Lead Crystal: An Important Potential Source of Lead Exposure

Abstract

We have examined the potential of alcoholic beverages to elute Pb from crystal wine decanters and glasses. Port wine containing 89 Pb L^?1 was aliquoted into three lead crystal wine decanters. The wine Pb content rose steadily to a mean of 3,518 μg L^?1 after 4 months. We then analyzed wines and liquors which had been stored in crystal decanters in the homes of our colleagues for periods of six months or longer. In the first four homes, eight decanters contained beverages with a mean Pb concentration of 7,781μg L^?1 In a short-term experiment, white wine was found to elute small quantities of Pb from lead crystal glasses within minutes; the mean wine Pb concentration rose from 33 μg L^?1 at time zero to a mean of 99 μg L^?1 after four hours. We conclude that, in particular, lead crystal wine decanters are potentially an important source of Pb exposure for a segment of the population. In addition, lead crystal baby bottles, although not as widely available, were found to elute Pb into apple juice and infant formula; their sale should be banned.     

Combination of docking,molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone

In modern drug discovery process, ADME/Tox properties should be determined as early as possible in the test cascade to allow a timely assessment of their property profiles. To help medicinal chemists in designing new compounds with improved pharmacokinetics, the knowledge of the soft spot position or the site of metabolism (SOM) is needed. In silico methods based on docking, molecular dynamics and quantum chemical calculations can bring us closer to understand drug metabolism and predict drug–drug interactions. We report herein on a combined methodology to explore the site of metabolism prediction of a new cardioactive drug prototype, LASSBio-294 (1), using MetaPrint2D to predict the most likely metabolites, combined with structure-based tools using docking, molecular dynamics and quantum mechanical calculations to predict the binding of the substrate to CYP2C9 enzyme, to estimate the binding free energy and to study the energy profiles for the oxidation of (1). Additionally, the computational study was correlated with a metabolic fingerprint profiling using LC-MS analysis. The results obtained using the computational methods gave valuable information about the probable metabolites of (1) (qualitatively) and also about the important interactions of this lead compound with the amino acid residues of the active site of CYP2C9. Moreover, using a combination of different levels of theory sheds light on the understanding of (1) metabolism by CYP2C9 and its mechanisms. The metabolic fingerprint profiling of (1) has shown that the metabolites founded in highest concentration in different species were metabolites M1, M2 and M3, whereas M8 was found to be a minor metabolite. Therefore, our computational study allowed a qualitative prediction for the metabolism of (1). The approach presented here has afforded new opportunities to improve metabolite identification strategies, mediated by not only CYP2C9 but also other CYP450 family enzymes.     

Lead identification of conformationally restricted benzoxepin type combretastatin analogs: synthesis,antiproliferative activity,and tubulin effects

We have synthesized a series of polymethoxylated rigid analogs of combretastatin A-4 which contain a benzoxepin ring in place of the usual ethylene bridge present in the natural combretastatin products. The compounds display antiproliferative activity when evaluated against the MCF-7 and MDA human breast carcinoma cell lines. 5-(3-Hydroxy-4-methoxyphenyl)-4-(3,4,5-trimethoxyphenyl)-2,3-dihydro-benzoxepine (11g) was found to be the most potent product when evaluated against the MCF-7 breast cancer cell line. A brief computational study of the structure–activity relationship for the synthesized compounds is presented. These 4,5-diarylbenzoxepins are identified as potentially useful scaffolds for the further development of antitumor agents which target tubulin.     

A Free Energy Based Computational Pathway from Chemical Templates to Lead Compounds: A Case Study of COX-2 Inhibitors

Abstract

Automation of lead compound design in silico given the structure of the protein target and a definition of its active site vies for the top of the wish list in any drug discovery programme. We present here an enumeration of steps starting from chemical templates and propose a solution at the state of the art, in the form of a system independent comprehensive computational pathway. This methodology is illustrated with cyclooxygenase-2 (COX-2) as a target. We built candidate molecules including a few Non Steroidal Anti-inflammatory Drugs (NSAIDs) from chemical templates, passed them through empirical filters to assess drug-like properties, optimized their geometries, derived partial atomic charges via quantum calculations, performed Monte Carlo docking, carried out molecular mechanics and developed free energy estimates with Molecular Mechanics Generalized Born Solvent Accessibility (MMGBSA) methodology for each of the candidate molecules. For the case of aspirin, we also conducted molecular dynamics on the enzyme, the drug and the complex with explicit solvent followed by binding free energy analysis. Collectively, the results obtained from the above studies viz. sorting of drugs from non-drugs, semi-quantitative estimates of binding free energies, amply demonstrate the viability of the strategy proposed for lead selection/design for biomolecular targets.     

