Protection of iron-catalysed the radical damage to DNA and lipids by copper (II) bleomycin

The ability of Copper(II)-bleomycin to inhibit oxygen-free-radical damage to biomolecules has been assessed. This copper complex showed inhibitory properties towards iron-catalysed damage to phospholipid membranes and cell-free DNA. It was also able to prevent superoxide-dependent reduction of nitroblue tetrazolium (NBT). Unlike iron, copper-bleomycin does not damage DNA $\text{in vitro}$. This may result from a site-specific dismutation of superoxide radicals on the DNA molecule.     

Screening of Drug Metabolizing Enzymes for the Ginsenoside Compound K In Vitro: An Efficient Anti-Cancer Substance Originating from Panax Ginseng

Ginsenoside compound K (CK), a rare ginsenoside originating from Panax Ginseng, has been found to possess unique pharmacological activities specifically as anti-cancers. However, the role of cytochrome P450s (CYPs) in the metabolism of CK is unclear. In this study, we screened the CYPs for the metabolism of CK in vitro using human liver microsomes (HLMs) or human recombinant CYPs. The results showed that CK inhibited the enzyme activities of CYP2C9 and CYP3A4 in the HLMs. The K_m and V_max values of CK were 84.20±21.92 μM and 0.28±0.04 nmol/mg protein/min, respectively, for the HLMs; 34.63±10.48 μM and 0.45±0.05 nmol/nmol P450/min, respectively, for CYP2C9; and 27.03±5.04 μM and 0.68±0.04 nmol/nmol P450/min, respectively, for CYP3A4. The IC₅₀ values were 16.00 μM and 9.83 μM, and K_i values were 14.92 μM and 11.42μM for CYP2C9 and CYP3A4, respectively. Other human CYP isoforms, including CYP1A2, CYP2A6, CYP2D6, CYP2E1, and CYP2C19, showed minimal or no effect on CK metabolism. The results suggested that CK was a substrate and also inhibitors for both CYP2C9 and CYP3A4. Patients using CK in combination with therapeutic drugs that are substrates of CYP2C9 and CYP3A4 for different reasons should be careful, although the inhibiting potency of CK is much poorer than that of enzyme-specific inhibitors.     

A High-Order,Symplectic, Finite-Difference Time-Domain Scheme for Bioelectromagnetic Applications within the Mother/Fetus Model

An explicit high-order, symplectic, finite-difference time-domain (SFDTD) scheme is applied to a bioelectromagnetic simulation using a simple model of a pregnant woman and her fetus. Compared to the traditional FDTD scheme, this scheme maintains the inherent nature of the Hamilton system and ensures energy conservation numerically and a high precision. The SFDTD scheme is used to predict the specific absorption rate (SAR) for a simple model of a pregnant female woman (month 9) using radio frequency (RF) fields from 1.5 T and 3 T MRI systems (operating at approximately 64 and 128 MHz, respectively). The results suggest that by using a plasma protective layer under the 1.5 T MRI system, the SAR values for the pregnant woman and her fetus are significantly reduced. Additionally, for a 90 degree plasma protective layer, the SAR values are approximately equal to the 120 degree layer and the 180 degree layer, and it is reduced relative to the 60 degree layer. This proves that using a 90 degree plasma protective layer is the most effective and economical angle to use.     

Design of high performance nanozymes: a single-atom strategy

<正>Nanozymes, nanomaterials with enzyme-like characteristics,are emerging as novel artificial enzymes (Gao et al., 2007;Manea et al., 2004; Yan, 2018). They are superior to natural enzymes in many ways, such as higher stability, lower cost in preparation, and better robustness toward harsh environments (Wei and Wang, 2013). Various nanomaterials (e.g.,     

α‐ketoglutarate delays age‐related fertility decline in mammals

The fecundity reduction with aging is referred as the reproductive aging which comes earlier than that of chronological aging. Since humans have postponed their childbearing age, to prolong the reproductive age becomes urgent agenda for reproductive biologists. In the current study, we examined the potential associations of α‐ketoglutarate (α‐KG) and reproductive aging in mammals including mice, swine, and humans. There is a clear tendency of reduced α‐KG level with aging in the follicle fluids of human. To explore the mechanisms, mice were selected as the convenient animal model. It is observed that a long term of α‐KG administration preserves the ovarian function, the quality and quantity of oocytes as well as the telomere maintaining system in mice. α‐KG suppresses ATP synthase and alterations of the energy metabolism trigger the nutritional sensors to down‐regulate mTOR pathway. These events not only benefit the general aging process but also maintain ovarian function and delay the reproductive decline. Considering the safety of the α‐KG as a naturally occurring molecule in energy metabolism, its utility in reproduction of large mammals including humans deserves further investigation.     

The Role of Host Cytoskeleton in Flavivirus Infection

The family of flaviviruses is one of the most medically important groups of emerging arthropod-borne viruses. Host cell cytoskeletons have been reported to have close contact with flaviviruses during virus entry, intracellular transport, replication, and egress process, although many detailed mechanisms are still unclear. This article provides a brief overview of the function of the most prominent flaviviruses-induced or-hijacked cytoskeletal structures including actin, microtubules and intermediate filaments, mainly focus on infection by dengue virus, Zika virus and West Nile virus. We suggest that virus interaction with host cytoskeleton to be an interesting area of future research.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.