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213 results on '"Montgomery, Claire"'

1. Sexual dimorphism in a mouse model of Friedreich’s ataxia with severe cardiomyopathy

Author

Salinas, Lili, Montgomery, Claire B, Figueroa, Francisco, Thai, Phung N, Chiamvimonvat, Nipavan, Cortopassi, Gino, and Dedkova, Elena N

Subjects
Biochemistry and Cell Biology, Medical Physiology, Biomedical and Clinical Sciences, Biological Sciences, Heart Disease, Neurosciences, Genetics, Cardiovascular, Pediatric, Rare Diseases, Neurodegenerative, Animals, Friedreich Ataxia, Cardiomyopathies, Male, Disease Models, Animal, Female, Mice, Mice, Knockout, Sex Characteristics, Iron-Binding Proteins, Frataxin, Testosterone, Receptors, GABA, Biological sciences, Biomedical and clinical sciences
Abstract

Friedreich's ataxia (FA) is an autosomal recessive disorder caused by reduced frataxin (FXN) expression in mitochondria, where the lethal component is cardiomyopathy. Using the conditional Fxnflox/null::MCK-Cre knock-out (Fxn-cKO) mouse model, we discovered significant sex differences in the progression towards heart failure, with Fxn-cKO males exhibiting a worse cardiac phenotype, low survival rate, kidney and reproductive organ deficiencies. These differences are likely due to a decline in testosterone in Fxn-cKO males. The decrease in testosterone was related to decreased expression of proteins involved in cholesterol transfer into the mitochondria: StAR and TSPO on the outer mitochondrial membrane, and the cholesterol side-chain cleavage enzyme P450scc and ferredoxin on the inner mitochondrial membrane. Expression of excitation-contraction coupling proteins (L-type calcium channel, RyR2, SERCA2, phospholamban and CaMKIIδ) was decreased significantly more in Fxn-cKO males. This is the first study that extensively investigates the sexual dimorphism in FA mouse model with cardiac calcium signaling impairment.

Published
2024

2. Ketogenic diet and BHB rescue the fall of long-term potentiation in an Alzheimer’s mouse model and stimulates synaptic plasticity pathway enzymes

Author

Di Lucente, Jacopo, Persico, Giuseppe, Zhou, Zeyu, Jin, Lee-Way, Ramsey, Jon J, Rutkowsky, Jennifer M, Montgomery, Claire M, Tomilov, Alexey, Kim, Kyoungmi, Giorgio, Marco, Maezawa, Izumi, and Cortopassi, Gino A

Subjects
Biochemistry and Cell Biology, Biological Sciences, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Nutrition, Alzheimer's Disease, Complementary and Integrative Health, Neurosciences, Aging, Dementia, Neurodegenerative, 2.1 Biological and endogenous factors, Neurological, Humans, Mice, Animals, Aged, Long-Term Potentiation, Alzheimer Disease, Amyloid beta-Protein Precursor, Diet, Ketogenic, Mice, Transgenic, Mice, Inbred C57BL, Neuronal Plasticity, Biological sciences, Biomedical and clinical sciences
Abstract

The Ketogenic Diet (KD) improves memory and longevity in aged C57BL/6 mice. We tested 7 months KD vs. control diet (CD) in the mouse Alzheimer's Disease (AD) model APP/PS1. KD significantly rescued Long-Term-Potentiation (LTP) to wild-type levels, not by changing Amyloid-β (Aβ) levels. KD's 'main actor' is thought to be Beta-Hydroxy-butyrate (BHB) whose levels rose significantly in KD vs. CD mice, and BHB itself significantly rescued LTP in APP/PS1 hippocampi. KD's 6 most significant pathways induced in brains by RNAseq all related to Synaptic Plasticity. KD induced significant increases in synaptic plasticity enzymes p-ERK and p-CREB in both sexes, and of brain-derived neurotrophic factor (BDNF) in APP/PS1 females. We suggest KD rescues LTP through BHB's enhancement of synaptic plasticity. LTP falls in Mild-Cognitive Impairment (MCI) of human AD. KD and BHB, because they are an approved diet and supplement respectively, may be most therapeutically and translationally relevant to the MCI phase of Alzheimer's Disease.

Published
2024

5. Shc inhibitor idebenone ameliorates liver injury and fibrosis in dietary NASH in mice.

Author

Jiang, Joy X, Tomilov, Alexey, Montgomery, Claire, Hui, Chun Kui, Török, Natalie J, and Cortopassi, Gino

Subjects
Liver, Leukocytes, Mononuclear, Animals, Mice, Inbred C57BL, Mice, Liver Cirrhosis, Choline Deficiency, Disease Models, Animal, Ubiquinone, Alanine Transaminase, Aspartate Aminotransferases, Methionine, Protective Agents, Therapeutics, Diet, Signal Transduction, Phosphorylation, Male, Shc Signaling Adaptor Proteins, Fast Foods, Non-alcoholic Fatty Liver Disease, NASH, Shc, fibrosis, idebenone, inflammation, Chronic Liver Disease and Cirrhosis, Biotechnology, Digestive Diseases, Hepatitis, Liver Disease, Nutrition, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Oral and gastrointestinal, Pharmacology and Pharmaceutical Sciences, Toxicology
Abstract

Shc expression rises in human nonalcoholic steatohepatitis (NASH) livers, and Shc-deficient mice are protected from NASH-thus Shc inhibition could be a novel therapeutic strategy for NASH. Idebenone was recently identified as the first small-molecule Shc inhibitor drug. We tested idebenone in the fibrotic methionine-choline deficient (MCD) diet and the metabolic fast food diet (FFD) mouse models of NASH. In the fibrotic MCD NASH model, idebenone reduced Shc expression and phosphorylation in peripheral blood mononuclear cells and Shc expression in the liver; decreased serum alanine aminotransferase and aspartate aminotransferase; and attenuated liver fibrosis as observed by quantitative polymerase chain reaction (qPCR) and hydroxyproline quantification. In the metabolic FFD model, idebenone administration improved insulin resistance, and reduced inflammation and fibrosis shown with qPCR, hydroxyproline measurement, and histology. Thus, idebenone ameliorates NASH in two mouse models. As an approved drug with a benign safety profile, Idebenone could be a reasonable human NASH therapy.

