HSPiP and QbD Program-Based Analytical Method Development and Validation to Quantify Ketoconazole in Dermatokinetic Study.

Ketoconazole (KTZ) is the most potential azole anti-mycotic drug. The quantification of KTZ from various layers of the skin after topical application of lipidic nanocarriers is critical. We addressed a sensitive, specific, simple, rapid, reproducible, and economic analytical method to quantify KTZ from the treated skin homogenate using the Hansen solubility parameter (HSP, HSPiP software)-based modeling and experimental design. The software provided various HSP values for KTZ and solvents to compose the mobile phase. The Taguchi model identified the significant sets of factors to develop a robust bioanalytical method with reduced variability. In the optimization, acetonitrile (ACN) concentration (X1 as A) and the pH of mobile phase (X2 as B) were two factors against two responses (Y1: peak area and Y2: retention time). The HPLC (high-performance liquid chromatography) method validation was carried out based on US-FDA guidelines for the developed KTZ formulations (suspension, solid nanoparticles, and commercial product) extracted from the treated rat skin. The experimental solubility of KTZ was found to be maximum in the two solvents (ACN and ethyl acetate), based on HSP values. Surface response methodology (SRM) identified remarkable impact of ACN concentration and the mobile phase pH on the peak area and retention time. Analytical limits (0.17 and 0.50 µg/mL) were established for KTZ-SLNs (extracted from the skin). The method was implemented with high reproducibility, accuracy, and selectivity to quantify KTZ from the treated rat skin.

Automated chronic wounds medical assessment and tracking framework based on deep learning.

Chronic wounds are a latent health problem worldwide, due to high incidence of diseases such as diabetes and Hansen. Typically, wound evolution is tracked by medical staff through visual inspection, which becomes problematic for patients in rural areas with poor transportation and medical infrastructure. Alternatively, the design of software platforms for medical imaging applications has been increasingly prioritized. This work presents a framework for chronic wound tracking based on deep learning, which works on RGB images captured with smartphones, avoiding bulky and complicated acquisition setups. The framework integrates mainstream algorithms for medical image processing, including wound detection, segmentation, as well as quantitative analysis of area and perimeter. Additionally, a new chronic wounds dataset from leprosy patients is provided to the scientific community. Conducted experiments demonstrate the validity and accuracy of the proposed framework, with up to 84.5% in precision.

A rush to explore protein-ligand electrostatic interaction energy with Charger.

The mutual penetration of electron densities between two interacting molecules complicates the computation of an accurate electrostatic interaction energy based on a pseudo-atom representation of electron densities. The numerical exact potential and multipole moment (nEP/MM) method is time-consuming since it performs a 3D integration to obtain the electrostatic energy at short interaction distances. Nguyen et al. [(2018), Acta Cryst. A74, 524-536] recently reported a fully analytical computation of the electrostatic interaction energy (aEP/MM). This method performs much faster than nEP/MM (up to two orders of magnitude) and remains highly accurate. A new program library, Charger, contains an implementation of the aEP/MM method. Charger has been incorporated into the MoProViewer software. Benchmark tests on a series of small molecules containing only C, H, N and O atoms show the efficiency of Charger in terms of execution time and accuracy. Charger is also powerful in a study of electrostatic symbiosis between a protein and a ligand. It determines reliable protein-ligand interaction energies even when both contain S atoms. It easily estimates the individual contribution of every residue to the total protein-ligand electrostatic binding energy. Glutathione transferase (GST) in complex with a benzophenone ligand was studied due to the availability of both structural and thermodynamic data. The resulting analysis highlights not only the residues that stabilize the ligand but also those that hinder ligand binding from an electrostatic point of view. This offers new perspectives in the search for mutations to improve the interaction between the two partners. A proposed mutation would improve ligand binding to GST by removing an electrostatic obstacle, rather than by the traditional increase in the number of favourable contacts.

Solubility-physicochemical-thermodynamic theory of penetration enhancer mechanism of action.

The hypothesis for the investigation was that the overall mechanism of action of skin penetration enhancers is best explained by the Solubility-Physicochemical-Thermodynamic (SPT) theory. To our knowledge, this is the first report of the application of SPT theory in transdermal/topical/enhancer research. The SPT theory puts forward the concept that the mode of action of enhancers is related to solubility parameters, physicochemical interactions and thermodynamic activity. This paper discusses these concepts by using experimentally derived permeation data, various physicochemical and solubility parameters (ingredient active gap (IAG), ingredient skin gap (ISG), solubility of active in the formulation (SolV) and the formulation solubility in the skin (SolS)) generated by using FFE (Formulating for Efficacy™ - ACT Solutions Corp) software. These studies suggest that there is an inverse relationship between measured flux and IAG values given that there is an optimum ingredient skin gap, SolV and SolS ratio. The study demonstrated that the flux is actually proportional to a gradient of thermodynamic activity rather than the concentration and maximum skin penetration and deposition can be achieved when the drug is at its highest thermodynamic activity.

