dataesr/scientific-paragraphs-categorization huggingface dataset:
Cells were then depolarised to + 40 mV voltage clamp and mixed AMPA/NMDA mEPSCs recorded for 1 min, after which 10 µM CNQX was applied to the bath. Following full wash-in of CNQX (~2-3 min) a further 5 min of pure NMDA mEPSCs were recorded. In all experiments 50 µM AP-5 was then bath applied, to confirm that the mEPSCs recorded were NMDAR-mediated. All mEPSC data was analysed using a moving-template algorithm  55  , with templates made from the tri-exponential nonlinear fit to optimal mEPSCs at each holding potential using the event-detection interface of Stimfit. For mEPSCs at -70 mV, the minimum time between EPSCs was set to 7. 5 ms, and 25 ms for those at + 40 mV. Detected events were analysed if they had an amplitude greater than 3× the SD of the 5 ms preceding baseline of the mEPSC. HCN-mediated currents were measured as previously reported  30.
When a field response was observed, then a L4 SC was recorded in whole-cell patch-clamp with K-gluconate internal solution, as described above. Trains of 5 stimuli were then delivered at 5-10 Hz, with a stimulation intensity sufficient to produce an EPSC of large amplitude similar between genotypes (20-540 pA; WT: 181 ± 35 pA; Fmr1 -/y : 159 ± 34 pA; d. f. : = 23, t = 0. 44, P = 0. 66, T-test). In current-clamp, the EPSP summation was assessed as the ability of the recorded cell to fire an AP in response to this stimulus. Data are shown as the average P spike from 10 trials. Near-simultaneous dendritic spine 2-photon glutamate uncaging. To determine the summation properties of dendrites in L4 SCs we performed nearsimultaneous photolysis of Rubi-Glu at multiple dendritic spines  20, 49. Using a current-clamp optimized K-gluconate based internal solution supplemented with 0.
In a subset of experiments the HCN inhibitor ZD was applied to the perfusing ACSF and a further three repetitions collected. All uEPSP data was analysed as peak amplitude measured over the 20 ms directly following beginning of the photolysis stimuli. Data was either normalised to the first EPSP amplitude, or measured as the absolute simultaneous uEPSP, as plotted against the summed individual uEPSP amplitude for the same spines. In a set of experiments (without PTX, TTX or AlexaFluor 488), intrinsic electrophysiological properties of L4 SCs were measured, also in current-clamp mode. From resting membrane potential a hyper-to depolarizing family of current injections (-125 to +125 pA, 500 ms duration) were given to the recorded neuron. The input resistance, rheobase current, and action potential discharge frequency were all measured from triplicate repetitions.
The mounted tissue was then trimmed and gold-plated prior to insertion imaging. Initially, semi-thin sections trimmed from the surface of the block, and imaged under transmission electron microscopy at low power to confirm tissue ultrastructure and ROI selection for SBF-SEM. Next the tissue blocks were mounted in an SBF-SEM (3View, Gatan, CA, USA) and 3 × ~10 µm 2 ROIs chosen on the surface of the block, avoiding blood vessels or L4 SC somata, and imaged at 50 nm steps at ×8000 magnification (1024 × 1024, 10 nm pixel size). Approximately 100 sections were collected from each block, giving a total depth of 5 µm. SBF-SEM images were analysed offline using the TrakEM module of FIJI  57. Dendrites and spines were traced as surface profiles and then PSDs identified on dendritic spines as electron dense regions within 25 nm of the lipid bilayer.
When animal or paired cell data are shown and not modelled, datasets were tested for normality (d'Agostino-Pearson test) and either Student's t-test, Mann-Whitney non-parametric U-test, or Wilcoxon signed-rank tests performed. Comparison of linear and non-linear regression was performed with a sum-of-squares F-test. Statistically significant differences were assumed if p < 0. 05. Which statistical test employed is indicated throughout the text. Either GraphPad Prism or R was used for all statistical analyses. All statistical tests performed are presented in supplementary materials (Table  S1 ). Reporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article.
