dataesr/scientific-paragraphs-categorization huggingface dataset:
S11 , Table  S2 ). When occurring, host switches from bats often occurred toward humans (1. 9 host switches per reconciliation on average) or toward urban-living and/or domesticated animals, such as rats, camels, or pigs (>1 host switch on average; SI Appendix, Table  S3 ). Host switches to humans occurred mostly from domesticated mammals (camels, pigs, dogs), the house shrew and the house mouse, then followed by Asian palm civets, and lastly by bats and other rodents (SI Appendix, Table  S4 ). Results were consistent when subsampling the dataset to have an equal sampling effort per host species, suggesting that our results are not artifactually explained by the enhanced monitoring of coronaviruses in humans or domesticated animals (SI Appendix, Supplementary Information Text). Finally, we found that some sOTUs, in particular from Betacoronaviruses (e.
Mammalian hosts of Coronaviridae All 46 sOTUs of Coronaviridae with a full palmprint and associated data in the NCBI database were screened for the identification of its hosts. From those, 35 sOTUs were associated with mammalian hosts and were kept for downstream analyses. Serratus' associated metadata was used to identify GenBank accession codes linked to each sOTU. The complete set of 90,540 associated GenBank accession codes was screened to obtain the host information for each sOTU (on NCBI, Features>source>/host=). All the host species with a full Linnean name were kept as such. Accession codes with hosts leading to a generic level information were further inspected to identify the associated publication and determine the complete species name.
Dubious cases or accession codes without publications had their hosts disregarded. Common names or high-level host information (e. g. , host="bats") were generally eliminated except in a few cases where a domesticated species was found to be the host (i. e. , host="dog","canine" were Canis lupus; host="cat","feline" were Felis catus; host="pig","piglet","newborn piglet","sucking piglet","porcine","swine" were Sus scrofa). A final dataset of 116 mammalian hosts associated with the 35 sOTUs was assembled and used in downstream analyses. A matrix with the association between Coronaviridae sOTUs and mammalian species is available in SI Appendix, Dataset S1.
Geographic distribution of Coronaviridae We downloaded geographic range maps for each mammalian host species, with the exception of Homo sapiens, from the Map of Life website (https://mol. org/species/); see  (68). These maps follow the taxonomy of the Mammal Diversity Database (69) supplemented with the Handbook of the Mammals of the World (HWM) database and the Alien Checklist database for invasive species  (68). We created a world map with hexagonal, equal-area grid cells of 220km on which we mapped host and coronavirus species diversity, using the Mollweide world projection to accurately represent areas. At large spatial scales, cells with ~220km resolution return more reliable diversity estimates than smaller cells  (70). We considered that a host species was present in any given cell if its range covered at least 30% of the cell area to avoid overestimating diversity.
Patient-reported outcome measures and surveyed data At baseline, after informed consent, data on patient characteristics, comorbidities, and treatment with opioids and other analgesics were collected. In addition, baseline questionnaires/PROMs were used to assess patient-relevant parameters such as quality of life (using the European Quality of Life Five Domains  14  ), depression and anxiety (using the Hospital Anxiety and Depression Scale [HADS]  15  ), pain sensitivity (using the Pain Sensitivity Questionnaire  16  ), pain expectancy, pain catastrophising (using the Pain Catastrophizing Scale [PCS]  17  ), preoperative pain (using the Brief Pain Inventory  18, 19  ), and neuropathic qualities of preoperative pain (using the Douleur Neuropathique en 4 Questions and the Neuropathic Pain Symptom Inventory  20, 21  ).
Statistical analyses We present descriptive data of all PROMs as medians and interquartile range (IQR), graphically displayed in violin plots. PROMs related to pain intensity were further analysed using NRS 4 as a threshold based on Gerbershagen and colleagues. 26  To confirm the sensitivity-to-change/responsiveness of each PROM, we aimed to perform a criterion approach which is in accordance with the COSMIN recommendations. 11  PGIC and PSIC on d3 (primary outcome) and d7 (secondary outcome) assessing a patient's view on global and several specific changes related to the situation on d1 were used as anchors. 27  As none of the analyses presented here are null hypothesis testing, we refrain from reporting P-values.
