dataesr/scientific-paragraphs-categorization huggingface dataset:
falciparum digestive vacuole membrane, which fine tune the balance between nutrient and drug transport, revealing evidence for epistasis and compensation, and impacting both drug resistance and fitness. 6  shows nonrandom associations between genotypes in parasite clones recovered from untreated cultures. were called with GATK Haplotype Caller (https://software. broadinstitute. org/gatk/) following the best practices endorsed by the Pf3K project (https://www. malariagen. net/data/pf3K-5). Only SNP genotypes were used for this study. VCF files were generated by chromosome, and then were merged using bcftools (https://samtools. github. io/bcftools/bcftools. html) and filtered using vcftools (https://vcftools. sourceforge. net/). After filtration, only biallelic SNP variants with a VQSLOD score of at least 2, a map quality >30, and supported by no less than 5 reads per allelic variant were remained.
SNPs with minor allele frequency <2% were further removed from our analysis. We also removed samples with > 10% genotypes missing. In the final dataset, there were in total of 16,385 biallelic SNP loci and 321 isolates (1984 [134], 1990 [13], 2001 [34], 2008 [75], and 2014 [65]) remained for further analysis. The complexity of infection (monogenomic or polygenomic) was estimated as the inbreeding coefficient Fws from the merged VCF file using R package Biomix. The short-read sequence data for all isolates and those from across Africa that have been previously published are available from the European Nucleotide Archive, and sample identifiers are given in Supplementary Table  1.
Allele frequencies and pairwise differentiation. For each sample with a complexity of infection greater than 1, the allele with most reads was retained for mixed-allele genotypes to create a virtual haploid genome variation dataset. Allele frequencies were calculated in plink and pairwise differences between temporal populations and genetic clusters were estimated by Fst using Weir and Cockerham's method applied in the hierfstat package in R. The likelihood ratio test for allele frequency difference pFST was further calculated using vcflib. For a combined pFST p-value, the fisher method was performed in R metaseq package. The summary p-values were corrected for multiple testing using Benjamini-Hochberg (BH) method. Genome scans for selection. We considered samples collected in the same year as a single population irrespective of the location of collection.
We used the hapFLK approach to detect signatures of positive selection through haplotype differentiation following hierarchical clustering of Gambian temporal population groups compared to an outgroup from Tanzania, as described by Fariello et al. , 2013  47. P-values were computed for each SNP-specific value using the Python script provided with the hapFLK program, and values were corrected for multiple testing using the BH method. Secondly, we used pairwise relatedness based on identity by descent to derive an iR statistic for each SNP as implemented by the IsoRelate 18 package in R. Regions with overlapping iR and hapFLK -log10 p-values > 5 were considered as regions of interest.
Population analysis on pfaat1 and pfcrt evolution Datasets. We included two datasets in this study: 1) genotypes of 7,000 world-wide P. falciparum samples from MalariaGEN Pf community project (version 6. 0)  21. This dataset includes samples from South America (SM), West Africa (WA), Central Africa (CA), East Africa (EA), South Asia (SA), the western part of Southeast Asia (WSEA), the eastern part of Southeast Asia (ESEA) and Pacific Oceania (PO). 2) We also included 194 Thailand samples with whole genome sequencing data available from Cerqueira et al. 15  , and merged them into the WSEA population. Duplicate sequences were removed according to the sample's original ID (Hypercode). Only samples with single parasite infections (within-host diversity F WS > 0. 90) and >50% of SNP loci genotyped were included for further analysis.
Mapping and genotyping. We mapped the sequencing reads against the 3D7 reference genome (PlasmoDB version 46) using BWA mem (http://bio-bwa. sourceforge. net/), and deduplicated and trans-formatted the alignment files using picard tools v2. 0. 1 (http://broadinstitute. github. io/picard/). We recalibrated the base quality score based on a set of verified known variants  52  using BaseRecalibrator, and called variants through HaplotypeCaller. Both functions were from Genome Analysis Toolkit GATK v3. 7 (https://software. broadinstitute. org/gatk/). Only variants located in the core genome regions (defined in  52  ) were called and used for further analysis.
Genotype of parents. We merged calls from the two parents using GenotypeGVCFs in GATK, and applied standard filtration to the raw variant dataset as described in  53. We recalibrated the variant quality scores (VQSR) and removed loci with VQSR < 1. The final variants in VCF format were annotated using snpEff v4. 3 (https://pcingola. github. io/SnpEff/) with 3D7 (PlasmoDB, release46) as the reference. After filtration and annotation, we selected SNP loci that are distinct in the two parents and used those SNPs for further bulk segregant analysis. Bulk segregant analysis. We used statistical methods described previously in  25, 48, 50  for bulk segregant analysis. The variant calls from segregant progeny pools were merged together. Additionally, SNP loci with coverage < 30× were removed. We counted reads with genotypes of each parent and calculated allele frequencies.
