Search

Abstract Background Manganese ions (Mn2+) combined with adjuvants capable of damaging and lysing tumor cells form an antitumor nano-modulator that enhances the immune efficacy of cancer therapy through the cascade activation of the cyclic GMP-AMP interferon gene synthase-stimulator (cGAS-STING) pathway, which underscores the importance of developing antitumor nano-modulators, which induce DNA damage and augment cGAS-STING activity, as a critical future research direction. Methods and Results We have successfully synthesized an antitumor nano-modulator, which exhibits good dispersibility and biosafety. This nano-modulator is engineered by loading manganese dioxide nanosheets (M-NS) with zebularine (Zeb), known for its immunogenicity-enhancing effects, and conducting targeted surface modification using hyaluronic acid (HA). After systemic circulation to the tumor site, Mn2+, Zeb, and reactive oxygen species (ROS) are catalytically released in the tumor microenvironment by H+ and H2O2. These components can directly or indirectly damage the DNA or mitochondria of tumor cells, thereby inducing programmed cell death. Furthermore, they promote the accumulation of double-stranded DNA (dsDNA) in the cytoplasm, enhancing the activation of the cGAS-STING signalling pathway and boosting the production of type I interferon and the secretion of pro-inflammatory cytokines. Additionally, Zeb@MH-NS enhances the maturation of dendritic cells, the infiltration of cytotoxic T lymphocytes, and the recruitment of natural killer cells at the tumor site. Conclusions This HA-modified manganese-based hybrid nano-regulator can enhance antitumor therapy by boosting innate immune activity and may provide new directions for immunotherapy and clinical translation in cancer. Graphical Abstract

Abstract In the realm of multiferroicity in 2D magnets, whether magnetic and polar skyrmions can coexist within a single topological entity has emerged as an important question. Here, we study Janus 2D magnets CrInX 3 (X=Se, Te) for a comprehensive investigation of the magnetic ground state, magnetic excited state, and corresponding ferroelectric polarization by first-principles electronic structure calculations and Monte Carlo simulations. Specifically, we have thoroughly elucidated the magnetic exchange mechanisms, and have fully exemplified the magnetic field dependence of the magnon spectrum. More importantly, our study reveals a previously unrecognized, remarkably large spin-spiral-induced ferroelectric polarization (up to 194.9 μC/m2) in both compounds. We propose an approach to identify polar skyrmions within magnetic skyrmions, based on the observed direct correlation between spin texture and polarization density. Elucidating this correlation not only deepens our understanding of magnetic skyrmions but also paves the way for innovative research in the realm of multiferroic skyrmions.

Abstract Translating RNA-seq into clinical diagnostics requires ensuring the reliability and cross-laboratory consistency of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. As part of the Quartet project, we present an RNA-seq benchmarking study across 45 laboratories using the Quartet and MAQC reference samples spiked with ERCC controls. Based on multiple types of ‘ground truth’, we systematically assess the real-world RNA-seq performance and investigate the influencing factors involved in 26 experimental processes and 140 bioinformatics pipelines. Here we show greater inter-laboratory variations in detecting subtle differential expressions among the Quartet samples. Experimental factors including mRNA enrichment and strandedness, and each bioinformatics step, emerge as primary sources of variations in gene expression. We underscore the profound influence of experimental execution, and provide best practice recommendations for experimental designs, strategies for filtering low-expression genes, and the optimal gene annotation and analysis pipelines. In summary, this study lays the foundation for developing and quality control of RNA-seq for clinical diagnostic purposes.

The stability and mobility of proppant packs in hydraulic fractures during hydrocarbon production are numerically investigated by the lattice Boltzmann-discrete element coupling method (LB-DEM). This study starts with a preliminary proppant settling test, from which a solid volume fraction of 0.575 is calibrated for the proppant pack in the fracture. In the established workflow to investigate proppant flowback, a displacement is applied to the fracture surfaces to compact the generated proppant pack as well as further mimicking proppant embedment under closure stress. When a pressure gradient is applied to drive the fluid-particle flow, a critical aperture-to-diameter ratio of 4 is observed, above which the proppant pack would collapse. The results also show that the volumetric proppant flowback rate increases quadratically with the fracture aperture, while a linear variation between the particle flux and the pressure gradient is exhibited for a fixed fracture aperture. The research outcome contributes towards an improved understanding of proppant flowback in hydraulic fractures, which also supports an optimised proppant size selection for hydraulic fracturing operations.

As the new orientation, new requirement and new task to develop higher education, it is necessary to deeply implement the digital strategic action, construct a new form of higher education teaching, give full play to the role of the main channel in the classroom education, and comprehensively promote the ideological and political construction of curriculum. On the basis of the digital intelligence era, this paper deeply explores the ideological and political elements in each chapter according to the characteristics of the course, teaching objectives and teaching contents; it also draws the conclusion about the teaching reform and practice of the ideological and political construction of the course on Food Chemistry and Analysis. It puts forward some strategies: the improvement on educator' ideological and political teaching ability, the digital construction and improvement of high-quality ideological and political resources, the optimization of curriculum setting, and the innovation on "gene implantation" and "one, two, three, four" teaching modes. The ideological and political classroom of professional courses is taken as the carrier, the unity of inner knowledge and action is realized, and meanwhile the ideological and political education system is constructed about the course on Food Chemistry and Analysis, with the purpose to promote both the translation of professional knowledge and value guidance of students', and create a new pattern for the moral education.

Long noncoding RNAs (lncRNAs) are RNA transcripts longer than 200 nucleotides that do not code for proteins but have been linked to cancer development and metastasis. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1) influences crucial cancer hallmarks through intricate molecular mechanisms, including proliferation, invasion, angiogenesis, apoptosis, and the epithelial-mesenchymal transition (EMT). The current article highlights the involvement of MALAT-1 in drug resistance, making it a potential target to overcome chemotherapy refractoriness. It discusses the impact of MALAT-1 on immunomodulatory molecules, such as major histocompatibility complex (MHC) proteins and PD-L1, leading to immune evasion and hindering anti-tumor immune responses. MALAT-1 also plays a significant role in cancer immunology by regulating diverse immune cell populations. In summary, MALAT-1 is a versatile cancer regulator, influencing tumorigenesis, chemoresistance, and immunotherapy responses. Understanding its precise molecular mechanisms is crucial for developing targeted therapies, and therapeutic strategies targeting MALAT-1 show promise for improving cancer treatment outcomes. However, further research is needed to fully uncover the role of MALAT-1 in cancer biology and translate these findings into clinical applications.

Abstract The integrated design of traffic signal control (TSC) and reversible lane (RL) is an effective way to solve the problem of tidal congestion with uncertainty at isolated intersections, because of its advantage in making full use of temporal‐spatial transportation facilities. Considering the contradiction between the dynamic TSC scheme and the fixed RL scheme in one period, a two‐stage optimization method based on improved mean‐standard deviation (MSD) model for isolated intersections with historical and real‐time uncertain traffic flow is proposed. In the first stage, applying the same‐period historical data of multiple days, a robust optimal traffic signal control model with reversible lane based on MSD model (MSD‐RTR model) is put forward to obtain the fixed RL scheme and the compatible initial TSC scheme. A double‐layer nested genetic algorithm (DN‐GA) is designed to solve this model. In the second stage, applying real‐time period data and multi‐day same‐period historical data, a robust optimal dynamic traffic signal control model based on MSD model (MSD‐RDT model) is put forward to obtain the dynamic TSC scheme. Three modes which reflect the different weights of historical period and real‐time period in this MSD‐RDT model are presented to improve the model stability, and a multi‐mode genetic algorithm (MM‐GA) is designed. Finally, a case study is presented to demonstrate the efficiency and applicability of the proposed models and algorithms.

