dataesr/scientific-paragraphs-categorization huggingface dataset:
Training in  Mathematics for Real-World Systems ) and support from the  Labex CelTisPhyBio  ( ANR-11-LABX-0038 ,  ANR-10-IDEX-0001-02 ). MST Acknowledges the generous support of the  JSPS , via a long term fellowship, and the peerless hospitality of  Prof Yamamoto  at  Kyoto University  where this work was completed. Finally, all authors would like to extend their sincere thanks to  Daniela Kraft  and  Melissa Rinaldin  for discussions and access to unpublished data.
Amplicons were sequenced using a v2 PE500 kit with custom primers  (Kozich et al. , 2013)  on the Illumina MiSeq platform (KU Leuven Genomics Core) producing 2 × 250nt paired-end reads. Sequence reads were processed using R 3. 3. 2 (R Core Team, 2018) as previously reported by  Callahan et al. (2016b). Sequences were trimmed (the first 10 nucleotides and all nucleotides from position 190 onward were removed) and filtered (maximum two expected errors per read) on paired ends jointly. Sequence variants were inferred using the high-resolution DADA2 method  (Callahan et al. , 2016a)  and chimeras were removed. Taxonomy was assigned with a naive Bayesian classifier using the RDP v14 training set. Amplicon sequence variants (ASVs, hereafter called OTUs) which had no taxonomic assignment at phylum level or were assigned as "Chloroplast" or "Cyanobacteria" were removed from the dataset.
For Experiment 1, the final dataset contained 2,887,669 reads, on average 27,766 reads per sample (minimum = 4,133 reads, maximum = 63,594 reads). For Experiment 2, the final dataset contained 1,500,800 reads, Statistical analyses and plots were performed using R 3. 3. 2 (R Core Team, 2018). To investigate differences in community composition among samples (β-diversity), Bray-Curtis dissimilarity indices were calculated and plotted using Principal Coordinates Analysis (PCoA) with the phyloseq package  (McMurdie and Holmes, 2013). For Experiment 1, the effects of diet, genotype, community type (i. e. , BPK and GM) and their interactions on β-diversity were assessed through a PERMANOVA, using the Adonis function of the vegan package (tested using 999 permutations of rows). For Experiment 2, we also used a PERMANOVA to examine how microbiome inoculum, recipient genotype, community type, and their interactions might affect community composition.
For both experiments, analyses were carried out both for GMs and BPKs jointly and for each of them separately. Samples and taxa were clustered hierarchically based on Bray-Curtis dissimilarity indices, using the UPGMA (unweighted pair group method with arithmetic mean) agglomeration method, with the fastcluster package. A heat map of OTUs dominance in the different samples was obtained using the gplots package. To identify how bacterial classes differed among community types and diets, OTUs were grouped at class level, and differential abundance analyses were performed with the Bioconductor package DESeq2  (Love et al. , 2014). Venn diagrams illustrating overlap of OTUs among community types and diets were produced using Venny 2. 1. 0 online freeware  (Oliveros, 2007). For both experiments, we investigated the correlation between variation in BPK composition on the one hand and variation in GM composition on the other hand by performing a Mantel test to compare the Bray-Curtis dissimilarity matrices of the two community types (permutations = 999; statistics based on Pearson's correlation).
ACKNOWLEDGMENTS We would like to thank  Dries Bonte ,  Lore Bulteel ,  Steven Declerck ,  Shira Houwenhuyse ,  Lizanne Jansens ,  Gregory Maes ,  Koenraad Muylaert ,  Shinjini Mukherjee ,  Jeroen Raes ,  Robby Stoks ,  Caroline Souffreau , and the  FWO EVENET network  for stimulating discussions. We are also grateful to the  KU Leuven Genomics Core  for support with the sequencing.
Purpose: Gene therapy brings opportunities to discover cures for diseases for which there are no adequate treatments. As most gene therapies target rare diseases, several challenges are associated with their clinical development, such as limited population size, lack of established clinical pathways for development, and sometimes the absence of validated endpoints. The objective of this study was to systematically review and evaluate the methodology and design of European clinical trials (CTs) utilising gene therapy medicinal products (GTMPs). Methods: A systematic search of online CT databases was performed using keywords to identify CTs conducted with GTMPs in Europe, published from 1 January 1995 to 31 July 2019.
