Mitochondrial Mislocalization Underlies Aβ42-Induced Neuronal Dysfunction in a Drosophila Model of Alzheimer's Disease

The amyloid-β 42 (Aβ42) is thought to play a central role in the pathogenesis of Alzheimer's disease (AD). However, the molecular mechanisms by which Aβ42 induces neuronal dysfunction and degeneration remain elusive. Mitochondrial dysfunctions are implicated in AD brains. Whether mitochondrial dysfunctions are merely a consequence of AD pathology, or are early seminal events in AD pathogenesis remains to be determined. Here, we show that Aβ42 induces mitochondrial mislocalization, which contributes to Aβ42-induced neuronal dysfunction in a transgenic Drosophila model. In the Aβ42 fly brain, mitochondria were reduced in axons and dendrites, and accumulated in the somata without severe mitochondrial damage or neurodegeneration. In contrast, organization of microtubule or global axonal transport was not significantly altered at this stage. Aβ42-induced behavioral defects were exacerbated by genetic reductions in mitochondrial transport, and were modulated by cAMP levels and PKA activity. Levels of putative PKA substrate phosphoproteins were reduced in the Aβ42 fly brains. Importantly, perturbations in mitochondrial transport in neurons were sufficient to disrupt PKA signaling and induce late-onset behavioral deficits, suggesting a mechanism whereby mitochondrial mislocalization contributes to Aβ42-induced neuronal dysfunction. These results demonstrate that mislocalization of mitochondria underlies the pathogenic effects of Aβ42 in vivo

Radiation-induced lung toxicity in non-small-cell lung cancer: Understanding the interactions of clinical factors and cytokines with the dose-toxicity relationship

BACKGROUND AND PURPOSE: Current methods to estimate risk of radiation-induced lung toxicity (RILT) rely on dosimetric parameters. We aimed to improve prognostication by incorporating clinical and cytokine data, and to investigate how these factors may interact with the effect of mean lung dose (MLD) on RILT. MATERIALS AND METHODS: Data from 125 patients treated from 2004 to 2013 with definitive radiotherapy for stages I-III NSCLC on four prospective clinical trials were analyzed. Plasma levels of 30 cytokines were measured pretreatment, and at 2 and 4weeks midtreatment. Penalized logistic regression models based on combinations of MLD, clinical factors, and cytokine levels were developed. Cross-validated estimates of log-likelihood and area under the receiver operating characteristic curve (AUC) were used to assess accuracy. RESULTS: In prognosticating grade 3 or greater RILT by MLD alone, cross-validated log-likelihood and AUC were -28.2 and 0.637, respectively. Incorporating clinical features and baseline cytokine levels increased log-likelihood to -27.6 and AUC to 0.669. Midtreatment cytokine data did not further increase log-likelihood or AUC. Of the 30 cytokines measured, higher levels of 13 decreased the effect of MLD on RILT, corresponding to a lower odds ratio for RILT per Gy MLD, while higher levels of 4 increased the association. CONCLUSIONS: Although the added prognostic benefit from cytokine data in our model was modest, understanding how clinical and biologic factors interact with the MLD-RILT relationship represents a novel framework for understanding and investigating the multiple factors contributing to radiation-induced toxicity

Developing and Validating a New Multi-Dimensional Scale for Anti-Social Behaviour in a Higher Education Setting

The purpose of this research is to construct and validate a multi-dimensional scale of Anti-social Behaviour (hereafter ASB) in a Western higher education context (i.e. USA). To achieve this, four studies, each with a different sample, were performed. Study 1 (n = 150) followed an exploratory design to generate a pool of potential items measuring ASB. Study 2 (n = 254) explored the dimensionality of the items produced in Study 1 using Exploratory Factor Analysis (EFA) and reliability measures. Study 3 (n = 654) confirmed the factorial structure from Study 2 and assessed the measurement model invariance using structural equation modelling (SEM). Finally, Study 4 (n = 287) assessed the predictive validity of the ASB measure through testing a hypothetical path model linking ASB to narcissism and Machiavellianism via an SEM procedure. In total, our research findings conclude that the ASB measurement model is a two-factor multi-dimensional structure comprising: Interpersonal Antagonistic Behaviour (six items) as well as Indirect Distractive Behaviour (four items). The research and practical implications for universities are thereafter discussed

Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer

Pancreatic stellate cells (PSCs) differentiate into cancer-associated fibroblasts (CAFs) that produce desmoplastic stroma, thereby modulating disease progression and therapeutic response in pancreatic ductal adenocarcinoma (PDA). However, it is unknown whether CAFs uniformly carry out these tasks or if subtypes of CAFs with distinct phenotypes in PDA exist. We identified a CAF subpopulation with elevated expression of alpha-smooth muscle actin (alphaSMA) located immediately adjacent to neoplastic cells in mouse and human PDA tissue. We recapitulated this finding in co-cultures of murine PSCs and PDA organoids, and demonstrated that organoid-activated CAFs produced desmoplastic stroma. The co-cultures showed cooperative interactions and revealed another distinct subpopulation of CAFs, located more distantly from neoplastic cells, which lacked elevated alphaSMA expression and instead secreted IL6 and additional inflammatory mediators. These findings were corroborated in mouse and human PDA tissue, providing direct evidence for CAF heterogeneity in PDA tumor biology with implications for disease etiology and therapeutic development

Aβ42 Mutants with Different Aggregation Profiles Induce Distinct Pathologies in Drosophila

Aggregation of the amyloid-β-42 (Aβ42) peptide in the brain parenchyma is a pathological hallmark of Alzheimer's disease (AD), and the prevention of Aβ aggregation has been proposed as a therapeutic intervention in AD. However, recent reports indicate that Aβ can form several different prefibrillar and fibrillar aggregates and that each aggregate may confer different pathogenic effects, suggesting that manipulation of Aβ42 aggregation may not only quantitatively but also qualitatively modify brain pathology. Here, we compare the pathogenicity of human Aβ42 mutants with differing tendencies to aggregate. We examined the aggregation-prone, EOFAD-related Arctic mutation (Aβ42Arc) and an artificial mutation (Aβ42art) that is known to suppress aggregation and toxicity of Aβ42 in vitro. In the Drosophila brain, Aβ42Arc formed more oligomers and deposits than did wild type Aβ42, while Aβ42art formed fewer oligomers and deposits. The severity of locomotor dysfunction and premature death positively correlated with the aggregation tendencies of Aβ peptides. Surprisingly, however, Aβ42art caused earlier onset of memory defects than Aβ42. More remarkably, each Aβ induced qualitatively different pathologies. Aβ42Arc caused greater neuron loss than did Aβ42, while Aβ42art flies showed the strongest neurite degeneration. This pattern of degeneration coincides with the distribution of Thioflavin S-stained Aβ aggregates: Aβ42Arc formed large deposits in the cell body, Aβ42art accumulated preferentially in the neurites, while Aβ42 accumulated in both locations. Our results demonstrate that manipulation of the aggregation propensity of Aβ42 does not simply change the level of toxicity, but can also result in qualitative shifts in the pathology induced in vivo

