A comparative analysis of potential aerosol exposure in a wide-body aircraft cabin using tracer gas and fluorescent particles.

We compare two aerosol surrogate tracers in aircraft cabins for breathing and coughing sources: tracer gas collected in the ACER Boeing 767 mock-up and fluorescent particles collected in an actual Boeing 767 aircraft by the US Transportation Command (TRANSCOM). Each source was located individually in window and middle seats. Exposure generally decreased with source distance. A window seat breathing source resulted in good agreement between datasets for exposure (as percent of release) for the TRANSCOM hangar-AFT testing mode, which corresponds to the 11-row cabin ACER laboratory space. Average tracer gas exposure for a middle seat breathing source was higher in the ACER study than the fluorescent particle tracer exposure in the TRANSCOM study. Using a coughing source in a window seat, the exposure for the TRANSCOM data was higher within the first two rows from the source before decreasing to and tracking with the ACER levels, until increasing after about 5 m away. A similar trend was recorded for a middle seat coughing source with higher overall exposure for the TRANSCOM data. Sources of exposure variation between the studies include particle deposition. This work helps optimize aerosol dispersion research in aircraft cabins and provides some validation to the existing studies.

Unexpected Noncovalent Off-Target Activity of Clinical BTK Inhibitors Leads to Discovery of a Dual NUDT5/14 Antagonist.

Cofactor mimicry represents an attractive strategy for the development of enzyme inhibitors but can lead to off-target effects due to the evolutionary conservation of binding sites across the proteome. Here, we uncover the ADP-ribose (ADPr) hydrolase NUDT5 as an unexpected, noncovalent, off-target of clinical BTK inhibitors. Using a combination of biochemical, biophysical, and intact cell NanoBRET assays as well as X-ray crystallography, we confirm catalytic inhibition and cellular target engagement of NUDT5 and reveal an unusual binding mode that is independent of the reactive acrylamide warhead. Further investigation of the prototypical BTK inhibitor ibrutinib also revealed potent inhibition of the largely unstudied NUDIX hydrolase family member NUDT14. By exploring structure-activity relationships (SARs) around the core scaffold, we identify a potent, noncovalent, and cell-active dual NUDT5/14 inhibitor. Cocrystallization experiments yielded new insights into the NUDT14 hydrolase active site architecture and inhibitor binding, thus providing a basis for future chemical probe design.

Imidazo[1,2-b]pyridazines as inhibitors of DYRK kinases.

Selective inhibitors of DYRK1A are of interest for the treatment of cancer, Type 2 diabetes and neurological disorders. Optimization of imidazo [1,2-b]pyridazine fragment 1 through structure-activity relationship exploration and in silico drug design efforts led to the discovery of compound 17 as a potent cellular inhibitor of DYRK1A with selectivity over much of the kinome. The binding mode of compound 17 was elucidated with X-ray crystallography, facilitating the rational design of compound 29, an imidazo [1,2-b]pyridazine with improved kinase selectivity with respect to closely related CLK kinases.

Inequalities in urban air pollution in sub-Saharan Africa: an empirical modeling of ambient NO and NO2 concentrations in Accra, Ghana.

