Distribution Control and Environmental Fate of PFAS in the Offshore Region Adjacent to the Yangtze River Estuary─A Study Combining Multiple Phases Analysis.

The Yangtze River Estuary is the terminal sink of terrestrial per- and polyfluoroalkyl substances (PFAS) from the Yangtze River, while the environmental fate characteristics of legacy and emerging PFAS around this region have rarely been discussed. Here, 24 targeted PFAS in seawater, sediments, suspended particulate matter (SPM), and plankton in the offshore region adjacent to this estuary were investigated. The three dominant PFAS in all phases were perfluorooctanoic acid (PFOA, 23.8-61.9%), perfluorobutanoic acid (PFBA, 23.6-42.8%), and perfluoro(2-methyl-3-oxahexanoic) acid (HFPO-DA, 6.1-12.1%), and perfluoro-1-butane sulfonamide (FBSA, 0.1-7.3%) was first detected. The horizontal distributions of PFAS were dependent on salinity and disturbed by multiple water masses, while the vertical variations could be explained by their different partitioning characteristics in the water-SPM-sediment system (partition coefficients, Log Kd and Log Koc) and plankton (bioaccumulation factors, Log BAF). Although physical mixing was the major driver for PFAS settling (>83.7%), the absolute settling amount caused by the biological pump was still high (150.00-41994.65 ng m-2 day-1). More importantly, we found unexpected high Log Kd values of PFBA (2.24-4.55) and HFPO-DA (2.26-4.67), equal to PFOA (2.28-4.72), which brought concerns about their environmental persistence. Considering the increased detection of short-chain and emerging PFAS, more comprehensive environmental behaviors analysis is required urgently.

Semi-Supervised Deep Kernel Active Learning for Material Removal Rate Prediction in Chemical Mechanical Planarization.

The material removal rate (MRR) is an important variable but difficult to measure in the chemical-mechanical planarization (CMP) process. Most data-based virtual metrology (VM) methods ignore the large number of unlabeled samples, resulting in a waste of information. In this paper, the semi-supervised deep kernel active learning (SSDKAL) model is proposed. Clustering-based phase partition and phase-matching algorithms are used for the initial feature extraction, and a deep network is used to replace the kernel of Gaussian process regression so as to extract hidden deep features. Semi-supervised regression and active learning sample selection strategies are applied to make full use of information on the unlabeled samples. The experimental results of the CMP process dataset validate the effectiveness of the proposed method. Compared with supervised regression and co-training-based semi-supervised regression algorithms, the proposed model has a lower mean square error with different labeled sample proportions. Compared with other frameworks proposed in the literature, such as physics-based VM models, Gaussian-process-based regression models, and stacking models, the proposed method achieves better prediction results without using all the labeled samples.

Recent advances in sample preparation techniques in China.

Sample preparation is the procedure before instrumental analysis and significant to its effectiveness and efficiency. However, this procedure is usually time-consuming, labor intensive, and prone to error. In the last decade, the development of sample preparation techniques has received increasing attention, especially in complex sample application. To pretreat samples faster and more effectively, advanced materials, instrumentation, and methods have been combined with typical techniques, including extraction, membrane separation, and chemical conversion techniques. Researchers in China focused on the development of simple, efficient sample preparation methods with selective enrichment and rapid separation capabilities for target analysis in complicated sample matrix and contribute almost a half of the publications in this specific field. In this review, a panorama of sample preparation techniques in China has been composed from more than 140 references, and we highlight some promising methods developed during recent years and introduce different separation materials with respect to these methods.

A novel phase-unwrapping method by using phase-jump detection and local surface fitting: application to Dixon water-fat MRI.

