In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding of the RNA virus and its interactions with host proteins could improve therapeutic interventions for COVID-19. By using icSHAPE, we determined the structural landscape of SARS-CoV-2 RNA in infected human cells and from refolded RNAs, as well as the regulatory untranslated regions of SARS-CoV-2 and six other coronaviruses. We validated several structural elements predicted in silico and discovered structural features that affect the translation and abundance of subgenomic viral RNAs in cells. The structural data informed a deep-learning tool to predict 42 host proteins that bind to SARS-CoV-2 RNA. Strikingly, antisense oligonucleotides targeting the structural elements and FDA-approved drugs inhibiting the SARS-CoV-2 RNA binding proteins dramatically reduced SARS-CoV-2 infection in cells derived from human liver and lung tumors. Our findings thus shed light on coronavirus and reveal multiple candidate therapeutics for COVID-19 treatment.

B cells and tertiary lymphoid structures promote immunotherapy response.

Treatment with immune checkpoint blockade (ICB) has revolutionized cancer therapy. Until now, predictive biomarkers1-10 and strategies to augment clinical response have largely focused on the T cell compartment. However, other immune subsets may also contribute to anti-tumour immunity11-15, although these have been less well-studied in ICB treatment16. A previously conducted neoadjuvant ICB trial in patients with melanoma showed via targeted expression profiling17 that B cell signatures were enriched in the tumours of patients who respond to treatment versus non-responding patients. To build on this, here we performed bulk RNA sequencing and found that B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders. Our findings were corroborated using a computational method (MCP-counter18) to estimate the immune and stromal composition in this and two other ICB-treated cohorts (patients with melanoma and renal cell carcinoma). Histological evaluation highlighted the localization of B cells within tertiary lymphoid structures. We assessed the potential functional contributions of B cells via bulk and single-cell RNA sequencing, which demonstrate clonal expansion and unique functional states of B cells in responders. Mass cytometry showed that switched memory B cells were enriched in the tumours of responders. Together, these data provide insights into the potential role of B cells and tertiary lymphoid structures in the response to ICB treatment, with implications for the development of biomarkers and therapeutic targets.

Cracking the pattern of tumor evolution based on single-cell copy number alterations.

Copy number alterations (CNAs) are a key characteristic of tumor development and progression. The accumulation of various CNAs during tumor development plays a critical role in driving tumor evolution. Heterogeneous clones driven by distinct CNAs have different selective advantages, leading to differential patterns of tumor evolution that are essential for developing effective cancer therapies. Recent advances in single-cell sequencing technology have enabled genome-wide copy number profiling of tumor cell populations at single-cell resolution. This has made it possible to explore the evolutionary patterns of CNAs and accurately discover the mechanisms of intra-tumor heterogeneity. Here, we propose a two-step statistical approach that distinguishes neutral, linear, branching and punctuated evolutionary patterns for a tumor cell population based on single-cell copy number profiles. We assessed our approach using a variety of simulated and real single-cell genomic and transcriptomic datasets, demonstrating its high accuracy and robustness in predicting tumor evolutionary patterns. We applied our approach to single-cell DNA sequencing data from 20 breast cancer patients and observed that punctuated evolution is the dominant evolutionary pattern in breast cancer. Similar conclusions were drawn when applying the approach to single-cell RNA sequencing data obtained from 132 various cancer patients. Moreover, we found that differential immune cell infiltration is associated with specific evolutionary patterns. The source code of our study is available at https://github.com/FangWang-SYSU/PTEM.

Single-cell landscape reveals the immune heterogeneity of bone marrow involvement in peripheral T-cell lymphoma.

The prognosis of patients with peripheral T-cell lymphoma (PTCL) depends on bone marrow involvement (BMI). The bone marrow (BM) tumor microenvironment in PTCL remains unclear. We performed single-cell RNA sequencing (scRNA-seq) on 11 fresh BM samples from patients with BMI to reveal the associations of immune landscape and genetic variations with the prognosis of PTCL patients. Compared with PTCL not otherwise specified (NOS), angioimmunoblastic T-cell lymphoma (AITL) had a higher number of T cells, lower number of lymphocytes, and greater inflammation. Immune heterogeneity in AITL is associated with prognosis. In particular, specific T-cell receptor (TCR) T cells are enriched in patients with good response to anti-CD30 therapy. We observed RhoA mutation-associated neoantigens. Chidamide-treated patients had a higher number of CD4+ regulatory cells and a better treatment response compared with other patients. In the nonresponder group, T-cell enrichment progressed to secondary B-cell enrichment and subsequently diffuse large B-cell lymphoma. Moreover, AITL patients with lymphoma-associated hemophagocytic syndrome had more T follicular helper (Tfh) cells with copy number variations in CHR5. To our knowledge, this study is the first to reveal the single-cell landscape of BM microenvironment heterogeneity in PTCL patients with BMI. scRNA-seq can be used to investigate the immune heterogeneity and genetic variations in AITL associated with prognosis.

