Service development project to pilot a digital technology innovation for video direct observation of therapy in adult patients with asthma.

BACKGROUND: Adherence to pharmacotherapy and use of the correct inhaler technique are important basic principles of asthma management. Video- or remote-direct observation of therapy (v-DOT) could be a feasible approach to facilitate monitoring and supervising therapy, supporting the delivery of standard care. OBJECTIVE: To explore the utility and the feasibility of v-DOT to monitor inhaler technique and adherence to treatment in adults attending the asthma outpatient service in a tertiary hospital in Northern Ireland. METHOD: The project evaluated use of the technology with 10 asthma patients. Patient and clinician feedback was obtained, in addition to measures of patient engagement and disease-specific clinical markers to assess the feasibility and utility of v-DOT technology in this group of patients. RESULTS: The engagement rate with v-DOT for participating patients averaged 78% (actual video uploads vs expected video uploads) over a median 7 week usage period. Although 50% of patients reported a technical issue at some stage during the usage period, all patients and clinicians reported that the technology was easy to use and that they were satisfied with the outcomes. A range of positive impacts were observed, including optimised inhaler technique and an observed improvement in lung function. An increase in asthma control test scores aligned with clinical aims to promote adherence and alleviate symptoms. CONCLUSION: The v-DOT technology was shown to be a feasible method of assessing inhaler technique and monitoring adherence in this small group of adult asthma patients. A range of positive impacts for participating patients and clinicians were observed. Not all patients invited to join the project agreed to participate or engage with using the technology, highlighting that in this setting, digital modes of delivering care provide only one of the approaches in the necessary "tool kit" for clinicians and patients.

A meta-regression analysis to evaluate the effects of narasin on grow-finish pig performance.

Ionophores are feed additives that decrease gram-positive microbial populations by disrupting the ion transfer across cell membranes resulting in improved growth performance. Narasin (Skycis; Elanco Animal Health, Greenfield, IN) is an FDA-approved ionophore utilized for increased rate of weight gain and improved feed efficiency in growing-finishing pigs. A meta-regression analysis was conducted to evaluate the effects of added narasin in growing-finishing pig diets to predict its influence on average daily gain (ADG), feed efficiency (G:F), and carcass yield. A database was developed containing 21 technical reports, abstracts, and refereed papers from 2012 to 2021 representing 35 observations for growth performance data in studies ranging from 35 to 116 d in length (overall data). In addition, within these 35 observations, individual period data were evaluated (143 observations) using weekly, bi-weekly, or monthly performance intervals (period data). Regression model equations were developed, and predictor variables were assessed with a stepwise manual forward selection procedure. The ADG model using the overall data included ADG, ADFI, and G:F of the control group, added narasin dose, and narasin feeding duration categorized as longer or shorter than 65 d. Predictor variables included in the G:F model using overall data were ADG, ADFI, and G:F of the control group and added narasin dose. For carcass yield, the final model included ADFI and G:F of the control group, added narasin dose, and narasin feeding duration of longer than 65 d. In the period model for ADG, the predictors included ADG, ADFI, and G:F of the control group, added narasin dose, and average BW of the control group categorized into greater than or less than 105 kg. For period data for G:F, the model selected ADG, ADFI, and G:F of the control group and added narasin dose. Based on the results, the overall response to added narasin for ADG and G:F was quadratic and tended to decrease as ADG and G:F increased. A similar quadratic response was observed for the individual period data. In summary, using median values from the database for predictor variables, this meta-analysis demonstrated narasin would be expected to improve ADG between 1.06% and 1.65%, G:F between 0.71% and 1.71%, and carcass yield by 0.31% when fed continuously for longer than 65 d.

Time to re-set our thinking about airways disease: lessons from history, the resurgence of chronic bronchitis / PBB and modern concepts in microbiology.

