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Abstract Soft magnetic materials (SMMs) are indispensable for electromechanical energy conversion in high-efficiency applications, but they are exposed to increasing mechanical loading conditions in electric motors due to higher rotational speeds. Enhancing the yield strength of SMMs is essential to prevent the degradation in magnetic performance and failure from plastic deformation, yet most SMMs have yield strengths far below one gigapascal. Here, we present a multicomponent nanostructuring strategy that doubles the yield strength of SMMs while maintaining ductility. We introduce morphologically anisotropic nanoprecipitates through dislocation-driven precipitation induced by preceding deformation during heat treatment in an iron–nickel–cobalt–tantalum material. With all dimensions of the precipitates below the magnetic domain wall width, we achieve a high precipitate number density with a large specific surface area, small interprecipitate spacing, and high lattice mismatch, which impede dislocation glide and strengthen the material. Both the matrix and precipitates are ferromagnetic, yielding a high magnetic moment. This nanostructuring approach offers a pathway to two-gigapascal-strong ductile SMMs with moderately increased coercivity that can be tolerated in exchange for significantly improved mechanical performance for sustainable electrification.

Abstract Salvador, the capital of Bahia State in Brazil, has long struggled with pronounced economic and social inequality. This stratification has resulted in spatial segregation, leading to the expansion of favelas, typically near the city center, where segregation in various dimensions of social engagement intensifies tensions of inequities. The municipal government has made several attempts to address favela-related issues through urban planning policies. Notwithstanding the progress made in lowering violent crime and extreme poverty, these issues still exist. This paper explores the interaction between government-led practices and corresponding self-organized actions toward planning strategies, invoking a social justice framework and critical urban theories. It identifies mismatches between institutional objectives and residents’ expectations, highlighting that structural contradictions in the region’s social development remain unresolved. The analysis suggests that planning policies should consider key factors, such as resource redistribution, recognition of sociocultural identity, and political representation. On the basis of these findings, this paper offers insights into urban planning for favelas as examples of complex governance challenges. It also aims to contribute to the global discourse on similar urban planning issues.

Urban scenic forests provide urban residents with various physical and mental health and wellbeing services. However, in the research on the color quantification and health services of scenic forests, it is still unclear how their color quantification characteristics feedback on the stress - attention of the adolescent group. In this study, visual color elements (green, red and yellow) of three landscape forests were used to generate 48 images of four groups of urban landscape forests according to color combinations and proportions. Virtual images were used to assess the stress indicators and attention indicators of participants before and after viewing. The results showed that the four groups of experimental groups showed varying degrees of α wave reduction and β/α ratio increase after viewing, G1 group showed an extremely significant increase in β wave after image stimulation, G1 and G3 group significantly decreased θ/β power, G4 group and G5 control group had no significant change. Among the 16 channels of absolute α wave and absolute β wave in the brain, the F3 and F4 channels corresponding to the frontal lobe of the G3 group showed the most prominent consistency of β wave in the frontal cortex during highly concentrated mental activities. Our study shows that positive EEG (Electroencephalogram) feedback of arousal and attention recovery can be obtained by using monochromatic or two-color changing color features in urban landscape forest. This study can provide references and methods for urban forest planning, design and visual evaluation.

Nitrate leaching is the main pathway of reactive nitrogen loss in Chinese agricultural systems, leading to groundwater contamination. However, the effect of fertilization on reactive nitrogen losses through nitrate leaching under various natural conditions and key influencing factors in Chinese agricultural systems remains unclear. Therefore, we conducted a comprehensive meta-analysis of 394 observations from 50 published articles to investigate how management practices, climatic conditions, and soil properties influence nitrate leaching from upland and paddy fields in China. Our results showed that nitrogen fertilizer application (NFP) significantly increased nitrate leaching in paddy and upland fields, with paddy fields exhibiting lower nitrate leaching than upland fields. In paddy fields, soil pH and NFP timing were the main drivers of nitrate leaching, while in upland fields, NFP rate and pH were the main driving factors. The NFP rate showed a significant positive correlation with nitrate leaching in both upland and paddy fields. Combining chemical fertilizer and organic manure applications was the effective method for mitigating nitrate leaching in paddy and upland fields. The structural equation modeling (SEM) revealed significant effects of soil properties on the nitrate leaching in paddy and upland fields during the crop growing season (P15 ℃ helped mitigate the risk of nitrate leaching. Our findings provide valuable guidance for optimizing NFP in agricultural production to improve nitrogen use efficiency and reduce groundwater pollution.

With the rapid progress of artificial intelligence (AI) technology in medical scenarios, it becomes a trend for medical services to adopt various AI algorithms for auxiliary diagnosis and health care of patients. However, medical data is often sensitive and possibly owned by multiple participants without the willingness of data sharing. To solve this problem under the vertical partition scenario of medical data, a differentially private distributed collaborative XGBoost method named DP-DCXGBoost was proposed and applied for disease classification in the paper. Initially, a reputation-based participant selection algorithm was designed, which evaluated the contribution of participants to the global model and used it for reputation calculation to select proper participants. Then, in the collaborative training phase, the proposed method utilized the local vertical dataset of each participant to calculate feature buckets and splitting gains in order to collaboratively construct a differentially private global XGBoost classification model. Finally, the experimental analysis for two real disease datasets showed that the proposed method had good classification accuracy on the basis of preserving participants' data privacy.

Abstract Background To clarify the value of gait analysis and its consistency with traditional scoring scales for the evaluation of knee joint function after total knee arthroplasty (TKA). Methods This study included 25 patients with knee osteoarthritis (KOA) who underwent bilateral TKA, and 25 conditionally matched healthy individuals, categorised into the experimental and control groups, respectively. Patients in the experimental group underwent gait analysis and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) evaluation before and 1 year after TKA. Weight-bearing balance and walking stability were assessed using discrete trends of relevant gait indicators. Pearson’s correlation analysis was performed on the gait and WOMAC score data of the experimental group before and after TKA. Results One year after TKA, patients’ gait indices (except gait cycle) were significantly better than before surgery, but significantly worse than that of the control group (P 80%. The WOMAC scores and gait analysis results were significantly correlated before TKA (P

Ultra-microporous solid sorbents with high CO2 adsorption capacities and gas selectivity are preferred for carbon capture. Here we deliver such sorbents via a combination of narrow micropores, lack of mesopores and an abundance of CO2-philic functional groups. This was achieved by crosslinking lignin waste obtained from a local paper factory, in Lewis's acid deep eutectic solvents (DESs) such as [ChCl][ZnCl2]2 and [ChCl][FeCl3]2, varying crosslinker types and optimizing experimental parameters. Hypercrosslinked polymers (HCPs) prepared in [ChCl][FeCl3]2 with 1,4-dichloroxylene crosslinkers comprised quasi-unimodal, ultra-narrow micropores. At 298 K, 1 bar, and using a gas mixture comprising 15 vol.% CO2 and 85 vol.% N2 (similar to post-combustion flue gas), the CO2 adsorption capacity and CO2/N2 selectivity of this HCP reached 18.1 cm3 g−1 and 835, respectively. Deployed in temperature swing adsorption and evaluated for vacuum pressure swing adsorption, the CO2 recovery rates of this HCP were >87 %, outperforming commercial solid sorbents such as zeolite 13X and PSAO2 HP Molsiv™. The optimization of sorbent microporosity with CO2-philic functional groups could pave the route towards developing bio-derived solid sorbents for carbon capture.