Acknowledgements The authors wish to thank:  Drs. Alison Dunn  and  Rory Duncan  of the  Edinburgh Super-Resolution Imaging Consortium (ESRIC)  for expert advice and technical support;  Kathryn Whyte  and  Tracey Davey  of the  EM Research Service, Newcastle University , for technical assistance with electron microscopy. Funders:  Simons Foundation Autism Research Initiative  ( 529085 ), The  Patrick Wild Centre ,  Medical Research Council UK  ( MR/P006213/1 ), The  Shirley Foundation  and the  RS Macdonald Charitable Trust.
eclamc. org) (Figure  2 ); and EUROCAT, the European surveillance of congenital anomalies (www. eurocat-network. eu/) with 43 registries in 23 countries surveying more than 1. 7 million births per year in Europe. The Neuroviruses Emerging in the Americas Study (NEAS) is a collaborative network leading a multi-center study in the Americas to establish a comprehensive registry of the clinical, radiological and laboratory profile of patients with new onset of neurological disorders associated with Zika virus infections (www. neasstudy. org) (Figure  3 ). Given the links of ZIKV with Guillain-Barre Syndrome (GBS), the International GBS Outcome Study (IGOS) is a particularly important network coordinated by ZikaPLAN partner Erasmus University Medical Center in Rotterdam, The Netherlands  [9]. IGOS coordinates clinical data on GBS and biobanks, thereby aiming to identify clinical and biological determinants and predictors of disease course in GBS.
Analyses based on the pregnancy cohort data are underway to determine the spectrum of risks associated with ZIKV infections in pregnancy and to compare the attack rate of CZS by gestational week of infection and region. In addition to conducting detailed epidemiological analyses within each of the three ZikaPLAN study sites, our team of investigators is also leveraging our data in order to contribute to a series of individual participant data meta-analyses (IPD-MAs). These IPD-MAs include: (i) the Consórcio Coortes Brasil, which is informing ZIKV epidemic preparedness policies in Brazil, (ii) the pooled analysis of results from the EU-funded Zika Consortia, which is facilitating the sharing of best practices and epidemiological methods across the research consortia, and (iii) the WHO-led ZIKV IPD Consortium, which is enabling global pooling of data across all eligible studies  [13].
By pooling participantlevel data across studies, these IPD-MAs will increase the statistical power for assessing the risks associated with ZIKV infection within potentially important clinical subgroups, such as dengue co-infected pregnant women. Further, by including a diversity of populations, these collaborative data-sharing efforts will allow for meaningful investigations into the sources of heterogeneity in the current estimates of absolute and relative risks of adverse outcomes associated with congenital ZIKV infections. The protocol for the IPD-MA of longitudinal studies of pregnant women and their infants and children has meanwhile been published  [13]. Because the ZikaPLAN-affiliated study sites represent some of the first research teams to investigate microcephaly, we are privileged to be able to follow some of the world`s largest cohorts of children with CZS.
The unusual clusters of ZIKV associated GBS were first described by other groups in French Polynesia  [26]. We expanded the already existing IGOS, the largest global observational cohort study on GBS  [9] , to establish a case-control study for Zika (IGOS-Zika), that is now running in nine hospitals across three countries (Brazil, Argentina, Malaysia). International data and sample collection were further standardized by sharing the IGOS protocol with networks in Latin America (NEAS, CDC, Zika Neurology Network)  [27]. The IGOS database will also facilitate the comparison between ZIKV-related GBS and GBS after other infections. Additionally, collaborations with local neurologists in Recife, Brazil, are ongoing to describe a GBS cohort collected early in the ZIKV outbreak. As clinical guidelines for the management of GBS are currently lacking  [28] , we developed a globally applicable consensus report in collaboration with international and local experts to support the diagnosis and management of GBS.
This guideline, as well as results from an ongoing survey amongst Brazilian neurologists, will be used to develop training material and courses in collaboration with The Global Health Network. It is important to discover and characterise the mechanistic pathways of ZIKV infection in the pathogenesis of central (CNS) and peripheral nervous system (PNS) injury, focusing on both direct viral invasion, and the immune and autoimmune responses to viral infection. ZIKV tropism in the peripheral and central nervous systems (PNS and CNS, respectively) has now been defined in vitro and these data are guiding progress through in vivo work in which a neurological phenotype is also seen. We found the resistance of Schwann cells to infection, compared with CNS cells  [29]. Different viral isolates show different tropisms for nervous system cells.
