An ensemble machine learning model to uncover potential sites of hazardous waste illegal dumping based on limited supervision experience.

With the soaring generation of hazardous waste (HW) during industrialization and urbanization, HW illegal dumping continues to be an intractable global issue. Particularly in developing regions with lax regulations, it has become a major source of soil and groundwater contamination. One dominant challenge for HW illegal dumping supervision is the invisibility of dumping sites, which makes HW illegal dumping difficult to be found, thereby causing a long-term adverse impact on the environment. How to utilize the limited historic supervision records to screen the potential dumping sites in the whole region is a key challenge to be addressed. In this study, a novel machine learning model based on the positive-unlabeled (PU) learning algorithm was proposed to resolve this problem through the ensemble method which could iteratively mine the features of limited historic cases. Validation of the random forest-based PU model showed that the predicted top 30% of high-risk areas could cover 68.1% of newly reported cases in the studied region, indicating the reliability of the model prediction. This novel framework will also be promising in other environmental management scenarios to deal with numerous unknown samples based on limited prior experience.

Measuring climate change perception in China using mental images: A nationwide open-ended survey.

Current knowledge about public climate change perception mainly covers belief, concern, and attitudes. However, how this discourse is interpreted using individuals' own frame of reference remains largely unknown, particularly in many large emitters from non-Annex I countries such as China. This study, for the first time, performs a nationwide open-ended survey covering 4,037 respondents and collected 12,100 textual answers. Using a semiautomated coding method, we find seven mental images that exclusively represent the Chinese interpretation of the climate change issue, including global warming, distant icons, natural disasters, environmental degradation, cause, solution, and weather. Analysis of influencing factors shows that females, those with lower education levels, lower income, and older individuals tend to connect climate change with natural weather phenomena. Younger and well-educated residents in developed cities are more aware of various consequences and anthropogenic causes of climate change. People with stronger climate change beliefs, policy support, and personal experience of extreme weather are more likely to mention disastrous impacts, carbon emission as causes, and potential solutions. Employing the multilevel regression and post-stratification technique, we map the prevalence of mental images in China at the prefecture-city level. The results reveal significant geographical heterogeneity, with estimated national means ranging from a high of 55% (weather) to a low of 11% (solution). Our findings reveal diverse perspectives and a widespread misconception of climate change in China, suggesting the need for tailored clarification strategies to gain public consent.

Dynamic immunoediting by macrophages in homologous recombination deficiency-stratified pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease, notably resistant to existing therapies. Current research indicates that PDAC patients deficient in homologous recombination (HR) benefit from platinum-based treatments and poly-ADP-ribose polymerase inhibitors (PARPi). However, the effectiveness of PARPi in HR-deficient (HRD) PDAC is suboptimal, and significant challenges remain in fully understanding the distinct characteristics and implications of HRD-associated PDAC. We analyzed 16 PDAC patient-derived tissues, categorized by their homologous recombination deficiency (HRD) scores, and performed high-plex immunofluorescence analysis to define 20 cell phenotypes, thereby generating an in-situ PDAC tumor-immune landscape. Spatial phenotypic-transcriptomic profiling guided by regions-of-interest (ROIs) identified a crucial regulatory mechanism through localized tumor-adjacent macrophages, potentially in an HRD-dependent manner. Cellular neighborhood (CN) analysis further demonstrated the existence of macrophage-associated high-ordered cellular functional units in spatial contexts. Using our multi-omics spatial profiling strategy, we uncovered a dynamic macrophage-mediated regulatory axis linking HRD status with SIGLEC10 and CD52. These findings demonstrate the potential of targeting CD52 in combination with PARPi as a therapeutic intervention for PDAC.

Climate adaptation through crop migration requires a nexus perspective for environmental sustainability in the North China Plain.