Published
2021

6. Dimethyl fumarate dose-dependently increases mitochondrial gene expression and function in muscle and brain of Friedreich's ataxia model mice.

Author

Hui, Chun Kiu, Dedkova, Elena N, Montgomery, Claire, and Cortopassi, Gino

Subjects
Muscles, Brain, Mitochondria, Animals, Mice, Inbred C57BL, Mice, Friedreich Ataxia, Mitochondrial Proteins, Immunosuppressive Agents, Gene Expression Regulation, Dose-Response Relationship, Drug, Dimethyl Fumarate, Neurodegenerative, Genetics, Rare Diseases, Neurosciences, Brain Disorders, Pediatric, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Neurological, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Previously we showed that dimethyl fumarate (DMF) dose-dependently increased mitochondrial gene expression and function in cells and might be considered as a therapeutic for inherited mitochondrial disease, including Friedreich's ataxia (FA). Here we tested DMF's ability to dose-dependently increase mitochondrial function, mitochondrial gene expression (frataxin and cytochrome oxidase protein) and mitochondrial copy number in C57BL6 wild-type mice and the FXNKD mouse model of FA. We first dosed DMF at 0-320 mg/kg in C57BL6 mice and observed significant toxicity above 160 mg/kg orally, defining the maximum tolerated dose. Oral dosing of C57BL6 mice in the range 0-160 mg/kg identified a maximum increase in aconitase activity and mitochondrial gene expression in brain and quadriceps at 110 mg/kg DMF, thus defining the maximum effective dose (MED). The MED of DMF in mice overlaps the currently approved human-equivalent doses of DMF prescribed for multiple sclerosis (480 mg/day) and psoriasis (720 mg/day). In the FXNKD mouse model of FA, which has a doxycycline-induced deficit of frataxin protein, we observed significant decreases of multiple mitochondrial parameters, including deficits in brain mitochondrial Complex 2, Complex 4 and aconitase activity, supporting the idea that frataxin deficiency reduces mitochondrial gene expression, mitochondrial functions and biogenesis. About 110 mg/kg of oral DMF rescued these enzyme activities in brain and rescued frataxin and cytochrome oxidase expression in brain, cerebellum and quadriceps muscle of the FXNKD mouse model. Taken together, these results support the idea of using fumarate-based molecules to treat FA or other mitochondrial diseases.

Published
2021

7. The Histone H3 K4me3, K27me3, and K27ac Genome-Wide Distributions Are Differently Influenced by Sex in Brain Cortexes and Gastrocnemius of the Alzheimer’s Disease PSAPP Mouse Model

Author

Casciaro, Francesca, Persico, Giuseppe, Rusin, Martina, Amatori, Stefano, Montgomery, Claire, Rutkowsky, Jennifer R, Ramsey, Jon J, Cortopassi, Gino, Fanelli, Mirco, and Giorgio, Marco

Subjects
Biological Sciences, Genetics, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease, Brain Disorders, Aging, Human Genome, Dementia, Neurodegenerative, Acquired Cognitive Impairment, Neurosciences, Neurological, Alzheimer's disease, sex differences, PSAPP mice, histone marks, Alzheimer’s disease
Abstract

BackgroundWomen represent the majority of Alzheimer's disease patients and show typical symptoms. Genetic, hormonal, and behavioral mechanisms have been proposed to explain sex differences in dementia prevalence. However, whether sex differences exist in the epigenetic landscape of neuronal tissue during the progression of the disease is still unknown.MethodsTo investigate the differences of histone H3 modifications involved in transcription, we determined the genome-wide profiles of H3K4me3, H3K27ac, and H3K27me3 in brain cortexes of an Alzheimer mouse model (PSAPP). Gastrocnemius muscles were also tested since they are known to be different in the two sexes and are affected during the disease progression.ResultsCorrelation analysis distinguished the samples based on sex for H3K4me3 and H3K27me3 but not for H3K27ac. The analysis of transcription starting sites (TSS) signal distribution, and analysis of bounding sites revealed that gastrocnemius is more influenced than brain by sex for the three histone modifications considered, exception made for H3K27me3 distribution on the X chromosome which showed sex-related differences in promoters belonging to behavior and cellular or neuronal spheres in mice cortexes.ConclusionsH3K4me3, H3K27ac, and H3K27me3 signals are slightly affected by sex in brain, with the exception of H3K27me3, while a higher number of differences can be found in gastrocnemius.

Published
2021

8. Fast Optimization of Wildfire Suppression Policies with SMAC

Author

McGregor, Sean, Houtman, Rachel, Montgomery, Claire, Metoyer, Ronald, and Dietterich, Thomas G.

