Pharmacists' role in lung health

Breathing is important. In fact, most people take on average 23,000 breaths each day. However, most of us probably take this for granted and do not notice these breaths – unless of course maybe when we are exercising, or huffing and puffing because we are running late for the bus...

Assessing the combined effect of asbestos exposure and smoking on lung cancer: a Bayesian approach

We review the literature on the combined association between lung cancer and two environmental exposures, asbestos exposure and smoking, and explore a Bayesian approach to assess evidence of interaction between the exposures. The meta-analysis combines separate indices of additive and multiplicative relationships and multivariate relative risk estimates. By making inferences on posterior probabilities we can explore both the form and strength of interaction. This analysis may be more informative than providing evidence to support one relation over another on the basis of statistical significance. Overall, we find evidence for a more than additive and less than multiplicative relation.

Prediction of masonry compressive behaviour using a damage mechanics inspired modelling method

Masonry under compression is affected by the properties of its constituents and their interfaces. In spite of extensive investigations of the behaviour of masonry under compression, the information in the literature cannot be regarded as comprehensive due to ongoing inventions of new generation products – for example, polymer modified thin layer mortared masonry and drystack masonry. As comprehensive experimental studies are very expensive, an analytical model inspired by damage mechanics is developed and applied to the prediction of the compressive behaviour of masonry in this paper. The model incorporates a parabolic progressively softening stress-strain curve for the units and a progressively stiffening stress-strain curve until a threshold strain for the combined mortar and the unit-mortar interfaces is reached. The model simulates the mutual constraints imposed by each of these constituents through their respective tensile and compressive behaviour and volumetric changes. The advantage of the model is that it requires only the properties of the constituents and considers masonry as a continuum and computes the average properties of the composite masonry prisms/wallettes; it does not require discretisation of prism or wallette similar to the finite element methods. The capability of the model in capturing the phenomenological behaviour of masonry with appropriate elastic response, stiffness degradation and post peak softening is presented through numerical examples. The fitting of the experimental data to the model parameters is demonstrated through calibration of some selected test data on units and mortar from the literature; the calibrated model is shown to predict the responses of the experimentally determined masonry built using the corresponding units and mortar quite well. Through a series of sensitivity studies, the model is also shown to predict the masonry strength appropriately for changes to the properties of the units and mortar, the mortar joint thickness and the ratio of the height of unit to mortar joint thickness. The unit strength is shown to affect the masonry strength significantly. Although the mortar strength has only a marginal effect, reduction in mortar joint thickness is shown to have a profound effect on the masonry strength. The results obtained from the model are compared with the various provisions in the Australian Masonry Structures Standard AS3700 (2011) and Eurocode 6.

Development of a transient gradient enhanced non local continuum damage mechanics model for masonry

Due to the advent of varied types of masonry systems a comprehensive failure mechanism of masonry essential for the understanding of its behaviour is impossible to be determined from experimental testing. As masonry is predominantly used in wall structures a biaxial stress state dominates its failure mechanism. Biaxial testing will therefore be necessary for each type of masonry, which is expensive and time consuming. A computational method would be advantageous; however masonry is complex to model which requires advanced computational modelling methods. This thesis has formulated a damage mechanics inspired modelling method and has shown that the method effectively determines the failure mechanisms and deformation characteristics of masonry under biaxial states of loading.

Mechanical properties and damage tolerance of Y2SiO5

Y2SiO5 has potential applications as functional-structural ceramic and environmental/thermal barrier coating material. As an important grain-boundary phase in the sintered Si3N4, it also influences the mechanical and dielectric performances of the host material. In this paper, we present the mechanical properties of Y2SiO5 including elastic moduli, hardness, strength and fracture toughness, and try to understand the mechanical features from the viewpoint of crystal structure. Y2SiO5 has low shear modulus, low hardness, as well as high capacity for dispersing mechanical damage energy and for resisting crack penetration. Particularly, it can be machined by cemented carbides tools. The crystal structure characteristics of Y2SiO5 suggest the low-energy weakly bonded atomic planes crossed only by the easily breaking Y-O bonds as well as the rotatable rigid SiO4 tetrahedra are the origins of low shear deformation, good damage tolerance and good machinability of this material. TEM observations also demonstrate that the mechanical damage energy was dispersed in the form of the micro-cleavages, stacking faults and twins along these weakly bonded atomic planes, which allows the "microscale-plasticity" for Y2SiO5.