Patient characteristics A total of 3322 participants completed the study (Fig. 1 ). Patients who did not fill in questionnaires on d1, d3, or both, and any incomplete datasets, were excluded, leaving 2661 patients in this analysis. Of these, 972 (37%) underwent sternotomy, 695 (26%) surgery related to endometriosis (laparoscopy, complex surgery, hysterectomy), 510 (19%) total knee arthroplasty, and 484 (18%) breast surgery (conservation or mastectomy). The mean age of all patients was 54 yr (range: 18e91 yr). Overall, 65% of patients were females, which was biased by breast cancer and endometriosis-related surgery where only female patients were included. Overall, 44% of patients reported persistent pain before surgery (knee arthroplasty 91%, breast surgery 15%, endometriosis surgery 68%, sternotomy 16%) and 6% opioid use (knee arthroplasty 15%, breast surgery 1%, endometriosis surgery 8%, sternotomy 2%).
Discussion Here, we present the primary results of the prospective international multicentre PROMPT NIT-1 study, including data from 18 sites across 10 European countries. Our overall response rate was good, with 80% of patients fully completing all three questionnaires. In 2661 patients who underwent one of four different surgical procedures, pain-related outcomes generally improved from d1 to d3 and further to d7 after surgery. This held true for measures of pain intensity, physical function, and adverse events, whereas levels of self-efficacy remain partly unchanged. The improvement is reflected in the PGIC at d3 and d7, and in the PSICs for pain intensity, adverse events, and physical function. Consequently, PGIC (and PSIC as secondary outcome) were shown to reflect calculated changes between days relevant for the PROMs, consistently between surgeries.
Acknowledgements We would like to thank all the clinical investigators in the additional centres who participated in PROMPT NIT-1:  Benno Rehberg  ( Division of Anaesthesiology, Department of Anaesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland );  Viktoria Frebault ,  Charles Fiquet  and  Philippe Neyret  ( Orthopedy Unit, Infirmerie Protestante de Lyon, France );  Caterina Aurilio ,  Maria Caterina Pace , and  Pasquale Sansone  ( Department of Women, Child and General and Specialized Surgery, University of Campania Luigi Vanvitelli, Naples, Italy );  Dragana Unic-Stojanovic  ( Institute for Cardiovascular Diseases Dedinje, Medical faculty University of Belgrade, Belgrade, Serbia );  Germano Cardoso ,  Patricia Redondo ,  Sofia Dias ,  Sofia Travisco ,  Maria Amelia Gomes ,  Rita Canotilho ,  C atia Ribeiro , and  Ana Margarida Correia  ( Surgery ,  Instituto Português de Oncologia Porto, Portugal );  Julien Cabaton  ( Anesth esie e R eanimation en Orthop edie ,  Centre Paul Santy e Hôpital Priv e Jean Mermoz, Lyon, France );  Maria A.
In addition, she receives scientific support from the  German Research Foundation (DFG) , the  Federal Ministry of Education and Research (BMBF) , the  Federal Joint Committee  (G-BA), and 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. All money went to the institutions ( WWU/UKM)  EMPZ is working for. All the other authors have no conflicts of interest to declare.
Acknowledgments 21 This work was supported by the  Oswaldo Cruz Foundation intramural  funding, as well as  CNPq , and  FAPERJ (Brazil). The work was also partially funded by a grant from  MercoSur  through the  Fund for Structural Convergence (FOCEM). It was developed in the framework of the  National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM ;  CNPq) ,  Rio de Janeiro Research Network  on Neuroinflammation (Faperj),  INOVA-IOC Network on Neuroimmunomodulation (IOC/Fiocruz)  and  Experimental Pathology Laboratory of Fluminense Federal University.
a b s t r a c t The occurrence of coronary artery embolism (CE) has been associated with various clinical conditions, including aortic and mitral prosthetic heart valve implantation, atrial fibrillation (AF), dilated cardiomyopathy, neoplasia, infective endocarditis, atrial septal defect, cardiac tumors, and hypercoagulable states. CE is also a rare cause of myocardial infarction (MI), with a prevalence of about 5%, a figure probably underestimated. The purpose of this article was to determine the current state of knowledge on acute coronary syndrome (ACS) related to CE. We thus performed a comprehensive structured literature search of the MEDLINE database for articles published between 1 January 1990 and 31 December 2021. The diagnosis of CE remains difficult despite the currently used Shibata classification, which is based on major criteria, including angiographic characteristics: globular filling defects, saddle thrombi or multiple filling defects and absence of atherosclerosis in the coronary arteries.
