scGPT: toward building a foundation model for single-cell multi-omics using generative AI.

Generative pretrained models have achieved remarkable success in various domains such as language and computer vision. Specifically, the combination of large-scale diverse datasets and pretrained transformers has emerged as a promising approach for developing foundation models. Drawing parallels between language and cellular biology (in which texts comprise words; similarly, cells are defined by genes), our study probes the applicability of foundation models to advance cellular biology and genetic research. Using burgeoning single-cell sequencing data, we have constructed a foundation model for single-cell biology, scGPT, based on a generative pretrained transformer across a repository of over 33 million cells. Our findings illustrate that scGPT effectively distills critical biological insights concerning genes and cells. Through further adaptation of transfer learning, scGPT can be optimized to achieve superior performance across diverse downstream applications. This includes tasks such as cell type annotation, multi-batch integration, multi-omic integration, perturbation response prediction and gene network inference.

Transformers in single-cell omics: a review and new perspectives.

Recent efforts to construct reference maps of cellular phenotypes have expanded the volume and diversity of single-cell omics data, providing an unprecedented resource for studying cell properties. Despite the availability of rich datasets and their continued growth, current single-cell models are unable to fully capitalize on the information they contain. Transformers have become the architecture of choice for foundation models in other domains owing to their ability to generalize to heterogeneous, large-scale datasets. Thus, the question arises of whether transformers could set off a similar shift in the field of single-cell modeling. Here we first describe the transformer architecture and its single-cell adaptations and then present a comprehensive review of the existing applications of transformers in single-cell analysis and critically discuss their future potential for single-cell biology. By studying limitations and technical challenges, we aim to provide a structured outlook for future research directions at the intersection of machine learning and single-cell biology.

Total-factor energy efficiency of ten major global energy-consuming countries.

Improving energy efficiency is regarded as a key path to tackling global warming and achieving the Sustainable Development Goals (SDGs). In 2020, the energy consumption of the world's ten major energy-consuming countries accounted for 66.8% of the global total. This paper applied data envelopment analysis (DEA) to calculate these ten major energy-consuming countries' total-factor energy efficiency (TFEE) at national and sectoral levels from 2001-2020, and explored the influencing factors of total-factor energy efficiency with the Tobit regression model. The results showed significant difference in the ten countries' energy efficiency. The United States and Germany topped the list for total-factor energy efficiency, while China and India were at the bottom. Meanwhile, the energy efficiency of the industrial subsector has increased significantly over the past two decades, while that of the other subsectors has been relatively flat. The industrial structure upgrading, per capita GDP, energy consumption structure, and foreign direct investment had significant impacts on energy efficiency with national heterogeneity. Energy consumption structure and GDP per capita were determinative factors of energy efficiency.

DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics.

Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex and heterogeneous single-cell RNA sequencing (scRNA-seq) data. Using a graph convolution network, DeepVelo overcomes these limitations by generalizing RNA velocity to cell populations containing time-dependent kinetics and multiple lineages. DeepVelo infers time-varying cellular rates of transcription, splicing, and degradation, recovers each cell's stage in the differentiation process, and detects functionally relevant driver genes regulating these processes. Application to various developmental and pathogenic processes demonstrates DeepVelo's capacity to study complex differentiation and lineage decision events in heterogeneous scRNA-seq data.

Gelatin/polyvinyl alcohol films loaded with doubly stabilized clove essential oil chitosomes: Preparation, characterization, and application in packing marinated steaks.

In this study, a promising active food-packaging film of Gelatin/polyvinyl alcohol (GEL/PVA) integrated with doubly stabilized clove essential oil chitosome nanoparticles (CNP) was developed to maintain the freshness of marinated steaks. Results from the XRD and SEM experiments indicated excellent compatibility between the CNP and GEL/PVA matrix. Additionally, CNP was found to introduce more free hydroxyl groups, enhance the water retention and surface wettability of the CNP-GEL/PVA (C-G/P) film, and significantly reduce the swelling index from 963.78% to 495.11% (p < 0.05). Notably, the highest tensile strength and elongation at break (53.745 MPa and 46.536%, respectively) were achieved with the addition of 30% (v/v, based on the volume of gelatin) CNP; UVC was fully absorbed with 40% CNP; and films containing 60% CNP showed optimal inhibition of both Staphylococcus aureus and Escherichia coil, extending the shelf life of marinated steak from 3 to 7 days.

