dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion and future directions for metabolomic analyses in BiB In this data note we have described multiple datasets with NMR and MS metabolomic measures in the BiB cohort. The wealth of metabolomics data available in BiB provides opportunities for addressing a range of research questions. In this section, we discuss the strengths and limitations of the data, together with some of our insights for using these data. We also provide information on plans for future measurements of metabolomics in BiB. A key strength of these datasets is that they are based within a cohort that has very detailed information on 13,776 pregnancies. This includes detailed socioeconomic, education, cognitive, and mental and physical health data. We have OGTT results and fasting pregnancy blood samples on most (83%) of the mothers, genomics (genome wide and sequence) data and epigenomics data in maternal pregnancy and offspring cord blood.
It provides considerably more information than clinical chemistry measures that are conventionally measured in cohorts (e. g. glucose, total cholesterol, LDLc, HDLc and triglycerides) and at not much more cost (~£20 per sample). As a result, we have been able to obtain these data on large numbers of women in pregnancy, offspring cord blood and in samples taken in offspring at 12-and 24-months assessments. By contrast, the MS data covers more of the metabolome, including being able to assess energy metabolism (which might be important in pregnancy) and markers of medications such as paracetamol. However, it is more expensive (~£80-£200, depending on how many samples are assayed at a time). By having access to both datasets here, we can have broader coverage of the metabolome  21. There are potential uses for both platforms -ranging from disease prediction to causal analyses using methods such as MR  22.
Both platforms have been used in previous GWAS of metabolites  23. As such, BiB could be used to explore whether genetic instruments from GWAS can be related to NMR or MS metabolites in pregnancy. Access to this unique metabolomic data is a big advantage in BiB. However, we have been unable to validate findings in external cohorts. The work described above cannot be replicated because we cannot find other independent studies with relevant data  17. We hope that this data note will encourage other studies to collect similar data in pregnancy, offspring cord blood, and in mothers and offspring postnatally throughout their life-course. There are some additional important limitations of the data to consider. The impact of these limitations will depend on the research question. All the metabolomics datasets were collected on subsamples ranging from 11,480 with maternal pregnancy NMR samples (83% of the eligible 13,776 participants) to 1,000 (7%) with MS cord blood samples.
Smaller sample sizes may be statistically inefficient in some analyses and the selection processes (Figure  4  and Figure  6 ) may result in selection bias in some analyses. It is notable and provides some reassurance that, even for the smaller samples, distributions of most characteristics are similar between participant groups with different types of metabolomics at different time points and the whole cohort (Table  2  and Table  3 ). As Metabolon MS data have been collected only on White British and Pakistani women it cannot be assumed that analyses with these data would generalize to other ethnic groups. BiB cohort participants were largely recruited at the OGTT (with a small number recruited after that). This was opportunistic as we had no funding for initiating the cohort. After consultation with the community and health care providers, we established that this would be a suitable time to obtain consent, interview pregnant women and collect a fasting blood sample for research.
However, it means that we are likely to have missed women who did not attend the OGTT and were not captured later in pregnancy or at delivery, and those who delivered pre-term before they attended their OGTT. We have previously compared BiB participants to non-BiB births occurring between 2007-2011 8. Summary data from obstetric and delivery records were obtained for 11,761 non-BiB births, which would include some who moved to Bradford shortly before delivery (and would not have been eligible to recruit). The comparison showed a small number of differences. BiB participants were less likely to include younger mothers (age 20-24 years) and had a higher proportion of South Asian and nulliparous mothers. There were differences in gestational age and preterm delivery that reflected recruiting BiB participants relatively late in pregnancy  8.
This selection on gestational age may introduce selection bias in some BiB analyses, including those using the metabolomics data described here. A limitation is that BiB only has pregnancy metabolomics at a single time point and does not have pre-pregnancy measurements. Previous research suggests metabolites change upon becoming pregnant and then revert to pre-pregnancy levels  5  and that they change during pregnancy  24. Earlier measures would be valuable for prediction of future adverse outcomes to enable earlier antenatal monitoring and intervention. This data note has focused on metabolomics data that have been quantified by high throughput commercial platforms (Nightingale Health© NMR and Metabolon MS). On a small subsample of BiB participants (N = 199) NMR urine and serum MS blood metabolites have been quantified at Imperial College, London, as part of the HELIX collaboration.
