scGRN-Entropy: Inferring cell differentiation trajectories using single-cell data and gene regulation network-based transfer entropy.

Research on cell differentiation facilitates a deeper understanding of the fundamental processes of life, elucidates the intrinsic mechanisms underlying diseases such as cancer, and advances the development of therapeutics and precision medicine. Existing methods for inferring cell differentiation trajectories from single-cell RNA sequencing (scRNA-seq) data primarily rely on static gene expression data to measure distances between cells and subsequently infer pseudotime trajectories. In this work, we introduce a novel method, scGRN-Entropy, for inferring cell differentiation trajectories and pseudotime from scRNA-seq data.

ABC2A: A Straightforward and Fast Method for the Accurate Backmapping of RNA Coarse-Grained Models to All-Atom Structures.

RNAs play crucial roles in various essential biological functions, including catalysis and gene regulation. Despite the widespread use of coarse-grained (CG) models/simulations to study RNA 3D structures and dynamics, their direct application is challenging due to the lack of atomic detail. Therefore, the reconstruction of full atomic structures is desirable.

Computational Modeling of DNA 3D Structures: From Dynamics and Mechanics to Folding.

DNA carries the genetic information required for the synthesis of RNA and proteins and plays an important role in many processes of biological development. Understanding the three-dimensional (3D) structures and dynamics of DNA is crucial for understanding their biological functions and guiding the development of novel materials. In this review, we discuss the recent advancements in computer methods for studying DNA 3D structures.

Predicting 3D structures and stabilities for complex RNA pseudoknots in ion solutions.

RNA pseudoknots are a kind of important tertiary motif, and the structures and stabilities of pseudoknots are generally critical to the biological functions of RNAs with the motifs. In this work, we have carefully refined our previously developed coarse-grained model with salt effect through involving a new coarse-grained force field and a replica-exchange Monte Carlo algorithm, and employed the model to predict structures and stabilities of complex RNA pseudoknots in ion solutions beyond minimal H-type pseudoknots. Compared with available experimental data, the newly refined model can successfully predict 3D structures from sequences for the complex RNA pseudoknots including SARS-CoV-2 programming-1 ribosomal frameshifting element and Zika virus xrRNA, and can reliably predict the thermal stabilities of RNA pseudoknots with various sequences and lengths over broad ranges of monovalent/divalent salts.

RNAStat: An Integrated Tool for Statistical Analysis of RNA 3D Structures.

The 3D architectures of RNAs are essential for understanding their cellular functions. While an accurate scoring function based on the statistics of known RNA structures is a key component for successful RNA structure prediction or evaluation, there are few tools or web servers that can be directly used to make comprehensive statistical analysis for RNA 3D structures. In this work, we developed RNAStat, an integrated tool for making statistics on RNA 3D structures.

Ab initio predictions for 3D structure and stability of single- and double-stranded DNAs in ion solutions.

The three-dimensional (3D) structure and stability of DNA are essential to understand/control their biological functions and aid the development of novel materials. In this work, we present a coarse-grained (CG) model for DNA based on the RNA CG model proposed by us, to predict 3D structures and stability for both dsDNA and ssDNA from the sequence. Combined with a Monte Carlo simulated annealing algorithm and CG force fields involving the sequence-dependent base-pairing/stacking interactions and an implicit electrostatic potential, the present model successfully folds 20 dsDNAs (≤52nt) and 20 ssDNAs (≤74nt) into the corresponding native-like structures just from their sequences, with an overall mean RMSD of 3.

rsRNASP: A residue-separation-based statistical potential for RNA 3D structure evaluation.

Knowledge-based statistical potentials have been shown to be rather effective in protein 3-dimensional (3D) structure evaluation and prediction. Recently, several statistical potentials have been developed for RNA 3D structure evaluation, while their performances are either still at a low level for the test datasets from structure prediction models or dependent on the "black-box" process through neural networks. In this work, we have developed an all-atom distance-dependent statistical potential based on residue separation for RNA 3D structure evaluation, namely rsRNASP, which is composed of short- and long-ranged potentials distinguished by residue separation.

SS-RNN: A Strengthened Skip Algorithm for Data Classification Based on Recurrent Neural Networks.

Recurrent neural networks are widely used in time series prediction and classification. However, they have problems such as insufficient memory ability and difficulty in gradient back propagation. To solve these problems, this paper proposes a new algorithm called SS-RNN, which directly uses multiple historical information to predict the current time information.

Salt-Dependent RNA Pseudoknot Stability: Effect of Spatial Confinement.

Macromolecules, such as RNAs, reside in crowded cell environments, which could strongly affect the folded structures and stability of RNAs. The emergence of RNA-driven phase separation in biology further stresses the potential functional roles of molecular crowding. In this work, we employed the coarse-grained model that was previously developed by us to predict 3D structures and stability of the mouse mammary tumor virus (MMTV) pseudoknot under different spatial confinements over a wide range of salt concentrations.

3D structure stability of the HIV-1 TAR RNA in ion solutions: A coarse-grained model study.

