dataesr/scientific-paragraphs-categorization huggingface dataset:
The Good Manufacturing Practice (GMP) drug substance of UCPVax was produced by PolyPeptide biotech (Strasbourg, France). Clinical grade peptide production and formulation will be performed according to GMP preparation and compliance by the Pharmacy Department of the University Hospital of Besancon like in the previous trial in lung cancer (Clinical Trial NCT02818426). The two UCPVax peptides, UCP2 and UCP4 at 1 mg/ml (combined with Montanide ISA51 as adjuvant), will be injected subcutaneously in two separate sites (one site per peptide) (Figure  1 ) at days 1, 8, 15, 29, 36, and 43 (priming phase) following by boost vaccinations: every 6 weeks for the two first boosts (W13 and W19) and every 9 weeks afterward (W28, W37, and W46).
Novelty statement What is the new aspect of your work? CADENZA (NCT03347422) is the first placebo-controlled Phase 3 study of a pharmacologic therapy specifically targeted for cold agglutinin disease (CAD) in patients with CAD and no recent (within 6 months of enrolment) history of red blood cell transfusion, and the data presented in this manuscript represent its first findings on the impact of inhibition of the classical complement pathway via sutimlimab on patient-reported health outcomes in CAD.
19 Consequently, there is a substantial unmet need for an effective therapy for CAD with a favourable safety and tolerability profile. Targeting the classical complement pathway is a rational therapeutic approach for the management of haemolysis in CAD. 13, 20 timlimab is a first-in-class humanised monoclonal antibody and C1s inhibitor that selectively targets the classical complement pathway, while retaining the immune surveillance functions of C1q and the lectin and alternative complement pathways. 21, 22 In the Phase 1 Part A/B trials of sutimlimab, a 90% reduction of classical complement activity was observed. 21 In the Phase 3 CARDINAL (ClinicalTrials. gov, NCT03347396) and CADENZA (NCT03347422) trials, which examined the effect of sutimlimab in patients with and without a recent history of transfusion, respectively, treatment rapidly halted haemolysis and increased Hb levels, coinciding with near-complete inhibition of the classical complement pathway.
13, 20  is important to show that this translates into an improved QoL for patients, and that the overall burden and benefits of treatment are favourable. In the CARDINAL trial, sutimlimab rapidly improved patient-reported outcomes (PROs) (Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-Fatigue], the 12-Item Short Form Health Survey [SF-12], EuroQol visual analogue scale [EQ-VAS], Patient Global Impression of Change [PGIC] and Patient Global Impression of (fatigue) Severity [PGIS]). 23 In the CADENZA trial, sutimlimab, but not placebo, rapidly increased mean FACIT-Fatigue scores by approximately 5 points and pursued this improvement through to Week 26. 20 In a recent pooled analysis of data from CARDINAL and CADENZA, a FACIT-Fatigue score increase of 5 points was estimated to be a clinically important change (CIC) in patients with CAD.
| Statistical analyses The full analysis set (FAS) consisted of all randomised subjects who received at least one dose (including a partial dose) of the study drug. In the overall trial, statistical analysis was performed using SAS ® version 9. 3 or higher (SAS Institute Inc. , Cary, NC). For the PRO endpoints, continuous endpoints were summarised by visit and treatment arm using descriptive statistics for the FAS. When applicable, missing items were handled based on the specific PRO instrument. Subjects missing baseline evaluations were not included in the PRO analyses. The FACIT-Fatigue questionnaires were analysed as recommended by the questionnaire authors (see http://www. ser. es/wpcontent/uploads/2015/03/FACIT-F_INDICE. pdf). The questionnaires were considered complete, and the subscale total score could be calculated, if at least 7 of the 13 items were answered by the subject.
