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Abstract The senescence of alveolar type II (AT2) cells impedes self-repair of the lung epithelium and contributes to lung injury in the setting of idiopathic pulmonary fibrosis (IPF). Yes-associated protein 1 (YAP1) is essential for cell growth and organ development; however, the role of YAP1 in AT2 cells during pulmonary fibrosis is still unclear. YAP1 expression was found to be downregulated in the AT2 cells of PF patients. Deletion of YAP1 in AT2 cells resulted in lung injury, exacerbated extracellular matrix (ECM) deposition, and worsened lung function. In contrast, overexpression of YAP1 in AT2 cells promoted alveolar regeneration, mitigated pulmonary fibrosis, and improved lung function. In addition, overexpression of YAP1 alleviated bleomycin (BLM) -induced senescence of alveolar epithelial cells both in vivo and in vitro. Moreover, YAP1 promoted the expression of peroxiredoxin 3 (Prdx3) by directly interacting with TEAD1. Forced expression of Prdx3 inhibited senescence and improved mitochondrial dysfunction in BLM-treated MLE-12 cells, whereas depletion of Prdx3 partially abrogated the protective effect of YAP1. Furthermore, overexpression of Prdx3 facilitated self-repair of the injured lung and reduced ECM deposition, while silencing Prdx3 attenuated the antifibrotic effect of YAP1. In conclusion, this study demonstrated that YAP1 alleviates lung injury and pulmonary fibrosis by regulating Prdx3 expression to improve mitochondrial dysfunction and block senescence in AT2 cells, revealing a potential novel therapeutic strategy for pulmonary fibrosis.

ABSTRACT Background Renal ischaemia‒reperfusion injury (IRI) is the primary cause of acute kidney injury (AKI). To date, effective therapies for delaying renal IRI and postponing patient survival remain absent. Ankyrin repeat domain 1 (ANKRD1) has been implicated in some pathophysiologic processes, but its role in renal IRI has not been explored. Methods The mouse model of IRI‐AKI and in vitro model were utilised to investigate the role of ANKRD1. Immunoprecipitation‐mass spectrometry was performed to identify potential ANKRD1‐interacting proteins. Protein‒protein interactions and protein ubiquitination were examined using immunoprecipitation and proximity ligation assay and immunoblotting, respectively. Cell viability, damage and lipid peroxidation were evaluated using biochemical and cellular techniques. Results First, we unveiled that ANKRD1 were significantly elevated in renal IRI models. Global knockdown of ANKRD1 in all cell types of mouse kidney by recombinant adeno‐associated virus (rAAV9)‐mitigated ischaemia/reperfusion‐induced renal damage and failure. Silencing ANKRD1 enhanced cell viability and alleviated cell damage in human renal proximal tubule cells exposed to hypoxia reoxygenation or hydrogen peroxide, while ANKRD1 overexpression had the opposite effect. Second, we discovered that ANKRD1's detrimental function during renal IRI involves promoting lipid peroxidation and ferroptosis by directly binding to and decreasing levels of acyl‐coenzyme A synthetase long‐chain family member 3 (ACSL3), a key protein in lipid metabolism. Furthermore, attenuating ACSL3 in vivo through pharmaceutical approach and in vitro via RNA interference mitigated the anti‐ferroptotic effect of ANKRD1 knockdown. Finally, we showed ANKRD1 facilitated post‐translational degradation of ACSL3 by modulating E3 ligase tripartite motif containing 25 (TRIM25) to catalyse K63‐linked ubiquitination of ACSL3, thereby amplifying lipid peroxidation and ferroptosis, exacerbating renal injury. Conclusions Our study revealed a previously unknown function of ANKRD1 in renal IRI. By driving ACSL3 ubiquitination and degradation, ANKRD1 aggravates ferroptosis and ultimately exacerbates IRI‐AKI, underlining ANKRD1's potential as a therapeutic target for kidney IRI. Key Points/Highlights Ankyrin repeat domain 1 (ANKRD1) is rapidly activated in renal ischaemia‒reperfusion injury (IRI) models in vivo and in vitro. ANKRD1 knockdown mitigates kidney damage and preserves renal function. Ferroptosis contributes to the deteriorating function of ANKRD1 in renal IRI. ANKRD1 promotes acyl‐coenzyme A synthetase long‐chain family member 3 (ACSL3) degradation via the ubiquitin‒proteasome pathway. The E3 ligase tripartite motif containing 25 (TRIM25) is responsible for ANKRD1‐mediated ubiquitination of ACSL3.

With the development of artificial intelligence technology and the disclosure of massive judicial data, the LJP task for ＆quot;smart justice＆quot; services has received widespread attention from academia and industry.The task aims to predict the charges, laws, and sentences of a case based on limited factual descriptions of the text.However, existing work lacks research on intelligent decision-making in easily confusing judicial cases, and related models often lack interpretability, which leads to heavy reliance on domain experts for model predictions and hinders the application of LJP in different legal systems.To this end, this article proposes a judicial judgment prediction method CGLJ based on causal graph analysis.Firstly, the causal relationships among elements are mined from unstructured legal fact description texts.Then a causal graph is constructed using a composition method of easily confused accusation clustering.It not only considers the difference among similar fact descriptions, but also enhances the interaction between fact descriptions and laws and regulations.Finally, the constructed causality diagram is integrated into a deep neural network for joint inference to obtain the decision prediction result.In addition, this paper also visualizes the causal diagram inference process in the model prediction, providing better interpretability for the judgment result.The experimental result on the CAIL2018 judicial judgment prediction dataset shows that the proposed method achieves better result than the baseline models.

