dataesr/scientific-paragraphs-categorization huggingface dataset:
Comparison dendrograms for similarity analysis of clusters For an unsupervised comparison of the myeloid clusters identified from multiple datasets, we identified the top 2,000 highly variable genes across different clusters, calculated the mean expression of these genes in each cluster and performed hierarchical clustering using the distance defined as (1 - Pearson correlation coefficient)/2. Here, we used the batch-corrected expression value from the CCA function of the Seurat package. For comparison of stromal cell clusters reported in OC ascites  15  and that detected in ascites in our study, we used the top 1,000 highly variable genes.
Differential expression and Gene Ontology enrichment analysis The significantly overexpressed marker genes for clusters were identified using the FindAllMarkers() function of Seurat. Genes with adjusted P value < 0. 05 by Wilcoxon rank-sum test were defined as cluster-specific signature genes. For two different clusters, we used the Wilcoxon test to evaluate the significance of each gene, with multiple hypothesis correction using the BH procedure. Genes with adjusted P value <0. 05 were considered as differentially expressed genes that were further used for GO enrichment analysis with the clusterProfiler package (v. 3. 14. 3). GO terms with adjusted P values <0. 05, using the BH procedure, were considered significant.
Cell-cell interaction analysis We used cellphoneDB (v. 3. 0. 0)  64  based on cellphoneDB database v. 2. 0. 0 to infer cell-cell interactions of selected ligand-receptor pairs between tumor-enriched macrophages and T cell subsets, DES + mesothelial Article https://doi. org/10. 1038/s43018-023-00599-8 cells and indicated immune cell subsets, as well as DC clusters and MAIT cells. The potential interaction strength between two cell subsets was predicted based on the expression of ligand-receptor pairs. The enriched ligand-receptor interactions between two cell subsets were calculated based on a permutation test. We extracted significant ligand-receptor pairs with a P value <0. 01.
Survival analysis The TCGA OC data and microarray data of GSE9891, GSE19829 to GPL8300 were used to evaluate the prognostic performance of gene sets derived from different EC clusters. We used the mean expression of signature genes for distinct cell clusters to evaluate the enrichment of corresponding EC types in patients diagnosed with HGSOC. Specifically, for IL13RA1 + and VCAM1 + EC clusters, we used the top 20 differentially expressed genes of these two clusters as signature genes to define their signatures, (provided in Source Data Fig. 7f ). We performed survival analysis using the Cox proportional hazards model implemented in the R package survival (v. 3. 2. 3) to correct patient age and plotted Kaplan-Meier survival curves using the R function ggsurvplot.
Acknowledgements We thank all patients and their families for participating in this study. We thank  S. Cheng  for discussions. This project was supported by funding from the  National Natural Science Foundation of China  ( 81930064  to Xipeng Wang,  91942307 ,  31991171  and  81988101  to Z. Z. and  32100722  to Z. Li),  National Key Research and Development Plan  ( 2022YFC2704201  to Xipeng Wang) and  Beijing Municipal Science and Technology Commission  ( Z201100005320014  and  Z211100003321005  to Z. Z. ) and sponsored by the  Program of Shanghai Academic/ Technology Research Leader  ( 22XD1402000  to  Xipeng Wang ).
Data availability The scRNA-seq and scTCR-seq data supporting the findings of this study have been deposited at GSA-Human under accession code PRJCA005422, with the processed data deposited in Mendeley Data (https://doi. org/10. 17632/rc47y6m9mp. 1)  65. An interactive web portal for analysis and visualization of single-cell data is available at http://ov. cancer-pku. cn/. Bulk-RNA-seq data of mice are available from NCBI Gene Expression Omnibus under accession no. GSE223121. Previously published microarray data analyzed together are available under accession codes GSE9891 and GSE19829 to GPL8300. All other supporting data of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.
All n = 8 ascites samples from 10 HGSOC patients were analyzed. d, All-by-all heat map showing different gene expression in myeloid cells from datasets of our study (OV) and that of HCC and CRC (excluding all proliferative subsets). Clustered by similarities between myeloid subsets. Rows represent clusters and columns represent genes. N = 3 tumor types were used for analysis. e, Heatmap showing expression levels of top 20 differentially expressed genes of M01 and M02 in all three DC clusters (left), and correlation of DC-LAMP3 (M03) with DC-CD1C (M01) and DC-CLEC9A (M02) calculated using these genes (right). Genes, P value < 0. 05, Two-sided Wilcoxon test adjusted by Benjamini-Hochberg (BH) procedure; log2(fold change) > 0. 5. Correlation was analyzed using a Pearson correlation coefficient.