To solve the problem of complex and difficult to quantify factors affecting investment returns and risks in clean energy power grids, this study comprehensively applies the interpretive structural model and Monte Carlo model to the analysis of investment risk-returns in clean energy power grid projects. The interpretive structural model is utilized to analyze project investment returns, while the Monte Carlo model is used to analyze project investment risks. The project investment risk is based on the factor analysis of project investment returns, and key risk factors are identified through 1000 simulations, and the impact of these risks on project returns is quantified. By combining the two, the investability of the project is analyzed. The results showed that grid electricity prices, kilowatt hour subsidies, technology learning rates, total annual sunshine hours, and system power generation efficiency were key factors driving investment returns. The average expected value of investment return was about 20%, and the probability of investment return below 6% was close to 0. The overall project is worth investing in. From this, it can be seen that the research designed investment risk-return analysis methods for clean energy grid projects can effectively distinguish the main factors affecting investment returns and risks, and pre simulate the risk situation of returns. This study can provide reference for investor decision-making.

In this study, we examine the peer effect on climate risk information disclosure by analyzing A-share listed companies in China. We find that industry peers influence target firms’ climate risk information disclosure through active (passive) imitation resulting from cost–benefit considerations (institutional pressures). Leader companies are more likely to be emulated by within-industry follower companies and target firms prefer to learn from similar within-industry firms. Executive overconfidence and performance pressure negatively affect target firms’ willingness to emulate their peers. Finally, the peer effect of climate risk information disclosure demonstrates a regional aspect. Our findings have implications for reasonable climate risk information disclosure at the micro level and effective regulation to move toward achieving carbon peak/neutrality at the macro level.

To investigate the substitutability of the simulation results using the single-dome combustor as the computational domain to the triple-dome combustor, three-dimensional numerical simulations were conducted on both models and the differences in various performances between the two combustors were compared and analyzed. The findings reveal that the simulation results obtained using the single-dome combustor as the computational domain can effectively substitute for those of the triple-dome combustor in terms of critical performance metrics, including velocity distribution in the central cross-section, morphology and size of back-flow regions, total pressure loss coefficient, combustion efficiency, outlet temperature distribution and pollutant emissions. Under takeoff conditions, the flame tube outlet of the single-dome combustor exhibits higher OTDF and RTDF values compared to the triple-dome combustor, with similar radial temperature distribution shapes. Additionally, the NOx emissions of the flame tube outlet are slightly lower in the single-dome combustor compared to the triple-dome combustor, while the Soot emissions are slightly higher. However, both the NOx and Soot emissions are within the same order of magnitude for both combustors. Under idle conditions, both the single-dome and triple-dome combustors show almost zero CO emissions at the flame tube outlet section.

The joint use of hyperspectral image (HSI) and light detection and ranging (LiDAR) data has gained significant performance on land-cover classification. Although spatial–spectral feature learning methods based on convolutional neural networks and transformer networks have achieved prominent advances, contextual information described by fixed convolutional kernels and all self-attention heads selected have limited ability to characterize the detailed information and nonredundant features of land-covers on multimodal data. In this article, a multiscale head selection transformer (MHST) network, is proposed to fully explore detailed and nonredundant features in spatial and spectral dimensions of HSI and LiDAR data. To better acquire detailed information of spatial and spectral features at different scales, a multiscale spectral–spatial feature extraction module, including cascaded multiscale 3-D and 2-D convolutional layers, is inserted into MHST. Simultaneously, an adaptive global feature extraction module based on head selection pooling transformer is given after transformer encoder module for alleviating token redundancy in an adaptive computation style. Finally, we develop a multimodal–multiscale feature fusion classification module with local features and global class token, to exploit a powerful global–local fuse style. The extensive experiments on three popular datasets demonstrate that MHST significantly outperforms other related networks.

Abstract Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due to the variability in technical details across different laboratories, particularly in terms of panel size, somatic mutation detection and TMB calculation rules. Currently, systematic evaluations of the impact of these technical factors on existing assays and best practice recommendations remain lacking. We assessed the performance of 50 participating panel-based TMB assays involving 38 unique methods using cell line samples. In silico experiments utilizing TCGA MC3 datasets were performed to further dissect the impact of technical factors. Here we show that the panel sizes beyond 1.04 Mb and 389 genes are necessary for the basic discrete accuracy, as determined by over 40,000 synthetic panels. The somatic mutation detection should maintain a reciprocal gap of recall and precision less than 0.179 for reliable psTMB calculation results. The inclusion of synonymous, nonsense and hotspot mutations could enhance the accuracy of panel-based TMB assay. A 5% variant allele frequency cut-off is suitable for TMB assays using tumor samples with at least 20% tumor purity. In conclusion, this multicenter study elucidates the major technical factors as sources of variability in panel-based TMB assays and proposed comprehensive recommendations for the enhancement of accuracy and consistency. These findings will assist clinical laboratories in optimizing the methodological details through bioinformatic experiments to enhance the reliability of panel-based methods.

Abstract Previous studies on the molecular classification of cholangiocarcinoma (CCA) focused on certain anatomical sites, and disregarded tissue contamination biases in transcriptomic profiles. We aim to provide universal molecular classification scheme and prognostic biomarker of CCAs across anatomical locations. Comprehensive bioinformatics analysis is performed on transcriptomic data from 438 CCA cases across various anatomical locations. After excluding CCA tumors showing normal tissue expression patterns, we identify two universal molecular subtypes across anatomical subtypes, explore the molecular, clinical, and microenvironmental features of each class. Subsequently, a 30-gene classifier and a biomarker (called “CORE-37”) are developed to predict the molecular subtype of CCA and prognosis, respectively. Two subtypes display distinct molecular characteristics and survival outcomes. Key findings are validated in external cohorts regardless of the stage and anatomical location. Our study provides a CCA classification scheme that complements the conventional anatomy-based classification and presents a promising prognostic biomarker for clinical application.

Real-time monitoring technologies of surface deformation represented by the global navigation satellite system (GNSS) are essential for landslides early warning. Monitoring methods such as GNSS require on-site manual installation. Therefore, it becomes nearly impossible to deploy surface monitoring equipment when landslides are located in high mountain valleys that are challenging for personnel to access, and/or in hazardous situations. We propose an intelligent real-time monitoring and early-warning technology that employs an unmanned aerial vehicle (UAV) as a carrier to deploy GNSS equipment. A system was initially designed with five components: an adaptive sampling GNSS receiver, an intelligent cooperative network transmission module, UAV-dropped GNSS equipment, special delivery UAV, and an intelligent monitoring and early warning cloud platform. This new technology was applied to a real landslide in Gansu Province, China, in 2020. The mean absolute error of 30 days in the east, north, and upward directions were 1.2, 1.3, and 2.9 mm/d, respectively, comparing the deformation velocity between the traditional monitoring station and the UAV-dropped monitoring station. This observation facilitated the successful prediction of a landslide hazard on 27 January 2021, allowing for a timely alert to be issued. Collectively, the results of this study established that UAV-deployed GNSS technology can accomplish unmanned deployment of GNSS equipment for landslide monitoring to ensure early warning issuance in inaccessible and/or high-risk areas.

IntroductionGlioma, a prevalent and deadly brain tumor, is marked by significant cellular heterogeneity and metabolic alterations. However, the comprehensive cell-of-origin and metabolic landscape in high-grade (Glioblastoma Multiforme, WHO grade IV) and low-grade (Oligoastrocytoma, WHO grade II) gliomas remains elusive.MethodsIn this study, we undertook single-cell transcriptome sequencing of these glioma grades to elucidate their cellular and metabolic distinctions. Following the identification of cell types, we compared metabolic pathway activities and gene expressions between high-grade and low-grade gliomas.ResultsNotably, astrocytes and oligodendrocyte progenitor cells (OPCs) exhibited the most substantial differences in both metabolic pathways and gene expression, indicative of their distinct origins. The comprehensive analysis identified the most altered metabolic pathways (MCPs) and genes across all cell types, which were further validated against TCGA and CGGA datasets for clinical relevance.DiscussionCrucially, the metabolic enzyme phosphodiesterase 8B (PDE8B) was found to be exclusively expressed and progressively downregulated in astrocytes and OPCs in higher-grade gliomas. This decreased expression identifies PDE8B as a metabolism-related oncogene in IDH-mutant glioma, marking its dual role as both a protective marker for glioma grading and prognosis and as a facilitator in glioma progression.

