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Ambient air pollution poses a major global public health risk. Lower-cost air quality sensors (LCSs) are increasingly being explored as a tool to understand local air pollution problems and develop effective solutions. A barrier to LCS adoption is potentially larger measurement uncertainty compared to reference measurement technology. The technical performance of various LCSs has been tested in laboratory and field environments, and a growing body of literature on uses of LCSs primarily focuses on proof-of-concept deployments. However, few studies have demonstrated the implications of LCS measurement uncertainties on a sensor network's ability to assess spatiotemporal patterns of local air pollution. Here, we present results from a 2-year deployment of 100 stationary electrochemical nitrogen dioxide (NO2) LCSs across Greater London as part of the Breathe London pilot project (BL). We evaluated sensor performance using collocations with reference instruments, estimating ∼ 35 % average uncertainty (root mean square error) in the calibrated LCSs, and identified infrequent, multi-week periods of poorer performance and high bias during summer months. We analyzed BL data to generate insights about London's air pollution, including long-term concentration trends, diurnal and day-of-week patterns, and profiles of elevated concentrations during regional pollution episodes. These findings were validated against measurements from an extensive reference network, demonstrating the BL network's ability to generate robust information about London's air pollution. In cases where the BL network did not effectively capture features that the reference network measured, ongoing collocations of representative sensors often provided evidence of irregularities in sensor performance, demonstrating how, in the absence of an extensive reference network, project-long collocations could enable characterization and mitigation of network-wide sensor uncertainties. The conclusions are restricted to the specific sensors used for this study, but the results give direction to LCS users by demonstrating the kinds of air pollution insights possible from LCS networks and provide a blueprint for future LCS projects to manage and evaluate uncertainties when collecting, analyzing, and interpreting data.

Introduction: Bacterial biofilms are an important virulence factor in chronic periprosthetic joint infection (PJI) and other orthopedic infection since they are highly tolerant to antibiotics and host immunity. Antibiotics are mixed into carriers such as bone cement and calcium sulfate bone void fillers to achieve sustained high concentrations of antibiotics required to more effectively manage biofilm infections through local release. The effect of antibiotic diffusion from antibiotic-loaded calcium sulfate beads (ALCS-B) in combination with PMMA bone cement spacers on the spread and killing of Pseudomonas aeruginosa Xen41 (PA-Xen41) biofilm was investigated using a “large agar plate” model scaled for clinical relevance. Methods: Bioluminescent PA-Xen41 biofilms grown on discs of various orthopedic materials were placed within a large agar plate containing a PMMA full-size mock “spacer” unloaded or loaded with vancomycin and tobramycin, with or without ALCS-B. The amount of biofilm spread and log reduction on discs at varying distances from the spacer was assessed by bioluminescent imaging and viable cell counts. Results: For the unloaded spacer control, PA-Xen41 spread from the biofilm to cover the entire plate. The loaded spacer generated a 3 cm zone of inhibition and significantly reduced biofilm bacteria on the discs immediately adjacent to the spacer but low or zero reductions on those further away. The combination of ALCS-B and a loaded PMMA spacer greatly reduced bacterial spread and resulted in significantly greater biofilm reductions on discs at all distances from the spacer. Discussion: The addition of ALCS-B to an antibiotic-loaded spacer mimic increased the area of antibiotic coverage and efficacy against biofilm, suggesting that a combination of these depots may provide greater physical antibiotic coverage and more effective dead space management, particularly in zones where the spread of antibiotic is limited by diffusion (zones with little or no fluid motion).

Ammonium-containing aerosols are a major component of wintertime air pollution in many densely populated regions around the world. Especially in mountain basins, the formation of persistent cold-air pools (PCAPs) can enhance particulate matter with diameters less than 2.5 µm (PM2.5) to levels above air quality standards. Under these conditions, PM2.5 in the Great Salt Lake region of northern Utah has been shown to be primarily composed of ammonium nitrate; however, its formation processes and sources of its precursors are not fully understood. Hence, it is key to understanding the emission sources of its gas phase precursor, ammonia (NH3). To investigate the formation of ammonium nitrate, a suite of trace gases and aerosol composition were sampled from the NOAA Twin Otter aircraft during the Utah Winter Fine Particulate Study (UWFPS) in January and February 2017. NH3 was measured using a quantum cascade tunable infrared laser differential absorption spectrometer (QC-TILDAS), while aerosol composition, including particulate ammonium (pNH4), was measured with an aerosol mass spectrometer (AMS). The origin of the sampled air masses was investigated using the Stochastic Time-Inverted Lagrangian Transport (STILT) model and combined with an NH3 emission inventory to obtain model-predicted NHx (=NH3+pNH4) enhancements. Enhancements represent the increase in NH3 mixing ratios within the last 24 h due to emissions within the model footprint. Comparison of these NHx enhancements with measured NHx from the Twin Otter shows that modelled values are a factor of 1.6 to 4.4 lower for the three major valleys in the region. Among these, the underestimation is largest for Cache Valley, an area with intensive agricultural activities. We find that one explanation for the underestimation of wintertime emissions may be the seasonality factors applied to NH3 emissions from livestock. An investigation of inter-valley exchange revealed that transport of NH3 between major valleys was limited and PM2.5 in Salt Lake Valley (the most densely populated area in Utah) was not significantly impacted by NH3 from the agricultural areas in Cache Valley. We found that in Salt Lake Valley around two thirds of NHx originated within the valley, while about 30 % originated from mobile sources and 60 % from area source emissions in the region. For Cache Valley, a large fraction of NOx potentially leading to PM2.5 formation may not be locally emitted but mixed in from other counties.