In contrast to significant declines in deaths due to lung cancer and cardiac disease in Westernised countries, the mortality due to 'chronic obstructive pulmonary disease' (COPD) has minimally changed in recent decades while 'the incidence of bronchiectasis' is on the rise. The current focus on producing guidelines for these two airway 'diseases' has hindered progress in both treatment and prevention. The elephant in the room is that neither COPD nor bronchiectasis is a disease but rather a consequence of progressive untreated airway inflammation. To make this case, it is important to review the evolution of our understanding of airway disease and how a pathological appearance (bronchiectasis) and an arbitrary physiological marker of impaired airways (COPD) came to be labelled as 'diseases'. Valuable insights into the natural history of airway disease can be obtained from the pre-antibiotic era. The dramatic impacts of antibiotics on the prevalence of significant airway disease, especially in childhood and early adult life, have largely been forgotten and will be revisited as will the misinterpretation of trials undertaken in those with chronic (bacterial) bronchitis. In the past decades, paediatricians have observed a progressive increase in what is termed 'persistent bacterial bronchitis' (PBB). This condition shares all the same characteristics as 'chronic bronchitis', which is prevalent in young children during the pre-antibiotic era. Additionally, the radiological appearance of bronchiectasis is once again becoming more common in children and, more recently, in adults. Adult physicians remain sceptical about the existence of PBB; however, in one study aimed at assessing the efficacy of antibiotics in adults with persistent symptoms, researchers discovered that the majority of patients exhibiting symptoms of PBB were already on long-term macrolides. In recent decades, there has been a growing recognition of the importance of the respiratory microbiome and an understanding of the ability of bacteria to persist in potentially hostile environments through strategies such as biofilms, intracellular communities, and persister bacteria. This is a challenging field that will likely require new approaches to diagnosis and treatment; however, it needs to be embraced if real progress is to be made.

Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems.

Predicting complex dynamics in physical applications governed by partial differential equations in real-time is nearly impossible with traditional numerical simulations due to high computational cost. Neural operators offer a solution by approximating mappings between infinite-dimensional Banach spaces, yet their performance degrades with system size and complexity. We propose an approach for learning neural operators in latent spaces, facilitating real-time predictions for highly nonlinear and multiscale systems on high-dimensional domains. Our method utilizes the deep operator network architecture on a low-dimensional latent space to efficiently approximate underlying operators. Demonstrations on material fracture, fluid flow prediction, and climate modeling highlight superior prediction accuracy and computational efficiency compared to existing methods. Notably, our approach enables approximating large-scale atmospheric flows with millions of degrees, enhancing weather and climate forecasts. Here we show that the proposed approach enables real-time predictions that can facilitate decision-making for a wide range of applications in science and engineering.

Effect of Human Head Shape on the Risk of Traumatic Brain Injury: A Gaussian Process Regression-based Machine Learning Approach.

