dataesr/scientific-paragraphs-categorization huggingface dataset:
The bacterial and fungal alpha diversities in soil and inside plant tissues were compared using a two-way ANOVA test with the "aov" function. When the bacterial soil data failed to meet the assumptions of parametric ANOVA after log, square root, and several power transformations, the non-parametric Kruskal-Wallis one-way test of variance was performed with the "kruskal. test" of the "pgirmess" package. A multiple comparison test, post hoc was then performed between treatments using "kruskalmc" functions of the "pgirmess" package in order to distinguish which treatments were significantly different from one another. An indicator species analysis was performed based on the IndVal index to identify microbial OTUs that were significantly correlated to high contamination using the "multipatt" function in the "labdsv" package.
). The ACSM was used to measure mass concentrations of particulate ammonium, nitrate, sulfate, chloride, and organic species in the submicron size range. Mass calibration was obtained by sampling monodisperse ammonium nitrate and ammonium sulfate. The instrument collection efficiency was calculated to be 1 during BUNIAACIC, through the comparison of the mass concentration of species measured by the ACSM and MAAP (black carbon equivalent; BC e ) with the integrated mass of the SMPS. Further instrumental details and data post-processing is given by  Brito et al. (2014). A weather station (Davis, USA) at the top of the tower provided meteorological data (wind speed and direction, temperature, RH, etc. ). As well as the instruments in the container, a wide issue bioaerosol sensor (WIBS; model 3M, University of Hertfordshire) was operated in a weatherproof box on the ground, a short distance from the base of the tower, with a short (1 m) 1/4 in.
(2015). Particles smaller than 0. 8 µm were rejected from analysis due to low counting efficiency. The baseline fluorescence of the instrument is measured during so-called forced trigger (FT) sampling periods, where the instrument triggers the flash lamps and records the resultant fluorescence in the absence of aerosol in the sample volume. The mean fluorescence in a FT period is treated as the baseline fluorescence of the optical chamber during the sample period. For a particle to be considered fluorescent (FBAP) it must exhibit a fluorescence greater than a threshold value, defined as the baseline fluorescence plus 3 standard deviations, in any channel. During data processing, the threshold value for each channel is subtracted from the single-particle fluorescence data and the value is clipped at zero with all values greater than zero being considered significantly fluorescent compared to the instrument baseline.
Removal of pollution episodes In order to focus on the natural (biogenic) aerosol, for comparison with the wet season, it was necessary to exclude periods affected by pollution. While the site is described as pristine, it can nevertheless be affected by local emissions and regional transport of pollutants: biomass burning emissions from outside the reserve, the urban plume from Manaus, and pollution from the nearby diesel generator. For each day of the campaign 7-day back trajectories were calculated using the HYSPLIT model  (Draxler and Hess, 1998)  at 30 min intervals and six altitudes above TT34 (0, 250, 500, 1000, 2000, and 4000 m a. s. l). The horizontal and vertical wind fields employed here were from the NCEP/NOAA 1 • × 1 • Global Data Assimilation System (GDAS) reanalysis product. These back trajectories were used to identify air masses arriving at TT34 which had either passed over Manaus or passed nearby active fire zones.
The results were largely the same between 0 and 2000 m, with very little influence from the upper-level flow at 4000 m. A bounding box was drawn between -3. 16 and -2. 88 • latitude and between -60. 12 and -59. 81 • longitude to define the Manaus influence zone (see Fig. 1 ), and any back trajectory passing over this box at any altitude up to 2000 m was flagged. Air masses potentially impacted by biomass burning were identified by coupling the back trajectory measurements to satellite-detected fires as measured by the MODIS instrument. This operates on the Aqua and Terra satellites, which have local overpass times in the morning and afternoon, respectively. The fire detection data (specific product: MCD14ML) were produced by the University of Mary- land and acquired from the online Fire Information for Resource Management System (FIRMS; https://earthdata.
nasa. gov/data/near-real-time-data/firms/about). At each location along the back trajectories, the surrounding 1 • box was interrogated for any fire counts at the nearest Terra/Aqua overpass. If any were present, this trajectory was flagged as potentially influenced by biomass burning. This technique is subject to uncertainties associated with trajectory errors (e. g. Fleming et al. , 2012)  and the detection of fires in cloudy scenes, or false detection of fires  (Schroeder et al. , 2008) , and therefore can only be considered qualitative. Finally, data were investigated for possible contamination from the generator if the local wind direction was in the range of 270-340 • ; however, there were no instances of generator contamination during the measurement periods of this study. In the event of any flag, the black carbon data (from the MAAP) were checked along with the particle counts (where available), and aerosol data were excluded if the pollution flag coincided with a significant increase in these concentrations.
