dataesr/scientific-paragraphs-categorization huggingface dataset:
17. 0) and R/RStudio (V. 4. 0. 5). 18 19 ta quality To ensure high data quality, we developed simple userfriendly questionnaires which were piloted prior to use. We recruited and trained data collectors who met a minimum level of competency as described above and through pre-post training examinations. Supervisors oversee study implementation by supporting data collectors with weekly on-the site mentorship and weekly team meetings. Supervisors independently conduct home visits on a 5% random sample of households to validate data collector performance. Within the electronic data capture system, we built single field value checks, interfield logic checks and interform logic checks. In case of an error at the time of data entry, pop-up warnings are triggered, prompting the user to resolve any issues prior to saving the record.
Data analysis For each of the primary outcomes, we will calculate the period prevalence and incidence at community and health facilities levels. To estimate period prevalence, we will sum the 2-week periods over all the participants within certain age ranges as the denominator and sum the number of episodes within that 2-week period as the numerator (i. e. , cases over sum of person-days observed or person-days recalled). We will estimate the incidence for each outcome by taking the sum of all the person-time contributed by each person as the denominator, and the sum of all episodes over the study period as the numerator. Missing data will be assessed through quality assurance checks by field supervisors and rectified through a documented error correction system. Remaining incomplete data will be addressed through analytical approaches.
A BS TRACT: This systematic MDSGene review covers individuals with confirmed genetic forms of primary familial brain calcification (PFBC) available in the literature. Data on 516 (47% men) individuals, carrying heterozygous variants in SLC20A2 (solute carrier family 20 member 2, 61%), PDGFB (platelet-derived growth factor subunit B, 12%), XPR1 (xenotropic and polytropic retrovirus receptor, 16%), or PDGFRB (platelet-derived growth factor receptor beta, 5%) or biallelic variants in MYORG (myogenesis-regulating glycosidase, 13%) or JAM2 (junctional adhesion molecule 2, 2%), were extracted from 93 articles. Nearly one-third of the mutation carriers were clinically unaffected. Carriers of PDGFRB variants were more likely to be clinically unaffected (54%), and the penetrance of SLC20A2 and XPR1 variants (<70%) was lower in comparison to the remaining three genes (>85%).
Literature Search and Eligibility and Inclusion Criteria The literature search and data extraction protocols employed in this review have been established for the generation and maintenance of the MDSGene database. 14 omprehensive literature searches for publications on individuals with PFBC with confirmed SLC20A2, PDGFB, PDGFRB, XPR1, MYORG, and JAM2 variants were performed by entering standardized search terms (Supplementary Table  S1 ) into NCBI's PubMed search engine (https://www. ncbi. nlm. nih. gov/pubmed). Titles, abstracts, and, when relevant, full texts of peer-reviewed, original articles written in English and published until August 1, 2020, were screened for inclusion. Only publications reporting at least 1 individual with PFBC with at least one SLC20A2, PDGFB, PDGFRB, or XPR1 variant or two (biallelic) MYORG or JAM2 changes were considered eligible.
Moreover, reviews of any of the six disease-related genes were screened for further data and additional potentially relevant articles. We accessed the Human Gene Mutation Database Professional (version 2020. 2; https://portal. biobase-international. com/cgi-bin/portal/ login. cgi) for variants and respective publications that we may have missed using the aforementioned approaches. An overview of the literature search and the filtering procedure is shown in Supplementary Figure  S2. All included articles and reviews are provided in Appendix S1. We excluded variants that had a minor allele frequency ≥1% based on the gnomAD Browser (https:// gnomad. broadinstitute. org/; v. 2. 1. 1)  15 and/or dbSNP (http://www. ncbi. nlm. nih. gov/snp/). 16 By definition, only individuals with reported brain calcification and with at least one variant in one of the AD-PFBC-related genes or homozygous/compound heterozygous variants in AR-PFBC genes were designated "individuals with PFBC" and included in the study.
Data Collection and Analysis Data on demographic, genetic, radiological, and clinical/ phenotypic variables were extracted for each included individual (see Supplementary Table  S2 ). Importantly, data were collected from all previously or subsequently published articles referring to the same individuals. Physical location; genomic, coding, and protein nomenclature; genotype; and zygosity were obtained for all changes. To estimate the influence of the variant severity on the clinical status, age at onset (AAO), or number of affected brain regions, we subclassified all the changes into more (predicted to result in the loss of protein) or less severe mutations. Details regarding data curation, mutation mapping, pathogenicity scoring, and statistical analyses are provided in Appendix S1.