Crop migration can moderate the impacts of global warming on crop production, but its feedback on the climate and environment remains unknown. Here we develop an integrated framework to capture the climate impacts and the feedback of adaptation behaviours with the land-water-energy-carbon nexus perspective and identify opportunities to achieve the synergies between climate adaptation and environmental sustainability. We apply the framework to assess wheat and maize migration in the North China Plain and show that adaptation through wheat migration could increase crop production by ~18.5% in the 2050s, but at the cost of disproportional increment in land use (~19.2%), water use (~20.2%), energy use (~19.5%) and carbon emissions (~19.9%). Irrigation and fertilization management are critical mitigation opportunities in the framework, through which wheat migration can be optimized to reduce the climatic and environmental impacts and avoid potential carbon leakage. Our work highlights the sustainable climate adaptation to mitigate negative environmental externalities.

Water Scarcity Assessment of Hydropower Plants in China under Climate Change, Sectoral Competition, and Energy Expansion.

Hydropower plays a pivotal role in low-carbon electricity generation, yet many projects are situated in regions facing heightened water scarcity risks. This research devised a plant-level Hydropower Water Scarcity Index (HWSI), derived from the ratio of water demand for electricity generation to basin-scale available runoff water. We assessed the water scarcity of 1736 hydropower plants in China for the baseline year 2018 and projected into the future from 2025 to 2060. The results indicate a notable increase in hydropower generation facing moderate to severe water scarcity (HWSI >0.05), rising from 10% in 2018 to 24-34% of the national total (430-630 TWh), with a projected peak in the 2030s-2040s under the most pessimistic scenarios. Hotspots of risk are situated in the southwest and northern regions, primarily driven by decreased river basin runoff and intensified sectoral water use, rather than by hydropower demand expansion. Comparative analysis of four adaptation strategies revealed that sectoral water savings and enhancing power generation efficiency are the most effective, potentially mitigating a high of 16% of hydropower risks in China. This study provides insights for formulating region-specific adaptation strategies and assessing energy-water security in the face of evolving environmental and societal challenges.

Data-driven approaches linking wastewater and source estimation hazardous waste for environmental management.

Industrial enterprises are major sources of contaminants, making their regulation vital for sustainable development. Tracking contaminant generation at the firm-level is challenging due to enterprise heterogeneity and the lack of a universal estimation method. This study addresses the issue by focusing on hazardous waste (HW), which is difficult to monitor automatically. We developed a data-driven methodology to predict HW generation using wastewater big data which is grounded in the availability of this data with widespread application of automatic sensors and the logical assumption that a correlation exists between wastewater and HW generation. We created a generic framework that used representative variables from diverse sectors, exploited a data-balance algorithm to address long-tail data distribution, and incorporated causal discovery to screen features and improve computation efficiency. Our method was tested on 1024 enterprises across 10 sectors in Jiangsu, China, demonstrating high fidelity (R² = 0.87) in predicting HW generation with 4,260,593 daily wastewater data.

Care needs for urinary incontinence in older adults: Latent profile analysis.

AIM: This study utilized latent profile analysis to investigate care needs subgroups among older adults with urinary incontinence. METHODS: The "Elderly Urinary Incontinence Care Needs Inventory" surveyed 510 participants in two Guangzhou City hospitals from July 2022 to June 2023. Latent profile analysis created a classification model, and variance and correlation analysis assessed influencing factors. RESULTS: A total of 510 older adults with urinary incontinence participated. The standardized total care needs score was 78.77 ± 5.03, with variations across dimensions: social participation needs scored (71.16 ± 10.32), daily life care needs (78.80 ± 5.51), medical care needs (77.33 ± 12.17), psychological comfort needs (76.97 ± 6.51) and health education needs scored highest (82.67 ± 6.77). Three distinct profiles emerged: "medium," "high SPN-PCN" and "high DLCN-MCN-HEN". The majority belonged to the "high SPN-PCN" profile. Significant correlations were found with age, education, leaks and frequency of micturitions. CONCLUSION: Research findings showed the existence of three distinct categories, with a notable majority of participants belonging to the "high SPN-PCN" group. The significance of having these classes identified lies in the move away from a one-size-fits-all approach to a more nuanced understanding of care needs. Customized nursing interventions can be devised based on specific factors, such as age, education level, urinary incontinence-related symptoms and potential category. For instance, for the "high SPN-PCN" group, our nursing strategy can encompass heightened psychological support and expanded opportunities for social engagement.Furthermore, in the training and education of healthcare professionals, recognizing and meeting the needs of each potential category of older adults might require more attention. Geriatr Gerontol Int 2024; 24: 758-765.

