http://www. nemo-ocean. eu/About-NEMO. Competing interests. The authors declare that they have no conflict of interest.
One-way ANOVA with Bonferroni's multiple comparisons. Jejunal explants were exposed i) with complete medium (control), ii) with 10 9 CFU/mL L. rhamnosus in complete medium, iii) pre-treated with complete medium 1 h and then exposed to 10 µM DON in complete medium or iv) pre-incubated 1 h with 10 9 CFU/mL L. rhamnosus and then exposed to 10 µM DON in complete medium. After 3 h of incubation, gene expression was assessed. Relative expression of mRNA encoding for pro-inflammatory cytokines and chemokines was measured by RT-qPCR. Data are normalized to housekeeping gene RPL32 and expressed, in arbitrary unit, as mean and SEM of explants from 6 animals. One-way ANOVA with Bonferroni's multiple comparisons.
Imposition of mandatory screening programmes and open registries of test results as a prerequisite for kennel club registration could result in breeders choosing to breed non-registered dogs instead. However, lack of adherence to programmes and incomplete data pose significant barriers to achieving health improvement. This underlined the importance of education and communication between the different stakeholders (including breeders, owners, veterinarians, geneticists and judges) in the design and implementation of effective health strategies. The group discussed their diversity of experiences across countries in relation to breed-specific health strategies and access to their local resources and tools that could be shared more widely. The use of the DogWell Net. com platform website as a repository for such resources was recommended.
In response to, and building on discussions at the 1st IDHW and 2nd IDHW, the IPFD is overseeing the development of an online resource of relevant information from GTPs describing quality measures (QMs) for DNA testing. Further development into 2018 will include platforms for expert reviews of tests; coordinating a proficiency testing scheme, and genetic advice and education. The model depends on GTPs and multi-stakeholders participating voluntarily. An open-access prototype was developed using data provided by GTPs indicating a spectrum of initial QMs, from international accreditations to customer care. This centralized resource aims to aid kennel/breed clubs, breeding advisors and owners to make better informed decisions on GTPs and testing. The 34 theme participants included representatives from GTPs, geneticists and researchers, kennel clubs/ registration bodies, and owners/breeders.
These four main data areas were also echoed from each of the other themes. Some additional numbersbased comments from the other themes included the value of longitudinal evaluation of breed health to assess the impact of programs and that data collection efforts (e. g. breed club health surveys, antibiotic use and AMR, behavioral assessments) need to be enhanced and coordinated. Additional actions to facilitate progress on all identified needs included publishing data results, for example in CGE; creating a meeting place for people who have data or questions regarding data on DogWellNet. com; and exploring funding for knowledge sharing and working together on an international level.
These reflected the goals of identifying priorities, gaps and actions, as well as building on international communication and collaboration. In many cases, firm plans were drawn up during the meeting to meet these actions. Working groups with specific tasks were identified and many plan to communicate through forum communities on DogWellNet. com. Each of these outcomes are hugely welcome for their own direct value but also because they are strong evidence of the willingness of the various stakeholders to share data and resources and to work as teams for the greater benefit of canine health. The greatest challenge will be to continue the positive momentum generated by the meeting into sustained action. At the time of publication, several groups from the conference remain very active. Another exciting development post-workshop was an IPFD veterinary student project which has assembled resources on the AMR topic (https://dogwellnet.
Patient cohorts The SPACE cohort is a prospective study which includes patients with short-term CBP (≥3 months, ≤2 years, and an onset <45 years) at a minimum age of 16 years from five Rheumatology outpatient clinics in the Netherlands, Norway, and Italy. DESIR is a prospective longitudinal cohort running in 25 centers in France (clinicaltrials. gov, NCT01648907). Patients between the ages of 18 and 50 years with inflammatory back pain (IBP) according to the Calin  [14]  or Berlin  [15]  criteria, persisting ≥3 months but <3 years, were included. In addition, the treating rheumatologist had to have a substantial suspicion of axSpA (level of confidence ≥5 on a 0-10 rating scale, where 0 = not confident and 10 = very confident). A detailed description of both cohorts is provided elsewhere  [16, 17].