Identified Individuals, Unique Variants, and Missing Data Our literature search identified 648 genetically confirmed carriers of variants in PFBC-related genes, 362 of whom harbor SLC20A2, 70 PDGFB, 29 PDGFRB, 33 XPR1, 143 MYORG, and 11 JAM2 changes (Supplementary Table  S3 ). Of these individuals, 132 were excluded from the review, as detailed in Supplementary Table  S3. Thus, we analyzed data from 516 individuals, 317 carrying mutations in SLC20A2 (61%), 64 in PDGFB (12%), 26 in PDGFRB (5%), 32 in XPR1 (6%), 66 in MYORG (13%), and 11 in JAM2 (2%) (Table  1  and Supplementary Table  S3 ). Across all 516 included individuals, 219 unique (different) sequence alterations were found (119 in SLC20A2, 22 in PDGFB, 9 in PDGFRB, 12 in XPR1, 49 in MYORG, and 8 in JAM2). Twelve were rated definitely pathogenic, 167 probably pathogenic, and 40 possibly pathogenic based on MDSGene criteria (Fig.
SLC20A2 We identified 317 individuals (44% male, 53% female, 3% unknown) from 167 different families carrying mutations in the SLC20A2 gene. Their origins are shown in Supplementary Figure  S5. One hundred FIG. 1. Overview of (A) pathogenicity and (B) type of the 219 unique variants (in all six genes collectively) included in this study. Every mutation was counted once, regardless of the frequencies in mutation carriers. Variant with an unknown effect -the consequence of this variant cannot be predicted at the protein level. 1 ; Supplementary Fig. S7 ). The most frequent motor manifestations in 21 clinically affected patients were speech disturbance and parkinsonism (29%). Concerning nonmotor signs, 8 patients (38%) showed cognitive deficits (Table  2 ; Supplementary Fig. S8 ). Seventy-one percent of the affected individuals (n = 15) had calcifications in the basal ganglia and in one to three of the other brain regions (thalamus, cerebellum, and white matter), whereas the data for the remaining clinically affected XPR1 mutation carriers (n = 6) were missing (Table  3 ; Supplementary Figs.
Discussion This article comprehensively analyzes reported genetic, clinical, and neuroradiologic findings in individuals with genetically confirmed PFBC. Carriers of the PFBC-related variants may clinically present with motor and/or M D S G E N E R E V I E W : P R I M A R Y F A M I L I A L B R A I N C A L C I F I C A T I O N nonmotor phenotypes or may remain unaffected. Data on a subset of these individuals are available on MDSGene (www. MDSGene. org); according to the focus of the MDSGene database on patients with movement disorders, MDSGene contains data solely on PFBC patients who manifest motor signs (Supplementary Fig. S2 ). Over 20% of individuals the data of whom we initially collected have been disregarded in our final analyses for various reasons (Supplementary Table  S3 ). Importantly, as the presence of calcification observed on neuroimaging was one of the inclusion criteria, 5 paraclinically unaffected individuals harboring variants rated as probably (n = 4) and possibly pathogenic (n = 1) have not been considered further.
Sampling strategy The French NGO ACRO monitors environmental radioactivity with local inhabitants. Its Citizen Observatory of Radioactivity in the Environment (CORE) monitors the impact of nuclear plants in Normandy and along the Loire River. ACRO's laboratory is certified by the French nuclear safety authorities for several radioactivity determination methods. All data produced in this program are published online (www. acro. eu. org) and uploaded into the French national database ( ewww. mesure-radioactivit&eacute;. fr). In early 2016, samples collected by ACRO at La Hague in a small river flowing to the west of the nuclear reprocessing plant, the Ru des Landes, revealed the presence of several artificial radioelements that are usually only found in trace amounts: 60 Co, 129 I, 137 Cs, and 241 Am.
