dataesr/scientific-paragraphs-categorization huggingface dataset:
The identified proteins belong to abundant glycoproteins in blood plasma, spanning three orders of magnitude in abundance (Fig. 2a ). Previous clinical glycosylation studies are commonly based on a glycomics workflow in which glycans are released from circulating blood glycoproteins whereas here we analyse intact glycopeptides. To investigate the correlation between the two approaches, we compared our glycoproteomics results for healthy individuals as inferred glycomes with available glycomics data  [4]  in Fig. 2c. The distributions of glycan intensities, expressed as relative glycan fractions, are nearly identical between our glycoproteomics data and reference glycomics dataset (R 2 = 0. 99) indicating that our workflow has no particular bias towards specific glycoforms and that we can expand current glycomics-based knowledge using our more in-depth glycoproteomics approach.
Glycopeptide biomarker discovery in clinical samples The diversity in glycosylation sites and glycoforms captured by a single glycoproteomics experiment has the potential to identify high-specificity signatures for a variety of human diseases. Indeed, multiple individual glycoproteins in this dataset have already been described as biomarkers for diseases such as cancer, immune disease, cirrhosis and rheumatoid arthritis  [39]. Thus, we evaluated the potential of our holistic glycoproteomics workflow for biomarker discovery on a cohort of rare human genetic diseases. We included genetic defects in a broad range of underlying biological pathways such as glycosyltransferases, sugar metabolism and Golgi homeostasis, of which at least 3 patient samples were available for analysis (10 disease groups).
Samples were characterised by intact transferrin glycoprofiling using a clinically validated test by high-resolution mass spectrometry (TRFE IP-MS)  [28]. Available data was used to assess the clinical validity of glycopeptide profiling data by comparison with transferrin glycopeptide results at glycome level, showing strong correlation for individual samples (PPC r = 0. 97; supplementary data). To identify glycopeptide differentials as possible biomarkers, exploratory chemometrics was performed by PCA using glycopeptide feature data from the 10 CDG groups and controls (n = 40). Both glycoproteomics and TRFE IP-MS data showed clear separation between healthy individuals and each of the CDG defects by their first principal component in PCA score plots (Fig. 4a  and supplementary Fig. 3 ). Glycopeptide profiling data achieved complete separation between four disease groups (COG5, DYM, NANS and PGM1) whereas the 95% confidence intervals overlapped for TRFE IP-MS data.
Acknowledgements This research was part of the  Netherlands X-omics Initiative  and partially funded by  NWO  (project  184. 034. 019 ), supported by  ZonMw Medium Investment   Grant  ( 40-00506-98-9001 ) and  EUROGLYCAN-omics  ( ERARE18-117 ), under the frame of  E-Rare-3 , the  ERA-Net for Research on Rare Diseases. The authors are grateful to  dr. Doroteya Staykova  for the review of our work as expert statistician.
19, 20 The work in MM was pioneered <10 years ago by Palumbo et al, who published the first so-called IMWG Frailty Score. 5 This work was seminal and drew the attention of the community on the frailty concept. 2] [23] [24] [25] [26]  An electronic frailty index based on data from administrative claims and electronic health records was also recently published (US Veterans Affairs Frailty Index). 27 These scores, which have classified 20% to 50% of patients as frail, have prognostic value and have consistently demonstrated increased rates of adverse events, treatment discontinuation, and worse PFS and OS in frail versus fit (or less frail) patients. Apart from scores, different approaches exist to measure muscle function and physical performance status, and experts have recently recommended the use of a grip strength, 4-meter gait speed, or the Short Physical Performance Battery test to measure physical performance in daily practice.
The IFM group presented data for 773 patients initiating a nontransplant first line of therapy between 2017 and 2019 (EMMY cohort), of whom 162 received Rd (21%; median age of 79 years) and 158 received VRd (20%; median age of 69 years). 61 For patients who received Rd, the median time to next treatment by age (<75 or ≥75 years) was identical at approximately 29 months. In contrast, for patients who received VRd, the median time to next treatment was almost 35 months in patients aged <75 years but only 17 months in patients aged ≥75 years. In the PEGASUS study,  62  an anchored indirect treatment comparison, leveraging data from individual patients, was made between patients given DRd in the MAIA study and patients treated with VRd from the Flatiron Health electronic health record-derived database.