Brisbane's Creative Industries 2003

EXECUTIVE SUMMARY\ud The BRISBANE’S CREATIVE INDUSTRIES 2003 report is a project commissioned by the Brisbane\ud City Council. This report is divided into 5 sections:\ud 1. Creative Industries – A Brief Overview\ud 2. Employment in the Creative Industries\ud 3. Financial Dimensions\ud 4. The Brisbane "Hotspots"\ud 5. Conclusions\ud The first section, "Creative Industries – A Brief Overview", presents:\ud A definition of the creative industries, building on sectors outlined by the UK Creative\ud Industries Task Force, and based in the Australian Culture and Leisure Classifications produced by the Australian Bureau of Statistics.\ud The second section, "Employment in the Creative Industries", assesses these dimensions of creative industries in Brisbane in comparison with state, national and global data. This section indicates that: Total employment in the creative industries in the seven main capital cities is 225,905. Brisbane has 25,324 workers employed in the creative industries, which corresponds to 11.2% of all creative industries workers in the seven main capital cities and 3.4% of the working population of Brisbane, compared to the national average of 4.2%. \ud \ud The relative size of each sector as a percentage of those employed in the creative industries in Brisbane is: Literature and Print Media (31.1%), Performing Arts (5.1%), Music Composition and Publishing (2.1%), Visual Arts and Crafts (5.1%), Design (26.3%), Broadcasting, Electronic Media and Film (17.4%), Other Arts (1.7%), and Heritage (11.2%). Creative occupations with the largest employment are 2121 Architects and Landscape Architects (1,230 persons), 2533 Designers and Illustrators (1,107 persons), and 2534 Journalists and Related Professions (914 persons).\ud \ud • Creative industries workers on average earn higher incomes than non-creative industries\ud workers. Median individual weekly incomes are much less for Brisbane creative industries workers ($666)than their counterparts in Sydney ($838), Melbourne ($763) and Canberra ($814). Broadcasting, Electronic Media and Film provides the highest individual weekly median income.\ud \ud • Between 1996 and 2001, Brisbane experienced a decline in the numbers of persons employed in the Performing Arts (-2.7%), Heritage (-8.8%), and Music Composition and Publishing (-9.1%), and an increase in the numbers of persons employed in Other Arts (19.8%), Broadcasting, Electronic Media and Film (12.5%), Design (5.8%) and Visual Arts and Crafts (5.6%).\ud \ud The third section, "Financial Dimensions", describes the financial characteristics associated with the creative industries activities across all eight creative industries sectors and concludes with the following significant findings:\ud • Based on 1996-1997 data, the industry sectors with highest potential for financial growth were Film and Video Production and Distribution, and Music and Theatre Productions. The sectors with the highest potential for employment growth were Architectural Services, Film and Video Production and Distribution, and Music and Theatre Productions.\ud • The activities with the largest profit margin are commercial television services (24.6%), manufacture of recorded music (16.3%), studio sound recording (13.8%) and motion picture distribution (11.4%).\ud • Australia-wide, the creative industries attracted 4,027.2m in funding from across the three levels of government in 2000-2001.\ud • The Queensland state government provided 288.5m in funding to the creative industries in 2000-2001, of which 87.1% was allocated to Heritage, 6.9% to Performing Arts Venues, and 4.7% to Performing Arts.\ud The fourth section, "The Brisbane Hotspots", outlines existing and emerging hotspots of Brisbane’s creative industries and indicates that:\ud • The data confirm that Brisbane does not have true creative industries clusters but does have the capacity for development and, given the appropriate forms of intervention and investment, true creative industries clusters are likely to form.\ud • The overall strengths of Queensland’s creative industries are seen as the presence of highly talented individuals, high levels of innovation, strong government support for the sector, competitive prices for creative output and a culture that values diversity and enthusiasm.\ud • Queensland’s creative industries weaknesses are identified as the small size of demand in the local market, lack of critical mass, weaknesses in some skills (such as script-writing, business and marketing), lack of an entrepreneurial culture, failure to network and collaborate, remoteness from major markets and limited access to capital.\ud • Brisbane has identifiable creative industries hotspots including: Craft, Design, and Visual Arts;\ud Games and Leisure Software; Contemporary Music; Film and Television; and Performing Arts.\ud The fifth section, "Conclusions", integrates the data presented on Brisbane’s creative industries:\ud • The creative industries in Brisbane are relatively small.\ud • The largest industries are based in Literature and Print Media; Design; and Broadcasting, Electronic Media and Film.\ud • The focus of Brisbane’s creative industries is primarily to the local market, whereas a stronger\ud interstate and international focus is required for strong economic impact to develop.\ud • Current methodologies based upon ABS data to identify the creative industries under-report emerging industries, particularly those industries based in new media and IT