Young people's experiences of sexual and reproductive health interventions in rural KwaZulu-Natal, South Africa

Despite efforts to address HIV-infection, adolescents and young peoples’ (AYP) engagement in interventions remain suboptimal. Guided by a risk protection framework we describe factors that support positive and negative experiences of HIV and SRH interventions among AYP in rural KwaZulu-Natal, South Africa, using data from: community mapping; repeat semi-structured individual interviews (n = 58 in 2017, n = 50 in 2018, n = 37 in 2019–2020); and group discussions (n = 13). AYP who had appropriate and accurate HIV-and SRH-related information were reported to use health-care services. Responsive health-care workers, good family and peer relationships were seen to be protective through building close connections and improving self-efficacy to access care. In contrast to cross-generational relationships with men, alcohol and drug use and early pregnancy were seen to put AYP at risk. Policies and interventions are needed that promote stable and supportive relationships with caregivers and peers, positive social norms and non-judgemental behaviour within clinical services

Selective adsorption of PVP on the surface of silver nanoparticles

The use of surfactants to affect the shape evolution of silver nanoparticles is explored. This allows one to fine-tune the morphological evolution and the optical properties of the metal nanoparticles. Polyvinyl pyrrolidone (PVP) has been used as a surfactant to control the growth of silver nanoparticles at room temperature. In this paper, molecular dynamics simulations were performed to understand regio-selective adsorption of PVP that leads to the preferential growth of silver nanoparticles in dimethylformamide (DMF). The interaction energies between PVP and Ag(1 1 0), Ag(1 0 0) and Ag(1 1 1) crystal planes were calculated and in addition the length density profile of the surfactant on silver surfaces was also examined. Importantly, it has been demonstrated that the length distribution profiles analysis obtained from the molecular dynamics study fully explained the adsorption of PVP on the surface of silver nanoparticles through the carbonyl group of the PVP ring. The application of molecular dynamics simulation technique is important in understanding the evolution of silver nanoparticles and is vital in choosing the right surfactants

Synthesis, density functional theory, molecular dynamics and electrochemical studies of 3-thiopheneacetic acid-capped gold nanoparticles

Gold nanoparticles capped with a bifunctional ligand, 3-thiopheneacetic acid (3-TAA) were synthesised by borohydride reduction at room temperature. The transmission electron microscopy (TEM) analysis showed that the particle aggregates and had semi-linear partial linkages that could be attributed to multi-modal binding of the ligand with various gold nanoparticles through the terminal thiolether (–S–) group and oxygen of the carboxylic (–COOH) group. This bimodal interaction led to limited stability of the resultant nanoparticles when tested using highly electrolytic media. To investigate further, density functional theory (DFT) quantum chemical and molecular dynamic calculations were conducted. The energetically favorable binding modes of the ligand to gold nanoparticle surfaces using the Gaussian program were studied. The DFT results showed kinetic stability of Au–3-TAA–Au interactions leading to inter-particle coupling or aggregation. Electrochemical analysis of the resultant nature of the capping agent revealed that 3-thiopheneacetic acid did not form a polymer during the preparation of Au–3-TAA. The cyclic voltammograms of Au–3-TAA nanoparticles coated glassy carbon electrode showed a typical gold character with the oxidation and reduction peaks at 1.4 V and 0.9 V, respectively

The influence of helium-induced defects on the migration of strontium implanted into SiC above critical amorphization temperature

The presence of radiation-induced defects and the high temperature of implantation are breeding grounds for helium (He) to accumulate and form He-induced defects (bubbles, blisters, craters, and cavities) in silicon carbide (SiC). In this work, the influence of He-induced defects on the migration of strontium (Sr) implanted into SiC was investigated. Sr-ions of 360 keV were implanted into polycrystalline SiC to a fluence of 2 × 1016 Sr-ions/cm2 at 600°C (Sr-SiC). Some of the Sr-SiC samples were then co-implanted with He-ions of 21.5 keV to a fluence of 1 × 1017 He-ions/cm2 at 350°C (Sr + He-SiC). The Sr-SiC and Sr + He-SiC samples were annealed for 5 h at 1,000°C. The as-implanted and annealed samples were characterized by Raman spectroscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), transmission electron microscopy (TEM), and Rutherford backscattered spectrometry (RBS). Implantation of Sr retained some defects in SiC, while co-implantation of He resulted in the formation of He-bubbles, blisters, and craters (exfoliated blisters). Blisters close to the critical height and size were the first to exfoliate after annealing. He-bubbles grew larger after annealing owing to the capture of more vacancies. In the co-implanted samples, Sr was located in three regions: the crystalline region (near the surface), the bubble region (where the projected range of Sr was located), and the damage region toward the bulk. Annealing the Sr + He-SiC caused the migration of Sr towards the bulk, while no migration was observed in the Sr-SiC samples. The migration was governed by “vacancy migration driven by strain fileds.