Summary: Aging is closely associated with inflammation, which affects renal function reserve (RFR) in the kidneys. This study aims to investigate the impact of reduced RFR reduction on kidney aging and the influence of renal inflammation and RFR reduction on this process. Natural aging rats and those subjected to unilateral nephrectomy (UNX), 1/6 nephrectomy (1/6NX), and unilateral ureteral obstruction (UUO) were observed at 6, 12, 18, and 21 months. Our findings suggest that RFR reduction and renal inflammation can accelerate kidney aging, and inflammation contributes more. Metabolomics analysis revealed alterations in amino acid metabolism contribute to RFR decline. Furthermore, experiments in vitro confirmed the involvement of pentose phosphate pathway (PPP) in promoting aging though inflammation. Our research provides novel insights into for the mechanism of kidney aging and provides indirect support for clinical treatment decisions, such as addressing kidney inflammation, stones, or tumors that may necessitate partial or complete nephrectomy.

AimThe objective of this study is to develop accurate machine learning (ML) models for predicting the neurological status at hospital discharge of critically ill patients with hemorrhagic and ischemic stroke and identify the risk factors associated with the neurological outcome of stroke, thereby providing healthcare professionals with enhanced clinical decision-making guidance.Materials and methodsData of stroke patients were extracted from the eICU Collaborative Research Database (eICU-CRD) for training and testing sets and the Medical Information Mart for Intensive Care IV (MIMIC IV) database for external validation. Four machine learning models, namely gradient boosting classifier (GBC), logistic regression (LR), multi-layer perceptron (MLP), and random forest (RF), were used for prediction of neurological outcome. Furthermore, shapley additive explanations (SHAP) algorithm was applied to explain models visually.ResultsA total of 1,216 hemorrhagic stroke patients and 954 ischemic stroke patients from eICU-CRD and 921 hemorrhagic stroke patients 902 ischemic stroke patients from MIMIC IV were included in this study. In the hemorrhagic stroke cohort, the LR model achieved the highest area under curve (AUC) of 0.887 in the test cohort, while in the ischemic stroke cohort, the RF model demonstrated the best performance with an AUC of 0.867 in the test cohort. Further analysis of risk factors was conducted using SHAP analysis and the results of this study were converted into an online prediction tool.ConclusionML models are reliable tools for predicting hemorrhagic and ischemic stroke neurological outcome and have the potential to improve critical care of stroke patients. The summarized risk factors obtained from SHAP enable a more nuanced understanding of the reasoning behind prediction outcomes and the optimization of the treatment strategy.

Neurodevelopmental cell communication plays a crucial role in neuroblastoma prognosis. However, determining the impact of these communication pathways on prognosis is challenging due to limited sample sizes and patchy clinical survival information of single cell RNA-seq data. To address this, we have developed the cell communication pathway prognostic model (CCPPM) in this study. CCPPM involves the identification of communication pathways through single-cell RNA-seq data, screening of prognosis-significant pathways using bulk RNA-seq data, conducting functional and attribute analysis of these pathways, and analyzing the post-effects of communication within these pathways. By employing the CCPPM, we have identified ten communication pathways significantly influencing neuroblastoma, all related to axongenesis and neural projection development, especially the BMP7-(BMPR1B-ACVR2B) communication pathway was found to promote tumor cell migration by activating the transcription factor SMAD1 and regulating UNK and MYCBP2. Notably, BMP7 expression was higher in neuroblastoma samples with distant metastases. In summary, CCPPM offers a novel approach to studying the influence of cell communication pathways on disease prognosis and identified detrimental communication pathways related to neurodevelopment.

【Objective】A mathematical evaluation model, D(x), was established to provide a reference for the evaluation, identification and genetic improvement of seed vitality traits in rice.【Method】Taking 25 rice seeds as materials, multiple indexes were determined through standard germination experiment, tetrazolium staining identification, field simulation experiment and Q2 technology, and these indexes were analyzed by principal component analysis combined with membership function method and multiple linear regression, to establish the mathematical evaluation model for seed vitality, D(x). And the D(x) model was used to evaluate the influence of different cultivation densities on rice seed vitality.【Result】The results showed that the average values of germination vigor, germination rate, 7-day bud length, hundred-seed fresh weight, field bud length, field root length, starting metabolism rate (SMR), increased motabolism time (IMT), relative germination time (RGT), and tetrazolium staining rate of indica rice were all higher than those of japonica rice. However, only the average values of 7-day root length, hundred-seed dry weight, and oxygen metabolism rate (OMR) of indica rice were slightly lower than those of japonica rice. In the Q2 test, japonica rice exhibited better performance in IMT value, RGT value, and other indicators. Correlation analysis of 13 rice seed vitality indexes revealed varying degrees of correlations among them. In the Q2 test, SMR value was extremely significantly correlated with IMT value, OMR value, RGT value, and hundred-seed dry weight, and significantly correlated with field bud length. OMR value was extremely significantly correlated with SMR value, IMT value, RGT value, and significantly correlated with germination vigor. A seed vitality comprehensive mathematical evaluation model Y(x) = 0.693+0.003X1-0.006X2-0.127X6-0.004X8+0.234X9 (R2=0.94) was established through stepwise regression. The predicted vitality values (Y) obtained from these five indexes were in close agreement with the order of field emergence rate among the tested materials, and they were highly correlated (r=0.83), indicating that this regression equation could effectively predict rice seed vitality.【Conclusion】Five individual indexes, namely, germination vigor, germination rate, hundred-seed dry weight, oxygen metabolism rate (OMR) and germination initiation time (IMT) could be selected as the basis for the evaluation of seed vitality.

Flow field data generated by ocean models are important for simulating ocean currents and circulation patterns, which are essential components in digital Earth construction. To evaluate the accuracy of model-simulated flow fields, Array for Real-time Geostrophic Oceanography (Argo) float observations can be considered benchmarks. In this study, a novel method for comparing Argo profiles with 3-dimensional trajectories obtained by simulating Argo floats in Hybrid Coordinate Ocean Model (HYCOM)-provided flow fields was proposed. Surface and subsurface trajectories were calculated, and their spatial matching characteristics were analyzed. The results demonstrated that (1) the HYCOM surface and subsurface flow fields generally conform to the basic characteristics and trends of ocean currents; (2) the HYCOM sea surface current field error pattern exhibits a symmetrical distribution centered on the equator in the Northern and Southern Hemispheres and increases with increasing latitude; and (3) the HYCOM subsurface flow field exhibits regional differences, with the largest differences in the Gulf Stream, North Atlantic Warm Current, and Westerly Wind Drift region. Through analysis of the disparities between HYCOM and Argo data, the effectiveness of using model simulation data can be enhanced, and the accuracy and dependability of ocean models can be improved.

