dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Analysis Spearman's correlation coefficient r s was used to correlate PSA level and quantitative SPECT parameters (SUVmax, NOMV, and TLOM) at baseline, and their variations between two scans. The receiver-operating-characteristic (ROC) curve was drawn to estimate the most discriminating threshold for each parameter to maximize the sensitivity and specificity in predicting the PFS, the DSS and the OS. By dichotomizing the parameters based on their cut-point, a Kaplan-Meier survival curve was generated and Logrank test was used to compare PFS, DSS and OS between each of the two groups  (15). Significance level of p-value was 0. 05. Statistical analysis was performed with XLSTAT software v19. 5 (Addinsoft, Paris, France).
Data Collection Data were collected by retrospective review of the patients' medical charts and entered using electronic case report forms. Collected parameters included demographic information, previous ocular history, type of DME, number and dates of the dexamethasone intravitreal implant injections, additional treatments for DME (before and after dexamethasone intravitreal implant administration), BCVA and IOP throughout the study period, cataract progression throughout the study period, and the occurrence of any complications. All IOP measurements were measured by Goldman applanator tonometer. All visual acuity measurements were measured using Snellen charts and later were converted into logarithm of the minimum angle of resolution for statistical analysis. Data regarding CMT and presence of intraretinal fluid from OCT scans were collected.
Data Analysis Analysis by Series. All patients included in the analysis received a minimum of 2 dexamethasone intravitreal implants with an interval of 3 to 6 months (AE2 weeks) between injections and at least 3 months of follow-up after the last injection that met the inclusion criteria. Treatment outcome was defined as the change from the day of first injection to the result of last injection up to 6 months after the last injection. Analysis by Injection. This analysis included all visual and anatomic observations of each study patient in the 6 months after each injection received (including those who were not included in the analysis per series because of injection intervals of more than 6 months or a single injection being received). The data were analyzed and displayed to depict the change over time in study outcomes up to 6 months after any injection.
Statistical Analysis The data were analyzed using SAS software version 9. 3 (SAS Institute, Cary, NC). All measured variables and derived parameters were tabulated by descriptive statistics. For categorical variables, summary tables were provided, giving sample size and absolute and relative frequency by individual treatment groups. For continuous variables, summary tables were provided giving sample size, arithmetic mean, standard deviation, minimum, median, and maximum by individual treatment groups. Analyzed groups for the tables included HbA1c status, DME duration, and DME status. Changes from baseline for ETDRS and CMT were tabulated per group. Differences were tested using independent sample t tests. The number of injections resulting in an increase of 10 or 15 ETDRS letters or a decrease of 10 or 15 ETDRS letters was tabulated by the number of frequency of participants.
Data analysis We included only participants who attended all three testing sessions for our main analysis (n = 45) as we deemed this type of setting most relevant to POCD research. Patients are typically tested before surgery, again upon discharge and then re-attend the clinic for a follow-up several months thereafter. Analyses comparing baseline (T0) with 3-month follow-up (T2) were repeated post-hoc for participants who had only attended T0 and T2 (n = 57; see Additional file 1). Data on either SRT or GP were missing at T1 for one participant, respectively. Data on TMT-B were missing on T2 for one participant. These participants were not excluded. First, mean scores on each test were compared across time points using repeated measures analyses of variance (ANOVA) with pairwise comparison between time points T0 to T1 and T0 to T2.
Funding This work was funded by the  European Union ,  Seventh Framework Programme  [FP7/2007-2013], under Grant agreement no. HEALTH-F2-2014-602461   BioCog [Biomarker Development for Postoperative Cognitive Impairment  in the Elderly]: http://www. biocog. eu. The funder had no role in the design of this study, collection of data, data analysis, interpretation of results or writing of this manuscript.
