Selective aortic arch perfusion: a first-in-human observational cadaveric study.

BACKGROUND: Selective aortic arch perfusion (SAAP) is a novel endovascular technique that combines thoracic aortic occlusion with extracorporeal perfusion of the brain and heart. SAAP may have a role in both haemorrhagic shock and in cardiac arrest due to coronary ischaemia. Despite promising animal studies, no data is available that describes SAAP in humans. The primary aim of this study was to assess the feasibility of selective aortic arch perfusion in humans. The secondary aim of the study was to assess the feasibility of achieving direct coronary artery access via the SAAP catheter as a potential conduit for salvage percutaneous coronary intervention. METHODS: Using perfused human cadavers, a prototype SAAP catheter was inserted into the descending aorta under fluoroscopic guidance via a standard femoral percutaneous access device. The catheter balloon was inflated and the aortic arch perfused with radio-opaque contrast. The coronary arteries were cannulated through the SAAP catheter. RESULTS: The procedure was conducted four times. During the first two trials the SAAP catheter was passed rapidly and without incident to the intended descending aortic landing zone and aortic arch perfusion was successfully delivered via the device. The SAAP catheter balloon failed on the third trial. On the fourth trial the left coronary system was cannulated using a 5Fr coronary guiding catheter through the central SAAP catheter lumen. CONCLUSIONS: For the first time using a perfused cadaveric model we have demonstrated that a SAAP catheter can be easily and safely inserted and SAAP can be achieved using conventional endovascular techniques. The SAAP catheter allowed successful access to the proximal aorta and permitted retrograde perfusion of the coronary and cerebral circulation

Field measurements of trace gases and aerosols emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Niño

Peat fires in Southeast Asia have become a major annual source of trace gases and particles to the regional-global atmosphere. The assessment of their influence on atmospheric chemistry, climate, air quality, and health has been uncertain partly due to a lack of field measurements of the smoke characteristics. During the strong 2015 El Niño event we deployed a mobile smoke sampling team in the Indonesian province of Central Kalimantan on the island of Borneo and made the first, or rare, field measurements of trace gases, aerosol optical properties, and aerosol mass emissions for authentic peat fires burning at various depths in different peat types. This paper reports the trace gas and aerosol measurements obtained by Fourier transform infrared spectroscopy, whole air sampling, photoacoustic extinctiometers (405 and 870 nm), and a small subset of the data from analyses of particulate filters. The trace gas measurements provide emission factors (EFs; grams of a compound per kilogram biomass burned) for up to ∼ 90 gases, including CO2, CO, CH4, non-methane hydrocarbons up to C10, 15 oxygenated organic compounds, NH3, HCN, NOx, OCS, HCl, etc. The modified combustion efficiency (MCE) of the smoke sources ranged from 0.693 to 0.835 with an average of 0.772 ± 0.053 (n = 35), indicating essentially pure smoldering combustion, and the emissions were not initially strongly lofted. The major trace gas emissions by mass (EF as g kg-1) were carbon dioxide (1564 ± 77), carbon monoxide (291 ± 49), methane (9.51 ± 4.74), hydrogen cyanide (5.75 ± 1.60), acetic acid (3.89 ± 1.65), ammonia (2.86 ± 1.00), methanol (2.14 ± 1.22), ethane (1.52 ± 0.66), dihydrogen (1.22 ± 1.01), propylene (1.07 ± 0.53), propane (0.989 ± 0.644), ethylene (0.961 ± 0.528), benzene (0.954 ± 0.394), formaldehyde (0.867 ± 0.479), hydroxyacetone (0.860 ± 0.433), furan (0.772 ± 0.035), acetaldehyde (0.697 ± 0.460), and acetone (0.691 ± 0.356). These field data support significant revision of the EFs for CO2 (g-8 %), CH4 (g-55 %), NH3 (g-86 %), CO (+39 %), and other gases compared with widely used recommendations for tropical peat fires based on a lab study of a single sample published in 2003. BTEX compounds (benzene, toluene, ethylbenzene, xylenes) are important air toxics and aerosol precursors and were emitted in total at 1.5 ± 0.6 g kg-1. Formaldehyde is probably the air toxic gas most likely to cause local exposures that exceed recommended levels. The field results from Kalimantan were in reasonable agreement with recent lab measurements of smoldering Kalimantan peat for overlap species, lending importance to the lab finding that burning peat produces large emissions of acetamide, acrolein, methylglyoxal, etc., which were not measurable in the field with the deployed equipment and implying value in continued similar efforts. The aerosol optical data measured include EFs for the scattering and absorption coefficients (EF Bscat and EF Babs, m2 kg-1 fuel burned) and the single scattering albedo (SSA) at 870 and 405 nm, as well as the absorption Ångström exponents (AAE). By coupling the absorption and co-located trace gas and filter data we estimated black carbon (BC) EFs (g kg-1) and the mass absorption coefficient (MAC, m2 g-1) for the bulk organic carbon (OC) due to brown carbon (BrC). Consistent with the minimal flaming, the emissions of BC were negligible (0.0055 ± 0.0016 g kg-1). Aerosol absorption at 405 nm was ∼ 52 times larger than at 870 nm and BrC contributed ∼ 96 % of the absorption at 405 nm. Average AAE was 4.97 ± 0.65 (range, 4.29-6.23). The average SSA at 405 nm (0.974 ± 0.016) was marginally lower than the average SSA at 870 nm (0.998 ± 0.001). These data facilitate modeling climate-relevant aerosol optical properties across much of the UV/visible spectrum and the high AAE and lower SSA at 405 nm demonstrate the dominance of absorption by the organic aerosol. Comparing the Babs at 405 nm to the simultaneously measured OC mass on filters suggests a low MAC (∼ 0.1) for the bulk OC, as expected for the low BC/OC ratio in the aerosol. The importance of pyrolysis (at lower MCE), as opposed to glowing (at higher MCE), in producing BrC is seen in the increase of AAE with lower MCE (r2 = 0.65)