Context: Deficit drip irrigation is an advanced agricultural technology widely promoted and applied around the world to maintain/increase yield and quality while simultaneously minimizing water consumption. However, there is still a lack of comprehensive research on the effects of deficit drip irrigation at different stages on apple yield, water productivity, and quality. Objective: The aim was to investigate the effects of deficit drip irrigation treatments (DDITs) on apple yield, quality, and water productivity (WP), and optimize the deficit drip irrigation strategy for apples in the Loess Plateau of China. Methods: a two-year field experiment was conducted with 17 irrigation treatments, including a control treatment (CK, full irrigation (FI)) and four DDITs (D15%, D30%, D45%, D60%) during the bud burst to leafing stage (I), flowering to fruit set stage (II), fruit expansion stage (III), and fruit maturation stage (IV). The optimal irrigation management was determined using the fuzzy Borda combined model, which was based on four different single evaluation models of the TOPSIS method, principal component analysis (PCA), grey correlation analysis (GCA), and membership function analysis (MFA). Results: The DDITs at stage IV decreased midday leaf water potential (Ψs) by 2.57–20.00% compared with CK, and the difference of Ψs between IV-D30%, IV-D45%, IV-D60%, and CK were significant in two years (P

Introduction: The prevalence of major depressive disorder (MDD) has gradually increased and has attracted widespread attention. The aim of this study was to investigate the effect of a probiotic compound consisting of Bacillus coagulans and Clostridium butyricum, on a mouse depression model.Methods: Mice were subjected to chronic unpredictable mild stress (CUMS) and then treated with the probiotics at different concentrations. And mice received behavior test such as forced swimming test and tail suspension test. After that, all mice were sacrificed and the samples were collected for analysis. Moreover, prefrontal cortex (PFC) gene expression and the gut microbiota among different groups were also analyzed.Results: Probiotics improved depressive-like behavior in CUMS mice, as indicated by decreased immobility time (p < 0.05) in the forced swimming test and tail suspension test. probiotics intervention also increased the level of 5-hydroxytryptamine (5-HT) in the prefrontal cortex and decreased the adrenocorticotropic hormone (ACTH) level in serum. In addition, by comparing the PFC gene expression among different groups, we found that the genes upregulated by probiotics were enriched in the PI3K-Akt signaling pathway in the prefrontal cortex. Moreover, we found that downregulated genes in prefrontal cortex of CUMS group such as Sfrp5 and Angpt2, which were correlated with depression, were reversed by the probiotics. Furthermore, the probiotics altered the structure of the gut microbiota, and reversed the reduction of cob(II)yrinate a,c-diamide biosynthesis I pathway in CUMS group. Several species like Bacteroides caecimuris and Parabacteroides distasoni, whose abundance was significantly decreased in the CUMS group but reversed after the probiotics intervention, showed significantly positive correlation with depression associated genes such as Tbxas1 and Cldn2.Discussion: These findings suggested that CUMS-induced depression-like behavior can be alleviated by the probiotics, possibly through alterations in the PFC gene expression and gut microbiota.

BackgroundThe association between Body Mass Index (BMI), frailty index (FI), and dietary supplement in cancer survivors has been a subject of growing interest. This study investigates the relationship of BMI and FI with mortality in American cancer survivors and explores the impact of dietary supplement usage on different BMI and FI groups.MethodsThree thousand nine hundred and thirty-two cancer patients from the National Health and Nutrition Examination Survey (NHANES) database were included in the analyses. BMI, FI, and supplement usage were obtained through the NHANES structured survey and the 49-item FI tool. Weighted logistic and Cox proportional hazards models, Kaplan–Meier survival analyses, and propensity score matching (PSM) were used to elucidate the relationships between BMI, FI, dietary supplement, and mortality outcomes.ResultsThe study found significant associations between higher BMI and increased frailty (Odds ratio [OR] = 1.04, 95% confidence interval [95% CI], 1.02–1.06). BMI 0.2 are associated with an increased mortality rate. Dietary supplement use can reduce all-cause and cancer mortality in cancer patients with BMI

In order to make the micro permanent magnet linear motor in this paper have an excellent position response in MEMS application scenarios, an electromagnetic force ripple suppression strategy based on harmonic current injection is proposed. Because of the simulation phenomenon of large force ripple under standard sinusoidal current driving, combined with the non-sinusoidal distribution model of the air-gap magnetic field, it is theoretically verified that the odd harmonic current injection can effectively suppress the force ripple. The electromagnetic force under the fundamental + 3rd/7th harmonic currents and only the fundamental current is compared by simulation. The force ripple coefficient is reduced from 31% to 1.3%, and the position response speed is increased by about 11% in the 4 mm position closed-loop response simulation. The experimental results show that under a current with 200 Hz frequency, the motor can achieve a displacement of 5 mm within 0.11 s, providing a peak velocity of 40 mm/s, which verifies the correctness of the design concept and control strategy of the micro linear permanent magnet motor.

A tunnel magnetic resistance (TMR) sensor is a magnetic detection sensor with low power consumption and high sensitivity. The TMR sensor has promising applications in the position detection of micro permanent magnet linear actuators since the surrounding magnetic field of the micro actuator in this paper will be changed by its movement. Firstly, according to the air-gap magnetic field distribution characteristics of the micro permanent magnet linear actuator and the detection principle of the TMR sensor, the integrated installation parameters of TMR sensors were determined. Then, with the help of TMR technology, the backpropagation neural network (BPNN) algorithm and improved BPNN using particle swarm optimization (PSO) algorithm were used to study the position identification strategy of the slider, and the algorithm strategy with the minimum error was selected. Finally, the experimental results show that the slider position identification strategy based on the PSO-BPNN algorithm can achieve position tracking error within 0.1 mm under the given step position tracking and sinusoidal position tracking, and the movements can be repeated well.

Dissolution of lithium cobalt oxide (LCO) is the key step for the recovery of valuable metals (e.g., Co and Li) from spent LCO-based lithium-ion batteries (LIBs). However, the dissolution process of LCO either needs toxic solvents, and high temperature, or shows low efficiency. Deep eutectic solvents (DESs) are potential green solvents to dissolve LCO. Here, DESs with polyethylene glycol (PEG) as hydrogen bond acceptor and ascorbic acid (AA) as hydrogen bond donor are found to dissolve LCO with 84.2% Co leaching efficiency at 80 oC and 72 h, which is higher than that from the reported references by common DESs. Furthermore, both DESs components (i.e., PEG and AA) are cheap, biodegradable, and biocompatible. AA could be easily and abundantly extracted from natural fruits or vegetables. It provides a new guide for the green, mild, and efficient dissolution of LCO aiming at sustainable recovery of spent LIBs.

Low-temperature silver paste (LT-SP) is a critical conductive material for its use in flexible electronic devices. The high-purity thinner-coated Ag NPs with a size of about 100–200 nm are important for their oxidation resistance. Here, by adjusting mixed reduction of ascorbic acid (Vc), glucose (Clu), and sodium citrate (Na(3)Cit), with n(AgNO3): n(SDS) at 3:1, the size of obtained Ag NPs can be decreased to 158.1 nm. A simple natural precipitation purification was performed to obtain large-scale, thinner SDS-coated Ag NPs with lower energy consumption. With the increase of purification times from 1 to 3 and 5, the purification time was longer and longer, the surface coating layer decreased from 3.716 to 1.429 and 1.093 wt.%, and the size of the initial soft agglomerated Ag NPs gradually dispersed from 481.4 to 153.5 and 97.6 nm, indicating that the surface coating layer gradually became thinner. Considering the properties requirement/time-cost, 3 times purification was chosen. To improve the properties of LT-SP, a single green–white glue (PVAc) with excellent adhesion was used as the organic carrier, which was added to the obtained Ag NPs to produce a series of LT-SP samples. When Ag-4.8 wt.% PVAc, a low resistance of 6.2 × 10−8 Ω cm could be obtained by sintering at 140 °C for 25 min, and excellent electrical conductivity was still maintained after 50,000 times bending. Its adhesion could reach the 4B standard confirmed by the Burger test. In summary, an excellent LT-SP can be large-scale produced with high-purity thinner SDS-coated Ag NPs and PVAc organic carriers.