As the global incidence of diabetes rises and diagnoses among younger patients increase, transplant centers worldwide are encountering more organ donors with diabetes. This study examined 80 donors and 160 recipients, including 30 donors with diabetes (DD) and their 60 recipients (DDR). The control group comprised 50 non-diabetic donors (ND) and 100 recipients (NDR). We analyzed clinical, biochemical, and pathological data for both diabetic and control groups, using logistic regression to identify risk factors for delayed graft function (DGF) after kidney transplantation. Results showed that pre-procurement blood urea nitrogen levels were significantly higher in DD [18.20 ± 10.63 vs. 10.86 ± 6.92, p = 0.002] compared to ND. Renal pathological damage in DD was notably more severe, likely contributing to the higher DGF incidence in DDR compared to NDR. Although DDR had poorer renal function during the first three months post-transplant, both groups showed similar renal function thereafter. No significant differences were observed in 1-year or 3-year mortality rates or graft failure rates between DDR and NDR. Notably, according to the Renal Pathology Society (RPS) grading system, kidneys from diabetic donors with a grade > IIb are associated with significantly lower postoperative survival rates. Recipient gender [OR: 5.452 (1.330–22.353), p = 0.013] and pre-transplant PRA positivity [OR: 34.879 (7.698–158.030), p

BackgroundPost-stroke depression (PSD) is a well-established psychiatric complication following stroke. Nevertheless, the relationship between early-onset PSD and homocysteine (Hcy) or fibrinogen remains uncertain.MethodsAcute ischemic stroke (AIS) patients who met the established criteria were enrolled in this study. Early-onset PSD was diagnosed two weeks after the stroke. The severity of depressive symptoms was assessed by the Hamilton Depression Scale-17 items (HAMD-17), with patients scored ≥7 assigned to the early-onset PSD group. Spearman rank correlation analysis was employed to evaluate the associations between Hcy, fibrinogen, and HAMD scores across all patients. Logistic regression analysis was conducted to investigate the relationship between Hcy, fibrinogen, and early-onset PSD. Receiver operating characteristic curve (ROC) analysis was ASSDalso performed to detect the predictive ability of Hcy and fibrinogen for early-onset PSD.ResultsAmong the 380 recruited patients, a total of 106 (27.89%) patients were diagnosed with early-onset PSD. The univariate analysis suggested that patients in the PSD group had a higher admission National Institutes of Health Stroke Scale (NIHSS) score, modified Rankin Scale score (mRS), Hcy, and fibrinogen levels than patients in the non-PSD group (P

Background The purpose of this study is to employ a competing risk model based on the Surveillance, Epidemiology, and End Results (SEER) database to identify prognostic factors for elderly individuals with sigmoid colon adenocarcinoma (SCA) and compare them with the classic Cox proportional hazards model. Methods We extracted data from elderly patients diagnosed with SCA registered in the SEER database between 2010 and 2015. Univariate analysis was conducted using cumulative incidence functions and Gray’s test, while multivariate analysis was performed using both the Fine-Gray and Cox proportional hazards models. Results Among the 10,712 eligible elderly patients diagnosed with SCA, 5595 individuals passed away: 2987 due to sigmoid colon adenocarcinoma and 2608 from other causes. The results of one-way Gray’s test showed that age, race, marital status, AJCC stage, differentiation grade, tumor size, surgical status, liver metastasis status, lung metastasis status, brain metastasis status, radiotherapy status, and chemotherapy status all affected the prognosis of SCA ( P < .05). Multivariate analysis showed that sex, age, race, marital status, and surgical status affected the prognosis of SCA ( P < .05). Multifactorial Fine-Gray analysis revealed that key factors influencing the prognosis of SCA patients include age, race, marital status, AJCC stage, grade classification, surgical status, tumor size, liver metastasis, lung metastasis, and chemotherapy status ( P < .05). Conclusion Data from the SEER database were used to more accurately estimate CIFs for sigmoid colon adenocarcinoma-specific mortality and prognostic factors using competing risk models.

Cerebral small vessel disease (SVD) may be associated with an increased risk of depressive symptoms. Serum uric acid (SUA), an antioxidant, may be involved in the occurrence and development of depressive symptoms, but the mechanism remains unknown. Moreover, the relationship between structural brain networks and SUA has not been explored. This study examined the relationship between SUA and depressive symptoms in patients with SVD using graph theory analysis. We recruited 208 SVD inpatients and collected fasting blood samples upon admission. Depressive symptoms were assessed using the 24-item Hamilton Depression Rating Scale (HAMD-24). Magnetic resonance imaging was used to evaluate SVD, and diffusion tensor images were used to analyze structural brain networks using graph theory. Patients with depressive symptoms (n = 34, 25.76%) compared to those without (334.53 vs 381.28 μmol/L, p = 0.017) had lower SUA levels. Graph theoretical analyses showed a positive association of SUA with betweenness centrality, nodal efficiency, and clustering coefficients and a negative correlation with the shortest path length in SVD with depressive symptoms group. HAMD scores were significantly associated with nodal network metrics in the right cerebral hemisphere. Our findings suggested that lower SUA levels are significantly associated with disrupted structural brain networks in the right cerebral hemisphere of patients with SVD who have depressive symptoms.

Judicial named entity recognition (JNER) is a basic task of judicial intelligence and judicial service informatization. At present, the research of JNER has attracted extensive attention. However, the existing JNER methods usually can only assign a single label to a token in the input sequence, which is not applicable to nested entities where a token may be assigned two or more different labels at the same time. Therefore, this paper introduces the machine reading comprehension (MRC) framework into JNER, and proposes a judicial nested NER method based on the MRC. Firstly, we design the question template according to the characteristics of judicial nested named entities, and construct the legal text named entity dataset in MRC format. Next, we introduce the span extraction MRC model based on the pre-trained to encode the question and text, and learn the context knowledge of the entity in the question. Finally, we extract the starting and end positions of the matching span respectively through two classifiers, to get the corresponding entities. The experimental results on the information extraction dataset in “CAIL2021” show, compared with the existing baseline models, the proposed method effectively improves the recognition effect of nested entities commonly existing in the judicial field.

