dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements. The authors would like to thank the participants who volunteered to take part in the study; the investigators ( Ildikó Batta ,  Budapest, Hungary; Éva Horzsa, Budapest, Hungary; Éva Kovács, Szeged, Hungary; István Tokodi, Székesfehérvár, Hungary; Alfonso Carmona Martinez, Sevilla, Spain; Iolanda Jordan Garcia, Barcelona, Spain; Maria Luisa Navarro Gómez, Madrid, Spain; Tiina Karppa, Helsinki, Finland; Anitta Ahonen, Järvenpää, Finland; Satu Kokko, Oulu, Finland; Miia Virta, Tampere, Finland; Marita Paassilta, Espoo, Finland; Ilkka Seppä, Turku, Finland ;  Matthias Donner ,  Mönchengladbach, Germany; Rolf Ebert, Tauberbischofheim, Germany; Eivy Franke-Beckmann, Erfurt, Germany; Michael Horn, Schönau, Germany; Roland Knecht, Bretten, Germany; Ralph Köllges, Mönchengladbach, Germany; Thorsten Krause, Goch, Germany; Renate Mangelsdorf-Taxis, Bönnigheim, Germany; Andreas Schmutte, Datteln; Thomas Beck, Bochum, Germany; Friedrich Kaiser, Hamburg, Germany ) and their site staff, staff at the  Vaccine Evaluation Unit, Public Health England , the  NETSTAP-Study Group in Germany  (http://www.
Viral vectors The coding sequence of P1A (NCBI RefSeq NP_035765. 1), MAGE-A3 (NCBI RefSeq NM_005362. 3) and NY-ESO-1 (GenBank: U87459. 1) were purchased as strings DNA fragments from GeneArt (Thermo Fisher Scientific, Paisley, UK). Further details on vector construction are described in the online supplemental materials.
Cells were then surface stained, fixed and permeabilized (BD Cytofix/Cytoperm), then stained intracellularly for cytokine production with anti-IFN-γ-APC (clone XMG1. 2), anti-IL-2-PE (clone JES6-5H4), and anti-TNFα-BV650 (clone MP6-XT22), and then acquired on a Fortessa flow cytometer (BD Biosciences). All mAbs were purchased from BioLegend. Data were analyzed with FlowJo software v10 (Tree Star, Ashland, Oregon). Analysis of multifunctional CD8 + T-cell responses was performed via a Boolean analysis of IFN-γ + , TNF-α + , IL-2 + events in the CD8 + gate using FlowJo. Pestle (NIH, Bethesda) and SPICE (Vaccine Research Centre, NIH, Bethesda) software were used to generate graphical representations of proportions of T cells expressing 1, 2 or all 3 cytokines.
Acknowledgements We thank  V. Clark  and  H. Gray  for animal husbandry, and  F. Howe ,  M. Muers  and  Xiao Qin  for critical manuscript reading. Contributors IR, AVSH, CSKL and BJVdE conceived the experiments. JM, CSKL and BJVdE designed the experiments. IR and CSKL designed the viral vectors. CSKL and EP generated all viral vector constructs and IR supervised the viral vectors construction. JM, LN, RAR-V, VP-A, YZ, FC and CSKL performed the experiments. JM, HFC, RAR-V and CSKL analyzed the data. JM, CSKL and BJVdE wrote the manuscript.
Funding This work was supported by  Ludwig Cancer Research and CRUK Oxford Center Development Fund  ( CRUKDF 0216-BVDE ) to BJVdE. and IR. VP-A was registered in the  EMJMD LIVE (Erasmus+ Mundus Joint Master Degree Leading International Vaccinology Education ), cofunded by the  EACEA (Education, Audiovisual and Culture Executive Agency , award  2015-2323 ) of the European commission, and received a scholarship from the  EACEA. CSKL was supported by a fellowship from  Swiss National Science Foundation  ( P300P3_155374 ).
Increasing COVID-19 Testing Capacity in Ifanadiana District One of the most fundamental steps to respond to COVID-19 is reliable testing data for patient diagnostics, planning, and research. The testing landscape is exceedingly complex and evolving in real time due to changes in technologies, their validation, clinical capacity and local and global supply chains. According to government policy, suspected cases are confirmed by a gold standard nucleic acid amplification test (NAAT)-RT-PCR or GeneXpert-to be included in the national COVID-19 statistics. Since the start of the pandemic, Madagascar has completed over 200,000 tests. There are four laboratories performing confirmation tests by RT-PCR, all of which are located in the capital city of Antananarivo. Rapid technological advances led to several COVID-19 testing options, including the Xpert R Xpress SARS-CoV-2 cartridge, which relies on existing GeneXpert machines.
