dataesr/scientific-paragraphs-categorization huggingface dataset:
Either scenario, i. e. , the addition of exogenous N or degradation of endogenous organic matter, could result in corresponding directional changes in δ  15  N enamel values in relation to N content. However, the N content and δ 15 N enamel values of the fossil samples are within the range of modern specimens and show no correlation (see Fig. 4 ), indicating good enamel-bound organic matter preservation in our fossil dataset. These observations are consistent with the results of laboratory degradation experiments  38  and with measurements of million-year-old marine microfossils  39, 82, 83  , which suggest that biomineral structures act as an effective physical barrier that protects organic matter from degradation. Although it is a small dataset, the paired δ 15 N enamel and δ 15 N dentin-collagen values for the four fossil specimens are also positively, though not significantly, correlated (see Fig.
2  and Fig. S7 ). Within the THM assemblage, fossil δ 15 N enamel values record trophic enrichment in 15 N (i. e. , low values for herbivores, intermediate values for omnivores, and a high value for the carnivore; Fig. 5 ). While the current fossil dataset is too small to draw any strong conclusions regarding the trophic structure of the THM fossil assemblage, these patterns corroborate the good preservation of dietary N-isotope compositions in tooth enamel for samples in which the collagen is already degraded. Additionally, we observed some interesting results. For example, the δ 15 N enamel values of the browsers were relatively high compared to those of the grazers, deviating from the pattern of low δ 15 N enamel values observed for browsers in the modern African fauna. African herbivores living in forests generally exhibit lower δ 15 N collagen values than herbivores from more open (i.
Indeed, given what is known about the inherent variability in δ 15 N related to abiotic and biotic factors, the coherence of our modern dataset and the consistency of the enrichment in  15  N between trophic levels in samples drawn from disparate localities is remarkable, and demonstrates that δ 15 N enamel is a robust trophic proxy with great potential for application in paleodietary studies. The results of our analysis of δ 15 N enamel of enamel samples from modern and fossil teeth are highly promising. In the archeological and paleontological record, the degradation of organic matter (specifically collagen) is a fundamental limitation  91  restricting measurements to relatively young, wellpreserved samples. Therefore, the ability to measure the nitrogen isotope composition of the organic matter preserved in diagenetically robust tooth enamel (for example, at Tam Hay Marklot Cave) has the potential to be used to investigate the trophic ecology of ancient or even extinct animals over time periods far beyond the limit of collagen preservation.
Tooth enamel carbon isotope measurement. Small aliquots (50-100 µg) of untreated enamel powder were measured using high-precision continuous-flow mass spectrometry. δ 13 C enamel analyses were performed at the MPIC on a Thermo Delta-V continuous-flow mass spectrometer coupled to a Gasbench II gas preparation system, equipped with a liquid nitrogen cryogenic trap (i. e. , the "cold trap method")  97. Untreated enamel powder (see Fig. S5 ) was reacted with >99% H 3 PO 4 for 90 min at 70 °C before the resulting CO 2 was introduced to the continuous flow system. Isotope data are calculated by direct comparison to eleven replicates of a tooth enamel standard (AG-Lox; δ 13 C = -11. 46 ± 0. 2‰) analyzed in each batch. Samples were analyzed in a total of seven analytical batches, and samples were measured in duplicate or triplicate (where possible) in different batches.
Acknowledgements We thank  F. Rubach ,  S. Brömme ,  M. Schmitt , and  B. Hinnenberg  ( Climate Geochemistry Department, Max Planck Institute for Chemistry, Germany ) for technical support,  D. Winkler  ( Zoological Institute, University of Kiel, Germany ) and  T. Kaiser  ( Center of Natural History, University of Hamburg, Germany ) for assistance in sampling the modern African fauna. We thank  J. Broska  and  P. Held  for collagen preparation and δ 13 C/δ 15 N analysis of bone collagen. We also thank  S. Luangaphay  ( Department of National Heritage, Ministry of Information and Culture in Vientiane, Laos ) for the authorization to study the published fauna of  Tam Hay Marklot ,  P. O. Antoine , who aided in taxonomic identification and analysis of the fauna, and researchers who are part of the  Laos  project and participated in the fieldwork ( F.
