dataesr/scientific-paragraphs-categorization huggingface dataset:
It is of clinical importance to accurately identify crystals found in the tissue as soon as possible. Figure  1  presents a typical set of data which can be obtained through classical µFTIR spectroscopy. Here, FTIR hyperspectral images were recorded with a Spectrum Spotlight 400 FTIR imaging system (Perkin Elmer Life Sciences, France), with a spectral resolution of 8 cm -1. Each spectral image, covering the biopsy, consisted of about 30,000 spectra. A precise identification of PMCD is straightforward through the position of characteristic IR absorption bands. The two primary features due to proteins (Figure  1c ), are the amide I (1600-1700 cm -1 ) and amide II (1500-1560 cm -1 ) bands, which arise primarily from the C-O and C-N stretching vibrations of the peptide bond, respectively  [14].
Apart from these contributions, IR absorption bands of calcium oxalate monohydrate (COM) positioned at 780 cm -1 (black arrow in Figure  1c ) or at 1314 cm -1 (red arrow in Figure  1c ) may be selected to obtain the spatial distribution of COM crystallites within the biopsy. One drawback is that IR spectroscopy needs a data bank in which spectra of chemical compounds are gathered to compare them to the IR spectra collected from the sample  [50]. In the case of the presence of a chemical compound with unknown crystallographic structure in the chemical composition of an abnormal deposit, X-ray scattering constitutes a more valuable technique  [51] [52] [53]. In most clinical cases, µFTIR spectroscopy is able to characterize microcristals present in kidney biopsies  [49, 54]. Such measurements are also performed at Tenon hospital.
We used the open-source Quasar software (https: //quasar. codes) and the Orange Spectroscopy toolbox for multivariate statistical analysis  [75]. To generate data of high signal-to-noise ratio, 20-50 spectra were collected. In Figure  2 , we can see a typical IR spectrum corresponding to the DHA compound. Two configurations have been used (Figure  3 ). In the first configuration, the transitions between the different IR sources are clearly visible and are positioned at 1663 cm -1 , 1359 cm -1 and 995 cm -1. In the second configuration, the transitions between the different IR sources are clearly visible and are positioned at 1520 cm -1 and 1205 cm -1 (Figure  3 ). Regarding classical FTIR spectroscopy  [46, 47] , each kidney stone was analyzed in absorbance mode on a Bruker Vector 22 spectrometer by accumulation of 32 spectra between 4000 and 400 cm -1 , with resolution 4 cm -1 and time acquisition 1 s/spectrum.
Information sources The search strategy included electronic searches in four databases, websites and journal hand searches and reference lists searches. The Cochrane Database of Systematic Reviews was first searched. CINAHL, PubMed and PsycINFO were searched separately on EBSCOhost platform. An additional search was conducted with keywords found in titles of retrieved articles. The International Clinical Trial Registry Platform (ICTRP) was searched with trauma in title and substance use disorder in condition. Reference lists of relevant systematic reviews, meta-analyses and studies identified in the search were inspected. Searches of the following websites were conducted: European Society for Traumatic Stress Studies ( https://www. estss. org ), United Kingdom Psychological Trauma Society ( http://www.
Data extraction and management After verifying inclusion criteria for each study, relevant characteristics were systematically extracted by one reviewer using the Cochrane Collaboration data collection form ( Cochrane Effective Practice and Organisation of Care EPOC, 2017 ). A free version of Review Manager software (The Nordic Cochrane center, The Cochrane Collaboration, 2014) permitted calculations of standardised mean differences between intervention and control groups using study data on ER, PTSD and SUD severity outcomes. For the abstinence outcome, odds ratios were calculated. Double checking was performed.
Data analysis and synthesis methods Analysis and synthesis were conducted following the Cochrane Handbook for Systematic Reviews of Interventions  ( Higgins, 2019 )  and the Cochrane Consumers and Communication Review Group  ( Ryan, 2013 ). Reporting was guided by Synthesis Without Meta-Analysis (SWiM) reporting guideline  ( Campbell et al. , 2020 ). (a) The following characteristics were explored in a systematic structured way and descriptive data were collated in tables allowing for visual examination: design, age, sex and number of participants, type of population, type of intervention, duration, completion rate, treatment settings, and delivery format. (b) Study findings were analysed for each outcome including intervention direction and size of effect. Though it was hypothesised that studies would differ regarding comparator, it was decided to summarize effect estimates for each outcome when five or more RCTs were selected.