Model building and model checking for biochemical processes

A central claim of computational systems biology is that, by drawing on mathematical approaches developed in the context of dynamic systems, kinetic analysis, computational theory and logic, it is possible to create powerful simulation, analysis, and reasoning tools for working biologists to decipher existing data, devise new experiments, and ultimately to understand functional properties of genomes, proteomes, cells, organs, and organisms. In this article, a novel computational tool is described that achieves many of the goals of this new discipline. The novelty of this system involves an automaton-based semantics of the temporal evolution of complex biochemical reactions starting from the representation given as a set of differential equations. The related tools also provide ability to qualitatively reason about the systems using a propositional temporal logic that can express an ordered sequence of events succinctly and unambiguously. The implementation of mathematical and computational models in the Simpathica and XSSYS systems is described briefly. Several example applications of these systems to cellular and biochemical processes are presented: the two most prominent are Leibler et al.'s repressilator (an artificial synthesized oscillatory network), and Curto-Voit-Sorribas-Cascante's purine metabolism reaction model.     

Identification of a Potential Lead Structure for Designing New Antimicrobials to Treat Infections Caused by Staphylococcus epidermidis-Resistant Strains

Bacterial infections are a significant cause of morbidity and mortality among critically ill patients. The increase of antibiotic resistance in bacteria from human microbiota—such as Staphylococcus epidermidis, an important nosocomial pathogen that affects immunocompromised patients or those with indwelling devices—increased the desire for new antibiotics. In this study we designed, synthesized, and determined the antimicrobial activity of 27 thieno[2,3-b]pyridines (1, 2, 2a–2m, 3, 3a–3m) derivatives against a drug-resistant clinical S. epidermidis strain. In addition, we performed a structure-activity relationship analysis using a molecular modeling approach, and discuss the drug absorption, distribution, metabolism, excretion, and toxicity profile and Lipinski’s “rule of five,” which are tools to assess the relationship between structures and drug-like properties of active compounds. Our results showed that compound 3b (5-(1H-tetrazol-5-yl)-4-(3`-methylphenylamino)thieno[2,3-b]pyridine) was as active as oxacillin and chloramphenicol but with lower theoretical toxicity risks and a better drug likeness and drug score potential than chloramphenicol. All molecular modeling and biological results reinforced the promising profile of 3b for further experimental investigation and development of new antibacterial drugs. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Defining a mutational signature for endometrial cancer screening and early detection

IntroductionThe current availability of genomic information represents an opportunity to develop new strategies for early detection of cancer. New molecular tests for endometrial cancer may improve performance and failure rates of histological aspirate-based diagnosis, and provide promising perspectives for a potential screening scenario. However, the selection of relevant biomarkers to develop efficient strategies can be a challenge.Materials and methodsWe developed an algorithm to identify the largest number of patients with endometrial cancer using the minimum number of somatic mutations based on The Cancer Genome Atlas (TCGA) dataset.ResultsThe algorithm provided the number of subjects with mutations (sensitivity) for a given number of biomarkers included in the signature. For instance, by evaluating the 50 most representative point mutations, up to 81.9% of endometrial cancers can be identified in the TCGA dataset. At gene level, a 92.9% sensitivity can be obtained by interrogating five genes.DiscussionWe developed a computational method to aid in the selection of relevant genomic biomarkers in endometrial cancer that can be adapted to other cancer types or diseases.     

Inadvertent Transarterial Lead Placement in the Left Ventricle and Aortic Cusp: Percutaneous Lead Removal with Carotid Embolic Protection and Stent Graft Placement

Background/PurposeTransarterial lead implantation in the left ventricle or aorta is a rare complication. Percutaneous lead removal is associated with significant thromboembolic and bleeding risk. We present two cases of lead removal from the left ventricle via the left subclavian artery with concurrent carotid embolic protection followed by stent graft placement in the subclavian artery.Methods/ResultsPatient 1 underwent prior pacemaker implant with atrial and ventricular active fixation leads positioned in the right coronary cusp and the left ventricle, respectively. Patient 2 had prior ICD implant with a single active fixation lead positioned in the left ventricular apex. Lead removal was performed in a hybrid operating room. Distal embolic filter wires were deployed in the carotid arteries following anticoagulation. Intravascular ultrasound of the left subclavian artery was performed and as the leads were withdrawn, a covered stent was deployed at the removal site. Final angiography demonstrated no evidence of embolic phenomena. Both patients underwent transvenous lead implantation followed by an uneventful postoperative clinical course.ConclusionsTransarterial percutaneous lead removal may be safely performed using embolic filter protection of the cerebral circulation and stent graft placement of the arterial entry site.     

