trying...
1850101MCID_676f086ce2ae64a85e05b8fb 39717659 Maier W[author] maier w[Author] maier w[Author] trying2...
trying...
3971765920241224
0166-06161092024DecStudies in mycologyStud MycolKnown from trees and the tropics: new insights into the Fusarium lateritium species complex.403450403-45010.3114/sim.2024.109.06The Fusarium lateritium species complex (FLSC) currently comprises 11 phylogenetic species, including accepted names such as F. lateritium, F. sarcochroum, and F. stilboides, which have mostly been reported in association with citrus and coffee. Many varieties were documented by Wollenweber & Reinking (1935), which is indicative of a wider diversity of species within this group. The lack of type material in some cases, especially for the older names, means that definition by molecular phylogeny is very difficult. In the present study, we examined 179 strains related to F. lateritium from different countries and substrates. Historic reference material, including representative strains from the Wollenweber & Reinking (1935) varieties were included in this study, DNA sequences were generated for comparison, and the morphology correlated with original descriptions to enable the correct application of older names. Strains were characterized by multi-gene phylogenetic analyses based on fragments of the β-tubulin (tub2), calmodulin (CaM), RNA polymerase II second largest subunit (rpb2), and translation elongation factor 1-alpha (tef1) genes, evaluation of morphological characters and host-substrate preferences. The biological species concept was tested by crossings in vitro. Strains previously identified as F. lateritium, F. stilboides, or one of their varieties based on morphology, were found to belong to 16 species in the FLSC, but also to species from six other species complexes (SC), including the F. citricola SC, F. heterosporum SC, F. incarnatum-equiseti SC, F. redolens SC, F. sambucinum SC, and the F. tricinctum SC. Eleven new phylogenetic and two biological species are described in the FLSC, and emended descriptions are provided for four previously described species. An epitype is designated for F. lateritium, and F. lateritium var. longum, a former variety within the FLSC, is lecto- and epitypified, and elevated to species level with a replacement name. Taxonomic novelties: New species: F. aurantii M.M. Costa, Sand.-Den. & Crous, F. chlamydocopiosum M.M. Costa, Sand.-Den. & Crous, F. citri-sinensis L. Zhao & J.X. Deng, F. coffeibaccae M.M. Costa, L.H. Pfenning, Sand.-Den. & Crous, F. crocatum M.M. Costa, Sand.-Den. & Crous, F. malawiense M.M. Costa, Sand.-Den. & Crous, F. microcyclum M.M. Costa, Sand.-Den. & Crous, F. oliniae M.M. Costa, Sand.-Den. & Crous; F. rufum M.M. Costa, Sand.-Den. & Crous, F. stramineum M.M. Costa, Sand.-Den. & Crous, F. velutinum M.M. Costa, Sand.-Den. & Crous, F. verruculosum M.M. Costa, Sand.-Den. & Crous; Replacement name: F. hanswilhelmii M.M. Costa, Sand.-Den. & Crous; Epitype (basionym): F. lateritium Nees, F. lateritium var. longum Wollenw.; Lectotype (basionym): F. lateritium var. longum Wollenw. Citation: Costa MM, Sandoval-Denis M, Moreira GM, Kandemir H, Kermode A, Buddie AG, Ryan MJ, Becker Y, Yurkov A, Maier W, Groenewald JZ, Pfenning LH, Crous PW (2024). Known from trees and the tropics: new insights into the Fusarium lateritium species complex. Studies in Mycology 109: 403-450. doi: 10.3114/sim.2024.109.06.© 2024 Westerdijk Fungal Biodiversity Institute.CostaM MMMWesterdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands.Sandoval-DenisMMWesterdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands.MoreiraG MGMDepartment of Plant Pathology, Universidade Federal de Lavras, 37200-900, Lavras MG, Brazil.KandemirHHWesterdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands.KermodeAACAB International (CABI), Bakeham Lane, TW20 9TY Egham, Surrey, United Kingdom.BuddieA GAGCAB International (CABI), Bakeham Lane, TW20 9TY Egham, Surrey, United Kingdom.RyanM JMJCAB International (CABI), Bakeham Lane, TW20 9TY Egham, Surrey, United Kingdom.BeckerYYInstitute for Epidemiology and Pathogen Diagnostics, Julius Kühn Institute (JKI), Federal Research Centre for Cultivated Plants, Messeweg 11-12, 38104 Braunschweig, Germany.YurkovAADepartment of Bioresources for Bioeconomy and Health Research, Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Inhoffenstraße 7B, 38124 Braunschweig, Germany.MaierWWInstitute for Epidemiology and Pathogen Diagnostics, Julius Kühn Institute (JKI), Federal Research Centre for Cultivated Plants, Messeweg 11-12, 38104 Braunschweig, Germany.GroenewaldJ ZJZWesterdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands.PfenningL HLHDepartment of Plant Pathology, Universidade Federal de Lavras, 37200-900, Lavras MG, Brazil.CrousP WPWWesterdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands.Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa.Microbiology, Department of Biology, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands.engJournal Article20240926
NetherlandsStud Mycol84119840166-0616Biological species conceptfungal taxonomymultigene phylogenynew taxaThe authors declare that there is no conflict of interest.202461220248252024122462120241224620202412244482024926ppublish39717659PMC1166342210.3114/sim.2024.109.06Afanide B, Mabadeje SA, Naqvi SHZ. (1976). Gibberella baccata, the perfect state of Fusarium lateritium in Nigeria. Mycologia 68: 1108–1111.Bilaĭ VI. (1955). Fusarii (Biologija i sistematika). Isdatelstvo Akademii Nauk Ukraniskoi SSE, Kiev, Ukraine: (in Russian).Booth C. (1971). The genus Fusarium. Commonwealth Mycological Institute, Kew, Surrey, England, UK.Carbone I, Kohn LM. (1999). A method for designing primer sets for speciation studies in filamentous ascomycetes. Mycologia 91: 553–556.Cavalcanti AD, Santos ACS, Ferro LO. et al. (2020). Fusarium massalimae sp. nov. (F. lateritium species complex) occurs endophytically in leaves of Handroanthus chrysotrichus. Mycological Progress 19: 1133–1142.Costa MM, Saleh AA, Melo MP. et al. (2022). Fusarium mirum sp. nov., intertwining Fusarium madaense and Fusarium andiyazi, pathogens of tropical grasses. Fungal Biology 126: 250–266.35183341Cowger C, Ward TJ, Nilsson K. et al. (2020). Regional and field-specific differences in Fusarium species and mycotoxins associated with blighted North Carolina wheat. International Journal of Food Microbiology 323: 108594.32229393Crous PW, Gams W, Stalpers JA. et al. (2004). MycoBank: an online initiative to launch mycology into the 21st century. Studies in Mycology 50: 19–22.Crous PW, Boers J, Holdom D. et al. (2022). Fungal Planet description sheets: 1383–1435. Persoonia 48: 261–371.PMC1079228838234686Crous PW, Lombard L, Sandoval-Denis M. et al. (2021). Fusarium: more than a node or a foot cell. Studies in Mycology 98: 100116.PMC837952534466168Crous PW, Verkley GJM, Groenewald JZ. et al. (2019). Fungal Biodiversity. Westerdijk Laboratory Manual Series 1. Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands.Dean R, Van Kan JAL, Pretorius ZA. et al. (2012). The top 10 fungal pathogens in molecular plant pathology. Molecular Plant Pathology 13: 414–430.PMC663878422471698Doidge EM. (1938). Some South African fusaria. Bothalia 3: 331–483.Geiser DM, Al-Hatmi A, Aoki T. et al. (2021). Phylogenomic analysis of a 55.1 kb 19-gene dataset resolves a monophyletic Fusarium that includes the Fusarium solani species complex. Phytopathology 111: 1064–1079.33200960Geiser DM, Lewis Ivey ML, Hakiza G. et al. (2005). Gibberella xylarioides (anamorph: Fusarium xylarioides), a causative agent of coffee wilt disease in Africa, is a previously unrecognized member of the G. fujikuroi species complex. Mycologia 97: 191–201.16389971Gerlach W, Nirenberg H. (1982). The genus Fusarium – a pictorial atlas. Mitteilungen aus der Biologischen Bundesanstalt für Land- und Forstwirtschaft Berlin-Dahlem 209: 1–406.Gordon WL. (1952). The occurrence of Fusarium species in Canada. II. Prevalence and taxonomy of Fusarium species in cereal seeds. Canadian Journal of Botany 30: 209–251.Groenewald JZ, Nakashima C, Nishikawa J. et al. (2013). Species concepts in Cercospora: spotting the weeds among the roses. Studies in Mycology 75: 115–170.PMC371388724014899He J, Li DW, Cui WL. et al. (2024). Morphological and phylogenetic analyses reveal three new species of Fusarium (Hypocreales, Nectriaceae) associated with leaf blight on Cunninghamia lanceolata in China. MycoKeys 101: 45–80.PMC1079057938229910Hoang DT, Chernomor O, von Haeseler A. et al. (2018). UFBoot2: improving the ultrafast bootstrap spproximation. Molecular Biology and Evolution 35: 518–522.PMC585022229077904Hyde KD, Norphanphoun C, Ma J. et al. (2023). Mycosphere notes 387–412 – novel species of fungal taxa from around the world. Mycosphere 14: 663–744.Jacobs A. (2010). Taxonomy of species within Gibberella fujikuroi complex. Ph.D. dissertation. University of Pretoria, Pretoria, South Africa.Kalyaanamoorthy S, Minh BQ, Wong TKF. et al. (2017). ModelFinder: fast model selection for accurate phylogenetic estimates. Nature Methods 14: 587–589.PMC545324528481363Katoh K, Rozewicki J, Yamada KD. (2019). MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Briefings in Bioinformatics 20: 1160–1166.PMC678157628968734Kerényi Z, Moretti A, Waalwijk C. et al. (2004). Mating type sequences in asexually reproducing Fusarium species. Applied and Environmental Microbiology 70: 4419–4423.PMC49239015294768Kim HS, Lohmar JM, Busman M. et al. (2020). Identification and distribution of gene clusters required for synthesis of sphingolipid metabolism inhibitors in diverse species of the filamentous fungus Fusarium. BMC Genomics 21: 510.PMC737691332703172Klittich C, Leslie JF. (1988). Nitrate reduction mutants of Fusarium moniliforme. Genetics 118: 417–423.PMC120329617246415Kumar S, Stecher G, Tamura K. (2016). MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Molecular Biology and Evolution 33: 1870–1874.PMC821082327004904Laraba I, Busman M, Geiser DM. et al. (2022). Phylogenetic diversity and mycotoxin potential of emergent phytopathogens within the Fusarium tricinctum species complex. Phytopathology 112: 1284–1298.34989594Lawrence EB, Nelson PE, Toussoun TA. (1985a). Inheritance of compatibility and sex in Gibberella baccata. Phytopathology 75: 322–324.Lawrence EB, Nelson PE, Toussoun TA. (1985b). Genetics of certain morphological characteristics in Gibberella baccata. Phytopathology 75: 741–747.Leslie JF, Summerell BA. (2006). The Fusarium laboratory manual. Blackwell Publishing Professional, USA.Li W, Cowley A, Uludag M. et al. (2015). The EMBL-EBI bioinformatics web and programmatic tools framework. Nucleic Acids Research 43: W580–W584.PMC448927225845596Lima CS, Pfenning LH, Costa SS. et al. (2012). Fusarium tupiense sp. nov., a member of the Gibberella fujikuroi complex that causes mango malformation in Brazil. Mycologia 104: 1408–1419.22675046Liu YJ, Whelen S, Hall BD. (1999). Phylogenetic relationships among ascomycetes: evidence from an RNA polymerase II subunit. Molecular Biology and Evolution 16: 1799–1808.10605121Logrieco A, Rizzo A, Ferracane R, Ritieni A. (2002). Occurrence of beauvericin and enniatins in wheat affected by Fusarium avenaceum head blight. Applied and Environmental Microbiology 68: 82–85.PMC12655311772612Lombard L, Sandoval-Denis M, Lamprecht SC. et al. (2019). Epitypification of Fusarium oxysporum – clearing the taxonomic chaos. Persoonia 43: 1–47.PMC708586032214496Minh BQ, Schmidt HA, Chernomor O. et al. (2020). IQ-TREE 2: new models and efficient methods for phylogenetic inference in in the genomic era. Molecular Biology and Evolution 37: 1530–1534.PMC718220632011700Miller MA, Pfeiffer W, Schwartz T. (2012). The CIPRES science gateway: enabling high-impact science for phylogenetics researchers with limited resources. In: Proceedings of the 1st conference of the extreme science and engineering discovery environment: Bridging from the extreme to the campus and beyond. Association for Computing Machinery, USA: 1–8.Nees von Esenbeck CG. (1817). Das System der Pilze und Schwaemme: Ein Versuch. In der Stahelschen Buchhandlung, Würzburg, Germany.Nelson PE, Toussoun TA, Marasas WFO. (1983). Fusarium species: An illustrated manual for identification. Pennsylvania State University Press, USA.Nguyen LT, Schmidt HA, Von Haeseler A. et al. (2015). IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Molecular Biology and Evolution 32: 268–274.PMC427153325371430Nirenberg HI. (1976). Untersuchungen über die morphologische und biologische Differenzierung in der Fusarium-Sektion Liseola. Mitteilungen aus der Biologischen Bundesanstalt für Land- und Forstwirtschaft Berlin-Dahlem 169: 1–117.Nylander JAA. (2004). MrModeltest v2. Program distributed by the author. Evolutionary Biology Centre, Uppsala University, Sweden.O’Donnell K, Cigelnik E. (1997). Two divergent intragenomic rDNA ITS2 types within a monophyletic lineage of the fungus Fusarium are nonorthologous. Molecular Phylogenetics and Evolution 7: 103–116.9007025O’Donnell K, Cigelnik E, Nirenberg HI. (1998). Molecular systematics and phylogeography of the Gibberella fujikuroi species complex. Mycologia 90: 465–493.O’Donnell K, Rooney AP, Proctor RH. et al. (2013). Phylogenetic analyses of RPB1 and RPB2 support a middle Cretaceous origin for a clade comprising all agriculturally and medically important fusaria. Fungal Genetics and Biology 52: 20–31.23357352O’Donnell K, Sarver BAJ, Brandt M. et al. (2007). Phylogenetic diversity and microsphere array-based genotyping of human pathogenic Fusaria, including isolates from the multistate contact lens-associated U.S. keratitis outbreaks of 2005 and 2006. Journal of Clinical Microbiology 45: 2235–2248.PMC193301817507522O’Donnell K, Sutton DA, Fothergill A. et al. (2008). Molecular phylogenetic diversity, multilocus haplotype nomenclature, and in vitro antifungal resistance within the Fusarium solani species complex. Journal of Clinical Microbiology 46: 2477–2490.PMC251948318524963Padwick GW. (1940). The genus Fusarium. V. Fusarium udum Butler, F. vasinfectum Atk. and F. lateritium Nees var. uncinatum Wr. The Indian Journal of Agricultural Sciences 10: 869–878.Pascoe IG. (1990). Fusarium morphology I. Identification and characterization of a third conidial type, the mesoconidium. Mycotaxon 37: 121–160.Pereira CB, Ward TJ, Del Ponte EM. et al. (2021). Five-year survey uncovers extensive diversity and temporal fluctuations among fusarium head blight pathogens of wheat and barley in Brazil. Plant Pathology 70: 426–435.Perera RH, Hyde KD, Maharachchikumbura SSN. et al. (2020). Fungi on wild seeds and fruits. Mycosphere 11: 2108–2480.Pfenning LH, de Melo MP, Costa MM. et al. (2019). Fusarium udum revisited: a