dataesr/scientific-paragraphs-categorization huggingface dataset:
Moreover, there is a structural correlation to this antiferromagnetic interaction as shown in Fig. 3 , which presents J as a function of the Gd-F-Cr angle. To shed light on this issue, as well as on the angular dependence of J, we performed DFT (B3LYP/TZV) calculations on 1. All the calculations were performed with the Gaussian 09 program suite (cf. ESI † for computational details). The computed J value of 0. 80 cm À1 for 1 is in excellent agreement with the values extracted from experiments (see Table  S2  for DFT computed energies, ESI †). The reproduction of both the sign and the magnitude of J provides confidence in the computed J values. Understanding the mechanism by which the coupling is operational in this {Cr-Gd} pair is important, as it is expected to provide clues about the nature of the exchange interaction and its angular dependence.
The observed variation and magnitude of J is reproduced and rationalised by DFT calculations in terms of geometric variation of 3d-4f overlap and charge transfer. This insight paves the way for preparative control of magnetic exchange interactions in systems with small magnetic anisotropy and thereby for the development of new molecular, magnetic coolers. K. S. P. and S. P. thank the Danish Ministry of Science, Innovation and Higher Education for an EliteForsk travel scholarship and a Sapere Aude Fellowship (10-081659), respectively. GR thanks DST (SR/S1/IC-41/2010; SR/NM/NS-1119/2011) for financial support and SKS thanks IITB for SRF fellowship. GR and SKS acknowledge the HPC facility at IITB.
Mass Spectrometry For confirmation of the presence of the disulphide bridge the b F108C/G123C mutant was buffer exchanged into 250 mM ammonium acetate at pH 7. 5, concentrated to 10 mM using Amicon Ultra 0. 5 ml centrifugal filters (Millipore UK Ltd, Watford UK) and then diluted 2:1 in denaturing buffer (50:50 water:methanol). Mass spectrometry experiments were carried out on a Synapt HDMS (Waters Ltd, Manchester, UK) QTOF mass spectrometer  [26]  and 2. 5 ml aliquots of protein samples were delivered to the mass spectrometer by means of nanoESI using gold-coated capillaries, prepared in house. Typical instrumental parameters were as follows: source pressure 6 mbar, capillary voltage 1. 20 kV, cone voltage 40 V, trap energy 10 V, transfer energy 8 V, and trap pressure 3. 6610-2 mbar. Data acquisition and processing were carried out using MassLynx (ver.
Structural Biology Crystals were obtained from sitting drop vapour diffusion against a reservoir of 0. 1 M Hepes sodium pH 7. 5, 2% polyethylene glycol (PEG) 400, 2. 0 M ammonium sulphate. Data were recorded at the ESRF ID23-1 to a resolution of 2. 7 A ˚from a single crystal bathed in crystallization mother liquor with 10% glycerol, cooled to 100 K prior to data collection (Table  S2 ). Data were processed using MOSFLM/SCALA  [27, 28]. The structure was solved by molecular replacement [with the starting model of the A. faecalis high resolution structure (PDB 1 g8k -see RCSB www. pdb. org)] with separate a chain and b chains (cut to polyalanine where residues were not conserved) using the program PHASER  [29, 30]  as implemented in CCP4  [31]. The structure was rebuilt to the correct sequence with a combination of the program BUCCANEER  [32]  and manual intervention with COOT  [33].
EPR EPR spectroscopy was performed on wild type and mutant enzymes obtained after the desalting step. Redox titrations were performed with approximately 2 mg of enzymes, at 15uC, pH 8, as described by Dutton  [37]  and adapted as described by Duval  [12]  in the presence of the following redox mediators at 100 mM: 1,4 p-benzoquinone, DCPIP, 2,5-dimethyl-p-benzoquinone, 2hydroxy 1,2-naphthoquinone, 1,4-naphthoquinone. Reductive titrations were carried out using sodium dithionite, and oxidative titrations were carried out using ferricyanide. EPR spectra were recorded on a Bruker ElexSys X-band spectrometer fitted with an Oxford Instruments liquid-Helium cryostat and temperature control system. The results of the wild type and mutant enzyme redox data were obtained with two separate enzyme preparations.