HELIX aims to identify the human exposome in pregnancy and childhood. Metabolite measurements were undertaken alongside similar subsamples from five other cohorts (total N = 1,192). In all six cohorts, samples were from children aged between 6-11 years (BiB participants were mean age 6. 6 years). 44 urine metabolites (24 semi-quantified) and 188 serum (56 fully quantified) metabolites were measured. We have not described these metabolomics datasets here as the assays are unique to a small subgroup of BiB participants and any research on these participants is best done together with the other HELIX cohort subgroups on whom the same metabolomic data obtained at the same time and using the same methods is available. Further information about the samples and methods used can be found elsewhere  25.
Up until March 2020, we were undertaking a follow-up of BiB parents and offspring, including collecting further blood samples with funding available to complete the NMR analyses on offspring and parent serum/plasma collected at this follow-up. However, that follow-up stopped on the 16 th March 2020 when restrictions on normal life due to the COVID-19 pandemic began in the UK. At the time of submitting this paper we do not know when face-to-face data collection will be possible to start again and what the best plans would be for further blood sample collection. At the relevant time we will discuss different potential scenarios for completing that planned follow-up with our scientific advisory groups. Whatever the decision, we should have some participants with serum/plasma NMR measures collected ~8-9 years after birth.
Cord blood NMR -Dataset 2 N = 7,980 children. Single timepoint using cord blood, EDTA plasma. 3 Infants NMR (aged 12 or 24 months) -Dataset 108 at either 12-or 24-months using serum samples. N = 1,690 at 12 months. N = 1,536 at 24 months. N = 1,118 at both timepoints.
Once you have formulated your request please complete the 'Expression of Interest' form available here and email the BiB research team (borninbradford@ bthft. nhs. uk). • If your request is approved, we will ask you to sign a collaboration agreement; if your request involves biological samples, we will ask you to complete a material transfer agreement. Extended data Open Science Framework: Metabolomics data in the Born in Bradford cohort. https://doi. org/10. 17605/OSF. IO/YST7N 11. • MS_Metabolite_Details. xlsx (Lists the names and details of all metabolites assessed by the Metabolon platform in the BiB MS dataset 1a (sheet 1) and BiB MS dataset 2 (sheet 2). Data are available under the terms of the Creative Commons Attribution 4. 0 International license (CC-BY 4. 0).
Acknowledgements Our thanks to all the children (and parents), teachers and school staff who were involved in the research, and staff at the  Bristol Bioresource Laboratory  who manage the BiB biobank, including cataloguing and shipping samples (e. g. to Metabolon) and at the  Bristol Metabolomics Research  who ran NMR analyses. Thanks also to the  Born in Bradford (BiB) Research Assistants  for data collection. Born in Bradford is only possible because of the enthusiasm and commitment of the  Children and Parents in BiB. We are grateful to all the participants, practitioners and researchers who have made Born in Bradford happen.
Grant information: Core funding for BiB has been provided by the  Wellcome Trust  [101597], a joint grant from the  UK Medical Research Council (MRC)  and  UK Economic and Social Science Research Council (ESRC)  [ MR/N024397/1 ], the  British Heart Foundation  [ CS/16/4/32482 ] and the  National Institute for Health Research ARC Yorkshire and Humber  [ NIHR200166 ]. Funding for the metabolomics analyses has been provided by the  US National Institutes of Health  [ R01 DK10324 ], the  European Research Council (ERC)  under the European Union's  Seventh Framework Programme  [FP7/2007-2013] /  ERC  grant agreement no  669545  and the  MRC  via the  MRC Integrative Epidemiology Unit Programme  to  D. A. L  [ MC_UU_00011/6 ]. K. T. is supported by a  British Heart Foundation Doctoral Training Program  [ FS/17/60/33474 ].
N. M. PhD studentship is funded by the  National Institute for Health Research (NIHR) Biomedical Centre at the University Hospitals Bristol NHS Foundation Trust  and the  University of Bristol. K. T. , N. M. , N. J. G, K. B. and D. A. L. work in a unit that is supported by the  University of Bristol and UK Medical Research Council  [ MC_UU_00011/6 ]. D. A. L is a  NIHR Senior Investigator  [ NF-0616-10102 ]. The  ALL IN sub-study  was supported by the  Wellcome Trust  [ 083521 ]. Funding was also provided by the  National Institute for Health Research (NIHR)  under its Collaboration for  Applied Health Research and Care (CLAHRC)  for Yorkshire and Humber.
