dataesr/scientific-paragraphs-categorization huggingface dataset:
Near-infrared Spectroscopy measurements Cerebral oxygenation in the left prefrontal (PFC) and motor (MC) cortex was assessed by monitoring changes in oxy-and deoxy-hemoglobin (O 2 Hb and HHb, respectively) obtained with spatially resolved, continuous wave nearinfrared spectroscopy (NIRS) (Oxymon MkIII, Artinis, Zetten, Netherlands). Theoretical and performance details of NIRS have been previously described  (Perrey, 2008). PFC NIRS probes were centered between Fp1 and F3 locations according to the international 10-20 EEG system, with 3. 5cm interoptode distance. MC NIRS data were expressed as the average of a 4-channel square setting (3-cm interoptode distance) fixed with headbands between Cz and C3 locations. Muscle oxygenation was assessed from the right vastus lateralis (at mid thigh) using a 4-cm interoptode distance.
Real-time quantitative PCR was performed using the fluorescent SYBR Green dye (Thermo Fisher Scientific, Illkirch-Graffenstaden, France) and the CFX384 TouchTM Real-time PCR Detection System (Bio-Rad, Marnes la Coquette, France). The primer sequences used for qPCR are detailed in Table  S4. Two independent liver fragments were processed and analyzed for each animal, and each measurement was performed in duplicate. The specificity of each gene amplification was verified at the end of quantitative PCR reactions, through analysis of the dissociation curves of the PCR products. Amplification curves were analyzed with CFX Manager Software (Bio-Rad, Marnes la Coquette, France), using the comparative cycle threshold method. Relative quantification of the steady-state target mRNA levels was calculated after normalization of the total amount of cDNA tested to the 18S rRNA endogenous reference, using the 2 (-∆∆Ct)  method.
Imaging Data Analysis Images were analyzed with PMOD software (version 3. 9, PMOD Technologies LLC, Zurich, Switzerland), as described in a previous rat study  [29]. Regions of interest (ROI) were drawn on planar images over the liver and intestine (assumed to represent excreted bile). Standardized ROIs consisted in the largest part possible of each organ, excluding the overlapping region. The whole-heart was delineated to derive an image-derived blood input function, as previously described  [29]. Corresponding TACs were generated by plotting the mean radioactivity counts (counts per second (cps)) in each region of interest normalized to the injected radioactivity amount in each animal (cps/MBq) versus time. A previously developed four-compartment pharmacokinetic model, which had already been applied to describe the transporter-mediated hepatobiliary disposition of 99m Tc-mebrofenin in rats  [29, 39] , was used to estimate the rate constants that describe the transfer of the radiotracer between the blood and hepatocytes (k 1 and k 2 , min -1 ), from hepatocytes to the intrahepatic bile ducts (k 3 , min -1 ), and from the intrahepatic bile ducts to bile excreted into the intestine (k 5 , min -1 ).
Louise Breuil and Nicolas Tournier received funding from the French National Research Agency (grant number ANR-19-CE17-0027). This work was performed on a platform member of the France Life Imaging network (grant number ANR-11-INBS-0006). Institutional Review Board Statement: All of the animal experiments were in accordance with the recommendations of the European Community for animal experiments (2010/63/UE) and the French National Committees (law 2013-118) for the care and use of laboratory animals. The experimental protocol was approved by a local ethics committee for animal use (CETEA) and by the French ministry of agriculture (APAFIS#5375-20l60513 17426342, and 13 December 2018). Informed Consent Statement: Not applicable.
Funding: Louise Breuil and Nicolas Tournier received funding from the French National Research Agency (grant number ANR-19-CE17-0027). This work was performed on a platform member of the France Life Imaging network (grant number ANR-11-INBS-0006). Institutional Review Board Statement: All of the animal experiments were in accordance with the recommendations of the European Community for animal experiments (2010/63/UE) and the French National Committees (law 2013-118) for the care and use of laboratory animals. The experimental protocol was approved by a local ethics committee for animal use (CETEA) and by the French ministry of agriculture (APAFIS#5375-20l60513 17426342, and 13 December 2018). Informed Consent Statement: Not applicable.