Road traffic has become the leading source of air pollution in fast-growing sub-Saharan African cities. Yet, there is a dearth of robust city-wide data for understanding space-time variations and inequalities in combustion related emissions and exposures. We combined nitrogen dioxide (NO2) and nitric oxide (NO) measurement data from 134 locations in the Greater Accra Metropolitan Area (GAMA), with geographical, meteorological, and population factors in spatio-temporal mixed effects models to predict NO2 and NO concentrations at fine spatial (50 m) and temporal (weekly) resolution over the entire GAMA. Model performance was evaluated with 10-fold cross-validation (CV), and predictions were summarized as annual and seasonal (dusty [Harmattan] and rainy [non-Harmattan]) mean concentrations. The predictions were used to examine population distributions of, and socioeconomic inequalities in, exposure at the census enumeration area (EA) level. The models explained 88% and 79% of the spatiotemporal variability in NO2 and NO concentrations, respectively. The mean predicted annual, non-Harmattan and Harmattan NO2 levels were 37 (range: 1-189), 28 (range: 1-170) and 50 (range: 1-195) µg m-3, respectively. Unlike NO2, NO concentrations were highest in the non-Harmattan season (41 [range: 31-521] µg m-3). Road traffic was the dominant factor for both pollutants, but NO2 had higher spatial heterogeneity than NO. For both pollutants, the levels were substantially higher in the city core, where the entire population (100%) was exposed to annual NO2 levels exceeding the World Health Organization (WHO) guideline of 10 µg m-3. Significant disparities in NO2 concentrations existed across socioeconomic gradients, with residents in the poorest communities exposed to levels about 15 µg m-3 higher compared with the wealthiest (p < 0.001). The results showed the important role of road traffic emissions in air pollution concentrations in the GAMA, which has major implications for the health of the city's poorest residents. These data could support climate and health impact assessments as well as policy evaluations in the city.

Discovery of PFI-6, a small-molecule chemical probe for the YEATS domain of MLLT1 and MLLT3.

Epigenetic proteins containing YEATS domains (YD) are an emerging target class in drug discovery. Described herein are the discovery and characterization efforts associated with PFI-6, a new chemical probe for the YD of MLLT1 (ENL/YEATS1) and MLLT3 (AF9/YEATS3). For hit identification, fragment-like mimetics of endogenous YD ligands (crotonylated histone-containing proteins), were synthesized via parallel medicinal chemistry (PMC) and screened for MLLT1 binding. Subsequent SAR studies led to iterative MLLT1/3 binding and selectivity improvements, culminating in the discovery of PFI-6. PFI-6 demonstrates good affinity and selectivity for MLLT1/3 vs. other human YD proteins (YEATS2/4) and engages MLLT3 in cells. Small-molecule X-ray co-crystal structures of two molecules, including PFI-6, bound to the YD of MLLT1/3 are also described. PFI-6 may be a useful tool molecule to better understand the biological effects associated with modulation of MLLT1/3.

Mortality from leading cancers in districts of England from 2002 to 2019: a population-based, spatiotemporal study.

BACKGROUND: Cancers are the leading cause of death in England. We aimed to estimate trends in mortality from leading cancers from 2002 to 2019 for the 314 districts in England. METHODS: We did a high-resolution spatiotemporal analysis of vital registration data from the UK Office for National Statistics using data on all deaths from the ten leading cancers in England from 2002 to 2019. We used a Bayesian hierarchical model to obtain robust estimates of age-specific and cause-specific death rates. We used life table methods to calculate the primary outcome, the unconditional probability of dying between birth and age 80 years by sex, cancer cause of death, local district, and year. We reported Spearman rank correlations between the probability of dying from a cancer and district-level poverty in 2019. FINDINGS: In 2019, the probability of dying from a cancer before age 80 years ranged from 0·10 (95% credible interval [CrI] 0·10-0·11) to 0·17 (0·16-0·18) for women and from 0·12 (0·12-0·13) to 0·22 (0·21-0·23) for men. Variation in the probability of dying was largest for lung cancer among women, being 3·7 times (95% CrI 3·2-4·4) higher in the district with the highest probability than in the district with the lowest probability; and for stomach cancer for men, being 3·2 times (2·6-4·1) higher in the district with the highest probability than in the one with the lowest probability. The variation in the probability of dying was smallest across districts for lymphoma and multiple myeloma (95% CrI 1·2 times [1·1-1·4] higher in the district with the highest probability than the lowest probability for women and 1·2 times [1·0-1·4] for men), and leukaemia (1·1 times [1·0-1·4] for women and 1·2 times [1·0-1·5] for men). The Spearman rank correlation between probability of dying from a cancer and district poverty was 0·74 (95% CrI 0·72-0·76) for women and 0·79 (0·78-0·81) for men. From 2002 to 2019, the overall probability of dying from a cancer declined in all districts: the reductions ranged from 6·6% (95% CrI 0·3-13·1) to 30·1% (25·6-34·5) for women and from 12·8% (7·1-18·8) to 36·7% (32·2-41·2) for men. However, there were increases in mortality for liver cancer among men, lung cancer and corpus uteri cancer among women, and pancreatic cancer in both sexes in some or all districts with posterior probability greater than 0·80. INTERPRETATION: Cancers with modifiable risk factors and potential for screening for precancerous lesions had heterogeneous trends and the greatest geographical inequality. To reduce these inequalities, factors affecting both incidence and survival need to be addressed at the local level. FUNDING: Wellcome Trust, Imperial College London, UK Medical Research Council, and the National Institute of Health Research.

