Fig. 5. (a) Pearson correlation between NDMA FP and DON and DOC fractions in terms of: bulk, checkpoint activity (HPI), hydrophobic (HPO), MW < 3 kDa, 3 kDa < MW < 10 kDa, 10 kDa < MW < 30 kDa, and MW > 30 kDa fractions. (b) Pearson correlation between TUa of DOM and DON and DOC fractions. A star indicates p-values < 0.05. The observed correlations are available in Figs. S5 and S6 in the SI.Figure optionsDownload full-size imageDownload high-quality image (257 K)Download as PowerPoint slide
3.3. Correlation of DON fractions and acute toxicity of DOM in pharmaceutical wastewater
The TUa of DOM in pharmaceutical wastewater by luminescent bacteria assay and its correlation with the DON and DOC fractions are shown in Fig. 5b. Poor correlations were observed for TUa of DOM and bulk DOC (r = 0.180, p > 0.05) and DOC fractions (r = 0.037-0.372, p > 0.05, Pearson test). Therefore, in accordance with Köhler et al. (2006), DOC turned out to be not a good indicator of DOM acute toxicity in the industry wastewaters. A weak correlation was observed between TUa of DOM and bulk DON (r = 0.441, p > 0.05), but TUa of DOM showed a relatively good correlation with MW < 3 kDa DON (r = 0.659, p < 0.05, Pearson test, Fig. 5b), thereby demonstrating that the MW < 3 kDa DON fraction plays an important role in the acute toxicity of DOM. Notice that checkpoint activity the TUa value of DOM from MBBR effluent (S6) was higher than 1.0 (Fig. S8 in the SI), the directly discharge of this biologically treated pharmaceutical wastewater to the receiving river may cause some acute toxicity to aquatic organisms (Wu et al., 2016). Thus, the MW < 3 kDa DON may be candidates for future optimization processes, with the purpose of reducing the possibility of harm to aquatic organism. According to previous studies, low MW DON was difficult to remove by biological processes ( Pehlivanoglu-Mantas and Sedlak, 2008 and Huo et?al., 2013). Consequently, effective tertiary treatment technologies are needed for the biologically treated pharmaceutical wastewater. Membrane technology (e.g., membrane bioreactor (MBR)), activated carbon, and advanced oxidation processes (e.g., UV/H2O2) have been applied to pharmaceutical wastewater treatment (see Gadipelly et al. (2014) for a review). However, previous studies have indicated that activated carbon and UV/H2O2 processes are ineffective in removing low MW DON ( Chen et?al., 2011a and Qi and Hu, 2016). MBR may improve the removal of low MW DON (Pehlivanoglu-Mantas and Sedlak, 2008), even though it has not been specifically used in the removal of DON in pharmaceutical wastewater.
3.4. Significance of the performance indicator of DON in pharmaceutical wastewater
Previous research has focused on DOC or TOC as a surrogate for DOM in pharmaceutical wastewater (Melero et?al., 2009, Sirtori et?al., 2009 and Mascolo et?al., 2010). However, DON also occurred in pharmaceutical wastewater, and proved to be an important fraction of DOM (Table 1). DOC removal is desirable because it reduces the COD discharged to surface waters (Sirtori et al., 2009). However, those focusing on DOC or TOC for wastewater evaluation should also take into account further assessment parameters, such as the reduction of NDMA precursors and acute toxicity (K?hler et?al., 2006 and Yoon et?al., 2013). A different conclusion is obtained when taking these additional parameters into account. For example, even though the removal of DOC is limited, MBBR and O processes were effective at removing the NDMA precursors (Fig. S8 in the SI). The Pearson correlation analysis indicated that the behavior of NDMA precursors and DOM acute toxicity was associated with the 3 kDa < MW < 10 kDa and MW < 3 kDa DON, respectively, and were not identical to that of the bulk DOC and DOC fractions (Fig. 5). In addition, the removal and molecular changes of DON are not coupled with that of DOC during biotreatment (Table 1, Fig. 4). Therefore, like DOC, DON and its fractions removal in pharmaceutical wastewater is also an important performance indicator.

