Physiochemical Information Research Articles

Luminescence-Based Infrared Thermal Sensors: Comprehensive Insights.

Recent chronological breakthroughs in materials innovation, their fabrication, and structural designs for disparate applications have paved transformational ways to subversively digitalize infrared (IR) thermal imaging sensors from traditional to smart. The noninvasive IR thermal imaging sensors are at the cutting edge of developments, exploiting the abilities of nanomaterials to acquire arbitrary, targeted, and tunable responses suitable for integration with host materials and devices, intimately disintegrate variegated signals from the target onto depiction without any discomfort, eliminating motional artifacts and collects precise physiological and physiochemical information in natural contexts. Highlighting several typical examples from recent literature, this review article summarizes an accessible, critical, and authoritative summary of an emerging class of advancement in the modalities of nano and micro-scale materials and devices, their fabrication designs and applications in infrared thermal sensors. Introduction is begun covering the importance of IR sensors, followed by a survey on sensing capabilities of various nano and micro structural materials, their design architects, and then culminating an overview of their diverse application swaths. The review concludes with a stimulating frontier debate on the opportunities, difficulties, and future approaches in the vibrant sector of infrared thermal imaging sensors.

Acupoit is the "transducer" in the physiochemical information coupling response of acupuncture

Acupoint is the initial response site of acupuncture stimulus and also the source link of the effect onset of acupuncture. Acupuncture is a mechanical physical stimulus. How is the mechanical force of acupuncture transduced into neuroelectrical and biochemical signals at acupoint? How does the physiochemical information of acupoint launch acupuncture effect? All of these remain the common and crucial questions in the study of acupuncture effect mechanism. Physical changes are induced in the local tissue of acupoint by needling techniques, such as the deformation and displacement of muscle fibers, which may act on the nerve ending receptors and produce electroneurographic signals. Besides, these changes may activate the mechanosensitive ion channels of the cytomembrane in acupoint site. Through cellular signal transduction, the physical signals may be transformed into chemical ones to trigger the physiochemical coupling response of acupoint microenvironment. Eventually, acupuncture effect is generated via nerves and body fluids. "The mechanical force of acupuncture", through "the physiochemical transduction", promotes the body's perception and transmits acupuncture signals. It suggests that acupoint is the "transducer" in the physiochemical information coupling response of acupuncture.

Random Forest-Based Compound ATC Classification Using Structural and Physiochemical Information

Random Forest-Based Compound ATC Classification Using Structural and Physiochemical Information

QSAR modeling the toxicity of pesticides against Americamysis bahia

The widespread use of pesticides has received increasing attention in regulatory agencies because their extensive overuse and various adverse effects on all living organisms. Organizations such as EPA and ECHA have published laws that pesticides should be fully evaluated before bring them to market. In the present study, we evaluated the pesticides toxicity using the Quantitative Structural-Activity Relationship (QSAR) method. The models for the single class pesticides (herbicides, insecticides and fungicides) as well as the general class pesticides (the combined dataset plus some microbicides, molluscicides, etc.) were developed using the Genetic Algorithm and Multiple Linear Regression method. The internal and external validation results suggested that all the obtained models were stable and predictive. According to the modeling descriptors, the lipophilic descriptors contributed positively while all the electrotopological state descriptors showed a negative contribution, their presences in every model verified the conspicuous influence of molecular lipophilicity and hydrophilicity on the pesticides toxicity. However, the influence of topological structure descriptors was different and varies with the physiochemical information they encode. Finally, the models presented in this paper would help assess the pesticides toxicity against Americamysis bahia, shorten test time, and reduce the cost of pesticides risk assessment.

Modeling pesticides toxicity to Sheepshead minnow using QSAR.