A search of the PDB database reveals that the a subunit is closely related to the periplasmic nitrate reductase (NapA) from Desulfovibrio desulfuricans (PDB 2NAP, gives a superposition of the a subunit from NT-26 of 2. 1 A ˚for 619 matching ca atoms), which has two pterin co-factors ligated to Mo and a 4Fe-4S cluster (not the 3Fe-4S seen in AioA). Other similar structures are all members of the DMSO reductase family. Some periplasmic nitrate reductases do possess a small b subunit but this is dissimilar to the typical Rieske fold of the AioB subunit  [6, 38]. Analysis of protein-protein interactions using PISA (Protein Interfaces, Surfaces and Assemblies)  [39]  shows that the a and b subunits that come together to form the heterodimer bury 8000 A ˚2 of exposed surface area. The same analysis reveals that the four heterodimers present in the asymmetric unit are arranged as two stable heterotetramers, and each heterotetramer buries 22000 A ˚2 of surface area (meaning the tetramerisation buries a further 6000 A ˚2 of surface area) (Figure  4 ).
Consequently PISA analysis does not identify in this crystal the heterotetramer as stable. For the NT-26 Aio, biochemical data suggests that the heterotetramer is stable in solution and the functional unit. The data for the A. faecalis Aio are less clear cut with a heterodimer being regarded as the functional unit. However, the conservation of the tetrameric arrangement in three different crystals, with two crystal forms showing stable arrangements with extensive buried surface area, argues that the heterotetramer is most likely to be the functional unit for the Aio. In fact, we have recently demonstrated that the recombinant version of the A. faecalis Aio expressed in E. coli is a heterotetramer as determined by gel filtration chromatography (Heath & Santini, unpublished data). The multiple arrangement and apparent variability in heterotetramer strength (as judged by PISA) in A.
If correct then this would give an overall charge of 22. Reduction from the +VI state may have occurred during data collection (as proposed for the A. faecalis enzyme) or the enzyme may have a five coordinate +VI oxidation state. There is no evidence in the NT-26 Aio for a sixth ligand to the Mo centre. In the A. faecalis Aio Ellis et al. [6]  proposed the presence of a hydroxide in the +VI state, although this gave an unusual geometry which would require some re-arrangement of the protein. The second coordination sphere around the Mo is identical in both the A. faecalis and NT-26 AioA subunits, comprising H199, N200, R201, E207, K385, R447 and H451 (NT-26 numbering). These residues are predicted to control the recognition and orientation of the incoming arsenite. Several residues surrounding the 3Fe-4S centre are different between the A.
The sequences obtained were aligned to huntingtin gene sequence from PubMed with the Serial cloner 2. 0 software (available at: http://serialbasics. free. fr/Serial_Cloner. html). Behavioral testing. Behavioral testing was performed as described previously  (David et al. , 2009). Immunohistochemistry. Mice were anesthetized with ketamine (250 mg/ ml; 100 l/10 g of body weight) by intraperitoneal injections. Mice were then perfused with a saline solution and, after complete blood clearing, by paraformaldehyde (PFA) 4%. Brains were removed and kept in PFA 4% overnight. They were then cryoprotected in 30% sucrose. Frozen blocks were sectioned at 35 m and slices were kept free-floating in PBS with 0. 1% azide. Serial sections were made, each one covering the whole hippocampus. TUNEL staining was performed with DeadEnd Fluorometric TUNEL System (Promega) according to the manufacturer's instruction, with the addition of a prior permeabilization step in 0.
3% H 2 O 2 in 0. 1 M TBS. Slices were blocked with 10% normal donkey serum in 0. 1 M TBS with 0. 5% Triton X100. Slices were then incubated overnight at 4°C in blocking solution containing goat anti-DCX antibody (Santa Cruz Biotechnology). After washing, slices were incubated with biotinylated donkey antigoat. Revelation was performed as described for BrdU immunostaining and sections were dehydrated and mounted as before. For Sholl analysis, DCX-positive cells with tertiary, relatively untruncated dendritic branches were traced for each 35 m hippocampal slice using Neurolucida software (MicroBrightField) on an Olympus BX51 microscope equipped with a motorized stage device and ϫ100 immersion oil objective. DCX immunohistochemistry was done to maximize the labeling of dendrites. Sholl analysis for dendritic complexity was performed using the accompanying software (NeuroExplorer; Micro-BrightField, version 10), calculating dendritic complexity including dendritic length and number of intersections (branch points).