Data collection From January 2003 to July 2018, 12 women underwent adrenalectomy during pregnancy at Cochin Hospital, Paris, France, a tertiary referral center both for complicated pregnancies and adrenal disease. Demographic, clinical, radiologic, and pathologic data were obtained from a prospectively maintained database with additional retrospective review of the charts of the patients and newborn charts. For each patient, the diagnosis was confirmed by an experienced pathologist and classified according to the World Health Organization. This study was approved by the National Data Protection Authority (Commission Nationale de l'Informatique et des Libertés, CNIL n° 1755849), by our Institutional Review Board, and was conducted according to the ethical standards of the Committee on Human Experimentation, and reported according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Statistical analysis Quantitative data were reported as medians (interquartile range). Qualitative data were reported as number of patients (percentage of patients). Comparisons between the 2 groups were performed by the Fisher's exact test for categorical variables, and the Mann-Whitney U test for continuous variables. P values <0. 05 were considered statistically significant recognizing that the number of patients was small and the statistical robustness was limited. All analyses were performed using SPSS for Mac OSX (version 22. 0, IBM Corp, Armonk, NY,.
FACS analysis For determination of IFT20 expression in RCC4+pVHL-, RCC4-, RCC4 siCtl-, RCC4 siVDAC1-, RCC4 siLGMN-cells, cellular suspensions (1 × 10 6 cells) were resuspended in 4% PFA for 15 min and washed 3 times in cold PBS/BSA 0. 1%. Cell suspensions were then incubated with a polyclonal rabbit anti-IFT20 (1 µg/1 × 10 6 cells; Proteintech) for 1 h at 4°C in PBS/BSA 0. 1% buffer. After washing, cells were incubated with Alexa 488-conjugated secondary goat anti-rabbit antibody (µg/1 × 10 6 cells;) for 30 min and washed prior to analysis. Samples were collected with Miltenyi MCSQuant10 (Bergisch Gladbach, Germany) and analyzed with FlowJo Software. Secondary antibody in the control experiment was identical to that described supra.
Tumor spheroid invasion assay A cell suspension of 15 × 10 3 cells/mL was prepared and 200 µL aliquots were put in 24 wells containing solidified agarose 1% and incubated at 37 o C for 48h. Spheroids containing 3000 cells each were placed on the inside of the cover of a culture dish and incubated at 37 o C. Formed spheroids were transferred into wells containing matrigel 25% + 1 mg/mL 3D collagen I gel and left to grow for the designated time (24h, 48h and 72h). Diameters of the spheroids were monitored by an Evos optical microscope. Cell invasion through the surrounding collagen was measured using the ImageJ software and the final spheroid size was compared to the initial size at time zero. At least 8 spheroids were analyzed per condition and at least three independent experiments were performed.
Gene expression microarray analysis Normalized RNA sequencing (RNA-Seq) data produced by The Cancer Genome Atlas (TCGA) were downloaded from cbioportal (www. cbioportal. org, TCGA Provisional; RNA-Seq V2). Different parameters were available for 375 ccRCC tumor samples, with information for VHL status (methylation, mutation and deletion)  [34, 35]. We performed a differential expression analysis between patients with a "primary cilium" signature and patients with a "no primary cilium" signature using the Bioconductor package DESeq2. The results published here are in whole or in part based upon data generated by the TCGA Research Network: http://cancergenome. nih. gov/.
Database analysis To assess the effect of the presence or absence of the primary cilium in ccRCC from Cohort C, we performed a differential analysis between the group expressing the primary cilium (n=48 patients) and the group expressing no primary cilium (n=327 patients) by computing the ratio and p-values obtained with a Wilcoxon rank sum test. We then performed a functional and pathway enrichment analysis on differentially expressed genes (p-value < 0. 05 and absolute ratio > 0. 7) based on Reactome databases using the geneSCF tool  [36]. The terms are considered significant only if enriched with a p-value < 0. 05.
Statistics All values are the means±SEM. Statistical analyses were performed using the Student's t test in Microsoft Excel. The p values are indicated. All categorical data used numbers and percentages. Quantitative data were presented using the median and range or mean. Differences between groups were evaluated using the chi square test for categorical variables and the Student's t test for continuous variables. Analyses were performed using SPSS 16. 0 statistical software (SPSS Inc. , Chicago, Ill). All statistical tests were two-sided, and p-values <0. 05 indicated statistical significance whereas p-values between 0. 05 and 0. 10 indicated a statistical tendency.
