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Abstract Background Lung cancer (LC) is currently the number one malignancy death rate disease in China, and its disease burden is serious. The study aimed to analyze trends of LC and its risk factor attributable disease in China from 1990 to 2019 and predict the next 41 years. Methods The average annual percentage change (AAPC) was used to analyze the trend of LC and its risk factor attributable incidence, deaths, and disability‐adjusted life years (DALYs) rate in China from 1990 to 2019, collected in the Global Burden of Disease 2019. Cochran–Armitage trends examine trends in lung cancer disease burden by sex, age, and attributable risk factor groups in China from 1990 to 2019. In addition, based on data on death and DALYs rate due to LC and its risk factors between 1990 and 2019, an autoregressive integrated moving average (ARIMA) model was developed to predict the change in the trend of burden of disease due to LC and its risk factors over the next 41 years, and the model was evaluated using the model parameters root mean square error, mean absolute error, and mean absolute percentage error. Results From 1990 to 2019, the incidence, mortality and DALYs of LC were all increased. Among the eight risk factors associated with lung cancer, the DALYs rate and mortality rate of lung cancer risk factors for Chinese residents increased from 1990 to 2019, except for household air pollution from solid fuels and diet low in fruit, which showed a decrease; among them, the DALYs rate and mortality rate due to ambient particulate matter pollution showed the greatest increase with AAPC values of 2.880 and 3.310, respectively, while DALYs and mortality rates due to household air pollution from solid fuels showed the largest decreases, with AAPC values of −4.755 and −4.348, respectively. The results of the ARIMA model predictions show that both the mortality rate and the rate of DALYs for lung cancer are increasing yearly, and it is predicted that the rate of DALYs for lung cancer by 2060 will reach 740.095/100 000 and the mortality rate will reach 35.151/100 000. It is expected that by 2060, the top four risk factors for lung cancer in China will be, in order of DALYs rate and mortality rate, smoking, ambient particulate matter pollution, high fasting plasma glucose (HFPG), and secondhand smoke, with HFPG showing the greatest increase. Conclusions The LC burden increased from 1990 to 2019 in China, the LC burden that could be attributed to HFPG will continue to increase in the next 40 years, and will be the third most factor by 2060. Targeted interventions are warranted to facilitate the prevention of LC and improvement of health‐related quality of life patients with LC.

Abstract Background M2-like tumor-associated macrophages (M2-like TAMs) play key roles in tumor progression and the immune response. However, the clinical significance and prognostic value of M2-like TAMs-associated regulatory genes in gastric cancer (GC) have not been clarified. Methods Herein, we identified M2-like TAM-related genes by weighted gene coexpression network analysis of TCGA-STAD and GSE84437 cohort. Lasso-Cox regression analyses were then performed to screen for signature genes, and a novel signature was constructed to quantify the risk score for each patient. Tumor mutation burden (TMB), survival outcomes, immune cells, and immune function were analyzed in the risk groups to further reveal the immune status of GC patients. A gene-drug correlation analysis and sensitivity analysis of anticancer drugs were used to identify potential therapeutic agents. Finally, we verified the mRNA expression of signature genes in patient tissues by qRT-PCR, and analyzed the expression distribution of these genes by IHC. Results A 4-gene (SERPINE1, MATN3, CD36, and CNTN1) signature was developed and validated, and the risk score was shown to be an independent prognostic factor for GC patients. Further analyses revealed that GC patients in the high-risk group had a worse prognosis than those in the low-risk group, with significant differences in TMB, clinical features, enriched pathways, TIDE score, and tumor microenvironment features. Finally, we used qRT-PCR and IHC analysis to verify mRNA and protein level expression of signature genes. Conclusion These findings highlight the importance of M2-like TAMs, provide a new perspective on individualized immunotherapy for GC patients.

Enterprise innovation investment is influenced by the actions of innovation subjects, whereas regulating shareholders’ equity pledge behavior facilitates innovation investment and finance but also carries dangers and affects enterprise innovation investment. Methods:This paper builds an unbalanced panel model to empirically analyze the impact of controlling shareholders’ equity pledges on corporate innovation and its heterogeneous characteristics. It also looks at the moderating role of corporate financing constraints and the mediating role of equity incentives, using data from A-share listed companies in China’s pharmaceutical manufacturing industry from 2015 to 2022. Innovation investment is substantially inversely correlated with controlling shareholders’ equity pledge; that is, firms’ creative behavior and intensity are inhibited by equity pledge. Results and conclusions:The results also show that controlling shareholders’ equity commitments have a more pronounced negative impact on enterprises’ ability to innovate than non-state-owned and decentralized equity firms. The relationship between company innovation and the equity pledge of controlling shareholders is somewhat mediated by equity incentives. The relationship between controlling shareholders’ equity promises and enterprises’ innovation is negatively moderated by financing limitations, which also reduces R&D expenditure and stifles innovation.

Abstract Monsoonal precipitation is dominated by intraseasonal variabilities, whose skillful prediction lead time is currently less than 5 days and remains a grand challenge. Here we show that an intrinsic variability in the Indian Ocean, the Central Indian Ocean (CIO) mode, when combined with a machine learning (ML) algorithm, can produce skillful predictions of intraseasonal precipitation over the monsoon region with a lead time of over 15 days, which is close to the theoretical predictability limit. This remarkable skill improvement stems from the fact that the CIO mode is dynamically related to the intraseasonal monsoon rainfall, while the data‐driven ML algorithm suppresses unwanted high‐frequency noise. Using the CIO mode and the ML algorithm, the forecast system hybridizes physical fundamentals and versatility of data‐driven algorithms. The identification of CIO mode and the verification of its significant contribution to intraseasonal predictions advance our understanding of the coupled monsoon system and also underscores the great potential of ML techniques in weather forecasts and climate predictions.

