dataesr/scientific-paragraphs-categorization huggingface dataset:
The results were analysed in the realplex software version 2. 2 (Eppendorf ® ), where the threshold cycle (C T ) values were determined. The ACT1 and MAC1 genes were used as calibrator and gene control respectively [using the primers ACT1-F and ACT1-R or MAC1_F_qPCR and MAC1_R_qPCR, respectively (Supplementary Data 2)]. The relative gene expression (n-fold, for the clinical isolates as compared with the reference strain SC5314) for the following genes: RME1 (RME1_F_qPCR and RME1_R_qPCR), PGA55 (PGA55_F_qPCR and PGA55_R_qPCR), CSP1 (CSP1_F_qPCR and CSP1_R_qPCR), CSP2 (CSP2_F_qPCR and CSP2_R_qPCR) and ORF19. 654 (ORF19. 654_F_qPCR and ORF19. 654_R_qPCR) was validated by using the 2 -ΔΔCT method, in the following manner: ΔC T = C T (selected gene)-C T (ACT1 calibrator gene) calculated for both reference strain (SC5314) and clinical isolates, and ΔΔC T = ΔC T (clinical isolates)-ΔC T (reference strain).
Similarly, relative gene expression levels of SFL1 (SFL1_F_qPCR and SFL1_R_qPCR) and NRG1 (NRG1_F_qPCR and NRG1_R_qPCR) were measured in strains SC5314, CEC3620, CEC2018, CEC1424 and CEC1426. For all strains, three technical replicates were performed for three biological replicates. Data were expressed as the mean ± SD. Differences were analysed by the two-tailed Student's t-test, a P value < 0. 05 was considered as statistically significant. Autoregulation assay. The C. albicans rme1ΔΔ knockout mutant and WT strains expressing both P TET -RME1 and the CSP1-GFP fusion were incubated overnight in YPD liquid medium at 30 °C, then diluted to an OD 600 of 0. 2 in 25 mL of YPD liquid medium supplemented with 40 μg/mL doxycycline and grown for 3 h at 30 °C. Cells were harvested by centrifugation, washed with water and resuspended in fresh YPD liquid medium without doxycycline and incubated during 21 h at 30 °C.
Phylogenetic analyses. The alignment was done using MUSCLE v3. 8. 311  69  with default parameters. The software trimAl v32  70  was then used to trim the alignments generated by MUSCLE, with-automated1 option (implements a heuristic to decide the most appropriate mode depending on the alignment characteristics). We then used ProTest v2. 43  71  to choose the best protein substitution models for each alignment, namely JTT + I + G + F. A maximum likelihood analysis was conducted with PHYML v3. 0. 14  72  to reconstruct phylogenetic trees; support for the branches were determined from bootstrap analysis of 100 resampled datasets. Mating experiments. Opaque cells were obtained from arg-and his-rme1 KO mutants (CEC5914 and CEC5917, respectively) as well as CEC5919 and CEC5921, arg-and his-derivatives of the reference strain SN76, respectively, by plating on Lsorbose  73.
Acknowledgements This research was supported by grants from the  Agence Nationale de la Recherche  ( KANJI ,  ANR-08-MIE-033-01  to C. d. E. and F. D. ; CANDIHUB,  ANR-14-CE-0018  to C. d. E. ;  IBEID ,  ANR-10-LABX-62-IBEID  to C. d. E. ), the  European Commission (FIN-SysB ,  PITN-GA-2008-214004  to C. d. E. ) and the  French Government 's  Investissement d'Avenir program  ( Institut de Recherche Technologique BIOASTER ,  ANR-10-AIRT-03  to C. d. E. and F. D. ). S. Z. is an  Institut Pasteur International Network Affiliate Program Fellow. S. Z. , L. v. W. and A. H. C. were the recipients of post-doctoral fellowships from the  European Commission (FINSysB ,  PITN-GA-2008-214004  to SZ), the  Agence Nationale de la Recherche  ( KANJI ,  ANR-08-MIE-033-01  to S. Z. ;  ERA-Net Infect-ERA, FUN-COMPATH ,  ANR-14-IFEC-0004  to A.