Post-transplant anemia is one of the most common complications in kidney transplant recipients, severely affecting patient prognosis and quality of life, and is an independent predictor of graft kidney loss and patient mortality. However, our clinical understanding and the attention given to post-transplant anemia are currently insufficient. This paper reviews the current status, risk factors, and therapeutic progress in anemia after transplantation in kidney transplant recipients. We recommend that clinical staff pay attention to anemia and its complications in kidney transplant recipients and intervene early for anemia.

ObjectiveSepsis-associated encephalopathy (SAE) is strongly linked to a high mortality risk, and frequently occurs in conjunction with the acute and late phases of sepsis. The objective of this study was to construct and verify a predictive model for mortality in ICU-dwelling patients with SAE.MethodsThe study selected 7,576 patients with SAE from the MIMIC-IV database according to the inclusion criteria and randomly divided them into training (n = 5,303, 70%) and internal validation (n = 2,273, 30%) sets. According to the same criteria, 1,573 patients from the eICU-CRD database were included as an external test set. Independent risk factors for ICU mortality were identified using Extreme Gradient Boosting (XGBoost) software, and prediction models were constructed and verified using the validation set. The receiver operating characteristic (ROC) and the area under the ROC curve (AUC) were used to evaluate the discrimination ability of the model. The SHapley Additive exPlanations (SHAP) approach was applied to determine the Shapley values for specific patients, account for the effects of factors attributed to the model, and examine how specific traits affect the output of the model.ResultsThe survival rate of patients with SAE in the MIMIC-IV database was 88.6% and that of 1,573 patients in the eICU-CRD database was 89.1%. The ROC of the XGBoost model indicated good discrimination. The AUCs for the training, test, and validation sets were 0.908, 0.898, and 0.778, respectively. The impact of each parameter on the XGBoost model was depicted using a SHAP plot, covering both positive (acute physiology score III, vasopressin, age, red blood cell distribution width, partial thromboplastin time, and norepinephrine) and negative (Glasgow Coma Scale) ones.ConclusionA prediction model developed using XGBoost can accurately predict the ICU mortality of patients with SAE. The SHAP approach can enhance the interpretability of the machine-learning model and support clinical decision-making.

The potential of potassium chloride (KCl) to be used as a substitute for sodium chloride (NaCl) was studied by monitoring the effects of salt treatment on thermal behavior, aggregation kinetics, rheological properties, and protein conformational changes. The results show that the addition of KCl can improve solubility, reduce turbidity and particle size, and positively influence rheological parameters such as apparent viscosity, consistency coefficient (K value), and fluidity index (n). These changes indicate delayed thermal denaturation. In addition, KCl decreased the content of β-sheet and random coil structures and increased the content of α-helix and β-turn structures. The optimal results were obtained with 2% KCl addition, leading to an increase in Tp up to 85.09 °C. The correlation results showed that Tp was positively correlated with solubility, α-helix and β-turn but negatively correlated with ΔH, turbidity, β-sheet and random coil. Overall, compared to NaCl, 2% KCl is more effective in delaying the thermal aggregation of LWE, and these findings lay a solid theoretical foundation for the study of sodium substitutes in heat-resistant liquid egg products.

BackgroundsThe present study was designed to establish and validate a prediction model for high ovarian response (HOR) in the GnRH antagonist protocol.MethodsIn this retrospective study, the data of 4160 cycles were analyzed following the in vitro fertilization (IVF) at our reproductive medical center from June 2018 to May 2022. The cycles were divided into a training cohort (n=3121) and a validation cohort (n=1039) using a random sampling method. Univariate and multivariate logistic regression analyses were used to screen out the risk factors for HOR, and the nomogram was established based on the regression coefficient of the relevant variables. The area under the receiver operating characteristic curve (AUC), the calibration curve, and the decision curve analysis were used to evaluate the performance of the prediction model.ResultsMultivariate logistic regression analysis revealed that age, body mass index (BMI), follicle-stimulating hormone (FSH), antral follicle count (AFC), and anti-mullerian hormone (AMH) were independent risk factors for HOR (all P< 0.05). The prediction model for HOR was constructed based on these factors. The AUC of the training cohort was 0.884 (95% CI: 0.869–0.899), and the AUC of the validation cohort was 0.884 (95% CI:0.863–0.905).ConclusionThe prediction model can predict the probability of high ovarian response prior to IVF treatment, enabling clinicians to better predict the risk of HOR and guide treatment strategies.

The incidence of lung cancer (LC) in Idiopathic Pulmonary Fibrosis (IPF) patients is more than twice that in non-IPF. This study aims to investigate IPF-to-LC pathogenesis and to develop a predictor for detecting IPF predisposing patients to LC. We conducted unsupervised clustering to detect high-risk subtypes from IPF to LC. Subsequently, we performed single-cell RNA-seq analysis to characterize high-risk IPF by examining the immune microenvironment. We identified 42 common immune function-related pathogenic genes between IPF and LC. We developed an LC risk classifier for IPF patients, comprising five genes: SPP1, MMP9, MMP12, FABP4, and IL1B. The five-gene classifier can successfully distinguish the high-risk population from IPF patients. High-risk IPF patients exhibited an immunosuppressive microenvironment with higher oncogene expression than low-risk patients. Single-cell analysis revealed that SPP1+ macrophages at the terminal of macrophages' developmental trajectory may promote the progression from IPF to LC. The strong crosstalk between SPP1+ macrophages and inflammation-related cancer-associated fibroblasts promoted the tumorigenic process in IPF. In vitro, assays showed that co-culturing macrophages overexpressing SPP1 with MRC-5 cells induced the transition of fibroblasts into cancer-associated fibroblasts. SPP1 produced by macrophages promoted epithelial-mesenchymal transition in alveolar epithelial cells via stimulating the upregulation of N-cadherin and Vimentin in MLE-12 cells. This study provided a novel method to identify the LC risk population from IPF, revealing the cellular interactions involved in the transition from IPF to LC. Our findings highlighted SPP1 as a critical driver in IPF progression, offering a potential target for therapy in fibrosis.

