dataesr/scientific-paragraphs-categorization huggingface dataset:
Radiocarbon dating and age-depth modelling Four bulk, and fourteen macrofossil samples (n = 18) were sent for AMS radiocarbon dating (Table  1 ). Prior to analysis, samples underwent both acid and alkali treatment to remove carbonates. Calibration and age-depth modelling was conducted with Bacon  (Blaauw and Christen, 2011) , version 2. 2, using the default settings. The Bacon script constructs an age-depth model by applying an iterative Markov Chain Monte Carlo process by which several thousands of independent likely age-depth models and accumulation rates are constructed between each dated level  (Blaauw and Christen, 2011). In this process the sequence is divided into sections, with a priori memory of accumulation rate inherited from the previous sections. This process avoids sharp.
Statistical analysis Following Martínez  Cortizas et al. (2019)  concentration values from the LOI, WD-XRF and ICP-OES analysis were re-calculated into mass accumulation rates (MAR) prior to statistical analysis (concentration X PAR (g m -2 yr -1 )). Principal component analysis (PCA) was conducted using the software JMP 14, in correlation mode with a varimax rotation on z-score transformed data. The z-score transformation avoids scaling effects of the data and transforms it to average-centered distributions  (Eriksson et al. , 1999).
X-ray diffraction (XRD) mineral analysis XRD analyses were conducted at the Department of Geological Sciences, Stockholm University, using a PANalytical X-ray diffraction system (X'Pert Powder) equipped with a point detector. Pre-treatment of samples followed  Sjöström et al. (2019). The samples were analysed from 2° to 70° 2θ, with CuKα radiation at 45 kV and 40 mA, passing through a curved graphite monochromator, programmable fixed divergence and receiving slits (1°), step size 0. 020° and a count time of 2 s. Prior to analysis the ash residues were washed three times in deionized water in order to remove soluble salts. Processing of the diffractograms, such as determination of background, smoothing, peak localization, and mineral identification was done in HighScore, a PA-Nalytical software with integrated mineral reference patterns from the ICSD database (2012).
Analytical performance WD-XRF and ICP-OES Eighty-eight samples were analysed by WD-XRF acquiring concentration data for Al, Ca, Fe, K, Mg, Na, P, S, Si, and Ti. Accuracy and precision were assessed using NIST 8437 (n = 3) and an internal peat standard (QC PM) (n = 3). Accuracy expressed as the relative deviation from the certified values was generally 10% or better with the exception of Ca, which is present in very low concentrations in NIST 8437. Absolute deviations from the certified values were never larger than 0. 02% or 2 ppm. The precision (relative standard deviation, % RSD) was within 10% for a majority of elements with the exception of Na, which was within 15% (presented in Appendix C: Table  1 ). Aluminium was below the detection limit (1‰) in 34 samples. The concentration values were set to half the detection limit in these samples for the statistical analysis and inter-analytical comparison.
For the ICP-AES analysis 149 samples were analysed (122 ashed peat samples, 14 blanks, and 15 standards) acquiring data for Al, Ca, Fe, K, Mn, Mg, REE (Dy, Eu, Ga, Ho, La, Nd, Y), Rb, Sc, Ti, P and Sr. In order to quantify the accuracy of the wide range of analysed elements, we used a set of three certified reference materials (standards): NIST CRM -2711a (n = 4), a contaminated top soil and LKSD-1 (n = 5) and LKSD-4 (n = 6), two composites of Canadian lake sediments issued by Geological Survey of Canada  (Lynch 1990 , Lynch 1999). Two of the analysed reference samples were removed due disproportionally low reported values for several elements. Here, accuracy is expressed as deviations from the certified values. Calcium, Dy, Eu, Fe, Ga, K, La, Mg, Mn, Nd, Na, P, Sr, Sc, Y, and Yb were within 15% of the certified/ recommended values while the recovery of Al and Ti was lower (72% and 75%, respectively) (Appendix C: Table  2 ).