Quality appraisal The general risk of bias was moderate to high, with high variability across studies. Graphical representations of the authors judgements were generated within a systematic review software ( Review Manager RevMan, 2014 ) and are presented in Fig. 2. The risk of bias judgements for each RCT are reported in Fig. 3. The psychological nature of the intervention rendered a double-blind methodology impossible  ( Roberts et al. , 2016 ). Blinding of the outcome assessments was reported in seven studies. The presence of active components in control groups  ( Najavits and Hien, 2013 )  and the use of selfreported questionnaires to assess ER, PTSD and SUD outcomes in many studies  ( Grundmann et al. , 2018 )  was a limitation to the data validity.
Sample Size In qualitative research, the number of interviewees is not a determining factor in the significance of the results. Data saturation through redundancy will be the main indicator. Thus, an initial sample size is estimated but the final sample size will be determined by data saturation  [29]. Concerning this specific population of SLAM representatives, in the absence of previous knowledge about their participation in focus groups, it is difficult to estimate precisely the number of participants. There is one SLAM per geographic department and five and 12 representatives in a SLAM, that is to say about 500 SLAM representatives in France. They are mostly from the state civil service (excluding national education), but within the state civil service, they cover a wide variety of professions and all categories of agents.
Given that it is recognized that, in the case of a homogeneous sample, (i) the first five-six participants produce the majority of new information in the dataset, while little information is obtained from subsequent participants, and (ii) that data from the first 10 participants identify 80-92% of the information  [30] , and that when the sample size is around 20 interviews then little new information will be collected  [31] , the five focus groups consisting of six to 12 SLAM representatives (30 to 60 participants) will be organized to allow for r data saturation (i. e. , when no new codes or themes emerge). Focus group interviews will be discontinued when data saturation is reached.
Description of the Interview and Data Collection The focus groups will be supervised by two researchers: C. M. who is a doctor, addictologist, doctor in human and social sciences, and B. D. who is a doctoral student trained in qualitative research. For ethical reasons and respect for confidentiality, these two researchers will not know the participants (only the research manager will be aware of personal data). They will only know the number and the breakdown by gender of the group. Upon arrival, the participant will sit down in the group interview room where the desk sign with his or her ID code is located. The interviews will be filmed in order to link these socio-demographic criteria (by vision of the sign) to the remarks made: this will be done in the written transcription by affixing the identifying code before the verbatim, and this will make it possible to better contextualize the story.
Data Analysis To analyze these qualitative data, the methodological framework proposed by  Braun and Clarke (2006)   [32] , which consists in carrying out a thematic analysis, will be applied. The recordings of the speeches will be transcribed verbatim, following the exact course of the interview, and mentioning all the elements of communication, including the non-verbal cues, in order to fully understand the interactions (laughs, hesitations, attitudes). Then, the verbatims will be analyzed using NVivo 11 pro software (QSR International, Burlington, MA, USA). Coding and thematic analysis will be carried out by the researchers who carried out the interviews. The report of the qualitative analysis will follow the COREQ (COnsolidated criteria for REporting Qualitative research), guidelines recommended by the EQUATOR network (Enhancing the QUAlity and Transparency Of health Research) for reporting qualitative research.
This knowledge of the typologies of alcohol use (mild, moderate or severe alcohol use disorders) in the professional social setting will make it possible, according to the alcohol healthrelated risk and treatment response pyramid, to formulate more appropriate prevention measures  [35]. This study has several strenghs. First, the choice of interviewing SLAM representatives, who may be witnesses to alcohol-related problems without being directly involved because people affected by alcohol problems find it difficult to talk about them. Second, even if some SLAM representatives are retired, they have a perfect knowledge of health problems in the workplace because they are in charge of carrying out prevention/health promotion actions in the public service workplaces. Third, the choice of focus-group interviews that involve group interactions will generate deeper and richer data in many scenarios  [36].
