Phase separation provides a mechanism to drive phenotype switching.

Phenotypic switching plays a crucial role in cell fate determination across various organisms. Recent experimental findings highlight the significance of protein compartmentalization via liquid-liquid phase separation in influencing such decisions. However, the precise mechanism through which phase separation regulates phenotypic switching remains elusive.

Power-law behavior of transcriptional bursting regulated by enhancer-promoter communication.

Revealing how transcriptional bursting kinetics are genomically encoded is challenging because genome structures are stochastic at the organization level and are suggestively linked to gene transcription. To address this challenge, we develop a generic theoretical framework that integrates chromatin dynamics, enhancer-promoter (E-P) communication, and gene-state switching to study transcriptional bursting. The theory predicts that power law can be a general rule to quantitatively describe bursting modulations by E-P spatial communication.

4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction.

Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance.

Phase separation reduces cell-to-cell variability of transcriptional bursting.

Gene expression is a stochastic and noisy process often occurring in "bursts". Experiments have shown that the compartmentalization of proteins by liquid-liquid phase separation is conducive to reducing the noise of gene expression. Therefore, an important goal is to explore the role of bursts in phase separation noise reduction processes.

Inferring transcriptional bursting kinetics from single-cell snapshot data using a generalized telegraph model.

Gene expression has inherent stochasticity resulting from transcription's burst manners. Single-cell snapshot data can be exploited to rigorously infer transcriptional burst kinetics, using mathematical models as blueprints. The classical telegraph model (CTM) has been widely used to explain transcriptional bursting with Markovian assumptions.

Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics.

Gene expression in mammalian cells is highly variable and episodic, resulting in a series of discontinuous bursts of mRNAs. A challenge is to understand how static promoter architecture and dynamic feedback regulations dictate bursting on a genome-wide scale. Although single-cell RNA sequencing (scRNA-seq) provides an opportunity to address this challenge, effective analytical methods are scarce.

Silent transcription intervals and translational bursting lead to diverse phenotypic switching.

Gene-expression bimodality, as a potential mechanism generating phenotypic cell diversity, can enhance the survival of cells in a fluctuating environment. Previous studies have shown that intrinsic or extrinsic regulations could induce bimodal gene expressions, but it is unclear whether this bimodality can occur without regulation. Here we develop an interpretable and tractable model, namely a generalized telegraph model (GTM), which considers silent transcription intervals and translational bursting, each being characterized by a general distribution.

Exact results for queuing models of stochastic transcription with memory and crosstalk.

Gene transcription is a complex multistep biochemical process, which can create memory between individual reaction events. On the other hand, many inducible genes, when activated by external cues, are often coregulated by several competitive pathways with crosstalk. This raises an unexplored question: how do molecular memory and crosstalk together affect gene expressions? To address this question, we introduce a queuing model of stochastic transcription, where two crossing signaling pathways are used to direct gene activation in response to external signals and memory functions to model multistep reaction processes involved in transcription.

Analytical results for non-Markovian models of bursty gene expression.

Modeling stochastic gene expression has long relied on Markovian hypothesis. In recent years, however, this hypothesis is challenged by the increasing availability of time-resolved data. Correspondingly, there is considerable interest in understanding how non-Markovian reaction kinetics of gene expression impact protein variations across a population of genetically identical cells.

Epidemiological analysis of primary liver cancer in the early 21st century in Guangxi province of China.

Background And Objective: In Guangxi province, from 1970s to 1990s, the mortality of primary liver cancer (PLC) ranked the first among a variety of malignant tumors. Investigating the epidemiological characteristics of PLC is very important for developing reasonable and effective treatment strategy, allocating health resources rationally, and evaluating the quality of PLC prevention and control. This study was to analyze the mortality and epidemiological characteristics of PLC in Guangxi province between 2004 and 2005.

[Study on the relationship between familial clustering of hepatocellular carcinoma and polymorphism of cytochrome P450 2E1 gene in Zhuang population, Guangxi].

Objective: To study the relationship between familial clustering of hepatocellular carcinoma (HCC) and the polymorphism of cytochrome P450 2El gene (CYP2E1) as well as of other relevant risk factors to the cancer.

Methods: Peripheral blood samples were collected from 91 members of 10 HCC clustering families and 102 of 10 control families, among Zhuang population, in Guangxi. The area had been with high incidence rate of HCC.

[A cross-sectional study on liver diseases in the rural residents in southern Guangxi, China].

Objective: To study the epidemiological characteristics of liver diseases in a rural population in Southern Guangxi, China.

Methods: The enzyme immunoassays was used to detect of HBsAg and AFP. AFP positive serum samples were further examined for concentration of AFP by using a radio immunoassays.

Genetic polymorphisms in the methylenetetrahydrofolate reductase and thymidylate synthase genes and risk of hepatocellular carcinoma.

Unlabelled: Methylenetetrahydrofolate reductase (MTHFR) and thymidylate synthase (TYMS) are known to play a role in DNA methylation, synthesis, and repair. The genetic mutations in MTHFR and TYMS genes may have influences on their respective enzyme activities. Data on the association studies of the MTHFR and TYMS genetic polymorphisms and risk of hepatocellular carcinoma (HCC) are sparse.

Phase IIa chemoprevention trial of green tea polyphenols in high-risk individuals of liver cancer: modulation of urinary excretion of green tea polyphenols and 8-hydroxydeoxyguanosine.

Modulation of urinary excretion of green tea polyphenols (GTPs) and oxidative DNA damage biomarker, 8-hydroxydeoxyguanosine (8-OHdG), were assessed in urine samples collected from a randomized, double-blinded and placebo-controlled phase IIa chemoprevention trial with GTP in 124 individuals. These individuals were sero-positive for both HBsAg and aflatoxin-albumin adducts, and took GTP capsules daily at doses of 500 mg, 1000 mg or a placebo for 3 months. Twenty-four hour urine samples were collected before the intervention and at the first and third month of the study.

Effect of cytokine genotypes on the hepatitis B virus-hepatocellular carcinoma association.

Background: In Southern Guangxi, China, chronic infection with the hepatitis B virus (HBV) acquired during the perinatal period from carrier mothers is a primary cause of hepatocellular carcinoma. However, only a minority of HBV carriers eventually develop hepatocellular carcinoma. The authors hypothesized that cytokine genotypes may be important codeterminants of the risk of HBV-related hepatocellular carcinoma.