Cholic Acid-Based Antimicrobial Peptide Mimics as Antibacterial Agents

There is a significant and urgent need for the development of novel antibacterial agents to tackle the increasing incidence of antibiotic resistance. Cholic acid-based small molecular antimicrobial peptide mimics are reported as potential new leads to treat bacterial infection. Here, we describe the design, synthesis and biological evaluation of cholic acid-based small molecular antimicrobial peptide mimics. The synthesis of cholic acid analogues involves the attachment of a hydrophobic moiety at the carboxyl terminal of the cholic acid scaffold, followed by the installation of one to three amino acid residues on the hydroxyl groups present on the cholic acid scaffold. Structure–activity relationship studies suggest that the tryptophan moiety is important for high antibacterial activity. Moreover, a minimum of +2 charge is also important for antimicrobial activity. In particular, analogues containing lysine-like residues showed the highest antibacterial potency against Gram-positive S. aureus. All di-substituted analogues possess high antimicrobial activity against both Gram-positive S. aureus as well as Gram-negative E. coli and P. aeruginosa. Analogues 17c and 17d with a combination of these features were found to be the most potent in this study. These compounds were able to depolarise the bacterial membrane, suggesting that they are potential antimicrobial pore forming agents

Mechanism for controlling the monomer-dimer conversion of SARS coronavirus main protease

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Global prevalence of WHO infant feeding practices in 57 LMICs in 2010-2018 and time trends since 2000 for 44 LMICs

Background:The World Health Assembly set a global target of increasing exclusive breastfeeding for infants under 6 months to at least 50% by year 2025. However, little is known about the current status of breastfeeding practice, as well as the trends in breastfeeding practices during recent years. We examined global prevalence of the World Health Organization (WHO) feeding practices in 57 low- and middle-income countries (LMICs) and time trends since 2000 for 44 selected countries.Methods:We included 57 eligible LMICs that had completed data on breastfeeding and complementary feeding in 2010–2018 from the Demographic and Health Surveys (DHS) for examining current feeding status. We further selected 44 LMICs that had two standard DHS surveys between 2000 and 2009 and 2010–2018 to examine time trends of feeding status. We calculated global, regional, and national weighted prevalence estimates and 95% confidence intervals (CIs) for five breastfeeding indicators and two complementary feeding indicators.Findings:In 57 LMICs during 2010–2018, global weighted prevalence was 51.9% for early initiation of breastfeeding, 45.7% for exclusive breastfeeding under 6 months, 32.0% for exclusive breastfeeding at 4–5 months, 83.1% for continued breastfeeding at 1 year, 56.2% for continued breastfeeding at 2 years, 14.9% for introduction of solid, semi-solid or soft foods under 6 months, and 63.1% for introduction of solid, semi-solid or soft foods at 6–8 months. Eastern Mediterranean (34.5%) and European regions (43.7%) (vs. South-East Asia/Western Pacific (55.2%)), and upper middle-income countries (38.4%) (vs. lower middle-income countries (47.4%)) had poorer performance of exclusive breastfeeding under 6 months. South-East Asia/Western Pacific regions (51.0%) (vs. other regions (68.3%-84.1%)) and low-income (66.4%) or lower middle-income countries (58.2%) (vs. upper middle-income countries (81.7%)) had lower prevalence of introduction of solid, semi-solid or soft foods at 6–8 months. In 44 selected LMICs from 2000 to 2009 to 2010–2018, total weighted prevalence presented an increase of 10.1% for exclusive breastfeeding under 6 months, but a 1.7% decrease for continued breastfeeding at 1 year. Over this period, the Eastern Mediterranean region had a 5.3% decrease of exclusive breastfeeding under 6 months, and the European region had a 2.0% increase for introduction of solid, semi-solid or soft foods under 6 months. The prevalence of introduction of solid, semi-solid or soft foods at 6–8 months decreased in South-East Asia/Western Pacific region by 15.2%, and in lower middle-income countries by 24.4%.Interpretation:Breastfeeding practices in LMICs have continued to improve in the past decade globally, but practices still lag behind the WHO feeding recommendations. Breastfeeding practices differed greatly across WHO regions, with the Eastern Mediterranean and European regions, and upper middle-income countries facing the greatest challenges in meeting targets. Continued efforts are needed to achieve the 2025 global breastfeeding target

