dataesr/scientific-paragraphs-categorization huggingface dataset:
Patient Selection Patients eligible for analysis were adults diagnosed with mCRC and scheduled to receive TARE with Y90 resin microspheres. There were no specific exclusion criteria. All included patients signed an informed consent form. This research project was performed in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Patient recruitment took place between 1 January 2015 and 31 December 2017. Follow-up data was collected until 31 December 2019. Sites were requested to follow-up with the patient every 3 months for 24 months after the first TARE treatment. In addition, sites were encouraged to obtain follow-up information from referring physicians if follow-up evaluations were not performed at the site of the TARE treatment.
Assessments Detailed information concerning the timing of assessments can be found in Helmberger et al, 2020 [21]. At the time of first treatment, baseline data, demographics and treatment-related data were collected. The number of tumors were considered for the whole liver, whereby the category "uncountable" was included in cases where the number of tumors exceeded reliable counting of lesions. Tumor burden was presented as percentage of tumor volume (mL) per liver volume (mL). Treatment intention was defined before the procedure, whereby "ablation" was defined as an attempt to create an ablative effect with the Y90 resin microspheres, and "palliative" as any intention not part of a curative approach. Information concerning post-TARE treatments, safety data and time to event data were collected at every followup.
Sites were requested to include available imaging data, but the observational nature of the study prevent any mandates on the type of imaging (CT, MRI, PET). Imaging data was evaluated by the local investigator or physician performing the followup imaging. Time-to-event was defined from the date of the first TARE treatment until the date of the event. Safety outcomes are described as occurrences of any adverse events according to the Common Terminology Criteria for Adverse Events, version 4. 03. A priori expected serious adverse events (SAEs, grade 3 and 4) were abdominal pain, fatigue, fever, nausea, vomiting, gastrointestinal ulceration, gastritis, radiation cholecystitis, radiation pancreatitis, and radioembolization-induced liver disease (REILD) and were included as answer options in the electronic case report form.
2 when deciding to enter a predictor into the stepwise model. The model with the lowest Akaike information criterion value was considered as the final model. Data was presented using hazard ratio (HR) and 95% confidence interval (CI). All available data are used, and no imputations of missing data are made. Where data was missing, it was indicated in the tables. An additional propensity score analysis was performed to further analyse the role of the two main methods to calculate the prescribed Y90 activity, [modified] Body Surface Area ([m]BSA) and partition model, in the survival outcomes of TARE treatments (see Supplement 1 for the propensity score analysis methods).
Both cohorts reported that TARE was well-tolerated by patients with an acceptable toxicity (7% and 3% SAEs, respectively) similar to our findings (11. 8%). 0] [31] [32] [33]  The dataset from the French prospective multicentre observational study CIRSE Registry for SIR-Spheres in France (CIRT-FR) reported 27% SAE occurrence in 63 mCRC patients treated with TARE (data forthcoming). Despite many promising efficacy signals from above studies, the SIRFLOX and FOXFIRE randomized controlled trials remained without any significant survival benefit for first line mCRC patients compared to chemotherapy. 18 , 19 With TARE as second line treatment combined with systemic therapy, the recent randomized controlled EPOCH trial reported a significant improvement in PFS and hPFS compared to systemic therapy alone (HR 0.
Additionally, no data on tumor markers relevant to mCRC, such as CEA and CA 19-9 levels, or molecular characteristics such as RAS, BRAF or MSI status were collected. Although selection bias cannot be ruled out, regular remote monitoring and contractual agreements were put in place to reduce selection bias. Sites were encouraged to follow-up with patients when follow-up visits happened with the patient's referring physician, instead of on site. Remote monitoring was done to improve data quality; however, no source data verification was performed. Investigators evaluating imaging data instead of a central image review could have introduced bias concerning PFS or hPFS and should be considered when interpreting this data. We attempted to collect quality-of-life data -on a voluntary basis for the patientat the time of treatment and at every follow-up until the study exit.
The relevance of the collected dataset is currently being evaluated. The relatively high number of censored patients of OS (62/237, 26. 2%) and PFS (27/237, 11. 4%) is comparable to other studies in oncology and reflects the clinical reality of patients being treated in larger institutions having access to multiple treatments and studies. 49 Despite our promising results when comparing partition model with body surface driven dosing models, it must be noted that only 42/237 (17. 7%) patients received TARE dosage calculated using partition model. This imbalance in dose calculation methods needs to be considered when interpreting the results. Nevertheless, it is encouraging that both the multivariable analysis and the propensity score analysis were consistent in pointing towards the survival benefits of partition model dosimetry.