In a recent elderly subgroup analysis of the KarMMa study (NCT03361748), treatment outcomes for idecabtagene vicleucel (ide-cel, bb2121) were similar in patients aged ≥70 years (n=20; 4 patients aged >75 years) and those who were younger (aged ≥65 years, n=45). However, none of the patients in the older age group were frail or >80 years of age, and all had an ECOG performance status of 0 or 1. 65  Few data in frail patients exist with carfilzomib. 66.
The study will hopefully serve as a prototype for new trials in frail patients. Two other studies will have results in the next few years: the IFM 2017-03 trial (NCT03993912),  68  a dexamethasone sparing study for frail patients, and the UK-MRA FiTNEss (Myeloma XIV)  69  trial. It remains that there is currently no proven frailty-adjusted treatment approach. Both daratumumab studies have presented a frailty subanalysis (simplified frailty score with age, CCI, and ECOG; Table  3 ). 70, 71 In the ALCYONE study, 44. 6% of patients were frail. After a median follow-up of 40. 1 months, the frail patients in the D-VMP group had a shorter median PFS than the nonfrail patients (32. 9 and 45. 7 months, respectively). 70 Similar median PFS was observed for frail and nonfrail patients treated with VMP (19.
Design of primers and TaqMan probes The primers and probes were designed using Primer3Plus and the genomic sequences available on Genbank (in 2021, when the primers were designed) for the three genera of the Microviridae family. Using BLAST alignment for nucleotides, the identity ranged from 98. 9 % to 99. 9 % (coverage: 100 %) between ϕX174 sequence with accession number NC_001422. 1 and the 114 other complete sequences of Sinsheimervirus. The identity ranged from 84. 0 % to 100 % (coverage: 84 % to 100 %) between α3 sequence with accession number NC_001330. 1 and the 14 other Alphatrevirus sequences. It ranged from 91. 3 % to 100 % (coverage: 99 % to 100 %) between G4 sequence with accession number NC_001420. 2 and the 19 other Gequatrovirus sequences. The previously described PCR system for ϕX174 detection  (Dika et al.
, 2015)  matched with only 63 % of the 115 sequences of Sinsheimervirus, but this result could be improved to 86 % by degenerating one nucleotide on the reverse primer at position 1727 on NC_001422. 1. The system with the degenerated reverse primer was used for ϕX174-like phage detection and quantification. The primers and probes were located in the replicase gene for α3-like phages and in the hypothetical Protein A for G4-like phages because of the relatively small amount of sequence variation encountered in those areas. BLAST alignments showed that these two PCR systems detected all the complete sequences of their genus disponible on Genbank. The specificity for each genus could also be estimated at 100 % for the three PCR assays. An additional validation was done by testing DNA from α3, G4-like, and ϕX174 with each PCR detection assay.
Real-time PCR The real-time PCR technique was used to genotype the PFU recovered from the plates for each Microviridae genus. For influents samples, a total of 1001 PFU were genotyped. The number of genotyped PFU per WWTP varied between 218 (WWTP-1) and 283 (WWTP-3). For effluent samples, a total of 664 PFU were genotyped. The number of genotyped PFU per WWTP varied between 110 (WWTP-4) and 269 (WWTP-2). The detailed data are given in Supplementary Table  S1. The reactions were performed using the TaqMan Universal PCR Master Mix (ThermoFisher Scientific). In accordance with the manufacturer's recommendations, each reaction was performed in a 25 μL reaction mixture containing 5 μL of template DNA and 15 µL of 1 × TaqMan mix, 800 nM of each primer and 200 nM of the probe, and molecular grade water (Sigma).
5. 0. The sequence is available on GenBank with accession number OR492646. BLAST analysis showed between 92. 1 % and 96. 7 % identity (coverage: 100 %) with the 20 other complete sequences of G4-like phages, 77 % identity (coverage: 33 %) with the NC_001422. 1 sequences (Escherichia phage phiX174, complete genome) and between 71. 1 % and 75. 8 % identity (coverage: 24 % to 32 %) with the 15 complete sequences of α3-like phages.
