dataesr/scientific-paragraphs-categorization huggingface dataset:
A randomized double-blind phase II study of adjuvant pembrolizumab or placebo is ongoing for patients with MSI/dMMR solid tumors with persistent circulating tumor DNA following surgery is ongoing (NCT03832569). Combinations of anti-PD1 and anti-CTLA4 monoclonal antibodies (e. g. , nivolumab plus ipilimumab) seem more effective than anti-PD1 or anti-PDL1 agents alone (e. g. , nivolumab, pembrolizumab, dostarlimab; durvalumab, avelumab) in terms of objective response rates that rise from 30% to 60% and one-year overall survival rate with a 15% improvement in a non-randomized phase II study  [23]. Nonetheless there is currently no data from randomized trials comparing monotherapy to combination therapy. The ongoing CA209-8HW will provide useful data for the comparison of nivolumab with or without ipilimumab; NCT04008030)  [46].
Lessons From the FOxTROT Study Pre-or peri-operative therapeutic strategies have been successful in many gastro-intestinal cancer locations. The phase III FOxTROT study (NCT00647530) provided useful data about such strategies for CC patients  [61]. In this randomized trial, 1052 patients with localized CC predicted as stage T3-4, N0-2, M0 by CT-scan were randomized to a perioperative sequence (6 weeks of FOLFOX, then surgery, then 18 weeks of FOLFOX) or the standard strategy (surgery then 24 weeks of FOLFOX). Neoadjuvant treatment was well tolerated and associated with evidence of histological regression in 59% of patients (4% of pathological complete response), histological downstaging and reduced rate of incomplete resections (5% vs. 10%). One should keep in mind that pathologic response has not been demonstrated as a surrogate marker of relapse-free survival or overall survival in CC.
Normative data for the CAMCOG-DS and mCRT in asymptomatic DS individuals To exclude preclinical AD, we derived normative data in the younger subjects (≤35 years: 107 subjects for the CAMCOG-DS and 89 subjects for the mCRT). Normative data were generated in aDS individuals in mild and moderate ID separately. Scores corresponding to the 1st, 5th, and 10th percentiles were used to define pathological performances (see Appendix for further details). For the CAMCOG-DS, cut-points corresponding to the 1st, 5th, and 10th percentiles for subjects with mild ID were, respectively, 77, 78, and 80. In subjects with moderate ID, cut-points corresponding to these percentiles were as follows: 48, 53, and 59, respectively. For the mCRT, cut-points for the participants with mild ID were 34 for the 1st percentile, and 35 for the 5th and 10th percentiles.
ACKNOWLEDGMENTS The authors would like to thank all the participants with Down's syndrome, their families, and their carers for their support of and dedication to this research. We also acknowledge the  Fundació Catalana Síndrome de Down  for global support;  Reyes Alcoverro ,  Marta Salinas , and  Tania Martínez  for administrative support;  Concepción Escolá  and  Diana Garzón  for nursing handling. We also thank the PET imaging technologist, radiographers, technicians, and radiochemists at the  Wolfson Brain Imaging Centre , as well as the clinicians for their help in acquiring the data reported in this article. This study was supported by the  Fondo de Investigaciones Sanitario (FIS) ,  Instituto de Salud Carlos III  ( PI14/01126  and  PI17/01019  to  Juan Fortea ,  PI13/01532  and  PI16/01825  to  Rafael Blesa ,  PI18/00335  to  Maria Carmona-Iragui ,  INT19/00016  and  PI18/00435  to  Daniel Alcolea , and  PI14/1561  and  PI17/01896  to  Alberto Lleó ) and the  CIBERNED program (Program 1 ,  Alzheimer Disease  to  Alberto Lleó  and SIGNAL study, www.
Where possible, the recommendations in this document are evidence based. It is intended to set reasonable standards that can be applicable worldwide, while recognizing the different resources, technological availability, disease prevalence, and health care delivery logistics in various parts of the world. In addition, parts of this and from all peer reviewers (Appendix 2). Of the 38 committee members, 17 (45%) had no relevant RWIs. Recommendations were drafted by the members who did not have relevant RWIs. Members of the writing group conducted comprehensive literature searches of electronic databases, including Medline (via PubMed), Embase, and the Cochrane Library. Evidence tables were constructed to summarize the retrieved studies, with nonrandomized observational designs representing the predominant form of evidence (Appendix S1).
