dataesr/scientific-paragraphs-categorization huggingface dataset:
Quantification and statistical analysis Flow cytometry analysis and quantifications were done with FlowJo10 software. Statistical analyses were performed using Graph-Pad Prism (v8), Microsoft Excel for Mac (v14. 7. 3), Python (v3. 6. 8), and R (v4. 0. 0). For the identification of overlapping clonotypes in uninfected individuals a maximum of one amino acid length difference and three or less differences in absolute amino acid composition of CDR3s were considered as similar. To calculate the CDRH3 sequence overlap between replicates in the control experiment (Fig. 1 c ), a random sample of n = 3623 (i. e. the size of the smallest dataset) was drawn from all unique CDRH3s of each set and the overlap (i. e. identical CDRH3 sequences) between these random samples was determined. Sampling and overlap determination was repeated 100 times and the mean overlap over all iterations was reported.
Testing for significant differences between CDR3 length distributions and V gene mutation frequency distributions (Fig. 1d, e ) was performed by global Kruskal-Wallis tests (stats. kruskal, Scipy v. 1. 5. 2) and Dunn post-hoc tests (posthoc_dunn, scikit_posthocs v. 0. 4. 0 with 'holm' method for p value adjustment). To estimate the fraction of spiked-in lymphoma B cells among naive B cells from an uninfected donor (Supplementary Fig. 3 ), the pairwise Levenshtein distance of all re-constituted CDRH3s was determined (python-Levenshtein v. 0. 12. 2) in comparison to the most frequent cell line CDRH3. The observed distance frequencies revealed a bimodal distribution from which all comparisons with <4 amino acid distance (first peak) were counted as a B cell line CDRH3 and divided by all comparisons to get the fraction.
For cluster analysis of the mixed cell sample (Supplementary Fig. 3 ), a network analysis was performed with the networkx python package (v. 2. 2). Each node represents a unique CDRH3. The node size is proportional to the frequency among all identified CDRH3s and nodes are connected, if they share at least 75% of their CDRH3 amino acid sequence. Nodes are colored according to the cell lines if they share at least 75% of the CDRH3 amino acid sequence with a cell line. Phylogenetic trees of viral panels (Supplementary Fig. 4 ) were generated and illustrated from aligned viral sequences from the CATNAP database  59  with Geneious Prime software (v. 2020. 2. 4, Jukes-Cantor genetic distance model and Neighbor-Joining method with 100 bootstrap replicates). Testing for significant differences in mean CDR3 lengths and mean V gene mutation frequencies (Fig.
Acknowledgements We thank all members of the  Klein Laboratory  for support and helpful discussion,  Viera Kovacova ,  Antonios Papadakis ,  Lukas Maas , and  Milos Nikolic  for advice on data evaluation and NGS pipeline programming,  Peter Nürnberg ,  Janine Altmüller , and  Christian Becker  from the  Cologne Center for Genomics (CCG ) for sequencing support,  Michael Lässig  and  Christa Stitz  for support within the CRC1310, and  Till Schoofs  for assistance in antibody selection. This work was funded by grants from the  German Research Foundation  (DFG;  CRC 1279  to F. K. ;  CRC 1310  to F. K. , C. K. , A. M. W. , A. N. , J. G. , A. B. ), the  German Center for Infection Research  (DZIF to P. S. , F. K. ), the  European Research Council  ( ERC-StG639961  to F. K;  CoG 724208  to A. M.
W. ), the  Agence Nationale de la Recherche  ( ANR-19-CE45-0018 RESP-REP  to T. M. ),  CAREER Award  from the  National Science Foundation  (Grant No. 2045054  to A. N. ), the  MIRA  award from the  National Institutes of Health  (Grant No. 1R35GM142795-01  to A. N. ), and the  DFG-Emmy Noether Program  (Project No. 495793173  to P. S. ).
Data availability The NGS data generated in this study have been deposited in the Sequence Read Archive (SRA) under the accession codes SAMN29624595 to SAMN29624713 [https://www. ncbi. nlm. nih. gov/ sra?linkname=bioproject_sra_all&from_uid=857338] and the BioProject database under accession code PRJNA857338. The HIV-1 neutralizing antibody data used in this study are freely available in the Los Alamos HIV sequence database under their names as listed in Supplementary Data 4 [https://www. hiv. lanl. gov/components/sequence/ HIV/neutralization/main. comp]. V/D/J reference data was received from the IMGT database [https://www. imgt. org/genedb/]. All remaining data that support the findings of this study are included in this article (and its supplementary information files). Requests for any additional data should be directed to the corresponding author and may be subject to restrictions based on data and privacy protection regulations and/or may require a Material Transfer Agreement (MTA).