Clinical data collection All patients underwent a diagnostic work-up according to a fixed protocol which includes physical examination, laboratory assessments (HLA-B27, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR)), and magnetic resonance imaging (MRI) as well as radiographs of sacroiliac joints. The presence and history of clinical SpA features were assessed: IBP, good response to nonsteroidal anti-inflammatory drugs (NSAIDs), peripheral arthritis, dactylitis, enthesitis, AAU, IBD, and psoriasis. Patients were asked about the presence of any of the following SpA diseases in first-or seconddegree relatives: AS, AAU, ReA, IBD, and psoriasis. For each SpA disease the possible answers were "yes", "no" or "unknown/uncertain". A PFH was defined as the presence of ≥1 SpA-related disease in first-(mother, father, sister, brother, daughter, son) or second-degree relatives (aunt, uncle, niece, nephew, grandmother, and grandfather) reported by the patient  [8].
Acknowledgements The DESIR cohort was sponsored by the  Département de la Recherche Clinique et du Développement de l'Assistance Publique-Hôpitaux de Paris. This study is conducted under the umbrella of the  French Society of Rheumatology  and  INSERM  ( Institut National de la Santé et de la Recherche Médicale ). The database management is performed within the  Department of Epidemiology and Biostatistics  ( Professor Paul Landais ,  D. I. M. ,  Nîmes, France). An unrestricted grant from  Pfizer  was allocated for the 10 years of the follow-up of the recruited patients. The authors thank the different regional participating centers: Pr. M. Dougados (Paris, Cochin B), Pr. A. Kahan (Paris, Cochin A), Pr. O. Meyer, Pr. P. Dieudé (Paris, Bichat), Pr. P. Bourgeois, Pr. L. Gossec (Paris, La Pitié Salpetrière), Pr.
French insurance is part of a public-private partnership with the French State to compensate flood-related damages, and there is growing concern among insurers about damaging climatic events. To promote preventive actions as well as to take them into account in flood risk assessment, insurers have recently expressed the need to develop a rating system of preventive actions. This study identified Action Programs for Flood Prevention (Programme d'Action pour la Prevention des Inondations-PAPI) as the key French public policy instrument: they provide an overview of the diversity of actions that are conducted locally at the relevant risk basin scale. A database of all intended actions in the 145 launched PAPIs was constructed and the actions were coded (88 codes). The analysis consisted of two steps: (1) We conducted an expert valuation using the Analytic Network Process and the Analytic Hierarchy Process, aiming at creating an experimental national rating system.
Construction of a PAPI Action Database A database gathering the actions that will be or have been implemented in PAPIs was constructed based on the analysis of the 145 PAPI application forms. To be able to compare actions from one PAPI to another, a coding method was used: from a sample of PAPIs and existing recognized types of actions (subsidized actions, research work, and so on), 88 codes were determined to represent the diversity of actions within each PAPI (Guillier 2016a) (Table  1 ). For instances, hydraulic modeling (for example, flow velocity) and hydrologic modeling (for example, mapping the consequences of extreme events) are coded as ''Hazard knowledge. '' Each code mainly corresponds to one axis within PAPI's structure in seven axes. 6 he identification of 88 codes, representing the diversity of actions that a risk basin may mobilize, offers the opportunity, through the assessment of their effectiveness, to identify and emphasize the most interesting actions.
There is therefore a need for methods to accurately measure the heterogeneity of a tumour from a single sample. Quantification of ITH is a proxy for the evolvability of a tumour. A more diverse tumour is more likely to contain cells that are pre-adapted to a new selective pressure (e. g. chemotherapy). Indeed, recent studies designed different ways to measure ITH and reported it was positively associated with poorer survival. Mengelbier et al. used the presence of subclonal alterations from SNP array data in paediatric cancer 19 , while other groups inferred ITH from paired sequencing and SNP-array data in pan-cancer analyses  20,  21. Mroz et al. developed a statistic.