Elemental ratios From the elemental datasets three elemental ratios were plotted to explore mineralogical and grain size changes: K/Al XRF , Si/Ti XRF , and La/Y ICP (Fig. 5C. ). The K/Al ratio (average 0. 23 ± 0. 31, n = 108) is relatively stable between ~8300 and 5750 cal BP. This is followed by an increase that is sustained until ~4500 cal BP (0. 35 ± 0. 36, n = 39), peaking at ~5200 cal BP (0. 79). The ratio thereafter stays low until ~2200 cal BP, except for a minor peak around ~3070 cal BP. The ratio thereafter generally increases towards the present (from 0. 10 to 0. 40, n = 33) with peaks noted at ~1940 (0. 17), ~1240 (0. 36), ~740 (0. 25), and ~240 cal BP (0. 44). Initially, both Si/Ti XRF and Sc/Ti ICP ratios were explored as Si content may be associated to both inorganic and biogenic mineral phases (e.
CP2 thus appears to be controlled not only by leaching and outwashing, and/or diffusion, but, given the surprising presence of carbonates, by increased Ca content, carbonate precipitation and/or preservation (see below) in certain parts of the record. The third component of PCA 5500 explains only a minor part of the total dataset variance (7%) but most of the variance of P. Phosphorous is derived via aeolian deposition to bogs, both as inorganic minerals (i. e. apatite)  (Wieder, 2006)  and organic particles  (Newman, 1995) , but has a different fate after deposition than conservative lithophile elements  (Le Roux et al. , 2006). Phosphorous is an important nutrient and is therefore expected to be rapidly taken up by plants in the biologically active layer  (Wieder, 2006) , although deposited P seems to be largely retained in the peat  (Schillereff et al.
Elevated nutrient availability is also supported by the presence of brown mosses  (Vitt and Wieder, 2008)  during the early part of HPAE (Appendix A). The undecomposed peat observed during this phase, indicates increased wetness, possibly related to strengthening of westerly airflows and increasing regional precipitation around mid-Holocene  (Rundgren, 2008). Between ~4000 and ~2480 cal BP the temporal resolution of the record is low and only one sample was analysed for mineralogical composition (~3070 cal BP). From this time and onwards, the mineralogy becomes more diverse with typical felsic minerals (quartz, feldspars, muscovite) occurring in varying amount along with occurrence of carbonates. This change is also reflected in the elemental dataset with concordant increases in Al, K, and Na when feldspars and muscovite are identified (Appendix E).
Acknowledgements We wish to thank the students at  Per Brahegymnasiet  for conducting the modified macro-fossil analysis,  Heike Siegmund , Scientific engineer at the  Dept. of Geological Science, (Stockholm Uni. ) for the C, N, and δ 13 C analysis and Pär Hjemlquist, Scientific engineer at Dept. of  Environmental Science (Stockholm University ) for support during the clean lab digestion procedure. Jenny Söderlindh  (MSc) assisted with ashing of peat samples. Carina Johansson , Scientific engineer,  Mikaela Holm  (MSc), and  Dr. Richard Gyllencreutz  (Dept. of  Geological Sciences, Stockholm University ) are thanked for support in the field, lab, and interpretation discussions. Prof. Henrik Skogby  ( Swedish Museum of Natural History ) and  Inés Fernández Cereijo  (Molecular structure specialist,  Universitdade de Santiago de Compostela ) are thanked for XRD mineral identification.
Purpose In MONARCH 1 (NCT02102490), single-agent abemaciclib demonstrated promising efficacy activity and tolerability in a population of heavily pretreated women with refractory HR+, HER2-metastatic breast cancer (MBC). To help interpret these results and put in clinical context, we compared overall survival (OS) and duration of therapy (DoT) between MONARCH 1 and a real-world single-agent chemotherapy cohort. Methods The real-world chemotherapy cohort was created from a Flatiron Health electronic health records-derived database based on key eligibility criteria from MONARCH 1. The chemotherapies included in the cohort were single-agent capecitabine, gemcitabine, eribulin, or vinorelbine. Results were adjusted for baseline demographics and clinical differences using Mahalanobis distance matching (primary analysis) and entropy balancing (sensitivity analysis).
Abemaciclib has demonstrated clinical activity as monotherapy in patients with HR+, HER2-MBC heavily pretreated with both endocrine and chemotherapy in the metastatic setting in MONARCH 1 (NCT02102490)  [15]. MONARCH 1 was a single-arm phase II trial including patients with disease progression on or after endocrine therapy, with prior exposure to a taxane, and with at least 2 prior chemotherapy regimens including at least 1 in the metastatic setting. The objective response rate (ORR) was  19. 7% (95% CI [confidence interval],  13. 3, 27. 5) , and the median OS was 22. 3 months  [15]. Although this was a single-arm study, the ORR and OS observed in MONARCH 1 suggest single-agent abemaciclib may offer a more favorable benefit-risk profile than what might be expected in patients receiving cytotoxic chemotherapy  [6, 8].