Demeter ,  L. Shackelford ,  P. Duringer ,  J. L. Ponche ,  Q. Boesch ,  E. Patole-Edoumba ,  T. E. Dunn ,  A. Zachwieja ,  E. Suzzoni ,  S. Frangeul ,  S. Duangthongchit ,  T. Sayavonkhamdy ,  P. Sichanthongtip , and  D. Sihanam ). This study was funded by the  Max Planck Society  ( A. Martínez-García ), the  European Research Council (ERC)  under the European Union's  Horizon 2020 Research and Innovation Program  (Grant Agreement  681450 ) ( ERC Consolidator Grant Agreement  to  T. Tütken ); the  Paul Crutzen Nobel Prize fellowship  of the  Max Planck Society  to  N. N. Duprey ; and the  Deutsche Forschungsgemeinschaft (DFG)  Grant  LU 2199/1-2  and the  Emmy Noether Fellowship   LU 2199/2-1  to  T. Lüdecke. Prior  method development work was supported by the  Scott Fund of the Department of Geosciences, Princeton University  (to D.
Remote Sensing To map volcanic landforms and tectonic structures in North Abaya, we used a 12. 5 m digital elevation model (DEM) from the Japanese ALOS satellite (ALOS PALSAR). These data were combined with previous fault data bases  of Agostini et al. (2011)  and  Corti et al. (2013). Ground deformation is frequently observed at geothermal sites in Ethiopia (e. g. ,  Biggs et al. , 2011; Birhanu et al. , 2018; Hutchison et al. , 2016; Lloyd et al. , 2018b)  and for Abaya, we evaluated this using satellite radar interferometry (InSAR). Recently,  Albino and Biggs (2021)  used Sentinel-1 data provided by the European Space Agency (ESA) to generate an InSAR time series along the entire EARS for the period 2015-2020. Here we explore a subset of the data from North Abaya and for full details of the processing, the reader should refer to  Albino and Biggs (2021).
Note that in all cases CO 2 flux was measured before the 50 cm hole was made and since penetration through the soil causes frictional heat, the probe was left in place until a stable temperature reading was obtained. In some locations the 50 cm depth could not be reached (due to stones or bedrock) and so the depth of the probe was recorded as well as the temperature (Data Set S1). In areas of volcanic-hydrothermal gas emissions, there are usually multiple sources of CO 2 (i. e. , magmatic gases variably mixed with biogenic and terrestrial background). Chiodini et al. (1998)  applied a graphical statistical approach (originally by  Sinclair, 1974)  to demonstrate that volcanically influenced degassing areas often show bimodal CO 2 flux populations, and that these populations can be distinguished using the inflection points on logarithmic probability plots.
In our study, we used probability plots and the inflection points to identify different background and volcanic-hydrothermal populations in both our temperature and CO 2 flux data sets (Section 4. 3). To produce maps of CO 2 flux and temperature, we used a sequential Gaussian simulation (sGs) method  (Cardellini et al. , 2003). These methods allow the user to undertake hundreds of realizations of the survey grid and are particularly useful for CO 2 because they constrain the uncertainty in the total flux. sGs methods require a high sampling density and hence were attempted only on the Western flank of the Abaya Graben and the flank of the SDHRC. Three hundred sGs were performed using the sgsim simulation tool  (Deutsch & Journel, 1998)  in the Stanford Geostatistical Modeling Software (SGeMS) package  (Remy et al.
3. CO 2 flux and temperature are greatest around the wedge of the Abaya horst (i. e. , toward the southern extent of the Western Abaya graben fault). Note that between ∼1,500 and ∼2,300 m along the profile, we were unable to access the hanging wall of the fault because of surface water. The lack of high CO 2 in this area likely reflects a gap in sampling rather than a genuine decrease in CO 2 flux in this section of the fault. The data that are shown in this area are from the footwall. show close resemblance to a subcontinental lithospheric mantle (SCLM) source  (Bräuer et al. , 2016; Gautheron & Moreira, 2002; Gilfillan & Ballentine, 2018 ; Figure  11c ).
3 He/ 4 He is corrected for air and given in R C /R A notation. The X-value is calculated as ( 4 He/ 20 Ne) measured /( 4 He/ 20 Ne) air and provides an assessment of how much air has been entrained into the sample. X-values close to 1 are air-dominated, and those with much higher X-values indicate that very little air has been incorporated into the sample. Endmember 3 He/ 4 He for depleted mid-ocean ridge basalts (MORB), subcontinental lithospheric mantle (SLCM), plume and crust are shown on the left of the plot after values from Gilfillan and Ballentine (2018),  Bräuer et al. (2016) ,  Hilton et al. (2011) ,  Graham (2002) , and  Gautheron and Moreira (2002). Gas geochemcial data from Ethiopia, Kenya and Tanzania are from (Figure  11a ), it becomes evident that their high CO 2 concentrations as well as δ 13 C values of -6.
