dataesr/scientific-paragraphs-categorization huggingface dataset:
4 mm yr -1 with negligible increases for the horizontal components. The different epoch of the GPS data used for BREN (2007-2010) required a different elastic correction for that site as CS2 data were not available before November 2010. The estimate we produce is based on ICESat data  (2003) (2004) (2005) (2006) (2007) (2008) (2009)  and a surface mass balance and firn densification model derived from RACMO2  (Ligtenberg et al. 2011; Lenaerts et al. 2012 ), using the process described by  Gunter et al. (2014). We filtered the input fields with a Gaussian filter with a 6σ width of 100 km and replaced the load changes north of 69. 5 • S with those used by  Nield et al. (2014)  for the same period. Our BREN vertical elastic correction (0. 59 mm yr -1 ) is 1. 26 mm yr -1 smaller than the elastic term adopted by  Thomas et al.
2009) , with the C20 coefficient from Satellite Laser Ranging data  (Cheng et al. 2011)  and degree 1 coefficients from the approach by  Swenson et al. (2008). The mass trend due to GIA was removed, based on the solution of A et al. (2013) (http://grace. jpl. nasa. gov). The estimated signal magnitude was ∼-0. 5 mm yr -1 across Palmer Land. However, due to the degree of uncertainty associated with the driving processes and the spatial uniformity of the signal across the AP, we did not correct for these components of deformation but consider them further when comparing data with GIA model predictions.
Ice history reconstructions Ice history models used in this study are the product of field data constraints combined with glaciological insights and, in some cases, physical ice sheet models of varying complexity. The main aspect of a given ice history, which effects GIA, is the timing and magnitude of ice mass change. These drivers interact with the rheology of the modelled mantle to produce the modelled GIA rate. A total of 9 different ice history reconstructions were used in this study. With the exception of ICE-5G  (Peltier 2004 ), all were modifications on the W12 ice model  (Whitehouse et al. 2012a) , where changes were applied in order to determine whether the GPS data are able to constrain Holocene regional-scale ice load changes across Palmer Land. Details of the origin and construction of each ice history are summarized in Table  4  and described in detail below.
Acceptable range of D When comparing the GPS data and GIA model predictions we corrected for the weighted mean difference between data and model prediction D (eq. 1). Several factors contribute to the range of acceptable D values. Relative motions between the reference frames of the GPS data and GIA modelling could contribute an offset, primarily along the Z-axis of the reference frame. Recent estimates of the motion of CM (GPS) relative to CE (GIA model) suggest the two differ by less than ±0. 5 mm yr -1  (Argus et al. 2014). Farfield elastic effects, due predominantly to ongoing changes in global water distribution, could also influence deformation in the AP. As outlined in Section 2. 2, we estimate that the combined effect of these two processes is uniformly ≈-0. 5 mm yr -1 in Palmer Land over the GPS data collection period (Fig.
Model fit to the data In this section, we move from comparing regional trends along the AP transect to analysing the fit of the GIA rate predictions to the GPS rates. We calculated D for each Earth and ice model combination. Models with a D value outside the acceptable range were rejected. The remaining model combinations were then ranked by lowest DWRMS (Table  5 ; Table  S1 ). When all 12 GPS sites are considered, model combinations with a reasonable D value display poor DWRMS fits (Table  5 , Figs  7a  and b ). To investigate the source of the overall misfit, we analysed the SE sites (HTON, MKIB and BEAN) and other GPS sites separately. We divided the sites in this manner because the SE sites display a spatially coherent pattern of much higher uplift rates than the other sites (Fig. 2 ).
2011; Lenaerts et al. 2012). In particular, since ICESat data coverage is reduced in the northern Peninsula the accuracy of their estimate may be affected in the northern part of our region (e. g. near TRVE). The estimates of  Gunter et al. (2014)  and those presented here are also based on data covering two different periods and hence any errors in removing short-term effects will alter this comparison. Nevertheless, the agreement is impressive and supports the accuracy of our GPS velocities and the  Gunter et al. (2014)  results and indirectly corroborates the ice mass balance estimate of this region from  Gunter et al. (2014). The original  Gunter et al. (2014)  empirical uplift rates lie below the rates we measure in Palmer Land (Fig. 2b ). This offset is probably due to the GIA bias correction that  Gunter et al.
