dataesr/scientific-paragraphs-categorization huggingface dataset:
A tuning procedure (tune. block. splsda) with 50 × 10-fold crossvalidation was applied to determine the optimal number of variates. Final model performance was assessed using 10-fold cross-validation repeated 50 times. We did not apply supervised analysis to our fungal data due to poor model fit. To cross-validate our supervised analysis and also examine fungi-metabolite associations in the field, we applied an unsupervised omics integration methodsparse partial least squares (sPLS) regression, using the mixomics package in R  [41]. For model parameterisation, we set the number of metabolite features to include in our model for each component (keepY) to 111, corresponding to the number of metabolites found to be discriminative of disease dynamic based on single omics analyses. We selected 21 bacterial ASVs to be included for each component (keepX), which corresponds to the number of differentially abundant taxa with an effect size > 1 or < -1 and corrected p-values < 0.
Host skin metabolome maps to disease dynamic and population 2014 metabolite features were measured in negative ion mode. Disease dynamic and population were significant factors driving variability in metabolome (PERMANOVA dynamic Pseudo-F (1, 54) = 10. 93, R 2 = 0. 17 p = 0. 001, population Pseudo-F (3, 52) = 13. 14, R 2 = 0. 43, p = 0. 001, Fig. 3a ). Univariate analysis identified 870 differentially abundant metabolite features, of which 183 had a log 2 fold change > 1. 5 (Fig. 3b , Supplementary  Data 7). PLS-DA based on disease dynamic yielded 121 metabolite features with a VIP score > 2, of which 111 were considered most informative (VIP > 2, q < 0. 05, log 2 fold change > 1. 5, Supplementary Data 8). Following putative annotation of the most informative metabolite features, one of the features was suspected to be the anti-Bd metabolite indole-3-carboxaldehyde.
More detailed investigation of the MS/MS data for this metabolite (m/z 144. 04606 RT 6. 96 min) kindled our interest in a second, following the peak of the same m/z in the spectra at 8. 73 min, present in the XCMS matrix but originally filtered out as thought to be due to some higher blank signal. However, upon closer inspection, the intensities of this second peak behaved similarly to m/z 144. 04606 with higher intensity in the epizootic population (Wilcoxon's test W = 17, p < 0. 001, SI Fig. 2 ). Whilst both ions were putatively annotated as the anti-Bd metabolite indole-3-carboxaldehyde, the MS/MS data for the second signal resembled those in spectral databases (https:// mona. fiehn lab. ucdav is. edu/ spect ra/ displ ay/ PR100 508; https:// mona. fiehn lab. ucdav is. edu/ spect ra/ displ ay/ PB000 507) and from an authentic standard fragmented in-house, thus providing evidence for the presence (and increased abundance in the epizootic population) of indole-3-carboxaldehyde on wild A.
05). Microbiome/metabolome integration using DIABLO  [48]  identified bacterial and metabolite features discriminating control and exposure treatments (Fig. 6a, b , Supplementary Data 21). Bd exposure was associated with enrichment of bacterial ASVs and metabolite features (Fig. 6c, d ) indicating that infection drives changes in microbe-metabolite interactions. All three discriminatory bacterial ASVs (Acinetobacter, Sphingobacterium, Comamonas) identified using ALDEx2 were also identified by DIABLO.
Sequencing and phylogenetic analysis The ampli ed fragment (~ 830 bp) resulting from the secondary reaction of n-PCR was puri ed using the GFX PCR DNA Band Puri cation® Kit (GE Health Sciences, Champaign, IL, USA) and sequenced with the aid of DYEnamic® ET Kit Cycle Sequencing® Terminator Dye (GE Health Sciences, Champaign, IL, USA) on a MegaBACE® sequencer (GE Health Sciences, Champaign, IL, USA). Sequencing reactions were performed at least three times in both directions with the n-PCR secondary reaction primers. The consensus sequence was analyzed using CodonCode Aligner v. 2. 0. 4 software (CodonCode Corp. , Dedham, MA) and aligned with Cryptosporidium reference sequences published in GenBank (https://blast. ncbi. nlm. nih. gov/Blast. cgi) using MEGA X software  (Kumar et al. 2018 ) by the neighborjoining method  (Saitou and Nei, 1987)  after estimating the distance using the Kimura 2-parameter model  (Kimura 1980).