Subjects
Computer Science - Learning, Statistics - Machine Learning
Abstract

Managers of US National Forests must decide what policy to apply for dealing with lightning-caused wildfires. Conflicts among stakeholders (e.g., timber companies, home owners, and wildlife biologists) have often led to spirited political debates and even violent eco-terrorism. One way to transform these conflicts into multi-stakeholder negotiations is to provide a high-fidelity simulation environment in which stakeholders can explore the space of alternative policies and understand the tradeoffs therein. Such an environment needs to support fast optimization of MDP policies so that users can adjust reward functions and analyze the resulting optimal policies. This paper assesses the suitability of SMAC---a black-box empirical function optimization algorithm---for rapid optimization of MDP policies. The paper describes five reward function components and four stakeholder constituencies. It then introduces a parameterized class of policies that can be easily understood by the stakeholders. SMAC is applied to find the optimal policy in this class for the reward functions of each of the stakeholder constituencies. The results confirm that SMAC is able to rapidly find good policies that make sense from the domain perspective. Because the full-fidelity forest fire simulator is far too expensive to support interactive optimization, SMAC is applied to a surrogate model constructed from a modest number of runs of the full-fidelity simulator. To check the quality of the SMAC-optimized policies, the policies are evaluated on the full-fidelity simulator. The results confirm that the surrogate values estimates are valid. This is the first successful optimization of wildfire management policies using a full-fidelity simulation. The same methodology should be applicable to other contentious natural resource management problems where high-fidelity simulation is extremely expensive.

Published
2017

9. Factoring Exogenous State for Model-Free Monte Carlo

Author

McGregor, Sean, Houtman, Rachel, Montgomery, Claire, Metoyer, Ronald, and Dietterich, Thomas G.

Subjects
Computer Science - Learning, Statistics - Machine Learning
Abstract

Policy analysts wish to visualize a range of policies for large simulator-defined Markov Decision Processes (MDPs). One visualization approach is to invoke the simulator to generate on-policy trajectories and then visualize those trajectories. When the simulator is expensive, this is not practical, and some method is required for generating trajectories for new policies without invoking the simulator. The method of Model-Free Monte Carlo (MFMC) can do this by stitching together state transitions for a new policy based on previously-sampled trajectories from other policies. This "off-policy Monte Carlo simulation" method works well when the state space has low dimension but fails as the dimension grows. This paper describes a method for factoring out some of the state and action variables so that MFMC can work in high-dimensional MDPs. The new method, MFMCi, is evaluated on a very challenging wildfire management MDP., Comment: 9 pages, 5 figures. Corrected equation 4

Published
2017

14. Post-anaesthesia pulmonary complications after use of muscle relaxants (POPULAR): a multicentre, prospective observational study

