dataesr/scientific-paragraphs-categorization huggingface dataset:
In addition, we estimated the interactions between each pair of predictors in the community invasibility model to show the interplay of the mechanisms behind them by using the "gbm. interactions" function in the "dismo" package  70. As BRT accounts for spatial autocorrelation in neither the dependent nor predictor variables, we also ran an autoregressive error (SAR error ) model for the community invasibility patterns and compared these results with those of the BRT, to check if spatial autocorrelation affected the results. We scaled all predictor variables to have zero mean and unit variance to ensure equal weighting in the model. Quadratic terms were included in the SAR error model to consider non-linear responses. We used 'poly2nb' and 'nb2listw' functions in 'spdep' R package to extract the neighbors list based on watersheds with contiguous boundaries and constructed the spatial weights matrix as the spatial constraint in the SAR error model.
The spatial autocorrelation analysis was performed using the 'spatialreg' and 'spdep' R packages  71. We used Nagelkerke's R-squared  72  as the pseudo R-squared to qualify the SAR error model's performance. After model fitting, we checked for broad spatial autocorrelation in model residuals by computing the Moran's I statistic  73. The results of SAR error models are provided in the supplementary material (Table  S4 ). The core drivers identified by the BRT models were confirmed by the SAR error analysis, suggesting spatial autocorrelation did not have an important effect on our results. All statistical analyses were performed with R software version 4. 1  74.
Acknowledgements This work was partially funded by the  Center of Advanced Systems Understanding (CASUS) , which is financed by  Germany's Federal Ministry of Education and Research (BMBF)  and by the  Saxon Ministry for Science, Culture and Tourism (SMWK)  with tax funds on the basis of the budget approved by the  Saxon State Parliament. G. S. is supported by the  National Key R&D Program of China  (Grant no. 2018YFD0900904 ). S. B. is supported by  CEBA  ( ANR-10-LABX-25-01 ) and  TULIP  ( ANR-10-LABX-0041 ) projects.
Data availability All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary information. FISHMORPH is publicly available through figshare (https://doi. org/10. 6084/m9. figshare. 14891412). Fish Traits database for North American freshwater fishes can access through https://www. sciencebase. gov/catalog/ item/5a7c6e8ce4b00f54eb2318c0. Additional data and files related to this paper have been deposited in the Zenodo repository (https://doi. org/10. 5281/zenodo. 7802871)  75.
Data and code availability d Mouse Affymetrix gene array data have been deposited at NCBI GEO depository and are accessible with the accession number GSE164765, or using the link https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE164765. Human Affymetrix data have been deposited at www. ebi. ac. uk/arrayexpress with accession numbers E-MTAB-2246 (IgD + CD27 + , IgD À CD27 + ) and E-MTAB-9620 (IgD + CD27 -). Phospho-proteomics: All raw files, processing outputs and log files as well as R scripts for processing and their respective outputs are available at http://www. proteomexchange. org/with repository identifier PXD031433. d This paper does not report original code. d Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.
Flow cytometry Flow cytometric staining was performed as previously described. 75 For surface staining cells were blocked with anti-CD16/32 (clone 2. 4G2, BD Bioscience) and stained with the indicated combination of fluorochrome-conjugated antibodies for 20 min on ice. For biotinylated antibodies, cells were further incubated with Streptavidin conjugated to fluorochrome for 15 min. Dead cells were excluded by DAPI or PI, and fixable Viability Dyes (eBioscience, Cat. # 65-0865, 65-0863, 65-0866). All cells were acquired on BD FACS Canto II, Fortessa flow cytometers and analyzed with FlowJo software (version 8. 87). For ImageStream analysis, human splenic samples were stained as described above and permeabilized with Fix & Perm reagents (Caltag Laboratories) for FOXO1 staining. Samples were run on an ImageStream X Mk II (Amnis Corp, Luminex) and a 60x magnification was used for all acquisitions.
Data were acquired using the INSPIRE software (Amnis Corp, Luminex) and analyzed using the IDEAS software (version 6. 2 Amnis Corp, Luminex). At least, 30,000 events were collected for each B cell subpopulation in all experiments. Immunization and ELISA To measure T cellT-cell independent  76  immune responses, age-matched AKT BOE and control mice were immunized intraperitoneally (i. p. ) with 10 mg/mouse NP 27 -Ficoll (Biosearch Technologies) or with 10 mg/mouse NP-LPS (LGC Biosearch) in 200 mL sterile PBS. To measure T-cell-dependent response, age-matched mice were immunized with 20 mg alum-precipitated NP 28 -CGG (Biosearch Technologies). Serum was taken from tail vein on day 0 (unimmunized), 7, 14, 21, and 28 after immunization. Antibody titers and NP-specific antibodies were determined by ELISA using NP-specific standards.