The spatial and temporal variations of net surface radiation (Rn) are critical for comprehending ecological environments. Nonetheless, the intricate interplay among Rn dynamics, vegetation growth, climate, and natural factors remains inadequately elucidated. In this study, we estimated net surface radiation based on Landsat data and ERA5 meteorological data in the Google Earth Engine (GEE) platform, which closely matched the observable spatial distribution (R2 = 0.96), with an average growth rate of 0.15 MJ m−2 mth−1. Trend analyses and spatial autocorrelation were used to explore the spatial and temporal changes in net radiation from 2000 to 2020, the global Moran's index for net radiation was found to exceed 0.76, with fluctuating increases, showing a highly positive spatial distribution of Rn. Local Moran's I predominantly fell into two categories: ‘High-High’ and ‘Low-Low’, with the first increasing in range and the latter decreasing. Combining GeoDetector and PLS-SEM analyses, temperature and vegetation emerge as predominant drivers of net surface radiation variation within the study area, each contributing more than 17% to Rn change. Furthermore, interactions between any two factors typically exhibits nonlinear enhancement. PLS-SEM underscores the influence of vegetation and climate on Rn, with other factors indirectly affecting net radiation changes by influencing vegetation growth.

Abstract Image decomposition plays a crucial role in various computer vision tasks, enabling the analysis and manipulation of visual content at a fundamental level. Overlapping and sparse images pose unique challenges for decomposition algorithms due to the scarcity of meaningful information to extract components. Here, we present a solution based on deep learning to accurately extract individual objects within multi-dimensional overlapping-sparse images, with a direct application to the decomposition of overlaid elementary particles obtained from imaging detectors. Our approach allows us to identify and measure independent particles at the vertex of neutrino interactions, where one expects to observe images with indiscernible overlapping charged particles. By decomposing the image of the detector activity at the vertex through deep learning, we infer the kinematic parameters of the low-momentum particles and enhance the reconstructed energy resolution of the neutrino event. Finally, we combine our approach with a fully-differentiable generative model to improve the image decomposition further and the resolution of the measured parameters. This improvement is crucial to search for asymmetries between matter and antimatter.

Study region: Inner Mongolia Autonomous Region, North China Study focus: Sensible heat flux (H) quantifies the intensity of water evapotranspiration, making the factors influencing H pivotal to water consumption. North China's semi-arid grasslands are characterized by widespread grazing and strong wind conditions. Grazing strategy modifies surface air heat transfer resistance via vegetation and consequently alters H. Nevertheless, the majority of studies overlook the impact of the observed variables' time scale on H estimation. This paper employs a ''big-leaf'' model to estimate H, incorporating both grazing management strategy and data time scale, validated using the Bowen ratio, and attempted to analyze the factors that affect H. New hydrological insights for the region: Aerodynamic characteristics estimated from daily data typically exceed estimates derived from hourly data. The influence of surface radiative temperature and air temperature on H outweighs that of aerodynamic resistance, whereas aerodynamic resistance accounts for the disparity in estimating H between daily and hourly data. In grazing-prohibited grasslands, the daily H values estimated by the Big Leaf model closely match those obtained from the Bowen ratio. When estimating the hourly H value for grazing prohibited and grazing grasslands, the increase was 25.95 w/m2 and 52.27 w/m2 compared to the daily scale, respectively. For the estimation of water and heat fluxes across different regions, the temporal scale of input data is a pivotal factor.

IntroductionThe systematic review and network meta-analysis (NMA) consolidate all relevant randomized controlled trials (RCTs) related to initial immunotherapy treatments for advanced esophageal squamous cell carcinoma (ESCC). Our goal is to thoroughly assess the effectiveness and safety of various immunotherapy methods, focusing on overall survival (OS) and progression-free survival (PFS) among patients with advanced ESCC positive for PD-L1.MethodsWe conducted a systematic search of the PubMed, Embase, Cochrane Library, and Web of Science databases, covering all records from their inception until January 22, 2024. The inclusion criteria targeted patients with advanced ESCC undergoing first-line immunotherapy or chemotherapy, limiting the study selection to randomized controlled trials (RCTs) exclusively. The study upholds the values of openness, originality, and dependability, as evidenced by its enrollment in the Prospective Register of Systematic Reviews (CRD42024504992).ResultsOur analysis encompasses 7 RCTs, totaling 4688 patients, and evaluates 8 distinct immunotherapy combinations. In advanced ESCC patients irrespective of PD-L1 expression, both sintilimab-chemotherapy and toripalimab-chemotherapy regimens demonstrated comparable OS benefits (HR=0.92, 95% CI: 0.64-1.33). The most pronounced PFS advantages were seen with sintilimab-chemotherapy and camrelizumab-chemotherapy as compared to standard chemotherapy (HR=0.56, 95% CI: 0.46-0.58). Notably, camrelizumab-chemotherapy (HR=0.83, 95% CI: 0.59-1.16) and nivolumab-ipilimumab (HR=0.84, 95% CI: 0.60-1.17) demonstrated significant safety profiles over chemotherapy alone. Subgroup analysis based on PD-L1 expression revealed nivolumab-chemotherapy to yield the highest OS benefit (HR=0.54, 95% CI: 0.37-0.79) in ESCC patients with PD-L1 expression ≥1%. Furthermore, camrelizumab-chemotherapy (HR=0.51, 95% CI: 0.39-0.67) exhibited superior PFS benefits. Among patients with PD-L1 expression ≥10%, camrelizumab-chemotherapy (HR=0.52, 95% CI: 0.35-0.78) emerged as the most efficacious in improving OS, while serplulimab-chemotherapy (HR=0.48, 95% CI: 0.34-0.68) was associated with the longest PFS benefit.ConclusionThe integration of immune checkpoint inhibitors (ICIs) with chemotherapy appears to significantly enhance survival outcomes in patients with advanced ESCC compared to chemotherapy alone. Sintilimab-chemotherapy is potentially the optimal regimen for patients without PD-L1 expression. In contrast, nivolumab-chemotherapy and camrelizumab-chemotherapy are likely to offer the best OS and PFS benefits, respectively, in patients with PD-L1 expression ≥1%. Among those with PD-L1 expression ≥10%, camrelizumab-chemotherapy is projected to provide the greatest OS advantage, whereas serplulimab-chemotherapy is anticipated to offer the most prolonged PFS benefit. Since most of the patients in this study originated from Asia, the above findings are more applicable to the Asian population.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42024504992.

