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Hepatocellular carcinoma (HCC) is a widely prevalent and malignantly progressive tumor. Most patients are typically diagnosed with HCC at an advanced stage, posing significant challenges in the execution of curative surgical interventions. Non-coding RNAs (ncRNAs) represent a distinct category of RNA molecules not directly involved in protein synthesis. However, they possess the remarkable ability to regulate gene expression, thereby exerting significant regulatory control over cellular processes. Notably, ncRNAs have been implicated in the modulation of programmed cell death (PCD), a crucial mechanism that various therapeutic agents target in the fight against HCC. This review summarizes the clinical significance of ncRNA regulation of PCD in HCC, including patient diagnosis, prognosis, drug resistance, and side effects. The aim of this study is to provide new insights and directions for the diagnosis and drug treatment strategies of HCC.
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Traditional business process-extraction models mainly rely on structured data such as logs, which are difficult to apply to unstructured data such as images and videos, making it impossible to perform process extractions in many data scenarios. Moreover, the generated process model lacks analysis consistency of the process model, resulting in a single understanding of the process model. To solve these two problems, a method of extracting process models from videos and analyzing the consistency of process models is proposed. Video data are widely used to capture the actual performance of business operations and are key sources of business data. Video data preprocessing, action placement and recognition, predetermined models, and conformance verification are all included in a method for extracting a process model from videos and analyzing the consistency between the process model and the predefined model. Finally, the similarity was calculated using graph edit distances and adjacency relationships (GED_NAR). The experimental results showed that the process model mined from the video was better in line with how the business was actually carried out than the process model derived from the noisy process logs.
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Background: Intrahepatic cholangiocarcinoma (ICC) poses a significant clinical challenge, demanding a thorough understanding of prognostic indicators for effective patient management. Despite reports suggesting the impact of perineural invasion (PNI) on the prognosis of early-stage ICC patients, there has been a dearth of comprehensive research specifically targeting this subgroup. This study seeks to investigate the influence of PNI on survival outcomes in early-stage ICC patients and aims to enhance the prognostic value of the American Joint Committee on Cancer (AJCC) T category. Methods: A cohort of 268 early-stage (T1-T2N0M0) ICC patients, who underwent curative-intent resection (R0) between 2011 and 2015 at the Eastern Hepatobiliary Surgery Hospital, were enrolled in this study. Lasso and Cox regression analyses were employed to explore differences in clinical and prognostic data. Kaplan-Meier curves were generated to illustrate the clinical significance of the combination of PNI and T category. Results: Among the 268 patients, 24.6% exhibited PNI. Patients with PNI demonstrated shorter recurrence-free survival (RFS) [median RFS: 16 months (interquartile range, 9.5-19 months)] and overall survival (OS) [median OS: 16.53 months (interquartile range, 10-25 months)]. PNI emerged as an independent risk factor for both RFS and OS in T1- and T2-stage patients (all P<0.05), whereas tumor size was only an independent risk factor for OS (P=0.004). PNI was associated with all prognostic markers for ICC patients, including gender, jaundice, cholangitis, hepatitis B virus (HBV) infection, cancer antigen 199 (CA199), preoperative serum albumin, and preoperative platelet count (all P<0.05). However, there was no significant difference in RFS (P=0.270) and OS (P=0.360) between T2 patients without PNI and T1 patients with PNI. Conclusions: This study underscores PNI as a robust prognostic factor in early-stage ICC, emphasizing the necessity of incorporating PNI into the AJCC T category for precise risk stratification. Clinically, understanding the impact of PNI on survival outcomes can guide tailored treatment strategies for early ICC patients.
