dataesr/scientific-paragraphs-categorization huggingface dataset:
Whole-genome metagenomic diversity with phylogeny As with the detection of microorganisms and their abundances, diversity is a key parameter in the analysis of microbial communities. The use of phylogenetic information in calculating this diversity for microbial samples was introduced in the form of UniFrac analysis. UniFrac uses the distances in a phylogenetic tree generated using 16s rRNA genes to estimate overall genetic diversity. While tools such as Unifrac, for integrating phylogenetic information, are easily applicable to 16s molecules, the same cannot be said for the analysis of whole-genome shotgun metagenomic sequencing. However, we found that with a defined set of genomes used to build our custom database, we could also construct a phylogenetic tree using 16s rRNA genes from these same representative sequences.
species present in the artificial samples. Colors correspond to: Orange: Kraken2 with CustomDB-species, Blue: Kraken2 with Cus-tomDB-genus, Red: Kraken2 with microbial 'fatfree' database, Green: MetaPhlAn3, Yellow: Ground Truth. (B) Heatmap of the base 2 logarithmic differences in relative abundance of the same 100 species between the methods compared to ground truth. Colored in red are the species that are underrepresented or absent in the methods' profiles. Colored green are the species that are overrepresented.
______________________________________________________________________________ We were able to identify and download a combined 10 202 16S rRNA gene sequences, from the SILVA and NCBI nucleotide database, out of a total of 13 610 bacteria species. MAFFT (Multiple Alignment using Fast Fourier Transform) was used to align the sequences and RAxML (Randomized Axelerated Maximum Likelihood) was subsequently employed to generate the phylogenetic tree. Construction of the 16s rRNA gene tree requires approximately seven days of computational time. The placement of the other 3 408 species is described in the Methods section. Briefly, we identified the Most Recent Common Ancestor (MRCA) and determined position of the new leaf node by maximizing purity and inclusiveness of the target species, exemplified in Figure  S2.
However, when Faith's phylogenetic diversity metric was used, a calculation which does account for phylogenetic distances in the calculation of diversity, a significant difference was identified (Mann -Whitney-U with FDR p-value = 1. 84-18). We performed a similar comparison of β-diversities, which measure the differences in community composition between samples. Pairwise comparisons are performed in order to calculate a distance matrix for all samples. Analysis of metagenomic samples commonly uses Bray-Curtis dissimilarity as a mean of calculating distance. This measurement handles sparce datasets with many zeros while returning a bounded range of values between zero and one. Bray-Curtis dissimilarity integrates counts but not phylogenetic information. Figure  4C  displays a plot of Bray-Curtis dissimilarity β-diversities for LD-18 and HD-18 samples.
An Improvement over large general database for metagenomic The analysis of metagenomic samples, and particularly samples from clinical studies, relies on the correct identification of short sequencing reads through comparison against sequences deposited in public databases. While the expansion of microbial databases has allowed for the identification of a larger proportion of reads in metagenomic studies, this advance has not been without challenges. Increased database size inevitably leads to fewer unique markers for precise identification of species and strains. Not surprisingly, the species of most interest, including key community players or potential pathogens, are often the most-studied and therefore the most overrepresented in databases. The over-representation of commonly identified species has been shown to contribute to biases in analysis  [9].
Even tools designed to aid researchers in the analysis of human microbiota samples, such as MetaPhlAn, can be affected by biases, in abundance estimations. Recent work identifying Klebsiella pneumoniae/Kocuria rosea as a possible additional community state type (CST), reinforced our previous experience in quantification potential pathogens in the vaginal microbiota  [4, 33]. Results in this work demonstrate further potential for biases in quantification for microbiota samples. For the Faecalibacterium genus (Figure  2 ), the most intensively studied and sequenced species, Faecalibacterium prausnitzii, is readily detected. However, recently isolated species (e. g. Faecalibacterium sp. I3389 and Faecalibacterium sp. I4384), which could be important for novel metabolic functions, are only detected using our custom database  [32].
