dataesr/scientific-paragraphs-categorization huggingface dataset:
Upon extensive quality control, SCRINSHOT (64-gene panel with high sensitivity), ISS (160-gene panel with highmedium sensitivity) and ST/VISIUM (untargeted method) were used as integrating spatial transcriptomic methods. Spapros probe selection was used for targeted methods  [46]. Expression patterns were compared using VISIUM-based spatial transcriptomic methods and ST-Cell type deconvolution using stereoscopic imaging was used to predict which cell type can appear at specific locations  [47]. A machine learning-based segmentation using BIAS software for single-cell level analysis detected 6535 nuclei segmented in 20 min with 70-95% efficiency compared with 9574 nuclei segmented manually in 24 h. Probabilistic cell typing using pciSeq, identification of cell types by SCRINSHOT and niche analysis were utilised to identify cell types, cell communication networks and gene expression  [48].
The identification of the cellular niches present in healthy lung serves as a reference for the identification of abnormal disease-associated cell niches. Amanda Oliver (Cambridge, UK) then discussed how to combine scRNAseq and spatial data to generate a spatial lung atlas. VISIUM analysis was performed to investigate where the cells identified by scRNAseq suspension data [49] aligned in the context of the tissue. 80 cell types/states and their spatial organisation were identified, including 11 novel cell types/states not detected in the consensus dataset. The VISIUM analyses were combined with manual structural annotations and with the cell2location algorithm as unbiased analysis to predict which cell types are present in each location, to colocalise cell types/states [50]. This approach identified localisation of new cell types, such as peribronchial fibroblasts, which have been associated with lower lung function and COPD by functional GWAS, and are enriched in idiopathic pulmonary fibrosis (IPF) samples compared to controls  [51].
Cell signature deconvolution of bulk RNA-sequencing data showed that aberrant basaloid and myofibroblast states appear early in IPF and persist  [52] , with KRT17 + KRT5 -basaloid cells more abundant in early-stage IPF. Laser capture microdissection coupled with mass spectrometry was used for analysis of their interaction with mesenchymal cells. A pilot experiment identified specific niche proteomes with distinct ECM composition, indicating that the matrisome is a good disease predictor. An organotypic ex vivo model of human lung fibrogenesis ( precision-cut lung slices) was used to functionally validate potential targets. This model showed signs of disease progression upon treatment with a pro-fibrotic cytokine cocktail  [53] , especially early stages, correlating with in vivo models and patient data.
Provenance: Commissioned article, peer reviewed. Conflict of interest: S. Cuevas Ocaña was supported by an Action for Pulmonary Fibrosis award to support attendance at the European Respiratory Society International Congress 2022. S. Rolandsson Enes declares personal consulting fees from Swedish StromaBio AB outside the submitted work. C. Voss declares research funding and salary from the European Union's Horizon 2020 research and innovation programme under grant agreement https://doi. org/10. 1183/23120541. 00561-2022.
2  A systematic literature review confirmed that the largest proportion of costs are attributed to indirect costs due to reduced productivity at work. 19 However, no literature was identified reporting on DED-related productivity loss or indirect costs in Europe. We report the results of a patient survey, which aimed to assess the burden of self-reported DED among adults in eight European countries. The objective of the present study was to assess country-specific descriptive data in a large number of subjects; however, the study was not designed to compare the burden of DED between countries.
The number of panel points varied depending on the duration of participant's tenure in the panel and were in line with local regulations/guidelines. All data were anonymised. The study documents, including screener, consent form and study questions, were approved by a central institutional review board. Two convenience samples were recruited: (1) participants with self-reported DED and (2) participants without self-reported DED. Participants were asked to select any medical condition they experience from a list of conditions (online supplemental table 1). Those who indicated a diagnosis of DED from the list of medical conditions were included in the DED group. Participants were also included in the DED group if they reported having at least two of the six most common symptoms of DED at the time of the survey (eye discomfort, including feelings of dryness, grittiness or soreness in the eyes; burning sensation in the eyes; feeling as if something is in the eye; eyelids that stick together on waking; temporarily blurred vision, which usually improves blinking; tired eyes).