PURPOSE: This study aims to develop an accurate and robust phase-unwrapping method that works effectively under severe noise, rapid-varying phase, and disconnected regions for water-fat Dixon MRI. METHODS: The proposed method first segments the phase map into blocks by automatically detecting phase jumps, and then clusters the pixels near phase jumps into residual pixels. Thereafter, the proposed method sequentially performs intrablock, interblock, and residual-pixel unwrapping using the local surface fitting approach. To address intrablock wraps, the proposed method segments each block into subblocks using the phase partition approach and then performs inter-subblock unwrapping using a block-growing approach. The phase derivative variance is used as the quality criterion to determine the region-growing path of residual pixels. The performance of the proposed method was evaluated on simulation and in vivo Dixon data. RESULTS: The proposed method obtained accurate phase-unwrapping results in the simulation experiment with severe noise, rapid-varying phase, and disconnected regions, and the mean and SD error ratio was 0.26 ± 0.07%. For 505 in vivo knee and ankle images, the total water-fat swap ratio by the proposed method was 1.78%, whereas those by phase region expanding labeler for unwrapping discrete estimates and clustering and local surface fitting were 38.42% and 7.72%, respectively. CONCLUSION: The proposed method achieves accurate and robust performance in phase unwrapping and can benefit phase-related MRI applications such as Dixon water-fat separation.

Improved dsRNA isolation and purification method validated by viral dsRNA detection using novel primers in Saccharomyces cerevisiae.

Accurate genomic sequencing demands high-quality double-stranded RNA (dsRNA). Existing methods for dsRNA extraction from yeast, fungi, and plants primarily rely on cellulose, suitable only for small volume extractions, or the time-consuming lithium chloride precipitation. To streamline the traditional phenol-chloroform-based dsRNA extraction method, the main challenge is the reduction of mitochondrial DNA (mtDNA) and Single Stranded RNA (ssRNA) to no detectable levels after gel electrophoresis. This challenge is successfully addressed through the modified approach described here, involving phenol extraction at low pH, followed by the addition of ammonium sulfate to the aqueous buffer. The dsRNA isolated using this novel method exhibits comparable quality to that obtained through cellulose purification, and it is readily amenable to RT-PCR. Moreover, a single batch of yeast cell RNA isolation requires only 2-3 h of hands-on time, thus simplifying and expediting the process significantly.•Buffers were redesigned from [32,33,35].•No DNASE, Ribonuclease A or beads were used during the purification.•Simple and inexpensive dsRNA extraction and purification method is described.

The effect of rainfall runoff on phase partition of palladium in receiving water bodies and the underlying influential mechanism.

The influx of rainfall runoff intensifies phase partition of the pollutant in receiving water bodies, and the phase partition plays an important role in the speciation transformation and spatial partition of pollutants. In this study, the Meishe River on Hainan Island, China, was adopted as the research area, and palladium (Pd) was selected as the target pollutant. The purpose of this study was to explore phase partition of Pd in receiving water bodies and the underlying influential mechanism. The partition coefficients (Kds) of Pd between water and suspended particulate matter in receiving water bodies and rainfall runoff were 0.74 (0.1 × 10-2 - 8.75) and 2.74 (0.5 × 10-2 - 15.70), respectively. These results indicated that Pd dominated the dissolved phase in the receiving water bodies and that Pd dominated the particulate phase in rainfall runoff. Variations in the Kd value of Pd in the receiving water bodies were relatively smooth over time during the precipitation events in May and June. There were no significant differences in phase partition of Pd between the receiving water bodies and rainfall runoff. The Kd value for Pd in the receiving water bodies showed a fluctuating upward trend over time during the precipitation events in August, and the difference in Kd values of Pd between the receiving water bodies and the rainfall runoff were large. Variations in the Kd value of Pd among sections of the receiving water bodies could be roughly divided into two categories, namely, U and inverted-U types. After rainfall runoff converged for 20-25 min, the Pd phase transitions were more frequent within 7 m downstream of the outfall. The Kd value of Pd in the receiving water bodies was correlated with pH, Eh, and total suspended solid (TSS), and the correlation coefficients were 0.52, -0.57, and 0.84, respectively (p < 0.05). Compared with rainfall runoff, pH, Eh, TSS had less influence on phase partition of Pd in receiving water bodies. This might be attributed to the dilution effect of natural water and the unique dynamic mechanism of rivers.

Transport and partitioning of metals in river networks of a plain area with sedimentary resuspension and implications for downstream lakes.