Acknowledgments The authors want to thank the patients, the CIRT investigators and site staff involved in the study, in particular the local study nurses that contributed significantly to the quality of the collected data through feedback and comments during the data collection phase. The CIRT study was funded by an independent investigator-initiated research grant from  SIRTEX Medical Europe GmbH (Bonn, Germany ). The electronic data capturing system was developed and supported by  ConexSys Inc  (Lincoln,  RI, United States ) and a customized data management system was designed by  Joaquin Padilla Montani (Vienna, Austria). Necessar y ser ver infrastructure was developed and maintained by  ITEA GmbH (Vienna, Austria ). The authors thank the  CIRSE Central Office  and the staff of the  CIRSE Clinical Research department  for their support during the design and setup of the study and drafting of the manuscript.
Axel Schmid, University Hospital Erlangen, Department of Radiology, Maximiliansplatz 1, 91054, Erlangen, Germany. Alessandro Vit ,  Azienda Ospedaliero Universitaria, SOC Diagnostica Angiografica e Radiologia Interventistica , via Grazzano 150/C, 33100,  Udine, Italy. The CIRT study was funded by an independent investigatorinitiated research grant from  SIRTEX Medical Europe GmbH (Bonn, Germany ). CIRSE, the  Cardiovascular and Interventional Radiological Society of Europe , was responsible for the independent execution of the CIRT study.
PARP domain conformational changes To explore the conformational effect of PARP-PARP interactions, we mined the Protein Data Bank (PDB) using the Protein Interfaces, Surfaces and Assemblies (PISA) tool  21  , identifying 88 PARP domain pairs in head-like contacts and 238 in tail-like contacts (Extended Data Fig. 5a  and Supplementary Table  1 ). The two contacts did not co-occur in any crystal structure. Head-like contacts appeared to induce (1) an open conformation of the D-loop 'base' and (2) a fully ordered β6-β7 loop atop the D-loop (Fig. 4a , Extended Data Fig. 5c  and Supplementary Table  1 ), as observed by cryo-EM. Although other determinants of D-loop conformation probably exist, such as small-molecule ligands (see Discussion), these observations suggest that the head contact opens the adenosine subsite of the NAD + pocket.
Vitrified grids were imaged in separate data collection sessions using Titan KRIOS transmission electron microscopes (Thermo Fisher Scientific) operated at 300 keV at the Electron Bio-Imaging Centre, Diamond Light Source, UK. A total of five datasets were collected with direct-detector cameras, four with a Gatan K2 Summit and one with a Gatan K3 camera in super-resolution counting mode using EPU software (Thermo Fisher Scientific, v1. 14. 0. 54). Cryo-EM micrographs were collected as movies with a nominal pixel size of 1. 06 Å (super-resolution dataset with a pixel size of 0. 53 Å), a total accumulated dose of 40 electrons per Å 2 and applied defocus values from -1. 2 to -3. 5 μm.
Image processing Movies were processed using RELION (v2. 10 and 3. 08)  37, 38. Images were motion-corrected and dose-weighted using MotionCor2 (ref. 39 ). Movies from the K3 super-resolution counting dataset were 2× binned at this stage, resulting in a pixel size of 1. 06 Å. The contrast transfer function (CTF) was estimated using CTFFIND4 (ref. 40 ). Straight portions of filaments were manually selected as start-end coordinates and extracted with a box size of 400 pixels and an inter-box distance of 27. 2 Å (asymmetric unit 2). Reference-free 2D classification was performed, and segments from suboptimal 2D class averages were discarded. Selected particles from good 2D classes from each dataset were combined (139,880 particles in total). To estimate the helical symmetry parameters, the best 2D class averages were padded in a larger box of 1,200 × 1,200 pixels for finer Fourier sampling, and their power spectra generated in Bshow (from Bsoft v1.
Model building, refinement and validation To aid model building, the post-processed map was locally sharpened using Phenix Autosharpen (from Phenix v1. 18. 2-3874)  47  using a high-resolution cut-off of 3. 0 Å. An initial model of a single TNKS2 SAM-PARP G1032W protomer was built in Coot  48  after fitting the TNKS2 PARP domain (PDB code 5NWG, chain IB)  33  and SAM domain (PDB code 5JRT)  4  into the central region of the sharpened cryo-EM map where resolution was highest, using UCSF Chimera (v1. 14)  49. A TNKS2 SAM-PARP G1032W filament of ten protomers per protofilament was obtained by applying helical and D1 symmetry to the protomer (equivalent to chain E of the presented model) in UCSF Chimera. The resulting filament model, containing ten protomers in each protofilament (A to J in sense direction, and K to T in antiparallel direction; see Extended Data Fig.