Acknowledgements. The authors wish to thank the  Large-scale Biosphere-Atmosphere (LBA)  project group at the  National Institute for Amazonian Research (INPA) in Manaus  for logistical support before and during the field deployment. The  Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate project  was funded by the  UK Natural Environment Research Council  ( NERC ; grant  NE/I030178/1 ). NERC  also funded the PhD studentship of  E. Darbyshire. J. Brito  was funded by  Fundação de Amparo à Pesquisa do Estado de São Paulo  ( FAPESP ; project  2013/25058-1 ). Edited by: A. Huffman Reviewed by: three anonymous referees.
Statistical analysis All statistical tests were performed using GraphPad Prism software version 5 (GraphPad Inc. , San Diego, CA, USA). Data that were not normally distributed were displayed as median along with interquartile ranges and were compared with Mann-Whitney U test for two group comparisons. The Gaussian data were reported as the mean ± standard deviation and were analysed using the t test for two group comparisons. Proportions were compared using the χ 2 test or the Fisher's exact test, as appropriate. Correlations were determined using the Spearman test. A comparison was considered statistically significant if the p value was ≤0. 05.
DISCUSSION SMA is caused by partial or complete loss of the SMN1 gene function and is classified in five clinical variants of increasing severity depending on the level of residual, ubiquitous SMN protein. Past attempts to treat murine models of SMA by gene replacement therapy have shown very significant results in terms of efficacy. 36, 37  However, because of differences in the delivery route, dosage, age at injection, viral vector serotype, and transgene expression cassette, these studies are difficult to compare and defining the best strategy to treat this disease remains challenging. Nevertheless, on the basis of the promising results obtained by systemic IV delivery, a phase 1/2 clinical trial started in 2014 at Nationwide Children's Hospital (Ohio State University, Columbus USA; trial ID: NCT02122952), with the aim of proving safety and efficacy of gene therapy by intravascular administration of a scAAV9 vector expressing the human SMN1 transgene.
Statistical analysis Data were analyzed with Graphpad Prism version 5 (Graphpad Software) and expressed as mean ± standard error of the mean (with n = 8, if not otherwise stated). Statistical differences between mean values were tested using one-way analysis of variance and two-way analysis of variance followed by a Bonferroni correction for false discovery rate where appropriate. From the survival data Kaplan-Meier curves were generated and tested using the Mantel-Cox log-rank test. Differences between values were considered to be significant with: *P < 0. 05, **P < 0. 01, ***P < 0. 001.
Data analysis Images were captured with a DM6000 microscope (Leica, Nanterre, France) and analyzed using MetaMorph software (Molecular Devices, Sunnyvale, CA). For labeling density analysis, image files were inverted and opened in gray-scale. Subsequently, using the thresholding function of Fiji  [29]  to discriminate objects of interest from the surrounding background, the total surface occupied by immunoreactive structures (i. e. , total stained pixels) above this set threshold was estimated within a standard area (ROI manager). Images were taken at objective ×20 on a Leica microscope. The resulting values were expressed in surface units corresponding to 306,804 μm 2. The results were expressed as the mean ± SEM of six to eight values per structure and per animal. Images for co-localization were taken with an Olympus FV1000 laser-scanning confocal microscope (Olympus, Philadelphia, USA) and acquisitions were obtained using the Olympus Fluoview software version 4.
