dataesr/scientific-paragraphs-categorization huggingface dataset:
Enhancer RNAs For eRNA published annotation in HCT116 of conservative eRNA was used  50. Beside the eRNA placed outside of annotated genes, we analysed how many of these eRNA fall into regions of the upregulated genes de ned in CYTO-seq. In total, 362 GENCODE annotated RNAs overlap with the upregulated eRNAs (with at least 1 nt of overlap), including 298 lncRNAs and 27 PCG, and 342 Scallop annotated lncRNA. For further analysis those RNAs were classi ed as eRNAs.
Recursive analysis For the gene to be retained in the nal list, it had to be differentially expressed in the same direction in both control + versus tagged cells + but also between tagged cells -versus tagged cells +, if in the latter the same gene was not differentially expressed between control cells -versus control cells +. For XRN1-AID dataset rst comparison: control + versus clone + and clone -versus clone + was performed for each clone independently and intersected with addition of genes differentially expressed for both clones in only comparison of clone -versus clone + but not in control cells -versus control + was retained in the list (Fig S6B ), where + indicates addition of auxin.
Metagenes In order to select the wanted parts (exons and introns), we have created rstly metatranscripts as follows: the exons from all the transcripts of each gene were merged with BEDTools v2. 29 108 , in order to have non-redundant segments of exons, and these exons were numbered; introns were inferred from these exons. The rst exon, rst intron, second exon, last intron and last exon were selected for each gene. The alignment les were converted in BigWig les with RPM normalization (reads per million of mapped reads), using UCSC tools (http://hgdownload. cse. ucsc. edu/admin/exe/linux. x86_64/), and for each part and each gene, the read coverage was extracted. The obtained signal was scaled on 100 positions using the R base approx function (allows to compute interpolations), with the following parameters: method="linear", ties="ordered".
The average value was computed at each of the 100 positions, and the result was plotted using the R packages: rtracklayer 109 and ggplot2 110. Active ORFs detection Ribotricer 1. 3. 1 111 was used to detect long and short actively translating ORFs. The rst step consisted in the generation of all candidate ORFs from the combined GTF annotation (GENCODE v26, Scallop and eRNAs) and hg38 genome, by using the command "prepare-orfs" with the following parameters: --start_codons "ATG, CTG, TTG, GTG, AGG, ACG, AAG, ATC, ATA, ATT" -min_orf_length 30 -longest. The resulting table was converted into GFF by custom command lines. The second step consisted in the use of the command "detect-orfs" to determine translating ORFs from the candidate ORFs for each Ribo-seq alignment. The GFF across all the samples were concatenated and then the redundancies were ltered out based on the following columns of the GFF: chromosome, start, end, strand, attributes.
Read counting and Differential expression Read on gene, exon, and ORF levels were performed on the combination of the human gene annotation GENCODE v26, eRNAs, and new transcripts from Scallop, using featureCounts v2. 0. 0 112 with the parameters -s 2 -O 9 (raw counts for Ribo-seq for each of gene features are presented in Fig. S3B  and table  S5 ). Analysis for Fig1 were done using GENCODE annotation for normalization of DESeq2 data for unreferenced genes. For further quanti cations, modi ed annotation including eRNA and Scallop transcripts was used. The conditions were compared using DESeq2, with the following parameters: betaPrior=FALSE, independentFiltering=F, cooksCutoff=F. Only the features with adjusted p-value <= 0. 05, read counts >=20 and abs(log2FoldChange)>= 0. 585 were retained as differentially expressed.
Heatmaps of expression were obtained using the R package ComplexHeatmap from bioconductor 113. HLA binding prediction HLA alleles from MM patients were determined using the tool seq2HLA  76. ORFs candidates were converted into peptides using the SeqinR R package, and only the ones with a length >= 8 amino acids were kept. The lists of peptides and HLA alleles were given to the tool netMHCpan-4. 1 in order to determine the binding status. Only the peptides with an elution ligand rank <= 0. 5 were kept for downstream analysis. S1  and S2 ). E) Supervised clustering heatmaps of a z-score of differentially expressed genes (n=7644) in DIS3-AID in comparison to a control (cntrl), treated (+) or not (-) with auxin.
