dataesr/scientific-paragraphs-categorization huggingface dataset:
One of the biggest challenges has been obtaining quantitative radiobiological data from in vitro/vivo experiments, which is essential to understanding the FLASH effect's dependencies on the different beam parameters. Currently, there are two conditions which seems to trigger the FLASH effect: average dose rate greater than 40 Gy/s and a total irradiation time less than 0. 2 s  [10] [11] [12] [13] [14] [15]. Nevertheless, the beam temporal structure is quite complex, and these two parameters are not enough to fully describe it. An exhaustive representation of the temporal structure is reported in Figure  1 : Where In case of a single irradiation, the following relations hold: If the irradiation consists of multiple sub-irradiations, the previous equations can be easily generalized and the additional relations hold: PRF 1 t r s -1 (1) t Fl n p -1 PRF + t p n p -1 PRF s [ ] (2) TD np i 1 D i p n p • D p , t IRR t FL 1 + t D 1 +.
More specifically, the electron accelerators adopted for FLASH radiobiological experiments are not provided with real-time monitoring of beam parameters, which makes it impossible to take output variation into account. These accelerators are typically electron accelerators designed for industrial use or modified medical accelerators, where diffuser filters and monitor chambers have been removed from the beam path  [26]. This fact has somehow limited the researchers' ability to obtain accurate and fully reproducible data on the radiobiological impact of the various beam time structure parameters potentially impacting FLASH effect. Although the FLASH effect's robustness has been validated by various animal models, organs, and radiobiology research works, the radiobiological mechanism underlying the effect is still unknown.
It is therefore essential, before the clinical translation, to quantify any dependence of the entity of the FLASH effect on the beam volume (dimension of the beam) and on the dose fractionation, since the movement of the gantry to pass from one field of view to another is not temporally compatible with the times need to trigger the FLASH effect (<0. 1-0. 2 s). In summary, while FLASH-RT has shown promising results, there are still many uncertainties and many issues that need to be addressed before it can be used in clinical practice. Further research is necessary to determine the radiobiological mechanism underlying the FLASH effect and to investigate the dependence of the effect on various beam parameters on the irradiated tissues. Advances in accelerator technology and dosimetry may provide a way to overcome the current limitations and enable researchers to obtain quantitative radiobiological data from in vitro/vivo experiments.
Advances in accelerator technology and dosimetry may provide a way to overcome the current limitations and enable researchers to obtain quantitative radiobiological data from in vivo experiments. The proposed design of a new research LINAC provides a promising avenue for further research into FLASH-RT, essential to study the response of dosimeters to UHDP beams, the quantitative dependence of the effect on the beam parameters and the mechanisms underlying the effect itself. All this is essential for the development of specific dosimetric protocols, to understand the optimal characteristics of clinical FLASH LINACs and, in general, to arrive at the optimal clinical implementation of the FLASH effect in the shortest possible time.
Funding The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was funded by  Piano Nazionale di Ripresa e Resilienza (PNRR) ,  Missione 4 ,  Componente 2 ,  Ecosistemi dell ' Innovazione-Tuscany Health Ecosystem (THE) ,  Spoke 1 "Advanced Radiotherapies and Diagnostics in Oncology "- CUP I53C22000780001.
To date, the only genetic evidence directly linking core nuclear pore component(s) to ALS, are mutations in GLE1, encoding a protein involved in mRNA export and translation and associated with the nuclear pore found in ALS patients  23. Here, we show that ALS heritability is enriched in splicing regulating variants and in binding sites of a subset of RNA binding proteins including TDP-43 and FUS. Our discovery and replication transcriptome-wide association study identify 6 loci associated with ALS, among them 3 were novel. We performed rare-variant burden analysis on this set of gene in a WGS dataset including 9,390 ALS and FTD patients and 4594 controls. Among these 6 genes, rare variants in NUP50 were associated with ALS. Furthermore, we identified ALS patients carrying haploinsufficient mutations in NUP50, and demonstrated the critical role of NUP50 in neuronal survival and motor neuron function in multiple models.
Cell type specific and molecular trait heritability of ALS We first aimed at better characterizing the involvement of specific cell types in ALS heritability. To this aim, we applied stratified linkage disequilibrium  24  (LD) score regression (S-LDSC) to the most recent ALS GWAS data  8  , and compared ALS heritability estimates to two other neurodegenerative diseases (Alzheimer's disease, AD, and Parkinson's disease, PD) and two neuropsychiatric diseases (Autism spectrum disorder, ASD and schizophrenia, SCZ). To specify cell-type specific gene expression, we used datasets of single-nuclei Assay for Transposase Accessible Chromatin sequencing (snATAC-seq) of humanderived brain samples  25  , identified open-chromatin region (OCR) in 6 different brain cell types, and partitioned heritability into these cell types according to the OCR annotation (Fig.