The separation and turbulent transition of the flow in a compressor blade channel are investigated through direct numerical simulations (DNS) at a Reynolds number of 1.367 × 105. Based on the original DNS data, both time-averaged statistics and instantaneous vortex structures of the flow field are extensively analyzed. The vortices are visualized and studied by the Liutex method, and the streaming dynamic mode decomposition (SDMD), a low-storage variant of conventional DMD, is applied to the large datasets obtained on both pressure and suction sides. The physical quantity analyzed with SDMD is the Liutex magnitude R. The DNS results indicate that flow separation occurs on both sides of the blade. On the pressure surface, the separation is weak and the flow remains in a natural transition dominated by viscous Tollmien–Schlichting instabilities. In contrast, owing to the presence of a large laminar separation bubble, the flow experiences a separation transition governed by inviscid Kelvin–Helmholtz instabilities on the suction surface. The SDMD results suggest that a broad range of vortex frequencies exist in the transition flow, and the scale of the spatial structures is negatively correlated with the frequency of the mode. On the pressure surface, the extracted SDMD modes are primarily related to Kelvin–Helmholtz rolls, whereas on the suction side, influenced by the separated boundary layer, the modal structures exhibit greater diversity.

BackgroundHeat stroke is a severe heat-related illness, and it is necessary to explain in depth the effect of high temperature on heat stroke in the context of global warming. ObjectiveTo describe the epidemiological characteristics of reported heat stroke cases in Shanghai from 2013 to 2022, analyze the influence of daily mean temperature threshold on heat stroke, and identify susceptible populations, so as to provide data support for the development of relevant social and public policies. MethodsData from case reports on heat stroke were collected in Shanghai from 2013 to 2022. Heat stroke associated daily mean temperature threshold, lag effects, and susceptible populations were estimated using piecewise regression model and distributed lag non-linear model. ResultsAmong the 3479 cases reported from June to August of 2013—2022 in Shanghai, the male-to-female ratio was 3.34. A positive association between daily mean temperature and heat stroke was found, the association was strongest on the day of exposure and persisted until lag day 2, with an estimated threshold at 33.1 ℃. Using the median value of daily mean temperature as the reference value (28.1 ℃), the peak cumulative effect of extreme high temperature (33.1 ℃) appeared at lag 0-2 days with a relative risk (RR) value and its 95%CI of 25.32 (17.49-36.64) for all included cases; the RRs for male and female were 26.33 (17.78, 38.98) and 25.20 (12.52, 50.72), respectively, and no statistically significant difference was found between sexes (P＞0.05); the RRs were much greater in population aged 45-64 years (25.17, 95%CI: 15.54, 40.78) and 65 years and above (76.98, 95%CI: 34.80, 170.30), significantly higher than the values in those aged 16-44 years (20.22, 95%CI: 12.22, 33.44) (P＜0.05); urban areas showed a greater RR (49.09, 95%CI: 19.60, 122.95) than rural areas (23.65, 95%CI: 16.13, 34.67) (P＜0.05). ConclusionHigh temperature is significantly associated with heat stroke cases reported in Shanghai, with a threshold of 33.1℃ for daily mean temperature. The middle-aged and elderly adults and urban residents are more vulnerable to heat stress than those younger and living in rural areas.

Abstract The Real-Time Kinematic (RTK) positioning method of the Global Navigation Satellite System (GNSS) has been widely used for landslide monitoring. The stability of its reference station is crucial to obtain accurate and reliable monitoring results. Unstable reference stations due to the geological environment and human activities are difficult to detect and in practical applications often ignored. As a result, it affects the positioning solutions and subsequently the interpretation and detection of landslide motions, which must be addressed in GNSS landslide monitoring. To solve this problem, we propose using the Precise Point Positioning (PPP) technique to analyze the stability of the reference station by verifying its position. The deformations of the monitoring stations are then compensated. First, the reference station coordinates are obtained by the PPP technique and tectonic motion is considered in data processing. The change or breakout of the reference station position is then determined using a cumulative sum control chart method. Finally, each monitoring station’s displacements are compensated according to the displacements of the reference station. According to the results of the Tengqing landslide experiment, the PPP technique can be used in GNSS landslide monitoring to analyze the stability of reference stations. With PPP, millimeter-level accuracy for the coordinates of reference stations is achieved. Compared to the traditional deformation series, the compensated displacement series more reliably reflects the landslide motions. This study will increase the reliability of monitoring results and contribute to implementing GNSS in monitoring landslides.

A novel method is proposed for accurately determining the local wall friction through the near-wall measurement of time-average velocity profile in a Type-A turbulent boundary layer (TBL). The method is based on the newly established analytical wall-law in Type-A TBL. The direct numerical simulations (DNS) data of turbulence on a zero-pressure-gradient flat-plate (ZPGFP) is used to demonstrate the accuracy and the robustness of the approach. To verify the reliability and applicability of the method, a two-dimensional particle image velocimetry (PIV) measurement was performed in a ZPGFP TBL with a low-to-moderate Reynolds number (Re). Via utilizing the algorithm of single-pixel ensemble correlation (SPEC), the velocity profiles in the ZPGFP TBL were resolved at a significantly improved spatial resolution, which greatly enhanced the measurement accuracy and permitted us to accurately capture the near-wall velocity information. The accuracy of the approach is then quantitatively validated for the high Reynolds number turbulence using the ZPGFP TBL data. The research demonstrates that the current method can provide the precise estimation of wall friction with a mean error of less than 2%, which not only possesses the advantage of its insensitivity to the absolute wall-normal distance of the measuring point, but also its capability of providing an accurate prediction of wall shear stress based on fairly sparse experimental data on the velocity profile. The current study demonstrates that the wall shear stress can be accurately estimated by a velocity even at a single-point either measured or calculated in the near-wall region.

Astragalus membranaceus is a famous traditional medicinal plant. However, drought and cadmium (Cd) pollution are the main abiotic stress factors that affect plant growth and yield and the ability to improve the host’s stress resistance through the use of beneficial endophytic fungi. To evaluate the tolerance of dark septate endophytes (DSE) to various abiotic stresses, 10 DSE strains [Microsphaeropsis cytisi (Mc), Alternaria alstroemeriae (Aa), Stagonosporopsis lupini (Sl), Neocamarosporium phragmitis (Np), Paraphoma chlamydocopiosa (Pc), Macrophomina phaseolina (Mp’), Papulaspora equi (Pe), Alternaria tellustris (At), Macrophomina pseudophaseolina (Mp), and Paraphoma radicina (Pr)] were investigated under different drought and Cd stressors in vitro by using solid-plate cultures and liquid-shaker cultures in the current study. The experiments involved using varying concentrations of PEG (0, 9, 18, and 27%) and Cd2+ (0, 25, 50, and 100 mg/L) to simulate different stress conditions on DSE. Additionally, the effect of DSE (Np and At) on the growth of A. membranaceus at different field water capacities (70% and 40%) and at different CdCl2 concentrations (0, 5, 10, and 15 mg Cd/kg) in soil was studied. The results demonstrated that the colony growth rates of Aa, Np, Pc, Mp’, and Mp were the first to reach the maximum diameter at a PEG concentration of 18%. Aa, Np, and At remained growth-active at 100 mg Cd/L. In addition, Aa, Np, and At were selected for drought and Cd stress tests. The results of the drought-combined-with-Cd-stress solid culture indicated that the growth rate of Np was significantly superior to that of the other strains. In the liquid culture condition, the biomasses of Np and Aa were the highest, with biomasses of 1.39 g and 1.23 g under the concentration of 18% + 25 mg Cd/L, and At had the highest biomass of 1.71 g at 18% + 50 mg Cd/L concentration, respectively. The CAT and POD activities of Np reached their peak levels at concentrations of 27% + 50 mg Cd/L and 27% + 25 mg Cd/L, respectively. Compared to the control, these levels indicated increases of 416.97% and 573.12%, respectively. Aa, Np, and At positively influenced SOD activity. The glutathione (GSH) contents of Aa, Np, and At were increased under different combined stressors of drought and Cd. The structural-equation-modeling (SEM) analysis revealed that Aa positively influenced biomass and negatively affected Cd content, while Np and At positively influenced Cd content. Under the stress of 40% field-water capacity and the synergistic stress of 40% field-water capacity and 5 mg Cd/kg soil, Np and At significantly increased root weight of A. membranaceus. This study provides guidance for the establishment of agricultural planting systems and has good development and utilization value.

