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The flowers of selected Camellia yuhsienensis Hu specimens were studied at different stages of flowering to determine the volatile components of floral fragrance and how their concentrations changed during efflorescence. The mechanism of fragrance formation and release was also studied in order to provide a theoretical basis for the practical use of C. yuhsienensis Hu flowers. Headspace solid‐phase microextraction (HS‐SPME) was used to extract the natural floral volatile oils of C. yuhsienensis Hu at the different stages, and the floral fragrance components were analysed by gas chromatography–mass spectrometry (GC–MS). A total of 31, 59 and 55 compounds were detected at the budding, early‐blooming and full‐blooming stages respectively. These floral fragrance components included terpene alcohols, as well as other aromatic and aliphatic compounds, and the relative concentrations of the various compounds at different stages of flowering, were different, and those of fatty alcohols and terpene alcohols having higher relative contents at all stages. The main component at the budding stage of C. yuhsienensis Hu was ocimene, which has a grassy fragrance, accompanied by the scent of neroli oil, which gives it a refreshing, gentle and sweet, and explains why the floral fragrance of C. yuhsienensis Hu at the budding stage is extremely thin: the main component during the early‐blooming stage was 3‐carene. A higher percentage of 3‐carene increased the sweetness of the scent, manifesting the typical fragrant characteristics of C. yuhsienensis Hu. The main identified compound at the full‐blooming stage was α‐farnesene, which has a delicate fragrance, accompanied by a balsamic aroma, similar to the scent of gardenia, which is consistent with the sensory characteristics of C. yuhsienensis Hu. [ABSTRACT FROM AUTHOR]

Background: Diabetes retinopathy (DR) is a complication of diabetes that affects patients' vision. Previous studies have found blueberry anthocyanins extract (BAE) can inhibit the progression of DR, but its mechanism is not completely clear. Methods: To study the role of BAE in diabetes retinopathy, we treated human retinal endothelial cells (HRCECs) with 30 mM high glucose to simulate the microenvironment of diabetes retinopathy and used BAE to intervene the in vitro high glucose-induced retinopathy model. HRCEC cell viability and apoptosis rates were examined by Cell Counting Kit 8 (CCK-8) assay and flow cytometry assay. The binding sites between miR-33 and glucocorticoid-induced transcript 1 (GLCCI1) were assessed by luciferase reporter assay. Retinal neovascularization and oxidative stress contribute to diabetic retinopathy. The tubule formation assay was applied to detect the retinal neovascularization. The oxidative stress in the HRCECs was manifested by the reactive oxygen species (ROS) level, the malondialdehyde (MDA) level, and the superoxide dismutase (SOD) activity. Results: Compared with HRCECs cells cultured under normal conditions, high glucose (HG) can induce oxidative stress in HRCRCs, specifically manifested in the increase of ROS and MDA levels, and the decrease of SOD activity. BAE relieved the tubule formation in n the HRCEC. BAE also relieved the ROS and MDA levels and increased the SOD activity. Luciferase reporter assay revealed that GLCCI1 is a target molecule downstream of miR-33. In HRCEC, BAE significantly inhibited the expression of miR-33 induced by HG. miR-33 mimic inhibited the BAE's effects on oxidative stress and angiogenesis in an in vitro high glucose-induced retinopathy model. Conclusion: BAE alleviated the oxidative stress and microangiogenesis of HRCEC by regulating the miR-33 /GLCCI1 axis. [ABSTRACT FROM AUTHOR]

A new method is developed for the robust stabilization of a Markov jump system with general discrete state time-delay and partly unknown transition probabilities. In contrast to most existing literature, a set of numerical testable conditions, rather than a huge matrix inequality, are established for the resulting closed-loop system in order to justify the stochastic stability and disturbance attenuation capability with the aid of a non-monotonic design approach. To be specific, by constructing a stochastic Lyapunov function via the application of an n -samples variation, sufficient conditions for the existence of a dissipative state feedback controller are derived with less conservativeness, that is, with larger stochastic stable region and better attenuation level. Three examples including a numerical example, a pest's structured population model and an F-404 test aircraft model are presented to demonstrate the advantage and practical potential of the proposed methodology. [ABSTRACT FROM AUTHOR]

A Parasitic Model is proposed in this study for Digital Earth running on mobile phones through a mobile network. Because of mobile phones' limited capabilities in high-performance computing, rendering, storing, and networking (CRSN), these functions are accomplished by a superior host computer in this model. Rendered virtual scenes are compressed in a time-series as a data stream and are sent to the mobile phone through a mobile network, thus allowing Digital Earth to be operated on a mobile phone. This study examines a prototype and shows that a Mobile Digital Earth based on a Parasitic Model can achieve functionality beyond the mobile phone's actual hardware capabilities and can reduce network traffic. These results demonstrate quasi-real-time interactions, but with bandwidth increases in next-generation mobile networks such as 4G and 5G, there is potential for real-time interactions in the near future. [ABSTRACT FROM AUTHOR]

COVID-19 vaccine-induced protection declines over time. This waning of immunity has been described in modelling as a lower level of protection. This study incorporated fine-scale vaccine waning into modelling to predict the next surge of the Omicron variant of the SARS-CoV-2 virus. In Hong Kong, the Omicron subvariant BA.2 caused a significant epidemic wave between February and April 2022, which triggered high vaccination rates. About half a year later, a second outbreak, dominated by a combination of BA.2, BA.4 and BA.5 subvariants, began to spread. We developed mathematical equations to formulate continuous changes in vaccine boosting and waning based on empirical serological data. These equations were incorporated into a multi-strain discrete-time Susceptible-Exposed-Infectious-Removed model. The daily number of reported cases during the first Omicron outbreak, with daily vaccination rates, the population mobility index and daily average temperature, were used to train the model. The model successfully predicted the size and timing of the second surge and the variant replacement by BA.4/5. It estimated 655,893 cumulative reported cases from June 1, 2022 to 31 October 2022, which was only 2.69% fewer than the observed cumulative number of 674,008. The model projected that increased vaccine protection (by larger vaccine coverage or no vaccine waning) would reduce the size of the second surge of BA.2 infections substantially but would allow more subsequent BA.4/5 infections. Increased vaccine coverage or greater vaccine protection can reduce the infection rate during certain periods when the immune-escape variants co-circulate; however, new immune-escape variants spread more by out-competing the previous strain., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)