dataesr/scientific-paragraphs-categorization huggingface dataset:
ACAD9 has structural features unique among the ACAD family The comparison of our ACAD9 S191A structure with both the VLCADbased ACAD9 homology model  7  and a very recently published VLCAD crystal structure (PDB:7S7G  19  ) revealed a high structural similarity, with RMSD values of 1. 16 Å and 1. 11 Å, respectively (Fig. 4A ). A visualisation of the evolutionary conserved residues also reveals that the dehydrogenase domains are quite conserved within the ACAD family  20  (Fig. 4B ). Intriguingly, and in agreement with previous studies  7, 12  , ACAD9 is the only ACAD family member capable of binding ECSIT and assisting CI assembly (Supplementary Fig. 2A ), whereas VLCAD does not fulfil these functions  12. Thus, given that the ECSIT binding induces the flipping of the gatekeeper loop, we generated ACAD9 point mutants intended to mimic the VLCAD sequence on this loop and analysed them by DLS and mass photometry.
Experiments were repeated thrice with similar results. E DLS measurements of ACAD9 mutants designed to mimic the VLCAD loop. The ACAD9 A184S mutant exhibits similar behaviour to ACAD9 WT. The double mutant ACAD9 SR194TS is destabilised, although the effect was less profound in complex with ECSIT CTER ; some complex is formed but at higher MW than ACAD9 WT -ECSIT CTER. In contrast, the double mutant ACAD9 A184S/SR194TS shows no change in MW before and after reconstitution with ECSIT CTER , however, we can attribute this to a reduction in protein stability while retaining the ability to bind ECSIT CTER. Blue and red dashed lines indicate the expected MW for ACAD9 WT homodimer and ACAD9 WT -ECSIT CTER complex, respectively. Data are presented as mean values ± SD of at least n = 3 biological replicas.
F Acyl-CoA dehydrogenase (ACAD) activity of ACAD9 WT , ACAD9 mutants, and VLCAD determined by an ETF fluorescence reduction assay. After addition of the ACAD specific substrate palmitoyl-CoA (C16:0), there is a clear loss of ETF fluorescence in ACAD9 WT , ACAD9 A184S and VLCAD in comparison to the other ACAD9 mutants, over 300 s of reaction measurement. Data are presented as box-whisker plots with median quartiles and from minimum to maximum values, at least n = 3 biological replicas. Statistical significance was calculated with an RM-one way ANOVA with Dunnett's multiple comparisons test relative to ACAD9. p values are indicated (non-significant p = 0. 8508, p = 0. 3179; ****p ≤ 0. 0001). Source data are provided as a Source Data file. outward  19. This extended loop mediates trans interactions with the equivalent loop of another symmetry related VLCAD molecule (Supplementary Fig.
Experiments were repeated thrice with similar results. E DLS measurements of ACAD9 WT , ACAD9 VLCAD and VLCAD ACAD9 show similar behaviour. However, in the case of ACAD9 VLCAD , there is a significant reduction in complex formation in comparison to ACAD WT -ECSIT CTER , implying that this mutation does indeed evoke VLCAD-like tendencies. The reverse is also true in the case of VLCAD ACAD9 , a large average MW is seen, indicating the formation of a VLCAD ACAD9 -ECSIT CTER complex. This indicates that VLCAD ACAD9 behaves less like VLCAD WT and more like ACAD9 WT through the mutation of these key residues. Blue and red dashed lines indicate the expected MW for ACAD9 homodimer and ACAD9 WT -ECSIT CTER complex, respectively. Data are presented as mean values ± SD of at least n = 3 biological replicas.
6B ). Analysis of the faster migrating band by proteolytic in-gel digestion mass spectrometry revealed that ECSIT CTER was multiphosphorylated (Supplementary Data 2). We were able to identify nine high-confidence Threonine/Serine phosphorylation sites, including a kinase recognition sequence TSS motif (res. 401-403)  24  (Fig. 6C ). Excitingly, one of the identified potential phosphorylation sites was Thr320, which resides within the ECSIT sequence visible in our ACAD9 WT -ECSIT CTER structure (Fig. 6C ). Thr320 forms hydrogen bonds with Gln331, stabilising the helical sequence that enters into the ACAD9 binding cavity. We therefore constructed an ECSIT CTER phosphomimetic mutant where Thr320 was replaced by a Glutamate (T320E). Remarkably, this mutant exhibited a significantly reduced binding affinity for ACAD9 (Fig.
