dataesr/scientific-paragraphs-categorization huggingface dataset:
Right: Heatmaps illustrate swimming activity. Scale bar, 10 cm. The numbers in the brackets indicate the numbers of mice. n. s. , no significance; *P < 0. 05; **P < 0. 01; ***P < 0. 001 (two-way ANOVA with Sidak's multiple comparaisons test for a-i; two-tailed Mann-Whitney test for j). Mean ± SEM. For detailed P values, see Source data. Source data are provided as a Source data file. See also Supplementary Fig. 8.
The common weighting factor of (1/3) was determined by the assumed equality of the maximum partial conductivities in the total conductivity: G TRPM5 ¼ G TRPM5;Na þ G TRPM5;K þ G TRPM5;Cs; G TRPM5;Na ¼ G TRPM5;K ¼ G TRPM5;Cs ¼ G TRPM5 =3: With the given E Na and E K, the value E TRPM5 = 0 mV was provided by setting E Cs = 40 mV. Correspondingly, specific components of the total J TRPM5 current were J TRPM5,Na = (1/3)•G TRPM5 •(E -E Na ), J TRPM5,K = (1/3)•G TRPM5 •(E -E K ), J TRPM5,Cs = (1/3)•G TRPM5 •(E -E Cs ). Data quantification. Electrophysiological data analyses were analyzed off-line with the Clampfit 10. 7 software (Molecular Devices). For intracellular recordings, several basic criteria were set to ensure optimum quality of intracellular recordings. Only cells exhibiting a stable resting membrane potential, access resistance (no >20% variation), and an action potential amplitude >40 mV under normal aCSF were considered.
We computed responses at each interpulse interval. Behavioral analyses. For walking, the CatWalkXT software (Noldus Information Technology, Netherlands) was used to measure a broad number of spatial and temporal gait parameters in several categories. These include (i) dynamic parameters related to individual paw prints, such as duration of the step cycle with the respective duration of the swing and stance phases; (ii) parameters related to the position of paw prints with respect to each other, for example, the stride length (distance between two consecutive placement of the same paw) and the base of support (the width between the paw pairs); (iii) parameters related to time-based relationships between paw pairs, as well as step patterns. These parameters were calculated for each run and for each paw.
Statistics. No statistical method was used to predetermine sample size. Group measurements were expressed as mean ± SEM. When two groups (control vs transgenic mice) were compared, we used the unpaired Mann-Whitney test. Fisher test was used to compare the percentages of bistability. When two conditions (control vs drugs) were compared, we used Wilcoxon matched pairs test. We also used a one-way or two-way analysis of variance tests for multiple comparisons. For all statistical analyses, the data met the assumptions of the test and the variance between the statistically compared groups was similar. The level of significance was set at P < 0. 05. Statistical analyses were performed using the Graphpad Prism 7 software. They are indicated in the figure legends.
Acknowledgements We are grateful to  Dr Michael Caterina ,  Aziz Mocqrich ,  Dr Pierre Launay , and  Dr Robert F. Margolskee  for their generous gift of transgenic Trpv2 -/-, Trpv1-3 -/-, Trpm4 -/-, and Trpm5 -/-mice, respectively. We are grateful to  Geneviève Rougon  and  Nejada Dingu  for their critical reading of the manuscript,  Cécile Brocard  for extensive genotyping and technical advices in Western blotting, and  Anne Duhoux  for animal care. This research has received supported from  Agence National de la Recherche Scientifique (CalpaSCI ,  ANR-16-CE16-0004  to F. B. ; nEURo *AMU ,  ANR-17-EURE-0029  to B. D. ), the  French Institut pour la Recherche sur la Moelle épinière et l'Encéphale  (to F. B. ), and the  PRESTIGE program  ( PRESTIGE-2017-1-0006 ,  PCOFUND-GA-2013-609102  to R.
An important component of the HBM4EU project is the derivation of human biomonitoring guidance values (HBM-GVs) for priority substances identified in the HBM4EU prioritisation process at European level. HBM-GVs aim to improve chemical risk assessment or health impact assessment by comparing these benchmark values with measured data in biomonitoring programmes. Where the database is sufficient, HBM-GVs are derived for the general population and for occupationally exposed adults with the contribution of national and EU expertise. In this paper the derivation of HBM-GVs both for the general population and for workers are presented for cadmium  (Cd). Cd is a hazardous metal found naturally in the environment at low levels and as a contaminant in food. Cd was, but is decreasingly used as industrial material.