Acknowledgements The authors would like to thank  Jessica Commane ,  Liam Marshall ,  Phillip Cooney  ( Novartis Ireland, Dublin, Ireland ),  Sameena Haque  ( Novartis Pharmaceuticals UK, London, UK ) and  Charis Lau  ( Novartis Pharmaceuticals Corporation, USA ) for their contribution in the interpretation of data, and  Deepshikha Roy  and  Gurpreet Kaur Virya  ( Novartis Healthcare, Hyderabad, India ) for their medical writing support and editorial assistance. Contributors KGB, EMM, JB-d-C, JM, BS, PO'B, MJQ, MR and ML contributed to the concept and design of the study. JM performed data acquisition. JM, PO'B and BS collaborated on the analysis and interpretation of data. KGB, EMM, JB-d-C, JM, BS, PO'B, MJQ, MR and ML drafted the manuscript and revised it critically for important intellectual content.
The cardiac action potential (AP) is a key species-specific feature of cardiomyocytes that occurs in response to coordinated actions of ion channels. It represents the first step of the cardiac excitation-contraction coupling and it is crucial for cardiomyocyte (CM) physiology. Changes in the cardiac AP may primarily occur as a consequence of diseases or as a direct or unwanted response to drugs. Our ability to quantify these changes defines the reliability of our measurements and its throughput. Cardiac AP parameters are often quantified through manual time-consuming data analysis protocols or custom-made and proprietary data analysis pipelines; to the best of our knowledge, no tools are currently available for automated cardiac AP analysis and AP parameter quantification. Here we introduce a free and open source software tool named Batch Action PoTential Analyser (BAPTA), written in the R language, designed to i) overcome the inherent operator-dependent bias on trace selection affecting reproducibility, ii) vastly improve the throughput of the analyses of large datasets and iii) analyse both spontaneous and triggered APs from CMs of multiple species and origin.
The same strategy has been successful for our previous tool, MUSCLEMOTION  [7] , in the analysis of contraction profiles from high-speed movies of beating CMs from multiple species. Examples currently exist for the analysis of neuronal APs  [8] , sinoatrial node cells  [9]  and optical mapping in whole hearts  [10, 11] , but a solution for atrial and ventricular single cell data in multiple species is currently lacking. Here, we propose an open source software tool named Batch Action PoTential Analyser (BAPTA), written in the R language  [12] , which is capable of automatically extracting key features of APs from spontaneously beating or electrically stimulated (paced) CMs from multiple species at high-throughput. We extensively validated BAPTA with four different use-cases to assess: 1) pharmacological effects on spontaneously-beating sinoatrial node (SAN) CMs derived from mice; 2) electrophysiological changes on AP caused by a cardiomyopathy in rat adult ventricular CMs; 3) the rate-dependence of AP properties in adult guinea pig CMs; 4) the maturation status of ventricular-like human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).
Spontaneously beating CMs In spontaneously beating CMs, the identification of a Maximum Diastolic Potential (MDP) and APDs are more challenging, particularly in situations where Vm oscillations significantly alter the AP contour. The automatic detection of peaks was achieved through iterative steps aimed to improve the accuracy of the readout. BAPTA identifies peaks with the findpeaks function in the pracma package  [20] , using a threshold minimum peak height which can be customized by the user in the interface to exclude -if required-every non-physiological alteration of the membrane potential that cannot be attributed to the AP. An additional level is introduced to ensure that all the peaks are picked up correctly by looping through all the values above the minimum peak height to verify whether they are the true peaks or artifacts.
Discussion Efficient and scalable methods to analyse electrophysiological parameters represent a significant benefit for scientists and laboratories working on cardiovascular electrophysiology. Here we have presented BAPTA, an easy-to-use open source software tool for the automatic analysis and quantification of relevant parameters of cardiac APs acquired with patch clamp. Overall, its integration into current research practices will significantly facilitate the assessment of cardiac cellular electrophysiology and will improve data sharing, reproducibility and comparisons of those working in stem cell biology departments lacking expertise in electrophysiology or laboratories aiming to optimize data analysis. The applications for BAPTA are very broad and include: i) the assessment of the effects of drugs on the cardiac APD  [3] ; ii) the identification of a disease phenotype associated with cardiac channelopathies and in particular with APD shortening, as in the Short QT Syndrome  [37] , APD prolongation as in the Long QT Syndrome  [38] , or with changes in the AP contour such as in the Brugada Syndrome  [39] ; iii) the comparison of species-specific AP features and iv) to rapidly establish the effects of genetic variants of unknown significance  [40].