Visualizing the knowledge structure and evolution of bioinformatics

Background

Bioinformatics has gained much attention as a fast growing interdisciplinary field. Several attempts have been conducted to explore the field of bioinformatics by bibliometric analysis, however, such works did not elucidate the role of visualization in analysis, nor focus on the relationship between sub-topics of bioinformatics.

Results

First, the hotspot of bioinformatics has moderately shifted from traditional molecular biology to omics research, and the computational method has also shifted from mathematical model to data mining and machine learning. Second, DNA-related topics are bridge topics in bioinformatics research. These topics gradually connect various sub-topics that are relatively independent at first. Third, only a small part of topics we have obtained involves a number of computational methods, and the other topics focus more on biological aspects. Fourth, the proportion of computing-related topics hit a trough in the 1980s. During this period, the use of traditional calculation methods such as mathematical model declined in a large proportion while the new calculation methods such as machine learning have not been applied in a large scale. This proportion began to increase gradually after the 1990s. Fifth, although the proportion of computing-related topics is only slightly higher than the original, the connection between other topics and computing-related topics has become closer, which means the support of computational methods is becoming increasingly important for the research of bioinformatics.

Conclusions

The results of our analysis imply that research on bioinformatics is becoming more diversified and the ranking of computational methods in bioinformatics research is also gradually improving.

     

Coronary Sinus Lead Removal: A Comparison between Active and Passive Fixation Leads

BackgroundImplantation of coronary sinus (CS) leads may be a difficult procedure due to different vein anatomies and a possible lead dislodgement. The mode of CS lead fixation has changed and developed in recent years.ObjectivesWe compared the removal procedures of active and passive fixation leads.MethodsBetween January 2009 and January 2014, 22 patients at our centre underwent CS lead removal, 6 active and 16 passive fixation leads were attempted using simple traction or lead locking devices with or without laser extraction sheaths. Data on procedural variables and success rates were collected and retrospectively analyzed.ResultsThe mean patient age was 67.2 ± 9.8 years, and 90.9% were male. The indication for lead removal was infection in all cases. All active fixation leads were Medtronic^® Attain StarFix^™ Model 4195 (Medtronic Inc., Minneapolis, MN, USA). The mean time from implantation for the active and passive fixation leads was 9.9 ± 11.7 months (range 1.0–30.1) and 48.7 ± 33.6 months (range 5.7–106.4), respectively (p = 0.012). Only 3 of 6 StarFix leads were successfully removed (50%) compared to 16 of 16 (100%) of the passive fixation CS leads (p = 0.013). No death or complications occurred during the 30-day follow-up.ConclusionAccording to our experience, removal of the Starfix active fixation CS leads had a higher procedural failure rate compared to passive.     

Synthesis and Preliminary Thermodynamic Investigation of Hypoxanthine-Containing Peptide Nucleic Acids

Abstract

A new, hypoxanthine-conaining PNA monomer, PNAs and complementary DNAs were designed, produced and investigated by thermal denaturation studies in order to find the analogue of inosine at PNAs [1]. Thermodynamic data were determined with the van't Hoff method [2, 3]. The measured and computational values were correlated.     

SCYN: single cell CNV profiling method using dynamic programming

Background

All diseases containing genetic material undergo genetic evolution and give rise to heterogeneity including cancer and infection. Although these illnesses are biologically very different, the ability for phylogenetic retrodiction based on the genomic reads is common between them and thus tree-based principles and assumptions are shared. Just as the different frequencies of tumor genomic variants presupposes the existence of multiple tumor clones and provides a handle to computationally infer them, we postulate that the different variant frequencies in viral reads offers the means to infer multiple co-infecting sublineages.

Results

We present a common methodological framework to infer the phylogenomics from genomic data, be it reads of SARS-CoV-2 of multiple COVID-19 patients or bulk DNAseq of the tumor of a cancer patient. We describe the Concerti computational framework for inferring phylogenies in each of the two scenarios.To demonstrate the accuracy of the method, we reproduce some known results in both scenarios. We also make some additional discoveries.

