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ObjectiveTo determine the variation of IFN-γ and IL-17 responses to M. tuberculosis antigens in healthy TST+ humans.MethodsWe isolated peripheral blood mononuclear cells from 21 TST+ healthy adults, stimulated them with phytohemagglutinin (PHA), PPD, Ag85B, ESAT-6, and live M. bovis BCG, and assayed IFN-γ and IL-17 secretion by ELISA in supernatants after 24 or 72 hours of incubation respectively.ResultsAs in other studies, we found a wide range of IFN-γ responses to M. tuberculosis antigens; the variation significantly exceeded that observed in the same donors to the polyclonal T cell stimulus, phytohemagglutinin (PHA). In addition, we assayed IL-17 secretion in response to the same stimuli, and found less subject-to-subject variation. Analysis of the ratio of IFN-γ to IL-17 secretion on a subject-to-subject basis also revealed a wide range, with the majority of results distributed in a narrow range, and a minority with extreme results all of which were greater than that in the majority of subjects. The data suggest that study of exceptional responses to M. tuberculosis antigens may reveal immunologic correlates with specific outcomes of M. tuberculosis infection.ConclusionVariation of IFNγ and IFN-γ/IL-17 responses to mycobacterial antigens exceeds that of responses to the polyclonal stimulus, PHA, in TST positive healthy humans. This indicates a quantitative spectrum of human immune responses to infection with M. tuberculosis. Since the outcome of human infection with M. tuberculosis varies greatly, systematic study of multiple immune responses to multiple antigens is likely to reveal correlations between selected immune responses and the outcomes of infection.

There are a few common species and many rare species in a biological community or a multi-species collection in given space and time. This hollow distribution curve is called species abundance distribution (SAD). Few studies have examined the patterns and dynamics of SADs during the succession of forest communities by model selection. This study explored whether the communities in different successional stages followed different SAD models and whether there existed a best SAD model to reveal their intrinsic quantitative features of structure and dynamics in succession. The abundance (the number of individuals) of each vascular plant was surveyed by quadrat sampling method from the tree, shrub and herb layers in two typical communities (i.e., the evergreen needle- and broad-leaved mixed forest and the monsoon evergreen broad-leaved forest) in southern subtropical Dinghushan Biosphere Reserve, South China. The sites of two forest communities in different successional stages are both 1 ha in area. We collected seven widely representative SAD models with obviously different function forms and transformed them into the same octave (log2) scale. These models are simultaneously confronted with eight datasets from four layers of two communities, and their goodness-of-fits to the data were evaluated by the chi-squared test, the adjusted coefficient of determination and the information criteria. The results indicated that: (1) the logCauchy model followed all the datasets and was the best among seven models; (2) the fitness of each model to the data was not directly related to the successional stage of forest community; (3) according to the SAD curves predicted by the best model (i.e., the logCauchy), the proportion of rare species decreased but that of common ones increased in the upper layers with succession, while the reverse was true in the lower layers; and (4) the difference of the SADs increased between the upper and the lower layers with succession. We concluded that the logCauchy model had the widest applicability in describing the SADs, and could best mirror the SAD patterns and dynamics of communities and their different layers in the succession of forests. The logCauchy-modeled SADs can quantitatively guide the construction of ecological forests and the restoration of degraded vegetation.

In the developing neocortex, cells in the ventricular/subventricular zone are largely multipotent neural stem cells and neural progenitor cells. These cells undergo self-renewal at the early stage of embryonic development to amplify the progenitor pool and subsequently differentiate into neurons. It is thus of considerable interest to investigate mechanisms controlling the switch from neural stem cells or neural progenitor cells to neurons. Here, we present evidence that Kif2a, a member of the Kinesin-13 family, plays a role in regulating the proliferation and differentiation of neural stem cells or neural progenitor cells at embryonic day 13.5. Silencing Kif2a by use of in utero electroporation of Kif2a shRNA reduced neural stem cells proliferation or self-renewal but increased neuronal differentiation. We further found that knockdown of Kif2a decreased the protein level of β-catenin, which is a critical molecule for neocortical neurogenesis. Together, these results reveal an important function of Kif2a in embryonic neocortical neurogenesis.

