Neuropsychological performance in young adults with cannabis use disorder.

Funder: NIHR MedTechFunder: in vitro diagnostic Co-operativeFunder: nihr cambridge biomedical research centreFunder: Wallitt Foundation and Eton CollegeFunder: Wellcome Trust Collaborative AwardBACKGROUND AND AIMS: Cannabis is a commonly used recreational drug in young adults. The worldwide prevalence in 18- to 25-year-olds is approximately 35%. Significant differences in cognitive performance have been reported previously for groups of cannabis users. However, the groups are often heterogeneous in terms of cannabis use. Here, we study daily cannabis users with a confirmed diagnosis of cannabis use disorder (CUD) to examine cognitive performance on measures of memory, executive function and risky decision-making. METHODS: Forty young adult daily cannabis users with diagnosed CUD and 20 healthy controls matched for sex and premorbid intelligence quotient (IQ) were included. The neuropsychological battery implemented was designed to measure multiple modes of memory (visual, episodic and working memory), risky decision-making and other domains of executive function using subtests from the Cambridge Neuropsychological Test Automated Battery (CANTAB). RESULTS: Our results showed that young adult daily cannabis users with CUD perform significantly poorer on tasks of visual and episodic memory compared with healthy controls. In addition, executive functioning was associated with the age of onset. CONCLUSIONS: Further research is required to determine whether worse performance in cognition results in cannabis use or is a consequence of cannabis use. Chronic heavy cannabis use during a critical period of brain development may have a particularly negative impact on cognition. Research into the persistence of cognitive differences and how they relate to functional outcomes such as academic/career performance is required

Tau-targeting antisense oligonucleotide MAPTRx in mild Alzheimer’s disease: a phase 1b, randomized, placebo-controlled trial

Tau plays a key role in Alzheimer’s disease (AD) pathophysiology, and accumulating evidence suggests that lowering tau may reduce this pathology. We sought to inhibit MAPT expression with a tau-targeting antisense oligonucleotide (MAPTRx) and reduce tau levels in patients with mild AD. A randomized, double-blind, placebo-controlled, multiple-ascending dose phase 1b trial evaluated the safety, pharmacokinetics and target engagement of MAPTRx. Four ascending dose cohorts were enrolled sequentially and randomized 3:1 to intrathecal bolus administrations of MAPTRx or placebo every 4 or 12 weeks during the 13-week treatment period, followed by a 23 week post-treatment period. The primary endpoint was safety. The secondary endpoint was MAPTRx pharmacokinetics in cerebrospinal fluid (CSF). The prespecified key exploratory outcome was CSF total-tau protein concentration. Forty-six patients enrolled in the trial, of whom 34 were randomized to MAPTRx and 12 to placebo. Adverse events were reported in 94% of MAPTRx-treated patients and 75% of placebo-treated patients; all were mild or moderate. No serious adverse events were reported in MAPTRx-treated patients. Dose-dependent reduction in the CSF total-tau concentration was observed with greater than 50% mean reduction from baseline at 24 weeks post-last dose in the 60 mg (four doses) and 115 mg (two doses) MAPTRx groups. Clinicaltrials.gov registration number: NCT03186989

Predicting panicle initiation timing in rice grown using water efficient systems

Management strategies that improve water efficiency in water-limited rice systems are needed for sustainable production. In southeast Australia growers are increasing implementing drill seeding and also delayed permanent water (DPW) irrigation practice to improve water productivity. This change in timing of permanent water application has a large influence on crop phenology which impacts the timing of crop management practices. Two types of phenological models were assessed to predict panicle initiation (PI) timing in fields managed using drill sowing and DPW. A single-stage model was contrasted with a two-stage efficiency model. The single-stage model assumed temperature across the planting to PI period equally contributes to PI timing. The two-stage efficiency model allowed for differential temperature efficiencies between the pre (aerobic) and post (anaerobic) permanent water periods. Four temperature indices, one growing degree day and three parameterisations of degree day (DD) were tested. Observations of PI from seven seasons and seven locations were used to parameterise (n = 55) and validate (n = 7) the models. The best model was for the two-stage efficiency approach using the original DD parameters with RMSE of 3.8 and 4.4 days for the parameterising and validating data, respectively. The methodology outlined can be used for other varieties, physiological stages and water management strategies to develop models to better predict phenology in rice systems managed with DPW.Funding for the research was provided by AgriFutures Australia and NSW Department of Primary Industries, Australia

Economic cost of environmental flows in an unregulated river system

This paper applies a stochastic dynamic programming framework, incorporating links to hydrological and biophysical models, to assess the economic costs of environmental flows in an unregulated river system in the Namoi Valley of northern New South Wales

Economic cost of environmental flows in an unregulated river system

This paper applies a stochastic dynamic programming framework, incorporating links to hydrological and biophysical models, to assess the economic costs of environmental flows in an unregulated river system in the Namoi Valley of northern New South Wales, Australia. Structural adjustment decisions are included in the model to account for farmer responses to changes in environmental flows through the introduction of a water sharing plan. The results of the analysis indicate that the proposed level of environmental flows reduces water extractions by around 6 per cent, and imposes an opportunity cost of less than 1 per cent in terms of reduced net income over a 20-year period