5 mg/ml) and laminin (10 mg/ml) overnight at 4°C and then washed three times with neuronal medium. One million neurons were plated in the cell body/proximal compartment of the chamber. The microscope and the chamber were kept at 37°C. Images were recorded with a 100ϫ PlanApo N. A. 1. 4 oil-immersion objective on a Leica DM IRBE microscope and collected every 200 ms in stream mode with 150 ms of exposure and a 2 ϫ 2 binning using a Micromax camera (Ropper Scientific) controlled by MetaMorph software (Molecular Devices). Videos, kymographs, and analyses were generated with ImageJ software (http://rsb. info. nih. gov/ij/). Maximal projection was performed to identify the vesicles paths, which in our system corresponds to vesicle movements in axons. Kymographs and analyses were generated with the KymoToolBox, a home-made plug-in previously described  (Zala et al.
Cover-slips were mounted in 0. 1 g/ml Mowiol 4-88 (Calbiochem) in 20% glycerol. Acquisitions of images were performed with a confocal Leica SP5 microscope. Analysis of BDNF vesicles on MTs was performed using ImageJ software (http://rsb. info. nih. gov/ij/). Statistical analyses. Statview 4. 5 software (SAS Institute) was used for statistical analysis. The criterion for statistical significance was set at p Ͻ 0. 05. Data are expressed as mean ϮSEM.
Ablation of HTT phosphorylation at S1181/S1201 promotes survival and maturation of newborn neurons in the hippocampal dentate gyrus The hippocampus is important for the regulation of mood disorders and hippocampal neurogenesis is involved, at least in part, in the regulation of the response to antidepressants (for review, see  Samuels and Hen, 2011). We thus focused our attention on neurogenesis in the dentate gyrus of the hippocampus in 14-week-old animals that had performed the behavioral tests. We first estimated the number of proliferating cells using Ki67 and apoptotic cell death using a TUNEL assay. We did not observe any differences in the numbers of proliferating and apoptotic cells in the dentate gyrus between the different genotypes (data not shown) (Fig. 3A ). We next assessed the survival rate of newly generated neurons by labeling with the thymidine analog BrdU (Fig.
This work was supported by grants from  Agence Nationale pour la Recherche ,  Maladies Rares  (Grant  ANR-09-BLAN-0080 ),  Association pour la Recherche sur le Cancer  (ARC subvention libre n°3188),  Federation pour la Recherche sur le Cerveau (FRC) ,  CNRS ,  INSERM , and  Institut Curie  to S. H. Fellowship support was provided by  Fondation pour la Recherche Medicale  (K. B. ) and by the  French Minister of Research  (K. B. , S. O. ). The mouse mutant line was established at the  Mouse Clinical Institute (Strasbourg, France)  in the Targeted Mutagenesis and  Transgenesis Department  with funds from Grant  ANR-09-BLAN-0080. P. P. and  D. J. D. Universite  ´Paris-Sud 11; F. S. and S. H. are INSERM investigators. We thank the staff from  Institut Curie  facilities: Animal, Histology, Imaging,.
Secondly, the applicability of this method was tested by running a full scale test using an original pyrosequencing dataset of 18S rRNA genes of small lacustrine protists (0. 2-5 mm) from eight freshwater ecosystems. Our results revealed that i) fewer than 5% of the operational taxonomic units (OTUs) identified through clustering and phylogenetic affiliation had been previously detected in lakes, based on comparison to sequence in public databases; ii) the sequencing depth provided by the NGS coupled with a phylogenetic approach allowed to shed light on clades of freshwater protists rarely or never detected with classical molecular ecology approaches; and iii) phylogenetic methods are more robust in describing the structuring of under-studied or highly divergent populations. More precisely, new putative clades belonging to Mamiellophyceae, Foraminifera, Dictyochophyceae and Euglenida were detected.
The taxonomic assignment of such data is often inferred from supervised classification with the Ribosomal Database Project Classifier (RDP)  [15] , sequence similarity with BLAST  [16] [17] [18]  or both  [19, 20]. Pairwise identity scores via BLAST remain the most commonly used tool for large eukaryotic datasets  [14, [21] [22] [23] [24] [25] [26]. However, as claimed by Bik et al. [26] , assigning accurate taxonomy to eukaryotic operational taxonomic units (OTUs) is more difficult than the approaches used for Bacteria; the relative paucity of sequences in public eukaryotic databases results in many sequences without significant top BLAST matches  [26]. Furthermore, the best BLAST match assigns a single organism as the most likely phylogenetic neighbor, without specifying the level of relatedness (class, order or phylum) of the compared sequences  [27].
