Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis

In this article, a dataset from a collaborative nontarget screening trial organised by the NORMAN Association is used to review the state-of-the-art and discuss future perspectives of non-target screening using high-resolution mass spectrometry in water analysis. A total of 18 institutes from 12 European countries analysed an extract of the same water sample collected from the River Danube with either one or both of liquid and gas chromatography coupled with mass spectrometry detection. This article focuses mainly on the use of high resolution screening techniques with target, suspect, and non-target workflows to identify substances in environmental samples. Specific examples are given to emphasise major challenges including isobaric and co-eluting substances, dependence on target and suspect lists, formula assignment, the use of retention information, and the confidence of identification. Approaches and methods applicable to unit resolution data are also discussed. Although most substances were identified using high resolution data with target and suspect-screening approaches, some participants proposed tentative non-target identifications. This comprehensive dataset revealed that nontarget analytical techniques are already substantially harmonised between the participants, but the data processing remains time-consuming. Although the objective of a Bfullyautomated identification workflow^ remains elusive in the short term, important steps in this direction have been taken, exemplified by the growing popularity of suspect screening approaches. Major recommendations to improve non-target screening include better integration and connection of desired features into software packages, the exchange of target and suspect lists, and the contribution of more spectra from standard substances into (openly accessible) databases.This work was supported in part by the SOLUTIONS project, which received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 603437

Health services use among children diagnosed with medium-chain acyl-CoA dehydrogenase deficiency through newborn screening: A cohort study in Ontario, Canada

Background: We describe early health services utilization for children diagnosed with medium-chain acyl-CoA dehydrogenase (MCAD) deficiency through newborn screening in Ontario, Canada, relative to a screen negative comparison cohort. Methods: Eligible children were identified via newborn screening between April 1, 2006 and March 31, 2010. Age-stratified rates of physician encounters, emergency department (ED) visits and inpatient hospitalizations to March 31, 2012 were compared using incidence rate ratios (IRR) and incidence rate differences (IRD). We used negative binomial regression to adjust IRRs for sex, gestational age, birth weight, socioeconomic status and rural/urban residence. Results: Throughout the first few years of life, children with MCAD deficiency (n = 40) experienced statistically significantly higher rates of physician encounters, ED visits, and hospital stays compared with the screen negative cohort. The highest rates of ED visits and hospitalizations in the MCAD deficiency cohort occurred from 6 months to 2 years of age (ED use: 2.1-2.5 visits per child per year; hospitalization: 0.5-0.6 visits per child per year), after which rates gradually declined. Conclusions: This study confirms that young children with MCAD deficiency use health services more frequently than the general population throughout the first few years of life. Rates of service use in this population gradually diminish after 24 months of age

Structural features and kinetic characterization of alanine racemase from Staphylococcus aureus (Mu50)

The tertiary structure and kinetic properties of alanine racemase from Staphylococcus aureus are described and compared to other related alanine racemase structures

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Background: The NORMAN Association (https://www.norman-.network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-.network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https:// zenodo.org/communities/norman-.sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox. epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-.network.com/nds/SLE/)

Scoping review of patient- and family-oriented outcomes and measures for chronic pediatric disease.

Improvements in health care for children with chronic diseases must be informed by research that emphasizes outcomes of importance to patients and families. To support a program of research in the field of rare inborn errors of metabolism (IEM), we conducted a broad scoping review of primary studies that: (i) focused on chronic pediatric diseases similar to IEM in etiology or manifestations and in complexity of management; (ii) reported patient- and/or family-oriented outcomes; and (iii) measured these outcomes using self-administered tools.We developed a comprehensive review protocol and implemented an electronic search strategy to identify relevant citations in Medline, EMBASE, DARE and Cochrane. Two reviewers applied pre-specified criteria to titles/abstracts using a liberal accelerated approach. Articles eligible for full-text review were screened by two independent reviewers with discrepancies resolved by consensus. One researcher abstracted data on study characteristics, patient- and family-oriented outcomes, and self-administered measures. Data were validated by a second researcher.4,118 citations were screened with 304 articles included. Across all included reports, the most-represented diseases were diabetes (35%), cerebral palsy (23%) and epilepsy (18%). We identified 43 unique patient- and family-oriented outcomes from among five emergent domains, with mental health outcomes appearing most frequently. The studies reported the use of 405 independent self-administered measures of these outcomes.Patient- and family-oriented research investigating chronic pediatric diseases emphasizes mental health and appears to be relatively well-developed in the diabetes literature. Future research can build on this foundation while identifying additional outcomes that are priorities for patients and families

