Global analysis of serum microRNAs as potential biomarkers for lung adenocarcinoma

Early diagnosis and the ability to predict the most relevant treatment option for individuals is essential to improve clinical outcomes for non-small cell lung cancer (NSCLC) patients. Adenocarcinoma (ADC), a subtype of NSCLC, is the single biggest cancer killer and therefore an urgent need to identify minimally invasive biomarkers to enable early diagnosis. Recent studies, by ourselves and others, indicate that circulating miRNA s have potential as biomarkers. Here we applied global profiling approaches in serum from patients with ADC of the lung to explore if miRNA s have potential as diagnostic biomarkers. This study involved RNA isolation from 80 sera specimens including those from ADC patients (equal numbers of stages 1, 2, 3, and 4) and age- and gender-matched controls (n = 40 each). Six hundred and sixty-seven miRNA s were co-analyzed in these specimens using TaqMan low density arrays and qPCR validation using individual miRNA s. Overall, approximately 390 and 370 miRNA s were detected in ADC and control sera, respectively. A group of 6 miRNA s, miR-30c-1* (AU C = 0.74; P < 0.002), miR-616(AU C = 0.71; P = 0.001), miR-146b-3p (AU C = 0.82; P < 0.0001), miR-566 (AU C = 0.80; P < 0.0001), miR-550 (AU C = 0.72; P = 0.0006), and miR-939 (AU C = 0.82; P < 0.0001) was found to be present at substantially higher levels in ADC compared with control sera. Conversely, miR-339-5p and miR-656 were detected at substantially lower levels in ADC sera (co-analysis resulting in AU C = 0.6; P = 0.02). Differences in miRNA profile identified support circulating miRNA s having potential as diagnostic biomarkers for ADC. More extensive studies of ADC and control serum specimens are warranted to independently validate the potential clinical relevance of these miRNA s as minimally invasive biomarkers for ADC.

Prognostic and therapeutic relevance of FLIP and procaspase-8 overexpression in non-small cell lung cancer

Non-small cell lung carcinoma remains by far the leading cause of cancer-related deaths worldwide. Overexpression of FLIP, which blocks the extrinsic apoptotic pathway by inhibiting caspase-8 activation, has been identified in various cancers. We investigated FLIP and procaspase-8 expression in NSCLC and the effect of HDAC inhibitors on FLIP expression, activation of caspase-8 and drug resistance in NSCLC and normal lung cell line models. Immunohistochemical analysis of cytoplasmic and nuclear FLIP and procaspase-8 protein expression was carried out using a novel digital pathology approach. Both FLIP and procaspase-8 were found to be significantly overexpressed in tumours, and importantly, high cytoplasmic expression of FLIP significantly correlated with shorter overall survival. Treatment with HDAC inhibitors targeting HDAC1-3 downregulated FLIP expression predominantly via post-transcriptional mechanisms, and this resulted in death receptor- and caspase-8-dependent apoptosis in NSCLC cells, but not normal lung cells. In addition, HDAC inhibitors synergized with TRAIL and cisplatin in NSCLC cells in a FLIP- and caspase-8-dependent manner. Thus, FLIP and procaspase-8 are overexpressed in NSCLC, and high cytoplasmic FLIP expression is indicative of poor prognosis. Targeting high FLIP expression using HDAC1-3 selective inhibitors such as entinostat to exploit high procaspase-8 expression in NSCLC has promising therapeutic potential, particularly when used in combination with TRAIL receptor-targeted agents.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Toxic state–corporate crimes, Neo-liberalism and green criminology : the hazards and legacies of the oil, chemical and mineral industries

This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.

Comparing female victims of separation/divorce assault across geographical regions

Recent analyses of National Crime Victimization Survey (NCVS) data show that male-to-female separation/divorce assault varies across geographic regions in the United States, with rural rates of such woman abuse being higher than those for suburban and urban areas. Using the same data set, the main objective of this paper is to present the results of an investigation into whether characteristics of female victims of separation/divorce assault also differ across urban, suburban, and rural communities.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Where are all the female participants in sports and exercise medicine research?

