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Monkeypox was declared a global health emergency by the World Health Organization, and as of March 2023, 86,000 confirmed cases and 111 deaths across 110 countries have been reported. Its causal agent, monkeypox virus (MPV) belongs to a large family of double-stranded DNA viruses, Orthopoxviridae, that also includes vaccinia virus (VACV) and others. MPV produces two distinct forms of viral particles during its replication cycles: the enveloped viron (EV) that is released via exocytosis, and the mature viron (MV) that is discharged through lysis of host cells. This study was designed to develop multi-valent mRNA vaccines against monkeypox EV and MV surface proteins, and examine their efficacy and mechanism of action. Four mRNA vaccines were produced with different combinations of surface proteins from EV (A35R and B6R), MV (A29L, E8L, H3L and M1R), or EV and MV, and were administered in Balb/c mice to assess their immunogenicity potentials. A dynamic immune response was observed as soon as seven days after initial immunization, while a strong IgG response to all immunogens was detected with ELISA after two vaccinations. The higher number of immunogens contributed to a more robust total IgG response and correlating neutralizing activity against VACV, indicating the additive potential of each immunogen in generating immune response and nullifying VACV infection. Further, the mRNA vaccines elicited an antigen-specific CD4+T cell response that is biased towards Th1. The mRNA vaccines with different combinations of EV and MV surface antigens protected a mouse model from a lethal dose VACV challenge, with the EV and MV antigens-combined vaccine offering the strongest protection. These findings provide insight into the protective mechanism of multi-valent mRNA vaccines against MPV, and also the foundation for further development of effective and safe mRNA vaccines for enhanced protection against monkeypox virus outbreak.

Manipulations of morphological properties of nanobiomaterials have been demonstrated to modulate the outcome of osteoimmunomodulation and eventually osteogenesis through innate immune response. However, the functions and mechanisms of adaptive immune cells in the process of nanobiomaterials-mediated bone regeneration have remained unknown. Herein, we developed bone-mimicking hydroxyapatite (HAp) nanorods with different aspect ratios as model materials to investigate the impacts of the nanoshape features on osteogenesis and to explore the underlying mechanisms focusing on the functions of T cells and T cell-derived cytokines. HAp nanorods with different aspect ratios (HAp-0, HAp-30, and HAp-100) were implanted into mouse mandibular defect models. Micro-CT and hematoxylin and eosin staining demonstrated that HAp-100 had the best osteogenic effects. Flow cytometry analysis revealed that HAp-100 increased the percentage of T cells in injured mandibles. The osteogenic effects of HAp-100 were significantly blunted in injured mandibles of TCRβ–/–mice. The Luminex xMAP assay and ELISA showed that HAp-100 induced a marked increase of interleukin (IL)-22 in injured mandibles. In cultured T cells, HAp-100 manifested the best capacity to induce the production of IL-22. Conditioned media from HAp-100-primed T cells promoted osteogenesis and JAK1/STAT3 activation in bone marrow stromal cells, all of which were abolished by neutralizing antibodies against IL-22. In summary, bone-mimicking HAp nanorods with different aspect ratios could regulate osteogenesis through modulation of T cells and IL-22 in the bone regeneration process. These findings provided insights for mediation of the immune response of T cells by nanomaterials on osteogenesis and strategies for designing biomaterials with osteoimmunomodulative functions.

Quorum sensing (QS) is a signaling mechanism for cell-to-cell communication between bacteria, fungi, and even eukaryotic hosts such as plant and animal cells. Bacteria in real life do not exist as isolated organisms but are found in complex, dynamic, and microecological environments. The study of interspecies QS and interkingdom QS is a valuable approach for exploring bacteria–bacteria interactions and bacteria–host interaction mechanisms and has received considerable attention from researchers. The correct combination of QS signals and receptors is key to initiating the QS process. Compared with intraspecies QS, the signal regulation mechanism of interspecies QS and interkingdom QS is often more complicated, and the distribution of receptors is relatively wide. The present review focuses on the latest progress with respect to the distribution, structure, and signal transduction of interspecies and interkingdom QS receptors and provides a guide for the investigation of new QS receptors in the future.

Accurate estimates of fossil fuel CO2(FFCO2) emissions are of great importance for climate prediction and mitigation regulations but remain a significant challenge for accounting methods relying on economic statistics and emission factors. In this study, we employed a regional data assimilation framework to assimilate in situNO2observations, allowing us to combine observation-constrained NOxemissions coemitted with FFCO2and grid-specific CO2-to-NOxemission ratios to infer the daily FFCO2emissions over China. The estimated national total for 2016 was 11.4 PgCO2·yr–1, with an uncertainty (1σ) of 1.5 PgCO2·yr–1that accounted for errors associated with atmospheric transport, inversion framework parameters, and CO2-to-NOxemission ratios. Our findings indicated that widely used “bottom-up” emission inventories generally ignore numerous activity level statistics of FFCO2related to energy industries and power plants in western China, whereas the inventories are significantly overestimated in developed regions and key urban areas owing to exaggerated emission factors and inexact spatial disaggregation. The optimized FFCO2estimate exhibited more distinct seasonality with a significant increase in emissions in winter. These findings advance our understanding of the spatiotemporal regime of FFCO2emissions in China.