A new In Situ Oxidized 2D Layered MnBi2Te4 Cathode for High-Performance Aqueous Zinc-Ion Battery.

Recently, aqueous zinc ion batteries (AZIBs) with the superior theoretical capacity, high safety, low prices, and environmental protection, have emerged as a contender for advanced energy storage. However, challenges related to cathode materials, such as dissolution, instability, and structural collapse, have hindered the progress of AZIBs. Here, a novel AZIB is constructed using an oxidized 2D layered MnBi2Te4 cathode for the first time. The oxidized MnBi2Te4 cathode with large interlayer spacing and low energy barrier for zinc ion diffusion at 240 °C, exhibited impressive characteristics, including a high reversibility capacity of 393.1 mAh g-1 (0.4 A g-1), outstanding rate performance, and long cycle stability. Moreover, the corresponding aqueous button cell also exhibits excellent electrochemical performance. To demonstrate the application in practice in the realm of flexible wearable electronics, a quasi-solid-state micro ZIB (MZIB) is constructed and shows excellent flexibility and high-temperature stability (the capacity does not significantly degrade when the temperature reaches 100 °C and the bending angle exceeds 150°). This research offers effective tactics for creating high-performance cathode materials for AZIBs.

Prenatal Diagnosis of Cerebellar Cortical Dysplasia: Case Report.

This was a study of 12 cerebellar cortical dysplasias (CCDs) fetuses, these cases were characterized by a disorder of cerebellar fissures. Historically, CCD diagnosis was primarily performed using postnatal imaging. Unique to this study was the case series of CCD for prenatal diagnosis using prenatal ultrasound, as well as we found that AXIN1 and FOXC1 mutations may be related to CCD.

Dynamic Traffic Data in Machine-Learning Air Quality Mapping Improves Environmental Justice Assessment.

Air pollution poses a critical public health threat around many megacities but in an uneven manner. Conventional models are limited to depict the highly spatial- and time-varying patterns of ambient pollutant exposures at the community scale for megacities. Here, we developed a machine-learning approach that leverages the dynamic traffic profiles to continuously estimate community-level year-long air pollutant concentrations in Los Angeles, U.S. We found the introduction of real-world dynamic traffic data significantly improved the spatial fidelity of nitrogen dioxide (NO2), maximum daily 8-h average ozone (MDA8 O3), and fine particulate matter (PM2.5) simulations by 47%, 4%, and 15%, respectively. We successfully captured PM2.5 levels exceeding limits due to heavy traffic activities and providing an "out-of-limit map" tool to identify exposure disparities within highly polluted communities. In contrast, the model without real-world dynamic traffic data lacks the ability to capture the traffic-induced exposure disparities and significantly underestimate residents' exposure to PM2.5. The underestimations are more severe for disadvantaged communities such as black and low-income groups, showing the significance of incorporating real-time traffic data in exposure disparity assessment.

Regulatory Insights for On-Board Monitoring of Vehicular NOx Emission Compliance.

Nitrogen oxide (NOx) emissions from heavy-duty diesel vehicles (HDDVs) have adverse effects on human health and the environment. On-board monitoring (OBM), which can continuously collect vehicle performance and NOx emissions throughout the operation lifespan, is recognized as the core technology for future vehicle in-use compliance, but its large-scale application has not been reported. Here, we utilized OBM data from 22,520 HDDVs in China to evaluate their real-world NOx emissions. Our findings showed that China VI HDDVs had a 73% NOx emission reduction compared with China V vehicles, but a considerable proportion still faced a significant risk of higher NOx emissions than the corresponding limits. The unsatisfactory efficiency of the emission treatment system under disadvantageous driving conditions (e.g., low speed or ambient temperature) resulted in the incompliance of NOx emissions, especially for utility vehicles (sanitation/garbage trucks). Furthermore, the observed intertrip and seasonal variability of NOx emissions demonstrated the need for a long-term continuous monitoring protocol instead of instantaneous evaluation for the OBM. With both functions of emission monitoring and malfunction diagnostics, OBM has the potential to accurately verify the in-use compliance status of large-scale HDDVs and discern the responsibility of high-emitting activities from manufacturers, vehicle operators, and driving conditions.