01 (Fig. 3a ). We then sought to replicate this association of rare variants in NUP50 in ALS using an independent whole-genome sequencing dataset 6596 ALS patients and 2584 controls (http://databrowser. projectmine. com/). Here again, in this dataset, most NUP50 derived transcripts, including the canonical NUP50 transcript (ENST00000396096), displayed significant association at a suggestive p-value (P = 0. 024; odds ratio = 2. 83; 95%CI, 1. 20-6. 64). Last, we performed inverse variance weighted meta-analysis using both discovery and replication cohorts and observed an increase burden of rare variant on NUP50 (P = 3. 7 × 10 -03 ; odds ratio = 3. 29; 95%CI, 1. 37-7. 87), in a range similar to SOD1 (P = 2. 45 × 10 -03 ; odds ratio = 8. 10; 95%CI, 1. 88-34. 8) in ALS patients (Fig. 3b ). Interestingly, neither GRN (P = 0.
42; odds ratio = 1. 92; 95%CI, 0. 31-11. 6) nor TET2 (P = 0. 31; odds ratio = 1. 37; 95%CI, 0. 71-2. 62) showed suggestive rare variant burden in the replication dataset, consistent with their association to FTD and not ALS. In all, our results demonstrate an increased burden of rare variants in the NUP50 gene within the ALS/FTD continuum. To characterize the potential NUP50 variants, we filtered all SNP and short coding insertions/deletions affecting coding sequence, splice acceptor/donor site or non-coding regions (introns, 5′UTR, 3′ UTR) of NUP50, and identified 11 potentially pathogenic NUP50 variants in 41 patients from both discovery and replication cohorts used in rare variant burden analysis (Fig. 3c ). Among the 9 missense and structural mutations identified across the different cohorts, all variants have CADD (combined annotation dependent depletion) scores > 20 (Table  2 ) suggesting high pathogenicity.
For instance, we observed two rare structural variants (22:g. 45564117A>G and 22:g. 45567544C>T) in 12 patients but none in controls. These two variants are localized in the importin-alpha domain and predicted to impact NUP50 function (Table  2 ). Finally, we also observed a splice-acceptor mutation in a patient with FTD (22:g. 45567480G>C). This variant has a low allele frequency (gnomAD MAF = 3. 9 × 10 -06 ) and is predicted to disrupt a splice-acceptor site in exon 3 (Table  2 ). Some of the missense NUP50 mutations identified in ALS patients were also reported at very low frequency in the ExAC database (minor allele frequency<3 × 10 -5 ) classifying them as strong ALS risk factors. We screened an additional cohort of 330 French ALS patients 37 and identified a second frameshift mutation in a patient (Patient 1) for which lymphoblasts were available.
Patient 1 carried a single nucleotide deletion (variant location: 22:g. 45571791delT, cDNA change:c. 174delT, not found in GnomAD) leading to frameshift and premature stop codon (p. Phe58Leufs*37), which was confirmed by Sanger sequencing (Fig. S2a, b ). Other ALS genes were further interrogated for this specific patient, and did not show potentially pathogenic variants, as variants in SS18L1 (c. 1036 + 17_1036 + 133del) and NEFH (c. 85G>T, p. Ala29Ser) were present in control databases. Patient 1 had disease onset at 33 years with signs of upper and lower motor neuron involvement first restricted to the lower limbs, leading to a slowly progressive paralysis. He died from pulmonary embolism after bacterial meningitis at the age of 52 years, 224 months after the onset of the disease. Western blotting showed decreased levels of NUP50 Manhattan plot of ALS transcriptome-wide association study (TWAS) using gene expression from the GTEx consortium brain tissues.
Discussion Our current study provides evidence that ALS heritability lies in neuronally expressed genes, and in splicing events related to a small set of RNA binding proteins. Integrating RNA expression levels in GWAS led us to prioritize 6 genes as associated with ALS risk with genome-wide significance, 3 of them in known ALS loci. Among these 6 genes, NUP50 was the only gene also showing significant association in two independent cohorts of ALS/FTD or ALS patients using rare variant burden analysis. 3 independent biological validations strengthened that loss of NUP50 could be functionally involved in ALS. These major results are summarized in Fig. 7. We first characterized ALS heritability by integrating GWAS with various datasets. Here splicing QTLs variants were significantly associated with ALS risk, in particular in genes expressed in neurons.