The dissociation constants for hElp123 align with previously described values for yeast Elp123 and archaeal Elp3  40, 43. Next, we examined the enzymatic activity of hElp123 WT by measuring tRNA-induced acetyl-CoA (ACO) hydrolysis rates. ACO provides the acetyl group that is transferred to U 34 to form cm 5 U 34 in the initial step of the modification. Our data show that the activity of hElp123 WT was stimulated by tRNA Arg UCU , while tRNA Arg ACG did not stimulate its hydrolysis rate (Fig. 3c ). Our results using MST and ACO assays confirm that hElp123 WT , like bacterial and archaeal stand-alone Elp3 proteins  43, 44  , is nonselective towards the binding of different tRNA species, but strictly requires U 34 to initiate the modification reaction. We then asked whether the identified single amino acid substitutions in Elp2 influence the assembly and the tRNAinduced ACO hydrolysis activity of the Elp123 sub-complex.
d Normalized acetyl-CoA hydrolysis activity assay results for hElp123 variants incubated with tRNA Arg UCU (n = 3 independent experiments). Statistical analysis: one-way ANOVA (α = 0. 05) with a Dunnett's post-hoc test. Statistically significant differences are indicated (*p ≤ 0. 05; ****p ≤ 0. 0001; ns not significant: p = 0. 6823), Data represent mean ± SD. Source data are provided as a Source Data file. fiber tracts at axonal bundle resolution and provides deep insights into tractography and brain connectome. We analyzed five major white matter structures in the Elp2H206R brain, namely the hippocampal commissure, anterior commissure, corpus callosum, internal capsule, and afferent and efferent cerebellar tracts. In contrast to brains of wild-type mice (Fig. 5a, c ), both commissures and internal capsules in Elp2H206R mice revealed significantly reduced fractional anisotropy (Fig.
Methods Patient ascertainment and phenotyping. Patients with homozygous or compound heterozygous variants in the ELP2 gene were recruited from research or diagnostic programs in Europe, Australia, and the US. Grouping of clinical data for this series was facilitated by GeneMatcher  74. All patients were clinically evaluated by neurologists and clinical geneticists at their respective tertiary healthcare centers, and clinical information was collected from medical files in combination with standardized questionnaires and face-to-face interviews with patients and their families. Seizures were classified according to the International League Against Epilepsy classification  75. Where available, MRI images were reviewed by an expert neuroradiologist (C. G. M). Written informed consent was obtained from all participants.
Experiments were conducted using a constant 100 nM concentration of Cy5-labled tRNA Arg UCU or tRNA Arg ACG in MST Buffer (20 mM HEPES, 150 mM NaCl, 5 mM DTT, pH 8. 0, 0. 0125% Tween 20) and incubated with 16 serial dilutions of hElp123 WT (starting from 12 μM). Measurements were performed at 100% excitation power in Premium Coated capillaries on the Monolith NT. 115 (Nanotemper Technologies) at 25 °C. Obtained data were analyzed and dissociation constant values were calculated using MO. Affinity software (Nanotemper Technologies). Acetyl-CoA hydrolysis activity assay. Each of the hElp123 variants in concentration of 0. 15 μM was mixed with 2 μM tRNA and 100 μM ACO and incubated for 3 h at 37 °C. Next, the samples were passed through a 3 kDa cutoff concentrator (EMD Millipore). Flow-through was collected and pipetted into a 96-well plate.
Acoustic data were recorded for 5 min using Audacity v2. 1. 3 (available at http://audacityteam. org/; the name Audacity is a registered trademark of Dominic Mazzoni) software with a sampling rate of 250,000 Hz. For acoustical analysis, USV recordings were transferred to Raven Pro v1. 5 (Cornell Laboratory of Ornithology) software. Total number of calls, call duration, and peak frequency, and amplitude were calculated for a 5 min recording session. All behavioral analyses were performed by researchers blinded to the genotype of the animals. Tissue and embryo collection. Experimental animals were anaesthetized using Zoletil (50 mg/kg, i. p. ) and Dormitor (1 mg/kg, i. p. ) and transcardially perfused with phosphate-buffered saline (PBS), followed by 4% paraformaldehyde (PFA) solution. Following dissection, brain tissue was drop-fixed in 4% PFA at 4 °C for 12 h under constant agitation.
DWI datasets were zero-filled by a factor of 1. 5 in all dimensions and Fourier transformed for improved fiber tracking  83  to 80 µm isotropic resolution. Advanced normalization tools (ANTS) affine and diffeomorphic registrations were used to create separate three-dimensional templates for the wild-type and Elp2H206R animal groups. The Brookhaven National Laboratory 3D MRI C57BL/ 6J adult mouse brain atlas  84  was then registered to each sample and normalised back into the original sample space using ANTS (inverse warp and affine transformation). The atlas-registered samples were segmented into 20 distinct brain regions and ITK-SNAP software enabled the acquisition of volumetric statistics for each region. For the tractography and structural connectome analyses, DWI datasets were first intensity-bias corrected with ANTS N4BiasFieldCorrection.
