dataesr/scientific-paragraphs-categorization huggingface dataset:
We estimated the systematic uncertainty due to the energy resolution on the fitted photon index Γ to be ∼2%; this is negligible compared to the statistical uncertainty. We also performed a joint likelihood fit of the LST-1 data and LHAASO flux points to find the spectrum of the source in the multi-GeV to multi-TeV range. Provided the hard TeV and soft multi-TeV spectrum, for the spectral shape, we considered a PL with an exponential cutoff (ECPL) defined as dN/dE = N 0 (E/E 0 ) -Γ exp(-E/E cutoff ). The best-fit parameters are listed in Table  1. As a second step, we performed a maximum-likelihood estimation of the source flux in six logarithmically spaced energy bins between 100 GeV and 100 TeV, using ECPL spectral parameters fitted in the previous step. We did not reach a significant source detection in the TeV range, and therefore calculated 95% confidence level differential flux upper limits (ULs) in individual energy bins, which are shown in Fig.
Looking at all sources present in the 4FGL-DR3 catalog and their 95% positional errors, there are no counterparts overlapping with the uncertainty position provided by LHAASO (see Fig. 3 ). The closest source is 4FGL J2108. 0+5155, which lies 0. 13 • away. Above 1 GeV, the source spectrum is well fitted by a log parabola with a normalization of (9. 8 ± 0. 9) × 10 -13 ph cm -2 s -1 MeV -1 , α = 2. 5 ± 0. 2 and β = 0. 37 ± 0. 18, assuming the same E b value as that of the catalog (i. e. , Table  1. Best-fit parameters for the spectral analysis performed on the LST-1 data alone using a PL model of the spectrum, and for the joint fit to LST-1 and LHAASO data using ECPL. E b = 1580. 67 MeV). The other three 4FGL sources visible in Fig. 3  are fainter and present a softer log-parabolic spectrum with a turnover at lower energies, with the only exception being J2109.
5+5238c, whose spectrum is a PL with a photon index of 2. 6, which locally overtakes the flux of 4FGL J2108. 0+5155 above a few tens of GeV. Data Spectral N 0 Γ E cutoff -2 log L model [×10 -14 cm -2 s -1 TeV -1 ] [TeV] LST-1 PL 8. 0 ± 5 The spectrum of the closest source to LHAASO J2108+5157, namely 4FGL J2108. 0+5155, presents a steep decrease above a few GeVs, which is not compatible with the. By rerunning the analysis, extending the low-energy threshold to 500 MeV and to 300 MeV, and properly increasing and adapting the selected ROI, the fitted spectra that we obtain present some scatter at low energy, which is due to the large instrument PSF. Although it depends on how much freedom we allow in the fit to the neighboring sources and to the Galactic diffuse emission, in all cases the trend converges toward a unique and consistent behavior above a few GeVs.
XMM-Newton The field surrounding LHAASO J2108+5157 was observed by XMM-Newton on June 11, 2021, for a total of 13. 6 ks. The observation was centered on RA(J2000)=317. 0170 • , Dec(J2000) = +51. 9275 •. We reduced the data from the European Photon Imaging Camera (EPIC) 8 of XMM-Newton using XMMSAS v19. 1 and the X-COP data-analysis pipeline  (Eckert et al. 2017; Ghirardini et al. 2019 ). After screening the data and creating calibrated event files using the standard chains, we used the XMMSAS tasks pn-filter and mos-filter to filter out time periods affected by strong soft proton flares. After excising the flaring time periods, the clean exposure time is 4. 7 ks (MOS1), 4. 9 ks (MOS2), and 3. 0 ks (pn). From the clean event files, we extracted images in the soft (0. 5-2 keV) and hard (2-7 keV) bands, and used the eexpmap task to create effective exposure maps accounting for vignetting, bad pixels, and chip gaps.
To estimate the nonX-ray CR-induced background (NXB), we made use of the unexposed corners of the detectors to rescale the filter-wheel-closed event files available in the calibration database. We then reprojected the filterwheel-closed data to match the attitude file of our observation 8 The EPIC is made of three co-aligned detectors: MOS1, MOS2 and pn. Fig. 4. Fermi-LAT TS maps computed assuming various photon indexes for the putative source, and above different threshold energies. Each TS map is smoothed with a Gaussian whose sigma is equal to 68% of the Fermi-LAT PSF containment radius measured at each corresponding threshold energy. This size is reported with a cyan segment in the bottom left corner of each plot. Black contours are overplotted with a linear scale to better localize the position of the TS peaks.