Trajectory prediction is a crucial step in the pipeline for autonomous driving because it not only improves the planning of future routes, but also ensures vehicle safety. On the basis of deep neural networks, numerous trajectory prediction models have been proposed and have already achieved high performance on public datasets due to the well-designed model structure and complex optimization procedure. However, the majority of these methods overlook the fact that vehicles’ limited computing resources can be utilized for online real-time inference. We proposed a Lane Transformer to achieve high accuracy and efficiency in trajectory prediction to tackle this problem. On the one hand, inspired by the well-known transformer, we use attention blocks to replace the commonly used Graph Convolution Network (GCN) in trajectory prediction models, thereby drastically reducing the time cost while maintaining the accuracy. In contrast, we construct our prediction model to be compatible with TensorRT, allowing it to be further optimized and easily transformed into a deployment-friendly form of TensorRT. Experiments demonstrate that our model outperforms the baseline LaneGCN model in quantitative prediction accuracy on the Argoverse dataset by a factor of $10\times $ to $25\times $ . Our $7ms$ inference time is the fastest among all open source methods currently available. Our code is publicly available at: https://github.com/mmdzb/Lane-Transformer.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease with unknown etiology and limited therapeutic options. Activation of fibroblasts is a prominent feature of pulmonary fibrosis. Here we report that lncRNA DACH1 (dachshund homolog 1) is downregulated in the lungs of IPF patients and in an experimental mouse model of lung fibrosis. LncDACH1 knockout mice develop spontaneous pulmonary fibrosis, whereas overexpression of LncDACH1 attenuated TGF-β1-induced aberrant activation, collagen deposition and differentiation of mouse lung fibroblasts. Similarly, forced expression of LncDACH1 not only prevented bleomycin (BLM)-induced lung fibrosis, but also reversed established lung fibrosis in a BLM model. Mechanistically, LncDACH1 binding to the serine/arginine-rich splicing factor 1 (SRSF1) protein decreases its activity and inhibits the accumulation of Ctnnb1. Enhanced expression of SRSF1 blocked the anti-fibrotic effect of LncDACH1 in lung fibroblasts. Furthermore, loss of LncDACH1 promoted proliferation, differentiation, and extracellular matrix (ECM) deposition in mouse lung fibroblasts, whereas such effects were abolished by silencing of Ctnnb1. In addition, a conserved fragment of LncDACH1 alleviated hyperproliferation, ECM deposition and differentiation of MRC-5 cells driven by TGF-β1. Collectively, LncDACH1 inhibits lung fibrosis by interacting with SRSF1 to suppress CTNNB1 accumulation, suggesting that LncDACH1 might be a potential therapeutic target for pulmonary fibrosis.

ObjectiveThe objective of the study was to explore the effect of body mass index (BMI) and insulin resistance (IR) levels on first-time assisted conception results and perinatal outcomes in young polycystic ovary syndrome (PCOS) patients.DesignThis was a single-center, retrospective, observational cohort study.PatientsYoung women with PCOS undergoing their first embryo transfer were included in the study.Main outcome measureEarly pregnancy loss rate was the main outcome measure.ResultsThe early pregnancy loss rate in the overweight + insulin resistance group (OW+IR group) was significantly higher than that in the non-overweight + non-insulin resistance group (NOW+NIR group) (18.16% vs. 9.02%, Bonferroni correction, P = 0.012). The early pregnancy loss rate in the non-overweight + insulin resistance group (NOW+IR group) and overweight + non-insulin resistance group (OW+NIR group) (18.18% and 17.14%, respectively) were also higher than that in the NOW+NIR group (6.07%), but the difference was not statistically significant (Bonferroni correction, all P > 0.05). No significant difference was found in clinical pregnancy rate, live birth rate, and macrosomia rate (all P > 0.05). After adjusting for confounding factors, BMI and IR levels were identified as independent risk factors for early pregnancy loss rate.ConclusionBMI and IR levels are independent risk factors for early pregnancy loss in young PCOS patients during the first embryo transfer cycle. Multiple indicators should be considered when assessing pregnancy outcomes, which will promote individualized pregnancy guidance and treatment procedures for PCOS patients.

Bone marrow-derived mesenchymal stem cells (BMSCs) are increasingly being used in bone marrow transplantation (BMT) to enable homing of the allogeneic hematopoietic stem cells and suppress acute graft versus host disease (aGVHD). The aim of this study was to optimize the labelling of BMSCs with superparamagnetic iron oxide particles (SPIOs), and evaluate the impact of the SPIOs on the biological characteristics, gene expression profile and chemotaxis function of the BMSCs. The viability and proliferation rates of the SPIO-labeled BMSCs were analyzed by trypan blue staining and CCK-8 assay respectively, and the chemotaxis function was evaluated by the transwell assay. The expression levels of chemokine receptors were measured by RT-PCR and flow cytometry. The SPIOs had no effect on the viability of the BMSCs regardless of the labelling concentration and culture duration. The labelling rate of the cells was higher when cultured for 48 h with the SPIOs. Furthermore, cells labeled with 25 µg/ml SPIOs for 48 h had the highest proliferation rates, along with increased expression of chemokine receptor genes and proteins. However, there was no significant difference between the chemotaxis function of the labeled and unlabeled BMSCs. To summarize, labelling BMSCs with 25 µg/ml SPIOs for 48h did not affect their biological characteristics and chemotaxis function, which can be of significance for in vivo applications.