Author

Abad Gurumeta, Alfredo, Abernethy, Caroline, Abigail, Patrick, Achaibar, Kira, Adam, Emily, Afshari, Arash, Agudelo Montoya, M. Elizabeth, Akgün, Fatma Nur, Aletti, Gabriele, Alkış, Neslihan, Allan, Katie, Allan, Ashley, Allaouchiche, Bernard, Allcock, Clare, Almasy, Emoke, Amey, Isobel, Amigoni, Maria, Andersen, Elin, Andersson, Peder, Anipchenko, Natalya, Antunes, Pedro, Armstrong, Earlene, Aslam, Tayyba Naz, Aslin, Bjorn, Assunção, José Pedro, Ausserer, Julia, Avvai, Mary, Awad, Nahla, Ayas Montero, Begoña, Ayuso, Mercedes, Azevedo, Patricia, Badarau, Victoria, Badescu, Roxana, Baiardo Redaelli, Martina, Baird, Colin, Baird, Yolanda, Baker, Tim, Balaji, Packianathaswamy, Bălan, Cristina, Balandin, Alina, Balescu-Arion, Carmen, Baliuliene, Vilda, Baltasar Isabel, Jorge, Baluch, Saif Nasr, Bandrabur, Daniela, Bankewitz, Carla, Barber, Katrina, Barbera, Francesco, Barcraft-Barnes, Helena, Barletti, Valentina, Barnett, Gill, Baron, Kirsty, Barros, Ana, Barsan, Victoria, Bartlett, Pauline, Batistaki, Chrysanthi, Baumgarten, Georg, Baytas, Volkan, Beauchamp, Nigel, Becerra Cayetano, Isabel A., Bell, Stephanie, Bellandi, Mattia, Belletti, Alessandro, Belmonte Cuenca, Julio, Benitez-Cano, Adela, Beretta, Luigi, Berger, Marc, Bergmann, Nicole, Bergmark, Kristina, Bermudez Lopez, Maria, Bernotaite, Monika, Beurskens, Charlotte, Bidd, Heena, Bifulco, Francesca, Bignami, Elena, Bilic, Aleksandar, Bilskiene, Diana, Bischoff, Petra, Bishop, Luke, Bjonness, Therese, Blaylock, Hether, Blethyn, Kate, Blincoe, Thomas, Blokhin, Ivan, Blunt, Nadia, Boer, Christa, Bois, Grégory, Bonicolini, Eleonora, Booth, Joanna, Borecka-Kedzierska, Miroslawa, Borstnar, Katarina, Borys, Michał, Boselli, Emmanuel, Bouvet, Lionel, Bouwman, Arthur, Bowen, Leonora, Bowrey, Sarah, Boxall, Leigh, Božić, Teodora, Bradley, Tom, Branco, Teresa, Brazzi, Luca, Brazzoni, Marcella, Brear, Tracy, Brogly, Nicolas, Brohi, Farooq, Broms, Jacob, Bubliauskas, Andrius, Bucolo, Gea Erika, Buerkle, Hartmut, Buggy, Donal, Buhre, Wolfgang, Bukauskas, Tomas, Butturini, Francesco, Byttner, Anders, Cabrera Díaz, Itahísa, Calderon, Adriana, Calhau, Ricardo, Callejo, Angel, Cammu, Guy, Campesato, Manuela, Can, Özlem S, Candeias, Margarida, Cantor, Andreea, Carise, Elsa, Carmona, Cristina, Carreteiro, Joana, Carrieri, Cosima, Carter, Anna, Casal, Manuela, Casanova, Irene, Cascella, Marco, Casero, Luis M., Casiraghi, Guiseppina Maria, Castelo-Branco, Laila, Castro Arranz, Carlos, Cernea, Daniela Denisa, Cervantes, Jesoporiol, Chandler, Ben, Charnock, Robert, Chatzimicali, Aikaterini, Chinery, Elane, Chishti, Ahmed, Chondhury, Priyakam, Christie, Emily, Christodoudiles, George, Ciardo, Stefano, Cimpeanu, Luminata, Cindea, Iulia, Cinnella, Gilda, Clark, Sebastian, Clayton, Matthew, Cocu, Simona, Collyer, Thomas, Colvin, Carie, Cope, Sean, Copeta, Filomena, Copotoiu, Sanda-Maria, Correia de Barros, Filinto, Corso, Ruggero Massimo, Cortegiani, Andrea, Costa, Gabriela, Cowton, Amanda, Cox, Nicolas, Craig, James, Cricca, Valentina, Cronin, John, Cunha, Mariana, Cuomo, Arturo, Curley, Katherine, Czuczwar, Mirosław, Dabrowska, Domenika, Damster, Sabrine, Danguy des Déserts, Marc, Daniliuc, Aura, Danninger, Thomas, Darwish, Imad, Dascalu, Corina, Davies, Kirsty, Davies, Simon, De Boer, Hans, De Flaviis, Adelisa, De Selincourt, Gabrielle, Deana, Cristian, Debaene, Bertrand, Debreceni, Gabor, Dedhia, Jatin, Delgado Garcia, Isabel, Della Rocca, Giorgio, Delroy-Buelles, Llana, Desai, Tejal, Dhillon, Parveen, Di Giacinto, Ida, Di Mauro, Piero, Diaz Gomez, Tamara V., Dimitrovski, Aleksandar, Dinic, Vesna, Dîrzu, Dan-Sebastian, Divander, Mona Britt, Dolinar, Janez, Domingues, Susana, Doolan, James, Downes, Charlotte, Dragoescu, Nicoleta Alice, Droc, Gabriela, Dum, Elisabeth, Dumitrescu, Alexandra, Duncan, Louise, Dzurňáková, Paul, Eberl, Susanne, Edwards, Jayne, Edwards, Mark, Ekelund, Kim, Ekengren, Patrik, Elghouty, Eyad, Ellerkmann, Richard, Ellis, Helen, Elme, Andreas, Ernst, Thomas, Errando, Carlos