CONCLUSION We present data from a spatially dense network of GPS sites in Palmer Land in the southern Antarctic Peninsula. After removing a model of elastic effects and tectonic plate motion, horizontal GPS velocities suggest centres of former ice loss in Marguerite Bay, west of Palmer Land and in the region of the southwest Ronne Ice Shelf. Differences between competing models of plate tectonic motion represent an important limitation to the further interpretation of the horizontal velocities. We compared our new GPS uplift data with the spatially continuous, but independent, estimates of  Gunter et al. (2014)  and show good agreement, supporting the empirical GIA methodology of  Gunter et al. (2014). We attempted to reproduce the GPS uplift rates using a model of GIA considering a range of ice histories, including modifications to a published ice history (W12).
Either grounding line retreat occurred significantly later in the Holocene than previously assumed or the region hosted more ice at the LGM. Given evidence for low upper mantle viscosity in this region, which would cause more recent ice-load changes to dominate the present-day uplift, we consider later retreat as being most likely. This outcome joins other recent observations (e. g. Bradley et al. 2015)  in highlighting the need for further glaciological, geological and geodetic work in the southern Weddell Sea to constrain the timing of grounding line retreat in the Holocene. The current GPS data set cannot reliably discriminate between different post-5 ka ice history scenarios. GPS uncertainties will reduce as time-series grow, especially at SUGG and HAAG and, together with unpublished GPS sites further east, will allow the spatial pattern of present-day uplift in this region to be well characterised.
A C K N O W L E D G E M E N T S This work was funded by NERC grant: NE/F01452X/1. MAK is a recipient of an Australian Research Council Future Fellowship (project number FT110100207). PLW is a recipient of a NERC Independent Research Fellowship (NE/K009958/1). REMR is recipient of a Netherlands Organisation for Scientific Research VIDI grant (project number 864. 12. 012). OD is supported by the New Netherlands Polar Programme of the Netherlands Organization for Scientific Research. We thank Matt Burke for deploying the CAP-GIA sites and British Antarctic Survey engineers for maintaining them and downloading data. We acknowledge the hard work of the ANET team in deploying and maintaining SUGG and HAAG. This work is based on data services provided by the UNAVCO Facility with support from the National Science Foundation (NSF) and National Aeronautics and Space Administration (NASA) under NSF Cooperative Agreement No.
Source of tissue LV samples were obtained from 13 DCM patients undergoing cardiac transplantation and 10 non-diseased donor hearts as CNT samples. The clinical history, ECG, Doppler echocardiography, hemodynamic studies, and coronary angiography data were available on patients. Nonischemic DCM was diagnosed when patients had intact coronary arteries on coronary angiography, and LV systolic dysfunction (LV ejection fraction [LVEF] <40%) with a dilated nonhypertrophic left ventricle (LV end-diastolic diameter [LVEDD] >55mm). Twenty three per cent of the DCM patients were diagnosed with SMVT and 10 out of 13 were free of this arrhythmia. To improve the numerical base with a higher number of patients in protein analysis we increased the DCM samples up to 19. All patients were functionally classified according to the New York Heart Association (NYHA) criteria and received medical treatment according to the guidelines of the European Society of Cardiology  [10].
RNA-seq analysis and data computational analysis The description of RNA-seq procedure and data computational analysis are extensively described by Rosello-Lleti et al  [12]. The data presented in this paper have been deposited in NCBI's Gene Expression Omnibus (GEO)  [13]  and are accessible through GEO Series accession number GSE55296 (http://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE55296).
Discussion DCM is one of the most frequent pathologies causing HF. In this disease, impairment in proper cardiac contraction occurs  [1]. This process is carried out by ion currents whose concentration changes at different stages of action potentials to produce contraction and relaxation of cardiac fibers  [15]. Cardiac ion channels are thus the key components of this fine-tuned process, and their deregulation can cause heart dysfunction. We performed an RNA-seq technique to elucidate and compare the differentially expressed genes in DCM patients. Among these genes, we identified genes included in the ion channel category. RNA-seq allowed identification of a higher number of differentially expressed genes (2189 additional altered genes) and also genes codifying ion channels (21 additional altered genes) as compared to the microarray technique, providing a greater depth and sensitivity level in addition to have revealed consistent results among datasets.
In addition, NotI and MluI restriction enzyme sites were added to the 5= and 3= termini to enable directional cloning into a modified (low-copy-number) pBR322 vector  (15). Since full-length SIVcpz and SIVgor molecular clones are notoriously unstable, plasmids were grown in MAX Efficiency Stbl2 competent cells (Invitrogen) at 30°C and harvested before reaching saturating density, and each IMC was completely sequenced prior to biological analyses to confirm its integrity. The newly derived SIVcpz clones LB715 and TAN13 have been submitted to the National Institutes of Health Research and Reference Program (Rockville, MD), and their nucleotide sequences are available at GenBank. Phylogenetic analysis. Amino acid sequences inferred from env genes of HIV-1 (YU2, GenBank accession no. M93258; JRCSF, accession no.