Software and data processing The following data were extracted and frequentist processing using MS Excel (2010) was performed: registration number, sponsor protocol number, CT name, official title of the CT, scientific title, type of the trial, phase, trial design, investigational medicinal product (IMP) identification as GTMP or not, trade name/international nonproprietary name (INN), principal sponsor, disease/indication (s) and URL. The search was conducted in August 2019.
This was considered adequate to avoid differences in health-related behaviors between the intervention groups. For these studies, there was no specific information in the protocol or published data on blinding of patients and researchers  [6, [9] [10] [11]. As outlined in RoB 2. 0, when multiple analyses are reported for estimation of intervention effect, the effect of assignment to interventions should be estimated by intention-to-treat (ITT) analysis that includes all randomised participants  [4]. In two of the analysed RCTs (study nos. 2012-001700-37 and 2006-001246-13), ITT analyses were performed  [5, 11]. In study no. 2011-004761-33, analyses were performed in a perprotocol (PP) population defined as all randomised participants who received at least nine doses of assigned intervention.
The reasons for discontinuation in the ITT population were similar between treatment and placebo groups and well described in the published paper  [7]. In study no. 2004-002508-13, efficacy analyses were performed in a modified ITT (mITT) population which included all randomised patients who had at least one post randomisation treadmill exercise test (273 (94. 5%) vs 289) and additional PP patients data analyses were conducted  [12]. Safety endpoints on all randomised patients were analysed by the Wilcoxon-Mann-Whitney (WMW) test. Based on the above data, the risk of bias due to deviations from the intended interventions for all reviewed RCTs was evaluated as low. The published results did not mention non-adherence to the therapy, which could have negatively affected the results  [9, 10]. There was no data on patient adherence to the assigned interventions or discussion regarding the reasons for such deviations if they arose in any of the reviewed RCTs.
Risk of bias due to missing outcome data This domain addressed risk of bias due to missing outcome data, including biases introduced by procedures used to impute or otherwise account for missing outcome data  [4]. These biases rise not only because of missing data but most notably because of missing data mechanism. From the data given in the CTs synopses and published results, it was very challenging to identify whether the chance that the outcome was missing depended on its true value. For this reason, the assessment of the analysed RCTs was performed based on whether the outcome was measured in all participants. The size of the number of participants with missing outcome data and analyses was used to confirm that missing data id not significantly alter the estimated interventions effect.
In study no. 2012-001700-37, primary analysis of the primary and secondary endpoints was done in mITT population that comprised all randomised participants who received the intervention and excluded subjects who were AAV1 neutralizing antibody positive (243 patients, 97%). Secondary analyses were conducted with the ITT population, which consisted of all 250 randomised patients. Data obtained by both analyses were similar (ITT: n = 250, HR 95% CI, recurrent events: 0. 92 (0. 53-1. 62); terminal events: 1. 23 (0. 71-2. 14); mITT: n = 243, HR 95% CI, recurrent events: 0. 93 (0. 53-1. 65); terminal events: 1. 27 (0. 72-2. 24)). The joint frailty model, a semi-parametric analysis that takes into account recurrent clinical events, uneven follow-up periods between groups, and terminal events as a competing risk  [5] , was used in the primary study analysis.
In study no. 2011-004761-33, the primary analysis was done in PP population predefined as participants who received at least nine doses of IMP or placebo. ANCOVA testing was conducted by the trial investigators to adjust the treatment effect in the IMP group versus placebo at 12 months follow up. The ANCOVAadjusted treatment effect (3. 7%, 95% CI 0. 1-7. 3; p = 0 • 046) was comparable with the treatment effect in patients in the ITT population (3. 6%, 95% CI 0. 2-7. 0; p = 0. 039) which demonstrated that probable values of the missing outcome data did not significantly alter the estimated intervention effect. The reasons for missing data between the two intervention groups were similar, well documented, and not related to the CT outcome itself  [7]. In study no. 2006-001246-13, the primary efficacy and safety analyses were done in the ITT population comprising all 732 patients enrolled in the CT.