Data source This retrospective study utilized the Flatiron Health electronic health records (EHR)-derived database and included patients diagnosed with MBC from 01 January, 2011, to 28 February, 2018. The Flatiron Health database is a US-based longitudinal, demographically and geographically diverse database derived from EHR data from over 280 cancer clinics (~ 800 sites of care) representing more than 2. 1 million active cancer patients. As of March 2018, the Flatiron MBC cohort included more than 15,000 patients with MBC from approximately 180 clinics. Patients were included in the cohort if they were stage IV at initial diagnosis or if they developed recurrent MBC after an initial diagnosis of early stage breast cancer. The database includes both structured and some unstructured EHR data elements, such as patient demographics (gender, race, birth year, and state of residence), type of cancer facility visited (community vs.
Those included had an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1 (within 60 days before or 30 days after the eligible line of therapy). Patients who received CDK4 & 6 inhibitor drugs (palbociclib, ribociclib, and/or abemaciclib) in prior lines of therapy were excluded. Patients who received prior HER2 targeted therapy were excluded. Patients with diagnosis codes for central nervous system (CNS) metastasis  (ICD 9: 198. 3 and 198. 4 ; ICD 10: C79. 31, C79. 32, and C79. 49) on or before the eligible line of therapy were excluded. Due to limited information within the data on the adjuvant setting, prior taxane and endocrine therapy in the adjuvant and/or metastatic setting were not required. Patients who received monotherapy with capecitabine, gemcitabine, eribulin, or vinorelbine in 1 or more lines of therapy qualified as eligible based on the above selection criteria.
If a patient had only 1 eligible line of therapy, the index drug was the drug contained in the eligible line and the index date was the start date of the eligible line. If the patient had multiple eligible lines of therapy, a line was randomly selected from eligible lines and the index date was the start date of the randomly selected line of therapy (Table  2 ). The patients were followed from the index date until the date of death, loss to follow-up, or end of the database. The index date must have occurred at least 3 months prior to the end of the database.
The treatment effect was also evaluated among 2 subsets in additional sensitivity analyses. Since Flatiron Health data are US-based, the first subset was among US patients only, where treatment effect was evaluated between the entire real-world cohort and MONARCH 1 US patients. The second subset was US patients with prior endocrine therapy in the metastatic setting, where treatment effect was evaluated between the real-world cohort with prior endocrine therapy in the metastatic setting and the MONARCH 1 US patients with prior endocrine therapy in the metastatic setting to try and account for the prior endocrine therapy inclusion criterion within the trial. Duration of therapy was defined as time from index date to last order or administration of the eligible drug during the line of therapy.
If the drug was an oral medication, then 30 days were added to the last order date to assume a 30-day supply. Quartiles and median duration of treatment along with 95% CIs were estimated using the Kaplan-Meier method. The Cox model was used to estimate HR. All hypothesis tests were conducted at a 2-sided alpha level of 0. 05, unless otherwise stated. All CIs were given at a 2-sided 95% level, unless otherwise stated. Data were analyzed using SAS version 9. 2 or later (SAS Institute Inc. ) and R (The R Foundation).
Discussion Abemaciclib has demonstrated clinical activity as a monotherapy in patients with HR+, HER2-MBC heavily pretreated in the advanced setting with both endocrine and chemotherapy in MONARCH 1 (NCT02102490)  [15]. Here, we compared OS and duration of treatment in MONARCH 1 with a matched real-world cohort of patients who received standard-of-care treatment with single-agent chemotherapy and had not previously received CDK4 & 6 inhibitors using the Flatiron database. Although MONARCH 1 did not include a control arm, this real-world chemotherapy cohort provided a data source representative of a control arm. The OS was significantly longer in the MONARCH 1 cohort at 22. 3 months compared to 13. 6 months in the matched real-world chemotherapy cohort. Duration of treatment was not significantly different between the two groups; however, it was numerically longer in the MONARCH 1 cohort (4.