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Background: The lack of effective biomarkers for the treatment of postoperative recurrence in hepatocellular carcinoma (HCC) persists despite lenvatinib therapy. This study aims to identify beta-actin (ACTB) as a predictive biomarker for lenvatinib that can facilitate individualized treatment for HCC. Methods: This retrospective study included a subset of patients with HCC who underwent partial hepatectomy, with some receiving postoperative lenvatinib treatment and others not receiving lenvatinib treatment. A propensity score matching (PSM) analysis of patients who underwent treatment with or without lenvatinib following HCC partial hepatectomy was performed. Immunohistochemistry was employed to determine the levels of ACTB expression in HCC samples obtained from matched patients (n=225) enrolled in this study. The X-Tile was employed to determine the optimal cut-off point of ACTB levels for predicting time to recurrence (TTR). To assess the correlation between ACTB levels and lenvatinib efficacy, a subgroup analysis of TTR was conducted. A Cox regression model with an interaction term was utilized to assess the predictive significance of the model. Subsequently, a nomogram was developed and its discriminative ability and predictive accuracy were assessed using the concordance index (C-index) and calibration curve. For the investigation of the ACTB expression, HCC and para-tumoral normal tissues were employed. The patient-derived xenograft (PDX) model was utilized to validate the correlation between ACTB levels and lenvatinib responsiveness. Results: After PSM, a total of 76 patients who underwent postoperative lenvatinib treatment were included in the analysis, with a median TTR of 24.35 months. Early-stage HCC patients with lower levels of ACTB exhibited a more favorable response to lenvatinib therapy compared to those with higher levels. The reduced expression of ACTB was indicative of the benefits of lenvatinib, as opposed to higher levels {hazard ratio (HR) =0.243 [95% confidence interval (CI): 0.096-0.619], P<0.001, P value for interaction =0.014}. In approximately 81.8% of cases involving HCC patients, there was an observed increase in the expression of ACTB. Multivariate analysis of the lenvatinib cohort revealed Child-Pugh [HR =5.416 (95% CI: 1.390-21.104), P=0.015], Barcelona Clinic Liver Cancer (BCLC) stage [HR =2.508 (95% CI: 1.116-5.639), P=0.026], and ACTB [HR =5.879 (95% CI: 2.424-14.259), P<0.001] score as independent factors for TTR, and all were included in the nomogram. The survival probability based on the calibration curve showed that the prediction of the nomogram was in good agreement with the actual observation. The C-index of the nomogram for predicting survival was 0.76 (95% CI: 0.71-0.84). Moreover, the PDXs derived from tumors exhibiting low levels of ACTB expression demonstrated a heightened sensitivity to lenvatinib treatment. Conclusions: In patients with tumors treated with lenvatinib, low ACTB expression can predict a lower risk of recurrence. The validation of this potential biomarker in independent cohorts is necessary prior to its implementation for precision treatment stratification in patients undergoing partial hepatectomy for early-stage HCC.
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Cystic Echinococcosis (hydatidosis) is caused by the larval stage of Echinococcus spp. It is an animal-borne zoonotic parasitic disease with local epidemic and natural foci, which is very common in northwest China. In recent years, a considerable attention has been paid to the epidemic investigation of hydatid disease in humans and sheep, but there are few large-scale epidemic investigation and data analysis of bovine hydatid disease. We systematically reviewed and analyzed the prevalence of bovine hydatid disease (2000-2021) in China for the first time. Several databases including CNKI, Wanfang, VIP Chinese periodical database, Baidu Library, PubMed and ScienceDirect were used to search 57 articles and 72 sets of valid data about bovine hydatid disease in China from 2000 to 2021. We used the random effect model in META package of R software, and PAS for rate conversion. The subgroup analysis and univariate meta regression analysis were used to reveal the factors leading to the heterogeneity of the study. The total prevalence rate of bovine hydatid disease in China from 2000 to 2021 is estimated to be 17.27% (10898/63113). According to the analysis of sampling years, the lowest positive rate since 2016 is 7.54% (1503/19929). The highest prevalence rate of bovine hydatid disease is 53.93% (4340/8048). The infection rate of bovine liver accounted for the highest proportion of the total infections, 45.2% (2040/4507). We also assessed the effects of different geographical and climatic factors on the prevalence of bovine hydatid disease. The results showed that the prevalence rate of hydatid disease was higher in cold and humid areas. Although the infection rate of bovine hydatid disease has declined in recent years, it is still necessary to carry out long-term surveillance and control of hydatid disease, cut off the infection route and reduce the risk of infection in high-risk areas.