Genetics GWAS summary association statistics. We used the summary association statistics from the latest GWAS of ALS  8. Also summary association statistics for SCZ and ASD were obtained from the PGC consortium (https://www. med. unc. edu/pgc/). AD and PD summary association statistics were obtained from the latest GWAS  51, 52. All datasets used in the current study are referenced in Supplementary Data 1. Quality control and imputation. For each cohort, SNPs were first annotated according to dbSNP150 and mapped to the hg38 reference genome. All multi-allelic and palindromic (A/T or C/G) SNPs were excluded. Low quality SNPs and genotyped individuals were excluded using PLINK 2. 0 (-geno 0. 02 and-mind 0. 1). The following filter criteria were applied: MAF > 0. 01, SNP genotyping rate > 0. 98, Deviation from Hardy-Weinberg disequilibrium in controls P > 1 × 10 -5.
Then, more stringent QC thresholds were applied to exclude individuals: individual missingness > 0. 02, inbreeding coefficient |F| >0. 2, mismatches between genetic and reported gender, and missing phenotypes (PLINK-mind 0. 02,-het,-check-sex). Duplicate individuals were removed (king-cutoff = 0. 084). Population structure was assessed by projecting 1000 G principal components (PCs) and outliers from the European ancestries population were removed (>4 SD on PC1-4). Finally, samples in common between the individual genotype data and van Rheenen's study were identified using the checksum program id_geno_checksum and were removed from our analyses. Finally, 8214 cases and 14,129 controls were used for imputation. Post Imputation quality control. Cohorts were then imputed using the TOPMED reference panel (hg38) on the TOPMED imputation server (https://imputation.
biodatacatalyst. nhlbi. nih. gov/#!). Data was phased using Eagle 2. 3. Post-imputation variant-level quality control included removing all monomorphic SNPs and multi-allelic SNPs from each cohort. SNPs with MAF < 1% in the TOPMED imputation panel were excluded. Subsequently, INFO scores were calculated for each cohort based on dosage information using SNPTEST v2. 5. 4-beta3. Within each cohort, SNPs with an INFO-score < 0. 3 and those deviating from Hardy-Weinberg equilibrium at P < 1 × 10 -6 in control subjects were removed. All cohorts were combined including SNPs that passed quality control in every cohorts yielding 9,625,489 autosomal SNPs. Whole genome sequencing. Whole genome sequencing from 3015 ALS/FTD patients and 2,031 controls were processed as described above. Duplicate individuals were removed (king-cutoff = 0.
000 mQTLs in 46656 CpG sites. Brain QTLs-based annotations. We construct the annotations for any given Brain QTL datasets using the observed marginal association statistics as previously described  53. Briefly, each annotation is a vector that assigns a value to each SNP. Given a indicate our annotation for one QTL dataset where a j indicates the value assigned to SNP j. For continuous probabilistic annotations (MaxCPP), 0 ≤ a j ≤ 1. Let S = (s 1 , s 2 , …s g ) indicate an m × g matrix of the observed marginal association statistics obtained for each QTL dataset, where m is the number of SNPs and g is the number of eGenes (for example, genes that have at least one significant cis-eQTLs). Let s i be the vector of marginal association statistics of gene i for all cis variants. Utilizing s i and the LD structure, we can compute the CPP for each variant.
After obtaining the MaxCPP annotations, we ran S-LDSC  54  to generate the LD score of each variant in each annotation using the same procedure  27. Regression SNPs, which are used by S-LDSC to estimate τ from marginal association statistics, were obtained from the HapMap Project phase  55. Using the LD score for each annotation and the marginal statistics obtained from the trait phenotypes (GWAS-ALS), we computed the enrichment, the coefficient τ and calculated the p-value for each annotation conditional on the baseline model v1. 1 and all MaxCPP annotation  56. For cell-type enrichment analyses  25  we used humanderived single-cell ATAC sequencing data on major brain cell-types (GSE147672). Disease-relevant gene-sets annotation (MaxCPP-ExAC) were constructed as previously described  53. Briefly, eQTLs and sQTLs annotation were restricted to the 3,230 genes that are strongly depleted of protein-truncating variants  28.
"Damaging" variants were missense variants predicted to be damaging by seven prediction algorithms (SIFT, Polyphen-2, LRT, MutationTa-ster2, Mutations Assessor, and PROVEAN). "Missense" variants are those missense variants that did not meet the "damaging" criteria. All combinations of allele frequency threshold and variant annotations were used to test the genic burden on a transcript level in a Firth logistic regression framework where burden was defined as the number of variants per individual. Sex and the first 20 principal components were included as covariates. All ENSEMBL protein coding transcripts for which at least five individuals had a non-zero burden were included in the analysis. Meta-analysis was performed using an inverse variance weighted methods  60.