This study showed that metal transport and partitioning are primarily controlled by suspended solids with seasonal flow regimes in plain river networks with sedimentary resuspension. Eight metal species containing iron (Fe), manganese (Mn), cadmium (Cd), chrome (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn), in multiple phases of sediments, suspended solids (>0.7 µm), colloids (1 nm-0.7 µm) and dissolved phase (<1 nm) were analysed to characterize their temporal-spatial patterns, partitioning and transport on a watershed scale. Metal concentrations were associated with suspended solids in the water column and decreased from low flow to high flow. However, metal partitioning between particulate phase (suspended solids) and dissolvable phases (colloids and dissolved phase) was reversed and increased from low flow to high flow with decreased concentration of total suspended solids and median particle size. Partition coefficients (kp) showed differences among metal species, with higher values for Pb (354.3-649.0 L/g) and Cr (54.2-223.7 L/g) and lower values for Zn (2.5-25.2 L/g) and Cd (17.3-21.0 L/g). Metal concentrations in sediments increased by factors of 1.2-3.0 from upstream to downstream in watersheds impacted by urbanization. The behaviours of metals in rivers provide deeper insight into the ecological risks they pose for downstream lakes, where increased redox potential and organic matter may increase metal mobility due to algal blooms. Areas with heavy pollution of metals and the transport routines of metals in the river networks were also revealed in our research.

Development of an innovative maceration technique to optimize extraction and phase partition of natural products.

The active component extraction from plants is the first crucial step in natural product research. For non-targeted extraction with an objective to isolate and characterize as many compounds as possible, the most classical technique, and the simplest to implement, is the Soxhlet extraction; however, it does not allow retrieving all the compounds from the plant (when it does not additionally cause artifacts during long heating process). The second most used technique is the extraction by successive macerations using solvents of increasing polarity. While this method is frequently used, few studies are available to rationalize and optimize it. Furthermore, this extraction technique requires some enhancement mainly for efficiency, environmental and time constraint reasons. Here, we present an innovative method of successive macerations using a mixture of solvents with the aim of simultaneously improving the yield, the partition of the compounds between the different phases and reducing the volume of extraction solvents. Triphasic systems were prepared by mixing five solvents (n-heptane, ethyl acetate, acetonitrile, butan-1-ol, water) in various proportions. To validate this method, the most efficient triphasic system was subsequently used to perform three successive macerations with a polarity gradient on a model plant before being extended to several alpine plants. Our results showed an overall good yield compared to conventional maceration techniques, while improving phase partition and reducing extraction time and volume of solvents.

Distribution, residue level, sources, and phase partition of antibiotics in surface sediments from the inland river: a case study of the Xiangjiang River, south-central China.

In view of the increasing attention on antibiotic contamination and their scarce data in the inland river (especially for the sediment), the occurrence of 28 antibiotics in sediments from the Xiangjiang River was comprehensively analyzed, and 22 antibiotics were detected with a total concentration ranging from 4.07 to 2090 ng g-1. The residue was almost at a moderate or higher level in the aquatic environment around the world. Fluoroquinolones and tetracyclines were the dominant detected antibiotics, and the maximum total concentration could reach to 2085 ng g-1, though that in surface water was just 33.4 ng L-1. Oxytetracycline and chlortetracycline could be detected with high concentration in areas with lower population density. Usage profile of each antibiotic may be responsible for the spatial variation. Principal component analysis-multiple linear regression model indicated that direct discharge of domestic wastewater and livestock or aquaculture sewage could contribute 94.2% of the pollution. Redundancy analysis was used to screen out the environment variables, which were closely related to the pseudo-partitioning coefficients (Kd) of antibiotics in sediment and surface water for the first time, and showed that the Kd was correlated with sediment pH negatively and organic carbon, total phosphorus, and conductivity of the sediments positively. High sedimentary organic carbon was considered to promote the higher Kd in this river. This study would deepen the understanding of the occurrence of antibiotics in sediments from the inland rivers and provide scientific support for controlling the antibiotic contamination.

PCDD/F levels and phase distributions in a full-scale municipal solid waste incinerator with co-incinerating sewage sludge.