3j ), was real-space refined using Phenix Refine (from Phenix v1. 18. 2-3874)  47  (maximum of 100 iterations, 5 macrocycles, target bond root-mean-square deviation of 0. 01, target angles root-mean-square deviation of 1. 0, secondary structure restraints, non-crystallographic symmetry (NCS) detection and refinement, and Ramachandran restraints). Chain E was extracted and subjected to multiple iterations of model building in Coot, symmetrization in UCSF Chimera and real-space refinement in Phenix Refine. The final model was validated using MolProbity  50  , implemented in the Phenix software package. The FSC map versus model plot was calculated using mtriage in Phenix  51. Model refinement and validation statistics are shown in Extended Data Table  1.
All further processing steps were carried out in RELION (v3. 1. 0)  38. Several rounds of reference-free 2D classification were conducted, and the best class averages were used as templates for reference-based auto-picking. Particles (n = 20,131) were subsequently extracted and subjected to 2D classification, resulting in a cleaned dataset of 18,720 particles. A first round of asymmetric 3D refinement was carried out against a featureless cylinder, resulting in a map with a clear D1 symmetry axis. A second round of refinement was then carried out against this map with applied D1 symmetry, yielding a final map that showed clear features of a two-start helix. Projections of the final map were compared with projections of both the SAM domain filament from the SAM-PARP model and the single-stranded TNKS2 SAM domain filament crystal structure (PDB ID 5JRT  4  ), low-pass filtered to 20 Å.
3% FBS. Twenty hours following media change, cells from two technical replicates were lysed using passive lysis buffer (Promega) and processed for luminometry using the Dual-Luciferase Reporter Assay system (Promega). Plates were read using a POLARstar Omega plate reader (BMG Labtech), using the Omega software (v5. 70). Data were analysed using Microsoft Excel for Mac (v16. 57) and GraphPad Prism (v9. 3. 1). Upon background subtraction, ratios of firefly luciferase to Renilla luciferase signals were calculated for each of the two technical replicates. The means of the technical replicates were further analysed as indicated in the figure legends. Cells from the third and fourth technical replicates were lysed in 2× SDS sample buffer and used to monitor the expression levels of TNKS2 by western blotting.
The reaction was stopped by adding 25 μl of 4× SDS sample buffer and boiled for 5 min at 100 °C. Samples were analysed by western blotting using pan-ADP-ribose binding reagent (MABE1016, Millipore). Levels of pan-ADP-ribose were quantified using ImageJ software (NIH, v2. 3. 0/1. 53f), which involved background correction (using an empty lane) and normalizing to the levels of TNKS2 variants quantified from the without-NAD + conditions. For quantitation of in vitro PARylation, the portion of the lane corresponding to TNKS2 and above was measured (primarily auto-PARylation, see examples in Supplementary Fig. 1  (1) and (  5 )). Where background correction gave rise to negative values, these were constrained to zero. Data were expressed relative to WT TNKS2.
His 6 -MBP-TNKS2 SAM-PARP activity assays Equal amounts (1 μM) of purified recombinant proteins in a final purification buffer (50 mM HEPES-NaOH (pH 7. 5), 500 mM NaCl and 2 mM TCEP and 10% glycerol) were incubated with or without 0. 2 mM NAD + for 30 min at 30 °C in a thermoblock (VWR) with mild shaking (180 rpm). A higher concentration of NAD + (0. 5 mM) was used for the experiments shown in Extended Data Fig. 1. The reaction was stopped by adding 4× SDS loading buffer. Samples were resolved by SDS-PAGE, and ADP-ribosylation was detected using an anti-pan-ADP-ribose binding reagent (1:10,000 dilution; MABE1016, Millipore). Protein loading was assessed by Ponceau S (cat. no. P7170, Sigma-Aldrich) or Revert 700 total protein stain (cat. no. 926-11021, LI-COR).
Just before mass photometry measurements, 12 μl of buffer were pipetted into a well and used to identify the focal position for data collection using the autofocus function. Samples were diluted to an intermediate concentration of 250 nM and then immediately to a final concentration of 50 nM in the well (3 μl of 250 nM protein added to the 12-μl drop of buffer), except for the Y920A/G1032W variant, which was diluted to a final concentration of 10 nM because of the high number of binding events in the field of view due its monomeric state. Data acquisition was performed using the Refeyn Acquire MP software (v2. 3. 1). Mass photometry movies of 6,000 frames were recorded from a 10 × 10 μm instrument field of view at a frame rate of 362. 4 Hz, with a frame binning value of 4, resulting in an effective frame rate of 90.
