dataesr/scientific-paragraphs-categorization huggingface dataset:
While this needs to be further investigated, it might also represent a source of potential novel biocontrol agents that can be safely used to extend the shelf life of minimally processed vegetables. Storage light conditions only influenced the total bacterial counts and chlorophyll content, while no effect was observed for any other parameter we measured or within the metabarcoding dataset. Our previous study  (Zappia et al. , 2019 ) investigated a similar question, suggesting also that storage light condition influenced the total bacterial count, with higher counts when the product was exposed to light. Similar results were observed also on asparagus  (Sanz Cervera et al. , 2009) , cauliflower and broccoli  (Olarte et al. , 2009). The presence of light might trigger microbial growth through a series of mechanisms, but we speculate that this is driven by small increases in leaf's surface temperature, helping microorganisms to grow faster.
Polymorphic genomic inversions are chromosomal variants with intrinsic variability that play important roles in evolution, environmental adaptation, and complex traits. We investigated the DNA methylation patterns of three common human inversions, at 8p23. 1, 16p11. 2, and 17q21. 31 in 1,009 blood samples from children from the Human Early Life Exposome (HELIX) project and in 39 prenatal heart tissue samples. We found inversion-state specific methylation patterns within and nearby flanking each inversion region in both datasets. Additionally, numerous inversion-exposure interactions on methylation levels were identified from earlylife exposome data comprising 64 exposures. For instance, children homozygous at inv-8p23. 1 and higher meat intake were more susceptible to TDH hypermethylation (P = 3.
Results Frequency of inversions at 8p23. 1, 16p11. 2, and 17q21. 31. We analyzed data from the Human Early Life Exposome (HELIX) project, a multicenter European cohort (Spain, United Kingdom, France, Lithuania, Norway, and Greece). This project comprises 1301 children with genomic, transcriptomic, epigenomic, and exposome data  36. HELIX has the goal of characterizing the exposome during early life and evaluating its relationship with molecular signatures and child health outcomes. The genomewide blood DNA methylation and blood cell transcriptome were measured at the ages between 6 and 11. From this dataset, we selected children with genetic and methylation data. We used Peddy  37  to estimate major population ancestry groups and individuals of European ancestry were kept in the analysis, resulting in a total of 1009 children included in the analyses.
5. 9E-08 The table illustrates the top 45 significant associations of CpG sites (±1 Mb) and the interactions of three common human inversions (inv-8p23. 1, inv-16p11. 2 and inv-17q21. 31) with exposures in the HELIX exposomic data. The full table is available in Supplementary Data 5. The first column indicates the exposure involved in the interaction (the description of the exposures is detailed in Supplementary Data 4). Exposures are described by their families and the period which they were measured. The inversion column describes the inversion interacting with the exposure. CpG sites are described by their name, location, and gene symbol (written in italics), when mapped to a gene. The Effect column represents the estimate of the interaction effect and the P-value column its nominal level of significance.
We observed that inversions significantly interacted with a wide range of exposures affecting DNA methylation across the inverted segments. Therefore, inversions are common copy-neutral polymorphisms that seem to be important contributors to gene-environment interactions, whose detection remains elusive in genomic and high-dimensional exposure data  [56] [57] [58]. We analyzed data from an exposome study, covering a wide range of exposure families believed to affect children's development. The exposome data included environmental exposures but also exposures from the diet, urban exposome, and chemical compounds  31. In total, we assessed 64 exposures (7 during pregnancy and 57 at 6-11 years of age) grouped in 12 families. We observed inversion interactions in most of the exposure families, most prominently in metals, diet, phenols, and organochlorines.
Molecular phenotypes Inversion genotype data. DNA was obtained from buffy coat collected in EDTA tubes at 6-11 years of age. Briefly, DNA was extracted using the Chemagen kit (Perkin Elmer) in batches of 12 samples. Samples were extracted by cohort and following their position in the original boxes. DNA concentration was determined in a NanoDrop 1000 UV-Vis Spectrophotometer (ThermoScientific) and with Quant-iT™ PicoGreen® dsDNA Assay Kit (Life Technologies). Genome-wide genotyping was performed using the Infinium Global Screening Array (GSA) MD version 1 (Illumina) at the Human Genomics Facility (HuGe-F), Erasmus MC (www. glimdna. org). Genotype calling was done using the GenTrain2. 0 algorithm based on a custom clusterfile for 692,367 variants implemented in the GenomeStudio software. Annotation was done with the GSAMD-24v1-0_20011747_A4 manifest, SNP coordinates were reported on human reference GRCh37 and Source strand (Forward strand report in GenomeStudio).