H. C. ; CANDIHUB,  ANR-14-CE-0018  to L. v. W. ), the  French Government 's  Investissement d'Avenir program  ( Institut de Recherche Technologique BIOASTER ,  ANR-10-AIRT-03  to S. Z. and A. H. C. ) from the  National Council of Science and Technology, Mexico  to A. H. C. V. B. was supported by a grant from the  Pasteur-Paris University (PPU)   International PhD program  and the " Fondation Daniel et Nina Carasso ", ID belongs to the  Pasteur-Paris University (PPU) International PhD program , which has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie  grant agreement No  665807 , and from the  Institut Carnot Pasteur Microbes & Santé.
2000; Markov et al. 2014a ). This pattern allowed us to estimate the hierarchy of 40 areas in macaque cortex  (Barone et al. 2000; Markov et al. 2014a )  (Fig 1D ii). This expands previous estimates of the hierarchy based on 29 or 30 areas from the same database  (Markov et al. 2014a; Mejias et al. 2016). We divided the D1 receptor density by the neuron density  (Collins et al. 2010).
A large-scale model of macaque cortex incorporating multiple macroscopic gradients We then built a large-scale model of macaque cortex where the local circuit  (Fig 2A, left)  acted as a building block. We placed the local circuit in each of 40 cortical areas across macaque cortex  (Fig 2A, right). However, these local circuits varied across areas in three key properties, namely long-distance connectivity, strength of excitation and modulation by D1 receptors. We defined the connections between areas using quantitative retrograde tract-tracing data  (Markov et al. 2014b). This data was collected in the same lab under the same conditions for injections into 40 distinct cortical areas. This offers high fidelity reconstruction of the weighted and directed connections between neurons in large sections of macaque cortex  (Kennedy et al.
In simulations, stimulus-selective activity propagated from visual cortex to temporal, parietal and frontal cortex. Activity in visual cortex was relatively insensitive to dopamine (Fig 2E  , F ). In all cases, there was a strong transient response in visual areas, before a quick return to baseline firing rates, like V1 neurons recorded from behaving monkeys (Vugt et al. Long-range connectivity determines the distributed working memory activity pattern The pattern of areas showing working memory activity in the model closely matches the areas in which persistent activity has been seen experimentally during working memory tasks. Leavitt and colleagues collated data from over 90 studies recording single-unit and multi-unit activity as monkeys performed delay tasks  (Leavitt et al. 2017). For each studied area, they quantified the number of studies in which persistent activity was observed or not observed during the delay period of the task.
Neuronal density data The in-vitro autoradiography data accurately quantifies the density of receptors across cortex. However, it is important to bear in mind that the density of neurons also varies across the cortex. Collins and colleagues measured the density of neurons across the entire macaque cortex using the isotropic fractionator (a. k. a. brain soup) method  (Collins et al. 2010). After mapping the neuron density data from the study by  Collins et al. 2010  and the receptor data to a common atlas, we divided the receptor density by the neuron density, to obtain an estimate of D1 receptors per neuron in each cortical area.
Retrograde tract-tracing The inter-areal connectivity data in this paper is part of an ongoing effort to map the cortical connectome of the macaque using retrograde tract-tracing  (Markov et al. 2013 (Markov et al. , 2014a,b),b). For each target area, a retrograde tracer was injected into the cortex. The tracer was taken up in the axon terminals in this area, and retrogradely transported to the cell bodies of neurons that projected to the target. These cell bodies could be throughout the brain. Each of these cell bodies in cortex was counted as a labelled neuron (LN). The amount of labelled neurons was counted in all cortical areas except for the injected target area. The cortical areas that send axons to the target area are called source areas. As there are uncontrollable differences in tracer volume and uptake between injections, we estimated the strength of connections as follows.