Luis, Estenes, Simao, Ewaldsson, Callis, Farid, Nahla, Featherstone, James, Febres, Daniela, Fedorov, Sergey, Feggeler, Johanna, Feijten, Prisca, Fellmann, Tobias, Fernandez Candil, Juan, Fernandez Castineira, Ana, Fernández Castineira, Juan, Fernando, Aruna, Ferrando, Carlos, Ferreira, Leonia, Ferreira, Patrick, Feyling, Anders, Filipescu, Daniela, Fleischer, Andreas, Floris, Leda, Foerster, Urs, Fox, Benjamin, Franke, Uwe, Frasca, Denis, Frey, Christian, Frost, Victoria, Fullin, Giorgio, Fumagalli, Jacopo, Furneval, Julie, Fusari, Maurizio, Gallacher, Stuart, Galushka, Svetlana, Gambale, Giorgio, Gambino, Irene, Garcia-Perez, Maria Luisa, Garg, Sanjeev, Garlak, Justyna, Gavranovic, Zeljka, Gavrilov, Roman, Gaynor, Lames, Gecaj Gashi, Agreta, Georghiou, Maria, Gerjevic, Bozena, Gferer, Gudrun, Giarratano, Antonino, Gibson, Andy, Gievski, Vanja, Giles, Julian, Gillberg, Lars, Gilowska, Katarzyna, Gilsanz Rodriguez, Fernando, Gioia, Antonio, Giovannoni, Cecilia, Girotra, Vandana, Gkinas, Dimitrios, Gkiokas, George, Godoroja, Daniela, Goebel, Ulrich, Goel, Vandana, Gonzalez, Matilde, Goranovic, Tatjana, Gornik-Wlaszczuk, Ewa, Gosavi, Smita, Gottfridsson, peter, Gottschalk, André, Granell, Manuel, Granstrom, Anna, Grassetto, Alberto, Greenwood, Anna, Grigoras, Ioana, Grintescu, Ioana, Gritsan, Alexey, Gritsan, Galina, Grynyuk, Andriy, Guadagnin, Giovanni Maria, Guarnieri, Marcello, Güçlü, Çiğdem, Guerrero Diez, Maria, Gunenc, Ferim, Günther, Ulf, Gupta, Pawan, Guttenthaler, Vera, Hack, Yvonne, Hafisayena, Ade, Hagau, Natalia, Haldar, Jagannath, Hales, Dawn, Hancı, Volkan, Hanna-Jumma, Sameer, Harazim, Hana, Harlet, Pierre, Harper, Daniel, Harris, Benjamin, Harvey, Orla, Hashimi, Medita, Hawkins, Lesley, Hayes, Conrad, Heaton, James, Heier, Tom, Helliwell, Laurence, Hemmes, Sabrine, Henderson, Kate, Hermanides, Jeroen, Hermanns, Henning, Herrera Hueso, Berta, Hestenes, Siv, Hettiarachchi, Roshane, Highgate, Judith, Hodgson, Keith, Hoelbling, Daniel, Holland, Jonathan, Horhota, Lucian, Hormis, Anil, Hribar, Renata, Hua, Alina, Humphreys, Sally, Humphries, Ryan, Humpliková, Simona, Hunt, Janez, Husnain, Ali, Hussein, Ahmed, Hyams, Benjamin, Iannuccelli, Fabrizio, Ilette, Katie, Ilyas, Carl, Inan, Turgay, India, Immaculada, Ionițăv, Victor, Irwin, Foo, Jain, Vipul, Janez, Benedikt, Jankovic, Radmilo, Jenkins, Sarah, Jenko, Matej, Jimenez, Raquel, Jiménez Gomez, Bárbara, Joachim, Sugganthi, Joelsson-Alm, Eva, John, John, Jonikaite, Lina, Jovic, Miomir, Jungwirth, Bettina, Junke, Etienne, Kabakov, Borys, Kadaoui, Salah-Din, Kanski, Andrzej, Karadag, Süheyla, Karbonskiene, Aurika, Karjagin, Juri, Kasnik, Darja, Katanolli, Fatos, Katsika, Eleni, Kaufmann, Kai, Keane, Helen, Kelly, Martin, Kent, Melanie, Keraitiene, Grazina, Khudhur, Ahmed, Khuenl-Brady, Karin, Kidd, Laurie, King, Siobhan, Kirchgäßner, Katharina, Klancir, Tino, Klucniks, Andris, Knotzer, Johann, Knowlden, Peter, Koers, Lena, Kompan, Janez, Koneti, Kiran K, Kooij, Fabian, Koolen, Eric, Koopman - van Gemert, Anna Wilhelmina Margaretha Maria, Kopp, Kristen, Korfiotis, Dimitrios, Korolkov, Oleg, Kosinová, Martina, Köstenberger, Markus, Kotzinger, Oskar, Kovačević, Marko, Kranke, Peter, Kranke, Eva, Kraus, Christiane, Kraus, Stephanie, Kubitzek, Christiane, Kucharski, Rafal, Kucukguclu, Semih, Kudrashou, Allaksandr, Kumar, Vinayak, Kummen, Live, Kunit, Cornelia, Kushakovsky, Vlad, Kuvaki, Bahar, Kuzmanovska, Biljana, Kyttari, Aikaterina, Landoni, Giovanni, Lau, Gary, Lazarev, Konstantin, Legett, Samantha, Legrottaglie, Anna Maria, Leonardi, Silvia, Leong, Maria, Lercher, Helene, Leuvrey, Matthieu, Leva, Brigitte, Levstek, Meta, Limb, James, Lindholm, Espen, Linton, Fiona, Liperi, Corradero, Lipski, Fabian, Lirk, Philipp, Lisi, Alberto, Lišková, Katarina, Lluch Oltra, Aitana, Loganathan, Vinothan, Lombardi, Stefania, Lopez, Eloisa, Lopez