Predicting Ca2+ -binding sites using refined carbon clusters.

Identifying Ca(2+) -binding sites in proteins is the first step toward understanding the molecular basis of diseases related to Ca(2+) -binding proteins. Currently, these sites are identified in structures either through X-ray crystallography or NMR analysis. However, Ca(2+) -binding sites are not always visible in X-ray structures due to flexibility in the binding region or low occupancy in a Ca(2+) -binding site. Similarly, both Ca(2+) and its ligand oxygens are not directly observed in NMR structures. To improve our ability to predict Ca(2+) -binding sites in both X-ray and NMR structures, we report a new graph theory algorithm (MUG(C) ) to predict Ca(2+) -binding sites. Using carbon atoms covalently bonded to the chelating oxygen atoms, and without explicit reference to side-chain oxygen ligand co-ordinates, MUG(C) is able to achieve 94% sensitivity with 76% selectivity on a dataset of X-ray structures composed of 43 Ca(2+) -binding proteins. Additionally, prediction of Ca(2+) -binding sites in NMR structures was obtained by MUG(C) using a different set of parameters, which were determined by the analysis of both Ca(2+) -constrained and unconstrained Ca(2+) -loaded structures derived from NMR data. MUG(C) identified 20 of 21 Ca(2+) -binding sites in NMR structures inferred without the use of Ca(2+) constraints. MUG(C) predictions are also highly selective for Ca(2+) -binding sites as analyses of binding sites for Mg(2+) , Zn(2+) , and Pb(2+) were not identified as Ca(2+) -binding sites. These results indicate that the geometric arrangement of the second-shell carbon cluster is sufficient not only for accurate identification of Ca(2+) -binding sites in NMR and X-ray structures but also for selective differentiation between Ca(2+) and other relevant divalent cations.

A Special Ancient Bronze Sword and Its Possible Manufacturing Technique from Materials Science Analysis.

In this study, it was found that an ancient bronze sword had special microstructures, i.e., a tin (Sn)-rich layer (Sn: 38.51 wt.%), that was around 0.1-0.3 mm in thickness in the bronze substrate (Sn: 18.57 wt.%). This sword was unearthed from the same Chu tombs of the "Sword of Gou Jian", and dated back to the late Spring and Autumn Period (496 BC-464 BC). The experimental and theoretical analyses revealed that (1) the Sn-rich layer exhibited higher microhardness (around 650 HV) than the sword body (around 300 HV); (2) the Sn-rich layer showed a brittle fracture due to the formation of a large amount of α + δ eutectoid, while the sword body was of good toughness due to a large amount of α-Cu solid solution phase; and (3) theoretical calculations of Sn diffusion in the Cu substrate indicated that this Sn-rich layer could have been formed within several hours or several days if the temperature was above 600 °C. Therefore, this sword was proposed to be a novel kind of composite bronze sword, and the possible manufacturing technique was a surface treatment called "dip or wipe tinning" or tin amalgam, which was widely used in the Bronze Age. Technically, this process possesses more advantages than the well-known two-times casting for making the "double-colour" or bi-metallic composite bronze sword. This research showed that the materials processing level was beyond our expectations for ancient China 2500 years ago.

[Breathing waveform and respiratory ring in the role of mechanical ventilation].

To learn reading respiratory waveform and ring is a key step to good use of respirator, which will help clinicians to analyze the status of the use of respirator and real time changes in patient's lung mechanics from the changes of respiratory wave and ring, for making use of respirator reasonably, scientifically and objectively to provide advanced methods. This article only explains the physical basis of respiratory wave and ring.

Towards predicting Ca2+-binding sites with different coordination numbers in proteins with atomic resolution.

Ca(2+)-binding sites in proteins exhibit a wide range of polygonal geometries that directly relate to an equally-diverse set of biological functions. Although the highly-conserved EF-Hand motif has been studied extensively, non-EF-Hand sites exhibit much more structural diversity which has inhibited efforts to determine the precise location of Ca(2+)-binding sites, especially for sites with few coordinating ligands. Previously, we established an algorithm capable of predicting Ca(2+)-binding sites using graph theory to identify oxygen clusters comprised of four atoms lying on a sphere of specified radius, the center of which was the predicted calcium position. Here we describe a new algorithm, MUG (MUltiple Geometries), which predicts Ca(2+)-binding sites in proteins with atomic resolution. After first identifying all the possible oxygen clusters by finding maximal cliques, a calcium center (CC) for each cluster, corresponding to the potential Ca(2+) position, is located to maximally regularize the structure of the (cluster, CC) pair. The structure is then inspected by geometric filters. An unqualified (cluster, CC) pair is further handled by recursively removing oxygen atoms and relocating the CC until its structure is either qualified or contains fewer than four ligand atoms. Ligand coordination is then determined for qualified structures. This algorithm, which predicts both Ca(2+) positions and ligand groups, has been shown to successfully predict over 90% of the documented Ca(2+)-binding sites in three datasets of highly-diversified protein structures with 0.22 to 0.49 A accuracy. All multiple-binding sites (i.e. sites with a single ligand atom associated with multiple calcium ions) were predicted, as were half of the low-coordination sites (i.e. sites with less than four protein ligand atoms) and 14/16 cofactor-coordinating sites. Additionally, this algorithm has the flexibility to incorporate surface water molecules and protein cofactors to further improve the prediction for low-coordination and cofactor-coordinating Ca(2+)-binding sites.

