dataesr/scientific-paragraphs-categorization huggingface dataset:
CONCLUSIONS Based on insights from individuals with SMA and caregivers, maintaining functional ability based on a patient-friendly version of the MFM32 is a meaningful outcome to patients and their families. When considering improvement, single-point changes across multiple items is important. The quantitative data using the validated MFM32 assessment and using multiple anchors in a sample with a median age range of 5-8 years old across anchor groups, demonstrated that a ∼3-point improvement is meaningful in individuals with Type 2 and non-ambulant Type 3 SMA. Overall, the qualitative and quantitative findings from this study support the importance of examining a range of meaningful change thresholds on the MFM32 including ≥0 points change reflecting stabilization or improvement and ≥3 points change reflecting a higher threshold of improvement.
ETHICS STATEMENT Ethical approval and oversight of the qualitative interview study was provided by Copernicus Group Independent Review Board, a centralized IRB in the US (Approval Reference Number IRB 20192527). Written informed consent was obtained from participants aged ≥18 years old and written informed consent was provided by caregivers for individuals aged 12-17 years old prior to the interviews, as well as obtaining assent from adolescents. The online survey was conducted following market research principles and hence did not receive ethical approval but was consistent with British Healthcare Business Intelligence Association guidelines for Adverse Event Reporting in Market Research as well as General Data Protection Regulation guidelines and guidelines set by ESOMAR and EphrMRA for all European research.
FUNDING The qualitative interviews, online survey and the exploratory analyses conducted using SUNFISH Part 2 clinical trial data (NCT02908685) described in this manuscript were funded by F. Hoffmann-La Roche. Funding was provided by Roche Products Ltd. and F. Hoffmann-La Roche in the form of salaries for Roche employees, and consultancy fees paid to Adelphi Values (qualitative interviews) and Charles River Associates Inc. (survey).
ACKNOWLEDGMENTS The authors would like to thank additional contributors from  SMA Europe  ( Mencía de Lemus ,  Ria Broekgaarden ,  Inge Schwersenz , and  Vitaliy Matyushenko ) and  Cure SMA  ( Lisa Belter  and  Jill Jarecki)  for their contributions to the qualitative interviews and online survey,  Adelphi Values  for conducting the qualitative interview study ( Jessica Flynn ,  Alyson Young  and  Rob Arbuckle ),  Charles River Associates  for conducting the online survey ( Sonia Reif  and  Angela De Martini ), and  Roche  colleagues for valuable insights on the qualitative studies ( Fani Petridis  and  Johannes Reithinger ) and quantitative analyses ( Ying Yan ,  Yue Li , and  Tammy McIver ). The authors thank  Michelle Kim, Ph. D. of MediTech Media  for providing medical writing support, which was funded by  F.
Caco-2 cells were grown on Transwell semi-permeable filter support (12 mm-diameter wells, polystyrene membranes with 0. 4 μm pores, Costar, Corning) and seeded at 2. 9 × 10 4 cells per well with Trans-Epithelial Electrical Resistance (TEER) readings of > 1500 ohms cm -2 (8-10 days, HTS robot REMS autosampler, World precision instruments). TEER was measured before adding 1 × 10 6 CFU of each Bifidobacterium strain onto the apical surface and co-incubated for 3 h at 37 °C/10% CO 2 , prior to treatment of the basolateral medium with TNF-⍺ (100 ng/ mL) for an additional 21 h. Experiments were performed at least in duplicate. The strain Lactobacillus rhamnosus LGG was used as positive control  61, 62. The resulting data presented as a TEER ratio: PCR-detection of serpin gene. Bacterial DNA extractions were performed according to the procedures of the Instagene kit (BIORAD, France).
Statistical analysis. All results were expressed as means ± standard error of the mean (SEM). We performed a one-way ANOVA for normal samples and multiple comparisons were carried out using Tukey's test. For non-normal samples and/or with unequal variances, non-parametric tests were performed within groups (Kruskal-Wallis test) and multiple comparisons were carried out using Dunn's test using GraphPad Prism 7 software (GraphPad Software, San Diego, CA, USA). We employed an alpha level of 0. 05.
Acknowledgements We would like to thank  Claude Blondeau  for his help for the writing assistance, technical editing, language editing, and proofreading of the manuscript. We wish to thank the staff of the  INRAE Infectiology of Fishes and Rodents Facility (IERP-UE907, Jouy-en-Josas Research Center, France ) in which animal experiments have been performed. IERP Facility belongs to the  National Distributed Research Infrastructure for the Control of Animal and Zoonotic Emerging Infectious Diseases through In vivo Investigation.