Focus group interviews collect data from each participant and generate new questions and answers through interactive verbal communication among group members. This provides an opportunity to learn about the needs and feelings of participants and to explore the influence of cultural values and beliefs  [28]. This study has several limitations. First, due to the fact that SLAM representatives do not have clinical expertise in mental health, the data collected will be personal perceptions of a social environment but not a diagnosis. Second, the choice of the participant can lead to "confirmation bias" because humans tend to select information that is consistent with what they believe (or want to believe) and interpret the information available to them in favor of their preferred hypotheses  [37].
Liquid nano-chromatography and mass spectrometry analysis This analysis was achieved with a linear ion trap-Orbitrap mass spectrometer (LTQ Orbitrap Elite, Thermo Scientific) equipped with a nano-ESI source and coupled to a nanoliquid chromatography (Easy-nLC II, Thermo Scientific). The separation was achieved on a reversed phase C18 column (NikkyoTechnos, Japan) using a linear gradient of 15% to 55% B over 120 min (mobile phase A: H2O/0. 1% FA; mobile phase B: ACN/0. 1% FA)after sample loading onto an enrichment column. Hence, the eluate was sent to the mass spectrometer with capillary voltage set at 1. 5 kV. The mass spectrometer was operated in the data-dependent mode. MS scans were performed in the orbitrap analyzer (from m/z 300 to 2000 with a resolution of 30,000) and MSMS data were acquired in the linear ion trap.
At last, themass spectrometer targeted the 20 most intense peptide ions for fragmentation (top20 method) with applying dynamic exclusion for 30 s. Raw data were imported in Progenesis LC-MS software (Nonlinear Dynamics). For comparison, one sample was set as a reference and the retention times of all other samples within the experiment were aligned. After alignment and normalization, statistical analysis was performed for one-way analysis of variance (ANOVA) calculations. For quantification, peptide features presenting p value < 0. 05 were kept and MS/MS spectra from selected peptides were exported for peptide identification using Mascot (Matrix Science). Total cumulative abundance of any given protein was calculated by summing the abundances of the different peptides.
Statistics and bioinformatics analysis Proteins were annotated with GO terms from NCBI in concordance with gene ontology (GO) standards. Additional annotations were obtained from Uniprot (http://www. uniprot. org/) and used to further classify proteins according to biological process, cellular component, protein class and molecular function. To integrate the observed proteomic alterations, proteins displaying significantly differential abundances between the different groups of animals were analyzed using bioinformatics research tools/databases (http://www. pantherdb. org/ to identify molecular function andhttp://stitch. embl. de/cgi/ to plot predicted protein interactions).
Interaction network analysis The abundance of proteins involved in the drug detoxification process in the liver was also investigated (Figure  3 ). These proteins displayed an increased abundance under lithium exposure (such as GST kappa, +66%; GST mu, +40%; epoxide hydrolase, +36%; cytochrome P450 2A2, +62%; cytochrome P450 2C11, +48%). Interactions of these proteins with other protein partners were obtained by searching the STRING online database (Figure  4 ). The presented protein functional association networks are the result of the entry proteins "Epoxide hydrolase" (Ephx) and "Cytochrome P 450 2A2" (Cyp2a2). Interestingly, Ephx binds directly to proteins such as gluthation-Stransferase (Gstm1,Gsto1,Gsta4,Gstt1, Gstt2 and Mgst1) and cytochrome P450 (Cyp1a1, In addition, a more global network was represented (Figure  5 ) which enables the visualization of important regulations at multiple levels (protein-protein interactions and protein-chemical interactions).
Statistical Analysis Statistical analyses were performed with GraphPad Prism v7. 05 (GraphPad Software, San Diego, CA, USA). Parasitemia between groups under different treatment conditions were analyzed using one way-ANOVA and the Kruskal-Wallis test. Parasitemia was analyzed, and, when appropriate, the significance of the differences between mean values of two groups was determined using Welsh's t-test. Survival analysis was assessed using the Log-rank (Mantel-Cox) test. Statistical differences in ECM scores between the two groups were assessed using the unpaired test with Welch's correction.
Acknowledgments: The authors thank  P. Grellier  and  D. Depoix  ( French National Museum of Natural History (MNHN), Microorganism Communication and Adaptation Molecules (MCAM)-UMR 7245, Paris, France ) for kindly providing the  Plasmodium berghei ANKA strain and Provepharm SAS (Marseille, France)  for providing the methylene blue (Proveblue ® ).