Pseudoflavonifractor capillosus, a species associated with the used of proton pump inhibitors, was recently reclassified, and is another apt example where a custom database build at the genus level is the only method able to provide accurate quantification  [34, 35]. Our results confirmed that building the custom database at the genus level offered the best precision and sensitivity for most use cases. Building a custom database from a fixed set of genomes, stored in the prerequisite file, has allowed for the inclusion of significant additional functionality. The assessment of diversity in microbial populations is often critical to understanding function and stability in a given environment  [36]. We have shown here that incorporating taxonomic distances in α-and β-diversities contributes significantly to the power of the analyses being performed.
We have described here the use of the 16S rRNA genes to build a tree for the calculation and use of taxonomic information. This taxonomic information is otherwise difficult to assess and is routinely ignored in standard whole-genome metagenomic analysis. A further example of added functionality is in the improved accuracy of quantification of the taxa present in sequenced samples through appropriate normalization of data. Bracken normalization, used to correct read quantification based on Kraken mapping, is performed based on a correction file built from a custom database in comparison to its component genomes. This type of correction is especially pertinent in human microbiota studies where correct quantification of closely related species can mean the difference between pathogen and commensal  [37, 38].
Perspectives and improvements The decision to build the Moonbase custom database from a predetermined set of species presents challenges in keeping data updated to reflect the latest results in sequencing and in taxonomic assignments. The advantages of a custom database relay on having access to the most up-to-date sequencing data and taxonomic annotations. This can only be achieved through regular updates. The custom databases that are generated by Moonbase are ultimately dependent on the composition of the individual samples, as determined by the integrated MetaPhlAn component. As such, it is important that future updates to the MetaPhlAn analysis pipeline be reflected in the Moonbase pipeline. In constructing the database, we found one of the most challenging tasks to be resolving the often-conflicting taxonomic identifications across MetaPhlAn3, Kraken2, NCBI and SILVA databases.
Our ultimate solution was to include a dedicated file to makes the necessary correspondence for all possible genomes that could be included in the database and 16s tree. While preparing an update to the recently published MetaPhlAn4 database, we will explore integration of the species and alignments from the All-Species Living Tree Project (LTP)  [39]. LTP includes both Bacterial and Archaeal species, and we plan to include Archaea in a future version of the tool. Although the number of archaea in the human microbiota is small, methanogens have been isolated from several sites and been shown to play an important role in metabolism in the intestinal microbiota  [40, 41]. It is our hope that standardization and simplification of the update process will allow us to generate annual updates to the Moonbase tool.
Conclusions Our development and in-depth testing of the Moonbase pipeline underscores the importance of using properly tailored databases appropriate for the types of metagenomic analyses being performed and the environments being studied. This observation is particularly critical for capturing less-studied but potentially significant microbial species in complex communities. The Moonbase custom database not only enhances the precision and sensitivity of species identification but also allows for nuanced analyses like taxonomic distance-based diversity assessments. As sequence databases push into tera-and peta-base scales, project-specific databases such as Moonbase, capable of harnessing and focusing available data for researchers, will become an ever more important resource.
Quantitative real time RT-PCR analysis for gene expression Gene primers were designed from porcine genes considering the intron-exon organization from the Ensembl database. Gene primers were preferentially designed in the 3′ UTR (last 1000 base pairs) or the exons using LightCycler Probe Design2 software (Roche Diagnostics). The primer pairs were con rmed using Primer3 (http://frodo. wi. mit. edu/primer3/). Sequences are available in Supplementary Data 4. RNA samples were reverse transcribed from 2 µg as previously described  [97]. The resulting cDNA samples were completed to 100 µl. The for each gene consisted of four/six replicates per genotype, sex and gestational day, calibrator sample, a serial diluted pool and negative controls. The Pfa method  [99]  was applied to calculate the relative expression of each gene as described by Bonnet et al.