DWIs were subsequently processed using MRtrix3 software for fiber orientation distribution modeling under the constrained spherical deconvolution method. Region-specific tractography was performed for the hippocampal commissure, anterior commissure, corpus callosum, internal capsule, and cerebellum. Regions of interest (ROIs) were manually seeded from mid-sagittal and coronal sections for all tracts except the cerebellum, and fiber tracts were generated using the iFOD2 algorithm  85  at 100 seeds per voxel before threshold masking all tracts at 10%. Cerebellar tracts were seeded from the entire cerebellum segmentation assigned during volumetric atlas registration, and fiber tracking was executed at 2 seeds per voxel. For structural connectome mapping, whole-brain tractography was generated at 10 seeds per voxel and segmented according to the modified Centre for Advanced Imaging (CAI) -John Hopkins University MRI atlas  86.
Images were obtained using Olympus BX-51 upright brightfield microscope. Whole-brain images were acquired as tiled image stacks. Cortical layers thickness relative to section thickness and cerebellar area relative to wholebrain area were measured using ImageJ software  88. Measurements of length and area are indicated by lines on the respective figures. Immunofluorescence staining, imaging, and analyses. Paraffin-embedded tissue sections underwent deparaffinization, whilst cryo-embedded sections were thawed at room temperature for 20 min and then hydrated in PBS for 10 min. Heatinduced antigen retrieval was performed using citrate buffer-based unmasking solution (Abacus) at 100 °C for 10 min. For unspecific binding of antibodies, M. O. M. blocking reagent (Vector) was used for primary antibodies raised in mouse, and 4% horse serum (Life Technologies) for the antibodies raised in species other than mouse.
Whole-cerebellum images were acquired as tiled image stacks. Image processing and quantification of cortical thickness, cell number, cell density, MBP, and acetyl-α-tubulin mean pixel intensity were performed by using ImageJ software  88. For the relative thickness of cortical layers, the thickness of the Cux1 + and Ctip2 + layers were measured relative to the overall cortical thickness (from the top cortical layer to the white matter; layers I-VI). Length measurements are indicated by lines on the respective figures. Sizes of the sections on which cell number and cell density quantifications were performed are specified in figures. Neurosphere assay. Brains of 14. 5 dpc mice were isolated from the skull and dissected manually on the coronal plane to expose the lateral ventricles at the level of the corpus callosum.
Axons and basal dendritic trees were manually traced using Simple Neurite Tracer  89. The total dendritic length was measured, and the branching complexity quantified via the Sholl Analysis plugin  90  distributed within the FIJI software package  91. For dendritic spine analyses, the number of clearly defined spines along a 10 μm stretch of each neuron's tertiary dendritic shaft was counted. Transcriptome analysis. Cortical tissue was dissected from 14. 5 dpc embryos and RNA was extracted using RNeasy Micro Kit (Qiagen) according to manufacturer's instructions. Prior to sequencing, the quality of RNA samples was assessed by Agilent 2100 bioanalyzer (Agilent Technologies, USA). RNA-sequencing was performed using the Illumina NovaSeq 6000 platform. Image analysis was performed in real time by the NovaSeq Control Software (NCS) v1.
6. 0 and Real-Time Analysis (RTA) v3. 4. 4, running on the instrument computer. RTA performs realtime base calling on the NovaSeq instrument computer. The Illumina bcl2fastq 2. 20. 0. 422 pipeline was used to generate the sequence data. The sequence reads were aligned against the mouse genome (Build version mm10). The STAR aligner (v2. 5. 3a) was used to map reads to the genomic sequences. The counts of reads mapping to each known gene were summarized at gene level using the feature-Counts v1. 5. 3 utility of the subread package (available at http://subread. sourceforge. net/). The transcripts were assembled with the StringTie v1. 3. 3 tool (available at http://ccb. jhu. edu/software/stringtie/) utilizing the reads alignment with M6 and reference annotation-based assembly option (RABT). This generated assembly for known and potentially novel transcripts.