The initial dataset consisted of 1,397 samples and 692,367 variants. Samples with discordant sex, duplicated, contaminated (high heterozygosity), and relatives (IBD > 0. 185) were filtered out. SNPs with variant call rate <95%, minimum allele frequency <1%, and HWE Pvalue (1 × 10 -6 ) were excluded. Major population ancestry groups were estimated using Peddy  37  and only individuals of European ancestry were kept in the analysis. The final dataset consisted of 1,009 samples and 509,344 SNP variants. From this dataset, we selected inversions that could be genotyped with scoreInvHap and had more than 10 CpG sites in the inversion region: inv-8p23. 1, inv-16p11. 2, and inv-17q21. 31 (Table  2  and Supplementary Tables  2  and 3 ). DNA methylation. The DNA was obtained using the same methodology as for genetics data.
DNA methylation was assessed using the Infinium Human Methylation 450 beadchip (Illumina), following the manufacturer's protocol. Minfi R package  72  was used for the preprocessing of DNA methylation data. MethylAid package  73  was employed to perform the first quality control of the data. Probes with low call rates were filtered following the guidelines of Lehne et al. 74. The functional normalization method was further applied, including Noob background subtraction and dye-bias correction  75. Several quality-control checks were performed: sex consistency using the shinyMethyl package  76  , consistency of duplicates, and genetic consistency for the samples that had genome-wide genotypic data. Duplicated samples and control samples were removed, as well as probes that measure methylation levels at non-CpG sites  77.
Probes that cross-hybridize were excluded. Moreover, we used InfiniumAnnotation from https://zwdzwd. github. io/ InfiniumAnnotation to filter probes where 30-bp 3′-subsequence of the probe is nonunique, probes with INDELs, probes with extension base inconsistent with specified color channel (type I) or CpG (type II) based on mapping, probes with a SNP in the extension base that causes a color-channel switch from the official annotation, and probes where 5-bp 3′-subsequence overlap with any of the SNPs with global population frequency higher than 1%. Consequently, the number of CpG probes analyzed was 371,533, initially available for 1192 subjects. We then used Combat algorithm to remove the batch effects supported by the slide. Methylation levels were expressed as beta values (average methylation levels for an individual, between 0 for a never-methylated CpG site and 1 for an alwaysmethylated CpG site) and CpG sites were annotated to genes by Illumina HM450 manifest file (version 1.
2). We discarded the subjects without inversion-status data and without European ancestry based on genomic data, resulting in 1009 individuals for the analysis. For each inversion, we selected the CpG sites contained in the inversion region ±1 Mb, resulting in 848 CpG sites for inv-8p23. 1, 401 for inv-16p11. 2, and 666 for inv-17q21. 31 (Table  2  and Supplementary Table  2 ). Blood cell-type proportions were estimated from methylation data according to Houseman et al. algorithm  78  and Reinius reference panel  79. Gene expression. At the period of clinical examination that took place when children were between 6 and 11 years old, RNA was extracted from whole blood collected in Tempus tubes. Samples with RIN > 5 were considered. Gene expression was assessed using the GeneChip ® Human Transcriptome Array 2.
0 (HTA 2. 0) (Affymetrix, USA) at the University of Santiago de Compostela (USC, Spain), following the manufacturer's protocol. Samples were randomized and balanced by sex and cohort within each batch. Data were normalized at the gene level with the GCCN (SST-RMA) algorithm, and batch effects and blood cell-type composition were controlled with two surrogate variable analysis (SVA) methods, isva  80  and SmartSVA 81 , during the differential expression analyses. Gene expression values were log2 transformed, and annotation of transcript clusters (TCs) to genes was done with NetAffx annotation (version 36). Genes without Gene Symbol annotation or with call rate <20% were removed, restricting to 25,255 genes. From this number of genes, we selected those within the inversion regions ±1 Mb (inv-8p23.