Allele frequencies of 3D7 were plotted across the genome, and outliers were removed following Hampel's rule  54  with a window size of 100 loci. We performed the bulk segregant analysis using the R package QTLseqr 55. Extreme-QTLs were defined as regions with G prime > 20  56. Once a QTL was detected, we calculated an approximate 95% confidence interval using Li's method  57  to localize causative genes.
Acknowledgments We thank past and present staff and visiting researchers at the  MRC Unit in The Gambia  involved in studies from which samples were archived, including those under the earlier directorships of  Prof Brian Greenwood  and  Prof Tumani Corrah. Work at  Texas Biomedical Research Institute  was conducted in facilities constructed with support from  Research Facilities Improvement Program  grant  C06 RR013556. SMRU is part of the  Mahidol Oxford University Research  Unit supported by the  Wellcome Trust of Great Britain. We thank the staff of the  Wellcome Trust Sanger Institute Sample Logistics, Sequencing and Informatics facilities  for their contributions. The  Structural Biology Core  at The  University of Texas Health Science Center at San Antonio  is a part of Institutional Research Cores supported by the  Office of the Vice President for Research  and the  Mays Cancer Center Drug Discovery and Structural Biology Shared Resource (National Institutes of Health  grant  P30 CA054174 ).
Numerical Model We perform 3-D geodynamic simulations using LaMEM  (Kaus et al. , 2016). This finite difference staggered grid discretization code uses particle-in-cell methods to solve the energy, momentum, and mass conservation equations. The rheologies of the rocks are assumed to be visco-elasto-plastic and the total deviatoric strain rate is given by: ε𝜖𝑖𝑖𝑖𝑖 = ε𝜖𝑣𝑣𝑖𝑖𝑣𝑣 𝑖𝑖𝑖𝑖 + ε𝜖𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖 + ε𝜖𝑝𝑝𝑒𝑒 𝑖𝑖𝑖𝑖 = 1 2𝜂𝜂𝑒𝑒𝑒𝑒𝑒𝑒 𝜏𝜏𝑖𝑖𝑖𝑖 + 1 2𝐺𝐺 𝜕𝜕𝜏𝜏𝑖𝑖𝑖𝑖 𝜕𝜕𝜕𝜕 + λ𝜆 𝜕𝜕𝜕𝜕 𝜕𝜕𝜕𝜕𝑖𝑖𝑖𝑖 , where       ,     , and     are the viscous, elastic, and plastic strain rates, respectively. η eff is the effective viscosity, G the elastic shear modulus, τ ij the deviatoric stress tensor, t the time,  λ is the plastic multiplier, Q the plastic flow potential and σ ij = -P + τ ij the total stress. The effective viscosity η eff is given by: where A is the exponential prefactor, n the stress exponent of the dislocation creep,    is the second invariant of the viscous strain rate tensor, E, V are the activation energy and volume, respectively, P is the pressure, R is the gas constant, and T is the temperature.
Data Availability Statement Seismic data were obtained courtesy of Pusdatin ESDM, Indonesia (MoU LIPI, Indonesia). Numerical code LaM-EM (  9 ) is available at https://bitbucket. org/bkaus/lamem. All maps were done with GMT  (Wessel et al. , 2019). All other data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.
Several startup companies that sell prefabricated substrates exist today, which is a partial step towards standardization -though in our experience their rigidities need to be verified by the end user. Python, ImageJ/Fiji, and even Matlab scripts are now available online for calculating stresses, force maps and energies from bead images (see for example https://sites. google. com/site/ qingzongtseng/tfm, https://github. com/topics/traction-forcemicroscopy, https://github. com/MBPPlab/TFM_v1). Though this does not completely solve the problem, it is a step in the right direction towards standardization. To further complexify the picture, the generation of mechanical forces by biological systems are space and time scales dependent, from cells, down to single molecules and up to entire organisms, lasting less than a few seconds up to hours and even over their whole lifetime.