Figure11. (a) Carbon isotopes (δ 13 C) of soil gas and fumarole samples from Ethiopian, Kenyan and Tanzania volcanic-hydrothermal systems. δ 13 C of CO 2 is plotted against the reciprocal of CO 2 concentration in the sample. The data define a triangular array defined by three endmembers: air, biogenic CO 2 (with characteristic light δ 13 C of -20‰ and -25‰) and magmatic CO 2 (with δ 13 C between -3‰ and -8‰). (b) Inset of (a) showing δ 13 C for the highest concentration samples (note the logarithmic rather than reciprocal scale). (c) He isotopes versus X-value. 3 He/ 4 He is corrected for air and given in R C /R A notation. The X-value is calculated as ( 4 He/ 20 Ne) measured /( 4 He/ 20 Ne) air and provides an assessment of how much air has been entrained into the sample. X-values close to 1 are air-dominated, and those with much higher X-values indicate that very little air has been incorporated into the sample.
To utilize these new drugs most efficaciously, studies are needed to identify patient populations that would benefit most from these new antifungal treatments. However, demographic and clinical factors that are associated with prolonged hospitalization solely to complete iv AF Tx have to date not been sufficiently described. In order to delineate characteristics, as well as identify predictors for prolonged hospitalization solely to complete AF Tx, we performed a sub-analysis of the ECMM Candida III dataset  [4].
First, univariable analysis of clinical predictors was performed. All variables significant at p B 0. 15 in univariable analyses were considered as possible predictor variables for multivariable analysis. This study was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. For the database, retrospective data entry, and data analysis a central ethical approval was obtained at the University of Cologne, Germany (EK 17-485) that indicates that, generally, neither informed consent nor institutional review board (IRB) approval of each participating hospital would be required. Each participating hospital was required to obtain local IRB confirmation or approval as deemed necessary by the respective local regulations/authorities.
Results A total of 621 unique patients with culture proven candidemia were included in the parent study. Of those, 16. 1% (100/621), reported from 33 institutions in 16 countries had prolonged hospitalization specifically for the completion of iv AF Tx according to the treating physician. Hospitalization was prolonged solely to complete iv AF Tx by a median of 16 days (IQR 8 -28; mean 22 days, SD 19 days; data available from 81 patients); the total duration of hospitalization in that group was median 21 days (IQR 15-45, mean 35 days). The median duration of hospitalization in those without prolonged hospitalization for iv AF Tx (n = 521) was 14 days (IQR 5-30 days; mean 22 days, SD 42). For the cohort of 100 patients with prolonged hospitalization solely to complete iv AF Tx, patient characteristics, risk factors, treatment, as well as distribution of Candida spp.
Acknowledgements The authors would like to acknowledge the contribution of  Prof. Nikolai Klimko , who unfortunately passed away before the manuscript was submitted for publication. Author contributions Substantial contribution to study concept and design: MH, PK, OC, JSG, ME, Substantial contribution to the acquisition of data for the work: All authors. Accessed and verified all data: MH, JSG, and ME, Substantial contribution to the statistical analysis or interpretation of data: ME, MH. Drafting the manuscript: MH, ME, Critical review of the manuscript and final approval for publication: all authors. Funding Open access funding provided by  Medical University of Graz. The study was partly funded by an  Investigator Initiated Research Grant  from  Scynexis  ( PIs Hoenigl  and Cornely) and an  Investigatior Initiated Research Granz  from  Mundipharma Inc.
The funders had no influence on the study design or on the analysis of the results. cide, IMMY,  Mundipharma  and  Scynexis. JSG has received lecture honoraria from  Gilead  and  Pfizer , outside of the submitted work. JPG has received lecture honoraria from  Gilead ,  MundiPharma  and  Pfizer , outside of the submitted work. TB reports receipt of speaker fees, advisory Board fees and research fellowship funding from  Gilead sciences , research grants from  Pfizer  and  MSD  and advisory Board fees from  Mundipharma. SAA reports research grant from  Cidara , lecture honoraria from  Gilead , and travel grant from  Astellas. AA-I has received honoraria for educational talks of behalf of  Gilead  and  Pfizer , outside of the submitted work. NK was a speaker for  Astellas ,  Gilead Sciences ,  Merck/MSD , and  Pfizer  and an adviser for  Gilead Sciences ,  Merck/MSD , and  Pfizer , all outside the submitted work.