Conclusions

Concerti successfully extracts and integrates information from multi-point samples, enabling the discovery of clinically plausible phylogenetic trees that capture the heterogeneity known to exist both spatially and temporally. These models can have direct therapeutic implications by highlighting “birth” of clones that may harbor resistance mechanisms to treatment, “death” of subclones with drug targets, and acquisition of functionally pertinent mutations in clones that may have seemed clinically irrelevant. Specifically in this paper we uncover new potential parallel mutations in the evolution of the SARS-CoV-2 virus. In the context of cancer, we identify new clones harboring resistant mutations to therapy.

     

The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation*

ABSTRACT

Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.     

A combined proteomics and computational approach provides a better understanding of HCV-induced liver disease

Evaluation of: Diamond DL, Krasnoselsky AL, Burnum KE et al. Proteome and computational analyses reveal new insights into the mechanisms of hepatitis C virus-mediated liver disease posttransplantation. Hepatology 56(1), 28–38 (2012).

HCV is a major cause of chronic liver disease worldwide and is a formidable therapeutic challenge. Recently, Diamond et al. analyzed the proteomic profiles of liver samples from HCV-positive liver transplant recipients, supplemented with an independent metabolite analysis. They used a computational approach, which highlighted the enriched functional themes and topological attributes associated with the protein association network based on their clinical data and suggested a crucial role of oxidative stress in fibrosis progression in HCV infection. Their findings provide new insights into the mechanisms that regulate the progression of HCV-associated liver fibrosis, which may be useful for identification of suitable biomarkers to evaluate the onset and severity of hepatic fibrosis and the development of new therapeutic and anti-HCV strategies.     

Midvale Community Lead Study

Abstract

The primary objective of this study was to ascertain whether children living in close proximity to mill tailings and a former lead smelter site were currently exhibiting elevated blood lead (PbB) concentrations. To address this issue, the mean PbB for community children and the relationship between PbB and the proximity of the child's residence to the site was estimated. A secondary objective was to identify and quantify accessible lead (Pb) and arsenic (As) in the environment (e.g. Pb in soil, dust, paint and water or As in soil and dust). A third objective was to test for association between specific sources of environmental Pb and PbB and to estimate the relative contribution of these proximate sources of lead to the children's PbB. The data analytic methods allowed estimation of both direct and indirect impact of environmentally accessible Pb. The average PbB level of all children screened in Midvale was 5.2 μg dL^?1. Three percent exceeded 15 μg dL^?1; 12.7% exceeded 10 μg dL^?1. Pb-based house paint and Pb contaminated soil were identified as principal contributors to PbB. PbB was found to increase 1.25 μg dL^?1 per 1,000 ppm increase in lead in soil. Proximity of residence to the mill and smelter site was found to be a strong predictor of Pb in soil, and therefore indirectly related to increases in PbB.     

Reliability of a computational platform as a surrogate for manually interpreted immunohistochemical markers in breast tumor tissue microarrays

BackgroundPathologist and computational assessments have been used to evaluate immunohistochemistry (IHC) in epidemiologic studies. We compared Definiens Tissue Studio® to pathologist scores for 17 markers measured in breast tumor tissue microarrays (TMAs) [AR, CD20, CD4, CD8, CD163, EPRS, ER, FASN, H3K27, IGF1R, IR, Ki67, phospho-mTOR, PR, PTEN, RXR, and VDR].Methods5 914 Nurses’ Health Study participants, diagnosed 1976–2006 (NHS) and 1989–2006 (NHS-II), were included. IHC was conducted by the Dana-Farber/Harvard Cancer Center Specialized Histopathology Laboratory. The percent of cells staining positive was assessed by breast pathologists. Definiens output was used to calculate a weighted average of percent of cells staining positive across TMA cores for each marker. Correlations between pathologist and computational scores were evaluated with Spearman correlation coefficients. Receiver-operator characteristic curves were constructed, using pathologist scores as comparison.ResultsSpearman correlations between pathologist and Definiens assessments ranged from weak (RXR, rho=-0.05; CD163, rho = 0.10) to strong (Ki67, rho = 0.79; pmTOR, rho = 0.77). The area under the curve was >0.70 for all markers except RXR.ConclusionOur data indicate that computational assessments exhibit variable correlations with interpretations made by an expert pathologist, depending on the marker evaluated. This study provides evidence supporting the use of computational platforms for IHC evaluation in large-scale epidemiologic studies, with the caveat that pilot studies are necessary to investigate agreement with expert assessments. In sum, computational platforms may provide greater efficiency and facilitate high-throughput epidemiologic analyses.