Whole exome sequencing and genetic analyses in French patients Whole Exome Sequencing (WES) analyses were performed on French patient cohorts (including 200 family members with 150 index cases and 180 sporadic cases with 100 patients with ALS onset before 40 years and 80 autopsied cases) as previously described  37. These patient cohorts were devoid of mutation in the 4 major ALS genes (including repeat expansions in C9orf72 and/or mutation in SOD1, TARDBP and FUS). These exome databases were interrogated to select heterozygous or homozygous qualifying variants in coding or non coding region of NUP50 gene with a minor allele frequency (MAF) threshold <0. 005% in gnomAD database for heterozygous variants and ≤1% for homozygous variants. Any patient with a NUP50 variant was further interrogated for a list of 35 rare ALS related genes (including ALS2, ANG, ANXA11, ATP13A2, CCNF, CHCHD10, CHMP2B, DAO, DCTN1, DNAJC7, ERLIN2, FIG4, GLE1, GLT8D1, HNRNPA1, HNRNPA2B1, KIF5A, MAPT, MATR3, NEK1, OPTN, PFN1, PRPH, SETX, SIGMAR1, SPG11, SQSTM1, SS18L1, TAF15, TBK1, TIA1, TUBA4A, UBQLN2, VAPB and VCP) to select variants with a MAF <0.
Afterwards, cells were washed again 3 times and mounted with Pro-Long TM Gold Antifade mountant with DAPI (ThermoFisher Scientific, P36934) mixed to ibidi Mounting Medium (Ibidi, 50001). Confocal microscopy was performed with a laser-scanning microscope (Leica DMi8) equipped with an ACS APO 63 x oil DIC immersion objective. Images were captured using the LasX software (Leica), with a resolution of 1024 × 1024 pixels and a number of Z-stacks (step size of 0. 5 μm) enough to span the complete cell soma. To analyze the intensity of nuclear NUP50 (with ImageJ), we extracted the single plan from the complete Z-stack where nucleus of the neuron of interest was showing the largest shape. Viability assay. For cell viability, cells were detached by scraping and resuspended in PBS. TO-PRO-3 iodide (Fisher Scientific, T-3605) was added at 20 nM to each sample and gently mixed just prior to analysis, and 50,000 cells were FACS-analyzed using BD LSRII flow cytometer (BD Biosciences).
The membranes were incubated in 5% PBSmilk solution for 1 h, then with the primary antibody (1:1000) against ubiquitin (3933 S, Cell signaling), RanGAP1 (330800, Thermo Fisher Scientific), p62/SQSTM1 (abcam56416) Nup153 (Abcam 247000), NPC (abcam Ab24609), G3BP1 (proteintech 13057-2-AP) in PBS overnight at 4 °C, washed 3 times with PBS and incubated with anti-mouse (Abliance BI4413) or rabbit (Abliance BI2407) horseradish peroxidase-conjugated secondary antibody. After washing three times with PBS, the membranes were developed with ECL Luminata Forte Western HRP (Millipore) and scanned with a BioRad Molecular Imager ChemiDoc XRS +. Stain free detection was used as loading control and image analyses were performed using ImageLab BioRad software.
Acknowledgements The authors would like to thank  Andrea CHICI  ( Neuromuscular Disease Unit/ALS Clinic, Kantonsspital St. Gallen, St. Gallen, Switzerland), Pierre de la Grange (Genosplice, Paris, France ),  Danielle Seilhean  ( ICM, Paris, France ),  Charles Duyckaerts (ICM, Paris France) ,  NeuroCEB (Paris, France) , the Généthon cell and DNA bank ( Evry, France ) for patient tissues, DNA and lymphoblasts, and  Anca MARIAN  ( Imagine ) for technical assistance, iGenseq and iCONICS core facilities ( Paris, France ) for whole exome sequencing data. Image acquisition and image analysis were performed on the Imaging Platform of the CRBS,  PIC-STRA UMS 38, Inserm, Unistra. We would like to thank the  DEMENTIA-Seq  and the AnswerALS consortia for providing genomic data used in this manuscript.