Co-incinerating sewage sludge in municipal solid waste incinerators (MSWIs) is an up-to-date disposal way with great prospects to market. To verify the environmental safety of this disposal method, a field study was conducted in a MSWI which has achieved PCDD/Fs ultra-low emission. PCDD/F phase partitioning characteristics, congener profiles, and the influence of selective catalytic reduction (SCR) were also investigated. PCDD/F emission levels ranged from 0.0031 to 0.0053 ng I-TEQ/Nm3, distinctly lower than the national standard. For tests co-incinerating 5% sludge, PCDD/F emission levels were averagely 32% lower than tests mono-combusting municipal solid waste. The phase partitioning study found that PCDD/Fs enriched in condensed water took a non-negligible proportion of the total concentration in flue gas. The removal efficiency of SCR in tests co-incinerating sludge was averaged at 41.9%. However, in tests without adding sewage sludge, PCDD/F concentrations in flus gas after SCR were increased. It was found that the elevations were mainly attributed to the increase of low-chlorinated PCDF congeners in gas-phase. By inference, memory effect existing in SCR might be responsible for the increase of PCDD/F levels. PCDD to PCDF ratios in most of the sampling points were >1, suggesting that de novo synthesis is not the dominant formation pathway in the studied incinerator. This study verified that co-incinerating sewage sludge in the MSWI would not elevate the emission levels of PCDD/Fs. If all of the yielded municipal waste is incinerated with adding 5% sewage sludge, more than half of sewage sludge can be disposed safely in Shenzhen.

Distribution, source, and environmental risk assessment of phthalate esters (PAEs) in water, suspended particulate matter, and sediment of a typical Yangtze River Delta City, China.

Phthalates (PAEs) in drinking water sources such as the Yangtze River in developing countries had aroused widespread concern. Here, the water, suspended particulate matter (SPM), and sediment samples were collected from 15 sites in wet and dry seasons in Zhenjiang, for the determination of six PAEs (DMP, DEP, DIBP, DBP, DEHP, and DOP) using the solid-phase extraction (SPE) or ultrasonic extraction coupled with gas chromatography-mass spectrometry (GC-MS). The total concentrations of six PAEs (Σ6PAEs) spanned a range of 2.65-39.31 µg L-1 in water, 1.97-34.10 µg g-1 in SPM, and 0.93-34.70 µg g-1 in sediment. The partition coefficients (Kd1) of PAEs in water and SPM phase ranged from 0.004 to 3.36 L g-1 in the wet season and from 0.12 to 2.84 L g-1 in the dry season. Kd2 of PAEs in water and sediment phase was 0.001-9.75 L g-1 in the wet season and 0.006-8.05 L g-1 in the dry season. The dominant PAEs were DIBP, DBP, and DEHP in water and SPM, DIBP, DEHP, and DOP in sediment. The concentration of DBP in water exceeded the China Surface Water Standard. The discharge of domestic sewage and industrial wastewater might be the main potential sources of PAEs. The risk quotient (RQ) method used for the risk assessment revealed that DBP (0.01 < RQ < 1) posed a medium risk, while DIBP and DEHP (RQ > 1) posed a high environmental risk in water, DIBP (RQ > 1) also showed a high risk in sediment.

Occurrence, transportation, and distribution difference of typical herbicides from estuary to bay.

In several watersheds, agricultural activities are the cause of pollution, mainly due to the discharge of herbicides. Often, these herbicide plumes are transported to the surrounding bays. Samples of water, suspended particulate sediments (SPSs), and sediments from 37 sites in the Jiaozhou Bay in the western Pacific Ocean were collected in April 2018. The total concentrations of atrazine and acetochlor in these samples were analyzed, that showed different patterns in each sampled area. Atrazine had 2-3 times higher concentrations in coastal areas and bays compared to the estuary, indicating that it had a higher residence time in the marine environment. In contrast, acetochlor concentration decreased with an increase in the depth of seawater. Both the spatial distributions and the vertical concentrations in water, SPS, and sediment proved that these two herbicides had different responses during transportation from the estuary to the bay. Despite the significant difference in concentration of the two herbicides in the water and sediment, their spatially averaged value in SPS was very close, indicating that the particles had saturated sorption capability. The organic carbon normalized partition coefficient (LogKoc) was used to explain the partitioning of the herbicides between water and sediment. The LogKoc difference between herbicides demonstrated that acetochlor was strongly phase partitioned in the coastal and the bay areas, thereby causing similar distributions of acetochlor in the three matrices. Atrazine had a higher LogKoc value in the estuary, which explained its higher concentration in the estuary SPS. The correlation and redundancy analyses both demonstrated that the concentrations of the herbicides in water were sensitive to dissolved organic carbon and dissolved oxygen. The current tides and bathymetry were the critical factors in determining the spatial distribution of herbicides in the water and sediment, resulting in a low herbicide load in the river mouth area.