The aim of this study is to estimate the ratio of male and female participants in Sports and Exercise Medicine research. Original research articles published in three major Sports and Exercise Medicine journals (Medicine and Science in Sport and Exercise, British Journal of Sports Medicine and American Journal of Sports Medicine) over a three year period were examined. Each article was screened to determine the following: total number of participants, the number of female participants and the number of male participants. The percentage of females and males per article in each of the journals was also calculated. Cross tabulations and Chi square analysis were used to compare the gender representation of participants within each of the journals. Data were extracted from 1, 382 articles involving a total of 6, 076, 705 participants. 2, 366, 998 (39%) participants were female and 3, 709, 707 (61%) male. The average percentage of female participants per article across the journals ranged from 35-37%. Females were significantly under-represented across all of the journals (X2 =23566, df=2, p<0.00001). There were no significant differences between the three journals. In conclusion, Sports and Exercise Medicine practitioners should be cognisant of sexual dimorphism and gender disparity in the current literature.

Normal human mammary epithelial cells spontaneously escape senescence and acquire genomic changes

Senescence and genomic integrity are thought to be important barriers in the development of malignant lesions. Human fibroblasts undergo a limited number of cell divisions before entering an irreversible arrest, called senescence. Here we show that human mammary epithelial cells (HMECs) do not conform to this paradigm of senescence. In contrast to fibroblasts, HMECs exhibit an initial growth phase that is followed by a transient growth plateau (termed selection or M0; refs 3-5), from which proliferative cells emerge to undergo further population doublings (approximately 20-70), before entering a second growth plateau (previously termed senescence or M1; refs 4-6). We find that the first growth plateau exhibits characteristics of senescence but is not an insurmountable barrier to further growth. HMECs emerge from senescence, exhibit eroding telomeric sequences and ultimately enter telomere-based crisis to generate the types of chromosomal abnormalities seen in the earliest lesions of breast cancer. Growth past senescent barriers may be a pivotal event in the earliest steps of carcinogenesis, providing many genetic changes that predicate oncogenic evolution. The differences between epithelial cells and fibroblasts provide new insights into the mechanistic basis of neoplastic transformation.

Loss of chromosomal integrity in human mammary epithelial cells subsequent to escape from senescence

The genomic changes that foster cancer can be either genetic or epigenetic in nature. Early studies focused on genetic changes and how mutational events contribute to changes in gene expression. These point mutations, deletions and amplifications are known to activate oncogenes and inactivate tumor suppressor genes. More recently, multiple epigenetic changes that can have a profound effect on carcinogenesis have been identified. These epigenetic events, such as the methylation of promoter sequences in genes, are under active investigation. In this review we will describe a methylation event that occurs during the propagation of human mammary epithelial cells (HMEC) in culture and detail the accompanying genetic alterations that have been observed.

Gelatine methacrylamide-based hydrogels : an alternative three-dimensional cancer cell culture system

Modern cancer research requires physiological, three-dimensional (3-D) cell culture platforms, wherein the physical and chemical characteristics of the extracellular matrix (ECM) can be modified. In this study, gelatine methacrylamide (GelMA)-based hydrogels were characterized and established as in vitro and in vivo spheroid-based models for ovarian cancer, reflecting the advanced disease stage of patients, with accumulation of multicellular spheroids in the tumour fluid (ascites). Polymer concentration (2.5-7% w/v) strongly influenced hydrogel stiffness (0.5±0.2kPa to 9.0±1.8kPa) but had little effect on solute diffusion. The diffusion coefficient of 70kDa fluorescein isothiocyanate (FITC)-labelled dextran in 7% GelMA-based hydrogels was only 2.3 times slower compared to water. Hydrogels of medium concentration (5% w/v GelMA) and stiffness (3.4kPa) allowed spheroid formation and high proliferation and metabolic rates. The inhibition of matrix metalloproteinases and consequently ECM degradability reduced spheroid formation and proliferation rates. The incorporation of the ECM components laminin-411 and hyaluronic acid further stimulated spheroid growth within GelMA-based hydrogels. The feasibility of pre-cultured GelMA-based hydrogels as spheroid carriers within an ovarian cancer animal model was proven and led to tumour development and metastasis. These tumours were sensitive to treatment with the anti-cancer drug paclitaxel, but not the integrin antagonist ATN-161. While paclitaxel and its combination with ATN-161 resulted in a treatment response of 33-37.8%, ATN-161 alone had no effect on tumour growth and peritoneal spread. The semi-synthetic biomaterial GelMA combines relevant natural cues with tunable properties, providing an alternative, bioengineered 3-D cancer cell culture in in vitro and in vivo model systems.