Tumour islet Foxp3+ T-cell infiltration predicts poor outcome in nonsmall cell lung cancer

The impact of host immunity on outcome in nonsmall cell lung cancer (NSCLC) is controversial. We examined the relationship between lymphoid infiltration patterns in NSCLC and prognosis. Tumour- and stroma-infiltrating CD3+, CD8+ and forkhead box P3 (Foxp3)+ T-lymphocytes were identified using immunohistochemistry and a novel image analysis algorithm to assess total, cytotoxic and regulatory T-lymphocyte counts, respectively, in 196 NSCLC cases. The median cell count was selected as a cut-point to define patient subgroups and the ratio of the corresponding tumour islet:stroma (TI/S) counts was determined. There was a positive association between overall survival and increased CD8+ TI/S ratio (hazard ratio (HR) for death 0.44, p<0.001) but an inverse relationship between Foxp3+ TI/S ratio and overall survival (HR 4.86, p<0.001). Patients with high CD8+ islet (HR 0.48, p<0.001) and Foxp3+ stromal (HR 0.23, p<0.001) counts had better survival, whereas high CD3+ and CD8+ stromal counts and high Foxp3+ islet infiltration conferred a worse survival (HR 1.55, 2.19 and 3.14, respectively). By multivariate analysis, a high CD8+ TI/S ratio conferred an improved survival (HR 0.48, p=0.002) but a high Foxp3+ TI/S ratio was associated with worse survival (HR 3.91, p<0.001). Microlocalisation of infiltrating T-lymphocytes is a powerful predictor of outcome in resected NSCLC.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

Investigation of the interaction between non-small cell lung cancer cells and immortalised normal bronchial epithelial cells

Non-small cell lung cancer consists of a diverse range of molecular and pathological features. This may be due in part to the critical interaction between normal and lung cancer cells. Consequently resulting in ‘normal’ cells acting in a malignant fashion. This project aims to identify pathways responsible for this altered ‘normal’ behaviour.

Examination of EXOSC4 as a new prognostic marker and a novel therapeutic avenue in lung adenocarcinoma

Although prevention and early detection of the disease greatly improved over the past few years, lung cancer remains the leading cause of cancer deaths. In order to be able to treat a larger population, we are in urgent need for novel treatments. While it is known that DNA repair genes play a major role in the oncogenic transformation, they also represent a weakness of cancers that constitute a therapeutic opportunity. To identify novel DNA repair genes implicated in Lung cancers, we conducted an in silico investigation to identify genes co-regulated with two DNA repair factors, BRCA2 and hSSB1. This approach allowed for the identification of EXOSC4, a component of the RNA Exosome machinery, as a potential factor involved in the maintenance of genome stability and that is deregulated in lung cancer.

CDCA3 regulates the cell cycle and modulates cisplatin sensitivity in non-small cell lung cancer

Cisplatin-based regimens are currently the most effective chemotherapy for non-small cell lung cancer (NSCLC). Cisplatin forms DNA crosslinks to stall DNA replication and induce apoptosis. However, intrinsic and acquired chemoresistance is a major therapeutic problem. We have identified ‘cell division cycle associated protein 3’ (CDCA3) as a novel protein that may prove useful in delaying or preventing cisplatin resistance in NSCLC. CDCA3 functions as part of an ubiquitin ligase complex to degrade the endogenous cell cycle inhibitors. While a role for CDCA3 in disease is emerging with elevated expression noted in oral squamous cell carcinoma, little else is known about CDCA3 or whether this protein may prove useful clinically.