INTRODUCTION: Computational head injury models are promising tools for understanding and predicting traumatic brain injuries. However, most available head injury models are "average" models that employ a single set of head geometry (e.g., 50th-percentile U.S. male) without considering variability in these parameters across the human population. A significant variability of head shapes exists in U.S. Army soldiers, evident from the Anthropometric Survey of U.S. Army Personnel (ANSUR II). The objective of this study is to elucidate the effects of head shape on the predicted risk of traumatic brain injury from computational head injury models. MATERIALS AND METHODS: Magnetic resonance imaging scans of 25 human subjects are collected. These images are registered to the standard MNI152 brain atlas, and the resulting transformation matrix components (called head shape parameters) are used to quantify head shapes of the subjects. A generative machine learning model is used to generate 25 additional head shape parameter datasets to augment our database. Head injury models are developed for these head shapes, and a rapid injurious head rotation event is simulated to obtain several brain injury predictor variables (BIPVs): Peak cumulative maximum principal strain (CMPS), average CMPS, and the volume fraction of brain exceeding an injurious CMPS threshold. A Gaussian process regression model is trained between head shape parameters and BIPVs, which is then used to study the relative sensitivity of the various BIPVs on individual head shape parameters. We distinguish head shape parameters into 2 types: Scaling components ${T_{xx}}$, ${T_{yy}}$, and ${T_{zz}}$ that capture the breadth, length, and height of the head, respectively, and shearing components (${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$) that capture the relative skewness of the head shape. RESULTS: An overall positive correlation is evident between scaling components and BIPVs. Notably, a very high, positive correlation is seen between the BIPVs and the head volume. As an example, a 57% increase in peak CMPS was noted between the smallest and the largest investigated head volume parameters. The variation in shearing components ${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$ on average does not cause notable changes in the BIPVs. From the Gaussian process regression model, all 3 BIPVs showed an increasing trend with each of the 3 scaling components, but the BIPVs are found to be most sensitive to the height dimension of the head. From the Sobol sensitivity analysis, the ${T_{zz}}$ scaling parameter contributes nearly 60% to the total variance in peak and average CMPS; ${T_{yy}}$ contributes approximately 20%, whereas ${T_{xx}}$ contributes less than 5%. The remaining contribution is from the 6 shearing components. Unlike peak and average CMPS, the VF-CMPS BIPV is associated with relatively evenly distributed Sobol indices across the 3 scaling parameters. Furthermore, the contribution of shearing components on the total variance in this case is negligible. CONCLUSIONS: Head shape has a considerable influence on the injury predictions of computational head injury models. Available "average" head injury models based on a 50th-percentile U.S. male are likely associated with considerable uncertainty. In general, larger head sizes correspond to greater BIPV magnitudes, which point to potentially a greater injury risk under rapid neck rotation for people with larger heads.

Revealing the hidden structure of disordered materials by parameterizing their local structural manifold.

Durable interest in developing a framework for the detailed structure of glassy materials has produced numerous structural descriptors that trade off between general applicability and interpretability. However, none approach the combination of simplicity and wide-ranging predictive power of the lattice-grain-defect framework for crystalline materials. Working from the hypothesis that the local atomic environments of a glassy material are constrained by enthalpy minimization to a low-dimensional manifold in atomic coordinate space, we develop a generalized distance function, the Gaussian Integral Inner Product (GIIP) distance, in connection with agglomerative clustering and diffusion maps, to parameterize that manifold. Applying this approach to a two-dimensional model crystal and a three-dimensional binary model metallic glass results in parameters interpretable as coordination number, composition, volumetric strain, and local symmetry. In particular, we show that a more slowly quenched glass has a higher degree of local tetrahedral symmetry at the expense of cyclic symmetry. While these descriptors require post-hoc interpretation, they minimize bias rooted in crystalline materials science and illuminate a range of structural trends that might otherwise be missed.

Medication Adherence in Children with Asthma.

Asthma is the most common chronic disease in childhood. If untreated, asthma can lead to debilitating daily symptoms which affect quality of life, but more importantly can lead to fatal asthma attacks which unfortunately still occur globally. The most effective treatment strategy for controlling asthma is for the patient to follow a personalised asthma action plan (PAAP) which will invariably include regular use of an inhaled corticosteroid. To examine medication adherence in children with asthma, we collated recent evidence from systematic reviews in this area to address the following 5 key questions; What is adherence? Is there evidence that children are not adhering to preventer medication? Why is adherence poor and what are the barriers to adherence? Does good adherence improve outcomes in asthma? And lastly, how can treatment adherence be improved?

Effect of In utero Exposure to Air Pollution on Adulthood Hospitalizations.

