dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2000) , One-Class Support Vector Machine (OCSVM, domain-based method)  (Wang et al. , 2004) , and Isolation Forest (IF, isolation-based method)  (Liu et al. , 2008). In general, IF and OCSVM are reported to achieve the best outlier detection results for large data sets. LOF has an average performance for different multivariate set sizes. They all stand out for their robustness when noise is introduced into the dataset  (Domingues et al. , 2018). If an extract is considered an outlier in at least one algorithm, an SC value of '1' is given; otherwise, '0'. Supplementary Figure  S81  shows the detailed calculations performed for obtaining the SC score.
Extensive metabolite profiling of all extracts was performed by UHPLC-HRMS/MS operating in Data Dependent Acquisition mode. A careful comparison of the Base Peak Intensity (BPI) traces for both positive and negative ionization modes with the semiquantitative Charged Aerosol Detector trace (CAD) indicated that the positive mode was the most representative of the composition of the extracts. Thus, for this study, only the positive ionization data was considered. The data were processed with MZmine3  (Pluskal et al. , 2010) , producing a list of 16,139 features. After the application of the MS 1 Ion identity feature grouping, these features were grouped into 14,554 IIN, where 3,610 features were identified with their adducts. The resulting tables and spectral data were uploaded to the GNPS website to generate a Feature Based Molecular Network  (Wang et al.
, 2016; Nothias et al. , 2020). The resulting MN was composed of 16,139 nodes (5,922 singletons) and 22,656 edges. As a result of the annotation process against the GNPS public spectral libraries, 2,494 nodes (ca 15%) were annotated, wherefrom 1751 nodes (ca 11%) were considered valid after cleaning and filtering. This was followed by extensive spectral matching against in-silico predicted MS 2 NPs databases from ISDB-DNP and computational annotation with SIRIUS  (Allard et al. , 2016; Dührkop et al. , 2019; Rutz et al. , 2022). After these processes, a total of TABLE 1 Top and lowest five results from the application of Inventa on the Celastraceae set. It shows a summary of the most representative results including the number of reported compounds in the species (rcs) and in the genus (rcg), the new chemical class in the species (nccs) and in the genus (nccg).
The feature-based ion map can be found in Supplementary Figure  S82. Frontiers in Molecular Biosciences frontiersin. org 514 compounds, respectively. For example, the extract ranked three has the same FC as first rank. However, the high number of compounds reported in both species and genus (LC 0. 66) suggested a lower possibility of finding new compounds. The CC value of 1, addition of CCs 0. 5 and CCg 0. 5, implied that at least one chemical class proposed by SIRIUS-CANOPUS had not been reported in species or the genus. CANOPUS proposed the chemical class dihydro-β-agarofuran sesquiterpenoids for the major peaks in the extract according to the BPI (see Figure  2A , zone highlighted in green). Finally, the SC value of 1 indicated that the extract was considered dissimilar within the data set based on its total spectral pattern (MEMO vector), implying a particular composition.
For the Pristimera indica roots extract, the application of the quantile-based filter on the remaining 104 features after intensity-based filtering left a total of 26 features. This data reduction was found consistent with the visible BPI peaks after visual inspection of the chromatogram (see Figure  2A ). Furthermore, it was found to be in good agreement with all the prioritized NPs that could finally be isolated, as detailed below. The effect of filtering was evaluated for the complete set of Celastraceae, and it significantly lowered the number of features for all extracts. Inventa's scores were not strongly affected but highlighted better the putative novel NPs. Depending on the set of extracts to be evaluated, comparing the results before and after filtering may help the selection process.
Acknowledgments The authors extend a special thanks to  BD and Green Mission Pierre Fabre ,  Pierre Fabre Research Institute, Toulouse, France  for the establishment of the collaboration and for sharing the great extract collection. The  School of Pharmaceutical Sciences of the University of Geneva  (J-LW) is thankful to the  Swiss National Science Foundation  for the support in the acquisition of the  NMR 600 MHz (SNF: Equipment  grant  316030_164095 ). L-MQ-G is thankful for the scholarship (N 214171025) from  Ministerio de Ciencia, Tecnología y Telecomunicaciones ,  MICITT ,  Costa Rica. The authors thank  Egon Willighagen  for the help with fully defined SMILES upload on Wikidata.
