dataesr/scientific-paragraphs-categorization huggingface dataset:
The theoretical characterization of the asymptotic behavior of analog data assimilation schemes is also an interesting avenue of research. Similarly to the theoretical analysis of ensemble Kalman filters and particle filters  (Le Gland et al. 2009) , the derivation of convergence conditions, possibly associated with reconstruction bounds, would be of key interest to bound the reconstruction performance of the proposed analog schemes with respect to their model-driven counterpart. Chapron, Valérie Monbet, and Anne Cuzol. The authors would also like to thank Phi Viet Huynh for his valuable contribution to both the AnDA Matlab toolbox and the AnDA Python library. We are also grateful to the two anonymous reviewers, whose comments helped to improve the manuscript. We thank Geraint Jones for his English grammar corrections.
RNAseq Three biological replicates, each one composed of heavy polysomal fractions of two samples were analyzed by RNAseq (n = 4 mice per biological replicate). RNAseq libraries were constructed with the Truseq stranded mRNA sample preparation (Low throughput protocol) kit from Illumina. One-hundred nanogram of total RNA was used for the construction of the libraries. The first step in the workflow involves purifying the poly-A containing mRNA molecules using poly-T oligo attached magnetic beads. Following purification, the mRNA was fragmented into small pieces using divalent cations under elevated temperature. The cleaved RNA fragments were copied into first strand cDNA using SuperScript II reverse transcriptase, Actinomycin D and random hexamer primers. The second strand cDNA was synthesized by replacing dTTP with dUTP.
Bioinformatic RNAseq Analysis Image analyses and base calling were performed using the Illumina HiSeq Control Software and the Real-Time Analysis component. Demultiplexing was performed using Illumina's conversion software (bcl2fastq 2. 17). The quality of the raw data was assessed using FastQC from the Babraham Institute and the Illumina software SAV (Sequencing Analysis Viewer). A splice junction mapper, TopHat 2. 0. 13  (Kim et al. , 2013; using Bowtie 2. 2. 3 (Langmead and Salzberg, 2012) ), was used to align RNAseq reads to the mouse genome (UCSC mm10) with a set of gene model annotations (genes. gtf downloaded from UCSC on May 23, 2014). Final read alignments having more than three mismatches were discarded. Then, the counting was performed with HTSeq count 0. 6. 1p1 (union mode;  Anders et al.
, 2015). The data is from a strand-specific assay, the read has to be mapped to the opposite strand of the gene. Before statistical analysis, genes with less than 15 reads (cumulating all the analyzed samples) were filtered and thus removed. Differentially expressed genes were identified using the Bioconductor  (Gentleman et al. , 2004)  package DESeq2 1. 4. 5  (Anders and Huber, 2010). Translational efficiency was estimated, for each gene and genotype, as the ratio between heavy polysomal fractions associated mRNA counts and cytosolic steady-state mRNA counts. The Xtail 1. 1. 5 (Xiao et al. , 2016 ) R package was used to identify genes showing differential translation efficiency values between genotypes. Data were normalized using the Bioconductor  (Gentleman et al. , 2004)  package DESeq2 1.
4. 5  (Anders and Huber, 2010)  normalization method. Genes with adjusted P value less than 5% (according to the FDR method from Benjamini-Hochberg) were declared differentially expressed/differentially translated. To perform the functional analysis of the resulting list of genes with the Gene Ontology (GO) annotations, the topGO  (Alexa et al. , 2006)  package from Bioconductor was used. Overrepresented GO terms were identified using Fisher's exact test with the weight method that is implemented in the topGO package. As confidence threshold we used a P value of 1%. To perform this.