Does a Preoperative Mental Health Diagnosis Affect Pain Management in Patients With Adolescent Idiopathic Scoliosis Undergoing Surgery?

BACKGROUND: Patients with adolescent idiopathic scoliosis (AIS) are typically treated surgically with posterior spinal fusion (PSF) when the curve continues to progress beyond 45 to 50 degrees. In adult patients, studies have shown that preoperative psychiatric diagnoses are associated with poorer clinical outcomes after lumbar spine surgery. This study aims to address whether a preoperative mental health disorder affects outcomes in pediatric patients with AIS treated with PSF. METHODS: We conducted a retrospective study of pediatric patients with a history of AIS requiring operative treatment with PSF at a single center with a minimum of 2-year follow-up. These patients were split into 2 groups: a subset that had a mental health disorder (MHD), and a control group. The MHD subset included patients with anxiety disorder, major depressive disorder, bipolar disorder, manic disorder, obsessive-compulsive disorder, attention deficit hyperactivity disorder, and stress disorder. The 2 groups were compared using independent student t -test and χ 2 analysis. RESULTS: A total of 417 patients were included in the study. Ninety-three patients were included in the MHD group, and 324 patients were included in the control group. The mean pain score for the MHD group was greater (3.93) compared with the control group (3.34). The PCA demands during inpatient stay for the MHD group were also greater (236.7) compared with the control group (140.0). There was no significant difference in the length of stay in the hospital between the MHD group (4.7 days) and the control group (4.6 days). There was a greater number of patients in the MHD cohort (25.8%) still using narcotic pain medication at first follow-up compared with the control group (12.0%). CONCLUSION: This study suggests that patients with AIS with a preoperative mental health disorder undergoing PSF experience more pain after surgery and require more pain medication during their recovery. LEVEL OF EVIDENCE: III. This is a retrospective review of pediatric patients with adolescent idiopathic scoliosis and a preoperative mental health diagnosis and their pain management requirements during the recovery period from posterior spinal fusion.

Waveguide-integrated chip-scale optomechanical magnetometer.

Optomechanical magnetometers enable highly sensitive magnetic field sensing. However, all such magnetometers to date have been optically excited and read-out either via free space or a tapered optical fiber. This limits their scalability and integrability, and ultimately their range of applications. Here, we present an optomechanical magnetometer that is excited and read-out via a suspended optical waveguide fabricated on the same silicon chip as the magnetometer. Moreover, we demonstrate that thermomechanical noise limited sensitivity is possible using portable electronics and laser. The magnetometer employs a silica microdisk resonator selectively sputtered with a magnetostrictive film of galfenol (FeGa) which induces a resonant frequency shift in response to an external magnetic field. Experimental results reveal the retention of high quality-factor optical whispering gallery mode resonances whilst also demonstrating high sensitivity and dynamic range in ambient conditions. The use of off-the-shelf portable electronics without compromising sensor performance demonstrates promise for applications.

Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors.

We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property-free knowledge base for future anticoronavirus drug discovery.

Navigating polycrisis: long-run socio-cultural factors shape response to changing climate.