RGCs and activated tissue macrophage/microglia labeling and counting Eight microscopic images were captured using a ×20 objective in the peripheral retina and then peripheral, middle, and central regions in whole flat-mounted retina labeled with Brn-3a and CD68 (which plays a role in phagocytic activities of tissue macrophages) antibodies, respectively. Images were captured with a DM6000 microscope (Leica), and automatic enumeration of RGC nuclei was assessed in a blind manner with MetaMorph software (MolecularDevices). Iba1-and CD68-positive cells were counted with the Fiji cell-counter plugin (ImageJ software, NIH, Bethesda, MD, USA)  [30]. The Iba1-and CD68positive cells in the central retina were quantified around the ON head. In order to analyze the density of neuronal cell population (labeled with the NeuN marker) in SC of EVC and control groups we used an automatic counting cell software (Explora Nova Morpho Strider; 2D Analysis).
RT-PCR First-strand cDNA synthesis (20 μl reaction) was performed with a High-Capacity cDNA Reverse Transcription kit (Applied Biosystems, Life Technologies). Concentrations of each sample were adjusted to 5 ng/μl of cDNA. Realtime PCR amplification of each sample was performed in triplicate, on the 7300 Real-Time PCR system (Applied Biosystems, Life Technologies). TaqMan® Gene Expression Assays (Applied Biosystems) were used for target genes: GFAP (Rn01460868_m1), IL1β (Rn0058 0432_m1), CCL2 (Rn00580555_m1), Nox2 (Rn00576 710_m1), Nox4 (Rn00585380_m1), TNFα (Rn01525 859_g1), CD68 (Rn01495634_g1), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Rn01775763_g1). Specific mRNA levels were calculated after normalization of the results for each sample with those for GADPH mRNA. The data are presented as relative mRNA units with respect to control values.
Acknowledgements This work was supported in part by an unrestricted grant by  Institut National pour la Santé et la Recherche Médicale (INSERM)  and  Agence National pour la recherché  ( ANR R06282DS ) funds. The authors thank all of the core facilities of  Institut de la vision ,  Région Ile-de-France , and  Ville de Paris. They also thank  Linda Northup  for the editorial assistance with the manuscript.
Sample Populations. Only adult crania were included, and crania with obvious facial osteological deformation (e. g. alveolar atrophy) were excluded. We designed our sample to contain an approximately even distribution of males and females, since no evidence has been found indicating gender bias in the climatic impact on facial morphology. The selected crania were subsequently scanned with a Konica Minolta noncontact three-dimensional (3-D) digitizer Range 7. The resolution of the surface scanner is 40 mm. All scans were reconstructed to a 3-D mesh with the software Rapidform VOX 2 V R (INUS Technology).
Shape Data The landmarks and semilandmarks were designed to best reflect the mid-facial shape. The total mid-facial dataset was divided into three parts: (1) The zygomatic dataset (eight landmarks, fourteen curve semilandmarks, and 177 surface semilandmarks) represents the overall shape of the zygomatic bone; (2) the nasal dataset (four landmarks, 26 curve semilandmarks, and 180 surface semilandmarks) represents the shapes around the nasal aperture, the topography of infraorbital surface; (3) the alveolar dataset (three landmarks, 21 curve semilandmarks, and 96 surface semilandmarks), represents the prognagm and alveolar morphology (Fig. 2 ). The zygomatic and nasal parts are separated based on the zygomaticomaxillare suture, reflecting the morphology of the nasal and cheek area, respectively, while the alveolar process of the maxilla is considered to be alveolar.
The four datasets (total, zygomatic, nasal, and alveolar) were analysed separately in all subsequent procedures. Landmarks were chosen on each individual so as to be homologous across all specimens, as suggested by  Martin (1988) , and their 3-D coordinates were acquired (Table  2 ). Sliding curve semilandmarks were digitized along the major curves of the vault, including the curves of the sagittal, occipital and brow ridges, and each was manually re-sampled on each individual specimen. The landmarks and curve semilandmarks on all specimens were digitized by one author (Y. C. ). The surface semilandmarks were digitized according to the techniques described by  (Freidline et al. , 2012a (Freidline et al. , ,b, 2013 (Freidline et al. , , 2015)). First, a mesh of surface semilandmarks was digitized using one of the specimens in this study as a 'template' individual.