, 2020) , which aims to support the use of omics research among the ESA space biology community. Despite vast interest in, and the immense quantity of biological information gained from space omics research, the knowledge of ESA-related space omics works as a collective and remains poorly defined as current records (i. e. , ESA Erasmus Experiment Archive) cannot be easily leveraged due to the limited search capabilities. However, a better understanding of such contributions is necessary to unify and promote the development of space omics among ESA and ESA state members. This is particularly relevant if European state members want to keep pace with global omics efforts, which has seen a boom in activity since the initiation of the National Aeronautic Space Administration (NASA) GeneLab data repository, which allows the sharing of spaceflight omics data and provides improved visualization and analysis tools free to the public  (Ray et al.
It is also possible that literature searching-associated caveats could have omitted such studies (see 'limitations'). Nonetheless, it was possible to identify 33 datasets on the Genelab repository that acknowledge ESA contributions and 44 datasets where the Space Omics Topical Team contributed to the generation and/or analysis. Thus, 65 datasets in total-excluding overlaps-accounting for approximately 1/5 of the whole GeneLab repository (Table  S9 ).
, 2010). The Drosophila research landscape in Europe is quite different now, due to the premature close of the leading Drosophila lab. For some time, a collaboration with the plant microgravity lab, also in Madrid, facilitated European researchers to undertake a number of ongoing omics projects in simulated microgravity  (Herranz et al. , 2012 (Herranz et al. , , 2013a)) , and USA-based researchers have been populating the GeneLab database with Drosophila datasets (e. g. (Hateley et al. , 2016; Hosamani et al. , 2016; Ogneva et al. , 2016) ). In the case of C. elegans, these nematodes offer many advantages compared to other experimental species such as the ease of handling/culturing, the microscopic size, and the opportunities for genetic manipulation  (Etheridge et al. , 2011; Higashibata et al.
, 2020). Based on the additional richness of data obtained in these studies, future studies should use cutting-edge technologies such as single-cell sequencing and imaging metabolomics to maximize the data obtained from these limited samples. Owing to the relatively limited supply of biological spaceflight tissues, these studies often combine data from human cell lines, the NASA twin study, as well as from various rodent tissues (i. e. , cartilage, liver, bone, muscle, etc) and serum/plasma. Investigations into the field of regenerative medicine have been conducted to examine the impact of the space environment on mouse stem cells  (Acharya et al. , 2018; Shinde et al. , 2016). Several studies focused on comparative analysis between human samples (e. g. , blood serum/plasma) from the astronauts on different space missions.
Additionally, data collected from research systems simulating reduced gravity (e. g. , clinostat, random positioning machine, and parabolic flights) from mice and humans have been used to compare to samples collected after spaceflight on the ISS, Bion-M1 and Bion-M3, or the Rodent Research 1 and 3 space missions. Only two European-contributed studies so far have performed proteomic analysis  (da Silveira et al. , 2020; Tascher et al. , 2017) , while only a single metabolomics study was documented examining astronauts serum and urine (da Silveira et al. , 2020). There is a notable absence of lipidomic studies and metagenomic analysis of the rodent microbiome, although some are starting to emerge  (Alauzet et al. , 2019 (Alauzet et al. , , 2020;; Tai et al. , 2020). We predict that cellular lipidomic and microbiome studies will constitute a major axis of biomedical research to understand physiological adaptations during space travel and extraterrestrial settlement.
Regarding funding, Belgium, Germany, and Spain have the highest number of works (co)funded by ESA, with 23, 13, and 7 publications, respectively (Table  S10 ). This shows that from the top five space omics-contributing countries in Europe, Belgian and German investigations are mainly supported by ESA, while Spanish studies are supported by both ESA-dependent and independent funding schemes. However, UK and French research was carried out with little ESA (co)funding. It is unclear whether this is the result of ESA policy, or whether it reflects research funded exclusively from national sources (which are not considered as ESA (co)funded), or if the project/s are funded by a completely different source. Focusing on publications which acknowledge ESA (co)funding and have been published in the last 5 years (2016-2020), Belgium and Germany still rank as the countries with the most ESA-(co)funded outputs, with 8 and 7 publications, respectively.