ACKNOWLEDGMENTS We thank  J. Kirsch ,  H. Schliemann , the  Regine von Ramin Laboratory (DRFZ) ,  Petra Adams-Quack  and  Elena Zurkowski  ( IMM, Mainz ), and  Michael Dussiot  ( IMAGINE ) for excellent technical help. We thank  E. Six  and  I. Andre(IMAGINE)  for the OP9 and OP9-DLL1 cell lines. We thank  V. Asnafi  and  E. Macintyre  ( INEM ) for REC-1 cells. The N. H. lab was supported by the  Fritz Thyssen Foundation ,  AZ 10. 13. 2. 173  and by the  DFG  grant  HO4440/1-1 ,  HO4440/1-2 , project number  318346496 ,  SFB1292/2 TP20 , and the  Research Center Immunology (FZI). The S. F. lab is supported by  ERC   PREG-LAB 647696 ,  AXA Chair Translational Immunology ,  Agence Nationale de la Recherche  ( ANR-16-CE18-0007-01 ), Chair of  Excellence (UniversiteSorbonne Paris Cite). M. R. is supported by the  DFG  ( SFB1160 ,  B02 ).
F. R. L. was funded by the  Institut National de la Santeet de la Recherche Medicale (Inserm) , the  French government  (managed by  French National Research Agency [Agence Nationale de la Recherche ] through the  Investissements d'avenir program  [ Institut Hospitalo-Universitaire Imagine , grant reference,  ANR-10-IAHU-01 ;  Recherche Hospitalo-Universitaire , grant reference,  ANR-18-RHUS-0010 ]), and other grants from the  Agence National de la Recherche  ( ANR-18-CE17-0001.
guidelines of the Translational Animal Research Center (TARC) of the University of Mainz and approved by the institutional committee on animal experimentation and the government of Rheinland-Pfalz (RLP). All experiments were reviewed and approved by appropriate institutional review committees (LAGeSo Berlin), and were conducted according to French, and German legislations, in compliance with European community council directive 68/609/EEC guidelines. Continued REAGENT or RESOURCE SOURCE IDENTIFIER Deposited data Raw and analyzed human array data This paper E-MTAB-2246, E-MTAB-9620 Raw and analyzed mouse array data This paper GSE164765 Phospho-proteomics data This paper PXD031433 Experimental models: Cell lines Mouse: OP9-hDLL1 cells Six et al. 74 N/A Human: REC-1 cells ATCC CRL-3004 Experimental models: Organisms/strains Mouse: R26-fl-Akt-C PMID: 33140819 N/A Mouse: R26-fl-FoxO1ADA PMID: 22057897 N/A Mouse: CD19-Cre PMID: 7543183 N/A Software and algorithms FLOWJO X 10.
Data sources Outcome data Two AMD phenotypes were used as outcome measures in this study. The first one was early AMD. The GWAS summary statistics for this phenotype were taken from a meta-analysis by  Winkler et al. , 2020. This meta-analysis focussed on populations of European ancestries and used data from the ARIC, AugUR, CHS, GHS, IAMDGC, KORA S4, LIFE-Adult NICOLA, UKBB, and WHI studies (14,034 early AMD cases and 91,214 controls overall). A full description of how these studies classified participants as 'early AMD' can be found in the relevant publication  Winkler et al. , 2020;  briefly, a number of approaches considering drusen size/area and the presence or absence of pigmentary abnormalities were utilised including the 3 Continent Consortium (3CC) severity scale  (Klein et al. , 2014) , the Rotterdam Eye Study classification  (Korb et al.
Exposure data A phenome-wide screen was performed to make causal inferences on the role of a wide range of traits in early and advanced AMD. To achieve this, both published and unpublished GWAS data from the IEU open GWAS database were used; these were accessible via the TwoSampleMR programme in R  (Hemani et al. , 2018). All European GWAS within this database were included with the exception of imaging phenotypes and expression quantitative trait locus related data which were removed. The restriction to European datasets limits the generalisability of the results to other populations but is necessary to produce reliable findings. In the early AMD analysis, studies from the 'ukb' and 'met-d' batches were excluded as data for these studies were entirely from the UK Biobank resource and, as a result, there was extensive population overlap with the early AMD GWAS  (Sudlow et al.
