A comprehensive evaluation of full-spectrum cell-free RNAs highlights cell-free RNA fragments for early-stage hepatocellular carcinoma detection.

BACKGROUND: Various studies have reported cell-free RNAs (cfRNAs) as noninvasive biomarkers for detecting hepatocellular carcinoma (HCC). However, they have not been independently validated, and some results are contradictory. We provided a comprehensive evaluation of various types of cfRNA biomarkers and a full mining of the biomarker potential of new features of cfRNA. METHODS: We first systematically reviewed reported cfRNA biomarkers and calculated dysregulated post-transcriptional events and cfRNA fragments. In 3 independent multicentre cohorts, we further selected 6 cfRNAs using RT-qPCR, built a panel called HCCMDP with AFP using machine learning, and internally and externally validated HCCMDP's performance. FINDINGS: We identified 23 cfRNA biomarker candidates from a systematic review and analysis of 5 cfRNA-seq datasets. Notably, we defined the cfRNA domain to describe cfRNA fragments systematically. In the verification cohort (n = 183), cfRNA fragments were more likely to be verified, while circRNA and chimeric RNA candidates were neither abundant nor stable as qPCR-based biomarkers. In the algorithm development cohort (n = 287), we build and test the panel HCCMDP with 6 cfRNA markers and AFP. In the independent validation cohort (n = 171), HCCMDP can distinguish HCC patients from control groups (all: AUC = 0.925; CHB: AUC = 0.909; LC: AUC = 0.916), and performs well in distinguishing early-stage HCC patients (all: AUC = 0.936; CHB: AUC = 0.917; LC: AUC = 0.928). INTERPRETATION: This study comprehensively evaluated full-spectrum cfRNA biomarker types for HCC detection, highlighted the cfRNA fragment as a promising biomarker type in HCC detection, and provided a panel HCCMDP. FUNDING: National Natural Science Foundation of China, and The National Key Basic Research Program (973 program).

Identification of necroptosis-related genes as prognostic indicators for lower-grade glioma.

The purpose of this research is to develop a predictive model based on necroptosis-related genes to predict the prognosis and survival of lower grade gliomas (LGGs) efficiently. To achieve this goal, we searched for differentially expressed necrotizing apoptosis-related genes using the TCGA and CGGA databases. To construct a prognostic model, LASSO Cox and COX regression analyses were conducted on the differentially expressed genes. In this study, three genes were used to develop a prognostic model of necrotizing apoptosis, and all samples were split into high- and low-risk groups. We observed that patients with a high-risk score had a worse overall survival rate (OS) than those with a low-risk score. In the TCGA and CGGA cohorts, the nomogram plot showed a high capacity to predict overall survival of LGG patients. GSEA analysis revealed that the high-risk group was enriched for inflammatory responses, tumor-related pathways, and pathological processes. Additionally, the high-risk score was associated with invading immune cell expression. In conclusion, our predictive model based on necroptosis-related genes in LGG was shown to be effective in the diagnosis and could predict the prognosis of LGG. In addition, we identified possible targets related to necroptosis-related genes for glioma therapy in this study.

Effect of Xiaoyutang Combined with Intraperitoneal Heat Perfusion Chemotherapy on Immune Function, Circulating mir, Prognosis, and Survival of Postoperative Patients with Colorectal Cancer.

OBJECTIVE: To explore the effects of Xiaoyutang combined with intraperitoneal heat perfusion chemotherapy on immune function, circulating Mir, and prognosis and survival of postoperative patients with colorectal cancer. METHODS: A total of 96 patients with colorectal cancer who were treated in our hospital from May 2018 to August 2019 and followed up to August 2021 were selected as the study subjects. The patients were randomly divided into a control group and study group by a 1 : 1 random number table method, 48 cases in each group. Patients in the control group were given intraperitoneal thermal perfusion chemotherapy after surgery, and patients in the research group were treated with Xiaoyutang on this basis. The treatment cycle was 21 days, and all patients were treated for 3 consecutive cycles. The therapeutic efficacy, immune function (CD3+, CD4+, and CD4+/CD8+), circulating mir (mir-29a, mir-145, and mir-92a), prognosis, and survival of the two groups were compared. RESULTS: After 3 cycles of treatment, ORR and DCR in the study group were higher than those in the control group (60.42% vs. 37.50%) and 85.42% vs. 66.67%, respectively, with statistical significance (P < 0.05). There were statistically significant differences in CD3+, CD4+, CD4+/CD8+, mir-29a, mir-145, and mir-92a time points and intergroup and intergroup interactions between the two groups (P < 0.05); the levels of CD3+, CD4+, and CD4+/CD8+ in the study group were higher than those in the control group after 1, 2, and 3 cycles of treatment (P < 0.05); the expressions of mir-29a, mir-145, and mir-92a were significantly lower than those in the control group (P < 0.05). By the end of follow-up, 3 cases were lost to follow-up in the study group and 5 cases in the control group. The recurrence rate and mortality of the study group were lower than those of the control group at 1- and 2-year follow-up (P > 0.05), and the mean survival time of patients in the study group was higher than that in the control group; the differences were statistically significant (χ 2 = 5.151, P = 0.023). CONCLUSION: Xiaoyutang combined with peritoneal heat perfusion chemotherapy has a good postoperative effect on patients with colorectal cancer, which can effectively improve the immune function and circulating Mir of patients with colorectal cancer, reduce tumor recurrence, and improve the prognosis of patients.