Code availability IGoR is freely available on the GitHub repository [https://github. com/ statbiophys/IGoR]. A detailed description of the workflow, including the complete analysis pipeline with example data to run the code, is provided in the public GitHub repository [https://github. com/ statbiophys/bnabs_prob], also available on Zenodo 101 [https://doi. org/ 10. 5281/zenodo. 8409733].
Even thought, its applicability on periods marked by less important climate changes remains to be tested. Although, our approach may concern a limited number of well-studied sites. However, with more 535 All operations on NetCDF files (the standard file format for the outputs of the IPSL models) were performed using CDO (Climate Data Operators)  (Schulzweida, 2019). Maps, plots and analyses were produced using the R free software (R Development Core Team, 2018) and the libraries ncdf4 (http://dwpierce. com/software), raster  (Hijmans and van Etten, 2012) , FactoMineR  (Lê et al. , 2008) , corrplot  (Wei and Simko, 2021)  and ggplot2  (Wickham, 2015).
Real vascular networks are quite disordered  [6] , for which our LBM can straightforwardly be adapted in the future. Besides helping understand blood flow under physiological and pathological conditions in microcirculation, this study may also shed light on biomedical applications such as the design of appropriate networks for cell sorting and the conception of tailored microparticles for a targeted drug delivery. ZS and CM thank CNES (Centre National d'Etudes Spatiales) for a financial support and for having access to experimental data, and the French-German university program "Living Fluids" (grant CFDA-Q1-14). ZS and JSL acknowledge IdEx (Initiative d'Excellence) Bordeaux, La Region Nouvelle-Aquitaine and the French National Research Agency through GASPP ANR-19-CE06-0012 for funding.
Acknowledgments We apologize for relevant citations not included because of space limitations. We are grateful to  Pierre-Emmanuel Milhiet  and all the members of the team for critical reading of the manuscript. Work in the Constantinou laboratory is funded by the  Fondation MSD AVENIR , the  French Agence Nationale de la Recherche  ( AAPG2021 ), and by the  French Institut National du Cancer  ( AAP PLBIO 2021 ).
ACKNOWLEDGEMENTS We would like to express our sincere gratitude to  Octavia Ionescu (Université Paris Cité, LPS ,  EA4471 ),  Mélody Mailliez  ( Université Paris Cité ,  LPS ,  EA4471 ), and  Aurélien Brest  ( Université de Bordeaux, LABPSY, UR4471 ) for their review of our article and their advice, as well as for all the wonderful discussions we had.
Data Seven lysimeters from two French experimental sites located in northeastern France are used in this study. There are three lysimeters from the GISFI experimental station (French Scientific Interest Group -Industrial Wasteland) at Homécourt (49 • 21 N, 5 • 99 E; altitude 430 m), with a data record from 2009 to 2016 (hereafter G1, G2, G3, and G4), and three lysimeters from OPE experimental station (Perennial Environmental Observatory) close to Osne-le-Val (48 • 5092 N, 5 • 2119 E; altitude 224 m), with a data record from 2014 to 2019 (hereafter O1, O2, and O3). These two sites are separated by a distance of 97 km. Their soils are classified according to the World Reference Base for Soil Resources (WRB;  Hazelton and Murphy, 2016). For the lysimeters, the rain intercepted by the vegetation is assumed to evaporate or to eventually reach the ground, as this is the case for all natural surfaces with a vegetation canopy.
50, 1. 0, and 1. 5 m depth, with an additional measurement at 0. 2 m for the OPE lysimeters. The weight is measured continuously with a 0. 1 kg precision, giving an idea of the time variations in the total soil water volume in the column, and a tipping counter measures the drainage water at the bottom. Data are continuously monitored on an hourly basis using a data logger. On the GISFI site, TDR probes are TRIME-PICO 32 sensors with internal TDR electronics. They are set horizontally and record the water content (in cm 3 cm -3 ) on an hourly basis. The calibration is performed on two measurements, namely one in a dry condition and one in a water-saturated condition. At the OPE site, the soil moisture sensors used (UMP-1; Umwelt-Geräte-Technik GmbH) are based on a frequency domain reflectometry (FDR) method and measure the local change in dielectric permittivity.