A urinary microRNA panel that is an early predictive biomarker of delayed graft function following kidney transplant

Predicting immediate and subsequent graft function is important in clinical decision-making around kidney transplantation, but is difficult using available approaches. Here we have evaluated urinary microRNAs as biomarkers in this context. Profiling of 377 microRNAs in the first urine passed post-transplantation identified 6 microRNAs, confirmed to be upregulated by RT-qPCR in an expanded cohort (miR-9, -10a, -21, -29a, -221, and -429, n = 33, P < 0.05 for each). Receiver operating characteristic analysis showed Area Under the Curve 0.94 for this panel. To establish whether this early signal was sustained, miR-21 was measured daily for 5 days post-transplant, and was consistently elevated in those developing Delayed Graft Function (n = 165 samples from 33 patients, p < 0.05). The biomarker panel was then evaluated in an independent cohort, sampled at varying times in the first week post-transplantation in a separate transplant center. When considered individually, all miRs in the panel showed a trend to increase or a significant increase in those developing delayed Graft Function (miR-9: P = 0.068, mIR-10a: P = 0.397, miR-21: P = 0.003, miR-29a: P = 0.019, miR-221: P = 0.1, and miR-429: P = 0.013, n = 47) with Area Under the Curve 0.75 for the panel. In conclusion, combined measurement of six microRNAs had predictive value for delayed graft function following kidney transplantation. Introductio

Boreal Forest Fire Emissions in Fresh Canadian Smoke Plumes: C-1-C-10 Volatile Organic Compounds (Vocs), Co2, Co, No2, No, Hcn and Ch3Cn