The enhancement of scientific research capabilities among museum personnel—personnel is a crucial aspect in driving the advancement of museums. However, it is observed that museum personnel in Chinese mainland, particularly the younger ones, have not demonstrated sufficient engagement in this regard. The objective of this paper is to investigate the underlying causes of this phenomena. This study employs in-depth interviews with a sample of 10 young museum personnel. The methodology is guided by Weiner’s Cognitive (attribution)-emotion-action model (CEAM) of motivation framework. The findings indicate that there are 14 elements that influence the motivation of museum personnel to engage in scientific research. These characteristics are associated with three aspects of attribution, namely Locus, Stability, and Controllability. Especially, the “external-stable-uncontrollable” and “external-unstable-uncontrollable” two attribution will serve as a catalyst for museums to enhance their efforts in optimizing the research willingness of their professionals, so facilitating the provision of sustained and immediate support.

Abstract Autonomous robots used in infrastructure inspection, space exploration and other critical missions operate in highly dynamic environments. As such, they must continually verify their ability to complete the tasks associated with these missions safely and effectively. Here we present a Bayesian learning framework that enables this runtime verification of autonomous robots. The framework uses prior knowledge and observations of the verified robot to learn expected ranges for the occurrence rates of regular and singular (e.g., catastrophic failure) events. Interval continuous-time Markov models defined using these ranges are then analysed to obtain expected intervals of variation for system properties such as mission duration and success probability. We apply the framework to an autonomous robotic mission for underwater infrastructure inspection and repair. The formal proofs and experiments presented in the paper show that our framework produces results that reflect the uncertainty intrinsic to many real-world systems, enabling the robust verification of their quantitative properties under parametric uncertainty.

Abstract Tissue-resident Natural Killer (trNK) cells are crucial components of local immunity that activate rapidly upon infection. However, under steady state conditions, their responses are tightly controlled to prevent unwanted tissue damage. The mechanisms governing their differentiation and activation are not fully understood. Here, we characterise uterine trNK cells longitudinally during pregnancy by single cell RNA sequencing and find that the combined expression pattern of 4-1BB and CD55 defines their three distinct stages of differentiation in mice. Mechanistically, an IL-21R-STAT3 axis is essential for initiating the trNK cell differentiation. The fully differentiated trNK cells demonstrate enhanced functionality, which is necessary for remodelling spiral arteries in the decidua. We identify an apoptotic program that is specific to the terminal differentiation stage, which may preclude tissue damage by these highly activated trNK cells. In summary, uterine trNK cells become intensely active and effective during pregnancy, but tightly controlled via a differentiation program that also limits potential harm, suggesting an intricate mechanism for harnessing trNK cells in maintaining pregnancy.

Abstract Background T lymphoma invasion and metastasis 1 (Tiam1) is a tumor related gene that specifically activates Rho-like GTPases Rac1 and plays a critical role in the progression of various malignancies. Glycolysis plays an important role in cancer progression, it is crucial for supplying energy and producing metabolic end products, which can maintain the survival of tumor cells. As yet, however, the mechanism of Tiam1 in glycolysis reprogramming of pancreatic cancer (PC) remains to be clarified. Here, we investigated the functional role of Tiam1 in PC cell proliferation, metastasis and glycolysis reprogramming. It is expected to provide a new direction for clinical treatment. Methods The clinical relevance of Tiam1 was evaluated in 66 patients with PC, the effect of Tiam1 on cell proliferation was detected via 5-Ethynyl-2′-deoxyuridine (EdU) and colony formation. The ability of cell migration was detected by the wound healing and Transwell. Quantitative real time polymerase chain reaction (qRT-PCR) and luciferase reporter gene experiments clarify the regulatory relationship of miR-590-5p inhibiting Tiam1. Detection of the molecular mechanism of Tiam1 regulating glucose metabolism reprogramming in PC by glucose metabolism kit. RNA sequencing and Co-Immunoprecipitation (CoIP) have identified glucose transporter protein 3 (SLC2A3) as a key downstream target gene for miR-590-5p/Tiam1. Results We found that Tiam1 expression increased in PC tissues and was associated with lymph node metastasis. The silencing or exogenous overexpression of Tiam1 significantly altered the proliferation, invasion, and angiogenesis of PC cells through glucose metabolism pathway. In addition, Tiam1 could interact with the crucial SLC2A3 and promote the evolution of PC in a SLC2A3-dependent manner. Moreover, miR-590-5p was found to exacerbate the PC cell proliferation, migration and invasion by targeting Tiam1. Furthermore, the reversing effects on proliferation, migration and invasion were found in PC cells with miR-590-5p/Tiam1 overexpression after applying glucose metabolism inhibition. Conclusions Our findings demonstrate the critical role of Tiam1 in PC development and the miR-590-5p/Tiam1/SLC2A3 signaling pathway may serve as a target for new PC therapeutic strategies. Graphical Abstract

Abstract Particle track fitting is crucial for understanding particle kinematics. In this article, we use artificial intelligence algorithms to show how to enhance the resolution of the elementary particle track fitting in dense detectors, such as plastic scintillators. We use deep learning to replace more traditional Bayesian filtering methods, drastically improving the reconstruction of the interacting particle kinematics. We show that a specific form of neural network, inherited from the field of natural language processing, is very close to the concept of a Bayesian filter that adopts a hyper-informative prior. Such a paradigm change can influence the design of future particle physics experiments and their data exploitation.

Innate lymphoid cells (ILCs), as the innate counterpart of CD4+ T helper (Th) cells, play crucial roles in maintaining tissue homeostasis. While the ILC subsets and their corresponding Th subsets demonstrate significant similarities in core programming related to effector function and regulatory mechanisms, their principal distinctions, given their innate and adaptive lymphocyte nature, remain largely unknown. In this study, we have employed an integrative analysis of 294 bulk RNA-sequencing results across all ILC and Th subsets, using scRNA-seq algorithms. Consequently, we identify two genesets that predominantly differentiate ILCs from Th cells, as well as three genesets that distinguish various immune responses. Furthermore, through chromatin accessibility analysis, we find that the ILC geneset tends to rely on specific transcriptional regulation at promoter regions compared with the Th geneset. Additionally, we observe that ILCs and Th cells are under differential transcriptional regulation. For example, ILCs are under stronger regulation by multiple transcription factors, including RORα, GATA3, and NF-κB. Otherwise, Th cells are under stronger regulation by AP-1. Thus, our findings suggest that, despite the acknowledged similarities in effector functions between ILC subsets and corresponding Th subsets, the underlying regulatory machineries still exhibit substantial distinctions. These insights provide a comprehensive understanding of the unique roles played by each cell type during immune responses.