Acknowledgments The project leading to this publication has received some funding from  France 2030 , the  French Government program  managed by the  French National Research Agency  ( ANR-16-CONV-0001 ) and from  Excellence Initiative of Aix-Marseille University  -A*MIDEX. Part of this work was also supported by institutional grants from  Inserm ,  CNRS  and  Aix-Marseille University  to the LAI and from  CNRS  and  Aix-Marseille University  to the CINAM. FM was supported as a PhD grant by the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement  No713750 , with the financial support of the  Regional Council of Provence-Alpes-Cote d'Azur  and with of the A*MIDEX (n°ANR- 11-IDEX-0001-02 ), funded by the  Investissements d' Avenir  project funded by the  French Government , managed by the  French National Research Agency (ANR).
Catch data Catch data (number of fish individuals caught for each species) recorded on the last fishing trip (question 21) was analysed to investigate the link between the typology of fishers defined through the cluster analysis and the species profile of their catches. To this purpose, a Pearson's Chi-squared test was applied to the contingency table crossing the groups of fishers with the 14 main species in their catches. A clustered  heatmap was used to summarise the standardised residuals of the Chi-squared test (Agresti 2007). Clustering of groups of fishers and species used Euclidean distances and the Ward agglomerative method  (Murtagh and Legendre 2014). All statistical analyses were run using the R software (R Core Team 2020). The Fuzzy Correspondence Analysis used the ade4 package  (Thioulouse et al.
2018 ) and the function catdes of the FactoMineR package for assessing the relevance of the variables for each group of fishers  (Lê et al. 2008). The function pheatmap of the pheatmap package  (Kolde 2019 ) was used for the graphical representation of the results of the catdes function and of the Chi-squared residuals of the catch data. The function chisq. posthoc. test of the chisq. posthoc. test package  (Ebbert 2019)  was used for the post-hoc Chi-squared test of the fishers' perception of global environmental change. The code is available on GitHub (https:// github. com/ umr-marbec/ LEK_ Mauri tius).
Fishers who did not answer to Fishing area (n = 2), Gear (n = 2) and FAD (n = 1) questions were also removed, resulting in a data table of 225 fishers. The projection of the fishers along the first two axes of the FCA highlighted the main tendencies concerning their fishing habits (Fig. 3 ). Axis 1, summarizing 19. 7% of the total variance opposed fishers from the East region, using small wooden pirogues (< 8 m), small outboard engine < 8 CV), baskets and not fishing on FADs (on the right side of the FCA projections in Fig. 3 ) to fishers from the West region, using fibre glass boats with big outboard engine (> 26 CV), fishing in the deep sea with vertical lines and using FADs (on the left side). Axis 2, summarizing 13. 5% of the total variance, opposed fishers from the North region, using larger outboard engine (> 26 CV) (on the top side of the FCA projections in Fig.
Acknowledgements The authors would like to thank all participants of the fishing community for their time and knowledge sharing, two trainee projects assistants  T. Kaully  and  P. Raghbor  and field assistants involved in administering the survey. CA is thankful to  Prof J Andre Ndione  for advice on design of survey questions related to global change and to  J Naggea  for assistance with literature on artisanal fishers.
In addition, as tracer distribution changes during the dynamic frame sequence, a mutual information (MI) score was used to identify the starting frame for motion correction that is characterised by a sufficiently similar tracer distribution with the reference (last) frame. Validation of the approach was performed based on a simulated F18-fluoro-deoxy-glucose (FDG) dynamic sequence synthesised from the digital Zubal phantom. Inter-frame motion was added to each dynamic frame (except the reference frame). Total brain voxel displacement based on the added motion was constrained to 25 mm, which included both translation (0-15 mm in x, y and z) and rotation (0-0. 3 rad for each Euler angle). Twenty repetitions were performed for each dataset with arbitrarily simulated motion, resulting in 20 synthetic datasets, each consisting of 36 dynamic frames (frame 37 was the reference frame).
The user can select the number of iterations at each resolution level with values of 100/50/25 (coarse/medium/fine) iterations set as the default, which proved to be a solid choice upon testing during development to compromise speed and robustness. These default values yielded excellent alignment performance over a large range of studies during our testing phase. The average time to perform alignment of one frame is < 1s on a laptop computer with 8 GB of RAM. The software is built around Kitware's Insight Segmentation and Registration Toolkit  [22, 23]  and command line tools.