common, but poorly understood member of the Fusarium fujikuroi species complex. Mycological Progress 18: 107–117.Proctor RH, Van Hove F, Susca A. et al. (2013). Birth, death and horizontal transfer of the fumonisin biosynthetic gene cluster during the evolutionary diversification of Fusarium. Molecular Microbiology 90: 290–306.23937442Raillo A. (1950). Fungi of the genus Fusarium. State Publishing House of Agricultural Literature, Moscow, USSR.Rayner RW. (1970). A mycological colour chart. CMI and British Mycological Society. Kew, Surrey, England, UK.Ronquist F, Teslenko M, Van der Mark P. et al. (2012). MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Systematic Biology 61: 539–542.PMC332976522357727Saccardo PA. (1879). Fungi Gallici lecti a cl. viris P. Brunaud, C.C. Gillet et Abb. Letendre. Michelia 1: 500–538.Samuels GJ, Nirenberg HI, Seifert KA. (2001). Perithecial species of Fusarium. In: Fusarium: Paul E. Nelson Memorial Symposium (Summerell BA, Leslie JF, Backhouse D, Bryden WL, Burgess LW, eds). APS Press, USA: 1–14.Sandoval-Denis M, Guarnaccia V, Polizzi G. et al. (2018). Symptomatic Citrus trees reveal a new pathogenic lineage in Fusarium and two new Neocosmospora species. Persoonia 40: 1–25.PMC614664030504994Sandoval-Denis M, Lombard L, Crous PW. (2019). Back to the roots: a reappraisal of Neocosmospora. Persoonia 43: 90–185.PMC708585732214499Snyder WC, Hansen HN. (1945). The species concept in Fusarium with reference to Discolour and other sections. American Journal of Botany 32: 657–666.Stamatakis A. (2014). RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30: 1312–1313.PMC399814424451623Sung GH, Sung JM, Hywel-Jones NL. et al. (2007). A multi-gene phylogeny of Clavicipitaceae (Ascomycota, Fungi): identification of localized incongruence using a combinational bootstrap approach. Molecular Phylogenetics and Evolution 44: 1204–1223.17555990Suwannarach N, Khuna S, Kumla J. et al. (2023). Fusarium endophyticum sp. nov. (Nectriaceae, Hypocreales), a new endophytic fungus from northern Thailand. Phytotaxa 606: 43–53.Tan YP, Shivas RG. (2023). Nomenclatural novelties. Index of Australian Fungi 10:1–17.Wang MM, Crous PW, Sandoval-Denis M. et al. (2022). Fusarium and allied genera from China: species diversity and distribution. Persoonia 48: 1–53.PMC1079228638234691Wollenweber HW. (1924). Pyrenomyceten-Studien. I. Angewandte Botanik 6: 300–313.Wollenweber HW. (1916–1935). Fusaria autographice delineata. Selbstverlag, Berlin, Germany.Wollenweber HW. (1917). Fusaria Autographice Delineata. Annales Mycologici 15: 1–56.Wollenweber HW. (1930). Fusaria Autographice Delineata 3: 660–1100. Berlin, Germany.Wollenweber HW. (1931). Fusarium – Monographie. Fungi parasitici et saprophytici. Zeitschrift für Parasitenkunde 3: 260–516.Wollenweber HW, Reinking OA. (1935). Die Fusarien. Verlagsbuchandlung Paul Parey, Berlin, Germany.Woudenberg JHC, Aveskamp MM, De Gruyter J. et al. (2009). Multiple Didymella teleomorphs are linked to the Phoma clematidina morphotype. Persoonia 22: 56–62.PMC278954120198138Wu F. (2007). Measuring the economic impacts of Fusarium toxins in animal feeds. Animal Feed Science and Technology 137: 363–374.Xue AG, Chen Y, Seifert K. et al. (2019). Prevalence of Fusarium species causing head blight of spring wheat, barley and oat in Ontario during 2001–2017. Canadian Journal of Plant Pathology 41: 392–402.Yilmaz N, Sandoval-Denis M, Lombard L. et al. (2021). Redefining species limits in the Fusarium fujikuroi species complex. Persoonia 46: 129–162.PMC931139235935895Zeller KA, Summerell BA, Bullock S. et al. (2003). Gibberella konza (Fusarium konzum) sp. nov. from prairie grasses, a new species in the Gibberella fujikuroi species complex. Mycologia 95: 943–95421149001Zhao L, Wei X, Huang CX. et al. (2022). Fusarium citri-sinensis sp. nov. (Ascomycota: Nectriaceae) isolated from fruit of Citrus sinensis in China. Phytotaxa 555: 259–266.395404612024112620241126
1520-688296472024Nov26Analytical chemistryAnal ChemValidated Multimethod Approach for Full Characterization of 2'-Fucosyl-d-lactose as an Industrially Produced Human Milk Oligosaccharide.186151862418615-1862410.1021/acs.analchem.4c01926Human milk oligosaccharides are of high interest as active ingredients in infant formulas and dietary food supplements. Full characterization of members of this compound class is challenging due to the intrinsic complexity of byproducts during synthesis by fermentation. Moreover, when method validation is targeted for a regulated environment, a robust chromatographic separation of the highly polar oligosaccharides needs to be addressed, including isomers and compounds relevant for potential product adulteration. We present a combined approach of validated chromatography and NMR spectroscopy, which allows for full mass balancing of industrially produced 2'-fucosyl-d-lactose. A combination of NMR spectroscopy, mass spectrometry, and action IR spectroscopy tackles structural elucidation of monoacetylated species as a new class of byproducts.NeuVolkerV0009-0009-7662-3152Analytical and Materials Science, BASF SE, Carl-Bosch-Strasse 38, Ludwigshafen am Rhein 67056, Germany.HoffmannWaldemarWAnalytical and Materials Science, BASF SE, Carl-Bosch-Strasse 38, Ludwigshafen am Rhein 67056, Germany.WeißThomas DTDAgricultural Solutions, BASF SE, Speyerer Strasse 2, Limburgerhof 67117, Germany.PuhlMichaelMChemicals and Catalysis Research, BASF SE, Carl-Bosch-Strasse 38, Ludwigshafen am Rhein 67056, Germany.AbikhodrAliAIsospec Analytics SA, Renens CH-1020, Switzerland.WarnkeStephanSIsospec Analytics SA, Renens CH-1020, Switzerland.Ben FalehAhmedAIsospec Analytics SA, Renens CH-1020, Switzerland.KlinckSandraSAnalytical and Materials Science, BASF SE, Carl-Bosch-Strasse 38, Ludwigshafen am Rhein 67056, Germany.PommerMariaMAnalytical and Materials Science, BASF SE, Carl-Bosch-Strasse 38, Ludwigshafen am Rhein 67056, Germany.KellnerSarahSAnalytical and Materials Science, BASF SE, Carl-Bosch-Strasse 38, Ludwigshafen am Rhein 67056, Germany.MaierWalterWAnalytical and Materials Science, BASF SE, Carl-Bosch-Strasse 38, Ludwigshafen am Rhein 67056, Germany.engJournal ArticleValidation Study20241114
United StatesAnal Chem03705360003-27000OligosaccharidesXO2533XO8R2'-fucosyllactose0TrisaccharidesJ2B2A4N98GLactoseIMMilk, HumanchemistryHumansOligosaccharideschemistryanalysisTrisaccharideschemistryMagnetic Resonance SpectroscopyLactosechemistryMass Spectrometry2024112663420241114173820241114653ppublish3954046110.1021/acs.analchem.4c019263947029720241029