Rows represent clusters and columns represent genes. All n = 8 ascites samples from HGSOC patients were used for analysis. f, UMAP plots showing the similarity of ascites-derived cancer-associated fibroblasts (CAF) reported by Aviv (left) and stromal cells enriched in ascites in our dataset (right). For a-c, all n = 31 HGSOC samples were used for analysis. https://doi. org/10. 1038/s43018-023-00599-Distribution and gene expressions of endothelial cells as well as of E02, E06 with prognosis. Tissue distribution each endothelial cell cluster identified in patients, colored by different tissues and clusters (lower). b, Heatmap showing the expression levels of indicated marker genes of tip-like endothelial cell in 8 endothelial cell clusters. Rows represent clusters and columns represent genes.
c, Heatmap showing the expression levels of genes involved in MHC-II antigen presentation in 8 endothelial cell clusters. Rows represent clusters and columns represent genes. d, The Kaplan-Meier overall survival curves of HGSOC patients grouped by the gene signature expression of VCAM1 + ENDO cells (E06). TCGA OV data. HR, hazard ratio. Multivariate Cox regression. e, The Kaplan-Meier overall survival curves of HGSOC patients grouped by the gene signature expression of IL13RA1 + ENDO cells (E02). TCGA OV data. HR, hazard ratio. Multivariate Cox regression. f, The Kaplan-Meier overall survival curves of HGSOC patients grouped by the gene signature expression of VCAM1 + ENDO cells (E06). Microarray GSE9891 and GSE19829-GPL8300. HR, hazard ratio. Multivariate Cox regression. Statistical significance (P value) was determined by Kaplan-Meier survival curves and log-rank test (d-f).
Following a comprehensive assessment, the university initiated a pilot program to facilitate teachers and students in exploring potential applications of ChatGPT. However, the students were permitted to engage with ChatGPT solely under the supervision and approval of their respective teachers. Recently, the Hong Kong Polytechnic University and the City University of Hong Kong decided to offer free access to ChatGPT and its version, respectively  (Fung, 2023). Given the advantages of ChatGPT in supporting students' active learning and the trend of embracing the use of AI technology among institutions in Hong Kong, the growing popularity of ChatGPT is expected, and factors that drive students' use intentions would be under the spotlight in the education sector. As suggested by expectancy theory, individuals have a higher intention to act if it is associated with more positive outcomes  (Vroom, 1964).
The large language model represented by ChatGPT exhibits the ability to think and answer questions like a human being, manifesting a creative capacity that was previously unavailable to AI, marking a qualitative leap from quantitative change  (Kosinski, 2023). Similar to  Chang and Hideyoshi (2021) , who found that IM is an important motivator that influences user interaction with a virtual assistant, we expect that IM should impact BI to use ChatGPT. Additionally, PU and PEOU highly depend on learners' ability to interact with ChatGPT and not just on the technology itself. It is possible that even though ChatGPT is easy to use, learners may not use it simply because they fail to reflect on the answers generated from ChatGPT and provide appropriate responses. As PU and PEOU highly depend on the users' ability to use them, we expect that the results of previous studies cannot be generalized to the use of ChatGPT.
Hackers can then publish a malicious package to repositories under the name of non-existent packages recommended by ChatGPT. When users later query a question similar to ChatGPT, it suggests a previously non-existent package. Innocent users may then unknowingly use the package and execute the malicious code contained within it. Thus, hackers can successfully deliver malicious packages to unsuspected users with the aid of ChatGPT  (Wu, Duan, & Ni, 2023). ChatGPT may pose privacy risks to learners. With insufficient measures for preserving and sharing personal data, the ChatGPT developer is likely to encounter challenges complying with General Data Protection Regulation by the European Union  (Lacapra et al. , 2023). For example, ChatGPT may share user data with third-party entities without explicit user permission  (Wu, Duan, & Ni, 2023).