Nowadays, the environmental risk caused by the widespread use of pesticides and their ubiquitous residuals has received more and more attention in academia and regulatory agencies. Due to the large number of pesticides used in agriculture and their adverse effects on all living organisms and the numerous end-points, it is necessary to employ the in silico tools to quickly highlight hazardous pesticides. In this study, we have evaluated the toxicity of pesticides against Sheepshead minnow with the Quantitative Structure-Activity Relationship (QSAR) approach. The models for the specific-type (insecticides, herbicides and fungicides) as well as the general-type (combing all the specific-type pesticides and some microbicides, nematicides, etc.) pesticides were developed using the Genetic Algorithm and the Multiple Linear Regression method, subsequently validated with various metrics. The validation results suggested that the obtained models were highly robust, externally predictive and characterized by a broad applicability domain. Considering the modeling descriptors, the toxicity of pesticides would increase with the lipophilicity and decrease with the polarity and hydrophilicity. Most electrotopological state descriptors contribute negatively to the toxicity, while the influence of topological structure descriptors mainly depends on the physiochemical information they encode. The models proposed in this paper would be useful in filling the data gaps, prioritizing and then focusing experiments on more hazardous pesticides.

PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.

The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics.

A hybrid land use regression/line-source dispersion model for predicting intra-urban NO2

Land use regression (LUR) has evolved as a standard tool for estimating intra-urban variation in long-term air pollution exposures. LUR, however, generally relies on observed spatial relationships between distributed sources and pollution measures, rather than meteorological or physio-chemical information. Incorporating traffic-meteorological interaction information into LURs via dispersion models may improve accuracy and physical interpretability. To examine whether deterministic dispersion output improves LUR predictions for nitrogen dioxide (NO2), we incorporated hourly Caline3QHCR dispersion information into existing winter-time regression models originally designed to disentangle effects of multiple sources (e.g., legacy industry, vehicle traffic) and concentration modifiers (e.g., elevation) across Pittsburgh, PA. Caline3QHCR output improved overall cross-validated R2 values by 0.10, 0.03, and 0.05 for the weekday, full-week, and merged years models, respectively. The addition of Caline3 output as an independent covariate effectively displaced two road-specific predictors, one built environment predictor and one meteorological predictor across two winter-season models. The incorporation of study-specific dispersion principles may corroborate overall LUR model interpretability and could be applied similarly to preexisting LUR models that lack strong source-concentration relationships. Model improvements were observed at sites with relatively higher NO2 concentrations that exhibited higher traffic volumes and were in closer proximity to roadways (<300m), which may have an important bearing towards better characterizing exposures in both near-roadway and high-traffic environments.

Cross-species conservation of complementary amino acid-ribonucleobase interactions and their potential for ribosome-free encoding.

The role of amino acid-RNA nucleobase interactions in the evolution of RNA translation and protein-mRNA autoregulation remains an open area of research. We describe the inference of pairwise amino acid-RNA nucleobase interaction preferences using structural data from known RNA-protein complexes. We observed significant matching between an amino acid’s nucleobase affinity and corresponding codon content in both the standard genetic code and mitochondrial variants. Furthermore, we showed that knowledge of nucleobase preferences allows statistically significant prediction of protein primary sequence from mRNA using purely physiochemical information. Interestingly, ribosomal primary sequences were more accurately predicted than non-ribosomal sequences, suggesting a potential role for direct amino acid-nucleobase interactions in the genesis of amino acid-based ribosomal components. Finally, we observed matching between amino acid-nucleobase affinities and corresponding mRNA sequences in 35 evolutionarily diverse proteomes. We believe these results have important implications for the study of the evolutionary origins of the genetic code and protein-mRNA cross-regulation.

P77 Creation and Evaluation of a 2D/3D Molecular Database for Drugs Used to Target the Respiratory System

BackgroundHealthcare students and professionals could benefit greatly from using a holistic drug database as a reference point for clinical, physiochemical and structural information.1 The involvement of certain drug therapy in...