Similarly to the previous software tool MUSCLEMOTION  [7] , BAPTA can be expanded and integrated into large data analyses pipelines and coupled with other software tools to automatically quantify biological parameters as calcium transients or contractility. Here, BAPTA was effective in the analysis of APs from the most widely used species and platforms in both academia and industry. The reliability of BAPTA was assessed on a broad range of experimental conditions and on a wide range of AP shapes, making us confident that such capabilities will extend to APs from species not specifically tested here (e. g. APs from zebrafish CMs, adult mouse CMs, human atrial CMs, etc. ). Currently, to the best of our knowledge, open source solutions for the analysis of spontaneous and triggered cardiac APs exist but they are often limited by command-line input interfaces; a few commercial solutions might partially circumvent this limitation, but usually require programming skills, extensive timing for manual data analysis, costly licences and rely on proprietary and closed source software environments.
The reason behind this is the automatic steady-state selection that prioritizes hyperpolarized APs in stable regions of the recordings rather than using the last sweeps of the recordings as generally performed manually. As previously mentioned for SD1, this systematic behavior is reproducible across different datasets and does not affect the final results in case all datasets were analyzed with the reproducible criteria included in BAPTA. A massive gain in the time spent for the analyses was also achieved: the manual analyses of the data included in this manuscript took several weeks to be completed, while the very same data could be analysed by BAPTA overnight. Overall, BAPTA provides quantitative information on relevant cardiac AP parameters in multiple conditions, significantly improves the reproducibility and throughput of current-clamp data analysis and offers solid and efficient operator-independent readouts that perfectly couples with large high throughput screening capabilities.
This work was supported by a Marie Skłodowska-Curie Individual Fellowship (H2020-MSCA-IF-2017; Grant Agreement No. 795209, LS), a Fondazione CARIPLO, "Biomedical Research Conducted by Young Researchers" (Grant No. 2019-1691, LS), a Leducq Foundation grant (18CVD05, PJS, LS, LC), and a PhD fellowship from the University of Verona (VL), CVie Therapeutics Limited (Taipei, Taiwan), Windtree Therapeutics (Warrington, USA), and FAR2019 of the University of Milano-Bicocca (ET, CR, MR, AZ) , Fondation Leducq (No. TNE FANTASY 19CV03, ET).
4:1 and eluted with 12 µl EB. Quantity and fragment size of the libraries were determined with a Qubit dsDNA HS assay kit (#Q32854, Invitrogen) and a TapeStation 4150 with D1000 High Sensitivity Assay (#5067-5585, Agilent; Santa-Clara; California, United States), respectively. Six to eight differently barcoded libraries were multiplexed and sequenced on a single lane of a NextSeq™ 550 system (paired-end, 75 bp, Illumina; San Diego, California, United States) with mid-output at the Genome and Proteome Core Facility of DKFZ. ACT-seq data was analyzed as previously described  32. For oligonucleotides sequences, see Supplementary Table  3.
Identification of a putative novel oncogenic neo-enhancer associated with an intergenic 3'TAL1 microinsertion To investigate TAL1 deregulation mechanisms, we took advantage of the Blueprint Consortium T-ALL ChIP-sequencing series  33, 34. We focused on H3K4me3 and H3K27ac enrichment over the TAL1 locus in eight primary T-ALL samples and the normal thymus (Figure  1A ). TAL1 expression was analyzed using available RNA-seq data (n=6) and/or RQ-PCR (n=8). Five patient samples displayed high TAL1 expression and were considered TAL1 positive (TAL1+) and three TAL1 negative (TAL1-) (Supplementary Figure  1A-B ). Allelic expression analysis by RNA-seq and Sanger sequencing revealed that all five TAL1+ samples had monoallelic TAL1 expression, indicating in cis-deregulation mechanisms (Figure  1C -E and Supplementary Figure  1C ).