6D  and Supplementary Fig. 10A ), suggesting that the phosphorylation of Thr320 may negatively regulate ACAD9 binding. We next sought to examine the potential ECSIT CTER phosphorylation sites in vivo. To this end, we treated ECSIT CTER with an endogenous kinase pool from human neuronal cells (Fig. 6E, F ). We observed strong 32 P-radiolabelling of ECSIT CTER , providing evidence that ECSIT undergoes phosphorylation ex cellulo. Subsequent analyses by proteolytic in-gel digestion mass spectrometry confirmed that ECSIT CTER was multiphosphorylated (Fig. 6G ), and identified six highconfidence Threonine/Serine sites, including five already detected in vitro: Ser269, Thr320, the TSS motif and the C-terminal residue Ser431 (Fig. 6C , G and Supplementary Data 3).
Bottom, NADH-dehydrogenase activity assays of CI in WT (green) and APP (red) cells at different concentrations (0. 5, 0. 1, and 0. 01 mg/ml, respectively). Data are presented as mean values ± SD of n = 3 biological replicas. Statistical significance was calculated with two-way ANOVA followed by Sidak's multiple comparison. Significant p < 0. 0001. n. s. non-significant. F Cell extracts from H4 cells, both WT and APP, incubated with ECSIT CTER confirmed the phosphorylation of ECSIT CTER ex cellulo by a kinase pool. G Quantitative mapping of the ECSIT CTER phosphopeptides indicate a decreased phosphorylation level under amyloidogenic conditions, with Thr320 (in green) displaying the highest differential level. Data are presented as normalised values and median of n = 2 biological replicas. Source data are provided as a Source Data file and in Supplementary Data 2 and 3.
Cryo-EM data collection Grids were pre-screened on a Glacios microscope (Thermo Scientific) of the EM platform of the Institute of Structural Biology (IBS), Grenoble, France. Datasets were collected at the European Synchrotron Radiation Facility CM01, on a Titan Krios microscope (Thermo Scientific) operating at 300 kV with a Quantum energy filter (slit width 20 eV)  35. The ACAD9 WT -ECSIT CTER and ACAD9 WT data sets were recorded at zero degrees stage tilt on a K2 summit direct electron detector (Gatan) running in counting mode, at a magnification of ×165,000, corresponding to a pixel size of 0. 827 Å/pixel at the specimen level. The ACAD9 S191A data set was recorded at a 35°stage tilt, on a K3 direct electron detector (Gatan) operating in super-resolution mode, at a magnification of ×105,000, with a sampling pixel size of 0.
Model building and refinement To build a model of ACAD9 WT -ECSIT CTER , a homology model of ACAD9 dimer based on the human very long-chain Acyl-CoA dehydrogenase (VLCAD, PDB:3b96), was used as the initial structure  7. AF2 models were not available at the time. In this model, each ACAD9 protomer contains residues 38-621 and binds one FAD molecule (a total of two FADs in the ACAD9 dimer). The homology model was rigid-body fitted into the 3D reconstruction of ACAD9 WT -ECSIT CTER using ChimeraX 1. 2  37. A first round of real space refinement was conducted enabling rigid body, global minimisation, local grid search and atomic displacement parameter (ADP) refinement parameters; rotamer Ramachandran, noncrystallographic symmetry (NCS) and reference model (VLCAD-based homology model) restraints were also imposed.
AlphaFold modelling Structures of ACAD9 (human, residues 1-621, monomer) and ECSIT (human, residues 1-431) were available in the AlphaFold Protein Structure Database (AF2 v2. 2. 4)  17, 30. The PDB files were downloaded and compared to the structures produced from experimental data. For the structural comparison of ECSIT model (residues 320-334) built based on the cryo-EM map, the AF2 ECSIT model was cropped to match the sequence of our construct without the addition of His-Tags. The structures were aligned and RMSD values generated using Chi-meraX 1. 2  37. AlphaFold modelling of the ACAD9-ECSIT subcomplex was conducted using ColabFold (v1. 3. 0) prediction tools  42. The protein sequences for ACAD9 (human) and ECSIT (human) were taken from UniPROT  43  and modified to match the constructs used in our experiments: ACAD9 contained residues 38-621 and ECSIT contained residues 221-431.
