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Regulatory impact analysis, a crucial aspect of the development of railway transportation in China, has faced increasing challenges due to the complex nature of the transportation system and various influencing factors. This study proposes an improved comparative static model (ICSM) that intelligently integrates recursive principles and the Laplace transform to estimate the impact of macroeconomic policy reforms on the economic variables of China Railway Corporation (CRC). The ICSM integrates recursive principles and Laplace transform to solve complex conditions of eigenvalues as multiple roots and a coefficient matrix unable to diagonalize in the ICSM. Additionally, the paper discusses the government’s potential impact on variables such as freight and labor after reform and highlights the sensitivity of tax policy compared to investment subsidies in the short term. The findings provide theoretical and methodological support for optimizing railway freight management during the reform process and can serve as a reference for temporary economic policy adjustments.

Landslides cause severe damage to life and property with a wide-ranging impact. Infiltration of rainfall is one of the significant factors leading to landslides. This paper reports on a phase creep landslide caused by long-term rainfall infiltration. A detailed geological survey of the landslide was conducted, and the deformation development pattern and mechanism of the landslide were analyzed in conjunction with climatic characteristics. Furthermore, reinforcement measures specific to the landslide area were proposed. To monitor the stability of the reinforced slope, a Beidou intelligent monitoring and warning system suitable for remote mountainous areas was developed. The system utilizes LoRa Internet of Things (IoT) technology to connect various monitoring components, integrating surface displacement, deep deformation, structural internal forces, and rainfall monitoring devices into a local IoT network. A data processing unit was established on site to achieve preliminary processing and automatic handling of monitoring data. The monitoring results indicate that the reinforced slope has generally stabilized, and the improved intelligent monitoring system has been able to continuously and accurately reflect the real-time working conditions of the slope. Over the two-year monitoring period, 13 early warnings were issued, with more than 90% of the warnings accurately corresponding to actual conditions, significantly improving the accuracy of early warnings. The research findings provide valuable experience and reference for the monitoring and warning of high slopes in mountainous areas.

This study presents a novel Buyback Rail Freight Option (BRFO), leveraging Stackelberg game theory to enhance the strategic management of rail freight transactions. By integrating traditional buyback theory with a multi-phase trigeminal tree pricing model and parameter identification through a nonparametric Ito stochastic method, the research addresses key challenges of information asymmetry and market uncertainty. The proposed methodology emphasizes dynamic pricing strategies and market adaptation, constructing a Nash equilibrium framework within railway freight pricing. The findings suggest significant strategic benefits for railway enterprises, positioning BRFO as a crucial tool for improving competitiveness in the face of alternative transport options.

The unique cell wall of  Mycobacterium tuberculosis  (Mtb) creates a barrier to hydrophilic drugs, which is crucial for its survival and pathogenicity. However, the immune reactivity elicited by its components remains incompletely understood. We aimed to assess the antibody responses induced by  Mtb H37Rv  cell wall components and to develop and characterize antigen-specific polyclonal antibodies (pAbs). Rabbits were immunized with these components. Immune serum reactivity was tested against various Mtb antigens. Specific polyclonal antibodies (pAbs) were purified by affinity chromatography. The results showed that immune serum reacted with lipoarabinomannan (LAM), ESAT-6 secretion system-1 (Esx-1) secreted protein B (EspB), and Mtb8, but showed no reactivity with other tested Mtb antigens. LAM-, EspB-, or Mtb8-specific pAbs were subsequently affinity-purified. The affinity-purified LAM pAb, EspB pAb, and Mtb8 pAb each demonstrated high specificity and sensitivity, showing no cross-reactivity with non-target antigens. They recognized antigens in culture supernatants and cells from diverse mycobacterial strains, including both slow-growing mycobacteria (SGM) and rapid-growing mycobacteria (RGM). In a sandwich ELISA using LAM pAb as the capture antibody and biotinylated LAM-specific monoclonal Abs (BJRbL01-Bio, BJRbL03-Bio, BJRbL20-Bio, BJRbL52-Bio, or BJRbL76-Bio) as detection antibodies, the assay detected SGM but did not react with RGM species. EspB pAb recognized EspB in both cell lysate and culture supernatant fractions, where full-length and mature EspB are predominantly found, respectively. Mtb8 pAb reacted with monomeric and polymeric forms of Mtb8. In conclusion, we successfully generated novel pAbs against LAM, EspB, and Mtb8, providing promising research tools for investigating these critical molecules. Key points Rabbit antibodies against Mtb H37Rv cell wall components target LAM, EspB, and Mtb8 Novel LAM-, EspB-, and Mtb8-specific pAbs were generated and characterized Broad mycobacterial reactivity and specific target detection confirm pAb utility

ZC3H12A is a key RNA-binding protein and ribonuclease that plays a central role in negatively regulating inflammation and maintaining immune homeostasis. It does this by degrading the mRNA of multiple inflammatory mediators (such as IL-6 and IL-1β), as well as through its deubiquitinating enzyme activity. Not only does it limit excessive immune activation by regulating innate and adaptive immune cells (e.g., macrophages and T cells), but it also exerts bidirectional effects in tumors, acting as an anti-tumor factor to inhibit angiogenesis and oncogenic signal pathways, while promoting tumor progression under specific conditions. In recent years, ZC3H12A has emerged as a critical target for tumor immunotherapy, particularly CAR-T cell therapy. Its knockout significantly enhances T-cell persistence and anti-tumor efficacy, demonstrating broad translational potential. Furthermore, ZC3H12A plays a crucial role in systemic metabolic–immune crosstalk and infectious diseases. This review systematically summarizes the multifunctional roles of ZC3H12A in immune regulation, tumor therapy, metabolic disorders and inflammation-related diseases, with the aim of providing new insights into its potential application in the treatment of human diseases.

