dataesr/scientific-paragraphs-categorization huggingface dataset:
analysis of the mitochondrial genomes in basal hymenopterans. Nature Scientific Reports. [Online] 6, 20972. Available from: doi:10. 1038/srep20972 [Accessed: 26 March 2019]. Data Accessibility The mtDNA alignment used to design the primers and probes will be uploaded to Dryad open repository. Author contributions The research was planned by PNG, TWJG & MCF. mtDNA sequences were compiled and aligned by AR. Primer and TaqMan MGB probe design was done by PNG. Assay validation was carried out by PNG and LMB. PNG, RV, TWJG and CW carried out fieldwork in South Africa. SOH and TS carried out whole genome sequences analyses. PNG wrote the article with input from all authors.
Acknowledgements PNG and MCF were supported by the  Morris Animal Foundation , the  Leverhulme Trust  ( RPG-2014-273 ), the  Natural Environment Research Council  ( NERC NE/E006841/1 ) and a PhD DTP award by the  ICL Grantham Institute. MCF is a fellow in the  CIFAR 'Fungal Kingdoms' program. The authors would like to thank  Tim James ,  University of Michigan  for providing DNA extract of isolates  UM42  and  CLFT-065.
Material and methods Cross-sectional data were obtained from the French PPS in 2017 which provided a nationally representative sample of adult inpatients in 401 healthcare facilities  [11, 12]. In the protocol for European PPSs  [6] , current individual antimicrobial treatment was characterized by up to four antimicrobial agents prescribed simultaneously. For each agent the prescription context and one of 22 clinical indications were recorded. For this article, we only considered prescription context where the agent is intended for curative treatment of an infection and excluded contexts of surgical or medical prophylaxis. Clinical indications correspond to the anatomical site of the infection targeted by the treatment (in the PPS protocol this variable is termed diagnosis). Independently of treatment information, the presence of an HAI at study time (active HAI) was recorded for each inpatient.
Cytometric beads array Cytokines expression was evaluated using the Human T Helper Cytokine Panel (Biolegend, San Diego, CA) according to the manufacturer's recommendations. Briefly, the supernatants were diluted with a 1:2 ratio: 25 µl of diluted supernatant were transferred into the 96-well plate, 25 µl of mixed capture beads, 25 µl of detection antibodies cocktail and 25 µl of SA-PE were added into each well. Data were acquired on BD™ FACS Fortessa flow cytometer and analyzed with Biolegend legendplex software.
Safety assessment After each patch application, participants were observed for 90 minutes. Diary cards recorded solicited local and systemic reactions for 14 days after each application. Adverse events and serious adverse events were recorded through the entire study period; reactogenicity events were solicited through day 42. An independent Data and Safety Monitoring Board (DSMB) reviewed two interim safety analyses once all participants of cohorts 1 and 3 had reached day 28 (visit 5) and day 16 (visit 4), respectively, before dose escalation to Viaskin-PT 50 mg.
Statistical analyses The sample size was based on clinical and practical considerations and not on a formal power calculation. Categorical variables are described by counts and percentages, and continuous variables by means and standard deviations or median and interquartile ranges (IQR) for non-normal distributions. Differences between Viaskin-PT and Viaskin-placebo were assessed at day 42 by Wilcoxon's rank sum test (IgG concentration) or Fisher's exact test (seroconversion status and seroresponse rate). When applicable, two-sided tests at the 5% significance level were used with no multiplicity adjustment. Statistical analyses were performed by DBV Technologies, Paris, France using the Statistical Analysis System SAS® Entreprise Guide 7. 1 (SAS Institute, Cary, NC, USA). The statistical analysis plan is provided by request.
Acknowledgements The authors thank the study staff of the  Clinical Trial Unit (CTU) , the paediatric  CTU Plateforme  de recherche p ediatrique and participating volunteers at the  University Hospital of Geneva, Switzerland  for their contribution to the study. The authors would also like to thank  DBV's team  for their contribution;  C ecile Vauleon  and  Chiara Cefala  for regulatory submissions and V eronique Dhelft for vaccine pharmaceutical and analytical development. Thanks to  Christine Kreuz  from  Bertin Pharma  for Chinese hamster ovary serological assay development and testing. The authors would also like to thank the  BioNet-Asia team  for their contribution:  Jane Spiegel  for regulatory preparation,  Mukesh Chauhan  and  Woranut Suksotkhiao  for manufacturing and release of PTgen.