Acknowledgments This study was supported by the  ADEREM (Association pour le Développement de la Recherche Médicale au CHU de Marseille) , the  Association Française contre les Myopathies (AFM-Téléthon)   MoThARD program  and by  Pfizer. TTM received funding from  France Excellence Scholarship  of the  French Embassy in Vietnam , from the  French Society of Pediatric Endocrinology and Diabetology (SFEDP)  and from the  Marseille Rare Disease (MarMaRa) Institute of Aix-Marseille University. The authors wish to thank  Frederique Magdinier ,  Natacha Broucqsault  and  Claire El Yazidi  from the  Marseille Medical Genetics  (MMG) cell reprogramming & differentiation facility (MaSC);  Sébastien Courrier , from the MMG microscopy platform;  Valerie Delague ,  Catherine Aubert ,  Christel Castro  and  Camille Humbert  from  MMG's Genomics and Bioinformatics (GBiM ) platform;  Carole Siret  and  Mathieu Fallet  from the  Centre d'Immunologie de Marseille-Luminy (CIML );  Ivo Vanzetta  and  Alberto Lombardini  from the  Institut de Neurosciences de la Timone  (INT) microscopy platform, and  Laurie Arnaud  and  Emmanuel Nivet  from the  Institut de Neurophysiopathologie (INP), all in Marseille , for their expert assistance, advice or reagents.
Briefly, after paraffin removal, endogenous peroxidase of the intestinal tissue was inhibited and goat serum was applied for 20 min to block potential non-specific binding sites of Ig. Slides were washed twice with PBS, 0. 1% Tween 20, and 1% BSA (PTB) between each step. Slides were incubated for 1 h with rabbit anti-AvBD2 polyclonal antibodies (1:2,500 dilution in PTB). These purified anti-AvBD2 IgG were obtained from rabbit antiserum toward natural AvBD2 (available on demand), and were controlled by Western blot and by ELISA as described in a database (doi:10. 57745/OYOAWF). Slides were incubated 30 min with secondary antibodies peroxidase-conjugated goat anti-rabbit Ig (Histofine simple stain AP, Nichirei Biosciences, Japan) diluted at 70% in goat serum. Peroxidase substrate (DAB, Labvision, Sweden), giving a brown staining after enzyme reaction, was added for 10 min.
It can be first noticed that there is a high variability in % AvBD2 between individuals for both lines: from 0 to 4% with a mean value of 1. 37 § 1. 63% for chicks of line L, and from 0 to 3% with a mean value of 1. 33 § 1. 20% for chicks of line S. However, AvBD2 level is not correlated with the quality score value (data not shown; data available in a database at doi:10. 57745/OYOAWF). This result indicates this defensin cannot be selected as a potent biomarker of the robustness of chicks. However, it can be observed from the linear regression a significant negative correlation between these immune parameters in the S line chicks. A hypothesis explaining this result relies on an increased immunization by opportunistic bacteria crossing the epithelium of potentially fragilized S chicks, in conjunction with a low mucosal AvBD2 level unable to eliminate bacteria reaching the blood stream.
ACKNOWLEDGMENTS The authors also wish to thank  Marie-Claire Blache  ( UMR PRC, Centre INRAE Val de Loire, Nouzilly, France ) for assistance in image analysis. This work was financially supported by a grant  CAS-DAR RT  ( 2018-2021 ) from the  Minist ere de l'Agricuture et de l'Alimentation (France)  for the project number  1727  " Chick 'Tip" coordinated by  A. Travel  ( ITAVI, Nouzilly, France ).
Four models of various complexity were fitted to each dataset: Additive (only the additive terms Ai were considered), Dominance (Ai and Dij), Epistasis (Ai and AAij), and Full model (Ai, Dij, and AAij). The four models were compared by a model selection procedure based on the Akaike Information Criterion  (Anderson & Burnham, 2004) ; AIC differences larger than 2 units were considered as substantial differences between models. Models were fit independently on Weight and Silique number; and both genetic differentiation levels (Lineage and Population) were considered.
Acknowledgements We acknowledge the  MRI facility , member of the national infrastructure France-BioImaging supported by the  French National Research Agency  ( ANR-10-INBS-04 ), the  Proteomics Platform (PPM) of BioCampus Montpellier , and the  NGS unit of Vienna BioCenter Core Facilities. This work was supported by an  Advanced Grant  from the  "Investissements d'avenir" program   Labex EpiGenMed  ( ANR-10-LABX-12-01 ) and an " Accueil de Chercheurs de Haut Niveau " grant ( ANR-16-ACHN-0017 ) from the  French National Research Agency  to KM, and a " Fin de these" program  fellowship from  Fondation pour la Recherche Médicale (FRM)  to SS.