Clinical image data The developed motion correction method was applied to three different clinical dynamic tracer studies that included both F18-labeled fluorodeoxyglucose (FDG) and fluoroethyl-L-tyrosine (FET) and C11-labeled (alpha-methyl-tryptophan (AMT)) tracers. In addition to tracer variability, these datasets were also acquired from three different PET systems (Table  1 ). The AMT data included six studies to examine tryptophan metabolism in adult patients and was performed on a Discovery STE PET/CT system (General Electric Healthcare, United States). The study consisted of a 7 × 5 min dynamic frame sequence initiated at 25 min p. i. All images were reconstructed using a standard OSEM reconstruction routine, yielding image frames with 128 × 128 × 47 matrix size and a voxel size of 2.
Digital phantom Figure  5  shows the mean and standard deviation of the imposed displacement across the frame sequence (blue graph), which was derived from all 100 simulated dynamic curves. The graph indicates a displacement across the dynamic sequence between 10mm and 25 mm (16 ± 5 mm, TABLE  1  The details of all four clinical datasets are listed to provide an overview of important information, such as the system and frame durations. It also summarises the variety of data by using three different tracers and four different devices with which the data was captured. Figure  6A  demonstrates increased MI scores at the coarse (visually observable in Figure  1 ) resolution level, with the MI scores approaching the plateau phase at an earlier time than those at the medium and fine resolution levels.
Acknowledgements This research is funded by  Vietnam National Foundation for Science and Technology Development (NAFOSTED)  under grant number  103. 01-2019. 380. This work used the  Extreme Science and Engineering Discovery Environment (XSEDE) , which is supported by  National Science Foundation  grant number  OCI-1053575. Dorra Khiri ,  Sonia Taamalli ,  Florent Louis , and  Abderrahman El Bakali  appreciated the support from the  LABEX CaPPA (Chemical and Physical Properties of the Atmosphere) , which is funded by the  French National Research Agency (ANR)  through the  PIA (Programme d'Investissement d'Avenir)  under contract  ANR-11-LABX-0005-01  and also the  Regional Council "Hauts de France" and the "European Funds for Regional Economic Development".
Whole transcriptome analysis from iRPE cells reveals altered expression of genes related to cell adhesion and extracellular matrix In order to assess the transcriptional changes associated with the defective RPE phenotype observed in hiRPE cells carrying the PRPF31 mutation, we performed whole transcriptome sequencing using biological triplicates from Control, Cys247X-Asympto (Cys247X-As) and Cys247X iRPE cells. Analysis of the expression adhesion molecules such as seven members of the protocadherin/ cadherin family, which were found among the most differentially expressed in iRPE cells carrying a PRPF31 mutation (Supplementary Fig. 8  and Supplementary Data 2). Pathway enrichment analysis of the selected DEGs confirmed a large deregulation of extracellular matrix genes and genes related to cell adhesion, such as Claudin 3 and 19 (Supplementary Fig.
Splicing defects in iRPE cells and retinal organoids carrying PRPF31 mutations Based on the role of PRPF31 as a splicing factor, we used our whole transcriptome data from iRPE cells and retinal organoids at D100 to identify differences in splicing events between Cys247X patients (affected) and others (control, asymptomatic carrier and isogenic corrected). Using rMATS software and filtering parameters of a minimum PSI value of 10%, a deltaPSI of 10% and an FDR value lower than 0. 05, we identified 2233 splicing events in iRPE cells for Cys247X vs Control, 760 for Cys247X vs Cys247X-As, and 1660 for Cys247X-As vs Control (Fig. 10a ). We selected significant splicing events occurring in both comparisons for Cys247X vs Control, and Cys247X vs Cys247X-As but not in Cys247X-As vs Control. Such approach led to the identification of 230 splicing events altering a total of 152 unique genes (Supplementary Data 4).
Green, Biological Process; orange, Cell Compartment; blue, Molecular Function. e Differential expression analysis by RT-qPCR of CRYBA1, CRYBB1, DNMT3B, GDF15, and PIM (upper panel) and of NXLN1, GUCY2D, SOX7, GUCA1B, and ARR3 (lower panel) in Cys247X-Iso, Control, Cys247X-As, and Cys247X iRPE cells. Fold expression is relative to Cys247X-Iso. Values are mean ± SD, n = 3 samples of 10-12 retinal organoids from N = 3 independent differentiations. Data were normalized against the geometric average ΔCt of 18 S housekeeping gene. Statistical significance assessed using the Kruskal-Wallis test (*P < 0. 05; **P < 0. 01; ***P < 0. 001). Scientific) as previously reported  37. The emergent iPSC colonies were picked under a stereomicroscope and expanded onto mitomycined human foreskin feeder layers.
c Circular visualization of selected GO enriched pathways from the identified 152 genes with alternative splicing events. Down-(blue dots) and up-regulated genes (red dots) within each GO pathway are plotted based on logFC. z score bars indicate if an entire biological process is more likely to be increased or decreased based on the genes it comprises. Green, Biological Process; orange, Cell Compartment; blue, Molecular Function. The table shows pathway identity number (ID), associated pathway name (Term), gene count from the analyzed dataset and the adjusted P value (adj_pval). The different categories of pathways are BP, Biological Process; CC, Cell Compartment; MF, Molecular Function. d Sashimi plots for the indicated genes representing the alternate splicing events in iRPE cells derived from Control (green), Cys247X-As (blue) and Cys247X (red).