Effects of postharvest processing on aroma formation in roasted coffee – a review

Postharvest processing of coffee cherries significantly influences sensory characteristics and commercial values. Aroma is one of the critical elements in product qualification and differentiation of coffees from different origins, roasting levels and brewing methods. Except for primary coffee volatile organic compounds (VOCs) (furans and pyrazines), which are generated during postharvest processing (dry, honey, wet processing and roasting), aldehydes, ketones, phenols, sulphur compounds and others could also contribute to the complex coffee flavour. Desirable flavour requires a balance between pleasant and defective VOCs. This review comprehensively discussed the mechanisms of conventional and novel postharvest processing of coffee beans, their impact on the sensorial profile of green and roasted coffee, and the composition, generation and analysis techniques of coffee VOCs. This review shows the feasibility of GC–MS and electronic nose (E-nose) in coffee VOCs and flavour detection, meanwhile building a comprehensive linkage between postharvest processing and coffee sensory characteristics

The Impact of Wet Fermentation on Coffee Quality Traits and Volatile Compounds Using Digital Technologies

Fermentation is critical for developing coffee’s physicochemical properties. This study aimed to assess the differences in quality traits between fermented and unfermented coffee with four grinding sizes of coffee powder using multiple digital technologies. A total of N = 2 coffee treatments—(i) dry processing and (ii) wet fermentation—with grinding levels (250, 350, 550, and 750 µm) were analysed using near-infrared spectrometry (NIR), electronic nose (e-nose), and headspace/gas chromatography–mass spectrometry (HS-SPME-GC-MS) coupled with machine learning (ML) modelling. Most overtones detected by NIR were within the ranges of 1700–2000 nm and 2200–2396 nm, while the enhanced peak responses of fermented coffee were lower. The overall voltage of nine e-nose sensors obtained from fermented coffee (250 µm) was significantly higher. There were two ML classification models to classify processing and brewing methods using NIR (Model 1) and e-nose (Model 2) values as inputs that were highly accurate (93.9% and 91.2%, respectively). Highly precise ML regression Model 3 and Model 4 based on the same inputs for NIR (R = 0.96) and e-nose (R = 0.99) were developed, respectively, to assess 14 volatile aromatic compounds obtained by GC-MS. Fermented coffee showed higher 2-methylpyrazine (2.20 ng/mL) and furfuryl acetate (2.36 ng/mL) content, which induces a stronger fruity aroma. This proposed rapid, reliable, and low-cost method was shown to be effective in distinguishing coffee postharvest processing methods and evaluating their volatile compounds, which has the potential to be applied for coffee differentiation and quality assurance and control