A network of sites provides the framework for a global biobank and quality laboratories for multi-site evaluations with rapid data collection, analysis and reporting. Standardized panels are representative of different geographic areas. Two of these commercial assays have been evaluated at three study sites in Colombia, Senegal and Thailand, and which were designed to detect patients' specific anti-ZIKV IgG and IgM antibodies. Additional four or more assays will be evaluated in 2019. While the results are still pending, this approach reduced the time for test evaluations and hence can resolve the bottleneck for market entry of ZIKV diagnostics. To enhance diagnostics development, ZikaPLAN has been actively involved in characterizing humoral and T cell responses. Through comparisons of known epitope sequences in their native structural conformations on target proteins from other flaviviruses with the corresponding sequences of ZIKV, candidate-conserved and cross-reactive ZIKV B-cell epitopes were identified on the E and NS1 proteins, while these ZIKV T cell epitopes were identified in the NS3 and NS5 protein sequences  [32].
Investigating the evolution of the Zika epidemic Analyses of viral genomes with ecological and epidemiological data yield an estimate that ZIKV was present in Northeast Brazil by February 2014 and is likely to have disseminated from there, nationally and internationally, before the first detection of ZIKV in the Americas  [45]. This was corroborated by a ZikaPLAN`s modeling study  [46]. Collating information on confirmed and suspected Zika cases across Latin-American countries [https://github. com/ kath-o-reilly/Zika-LAC-Outbreaks] a spatio-temporal dynamic transmission model for ZIKV infection was used to project its incidence in 90 major cities within 35 countries. A key output from the model included the clear demonstration that the ZIKV epidemic predominantly finished before 2018, with potential for only small pockets of low numbers of infections occurring in the region since  [47].
This project, ZikaPLAN is funded by the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 734584. Some authors have received additional research funding. For example, TS is supported by the National Institute for Health Research (NIHR), Health Protection Research Unit in Emerging and Zoonotic Infections (Grant No. IS-HPU-1112-10117), and NIHR Global Health Research Group on Brain Infections (No. 17/63/110). MERG as a group has received funding from Wellcome Trust UK, Department for International Development UK, Medical Research Council UK, the Brazilian funding through CNPq, Secretaria de Vigilância de Saúde (SVS), and Fundação do Amparo a Ciência e Tecnologia (FACEPE).
Acknowledgments We acknowledge all our consortium members and their institutions, as listed above, and we are thankful to many other institutional staff members (all the administrators and financial managers) who participate and support the implementation of the  ZikaPLAN  project in different capacities. We are grateful to our Scientific Advisory Board members ( Duane Gubler ,  James Sejvar ,  Herman Goossens ) and  Ethics Advisory Committee member (Anna Durbin)  for their timely support and guidance at various stages of the project so far. We appreciate our collaborative work with  ZIKAction  (Grant Agreement No. 734857 ) and  ZIKAlliance  (Grant Agreement No. 734548 ) which allows advancing common efforts and strengthening the research output. Our utmost thanks go to  Professor Laura C.
Comparison of RNA-seq data from input RNA fraction and heart-specific TU-fraction from control Hand>LacZ;UPRT flies was used to assess the suitability of TU-tagging in low-abundance heart cells. We found that transcripts of cardiac-specific genes such as Hand and Tin were highly enriched in the cardiac-tagged TU fractions, whereas the transcripts of Npc1b and Obp19b genes expressed in midgut  (Voght et al. , 2007)  and gustatory cells  (Galindo and Smith, 2001) , respectively, were depleted (Figure  2B ). Thus the TUtagging method proved well-suited to the transcriptional profiling of adult Drosophila cardiac cells, allowing the identification of both global gene deregulations (analyzed here) and isoform-specific differential gene expression (in a parallel study).
Optical heartbeat analyses of adult Drosophila hearts To assess cardiac physiology in adult flies, we used the method previously described  (Fink et al. , 2009; Ocorr et al. , 2007). Briefly, 1 week old flies were anesthetized using FlyNap (# 173025, Carolina), and then dissected in artificial hemolymph solution, removing head, legs, wings, gut, ovaries and fat body. The hearts were allowed to equilibrate with oxygenation for 15-20 min prior to filming 30 s movies with a Hamamatsu camera (>100 frames/s) under a Zeiss microscope (10X magnification). Movie analysis was performed with SOHA (semi-automatic optical heartbeat analysis) based on using Matlab R2009b (Mathworks, Natick, MA, USA) to collect contractility (diastolic and systolic diameters, fractional shortening) and rhythmicity (heart period, diastolic and systolic intervals and arrhythmicity index) parameters.