Genes PCR primers Forward Reverse Cox7a2 GCCCTTCGTCAGATTGCCCAG TCAGATGCCCCGCCTTTCAGA Cox7c GTTTGCCGCACCTTTCTTTA CAGAGACGAGGCATTGAATCT Slirp GGCCATGTAAGAAGGTGCACTGT ACCCAACCCATGCCTCTGTGA Uqcrh GCGTGTCTTCCCGGTCACAG TGACAAGGCTGAGGAGGACGA Uqcrb AGAGAGCCCTGGACCTGACT TGCCCACTCTTCTCTCTCCTT Timm8a1 TGCAGCATTTCATCGAGGTG GACTGTCCAACTTAGGCCCA Mrpl33 CTCCGAGAGAAGCTGAGCCT CCACTACTCAGAGGGAACGGA Dbi CAAGTGGGACTCGTGGAACA AGCTCGTCTACCTTTTCCACA β-actin CGTGAAAAGATGACCCAGATCA CACAGCCTGGATGGCTACGT Hprt2 GCAGTACAGCCCCAAAATGG GGTCCTTTTCACCAGCAAGCT analysis the differentially expressed genes were compared with those of all known genes present in the annotation. The GO categories were found in the Org. Mm. e. g. db package  (Carlson, 2017)  based on the gene reporter EntrezGeneID. cDNA Synthesis and Quantitative Real-Time PCR Synthesis of cDNA was performed on total RNA (input fraction) and heavy polysomal RNA, which were reverse transcribed to first strand cDNA using the SuperScript VILO TM cDNA synthesis kit (Invitrogen).
Resulting cDNA was used for quantitative real-time PCR (qRT-PCR), using 2× SYBR Green Mix and LC480 Real-Time PCR System (Roche) as described  (Puighermanal et al. , 2017). Analysis was performed using LightCycler 480 Software (Roche). Results are presented as linearized Cp-values normalized to housekeeping genes β-actin or Hprt2 and the ∆CP method was used to give the fold change. The primer sequences are indicated in Table  2.
Locomotor Activity Open Field Test Spontaneous exploratory behavior was monitored in an open field (white plastic box with 35 cm width × 45 cm length × 25 cm height) for 30 min. The open field was wiped with 70% ethanol between sessions. The center zone was defined as a virtual perimeter within 5 cm from the sides of the box. Experiments were filmed and an observer blinded to genotype scored the time spent in the center (4 paws inside the center zone) and the number of midline crosses (4 paws crossing a midline of the box) during the first 10 min. Videos were analyzed using Noldus EthoVision XT (Netherlands) software by calculating the total distance traveled, average speed, time spent immobile and immobility frequency.
Therefore, we next sought to analyze CI activity on total homogenates from the Acb of rpS6 P-/-mice and wild-type littermates. Despite the large number of downregulated genes encoding for CI proteins found in rpS6 phosphorylationdeficient mice, no alterations were observed in CI activity (Figure  7E ), even after correction with the activity of CS (Figure  7F ), a validated biomarker for mitochondrial density, as shown by the CI/CS ratio (Figure  7G ). On the other hand, we also measured ATP levels since half of the complex V-related genes analyzed were downregulated in rpS6 P-/- mice. However, no differences in Acb ATP content were found between genotypes (Figure  7H ). Together, our data indicate an altered translation, but not transcription, of a subset of mitochondria-related transcripts selectively in the Acb of rpS6 P-/-mice.
Krona-like plots (Fig. 1c ) display the complete taxonomic assignment for each of the sampling locations, while a Principal Component Analysis (PCA) (Fig. 1d ) depicts the scattering of all the samples containing elasmobranch reads across the two biogeographic areas. Even though several MOTUs are shared between the two regions, there is still a clear spread in MOTU (species) composition between New Caledonia and the Caribbean. No elasmobranch reads were detected in the two PCR negative controls that were performed and sequenced to detect potential contamination. Using the 127-bp COI fragment, we did not find a wholly unequivocal correspondence between MOTUs and species; since some MOTUs had 100% sequence identity matches with more than one species in the BOLD database. Although this issue mostly pertained to the genus Carcharhinus, which is known to be taxonomically problematic and polyphyletic  52  , it also affected the less speciose Rhizoprionodon and Negaprion.
It is a minimally invasive and resource-effective technique. The eDNA sampling and metabarcoding protocols are easy to standardize and the molecular assignment does not require taxonomic expertise. Nevertheless, our findings also reveal a number of concerns that should be addressed in future developments of shark/elasmobranch eDNA metabarcoding approaches. First the taxonomic resolution of the final dataset is strongly dependent on the choice of markers; while the use of COI as a metabarcoding marker has previously been criticized  58  , owing to its high sequence variability, which may impair the design of truly universal primers and complicate bioinformatics analysis -it can also be argued that COI presents two major advantages over other potential markers. First, the steadily growing international effort, headed by the Consortium for the Barcode of Life (CBOL), to develop a public DNA barcoding database with curated taxonomy, greatly facilitates taxonomic assignment.