Proxies Where an exposure instrument was not present in the outcome dataset, a suitable proxy was identified  (Hartwig et al. , 2016). In the early AMD analysis, this was achieved by using the TwoSampleMR software with a linkage disequilibrium R 2 value of ≥0. 9  (Purcell et al. , 2007). For the advanced AMD phenotype, data that were not derived from the TwoSampleMR resource were used and therefore the Ensembl server was utilised to identify proxies  (Cunningham et al. , 2022; Hemani et al. , 2018).
This conservative approach was selected as a large number of phenotypes was studied and because we wanted to focus on high confidence signals. Where causal traits for early AMD were identified, the relationship between these traits and advanced AMD was studied. These two AMD classifications are phenotypically distinct but are generally part of the same disease spectrum. When traits failed to replicate as causal factors in the advanced AMD dataset, it could not be inferred that these traits are not truly causal for early AMD. However, significance in both AMD phenotypes provided support for the detected causal links and evidence that a factor plays a role across the disease spectrum.
First, it downweighed fatty acid traits through limiting composite traits for SNV identification to HDL, LDL, and triglycerides. Second, numerous lipid traits with a potential role in AMD were not included in the analysis. For these reasons, we chose to conduct a more comprehensive analysis with a slightly altered approach. The following study design modifications were made compared to the study by  Zuber et al. , 2020:  1. Fatty acids were included as a composite trait (utilising GWAS data for serum fatty acids derived from the Nightingale Health 2020 resource as listed in TwoSampleMR package  [Hemani et al. , 2018] ). 2. All lipid and fatty acid measures included in a GWAS by  Kettunen et al. , 2016  were considered as potential causal traits (n = 102 traits). 3. A more recent AMD GWAS was used  (Winkler et al.
, 2020). 4. In general, multivariable MR (of any sort) cannot produce reliable results where the studied traits are ≥0. 99 correlated with respect to the included instruments. For this reason, where two traits were highly correlated, one was removed at random rather than by manually selecting traits in a manner which risks selection bias. MR-BMA for immune cell and complement phenotypes was additionally performed. In this analysis, instruments were obtained at genome-wide significance (p-value >5E-08) for every included exposure in the model (given that composite traits were not available/applicable). For the immune cell MR-BMA, all immune traits that were studied in a GWAS by  Orrù et al. , 2020  and were present in the TwoSampleMR package were used as exposures. In the complement analysis, all complement traits available in relevant studies by  Sun et al.
The MACE is a conservative estimate of the direct causal effect of an exposure on an outcome averaged across models. It is noted that the primary function of MR-BMA is to highlight the probable causal trait among a number of candidate causal risk factors. Although the MR-BMA findings can be used to interpret the direction of effect, they should not be necessarily viewed as an absolute guide to magnitude  (Zuber et al. , 2020). Software R version 4. 1. 0. TwoSampleMR version 0. 5. 6. RadialMR version 1. 0. MVMR version 0. 3. MR-BMA code was sourced from https://github. com/verena-zuber/demo_AMD  (Zuber, 2021; Zuber et al. , 2020).
Overview Focussing on early AMD, univariable MR analysis was applied to a broad range of traits. Following quality control, significant results were replicated in an advanced AMD dataset and further analyses were conducted using multivariable MR and MR-BMA  (Zuber et al. , 2020). Overall, 4591 traits were eligible for analysis. Among these, 44 were found to be putatively causal for early AMD (Table  1 , Source data 1). Most of these causal traits were serum lipoprotein concentration and compositional measures (n = 29). Other significant traits identified included immune cell phenotypes (n = 5), serum proteins (n = 6), and disease phenotypes (n = 4).
In univariable MR, rheumatoid arthritis was identified to be causally related to AMD as detailed above. Multivariable MR with effector memory CD8+ T cell absolute count as a second exposure *These traits (trait ID group 'met-c' in Source data 1) had 1. 9% sample overlap with the early AMD dataset, a minor degree of overlap which is unlikely to bias results; the remaining causal traits had no sample overlap with early AMD. Table  1  continued variable (utilising a Q-statistic minimisation procedure) demonstrated that the causal effect of rheumatoid arthritis was either mediated by immune cells or underpinned by correlated pleiotropy (rheumatoid arthritis effect size: 0. 03, 95% CI: -0. 007 to 0. 055; effector memory CD8+ T cell absolute count effect size 0. 07, 95% CI: 0. 001 to 0. 19). This finding persists in models assuming both very high (0.
9) and low (0. 1) phenotypic correlation. With respect to the relationship between AMD and psychiatric disease, no reverse causation was identified (p = 0. 31). More specific psychiatric traits which could be analysed were not significantly related to genetic liability to early AMD (Source data 1). An extensive range of psychiatric disorders were also explored in the advanced AMD dataset but no significant relationships were detected met-c-869 -1. 0 -0. 5 0. 0 0. 5 1. 0.