Methodology used for deriving HBM-GVs for Cd and its compounds In this paper, based on national and international recommendations, collected data on Cd were assessed to choose the relevant biomarkers, to identify the most sensitive critical effect and to select the key studies with the view of deriving HBM-GVs for the general population and workers. The consulted literature reveals, that effects of Cd exposure are mostly related to biomonitoring data, which provides a large database on a relationship between health effects and biomarkers levels of Cd.
Identification of a critical effect and selection of key studies A review of national and international derivations of internal TRV or internal critical values (used to calculate external TRV) was performed, as well as a bibliographic search on more recent or specific publications. Data collection was assessed to identify reliable information on possible critical effects and relevant studies (others than those described in the review of international or national recommendations for Cd exposure). The critical effect chosen from the adverse effects described in the literature (and based on national or EU organisation's evaluations) is the first adverse effect that occurs when the dose increases. The bibliographical research was conducted in the following databases until 2019: Medline, Scopus.
Overview of already existing toxicity reference values The epidemiological database on Cd allows for the derivation of HBM-GVs based on a relationship between human internal concentrations and health effects for both the general population and for workers. An overview of these existing internal values for U-Cd and B-Cd is detailed in tables below for the general population and for workers. These tables describe the selected critical effect, the POD and assessment factors applied to calculate the corresponding internal TRV.
GBP2 CAAX box increases targeting to F. novicida compared to GBP1 CAAX box GBP1 and GBP2 undergo a post-translational addition of a lipid prenyl group  (8). This prenylation is guided by a C terminal CAAX motif, which facilitates attachment of proteins to cell membranes (Table  1 ). Prenylation is required for GBP1 to target S. flexneri  (19) (20) (21)  and S. typhimurium,  (7, 19)  and for GBP-dependent inflammasome activity. ). These data reveal that prenylation is necessary for GBP1 and GBP2 targeting to F. novicida. Interestingly, the lipid moiety of GBP2 is a geranylgeranyl lipid that consists of a 20 carbon chain whereas GBP1 lipid moiety is a farnesyl, which is a shorter 15 carbon chain (Table  1 ). The type of prenylation is dictated by the sequence of the CAAX box  (8, 37). We thus wondered whether the difference in prenylation between GBP1 and 2 might play a role in bacteria targeting.
Permeabilization was done with in PBS-Triton 0. 1% for 10 min at RT. The samples were submerged in blocking buffer (5% BSA, 0. 1% Triton, 0. 02% NaN 3 in PBS) for 1 h at RT or 4°C O/N then stained with the appropriate antibodies, see Table  S3. DAPI (4′,6diamidino-2-phenylindole at 100 ng/ml, ThermoFischer Scientific) was used for DNA staining. Coverslips were mounted using Fluoromount G TM (Invitrogen) mounting medium. Images for statistical analysis were taken on a Nikon Eclipse Ts2R-FL inverted microscope. For representative images, the samples were imaged on a Zeiss LSM 800 confocal microscope or Zeiss Elyra 7 SIM/STORM microscope. ImageJ software was used for analysis. Phagosomal rupture assay. Quantification of vacuolar F. novicida escape was done using the βlactamase/CCF4 assay (Life Technologies)  (52).
ACKNOWLEDGMENTS We thank  D. Monack  ( Stanford University ) and  A. Cimarelli  ( CIRI ) for reagents. We acknowledge the contribution of  SFR Biosciences  ( UAR3444/CNRS ,  US8/Inserm ,  ENS de Lyon ,  UCBL ) flow cytometry and imaging facilities (especially  Elodie Chartre ). This project is supported by an  ANR  grant to TH ( Tulamibe ,  ANR-17-ASTR-0024-02 ). SVV is supported by a scholarship from  AID  ( AID 2019013 ) & Inserm.
Overall per-session averages are monitored and are documented as categorized deviations if they fall outside of the target range. In clinical trials, all pollen counts for each session are recorded and then archived as part of the study dataset. FRAUNHOFER: The concentration of allergen particles (pollen or allergen-lactose particles, in this case) is measured online using an LPC (LASAIR 550, PMT GmbH, Heimsheim, Germany) at a defined flow rate in six particle size classes (from 1 to 100 µm). The particle concentration is used as a surrogate marker of the allergen concentration, which is maintained in the pre-specified target range (±10%). Pollen grains can also be counted and inspected visually offline under the light microscope, after capture using two RISs. GA 2 LEN: A particle dispersal unit counts the number of particles or uses the line width and line density to calculate the dispersed amount.
b DNA binding of His-MBP-ZNF384 to the indicated biotinylated DNA substrated as measured by BLI. Quantified data are plotted on a timescale and normalized to His-MBP (control). c Schematic representation of full-length ZNF384 protein and its domains (C2H2, N-terminus, and Cterminus). d Live-cell imaging of the recruitment of the indicated GFP-ZNF384 proteins to DNA damage tracks generated by 365 nm UV-A laser microirradiationin BrdU-sensitized ZNF384 KO U2OS Flp-In/T-Rex cells. mCherry-NBS1, which was co-expressed with the GFP-ZNF384 proteins, served as a DNA damage marker. Representative images are shown. White triangles indicate irradiated regions. Scale bars: 10 µm (upper panel). Quantification of the data is shown as mean ± SEM from 30-40 cells (lower panel). e Quantification of FRAP measurements to assess the local dynamics of the indicated GFP-ZNF384 constructs.