The BOLD database (http://www. boldsystems. org/)  59, 60 currently includes >4 million sequences belonging to over 500,000 species, curated and identified by expert taxonomists. Secondly, the high mutation rate of COI enables identification at the species level, whereas the highly conserved sequences of other markers, such as 18S, make it often impossible to distinguish at the species or genus levels; and species-level identification is crucial for studies aimed at detecting rare species, such as is often the case for sharks. Nevertheless, using the 127 bp elasmobranch specific COI fragment  46  , we still recorded some ambiguity in the taxonomic assignment of some species of the genera Carcharhinus, Rhizoprionodon and Negaprion, owing to the limited sequence variability within the amplicon.
Consequently, the sequences of some MOTUs are 100% identical to individuals belonging to different species in the BOLD database. In our dataset, this is presented by several MOTUs belonging to either of two or more species. Furthermore, this has resulted in 3 MOTUs having 100% sequence identity for species occurring in New Caledonia, and species occurring in the Caribbean. One particular example is the Carcharhinus amblyrhynchos/limbatus MOTU. The bulk of sequences within this MOTU are from New Caledonia, 16730 compared to 146 in the Caribbean (Supplementary Table  S2 ). In all probability, the sequence reads from New Caledonia belong to both C. amblyrhynchos, the grey reef shark (a species abundant in this area and also the species most often visually detected during sampling operations, Supplementary Table  S1 ) and to Carcharhinus limbatus, the blacktip shark.
Since C. amblyrhynchos does not occur in the Caribbean, the 146 reads of this MOTU in the Caribbean samples most likely belong to C. limbatus. Similar considerations apply to Negaprion brevirostris/acutidens and Carcharhinus perezii/falciformis, whose MOTUs are shared between New Caledonia (365 and 206 reads respectively) and the Caribbean (91 and 1045 reads respectively). Negaprion brevirostris (lemon shark) is native to the Americas whereas N. acutidens (sicklefin lemon shark) is widely distributed throughout the Indo-Pacific. Carcharhinus falciformis, the silky shark, is circumtropical, while the distribution of Carcharhinus perezii (Caribbean reef shark) is restricted to the tropical western Atlantic Ocean. In order to resolve the issue with closely related species, it will be essential to design alternative primers that are able to amplify a longer fragment of the gene region, in addition to an improved reference database.
The libraries were quantified using the NEBNext qPCR quantification kit (New England Biolabs) and pooled in equimolar concentrations along with 1% PhiX (v3, Illumina) serving as a positive sequencing quality control. The libraries with a final molarity of 8 pM were sequenced on an Illumina MiSeq platform in a single MiSeq flow cell using v2 chemistry (2 × 150 bp paired-ends). Bioinformatic and Statistical Analyses. The bioinformatic analysis was based on the OBITools metabarcoding software suite  75. The pipeline used for data analysis is summarized in Supplementary Methods S3. Quality of the reads was assessed using FastQC. Paired-end reads were aligned using illuminapairedend and alignments with quality score >40 were kept. The aligned dataset was demultiplexed using ngsfilter. The length distribution of the demultiplexed reads showed a large percentage of short fragments (<95 bp), originating from non-specific amplifications and primer-dimer artefacts, which were not removed during the size selection step of library preparation.
Thus, a length filter (obigrep) was applied to the aligned reads (120-135 bp) in order to select only the fragments with the correct target size. Reads containing ambiguous bases were also removed. The reads were subsequently dereplicated using obiuniq and a chimera removal step was performed using the uchime-denovo algorithm  76  implemented in vsearch  77. The MOTUs were delimited using the sumaclust algorithm  75  with a constant similarity threshold of 99%. Taxonomic assignment of the representative sequences for each Molecular Operational Taxonomic Unit (MOTU) was performed using the ecotag algorithm  75. We built a bespoke elasmobranch reference database using a custom R script for retrieving all COI elasmobranch sequences available from the BOLD database  60  , and subsequently selecting those that included our 127 bp target fragment.
In order to add homologous sequences from other, non-elasmobranch taxa, an in silico PCR was performed against release R117 of the EMBL-EBI database using ecoPCR  78. Subsequently, the obtained reference sequences were added to the elasmobranch sequences obtained from BOLD. These additional reference sequences were added to our elasmobranch database in order to avoid the incorrect assignment of amplified sequences, belonging to other taxa, to elasmobranchs. This combined reference database is available from http://github. com/metabarpark/Reference-databases. The final refining of the dataset included taxonomy clustering of MOTUs assigned to the same species. Due to its high sensitivity, an additional challenge associated with eDNA metabarcoding, is the risk of contamination  79, 80  , and hence the possibility of introducing false positive results.