Bayesian inference of ancestral dates on bacterial phylogenetic trees.

The sequencing and comparative analysis of a collection of bacterial genomes from a single species or lineage of interest can lead to key insights into its evolution, ecology or epidemiology. The tool of choice for such a study is often to build a phylogenetic tree, and more specifically when possible a dated phylogeny, in which the dates of all common ancestors are estimated. Here, we propose a new Bayesian methodology to construct dated phylogenies which is specifically designed for bacterial genomics. Unlike previous Bayesian methods aimed at building dated phylogenies, we consider that the phylogenetic relationships between the genomes have been previously evaluated using a standard phylogenetic method, which makes our methodology much faster and scalable. This two-step approach also allows us to directly exploit existing phylogenetic methods that detect bacterial recombination, and therefore to account for the effect of recombination in the construction of a dated phylogeny. We analysed many simulated datasets in order to benchmark the performance of our approach in a wide range of situations. Furthermore, we present applications to three different real datasets from recent bacterial genomic studies. Our methodology is implemented in a R package called BactDating which is freely available for download at https://github.com/xavierdidelot/BactDating.

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens.

Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request.

Effects of acid diffusibility and affinity to cellulose on strength loss of polycarboxylic acid crosslinked fabrics.

1,2,3,4-Butanetetracarboxylic acid (BTCA) imparts good anti-wrinkle property to cotton fabrics and results in significant strength loss due to cross-linking and acid degradation of cellulose simultaneously. However, benzophenone-3,3',4,4'- tetracarboxylic acid (BPTCA), an aromatic acid, crosslinks cellulose effectively but causes less strength loss to the products under similar conditions. The difference in damages to cellulose fibers was analyzed by using diffusibility and corresponding affinity of the acids to cellulose fibers, which were estimated by their molecular sizes and Hansen solubility parameters (HSP). Both experimental results and theoretical speculations revealed consistent agreement, indicating that smaller acid molecules could diffuse into cellulose fiber more rapidly and deeply, resulting in more acid degradation. Besides, the aliphatic acid such as BTCA has higher molecular affinity than BPTCA to cellulose, causing additional more degradation of cellulose. Both factors are potential reasons of the observed more severe tensile strength loss of the BTCA treated cotton fabrics.

Impact of arterial input function selection on the accuracy of dynamic contrast-enhanced MRI quantitative analysis for the diagnosis of clinically significant prostate cancer.

PURPOSE: Using a limited temporal resolution dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) dataset to assess the impact of the arterial input function (AIF) choice on the transfer constant (K(trans) ) to distinguish prostate carcinoma (PCa) from benign tissue. MATERIALS AND METHODS: Thirty-eight patients with clinically important peripheral PCa (≥0.5 cc) were retrospectively studied. These patients underwent 1.5T multiparametric prostate MR with PCa and benign regions of interest (ROIs) selected using a visual registration with morphometric reconstruction obtained from radical prostatectomy. Using three pharmacokinetic (PK) analysis software programs, the mean K(trans) of ROIs was computed using three AIFs: an individual AIF (Ind-AIF) and two literature population average AIFs of Weinmann (W-AIF) and of Fritz-Hansen (FH-AIF). A pairwise comparison of the area under the receiver operating characteristic curves (AUROCC) obtained with different AIFs was performed. RESULTS: AUROCCs obtained with W-AIF (ranging from 0.801 to 0.843) were significantly higher than FH-AIF (ranging from 0.698 to 0.780, 0.002 ≤ P ≤ 0.045) and similar to or higher than Ind-AIF (ranging from 0.591 to 0.839, 0.014 ≤ P ≤ 0.9). Ind-AIF and FH-AIF provided similar AUROCC (0.34 ≤ P ≤ 0.81). The pairwise correlation of K(trans) values was moderate to very strong when comparing W-AIF with FH-AIF (the Spearman's correlation coefficients [SCCs] ranged from 0.55 to 0.93) and very weak to moderate when comparing W-AIF with Ind-AIF (the SCCs ranged from 0.018 to 0.59) or FH-AIF with Ind-AIF (the SCCs ranged from 0.30 to 0.51). CONCLUSION: W-AIF yielded a higher performance than FH-AIF and a similar or higher performance than Ind-AIF in distinguishing PCa from benign tissue.

MycoCAP - Mycobacterium Comparative Analysis Platform.