Development and characterization of wax-bovine bone protein-grapeseed oil composite oleogels: Experimental and molecular simulation studies.

Three new types of composite oleogel formulations were designed. Specifically, oleogels were prepared using 90% grapeseed oil as the oil phase and carnauba wax (CW)/beeswax/rice bran wax-bovine bone protein (BBP) as gelators. All samples were solid and had an oil-binding capacity of >90%. BBP addition considerably improved the waxy texture of the oleogel and had an important effect on the crystalline network. X-ray diffractometry indicated that BBP increased the ß'-crystal content. All samples showed sol-gel thermodynamic behavior under temperature scanning. Fourier-transform infrared spectroscopy and molecular docking confirmed the formation of noncovalent interactions dominated by van der Waals forces during the development of the oleogel. The optimal components of the three oleogels exhibited an excellent effect of slowing down the release of free fatty acids. This study could serve as a reference for the development and application of wax-protein as a new binary gelator in the food industry.

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.

Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored for diverse cell types. In this study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry. AGILE streamlines ionizable lipid development with efficient library design, in silico lipid screening via deep neural networks, and adaptability to diverse cell lines. Using AGILE, we rapidly design, synthesize, and evaluate ionizable lipids for mRNA delivery, selecting from a vast library. Intriguingly, AGILE reveals cell-specific preferences for ionizable lipids, indicating tailoring for optimal delivery to varying cell types. These highlight AGILE's potential in expediting the development of customized LNPs, addressing the complex needs of mRNA delivery in clinical practice, thereby broadening the scope and efficacy of mRNA therapies.

Simulating behavior of perfluorooctane sulfonate (PFOS) in the mainstream of a river system with sluice regulations.

Perfluorooctane sulfonate (PFOS) is a persistent, anionic and ubiquitous contaminant that undergoes long-range transport within the environment. Its behavior has attracted wide-range academic and regulatory attention. In this article, a mass balance model was employed to simulate PFOS concentrations in the mainstream of Haihe River water system, encompassing sluices and artificial rivers. The dynamic simulation of PFOS concentrations in both sediment and freshwater took into account fluctuations in PFOS emissions, water levels and water discharge. Furthermore, the study delved into exploring the impacts of sluices and artificial rivers on the behavior of PFOS. The simulated concentrations of PFOS in steady state agreed with the measured concentrations in surveys carried out in Nov. 2019, July 2020, Oct. 2020, and June 2021. Every year, approximately 24 kg PFOS was discharged into the Bohai Sea with Chaobai New River being the largest contributor for 44 %. Moreover, the transport of PFOS in the original rivers is likely to be restricted by sluices and replaced by artificial rivers. Monte Carlo analysis showed that model predictions of PFOS concentrations in sediment were subject to greater uncertainty than those in freshwater as the former is impacted by more parameters, such as density of sediment. This study provides a scientific basis for the local government to manage and control PFOS.

Estimating industrial process emission and assessing carbon dioxide equivalent of perfluorooctanoic acid (PFOA) and its salts in China.

Air pollution and climate change are closely linked because many greenhouse gases (GHGs) and air pollutants come from the same source. Perfluorinated compounds (PFCs) are new pollutants that have received high attention in recent years, as they are not only harmful to human health, but also important contributors to climate change. Therefore, PFCs are the key gases for the coordinated governance of air pollution and climate change. With the geographical shift of fluoropolymer production, the main emitters of perfluorooctanoic acid and its salts (PFOA/PFO) moved from North America, Europe and Japan to emerging Asian economies, especially China. In this study, industrial sources of PFOA/PFO in the Chinese atmosphere were identified, and its atmospheric emissions, carbon dioxide equivalent (CO2e) emissions and environmental risks were assessed. China released about 38.19 tons PFOA/PFO into the atmosphere through industrial activities in 2019, 97 % of which originated from the production of fluoropolymers. PFOA/PFO showed aggregative emission along the eastern coastal zone, especially in the Yangtze River Delta. Cumulative PFOA/PFO emission from all provinces equaled to 0.28-0.47 million tons CO2e, of which Jiangsu and Zhejiang took the lead, while Shanghai's CO2-equivalent emissions intensity of PFOA/PFO in terms of area, population, gross domestic product (GDP), and industrial added value took the first in China. The available monitoring data on atmospheric concentration of PFOA in urban and rural China implied that its distribution pattern was similar to PFOA/PFO emissions, that is, the concentrations in the eastern regions with the highest degree of industrialization were significantly higher than that in the central and western regions, and the PFOA concentrations in urban China were higher than that in the rural, which proved that industrial use was an important source of PFOA pollution and would cause significant risks to the environment.