| Data sharing statement Qualified researchers may request access to patient-level data and related study documents, such as the clinical study report, study protocol (with amendments), statistical analysis plan, and dataset specifications. Of note, patient-level data will be anonymised, and study documents will be redacted to protect the privacy of trial participants. Further information related to Sanofi's data sharing criteria, eligible studies, and process for requesting access can be found at: https:// www. vivli. org/. Note: FACIT-Fatigue score range is 0 (worst fatigue) to 52 (no fatigue); EQ-VAS scale (0-100): worst health (0) to best health (100); SF-12 scores range from 0 to 100 (higher scores representing better self-reported health). Abbreviations: EQ-VAS, EuroQol visual analogue scale; FACIT, Functional Assessment of Chronic Illness Therapy.
| FACIT-Fatigue scores Absolute FACIT-Fatigue scores have been reported elsewhere. 25 CIT-Fatigue responder rates (i. e. , percentage of patients with an improvement of ≥5 points) over time are shown in Figure  1 , alongside contextual data on haemolytic anaemia response rates (Hb ≥11 g/dl and/or Hb increased by ≥1. 5 g/dl from baseline; bilirubin normalisation to ≤20. 5 μmol/L). A maximum fatigue response rate of 63. 6% in the sutimlimab group was reached at Week 5. In the placebo arm, the maximum fatigue response rate was 45. 0%, recorded at Week 9. We previously reported that there was a significant difference in FACIT-Fatigue LS mean scores between sutimlimab and placebo. 20 Here, we demonstrate that clinically meaningful improvements in mean FACIT-Fatigue score of 5. 5 points (SD 7.
DATA AVAILABILITY STATEMENT Qualified researchers may request access to patient-level data and related study documents, such as the clinical study report, study protocol (with amendments), statistical analysis plan, and dataset specifications. Of note, patient-level data will be anonymised, and study documents will be redacted to protect the privacy of trial participants. Further information related to Sanofi's data sharing criteria, eligible studies, and process for requesting access can be found at: https:// www. vivli. org/.
S1 B). This finding implicates the AP2 complex in MR1 internalization. Considering we saw a higher internalization rate in human blood monocytes compared to T and B cells (Fig. 1  A), we reasoned that differences in AP2 expression might be responsible. Indeed, two transcriptomic datasets revealed that monocytes had the highest expression of three of the four genes encoding AP2 (Fig. S1 C ). Further, C1R and THP1 cells, which internalized MR1 similarly, expressed comparable levels of AP2A1 and AP2M1 protein (Fig. S2 A ).
3 H ). We quantitated the amount of MR1 + endosomes coinciding with early endosomes (EEA1 + ) or late endosomes/lysosome (LAMP1 + ). We found that MR1-Y313A was less likely to be within both types of endosomes than MR1-WT, with the difference being more pronounced for early rather than late endosomes (Fig. 3 H ). Collectively, these data suggest that MR1 contains a conserved tyrosine residue in the cytoplasmic tail that is recognized by the AP2 complex for efficient internalization from the cell surface into early endosomes. AP2 interacts with MR1 at the plasma membrane Our attempts to demonstrate an interaction between the AP2 complex with MR1, or the well-characterized AP2 cargo TfR, by immunoprecipitation were unsuccessful, likely due to the transient nature of AP2-cargo interactions. Instead, we employed the proximity ligation assay (PLA), which can measure protein interactions within fixed cells.
The precipitate was then divided into new tubes and incubated with buffers of varying pH with or without 10 µM Ac-6-FP and then washed. The remaining MR1 HC or β 2 m was detected by immunoblotting (IB). Protein abundance was quantitated with densitometry and shown as a percentage of that at pH 7 for each treatment (below). Molecular weight standards (kD) are shown. Data shown are the mean ± SD of replicates from two independent experiments (A-C and E, n = 4), or representative of two separate experiments (E). Statistical significance was calculated with two-way ANOVA with multiple comparison test where *, P < 0. 05; **, P < 0. 01; and ****, P < 0. 0001; or not significant (n. s. ). Source data are available for this figure: SourceData F6. Recycling may bring MR1 into acidic compartments, as seen for CD1 molecules, which will likely denature MR1-β 2 m complexes as they are unstable at pH < 6.