The first three waves of the cohort study (2014-2018) included biometric measurements of all household members. In 2021, dried blood spot (DBS) tests were added to support a range of serological tests, including for SARS-COV-2 antibodies to be analyzed in partnership with the Pasteur Institute of Madagascar. Point estimates of seroprevalence a year after introduction of the virus will provide a strong indication of the attack rate of COVID-19 in rural Madagascar. When combined with spatiotemporal data from patient diagnostics and mathematical modeling, this can be directly used for estimating effects of disease control strategies (i. e. , vaccines) over time.
To identify nucleotide polymorphisms, the mitochondrial markers were sequenced and the data were compared, including with published sequences from other regions. EmsB fragment length profiles were determined and confirmed by Kohonen network analysis and grouping of Sammon's nonlinear mapping with k-means clustering. The spatial distribution of genotypes was analyzed by SaTScan for the EmsB profiles found in Brandenburg. Results: With both the mitochondrial makers and the EmsB microsatellite fragment length profile analyses, mixed infections with different E. multilocularis genotypes were detected in foxes from Brandenburg and North Rhine-Westphalia. Genotyping using the mitochondrial markers showed that the examined parasite specimens belong to the European haplotype of E. multilocularis, but a detailed spatial analysis was not possible due to the limited heterogeneity of these markers in the parasite population.
The samples were then purified using SigmaSpin Post-Reaction Clean-Up Columns (Sigma-Aldrich Biochemie GmbH, Hamburg, Germany) according to the manufacturer's instructions. Ten microliters of Hi-Di ™ formamide was added to approximately 10 µl purified reaction product and analyzed in an ABI 3130 Genetic Analyzer (Applied Biosystems, Thermo Fisher Scientific, Braunschweig, Germany). Sequences were handled and analyzed using Geneious ® version 8. 3. 1 software (http:// www. genei ous. com, Biomatters, Auckland, New Zealand) and compared with those of other helminths deposited in the NCBI database (http:// www. ncbi. nlm. nih. gov/ nucle otide/) using BLAST ® (http:// blast. ncbi. nlm. nih. gov/ Blast. cgi).
EmsB analyses EmsB analyses were performed essentially as previously described  [16, 17]. In brief, PCR was conducted as described above with the primers EmsB A for and EmsB C rev, which was labeled with 6-carboxyfluorescein (6-FAM; Table  1 ). Amplicons were shipped to SMB Services in Molecular Biology GmbH, Berlin, Germany, for microsatellite length determination by capillary electrophoresis using the ABI Prism 3100 Genetic Analyzer (Life Technologies, Foster City, CA, USA). EmsB microsatellite profiles were visually determined by comparison with standards using GeneScan 500 ROX (Thermo Fisher Scientific, Waltham, MA, USA). Data were analyzed using GeneMapper ® Software 5 (Life Technologies GmbH, Darmstadt, Germany).
Statistical analyses and graphical visualization Statistical analyses were carried out using Excel (Microsoft Corporation, Redmond, WA, USA), R software version 3. 5. 3 (R Foundation for Statistical Computing, Vienna, Austria, https:// www. R-proje ct. org), and SaTScan v9. 3. 1 using the Bernoulli model with 999 Monte Carlo replications and allowing a maximum spatial cluster size of 50% of population at risk (Software for the spatial and space-time scan statistics, http:// www. satsc an. org/  [41] ). Fisher's exact test was performed in R with the function "fisher. test" implemented in the R package "stats. " P-values < 0. 05 were regarded as statistically significant. Bonferroni corrections  [42]  were performed in multiple testing settings. For the grouping of the visually determined EmsB microsatellite profiles, the supervised Kohonen network (KN), also called Kohonen maps (self-organizing Kohonen network/self-organizing Kohonen maps [SOM];  [43] [44] [45] ), was used.
For this purpose, the standardized numerical EmsB profiles as described elsewhere  [20, 27, 46]  were used as input data (x-map). The expected number of groups was set in the program (output data; y-map). The classification was then performed using the "xyf " function of the R package "kohonen. " The topology of the grid was hexagonal, and 10,000 iterations were performed. To validate the EmsB profile groups obtained by supervised KN, we also performed an unsupervised KN. The grid size for the map space was set to four samples per node, resulting in a grid size of 12 × 12  [44, 45]. The groups/clusters obtained in the unsupervised KN analysis were classified by a combination of the average silhouette method  [47] , r-function "fviz_nbclust" from the R package "factoextra, " and 30 indices for determining the best clustering scheme from the different results obtained by varying all possible combinations of the numbers of clusters, distance measures, and clustering methods (r-function "NbClust" from the R package "NbClust")  [48, 49].