Acknowledgments We would like to thank to  Munich Leukemia Laboratory  especially (MLL) especially  Claudia Haferlach  and  Wencke Walter  for access to MM patients data, imaging platform at IGH,  ICGex -NGS platform Institut Curie  especially  Sonia Lameiras  and  Virginie Raynal , The Cell and Tissue Imaging Platform - PICT-IbiSA  (member of France-Bioimaging - ANR-10-INBS-04 ) of the [UMR144 or  U934/UMR3215  or  UMR3664  or  UMR168  or Translational Department or NIMCE] of  Institut Curie  for help with light microscopy, especially  Olivier Leroy. Rocco Cipolla ,  Ugo Szachnowski ,  Matthieu Lejars ,  Setareh A aki ,  Perrine Verdys ,  Yago Arribas De Sandoval  and  Arthur Imbert  for technical assistance and discussions. Michael Schertzer  for critical reading of the manuscript. Nolwenn Jouvenet  for support and discussions.
A. M. and M. P. , were supported by the  European Research Council  ( ERC- consolidator  DARK-616180-ERC-2014 ). This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Sklodowska-Curie  grant agreement No  795109. This funding was attributed to DF. SW is funded by a  Wellcome Trust   Investigator Award  ( 223106/Z/21/Z ). This project was supported by a  VLIR  interuniversitaire onderzoeksprojecten ( MIMICRY -Modulating Immunity  and the  Microbiome for effective CRC ). Marina Serna  and  Oscar Llorca  acknowledge the support of the  National Institute of Health Carlos III to CNIO.
Patients Data and GTEx analysis: The data concerning patients samples were previously published  74. New counting on the raw reads was performed using kallisto  75. All further analysis followed the standard DESeq2 protocol. The extended ORF annotation for kallisto indexing for counting of expression in both our MM dataset and GTEx tissue samples. We performed querry on both the Ribo-seq identi ed DIST-ORFs candidates in addition to DIST-ORFs with detected peptides in immunopeptidomic analysis. We used the 90 th percentile values and TPM≤1 to de ne as threshold for de ning the ORFs speci cally expressed in MM, excluding testis.
Acknowledgments: The authors thank  Mélanie Annoussamy ,  Valérie Fauroux  and  Alexandra Bruneau  from  URC-CIC Paris Descartes Necker/Cochin  for implementation, monitoring, and data management, all patients and experts for sharing their views about functioning in patients with systemic sclerosis, and all scientific societies who accepted to circulate our survey:  Groupe Francophone de Recherche sur la Sclérodermie, Filière de Santé des Maladies Auto-Immunes et Auto-Inflammatoires Rares, Centre de Référence des Maladies Rares Orales et Dentaires, Société Française de Médecine Physique et de Réadaptation ,  Société Française de Rhumatologie ,  Société Française de Dermatologie ,  Société Nationale Française de Médecine Interne, Société Francophone de Néphrologie Dialyse et Transplantation, Société Française de Physiothérapie, Club Rhumatismes et Inflammations, Groupe ORPHALUNG, Association Nationale Française des Ergothérapeutes, Association des Jeunes Internistes, Association des Jeunes en Médecine Physique et de Réadaptation et Rhumatologues en Formation.
North American Consortium for the Study of End-stage Liver Disease (NACSELD) ACLF The NACSELD proposed a definition of ACLF in 2014, based on the analysis of the NACSELD database, which included 507 patients with acutely decompensated cirrhosis with infection  [10]. Four organ systems (circulation, respiration, kidney, brain) were assessed, and the presence of ≥ 2 OFs was defined as ACLF. The definition did not include changes in liver function and coagulation, which are the typical pathophysiological manifestations of ACLF.
Patients with chronic liver disease (with or without cirrhosis), with any type of precipitating event (intrahepatic or extrahepatic), and extrahepatic OFs should be included for data collection to ultimately arrive at a comprehensive definition of ACLF. More efforts are also required to develop and validate more accurate prognostic scores that can accommodate various aetiologies and phenotypes around the world. In addition, the unmet medical needs of diagnosing patients who have a high risk of progression to ACLF (pre-ACLF) at admission are eagerly awaited to be addressed in future studies. Using advanced approaches such as transcriptomics, proteomics and metabolomics, biomarkers including inflammatory markers, cell-death markers and functional characteristics of immune cells would also help accurately identify pre-ACLF patients to refine clinical prognostic models and provide novel therapeutic targets  [94].
Statistical methods Based on the effect size of interest (the N13 SEP amplitude change after secondary hyperalgesia induction, corresponding to Cohen's d 1. 8; G-Power 3. 0 a 0. 05; b 0. 95), we calculated the sample size of n = 14 participants needed to detect a difference in the N13 amplitude, comparable to that described in a previous study (Di  Lionardo et al. 2021). For each condition (HFS/LFS), descriptive summaries for the latencies and amplitudes of each SEP component (i. e. , N9, N13, N20-P25) are shown as mean ± standard deviation (SD) (Table  1 ). Cohen's d is used to calculate effect sizes. The Shapiro-Wilk test was performed to evaluate the data distribution, and the results showed that our variables had a gaussian distribution. One-way repeated measures analysis of variances (ANOVA) was used to compare pain ratings at the first minute, minute eight and at the end of LFS conditioning.