Methods We performed a comprehensive structured literature search using the MEDLINE database (PubMed; National Library of Medicine, NIH, Bethesda, MD, USA). We analyzed publications dated 1 January 1990 through 31 December 2021 with the following search terms, individually and in combination: coronary artery embolism, thromboembolism, myocardial infarction, acute coronary syndrome, follow-up, prognosis, endocarditis, atrial fibrillation, extracardiac embolism.
Acknowledgments YC reports having received grants, consulting fees, honoraria and/or delivering lectures for Servier,  Novartis ,  Boehringer ,  Pfizer , and  BMS. MZ received research grants from  Amarin Corp. LF reports having received grants, consulting fees, honoraria and/or delivering lectures for  Novartis, Boehringer ,  Pfizer ,  BMS  and  Medtronic. ND reports having received grants, consulting fees, honoraria from and/or delivering lectures for  Amgen, AstraZeneca ,  Bayer ,  BMS ,  Boehringer Ingelheim ,  MSD ,  Novo-Nordisk ,  Sanofi ,  Servier ,  UCB, Vifor.
, 2009). The MS2 RNA aptamer was fused to the 5' end of the vigR 3' UTR and placed under the control of the Pxyl/tet promoter of pRAB11  (Helle et al. , 2011). Inducible transcription of MS2-vigR 3' UTR was confirmed by Northern blot, and we find that 15 min of induction with anhydrotetracycline (ATc) leads to strong accumulation of the MS2 fusion (Supplementary Figure  3 ). The MS2 fusion was induced in S. aureus strain JKD6008 grown in BHI media to an OD600nm 3. 0. (mid-log growth phase). Cells were pelleted and lysed before loading onto an amylose column loaded with MS2 protein-His-MBP fusion to pull-down the MS2 aptamer. After washing, bound RNAs were eluted with maltose and precipitated for library preparation and sequencing  (Lalaouna et al. , 2015; Mercier et al. , 2021). Peaks were called within the sequencing datasets using blockbuster  (Langenberger et al.
From these 58 genomes, 14 representative strains were selected that demonstrated vigR transcript variation. The GenBank and blastn. out files from these 14 representative strains were used as input into Easyfig  (Sullivan et al. , 2011)  to generate Figure  1A. Northern blot. Total RNA was purified using the GTC-phenol:chloroform extraction method as performed previously for S. aureus  (Mediati et al. , 2022). At least 5 µg of RNA was treated with a 5:1 ratio of glyoxal denaturation mixture for 1 h at 55°C. Denatured RNA was resolved on a 1% BPTE-agarose gel containing SYBR Green (Thermo) and run for ~1 h at 100 V in 1x BPTE buffer. Intact 23S and 16S ribosomal RNA was confirmed on a Bio-Rad Chemi-doc and washed consecutively in 200 mL of 75 mM NaOH, 200 mL of neutralizing solution (1. 5 M NaCl and 500 mM Tris-HCI, pH 7.
ACKNOWLEDGEMENTS The pICS3 vector was a generous gift from  Brice Felden  ( Université de Rennes ). The authors thank  Ian Monk  for insightful discussions of S. aureus phylogenetics. DGM and JJT are supported by grants from the  National Health and Medical Research Council (NHMRC ,  GNT1139313 ) and the  Australian Research Council  (ARC,  DP220101938 ). This project received funding from the  European Union 's  H2020 research and innovation programme  under Grant Agreement No. 753137. This work of the  Interdisciplinary Thematic Institute IMCBio , as part of the  ITI 2021-2028 program  of the  University of Strasbourg ,  CNRS  and  Inserm , was supported by  IdEx Unistra  ( ANR-10-IDEX-0002 ), and by  SFRI-STRAT ' US  project ( ANR 20-SFRI-0012 ) and  EUR IMCBio  ( ANR-17-EURE-0023 ) under the framework of the  French Investments for the Future Program.
d. 75 μm, C18, Acclaim PepMap TM RSLC, 2 μm, 100Å, Thermo Scientific) regulated to a temperature of 50°C with a linear gradient from 2% to 25% buffer B (100% MeCN in 0. 1% formic acid) at a flow rate of 300 nL/min over 91 min. MS1 data were collected in the Orbitrap (120,000 resolution; maximum injection time 60 ms; AGC 4 x 10 5 ). Charges states between 2 and 7 were required for MS2 analysis, and a 60 s dynamic exclusion window was used. MS2 scan were performed in the ion trap in rapid mode with HCD fragmentation (isolation window 1. 2 Da; NCE 30%; maximum injection time 60 ms; AGC 104) For identification, the data were searched against the Homo Sapiens (UP000005640_9606) and the Plasmodium Falciparum 3D7 (UP000001450_36329) UniProt databases using Sequest HT through proteome discoverer (version 2.