1552-485X2024Oct29American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric GeneticsAm J Med Genet B Neuropsychiatr GenetOptimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.e33014e3301410.1002/ajmg.b.33014Decisions about when to change antidepressant treatment are complex and benefit from accurate prediction of treatment outcome. Prognostic accuracy can be enhanced by incorporating repeated assessments of symptom severity collected during treatment. Participants (n = 714) from the Genome-Based Therapeutic Drugs for Depression study received escitalopram or nortriptyline over 12 weeks. Remission was defined as scoring ≤ 7 on the Hamilton Rating Scale. Predictors included demographic, clinical, and genetic variables (at 0 weeks) and measures of symptom severity (at 0, 2, 4, and 6 weeks). Longitudinal descriptors extracted with growth curves and topological data analysis were used to inform prediction of remission. Repeated assessments produced gradual and drug-specific improvements in predictive performance. By Week 4, models' discrimination in all samples reached levels that might usefully inform treatment decisions (area under the receiver operating curve (AUC) = 0.777 for nortriptyline; AUC = 0.807 for escitalopram; AUC = 0.794 for combined sample). Decisions around switching or modifying treatments for depression can be informed by repeated symptom assessments collected during treatment, but not until 4 weeks after the start of treatment.© 2024 The Author(s). American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC.CarrEwanEDepartment of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), London, UK.RietschelMarcellaMDepartment of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.MorsOleOPsychosis Research Unit, Aarhus University Hospital-Psychiatry, Aarhus, Denmark.HenigsbergNevenNCroatian Institute for Brain Research, Medical School, University of Zagreb, Zagreb, Croatia.AitchisonKatherine JKJCollege of Health Sciences, Department of Psychiatry and Medical Genetics, University of Alberta, Edmonton, Alberta, Canada.Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada.Women and Children's Health Research Institute, University of Alberta, Edmonton, Alberta, Canada.Northern Ontario School of Medicine, Thunder Bay, Ontario, Canada.MaierWolfgangWDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany.German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.UherRudolfRDepartment of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada.FarmerAnneASocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.McGuffinPeterPSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.IniestaRaquelR0000-0003-1153-5417Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), London, UK.King's Institute for Artificial Intelligence, King's College London, London, UK.engNIHR Maudsley Biomedical Research CentreBrain and Behavior Research FoundationSeventh Framework ProgrammeEuropean Federation of Pharmaceutical Industries and AssociationsEuropean CommissionJournal Article20241029
United StatesAm J Med Genet B Neuropsychiatr Genet1012357421552-4841IMdepression remissionmachine learningrepeated measurestopological data analysis20248520231010202410120241029161420241029161420241029914aheadofprint3947029710.1002/ajmg.b.33014ReferencesAthreya, A. P., T. Brückl, E. B. Binder, et al. 2021. “Prediction of Short‐Term Antidepressant Response Using Probabilistic Graphical Models With Replication Across Multiple Drugs and Treatment Settings.” Neuropsychopharmacology 46, no. 7: 1272–1282. https://doi.org/10.1038/s41386‐020‐00943‐x.Bates, S., T. Hastie, and R. Tibshirani. 2023. “Cross‐Validation: What Does It Estimate and How Well Does It Do It?” Journal of the American Statistical Association 119: 1434–1445. https://doi.org/10.1080/01621459.2023.2197686.Beck, A. T., R. A. Steer, and M. G. Carbin. 1988. “Psychometric Properties of the Beck Depression Inventory: Twenty‐Five Years of Evaluation.” Clinical Psychology Review 8, no. 1: 77–100. https://doi.org/10.1016/0272‐7358(88)90050‐5.Bondar, J., A. Caye, A. M. Chekroud, and C. Kieling. 2020. “Symptom Clusters in Adolescent Depression and Differential Response to Treatment: A Secondary Analysis of the Treatment for Adolescents With Depression Study Randomised Trial.” Lancet Psychiatry 7, no. 4: 337–343. https://doi.org/10.1016/S2215‐0366(20)30060‐2.Browning, M., J. Kingslake, C. T. Dourish, G. M. Goodwin, C. J. Harmer, and G. R. Dawson. 2019. “Predicting Treatment Response to Antidepressant Medication Using Early Changes in Emotional Processing.” European Neuropsychopharmacology 29, no. 1: 66–75. https://doi.org/10.1016/j.euroneuro.2018.11.1102.Bubenik, P. 2018. “The Persistence Landscape and Some of Its Properties,” arXiv:1810.04963 [Math, Stat] http://arxiv.org/abs/1810.04963.Bull, L. M., M. Lunt, G. P. Martin, K. Hyrich, and J. C. Sergeant. 2020. “Harnessing Repeated Measurements of Predictor Variables for Clinical Risk Prediction: A Review of Existing Methods.” Diagnostic and Prognostic Research 4, no. 1: 9. https://doi.org/10.1186/s41512‐020‐00078‐z.Chazal, F., and B. Michel. 2017. “An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists,” arXiv:1710.04019 [Cs, Math, Stat] http://arxiv.org/abs/1710.04019.Chekroud, A. M., J. Bondar, J. Delgadillo, et al. 2021. “The Promise of Machine Learning in Predicting Treatment Outcomes in Psychiatry.” World Psychiatry 20, no. 2: 154–170. https://doi.org/10.1002/wps.20882.Chekroud, A. M., R. Gueorguieva, H. M. Krumholz, M. H. Trivedi, J. H. Krystal, and G. McCarthy. 2017. “Reevaluating the Efficacy and Predictability of Antidepressant Treatments: A Symptom Clustering Approach.” JAMA Psychiatry 74, no. 4: 370–378. https://doi.org/10.1001/jamapsychiatry.2017.0025.Dinga, R., L. Schmaal, B. W. J. H. Penninx, et al. 2019. “Evaluating the Evidence for Biotypes of Depression: Methodological Replication and Extension of.” NeuroImage. Clinical 22, no. 101: 796. https://doi.org/10.1016/j.nicl.2019.101796.Drysdale, A. T., L. Grosenick, J. Downar, et al. 2017. “Resting‐State Connectivity Biomarkers Define Neurophysiological Subtypes of Depression.” Nature Medicine 23, no. 1: 28–38. https://doi.org/10.1038/nm.4246.Gelenberg, A. J., M. P. Freeman, J. C. Markowitz, et al. 2010. Practice Guideline for the Treatment of Patients With Major Depressive Disorder. Virginia: American Psychiatric Association.Gueorguieva, R., A. M. Chekroud, and J. H. Krystal. 2017. “Trajectories of Relapse in Randomised, Placebo‐Controlled Trials of Treatment Discontinuation in Major Depressive Disorder: An Individual Patient‐Level Data Meta‐Analysis.” Lancet Psychiatry 4, no. 3: 230–237. https://doi.org/10.1016/S2215‐0366(17)30038‐X.Hamilton, M. 1967. “Development of a Rating Scale for Primary Depressive Illness.” British Journal of Social & Clinical Psychology 6, no. 4: 278–296. https://doi.org/10.1111/j.2044‐8260.1967.tb00530.x.Hilbert, K., S. L. Kunas, U. Lueken, N. Kathmann, T. Fydrich, and L. Fehm. 2020. “Predicting Cognitive Behavioral Therapy Outcome in the Outpatient Sector Based on Clinical Routine Data: A Machine Learning Approach.” Behaviour Research and Therapy 124, no. 103: 530. https://doi.org/10.1016/j.brat.2019.103530.Hosmer, D. W., and S. Lemeshow. 2000. Applied Logistic Regression. Hoboken, NJ: John Wiley & Sons.Iniesta, R., E. Carr, M. Carriere, N. Yerolemou, B. Michel, and F. Chazal. 2022. “Topological Data Analysis and Its Usefulness for Precision Medicine Studies.” Statistics and Operations Research Transactions 46, no. 1: 22.Iniesta, R., K. Hodgson, D. Stahl, et al. 2018. “Antidepressant Drug‐Specific Prediction of Depression Treatment Outcomes From Genetic and Clinical Variables.” Scientific Reports 8, no. 1: 5530. https://doi.org/10.1038/s41598‐018‐23584‐z.Iniesta, R., K. Malki, W. Maier, et al. 2016. “Combining Clinical Variables to Optimize Prediction of Antidepressant Treatment Outcomes.” Journal of Psychiatric Research 78: 94–102. https://doi.org/10.1016/j.jpsychires.2016.03.016.Kemp, D. E., S. J. Ganocy, M. Brecher, et al. 2011. “Clinical Value of Early Partial Symptomatic Improvement in the Prediction of Response and Remission During Short‐Term Treatment Trials in 3369 Subjects With Bipolar I or II Depression.” Journal of Affective Disorders 130, no. 1–2: 171–179. https://doi.org/10.1016/j.jad.2010.10.026.Kessler, R. C., H. M. van Loo, K. J. Wardenaar, et al. 2016. “Testing a Machine‐Learning Algorithm to Predict the Persistence and Severity of Major Depressive Disorder From Baseline Self‐Reports.” Molecular Psychiatry 21, no. 10: 1366–1371. https://doi.org/10.1038/mp.2015.198.Koutsouleris, N., R. S. Kahn, A. M. Chekroud, et al. 2016. “Multisite Prediction of 4‐Week and 52‐Week Treatment Outcomes in Patients With First‐Episode Psychosis: A Machine Learning Approach.” Lancet Psychiatry 3, no. 10: 935–946. https://doi.org/10.1016/S2215‐0366(16)30171‐7.Montgomery, S. A., and M. Åsberg. 