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This study delved into the interplay between CD244 and Src Homology 2 Domain Containing Phosphatase-2 (SHP2) in chronic obstructive pulmonary disease (COPD) pathogenesis, focusing on apoptosis and inflammation in cigarette smoke extract (CSE)-treated human bronchial epithelial (HBE) cells. Analysis of the GSE100153 dataset identified 290 up-regulated and 344 down-regulated differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) highlighted the turquoise module had the highest correlation with COPD samples. Functional enrichment analysis linked these DEGs to critical COPD processes and pathways like neutrophil degranulation, protein kinase B activity, and diabetic cardiomyopathy. Observations on CD244 expression revealed its upregulation with increasing CSE concentrations, suggesting a dose-dependent relationship with inflammatory cytokines (IL-6, IL-8, TNF-α). CD244 knockdown mitigated CSE-induced apoptosis and inflammation, while overexpression exacerbated these responses. Co-immunoprecipitation (Co-IP) confirmed the physical interaction between CD244 and SHP2, emphasizing their regulatory connection. Analysis of Concurrently, the Nuclear Factor-kappa B (NF-κB) and Mitogen-activated protein kinase (MAPK) signaling pathways showed that modulating CD244 expression impacted key pathway components (p-JNK, p-IKKβ, p-ERK, p-P38, p-lkBα, p-P65), an effect reversed upon SHP2 knockdown. These findings underscore the pivotal role of the CD244/SHP2 axis in regulating inflammatory and apoptotic responses in CSE-exposed HBE cells, suggesting its potential as a therapeutic target in COPD treatment strategies. [ABSTRACT FROM AUTHOR]

The large-scale ingot of the 7xxx-series aluminum alloys fabricated by direct chill (DC) casting often suffers from foundry defects such as cracks and cold shut due to the formidable challenges in the precise controlling of casting parameters. In this manuscript, by using the integrated computational method combining numerical simulations with machine learning, we systematically estimated the evolution of multi-physical fields and grain structures during the solidification processes. The numerical simulation results quantified the influences of key casting parameters including pouring temperature, casting speed, primary cooling intensity, and secondary cooling water flow rate on the shape of the mushy zone, heat transport, residual stress, and grain structure of DC casting ingots. Then, based on the data of numerical simulations, we established a novel model for the relationship between casting parameters and solidification characteristics through machine learning. By comparing it with experimental measurements, the model showed reasonable accuracy in predicting the sump profile, microstructure evolution, and solidification kinetics under the complicated influences of casting parameters. The integrated computational method and predicting model could be used to efficiently and accurately determine the DC casting parameters to decrease the casting defects. [ABSTRACT FROM AUTHOR]

The precision forming process is currently used for many difficult-to-cut parts such as aero-engine blades. However, satisfying the tolerance requirement of the forming accuracy is difficult. Thus, precision machining is used to ensure final accuracy of the part. The error of the near-net shape caused by the thermal process cannot be ignored in the machining process. If the cutting tool path is generated in terms of the design blade model, it would be too difficult to satisfy the material allowance and tolerance requirement of the design blade. In this paper, we propose a new flexible localization method to reconstruct a to-be-cut surface which improves the qualification rate. In this method, the tolerance and material allowance requirements are transformed into optimization constraints. Furthermore, the profile curves of the to-be-reconstructed blade surface are converted into the optimization variables. The material allowance distribution of the to-be-reconstructed surface needs to be as uniform as possible. Through this optimization, the profile curves of the blade surface at the specified height are obtained and used to evaluate the to-be-cut blade model. Finally, a typical compressor blade model is used to verify the proposed method. The results show that the approach can meet the tolerance requirements and ensure sufficient material allowance for the near-net shape blades.

ABSTRACT The coal-fired electric utility generation industry has been identified as the largest anthropogenic source of mercury (Hg) emissions in the United States. One of the promising techniques for Hg [...]

Objective: Gastric cancer (GC) is the fifth most common malignancy, the molecular targets of which have been increasingly explored in recent years. As a serine/threonine protein kinase, the role of WNK lysine deficient protein kinase 4 (WNK4) in GC was clarified in this study., Methods: Human GC lines AGS and MKN45 were stably transfected with a WNK4 mutant constructed by the CRISPR/Cas9 method and treated with cis-dichlorodiammine platinum (CDDP, 2 μg/mL) and 5-fluorouracil (5-FU, 5 μg/mL) for 48h. Tumor-bearing mice were established with 5×10 6 mutant-type AGS cells, and injected with 40 mg/kg WP1066, the inhibitor of signal transducer and activator of transcription 3 (STAT3), for 21 days. Cell malignant potential and tumor growth were assessed. STAT3 activation was identified by western blot and immunohistochemistry. The interaction between WNK4 and STAT3 was determined using co-immunoprecipitation and immunofluorescence co-localization., Results: WNK4 mutation promoted proliferation and invasion, and upregulated the p-STAT3/STAT3 value in GC cells with/without 5-FU and CDDP treatments, while inhibiting apoptosis of GC cells without drug treatment. In tumor-bearing mice, WNK4 mutation accelerated tumor growth, increased levels of p-STAT3, STAT3, and p-STAT3/STAT3, and strengthened the co-immunoprecipitation and co-localizing with STAT3; however, these effects were reversed by WP1066 treatment., Conclusion: Through activating STAT3, WNK4 mutation impacts both the natural and drug-treated growth of GC cells or tumors, suggesting a new avenue for preclinical research., (©The Author(s) 2024. Open Access. This article is licensed under a Creative Commons CC-BY International License.)