Mycobacterium spp. are renowned for being the causative agent of diseases like leprosy, Buruli ulcer and tuberculosis in human beings. With more and more mycobacterial genomes being sequenced, any knowledge generated from comparative genomic analysis would provide better insights into the biology, evolution, phylogeny and pathogenicity of this genus, thus helping in better management of diseases caused by Mycobacterium spp.With this motivation, we constructed MycoCAP, a new comparative analysis platform dedicated to the important genus Mycobacterium. This platform currently provides information of 2108 genome sequences of at least 55 Mycobacterium spp. A number of intuitive web-based tools have been integrated in MycoCAP particularly for comparative analysis including the PGC tool for comparison between two genomes, PathoProT for comparing the virulence genes among the Mycobacterium strains and the SuperClassification tool for the phylogenic classification of the Mycobacterium strains and a specialized classification system for strains of Mycobacterium abscessus. We hope the broad range of functions and easy-to-use tools provided in MycoCAP makes it an invaluable analysis platform to speed up the research discovery on mycobacteria for researchers. Database URL: http://mycobacterium.um.edu.my.

MycoBASE: expanding the functional annotation coverage of mycobacterial genomes.

BACKGROUND: Central to most omic scale experiments is the interpretation and examination of resulting gene lists corresponding to differentially expressed, regulated, or observed gene or protein sets. Complicating interpretation is a lack of functional annotation assigned to a large percentage of many microbial genomes. This is particularly noticeable in mycobacterial genomes, which are significantly divergent from many of the microbial model species used for gene and protein functional characterization, but which are extremely important clinically. Mycobacterial species, ranging from M. tuberculosis to M. abscessus, are responsible for deadly infectious diseases that kill over 1.5 million people each year across the world. A better understanding of the coding capacity of mycobacterial genomes is therefore necessary to shed increasing light on putative mechanisms of virulence, pathogenesis, and functional adaptations. DESCRIPTION: Here we describe the improved functional annotation coverage of 11 important mycobacterial genomes, many involved in human diseases including tuberculosis, leprosy, and nontuberculous mycobacterial (NTM) infections. Of the 11 mycobacterial genomes, we provide 9899 new functional annotations, compared to NCBI and TBDB annotations, for genes previously characterized as genes of unknown function, hypothetical, and hypothetical conserved proteins. Functional annotations are available at our newly developed web resource MycoBASE (Mycobacterial Annotation Server) at strong.ucdenver.edu/mycobase. CONCLUSION: Improved annotations allow for better understanding and interpretation of genomic and transcriptomic experiments, including analyzing the functional implications of insertions, deletions, and mutations, inferring the function of understudied genes, and determining functional changes resulting from differential expression studies. MycoBASE provides a valuable resource for mycobacterial researchers, through improved and searchable functional annotations and functional enrichment strategies. MycoBASE will be continually supported and updated to include new genomes, enabling a powerful resource to aid the quest to better understand these important pathogenic and environmental species.

HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

Validation of Toxtree and SciQSAR in silico predictive software using a publicly available benchmark mutagenicity database and their applicability for the qualification of impurities in pharmaceuticals.

The draft ICH M7 guidance (US FDA, 2013) recommends that the computational assessment of bacterial mutagenicity for the qualification of impurities in pharmaceuticals be performed using an expert rule-based method and a second statistically-based (Q)SAR method. The public nonproprietary 6489 compound Hansen benchmark mutagenicity data set was used as an external validation data set for Toxtree, a free expert rule-based SAR software. This is the largest known external validation of Toxtree. The Toxtree external validation specificity, sensitivity, concordance and false negative rate for this mutagenicity data set was 66%, 80%, 74% and 20%, respectively. This mutagenicity data set was also used to create a statistically-based SciQSAR-Hansen mutagenicity model. In a 10% leave-group-out internal cross validation study the specificity, sensitivity, concordance and false negative rate for the SciQSAR mutagenicity model was 71%, 83%, 77% and 17%, respectively. Combining Toxtree and SciQSAR predictions and scoring a positive finding in either software as a positive mutagenicity finding reduced the false negative rate to 7% and increased sensitivity to 93% at the expense of specificity which decreased to 53%. The results of this study support the applicability of Toxtree, and the SciQSAR-Hansen mutagenicity model for the qualification of impurities in pharmaceuticals.

Charge density analysis of 2-methyl-4-nitro-1-phenyl-1H-imidazole-5-carbonitrile: an experimental and theoretical study of C≡N···C≡N interactions.