Statistical analysis of structural characteristics of protein Ca2+-binding sites.

To better understand the biological significance of Ca(2+), we report a comprehensive statistical analysis of calcium-binding proteins from the Protein Data Bank to identify structural parameters associated with EF-hand and non-EF-hand Ca(2+)-binding sites. Comparatively, non-EF-hand sites utilize lower coordination numbers (6 +/- 2 vs. 7 +/- 1), fewer protein ligands (4 +/- 2 vs. 6 +/- 1), and more water ligands (2 +/- 2 vs. 1 +/- 0) than EF-hand sites. The orders of ligand preference for non-EF-hand and EF-hand sites, respectively, were H(2)O (33.1%) > side-chain Asp (24.5%) > main-chain carbonyl (23.9%) > side-chain Glu (10.4%), and side-chain Asp (29.7%) > side-chain Glu (26.6%) > main-chain carbonyl (21.4%) > H(2)O (13.3%). Less formal negative charge was observed in the non-EF-hand than in the EF-hand binding sites (1 +/- 1 vs. 3 +/- 1). Additionally, over 20% of non-EF-hand sites had formal charge values of zero due to increased utilization of water and carbonyl oxygen ligands. Moreover, the EF-hand sites presented a narrower range of ligand distances and bond angles than non-EF-hand sites, possibly owing to the highly conserved helix-loop-helix motif. Significant differences between ligand types (carbonyl, side chain, bidentate) demonstrated that angles associated with each type must be classified separately, and the EF-hand side-chain Ca-O-C angles exhibited an unusual bimodal quality consistent with an Asp distribution that differed from the Gaussian model observed for non-EF-hand proteins. The results of this survey more accurately describe differences between EF-hand and non-EF-hand proteins and provide new parameters for the prediction and design of different classes of Ca(2+)-binding proteins.

[Basic factors in choosing a respirator for neonates].

Based on the differences between respiration systems for adults and neonates, this article supposes that the respirator for newborn babies is largely different from that for children and adults. According to the characteristics of newborn babies respiratory systems, the article, further, points out some important factors which should be paid attention to, when buying the respirators.

Soil biochemical responses to nitrogen addition in a secondary evergreen broad-leaved forest ecosystem.

In order to investigate the effects of N deposition on soil biochemistry in secondary forests, one N addition experiment was conducted in a secondary evergreen broad-leaved forest in the western edge of Sichuan Basin, with the highest level of background N deposition (about 95 kg N ha-1 yr-1) in China. Three N treatment levels (+0, +50, +150 kg N ha-1 yr-1) were monthly added to soil surface in this forest beginning in April 2013. Soil biochemistry and root biomass of the 0-10 cm soil horizon were measured from May 2014 to April 2015. Soil respiration was measured for two years (September 2013 to August 2015). It was showed that N additions were correlated to significantly lower soil pH, microbial biomass C (MBC) concentration, MBC/microbial biomass N (MBN) ratio, root biomass, and soil respiration rate, and significantly higher concentrations of ammonium (NH4+) and nitrate (NO3-). These results indicate that N additions had a significant effect on the size of soil microbial community. In addition, soil C storage may potentially increase due to the dropped soil C release under N addition.

Predicting calcium-binding sites in proteins - a graph theory and geometry approach.