The accurate estimation of the infiltration boundary of a buried point source is required in the hydraulic design of a subsurface drip irrigation (SDI) system, as well as in the numerical simulation of soil water movement. In this study, an experiment was conducted to measure the variation in emitter flow rate and soil back pressure in silty loam soil. The infiltration cavity was observed, and the radius was estimated by matching the measured emitter flow rate and soil back pressure using HYDRUS-2D simulations. The relationship between the cavity radius, emitter flow rate, and soil back pressure, as affected by the soil bulk density, working pressure, and nominal emitter flow rate, are discussed. The results indicate that the infiltration cavity formed rapidly during irrigation with an irregular shape. The surface area increased as nominal emitter flow rate increased and soil bulk density increased. The variation of flow rate as a function of time had no necessary relationship with that of soil back pressure, due to the formation of the cavity. When the infiltration process became stable, higher soil bulk density resulted in increase in soil back pressure and decrease in emitter flow rate. However, the effects of working pressure and nominal emitter flow rate on soil back pressure were unclear. The emitter flow rate and back pressure, solved by an existing analytical model using estimated radius, demonstrated satisfactory agreement with the measured data, with the minimum root-mean-square error (RMSE), compared with those using a constant radius. When the infiltration boundary was taken as a constant head, the soil back pressure and cavity both significantly affected the simulated soil wetting patterns. The effect of cavity radius on the wetting front could be neglected for the constant flux boundary.

Hyperthermia therapy is considered an effective anticancer strategy. However, high temperature can trigger an excessive inflammatory response, leading to tumor self-protection, immunosuppression, metastasis, and recurrence. To address this issue, we reported a multifunctional photothermal nanoplatform to achieve mild hyperthermia photothermal therapy (mild PTT) based on cisplatin (DDP) and a ferrocene metal-organic framework (MOF-Fc) nanocomposite, which can specifically enhance ferroptosis-triggered oxidative stress levels and synchronously amplify mild hyperthermia PTT-mediated anticancer responses. Both in vitro and in vivo antineoplastic results verify the superiority of mild PTT with DDP/MOF-Fc@HA. The combination of DDP and MOF-Fc exhibits Fenton catalytic activity and glutathione depletion capacity, magnifying mild hyperthermia effects via the radical oxygen species (ROS)-adenosine triphosphate (ATP)-HSP silencing pathway, with important implications for clinical hyperthermia therapy.

PurposeA tertiary lymphoid structure (TLS) refers to an organized infiltration of immune cells that is linked to a positive prognosis and improved response to immunotherapy. However, methods that promote TLS formation are limited and challenging to implement in clinical settings. In this study, we aimed to promote the formation and maturation of TLSs in lung adenocarcinoma (LUAD) by combining low-dose radiotherapy (LDRT) with immunotherapy.MethodsTissue sections from 198 patients who had undergone surgery were examined. Risk factors for patient survival were assessed, and the relationship between TLSs and five-year survival was analyzed. The Kras-LSL-G12D spontaneous lung cancer mouse model was used to screen the optimal irradiation dose (0/1/2 Gy whole lung irradiation) for promoting TLS formation. LDRT combined with anti-PD-1 was used to promote the formation and maturation of TLSs.ResultsTLS+, TLSHigh, TLS+GC+ and CD8High within TLS+ were associated with a favorable prognosis. LDRT increased the formation of early TLSs in the Kras-LSL-G12D lung cancer mouse model. In addition, LDRT combined with anti-PD-1 treatment can significantly improve the maturity of TLSs in mouse LUAD, resulting in greater antitumor effects. This antitumor effect was strongly associated with the number of CD8+ T cells within the TLSs.ConclusionWe successfully applied LDRT combined with PD-1 inhibitor therapy for the first time, which increased both the quantity and maturity of TLSs in lung cancer. This approach achieved a promising antitumor effect.

In this comprehensive meta-analysis, our objective was to evaluate the diagnostic utility of graft-derived cell-free DNA (GcfDNA) in kidney allograft rejection and explore associated factors. We conducted a thorough search of PubMed, Embase, and the Cochrane Library databases, spanning from their inception to September 2022. Statistical analysis was executed utilizing Stata 15, Meta-DiSc 1.4, and Review Manager 5.4 software. The combined pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristics (SROC) curve from the synthesis of findings across ten studies were as follows: 0.75 (0.67–0.81), 0.78 (0.72–0.83), 3.36 (2.89–4.35), 0.32 (0.24–0.44), 8.77 (4.34–17.74), and 0.83 (0.80–0.86), respectively. Among the ten studies primarily focused on GcfDNA’s diagnostic potential for antibody-mediated rejection (ABMR), the optimal cut-off threshold demonstrated substantial diagnostic efficacy, with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the summary receiver operating characteristics curve values of 0.83 (0.74–0.89), 0.75 (0.70–0.80), 3.37 (2.64–4.30), 0.23 (0.15–0.36), 14.65 (7.94–27.03), and 0.85 (0.82–0.88), respectively. These results underscore the high diagnostic accuracy of GcfDNA in detecting rejection. Furthermore, the optimal cut-off threshold proves effective in diagnosing ABMR, while a 1% threshold remains a robust diagnostic criterion for rejection. Notably, for ABMR diagnosis, droplet digital PCR digital droplet polymerase chain reaction emerges as a superior method in terms of accuracy when compared to other techniques. Nonetheless, further research is warranted to substantiate these findings.

Abstract Background and Aims Sex determining region Y related high-mobility group box protein 9 (Sox9) is expressed in a subset of hepatocytes, and it is important for chronic liver injury. However, the roles of Sox9+ hepatocytes in response to the acute liver injury and repair are poorly understood. Methods In this study, we developed the mature hepatocyte-specific Sox9 knockout mouse line and applied three acute liver injury models including PHx, CCl4 and hepatic ischemia reperfusion (IR). Huh-7 cells were subjected to treatment with hydrogen peroxide (H2O2) in order to induce cellular damage in an in vitro setting. Results We found the positive effect of Sox9 deletion on acute liver injury repair. Small heterodimer partner (SHP) expression was highly suppressed in hepatocyte-specific Sox9 deletion mouse liver, accompanied by less cell death and more cell proliferation. However, in mice with hepatocyte-specific Sox9 deletion and SHP overexpression, we observed an opposite phenotype. In addition, the overexpression of SOX9 in H2O2-treated Huh-7 cells resulted in an increase in cytoplasmic SHP accumulation, accompanied by a reduction of SHP in the nucleus. This led to impaired mitochondrial function and subsequent cell death. Notably, both the mitochondrial dysfunction and cell damage were reversed when SHP siRNA was employed, indicating the crucial role of SHP in mediating these effects. Furthermore, we found that Sox9, as a vital transcription factor, directly bound to SHP promoter to regulate SHP transcription. Conclusions Overall, our findings unravel the mechanism by which hepatocyte-specific Sox9 knockout ameliorates acute liver injury via suppressing SHP signaling and improving mitochondrial function. This study may provide a new treatment strategy for acute liver injury in future. Graphical Abstract

