Force to change large cardinal strength

This dissertation includes many theorems which show how to change large cardinal properties with forcing. I consider in detail the degrees of inaccessible cardinals (an analogue of the classical degrees of Mahlo cardinals) and provide new large cardinal definitions for degrees of inaccessible cardinals extending the hyper-inaccessible hierarchy. I showed that for every cardinal $\kappa$, and ordinal $\alpha$, if $\kappa$ is $\alpha$-inaccerssible, then there is a $\mathbb{P}$ forcing that $\kappa$ which preserves that $\alpha$-inaccessible but destorys that $\kappa$ is $(\alpha+1)$-inaccessible. I also consider Mahlo cardinals and degrees of Mahlo cardinals. I showed that for every cardinal $\kappa$, and ordinal $\alpha$, there is a notion of forcing $\mathbb{P}$ such that $\kappa$ is still $\alpha$-Mahlo in the extension, but $\kappa$ is no longer $(\alpha +1)$-Mahlo. I also show that a cardinal $\kappa$ which is Mahlo in the ground model can have every possible inaccessible degree in the forcing extension, but no longer be Mahlo there. The thesis includes a collection of results which give forcing notions which change large cardinal strength from weakly compact to weakly measurable, including some earlier work by others that fit this theme. I consider in detail measurable cardinals and Mitchell rank. I show how to change a class of measurable cardinals by forcing to an extension where all measurable cardinals above some fixed ordinal $\alpha$ have Mitchell rank below $\alpha.$ Finally, I consider supercompact cardinals, and a few theorems about strongly compact cardinals. Here, I show how to change the Mitchell rank for supercompactness for a class of cardinals

Crop Updates 2001 - Oilseeds

ABSTRACT This session covers twenty five papers from different authors: FORWARD, Mervyn McDougall, CHAIRMAN, PULSES AND OILSEEDS PARTNERSHIP GROUP PLENARY 1. Implications of the ‘green-bridge’ for viral and fungal disease carry-over between seasons, Debbie Thackray, Agriculture Western Australia and Centre for Legumes in Mediterranean Agriculture 2. Insect pest development in WA via the ‘green-bridge’, Kevin Walden, Agriculture Western Australia VARIETIES 3. Performance of new canola varieties in AGWEST variety trials, G. Walton, Crop Improvement Institute, Agriculture Western Australia 4. New herbicide tolerant varieties in WA, Kevin Morthorpe, Stephen Addenbrooke, Pioneer Hi-Bred Australia P/L 5. IT v’s TT – Head to head, Paul Carmody, Centre for Cropping Systems, Agriculture Western Australia ESTABLISHMENT 6. Effect of stubble, seeding technique and seed size on crop establishment and yield of canola, Rafiul Alam, Glen Riethmuller and Greg Hamilton, Agriculture Western Australia 7. Canola establishment survey 2000, Rafiul Alam, Paul Carmody, Greg Hamilton and Adrian Cox, Agriculture Western Australia 8. Tramline farming for more canola, Paul Blackwell, Agriculture Western Australia NUTRITION 9. Comparing the phosphorus requirement of canola and wheat in WA, M.D.A. Bolland and M.J. Baker, Agriculture Western Australia 10. Will a rainy summer affect nitrogen requirement: Tailoring your fertiliser decisions using the new nitrogen calculator, A.J. Diggle, Agriculture Western Australia 11. Canola – More response to lime, Chris Gazeyand Paul Carmody, Centre for Cropping Systems, Agriculture Western Australia AGRONOMY 12. Hormone manipulation of canola development, Paul Carmody and Graham Walton, Agriculture Western Australia 13. Yield penalties with delayed sewing of canola, Imma Farre, CSIRO Plant Industry, Michael J. Robertson, CSIRO Sustainable Ecosystems, Graham H. Walton, Agriculture Western Australia, Senthold Asseng, CSIRO Plant Industry 14. Dry matter and oil accumulation in developing seeds of canola varieties at different sowing dates, Ping Si1, David Turner1 and David Harris2 , 1Plant Sciences, Faculty of Agriculture, The University of Western Australia, 2Chemistry Centre of Western Australia 13. Simulating oil concentrations in canola – virtually just the beginning, David Turner1 and Imma Farré2, 1Plant Sciences, Faculty of Agriculture, The University of Western Australia, 2CSIRO Plant Industry, Centre for Mediterranean Agricultural Research PESTS AND DISEASES 14. Further evidence that canola crops are resilient to damage by aphids, Françoise Berlandier and Christiaan Valentine, Entomology, Agriculture Western Australia 15. Management of Diamondback moth (DBM) in canola, David Cook, Peter Mangano, David Cousins, Françoise Berlandier, and Darryl Hardie, Crop Improvement Institute,Agriculture Western Australia 16. Effect of time of sowing in conjunction with fungicides on blackleg and yield of canola, Ravjit Khangura and Martin Barbetti, Agriculture Western Australia 17. Further developments in forecasting aphid and virus risk in canola, Debbie Thackray, Jenny Hawkes and Roger Jones, Agriculture Western Australia and Centre for Legumes in Mediterranean Agriculture 18. Efficiency of selected insecticides for the use on Diamondback Moth in canola, Kevin Walden, Agriculture Western Australia 19. Impact® applied ‘in furrow’ controls blackleg in canola, Cameron Weeks and Erin Hasson, Mingenew-Irwin Group Inc. 20. Effect of time of sowing and Impact® on canola yield, Esperance, Dave Eksteen, Agriculture Western Australia 21. Australian Plague Locust Campaign 2000, Kevin Walden, Agriculture Western Australia WEED CONTROL 22. New herbicide options for canola, John Moore and Paul Matson, Agriculture Western Australia HARVESTING 23. Effects of time of swathing and desiccant application on the seed yield and oil content of canola, Carla Thomas and Lionel Martin, Muresk Institute of Agriculture, Curtin University of Technology DECISION SUPPORT AND ADOPTION 24. Using canola monitoring groups to understand factors affecting canola production in Esperance, Dave Eksteen, Agriculture Western Australia 25. Nitrogen and canola, Dave Eksteen, Agriculture Western Australi