Boreal regions comprise about 17% of the global land area, and they both affect and are influenced by climate change. To better understand boreal forest fire emissions and plume evolution, 947 whole air samples were collected aboard the NASA DC-8 research aircraft in summer 2008 as part of the ARCTAS-B field mission, and analyzed for 79 non-methane volatile organic compounds (NMVOCs) using gas chromatography. Together with simultaneous measurements of CO2, CO, CH4, CH2O, NO2, NO, HCN and CH3CN, these measurements represent the most comprehensive assessment of trace gas emissions from boreal forest fires to date. Based on 105 air samples collected in fresh Canadian smoke plumes, 57 of the 80 measured NMVOCs (including CH2O) were emitted from the fires, including 45 species that were quantified from boreal forest fires for the first time. After CO2, CO and CH4, the largest emission factors (EFs) for individual species were formaldehyde (2.1 +/- 0.2 g kg(-1)), followed by methanol, NO2, HCN, ethene, alpha-pinene, beta-pinene, ethane, benzene, propene, acetone and CH3CN. Globally, we estimate that boreal forest fires release 2.4 +/- 0.6 TgC yr(-1) in the form of NMVOCs, with approximately 41% of the carbon released as C-1-C-2 NMVOCs and 21% as pinenes. These are the first reported field measurements of monoterpene emissions from boreal forest fires, and we speculate that the pinenes, which are relatively heavy molecules, were detected in the fire plumes as the result of distillation of stored terpenes as the vegetation is heated. Their inclusion in smoke chemistry models is expected to improve model predictions of secondary organic aerosol (SOA) formation. The fire-averaged EF of dichloromethane or CH2Cl2, (6.9 +/- 8.6) x 10(-4) g kg(-1), was not significantly different from zero and supports recent findings that its global biomass burning source appears to have been overestimated. Similarly, we found no evidence for emissions of chloroform (CHCl3) or methyl chloroform (CH3CCl3) from boreal forest fires. The speciated hydrocarbon measurements presented here show the importance of carbon released by short-chain NMVOCs, the strong contribution of pinene emissions from boreal forest fires, and the wide range of compound classes in the most abundantly emitted NMVOCs, all of which can be used to improve biomass burning inventories in local/global models and reduce uncertainties in model estimates of trace gas emissions and their impact on the atmosphere

Implementing Community-Created Self-Management Support Tools in Primary Care Practices: Multimethod Analysis From the INSTTEPP Study

Purpose: With one-half of Americans projected to be living with at least one chronic condition before 2020, enhancing patient self-management support (SMS) may improve health-related behaviors and clinical outcomes. Routine SMS implementation in primary care settings is difficult. Little is known about the practice conditions required for successful implementation of SMS tools. Methods: Four primary care practice-based research networks (PBRNs) recruited 16 practices to participate in a boot camp translation process to adapt patient-centered SMS tools. Boot camp translation sessions were held over a 2-month period with 2 patients, a clinician, and a care manager from each practice. Qualitative case comparison and qualitative comparative analysis were used to examine practice conditions needed to implement SMS tools. The Consolidated Framework for Implementation Research guided data collection and analysis. Results: Four different practice conditions affected the implementation of new SMS tools: functional practice organization; system that enables innovation and change; presence of a visible, activated champion; and synergy and alignment of SMS changes with other work. Qualitative comparative analysis suggested that it was necessary to have an enabling system, a visible champion, and synergy for a practice to at least minimally implement the SMS tools. Sufficiency testing, however, failed to show robust consistency to satisfactorily explain conditions required to implement new SMS tools. Conclusions: To implement tailored self-management support tools relatively rapidly, the minimum necessary conditions include a system that enables innovation and change, presence of a visible champion, and alignment of SMS changes with other work; yet, these alone are insufficient to ensure successful implementation

Adapting Boot Camp Translation Methods to Engage Clinician/Patient Research Teams Within Practice-Based Research Networks