The Gencode annotation containing both coding and non-coding annotation for mouse genome version GRcm38 (Ensemble release 81) were used as a guide (available at http://www. gencodegenes. org/mouse_releases/6. html). Differential gene expression was analyzed using edgeR (v3. 26. 0) in R 3. 6. 0. The default TMM normalization method of edeR was used to normalize the counts between samples. A generalized linear model was then used to quantify the differential expression between the groups. A CPM cut-off of 0. 5 was used. Genes with less than this value in at least six samples were removed from the dataset. After controlling for sex by incorporating it into the design model as a batch-effect, we found 917 (536 upregulated [greater expression in mutant samples], 381 downregulated [greater expression in control samples]) out of 14,266 genes being differentially expressed in the comparison of mutant vs.
6, 150 mM NaCl, 0. 1% Tween 20) for 1 hour, the membrane was washed twice with TBS-T and incubated with antibodies against: Acetyl-α-tubulin (1:1000; T6793), α-tubulin (1:500; MA1-80017), β-actin (1:1000; ab8224), Elp1 (1:1000; 5071), Elp2 (1:500; ab154643) and Elp4 (1:500; NBP2-16322) at 4 °C overnight. Next day, the membrane was washed three times for 5 min in TBS-T and incubated with relevant horseradish peroxidase-conjugated secondary antibodies (1:2500; Abcam) for 1 h at room temperature on a shaker. Peroxidase activity was detected using SuperSignal West Pico chemiluminescent (Thermo Fisher Scientific) by ChemiDoc MP imaging system (Bio-Rad Laboratories). Densitometric analysis of western blot images was performed using ImageJ software  88. In-gel destaining and trypsin digestion of proteins.
The TOF-MS scan acquisition time was set to 50 ms and each product ion scan to 25 ms. The data were acquired and processed using Analyst TF 1. 7 software (ABSCIEX, Canada). Protein identification and library compilation were carried out using Protein Pilot 5. 0. 2 for database searching. Peptide sequence identification and protein grouping were conducted by merging all individual IDA acquisition file from the gel fractions using the Paragon algorithm from Protein Pilot 5. 0. 2 against the Mus musculus Uniprot database complemented by the contaminant sequences from thegpm. org/crap/ with the following parameters: Cys alkylation was set to iodoacetamide, Trypsin was chosen as digestion enzyme, Special Factors: Gel-based-ID was enabled to account for potential, ID Focus: Biological modifications, Thorough ID, ProtScore (Conf) >10%, and False discovery analysis.
A total of 3454 individual proteins was identified with <1% global FDR and shared peptides across multiple proteins were removed before being aligned with the SWATH acquisition files using SWATH Acquisition MicroApp 2. 0 on the PeakView 2. 2 software. The processing settings were set as follows for the peak area extraction in all SWATH acquisition using the local generated ion library: Number of peptides per Protein: 6, Number of Transitions per Peptides: 6, Peptide Confidence Threshold: 99%, <1% FDR. Modified peptides were excluded for the protein quantitation and XIC extraction window: 15 min with a mass width of 50 ppm and retention times were aligned using a set of high intense Trypsin autodigest peptides. The ion, peptide, and protein area were exported as a text file and the integrated area values for each protein that was present in different gel bands for each gel lane were summed before statistical evaluations, correlation of variation, and fold change computation.
Acknowledgements We thank all members of the Wainwright and  Glatt laboratories  for discussion and suggestions. The authors acknowledge Jérémy Potriquet from the  AB Sciex company, Brisbane, Australia , for his assistance with proteome data quantification and analysis. This work was supported by the  First Team Grant  ( FirstTEAM/2016-1/2 ; A. C. G. and S. G. ) from the  Foundation for Polish Science. In addition, we thank the  MCB structural biology core facility  (supported by the  TEAM TECH CORE FACILITY/2017-4/6  grant from  Foundation for Polish Science)  for providing computational resources and support. We acknowledge the supports from the  Queensland NMR Network  and the  National Imaging Facility  (a  National Collaborative Research Infrastructure Strategy capability ) for the operation of 16.
4  T MRI at the Centre for Advanced Imaging , the  University of Queensland. Patient 6 (refer to Supplementary Table 1) was tested through the  Acute Care Flagship  of the  Australian Genomics Health Alliance , supported by grants from the  Royal Children's Hospital Foundation  ( 2017-906 ) and the  National Health and Medical Research Council  ( GNT1113531 ). The open-access publication of this article was funded by the  BioS Priority Research Area  under the program  Excellence Initiative -Research University at the Jagiellonian University in Krakow.