2 3 N = 2 , 32 Cord blood NMR -Dataset 2 N = 7,980 children. Single timepoint using cord blood, EDTA plasma. 3 Infants NMR (aged 12 or 24 months) -Dataset 108 at either 12-or 24-months using serum samples. N = 1,690 at 12 months. N = 1,536 at 24 months. N = 1,118 at both timepoints.
• Once you have formulated your request please complete the 'Expression of Interest' form available here and email the BiB research team (borninbradford@ bthft. nhs. uk). • If your request is approved, we will ask you to sign a collaboration agreement; if your request involves biological samples, we will ask you to complete a material transfer agreement. Extended data Open Science Framework: Metabolomics data in the Born in Bradford cohort. https://doi. org/10. 17605/OSF. IO/YST7N 11. • MS_Metabolite_Details. xlsx (Lists the names and details of all metabolites assessed by the Metabolon platform in the BiB MS dataset 1a (sheet 1) and BiB MS dataset 2 (sheet 2). Data are available under the terms of the Creative Commons Attribution 4. 0 International license (CC-BY 4. 0). • NMR_Quality_Report_Cord.
pdf (Summarizing quality observations in the NMR cord blood dataset) • NMR_Quality_Report_Infant. pdf (Summarizing quality observations in the NMR infant dataset) • NMR_Quality_Report_Pregnancy. pdf (Summarizing quality observations in the NMR pregnancy dataset) • MS_Quality_Report_Dataset1. pdf (QC report for MS dataset 1 from Metabolon) • MS_Quality_Report_Dataset2. pdf (QC report for MS dataset 2 from Metabolon) • NMR_Metabolite_Details. xlsx (Lists the names and units of all metabolic traits assessed by the NMR platform).
The NUMEN phases The NUMEN (NUclear Matrix Elements for Neutrinoless double beta decay) project is conceived in the view of a comprehensive study of many candidate systems for 0νββ decay. Moreover, this project promotes and is strictly connected with the upgrade of the INFN-LNS research infrastructure (POT-LNS) and with a specific R&D activity on detectors, materials and instrumentation. NUMEN is structured into four phases: • Phase 1: "The pilot experiment" -In 2013, the 40 Ca( 18 O, 18 Ne) 40 Ar DCE reaction was measured at INFN-LNS together with the competing processes: 40 Ca( 18 O, 18 F) 40 K SCE, 40 Ca( 18 O, 20 Ne) 38 Ar two-proton transfer and 40 Ca( 18 O, 16 O) 42 Ca two-neutron transfer  [5]. This work showed for the first time high resolution and statistically significant experimental data on DCE reactions in an wide range of transferred momenta.
Methods We analyzed retrospectively over an 8-year period (May 2005-July 2013) clinical and radiological data from a prospectively acquired database for consecutive HHT patients compared with control patients. All patients provided verbal informed consent. Parental consent was obtained in minor patients. The study protocol was identical for all patients. Patients with a CT exam in another radiological center were excluded. The study was approved by our local Ethics Committee (Comitede Protection des Personnes-Ile de France) as an observational retrospective analysis.
A nonionic contrast material (Iobitridol 300, Xenetix, Guerbet1 or Iohexol 300, Omnipaque, GE Healthcare SAS1) was injected into the antecubital vein through a 16-18 gauge needle. We used an automatic injector, with a flow rate of 4-5 mL/sec, and a maximum volume of 140mL. Image evaluation. Acquired data were transferred to a dedicated PACS reading system and reconstruction workstation (Carestream Health Vue PACS1). Multiplanar reconstructions (MPR) and Maximum Intensity Projections (MIP) images were obtained. All exams were read by two experienced senior radiologists, with at least 5 and 20 years of experience with HHT, respectively. A consensual interpretation was obtained in all cases.
