Consequences of Hyperoxia and the Toxicity of Oxygen in the Lung

Oxygen (O2) is life essential but as a drug has a maximum positive biological benefit and accompanying toxicity effects. Oxygen is therapeutic for treatment of hypoxemia and hypoxia associated with many pathological processes. Pathophysiological processes are associated with increased levels of hyperoxia-induced reactive O2 species (ROS) which may readily react with surrounding biological tissues, damaging lipids, proteins, and nucleic acids. Protective antioxidant defenses can become overwhelmed with ROS leading to oxidative stress. Activated alveolar capillary endothelium is characterized by increased adhesiveness causing accumulation of cell populations such as neutrophils, which are a source of ROS. Increased levels of ROS cause hyperpermeability, coagulopathy, and collagen deposition as well as other irreversible changes occurring within the alveolar space. In hyperoxia, multiple signaling pathways determine the pulmonary cellular response: apoptosis, necrosis, or repair. Understanding the effects of O2 administration is important to prevent inadvertent alveolar damage caused by hyperoxia in patients requiring supplemental oxygenation

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma:leveraging proteomics and machine learning for biomarker discovery

BACKGROUND: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma.METHODS: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony.FINDINGS: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively.INTERPRETATION: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted.FUNDING: Cancer Research UK, Blood Cancer UK, National Institute for Health Research.</p

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma:leveraging proteomics and machine learning for biomarker discovery

BACKGROUND: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma.METHODS: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony.FINDINGS: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively.INTERPRETATION: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted.FUNDING: Cancer Research UK, Blood Cancer UK, National Institute for Health Research.</p

Climate and Landscape Factors Associated with Buruli Ulcer Incidence in Victoria, Australia

Background Buruli ulcer (BU), caused by Mycobacterium ulcerans (M. ulcerans), is a necrotizing skin disease found in more than 30 countries worldwide. BU incidence is highest in West Africa; however, cases have substantially increased in coastal regions of southern Australia over the past 30 years. Although the mode of transmission remains uncertain, the spatial pattern of BU emergence in recent years seems to suggest that there is an environmental niche for M. ulcerans and BU prevalence. Methodology/Principal Findings Network analysis was applied to BU cases in Victoria, Australia, from 1981–2008. Results revealed a non-random spatio-temporal pattern at the regional scale as well as a stable and efficient BU disease network, indicating that deterministic factors influence the occurrence of this disease. Monthly BU incidence reported by locality was analyzed with landscape and climate data using a multilevel Poisson regression approach. The results suggest the highest BU risk areas occur at low elevations with forested land cover, similar to previous studies of BU risk in West Africa. Additionally, climate conditions as far as 1.5 years in advance appear to impact disease incidence. Warmer and wetter conditions 18–19 months prior to case emergence, followed by a dry period approximately 5 months prior to case emergence seem to favor the occurrence of BU. Conclusions/Significance The BU network structure in Victoria, Australia, suggests external environmental factors favor M. ulcerans transmission and, therefore, BU incidence. A unique combination of environmental conditions, including land cover type, temperature and a wet-dry sequence, may produce habitat characteristics that support M. ulcerans transmission and BU prevalence. These findings imply that future BU research efforts on transmission mechanisms should focus on potential vectors/reservoirs found in those environmental niches. Further, this study is the first to quantitatively estimate environmental lag times associated with BU outbreaks, providing insights for future transmission investigations.This project was supported by the World Health Organization and the National Institutes of Health and Fogarty International Center (NIH - R01TW007550). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Fogarty International Center or the National Institutes of Health. R.W. Merritt is gratefully acknowledged for supporting this research as part of NIH grant R01TW007550

Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women

BackgroundA non-invasive endometrial cancer detection tool that can accurately triage symptomatic women for definitive testing would improve patient care. Urine is an attractive biofluid for cancer detection due to its simplicity and ease of collection. The aim of this study was to identify urine-based proteomic signatures that can discriminate endometrial cancer patients from symptomatic controls.MethodsThis was a prospective case–control study of symptomatic post-menopausal women (50 cancers, 54 controls). Voided self-collected urine samples were processed for mass spectrometry and run using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning techniques were used to identify important discriminatory proteins, which were subsequently combined in multi-marker panels using logistic regression.ResultsThe top discriminatory proteins individually showed moderate accuracy (AUC &gt; 0.70) for endometrial cancer detection. However, algorithms combining the most discriminatory proteins performed well with AUCs &gt; 0.90. The best performing diagnostic model was a 10-marker panel combining SPRR1B, CRNN, CALML3, TXN, FABP5, C1RL, MMP9, ECM1, S100A7 and CFI and predicted endometrial cancer with an AUC of 0.92 (0.96–0.97). Urine-based protein signatures showed good accuracy for the detection of early-stage cancers (AUC 0.92 (0.86–0.9)).ConclusionA patient-friendly, urine-based test could offer a non-invasive endometrial cancer detection tool in symptomatic women. Validation in a larger independent cohort is warranted

Computational Modeling for the Activation Cycle of G-proteins by G-protein-coupled Receptors

In this paper, we survey five different computational modeling methods. For comparison, we use the activation cycle of G-proteins that regulate cellular signaling events downstream of G-protein-coupled receptors (GPCRs) as a driving example. Starting from an existing Ordinary Differential Equations (ODEs) model, we implement the G-protein cycle in the stochastic Pi-calculus using SPiM, as Petri-nets using Cell Illustrator, in the Kappa Language using Cellucidate, and in Bio-PEPA using the Bio-PEPA eclipse plug in. We also provide a high-level notation to abstract away from communication primitives that may be unfamiliar to the average biologist, and we show how to translate high-level programs into stochastic Pi-calculus processes and chemical reactions.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

Association of Accelerometry-Measured Physical Activity and Cardiovascular Events in Mobility-Limited Older Adults: The LIFE (Lifestyle Interventions and Independence for Elders) Study.