Identifying calcium-binding sites in proteins is one of the first steps towards predicting and understanding the role of calcium in biological systems for protein structure and function studies. Due to the complexity and irregularity of calcium-binding sites, a fast and accurate method for predicting and identifying calcium-binding protein is needed. Here we report our development of a new fast algorithm (GG) to detect calcium-binding sites. The GG algorithm uses a graph theory algorithm to find oxygen clusters of the protein and a geometric algorithm to identify the center of these clusters. A cluster of four or more oxygen atoms has a high potential for calcium binding. High performance with about 90% site sensitivity and 80% site selectivity has been obtained for three datasets containing a total of 123 proteins. The results suggest that a sphere of a certain size with four or more oxygen atoms on the surface and without other atoms inside is necessary and sufficient for quickly identifying the majority of the calcium-binding sites with high accuracy. Our finding opens a new avenue to visualize and analyze calcium-binding sites in proteins facilitating the prediction of functions from structural genomic information.

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Building a web-based tool to support clinical decisions in the control of Chlamydia trachomatis and Neisseria gonorrhoeae infections.

Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) are the agents of two common, sexually transmitted diseases afflicting women in the United States (http://www.cdc.gov). We designed a novel web-based application that offers simple recommendations to help optimize medical outcomes with CT and GC prevention and control programs. This application takes population groups, prevalence rates, parameters for available screening assays and treatment regimens (costs, sensitivity, and specificity), as well as budget limits as inputs. Its output suggests optimal screening and treatment strategies for selected at-risk groups, commensurate with the clinic's budget allocation. Development of this tool illustrates how a clinical informatics application based on rigorous mathematics might have a significant impact on real-world clinical issues.

Integration of Diverse Research Methods to Analyze and Engineer Ca-Binding Proteins: From Prediction to Production.

In recent years, increasingly sophisticated computational and bioinformatics tools have evolved for the analyses of protein structure, function, ligand interactions, modeling and energetics. This includes the development of algorithms to recursively evaluate side-chain rotamer permutations, identify regions in a 3D structure that meet some set of search parameters, calculate and minimize energy values, and provide high-resolution visual tools for theoretical modeling. Here we discuss the interdependency between different areas of bioinformatics, the evolution of different algorithm design approaches, and finally the transition from theoretical models to real-world design and application as they relate to Ca(2+)-binding proteins. Within this context, it has become evident that significant pre-experimental design and calculations can be modeled through computational methods, thus eliminating potentially unproductive research and increasing our confidence in the correlation between real and theoretical models. Moving from prediction to production, it is anticipated that bioinformatics tools will play an increasingly significant role in research and development, improving our ability to both understand the physiological roles of Ca(2+) and other metals and to extend that knowledge to the design of function-specific synthetic proteins capable of fulfilling different roles in medical diagnostics and therapeutics.

Analysis and prediction of calcium-binding pockets from apo-protein structures exhibiting calcium-induced localized conformational changes.

Calcium binding in proteins exhibits a wide range of polygonal geometries that relate directly to an equally diverse set of biological functions. The binding process stabilizes protein structures and typically results in local conformational change and/or global restructuring of the backbone. Previously, we established the MUG program, which utilized multiple geometries in the Ca(2+)-binding pockets of holoproteins to identify such pockets, ignoring possible Ca(2+)-induced conformational change. In this article, we first report our progress in the analysis of Ca(2+)-induced conformational changes followed by improved prediction of Ca(2+)-binding sites in the large group of Ca(2+)-binding proteins that exhibit only localized conformational changes. The MUG(SR) algorithm was devised to incorporate side chain torsional rotation as a predictor. The output from MUG(SR) presents groups of residues where each group, typically containing two to five residues, is a potential binding pocket. MUG(SR) was applied to both X-ray apo structures and NMR holo structures, which did not use calcium distance constraints in structure calculations. Predicted pockets were validated by comparison with homologous holo structures. Defining a "correct hit" as a group of residues containing at least two true ligand residues, the sensitivity was at least 90%; whereas for a "correct hit" defined as a group of residues containing at least three true ligand residues, the sensitivity was at least 78%. These data suggest that Ca(2+)-binding pockets are at least partially prepositioned to chelate the ion in the apo form of the protein.

Applying a mixed-integer program to model re-screening women who test positive for C. trachomatis infection.

We proposed a mixed-integer program to model the management of C. trachomatis infections in women visiting publicly funded family planning clinics. We intended to maximize the number of infected women cured of C. trachomatis infections. The model incorporated screening, re-screening, and treatment options for three age groups with respective age-specific C. trachomatis infection and re-infection rates, two possible test assays, and two possible treatments. Our results showed the total budget had a great impact on the optimal strategy incorporating screening coverage, test selection, and treatment. At any budget level, the strategy that used a relatively small per-patient budget increase to re-screen all women who tested positive 6 months earlier always resulted in curing more infected women and more cost-saving than the strategy that was optimal under the condition of not including a re-screening option.