Inflammatory meditated mechanisms of cisplatin resistance in non-small cell lung cancer

The majority of non-small cell lung cancer (NSCLC) patients present with advanced stage disease, where chemotherapy is usually the most common treatment option. While somewhat effective, patients treated with cisplatin-based chemotherapy will eventually develop resistance. Multiple pathways have been implicated in chemo-resistance, however the critical underlying mechanisms have yet to be elucidated. The aim of this project is to determine the role of inflammatory mediators in cisplatin resistance.

The overexpression of SASH1 stimulates cell death in lung cancer cells

SASH1 (SAM and SH3 domain-containing protein 1) is a recently identified gene with tumour suppressor properties with a role in the induction of apoptosis. Previous work has shown that 90% of lung cell lines have a decrease in SASH1 mRNA levels, however little characterisation of SASH1 function in lung cancer has been undertaken.

Afatinib versus gefitinib as first-line treatment of patients with EGFR mutation-positive non-small-cell lung cancer (LUX-Lung 7): a phase 2B, open-label, randomised controlled trial

Background The irreversible ErbB family blocker afatinib and the reversible EGFR tyrosine kinase inhibitor gefitinib are approved for first-line treatment of EGFR mutation-positive non-small-cell lung cancer (NSCLC). We aimed to compare the efficacy and safety of afatinib and gefitinib in this setting. Methods This multicentre, international, open-label, exploratory, randomised controlled phase 2B trial (LUX-Lung 7) was done at 64 centres in 13 countries. Treatment-naive patients with stage IIIB or IV NSCLC and a common EGFR mutation (exon 19 deletion or Leu858Arg) were randomly assigned (1:1) to receive afatinib (40 mg per day) or gefitinib (250 mg per day) until disease progression, or beyond if deemed beneficial by the investigator. Randomisation, stratified by EGFR mutation type and status of brain metastases, was done centrally using a validated number generating system implemented via an interactive voice or web-based response system with a block size of four. Clinicians and patients were not masked to treatment allocation; independent review of tumour response was done in a blinded manner. Coprimary endpoints were progression-free survival by independent central review, time-to-treatment failure, and overall survival. Efficacy analyses were done in the intention-to-treat population and safety analyses were done in patients who received at least one dose of study drug. This ongoing study is registered with ClinicalTrials.gov, number NCT01466660. Findings Between Dec 13, 2011, and Aug 8, 2013, 319 patients were randomly assigned (160 to afatinib and 159 to gefitinib). Median follow-up was 27·3 months (IQR 15·3–33·9). Progression-free survival (median 11·0 months [95% CI 10·6–12·9] with afatinib vs 10·9 months [9·1–11·5] with gefitinib; hazard ratio [HR] 0·73 [95% CI 0·57–0·95], p=0·017) and time-to-treatment failure (median 13·7 months [95% CI 11·9–15·0] with afatinib vs 11·5 months [10·1–13·1] with gefitinib; HR 0·73 [95% CI 0·58–0·92], p=0·0073) were significantly longer with afatinib than with gefitinib. Overall survival data are not mature. The most common treatment-related grade 3 or 4 adverse events were diarrhoea (20 [13%] of 160 patients given afatinib vs two [1%] of 159 given gefitinib) and rash or acne (15 [9%] patients given afatinib vs five [3%] of those given gefitinib) and liver enzyme elevations (no patients given afatinib vs 14 [9%] of those given gefitinib). Serious treatment-related adverse events occurred in 17 (11%) patients in the afatinib group and seven (4%) in the gefitinib group. Ten (6%) patients in each group discontinued treatment due to drug-related adverse events. 15 (9%) fatal adverse events occurred in the afatinib group and ten (6%) in the gefitinib group. All but one of these deaths were considered unrelated to treatment; one patient in the gefitinib group died from drug-related hepatic and renal failure. Interpretation Afatinib significantly improved outcomes in treatment-naive patients with EGFR-mutated NSCLC compared with gefitinib, with a manageable tolerability profile. These data are potentially important for clinical decision making in this patient population.