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The growing burden of expired medicines contributes to environmental contamination and landfill waste accumulation. Medicinal honey, with its non-toxic nature and potentially long shelf-life, represents a promising and underutilised therapeutic that avoids some of these issues. However, limited knowledge on how its antimicrobial properties change over time combined with a lack of reliable processes in the honey industry for measuring antimicrobial potential, hinder its clinical adoption. Using a diverse selection of 30 Australian honey samples collected between 2005 and 2007, we comprehensively evaluated their antibacterial and antifungal activity and pertinent physical and chemical properties with the aims of assessing the effect of long-term storage on activity, pinpointing factors associated with antimicrobial efficacy, and establishing robust assessment methods. Minimum inhibitory concentration (MIC) assays proved superior to the standard phenol equivalence assay in capturing the full range of antimicrobial activity present in honey. Correlations between activity and a range of physical and chemical properties uncovered significant associations, with hydrogen peroxide, antioxidant content, and water activity emerging as key indicators in non-Leptospermum honey. However, the complex nature and the diverse composition of honey samples precludes the use of high-throughput chemical tests for accurately assessing this activity, and direct assessment using live microorganisms remains the most economical and reliable method. We provide recommendations for different methods of assaying various honey properties, taking into account their accuracy along with technical difficulty and safety considerations. All Leptospermum and fourteen of seventeen non-Leptospermum honey samples retained at least some antimicrobial properties after 15-17 years of storage, suggesting that honey can remain active for extended periods. Overall, the results of this study will help industry meet the growing demand for high-quality, medicinally active honey while ensuring accurate assessment of its antimicrobial potential.

(1) Background: The oil stability of tree nuts during storage can be influenced by storage conditions such as temperature, humidity, and moisture concentration. However, few studies have assessed how the presence of testa and shell affects the oil stability of tree nuts during storage. We aimed to determine how storage conditions affect oil stability in almond and canarium, in particular, the presence of testa and storage time of nut-in-shell (NIS). (2) Methods: We measured peroxide value (PV), free fatty acid (FFA) and hexanal concentrations of almond and canarium (blanched vs. kernel-in-testa) stored at 45 °C for 24 days. We also measured PV, FFA and fatty acid composition of canarium samples at days 0 and 140 stored as NIS under ambient conditions. (3) Results: The presence of testa in almond and canarium decreased hexanal and PV concentrations at day 24 of incubation. Canarium PV and FFA concentrations increased over 140 days of storage in the shell compared to day 0. However, both PV and FFA concentrations remained within the acceptable threshold during storage. No changes in fatty acid composition were found during NIS storage. (4) Conclusions: Testa and shell could act as a natural coating, slowing down oxidation rates. Hence, long-term storage on nuts in testa or nuts in shell are recommended for tree nuts.

Wheel and rail wear seriously affects the safety and reliability of train operations. In this study single-carriage and double-carriage models considering the connecting unit of a high-speed train are developed to investigate the normal forces, lateral forces, and lateral displacements of wheelsets. Based on the results from these models, the Archard wear model is employed to predict the wheel wear. In addition, based on the daily measured data, a nonlinear autoregulatory (NAR) model and a wavelet neural network (WNN) model are developed to predict the wheel wear over a longer time period. The simulation results show that, compared with the single-carriage model, the normal forces, lateral forces, and lateral displacements of the wheelsets close to the connecting unit in the double-carriage model increase to a certain extent dependent on the speed. The wheel wear predictions show that the wheel wear on the wheelsets near the connecting unit is slightly larger than on the wheelsets far from the connecting unit. Based on the mean square error, the NAR model has somewhat better performance in the wheel wear prediction than the WNN model. The research results represent an important contribution to the maintenance and safe operation of high-speed trains.

Abdominal aortic aneurysm (AAA) is an important cause of death in older adults, which has no current drug therapy. Inflammation and abnormal redox status are believed to be key pathogenic mechanisms for AAA. In light of evidence correlating inflammation with aberrant fatty acid profiles, this study compared erythrocyte fatty acid content in 43 AAA patients (diameter 3.0–4.5 cm) and 52 healthy controls. In addition, the effect of omega-3 PUFA (n-3 PUFA) supplementation on erythrocyte fatty acid content was examined in a cohort of 30 AAA patients as part of a 12 week randomized placebo-controlled clinical trial. Blood analyses identified associations between AAA and decreased linoleic acid (LA), and AAA and increased Δ6-desaturase activity and biosynthesis of arachidonic acid (AA) from LA. Omega-3 PUFA supplementation (1.5 g DHA + 0.3 g EPA/day) decreased red blood cell distribution width (14.8 ± 0.4% to 13.8 ± 0.2%; P = 0.003) and levels of pro-inflammatory n-6 PUFAs (AA, 12.46 ± 0.23% to 10.14 ± 0.3%, P < 0.001; adrenic acid, 2.12 ± 0.13% to 1.23 ± 0.09%; P < 0.001). In addition, Δ-4 desaturase activity increased (DHA/docosapentaenoic acid ratio, 1.85 ± 0.14 to 3.93 ± 0.17; P < 0.001) and elongase 2/5 activity decreased (adrenic acid/AA ratio, 0.17 ± 0.01 to 0.12 ± 0.01; P < 0.01) following supplementation. The findings suggest that n-3 PUFAs improve fatty acid profiles and ameliorate factors associated with inflammation in AAA patients.

