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The open question, which seems to be also the final part, in terms of studying the Cauchy problem for the weakly coupled system of semilinear damped wave equations or reaction–diffusion equations, is so far known as the sharp lifespan estimates in the critical case. In this paper, we mainly investigate lifespan estimates for solutions to the weakly coupled system of semilinear damped wave equations in the critical case. By using a suitable test function method associated with nonlinear differential inequalities, we catch upper bound estimates for the lifespan. Moreover, we establish polynomial-logarithmic type time-weighted Sobolev spaces to obtain lower bound estimates for the lifespan in low spatial dimensions. Then, together with the derived lifespan estimates, new and sharp results on estimates for the lifespan in the critical case are claimed. Finally, we give an application of our results to the semilinear reaction–diffusion system in the critical case.

Focus on the shortage of Leymus chinensis seeds’ discrete element parameters in the research of the seeds in production equipment, the study carried out parameter calibration and verification. The focus of this study is on the shortage of discrete element parameters for Leymus chinensis seeds in research related to seed production equipment. The study involved parameter calibration and verification. First, the physical property parameters of the seeds were measured through physical experiments to determine the range of the simulation parameters. Using Response Surface Methodology, a simulation accumulation test was conducted. Subsequently, the simulation parameters were calibrated and optimized. Specifically, significant parameters affecting the repose angle were identified using the Plackett–Burman Design test. The optimal value range of these parameters was then determined through a steepest slope climbing test. A second-order regression model between the significant parameters and the simulated stacking angle was established through the Box–Behnken Design experiment. The regression model was optimized by using the repose angle from the physical test as the target value. The obtained optimal parameter combination was then used to conduct a simulation test. The results showed that the relative error between the simulation and physical test was only 0.94%. This proves the accuracy, reliability, and authenticity of the simulated contact parameters. The study provides a theoretical basis for the optimization design and simulation research of Leymus chinensis seeds harvesting technology and equipment.

Recent advances highlight the pivotal role of nicotinamide adenine dinucleotide (NAD + ) in ovarian aging. However, the roles of de novo NAD + biosynthesis on ovarian aging are still unknown. Here, we found that genetic ablation of Ido1 (indoleamine‐2,3‐dioxygenase 1) or Qprt (Quinolinate phosphoribosyl transferase), two critical genes in de novo NAD + biosynthesis, resulted in decreased ovarian NAD + levels in middle‐aged mice, leading to subfertility, irregular estrous cycles, reduced ovarian reserve, and accelerated aging. Moreover, we observed impaired oocyte quality, characterized by increased reactive oxygen species and spindle anomalies, which ultimately led to reduced fertilization ability and impaired early embryonic development. A transcriptomic analysis of ovaries in both mutant and wild‐type mice revealed alterations in gene expression related to mitochondrial metabolism. Our findings were further supported by the observation of impaired mitochondrial distribution and decreased mitochondrial membrane potential in the oocytes of knockout mice. Supplementation with nicotinamide riboside (NR), an NAD + booster, in mutant mice increased ovarian reserve and improved oocyte quality. Our study highlights the importance of the NAD + de novo pathway in middle‐aged female fertility.

Polycystic ovary syndrome (PCOS) is a complex endocrine metabolic disorder that affects 5–10% of women of reproductive age. The endometrium of women with PCOS has altered immune cells resulting in chronic low-grade inflammation, which attribute to recurrent implantation failure (RIF). In this study, we obtained three PCOS and RIF datasets respectively from the Gene Expression Omnibus (GEO) database. By analyzing differentially expressed genes (DEGs) and module genes using weighted gene co-expression networks (WGCNA), functional enrichment analysis, and three machine learning algorithms, we identified twelve diseases shared genes, and two diagnostic genes, including GLIPR1 and MAMLD1. PCOS and RIF validation datasets were assessed using the receiver operating characteristic (ROC) curve, and ideal area under the curve (AUC) values were obtained for each disease. Besides, we collected granulosa cells from healthy and PCOS infertile women, and endometrial tissues of healthy and RIF patients. RT-PCR was used to validate the reliability of GLIPR1 and MAMLD1. Furthermore, we performed gene set enrichment analysis (GSEA) and immune infiltration to explore the underlying mechanism of PCOS and RIF cooccurrence. Through the functional enrichment of twelve shared genes and two diagnostic genes, we found that both PCOS and RIF patients had disturbances in metabolites related to the TCA cycle, which eventually led to the massive activation of immune cells.