Gastrokine-1, an anti-amyloidogenic protein secreted by the stomach, regulates diet-induced obesity

Obesity and its sequelae have a major impact on human health. The stomach contributes to obesity in ways that extend beyond its role in digestion, including through effects on the microbiome. Gastrokine-1 (GKN1) is an anti-amyloidogenic protein abundantly and specifically secreted into the stomach lumen. We examined whether GKN1 plays a role in the development of obesity and regulation of the gut microbiome. Gkn1−/− mice were resistant to diet-induced obesity and hepatic steatosis (high fat diet (HFD) fat mass (g) = 10.4 ± 3.0 (WT) versus 2.9 ± 2.3 (Gkn1−/−) p < 0.005; HFD liver mass (g) = 1.3 ± 0.11 (WT) versus 1.1 ± 0.07 (Gkn1−/−) p < 0.05). Gkn1−/− mice also exhibited increased expression of the lipid-regulating hormone ANGPTL4 in the small bowel. The microbiome of Gkn1−/− mice exhibited reduced populations of microbes implicated in obesity, namely Firmicutes of the class Erysipelotrichia. Altered metabolism consistent with use of fat as an energy source was evident in Gkn1−/− mice during the sleep period. GKN1 may contribute to the effects of the stomach on the microbiome and obesity. Inhibition of GKN1 may be a means to prevent obesity

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven\u27t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics

Multi-Omics Characterization of Early- and Adult-Onset Major Depressive Disorder

Age at depressive onset (AAO) corresponds to unique symptomatology and clinical outcomes. Integration of genome-wide association study (GWAS) results with additional “omic” measures to evaluate AAO has not been reported and may reveal novel markers of susceptibility and/or resistance to major depressive disorder (MDD). To address this gap, we integrated genomics with metabolomics using data-driven network analysis to characterize and differentiate MDD based on AAO. This study first performed two GWAS for AAO as a continuous trait in (a) 486 adults from the Pharmacogenomic Research Network-Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS), and (b) 295 adults from the Combining Medications to Enhance Depression Outcomes (CO-MED) study. Variants from top signals were integrated with 153 p180-assayed metabolites to establish multi-omics network characterizations of early (p = 8.77 × 10−8) localized to an intron of SAMD3. In silico functional annotation of top signals (p −5) demonstrated gene expression enrichment in the brain and during embryonic development. Network analysis identified differential associations between four variants (in/near INTU, FAT1, CNTN6, and TM9SF2) and plasma metabolites (phosphatidylcholines, carnitines, biogenic amines, and amino acids) in early- compared with adult-onset MDD. Multi-omics integration identified differential biosignatures of early- and adult-onset MDD. These biosignatures call for future studies to follow participants from childhood through adulthood and collect repeated -omics and neuroimaging measures to validate and deeply characterize the biomarkers of susceptibility and/or resistance to MDD development