F9. The protein bands were quantitated with densitometry. Molecular weight standards (kD) are shown. (F) HeLa cells transduced without or with MR1-WT or the mutants were incubated with or without 5-OP-RU for 4 h and then fixed. PLA performed as for Fig. 1  A, with antibodies in the following combinations: (i) rabbit anti-β 2 m and mouse anti-MR1 luminal domain (clone 8F2. F9); (ii) rabbit anti-AP2A1 and mouse anti-MR1 luminal domain (clone 8F2. F9); (iii) rabbit anti-AP2M1 and mouse anti-MR1 luminal domain (clone 8F2. F9). The PLA spots were enumerated, and each dot represents one cell. The average number of PLA spots for ii and iii for each of two experiments were also calculated relative to the number of MR1-β 2 m spots in i and expressed as a fold change of HeLa cells. Data are shown as mean ± SD of replicates from one experiment representative of two (A; n = 2) or the mean ± SD of replicates from two independent experiments (B-F; n = 4).
Human PBMC expression data The relative expression of the transcripts for each AP2 subunit was obtained from (i) The Immunological Genome Project Ultra Low Input RNAseq dataset (https://www. immgen. org/ Databrowser19/HumanExpressionData. html; Heng et al. , 2008) ; and (ii) The Human Protein Atlas version 21. 0 "RNA HPA blood cell gene data" (https://www. proteinatlas. org/about/ download;  Uhlen et al. , 2019).
Confocal microscopy and PLA Confocal microscopy images were acquired on a Zeiss LSM780 with a 40× oil lens (numerical aperture 1. 4) at room temperature (22°C) and captured with a photo multiplier tube detector by Zen 2012 software. Slides were imaged in 90% glycerol, 20 mM Tris-HCl, pH 8, 0. 2 M DABCO (Sigma-Aldrich). Imaging was performed on 10-25 cells from each of two random fields of view, for each of two experiments. Internalized MR1 was followed in HeLa cells overexpressing MR1-WT or Y313A were treated with 10 µM 5-OP-RU for 4 h and then placed on ice to stop protein traffic. Surface MR1 were labeled with mouse anti-MR1 (clone 8F2. F9), then washed and incubated at 37°C in folatefree RPMI (Gibco) with 10% FCS for 4 h to allow internalization. Cells were washed, fixed, and permeabilized in 2% PFA and 0.
05% saponin in PBS, after which permeabilized and blocked in 5% normal donkey serum in 0. 05% saponin in PBS. Next cells were stained with goat anti-EEA1 and rabbit anti-LAMP1 followed by secondary antibodies (anti-goat Alexa Fluor [AF] 647, anti-rabbit AF568, and anti-mouse AF488). Finally, nuclei were labeled with DAPI (1 mg/ml). Images were analyzed using Imaris software (Bitplane, version 9. 6. 1). Each cell was segregated using the "Surfaces" function on the MR1 surface stain. The MR1+, EEA1+, or LAMP1+ endosomes were identified using the "Spots" function and overlapping spots were enumerated. For PLA, HeLa cells overexpressing MR1 or not were seeded onto the coverslips then treated with 10 µM 5-OP-RU as indicated. After washing with PBS, the plasma membrane was stained with the Cell Plasma Membrane Staining kit (ab219941; Abcam; ex.
540 nm, em. 590 nm) as instructed by manufacturer. Fixation, permeabilization, and DAPI staining were performed as above. For each PLA assay, a pair of mouse and rabbit primary antibodies were used to label the indicated targets. PLA was carried out with Far Red Duolink PLA reagents (DUO92008; Sigma-Aldrich; ex. 594, em. 624) with anti-mouse PLUS (DUO92001) and anti-rabbit MINUS (DUO92005) probes according to the manufacturer's instructions. Images were analyzed using Imaris software (Bitplane, version 9. 6. 1). Each cell was segregated using the "Surfaces" function on the plasma membrane stain, then PLA spots were enumerated within each cell using the "Spots" function.
