dataesr/scientific-paragraphs-categorization huggingface dataset:
Numerical simulations To assess the combined effect of the relative orientation of the AlGaAs crystalline axes and the metasurface lattice with respect to the LC director, we have investigated two geometries with AlGaAs nanodiscs, having thickness of 200 nm, as meta-atoms arranged in a square lattice with axes parallel to either (i) the [110] and [110] crystallographic directions (square geometry, figure  1(b) ) or (ii) the [100] and [010] (diamond geometry, figure  1(c )), with the director always parallel to  [110]. To find indications on the geometry enabling a large SH modulation, we have simulated the nonlinear optical response of such metasurfaces as a function of the radius r of each nanodisc, lattice period p, and orientation of the pump linear polarization. We have performed finite-element method simulations using the commercial software COMSOL Multiphysics.
Acknowledgments The authors acknowledge financial support from the  European Union 's  Horizon 2020 Research and Innovation program  under the Grant Agreement No. 899673  (METAFAST) and from the  Italian Ministry of University and Research  through the  PRIN  Project  NOMEN  ( 2017MP7F8F ). This work was partly supported by the  French RENATECH network. AF and RC would like to acknowledge the financial support ' DEMETRA-Sviluppo di tecnologie di materiali edi tracciabilità per la sicurezza e la qualità dei cibi'  ( PON ARS01 00401 ) funded by  Piano Operativo Nazionale-Ministero dell'Università e della Ricerca.
Premise: Nonstructural carbohydrates (NSCs) play a key role in tree performance and functioning and are stored in radial and axial parenchyma (RAP) cells. Whether this relationship is altered among species and climates or is linked to functional traits describing xylem structure (wood density) and tree stature is not known. Methods: In a systematic review, we collated data for NSC content and the proportion of RAP in stems for 68 tree species. To examine the relationships of NSCs and RAP with climatic factors and other functional traits, we also collected climatic data at each tree's location, as well as wood density and maximum height. A phylogenetic tree was constructed to examine the influence of species' evolutionary relationships on the associations among NSCs, RAP, and functional traits.
Field measurements provide useful data, but due to the seasonality in NSC fluxes, largescale studies are difficult to perform because repeated sampling must be performed throughout the year  (Martínez-Vilalta et al. , 2016). A systematic review of available data with multiple seasonal sampling points can therefore provide an alternative perspective and complementary evidence to validate the relationship between NSCs and RAP in tree stems across species and climates. Along with vessels and fibers, RAP is a key component of wood structure and partially determines wood density  (Ziemińska et al. , 2013; Fortunel et al. , 2014; Osazuwa-Peters et al. , 2017). Martínez-Cabrera et al. (2009)  showed that RP surface area decreased with increasing wood density in shrubs. Conversely, other studies on trees have shown that there is a positive correlation between wood density and xylem ray volume  (Taylor, 1969; Rahman et al.
Here we compiled a database of NSC content, RAP fractions, wood density, and maximum tree height for 68 tree species that span a wide spectrum of characteristics, to provide a new outlook and further insight on their relationships across climates and evolutionary subdivisions. In line with previous findings, we hypothesized that (1) tree stems with large RAP fractions also have high NSC content and that RP fractions play a greater role in NSC storage than AP fractions; (2) RAP fractions and NSC content increase with increasing wood density but are smaller in taller trees; (3) RAP fractions, NSC content, and wood density all increase with warmer MAT, but decrease with increasing MAP.
Description of the data set We combined available NSC and RAP data from specialized databases and a literature survey. We focused on data from tree stems only. Firstly, data on radial parenchyma (RP), axial parenchyma (AP) and RAP for a total of 1439 tree species were taken from the global wood parenchyma database  (Morris et al. , 2016)  and  Zheng and Martinez-Cabrera (2013)  via the TRY Plant Trait Database (https://www. try-db. org/TryWeb/ Home. php; Kattge et al. , 2011). Data on NSCs for 177 tree species were taken from a global NSC database (https://doi. org/ 10. 5061/dryad. j6r5k; Martínez-Vilalta et al. , 2016). When a tree species in the original database had multiple values, we calculated the mean. A comparison of the global wood parenchyma and NSC databases showed that 39 tree species had both NSC and RAP data.