Site exploratory case studies were conducted at only two companies as recommended by Malaysia Automotive, Robotic & IoT Institute (MARii) due to confidentiality issues, time constraints, and their willingness to participate. The only selection criteria for the case studies were that they implement alternative green practices such as rebuilding and restoration vehicle parts. Data was collected through interview sessions with key operational personnel such as the general manager or senior production engineer. For matter confidentiality, each company is simply referred to as Company A and Company B. The interview sessions were conducted simultaneously with site observations as well as an adapted open-ended questionnaire  [10]  to allow flexibility in understanding the questions and in providing answers  [27].
, 2015). The absence of a pronounced seasonal variation in the Southern Hemisphere has been recently attributed to mercury uptake by the terrestrial vegetation which, due to land distribution, is smaller in the Southern Hemisphere  (Jiskra et al. , 2018). In this paper we analyse the Cape Point (CPT) data for the 2007-2017 period and compare them with the data from Amsterdam Island (AMS) obtained in the years 2012-2017. Mercury concentrations remain nearly constant at both sites during the 2012-2017 period. Using simultaneously measured 222 Rn, CO, O 3 , CO 2 , and CH 4 concentrations at CPT and AMS, we investigate the possible reasons for the trend and its change.
, 2017). Annual volcanic SO 2 emissions, as a proxy for volcanic Hg emissions, also do not show exceptionally low emissions in 2009, although the emissions in 2014 were the second highest on record (after 2011) in the 1996-2018 period (https://disc. gsfc. nasa. gov/datasets/MSVOLSO2L4_V3/summary, last access: 19 November 2019). Tropospheric mercury concentrations were found to be influenced by the El Niño-Southern Oscillation (ENSO;  Slemr et al. , 2016b). Such influence could also be a reason for the observed inter-annual variation in GEM concentrations at Cape Point. Table  4  shows correlations of 3-month running averages and medians of GEM concentrations at CPT with 3-month running average of the Southern Oscillation Index (SOI) for 2007-2014 and 2012-2017 and compares them with the 2012-2017 period at AMS.
Acknowledgements. This publication forms part of the output of the  Biogeochemistry Research Infrastructure Platform (BIOGRIP) of the Department of Science and Innovation of South Africa. We thank the  CPT  team for providing the data on which this paper is based. We also thank  Andreas Weigelt  and  Ralf Ebinghaus  from the  Helmholtz-Zentrum in Geesthacht  who for years supported mercury measurements at  CPT  and  Ernst-Günther Brunke  who was responsible for the CPT operation until he retired in 2015. Olivier Magand ,  Aurelien Dommergue  and  Hélène Angot  deeply thank all overwintering staff at  AMS  and the  French Polar Institute Paul-Emile Victor (IPEV)  staff and scientists who helped with the setup and maintenance of the experiment at AMS in the framework of the  GMOStral-1028 IPEV program.
We also thank the  IPEV RAMCES-416 program  which provided greenhouse gas and 222 Rn data for AMS. Last but not least we would also like to thank the reviewers for their in-sightful and constructive feedback, which has helped to improve the clarity and utility of the revised manuscript. Financial support. Logistical and financial support for AMS has been provided by  IPEV  ( GMOstral-1028 program ) since 2012. Funds obtained through the  European Union Seventh Framework Programme  project  Global Mercury Observation System  (GMOS; http://www. gmos. eu/), Labex OSUG@2020  ( ANR10 LABX56 ) and  LEFE CNRS-INSU (SAMOA program ) also contributed to this work. The article processing charges for this open-access publication were covered by the  Max Planck Society. Review statement. This paper was edited by  Ralf Ebinghaus  and reviewed by two anonymous referees.