Post Autopsy Diagnostic Methods We used Next Generation Sequencing (NGS)-based transcriptomic analysis to search for viral transcripts in meninges and brain frontal lobe. This technique is agnostic and provides sequences of both the human transcriptome and pathogen, the latter of which that may be identified by similarity with known microbes. RNA from meninges and brain frontal lobe samples were extracted and used to construct a cDNA library and sequenced using the Illumina technology. Sequences were aligned after translation against a comprehensive viral protein reference database (details in supplementary data). We completed the viral genome gaps by applying standard molecular biology methods (supplementary data). Once the pathogen identified, we used previously described PCRs (Supplementary data and  [5] [6] [7] ) to confirm the presence of virus from necropsy samples and CSF.
Results We found sequences in meninges and brain frontal lobe samples covering the quasi-full length of a genome related to EBLV-1a lyssavirus (Genbank accession number MW551946). Based on phylogenetic analysis (Fig. 3 ), the closest relatives were other EBLV-1a strains from bats identified in France  [12]. Based on PCR results, the viral load was around 500-fold higher in the frontal lobe than in meninges. In contrast, no viral RNA was detected in CSF sampled on the day of hospitalization and 34 days later. Immunochemical analyses of multiple paraffin-embedded brain samples using a polyclonal antiserum detecting EBLV-1a was negative, but electronic microscopy suggested the presence of rhabdovirus particles (Supplementary data). Infectious virus was not detected from these samples. A high titer (1/1200) of antibodies neutralizing EBLV-1 virus was detected in the serum sampled the day of hospitalization, but not detected in the CSF samples collected the same day and 34 days later.
Notes This work was supported by Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases" (grant no. ANR-10-LABX-62-IBEID). The authors have declared no conflict of interest. At day 5, Fluid Attenuated Inversion Recovery (FLAIR) transverse images showed an apparently normal cerebellum (A) whereas a well demarcated zone of high intensity was visible at the bottom of the pons (B). At that stage, the thalamus and caudate nucleus were slightly hyperintense bilaterally (C) and the other part of the brain seemed normal (D). At day 23, there was an obvious edema of the cerebellum (E) and the high intensity signal of the pons had diffused to the dentate nucleus of cerebellum bilaterally (F). The brain was overtly swollen with an increased high intensity signal of the lenticular nuclei and insula (G).
Metatranscriptomics Nucleic acids from meninges and brain frontal lobe samples were extracted after a bead-beating step with the MagNA Lyser using the MagNA Pure Compact RNA Isolation kit (Roche Molecular Systems, Inc. ) including a DNase treatment. Total RNA was used to construct a cDNA library with the SMARTer Stranded Total RNA-Seq Kit -Pico Input Mammalian (Takara Bio, kit v. 2). A total of 49 and 94 raw million reads of 150 bp for meninges and frontal lobe sample respectively were processed with an agnostic in-house bioinformatics pipeline as described 1. Sequences were aligned after translation against a viral protein reference comprehensive database (RVDB-prot. V20. 0 ) 2. Ninety percent coverage of the genome was obtained by NGS from the frontal lobe sample.
Source of fish The fish used in this experiment came from a study supported by the FP7 programme of the European ARRAINA project (Advanced Research Initiatives for Nutrition and Aquaculture) (N_288925). The aim was to study the long-term effects of diets free of FM and FO from the first feeding onwards  (6, 41). Rainbow trout was produced at the INRAE experimental fish hatchery of Lées Athas (Pyrénées-Atlantiques, France). At the stage of yolk-sac larvae, the rainbow trout fry was separated randomly into twelve groups and fed three experimental diets in quadriplicate for each diet. The fish were reared from 0. 14 g body weight (BW) during 7 months in 50 l tank (310 fish per tank) in the same experimental farm with a natural photoperiod and a constant water temperature of 7 ± 1°C. At an average body weight of 12⋅5 g, the fish were then transferred to the INRAE experimental fish farm in Donzacq, Landes, France.
The acquisition conditions of plasma and extracts (diet, liver and muscle) are summarised in Table  3. To optimise NMR acquisitions, automated tuning and matching, locking, shimming (TopShim) and 90°hard pulse calibration (pulsecal) were performed for each sample. A Fourier transformation was applied to the signal after zero-filling (64k) for extracts and apodization (LB 0⋅3 Hz) for extract and plasma spectra. The resulting spectra were manually phased with TopSpin (v. 3⋅0, Bruker). For plasma, diet and tissue extracts, chemical shift calibration, baseline correction, peak realignment, non-uniform bucketing and signal-to-noise ratio were determined using the NMRProcFlow web tool (www. nmrprocflow. org)  (45). Each spectral region of interest was determined manually, using either the intelligent bucketing module or the variable size bucketing module of the NMRProcFlow for each dataset.