Incorporating a non-reactive heavy metal simulation module into SWAT model and its application in the Athabasca oil sands region.

Heavy metal contaminations in an aquatic environment is a serious issue since the exposure to toxic metals can cause a variety of public health problems. A watershed-scale model is a useful tool for predicting and assessing heavy metal fate and transport in both terrestrial and aquatic environments. In this study, we developed a simulation module for non-reactive heavy metals and incorporated it into the widely used Soil Water Assessment Tool (SWAT) model. The simulated processes in the developed model include heavy metal deposition, partitioning in soil and water, and transport by different pathways in both terrestrial and aquatic environments. Three-phase partitioning processes were considered in the module by simulating heavy metals portioning to dissolved organic carbon in the soil and stream. This developed module was used for watershed-scale simulation of heavy metal processes in the Muskeg River watershed (MRW) of the Athabasca oil sands region in western Canada for the first time. The daily streamflow and sediment load from 2015 to 2017 were first calibrated and validated. Subsequently, the daily Lead and Copper loads at the outlet station were used for heavy metal calibration and validation. The performances for the daily heavy metal loads simulation during the whole simulation period can be considered as "satisfactory" based on the recommended model performance criteria with the Nash-Sutcliffe efficiency as 0.41 and 0.71 for Pb and Cu loads, respectively. The simulation results indicate that the spring and summer are hot moments for heavy metal transport and the snowmelt in spring and rainfall runoff events in summer are the main driving forces for the metal transport in the MRW. We believe the developed model can be a useful tool for simulating the fate and transport of non-reative heavy metals at watershed scale and further used to assess management scenarios for mitigating heavy metal pollution in the Athabasca oil sands region.

Soft sensor design based on phase partition ensemble of LSSVR models for nonlinear batch processes.

Traditional single model based soft sensors may have poor performance on quality prediction for batch processes because of the strong nonlinearity, multiple-phase, and time-varying characteristics. Therefore, a phase partition based ensemble learning framework upon least squares support vector regression (LSSVR) is proposed for soft sensor modeling. Firstly, multiway principal component analysis (MPCA) is employed to handle high-dimensional datasets and extract essential correlation information. Then, different operation phases of the process can be identified by the phase partition strategy based on Gaussian mixture model (GMM) method. Meanwhile, the optimal Gaussian component number is determined by Bayesian information criterion (BIC) technique. Further, multiple localized LSSVR models are constructed to characterize the various dynamic relationships between quality and process variables for local regions, while the grid search (GS) and ten-fold cross-validation methods are introduced to parameter optimization for each local model. Finally, the posterior probability for each test sample with respect to different phases can be estimated by Bayesian inference strategy, and local outputs are integrated to produce the final quality prediction results. Feasibility and superiority of the proposed soft sensor are validated through a case study for penicillin fermentation process. It can achieve satisfactory prediction accuracy and effectively tackle nonlinear and multi-phase modeling problems in chemical and biological processes.

Isolation of Plasma Membrane and Plasma Membrane Microdomains.

The plasma membrane surrounds the cytoplasm of a cell and functions as a barrier to separate the intracellular compartment from the extracellular environment. Protein and lipid components distribute nonuniformly and the components form clusters with various functions in the plasma membrane. These clusters are called as "microdomains." In plant cells, microdomains have been studied extensively because they play important roles in biotic/abiotic stress responses, cellular trafficking, and cell wall metabolism. Here we describe a standard protocol for the isolation of the plasma membrane and microdomains from plant cells, Arabidopsis and oat.

Are fluorine-rich pharmaceuticals lost by partition into fluorous phases?

The recently developed technology of droplet microfluidics has demonstrated great potential for many applications such as biochemical assay, high throughput screening, cell culture, directed evolution, and chemical synthesis. Intrigued by its capabilities for miniaturization, flexible manipulation, rapid reagent mixing and high throughput experimentation and analysis, the pharmaceutical industry has begun to investigate droplet microfluidic implementation in medicinal and process chemistry. Segmented by an immiscible secondary phase, usually perfluorinated oil, aqueous or organic droplets serve as individual micro-reactors without suffering cross-contamination. As many drug molecules contain fluorines, it is necessary to investigate whether such compounds will be preferentially extracted into the fluorous phase via fluorophilic solvation, which could lead to erroneous analytical results. In this work, we chose drugs with up to 10 fluorines to probe their partition into perfluorodecalin (PFD) from a variety of organic solvents. A fast and straightforward MISER (Multiple Injections in a Single Experimental Run) LC-MS method was applied to measure the loss of drug after mixing with PFD. We found that no significant partition occurred, with the concentration of drugs in the 'experimental' group measured as ±10% of the 'control' group. The RSD% of multiple injections is <5%. The finding was further validated by the conventional LC-MS approach.