Statistical analysis All the statistical tests were performed using GraphPad-PRISM software (version 9. 5. 0). The α level was fixed at 0. 05. All data were analysed for single outliers using the Grubbs test. After removing the detected single outliers, the normality of the data sets was assessed using the Shapiro-Wilk test. All data were independent of each other. So, we used the Kruskal-Wallis test followed by a post-hoc Dunn multiple pairwise comparison test to compare more than two samples. A Mann-Whitney test was used to compare two samples. Asterisks were used to indicate significant differences: * for p-value ≤ 0. 05; ** for p-value ≤ 0. 01; *** for p-value ≤ 0. 001, and **** for p-value ≤ 0. 0001.
Discussion This study aimed to increase knowledge about SC belonging to the Microviridae family in WW, and to better understand the effect of WW treatments on their inactivation and removal. PCR assays were developed here for the quantification of the three genera of Microviridae, which is the only remaining recognized family in the SC  (Turner et al. , 2021). The design of these PCR assays was done by using the complete sequences available on Genbank which are more numerous for ϕX-174-like genus than the other genera. Three PCR assays were necessary since this family is too genetically diverse to create a single PCR assay that can target all its members. A previous study proposed a PCR assay that only targeted the ϕX-174-like genus  (Lee, 2009)  and did not detect all Microviridae or compare the three genera of Microviridae between each other.
Acknowledgments This work was performed within the scope of Norostan, a project funded by the  French Ministry of Agriculture and Food "CASDAR Recherche Technologique " (n •  19ART374748 ). This study was also supported by the  Actia VIROcontrol Joint Technological Unit. The authors want to thank the  "Syndicat Intercommunal du Bassin d'Arcachon"  for kindly supplying raw and treated WW samples from WWTP. Additional support was obtained from  Zone Atelier Moselle (ZAM).
Heterogeneity in the generation model between the training and the target samples would lead to misclassification. Such models have been developed to predict modes either at the trip level (4) or for small windows of, for example, 1 minute (where a posteriori smoothing is then needed to mitigate incoherent switching between different modes)  (29). Unsupervised methods do not need a database of trips with preclassified modes. Rather, considering that the different motorized and nonmotorized modes each have their own distribution of speeds, they attempt to classify the trips into modal categories on the basis of the distribution of speeds in each trip segment, removing the need for manual labeling  (10, 53). Most transport mode recognition algorithms rely only on GPS data, whereas some have combined GPS and accelerometer data (4).
This approach is also referred to as prompted recall surveys because the preanalyzed GPS tracks are used to stimulate participants' recall. In the RECORD GPS/MultiSensor Studies and MobiliSense project, I use one of the most advanced applications to date: (a) It segments GPS tracks into visited places, trips, and unimodal trip stages; (b) it recognizes the places visited from previously reported participants' regular destinations and general points of interest; (c) it imputes travel modes from GPS speeds, self-reported use of transit, and geographic data on transit stops; (d ) it allows investigators to import transit trip itineraries and times from the General Transit Feed Specification data; and (e) it includes a number of tools for manually editing the GPS tracks (retrieving short stops, segmenting tracks to create a stop, manual drawing, imputation of street-network itineraries).
Analytical Biases in Sensor-Based Short-Term Effect Studies Because of the burden of sensor-based protocols, participants can drop out from the study or have missing portions of repeated observations. If study dropout or missing data are determined by the exposure or by a determinant of the exposure and by the outcome or a determinant of the outcome, then selection biases can distort the association of interest. Such biases can alter associations estimated from between-individual but also within-individual comparisons (including when estimated with case-crossover analysis). Regarding confounding, associations based on within-individual comparisons are threatened by time-varying confounders, for example momentary physical activity when assessing the relationship between ambient noise or stressful social interactions and blood pressure (behavioral confounder) or as another example the type of activity or accompanying persons when investigating the relationship between place characteristics and well-being (situational confounders).
