Alpha-solanine inhibits endothelial inflammation via nuclear factor kappa B signaling pathway.

BACKGROUND: Alpha-solanine (α-solanine) is the main glycoalkaloid in potato plants. It possesses anticarcinogenic properties and exerts toxic effects. Alpha-solanine can regulate the nuclear factor kappa B (NF-κB) signaling pathway in cancer cells and macrophages. However, little is known about the anti-inflammatory effects and the related molecular mechanisms of α-solanine on endothelial cells. OBJECTIVES: This study aims to examine the effects of α-solanine on endothelial inflammation in vitro, and to evaluate its influence on regulating the NF-κB signaling pathway. MATERIAL AND METHODS: Tumor necrosis factor alpha (TNF-α)-pcDNA3.1(+) plasmid vector was constructed and transfected into human umbilical vein endothelial cells (HUVECs). The expression of TNF-α was examined with quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot. Following treatment with α-solanine or the specific NF-κB inhibitor SN50 for 24 h, cell viability was detected using Cell Counting Kit-8 (CCK-8) assay. Interleukin 6 (IL-6) and TNF-α levels in cell supernatant were detected using enzyme-linked immunosorbent assay (ELISA). The relative protein levels of phospho-P65 (p-P65), phospho-inhibitor of NF-κBα (p-IκBα) and IκB kinase (IKK) α/ß were examined with western blot. RESULTS: The α-solanine inhibits TNF-α-induced inflammatory injury in HUVECs. Compared with control cells, the cell viability was significantly decreased, the levels of TNF-α and IL-6 were significantly increased, and the relative protein levels of p-P65, p-IκBα and IKKα/ß were significantly upregulated in TNF-α-overexpressed cells. The treatment with α-solanine or SN50 decreased the levels of TNF-α and IL-6, and downregulated the relative protein levels of p-P65, p-IκBα and IKKα/ß in TNF-α-overexpressed HUVECs. CONCLUSIONS: This study demonstrated for the first time that α-solanine inhibits endothelial inflammation through the NF-κB signaling pathway. The α-solanine was suggested to be an inhibitor of the NF-κB signaling pathway in endothelial cells. The anti-inflammatory effect of α-solanine may provide a new perspective for the prevention and treatment of phlebitis.

A data-driven method to learn a jump diffusion process from aggregate biological gene expression data.

Dynamic models of gene expression are urgently required. In this paper, we describe the time evolution of gene expression by learning a jump diffusion process to model the biological process directly. Our algorithm needs aggregate gene expression data as input and outputs the parameters of the jump diffusion process. The learned jump diffusion process can predict population distributions of gene expression at any developmental stage, obtain long-time trajectories for individual cells, and offer a novel approach to computing RNA velocity. Moreover, it studies biological systems from a stochastic dynamic perspective. Gene expression data at a time point, which is a snapshot of a cellular process, is treated as an empirical marginal distribution of a stochastic process. The Wasserstein distance between the empirical distribution and predicted distribution by the jump diffusion process is minimized to learn the dynamics. For the learned jump diffusion process, its trajectories correspond to the development process of cells, the stochasticity determines the heterogeneity of cells, its instantaneous rate of state change can be taken as "RNA velocity", and the changes in scales and orientations of clusters can be noticed too. We demonstrate that our method can recover the underlying nonlinear dynamics better compared to previous parametric models and the diffusion processes driven by Brownian motion for both synthetic and real world datasets. Our method is also robust to perturbations of data because the computation involves only population expectations.

Steady-state joint distribution for first-order stochastic reaction kinetics.

While the analytical solution for the marginal distribution of a stochastic chemical reaction network has been extensively studied, its joint distribution, i.e., the solution of a high-dimensional chemical master equation, has received much less attention. Here we develop an alternative method of computing the exact joint distributions of a wide class of first-order stochastic reaction systems in steady-state conditions. The effectiveness of our method is validated by applying it to four gene expression models of biological significance, including models with 2A peptides, nascent mRNA, gene regulation, translational bursting, and alternative splicing.

Phenotypic equilibrium as probabilistic convergence in multi-phenotype cell population dynamics.