Wild-grown edible mushrooms are important in world diets and are also efficient metal accumulators. Yunnan, Southwest China, is the main producing region, with typically high levels of geochemical metals. The environmental factors, bioaccumulation, distribution and human health risks of metals were examined in paired soil and Tricholoma matsutake (n = 54). T. matsutake grows on acidified soils (pH = 3.95–6.56), and metals show a strong heterogeneity, with Fe, Mn, Zn and Cu in the ranges of 16–201, 0.046–8.58 g kg−1, and 22.6–215, 3.7–155 mg kg−1. High soil Fe content led to great accumulation in T. matsutake (0.24–18.8 g kg−1). However, though the soil Mn content was higher than that of Zn and Cu, their concentrations in T. matsutake were comparable (21.1–487 vs. 38.7–329 and 24.9–217 mg kg−1). This suggested that T. matsutake prefers to accumulate Zn and Cu compared to Mn, and this is supported by the bioaccumulation factors (BAFs = 0.32–17.1 vs. 0.006–1.69). Fe was mainly stored in stipes, while Mn, Zn and Cu were stored in caps, and the translocation factors (TFs) were 0.58 vs. 1.28–1.94. Therefore, stipe Fe showed the highest health risk index (HRI) at 1.28–26.9, followed by cap Cu (1.01–2.33), while 98–100% of the Mn and Zn were risk-free. The higher concentration and greater risk of Fe was attributed to the significant effect of soil Fe content (R = 0.34) and soil pH (R = −0.57). This study suggested that Fe, as an essential mineral, may exert toxic effects via the consumption of T. matsutake from high geochemical background areas.

The expansion of the construction land scale has been vital in supporting rapid economic development and meeting social needs. However, the spatial heterogeneity in the effect of construction land scale on carbon emission intensity at the county level remains underexplored. Therefore, comprehensively investigating the relation between the construction land transfer scale and carbon emission intensity holds substantial research value. Using panel data from 2007 to 2021, this study analyzes the spatiotemporal differentiation characteristics of carbon emission intensity and the effect of construction land scale on carbon emission intensity at the county level in Jiangsu Province, China. The findings reveal that carbon emission intensity at the county level in Jiangsu Province generally exhibits a continuous downward trend over time and a spatial distribution characterized by a gradual decrease from the southern counties to the central and northern counties. Moreover, there is a significant positive relation between the construction land transfer scale and carbon emission intensity, a conclusion supported by robustness tests. Furthermore, mediating analysis indicates that reduction of the construction land transfer scale exhibits a significant promoting effect on green technology innovation and industrial structure upgrading, which, in turn, has a significant inhibitory effect on carbon emission intensity. The impact of the construction land transfer scale from different sources, supply methods, types, and of county economic strength on carbon emission intensity has significant heterogeneity.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease refractory to all targeted and immune therapies. However, our understanding of PDAC microenvironment especially the metastatic microenvironment is very limited partly due to the inaccessibility to metastatic tumor tissues. Here, we present the single-cell transcriptomic landscape of synchronously resected PDAC primary tumors and matched liver metastases. We perform comparative analysis on both cellular composition and functional phenotype between primary and metastatic tumors. Tumor cells exhibit distinct transcriptomic profile in liver metastasis with clearly defined evolutionary routes from cancer cells in primary tumor. We also identify specific subtypes of stromal and immune cells critical to the formation of the pro-tumor microenvironment in metastatic lesions, including RGS5+ cancer-associated fibroblasts, CCL18+ lipid-associated macrophages, S100A8+ neutrophils and FOXP3+ regulatory T cells. Cellular interactome analysis further reveals that the lack of tumor-immune cell interaction in metastatic tissues contributes to the formation of the immunosuppressive microenvironment. Our study provides a comprehensive characterization of the transcriptional landscape of PDAC liver metastasis.

Importance: Pathological perturbations of the brain often spread via connectome to fundamentally alter functional consequences. By integrating multimodal neuroimaging data with mathematical neural mass modeling, brain network models (BNMs) enable to quantitatively characterize aberrant network dynamics underlying multiple neurological and psychiatric disorders. We delved into the advancements of BNM-based medical applications, discussed the prevalent challenges within this field, and provided possible solutions and future directions. Highlights: This paper reviewed the theoretical foundations and current medical applications of computational BNMs. Composed of neural mass models, the BNM framework allows to investigate large-scale brain dynamics behind brain diseases by linking the simulated functional signals to the empirical neurophysiological data, and has shown promise in exploring neuropathological mechanisms, elucidating therapeutic effects, and predicting disease outcome. Despite that several limitations existed, one promising trend of this research field is to precisely guide clinical neuromodulation treatment based on individual BNM simulation. Conclusion: BNM carries the potential to help understand the mechanism underlying how neuropathology affects brain network dynamics, further contributing to decision-making in clinical diagnosis and treatment. Several constraints must be addressed and surmounted to pave the way for its utilization in the clinic.

Abstract BRD4 is a member of the BET protein family involved in chromatin remodeling and transcriptional regulation. Several BET inhibitors (BETi) have entered clinical trials, demonstrating potential in inducing cancer cell apoptosis and tumor regression. However, resistance to BETi is common in solid tumors. In pancreatic cancer, it is found that cancer‐associated fibroblasts (CAFs) in the tumor microenvironment reduce the BET inhibitor JQ1 sensitivity by inducing BRD4 expression. Moreover, CAFs play a crucial role in the formation of a dense stromal barrier. Therefore, targeting CAFs in the tumor microenvironment of pancreatic cancer not only enhances cancer cells sensitivity to JQ1 but also increases drug perfusion and improves oxygen supply, thus reducing glycolysis and limiting energy supply. To address this challenge, a homologous targeting mechanism utilizing activated fibroblast membrane‐coated liposomes is proposed for specific drug precise target to CAFs‐rich pancreatic cancer. Additionally, TAT peptides enable liposomes penetration, delivering PFD for targeted anti‐fibrotic therapy, reducing extracellular matrix generation and glycolysis, and enhancing JQ1 delivery and sensitivity. In conclusion, the findings indicate the tremendous potential of this CAFs‐targeting liposomal delivery system in pancreatic cancer.

Marine fungi are essential for the ecological function of estuarine ecosystems. However, limited studies have reported on the structure and assembly pattern of the fungal communities in estuaries. The purpose of this study is to reveal the structure and the ecological process of the fungal community in the Yangtze River Estuary (YRE) by using the amplicon sequencing method. Phyla of Ascomycota, Basidiomycota, and Chytridiomycota were dominant in the seawater and sediment samples from YRE. The null model analysis, community-neutral community model (NCM), and phylogenetic normalized stochasticity ratio (pNST) showed that the stochastic process dominated the assembly of fungal communities in YRE. Drift and homogeneous dispersal were the predominant stochastic processes for the fungal community assembly in seawater and sediment samples, respectively. The co-occurrence network analysis showed that fungal communities were more complex and closely connected in the sediment than in the seawater samples. Phyla Ascomycota, Basidiomycota, and Mucoromycota were the potential keystone taxa in the network. These findings demonstrated the importance of stochastic processes for the fungal community assembly, thereby widening our knowledge of the community structure and dynamics of fungi for future study and utilization in the YRE ecosystem.

Abstract A favorable environment can induce vegetation overgrowth to exceed the ecosystem carrying capacity, exacerbating water resource depletion and increasing the risk of lagged effects on vegetation degradation. This phenomenon is defined as structural overshoot, which can lead to large‐scale forest mortality and grassland deterioration. However, the current understanding of structural overshoot remains incomplete due to the complex time‐varying interactions between vegetation and climate. Here, we used a dynamic learning algorithm to decompose the contributions of vegetation and climate to drought occurrence, trace the connection between antecedent and concurrent vegetation dynamics, thus effectively capturing structural overshoot. This study focused on the climate‐sensitive hotspot in Northwest China drylands, where significant vegetation greening induced by a warming and wetting climate was detected during 1982–2015, leading to soil moisture deficit and aggravating vegetation degradation risks during droughts. We found that during this period, structural overshoot induced approximately 34.6% of the drought events, and lagged effects accounted for 16.7% of the vegetation degradation for these overshoot drought events. The occurrence of overshoot droughts exhibited an increasing trend over time, which was primarily driven by vegetation overgrowth followed by precipitation variation. Although the severity of overshoot and non‐overshoot droughts were generally comparable in spatial distribution, the impact of overshoot droughts is still becoming increasingly obvious. Our results indicate that the expected intensified overshoot droughts cannot be ignored and emphasize the necessity of sustainable agroecosystem management strategies.

