dataesr/scientific-paragraphs-categorization huggingface dataset:
Tissue analysis was performed on several animals (two to three per group, except for asymptomatic animals). For GFAP and Iba-1 immunolabelings, several tissues sections (n = 3-9) were analyzed per group of animals. GFAP-positive cells were quantified by measuring the intensity of the labeling once the background was subtracted, using the Fiji software (2. 0 version 2. 0; National Institutes of Health, Bethesda, MD)  (28). A global threshold was applied to the image for intensity measurement. The values are expressed as mean ± SEM and normalized by surface unit in square millimeters. Iba-1-positive cells were counted using the Fiji software and expressed as mean cell number ± SEM and normalized by surface unit in square millimeters.
Software and statistical analyses Kaplan-Meier survival curves were done using the GraphPad Prism software (La Jolla, CA). Animals inoculated by ip route and fed the chow diet (first and second set of experiments) were analyzed as a single group. The difference between curves was tested using the nonparametric Mantel-Cox test, with a probability of 0. 05 defined as a significant difference. Survival times are expressed as median values and lipid levels are expressed as mean ± SEM. The statistical significance of differences between data means was determined with a Student's t-test or a two-way ANOVA analysis, as appropriate.
This study was supported by grants from  Institut National de la Santé et de la Recherche Médicale (INSERM)  and the  Agence Nationale de la Recherche (ANR)  under the program " Investissements d'Avenir " with reference  ANR-11-LABX-0021-LipSTIC. Additional support was provided by a fellowship from the  China Scholarship Council  under the  PHC CAI YUANPEI 2014-16  project number  32106RD  to  Y. W.  Author 's Choice-Final version free via Creative Commons CC-BY license.
Acrodiscus Zanardini is a poorly known monotypic endemic Mediterranean genus based on A. vidovichii (Menegh. ) Zanardini. Rarely reported, its reproductive structures have remained undocumented, leaving its exact taxonomic position uncertain. Solely on the basis of its vegetative structure, Zanardini provisionally placed it in the family Cryptonemiaceae of the order Cryptonemiales (currently the Halymeniaceae of the Halymeniales), although he was uncertain as to whether the new genus actually belonged to that family or should instead be included in the Gigartinaceae of the Gigartinales (where Meneghini had originally placed it). In the present study we have extensively sampled A. vidovichii and documented its vegetative and tetrasporangial features. As well, we provide molecularsequence data (COI-5P, rbcL, LSU) that indicate its phylogenetic affinities.
Herbarium designations are given as directed by the Index Herbariorum (Thiers continuously updated). For morpho-anatomical observations, thalli were hand-sectioned with single-edged razor blades, stained with 1% aniline blue, and observed using a Nikon Optiphot-2 equipped with a Nikon Coolpix 4500 camera (Leica Microsystems, Italy). Sequence data generated for COI-5P, rbcL and LSU genes were submitted to BOLD (http://www. barcodinglife. org) and to GenBank  (Clark et al. 2016). Accession numbers, together with collection information, are given in Table  1. DNA extraction was performed as outlined in  Manghisi et al. (2010b). The barcode region COI-5P was PCR amplified as detailed in  Saunders & McDevitt (2012) , the nuclear LSU rRNA gene was PCR amplified as detailed in  Harper & Saunders (2001) , and the plastid rbcL gene was amplified with various primer combinations as specified by  Freshwater & Rueness (1994)  and  Wang et al.
(2000). Sequences were generated using the BigDye Terminator v. 3. 1 Cycle Sequencing Kit (PE Applied Biosystems [ABI], Foster City, CA, USA) and analyzed using an ABI Prism 3130XL genetic analyzer at    the CEMAR, University of New Brunswick, Canada, or an ABI Prism 3730XL at the Genoscope (www. genoscope. fr) in Evry, France. Forward and reverse sequence reads were assembled into contigs with the software  ChromasPro (v. 1. 7. 6. 1, Technelysium Pty Ltd)  and edited. Multiple sequence alignments were constructed in  SeaView v. 4. 3. 3 (Gouy et al. 2010)  and included both data from GenBank and sequences generated for the present study. Newly generated COI-5P sequences were subjected to distance analysis in PAUP*  (Swofford 2002). For rbcL analyses, an initial alignment of 728 sequences and 1258 nucleotide positions was subjected to neighbor-joining (NJ) distance analysis under a K2 nucleotide substitution model in PAUP* to identify species groups.