We consider the cell population dynamics with n different phenotypes. Both the Markovian branching process model (stochastic model) and the ordinary differential equation (ODE) system model (deterministic model) are presented, and exploited to investigate the dynamics of the phenotypic proportions. We will prove that in both models, these proportions will tend to constants regardless of initial population states ("phenotypic equilibrium") under weak conditions, which explains the experimental phenomenon in Gupta et al.'s paper. We also prove that Gupta et al.'s explanation is the ODE model under a special assumption. As an application, we will give sufficient and necessary conditions under which the proportion of one phenotype tends to 0 (die out) or 1 (dominate). We also extend our results to non-Markovian cases.

Flexibility and symmetry of prokaryotic genome rearrangement reveal lineage-associated core-gene-defined genome organizational frameworks.

UNLABELLED: The prokaryotic pangenome partitions genes into core and dispensable genes. The order of core genes, albeit assumed to be stable under selection in general, is frequently interrupted by horizontal gene transfer and rearrangement, but how a core-gene-defined genome maintains its stability or flexibility remains to be investigated. Based on data from 30 species, including 425 genomes from six phyla, we grouped core genes into syntenic blocks in the context of a pangenome according to their stability across multiple isolates. A subset of the core genes, often species specific and lineage associated, formed a core-gene-defined genome organizational framework (cGOF). Such cGOFs are either single segmental (one-third of the species analyzed) or multisegmental (the rest). Multisegment cGOFs were further classified into symmetric or asymmetric according to segment orientations toward the origin-terminus axis. The cGOFs in Gram-positive species are exclusively symmetric and often reversible in orientation, as opposed to those of the Gram-negative bacteria, which are all asymmetric and irreversible. Meanwhile, all species showing strong strand-biased gene distribution contain symmetric cGOFs and often specific DnaE (α subunit of DNA polymerase III) isoforms. Furthermore, functional evaluations revealed that cGOF genes are hub associated with regard to cellular activities, and the stability of cGOF provides efficient indexes for scaffold orientation as demonstrated by assembling virtual and empirical genome drafts. cGOFs show species specificity, and the symmetry of multisegmental cGOFs is conserved among taxa and constrained by DNA polymerase-centric strand-biased gene distribution. The definition of species-specific cGOFs provides powerful guidance for genome assembly and other structure-based analysis. IMPORTANCE: Prokaryotic genomes are frequently interrupted by horizontal gene transfer (HGT) and rearrangement. To know whether there is a set of genes not only conserved in position among isolates but also functionally essential for a given species and to further evaluate the stability or flexibility of such genome structures across lineages are of importance. Based on a large number of multi-isolate pangenomic data, our analysis reveals that a subset of core genes is organized into a core-gene-defined genome organizational framework, or cGOF. Furthermore, the lineage-associated cGOFs among Gram-positive and Gram-negative bacteria behave differently: the former, composed of 2 to 4 segments, have their fragments symmetrically rearranged around the origin-terminus axis, whereas the latter show more complex segmentation and are partitioned asymmetrically into chromosomal structures. The definition of cGOFs provides new insights into prokaryotic genome organization and efficient guidance for genome assembly and analysis.

[Case-control study on minimally invasive percutaneous plate osteosynthesis for the treatment of distal tibial comminuted fractures at different operation times].

OBJECTIVE: To compare clinical outcomes of minimally invasive percutaneous plate osteosynthesis (MIPPO) in treating distal tibial comminuted fractures at early and delayed stage. METHODS: From January 2006 to January 2012,66 patients with distal tibial comminuted fractures were treated by MIPPO. All patients were divided into primary group and delayed group according to operation time. There were 31 patients in primary group, including 18 males and 13 females aged 21 to 57 years old with an average of (39.0 +/- 17.8), treated by MIPPO at primary stage,according to Tscherne soft tissue injury, 18 cases were grade I ,12 cases were grade II and 1 case were grade III. Thirty-five patients were treated by MIPPO at delayed stage, including 16 males and 19 females aged 24 to 55 years old with an average of (39.5 +/- 15.2), according to Tscherne soft tissue injury, 6 cases were grade I, 26 cases were grade II and 3 cases were grade III. Operation time, blood loss, hospital stay, fracture healing time and complications of two groups were recorded and observed, Lowa scoring of ankle joint were used to evaluated therapeutic effects at final following and AP and lateral X-rays were used to evaluated fracture reduction and alignment. RESULTS: All patients were followed up, the time of following-up of primary group was (13.5 +/- 3.5) months, (15.2 +/- 3.8) months in delayed group, there was no significant meaning between two groups (t = 1.882, P = 0.064). There was no significant differences between two groups in operation time and blood loss (P > 0.05), but hospital stay in primary group was shorter than that of delayed group(P<0.05). There was no significant meaning between primary group (5.5 +/- 2.8) and delayed group (6.2 +/- 3.1) in fracture healing time (t = 0.958, P = 0.342); there was no significant meaning between primary group (87.6 +/- 6.8) and delayed group (89.6 +/- 5.2) in Lowa scores at final following-up (t = 1.351, P = 0.182). Two cases occurred postoperative superficial inflammatory reaction around fibular incision in primary group, 1 case occurred postoperative superficial inflammatory reaction around fibular incision and 1 case occurred delayed deep incision infection in delayed group at four months after operation. There was no significant differences in incidence of postoperative soft tissue complications between primary group (6.5%) and delayed group (5.7%) (t = 0.016, P = 0.900). CONCLUSION: For distal tibial comminuted fractures with grade I and II of Tscherne soft tissue injury, MIPPO at primary stage can not increase incidence of soft tissue complications, also can obtain the same clinical outcomes just like delayed MIPPO.