From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational data during COVID-19, to predict surface-level NO2, O3, and fine particle concentration in the Los Angeles megacity. Our model exhibits high fidelity in reproducing pollutant concentrations in the Los Angeles Basin and identifies major factors controlling each species. During the strictest lockdown period, traffic reduction led to decreases in NO2 and particulate matter with aerodynamic diameters <2.5 µm by -30.1% and -17.5%, respectively, but a 5.7% increase in O3 Heavy-duty truck emissions contribute primarily to these variations. Future traffic-emission controls are estimated to impose similar effects as observed during the COVID-19 lockdown, but with smaller magnitude. Vehicular electrification will achieve further alleviation of NO2 levels.

Spatial and Cross-Sectoral Transfer of Air Pollutant Emissions from the Fleet Electrification in China by 2030.

Fleet electrification shifts emission sources from the tailpipe to electricity generation and automotive supply chains subsequently, with emission transfer among regions. Such a spatial and cross-sectoral transfer of air pollutant emissions might embody uncertain environmental benefits spatially, which has not been comprehensively quantified, mainly due to the complexity of manufacturing processes of electric vehicle (EV) components (e.g., battery). We developed a hybrid life cycle assessment by combining inventory data of major processes and cross-sectoral input-output information and identified how China's EV deployment would influence the spatial redistribution of air pollutant emissions currently (2017) and in the future (2030). The results indicate that fleet electrification could readily reduce life cycle nitrogen oxides (NOx) and nonmethane volatile organic compound (NMVOC) emissions by 12-93%, and the reductions are estimated to be concentrated in major cities and urban agglomerations. However, increased demand for electricity and power battery production could increase PM2.5 and SO2 emissions in 17-55% of grids under all the scenarios, which emerge in coal-rich (e.g., Inner Mongolia, Shanxi) and industrial (e.g., Shandong, Henan, Jiangsu) provinces. By tracing the upstream, 31-55% of vehicle-cycle emissions are from deep supply chains but exhibit diverse sources. It suggests the necessity to relieve emissions leakage of fleet electrification by synchronizing effective environmental management across multiple sectors through EV supply chains.

Updating On-Road Vehicle Emissions for China: Spatial Patterns, Temporal Trends, and Mitigation Drivers.

Vehicle emissions in China have been decoupled from rapid motorization owing to comprehensive control strategies. China's increasingly ambitious goals for better air quality are calling for deep emission mitigation, posing a need to develop an up-to-date emission inventory that can reflect the fast-developing policies on vehicle emission control. Herein, large-sample vehicle emission measurements were collected to update the vehicle emission inventory. For instance, ambient temperature correction modules were developed to depict the remarkable regional and seasonal emission variations, showing that the monthly emission disparities for total hydrocarbon (THC) and nitrogen oxide (NOX) in January and July could be up to 1.7 times in northern China. Thus, the emission ratios of THC and NOX can vary dramatically among various seasons and provinces, which have not been considered well by previous simulations regarding the nonlinear atmospheric chemistry of ozone (O3) and fine particulate matter (PM2.5) formation. The new emission results indicate that vehicular carbon monoxide (CO), THC, and PM2.5 emissions decreased by 69, 51, and 61%, respectively, during 2010-2019. However, the controls of NOX and ammonia (NH3) emissions were not as efficient as other pollutants. Under the most likely future scenario (PC [1]), CO, THC, NOX, PM2.5, and NH3 emissions were anticipated to reduce by 35, 36, 35, 45, and 4%, respectively, from 2019 to 2025. These reductions will be expedited with expected decreases of 56, 58, 74, 53, and 51% from 2025 to 2035, which are substantially promoted by the massive deployment of new energy vehicles and more stringent emission standards. The updated vehicle emission inventory can serve as an important tool to develop season- and location-specific mitigation strategies of vehicular emission precursors to alleviate haze and O3 problems.

Emission Measurements on a Large Sample of Heavy-Duty Diesel Trucks in China by Using Mobile Plume Chasing.

Real-world heavy-duty diesel trucks (HDTs) were found to emit far more excess nitrogen oxides (NOX) and black carbon (BC) pollutants than regulation limits. It is essential to systematically evaluate on-road NOX and BC emission levels for mitigating HDT emissions. This study launched 2109 plume chasing campaigns for NOX and BC emissions of HDTs across several regions in China from 2017 to 2020. It was found that NOX emissions had limited reductions from China III to China V, while BC emissions of HDTs exhibited high reductions with stricter emission standard implementation. This paper showed that previous studies underestimated 18% of NOX emissions in China in 2019 and nearly half of the real-world NOX emissions from HDTs (determined by updating the emission trends of HDTs) exceeded the regulation limits. Furthermore, the ambient temperature was identified as a primary driver of NOX emissions for HDTs, and the low-temperature penalty has caused a 9-29% increase in NOX emissions in winter in major regions of China. These results would provide important data support for the precise control of the NOX and BC emissions from HDTs.