Briefly, 96-well plates were seeded with TZM-bl cells (8,300 cells per well) overnight in Dulbecco's modified Eagle's medium (DMEM) containing 10% fetal bovine serum (FBS). Serial (5-fold) dilutions of chimpanzee plasma (1:20, 1:100, 1:500, 1:2,500, and 1:12,500) or anti-HIV-1 monoclonal antibodies and immunoadhesins (10, 2, 0. 4, 0. 08, and 0. 016 g/ml) were incubated with 4,800 infectious units (IU) of transfection-derived virus in a total volume of 100 l in the presence of DEAE-dextran (40 g/ml) for 1 h at 37°C, and this mixture was then added to TZM-bl cells in 96-well plates. After 48 h, TZM-bl cells were analyzed for luciferase expression using a Synergy H4 Hybrid microplate reader (Bio-Tek) with Gen5 version 1. 11 software. To test the neutralization capacity of anti-CD4 and anti-CCR5 receptor antibodies, 5-fold serial dilutions (10, 2, 0.
IC 50 s were calculated by linear regression. All monoclonal antibodies were tested in CD4 ϩ T cells from three different chimpanzee donors. Statistical analyses. Statistical analyses were performed using Prism version 5. 0d software (GraphPad), and correlations were assessed using Spearman tests. Geometric mean IC 50 s were calculated using Microsoft Excel version 14. 3. 9 software. Accession numbers. The nucleotide sequences of SIVcpz strains LB715 and TAN13 as well as the chimpanzee CD4 and CCR5 genes used for transfection are available under GenBank accession no. KP861923, JQ768416, KP235488, and KP235489, respectively.
ACKNOWLEDGMENTS We thank the staffs of  Chimp Haven , the  Southwest National Primate Research Center (SNPRC) , and the  Yerkes Regional Primate Research Center (YRPRC)  for sample collection from captive chimpanzees,  John P. Moore  and  Raiees Andrabi  for expert advice,  Jun Takehisa  for IMC construction,  Erica Parrish ,  Andrew Smith ,  Andrew Caffro ,  Miguel Ramirez , and  Eric Ruff  for technical assistance, and  Shivani Sethi  for artwork and manuscript preparation. This work was supported by grants from the  National Institutes of Health  ( R37 AI 50529 ,  R01 AI 58715 ,  R37 AI 066998 ,  P01 AI 088564 ,  P51 RR 000165 , and  P30 AI 045008 ). The views and opinions expressed in this publication represent the authors' views alone and do not express or imply the views, endorsement, or financial support of the  Federal Government  or any of its agencies, including the  National Institutes of Health , unless otherwise stated by an authorized representative thereof.
Introduction Systematics is the science of the world's biodiversity and its interrelationships. Its language is provided by taxonomy, the theory and practise of identifying, describing and classifying organisms  [1]. Traditionally, taxonomy relied on morphological characters, yet, given the limitations of morphology-based methods in e. g. distinguishing between cryptic species or in interpreting intra-specific variation, an integrative approach of taxonomy has been proposed  [2]. A review of the literature, however, revealed a lack of consensus on what methodologies should be included in integrative taxonomy and on how different characters should be weighthed against each other  [3]. Schlick-Steiner et al. [1]  suggested the use of at least three independent datasets: morphology, nuclear DNA and supporting evidence from one additional discipline.
Hence, the distribution of parasites provides additional information about the systematics of their hosts  [18] [19]. An additional advantage of using parasites relates to their often shorter generation time leading to potentially higher genetic and/or morphological differentiation than observed in their hosts. Therefore, species-specific parasites can provide a magnifying glass that can be used to resolve their hosts' taxonomy  [20]. This is especially promising for hosts belonging to recently or rapidly formed radiations, the taxonomy of which is often difficult to unravel. For such taxa, an integrative approach is almost essential as different datasets often reflect alternative evolutionary scenarios  [1]. The cichlid flocks of the East African Great Lakes form the most spectacular vertebrate radiations  [21].
