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Tip leakage loss significantly influences aerodynamic performance of high-pressure turbines, with squealer tips serving as an effective control strategy. The development of a tip leakage loss model is crucial for evaluating and predicting turbine aerodynamic performance and guiding blade tip design. This study presents a novel leakage loss model for squealer tips, employing a hybrid approach that integrates physics-driven and data-driven methodologies, followed by comprehensive validation. The leakage flow within the squealer tip gap is modeled into three basic flows: Vena contracta motion in both the pressure-side and suction-side squealer tip gaps, and jet diffusion inside the cavity. The specific flow pattern and loss magnitude inside the cavity are intricately linked to the evolution of the scraping vortex. The paper introduces a methodology for modeling the scraping vortex through deep learning, grounded in the separation and reattachment theory of backstep flow. Subsequently, it presents a physical model of the leakage flow across the squealer tip gap, informed by the classical theories of three identified basic flows and the scraping vortex's behavior. The influences of complex factors that are challenging to address solely through physical modeling are also taken into consideration with the aid of machine learning. The proposed model enables a rapid and precise prediction of key flow features, such as scraping vortex characteristics, discharge coefficient, leakage flow rate and momentum, alongside total leakage flow rate and leakage loss. This model provides a reliable analytical tool for predicting leakage performance and guiding designs for the squealer tip. [ABSTRACT FROM AUTHOR]

Turbomachinery plays a vital role in energy conversion systems, with aerodynamic issues being integral to its entire lifecycle, spanning the period of design, validation, and maintenance. Conventionally, the reliance on skilled aerodynamic engineers has been pivotal in the successful development of turbomachines. However, in the current era of burgeoning artificial intelligence (AI) technology, researchers are increasingly turning to AI to replace human expertise and decision-making in these aerodynamic issues and to solve previously intractable aerodynamic problems. This paper presents a systematic literature review of the latest advancements in applying AI to turbomachinery aerodynamics, encompassing the design, validation, and maintenance of compressors and turbines. It underscores how AI is revolutionizing the research paradigm of turbomachinery aerodynamics. AI’s powerful learning capability facilitates more precise and convenient aerodynamic analyses and inspires innovative aerodynamic design ideas that go beyond the capabilities of classical design techniques. Additionally, AI’s autonomous decision-making capability can be employed for aerodynamic optimization and active flow control of turbomachines, generating optimal aerodynamic solutions and complex control strategies that surpass human brains. As a main contribution, we provide a detailed exposition of the future intelligent turbomachinery research and development (R &D) system, along with highlighting potential challenges such as physics embedding, interactive 3D design optimization, and real-time prognoses. It is anticipated that harnessing AI’s full potential will lead to a comprehensive AI-based turbomachinery R &D system in the future. [ABSTRACT FROM AUTHOR]

Liver cirrhosis remains a significant global public health concern, with liver transplantation standing as the foremost effective treatment currently available. Therefore, investigating the pathogenesis of liver cirrhosis and developing novel therapies is imperative. Mitochondrial dysfunction stands out as a pivotal factor in its development. This study aimed to elucidate the relationship between mitochondria dysfunction and liver cirrhosis using bioinformatic methods to unveil its pathogenesis. Initially, we identified 460 co-expressed differential genes (co-DEGs) from the GSE14323 and GSE25097 datasets, alongside their combined datasets. Functional analysis revealed that these co-DEGs were associated with inflammatory cytokines and cirrhosis-related signaling pathways. Utilizing weighted gene co-expression network analysis (WCGNA), we screened module genes, intersecting them with co-DEGs and oxidative stress-related mitochondrial genes. Two algorithms (least absolute shrinkage and selection operator (LASSO) regression and SVE-RFE) were then employed to further analyze the intersecting genes. Finally, COX7A1 and IFI27 emerged as identifying genes for liver cirrhosis, validated through a receiver operating characteristic (ROC) curve analysis and related experiments. Additionally, immune infiltration highlighted a strong correlation between macrophages and cirrhosis, with the identifying genes (COX7A1 and IFI27) being significantly associated with macrophages. In conclusion, our findings underscore the critical role of oxidative stress-related mitochondrial genes (COX7A1 and IFI27) in liver cirrhosis development, highlighting their association with macrophage infiltration. This study provides novel insights into understanding the pathogenesis of liver cirrhosis. [ABSTRACT FROM AUTHOR]

The PCHE has been recognized as a promising heat exchanger for hypersonic precooled aero-engines due to its superior thermal performance, high compactness and robustness. The present work focuses on the experimental thermal-hydraulic performance study of a novel zigzag microchannel PCHE. The results indicate that the pressure loss caused by friction is the main source. The Fanning correlation proposed by Moisseysev shows more precise prediction results, whose prediction deviations are within 10.0%. The measured Nu is markedly 1.24 ~ 1.94 times higher than that of the straight channel and a new Nu correlation was developed and the maximum deviations do not exceed 5%. [ABSTRACT FROM AUTHOR]

Liver fibrosis, acute liver injury or liver failure, liver tumors, and immune rejection after liver transplantation are common clinical liver diseases. Immune responses are the key to determining the prognosis of liver diseases. Liver transplantation could be the last resort for patients with liver failure. However, the use of liver transplantation is limited because of the scarcity of organ donors, immunological rejection in recipients, and high cost. Mesenchymal stem cells (MSCs) are pluripotent adult stem cells with extensive anti‐inflammatory and immunomodulation effects. MSCs can be effectively used for treating liver diseases but without the limitations that are associated with liver transplantation. Therefore, several clinical trials have utilized MSCs for the treatment of refractory liver diseases and the related mechanism is increasingly being elucidated. We have mainly summarized the recent studies that focus on the immunomodulation mechanism of MSC therapy in liver diseases. Further, we have presented our insights on the prospects of using MSCs in the treatment of liver diseases. [ABSTRACT FROM AUTHOR]