4). Enzyme specificity was set to trypsin and a maximum of two miss cleavages sites were allowed. Oxidized methionine, Met-loss, Met-loss-Acetyl and N-terminal acetylation were set as variable modifications. Carbamidomethylation of cysteins were set as fixed modification. Maximum allowed mass deviation was set to 10 ppm for monoisotopic precursor ions and 0. 6 Da for MS/MS peaks. The resulting files were further processed using myProMS v3. 9. 3 (https://github. com/bioinfo-pf-curie/myproms)  (Poullet et al, 2007)  FDR calculation used Percolator  (The et al, 2016)  and was set to 1% at the peptide level for the whole study. The label free quantification was performed by peptide Extracted Ion Chromatograms (XICs), reextracted across all conditions and computed with MassChroQ version 2. 2. 21  (Valot et al, 2011)  For protein quantification, XICs from proteotypic peptides shared between compared conditions (TopN matching) and missed cleavages were allowed.
Acknowledgments We thank  L. Mancio Silva ,  E. Real  and  J. Bryant  for critical reading this manuscript. This work was supported by the  Laboratoire d'Excellence (LabEx) ParaFrap  [ ANR-11-LABX-0024 ],  ERC   AdG PlasmoSilencing  ( 670301 ),  ANR-JC  ( 18-CE15-0009-01 ). We thank  Miguel Santos ,  Camille Cohen  and  Marta Miera Maluenda  for technical assistance with this project. With financial support from  "la Région Île-de-France " ( N°EX061034 ) and  ITMO Cancer of Aviesan and INCa  on funds administered by  Inserm  ( N°21CQ016-00 ) for MS analysis.
Participants and ethical statement Thirty-three right-handed individuals (9 males, 24 females; mean (SD) age 24. 5 (3. 4) years, range  with no history of neurological, physical, or psychiatric illness were included in this study. Two other individuals were initially recruited, but their data could not be analysed owing to the poor quality of the fNIRS signal. The Edinburgh Handedness Inventory  [21]  was used to evaluate handedness. All participants had an Edinburgh laterality ratio ≥ 80. Full written consent was obtained from all participants in accordance with the Declaration of Helsinki. This study was approved by the Institutional Review Board CPP NORD-OUEST I on 21st January 2021 (no. 2020-A02936-33) and was registered on clinical trials. gov (NCT04738851). The study is reported according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
The current neuropsychiatric nosological categories underlie pragmatic treatment choice, regulation and clinical research but does not encompass biological rationale. However, subgroups of patients suffering from schizophrenia or Alzheimer's disease have more in common than the neuropsychiatric nature of their condition, such as the expression of social dysfunction. The PRISM project presents here initial quantitative biological insights allowing the first steps toward a novel trans-diagnostic classification of psychiatric and neurological symptomatology intended to reinvigorate drug discovery in this area. In this study, we applied spectral clustering on digital behavioural endpoints derived from passive smartphone monitoring data in a subgroup of Schizophrenia and Alzheimer's disease patients, as well as age matched healthy controls, as part of the PRISM clinical study.
Eligible participants attended their study centre on three assessment days. Assessment day 1 included further screening, collection of questionnaire measures, behavioural testing, a blood draw and optional installation of a smartphone application for the remote collection of sociability and social exploration data (Behapp service  ( Jagesar et al. , 2021 ) ; www. Behapp. com ). Assessment days 2 and 3 each included an MRI and EEG neuroimaging session, during which various structural and functional scans were acquired. Follow-up activities consisted of continued Behapp app data collection and remote completion of a short set of social withdrawal questionnaires near the end of the follow-up period ( + 42 days from assessment day 1). A flow diagram of the clinical study protocol is provided in Fig.