1979. “A New Depression Scale Designed to Be Sensitive to Change.” British Journal of Psychiatry 134: 382–389.NICE. 2022. “Depression in Adults: Treatment and Management,” National Institute for Health and Care Excellence https://www.nice.org.uk/guidance/ng222.Paul, R., T. F. M. Andlauer, D. Czamara, et al. 2019. “Treatment Response Classes in Major Depressive Disorder Identified by Model‐Based Clustering and Validated by Clinical Prediction Models.” Translational Psychiatry 9, no. 1: 187. https://doi.org/10.1038/s41398‐019‐0524‐4.Pearson, R., D. Pisner, B. Meyer, J. Shumake, and C. G. Beevers. 2019. “A Machine Learning Ensemble to Predict Treatment Outcomes Following an Internet Intervention for Depression.” Psychological Medicine 49, no. 14: 2330–2341. https://doi.org/10.1017/S003329171800315X.Pedregosa, F., G. Varoquaux, A. Gramfort, et al. 2011. “Scikit‐Learn: Machine Learning in Python.” Journal of Machine Learning Research 12: 2825–2830.Python GLMNET. 2021. “Python Civis Analytics,” .Quitkin, F. M., P. J. McGrath, J. W. Stewart, et al. 1996. “Chronological Milestones to Guide Drug Change. When Should Clinicians Switch Antidepressants?” Archives of General Psychiatry 53, no. 9: 785–792. https://doi.org/10.1001/archpsyc.1996.01830090031005.Rapaport, M. H., and R. E. Maddux. 2002. “Challenges in the Development of Clinical Trials for Major Depressive Disorder: Lessons Learned From Trials in Minor Depression.” Dialogues in Clinical Neuroscience 4, no. 4: 402–407.Riihimäki, H., W. Chachólski, J. Theorell, J. Hillert, and R. Ramanujam. 2020. “A Topological Data Analysis Based Classification Method for Multiple Measurements.” BMC Bioinformatics 21, no. 1: 336. https://doi.org/10.1186/s12859‐020‐03659‐3.Seabold, S., and J. Perktold. 2010. “Statsmodels: Econometric and statistical modeling with python,” 9th Python in Science Conference.Skelton, M., E. Carr, J. E. J. Buckman, et al. 2022. “Trajectories of Depression and Anxiety Symptom Severity During Psychological Therapy for Common Mental Health Problems.” Psychological Medicine 53, no. 13: 6183–6193. https://doi.org/10.1017/S0033291722003403.Szegedi, A., W. T. Jaansen, A. P. P. van Willigenburg, E. van der Meulen, H. H. Stassen, and M. E. Thase. 2009. “Early Improvement in the First 2 Weeks as a Predictor of Treatment Outcome in Patients With Major Depressive Disorder: A Meta‐Analysis Including 6562 Patients.” Journal of Clinical Psychiatry 70, no. 3: 344–353.The GUDHI Project. 2020. “GUDHI user and reference manual (3.1.1). GUDHI Editorial Board,” https://gudhi.inria.fr/doc/3.1.1/.Troyanskaya, O., M. Cantor, G. Sherlock, et al. 2001. “Missing Value Estimation Methods for DNA Microarrays.” Bioinformatics 17, no. 6: 520–525. https://doi.org/10.1093/bioinformatics/17.6.520.Uher, R., A. Farmer, W. Maier, et al. 2008. “Measuring Depression: Comparison and Integration of Three Scales in the GENDEP Study.” Psychological Medicine 38, no. 2: 289–300. https://doi.org/10.1017/S0033291707001730.Uher, R., P. Huezo‐Diaz, N. Perroud, et al. 2009. “Genetic Predictors of Response to Antidepressants in the GENDEP Project.” Pharmacogenomics Journal 9, no. 4: 225–233. https://doi.org/10.1038/tpj.2009.12.Uher, R., O. Mors, M. Rietschel, et al. 2011. “Early and Delayed Onset of Response to Antidepressants in Individual Trajectories of Change During Treatment of Major Depression: A Secondary Analysis of Data From the Genome‐Based Therapeutic Drugs for Depression (GENDEP) Study.” Journal of Clinical Psychiatry 72, no. 11: 1478–1484. https://doi.org/10.4088/JCP.10m06419.Uher, R., R. H. Perlis, N. Henigsberg, et al. 2012. “Depression Symptom Dimensions as Predictors of Antidepressant Treatment Outcome: Replicable Evidence for Interest‐Activity Symptoms.” Psychological Medicine 42, no. 5: 967–980. https://doi.org/10.1017/S0033291711001905.Uher, R., N. Perroud, M. Y. M. Ng, et al. 2010. “Genome‐Wide Pharmacogenetics of Antidepressant Response in the GENDEP Project.” American Journal of Psychiatry 167, no. 5: 555–564. https://doi.org/10.1176/appi.ajp.2009.09070932.Van Rossum, G., and F. L. Drake. 2009. “Python 3 Reference Manual,” CreateSpace.Ward, J., N. Graham, R. J. Strawbridge, et al. 2018. “Polygenic Risk Scores for Major Depressive Disorder and Neuroticism as Predictors of Antidepressant Response: Meta‐Analysis of Three Treatment Cohorts.” PLoS One 13, no. 9: e0203896. https://doi.org/10.1371/journal.pone.0203896.Webb, C. A., Z. D. Cohen, C. Beard, M. Forgeard, A. Peckham, and T. Björgvinsson. 2020. “Personalized Prognostic Prediction of Treatment Outcome for Depressed Patients in a Naturalistic Psychiatric Hospital Setting: A Comparison of Machine Learning Approaches.” Journal of Consulting and Clinical Psychology 88, no. 1: 25–38. https://doi.org/10.1037/ccp0000451.392275242024121720241217
1468-286910162024DecJournal of urban health : bulletin of the New York Academy of MedicineJ Urban HealthA Framework for Measuring Neighborhood Walkability for Older Adults-A Delphi Consensus Study.118811991188-119910.1007/s11524-024-00910-7While mobility in older age is of crucial importance for health and well-being, it is worth noting that currently, there is no German language framework for measuring walkability for older adults that also considers the functional status of a person. Therefore, we combined the results of an expert workshop, a literature review, and a Delphi consensus survey. Through this, we identified and rated indicators relevant for walkability for older adults, additionally focusing on their functional status. The expert workshop and the review led to an extensive list of potential indicators, which we hope will be useful in future research. Those indicators were then adapted and rated in a three-stage Delphi expert survey. A fourth additional Delphi round was conducted to assess the relevance of each indicator for the different frailty levels, namely "robust," "pre-frail," and "frail." Between 20 and 28 experts participated in each round of the Delphi survey. The Delphi process resulted in a list of 72 indicators deemed relevant for walkability in older age groups, grouped into three main categories: "Built environment and transport infrastructure," "Accessibility and meeting places," and "Attractiveness and sense of security." For 35 of those indicators, it was suggested that functional status should be additionally considered. This framework represents a significant step forward in comprehensively covering indicators for subjective and objective walkability in older age, while also incorporating aspects of functioning relevant to older adults. It would be beneficial to test and apply the indicator set in a community setting.© 2024. The Author(s).KollerDanielaD0000-0002-3203-7188Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany. daniela.koller@med.uni-muenchen.de.BödekerMalteMFederal Centre for Health Education, Cologne, Germany.DappUlrikeU0000-0001-9497-2860Geriatrics Centre, Scientific Department at the University of Hamburg, Albertinen-Haus, Hamburg, Germany.GrillEvaE0000-0002-0273-7984Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.German Center for Vertigo and Balance Disorders, LMU University Hospital, Munich, Germany.FuchsJudithJ0000-0003-1594-2319Department of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin, Germany.MaierWernerW0000-0003-4356-7296Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.StroblRalfR0000-0002-7719-948XInstitute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.German Center for Vertigo and Balance Disorders, LMU University Hospital, Munich, Germany.engJournal Article20240903