The need for adjuvants for Shigella vaccines to ensure protective efficacy among children in In subsequent discussion, the consensus preference for new Shigella vaccines was an adjuvant that has a large safety database and ideally one included in a pediatric licensed vaccine formulation. It was uncertain whether an adjuvant other than an aluminum salt would be safe and efficacious in the target population. Though this will partly be answered by current studies of Shigella vaccine formulations in African children, the group appreciated the lost opportunity with delaying testing of alternative adjuvants until new clinical data are available. Participants considered it valuable to evaluate new Shigella candidate vaccine formulations with novel adjuvants head-to-head with aluminum salt and unadjuvanted formulations in preclinical animal models, while appreciating some adjuvants might not have commercialscale processes.
Clinical and microbiologic endpoints for Shigella vaccine efficacy studies in children in LMICs Organizers: Patricia Pavlinac (University of Washington); Richard Omore (Kenya Medical Research Institute); Elizabeth T. Rogawski McQuade (Emory University); Chad Porter (NMRC) Several candidate Shigella vaccines are advancing toward necessary efficacy evaluations in children in LMICs. In this workshop, presenters reviewed data and recent consensus statements regarding endpoints for pivotal efficacy studies of Shigella vaccines for this population. Various clinical and microbiological endpoints were examined with consideration of the sample size implications. The framework for the discussion was that a primary goal of a pivotal efficacy trial should be to estimate the efficacy of a Shigella vaccine administered to young children against diarrheal episodes caused by antigenic types contained in the vaccine.
The inflammatory markers were measured by ELISA assays. The intracellular oxidative stress (ROS) in microglial cells was measured using Deep Red CellROX probe. The cell migration was examined by wound healing using the Oris Cell migration assay. Results: These data showed the ability of A. montana (mother tincture and mainly 1C dilution) to significantly reduce TNFα production in inflamed macrophages compared with vehicle (control). They significantly reduced both IL-6 and MCP-1 in inflamed human microglial cells and significantly decreased COX-2 expression in inflamed murine fibroblasts. Moreover, A. montana mother tincture reduced the cell migration whereas 9C dilution significantly enhanced the migration of fibroblast cells compared with vehicle. The expression of ICAM-1 was significantly reduced with A.
Intracellular reactive oxygen species (ROS) level. The level of reactive oxygen species (ROS) was assessed using the cell-permeant CellROX™ Deep Red Reagent (Invitrogen C10422) which is a fluorogenic probe upon oxidation that serves as a direct measurement of ROS levels. The microglial cells were stained with 10 μM CellROX™ Deep Red reagent for 30 min before the end of the treatments, then washed with DPBS and fixed with 3. 7% formaldehyde solution (37wt. % in H 2 O stock) (Sigma Aldrich-Merck F1635) in DPBS before image acquisition. For each well, at least 3 images were randomly acquired with identical exposure parameters using an inverted fluorescence microscope (Zeiss, Axio Observer Z1) equipped with Hamamatsu camera (Orca Flash 4. 0) and a LD Plan-Neofluar 20x objective. The quantification of fluorescence was performed using open-source ImageJ software with a home-made specific plugin developed by Gly-CRRET lab at University Paris-Est Creteil.
Statistical analysis Statistical analysis was performed using GraphPad Prism software (version 7. 00). Each result is representative of at least 3 independent experiments. The Shapiro Wilk test for normality and Bartlett's test for homoscedasticity were used. Multiple comparisons were performed using a parametric 1-way ANOVA followed by the Dunnett's post-hoc test or using a non-parametric Kruskal-Wallis test followed by the Dunn's post-hoc test to show significant differences against vehicle. The p values were defined as follows: p < 0. 05*; p < 0. 01**; p < 0. 001***; p < 0. 0001****. To validate each of the models of inflammation or migration, the same statistical analysis was performed as described above against inflamed group or cell culture medium with 2% FBS with the positive controls (anti-inflammatory reagent or cytochalasin D) and the untreated group or PDGF bb, respectively.
Acknowledgements We acknowledge the contributions of the CELPHEDIA Infrastructure "http://www. celphedia. eu/", especially the center  AniRA-PBES in Lyon. We are grateful to  Gilles Carpentier  ( Gly-CRRET, Université Paris-Est Creteil ) for optimizing image analysis method with the development of a specific plugin for ImageJ. We thank  Dr Stéphanie Chanut  for help creating the graphical abstract. The authors thank  Jo-Ann Elicia West , MSc, EI (http://www. jew estms. com), an independent publication consultant in  Cartigny L'Epinay, France , for providing medical writing, language editing and manuscript submission support, which was funded by  Laboratoires Boiron, Messimy, France  in accordance with Good Publication Practice (GPP3) guidelines (http://www. ismpp. org/gpp3). The listed authors have authorized the submission of their manuscript via third party and approved all statements or declarations.