Data are representative of the replicates for each experimental group. Orange highlights in the sashimi plots indicate the alternative splicing events and numbers correspond to the number of junction reads for each event. ITG6A: Integrin Subunit Alpha 6; BEST1: Bestrophin 1; SCARB1: Scavenger Receptor Class B Member 1. medium change. iPSCs were passaged once a week with the enzyme-free Gentle cell dissociation reagent (StemCell TM Technologies) at RT for 6 min. Detached cell aggregates were collected in mTeSR TM 1 medium and carefully pipetted up and down to obtain uniform suspensions of cell aggregates that are transferred to fresh rhVTN-coated plates in a 1:10 to 1:60 ratio. iPSCs were cryopreserved with the CryoStor CS10 cell freezing medium (StemCell TM Technologies).
All of the analyzed metaphases were karyotyped using the MetaSystems Isis software (MetaSystems). In vitro and in vivo three germ layer differentiation To validate the pluripotency of hiPSC lines, a teratoma-formation assay was performed as previously described  55  with slight modifications. Briefly, 1 × 10 6 to 2 × 10 6 cells were injected into the rear leg muscle of 6-week-old NOD Scid gamma (NSG) mice (Charles River). Animals were killed according to the recommendations of our local ethical and animal care committee (Institut de la Vision -Authorization B-75-12-02 delivered by the Ministry of Agriculture). After 9-10 weeks, teratomas were dissected and fixed in 4% paraformaldehyde. Samples were then embedded in paraffin, and sections were stained with hematoxylin/eosin. Pluripotent state of iPSCs was also assessed in vitro using the STEMdiff TM trilineage differentiation kit (StemCell TM Technologies) according to the manufacturer's instructions.
Mutation screening Genomic DNA from control and patients iPSCs were extracted using the Nucleospin Tissue Kit (Macherey-Nagel) following the manufacturer's instructions. PCR amplification flanking PRPF31 mutations in exons 4 or 8 (Supplementary Data 6) was performed using HOT FIRE Pol DNA Polymerase (Solis BioDyne). PCR products were sequenced using BigDye® Terminator v1. 1 Cycle Sequencing Kit (Thermo Fisher Scientific) on a 3730 DNA analyzer (Applied Biosystems).
The genotype was finally visualized after migration of the DNA in a 3% agarose gel (Supplementary Data 6). After validation by sequencing, corrected IPSC lines were selected, pluripotent status was validated by immunostaining for pluripotency markers, and the genomic stability was assessed by detection of recurrent genetic abnormalities using the iCS-digital TM PSC test by Stem Genomics (Montpellier, France). Off-target sequences were predicted using the CRISPOR tool website (http://crispor. tefor. net). The sgRNA off-target sequence was blasted against the human genome reference (https://blast. ncbi. nlm. nih. gov/ Blast. cgi). Capture intervals of predicted off-target sites were expanded by ~500 bp in both the 5′ and 3′ directions to design specific primers ensuring accurate detection of any genetic lesion occurring at or near the selected sites.
Immunostaining, imaging, and cell counting Immunofluorescence was performed either on fixed cells or on retinal organoid cryosections. Slides were then incubated for 1 h with a blocking solution (PBS, 0. 2% gelatine, and 0. 1% Triton X-100) at RT. Incubation with the primary antibody (Supplementary Data 6), appropriately diluted in blocking solution, was performed alternatively for 1 h at RT or overnight at 4 °C. Slides were washed four times in PBT (PBS with 0. 1% Tween-20) and then incubated for 1 h at RT with appropriate secondary antibody conjugated with either AlexaFluor-488, 594 or 647 (Interchim) diluted at 1:600 in the blocking solution. To counterstain the nuclei, slides were washed twice in PBT, and incubated with DAPI diluted at 1:1000 in PBS. Finally, slides were washed two times in PBS before mounting with Fluoromount-G (Southern Biotech).