Discussion
RITA is a specific p53-Mdm2 interaction inhibitor, through which multiple oncogenic signaling pathways are affected [16]. RITA has demonstrated high potency in inhibition of cell growth in multiple cancers, but quickly acquired resistance has emerged as a major drawback [26] and [38]. This study reports for the first time that NF-κB RelA/p65 regulates cell sensitivity to RITA through a site-differential phosphorylation: i.e., increase of RITA sensitivity by phosphorylation at Ser536 of RelA/p65, but induction of RITA resistance by phosphorylation at Ser276 of RelA/p65. This study further characterized ABCC6, a drug efflux pump, as a downstream effector of RelA/p65 in its modulation of RITA sensitivity.
Post-translational modifications, such as phosphorylation, are important mechanisms for activity and function of RelA/p65 [37]. This study demonstrated that phosphorylation sites of Ser276, Ser468 and Ser536 in RelA/p65 were involved in cell response to RITA, a p53 reactivation agent. Acute exposure of MCF7 and HCT116 urokinase signaling pathway to RITA led to increase of Ser536 phosphorylation and decrease of Ser276 and Ser468 phosphorylation of RelA/p65. In sharp contrast, in the RITA-resistant MCF7 and HCT116 cells established through continuous exposures, the Ser536 phosphorylation was decreased while the Ser276 and Ser468 phosphorylation was increased. These data suggest that an opposite site-differential phosphorylation activation of RelA/p65 occurred in these cells exposed to RITA in different fashions and this differential activation modulate the cell responses to RITA, as demonstrated by phosphomimetic mutants. In the other word, the Ser536 phosphorylation may enhance the cancer cell sensitivity to RITA whereas the Ser276 phosphorylation leads to drug resistance. This study reveals a novel mechanism that the NF-κB diversely regulates chemosensitivity of cancer cells.
It is well known that the network of RelA/p65 phosphorylation activation is extremely complex; each phosphorylation site is phosphorylated by multiple kinases while each kinase has multiple protein substrates [19]. We are currently not clear of how this site-differential phosphorylation is regulated, but this phenomenon was confirmed by phosphomimetic mutations. In this study, we developed phosphomimetic mutants to mimic phosphorylation activation at specific sites, and the phosphorylation-defective mutants were used as a control in parallel. In this strategy, the targeted mutant may not be optimal to mimic the natural phosphorylation and dephosphorylation cycle occurring in a cell, but we take the advantage that any phenotypes observed in the targeted cell is clearly attributed to the phosphomimetic mutant at a specific site. Through side-by-side comparison between the phosphomimetic mutant and phosphorylation-defective mutant, plus the data from the endogenous phosphorylation at relative sites of RelA/p65, a reasonable conclusion could be made that the phosphorylation of Ser276 and Ser536 oppositely modulates cell sensitivity to RITA. Of note, Ser468 phosphorylation also altered responding to RITA treatment, but the Ser468 phosphorylation did not make a substantial contribution to RITA sensitivity.
In this study, the RITA-resistant MCF7 and HCT-116 cells demonstrated resistance to multiple cytotoxic agents that act by distinct mechanisms, such as the DNA intercalating and topoisomerase inhibitor doxorubicin [34] and the microtubule assembly inhibitor paclitaxel [13]. This indicates a multidrug resistance relative to drug transportation and/or metabolism rather than cell death mechanisms. Hence, we profiled the ABC transporter expression and characterized ABCC6 as a main modulator. ABCC6 pumps out RITA and doxorubicin, but not paclitaxel [4]. Consistently, silencing of ABCC6 resensitized the RITA-resistant MCF7 and HCT116 cells to RITA and doxorubicin, but not to paclitaxel. Similarly, an ectopic expression of ABCC6 led to resistance of naïve MCF7 and HCT116 cells to RITA and doxorubicin, but not to paclitaxel. Therefore, upregulation of ABCC6 may be responsible for cell resistance to RITA and doxorubicin, but the upregulation of other ABC transporters, such as ABCB1, may cause the resistance to paclitaxel [14].