The phenotype cage contained a shelter (adjusted in height because of the cannula on the head) with nesting material. The movement of the mice was continuously tracked by EthoVision XT 13 software for calculation of the distance moved and time spent in the different areas of the cage (Fig. S1 ). As tracking was lost sometimes when mice were in their shelter, we calculated the total shelter time as sum of the tracked time in their shelter (hidden zone) and the time the mice were not detected. To assess anxiety, we used the light spot test adapted from Aarts et al. (Aarts et al. , 2015). During the third dark period, the light incorporated in the phenotyper cage topunit above the food area was put on from 20. 15 to 21. 15 h as an anxiety stimulus. Outcome measures were generated per hour for day/night 1 and day/ night 2 to investigate spontaneous behaviour.
cDNA input was equivalent to 12. 5 ng RNA per reaction. Droplets were generated with the Automated Droplet Generator (Bio-Rad). The PCR reaction consisted of 10 min 95 • C initiation; 40 cycles of 30 s 94 • C, 1 min 58 • C; final 10 min 98 • C, all with a ramp rate of 2 • C/s. After the PCR reaction, droplets were counted with the QX200 Droplet reader (Bio-Rad) and analysis was done with the QuantaSoft Analysis Pro software (Bio-Rad) setting a manual threshold of 1500 for both channels. Exon skip efficiency was calculated by dividing the concentration of skipped hHTT RNA by the sum of concentrations for skipped and unskipped hHTT RNA. For each sample, the average of two ddPCR runs was calculated.
RNAseq reads were processed using the opensource BIOWDL RNAseq pipeline v5. 0. 0 (https://zenodo. org/record/5109461#. Ya2yLFPMJhE) developed at the LUMC. This pipeline performs FASTQ preprocessing (including quality control, quality trimming, and adapter clipping), alignment, read quantification, and optionally transcript assembly. FastQC was used for checking raw read QC. Adapter clipping was performed using Cutadapt (v2. 10) with the default settings. RNAseq reads' alignment was performed using STAR (v2. 7. 5a) on a customized mouse reference genome where GRCm39 mouse reference genome is combined with the Homo sapiens huntingtin (HTT), transcript variant 1 (NM_001388492). The gene read quantification was performed using HTSeq-count (v0. 12. 4) with setting "-stranded = yes". The gene annotation used for quantification was Ensembl version 106 with an added entry for the HTT transcript (NM_001388492).
Differential gene expression analysis was performed in R (v4. 0. 2) using DESeq2 (v1. 30. 1) on separate data sets containing the samples of two groups to be compared, selecting genes with >5 counts per million for at least 7 samples. Differential expression was performed using the DESeq-function with default settings and results were extracted with disabled independent filtering. Genes with an adjusted P-value (Benjamini-Hochberg) of <0. 1 were considered significantly differentially expressed. Official gene symbols were assigned to ENSEMBL identifiers using the getBM function of biomaRt package (v 2. 46. 3). Vsttransformed data was visualized using pheatmap (v1. 0. 12) applying scaling per row. For pathway assessment, overrepresentation analysis was performed using GeneTrail 3. 2  (Gerstner et al.
No enlargement of the lateral ventricle was observed, a side effect described upon administration of for instance the gapmer AON tominersen  (Tabrizi et al. , 2022). However, scrambled AON seemed to cause general brain enlargement that, to our knowledge, has not been described before. Most studies involving AON administration include either a vehicle or scrambled control and hence do not allow assessment of the scrambled AON. Our data for both gene expression and brain anatomy showed a significant effect of scrambled AON, emphasizing the importance of including scrambled AONs in treatment studies to better understand the effect of exposure of the brain to AON compounds, regardless of their sequence. Our study was limited by the mild phenotype present in YAC128/B6 mice, which did not show striatal neuronal death reflected by DARPP32 expression.