Canola oil is an excellent vehicle for eliminating pesticide residues in aqueous ginseng extract.

BACKGROUND: We previously reported that two-phase partition chromatography between ginseng water extract and soybean oil efficiently eliminated pesticide residues. However, an undesirable odor and an unpalatable taste unique to soybean oil were two major disadvantages of the method. This study was carried out to find an alternative vegetable oil that is cost effective, labor effective, and efficient without leaving an undesirable taste and smell. METHODS: We employed six vegetable oils that were available at a grocery store. A 1-mL sample of the corresponding oil containing a total of 32 pesticides, representing four categories, was mixed with 10% aqueous ginseng extract (20 mL) and equivalent vegetable oil (7 mL) in Falcon tubes. The final concentration of the pesticides in the mixture (28 mL) was adjusted to approximately 2 ppm. In addition, pesticides for spiking were clustered depending on the analytical equipment (GC/HPLC), detection mode (electron capture detector/nitrogen-phosphorus detector), or retention time used. Samples were harvested and subjected to quantitative analysis of the pesticides. RESULTS: Soybean oil demonstrated the highest efficiency in partitioning pesticide residues in the ginseng extract to the oil phase. However, canola oil gave the best result in an organoleptic test due to the lack of undesirable odor and unpalatable taste. Furthermore, the qualitative and quantitative changes of ginsenosides evaluated by TLC and HPLC, respectively, revealed no notable change before or after canola oil treatment. CONCLUSION: We suggest that canola oil is an excellent vehicle with respect to its organoleptic property, cost-effectiveness and efficiency of eliminating pesticide residues in ginseng extract.

Separation properties of saccharides on a hydrophilic stationary phase having hydration layer formed zwitterionic copolymer.

A novel water-holding adsorbent bonded with a zwitterionic polymer, diallylamine-maleic acid copolymer, was developed. With this adsorbent, hydrophilic solutes are partitioned by a hydration layer that forms on the zwitterions, as a main separating force. When the adsorbent was used to separate saccharides by normal-phase partition chromatography, the saccharides eluted in the order, mono-, di- and trisaccharide. The elution profile for mono- and di-saccharides was similar but not identical to that on anion exchange columns. This indicated that the adsorbent exhibited a complex retention behavior by the existence of both anion and cation exchange moieties in the functional polymer. Selecting Na(+) as a counter-ion of the maleate moiety enhanced the retention of saccharide. When used in an high performance liquid chromatography (HPLC) system with gradient elution, the adsorbent enabled the simultaneous analysis of mono-, di- and oligosaccharides.

Isomers of Dechlorane Plus in an aquatic environment in a highly industrialized area in Southern China: spatial and vertical distribution, phase partition, and bioaccumulation.

Dechlorane Plus (DP) was determined in aquatic environment including sediment, sediment core, water, and fish species in a highly industrialized area in Pearl River Delta, South China. DP was analyzed in sediments and water at concentration ranging from 0.08 to 19.4 ng/g dry weight and from 0.24 to 0.78 ng/L, respectively. DP was detected in 80% of fish samples with concentration between undetectable level to 189 ng/g lipid weight. DP levels were significantly higher in the top layer (depth less than 36 cm with concentration ranging from 0.35 to 57.6 ng/g) than in the lower section (concentration ranging from 0.02 to 0.72 ng/g), indicating an increase in DP contamination in recent years. The fraction of anti-DP in the sediment and water are close to that in the technical mixtures implying no stereospecific degradation occurring. An enrichment of syn-DP was observed in three fish species suggesting that a stereospecific metabolism of anti-DP and/or stereoselective uptake of syn-DP occurring in fish species. The calculated BSAFs are 0.024, 0.037, and 0.10 for DP, in mud carp, nile tilapia, and plecostomus, respectively, suggesting relatively low bioavailability of DP isomers in the sediments.