United StatesJ Urban Health98099091099-3460IMHumansDelphi TechniqueWalkingAgedResidence CharacteristicsConsensusEnvironment DesignFemaleMaleBuilt EnvironmentAged, 80 and overFunctional StatusAgeDelphiFunctioningNeighborhoodQualitative researchWalkability2024726202412171230202494112024932325202493ppublish3922752410.1007/s11524-024-00910-710.1007/s11524-024-00910-7PMC11652456Marquez DX, Aguinaga S, Vasquez PM, et al. A systematic review of physical activity and quality of life and well-being. Transl Behav Med. 2020;10(5):1098–109.PMC775299933044541Pahor M, Guralnik JM, Ambrosius WT, et al. Effect of structured physical activity on prevention of major mobility disability in older adults: the LIFE study randomized clinical trial. JAMA. 2014;311(23):2387–96.PMC426638824866862WHO. National programmes for age-friendly cities and communities: a guide. Geneva: World Health Organization; 2023.Hand CL, Howrey BT. Associations among neighborhood characteristics, mobility limitation, and social participation in late life. J Gerontol B Psychol Sci Soc Sci. 2019;74(3):546–55.PMC637703528158866Kerr J, Rosenberg D, Frank L. The role of the built environment in healthy aging. J Plan Lit. 2012;27(1):43–60.Levasseur M, Genereux M, Bruneau JF, et al. Importance of proximity to resources, social support, transportation and neighborhood security for mobility and social participation in older adults: results from a scoping study. BMC Public Health. 2015;15:503.PMC446086126002342White DK, Jette AM, Felson DT, et al. Are features of the neighborhood environment associated with disability in older adults? Disabil Rehabil. 2010;32(8):639–45.PMC290801320205576Prince SA, Lancione S, Lang JJ, et al. Examining the state, quality and strength of the evidence in the research on built environments and physical activity among adults: an overview of reviews from high income countries. Health Place. 2022;77: 102874.36055165Bödeker M, Bucksch J, Fuhrmann H. Bewegungsfreundlichkeit von Wohnumgebungen messen. Prävention und Gesundheitsförderung. 2012;7(3):220–6.Cerin E, Nathan A, van Cauwenberg J, et al. The neighbourhood physical environment and active travel in older adults: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):15.PMC529483828166790Iroz-Elardo N, Adkins A, Ingram M. Measuring perceptions of social environments for walking: a scoping review of walkability surveys. Health Place. 2021;67: 102468.33285411Cervero R, Kockelman K. Travel demand and the 3Ds Density, diversity, and design. Transportation Research Part D: Transport and Environment. 1997;2(3):199–219.Ewing R, Cervero R. Travel and the built environment. J Am Plann Assoc. 2010;76(3):265–94.Peters M, Muellmann S, Christianson L, et al. Measuring the association of objective and perceived neighborhood environment with physical activity in older adults: challenges and implications from a systematic review. Int J Health Geogr. 2020;19(1):47.PMC765461333168094Turner VK, Middel A, Vanos JK. Shade is an essential solution for hotter cities. Nature. 2023;619(7971):694–7.37495873Buck C, Eiben G, Lauria F, et al. Urban moveability and physical activity in children: longitudinal results from the IDEFICS and I Family cohort. Int J Behav Nutr Phys Act. 2019;16(1):128.PMC690722831829198Buck C, Tkaczick T, Pitsiladis Y, et al. Objective measures of the built environment and physical activity in children: from walkability to moveability. J Urban Health. 2015;92(1):24–38.PMC433811825380722Frank LD, Sallis JF, Saelens BE, et al. The development of a walkability index: application to the Neighborhood Quality of Life Study. Br J Sports Med. 2010;44(13):924–33.19406732Cerin E, Conway TL, Saelens BE, Frank LD, Sallis JF. Cross-validation of the factorial structure of the neighborhood environment walkability scale (NEWS) and its abbreviated form (NEWS-A). Int J Bevah Nutr Phys Act. 2009;6:32.PMC270006919508724Barnett DW, Barnett A, Nathan A, et al. Built environmental correlates of older adults’ total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):103.PMC554752828784183Cerin E, Saelens BE, Sallis JF, Frank LD. Neighborhood environment walkability scale: validity and development of a short form. Med Sci Sports Exerc. 2006;38(9):1682–91.16960531Glicksman A, Ring L, Kleban MH, Hoffman C. Is, “walkability” a useful concept for gerontology? J Hous Elderly. 2013;27(1–2):241–54.PMC366536423729951King AC, Sallis JF, Frank LD, et al. Aging in neighborhoods differing in walkability and income: associations with physical activity and obesity in older adults. Soc Sci Med. 2011;73(10):1525–33.PMC363754721975025Oswald F, Konopik N. Impact of out-of-home activities, neighborhood and urban-related identity on well-being in old age. Z Gerontol Geriatr. 2015;48(5):401–7.26066027Rosso AL, Harding AB, Clarke PJ, Studenski SA, Rosano C. Associations of neighborhood walkability and walking behaviors by cognitive trajectory in older adults. Gerontologist. 2021;61(7):1053–61.PMC852268833428735Timmermans EJ, Visser M, Wagtendonk AJ, Noordzij JM, Lakerveld J. Associations of changes in neighbourhood walkability with changes in walking activity in older adults: a fixed effects analysis. BMC Public Health. 2021;21(1):1323.PMC825936834225681Van Cauwenberg J, Van Holle V, De Bourdeaudhuij I, Van Dyck D, Deforche B. Neighborhood walkability and health outcomes among older adults: the mediating role of physical activity. Health Place. 2016;37:16–25.26699447Van Holle V, Van Cauwenberg J, Gheysen F, et al. The association between Belgian older adults’ physical functioning and physical activity: what is the moderating role of the physical environment? PLoS ONE. 2016;11(2): e0148398.PMC475246526872017Van Holle V, Van Cauwenberg J, Van Dyck D, Deforche B, Van de Weghe N, De Bourdeaudhuij I. Relationship between neighborhood walkability and older adults’ physical activity: results from the Belgian Environmental Physical Activity Study in Seniors (BEPAS Seniors). Int J Behav Nutr Phys Act. 2014;11:110.PMC414522825148845Shafizadeh M, Jane Manson, Fowler-Davis S, et al. Effects of enriched physical activity environments on balance and fall prevention in older adults: a scoping review. J Aging Phys Act. 2020;29(1):178–91.32732456Abe T, Carver A, Sugiyama T. Associations of neighborhood built and social environments with frailty among mid-to-older aged Australian adults. Geriatr Gerontol Int. 2021;21(10):893–9.34355479Martins BA, Visvanathan R, Barrie HR, et al. Built environment and frailty: neighborhood perceptions and associations with frailty, experience from the Nagoya longitudinal study. J Appl Gerontol. 