Results Cryptosporidium oocysts were detected in all fecal samples by microscopic analysis of smears stained using the Ziehl-Neelsen technique (Fig. 1 ). Molecular analysis revealed ampli cation of Cryptosporidium DNA in all samples analyzed. By sequencing the fragment ampli ed by n-PCR, the species C. galli was identi ed in all samples, but in one of the birds, a mixed infection was detected since in one of the sequencing runs, the species C. andersoni was identi ed. The C. galli isolates from the present study shared 92. 54-96. 41% similarity with other C. galli isolates according to nBlast analysis, and the C. andersoni isolate from one of the birds shared 98. 85% identity with C. andersoni from slaughterhouse wastewater. Molecular characterization of the seven Cryptosporidium samples was performed with phylogenetic reconstructions of the 18S rRNA gene using a total of 329 positions in the nal dataset.
The 100% positivity of saffron nches, family Emberizidae, was high, but the number of samples collected and analyzed was low, making it di cult to compare the prevalence with that reported in most studies of Cryptosporidium in captive and wild birds. One factor that may interfere with the rate of Cryptosporidium infection is a difference in the age of the animals (de Graaf et al. , 1999;  Nichols, 2008) , although almost all reports of Cryptosporidium infections in captive or wild birds do not specify the age range of the animals examined. aveola and was positive for C. galli according to n-PCR sequencing (accession number in GenBank not available). Even though our research represents the third diagnostic report of C. galli in S. aveola, further studies are still needed on species or genotypes of Cryptosporidium that can infect this species of Passeriformes.
Recombinant Proteins The bacterial expression plasmids of pET21a containing the codonoptimized synthetic genes lacking the sequences for the signal peptide and GPI-anchor signal of Plasmodium yoelii circumsporozoite protein (PyCSP; accession number P06914; amino acids  and Plasmodium falciparum circumsporozoite protein (PfCSP; accession number XP_001351122; amino acids 27-384, containing just 23x NANP and 3x NVDP repeats), both coupled to a C-terminal hexahistidine tag were employed for the expression of the respective proteins as described before  (22). Briefly, the recombinant proteins were expressed in Escherichia coli BL21 (DE3) Star (Invitrogen, Carlsbad, CA, USA), on induction with 1 mM isopropyl-b-Dthiogalactoside (IPTG) (NZYTech, Lisbon, Portugal) for 4h at 37°C (PyCSP) and 34°C (PfCSP).
Plates were washed and revealed using ophenylenediamine dihydrochloride (OPD; Sigma, St Louis, Mo, USA), according to the manufacturer's instructions. The reaction was stopped with 3M HCl and the plates read at 492nm in a Synergy 2 microplate reader (Biotek Instruments, Winooski, Vt, United States) with the Gen5 software (Biotek Instruments). Sera antibody titers were determined by plotting the O. D. values against the respective dilution, and curve fitting the data with a power series curve used to determine the dilution at which O. D. equals 0. 1 which we have established as our cut-off point for the presence of specific antibodies  (39).
ELISAs for Determination of IgG Against Synthetic CSP Peptides For the detection of anti-peptide antibodies, high-binding 96well flat-bottom plates Nunc MaxiSorp (Thermo Fisher Scientific) were coated overnight with 5 mg mL -1 of each peptide in PBS. The next day, plates were blocked with 1% bovine serum albumin (BSA) in PBS, for 1 h at 37°C and washed with 0. 02% (v/v) Tween-20 in PBS. Single dilutions of the sera were performed in PBS 0. 25% BSA and incubated, in duplicate, for 1h at 37°C followed by incubation with a horseradish peroxidase-conjugated goat anti-mouse IgG (1:5,000, Southern Biotech). Plates were washed and revealed using OPD (Sigma), according to the manufacturer's instructions. The reaction was stopped with 3M HCl and the plates read at 492nm in a Synergy 2 microplate reader (Biotek Instruments) with the Gen5 software (Biotek Instruments).