GenBank accession numbers of sequences used for the final alignments are listed in Table  3. All phylogenetic analyses were performed in MrBayes v. 3. 1. 2 or 3. 2. 1 (parallel version;  Altekar et al. 2004; Ronquist & Huelsenbeck 2003) , RAxML (online version, http://embnet. vital-it. ch/raxml-bb/; Stamatakis et al. 2008) , and PhyML 3. 0 (online version, http://atgc. lirmm. fr/phyml; Guindon & Gascuel 2003). Maximum Likelihood analyses were performed with bootstrap resampling to estimate robustness of the internal nodes  (Felsenstein 1985) , based on 1000 replicates in PhyML, with a GTR+G+I substitution model (with all parameters estimated during the search), starting from ten random BIONJ trees  (Gascuel 1997)  with subtree pruning and regrafting (SPR) as branch-swapping algorithm. Furthermore, Maximum Likelihood (ML) analyses were also performed with bootstrap resampling based on 100 replicates in RAxML, with a GTR+G+I substitution model with three partitions for rbcL, corresponding to each codon position, and with four partitions for the concatenate analyses corresponding to LSU and each codon position of rbcL.
For Bayesian inference both the rbcL and the concatenate data sets were also partitioned as above. The covarion-like model  (Huelsenbeck 2002)  was combined with the GTR+G model of sequence evolution linking or unlinking parameters among partitions (shape, statefreq, revmat, switchrates, Tratio) and setting the prior for the site specific rates as "variable". Different analytical strategies were tested in order to reach convergence. Each analysis consisted of two parallel runs, each run using four chains, one cold and three incrementally heated. A single run consisted of 5 million generations that were sampled every 1000 th tree. After completion of the two runs, likelihood values were plotted against the number of generations to evaluate when MCMC chains reached stability, in order to set an appropriate burn-in value for each analysis.
Phylogenetic analyses The DNA barcode region was generated for 15 samples from different Mediterranean localities, including the type area; the sequences are now lodged in BOLD and Genbank (Table  1 ). Divergence among generated sequences ranged from 0-3 bp (0-0. 53%), which is a typical level of within-species variation. Phylogenetic analyses inferred from both rbcL and LSU markers (Fig. 8.
List of sequences from GenBank used in phylogenetic analyses. Memorie del Reale Istituto Veneto di Scienze, Lettere ed Arti 14: 201 (1868). -Chondrus? vidovichii Menegh. in Savi, Sezione di Botanica, e Fisiologia Vegetabile, Adunanza del dì 16 Settembre 1841.
Acknowledgements Acquisition of molecular data was carried out at the  CNRS-UMS 2700 in Service de Systématique Moléculaire, MNHN, Paris. This project was supported by the network 'Speed ID' and 'Bibliothèque du Vivant ' funded by  CNRS ,  Muséum national d'Histoire naturelle, INRA  and  CEA  ( Centre National de Séquençage ) with funds provided by the ATM ' Taxonomie moléculaire: DNA Barcode et gestion durable des collections '. A. M. was the recipient of a postdoctoral grant by the  Research in Paris 2010 program  from the city of Paris. The authors want to thank  José M. Utge ,  Luca Lavelli ,  Jordi Rull  and  Noemi Salvador  for their help in collecting the samples. We acknowledge the following curators of herbaria for their assistance:  Jenny Bryant  (retired,  Natural History Museum, London, UK ),  Florence Rousseau and Bruno de Reviers  ( Muséum national d'Histoire naturelle, Paris, France ),  Nicolien Sol  and  Herre Stegenga  ( Nationaal Herbarium Nederland, Leiden University, Leiden, the Netherlands ),  Chiara Nepi  ( Herbarium Universitatis Florentinae, Natural History Museum, Florence, Italy ),  Raffaella Trabucco  ( Natural History Museum, Venice, Italy ),  Rossella Marcucci  ( Herbarium Patavinum, Padua, Italy ),  Lucia Amadei  and  Simonetta Maccioni  ( Herbarium Horti Pisani, University of Pisa, Italy ), as well as the librarians  Giovanna Ciulli  and  Barbara Lapucci  ( Library of Natural and Enviromental Sciences, University of Pisa, Italy ).