2021;40(6):609–19.32368955WHO, editor. How to use the ICF: A practical manual for using the International Classification of Functioning, Disability and Health(ICF). Exposure draft for comment. Geneva: World Health Organization; 2013.Nasa P, Jain R, Juneja D. Delphi methodology in healthcare research: how to decide its appropriateness. World J Methodol. 2021;11(4):116–29.PMC829990534322364Spranger J, Homberg A, Sonnberger M, Niederberger M. Reporting guidelines for Delphi techniques in health sciences: a methodological review. Z Evid Fortbild Qual Gesundhwes. 2022;172:1–11.35718726Grill E, Bronstein A, Furman J, Zee DS, Muller M. International Classification of Functioning, Disability and Health (ICF) core set for patients with vertigo, dizziness and balance disorders. J Vestib Res. 2012;22(5–6):261–71.23302707Yesuf EA, Grill E, Froschl G, Koller D, Haile-Mariam D. Administrators, health service providers, and consumers perspectives of functions of district health-care systems in Oromia region, Ethiopia: a qualitative study. Int J Health Plann Manage. 2019;34(2):836–50.30729577Bergman H, Béland F, Karunananthan S, Hummel S, Hogan D, Wolfson C. Developing a working framework for understanding frailty. Engl Trans Article Publ Gérontol Soc. 2014;109:15–29.Whitson H, Purser J, Cohen H. Frailty thy name is … Phrailty? J Gerontol A Biol Sci Med Sci. 2007;62:728–30.PMC264813317634319Dapp U, Minder C, Anders J, Golgert S, von Renteln-Kruse W. Long-term prediction of changes in health status, frailty, nursing care and mortality in community-dwelling senior citizens - results from the Longitudinal Urban Cohort Ageing Study (LUCAS). BMC Geriatr. 2014;14:141.PMC428957625522653Fried L, Tangen C, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56A:M146-156.11253156SoSci Survey (Version 3.1.06) [computer program]. Version: Available at https://www.soscisurvey.de (2019). Accessed 1 Jul 2023.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; 2021. https://www.R-project.org/.Hunter RH, Anderson LA, Belza B, et al. Environments for healthy aging: linking prevention research and public health practice. Prev Chronic Dis. 2013;10:E55.PMC364069323597393Michael YL, Keast EM, Chaudhury H, Day K, Mahmood A, Sarte AF. Revising the senior walking environmental assessment tool. Prev Med. 2009;48(3):247–9.PMC500360119136025Van Dyck D, Cardon G, Deforche B, Sallis JF, Owen N, De Bourdeaudhuij I. Neighborhood SES and walkability are related to physical activity behavior in Belgian adults. Prev Med. 2010;50(Suppl 1):S74-79.19751757Dapp U. Gesundheit und Verkehr im urbanen Raum. In: von Renteln-Kruse W, editor. Mobilität und Verkehrssicherheit im Alter. Berlin: De Gruyter; 2017. pp. 76–95.Dapp U. Mobilität und funktionale Kompetenz im Alter. In: von Renteln-Kruse W, editor. Mobilität und Verkehrssicherheit im Alter. Berlin: De Gruyter; 2017. pp. 46–60.Neumann L, Dapp U, Jacobsen W, van Lenthe F, von Renteln-Kruse W. The MINDMAP project: mental well-being in urban environments Design and first results of a survey on healthcare planning policies, strategies and programmes that address mental health promotion and mental disorder prevention for older people in Europe. Z Gerontol Geriat. 2017;50:588–602.PMC5649390288196933921713920240903
2158-31881412024Aug31Translational psychiatryTransl PsychiatryCorrection: Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis.35035035010.1038/s41398-024-03064-xLiDanyangD0000-0001-7470-6645Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK.Cancer Centre, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, CN, China.PainOliverO0000-0001-5680-3281Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, GB, UK.FabbriChiaraC0000-0003-0276-7865Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK.Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.WongWin Lee EdwinWLE0000-0001-6905-6449Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK.Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.LoChris Wai HangCWHSocial, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK.RipkeStephanS0000-0003-3622-835XDepartment of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, DE, Germany.Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.CattaneoAnnamariaA0000-0002-9963-848XBiological Psychiatry Laboratory, IRCCS Fatebenefratelli, Brescia, Italy.Department of Pharmacological and Biomedical Sciences, University of Milan, Milan, Italy.SoueryDanielDLaboratoire de Psychologie Medicale, Universitè Libre de Bruxelles and Psy Pluriel, Centre Européen de Psychologie Medicale, Brussels, Italy.DernovsekMojca ZMZ0000-0001-5344-7007University Psychiatric Clinic, University of Ljubliana, Ljubljana, Slovenia.HenigsbergNevenN0000-0002-5303-1834Department of Psychiatry, Croatian Institute for Brain Research, University of Zagreb Medical School, Zagreb, HR, Croatia.HauserJoannaJ0000-0002-6621-3493Psychiatric Genetic Unit, Poznan University of Medical Sciences, Poznan, Poland.LewisGlynG0000-0001-5205-8245Division of Psychiatry, University College London, London, GB, UK.MorsOleOPsychosis Research Unit, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.PerroudNaderNDepartment of Psychiatry, Geneva University Hospitals, Geneva, CH, Switzerland.RietschelMarcellaM0000-0002-5236-6149Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, University of Heidelberg, Central Institute of Mental Health, Mannheim, Denmark.UherRudolfR0000-0002-2998-0546Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.MaierWolfgangWDepartment of Psychiatry and Psychotherapy, University of Bonn, Bonn, Denmark.BauneBernhard TBTDepartment of Psychiatry, University of Münster, Münster, Denmark.Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Australia.BiernackaJoanna MJM0000-0001-9350-4440Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.BondolfiGuidoGDepartment of Psychiatry, Geneva University Hospitals, Geneva, CH, Switzerland.DomschkeKatharinaK0000-0002-2550-9132Department of Psychiatry and Psychotherapy, Medical Center, University of Freiburg, Freiburg, Denmark.KatoMasakiMDepartment of Neuropsychiatry, Kansai Medical University, Osaka, Japan.LiuYu-LiYL0000-0001-7519-2965Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan.SerrettiAlessandroADepartment of Medicine and Surgery, Kore University of Enna, Enna, Italy.TsaiShih-JenSJ0000-0002-9987-022XDepartment of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan.WeinshilboumRichardR0000-0002-4911-7985Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA.GSRD Consortium, the Major Depressive Disorder Working Group of the Psychiatric Genomics ConsortiumMcIntoshAndrew MAM0000-0002-0198-4588Division of Psychiatry, University of Edinburgh, Edinburgh, GB, UK.LewisCathryn MCM0000-0002-8249-8476Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK. cathryn.Lewis@kcl.ac.uk.Department of Medical & Molecular Genetics, King's College London, London, GB, UK. cathryn.Lewis@kcl.ac.uk.engPublished Erratum20240831
United StatesTransl Psychiatry1015626642158-3188IMTransl Psychiatry. 2024 Jul 19;14(1):296. doi: 10.1038/s41398-024-02981-13902583820249116172024911616202483123132024831epublish39217139PMC1136601610.1038/s41398-024-03064-x10.1038/s41398-024-03064-xtrying2...
Publications by W Maier | LitMetric
Browse Categories