Secondly, according to the selection criteria of  Martínez-Vilalta et al. (2016) , we used the terms "NSC" or "nonstructural carbohydrates" in Google Scholar to search for peer-reviewed scientific papers that were published after the year 2015 (i. e. , were not included in the database developed by  Martínez-Vilalta et al. , 2016) , and that reported NSC content (Appendix S1). We found NSC data for another 18 tree species that were also included in the global wood parenchyma database. NSC data were obtained from tables or extracted from figures using Engauge Digitizer 4. 1  (Mitchell et al. , 2022). In addition, we also searched the xylem collection at CIRAD (Montpellier, France) that comprises microscope slides (tangential, transversal and radial sections of stem wood). In the CIRAD xylem collection, we found 11 tree species for which NSC data also existed in the global NSC database.
Three microphotographs of transversal sections for each species were taken with an APO x5 lens using a digital camera (EOS 500D; Canon, Tokyo, Japan) mounted on a light microscope (BX 60 F; Olympus, Tokyo, Japan). Parenchyma areas were manually colored in Photoshop (Adobe, San Jose, CA, USA) and the proportions of RAP (the total surface area of parenchyma divided by xylem surface area, %) for each species were quantified using ImageJ 1. 52 software (National Institutes of Health, Bethesda, MD, USA). An example of an image is shown in Appendix S2. In most studies, NSC content was expressed as milligrams per gram dry mass; any NSC values in other units were converted to milligrams per gram for comparison. All RAP units were expressed as percentages. The database of NSC and RAP contained data for 68 tree species (Appendix S3), and only species' averages were used.
Because NSC data were collected in different months, we collated the mean and maximum of NSC values and recorded them as NSC mean and NSC max , respectively. NSC mean represents the average state of the NSC during the year and thus balances the influence of seasonal variation. NSC max is the maximum content of NSC throughout the year. In addition to NSC (n = 65) and RAP (n = 60) values, data for mean values of soluble sugars (n = 58), mean values of starch (n = 62), AP (n = 39), and RP (n = 64) were also included in this database. All species' names were checked against standard taxonomic nomenclature. Based on tree evolutionary subdivision, tree species were divided into angiosperms (n = 49) and gymnosperms (n = 19). We also divided tree species into deciduous species (n = 27) and evergreen species (n = 41) according to leaf habit.
We recovered wood density data (n = 65) for the above tree species from the global wood density database  (Chave et al. , 2009; https://doi. org/10. 5061/dryad. 234, Zanne et al. , 2009)  and additional literature sources (Appendix S1), where wood density is defined as the oven-dry mass divided by green volume. We also obtained maximum tree height (H max ) data (n = 63) via the TRY Plant Trait Database (https:// www. try-db. org/TryWeb/Home. php; Kattge et al. , 2011)  and additional literature sources (Appendix S1). We identified the locations (latitude and longitude) from the original publications that contained the NSC data for the 68 tree species. When mean annual temperature (MAT) and mean annual precipitation (MAP) were not presented in the original articles, we used their locations to extract them from Bioclim layers based on the WorldClim Global Climate Database  (Fick and Hijmans, 2017)  for the period 1970-2000 using ArcMap software (version 10.
5, ESRI, San Jose, California, USA). According to this geographical information, the climates where species were growing were divided into temperate (n = 41), subtropical (n = 6), and tropical (n = 21) climate. As in any systematic review of data, there are several caveats. First, studies may differ in trait measuring protocols. Second, some species are widespread and, accordingly, NSC, RAP, and wood density data from independent studies may be sampled in different countries, continents or climates, reducing the quality of the data matching (due to intraspecific variability in traits). To limit these effects, the following criteria for data selection were applied. First, for a given trait, we considered that species included in the same published database followed the same or similar protocols, and thus are comparable by default.
For data from supplementary individual papers, we checked the measuring protocol and assessed whether it was compatible with those described in the global wood parenchyma database and global NSC database cited above. Finally, for each species, we checked the sampling location and year for each of the traits. Eighteen species were found to have trait values from different continents or climates. We conducted the main statistical analyses with and without those species, and the results were not significantly different. Therefore, we present the results for all 68 species. We also analyzed the variability of RAP, NSCs, and wood density within a single species across the different locations. We calculated the coefficient of variation for %RAP, NSC mean , NSC max , and wood density of the same tree species from different locations (when more than three values were available).