The data were then standardised and normalised to the total intensity of the spectra. Compounds were identified by comparing the spectra of individual compoundsanalysed under the same conditions of preparation (solvent and/or pH)to those available in the home database, the NMR HMDB (www. hmdb. ca), BMRB (http://www. bmrb. wisc. edu/metabolomics/) and Chenomx (Chenomx Metabolite Reference Libraries, www. chenomx. com) databases, and based on data from the literature  (24, 26)  and their annotation status according to MSI Metabolomic Standards Initiative  (46). For a selection of metabolites, identification was confirmed by spiking commercially available reference compounds on representative samples and by the acquisition of 2D 1 H-NMR spectra on a selection of samples. Patterns of resonance that could not be identified were named according to the following example: unkDD6.
15, meaning the unknown doublet of a doublet pattern of resonances centred on 6⋅15 ppm. For the diet 1 H-NMR spectra, resonance groups were selected and integrated using the NMRProcFlow  (45)  , then the absolute concentration of each compound was calculated using the electronic reference (TopSpin ERETIC2 module), and the calibration of signals with glucose (2⋅5-100 mM) and glutamate (2⋅5-30 mM) standard curves. The concentration in mol/l was then converted to g/l and transformed into a content by dividing it by the amount of lyophilised powder used for extraction. The content of each organic or amino acid was expressed as g of the acid form per weight unit. The content of NMR unknown compounds was calculated, hypothesising that the observed resonance corresponded to one proton and using an arbitrary molecular weight of 100 Da.
Acknowledgments The authors wish to thank  Dr Sadasivam J. Kaushik  for his invaluable support, his ideas and the design of the experimental diets;  Dr Viviana Lazzaroto  for her help and discussion on the experiment; and the technical staff for their great contribution, especially  Frederic Terrier  for the experimental part and  Laurence Laroquet  for the analytical part. This work was supported by the  ARRAINA European project  (No. FP7-KBBE 288925 ) and the  French MetaboHUB project  (No. ANR-11-INBS-0010 ). G. C. and F. M. have designed and managed the fish nutrition part; B. M. H. and B. F. have contributed to biofluid and tissue sampling; B. M. H. has contributed to tissue extraction; B. M. H. , C. D. and M. M. have managed the metabolomic part (NMR acquisition, spectral analysis, quantification and annotation) under the supervision of A.
quote all the original publications. We thank actual and past members of our team for their essential contributions to the discoveries we have made on the HEV topic in the past 25 years. We are also grateful to all our collaborators in the clinics. Work in the  Girard laboratory  is supported by the  Fondation ARC pour la Recherche sur le Cancer  ( SL220110603471 ,  PGA 120150202411 ,  PGA1 RF20180206911 ),  Institut National du Cancer  ( INCa_2013-098 ,  INCa_2017-155 ),  Agence Nationale de la Recherche  ( ANR-12-BSV1-0006-01 ),  IDEX UNITI  ( ATS 2014 ),  Laboratoire d'Excellence Toulouse Cancer (LABEX TOUCAN)  and the  Fondation pour la Recherche Médicale  ( FRM ECO201806006827 ,  FRM ECO202006011469 ). article is licensed under a Creative Commons Attribution 4.
Human Leptospirosis Cases Data on leptospirosis cases were obtained for each of the 133 sub-districts and the 1982 villages, for the years 2004-2014 from Public Health Department of Mahasarakham province, Thailand (Figure  2B ). This research includes all cases of leptospirosis obtained from the Department of Public Health of Mahasarakham Province. The cases of leptospirosis have been clinically diagnosed in hospitals by trained clinicians: patients used to work in paddy, damp and swampy places, presented signs of headaches, high fever and muscle pain. Only patients with severe symptoms have been laboratory confirmed for leptospirosis. Leptospirosis cases are then symptomatic cases obtained through passive surveillance and may not reflect the true incidence due to underreporting of asymptomatic cases.
Data Integration Data were obtained at different levels: leptospirosis cases at village level, livestock number at sub-district level, population size at sub-district level for the year 2014, the average slope at the sub-district level, flood cover percentage of the sub-district (see Section 2. 3. 3), rainfall (see Section 2. 3. 2) at provincial level. We analyzed the data at the sub-district level. For that, we aggregated the leptospirosis cases at the sub-district level by summing cases of all villages of the sub-district and we considered similar rainfall values for each sub-district.