H9N2 avian influenza virus (AIV) has caused significant losses in chicken flocks throughout china in recent years. There is a limited understanding of the genetic and antigenic characteristics of the H9N2 virus isolated in chickens in southwestern China. In this study a total of 12 field strains were isolated from tissue samples from diseased chickens between 2013 and 2016. Phylogenetic analysis of the Hemagglutinin (HA) and Neuraminidase (NA) nucleotide sequences from the 12 field isolates and other reference strains showed that most of the isolates in the past four years could be clustered into a major branch (HA-branch A and NA-branch I) in the Clade h9.4.2 lineages. These sequences are accompanied by nine and seven new amino acids mutations in the HA and NA proteins, respectively, when compared with those previous to 2013. In addition, four new isolates were grouped into a minor branch (HA-branch B) in the Clade h9.4.2 lineages and two potential N-glycosylation sites were observed due to amino acid mutations in the HA protein. Three antigenic groups (1-3), which had low antigenic relatedness with two commonly used vaccines in China, were identified among the 12 isolates by antigenMap analysis. Immunoprotection testing showed that those two vaccines could efficiently prevent the shedding of branch A viruses but not branch B viruses. In conclusion, these results indicate the genotype of branch B may become epidemic in the next few years and that a new vaccine should be developed for the prevention of H9N2 AIV.

Parkinson's disease (PD) is characterized by the progressive degeneration of the dopaminergic neurons in the substantia nigra (SN) region. Acteoside has displayed multiple biological functions. Its potential role against PD and the underlying signaling mechanisms are largely unknown. Here, we showed that oral administration of acteoside significantly attenuated parkinsonism symptoms in rotenone-induced PD rats. Further, acteoside inhibited rotenone-induced α-synuclein, caspase-3 upregulation and microtubule-associated protein 2 (MAP2) downregulation in PD rats. The molecular docking and molecular dynamics (MD) simulation results indicated that acteoside may directly bind to and inhibit caspase-3. Acteoside formed hydrogen bonds with at least six residues of caspase-3: ThrA177, SerA178, GlyA238, SerB339, ArgB341 and TrpB348. In addition, a pi-pi interaction was formed between acteoside and caspase-3's HisA237, which might further stabilize the complex. MD simulation results demonstrated that the binding affinity of the caspase-3-acteoside complex was higher than that of caspase-3 and its native ligand inhibitor. Together, we show that acteoside binds to caspase-3 and exerts neuroprotection in the rotenone rat model of PD.

Panax notoginseng (Burk.) F.H. Chen, called Sanqi in China, is a perennial herb that has been used as a medicinal herb in traditional Chinese medicine for more than 400 years. Because notoginseng is included in many proprietary Chinese medicines, the quality of notoginseng directly affects its efficacy and safety. However, considering the complex and special growth environment requirements of notoginseng, it is insufficient to evaluate its quality based solely on the analysis of marker chemicals. Thus, in this study, we tried to evaluate the quality of notoginseng with integrated indicators: (1) the concentration of five marker chemicals, notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1 and ginsenoside Rd; (2) the anticoagulant activity (ACA); and (3) twenty-one ecological factors (e.g., longitude, latitude, elevation and soil data). Using these 27 parameters, notoginseng from different regions could be distinguished effectively, indicating a remarkable divergence of quality. A correlation analysis showed that variations of the ecological factors were closely associated with the saponins content and biopotency. For instance, the total nitrogen (TN), alkali hydrolysis nitrogen (AHN) and rapidly available potassium (RAPT) were significantly correlated with ACA, and RAPT was significantly correlated with the content of ginsenoside Rd and notoginsenoside R1. The results demonstrated that the high-quality notoginseng was produced from the emerging regions such as Kunming, Qujing and Honghe, which had higher ACA and saponin content than the notoginseng produced in traditional regions such as Wenshan and Baise.