AbstractIncreasing attention has recently been paid to the flipped classroom (FC) due to advancements in information technology. Self-efficacy plays a crucial role in the learning effect of students. However, the impact of flipped classrooms on students’ self-efficacy remains uncertain. In this study, we have developed a theoretical framework focusing on self-efficacy to understand its relationship with the flipped classroom better. This meta-analysis investigates the influence of the FC approach on self-efficacy across various educational settings. A total of 22 articles were selected in the meta-analysis, revealing that the FC approach can enhance self-efficacy, thereby potentially increasing student engagement in learning. Subgroup analyses revealed that technicality subjects and the short duration of the intervention fit the FC more. These results emphasize the significance of considering self-efficacy in the context of flipped classrooms and highlight the approach’s benefits. Furthermore, careful course design is essential to optimize the effectiveness of flipped classrooms. However, due to the heterogeneity and limitations of the included studies, the results should be interpreted with caution. Future research is recommended to explore further the effectiveness of the FC approach on self-efficacy in various educational settings.

Mode transition is an important dynamic process of an adaptive cycle engine (ACE). In order to obtain a smooth mode transition process, the closed-loop controller is designed based on the strong robust augmented linear quadric regulator (ALQR) method, and with the objective of minimizing the thrust fluctuation in the process of mode transition, an open-loop geometrical mechanism control schedules optimization method based on Bézier curves is proposed, so that the closed-loop control and the open-loop control can work in coordination. The simulation results at the subsonic cruise operating point and supersonic cruise operating point show that based on the optimized open-loop geometrical mechanism control schedules and the designed closed-loop ALQR control system, the ACE achieves fast and smooth geometrical mechanisms and engine output transition during the mode transition process with a maximum thrust fluctuation of 2.58%, which is much smaller than that of the traditional linear variation geometric mechanisms with a maximum 4.64% thrust fluctuation, which verifies the effectiveness of the proposed control method.

Abstract Mutations in CHCHD10, a gene coding for a mitochondrial intermembrane space protein, are associated with Frontotemporal dementia (FTD)-Amyotrophic lateral sclerosis (ALS) spectrum disorders, which are pathologically characterized by cytoplasmic inclusions containing TDP-43. FTD/ALS-linked CHCHD10 mutations and TDP-43 inclusions similarly induce mitochondrial defects in respiration, fusion/fission, mtDNA stability, and cristae structure, while sizeable amounts of cytoplasmic TDP-43 aggregates are found in mitochondria. However, the mechanistic link between CHCHD10 and TDP-43 pathogenesis remains unclear. In this study, we present immunohistochemical and biochemical evidence demonstrating that insoluble CHCHD10 aggregates accumulate and colocalize with phospho-TDP-43 inclusions in brains of FTLD-TDP and AD patients, and that insoluble CHCHD10 levels tightly correlate with insoluble TDP-43 levels in control and FTLD-TDP brains. In an experimental exploration of this pathological phenotype, transgenic mice neuronally expressing FTD/ALS-linked CHCHD10R15L or CHCHDS59L mutations but not CHCHD10WT transgenic mice exhibit significantly increased CHCHD10 aggregation and phospho-TDP-43 pathology, which often colocalize within the same inclusions. Such pathologies are reflected in poor functional outcomes in long-term synaptic plasticity, motor unit physiology, and behavior in CHCHD10R15L and CHCHDS59L transgenic mice. In contrast, expression of CHCHD10WT in hTDP-43 transgenic mice (TAR4;CHCHD10WT) significantly mitigates phospho-TDP-43 pathology and rescues TDP-43-induced impairments in synaptic integrity and long-term synaptic plasticity. In isolated mitochondria, the S59L mutation induces the aggregation of resident CHCHD10S59L protein as well as the aggregation and slower turnover of recombinant TDP-43 imported into mitochondria. Likewise, in an in vitro cell-free system, the S59L mutation induces the aggregation of CHCHD10S59L protein while simultaneously enhancing the aggregation of recombinant TDP-43, as evidenced by filter trap assays and atomic force microscopy. In contrast, recombinant CHCHD10WT inhibits the growth of TDP-43 aggregates. These results in human brains, transgenic mice, and in vitro systems substantiate the role of wild type and mutant CHCHD10 in modulating mitochondrial CHCHD10 and TDP-43 pathogenesis together with associated phenotypes in long-term synaptic plasticity and motor unit physiology in mice and humans.

Innate immune receptor TLR4 plays an important role in glycolipid metabolism. The objective of this study is to investigate the inhibitory effects of blocking TLR4 on hyperglycemia and hyperlipidemia by comparing WT and TLR4−/− mice in obesity and diabetes modeling. The knockout of the TLR4 gene could prevent weight gain induced by a high-fat diet (HFD)/high-sugar and high-fat diet (HSHFD), and the differences in the responses existed between the sexes. It extends the time required to reach the obesity criteria. However, when mice were injected with intraperitoneal streptozotocin (STZ) after being fed by HSHFD for two months, TLR4−/− mice exhibited less weight loss than WT. Blocking TLR4 alleviated the changes in body weight and blood glucose, consequently reducing the efficiency of diabetes modeling, especially for male mice. Additionally, male TLR4−/− obese mice exhibit lower total cholesterol (TC) and low-density lipoprotein (LDL) levels in serum and less formation of fat droplets in the liver compared to WT. On the other hand, the knockout of TLR4 significantly increased the high-density lipoprotein (HDL) of male mice. This study should provide new insights into the role of TLR4, as well as opportunities to target novel approaches to the prevention and treatment of metabolic diseases like obesity and diabetes.

Blueberries are fruits known for their high level of anthocyanins, which have high nutritional value and several biological properties. However, the chemical instability of anthocyanins is one of the major limitations of their application. The stability of blueberry anthocyanin extracts (BAEs) encapsulated in a ferritin nanocarrier was investigated in this study for several influencing parameters, including pH, temperature, UV–visible light, redox agents, and various metal ions. The outcomes supported the positive role of protein nanoparticles in enhancing the stability of blueberry anthocyanins by demonstrating that the stability of encapsulated BAE nanoparticles with ferritin carriers was significantly higher than that of free BAEs and a mixture of BAEs and ferritin carriers. This study provides an alternative approach for enhancing blueberry anthocyanin stability using ferritin nanocarrier encapsulation.