Introduction: Hypoxia is one of the important reasons for the poor therapeutic efficacy of current pancreatic cancer treatment, and the dense stroma of pancreatic cancer restricts the diffusion of oxygen within the tumor. Methods: A responsive oxygen-self-supplying adv-miRT-CAT-KR (adv-MCK) cascade reaction system to improve hypoxia in pancreatic cancer is constructed. We utilized various experiments at multiple levels (cells, organoids, in vivo) to investigate its effect on pancreatic cancer and analyzed the role of immune microenvironment changes in it through high-throughput sequencing. Results: The adv-MCK system is an oncolytic adenovirus system expressing three special components of genes. The microRNA (miRNA) targets (miRTs) enable adv-MCK to selectively replicate in pancreatic cancer cells. Catalase catalyzes the overexpressed hydrogen peroxide in pancreatic cancer cells to generate endogenous oxygen, which is catalyzed by killerRed to generate singlet oxygen (1O2) and further to enhance the oncolytic effect. Meanwhile, the adv-MCK system can specifically improve hypoxia in pancreatic cancer, exert antitumor effects in combination with photodynamic therapy, and activate antitumor immunity, especially by increasing the level of γδ T cells in the tumor microenvironment. Conclusion: The responsive oxygen-self-supplying adv-MCK cascade reaction system combined with photodynamic therapy can improve the hypoxic microenvironment of pancreatic cancer and enhance antitumor immunity, which provides a promising alternative treatment strategy for pancreatic cancer.

Summary: Background: Human immunodeficiency virus (HIV) significantly increases the risk of non-Hodgkin lymphoma (NHL) development, yet the population-level impact on NHL burden is unquantified. We aim to quantify this association and estimate the global burden of HIV-associated NHL. Methods: In this meta-analysis, we searched five databases (PubMed, EMBASE, Cochrane Library, Web of Science, Scopus) from database inception up to September 13, 2023, identifying cohort, case–control, or cross-sectional studies with an effective control group to assess NHL risk among individuals with HIV infection, with two authors extracting summary data from reports. Global and regional HIV-associated population attributable fraction (PAF) and NHL disease burden were calculated based on the pooled risk ratio (RR). HIV prevalence and NHL incidence were obtained from the Joint United Nations Programme on HIV/AIDS (UNAIDS) and Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Trends in NHL incidence due to HIV were assessed using age-standardised incidence rate (ASIR) and estimated annual percentage change (EAPC). This study was registered with PROSPERO (CRD42023404150). Findings: Out of 14,929 literature sources, 39 articles met our inclusion criteria. The risk of NHL was significantly increased in the population living with HIV (pooled RR 23.51, 95% CI 17.62–31.37; I2 = 100%, p

Water availability and nitrogen (N) supply are two major issues that affect plant productivity, however, the processes of water and N utilization and their hormone regulation are not conclusive in response to varying water-N interaction. The objective of this study was to evaluate the effects of water stress (WS) at different growth stages on maize plant development, root morphology, water utilization, hormone signaling and N accumulation under various N conditions. A set of controlled drought stress at 60% field capacity was conducted from bell (V12) to tassel (VT) stage (V12-VT, denoted as W1W2), from silk (R1) to milk (R3) stage (R1-R3, denoted as W2W1) and their compound stages (V12-R3, denoted as W1W1) under high- and low-N supply, respectively. The results indicated that compared to the well-watered control (W2W2), W2W1 reduced root length, root area, and shoot dry matter by 4.68–19.15%, 5.92–11.97% and 4.38–29.61%, respectively, while W1W2 promoted the root system and improved the shoot growth, grain formation and plant water use efficiency (WUEp). High N supply tended to aggravate WS with a poorer root system and lower leaf water potential (ψleaf) but higher leaf abscisic acid (ABA) accumulation at different growth stages. Leaf ABA significantly increased while stomatal conductance (Gs) decreased under WS and N-rich environment, hence increasing leaf intrinsic water use efficiency (WUEi). Root zeatin-riboside (ZR) was higher for well-watered and N-rich conditions. Moreover, leaf ABA significantly increased with the decrease of ψleaf (R2 =0.51 for R3, R2 =0.35 for dough stage (R4)) and the variation of ψleaf was relatively constant (≤0.3 MPa) with different water treatments, indicating that maize performed isohydric behavior to response water stress and N-rich environment. This study suggests that to promote the potential of water- and N-saving and improve crop productivity in maize cultivation, mild water stress at vegetative growth stages and appropriate N supply are of great importance.

Lithium compounds, a classic class of metal complex medicine that target GSK 3β and are widely known as mood-stabilizer, have recently been reported as potential anti-tumor drugs. The objective of this investigation was to explore the anticancer potential of lithium chloride (LiCl) and elucidate its mode of action in pancreatic cancer cells. The MTT, colony formation, and Edu assay were used to evaluate the impact of LiCl on pancreatic cancer cell proliferation. Various methods were employed to investigate the anti-tumor activity of LiCl and its underlying mechanisms. Cell cycle analysis and apoptosis detection assays were utilized for in vitro experiments, while the orthotopic pancreatic cancer mouse model was employed to evaluate the effectiveness of LiCl treatment in vivo. Furthermore, the impact of LiCl on the proliferation of patient-derived organoids was also studied. The results demonstrated that LiCl inhibited the proliferation of pancreatic cancer (PC) cells, induced G2/M phase arrest, and activated apoptosis. Notably, the triggering of endoplasmic reticulum (ER) stress by LiCl was observed, leading to the activation of the PERK/CHOP/GADD34 pathway, which subsequently promoted apoptosis in PC cells. In the future, Lithium compounds could become an essential adjunct in the treatment of human pancreatic cancer.

Abstract A wide spectrum of metabolites (mainly, the three major nutrients and their derivatives) can be sensed by specific sensors, then trigger a series of signal transduction pathways and affect the expression levels of genes in epigenetics, which is called metabolite sensing. Life body regulates metabolism, immunity, and inflammation by metabolite sensing, coordinating the pathophysiology of the host to achieve balance with the external environment. Metabolic reprogramming in cancers cause different phenotypic characteristics of cancer cell from normal cell, including cell proliferation, migration, invasion, angiogenesis, etc. Metabolic disorders in cancer cells further create a microenvironment including many kinds of oncometabolites that are conducive to the growth of cancer, thus forming a vicious circle. At the same time, exogenous metabolites can also affect the biological behavior of tumors. Here, we discuss the metabolite sensing mechanisms of the three major nutrients and their derivatives, as well as their abnormalities in the development of various cancers, and discuss the potential therapeutic targets based on metabolite-sensing signaling pathways to prevent the progression of cancer.

Abstract X-ray absorption spectroscopy (XAS) is a well-established method for in-depth characterization of electronic structure. In practice hundreds of energy-points should be sampled during the measurements, and most of them are redundant. Additionally, it is also tedious to estimate reasonable parameters in the atomic Hamiltonians for mechanistic understanding. We implement an Adversarial Bayesian optimization (ABO) algorithm comprising two coupled BOs to automatically fit the many-body model Hamiltonians and to sample effectively based on active learning (AL). Taking NiO as an example, we find that less than 30 sampling points are sufficient to recover the complete XAS with the corresponding crystal field and charge transfer models, which can be selected based on intuitive hypothesis learning. Further applications on the experimental XAS spectra reveal that less than 80 sampling points give reasonable XAS and reliable atomic model parameters. Our ABO algorithm has a great potential for future applications on automated physics-driven XAS analysis and AL sampling.