Data availability. Cape Point data are available on the GMOS website at http://sdi. iia. cnr. it/geoint/publicpage/ GMOS/gmos_historical. zul (GMOS, 2020a). Amsterdam Island GEM data are freely available in the catalogue section at https://gmos. aeris-data. fr/catalogue/ (GMOS, 2020b). Those used in this article (AMS site, L2) have the unique identifier bcb74d91-d6ea-4f83-a897-f98f8ecd044c. Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/acp-20-7683-2020-supplement. Author contributions. LM, CL, TM, HA, OM, AD, PG, and MR provided the data on which this work is based. FS made the statistical analysis and prepared the manuscript in collaboration with LM, HA, OM, and JB.
This comprises Section 4. The first author was supported by the ANR project SRGI ANR-15-CE40-0018 and by the ANR project Quaco ANR-17-CE40-0007-01. The second author was partially supported by grant #524713 from the Simons Foundation and by the National Security Agency under Grant Number H98230-15-1-0171. We thank Dario Prandi, Masha Gordina, and Nate Eldredge for helpful conversations.
Cohort The BiB study is a population-based prospective birth cohort. In total, 12,453 women who experienced 13,776 pregnancies were recruited at their oral glucose tolerance test (OGTT) at approximately 26-28 weeks' gestation, which was offered to all women booked for delivery at Bradford Royal Infirmary (BRI). Eligible women had an expected delivery between March 2007 and December 2010. The study is unique because it includes high proportions of White European and South Asian families, all residing in Bradford, UK. Bradford is a city in the North of England with high levels of socioeconomic deprivation, and the cohort was started due to a high prevalence of poor child health in the city  8. Full details of the study methodology were reported previously  8. The study website provides more information, including protocols, questionnaires and information on how researchers can access data and a full list of all available data.
Children enrolled in the BiB cohort, and born on or after 1 March 2008 with a maternal baseline questionnaire were eligible to take part in ALL IN. Mothers were invited to participate in ALL IN one month before their child's first birthday. A questionnaire was completed by those who consented, and a 5ml venous blood sample was taken from the child, centrifuged, and stored at -80°C. This was repeated one year later to provide questionnaire data and serum from a ~12-month visit (mean age of 14 months, ranging from 9-18 months) and a ~24-month visit (mean age of 26 months, ranging from 23-33 months). Trained community research administrators (CRAs) recruited participants, obtained consent, and collected data, including blood samples, at each visit. They received training in phlebotomy and were assessed by the senior paediatric phlebotomist at the BRI.
Ametop cream or Cryogesic spray were used to anaesthetise the venepuncture site. Only two attempts at venepuncture were permitted for each child. There was a fridge in the clinic for storing bloods before transfer to the lab. The blood samples taken on home visits were kept in a cool bag with an ice pack and then taken straight to the laboratory at BRI within 1-2 hours. The times of each step (blood taken, arrived at lab, centrifuged, aliquoted, frozen) were recorded on the blood form and were entered onto a database (so that researchers can check distribution of times if needed). For home or clinic visits outside normal working hours, the CRA who took the blood sample would centrifuge the blood at the lab and leave it in the lab fridge for processing the next day. All infant metabolomics were performed on serum samples.
Metabolomic datasets in BiB There are six metabolomics datasets including different populations and timepoints available in BiB. These are described below and summarized in Table  1  and Figure  1. We have divided the methods between the two main platforms (NMR and MS). We describe the methods used to generate each dataset and use flow charts to illustrate how selection was performed. NMR metabolomics NMR methods. We describe the NMR methods which apply to all the NMR datasets described in Table  1. Profiling of circulating lipids, fatty acids, and metabolites was done by a high-throughput targeted NMR platform (Nightingale Health© (Helsinki, Finland)) at the University of Bristol, providing quantitative information on 227 metabolic traits (including ratios and other traits derived from the quantified NMR spectra)  1.
Mass Spectrometry 4 Pregnancy MS -Dataset 1a N = 1,000 pregnancies. Single timepoint using EDTA plasma taken from a fasted blood sample between 26-28 weeks' gestation. Of the 1,000, 50% are White British and the other 50% are Pakistani ethnicity. 5 Cord blood MS -Dataset 1b N = 1,000 children (paired with women from Dataset 1a). Single timepoint using cord blood, EDTA plasma. 6 Pregnancy MS -Dataset 2 N = 2,000 pregnancies within a case-cohort design. EDTA plasma sample taken between 26-28 weeks' gestation. Of the 2,000 women, 47% are White British and 53% are Pakistani. NMR, nuclear magnetic resonance; MS, mass spectrometry; EDTA, ethylenediamine tetraacetic acid. check various issues related to the sample integrity and the biomarker quantification. QC reports for the NMR datasets can be found in the Extended data  11.