0, 31. 0 1. 5 m 61. 6, 14. 3, 24. 1 61. 6, 14. 3, 24. 1 62. 4, 15. 2, 22. 4  56. 0, 24. 0, 20. 0 0. 0, 19. 0, 81. 0 22. 0, 6. 0, 72. 0 16. 0, 53. 0, 31. 0 * Hypereutric Cambisol. the ISBA LSM are observed in situ at an hourly time step by two local meteorological stations (one at OPE and one at GISFI). The atmospheric forcing is assumed to be identical for all of the lysimeters at each site. Annual precipitation is 20 % higher at the OPE site (876 mm yr -1 ) than at the GISFI experimental station (727 mm yr -1 ). Long-wave radiation is derived from atmospheric conditions, using the equation of  Prata (1996). Atmospheric data gaps are filled by regressions on available data, using two neighbouring meteorologic stations. The gaps represent up to 12 % of the observations for the GISFI site. All soils for all of the lysimeters are described in Table  1 , while all available observations and their characteristics are summarized in Table  S2.
This soil infiltration is the flux of water reaching the soil surface (i. e. the sum of the precipitation not intercepted by the canopy, the dripping from the vegetation, and the snowmelt). At the bottom of the soil column, a fine layer of 5 cm is used to simulate a seepage face lower boundary condition (LBC) instead of the usual free-drainage LBC used in ISBA (see Sect. S1. 3). Such a seepage face LBC is recommended to simulate the lysimeters  (Séré et al. , 2012; Tifafi et al. , 2017). Finally, to compute the initial conditions, a spin-up of 1 year is done, using the first year of each forcing dataset in order to ensure an adequate numerical equilibrium for soil water.
Soil parameters The rich datasets collected by the lysimeters (hourly resolution with 3220 observations on average by lysimeters and by depth) allow us to estimate the soil hydrodynamic parameters, such as in previous studies  (Brooks and Corey, 1966; van Genuchten, 1980; Carsel and Parrish, 1988). For instance, Fig. 1  plots the observed soil water retention curves, namely the volumetric water content, ω, as a function of the logarithm of the absolute value of the soil matrix potential, ψ (dots with different colours for each depth) for lysimeters G2 and O1 (other lysimeters are given in Figs. S1 and S2 in the Supplement). To remove the effect of hysteresis on the observed soil water retention curves (i. e. the difference in soil water retention curve measured under wetting and drying process;  Haines, 1930) , we have averaged the ω values for each ψ values.
4 m depth. In lysimeters O1 and O3, the root depth reached 0. 8 m from 2014 to 2018 and 2 m thereafter. Standard ISBA values of maximum photosynthesis, leaf nitrogen content, and specific leaf area were used for the lysimeters covered by grass, but specific values were derived form the TRY database  (Kattge et al. , 2020)  for alfalfa, as this crop is not a standard vegetation type in ISBA. As there are no measurements of LAI for these lysimeters, the simulation of the LAI can only be compared to the literature. As expected, the simulated LAI is minimal between December and April and maximal in August, and there are variabilities between years (Fig. S4 ). For soils with grass (G4, O1, O2, and O3), the maximum LAI varies between 3 and 5, and the mean annual LAI varies between 1. 3 and 2. These values are similar to those found in other studies  (Calvet, 2000; Darvishzadeh et al.
Results Here, we present the main results for each model approach described in Sect. 2. 3 in terms of simulated soil water and drainage water dynamics, water budget, and intense drainage water events. We used four skill scores to assess the ability of each model approach to reproduce the observation. These include the overall bias between the simulation and observation, the centred root mean square error (CRMSE) computed by subtracting the simulated and observed annual means from their respective time series before computing a standard root mean square error, the coefficient of determination (R 2 ) or the Pearson correlation (R), and the Nash and Sutcliffe (1970) efficiency criterion (NASH) that determines the relative magnitude of the residual variance compared to the measured data variance.
Soil water dynamics The dataset allows the assessment of the evolution of the total soil water mass derived from the mass of the lysimeter, of the soil volumetric water content at several depths, and of the drainage water flux at the bottom of the lysimeters. In the following analysis, periods during which the meteorological forcing is reconstructed or when data are of poor quality (Table S1 in the Supplement) are not taken into account in the score computation. These periods are short, except for the drainage water of lysimeter G3 (23 % of the duration).