We screened TAL1+ patients for the known recurrent mechanisms of TAL1 deregulation. Of these five TAL1+ patients, one patient (UPNT-760) had a SIL-TAL1 microdeletion, one patient (UPNT-885) had the 5' superenhancer mutation (5'SE) and one patient (UPNT-820) had a translocation involving TAL1 and the TRB locus. Two patients (UPNT-753 and UPNT-802) had unidentified TAL1 deregulation mechanisms and were considered "unresolved". ChIP-seq data for H3K27ac and H3K4me3 marks showed enrichment over the TAL1 gene body in all five monoallelically expressing TAL1+ patients (Figure  1A ). As expected, H3K27ac enrichment encompassing the 5'super-enhancer was observed in the UPNT-885 sample. In addition, we noticed a unique dual monoallelic enrichment over an intergenic region downstream of the TAL1 gene in one unresolved monoallelic TAL1+ patient (UPNT-802) that was absent in all other TAL1+ patients, suggesting the presence of a novel regulatory element (Figure  1B  and Supplementary Figure  2 ).
ONT sequencing of TAL1 transcripts Total RNAs purified from Jurkat cells and PDX cells were reverse transcribed with dT (2/3) and random (1/3) primers and Maxima H Minus Reverse Transcriptase (Thermo Scientific). Prior to ONT sequencing, TAL1 transcripts were amplified with different primer pairs for 40 amplification cycles using Phusion Plus DNA Polymerase and analyzed by agarose gel (see Figure  5C ). For ONT sequencing, each TAL1 amplicon was processed independently in each sample by two PCR steps  6. First, a pre-amplification of 24-cycles with specific primers corresponding to the first and last exons, and then a second amplification of 20-cycles to add the barcodes. The multiplexed library was constructed using the Oxford Nanopore SQK-LSK109 kit and sequenced on MinION device. Raw data was processed for base calling using "GUPPY [https://community.
nanoporetech. com/downloads] and long-read sequences were analyzed with a homemade pipeline. Briefly, using "LAST version 1205 [https://gitlab. com/mcfrith/last]", the sequences were aligned to the Human Genome hg19 and the corresponding BAM files were reviewed manually to annotate all exons. Exons were used to produce a universal reference and all reads were aligned to this particular reference with LAST. Using standard genomic tools, samtools, bedtools, a specific transcript barcode was generated for each sequence depending on its exon architecture, then pooled in clusters defining each alternative TAL1 transcripts. Given the library preparation, we only retained the sequence containing at least the first and last exons in their barcode. Finally, we only retained transcripts seen 10 times.
The authors would like to thank the Genomics and proteomics Core facilities at DKFZ We would also like to thank  Guillaume Charbonnier  for his help processing the NGS data and Frederic Tores from the bioinformatics platform of  Imagine Institute  for the ONT analysis. The study was supported in part by the  Helmholtz-Foundation. AT was supported by the  DKFZ Postdoctoral  fellowship. The Work in the VA lab was supported by  ARC-Labellisation and the associations "Force hémato" and "Laurette Fugain. "This study was also supported in VA and SS lab by grants from  INCA   PLBIO18-031 ,  PLBIO 2018-00252 , and ITMO Cancer Epig-2015. SS was supported by la Ligue Contre le cancer (labellisation 2018) and the RNAsequencing was funded by  LIGUE. This work was also supported by the  La Fondation pour la Recherche Médicale  with the grant,  FDT202012010638 , which was attributed to CS.
Remarkable structural homologies between the main proteases of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the avian infectious bronchitis virus (IBV) were revealed by comparative amino-acid sequence and 3D structural alignment. Assessing whether reported IBV 3CLPro inhibitors could also interact with SARS-CoV-2 has been undertaken in silico using a PubChem BioAssay database of 388 compounds active on the avian infectious bronchitis virus 3C-like protease. Docking studies of this database on the SARS-CoV-2 protease resulted in the identification of four covalent inhibitors targeting the catalytic cysteine residue and five non-covalent inhibitors for which the binding was further investigated by molecular dynamics (MD) simulations. Predictive ADMET calculations on the nine compounds suggest promising pharmacokinetic properties.
Introduction Potential drugs able to fight the coronavirus disease 2019 (COVID-19) are still very scarce  [1]. Several compounds have been reported to be active on the spike protein, the RNA-dependent RNA polymerase, the 3C-like (3CLpro, or Main protease, M Pro ), and papain-like (PLpro) viral proteases  [2] , and repurposing approaches were also released  [3] [4] [5]. Bioinformatics and molecular docking techniques applied to available databases and XRD protein structures are essential tools for the discovery of new compounds and therapies effective against COVID-19  [6] [7] [8] [9] [10]. Among possible targets, the main protease (M pro ) is the most studied one owing to its crucial role in the virus replication process  [11] [12] [13] , and either non-covalent M pro inhibitors  [14]  or covalent ones targeting the catalytic cysteine residue  [15] [16] [17] [18] [19] [20]  have been described.