1: 83 genes; inv-16p11. 2: 58 genes; inv-17q21. 31: 61 genes). From a total of 1158 subjects that had transcriptomic data, we selected individuals with European ancestry (based on genomic data) who had available inversion-status data and celltype proportions assessed from methylation data, resulting in a total of 790 subjects (Table  2  and Supplementary Table  1 ). Exposome assessment. The assessment of the exposome has been previously published  82. In our study, we included 7 exposures assessed during pregnancy and 57 exposures assessed during childhood at age 6-11 y (Supplementary Data 4). These 64 exposures were selected from the entire exposome dataset according to the number of missing values they had. We did not include exposures that had more than 10% of missings in the whole dataset or with more than 20% missing in one or more cohorts.
Air pollution, natural spaces, and building environment quantification were assessed during the year before child examination or during pregnancy by environmental geographic information systems (GIS). Tobacco smoke and diet were evaluated by questionnaires. Missing values for all exposures were imputed using the method of chained equations  84  , as described in detail elsewhere  82. Most exposure variables were transformed as described in Supplementary Data 4. Fetal heart-tissue samples. Human fetal samples from 40 fetuses of terminated pregnancies due to a major congenital heart defect (gestational age 21-22 weeks in all cases) were obtained from Biobanc Hospital Universitari Vall d'Hebron (HUVH) in a related project addressed to define the genetic and epigenetic basis of congenital heart defects  38.
Informed consent was obtained from parents and the study was approved by the institutional ethics committee. Heart-tissue DNA was obtained following necropsy using standard procedures, whole-genome sequencing was performed at Centogene, and DNA methylation was measured with Infinium MethylationEPIC  38. After quality control, one sample was discarded (Supplementary Table  4 ). During the preprocessing of methylation data, probes with a single-nucleotide polymorphism (SNP) with overall population frequency higher than 1% based on InfiniumAnnotation from https://zwdzwd. github. io/InfiniumAnnotation were removed. Selecting the CpG sites within the inversion region ±1 Mb, we analyzed 898 CpG sites from inv-8p23. 1, 409 from inv-16p11. 2, and 698 from inv-17q21. 31.
Statistics and reproducibility Genome-wide analysis. Differential methylation analyses were performed using MEAL Bioconductor's package  85. We performed a differential mean analysis The table shows the length in kb, the mapping coordinates hg19 ±1 Mb, the frequency of all the inversions obtained from scoreInvHap  11  , and the number of samples and features used in transcriptome and methylome analysis for each inversion. (DMA) on inversion genotypes using the function runDiffMeanAnalysis that calls limma  86. Based on a priori knowledge, we adjusted all the regression models by sex, age, population stratification (using the first 10 principal components of the GWAS that highly correlated with cohort), and cell type (Supplementary Tables  1  and 2 ). To correct for the variance between cohorts, we performed this analysis for each cohort separately, and we meta-analyzed the results using the function metagen from meta package  87.
Acknowledgements We are grateful to all the participating children, parents, practitioners, and researchers in the six countries who took part in this study. The study has received funding from the  European Community 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no  308333  ( HELIX  project), and the  H2020-EU. 3. 1. 2. - Preventing Disease Programme  under grant agreement no  874583  ( ATHLETE  project). The HELIX geno-.
Palmitate treatment alters circadian oscillations in primary human myotubes Primary skeletal muscle cells were synchronized, treated with palmitate or BSA-vehicle, and harvested every 6 h (Fig  1A ). The RAIN algorithm was used to determine rhythmic oscillations of genes and identified 37% of all transcripts as cycling  (Fig 1B). Genes cycling in the control condition, but not after palmitate treatment, were considered repressed by palmitate and represented 20% of all transcripts and >50% of cycling transcripts (Fig  1B ). Conversely, genes not cycling in the control condition, but cycling after palmitate treatment, were induced by palmitate and represented 11% of all transcripts. Genes cycling in both BSA-vehicle-and palmitate-treated conditions were considered unaffected by palmitate and only represented 6% of all detected transcripts  (Fig 1B).
Dysregulated lipid homeostasis is associated with metabolic diseases. Individuals with obesity exhibit elevated levels of circulating free fatty acids concomitant with disturbances in circadian rhythmicity  (Sardon Puig et al, 2020). To test whether obesity directly affects the acetylation of histones in skeletal muscle, the abundance of H3K27ac was measured in vastus lateralis biopsies from men with obesity versus normal weight  (Fig 3E and F). We found that the acetylation of H3K27 was unaffected by obesity in biopsies obtained in the morning after an overnight fast. In publicly available datasets, gene ontology pathways related to histone modifications were enriched in skeletal muscle biopsies obtained from participants before and after a meal rich in saturated fat  (Fig 3G). Conversely, pathways related to histone modifications were not significantly enriched in skeletal muscle obtained from participants after a meal rich in polyunsaturated fatty acids.