Participant selection and characteristics of those with NMR data. In this subsection, we present flow charts to illustrate selection and inclusions into the NMR participant groups (Figure  4 ) and describe participant characteristics for the BiB NMR datasets (Table  2 ). Metabolite concentrations were quantified using area-under-the-curve of primary MS ions and were expressed as the means of the medians (MoM) value for all batches processed on the given day.
Mass spectrometry metabolomics Validation of the MS platform. Details of the Metabolon QC procedures and data quality for the Metabolon BiB datasets are described in the reports found in the Extended data  11. In brief, procedures were conducted to: (i) assure that all aspects of the Metabolon process are operating within specifications, (ii) assess the effect of a non-plasma matrix on the Metabolon process and distinguish biological variability from process variability, (iii) assess the contribution to compound signals from the process (using Process Blank) and (iv) segregate contamination sources in the extraction (using Solvent Blank). As an additional data QC, we explored correlations between MS and both NMR and clinical chemistry fasting glucose measures (glucose is the only common trait we have data on for MS, NMR, and clinical chemistry).
Participant selection and characteristics of those with MS data. The flow of participants into the MS datasets are illustrated in Figure  6 , and the characteristics of participants included in the two MS datasets provided in Table  3. Only women of either Pakistani or White British ethnic background were included in the MS datasets because, due to cost, we were only able to do this on a subset of the cohort. As these two groups represent ~85% of BiB it was felt the numbers for any other group would be too small for meaningful analyses. In Dataset 1, 1,000 women were selected on the basis that they had stored fasting plasma, a useable cord blood sample, genome wide data on both mother and offspring and were either of White British or Pakistani origin (Figure  6A ). Following these inclusions, 500 women were selected at random from each ethnic group (White British and Pakistani).
In Dataset 2, a case-cohort design was used  13, 14. A case-cohort design consists of a cohort with an over-sampling of all cases. The BiB case-cohort consists of 2,000 women (only pregnancy samples were assayed in Dataset 2). As with Dataset 1, women were selected based on certain characteristics shown in Figure  6B , including that they had not already had Metabolon MS analyses. From those who fulfilled these pre-specified criteria, six groups of cases were selected: women with (a) gestational diabetes; (b) gestational hypertension; (c) pre-eclampsia; (d) preterm birth; (e) congenital anomaly; (f) stillbirth. In total, 801 women had experienced one or more of these conditions. Having selected all cases these were then replaced into the eligible cohort and a sub-cohort of 1,199 women were randomly selected from the eligible cohort.
Thus, the comparison group in this case-cohort study is representative of the eligible cohort (i. e. the cohort comparison group includes some of the cases in proportions that would reflect the whole cohort). The final BiB case-cohort sample consists of three groups (Figure  6B ): 1) selected as comparison group (N = 1,199), 2) selected as cases only (N = 408), and 3) selected as a case and control (N = 393). The comparison group in any analyses will vary depending on the research question. For the MS dataset, researchers are given the option of using the 'raw' data from Metabolon or a quantified (scaled) data set, in which missing data have been imputed and the multiple of median values transformed to standard deviation-(z-) scores (by subtracting the sample mean value for each metabolite from the participant value and then dividing by the sample standard deviation for that metabolite).
Overlap between metabolomics datasets Having participants in multiple datasets (i. e. maternal pregnancy, offspring cord, offspring 12-24 months) and across the two metabolomic platforms provides scope for unique research opportunities. Figure  7  illustrates the overlap between BiB   blood sample and 1,981 had at least one measurement from either the 12-or 24-month ALL IN subsample. All the mothers with a pregnancy MS sample (from either the first or second dataset) also have an NMR sample. There were 7,919 children in total with an NMR sample in cord blood with 1,275 of these also having at least one measure from the 12-or 24-month subsample. Of those with NMR cord blood data, 2,486 had a mother with MS pregnancy data (from either the first or second dataset) and 1,000 have MS cord blood data.
