δ13C values of soil organic carbon and their responses to C3 and C4 plants shift in Mengzi karst graben basin, SW China

Understanding the controlling factors of soil organic carbon isotope (δ13CSOC) change and the vegetation succession process is crucial to guide ecological restoration and agricultural cultivation in karst rocky desertification region. However, the information about the combination of C3 and C4 plant distribution and rocky desertification remains unknown. Soils from different landforms, including basin, slope, and plateau, were sampled to investigate the spatial variance of the δ13CSOC distribution characteristics. The contribution of C3 and C4 plant species for δ13CSOC under the different rocky desertification grades (LRD: light rocky desertification; MRD: moderate rocky desertification; and SRD: severe rocky desertification) in Mengzi karst graben basin of Southwest (SW) China was also discussed. The δ13CSOC  value decreased with the increase of altitude from basin, slope to plateau. At the same landform, different rocky desertification grades had no significant effect on the δ13CSOC in slope and plateau. Nevertheless, there were significant differences of δ13CSOC C between LRD and SRD in the basin. The C4 plants account for more than 70% in the basin and slope, while C3 plants account for more than 70% in the plateau. This may be due to the long-term cultivation of corn in the historical period in the basin and slope. However, the plateau area is not suitable for the growth of C4 plants such as corn due to the cold climate. In addition, in the same landform, with the aggravation of rocky desertification, the proportion of C4 plants for δ13CSOC increased with the proportion of C3 plants decreased. With the aggravation of rocky desertification, the composition of vegetation species changed from arbour (C3 plants) to small shrubs and herbs (C4 plants).Razumevanje povezave med spremembami izotopa v organskem ogljiku v tleh (δ13CSOC) in procesi ekološke sukcesije je pomembno pri restavraciji in kultivaciji kraških degradiranih območij. O povezavi med porazdelitvijo sestoja rastlin C3 in C4 ter skalno dezertifikacijo na kraških območjih vemo le malo. Prostorsko spremenljivost δ13CSOC smo določali na različnih površinskih oblikah; v kotlini, na pobočjih in na kraški planoti na območju Mengzi v provinci Junan na jugovzhodu Kitajske. V vseh reliefnih oblikah smo obravnavali prispevek rastlinskih vrst C3 in C4 k vrednosti δ13CSOC . Posebno pozornost smo posvetili tudi različnim stopnjam dezertifikacije (LRD: majhna; MRD: zmerna; in SRD: visoka). V splošnem vrednost δ13CSOC pada z naraščanjem nadmorske višine. Na planoti in pobočjih stopnja dezertifikacije ne vpliva pomembno na δ13CSOC, v kotlini pa je značilna razlika med območji z nizko stopnjo dezertifikacije in območji z visoko stopnjo dezertifikacije. Sestoji rastlin C4 tvorijo več kot 70 % rastlinja v kotlini in na pobočjih, sestoji rastlin C3 pa 70 % rastlinja na planoti. Razlika je verjetno posledica pridelave koruze v kotlini in na pobočjih, saj planota zaradi hladne klime ni primerna za sajenje rastlin C4, kot je koruza. Sočasno z napredovanjem dezertifikacije upada delež rastlin C4 (npr. dreves) in narašča delež rastlin C3 (grmičevje in zeli)

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

BACKGROUND: The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. RESULTS: We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. CONCLUSION: As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential

Metal-organic framework derived hierarchical porous TiO2 nanopills as a super stable anode for Na-ion batteries