6 Hz. Data processing. Data were processed and analysed using Refeyn Discover MP software (v2. 3. 0) by performing three main steps: (1) background removal, (2) identification of particle landing events on the coverslip acquisition field, and (3) particle fitting to extract maximum contrast. Default parameters were used for all steps. Individual particle contrasts from each individual movie were converted to mass using a contrast-to-mass calibration. Five datasets for each His 6 -MBP-TNKS2 SAM-PARP variant were merged to give a single kernel density estimate curve, using a Gaussian kernel with a fixed bandwidth of 5 kDa. The minimum between monomer and dimer peaks on the kernel density estimate curve for each variant was used as a cut-off to estimate the proportion of monomeric/oligomeric species in the sample.
Three variants (PARP-PARP tail combination, PARP-PARP head-tail combination and SAM/linker-PARP combination [PARP]) gave lower-quality data, characterized by multiple 'sticky' binding/unbinding species, low numbers of fitted events and poor definition between peaks. For these variants, the monomer/oligomer cut-off was instead taken from the G1032W variant. These cut-offs were then applied to the five datasets for each variant to calculate the mean percentage of monomeric and >monomeric events, with s. e. m. , using Microsoft Excel for Mac (v16. 57) and GraphPad Prism (v9. 3. 1). Note that the quantifications in Fig. 5e  and Extended Data Fig. 9b  show the percentages of particles that are monomeric or multimeric; this is distinct from the percentages of protein molecules in different assembly states (monomeric or >monomeric).
For example, a mass photometry peak corresponding to dimers and of equal height to the monomer peak contains twice as many proteins. Mass calibration. Contrast-to-mass calibration was performed in acquisition buffer. NativeMark unstained protein standard (#LC0725, Thermo Fisher Scientific), which contains proteins in the range of 20-1,200 kDa, was diluted 1:100 in acquisition buffer, and 5 μl were added to a 12-μl drop in a well for measurement. The following masses were used to generate a standard calibration curve in the Discover MP software: 146, 480 and 1,048 kDa. As polymers will dissociate upon dilution, measurements probably reflect dissociation products. This explains how mutations in the PARP-PARP head interface affect polymerization, although the detected polymeric species are smaller than the shortest polymers that would enable PARP-PARP domain contacts.
Z-stacks were imported into ImageJ/FIJI software (NIH, v2. 3. 0/1. 53f) and used to generate maximum intensity projections for analysis. At least two coverslips were analysed per condition. CellProfiler (Broad Institute, v3. 1. 9) was used to quantitate the number of puncta per cell and the size (area) of each individual punctum from image projections. The analysis pipeline was created to (1) identify cytoplasm using CellMask staining, (2) identify objects within this area using the IdentifyPrimaryObjects function, and (3) measure the number of puncta per cell and their size (area) in pixels. The average number of puncta per cell and the average size of puncta were calculated for three independent experiments, with a minimum of 150 cells quantified per condition in each experiment (Supplementary Table  4 ).
Differential scanning fluorimetry Thermal stability of the His 6 -MBP-TNKS2 SAM-PARP WT and mutant proteins was assessed using differential scanning fluorimetry  58, 59. Five μM of WT or mutant protein in purification buffer (20 mM HEPES-NaOH (pH 7. 5), 500 mM NaCl and 2 mM TCEP) were mixed with 5x SYPRO Orange (Invitrogen; relative to 5,000 × stock of undisclosed concentration), and 20 μl of each setup were transferred onto a 96-well PCR plate. Melting curves were obtained on a QuantStudio 6 Flex PCR machine (Thermo Fisher Scientific) with QuantStudio real-time PCR software (v1. 7. 1). Temperature increases were linear from 22 °C to 95 °C with 0. 5 °C per 15-s increments. Fluorescence intensity was measured in real time using the ROX channel. Average fluorescence intensities from three parallel experiments for each protein were normalized (0-100%), smoothed and plotted against the temperature using GraphPad Prism (v9.
See Supplementary Table  1  for PDB codes and analysis. Red lines denote side chain interactions amongst mutated residues. The black star denotes the combination of those mutations labelled by a grey star for each set. K1014A α2 is a control mutation outside the tail interface. N1022A  was designed to disrupt a potential contact with the SAM domain of the protomer interacting in the PARP:PARP head mode, but also contributes to the PARP:PARP tail interface. The ≈45% reporter reduction conferred by the R932A SAMα5 mutation is likely due to its moderate impact on polymerisation  4. Given that the combined SAM domain mutations disrupting the SAM/linker:PARP interface did not affect reporter activation, the K1003A PARPα2 mutation likely acts through a mechanism that is independent of the SAM/linker:PARP interaction.