There were 2,108 children with at least one NMR measure at either the 12-or 24-months assessment and of these, 690 have a mother with MS metabolite measures in pregnancy data (from either dataset) and 229 have MS cord blood data. Although the exclusion criteria for MS dataset 2 was no prior MS metabolomics (Figure  6 ), there was one mother with MS metabolomics in both datasets from different pregnancies.
Using the BiB metabolomic data, including a summary of published, ongoing and future research using these data The current BiB metabolite data have been quantified on blood samples collected during pregnancy, cord blood at birth and in the offspring at 12-and 24-months. These are critical time periods for life-course research and the combination of Figure  6A  shows dataset 1 which includes 1,000 pregnancies and infants with MS metabolomics during pregnancy (26-28 weeks' gestation (dataset 1a)) and in cord blood (dataset 1b). Figure  6B  shows dataset 2 which includes 2,000 pregnancies (26-28 weeks' gestation) with MS metabolomics within a case-cohort design. Abbreviations: MS, mass spectrometry; BiB, Born in Bradford; GWAS, genome wide association study; EDTA, ethylenediaminetetraacetic acid; HDP, hypertensive disorders of pregnancy; GD, gestational diabetes; GHT, gestational hypertension; PE, pre-eclampsia, PTB, preterm birth; CA, congenital anomaly; SB, still birth.
these data with large amounts of genomic, epigenomic, social and health data makes BiB a platform which provides scope for unique research opportunities. Issues for data users 1. Batch effects: The quantified NMR metabolites that have been measured in BiB are represented in clinically meaningful units, so can be compared to results from other studies. By contrast the Metabolon MS metabolites are quantified in relative abundance i. e. in relation to other quantified MS measurements that were run on the same day. The MS Dataset 1 and Dataset 2 were obtained ~2 years apart and have been normalized to different references, so are not directly comparable. For example, the value of a specific metabolite from a maternal pregnancy sample in Dataset 1 compared to the same metabolite in Dataset 2 may differ because they are from different batches.
Because of the different selection process for the two datasets (Dataset 1 is paired pregnancyoffspring cord blood samples and Dataset 2 has a case-cohort sampling frame) it is not possible to normalize them to the same reference. We recommend running analyses separately in each of the two datasets and comparing results, then meta-analyse if appropriate. In principal components analyses, 37 of the 1,000 women with a pregnancy sample in  a This column comprises of the full case-cohort dataset of 2,000 pregnancies. This includes 801 selected cases and the 1,199 random cohort. b This column includes only the 1,199 random cohort to compare to the full case-cohort with the selected cases. Data are means ± SD or n (%) unless stated. Abbreviations: BiB, Born in Bradford; BMI, body mass index; kg, kilogram; IMD, index of multiple deprivation (taken from 2010 national quintiles).
There were nine ethnic groups, of which White British and Pakistani were the main homogeneous groups. The 'Other' ethnicity category comprises: White Other, Mixed-White and Black, Mixed-White and South Asian, Black, Indian, Bangladeshi or Other ethnicity. Dataset 1 of MS data had notably different values to those in the remaining 963 women, which appeared to be a batch effect (see Figure in Extended data  11  ). This is a new finding and in previous analyses using these data we have not treated these 37 women differently. However, for future analyses we would recommend researchers consider running analyses with all women and in a sensitivity analysis with these 37 women removed.
Potential causal effects in these studies will be explored where possible by replication, the use of Mendelian randomization (MR) and triangulation with other types of data and study designs. In ongoing work, we are using data from both MS datasets to evaluate whether MS-derived metabolomics are better predictors of gestational diabetes, hypertensive disorders of pregnancy, small and large for gestational age and preterm birth, than risk factors alone (with external validation being undertaken in the POPs cohort). By combining both NMR and MS data, we are exploring the relationships between maternal pregnancy metabolites and their offspring cord blood metabolites. BiB also contributes to metabolomic studies that are being undertaken by large collaborative efforts. This includes the European H2020 funded LifeCycle project  20  , in which we are exploring exposure to maternal hypertensive disorder of pregnancy, gestational diabetes, small and large for gestational age and preterm delivery on offspring subsequent metabolic profile.