Data on adjuvant therapy, including prior taxane use, are not complete in the real-world chemotherapy cohort because patients may have received care prior to adoption of an EHR at the practice, or patients may have received care at a practice outside the Flatiron Health network. Other variables such as sites of metastatic disease (e. g. visceral disease or liver metastases), previous cancers, and comorbidities were not included in the Flatiron Health data. Therefore, residual differences between the real-world chemotherapy and MONARCH 1 cohorts may have contributed to the observed outcomes, even after matching on key measured variables. Another limitation is orders for oral therapies may be incomplete in the structured EHR data, as subsequent refills may not be documented, thus duration of treatment may have been underestimated in the real-world chemotherapy cohort.
(https ://flati ron. com/real-world -evide nce/) 02 2018 * b Eligible line contains any single-agent treatment (capecitabine, gemcitabine, eribulin, and vinorelbine) (a) received 1-2 lines of therapy containing chemotherapy drug prior to eligible line, (b) had a positive test for ER or positive test for PR on or before the eligible line, (c) had a negative test for HER2 on or before the line containing single-agent treatment, (d) had an ECOG PS ≤ 1 (60 day window prior or 30 days after), (e) no diagnosis codes for CNS metastasis on or before the eligible line, (f) eligible line occurs ≥ 3 months prior to end of database, (g) no CDK4 & 6 inhibitor and no clinical study drug prior to the eligible line * Date of most recent dataset utilized in the analyses, Feb 2018, mortality v2. 0 N All MBC in Flatiron a Health real-world cohort (Feb 2018) 15,277 Include all female patients with MBC diagnosed from 1 Jan, 2011-28 Feb, 2018 15,073 Include patients who had any single-agent treatment of (capecitabine, gemcitabine, eribulin, or vinorelbine) in line 2 or later 2312 Exclude any patient with prior trastuzumab, pertuzumab, lapatinib, or ado-trastuzumab emtansine treatment 2145 Select patients with eligible lines b (capecitabine, gemcitabine, eribulin, and vinorelbine) without ECOG missing lines of chemotherapy in the metastatic setting and progesterone receptor status.
Acknowledgements We thank all the patients and their caregivers for participation in the trial. We thank all the investigators and their support staff who generously participated in this work. This study was sponsored by  Eli Lilly and Company. Medical writing support was provided by  Tolu Makinde, PhD RAC , and  Sarah Beckman, PhD , and editorial support was provided by  Dana Schamberger , MA, and  Cynthia Abbott of Syneos Health  and funded by  Eli Lilly and Company. Funding This study was funded by  Eli Lilly and Company.
MATERIALS AND METHODS In this study NGS data derived from three Chinese patients (oral swabs) infected by SARS-CoV-2 were analysed (SRA projects PRJNA601736 and PRJNA603194). All datasets available in SRA up to February 20 th , 2020 were analysed. The two patients (SRR10903401 and SRR10903402/PRJNA601736), 39-and 21-year-old respectively, experienced unusual pneumonia. Despite his anti-viral treatment, patient 1 experienced more severe symptoms The two patients were admitted to the hospital on 25 th and 22 th December 2019 and were discharged in stable condition on 12 th and 11 th January 2020, respectively  [33]. The third 41year-old male patient (SRR1097138/PRJNA603194), presented acute onset of common COVID19 symptoms. A combinatory antiviral therapy was administered to the patient. However, he exhibited respiratory failure and was admitted to the intensive care unit.
Six days after his admission, he was transferred to another hospital in Wuhan for further treatment  [34]. Detailed clinical metadata of the patients are presented in Supplementary Material. The raw read data were aligned on the complete (29,891 bp) SARS-CoV-2 reference sequence (GenBank accession no. MN975262. 1, isolate 2019-nCoV_HKU-SZ-005b_2020) using bowtie2 v2. 3. 0  [35] , after quality check with FastQC v0. 11. 5  [36]. The resulting alignments were visualized with the Integrated Genomics Viewer (IGV) v2. 3. 60  [37]. After removing PCR duplicates, SNVs were called with a Bonferroni-corrected P-value threshold of 0. 05 using samtools v1. 7 (htslib1. 7. 2)  [38]  and LoFreq v2. 1. 5. LoFreq is a very accurate SNV caller especially designed for viral and bacterial genomes; its performance depends on the sequencing depth and the quality of the NGS reads.