Drainage water Drainage at 2 m depth is measured at an hourly frequency. However, to compensate for the measurement limits associated with a 0. 1 mm h -1 threshold, the data are aggregated daily. The annual volume drained varies significantly between the lysimeters at the same sites (Table  S2 ), although it is assumed that they are exposed to the same atmospheric conditions. At the GISFI experimental station, the mean annual drained water is at maximum levels for the bare-soil lysimeters G1 and G2 (> 300 mm yr -1 ). The mean annual drained water is 2 to 3 times lower for the lysimeters covered by vegetation. At the OPE experimental station, all the lysimeters have vegetation cover, and the mean annual drained water shows a variation of only 16 %, from 300 to 363 mm yr -1. Such values are comparable to the volume drained on the bare soil of the GISFI experimental station, which is mainly due to the higher mean annual precipitation at OPE.
Background Currently, little is known regarding the optimal technique for the abdominal phase of RAMIE. The aim of this study was to investigate the outcome of robot-assisted minimally invasive esophagectomy (RAMIE) in both the abdominal and thoracic phase (full RAMIE) compared to laparoscopy during the abdominal phase (hybrid laparoscopic RAMIE). Methods This retrospective propensity-score matched analysis of the International Upper Gastrointestinal International Robotic Association (UGIRA) database included 807 RAMIE procedures with intrathoracic anastomosis between 2017 and 2021 from 23 centers. Results After propensity-score matching, 296 hybrid laparoscopic RAMIE patients were compared to 296 full RAMIE patients. Both groups were equal regarding intraoperative blood loss (median 200 ml versus 197 ml, p = 0.
Materials and methods Data were acquired from the prospectively maintained database from the Upper GI International Robotic Association (UGIRA)  [12]. The UGIRA group was initiated in 2017 as a worldwide group investigating robotic surgery in upper gastrointestinal cancer and provides data on perioperative care of patients who underwent robotic esophagogastric surgery. Participating centers can provide data for the UGIRA database without a minimum number of robotic procedures. This design was intentionally chosen to also compare the first robot-assisted operations which might be under the influence of a learning curve. The registry consists of 23 participating centers and the UGIRA study group has a central institutional review board approval at the University Medical Center of Utrecht (17/837).
Statistical analysis Data management, missingness imputation and propensityscore matching (PSM) were all realized via Python 3. 9  [14]  within the integrated development environment of Visual Studio Code (Version 1. 59). Patients who underwent full RAMIE were compared to patients who underwent hybrid laparoscopic RAMIE. To account for missing data, casespecific and variable-specific missingness of more than 25% was excluded. Eventually, the overall rate of missing data in the whole dataset was calculated as 2. 0% which is widely accepted as a legitimate threshold for imputation. We performed multiple imputations with n = 1000 iterations via Iterative Imputer from Sci-kit learn  [15]. After multiple imputation, a propensity-score matching analysis was performed via the Python package pymatch (adapted from the R package Matching  [16] ) to reduce the effect of known confounders to a minimum.
Study population A total of 807 patients underwent Ivor-Lewis esophagectomy and were included for propensity-score matching. similarity, propensity-score matching was eventually performed with an average accuracy of the score of 65. 11% based on the selected preoperative variables. In Fig. 1B , the threshold is depicted in relation to the retained proportion of cases. Finally, 296 patients were matched for each group. The last two columns of Table  1  demonstrate the frequency distributions and test statistics of both matched groups with all parameters not showing any significant differences. Fig. 1  Overlap of data points with propensity-score plotted against data availability (see A). The augmentation of the PSM threshold does not necessarily lead to higher case numbers which is why a threshold of 0.
It has been shown that hybrid laparoscopic RAMIE can be performed with comparable costs in comparison to full RAMIE in the setting of a high-volume European medical center  [23]. If robotic assistance does truly lead to a decrease in postoperative complications, it is thinkable that costs could be saved on the long run regarding avoidable time and resources during intensive care and postoperative course  [24]. Concerning the limitations of this study, it is to state that the retrospective design based on the UGIRA database may not respect standardized operational steps of the participating centers (such as the implementation of a feeding jejunostomy during the abdominal phase). Similarly, the acquisition of data regarding abdominal lymph node yield and operational time during the abdominal phase is heterogeneously available with a significant missingness due to different approaches by the centers.