The main reasons for premature withdrawal were the sponsor's decision to discontinue treatment with the CT drug, withdrawal initiated by the investigator, and IC withdrawn by the patient  [6]. In study no. 2004-002508-13, out of 289 randomised participants across the 4 patient groups, 273 patients (94. 5%) that had at least one treadmill test were included in the efficacy analysis (mITT). The number of patients with missing test was similar across three treatment groups and placebo, and the reasons for not performing it were described in the published results. The WMW test, stratified by the presence or absence of diabetes mellitus at baseline was applied separately to three comparisons between each treatment group and the placebo group to compare the primary efficacy endpoint  [9]. Missing data from the 26-week peak walking time test (PWT), where the percentage change from baseline was used as primary efficacy endpoint, was input to the last-observation-carried-forward method (LOCF).
Risk of bias in measurement of the outcome This domain focuses mainly on differential errors related to intervention assignment. Such errors are less probable when outcome assessors are blinded to intervention assignment. Risk of bias in this domain depends on appropriateness of the method used for outcome measuring, the outcome assessor and whether the outcome assessor is blinded to intervention assignment  [4]. This data is important for assessing the risk of bias in outcome measurement, especially when knowledge of the intervention can influence the judgment of the outcome assessor. In Study no. 2012-001700-37, all patients, physicians and outcome assessors were blinded to treatment assignment. The study was an event-driven trial and all clinical events were reviewed by both a nonblinded Data Monitoring Committee and an independent blinded Clinical Endpoints Committee.
Any clinical events served as an automatic trigger for safety evaluation by the blinded Clinical Endpoints Committee  [12]. In study no. 2011-004761-33, the CT was monitored at intervals by an independent Data Monitoring and Ethics Committee (DMEC), which verified the blinded group data and provided written confirmation that the trial could continue without modification. Clinical examination results, including pulmonary function, gas transfer markers, and systemic inflammation indicators were examined in a masked manner by the DMEC  [14]. The available data for study no. 2006-001246-13 did not provide specific information on the masking of participants. However, the outcomes reported, including overall survival (OS) and the laboratory variables (complete blood count and chemistry panel), did not involve judgement that would potentially lead to bias.
The data from secondary efficacy endpoints, and progression-free survival were adjudicated by blinded peer review  [6]. In study no. 2004-002508-13, the methods of outcome measurement were very specific and the same measurement methods and thresholds in both the intervention and placebo groups were used at comparable time points. There was no specific data provided on trial participants masking. However, the primary efficacy parameter was assessed by PWT, which did not involve outcome assessor judgement. After the first interim assessment of unblinded patient safety data, assessment by the independent Data Monitoring Committee (DMC) was blinded  [9]. Only in one of the reviewed RCTs (study no. 2012-001700-37) was detailed information for blinding of all participants in the trial provided. All RCTs included in the analyses were predefined as double-blind.
2012-001700-37 was analysed based on the trial protocol and published data. The efficacy and safety endpoints analyses were performed as planned in the CT protocol. There were amendments in the protocol, which were presented in detail in the published data (https://www. clinicaltrialsregister. eu/ctr-search/trial/ 2012-001700-37/results). Post-hoc analyses for the primary and secondary endpoints, stratified by randomisation in the study before and after the protocol amendments, were performed to ensure that no meaningful differences in the treatment effect were observed (primary outcome: HR 0. 86 [95% CI 0. 32-2. 27] before amendment vs 1. 05 [0. 53-2. 08] after amendment; secondary outcome: 1. 14 [0. 53-2. 44] vs 1. 38 [0. 59-3. 25]) [5]. Standardised outcome measures for the cystic fibrosis (CF) CT were extensively discussed  [17] , but there was no consensus (http://www.
comet-initiative. org/stu dies/details/882). Study no. 2011-004761-33, was designed after extensive study of the published CF RCTs  [14]. A detailed plan for statistical analysis was approved and finalised before the database was locked and the study unblinded. The relevant data were extracted once the database was locked and the researchers were unblinded  [14]. No deviations were observed between planned and published outcome measurements and analyses. Currently, a program that is still ongoing started developing COS for CTs in renal cancer (http://www. comet-initiative. org/studies/details/1406). The clinical outcomes in study no. 2006-001246-13 were common for cancer therapy (patient survival and progressionfree survival). There was no deviation from the researchers' pre-specified intentions for planned outcome measurements and analyses  [11].