The experimental charge density distribution was determined for 2-methyl-4-nitro-1-phenyl-1H-imidazole-5-carbonitryle, using the Hansen-Coppens multipole model. Free R factor calculations were performed with MoPro software to find optimal restraints for a physically meaningful model. The crystal packing is determined to some extent by weak C-H···O and C-H···N hydrogen bonds but mostly by a lateral electrostatic interaction between antiparallel side-by-side C≡N groups. Electrostatic energy calculations were performed based on the experimental data and are in line with the high-level, explicitly correlated theoretical SCS-RI-MP2-F12 calculations of total energy. The molecular dipole moment and atomic charge values were compared for different experimental and theoretical models, to highlight the dependence of the electrostatic property outputs on the applied restraints. Interesting O···O contacts are also described. The results are compared with two recently investigated nitroimidazole derivatives, namely, 1-(2'-aminophenyl)-2-methyl-4-nitroimidazole and 1-phenyl-4-nitroimidazole.

Automated transportation of single cells using robot-tweezer manipulation system.

Manipulation of biological cells becomes increasingly important in biomedical engineering to address challenge issues in cell-cell interaction, drug discovery, and tissue engineering. Significant demand for both accuracy and productivity in cell manipulation highlights the need for automated cell transportation with integrated robotics and micro/nano manipulation technologies. Optical tweezers, which use highly focused low-power laser beams to trap and manipulate particles at micro/nanoscale, have emerged as an essential tool for manipulating single cells. In this article, we propose to use a robot-tweezer manipulation system to solve the problem of automatic transportation of biological cells, where optical tweezers function as special robot end effectors. Dynamics equation of the cell in optical tweezers is analyzed. A closed-loop controller is designed for transporting and positioning cells. Experiments are performed on live cells to demonstrate the effectiveness of the proposed approach in effective cell positioning.

Retrospectively gated cardiac cine imaging with temporal and spatial acceleration.

Parallel imaging methods are routinely used to accelerate the image acquisition process in cardiac cine imaging. The addition of a temporal acceleration method, whereby k-space is sampled differently for different time frames, has been shown in prior work to improve image quality as compared to parallel imaging by itself. However, such temporal acceleration strategies prove difficult to combine with retrospectively gated cine imaging. The only currently published method to feature such combination, by Hansen et al. [Magn Reson Med 55 (2006) 85-91] tends to be associated with prohibitively long reconstruction times. The goal of the present work was to develop a retrospectively gated cardiac cine method that features both parallel imaging and temporal acceleration, capable of achieving significant acceleration factors on commonly available hardware and associated with reconstruction times short enough for practical use in a clinical context. Seven cardiac patients and a healthy volunteer were recruited and imaged, with acceleration factors of 3.5 or 4.5, using an eight-channel product cardiac array on a 1.5-T system. The prescribed FOV value proved slightly too small in three patients, and one of the patients had a bigemini condition. Despite these additional challenges, good-quality results were obtained for all slices and all patients, with a reconstruction time of 0.98±0.07 s per frame, or about 20 s for a 20-frame slice, using a single processor on a single PC. As compared to using parallel imaging by itself, the addition of a temporal acceleration strategy provided much resistance to artifacts.

The MycoBrowser portal: a comprehensive and manually annotated resource for mycobacterial genomes.

In this paper, we present the MycoBrowser portal (http://mycobrowser.epfl.ch/), a resource that provides both in silico generated and manually reviewed information within databases dedicated to the complete genomes of Mycobacterium tuberculosis, Mycobacterium leprae, Mycobacterium marinum and Mycobacterium smegmatis. A central component of MycoBrowser is TubercuList (http://tuberculist.epfl.ch), which has recently benefited from a new data management system and web interface. These improvements were extended to all MycoBrowser databases. We provide an overview of the functionalities available and the different ways of interrogating the data then discuss how both the new information and the latest features are helping the mycobacterial research communities.

SeyeS - support system for preventing the development of ocular disabilities in leprosy.

Leprosy is an infectious disease caused by Mycobacterium Leprae, and generally compromises neural fibers, leading to the development of disabilities. These limit daily activities or social life. In leprosy, the study of disability considered functional (physical) and activity limitations; and social participation. These are measured respectively by EHF and SALSA scales; by and PARTICIPATION SCALE: The objective of this work was to propose a support system, SeyeS, to eyes disabilities development and progression identification, applying Bayesians network - BN's. It is expected that the proposed system be applied in monitoring the patient during treatment and after therapeutic cure of leprosy. SeyeS presented specificity 1 and sensitivity 0.6 in the identification of ocular disabilities development. With Seyes was discovered that the presence of trichiasis and lagophthalmos, tend to increase the probability of developing more disabilities. Otherwise, characteristics as cataracts tend to decrease development of other disabilities, considering that medical interventions could reduce it. The more import of this system is to indicate what should be monitored, and which elements needs interventions to not increasing patient's ocular disabilities.

DermaMan: scoring dermatology in your palm.

Personal Digital Assistants (PDAs) have become a part of everyday life. DermaMan is a freely available, Java-based, dermatology-specific calculator for handheld devices. It includes modules to compute PASI, MASI, SCORAD, and for calculations related to topical PUVA and Botox (R) administration.