NMR spectroscopy All NMR experiments have been recorded on a 600 MHz Bruker TM AVANCE III spectrometer equipped with a TCI cryoprobe at 298 K. The FrzS CheY backbone assignment was carried out by recording 3D HNCO, HN(CA)CO, HN(CO)CA, HNCA, CBCA(CO) NH and HNCACB experiments. The secondary structures were verified based on H N , N, C 0 , C a and C b backbone chemical shifts using TALOS+ webserver  (Shen et al, 2009). The data were processed using Topspin3. 6 (Bruker) and analysed with CCPNMR  (Vranken et al, 2005).
Acknowledgements We thank  Olivier Bornet  ( NMR platform of the Mediterranean Institute of Microbiology, FR 3479 Marseille ) for 3D NMR experiments acquisition and processing. This work was funded by the  Centre National de la Recherche Scientifique (CNRS) ,  Aix-Marseille University , the  European Research Council  to TM (JAWS-Advanced Grant  ERC-2019-ADG: 885145 ) and The  Agence Nationale de la Recherche  to RM and  LE (PILACT-AAPG-2022: 259552 ).
Sample size In total, a minimum of 60 households will be recruited. On the basis of national data and previous results, seven people on average are expected per household. 17 Among the 60 identified households, a total of 420 individuals are therefore expected to be followed up, leading to an estimate of 5040 collected samples. Based on our previous experiences, we estimated an ESBL growth of 30%. Thus, among the 5040 estimated samples to be collected, we expect to isolate a maximum of 1512 ESBLs. The human resources required, the number of households to be included at a monthly basis (four households per month) and the duration of the inclusion period (15 months) were determined so as not to overload both the teams working in the field and in the laboratory. The enrolment of ~420 subjects clustered within 60 households would allow detecting a minimum OR of 1.
pasteur. fr/en/tool/fq2dna). Briefly, after preprocessing the PE reads (ie, deduplication, trimming, clipping, putative contaminating human read removal, sequencing error correction, digital normalisation), fq2dna infers two de novo assemblies (ie, with and without PE read merging) using SPAdes and selects the less fragmented one. 23 Next, fq2dna filters out troublesome contigs (too short and/or significantly under covered by the PE reads). Finally, the assembled scaffolds are annotated using Prokka and classified as chromosome/plasmid using Platon. 24 25 In order to characterise the plasmid content of each sequenced and assembled isolate, the identified plasmid scaffolds will be next typed using PlasmidFinder and the last release of the associated Enterobacteriaceae replicon databank (https:// bitbucket.
org/genomicepidemiology/plasmidfinder_ db/src/master). 26 This plasmid sequence typing step will therefore allow studying the plasmid transmission. In complement, the determination of the acquired resistance gene content of each sequenced and assembled genome will be performed using ResFinder and the last release of the associated reference sequence database (https://bitbucket. org/genomicepidemiology/ resfinder_db/overview). 27  Thanks to the scaffold classification using Platon, each determined resistance gene will be assessed as carried on the chromosome or plasmid(s), therefore allowing.
The force of infection, which represents the risk of acquisition to which each susceptible newborn is exposed by unit of time, will be written as a sum of different components describing the different possible routes of colonisation. The model will be integrated in a statistical inference framework to analyse the data and estimate unknown model parameters (eg, transmission rates, impact of antibiotics). For each household, the model will be parameterised and initialised using the collected data at the individual level in each household, for example, individuals' status, antibiotic exposure, age, environmental swabs results. It will then be confronted to the collected data over time, and optimal parameters (ie, enabling the best reproduction of the longitudinal data) will be estimated. Due to the model complexity and the diversity of transmission routes assessed, a series of models of increasing complexity will be built to compare their likelihood given the data and acquisitions observed over time in the different households.
Ethics and dissemination Written informed consent will be obtained from all participants. In case the participant is minor (<18 years old), written informed consent will be asked to a parent or guardian of the participant. Assent will be asked to study participants aged 7-17 years. Data protection will follow both European Union and Malagasy data protection rules. Finally, all biological material (DNA) will be transferred in accordance with the international rules. The study was approved by the ethical committee in Madagascar (N° 190 MSANP/SG/AGMED/CERBM) and by the institutional review board (n° IRB2020-010) of Institut Pasteur, Paris, France. Findings will be reported to (1) participating families; (2) institutes and collaborators supporting the study; (3) local government to inform policy; (4) presented at local, national and international conferences; and (5) disseminated by peer-review publications.