Organic cation transporter 1 (OCT1, SLC22A1), like many solute carrier 22 (SLC22) family members, is important for the disposition of clinically important drugs, metabolites and signaling molecules. Several studies suggest that SLC22 family (eg. organic anion transporters or OATs and OCTs) bind and possibly transport prostaglandins with relatively high affinity (submicromolar). The affinities of OCT1 and OATs toward PGE2 and PGF2a reported in these cell-based transport studies are considerably greater than for xenobiotics and natural metabolite substrates--in many cases over 100-fold higher. This raises the possibility that prostaglandins are key endogenous substrates and/or that they act on the transporter in a manner different from other substrates such as xenobiotics and lower affinity metabolites. To further investigate OCT1-prostaglandin interactions, we designed biophysical studies using purified bovine OCT1 (Bos taurus, btOCT1/SLC22A1) with PGE2 analogs, in fluorescently labeled and label-free formats. Using fluorescence polarization (FP), we detected a binding of btOCT1 to the PGE2-Rhodamine conjugate at submicromolar affinity, consistent with affinity data for PGE2 from cells over-expressing the related human OCT1. Using purified native btOCT1 as analyte and biotinylated PGE2 analog as ligand, our data from surface plasmon resonance (SPR) revealed that btOCT1 specifically interacts to PGE2 with KD values in the hundred nanomolar range. BtOCT1 also demonstrated a slow association (ka) in the range of 103 M(-1) s(-1) and an even slower dissociation rate (kd) in the range of 10-4 s(-1) for PGE2, suggesting the possibility of a different mode of binding compared to other structurally unrelated transported substrates of low-affinity (eg. drugs, metabolites). Our results complement in vitro transport studies and provide direct evidence that OCT1--which is normally expressed in liver and other tissues--interacts with prostaglandin analogs. While it is not entirely clear from the published literature whether OCTs function as major prostaglandin transporters, the tight binding of the naturally occurring PGE2, as well as the slow dissociation rate, could conceivably affect the transport of lower affinity substrates such as drugs and metabolites by SLC22 transporters. More research is necessary to establish the extent to which individual SLC22 family members actually function as PG transporters in vitro and in vivo and to investigate whether PGs can, independent of being directly transported, alter the ability of SLC22 transporters to handle drugs and other substrates.

Cerium oxide nanoparticles (CeO2 NPs) have been shown to have significant interactions in plants. Previous study reported the specific-species phytotoxicity of CeO2 NPs by lettuce (Lactuca sativa), but their physiological impacts and vivo biotransformation are not yet well understood, especially in relative realistic environment. Butterhead lettuce were germinated and grown in potting soil for 30 days cultivation with treatments of 0, 50, 100, 1000 mg CeO2 NPs per kg soil. Results showed that lettuce in 100 mg·kg-1 treated groups grew significantly faster than others, but significantly increased nitrate content. The lower concentrations treatment had no impact on plant growth, compared with the control. However, the higher concentration treatment significantly deterred plant growth and biomass production. The stress response of lettuce plants, such as Superoxide dismutase (SOD), Peroxidase (POD), Malondialdehyde(MDA) activity was disrupted by 1000 mg·kg-1 CeO2 NPs treatment. In addition, the presence of Ce (III) in the roots of butterhead lettuce explained the reason of CeO2 NPs phytotoxicity. These findings demonstrate CeO2 NPs modification of nutritional quality, antioxidant defense system, the possible transfer into the food chain and biotransformation in vivo.