identification Collection locality Collection date Collector(s) Notes BOLD Process ID / GenBank accession no. KJ594944 a -KJ594947 b -KJ594952 c ACROV001-16 a,c REDEU456-11 a REDEU466-11 a REDEU488-11 a,c REDEU539-11 a REDEU544-11 a REDEU575-11 a REDEU580-11 a REDEU590-11 a REDEU604-11 a ACROV004-16 a - - - - - Tetra- sporic - - - - - - - - J. M. Utge, L. Le Gall J. M. Utge, L. Le Gall L. Le Gall, Y. Turpin L. Le Gall, F. Rousseau L. Le Gall, F. Rousseau L. Le Gall, J. M. Utge L. Le Gall, J. M. Utge L. Le Gall, J. M. Utge L. Le Gall, J. M. Utge L. Le Gall, J. M. Utge L. Le Gall, J. M. Utge L. Le Gall L. Le Gall 20 Jun. 2007 20 Jun. 2007 19 Oct. 2008 20 Oct. 2008 20 Oct. 2008 7 Jun. 2009 7 Jun. 2009 8 Jun. 2009 8 Jun. 2009 9 Jun. 2009 9 Jun. 2009 3 Oct. 2011 3 Oct. 2011 Vis, Croatia Vis, Croatia La Gabinière, Port Cros, France Montremian, Port Cros, France Montremian, Port Cros, France Montremian, Port Cros, France Montremian, Port Cros, France La Gabinière, Port Cros, France La Gabinière, Port Cros, France La Gabinière, Port Cros, France La Gabinière, Port Cros, France Corsica, France Corsica, France LLG0393 PC0152091 LLG0394 PC0152089 LLG2193 PC0152957 LLG2223 PC0152936 LLG2246 PC0152915 LLG2549 PC0162311 LLG2560 PC0162425 LLG2717 PC0162264 LLG2733 PC0162395 LLG2801 PC0162435 LLG2846 PC0162436 LLG4197 PC0145757 LLG4209 PC0145758.
Voucher identification Collection locality Collection date Collector(s) Notes BOLD Process ID / GenBank accession no. ACROV003-16 a,b,c - - ACROV002-16 a - - ACROV005-16 a - - - - - - - - - - - - - - - - - Tetra- sporic - A. Manghisi L. Le Gall, J. M. Utge L. Le Gall, A. Manghisi, M. Morabito L. Le Gall, J. M. Utge L. Le Gall, J. M. Utge L. Le Gall, J. M. Utge L. Le Gall L. Le Gall A. Manghisi, L. Lavelli, J. Rull, N. Salvador A. Manghisi, L. Lavelli, J. Rull, N. Salvador A. Manghisi,J. Rull, N. Salvador J. Rull, N. Salvador A. Manghisi, J. Rull, N. Salvador 29 Jun. 2005 13 Apr. 2011 17 Apr. 2011 18 Apr. 2011 18 Apr. 2011 21 Apr. 2011 7 Sep. 2011 7 Sep. 2011 22 Jun. 2003 23 Jun. 2003 2 Jun. 2004 3 Jun. 2004 4 Jun. 2004 Scilla, Reggio Calabria, Calabria, Italy Capo dell'Armi, Reggio Calabria, Calabria, Italy Scala dei Turchi, Agrigento, Sicily, Italy S.
Voucher identification Collection locality Collection date Collector(s) Notes BOLD Process ID / GenBank accession no. - - - - A. Manghisi, J. Rull, N. Salvador N. Salvador, J. Rull A. Manghisi, N. Salvador, J. 5 Jun. 2004 9 Jul. 2004 7 Jul. 2004 cala Figuera (Norte), Mallorca, Spain P. ta Colibre, I. Columbret Gran, Illes Columbrets, Castelló de la Plana, Spain Freu de Terra, Hospitalet de l'Infant, Tarragona, Spain BCN-Phyc 5906 BCN-Phyc 5907 BCN-Phyc 5908.
METHODS An electronic search of peer-reviewed scientific and medical literature published between January 1954 and September 2016 in Chinese and English was conducted using PubMed (MEDLINE), CNKI (China National Knowledge Infrastructure), VIP (Chongqing VIP Database), and CSPD (China Science Periodical Database, Wan Fang) and Web of Science databases. Gray literature and programmatic documents were also searched using Google, Google Scholar and other search engines using the same search terms. The following search terms (or their Chinese equivalents) were used: Anopheles sinensis, distribution, biology, bionomics, molecule, ecology and China. The decision tree for the inclusion or exclusion of articles is shown in Figure  1. Only publications reporting biology, bionomics, and molecules of An.
sinensis from China were included. Articles submitting a report on morphology, development, reproductive, life cycle, vector competence, larval and adult ecology, vector capacity, molecules involved in physiology and pathology were included. Studies involving insecticides were excluded because it would be the focus of a future review. These data were extracted and processed through a series of rigorous checking procedures before classification into a database. All results were initially reviewed for mosquito bionomics (larval and adult ecology), biology and related molecular studies based on the title and abstract. Relevant publications were further reviewed using the full text to determine whether the data focused on distribution, bionomics, epidemiology, vector competence, or identified molecules.