Spatial Autocorrelation of Leptospirosis Cases Correlogram analysis was used to identify spatial autocorrelation. Moran's I test was performed to test the significance of the correlations with spatialEco implemented in R  [33]. We also studied the autocorrelation by using sub-district as units and using the lag in terms of neighboring with the R spData package  [34]. We performed the analysis for the period 2004-2014 and also for the three years showing the highest number of cases.
Association between Leptospirosis Cases and Investigated Factors Using General Additive Modeling General Additive Modeling (GAM) is an extension of the generalized linear models with the adaptability for non-normally distributed variables. The model assumes that the response variable, here leptospirosis cases per sub-district and per month, is dependent on the univariate smooth-terms of independent variables  [46] : population size, number of cattle, number of pigs, number of buffaloes, rainfall, average slope and percentage of flooded area per sub-district. Investigating the number of cases allowed to investigate the smooth effect of population size, e. g. , the transition from rural to urban population. All models were fitted using the MGCV package implemented in R  [47]. We used the function gam.
Supplementary Materials: The following are available online at https://www. mdpi. com/article/10. 3390/tropicalmed6030115/s1. Funding: This research was funded by the French ANR (project FutureHealthSEA "Predictive scenarios of health in Southeast Asia"), grant number ANR-17-CE35-0003-01, S. M. is supported by the Thailand International Cooperation Agency (TICA) "Animal Innovative Health", and The APC was funded by the journal.
Tumor infiltration of ERBB2-CAR T cells activated under Treg-polarizing conditions is enhanced by short-term aKG-induced OXPHOS augmentation The data presented above suggested that aKG might alter the phenotype and persistence of antitumor T cells in an in vivo setting. This is particularly critical since it has been shown that the intratumoral presence of Tregs negatively impacts the potential of effector T cells to eradicate tumor  (Darrasse-Jeze et al. , 2009)  and the ''hostile'' environment of the tumor consumes high levels of nutrients  (Yong et al. , 2017b). Furthermore, aKG increased the ATP production rate from mitochondrial (C) IFNg, IL-17A, TNF, and GM-CSF levels were evaluated at day 3 of Treg polarization (n = 5). (D) DNA methylation in a CpG context (5mCpG) was evaluated by nanopore sequencing in the indicated conditions and the percentage of methylation is presented as boxplots with the number of reads in the 6 samples ranging from 1,260,564 to 6,145,824 reads (triplicates, 2 independent experiments).
Conversely, methylation in several DMR including Tbx21, Ifng, and Rorc was decreased. These epigentic changes can also be due to alterations in the aKG/succinate ratio, found to regulate cell fate through histone and DNA demethylation  (Carey et al. , 2015; Liu et al. , 2017; Mills et al. , 2016; TeSlaa et al. , 2016; Tischler et al. , 2019). Indeed, our data reveal a critical role for malonate, inhibiting succinate oxidation, in restoring Treg differentiation. Furthermore, 3-NP, inhibiting mitochondrial complex II activity, rescued Treg differentiation and downregulated expression of (C) IFNg, IL-17A, TNF, and GM-CSF secretion was quantified in the indicated conditions (day 3, n = 4). (D) Lipid droplet quantification was evaluated by Nile Red staining and representative histograms and quantifications are presented at day 4 (levels in control Treg conditions were arbitrarily set at ''1'').
A minimum of 300 events was recorded for each bead. Data analysis was performed using FCAPArray Software. Cell sorting was performed on a FACSARIA high-speed cell sorter and analyses were performed on FACS-Canto II or LSRII-Fortessa cytometers (BD Biosciences). A minimum of 10,000 events were recorded for each staining. Data analyses were performed using FlowJo software (Tree Star, Ashland, OR). Nanopore sequencing for evaluation of DNA methylation T cells (from male mice) were polarized in the indicated conditions and DNA (3 mg) from each sample (2 biological replicates) was enriched in immune identity genes using cas9 guided RNPs (Key Resources Table, Table  S7 ), as previously published  (Gilpatrick et al. , 2020)  and characterized  (Goldsmith et al. , 2021a; Goldsmith et al. , 2021b).