The method outlined in this article is a customization of the whole exhaust exposure method generated by Mullins et al. (2016) using reprogrammed primary human airway epithelial cells as described by Martinovich et al. (2017). It has been used successfully to generate recently published data (Landwehr et al. 2021). The goal was to generate an exhaust exposure model where exhaust is collected from a modern engine, real-world exhaust concentrations are used and relevant tissues exposed to assess the effects of multiple biodiesel exposures. Exhaust was generated, gently vacuumed into a dilution chamber where it was diluted 1/15 with air and then vacuumed into an incubator containing the primary cell cultures for exposure. Exhaust physico-chemical properties including combustion gas concentrations and particle spectra were then analyzed using a combustion gas analyzer and a Universal Scanning Mobility Particle Sizer. 24 h after exposure, cellular viability and mediator release were measured using Annexin-V/PI staining and meditator multiplexing kits respectively. This method was generated to test biodiesel exhaust exposures but can be easily adapted for any type of engine exhaust exposure or even potentially other respirable environmental exposures such as woodsmoke.The main customization points for this method are: • Exhaust generated by a diesel engine equipped with EURO VI exhaust after treatment devices including diesel particulate filter and diesel oxidation catalyst. • The generated exhaust was diluted 1/15 with air to replicate real world exposure concentrations. • Used primary human airway epithelial cells obtained from bronchoscope brushings from multiple volunteers and reprogrammed to allow multiple, comparative exposures from the same individual.

We report the first successful primary thoracoscopic repair of congenital diaphragmatic hernia (CDH) in a preterm infant born at 28 weeks of gestation weighing 1,043 g. Left-sided CDH was incidentally diagnosed on postnatal chest X-ray on day 1. The neonate subsequently underwent thoracoscopic repair with primary closure of the defect on day 8 weighing 1,150 g. Intraoperative arterial blood gas monitoring including end tidal carbon-dioxide remained within normal range throughout. Postoperative recovery was uneventful. One year neurodevelopmental outcome was normal for age with no CDH recurrence.

Abstract Ilex paraguariensis (yerba mate) is a native species from South America and is a rich source of bioactive compounds. There is a lack of research efforts on the phytochemical investigation of callus culture from this species. In the present study, an effort was made to optimize callus culture conditions and to identify secondary compounds. Calli were induced from 10 genotypes using leaf explants and the best genotype was selected to evaluate the effects of cytokinin types and concentrations on callus induction and biomass accumulation. The best genotype and cytokinin treatment were used to conduct one last experiment with sucrose concentrations in culture media and its effects on calli biomass, antioxidant activity and secondary compounds accumulation. Callus initiation was genotype dependent, and the 6-156-6 line had the best response. Zeatin supplemented medium showed higher callus induction rate (82%) and higher biomass accumulation after 120 days (328.2 mg). Higher biomass and secondary compounds accumulation were observed for calli on 3% sucrose medium. Antioxidant activity was not affected by sucrose concentrations. Yerba mate callus culture allowed the accumulation of chlorogenic acid, cryptochlorogenic acid, neochlorogenic acid, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, theobromine and caffeine.

Hyperspectral image (HSI) analysis has the potential to estimate organic compounds in plants and foods. Curcumin is an important compound used to treat a range of medical conditions. Therefore, a method to rapidly determine rhizomes with high curcumin content on-farm would be of significant advantage for farmers. Curcumin content of rhizomes varies within, and between varieties but current chemical analysis methods are expensive and time consuming. This study compared curcumin in three turmeric (Curcuma longa) varieties and examined the potential for laboratory-based HSI to rapidly predict curcumin using the visible–near infrared (400–1000 nm) spectrum. Hyperspectral images (n = 152) of the fresh rhizome outer-skin and flesh were captured, using three local varieties (yellow, orange, and red). Distribution of curcuminoids and total curcumin was analysed. Partial least squares regression (PLSR) models were developed to predict total curcumin concentrations. Total curcumin and the proportion of three curcuminoids differed significantly among all varieties. Red turmeric had the highest total curcumin concentration (0.83 ± 0.21%) compared with orange (0.37 ± 0.12%) and yellow (0.02 ± 0.02%). PLSR models predicted curcumin using raw spectra of rhizome flesh and pooled data for all three varieties (R2c = 0.83, R2p = 0.55, ratio of prediction to deviation (RPD) = 1.51) and was slightly improved by using images of a single variety (orange) only (R2c = 0.85, R2p = 0.62, RPD = 1.65). However, prediction of curcumin using outer-skin of rhizomes was poor (R2c = 0.64, R2p = 0.37, RPD = 1.28). These models can discriminate between ‘low’ and ‘high’ values and so may be adapted into a two-level grading system. HSI has the potential to help identify turmeric rhizomes with high curcumin concentrations and allow for more efficient refinement into curcumin for medicinal purposes.