Low VDAC1 and LGMN expression levels are linked to poor prognosis in ccRCC patients By interacting with hexokinase, or members of the Bcl-2 family, VDAC1 supports glycolysis and apoptosis is prevented. VDAC is thus involved in determining cellular survival or death, which is particularly relevant to cancer cells. To explore its possible role in ccRCC (kidney renal clear cell carcinoma, KIRC), we first interrogated the Gene Expression Profiling Interactive Analysis (GEPIA) human dataset. Interestingly, the patients' overall survival (OS; Figure  1A ) and disease-free survival (DFS; Figure  1B ) plots revealed a direct correlation between low levels of VDAC1 and a poor prognosis. As we had previously shown a link between the asparagine endopeptidase (LGMN) and VDAC1 in hypoxia (Supplementary Fig.
The GLI1/IFT20 signature correlates to the primary cilium and VDAC1 To further reinforce the link between VDAC1-ΔC and the percentage of ciliated cells, we evaluated the expression of genes involved in the biogenesis and the activity of the primary cilium. The analysis of our transcriptomic data in WT MEF in hypoxia versus normoxia  [23]  highlighted differences in the expression of genes related to the primary cilium. Given that mRNA levels of the GLI1 transcription factor and the intraflagellar transport protein 20 (IFT20) had been shown to be modified in hypoxia, -0. 59 and +0. 91 respectively (  [23] , NCBI Gene Expression Omnibus (GEO) (http://www. ncbi. nlm. nih. gov/geo/) under the series record number GSE63247) and because this combination, among all those tested, proved to be a fair reflect of the presence or absence of the primary cilium, we chose to examine these two genes as indicators for the activity and formation of the primary cilium.
However, the DOWN mRNAs indicated complete metabolic reprogramming (Figure  5F ). An in depth analysis of the TCGA database revealed 310 patients with pVHL-ccRCC and 65 patients with pVHL+ ccRCC defined via deletions, mutations and promoter methylation in pVHL (Figure  S9 ). Among the pVHL-tumors, 250 ccRCC tumors in the TCGA expressed both HIF-1 and -2 but 60 expressed only HIF-2. Using the primary cilium signature, we characterized two sub-groups, no primary cilium (PC-) and primary cilium (PC+) in each category. The PC+ group contained a low number of patients (10. 4%, 21. 7% and 13. 8%) compared to the PC-group and showed lower median survival. We also found that the majority of PC+ patients were mostly at advanced tumor stages (stage 3/4-66%) rather than stage 1/2 (34%), whereas we observed the opposite with PC-patients, 25.
Despite sunitinib's clinical efficacy, patients eventually develop drug resistance and disease progression  [41] [42] [43] [44] [45]. We thus checked if patients with tumors presenting the primary cilium, a GLI1+/IFT20+ signature and no VDAC1-ΔC are resistant or sensitive to sunitinib. Analysis of these patients from the clinical trial SUVEGIL (Clinical trials. gov Identifier: NCT00943839), who had been treated with sunitinib, revealed that they had a lower survival rate than the groups with no primary cilium (Figure  6A  and B , Table  S5 ). To reinforce these results, in vitro experiments were conducted using RCC4 and RCC4+pVHL cells in the absence or presence of sunitinib. We found that cells with VDAC1-ΔC were significantly more sensitive to treatment than RCC4+pVHL cells (Figure  S10A ).
PFS and OS were calculated from patient subgroups with GLI1/IFT20 mRNA levels that were less or greater than the third quartile. Statistical significance (p-value) is indicated. The median survival is also indicated. C, In silico analysis of immune cell type fraction (%) according to the primary signature status (no primary cilium and primary cilium). D, In silico analysis of regulatory T lymphocytes (T reg) fraction (%) according to the primary signature status (no primary cilium and primary cilium). E, Tumors from patients with no primary cilium signature and tumors from patients with primary cilium were compared. The level of PD1 mRNA was determined by RNAseq for the TCGA cohort. Statistical significance (p value) is indicated. F, Distribution of ccRCC patients from the TCGA database depending on the primary cilium signature and immunophenoscore.
Interestingly, we also found that each group (pVHL-/HIF-1+/HIF-2+, pVHL-/HIF-2+ and pVHL+) from the TCGA database presented 10. 4, 21. 7 and 13. 8% of patients, respectively, with a GLI1+/IFT20+ signature. The median survival of these patients was lower than for patients with a "no primary cilium" signature. Moreover, patients with this GLI1+/IFT20+ signature presented a significant correlation between aggressiveness and lower VDAC1 expression. Similarly, in our study, siRNA to VDAC1 and LGMN in RCC4 cells shifted the signature in GLI1+/IFT20+ and increased the primary cilium expression. These cells were characterized by higher invasion than siRNA to control cells suggesting a more aggressive phenotype. The same invasive behavior was found in RCC4+pVHL cells. The tumor aggressiveness in these patients could be the result of the combination of a switch to EMT process activation, re-expression or maintenance of the primary cilium, together with a decrease in VDAC1 and LGMN expression and thus the disappearance of the cleaved form of VDAC1.