Diversity and distribution of sulfate-reducing bacteria in four petroleum reservoirs detected by using 16S rRNA and dsrAB genes

Microbial sulfate reduction, an important metabolic process in petroleum reservoirs, is widely known as a major contributor to microbial influenced corrosion and deterioration of oil quality. To better control oil field corrosion and oil degradation caused by the sulfate-reducing bacteria (SRBs), the community structure and composition of SRBs in four oil reservoirs were investigated in this study by comparing clone libraries of 16S rRNA and dissimilatory sulfate reductase (dsrAB) genes. In addition, canonical correspondence analysis (CCA) was also employed to find relationship between biodata and physiochemical information. More information on SRB communities was obtained from nested-PCR-phylogenetic analyses of 16S rRNA genes and PCR primer sets amplifying six groups of SRBs frequently detected in oilfields all over the world were used. Amplified sequences belonging to Desulfotomaculum and Desulfobacter were the most dominant in all four reservoirs. The diversity of SRB communities increased while the temperature of the four oil reservoirs decreased from 63 to 21. Correlations between environmental variables and species distribution indicated that Desulfotomaculum was correlated with temperature, depth, and the concentration of acetate, propionate and sulphate. Desulfomicrobium, Desulfobacter and Desulfobulbus showed positive correlation with sulphur and salinity. Desulfobacterium was influenced by both salinity and the concentration of acetate. The results of this study provided important information on the microbial ecology of sulfate-reducing bacteria in different petroleum reservoirs.

MotViz: A Tool for Sequence Motif Prediction in Parallel to Structural Visualization and Analyses

Linking similar proteins structurally is a challenging task that may help in finding the novel members of a protein family. In this respect, identification of conserved sequence can facilitate understanding and classifying the exact role of proteins. However, the exact role of these conserved elements cannot be elucidated without structural and physiochemical information. In this work, we present a novel desktop application MotViz designed for searching and analyzing the conserved sequence segments within protein structure. With MotViz, the user can extract a complete list of sequence motifs from loaded 3D structures, annotate the motifs structurally and analyze their physiochemical properties. The conservation value calculated for an individual motif can be visualized graphically. To check the efficiency, predicted motifs from the data sets of 9 protein families were analyzed and MotViz algorithm was more efficient in comparison to other online motif prediction tools. Furthermore, a database was also integrated for storing, retrieving and performing the detailed functional annotation studies. In summary, MotViz effectively predicts motifs with high sensitivity and simultaneously visualizes them into 3D strucures. Moreover, MotViz is user-friendly with optimized graphical parameters and better processing speed due to the inclusion of a database at the back end. MotViz is available at http://www.fi-pk.com/motviz.html.

Adaptive GDDA-BLAST: fast and efficient algorithm for protein sequence embedding.

A major computational challenge in the genomic era is annotating structure/function to the vast quantities of sequence information that is now available. This problem is illustrated by the fact that most proteins lack comprehensive annotations, even when experimental evidence exists. We previously theorized that embedded-alignment profiles (simply “alignment profiles” hereafter) provide a quantitative method that is capable of relating the structural and functional properties of proteins, as well as their evolutionary relationships. A key feature of alignment profiles lies in the interoperability of data format (e.g., alignment information, physio-chemical information, genomic information, etc.). Indeed, we have demonstrated that the Position Specific Scoring Matrices (PSSMs) are an informative M-dimension that is scored by quantitatively measuring the embedded or unmodified sequence alignments. Moreover, the information obtained from these alignments is informative, and remains so even in the “twilight zone” of sequence similarity (<25% identity) [1]–[5]. Although our previous embedding strategy was powerful, it suffered from contaminating alignments (embedded AND unmodified) and high computational costs. Herein, we describe the logic and algorithmic process for a heuristic embedding strategy named “Adaptive GDDA-BLAST.” Adaptive GDDA-BLAST is, on average, up to 19 times faster than, but has similar sensitivity to our previous method. Further, data are provided to demonstrate the benefits of embedded-alignment measurements in terms of detecting structural homology in highly divergent protein sequences and isolating secondary structural elements of transmembrane and ankyrin-repeat domains. Together, these advances allow further exploration of the embedded alignment data space within sufficiently large data sets to eventually induce relevant statistical inferences. We show that sequence embedding could serve as one of the vehicles for measurement of low-identity alignments and for incorporation thereof into high-performance PSSM-based alignment profiles.