In modern scientific practice, it is necessary to consistently observe predetermined zones, with the expectation of detecting and identifying emerging targets or events inside such areas. This research presents an innovative imaging spectrometer system for the continuous monitoring of specific areas. This study begins by providing detailed information on the features and optical structure of the constructed instrument. This is then followed by simulations using optical design tools. The device has an F-number of 5, a focal length of 100 mm, a field of view of 3 × 7, and a wavelength range spanning from 400 nm to 600 nm. The optical path diagram demonstrates that the system’s dispersion and imaging pictures can be distinguished, hence fulfilling the system’s specifications. Furthermore, the utilization of a Modulation Transfer Function (MTF) graph has substantiated that the image quality indeed satisfies the specified criteria. To evaluate the instrument’s performance in the spectrum observation of fixed regions, a region-monitoring-type slitless imaging spectrometer was built. The equipment has the capability to identify a specific region and rapidly capture the spectra of objects or events that are present inside that region. The spectral data were collected effectively by the implementation of image processing techniques on the captured photos. The correlation coefficient between these data and the reference data was 0.9226, showing that the device successfully measured the target’s spectrum. Therefore, the instrument that was created successfully demonstrated its ability to capture images of the observed areas and collect spectral data from the targets located within those regions.

Ocular exposure to particulate matter (PM) causes local inflammation; however, the influence of neutrophils on PM-induced ocular inflammation is still not fully understood. In this study, we constructed a system to investigate the role of PM in ocular inflammation using a co-culture of human corneal epithelial cells (HCE-T) and differentiation-induced neutrophils (dHL-60). To investigate whether HCE-T directly endocytosed PM, we performed a holographic analysis, which showed the endocytosis of PM in HCE-T. The cytokines and chemokines produced by HCE-T were measured using an ELISA. HCE-T treated with PM produced IL-6 and IL-8, which were inhibited by N-Acetyl-L-cysteine (NAC), suggesting the involvement of ROS. Their co-culture with dHL-60 enhanced their production of IL-6, IL-8, and MCP-1. This suggests an inflammatory loop involving intraocular corneal epithelial cells and neutrophils. These cytokines and chemokines are mainly regulated by NF-κB. Therefore, this co-culture system was examined in the presence of an IKK inhibitor known to downregulate NF-κB activity. The IKK inhibitor dramatically suppressed the production of these factors in co-culture supernatants. The results suggest that the inflammatory loop observed in the co-culture is mediated through ROS and the transcription factor NF-κB. Thus, the co-culture system is considered a valuable tool for analyzing complex inflammations.

Abstract Osteoarthritis (OA) is an age-related degenerative disease without disease-modifying therapy. The lack of aging-induced osteoarthritis models makes the discovery of therapeutic drugs more challenging. The deficiency of ZMPSTE24 could induce Hutchinson–Gilford progeria syndrome (HGPS), a genetic disorder of rapid aging. However, the relationship between HGPS and OA remains unclear. Our results found that the expression of Zmpste24 was decreased in the articular cartilage during the aging process. Zmpste24 knockout mice, Prx1-Cre; Zmpste24 fl/fl mice and Col2-CreERT2; Zmpste24 fl/fl mice displayed OA phenotype. Loss of Zmpste24 in articular cartilage could exacerbate the occurrence and development of osteoarthritis. Transcriptome sequencing revealed that deletion of Zmpste24 or accumulation of progerin affects chondrocyte metabolism, inhibits cell proliferation and promotes cell senescence. Using this animal model, we elucidate the upregulation of H3K27me3 during chondrocyte senescence and discover the molecular mechanism by which lamin A mutant stabilizes EZH2 expression. The construction of aging-induced osteoarthritis models and the elucidation of the signaling pathways and molecular mechanisms of articular chondrocyte senescence would benefit the discovery and development of new drugs for OA.

STING (Stimulator of Interferon Genes) agonists have emerged as promising agents in the field of cancer immunotherapy, owing to their excellent capacity to activate the innate immune response and combat tumor-induced immunosuppression. This review provides a comprehensive exploration of the strategies employed to develop effective formulations for STING agonists, with particular emphasis on versatile nano-delivery systems. The recent advancements in delivery systems based on lipids, natural/synthetic polymers, and proteins for STING agonists are summarized. The preparation methodologies of nanoprecipitation, self-assembly, and hydrogel, along with their advantages and disadvantages, are also discussed. Furthermore, the challenges and opportunities in developing next-generation STING agonist delivery systems are elaborated. This review aims to serve as a reference for researchers in designing novel and effective STING agonist delivery systems for cancer immunotherapy.

AbstractBackground The kidney transplant recipients (KTRs) were diagnosed with Chronic Kidney Disease after transplantation (CKD-T). CKD-T can be affected by the microbial composition and metabolites. The present study integrates the analysis of gut microbiome and metabolites to further identify the characteristics of CKD-T.Methods We collected 100 fecal samples of KTRs and divided them into two groups according to the stage progression of CKD-T. Among them, 55 samples were analyzed by Hiseq sequencing, and 100 samples were used for non-targeted metabolomics analysis. The gut microbiome and metabolomics of KTRs were comprehensively characterized.Results As well as significant differences in gut microbiome diversity between the CKD G1-2T group and CKD G3T group. Eight flora including Akkermansia were found to be enriched in CKD G3T group. As compared with CKD G1-2T group, the relative abundance of some amino acid metabolism, glycerophospholipid metabolism, amino acid biosynthesis, carbohydrate metabolism and purine metabolism in CKD G3T group were differential expressed significantly. In addition, fecal metabolome analysis indicated that CKD G3T group had a unique metabolite distribution characteristic. Two differentially expressed metabolites, N-acetylornithine and 5-deoxy-5'-(Methylthio) Adenosine, were highly correlated with serum creatinine, eGFR and cystatin C. The enrichment of gut microbial function in CKD-T is correlated with the expression of gut metabolites.Conclusion Gut microbiome and metabolites in the progression of CKD-T display some unique distribution and expression characteristics. The composition of the gut microbiome and their metabolites appears to be different between patients with CKD G3T and those with CKD G1-2T.

Trace elements play a crucial role in the growth and bioactive substance content of medicinal plants, but their utilization efficiency in soil is often low. In this study, soil and Aconitum carmichaelii samples were collected and measured from 22 different locations, followed by an analysis of the relationship between trace elements and the yield and alkaloid content of the plants. The results indicated a significant positive correlation between zinc, trace elements in the soil, and the yield and alkaloid content of A. carmichaelii. Subsequent treatment of A. carmichaelii with both bulk zinc oxide (ZnO) and zinc oxide nanoparticles (ZnO NPs) demonstrated that the use of ZnO NPs significantly enhanced plant growth and monoester-type alkaloid content. To elucidate the underlying mechanisms responsible for these effects, metabolomic analysis was performed, resulting in the identification of 38 differentially expressed metabolites in eight metabolic pathways between the two treatments. Additionally, significant differences were observed in the rhizosphere bacterial communities, with Bacteroidota and Actinobacteriota identified as valuable biomarkers for ZnO NP treatment. Covariation analysis further revealed significant correlations between specific microbial communities and metabolite expression levels. These findings provide compelling evidence that nanoscale zinc exhibits much higher utilization efficiency compared to traditional zinc fertilizer.

