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With the advent of the era of 5G and big data, complex medical data with multiple dimensions and a large sample size bring both opportunities and challenges for clinical medicine in the new era. Compared with conventional methods, artificial intelligence can detect the hidden patterns within large datasets, and more and more scholars are applying such advanced technology in the diagnosis and treatment of diseases. After development and perfection for more than half a century, liver transplantation has become the most effective treatment method for end-stage liver diseases. Unlike the analysis of "single-patient" data in other fields, liver transplantation usually requires the consideration of the features of both the donor and the recipient and the variables during transplantation, thus generating a larger volume of medical data than other diseases, which is particularly in line with the advantages of artificial intelligence. Effective application of artificial intelligence and its combination with clinical research will usher in the new era of precision medicine. The advantages and limitations of artificial intelligence technology should be comprehensively discussed for the cross-application of artificial intelligence in liver transplantation, and the future directions of this field should also be proposed. [ABSTRACT FROM AUTHOR]

To investigate the clinical prognosis of the liver transplant recipients diagnosed with hepatocellular carcinoma (HCC) complicated with microvascular invasion (MVI). Methods Clinical data of 3 447 HCC recipients undergoing liver transplantation were extracted from Surveillance, Epidemiology, and End Results (SEER) database of American National Cancer Institute. According to the incidence of MVI, all recipients were divided into MVI (n=376) and non-MVI groups (n=3 071). The clinical prognosis of liver transplant recipients was statistically compared between two groups by analyzing the 1-, 3- and 5-year overall survival (OS) and liver cancer specific survival (LCSS). Relevant clinical data including age, gender, race, pathological staging, tumor size, lymph node metastasis, distant metastasis, tumor-node-metastasis (TNM) staging and MVI were recorded in two groups. The independent risk factors of clinical prognosis of HCC recipients undergoing liver transplantation were analyzed by multivariate Cox regression model. The nomogram for predicting the clinical prognosis of the recipients was delineated. The accuracy of the prediction model was evaluated by the consistency index. Results In the non-MVI group, the 1-, 3- , 5-year OS and LCSS were 93.5%, 82.1%, 75.3% and 98.3%, 93.8%, 90.7%, significantly higher than 88.8%, 72.1%, 68.4% and 95.3%, 83.1%, 80.4% in the MVI group (all P<0.05). Multivariate regression analysis showed that pathological staging, tumor size, lymph node metastasis, distant metastasis, TNM staging and MVI were the independent risk factors of OS and LCSS in HCC recipients undergoing liver transplantation (all P<0.05). The nomogram consistency index was calculated as 0.624 (0.602- 0.648). Conclusions MVI is an independent risk factor of the clinical prognosis of HCC recipients undergoing liver transplantation, which is significantly correlated with poor prognosis of the recipients. The nomogram based on MVI can predict the clinical prognosis of these recipients. [ABSTRACT FROM AUTHOR]

免疫耐受是指免疫系统接触抗原后所导致的特异性免疫无应答和低应答状态。 肝移植术后患者如何形成免疫耐受是移植科医师关注的问题之一， 揭示移植免疫耐受的规律可减少长期服用免疫抑制剂相关不良反应。 因此， 关于肝移植术后临床免疫耐受的研究相继展开。 筛选入组患者和临床指标的标准、 寻找免疫耐受预测指标、 发现免疫耐受机制， 是临床免疫耐受研究的主要问题。 [ABSTRACT FROM AUTHOR]

Objective To establish a non-venous bypass orthotopic liver transplantation model in Bama miniature pigs with high repeatability and stability. Methods Twelve Bama miniature pigs were randomly divided into the donor group (n=6) and recipient group (n=6). Pigs underwent non-venous bypass orthotopic liver transplantation. The time of anhepatic phase during operation was shortened, blood pressure during anhepatic phase was stably maintained, and management of anesthesia and body fluid during operation were strengthened. The operation time, anhepatic phase and survival status of the recipients were observed and recorded. The intraoperative heart rate, mean arterial pressure (MAP) and changes in arterial blood gas analysis were monitored. The perioperative liver function was evaluated. Results Among 6 Bama miniature pigs, 1 died from transplantation failure intraoperatively. The operation time of the remaining 5 pigs was (247±27) min and the time of anhepatic phase was (46±4) min. Three animals survived for more than 2 weeks. Compared with the preanhepatic phase, the heart rate of the animals was significantly faster, MAP was considerably reduced to (46±6) mmHg, blood pH value, base excess (BE) and HCO3 - level were all significantly decreased and serum level of K+ was significantly elevated during the anhepatic phase (all P<0.05). In the neohepatic phase, MAP of Bama miniature pigs was significantly increased, heart rate was dramatically slower.Blood pH value, BE, HCO3 - level were significantly increased and serum level of K+ was significantly declined (all P<0.05). During abdominal closure, MAP, blood gas indexes and serum level of K+ were almost recovered to those in the preanhepatic phase. Compared with preoperative levels, the levels of alanine aminotransferase（ALT）, aspartate aminotransferase（AST）, lactate dehydrogenase（LDH）and alkaline phosphatase（ALP）were significantly increased after operation (all P<0.05), the change in AST was the most obvious, and it gradually decreased at postoperative 2 d. The level of γ-gutamyl transferase （GGT） did not significantly elevated. The level of total bilirubin (TB) was evidently elevated at postoperative 5 d. Compared with the preoperative levels, the levels of total protein (TP) and albumin (ALB) were significantly decreased after operation (both P<0.05), and began to gradually increase at postoperative 1 d. Conclusions The non-venous bypass orthotopic liver transplantation model of Bama miniature pig is convenient, with highly reproducible and survival rate, which can be utilized as a standardized liver transplantation model. [ABSTRACT FROM AUTHOR]