This implies that the fraction of neurons coming from the supragranular layers in a given connection gives an estimate of the relative hierarchical position of two connected areas  (Barone et al. 2000; Markov et al. 2014a ). Here, following  (Markov et al. 2014a ), we estimate a set of hierarchical levels (one per area) that best predicts the SLN values for all connections in the dataset. The model to estimate the hierarchy has the form g(E(SLN )) = Xβ (4) where g is a function that links the SLN of the connection between areas to the hierarchical distance between them. β is a column vector of length n areas,SLN , containing the hierarchy values to be estimated. X is an incidence matrix of shape n conns × n areas,SLN , where n conns (= 2619) is the number of connections between cortical areas in the remaining dataset.
Integration of anatomical datasets All anatomical data was mapped to the appropriate parcellations on the Yerkes19 surface. For the present study, we mapped all data to the 40 area Lyon subgraph  Markov et al. 2014b , as the areas in this parcellation were generally larger than those in the Jülich macaque atlas  (Impieri et al. , 2019; Niu et al. , 2020; Rapan et al. , In Prep; Niu et al. , In prep;  this paper) and the Queensland (spine count) injection sites  (Elston 2007) , and closer to standard areal descriptions than the Vanderbilt (neuronal density)  (Collins et al. 2010)  sections. The receptor densities were quantified in 109 cortical regions defined by cyto-and receptor-architecture. The delineation of cortical region borders in the superior parietal lobe is described in  (Impieri et al.
2016  to 40 areas in this paper. For the spine count data, outlines of the 27 injection sites were drawn on the Yerkes19 surface by SFW with reference to the original papers (most of which had substantial anatomical description and hand-drawn maps), as well as anatomical papers cited within the original papers  (Cavada and Goldman-Rakic 1989; Preuss and Goldman-Rakic 1991)  and the Lyon and Jülich macaque atlases. Again, boundaries were independently assessed by anatomists (LR, MN, NPG). Spine count data was expressed according to injection sites, rather than entire cortical areas. As such, we found the number of vertices from each injection site overlapping with each area in the Lyon atlas. For each Lyon area, the spine count was an average of the spine counts for all the injection sites overlapping with the area, weighted by the number of vertices of each injection site contained within the area.
In this way we estimated the spine counts on pyramidal cells in 24 of the 40 regions in the Lyon atlas. Based on the strong positive correlation between spine count and cortical hierarchy (r = 0. 61, p = 0. 001), and following previous work  (Chaudhuri et al. 2015; Mejias and Wang 2019) , we inferred the spine count for the remaining regions based on the hierarchy using linear regression. Delineations of the areal borders for each atlas, and the anatomical data in the Yerkes19 space will be made available on the BALSA database upon publication.
Large-scale connectivity structure Each of the cortical areas is connected using connectivity strengths derived from the retrograde tract-tracing data. Parts of this dataset of been included in previous publications  (Markov et al. 2013 (Markov et al. , 2014a,b),b). The long-range connectivity matrices are built from the FLN matrix. However, as noted in  (Mejias et al. 2016) , the FLN matrix spans 5 orders of magnitude. The relationship between anatomical and physiological connectivity strengths is not clear, but if we were to use the raw FLN values in the large-scale model, many of the weaker connections would become irrelevant. To deal with this, we rescale the FLN matrix in order to increase the influence of smaller connections while maintaining the topological structure  (Mejias et al.
C ii) Number of dendritic spines on the basal dendrites of layer III pyramidal cells. D i) 40 injected areas in the retrograde tract-tracing database of Kennedy and colleagues (Markov et al. 2014b). D ii) Cortical hierarchy, calculated based on the laminar pattern of inter-areal connections. E) The density of D1 receptors divided by neuron density. Regions that have not yet been measured shown in gray. F) There was a strong positive correlation between the D1 receptor density per neuron and the cortical hierarchy, estimated independently based on the laminar origin of cortico-cortical connections. D1R, D1 receptor density.