Acknowledgements We thank all staff, students and volunteers from Glover's  Reef Research Station, Discovery Bay Marine Laboratory and Field Station, Montego Bay Marine Park, Bimini Biological Field Station (Sharklab) , the  SFS Center for Marine Studies , and the crew of the research vessel Amborella, for their assistance with sample collection. We also thank  Alexandre De Menezes  and  Ian Goodhead  for technical discussions and  Andjin Siegenthaler  for assistance with our sampling area maps. We are also grateful to  Kathryn Matthews  and  Angelo Villagomez  for logistic support. This work was co-funded by the  Pew Charitable Trusts , the  University of Salford  R&E strategy funding, the  Total Foundation  and the Government of New Caledonia.
Motivating example in phylogeny. As a simple motivating example, we consider a univariate problem in phylogeny. We want to reconstruct a tree between many species based on some simple features (like the height, or the weight of individuals). Ideally, this tree should resemble the known phylogeny. We illustrate this task on the "Animal Ageing Longevity Database" 1  , which provides various features for many animal species. Here, we consider classifying bird species based on their birth weight. The known phylogeny groups these n = 184 individuals into 40 bird families, themselves grouped into 15 orders. We reconstruct the tree based on the weights and check whether it matches the orders and the family classification. Recovered solution paths of (2) are plotted in Figure  1  for a) the Cas-ANOVA weights  (Bondell and Reich, 2008b)  ; b) the "default" Clusterpath weights  (Hocking et al.
Two individuals k and are in the same multidimensional cluster if they have been fused on every dimension. This multidimensional classification is recovered on a grid of λ in the clusterpath package and in the fusedanova package. Note however that the classification recovered over all the dimensions is not necessarily better than those recovered on single, well-chosen features. We illustrate this point at the end in Section 8 on phylogenetic data: in a number of cases, the best agreement with the known phylogeny is obtained by a single-feature-based tree.
cross-validation q q embedded classical number of conditions K (log) We tried other implementations to solve (6) such as the Clusterpath package by  Hocking et al. (2011) , the flsa package by  Hoefling (2010)  or the genlasso package by  Tibshirani and Taylor (2011). These implementations do not fully exploit the structure of the problem and have runtimes considerably longer than ours, even for moderate K. Thus, we do not report their timings here.
Such weights correspond to the Clusterpath weights adapted to the ANOVA setup. We use our own code for each method. Typically, the computational burden required by Cas-ANOVA is huge, compared to the other two procedures as the path of solutions may contain splits. Qualitatively, the difference would be as in Figure  3 , middle panel. Thus, we typically force the algorithm not to split when using the Cas-ANOVA weights. We generate data as specified below, and for each procedure we check whether there exists at least one λ for which the correct structure is identified along the path of solutions. The probability of true support recovery is evaluated by replicating this experiment a large number of times (8096 times 4  ). To investigate the asymptotic behavior of each method, we vary n from 50 to 1,000 and consider two scenarios for the initial number of groups K.
PLS regression for LNC assessment To assess leaf nitrogen content from spectral data a PLS-R model for LNC assessment has been tested using the following procedure: -Before PLS-R computation, every spectrum R j () was pre-processed using a log-center operation, giving a spectrum R jLC (). It consists in computing for each wavelength the logarithm of the amplitude value, and then subtracting the mean amplitude for the whole spectrum (centering). This allows converting multiplicative effects (see further) into additive effects, which are then eliminated by the centering. -A PLS-R calibration was made based on the set of 57 (R jLC (), LNC j ) couples issued from the experimental dataset. This calibration provided a set of B coefficients [B(), b0] allowing the LNC estimation of any new spectrum according to the following equation: LNC* = R LC () T.
Whole blood (WB), tumor and adjacent normal tissue of 40 early stage NSCLC patients were collected and single cells suspension achieved via mechanical disruption and enzymatic digestion. To characterize the cellular composition, differentiation and activation status of immune cells, 9 color flow cytometry was performed using six antibody panels aimed at major leukocyte populations. Samples were analyzed on a FACS Fortessa using FlowJo software. Significance (p < 0. 05) was determined by Friedman tests with Dunn's multiple comparison analyses. Results: Granulocytes were less frequent in tumor and normal tissue compared to WB. As a consequence, proportion of lymphocytes among leucocytes was significantly higher in lung and tumor tissues. Regarding lymphocyte subsets, proportions of T cells and the major CD4-, CD8-and γδTCR-expressing subsets were comparable in all three compartments whereas B cells tended to be higher in tumor and lower in lung tissue.