Cells were analyzed in a BD FACSCanto II flow cytometer (BD Biosciences, Franklin Lakes, NJ, U. S. ) running BD FACSDiva Software version 6. 1. 3 (BD Biosciences), and results analyzed using FlowJo version 10. 7. 1 (FlowJo LLC, Ashland, OR, USA). GC B cells were defined as B cells (B220 + CD4 -) expressing CD95 and PNA. T FH cells were defined as CD4 T cells (B220 -CD4 + CD44 + ) expressing CXCR5, along with PD-1. These cell populations were assessed in the spleen. Long lived plasma cells (LLPCs) were characterized, in the bone marrow, as B220 -/low CD138 + cells.
Statistical Analysis Statistical significance was determined with Log-Rank (Mantel-Cox) test for the incidence of blood stage infection, unpaired two-tailed t-test or 2-way ANOVA with Tukey's multiple comparisons test for comparison of anti-CSP IgG titers, or 2way ANOVA with Bonferroni's multiple comparison test for comparison of functional in vitro sporozoite assays, cell populations, and cytokine concentration (comparing between different adjuvanted formulations and between formulations with and without protein for each adjuvant). Analysis was performed using GraphPad Prism version 7 (GraphPad Software, San Diego, CA, USA) or RStudio running R version 3. 4. 2 for Mac OS X.
However, we propose here that 5'ppp-dsRNA may be an equally good alternative, having displayed similar, and, under some conditions, even better, adjuvant effects without inducing as high a systemic proinflammatory profile. Other RIG-I agonists have also been shown to be less inflammatory and induce lower serum cytokine release, even upon intravenous administration, especially compared with poly(I:C)  (60, 61). Currently, RIG-I agonists have mostly been explored as immunotherapeutic agents against cancer (70). Results from s o m e o f t h e s e c l i n i c a l t r i a l s ( N C T 03 7 3 9 1 38 an d NCT03065023) and others  (71) , show that RIG-I agonists can be safely administered to humans and can be produced under Good Manufacturing Practices (GMP), demonstrating the potential for these substances to be licensed for human use.
ACKNOWLEDGMENTS The authors thank  Rui Appelberg  and  Mariana Resende , from  i3S , for providing the hybridomas for production of the T cell depletion antibodies;  Pedro Ferreirinha  and  Alexandra Correia  from  i3S  for their contribution with ELISpot assay. The authors acknowledge the support of the following i3S Scientific Platforms: Animal Facility and Translational Cytometry, as well as  BioSciences Screening ,  Advanced Light Microscopy  and Histology and  Electron Microscopy , members of the national infrastructure  PPBI-Portuguese Platform of BioImaging  (supported by  POCI-01-0145-FEDER-022122 ).
FUNDING The work was funded by  Fundacão para a Ciencia e Tecnologia (FCT)/Ministeŕio da Educacão e Ciencia (MEC)  and  FEDER  through the project  PTDC/SAU-PAR/31340/2017  (to JT) and the research Unit No. 4293. The authors acknowledge funding from  French Government 's  Investissement d'Avenir program ,  Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases " (grant no. ANR-10-LABX-62-IBEID  to RA). JT, DC, MS, and AR received individual funding from  FCT  ( CEECIND/02362/2017 ,  SFRH/BD/123734/2016 ,  SFRH/ BD/133485/2017  and  SFRH/BD/133276/2017 , respectively).