12 cells per condition were analyzed. Boxplot limits correspond to the 25th and 75th percentiles and the center line in the box indicates the median value. The whiskers extend 1. 5 times the interquartile range. P values were calculated using an unpaired Student's t test, assuming unequal variances. f Live-cell imaging of the recruitment of the indicated GFP-ZNF384 proteins to DNA damage tracks generated by 405 nm laser micro-irradiation in Hoechst-sensitized ZNF384 KO U2OS Flp-In/T-Rex cells. White triangles and photoactivatable H2B-PTR, which were co-expressed with the indicated GFP-ZNF384 proteins, indicate irradiated regions. Representative images are shown. Scale bars 4 µm (left panel). Data are presented as mean values ± SEM. P values were calculated using an unpaired Student's t test, assuming unequal variances (right panel).
White triangles indicate irradiated regions. Quantification of the data is presented as the mean ± SD from >60 cells acquired in two independent experiments. Scale bar 5 μm. c Western blot analysis of ZNF384 expression in cells from (b). Tubulin is a loading control. d Representative images of RPE1-hTERT cells transfected with the indicated siRNAs, in which FRAP measurements were performed to assess the local turnover of GFP-Ku70 at the sites of DNA damage. DNA damage was induced in the region indicated with a dashed line. Subsequent FRAP was induced in a subarea within the DNA damage region, as indicated with an unbroken line. Images are pseudocolored according to the look-up table displayed on the right. Scale bar 4 μm. e Normalized FRAP curves from (d). f Association (k' on ) rates of GFP-Ku70 measured by FRAP after fitting of the curves from (e).
g Dissociation (k off) rates of GFP-Ku70 after fitting of the curves from (e). Data from (e-g) was collected from 15 cells per condition. Boxplot limits correspond to the 25th and 75th percentiles and the center line in the box indicates the median value from a representative of two independent replicates. Statistical significance was calculated using the unpaired Student's t test, assuming unequal variances. Source data are provided as a Source Data file. sensitive to treatment with PARPi (Supplementary Fig. 14B, C ), in contrast to HR-deficient cells depleted of BRCA1  49. Given that ZNF384 is critical for Ku70/Ku80 loading at DSBs and that loss of Ku70/Ku80 has been linked to increased DNA-end resection and HR levels  50, 51  , we assessed whether ZNF384 affects DNA-end resection. Cells depleted of ZNF384 did not show a significant difference in RPA foci number and foci intensity (Supplementary Fig.
75 oil-immersion objective. The growth medium was replaced by CO 2 -independent Leibovitz's L15 medium supplemented with 10% FCS and cells were kept at 37 °C. The laser output power was set to 72-80 to generate strictly localized sub-nuclear DNA damage. Cells were micro-irradiated (two iterations per pixel) within 5 min using Andor IQ software (version 3. 6). Following micro-irradiation, cells were incubated for the indicated timepoints at 37 °C in Leibovitz's L15 and subsequently fixed with 4% formaldehyde before immunostaining. Images of fixed samples were acquired on a Zeiss AxioImager M2 or D2 wide-field fluorescence microscope equipped with ×40, ×63, and ×100 PLAN APO (1. 4 NA) oilimmersion objectives (Zeiss), an HXP 120 metal-halide lamp used for excitation and the following filters: DAPI (excitation filter: 350/50 nm, dichroic mirror: 400 nm, emission filter: 460/50 nm), GFP/Alexa 488 (excitation filter: 470/40 nm, dichroic mirror: 495 nm, emission filter: 525/50 nm), mCherry (excitation filter: 560/40 nm, dichroic mirror: 585 nm, emission filter: 630/75 nm), Alexa 555 (excitation filter: 545/25 nm, dichroic mirror: 565 nm, emission filter: 605/70 nm), Alexa 647 (excitation filter: 640/30 nm, dichroic mirror: 660 nm, emission filter: 690/50 nm).