(2018)  phylogenetic hypothesis. We also performed a Mantel test between correlation matrices with and without PICs to determine whether correlation patterns differ when including PICs. As correlation tests are sensitive to missing data, we removed the species for which wood trait data were missing (n = 15) when running the PCA. Some tree species were located in the southern hemisphere, therefore latitude values were negative, so we took the absolute value of the latitude value when performing PCA and Pearson analyses. Data in text are means ± SE. All analyses were performed in R software (R Core Team, 2019) using packages APE  (Paradis et al. , 2004) , caper  (Orme et al. , 2018) , lmerTest  (Kuznetsova et al. , 2017) , multcomp  (Hothorn et al. , 2008) , and VEGAN  (Dixon, 2003).
Wood density was positively correlated with %RAP in both deciduous and evergreen species (Appendix S5). Across all species, wood density was positively correlated with %RP, but not with %AP (Figure  3D, G ). We found the same pattern when separately analyzing angiosperm and gymnosperm species (Figure  3E, H ). Within climate zones, %AP and %RP were correlated with wood density only in temperate species (Figure  3F, I ). We found that H max was strongly and negatively correlated with wood density and %RAP, but not with NSC mean and NSC max when all species were pooled together (Appendix S8). When analyzing separately angiosperms and gymnosperms, only wood density was significantly correlated with H max (Appendix S8). When data were divided by climate zones, NSC mean was weakly and negatively correlated with H max in temperate species (Appendix S8), and this relationship was largely driven by the presence of tall, coniferous and temperate species in the data set.
Both NSC mean and NSC max were positively correlated with H max in tropical species (Appendix S8). Wood density and %RAP were negatively correlated with H max in temperate species only (Appendix S8). Similar patterns were found between % RP and H max , while no significant correlations were found between %AP and H max (Appendix S9). Among the 68 species, only 53 species had complete data for NSC mean , NSC max , %RAP, wood density, H max , MAT, MAP, and latitude. The first two PCA axes for the five plant traits explained 56. 9% and 24. 0% of overall trait variation, respectively (Figure  4A ). NSC mean , NSC max , and %RAP loaded strongly on the first PCA axis, while wood density and H max mainly contributed to the second PCA axis (with opposite signs). Pearson correlation showed that %RAP was significantly and positively correlated with NSC mean , NSC max , and wood density, while H max was significantly and negatively correlated with %RAP and wood density (Table  2 ).
ACKNOWLEDGMENTS This work was supported by  China Scholarship Council  (Ph. D. bursary for G. Z. ). This work has benefited from support of a grant from  Investissement d'Avenir grants of the Agence Nationale de la Recherche  ( CEBA :  ANR-10-LABX-25-01 ). This study was co-financed by a  French-Chinese program PHC XU GUANGQI 2019  (ref. :  43379XF ). We thank  Dr. P. Langbour  ( CIRAD, France ) for access to the  CIRAD Xylotech, Montpellier. We thank  Prof. Y. Y. Zhang  ( Xiamen University, China. ) for her valuable suggestions on data analysis. We are very thankful for the constructive comments by the Associated Editor and reviewers, which greatly improved this manuscript.
Recently, the Sony ID7000 became available with different laser configurations that can be remodeled. The ID7000 Software analysis is based on the previously described Weighted Least Squares Method algorithm  [8]  that allows the easy detection of auto-fluorescence (AF) that can be incorporated in the panel as independent fluorescent parameters. The fetal liver (FL) is a highly auto-fluorescent tissue where hepatic and hematopoietic cells differentiate alongside and where hepatic and mesenchymal cells play, yet ill-defined, roles in hematopoietic differentiation  [12]  and in the establishment of the hematopoietic stem cell compartment  [13]. In addition, although surface markers for different populations have been identified, a global analysis of the FL stroma using epithelial and mesenchymal markers has not been undertaken.
| MATERIALS AND METHODS The experiment was designed to identify populations of stromal cells in the mouse FL at different stages of gestation. Before staining, cell suspensions were filtered with a 100 μm cell strainer (BD). All experiments using E14. 5 and E18. 5 embryos were done by pooling FL cells from the same litter in each experiment, in three or more biological replicates. In an independent experiment, FL cells were analyzed after mechanical dissociation (in two biological replicates; data not shown).