1,200 bp) and on short sequences that simulate pyrosequencing outputs. Secondly, the different methods of taxonomic assignment (i. e. , tree-based, similarity and probabilistic approaches) were compared with each other, in a first attempt to determine the best method for affiliating protists in the context of massively parallel sequencing of amplicons. Thirdly, the accuracy of phylogenetic affiliation was compared on amplicons covering different variable regions (V1 to V9), and finally, a dataset of original pyrosequencing data obtained from lacustrine small protists was analyzed by the treebased approach that was developed.
e. , genus), BLAST and RDP allowed for the affiliation of 62. 3% and 68. 4% of reference sequences. Thus, our phylogenetic affiliation method outperformed the other methods on near fulllength sequences. However, as environmental sequences are generally quite divergent from referenced ones and their affiliation needs to be checked manually, sequences belonging to freshwater clades  [6, 7]  were also processed by our phylogenetic affiliation method to evaluate how it behaved on these datasets. The phylogenetic analysis of these environmental sequences (Sanger,. 1,200 bp) enabled us to retrieve the affiliations obtained by other authors together with the delineation of freshwater clades corresponding to Cercozoa clade  [6]  and Perkinsea clades 1 and 2  [7]  (Figure  S1 ). Different 18S rRNA gene regions were targeted by simulating amplicons with lengths of 200 and 400 bp starting from a conserved region given by the following forward primers: NSF4, NSF370, NSF573 NSF963, NSF1179 and NSF1419 (Table  S2 ).
Because the V8-V9 region is often missing in public databases, the results obtained from this region were based only on 300 sequences included in the reference database. The affiliation results at the genus rank differed according to length, variability within the studied region and method used for taxonomic affiliation (Table  1 ). For the six regions tested, the accuracy increased with amplicon length for both affiliation methods implemented in PANAM, LCA and NN. Considering the affiliation methods, LCA specificity was higher than that of NN for fragments of 200 bp only for the V1 and V8 regions, and LCA specificity was always better for fragments of 400 bp. The comparisons with the other affiliation tools implemented in pipelines dedicated to pyrosequencing results showed that at 200 bp, BLAST outperformed RDP, STAP and PANAM, with the exception of the V8 region, for which PANAM (LCA) gave the highest result (68.
7%). In contrast, for 400 bp amplicons, the most accurate affiliations were obtained with PANAM, with the exception of the V5-V6 amplicon. In this last region, we observed a decrease in the accuracy of the affiliation, coupled with a sharper decline for the phylogeny-based affiliations. The specificity therefore varied between 64. 2% (V5-V6) and 79. 2% (V8-V9) at the genus level. In addition to the accuracy of assignment, this phylogenetic affiliation method was developed to optimize processing time for large datasets. Thus with a 2 GHz Intel(R) Xeon(R) and 24 GB RAM and with a single 32-bit CPU, PANAM can process the phylogenetic analysis of 1000 eukaryotic OTUs of 400 bp in approximately 20 minutes, regardless of the affiliation method. The run time increased with the number of OTUs, regardless of the length.
1,000 near-full-length sequences were randomly picked from the reference database and removed from it for the simulations. For PANAM, simulations were repeated 5 times and the standard variation is less than 0. 03. 1. B. Accuracy of the phylogenetic affiliation in relation with the variable region targeted. The specificity was tested with PANAM-LCA and a sequence length equal to 400 bp. doi:10. 1371/journal. pone. 0058950. g001 sequences) showed that Bourget Lake harboured the largest number of species (Table  2 ). This normalization also had an effect on the richness estimates in Godivelle Lake and Geneva Lake. In the lakes studied, regarding level 2 and 3 from EMBL taxonomy (displayed in Table  S3 , a PANAM table output, including number of sequences, OTUs and diversity indexes), the major phylogenetic groups were Fungi, Alveolata and Stramenopiles representing 73.
Discussion As the interplay between evolution and ecology receives more attention in ecosystem studies  [38] , there is greater interest in phylogenetic approaches for deciphering the mechanisms that govern the diversity and functioning of communities and ecosystems. However, the phylogenetic methods that are typically applied to Sanger-sequenced SSU rRNA are computationally expensive and cannot be readily used to handle NGS datasets; therefore, pyrosequencing reads are mainly analyzed by other approaches. The method described in this study is a response to the challenge of analyzing hundreds of thousands of SSU rRNA genes in a phylogenetic framework, inferring taxonomies from sister sequences and describing clades. This method has been implemented and tested for microorganisms with an emphasis on protists, which are not well served by bioinformatics tools dedicated to NGS data, although the early focus on bacterial and archaeal diversity has recently broadened to include eukaryotic microorganisms  [39, 40] ; thus, the database provided in PANAM includes reference sequences from protists, Bacteria and Archaea and can be used for taxonomic assignment of all microorganisms.