Background:Biofilm formation is considered to be one of reasons for difficulty in the prevention and control of Streptococcus suis. Aims:To explore the potential genes involved in the biofilm formation of S. suis. Methods:Transposon mutagenesis technology was used to screen biofilm-defective strains of S. suis, and the potential genes related to biofilm were identified. Results:A total of 19 genes were identified that were involved in bacterial metabolism, peptidoglycan-binding protein, cell wall synthesis, ABC transporters, and so on. Conclusion:This study constructed 979 transposon mutation libraries of S. suis. A total of 19 gene loci related to the formation of S. suisbiofilm were identified, providing a reference for exploring the mechanism of S. suisbiofilm formation in the future.

Large-scale population migration accompanied by rapid urbanization is expected to cause the spatial relocation of air pollution because of heterogeneous energy use and consumption preferences of rural versus urban areas in China. In this study, we adopted an integrated approach by combining a population migration model and environmentally extended input–output analysis to quantify impacts of rural-to-urban (RU) and urban-to-urban (UU) migrations on emissions of NOx, SO2, and primary PM2.5in China. Results indicate that population migration increases NOx(1.42 Mt), SO2(1.30 Mt), and primary PM2.5(0.05 Mt) emissions, accounting respectively for 5.4, 4.8, and 0.4% of China’s total in 2012. RU migration, involving 54% of the migrating population, significantly increases NOxand SO2emissions because of high urban indirect per-capita emissions from consumption and investment. RU migration influences negligibly primary PM2.5emissions reflecting the small rural–urban difference in per-capita emissions. Interestingly, UU migration, mostly from inland to coastal provinces, leads to a slight emission decrease for the three pollutants, attributable to the greener development in coastal cities. A significant emission growth can be traced back to heavy and utility industries, suggesting that future emission control of these sectors should reduce the exposure to air pollution of the growing urban population.

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In several organ systems, the transitional zone between different types of epithelium is a hotspot for pre-neoplastic metaplasia and malignancy, but the cells of origin for these metaplastic epithelia and subsequent malignancies remain unknown. In the case of Barrett’s oesophagus, intestinal metaplasia occurs at the gastro-oesophageal junction, where stratified squamous epithelium transitions into simple columnar cells. On the basis of a number of experimental models, several alternative cell types have been proposed as the source of this metaplasia but in all cases the evidence is inconclusive: no model completely mimics Barrett’s oesophagus in terms of the presence of intestinal goblet cells. Here we describe a transitional columnar epithelium with distinct basal progenitor cells (p63+KRT5+KRT7+) at the squamous–columnar junction of the upper gastrointestinal tract in a mouse model. We use multiple models and lineage tracing strategies to show that this squamous–columnar junction basal cell population serves as a source of progenitors for the transitional epithelium. On ectopic expression of CDX2, these transitional basal progenitors differentiate into intestinal-like epithelium (including goblet cells) and thereby reproduce Barrett’s metaplasia. A similar transitional columnar epithelium is present at the transitional zones of other mouse tissues (including the anorectal junction) as well as in the gastro-oesophageal junction in the human gut. Acid reflux-induced oesophagitis and the multilayered epithelium (believed to be a precursor of Barrett’s oesophagus) are both characterized by the expansion of the transitional basal progenitor cells. Our findings reveal a previously unidentified transitional zone in the epithelium of the upper gastrointestinal tract and provide evidence that the p63+KRT5+KRT7+basal cells in this zone are the cells of origin for multi-layered epithelium and Barrett’s oesophagus.

Ever-increasing ambient ozone (O3) pollution in China has been exacerbating cardiopulmonary premature deaths. However, the urban-rural exposure inequity has seldom been explored. Here, we assess population-scale O3exposure and mortality burdens between 1990–2019 based on integrated pollution tracking and epidemiological evidence. We find Chinese cities have been suffering from climbing O3exposure by 4.3±2.8 ppb per decade as a result of rapid urbanization and growing prosperity of socioeconomic activities. Rural residents are broadly exposed to 9.8±4.1 ppb higher ambient O3than the adjacent urban citizens, and thus urbanization-oriented migration compromises the exposure-associated mortality on total population. Cardiopulmonary excess premature deaths attributable to long-term O3exposure, 373 500 (95% UI: 240 600–510 900) in 2019, is underestimated in previous studies due to ignorance of cardiovascular causes. Future O3pollution policy should focus more on rural population who are facing an aggravating threat of mortality risks to ameliorate environmental health injustice.