BackgroundM2-like tumor-associated macrophages (M2-like TAMs) have important roles in the progression and therapeutics of cancers. We aimed to detect novel M2-like TAM-related biomarkers in hepatocellular carcinoma (HCC) via integrative analysis of single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data to construct a novel prognostic signature, reveal the “immune landscape”, and screen drugs in HCC.MethodsM2-like TAM-related genes were obtained by overlapping the marker genes of TAM identified from scRNA-seq data and M2 macrophage modular genes identified by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were carried out to screen prognostic genes from M2-like TAM-related genes, followed by a construction of a prognostic signature, delineation of risk groups, and external validation of the prognostic signature. Analyses of immune cells, immune function, immune evasion scores, and immune-checkpoint genes between high- and low-risk groups were done to further reveal the immune landscape of HCC patients. To screen potential HCC therapeutic agents, analyses of gene–drug correlation and sensitivity to anti-cancer drugs were conducted.ResultsA total of 127 M2-like TAM-related genes were identified by integrative analysis of scRNA-seq and bulk-seq data. PDLIM3, PAM, PDLIM7, FSCN1, DPYSL2, ARID5B, LGALS3, and KLF2 were screened as prognostic genes in HCC by univariate Cox regression and LASSO regression analyses. Then, a prognostic signature was constructed and validated based on those genes for predicting the survival of HCC patients. In terms of drug screening, expression of PAM and LGALS3 was correlated positively with sensitivity to simvastatin and ARRY-162, respectively. Based on risk grouping, we predicted 10 anticancer drugs with high sensitivity in the high-risk group, with epothilone B having the lowest half-maximal inhibitory concentration among all drugs tested.ConclusionsOur findings enhance understanding of the M2-like TAM-related molecular mechanisms involved in HCC, reveal the immune landscape of HCC, and provide potential targets for HCC treatment.

Ginsenoside Rc (GRc), an active component isolated from ginseng, has been reported to have anti-inflammatory properties. However, the potential mechanism of its effect on rheumatoid arthritis (RA) is not reported. The present study established the RA model by injection of complete Freund’s adjuvant in the hind paw. GRc was administrated by gavage daily. The results showed that GRc ameliorated the swelling rate of both hind paws and reduced the arthritis score in rats. Meanwhile, GRc inhibited cartilage damage and inflammatory cell infiltration in the joint tissue. Furthermore, GRc significantly decreased the concentration of pro-inflammatory cytokines in the joint tissue of rats. Additionally, GRc downregulated the NF-κB signaling pathway. In conclusion, these findings show that GRc remarkably reduced cartilage damage and inflammatory response in the RA rat model by inhibiting of NF-κB signaling pathway.

BackgroundBile acids (BAs) have been proposed to promote gastrointestinal cells carcinogenesis. However, studies on serum total bile acid (TBA) levels and gastrointestinal cancers (GICs) risk are rare.MethodsWe conducted a retrospective case–control study from 2015 to 2019 at the First Affiliated Hospital of Air Force Military Medical University, in which 4,256 GICs cases and 1,333 controls were recruited. Patients’ demographic, clinical and laboratory data were collected. The odds ratios (ORs) with 95% confidence intervals (CIs) were estimated using binary logistic regression models.ResultsPositive associations were observed between serum TBA levels and risks of esophageal cancer (EC), gastric cancer (GC) and colorectal cancer (CRC). Overall, ORs of EC, GC and CRC risk rose with the TBA levels increasing. After adjustment for potential confounders, the OR of TBA-positive for EC risk was 4.89 (95% CI: 3.20-7.49), followed by GC (OR: 3.92, 95% CI: 2.53-6.08), and CRC (OR: 3.32, 95% CI: 2.04-5.11). Patients aged 60 years or older have a higher risk of GICs, especially for EC patients. Males are associated with a higher risk of GC, while females are associated with a higher risk of CRC. Preoperative serum TBA positive and negative was significantly different in the presence or absence of hematogenous metastasis among EC patients (P=0.014), and lymph node metastasis among GC patients (P=0.018).ConclusionsThis retrospective study showed positive associations between serum TBA level and GICs risk, and a higher serum TBA level constitutes a risk factor for GICs.

With the high penetrated photovoltaics (PVs) accessing distribution networks (DNs) in the future, the overvoltage of distribution network will be more serious, and the voltage control will be more complex. To solve this problem, a cluster partition-based zonal voltage control method for DN is proposed in this study. First, a cluster partition method using a comprehensive performance index is proposed: in terms of DN structure, a global density quality function index is introduced to measure the coupling degree of nodes in clusters. In terms of cluster function, the inconsistency coefficient index is presented to reflect the PV output characteristics, and a node membership function index is presented to limit the scale of the cluster. Then, the DN cluster partition is carried out under the fast Newman (FN) algorithm. Second, a second-order cone programming (SOCP) model of voltage control is established to maximize the PV consumption in each cluster. To achieve the coordinated optimization of clusters, an iterative optimization strategy among clusters is proposed. Finally, the effectiveness and rationality of the proposed method are verified in a 10 kV actual feeder system in Zhejiang Province, China.

Abstract Background Particulated juvenile allograft cartilage (PJAC) has a good short-term clinical efficacy in repairing articular cartilage defects, but the proliferation ability of PJAC and the biological characteristics of transplanted cells after transplantation are still unclear. Purpose To study the cartilage proliferation ability of PJAC in repairing full-thickness cartilage defects and the reasons for proliferation to provide experimental evidence for its clinical application. Study design Controlled laboratory study. Methods Twenty Guizhou minipigs were randomly divided into the experimental group and control group. In all minipigs, an 8-mm cylindrical full-thickness cartilage defect was created in the femoral trochlea of one knee. The experimental group received PJAC transplantation from five juvenile donors of Guizhou minipigs (PJAC group; n = 10) and the control group received transplantation of autologous cartilage chips (ACC group; n = 10). Both groups were followed at 1 and 3 months after surgery, immunohistochemical evaluation of the tissue sections Ki-67 and Lin28 was conducted, the positive rate was calculated according to the staining, and the proliferation ability of PJAC was analyzed. Results All 20 Guizhou minipigs were followed, and there was no infection or incision healing disorder after surgery. By Ki-67 and Lin28 immunohistochemical tests, the positive rate of Ki-67 was 88.9 ± 0.2% in the PJAC group and 28.3 ± 3.6% in the ACC group at 1 month, and the difference was statistically significant (P