Here we derived two methods to quantify ITH from individual SNP-array cancer samples and assessed their accuracy and usefulness. We first used publicly available data to generate synthetic copy number profiles, and used these profiles to generate in silico mixtures of related (sub)clones upon which we assess the performance of the ITH measures and also their sensitivity to variations in cellularity. We next created in vitro mixtures of clonally derived cell lines to further assess the performance of the ITH scores on real SNP-array data. We finally compared our scores to an existing method before investigating their prognostic potential in vivo in over 5,000 clinical samples across 16 cancer types.
Their formulas are given in (  2 ) and (3). ∑ λ = × - ≤ × ≠ K r n n I d r ( ) ( 1) ( ) e (2) i j ij ij π = L r K r ( ) ( ) ( 3 ) where λ is the area of the window, n the number of points, d ij is the euclidean distance between points i and j and e ij is the isotropic edge correction weight. The sum is taken over all ordered pairs of points i and j and I(d ij < = r) is an indicator that equals 1 if d ij is less than or equal to r. We used the spatstat R package  26  to calculate the difference between the reported L(r) values and the theoretical expected values for all radiuses from 0 to a maximum radius r max in 0. 001 increments. R, the sum of all the differences, was taken as the diversity index. Note that spatial homogeneity is expected when points are located at random on the plane, a lower R value is therefore expected as genetic diversity increases.
1 ). We first generated in silico datasets from publicly available SNP array data on 16 sets from The Cancer Genome Atlas (TCGA) corresponding to different cancer types. We generated 10 "clonal" CN profiles per set, taking into account the distributions of ploidy and percentage of altered genome in each set. An additional 4 "subclonal" profiles were derived from each clonal profile based on an expected divergence of 15% ± 5% of the genome (see Methods). The median percentage of genome altered of the synthetic mixtures and TCGA data were correlated on a per-cancer type basis (R 2 = 0. 90, p < 0. 001, Fig. 2a, b ), indicating that we had generated set of synthetic profiles resembling publicly available cancer data. A total of 707,200 mixtures were generated in-silico using different combinations of clonal and subclonal profiles at 4 different levels of cellularity (percentage of tumour cells in a sample): 20%, 40%, 60% and 80%.
Indeed, the fit of all points rather than of the medians were poor although the (anti-)correlation was highly significant (R 2 = 0. 01, p < 2e -16 in both cases). Notably the R score displayed a more pronounced slope with lesser variability than the S score. Within the in-silico mixtures, the percentage of genome altered (see Methods) was highly correlated to the S score and anti-correlated to the R score (p < 0. 001, Supplementary Figure  2 ). However, the median percentage of genome altered was not correlated to the true Shannon diversity of the in-silico mixtures (R 2 = 0. 21, p = 0. 07, Supplementary Figure  3 ). Our synthetic dataset analysis therefore suggests that the overall level of genetic alterations present in the genome is an inadequate way of assessing the clonal diversity of a tumour from a single SNP array sample.
51). We however note that this dataset assumed perfect detection of CNAs rounded to the closest integer, while this could in practice affect genotype prediction. In-vitro cellular evolution and isogenic clonal mixtures. Two rounds of single cell cloning were used to generate twelve isogenic cell lines from the chromosomally unstable SW620 colorectal cancer cell line (Fig. 4a , see Methods). We analysed the proliferation rate of the 12 isogenic cell populations, and found they exhibited different growth patterns. We selected 4 clones (designated A, B, C and D), because of their apparent different growth dynamics (Fig. 4b ). DNA was extracted from each clone, and we created 12 mixtures consisting of DNA from 2 to 4 of these cell populations at different proportions. We calculated the expected diversity of each mixture ("true diversity"), using the Shannon diversity index based on the frequency of each population (Supplementary Table  2 ).