Insights into the value of seasonal climate forecasts to agriculture

Seasonal climate forecasts (forecasts) aim to reduce climate-related productivity risk by helping farmers make decisions that minimise losses in poor years and maximise profits in good years. Most Australian forecast valuations have focused on fertiliser decisions to wheat operations, and few assessments have evaluated the benefit of incremental improvements of forecast skill. These gaps have limited our understanding of forecast value to the broader agriculture sector and the benefit of investments to improve forecast skill. To address these gaps, we consistently assessed forecast value for seven Australian case studies (southern grains, northern grains, southern beef, northern beef, lamb, cotton, and sugar). We implemented a three-stage methodology which consisted of engagement with industry practitioners; modelling production under different climatic and environmental conditions; and economic modelling to evaluate forecast value for eleven levels of forecast skill. Our results show that forecast value was often low and highly variable. Value was found to vary based on forecast attributes (forecast skill, resolution and state), industry application and prevailing conditions (environmental and market). This is the first Australian valuation study where the same methodological approach was applied across multiple industries, incremental improvements in skill were valued, and prevailing conditions were explicitly evaluated for impact on value

Insights into the value of seasonal climate forecasts to agriculture

Seasonal climate forecasts (forecasts) aim to reduce climate-related productivity risk by helping farmers make decisions that minimise losses in poor years and maximise profits in good years. Most Australian forecast valuations have focused on fertiliser decisions to wheat operations, and few assessments have evaluated the benefit of incremental improvements of forecast skill. These gaps have limited our understanding of forecast value to the broader agriculture sector and the benefit of investments to improve forecast skill. To address these gaps, we consistently assessed forecast value for seven Australian case studies (southern grains, northern grains, southern beef, northern beef, lamb, cotton, and sugar). We implemented a three-stage methodology which consisted of engagement with industry practitioners; modelling production under different climatic and environmental conditions; and economic modelling to evaluate forecast value for eleven levels of forecast skill. Our results show that forecast value was often low and highly variable. Value was found to vary based on forecast attributes (forecast skill, resolution and state), industry application and prevailing conditions (environmental and market). This is the first Australian valuation study where the same methodological approach was applied across multiple industries, incremental improvements in skill were valued, and prevailing conditions were explicitly evaluated for impact on value

Insights into the value of seasonal climate forecasts to agriculture

Seasonal climate forecasts (forecasts) aim to reduce climate-related productivity risk by helping farmers make decisions that minimise losses in poor years and maximise profits in good years. Most Australian forecast valuations have focused on fertiliser decisions to wheat operations, and few assessments have evaluated the benefit of incremental improvements of forecast skill. These gaps have limited our understanding of forecast value to the broader agriculture sector and the benefit of investments to improve forecast skill. To address these gaps, we consistently assessed forecast value for seven Australian case studies (southern grains, northern grains, southern beef, northern beef, lamb, cotton, and sugar). We implemented a three-stage methodology which consisted of engagement with industry practitioners; modelling production under different climatic and environmental conditions; and economic modelling to evaluate forecast value for eleven levels of forecast skill. Our results show that forecast value was often low and highly variable. Value was found to vary based on forecast attributes (forecast skill, resolution and state), industry application and prevailing conditions (environmental and market). This is the first Australian valuation study where the same methodological approach was applied across multiple industries, incremental improvements in skill were valued, and prevailing conditions were explicitly evaluated for impact on value

Growth factor independence 1 expression in myeloma cells enhances their growth, survival, and osteoclastogenesis

Abstract Background In spite of major advances in treatment, multiple myeloma (MM) is currently an incurable malignancy due to the emergence of drug-resistant clones. We previously showed that MM cells upregulate the transcriptional repressor, growth factor independence 1 (Gfi1), in bone marrow stromal cells (BMSCs) that induces prolonged inhibition of osteoblast differentiation. However, the role of Gfi1 in MM cells is unknown. Methods Human primary CD138+ and BMSC were purified from normal donors and MM patients’ bone marrow aspirates. Gfi1 knockdown and overexpressing cells were generated by lentiviral-mediated shRNA. Proliferation/apoptosis studies were done by flow cytometry, and protein levels were determined by Western blot and/or immunohistochemistry. An experimental MM mouse model was generated to investigate the effects of MM cells overexpressing Gfi1 on tumor burden and osteolysis in vivo. Results We found that Gfi1 expression is increased in patient’s MM cells and MM cell lines and was further increased by co-culture with BMSC, IL-6, and sphingosine-1-phosphate. Modulation of Gfi1 in MM cells had major effects on their survival and growth. Knockdown of Gfi1 induced apoptosis in p53-wt, p53-mutant, and p53-deficient MM cells, while Gfi1 overexpression enhanced MM cell growth and protected MM cells from bortezomib-induced cell death. Gfi1 enhanced cell survival of p53-wt MM cells by binding to p53, thereby blocking binding to the promoters of the pro-apoptotic BAX and NOXA genes. Further, Gfi1-p53 binding could be blocked by HDAC inhibitors. Importantly, inoculation of MM cells overexpressing Gfi1 in mice induced increased bone destruction, increased osteoclast number and size, and enhanced tumor growth. Conclusions These results support that Gfi1 plays a key role in MM tumor growth, survival, and bone destruction and contributes to bortezomib resistance, suggesting that Gfi1 may be a novel therapeutic target for MM