Source-specific ecological risks and critical source identification of PPCPs in surface water: Comparing urban and rural areas.

To control the concentrations of pharmaceutical and personal care products (PPCPs) in the surface water of urban and rural areas, it is important to explore the spatial variation in source-specific ecological risks and identify critical sources. Here, we focused on 22 PPCPs found in the effluent from wastewater treatment plants and surface water in Tianjin, and source-specific risk was quantitatively apportioned combining positive matrix factorization with ecological risk assessment. Results showed that rural areas exhibited a more severe contamination level than urban areas. Medical wastewater (30.1 %) accounted for the highest proportion, while domestic sewage posed the greatest threat to aquatic ecosystems. The incidence of potential risks (RQ > 0.01) caused by domestic sewage in urban areas (88.9 %) was higher than that in rural areas (75.9 %). However, PPCP risks caused by farmland drainage, aquaculture, and livestock discharge were mainly distributed in rural areas. The critical source identified in the entire region was domestic sewage (weight, 0.36), and its weight (0.51) in urban areas was greater than that in rural areas (0.32). The impact of aquaculture (weight, 0.16) in rural areas was noteworthy. These findings may contribute to developing environmental management strategies in key areas to help alleviate PPCP contamination worldwide.

Multimedia fate of sulfamethoxazole (SMX) in a water-scarce city by coupling fugacity model and HYDRUS-1D model.

Increased concentrations of pharmaceutical and personal care products (PPCPs) have raised concerns about their impact on the ecological system and human health. To understand the environmental impact of PPCPs, we evaluated the fate of a typical PPCP of sulfamethoxazole (SMX) in a water-scarce city of Tianjin during 2013-2020 using a coupled model based on the dynamic fugacity model and HYDRUS-1D model. The results showed that the coupled model successfully simulated the reported SMX concentrations in the main fate media of water and soils, which accounted for 46.4 % and 53.0 % with equilibrium concentrations of 135-165 ng/L and 0.4-0.5 ng/g, respectively. The cross-media transfer flux results showed that advection was the prime input path for SMX in water, while degradation was the dominant output path. Wastewater irrigation and degradation were the main transfer processes of SMX in the soil. Moreover, human activities (i.e., emission loads) and climate (i.e., temperature and precipitation) change can significantly affect the concentrations and transfer rate of SMX in the media. These findings provide basic data and methods for the risk assessment of SMX in water-scarce regions.

Carbon flow through continental-scale ground logistics transportation.

The flourishing logistics in both developed and emerging economies leads to huge greenhouse gas (GHG) emissions; however, the emission fluxes are poorly constrained. Here, we constructed a spatial network of logistic GHG emissions based on multisource big data at continental scale. GHG emissions related to logistics transportation reached 112.14 Mt CO2-equivalents (CO2e), with seven major urban agglomerations contributing 63% of the total emissions. Regions with short transport distances and well-developed road infrastructure had relatively high emission efficiency. Underlying value flow of the commodities is accompanied by logistics carbon flow along the supply chain. The main driving factors affecting GHG emissions are driving speed and gross domestic product. It may mitigate GHG emissions by 27.50-1162.75 Mt CO2e in 15 years if a variety of energy combinations or the appropriate driving speed (65-70 km/h) is adopted. The estimations are of great significance to make integrated management policies for the global logistics sector.

Stretchable ultrasonic arrays for the three-dimensional mapping of the modulus of deep tissue.

Serial assessment of the biomechanical properties of tissues can be used to aid the early detection and management of pathophysiological conditions, to track the evolution of lesions and to evaluate the progress of rehabilitation. However, current methods are invasive, can be used only for short-term measurements, or have insufficient penetration depth or spatial resolution. Here we describe a stretchable ultrasonic array for performing serial non-invasive elastographic measurements of tissues up to 4 cm beneath the skin at a spatial resolution of 0.5 mm. The array conforms to human skin and acoustically couples with it, allowing for accurate elastographic imaging, which we validated via magnetic resonance elastography. We used the device to map three-dimensional distributions of the Young's modulus of tissues ex vivo, to detect microstructural damage in the muscles of volunteers before the onset of soreness and to monitor the dynamic recovery process of muscle injuries during physiotherapies. The technology may facilitate the diagnosis and treatment of diseases affecting tissue biomechanics.