Lung alveolar development in late gestation is a process important to postnatal survival. Follistatin-like 1 (Fstl1) is a matricellular protein of the Bmp antagonist class, which is involved in the differentiation/maturation of alveolar epithelial cells during saccular stage of lung development. This study investigates the role of Fstl1 on elastin deposition in mesenchyme and subsequent secondary septation in the late gestation stage of terminal saccular formation. To this aim, we modified the renal capsule allograft model for lung organ culture by grafting diced E15.5 distal lung underneath the renal capsule of syngeneic host and cultured up to 7 days. The saccular development of the diced lung allografts, as indicated by the morphology, epithelial and vascular developments, occurred in a manner similar to that in utero. Fstl1 deficiency caused atelectatic phenotype companied by impaired epithelial differentiation in D3 Fstl1(-/-) lung allografts, which is similar to that of E18.5 Fstl1(-/-) lungs, supporting the role of Fstl1 during saccular stage. Inhibition of Bmp signaling by intraperitoneal injection of dorsomorphin in the host mice rescued the pulmonary atelectasis of D3 Fstl1(-/-) allografts. Furthermore, a marked reduction in elastin expression and deposition was observed in walls of air sacs of E18.5 Fstl1(-/-) lungs and at the tips of the developing alveolar septae of D7 Fstl1(-/-) allografts. Thus, in addition to its role on alveolar epithelium, Fstl1 is crucial for elastin expression and deposition in mesenchyme during lung alveologenesis. Our data demonstrates that the modified renal capsule allograft model for lung organ culture is a robust and efficient technique to increase our understanding of saccular stage of lung development.

Experiential and sensory evaluation is an ancient method that remains important in the current quality control system of Traditional Chinese Medicines (TCMs). The process is rapid and convenient when evaluating the quality of crude materials in TCM markets. However, sensory evaluation has been met with skepticism because it is mainly based on experience and lacks a scientific basis. In this study, rhubarb was selected to demonstrate how color-based sensory evaluation could differentiate the quality of herbal medicines objectively. The colors of the rhubarb samples, expressed as RGB values, were obtained from different parts and forms of the plant, including the plant's surface, fracture surface color, and a powdered form with or without treatment with a color-developing reagent. We first divided the rhubarb samples into three grades based on the total content of five hydroxyanthraquinone derivatives, the major pharmacological components in rhubarb. Then, a three-layer back-propagation artificial neural network (BP-ANN), calibrated with selected training samples, was used to correlate the quality of the rhubarb with its color. The color of the rhubarb powder after coloration attained the highest accuracy (92.3%) in predicting the quality grade of the test samples with the established artificial neural networks. Finally, a standardized colorimetric grading scale was created based on the spatial distribution of the rhubarb samples in a two-dimensional chromaticity diagram according to the colors of the powdered rhubarb after color enhancement. By comparing the color between the scale and the tested samples, similar to performing a pH test with indicator paper, subjects without sensory evaluation experience could quickly determine the quality grade of rhubarb. This work illustrates the technical feasibility of the color-based grading of rhubarb quality and offers references for quantifying and standardizing the sensory evaluation of TCMs, foods and other products.

The routine prediction of three-dimensional protein structure from sequence remains a challenge in computational biochemistry. It has been intuited that calculated energies from physics-based scoring functions are able to distinguish native from nonnative folds based on previous performance with small proteins and that conformational sampling is the fundamental bottleneck to successful folding. We demonstrate that as protein size increases, errors in the computed energies become a significant problem. We show, by using error probability density functions, that physics-based scores contain significant systematic and random errors relative to accurate reference energies. These errors propagate throughout an entire protein and distort its energy landscape to such an extent that modern scoring functions should have little chance of success in finding the free energy minima of large proteins. Nonetheless, by understanding errors in physics-based score functions, they can be reduced in a post-hoc manner, improving accuracy in energy computation and fold discrimination.

The hepatotoxicity of some Chinese herbs has been a cause for concern in recent years. However, some herbs, such as rhubarb, have been documented as having both therapeutic and toxic effects on the liver, leading to the complex problem of distinguishing the benefits from the risks of using this herb. To comparatively analyze the dose-response relationship between rhubarb and hepatic health, we administrated total rhubarb extract (RE) to normal and carbon tetrachloride (CCl(4))-treated rats for 12 weeks at 4 dosage levels (2.00, 5.40, 14.69 and 40.00 g·kg(-1), measured as the quantity of crude material), followed by biochemical and histopathological tests of the rats' livers. A composite pattern was extracted by factor analysis, using all the biochemical indices as variables, into a visual representation of two mathematically obtained factors, which could be interpreted as the fibrosis factor and the cellular injury factor, according to the values of the variable loadings. The curative effect of administering the two lowest dosages of RE to CCl(4)-treated rats was mainly expressed as a decrease in the extent of cellular injury. The hepatoprotective mechanism of RE might be related to its antioxidant effect, the antagonism of the free radical damage to hepatocytes caused by CCl(4). By contrast, the RE-induced liver damage was mainly expressed as a significant increase in the amount of fibrosis in both normal rats at all dosage levels and CCl(4)-treated rats at the two highest dosage levels. Therefore, the hepatotoxic potential of RE could be attributable to the liver cell fibrosis induced by high doses of the herb. This study illustrates the bidirectional potential of rhubarb and demonstrates the feasibility of using factor analysis to study the dose-response relationships between herbal medicines and hepatotoxicity or the healing effects of these herbs by extracting the underlying interrelationships among a number of functional bio-indices in a holistic manner.