RESULTS Figure  1  illustrates the search results. The initial search strategy generated 1469 records. After first round review of titles and abstracts, a total of 824 articles were amalgamated for review. After removing 44 duplicates, 722 relevant publications were further reviewed based on the full text to find out whether primary or secondary data on the biology, bionomics, molecules. Finally, a total of 538 papers and reports met these criteria. Selected articles were saved in Endnote and their characteristics corresponding to the criteria manually entered into Microsoft Excel for ongoing data management. From these articles, we assessed risk of bias for included studies but did not exclude studies on the basis. The outcomes of analysis by study area are outlined below.
BIONOMICS Distribution Anopheles sinensis has been recorded from Afghanistan, Myanmar, Cambodia, China, Indonesia, India, Japan, Korea, Malaysia, Singapore, Thailand, and Vietnam  (Reid, 1953). It is distributed in 29 provinces within China and all regions except Xinjiang and Qinghai provinces  (Lu et al. , 1997). Xu and Feng (1975)  published the first national distribution of the Anopheles hyrcanus complex in China including An. sinensis. The report primarily consisted of a brief survey of egg, larval, pupa and adult stages around the surveyed sites during 1962-1965. The results were limited to a short description of the main bionomic characteristics. In the present review, an An. sinensis distribution map was produced by overlaying occurrence data from 332 source collected reports. An. sinensis was the mosquito taxon most commonly found and identified in China.
Seasonal Population Fluctuation In almost all areas in China, An. sinensis was found from July to December with a population peak in August. The population density of An. sinensis in cow sheds had a June peak in most places with a second small peak in late August or September. In Heilongjiang, Jilin, Liaoning and Xizang, An. sinensis was recorded only in August and September after which no specimens were found due to cold weather. In some warmer provinces like Yunnan, active An. sinensis were present in December but in relatively small numbers. In general, the collection data showed the seasonal abundance of An. sinensis fluctuated monthly (temperature-driven model) at various study sites during different study periods. An. sinensis emerged in April, developed into large populations from July to December with a peak in August.
Larval Habitats Anopheles sinensis larvae were found in diverse habitats. Examples of major habitats include rice-fields and ponds  (Liu et al. , 1962). The larvae were also collected in irrigation channels, abandoned wells, ground pools, and pools beside rivers, marshes, stream margins, ditches, seepages, shallow ponds, sumps, hoof footprints, and wheel tracks. The larvae have also been found in polluted pools and cesspits  (Cai, 1959). Environmental factors associated with larval habitats have been studied. The available data  (Anonymous, 1973b; You and Xu, 1979; Chen, 1990)  observed that the breeding sites of An. sinensis were located within 50-200 m from irrigation wells, human or livestock settings, and the larvae were most often found in water bodies with abundant aquatic vegetation.
Biting Habits and Feeding Preferences Female An. sinensis fed throughout the night but were most active from sunset to midnight. Peaking feeding activity apparently occurred at different times depending on locality and habitats. Cai (1959)  showed that An. sinensis in human dwellings fed from dusk to dawn, with two peaks one between 8:00 pm and 9:00 pm and another at 1:00 am. In cow sheds, only one peak occurred at 8:00 pm. Chen et al. (1979)  observed peak activity in Henan province occurring between 8:00 pm to 9:00 pm. Peak activity in Zhejiang province was from 9:00 pm to 10:00 pm  (Zhang et al. , 1990). Similar peak activity has been recorded in several other areas of China and during different time periods. Considering that these data were somewhat dated, we examined the most recent studies conducted between 2013 and 2014 in Hunan Province  (Zhu et al.
This could be partially explained by the differences in the investigation periods and the methods used in An. sinensis collection, such as larval collection tools, light traps, and human baited trap. Adult An. sinensis have been incriminated as a natural and experimental malaria (P. vivax) vector in China, Indonesia, Japan, and South Korea  (Ree, 2005). The known published data on An. sinensis host selection in China indicated that the degree of anthropophily of An. sinensis was low, and it was generally concluded that An. sinensis is not an effective malaria vector, especially in northern China. However, since 1960, uninterrupted malaria cases have occurred in central China, where An. sinensis is the only vector in most areas, thus it is difficult to explain why An. sinensisis appears to be an effective malaria vector in these areas.