Sweden was third with 4 publications, followed by Italy with 3 publications, then Spain, Austria, and the Netherlands with 2 publications each, and France, Ireland, Slovenia, and Norway with 1 publication each (Figure  2  and Table  S12 ). The UK, the fourth biggest space omics producer in Europe, had no ESA (co)funding in the last 5 years, and France, at fifth place overall, acknowledged 1 ESA-(co)funded work (Tables  S10  and S12 ). These differences in acknowledgment may reflect different national funding priorities. Although this review is primarily focused on space omics research, we want to give a glimpse of the research performed in Europe across the whole biological sciences landscape. Focusing on the distribution of life science experiments per subdiscipline in the last 50 years (data extracted from the ESA ERASMUS archive, note that this information is general, non-specific to space omics (Figure  3 ), we found that the numbers vary depending on ESA priorities and platform development/availability at any time.
For example, human physiology is typically stable in relative numbers, but exobiology/radiation topics were highly relevant in the period 2006-2010. Such variations in the topics/samples that are primarily selected to be flown by ESA may have an impact on the publications produced by the European space omics researchers, in comparison with the research teams working under NASA-flown experiments. The large number of experiments flown with ESA participation in Figure  3  highlights the importance of implementing common methodological approaches across independent experiments, so that results obtained from many different biological sub-disciplines can be harmonized and compared, in turn, capitalizing upon the scarce biological material recovered from spaceflight experiments. Taken together, this data demonstrate that the European space omics research community will benefit from a coordinated funding strategy, more communication between European Union (EU), ESA, and national funding agencies, and more opportunities to interact with the broader space biology community.
It is the entity that channels the funding and support applications for national and international research and development projects of Spanish companies, but is the link between ESA (paying for the payload ticket to space) and the national research programs (paying for the researcher's lab working costs). In Spain, it is usual to acknowledge the ministry first because the money comes directly from its research grant with certain reference number. CDTI or ESA ''co-funding'' of Spanish research is invisible in most cases. When ESA is acknowledged, it is not unusual to occur without a grant reference. Despite these issues, 63. 6% of the space omics work carried out in Spain acknowledges ESA (Table  S10 ), and it is interesting to note that all the outputs came from Madrid (Table  S11 ). In Belgium, there is no dedicated national space agency, and the funding pipeline is similar as Spain.
CONCLUSIONS ESA continues to be a major contributor to the field of space omics, mainly as a partner with other space agencies such as NASA and JAXA. An ESA-funded Space Omics Topical Team has been created to argue for the necessity of ESA and ESA state members to unify databases and resources and to promote the development of space omics to fulfill the role that Europe is expected to have in the field. This will also facilitate collaborations while preserving and promoting European-funded spaceflight experiments. In our view, there is a critical mass of European space biology researchers who can significantly contribute to space-related life science; the effectiveness of this depends on the prioritization and coordination of funding by ESA and complementary European funding bodies. In regard to the inclusion of studies without direct ESA (co)funding but being associated with ESA member states in Europe, our Space Omics Topical Team will make a number of recommendations in a follow up publication including the need for consistency/regulation in acknowledging ESA funding of the spaceflight opportunities and/or support with ground-based simulation experiments and the promotion of Findable, Accessible, Interoperable, Reusable (i.
ACKNOWLEDGMENTS All listed authors are members of the  ESA Space Omics Topical Team , funded by the  ESA  grant/contract  4000131202/20/NL/PG/pt  ''Space Omics: Toward an integrated ESA/NASA -omics database for spaceflight and ground facilities experiments'' awarded to RH, which was the main funding source for this work. Individual authors also acknowledge support from: the  Medical Research Council  part of a  Skills Development Fellowship  [grant number  MR/T026014/1 ] awarded to CSD; the  Spanish   CAM TALENTO program  project  2020-5A_BIO-19724  to MAFR; the  Spanish Plan Estatal de Investigacion Cientı ´fica y Desarrollo Tecnologico  Grant  RTI2018-099309-B-I00  to FJM, the  Swedish Research Council VR  grant  2020-04864  to SG and the  French Centre National d'Etudes Spatiales  grant  DAR 2020-4800001004 ,  2021-4800001117  to ECD.