ABSTRACT Currently, DNA-based nucleic acid amplification tests (NAATs) and RNA-based NAATs are employed to detect reproductive tract infection (RTI) pathogens including Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Ureaplasma urealyticum (UU). Although evaluations of DNA-based NAATs have already existed, the comparison of the two methods is scarce. Thus, we compared the limits of detection (LODs) of DNA-based and RNA-based NAATs on the same experimental conditions. Inactivated culture supernatants of CT, NG, and UU with determined pathogen DNA and RNA load were used to evaluate LODs of seven DNA kits and one RNA kit. The LODs of the seven DNA kits for CT, NG, and UU ranged between 38–1,480, 94–20,011, and 132–2,011 copies/mL, respectively. As for RNA kits, they could detect samples at RNA concentrations of 3,116, 2,509, and 2,896 copies/mL, respectively. The RNA concentrations of CT, NG, and UU were 40, 885, and 42 times that of corresponding pathogen DNA concentrations in the employed supernatants, so RNA kits could detect pathogen DNA concentrations as low as 78 copies/mL, 3 copies/mL, and 69 copies/mL, respectively, but the level of pathogen load that the RNA tests could detect was primarily dependent on the infectious phase and transcriptional level of RNA. Thus, a schematic of bacterial dynamics during the period of reproductive tract infections was provided, which suggests that in terms of the analytical sensitivity of pathogen detection, RNA tests are more suitable for detecting active infection and recovery phase, while DNA tests are more suitable for detection in the early stage of infection. IMPORTANCE Reproductive tract infections have considerable effects on the health of humans. CT, NG , and UU are common pathogens. Although evaluation of DNA-based tests has already existed, the comparison between DNA-based and RNA-based tests is rare. Therefore, this study compared the limits of detection of the two tests on the same experimental conditions. Results suggested that most DNA-based NAATs could detect CT, NG, and UU at DNA concentrations lower than 1,000 copies/mL, while RNA-based NAATs could detect bacteria at RNA concentrations around 3,000 copies/mL. Considering the copy number of RNA per bacterium is dynamic through the growth cycle, further comparison is combined with a schematic of bacterial dynamics. Results suggested that in terms of the analytical sensitivity of pathogen detection, RNA tests are more suitable for detecting active infection and recovery phase, while DNA tests are more suitable for detection in the early stage of infection.

Abstract Currently, Global Navigation Satellite System (GNSS) Real-Time Kinematic positioning (RTK) and Precise Point Positioning (PPP) techniques are widely employed for real-time monitoring of landslides. However, both RTK and PPP monitoring techniques have their limitations, such as limited service coverage or long convergence times. PPP-RTK technique which integrates RTK and PPP is a novel approach for monitoring landslides with the advantages of rapid convergence, high-precision, and a wide service area. This study summarizes the limitations of RTK, PPP, and PPP-RTK monitoring techniques and suggests some improved strategies. Their performances are compared and analyzed using real monitoring data. The experiment results demonstrate that RTK is the best option for small-scale (the baseline distance

Abstract Background Hair follicle stem cells (HFSCs) are considered as a promising cell type in the stem cell transplantation treatment of neurological diseases because of their rich sources, easy access, and the same ectoderm source as the nervous system. Hepatocyte growth factor (HGF) is a pleiotropic cytokine that shows neuroprotective function in ischemic stroke. Here we assessed the therapeutic effects of HFSCs on ischemic stroke injury and the synthetic effect of HGF along with HFSCs. Methods Rat HFSCs were intravenously transplanted into a middle cerebral artery ischemia/reperfusion (I/R) rat model. Neurological scoring and TTC staining were performed to assess the benefits of HFSC transplantation. Inflammatory cytokines, blood–brain barrier integrity and angiogenesis within penumbra were estimated by Western blot and immunohistochemistry. The differentiation of HFSCs was detected by immunofluorescence method 2 weeks after transplantation. Results HFSC transplantation could significantly inhibit the activation of microglia, improve the integrity of blood–brain barrier and reduce brain edema. Moreover, the number of surviving neurons and microvessels density in the penumbra were upregulated by HFSC transplantation, leading to better neurological score. The combination of HFSCs and HGF could significantly improve the therapeutic benefit. Conclusion Our results indicate for the first time that HGF modified HFSCs can reduce I/R injury and promote the neurological recovery by inhibiting inflammatory response, protecting blood–brain barrier and promoting angiogenesis.

Introduction: Clinical precision oncology increasingly relies on accurate genome-wide profiling using large panel next generation sequencing; however, difficulties in accurate and consistent detection of somatic mutation from individual platforms and pipelines remain an open question. Objectives: To obtain paired tumor–normal reference materials that can be effectively constructed and interchangeable with clinical samples, and evaluate the performance of 56 panels under routine testing conditions based on the reference samples. Methods: Genes involved in mismatch repair and DNA proofreading were knocked down using the CRISPR-Cas9 technology to accumulate somatic mutations in a defined GM12878 cell line. They were used as reference materials to comprehensively evaluate the reproducibility and accuracy of detection results of oncopanels and explore the potential influencing factors. Results: In total, 14 paired tumor–normal reference DNA samples from engineered cell lines were prepared, and a reference dataset comprising 168 somatic mutations in a high-confidence region of 1.8 Mb were generated. For mutations with an allele frequency (AF) of more than 5% in reference samples, 56 panels collectively reported 1306 errors, including 729 false negatives (FNs), 179 false positives (FPs) and 398 reproducibility errors. The performance metric varied among panels with precision and recall ranging from 0.773 to 1 and 0.683 to 1, respectively. Incorrect and inadequate filtering accounted for a large proportion of false discovery (including FNs and FPs), while low-quality detection, cross-contamination and other sequencing errors during the wet bench process were other sources of FNs and FPs. In addition, low AF (

The adaptive Frequency-Hopping(FH) technique based on interference sensing can further enhance the anti-interference performance of hybrid Direct-Sequence/FH Spread Spectrum(DS/FH SS) system and FH Orthogonal Frequency Division Multiplexing(FH-OFDM) system. Existing interference sensing algorithms cannot provide an accurate detection performance for both stationary and non-stationary LFM interference, and have the problem of misjudging useful signal as interference due to the dynamic time-frequency characteristics of useful signal. To improve the sensing detection capability with low false alarm rate, this paper proposes an algorithm, by analyzing the duration units of frequency points and combining the least-squares fitting method to sense stationary and non-stationary LFM interference. Simulations have been carried out to demonstrate the effectiveness of our interference sensing algorithm.

In this paper, a grid-forming (GFM) control is developed based on the nonlinear Port-Hamiltonian (PH) system theory to systematically achieve tracking control and Lyapunov-based stability by considering the power flow dynamic, voltage and current dynamics of voltage source converters (VSCs) system. The proposed controller is robust to both matched constant and periodic disturbances (e.g., grid voltage/frequency fluctuation, load change, voltage harmonics) and nonlinearities due to structural model uncertainties (e.g., output/line impedance variation, coupling effect). Compared to the conventional linear proportional resonant (PR)-based controller, the proposed PH-based nonlinear controller has uniform transient dynamic performance among different operating conditions in large disturbance rejection scenarios, resulted from the ensured closed-loop (semi)globally stable and uniform error dynamics with design facilitated configurable interconnection and damping matrices fixed by initial settings. Experimental results are presented to demonstrate the effectiveness of the proposed control framework in various working conditions.

Traditional synthetic-aperture radar (SAR) imaging, while adept at capturing stationary scenes with clarity, often results in the blurring of moving targets due to Doppler spectrum disparities. To overcome this, this study introduces an innovative optical approach for imaging moving targets. By employing a spatial light modulator (SLM), the phase information of SAR data can be modulated onto a light beam. Then, the light propagation path is meticulously designed to take advantage of the free propagation of light to compensate for the phase differences in SAR data, thereby achieving focal clarity. Simulations and experimental validations have demonstrated that this method surpasses traditional digital imaging techniques in terms of focusing precision. Additionally, the processing delay is only as long as the time taken for light propagation. The optical path is simple, avoiding complex assembly and alignment. This novel approach opens up new possibilities for the SAR imaging of moving targets, offering potential applications in moving target extraction, separation, and velocity estimation.