Correlation between betas Figure  1. Plot illustrating the correlations between the beta values for the metabolites considered in our Mendelian randomisation Bayesian model averaging (MR-BMA) analysis for early age-related macular degeneration (AMD). This plot visually represents the correlation matrix between the genetic associations of the exposure variables with respect to their instruments. The traits are labelled according to their 'Trait ID'; further information can be found in the Source data 1. (Source data 1). Due to the broad nature of this trait, and the negative results for all disorders explored, it was not possible to discern the driving signal behind the significant result for psychiatric disease. It appears probable that psychiatric disease is a false-positive result given that it lacks: the supporting evidence of biological plausibility; validation in an advanced AMD dataset; or supportive evidence through significance of other similar traits in the early AMD analysis.
Acknowledgements We acknowledge funding from the  Wellcome Trust  ( 224643/Z/21/Z ;  200990/Z/16/Z ); the  University of Manchester 's  Wellcome Institutional Strategic Support Fund (Wellcome ISSF)  grant ( 204796/Z/16/Z ); the  UK National Institute for Health Research (NIHR) Academic Clinical Fellow and Clinical Lecturer Programmes ;  Retina UK and Fight for Sight  ( GR586 ); the  Australian National Health and Medical Research Council (NHMRC)  ( 1150144 ).
Animals Three male calves affected by congenital skin fragility were observed within a period of 5 years on two commercial farms that are more than 300 km distant from each other and with no obvious link (i. e. no recent history of trade of reproducers between them or with a common herd). Only one of the breeders kept genealogical records, which were extracted from the French national pedigree database. The three affected calves were euthanized by intravenous injection of T61 (MSD France) and subjected to a complete post-mortem examination. Oral mucosa and skin from various regions of the body were sampled for histological examinations. In addition, the tip of one pinna was collected from each animal for DNA extraction. At the time of the study, biological samples for DNA extraction were also available for the three dams of the cases, one of their sire, and one of their unaffected half-brother.
Mapping of the new JEB locus The three affected calves, five of their close relatives (see section "Animals"), as well as 10,914 controls from the Charolais breed were genotyped with different single nucleotide polymorphism (SNP) arrays over time (Illumina Bovine SNP50, EuroG10K and EuroGMD). Genotypes were phased and imputed to the Bovine SNP50 using the FImpute3 software  [11]  within the framework of the French genomic evaluation, as described in  [12]. Assuming a monogenic recessive inheritance, we searched for identical-by-descent (IBD) haplotypes of at least 20 SNPs (~ 1 Mb) that were in the homozygous state in the three cases and found only in the heterozygous state and at a low frequency in the control group.
The remaining variants were annotated using Variant Effect Predictor (Ensembl release 106; https:// www. ensem bl. org/ info/ docs/ tools/ vep/ index. html). We focused on the following categories of annotations: substitutions with a SIFT score ≤ 0. 05, premature start, start loss, stop loss, stop gain, frameshift, inframe insertion or deletion, and splice donor or acceptor site. In addition, we detected structural variants (SV) within the mapping interval using Pindel  [14] , Delly  [15]  and Lumpy software  [16]  and applied the same filters after comparison with analogous catalogs of SV of 200 control genomes reported in  [17, 18].
Genotyping of the ITGB4 deletion and ITGA6 splice site variant The three JEB-affected calves, their dams, one of their sires and one unaffected male halfsib were genotyped for the ITGB4 deletion by PCR and agarose gel electrophoresis (as described in  [3] ) and for the ITGA6 splice site variant (g. 24112740C > A on chromosome 2) by PCR and Sanger sequencing. A 518-bp segment encompassing this substitution was amplified using a Mastercycler Pro thermocycler (Eppendorf ) with primer pair ACT GGC TGT GTT TTC ACG A/CCA AAG AAT CCC ACC AAA GA and the GoTaq Flexi DNA Polymerase kit (Promega), following the manufacturer's instructions. Amplicons were purified and sequenced on both strands by Eurofins MWG (Hilden, Germany). Finally, variant calling was performed with the novoSNP software  [19]. In addition, to genotype the ITGA6 splice variant on a large scale, we added a probe to the Illumina EuroGMD SNP array using the following design: TCA CTT ACC AGG CAA TGT TGT TTT TTT TTT CCC CTC CGA GCT GGT CTC TTA AAA TACTNN[A/C]AGG GAA AGC CCT CAG TTC TCT ATA TGC AGA GTA AGT CAG AGT GTC TGG AAA AGT GGC AAT The EuroGMD SNP array is routinely used for genomic evaluation in France and genotypes of 186,154 animals from 15 breeds were available for this variant.
