Semi-empirical model for Henry's law constant of noble gases in molten salts.

Henry's law constant, which describes the proportionality of dissolved gas to partial pressure of free gas in liquid-gas equilibrium systems, can also be applied to mass transport applications. In this work, we investigated an approach for determining the solubility of noble gases in a molten salt liquid utilizing the equilibrium concept of Henry's gas constant. Henry's gas constant is described as a mathematical function dependent on the van der Waals radius of the noble gas and the temperature of the molten salt. The alteration in Gibbs free energy encompasses contributions from both surface and volume energies. Enthalpy and entropy are deduced from these surface and volume energies in the Gibbs free energy formulation. A comparative analysis was conducted between the conventional method and our proposed model. Moreover, useful chemical properties can be determined from examination of surface and volume energies. Our findings provide an accurate and general theory of Gibbs free energy that can be validated experimentally based on the model proposed herein. This work unifies the prediction of Henry gas constant and subsequently the entropy and enthalpy calculation for noble gases in a molten salt solution to a single functional form using van der Waals radius of the gas and temperature of the system. This functional form is then used to perform a multiple regression method to find two parameters corresponding to the surface energy and volume energy. These two parameters are consistent between all combinations of noble gas and molten salt.

Well-scale multiphase flow characterization and validation using distributed fiber-optic sensors for gas kick monitoring.

Early detection of a gas kick is crucial for preventing uncontrolled blowout that could cause loss of life, loss of assets, and environmental damage. Multiphase flow experiments conducted in this research demonstrate the capability of downhole fiber optic sensors to detect a potential gas influx in real-time in a 5000 ft deep wellbore. Gas rise velocities estimated independently using fiber optic distributed acoustic sensor (DAS), distributed temperature sensor (DTS), downhole gauges, surface measurements, and multiphase flow correlations show good agreement in each case, demonstrating reliability in the assessment. Real-time data visualization was implemented on a secure cloud-based platform to improve computational efficiency. This study provides novel insights on the effect of circulation rates, gas kick volumes, backpressure, and injection methods on gas rise dynamics in a full-scale wellbore.

Rooibos (Aspalathus linearis) Genome Size Estimation Using Flow Cytometry and K-Mer Analyses.

Plant genomes provide information on biosynthetic pathways involved in the production of industrially relevant compounds. Genome size estimates are essential for the initiation of genome projects. The genome size of rooibos (Aspalathus linearis species complex) was estimated using DAPI flow cytometry and k-mer analyses. For flow cytometry, a suitable nuclei isolation buffer, plant tissue and a transport medium for rooibos ecotype samples collected from distant locations were identified. When using radicles from commercial rooibos seedlings, Woody Plant Buffer and Vicia faba as an internal standard, the flow cytometry-estimated genome size of rooibos was 1.24 ± 0.01 Gbp. The estimates for eight wild rooibos growth types did not deviate significantly from this value. K-mer analysis was performed using Illumina paired-end sequencing data from one commercial rooibos genotype. For biocomputational estimation of the genome size, four k-mer analysis methods were investigated: A standard formula and three popular programs (BBNorm, GenomeScope, and FindGSE). GenomeScope estimates were strongly affected by parameter settings, specifically CovMax. When using the complete k-mer frequency histogram (up to 9 × 105), the programs did not deviate significantly, estimating an average rooibos genome size of 1.03 ± 0.04 Gbp. Differences between the flow cytometry and biocomputational estimates are discussed.

Distributed Fiber Optic Sensing for Real-Time Monitoring of Gas in Riser during Offshore Drilling.

Effective well control depends on the drilling teams' knowledge of wellbore flow dynamics and their ability to predict and control influx. Unfortunately, detection of a gas influx in an offshore environment is particularly challenging, and there are no existing datasets that have been verified and validated for gas kick migration at full-scale annular conditions. This study bridges this gap and presents pioneering research in the application of fiber optic sensing for monitoring gas in riser. The proposed sensing paradigm was validated through well-scale experiments conducted at Petroleum Engineering Research & Technology Transfer lab (PERTT) facility at Louisiana State University (LSU), simulating an offshore marine riser environment with its larger than average annular space and mud circulation capability. The experimental setup instrumented with distributed fiber optic sensors and pressure/temperature gauges provides a physical model to study the dynamic gas migration in full-scale annular conditions. Current kick detection methods primarily utilize surface measurements and do not always reliably detect a gas influx. The proposed application of distributed fiber optic sensing overcomes this key limitation of conventional kick detection methods, by providing real-time distributed downhole data for accurate and reliable monitoring. The two-phase flow experiments conducted in this research provide critical insights for understanding the flow dynamics in offshore drilling riser conditions, and the results provide an indication of how quickly gas can migrate in a marine riser scenario, warranting further investigation for the sake of effective well control.

Transcriptomics of the Rooibos (Aspalathus linearis) Species Complex.