An allosteric model of the inositol trisphosphate receptor with nonequilibrium binding.

The inositol trisphosphate receptor (IPR) is a crucial ion channel that regulates the Ca(2+) influx from the endoplasmic reticulum (ER) to the cytoplasm. A thorough study of the IPR channel contributes to a better understanding of calcium oscillations and waves. It has long been observed that the IPR channel is a typical biological system which performs adaptation. However, recent advances on the physical essence of adaptation show that adaptation systems with a negative feedback mechanism, such as the IPR channel, must break detailed balance and always operate out of equilibrium with energy dissipation. Almost all previous IPR models are equilibrium models assuming detailed balance and thus violate the dissipative nature of adaptation. In this article, we constructed a nonequilibrium allosteric model of single IPR channels based on the patch-clamp experimental data obtained from the IPR in the outer membranes of isolated nuclei of the Xenopus oocyte. It turns out that our model reproduces the patch-clamp experimental data reasonably well and produces both the correct steady-state and dynamic properties of the channel. Particularly, our model successfully describes the complicated bimodal [Ca(2+)] dependence of the mean open duration at high [IP3], a steady-state behavior which fails to be correctly described in previous IPR models. Finally, we used the patch-clamp experimental data to validate that the IPR channel indeed breaks detailed balance and thus is a nonequilibrium system which consumes energy.

Overshoot in biological systems modelled by Markov chains: a non-equilibrium dynamic phenomenon.

A number of biological systems can be modelled by Markov chains. Recently, there has been an increasing concern about when biological systems modelled by Markov chains will perform a dynamic phenomenon called overshoot. In this study, the authors found that the steady-state behaviour of the system will have a great effect on the occurrence of overshoot. They showed that overshoot in general cannot occur in systems that will finally approach an equilibrium steady state. They further classified overshoot into two types, named as simple overshoot and oscillating overshoot. They showed that except for extreme cases, oscillating overshoot will occur if the system is far from equilibrium. All these results clearly show that overshoot is a non-equilibrium dynamic phenomenon with energy consumption. In addition, the main result in this study is validated with real experimental data.

Kinetic behavior of the general modifier mechanism of Botts and Morales with non-equilibrium binding.

In this paper, we perform a complete analysis of the kinetic behavior of the general modifier mechanism of Botts and Morales in both equilibrium steady states and non-equilibrium steady states (NESS). Enlightened by the non-equilibrium theory of Markov chains, we introduce the net flux into discussion and acquire an expression of the rate of product formation in NESS, which has clear biophysical significance. Up till now, it is a general belief that being an activator or an inhibitor is an intrinsic property of the modifier. However, we reveal that this traditional point of view is based on the equilibrium assumption. A modifier may no longer be an overall activator or inhibitor when the reaction system is not in equilibrium. Based on the regulation of enzyme activity by the modifier concentration, we classify the kinetic behavior of the modifier into three categories, which are named hyperbolic behavior, bell-shaped behavior, and switching behavior, respectively. We show that the switching phenomenon, in which a modifier may convert between an activator and an inhibitor when the modifier concentration varies, occurs only in NESS. Effects of drugs on the Pgp ATPase activity, where drugs may convert from activators to inhibitors with the increase of the drug concentration, are taken as a typical example to demonstrate the occurrence of the switching phenomenon.