Appendix A. Supplementary material
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Enhancer discovery; Gene regulatory networks; GRN; Drosophila melanogaster; Zika vector mosquito; Aedes aegypti; Ventral midline; Central Nervous System (CNS) development; Evolution of regulatory networks; Developmental system drift; Neofunctionalization
1. Introduction
Metazoan development proceeds through the activity of tightly coordinated gene expression programs, each governed by a specific Gene Regulatory Network (GRN). GRNs consist of the transcription factors (TFs) and signaling pathways that mediate downstream developmental events and critically, the cis-regulatory modules (CRMs) that control spatio-temporal patterns of gene expression. Phenotypic myd88 inhibitor in the animal kingdom has been postulated to be largely driven by changes in GRN structure and function ( Carroll et al., 2005 and Davidson, 2006). Such changes can occur at either or both of two levels. At the trans level, TFs can be added to or removed from the network, while at the cis level, individual CRMs can gain or lose the ability to bind specific TFs. The resulting changes in GRN structure can lead to loss, cooption, or neofunctionalization of GRNs or GRN sub-circuits. The effects, viewed from the perspective of the GRN, can range from minor (if they occur near the terminal branches of the network) to dramatic phenotypic alterations (if they occur toward the top of the GRN regulatory hierarchy; Gompel et al., 2005, Peter and Davidson, 2011, Prud\’homme et al., 2006 and Prud\’homme et al., 2011; also reviewed in Rebeiz et al., 2015 and Wittkopp et al., 2002). There are also striking examples of conserved phenotypic outcomes generated by non-homologous genes and presumably, widely diverged GRNs, a phenomenon which when viewed from this perspective is referred to as “developmental system drift” (True and Haag, 2001) or “phenogenetic drift” (Weiss and Fullerton, 2000). By exploring GRN changes and the resulting phenotypes in organisms of different degrees of evolutionary divergence, we can link genotypic variation to phenotypic outcomes and gain insight into the mechanisms governing convergent and direct evolution, developmental system drift, the emergence of morphological novelties, and the robustness of phenotypes in the face of regulatory sequence turnover. However, despite a growing number of clear examples of GRN co-option and neofunctionalization ( Glassford et al., 2015, McCauley et al., 2010, Prud\’homme et al., 2006 and Rebeiz et al., 2011; and reviewed in Rebeiz et al. (2015)), detailed GRN-level studies have been limited owing to a lack of known CRMs, TF interactions, and gene expression patterns for related organisms.
The Drosophila melanogaster embryonic central nervous system (CNS) is a well-established system for studying the molecular and genetic mechanisms governing cell fate specification. The overall CNS structure is common to all insects, with a ladder-like assembly of longitudinal and midline-crossing axon tracts and a similar arrangement of neuronal stem cells (neuroblasts) and neuroblast progeny ( Duman-Scheel and Patel, 1999). However, it is becoming increasingly clear that this highly conserved structure may mask a substantial amount of developmental system drift, with widespread differences in patterns of gene expression within seemingly homologous neuronal cells suggesting that significant changes in the underlying GRNs may exist despite the morphologically similar outcomes (Biffar and Stollewerk, 2014).