Data collection The splenic artery aneurysm was defined as a focal dilation in its diameter of > 50% compared to the normal vessel diameter. The vascular analysis consisted in detection, enumeration and sizing of SAA. We measured the maximal transverse diameter of the aneurysmal sac in fusiform aneurysms and the largest diameter of the aneurysmal sac in sacciform aneurysms. In case of multiple SAA, the measurements of the two largest aneurysms were reported. Three locations of aneurysms were distinguished: intra-parenchymal aneurysm, truncular aneurysm defined as SAA located from the origin of the splenic artery to the first division of the splenic artery and hilar SAA defined as located from the first division of splenic branches to the splenic parenchyma. Multiple locations were defined as the association of two or more of the previously described locations.
0001). In HHT patients, SAA were significantly more frequent in case of pancreatic involvement (39. 1% vs 17. 2%, p = 0. 001). However, there was no anatomic contiguity between the pancreatic telangiectasia and the SAA. Tables  4  and 5  show CV risk factors and pregnancy in HHT patients and controls, with or without SAA. Unlike other characteristics, data concerning CV risk factors and pregnancy were obtained in 161 HHT patients and 77 controls. There was no statistical difference in terms of hypertension, smokers and dyslipidemia between HHT and controls. Diabetes and familial history of CVD were found to be significantly lower in HHT compared to controls. The CV risk factors were not statistically different in patients with or without SAA in both groups. We found significantly more SAA in women with multiple pregnancies in the HHT population (Fig  3 , 67.
However, our study has some limitations. Only some patients screened for HHT had a CT scan in our center. Only complete scans with arterial time and portal time were included, and only CT scans of good imaging quality were selected. This could represent a selection bias. We adjusted our data on gender and age, to obtain two homogeneous and comparable groups. This led to a reduction in the size of the two groups, and therefore a loss of power. Nevertheless, the number of patients remained high (186 in each arm) and we were able to demonstrate a significant increase in SAA in HHT patients. We did not collect prospectively arteriosclerosis risk factors (except age and gender) and analyze the parity or the number of pregnancies in women prospectively, but we obtained the information retrospectively and therefore, some data are missing, particularly in the control group.
Antimicrobial susceptibility testing Antibiotic susceptibility tests and interpretations for the bacterial isolates were carried out by VITEK2 automated system (bioMerieux, Durham, North Carolina). Antibiotic resistance data were extracted from the hospital information system using software. The antimicrobial agents tested were as per Clinical and Laboratory Standards Institutes (CLSI) guidelines (M100-edition 28th)  12  and The European Committee on Antimicrobial Susceptibility Testing (EUCAST) rules for each isolate. Organisms resistant to more than three classes of drugs were considered as Multi Drug Resistant.
All data will be kept confidential and will be stored in pseudonymised form. The patient has the right to withdraw from the study at any time without providing a reason and without their medical treatment being affected. observation In the observational part, all adult patients undergoing cardiac surgery in the participating centres will be included. Data regarding routine management will be collected, especially the adherence with the different elements of the KDIGO bundle (online supplementary material 2). This includes (1) discontinuation of all nephrotoxic agents, (2) optimisation of volume status and haemodynamics (target mean arterial pressure (MAP) ≥65 mm Hg (not fulfilled if MAP is <65 mm Hg and no treatment is initiated to achieve this goal), (3) functional haemodynamic monitoring (including echocardiography, pulse contour cardiac output or pulmonary artery catheter), (4) close monitoring of serum creatinine every 12 hours and urine output hourly, (5) avoidance of hyperglycaemia (blood glucose levels ≤150 mg/dL or ≤8.
Open access statistical analysis The study is designed to examine the feasibility of the trial protocol in a multicentre setting (as previously described). In the observational study, we will evaluate whether the different elements of the KDIGO guidelines are already implemented in routine clinical practice. The primary endpoint of the observational study is the binary indicator whether the CV surgery AKI bundle is completely fulfilled at all times or not. Descriptive data analyses will include the calculation of means, SD and absolute and relative frequencies. No formal statistical hypothesis will be tested. In the interventional trial, beyond descriptive analyses, inferential statistical analyses will be performed. In the primary statistical analysis, the two treatment groups will be pooled together and the compliance rate across all recruited study patients will be estimated along with a twosided 95% CI according to Clopper-Pearson (Fleiss 2003).