Uncovering the complex periodic variations in soil moisture can provide a significant reference for climate prediction and hydrological process simulation. We used wavelet analysis to quantify and identify the multi-scale periodic variations of soil moisture in the desert steppe of Inner Mongolia from 2009 to 2019 and analyzed the differences between the multi-scale periodic changes in soil moisture at the bottom (BS) and upper slope (US). The results show that the interannual variability in soil moisture at the BS and US has a significant upward trend. Moreover, the amount and volatility decrease with the increase in soil depth in the range of 0–30 cm, and the soil moisture at the BS is 26.4% higher than the US. The soil moisture has periodic changes of 0.5a, 1a, 2a, 3a and 3.5a in the desert steppe environment of Inner Mongolia. The periodic structure and intensity of different slope positions are greatly different. Soil moisture at the US has more complex multi-scale periodic changes, and the periodic oscillations of 3.5a, 3a, and 1a are dominant. The periodic oscillations of 0.5a and 1a are dominant at the BS. At the BS, the intensity of periodic oscillation of 1a after January 2015 has weakened. The weakening of soil moisture by temperature, rainfall and soil temperature caused the change in the multiple time-scale periodic oscillation of soil moisture.

Abstract Long non-coding RNA (lncRNA) was reported to be a critical regulator of cellular homeostasis, but poorly understood in idiopathic pulmonary fibrosis (IPF). Here, we systematically identified a crucial lncRNA, p53-induced long non-coding RNA TP53 target 1 (TP53TG1), which was the dysregulated hub gene in IPF regulatory network and one of the top degree genes and down-regulated in IPF-drived fibroblasts. Functional experiments revealed that overexpression of TP53TG1 attenuated the increased expression of fibronectin 1 (Fn1), Collagen 1α1, Collagen 3α1, ACTA2 mRNA, Fn1, and Collagen I protein level, excessive fibroblasts proliferation, migration and differentiation induced by TGF-β1 in MRC-5 as well as PMLFs. In vivo assays identified that forced expression of TP53TG1 by adeno-associated virus 5 (AAV5) not only prevented BLM-induced experimental fibrosis but also reversed established lung fibrosis in the murine model. Mechanistically, TP53TG1 was found to bind to amount of tight junction proteins. Importantly, we found that TP53TG1 binds to the Myosin Heavy Chain 9 (MYH9) to inhibit its protein expression and thus the MYH9-mediated activation of fibroblasts. Collectively, we identified the TP53TG1 as a master suppressor of fibroblast activation and IPF, which could be a potential hub for targeting treatment of the disease.

Background and aimsIn the course of clinical practice, hepatic ischemia/reperfusion (I/R) injury is a prevalent pathophysiological event and is caused by a combination of complex factors that involve multiple signaling pathways such as MAPK and NF-κB. USP29 is a deubiquitinating enzyme important during the development of tumors, neurological diseases, and viral immunity. However, it is unknown how USP29 contributes to hepatic I/R injury.Methods and resultsWe systematically investigated the role of the USP29/TAK1-JNK/p38 signaling pathway in hepatic I/R injury. We first found reduced USP29 expression in both mouse hepatic I/R injury and the primary hepatocyte hypoxia-reoxygenation (H/R) models. We established USP29 full knockout mice (USP29-KO) and hepatocyte-specific USP29 transgenic mice (USP29-HTG), and we found that USP29 knockout significantly exacerbates the inflammatory infiltration and injury processes during hepatic I/R injury, whereas USP29 overexpression alleviates liver injury by decreasing the inflammatory response and inhibiting apoptosis. Mechanistically, RNA sequencing results showed the effects of USP29 on the MAPK pathway, and further studies revealed that USP29 interacts with TAK1 and inhibits its k63-linked polyubiquitination, thereby preventing the activation of TAK1 and its downstream signaling pathways. Consistently, 5z-7-Oxozeaneol, an inhibitor of TAK1, blocked the detrimental effects of USP29 knockout on H/R-induced hepatocyte injury, further confirming that USP29 plays a regulatory role in hepatic I/R injury by targeting TAK1.ConclusionOur findings imply that USP29 is a therapeutic target with promise for the management of hepatic I/R injury via TAK1-JNK/p38 pathway-dependent processes.

BackgroundHepatic ischemia-reperfusion (I/R) injury is an unavoidable pathological process that occurs after liver transplantation. However, the immune-related molecular mechanism still remains unclear. This study aims to further explore the biological mechanisms of immune-related genes in hepatic I/R injury.MethodsGene microarray data was downloaded from the Gene Expression Omnibus (GEO) expression profile database and the differentially expressed genes (DEGs) were taken for intersection. After identifying common DEGs, functional annotation, protein-protein interaction (PPI) network, and modular construction were performed. The immune-related hub genes were obtained, which their upstream transcription factors and non-RNAs were predicted. Validation of the hub genes expression and immune infiltration were performed in a mouse model of hepatic I/R injury.ResultsA total of 71 common DEGs were obtained from three datasets (GSE12720, GSE14951, GSE15480). The GO and KEGG enrichment analysis results indicated that immune and inflammatory response played an important role in hepatic I/R injury. Finally, 9 immune-related hub genes were identified by intersecting cytoHubba with immune-related genes, including SOCS3, JUND, CCL4, NFKBIA, CXCL8, ICAM1, IRF1, TNFAIP3, and JUN.ConclusionOur study revealed the importance of the immune and inflammatory response in I/R injury following liver transplantation and provided new insights into the therapeutic of hepatic I/R injury.

Abstract In the field of network security, although there has been related work on software vulnerability detection based on classic machine learning, detection ability is directly proportional to the scale of training data. A quantum neural network has been proven to solve the memory bottleneck problem of classical machine learning, so it has far-reaching prospects in the field of vulnerability detection. To fill the gap in this field, we propose a quantum neural network structure named QDENN for software vulnerability detection. This work is the first attempt to implement word embedding of vulnerability codes based on a quantum neural network, which proves the feasibility of a quantum neural network in the field of vulnerability detection. Experiments demonstrate that our proposed QDENN can effectively solve the inconsistent input length problem of quantum neural networks and the problem of batch processing with long sentences. Furthermore, it can give full play to the advantages of quantum computing and realize a vulnerability detection model at the cost of a small amount of measurement. Compared to other quantum neural networks, our proposed QDENN can achieve higher vulnerability detection accuracy. On the sub dataset with a small-scale interval, the model accuracy rate reaches 99%. On each subinterval data, the best average vulnerability detection accuracy of the model reaches 86.3%.