Climate Data The climatic data were obtained from the KNMI Climate Explorer database (http://www. climexp. knmi. nl) on 23 October 2015 for the sampling locations included in this study (Table  1 ). We used the mean temperature of the warmest and coldest month (8C, T max and T min ), the mean precipitation of the wettest and driest month (mm, P max and P min ), the highest and lowest monthly sea level pressure (mb, SP max and SP min ) and the highest and lowest monthly surface solar radiation (S max and S min ) as climatic indicators for each population. These indicators are listed in Table  1  and visualized in Fig. 1B. The temperature, precipitation and sea level pressure data was retrieved from the monthly station data (for the exact period see Supporting Information Table  S1 ) in the KNMI dataset, and surface solar radiation data was obtained from the FRESCO dataset at 0.
Genetic Data Genetic information was collected from the 1000 Genomes Project (The 1000 Genomes  Project et al. , 2012)  and the PanAsian SNP project (PanAsian SNP  Consortium et al. , 2009). Exact matching of morphological samples with genetic samples is not possible due to limitations in both data sets. Matching between geographic neighbors was therefore conducted in order to preserve a meaningful number of samples (e. g. ,  Harvati and Weaver, 2006). Genetic samples from the British (GBR, 107 individuals), Kenyan (LWK, 116 individuals), Han Chinese from Beijing (CHB, 108 individuals), Southern Han Chinese (CHS, 171 individuals) and Mexican descendants from Los Angeles (MXL, 107 individuals) were selected in the 1000 Genomes Project dataset to represent German/Austrian, Kenyan, Han North, Han South, and American Indian populations, respectively.
e. , a genomic location that shows nucleotide variation in a population) for each chromosome. SNPs were retrieved from chromosomes 10, Fig. 2. Landmarks (blue), curve-semilandmarks (purple), surface-semilandmarks (yellow for the zygomatic dataset, light green for the nasal dataset, and orange for the alveolar dataset) used in the analysis. 21, and 22, which resulted in 2821, 969, and 313 SNPs common to both databases, respectively. No further information was retrieved from other chromosomes, because the above three chromosomes returned exactly the same results in the Mantel and partial Mantel tests (see below). The frequency of each nucleotide (A, T, G or C) at each SNP was then calculated for each population and stored in a three dimensional matrix with axes of SNP, Population and Nucleotide Frequency.
Statistical Methods Test for climate-shape correlations. To test for correlations between mid-facial shape, climate and genetic data, we used Mantel matrix correlation tests  (Mantel, 1967)  in ecodist  (Bjornstad and Falck, 2001) , an R function package. Euclidean distances were calculated between each specimen for climate and genetic data, and Procrustes distances for shape data were used as inputs in Mantel tests. Matrix permutations (10,000 iterations) were then used to assess significance, with the alpha level set at a 5 0. 05. To account for population history effects, we ran partial Mantel tests on the correlation between cranial shape and climate in which matrices of genetic distance between populations (as a proxy for population history, following  Evteev et al. , 2014; Noback and Harvati, 2015)  were kept constant.
The strongest correlations exist between the zygomatic and temperature (r 5 0. 113, p 5 0. 0058), and the alveolar and sea-level pressure (r 5 0. 221, P < 0. 0001). Different climatic conditions thus seems to impact the shape of various parts of the mid-face independently, with temperature, and sunshine having a moderate general effect, and pressure having a higher and more specific effect on the alveolar section. Our dataset includes samples from an American Indian population, which are known to retain morphological traits from their Siberian ancestors despite living in a much warmer climate. To explore the putative effect of this population on our observations, we conducted a new correlation analysis with the American Indian population excluded from the dataset. The results show only minor variations compared to the study with all populations: the uncorrected correlation between zygomatic and climatic variables precipitation and pressure became nonsignificant, as well as the corrected correlation between alveolar and sunshine; the value of the corrected correlation between the nasal part and temperature also slightly increased (Supporting Information Table  S2 ).
Consequently, the correlations that remained for mid-face subparts after genetic distance correction can be more confidently attributed to some kind of geographical adaptation unrelated to population history. Evteev and Movsesian (2016)  suggested that the use of multiple neutral population distance markers (i. e. , mtDNA, SNPs, and cranial nonmetrics markers) should be considered when exploring the association between face morphology and climatic factors, to avoid the specific drawbacks of each type of data. According to the same authors, SNPs are the technically most reliable markers, but they suffer from small sample sizes and from insufficient representation of populations at the local scale. However, our analysis are not affected by these limitations, since our morphological samples are differentiated at the global (worldwide) scale with corresponding genetic samples available in the 1000 Genomes Project and the PanAsian SNP databases, and since almost all the selected genetic populations included more than 50 individuals.
