Comprehensive Evaluation of Environmental Policy for Water Pollutants and Greenhouse Gases Reduction in Jiaxing city, China

Recently, various environmental problems have been generated with the rapid economic development in China. That’s because China currently over-emphasized economic development beyond environmental issues; therefore, now it is important to enforce optimal environmental policies in order to achieve economic development as well as environmental improvement. In this study, we selected Jiaxing city as research area for that the environmental pollution problem has become prominent with economic high growth, and we constructed environmental system model and social economic model to establish the scenarios. Through computer simulation, we can evaluate the efficiency of the comprehensive environmental policies from both environmental preservation and social economic development aspects. While the social-economic model shows the socioeconomic activities which are vital events, fortune and service, such as production, finance and budget; the environmental system model shows the water pollutants and the greenhouse gas movement in the region. The dynamic optimization simulation is accomplished based on this environmental and socio-economic system model. In view of the restriction on water pollutants, greenhouse gas total exhausted amount, and economic activity in the catchment area, the simulation we practiced can provide concrete inner-generating optimal policies which can achieve the best economic and environment improvement with the consideration of policy, regional and timing choice in Jiaxing City, China.

2-Fluoro-N′-(2-hy­droxy­benzyl­idene)benzohydrazide

In the title compound, C14H11FN2O2, an intra­molecular O—H⋯N hydrogen bond influences the mol­ecular conformation; the two benzene rings form a dihedral angle of 18.4 (3)°. The F atom is disordered over two positions in a 0.717 (5):0.283 (5) ratio. In the crystal, inter­molecular N—H⋯O hydrogen bonds link the mol­ecules into chains extending along the c axis

2-Fluoro-N′-(2-meth­oxy­benzyl­idene)benzohydrazide

The mol­ecule of the title compound, C15H13FN2O2, exists in a trans configuration with respect to the methyl­idene unit. The two benzene rings form a dihedral angle of of 64.7 (2)°. In the crystal, mol­ecules are linked through N—H⋯O hydrogen bonds into chains propagating along the c axis

Arp2/3 Complex Regulates Asymmetric Division and Cytokinesis in Mouse Oocytes

Mammalian oocyte meiotic maturation involves oocyte polarization and a unique asymmetric division, but until now, the underlying mechanisms have been poorly understood. Arp2/3 complex has been shown to regulate actin nucleation and is widely involved in a diverse range of processes such as cell locomotion, phagocytosis and the establishment of cell polarity. Whether Arp2/3 complex participates in oocyte polarization and asymmetric division is unknown. The present study investigated the expression and functions of Arp2/3 complex during mouse oocyte meiotic maturation. Immunofluorescent staining showed that the Arp2/3 complex was restricted to the cortex, with a thickened cap above the meiotic apparatus, and that this localization pattern was depended on actin. Disruption of Arp2/3 complex by a newly-found specific inhibitor CK666, as well as by Arpc2 and Arpc3 RNAi, resulted in a range of effects. These included the failure of asymmetric division, spindle migration, and the formation and completion of oocyte cytokinesis. The formation of the actin cap and cortical granule-free domain (CGFD) was also disrupted, which further confirmed the disruption of spindle migration. Our data suggest that the Arp2/3 complex probably regulates oocyte polarization through its effect on spindle migration, asymmetric division and cytokinesis during mouse oocyte meiotic maturation

A system-level mechanistic investigation of traditional Chinese medicine, Yinlai Decoction, for related diseases

Purpose: To systemically explore the pharmacological mechanisms of traditional Chinese medicine, Yinlai Decoction (YD), used in the clinical management of pediatric diseases such as pneumonia and recurrent respiratory tract infections.Methods: An ingredient-target-disease database of YD was constructed using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). First, the molecular targets related to lung and stomach diseases were searched and screened to avoid duplication. Second, the associations between these molecular targets were evaluated via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Gene Ontology (GO) and Pathway enrichment analysis in STRING.Results: A total of 627 chemical ingredients and 654 protein targets in YD were obtained. After further screening, 38 molecular targets linked to respiratory diseases, inflammatory responses and various infections were identified. Finally, 576 GO terms and 75 KEGG pathway terms were obtained by analyzing gene functional annotation clusters and abundance value of these targets. Most of these terms were closely related to the inflammatory response.Conclusion: Based on these in silico findings, the use of YD for treating respiratory diseases, inflammation and various infections, most probably via the suppression of inflammation, has been established. The approach adopted in this study can serve as a model methodology to develop an innovative TCM candidate drug at a network pharmacology level.Keywords: Yinlai Decoction, Network (System) pharmacology, Inflammation, Interacting genes/proteins, Gene ocntology, Pathway enrichment analysi

Identification of prognostic cancer-associated fibroblast markers in luminal breast cancer using weighted gene co-expression network analysis

BackgroundCancer-associated fibroblasts (CAFs) play a pivotal role in cancer progression and are known to mediate endocrine and chemotherapy resistance through paracrine signaling. Additionally, they directly influence the expression and growth dependence of ER in Luminal breast cancer (LBC). This study aims to investigate stromal CAF-related factors and develop a CAF-related classifier to predict the prognosis and therapeutic outcomes in LBC.MethodsThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to obtain mRNA expression and clinical information from 694 and 101 LBC samples, respectively. CAF infiltrations were determined by estimating the proportion of immune and cancer cells (EPIC) method, while stromal scores were calculated using the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Weighted gene co-expression network analysis (WGCNA) was used to identify stromal CAF-related genes. A CAF risk signature was developed through univariate and least absolute shrinkage and selection operator method (LASSO) Cox regression model. The Spearman test was used to evaluate the correlation between CAF risk score, CAF markers, and CAF infiltrations estimated through EPIC, xCell, microenvironment cell populations-counter (MCP-counter), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. The TIDE algorithm was further utilized to assess the response to immunotherapy. Additionally, Gene set enrichment analysis (GSEA) was applied to elucidate the molecular mechanisms underlying the findings.ResultsWe constructed a 5-gene prognostic model consisting of RIN2, THBS1, IL1R1, RAB31, and COL11A1 for CAF. Using the median CAF risk score as the cutoff, we classified LBC patients into high- and low-CAF-risk groups and found that those in the high-risk group had a significantly worse prognosis. Spearman correlation analyses demonstrated a strong positive correlation between the CAF risk score and stromal and CAF infiltrations, with the five model genes showing positive correlations with CAF markers. In addition, the TIDE analysis revealed that high-CAF-risk patients were less likely to respond to immunotherapy. Gene set enrichment analysis (GSEA) identified significant enrichment of ECM receptor interaction, regulation of actin cytoskeleton, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathway gene sets in the high-CAF-risk group patients.ConclusionThe five-gene prognostic CAF signature presented in this study was not only reliable for predicting prognosis in LBC patients, but it was also effective in estimating clinical immunotherapy response. These findings have significant clinical implications, as the signature may guide tailored anti-CAF therapy in combination with immunotherapy for LBC patients