Hepatitis B virus core antigen mutations predict post-operative prognosis of patients with primary hepatocellular carcinoma.

The aim of this study was to explore the relationship between hepatitis B virus (HBV) core antigen (HBc) mutations and the post-operative prognosis of HBV-related hepatocellular carcinoma (HCC). In total, 98 patients suffering from HBV-related HCC and treated with surgery were enrolled, with a 48 month follow-up. The preCore/Core region of the HBV genome from tumour tissue (TT) and paired adjacent non-tumour tissue (ANTT) of these patients was sequenced, and a phylogenetic tree was reconstructed. The correlations between the viral features and evolutionary divergence of preCore/Core amino acid sequences from 67 paired TTs and ANTTs were analysed. Cox proportional hazard model analysis was applied for post-operative hazard risk evaluation. Phylogenetic analysis revealed that all of the sequences were ascribed to genotype C. The evolutionary divergence of amino acid sequences from matched TTs and ANTTs was significantly negatively correlated with serum and intrahepatic HBV DNA levels. Multivariate analysis showed that the HBc E77 mutation was associated with shorter overall survival, and HBc S87 and P156 mutations were independent risk factors for relapse. Furthermore, in contrast to with patients without the S87 mutation, no correlation was observed between serum HBV DNA and intrahepatic HBV DNA in HCC patients with the S87 mutation. Analysis of the intrahepatic sequence may advance our understanding of viral status; thus, it is useful for prognosis prediction for HBV-related HCC.

The universal fuzzy logical framework of neural circuits and its application in modeling primary visual cortex.

Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Although there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.

Synchronized oscillation in a modular neural network composed of columns.

The columnar organization is a ubiquitous feature in the cerebral cortex. In this study, a neural network model simulating the cortical columns has been constructed. When fed with random pulse input with constant rate, a column generates synchronized oscillations, with a frequency varying from 3 to 43 Hz depending on parameter values. The behavior of the model under periodic stimulation was studied and the input-output relationship was non-linear. When identical columns were sparsely interconnected, the column oscillator could be locked in synchrony. In a network composed of heterogeneous columns, the columns were organized by intrinsic properties and formed partially synchronized assemblies.

Modeling the acceleration sensitive neurons in the pigeon optokinetic system.

Recent physiological findings revealed that about one-third of motion-sensitive neurons in the pigeon's pretectal nucleus encoded the acceleration of visual motion. Here we propose a microcircuit hypothesis, in which the slow adaptive depressions play a significant role in response generating, to account for the origin of the three important properties of the acceleration-sensitive neurons: the plateau-shaped speed-tuning curves, the opposite-signed after-responses (OSARs) and the acceleration sensitivities. The flat plateau within the speed-tuning curves and the OSARs to motion offset observed in experiments are reproduced successfully in simulations, and the simulative responses of the acceleration-sensitive neurons to step changes, ramp changes in stimulus speed and sine wave modulations of stimulus speed are qualitatively consistent with physiological observations. Thus, a biologically plausible substrate for the neurons' classification and the origin of the three properties are provided.

Perception of illusory contours enhanced in motion.

Investigation on illusory contours is important for understanding the mechanisms underlying the object recognition of human visual system. Numerous researches have shown that illusory contours formed in motion and stereopsis are generated by the unmatched features. Here we conduct three psychophysical experiments to test if Kanizsa illusory contours are also caused by unmatched information. Different types of motion (including horizontal translation, radial expanding and shrinking) are utilized in the experiments. The results show that no matter under what kind of motion, when figures or background move separately illusory contours are perceived stronger, and there is no significant difference between the perceived strength in these two types of motion. However, no such enhancement of perceived strength is found when figures and background move together. It is found that the strengthened unmatched features generate the enhancement effect of illusory contour perception in motion. Thus the results suggest that the process of unmatched information in visual system is a critical step in the formation of illusory contours.