Green, red, magenta, and white elements are the same as those used and described in Fig. 3. The small white ticks on both axes are in units of 0. 1 •. Each subplot has been renormalized to its own maximum value to make its color-scale and isocontours comparable. and extracted model-particle background images from the rescaled filter-wheel-closed event files. Finally, we summed up the images of the three EPIC instruments as well as the NXB maps. We also created a total EPIC exposure map by summing up the exposure maps of the three instruments, weighted by their respective effective area. We ran the XMMSAS task ewavelet to detect X-ray sources in the field. The resulting catalog contains 11 sources in the soft band and 2 in the hard band. The brightest source in the field is associated with the eclipsing binary star V* V1061 Cyg (RX J2107.
To this end, we used the public code pyproffit  (Eckert et al. 2020)  to extract the brightness profile of unresolved emission across the field. The NXB-subtracted, vignetting-corrected profiles are consis- tent with a flat brightness distribution, which is compatible with the expected sky background emission made of a combination of the local hot bubble, the Galactic halo, and the cosmic X-ray A75, page 7 of 16 background. If the source is smaller than the XMM-Newton FoV (30 in diameter), we can use the measured count rates in the outer regions of the field to estimate the local sky background emission and set the maximum allowed number of source counts on top of the background. For aperture photometry performed in the Poisson regime, the S/N is given by S /N = N src N src + N bkg , (1) where N src is the number of (background-subtracted) source counts and N bkg is the total number of background counts (sky background + NXB).
The conversion factors were then used to determine the corresponding flux upper limits. Table  3  provides a list of upper limits for a wide range of scenarios. The allowed values are in the range 10 -15 -10 -13 erg cm -2 s -1 depending on the assumed source size and spectrum. In order to estimate a flux upper limit in the full region of a possible extension of the UHE source from the data available (95% extension upper limits has a radius of 16 arcmin), we scaled the 6 arcmin upper limits by the ratio of the two radii. However, we note that there is no surface brightness gradient across the XMM-Newton FoV, which would be expected for a very extended source centered at the UHE source coordinates. This means that any low-surface-brightness extended source would need to be not only very extended but also uniform across the XMM-Newton FoV, which is not very likely.
Molecular clouds LHAASO J2108+5157 is located in the direction of relatively dense molecular clouds. Cao et al. (2021a)  searched the database of molecular clouds in the Galactic plane (Miville-Deschênes et al. 2017) and found its position close to the direction of two molecular clouds [MML2017]2870 and [MML2017]4607 with distances of 1. 43 kpc and 3. 28 kpc, and masses of 3. 5 × 10 4 M and 8. 5 × 10 3 M , respectively. To estimate the total gas density in the direction of LHAASO J2108+5157, we considered a contribution of H 2 molecular density and of neutral hydrogen HI density. We used 12 CO(1-0) line-emission observations collected during the composite survey by  Dame et al. (2001)  to estimate the density and distance of the molecular clouds. We note that, given the Galactic longitude of the source, namely l > 90 • , the kinematic distance of each molecular cloud has only a single solution (see e.
Leptonic scenario of emission As most of the VHE sources in our Galaxy have been identified as PWNe  (Hess & Abdalla 2018c) , we first examine this possible scenario of emission. Here, we provide quantitative estimates of and limits on the leptonic scenario of emission derived from the data, and compare them with the physical properties of known PWNe/TeV halos. We used the naima 9 package  (Zabalza 2015)  to derive a parent electron distribution reproducing IC dominated  (Khangulyan et al. 2014 ) VHE to UHE emission of LHAASO J2108+5157. For the sake of simplicity, we assume a single electron spectrum in the form of an ECPL f (E) ∼ E -α exp(-E/E c ). As the source was not detected in the X-ray range, we only considered IC emission using the LST-1 and LHAASO flux 9 https://naima. readthedocs.
False Notes. Normalization of the spectrum N 0 is calculated for the source distance of 1 kpc. VHE-UHE emission of LHAASO J2108+5157 is assumed to be dominated by emission due to IC scattering of electrons on CMB (T = 2. 83 K, u = 0. 26 eVcm -3 ) and FIR (T = 20 K, u = 0. 3 eVcm -3 ) seed photon fields. ] Fig. 7. Multiwavelength SED of LHAASO J2108+5157 showing a leptonic scenario of emission. Observations with different instruments are represented by data points of different colors: XMM-Newton r = 6 (blue), r = 16 (green), Fermi-LAT (red), LST-1 (purple), and LHAASO-KM2A (yellow). The black solid line represents the bestfitting IC-dominated emission of LST-1 and LHAASO data. The corresponding synchrotron radiation of the same population of electrons is represented with dashed and dash-dotted lines for B = 1.
