56 research outputs found

    Conifer Responses to a Stylet-Feeding Invasive Herbivore and Induction with Methyl Jasmonate: Impact on the Expression of Induced Defenses and a Native Folivore

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    Trees attacked by multiple herbivores need to defend themselves against dynamic biotic challenges; appropriate responses to one stressor can elicit hormonal responses that are antagonistic to another. Hemlock (Tsuga canadensis) infestation by hemlock woolly adelgid (HWA; Adelges tsugae) results in the accumulation of the defensive hormone salicylic acid. We explored the potential for HWA infestation to interfere with anti‐folivore‐induced defence signalling and its implications for a native folivore (hemlock looper; Lambdina fiscellaria). Hemlocks were infested with HWA and/or sprayed with methyl jasmonate; foliar defences were analyzed and foliage quality for looper larvae was assessed. Both treatments activated foliar defensive traits, including a HWA‐mediated increase in peroxidase activity and an accumulation of cell wall‐bound phenolics and lignin, as well as a methyl jasmonate‐mediated increase in lipoxygenase activity. The two treatments had an additive effect on other defensive traits and both treatments negatively affected looper performance. These results suggest that salicylic acid and jasmonic acid are not strictly antagonistic in conifers and that both have a role in anti‐folivore defence signalling. The present study illustrates the need for a better understanding of hormone signalling, cross‐talk and induced responses in conifers

    The Iowa Homemaker vol.16, no.3

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    Cover by Dorothy Coe The Way to His Heart by Win Hanssen, page 2 “Don’ts” for the Rushee by Stella Mae Brinkman, page 3 Sally Says, “Swinging Shoulders – Swirling Skirts” by Katherine Hoffman, page 4 Travel With Richard Halliburton by Emma Jean Scudder, page 6 Have a Treasure-Hunt Spread by Louise Peterson, page 7 Vocational Possibilitites, page 8 Our 1936 Graduates at Work by Gay Starrak, page 9 Behind Bright Jackets, page 10 Is Your Room “You”? by Betty Shoemaker, page 11 What’s New in Home Economics, page 12 Do You Keep a Diary?, page 15 Books to Read, page 16 Catt Gown Is Historic, page 18 Dr. Nickell at Iowa State, page 18 Facts on Child Health, page 20 Want to Remember Names?, page 22 Vitamin A Deficiency Test, page 2

    Facilitation between invasive herbivores: hemlock woolly adelgid increases gypsy moth preference for and performance on eastern hemlock

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    Interactions between invertebrate herbivores with different feeding modes are common on long‐lived woody plants. In cases where one herbivore facilitates the success of another, the consequences for their shared host plant may be severe. Eastern hemlock (Tsuga canadensis), a canopy‐dominant conifer native to the eastern U.S., is currently threatened with extirpation by the invasive stylet‐feeding hemlock woolly adelgid (Adelges tsugae). The effect of adelgid on invasive hemlock‐feeding folivores remains unknown. This study evaluated the impact of feeding by hemlock woolly adelgid on gypsy moth (Lymantria dispar) larval preference for, and performance on, eastern hemlock. To assess preference, 245 field‐grown hemlocks were surveyed for gypsy moth herbivory damage and laboratory paired‐choice bioassays were conducted. To assess performance, gypsy moth larvae were reared to pupation on adelgid‐infested or uninfested hemlock foliage, and pupal weight, proportional weight gain, and larval period were analysed. Adelgid‐infested hemlocks experienced more gypsy moth herbivory than did uninfested control trees, and laboratory tests confirmed that gypsy moth larvae preferentially feed on adelgid‐infested hemlock foliage. Gypsy moth larvae reared to pupation on adelgid‐infested foliage gained more weight than larvae reared on uninfested control foliage. These results suggest that the synergistic effect of adelgid and gypsy moth poses an additional threat to eastern hemlock that may increase extirpation risk and ecological impact throughout most of its range

    Bezielle Selectively Targets Mitochondria of Cancer Cells to Inhibit Glycolysis and OXPHOS

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    Bezielle (BZL101) is a candidate oral drug that has shown promising efficacy and excellent safety in the early phase clinical trials for advanced breast cancer. Bezielle is an aqueous extract from the herb Scutellaria barbata. We have reported previously that Bezielle was selectively cytotoxic to cancer cells while sparing non-transformed cells. In tumor, but not in non-transformed cells, Bezielle induced generation of ROS and severe DNA damage followed by hyperactivation of PARP, depletion of the cellular ATP and NAD, and inhibition of glycolysis. We show here that tumor cells' mitochondria are the primary source of reactive oxygen species induced by Bezielle. Treatment with Bezielle induces progressively higher levels of mitochondrial superoxide as well as peroxide-type ROS. Inhibition of mitochondrial respiration prevents generation of both types of ROS and protects cells from Bezielle-induced death. In addition to glycolysis, Bezielle inhibits oxidative phosphorylation in tumor cells and depletes mitochondrial reserve capacity depriving cells of the ability to produce ATP. Tumor cells lacking functional mitochondria maintain glycolytic activity in presence of Bezielle thus supporting the hypothesis that mitochondria are the primary target of Bezielle. The metabolic effects of Bezielle towards normal cells are not significant, in agreement with the low levels of oxidative damage that Bezielle inflicts on them. Bezielle is therefore a drug that selectively targets cancer cell mitochondria, and is distinguished from other such drugs by its ability to induce not only inhibition of OXPHOS but also of glycolysis. This study provides a better understanding of the mechanism of Bezielle's cytotoxicity, and the basis of its selectivity towards cancer cells

    Correlates of protection against symptomatic and asymptomatic SARS-CoV-2 infection

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    The global supply of COVID-19 vaccines remains limited. An understanding of the immune response that is predictive of protection could facilitate rapid licensure of new vaccines. Data from a randomized efficacy trial of the ChAdOx1 nCoV-19 (AZD1222) vaccine in the United Kingdom was analyzed to determine the antibody levels associated with protection against SARS-CoV-2. Binding and neutralizing antibodies at 28 days after the second dose were measured in infected and noninfected vaccine recipients. Higher levels of all immune markers were correlated with a reduced risk of symptomatic infection. A vaccine efficacy of 80% against symptomatic infection with majority Alpha (B.1.1.7) variant of SARS-CoV-2 was achieved with 264 (95% CI: 108, 806) binding antibody units (BAU)/ml: and 506 (95% CI: 135, not computed (beyond data range) (NC)) BAU/ml for anti-spike and anti-RBD antibodies, and 26 (95% CI: NC, NC) international unit (IU)/ml and 247 (95% CI: 101, NC) normalized neutralization titers (NF) for pseudovirus and live-virus neutralization, respectively. Immune markers were not correlated with asymptomatic infections at the 5% significance level. These data can be used to bridge to new populations using validated assays, and allow extrapolation of efficacy estimates to new COVID-19 vaccines

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

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    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/)

    Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium

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    BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia

    Towards Equitable, Diverse, and Inclusive science collaborations: The Multimessenger Diversity Network

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

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    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

    Get PDF
    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 SkƂodowska-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
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