Carbon Sequestration Potential of Biomass Production along Highways in China.

In response to climate change, China is making great efforts to increase the green area for carbon sequestration. Road verges, as marginal land with favorable conditions for plant growth and ease of transportation, can be used for biomass production, but the biomass production and carbon sequestration potential have not been assessed. Here, we mapped the biomass production potential of road verges in China by combining a biomass model and Geographic Information System and then evaluated the effect of road runoff and CO2 fertilization on the production according to the runoff coefficient and vehicle emission inventory. Nationwide, road verges can produce 15.86 Mt C yr-1 of biomass. Road runoff contributes to a biomass production of 1.26 Mt C yr-1 through increasing soil water availability, which mainly occurs in arid regions. The CO2 fertilization effect by vehicle emission is considerable in Eastern and Southern China, contributing to a production of 0.09 Mt C yr-1. Life cycle assessment shows that major road verges in China have a carbon sequestration potential of 6.87 Mt C yr-1 currently. Our results revealed that road verges can make a significant contribution to carbon neutrality under proper management.

Vehicular Ammonia Emissions Significantly Contribute to Urban PM2.5 Pollution in Two Chinese Megacities.

Ammonia (NH3) plays a vital role in the formation of fine particulate matter (PM2.5). Prior studies have primarily focused on the control of agricultural NH3 emissions, the dominant source of anthropogenic NH3 emissions. The air quality impact from vehicular NH3 emissions, which could be particularly important in urban areas, has not been adequately evaluated. We developed high-resolution vehicular NH3 emission inventories for Beijing and Shanghai based on detailed link-level traffic profiles and conducted atmospheric simulations of ambient PM2.5 concentrations contributed by vehicular NH3 emissions. We found that vehicular NH3 emissions shared high proportions among total anthropogenic NH3 emissions in the urban areas of Beijing (86%) and Shanghai (45%), where vehicular NH3 was primarily emitted by gasoline vehicles. Local vehicular NH3 emissions could be responsible for approximately 3% of urban PM2.5 concentrations during wintertime, and the contributions could be much higher during polluted periods (∼3 µg m-3). We also showed that controlling vehicular NH3 emissions will be effective and feasible to alleviate urban PM2.5 pollution for megacities in the near future.

Increased Impact of Aviation on Air Quality and Human Health in China.

China's civil aviation market has rapidly expanded, becoming the world's second-largest. However, the air quality and health impacts caused by its aircraft emissions have been inadequately assessed. Here, we leverage an updated emission inventory of air pollutants with improved temporal and spatial resolution based on hundreds of thousands of flight trajectories and simulate aviation-attributable contributions to ground-level air pollution in China. We find that in 2017, the annual-average aviation-attributed PM2.5 and O3 concentrations were 0.4-1.5 and 10.6-14.5 µg·m-3, respectively, suggesting that aviation emissions have become an increasingly important source of ambient air pollution. The contributions attributable to high-altitude emissions (climb/cruise/descent) were comparable to those at low altitudes (landing and takeoff). Aviation-attributed ambient PM2.5 and O3 exposures are estimated to have caused about 67,000 deaths in China in 2017, with populous coastal regions in Eastern China suffering the most due to the dense aviation activity. We recommend that industrial and policy stakeholders expedite an agenda of regulating air pollutants harmonized with decarbonization efforts for a more sustainable aviation future.

Health benefits of on-road transportation pollution control programs in China.

China started to implement comprehensive measures to mitigate traffic pollution at the end of 1990s, but the comprehensive effects, especially on ambient air quality and public health, have not yet been systematically evaluated. In this study, we analyze the effects of vehicle emission control measures on ambient air pollution and associated deaths attributable to long-term exposures of fine particulate matter (PM2.5) and O3 based on an integrated research framework that combines scenario analysis, air quality modeling, and population health risk assessment. We find that the total impact of these control measures was substantial. Vehicular emissions during 1998-2015 would have been 2-3 times as large as they actually were, had those measures not been implemented. The national population-weighted annual average concentrations of PM2.5 and O3 in 2015 would have been higher by 11.7 µg/m3 and 8.3 parts per billion, respectively, and the number of deaths attributable to 2015 air pollution would have been higher by 510 thousand (95% confidence interval: 360 thousand to 730 thousand) without these controls. Our analysis shows a concentration of mortality impacts in densely populated urban areas, motivating local policymakers to design stringent vehicle emission control policies. The results imply that vehicle emission control will require policy designs that are more multifaceted than traditional controls, primarily represented by the strict emission standards, with careful consideration of the challenges in coordinated mitigation of both PM2.5 and O3 in different regions, to sustain improvement in air quality and public health given continuing swift growth in China's vehicle population.