Ethics This retrospective observational study included all consecutive patients admitted for cardiac surgery under cardiopulmonary bypass at Amiens Hospital University in France from January 1, 2008, to December 31, 2018. According to French laws on medical research, the study falls within the scope of French Reference Methodology MR-004 (declaration identifier: DRCI_ANESTHREA_ ABOUARAB, declaration on the 8th of October 2018)  [10]. The study did not require informing or consent of the patients. No identification or nominative data of the patients were collected. Reporting is according to a guideline on reports of propensity score analysis  [11].
Data extraction Data were collected from our institutional database using the French classification for medical procedures "Classification Commune des Actes Médicaux" (CCAM). Each diagnosis (outcome) was associated with a unique diagnostic code number. The coding of medical acts and diagnoses in our database was carried out by the same physician. We performed computerized data extraction from our local data system DxCare ® (DxCare ® , Medasys) and Clinisoft ® (Centricity Critical Care Clinisoft ® , GE Healthcare), the two computerized systems we have been using since 2007.
Data collection and definition of acute kidney injury We collected the following data from our local database: age, gender, body-mass index, medical history (hypertension, coronary disease, diabetes, dyslipidemia, chronic kidney disease, peripheral vascular disease), the type of surgery (coronary bypass graft, valve surgery, combined surgery, and other surgery), the duration of CPB, and the duration of the aortic clamp. The following postoperative data were collected: Simplified Acute Physiology Score II (SAPS II) at ICU admission, cumulative dose of norepinephrine within 48 h after admission (mg), cumulative diuresis at day 1 and day 2 (ml), cumulative dose of crystalloid expansion and colloid expansion after 24 and 48 h (ml), creatinine (µmol l -1 ) at ICU admission/day 1/day 2, arterial partial pressure in oxygen (PaO 2 , expressed in mmHg) at ICU admission/day 1/day 2, aspartateamino-transferase (ASAT) at ICU admission/day 1/day 2, and the duration of ICU stay (days).
Outcomes (renal failure and death) are reported as percentages and 95% confidence intervals after weighting. Odds ratios (ORs) were estimated after weighting on the propensity score and compared using Pearson's χ 2 test. All tests were two-sided, with a significance level of 5%. Statistical analyses were performed using R software, version 4. 0. 4. ©2021, with the « tableone», « survey», « mice», « ggplot2», « car», « questionr», « weights», « WeightIt», « cobalt», and « epiR» packages.
Study population (Fig. 1) In total, 5938 patients from January 1, 2008, to December 31, 2017, were initially selected from the database. Among them, 885 were excluded: 105 because of beating-heart surgery, 25 because of being refractory to CPB weaning with the requirement of a circulatory support device, 82 for a non-cardiac procedure under CPB, 196 because of nonscheduled surgery (aortic dissection or active endocarditis), and 408 because of exposure to other drugs or because of active bleeding. Finally, the data of 5053 patients were analyzed.
Discussion In this population-based observational propensity scorematched study among cardiac surgery patients, we found that exposure to norepinephrine is associated with a higher risk of AKI and in-ICU mortality. Our results are in accordance with those of previous reports (Table  4 ). Ours is the largest observational study, to date, on the association between norepinephrine exposure and postoperative morbi-mortality and the first to use a matched propensity analysis. Our study had several strengths. Preoperative, intraoperative, and postoperative data were extracted from our local database, reducing the risk of error. The monitoring of diuresis was reported hourly in our electronic record, which is our routine standard care, allowing the precise determination of AKI. In addition, the large amount of collected data, including biological investigations, made it possible to control for numerous cofounders.
There was no preset upper age limit. Data on patient-, disease-, and treatment-related characteristics collected at the time of allo-HCT are shown on Table  1. A total of 547 patients with ALL with CNS-positive (n = 96) or CNS-negative (n = 451) involvement receiving an allo-HCT at one of the EBMT participating centers were included. Completeness of follow-up after allo-HCT was calculated using the method described by Clark et al  12  ; and they were 90% and 93% at the date of the analysis (June 01, 2021).
