Antifibrotic effect of the Chinese herbs, Astragalus mongholicus and Angelica sinensis, in a rat model of chronic puromycin aminonucleoside nephrosis

Nephrotic syndrome has long been treated in China with two herbs, Astragalus mongholicus and Angelica sinensis, which may have antifibrotic effects. METHODS: Rats with chronic puromycin-induced nephrosis were treated with Astragalus and Angelica 3 mL/d (n = 7) or enalapril 10 mg/kg/d (n = 7). Normal control rats (n = 7) received saline rather than puromycin, and an untreated control group (n = 7) received puromycin but no treatment. After 12 weeks, stained sections of the glomerulus and tubulointerstitium were evaluated for injury. Immunohistochemistry staining measured extracellular matrix components, transforming growth factor-beta1 (TGFbeta1), osteopontin, ED-1-positive cells, and alpha-actin. TGFbeta1 mRNA was assessed by in situ hybridization. Renin, ACE activity, angiotensin, and aldosterone were measured by radioimmunoassay or colorimetry. In the untreated rats, chronic renal injury progressed to marked fibrosis at 12 weeks. Astragalus and Angelica significantly reduced deterioration of renal function and histologic damage. Expressions of type III and IV collagen, fibronectin, and laminin also decreased significantly. This anti-fibrotic effect was similar to that of enalapril. The herbs had no effect on the renin-angiotensin system but did reduce the number of ED-1-positive, and alpha-actin positive cells and expression of osteopontin compared to untreated controls. The combination of Astragalus and Angelica retarded the progression of renal fibrosis and deterioration of renal function with comparable effects of enalapril. These effects were not caused by blocking the intrarenal renin-angiotensin system, but associated with suppression of the overexpression of TGFbeta1 and osteopontin, reduction of infiltrating macrophages, and less activation of renal intrinsic cells [corrected].     

松科的核型和系统发育研究

松科通常主要依据长、短枝及叶等的形态特征分成冷杉亚科、落叶松亚科和松亚科。该科各属的核型可以划分成5个类型：(1)松型(24(22)m+0(2)sm);(2)冷杉型((22～14)m十(2～l0)sm(st));(3)落叶松型(12m+12sm(st));(4)花旗松型(10m+12sm+4t);(5)金钱松型(4sm+40t(4SC))。本文根据核型资料的比较分析,各属从原始到进化的顺序可能是：松属(松型核型)-银杉属、云杉属、铁杉属、(雪松属)、油杉属、冷杉属(冷杉型核型)→黄杉属、落叶松属(花旗松型核型和落叶松型核型)→金钱松属(金钱松型核型)。这个顺序和亲缘关系在以核型的平均臂比为纵坐标、染色体长度比为横坐标的坐标图上得到清楚反映(不包括金钱松属)。核型为K(2n)＝44＝4sm+40t(4SC)的单型属金钱松属不仅在染色体数目和核型上与其他各属差异明显,而且具有独特的习性和-系列形态学和解剖学的特征,如落叶乔木(仅同落叶松属),短枝之叶簇状密生而辐射平展呈圆盘状,叶枕在落叶后密集成环节状,雄球花多数簇生短枝顶端,种鳞卵状披针形,成熟时与基部贴生的苞鳞连同崩解的球果中轴一起脱落,叶中3个树脂道及其分布,维管束帽缺如以及传输组织铁杉型(仅同铁杉属)等。因此,本文将金钱松属提升为一个新亚科Pseudolaricoideae L.C．Li,并把原来的3个亚科降为相应的族而隶于松亚科。松科里唯一具K(2n)=24＝12m+12sm(st)核型的黄杉属和落叶松属组成落叶松族,而雪松属按其核型与冷杉族更相近而置于该族。本文根据核型资料建立的松科新系统也得到形态、解剖、植化、免疫、生化、胚胎及占植物等学科有关资料的支持。本文还讨论了前人的松科演化系统。     

Examination of the quality of various force fields and solvation models for the equilibrium simulations of GA88 and GB88

Elucidating the relationship between sequence and conformation is essential for the understanding of functions of proteins. While sharing 88 % sequence identity and differing by only seven residues, GA88 and GB88 have completely different structures and serve as ideal systems for investigating the relationship between sequence and function. Benefiting from the continuous advancement of the computational ability of modern computers, molecular dynamics (MD) simulation is now playing an increasingly important role in the study of proteins. However, the reliability of MD simulations is limited by the accuracy of the force fields and solvent model approximations. In this work, several AMBER force fields (AMBER03, AMBER99SB, AMBER12SB, AMBER14SB, AMBER96) and solvent models (TIP3P, IGB5, IGB7, IGB8) have been employed in the simulations of GA88 and GB88. The statistical results from 19 simulations show that GA88 and GB88 both adopt more compact structures than the native structures. GB88 is more stable than GA88 regardless of the force fields and solvent models utilized. Most of the simulations overestimated the salt bridge interaction. The combination of AMBER14SB force field and IGB8 solvent model shows the best overall performance in the simulations of both GA88 and GB88. AMBER03 and AMBER12SB also yield reasonable results but only in the TIP3P explicit solvent model.     