Both methods proposed a cluster size of four groups as the optimum. As a second method for checking the EmsB profiles, Sammon's nonlinear mapping with k-means clustering was used  [50]. For this purpose, the standardized numerical EmsB profiles determined in this work were used as the data basis and the distances between them were calculated. This calculation was performed with the function "dist" of the R package "stats. " Based on the distances, data were analyzed using the R function "sammon" of the R package "MASS. " The k-means cluster analysis was performed using "kmeans" of the R package "stats"  [51]. The analysis was performed under the assumption that there were three clusters. To validate the visual assignment of EmsB profiles and to make the results comparable to previously published data  [52] , hierarchical clustering analysis (Euclidian distance, average link clustering method) was carried out using in the R package "pvclust.
" To improve the reading of the dendrogram, it was modified using the "hang. dendrogram" command from the R package "dendexted" setting the parameter "hang = 0. 1. " This parameter changes the fraction of the plot height, in which labels hang below the rest of the plot. A negative value causes the labels to hang down from 0. Approximate unbiased P-values (italic numbers on nodes, in percent) were calculated with a multiscale bootstrap (B = 1000). The ArcGIS 10. 0 program (Esri, Redlands, CA, USA) was used to visualize geographical data.
The ATP6 sequences of all five worm specimens recovered from fox Fu/2009/1860 exhibited a SNP at position 6375 (C to T). Three of the four SNPs resulted in amino acid changes (alanine to valine, serine to proline, and histidine to tyrosine). To increase the robustness of previous phylogenetic analyses, the sequence data were concatenated and reanalyzed for a total of 3189 aligned bp. All concatenated sequences determined in this study could be assigned to the species E. multilocularis (Additional file 1: Figure  S8 ). Also with the concatenated dataset, our samples form a separate clade within the monophylum E. multilocularis. Here, the E. multilocularis clade is a sister group of E. shiquicus. Both E. oligarthra and E. vogeli form independent branches in this analysis. Within the E. granulosus s.
Validation of the visual determination of EmsB profiles To evaluate the reliability of the visual determination of EmsB profiles and to determine their distinctiveness, supervised self-organizing KN analysis was performed and the results displayed in SOM. The standardized numerical EmsB profiles found in this study were used as the data basis. Due to a change in the standard for capillary gel electrophoresis, 38 samples had to be removed from the data set, so that 427 samples remained for KN analysis. Profiles D and E were combined into one group, because only one of the 490 samples for which an EmsB profile could be determined was assigned to profile E. After the number of expected groups (equivalent to the number of expected EmsB profiles) had been set, classification by the KN was carried out using the "xyf " function in R package "kohonen.
5 ). These groups were spatially separated from each other. The samples which could not be visually assigned to any profile scattered around the cloud representing samples with profile G. Hierarchical clustering analysis also classified the EmsB genotyping data of the E. multilocularis isolates into four groups when we applied a threshold of 0. 08 for the genetic distance  [18]  (Fig. 6 ). The profiles D, G, and H were clustered in three separate clusters, with the fourth cluster consisting mainly of samples representing patterns that could not be assigned to any known EmsB profile and single isolates representing EmsB profiles D or G. These results confirm in multiple ways the validity of the visual determination of profiles. It seems likely that samples that could not be attributed to any established profile belong to at least one separate profile.
[16] , who applied five main profiles (D-H) for European E. multilocularis isolates. An EmsB profile does not necessarily represent a single genotype. One profile (e. g. D, G, or H) can consist of different genotypes, as described in the original papers  [16, 17]  and also clearly evident from Fig. 6. The height of each peak in each profile can vary slightly due to different numbers of repeats in the genome, leading to the respective peak in the microsatellite analysis  [14]. Since visual inspection of EmsB profiles is not entirely based on measurable quantitative effects, but has an inherent arbitrary element, we validated the visual determination of the profiles by a KN analysis  [43]  and Sammon's nonlinear mapping with k-means clustering  [50, 51]. In the Kohonen self-organizing network analysis, a self-organizing network is based on a data set, on which the network is trained to recognize patterns  [43] [44] [45] 59].