Spatial Relationship Analysis The previously obtained images of the objects (a tumor mass, a whole-tumor section, or a ROI in the same section) were registered and merged using Adobe Photoshop 23. 3. 2 software. Intensity plot profiles of the fluorescence signals were created and superimposed using ImageJ 1. 53t software (National Institutes of Health, Bethesda, MD, USA). The spatial relationship between the imaging components was then visually determined.
Acknowledgments:  Authors M. Degardin  and  D. Boturyn  wish to acknowledge support from the  ICMG Chemistry Nanobio Platform (Grenoble, France) , on which the peptide synthesis was performed, and the  Labex ARCANE  and  CBH-EUR-GS  ( ANR-17-EURE-0003 ). The authors would also like to thank the staff of the  Laboratory Animal Sciences section (QST)  for animal care.
8. 5; Bernex-Switzerland). From reconstructed 3D images, we traced an axial section along the palatal vault. 3 perpendicular sections were chosen for the analysis. The first crossed the two centers of the palatal root of the first molars (right and left), and was framed by the other two sections with an increment of 200 µm mesial and distal, and a 2D image representing a frontal cut was extracted from each. Alveolar bone resorption was analyzed on these 2D images, using Fiji software  (23) , after application of automatic momentpreserving thresholding  (24) , by measuring the distance between 2 anatomical landmarks: the alveolar bone crest (ABC) and the cement-enamel junction (CEJ), on a coronal section of the maxillary first molars. The measurements were performed using Fiji software (Wayne Rasband, version java 1.
Then, the stained sections were transferred into light green solution (0. 1% fast green, 2% acetic acid) for 5min and rinsed in a 2% acetic acid solution for 5 min and washed in distilled water for 5 min. All colorants were filtered before use. The stained sections were dehydrated in 95% ethanol for 3 min, 100% ethanol for 3 min and cleared in toluene for 3 min. After dehydration, slides were mounted with distrene-plasticizer-xylene (DPX) resin (PanReacApplichem, Germany). Histological microscopy was performed using a Leitz DMRB microscope (Leica Microsystems) set for transmitted light illumination and equipped with a Sony DXC-950 CCD camera. For histomorphometric evaluation, various in situ analyses were performed using the imaging software Fiji  (23). The periodontal attachment level (AL) was measured as the distance in mm from the cement-enamel junction (CEJ) to the bottom of periodontal pocket defined as the first functional collagen fibers of the periodontal attachment.
Acquisition of immunohistochemistry and immunofluorescence images was performed by microscopy as indicated in the histomorphometric analysis section. Quantitative analysis was performed on computerized images. For quantitative analysis, a ROI of 0. 082 mm 2 was selected in the connective tissue at the vicinity of the site of induction. Positive-stained cells were then counted manually in the ROI. We used Fiji software  (23)  to quantify the level of NLRP3 expression along the alveolar bone crest. A (130 µm length) x (10 µm thick) segmented line was manually drawn along the alveolar bone crest, and the mean intensity was measured by Fiji. Co-staining analysis between NLRP3 and PMN (see Table  1  for antibodies) was performed using Fiji software with the Colocalization Threshold plugin on a constant region cropped around the alveolar bone crest.
Statistics The statistical analysis was performed on Prism software (Graph Pad V. 8). The differences were tested for significance, after normality verification with the Shapiro-Wilk test adapted to small samples. When normality was established for all groups, we used ordinary oneway ANOVA non-parametric test, followed by uncorrected Dunn's test for the micro-CT analysis of bone resorption, and the uncorrected Fisher's test for histomorphometric and immunostaining analyses. When normality was not established for one or more groups, Kruskall-Wallis test was applied, followed by group comparisons using Welch's t-test. The Spearman correlation coefficient (Spearman's r, non-normal distribution) was used to determine the level of correlation between RANKL fluorescence intensity values and osteoclast numbers or ABC-CEJ distance.