Acknowledgments This research was supported by grants from the  Fondation Flavien , the  Fondation ARC, La Ligue contre le Cancer and Fondation de France. This work has been also supported by the  French government , through the  UCA JEDI Investments  in the Future project manuscript. We acknowledge the excellent support of the  Nice-Sophia Antipolis Functional Genomics Platform , the microscopy facility of  C3M-INSERM U1065  (the help of  Maeva Gesson  is acknowledged) and the  Canceropole PACA. The authors would like to thank the  "Centre de Ressources Biologiques" from Necker and Saint Joseph Hospitals (Paris, France) and Bicêtre Hospital (Le Kremlin-Bicêtre, France)  for the samples of the PREDIR cohort, and  Dr Sophie Ferlicot ,  Dr Virginie Verkarre  and  Dr Vincent Molinié  for their histological analyses.
Blood sam-ples were collected at septic shock onset (T0) and 1 day (T1), 2 days (T2), 7 days (T3), 14 days (T4), 21 days (T5), and 28 days (T6) thereafter. Relevant baseline data (demographic data, primary site of infection), clinical data (disease severity scores, such as Simplified Acute Physiology Score (SAPS) II, Sequential Organ Failure Assessment Score (SOFA), and Acute Physiology Health Evaluation score (APACHE) II), surgical procedures, antifungal therapy, and outcome parameters as well as routine infection parameters (e. g. , leukocytes, C-reactive protein (CRP), procalcitonin (PCT), and body temperature) were collected. Moreover, EDTA plasma samples from 48 healthy individuals were obtained from Thermo Fisher Scientific internal serum bank, which served as quality controls (QC) for mass spectrometry (MS) measurements.
2. 5. Group Definitions. Candida spp. in the respiratory tract or in fluids from drainages were classified as colonization. Positive results in blood cultures, intraoperative swabs, and Aspergillus spp. in deep respiratory tract specimens with accompanying pulmonary infiltrates were classified as infection. 2. 6. Statistical Analyses. Ratio calculations after MS analysis were performed as described elsewhere  [21]. All study data were entered into an electronic database (Excel 2013 Microsoft Corp, Redmond, USA) and evaluated using SPSS software (Version 24. 0; SPSS, Inc. , Chicago, USA). Principal Component Analysis (PCA) and correlations were performed with JUMP 13. 1. 0 software (SAS Institute, Cary, USA). Figures were created using GraphPad Prism (GraphPad Software, La Jolla, USA). Categorical data were summarized using absolute and relative frequencies.
921 at 7 days following the onset of septic shock (T3) (Supplementary Material Figure  2 ). As previously described throughout our workgroup, the diagnostic performance of procalcitonin (PCT), BDG, and CRP for early IFI detection within the presented cohort of septic shock patients was poor  [21]. However, the combination of these routinely used infection biomarkers (e. g. , PCT) and innovative fungal biomarkers (e. g. , MR-proADM, sICAM-1, and IL-17A) was shown to improve the Plasma samples were collected at the onset of septic shock (T0) and 1 day (T1), 2 days (T2), 7 days (T3), 14 days (T4), 21 days (T5), and 28 days (T6) afterwards. Data in box plots are given as median, 25th percentile, 75th percentile with the 10th as well as 90th percentile at the end of the whiskers. Concerning symbolism and higher orders of significance: * p < 0:05, * * p < 0:01, and * * * p < 0:001.
Discussion This secondary analysis of prospectively collected data identified sICAM-1, thrombospondin-1, and vinculin as suitable biomarkers for early identification of septic shock patients suffering from an IFI as compared to solely colonized patients or patients without any fungal findings. The diagnostic value could be further strengthened by a combination of the aforementioned biomarkers as well as the combined use of sICAM-1 and MR-proADM (which was previously reported to be of diagnostic value in sepsis-associated IFI  [21] ). The diagnosis of an IFI remains a challenge in daily clinical routine, as most of the available diagnostic tools are associated with relevant weaknesses  [20, 21]. In particular, the sensitivity of culture-based technologies is known to be poor, so that only a small portion of septic patients with an IFI can be identified in the early disease course  [32, 33].