Two-way ANOVA, and post hoc multiple comparisons with Sidak's correction when significant, were used to assess the effect of time (before and after secondary hyperalgesia induction) and side (active vs. control) and their interaction on the amplitude of SEP components, separately for the two different human models of secondary hyperalgesia used. T-test for unpaired data was used to compare the percentage of change pre vs post conditioning between HFS and LFS, to test if the two experimental pain models differently modulated the N13. To test the intrinsic variability of the N13, we calculated the percentage of change in the two consecutive blocks of 650 stimuli. To test if the difference observed due to the conditioning model outclassed the intrinsic variability of the N13, we performed a t-test between the percentage of change between blocks and the percentage of change pre vs post conditioning.
Results The mean intensity of HFS and LFS was 7. 8 ± 2 mA and 2. 8 ± 0. 7 mA, respectively. The pain rating for HFS was 80. 14 ± 17. 9; the pain ratings for LFS were 33. 6 ± 12. 3 at the first minute, 37. 8 ± 12. 8 at minute eight and 39. 3 ± 18 at the end of the stimulation, with no significant difference across the three measures (ANOVA, F  (1. 603, 20. 84) = 0. 6966; p = 0. 2974). In all participants, HFS and LFS induced an area of secondary hyperalgesia. In the 18 participants, the mean radius of the area was 3. 09 ± 0. 8 cm for HFS and 2. 98 ± 1. 18 cm for LFS and the hyperalgesia score was 0. 64 ± 0. 42 for HFS and 0. 32 ± 0. 26 for LFS. The analysis performed on paired data of 10 participants showed a significantly larger radius (3. 29 ± 1. 1 cm for HFS and 2. 8 ± 1. 1 cm for LFS) and a higher score (0.
2 ). The unpaired t-test of the N13 percentage of change between HFS and LFS showed a different effect of the two experimental pain models, though only approaching significance (p = 0. 051, Cohen's d 0. 77). The paired t-test between the N13 percentage of change between blocks and pre vs post conditioning, showed that the increase induced by LFS was significantly higher than the intrinsic variability of the N13 amplitude (t-test of pooled data active/control, n = 28; p < 0. 007, Cohen's d 0. 61). No significant difference was found for HFS (t-test of pooled data active/control, p = 0. 54).
Limitations Admittedly our study has a few limitations. A reliable evaluation of LFS-induced N13 SEP modulation at single subject level is likely prevented by the modest amplitude of ulnar-nervemediated N13 SEP and the slight amplitude increase following LFS. Attention might concur with the differential effect of LFS and HFS on the N13 SEP amplitude changes we found. Prior research demonstrated that nociceptive responses, such as the nociceptive flexion reflex, that are mediated by the dorsal horn, are modulated by attention  (Lannon et al. , 2021). We cannot exclude that HFS and LFS might differentially trigger attention and top-down modulation of N13 SEP. The subjects submitted to both experiments were not the same (10 out of 14), hence we cannot rule out a subject-dependent effect. Lastly, the comparison between the effect of HFS and LFS was calculated through an unpaired t-test, though part of the data were paired.
Conflict of interest and Acknowledgements The authors declare no conflict of interest regarding this work, which has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement  No [777500]. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA. The statements and opinions presented here reflect the author's view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained therein. https://www. imi-paincare. eu; https://www. imi. europa. eu.
Focused 3D classification of the Pol III bound to IN1 dataset showed that approximately one third of the particles contain C11-Ct in the funnel pore (Supplementary Fig. 1 , map B), while the remaining particles presented no density for this domain (Supplementary Fig. 1, map C ). Comparison of structures derived from these two maps uncovered Pol III rearrangements for C11-Ct accommodation, mainly involving opening of the C160 funnel and C128 fork domains using a kink in the C160 bridge helix as hinge, associated with a fully ordered C160 trigger loop (Fig. 3b ). This loop is disordered in reported apo or elongating yeast Pol III structures  12. Additionally, residues R698 and Y701 in C128 switch their conformation to allow access of the C11 acidic loop, comprising residues 88-93 that are involved in RNA cleavage  31  , into the active site (Fig.