Data availability statement Inventa can be found on https://github. com/luigiquiros/ inventa (https://luigiquiros. github. io/inventa/). All RAW (Thermo),. mzML datafiles (positive ionization mode) and metadata are available on the Massive MSV000087970, (doi: 10. 25345/C5PJ9N). An interactive visualization can be displayed using the GNPS Dashboard. The raw data files for the NMR and.
RESULT For analysis, survey data from 110 respondents of youth POGI and POGI members were imported into SPSS from Google Sheets. The normality of the Data was analyzed using the Shapiro Wilk test and the Kolmogorov-Smirnov test. Each of the fourteen questions, rated on a 3-point Likert scale, was tuned to give us an idea of whether webinar-style information distribution would be helpful to end-users. The overall utility score was derived from the average of these values, and a generalized standard analytic was performed with this parameter as the dependent variable. Based on Table  2 , the average pretest score was 44. 82, while the average post-test score was 57. 45, with a significance value of p=0. 001 (p<0. 05). This shows a significant difference between the scores before and after the webinar and discussion of materials regarding the complete Covid-19 vaccination for women, pregnant, and breastfeeding mothers.
As new metabolite exerkines are identified, our dataset can be revisited to test and explore possible interactions. We identified 2-HB as an exercise-induced metabolite that may reflect the cytosolic redox state and energy stress at a systemic level. 2-HB levels were elevated in all tissues but only after early active phase exercise at ZT15. Selective accumulation of 2-HB indicates exercise at ZT15 evoked systemic metabolic stress. Normally considered a byproduct of GSH production or threonine catabolism, 2-HB also accumulates when mitochondrial metabolism of its precursor 2-KB is impaired  (Miyazaki et al. , 2015)  or in response to an elevated NADH/NAD + ratio due to increased lipid oxidation. In this context, 2-KB can serve as an electron acceptor, forming 2-HB and regenerating NAD + through oxidation of cytosolic NADH by LDH  (Gall et al.
Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS) Imaging Frozen tissue samples were cryosectioned into 12 mm sections using Microm560 (Microm International, Walldorf, Germany) and thaw mounted onto indium tin oxide-coated conductive slides (Bruker Daltonics, Bremen, Germany). The slides were pre-treated with 1:1 poly-l-lysine (Sigma-Aldrich, Munich, Germany) and 0. 1% Nonidet P-40 (Sigma) before mounting. Measurements were conducted, as described  (Aichler et al. , 2017; Kunzke et al. , 2020). Briefly, the samples were covered with 10 mg/ml 1,5-diaminonaphthalene (DAN) matrix (Sigma-Aldrich) in 70% acetonitrile, using a SunCollect sprayer (Sunchrom, Friedrichsdorf, Germany). Data were acquired in negative ion mode using a Bruker Solarix 7. 0 T Fourier-transform ion cyclotron resonance (FTICR) mass spectrometer (Bruker Daltonics) over a mass range of 50-650m/z and at a lateral resolution of 60 mm.
MetaboAnalyst Metabolites positively or negatively associated with 2-HB were determined according to Spearman correlation adjusted p < 0. 05 after multiple testing by Benjamini-Hochberg. Enrichment analysis of 2-HB associated metabolites was performed using MetaboAnalyst  (Chong et al. , 2019)  with default parameters and Kyoto Encyclopedia of Genes and Genomes (KEGG) IDs. Quantitative Enrichment Analysis was performed via the Enrichment Analysis module using the pathway based KEGG metabolite set library (84 metabolite sets based on human metabolic pathways) or the main-class chemical structures library (464 main chemical class metabolite sets).
Metabolite Correlation and Network Statistics Metabolite data were auto scaled before correlation analysis. Pearson's correlation coefficient was calculated on log normalized data to estimate inter-and intra-tissue metabolite pair correlations. Networks are based on metabolite-pair correlations with an estimated p value < 0. 0001. Undirected networks were analyzed and visualized using the Compound Spring Embedder (CoSE) layout of Cytoscape  (Dogrusoz et al. , 2009). Node degree refers to the number of connected neighbor nodes/metabolites. Node closeness was calculated using MATLAB 2020a centrality function as the reciprocal of the sum of the length of the shortest paths between the node and all other nodes in the graph.
KEGG Enrichment Analysis Metabolites for enrichment were selected based on ANOVA test for differences between groups (exercise vs sedentary, tissue profiling) or paired t test for significant uptake/release (A/V profiling), p values < 0. 05. Metabolites were annotated based on Metabolon KEGG annotation. KEGG pathway definitions were downloaded from https://www. genome. jp, release 98. 0. KEGG pathway significance was estimated using a hypergeometrical distribution test. Data Processing and Quantification for Targeted GC-MS Raw files were converted into centroid mode and exported as netCDF files. Metabolites without available standard were identified based on the spectral similarity and retention index criteria using in-house and NIST 17 spectral libraries. 0. 85 of similarity score and less than 30 RI difference was used for successful annotation.