Empirical analyses have demonstrated that individuals exposed to severe air pollution in utero have worse health outcomes during childhood. However, there is little evidence on the long-term health impacts of air pollution exposure. The objective of this paper is to estimate the effect of in utero exposure to the Great London Smog of 1952 (GLS) on five health outcomes identified through a scoping review to be those most likely affected: respiratory, circulatory, neoplasms, mental health, and nervous system conditions. We use the GLS, an extreme air pollution event in December 1952, as a quasi-natural experiment to estimate the effect of exposure to air pollution in utero on adulthood health. Data from the UK Biobank is analysed for a cohort of participants born from December 1952 to July 1956. Differences in health outcomes between adults exposed and not exposed to the GLS due to their birth dates, born inside and outside London, were explored. Our primary focus is hospitalization events between 1997 and 2020 (corresponding to ages 40 to 69), as recorded in linked administrative data from the National Health Service (NHS). Specifically, the five primary outcomes are binary variables indicating that the individual had at least one hospitalization where the main cause of hospitalization is related to respiratory, circulatory, neoplasms, mental health, or nervous system conditions. The analytical sample comprised 36,281 individuals. A positive effect on adulthood hospitalizations due to respiratory conditions was observed. If exposed to the GLS in utero, the probability of at least one respiratory health-related hospitalization between 1997 and 2020 increased by 2.58 percentage points (95% CI 0.08, 4.30, p = 0.03), a 23% increase relative to the sample mean. Small effects were found for all other outcomes, suggesting that these conditions were not affected by the GLS. We do not find heterogeneous effects by sex or childhood socioeconomic status. This study found that a 5-day pollution exposure event while in utero significantly increased respiratory-related hospitalizations at ages 40 to 69 but had no impact on hospitalizations due to circulatory, neoplasms, mental health, and nervous system conditions.

Lactational transfer of sulforaphane-N-acetylcysteine in vivo and in human breast milk.

Sulforaphane (SFN) is a bioactive phytonutrient found in cruciferous vegetables. There is a lack of detailed information on the lactational transfer of SFN and SFN metabolites, and potential pharmacological effects on breastfeeding infants. We carried out two maternal supplementation studies in a mouse model, wherein lactating dams received either vehicle, 300 or 600 ppm SFN from postnatal day (PND) 1 to 5, or in a second experiment, vehicle or 600 ppm SFN from PND 1 to 14. The parent compound was only detectable in milk and plasma from dams receiving 600 ppm SFN for five days. The predominant metabolite SFN-N-acetylcysteine (SFN-NAC) was readily detected in milk from dams receiving 300 and 600 ppm SFN for five days or 600 ppm for 14 days. Maternal SFN-NAC plasma levels were elevated in both 600 ppm groups. Maternal hepatic and pulmonary expression of NRF2-related genes, Nqo1, Gsta2, Gstm1, and Gstp1, were significantly increased, generally following a dose-response; however, offspring induction varied. PND5 neonates in the 600-ppm group exhibited significantly elevated expression of Nqo1, Gsta2, and Gstp1 in liver, and Gstm1 and Gstp1 in lung. Findings support maternal dietary supplementation with SFN induces NRF2-related gene expression in neonates via lactational transfer of SFN-NAC. However, NQO1 enzyme activity was not significantly elevated, highlighting the need to optimize dosing strategy. Additionally, in a pilot investigation of lactating women consuming a typical diet, without any purified SFN supplementation, 7 out of 8 breast milk samples showed SFN-NAC above the limit of quantification (LOQ). Notably, the one sample below the LOQ was collected from the only participant who reported no consumption of cruciferous vegetables in the past 24 h. The parent compound was not detected in any of the human breast milk samples. Overall, these data indicate lactational transfer of SFN-NAC at dietary relevant levels. Future studies are needed to evaluate pharmacokinetics and pharmacodynamics of lactational transfer for potential preventive or therapeutic effects in breastfeeding children.

A stepwise approach for functional near infrared spectroscopy measurement during natural bladder filling.