Material and methods Patients. All patients with COVID-19 were confirmed to be infected by SARS-CoV-2 by real-time reverse transcriptase PCR (RT-qPCR) testing or by a positive serology for anti-SARS CoV-2 IgG. aPL dosage was performed on serum samples collected from 157 COVID-19 patients admitted between March 2020 and July 2021 in the University Hospital of Marseilles (France) and consecutively referred to the hospital laboratory for immunological exploration. Clinical data were collected from the day of sampling. They included co-morbidities (history of thrombosis, history of stroke, coronary heart disease, hypertension, diabetes, heart failure and chronic respiratory disease), clinical presentation (mild or severe), and duration of symptoms. Definitions. "Severe clinical presentation" was defined based on at least one of the following criteria: respiratory rate > 30 cycles/min, oxygen saturation ≤ 93%, PaO 2 /FiO 2 ratio ≤ 300 mmHg, shock (defined by the need of vasopressors) or respiratory failure requiring the admission to intensive care units (ICUs)  22.
Ethics. All serum samples collected from patients infected by SARS-CoV-2 were part of a declared Biobank (DC 2020-4028) in compliance with ethical directives. For ICU non-COVID-19 patients, samples were part of a declared Biobank (DC 2012-1704) in compliance with ethical directives. Informed consent was obtained from all participants. This study received approval from the national review board Comité de Protection des Personnes Ile de France XI (20027-60604, March 25th 2020) and fulfilled local requirements in terms of data collection and protection of data (RGPD/APHM 2020-80). This study was conducted according to the Declaration of Helsinki. Biological tests. aCL and aB2GPI levels were measured by ELISA with Cardiolisa Theradiag (Marne la Vallée, France) and Orgentec Diagnostica (Mainz, Germany), respectively.
PCR products were purified using ExoSAP-IT ® USB (Affymetrix, Thermo Fisher Scientific). Bidirectional sequence was performed using the fluorescent BigDye terminator method (Big Dye version 1. 1 Cycle Sequencing Kit, Applied Biosystems, Thermo Fisher Scientific) and sequence reactions were run on Applied Biosystems ABI Prism 3130 XL. Nucleotide and amino acid sequences were analysed using Seqscape software (version 2. 5, Applied Biosystems). UL40 sequences were determined using of the UL40 sequences from HHV5 (Merlin strain), as references (NCBI Reference Sequence: NC_006273. 2). The results of UL40 sequencing are reported in the supplemental Table  S1.
For the analysis of HV, since the infecting strains were unckown, 3 of the most common UL40 peptides (VMAPRTLIL, VMAPRTLLL, VMAPRSLLL) were used for detection assays. A FMO condition (Fluorescence Minus One; all labelled-markers except one) without tetramer was performed for each sample as a negative control. Data acquisition was performed using BD LSR Fortessa ™ X-20 and BD CANTO II ™ and analyses were performed using BD DIVA ™ Software v8. 0 (BD Biosciences). Compensations were made by using anti-mouse k chain Ab-coated beads (anti-mouse Ig, k chain/negative control compensation particles set, BD Biosciences) incubated with corresponding mAb at the same concentration during 15 min at RT. Gating analysis strategy is depicted in (Supplemental Figure  S2 ) and was identical for all samples.
1, Thermo Fisher, Courtaboeuf, France) and APC-Fire750 anti-TCRgd2 (clone B6, Biolegend), PE-anti-CD158 (clone HP-MA4, Biolegend, San Diego, CA, USA), BV785-anti-PD-1 (clone EH12. 2H7, Biolegend), BV570-anti-CD4 (clone RPA-T4, Biolegend), FITC-anti-CD57 (clone HNK-1, Biolegend), BV510anti-CD3 (clone OKT3, Biolegend), BUV395-anti-CD45RA (clone 5H9, BD Bioscience) BV805-anti-CD8 (clone SK1, BD Bioscience), BUV737-anti-CD56 (clone NCAM16. 2, BD Bioscience) and BUV496-anti-CD16 (clone 3G8, BD Biosciences) mAbs. Cells were incubated with anti-NKG2C mAb before CD94 blockage to avoid interference due to CD94 blocking. The fluorescence intensities were then analyzed using SpectroFlo ™ software version 2. 2. 0 (Cytek Biosciences). The frequency of major immune cell populations was determined using FlowJo ™ Software v10 (BD Biosciences) based on manual gating strategies as we reported (23) and as shown in the Supplemental Figure  S3.