CONCLUSION Bony surfaces provide new information on the variation in skeletal morphology. This study focuses for the first time on the association between surface morphology of the mid-face and variable climatic parameters. Furthermore, genetic data were included to correct for spurious associations caused by phylogenetic relationships between populations rather than climatic factors. Our findings confirm the previously reported association of climatic variables with facial shape, especially the nasal aperture  (Coon et al. , 1950; Carey and Steegmann, 1981; Roseman, 2004; Roseman and Weaver, 2004; Nicholson and Harvati, 2006) , and reveal new trends, with the zygomatic becoming more prominent and the nasal aperture becoming more rectangular in populations living in temperate climates compared to populations from tropical climates.
ACKNOWLEDGEMENTS We are indebted to  Dr. Xiujie Wu  ( IVPP ) who kindly shared her skeletal scans with us. We are grateful to curators and collection managers at the  IVPP (Beijing) , the  Evidence Identification Centre of Public Security Bureau of China's Ministry of Public Security (Beijing) , the  Kenya National Museum (Nairobi)  and the  American Museum of Natural History (New York ) for providing access to their specimens. The authors also thank  Dr. Melinda Yang  and two anonymous reviewers who provided valuable comments to improve this paper.
The corresponding UV-Vis. spectra were recorded from 230 nm to 800 nm to follow the evolution of complexation on a Cary 50 (Varian) or a Cary 5000 (Agilent) spectrophotometer maintained at (25. 0 ± 2°C. The spectrophotometric data were then analyzed with Specfit  [48]  program which adjusts the absorptivities and the stability constants of the species formed at equilibrium. Specfit uses factor analysis to reduce the absorbance matrix and to extract the eigenvalues prior to the multiwavelength fit of the reduced data set according to the Marquardt algorithm  [49, 50].
Assuming these facts, we can propose that the complexation of the quercetin first proceeds through its catecholate binding site. The Cu(II) and Zn(II) complexation properties of quercetin, rutin and (+)catechin were then examined using the same analytical approach. The stability sequence satisfactorily follows the Irving-Williams order  [73]  with the Cu(II) complexes being the more stable with respect to Zn(II). In addition, cupric monochelate LCu and bischelates L 2 Cu were characterized for quercetin in agreement with reported data  [74].
Discussion In this study, red blood cells (RBCs) were subjected to in vitro extracellular metal ion-induced hemolysis. We investigated the response of RBCs to the generated damage and their (anti)oxidant status. The impact of three relevant flavonoids was examined on the hemolysis and the (anti)oxidant markers of the treated RBCs. These biochemical data were compared to physicochemical data related on metal binding. In human cells, H 2 O 2 , a by-product of oxygen metabolism, may be present at micromolar concentrations and is relatively harmless as it reacts with biomolecules at relatively low rates. In addition, specific enzymes facilitate its removal. However, metal (e. g. , Fe, Cu) ions can catalyze the conversion of H 2 O 2 into a highly reactive and damaging hydroxyl radical (HO • ). Fe mostly occurs in its +II and +III oxidation states.
conditions (e. g. food availability or predation) varies according to its intrinsic attributes (e. g. age, previous allocation of resources towards reproduction). 2. We used 29 years of reproductive data from marked female tawny owls and natural variation in food availability (field vole) and predator abundance (northern goshawk) to quantify the extent to which extrinsic and intrinsic factors interact to influence owl reproductive traits (breeding propensity, clutch size and nest abandonment).
were recorded breeding) in 2013 (N = 40), to remove any bias that unknown non-breeding events occurring in the last few years of the study period could induce. To determine the extent to which owls adjust the amount of resources they allocate towards reproduction in response to variation in food availability and predation risk, we modelled variation in clutch size. In addition, we examined the decision or capability to continue with a breeding attempt by classifying each breeding attempt as "complete", if at least one chick fledged, or "incomplete" if not (fitted as a binary covariate). These two analyses were based on a different dataset to that used for the breeding propensity analysis, as it contained all breeding attempts by all known individuals (N = 241), including first time-breeders between 1985-2013.