Topological and random spread models with frozen symbols.

When a symbol or a type has been "frozen" (namely, a type of which an individual only produces one individual of the same type), its spread pattern will be changed and this change will affect the long-term behavior of the whole system. However, in a frozen system, the ξ-matrix and the offspring mean matrix are no longer primitive so that the Perron-Frobenius theorem cannot be applied directly when predicting the spread rates. In this paper, our goal is to characterize these key matrices and analyze the spread rate under more general settings both in the topological and random spread models with frozen symbols. More specifically, we propose an algorithm for explicitly computing the spread rate and relate the rate with the eigenvectors of the ξ-matrix or offspring mean matrix. In addition, we reveal that the growth of the population is exponential and that the composition of the population is asymptotically periodic. Furthermore, numerical experiments are provided as supporting evidence for the theory.

Mathematical analysis of topological and random m-order spread models.

This paper focuses on the analysis of two particular models, from deterministic and random perspective respectively, for spreading processes. With a proper encoding of propagation patterns, the spread rate of each pattern is discussed for both models by virtue of the substitution dynamical systems and branching process. In view of this, we are empowered to draw a comparison between two spreading processes according to their spreading models, based on which explanations are proposed on a higher frequency of a pattern in one model than the other. These results are then supported by the numerical evidence later in the article.

Spread rates of spread models with frozen symbols.

This article aims to compare the long-term behavior of a spread model before and after a type in the model becomes frozen, namely, a type of which an individual only produces individuals of the same type. By means of substitution dynamical systems and matrix analysis, the first result of this work gives the spread rates of a 1-spread model with one frozen symbol. Later, in the work, this is shown to hold under more general settings, which include generalized frozen symbols and frozen symbols in m-spread models. Numerical experiments are provided as supporting evidence for the theory.

Optimization of endometrial cancer organoids establishment by cancer-associated fibroblasts.

Most endometrial cancers (EC) are diagnosed at an early stage with a favorable prognosis. However, for patients with advanced or recurrent disease, the chemotherapy response rate and overall survival remain poor. A novel in vitro model, tumor organoids, has important value in providing a more individualized treatment plan for tumor patients. However, the slow growth of the established EC organoid seriously hinders the application of EC organoids. Cancer-associated fibroblasts (CAFs), the main component of tumor stroma, have been reported to promote the proliferation of endometrial cancer cell lines and primary endometrial cancer cells in vivo and in vitro. Therefore, we optimized the current endometrial cancer organoid by introducing CAFs isolated from EC lesions. Here we developed long-term expandable organoids from endometrial cancer lesions, which show disease-associated traits and cancer-linked mutations. Based on the co-culture of CAFs and endometrial cancer organoids, we found that CAFs could promote the growth of endometrial cancer organoids, might by secreting factors according to the result that CAFs could also promote the growth. Our research provided a more promising model for the basic and preclinical study of endometrial cancer.

A machine learning-based prediction model of H3K27M mutations in brainstem gliomas using conventional MRI and clinical features.

BACKGROUND: H3K27M is the most frequent mutation in brainstem gliomas (BSGs), and it has great significance in the differential diagnosis, prognostic prediction and treatment strategy selection of BSGs. There has been a lack of reliable noninvasive methods capable of accurately predicting H3K27M mutations in BSGs. METHODS: A total of 151 patients with newly diagnosed BSGs were included in this retrospective study. The H3K27M mutation status was obtained by whole-exome, whole-genome or Sanger's sequencing. A total of 1697 features, including 6 clinical parameters and 1691 imaging features, were extracted from pre- and post-contrast T1-weighted and T2-weighted images. Using a random forest algorithm, 36 selected MR image features were integrated with 3 selected clinical features to generate a model that was predictive of H3K27M mutations. Additionally, a simplified prediction model comprising the Karnofsky Performance Status (KPS) at diagnosis, symptom duration at diagnosis and edge sharpness on T2 was established for practical clinical utility using the least squares estimation method. RESULTS: H3K27M mutation was an independent prognostic factor that conferred a worse prognosis (p = 0.01, hazard ratio = 3.0, 95% confidence interval [CI], 1.57-5.74). The machine learning-based model achieved an accuracy of 84.44% (area under the curve [AUC] = 0.8298) in the test cohort. The simplified model achieved an AUC of 0.7839 in the test cohort. CONCLUSIONS: Using conventional MRI and clinical features, we established a machine learning-based model with high accuracy and a simplified model with improved clinical utility to predict H3K27M mutations in BSGs.

The regulation of microRNA expression by DNA methylation in hepatocellular carcinoma.