Purpose: Boot camp translation is a proven process to engage community members and health professionals in translating and disseminating evidence-based “best practices” models for health prevention and chronic illness care. Primary care practice improvement studies, particularly involving patient-driven change, as seen with self-management support (SMS), require engaged practice teams that include patients. Models of engagement such as boot camp translation may be effective. Methods: Four geographically dispersed practice-based research networks (PBRNs) from the Meta-LARC consortium engaged 16 practices to form SMS implementation teams involving a clinician, care manager, and 2 patients in each team. Our study adapted the boot camp translation model to engage the implementation teams in describing patient SMS, studying the Agency for Healthcare Research and Quality’s SMS Resource Library, and adapting and implementing self-management tools at each practice site. Testimonials and quotes were collected across the 4 PBRNs through a facilitated brainstorming discussion and consensus model at each PBRN kickoff meeting to address the focused question, “What do patients want and need in order to self-manage their chronic illnesses?” Results: Testimonials collected across the 4 PBRNs and participation levels indicated there was a high degree of engagement in the boot camp translation process across the PBRNs and the practices. Each PBRN developed themes expressed by patients and the practices regarding what patients want and need to self-manage their illnesses. Each practice selected, adapted, and implemented an SMS tool. Conclusions: Results suggest that adapted boot camp translation was effective in guiding multiple practices to implement self-management support tools for the INSTTEPP trial. Additional study of the adapted boot camp translation process in practice quality improvement and practice redesign studies is needed

Limitations in representation of physical processes preven successful simulation of PM2.5 during KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements

How to Translate Self-Management Support Tools Into Clinical Practice

Purpose: Patient self-management is an inevitable part of the work of being a patient, and self-management support (SMS) has become increasingly important in chronic disease management. However, the majority of SMS resources available in the Agency for Healthcare Research and Quality SMS Resource Library were developed without explicit collaboration between clinicians and patients. Methods: Translation of SMS tools derived from the library into primary care practices occurred utilizing boot camp translation in four different practice-based research networks (PBRNs). The typical model of boot camp translation was adapted for the purpose of the Implementing Networks’ Self-management Tools Through Engaging Patients and Practices (INSTTEPP) study to develop SMS tools for implementation in the participating practices. Clinicians, clinic staff members, and patients were involved throughout the translation process. Existing resources from the SMS library were reviewed and adapted by each boot camp translation group to create tools unique to the patients in each network. Results: There was no preexisting resource within the library that was deemed suitable for implementation without modification. Each network adapted tools from the SMS library to create different products. Common themes emerged from each network’s translation process that highlighted the importance of patient engagement in the translation process. Boot camp translation, in conjunction with PBRNs, can be implemented to adapt SMS tools for implementation in member practices. Conclusions: Boot camp translation with a combination of practices and patients can be implemented to facilitate a process of local adaptation that improves the local applicability of SMS tools in primary care clinics

miR-141 mediates recovery from acute kidney injury

Acute kidney injury (AKI) is a global clinical problem characterised by a sudden decline in renal function and mortality as high as 60%. Current AKI biomarkers have limited ability to classify disease progression and identify underlying pathological mechanisms. Here we hypothesised that alterations in urinary microRNA profiles could predict AKI recovery/nonrecovery after 90 days, and that injury-specific changes would signify microRNA mediators of AKI pathology. Comparison of urinary microRNA profiles from AKI patients with controls detected significant injury-specific increases in miR-21, miR-126 and miR-141 (p < 0.05) and decreases in miR-192 (p < 0.001) and miR-204 (p < 0.05). Expression of miR-141 increased in renal proximal tubular epithelial cells (PTECs) under oxidative stress in vitro and unilateral ischaemic reperfusion injury in vivo. Forced miR-141 expression in the presence of H2O2 increased PTEC death and decreased cell viability. Of nine messenger RNA targets with two or more miR-141 3’-untranslated region binding sites, we confirmed protein tyrosine phosphatase receptor type G (PTPRG) as a direct miR-141 target in PTECs. PTPRG-specific siRNA knockdown under oxidative stress increased PTEC death and decreased cell viability. In conclusion, we detected significant alterations in five urinary microRNAs following AKI, and identified proximal tubular cell PTPRG as a putative novel therapeutic target