ACKNOWLEDGMENTS This article has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement  647000 , 2014  ERC   Consolidator grant ,  MobiliSense  project); from the  European Union   Horizon 2020 Programme  [grant agreement  667661 ,  Promoting Mental Wellbeing  in the Ageing Population (MINDMAP)]; and from  ANR (French National Research Agency , grant agreement  ANR-15-CE36-0005-02 ,  HANC  project).
a  Joy Ventures Research Grant  and funding from  Tiny Blue Dot Foundation. Manos Tsakiris  was supported by the  European Research Council   Consolidator Grant  ( ERC-2016-CoG-724537 ) for the  INtheSELF  project under the FP7. Micah Allen  is supported by a  Lundbeckfonden Fellowship  ( R272-2017-4345 ) and by the  European Research Council   Starting Grant  ( ERC-2020-StG-948788 ). Guillaume Dumas  is supported by the  Fonds de recherche du Québec  (FRQ;  285289 ),  Natural Sciences and Engineering Research Council of Canada (NSERC ;  DGECR-2023-00089 ), and the  Azrieli Global Scholars Fellowship  from the  Canadian Institute for Advanced Research (CIFAR)  in the  Brain, Mind, & Consciousness program. Karl Friston  is supported by funding for the  Wellcome Centre for Human Neuroimaging  (Ref:  205103/Z/16/Z ), a  Canada-UK   Artificial Intelligence Initiative  (Ref:  ES/T01279X/1 ) and the  European Union 's  Horizon 2020 Framework Programme for Research and Innovation  under the  Specific Grant  Agreement No.
It is designed to facilitate scalability and translation into policy by leveraging existing resources, while strengthening local capacities in research, health, and community institutions. Findings will constitute an evidence base for potential policy changes in malaria prevention in pregnancy, allowing local national malaria control programmes to reach their goals. lock and key and will be accessible only to authorized persons including the project coordinator, principal investigators and data managers. Information stored in electronic databases will be protected by unique usernames and passwords, accessible only to appropriate authorized personnel. Study results will be disseminated through conference presentations, and publications in relevant peer-reviewed journals.
The objective of our study was to assess the differences in seasonal patterns of I. ricinus nymphal abundance associated with distinct climates observed in France. A seven-year longitudinal study, involving monthly I. ricinus collections, was carried out at six locations in France. The species I. ricinus was targeted because it is responsible for major human vector-borne diseases in Europe (Lyme borreliosis and Tick Borne Encephalitis). This dataset allowed the fitting of statistical models of nymph abundance with time. Wrongnak et al. (2022a)  fitted a model on the same data set to explore the influence of meteorological variables on tick abundance for predictive purposes. Our modelling approach is complementary and aims to describe the seasonal patterns of I. ricinus by site and to relate them to temperature features of the different geographical locations.
A transcriptomic study revealed that prf transcription levels increased during the innate CMC response, as well as during intravitreal NNV infection, pointing to a possible activation of the CMC to clear NNV-infected cells in European sea bass  [24, 25]. Therefore, it is necessary to further study perforins in fish, particularly in European sea bass, to clarify their participation in the immune response, but especially in the CMC activity for viral removal. The main objective of this study was to identify prf genes and characterize their regulation in European sea bass, due to its relevance in the Mediterranean aquaculture sector. The sequences, obtained from genome databases, were analysed bioinformatically and the transcription levels studied in naïve organs, in vitro stimulated head-kidney cells, CMC and in vivo NNV-infected fish.
Bioinformatic analysis European sea bass perforin (prf) sequence (KY801204), now renamed to prf1. 9, was already known and used in previous studies  [24, 25]. Novel mRNA and putative protein sequences of sea bass prf were obtained from genome databases (Ensembl and http://seabass. mpipz. mpg. de/). Predicted protein sequences were used to retrieve fish and tetrapod orthologues from the NCBI databases by the basic local alignment tool (BLAST). The evolutionary history was inferred using the Neighbour-Joining method by Mega software v11. 0 with the bootstrap value set to 1,000 replications  [26]. Proteins belonging to the MACP Family, such as the complement proteins C6-C9 and macrophage-expressed gene 1 protein (MPEG1), were also included. Predicted proteins were used for multiple sequence alignments using the CLUSTALW program v2.
Stability of the housekeeping genes was routinely confirmed by the BestKeeper® software. The primers used were designed specifically using the Oligo Perfect software tool (Thermo Fisher Scientific) and are shown in Supplementary Table  1. Prior the experiment, the specificity of each primer pair was studied using positive and negative samples. A melting curve analysis of the amplified products validated the primer for specificity at each use. Negative controls with no template were always included in the reactions.