Analyzing the factors influencing traffic congestion is essential for urban planning and coordinated development. Previous research frequently focuses on the internal aspects of traffic systems, often overlooking the impact of external factors on congestion sources. Therefore, this study utilizes a geospatial dataset and mobile signaling data, firstly applying the Fuzzy C-Means (FCM) algorithm to identify congested roads of different levels and trace the localization of travelers’ origins on regional congested roads. Furthermore, it employs the LightGBM method to study the influence of the built environment of various congestion sources on network-level congestion. The findings are as follows: (1) There is a positive correlation between traffic congestion and geographical location, with congestion predominantly caused by a few specific plots and demonstrating a concentrated trend in city centers. (2) Residential population density is the most critical factor, accounting for over 12% of the congestion contribution, followed by road density and working population density. (3) Both residential and working population densities show a non-linear positive correlation with congestion contribution, while the mixture of land use displays a non-linear V-shaped influence. Additionally, when residential population density is between 8000 and 11,000, it notably exacerbates congestion contribution. Significantly, by emphasizing land use considerations in traffic system analysis, these findings illuminate the intricate linkages between urban planning and traffic congestion, advocating for a more comprehensive approach to urban development strategies.

Change detection in remote sensing enables identifying alterations in surface characteristics over time, underpinning diverse applications. However, conventional pixel-based algorithms encounter constraints in terms of accuracy when applied to medium- and high-resolution remote sensing images. Although object-oriented methods offer a step forward, they frequently grapple with missing small objects or handling complex features effectively. To bridge these gaps, this paper proposes an unsupervised object-oriented change detection approach empowered by hierarchical multi-scale segmentation for generating binary ecosystem change maps. This approach meticulously segments images into optimal sizes and leverages multidimensional features to adapt the Iteratively Reweighted Multivariate Alteration Detection (IRMAD) algorithm for GaoFen WFV data. We rigorously evaluated its performance in the Yellow River Source Region, a critical ecosystem conservation zone. The results unveil three key strengths: (1) the approach achieved excellent object-level change detection results, making it particularly suited for identifying changes in subtle features; (2) while simply increasing object features did not lead to a linear accuracy gain, optimized feature space construction effectively mitigated dimensionality issues; and (3) the scalability of our approach is underscored by its success in mapping the entire Yellow River Source Region, achieving an overall accuracy of 90.09% and F-score of 0.8844. Furthermore, our analysis reveals that from 2015 to 2022, changed ecosystems comprised approximately 1.42% of the total area, providing valuable insights into regional ecosystem dynamics.

Rice is a primary food source, and height is a crucial parameter affecting its growth status. Consequently, high-precision, real-time monitoring of quantitative changes in crop height are required for improved crop production. Polarimetric interferometric SAR (PolInSAR) has both polarization and interferometric observation capabilities. Due to the short height of crops and rapid growth changes, the large spatial and short temporal baselines of PolInSAR data are essential for effective crop height inversion; however, relevant satellite-borne SAR and airborne SAR data are currently limited. This study presents a PolInSAR rice height inversion algorithm that uses the oriented volume over ground (OVoG) mode with PolInSAR 0-time and controllable spatial baseline data from a LAMP microwave anechoic chamber. Exploiting the advantages of microwave anechoic chamber measurement data, which includes continuous frequency bands, multiple baselines, and varied incidence angles, the influences of incident angles, baseline length, number of baselines, and baseline combinations are assessed. The highest accuracy rice plant height inversion has a root mean square deviation (RMSE) of 0.1093 m and is achieved with an incidence angle of 35–55°, baseline length of 0.25°, and three to four baselines. Furthermore, an imaging geometric equivalence analysis provides reliable foundation data to guide research into new earth observation SAR systems. The results indicate that, under simulated observations from the GF3 satellite at an altitude of 755 km, the optimal spatial baseline ranges for various frequency bands are as follows: L-band: 10.93–42.59 km; S-band: 4.10–15.97 km; C-band: 2.48–9.64 km; X-band: 1.36–5.32 km; Ku-band: 0.87–3.40 km. Notably, the measurement modes corresponding to the C, X, and Ku bands are ultimately identified as the most suitable for PolInSAR rice height inversion.

Abstract Abnormal epigenetic regulation is identified to correlate with cancer progression and renders tumor refractory and resistant to reactive oxygen species (ROS)‐based anti‐tumor actions. To address it, a sequential ubiquitination and phosphorylation epigenetics modulation strategy is developed and exemplified by the well‐established Fe‐metal‐organic framework (Fe‐MOF)‐based chemodynamic therapy (CDT) nanoplatforms that load the 26S proteasome inhibitor (i.e., MG132). The encapsulated MG132 can blockade 26S proteasome, terminate ubiquitination, and further inhibit transcription factor phosphorylation (e.g., NF‐κB p65), which can boost pro‐apoptotic or misfolded protein accumulations, disrupt tumor homeostasis, and down‐regulate driving genes expression of metastatic colorectal cancer (mCRC). Contributed by them, Fe‐MOF‐unlocked CDT is magnified to considerably elevate ROS content for repulsing mCRC, especially after combining with macrophage membrane coating‐enabled tropism accumulation. Systematic experiments reveal the mechanism and signaling pathway of such a sequential ubiquitination and phosphorylation epigenetics modulation and explain how it could blockade ubiquitination and phosphorylation to liberate the therapy resistance to ROS and activate NF‐κB‐related acute immune responses. This unprecedented sequential epigenetics modulation lays a solid foundation to magnify oxidative stress and can serve as a general method to enhance other ROS‐based anti‐tumor methods.

BackgroundPeople usually spend most of their time indoors, so indoor fine particulate matter (PM2.5) concentrations are crucial for refining individual PM2.5 exposure evaluation. The development of indoor PM2.5 concentration prediction models is essential for the health risk assessment of PM2.5 in epidemiological studies involving large populations.MethodsIn this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM2.5 concentration prediction models. Indoor PM2.5 concentration data, which included 11,712 records from five types of places, were obtained by on-site monitoring. Moreover, the potential predictor variable data were derived from outdoor monitoring stations and meteorological databases. A ten-fold cross-validation was conducted to examine the performance of all proposed models.ResultsThe final predictor variables incorporated in the MLR model were outdoor PM2.5 concentration, type of place, season, wind direction, surface wind speed, hour, precipitation, air pressure, and relative humidity. The ten-fold cross-validation results indicated that both models constructed had good predictive performance, with the determination coefficients (R2) of RFR and MLR were 72.20 and 60.35%, respectively. Generally, the RFR model had better predictive performance than the MLR model (RFR model developed using the same predictor variables as the MLR model, R2 = 71.86%). In terms of predictors, the importance results of predictor variables for both types of models suggested that outdoor PM2.5 concentration, type of place, season, hour, wind direction, and surface wind speed were the most important predictor variables.ConclusionIn this research, hourly average indoor PM2.5 concentration prediction models based on multiple types of places were developed for the first time. Both the MLR and RFR models based on easily accessible indicators displayed promising predictive performance, in which the machine learning domain RFR model outperformed the classical MLR model, and this result suggests the potential application of RFR algorithms for indoor air pollutant concentration prediction.

Abstract Background CD97 is the most widely expressed G protein-coupled receptor in the epidermal growth factor seven-span transmembrane family. It plays a vital role in cell adhesion, migration, and cell connection regulation. We explored the role of CD97 in hepatocellular carcinoma (HCC). Methods We evaluated CD97 mRNA expression in HCC using TNMplot and the Gene Expression Omnibus database. The clinical prognostic significance of CD97 in HCC patients was evaluated by gene expression profiling interactive analysis, the Kaplan–Meier plotter, and the UALCAN database. The Tumor Immune Estimation Resource (TIMER) and CIBERSORT databases were used to analyze the relationships among CD97, genes positively related with CD97, and tumor-infiltrating immune cells. Results CD97 was highly expressed in HCC tissues and was associated with an adverse prognosis. CD97 and genes positively related with CD97 were positively correlated with the abundance of tumor-infiltrating immune cells and strongly correlated with tumor-infiltrating macrophages (all r ≥ 0.513, P < 0.001). CD97 was positively correlated with M2 macrophage and tumor-associated macrophage markers (both r ≥ 0.464, P < 0.001). CD97 was found to be an immune-related gene in HCC and positively correlated with the TOX, PD-L1, PD-L2, CTLA4, and PD-1 immune checkpoint genes. CD97 copy number alterations affect the level of immune cell infiltration and mRNA expression. Conclusions CD97 can be used as a potential molecular marker of prognosis in HCC, which is associated with immune cell infiltration.