Abstract Background Ericoid mycorrhizal fungi (EMF) play important roles in mineral cycling and plant nutrient acquisition, and they increase plant survival in nutrient-poor environments. In this study, we detected the colonization of EMF using a green fluorescent protein (GFP) expression method and in situ PCR. Results Genetic transformants of Cryptosporiopsis ericae and Sordariomycetes sp. expressing GFP were obtained via Agrobacterium tumefaciens-mediated transformation. GFP transformants were able to infect Vaccinium uliginosum, and their fluorescence was visible in the hair roots. Both in situ PCR and the GFP-expressing method indicated that EMF could colonize the hair roots of V. uliginosum 2 weeks after inoculation. Conclusions This research represents the first attempt to detect ericoid mycorrhizal colonization using in situ PCR. A GFP-expressing method is an excellent system for detecting the colonization of EMF, but it is dependent on the successful transformation and expression of the gfp gene. In situ PCR and the GFP expression may be developed as new tools to study the interactions of EMF both with ericaceous plants and with the environment.

Pathogenic Th17, featured by their production of pro-inflammatory cytokines, are considered as a key player in most autoimmune diseases. The transcriptome of them is obviously distinct from that of conventional regulatory Th17. However, chromatin accessibility of the two Th17 groups have not been comprehensively compared yet. Here, we found that their chromatin-accessible regions(ChARs) significantly correlated with the expression of related genes, indicating that they might engage in the regulation of these genes. Indeed, pathogenic Th17 specific ChARs (patho-ChARs) exhibited a significant distribution preference in TSS-proximal region. We further filtered the patho-ChARs based on their conservation among mammalians or their concordance with the expression of their related genes. In either situation, the filtered patho-ChARs also showed a preference for TSS-proximal region. Enrichment of expression concordant patho-ChARs related genes suggested that they might involve in the pathogenicity of Th17. Thus, we also examined all ChARs of patho-ChARs related genes, and defined an opening ChAR set according to their changes in the Th17 to Th1 conversion. Interestingly, these opening ChARs displayed a sequential accessibility change from TSS-proximal region to TSS-distal region. Meanwhile, a group of patho-TFs (transcription factors) were identified based on the appearance of their binding motifs in the opening ChARs. Consistently, some of them also displayed a similar preference for binding the TSS-proximal region. Single-cell transcriptome analysis further confirmed that these patho-TFs were involved in the generation of pathogenic Th17. Therefore, our results shed light on a new regulatory mechanism underlying the generation of pathogenic Th17, which is worth to be considered for autoimmune disease therapy.

Cardiac diseases compose a fatal disease category worldwide. Over the past decade, high-throughput transcriptome sequencing of bulk heart tissues has widened our understanding of the onset and progression of cardiac diseases. The recent rise of single-cell RNA sequencing (scRNA-seq) technology further enables deep explorations of their molecular mechanisms in a cell-type-specific manner. However, due to technical difficulties in performing scRNA-seq on heart tissues, there are still few scRNA-seq studies on cardiac diseases. In this study, we demonstrate that an effective alternative could be cell-type-specific computational reconstruction of bulk transcriptomes. An integrative bulk transcriptome dataset covering 110 samples from 12 studies was first constructed by re-analysis of raw sequencing data derived from the heart tissues of four common cardiac disease mouse models (myocardial infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy, and arrhythmogenic right ventricular cardiomyopathy). Based on the single-cell reference covering four major cardiac component cell types and 22 immune cell subtypes, for each sample, the bulk transcriptome was reconstructed into cellular compositions and cell-type-specific expression profiles by CIBERSORTx. Variations in the estimated cell composition revealed elevated abundances of fibroblast and monocyte during myocardial infarction, which were further verified by our flow cytometry experiment. Moreover, through cell-type-specific differential gene expression and pathway enrichment analysis, we observed a series of signaling pathways that mapped to specific cell type in diseases, like MAPK and EGFR1 signaling pathways in fibroblasts in myocardial infarction. We also found an increased expression of several secretory proteins in monocytes which may serve as regulatory factors in cardiac fibrosis. Finally, a ligand–receptor analysis identified key cell types which may serve as hubs in cellular communication in cardiac diseases. Our results provide novel clues for the cell-type-specific signatures of cardiac diseases that would promote better understanding of their pathophysiological mechanisms.

Human papillomaviruses (HPVs), for instance, HPV 16 and HPV 18, are concerned associated with cervical cancer. Thus, it is essential to suppress HPVs-in HPV-positive cervical cancer for treating cervical cancer. The purpose of this study was to explore the proposed molecular mechanisms, which that underlies the antintumor potential of juglone to treat of HPV-positive on cervical cancer cells. The results showed that juglone suppressed HPV-positive cell growth in a dose- and time-dependent way. In addition, cell invasion and metastasis were also inhibited by juglone. Nevertheless, when pin 1 was knocked down in HPV-positive cells, cell proliferation, invasion and metastasis were reduced. This study was designed to acquire an understanding of the mechanism of invasion and metastasis in HPV-positive cells suppressed by juglone. It provides evidence of the advantageous use of juglone in the future. Keywords: Juglone, HPV-positive, Cervical cancer cells, Invasion, Metastasis

The Large Eddy Simulation (LES) method and Delayed Detached Eddy Simulation (DDES) method combined with the Ffowcs Williams and Hawkings (FW–H) analogy are used to predict the self-noise of NACA 65(12)-10 airfoil at low to moderate Reynolds numbers. The computational results have been validated through the comparison with experimental data and NAFNoise predictive data. The results indicate that both LES and DDES methods can output correct sound pressure level (SPL) spectra at a Reynolds number of 2 × 105, but only the LES method is capable of providing reasonable SPL spectra at a Reynolds number of 5 × 105, which the DDES method has failed to do. The broadband noise below 10 kHz obtained from the DDES method is lower than that from NAFNoise prediction by up to 50 dB. Further analysis shows that the DDES method fails to capture the separation and reattachment on the suction side near the trailing edge. Besides, the magnitude of pressure fluctuation on the airfoil surface obtained from the DDES method is far smaller than that from the LES method, providing incorrect acoustic source information for the FW–H equation. In the near-wall region for the DDES case, the Reynolds-averaged Navier–Stokes method is used to compute the unsteady flow field, providing too large viscosity and too small Reynolds stress near the airfoil surface, which makes it difficult to capture the influence of small-scale eddies in the flow field. The characteristics of the DDES method above could cause errors in simulating the unsteady flow field at a Reynolds number of 105 range. On the contrary, the LES method could give better prediction of broadband noise under different incoming flow conditions.