The Release of TcsL in P. sordellii Is Facilitated by the PaLoc-Encoded Holin TcsE To determine the roles of the PaLoc-associated holin gene in LCGT secretion, we focused on the role of TcsE in the secretion of TcsL. Two independent P. sordellii strain ATCC 9714 tcsE mutants were constructed using the TargeTron insertional inactivation system. The mutations were confirmed using PCR (data not shown) and Southern hybridisation (Figure  S1 ) and were complemented in trans through the introduction of wild-type tcsE cloned in the clostridial vector pRPF185, under the control of a Tet inducible promoter. The wildtype, mutant, and complemented isogenic panel of strains were then tested for their ability to release TcsL. To do this, P. sordellii strains at the mid-exponential growth phase were diluted to a low optical density in TY broth (a media deficient in glucose, as the sugar is known to repress TcsL expression  [32] ) and grown for either 10 or 22 h.
g. , a decrease vs. an increase). However, the differences in these three proteins are unlikely to be due to the action of TcsE, as they are not reciprocal in their abundance between the WT vs. MT and the C vs. VC comparison. They are either increased in both the mutant and the complemented strain, or they are both reduced in abundance, suggesting that the presence of TcsE is not controlling any differences in abundance. As TcsL is the only protein that appeared in the cutoff in both comparisons (Table  1 , Figure  5 ) and displays a reciprocal pattern between the M vs. WT and V vs. VC comparisons (0. 48 vs. 2. 25, Table  1 ), we suggest that the TcsE-mediated secretion of TcsL is specific, being the only protein released by this holin-like protein under both conditions tested. The proteins and their protein ID accession numbers are listed in the order of fold change.
Bioinformatic Analysis Sequences representing the clostridial PaLocs and associated genome sequences were obtained from GenBank  [45] , with primary accession numbers for each sequence as follows: C. difficile 630  [46] : CP010905, P. sordellii ATCC 9714  [47] : LN679999, P. sor-dellii JGS6382  [47] : LN681235, C. perfringens JIR12708  [48] : LN835295 and C. novyi (A) BKT29909  [49] : JENM01000095. The sequences were further manually annotated using Artemis  [50]  on the basis of homology to entries in the Pfam database  [35]  via the HMM-SCAN search on the HMMER web server  [51]. The prediction of signal peptides and transmembrane domains within predicted amino acid sequences was performed using the Phobius web server  [52]  and confirmed using SignalP 4. 1  [53]. Protein molecular weights were determined using SnapGene Viewer (from GSL Biotech; available at snapgene.
PCR reactions were converted to droplets in DG8 TM cartridges (Bio-Rad) using the QX200 TM droplet generator (Bio-Rad) and amplified in a C1000 Touch TM thermal cycler (Bio-Rad). Amplification events within individual droplets were measured by the QX200 TM droplet reader (Bio-Rad), and the resulting data were analysed using QuantaSoft TM software (Bio-Rad). tcsL expression levels represent the number of transcripts per ng of cDNA, as a percentage of the transcripts of the housekeeping gene rpoA. Statistical analysis was carried out using the Mann-Whitney U test on four independent biological replicates.
To do this, samples were separated by SDS-PAGE in a 4-15% gradient Stain-Free gel (Bio-Rad), and proteins in each lane were detected using the ChemiDoc Imaging system (Bio-Rad). Using Image Lab (Bio-Rad) software, densitometry against the BenchMark protein standard (Thermo Fisher Scientific) allowed protein concentrations to be determined. Samples were then diluted to 0. 4 µg/ µL using 1× LDS buffer. Then, 10 µg of protein from each sample (4 biological replicates) was simultaneously reduced and alkylated with 50 mM TCEP and 50 mM chloroacetamide, respectively, for 5 min at 95 • C. Proteins were then digested in-solution with 500 ng trypsin (Promega) and incubated overnight at 37 • C. Deoxycholate (DOC) was removed by phase transfer using an equal volume of ethyl acetate and acidified to 0.