Background: Hepatic ischemia-reperfusion injury (HIRI) stands as an unavoidable complication arising from liver surgery, profoundly intertwined with its prognosis. The role of lysine methyltransferase SET domain bifurcated 1 (SETDB1) in HIRI remains elusive, despite its confirmation as a potential therapeutic target for diverse diseases. Here, we investigated the mechanism by which SETDB1 regulated HIRI. Methods: RNA sequencing data were used to identify the expression and potential targets of SETDB1 through bioinformatics analysis. To elucidate the impact of SETDB1 on HIRI, both an in vivo model of HIRI in mice and an in vitro model of hepatocyte hypoxia/reoxygenation were established. Biochemical and histological analyses were used to investigate the influence of SETDB1 on liver damage mediated by HIRI. Chromatin immunoprecipitation and coimmunoprecipitation were implemented to explore the in-depth mechanism of SETDB1 regulating HIRI. Results: We confirmed that hepatocellular SETDB1 was up-regulated during HIRI and had a close correlation with HIRI-related inflammation and apoptosis. Moreover, inhibition of SETDB1 could mitigate HIRI-induced liver damage, inflammation, and apoptosis. Through our comprehensive mechanistic investigation, we revealed that SETDB1 interacts with apoptosis-signal-regulating kinase 1 (ASK1) and facilitates the methylation of its lysine residues. Inhibition of SETDB1 resulted in reduced phosphorylation of ASK1, leading to a marked suppression of downstream c-Jun N-terminal kinase (JNK)/p38 signaling pathway activation. The therapeutic effect on inflammation and apoptosis achieved through SETDB1 inhibition was nullified by the restoration of JNK/p38 signaling activation through ASK1 overexpression. Conclusions: The findings from our study indicate that SETDB1 mediates lysine methylation of ASK1 and modulates the activation of the ASK1–JNK/p38 pathway, thus involved in HIRI-induced inflammation and apoptosis. These results suggest that SETDB1 holds promise as a potential therapeutic target for mitigating HIRI.

BackgroundThe 5-year survival rate for pancreatic cancer (PC) is incredibly low, resulting in this often being a fatal disease. Timely and accurate assessment of the survival rate and prognosis of patients with PC is of great significance for the development of new programs for prevention, monitoring, and treatment.MethodsPeriod analysis and further stratified analysis were used to determine the 5-year relative survival rate (RSR) of patients with PC from 2002 to 2016 using the Surveillance, Epidemiology, and End Results (SEER) project database of the National Cancer Institute. Based on this, a generalized linear model was created to predict the survival rate of patients from 2017 to 2021.ResultDuring 2002–2016, the 5-year RSR of patients with PC increased from 7.9 to 23.7%. The generalized linear model predicted that the survival rate had increased to 33.9% during 2017–2021, and hence, it was still unacceptably low. The survival rate of patients aged ≥75 years at diagnosis was the lowest among all age groups and was predicted to be only 21.4% during 2017–2021. Notably, the survival rate of patients with differentiation grade III at diagnosis remains particularly low at 7.6%.ConclusionThe survival rates of patients with PC, although slightly improved, remain extremely low. Timely assessment of the trend of survival rate changes in patients with PC further improves the prognosis of tumor patients and provides data support for relevant medical works to formulate effective tumor prevention and control policies.

H1s, or linker histones, are ubiquitous proteins in eukaryotic cells, consisting of a globular GH1 domain flanked by two unstructured tails. Whilst it is known that numerous non-allelic variants exist within the same species, the degree of interspecific and intraspecific variation and divergence of linker histones remain unknown. The conserved basic binding sites in GH1 and evenly distributed strong positive charges on the C-terminal domain (CTD) are key structural characters for linker histones to bind chromatin. Based on these features, we identified five linker histones from 13 GH1-containing proteins in castor bean (Ricinus communis), which were named as RcH1.1, RcH1.2a, RcH1.2b, RcH1.3, and RcH1.4 based on their phylogenetic relationships with the H1s from five other economically important Euphorbiaceae species (Hevea brasiliensis Jatropha curcas, Manihot esculenta Mercurialis annua, and Vernicia fordii) and Arabidopsis thaliana. The expression profiles of RcH1 genes in a variety of tissues and stresses were determined from RNA-seq data. We found three RcH1 genes (RcH1.1, RcH1.2a, and RcH1.3) were broadly expressed in all tissues, suggesting a conserved role in stabilizing and organizing the nuclear DNA. RcH1.2a and RcH1.4 was preferentially expressed in floral tissues, indicating potential involvement in floral development in castor bean. Lack of non-coding region and no expression detected in any tissue tested suggest that RcH1.2b is a pseudogene. RcH1.3 was salt stress inducible, but not induced by cold, heat and drought in our investigation. Structural comparison confirmed that GH1 domain was highly evolutionarily conserved and revealed that N- and C-terminal domains of linker histones are divergent between variants, but highly conserved between species for a given variant. Although the number of H1 genes varies between species, the number of H1 variants is relatively conserved in more closely related species (such as within the same family). Through comparison of nucleotide diversity of linker histone genes and oil-related genes, we found similar mutation rate of these two groups of genes. Using Tajima’s D and ML-HKA tests, we found RcH1.1 and RcH1.3 may be under balancing selection.