For PAR-3H experiments and ZNF384 recruitment experiments, images were collected every 5 s for 10 min. For ZNF384 and WWE recruitment with late PARP inhibitor treatment, Z-stacks (1-μm steps) of irradiated nuclei were collected every 30 s for 15 min. Image collection was paused 3 min post damage and olaparib was added to the imaging media to a final concentration of 30 μM. For protein recruitment analysis, a custom-made MATLAB (MathWorks) program R2014b (version 8. 4. 0. 150421) (available upon request). For reviewing purposes, the following link can be used: https://github. com/sehuet/Singh-image-processing was used to segment the site of damage (I d ) as determined by the photoactivated H2B area, the total nuclear fluorescence (I nd ), and an area of background outside of the cell (I bg ).
Wide-field 3D images were acquired using a Leica DMi8 microscope (×63/1. 4 NA) and deconvolved using Huygens Professional (version 19. 10). Confocal images of immunostained cells were captured using a Leica SP8-X SMD (×63/1. 4 NA). Proximity ligation assay (PLA). U2OS AsiSI-ER cells were seeded on 12-mm coverslips and after 24 h treated with 1 µM 4-hydroxytamoxifen (4-OHT, Sigma) for 5 h to induce DSBs. Subsequently, cells were fixed in 4% paraformaldehyde and permeabilized in 0. 5% TritonX-100. Primary antibodies rabbit anti-53BP1 (NOVUS Biologicals NB100-304), mouse anti-γH2AX (Millipore clone JBW301), and rabbit anti-ZNF384 (ATLAS antibodies HPA004051) were used to stain selected proteins. Proximity Ligation Assay was performed with Duolink In Situ PLA Probe Anti-Mouse Plus (Sigma) and Anti-Rabbit Minus (Sigma), and with Duolink In Situ Detection Reagents Orange (Sigma) according to the manufacturer's instructions.
Full-scan MS spectra were obtained with a resolution of 70,000, a target value of 3 × 10 6 , and a scan range from 400 to 2000 m/z. Maximum Injection Time (IT) was set to 50 ms. Higher-Collisional Dissociation (HCD) tandem mass spectra (MS/MS) were recorded with a resolution of 35,000, a maximum IT of 20 ms, a target value of 1 × 10 5 and a normalized collision energy of 25%. The precursor ion masses selected for MS/MS analysis were subsequently dynamically excluded from MS/MS analysis for 60 s. Precursor ions with a charge state of 1 and greater than 6 were excluded from triggering MS/MS events. Three replicates were included per condition with two technical repeats each. Mass-spectrometry data analysis. Raw mass-spectrometry files were analyzed with MaxQuant software (v1. 5. 5. 1) as described  75  with the following modifications from default settings: the maximum number of mis-cleavages by trypsin/p was set to 3, label-free quantification (LFQ) was enabled disabling the Fast LFQ feature.
The Match-between-runs feature was enabled with a match time window of 0. 7 min and an alignment time window of 20 min. We performed the search against an in silico digested UniProt reference proteome for Homo sapiens (June 8, 2020). Analysis output from MaxQuant was further processed in the Perseus computational platform (version 1. 5. 5. 3)  75. Proteins identified as common contaminants, only identified by site and reverse peptide, were filtered out, and then all the LFQ intensities were log2 transformed. Different biological repeats of each condition were grouped and only protein groups identified in all three biological replicates in at least one condition were included for further analysis. Missing values were imputed using Perseus software by normally distributed values with a 1. 8 downshift (log2) and a randomized 0.
Membranes were scanned and analyzed using an Odyssey Infrared Imaging System (Licor; V3. 0) and Image Studio Lite (version 5. 2). Uncropped blots are provided in the source data file. Chromatin fractionation. Chromatin fractionation was performed using a previously published protocol  76  with few modifications. Briefly, 100. 000-150. 000 cells were grown per 6-cm dish for 24 h and then transfected with siRNAs. Next, the cells were treated with 500 µM phleomycin for 1 h, washed three times with PBS, and incubated in NETN extraction buffer (100 mM NaCl, 1 mM EDTA, 20 mM Tris-Cl pH 8, 0. 5% NP-40 + proteasome inhibitors). After 15 min of incubation on ice, samples were taken for the chromatin-unbound fraction and mixed with the same amount of 2× Laemmli buffer. Cells were washed with PBS, lysed, and incubated in Laemmli buffer with benzonase for 15 min to obtain the chromatin-bound fraction.