Rodríguez, Maria, Lorenzini, Laura, Lowicka, Malgorzata, Lugovoy, Alexander, Luippold, Madeleine, Lumb, Andrew, Macas, Andrius, Macgregor, Mark, Machado, Humberto, Maciariello, Maria, Madeira, Isabel, Maitan, Stefan, Majewski, Jacek, Maldini, Branka, Malewski, Georgia, Manfredini, Livia, Männer, Olja, Marchand, Bahareh, Marcu, Alexandra, Margalef, Jordi, Margarson, Michael, Marinheiro, Lucia, Markic, Ana, Markovic Bozic, Jasmina, Marrazzo, Francesco, Martin, Jane, Martin Ayuso, Maria, Martinez, Esteher, Martino, Enrico Antonio, Martinson, Victoria, Marusic-Gaser, Katarina, Mascarenhas, Catia, Mathis, Cindy, Matsota, Paraskevi, Mavrommati, Eleni, Mazul Sunko, Branka, McCourt, Killian, McGill, Neil, McKee, Raymond, Meço, Başak Ceyda, Meier, Sonja, Melbourne, Susan, Melbybråthen, Grethe, Meli, Andrea, Melia, Aiden, Melotti, Rita Maria, Menga, Maria Rosaria, Mercer, Pauline, Merotra, Susan, Mescolini, Silvia, Metterlein, Thomas, Michalov, Martin, Michlig, Sam, Midgley, Susan, Milić, Morena, Milojevic, Milan, Miñana, Amanda, Minto, Gary, Mirabella, Lucia, Mirea, Liliana, Mittelstädt, Ludger, Moeglen, Aude, Moise, Alida, Mokini, Zhirajr, Molin, Anna, Moltó, Luis, Monea, Maria Concetta, Montalto, Francesca, Montgomery, Jane, Montgomery, Claire, Montillo, Gerardo, Moore, Sally, Moore, Faye, Moreira, Zelia, Moreno, Tania, Moreno, Ricardo, Moret, Enrique, Moreton, Sarah, Morgan, Marianne, Moro Velasco, Concepción, Morri, Davide, Moull, Alice, Moura, Fernando, Mráz, Peter, Mrozek, Katarzyna, Mukhtar, Karim, Muniyappa, Sudeshkumar, Murray, Heather, Murthy, Burra VS, Mushambi, Mary, Nadolski, Maria, Nardelli, Pasquale, Nardin, Giordano, Navarro Pérez, Rosalía, Naveiro, Andrea, Negri, Manuela, Nesek Adam, Visnja, Neskovic, Vojislava, Neuwersch, Stefan, Neves, Miriam, Nguyen, Bavinh, Ní Eochagáin, Aisling, Nicholas, Caroline, Nightingale, Jeremy, Norrie, Kylie, Novak-Jankovic, Vesna, Novakova, Andrea, Novillo, Marta, Numan, Sandra, Oduro-Dominah, Louise, Oldner, Anders, Oliveira, Isabel, Ologoiu, Daniela, Oloktsidou, Irini, O'Reilly, Rosalind, Orlando, Alessandro, Ovezov, Alexey, Ozbilgin, Sule, Paal, Peter, Padin Barreiro, Lidia, Palugniok, Ryszard, Papaioannou, Alexandra, Papapostolou, Konstantinos, Paranthaman, Prabhakar, Pardey Bracho, Gilda, Parente, Suzana, Parfeni, Alexandru, Pasin, Laura, Passey, Samuel, Pastor, Ernesto, Patch, Sarah, Patil, Andan, Paunescu, Marilena-Alina, Pehboeck, Daniel, Pereira, Manuela, Pereira, Carla, Perez Caballero, Paula, Pérez García, Aníbal, Pérez Soto, Antonia, Perez Tejero, Gisela, Perez-Cerda, Francisco, Pesenti, Antonio, Petta, Rocco, Philippe, Simon, Pickering, David, Pico Veloso, Jandro, Pina, Pedro, Pinho-Oliveira, Vítor, Pinol, Santiago, Pinto, Rita, Pistidda, Laura, Pitterle, Manuela, Piwowarczyk, Paweł, Plotnikova, Olga, Pohl, Holger, Poldermann, Jorinde, Polkovicová, Lucia, Pompei, Livia, Popescu, Mihai, Popović, Radmila, Pota, Vincenzo, Potocnik, Miriam, Potręć, Beata, Potter, Alison, Pramod, Nalwaya, Prchalova, Martina, Preckel, Benedikt, Pugh, Richard, Pulletz, Mark, Radoeshki, Aleksandar, Rafi, Amir, Ragazzi, Riccardo, Raineri Santi, Maurizio, Rajamanickam, Tamiselvan, Rajput, Zahra, Ramachandran, Rajeskar, Ramasamy, Radhika, Ramessur, Suneil, Rao, Roshan, Rasmussen, Anders, Rato, André, Razaque, Usman, Real Navacerrada, M. Isabel, Reavley, Caroline, Reid, James, Reschreiter, Henrik, Rial, Erick, Ribas Carrasco, Patricia, Ribeiro, Sandy, Rich, Nathalie, Richardson, Lydia, Rimaitis, Kestutis, Rimaitis, Marius, Ringvold, Else-Marie, Ripke, Fabian, Ristescu, Irina, Ritchie, Keith, Ródenas, Frederic, Rodrigues, Patrícia, Rogers, Emma, Rogerson, David, Romagnoli, Stefano, Romero, Esther, Rondovic, Goran, Rose, Bernd Oliver, Roth, Winfried, Rotter, Marie-Therese, Rousseau, Guy, Rudjord, Anders, Rueffert, Henrik, Rundgren, Malin, Rupprecht, Korbinian, Rushton, Andrew, Russotto, Vincenzo, Rypulak, Elżbieta, Ryszka, Maciej, Sà, Jacinta, Sà