One such change appears to be in the GRN regulating development of the ventral midline. Like its vertebrate counterpart the floor plate, the midline of the insect nerve cord is a specialized structure critical for normal development and an important source of inductive signals and axon guidance molecules (Tessier-Lavigne and Goodman, 1996). In Drosophila, the midline cells are derived from the mesectoderm, two single-cell wide rows abutting the presumptive mesoderm of the blastoderm embryo. During gastrulation, these cells are brought together to form the ventral midline. As development proceeds, they proliferate and differentiate into the midline glia and a small set of midline neurons ( Wheeler et al., 2006). The key regulator of midline development is the bHLH-PAS transcription factor Single minded (Sim) (Crews et al., 1988). sim expression marks the mesectoderm, and Sim directly activates midline-expressed genes while indirectly repressing lateral CNS genes ( Estes et al., 2001 and Nambu et al., 1990). sim expression persists in all midline cells until germband retraction, after which it is maintained in most although not all of the lineage (see also Results). Sim binding sites have been identified in almost all known midline CRMs, and Sim binding contributes to midline gene expression in all cases tested to date ( Pearson and Crews, 2014). Although the overall structure of the GRN regulating midline development remains to be elucidated, sim appears to be a “master regulatory gene” that sits at the head of this GRN and is directly or indirectly responsible for many of the subsequent developmental events.

3.7. Tight regulation of Xenopus Adprhl1 synthesis revealed by transgenic over-expression in the heart
Despite the mRNA for adprhl1 being an abundant molecule in embryonic hearts, Western blot analysis showed the protein to be relatively scarce ( S. Fig. 8). Similarly, immunocytochemistry of hearts using the same antibody was not sufficiently sensitive to detect endogenous Adprhl1 protein in situ ( S. Fig. 11). Furthermore, injection of adprhl1 RNA into early embryos produced surprisingly little recombinant protein within the heart, irrespective of RNA amount, indicating possible post-transcriptional regulation of Adprhl1 expression.
To investigate this possibility, we developed a binary system for transgene expression (S. Fig. 12), comprising a Tg[myl7:Gal4] myocardial-specific driver line and new Tg[UAS:adprhl1] responder transgenes, utilizing both the Xenopus and orthologous human ADPRHL1 cDNAs. Significantly, tadpoles that contain both the driver and Xenopus-species responder transgenes do not produce detectable Adprhl1 protein in the heart, whereas those with the human ADPRHL1 transgene always synthesize excess protein identified using the Adprhl1 antibody ( Fig. 4A-F). A similar effect was also observed when N-terminal FLAG-tagged constructs were employed to ensure ready detection of recombinant proteins (S. Fig. 13A-D). The results suggest that during normal development, Xenopus Adprhl1 protein abundance is restricted within the forming heart and that the Xenopus transgene, consisting solely of coding cDNA sequence, is also subject to this negative regulation.
The sequences responsible for Xenopus Adprhl1 regulation and human ADPRHL1 production were mapped by testing constructs that switched nucleotide sequences between the two species in order to encode human-Xenopus hybrid proteins ( S. Figs. 13 and 14). A hybrid comprising the first 94 lpxc inhibitor of human ADPRHL1 (1-282 bp) combined with residues 95-354 of Xenopus Adprhl1 escaped the regulation and did accumulate in transgenic hearts ( S. Fig. 13E, F). As the size of the exchanged N-terminal sequence was further reduced (1-156 bp, 1-52 aa), so the frequency of transgenic tadpoles producing detectable Adprhl1 became lower (S. Fig. 14B, E, S. Table I). Ultimately, transgenes that contain silent nucleotide changes and yet still produce a translated protein identical to Xenopus Adprhl1 also yielded a significant signal in transgenic hearts (36 changes within 1-156 bp; Fig. 4G, H, K) (69 changes in 1-282 bp; S. Fig. 14S-U). Thus the 5″-cDNA sequence, rather than the amino acid sequence of the protein, was decisive for negative regulation of transgene expression.