Acknowledgements. We gratefully acknowledge financial support from the following agencies and organisations:  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ,  Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ,  Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ,  Fundação de Apoio à Ciência, Tecnologia e Inovação do Paraná -Fundação Araucária, Ministry of Science, Technology, Innovations and Communications (MCTIC) ,  Brasil ;  Ministry of Education and Science, National RI   Roadmap  Project  DO1-153/28. 08. 2018 , Bulgaria ;  Croatian Science Foundation ,  Rudjer Boskovic Institute ,  University of Osijek, University of Rijeka, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia ;  Ministry of Education , Youth and Sports, MEYS  LM2015046 ,  LM2018105 ,  LTT17006 ,  EU/MEYS CZ.
000X. 411. 01 , PGE2022/28. 06. 000X. 411. 01  and  PGE2022/28. 06. 000X. 711. 04 , and grants  PGC2018 the " Centro de Excelencia Severo Ochoa" program  through grants no. SEV-2017-0709 ,  CEX2019-000920-S ; the " Unidad de Excelencia María de Maeztu" program  through grants no. CEX2019-000918-M ,  CEX2020-001058-M ; the " Ramón y Cajal" program  through grant  RYC-2017-22665 ; the " Juan de la Cierva-Incorporación" program  through grant no. IJC2019-040315-I. They also acknowledge the "Programa Operativo" FEDER   2014-2020 ,  Consejería de Economía y Conocimiento de la Junta de Andalucía (Ref. 1257737 ),  PAIDI 2020 (Ref. P18-FR-1580 ) and  Universidad de Jaén ; " Programa Operativo de Crecimiento Inteligente "  FEDER 2014-2020 (Ref. ESFRI-2017-IAC-12 ),  Ministerio de Ciencia e Innovación ,  15%  co-financed by  Consejería de Economía, Industria ,  Comercio y Conocimiento del Gobierno de Canarias ; the  "CERCA" program  of the  Generalitat de Catalunya ; and the  European Union 's " Horizon 2020 "  GA:824064 and NextGenerationEU ; We acknowledge the  Ramon y Cajal program  through grant  RYC-2020-028639-I ;  State Secretariat for Education, Research and Innovation (SERI)  and  Swiss National Science Foundation (SNSF) , Switzerland; the research leading to these results has received funding from the  European Union 's  Seventh Framework Programme  ( FP7/2007-2013 ) under grant agreements No 262053 and No  317446.
This project is receiving funding from the  European Union 's  Horizon 2020 research and innovation programs  under agreement No  676134. This research has made use of the observations obtained with  XMM-Newton , an  ESA  science mission with instruments and contributions directly funded by  ESA Member States  and  NASA. This research has made use of the SIMBAD database, operated at  CDS, Strasbourg, France. Author Contribution: M. Balbo: Fermi-LAT data analysis, paper drafting and edition; D. Eckert: XMM-Newton data analysis, paper drafting and edition;  J. Juryšek : project leadership, LST data analysis, paper drafting and edition, theoretical modelling, theoretical interpretation; A. Tramacere: theoretical modelling, theoretical interpretation; G. Pirola: LST analysis cross-check;  R. Walter : project initiator & leadership, theoretical interpretation, XMM ToO.
Data are represented as mean ± SEM, n = 3 for pSMAD1,5 staining and n = 4 for ZO1 staining. Statistical analysis: Statistical analysis: (b) two-way ANOVA followed by Sidak's multiple comparison test were used to analyzed pSMAD1,5 counts and unpaired t-test were used to analyzed ZO1 organized areas P-values: (***) <0. 001, (*) <0. 05. For all panels "n" corresponds to the number of biological replicates unless stated otherwise. Source data are provided as a Source Data file. system to investigate the physical effects of disrupted epithelial cell polarity and architecture on the cellular response to TGF-β proteins at the human MES onset. We demonstrated that GPC4 downregulation in hiPSCs results in a distinct morphological organization of hiPSC monolayers wherein alteration of TJs leads to a mosaic hiPSC structural pattern with areas of disrupted epithelial integrity.
Cell cycle analysis hiPSCs were seeded on Matrigel-coated plates and analyzed at 30-50% of cells confluency. Nuclei were extracted with lysis buffer (Chemometec) and incubated with 10 µg/ml of DAPI for 5 min at 37 °C. Nuclear DAPI intensity was measured with the Cytometer NucleoCounter® NC-3000™ (Chemometec) and cell cycle was analyzed with the Nucleo-View NC-3000™ program (Chemometec).