Calibration of diversity scores to in-silico and in-vitro data. Both scores rely on a tunable parameter: the number of bins for the S score and the maximum radius size for the R score. We therefore used our in-silico and in-vitro data to define the most appropriate parameters for use on real data. We selected 10 possible values for the number of bins (6 to 24) in the S score, and 7 for the maximum radius (0. 025 to 0. 25) in the R score, then analysed the correlation between the obtained scores and the true diversity in the in-silico and in-vitro datasets (Supplementary Figures  8  and 9 ). We furthermore analysed their power to discriminate between monoclonal and polyclonal samples using AUC calculations. The synthetic data suggested that increasing the number of bins by increments of 2 from 6 to 24 bins would yield S scores more correlated and more predictive with each increment.
Association with survival in available clinical datasets. We calculated the S score on 5,078 samples with survival data from the TCGA dataset, and investigated its relationship with clinical outcome. We used univariate Cox proportional hazard models to test the relationship in both overall and relapse-free survival data (Supplementary Tables  3  and 4 , Fig. 5a, b ). In univariate Cox regression, S was significantly associated with survival in multiple cancers, though the only association that held to multiple testing was the one between higher diversity and poorer survival (OS and RFS) in head and neck cancers, for both scores (p < 0. 05). Furthermore, repeating the analysis including either S or R and clinical stage (as a categorical variable) in multivariate models indicated that both measures were still significant covariates after correction for stage in head & neck cancers, but not in other tumour types.
However, S and R were respectively correlated and anti-correlated with stage across tumours (p < 2e -16 , independence test; Fig. 5c, d , Supplementary Figures  10  and 11 ), particularly in bladder, breast, colon, head & neck and kidney clear cell cancers. We further investigated a pan-cancer meta-dataset by pooling all samples together and found that S was significantly associated with poor relapse-free survival in this dataset (p = 0. 001) but not with overall survival, while R showed no association. Both scores were also highly correlated with the percentage of genome altered in all tumours (R² = 0. 48, p < 2e -16 ; Supplementary Figure  12 ), and a survival analysis using the percentage of genome altered yielded comparable results, with significance in multiple cancer types (Supplementary Table  5 ).
Comparison to EXPANDS' number of clones. To our knowledge, no other method or algorithm has been designed to estimate diversity using only individual SNP array data. However, the EXPANDS software uses single nucleotide allele frequencies from sequencing data in combination with SNP array data to predict the number of clones in a sample  27. Using TCGA data from 9 tumour types samples where EXPANDS estimated more than 2 clones were present had poorer survival than samples with 2 or fewer large clones  20. We compared our scores to the EXPANDS number of clones and found that the S and R scores were significantly correlated and anti-correlated, respectively (p < 0. 001, Fig. 6 ) but R 2 values were low (0. 08 and 0. 09), indicating high variability. The extra information added by mutation calls from sequencing data, which can more accurately measure clonal frequencies, could however explain the low R 2 values.
Discussion Intra-tumour genetic diversity is a major hurdle to cancer prognostication and therapy and there is no 'gold standard' for its quantification, particularly from routine clinical samples. Although the use of multiple samples provides important insight into the clonal architecture of tumours  28  , in practice multiple samples are rarely collected routinely apply because of the inherent difficulties associated with sampling more of the cancer and the prohibitive increased costs of multi-sample assays. SNP-arrays have been widely used in cancer genetic studies to unravel the genomic landscape of multiple tumour types, however typically only one SNP-array is analysed per tumour. Here we developed two novel metrics to quantify genetic diversity in SNP-array data from single samples and evaluated their performance using in-silico and in-vitro data, and assessed their prognostic value on publicly available data.
This sensitivity issues potentially explains why EXPANDS software, that integrates CN and sequencing data, measures much more variability in clonal composition than the SNP-array only methods we present here. In addition, copy number alterations have recently been linked to clonal expansions during punctuated cancer evolution  30, 31  , which could imply they would be less frequently subclonal in small tumour regions than sequence levels variations that accrue continuously  32. Finally, the ability to detect subclonal alterations in our method was inevitably correlated to the total number of alterations in a sample -subclones cannot be detected unless they bear unique CNAs. This is a confounding issue, and future improvements of copy-number-based ITH quantification should thus aim at reliably teasing apart low diversity and high CNA load samples from those with high diversity and low CNA load -though this may prove intractable.