The non-linear gradient conditions for Buffer B were as follows: 2. 5-7. 5% over 1 min, 7. 5-37. 5% over 90 min, 37. 5-42. 5% over 3 min, 42. 5-99% over 5 min, 99% hold 6 min, 99-2. 5% over 1 min, and 2. 5% hold 17 min. Data were collected in positive mode using data-dependent acquisition. MS scan properties were as follows: scan range (m/z) 375-1575, Orbitrap resolution 120,000, AGC target 1E6, maximum injection time 54 ms, and dynamic exclusion 15 s. MS/MS scan properties were as follows: HCD activation, isolation window of 1. 8 (m/z), collision energy 32%, Orbitrap resolution 30,000, AGC target 2E5, maximum injection time 54 ms. Raw files were analysed using the MaxQuant platform  [61]  version 1. 5. 5. 1, searching against a concatenated database consisting of predicted P. sordellii ATCC9714 coding sequences from the available genome sequence (Genbank accession numbers LN679998, LN679999, and LN680000).
Contaminant proteins from the media (yeast proteins (UniProt Proteome ID UP000002311) and casein subtypes (UniprotKB P02666, P02668, P02662 and P02663)) and products encoded by the Group II Intron or pRPF185 vector (ErmB (UniprotKB P20173) and β-glucuronidase (UniprotKB P05804)) were also identified but removed from further comparative analysis. Spectra were searched with the following criteria: specific digestion mode; maximum 2 missed cleavages; fixed modification of carbamidomethylcysteine; variable modifications of methionine oxidation; and N-terminal acetylation. Labelfree quantification (LFQ), and match between run options were enabled, and false discovery rates of 1% for proteins and peptides were applied, with 2 minimum peptides required for identification. The raw data from this analysis are provided in Supplementary Data set 1.
36. 32 Using these thresholds, we performed variant clumping implemented in PLINK 1. 9  33  to select cisgenetic instruments for each protein, with an LD model derived from individual-level genotype data imputed against the Haplotype Reference Consortium 34 reference panel from a random sample of 10,000 UK Biobank  35  participants. MR estimates were calculated using the Wald ratio estimator for proteins with a single instrument selected, or the inversevariance weighted (IVW) estimator for proteins with 2 or more instruments. The Wald ratio estimates are calculated as the regression coefficient for genetic association with the outcome divided by the regression coefficient for genetic association with circulating protein levels. The IVW estimates are calculated as the average of instrument ratio coefficients weighted by the inverse variance.
MR with principal components is an alternative model to account for correlation between instruments,  32  and MR with Egger regression estimator provides estimates accounting for residual horizontal pleiotropy. 12 To reduce spurious associations that may arise because of excess multicollinearity or bias toward the null because of weak instruments in 2-sample MR,  14  outlier point estimates with a value outside 1. 5 times the interquartile range above the upper quartile and below the lower quartile were removed. An association was declared as robust if all point estimates from the multiverse sensitivity analysis were directionally concordant with estimates from the primary MR analysis, including those on the basis of strict instrument selection parameters and a standard IVW model. The IVW and MR with Egger regression estimates were calculated using the MendelianRandomization package in R,  38  with a fixed-effect model for 3 or fewer genetic instruments, or a multiplicative random-effects model otherwise.
Evaluation of Druggability and Clinical Development Activity We extracted the druggability profile of candidate target proteins from an updated list of druggable genes. 6 To evaluate clinical development activity of candidate drugs targeting the candidate proteins, we queried the ChEMBL  46  (release 27) database to get information on drug molecule types, approved indications, and target outcomes in clinical trials. We complemented this query by performing a manual search through the https://www. ClinicalTrials. gov website for each candidate target.
Causal Effect Estimation With cis-MR Of the 90 proteins being studied, cis region genetic association summary statistics were available for 83 proteins encoded by autosomal genes (Table  S2 ). Cis region sizes varied according to gene length from 401 to 705 kbp and contained a mean of 1181 variants (SD, 498). Using the primary instrument selection parameter with LD r 2 threshold of 0. 4 and P value threshold of 10 -4 , we identified 75 proteins with 1 to 125 (median, 23) cisgenetic instrument, including 40 of the 44 observationally associated proteins. For comparison, conventional instrument selection parameters (LD r 2 <0. 05, P<5×10 -8 ) identified 70 proteins with 1 to 28 (median, 5) cisgenetic instruments. Instrument-specific estimates are provided in the data and code at https:// github.