Data analysis The RNA-sequencing data were checked for good quality using the FastQC package (http://www. bioinformatics. babraham. ac. uk/projects/fastqc/). Each sample was aligned to the reference Dmel genome release 5. 49 using Bowtie2  (Langmead and Salzberg, 2012). The aligned reads were sorted and indexed using SAMtools  (Li et al. , 2009). Pearson correlation was determined for each duplicate of each condition. Differential gene expression was obtained using a pipeline based on the Deseq2 package. Rlog transformation was applied on raw count data obtained for the duplicates of each condition before computing differential expression. Genes were tested individually for differences in expression between conditions. We set a fold-change threshold at 1. 7 and p-value threshold at 0. 05 for meaningful differential up-expression, and fold-change threshold at 0.
Statistical analyses and access to RNAseq data All statistical analyses were performed using GraphPad Prism v5. 02 software (GraphPad Inc, USA). Fisher's exact test was applied to analyze statistical significance of conduction defect phenotypes, and Mann-Whitney U test to analyze RT-qPCR data from mouse and human heart samples and Western blot a2d3 expression data in human samples. We also applied one-way ANOVA, Kruskal-Wallis Dunn's multiple comparison post-test to statistically analyze RT-qPCR data for stj isoforms and changes in diastolic and systolic heart diameters. All RNAseq data reported here were deposited with the GEO-NCBI tracking system under accession number #18843071.
The geology of the canyon and surrounding shelf is captured by video footage and observations recorded in the dive event logs. A suite of bathymetry maps were generated post-cruise at different spatial resolutions (see below), which depict the overall canyon system as well as localized topographic features at each of the ROV dive locations where sampling was undertaken. Additional geological information has been gathered from spot sampling of rocks and sediments from the substrate, canyon walls, and plateau. A list of all samples collected during the cruise encompassing seawater, biological, and geological samples as well as complementary datasets are reported in the SOI Cruise FK150301 Final Report 1  (McCulloch et al. , 2017). The dive numbers in the figures and tables relate to the nine ROV survey and faunal collection dives only, so are offset by one from SOI D07 that was the USBL recovery dive.
Multibeam Bathymetric Analysis High-resolution bathymetric data were acquired using Kongsberg EM 302 and 710 multi-beam echo sounders. Post-cruise, bathymetry maps of the canyon and all dive sites were generated at different spatial resolutions. The multi-beam echo-sounder data was processed using CARIS HIPS and SIPS 7. 0 software. After loading raw data and applying tide corrections, the data were 'cleaned' using the Swath Editor that consists of interactively selecting and rejecting soundings as well as filtering functions, which automatically detected and rejected outliers. Following data correction and cleaning, a digital terrain model (DTM) was generated at 20 m resolution for the entire canyon (Figure  1 ), and at 10 m resolution for the ROV dive areas (Figures  2 3 4 ). The DTMs were exported in ASCII ESRI format and analyzed with ArcGIS 10.
Seawater DIC was measured on board using an Apollo SciTech Dissolved Inorganic Carbon analyzer. Dissolved inorganic nutrients, including ammonium (NH 4 + ), nitrate+nitrite (commonly referred to as just 'nitrate' or NO 3 -), phosphate (HPO 4 2-), and silica [Si(OH) 4 ] were analyzed at the University of Western Australia on a Lachat autoanalyzer using standard spectrophotometric methods. Seawater pH, pCO 2 , calcite saturation state ( calcite ), and aragonite saturation state ( aragonite ) were calculated postcruise using MATLAB version 1. 1 of the CO2SYS software  (van Heuven et al. , 2011). Stable C and O isotope measurements of 29 seawater samples from five sites (A: n = 9, B: n = 9, E: n = 11) were undertaken in the West Australian Biogeochemistry Centre at The University of Western Australia.
Accelerator mass spectrometry (AMS) 14 C analysis was conducted using the STAR facility at ANSTO  (Fink et al. , 2004) , with a typical analytical precision of better than 0. 35% (1σ). Oxalic acid I (HOx-I) was used as the primary standard for AMS 14 C determination, and oxalic acid II (HOx-II) and IAEA-C7 reference material were employed as secondary standards. The AMS results are presented in 14 C, the per mil deviation from the absolute radiocarbon standard  (Stuiver and Polach, 1977). CTD-Rosette data were visualized using the Ocean Data View software (version 4. 7. 10), and all graphs of seawater parameters discussed above have been generated using this program.