Effect of Material Anisotropy on the Mechanical Response of Automotive Steel under High Strain Rates.

A constitutive model for automobile steel with high elongation needs to be established to predict the dynamic deformation behavior under hydroforming applications. In order to clarify the confusing discrepancy in the essential parameters of the classical Cowper-Symonds (C-S) model, a series of automobile structural steels have been employed to investigate the strain rate response by conducting tensile dynamic deformation. Metallographic microscopy and orientation distribution functions were used to characterize the microstructure and texture components of the steels. The microstructure observation discloses that the matrix of all steels is mainly of ferrite and the texture constituent provides a framework for steel to withstand external deformation. The C-S model can be applied to simulate the dynamic deformation with satisfied expectations. It is concluded that the essential parameters D and p in the model show a specific relationship with the steel grade, and the parameter D is proportional to the steel grade and related to material anisotropy, while the parameter p is inversely proportional to the steel grade and has close links with the grain boundary characteristics.

Influences of impervious surfaces on ecological risks and controlling strategies in rapidly urbanizing regions.

Reducing ecological risks is important for promoting regional sustainable development. However, studies on the influence of impervious surfaces on ecological risks and risk control strategies in regions undergoing rapid urbanization are limited. Therefore, this study aimed to demonstrate the spatial-temporal dynamics of regional ecological risks using Beijing as a case study to reveal the influence of impervious surfaces and explore the controlling strategies of risks. We first characterized the ecological risks in Beijing based on the ecosystem service values and mapped the risk levels and temporal variations in risks. We then identified the ecological risk increases caused by impervious surface expansion and built linear regression models for impervious surface coverage (ISC) and risk index. Finally, we formulated ecological risk control strategies for the strategy categories identified based on the ISC thresholds. The results show that the mountainous areas mainly exhibited low ecological risk levels, and the plain areas mainly showed high levels. The expansion of impervious surface was the main cause of the relatively large temporal increase in ecological risks from 2005 to 2015. Moreover, the strategies for ecological risk control can be divided into four categories based on the division of ISC, with 30%, 70%, and 90% as the thresholds. For risk control strategies, reducing ISC is the most important measure to reduce ecological risks for the category with an ISC range of 90%-100%, and increasing the area proportions of forests and water bodies is the most effective measure for the category with an ISC range of 0%-30%. For the other two categories, controlling the ISC and other strategies are required. Our study can increase the understanding of the influences of impervious surfaces on ecological risks in rapidly urbanizing regions and help inform the formulation of strategies for controlling the ecological risks in Beijing.

Effects of urbanization on the distribution of polycyclic aromatic hydrocarbons in China's estuarine rivers.

Estuarine rivers are the primary medium for transporting pollutants from human activities to the ocean. Polycyclic aromatic hydrocarbons (PAHs) have substantial toxicity and pose a significant risk to ecosystem and human health. However, the influences of urbanization on their distribution, particularly in China where urbanization is occurring rapidly, remain unclear. This study took three coastal economic circles of China as research areas, and investigated PAHs (16 species) in the estuarine river water. 95.9% of the sampling sites demonstrated moderate PAHs pollution and moderate ecological risk. Coal and petroleum combustion was the primary source of PAHs, but the source composition varied among the regions. Air pollution caused by energy emissions, particularly carbon emissions, has a critical and differential effect on PAHs distribution and deposition. With the increasing use of clean energy, PAHs emissions have been gradually reduced, which provides an effective option for PAHs reduction in a rapidly urbanizing coastal region.

Two-dimensional dysprosium(III) coordination polymer: Structure, single-molecule magnetic behavior, proton conduction, and luminescence.

A new dysprosium (III) coordination polymer [Dy(Hm-dobdc) (H2O)2]·H2O (Dy-CP), was hydrothermal synthesized based on 4,6-dioxido-1,3-benzenedicarboxylate (H4m-dobdc) ligand containing carboxyl and phenolic hydroxyl groups. The Dy(III) center adopts an octa-coordinated [DyO8] geometry, which can be described as a twisted square antiprism (D 4d symmetry). Neighboring Dy(III) ions are interconnected by deprotonated Hm-dobdc3- ligand to form the two-dimensional infinite layers, which are further linked to generate three-dimensional structure through abundant hydrogen bonds mediated primarily by coordinated and lattice H2O molecules. Magnetic studies demonstrates that Dy-CP shows the field-induced slow relaxation of magnetization and the energy barrier U eff/k B and relaxation time τ 0 are 35.3 K and 1.31 × 10-6 s, respectively. Following the vehicular mechanism, Dy-CP displays proton conductivity with σ equal to 7.77 × 10-8 S cm-1 at 353 K and 30%RH. Moreover, luminescence spectra reveal that H4m-dobdc can sensitize characteristic luminescence of Dy(III) ion. Herein, good magnetism, proton conduction, and luminescence are simultaneously achieved, and thus, Dy-CP is a potential multifunctional coordination polymer material.