We found histone H3K27ac was associated with changes in genes involved in fatty acid metabolism, consistent with earlier reports in the pancreas and colon of diet-induced obese mice  (Li et al, 2014; Nammo et al, 2018). Conversely, histone H3K27ac was unaltered in skeletal muscle of men with obesity as compared to normal weight. Because the biopsies were taken in the morning, we cannot exclude the possibility that diurnal signaling of histone H3K27ac may differ between the groups. The biopsies were also taken in fasted individuals, and given that histone acetylation is transiently induced by fatty acids, our results may differ in fed individuals or in those after a high-fat meal. Nevertheless, our data suggest that lipid-induced changes, rather than obesity per se, may directly contribute to the metabolic dysregulation of histone H3K27ac observed in skeletal muscle.
RNA-seq reads (n ≈ 38. 5 M) from FASTQ files were quality-trimmed using Trim_Galore (v0. 4. 3) and aligned using STAR (v2. 5. 3a)  (Dobin et al, 2013)  with Ensembl human annotation (GRCh38, release 92). Gene features were counted using featureCounts  (Liao et al, 2014)  from the subread (v1. 5. 2) package and analyzed with edgeR  (Robinson et al, 2010). The logCPM (count per million) values for each gene were calculated using the limma's voom function while correcting for batch effect from participants using the duplicateCorrelation function  (Ritchie et al, 2015). For the time series data, each gene was normalized using the "scale" function in R. For each gene, data were centered by subtracting the mean value for that gene and scaling was done by dividing the centered data by the SD. Acetylated H3K27 chromatin immunoprecipitation and sequencing (ChIP-seq) Acetylated H3K27 ChIP-sequencing was performed as described  (Williams et al, 2020).
Processing of H3K27ac ChIP-seq data The quality of H3K27ac ChIP-seq samples was assessed using the FastQC software. One sample was of poor quality and had to be excluded. Quality was trimmed with Trimmomatic (v0. 32)  (Bolger et al, 2014)  on the same parameters to clip adapters to remove lowquality sequences using a minimum quality of 30, a sliding window of 5, and a minimum length of 40 bp. Reads were mapped to Homo sapiens reference genome using the Bowtie2 (v2. 3. 2-foss-2016b) aligner  (Langmead & Salzberg, 2012). Duplicate removal was performed using SAMtools (v1. 5-foss-2016b)  (Li et al, 2009) , and then, BAM files were subjected to peak count using the MACS2 software (v2. 1. 0)  (Zhang et al, 2008)  for broad peaks using a q-value of 0. 01 and a shift of 147 bp. Called peaks were quantified with featureCounts (v1.
6. 3)  (Liao et al, 2014)  and associated with closest genes using the RGmatch software  (Furio-Tari et al, 2016) , mapping regions to the transcriptomic start site and the promoter of the first exon. The resulting peak matrix was Reads Per Kilobase of transcript, per Million mapped reads (RPKM) normalized and batch-corrected using ComBat  (Johnson et al, 2007)  to correct for sequencing lane bias.
Bioinformatics analysis Time series samples were analyzed with the R package RAIN  (Thaben & Westermark, 2014)  to capture the rhythmic oscillations and determine peak times of the gene expression and acetylated regions. Rhythmicity was determined based on a 24-h longitudinal period. Genes and H3K27-acetylated regions were considered rhythmic when FDR < 0. 1. The limma R package  (Ritchie et al, 2015)  was used to determine differential gene expression and histone acetylation. The effect of time was blocked using a linear function to study the independent effect of palmitate. The effect of palmitate and obesity was considered significant when FDR < 0. 1. An enrichment of functional clusters was performed on significant genes (FDR < 0. 1) using clusterProfiler  (Yu et al, 2012). Results of the analyses are available in Supplemental Data 1.
