阿托伐他汀预处理对心肌缺血再灌注损伤大鼠心室重构、炎症反应和氧化应激的影响

目的:研究阿托伐他汀预处理对心肌缺血再灌注损伤大鼠心室重构、炎症反应和氧化应激的影响。方法:选取90只SD级大鼠进行研究,将其随机分成假手术组、缺血再灌注组、阿托伐他汀组,每组30只。假手术组与缺血再灌注组大鼠予以生理盐水(5 m L/d)连续灌胃7d处理,阿托伐他汀组予以阿托伐他汀20 mg/(kg·d)连续灌胃7 d,上述干预结束后,缺血再灌注组与阿托伐他汀组大鼠通过阻断大鼠冠状动脉左前降支的方式建立心肌缺血再灌注损伤模型。比较三组大鼠心室重构指标水平、炎症反应以及氧化应激相关指标水平。结果:缺血再灌注组、阿托伐他汀组大鼠的左室相对重量、右室相对重量、室间隔厚度、肿瘤坏死因子-α(TNF-α)、白细胞介素-1β(IL-1β)、丙二醛(MDA)、乳酸脱氧酶(LDH)水平均高于假手术组,且阿托伐他汀组大鼠上述指标均低于缺血再灌注组(均P<0.05);缺血再灌注组、阿托伐他汀组大鼠白介素-10(IL-10)、超氧化物气化酶(SOD)水平低于假手术组,且阿托伐他汀组大鼠IL-10、SOD水平高于缺血再灌注组(均P<0.05)。结论:阿托伐他汀预处理可有效预防心肌缺血再灌注损伤大鼠心室重构,同时可在一定程度上改善大鼠的炎症反应和氧化应激反应。     

益智不同组织多糖含量及其生物合成途径分析

为了解益智（Alpinia oxyphylla）多糖生物合成途径关键酶功能,对其茎、叶、果实中的多糖含量及其单糖组成进行了研究,并采用Real-Time qPCR分析了益智多糖生物合成关键酶基因的表达模式。结果表明,益智多糖含量依次为果实 > 叶 > 茎,主要由葡萄糖、木糖、甘露糖、半乳糖和阿拉伯糖组成;利用益智转录组数据共获得47 690条unigenes,其中31 892条在NR、Swiss-Prot、KEGG、COG、KOG、GO和Pfam数据库获得注释,其中208个unigenes参与益智多糖的生物合成,涉及15个酶。表达分析表明,所筛选的18个基因在茎、叶、果实中均有表达,14个基因在果实中的表达量最高,以糖基转移酶基因和UDP-葡萄糖焦磷酸化酶基因的表达量最高,且其表达模式与不同组织中葡萄糖含量的变化一致。     

Visualization Analysis of CRISPR Gene-editing Knowledge Map based on Citespace

Biology Bulletin - CRISPR is an adaptive immune defense system found in bacteria and archaea that is resistant to heterologous invasive genetic material. Later studies showed that the CRISPR system...     

A Highlights from MBoC Selection: Serine 129 phosphorylation of membrane-associated α-synuclein modulates dopamine transporter function in a G protein–coupled receptor kinase–dependent manner

Most α-synuclein (α-syn) deposited in Lewy bodies, the pathological hallmark of Parkinson disease (PD), is phosphorylated at Ser-129. However, the physiological and pathological roles of this modification are unclear. Here we investigate the effects of Ser-129 phosphorylation on dopamine (DA) uptake in dopaminergic SH-SY5Y cells expressing α-syn. Subcellular fractionation of small interfering RNA (siRNA)–treated cells shows that G protein–coupled receptor kinase 3 (GRK3), GRK5, GRK6, and casein kinase 2 (CK2) contribute to Ser-129 phosphorylation of membrane-associated α-syn, whereas cytosolic α-syn is phosphorylated exclusively by CK2. Expression of wild-type α-syn increases DA uptake, and this effect is diminished by introducing the S129A mutation into α-syn. However, wild-type and S129A α-syn equally increase the cell surface expression of dopamine transporter (DAT) in SH-SY5Y cells and nonneuronal HEK293 cells. In addition, siRNA-mediated knockdown of GRK5 or GRK6 significantly attenuates DA uptake without altering DAT cell surface expression, whereas knockdown of CK2 has no effect on uptake. Taken together, our results demonstrate that membrane-associated α-syn enhances DA uptake capacity of DAT by GRKs-mediated Ser-129 phosphorylation, suggesting that α-syn modulates intracellular DA levels with no functional redundancy in Ser-129 phosphorylation between GRKs and CK2.     