Climate variability and natural hazards like floods and earthquakes can act as environmental shocks or socioecological stressors leading to instability and suffering throughout human history. Yet, societies experience a wide range of outcomes when facing such challenges: some suffer from social unrest, civil violence or complete collapse; others prove more resilient and maintain key social functions. We currently lack a clear, generally agreed-upon conceptual framework and evidentiary base to explore what causes these divergent outcomes. Here, we discuss efforts to develop such a framework through the Crisis Database (CrisisDB) programme. We illustrate that the impact of environmental stressors is mediated through extant cultural, political and economic structures that evolve over extended timescales (decades to centuries). These structures can generate high resilience to major shocks, facilitate positive adaptation, or, alternatively, undermine collective action and lead to unrest, violence and even societal collapse. By exposing the ways that different societies have reacted to crises over their lifetime, this framework can help identify the factors and complex social-ecological interactions that either bolster or undermine resilience to contemporary climate shocks. This article is part of the theme issue 'Climate change adaptation needs a science of culture'.

Structural-demographic analysis of the Qing Dynasty (1644-1912) collapse in China.

This paper analyzes the collapse of the Qing dynasty (1644-1912) through the lens of the Structural Demographic Theory (SDT), a general framework for understanding the drivers of socio-political instability in state-level societies. Although a number of competing ideas for the collapse have been proposed, none provide a comprehensive explanation that incorporates the interaction of all the multiple drivers involved. We argue that the four-fold population explosion peaking in the 19th century, the growing competition for a stagnant number of elite positions, and increasing state fiscal stress combined to produce an increasingly disgruntled populace and elite, leading to significant internal rebellions. We find that while neither the ecological disasters nor the foreign incursions during the 19th century were sufficient on their own to bring down the Qing, when coupled with the rising internal socio-political stresses, they produced a rapid succession of triggering events that culminated in the Qing collapse.

Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning.

Advances in computer vision, driven by deep learning, allows for the inference of environmental pollution and its potential sources from images. The spatial and temporal generalisability of image-based pollution models is crucial in their real-world application, but is currently understudied, particularly in low-income countries where infrastructure for measuring the complex patterns of pollution is limited and modelling may therefore provide the most utility. We employed convolutional neural networks (CNNs) for two complementary classification models, in both an end-to-end approach and as an interpretable feature extractor (object detection), to estimate spatially and temporally resolved fine particulate matter (PM2.5) and noise levels in Accra, Ghana. Data used for training the models were from a unique dataset of over 1.6 million images collected over 15 months at 145 representative locations across the city, paired with air and noise measurements. Both end-to-end CNN and object-based approaches surpassed null model benchmarks for predicting PM2.5 and noise at single locations, but performance deteriorated when applied to other locations. Model accuracy diminished when tested on images from locations unseen during training, but improved by sampling a greater number of locations during model training, even if the total quantity of data was reduced. The end-to-end models used characteristics of images associated with atmospheric visibility for predicting PM2.5, and specific objects such as vehicles and people for noise. The results demonstrate the potential and challenges of image-based, spatiotemporal air pollution and noise estimation, and that robust, environmental modelling with images requires integration with traditional sensor networks.

Continuous Optical-to-Mechanical Quantum State Transfer in the Unresolved Sideband Regime.

Optical-to-mechanical quantum state transfer is an important capability for future quantum networks, quantum communication, and distributed quantum sensing. However, existing continuous state transfer protocols operate in the resolved sideband regime, necessitating a high-quality optical cavity and a high mechanical resonance frequency. Here, we propose a continuous protocol that operates in the unresolved sideband regime. The protocol is based on feedback cooling, can be implemented with current technology, and is able to transfer non-Gaussian quantum states with high fidelity. Our protocol significantly expands the kinds of optomechanical devices for which continuous optical-to-mechanical state transfer is possible, paving the way toward quantum technological applications and the preparation of macroscopic superpositions to test the fundamentals of quantum science.