RESEARCH PROGRESS ON PREDICTION MODELS FOR PHYSICAL PROPERTIES OF IONIC LIQUID

The field of ionic liquid has gained rapid growth in recent years and occupied a forefront in green chemistry. As a useful instrument to the research and development of novel ionic liquids, the physical properties are of utmost importance. Thus, great efforts have been made to obtain these important data, as it is far from getting sufficient physiochemical information for intensive and extensive investigation which consequently becomes a bottleneck for the theoretical and applicable research of ionic liquids. Additionally, with the given immeasurable possible ionic liquids by various cation and anion combinations, it is an impossible task to find an ideal ionic liquid with desired physical properties using conventionally "try and error" process. For these reasons, exploration of novel prediction models for physical properties of ionic liquid is imperative. This paper gives an overview of recent progress of various prediction models.

Synthesis, characterization and physiochemical information, along with antimicrobial studies of some metal complexes derived from an ON donor semicarbazone ligand

Eight new transition metal complexes of benzaldehyde-N(4)-phenylsemicarbazone have been synthesized and characterized by elemental analyses, molar conductance, electronic and infrared spectral studies. In all the complexes, the semicarbazone is coordinated as neutral bidentate ligand. (1)H NMR spectrum of [Zn(HL)(2)(OAc)(2)] shows that there is no enolisation of the ligand in the complex. The magnetic susceptibility measurements indicate that Cr(III), Mn(II), Fe(III), Co(II) and Cu(II) complexes are paramagnetic and Ni(II) is diamagnetic. The EPR spectrum of [Mn(HL)(2)(OAc)(2)] in DMF solution at 77K shows hyperfine sextet with low intensity forbidden lines lying between each of the two main hyperfine lines. The g values calculated for the [Cu(HL)(2)SO(4)] complex in frozen DMF, indicate the presence of unpaired electron in the d(x)(2) - (y)(2) orbital. The metal ligand bonding parameters evaluated showed strong in-plane sigma bonding and in-plane pi bonding. The ligand and complexes were screened for their possible antimicrobial activities.

SP ORCalc: A development of a database analysis that provides putative metabolic enzyme reactions for ligand-based drug design

Understanding both the enzyme reactions that contribute to intermediate metabolism and the biochemical fate of candidate therapeutic and toxic agents are essential for drug design. Traditional metabolic databases indicate whether reactions have been observed but do not provide the likelihoods of reactions occurring, for example those of mixed function oxygenases and oxidases, during phase I metabolism. The desire for more quantitative predictions motivated the development of the recently introduced Substrate Product Occurrence Ratio Calculator (SP ORCalc) that identifies metabolically labile atom positions in candidate compounds. This paper describes a further development and provides a clearer explanation of SP ORCalc for the computational pharmacology, medicinal chemistry and drug design communities interested in metabolic prediction of xenobiotics using chemical databases of biotransformations. Examples of reaction centre detection in Metabolite™ are described followed by a demonstration of almokalant, an anti-arrhythmic agent, undergoing phase I metabolism. In general, occurrence ratio ( OR) values are calculated throughout a compound and its transformed metabolites to give propensity ( p) values at each atom position. The OR values from substrates and products in the database are essential for addition and elimination reactions. For almokalant, the resulting p values ranged from 10 −1 to 10 −5 and their order of magnitude reflected the known and experimentally observed metabolites. SP ORCalc depends entirely on the level of detail from isoform- or species-specific reaction classes in Metabolite™. Labile atom positions (sites of metabolism) are identified in both the candidate compound and its metabolites. In general, the likelihood of one enzyme isoform-dependent reaction occurring relative to another and the putative metabolic routes from different isoforms can be investigated. SP ORCalc can be developed further to include suitable three-dimensional, structure–activity and physiochemical information.