The NORMAN Suspect List Exchange (NORMAN-SLE): Facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/)

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.The NORMAN-SLE project has received funding from the NORMAN Association via its joint proposal of activities. HMT and ELS are supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. ELS, PC, SEH, HPHA, ZW acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036756, project ZeroPM: Zero pollution of persistent, mobile substances. The work of EEB, TC, QL, BAS, PAT, and JZ was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). JOB is the recipient of an NHMRC Emerging Leadership Fellowship (EL1 2009209). KVT and JOB acknowledge the support of the Australian Research Council (DP190102476). The Queensland Alliance for Environmental Health Sciences, The University of Queensland, gratefully acknowledges the financial support of the Queensland Department of Health. NR is supported by a Miguel Servet contract (CP19/00060) from the Instituto de Salud Carlos III, co-financed by the European Union through Fondo Europeo de Desarrollo Regional (FEDER). MM and TR gratefully acknowledge financial support by the German Ministry for Education and Research (BMBF, Bonn) through the project “Persistente mobile organische Chemikalien in der aquatischen Umwelt (PROTECT)” (FKz: 02WRS1495 A/B/E). LiB acknowledges funding through a Research Foundation Flanders (FWO) fellowship (11G1821N). JAP and JMcL acknowledge financial support from the NIH for CCSCompendium (S50 CCSCOMPEND) via grants NIH NIGMS R01GM092218 and NIH NCI 1R03CA222452-01, as well as the Vanderbilt Chemical Biology Interface training program (5T32GM065086-16), plus use of resources of the Center for Innovative Technology (CIT) at Vanderbilt University. TJ was (partly) supported by the Dutch Research Council (NWO), project number 15747. UFZ (TS, MaK, WB) received funding from SOLUTIONS project (European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 603437). TS, MaK, WB, JPA, RCHV, JJV, JeM and MHL acknowledge HBM4EU (European Union’s Horizon 2020 research and innovation programme under the grant agreement no. 733032). TS acknowledges funding from NFDI4Chem—Chemistry Consortium in the NFDI (supported by the DFG under project number 441958208). TS, MaK, WB and EMLJ acknowledge NaToxAq (European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 722493). S36 and S63 (HPHA, SEH, MN, IS) were funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Project No. (FKZ) 3716 67 416 0, updates to S36 (HPHA, SEH, MN, IS) by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) Project No. (FKZ) 3719 65 408 0. MiK acknowledges financial support from the EU Cohesion Funds within the project Monitoring and assessment of water body status (No. 310011A366 Phase III). The work related to S60 and S82 was funded by the Swiss Federal Office for the Environment (FOEN), KK and JH acknowledge the input of Kathrin Fenner’s group (Eawag) in compiling transformation products from European pesticides registration dossiers. DSW and YDF were supported by the Canadian Institutes of Health Research and Genome Canada. The work related to S49, S48 and S77 was funded by the MAVA foundation; for S77 also the Valery Foundation (KG, JaM, BG). DML acknowledges National Science Foundation Grant RUI-1306074. YL acknowledges the National Natural Science Foundation of China (Grant No. 22193051 and 21906177), and the Chinese Postdoctoral Science Foundation (Grant No. 2019M650863). WLC acknowledges research project 108C002871 supported by the Environmental Protection Administration, Executive Yuan, R.O.C. Taiwan (Taiwan EPA). JG acknowledges funding from the Swiss Federal Office for the Environment. AJW was funded by the U.S. Environmental Protection Agency. LuB, AC and FH acknowledge the financial support of the Generalitat Valenciana (Research Group of Excellence, Prometeo 2019/040). KN (S89) acknowledges the PhD fellowship through Marie Skłodowska-Curie grant agreement No. 859891 (MSCA-ETN). Exposome-Explorer (S34) was funded by the European Commission projects EXPOsOMICS FP7-KBBE-2012 [308610]; NutriTech FP7-KBBE-2011-5 [289511]; Joint Programming Initiative FOODBALL 2014–17. CP acknowledges grant RYC2020-028901-I funded by MCIN/AEI/1.0.13039/501100011033 and “ESF investing in your future”, and August T Larsson Guest Researcher Programme from the Swedish University of Agricultural Sciences. The work of ML, MaSe, SG, TL and WS creating and filling the STOFF-IDENT database (S2) mostly sponsored by the German Federal Ministry of Education and Research within the RiSKWa program (funding codes 02WRS1273 and 02WRS1354). XT acknowledges The National Food Institute, Technical University of Denmark. MaSch acknowledges funding by the RECETOX research infrastructure (the Czech Ministry of Education, Youth and Sports, LM2018121), the CETOCOEN PLUS project (CZ.02.1.01/0.0/0.0/15_003/0000469), and the CETOCOEN EXCELLENCE Teaming 2 project supported by the Czech ministry of Education, Youth and Sports (No CZ.02.1.01/0.0/0.0/17_043/0009632).Peer reviewe