Couto, Paula, Saby, Sandrine, Sagic, Jelena, Saleh, Omar, Sales, Gabriele, Sánchez Sánchez, Yván, Sanghera, Sumayer, Şanli Karip, Ceren, Santiveri Papiol, Francisco Javier, Santos, Sofia, Sarno, Stephen, Saul, Daniel, Saunders, David, Savic, Nenad, Scalco, Loïc, Scanlon, Deborah, Schaller, Stefan, Schax, Christoph, Scheffer, Gert Jan, Schening, Anna, Schiavone, Vincenzo, Schmidt-Ehrenberg, Florian, Schmidt-Mutter, Catherine, Schönberg, Christina, Schopflin, Christian, Schreiber, Jan-Uwe, Schultz, Marcus, Schurig, Marlen, Scott, Carmen, Sebestian, Siby, Sehgal, Selena, Sem, Victoria, Semenas, Egidijus, Serafini, Elena, Serchan, Pashalitsa, Shields, Martin, Shobha, Ramakrishnan, Shosholcheva, Mirjana, Siamansour, Tanja, Siddaiah, Narendra, Siddiqi, Khalid, Sinclair, Rhona, Singh, Permendra, Singh, Rajendra, Sinha, Aneeta, Sinha, Ashok, Skinner, Amanda, Smee, Elizabeth, Smekalova, Olga, Smith, Neil, Smith, Thomas, Smitz, Carine, Smole, Daniel, Sojčić, Nataša, Soler Pedrola, Maria, Somanath, Sameer, Sonksen, Julian, Sorella, Maria Christina, Sörmus, Alar, Soro, Marina, Soto, Carmen, Spada, Anna, Spadaro, Savino, Spaeth, Johannes, Sparr, Harald, Spielmann, Annika, Spindler-Vesel, Alenka, Stamelos, Matthaios, Stancombe L, Liucia, Stanculescu, Andreea, Standl, Thomas, Standley, Tom, Stanek, Ondrej, Stanisavljević, Snežana, Starczewska, Malgorzata, Stäuble, Christiane, Steen, Julie, Stefan, Oana Maria, Stell, Elizabeth, Stera, Caterina, Stevens, Markus, Stoerckel, Marlène, Stošić, Biljana, Stourac, Petr, Stroumpoulis, Konstantinos, Struck, Rafael, Suarez de la Rica, Alejandro, Sultanpori, Altaf, Sundara Rajan, Rajinikanth, Suying, Ong, Svensen, Christer, Swan, Louise, Syrogianni, Paulina, Sysiak, Justyna, Szederjesi, Janos, Taddei, Stefania, Tan Hao, Ern, Tanou, Virginia, Tarabová, Katarina, Tardaguila Sancho, Paula, Tarroso, Maria, Tartaglione, Marco, Taylor, Emma, Tbaily, Lee, Telford, Richard, Terenzoni, Massimo, Theodoraki, Kassiani, Thornley, Helen, Tiganiuc, Liviu, Toim, Hardo, Tomescu, Dana, Tommasino, Concezione, Toni, Jessica, Toninelli, Arturo, Toretti, Ilaria, Townley, Stephen, Trepenaitis, Darius, Trethowan, Brian, Tsaousi, Georgia, Tsiftsi, Aikaterini, Tudor, Adrada, Turan, Güldem, Turhan, Sanem Çakar, Unic-Stojanovic, Dragana, Unterbuchner, Christoph, Unzueta, Carmen, Uranjek, Jasna, Ursic, Tomaz, Vaida, Simona, Valldeperas Ferrer, Silvia, Valldeperas Hernandez, Maria Inmaculada, Valsamidis, Dimitri, Van Beek, Rienk, Van dasselaer, Nick, Van Der Beek, Tim, Van Duivenvoorde, Yoni, van Klei, Wilton A., Van Poorter, Frans, Van Zaane, Bas, Van Zundert, Tom, Van Zyl, Rebekka, Vargas Munoz, Ana Milena, Varsani, Nimu, Vasconcelos, Pedro, Vassilakis, Georgios, Vecchiatini, Tommaso, Vecera, Lubomir, Vercauteren, Marcel, Verdouw, Bas, Verheyen, Veerle, Verri, Marco, Vicari Sottosanti, Luigi Giancarlo, Vico, Manuel, Vidal Mitjans, Patricia, Vilardi, Anna, Vissicchio, Daniela, Vitale, Giovanni, Vitković, Bibiana, Vizcaychipi, Marcela Paola, Voicu, Alexandra, Voje, Minca, Volfová, Ivana, Volta, Carlo Alberto, Von Lutterotti, Theresa, von Tiesenhausen, Anna, Vrecic-Slabe, Simona, Vukcevic, Dejan, Vukovic, Rade, Vullo, P. Agostina, Wade, Andrew, Wallberg, Hanna, Wallden, Jakob, Wallner, Johann, Walther Sturesson, Louise, Watson, Davina, Weber, Stefan, Wegiel Leskiewiq, Anna, Weller, Debbie, Wensing, Carine, Werkmann, Markus, Westberg, Henrik, Wikström, Erik, Williams, Benedict, Wilson, Robin, Wirth, Steffen, Wittmann, Maria, Wood, Laura, Wright, Stella, Zachoval, Christian, Zambon, Massimo, Zampieri, Silvia, Zampone, Salvatore, Zangrillo, Alberto, Zani, Gianluca, Zavackiene, Asta, Zieglerder, Raphael, Zonneveldt, Harry, Zsisku, Lajos, Zucker, Tom-Philipp, Żukowski, Maciej, Zuleika, Mehrun, Zupanĕiĕ, Darja, Kirmeier, Eva, Eriksson, Lars I, Lewald, Heidrun, Jonsson Fagerlund, Malin, Hoeft, Andreas, Hollmann, Markus, Meistelman, Claude, Hunter, Jennifer M, Ulm, Kurt, and Blobner, Manfred