Urothelial carcinoma (UC) is a highly prevalent malignancy that remains difficult to treat in the case of muscle-invasive tumors  (11). Nonmetastatic muscle-invasive bladder cancers (MIBC) are mainly treated with cisplatin-based neoadjuvant chemotherapy followed by radical cystectomy and harbor a poor prognosis, with a 5-year survival of 60%  (12). However, a significant subset of patients are ineligible for neoadjuvant cisplatin-based chemotherapy. Since 2017, immune-checkpoint blockers (ICB), such as anti-PD-1/PD-L1 antibodies, have emerged as a successful immunotherapeutic strategy for advanced UC  (13) (14) (15) (16) (17) (18). Driven by the promising results in advanced diseases, ICB indications have been considered for the treatment of lower stage bladder tumors, including non-MIBC and nonmetastatic MIBC (NCT02844816, NCT02901548, and NCT02792192; refs.
In contrast, in rodent and human breast cancers, a functional T FH response orchestrated in TILs within active TLS has been associated with cytotoxic CTL responses that governed their prognosis  (34). Hence, by bridging the two arms of the adaptive immune system (B cells and CD8 + T cells) within TLS, T FH indirectly contribute to exert an immune pressure against tumor progression in human and rodent ovarian cancers  (35, 36). When investigating the PANDORE single-arm, phase II trial (NCT03212651), which enrolled patients with MIBC treated with neoadjuvant pembrolizumab, we obtained evidence that T FH stand among the main therapeutic targets of neoadjuvant pembrolizumab, both in blood and in the bladder. Baseline blood memory T FH together with B cells became activated by pembrolizumab, facilitating the orchestration of tertiary lymphoid-like (TLS-like) structures and CD8 + TIL accumulation, translating into clinical benefit.
Clinical Efficacy of Pembrolizumab in the PANDORE Study Between October 2017 and May 2019, we enrolled 44 cisplat inineligible patients with localized MIBC in the PANDORE trial (NCT03212651), but only 39 patients were included in the final analysis (Supplementary Fig. S1A  and S1B ). Among these patients, 25 (64%) met cisplatin ineligibility and 14 (36%) declined chemotherapy. Following baseline transurethral resection of bladder tumor (TURBT), 39 patients were then treated with pembrolizumab (200 mg) every 3 weeks for a total of three cycles before radical cystectomy (Supplementary Fig. S1B ). Clinical and tumor characteristics are summarized in Supplementary Table  S1  and Fig. 1. All tumors were UC. Briefly, most patients were men (74. 4%), with a median age of 72 years [interquartile range (IQR):  [67] [68] [69] [70] [71] [72] [73] [74] [75] [76] [77] [78]  and presented a clinical-stage cT2 (82.
Study Design and Population PANDORE. PANDORE is a prospective, single-arm phase II trial testing the antitumor activity of preoperative pembrolizumab monotherapy in patients with histologically confirmed (T2-T4aN0M0) transitional cell carcinoma of the bladder (NCT03212651). Pembrolizumab was given at the recommended dose of 200 mg every 3 weeks for three cycles followed by cystectomy with appropriate lymph node dissection. Patients were 18 years of age or older, ineligible for cisplatin or refused cisplatin-based chemotherapy, had diagnostic transurethral resection (TURBT) blocks available, and had adequate hematologic and end-organ function. Key exclusion criteria included documented severe autoimmune disease, chronic infectious disease, use of systemic immunosuppressive medications, and prior use of ICBs.
MATCH-R (Validation Cohort). MATCH-R is a prospective trial studying the evolution of the clonal architecture of tumors from patients with advanced cancer and treated with molecular targeted agents to identify mechanisms of acquired resistance (NCT02517892). The design of the study has been reported previously  (78). Briefly, the primary objective of this study is to characterize molecular mechanisms of resistance to targeted therapies and immunotherapy by next-generation sequencing and the development of patient-derived xenografts and cell lines. Patients treated with pembrolizumab with metastatic MIBC were enrolled in our study and define the validation cohort 3. Baseline, ontreatment, and postprogression biopsies were performed in patients treated with pembrolizumab. In addition, blood samples were collected longitudinally throughout the treatment and at progression in patients for collecting serum, plasma, and circulating tumor DNA.
Each deposit was manually performed and then covered with 2 μL of a matrix solution (HCCA-portioned-Matrix for Maldi-TOF-MS measurements in microorganism identification-(Bremen) with 500 μL of Solution OS (acetinitrile 50%/water 47. 5%/trifluoroacetic acid 2. 5%; LCH CHIMIE). This analysis was performed using a MicroFlex mass spectrometer (Bruker France Daltonics) according to the manufacturer's recommendations. The acquired spectrum was then loaded into the MALDI Biotyper Software (Bruker France Daltonics) and analyzed using the standard pattern-matching algorithm, which compared the spectrum acquired with that present in the library (Bruker database, constantly updated). Score values of ≥1. 7 but <2 indicated identification beyond the genus level, and score values of ≥2. 0 indicated identification at the species level.