The gut microbiota plays an important role in the development of nonalcoholic steatohepatitis (NASH). This study investigated the preventive effect of (DO), including whether its effect was related to the gut microbiota, intestinal permeability and liver inflammation. A NASH model was established in rats using a high-fat diet (HFD) and gavage with different doses of DO or Atorvastatin Calcium (AT) for 10 weeks. Body weight and body mass index along with liver appearance, weight, index, pathology, and biochemistry were measured to assess the preventive effects of DO on NASH rats. Changes in the gut microbiota were analyzed by 16S rRNA sequencing, and intestinal permeability and liver inflammation were determined to explore the mechanism by which DO treatment prevented NASH. Pathological and biochemical indexes showed that DO was able to protect rats against HFD-induced hepatic steatosis and inflammation. Results of 16S rRNA sequencing showed that Proteobacteria, , and differed significantly at the phylum, genus, and species levels. DO treatment modulated the diversity, richness, and evenness of gut microbiota, downregulated the abundance of the Gram-negative bacteria Proteobacteria, , and , and reduced gut-derived lipopolysaccharide (LPS) levels. DO also restored expression of the tight junction proteins, zona occludens-1 (ZO-1), claudin-1, and occludin in the intestine and ameliorated the increased intestinal permeability caused by HFD, gut microbiota such as , , , and , and LPS. Lower intestinal permeability reduced LPS delivery to the liver, thus inhibiting TLR4 expression and nuclear factor-kappaB (NF-κB) nuclear translocation, improving liver inflammation. These results suggest that DO may alleviate NASH by regulating the gut microbiota, intestinal permeability, and liver inflammation.

As an indispensable part of the power system, transformers need to be continuously monitored to detect anomalies or faults in a timely manner to avoid serious damage to the power grid and society. This article proposes a combined model for transformer state prediction, which integrates gas concentration prediction and fault diagnosis models. First, based on the historical monitoring data, each characteristic gas sequence is subjected to one optimal variational mode decomposition (OVMD) and one complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). The decomposed sub-sequences are input into a bi-directional long short-term memory network (Bi-LSTM) optimized by the sparrow search algorithm (SSA) for prediction, and the predicted value of each sub-sequence was then superimposed to be the predicted value of the characteristic gas. We input the predicted values of each gas into the improved sparrow search algorithm-optimized support vector machine (ISSA-SVM) model, which can output the final fault type. After the construction of the combined model of state prediction is completed, this paper uses three actual cases to test the model, and at the same time, it uses the traditional fault diagnosis methods to judge the cases and compare these methods with the model in this paper. The results show that the combined model of transformer state prediction constructed in this paper is able to predict the type of transformer faults in the future effectively, and it is of great significance for the practical application of transformer fault type diagnosis.

As a traditional Chinese medicine, Salvia miltiorrhiza Bunge was first recorded in the Shennong Materia Medica Classic and is widely used to treat “the accumulation of symptoms and masses”. The main active ingredient of Salvia miltiorrhiza Bunge, Tanshinone IIA (TIIA), has shown anti-inflammatory, antitumor, antifibrosis, antibacterial, and antioxidative activities, etc. In this study, the results showed that TIIA could inhibit the proliferation and migration of HepG2 cells and downregulate glutathione (GSH) and Glutathione Peroxidase 4 (GPX4) levels; besides, TIIA induced the production of Reactive Oxygen Species (ROS), and upregulated the total iron content. Based on network pharmacology analysis, the antitumor effect of TIIA was found to be focused on the endoplasmic reticulum (ER)-mediated ferroptosis signaling pathway, with protein kinase R (PKR)-like ER kinase (PERK)-activating transcription factor 4 (ATF4)-heat shock 70 kDa protein 5 (HSPA5) as the main pathway. Herein, TIIA showed typical ferroptosis characteristics, and a ferroptosis inhibitor (ferrostatin-1) was used to verify the effect. The antitumor effects of TIIA, occurring through the inhibition of the PERK-ATF4-HSPA5 pathway, were further observed in vivo as significantly inhibited tumor growth and the improved pathological morphology of tumor tissue in H22-bearing mice. In summary, the antitumor mechanism of TIIA might be related to the downregulation of the activation of PERK-ATF4-HSPA5 pathway-mediated ferroptosis.