TracrRNA and crRNA were purchased from Integrated DNA Technologies (IDT). Samples were barcoded and multiplexed using the Nanopore Ligation Sequencing kit (SQK-LSK109) and Native barcode expansion kit according to manufacturer's instructions (Oxford Nanopore Technology, Oxford UK) without PCR amplification. Sequencing of native DNA was conducted on a MinION sequencer on ONT flow cells with protein pore R9. 4 1D chemistry for 48h. Fast5 files were basecalled with Megalodon (using the Rerio ONT model ''res_dna_r941_min_modba-ses_5mC_5hmC_v001. cfg'') and aligned with minimap2 to the mm10 mouse genome. The methylation status of each CpG site was determined by Megalodon after demultiplexing with Deepbinner (v. 0. 2. 0)  (Liu et al. , 2021; Wick et al. , 2018). Data processing and statistical analyses were performed using R/Bioconductor (R version 4.
After amplification, melting curve analysis was performed with denaturation at 95 C for 5 s and continuous fluorescence measurements from 65 C to 97 C at 0. 11 C/s. Each sample was amplified in triplicate. Data were analyzed by LightCyclerâ 480 Software (Version 1. 5) and Microsoft Excel. Relative expression was calculated by normalization to HPRT as indicated (delta-Ct). Real-time PCR CT values were analyzed using the 2(-Delta Delta C(T)) method to calculate fold expression (ddCt).
Evaluation of mitochondrial complexes Cells (1e6) were lysed in a RIPA or NP-40 lysis buffer. After a 20-min incubation on ice, extracts were centrifuged, and supernatants were harvested. Extracts were resolved on SDS-polyacrylamide pre-cast electrophoresis gels (8. 5 to 12%) and transferred electrophoretically onto polyvinylidene difluoride (PVDF) membranes. PVDF membranes were incubated with the OXPHOS rodent monoclonal antibody cocktail (1/250, Thermo Fisher) diluted in PBST-1% milk in for 45 min-1 hour at RT and with horseradish peroxidase-conjugated anti-mouse secondary Ab (1/5000). Immunoreactive proteins were visualized using enhanced chemiluminescence (ECL, Amersham) according to the manufacturer's instructions. Loading control levels were assessed following amido black staining and proteins were quantified with ImageJ software and normalized to actin levels.
Lipid analyses Mass spectrometry-based lipid analysis was performed at Lipotype GmbH (Dresden, Germany) as previously described  (Sampaio et al. , 2011)  and triplicate samples (1x10 6 ) were evaluated. Briefly, lipids were extracted using a two-step chloroform/methanol procedure  (Ejsing et al. , 2009). Samples were analyzed by direct infusion on a QExactive mass spectrometer (Thermo Scientific) equipped with a TriVersa NanoMate ion source (Advion Biosciences) as described  (Mitroulis et al. , 2018). Data were analyzed as previously described, using an in-house lipid identification software based on LipidXplorer  (Levental et al. , 2020; Wang and Han, 2016). Analyses were only performed on samples with a signal-to-noise ratio > 5 and a 5-fold higher signal intensity than in corresponding blank samples.
Lipidomic analysis yielded a list of > 600 individual lipid species. Quantities were determined by first transforming all detected lipids into mol% as a function of total lipids. Molar percentages of membrane lipids were determined after removing TAG and CE from the analysis. Storage lipids were analyzed as a function of TAGs and CE. Class composition was further evaluated in the datasets as well as the number of carbons and level of unsaturation in individual species. Spectral imaging and generalized polarization Spectral imaging was performed as previously described  (Levental and Levental, 2015; Levental et al. , 2016; Levental et al. , 2017; Sezgin et al. , 2012; Sezgin et al. , 2015b). Following staining of cells with 1 mg/ml Di-4-AN(F)EPPTEA for 5 min at room temperature, cells were evaluated by confocal based spectral imaging  (Sezgin et al.
Cell extracts and media were centrifuged at 16,000 g for 10min at 4 C and supernatants were analyzed by HPLC-MS. Samples were separated on a Thermo Scientific Accela liquid chromatography system coupled with a guard column (Hichrom) and a ZIC-pHILIC column (Merck). Separations were performed using a gradient elution in a solution of 20mM ammonium carbonate, with 0. 1% ammonium hydroxide and acetonitrile. Metabolites were detected using a Thermo Scientific Exactive Orbitrap mass spectrometer with electrospray ionization, operating in a polarity switching mode. Raw data were analyzed with Xcalibur 2. 2 and LCquan 2. 7 Thermo scientific software. Tracing of metabolites into fatty acids T cells polarized in the indicated conditions were incubated in RPMI medium without glucose or glutamine and supplemented with uniformly labeled [U- 13 C 6 ]glucose, [U- 13 C 5 -15 N 2 ]glutamine, or [U- 13 C 5 ]dimethyl alpha ketoglutarate (generated by RTI international and confirmed by GC-MS) for 24h.