NCOA7 is a nuclear receptor coactivator that is downregulated in a variety of cancers. However, the expression and prognostic significance of NCOA7 in clear cell renal cell carcinoma (ccRCC) remain unknown. The expression of NCOA7 in ccRCC tissues was analyzed using bioinformatics analysis, Western blotting, and immunohistochemistry. Kaplan–Meier analysis, the receiver operating characteristic (ROC) curve, and clinicopathological correlation analysis were used to assess the predictive power of NCOA7. Overexpression function tests were conducted in cells and mouse models to clarify the function and mechanism of NCOA7 in inhibiting the progression of ccRCC. NCOA7 expression was downregulated in all three subtypes of renal cell carcinoma, and only had significant prognostic value for patients with ccRCC. NCOA7 overexpression inhibited the proliferation, invasion, and metastasis of ccRCC cells in vivo and in vitro. Mechanistically, NCOA7 inhibited the MAPK/ERK pathway to regulate epithelial–mesenchymal transformation (EMT) and apoptosis, thereby inhibiting the progression of ccRCC. NCOA7 inhibits tumor growth and metastasis of ccRCC through the MAPK/ERK pathway, thus indicating its potential as a prognostic marker and therapeutic target for ccRCC.

The K+ transporter KT/HAK/KUP (K+ transporter/high-affinity K+/K+ uptake) family has a critical effect on K+ uptake and translocation in plants under different environmental conditions. However, the functional analysis of KT/HAK/KUP members in sweet potatoes is still limited. The present work reported the physiological activity of a new gene, IbHAK11, in the KT/HAK/KUP family in sweet potatoes. IbHAK11 expression increased significantly in the low K+-tolerant line compared with the low K+-sensitive line following treatment with low K+ concentrations. IbHAK11 upregulation promoted root growth in Arabidopsis under low K+ conditions. Under high saline stress, transgenic lines had superior growth and photosynthetic characteristics compared with the wild-type (WT). As for IbHAK11-overexpressing plants, activation of both the non-enzymatic and enzymatic reactive oxygen species (ROS) scavenging systems was observed. Therefore, IbHAK11-overexpressing plants had lower malondialdehyde (MDA) and ROS levels (including H2O2 and O2−) compared with WT under salt-induced stress. We also found that under both low K+ and high salinity conditions, overexpression of IbHAK11 enhanced K+ translocation from the root to the shoot and decreased Na+ absorption in Arabidopsis. Consequently, IbHAK11 positively regulated K+ deficiency and high salinity stresses by regulating K+ translocation and Na+ uptake, thus maintaining K+/Na+ homeostasis in plants.

Iron walnut (Juglans sigillata Dode) is a native species in southwestern China that exhibits variation in both fruit morphology and shell thickness. However, the underlying molecular processes controlling hardened endocarp development in walnut has not yet been reported. Here, we generated transcriptional profiles of iron walnut endocarp at three developmental stages using “Dapao”, the most common commercial variety. Using pairwise comparisons between these three stages, a total of 8555 non-redundant differentially expressed genes (DEGs) were identified, and more than one-half of the total DEGs exhibited significant differential expression in stage I as compared with stage II or stage III, suggesting that the first stage may ultimately determine the final characteristics of the mature walnut shell. Furthermore, in the clustering analysis of the above DEGs, 3682, 2349, and 2388 genes exhibited the highest expression in stages I, II, and III, respectively. GO enrichment analysis demonstrated that the major transcriptional variation among the three developmental stages was caused by differences in cell growth, plant hormones, metabolic process, and phenylpropanoid metabolism. Namely, using the tissue-specific expression analysis and a gene co-expression network, we identified MADS-box transcription factor JsiFBP2 and bHLH transcription factor JsibHLH94 as candidate regulators of endocarp formation in the early stage, and JsiNAC56 and JsiMYB78 might play key roles in regulating the lignification process of endocarp in the late stage. This study provides useful information for further research to dissect the molecular mechanisms governing the shell formation and development of iron walnut.

ObjectiveThe objective of the study was to explore the effect of insulin resistance on pregnancy outcomes in patients with polycystic ovary syndrome (PCOS) from the first embryo transfer cycle.DesignThis was a single-center, retrospective, observational cohort study.PatientsIncluded in the study were women with PCOS for the first embryo transfer.Main Outcome MeasuresEarly miscarriage rate and macrosomia rate were the main outcome measures.ResultsWith increased HOMA-IR, the early miscarriage rate (7.14, 13.21, and 16.22%, respectively; P = 0.039), macrosomia rate (5.78, 11.79, and 17.58%, respectively; P = 0.026) and the incidence of gestational diabetes (GDM) (10.00, 14.50, and 25.67% respectively; P = 0.002) significantly increased, while the live birth rate markedly decreased (63.03, 55.27, and 47.88%, respectively; P = 0.004). No significant difference was found in clinical pregnancy rate, late miscarriage rate, low birthweight rate and baby gender ratio (all P >0.05). After adjusting for confounding factors, HOMA-IR was an independent risk factor of early miscarriage rate and macrosomia rate.ConclusionInsulin resistance is an independent risk factor for early miscarriage and macrosomia in PCOS patients during the first embryo transfer cycle. It is essential to give more attention before and after pregnancy for PCOS women with high HOMA-IR.

Abstract Contrary to the conventional detection method like radiography, the near infrared light source has been demonstrated to be suitable for dental imaging due to different reflectivity among enamel, dentin, and caries lesion. In this paper, three light sources with different bandwidths based on a transillumination method are compared. The contrast among enamel, dentin, and caries lesion is calculated in different situations. The experimental results show that the random fiber laser has the best comprehensive quality in dental imaging due to its high spectral density, low coherence, and deep penetration. This work provides a guidance for light source selection in dental imaging.

Ischemia–reperfusion (I/R) is a common pathological phenomenon that occurs in numerous organs and diseases. It generally results from secondary damage caused by the recovery of blood flow and reoxygenation, followed by ischemia of organ tissues, which is often accompanied by severe cellular damage and death. Currently, effective treatments for I/R injury (IRI) are limited. Ferroptosis, a new type of regulated cell death (RCD), is characterized by iron overload and iron-dependent lipid peroxidation. Mounting evidence has indicated a close relationship between ferroptosis and IRI. Ferroptosis plays a significantly detrimental role in the progression of IRI, and targeting ferroptosis may be a promising approach for treatment of IRI. Considering the substantial progress made in the study of ferroptosis in IRI, in this review, we summarize the pathological mechanisms and therapeutic targets of ferroptosis in IRI.

