ObjectiveTo screen long non-coding RNAs (lncRNAs) relevant to programmed cell death (PCD) and construct a nomogram model predicting prognosis of hepatocellular carcinoma (HCC). MethodsThe HCC patients selected from The Cancer Genome Atlas (TCGA) were randomly divided into training set and validation set according to 1∶1 sampling. The lncRNAs relevant to PCD were screened by Pearson correlation analysis, and which associated with overall survival in the training set were screened by univariate Cox proportional hazards regression (abbreviation as “Cox regression”), and then multivariate Cox regression was further used to analyze the prognostic risk factors of HCC patients, and the risk score function model was constructed. According to the median risk score of HCC patients in the training set, the HCC patients in each set were assigned into a high-risk and low-risk, and then the Kaplan-Meier method was used to draw the overall survival curve, and the log-rank test was used to compare the survival between the HCC patients with high-risk and low-risk. At the same time, the area under receiver operating characteristic curve (AUC) was used to evaluate the value of the risk score function model in predicting the 1-, 3-, and 5-year overall survival rates of HCC patients in the training set, validation set, and integral set. Then the nomogram was constructed based on the risk score function model and factors validated in clinic, and its predictive ability for the prognosis of HCC patients was evaluated. ResultsA total of 374 patients with HCC were downloaded from the TCGA, of which 342 had complete clinicopathologic data, including 171 in the training set and 171 in the validation set. Finally, 8 lncRNAs genes relevant to prognosis (AC099850.3, LINC00942, AC040970.1, AC022613.1, AC009403.1, AL355974.2, AC015908.3, AC009283.1) were screened out, and the prognostic risk score function model was established as follows: prognostic risk score=exp1×β1+exp2×β2...+expi×βi (expi was the expression level of target lncRNA, βi was the coefficient of multivariate Cox regression analysis of target lncRNA). According to this prognostic risk score function model, the median risk score was 0.89 in the training set. The patients with low-risk and high-risk were 86 and 85, 86 and 85, 172 and 170 in the training set, validation set, and integral set, respectively. The overall survival curves of HCC patients with low-risk drawn by Kaplan-Meier method were better than those of the HCC patients with high-risk in the training set, validation set, and integral set (P<0.001). The AUCs of the prognostic risk score function model for predicting the 1-, 3-, and 5-year overall survival rates in the training set were 0.814, 0.768, and 0.811, respectively, in the validation set were 0.799, 0.684, and 0.748, respectively, and in the integral set were 0.807, 0.732, and 0.784, respectively. The multivariate Cox regression analysis showed that the prognostic risk score function model was a risk factor affecting the overall survival of patients with HCC [<0.89 points as a reference, RR=1.217, 95%CI (1.151, 1.286), P<0.001]. The AUC (95%CI) of the prognostic risk score function model for predicting the overall survival rate of HCC patients was 0.822 (0.796, 0.873). The AUCs of the nomogram constructed by the prognostic risk score function model in combination with clinicopathologic factors to predict the 1-, 3-, and 5-year overall survival rates were 0.843, 0.839, and 0.834. The calibration curves of the nomogram of 1-, 3-, and 5-year overall survival rates in the training set were close to ideal curve, suggesting that the predicted overall survival rate by the nomogram was more consistent with the actual overall survival rate. ConclusionThe prognostic risk score function model constructed by the lncRNAs relevant to PCD in this study may be a potential marker of prognosis of the patients with HCC, and the nomogram constructed by this model is more effective in predicting the prognosis (overall survival) of patients with HCC.
Subject recruitment is a key component that affects the progress and results of clinical trials, and generally conducted with eligibility criteria (includes inclusion criteria and exclusion criteria). The semantic category analysis of eligibility criteria can help optimizing clinical trials design and building automated patient recruitment system. This study explored the automatic semantic categories classification of Chinese eligibility criteria based on artificial intelligence by academic shared task. We totally collected 38 341 annotated eligibility criteria sentences and predefined 44 semantic categories. A total of 75 teams participated in competition, with 27 teams having submitted system outputs. Based on the results, we found out that most teams adopted mixed models. The mainstream resolution was applying pre-trained language models capable of providing rich semantic representation, which were combined with neural network models and used to fine-tune the models with reference to classifier tasks, and finally improved classification performance could be obtained by ensemble modeling. The best-performing system achieved a macro F1 score of 0.81 by using a pre-trained language model, i.e. bidirectional encoder representations from transformers (BERT) and ensemble modeling. With the error analysis we found out that from the point of data processing steps the data pre-processing and post-processing were very important for classification, while from the point of data volume these categories with less data volume showed lower classification performance. Finally, we hope that this study could provide a valuable dataset and state-of-the-art result for the research of Chinese medical short text classification.
The fundamental reason why the organic lesions of chronic heart failure are difficult to reverse is ventricular remodeling. Myocardial fibrosis (MF) is an important pathological basis of ventricular remodeling. Its development process involves complex biological mechanisms and neuroendocrine system. Extracellular signal-regulated kinase (ERK) pathway is a classic pathway for the treatment of tumors. It is found that the inhibition of the ERK pathway can also slow down the progressive aggravation of MF. Therefore, exploring the mechanism of ERK pathway in MF may provide a new idea for the prevention and treatment of chronic heart failure. In this paper, the mechanism of ERK pathway in the occurrence and development of MF and its inhibition drugs were described, in order to provide evidence for the prevention and treatment of MF in chronic heart failure based on this pathway.
ObjectiveTo investigate the voice function before and after surgery in patients undergoing axillary thyroidectomy with da Vinci robotic Xi system. MethodsSeventy female patients who underwent robotic thyroid cancer radical resection in Panzhihua Central Hospital from March 2022 to March 2023 were selected. The voice dysfunction index scale VHI-10, auditory perception evaluation scale GRBAS and voice analysis software were used to evaluate the voice function of patients subjectively and objectively at 1 day before operation, 1 week and 3 months after surgery. ResultsThe operative time was (128.13±48.36) min, the amount of blood loss was (16.36±8.23) mL. There were no significant differences in the points of function, physiology and emotion evaluated by VHI-10 scale at 1 week and 3 months after operation compared with those before operation (P>0.05). There were no significant differences in the three characteristics points of voice roughness, breathiness, and strain evaluated by GRBAS scale at 1 week and 3 months after operation (P>0.05). At 1 week after operation, the total hoarseness grade and asthenia evaluated by GRBAS scale were increased in different degrees as compared with those before operation and the difference was statistically significant (P<0.05), while the total hoarseness grade and asthenia points were decreased at 3 months after operation and there was no significant difference as compared with that before operation (P>0.05). Voice acoustic analysis results showed that there were no significant differences in fundamental frequency, jitter, shimmer and harmonic to noise ratio of the patients between at 1 week or 3 months after operation and before operation (P>0.05). The maximum phonation time (MPT) of patients was decreased at 1 week after operation as compared with that before operation, and the difference was statistically significant (P<0.05). The MPT of the patients recovered at 3 months after operation, and there was no significant difference as compared with that before operation (P>0.05). The dysphonia severity index (DSI) of patients at 1 week after surgery was decreased as compared with that before surgery, and the difference was statistically significant (P<0.05). The DSI was increased at 3 months after operation and there was no significant difference as compared with that before operation (P>0.05). ConclusionRobot radical thyroidectomy via axillary breast is safe and can protect the voice function.