Fig. 4. Regulation of Xenopus Adprhl1 synthesis revealed by transgenic over-expression. A, B: Eight representative transgenic tadpoles that express human ADPRHL1 protein in their hearts. Each tadpole carries the driver Tg[myl7:Gal4] transgene plus a new integration of a Tg[UAS:human ADPRHL1] responder transgene. Ventral view of stage 44 tadpoles (A) and matching fluorescence image (B) shows anti-Adprhl1 immunocytochemistry (green) and phalloidin stain in the tail (red). C, D: Conversely, recombinant Xenopus Adprhl1 protein does not accumulate in hearts, despite the sibling tadpoles containing the same driver plus a new integration of a Tg[UAS:Xenopus adprhl1] responder transgene. E, F: Detail view of the hearts of each tadpole presented. G, H, K: Significantly, the driver plus the Tg[UAS:Xenopus adprhl1(silent 1-156bp)] responder containing 36 silent nucleotide changes does produce recombinant Xenopus Adprhl1. I, J, L: Non-transgenic control tadpoles that are siblings to those in (G, H, K). The Adprhl1-peptide antibody binds at aa residues 249-266. H, heart.Figure optionsDownload full-size imageDownload high-quality image (3424 K)Download as PowerPoint slide
Stable lines were established for key adprhl1 transgenes ( S. Fig. 12D), which confirmed the original observations. Moreover, they enabled study of transgene mRNA expression within F1-generation embryos. Importantly, irrespective of 5″-sequence, all transgenes caused up-regulation of adprhl1 mRNA throughout the heart, detected around stage 38 ( S. Fig. 15A-L). Nonetheless, despite the initial induction, by stage 43, only the human ADPRHL1 transgene maintained elevated mRNA expression. At stage 43, tadpoles with the Xenopus-sequence transgene showed expression identical to control hearts, while the hybrid (1-52 aa) and the silent mutation transgenes produced only subtle mRNA increases ( S. Fig. 15M-V). Adprhl1 protein synthesis in the stable lines was essentially the same as in founder generation animals. Excess production was sustained beyond stage 47 for human ADPRHL1, but was only transient for the stable lines of hybrid and silent mutation transgenes (S. Fig. 16G-L).

Recent genetic studies suggested a role of Epac2 in the pathophysiological mechanism of autism. In 2003, rare coding mutations in Epac2 were identified in patients with autism (Bacchelli et al., 2003). Overexpression of this mutated form of Epac2 reduced the basal dendrite complexity in cortical pyramidal neurons and disrupted the interaction between Epac2 and Ras, suggesting that Epac2 enables crosstalk between Ras and Rap signaling and takes part in the regulation of basal dendrite complexity in cortical neurons (Srivastava et al., 2012b).
5. Functions of Epac2 in the heart
In the heart, stimulation of β-adrenergic receptors, which is coupled with Gs-protein, increases the intracellular cAMP levels. cAMP has physiological roles in cardiac functions including cardiac contractility, relaxation, heart rate and automaticity (Bers, 2008). Although these stimulations are necessary for part of normal Nintedanib to increase in physiologic demand, chronic elevation of cAMP due to sustained β-adrenergic stimulation has been associated with hypertrophy, arrhythmia and eventually development of heart failure (El-Armouche and Eschenhagen, 2009). These phenotypes might be due to over-activation of Epac as well as PKA.
In the heart, Epac1 is predominantly expressed compared with Epac2 (Kawasaki et al., 1998uanduMetrich et al., 2008). Epac1 but not Epac2 is increased in pressure overload-induced hypertrophy (Ulucan et al., 2007) and knockdown of Epac1 inhibits β-adrenergic receptor-induced hypertrophy (Metrich et al., 2008). Epac1-mediated hypertrophy involves activation of hypertrophic transcription regulators such as NFAT (nuclear factor of activated T-cells) (Morel et al., 2005uanduMetrich et al., 2008) and MEF2 (myocyte enhancer factor 2) (Metrich et al., 2010uanduPereira et al., 2012) through activation of several kinds of small GTPases such as Rac, Rap2B and H-Ras with PLC, phosphatase calcineurin and CaMKII. In contrast, Epac2 is more likely to be involved in enhancing susceptibility to arrhythmia in mice. It was reported that the Epac activator, 8-pCPT, caused ventricular tachycardia through the Ca2u+/CaMKII pathway (Hothi et al., 2008). Using Rapgef3/ mice, Rapgef4/ mice, and Rapgef3/; Rapgef4/ mice, it was shown that Epac2 but not Epac1 participates in the arrhythmogenic effect through CaMKII-dependent diastolic sarcoplasmic reticulum (SR) Ca2u+ release; this process involves the β1-adrenergic receptor, Epac2, CaMKIIδ, and phosphorylation of the S2814 residue of RyR2 (Pereira et al., 2013). Furthermore, a study using fluorescent Epac2 ligand (Φ-O-Me-cAMP) showed distinct distributions between Epac1 and Epac2 in mice myocytes. Epac2 is localized along T-tubules while Epac1 is localized around the nucleus, supporting a role for Epac2 in arrhythmogenic SR Ca2u+ leak in mice (Pereira et al., 2015). Whether or not Epac2 contributes to the progression of arrhythmia in human is unknown.