8 Acknowledgments SB acknowledges support from the  Office of Naval Research (ONR)  as part of the  Multidisciplinary University Research Initiatives (MURI) Program , under grant number  N00014-16-1-2617  and from the  UF Informatics Institute. SZ wishes to thank the  French ANR  for its support through its flash Covid-19 program -NANODROP grant, the  ERS Advanced Grant TRUFLOW  and the  PRACE network for its Covid-19 Fast Track Call grant  NANODROP on the Irene TGCC. AS acknowledges funding from the  PRIN  project Advanced computations and experiments in turbulent multiphase flow (Project No. 2017RSH3JY ). GA acknowledges support through the  NSF  Grant No. CBET 2029548  and the Clarkson IGNITE Fellowship. LB acknowledges support from the  Smith Family Foundation , the  Massachusetts Institute of Technology (MIT) Policy Lab , the  MIT Reed Fund , and the  Esther and Harold E.
EXPLOITING CARBOXYLATING ENZYMES FOR CO 2 FIXATION IN HETEROTROPHIC ORGANISMS Carboxylating Enzymes as a Key Reaction in Heterotrophic Organisms for CO 2 Fixation In an elegant paper published in 2010, Bar-Even et al. (  2010 ) developed a constrained-based modeling approach that explored all possibilities that could be devised from a repertoire of ∼5,000 known metabolic enzymes reported in the KEGG database (https://www. genome. jp/kegg/pathway. html) to generate carbon fixation pathways that are alternative to the 5 known to date. Criteria used in their modeling were (i) the enzyme's specific activity is equal or superior to that of RuBisCO which is used as the benchmark activity; (ii) a minimal energy cost of the pathway, which corresponds to the cost in NAD(P)H, ferredoxins, FADH 2 , and ATP in the production of one mole of products from CO 2 ; (iii) thermodynamic feasibility of the pathway under a plausible physiological range of metabolites concentrations; (iv) topology of the pathway, which incorporates the number of enzymatic reactions the carbon fixation pathway can make as an independent unit and (v) the compatibility or integration of this synthetic pathway with the endogenous metabolic network.
Statistical methods Data are presented as mean ± half-width of 95% confidence interval. Normality of the data was assessed for each variable with the Shapiro-Wilk test. In case of a failed normality test, the variable was log-transformed. Repeated measures analyses of variance (ANOVA) using linear mixed-effect model fits by a restricted maximum likelihood (REML) method were applied to calculate statistical significances followed by Dunnett or Holm-Sidak post-hoc tests, using a significance level of p < 0. 05, and all p values two-sided.
Acknowledgements The authors thank  Aurélie Baudat ,  Xavier Belin  and  Sylvie Roulet  for their technical assistance in animal handling, surgical preparation and sample processing. The authors thank  Didier Colin ,  Stéphane Germain  and  Frédéric Bois  for their technical support in imaging acquisition. The authors also thank  Matts Wallin  and  Magnus Hallback  for their excellent technical support in the application of the variable pattern.
Using a simple, environment friendly proteome extraction (TOP), we were able to optimize the analysis of clinical samples. Using our TOP method we analyzed a clinical cohort of microsatellite stable (MSS) and unstable (MSI-H) colorectal carcinoma (CRC). We identified a tumor cell specific, STAT1-centered, immune signature expressed by the MSI-H tumor cells. We then showed that long, but not short, exposure to Interferon-g induces a similar signature in vitro. We identified 10 different temporal protein expression patterns, classifying the Interferon-g protein temporal regulation in CRC. Our data sheds light on the changes that tumor cells undergo under long-term immunological pressure in vivo, the importance of STAT proteins in specific biological scenarios. The data generated could help find novel clinical biomarkers and therapeutic approaches.
On average, these tumors display a high mutation rate of 12-40 mutations/Mb  (7). As a result, MSI-H tumors can produce abnormal proteins that might act as neo-antigens and trigger an effective immune response against the tumor  (10). There is an increasing body of evidence that shows a unique and complex interplay between the MSI-H tumor cells and the immune microenvironment. Although much is unknown, it has been shown that MSI-H tumors show an immune active tumor microenvironment with high levels of several immune checkpoint proteins  (11). Recently, the Food and Drug Administration (FDA) granted accelerated approval to Pembrolizumab (Keytruda) for the treatment of MSI-H (MMRD) solid tumors arising from different organs, thus granting the first histology agnostic treatment approval. This was based on data collected from several KEYNOTE clinical trials that enrolled MSI-H cancer patients irrespectively of the tumor origin.