Care Needs of Older Adults With Urinary Incontinence: A Cross-Sectional Study.

PURPOSE: To explore care requirements of older adults with urinary incontinence (UI) and contributing factors. METHOD: This cross-sectional study used the Older Adults Urinary Incontinence Care Needs Inventory to survey participants with UI in three large-scale tertiary hospitals located in Guangzhou City, China, from January 2023 to November 2023. Statistical analyses, including analysis of variance, t tests, correlation analyses, and linear regression models, were conducted to assess factors influencing participants' care needs. RESULTS: A total of 530 older adults with UI participated in the survey and mean standardized score for overall care needs was 78.65 (SD = 5.01), with mean scores for each dimension ranging from 70.88 (SD = 10.55) for social participation needs to 82.45 (SD = 7.11) for health education needs. Factors that were found to influence incontinence care needs in older adults included age, literacy level, number of leaks, and type of disease (F = 37.07, adjusted R2 = 0.290, p < 0.001). CONCLUSION: Comprehensive care for older adults with UI, encompassing physiological, psychological, and social aspects, is crucial. It is essential to tailor care to individual needs and characteristics, taking into account factors, such as age and education, to ensure effective care. [Journal of Gerontological Nursing, 50(5), 43-49.].

Overview of the recent advances in porcine epidemic diarrhea vaccines.

Vaccination is the most effective means of preventing and controlling porcine epidemic diarrhea (PED). Conventional vaccines developed from porcine epidemic diarrhea virus (PEDV) GI-a subtypes (CV777 and SM98) have played a vital role in preventing classical PED. However, with the emergence of PEDV mutants in 2010, conventional PEDV GI-a subtype-targeting vaccines no longer provide adequate protection against PEDV GII mutants, thereby making novel-type PED vaccine development an urgent concern to be addressed. Novel vaccines, including nucleic acid vaccines, genetically engineered subunit vaccines, and live vector vaccines, are associated with several advantages, such as high safety and stability, clear targeting, high yield, low cost, and convenient usage. These vaccines can be combined with corresponding ELISA kits to differentiate infected from vaccinated animals, which is beneficial for disease confirmation. This review provides a detailed overview of the recent advancements in PED vaccines, emphasizing on the research and application evaluation of novel PED vaccines. It also considers the future directions and challenges in advancing these vaccines to widespread use in clinics.

Informing Urban Flood Risk Adaptation by Integrating Human Mobility Big Data During Heavy Precipitation.

Understanding the impact of heavy precipitation on human mobility is critical for finer-scale urban flood risk assessment and achieving sustainable development goals #11 to build resilient and safe cities. Using ∼2.6 million mobile phone signal data collected during the summer of 2018 in Jiangsu, China, this study proposes a novel framework to assess human mobility changes during rainfall events at a high spatial granularity (500 m grid cell). The fine-scale mobility map identifies spatial hotspots with abnormal clustering or reduced human activities. When aggregating to the prefecture-city level, results show that human mobility changes range between -3.6 and 8.9%, revealing varied intracity movement across cities. Piecewise structural equation modeling analysis further suggests that city size, transport system, and crowding level directly affect mobility responses, whereas economic conditions influence mobility through multiple indirect pathways. When overlaying a historical urban flood map, we find such human mobility changes help 23 cities reduce 2.6% flood risks covering 0.45 million people but increase a mean of 1.64% flood risks in 12 cities covering 0.21 million people. The findings help deepen our understanding of the mobility pattern of urban dwellers after heavy precipitation events and foster urban adaptation by supporting more efficient small-scale hazard management.

Economic risks hidden in local water pollution and global markets: A retrospective analysis (1995-2010) and future perspectives on sustainable development goal 6.