Elderly people and patients with comorbidities are at higher risk of COVID-19 infection, resulting in severe complications and high mortality. However, the underlying mechanisms are unclear. In this study, we investigate whether miRNAs in serum exosomes can exert antiviral functions and affect the response to COVID-19 in the elderly and people with diabetes. First, we identified four miRNAs (miR-7-5p, miR-24-3p, miR-145-5p and miR-223-3p) through high-throughput sequencing and quantitative real-time PCR analysis, that are remarkably decreased in the elderly and diabetic groups. We further demonstrated that these miRNAs, either in the exosome or in the free form, can directly inhibit S protein expression and SARS-CoV-2 replication. Serum exosomes from young people can inhibit SARS-CoV-2 replication and S protein expression, while the inhibitory effect is markedly decreased in the elderly and diabetic patients. Moreover, three out of the four circulating miRNAs are significantly increased in the serum of healthy volunteers after 8-weeks’ continuous physical exercise. Serum exosomes isolated from these volunteers also showed stronger inhibitory effects on S protein expression and SARS-CoV-2 replication. Our study demonstrates for the first time that circulating exosomal miRNAs can directly inhibit SARS-CoV-2 replication and may provide a possible explanation for the difference in response to COVID-19 between young people and the elderly or people with comorbidities.

Given the complex nature of ulcerative colitis, combination therapy targeting multiple pathogenic genes and pathways of ulcerative colitis may be required. Unfortunately, current therapeutic strategies are usually based on independent chemical compounds or monoclonal antibodies, and the full potential of combination therapy has not yet been realized for the treatment of ulcerative colitis. Here, we develop a synthetic biology strategy that integrates the naturally existing circulating system of small extracellular vesicles with artificial genetic circuits to reprogram the liver of male mice to self-assemble multiple siRNAs into secretory small extracellular vesicles and facilitate in vivo delivery siRNAs through circulating small extracellular vesicles for the combination therapy of mouse models of ulcerative colitis. Particularly, repeated injection of the multi-targeted genetic circuit designed for simultaneous inhibition of TNF-α, B7-1 and integrin α4 rapidly relieves intestinal inflammation and exerts a synergistic therapeutic effect against ulcerative colitis through suppressing the pro-inflammatory cascade in colonic macrophages, inhibiting the costimulatory signal to T cells and blocking T cell homing to sites of inflammation. More importantly, we design an AAV-driven genetic circuit to induce substantial and lasting inhibition of TNF-α, B7-1 and integrin α4 through only a single injection. Overall, this study establishes a feasible combination therapeutic strategy for ulcerative colitis, which may offer an alternative to conventional biological therapies requiring two or more independent compounds or antibodies. Management of ulcerative colitis can require a combination of treatments targeting different pathways. Here the authors design a therapy for ulcerative colitis based on a multitargeted genetic circuit to simultaneously target TNF-α, B7-1 and integrin α4, and show the therapy is effective in male mice with induced or spontaneous genetic colitis.

Predicting the status of train delays, a complex and dynamic problem, is crucial for railway enterprises and passengers. This paper proposes a novel hybrid deep learning model composed of convolutional neural networks (CNN) and temporal convolutional networks (TCN), named the CNN + TCN model, for predicting train delays in railway systems. First, we construct 3D data containing the spatiotemporal characteristics of real-world train data. Then, the CNN + TCN model employs a 3D CNN component, which is fed into the constructed 3D data to mine the spatiotemporal characteristics, and a TCN component that captures the temporal characteristics in railway operation data. Furthermore, the characteristic variables corresponding to the two components are selected. Finally, the model is evaluated by leveraging data from two railway lines in the United Kingdom. Numerical results show that the CNN + TCN model has greater accuracy and convergence performance in train delay prediction.

The cGAS-STING pathway initiates the core cascade of innate immune defense by recognizing pathogen-associated and self-derived abnormal nucleic acids, and key molecules (such as cGAS, STING, downstream IFN-β, IL-6, etc.) may serve as biomarkers in various diseases. The diverse mechanisms by which distinct nucleic acids activate this pathway provide novel insights for therapeutic strategies targeting infectious diseases, cancer, and autoimmune disorders. To prevent aberrant cGAS-STING pathway activation, cells employ multiple regulatory mechanisms, including restricting self-DNA recognition and terminating downstream signaling. Strategies to mitigate pathological activation involve reducing nucleic acid accumulation through nuclease degradation (e.g., of mitochondrial DNA or neutrophil extracellular traps, NETs) or directly inhibiting cGAS or STING. This review elucidates the molecular mechanism of nucleic acid-mediated regulation of cGAS-STING and its role in disease regulation.

The different rail transit systems, such as regional railway and urban rail transit, cooperate to form the syncretic railway network (SRN). With the rapid development of SRN, the limited transportation capacity is inadequate to meet the booming passenger flow during peak hours, where cascading failures caused by large passenger flow become a threat to SRN. This paper adopts a state equation to depict the failure‐restoration process and investigates detailed restoration strategies considering the characteristics of recoverable and repeatable failures of stations. Specifically, three different restoration strategies—spontaneous restoration strategy (SRS), active restoration strategy (ARS), and hybrid restoration strategy (HRS)—are proposed, and the varying effects of restoration time, restoration probability, restoration objective, and restoration priority for SRN with ARS are compared. These restoration strategies are applied to the actual SRN in Chengdu, where it is found that HRS has a better effect than other strategies. Furthermore, stations in the metro network with higher passenger flow allocate more restoration resources to improve the robustness of SRN, while the restoration effect of SRN increases noticeably with the restoration coefficient and the reserve coefficient. The restoration strategies presented in this paper can improve the safety management of SRN.