Acknowledgements We thank the breeders and  E. Passe  (breeding technician) for providing access to the animals,  C. Escouflaire  and  S. Fritz  ( Eliance ) for their assistance in handling SNP-array genotyping data, and the members of the 1000 bull genome consortium for the excellent collaboration. This work is dedicated to the memory of our dear friend and colleague, Dr. med. vet. Jean-Marie Gourreau , who passed away while the manuscript was being prepared.
Acknowledgements Y. L. acknowledges support from  Agence Nationale de la Recherche  (grant n  ∘ ANR-17-CE30-0011-11 ) and  Labex PALM  (grant n  ∘ ANR-10-LABX-0039-PALM ). Y. L. would like to thank  D. Hagenmuller  for fruitfuil discussions.
Conserved photochemical properties of DPH We then investigated the light-sensing properties of DPH proteins from different environments, by generating recombinant DPH from two genes abundant in the Tara Oceans dataset (Fig. 2a ) and from five coastal centric diatom species (Extended Data Fig. 2 , Table  1 ). These DPH all bind BV and show very similar absorption spectra and Pr -Pfr difference spectra (Fig. 2b , Extended Data Fig. 2 ), with maximal peaks in FR (767 nm +/-2 nm), R (680 nm +/-4 nm) and minor peaks in B (423 nm +/-2 nm and 383 nm +/-4 nm) for Pfr and Pr forms, respectively (Fig. 2b , Extended Data Fig. 2 , Extended Data Table  2 ). Hence, along with previous results from the centric diatom Thalassiosira pseudonana and the model pennate diatom Phaeodactylum tricornutum  6  , DPH light sensing features are widely conserved, with to our knowledge the most red-shifted FR absorption peak for Pfr.
DPH fluence rate-response curves To resolve the apparent incongruence between the DPH absorption spectra and the Rpoor light field that diatoms are exposed to in the ocean, we characterized the wavelength-and intensity-dependence of DPH responses in vivo. To this aim, we generated reporter lines in the model species P. tricornutum in which the Yellow Fluorescent Protein (YFP) was expressed under control of the DPH-regulated, FRinducible HSF4. 6a gene promoter 6 in wild type (WT) and DPH knock-out genetic backgrounds (dph). As shown in Fig. 3a  the YFP signal, as measured by flow cytometry, increases upon FR-light treatment in WT background, while no changes could be detected in WT cells kept in the dark or in dph lines. DPH-dependent fluence rate response curves were then obtained from the quantification of the YFP signal of reporter lines exposed for 10 min to different intensities of various monochromatic lights compared to the signal measured in darkness (see Methods and Extended Data Figs.
Search for DPH and diatom aureochrome genes in environmental sequence data Known DPH sequences were aligned with mafft v7. 4  32  to generate separate Centric and Pennate HMM (Hidden Markov Models) profiles for each DPH domain, covering nearly the full-length protein. HMM searches (HMMER version 3. 2; http://hmmer. org/) were performed against known phytochromes from streptophytes, chlorophytes, glaucophytes, cryptophytes, bacteria, cyanobacteria, fungi and stramenopiles  6  , the MetDB database (https://metdb. sb-roscoff. fr/metdb/), diatom genomes and transcriptomes (see Supp Data1), Tara Ocean sequence data ( Tara Oceans gene catalog (MATOU-v2)  7, 8  and Tara Oceans diatom Metagenome Assembled Genomes, or MAGs 9 , and a set of proteins specific for each domain (either the proteins used in the corresponding Pfam domain alignment or if these were too few in numbers, 1000 randomly selected proteins from proteins known to possess the specific domain in InterPro).
Sequences were aligned to the aureochrome HMM model using hmmalign and the phylogenetic tree was reconstructed with FastTree 35 (v2. 1, default settings i. e. JTT+CAT, Shimodaira-Hasegawa test with 1000 resampling). Only sequences branching in the diatom clades (as delimited by the sister Bolidophyceae clade) were annotated as diatom aureochromes (see Extended Data Fig. 9 ). Mapped reads to the Tara Oceans gene catalog (MATOU-v2) 7,8 sequences were retrieved from each Tara Oceans sample. Relative abundances were expressed as the sum of all reads mapping to centric DPH (or centric AUREO) divided by the sum of all the reads mapping to centric diatom genes. The analysis was performed on average values of the four size fractions when all were available (0. 8-inf, 0. 8 to 5 µm or 0. 8 to 3 µm; 5 to 20 µm or 3 to 20 µm; 20 to 180 µm; 180 to 2000 µm; see Fig.