Do poverty and wealth look the same the world over? A comparative study of 12 cities from five high-income countries using street images.

Urbanization and inequalities are two of the major policy themes of our time, intersecting in large cities where social and economic inequalities are particularly pronounced. Large scale street-level images are a source of city-wide visual information and allow for comparative analyses of multiple cities. Computer vision methods based on deep learning applied to street images have been shown to successfully measure inequalities in socioeconomic and environmental features, yet existing work has been within specific geographies and have not looked at how visual environments compare across different cities and countries. In this study, we aim to apply existing methods to understand whether, and to what extent, poor and wealthy groups live in visually similar neighborhoods across cities and countries. We present novel insights on similarity of neighborhoods using street-level images and deep learning methods. We analyzed 7.2 million images from 12 cities in five high-income countries, home to more than 85 million people: Auckland (New Zealand), Sydney (Australia), Toronto and Vancouver (Canada), Atlanta, Boston, Chicago, Los Angeles, New York, San Francisco, and Washington D.C. (United States of America), and London (United Kingdom). Visual features associated with neighborhood disadvantage are more distinct and unique to each city than those associated with affluence. For example, from what is visible from street images, high density poor neighborhoods located near the city center (e.g., in London) are visually distinct from poor suburban neighborhoods characterized by lower density and lower accessibility (e.g., in Atlanta). This suggests that differences between two cities is also driven by historical factors, policies, and local geography. Our results also have implications for image-based measures of inequality in cities especially when trained on data from cities that are visually distinct from target cities. We showed that these are more prone to errors for disadvantaged areas especially when transferring across cities, suggesting more attention needs to be paid to improving methods for capturing heterogeneity in poor environment across cities around the world. Supplementary Information: The online version contains supplementary material available at 10.1140/epjds/s13688-023-00394-6.

Explaining population booms and busts in Mid-Holocene Europe.

Archaeological evidence suggests that the population dynamics of Mid-Holocene (Late Mesolithic to Initial Bronze Age, ca. 7000-3000 BCE) Europe are characterized by recurrent booms and busts of regional settlement and occupation density. These boom-bust patterns are documented in the temporal distribution of 14C dates and in archaeological settlement data from regional studies. We test two competing hypotheses attempting to explain these dynamics: climate forcing and social dynamics leading to inter-group conflict. Using the framework of spatially-explicit agent-based models, we translated these hypotheses into a suite of explicit computational models, derived quantitative predictions for population fluctuations, and compared these predictions to data. We demonstrate that climate variation during the European Mid-Holocene is unable to explain the quantitative features (average periodicities and amplitudes) of observed boom-bust dynamics. In contrast, scenarios with social dynamics encompassing density-dependent conflict produce population patterns with time scales and amplitudes similar to those observed in the data. These results suggest that social processes, including violent conflict, played a crucial role in the shaping of population dynamics of European Mid-Holocene societies.

Dominant-negative variant in SLC1A4 causes an autosomal dominant epilepsy syndrome.

SLC1A4 is a trimeric neutral amino acid transporter essential for shuttling L-serine from astrocytes into neurons. Individuals with biallelic variants in SLC1A4 are known to have spastic tetraplegia, thin corpus callosum, and progressive microcephaly (SPATCCM) syndrome, but individuals with heterozygous variants are not thought to have disease. We identify an 8-year-old patient with global developmental delay, spasticity, epilepsy, and microcephaly who has a de novo heterozygous three amino acid duplication in SLC1A4 (L86_M88dup). We demonstrate that L86_M88dup causes a dominant-negative N-glycosylation defect of SLC1A4, which in turn reduces the plasma membrane localization of SLC1A4 and the transport rate of SLC1A4 for L-serine.

Changes in life expectancy and house prices in London from 2002 to 2019: hyper-resolution spatiotemporal analysis of death registration and real estate data.