Host genetics: barcoding For 30 specimens (S. diagramma (n = 5), S. babaulti (n = 16), S. marginatus (n = 4), S. pleurospilus (n = 3) and P. curvifrons (n = 2)) encompassing all the nominal taxa except S. margaretae, the first subunit of the cytochrome c oxidase gene (COI) was sequenced following  [74]. As these species do not form a monophylum, specimens from all other "sediment dwelling" tropheine species were included in the barcoding analysis: L. dardennii (n = 3), 'C. ' horei (n = 3) and 'G. ' pfefferi (n = 3). Sequences are available at NCBI GenBank under accession numbers KP336420-KP336458. Sequence analysis was carried out in MEGA v. 5  [75]. Model selection performed using the same software indicated the Kimura-2-parameter  [76]  + Γ model (with gamma-shape parameter = 0. 14) as optimal model of molecular evolution, based on the Bayesian information criterion.
Acknowledgments This is the sixth publication in a series on the ancyrocephalids of Lake Tanganyika. P. I. Hablützel ,  J. A. M. Raeymaekers ,  A. F. Grégoir ,  J. Bamps ,  D. Muzumani Risasi ,  T. Mulimbwa  N'sibula,  F. Muterezi Bukinga ,  V. Muderhwa Nshombo ,  J. Mbirize Ndalozibwa ,  V. Lumami Kapepula ,  C. Gillardin ,  G. Banyankimbona ,  C. Sturmbauer ,  L. Makasa ,  J. K. Zimba ,  T. Veall ,  O. R. Mangwangwa ,  A. Avenant-Oldewage  and  S. Risch  are gratefully acknowledged for their help in collecting the material for this study,  A. Konings  and  R. Blažek  for pictures of cichlids,  A. Reygel  for providing Fig 3,  G. Cael  for providing Fig 15 and  E. J. Vreven  for the inspection of the NMW specimens. This is publication ISE-M  2015-046.
Royal Museum  for  Central Africa , the  Muséum national d'Histoire naturelle  and the Iziko At the time of conducting this research, M. V. S. and M. P. M. V. were Ph. D. fellows, and T. H. a postdoctoral fellow of the Research Foundation -Flanders data also supported the synonymy between S. pleurospilus and S. babaulti, a species that contains a large amount of geographical morphological variation. ( FWO-Vlaanderen ). Field work was funded by two travel grants from the  Research Foundation -Flanders  to M. P. M. V. and two grants from the  King Leopold III Fund for Nature Exploration and Conservation  to M. V. S. and  M. P. M. V. Currently , M. P. M. V. is supported by the  Czech Science Foundation , Project no. P505/12/G112  ( European Centre of Ichthyoparasitology (ECIP) -Centre of excellence).
The plates were read using a bottom-read plate reader (LT-5000MS ELISA Reader, Labtech, East Sussex, UK) at λ = 570 nm. In these experiments, the fi rst and last rows in the 96-well plates were fi lled only with PBS and the well A1 was used as the blank for the reading. Manta data analysis software (associated with the instrument) was used for the read-outs.
Acknowledgements G. G. is a recipient of "Research Based University Chairs of  Excellence-Universities of Paris  ( RBUCE-UP)" independent research grant  from  European Research Council (ERC). This work was funded by the  RBUCE-UP  grant agreement (# 00001002483/78 ) between the  ERC  and  Université Paris Sud. Part of this research was also funded by the  ERC  under the Framework Program FP7/2007-2013 (Grant Agreement  N°249835 ). UMR 8612 (Couvreur team) is a member of the laboratory of excellence NANOSACLAY. The authors thank the service of the animal experimentation from the  IFR141 IPSIT (Châtenay Malabry ). Ms. Julie Mougin  ( UMR 8612 ) and  Mrs. Ghislaine Frébourg  (Electron Microscopy.
Conclusions We have analysed quantitatively the dynamics of water molecules and protons confined in the Aquivion membrane and PFOS surfactant system, on an extended hydration range and time scale (from tenth of ps to hundreds of ps). A complex dynamical behaviour originating from nanoscale confinement in a charged nanostructured host matrix was found. Two populations of protons and similar processes were observed in both the state-ofthe art commercial membrane for fuel cells and the self-assembled PFOS structures. Slow localized proton jumps and long-range diffusion were identified from high resolution backscattering QENS data (on IN16B). Fast rotational motions and fast localized translational diffusion were obtained by ToF measurements performed at two different wavelengths. An accurate comparison of the effect of hydration on the hopping process, local and nanometric diffusive motions was obtained after a multi-Lorentzian analysis of the full set of QENS data.