Neurobrucellosis is a chronic complication of human brucellosis that is caused by the presence of Brucella spp in the central nervous system (CNS) and the inflammation play a key role on the pathogenesis. Doxycycline (Dox) is a widely used antibiotic that induces apoptosis of bacteria-infected cells. However, the mechanisms of Brucella inhibition of microglial apoptosis and Dox induction of apoptosis are still poorly understood. In this study, we found that Brucella suis S2 strain (B. suis S2) increased calreticulin (CALR) protein levels and inhbited HMC3 cell apoptosis. Hence, we constructed two HMC3 cell line variants, one with stable overexpression (HMC3-CALR) and one with low expression of CALR (HMC3-sh-CALR). CALR was found to decrease levels of p-JNK and p-p53 proteins, as well as suppress apoptosis in HMC3 cells. These findings suggest that CALR suppresses apoptosis by inhibiting the JNK/p53 signaling pathway. Next, we treated HMC3, HMC3-CALR and HMC3-sh-CALR cell lines with B. suis S2 or Dox. Our results demonstrate that B. suis S2 restrains the JNK/p53 signaling pathway to inhibit HMC3 cell apoptosis via increasing CALR protein expression, while Dox plays the opposite role. Finally, we treated B. suis S2-infected HMC3 cells with Dox. Our results confirm that Dox induces JNK/p53-dependent apoptosis in B. suis S2-infected HMC3 cells through inhibition of CALR protein expression. Taken together, these results reveal that CALR and the JNK/p53 signaling pathway may serve as novel therapeutic targets for treatment of neurobrucellosis.

Bacteria play a pivotal role in shaping ecosystems and contributing to elemental cycling and energy flow in the oceans. However, few studies have focused on bacteria at a trans-basin scale, and studies across the subtropical Northwest Pacific Ocean (NWPO), one of the largest biomes on Earth, have been especially lacking. Although the recently developed high-throughput quantitative sequencing methodology can simultaneously provide information on relative abundance, quantitative abundance, and taxonomic affiliations, it has not been thoroughly evaluated. We collected surface seawater samples for high-throughput, quantitative sequencing of 16S rRNA genes on a transect across the subtropical NWPO to elucidate the distribution of bacterial taxa, patterns of their community structure, and the factors that are potentially important regulators of that structure. We used the quantitative and relative abundances of bacterial taxa to test hypotheses related to their ecology. Total 16S rRNA gene copies ranged from 1.86 × 108 to 1.14 × 109 copies L−1. Bacterial communities were distributed in distinct geographical patterns with spatially adjacent stations clustered together. Spatial considerations may be more important determinants of bacterial community structures than measured environmental variables. The quantitative and relative abundances of bacterial communities exhibited similar distribution patterns and potentially important determinants at the whole-community level, but inner-community connections and correlations with variables differed at subgroup levels. This study advanced understanding of the community structure and distribution patterns of marine bacteria as well as some potentially important determinants thereof in a subtropical oligotrophic ocean system. Results highlighted the importance of considering both the quantitative and relative abundances of members of marine bacterial communities.

The Greater Mekong River Subregion (GMS) is a global biodiversity hotspot. Macrofungi play an essential role as decomposers, parasites, and symbionts, and are also an important source of medicine, food, and income for many communities in the GMS; however, the diversity and composition of macrofungi in this region remain poorly understood. In order to help address this knowledge gap, we established 20 permanent study plots in the GMS (native forests, tea plantation, pine plantations, mixed rubber and coffee plantation). Macrofungal diversity and community composition were evaluated across four study sites classified to two climate types and two management methods. Heat maps and nonmetric multidimensional scaling (NMDS) were used to show differences in macrofungal community composition, and linear relationships were illustrated in order to analyze how environmental factors influenced macrofungal diversity and community composition. In total, 7028 specimens were collected, belonging to 1360 species, 216 genera, and 79 families. Russula, Lactarius, Amanita, Mycena, Suillus, and Inocybe were found to be the dominant genera in the GMS. We found that ectomycorrhizal fungi were dominant in temperate forests and that saprobic fungi were dominant in tropical forests. We also found that macrofungal community composition in native forests differed from that of plantation forests, indicating that plantations can provide different and complementary habitats for macrofungal growth. Our analysis of environmental factors revealed that macrofungal diversity was weakly correlated with tree species richness, and strongly correlated with elevation and latitude.

Actin filament-associated protein-120kD (AFAP-120) is an alternatively spliced isoform of actin filament-associated protein-110kD (AFAP-110) and contains an additional neuronal insert (NINS) fragment in addition to identical domains to the AFAP-110. Unlike AFAP-110 widely expressed in tissues, AFAP-120 is specifically expressed in the nervous system and plays a role in organizing dynamic actin structures during neuronal differentiation. However, anti-AFAP-120 antibody is still commercially unavailable, and this may hinder the function research for AFAP-120. In this study, we simultaneously used the ABCpred online server and the BepiPred 1.0 server to predict B-cell epitopes in the exclusive NINS sequence of human AFAP-120 protein, and found that a 16aa-peptide sequence was the consensus epitope predicted by both tools. This peptide was chemically synthesized and used as an immunogen to develop polyclonal antibody against AFAP-120 (anti-AFAP-120). The sensitivity and specificity of anti-AFAP-120 were analyzed with immunoblotting, immunoprecipitation, and immunofluorescence assays. Our results indicated that anti-AFAP-120 could react with over-expressed and endogenous human AFAP-120 protein under denatured condition, but not with human AFAP-110 protein. Moreover, native human AFAP-120 protein could also be recognized by the anti-AFAP-120 antibody. These results suggested that the prepared anit-AFAP-120 antibody would be a useful tool for studying the biochemical and biological functions of AFAP-120.