(1) Background: The aim of this study was to identify risk factors for distant metastasis of pancreatic ductal adenocarcinoma (PDAC) and develop a valid predictive model to guide clinical practice; (2) Methods: We screened 14328 PDAC patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Lasso regression analysis combined with logistic regression analysis were used to determine the independent risk factors for PDAC with distant metastasis. A nomogram predicting the risk of distant metastasis in PDAC was constructed. A receiver operating characteristic (ROC) curve and consistency-index (C-index) were used to determine the accuracy and discriminate ability of the nomogram. A calibration curve was used to assess the agreement between the predicted probability of the model and the actual probability. Additionally, decision curve analysis (DCA) and clinical influence curve were employed to assess the clinical utility of the nomogram; (3) Results: Multivariate logistic regression analysis revealed that risk factors for distant metastasis of PDAC included age, primary site, histological grade, and lymph node status. A nomogram was successfully constructed, with an area under the curve (AUC) of 0.871 for ROC and a C-index of 0.871 (95% CI: 0.860–0.882). The calibration curve showed that the predicted probability of the model was in high agreement with the actual predicted probability. The DCA and clinical influence curve showed that the model had great potential clinical utility; (4) Conclusions: The risk model established in this study has a good predictive performance and a promising potential application, which can provide personalized clinical decisions for future clinical work. [ABSTRACT FROM AUTHOR]

Liver fibrosis is a wound-healing process that occurs in response to severe injuries and is hallmarked by the excessive accumulation of extracellular matrix or scar tissues within the liver. Liver fibrosis can be either acute or chronic and is induced by a variety of hepatotoxic causes, including lipid deposition, drugs, viruses, and autoimmune reactions. In advanced fibrosis, liver cirrhosis develops, a condition for which there is no successful therapy other than liver transplantation. Although liver transplantation is still a viable option, numerous limitations limit its application, including a lack of donor organs, immune rejection, and postoperative complications. As a result, there is an immediate need for a different kind of therapeutic approach. Recent research has shown that the administration of mesenchymal stromal cells (MSCs) is an attractive treatment modality for repairing liver injury and enhancing liver regeneration. This is accomplished through the cell migration into liver sites, immunoregulation, hepatogenic differentiation, as well as paracrine mechanisms. MSCs can also release a huge variety of molecules into the extracellular environment. These molecules, which include extracellular vesicles, lipids, free nucleic acids, and soluble proteins, exert crucial roles in repairing damaged tissue. In this review, we summarize the characteristics of MSCs, representative clinical study data, and the potential mechanisms of MSCs-based strategies for attenuating liver cirrhosis. Additionally, we examine the processes that are involved in the MSCs-dependent modulation of the immune milieu in liver cirrhosis. As a result, our findings lend credence to the concept of developing a cell therapy treatment for liver cirrhosis that is premised on MSCs. MSCs can be used as a candidate therapeutic agent to lengthen the survival duration of patients with liver cirrhosis or possibly reverse the condition in the near future. [ABSTRACT FROM AUTHOR]

Mesenchymal stem cell (MSC) transplantation, as an alternative strategy to orthotopic liver transplantation, has been evaluated for treating end-stage liver disease. Although the therapeutic mechanism of MSC transplantation remains unclear, accumulating evidence has demonstrated that MSCs can regenerate tissues and self-renew to repair the liver through differentiation into hepatocyte-like cells, immune regulation, and anti-fibrotic mechanisms. Multiple clinical trials have confirmed that MSC transplantation restores liver function and alleviates liver damage. A sufficient number of MSCs must be home to the target tissues after administration for successful application. However, inefficient homing of MSCs after systemic administration is a major limitation in MSC therapy. Here, we review the mechanisms and clinical application status of MSCs in the treatment of liver disease and comprehensively summarize the molecular mechanisms of MSC homing, and various strategies for promoting MSC homing to improve the treatment of liver disease. [ABSTRACT FROM AUTHOR]

Surgical resection is the only possible cure for pancreatic cancer, it remains controversial whether extend lymphadenectomy in pancreatoduodenectomy (EPD) is better than standard lymphadenectomy in pancreatoduodenectomy (SPD). The aim of this study was to compare the efficacy of EPD with SPD for pancreatic head adenocarcinoma. A specific search of online databases including PubMed, Web of Science, Embase, and Cochrane library was conducted from January 1990 to October 2018. Relative perioperative outcomes were synthesized. Single-arm meta-analysis was also performed. A total of eight studies involving 687 (342 vs 345) patients were included for analysis in our study. The number of lymph nodes harvested [24.54 vs 13.29; weighted mean difference (WMD) −10.69, P = 0.000], operative time (469.84 min vs 354.85 min; WMD -99.09, P = 0.000), and diarrhea (postoperative three months) [45.1% vs 18.2%; odds radio (OR) 0.20, P = 0.014] were significantly higher in patients who underwent EPD than SPD. The perioperative complications (35% vs 28.8%; OR 0.79, P = 0.186), tumor size (3.27 cm vs 3.248 cm; WMD -0.11, P = 0.256), lymph node metastasis (66% vs 55.9%; OR 0.71, P = 0.105), and positive margin (10.4% vs 11.3%; OR 1.28, P = 0.392) were no significant differences between EPD group and SPD group. Extended lymphadenectomy in pancreatoduodenectomy dose not contribute to the overall survival of patients with adenocarcinoma of the pancreatic head [hazard ratio (HR) 0.95; 95% CI 0.78–1.15; P = 0.61]. The update meta-analysis shows that EPD failed to improve the overall survival, may even lead to increased morbidity. [ABSTRACT FROM AUTHOR]