Mass spectrometry data processing The raw mass spectrometry data was processed with MaxQuant (v1. 6. 17. 0)  47  and searched against the Uniprot-proteome UP000000625 database (E. coli, 4450 entries, May 2022, ECSIT in vitro experiment) or the Uniprot-proteome UP000005640 database (homo sapiens, 20603 entries, May 2022, ECSIT ex cellulo experiment) containing each the sequence of the protein of interest and common contaminants. The data was searched with the following modifications: Carbamidomethyl (C) as fixed modification, acetylation (Protein Nterm), oxidation (M) and phosphorylation (STY) as variable modifications. The default mass error tolerance for the full scan MS spectra (20 ppm) and for MS/MS spectra (0. 5 Da) was used. A maximum number of 3 missed cleavages was allowed. For protein identification, a minimum of 2 unique peptides with a peptide length of at least seven amino acids and a false discovery rate below 0.
Acknowledgements We are grateful to  Dr. C. Mas  ( IBSG Grenoble ) for support with ITC and mass photometry. We thank  Dr. G. Leonard  ( ESRF ),  Dr. S. Bohic  ( ESRF, INSERM ) and  Dr. C. Petosa  ( IBS Grenoble ) for discussions. We thank  Dr. N. Burgess-Brown  ( Oxford University ) for the VLCAD plasmid and  Dr. P. Aloy  ( IRB Barcelona ) for H4 cell lines. We are grateful to  Dr. G. Schoehn  for establishing and managing the IBS cryo-electron microscopy platform, and to  Dr. E. Zarkadas  for assistance at the Glacios microscope. This work used the  EMBL Proteomics Core Facility  and the platforms of the Grenoble Instruct Center (ISBG; UMS 3518  CNRS-CEA-UJF-EMBL ) with support from  FRISBI  ( ANR-10-INSB-05-02 ) and  GRAL  ( ANR-10-LABX-49-01 ) within the  Grenoble Partnership for   Structural Biology  (PSB).
Data availability The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository  49  with the dataset identifiers PXD042858 (in vitro experiment) and PXD042905 (ECSIT experiment with cell extracts). The cryo-EM maps have been deposited in the Electron Microscopy Data Bank (EMDB) under accession codes EMD-17659 (ACAD9-WT in complex with ECSIT-CTER); EMD-17660 (Cryo-EM structure of human ACAD9-S191A); and EMD-17661 (ACAD9 homodimer WT). The atomic coordinates have been deposited in the Protein Data Bank (PDB) under accession codes PDB 8PHE (ACAD9-WT in complex with ECSIT-CTER) and PDB 8PHF (Cryo-EM structure of human ACAD9-S191A). Additional atomic coordinates referred to within this paper are in the PDB under the accession codes 7S7G (Crystal Structure Analysis of Human VLCAD) and 3B96 (Structural Basis for Substrate Fatty-Acyl Chain Specificity: Crystal Structure of Human Very-Long-Chain Acyl-CoA Dehydrogenase).
en Biologie Sante et Agronomie (IBISA). We acknowledge the ESRF for provision of beam time on CM01. The ESRF in-house Research Program supported this work. The EM work was funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 647784 to I. G. This work was partially funded by the Agence Nationale de la Recherche (ANR) MitoCompAs (ANR-22-CE11-0031) program to I. G. and M. S. -L.
Source data are provided as a Source Data file. minimize Coulomb effects ("Methods" section). The two other QPCs controlled by uncolored metallic split gates are only used for characterization purposes and to establish the generic (QPC independent) character of our observations ("Methods" section). Indeed, in contrast with the small quantum dot implementation of the Kondo model  35, 36  , multiple connected channels would compete to screen the charge Kondo pseudospin  27, 28, 31, 32  , a phenomenon with profound consequences described by another model referred to as multi-channel Kondo  [1] [2] [3] 37. For the data shown in the main manuscript, the path across each of these two other QPCs is disconnected. The island's charge sensor consists in an additional QPC whose conductance G sens changes by capacitive coupling with the electrical potential of the island.
Electronic temperature The electronic temperature T is obtained from on-chip thermal noise measured on an ohmic contact. The conversion factor is calibrated from the linear slope of thermal noise vs temperature of the mixing chamber, at sufficiently high temperature where the difference between electron and mixing chamber temperatures is negligible. In practice, the calibration is performed above 40 mK where the high linearity of noise vs temperature attests of the good thermal anchoring of the electrons (here, differences between in-situ electronic temperature T and readings of RuO 2 thermometers fixed to the mixing chamber develop essentially below 20 mK). The data displayed in the main manuscript are obtained at T = {9. 4 ± 0. 3, 14. 4 ± 0. 1, 21. 6 ± 0. 2, 30. 4 ± 0. 1, 46. 2 ± 0. 1, 68.