Research method In this study, two software packages were used for the data analysis: analysis of moment structure (AMOS) and Smart PLS 3. 0. (PLS). AMOS was used to test the goodness of fit (GOF) indices in the measurement model (MM), whereas PLS was used to test the validity, reliability, discriminant validity, and proposed hypotheses. Structural equation modeling (SEM) was used because of multiple measurement items against constructs within the multivariate environment and to identify the association between dependent and independent variables simultaneously instead of individual testing of relationships  (Hair et al. , 2019). Therefore, the two-step approach endorsed by  Gerbing and Anderson (1993)  was used to conduct the SEM analysis of the data. First, the measurement model was analyzed to determine the relationship between the observed and unobserved variables through confirmatory factor analysis (CFA) using PLS.
Data collection and respondents A quantitative cross-sectional survey-based study was conducted in July 2023. Using convenience sampling, we randomly distributed the revised questionnaire using a user-friendly survey tool (www. qualtrics. com) to undergraduate students from eight universities in Hong Kong after a pilot study of 50 students. The respondents' participation is voluntary, with options for them to decline participation or exit the survey at any time. As it was challenging to estimate the total sample size,  Hair et al. 's (2019)  criteria were used to determine the population size, that is, five to ten responses per item. As there were 16 items, a sample size of 80-160 was regarded as sufficient. Of the 526 returned questionnaires, 473 respondents (89. 9% of the total respondents) indicated their experience of using ChatGPT.
Confirmatory factor analysis This study comprises an overall CFA model, with a discussion of MM development. To ensure CFA accuracy,  Hair et al. (2019)  examined GOF indicators and their convergent and discriminant validities. The first step of the CFA was to evaluate the GOF indices of the MM. The GOF indices of our MM and the values recommended in the literature are listed in Table  3. The findings indicate that the overall MM offered an adequate fit for the data with all 16 items. The GOF results suggest that the chi-square test is significant at the 0. 010 level. However, the absolute fit index of the minimum discrepancy chi-square can be ignored if the sample size exceeds 200  (Hair et al. , 2019). The GFI value was 0. 972, which is greater than the recommended value of 0. 9. After adjusting for degrees of freedom relative to the number of variables, the adjusted GFI (AGFI) was 0.
Limitations and future work This exploratory study had several limitations. First, the scope of respondents was restricted to Hong Kong students. Given the low digital literacy among Hong Kong students, future studies can expand this data collection to developing countries with lower digital literacy and other developed countries with higher digital literacy. Second, the education level of the sample was confined to undergraduates who were recruited randomly from eight universities in Hong Kong. Future research could adopt stratified probability sampling to include students of different education levels or disciplines to generalize the results to a larger population. To achieve a comprehensive understanding of ChatGPT acceptance, researchers should employ longitudinal case studies that incorporate diverse data sources  (Liu & Ma, 2023).
Detection of eccDNAs and TE-mediated SVs in epigenetic mutants To characterize the eccDNA repertoire of the wild type and epigenetic mutants (ddm1, polIV, rdr6, ddm1 polIV, ddm1 rdr6, and ddm1 polIV rdr6), a series of 21 mobilome-seq experiments were conducted (Fig. 1a ). Briefly, after removal of genomic linear DNA with exonuclease V, the circular DNA molecules were amplified by random rolling circle and sequenced using Illumina or ONT platforms (Supplementary Fig. 1 ). Additionally, thirteen whole genome resequencing datasets using ONT long reads were produced from these samples, to investigate SVs (Fig. 1a ). The most abundant class of TE-eccDNA was identified as corresponding to the long terminal repeat (LTR) retrotransposon EVD, a TE previously observed as eccDNA in hypomethylated mutants  38.
4 ), despite a very high coverage with ONT reads (up to 34,695X, Fig. 1c ). Given the high frequency of truncated eccDNAs we analyzed their potential impact on genomic SVs. In this aim we selected EVD containing reads in our ONT genome resequencing datasets for WT, ddm1, ddm1 polIV, and ddm1 polIV rdr6 mutants. We excluded single polIV and rdr6 mutants and ddm1 rdr6 double mutants as there was no new detected EVD insertion in these mutant backgrounds. New insertions corresponding to truncated retrotransposon structures were detected at distinct loci in mutants (Fig. 2c, d ). We also observed a truncated insertion for ATCOPIA21 (Supplementary Fig. 5 ). Two of these truncated insertions contain clear target site duplications (TSDs). Of note, all truncated insertions possess two LTRs (Fig. 2c, d ) suggesting that only a fraction of truncated TEs are linked to new insertion events.