Sjögren’s syndrome (SjS), characterized by keratoconjunctivitis sicca and dry mouth, is a common autoimmune disease, especially in middle-aged women. The immunopathogenesis of SjS is caused by the sequential infiltration of T and B cells into exocrine glands, including salivary and lacrimal glands. Effector cytokines produced by these immunocytes, such as interferons (IFNs), IL-17, IL-22, IL-21, IL-4, TNF-α, BAFF and APRIL, play critical roles in promoting autoimmune responses and inducing tissue damages. Epigenetic regulations, including DNA methylation, histone modification and non-coding RNAs, have recently been comprehensively studied during the activation of various immunocytes. The deficiency of key epigenetic enzymes usually leads to aberrant immune activation. Epigenetic modifications in T and B cells are usually found to be altered during the immunopathogenesis of SjS, and they are closely correlated with autoimmune responses. In particular, the important role of methylation in activating IFN pathways during SjS progression has been revealed. Thus, according to the involvement of epigenetic regulations in SjS, target therapies to reverse the altered epigenetic modifications in auto-responsive T and B cells are worthy of being considered as a potential therapeutic strategy for SjS.

Osteosarcoma is a serious bone malignancy that threatens to human health, while the conventional chemotherapy exhibits ineffective and severe side effects. Here, a multi-approach for primary and metastatic tumors was developed by combining photothermal ablation-based in situ tumor vaccine with PD-1/PD-L1 blockade immunotherapy. Polyethyleimine modified golden nanorod (GNR-PEI) was prepared by conjugating of hyperbranched PEI to GNR via SAu bonds. The positive charged GNR-PEI could complex with cyclic dimeric guanosine monophosphate-adenosine monophosphate (cGAMP) by electrostatic interaction. GNR-PEI/cGAMP complex was further utilized for near-infrared laser-triggered phototherapy of primary tumors, generating in situ tumor vaccine, recruiting dendritic cells (DCs) to capture tumor-associated antigens. In addition, cGAMP is a kind of stimulator of interferon genes (STING) agonist that can stimulate the expansion and activation of DCs, arousing the specific immune killing effect of cytotoxic T cells. Furthermore, the combination of localized tumor vaccine and programmed cell death protein-1 (PD-1) monoclonal antibody (anti-PD-1), that could achieve the checkpoint-blockade and reverse tumor immune tolerance microenvironment, thus improving T cells specific recognition and killing of remaining and metastasis tumor cells. Hence, this combined strategy is expected to be further used in the clinical treatment of osteosarcoma.

Polyether ether ketone (PEEK) is a non-toxic polymer with elastic modulus close to human bone. Compared with metal implants, PEEK has advantages such as evasion of stress shielding effect, easy processing, and similar color as teeth, among others. Therefore, it is an excellent substitute material for titanium dental orthopedic implants. However, PEEK’s biological inertia limits its use as an implant. To change PEEK’s biological inertia and increase its binding ability with bone tissue as an implant, researchers have explored a number of modification methods to enhance PEEK’s biological activities such as cellular compatibility, osteogenic activity, and antibacterial activity. This review summarizes current biological activity modification methods for PEEK, including surface modification and blending modification, and analyzes the advantages and disadvantages of each modification method. We believe that modified PEEK will be a promising dental and orthopedic implant material.

Background: Accurate lymph nodes (LNs) assessment is important for rectal cancer (RC) staging in multiparametric magnetic resonance imaging (mpMRI). However, it is incredibly time-consumming to identify all the LNs in scan region. This study aims to develop and validate a deep-learning-based, fully-automated lymph node detection and segmentation (auto-LNDS) model based on mpMRI. Methods: In total, 5789 annotated LNs (diameter ≥ 3 mm) in mpMRI from 293 patients with RC in a single center were enrolled. Fused T2-weighted images (T2WI) and diffusion-weighted images (DWI) provided input for the deep learning framework Mask R-CNN through transfer learning to generate the auto-LNDS model. The model was then validated both on the internal and external datasets consisting of 935 LNs and 1198 LNs, respectively. The performance for LNs detection was evaluated using sensitivity, positive predictive value (PPV), and false positive rate per case (FP/vol), and segmentation performance was evaluated using the Dice similarity coefficient (DSC). Findings: For LNs detection, auto-LNDS achieved sensitivity, PPV, and FP/vol of 80.0%, 73.5% and 8.6 in internal testing, and 62.6%, 64.5%, and 8.2 in external testing, respectively, significantly better than the performance of junior radiologists. The time taken for model detection and segmentation was 1.3 s/case, compared with 200 s/case for the radiologists. For LNs segmentation, the DSC of the model was in the range of 0.81–0.82. Interpretation: This deep learning–based auto-LNDS model can achieve pelvic LNseffectively based on mpMRI for RC, and holds great potential for facilitating N-staging in clinical practice.

Pulse coupled neural network (PCNN) is widely used in image processing because of its unique biological characteristics, which is suitable for image fusion. When combining PCNN with non‐subsampled contourlet (NSCT) model, it is applied in overcoming the difficulty of coefficients selection for subband of the NSCT model. However in the original model, only the grey values of image pixels are used as input, without considering that the subjective vision of human eyes lacks the sensitivity to the local factors of the image. In this study, the improved pulse‐coupled neural network model has replaced the grey‐scale value of the image and introduced the weighted product of the strength of the gradient of the image and the local phase coherence as the model input. Finally, compared with other multi‐scale decompositions‐based image fusion and other improved NSCT‐PCNN algorithms, the algorithm presented in this study outperforms them in terms of objective criteria and visual appearance.

Mutations inCHCHD10 have been recently associated with frontotemporal dementia and amyotrophic lateral sclerosis. Here the authors study the functions of endogenous CHCHD10 in Caenorhabditis elegans, primary neurons, and mouse, and show that it normally protects mitochondria and synaptic integrity, and retains TDP-43 in the nucleus.

