Background: Hepatocellular carcinomas (HCCs) occur frequently in the digestive system and are associated with high mortality. This current study examined the regulatory relationship between interleukin (IL)-1 receptor-associated kinase 1 (IRAK1), NLR family pyrin domain-containing 3 (NLRP3) inflammasomes, and tumor-associated macrophages (TAMs) in the growth and metastasis of HCC. Methods: The expression of IRAK1 and NLRP3 was assessed in tissues and cells via quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analysis. Immunohistology was performed to detect the macrophage markers CD68, CD163, and CD168 in tumor tissues. Small interfering (si)RNA targeting IRAK1 (si-IRAK1) was designed to silence IRAK1 expression. Following si-IRAK1 transfection and/or co-culture with TAMs, HCC cell viability, proliferation, migration, and invasion, as well as the expression of NLRP3 and pro-inflammatory cytokines IL-1 β, IL-18, and monocyte chemotactic protein 1 (MCP-1) were assessed. Results: HCC tissues showed elevated expression of IRAK1 and NLRP3, as well as increased expression of the macrophage markers CD68, CD163, and CD168, compared to adjacent healthy tissues. Silencing of IRAK1 expression in HepG2 and Huh7 cells resulted in suppression of cell proliferation, migration, and invasion, and also reduced expression of NLRP3 and the pro-inflammatory cytokines IL-1β, IL-18, and MCP-1. Moreover, TAMs promoted HepG2 and Huh7 cell proliferation, migration, and invasion, and elevated the expression of NLRP3, IL-1β, IL-18, and MCP-1. Furthermore, IRAK1 silencing reversed the effects of TAMs on HepG2 and Huh7 cells. Conclusions: The expression of IRAK1 was associated with HCC growth and metastasis, as well as NLRP3 inflammasome activation. The ability of TAMs to promote HCC growth and metastasis may be activated by NLRP3 inflammasomes and regulated by IRAK1.
Coronary artery disease represents a formidable health threat to middle-aged and elderly populations worldwide. This research introduces an advanced BP neural network algorithm, EPSOSA-BP, which integrates particle swarm optimization, simulated annealing, and a particle elimination mechanism to elevate the precision of heart disease prediction models. To address prior limitations in feature selection, the study employs single-hot encoding and Principal Component Analysis, thereby enhancing the model's feature learning capability. The proposed method achieved remarkable accuracy rates of 93.22% and 95.20% on the UCI and Kaggle datasets, respectively, underscoring its exceptional performance even with small sample sizes. Ablation experiments further validated the efficacy of the data preprocessing and feature selection techniques employed. Notably, the EPSOSA algorithm surpassed classical optimization algorithms in terms of convergence speed, while also demonstrating improved sensitivity and specificity. This model holds significant potential for facilitating early identification of high-risk patients, which could ultimately save lives and optimize the utilization of medical resources. Despite implementation challenges, including technical integration and data standardization, the algorithm shows promise for use in emergency settings and community health services for regular cardiac risk monitoring.
Abstract Metabolic syndrome (MetS) is associated with depression, but its role in major depressive disorder comorbid with anxiety (AMD) is unclear. This study aimed to investigate the prevalence and clinical correlates of MetS in first-episode drug-naive (FEDN) patients with AMD in a Chinese Han population. In total, 1380 FEDN outpatients with AMD were recruited in this cross-sectional study. The sociodemographic features, clinical characteristics, history of suicide attempts, thyroid-stimulating hormone (TSH) levels, and MetS parameters of each subject were evaluated. All subjects were rated on the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), and the Positive and Negative Syndrome Scale positive symptom subscale. The prevalence of MetS among AMD patients was 8.04%. Compared to the non-MetS group, age, age of onset, TSH level, HAM-A and HAM-D scores, history of attempted suicide, and comorbid psychiatric symptoms were higher in the MetS group. Those in this group were also more likely to be married, and they had a lower educational level. Furthermore, age, psychiatric symptoms, suicide attempts, and higher TSH levels were independently associated with MetS in AMD patients. This study suggests a lower prevalence of MetS in FEDN patients with AMD in a Chinese Han population. Older age, comorbid psychiatric symptoms, history of attempted suicide, and higher TSH levels are related factors for MetS in AMD patients.