Both eccDNAs and genomic SVs contain chimeric TEs All eccDNAs described so far consisted exclusively of TE-derived DNA. In contrast, in ddm1 polIV rdr6 plants we observed a striking example of chimeric eccDNA, defined as a circle originating from different genomic loci. In this eccDNA, supported by 7 copies in a single long read (Fig. 3a ), a partial EVD fragment and a portion of the AT5G66440 gene (encoding a tRNA methyltransferase) had fused. EVD containing reads were extracted from ONT mobilomeseq datasets for the triple mutant plants and mapped to the reference genome. The mapping profile confirmed the presence of chimeric reads at the AT5G66440 locus (Fig. 3b ). Additionally, we detected an EVD insertion at the corresponding locus (AT5G66440) in the genome of the same plants (Fig. 3c ), flanked by a 5 bp TSD, a signature of integrase-mediated insertion (Fig.
Detection of TE insertion polymorphisms from ONT genomic reads Reads spanning the entire insertion and deletion sequence do not cause alignment breakpoints, but are flagged in the CIGAR. We developed a script to filter the CIGAR output. This pipeline can be found on GitHub (https://github. com/njaupan/CIGAR_SV). Briefly, in order to extract all reads containing insertions and deletions, we generated a PAF file from minimap2 (-cs -cx map-ont)  69. The CIGAR metrics were then indexed until the position of the SV on the reference genome. Breakpoints with more than 4 supported reads at the same position were selected. The start and end positions of the breakpoints were extracted from the PAF file and grouped to generate common breakpoints displayed in BED format. The breakpoint locations were finally filtered for the presence of 5-20 bp TSDs supporting bona fide TE insertion polymorphisms.
Acknowledgements We thank our EpiDiverse colleagues for stimulating discussions on eccDNAs,  Drs. G. Moissiard ,  T. Lagrange  and  S. Jackson  for fruitful comments on earlier versions of the manuscript and the platform " Bio-Environment" (UPVD, Perpignan , https://bio-environnement. univ-perp. fr/en)for sequencing. This work was supported by a grant from the  French National Agency for Research  ( ANR-21-CE20-0047  CropCircle) and a  European Training Network grant  ( EU H2020 Marie Skłodowska-Curie No 764965 EpiDiverse ) to M. M. ; a  LABEX TULIP  ( ANR-10-LABX-41 ) and  EUR   TULIP-GS  ( ANR-18-EURE-0019 ) grants to M. M. 's host lab LGDP. M. C. is funded by the  Royal Society   Research Grant   RGS\R1\201297  and  UK Research through the Biotechnology and Biological Sciences Research Council (BBSRC)  grant  BB/W008866/1.
We present a spectroscopic analysis of a sample of 48 M-dwarf stars (0. 2 M e < M < 0. 6 M e ) from the Hyades open cluster using high-resolution H-band spectra from the Sloan Digital Sky Survey/Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey. Our methodology adopts spectrum synthesis with LTE MARCS model atmospheres, along with the APOGEE Data Release 17 line list, to determine effective temperatures, surface gravities, metallicities, and projected rotational velocities. The median metallicity obtained for the Hyades M dwarfs is [M/H] = 0. 09 ± 0. 03 dex, indicating a small internal uncertainty and good agreement with optical results for Hyades red giants. Overall, the median radii are larger than predicted by stellar models by 1. 6% ± 2. 3% and 2. 4% ± 2. 3%, relative to a MIST and DARTMOUTH isochrone, respectively.
2016; Version 2020-01-30 ; a compilation of measurements of effective temperatures, surface gravities, and metallicities obtained from high-resolution, high signal-to-noise spectroscopy) with the list of Hyades members from  Goldman et al. (2013)  finds hundreds of matches (these results will be discussed in Section 4). However, despite the great amount of data available in the literature for the Hyades cluster, and the general consensus about it being a metal-rich open cluster, there have been no high-resolution spectroscopic abundance studies of the Hyades M dwarfs. Because the Hyades cluster is quite nearby, its M-dwarf members can be observed with available midsize telescopes and high-resolution spectrographs, such as those of the SDSS APOGEE survey  (Majewski et al. 2017). APOGEE has targeted a large number of Hyades members, including faint M dwarfs to a magnitude limit of H ≈ 12.