Acknowledgments The study was carried out with financial resources of the  Department of Anesthesiology (University of Heidelberg, Germany ). Furthermore, this study received a financial grant from  Heidelberg Foundation of Surgery. Biomarker measurements were carried out by  Thermo Fisher Scientific (Nimes, France, and Hennigsdorf, Germany ). We acknowledge financial support by  Deutsche Forschungsgemeinschaft  within the  funding programme Open Access Publishing , by the  Ministry of Science, Research and the Arts Baden-Württemberg , and by  Ruprecht-Karls-Universität Heidelberg.
De nition of the diel cycle First, all the data was converted to mean solar time (MST) using the equation: M ST = U T C + Lon 1 360 where UTC is the Coordinated universal time, and Lon is the longitude in degrees (west < 0, east > 0). MST assumes there is no day to day variation in the UTC of solar noon at a location, and for our dataset it is a good assumption, mainly since the majority of measurements were taken along the tropics. Each 24 h period was analyzed independently. For a day to be considered to have a diel cycle an increase in concentration had to be observed between 06:00 and 07:00 and a decrease after 17:00, with a greater N SSA_0. 58µm observed during daytime (see above for the diameter determination) during daytime. For this, we divided the day into four periods, from 00:00 to 05:00 (dawn), 07:00 to 11:59 (morning), 12:00 to 17:00 (afternoon) and from 19:00 to 23:59 (night).
Scanning electron microscope with Energy disperse X-ray analysis Using Scanning Electron Microscopy with energy-disperse X-ray analysis (SEM-EDX) and a similar particle classi cation scheme as described in Laskin et al. (  2012 )  18  , we classi ed each particle into one of ve major classes of aerosols: i) Sea salt: To perform the SEM-EDS analysis, we used a Zeiss Sigma500 SEM with a Bruker XFlash®-6|60 Quantax EDS detector, and the Bruker ESPRIT feature software package for automatic particle detection and chemical classi cation in EDS. The SEM was set at a working distance of about 7. 5mm (±0. 1), an accelerating voltage of 8. 0kV, an aperture size of 60μm, and a magni cation of 2000. The backscatter detector was used to acquire the images. For each lter four images, covering a total of 2471 μm 2 surface area, were taken and each particle above a minimum area of 0.
Pronounced diel cycles of pico-phytoplanktonic populations (e. g. , cyanobacteria) in the Equatorial Paci c, have been previously shown  27, 46, 47. Figure  S12B  shows the same as Fig. S12A , but for the Fiji -New Zealand leg. Here we do not observe diel This is compelling evidence for the marine origin of the aerosols. The collection lters were replaced at about 08:00-09:30 and 20:00-21:30 (see Table  S1  in the SI for timing details); (C) 24-hour signal of marine particle size index γ (vertical axis inverted). Particles grow during the day and shrink during the night. Data collected at 0. 5-3m below sea surface. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.
Acknowledgments Special thanks of gratitude to the  R/V Tara  crew. The authors will like thank the  Tara Paci c Coordinators  for their valuable comments on the manuscript. Funding: This research was supported by a research grant from  Scott Jordan  and  Gina Valdez , the  De Botton for Marine Science , the  Yeda-Sela center for Basic research , and a research grant from the  Yotam  Project. We are keen to thank the commitment of the following institutions for their nancial and scienti c support that made this unique  Tara Paci  c expedition possible: CNRS, PSL,  CSM ,  EPHE, Genoscope/CEA ,  Inserm ,  Université Côte d'Azur ,  ANR , agnès b. ,  UNESCO-IOC , the  Veolia Environment Foundation ,  Région Bretagne ,  Serge Ferrari ,  Billerudkorsnas ,  Amerisource Bergen Company, Lorient Agglomeration, Oceans by Disney , the  Prince Albert II de Monaco Foundation ,  L'Oréal, Biotherm ,  France Collectivités ,  Kankyo Station ,  Fonds Français pour l'Environnement Mondial (FFEM) ,  Etienne BOURGOIS , the  Tara Foundation  teams and crew.