2. 1 (Kim  et al. , 2015) using default options. Gene counts were quantified using feature Counts v2. 0. 1 from the Subread v2. 0. 1 package (Liao et al. , 2019). Alignment and gene counts were generated against the GRCh38. p13 (Ensembl release 101). The low expressed genes which did not have more than one count per million reads (1CPM) in at least three samples within each dataset were removed from further analysis. Gene counts were then normalized and used for differential expression testing using DESeq2 v1. 28. 0 60 (Supplementary Tables  1, 2 ).
Western-blots For western-blots, cells were lysed in 1X EBM lysis buffer in the presence of a protease and phosphatase inhibitors mixture  15. 20-50 μg of whole cell lysates were resolved on 10% Anderson gels and transferred to PVDF membranes. After blocking with 5% milk in PBS, 0. 1% Tween 100, the membranes were incubated overnight at 4 °C with primary antibodies. Primary antibodies used are listed in Supplementary Table  7. The membranes were then washed, incubated with anti-rabbit or anti-mouse IgG-peroxidase (1:4000, Jackson, ref. 211-035-109) at room temperature for 1 hr, and peroxidase activity was visualized with the ECL Plus Kit (Amersham). Full scan blots are provided in the Source Data file.
Live/ Dead cell discrimination was assayed either using DAPI (MERCK, #D9542) or L/D fixable Blue (Thermo Scientific, #L23105). Samples were analyzed directly upon completion of immunostaining protocol. Data was acquired on BD LSRFortessa 5Laser SORP cytometer (BD Bioscience) using HTS plate reader and analyzed on a standardized analysis matrix using BD FACS DIVA 9. 0. 1 software. Illustrations were generated on Cytobank 9. 4 (Beckman Coulter).
051). Micropatterns experiments were analysed using matlab R21b software. Morphological analysis. To quantify disrupted epithelial areas, ZO1 immunostaining was manually analyzed with Image J (version 2. 3. 051), and a MASK corresponding to the disrupted area was generated. From this MASK, 4 others concentric MASKs corresponding to four localizations, corresponding to 0 to 30 µm, 30 to 60 µm, 60 to 90 µm or >90 µm away from disrupted areas, were generated and used to analyze the correlation between cells positive for pSMAD1,5, pSMAD2, LEF1 or BRACH (as described in signal quantification and count) and their position relative to the disrupted areas. BMPR1A-ZO1 distance analysis. To quantify BMPR1A-ZO1 distance in the z-axis, BMPR1A and ZO1 z intensity distribution have been manually extracted using Zen Blue (version 3.
Statistical analyses All statistical analyses were performed with GraphPad Prism version 8 software. All statistical tests used are indicated in the respective figure legends and data were presented as mean ± SEM, unless stated otherwise. Statistics were reported as: ns = not significant, *p-value < 0. 05, **p-value < 0. 01, ***p-value < 0. 001. Precise p-value are provided in the source files.
Data availability The data that support this study are available in the source data provided with this paper. For the RNA-seq alignment and gene counts were generated against the GRCh38. p13 (Ensembl release 101; IDs: 2334371 [UID] 8687898 [GenBank] 8765528 [RefSeq]). The RNA-seq data and the read count matrix are available on Zenodo (https:// zenodo. org/) with the https://doi. org/10. 5281/zenodo. 5569383. The RNA-seq data have also been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE222186. Source data are provided with this paper.
Code availability The workflow allowing to achieve the differential expression analysis of RNA-seq data is available on Zenodo (https://zenodo. org/) with the https://doi. org/10. 5281/zenodo. 6908427 and is under the BSD-3 license. For the differential RNA-seq analyses, the genes with a log2fc between -0. 58 to 0. 58 and an adjusted p-value (padj) > 0. 01 were not considered as significantly differentially expressed.
To confirm amplification success, we tested 3 μl of the PCR product on an 1% agarose electrophoresis gel. After PCR, the products were diluted 1:99, after which 2 μl (1 μl for panel 5) of product was combined with 9. 5 μl HiDi and 0. 5 μl Liz 600 and ran on an ABI Prism® 3130XL Genetic analyzer (Applied Biosystems) using fluorescently labeled primers. Allele sizes were determined using GeneMapper TM Software ver. 4. 0 (Applied Biosystems). We performed Hardy-Weinberg and null-allele tests in Cervus ver. 3. 0. 7 (Supporting information for marker characteristics). Two markers with low variability (three alleles in each) showed relatively high estimated frequencies of null alleles (FH356: 0. 118, FH413: 0. 095). Assuming that null alleles were randomly distributed in the two populations, we have chosen to include these markers in our analyses.