Abstract Biochar application to the soil is a novel approach to carbon sequestration. Biochar application affects the emission of greenhouse gases (GHGs), such as CO 2 , CH 4 , and N 2 O, from different environments (e.g., upland soils, rice paddies and wetlands, and composting environments). In this review, the effect of biochar on GHGs emissions from the above three typical environments are critically evaluated based on a literature analysis. First, the properties of biochar and engineered biochar related to GHGs emissions was reviewed, targeting its relationship with climate change mitigation. Then, a meta‐analysis was conducted to assess the effect of biochar on the emissions of CO 2 , CH 4 , and N 2 O in different environments, and the relevant mechanisms. Several parameters were identified as the main influencing factors in the meta‐analysis, including the pH of the biochar, feedstock type, pyrolysis temperature, biochar application rate, C/N ratio of the biochar, and experimental scale. An overall suppression effect among different environments was found, in the following order for different greenhouse gases: N 2 O > CH 4 > CO 2 . We conclude that biochar can change the physicochemical properties of soil and compost in different environments, which further shapes the microbial community in a specific environment. Biochar addition affects CO 2 emissions by influencing oligotrophic and copiotrophic bacteria; CH 4 emissions by regulating the abundance of functional genes, such as mcrA (a methanogen) and pmoA (a methanotroph); and N 2 O emissions by controlling N‐cycling functional genes, including amoA , nirS , nirK , nosZ . Finally, future research directions for mitigating greenhouse gas emissions through biochar application are suggested.
Background The aim of this study is to find the potential survival related DNA methylation signature capable of predicting survival time for acute myelocytic leukemia (AML) patients. Methods DNA methylation data were downloaded. DNA methylation signature was identified in the training group, and subsequently validated in an independent validation group. The overall survival of DNA methylation signature was performed. Functional analysis was used to explore the function of corresponding genes of DNA methylation signature. Differentially methylated sites and CpG islands were also identified in poor-risk group. Results A DNA methylation signature involving 8 DNA methylation sites and 6 genes were identified. Functional analysis showed that protein binding and cytoplasm were the only two enriched Gene Ontology terms. A total of 70 differentially methylated sites and 6 differentially methylated CpG islands were identified in poor-risk group. Conclusions The identified survival related DNA methylation signature adds to the prognostic value of AML.
Digital filter plays an important role in the digital signal processing, with a wide range of theoretical and practical application. The essential characteristic of the digital filter is that it can make the useful signal as much as possible all go through, while maximally suppress the useless signal. Due to the structure and function of digital filter, the classical filter design methods will suffer from some shortcomings: slow convergence and local minimums. To overcome the shortcomings in FIR filter design, a novel P systems-based method for optimal FIR filter design under the framework of P system is proposed by combining parallel property of P system, which is named as Tissue P Systems algorithm (TPS). In the proposed TPS model, instead of traditional design methods, a star tissue P system is designed as its computing framework, while the impulse response coefficients of the filter are regarded as the objects in the elementary membranes. Each object in cells expresses a group of filter coefficients to be optimized by using velocity-position model of PSO, and inherent communication mechanism is used to share the objects among different elementary membranes, so as to determine the optimal filter parameters. Low-pass filter (LP), high-pass filter (HP), band-pass filter (BP) and band-stop filter (BS) are employed to verify the effectiveness of the proposed method. Five state-of-the-art design methods, which are Parks-McClellan (PM), real-coded GA (RGA), particle swarm optimization (PSO), differential evolution (DE) and opposition-based harmony search (OHS) are used to exhibit the advantages of the proposed framework. The comparison results demonstrate the proposed TPS model that obtains better performance regarding magnitude response, with minimum stopband ripple, and maximum stopband attenuation. Moreover, the simulation results also show that the proposed FIR filter can close the requirements of ideal filter to the maximum extent.
(3Z,9Z,6S,7R)-6,7-epoxy-3,9-octadecadiene (1) and (3Z,9Z,6R,7S)-6,7-epoxy-3,9-octadecadiene (2) have been stereoselectively synthesized in eight steps from 2-pentyn-1-ol with an overall yield of 8%. The key steps involved the Sharpless asymmetric dihydroxylation of (2E)-oct-2-en-5-yn-1-ol (6). The new synthetic method is suitable for multigram-scale preparation of 1 and 2 and might be used for producing sufficient quantities of the sex pheromone components for management of the pest of tea plantations.
Olanzapine-induced metabolic disorders have been increasingly concerned.However,the mechanism is still unknown.The establishment of an appropriate animal model to explore the mechanism is a most important way,and the stability and reproducibility of an animal model are of vital importance.In this paper,the studies on establishment of Olanzapine-induced metabolic disorder animal models are reviewed,and the influencing factors of the reproducibility of animal models are discussed,hoping to provide reference for the related research.
Pseudomonas aeruginosa PAO1 is a Gram-negative, opportunistic bacterial human pathogen which infects immunocompromised individuals.The bacterium carries a type III secretion system (T3SS) as a major virulence determinant.The strategy of T3SS inhibitors is to prevent the bacterium from injecting effector proteins into the host, and causing a change in the pathophysiology of the host cells.Based on the structure of a known T3SS inhibitor of P. aeruginosa, 20 new α-phenoxyacetamide derivatives have been designed and synthesized, and the structure-activity relationship results for these new derivatives have been discussed.Five derivatives have shown strong inhibitory effect against exoS gene expression of P. aeruginosa, and among them, N-(2-pyridylmethyl)-2-(2,4-dichlorophenoxy)-butanamide (5r) has not only exhibited stronger potency than the known T3SS inhibitor, but also better solubility in aqueous solution.
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