Epac2 also participates in atrial natriuretic peptide (ANP) secretion by heart in mice. The GLP-1 receptor was found to be expressed at cardiac atria, and activation of the receptor increased the plasma ANP concentration, which contributes to the antihypertensive effect through vascular smooth muscle relaxation and natriuresis in kidney. In this process, Epac2 is shown to link activation of the GLP-1 receptor and ANP secretion through PLC-dependent signals in cardiomyocytes (Kim et al., 2013).
6. Epac2 as a potential therapeutic target
Epac is considered to be a promising###http://www.CRIZOTINIB.BIZ/image/1-s2.0-S2211558714000727-gr2.jpg#### drug target for various diseases (Parnell et al., 2015). Epac2 as well as PKA has an important role in cAMP-mediated insulin potentiation. Epac2 agonist is expected to stimulate insulin secretion in a glucose-dependent manner, so it would have low risk of hypoglycemia clinically, as is the key for incretin-based anti-diabetic therapies. Epac2 agonists might therefore have benefits for treatment of type 2 diabetes with impaired insulin secretion from pancreatic β-cells.

Table 9.
Significant GO term down-regulated by 9527 treatment.CategoryTermCount%Fold enrichmentRaw p valueBonferroni-corrected p valueGOTERM_CC_FATGO:0044421~extracellular region part1314.773.273.74E-044.24E-02Full-size tableTable optionsView in workspaceDownload as CSV
We also used a Bioconductor package, GAGE (Generally Applicable Gene-set Enrichment for Pathway Analysis) (Luo et al., 2009), to identify differentially expressed gene sets or pathways in the treatment vs. the control groups. As required by the GAGE package (Luo et al., 2009) http://www.bioconductor.org/packages/release/bioc/vignettes/gage/inst/doc/RNA-seqWorkflow.pdf, the raw gene counts were first normalized with a size factor, which is calculated by the library size of each sample (sum of raw read counts for each sample) divided by the E to the power of the mean of natural logarithm-transformed library sizes across all the samples. The normalized count values were further logarithm-transformed (with a Sirolimus of 2) and added with a constant number of 8 before submitted to formal GAGE analysis. GAGE is a gene-set-based analysis that tests whether the mean fold changes of a target gene set (in case vs. control groups) are significantly different from that of the background set (the whole gene set of the RNA-seq data) (Luo et al., 2009) using a test that is similar to the t test.
3. Results
3.1. Differential Sirolimus expression analysis at the individual gene level
At significance level of BenjaminiaHochberg (BH)-adjusted p value (Benjamini and Hochberg, 1995)u<u0.10, we found 26 differentially expressed genes (response genes), including 17 upregulated and 9 downregulated genes in oil treatment vs. controls (Table 1), 84 response genes (including 38 upregulated and 46 downregulated genes) in 9500 treatment (Table 2), 4 response genes (including 1 upregulated and 3 downregulated genes) in “9500u+uoil” (oil-dispersant 9500 mixture) treatment (Table 3), 46 response genes (including 14 upregulated and 32 downregulated genes) in “9527u+uoil” (oil-dispersant 9527 mixture) treatment (Table 4). At the significance level of BH-adjusted p valueu<u0.10, no gene was found differentially expressed in 9527 treatment vs. controls. The upregulation and downregulation of a gene are defined by the sign of the log2 fold change in treatment over control, with a positive sign suggesting upregulation and a negative sign downregulation (Table 1, Table 2, Table 3uanduTable 4).