Introduction The coronavirus pandemic (COVID-19) has affected the functioning and capacity of healthcare systems worldwide. COVID-19 has also disproportionately affected older adults, including those living with dementia. In the context of COVID-19, decision-making surrounding place of care and place of death in this population involves significant new challenges. Objectives To explore key factors that influence place of care and place of death decisions in older adults. A secondary aim was to investigate key factors that influence the process and outcome of these decisions in older adults. To apply findings from current evidence to the context of COVID-19. Methods Rapid review of reviews, undertaken using WHO guidance for rapid reviews. Ten papers were included for full data extraction. These papers were published between 2005-2020. Data extracted was synthesised using narrative synthesis, with thematic analysis and tabulation. Results Papers included discussed actual place of death, as well as preferred. Results were divided into papers that explored the process of decision-making, and those that explored decision-making outcomes. Factors such as caregiver capacity, the availability of multidisciplinary teams, cultural appropriateness of care packages and advanced care planning were found to be key. Conclusions The process and outcomes of decision-making for older people are affected by many factors – all of which have the potential to influence both patients and caregivers experience of illness and dying. Within the context of COVID-19, such decisions may have to be made rapidly and be reflexive to changing needs of systems and of families and patients.

Introduction COVID-19 as a pandemic has disproportionately affected older adults, including those with dementia. The effects on health and social care systems has necessitated a rapid-response approach to care planning and decision-making in this population, with reflexivity and responsiveness to changing individual and system needs at its core. In light of this, a decision-making tool to help families of persons with dementia was developed using a combination of qualitative data and evidence synthesis. Objectives To develop a decision-aid using a combination of assessment and evidence-gathering methods for families of persons with dementia. Methods Semi-structured interviews with helpline staff from national end-of-life and supportive care organisations formed the basis of the tool design. Co-design with people living with dementia, current and former carers and experts in general practice and social care shaped the next stage. Simultaneously, a rapid review of current evidence on making decisions with older people at the end of life was undertaken. Results Output from interviews covered many topics, including trust, agency and confusion in making decisions in the context of COVID-19. The rapid review of existing evidence highlighted the need to consider both process and outcome elements of decision-making. Conclusions Combining different sources and forms of evidence was efficient and valuable in creating a novel decision-making tool for persons with dementia and their families within the context of COVID-19. The decision-aid covered care planning, caregiver support systems, access to information and contingency considerations. Upon publication, the tool was adopted by NHS England and other leading healthcare organisations. Disclosure No significant relationships.

SYSTEMS-2 is a randomised study of radiotherapy dose escalation for pain control in 112 patients with malignant pleural mesothelioma (MPM). Standard palliative (20 Gy/5#) or dose escalated treatment (36 Gy/6#) will be delivered using advanced radiotherapy techniques and pain responses will be compared at week 5. Data will guide optimal palliative radiotherapy in MPM.

Sheep are an important part of the global agricultural economy. Growth and meat production traits are significant economic traits in sheep. The Texel breed is the most popular terminal sire breed in the UK, mainly selected for muscle growth and lean carcasses. This is a study based on a genome-wide association approach that investigates the links between some economically important traits, including computed tomography (CT) measurements, and molecular polymorphisms in UK Texel sheep. Our main aim was to identify single nucleotide polymorphisms (SNP) associated with growth, carcass, health and welfare traits of the Texel sheep breed. This study used data from 384 Texel rams. Data comprised ten traits, including two CT measured traits. The phenotypic data were placed in four categories: growth traits, carcass traits, health traits and welfare traits. De-regressed estimated breeding values (EBV) for these traits together with sire genotypes derived with the Ovine 50 K SNP array of Illumina were jointly analysed in a genome wide association analysis. Eight novel chromosome-wise significant associations were found for carcass, growth, health and welfare traits. Three significant markers were intronic variants and the remainder intergenic variants. This study is a first step to search for genomic regions controlling CT-based productivity traits related to body and carcass composition in a terminal sire sheep breed using a 50 K SNP genome-wide array. Results are important for the further development of strategies to identify causal variants associated with CT measures and other commercial traits in sheep. Independent studies are needed to confirm these results and identify candidate genes for the studied traits.