Rooibos (Aspalathus linearis), widely known as a herbal tea, is endemic to the Cape Floristic Region of South Africa (SA). It produces a wide range of phenolic compounds that have been associated with diverse health promoting properties of the plant. The species comprises several growth forms that differ in their morphology and biochemical composition, only one of which is cultivated and used commercially. Here, we established methodologies for non-invasive transcriptome research of wild-growing South African plant species, including (1) harvesting and transport of plant material suitable for RNA sequencing; (2) inexpensive, high-throughput biochemical sample screening; (3) extraction of high-quality RNA from recalcitrant, polysaccharide- and polyphenol rich plant material; and (4) biocomputational analysis of Illumina sequencing data, together with the evaluation of programs for transcriptome assembly (Trinity, IDBA-Trans, SOAPdenovo-Trans, CLC), protein prediction, as well as functional and taxonomic transcript annotation. In the process, we established a biochemically characterized sample pool from 44 distinct rooibos ecotypes (1-5 harvests) and generated four in-depth annotated transcriptomes (each comprising on average ≈86,000 transcripts) from rooibos plants that represent distinct growth forms and differ in their biochemical profiles. These resources will serve future rooibos research and plant breeding endeavours.

Leveraging the utility of pharmacogenomics in psychiatry through clinical decision support: a focus group study.

BACKGROUND: Pharmacogenomics is starting to build momentum in clinical utility, perhaps the most in mental and behavioral healthcare. However, efficient delivery of this information to the point of prescribing remains a significant challenge. Clinical decision support has an opportunity to address this void by integrating pharmacogenomics into the clinician workflow. METHODS: To address the specific needs of mental health clinicians at the point of care, we conducted 3 focus groups with a total of 16 mental health clinicians. Each 1-h focus group was designed to identify the desired clinical decision support features, with a particular interest in pharmacogenomics, and potential negative or unintended consequences of clinical decision support integration at the point of care in a mental healthcare setting. We implemented an iterative design to expand upon knowledge generated in prior focus groups. The results from the guided discussion in the first focus group were used to develop a mental health clinical decision support prototype. This prototype was then presented during the next two focus groups to drive the discussion. RESULTS: This study has identified main themes related to the desired clinical decision support features of mental health clinicians, the use of pharmacogenomics in practice, and unintended and negative consequences of clinical decision support integration at the point of care. Clinicians desire a more complete picture of the medication history of patients and guidance to choose medications in relation to cost, insurance coverage, and pharmacogenetics interactions. Mental health clinicians agreed that pharmacogenetics is useful and impacts their prescribing decisions when the data are available. Several negative consequences of clinical decision support integration were identified including alert fatigue and frustration using the tool. Several points of contention were related to the integration of the clinical decision support with the electronic health record, including bidirectional flow of information, speed, location within workflow, and potential incompleteness of information. CONCLUSIONS: We have identified general and unique considerations of mental health clinicians with regard to clinical decision support. Clinical decision support that incorporates desired features while avoiding negative and unintended consequences will increase clinician usage and will have the potential to improve the care of patients.

Correction to: Novel metagenome-derived ornithine lipids identified by functional screening for biosurfactants.

The published online version contains mistake in the author list.

Novel metagenome-derived ornithine lipids identified by functional screening for biosurfactants.

Biosurfactants are amphiphilic molecules that interact with the surfaces of liquids leading to many useful applications. Most biosurfactants have been identified from cultured microbial sources, leaving a largely untapped resource of uncultured bacteria with potentially novel biosurfactant structures. To access the uncultured bacteria, a metagenomic library was constructed in Escherichia coli from environmental DNA within an E. coli, Pseudomonas putida and Streptomyces lividans shuttle vector. Phenotypic screening of the library in E. coli and P. putida by the paraffin spray assay identified a P. putida clone with biosurfactant activity. Sequence analysis and transposon mutagenesis confirmed that an ornithine acyl-ACP N-acyltransferase was responsible for the activity. Although the fosmid was not active in E. coli, overexpression of the olsB gene could be achieved under the control of the inducible T7 promoter, resulting in lyso-ornithine lipid production and biosurfactant activity in the culture supernatants. Screening for activity in more than one host increases the range of sequences that can be identified through metagenomic, since olsB would not have been identified if only E. coli had been used as a host. The potential of lyso-ornithine lipids as a biosurfactant has not been fully explored. Here, we present several biosurfactant parameters of lyso-ornithine lipid to assess its suitability for industrial application.

Visualization of Aspalathin in Rooibos (Aspalathus linearis) Plant and Herbal Tea Extracts Using Thin-Layer Chromatography.

Aspalathin, the main polyphenol of rooibos (Aspalathus linearis), is associated with diverse health promoting properties of the tea. During fermentation, aspalathin is oxidized and concentrations are significantly reduced. Standardized methods for quality control of rooibos products do not investigate aspalathin, since current techniques of aspalathin detection require expensive equipment and expertise. Here, we describe a simple and fast thin-layer chromatography (TLC) method that can reproducibly visualize aspalathin in rooibos herbal tea and plant extracts at a limit of detection (LOD) equal to 178.7 ng and a limit of quantification (LOQ) equal to 541.6 ng. Aspalathin is a rare compound, so far only found in A. linearis and its (rare) sister species A. pendula. Therefore, aspalathin could serve as a marker compound for authentication and quality control of rooibos products, and the described TLC method represents a cost-effective approach for high-throughput screening of plant and herbal tea extracts.