Background: Functional near infrared spectroscopy (fNIRS) is a versatile, noninvasive, and inexpensive tool that can be used to measure oxyhemoglobin (O2Hb) changes in the cortical brain caused by increasing bladder sensation during filling in upright posture. This study's purpose is to provide a rigorous methodologic template that can be implemented for comparative studies of fNIRS in the diagnosis and management of lower urinary tract symptoms including overactive bladder (OAB) and other forms of lower urinary tract dysfunction. Methods: Participants without any urologic conditions completed a validated oral hydration protocol facilitating and equilibrating natural bladder filling. First desire to void and real time bladder sensation (0-100%) were recorded using a Sensation Meter. A 24-channel fNIRS template simultaneously recorded prefrontal cortical O2Hb. Each channel was analyzed between "first desire" to void and 100% sensation, defined in this study as the period of "high sensation". Channels were sub-divided by cortical regions: right (nine channels), left (nine channels), middle (six channels). Results: A total of eight participants (male: n=4, female: n=4) were enrolled with mean age 39±19.9 years and body mass index (BMI) of 25±3.93 kg/m2. There were no differences in age, BMI, race, or OAB survey scores based on biological sex. Signal acquisition improved with power bank use, postural head support for motion reduction, and head cap optimization. Acceleration-based concurrent motion measurement was effectively utilized to remove motion artifacts. O2Hb concentration patterns appeared irregular during low sensation and increased during high sensation after first desire across the frontal cortex. Conclusions: Employing a stepwise approach, this study defined a methodological guide for improved prefrontal fNIRS signal acquisition and analysis during bladder filling. The technique demonstrated that prefrontal fNIRS cortical O2Hb increases with elevated bladder sensation in normal subjects and sets the stage for comparative studies in individuals with OAB and other forms of lower urinary tract dysfunction.

Review of the Safety, Efficacy and Tolerability of Palivizumab in the Prevention of Severe Respiratory Syncytial Virus (RSV) Disease.

Respiratory Syncytial Virus (RSV) is a major global cause of childhood morbidity and mortality. Palivizumab, a monoclonal antibody that provides passive immunity against RSV, is currently licensed for prophylactic use in specific "high-risk" populations, including congenital heart disease, bronchopulmonary dysplasia and prematurity. Available research suggests palivizumab use in these high-risk populations can lead to a reduction in RSV-related hospitalization. However, palivizumab has not been demonstrated to reduce mortality, adverse events or length of hospital stay related to RSV. In this article, we review the management of RSV, indications for palivizumab prophylaxis, the safety, cost-effectiveness and efficacy of this preventative medication, and emerging therapeutics that could revolutionize future prevention of this significant pathogen.

Active learning applied to automated physical systems increases the rate of discovery.

Active machine learning is widely used in computational studies where repeated numerical simulations can be conducted on high performance computers without human intervention. But translation of these active learning methods to physical systems has proven more difficult and the accelerated pace of discoveries aided by these methods remains as yet unrealized. Through the presentation of a general active learning framework and its application to large-scale boundary layer wind tunnel experiments, we demonstrate that the active learning framework used so successfully in computational studies is directly applicable to the investigation of physical experimental systems and the corresponding improvements in the rate of discovery can be transformative. We specifically show that, for our wind tunnel experiments, we are able to achieve in approximately 300 experiments a learning objective that would be impossible using traditional methods.

A porcine bladder model of pre-clinical urodynamics demonstrates increased afferent nerve activity during filling.