Investigating the metabolic capabilities of Mycobacterium tuberculosis H37Rv using the in silico strain iNJ661 and proposing alternative drug targets

<p>Abstract</p> <p>Background:</p> <p><it>Mycobacterium tuberculosis </it>continues to be a major pathogen in the third world, killing almost 2 million people a year by the most recent estimates. Even in industrialized countries, the emergence of multi-drug resistant (MDR) strains of tuberculosis hails the need to develop additional medications for treatment. Many of the drugs used for treatment of tuberculosis target metabolic enzymes. Genome-scale models can be used for analysis, discovery, and as hypothesis generating tools, which will hopefully assist the rational drug development process. These models need to be able to assimilate data from large datasets and analyze them.</p> <p>Results:</p> <p>We completed a bottom up reconstruction of the metabolic network of <it>Mycobacterium tuberculosis </it>H37Rv. This functional <it>in silico </it>bacterium, <it>iNJ</it>661, contains 661 genes and 939 reactions and can produce many of the complex compounds characteristic to tuberculosis, such as mycolic acids and mycocerosates. We grew this bacterium <it>in silico </it>on various media, analyzed the model in the context of multiple high-throughput data sets, and finally we analyzed the network in an 'unbiased' manner by calculating the Hard Coupled Reaction (HCR) sets, groups of reactions that are forced to operate in unison due to mass conservation and connectivity constraints.</p> <p>Conclusion:</p> <p>Although we observed growth rates comparable to experimental observations (doubling times ranging from about 12 to 24 hours) in different media, comparisons of gene essentiality with experimental data were less encouraging (generally about 55%). The reasons for the often conflicting results were multi-fold, including gene expression variability under different conditions and lack of complete biological knowledge. Some of the inconsistencies between <it>in vitro </it>and <it>in silico </it>or <it>in vivo </it>and <it>in silico </it>results highlight specific loci that are worth further experimental investigations. Finally, by considering the HCR sets in the context of known drug targets for tuberculosis treatment we proposed new alternative, but equivalent drug targets.</p

Mycobacterial dihydrofolate reductase inhibitors identified using chemogenomic methods and in vitro validation.

The lack of success in target-based screening approaches to the discovery of antibacterial agents has led to reemergence of phenotypic screening as a successful approach of identifying bioactive, antibacterial compounds. A challenge though with this route is then to identify the molecular target(s) and mechanism of action of the hits. This target identification, or deorphanization step, is often essential in further optimization and validation studies. Direct experimental identification of the molecular target of a screening hit is often complex, precisely because the properties and specificity of the hit are not yet optimized against that target, and so many false positives are often obtained. An alternative is to use computational, predictive, approaches to hypothesize a mechanism of action, which can then be validated in a more directed and efficient manner. Specifically here we present experimental validation of an in silico prediction from a large-scale screen performed against Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. The two potent anti-tubercular compounds studied in this case, belonging to the tetrahydro-1,3,5-triazin-2-amine (THT) family, were predicted and confirmed to be an inhibitor of dihydrofolate reductase (DHFR), a known essential Mtb gene, and already clinically validated as a drug target. Given the large number of similar screening data sets shared amongst the community, this in vitro validation of these target predictions gives weight to computational approaches to establish the mechanism of action (MoA) of novel screening hit

Genome-Scale Identification Method Applied to Find Cryptic Aminoglycoside Resistance Genes in Pseudomonas aeruginosa

BACKGROUND:The ability of bacteria to rapidly evolve resistance to antibiotics is a critical public health problem. Resistance leads to increased disease severity and death rates, as well as imposes pressure towards the discovery and development of new antibiotic therapies. Improving understanding of the evolution and genetic basis of resistance is a fundamental goal in the field of microbiology. RESULTS:We have applied a new genomic method, Scalar Analysis of Library Enrichments (SCALEs), to identify genomic regions that, given increased copy number, may lead to aminoglycoside resistance in Pseudomonas aeruginosa at the genome scale. We report the result of selections on highly representative genomic libraries for three different aminoglycoside antibiotics (amikacin, gentamicin, and tobramycin). At the genome-scale, we show significant (p<0.05) overlap in genes identified for each aminoglycoside evaluated. Among the genomic segments identified, we confirmed increased resistance associated with an increased copy number of several genomic regions, including the ORF of PA5471, recently implicated in MexXY efflux pump related aminoglycoside resistance, PA4943-PA4946 (encoding a probable GTP-binding protein, a predicted host factor I protein, a delta 2-isopentenylpyrophosphate transferase, and DNA mismatch repair protein mutL), PA0960-PA0963 (encoding hypothetical proteins, a probable cold shock protein, a probable DNA-binding stress protein, and aspartyl-tRNA synthetase), a segment of PA4967 (encoding a topoisomerase IV subunit B), as well as a chimeric clone containing two inserts including the ORFs PA0547 and PA2326 (encoding a probable transcriptional regulator and a probable hypothetical protein, respectively). CONCLUSIONS:The studies reported here demonstrate the application of new a genomic method, SCALEs, which can be used to improve understanding of the evolution of antibiotic resistance in P. aeruginosa. In our demonstration studies, we identified a significant number of genomic regions that increased resistance to multiple aminoglycosides. We identified genetic regions that include open reading frames that encode for products from many functional categories, including genes related to O-antigen synthesis, DNA repair, and transcriptional and translational processes