PBMC were washed twice in PBS before fluorescence analysis. The fluorescence intensities were measured with a 5-laser Cytek Aurora ™ spectral flow cytometer (Cytek Biosciences) using SpectroFlo ™ software version 2. 2. 0 (Cytek Biosciences). Cell division was quantified using Flowjo ® after gating on live CD3+ gdTCR-CD8+ tetramer positive (tet + ) or negative (tet -) T cell populations as depicted on Supplemental Figure  S2. For the analysis of cytokine production and effectors of cytotoxicity, PBMC were incubated for 4h in the presence of phorbol 12-myristate 13-acetate (PMA) and ionomycine (Cell Stimulation Cocktail, eBioscience ™ ) purchased from Sigma-Aldrich (St-Louis, MI, USA) with (for intracellular staining of cytokines and granzyme B) or without (for CD107a staining) brefeldin A and monensin in the presence or absence of HLApeptide tetramers.
Cell culture, in vitro HCMV infection and mRNA analyses We generated gene expression data from MRC-5 and primary human endothelial cells (EC) isolated from 5 individuals as we described (24); both cell types are commonly used in HCMV infection models. MRC-5 lung fibroblasts were purchased from the ATCC (CCL-171, Manassas, VA, USA) and grown in RPMI (Gibco) supplemented with 5% fetal calf serum (FCS, Gibco). Human primary vascular ECs were isolated by collagenase digestion as we previously reported (24) and used between passages 2 and 5. ECs were cultured in Endothelial Cell Basal Medium (ECBM) supplemented with 5% FCS, 0. 004 mL/ mL ECGS/Heparin, 0. 1 ng/mL hEGF, 1 ng/mL hbFGF, 1 µg/mL hydrocortisone, 50 µg/mL gentamicin and 50 ng/mL amphotericin B (C-22010, PromoCell, Heidelberg, Germany).
Statistical analyses Data are expressed as means ± SD, or as medians ± interquartile range between Q1 and Q3, or percentages. Appropriate statistical analyses were performed using GraphPad Prism TM Software (GraphPad, San Diego, CA, USA) or R and the web application FaDa (https://github. com/danger-r/FaDAapp) when indicated. For comparisons of groups Fisher exact test, chi-square test, Mann-Whitney U-test, ANOVA, or 2-sided paired t test were used as appropriate. A p-value <0. 05 was considered to represent a statistically significant difference.
Acknowledgments The authors thank the  Recombinant Protein Facility (P 2 R, Structure Fedeŕative de Recherche "Francois Bonamy", Nantes)  for the production of pHLA-E UL40 -and pHLA-A*02 pp65monomers. The authors also thank the  Etablissement Francais du Sang (EFS, Pays de la Loire, Nantes, France)  and the  Centre de Ressources Biologiques  ( CRB, CHU Nantes, France ) for blood sample collection and harvesting. Figure 7 has been created using BioRender. com.
Automated segmentation of new multiple sclerosis (MS) lesions in D MRI data is an essential prerequisite for monitoring and quantifying MS progression. Manual delineation of such lesions is time-consuming and expensive, especially because raters need to deal with D images and several modalities. In this paper, we propose Pre-U-Net, a D encoder-decoder architecture with pre-activation residual blocks, for the segmentation and detection of new MS lesions. Due to the limited training set and the class imbalance problem, we apply intensive data augmentation and use deep supervision to train our models e ectively. Following the same U-shaped architecture but di erent blocks, Pre-U-Net outperforms U-Net and Res-U-Net on the MSSEG-dataset, achieving a Dice score of. % on new lesion segmentation and an F score of.