Appraisal of Druggability and Existing Approved or Clinical-Phase Drug Candidates for Candidate Protein Targets To evaluate the druggability and drug development activities of candidate targets, we searched through a list of druggable genes,  6  the ChEMBL (release 27) drug discovery database, and a clinical trial registry (https:// www. clinicaltrials. gov, accessed on December 1, 2020). We grouped candidate targets into 3 categories corresponding to the highest status in the drug development pipeline: approved (targeted by drugs already approved for 1 or more conditions), in development (currently being investigated in clinical trials), and druggable (listed as druggable targets; Table  2 ). A candidate drug targeting adrenomedullin, adrecizumab (a humanized, monoclonal, nonneutralizing antibody against the N terminus of ADM  55  ), is entering phase II trials for septic shock (URL: https://www.
ClinicalTrials. gov; Unique identifier: NCT03085758), cardiogenic shock (Unique identifier: NCT03989531), and acute HF (Unique identifier: NCT04252937). A modified citrus pectin Gal-3 inhibitor has been evaluated for effects markers of collagen metabolism in patients with hypertension in a proof-of-concept clinical trial for cardiac fibrosis. 56 CSF-1 and MMP-12 inhibitors are currently being evaluated in clinical trials for non-HF conditions. Burosumab, a monoclonal antibody FGF-23 inhibitor, has already been approved for treating X-linked hypophosphatemia and hypophosphatemic rickets. Although we found no ongoing trials specific for CHI3L1 or CTSL1, inhibition of CTSL1 is proposed as potential treatment for SARS-CoV-2 infection, and several approved agents show inhibitory activity against CTSL1.
Acknowledgments The authors thank the participants of PIVUS, ULSAM, and studies included in the HOMAGE, SCALLOP, and HERMES consortia. The authors thank  Olink Proteomics  for providing proteomics assays used in PIVUS, ULSAM, and studies in the HOMAGE and SCALLOP consortia. The authors thank the investigators of consortia and research groups who performed GWAS analyses and made summary statistics data available to use in the present study. The authors acknowledge the use of the  UCL Myriad High Performance Computing Facility (Myriad@ UCL ), and associated support services in the completion of this work. A. H. , A. M. , A. D. H. ‚ and R. T. L. conceived and designed the study. J. S. , L. L, J. Ä. , and F. Z. provided data for observational meta-analysis. A. M. and R. T. L. provided data for MR analysis.
Sources of Funding This work is supported by the  BigData@Heart Consortium  funded by the  Innovative Medicines Initiative-2 Join Undertaking  under grand agreement No. 116074 , the  UCL Hospitals NIHR Biomedical Research Centre , the  British Heart Foundation (BHF)   Research Accelerator Award  ( AA/18/6/34223 ), and  UK Research and Innovation/ NIHR-funded Mulimorbidity Mechanism and Therapeutics Research Collaborative  ( MR/V033867/1 ). A. H. ( FS/18/65/34186 ) and M. G. -M. ( FS/17/70/33482 ) acknowledge support by the  BHF Cardiovascular Biomedicine PhD studentship. A. D. H. is an  NIHR Senior Investigator. A. F. S is supported by  BHF  grant  PG/18/503383 , and acknowledges support by grant  R01 LM010098  from the  National Institutes of Health  (United States). R. K. acknowledges support by the  Walker-Inman Endowment , the  Mandel Foundation , and grant  R03 HL144812-01.
L. L. is supported by a grant from the  Swedish Heart-Lung Foundation. J. Ä. is supported by grants from the  Swedish Research Council  ( 2019-01015  and  2020-00243 ) and the  Swedish Heart-Lung Foundation  ( 20180343  and  20210357 ). R. T. L. is supported by a  UK Research and   Innovation Rutherford Fellowship  hosted by  Health Data Research UK  ( MR/S003754/1 ) and  BigData@Heart Consortium  funded by the  Innovative Medicines Initiative-2 Joint Undertaking  under grant agreement No. 116074. C. F. , A. F. S. , and  R. T. L. acknowledge additional support from  UCL Hospitals NIHR Biomedical Research Center.
Data Analysis Analyses were performed using the "lavaan" library available on the R software (version 3. 6. 2). Path analysis was performed using data from the variance-covariance matrix involving the variables of interest (see Table  2  with Pearson's ρ correlation estimates). Given the significant violation of the multivariate normality of the distribution between the variables (Mardia Skewness = 292. 63; p < 0. 001; Mardia Kurtosis = 5. 46; p < 0. 001), the Robust Maximum Likelihood estimator (MLR) was chosen to estimate the model and the standardized coefficients (β) of its different paths. To establish the general adequacy of the model, we relied on the interpretation of the Goodness-of-Fit indices with regard to the recommendations of  Hu and Bentler (1999) , i. e. , absolute indices less than 0.