Acknowledgments We thank the  Melbourne Cytometry Platform  from the  Doherty Institute node and the Biological Optical Microscopy Platform  ( University of Melbourne ) for expert assistance. Finally, we thank  Prof. Jennifer Stow  for critical reading of this manuscript and expert advice. E. G. McWilliam is supported by a  National Health and Medical Research Council (NHMRC)   Ideas Grant  ( 2003192 ), and  J. A. Villadangos  is supported by research grants from the  Australian Research Council  (ARC;  DP170102471 ),  NHMRC  ( 1113293 ), and an  NHMRC   Senior Research Fellowship  ( 1058193 ). D. P. Fairlie  is an  NHMRC Senior Principal Research Fellow  ( 1117017 ). A. Hachani  acknowledges support from a  Horizon 2020_MSCA Global Fellowship grant  ( 657766 ). D. P. Fairlie  and  J. Rossjohn  acknowledge support from the  ARC Centre of Excellence in Advanced Molecular Imaging  ( CE140100011 ).
Patients who had previously received prednisone treatment alone during one month or less before MTX initiation were also included. Patients had a standardized assessment of skin, muscle and other organ involvement. Clinical and biological data were collected at disease onset and six months (M6) after treatment initiation. Muscle strength was assessed using the Childhood Myositis Assessment Scale (CMAS, range 0-52) and the Manual Muscle Testing (MMT) scale (range 0-80)  [4]  and skin disease activity using the skin Disease Activity Score tool (skin DAS, range 0-9)  [5]. Severe JDM was defined by i) the requirement for intensive care unit (ICU), and/or ii) the presence of skin ulcerations and/or iii) the presence of a severe muscle involvement, defined by CMAS < 15 or MMT < 30, and/or iv) the presence of a severe organ involvement: dysphonia and/or dysphagia, cardiac or pulmonary function impairment, gastrointestinal vasculitis occurring within the first month of diagnosis.
Muscle biopsies were centrally reviewed by one of the investigators (C. G. ) using the validated score tool for muscle biopsy evaluation in patients with JDM  [7]. All adverse events were recorded. Data were analyzed using descriptive statistics. Quantitative variables were described in terms of median with interquartile range (IQR), categorical variables as frequencies with percentages. Patients' characteristics at diagnosis were compared using chi-square or Fisher's exact test for discrete variables and Mann-Whitney U test for continuous variables. We conducted a univariate analysis to compare patients' characteristics at diagnosis according to the following endpoints at M6: CID, muscle-CID, skin-CID, and MTX intolerance leading to discontinuation before M6. A p-value less than 0. 05 (two-sided) was considered statistically significant.
Data was computed using the Medistica application software p-value. After parental consent, patients were registered in the French Centre des Maladies Rares (BAMARA). This study was approved by the Ethics board of Necker hospital. Sixty-six patients diagnosed with JDM have been followed in our centre during the considered study period. Seventeen patients did not meet eligibility criteria (ten received another first-line treatment and seven had amyopathic JDM), and four were excluded due to missing data at M6. Thus, forty-five patients were included in analyses. Demographic, clinical, immunological and muscle pathological characteristics at diagnosis are shown in Table  1. Median age at diagnosis was 8. 6 years (IQR 5. 8-11. 0). Dermatomyositis was classified as severe in thirty patients (67%), due to cutaneous ulcerations (16/45), severe muscle involvement (11/45), severe organ involvement (24/45) and/or requirement for ICU (6/45).