The effect of the learning curve may be significant for the results of the presented study since the UGIRA registry holds data from centers that are yet in their learning curve. Anyhow, in order to solely compare the robot-assisted abdominal phase to laparoscopy a cohort without a learning curve effect is needed. In this way, only cases after completion of the learning curve for both the thoracic as well as the abdominal phase could be included in a follow-up study. Finally, the significance of a learning curve effect during the abdominal phase has to be elucidated especially in this setting of two cavity surgery where the thoracic phase is performed robotically in any case. A strength of this study is the fact that it includes a large and international multicenter cohort representing the real practice of specialized hospitals.
ACKNOWLEDGMENTS This work by S. G. , L. W. , and B. Z. was supported by the  National Natural Science Foundation of China  under Grants No. 12005180 , No. 12275134 , and No. 12275232 , by the  Natural Science Foundation of Shandong Province  under Grants No. ZR2020QA083  and No. ZR2022QA026 , and by the  Project of Shandong Province Higher Educational Science and Technology Program  under Grant No. 2019KJJ007. The research by M. K. was financially supported by  Southern Federal University , 2020 Project No. VnGr/2020-03-IF.
Trait 'absorption' is a psychological construct with a rich history that was initially born from early work on hypnotic suggestibility. Absorption characterizes an individual's tendency to become effortlessly engrossed in the contents of experience, whether in terms of external sensory phenomena or internal imagery and fantasy, and is reliably associated with a constellation of psychological, cognitive, and behavioral traits. Here, we conducted a comprehensive neuroimaging investigation of associations between trait absorption and the brain. In particular, we assessed multivariate relationships between absorption scores and neuroimaging measures of grey matter density, as well as static and dynamic resting-state functional connectivity. We investigated these relationships using partial least squares in a discovery dataset (n = 201) and then attempted to reproduce results in an independent replication dataset (n = 68).
Results revealed a lack of significant associations between absorption and grey matter density across both datasets, and a significant association between absorption and static resting-state functional connectivity in the discovery dataset which was not replicated in the replication dataset. Additional control analyses further indicated the lack of a reliable brainabsorption relationship, whereas we found a replicable association between the closely related trait of 'openness to experience' and resting-state functional connectivity. We conclude that absorption is not reliably associated with brain structure or function in the present datasets and discuss factors that may have contributed to this result. This study serves as the first comprehensive and adequately powered investigation of the neural correlates of absorption and motivates future studies to refine the conceptualization of this perplexing trait.
This paucity of neural investigations of absorption is likely due to historical limitations in neuroimaging-based individual-differences research, including a lack of sufficiently powered datasets and poor signal-to-noise ratio in relevant assessments  (Marek et al. , 2022). Critically, however, analytical and technological advances over the past decade  (Buckner et al. , 2013; Dubois and Adolphs, 2016; Raichle, 2009) , combined with the coordinated collection of large-scale neuroimaging brain-behavior datasets  (Casey et al. , 2018; Mendes et al. , 2019; Snoek et al. , 2021; Sudlow et al. , 2015; Van Essen et al. , 2013) , have begun to mitigate such challenges and have given rise to a growing field of individual-differences (functional) MRI research  (Dubois and Adolphs, 2016). That said, it is important to note that, despite this progress, the field is still plagued by statistical concerns and uncertainty with respect to effect sizes of brain-behavior associations and the corresponding sample sizes required for reliable inferences  (Marek et al.
To do so, we leverage two open-access neuroimaging datasets: the PIOP1 dataset (n = 201) of the Amsterdam Open MRI Collection  (Snoek et al. , 2021)  which serves as our discovery dataset, and the MPI-Leipzig Mind-Brain-Body dataset (n = 68;  Mendes et al. , 2019)  which serves as our replication dataset. With respect to GMD, we hypothesized that higher absorption would be associated with greater GMD in regions comprising the FPCN, consistent with past work  (Grant et al. , 2013). Both FPCN-specific and whole-brain exploratory GMD analyses were conducted. With respect to RSFC, we hypothesized that higher absorption would be associated with (1) increased RSFC between regions comprising the FPCN and the default network (DN) and DAN, (2) reduced RSFC between FPCN subsystems, (3) increased RSFC between visual and DN regions, (4) reduced differentiation of unimodal and transmodal cortex, (5) decreased modularity, and (6) increased FPCN dynamic network flexibility.