3b , inset). Strikingly, focused classification of the Pol III-DNA bound to IN1 dataset showed that virtually all particles contain C11-Ct in the pore (Fig. 1b ; Supplementary Fig. 2 , map D). In contrast, focused classification of the Pol III-DNA dataset, which lacks IN1, produced the opposite result (Fig. 1c ; Supplementary Fig. 3 , map E). In the structure of Pol III-DNA bound to IN1, the Pol III bridge helix presents a straight conformation, associated to a conformational change in the nearby C11 acidic loop, while the trigger loop is fully ordered and retracted (Fig. 3c ). In yeast Pol II, an equivalent configuration with a straight bridge helix and a locked trigger loop has been observed in the reactivated intermediate of backtracking complexed with TFIIS 30 (Supplementary Fig. 9c , left panel).
Cryo-EM grid preparation and data acquisition The crosslinked complex between Pol III and IN1 was concentrated to 1 µM, then 4 µl were applied to glow-discharged copper 300 mesh C-flat 1. 2/1. 3 holey carbon grids (Protochips) in the chamber of a FEI Vitrobot at 10 °C and 100% humidity. The grids were blotted for 3. 5 s with blotting force -5 and vitrified by plunging into liquid ethane cooled with liquid nitrogen. Movies were acquired on a FEI Titan Krios (ThermoFisher) electron microscope at 300 keV using a K3 summit (Gatan) direct electron detector operated in 'super-resolution' mode at defocus values between -1. 0 and -2. 8 µm and a physical pixel size of 1. 06 Å, using EPU software. A total of 3321 non-tilted movies and 8900 movies tilted by 20°with 40 frames each were collected with an accumulated total dose of 42.
45 e-/Å 2. For Pol III-DNA in the presence or in the absence of IN1, 3 µl of the sample at 0. 4 or 0. 1 µM were supplemented with 8 mM CHAPSO (final concentration), applied to glow-discharged copper 300 mesh Quantifoil R1. 2/1. 3 grids coated with continuous carbon, and incubated in the chamber of a FEI Vitrobot at 24 °C and 100% humidity for 1 min. The grids were blotted for 4 sec with blotting force -5 and vitrified by plunging into liquid ethane cooled down to liquid nitrogen temperature. For Pol III-DNA bound to IN1, data were collected on a FEI Titan Krios electron microscope operated at 300 kV, using a K3 summit (Gatan) direct electron detector. Images were acquired at defocus values between -1. 0 and -2. 8 μm and a pixel size of 1. 085 Å. A total of 9327 movies with 40 frames each were collected with an accumulated total dose of 45.
12 e-/Å 2. For Pol III-DNA in the absence of IN1, data were collected on a Talos Arctica electron microscope operated at 200 kV, using a Falcon III (FEI) direct electron detector in electron counting mode. Images were acquired at defocus values varying between -1. 2 and -2. 6 μm at a pixel size of 0. 855 Å. A total of 2901 movies with 60 frames each were collected with an accumulated total dose of 30. 96 e-/Å 2.
Model building and refinement The available structure of the Poll III bound to a transcription bubble (PDB code: 5FJ8) was fitted in the 3D maps using UCSF Chimera  53  and employed as starting point for model building for Pol III subunits and the nucleic acid scaffold. A homology model of the C11 C-terminal Znribbon was generated with Phyre2 54 and used as reference for model building, while the C11 linker was manually modelled in Coot  55. Available structures of Pol III complexed to melted DNA (PDB code: 6EU1) and the Pol III-Maf1 complex (PDB code: 6TUT) were used as reference to improve coordinates of the stalk C17/C25 heterodimer, the C82/ C34/C31 heterotrimer and the C37/C53 heterodimer. The nucleic acid scaffold DNA model was adapted from a stalled Pol I elongation complex (PDB code: 6H67).
Acknowledgements We thank  Tornero   Laboratory  members  Federico M. Ruiz  for helpful advice and  Srdja Drakulic  for technical assistance, and  Amandine Bonnet  from  Lesage Laboratory  for C11 strain and plasmid constructions. We are grateful to  Ernesto Arias-Palomo  at  CIB-CSIC ,  Alistair Siebert  and  Vinod Vogirala  at the  Diamond Light Source , and  Teresa Bueno  and  Rocío Arranz  at the  CNB-CSIC Cryo-EM Facility  in the context of the CRIOMECORR project ( ESFRI-2019-01-CSIC-16 ) for support in cryo-EM data collection. We also acknowledge  Rafael Núñez  at the  CIB-CSIC EM Facility  for help during cryo-EM grid preparation,  Javier Méndez Viera  for yeast fermentation, and  Hung-Ta Chen  for providing pCW4 and pCWAmut plasmids. This work was supported by the  Agence Nationale de la Recherche  ( ANR-17-CE11-0025  to P.