This paper considers a concentric staged triple swirler lean direct injection (LDI) combustor and conducts numerical analysis to investigate the impact of inner and outer swirl flow of the pilot stage on the spray combustion characteristics and NOx emission. To simulate the flow field, spray dispersion, and the combustion process within the combustion chamber Large eddy simulation (LES) is employed. Three geometric dome parameters are studied including the pilot inner swirl angle, pilot outer swirl angle, and pilot flow rotating direction. The results indicate that: (1) The inner swirling flow is the main factor affecting the spray atomization process inside the swirl cup; (2) In downstream of the dump plane, the outer swirling flow determines the evolution of the precessing vortex core (PVC) structures which affect turbulence intensities in the shear layer and efficient spray dispersion, and (3) NOx emissions are related to the spray atomization efficiency and the average flame length in the combustion chamber. It is also shown that NOx emission in the triple swirler LDI combustors is significantly reduced by increasing the swirling intensity and flow rate of the pilot outer swirler.

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI), such as Erlotinib, have demonstrated remarkable efficacy in the treatment of non-small cell lung cancer (NSCLC) patients with mutated EGFR. However, the efficacy of EGFR-TKIs in wild-type (wt) EGFR tumours has been shown to be marginal. Methods that can sensitize Erlotinib to EGFR wild-type NSCLC remain rare. Herein, we developed a multifunctional superparamagnetic nanotheranostic agent as a novel strategy to potentiate Erlotinib to EGFR-wt NSCLCs. Our results demonstrate that the nanoparticles can co-escort Erlotinib and a vascular epithermal growth factor (VEGF) inhibitor, Bevacizumab (Bev), to EGFR-wt tumours. The nanotheranostic agent exhibits remarkable effects as an inhibitor of EGFR-wt tumour growth. Moreover, Bev normalizes the tumour embedded vessels, further promoting the therapeutic efficacy of Erlotinib. In addition, the tumour engagement of the nanoparticles and the vascular normalization could be tracked by magnetic resonance imaging (MRI). Collectively, our study, for the first time, demonstrated that elaborated nanoparticles could be employed as a robust tool to potentiate Erlotinib to EGFR-wt NSCLC, paving the way for imaging-guided nanotheranostics for refractory NSCLCs expressing EGFR wild-type genes.

Background: Knee osteoarthritis (OA) is a leading cause of pain in older adults. Previous studies indicated clinic-based transcranial direct current stimulation (tDCS) was effective to reduce pain in various populations, but no published studies have reported the efficacy of home-based self-administered tDCS in older adults with knee OA using a randomized clinical study. Objective: The purpose of this study was to evaluate the efficacy and feasibility of tDCS on clinical pain intensity in adults with knee OA pain. Methods: One hundred twenty participants aged 50–85 years with knee OA pain were randomly assigned to receive fifteen daily sessions of 2 mA tDCS for 20 min (n = 60) or sham tDCS (n = 60) over 3 weeks with remote supervision via telehealth. Clinical pain intensity was measured by the Numeric Rating Scale and Western Ontario and McMaster Universities Osteoarthritis Index. Also, we collected data on the tDCS experience via a questionnaire. Results: Participants (68% female) had a mean age of 66 years. Active tDCS significantly reduced pain intensity compared to sham tDCS after completion of the fifteen daily sessions (Cohen's d = 1.20; p-value < 0.0001). Participants showed high levels of satisfaction with their tDCS experience, and there have been no adverse events. Conclusion: We demonstrated that home-based self-administered tDCS was feasible and reduced clinical pain intensity in older adults with knee OA, which can increase its accessibility. Future studies with multi-site randomized controlled trials are needed to validate our findings. Trial registration: ClinicalTrials.gov Identifier NCT04016272.

Background and aims: The outcomes of current treatment for non-small cell lung cancer (NSCLC) are unsatisfactory and development of new and more efficacious therapeutic strategies are required. The Notch pathway, which is necessary for cell survival to avert apoptosis, induces the resistance of cancer cells to antitumour drugs. Notch pathway activation is controlled by the cleavage of Notch proteins/receptors mediated by A disintegrin and metalloproteinase 17 (ADAM17); therefore, ADAM17 is a reliable intervention target for anti-tumour therapy to overcome the drug resistance of cancer cells. This work aims to develop and elucidate the activation of Compound 2b, a novel-structured small-molecule inhibitor of ADAM17, which was designed and developed and its therapeutic efficacy in NSCLC was assessed via multi-assays.Methods and results: A lead compound for a potential inhibitor of ADAM17 was explored via pharmacophore modelling, molecular docking, and biochemical screening. It was augmented by substituting two important chemical groups [R1 and R2 of the quinoxaline-2,3-diamine (its chemical skeleton)]; subsequently, serial homologs of the lead compound were used to obtain anoptimized compound (2b) with high inhibitory activity compared with leading compound against ADAM17 to inhibit the cleavage of Notch proteins and the accumulation of the Notch intracellular domain in the nuclei of NSCLC cells. The inhibitory activity of compound 2b was demonstrated by quantitative polymerase chain reaction and Western blotting. The specificity of compound 2b on ADAM17 was confirmed via point-mutation. Compound 2b enhanced the activation of antitumor drugs on NSCLC cells, in cell lines and nude mice models, by targeting the ADAM17/Notch pathway.Conclusion: Compound 2b may be a promising strategy for NSCLC treatment.

ObjectiveTo investigate the predictive value of Controlling Nutritional Status (CONUT) score and systemic inflammation (SIS) score in the prognosis, short-term efficacy, and immune-related side effects of patient with recurrent or metastatic esophageal squamous cell carcinoma (R/M ESCC) receiving immunotherapy as second line therapy combined with or without radiotherapy.MethodsForty-eight patients with R/M ESCC who received second-line therapy with Camrelizumab were retrospectively studied. They were divided into the high and low score groups according to the CONUT and SIS score. Univariate and multivariate analyses were used to analyze factors that might affect patient prognosis and the effects of different CONUT score and SIS on the short-term efficacy and immune-related toxic and side effects of patients.ResultsThe 1- and 2-year overall survival (OS) and progression-free survival (PFS) rates were 42.9% and 22.5%, and 29.0% and 5.8%, respectively. The CONUT score ranged from 0 to 6 (3.31 ± 1.43), whereas the SIS score ranged from 0 to 2 (1.19 ± 0.73). Multivariate analysis showed that treatment related toxicity, number of cycles of Camrelizumab used, short-term effect and SIS score were independent prognostic factors for OS (P=0.044, 0.021, 0.021, 0.030, respectively), whereas SIS and CONUT scores were independent prognostic factors for PFS (P=0.005, 0.047, respectively). Patients with low CONUT/SIS score had a low incidence rate of immune-related adverse reactions (X2 = 9.735, 5.693; P=0.002, 0.017) and better short-term efficacy (X2 = 4.427, 7.438; P=0.035, 0.006).ConclusionR/M ESCC patients with low CONUT/SIS score have better prognosis, higher objective response rate, lower incidence of immune-related toxic and side effects after receiving immunotherapy as second-line therapy. CONUT scores and SIS scores may be reliable prognostic indicators for patient receiving immunotherapy as second-line therapy for R/M ESCC.