Strong tropical cyclone (TC) Ockhi occurred in the southeastern Arabian Sea (AS) in 2017. Ockhi greatly changed the oceanic conditions and induced large variation in chlorophyll-a (Chl-a). The dynamic mechanisms of the long-term phytoplankton bloom after the passage of the TC were investigated in this study. Prominent surface ocean responses, e.g., decreasing temperature and salinity, were identified from Argo data by comparing the pre- and post-conditions of the TC. A phytoplankton bloom was observed in southeastern AS after the passage of TC Ockhi within the area of (11°N-14°N, 67°E-70°E) and lasted for seven days. Interestingly, there were two weaker cyclonic eddies, with an average vorticity of less than 0.14 s-1, on the TC trajectory from November 28 to December 2. As Ockhi approached, strong vertical mixing occurred on December 3, increasing the eddy vorticity to 0.26 s-1. After the passage of Ockhi, both eddies, with a two-day oscillation period, were substantially enhanced. Especially from December 11 to 16, the vorticity above 70 m was as high as 0.2 s-1 in the thermocline. Because of the high photosynthetically available radiation (PAR) and low precipitation, the enhanced cyclonic eddies induced upwelling for the entire thermocline for over ten days and uplifted nitrates into the mixed layer. This study offers new insights on the influence of eddies in regulating the impacts of typhoons on Chl-a, and the results can help evaluate typhoon-induced biological responses in the future.

Abstract Exploration of high‐performance cathode materials for rechargeable aqueous Zn ion batteries (ZIBs) is highly desirable. The potential of molybdenum trioxide (MoO3) in other electrochemical energy storage devices has been revealed but held understudied in ZIBs. Herein, a demonstration of orthorhombic MoO3 as an ultrahigh‐capacity cathode material in ZIBs is presented. The energy storage mechanism of the MoO3 nanowires based on Zn2+ intercalation/deintercalation and its electrochemical instability mechanism are particularly investigated and elucidated. The severe capacity decay of the MoO3 nanowires during charging/discharging cycles arises from the dissolution and the structural collapse of MoO3 in aqueous electrolyte. To this end, an effective strategy to stabilize MoO3 nanowires by using a quasi‐solid‐state poly(vinyl alcohol)(PVA)/ZnCl2 gel electrolyte to replace the aqueous electrolyte is developed. The capacity retention of the assembled ZIBs after 400 charge/discharge cycles at 6.0 A g−1 is significantly boosted, from 27.1% (in aqueous electrolyte) to 70.4% (in gel electrolyte). More remarkably, the stabilized quasi‐solid‐state ZIBs achieve an attracting areal capacity of 2.65 mAh cm−2 and a gravimetric capacity of 241.3 mAh g−1 at 0.4 A g−1, outperforming most of recently reported ZIBs.

The literature has shown that the performance of the de-noising algorithm was greatly influenced by the dependencies between wavelet coefficients. In this paper, the bivariate probability density function (PDF) was proposed which was symmetric, and the dependencies between the coefficients were considered. The bivariate Cauchy distribution and the bivariate Student’s distribution are special cases of the proposed bivariate PDF. One of the parameters in the probability density function gave the estimation method, and the other parameter can take any real number greater than 2. The algorithm adopted a maximum a posteriori estimator employing the dual-tree complex wavelet transform (DTCWT). Compared with the existing best results, the method is faster and more efficient than the previous numerical integration techniques. The bivariate shrinkage function of the proposed algorithm can be expressed explicitly. The proposed method is simple to implement.

An external modulation laser module assembly (EMLMA) is proposed to suppress nonlinear errors in an interferometry system and improve its measurement performance. The EMLMA employs both phase modulation with radio frequency signal and a specific modulation amplitude switching mode, enabling the suppression of noise introduced by spurious reflections. The amplitude modulation reduces the influence of stray and background light by transforming the signal of interest to a high-frequency bandwidth. Experimental results show that the measurement error and stability of the interferometry system are significantly improved using the proposed light source module. After modulation, the spurious reflection-induced offset is decreased, and the measurement resolution improves from 7 to 2 nm. The EMLMA can replace the light source of any interferometric measurement system without altering the optical measurement structure. The proposed method reduces the influence of nonlinear errors in homodyne interferometry and provides a basis for further improvement of the interferometry performance.

Upon apoptotic stimuli, lysosomal proteases, including cathepsins and chymotrypsin, are released into cytosol due to lysosomal membrane permeabilization (LMP), where they trigger apoptosis via the lysosomal-mitochondrial pathway of apoptosis. Herein, the mechanism of LMP was investigated. We found that caspase 8-cleaved Bid (tBid) could result in LMP directly. Although Bax or Bak might modestly enhance tBid-triggered LMP, they are not necessary for LMP. To study this further, large unilamellar vesicles (LUVs), model membranes mimicking the lipid constitution of lysosomes, were used to reconstitute the membrane permeabilization process in vitro. We found that phosphatidic acid (PA), one of the major acidic phospholipids found in lysosome membrane, is essential for tBid-induced LMP. PA facilitates the insertion of tBid deeply into lipid bilayers, where it undergoes homo-oligomerization and triggers the formation of highly curved nonbilayer lipid phases. These events induce LMP via pore formation mechanisms because encapsulated fluorescein-conjugated dextran (FD)-20 was released more significantly than FD-70 or FD-250 from LUVs due to its smaller molecular size. On the basis of these data, we proposed tBid-PA interactions in the lysosomal membranes form lipidic pores and result in LMP. We further noted that chymotrypsin-cleaved Bid is more potent than tBid at binding to PA, inserting into the lipid bilayer, and promoting LMP. This amplification mechanism likely contributes to the culmination of apoptotic signaling.

Thermosensitive gels are commonly used as drug carriers in medical fields, mainly due to their convenient processing and easy functionalization. However, their overall performance has been severely affected by their unsatisfying biocompatibility and biodegradability. To this end, we synthesized poly(l-alanine) (PLAla)-based thermosensitive hydrogels with different degrees of polymerization by ring-opening polymerization. The obtained mPEG45−PLAla copolymers showed distinct transition temperatures and degradation abilities. It was found that slight changes in the length of hydrophobic side groups had a decisive effect on the gelation behavior of the polypeptide hydrogel. Longer hydrophobic ends led to a lower gelation temperature of gel at the same concentration, which implied better gelation capability. The hydrogels showed rapid gelling, enhanced biocompatibility, and better degradability. Therefore, this thermosensitive hydrogel is a promising material for biomedical application.