In contemporary logistics, the deployment of fixed-wing unmanned aerial vehicles (UAVs) as a transportation platform is experiencing rapid advancements, garnering substantial application within numerous logistic operations with pronounced efficacies. There are notable impediments to the utilization of commercial logistic-oriented fixed-wing UAVs, including elevated procurement and maintenance costs, extensive maintenance intervals, and unsuitability for small-volume, low-altitude transport tasks. These factors collectively exacerbate the risk associated with enterprise procurement and elevate the cost–benefit ratio. This study introduces the design and fabrication of a cost-efficient UAV for logistic delivery purposes, constructed primarily from cost-effective wood materials. This UAV is engineered to ferry payloads of up to 1000 g across a predefined aerial route at an altitude of 40 m. Upon reaching the designated location, the UAV is programmed to initiate the identification of the drop zone, thereafter descending to facilitate the release of the cargo. To mitigate the impact force during the landing phase, the payload was encapsulated within a sponge-damping layer, thereby preserving the integrity of the transported items. The empirical findings from outdoor delivery trials underscore the UAV’s ability to precisely execute payload drops at the targeted locations, confirming its potential to fulfill the logistical requirements for the transportation and delivery of small-volume items in a cost-effective, low-altitude framework. This investigation contributes to the burgeoning discourse on leveraging ultra-low-cost UAVs in logistics, offering a feasible solution to the challenges of cost and efficiency in UAV-operated delivery systems.

In this study, the constant temperature control system of a heating plate was established, ethanol–diesel fuel with different proportions was prepared, and a series of experiments were carried out. The experimental system was used to observe, summarize, and analyze four evaporation and crushing modes of mixed droplets, which were explosion, liquid filament stretching, exocytosis, and ejection mode. The evaporation process of four kinds of mixed droplets in their life cycle was analyzed by normalizing the diameter square. It was proposed that the evaporation process of droplets could be divided into the following three stages: a heating stage, a fluctuating evaporation stage, and an equilibrium evaporation stage. It was also pointed out that the expansion, ejection, and micro-explosion of droplets were the causes of fluctuating evaporation. The concept of expansion and crushing intensity was put forward and the expansion and crushing intensity of ethanol/diesel mixed droplets with different proportions were calculated. The reasons why expansion and crushing intensity first increased and decreased with the increase in ethanol blending ratio were analyzed. Finally, the time proportion of ethanol–diesel mixed droplets in each evaporation stage was calculated, which explained that the time proportion of the instantaneous heating stage showed a parabolic law with the increase in ethanol content.

The traditional PID controller in quadrotor UAVs has poor performance, a large overshoot, and a long adjustment time, which limit its stability and accuracy in practical applications. In order to solve this problem, an improved whale optimization fuzzy PID control strategy based on CRICLE chaos map initialization is proposed, and a detailed simulation analysis was carried out using MATLAB software (MATLAB R2022B). Firstly, to more realistically reflect quadrotor UAVs’ flight behavior, a dynamic simulation model was established, and the dynamics and kinematic characteristics of the aircraft were considered. Then, CRICLE chaotic mapping initialization was introduced to improve the global search ability of the whale optimization algorithm and to effectively initialize the parameters of the fuzzy PID controller. This improved initialization method helped to speed up the convergence process and improve the stability of the control system. In the simulation experiments, we compared the performance indicators of the improved CRICLE chaotic mapping initialization whale optimization fuzzy PID controller to the traditional PID and fuzzy PID controllers, including overshoot, adjustment time, etc. The results show that the proposed control strategy has better performance than the traditional PID and fuzzy PID controllers, significantly reduces overshoot, and achieves a significant improvement in adjustment time. Therefore, the improved CRICLE chaotic mapping initialization whale optimization fuzzy PID control strategy proposed in this study provides an effective solution for improving the performance of the quadrotor control system and has practical application potential.

BackgroundThe systemic immune-inflammation index (SII) has emerged as a promising marker predicting the prognosis of some cancers, while its role in urothelial carcinoma (UC) remains uncertain, especially in upper urinary tract urothelial carcinoma (UTUC). This meta-analysis aimed to investigate the association of SII with the prognosis of UC and the response to intravesical Bacillus Calmette-Guerin (BCG) therapy of non-muscle invasive bladder cancer (NMIBC).MethodsA systematic search in PubMed, Embase, Web of Science, and the Cochrane Library was performed to identify relevant studies. The extracted hazard ratios (HRs) and 95% confidence intervals (CIs) were used to evaluate the association between SII and overall survival (OS), cancer-specific survival (CSS), and recurrence-free survival (RFS) of patients with UC. Additionally, we pooled odds ratios (ORs) and 95% CIs to assess the relationship between SII and BCG response in patients with NMIBC. Subgroup and sensitivity analyses were performed to explore potential sources of heterogeneity.ResultsTwenty studies comprising a total of 12,645 patients were eligible. This meta-analysis revealed that high SII levels independently increased the risk of OS (HR 1.55, 95%CI 1.25–1.92), CSS (HR 1.82, 95%CI 1.36–2.45), and RFS (HR 1.26, 95% CI 1.18–1.35) in patients with UC, including those with upper tract urothelial carcinoma. Additionally, elevated SII levels could predict a lower response to intravesical BCG treatment (OR 0.18, 95%CI 0.07–0.45) and higher disease recurrence (HR 1.61, 95%CI 1.31–1.98) in patients with NMIBC. Furthermore, elevated SII levels were positively associated with advanced age, lymphovascular invasion, hydronephrosis, and high tumor grade and stage (pT ≥ 3).ConclusionsElevated preoperative SII levels are associated with poor survival outcomes in patients with UC, as well as worse response to BCG treatment in patients with NMIBC. Therefore, SII can serve not only as an independent prognostic predictor of patients with UC but also as a guide for BCG therapy in NMIBC.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023409077, identifier CRD42023409077.

The mortality rates of gastric cancer remain high due to limited therapeutic strategies. As a highly selective inhibitor of the BD2 domain of BET family proteins, ABBV-744 has potent chemotherapeutic activity against various human solid tumors. However, whether ABBV-744 has potential anti-tumor effects in gastric cancer remain largely unknown. In this study, we evaluated the effect of ABBV-744 on gastric cancer cells and explored the possible underlying mechanisms. We found that ABBV-744 inhibited the growth of gastric cancer cells and patient-derived tumor organoids in a dose-dependent manner. Cellular experiments revealed that ABBV-744 induced mitochondria damage, reactive oxygen species accumulation, cell cycle arrest and apoptotic cell death in gastric cancer cells. Transcriptomic analysis using RNA-sequencing data identified autophagy as a crucial pathway involved in the cell death caused by ABBV-744. Mechanically, further studies showed that ABBV-744 induced autophagy flux in gastric cancer cells by inactivating PI3K/AKT/mTOR/p70S6k and activating the MAPK signaling pathways. In vivo mouse xenograft studies demonstrated that ABBV-744 significantly suppressed the growth of gastric cancer cells via inducing autophagy. Taken together, our results suggest that ABBV-744 is a novel drug candidate for gastric cancer.