INTRODUCTION AND OBJECTIVES: Urodynamics are the accepted gold standard for the evaluation of multiple forms of voiding dysfunction. However, the tests are expensive, invasive, poorly reproducible, and often prone to artifacts. Therefore, there is a pressing need to develop next-generation urodynamics. The purpose of this study was to develop a novel ex vivo porcine bladder urodynamics model with afferent pelvic nerve signaling that can be used as a preclinical surrogate for bladder sensation. METHODS: Porcine bladders including the ureters and vascular supply were harvested from local abattoirs using an established protocol in both male and female animals. Ex vivo bladder perfusion was performed using physiologic MOPS (3-(N-morpholino) propanesulfonic acid) buffer solution. The pelvic nerve adjacent to the bladder was grasped with micro-hook electrodes and electroneurogram (ENG) signals recorded at 20 kHz. Bladders were filled with saline at a nonphysiologic rate (100 mL/min) to a volume of 1 L using standard urodynamics equipment to simultaneously record intravesical pressure. ENG amplitude was calculated as the area under the curve for each minute, and ENG firing rate was calculated as number of spikes (above baseline threshold) per minute. At the conclusion of the experiment, representative nerve samples were removed and processed for nerve histology by a pathologist (hematoxylin and eosin and S100 stains). RESULTS: A total of 10 pig bladders were used, and nerve histology confirmed the presence of nerve in all adequately processed samples. Vesical pressure, ENG firing rate, and ENG amplitude all increased as a function of filling. During filling tertiles (low fill: min 1-3, med fill: min 4-6, and high fill: min 7-10), normalized pressures were 0.22 ± 0.04, 0.38 ± 0.05, and 0.72 ± 0.07 (cmH2O). Similarly, normalized ENG firing rates were 0.08 ± 0.03, 0.31 ± 0.06, and 0.43 ± 0.04 spikes/minute, respectively, and normalized nerve amplitudes were 0.11 ± 0.06, 0.39 ± 0.06, and 0.56 ± 0.14) µV, respectively. Strong relationships between average normalized pressure values and averaged normalized ENG firing rate (r2 = 0.66) and average normalized ENG amplitude (r2 = 0.8) were identified. CONCLUSIONS: The ex vivo perfused porcine bladder can be used as a preclinical model for the development of next-generation urodynamics technologies. Importantly, the model includes a reproducible method to measure afferent nerve activity that directly correlates with intravesical pressure during filling and could potentially be used as a surrogate measure of bladder sensation.

Evaluation of field resistance in field-collected mosquito Culex quinquefasciatus Say through quantification of ULV permethrin/PBO formulation in field bioassays.

BACKGROUND: Pyrethroids are among the most applied adulticides worldwide to control mosquito vectors for prevention of arboviral diseases transmission. However, pesticide resistance development in a mosquito population could lead to decreased control efficacy. While most studies investigate the resistant genotype (i.e. kdr, CYP450, etc.) as explanatory variables, few field efficacy studies have measured pesticide quantities deposited at different distances from the sprayer in association with observed mosquito mortality. The current study determined field delivered amounts of an applied ULV permethrin/PBO formulation (31% permethrin + 66% piperonyl butoxide) by GC/MS and estimated practical resistance ratios using caged mosquito females. RESULTS: For field samples, the extraction method recovered 78 ± 3.92-108 ± 8.97% of the permethrin/PBO formulation when utilizing the peaks of PBO from GC/MS to estimate the concentrations of adulticide deposited near the mosquito cages. The field bioassay showed that the spatial distribution of permethrin/PBO formulation was heterogeneous among three pseudo-replicates within the same distance. Within the quantifiable permethrin/PBO range of 15.7-51.4 ng/cm2 , field-collected mosquito mortalities started at 64% and linearly increased reaching 100% only in two areas, while all Sebring susceptible mosquitoes died. The field LC95 resistance ratio (RR) of F0 Cx. quinquefasciatus ranged from 2.65-3.51, falling within the 95% CI of RR95 estimated by laboratory vial assays. Tests with and without PBO indicated P450's enzymes contributed to field resistance. CONCLUSION: Results showed the suitability of the collection and quantification method to estimate the field resistance ratio at the applied pesticide rate. Pesticide quantification would also allow the association of the known frequencies of resistance mechanisms (e.g. kdr, CYP450) with field mortalities to estimate the resistance level conferred by such mechanisms. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Cognitive activity at work and the risk of dementia.

Dementia prevalence is projected to rise steeply in coming decades, producing tremendous burdens on families, and health and social services. Motivated by the need for further robust evidence on modifiable risk factors, we investigate the relationship between cognitive activity at work and later-life dementia. Using data from the US Health and Retirement Study matched to the O*NET occupational database, we find that a one standard deviation increase in the cognitive activity associated with one's longest held occupation is associated with a 0.9 percentage point reduction in (predicted) dementia, or a 24% reduction relative to the mean. This relationship is consistently found across model specifications and robustness tests. When controlling for individual fixed-effects we find that the association between dementia and work cognitive activity increases with age. Overall, our results provide some evidence in support of the inclusion of cognitive activity at work as a recognized modifiable risk factor for dementia.