Diversity surveys and evolutionary relationships of aoxB genes in aerobic arsenite-oxidizing bacteria

A new primer set was designed to specifically amplify ca. 1,100 bp of aoxB genes encoding the As(III) oxidase catalytic subunit from taxonomically diverse aerobic As(III)-oxidizing bacteria. Comparative analysis of AoxB protein sequences showed variable conservation levels and highlighted the conservation of essential amino acids and structural motifs. AoxB phylogeny of pure strains showed well-discriminated taxonomic groups and was similar to 16S rRNA phylogeny. Alphaproteobacteria-, Betaproteobacteria-, and Gammaproteobacteria-related sequences were retrieved from environmental surveys, demonstrating their prevalence in mesophilic As-contaminated soils. Our study underlines the usefulness of the aoxB gene as a functional marker of aerobic As(III) oxidizers.     

Improving microbial fitness in the mammalian gut by in vivo temporal functional metagenomics

Elucidating functions of commensal microbial genes in the mammalian gut is challenging because many commensals are recalcitrant to laboratory cultivation and genetic manipulation. We present Temporal FUnctional Metagenomics sequencing (TFUMseq), a platform to functionally mine bacterial genomes for genes that contribute to fitness of commensal bacteria in vivo. Our approach uses metagenomic DNA to construct large‐scale heterologous expression libraries that are tracked over time in vivo by deep sequencing and computational methods. To demonstrate our approach, we built a TFUMseq plasmid library using the gut commensal Bacteroides thetaiotaomicron (Bt) and introduced Escherichia coli carrying this library into germfree mice. Population dynamics of library clones revealed Bt genes conferring significant fitness advantages in E. coli over time, including carbohydrate utilization genes, with a Bt galactokinase central to early colonization, and subsequent dominance by a Bt glycoside hydrolase enabling sucrose metabolism coupled with co‐evolution of the plasmid library and E. coli genome driving increased galactose utilization. Our findings highlight the utility of functional metagenomics for engineering commensal bacteria with improved properties, including expanded colonization capabilities in vivo.     

Differential susceptibility epidemic models

We formulate compartmental differential susceptibility (DS) susceptible-infective-removed (SIR) models by dividing the susceptible population into multiple subgroups according to the susceptibility of individuals in each group. We analyze the impact of disease-induced mortality in the situations where the number of contacts per individual is either constant or proportional to the total population. We derive an explicit formula for the reproductive number of infection for each model by investigating the local stability of the infection-free equilibrium. We further prove that the infection-free equilibrium of each model is globally asymptotically stable by qualitative analysis of the dynamics of the model system and by utilizing an appropriately chosen Liapunov function. We show that if the reproductive number is greater than one, then there exists a unique endemic equilibrium for all of the DS models studied in this paper. We prove that the endemic equilibrium is locally asymptotically stable for the models with no disease-induced mortality and the models with contact numbers proportional to the total population. We also provide sufficient conditions for the stability of the endemic equilibrium for other situations. We briefly discuss applications of the DS models to optimal vaccine strategies and the connections between the DS models and predator-prey models with multiple prey populations or host-parasitic interaction models with multiple hosts are also given.This research was partially supported by the Department of Energy under contracts W-7405-ENG-36 and the Applied Mathematical Sciences Program KC-07-01-01.     

Quantifying sequence and structural features of protein–RNA interactions

Increasing awareness of the importance of protein–RNA interactions has motivated many approaches to predict residue-level RNA binding sites in proteins based on sequence or structural characteristics. Sequence-based predictors are usually high in sensitivity but low in specificity; conversely structure-based predictors tend to have high specificity, but lower sensitivity. Here we quantified the contribution of both sequence- and structure-based features as indicators of RNA-binding propensity using a machine-learning approach. In order to capture structural information for proteins without a known structure, we used homology modeling to extract the relevant structural features. Several novel and modified features enhanced the accuracy of residue-level RNA-binding propensity beyond what has been reported previously, including by meta-prediction servers. These features include: hidden Markov model-based evolutionary conservation, surface deformations based on the Laplacian norm formalism, and relative solvent accessibility partitioned into backbone and side chain contributions. We constructed a web server called aaRNA that implements the proposed method and demonstrate its use in identifying putative RNA binding sites.