Sperm morphology Approximately 10-15 µl of diluted, fixed sperm was spread out on a microscope slide with a pipette and dried overnight. The slide was then washed with distilled water, to remove salt crystals, and left to dry for at least one hour. From each male, 10 or 30 (below) normal sperm cells were photographed, using a Leica DFC420 camera mounted on a Leica DM6000 B digital light microscope to obtain digital images at magnification of 160×. Sperm morphometry was performed using the image analysis software Leica Application suite ver. 4. 1. Sperm cells consist of three components; head, midpiece and tail, which were measured separately. The total length of the sperm cell was calculated by adding the length of these three components. Since four different persons were involved in the measurement of sperm morphology and preliminary analyses indicated large inter-measurer differences in the estimation of head length (F = 371.
Thirty-eight of these were sampled in the years 2007-2011 and their sperm morphological measurements were included in a previous paper  (Hogner et al. 2013 ). These measurements were not included in analyses of population differences in the present paper, which thus comprise data from 224 males. Data from svecica from 2013-2015 were taken from  Saetre et al. (2018) , where they were used in a different context.
2013b). Each of the sperm samples were recorded for about 30 s and 6 frames were used to optimize the recording of the sperm cells. For males included in experiments described in  Cramer et al. (2016) , only control conditions were included here (see also data description in  Saetre et al. 2018). For measuring the motility of the sperm cells, a computerassisted sperm analysis (HTM-CEROS II Sperm Analyzer; Hamilton Thorne Research, Beverly, MA) was used. The sperm analyser was set at a frame rate of 50 Hz and 25 frames (i. e. sperm cells were tracked for 0. 5 s). Each analysis was visually examined, and cell detection parameters were adjusted using the two interactive quality control plots as well as directly from visual examination of each recording. Three estimates of sperm velocity were calculated: straight line velocity (VSL), average path velocity (VAP), and curvilinear velocity (VCL).
Heterozygosity and sperm characteristics There were no significant relationships between individual heterozygosity and total sperm length, variation in total sperm length, sperm velocity or proportion of motile sperm cells, neither in GLMs (Table  2 ) nor in Spearman correlation tests (all |R sp | < 0. 07, all p > 0. 70). In the GLM analyses, the number of cells measured was positively related to CVwm of total sperm length, and subspecies identity was significantly related to the proportion of motile sperm cells (namnetum showing a higher proportion of motile sperm than svecica). Note that the latter relationship was not significant in the larger dataset testing for subspecies differences (Table  1 ).
Acknowledgements -We thank  Jan T. Lifjeld ,  Silje Hogner ,  Even Stensrud ,  Lars Erik Johannessen ,  Gunnhild Marthinsen ,  Jostein Gohli ,  Trond Øigarden ,  Erica Leder ,  Terje Laskemoen ,  Silje Larsen Rekdal ,  Celeste Santos Apolinario ,  Laurent Godet  and  Jérôme Fournier  for assistance in the field,  Terje Laskemoen ,  Even Stensrud  and  Gaute Grønstøl  for performing parts of the sperm measurements, and an anonymous reviewer for improving the manuscript. Funding -The study was financed by the  Norwegian Research Council  (grant no. 213592  to AJ) and the  Natural History Museum, University of Oslo. Permits -Permits to capture, ring and sample the Norwegian birds were issued to AJ from the  Norwegian Environment agency  (ringing permit no. 680 ) and the  Norwegian Food Safety Authority  ( FOTS id   1028  and  5127 ), while permits to capture, ring and sample the French birds were issued to MCE from the  French National History Museum  (ringing permit no.
Next, 300 µL of SYTO 9 green-fluorescent nucleic acid stain (Thermofisher, Waltham, MA, USA) was added in each well and incubated for 20 min in the dark. The SYTO 9 stain was removed and 300 µL SPW was added in each well. CLSM observations were immediately performed using a Zeiss LSM710 (Carl Zeiss Microscopy, Oberkochen, Germany) using a 63-x oil immersion objective. SYTO 9 was excited at 488 nm and fluorescence emission was detected between 500 and 550 nm. Images were taken every micrometer throughout the whole biofilm depth. For visualization and processing of three-dimensional (3D) images, the Zen 2. 1 SP1 software (Carl Zeiss Microscopy, Oberkochen, Germany) was used. Quantitative analyses of image stacks were performed using the COMSTAT software (http://www. imageanalysis. dk/)  [24].