Pollution from untreated wastewater discharges depletes clean water supply for humans and the environment. It poses adverse economic impacts by determining agricultural yields, manufacturing productivity, and ecosystem functionality. Current studies mainly focus on quantity-related water scarcity assessment. It is unknown how low water quality amplifies local water stress and induces cascading economic risks globally. In this study, we estimated both quality and quantity-related water scarcity index (WSI), local economic water scarcity risk (WSR), and cascading virtual WSR evident in global trade markets across 40 major economies from 1995 to 2010. We find developing countries, e.g., India and China, witnessed fast growth in both quantity and quality-related WSI. Major developed economies, e.g., the US and Germany, experienced a modest increase in water stress but alleviated quality-related risks. Local economic risk (WSR) grew from $116B to $380B, with quality-related risks rising from 20 % to 30 %. Virtual economic WSR in global supply chains increased from $39B to $160B, with quality-related risks increasing from 19 % to 27 %. China became the top exporter of economic WSR, ranked above the US, France, and Japan, and the second-largest position as an importer, trailing only the US. We finally conducted scenario modeling by 2030, assuming different progresses on SDG 6 targets. The findings suggest that only the most ambitious progress in both water quality enhancement and efficiency improvement helps to alleviate ∼20 % economic WSR globally. Our findings underscore the necessity for strategies that integrate management of untreated wastewater flows, improved water use efficiency, and diversification of supply chain networks to enhance global economic resilience to water challenges in the future.

TSPAN1 inhibits metastasis of nasopharyngeal carcinoma via suppressing NF-kB signaling.

Nasopharyngeal carcinoma (NPC) originates in the epithelial cells of the nasopharynx and is a common malignant tumor in southern China and Southeast Asia. Metastasis of NPC remains the main cause of death for NPC patients even though the tumor is sensitive to radiotherapy and chemotherapy. Here, we found that the transmembrane protein tetraspanin1 (TSPAN1) potently inhibited the in vitro migration and invasion, as well as, the in vivo metastasis of NPC cells via interacting with the IKBB protein. In addition, TSPAN1 was essential in preventing the overactivation of the NF-kB pathway in TSPAN1 overexpressing NPC cells. Furthermore, reduced TSPAN1 expression was associated with NPC metastasis and the poor prognosis of NPC patients. These results uncovered the suppressive role of TSPAN1 against NF-kB signaling in NPC cells for preventing NPC metastasis. Its therapeutic value warrants further investigation.

Integrating Augmented In Situ Measurements and a Spatiotemporal Machine Learning Model To Back Extrapolate Historical Particulate Matter Pollution over the United Kingdom: 1980-2019.

Historical PM2.5 data are essential for assessing the health effects of air pollution exposure across the life course or early life. However, a lack of high-quality data sources, such as satellite-based aerosol optical depth before 2000, has resulted in a gap in spatiotemporally resolved PM2.5 data for historical periods. Taking the United Kingdom as an example, we leveraged the light gradient boosting model to capture the spatiotemporal association between PM2.5 concentrations and multi-source geospatial predictors. Augmented PM2.5 from PM10 measurements expanded the spatiotemporal representativeness of the ground measurements. Observations before and after 2009 were used to train and test the models, respectively. Our model showed fair prediction accuracy from 2010 to 2019 [the ranges of coefficients of determination (R2) for the grid-based cross-validation are 0.71-0.85] and commendable back extrapolation performance from 1998 to 2009 (the ranges of R2 for the independent external testing are 0.32-0.65) at the daily level. The pollution episodes in the 1980s and pollution levels in the 1990s were also reproduced by our model. The 4-decade PM2.5 estimates demonstrated that most regions in England witnessed significant downward trends in PM2.5 pollution. The methods developed in this study are generalizable to other data-rich regions for historical air pollution exposure assessment.

Trade-offs between cold protection and air pollution-induced mortality of China's heating policy.