(version January 2021). Uni-Prot entry names for human ARTD family members are PARP1_HUMAN, PARP2_HUMAN, PARP3_HUMAN, PARP4_HUMAN, PAR15_HUMAN, PAR14_ HUMAN, PARP9_HUMAN, PAR10_HUMAN, PAR11_HUMAN, PAR12_ HUMAN, ZCCHV_HUMAN, PARPT_HUMAN, PAR16_HUMAN, PARP8_ HUMAN and PARP6_HUMAN. NCBI accession numbers for TNKS1 orthologues are NP_003738. 2 (Homo sapiens), NP_780300. 2 (Mus musculus), NP_989671. 1 (Gallus gallus), XP_035410112. 1 (Cygnus atratus), XP_019389515. 1 (Crocodylus porosus), XP_037752450. 1 (Chelonia mydas), XP_026528659. 1 (Notechis scutatus), XP_018099067. 1 (Xenopus laevis), XP_005451454 (Oreochromis niloticus), ENSDART00000111694. 5 (Danio rerio), XP_005171802. 1 (D. rerio), XP_014351007. 1 (Latimeria chalumnae), XP_036384182. 1 (Megalops cyprinoides) and XP_032873798. 1 (Amblyraja radiata).
NCBI accession numbers for TNKS2 orthologues are NP_079511. 1 (H. sapiens), NP_001157107. 1 (M. musculus), NP_989672. 1 (G. gallus), XP_035404219. 1 (C. atratus), XP_019411065. 1 (C. porosus), XP_007059469. 2 (C. mydas), XP_026526558. 1 (N. scutatus), XP_018082988. 1 (X. laevis), XP_005471626. 1 (O. niloticus), XP_006006371. 1 (L. chalumnae), XP_036385759. 1 (M. cyprinoides), XP_032889463. 1 (A. radiata) and XP_020371197. 1 (Rhincodon typus). Two tankyrase paralogues appear to emerge in cartilaginous fish (Chondrichthyes). NCBI accession numbers for all other tankyrase orthologues are XP_032806710. 1 (Petromyzon marinus), XP_002121662. 3 (Ciona intestinalis), XP_019641281. 1 (Branchiostoma belcheri), XP_789260. 4 (Strongylocentrotus purpuratus), XP_022094330. 1 (Acanthaster planci), NP_651410.
Negative-stain EM of TNKS2 SAM shows a two-start helix. a, Crop of a representative negative-stain electron micrograph (of 67) showing TNKS2 SAM filaments. b, 3D map of TNKS2 SAM alone (left) and rigid-body fitted with the SAM domain from the SAM-PARP model (right). c, Comparison between a 2D class average, a projection of the SAM domain filament 3D map from b, a projection of the SAM domain from the SAM-PARP model, and a projection of the single-stranded TNKS2 SAM DH902/924RE filament crystal structure (PDB ID 5JRT 4 ); scale bars, 50 Å. The features of both the 2D class average and the projection of the 3D map obtained for TNKS2 SAM show clear similarity to those of the two-start SAM domain helix from the SAM-PARP model, as opposed to the single-start helix from the crystal structure. This demonstrates that the TNKS2 SAM domain autonomously forms two-start helices.
Multiple sequence alignment of catalytic domains from tankyrase homologues and ARTD family members. The indicated tankyrase orthologues and paralogues as well as Diphteria-toxin like ADP-ribosyltransferase (ARTD) family members were aligned and sequences coloured by percentage identity. Numbering above the alignment corresponds to human TNKS2. Sequences not aligning with the reference sequence (human TNKS2) were deleted for clarity. Buried residues in the PARP:PARP head-to-head, tail-to-tail and SAM:PARP interfaces, as defined by the PISA server 21 , are shaded in orange, green and red, respectively. See Methods for accession numbers. Extended Data Fig. 7 | Luciferase reporter assays to analyse contributions of domain interfaces to tankyrase function. a-d, β-catenin-responsive TOPFlash luciferase reporter assay to analyse the contributions of PARP:PARP tail and head, inter-protofilament, and SAM/linker:PARP interactions (a, n = 6 (3 for K1014A); b, n = 4; c, n = 3; d, n = 3 independent experiments; individual data points and means; error bars, SEM).