ActivePPI: quantifying protein-protein interaction network activity with Markov random fields.

MOTIVATION: Protein-protein interactions (PPI) are crucial components of the biomolecular networks that enable cells to function. Biological experiments have identified a large number of PPI, and these interactions are stored in knowledge bases. However, these interactions are often restricted to specific cellular environments and conditions. Network activity can be characterized as the extent of agreement between a PPI network (PPIN) and a distinct cellular environment measured by protein mass spectrometry, and it can also be quantified as a statistical significance score. Without knowing the activity of these PPI in the cellular environments or specific phenotypes, it is impossible to reveal how these PPI perform and affect cellular functioning. RESULTS: To calculate the activity of PPIN in different cellular conditions, we proposed a PPIN activity evaluation framework named ActivePPI to measure the consistency between network architecture and protein measurement data. ActivePPI estimates the probability density of protein mass spectrometry abundance and models PPIN using a Markov-random-field-based method. Furthermore, empirical P-value is derived based on a nonparametric permutation test to quantify the likelihood significance of the match between PPIN structure and protein abundance data. Extensive numerical experiments demonstrate the superior performance of ActivePPI and result in network activity evaluation, pathway activity assessment, and optimal network architecture tuning tasks. To summarize it succinctly, ActivePPI is a versatile tool for evaluating PPI network that can uncover the functional significance of protein interactions in crucial cellular biological processes and offer further insights into physiological phenomena. AVAILABILITY AND IMPLEMENTATION: All source code and data are freely available at https://github.com/zpliulab/ActivePPI.

Effects of Artificial Islands Construction on the Spatial Distribution and Risk Assessment of Heavy Metals in the Surface Sediments from a Semi-closed Bay (Longkou Bay), China.

Artificial islands construction can significantly influence the spatial distribution of heavy metals in inshore sediments. In this study, the distribution and contamination of heavy metals (Cd, Co, Cr, Cu, Ni, Pb, Zn, As and Hg) in inshore sediments of the Longkou Bay and artificial island adjacent areas were investigated in 2013 and 2014, respectively. Results showed that the contents of heavy metals increased in the Longkou Bay and decreased in the west of the artificial island in 2014 compared with 2013. The contamination and potential eco-risk of heavy metals in the sediments were higher in 2014 than those in 2013. Cd and Hg showed a high potential eco-risk in LK02, and other metals were in the lower level. The results indicated that after the construction of artificial islands in the Longkou Bay, the contamination and eco-risk of heavy metals in the sediments markedly increased in the Longkou Bay.

Potential source contributions and risk assessment of PAHs in sediments from the tail-reaches of the Yellow River Estuary, China: PCA model, PMF model, and mean ERM quotient analysis.

Principal component analysis (PCA), positive matrix factorization (PMF), and the mean effects range-median quotient (MERM-Q) models were employed to determine occurrence levels, sources, and potential toxicological significance of polycyclic aromatic hydrocarbons (PAHs) in surface sediments of the Yellow River Estuary, China. Due to the grain size of sediments, cumulative effects, and distribution of oil fields, the total concentration of the 16 U.S. Environmental Protection Agency (US EPA) priority PAHs (T-PAHs) measured in sediments along transects in the offshore area was 119.51 ± 39.58 ng g-1 dry weight (dw), which is notably higher than that measured in rivers (75.00 ± 12.56 ng g-1 dw) and estuaries (67.94 ± 10.20 ng g-1 dw). PAH levels decreased seaward along all the studied transects in coastal Bohai Bay. Multivariate statistical analyses supported that PAHs in sediments were principally derived from coal and biomass combustion, oil pollution, and vehicular emissions. Based on the MERM-Q (0.0050 ± 0.0017), PAHs were at low potential of ecotoxicological contamination level. These results provide helpful information for protecting water resources and serving sustainable development in Construction of Ecological Civilization in the Yellow River Delta.

Petroleum hydrocarbons in a water-sediment system from Yellow River estuary and adjacent coastal area, China: Distribution pattern, risk assessment and sources.

Aliphatic hydrocarbons (AHs), biomarker and polycyclic aromatic hydrocarbons (PAHs) concentrations of surface water and sediment samples collected from Yellow River Estuary and adjacent coastal area in China were measured to determine their spatial distributions, analyze their sources and evaluate the ecological risk of PAHs in the water-sediment system. The spatial distributions of n-alkane in sediments are mainly controlled by the mixing inputs of terrigenous and marine components. In comparison with AHs, the total concentrations of Σ16PAHs in surface sediments from a transect of the offshore area were noticeably higher than that of the riverine and estuary areas. Additionally, the AHs and total PAHs concentrations all indicated an overall pattern of a seaward decrease. The PAHs concentrations during the dry season (mainly in the form of dissolved phase) were higher than that of PAHs (mainly dissolved phase and particulate phase form) in the flooding season. In comparison with global concentration levels of PAHs, the level of PAHs in suspended particulate matter and sediments from the Yellow River Estuary was lower than those from other countries, while the concentration of PAHs in the dissolved phase were in the middle range. Petroleum contamination, mainly from oil exploration and discharge of pollutants from rivers, was the main source of n-alkanes. The PAHs in the river were mostly of petrogenic origin, while those in the estuarial and marine areas originated mainly from pyrogenic sources. The results of the toxicology assessment suggested that the PAHs in sediments from Yellow River Estuary and adjacent coastal area exhibited a low potential eco-toxicological contamination level.