BackgroundHydroxylation is an important post-translational modification and closely related to various diseases. Besides the biotechnology experiments, in silico prediction methods are alternative ways to identify the potential hydroxylation sites.Methodology/principal findingsIn this study, we developed a novel sequence-based method for identifying the two main types of hydroxylation sites--hydroxyproline and hydroxylysine. First, feature selection was made on three kinds of features consisting of amino acid indices (AAindex) which includes various physicochemical properties and biochemical properties of amino acids, Position-Specific Scoring Matrices (PSSM) which represent evolution information of amino acids and structural disorder of amino acids in the sliding window with length of 13 amino acids, then the prediction model were built using incremental feature selection method. As a result, the prediction accuracies are 76.0% and 82.1%, evaluated by jackknife cross-validation on the hydroxyproline dataset and hydroxylysine dataset, respectively. Feature analysis suggested that physicochemical properties and biochemical properties and evolution information of amino acids contribute much to the identification of the protein hydroxylation sites, while structural disorder had little relation to protein hydroxylation. It was also found that the amino acid adjacent to the hydroxylation site tends to exert more influence than other sites on hydroxylation determination.Conclusions/significanceThese findings may provide useful insights for exploiting the mechanisms of hydroxylation.

The metabolic stability is a very important idiosyncracy of proteins that is related to their global flexibility, intramolecular fluctuations, various internal dynamic processes, as well as many marvelous biological functions. Determination of protein's metabolic stability would provide us with useful information for in-depth understanding of the dynamic action mechanisms of proteins. Although several experimental methods have been developed to measure protein's metabolic stability, they are time-consuming and more expensive. Reported in this paper is a computational method, which is featured by (1) integrating various properties of proteins, such as biochemical and physicochemical properties, subcellular locations, network properties and protein complex property, (2) using the mRMR (Maximum Relevance & Minimum Redundancy) principle and the IFS (Incremental Feature Selection) procedure to optimize the prediction engine, and (3) being able to identify proteins among the four types: "short", "medium", "long", and "extra-long" half-life spans. It was revealed through our analysis that the following seven characters played major roles in determining the stability of proteins: (1) KEGG enrichment scores of the protein and its neighbors in network, (2) subcellular locations, (3) polarity, (4) amino acids composition, (5) hydrophobicity, (6) secondary structure propensity, and (7) the number of protein complexes the protein involved. It was observed that there was an intriguing correlation between the predicted metabolic stability of some proteins and the real half-life of the drugs designed to target them. These findings might provide useful insights for designing protein-stability-relevant drugs. The computational method can also be used as a large-scale tool for annotating the metabolic stability for the avalanche of protein sequences generated in the post-genomic age.

BackgroundStudy of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner.Methods/principal findingsTo realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively.Conclusion/significanceOur results indicate that the network prediction system thus established is quite promising and encouraging.

