ALBERT

Description: Natural products play vital roles against infectious diseases since ancient times and most drugs in use today are derived from natural sources. Worldwide, multi-drug resistance becomes a massive threat to the society with increasing mortality. Hence, it is very crucial to identify alternate strategies to control these ‘super bugs’. Pseudomonas aeruginosa is an opportunistic pathogen reported to be resistant to a large number of critically important antibiotics. Quorum sensing (QS) is a cell–cell communication mechanism, regulates the biofilm formation and virulence factors that endow pathogenesis in various bacteria including P. aeruginosa. In this study, we identified and evaluated quorum sensing inhibitors (QSIs) from plant-based natural products against P. aeruginosa. In silico studies revealed that catechin-7-xyloside (C7X), sappanol and butein were capable of interacting with LasR, a LuxR-type quorum sensing regulator of P. aeruginosa. In vitro assays suggested that these QSIs significantly reduced the biofilm formation, pyocyanin, elastase, and rhamnolipid without influencing the growth. Especially, butein reduced the biofilm formation up to 72.45% at 100 µM concentration while C7X and sappanol inhibited the biofilm up to 66% and 54.26% respectively. Microscale thermophoresis analysis revealed that C7X had potential interaction with LasR (KD = 933±369 nM) and thermal shift assay further confirmed the biomolecular interactions. These results suggested that QSIs are able to substantially obstruct the P. aeruginosa QS. Since LuxR-type transcriptional regulator homologues are present in numerous bacterial species, these QSIs may be developed as broad spectrum anti-infectives in the future.

Description: Respiratory syncytial virus (RSV) is a major pathogen that causes severe lower respiratory tract infection in infants, the elderly and the immunocompromised worldwide. At present no approved specific drugs or vaccines are available to treat this pathogen. Recently, several promising candidates targeting RSV entry and multiplication steps are under investigation. However, it is possible to lead to drug resistance under the long-term treatment. Therapeutic combinations constitute an alternative to prevent resistance and reduce antiviral doses. Therefore, we tested in vitro two-drug combinations of fusion inhibitors (GS5806, Ziresovir and BMS433771) and RNA-dependent RNA polymerase complex (RdRp) inhibitors (ALS8176, RSV604, and Cyclopamine). The statistical program MacSynergy II was employed to determine synergism, additivity or antagonism between drugs. From the result, we found that combinations of ALS8176 and Ziresovir or GS5806 exhibit additive effects against RSV in vitro, with interaction volume of 50 µM2% and 31 µM2% at 95% confidence interval, respectively. On the other hand, all combinations between fusion inhibitors showed antagonistic effects against RSV in vitro, with volume of antagonism ranging from −50 µM2 % to −176 µM2 % at 95% confidence interval. Over all, our results suggest the potentially therapeutic combinations in combating RSV in vitro could be considered for further animal and clinical evaluations.

Description: Leaf chlorophyll content (LCC) is one of the most important factors affecting photosynthetic capacity and nitrogen status, both of which influence crop harvest. However, the development of rapid and nondestructive methods for leaf chlorophyll estimation is a topic of much interest. Hence, this study explored the use of the machine learning approach to enhance the estimation of leaf chlorophyll from spectral reflectance data. The objective of this study was to evaluate four different approaches for estimating the LCC of apple tree leaves at five growth stages (the 1st, 2nd, 3rd, 4th and 5th growth stages): (1) univariate linear regression (ULR); (2) multivariate linear regression (MLR); (3) support vector regression (SVR); and (4) random forest (RF) regression. Samples were collected from the leaves on the eastern, western, southern and northern sides of apple trees five times (1st, 2nd, 3rd, 4th and 5th growth stages) over three consecutive years (2016–2018), and experiments were conducted in 10–20-year-old apple tree orchards. Correlation analysis results showed that LCC and ST, LCC and vegetation indices (VIs), and LCC and three edge parameters (TEP) had high correlations with the first-order differential spectrum (FODS) (0.86), leaf chlorophyll index (LCI) (0.87), and (SDr − SDb)/ (SDr + SDb) (0.88) at the 3rd, 3rd, and 4th growth stages, respectively. The prediction models of different growth stages were relatively good. The MLR and SVR models in the LCC assessment of different growth stages only reached the highest R2 values of 0.79 and 0.82, and the lowest RMSEs were 2.27 and 2.02, respectively. However, the RF model evaluation was significantly better than above models. The R2 value was greater than 0.94 and RMSE was less than 1.37 at different growth stages. The prediction accuracy of the 1st growth stage (R2 = 0.96, RMSE = 0.95) was best with the RF model. This result could provide a theoretical basis for orchard management. In the future, more models based on machine learning techniques should be developed using the growth information and physiological parameters of orchards that provide technical support for intelligent orchard management.

Description: Three near-infrared emitters (2TPA-QBT, 2MeTPA-BT and TPA-QBT-MeTPA) were rationally designed and synthesized. Density functional theory (DFT) and time-dependent density functional theory (TDDFT) calculations showed that the introduction of mono- or di-methyl groups between the donors and acceptor could result in the spatial configuration changing greatly for 2MeTPA-QBT and TPA-QBT-MeTPA compared to their parent compound 2TPA-QBT. The emission of TPA-QBT-MeTPA had a more obvious hybridized local and charge transfer feature (HLCT) based on the influence of the steric hindrance of the methyl substituent. Attributed to their different spatial configurations and luminescence mechanisms, different emission wavelengths with photoluminescent quantum yields of 26%, 38% and 34% in toluene, as well as 24%, 27% and 31% in 4,4′-bis(N-carbazolyl)-1,1′-biphenyl (CBP) doped film, were observed for 2TPA-QBT, 2MeTPA-QBT and TPA-QBT-MeTPA, respectively. The constructed organic light-emitting devices (OLEDs) displayed electroluminescence with emission peaks at 728, 693 and 710 nm, with maximum external quantum efficiencies of 1.58%, 1.33% and 3.02% for the 2TPA-QBT, 2MeTPA-QBT and TPA-QBT-MeTPA-doped OLEDs, respectively. This work illustrated the effect of spatial configuration changes on the luminescence properties of donor-acceptor-type organic emitters.