The winter heating policy in northern China was designed to safeguard households from the harsh subfreezing temperatures. However, it has inadvertently resulted in seasonal spikes in air pollution levels because of the reliance on coal as an energy source. While the loss of life years attributable to mortality from air pollution caused by winter heating has been estimated, the beneficial effect of protection from cold temperatures has not been assessed, primarily due to a lack of individual-level data linking these variables. Our study aims to address this research gap. We provide individual-level empirical evidence that quantifies the impact of protection from cold temperatures and air pollution on mortality, studying 5,334 older adults living around the Huai River during the period between 2000 and 2018. Our adjusted Cox-proportional hazard models show that winter heating was associated with a 22% lower mortality rate (95% CI: 16-28%). Individuals residing in areas without access to winter heating are subjected to heightened mortality risks during periods of cold temperatures. The protective effect is offset by a 27.8% rise attributed to elevated PM2.5 levels. Our results imply that the equilibrium between the effects of these two factors is achieved when PM2.5 concentration exceeds 24.3 µg/m3 (95% CI: 18.4-30.2). Our research suggests that while the existing winter heating policy significantly mitigates winter mortality by lessening the detrimental effects of cold temperatures, future air pollution reduction could provide further health benefits.

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OBJECTIVES: To explore the association between assisted reproductive technology (ART) and birth weight discordance in twins (BWDT). METHODS: A retrospective analysis was conducted on twin infants born between January 2011 and December 2020 at the Third Affiliated Hospital of Guangzhou Medical University, with complete basic birth data. The impact of ART on the occurrence of BWDT was identified by the multivariate logistic regression analysis. RESULTS: A total of 3 974 pairs of twins were included, with 1 431 conceived naturally and 2 543 through ART. Neonates in the ART group had higher birth weights than those in the naturally conceived group (P<0.001). The incidence of BWDT was lower in the ART group compared to the naturally conceived group (16.17% vs 21.09%, P<0.001). The multivariate logistic regression analysis, adjusting for confounding factors such as maternal age, parity, pre-pregnancy body mass index, gestational diabetes, hypothyroidism, gestational age, and chorionic properties, showed no significant difference in the risk of BWDT between the ART and naturally conceived groups (P>0.05). CONCLUSIONS: ART is not associated with the risk of BWDT.

The economy-employment-environmental health transfer and embedded inequities of China's capital metropolitan area: a mixed-methods study.

BACKGROUND: Metropolitan areas have complex trade linkages internally and externally. This complexity stimulates the unequal spatial transfer of environmental health consequences, economy, and employment embodied in internal trade or trade with the outside regions, resulting in unequal exchange. Existing research has rarely discussed this issue at a refined scale, hindering targeted inequity alleviation policies. METHODS: We conducted a mixed-methods study, focusing on the most polluted metropolitan area in the world, the Beijing-Tianjin-Hebei region of China, and developed an integrated modelling framework to downscale the analysis of the trade-driven unequal transfer of PM2·5- related premature deaths, value added, and job opportunities to the city scale within Beijing-Tianjin-Hebei. The study couples a nested Multi-Regional Input-Output model table containing data from 13 Beijing-Tianjin-Hebei cities and 28 outer provinces in 2017 with a bottom-up emission inventory, value added and employment statistical data, the Weather Research and Forecasting-Comprehensive Air Quality Model with Extensions, the Global Exposure Mortality Model, and human capital methods. We also constructed two indices measuring unequal exchanges between PM2·5-related deaths and economic and employment gains embodied in trades between cities in Beijing-Tianjin-Hebei and trades with outside regions. FINDINGS: The Beijing-Tianjin-Hebei region as a single entity shifted 14 985 (95% CI 12 800-16 948) net deaths to regions outside the Beijing-Tianjin-Hebei through trade, most of which occurred in the central region of China. The industrial-based peripheral Beijing-Tianjin-Hebei cities suffered the most serious inequities when trading with other Beijing-Tianjin-Hebei cities and outside regions. While gaining equivalent local jobs, these industrial-based peripheral cities had 250% higher PM2·5-related deaths (10·2 PM2·5-related deaths for obtaining 1000 local jobs) than core cities (2·9 PM2·5-related deaths for obtaining 1000 local jobs) and 57·7% higher PM2·5-related deaths than agricultural-based peripheral cities (6·5 PM2·5-related deaths for obtaining 1000 local jobs). While gaining equivalent value added, industrial-based peripheral cities had 50·6% higher PM2·5-related deaths (¥13·9 of reduced human capital due to PM2·5-related premature deaths to obtain ¥1000 local value added) than core cities (¥9·2 of reduced human capital due to PM2·5-related premature deaths to obtain ¥1000 local value added) and 67·4% higher PM2·5-related deaths than agricultural-based peripheral cities (¥8·3 of reduced human capital due to PM2·5-related premature deaths to obtain ¥1000 local value added). INTERPRETATION: Treating metropolitan areas as a single entity obscured internal heterogeneity, potentially misleading policy makers into imposing strict regulations on the whole metropolitan area to alleviate the inequities it posed on outside regions. However, several peripheral Beijing-Tianjin-Hebei cities were disadvantaged in their trade with core Beijing-Tianjin-Hebei cities and outside regions. Therefore, policies should be tailored for particular cities within metropolitan areas. Future targeted policies should include, but not be limited to, making ecological compensations and incorporating the environment and health costs into the price of pollution-intensive goods and services. FUNDING: National Key Research and Devlopment Program of China, National Natural Science Foundation of China, and Jiangsu Natural Science Foundation.