Acknowledgements This project was funded by ( NIH/BMBF)  CRCNS grant (nos. R01MH122024  and  01GQ1902 ) to NPG and XJW;  NIH  grant  R01MH062349 ,  ONR  grant  N00014  and  James Simons  foundation grant  543057SPI  to XJW and the  European Union 's  Horizon 2020 Framework Programme for Research and Innovation  under the  Specific Grant Agreements 785907  ( Human Brain  Project  SGA2 ) and 945539 ( Human Brain  Project  SGA3 ) to KZ and  NPG. The authors would like to dedicate this manuscript to  Prof. Karl Zilles , who was an inspiring mentor, colleague and friend. Prof. Zilles  passed away earlier this year.
ID30A-3 (or MASSIF-3) is a mini-focus (beam size 18 mm Â 14 mm) highly intense (2. 0 Â 10 13 photons s À1 ), fixed-energy (12. 81 keV) beamline for macromolecular crystallography (MX) experiments at the European Synchrotron Radiation Facility (ESRF). MASSIF-3 is one of two fixed-energy beamlines sited on the first branch of the canted undulator setup on the ESRF ID30 port and is equipped with a MD2 micro-diffractometer, a Flex HCD sample changer, and an Eiger X 4M fast hybrid photon-counting detector. MASSIF-3 is recommended for collecting diffraction data from single small crystals ( 15 mm in one dimension) or for experiments using serial methods. The end-station has been in full user operation since December 2014, and here its current characteristics and capabilities are described.
, 2018)  on the other branch] as well as a beamline, BM29  (Pernot et al. , 2013) , dedicated to BioSAXS. Locating UPBL10 close to ID29 (de  Sanctis et al. , 2012)  created an 'MX Village', facilitating the common usage of ancillary technique laboratories and sharing services including the icOS in crystallo optical spectroscopy facility (von  Stetten et al. 2015) , a laboratory for the high-pressure cryo-cooling of biological macromolecules (HPMX;  Lafumat et al. , 2016; van der Linden et al. , 2014) , sample storage facilities both at 20 C and at cryogenic temperature, a sample preparation laboratory, and a data processing and backup computing area. ISSN 1600-5775 Conceived when CCD-based detectors were the staple device employed on synchrotron-based MX facilities, the original idea for the ID30A (MASSIF) beamlines was to create a hub of highly automated fixed-energy beamlines for the rapid characterization and sorting of samples.
These motors are operated in a closed-loop feedback mode and can be moved independently, or conjointly as pseudo motors for controlling the table height (thgt), translation (ttrans), roll (txrot), pitch (tyrot), and yaw (tzrot). The MD2 micro-diffractometer is, in contrast to all other MX beamlines, not permanently equipped with a Mini-Kappa goniometer head (MK3,  Brockhauser et al. , 2013)  to keep the sphere of confusion to less than 1 mm. However, the mounting of an MK3 device is available upon request. The maximum speed of the MD2 rotation axis is currently 720 s À1 , which allows, in combination with the fast Eiger X 4M detector, the recording of complete datasets in less than a second (Table  2 ). Additional built-in accessories of the MD2 include beam-cleaning apertures and a YAG screen for automatic alignment of the rotation axis and the X-ray beam [Fig.
Beamline control and data collection Low-level control of all beamline components and communication with the PMAC controller of the MD2 is provided by the newly developed ESRF standard software BLISS (Beamline Instrumentation Support Software; https:// gitlab. esrf. fr/bliss/bliss; Guijarro et al. , 2017). BLISS commands are mostly accessed transparently from the beamline control GUI MXCuBE2  (Gabadinho et al. , 2010; Oscarsson et al. , 2019) , but, for troubleshooting, a terminal interface is also available. All motors except those of the MD2 and that of the millisecond fast shutter are controlled by ESRF-developed IcePAP electronics  (Janvier et al. , 2013)  and pneumatically driven devices are controlled by WAGO control modules (https://www. wago. com). Users collect diffraction data via the MXCuBE2 GUI  (Gabadinho et al.