With an input requirement of 10 ng of total RNA, libraries were generated, templated on the Ion Chef TM and sequenced on the Ion S5 TM System. Sequencing data was analyzed and mapped with Torrent Suite Software and differential expression analysis was conducted with Affymetrix TM Transcriptome Analysis Console. Results: Our data showed that gene expression profiles can stratify NSCLC FFPE samples by histopathology and TIL levels. The expression profiles of FFPE and fresh frozen samples are highly correlated with an average correlation greater than 0. 9. Approximately 80% of the 40 samples show moderate to high expression of CD8+ T cell cytokines, IFNG and TNFa. We conducted a differential expression analysis between a group of samples (n = 8) with high percentage of surrounding and infiltrating lymphocytes and another group (n = 5) with low stromal content but devoid of infiltrating lymphocytes.
Materials and methods: We retrospectively investigated 120 pairs of cancerous and matched noncancerous tissue specimens from CRC patients who underwent the same standard chemotherapy and radical surgery. We stained the successive paraffin-embedded slides for those marker involved in glutathione metabolism (GSTM3, GSTP1, SRM, ODC1) respectively and correlate the expression of these markers with tumor grade, stage, overall survival (OS) and progression-free survival (PFS). We further integrated transcriptome data of 345 CRC patients from public geo database and investigated the correlations. Results: Expression of GSTM3 in tumor group are decreased than in matched noncancerous group, while GSTP1, SRM and ODC1 are overexpressed in tumor group. Moreover, within the tumor group, combined higher expression of GSTP1, SRM and ODC1 had lower 5-year PFS (52%) and OS (58%) than those with lower GSTP1 tumor group (60% and 66%, respectively; PFS HR: 1.
Materials and methods: Leveraging in-house syngeneic models and its detailed profiling data, including treatment response of anti PD-1, PD-L1, CTLA-4, OX-40, GITR, LAG3 and TIM3 antibodies, RNAseq data on tumor samples, and FACS analysis on both baseline and posttreatment tumor samples, we created the first in vivo screening panel for immunotherapy: MuScreen. MuScreen, a 3 month screening with up to 20 well-characterized syngeneic models, including both PD and efficacy arms to be selected by the researchers based on results observed from a large dataset. Test agents from multiple clients are pooled together for each run (sharing vehicle and other common groups) providing a significant reduction in the number of animals used and the associated costs. Results: CrownBio has established the first well-characterized in vivo panel for immunotherapy.
Materials and Methods: MALDI mass spectra were generated from pretreatment serum samples from 119 patients with metastatic melanoma (MM) treated with nivolumab at the Moffitt Cancer Center. A classifier development platform optimized for creation of multivariate molecular diagnostic tests which can generalize well to independent datasets was employed to create a test that identified patients with prolonged overall survival. This test classified samples into two groups: group 1 with prolonged survival and group 2 with short survival. The classifier was validated using two independent cohorts of MM patients receiving anti-PD-1 agents: 30 patients from Yale University (YU) and 25 patients, most treated with pembrolizumab, from Massachusetts General Hospital (MGH). The test was also applied to pretreatment sera collected from 21 patients from Yale that received combination PD-1/CTLA-4 blockade.
The subjects are vaccinated (up to three occasions) with models for peptide-and protein-based vaccines; HPV16 E7 peptide antigens and Keyhole Limpet Hemocyanin, using the TLR3 agonist poly-ICLC (Hiltonol) as adjuvant. The vaccine is as intradermal injections followed by illumination of the vaccination site. Local and systemic adverse effects will be assessed, and cellular and humoral immune responses will be analysed by ELISPOT and ELISA assays, respectively. Results: The principle of the fimaVacc technology will be presented, together with preclinical results showing that the fimaVacc strongly and synergistically enhances both cellular and humoral immune responses when given with several types of adjuvants including MPLA, poly-IC, Ploy-ICLC and gm-CSF. Data showing enhancement of TNF-α and INF-γ cytokine production from both CD4-and CD8+ T cells, and the improvement of anti-tumour effects in different clinically relevant mouse models, will be presented.