Hierarchical porous TiO2 nanopills were synthesized using a titanium metal-organic framework MIL-125(Ti) as precursor. The as-synthesized TiO2 nanopills owned a large specific surface area of 102 m2/g and unique porous structure. Furthermore, the obtained TiO2 nanopills were applied as anode materials for Na-ion batteries for the first time. The as-synthesized TiO2 nanopills achieved a high discharge capacity of 196.4 mAh/g at a current density of 0.1 A/g. A discharge capacity of 115.9 mAh/g was obtained at a high current density of 0.5 A/g and the capacity retention was remained as high as 90% even after 3000 cycles. The excellent electrochemical performance can be attributed to its unique hierarchical porous feature

miRecords: an integrated resource for microRNA–target interactions

MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords

SVRMHC prediction server for MHC-binding peptides

BACKGROUND: The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort. RESULTS: Recently, we demonstrated the appealing performance of SVRMHC, an SVR-based quantitative modeling method for peptide-MHC interactions, when applied to three mouse class I MHC molecules. Subsequently, we have greatly extended the construction of SVRMHC models and have established such models for more than 40 class I and class II MHC molecules. Here we present the SVRMHC web server for predicting peptide-MHC binding affinities using these models. Benchmarked percentile scores are provided for all predictions. The larger number of SVRMHC models available allowed for an updated evaluation of the performance of the SVRMHC method compared to other well- known linear modeling methods. CONCLUSION: SVRMHC is an accurate and easy-to-use prediction server for epitope-MHC binding with significant coverage of MHC molecules. We believe it will prove to be a valuable resource for T cell epitope researchers

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness

BACKGROUND: Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins. RESULTS: Using a distinctly large set of siRNA efficacy data assembled from a vast diversity of origins (the siRecords data, containing records of 3,277 siRNA experiments targeting 1,518 genes, derived from 1,417 independent studies), we conducted extensive analyses of all known features that have been implicated in increasing RNAi effectiveness. A number of features having positive impacts on siRNA efficacy were identified. By performing quantitative analyses on cooperative effects among these features, then applying a disjunctive rule merging (DRM) algorithm, we developed a bundle of siRNA design rule sets with the false positive problem well curbed. A comparison with 15 online siRNA design tools indicated that some of the rule sets we developed surpassed all of these design tools commonly used in siRNA design practice in positive predictive values (PPVs). CONCLUSION: The availability of the large and diverse siRNA dataset from siRecords and the approach we describe in this report have allowed the development of highly effective and generally applicable siRNA design rule sets. Together with ever improving RNAi lab techniques, these design rule sets are expected to make siRNAs a more useful tool for molecular genetics, functional genomics, and drug discovery studies

Meta-prediction of protein subcellular localization with reduced voting

Meta-prediction seeks to harness the combined strengths of multiple predicting programs with the hope of achieving predicting performance surpassing that of all existing predictors in a defined problem domain. We investigated meta-prediction for the four-compartment eukaryotic subcellular localization problem. We compiled an unbiased subcellular localization dataset of 1693 nuclear, cytoplasmic, mitochondrial and extracellular animal proteins from Swiss-Prot 50.2. Using this dataset, we assessed the predicting performance of 12 predictors from eight independent subcellular localization predicting programs: ELSPred, LOCtree, PLOC, Proteome Analyst, PSORT, PSORT II, SubLoc and WoLF PSORT. Gorodkin correlation coefficient (GCC) was one of the performance measures. Proteome Analyst is the best individual subcellular localization predictor tested in this four-compartment prediction problem, with GCC = 0.811. A reduced voting strategy eliminating six of the 12 predictors yields a meta-predictor (RAW-RAG-6) with GCC = 0.856, substantially better than all tested individual subcellular localization predictors (P = 8.2 × 10−6, Fisher's Z-transformation test). The improvement in performance persists when the meta-predictor is tested with data not used in its development. This and similar voting strategies, when properly applied, are expected to produce meta-predictors with outstanding performance in other life sciences problem domains

A Wide Bandwidth Circularly Polarized Microstrip Antenna Array Using Sequentially Rotated Feeding Technique

Abstract-A wide bandwidth circularly polarized microstrip antenna array using sequentially rotated feeding technique is presented in this paper. First a stacked microstrip antenna with tuning stub is designed, which meets wide bandwidth application. Then sequentially rotated feeding technique is introduced, basing on which a 4 element stacked microstrip antenna array with preferable axial ratio performance is achieved. The corresponding antenna array is fabricated and measured, the results of which shows that the antenna has the advantages of wide bandwidth, high gain and low axial radio, which has good application foreground