, 2010; Oscarsson et al. , 2019)  which is the standard interface on all MX beamlines at the ESRF. The metadata of each data collection are stored in the ISPyB database  (Delageniere et al. , 2011)  and can be recalled through the web-service EXI (https://exi. esrf. fr). Specific automated workflows are available and executed from within MXCuBE for complex tasks such as fast mesh scans, X-ray centring, helical data collections  (Flot et al. , 2010) , MeshAndCollect  (Zander et al. , 2015) , as well as MXpress workflows for fully automatic data collection  (Svensson et al. , 2015; McCarthy et al. , 2018). MASSIF-3 also features a more advanced workflow for helical data collection (Fig. 3 ). This workflow is especially useful for cases where crystals are thin elongated needles or plates and where start and end points for the helical trajectory are difficult to assign due to the opaqueness   and/or refraction (i.
e. lensing effects) of frozen mother liquor. In this workflow, initial start/stop points for the trajectory are refined and precisely determined by X-ray diffraction using two orthogonal line scans at each point. A data collection strategy taking into account that the radiation damage will be distributed over a larger crystal volume  (Zeldin et al. , 2013)  is then calculated using characterization images collected at the midpoint of the trajectory and is subsequently executed (Fig. 3 ). As on the other MX beamlines at the ESRF, all collected datasets are automatically processed using a series of software pipelines  [EDNAproc, GrenADeS (Monaco et al. , 2013) , XDSAPP  (Sparta et al. , 2016) , DIALS  (Winter et al. , 2018) , autoPROC  (Vonrhein et al. , 2011) ], the results of which are stored in the ISPyB database and are accessible, along with files containing the reduced data, through the web-service EXI (https://exi.
Results Opened to external users in December 2014, diffraction data collected on MASSIF-3 have, at the time of writing, contributed to 150 publications (source: ESRF-ILL Library; http:// www. epn-campus. eu/1/library/the-joint-ill-esrf-library/) and have resulted in more than 150 depositions in the Protein Data Bank (PDB; wwPDB consortium, 2019; http://biosync. sbkb. org/stats. do?stats_sec=RGNL&stats_focus_lvl=SITE&stats_ site=ESRF). Table  2  and Fig. 4  illustrate the high quality of data that can be routinely collected at the beamline. In a first experiment, we collected diffraction data from a Se-Met derivatized crystal of ferulic acid esterase (FAE;  Prates et al. , 2001)  with the aim of de novo structure determination using the SAD technique (f 00 = 3. 7 e À at 12. 834 keV). Data were measured according to a strategy proposed by an EDNA characterization  (Incardona et al.
, 2009)  at 100 K from a crystal cryo-protected using Paratone N and were automatically processed  (Monaco et al. , 2013). Subsequent de novo phasing performed with hkl2map  (Pape & Schneider, 2004)  and SHELXC/D/E (Uson & Sheldrick, 2018) found all 16 Se sites (8 per chain), and automatic building with ARP/WARP  (Langer et al. , 2008)  resulted in a model containing 280 and 281 residues (out of 297 residues) for the two FAE monomers in the asymmetric unit which was then further refined using Coot  (Emsley et al. , 2010)  and refmac5  (Kovalevskiy et al. , 2018). A representative section of electron density is shown in Fig. 4  which illustrates OMIT difference density for a double conformation for residue Gln127 (corresponding to Gln915 in PDB access code 1gkk). In a second experiment, bovine trypsin purchased as lyophilized powder from Sigma (reference: T9201) was crystallized as follows: A solution of 40 mg ml À1 trypsin, 10 mg ml À1 benzamidine (Sigma B-6506) and 3 mM CaCl 2 was mixed in a 1:1 ratio with reservoir solution [2 M (NH 4 ) 2 SO 4 in 100 mM Tris-HCl pH 8.