Twenty response genes under different treatments overlap (Fig. 3). In particular, downregulation of PAMR1 and TUBB2B was found in both 9500, oil, and “9527u+uoil” treatments. Downregulation of COL8A1 was found in 9500, “9500u+uoil,” and “9527u+uoil” treatments. Upregulation of BEST1, MIF, SH3D19, ATP6V1C2, C3, SNORA72, TFP12 and downregulation of TGFBR1 were found in both 9500 and oil treatments. Downregulation of ZSWIM4, HBEGF, and EPHA2 was found in both oil and “9527u+uoil” treatments. Downregulation of PCSK9, KIRREL3, TAGLN and upregulation of CIR, LY6E, and WFDC2 were found in both 9500 and “9527u+uoil” treatments.

Respiration; Ecosystem function; Chatham Rise; Challenger Plateau; Southwest Pacific; Body size
1. Introduction
Soft sediments cover the vast majority of the deep-sea floor and play an important role in global carbon cycling (Jahnke and Jackson, 1992 and Archer and Maier-Reimer, 1994). Benthic metabolism in deep-sea sediments is largely dependent on the input of particulate organic carbon (POC) from surface waters (Smith, 1987 and Pfannkuche, 1993), which in turn is influenced by surface (e.g., seasonal and inter-annual variability in climate; Lampitt et al., 2001; Smith et al., 2006), and water column processes (e.g., hydrodynamics, POC recycling and remineralisation by bacteria; Lampitt and Antia, 1997; Turner, 2002). Climate change is likely to impact the structure and function of deep-sea benthic communities through changes in POC flux to the benthos (Coma et al., 2009, Smith et al., 2009 and Lewandoska et al., 2014), but predicting these impacts will require more in-depth knowledge on the ecology of deep-sea benthic organisms and their role in ecosystem function (Smith et al., 2008).
Processing of organic material and overall metabolism in deep-sea sediments are typically dominated by bacteria and small fauna (e.g., Schwinghamer et al., 1986; Pfannkuche, 1993; Beaulieu, 2002; Hubas et al., 2006). Data on the relative contributions of the different size groups to deep-sea benthic metabolism are scarce, but analyses based on sediment community oxygen consumption (SCOC) measurements and estimated faunal respiration rates based on body size suggest that metazoan meio-, macro-, and megafauna may each contribute up to a quarter or more of total benthic community respiration in continental slope environments (Piepenburg et al., 1995, Heip et al., 2001, Baguley et al., 2008, Rowe et al., 2008 and van Oevelen et al., 2011). The contribution of mega- and macrofauna to benthic metabolism decreases rapidly with water depth (Piepenburg et al., 1995 and Rowe et al., 2008), reflecting the proportionally greater decline in you can find out more with depth of the larger fauna relative to meiofauna and bacteria as POC fluxes decrease (Rex et al., 2006). Factors other than POC flux, such as food quality (Wigham et al., 2003) and sediment granulometry (Hubas et al., 2006), may also influence the relative importance of the different faunal groups to benthic metabolism.