Alpha-Actinin regulates nuclear actin bundling and nuclear size in early G1

Nuclear actin and its biological relevance raised much interest in the past few years. Although its existence was initially discussed controversially, more recent data provided insights into its functions and address stimuli as well as dynamics of nuclear actin filaments. Hence, our group recently showed that nuclear volume expansion in early G1 of mammalian cells required a network of transient and dynamic F-actin inside the daughter nuclei. However, only few regulatory pathways in nuclear F-actin formation were identified, while higher organization of actin filaments remained mostly uninvestigated. As such, the roles of actin crosslinking proteins were less well explored, but members of the spectrin repeat family were proposed to have nuclear functions. For instance, nucleocytoplasmic shuttling of the actin-bundling protein Alpha actinin-4 was associated with invasive cancer phenotypes. We therefore decided to investigate non-muscle Alpha actinins and their roles in early G1 nuclei. We initially confirmed cytoplasmic and nuclear localization of Alpha actinin-4 in interphase and early G1 cells and its interaction with nuclear F-actin by immunostaining and phalloidin pulldown experiments. Subcellular fractionations and subsequent Co-immunoprecipitations revealed the presence of Alpha actinin-1 SNAP Flag in the nuclear compartment. Imaging of histone 2B mCherry expressing cells during early G1 and following 3D reconstructions allowed for nuclear volume analysis and revealed that Alpha actinin-4, but not Alpha actinin-1 was required for proper nuclear volume expansion. We further visualized nuclear F-actin (bundles) in fixed postmitotic cells by super-resolution microscopy. Expression of a nuclear targeted dominant negative mutant of Alpha actinin-4 exhibited a significant reduction of phalloidin-AlexaFluor647 localizations per nucleus compared to the wild-type construct. These nuclei further represented fewer actin filament bundles with reduced widths, suggesting that Alpha actinin-4 is a key regulator of nuclear F-actin bundling and proper nuclear volume expansion in early G1. Further investigations revealed an additional involvement of nuclear Alpha actinin-4 in other cellular processes such as proliferation. Together, this work provides information about crucial functions of Alpha actinin-4 in the nuclear compartment of postmitotic mammalian cells and might therefore aid future investigations into its role for tumorigenesis and metastasis

Anterior Pituitary Volume in Patients with Transfusion Dependent Anemias: Volumetric Approaches and Relation to Pituitary MRI‑R2

Purpose!#!Anterior pituitary iron overload and volume shrinkage is common in patients with transfusion-dependent anemia and associated with growth retardation and hypogonadotropic hypogonadism. We investigated the accuracy of different MRI-based pituitary volumetric approaches and the relationship between pituitary volume and MRI-R2, particularly with respect to growth and hypogonadism.!##!Methods!#!In 43 patients with transfusion-dependent anemia (12-38 years) and 32 healthy controls (12-72 years), anterior pituitary volume was measured by a sagittal T1 GRE 3D sequence at 1.5T and analyzed by 3D semi-automated threshold volumetry (3D-volumetry). This reference method was compared with planimetric 2D-volumetry, approximate volume calculations, and pituitary height. Using a multiple SE sequence, pituitary iron as MRI-R2 was assessed by fitting proton signal intensities to echo times. Growth and hypogonadism were obtained from height percentile tables and patients' medical charts. From body surface area and age adjusted anterior pituitary volumes of controls, Z‑scores were calculated for all subjects. Separation of controls and patients with respect to Z and pituitary R2 was performed by bivariate linear discriminant analysis.!##!Results!#!Tuned 2D volumes showed highest agreement with reference 3D-volumes (bias -4.8%; 95% CI:-8.8%|-0.7%). A linear discriminant equation of Z = -17.8 + 1.45 · R2 revealed optimum threshold sensitivity and specificity of 65% and 100% for discrimination of patients from controls, respectively. Of correctly classified patients 71% and 75% showed hypogonadism and growth retardation, respectively.!##!Conclusion!#!Accurate assessment of anterior pituitary size requires 3D or precise 2D volumetry, with shorter analysis time for the latter. Anterior pituitary volume Z‑scores and R2 allow for the identification of patients at risk of pituitary dysfunction