As an extremely common structural motif, RNA hairpins with bulge loops [e.g., the human immunodeficiency virus type 1 (HIV-1) transactivation response (TAR) RNA] can play essential roles in normal cellular processes by binding to proteins and small ligands, which could be very dependent on their three-dimensional (3D) structures and stability.

Structure folding of RNA kissing complexes in salt solutions: predicting 3D structure, stability, and folding pathway.

RNA kissing complexes are essential for genomic RNA dimerization and regulation of gene expression, and their structures and stability are critical to their biological functions. In this work, we used our previously developed coarse-grained model with an implicit structure-based electrostatic potential to predict three-dimensional (3D) structures and stability of RNA kissing complexes in salt solutions. For extensive RNA kissing complexes, our model shows great reliability in predicting 3D structures from their sequences, and our additional predictions indicate that the model can capture the dependence of 3D structures of RNA kissing complexes on monovalent/divalent ion concentrations.

Predicting 3D structure and stability of RNA pseudoknots in monovalent and divalent ion solutions.

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions.

Understanding the Relative Flexibility of RNA and DNA Duplexes: Stretching and Twist-Stretch Coupling.

The flexibility of double-stranded (ds) RNA and dsDNA is crucial for their biological functions. Recent experiments have shown that the flexibility of dsRNA and dsDNA can be distinctively different in the aspects of stretching and twist-stretch coupling. Although various studies have been performed to understand the flexibility of dsRNA and dsDNA, there is still a lack of deep understanding of the distinctive differences in the flexibility of dsRNA and dsDNA helices as pertains to their stretching and twist-stretch coupling.

Predicting 3D Structure, Flexibility, and Stability of RNA Hairpins in Monovalent and Divalent Ion Solutions.

A full understanding of RNA-mediated biology would require the knowledge of three-dimensional (3D) structures, structural flexibility, and stability of RNAs. To predict RNA 3D structures and stability, we have previously proposed a three-bead coarse-grained predictive model with implicit salt/solvent potentials. In this study, we further develop the model by improving the implicit-salt electrostatic potential and including a sequence-dependent coaxial stacking potential to enable the model to simulate RNA 3D structure folding in divalent/monovalent ion solutions.

RNA folding: structure prediction, folding kinetics and ion electrostatics.

Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution.

A coarse-grained model with implicit salt for RNAs: predicting 3D structure, stability and salt effect.

To bridge the gap between the sequences and 3-dimensional (3D) structures of RNAs, some computational models have been proposed for predicting RNA 3D structures. However, the existed models seldom consider the conditions departing from the room/body temperature and high salt (1M NaCl), and thus generally hardly predict the thermodynamics and salt effect. In this study, we propose a coarse-grained model with implicit salt for RNAs to predict 3D structures, stability, and salt effect.

A tissue-engineered gastric cancer model for mechanistic study of anti-tumor drugs.

The use of the traditional xenograft subcutaneous tumor model has been contested because of its limitations, such as a slow tumorigenesis, inconsistent chemotherapeutic results, etc. In light of these challenges, we aim to revamp the traditional model by employing an electrospun scaffold composed of polydioxanone, gelatin and elastin to boost the tumorigenesis. The scaffold featured a highly porous microstructure and successfully supported the growth of tumor cells in vitro without provoking apoptosis.

Disruption of pRb-p16INK4 pathway: a common event in ampullary carcinogenesis.

Background/aims: Aberrations of the pRb (Retinoblastoma gene protein)-p16INK4 pathway play a critical role in carcinogenesis. Our objective is to evaluate its role in tumorigenesis and the development of ampullary cancer.

Methodology: We examined expression status of p16INK4 protein and pRb immunohistochemically and assessed their possible prognostic relevance in 36 ampullary cancers.

Telomerase expression and p53 status in hepatocellular carcinoma.

Objectives: [corrected] Genomic instability is a driving force for tumorigenesis. Telomerase and p53 play central roles in maintaining genomic integrity. The purpose of this study was to assess the role of telomerase expression and p53 protein overexpression in hepatocellular carcinoma (HCC).

Deregulation of G1/S transition is a common event in carcinoma of the ampulla of vater.

Background/aims: Aberrant expression of cell cycle regulators and subsequent deregulation of G1/S transition is one of the most important characteristics of human cancer. The aim of this study was to determine the overall pattern of deranged expression of the cell cycle regulators involved in the G1/S transition in ampullary carcinoma.

Methodology: Using immunohistochemistry, we investigated the expression of p21WAF1/CIP1, p27Kip1, p16INK4, cyclin D1, cyclin E, pRb and p53 in 14 resected specimens of ampullary carcinoma and defined the proliferative activity of each tumor by quantifying Ki-67 antigen.

Proliferative marker Ki-67 in gallbladder carcinomas: high expression level predicts early recurrence after surgical resection.

To evaluate the prognostic value of proliferative maker Ki-67, its expression was determined immunohistochemically in 37 gallbladder carcinomas (GBCs). A high Ki-67 index was significantly correlated with tumor lymphatic invasion (P=0.007) and vascular invasion (P=0.