In three of the reviewed RCTs, blinding was described only with the broad term 'double blind'. Explicit reporting on the blinding mechanism for patients and trial personnel was given only in one of the RCTs. In addition, only limited data were provided in the reviewed RCTs regarding deviations from intended intervention that were inconsistent with the trial protocol. In study no. 2011-004761-33, initiation of a treatment non-compliant with the protocol was mentioned as a reason for dropout of patients. In EudraCT only synopses for RCTs results that contain modest information are available. The principles of the CONSORT statement should be widely followed for improving the quality of reporting of RCTs. Challenges in conducting CT with ATMP are also posed by their biological nature and specific manufacturing process.
Selection of reliable and well-defined objective endpoints which demonstrate clinical benefits and design plans for managing missing outcomes will minimize the bias in outcome analysis. In clinical areas where potential GTs may offer treatment options, academia should consider the development of COS to evaluate efficacy and safety similar to the coreHEM project (http://www. comet-initiative. org/stu dies/details/997). One of the limitations of the current review is that only a small number of RCTs were identified in our search. According to the Global Gene Therapy Clinical Trials Registry  [23] , 2686 CTs were conducted in a shorter time period than the current systematic review (1 January 1995-31 December 2018), which is a far greater number than that found in the current search. This may be due to lower keyword sensitivity of the databases employed in this review or the possibility that not all CTs with GTMPs conducted in Europe are registered in EudraCT and ICTRP.
F. A). A minimum of 20 × 10 3 cells was acquired per sample and data were analyzed using ModFit LT V3. 3 software (Verity Software House, Topsahm, Maine, USA, https ://www. vsh. com/produ cts/mflt/). The percentage of cells in G0/G1, S and G2/M was determined from DNA content histograms.
Apoptosis analysis. Apoptosis was evaluated by measuring the externalization of phosphatidylserine with Annexin V, and nucleus labelling with propidium iodide (PI). In this context, cultured cells were treated with different concentrations of FL3 for 48 h. Apoptosis rates were assessed using flow cytometry (LSR 2 with Diva 6. 2 Software, Becton Dickinson Biosciences, San Jose California, USA, https ://www. bdbio scien ces. com/en-us/ instr ument s/resea rch-instr ument s/resea rch-softw are/flow-cytom etry-acqui sitio n/facsd iva-softw are) using the Annexin V-FITC/PI Apoptosis kit (V13241, Thermo Fisher Scientific) according to the manufacturer's recommendations. RNA extraction and analysis. Total RNAs were isolated from the U87-MG cell line. 1 µg of RNA was retro-transcribed using the iScript Reverse Transcription Supermix (Bio-Rad Laboratories, Hercules, CA, USA) according to the manufacturer's instructions.
1 ). SA-β gal staining. U87-MG cells were seeded into 24 well plates at 5 × 10 4 cells per well, and then treated with FL3 for 48 h. Afterwards, the treatment was stopped, cells were washed with PBS, refilled with new fresh medium and incubated for 8 days. Medium was changed every two days. At each time point (2, 4, 6 and 8 days), an aliquot of the cells was fixed and stained with the senescence β-galactosidase staining kit #9860 (Cell Signaling), and then kept in a dry incubator (without CO 2 ) at 37 °C overnight. Cells were checked under an inverted microscope (Nikon Eclipse TS100, Nikon) for blue color detection and photos were taken using the NIS element software (Nikon). We did the same protocol of SA-β Gal staining on U87-MG (TMZ off), U373-MG and LN443 cells. Live/dead assay. U87-MG cells were seeded onto coverslips in 24 well plates at 5 × 10 4 cells per well, and then treated with 200 nM of FL3 for 48 h.
1 Hz by electrical stimulation of Schaffer collaterals and commissural fibers located in the stratum radiatum. The averaged slope of three PFVs and fEPSPs was measured using Win LTP software  [45, 46]. To assess the level of receptor activation, an index of synaptic efficacy (I SE ) corresponding to the fEPSP/PFV ratio was plotted against increasing stimulus intensity (300, 400 and 500 µA). Paired-pulse facilitation (PPF) of basal synaptic transmission was induced by electrical stimulation of afferent fibers with paired-pulse (inter-stimulus interval of 30 ms). PPF was calculated as the ratio of the slope of the second stimulation to the first one. Specific NMDAR-mediated fEPSPs were isolated in slices perfused with low Mg 2+ (0. 1 mM) containing aCSF and supplemented with the non-NMDAR antagonist 2,3-dioxo-6-nitro-1,2,3,4tetrahydrobenzoquinoxaline-7-sulfonamide (NBQX, 10 µM).