Abstract Background Calls to a telephone health helpline (THHL) have been previously evaluated for the ability to monitor specific syndromes, such as fever and influenza-like-illness or gastrointestinal illness. This method of surveillance has been shown to be highly correlated with traditional surveillance methods, and to have potential for early detection of community-based illness. Self-sampling, or having a person take his/her own nasal swab, has also proven successful as a useful method for obtaining a specimen, which may be used for respiratory virus detection. Methods This study describes a self-swabbing surveillance system mediated by a nurse-led THHL in Ontario whereby syndromic surveillance concepts are used to recruit and monitor participants with influenza-like illness. Once recruited, participants collect a nasal specimen obtained by self-swabbing and submit for testing and laboratory confirmation. Enumeration of weekly case counts was used to evaluate the timeliness of the self-swabbing surveillance system through comparison to other respiratory virus and influenza surveillance systems in Ontario. The operational efficiency of the system was also evaluated. Results The mean and median number of days between the day that a participant called the THHL, to the day a package was received at the laboratory for testing were approximately 10.4 and 8.6 days, respectively. The time between self-swab collection and package reception was 4.9 days on average, with a median of 4 days. The self-swabbing surveillance system adequately captured the 2014 influenza B season in a timely manner when compared to other Ontario-based sources of influenza surveillance data from the same year; however, the emergence of influenza B was not detected any earlier than with these other surveillance systems. Influenza A surveillance was also evaluated. Using the THHL self-swabbing system, a peak in the number of cases for influenza A was observed approximately one week after or during the same week as that reported by the other surveillance systems. Conclusion This one-year pilot study suggests that the THHL self-swabbing surveillance system has significant potential as an adjunct tool for the surveillance of influenza viruses in Ontario. Recommendations for improving system efficacy are discussed.

Ultrafine particle (UFP) number concentrations vary significantly on small spatial and temporal scales due to their short atmospheric lifetimes and multiplicity of sources. To determine UFP exposure gradients within a community, simultaneous particle number concentration measurements at a network of sites are necessary. Concurrent particle number size distribution measurements aid in identifying UFP sources, while providing data to investigate local scale effects of both photochemical and physical processes on UFP. From April to December 2007, we monitored particle number size distributions at 13 sites within 350 m–11 km of each other in the vicinity of the Ports of Los Angeles and Long Beach using Scanning Mobility Particle Sizers (SMPS). Typically, three SMPS units were simultaneously deployed and rotated among sites at 1–2 week intervals. Total particle number concentration measurements were conducted continuously at all sites. Seasonal and diurnal number size distribution patterns are complex, highly dependent on local meteorology, nearby PM sources, and times of day, and cannot be generalized over the study area nor inferred from one or two sampling locations. Spatial variation in particle number size distributions was assessed by calculating the coefficient of divergence (COD) and correlation coefficients (r) between site pairs. Results show an overall inverse relationship between particle size and CODs, implying that number concentrations of smaller particles (

Targeting immune checkpoint receptors on T cells is a common cancer treatment strategy. Frequently, this is accomplished through antibodies targeting the ligand of inhibitory co-receptors. Blocking the immune checkpoint PD-1 binding to its ligands PD-L1 and PD-L2 prevents downstream signaling and enhances anti-tumor T cell responses. This approach improves cancer patients’ outcomes. However, only one-third of the patients respond to these treatments. To better understand the mechanism of anti-PD-1 antibodies, we explored the location of PD-1 within the immune synapse. Surprisingly, we discovered that anti-PD-1 antibodies, besides blocking the interaction between PD-1 and its ligands, also removed PD-1 from the synapse. We demonstrated a correlation between removing PD-1 from the synapse by anti-PD-1 antibodies and the extent of T cell activation. Interestingly, a short version of the anti-PD-1 antibody, F(ab′)2, failed to remove PD-1 from the synapse and activate T cells. Using the syngeneic tumor model, we showed a superior anti-tumor effect of the anti-PD-1 antibody over the shorter version of the same antibody. Our data indicate that anti-PD-1 antibodies activate T cells by removing PD-1 from the synapse, and changing the location of PD-1 or other immune receptors within the immune synapse could serve as an alternative, efficient approach to treat cancer.

Because water characteristics can affect soil and plant status, it is important to check water quality periodically. However, water analysis reports are often confusing and cumbersome to read, focused primarily on monitoring sodium contents and little else. This new 3-page publication reviews several important water quality properties that need to be assessed when water samples are sent for analysis. Written by Marco Schiavon and Kimberly Moore. https://edis.ifas.ufl.edu/ep616