This study was funded by  Agence Nationale de la Recherche  ( ANR-16-CE92-0031 ,  ANR-16-CE16-0015 ,  ANR-19-CE17-0016 ,  ANR-20-CE17-0008  to L. D. ),  Fondation pour la recherche médicale  ( DEQ20180339179  to L. D. and post-doctoral position to SaM),  Axa Research Funds rare diseases  award  2019  (L. D. ),  Fondation Thierry Latran  (HypmotALS to L. D. and F. R. and Trials to F. R. ), Motor neuron disease association MNDA Dupuis/Apr16/852-791 (L. D. ),  Association Française contre les Myopathies (AFM-Téléthon , # 19466  to StM, # 23646  to L. D. and E. S. ),  Radala Foundation for ALS Research  ( 2019  to F. R. , 2020 to L. D. and  E. S. ), Deutsche Forschungsgemeinschaft (German Research Foundation ) (Project-ID  251293561 ,  CRC 1149 , individual grants  443642953 ,  431995586  and  46067541  to F.
Data availability The GWAS discovery/replication summary statistics and QTL annotation data generated in this study have been deposited in the zenodo database link: https://zenodo. org/record/7385500#. Y4h06uzMKBQ. The following publicly available datasets were used in this project: NIH Genome-Wide Association Studies of Amyotrophic Lateral Sclerosis; accession code: phs000126. v1. p1, Genome-Wide Association Study of Amyotrophic Lateral Sclerosis in Finland; accession code: phs000336, Genetic Epidemiology of Refractive Error in the KORA (Kooperative Gesundheitsforschung in der Region Augsburg) Study; accession code: phs000125. v1, International Age-Related Macular Degeneration Genomics Consortium-Exome Chip Experiment; accession code: phs000187. v1. DEMENTIA-SEQ: WGS in Lewy Body Dementia and Frontotemporal Dementia; accession code: phs001963.
v2. p1, AnswerALS; accession code: https://www. answerals. org/ The singlecell ATACseq data used in this study are available under the accession: https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE147672 Other data generated in this study are provided in the Supplementary Information/Source Data file. Source data are provided with this paper.
Conclusion In this article, we have assessed the ability of N 2 -derived nitrides N MoN and P MoN to act as the Lewis base component of an FLP system for SiÀ H and BÀ H bond cleavage. While both species were shown to be competent for SiÀ H bond activation of tertiary silanes, affording cationic silylimido species N 2 and P 2, BÀ H bond activation of Piers' borane could not be achieved, stable Lewis acid-base adducts N 3 and P 3 being formed instead. Computed Gibbs free energies of these reactions in the case of N MoN were found consistent with the observed reactivity or lack thereof. Unlike previously described with other hydroboranes,  [8]  P MoN did not undergo 1,2-BÀ H bond addition over the MoÀ N linkage. Structural data could be collected from crystalline materials obtained from the reactions involving N MoN, allowing for a comparison between the new species as well as with previously reported ones.
Triethylsilane and triphenylsilane were purchased from Sigma-Aldrich; the former was distilled over CaH 2 , degassed and stored in the glove box; the latter was used as received. 1 H, 11 B,  19  F,   19  F,  29  Si and 31 P NMR spectra were calibrated according to the IUPAC recommendation using a unified chemical shift scale based on the proton resonance of tetramethylsilane as primary reference. [27] Data are reported as follows: chemical shift, multiplicity (br = broad, s = singlet, d = doublet, t = triplet, q = quartet, p = quintet, m = multiplet), coupling constant (Hz), and integration. Infrared (IR) spectra were recorded in the glove box on an Agilent Cary 630 FTIR spectrophotometer equipped with ATR or transmission modules and are reported in wavenumbers (cm -1 ) with (s) and (m) indicating strong and medium absorption, respectively.
The structures have been solved by Direct Methods and refined by means of least-squares procedures using the SHELXS97  [28]  program included in the software package WinGX version 1. 63  [29]  or with the aid of the software package Crystal. [30] The Atomic Scattering Factors were taken from International tables for X-Ray Crystallography. [31] Hydrogen atoms were placed geometrically and refined using a riding model. All non-hydrogens atoms were anisotropically refined. Deposition Number(s) 2218305 (for N 1), 2218306 (for N 2b) and 2218307 (for N 3) contain(s) the supplementary crystallographic data for this paper. These data are provided free of charge by the joint Cambridge Crystallographic Data Centre and Fachinformationszentrum Karlsruhe Access Structures service.
Acknowledgements A. C. is grateful to the  French Ministry of National and Superior Education and Research (MENESR)  for a Ph. D. fellowship. L. M. thanks  Mitacs  for a Globalink research fellowship. A. S. , D. S. and Q. L. D. acknowledge the  European Research Council (ERC)  for funding (Grant Agreement 757501). All authors are indebted to the  French National Center for Scientific Research (CNRS)  for financial support. S. B. and N. M. acknowledge financial support from the  Université de Toulouse.