Surface ozone is damaging to human health and crop yields. When evaluating global air pollution risk, gridded datasets with high accuracy are desired to reflect the local variations in air pollution concentrations. Here, a cluster‐enhanced ensemble machine learning method was used to develop a new 0.5‐degree monthly surface ozone data set during 2003–2019 by combining numerous informative variables. The overall accuracy of our data set is 91.5% (90.8% for space and 92.3% for time). Historically, populations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest ozone concentrations. Globally, the population weighted ozone concentration in the peak season is 47.07 ppbv. Our results highlight that ozone pollution is intensifying in some regions, and implicate air quality management is crucial to secure human health from air pollution. Surface ozone is one of the most hazardous air pollutants to human health and plants. However, estimation of global surface ozone is still limited. Here, by using state‐of‐the‐art machine learning techniques, we fuse satellite, chemical transport model outputs, atmospheric reanalyses, and emission data with surface observations to construct a full coverage and long‐time period surface ozone data set. We demonstrate that surface population weighted ozone concentration in North America and Europe has decreased from 2003 to 2019, while ozone pollution in East Asia has intensified during 2016–2019. We also show at least 37% of the world's population is exposed to ozone greater than the World Health Organization's interim target one of 50 ppbv (MDA8) in the peak season. Our results could help identify the key regions for improving global air quality and offers an insightful data set for human health assessments and air quality management. A cluster‐enhanced ensemble machine learning method can predict global surface ozone with high accuracyPopulations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest MDA8 during 2003–2019At least 37% of world's population is exposed to greater than 50 ppbv MDA8 in peak seasons A cluster‐enhanced ensemble machine learning method can predict global surface ozone with high accuracy Populations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest MDA8 during 2003–2019 At least 37% of world's population is exposed to greater than 50 ppbv MDA8 in peak seasons

AbstractA grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 × 107L, 4.28 × 104t, 1.97 × 103t, 0.28 × 103t, and 0.14 × 103t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.

AbstractTo improve the accuracy and applicability of vehicular emission models, this study proposes a speed and vehicle-specific power (VSP) modeling method to estimate vehicular emissions and fuel consumption using data gathered by a portable emissions monitoring system (PEMS). The PEMS data were categorized into discrete speed-VSP bins on the basis of the characteristics of vehicle driving conditions and emissions in Chinese cities. Speed-VSP modal average rates of emissions (or fuel consumption) and the time spent in the corresponding speed-VSP bins were then used to calculate the total trip emissions (or fuel consumption) and emission factors (or fuel economy) under specific average link speeds. The model approach was validated by comparing it against measured data with prediction errors within 20% for trip emissions and link-speed-based emission factors. This analysis is based on the data of light-duty gasoline vehicles in China; however, this research approach could be generalized to other vehicle fleets in other countries. This modeling method could also be coupled with traffic demand models to establish high-resolution emissions inventories and evaluate the impacts of traffic-related emission control measures.

All four CATSPER channel pore-forming subunits (CATSPER1–4) are localized in the sperm principal piece. They form an alkalization-activated Ca2+-permeable channel and are required for sperm-hyperactivated motility, egg coat penetration, and male fertility. Unlike many other ion channels, the composition of the CATSPER protein complex is poorly defined. Herein, we describe the novel protein CATSPERG associated with the CATSPER complex. CATSPERG is predicted to be a single transmembrane-spanning protein with a large extracellular domain and a short intracellular tail. Like all the CATSPERs and the previously identified CATSPER-associated protein CATSPERB, CATSPERG is only expressed in testis and is localized in the sperm principal piece. In CATSPER1-deficient sperm, the CATSPERG protein (but not the K+channel protein KCNU1) is also lost. Together with previous findings, our data suggest that the CATSPER protein complex contains pore-forming proteins and two additional proteins (CATSPERB and CATSPERG) and that the trafficking and/or assembly of these proteins depends on CATSPER1.

The explosive spread of the 2019 novel coronavirus (COVID-19) provides a unique chance to rethink the relationship between human activity and air pollution. Though related studies have revealed substantial reductions in primary emissions, obvious differences do exist in the responses of secondary pollutants, like ozone (O3) pollution. However, the regional disparities of O3responses and their causes have still not been fully investigated. To better elucidate the interrelationship between anthropogenic emissions, chemical production, and meteorological conditions, O3responses caused by lockdowns over different regions were comprehensively explored at a global scale. Observational signals of air-quality change were derived from multi-year surface measurements and satellite retrievals. With similar substantial drops in nitrogen dioxide (NO2), ozone shows rising signals in most areas of both East Asia and Europe, even up to ∼14 ppb, while a non-negligible declining signal exists in North America, by about 2–4 ppb. Furthermore, the drivers behind the different O3responses are discussed based on meteorological analysis and O3sensitivity diagnosis. On the one hand, O3responses to NO2declines can be affected by the primary dependence on its precursors. On the other hand, it is also highly dependent on meteorological factors, especially temperature. Our study further highlights the great importance of taking into consideration both the regional disparities and synergistic effects of precursor reductions and meteorological influence for scientific mitigation of O3pollution.