), using the ESRF automatic molecular replacement pipeline  (Monaco et al. , 2013). The structure refinement based on the trypsin-fast dataset (PDB access code 6swv) demonstrates that on MASSIF-3 complete, high-quality diffraction datasets can be collected in less than a second (Table  2 ). The combination of the fast read-out detector and a fast rotation goniometer (up to 720 s À1 ) allows collection of diffraction data at room temperature from crystals  (Gotthard et al. , 2019). The combination of a few dozen data wedges derived from different diffraction data sets allows the collection of timeresolved data in the millisecond range (Aumonier et al. , submitted).
Conclusion ID30A-3 (MASSIF-3) is a fixed-energy (12. 81 keV), highly intense (> 10 13 photons s À1 ) and highly automated mini-beam (18 mm Â 14 mm) end-station dedicated to protein crystallography at the ESRF. The beamline has been in full user operation since December 2014 with, at the time of writing, data collected at the beamline contributing to more than 150 PDB depositions (https://www. rcsb. org; Berman et al. , 2003)  and more than 150 publications (https://epn-library. esrf. fr). MASSIF-3 is currently recommended for diffraction data collection from small crystals or from larger crystals where use of a relatively small beam will allow the use of helical data collections or the identification of the best diffracting segment of a crystal for a diffraction experiment. Moreover, the relatively small focal spot size is conducive to efficient, highquality experiments exploiting multi-sample or serial methods.
or in UniPuck (http://smb. slac. stanford. edu/robosync/Universal_Puck) containers. Each system needs its own specific FlexHCD gripper to transfer sample holders, and the exchange of grippers can be performed automatically within less than a minute via the beamline control GUI MXCuBE (http://MXCuBE. github. io/ MXCuBE; Gabadinho et al. , 2010; Oscarsson et al. , 2019).
Acknowledgements The authors gratefully acknowledge the  ESRF  past and present management for their support. We also would like to thank the  Joint Structural Biology Group (JSBG)  members and the  ESRF support groups (TID, BIG , safety group, alignment group, computing and network) for invaluable help in this project. We thank  Matthew Bowler  ( EMBL Grenoble ) for helping to define the scientific case for the beamline and for his involvement in the initial stages of the project. We thank  Ulrike Kapp  ( ESRF ) for preparing FAE and trypsin crystals. ESRF beam time, granted through the in-house research programme, is acknowledged. etal. , 2014.
5 / 20. 0 17. 7 / 19. 8 18. 5 / 20. 6 No. of protein atoms 4588 1629 1629 No. of water molecules 438 232 232 No. of ions and buffer molecules 8 Cd, 1 glycerol 1 Ca, 6 SO 4 , 1 Ca, 6 SO 4 , 1 benzamidine 1 benzamidine Mean B 19. 8 10. 9 11. 1 R. m. s. deviations Bond length (A ˚) 0. 012 0. 013 0. 013 Bond angle ( ) 1. 77 1. 78 1. 78 PDB code 6y8g 6swv.
The Busy Isolating City identity is constructed through consumption in public spaces, where consumer residents find refuge from the crowd. The Clustering City identity is constructed in specific market spaces and segregating spaces that are sociocultural enclaves  (Tanulku 2012). The Small City identity relates to a sense of hominess  (McCracken 1988 ) that exists in market and segregating spaces, where consumer residents feel that they 'know everybody. ' The Dark City identity derives from consumption behaviors in public spaces that are embedded with significant negative outcomes. Overall, our data analysis answers our three research questions: (1) How do consumers build identities with their cities? (2) How are attachment styles manifested in city identity building? (3) What is the interplay of attachment, spaces and consumption in the process of city identity building? In response, our findings are also threefold.