BACKGROUND:Data are sparse regarding the value of physical activity (PA) surveillance among older adults-particularly among those with mobility limitations. The objective of this study was to examine longitudinal associations between objectively measured daily PA and the incidence of cardiovascular events among older adults in the LIFE (Lifestyle Interventions and Independence for Elders) study. METHODS AND RESULTS:Cardiovascular events were adjudicated based on medical records review, and cardiovascular risk factors were controlled for in the analysis. Home-based activity data were collected by hip-worn accelerometers at baseline and at 6, 12, and 24&nbsp;months postrandomization to either a physical activity or health education intervention. LIFE study participants (n=1590; age 78.9±5.2 [SD] years; 67.2% women) at baseline had an 11% lower incidence of experiencing a subsequent cardiovascular event per 500&nbsp;steps taken per day based on activity data (hazard ratio, 0.89; 95% confidence interval, 0.84-0.96; P=0.001). At baseline, every 30&nbsp;minutes spent performing activities ≥500&nbsp;counts per minute (hazard ratio, 0.75; confidence interval, 0.65-0.89 [P=0.001]) were also associated with a lower incidence of cardiovascular events. Throughout follow-up (6, 12, and 24&nbsp;months), both the number of steps per day (per 500&nbsp;steps; hazard ratio, 0.90, confidence interval, 0.85-0.96 [P=0.001]) and duration of activity ≥500&nbsp;counts per minute (per 30&nbsp;minutes; hazard ratio, 0.76; confidence interval, 0.63-0.90 [P=0.002]) were significantly associated with lower cardiovascular event rates. CONCLUSIONS:Objective measurements of physical activity via accelerometry were associated with cardiovascular events among older adults with limited mobility (summary score &gt;10 on the Short Physical Performance Battery) both using baseline and longitudinal data. CLINICAL TRIAL REGISTRATION:URL: http://www.clinicaltrials.gov. Unique identifier: NCT01072500

Protocol for the proactive or reactive telephone smoking cessation support (PORTSSS) trial

Background: Telephone quit lines are accessible to many smokers and are used to engage motivated smokers to make quit attempts. Smoking cessation counselling provided via telephone can either be reactive (i.e. primarily involving the provision of evidence-based information), or proactive (i.e. primarily involving repeated, sequenced calls from and interaction with trained cessation counsellors). Some studies have found proactive telephone counselling more effective and this trial will investigate whether or not proactive telephone support for smoking cessation, delivered through the National Health Service (NHS) Smoking Helpline is more effective or cost-effective than reactive support. It will also investigate whether or not providing nicotine replacement therapy (NRT), in addition to telephone counselling, has an adjunctive impact on smoking cessation rates and whether or not this is cost effective. Methods: This will be a parallel group, factorial design RCT, conducted through the English national NHS Smoking Helpline which is run from headquarters in Glasgow. Participants will be smokers who call the helpline from any location in England and who wish to stop smoking. If 644 participants are recruited to four equally-sized trial groups (total sample size = 2576), the trial will have 90% power for detecting a treatment effect (Odds Ratio) of 1.5 for each of the two interventions: i) proactive versus reactive support and ii) the offer of NRT versus no offer. The primary outcome measure for the study is self-reported, prolonged abstinence from smoking for at least six months following an agreed quit date. A concurrent health economic evaluation will investigate the cost effectiveness of the two interventions when delivered via a telephone helpline. Discussion: The PORTSSS trial will provide high quality evidence to determine the most appropriate kind of counselling which should be provided via the NHS Smoking Helpline and also whether or not an additional offer of cost-free NRT is effective and cost effective for smoking cessation. Trial Registration: (clinicaltrials.gov): NCT0077594

C-reactive protein, interleukin-6, and prostate cancer risk in men aged 65 years and older.

Inflammation is believed to play a role in prostate cancer (PCa) etiology, but it is unclear whether inflammatory markers C-reactive protein (CRP) and interleukin-6 (IL-6) associate with PCa risk in older men. Using Cox regression, we assessed the relationship between baseline concentrations of CRP and IL-6 and the subsequent PCa risk in the Cardiovascular Health Study, a population-based cohort study of mostly European American men of ages >64 years (n = 2,234; mean follow-up = 8.7 years; 215 incident PCa cases). We also tested associations between CRP and IL-6 tagSNPs and PCa risk, focusing on SNPs that are known to associate with circulating CRP and/or IL-6. Neither CRP nor IL-6 blood concentrations was associated with PCa risk. The C allele of IL-6 SNP rs1800795 (-174), a known functional variant, was associated with increased risk in a dominant model (HR = 1.44; 95% CI = 1.03-2.01; p = 0.03), but was not statistically significant after accounting for multiple tests (permutation p = 0.21). Our results suggest that circulating CRP and IL-6 do not influence PCa risk. SNPs at the CRP locus are not associated with PCa risk in this cohort, while the association between rs1800795 and PCa risk warrants further investigation

American Gut: an Open Platform for Citizen Science Microbiome Research

McDonald D, Hyde E, Debelius JW, et al. American Gut: an Open Platform for Citizen Science Microbiome Research. mSystems. 2018;3(3):e00031-18