Publicly available datasets The GEO repository was used to download transcriptomic data from biopsies obtained from men before or after a high-fat meal (GSE31901), from men before or after 3 d of a high-fat diet (GSE68231), or from men with obesity versus normal weight (GSE25462, GSE43760, GSE73034, and GSE73078). For the datasets comparing individuals with obesity versus normal weight, only men with either BMI < 25 (healthy) or BMI ≥ 30 (obesity) were selected to enable comparisons with the other studies. In studies assessing the effects of high-fat feeding and obesity, skeletal muscle biopsies were collected after an overnight fast. All studies were processed with similar pipelines using the oligo package in R v4. 2. 0. Gene ontology pathway enrichment was performed using clusterProfiler  (Yu et al, 2012)  on the top 2,000 genes in each study, ranked on FDR.
Acknowledgements The authors are supported by grants from the  Novo Nordisk Foundation  ( NNF14OC0011493  and  NNF17OC0030088 ),  EFSD/Novo Nordisk Foundation Future Leader Award  ( NNF21SA0072747 ),  Swedish Diabetes Foundation  ( DIA2021-641  and  DIA2021-645 ),  Swedish Research Council  ( 2015-00165  and  2018-02389 ),  KID- funding ( 2-3591/2014 ), the  Strategic Research Program in Diabetes at Karolinska Institutet  ( 2009-1068 ),  Marie Skłodowska-Curie Actions  ( European Commission ,  675610  and  704978 ), and  Novo Nordisk postdoctoral  fellowship run in partnership with  Karolinska Institutet. Additional support was received from the  Novo Nordisk Foundation Center for Basic Metabolic Research at the University of Copenhagen  ( NNF18CC0034900 ).
Experimental procedure and participants Online participants. The online test was advertised and shared on social networks, mainly through Twitter. It could be performed either on computers or on tactile devices. Before taking part in the experiment, participants had to read and accept a written consent and to declare to be at least 18 years old, in compliance with the local Ethical Committee that approved our research (under the reference CER-Paris-Saclay-2019-061). Data collection for the purpose of the study started on January 15 th , 2021 and ended on March 15 th , 2021, as planned ahead of the experiment. The link to the test was still running after that date, but the data were not included in the current work. Before taking the test, all participants answered a demographic questionnaire consisting in a series of single-answer questions about: country of origin, age, gender, number of previous participations in the task (if any) and the highest level of education attained.
The instructions and the questionnaire were available in six languages: English, French, Italian, Spanish, Portuguese and Chinese. 3943 subjects participated and completed the online experiment (the ones that did not complete the task were not included in the data analysis). 2409 of them declared being women, 1294 men, 82 non-binary, 20 "other" than the previous ones, and  138  preferred not to answer. The average age was 28. 8 ± 9. 6 years. Himba. 87 Himba participants (39 women and 48 men) were recruited in small villages in the Kunene region, Northern Namibia. Most Himba do not know their age. Participants' age, 21. 1 ± 9. 4 years, was evaluated by local research assistants who were bilingual Namibians (in Otjiherero and English). Those assistants also instructed each participant, in their native language (Otjiherero), about how to perform the task on a tablet.
g. , 4 groups of 3). The first task provided a number of correctly read items in one minute, which was used as a proxy of reading abilities. The difference in correctly enumerated items between the second and the third task provided an implicit measure of the mastery of arithmetic operations, because grouped items can be enumerated faster if children know how to perform mental arithmetic ("groupitizing"; Ciccione & Dehaene, 2020;  Starkey & McCandliss, 2014). The main experimental task was performed on a tablet and, immediately before it, each child was provided with four examples of stimuli and their expected correct answers. The sample size of Himba and children participants was based on a previous study that used an identical trend judgment task  (Ciccione & Dehaene, 2021). All data and scripts for the analyses are available on the Open Science Framework at: https://osf.
Stimuli The stimulus generation algorithm was identical to the one used in a previous laboratory version of the task  (Ciccione & Dehaene, 2021). Each scatterplot was the graphical representation of a dataset randomly generated from a linear equation of the form yi = α xi + ei, where α is the prescribed slope and the ei are random numbers drawn from a normal distribution centered on zero and with standard deviation s. A total of 112 scatterplots were presented to participants, which were the result of the combinations of 3 orthogonal factors: 7 prescribed slopes (a = -0. 1875, -0. 125, -0. 0625, 0, +0. 0625, +0. 125 or +0. 1875); 4 levels of noise (σ = 0. 05, 0. 1, 0. 15 or 0. 2); and 4 numbers of points  (n = 6, 18, 38, 66). All coordinates on the x axis were fixed and equally spaced for each level of n.