The specificity corresponds to the number of genus correctly affiliated among the detected ones, computed from forward primers for 200 bp and 400 bp amplicons. These values correspond to the mean computed from five samples of 1000 sequences (with the exception of V9 region computed with 300 sequences). The standard variation is less than 0. 05. doi:10. 1371/journal. pone. 0058950. t001 The affiliation of simulated amplicons were obtained by the RDP Classifier trained on the near full-length sequences of the reference database used in PANAM. Surprisingly, trimming the reference database to the primer region did not result in an improvement of classification for 18S rRNA gene sequences (data not shown), in contrast to the results of Werner et al. [43]  on 16S rRNA gene sequences. As noted by these authors, a naı ¨ve Bayesian classification depends on the training set size.
The weak performance on the truncated sequences could thus be explained by the limited number of 18S rRNA gene sequences in public databases compared with 16S rRNA gene sequences, particularly for the V9 region (see the discussion below). The comparison of the tree-based method proposed with these tools in the context of taxonomic affiliation of 18S rRNA gene amplicons shows that regardless of the method that is used, taxonomic reliability depends on the sequence length and amplicon location on the SSU rRNA gene sequence. These results, which to our knowledge have not been examined for 18S rRNA gene sequences, are consistent with observations of 16S rRNA gene sequences from Bacteria and Archaea  [44]. Our results mostly illustrate the impact of sequence length on phylogenetic methods, which appears to be the main limitation of this approach.
Phylogenetic methods are generally considered superior to other approaches for taxonomic affiliation  [45]  as they assess relatedness between a set of sequences. They are also considered to be difficult to automate as i) their reliability greatly depends on the quality of the alignments, which need to be validated by experts in the field, and ii) they use intensive, time-consuming methods for tree building. In this study, we use the curated alignments sequences provided by SILVA, which is, at least for eukaryotic sequences, the only upto-date curated database. All high-quality and near full-length aligned sequences suitable for in-depth phylogenetic analysis were selected. However, the guide-tree for eukaryotes provided by SILVA, in contrast to the other domains, represents only an approximate phylogeny.
Thus, the bias observed between variable regions  [22]  could be due to primers that may not anneal uniformly to all groups, but also to the bioinformatic process used for the taxonomic identification. In summary, with the exception of Viridiplantae, the V8-V9 region appears to be a   S3 ). doi:10. 1371/journal. pone. 0058950. g002 good candidate for the study of protist diversity because the reliability of the taxonomic affiliation did not differ according to the phyla considered (i. e. , Stramenopiles, Fungi, Alveolata). However, sequence databases such as GenBank contain many fewer sequences that include the V9 region than other variable regions.
doi:10. 1371/journal. pone. 0058950. g003 description of the general picture of protists diversity obtained for these lakes. For an in-depth analysis of this PCC from lacustrine ecosystems, we introduced environmental sequences and taxonomies in the reference database to delineate specific clades as defined in previous publications (e. g. ,  [6, 37, 50] ). The introduction of ''environmental reference'' sequences reflecting the taxonomies of protists originating from specific environments can enhance the affiliation of poorly represented environmental sequences. Phylogenetic methods provide a clear edge in describing under-studied and complex communities. However, as with other methods, the precision of sequence mapping falls off when experimental sequences lie distant from reference SSU rRNA gene sequences  [51].
This observation is particularly true for environmental sequences, for which the availability of close relatives and wellannotated sequences in reference databases is limited, as is the case for the V9 region. If the referenced trees do not include known relatives branching close to experimental reads, divergent lineages form long-branch taxa with no close reference sequences at relatively deep internal nodes. This phenomenon results in a less precise taxonomic affiliation of these sequences; however, clades of interest could still be drawn, as very similar sequences (i. e. , sequences with low pairwise distance) are very well preserved among tree searches from de novo phylogenies  [29]. Most eukaryotic species are defined on morphological differences, however, as the majority of existing microorganisms on Earth have not yet been cultured, their phenotypic traits can hardly be described.