Statistical analysis All data are presented as mean ± standard error of the mean (SEM). Perforin transcription was presented as relative expression in naïve tissues or as fold change respect to the respective controls in the HK cells, CMC and NNV-infection assays. Results were analysed by a Student-t test to denote statistical differences between treated/infected and control groups. Normality was evaluated by the Shapiro-Wilk test. Nonparametric Pearson correlation test was applied to identify potential relations among gene expression. Statistical analyses were conducted using SPSS 20 software. Minimum level of significance was fixed in 0. 05.
Discussion CMC plays a crucial role in eradicating tumours and virus-infected cells in animals. This mechanism involves various effector cells, including T lymphocytes and NK cells, as well as a cytotoxic pathway mediated by the killing effector proteins, namely perforins and granzymes. Despite the comprehensive understanding of the CMC in mammals  [32]  our knowledge in fish is still limited. In an endeavour to shed light on this subject, we searched prf genes in the teleost European sea bass genome databases to evaluate their presence and functional characteristics. First, we performed an in silico search of the prf gene sequences in the  European sea bass genome, obtaining four genes, named as prf1. 2, prf1. 3, prf1. 5 and prf1. 9 with similar sizes in the predicted mature proteins compared to other fish  [13]  and human orthologues.
Acknowledgements This work was funded by  Ministerio de Ciencia e Innovación-Agencia Estatal de Investigación  ( MCIN/AEI/10. 13039/501100011033 , grant  PID2019-105522 GB-I00  to A. C. and  FPI  contract  PRE2020-093771  to L. C. ) and by the  ThinkInAzul programme  cofounded by the  European Union NextGenerationEU/PRTR ,  MICIN/AEI 10. 13039/501100011033  and  Fundación Séneca. Ministerio de Ciencia e Innovación  is also acknowleged by the  Juan de la Cierva Incorporación  contract to YV ( IJC2020-042733-I ).
Here, we establish a framework for testing scenarios of ancient origination and codiversification versus recent origination and diversification by host switches that combines probabilistic cophylogenetic models and biogeographic analyses (Fig  1 ). We then apply this framework to the Coronaviridae-mammals association. We assemble a dataset of all mammalian hosts of coronaviruses and a complete association matrix between host species and species-like Operational Taxonomic Units (sOTUs) of coronaviruses, as well as geographic repartition of Coronaviridae and their mammalian hosts. We construct a new Coronaviridae tree based on a recent proposition for the use of a well-conserved region of their RNA genome  (36, 37). Under the ancient origination scenario (Fig 1A ), long-term vertical transmission of Coronaviridae within mammalian lineages could lead to events of mammal-coronavirus cospeciations.
Results By screening the 46 sOTUs of Coronaviridae identified by Edgar et al. (36)  in public databases, we found 35 that were associated with mammalian hosts. Our trees of these 35 sOTUs support a well-defined split between Alphacoronaviruses and the other genera, regardless of the phylogenetic method used (Fig 2 ; SI Appendix, Fig. S1 ). Overall, Alphacoronaviruses form a monophyletic clade, Delta-and Gammacoronoviruses form sister clades, with the main uncertainty being on the placement of their ancestor in relation to Beta (i. e. as a sister to a monophyletic Beta-clade (Fig. 2 ) or within the Beta-clade (SI Appendix, Fig. S1 ). We found that mammalian hosts of coronaviruses belong to 31 families and 10 orders of mammals, and are widely distributed throughout the mammalian phylogeny (SI Appendix, Fig.
S7 ). ALE reconciliations inferred average numbers of 145 cospeciations, 65 losses, 0 duplication, and 92 host switches. Without investigating the time-consistency of the host switches, we would conclude that there are almost 1. 5 more diversification events of Coronaviridae that are related to ancient codiversification rather than host switches. However, on average 20% of the inferred host switches are time-inconsistent, including "back-in-time" host switches of >50 Myr (SI Appendix, Fig. S8 ), which suggests instead that extent Coronaviridae originated recently and diversified by frequent preferential host switches. 64% of the reconciliations found an origination of coronaviruses within bats, in particular within the Pteropodidae family (Fig. 2A-C ). We no longer found an origination in bats when randomly shuffling the dataset (SI Appendix, Fig.