| Autofluorescence analysis The unstained samples, after depletion of hematopoietic cells, were analyzed using the autofluorescence finder function as shown in Acquired full spectrum are analyzed with algorithms based on the WLSM as described previously  [8]. The accuracy of the unmixing is ensured by the analysis of the single stained samples. Further manual adjustments (usually not required) can be done. Acquisitions were done with similar settings of the laser PMT. Cells were sorted with a BD FACSAria III (BD Biosciences) according to the guidelines for the use of FCM and cell sorting  [6]. The FACSAria III was calibrated with CST beads following the manufacturer's protocols. Data were analyzed with the ID7000 (Sony, Inc) or FlowJo (v. 10. 7. 3, BD Biosciences) software.
The protocols currently recommended to isolate viable hepatocytes include enzymatic digestion similar to the procedure used in this study  [21]. Alternatively, a perfusion with an enzymatic solution is followed by a purification in a Percoll gradient  [22]. In any of these methods, 5-20 Â 10 6 hepatocytes  [21]  (1%-6%) can be obtained out of the 3 Â 10 8 hepatocytes in a mouse liver  [23]  indicating that no efficient procedure is currently available to isolate hepatocytes. Our study presents several innovations: (1) The ID7000 software analysis provides an easy tool to detect independent AF signals; (2) The unmixing algorithm subtracts the AF signals to allow accurate true fluorescence detection, a feature already present in the SP6800; (3) Importantly, the analytical tool treats the AF signals as fluorescence and increases, therefore, the panel of analyzed parameters.
ACKNOWLEDGMENTS We thank all members of the  FCM core facility , the members of the  Institut Pasteur laboratory ,  Antonio Bandeira ,  Paulo Vieira ,  Rachel Golub  and  Pablo Pereira. This work was financed by the  Institut Pasteur, INSERM, ANR  (grant  Twothyme , grant  DELSTAR  and grant  EPI-DEV ),  REVIVE Future Investment Program  and  Pasteur-Weizmann Foundation  through grants to A. C. This work was financed by  Portuguese funds through FCT/MCTES  in the framework of the project  PTDC/MED-OUT/32656/2017  ( POCI-01-0145-FEDER-032656 ). F. S. S is funded by the  REVIVE Future investments postdoctoral  grant ( Investissement d'Avenir ;  ANR-10-LABX-73 ). MP is funded by  FCT  grant  SFRH/BD/143605/2019.
| Morphological measurements Each worker used in the LT 50 trials was preserved in ethanol for morphological measurements. Cataglyphis spp. exhibit a various level of polymorphism, with only some species being highly polymorphic (bicolor, altisquamis and emmae). We did not select workers according to their size, so we randomly collected 30 workers from the colony that were used for LT 50 trials. Workers were individually mounted on a microscope slide with Vaseline and photographed together with a millimetre ruler using a digital camera Canon 30D with MP-E 65 mm macro lens. We measured standard morphological ant traits that are considered ecologically important  (Parr et al. , 2017)  using ImageJ software  (Schneider et al. , 2012). For each worker, we took 6 measurements: head length, inter eye distance (the distance between the eyes), mesosoma length (measured in lateral view from the edge of the pronotum to the most distant part of the propodeum), tarsus length, femur length and tibial length of the hind leg.
| Sequence analysis and phylogenetic inference We corrected, aligned and analysed all sequences in Geneious v. 8. 0  (Kearse et al. , 2012)  using the MAFFT plugin  (Katoh et al. , 2002)  with the auto option for other parameters set as default and then refined manually. We used DnaSP v. 5. 1  (Librado & Rozas, 2009)  to retrieve haplotypes through the algorithms provided by PHASE. All sequences were deposited in GenBank (Table  S2 ). We implemented Bayesian phylogenetic analyses on the concatenated DNA matrix in MrBayes 3. 2. 6  (Ronquist et al. , 2012)  via the CIPRES Science Gateway  (Miller et al. , 2010). To determine the best fitting substitution model for each partition, we used PartitionFinder v. 1. 1. 1 (Lanfear et al. , 2012) , with the following parameters: linked branch length, models available in MrBayes, BIC model selection, and greedy search algorithm.