Publications by authors named "W Maier"

  • Page 1 of 1
Known from trees and the tropics: new insights into the species complex.
M M Costa M Sandoval-Denis G M Moreira H Kandemir A Kermode W Maier

Stud Mycol

December 2024

The species complex (FLSC) currently comprises 11 phylogenetic species, including accepted names such as , , and , which have mostly been reported in association with citrus and coffee. Many varieties were documented by Wollenweber & Reinking (1935), which is indicative of a wider diversity of species within this group. The lack of type material in some cases, especially for the older names, means that definition by molecular phylogeny is very difficult.

View Article and Find Full Text PDF
Validated Multimethod Approach for Full Characterization of 2'-Fucosyl-d-lactose as an Industrially Produced Human Milk Oligosaccharide.
Volker Neu Waldemar Hoffmann Thomas D Weiß Michael Puhl Ali Abikhodr Walter Maier

Anal Chem

November 2024

Human milk oligosaccharides are of high interest as active ingredients in infant formulas and dietary food supplements. Full characterization of members of this compound class is challenging due to the intrinsic complexity of byproducts during synthesis by fermentation. Moreover, when method validation is targeted for a regulated environment, a robust chromatographic separation of the highly polar oligosaccharides needs to be addressed, including isomers and compounds relevant for potential product adulteration.

View Article and Find Full Text PDF
Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.
Ewan Carr Marcella Rietschel Ole Mors Neven Henigsberg Katherine J Aitchison Wolfgang Maier

Am J Med Genet B Neuropsychiatr Genet

October 2024

Decisions about when to change antidepressant treatment are complex and benefit from accurate prediction of treatment outcome. Prognostic accuracy can be enhanced by incorporating repeated assessments of symptom severity collected during treatment. Participants (n = 714) from the Genome-Based Therapeutic Drugs for Depression study received escitalopram or nortriptyline over 12 weeks.

View Article and Find Full Text PDF
A Framework for Measuring Neighborhood Walkability for Older Adults-A Delphi Consensus Study.
Daniela Koller Malte Bödeker Ulrike Dapp Eva Grill Judith Fuchs Werner Maier

J Urban Health

December 2024

While mobility in older age is of crucial importance for health and well-being, it is worth noting that currently, there is no German language framework for measuring walkability for older adults that also considers the functional status of a person. Therefore, we combined the results of an expert workshop, a literature review, and a Delphi consensus survey. Through this, we identified and rated indicators relevant for walkability for older adults, additionally focusing on their functional status.

View Article and Find Full Text PDF
Correction: Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis.
Danyang Li Oliver Pain Chiara Fabbri Win Lee Edwin Wong Chris Wai Hang Lo Wolfgang Maier

Transl Psychiatry

August 2024

View Article and Find Full Text PDF
Privacy Policy Site Map

© LitMetric 2024. All rights reserved.