To cite this version: Nerea Allende-Vega, Joaquin Marco Brualla, Paolo Falvo, Catherine Alexia, Michael Constantinides, et al. Metformin sensitizes leukemic cells to cytotoxic lymphocytes by increasing expression of intercellular adhesion molecule-1 (ICAM-1). Scientific Reports, Nature Publishing Group, 2022, 12 (1), pp. 1341. 10. 1038/s41598-022-05470-x. hal-03564112 or in acute myeloid leukemia (AML)  10. Metformin is being tested in relapsed and/or refractory multiple myeloma (MM) patients in combination with Nelfinavir (NCT03829020), with high-dose of dexamethasone (NCT02967276) and with Ritonavir (NCT02948283). The results of these clinical trials are not available yet. Immunotherapy is a promising approach to fight cancer. Changes in tumor metabolism impact interactions between immune and tumor cells  [11] [12] [13].
Metformin sensitized MM1. S cells to them, but not U266 or U937 (Fig. 3B ). This is in agreement with our previous results showing that some of the metformin effects in these leukemic cells depend on p53 status  20. (C) OCI-AML3 cells were treated with different concentrations (0. 0316; 0. 1; 0. 316; 1 and 2 mM) of metformin for 3 days, metformin was added every day and plasma membrane expression of the stress ligands MICA/B and ULBP1, the integrin ICAM-1 and the cell line marker CD33 were analyzed by FACs analysis. (D) Different MM cell lines MM1. S wtp53 and U266 mutp53 and the pro-monocytic myeloid leukemia cell U937 nullp53 were treated with 2 mM metformin for 3 days and the expression of the above described markers plus the MM cell line marker CD138 were analyzed by FACs. Data represent the Mean Fluorescence Intensity (MFI) levels compared to control, non-treated, cells.
(D) NB4 cells were incubated with different concentrations of ICAM-1 blocking peptides. The specific killing of tumor cells (7-AAD + ) was quantified by FACs. The data represent means ± SD; *p < 0. 05, **p < 0. 01, ***p < 0. 001 Student's t-test compared to control cells or as depicted in the graphic. evaluate, but it accumulates in ovarian cancer patient biopsies  52. Moreover, metformin concentration reaches on average 0. 41 mmol/kg in the colon of colorectal cancer patients daily treated with an oral low dose of 250 mg/d of metformin, with some patients reaching 1. 87 mmol/kg  53, 54. In addition, and remarkably, metformin effects are higher at low glucose concentration (1 mM), which are found in tumor microenvironment  52. This is probably the case of AML and MM patient bone marrow, which is highly infiltrated by glucose-consuming tumor cells.
(D) Different MM cell lines MM1. S wtp53 and U266 mutp53 and the pro-monocytic myeloid leukemia cell U937 nullp53 were treated with 2 mM metformin for 3 days and the expression of the above described markers plus the MM cell line marker CD138 were analyzed by FACs. Data represent the Mean Fluorescence Intensity (MFI) levels compared to control, non-treated, cells. The bar graphs represent means ± SD of 3 independent experiments; *p < 0. 05, **p < 0. 01, ***p < 0. 005 student t-test compare to control cells.
Funding This work was supported by the  PRT -K program 2018 and 2021(MV;  2018-021 ). This work was also supported by the  "Investissements d'avenir" Grant LabEx MAbImprove :  ANR-10-LABX-53  (MV), the  NK  001 project financed by the " Fond Européen de Développement Régional  " ( FEDER-FSE-IEJ 2014/2020 ) and by " Région Occitanie Pyrénées-Méditerranée ", by grant  PID2019-105128RB-I00  from  Ministerio de Ciencia e Innovación  to AA and by  Gobierno de Aragón  (Group  B31_20R ) cofinanced by Feder  2014-2020  " Building Europe from Aragon " and Grants from  AIRC  and  Italian Ministry of Health (FB).