The purpose of the present study is to contribute to the identification of other potential drugs using bioinformatics tools, namely homology modeling, molecular docking, XRD structures, and available databases of molecules related to two severe acute respiratory syndrome coronavirus (SARS-CoV) main proteases, the avian infectious bronchitis virus (IBV) 3CLPro and the SARS-CoV-2 M Pro. The PubChem BioAssay database collects and describes biological screenings and other assays, including the protocols and the structures of active (and inactive) compounds  [21, 22]. The idea is to start with a PubChem database of inhibitors active against the avian IBV 3CLPro and look for compounds that could also interact with the SARS-CoV-2 M Pro. The bioassay AID 1706, deposited in 2009 by The Scripps Research Institute Molecular Screening Center, is part of the project "Summary of probe development efforts to identify inhibitors of the SARS coronavirus 3C-like protease (3CLPro)" from the avian infectious bronchitis virus  [23] [24] [25] [26] [27].
The collection of 290,726 samples was tested for the inhibition of the peptide cleavage by 3CLPro using a fluorescent peptide. Among the 405 compounds active on the enzyme, 388 have their 3D structures directly retrievable from the database and can be used for further in silico investigations. The structural similarity between the 3C-like proteases in coronaviruses supports the interest in undertaking docking studies of compounds active on the avian IBV within the active site of the SARS-CoV-2 M Pro. With the crystal structures of the SARS-CoV-2 M Pro in complex with a covalent inhibitor  [28]  and of the IBV main protease  [29]  being both available, protein structure homology and docking studies of 3CLPro inhibitors to specifically target the SARS-CoV-2 M Pro active site were performed. Both non-covalent and covalent potential inhibitors were considered.
The stability of the complex of the protein and the potential non-covalent inhibitors was assessed by molecular dynamics (MD), and the predictive ADMET properties were examined. 290,726 samples was tested for the inhibition of the peptide cleavage by 3CLPro using a fluorescent peptide. Among the 405 compounds active on the enzyme, 388 have their 3D structures directly retrievable from the database and can be used for further in silico investigations. The structural similarity between the 3C-like proteases in coronaviruses supports the interest in undertaking docking studies of compounds active on the avian IBV within the active site of the SARS-CoV-2 M Pro. With the crystal structures of the SARS-CoV-2 M Pro in complex with a covalent inhibitor  [28]  and of the IBV main protease  [29]  being both available, protein structure homology and docking studies of 3CLPro inhibitors to specifically target the SARS-CoV-2 M Pro active site were performed.
Homology Studies The PDB structures of 3C-like proteases of avian IBV (PDB code 2Q6F)  [29]  and of SARS-CoV-2 (PDB code 6Y2F)  [28]  were downloaded from the PDB database. The multiple sequence alignment was obtained using the T-COFFEE server  [34] , with the corresponding FASTA file retrieved from the NCBI database. The ESPript server  [35]  used with the clustal W file generated the multiple sequence alignment. The PyMOL software generated the 3D-structural alignment between the two proteins and the comparison of the two active sites with divergent amino acids in the surroundings of the catalytic dyad shown in magenta.
Docking Studies for Covalent Inhibition The library of compounds active on the main protease of the avian IBV 3CLPro was obtained from the PubChem Bioassay (code AID 1706, https://pubchem. ncbi. nlm. nih. gov/bioassay/1706 (accessed on 5 June 2023)). A set of 388 compounds (out of 405) with their structures fully retrievable were downloaded as an SDF file. This library was then scrutinized to search for compounds bearing a soft electrophilic moiety, resulting in a sublibrary of 40 compounds (Table  S1 , Supplementary Information). Each of them was then docked within the M Pro active site of SARS-CoV-2, centered on the β-keto amide inhibitor, using the Arguslab software v4. 0. 1 (ArgusLaB 4. 0. 1; WA planetaria Software LLC: Seattle, WA, USA, 2004)  [36, 37]  with the Argusdock engine and default parameters.