Perfluoroalkyl acids (PFAAs) in water along the entire coastal line of China: Spatial distribution, mass loadings, and worldwide comparisons.

Perfluoroalkyl acids (PFAAs) have been ubiquitously distributed in water environment worldwide for a long time, especially in the estuaries and coastal areas. In this study, the distribution characteristics of 12 PFAAs in 91 main river estuaries along the entire coast of China were analyzed for the first time, and the riverine PFAAs fluxes into the coastal marine environment were estimated. Based on a mini-review, the PFAAs pollution in the coast of China at a global scale was evaluated, which was intended to reveal the overall level of PFAAs and to provide a science basis for strengthening environmental management along the coast of China. The results showed that perfluorooctanoic acid (PFOA), perfluorobutanoic acid (PFBA), and perfluorobutane sulfonic acid (PFBS) were dominant in the whole coastal region, which indicated the usage of PFAAs was changing from long-chain PFAAs to short-chain substitutes in China. With regard to the spatial distribution, the high PFAAs concentrations were found in the coastal areas of south Bohai Sea, Shandong Province from the north while those in the south were generally lower when taking the Qinling Mountain and Huaihe River as a dividing line. The estimated PFAAs riverine mass loading in the whole coastal region was 131 tons per year, and the discharge flux of the Yangtze River accounted for more than half (73.5 tons). In comparison with global data, PFAAs concentrations in the coast of China was at a moderate level, and the detected hotspots of high levels were strongly influenced by fluorochemical industries. However, the mass loading of PFAAs was diversified due to geographical differences and abundant river discharges.

Multiple pollutants stress the coastal ecosystem with climate and anthropogenic drivers.

Coastal ecosystem health is of vital importance to human well-being. Field investigations of major pollutants along the whole coast of China were carried out to explore associations between coastal development activities and pollutant inputs. Measurements of target pollutants such as PFAAs and PAHs uncovered notable levels in small estuary rivers. The Yangtze River was identified to deliver the highest loads of these pollutants to the seas as a divide for the spatial distribution of pollutant compositions. Soil concentrations of the volatile and semi-volatile pollutants showed a cold-trapping effect in pace with increasing latitudinal gradient. The coastal ecosystem is facing high ecological risks from metal pollution, especially copper (Cu) and zinc (Zn), while priority pollutants of high risks vary for different kinds of protected species, and the ecological risks were influenced by both climate and physicochemical properties of environmental matrices, which should be emphasized to protect and restore coastal ecosystem functioning.

Coupling relation between urbanization and ecological risk of PAHs on coastal terrestrial ecosystem around the Bohai and Yellow Sea.

Urbanization, the ecological risks of polycyclic aromatic hydrocarbons (PAHs) to terrestrial ecosystems, and the complex relationship between them have drawn globally attention. In this paper, a comprehensive indicator system was calculated to illustrate the levels of urbanization in 20 coastal cities around the Bohai and Yellow Sea. The top three cities with high levels of urbanization were Tianjin > Qingdao > Dalian. The ecological risk of phenanthrene (Phe) was 52.0%; while the risk of fluoranthene (Flt) was 25.8%, and that of pyrene (Pyr), benzo[a]anthracene (Bap), fluorene (Flu), and naphthalene (Nap) were below 20% throughout the entire region. Risks were high in Dandong, Tianjin, Tangshan, Nantong, and Lianyungang and low in Weihai, Dongying, and Rizhao. The degree of coupling between urbanization and ecological risk of PAHs was above high (0.6) and more than 50% of the coordination degrees were slight unbalance [0.3, 0.5). Furthermore, redundancy analysis showed that the indicator aspects of industry, transportation, and population made great contribution to PAHs risk. Industry correlated to Low Molecular Weight (LMW) PAHs, while transportation correlated to High Molecular Weight (HMW) PAHs. To minimize risk, urbanization scale should be under acceptable level, or the structure of industry and transportation should be optimized.