SPI1-Mediated Upregulation of the CST1 Gene as an Independent Poor Prognostic Factor Accelerates Metastasis in Esophageal Squamous Cell Carcinoma (ESCC) by Interacting with MMP2.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a highly lethal tumor type, but studies on the ESCC tumor microenvironment are limited. We found that cystatin SN (CST1) plays an important role in the ESCC tumor microenvironment. CST1 has been reported to act as an oncogene in multiple human cancers, but its clinical significance and underlying mechanism in ESCC remain elusive. METHODS: We performed ESCC gene expression profiling with data from RNA-sequencing and public databases and found CST1 upregulation in ESCC. Then, we assessed CST1 expression in ESCC by RT‒qPCR and Western blot analysis. In addition, immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA) were used to estimate the expression of CST1 in ESCC tissue and serum. Moreover, further functional experiments were conducted to verify that the gain and loss of CST1 in ESCC cell lines significantly influenced the proliferation and metastasis of ESCC. Mass spectrometry, coimmunoprecipitation, and gelatin zymography experiments were used to validate the interaction between CST1 and matrix metalloproteinase 2 (MMP2) and the mechanism of CST1 influence on metastasis in ESCC. RESULTS: Here, we found that CST1 expression was significantly elevated in ESCC tissues and serum. Moreover, compared with patients with low CST1 expression, patients with high CST1 expression had a worse prognosis. Overall survival (OS) and disease-free survival (DFS) were significantly unfavorable in the high CST1 expression subgroup. Likewise, the CST1 level was significantly increased in ESCC serum compared with healthy control serum, indicating that CST1 may be a potential serum biomarker for diagnosis, with an area under the curve (AUC) = 0.9702 and p < 0.0001 by receiver operating curve (ROC) analysis. Furthermore, upregulated CST1 can promote the motility and metastatic capacity of ESCC in vitro and in vivo by influencing epithelial mesenchymal transition (EMT) and interacting with MMP2 in the tumor microenvironment (TME). CONCLUSIONS: Collectively, the results of this study indicated that high CST1 expression mediated by SPI1 in ESCC may serve as a potentially prognostic and diagnostic predictor and as an oncogene to promote motility and metastatic capacity of ESCC by influencing EMT and interacting with MMP2 in the TME.

Sliding Window-Based Machine Learning for Environmental Inspection Resource Allocation.