1 mm × 100 mm, particle size 1. 8 μm, Agilent Technologies) coupled to a 6530 accurate mass Quantitative Time of Flight (QTOF) MS system equipped with a dual electrospray (ESI) source and operated in the positive ionization mode (Agilent Technologies Inc. ). Lipid were eluted over 83 min at constant temperature of 40 • C using a gradient of solvent A (0. 2 % formic acid and 10 mM ammonium formate in water) and B (0. 2 % formic acid and 5 mM ammonium formate in methanol:acetonitrile:MTBE, 55: 35:10 [v/v/v]). The raw lipidomic dataset has been deposited at Metabolomics Workbench (www. metabolomicsworkbench. org). The study reference number is # ST002569 and the link is: https://doi. org/10. 2122 8/M8ND9B. MS raw data processing was achieved using the Mass Hunter Qualitative Analysis software package (version B.
07) for peak picking and a bioinformatic script (available at MetaboICM/Metaborose (github. com) and MetaboICM/Data-processing: Script (github. com)), which we have developed and encoded in both Perl and R languages to enable optimal MS data alignment, retention time (RT) correction, filtering of presence, normalization, batch effect correction, and missing data imputation. The resulting final dataset lists reproducible high quality MS signals referred as features, which are characterized by a mass-over-charge (m/z), a corrected signal intensity, and a RT. Lipid annotation was achieved on features that passed our subjective selected criteria of significance (a corrected p-value of 0. 05 following Benjamini-Hochberg correction; corresponding to a p value of 0. 0038; and a foldchange (FC) < 0.
67 or > 1. 5) for the comparison of VLCAD -/-vs VLCAD +/+ mice receiving the same diet. Selected features were annotated by alignment with our in-house database containing >500 previously annotated lipids using MS/MS and public databases (Metlin and Lipid Map), as well as by MS/MS analyses, from which mass spectra were manually interpreted to identify the polar head and acyl chains based on their fragmentation pattern, as previously described in detail  [35].
Western Blot analysis Protein homogenates from pulverizing heart were separated on SDS polyacrylamide gel then transferred to nitrocellulose as previously described  [36]. Detection was carried out using primary antibodies against GRP78/BIP (Abcam, 1:1,000), CHOP (Cell Signaling Technology, 1:1,000), Ryanodine receptor 2 (RyR2) (Abcam, 1:2,000), phospholamban (PLB) (EMD Millipore, 1:1,000), SERCA2a (Thermo Scientific, 1:1,000). The HRP-conjugated β-Actin antibody (Santa Cruz Biotechnology) served as loading control. Signal were detected with the ChemiDoc Imaging System (Bio-Rad Laboratories, Berkeley, USA), and quantified with the Image Lab 6. 0 software (Bio-Rad Laboratories, Berkeley, USA).
Statistical analysis For untargeted lipidomic analysis, the final corrected dataset containing all features for VLCAD +/+ and VLCAD -/-mice under both dietary condition was imported into Mass Professional Pro (MPP: version B. 14. 00; Agilent Technologies Inc. ) for statistical analysis. Independent testing of each feature was achieved on log 2 transformed data using an unpaired Student t-test with Benjamini-Hochberg correction for comparison of VLCAD +/+ vs VLCAD -/-mice for each dietary condition. The selected threshold of significance was a corrected p-value <0. 05 as an estimation of false discovery rate of 5 % and an absolute fold change of 1. 5. Data for ACs, F 2 -IsoP and F 4 -NeuroP, as well as protein and gene expression were compared between VLCAD +/+ and VLCAD -/-mice under each dietary condition separately using an unpaired Student t-test or the non-parametric Mann and Whitney test whenever variances were significantly unequal using GraphPad Prism version 9.
0 (GraphPad software, Inc. ) and significance threshold was set as p < 0. 05. Supplementary analyses of these data were also conducted using a 2-way Anova (genotype vs. condition) and post-hoc Fisher's LSD test. Data are depicted as volcano plots as well as a heat map whereby the median of scaled lipids for each group was plotted using "pheatmap" in R (untargeted lipidomics) and as dotted box plots, where the midline represents the median, the box represents the interquartile range (IQR) between the first and third quartile, and dots are individual values.