For the datasets analyzed in this study (average read depth 133. 5x -598. 2x ) and based on the assessed read quality >Q30 = 88. 2 -92. 7%, LoFreq has calling sensitivity = ~1% and PPV=100  [39]. Variants supported by absolute read concordance (>98%) were filtered-out from intra-host variant frequency calculations. Four SNVs from sample SRR10903402 and 3 SNVs from sample SRR10971381 with statistically significant strand bias (P-value < 0. 05) were also excluded from further analyses. Variations were annotated to the reference genome using snpEff v4. 3p  [40] , SNVs effects were further filtered with snpSift v4. 3p  [41]  and the average mutation rate per gene across the viral genome was estimated using R scripts (v3. 6. 2) in RStudio v1. 1. 456. The colocalization of the intra-host SNVs and population level SNPs retrieved from www.
Sanchis et al. (2015)  have also used a method based on LC-HRMS to quantify 8 targeted PAAs in kitchen tool utensils with a LOD below 2. 5 µg kg -1 foodstuff. The mentioned article additionally shows the benefit of high-resolution mass spectrometry, as a post-processing method was used for the screening of 77 molecules. The migration tests in the said study were performed with water and 3% aqueous acetic acid as food simulants, with data acquisition in full scan mode. The objective of the current study, initiated by a collaboration of two independent stakeholders within the industry of pigment manufacturers and printing inks, was to compare the residual PAA content on the pigments (or pigment purity profile), used in coloured inks, and their transfer from printed tissues into a cold water extract.
To the knowledge of the authors, this study is the first to provide data on pigment purity profile and cold water extraction results from napkins prepared from said pigments. To achieve this study, monopigmented inks were prepared with a selection of azo or high performance polycyclic organic pigments, and napkins were printed with these inks. The colour indexes were selected from the actual Siegwerk portfolio of ink products for the tissue market. According to the authors, these are standard colour index numbers that can meet industry requirements on product performance and  especially with respect to regulation (see Table  1 ). The pigments under scope were sourced from different pigment suppliers, without any disclosure by the suppliers of their manufacturing process for confidentiality reasons.
The analytical parameters of the Ferro PAA analyses are described in Table  3. External calibration curves were constructed by diluting the working solutions of PAA at 5 and 50 µg L -1 with 100 mM aqueous ammonium formate buffer and LC/MS-MS grade methanol to a working concentration range of 0. 1-50 µg L -1 (0. 1, 0. 5, 1, 5, 10, 35 and 50 µg L -1 ) in a final ratio buffer/methanol (9:1). Linear or quadratic regression curves were calculated by least squares regression using Waters TargetLynx software, and accuracy and repeatability were determined by 3 injections at 1 and 10 µg L -1. The data for the calibration curve of each primary aromatic amine are reported in Table  3.
A Q-Exactive Focus mass spectrometer (ThermoFisher Scientific, Bremen, Germany) with HESI source in positive mode was used. The source conditions were as follows: sheath gas flow rate: N 2 : 45 arbitrary unit, auxiliary gas flow rate: 15 arbitrary unit, spray voltage: 3. 2 kV, capillary temperature: 320°C, auxiliary gas heater temperature: 310°C. Data acquisition was performed using the Full Scan mode (mass range from 70 to 300 Da) at a resolution of 70 000 FWHM (m/z 400). The automatic gain control (AGC target) was set up at 1e6. Calibration (in positive mode) of the mass spectrometer was performed weekly with the standard Calmix solution, Thermo Scientific Pierce TM LTQ Velos ESI (reference 88323). The accuracy of the system was better than 5 ppm for all the masses evaluated. For qualitative identification, mass windows of 5 ppm were set up.
The possible matrix effects (or signal alteration) during the analysis of the PAAs via LC-MS/MS were assessed by spiking of the CWE after extraction, a procedure specifically chosen to determine possible equipment-specific interactions between PAA and unknown compounds present in the CWE. Similar to  Mortensen et al. (2005) , the trueness was evaluated by the determination of the recovery in the spiked samples at concentrations 1 Rsd. avg: average relative standard deviation per duplicate analysis (two printed tissues per sample, 2 injections per tissue) *: not calculated because of lack of data of 5 and 10 µg L -1 for each sample, over a period of more than 1 year, as shown in Figure  1. The mean of the recoveries by spiking ranged from 47% to 125% at the two defined spiking concentrations, showing a high matrix effect.
Acknowledgments This work was partially funded by the  Vlaams Agentschap Innoveren & Ondernemen (VLAIO, Belgium)  under Grant  HBC 2016-0265. The authors thank  Lucas Pontier  from  Siegwerk analytical team  for his technical support on this project and  Thermo Electron SAS  for kindly supporting the method development by means of their application support and on Q-Exactive Focus instrument.