The great challenges of food security, climate change and environmental degradation resulting from unreasonable nitrogen fertilizer (NF) inputs necessitate the optimization of fertilizer application to ensure fruit production and environmental sustainability. However, there is a lack of systematic analysis on the effects of NF inputs on apple yield and reactive nitrogen losses (N2O emission, NH3 volatilization, and nitrate leaching) at the global scale. Therefore, we used a meta-analysis of 159 observations from 31 published studies to evaluate the response of apple yield and reactive nitrogen losses to NF. We aim to identify suitable NF rates, environmental conditions, and planting factors that improve apple yield while minimizing reactive nitrogen losses. Our results showed that NF significantly increased apple yield, N2O emission, NH3 volatilization, and nitrate leaching by 17.1%, 255.7%, 236.4%, and 68.7% compared with no nitrogen fertilizer (NNF), respectively. The effects of NF rates and environmental factors on the response of N2O emission, NH3 volatilization, and nitrate leaching to NF were prior to those of planting factors, but the result of apple yield was the opposite. Apple production under NF in regions with MAT (mean annual air temperature) ≥ 10 °C and MAP (mean annual precipitation) 450 kg ha−1). Our findings provide guidance for optimizing NF management in apple orchard to achieve high crop yields, reduce emissions, and mitigate pollution.

Background: Chemoresistance is a common event after cancer chemotherapy, including gastric cancer (GC). Cisplatin has been reported to induce the DNA damage response (DDR), thus leading to chemoresistance. VE-821, a specific inhibitor of ATR, has been proven to suppress a variety of solid malignancies effectively. Our study aimed to explore the effect of VE-821 on enhancing the chemical sensitivity to cisplatin and clarify the potential molecular mechanisms. Methods: Cell viability and apoptosis of MKN-45 and AGS were measured by CCK8 and flow cytometry assay respectively. Western blotting was used to detect the expression of target proteins. TCGA database was used to analyze the correlation between the ATR expression with the prognosis of GC patients. The viability of GC organoids was detected by Cell Titer Glo (CTG) through luminescence. Results: Cisplatin inhibited the proliferation and induced apoptosis of GC cells with a relatively high IC50 value, and increased the phosphorylation levels of ATR-CHK1 and H2AX. VE-821 achieved the same effects but by downregulating the phosphorylation levels of the ATR-CHK1 pathway. Besides, higher ATR expression in GC tissues was positively correlated with higher pathological stage in GC patients. Interestingly, ATR inhibition reversed cisplatin-induced STAT3 activation and enhanced H2AX levels. Moreover, VE-821 significantly sensitized GC cells to cisplatin, and these two drugs had synergistic effects in GC cell lines, organoids, and in vivo. Conclusion: Our results suggested VE-821 sensitized GC cells to cisplatin via reversing DDR activation. And VE-821 treatment may be a promising therapeutic strategy for GC patients with cisplatin resistance.

Electrocardiogram (ECG) signals are often used to diagnose cardiac status. However, most of the existing ECG diagnostic methods only use the time-domain information, resulting in some obviously lesion information in frequency-domain of ECG signals are not being fully utilized. Therefore, we propose a method to fuse the time and frequency domain information in ECG signals by convolutional neural network (CNN). First, we adapt multi-scale wavelet decomposition to filter the ECG signal; Then, R-wave localization is used to segment each individual heartbeat cycle; And then, the frequency domain information of this heartbeat cycle is extracted via fast Fourier transform. Finally, the temporal information is spliced with the frequency domain information and input to the neural network for classification. The experimental results show that the proposed method has the highest recognition accuracy (99.43%) of ECG singles compared with state-of-the-art methods. Clinical and Translational Impact Statement— The proposed ECG classification method provides an effective solution for ECG interrogation to quickly diagnose the presence of arrhythmia in a patient from the ECG signal. It can increase the efficiency of the interrogating physician by aiding diagnosis.

Abstract Background Metastasis is a significant factor that affects the survival of patients with non-small cell lung cancer (NSCLC). Nevertheless, the molecular regulatory mechanism underlying the metastasis is currently not fully understood. This study aims to identify the important role of miR-124-3p in metastasis of NSCLC, thereby providing a potential therapeutic intervention. Methods Exosome secretion was determined by Nanoparticle Tracking Analysis (NTA) and the uptake was measured by fluorescence inverted microscope. The binding mechanism between miR-124-3p and its upstream or downstream target genes was validated experimentally by Luciferase reporter. Cells migration was evaluated by transwell assays. Transcriptome sequencing on A549 was carried out to verify the potential signaling pathway underlying miR-124-3p regulation. Western blotting analysis was used to assess the level of AKT, p-AKT, PI3K, and p-PI3K protein expression in NSCLC cell lines. The role of miR-124-3p to suppress the tumor metastasis was verified in NSCLC xenograft model. Results Exosomes were more abundant in serum from patients with advanced lung cancer (n = 24 patients) than in these from patients with early-stage lung cancer (n = 30 patients), which suggested the potential correlation between amount of exosome secretion and the metastasis of NSCLC. Interestingly, the exosome release, uptake and the migration of NSCLC cells were notably inhibited by miR-124-3p. LINC00511 suppressed the expression of miR-124-3p to facilitate exosome transport due to its role as the competitive endogenous RNA for miR-124-3p. The miR-124-3p could directly target the 3′-UTR of Rab27a in NSCLC cells to inhibit exosome secretion and thereby prevent cell migration and invasion. Aside from the inhibition of exosome transport, miR-124-3p inhibited the activation of PI3K/AKT signaling in the intracellular environment. Finally, by measuring subcutaneous tumor weight and volume and lung metastasis, we also demonstrated that miR-124-3p inhibited tumor growth in vivo. Conclusion In NSCLC, miR-124-3p significantly suppressed metastasis through extracellular exosome transport and intracellular PI3K/AKT signaling. These findings provide new insights toward a better understanding of the NSCLC metastasis and suggest a potential treatment biomarker for NSCLC.

Geographic simulation models can be used to explore and better understand the geographical environment. Recent advances in geographic and socio-environmental research have led to a dramatic increase in the number of models used for this purpose. Some model repositories provide opportunities for users to explore and apply models, but few provide a general evaluation method for assessing the applicability and recognition of models. In this study, an academic impact evaluation method for models is proposed. Five indices are designed based on their pertinence. The analytical hierarchy process is used to calculate the index weights, and the academic impacts of models are quantified with the weighted sum method. The time range is controlled to evaluate the life-term and annual academic impacts of the models. Some models that met the evaluation criteria from different domains are then evaluated. The results show that the academic impact of a model can be quantified with the proposed method, and the major research areas that models impact are identified.

Despite being a common therapy for hepatocellular carcinoma (HCC), insufficient thermal ablation can leave behind tumor residues that can cause recurrence. This is believed to augment M2 inflammatory macrophages that usually play a pro-tumorigenic role. To address this problem, we designed d-mannose-chelated iron oxide nanoparticles (man-IONPs) to polarize M2-like macrophages into the antitumor M1 phenotype. In vitro and in vivo experiments demonstrated that man-IONPs specifically targeted M2-like macrophages and accumulated in peri-ablation zones after macrophage infiltration was augmented under insufficient microwave ablation (MWA). The nanoparticles simultaneously induced polarization of pro-tumorigenic M2 macrophages into antitumor M1 phenotypes, enabling the transformation of the immunosuppressive microenvironment into an immunoactivating one. Post-MWA macrophage polarization exerted robust inhibitory effects on HCC progression in a well-established orthotopic liver cancer mouse model. Thus, combining thermal ablation with man-IONPs can salvage residual tumors after insufficient MWA. These results have strong potential for clinical translation.