The individual data are then assigned to the respective groups. In our study, we trained the system with the numerical data of the determined profiles from Germany and reference samples from Switzerland. The aim of this study was to investigate the genetic diversity of E. multilocularis in the federal state of Brandenburg in foxes as definitive hosts, where we found a total of three known and one unknown EmsB profile. Previously published EmsB data from Germany  [20] , where genotyped isolates originated from human cases of alveolar echinococcosis, showed a significantly higher diversity (11 EmsB profiles) compared to the results of this study. Because of the different study setups, the previously published data were not included in the analysis in this study. The result of the analysis confirmed the existence of four groups of isolates in the study area, three of which could be attributed to existing EmsB profiles, whereas one comprised isolates that could not be visually assigned to any known EmsB profile.
multilocularis. It seems essential to collect, genotype, and compare more E. multilocularis specimens from different regions to further validate the discriminative power of EmsB and other markers and to perform more detailed spatial and temporal analyses regarding the distribution or spread of the parasite. We therefore fully support the EmsB Website for the Echinococcus Typing  [46]  and will be pleased to submit our genotyping data once an automatic upload function is implemented. Further markers should be identified, for example by next-generation sequencing (NGS) approaches, to improve the genotyping of E. multilocularis. This strategy is promising and may provide high discriminative power in E. multilocularis populations and allow precise identification of polymorphic and conserved regions.
3 mM) at longer, 24 hr, treatment times (Figure  S5 ). Decreases in phospho-FOXO1 are associated with FOXO1 translocation to the nucleus  (Van Der Heide et al. , 2004). Treatment with Mito-MGN or LY294002, used as a positive control, increased levels of FOXO1 within the nucleus in comparison with vehicle-treated cells (Figures  3H  and 3I ). The morphometric analysis pipeline is shown in Figure  S6. Moreover, the downstream of FOXO1 cell cycle regulator p27 was upregulated upon the treatment with Mito-MGN (Figure  3J ). Consistent with those results, Mito-MGN significantly increased the percent of B16. F10 cells within the G1 phase of the cell cycle (Figure  3K ). Taken together these data indicate that Mito-MGN effectively inhibits melanoma progression. The decrease in melanoma proliferation reflected the dose-dependent inhibition of mitochondrial complex I and decreased OXPHOS metabolism in Mito-MGN treated melanoma cells.
To rigorously dissect the increase in T cell activation, an unbiased screen of the functional effects of Mito-MGN on secreted cytokines was completed. Naive T cells were activated (Figure  5A ) and loaded to Iso-Code chips to determine single cell cytokine secretion. The polyfunctional profile (secreting >2 cytokines) of single cells was evaluated, and a polyfunctional strength index score generated, with further segregation into effector, stimulatory, chemoattraction, regulatory, and inflammatory categories. T cells treated with Mito-MGN exhibited a more effector and inflammatory phenotype, characterized by increased levels of IL-17A and IL-6 (Figures5F and 5G). Raw data from the IsoPlexis polyfunctional assay are listed in Table  S1. Finally, to ascertain if the measured changes in vitro correlated with functional changes in vivo we investigated the potential for T cell activation to participate in the anti-tumor effect of Mito-MGN.
Here, we have shown that Mito-CI, either the mitochondria-targeted polyphenol Mito-MGN or Mito-CP, each potently inhibits murine melanoma proliferation. Further, Mito-MGN more effectively inhibited melanoma growth than either the parent bioactive polyphenol magnolol or IACS-010759. Mito-MGN treatment decreased complex I-mediated cellular energy and increased the presence of damaged mitochondria in melanoma cell lines, likely rendering those cells unable to meet metabolic challenges following treatment with Mito-MGN. These mitochondria-targeted agents, while preferentially localizing within tumor cells, retain potent immune activating properties in T cells while abrogating suppressive effects of MDSC. Our data support the potential for exploiting metabolic reprogramming in multiple cell types to broadly inhibit tumor progression through the combination of tumor intrinsic and tumor extrinsic OXPHOS inhibition.
While the nearly 10-fold higher accumulation of Mito-MGN in melanoma cells was expected, detectable levels of the compound were measured within lymphocytes and MDSCs. Given the ratio of the compound within those cells relative to melanoma, we believe the off-tumor accumulation likely reflects the inherent lipophilic nature of the TPP + moiety. While levels within those immune cells were low, it resulted in discrete functional effects in T cells and MDSC. These off-tumor effects harmonize with on-tumor effects as immune depleting antibodies decreased the anti-melanoma effects of Mito-MGN. Taken together, our data suggest Mito-MGNs anti-tumor effects reflect a combination of on-tumor cell cycle inhibition with off-tumor T cell activation and depletion of suppressive myeloid cells. Cancers with mutations in the genes encoding mitochondrial complex I proteins in the electron transport chain are more susceptible to mitochondrial inhibition  (Gao et al.