Then, 400 nM of purified MBP or the different MBP-tagged ZNF384 proteins was used to measure the association of the analyte. The resulting data were processed using the ForteBio Data Analysis software (version 7. 1. 0. 38). Quantitative fluorescence in situ hybridization (FISH) of telomeres. Telomere FISH was based on a previously published protocol  57. Briefly, HCT116 cells were harvested following 2 h of colcemid (Sigma) incubation. After hypotonic swelling, cells were fixed in methanol/acetic acid, dropped on slides, and dried at 37 °C overnight. The next day slides were treated with RNaseA (R4642; Sigma), pepsin (P7000; Sigma) at pH 2, followed by formaldehyde fixation, washes in PBS, dehydration in ethanol, and air drying. Hybridization mixture containing 70% formamide, 0. 3 μg/ml Cy3-conjugated (C3TA2)3 peptide nucleic acid (PNA) probe in 10 mM Tris (pH 7.
Acknowledgements We thank  Robin van Schendel  and  Marcel Tijsterman  for the custom Sanger Sequence analyzer and help with the sequence analysis, and  Dik van Gent ,  Stephen Taylor ,  Geert Kopps ,  Bernard Lopez ,  Roger Greenberg ,  Maria Jasin ,  Jeremy Stark ,  Nicholas Lakin ,  Sylvia Gelpke-Vermeulen , and  Karoly Szuhai  for kindly providing valuable reagents. We also thank the  Microscopy-Rennes Imaging Center (BIOSIT, Université Rennes 1) , a member of the national infrastructure  France-BioImaging  supported by the  French National Research Agency  ( ANR-10-INBS-04 ), for providing access to their imaging setups, as well as  S. Dutertre  and  X. Pinson  for technical assistance with the microscopes. This research was financially supported by the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  ( ERC-StG 310913  to A.
Data availability The data that support this work are available from the corresponding author upon reasonable request. The mass-spectrometry proteomics data generated in this study and shown in Fig. 1d  and Supplementary Table  1  have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (https://www. ebi. ac. uk/ pride/)  77. Access can be obtained with the dataset identifier PDX020417. In addition, publicly available reference datasets for Homo sapiens (June 8, 2020) were used to search against an in Silico-digested UniProt reference proteome. Source data are provided with this paper.
Few studies have explored the relationship between OAC discontinuation and clinical outcomes. In this report, the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) collects starting and finishing dates of treatment which, unlike other databases, gives precise data regarding timing of treatment relative to outcomes. We assessed risk factors for discontinuing oral anticoagulants and its impact on clinical outcomes among 23,882 AF patients who were prescribed either VKA or DOACs for stroke prevention at the time of enrolment into GARFIELD-AF. All patients had a recent newly diagnosed AF and were followed prospectively for 2 years.
Methods The design of the GARFIELD-AF registry has been reported previously  [16]. In total, 52,014 patients of ≥18 years with non-valvular AF (diagnosed within the previous 6 weeks), and at least one non pre-specified risk factor for stroke (judged by the local investigator) were eligible for inclusion  [16]. Patients were enrolled prospectively from representative centres in 35 countries between May 2013 and August 2016. Intended minimum follow-up was 2 years  [16]. All followup beyond 2 years was truncated at 24-months. Data for this report were extracted from the study database on June 2019. This analysis involved patients with OAC usage from cohorts 3-5 only, because the exact treatment start and stop dates were recorded from cohort 3 onwards.
Procedures and outcome measures Collection of follow-up data occurred at 4-monthly intervals up to 24-months  [16]. In accordance with the study protocol, 20% of all electronic case report forms were monitored against source documentation  [17]. Timing of treatment is based upon the date treatment was started and the date treatment was discontinued. Changes in treatment type were recorded. Defining discontinuation based solely on stopping and never restarting a drug in a study where patients die or stop follow-up at different points will likely produce biased results. For example, Patient A stops drug and dies two days later. Patient B stops drug and restarts 3 days later. Patient A would be defined as discontinued and B would not. Yet at day 2, the day of the event, they were both off drug.
Many of these studies were retrospective in design, with small cohorts of patients, often from insurance or pharmacy databases  [20, 21, 23, 24]. We found that the rate of OAC discontinuation (VKAs and DOACs) was 13. 0%, with a median follow-up after discontinuation (number of days to death or last follow-up) of 511 days (IQR 291-648). Treatment persistence was achieved in 82% of patients by 1 year of follow-up and 79% by 2 years. Patients who discontinued OAC had differing demographic, geographical and clinical characteristics and experienced adverse outcomes more frequently. Type of OAC did not impact patient outcomes. Discontinuation rates of patients in GARFIELD-AF were lower compared to other registry studies and randomized trials  [5, [11] [12] [13] , although in line with rates found in the recent ORBIT II registry  [14].