A new electrochemical method for the determination of chondroitin sulfate based on its supramolecular interaction with cupferron-lead(II) complex

In this paper, the interaction of cupferron (Cup) and lead (II) complex [Cup-Pb (II)] with chondroitin sulfate (CS) was investigated by linear sweep voltammetric method. In the selected medium of pH 5.5 (acetic acid-hexamine buffer solution), Cup can interact with Pb (II) to form a stable complex of [Cup-Pb(II)], which has a sensitive second order derivative polarographic reductive peak at -0.64V (vs.SCE). After the addition of CS into Cup-Pb (II) complex solution, the reductive peak current decreased without any shift of the peak potential and no new peak appeared, which indicated that an unelectroactive supramolecular complex of CS with [Cup-Pb(II)] was formed. The binding reaction conditions were carefully investigated. Under the optimal conditions, the interaction mechanism was discussed. The decrease of reductive peak current was directly proportional to the CS concentration, thus a new quantitative determination method for CS was established with the linear regression equation as ΔIp″(nA)=36.97 C/mg L-1+12.45 (n=10, γ=0.995). The effects of other substances on the determination were carefully investigated and three synthetic samples were determined with satisfactory results. The binding constant (βs) and the binding number (m) of CS with [Cup-Pb(II)] complex were calculated from the voltammetric data with the results as βs=1.89×1010 and m≈2.5

Genetic and functional characterization of disease associations explains comorbidity

Understanding relationships between diseases, such as comorbidities, has important socio-economic implications, ranging from clinical study design to health care planning. Most studies characterize disease comorbidity using shared genetic origins, ignoring pathway-based commonalities between diseases. In this study, we define the disease pathways using an interactome-based extension of known disease-genes and introduce several measures of functional overlap. The analysis reveals 206 significant links among 94 diseases, giving rise to a highly clustered disease association network. We observe that around 95% of the links in the disease network, though not identified by genetic overlap, are discovered by functional overlap. This disease network portraits rheumatoid arthritis, asthma, atherosclerosis, pulmonary diseases and Crohn's disease as hubs and thus pointing to common inflammatory processes underlying disease pathophysiology. We identify several described associations such as the inverse comorbidity relationship between Alzheimer's disease and neoplasms. Furthermore, we investigate the disruptions in protein interactions by mapping mutations onto the domains involved in the interaction, suggesting hypotheses on the causal link between diseases. Finally, we provide several proof-of-principle examples in which we model the effect of the mutation and the change of the association strength, which could explain the observed comorbidity between diseases caused by the same genetic alterations

An inverse random source problem in a stochastic fractional diffusion equation

In this work the authors consider an inverse source problem the stochastic fractional diffusion equation. The interested inverse problem is to reconstruct the unknown spatial functions f and g (the latter up to the sign) in the source by the statistics of the final time data u(x, T). Some direct problem results are proved at first, such as the existence, uniqueness, representation and regularity of the solution. Then a reconstruction scheme for f and g up to the sign is given. To tackle the ill-posedness, Tikhonov regularization is adopted and some numerical results are displayed.Peer reviewe

Highly Sensitive Detection of Trace Tetracycline in Water Using a Metal-Organic Framework-Enabled Sensor

Due to the abuse application of antibiotics in the recent decades, a high level of antibiotics has been let out and remains in our environment. Electrochemical sensing is a useful method to sensitively detect antibiotics, and the key factor for a successful electrochemical sensor is the active electrode materials. In this study, a sensitive electrochemical sensing platform based on a metal-organic framework (MOF) of MIL-53 (Fe) was facilely fabricated. It shows highly selective and sensitive detection performance for trace tetracycline. Differential pulse voltammetry (DPV) was applied to analyze the detection of tetracycline. The linear range of tetracycline detection was 0.0643 μmol/L-1.53 μmol/L, and the limit of detection (LOD) is 0.0260 μmol/L. Furthermore, the MOF-enabled sensor can be effectively used in actual water bodies. The results indicate that the electrochemical sensor is a high potential sensing platform for tetracycline

Additional file 2 of The role of proteoglycan form of DMP1 in cranial repair

Additional file 2