Continuous variables were categorized according to the median for univariate analyses and included without categorization in the Cox proportional-hazards regression model. Patients with missing information were excluded from analyses. For prognostic analysis specifically pertaining to the CNS-positive group, a stepwise selection was performed for   conditioning intensity, cells source and T-cell depletion. Results were reported as the HR with 95% confidence intervals (CIs). Type I error rate was fixed at 0. 05 for determination of factors associated with time-to-event outcomes. All P values were 2-sided. Statistical analyses were performed with SPSS 24. 0 (SPSS Inc, Chicago, IL) and R 3. 4. 0 (R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Anti-Human CD40 Monoclonal Antibodies and Antigen Adducts Sequences and production methods for in-house-derived 12E12, 11B6, 24A3, 12B4, and CP [CP-870,893, a Pfizer Inc. agonistic antibody  (4) ] anti-human CD40 human IgG4 antibodies have been described  (13). The HIV-5pep antigen cassette (Flex-v1-Pep-gag17-f1-gag253-f2-nef116-f3-nef66-f4-pol158) attached to H chain C-termini has been detailed  (7, 14)  and is contained within GenPept Sequence ID: AJD85777. 1. The HPV16. E6/7 H chain adduct  (9)  has been described (GenBank KP684039). The Dockerin V1 (Doc) H chain adducts and Cohesin-Flu M1 protein were described elsewhere  (6). Other antigen adducts are described in the sections relevant to particular protocols.
Cells were subsequently washed and resuspended in Staining Buffer before being analyzed. All analysis plots were pre-gated on singlet events and live. Cells were analyzed with a FACSCanto II or an LSRFortessa (BD Biosciences). Data was analyzed with FlowJo ® Software (TreeStar; Ashland, OR, USA). The following antibodies were used for analysis of human DC activation: hCD80-PE, clone L307.
Statistical Analyses Data are presented as means ( ± SEM). Statistical significance was determined by Student's t test with or without Welch's correction. A P value < 0. 05 was considered as statistically significant. GraphPad Prism ® software was used for statistical calculations. The following nomenclature was used in figures to indicate the statistical significance: * P 0. 01 to 0. 05; ** P 0. 001 to 0. 01; *** P 0. 0001 to 0. 001; **** is P< 0. 0001.
However, the highly activating anti-CD40 11B6-CD40L-HIV5pep vaccine preferentially expanded the dominant A B FIGURE 4 | Expansion by CD40-targeted GNG antigen of HIV-1-specific T cells in HIV-1-infected donor PBMC cultures. HIV-1 + donor PBMCs were cultured with a dose range of anti-CD40-GNG fusion proteins with and without a low dose of sCD40L (100 ng/ml; 6 nM) and IL-2 for 9 days, followed by stimulation with peptides for pools HIV-1 Gag p17, Nef, and Gag p24 for 6 h, then analyzed by ICS. The data show the percentage at the end of the culture of antigen-specific (A) CD4 + and (B) CD8 + T cells producing IFNg + TNFa in response to peptide stimulation. Similar data were obtained in a replicated experiment (Supplemental Figure  2 ). Gag253-specific CD8 + T cell response, while the same CD4 + T cell responses to Gag17, Gag253, Nef66 were elicited, but to a lesser abundance (Figure  5B ).
The data are one representative of three independent experiments. (B) Total fluorescence of each anti-CD40-gp100-treated population was calculated and compared to the hIgG4-gp100-treated cells, which was set at 100%. Averaged over the three experiments and over the three time points anti-CD40 11B6-CD40L-gp100 gave a mean value of 155 ± 35; anti-CD40 11B6-gp100 mean = 107 ± 14; anti-CD40 12E12-gp100 mean = 107 ± 19. The overall values for anti-CD40 11B6-CD40L-gp100 were significantly greater compared to 11B6-gp100 (p = 0. 0032), 12E12-gp100 (p = 0. 0034), and hIgG4-gp100 (p = 0. 0015). ** indicates a statistically significant difference of P=0. 001-0. 01. 17, and 24, mice implanted with tumor at day 0 were vaccinated with anti-CD40 11B6-CD40L-Doc, anti-CD40 11B6-Doc, IgG4-CD40L-Doc, and non-targeting IgG4-Doc non-covalently linked to human Coh-Cyclin D1 (Figure  11A ).