Common Household Chemicals and the Allergy Risks in Pre-School Age Children

The risk of indoor exposure to volatile organic compounds (VOCs) on allergic airway diseases in children remains unknown.We examined the residential concentrations of VOCs, emitted from building materials, paints, furniture, and other lifestyle practices and the risks of multiple allergic diseases as well as the IgE-sensitization in pre-school age children in Sweden.In a case-control investigation (198 case children with asthma and allergy and 202 healthy controls), air samples were collected in the room where the child slept. The air samples were analyzed for the levels of eight classes of VOCs.A natural-log unit of summed propylene glycol and glycol ethers (PGEs) in bedroom air (equal to interquartile range, or 3.43 - 15.65 µg/m(3)) was associated with 1.5-fold greater likelihood of being a case (95% CI, 1.1 - 2.1), 1.5-fold greater likelihood of asthma (95% CI, 1.0 - 2.3), 2.8-fold greater likelihood of rhinitis (95% CI, 1.6 - 4.7), and 1.6-fold greater likelihood of eczema (95% CI, 1.1 - 2.3), accounting for gender, secondhand smoke, allergies in both parents, wet cleaning with chemical agents, construction period of the building, limonene, cat and dog allergens, butyl benzyl phthalate (BBzP), and di(2-ethylhexyl)phthalate (DEHP). When the analysis was restricted to the cases, the same unit concentration was associated with 1.8-fold greater likelihood of IgE-sensitization (95% CI, 1.1 - 2.8) compared to the non-IgE sensitized cases. No similar associations were found for the other classes of VOCs.We propose a novel hypothesis that PGEs in indoor air exacerbate and/or induce the multiple allergic symptoms, asthma, rhinitis and eczema, as well as IgE sensitization respectively

RNA Interference Can Rebalance the Nitrogen Sink of Maize Seeds without Losing Hard Endosperm

Background: One of the goals of plant breeding is to create crops to provide better nutrition for humans and livestock. Insufficient intake of protein is one of the most severe factors affecting the growth and development of children in developing countries. More than a century ago, in 1896, Hopkins initiated the well-known Illinois long-term selection for maize seed protein concentration, yielding four protein strains. By continuously accumulating QTLs, Illinois High Protein (IHP) reached a protein level 2.5-fold higher than normal maize, with the most increased fraction being the zein protein, which was shown to contain no lysine soon after the long-term selection program initiated. Therefore, IHP is of little value for feeding humans and monogastric animals. Although high-lysine lines of non-vitreous mutants were based on reduced zeins, the kernel soft texture precluded their practical use. Kernel hardness in opaque 2 (o2) could be restored in quality protein maize (QPM) with quantitative trait loci called o2 modifiers (Mo2s), but those did not increase total protein levels. Methods: The most predominant zeins are the 22- and 19-kDa a-zeins. To achieve a combination of desired traits, we used RNA interference (RNAi) against both a-zeins in IHP and evaluated the silencing effect by SDS-PAGE. Total protein, amino acid composition and kernel texture were analyzed. Conclusions: The a-zeins were dramatically reduced, but the high total seed protein level remained unchanged by complementary increase of non-zein proteins. Moreover, the residual zein levels still allowed for a vitreous hard seed. Suc

Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Modular and predictable assembly of porous organic molecular crystals

Nanoporous molecular frameworks are important in applications such as separation, storage and catalysis. Empirical rules exist for their assembly but it is still challenging to place and segregate functionality in three-dimensional porous solids in a predictable way. Indeed, recent studies of mixed crystalline frameworks suggest a preference for the statistical distribution of functionalities throughout the pores rather than, for example, the functional group localization found in the reactive sites of enzymes. This is a potential limitation for 'one-pot' chemical syntheses of porous frameworks from simple starting materials. An alternative strategy is to prepare porous solids from synthetically preorganized molecular pores. In principle, functional organic pore modules could be covalently prefabricated and then assembled to produce materials with specific properties. However, this vision of mix-and-match assembly is far from being realized, not least because of the challenge in reliably predicting three-dimensional structures for molecular crystals, which lack the strong directional bonding found in networks. Here we show that highly porous crystalline solids can be produced by mixing different organic cage modules that self-assemble by means of chiral recognition. The structures of the resulting materials can be predicted computationally, allowing in silico materials design strategies. The constituent pore modules are synthesized in high yields on gram scales in a one-step reaction. Assembly of the porous co-crystals is as simple as combining the modules in solution and removing the solvent. In some cases, the chiral recognition between modules can be exploited to produce porous organic nanoparticles. We show that the method is valid for four different cage modules and can in principle be generalized in a computationally predictable manner based on a lock-and-key assembly between modules