COVID-19 lockdowns and changes in loneliness among young people in the U.K.

RATIONALE: There has been growing concern that loneliness has increased throughout the COVID-19 lockdowns, and that the burden has fallen heavily on young people. This is important because loneliness is strongly linked to worse health outcomes. OBJECTIVE: We examine whether and how loneliness among young people changed during the pandemic across the different lockdown periods in 2020 and 2021. We also assess differences by gender, socioeconomic status, and economic activity before the COVID-19 outbreak. METHODS: We use nine waves of longitudinal data from the COVID-19 supplement of the UK Household Longitudinal Study (Understanding Society), collected between April 2020 and September 2021. We apply an individual fixed-effects event study design, which compares the loneliness reported by the same individual over lockdown transitions. We focus on loneliness reported by 1870 respondents aged between 16 and 24 years and compare it with pre-pandemic baselines. RESULTS: We find that the loneliness of young people tracked the extent of lockdown restrictions but had returned to baseline levels by September 2021. This loneliness response was more pronounced for females than males but similar for young people across higher and lower socioeconomic backgrounds. CONCLUSIONS: These results suggest that policy interventions aimed at increasing opportunities for in-person social interactions for young people in 'normal' times, might have some success in tackling loneliness, particularly for young females.

The use of remote video directly observed therapy to improve both inhaler technique and adherence to asthma medications.

Incorrect inhaler technique and non-adherence to inhaled preventer therapy often is the cause of poorly controlled asthma. Detecting and correcting non-adherence in asthma therapy has proven difficult. In addition, while patients may be able to demonstrate correct inhaler technique at the clinic recent evidence suggests that critical errors in inhaler technique occur in the home setting. Remote video directly observed therapy (vDOT) has recently been described as a potentially useful tool for addressing non-adherence while also allowing timely correction of inhaler technique errors. In this mini-review we describe the use of vDOT in asthma management.

A multisource database tracking the impact of the COVID-19 pandemic on the communities of Boston, MA, USA.

A pandemic, like other disasters, changes how systems work. In order to support research on how the COVID-19 pandemic impacted the dynamics of a single metropolitan area and the communities therein, we developed and made publicly available a "data-support system" for the city of Boston. We actively gathered data from multiple administrative (e.g., 911 and 311 dispatches, building permits) and internet sources (e.g., Yelp, Craigslist), capturing aspects of housing and land use, crime and disorder, and commercial activity and institutions. All the data were linked spatially through BARI's Geographical Infrastructure, enabling conjoint analysis. We curated the base records and aggregated them to construct ecometric measures (i.e., descriptors of a place) at various geographic scales, all of which were also published as part of the database. The datasets were published in an open repository, each accompanied by a detailed documentation of methods and variables. We anticipate updating the database annually to maintain the tracking of the records and associated measures.

Economic gradients in loneliness, social isolation and social support: Evidence from the UK Biobank.

Despite the substantial literature on how loneliness is associated with poor health and premature mortality, there is little detailed research on the extent of its economic gradients. We provide this evidence using a sample of around 400,000 respondents aged 40-70 years from the UK Biobank, who were assessed between 2006 and 2010. We focus on differences in loneliness, as well as social isolation and a lack of social support, across educational attainment, household income, local area deprivation, and recent experience of financial stress. We employ two statistical approaches, the first exploiting the large sample size and detailed geographical information about where respondents live, so we compare individuals who differ in their economic status but reside within the same postcode district. The second approach exploits the fact that for around 36,000 respondents we observe their social health and economic circumstances at two points in time (second wave of assessment conducted between 2014 and 2020), so we conduct a panel analysis that accounts for intercorrelations between the social health measures, and controls for incomplete follow-up of panel members. Across both approaches, we find a substantially higher probability of reporting loneliness, social isolation and a lack of social support, for men and women with lower economic status. Together with the existing health-loneliness literature, these findings establish a 'loneliness pathway' contributing to health inequalities, and consequently a need for effective interventions that might address loneliness and social isolation as part of a broad policy initiative on health inequalities.