J. Schwaab  is on the advisory board for Blueprint. I. Alvarez-Twose  reports consultancy (honoraria) for  Novartis and Blueprint. K. Brockow  reports advisory board (honoraria) for Blueprint. P. Bonadonna reports consultancy (honoraria) for  Novartis and Blueprint. O. Hermine is cofounder and stock holder of AB Science and reports research grants from  AB Science, Novartis ,  Celgene , and Lipomed. M. Niedoszytko reports honoraria from  ALK  and  Novartis  and support in clinical trials from  AB Science and Novartis. M. C. Carter  is supported by the  Division of Intramural Research, National Institute of Allergy and Infectious Disease. G. Hoermann reports honoraria from  Novartis  and  Incyte. W. R. Sperr reports consultancy (honoraria) for ThermoFisher,  AbbVie ,  Novartis ,  Pfizer ,  Incyte ,  Deciphera ,  Jazz ,  Teva , and  Celgene.
EXPECTED OUTCOMES The aim of this protocol is to perform a scRNA-seq experiment with multiple samples that can be efficiently demultiplexed through bioinformatic analysis. We performed a scRNA-seq experiment with 8 samples from thymus and spleen of 4 mice. Following cell harvesting, thymic and splenic samples were individually labelled with an Ab-HTO. We recommend performing a quality control for the Ab-HTO labelling step, as this gives the opportunity to the investigator to exclude (prior cell loading onto 103 Chromium Controller) samples that are not properly labelled (Figure  1 ). Indeed, unlabelled cells cannot be assigned to a given sample during the sequencing data pre-processing step. After Ab-HTO labelling, samples are pooled and analyzed by scRNA-seq using Chromium 103 platform. Two libraries are produced: cDNA and HTO, those are quantified with the Qubit system and we expect to obtain a concentration ranging from 15-30 ng/mL for cDNA library and 5-20 ng/mL for HTO library.
ACKNOWLEDGMENTS S. P. received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie Grant  Agreement No. 713750 , and from the  Regional Council of Provence-Alpes-Cote d'Azur ,  A*MIDEX  (No. ANR-11-IDEX0001-02 ). D. P. B. received financial support from  ITMO Cancer of AVIESAN (Alliance Nationale pour les Sciences de la Vie et de la Sante, National Alliance for Life Sciences & Health)  within the framework of the  Cancer Plan  (project n  C19046S ) and from  Centre National de la Recherche Scientifique (CNRS)  ' Osez l'interdisciplinarite!' program-'DMATh ' project. We acknowledge bioinformatic platform of CIML for technical support and  Biorender. comfor the creation of the figures.
When the data did not fit normality and variance homogeneity, a non-parametric test of Kruskall-Wallis (K-W) was used, and when it was significant, pairwise comparisons were done with the R package pgirmess  [52]. All statistical analyses were done with R software (R version 3. 6. 1, 2019) and the significance threshold was set at p < 0. 05.
0-21. 7 % according to  [1] ). The presence of coinfections is also consistent with the relatively high prevalence of HPV infections at inclusion  [11]  and can be explained by PAPCLEAR cohort having more sexual partners than the average of the population. By analyzing all the clinic samples of the seropositive women by a quantitative Polymerase Chain Reaction (qPCR) assay, we detected two productive HSV-2 infections, which this case study presents in details. In particular, we describe and analyze HSV-2 and HPV viral load dynamics, the immunological responses (circulating IgG and IgM antibodies and cytokines titration), the vaginal microbiota compositions, the vaginal pH, and data about demographic and sexual behavior.
HPV31 and HPV66 infections persisted until the end of the follow-up. Furthermore, after HSV-2 clearance, HPV31 virus load steadily decreased by one order of magnitude in 150 days to approximately 2. 7 × 10 4 copies per cell (Fig. 1A ). We characterized vaginal microbiota communities using metabarcoding of the 16S RNA. We performed taxonomy and CSTs assignments with the speciateIT and Valencia software packages  [12] , respectively. At inclusion, the vaginal microbiota was mainly dominated by Lactobacillus iners with a minority of Lactobacillus jensenii (Fig. 1C,  and D ). Strikingly, the increase in HSV-2 viral load from DoF 102 was accompanied by a switch from CST III to CST IV, with a more diverse profile dominated by facultative anaerobic species such as Gardnerella vaginalis and Atopobium vaginae.