Supplementary Oceanographic Data The Perth Canyon region includes a range of oceanographic infrastructure that has been established as part of the Australian Integrated Marine Observing System (IMOS) and an overview of the different data streams is provided in  Mihanović et al. (2016). These include oceanographic moorings that contain Acoustic Doppler Current Profilers (ADCP), surface currents measured by HF Radar, sea surface temperature from satellites and ocean glider transects. Data streams collected during the period of the RV Falkor voyage were abstracted from the IMOS data portal 2. Hourly data collected by the HF Radar systems were averaged over 24 h for March 9, 2015, and was overlain over the satellite derived sea surface temperature image for that date. Velocity profiles over the period March 1-15, 2015, from within the canyon were available from an IMOS mooring located in ∼500 m water depth (31.
7867 • S 114. 9400 • E). The Teledyne RDI Workhorse Long Ranger 75 kHz instrument was mounted on the sea bed and collected data at 15-min intervals in 16 m bins through the water column from 48 to 480 m from the seabed. Ocean gliders are autonomous vehicles that utilize a buoyancy engine to move through the water column in a saw-tooth pattern  (Pattiaratchi et al. , 2017). During the RV Falkor voyage a Seaglider, developed by the University of Washington was deployed in the Perth Canyon and undertook east-west transects to a maximum depth of 1,000 m. The sensors on the Seaglider included those for temperature, salinity, and DO (Seabird Electronics SBE41 CTD and SBE 43 DO sensor) and optical sensors for Chlorophyll fluorescence (BBFL2SLO 3 parameter optical sensor). IMOS data streams are provided in NetCDF-4 format with ocean glider data files containing meta-data and scientific data for each glider mission.
ACKNOWLEDGMENTS The authors gratefully acknowledge the  Schmidt Ocean Institute  for providing the RV Falkor and all necessary equipment and crew that enabled us to undertake this cruise ( FK150301 ). The Falkor crew and the ROV pilots from  Neptune Marine Services  are thanked for their expert assistance during the cruise. Kai Rankenburg  ( UWA ) is thanked for assistance with  U/Th  mass spectrometry. Ana Hara ,  Jane Fromont ,  Oliver Gomez ,  Lisa Kirkendale ,  Glenn Moore , and  Corey Whisson  (from  WAM ) are thanked for assistance with identifications and specimen processing. The ocean glider and HF Radar data were collected by the  IMOS Ocean Glider and ocean Radar facilities located  at the  University of Western Australia. The mooring data used in this paper were collected by the  CSIRO , a sub-facility of the  Australian National Mooring Network (ANMN).
Background Biomass degradation is an essential yet complex process in nature, particularly for degrading the plant cell wall  [1]. This structure is a highly heterogeneous material mainly composed of cellulose, hemicellulose, lignin and pectin, whose degradation is achieved through multiple means, including the use of enzymes with different and complementary activities  [2] [3] [4]. The secretion of such a wide variety of enzymes is the hallmark of filamentous fungi  [1, [5] [6] [7] [8]. Part of these enzymes are designed 'carbohydrate-active enzymes' (CAZYmes) and are compiled into the Carbohydrate Active Enzymes database (http:// www. cazy. org/; [9] ). They are assigned into five enzyme classes, including Glycoside Hydrolases (GH) and Auxiliary Activities (AA). This classification relies on amino acids sequence similarity, secondary and tertiary fold conservation, and stereochemical architecture of catalytic mechanisms.
Glucose repression Fig. 3  Focus on FC values during carbon starvation and after glucose addition. 'Carbon starvation': Shift of the mycelium from glucose medium to medium without carbon source (glucose condition used as calibrator sample; RT-qPCR data from this study); 'Glucose repression': addition of glucose to mycelium grown on wheat straw for 24 h (wheat straw condition as calibrator sample; RNA-seq data from a previous study  [59] ). The box-plot gathers log 2 (FC) values of the 62 GOIs (i. e. those presented in the 'C starvation' line in Fig. 2 , and those reminded in the Additional file 1 for the 'glucose repression' condition) T. versatilis by using a strain that carries 9 copies of xlnR under the control of its own promoter (xlnR + strain), as determined by a digital droplet PCR assay on genomic DNA.