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions. Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in eastern China, raising questions about the well-established relationship between human activities and air quality. Here, using comprehensive measurements and modeling, we show that the haze during the COVID lockdown was driven by enhancements of secondary pollution. In particular, large decreases in NOxemissions from transportation increased ozone and nighttime NO3radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter. Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants.

The COVID‐19 epidemic has substantially limited human activities and affected anthropogenic emissions. In this work, daily NOxemissions are inferred using a regional data assimilation system and hourly surface NO2measurement over China. The results show that because of the coronavirus outbreak, NOxemissions across the whole mainland China dropped sharply after 31 January, began to rise slightly in certain areas after 10 February, and gradually recover across the country after 20 February. Compared with the emissions before the outbreak, NOxemissions fell by more than 60% and ~30% in many large cities and most small to medium cities, respectively. Overall, NOxemissions were reduced by 36% over China, which were mainly contributed by transportation. Evaluations show that the inverted changes over eastern China are credible, whereas those in western China might be underestimated. These findings are of great significance for exploring the reduction potential of NOxemissions in China. In this study, we quantitatively estimate the impact of the COVID‐19 lockdown on NOxemissions over China based on nationwide surface hourly NO2monitoring data. We find that NOxemissions dropped sharply after 31 January and began to gradually recover after 20 February across the country; NOxemissions fell by more than 60% in many large cities and decreased by ~30% in most small to medium cities. Across the whole mainland China, NOxemissions were reduced by 36% due to the COVID‐19 lockdown. The spatiotemporal variations of NOxemissions across mainland China during COVID‐19 well inferred from surface NO2observationsNOxemissions fell by more than 60% in many large cities and by 36% across the whole mainland China due to the lockdownNOxemissions dropped sharply after 31 January and began to gradually recover after 20 February across the country

Ion channels can be regulated by a wide spectrum of neurotransmitters and hormones, largely through G-protein-coupled receptors (GPCRs). G-protein-independent activation of ion channel currents by GPCRs has also been recorded, although the molecular identity of the channels and the activation mechanisms remain largely unknown. UNC80 is a protein that is associated with the NALCN Na+ leak cation channel, and is required for the activation of this channel by the neuropeptide substance P through GPCR in a G-protein-independent fashion. Here, we show that UNC80 binds Src kinases and recruits Src into the channel complex. This finding is consistent with the known requirement for Src kinases in the activation of NALCN, and may lead to new insights into the molecular mechanisms underlying G-protein-independent activation of the channel.

China has implemented active clean air policies in recent years, and the spatiotemporal patterns of major pollutant emissions have changed substantially. In this study, we construct a regional air pollution data assimilation system based on the WRF/CMAQ model and ensemble Kalman filter algorithm to quantitatively optimize gridded CO emissions using hourly surface CO measurements over China. The Multi‐resolution Emission Inventory of China CO emission inventories in December 2012 and 2016 are treated as prior emissions, and the CO emissions in December 2013 and 2017 are optimized using the CO observations of December of 2013 and 2017, respectively. The results show that in both periods, assimilation of CO observations significantly improves the CO simulations and emission estimates. Assimilation increases the CO emissions in most areas of mainland China, especially in northern China, and the spatial patterns of the increases in the two periods are similar. Overall, the posterior CO emissions in December 2017 are 17% lower than those in December 2013. Large emission decreases are mainly found in most key urban areas and developed regions, and emission increases are mainly located in their surrounding areas and certain central and western regions, which might reflect the emission migration from developed regions or urban areas to developing regions or surrounding areas. These changes are not found in the prior emissions but are basically consistent with the emission control strategies and industrial transformation and upgrade phenomena in recent years, indicating that our CO assimilation system could successfully capture the temporal and spatial variations. CO emissions over China in December 2013 and 2017 were optimized using surface hourly CO observations, and the emission changes between these two periods were presented. We found that there were large emission decreases in key urbans and developed regions, and increases in their surrounding areas and some central and western regions, which were basically consistent with the emission control strategies and industrial transformation in recent years, might reflect the emission migration. A regional air pollution data assimilation system based on WRF/CMAQ and EnKF is constructedOverall, the CO emissions are reduced by 17% between December 2013 and 2017 over the whole mainland of ChinaThe emissions migration is found in the posterior emissions but not shown in the prior emissions