Open-Field The open-field test was performed in a device (50 × 50 × 20 cm, white plexiglass, Viewpoint) with an infrared floor allowing to record the animals in the absence of light (0 lux). Each mouse was allowed to freely explore the device for a period of 30 min. General exploration was measured by calculating the total distance traveled in the apparatus. Two zones (periphery vs. center) were designated digitally, and the time spent in each was measured using the software Ethovision (Noldus™, Wageningen, Netherlands). The percentage of time spent in the center zone, serving as an index of anxiety-like behavior, was assessed in the total duration of the test and only in the first one minute.
One day later, a relearning phase was performed with the same design as the learning phase, but the PF was transferred to the opposite quadrant. Once again, 72 h after the last day of relearning, probe-test 2 was performed by a unique trial (60 s). Each session was videotaped, and parameters (latency to find the PF, swimming velocity in learning/relearning phases, and time spent in each quadrant, swimming velocity in probe tests) were analyzed through the Ethovision software ((Noldus™, Wageningen, Netherlands).
Data Analysis All data are expressed as mean ± S. E. M, except the dosage of amino acids, the number of transitions in the black and white box, and the percentage of time in the center in the open field, which are expressed in median ± interquartile. After the assessment of normality of the data distribution, unpaired or paired t-test, one-sample t-test, one or two-way ANOVA (with repeated measures or not), and Mann-Whitney were used accordingly. One-or two-way ANOVA with repeated measurements were followed by Bonferroni-Dunn post hoc tests for multiple comparisons. In all cases, differences were considered significant when p < 0. 05. Analyses were performed with GraphPad Prism 8. 0 (GraphPad Software, San Diego, CA, USA) and Statview 5. 0 (BrainPower Inc, Fremont, CA, USA).
S. K. Palaninathan published a very exhaustive structural review in which he analysed TTR at atomic level, underlining its biological function and misfolding  46. In parallel, some of us examined all natural and chemical ligands, belonged to different chemical classes, able to stabilise the TTR tetramer, highlighting the structural modifications that have led to an improvement or to a decrease of their potency and/or selectivity  17. Since that time, several other natural compounds have been investigated for their ability to inhibit the TTR fibril formation and they have been also co-crystallised with TTR, growing the knowledge about interaction and affinity binding. In Table  1 , we have listed all the X-ray crystal structures, deposited at the PDB data bank, in which TTR is in complex with natural products or their metabolites.
The binding experiments in the presence of radiolabelled 125 I-T 4 , as a competitor, indicated that QUE does not displace the TTRbound hormone even at highest concentration (50 mM). On the contrary, fluorescence data showed that QUE is able to induce the displacement of TTR-bound to pterostilbene, which can bind to TTR independently from the presence or the absence of pre- incubated T 4  50. These results suggested a different binding site for polyphenol compounds compared to T 4 hormone, with a superior affinity for benzopyran structure to the stilbene one. The crystal structures of TTR-ligand complexed deposited in the PDB data bank do not furnished an explanation about the difference in the binding mechanism, obtained in solution. The superposition of TTR-QUE (4WNJ) and TTR-pterostilbene (4WNS) structures shows that the ligands fit in T 4 binding site, with a good density, only with site B using a negative binding cooperativity  50  (Figure  5(A) ).
Five different V30M TTR mutant crystal structures were solved in complex with c-M, a-M, and 3-isomangostin (Table  1 ). The crystals grown belong to the orthorhombic space group P2 1 2 1 2 with the cell parameters comparable to those deposited in the PDB data base. The resolution of the structures ranges from 1. 90 to 1. 40 Å. The structural analysis between TTR-c-M and TTR-a-M crystal complexes showed that the position and the orientation of the xanthones are very similar in T 4 -BS (r. m. s. d. 0. 36 Å)  54. Even so, the mangostins stabilise the TTR tetramer displaying a different binding mode compared to the most known TTR stabilisers (Figure  8(A, B )). The c-M binds diagonally against the 2-fold axis of the BS at the interface between two subunits of TTR (AA' or BB'), and its binding is associated with two chloride ions, derived by the Glabridin (GLA) is a prenylated isoflavane originally isolated from the roots of Glycyrrhiza glabra L.