Environmental regulation is pivotal in mitigating environmental risks and promoting sustainable development, yet regulators frequently encounter resource constraints when inspecting enterprises. To address this limitation, we employed four sliding window-based machine learning techniques to enhance effective environmental inspections. Utilizing feature-engineered time-series data of characteristic and compliance records from 16,777 chemical enterprises in Jiangsu between 2010 and 2021, the four models were used to establish the predictive models that link enterprise characteristics to the likelihood of inspection failure. The results indicated that the models were comparable with the widely utilized deep learning sequence model, the Long Short-Term Memory model, achieving areas under the ROC (receiver operating characteristic) curves exceeding 0.83. Past violation significantly influences future violations, with a more recent violation history exerting stronger impacts. Besides, using predicted failure rates, we proposed seven resource allocation scenarios, considering different regulation intensities to target high-risk enterprises. Notably, the provincial-level risk-based method yielded a significant inspection failure rate increase (detecting violation), surpassing 8-fold the baseline. Overall, our study offers regulators an optimized inspection resource allocation method, thereby enhancing the regulatory effectiveness. Moreover, this study demonstrates the potential of window-based machine learning techniques in environmental regulation and highlights the importance of data-driven decision-making for promoting sustainable development.

Samarium-Doped Lead Magnesium Niobate-Lead Titanate Ceramics Fabricated by Sintering the Mixture of Two Different Crystalline Phases.

The fabrication method plays a key role in the performance of lead magnesium niobate-lead titanate-based ceramics. (1 - w)[Pb(Mg1/3Nb2/3)0.67Ti0.33O3]-w[Pb1-1.5xSmx(Mg1/3Nb2/3)yTi1-yO3] piezoelectric ceramics were prepared by sintering the mixture of two different crystalline phases in which two pre-sintered precursor powders were mixed and co-fired at designated ratios (w = 0.3, 0.4, 0.5, 0.6). The X-ray diffraction results show that all the ceramics presented a pure perovskite structure. The grains were closely packed and the average size was ~5.18 µm based on observations from scanning electron microscopy images, making the ceramics have a high density that is 97.8% of the theoretical one. The piezoelectric, dielectric, and ferroelectric properties of the ceramics were investigated systematically. It was found that the properties of the ceramics were significantly enhanced when compared to the ceramics fabricated using the conventional one-step approach. An outstanding piezoelectric coefficient d33 of 1103 pC/N and relative dielectric permittivity ε33/ε0 of 9154 was achieved for the ceramics with w = 0.5.

CD24+LCN2+ liver progenitor cells in ductular reaction contributed to macrophage inflammatory responses in chronic liver injury.

BACKGROUND: CD24+CK19+/CD24+SOX9+ resident liver cells are activated and expanded after chronic liver injury in a ductular reaction. However, the sources and functions of these cells in liver damage remain disputed. RESULTS: The current study combined genetic lineage tracing with in vitro small-molecule-based reprogramming to define liver progenitor cells (LPCs) derived from hepatic parenchymal and non-parenchymal tissues. tdTom+ hepatocytes were isolated from ROSA26tdTomato mice following AAV8-Tbg-Cre-mediated recombination, EpCAM+ biliary epithelial cells (BECs) from wild-type intrahepatic bile ducts and ALB/GFP-EpCAM- cells were isolated from AlbCreERT/R26GFP mice. A cocktail of small molecules was used to convert the isolated cells into LPCs. These in vitro cultured LPCs with CD24 and SOX9 expression regained the ability to proliferate. Transcriptional profiling showed that the in-vitro cultured LPCs derived from the resident LPCs in non-parenchymal tissues expressed Lipocalin-2 (Lcn2) at high levels. Accordingly, endogenous Cd24a+Lcn2+ LPCs were identified by integration of sc-RNA-sequencing and pathological datasets of liver dysfunction which indicates that LPCs produced by ductular reactions might also originate from the resident LPCs. Transplantation of in-vitro cultured Cd24a+Lcn2+ LPCs into CCl4-induced fibrotic livers exacerbated liver damage and dysfunction, possibly due to LCN2-dependent macrophage inflammatory response. CONCLUSIONS: CD24+LCN2+ LPCs constituted the expanding ductular reaction and contributed to macrophage-mediated inflammation in chronic liver damage. The current findings highlight the roles of LPCs from distinct origins and expose the possibility of targeting LPCs in the treatment of chronic hepatic diseases.