A finite element model for protein transport in vivo

BackgroundBiological mass transport processes determine the behavior and function of cells, regulate interactions between synthetic agents and recipient targets, and are key elements in the design and use of biosensors. Accurately predicting the outcomes of such processes is crucial to both enhancing our understanding of how these systems function, enabling the design of effective strategies to control their function, and verifying that engineered solutions perform according to plan.MethodsA Galerkin-based finite element model was developed and implemented to solve a system of two coupled partial differential equations governing biomolecule transport and reaction in live cells. The simulator was coupled, in the framework of an inverse modeling strategy, with an optimization algorithm and an experimental time series, obtained by the Fluorescence Recovery after Photobleaching (FRAP) technique, to estimate biomolecule mass transport and reaction rate parameters. In the inverse algorithm, an adaptive method was implemented to calculate sensitivity matrix. A multi-criteria termination rule was developed to stop the inverse code at the solution. The applicability of the model was illustrated by simulating the mobility and binding of GFP-tagged glucocorticoid receptor in the nucleoplasm of mouse adenocarcinoma.ResultsThe numerical simulator shows excellent agreement with the analytic solutions and experimental FRAP data. Detailed residual analysis indicates that residuals have zero mean and constant variance and are normally distributed and uncorrelated. Therefore, the necessary and sufficient criteria for least square parameter optimization, which was used in this study, were met.ConclusionThe developed strategy is an efficient approach to extract as much physiochemical information from the FRAP protocol as possible. Well-posedness analysis of the inverse problem, however, indicates that the FRAP protocol provides insufficient information for unique simultaneous estimation of diffusion coefficient and binding rate parameters. Care should be exercised in drawing inferences, from FRAP data, regarding concentrations of free and bound proteins, average binding and diffusion times, and protein mobility unless they are confirmed by long-range Markov Chain-Monte Carlo (MCMC) methods and experimental observations.

Helicobacter pylorispecific immune response induced by conservative flagellin linear B-cell epitope

To testify the immunogenicity of a conservative B-cell linear epitope of Helicobacter pylori (H pylori) flagellin A. Different programs were used to analyze the secondary structure, molecular hydropathy, and surface accessibility of H pylori flagellin A. Linear B-cell epitopes were estimated based on the structural and physiochemical information. Analysis of residue divergence was proposed to screen a conservative linear epitope. The 29-peptide (Pep29mer) synthesized by chemical method, including the predicted conservative B-cell epitope and a known K2d compatible T-cell epitope, was used to immunize mice, and then H pylori-specific antibodies were detected by ELISA. Based on the analyses of divergent amino acid residues, structural and physiochemical characteristics, it was strongly suggested that the short fragment NDSDGR was the core of a conservative linear epitope in flagellin A. Animals immunized by Pep29mer acquired efficient immune response. In detail, serum H pylori-specific IgA and IgG1 increased significantly in immunized group, while IgG2a only had an insignificant change. H pylori-specific IgA in gastrointestinal flushing fluid also increased significantly. The conservative short fragment NDSDGR is the core of a linear B-cell epitope of flagellin A.

Nondestructive Localization of Surface Particles for Elemental Compositional Analysis by TOF-SIMS

A surface particle localization system based on oblique angle dark field optical scattering has been incorporated into time-of-flight secondary ion mass spectrometry. (TOF-SIMS) In this design, oblique incident laser light would be scattered to all directions by surface particles on silicon wafer and be collected at oblique angle to determine the x-y coordinate of the particle detected. This fast and nondestructive technique is an effective alternative to the standard method for imaging and localization of surface particles using primary ion bombardment by TOF-SIMS which might result in the alteration or loss of physiochemical information from the surface particles. (C) 2005 The Electrochemical Society.

Magnetic Resonance Imaging of the Orbit

Magnetic resonance has twin capabilities. It can provide anatomical (magnetic resonance imaging, MRI) and physiochemical (magnetic resonance spectroscopy) information. Nuclei with an odd mass number, particularly hydrogen in free water, have electromagnetic properties. When placed in a strong static magnetic field and excited by radiofrequency waves of a specific wavelength, these nuclei emit a signal. The MR signal can then be digitized, stored in a computer, and subsequently converted into an image. Factors that affect these images are tissue parameters (T1 and T2 time constants, proton density, and flow) and radiofrequency pulse sequences. Surface coils are useful for improving images of the orbit. The magnet can have a major and potentially dangerous influence on the surrounding environment, and access to the MRI area must be carefully controlled. Shielding of the MRI room prevents external factors from adversely affecting the MRI unit and the images produced.

The viscosity-temperature function of blood serum and its physio-chemical information content.

There are several types of illness leading to changes in the viscosity of blood, plasma or serum. Determination of the viscosity alone, therefore, will not make possible an unambiguous diagnosis of any particular complaint. However, determination of