While our studies did not complete a detailed analysis of these subset's we not a prior report indicating that SLEC preferentially utilize aerobic glycolysis while MPEC rely on OXPHOS for their energy needs  (Weyand and Goronzy, 2018). Thus, we would predict that Mito-MGN would enhance SLEC to MPEC ratio's in melanoma-bearing mice. Taken together, our data suggest that OXPHOS may be a key metabolic participant in immune suppression in cancer and may be exploited using mitochondria-targeted complex I inhibitors to selectively inhibit cells reliant on mitochondrial respiration. Moreover, mitochondria-targeted complex I inhibitors unravel an exciting potential in remodeling the immune microenvironment to promote anti-tumor immunity and potentially be used to enhance the response to front-line immunotherapies.
Limitations of study Our in vivo and in vitro data indicate that Mito-MGN has effects on both melanoma cells and T cells. While we demonstrated a role for inhibiting mitochondrial respiration and the cell cycle in melanoma cells, experimental data defining the mechanisms whereby this mitochondria-targeted OXPHOS inhibitor alters T cell activation MDSC viability and suppressive capacity have yet to be established. Examination of the potential for Mito-MGN to work cooperatively with immune checkpoint blockade require additional optimization experiments to rigorously establish effects of Mito-MGN on melanoma PD-L1 or other checkpoint protein levels. Dissecting the sequence of combined treatment would also be required. The studies here focus on CD8 + cytolytic T cells as a key anti-tumor effect.
Cell culture and proliferation measurements Male murine melanoma B16. F0 (ATCC-CRL-6322, RRID:CVCL_0604) and B16. F10 (ATCC-CRL-6475, RRID:CVCL_0159) cell lines were maintained in DMEM containing 10% v/v fetal bovine serum (Omega Scientific, Inc. Tarzana, CA), penicillin (100 U/ml), and streptomycin (100 mg/ml). Cell proliferation was monitored using the IncuCyte-S3 Live-Cell Imaging system (Essen Bioscience Inc. , Ann Arbor, MI) as a reproducible probe-free, noninvasive, measure of cellular confluence in real-time. Phase-contrast images were collected every 2 hr to measure changes in cellular confluency as a surrogate measurement of cellular proliferation. Additional OXPHOS inhibitors used were IACS-010759 (Cayman Chemicals Co. , Ann Arbor, MI)  (Molina et al. , 2018)  or Mito-CP synthesized in house at the Medical College of Wisconsin as described previously  (Boyle et al.
Following staining, cells were fixed with PBS in 1% w/v paraformaldehyde, or permeabilized for intracellular staining using Foxp3 Transcription Factor Staining Buffer (BD Biosciences Inc. San Jose, CA). A full list of antibodies and reagents for cellular labeling are detailed in Key Resources Table. Samples were acquired on BD LSRII or Fortessa X-20 flow cytometers and data analyzed using FlowJo software (FlowJo, LLC, Ashland, OR) (10. 6. 1; RRID:SCR_008520).
TMRE quantification Tetramethylrhodamine ethyl ester perchlorate (TMRE) was used to quantify mitochondrial integrity as described previously  (Boyle et al. , 2018). Briefly, cells were treated with Mito-MGN, MGN, TPP or FCCP for 1 hr. Cells were then incubated 45 min in TMRE (200 nM) and mechanically lifted from culture dishes for analysis using a BD-LSR II flow cytometer and FlowJo 10. 6. 1 software (BD Biosciences).
Cell cycle analysis B16. F10 cells (5x10 5 ) were seeded to a 6-well plate and immediately treated with Mito-MGN in complete medium. At 24 hr after treatment, cells were fixed with 70% v/v ethanol, and stained using a propidium iodide/RNase solution. Data were collected using a BD-LSR II Flow Cytometer and analyzed using FlowJo 10. 6. 1.
Object analysis Nikon Elements. nd2 files were processed into single channel maximum intensity projections (first 7 slices) TIFF files using an ImageJ macro  (Schindelin et al. , 2012)  (https://github. com/Hill-Lab/Mito-MGN-Scripts). These single channel images were then input into a CellProfiler pipeline  (McQuin et al. , 2018)  (https:// github. com/Hill-Lab/Mito-MGN-Scripts) to analyze the mean intensity of FOXO1 in the nucleus vs the cytosol. Images were first cropped and corrected for illumination variations. Primary objects were classified as nuclei using adaptive Otsu thresholding on the DAPI channel. Secondary objects were classified as cells using the FOX-O channel and the nuclei as input objects. Cells were identified using the Watershed -Image feature and the global Minimum Cross-Entropy thresholding method.