In the classical theory of acoustic waves, Blackstock’s model was proposed in 1963 to characterize the propagation of sound in thermoviscous fluids. In this paper, we investigate large-time asymptotic behaviors of the linear Cauchy problem for general Blackstock’s model (that is, without Becker’s assumption on monatomic perfect gases). We derive first and second asymptotic profiles of solution as t≫1 by applying refined WKB analysis and Fourier analysis. Our results not only improve optimal estimates in Chen et al. (Indiana Univ Math J 72(2), 2023) for lower dimensional cases, but also illustrate the optimal leading term and novel second profiles of solution with additional weighted L1 data.

Iron levels play a crucial role in fruit quality and long-term productivity in peach orchards. Traditional diagnostic techniques, while effective, are often costly, time-consuming, and reliant on expert intervention. In response to these limitations, this study introduces a novel and cost-efficient methodology for assessing iron status in peach trees in the Pinggu region of China. The proposed approach combines digital imaging and artificial neural networks (ANN) to improve the accuracy of leaf iron evaluation. A total of 832 leaf samples were collected, and their active iron content (Fe²⁺) was measured using standard laboratory procedures. High-resolution leaf images were captured and analyzed across RGB, HSV, and CIE Lab color spaces. Feature extraction and dimensionality reduction were performed using Principal Component Analysis (PCA), and classification of iron levels was conducted using a k-nearest neighbors (KNN) algorithm within a PCA-optimized ANN framework. The resulting model, leveraging six principal components, achieved an overall classification accuracy of 86.7%, with precision, recall, and F1-scores exceeding 86.5% for all classes. Receiver Operating Characteristic (ROC) curve analysis further confirmed the robustness of the model. Moderate iron levels were more prone to misclassification, typically confused with either low or severe levels, highlighting the challenge of moderate differentiation. These results suggest that the proposed framework has considerable potential for evaluating iron status in peach leaves and may serve as a cost-effective and scalable approach for supporting precision agriculture practices.

Acute kidney injury (AKI) is a common and serious complication following lung transplantation (LTx), and it is associated with high mortality and morbidity. This study assessed the incidence of AKI after LTx and analyzed the associated perioperative factors and clinical outcomes. This retrospective study included all adult LTx recipients at the China-Japan Friendship Hospital in Beijing between March 2017 and December 2019. The outcomes were AKI incidence, risk factors, mortality, and kidney recovery. Multivariate analysis was performed to identify independent risk factors. Survival analysis was presented using the Kaplan-Meier curves. AKI occurred in 137 of the 191 patients (71.7%), with transient AKI in 43 (22.5%) and persistent AKI in 94 (49.2%). AKI stage 1 occurred in 27/191 (14.1%), stage 2 in 46/191 (24.1%), and stage 3 in 64/191 (33.5%) of the AKI patients. Renal replacement therapy (RRT) was administered to 35/191 (18.3%) of the patients. Male sex, older age, mechanical ventilation (MV), severe hypotension, septic shock, multiple organ dysfunction (MODS), prolonged extracorporeal membrane oxygenation (ECMO), reintubation, and nephrotoxic agents were associated with AKI (P < 0.050). Persistent AKI was independently associated with pre-operative pulmonary hypertension, severe hypotension, post-operative MODS, and nephrotoxic agents. Severe hypotension, septic shock, MODS, reintubation, prolonged MV, and ECMO during or after LTx were related to severe AKI (stage 3) (P < 0.050). Patients with persistent and severe AKI had a significantly longer duration of MV, longer duration in the intensive care unit (ICU), worse downstream kidney function, and reduced survival (P < 0.050). AKI is common after LTx, but the pathogenic mechanism of AKI is complicated, and prerenal causes are important. Persistent and severe AKI were associated with poor short- and long-term kidney function and reduced survival in LTx patients.