Published
2019
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16. Diffusion of Asymmetric Swimmers

Author

Rutenberg, Andrew D., Richardson, Andrew J., and Montgomery, Claire J.

Subjects
Condensed Matter - Soft Condensed Matter, Condensed Matter - Statistical Mechanics, Quantitative Biology - Cell Behavior
Abstract

Particles moving along curved trajectories will diffuse if the curvature fluctuates sufficiently in either magnitude or orientation. We consider particles moving at a constant speed with either a fixed or with a Gaussian distributed curvature magnitude. At small speeds the diffusivity is independent of the speed. At larger particle speeds, the diffusivity depends on the speed through a novel exponent. We apply our results to intracellular transport of vesicles. In sharp contrast to thermal diffusion, the effective diffusivity increases with vesicle size and so may provide an effective means of intracellular transport., Comment: 4 pages, 3 figures (first figure takes awhile to print)

Published
2003
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35. Optimal spatial patterns of fuel management and timber harvest with fire risk

Author

Konoshima, Masashi, Albers, Heidi J., Montgomery, Claire A., and Arthur, Jeffrey L.

Subjects
Logging -- Methods, Timber, Fire ecology -- Analysis, Landscape -- Analysis, Earth sciences
Abstract

The stochastic and spatial nature of fire poses challenges for the cost-efficient allocation of fuel treatment over the landscape. A model that addresses complex but important components of fuel management decisions, spatial and dynamic aspects of fire risk, and a carefully designed framework that allows us to draw general insight into the optimal spatial pattern of management are necessary to provide a basis for developing efficient fuel treatment plans. For this purpose, we combine a physical fire model and a spatial-dynamic optimization model to explore harvest and fuel treatment across a hypothetical landscape under risk of a moving fire over a range of physical and economic conditions. Our model is able to describe spatial trade-offs involved in decision process, namely trade-offs between protection of on-site values and protection against fire spread. We found that the spatial configuration of management units can lead to heterogeneity in management across seemingly homogeneous units. Resume: La nature spatiale et stochastique du feu constitue un defi pour la repartition economique du traitement des combustibles dans le paysage. Un modele qui tient compte des composantes complexes mais importantes des decisions de gestion des combustibles, les aspects spatiaux et dynamiques de risque d'incendie, ainsi qu'un cadre concu avec soin qui permet d'obtenir une idee generale du patron spatial optimal de gestion sont necessaires pour fournir une base permettant de developper des plans efficaces de traitement des combustibles. A cette fin. nous avons combine un modele physique du feu et un modele dynamique d'optimisation spatiale pour etudier la recolte et le traitement des combustibles dans un pay-sage hypothetique oil un incendie peut se propager en utilisant une variete de conditions physiques et economiques. Notre modele est capable de decrire les compromis spatiaux qui font partie du processus de decision, nommement les compromis entre la protection des valeurs du site et la protection contre la propagation du feu. Nous avons trouve que la configuration spatiale des unites de gestion peut mener a une gestion heterogene parmi des unites en apparence homogenes [Traduit par la Redaction], Introduction Although fire is an important part of many forest ecosystems, the accumulation of fuel in forests in recent decades has created conditions that lead to uncharacteristic and catastrophic fires [...]

Published
2010

37. Spatial-endogenous fire risk and efficient management and timber harvest

Author

Konoshima, Masashi, Montgomery, Claire A., Albers, Heidi J., and Arthur, Jeffrey L.

Subjects
Forest fires -- Analysis, Forest fires -- Models, Forest fires -- United States, Forest management -- Research, Logging -- Research, Agricultural industry, Economics, Environmental issues
Abstract

The optimal spatial pattern of fuel management and timber harvest are analyzed using a spatial fire-behavior model and a stochastic dynamic-optimization model. The analysis revealed support for two current strategies in managing forests with fire risk, while revealing challenges in two other strategies.

Published
2008

38. Changes in attitudes about importance of and willingness to pay for salmon recovery in Oregon

Author

Montgomery, Claire A. and Helvoigt, Ted L.

Subjects
Native Americans -- Analysis, Economic conditions -- Analysis, Unemployment -- Analysis, Environmental issues
Abstract

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jenvman.2005.05.002 Byline: Claire A. Montgomery (a), Ted L. Helvoigt (b) Abstract: Salmon are perhaps the quintessential icon of the Pacific Northwest, affecting the region's culture, politics, and economy. The importance Oregonians place on salmon recovery and their willingness to pay for salmon recovery efforts was assessed biennially between 1996 and 2002 through the Oregon Population Survey. Based on these data, we found that Oregonians appear to have become less supportive toward salmon recovery and salmon recovery efforts over that time period; they were less likely to say salmon recovery is important and chose lower willingness to pay responses in 2002 than in 1996.Attitudes do appear to be related to the economic conditions and demographic composition of residents of the state. In particular, we found that local unemployment rates, age of respondent, and rural county residence are significantly negatively correlated with the respondent's expressed support for salmon recovery efforts. Attributes positively correlated with expressions of support for salmon include male gender, graduate-level education, and American Indian identity. We found that a significant portion of the decline in support is unexplained by the variables included in the analysis. Author Affiliation: (a) Department of Forest Resources, Oregon State University, Corvallis, OR 97331, USA (b) ECONorthwest, 99 W. 10th Avenue, Suite 400, Eugene, Oregon 97401, USA Article History: Received 30 June 2004; Revised 11 April 2005; Accepted 6 May 2005

Published
2006

41. Modeling joint production of wildlife and timber

Author

Nalle, Darek J., Montgomery, Claire A., Arthur, Jeffrey L., Polasky, Stephen, and Schumaker, Nathan H.

Subjects
Sustainable development -- Forecasts and trends, Wildlife management, Market trend/market analysis, Economics, Environmental services industry
Abstract

A method is developed that combines economic and ecological models in a dynamic and spatial analysis to evaluate land use decisions and find cost-effective alternatives for which it is not possible to do better on one objective without harming another objective. The method is demonstrated using timber production and species conservation on a forested landscape over a 100-year planning horizon.

Published
2004

45. Growth of Managed Older Douglas-fir Stands: Implications of the Black Rock Thinning Trial in the Coast Range of Western Oregon.

Author

Tappeiner, John, Adams, Darius, Montgomery, Claire, and Maguire, Douglas

Subjects
FOREST landowners, FOREST thinning, OLD growth forests, OPPORTUNITY costs, FOREST restoration, TRIALS (Law), CORPORATE finance
Abstract

The most recent remeasurement of growth (at approximate total stand age 100 years) from the Black Rock Thinning Trial in western Oregon provides useful information for forest owners interested in accelerating restoration of older forest characteristics in Douglas-fir stands of the Pacific Northwest. Thinnings at several intensities at total stand age of roughly 50 years effectively reset stand growth patterns. With quadratic mean diameters in thinned plots up to 40% higher than those of unthinned controls, thinned plot mean annual increments (MAIs) and periodic annual increments continue to rise 55 years after thinning, with the peak in board foot and cubic foot MAI apparently still decades in the future. Assuming repeatable future thinning responses similar to the Black Rock Trial, financial analysis of the opportunity costs of extending rotations to 100 years indicates that some thinning treatments can reduce opportunity costs by up to half at a 6% discount rate. [ABSTRACT FROM AUTHOR]

Published
2022
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