Multispectroscopic and Computational Study of the Interaction between α-Cembrenediol and Bovine Serum Albumin

α-Cembrenediol displays a diverse array of biological activities, encompassing antibacterial, antitumor, and neuroprotective effects. To comprehensively understand the in vivo transport, distribution, and elimination mechanisms associated with α-cembrenediol, its interaction with bovine serum albumin (BSA) was investigated. In this study, the interaction between α-cembrenediol and BSA was explored using various techniques, including UV absorption, steady-state fluorescence, circular dichroism spectrum, molecular docking, and molecular dynamics simulation. The results showed that there was a clear interaction between BSA and α-cembrenediol. Specifically, the KSV and Kb decreased with increasing temperature at 293, 303, and 310 K, indicating that α-cembrenediol interacted with BSA through a static quenching mechanism. Furthermore, the number of binding sites was approximately 1 at the three temperatures, suggesting the presence of a single specific binding site for α-cembrenediol on BSA. Moreover, the binding process occurred spontaneously (ΔG<0), primarily driven by hydrogen bonds and van der Waals forces (ΔH<0 and ΔS<0). α-Cembrenediol bound to the Sudlow site I of BSA. Binding of BSA to α-cembrenediol also caused its conformation to change. This study provides essential insights into the interaction between α-cembrenediol and BSA, contributing to a better understanding of the pharmacokinetic properties of the compound

Under-ice metabolism in a shallow lake in a cold and arid climate

Winter is a long period of the annual cycle of many lakes in the northern hemisphere. Low irradiance, ice, and snow cover cause poor light penetration into the water column of these lakes. Therefore, in northern lakes, respiration often exceeds primary production leading to low dissolved oxygen concentrations. This study aimed to quantify under-ice metabolic processes during winter in an arid zone lake with little snow cover. This study was carried out in a mid-latitude lake in Inner Mongolia, northern China. The study lake receives relatively high incoming solar radiation on the ice in mid-winter, and radiation can penetrate down to the bottom sediment as the lake is shallow and the ice lacks snow cover. Primary production and respiration were estimated during two winters using high-frequency sensor measurements of dissolved oxygen. To quantify under-ice metabolic processes, sensors were deployed to different depths. During both winters, sensors collected data every 10 min over several weeks. The amount of solar radiation controlled photosynthesis under ice; temperature and photosynthesis together appeared to control respiration. The balance between gross primary production and ecosystem respiration was especially sensitive to changes in snow cover, and the balance between P and R decreased. Our data suggest that photosynthesis by plankton, submerged plants, and epiphytic algae may continue over winter in shallow lakes in mid-latitudes when there is no snow cover on the ice, as may occur in arid climates. The continuation of photosynthesis under ice buffers against dissolved oxygen depletion and prevents consequent harmful ecosystem effects.Peer reviewe

Multi-band remote sensing based retrieval model and 3D analysis of water depth in Hulun Lake, China

Hulun Lake, a large lake located on the cold and arid Hulunbeir grassland in the Inner Mongolia Autonomous Region, is the fifth largest in China and the largest in the north of the country. However, the information on the lake’s characteristics (e.g., water depth versus surface area) is scarce in literature. Based on the lake’s physiographic features, this study developed and used a model that merges the sunlight reflection band with the thermal infrared radiation band to simulate the lake’s characteristics. The model verification and error analysis indicated an optimal model structure of logarithm. Thus, this logarithmic model was selected to analyze the spectral data. The results indicated that the model did a good job in reproducing observed water depths and accurately predicted the depths on 24 September 2007. This showed that this model can be reliably applied to the cold and arid region. Subsequently, the results were used to generate a triangular irregular network (TIN) model, which in turn was used to compute the functional relations between water level, surface area, and volume. The correlation between water level and volume is superior to that between water level and area. The regression equation developed in this study can be used to estimate the volume when water elevation is knowninfo:eu-repo/semantics/publishedVersio