Stellar Parameters and Metallicities We performed spectral synthesis modeling for APOGEE spectra, in order to derive effective temperatures, surface gravities, metallicities, oxygen abundances, and projected rotational velocities for 48 M-dwarf stars from the Hyades    open cluster. This spectral analysis employed 1D plane-parallel LTE MARCS model atmospheres  (Gustafsson et al. 2008) , the APOGEE DR17 line list  (Shetrone et al. 2015; Smith et al. 2021 ) and the radiative transfer code Turbospectrum2020 (Plez 2012) to compute synthetic spectra. We used the BACCHUS  (Masseron et al. 2016)  wrapper to derive chemical abundances, but took into account the associated line spread function (LSF) for each of the spectra analyzed, as the APOGEE spectra show fiber-to-fiber LSF variations, as well as wavelength LSF variations across the chips  (Nidever et al.
The median metallicity for the M dwarfs studied here is 〈[M/H]〉 = 0. 09 ± 0. 03, and shows no significant trend as a function of T eff ; it is also in good agreement with the median metallicity for the red giants from the literature (〈[M/H]〉 = 0. 12 ± 0. 03). The literature results reveal a dip in metallicity for the hotter dwarfs with effective temperatures between 6000 and 7000 K. The estimated uncertainties are shown as error bars. that analyzed the hotter main-sequence and red giant stellar members of this cluster, and their metallicities can be compared to the M-dwarf metallicity scale derived here. Using the PASTEL database  (Soubiran et al. 2016 ) as a starting point and by adding results from the literature for Hyades members, we compiled a total of 286 metallicity measurements for stars in the Hyades open cluster (with T eff in the range between 4500 and 7000 K), that were analyzed in 37 published works from 1990 to the present (note that these are not all studies about the Hyades open cluster, but highresolution studies that have results for at least one Hyades member.
(2018). Using the derived effective temperatures and luminosities we investigated radius inflation in the Hyades open cluster M dwarfs. The M-dwarf radii were compared to predicted radii from different sets of isochrone models that do not consider magnetic fields nor spots: DARTMOUTH  (Dotter et al. 2008) , MIST  (Choi et al. 2016) , and PARSEC  (Bressan et al. 2012; Nguyen et al. 2022) , and were found to be, overall larger than the model isochrones, except for the PARSEC isochrone (which was adjusted to empirical data of stellar radii in eclipsing binaries). The median (±MAD) radius inflation values for the sample considering MIST and DARTMOUTH models are, respectively, 1. 6% ± 2. 3% and 2. 4% ± 2. 3%. More detailed comparisons to isochrone models were investigated by dividing the M dwarfs into subsamples comprised of rapid rotators (P rot < 5 days) and slow rotators (P rot > 5 days).
Acknowledgments We thank the referee for comments that improved the paper significantly. F. W. acknowledges support from fellowship by  Coordenação de Ensino Superior-CAPES. K. C. acknowledges partial support by the  National Aeronautics and Space Administration  under grant No. 18-2ADAP18-0113 , issued through the  Astrophysics Division of the Science Mission Directorate. K. C. and V. S. acknowledge that their work here is supported, in part, by the  National Science Foundation  through  NSF  grant No. AST-2009507. D. S. thanks the  National Council for Scientific and Technological Development-CNPq. J. G. F. -T. gratefully acknowledges the grant support provided by  Proyecto Fondecyt Iniciación  grant No. 11220340 , and also from  ANID Concurso de Fomento a la Vinculación Internacional para Instituciones de Investigación Regionales (Modalidad corta duración) Proyecto  No.
As a predator case study, we use the most abundant species of diving predator in the Southern Ocean, the macaroni penguin (Eudyptes chrysolophus). For a foraging success metric, we used two decades of pre-breeding arrival body mass data for penguins returning to breed at Marion Island following their winter migration. Variability in penguin mass has been directly related to diving activity  (Lescroël et al. , 2021) , and changing prey abundance  (Croll et al. , 2006). Arrival body mass can therefore be considered a practical measure of foraging success, reflecting cumulative prey conditions over the preceding months of their migration, and which may then directly affect population dynamics (e. g. ,  Crawford et al. , 2008). However, while winter tracking data do exist for this population, these tracks are largely restricted to the first half of the winter migration  (Reisinger et al.