Summary: Background: Progress in reducing maternal and neonatal mortality, particularly in low-income and middle-income countries (LMICs) and regions, is insufficient to achieve the Sustainable Developmental Goals by 2030. High-quality postnatal care (PNC) for mothers and neonates is crucial for mothers and babies, yet it remains the most neglected intervention on the continuum of maternal and child care. We aimed to estimate the associations between observable factors and high-quality maternal and neonatal PNC in pooled and country-specific analyses. Methods: In this cross-sectional study, we used the most recent (2015–2022) Demographic and Health Surveys from 23 countries across Africa (n = 14), Southeast Asia (n = 3), Eastern Mediterranean (n = 2), Europe (n = 2), Americas (n = 1), and Western Pacific (n = 1). Women who, within the last 5 years, were aged 15–49 years at their last live birth that had delivered a singleton child were included. We identified eleven PNC behaviours recommended by the World Health Organization (WHO) to measure PNC quality, and applied thresholds to create binary outcomes for quality maternal and neonatal PNC. 15 factors were included in our analysis to assess their association with high-quality PNC for mothers and neonates in a series of single-adjusted and mutually adjusted logistic regression models, both in pooled and country-specific analysis. We also conducted two sets of subgroup analyses for place of residence and maternal age at last birth, and two sets of supplementary analyses to test the robustness of the results. Findings: Among 172,526 women and their most recent child, 41.42% (40.93–41.91) received quality maternal PNC while 42.34% (41.86–42.83) received quality neonatal PNC. In the pooled analysis, we found that the factors showing the strongest associations with quality maternal PNC were delivery by skilled birth attendants (SBAs) (OR: 4.92; 95% CI: 4.32–5.59), four or more antenatal care (ANC) visits (OR: 1.69, 1.58–1.81), and institutional delivery (OR: 1.61; 1.46–1.78). Consistent results were found for all factors of quality newborn care (e.g., delivery by SBA: OR, 4.25; 3.75–4.81; four or more ANC visits: OR, 1.83; 1.70–1.96) except institutional delivery. The association between these leading factors and PNC quality were broadly consistent across countries. Subgroup analyses and sensitivity analyses showed generally consistent results. Interpretation: Our study demonstrated that institutional delivery and frequent ANC visits had the strongest positive associations with quality PNC for both mothers and neonates. Our findings highlight that improvements to the quality of maternal and neonatal PNC in the LMICs we assessed are urgently needed to achieve ambitious maternal, newborn, and child health goals. Funding: China National Natural Science Foundation.

Support effect is an important issue in heterogeneous catalysis, while the explicit role of a catalytic support is often unclear for catalytic reactions. A systematic density functional theory computational study is reported in this paper to elucidate the effect of a model boron nitride (BN) support on the first N-H bond activation step of NH3 on Run (n = 1, 2, 3) metal clusters. Geometry optimizations and energy calculations were carried out using density functional theory (DFT) calculation for intermediates and transition states from the starting materials undergoing the N-H activation process. The primary findings are summarized as follows. The involvement of the model BN support does not significantly alter the equilibrium structure of intermediates and transition states in the most favorable pathway (MFP). Moreover, the involvement of BN support decreases the free energy of activation, ΔG≠, thus improving the reaction rate constant. This improvement is more obvious at high temperatures like 673 K than low temperatures like 298 K. The BN support effect leading to the ΔG≠ decrease is most significant for the single Ru atom case among all three cases studied. Finally, the involvement of the model BN may change the spin transition behavior of the reaction system during the N-H bond activation process. All these findings provide a deeper insight into the support effect on the N-H bond activation of NH3 for the supported Ru catalyst in particular and for supported transition metal catalysts in general.

Objectives: Manganese is one of the essential trace elements that are required by the human body. Klotho protein is a classic anti-aging marker. The association between the levels of serum manganese and serum klotho in individuals between the ages of 40–80 in the United States remains unclear.Methods: Data for this cross-sectional study was obtained from the National Health and Nutrition Examination Survey (NHANES 2011–2016) in the United States. We performed multiple linear regression analyses to investigate the association between the levels of serum manganese and serum klotho. Furthermore, we performed a fitted smoothing curve according to a restricted cubic spline (RCS). Stratification and subgroup analyses were performed for further verification of the results.Results: Weighted multivariate linear regression analysis showed that serum manganese levels were independently and positively associated with serum klotho levels (β = 6.30, 95% confidence interval: 3.30–9.40). Kruskal–Wallis test showed that participants with higher manganese quartiles had higher serum klotho levels (Q1: 808.54 ± 256.39 pg/mL; Q2: 854.56 ± 266.13 pg/mL; Q3: 865.13 ± 300.60 pg/mL; and Q4: 871.72 ± 338.85 pg/mL, p < 0.001). The RCS curve indicated that the association between the levels of serum manganese and serum klotho was non-linear. Furthermore, a significantly positive association was found between serum manganese and serum klotho levels in the majority of subgroups.Conclusion: A non-linear and positive association was found between the levels of serum manganese and serum klotho in individuals aged 40–80 in the United States according to the NHANES (2011–2016).

Due to relatively lower toxicity, bisphenol S (BPS) has become an alternative to previously used bisphenol A. Nevertheless, the occurrence of BPS and its ecological impact have recently attracted increasing attentions because the toxicology effect of BPS with life cycle or multigenerational exposure on aquatic organisms remains questionable. Herein, Daphnia magna (D. magna) multigenerational bioassays spanning four generations (F0–F3) and single-generation recovery (F1 and F3) in clean water were used to investigate the ecotoxicology of variable chronic BPS exposure. For both assays, four kinds of life-history traits (i.e., survival, reproduction, growth and ecological behavior) were examined for each generation. After an 18-day exposure under concentration of 200 μg/L, the survival rate of D. magna was less than 15 % for the F2 generation, whereas all died for the F3 generation. With continuous exposure of four generations of D. magna at environmentally relevant concentrations of BPS (2 μg/L), inhibition of growth and development, prolonged sexual maturity, decreased offspring production and decreased swimming activity were observed for the F3 generation. In particular, it is difficult for D. magna to return to its normal level through a single-generation recovery in clean water in terms of reproductive function, ecological behavior and population health. Hence, multi-generational exposure to low concentrations of BPS can have adverse effects on population health of aquatic organisms with short breeding cycles, highlighting the necessity to assess the ecotoxicology of chronic BPS exposure for public health.

The adhesion with substrate and conductivity of silver (Ag) conductive pattern are critical for practical applications of flexible electronic devices. Polymer vinyl acetate (PVAc) as an important solvent in Ag ink might largely improve the conductive pattern's adhesion property. However, the addition of PVAc in Ag ink also result in decreasing the patterns conductivity to about 210 ± 2 μΩ cm after infrared sintering at air atmosphere. Here, we found a facial method to eliminate the effect of the addition of PVAc for Ag conductive pattern. In this method, the thickness of PVAc layer coated on Ag particles surface was decreased via a washing treatment by ethanol mixed with acetone. After post-sintering treatment of ethanol brushing, a stable and conductive pattern was achieved. Owing to these treatments, compared with the blank sample, the adhesion of patterns was improved by the scratch test with higher damage force from 1 to 3.8 N. Meanwhile, the resistivity of the formed Ag pattern gradually decreased to 22 ± 0.5 μΩ cm after post-sintering treatment for 50 times, and this value did not change after bending 6000 times. The mechanism was given and confirmed by energy dispersive spectroscopy (EDS) analysis, indicating that the residual organic coatings on patterns had been taken away by the evaporation of alcohol molecular. LEDs pasted in the electronic circuit of our university badge were illuminated, indicating their wide application in the field of flexible electronic devices.