An orthotropic viscoelastic material model for passive myocardium: theory and algorithmic treatment

This contribution presents a novel constitutive model in order to simulate an orthotropic rate-dependent behaviour of the passive myocardium at finite strains. The motivation for the consideration of orthotropic viscous effects in a constitutive level lies in the disagreement between theoretical predictions and experimentally observed results. In view of experimental observations, the material is deemed as nearly incompressible, hyperelastic, orthotropic and viscous. The viscoelastic response is formulated by means of a rheological model consisting of a spring coupled with a Maxwell element in parallel. In this context, the isochoric free energy function is decomposed into elastic equilibrium and viscous non-equilibrium parts. The baseline elastic response is modelled by the orthotropic model of Holzapfel and Ogden [Holzapfel GA, Ogden RW. 2009. Constitutive modelling of passive myocardium: a structurally based framework for material characterization. Philos Trans Roy Soc A Math Phys Eng Sci. 367:3445–3475]. The essential aspect of the proposed model is the account of distinct relaxation mechanisms for each orientation direction. To this end, the non-equilibrium response of the free energy function is constructed in the logarithmic strain space and additively decomposed into three anisotropic parts, denoting fibre, sheet and normal directions each accompanied by a distinct dissipation potential governing the evolution of viscous strains associated with each orientation direction. The evolution equations governing the viscous flow have an energy-activated nonlinear form. The energy storage in the Maxwell branches has a quadratic form leading to a linear stress–strain response in the logarithmic strain space. On the numerical side, the algorithmic aspects suitable for the implicit finite element method are discussed in a Lagrangian setting. The model shows excellent agreement compared to experimental data obtained from the literature. Furthermore, the finite element simulations of a heart cycle carried out with the proposed model show significant deviations in the strain field relative to the elastic solution.     

Rb Suppresses Collective Invasion,Circulation and Metastasis of Breast Cancer Cells in CD44-Dependent Manner

Basal-like breast carcinomas (BLCs) present with extratumoral lymphovascular invasion, are highly metastatic, presumably through a hematogenous route, have augmented expression of CD44 oncoprotein and relatively low levels of retinoblastoma (Rb) tumor suppressor. However, the causal relation among these features is not clear. Here, we show that Rb acts as a key suppressor of multiple stages of metastatic progression. Firstly, Rb suppresses collective cell migration (CCM) and CD44-dependent formation of F-actin positive protrusions in vitro and cell-cluster based lymphovascular invasion in vivo. Secondly, Rb inhibits the release of single cancer cells and cell clusters into the hematogenous circulation and subsequent metastatic growth in lungs. Finally, CD44 expression is required for collective motility and all subsequent stages of metastatic progression initiated by loss of Rb function. Altogether, our results suggest that Rb/CD44 pathway is a crucial regulator of CCM and metastatic progression of BLCs and a promising target for anti-BLCs therapy.     

Properties of MHC Class I Presented Peptides That Enhance Immunogenicity

T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4–6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses.     

Prediction of Drug-Target Interactions for Drug Repositioning Only Based on Genomic Expression Similarity

Small drug molecules usually bind to multiple protein targets or even unintended off-targets. Such drug promiscuity has often led to unwanted or unexplained drug reactions, resulting in side effects or drug repositioning opportunities. So it is always an important issue in pharmacology to identify potential drug-target interactions (DTI). However, DTI discovery by experiment remains a challenging task, due to high expense of time and resources. Many computational methods are therefore developed to predict DTI with high throughput biological and clinical data. Here, we initiatively demonstrate that the on-target and off-target effects could be characterized by drug-induced in vitro genomic expression changes, e.g. the data in Connectivity Map (CMap). Thus, unknown ligands of a certain target can be found from the compounds showing high gene-expression similarity to the known ligands. Then to clarify the detailed practice of CMap based DTI prediction, we objectively evaluate how well each target is characterized by CMap. The results suggest that (1) some targets are better characterized than others, so the prediction models specific to these well characterized targets would be more accurate and reliable; (2) in some cases, a family of ligands for the same target tend to interact with common off-targets, which may help increase the efficiency of DTI discovery and explain the mechanisms of complicated drug actions. In the present study, CMap expression similarity is proposed as a novel indicator of drug-target interactions. The detailed strategies of improving data quality by decreasing the batch effect and building prediction models are also effectively established. We believe the success in CMap can be further translated into other public and commercial data of genomic expression, thus increasing research productivity towards valid drug repositioning and minimal side effects.