Background: London has outperformed smaller towns and rural areas in terms of life expectancy increase. Our aim was to investigate life expectancy change at very-small-area level, and its relationship with house prices and their change. Methods: We performed a hyper-resolution spatiotemporal analysis from 2002 to 2019 for 4835 London Lower-layer Super Output Areas (LSOAs). We used population and death counts in a Bayesian hierarchical model to estimate age- and sex-specific death rates for each LSOA, converted to life expectancy at birth using life table methods. We used data from the Land Registry via the real estate website Rightmove (www.rightmove.co.uk), with information on property size, type and land tenure in a hierarchical model to estimate house prices at LSOA level. We used linear regressions to summarise how much life expectancy changed in relation to the combination of house prices in 2002 and their change from 2002 to 2019. We calculated the correlation between change in price and change in sociodemographic characteristics of the resident population of LSOAs and population turnover. Findings: In 134 (2.8%) of London's LSOAs for women and 32 (0.7%) for men, life expectancy may have declined from 2002 to 2019, with a posterior probability of a decline >80% in 41 (0.8%, women) and 14 (0.3%, men) LSOAs. The life expectancy increase in other LSOAs ranged from <2 years in 537 (11.1%) LSOAs for women and 214 (4.4%) for men to >10 years in 220 (4.6%) for women and 211 (4.4%) for men. The 2.5th-97.5th-percentile life expectancy difference across LSOAs increased from 11.1 (10.7-11.5) years in 2002 to 19.1 (18.4-19.7) years for women in 2019, and from 11.6 (11.3-12.0) years to 17.2 (16.7-17.8) years for men. In the 20% (men) and 30% (women) of LSOAs where house prices had been lowest in 2002, mainly in east and outer west London, life expectancy increased only in proportion to the rise in house prices. In contrast, in the 30% (men) and 60% (women) most expensive LSOAs in 2002, life expectancy increased solely independently of price change. Except for the 20% of LSOAs that had been most expensive in 2002, LSOAs with larger house price increases experienced larger growth in their population, especially among people of working ages (30-69 years), had a larger share of households who had not lived there in 2002, and improved their rankings in education, poverty and employment. Interpretation: Large gains in area life expectancy in London occurred either where house prices were already high, or in areas where house prices grew the most. In the latter group, the increases in life expectancy may be driven, in part, by changing population demographics. Funding: Wellcome Trust; UKRI (MRC); Imperial College London; National Institutes of Health Research.

High-resolution patterns and inequalities in ambient fine particle mass (PM2.5) and black carbon (BC) in the Greater Accra Metropolis, Ghana.

Growing cities in sub-Saharan Africa (SSA) experience high levels of ambient air pollution. However, sparse long-term city-wide air pollution exposure data limits policy mitigation efforts and assessment of the health and climate effects. In the first study of its kind in West Africa, we developed high resolution spatiotemporal land use regression (LUR) models to map fine particulate matter (PM2.5) and black carbon (BC) concentrations in the Greater Accra Metropolitan Area (GAMA), one of the fastest sprawling metropolises in SSA. We conducted a one-year measurement campaign covering 146 sites and combined these data with geospatial and meteorological predictors to develop separate Harmattan and non-Harmattan season PM2.5 and BC models at 100 m resolution. The final models were selected with a forward stepwise procedure and performance was evaluated with 10-fold cross-validation. Model predictions were overlayed with the most recent census data to estimate the population distribution of exposure and socioeconomic inequalities in exposure at the census enumeration area level. The fixed effects components of the models explained 48-69 % and 63-71 % of the variance in PM2.5 and BC concentrations, respectively. Spatial variables related to road traffic and vegetation explained the most variability in the non-Harmattan models, while temporal variables were dominant in the Harmattan models. The entire GAMA population is exposed to PM2.5 levels above the World Health Organization guideline, including even the Interim Target 3 (15 µg/m3), with the highest exposures in poorer neighborhoods. The models can be used to support air pollution mitigation policies, health, and climate impact assessments. The measurement and modelling approach used in this study can be adapted to other African cities to bridge the air pollution data gap in the region.