g. temperature of the coldest and warmest months), and precipitations of the wet and dry quarters  (Hijmans et al. , 2005). The spatial resolution of the GIS layers was approximately 18. 5 × 18. 5 km (10 arcmin). For each species, we tested the variable importance with the variable selection procedure in the Biomod2 package v. 3. 3. 7  (Thuiller et al. , 2009). We averaged relative variable importance across all available algorithms in this package. After assessing pairwise correlations among all 19 bioclimatic variables, for each of the 19 species, we selected the three most important uncorrelated variables per species (Pearson's r <. 75). We then used these three variables (Table  S3 ) in ensemble forecasting to calculate the climatic suitability for each of the 19 Cataglyphis species. The models were calibrated and projected with the Biomod2 package which included 10 statistical and machine learning methods: (1) generalized linear models (GLM), (2) generalized additive models (GAM), (3) generalized boosted models (GBM), (4) classification tree analysis (CTA), (  5 ) flexible discriminant analysis (FDA), (  6 ) multivariate adaptive regression splines (MARS), (7) random forests (RF), (8) maximum entropy (Maxent), (9) surface range envelopes (SRE), and (10) artificial neural networks (ANN).
| Data analysis We examined the relationship between morphological and thermal traits by first log transforming the 6 morphological measurements and then reducing them with principal components analysis (PCA). PCA is the most common ordination method used in morphometry to represent body size, and in ants it is extensively used to assess ants' ecological requirements  (Oliveira et al. , 2022; Sosiak & Barden, 2021; Weiser & Kaspari, 2006). The first two PC axes accounted for the majority of variation in ant morphology so we used them in subsequent analyses. The first principal component (PC1) captured 97. 3% of variation in ant body size among the 19 Cataglyphis species, which accounted for variation in thorax length and total leg length  (Figures S5 and S6). A small proportion of variation (2.
Lastly, we tested if morphology (PC1 and PC2) or phylogeny are good predictors of species distributions also using Procrustean randomization tests with 999 permutations. All functions used in ordination analyses were from the ade4 package  (Dray & Dufour, 2007). We tested if a phylogenetic signal was present in physiological and morphological traits using the Abouheif Moran test. This analysis examines the trait of interest by focusing on the topology of the phylogenetic tree and not on branch lengths  (Pavoine et al. , 2008). We ran separate Abouheif Moran tests to examine phylogenetic signal in thermal tolerance (LT 50 and CCR time) and morphology (PC1 and PC2). All the analyses were performed in R version 3. 6. 3 (R Core Team, 2020).
But so far, a global soil temperature dataset is only starting to develop  (Lembrechts et al. , 2020)  and will hopefully be available for climatic niche studies in the near future. Using a comprehensive data set of physiological, morphological, phylogenetic and bioclimatic data, we showed that realized niches predicted with SDMs do not correspond to species' thermoregulatory traits in a genus of thermal specialist ants. This suggests that even for insects whose foraging activity and distribution are strongly tied to temperature, species distribution models should be used with caution when predicting climatic niches and distributions under climate change.
Patient collection Gene expression profile and clinical information of 130 wt patients and 6 healthy controls were collected from the TARGET-WT project  [17]. Gene expression data for the fragments per kilobase of nonoverlapping exons per million fragments mapped (FPKM) were computed from the raw count form first and then converted into transcripts per kilobase million (TPM) data. Noise was defined as mRNAs with a TPM value <1 in over 90% of the samples and were removed. Slides fixed in formalin and embedded in paraffin (FFPE) were collected from seven WT patients who underwent tumourectomy at the First Affiliated Hospital of Anhui Medical University (AHMU-WT cohort). Clinical features and follow-up information of the seven patients were obtained by telephone or during consult in the clinic, and we used death as the end point.
Immune infiltration and immuno-/chemotherapeutic response prediction The response to immunotherapy was evaluated by the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm  [19, 20]. Additionally, a subclass analysis of 47 melanoma patients who underwent anti-cytotoxic T lymphocyte-associated protein 4 (anti-CTLA4) or anti-programmed death-1 (anti-PD1) therapies was performed to compare the similarity of expression profile to WT in different risk groups, representing the potential response to immunotherapy  [21]. Additionally, we evaluated the response to chemotherapy for each patient with a public pharmacogenomics database, the Genomics of Drug Sensitivity in Cancer (GDSC) (https://www. cancerrxgene. org). Pazopanib, temsirolimus, and rapamycin, usually used for treating renal cell carcinoma, were chosen for the evaluation.