Analysis. The data analysis pipeline included the following algorithms developed internally: BWA-MEM v-0. 7. 12 for read alignment to the hg19 human reference genome and Samtools v-1. 2 and Picard-tools v-1. 139 for PCR duplicate quantification and removal. GATK Haplotype v-3. 4-46, snpEff v-4. 0, and MutaCaller-1. 7 (home pileup internally developed) were used for variant calling and classification. Variants were called with a minimum allelic frequency threshold of 1% for already classified variants (those known in the internal database) and 5% for nonclassified variants, and a read depth threshold of 30× for the total reads at the variant location and at least 10× for the variant. Several filters were applied to further select for potentially relevant variants among the called variants. The population databases Exac and gnomAd were used to automatically filter out polymorphism as soon as the population frequency was higher than 0.
5%. Nonclassified variants (not known in the internal database) were excluded if the intrarun recurrency was superior to 4. The tumor mutational load was assessed with the Mercury solution (Integragen) calculated by dividing the number of somatic mutations by the number of bases having a depth greater than 10. We used the data published by Lawrence and colleagues  (85). The somatic mutations used for the mutational load were filtered as follows: somatic score >3, mutated allele frequency in tumor tissue ≥5%, mutated allele count in tumor tissue ≥3, population heterozygous internal database frequency ≤1%, population homozygous internal database frequency ≤1%, and EVS and 100G and Exac variant frequency ≤0. 5% and consequences on protein: stop, start, missense, and splice for the SNPs and in-frame and frameshift for the indels.
Acknowledgments We thank pathologists, nurses, and clinical research associates from  Hôpital Européenn George Pompidou ,  Hôpital Begin ,  Institut Paoli-Calmettes ,  Hôpital Bichat , and  Hôpital Pitié-Salpétrière  for their participation in the PANDORE clinical trial. We are thankful to the flow and mass cytometry facility team of  Gustave Roussy  ( Philippe Rameau  and  Cyril Catelain ). We thank  Fluidigm  for their support. We are grateful for support for equipment from the  French Government Programme Investissements d'Avenir France BioImaging (FBI ; No. ANR-10-INSB-04-01 ) and the  French Government (Agence Nationale de la Recherche )  Investissement d'Avenir program ,  Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases"  ( ANR-10-LABX-62-IBEID ). A. -G. Goubet was supported by  Fondation pour la Recherche Médicale.
C. Alves Costa Silva was supported by  MSD Avenir. F. -X. Danlos was supported by  Fondation Philantropia. M. Roupret  was supported by  Fondation Foch  and the  Association Française d'Urologie (AFU). L. Zitvogel was funded by the  RHU Torino Lumière  ( ANR-16-RHUS-0008 ). L. Zitvogel and L. Derosa were supported by  RHU5  " ANR-21-RHUS-0017 "  IMMUNOLIFE, SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination  (SOCRATE), as well as the  SIGN'IT ARC  foundation. L. Zitvogel was supported by  European Union 's  Horizon 2020 research and innovation programme  under grant agreement number  825410  [project acronym:  ONCOBIOME , project title:  Gut OncoMicrobiome Signatures  (GOMS) associated with cancer incidence, prognosis, and prediction of treatment response]. L. Zitvogel also received an  ANR grant-French-German Ileobiome   19-CE15-0029-01.
L. Zitvogel  and  G. Kroemer  received a donation from the  Seerave Foundation. L. Zitvogel  and  G. Kroemer  were supported by the  Ligue contre le Cancer  (équipe labelisée);  ANR  projets blancs;  Cancéropôle Ile-de-France ;  Fondation pour la Recherche Médicale (FRM) ; a donation by Elior;  Institut National du Cancer (INCa) ;  Inserm (HTE) ;  Institut Universitaire de France ; the  LabEx Immuno-Oncology ; and  FHU CARE ,  Dassault , and  Badinter Philantropia. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U. S. C. Section 1734 solely to indicate this fact.