Data quality evaluation and calibration of on-road remote sensing systems based on exhaust plumes.

In recent years, with rapid increases in the number of vehicles in China, the contribution of vehicle exhaust emissions to air pollution has become increasingly prominent. To achieve the precise control of emissions, on-road remote sensing (RS) technology has been developed and applied for law enforcement and supervision. However, data quality is still an existing issue affecting the development and application of RS. In this study, the RS data from a cross-road RS system used at a single site (from 2012 to 2015) were collected, the data screening process was reviewed, the issues with data quality were summarized, a new method of data screening and calibration was proposed, and the effectiveness of the improved data quality control methods was finally evaluated. The results showed that this method reduces the skewness and kurtosis of the data distribution by up to nearly 67%, which restores the actual characteristics of exhaust diffusion and is conducive to the identification of actual clean and high-emission vehicles. The annual variability of emission factors of nitric oxide decreases by 60% - on average - eliminating the annual drift of fleet emissions and improving data reliability.

Variability of fuel consumption and CO2 emissions of a gasoline passenger car under multiple in-laboratory and on-road testing conditions.

An increasing divergence regarding fuel consumption (and/or CO2 emissions) between real-world and type-approval values for light-duty gasoline vehicles (LDGVs) has posed severe challenges to mitigating greenhouse gases (GHGs) and achieving carbon emissions peak and neutrality. To address this divergence issue, laboratory test cycles with more real-featured and transient traffic patterns have been developed recently, for example, the China Light-duty Vehicle Test Cycle for Passenger cars (CLTC-P). We collected fuel consumption and CO2 emissions data of a LDGV under various conditions based on laboratory chassis dynamometer and on-road tests. Laboratory results showed that both standard test cycles and setting methods of road load affected fuel consumption slightly, with variations of less than 4%. Compared to the type-approval value, laboratory and on-road fuel consumption of the tested LDGV over the CLTC-P increased by 9% and 34% under the reference condition (i.e., air conditioning off, automatic stop and start (STT) on and two passengers). On-road measurement results indicated that fuel consumption under the low-speed phase of the CLTC-P increased by 12% due to the STT off, although only a 4% increase on average over the entire cycle. More fuel consumption increases (52%) were attributed to air conditioning usage and full passenger capacity. Strong correlations (R2 > 0.9) between relative fuel consumption and average speed were also identified. Under traffic congestion (average speed below 25 km/hr), fuel consumption was highly sensitive to changes in vehicle speed. Thus, we suggest that real-world driving conditions cannot be ignored when evaluating the fuel economy and GHGs reduction of LDGVs.

Advances in emission control of diesel vehicles in China.

Diesel vehicles have caused serious environmental problems in China. Hence, the Chinese government has launched serious actions against air pollution and imposed more stringent regulations on diesel vehicle emissions in the latest China VI standard. To fulfill this stringent legislation, two major technical routes, including the exhaust gas recirculation (EGR) and high-efficiency selective catalytic reduction (SCR) routes, have been developed for diesel engines. Moreover, complicated aftertreatment technologies have also been developed, including use of a diesel oxidation catalyst (DOC) for controlling carbon monoxide (CO) and hydrocarbon (HC) emissions, diesel particulate filter (DPF) for particle mass (PM) emission control, SCR for the control of NOx emission, and an ammonia slip catalyst (ASC) for the control of unreacted NH3. Due to the stringent requirements of the China VI standard, the aftertreatment system needs to be more deeply integrated with the engine system. In the future, aftertreatment technologies will need further upgrades to fulfill the requirements of the near-zero emission target for diesel vehicles.

Integrated transcriptomic-genomic tool Texomer profiles cancer tissues.

Profiling of both the genome and the transcriptome promises a comprehensive, functional readout of a tissue sample, yet analytical approaches are required to translate the increased data dimensionality, heterogeneity and complexity into patient benefits. We developed a statistical approach called Texomer ( https://github.com/KChen-lab/Texomer ) that performs allele-specific, tumor-deconvoluted transcriptome-exome integration of autologous bulk whole-exome and transcriptome sequencing data. Texomer results in substantially improved accuracy in sample categorization and functional variant prioritization.