Statistical and geographical analysis To guarantee the patients' anonymity, a specific module was implemented in the questionnaires; the ArcGIS Survey 123 (Version 3. 17. 54) from the Esri company. This module allows the calculation of the doorto-door travel times between the place of residence or the workplace, to the community or hospital pharmacy, without saving the exact postal address of the patients, nor the pharmacy's address. The only data saved in the database was the calculated door-to-door travel time in minutes, based on the average traffic. Although we collected the number of patients per household, we did not calculate travel time per household since only five respondents belonged to the same household. It is therefore assumed that all respondents of this survey are statistically independent individuals.
The collected data included the preferred place from which to travel to the pharmacy; the place of residence, the workplace or other place. When respondents specified their preferred place, they also provided the estimated door-to-door travel time in minutes. In some cases, respondents also provided an estimation of the travel time from their non-preferred place. respondents, the posology was a priori calculated following the recommendations of the European Medicines Agency. 17  We deduced the dose (mg/kg) according to the injection rhythm; 1. 5 mg/kg for one injection weekly, 3 mg/kg for one injection fortnightly and 6 mg/kg for one injection monthly. Baseline characteristics were described by counts and percentages for categorical variables, medians and interquartile range for continuous variables, mentioned in brackets in the following order in the results section; community and then hospital pharmacy.
ACKNOWLEDGEMENTS The authors thank the scientific committee of the  PASO DOBLE DEMI  study;  Béatrice Clairaz  (Community pharmacist, co-president of the  French society of pharmaceutical sciences ,  Société Francophone des Sciences Pharmaceutiques Officinales, SFSPO) ,  Yesim Dargaud  (French reference centre for haemophilia, Lyon),  Félicia Ferrera  (cochair of the  Provence-Alpes-Cote-d'Azur Unions  for health professionals ( Société Française de Pharmacie Clinique, SFPC), Marseille ),  Nicolas Giraud  (President of the  French haemophilia association ,  Association Française des Hémophiles, AFH ),  Rémi Varin  ( Hospital pharmacist, Rouen ),  Fabienne Volot  ( Expert Centre Coordinator, Dijon ). The authors thank the team from  Roche  team the follow-up of the project ( Loïc Bergougnoux ,  Aurélie de Lehvenfehlt ).
3 The coherency of our cross-country uncertainty measures bases on the assumption that statistical agencies are equally able to acquire information. Note also that in constructing coherent macroeconomic variables statistical agencies take into account a plethora of series that include a huge amount of sensitive data partly only available to the statistical agency. 4 Thus, in contrast to the bottom-up approach of, e. g. ,  Jurado et al. (2015) , we follow a top-down approach, where we partly outsource the information acquisition to the statistical agency. We apply our procedure to a post WWII real-time dataset collected for 39 countries, deriving an international set of estimates of macroeconomic uncertainty. For the U. S. , our measure pinpoints periods of highest uncertainty during the mid-1970s, beginning of 1980s, beginning of 2000s, and during the recent great financial crisis, which is qualitatively consistent with other measures of U.
In a second step, we use our newly created international set of uncertainty indicators to investigate the role of labor adjustment costs in transmitting uncertainty shocks. We subdivide the countries into high employment protection legislation (EPL) countries and low employment protection legislation countries using the OECD Employment Protection Database. In an 8-variable VAR analysis that uses data from 1988Q1 to 2019Q4, we find that the degree of labor protection plays a crucial role in the propagation of uncertainty shocks. Uncertainty shocks affect the economy in countries with stricter employment protection legislation less than in countries with low labor protection standards. To learn more about the role played by EPL in the propagation mechanism of uncertainty shocks, we employ the theoretical model of  Bloom et al.
Data revisions can thus directly affect the uncertainty measures derived from survey of professional forecasters, whereas the uncertainty indicator estimated by our procedure takes these data revisions into account. Moreover, uncertainty estimates from survey of professional forecasters are restricted to a few countries and cannot be applied to a broad-based international setting, which is the focus of this paper. Uncertainty indicators based on surveys of professional forecasters have also their merits. For example, the amount of information used by professional forecasters for predicting GDP probably exceeds that of the single variable 3 Statistical agencies in OECD countries follow similar national accounting standards. The data provided by the OECD database is based on the 2008 System of National Account.