ACKNOWLEDGMENTS We are grieved by the tragic loss of our friend and colleague,  Paolo Sassone-Corsi. His generous guidance and insightful intellectual contributions were indispensable for this study. We thank  Uyen Thao Nguyen ,  Priya Ramamoorthy , and  Tom Vojko  ( Metabolon ) for technical and statistical support. This study was supported by the  Novo Nordisk Foundation  ( NNF14OC0011493 andNNF17OC0030088 ),  Knut and Alice Wallenberg Foundation  ( 2018. 0094 ),  Swedish Diabetes Foundation  ( DIA2018-357 ),  Swedish Research Council  ( 2015-00165 ),  Swedish Research Council for Sport Science  ( P2020-0064 ),  National Institute of Health ,  Institut National de la Sante et Recherche Medicale (INSERM) , and  Novo Nordisk Foundation Center for Basic Metabolic Research at the University of Copenhagen  ( NNF18CC0034900 ).
Bacterial colonies were then screened for identi cation by Matrix-Assisted Laser Desorption Ionization-Time Of Flight Mass Spectrometry (MALDI-TOF MS) instrument (Bruker Daltonics®, Bremen, Germany) as previously reported  (Seng et al. , 2009). Both of the two strains studied herein had a MALDI-TOF score lower than 2. 0, which did not allow their correct identi cation. Their spectra were then added to the local MALDI-TOF MS database (https://www. mediterranee-infection. com/urms-data-base). 16s Rrna Gene Sequencing And Identi cation The 16S rRNA sequences from both strains were directly extracted from their whole genomes sequences and then, compared by Basic Local Alignment Search Tool nucleotide (BLASTn) to the nr database (non-redundant databases) (BLAST, 2022). The obtained sequence similarity percentages allowed identi cation of the closest species to each strain, and to predict if it was new species (< 98.
, 2016). FAMEs were separated using an Elite 5-MS column and monitored by mass spectrometry (Clarus 500 -SQ 8 S, Perkin Elmer®, Courtaboeuf, France). Obtained spectra were compared with those contained in the repertory databases using MS Search 2. 0 operated with the Standard Reference Database 1A (National Institute of Standards and Technology-NIST, Gaithersburg, USA), and FAMEs mass spectral database (Wiley, Chichester, UK).
Whole Genomic Sequencing And Bioinformatic Analyses First, bacterial DNA was extracted using the EZ1 DNeasy Blood Tissue Kit (Qiagen® GmbH, Hilden, Germany) in line with the manufacturer's protocol  (Anani et al. , 2019). Whole-genome sequencing was performed using an Illumina® MiSeq sequencer (Illumina®, San Diego, CA, USA)  (Caporaso et al. , 2012). Then, sequenced genomes were assembled using SPAdes 3. 5. 0 software  (Prjibelski et al. , 2020) , which reduces short indels and the huge number of mismatches. Raw reads in contigs less than 700-bp-long were removed. Finally, the quality of the sequenced genome was checked using BLAST against the nr/nt database. This method allowed to better explore the relationship between a submitted assembly of our new species to the International Nucleotide Sequence Database Collaboration (INSDC), i.
e. DDBJ, ENA, or GenBank, and the assembly represented in the NCBI Reference Sequence (RefSeq) project. The global statistics section reported general statistics information including Gaps between scaffolds, number of scaffolds, number of contigs, total sequence length, and total ungapped length. Furthermore, taxonomic data were checked according to the best-matching-type strain with the declared new species repertory in NCBI (NCBI, 2022). During annotation, genomic parameters were evaluated including transfer-messenger RNAs (tmRNAs) and transfer RNAs (tRNAs) using ARAGORN version 1. 2 and ribosomal RNAs (rRNAs) using Barrnap version 0. 9  (Laslett et al. , 2004; Hyatt et al. , 2020). Generated le (. faa) was used for BLAST-P analyses against the Clusters of Orthologous Genes (COGs) database, and used for CRISPR-Cas identi cation  (Tatusov et al.