Untargeted lipidomics unveils glycerophospholipid (GPL) acyl chain remodeling in VLCAD -/-mouse hearts that is exacerbated under the high fat diet (HFD)/fasted condition Considering our previous finding of a lower DHA levels in GPLs in 7month-old VLCAD -/-mice  [23] , the impact of VLCADD on cardiac complex lipids, particularly GPL sub-classes, was further characterized under CD/fed (baseline) and HFD/fasted (mimicking metabolic decompensation) conditions. For this, we used a previously validated high-resolution LC-QTOF-based untargeted lipidomic workflow optimized for isomer resolution, which can detect >1000 reproducible MS features (defined by a mass-to-charge ratio (m/z), retention time and signal intensity) covering 20 lipid sub-classes, including their acyl side chains  [35]. The final dataset retained 2075 MS features eluting in the first 40 min of the chromatogram; this excluded glycerolipids because their MS signals were saturated under the HFD/fasted conditions.
29) under the HFD/fasted condition, of which 8 were common to both conditions. These lipids include LC-AC species such as C14:1-AC, which was lower in VLCAD -/-vs control mice under both conditions, concurring with the results of our targeted AC profiling; VLC-AC were,  however, not detected using the untargeted lipidomic workflow, attributed to the sensitivity performance between the two methods. Other lipid (sub-) classes include sphingolipids (SPs), but predominantly GPLs, both phosphatidylcholine (PC) and phosphatidylethanolamine (PE) species. Volcano plot showing the 2075 MS features retained in the final dataset following untargeted lipidomic analysis using high performance LC-QTOF of heart tissue samples of VLCAD -/-(n = 11 per condition) and VLCAD +/+ (n = 9 per condition) mice under A) standard diet (CD)/ fed and B) high fat diet (HFD)/fasted conditions.
Comparison between RLR vs. LLR for huge tumors in the entire unmatched and matched cohort Seven hundred and ninety-nine cases met study selection criteria of which 100 underwent RLR and 699 underwent LLR during the study period. LLR group patient was associated with significantly more previous abdominal surgery (P=0. 006), more malignant pathology (P=0. 010), more liver cirrhosis (P=0. 047) and more median blood loss (300 vs. 200 mL, P=0. 018) (Tables  1, 2 ). PSM and inverse probability of treatment-weighting (IPTW) were performed using the same demographic data criteria as mentioned above to develop propensityscores. After 1:3 PSM with 73 patients in the RLR arm and 219 patients in the LLR arm, both groups had comparable preoperative co morbid condition, liver function, tumour size, numbers and stage of disease.
Specifically, the Cavitron Ultrasonic Surgical Aspirator (CUSA) is not available in the robotic platform. However, with the introduction of several new models of surgical robots in the market, it can be anticipated that the barrier to access and cost of the robotic platform would likely decrease  (22, 23, 35). The main limitation of the current study is its retrospective nature and its associated biases. Despite matching, selection bias may have still have confounded the results observed. Furthermore, since this was a multicenter comparative study, there were differences in the institution or individual surgeon's MILR experience and surgical techniques deployed during MILR. Unfortunately, detailed information about individual surgeon experience was not available from this database. However, the heterogeneity in the surgical technique adopted by the different centers.
| Statistical analysis In total, 300 quadrats were surveyed during the experiment by on average 5. 7 observers, resulting in 5024 counts. We removed 34 quadrats from the analysis that contained no individuals of the target species, as these do not provide information on detection probability. We withdrew four additional quadrats that unexpectedly contained more than 300 individuals to avoid the leverage effect due to these density outliers (Appendix 3). Keeping these quadrats in the dataset would have led to a reduction in the slope of the density effect, which could result from a nonlinear relationship at high densities, but with only four quadrats, we could not reliably test this hypothesis. In some cases (N = 140, representing 2. 8% of the counts), the observers recorded more individuals than were truly present (Appendix 4).
We thus carried out the analyses on two datasets, one in which we removed these counts and one in which we set these counts to the true number of individuals. As there was no discernible difference in the results, we present the results of the former analysis in the main text and the latter in Appendix 7. After all filtering steps, 4319 counts remained in the dataset from which we had removed the observations with excess detections. We also performed the analyses keeping only the experienced botanists to verify that our results were not driven by an excess of novice observers in our sample. Despite some minor differences, our overall results remained unchanged (Appendix 8). We used a generalised linear mixed model (GLMMs) with a binomial distribution and a logit link function to analyse the association between detection probability and the variables we measured and some of their interactions.