The fragmentation pathways of protonated Amiton in the gas phase : towards the structural characterisation of organophosphorus chemical warfare agents by electrospray ionisation tandem mass spectrometry

Amiton (O,O-diethyl-S-[2-(diethylamino)ethyl]phosphorothiolate), otherwise known as VG, is listed in schedule 2 of the Chemical Weapons Convention (CWC) and has a structure closely related to VX (O-ethyl-S-(2-diisopropylamino)ethylmethylphosphonothiolate). Fragmentation of protonated VG in the gas phase was performed using electrospray ionisation ion trap mass spectrometry (ESI-ITMS) and revealed several characteristic product ions. Quantum chemical calculations provide the most probable structures for these ions as well as the likely unimolecular mechanisms by which they are formed. The decomposition pathways predicted by computation are consistent with deuterium-labeling studies. The combination of experimental and theoretical data suggests that the fragmentation pathways of VG and analogous organophosphorus nerve agents, such as VX and Russian VX, are predictable and thus ESI tandem mass spectrometry is a powerful tool for the verification of unknown compounds listed in the CWC. Copyright (c) 2006 Commonwealth of Australia. Published by John Wiley & Sons, Ltd.

Correlates of female sexual functioning : adult attachment and differentiation of self

Introduction Female sexual functioning is affected by a range of factors including motivation, psychological well-being, and relationship issues. In understanding female sexual dysfunction (FSD), there has been a tendency to privilege diagnostic and medical over relationship issues. Aim To investigate the association between women’s experience of intimacy in close relationships - operationalized in terms of attachment and degree of differentiation of self - and FSD. Methods Two hundred and thirty sexually active Australian women responded to an invitation to complete a set of validated scales to assess potential correlates of sexual functioning. Main Outcome Measures The Female Sexuality Function Index, the Experiences in Close Relationships Scale, the Differentiation of Self Inventory, as well as a set of study-specific questions were subject to hierarchical multiple regression analyses Results Relational variables of attachment avoidance and to a lesser degree, attachment anxiety were associated with FSD. Participants with lower levels of differentiation of self were more likely to report sexual difficulties. The inability to maintain a sense of self in the presence of intimate others was the strongest predictors of sexual problems. A history of sexual abuse in adulthood and higher levels of psychological distress were also associated with sexual difficulties. Conclusions The findings provide support for a relational understanding of female sexual functioning. Attachment avoidance, attachment anxiety, and degree of differentiation of self are shown to be associated with sexual difficulties. The findings support the need to focus on relational and psychological factors in women’s experience of sex.

Interaction of psychosocial risk factors explain increased neck problems among female office workers

This study investigated the relationship between psychosocial risk factors and (1) neck symptoms and (2) neck pain and disability as measured by the neck disability index (NDI). Female office workers employed in local private and public organizations were invited to participate, with 333 completing a questionnaire. Data were collected on various risk factors including age, negative affectivity, history of previous neck trauma, physical work environment, and task demands. Sixty-one percent of the sample reported neck symptoms lasting greater than 8 days in the last 12 months. The mean NDI of the sample was 15.5 out of 100, indicating mild neck pain and disability. In a hierarchical multivariate logistic regression, low supervisor support was the only psychosocial risk factor identified with the presence of neck symptoms. Similarly, low supervisor support was the only factor associated with the score on the NDI. These associations remained after adjustment for potential confounders of age, negative affectivity, and physical risk factors. The interaction of job demands, decision authority, and supervisor support was significantly associated with the NDI in the final model and this association increased when those with previous trauma were excluded. Interestingly, and somewhat contrary to initial expectations, as job demands increased, high decision authority had an increasing effect on the NDI when supervisor support was low.