Data collection The final sample for the PRISM clinical study consisted of 165 participants: 52 Alzheimer's Disease patients, 56 schizophrenia patients, 29 younger and 28 elderly healthy controls. In this study,   data from 59 participants was used. This number was lower than the actual number of participants in the study due to various reasons (e. g. , Behapp participation in the clinical study was optional; at the time of the study, Behapp was only available for Android phones; for that reason, participants with an iPhone did not participate in this part of the study). The demographic characteristics of the sample for the present study in terms of gender, ethnicity, age and years in education can be visualised in Table  1. Participants who consented to the remote collection of sociability data via Behapp were given the option of installing the app on their personal Android smartphone.
Participants were encouraged to allow follow-up data collection for 28 days (4 weeks) from assessment day 1, to allow for the collection sufficient data for meaningful analysis, but they were free to choose to discontinue Behapp data collection at any time whilst continuing with other aspects of the study. Whilst installed, the Behapp app passively monitored smartphone activities, including frequency, duration and diversity of events, such as incoming and outgoing phone calls (with number encryption), SMS usage, and social media activities (e. g. , WhatsApp and Facebook events), to provide an objective measure of sociability and social exploration in a longitudinal daily-life manner. No content (e. g. , from calls or messages) was collected. In the case of each participant, each one of these longitudinal endpoints was condensed into a cumulative measure, representing the total count of observed events throughout the follow-up period.
To accommodate variations in the duration of follow-up among partic-ipants, these consolidated measures were subsequently normalized by dividing them by the individualized follow-up durations of each participant. The PRISM clinical study involved 4 MRI data collection sites (3 using Philips Ingenia 3T-scanners and one using a Siemens Prisma 3Tscanner) in two countries (The Netherlands and Spain). The basic BOLD parameters were standardized between the different scanners and advanced shims were performed at all sites. Behavioural task data was collected using the P1vital® ePRO system. Tasks were completed online via a personalized account which researchers created for participants. The ePRO system is built to high, industryregulation standards, and site staff was provided with training and materials to ensure standardized data collection procedures across sites  ( Bilderbeck et al.
Participant inclusion in current analysis Within the full PRISM dataset we had access to Behapp endpoint data for 75 participants for whom we had derived endpoints available. We removed participants who had more than 10 missing endpoints and removed endpoints where more than 5 participants missed data. This resulted in inclusion of 59 participants (19 AD, 14 SZ, and 26 HC) and 62 endpoints. Remaining missing endpoints were replaced with the mean value for that endpoint in the avail-able participants. Finally, each endpoint score was converted to a z-score by subtracting its mean and dividing by its standard deviation across the population.
Note that this number is typically validated using (out-of-sample) cross-validation, however, in light of the current data exploration we have not implemented such cross-validation. To inform ourselves about the potential number of clusters present in our dataset we assessed the silhouette metric and a principal component decomposition of the similarity matrix. Based on the silhouette metric a solution with 2 or 3 clusters would yield the best possible separation. This was further confirmed by a PCA decomposition on the similarity matrix in order to estimate the underlying intrinsic dimensionality of the data. That the first 4 principal components cumulatively explained 80 % of the variance in the data. In terms of the percent of explained variance per component we observed a first inflection point ('elbow') at component number 3.
Relationship with imaging derived endpoints To assess the relationship between the cluster solution and endpoints derived from the imaging modalities present in PRISM, we implemented group-analyses using cluster-membership as groupidentifiers (instead of diagnostic label). Given the exploratory nature of these analyses and the limited number of participants we assessed effects at a significance level of p < 0. 05 without further correction for multiple comparisons. Group-level 1-factor ANOVA models were applied to endpoint data residualized for the effects of AGE, SEX, and SITE. The factor group comprised three levels corresponding to each participant's cluster membership. Table  2  lists the unimodal endpoints that were assessed and the modality they were derived from. Here, we assessed the effect of cluster membership on multi-modal components derived through linked-ICA  ( Groves et al.
Taken together the merit and practicality of a true trans-diagnostic, biology-driven classification system for use across psychiatry and neurology is emerging. In the present study the data collected from the deployment of the Behapp, a passive smartphone App, has been concentrated on  ( Jagesar et al. , 2021 ). The data collected within the unique framework of the PRISM project provides a compelling, first empirical demonstration of the unbiased identification of potentially novel, meaningful, biological phenotypes. With three clear groupings in the profile of the subjects; Healthy Controls, Alzheimer and Schizophrenic patients, along with major potential contributory factors; such as age and sex, a realistic null hypothesis would be that one or a small collection of these factors would be the most convincing driver for first order clustering.