Data availability The data that support this study are available from the corresponding authors upon request. Electron density maps and associated coordinates have been deposited in the Electron Microscopy and Protein Data Banks, respectively, as follows: Pol III + IN1 from focused classification on AC40 (EMD-14421/PDB 7Z0H), on C11-Ct with this domain in the funnel pore (EMD-14469/PDB 7Z30), and on C11-Ct with this domain disordered (EMD-14470/PDB 7Z31); Pol III-DNA + IN1 (EMD-14468/7Z2Z); and Pol III-DNA (EMD-16299/PDB 8BWS). Source data are provided with this paper.
Materials and Methods All patients who underwent 68 Ga-DOTATOC PET in the Department of Nuclear Medicine, Marseille, APHM, between January 2020 and April 2022 for suspected ONSM were retrospectively included. 68 Ga-DOTATOC PET was performed using an integrated PET/CT camera (General Electric Healthcare Discovery PET/CT 710) after the intravenous injection of a 2. 5 MBq/kg radiotracer. A protocol of 7 min of acquisition, 1 h postinjection, was used. Images were reconstructed on a 192 × 192 matrix using the ordered subsets expectation maximisation algorithm and were corrected for attenuation using a CT transmission scan. Standardised clinical and radiological data were recorded. When MR images were available, PET images were fused with the MR images using alignment algorithms. Hence, images could be represented as PET/MRI fused images, even if acquired with a PET/CT camera, and secondarily fused with MRI.
Results Twelve 68 Ga-DOTATOC PET scans for suspected ONSM were analysed. All patients presented with a unilateral optic nerve lesion in MR images. Most MRI examinations showed an isointense T1-weighted lesion with peripheral enhancement. Six examinations were considered positive due to intense 68 Ga-DOTATOC uptake, and six exams were considered negative. Table  1  summarises the main clinical data on the reported cases with their 68 Ga-DOTATOC results. Cases 1 to 6 were considered positive 68 Ga-DOTATOC examinations by virtue of their intense radiotracer binding in the optic lesion, which is strongly suggestive of ONSM (Figures  1 2 3 ). Of these, two patients presented with progressive vision loss at onset, and two were older patients (74 and 82 years old) with rapid vision loss. One patient (case 6) had already Of these, two patients presented with progressive vision loss at onset, and two were older patients (74 and 82 years old) with rapid vision loss.
Statistical analysis Continuous variables are expressed as means ± SD in case of normal distributions, otherwise as medians. Normality was assessed using visual inspection of density plot and Q-Q plot along with the Shapiro-Wilk test. Since most variables were not normally distributed, for quantitative variables possible differences between INVOS and clinical monitoring were assessed by means of a Mann-Whitney U Test. Association between the type of methods used and categorical variables was tested with a χ 2 test. A p-value <0. 05 was considered statistically significant. All data manipulation and analyses were conducted using SPSS version 27 (13).
Of the 6 patients who developed a postoperative ischemic event, 4 had embolization highlighted by post-operative CT and/or MRI which resulted in a non-disabling minor stroke or transient ischemic attack; hyperperfusion injury syndrome was present in 1 patient; and no apparent attributable cause was found in 1 patient. There was no statistical difference in the rate of ischemic events between symptomatic and asymptomatic patients (p = 0. 4413). General anesthesia was performed in 41 (60. 3%) who were monitored by INVOS, while 27 (39. 7%) patients underwent regional anesthesia with awake testing. Data were collected before and during clamping. Mean clamping time was 20 ± 6. 6 min. Table  2  reports data comparing patients who underwent INVOS vs. awake testing. Patients undergoing awake testing had a lower hospital stay and ICU stay during admission (p = 0.
Antifungal and antibiofilm activities of extracts The antifungal activity of the 32 extracts was evaluated against planktonic cells of C. albicans ATCC 28367. All plants, except R. japonica, showed no antifungal activity (MIC > 1000 μg mL À 1 ) (data not shown). Previous studies also reported the absence of antifungal activity of some species of Baccharis spp (e. g. , aerial parts of B. darwinii, B. microphylla, B. petiolata and B. santelicis; leaves of B. dracunculifolia, B. aracatubaensis and B. organensis, cladodes of B. burchellii) against C. albicans. [19, 20] nterestingly, EtOH and EtOH-H 2 O extracts of R. japonica leaves revealed the best antifungal activity, with MIC 50 of 250 μg mL À 1 and 15. 6 μg mL À 1 , respectively. The comparison of our results with those of Lee and Kim suggested that the leaves of R.