Sensitivity of the cells to a combination of variables We evaluated the four coding spaces using standard measures employed in rodents: the information content per spike (IC) and a sparsity index  [3, 6, 24]. The first quantity documents how much spatial information a spike conveys, while the second expresses spatial selectivity. To compare IC across coding spaces, we ensured that the same number of bins was used across cells and spaces and normalized IC with respect to the average IC of 999 surrogate datasets generated by randomly shuffling periods of spiking activity in time (see Materials and Methods). While this method may be conservative  [25] , it is widely used in rodent literature (e. g. ,  [1] [2] [3] [4] [5] [6] [7] ) as it effectively conveys information relative to the spatial distribution of the cell's activity  [26].
Statistical significance was tested by comparing measures derived from actual data with those in the 999 surrogate datasets. Significant IC (p < 0. 01) was present in at least one of the spaces for 111 out of the 189 cells (59%, responsive cells). The proportion of cells responsive to each space was significantly unequal (chi-squared test, p = 0. 014). The state space accounted for the largest number (84 cells, Fig 3A ), and pitting state space against the other three, there were more cells responsive to state space than to point of gaze (chi-squared test, p = 0. 012, Bonferroni corrected; the differences between state space and other spaces did not reach statistical significance). Sensitivity to these four variables was not mutually exclusive  (Fig 3B). Note that the simple difference of space dimensionality does not account for this IC difference (S1 Appendix, A5).
Hippocampal cells encode a fine-grained state-space representation of the maze How well does a coding space account for cell activity? As a majority of cells were responsive in the state space, we took this space as a reference. Then, for each cell, we compared the difference between the normalized index computed in state space and the corresponding normalized index in another coding space, considering only cells responsive in both spaces. Normalized indexes were obtained by subtracting the average indexes obtained from the surrogate data from the raw indexes in order to prevent any bias due to space structure. The joint distribution of these differences in IC and sparsity is illustrated in. The spike information content for the state space was systematically higher when compared to position, direction, or gaze space (Wilcoxon, all p < 0.
Inset: Distribution of the correlations between directional tuning in the center and in the periphery. Significantly high (red) and low (blue) correlations are indicated. D-F. Difference in information per spike versus difference in sparsity when comparing cell activity readout in state space to activity readout in position space (D), direction (E), and point of gaze (F). Same graphical conventions as in C. Statistical significance was obtained with permutation tests (surrogate spike datasets). Underlying data can be found at http://dx. doi. org/10. 6080/K0R49NQV. doi:10. 1371/journal. pbio. 2001045. g003 cells have a fine-grained representation of space that integrates position, direction, and point of gaze into a higher order trajectory representation.
The distribution of the latencies of the responses to the best landmark are left skewed when aligned on gaze and right skewed when aligned on landmark onset (Fig 7F, see Materials and Methods). For a small but nonnegligible proportion of cells, the response latency even preceded the landmark's entry in the FOV, suggesting a predictive representation of its location in space prior to becoming visible. To further examine the nature of this anticipatory activity, we analyzed the cell activity with respect to the eccentricity (distance in degrees to the fovea) of the best-driving landmark. We computed the population average, considering four different subsamples of the data: (1) all the 500 ms epochs that followed landmark appearance in the visual scene, (2) all the 500 ms epochs that preceded landmark appearance, (3) periods starting when the landmark had been visible for at least 1,000 ms, or (4) the whole dataset.
Cells fired in anticipation of the landmark (purple), but activity was higher if the monkey had previously made a saccade close to its expected point of appearance. Dashed line: average firing rate. Note that the vertical scale does not begin at zero. H. Landmark selectivity indices calculated for activity aligned on landmark appearance when gaze was not directed to them versus activity aligned on landmark foveation following its appearance. I. Same as H for the path selectivity index. Underlying data can be found at http://dx. doi. org/10. 6080/K0R49NQV. doi:10. 1371/journal. pbio. 2001045. g007 and an action but rather expressed self-position in an abstract, multidimensional representation of the maze.
Data analysis All data were analyzed with custom Matlab scripts. Activity maps. We computed each cell's mean firing rate for each spatial bin, simply dividing the number of spikes recorded in that bin by the total time spent in it. Only bins comprising at least four successful trials were kept. For display (Figs  2  and 4 ), a smoothing procedure was applied: the instantaneous firing activity was slightly smoothed with a Gaussian kernel of SD = 100 ms before computing the map. When comparing spaces, no smoothing was used and bin sizes were adjusted so that each map contained a similar number of bins (~200). Permutation statistics. To test the statistical significance of any index computed on the spike data, we created 999 surrogate data sets in which we divided the recording time into chunks of 5 s that we randomly shifted.