Lung alveolar development in late gestation is a process important to postnatal survival. Follistatin-like 1 (Fstl1) is a matricellular protein of the Bmp antagonist class, which is involved in the differentiation/maturation of alveolar epithelial cells during saccular stage of lung development. This study investigates the role of Fstl1 on elastin deposition in mesenchyme and subsequent secondary septation in the late gestation stage of terminal saccular formation. To this aim, we modified the renal capsule allograft model for lung organ culture by grafting diced E15.5 distal lung underneath the renal capsule of syngeneic host and cultured up to 7 days. The saccular development of the diced lung allografts, as indicated by the morphology, epithelial and vascular developments, occurred in a manner similar to that in utero. Fstl1 deficiency caused atelectatic phenotype companied by impaired epithelial differentiation in D3 Fstl1−/− lung allografts, which is similar to that of E18.5 Fstl1−/− lungs, supporting the role of Fstl1 during saccular stage. Inhibition of Bmp signaling by intraperitoneal injection of dorsomorphin in the host mice rescued the pulmonary atelectasis of D3 Fstl1−/− allografts. Furthermore, a marked reduction in elastin expression and deposition was observed in walls of air sacs of E18.5 Fstl1−/− lungs and at the tips of the developing alveolar septae of D7 Fstl1−/− allografts. Thus, in addition to its role on alveolar epithelium, Fstl1 is crucial for elastin expression and deposition in mesenchyme during lung alveologenesis. Our data demonstrates that the modified renal capsule allograft model for lung organ culture is a robust and efficient technique to increase our understanding of saccular stage of lung development. [ABSTRACT FROM AUTHOR]

Objective: It is well known that complement system C5a is excessively activated during the onset of sepsis. However, it is unclear whether C5a can regulate dentritic cells (DCs) to stimulate adaptive immune cells such as Th1 and Th17 in sepsis. Methods: Sepsis was induced by cecal ligation and puncture (CLP). CLP-induced sepsis was treated with anti-C5a or IL-12. IL-12+DC, IFNγ+Th1, and IL-17+Th17 cells were analyzed by flow cytometry. IL-12 was measured by ELISA. Results: Our studies here showed that C5a induced IL-12+DC cell migration from the peritoneal cavity to peripheral blood and lymph nodes. Furthermore, IL-12+DC cells induced the expansion of pathogenic IFNγ+Th1 and IL-17+Th17 cells in peripheral blood and lymph nodes. Moreover, IL-12, secreted by DC cells in the peritoneal cavity, is an important factor that prevents the development of sepsis. Conclusion: Our data suggests that C5a regulates IL-12+DC cell migration to induce pathogenic Th1 and Th17 cells in sepsis. [ABSTRACT FROM AUTHOR]

The routine prediction of three-dimensional protein structure from sequence remains a challenge in computational biochemistry. It has been intuited that calculated energies from physics-based scoring functions are able to distinguish native from nonnative folds based on previous performance with small proteins and that conformational sampling is the fundamental bottleneck to successful folding. We demonstrate that as protein size increases, errors in the computed energies become a significant problem. We show, by using error probability density functions, that physics-based scores contain significant systematic and random errors relative to accurate reference energies. These errors propagate throughout an entire protein and distort its energy landscape to such an extent that modern scoring functions should have little chance of success in finding the free energy minima of large proteins. Nonetheless, by understanding errors in physics-based score functions, they can be reduced in a post-hoc manner, improving accuracy in energy computation and fold discrimination. [ABSTRACT FROM AUTHOR]

Objective: It is well known that complement system C5a is excessively activated during the onset of sepsis. However, it is unclear whether C5a can regulate dentritic cells (DCs) to stimulate adaptive immune cells such as Th1 and Th17 in sepsis., Methods: Sepsis was induced by cecal ligation and puncture (CLP). CLP-induced sepsis was treated with anti-C5a or IL-12. IL-12(+)DC, IFNγ(+)Th1, and IL-17(+)Th17 cells were analyzed by flow cytometry. IL-12 was measured by ELISA., Results: Our studies here showed that C5a induced IL-12(+)DC cell migration from the peritoneal cavity to peripheral blood and lymph nodes. Furthermore, IL-12(+)DC cells induced the expansion of pathogenic IFNγ(+)Th1 and IL-17(+)Th17 cells in peripheral blood and lymph nodes. Moreover, IL-12, secreted by DC cells in the peritoneal cavity, is an important factor that prevents the development of sepsis., Conclusion: Our data suggests that C5a regulates IL-12(+)DC cell migration to induce pathogenic Th1 and Th17 cells in sepsis.