, 2000). Resistance genes were screened using ResFinder  (Bortolaia et al. , 2020). Other bioinformatic tools were also used such as AntiSMASH to search polyketide synthases (PKS) and non-ribosomal peptide synthetases (NRPS)  (Seemann, 2014). Circular maps of the two genomes were generated using CGView (Circular Genome Viewer) software. This Java application converts XML or tab-delimited input into a Vector Graphics format  (Stothard et al. , 2018). Besides, phylogenetic trees of interest were generated with the FastME 2. 1. 6. 1 software to highlight the position of each new bacterial strain among its closest relatives (Meier-Kolthoff et al. , 2019). Digital DNA-DNA Hybridization (dDDH) values were calculated to check the difference between the genomes using the following website (https://ggdc.
, 2020; Wang et al. , 2021) , had been detected in strain Marseille-P2698 genome. In addition, according to our results in ToxFinder-1. 0 software detecting toxins (ResFinder, 2022), our two strains did not possess toxin genes. Culturomica massiliensis (mas. si. li. en'sis. L. fem. adj. massiliensis, form "Massilia", the Latin name of Marseille, France, where the type strain was iso-lated). Bacterial cells are Gram-negative and rod-shaped. They are motile and non-spore-forming, with lengths ranging from 1. 5 to 3. 0 µm and diameters from 0. 3 to 0. 4 µm. The optimal growth conditions are 37°C, a strict anaerobic at-mosphere, and neutral pH. On 5% sheep blood-enriched Columbia agar, colonies appear small, circular, beige to white, and measure between 0. The type strain Marseille-P2698 (= CSUR P2698 = DSM 103121) was iso-lated from a stool specimen of a 66-year-old man with diabetes mellitus.
Funding This work was supported by the  French Government  under the  « Investissements d'avenir » (Investments for the Future) program  managed by the  Agence Nationale de la Recherche  ( ANR , fr:  National Agency for Research) , (reference: Méditerranée Infection  10-IAHU-03 ). This work was also supported by  Région Provence Alpes Côte d'Azur and European funding FEDER PRIMI.
Data Availability Statement The genomic and 16S rRNA gene sequences of Culturomica massiliensis sp. nov. were deposited in the GenBank database under accession numbers FLKM00000000 and LN998061, respectively. The genomic and 16S rRNA gene sequences of Emergencia timonensis sp. nov. were deposited in the GenBank database under accession numbers FLKM00000000 and LN998061, respectively.
Study Design and Population This prospective, observational cohort study was originally conducted between September 2015 and May 2018 at Marseille University Hospital, France, on 621 older patients with cancer to analyze the association of high serum B12 levels with C-reactive protein in older patients with cancer  [27]. Geriatric, oncological, and survival data from this study were secondarily analyzed to evaluate the prognostic value of FS for three-month survival and unplanned hospitalizations; eight patients with incomplete or missing FS assessments were excluded from the analysis. Patients enrolled were all patients with cancer aged 70 years or older living at home or in a nursing home, or hospitalized in rehabilitation units, referred by Oncology and Surgery units to the geriatric oncology unit for a CGA before initiation of any oncological treatment.
Data collection and Baseline Measurements Oncological, geriatric, and biological data were collected prospectively. Functional status was determined using the Activities of Daily Living (ADL) scale according to Katz et al. (impaired <6)  [8]  and the short Instrumental Activities of Daily Living (short IADL) scale according to Barberger-Gateau et al. (impaired <4)  [9, 10]. Geriatric frailties were detected using the G8 screening tool (impaired ≤14/17)  [28]  and the ECOG-PS vulnerability score (impaired ≥2)  [29]. The following geriatric domains were also assessed: nutritional status according to the Body Mass Index (BMI), the Mini Nutritional Assessment scale (MNA)  [30] , and albumin levels. The definition of malnutrition was derived from the recommendations of the French Department of Health (BMI < 21 and/or albumin levels <35 g/l and/or MNA < 17).
Patient characteristics (Table 1) Out of the 621 patients recruited  [27] , eight patients were excluded due to missing data concerning functional status. The final study sample comprised 613 patients. The median age was 81 years (interquartile range 70 to 98 years), the mean age was 81 ± 0. 2 years (youngest patient was 70 years, oldest was 98 years), and 61. 2% were men. A large majority of patients (89. 1%) were community-dwelling patients; only 4. 7% were living in nursing homes and 6. 2% were in rehabilitation units at the time of the survey. The most frequent types of tumours were lung and thoracic (22. 3%), digestive, head and neck tumours (25. 6%), prostate cancer (17. 3%), and urological and gynaecological cancers (16. 2%). Other localizations included breast cancer (n = 48; 7. 8%), haematological malignancies (n = 36; 5.
