Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth.

Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Palliative Care and Noninvasive Ventilation.

Palliative care is important for many patients who require noninvasive ventilation. The particular needs of patients with neuromuscular disease and chronic obstructive pulmonary disease are explored. Advance care planning is explored with tips for undertaking this important communication task. Brief comments regarding symptom burden, weaning, voluntary assisted dying, and self-care are included.

The prospective relationship between a-priori intentions for and patterns of e-cigarette use among adults who smoke cigarettes.

BACKGROUND: Electronic (e-)cigarettes may help adult cigarette smokers achieve cigarette cessation, depending on patterns of e-cigarette use. Among cigarette smokers who do not use e-cigarettes, it is unclear if and how a-priori intentions for use are related to uptake patterns. Longitudinal studies have focused on established e-cigarette users or adolescent and young adult populations exclusively. METHODS: Within a nationwide randomized clinical trial (N = 638), adult cigarette smokers not currently using e-cigarettes were randomized (2:1) to receive (or not) one-month sampling of e-cigarettes. An exploratory factor analysis (EFA) was performed on an established 15-item measure assessing a-priori intentions for e-cigarette use to identify latent variables. Among those receiving e-cigarette products, regression models examined relationships between intentions and: 1) uptake (yes/no), 2) frequency (number of days per week), and 3) amount (puffing episodes per day) of e-cigarette use at one-month follow-up. RESULTS: Two factors emerged from the EFA: 1) cigarette-related intentions (e.g., cigarette cessation, no smell) and 2) novel appeal of e-cigarettes (e.g., flavors). Three items remained and were treated as separate intentions: "feels like cigarette smoking", "curiosity", and "affordability". In the final multivariable models, "feel like cigarette smoking" predicted more frequent e-cigarette use (ß = 0.187, SE = 0.086, p = 0.03); however, none of the five factors/intentions were significantly associated with uptake or amount of use. CONCLUSIONS: For adult cigarette smokers not currently using e-cigarettes, a-priori intentions for using e-cigarettes might not be predictive of if or how these products will be used in the future, suggesting that motives may not drive use behavior.

Classification Accuracy of Biomarkers of Compliance.

Objectives: Evaluate the classification accuracy of biomarkers of nicotine exposure for identifying noncompliance in randomized controlled trials (RCTs) of very low nicotine content (VLNC) cigarettes. Methods: We combined data from 2 studies to evaluate the classification accuracy of biomarkers of nicotine exposure for identifying noncompliance in RCTs of VLNC cigarettes. Using a novel approach that did not require knowledge of each participant's compliance status, we modeled the distributions of total nicotine equivalents (TNE), total cotinine, and anatabine in compliant and noncompliant participants using a mixture model. Estimates of the classification accuracy were derived from the estimated densities. Results: TNE and total cotinine had near-perfect classification accuracy, but TNE had better classification accuracy than total cotinine (p = 0.03) and anatabine (p = 0.014). The classification accuracy of TNE and total cotinine decreased as self-reported study cigarettes increased; anatabine was similar, but the results were more statistically variable. Conclusions: TNE and total cotinine are better classifiers of compliance than anatabine. These results will be useful in determining biomarker thresholds for identifying noncompliance and will aid in the interpretation of future RCTs of VLNC cigarettes.