The results presented rsob. royalsocietypublishing. org Open Biol. 5: 150025 here suggest that the PASTA domain probably recognizes growing peptidoglycan strands, and regulates production of penicillin-binding proteins and distribution of proteins involved in division and generation of septum. Furthermore, our data indicate that the interactions of the PknB_PASTA domain with the cell wall are important, and that its abundance may serve as a controlling mechanism for the integrity of the cell wall and bacterial growth. Bacterial growth was followed by measurement of absorbance at 580 nm in a Jenway spectrophotometer. Growth of M. smegmatis in various media was performed using a Bioscreen Growth Analyser as described previously  [34]. Presented Bioscreen data are mean values of two independent experiments done in quintuplicate.
Microscopy Mycobacterium smegmatis bacilli were mounted on PBS and observed by phase contrast microscopy using a Diphot 300 inverted microscope with a 100 W mercury light source. Images were recorded using a 12/10 bit, high-speed Peltiercooled CCD camera (FDI, Photonic Science) using IMAGE-PRO PLUS (Media Cybernetics) software. Labelling of nascent peptidoglycan was done as described previously  [35]. Briefly, mycobacteria were grown in Sauton's medium in the presence of 20 ng ml 21 of tetracycline to exponential growth phase (OD 600 0. 5). A mixture of Vancomycin-BODIPY (Life Technologies) and unlabelled vancomycin (1 : 1) was added to cultures to the final concentration of 2 mg ml 21 , followed by a 2 h incubation at 378C with shaking. Bacteria were washed twice with PBS containing 0. 1% Tween 80 and used for fluorescence microscopy.
The raw data file obtained from each LC-MS/MS acquisition was processed using Proteome DISCOVERER (v. 1. 4. 0. 288, Thermo Scientific), searching each file in turn using MASCOT  [45]  (v. 2. 2. 04, Matrix Science) against the UniProtKB-Swissprot database. The peptide tolerance was set to 10 ppm and the MS/MS tolerance was set to 0. 02 Da. Fixed modifications were set as carbamidomethyl (C) and variable modifications set as oxidation (M). A decoy database search was performed. The output from Proteome DISCOVERER was further processed using SCAFFOLD Q þ S 4 (v. 4. 0. 5, Proteome Software, Portland, OR, USA). For quantitative experiments the digested peptides were labelled with the TMTsixplex Label Reagent kit (Life Sciences) according to the manufacturer's instructions. SCAFFOLD Qþ (v. 4. 3.
4, Proteome Software) was used to quantify Label Based Quantitation (iTRAQ, TMT, SILAC) peptide and protein identifications. Both protein and peptide identifications were accepted if they could be established at greater than 95. 0% probability and contained at least two identified peptides. Peptide probabilities from X! Tandem were assigned by the Peptide Prophet algorithm  [46]  with SCAFFOLD delta-mass correction. Peptide probabilities from MASCOT were assigned by the SCAFFOLD Local FDR algorithm. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD002120 and 10. 6019/PXD002120.
The plasmids were transformed into M. smegmatis and the resultant strains, designated as PknB1 ( pknB), PknB5 ( pknB-DPASTA) and MIND (empty plasmid), grew similarly in all media tested in the absence of the inducer tetracycline (data not shown). However, addition of tetracycline to the PknB1 or PknB5 strains affected growth in liquid medium (figure  2 ). This inhibitory effect was probably caused by the induction of expression of pknB and pknB-DPASTA from the pMind plasmid. When grown in the presence of tetracycline, PknB1 and PknB5 expressed the pknB versions from pMind at relatively high level, corresponding to 1% (+0. 3%) of all 16s-rRNA transcripts as judged by quantitative RT-PCR; no expression of the target gene was detected in mycobacteria in the absence of tetracycline. Interestingly, overexpressing the pknB versions resulted in different growth characteristics.
Another CrgA interaction partner, Wag31, was detected at similar levels in both strains. Interestingly, the TMP strain had more enzymes involved in biosynthesis of mycolyl-arabinogalactan (table 2; electronic supplementary material, table  S5 ), including several mycolyl-and galactofuranosyl-transferases. Regarding peptidoglycan-related enzymes, the levels of two metallob-lactamases, L,D-transpeptidase LdtB and D-alanyl-D-alanine carboxypeptidase DacB1, were increased in the TMP membrane fraction (table 2). Complete data are available via ProteomeXchange with identifier PXD002120. Collectively these results may suggest that the overexpression of the PASTA domain influences the biosynthesis and architecture of mycobacterial cell wall.