Study Design We performed a retrospective study in the day surgery unit of the Rouen University Hospital from January 2018 to February 2020. All outpatients were included in this study. We included all patients who underwent regional or general anesthesia (we could not distinguish general anesthesia from regional anesthesia in the database) by an anesthesiologist and those who underwent local anesthesia by the surgeon for day surgery. Patients who did not show up for their surgery or did not receive the various SMS text messages sent at the time of the procedure were not included in this study.
On the seventh day, the patient received another SMS text message asking about satisfaction with the management by using a numerical scale from 0 to 10, the need to have consulted the general practitioner, an emergency service, or to be rehospitalized in the context of the ambulatory surgery performed, as well as the pain felt and communicated using the numerical scale. The patients' answers were centralized by Calmedica and then analyzed in an Excel spreadsheet software (version 2019, Microsoft).
Primary and Secondary End Points The primary end point was the incidence of maximum pain experienced by the patient whether at rest or on mobilization, defined by NRS>3 on a scale of 0 to 10 (0=no pain, 10=maximum pain) on the seventh day following ambulatory surgery. Secondary end points were the incidence of severe pain on day 7 (NRS>6), moderate (NRS>3) or severe pain (NRS>6) on day 1, the presence of postoperative nausea and vomiting on day 1, the incidence of emergency consultation or rehospitalization within 7 days after surgery as well as the risk factors for this variable, and overall satisfaction with the management on a scale of 0 to 10. Demographic data such as age and sex as well as the type of surgery were also collected.
Statistical Analysis Because of the retrospective and cohort nature of this study, we did not perform an a priori calculation of the sample size. The results are expressed as median and first and third quartile for quantitative data and as percentages for qualitative variables. The different data were compared with a chi-square test using the Prism software (version 6, GraphPad) for the qualitative variables. An overall analysis and then a subgroup analysis differentiating the "general or regional anesthesia" group and the "local anesthesia" group was performed. Univariate and multivariate analyses were performed with logistic regression models using the R software (version 3. 0, R Core Team and the R Foundation for Statistical Computing). The variables included in the multivariate model were those clinically relevant, consistent with the literature, and with P<.
Results In this study, we analyzed the data of 6099 patients. The demographic, anesthesia regimen, and the surgical data of these patients are presented in Table  1. On the day after the surgery, 5. 2% (318/6099) of the patients presented with moderate-to-severe pain: 5. 9% (248/4187) in the general or regional anesthesia group and 3. 7% (70/1912) in the local anesthesia group. In the whole cohort, 1. 4% (87/6099) of the patients expressed severe pain, whereas 1. 5% (64/4187) of the patients in the general or local regional anesthesia group and 1. 2%  (23/1912)  in the local anesthesia group expressed severe pain. Seven days after the surgery, 18. 6% (1135/6099) of the patients presented with moderate-to-severe pain at 7 days after the day surgery: 21. 3% (892/4187) of the patients in the general or regional anesthesia group and 12.
Strengths and Limitations There are several limitations in this study. First, this study had a retrospective single-center design. However, the standardized organization of care teams was ensured because it was conducted in an outpatient surgery unit of a university hospital center. Second, we have no data on the different parameters. Patients were not identified as per the anesthesia regimen between general or regional anesthesia. Ophthalmology is also an important contributor to the number of local anesthesia cohorts, thereby leading to possible bias. The postdischarge medical adherence was not assessed in our study and may have contributed to the postoperative pain scores. Third, we did not measure patient perceptions with an adapted skill instrument. Multidimensional scales have now been developed and appear to be more relevant than a simple numerical scale  [28, 29].
The data collected include the period (month/year), the location (French administrative department or region), the production sector (among 19 bird species and 11 stages), the diseases manifested (among 178 referenced diseases in the network) and the pathogens involved including bacteria, viruses and parasites (among 368 referenced pathogens included in the network lexicon). Before 2016, the data were collected as Excel files and were recorded in an Access database. In 2016, a new web platform was developed. Since then, the RNOEA members enter their data in line or upload their files to the web platform. The data are then imported into the RNOEA Network database thanks to a programme developed with the R software. A case of "Enterococcus infection" corresponds to the identification of an Enterococcus in an autopsy of one or several diseased animals originating from a single poultry flock.