Real-time data We use data revisions of real GDP growth for 39 countries to construct the uncertainty indicators. Particularly, we use the first year-over-year growth rate of real GDP as a forecast for the final year-over-year growth rate of real GDP that we define as the growth rate published after three years ( = 12). 16 In order to obtain a comprehensive data set for various countries, we need to tap and combine several data sources. The largest part of our data is provided by the Original Release Data and Revisions Database. The Original Release Data and Revisions Database is part of OECD Main Economic Indicators database (OECD, 2017) and represents the central data source of this project. The database provides different releases of macroeconomic aggregates for many countries. This study uses data from 39 countries.
The authors assemble the dataset from original quarterly releases of different macroeconomic aggregates from 1962 to 1998 that is directly compatible with the Original Release Data and Revisions Database. We currently use these data for all countries except the U. S. , Germany, Italy, Australia and New Zealand. For the U. S. , we use data provided by the Federal Reserve of Philadelphia as they provide more exhaustive data compared to the data provided by Federal Reserve of Dallas. For Germany we rely on data provided by Boysen-Hogrefe and Neuwirth (  2012 ) and for Australia we use data provided by the Australian Real-Time Macroeconomic Database  (Lee et al. , 2012). For New Zealand we use data provided by the Reserve Bank of New Zealand  (Sleeman, 2006)  and for Italy, we also use data releases of ISTAT that were kindly provided by  Golinelli and Parigi (2008).
Estimates of macroeconomic uncertainty Using the econometric framework outlined in Section 3 and the real-time dataset described in Section 4, we obtain estimates of macroeconomic uncertainty for 39 countries. 19 We now present and discuss the resulting uncertainty measures. Thereby, we focus on uncertainty in the United States and global uncertainty. Our methodical framework provides macroeconomic uncertainty estimates for the United States that are similar to existing uncertainty measures. Fig. 2  presents our revision-based uncertainty measure for the U. S. (blue solid line) and compares it to existing proxies found in the literature. These alternative measures include the macroeconomic uncertainty indicator proposed by  Jurado et al. (2015)  (green solid line), the economic policy uncertainty index developed by  Baker et al.
17 Appendix B describes these various data sources and outlines the construction of our data base in more detail. We will provide the final real-time dataset as well as the code to construct it upon request. 18 See Fig. 9  in Appendix B for a better overview of average revisions. 19 We provide all uncertainty indicators on our personal websites. A. Dibiasi   all-time-high level of economic policy uncertainty. However, the economic policy uncertainty does not translate into macroeconomic uncertainty as both the revision based indicator as well as JLN return to very low levels after the recession. Although we obtain uncertainty estimates for 39 countries, for the sake of brevity, we abstain from discussing all countries in the main text and refer the reader to Appendix C for a presentation of all uncertainty indicators.
In order to study the role of EPL the propagation of uncertainty shocks we calibrate, solve and simulate the model of  Bloom et al. (2018)  twice, once for an economy for low EPL and once for an economy with high EPL. In order to ensure comparability A. Dibiasi and S. Sarferaz   (Bloom et al. , 2018). with  Bloom et al. (2018)  and the RBC literature in general, we do not change the calibration proposed by  Bloom et al. (2018) , except for the firing cost parameter. For the United States,  Bloom et al. (2018)  assume firing costs to be on average 1. 8% of an annual wage bill. For continental European economies -countries that according to the OECD Employment Protection Database have on average stricter EPL -studies report substantially higher firing costs  (Grund, 2006; Kramarz and Michaud, 2010).
Evidence from a VAR Now, we use the international set of revision based measures of uncertainty to test this theoretical prediction. We thus split countries into two groups according to their strictness of employment protection. 31 To split countries according to their degree of employment protection, we use the annual time series data of the OECD Employment Protection Database to calculate the average value of the strictness of employment protection. Specifically, we use the measure of individual and collective dismissals (EPRC_V1) from 1985 to 2013. Table  3  ranks countries according to the strictness of employment protection. The groups selected in Table  3  mirror our expectations with Anglo-Saxon economies displaying a low degree and continental European countries showing a higher degree of employment protection standards.