UNLABELLED: Emerging evidence indicates that microRNAs (miRNAs) are often dysregulated and play a fundamental role in hepatocellular carcinoma (HCC). However, the mechanism underlying miRNA dysregulation is still elusive. In the present study, we adopted an integrated analysis strategy combining data from genome-wide methylated DNA immunoprecipitation chip and miRNA expression microarray to study the regulation of DNA methylation on miRNA expression in HCC. We first characterized 864 differentially methylated regions (DMRs) located in 236 miRNA regions between cancerous and normal hepatocytes in HCC. We observed that the occurrence of miRNA DNA hypomethylation was more common than its hypermethylation while miRNA DNA hypermethylation was usually found in CpG islands. Then through correlation analysis between miRNA methylation and expression data, we identified 10 dysregulated miRNAs under the potential regulation of DNA methylation in HCC. Five of them (miR-148a, miR-375, miR-195, miR-497 and miR-378) were in hypermethylation and down-regulation status, while another five (miR-106b, miR-25, miR-93, miR-23a and miR-27a) were in hypomethylation and up-regulation status in HCC. Bioinformatics analysis showed that miR-148a may form a negative feedback loop with its targets DNMT1 and DNMT3B and the expression of the miR-195/497 cluster may be affected not only by their hypermethylated promoter region but also by their hypermethylated transcription factors NEUROG2 and DDIT3. CONCLUSION: our preliminary data and bioinformatics analysis suggest that DNA methylation plays an important and complex role in the regulation of miRNA expression in HCC, which may provide insights into the pathogenesis of HCC and thus may be used for diagnosis and intervention.

Multiple roles of SOCS proteins: differential expression of SOCS1 and SOCS3 in atherosclerosis.

Pro-inflammatory cytokines play a key pathogenic role in atherosclerosis, which are induced by the Janus kinase/signal transducer and activator of transduction (JAK/STAT) pathway. Furthermore, the JAK/STAT pathway is negatively regulated by the suppressor of cytokine signaling (SOCS) proteins. However, the change in SOCS expression levels and the correlation between SOCS expression and cholesterol levels in atherosclerosis is not yet well understood. To this end, a mouse model of atherosclerosis was established using apolipoprotein-deficient (ApoE(-/-)) mice. The mice were fed either a chow or high-fat diet. The mRNA and protein expression of SOCS1 and SOCS3 in plaque and vessels were determined at different time points. Furthermore, SOCS1 and SOCS3 mRNA expression was detected in the peripheral blood mononuclear cells (PBMCs) obtained from 18 male subjects with no coronary heart disease (non-CHD) population. The expression of SOCS1 in the ApoE(-/-) mice first increased and then decreased and the high-fat diet accelerated the appearance of the peak; the expression of SOCS3 increased with the increased feeding duration, and this trend was more pronounced in the mice fed the high-fat diet. SOCS1/CD68 and SOCS3/CD68 showed opposite trends in expression with the increased duration of the high-fat diet. Interleukin-6 (IL-6) expression in the main aorta of the ApoE(-/-) mice fed the high-fat diet also increased with the increased feeding duration. In the non-CHD population, the total serum cholesterol levels positively correlated with SOCS3 mRNA expression in the PBMCs (r=0.433, P=0.012). These results demonstrate the differential expression of SOCS1 and SOCS3 in atherosclerosis and suggest that SOCS3, together with IL-6 may promote the formation and development of atherosclerosis.

Copper(II)-mediated resolution of alpha-halo carboxylic acids with chiral O,O'-dibenzoyltartaric acid: spontaneous racemization and crystallization-induced dynamic resolution.

Herein we present a new example of coordination-mediated resolution of racemic acids by a chiral acid. The reaction of copper(II) acetate monohydrate, optically pure O,O'-dibenzoyltartaric acid (DBTA) and racemic alpha-bromo-2-chlorophenylacetic acid (HL1) in acetonitrile solution afforded a binuclear copper(II) complex with D-DBTA dianion, alpha-bromo-2-chlorophenylacetate and acetate as ligands. After decomposition of the complex with acid, the optically active acid ((R)-HL1) was obtained. Similarly, alpha-bromo-2-fluorophenylacetic acid (HL2), alpha-bromo-2-bromophenylacetic acid (HL3), alpha-chloro-2-chlorophenylacetic acid (HL4), alpha-chloro-2-fluorophenylacetic acid (HL5), alpha-bromophenylacetic acid (HL6), alpha-bromo-4-chlorophenylacetic acid (HL7), 2-bromopropionic acid (HL8) and 2-chloropropionic acid (HL9) were resolved by the same method. Satisfactory results were obtained for HL2 to HL5. For HL6 and HL7, only racemic acids were obtained. For the two alpha-halo aliphatic acids (HL8 and HL9), poor enantioselectivity was obtained. It is more interesting that three acids (HL1, HL2 and HL3) could spontaneously racemize in acetonitrile solution, which resulted in crystallization-induced dynamic resolution (CIDR) with greater than 50% yield.