Background: Cannabis is the most widely used illegal drug worldwide. Long-term use of cannabis is known to cause chronic bronchitis and airflow obstruction, but the prevalence of macroscopic emphysema, the doseresponse relationship and the dose equivalence of cannabis with tobacco has not been determined. Methods: A convenience sample of adults from the Greater Wellington region was recruited into four smoking groups: cannabis only, tobacco only, combined cannabis and tobacco and non-smokers of either substance. Their respiratory status was assessed using high-resolution CT (HRCT) scanning, pulmonary function tests and a respiratory and smoking questionnaire. Associations between respiratory status and cannabis use were examined by analysis of covariance and logistic regression. Results: 339 subjects were recruited into the four groups. A dose-response relationship was found between cannabis smoking and reduced forced expiratory volume in 1 s to forced vital capacity ratio and specific airways conductance, and increased total lung capacity. For measures of airflow obstruction, one cannabis joint had a similar effect to 2.5-5 tobacco cigarettes. Cannabis smoking was associated with decreased lung density on HRCT scans. Macroscopic emphysema was detected in 1/75 (1.3%), 15/92 (16.3%), 17/91 (18.9%) and 0/81 subjects in the cannabis only, combined cannabis and tobacco, tobacco alone and nonsmoking groups, respectively. Conclusions: Smoking cannabis was associated with a dose-related impairment of large airways function resulting in airflow obstruction and hyperinflation. In contrast, cannabis smoking was seldom associated with macroscopic emphysema. The 1:2.5-5 dose equivalence between cannabis joints and tobacco cigarettes for adverse effects on lung function is of major public health significance.

The reference ranges presented may be used to assist in the interpretation of Fe(NO) measurements in white adults.

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BackgroundColorectal cancer (CRC) is a heterogeneous and biologically poorly understood disease. To tailor CRC treatment, it is essential to first model this heterogeneity by defining subtypes of patients with homogeneous biological and clinical characteristics and second match these subtypes to cell lines for which extensive pharmacological data is available, thus linking targeted therapies to patients most likely to respond to treatment.MethodsWe applied a new unsupervised, iterative approach to stratify CRC tumor samples into subtypes based on genome-wide mRNA expression data. By applying this stratification to several CRC cell line panels and integrating pharmacological response data, we generated hypotheses regarding the targeted treatment of different subtypes.ResultsIn agreement with earlier studies, the two dominant CRC subtypes are highly correlated with a gene expression signature of epithelial-mesenchymal-transition (EMT). Notably, further dividing these two subtypes using iNMF (iterative Non-negative Matrix Factorization) revealed five subtypes that exhibit activation of specific signaling pathways, and show significant differences in clinical and molecular characteristics. Importantly, we were able to validate the stratification on independent, published datasets comprising over 1600 samples. Application of this stratification to four CRC cell line panels comprising 74 different cell lines, showed that the tumor subtypes are well represented in available CRC cell line panels. Pharmacological response data for targeted inhibitors of SRC, WNT, GSK3b, aurora kinase, PI3 kinase, and mTOR, showed significant differences in sensitivity across cell lines assigned to different subtypes. Importantly, some of these differences in sensitivity were in concordance with high expression of the targets or activation of the corresponding pathways in primary tumor samples of the same subtype.ConclusionsThe stratification presented here is robust, captures important features of CRC, and offers valuable insight into functional differences between CRC subtypes. By matching the identified subtypes to cell line panels that have been pharmacologically characterized, it opens up new possibilities for the development and application of targeted therapies for defined CRC patient sub-populations.

The aim of the present study was to determine the risk of lung cancer associated with cannabis smoking.A case-control study of lung cancer in adults f55 yrs of age was conducted in eight district health boards in New Zealand. Cases were identified from the New Zealand Cancer Registry and hospital databases. Controls were randomly selected from the electoral roll, with frequency matching to cases in 5-yr age groups and district health boards. Interviewer-administered questionnaires were used to assess possible risk factors, including cannabis use. The relative risk of lung cancer associated with cannabis smoking was estimated by logistic regression.In total, 79 cases of lung cancer and 324 controls were included in the study. The risk of lung cancer increased 8% (95% confidence interval (CI) 2-15) for each joint-yr of cannabis smoking, after adjustment for confounding variables including cigarette smoking, and 7% (95% CI 5-9) for each pack-yr of cigarette smoking, after adjustment for confounding variables including cannabis smoking. The highest tertile of cannabis use was associated with an increased risk of lung cancer (relative risk 5.7 (95% CI 1.5-21.6)), after adjustment for confounding variables including cigarette smoking.In conclusion, the results of the present study indicate that long-term cannabis use increases the risk of lung cancer in young adults.

Electronically recorded frequency of current salbutamol use is a strong predictor of risk of future adverse outcomes in asthma, with average daily use performing the best. These findings provide new information for clinicians considering metrics of salbutamol as predictors of future adverse outcomes in asthma.

CT lung density measurements cannot reliably detect the presence of emphysema in an individual. We recommend further investigation into lung density measurements before their widespread use in clinical practice.

Self-report is inaccurate in measuring actual use of inhaled asthma treatment with patients who underuse their maintenance therapy overreporting their use and those who overuse their therapy underreporting their use.