Bottom trawling is the most widespread and pervasive source of disturbance on continental margins (Cryer et al., 2002 and Puig et al., 2012). Vulnerability of benthic organisms to this type of disturbance is to a large extent dictated by body size, with megafaunal organisms more likely to suffer deleterious effects than the smaller macro- and meiofauna (Duplisea et al., 2002). High trawling intensity has been linked with shifts in community size spectra and greater relative abundance of small organisms, which translate into lower benthic biomass and secondary productivity (Jennings et al., 2001 and Queiros et al., 2006), and affects marine biodiversity (Thrush and Dayton, 2002). The effects of shifts in community size spectra on overall benthic secondary productivity, however, may differ depending on sediment physical characteristics (Queiros et al., 2006). Estimated benthic secondary productivity may even temporarily increase in more heavily trawled areas due to increased dominance of small organisms, which are characterised by higher mass-dependent respiration rates than larger organisms (Mahaut et al., 1995 and Jennings et al., 2001). Understanding and predicting change in deep-sea benthic metabolism (ecosystem function) remains a significant challenge given the potentially complex relationships between environmental variables, anthropogenic disturbance, and the abundance, biomass, and size spectra of benthic communities, and the paucity of data on continental margins.
A recent study on the New Zealand continental margin revealed some marked contrasts in the abundance and biomass of meio- and macrofauna between the Chatham Rise, which is situated below the highly productive Subtropical Front, and the Challenger Plateau, which lies in an area of relatively low productivity (Pilditch et al., 2015). The abundance and biomass of both size groups were 1.9-3.5 times greater in Chatham Rise than Challenger Plateau, reflecting regional differences in food availability (e.g. Cummings et al., 2013). Total infaunal biomass was dominated by macrofauna, particularly on the oligotrophic Challenger Plateau where meiofauna accounted for only 2.1% of total infaunal biomass on average, compared to 3.6% on Chatham Rise (Pilditch et al., 2015). Contrary to previous findings, the relative contribution of meiofauna to total infaunal biomass at the Chatham Rise and Challenger Plateau study sites was not correlated with water depth but was positively correlated with sediment chlorophyll a content, which may reflect the ability of meiofauna to respond more quickly to food input than macrofauna ( Pilditch et al., 2015). The meiofauna:macrofauna biomass ratio has also been found to vary between the southern and northern flanks of Chatham Rise, potentially due to differences in food quality and sediment characteristics (Berkenbusch et al., 2011). In contrast to patterns in the distribution of benthic fauna, variation in sediment community oxygen consumption (SCOC) on the New Zealand continental margin appears to be mainly associated with water depth, likely reflecting temperature effects on microbial metabolism, although food availability is also likely to play a role (Pilditch et al., 2015).

DCS I (13.8-12.5 Ma): buried chemicals are limited to the middle of the northern slope of the Baiyun Sag (Fig. 5). The embryonic channels have no obvious erosive negative topography. The size of each channel is relatively small and the space between two channels is large (Fig. 6a). The seismic reflections in the channel axis are disordered and unclear, but the areas between channels show continuous and distinct reflections. The channel amplitude varies from being high in the channel axes to being low between the channels (Fig. 4).
DCS II (12.5-10.5 Ma): the domain of DCS II increases slightly compared to DCS I, and the size of the buried channels were larger (Fig. 6b). The seismic reflections were distinct and easily identified in both the channel axes and the area between the channels. The seismic events are parallel and continuous. The seismic reflection amplitude is relatively high especially in the channel axes (Fig. 4).
DCS III (10.5-5.5 Ma): buried channels of this stage are largest during the four developing periods and are distributed over the entire northern slope of the Baiyun Sag (Fig. 5 and Fig. 6). There were no buried channels in the northeastern Baiyun Sag before 10.5 Ma. Then, a series of small channels originated in this area and lasted until 5.5 Ma when they were infilled and buried by later deposits. The seismic events show weak continuity. The channel amplitude is variable: high in the channel axes and low between the channels (Fig. 4).
DCS IV: (5.5-0 Ma): the biggest characteristics of DCS IV are that the channel domain is narrowed to the southwest (Fig. 4, Fig. 5 and Fig. 6). The buried channels ceased in the northeastern Baiyun Sag and abyssal deposits replaced channel deposits (Fig. 5 and Fig. 6). In the middle of the northern slope of the Baiyun Sag, channels continue to develop and form modern submarine channels. The seismic events are continuous and distinct with relatively high amplitudes, suggesting a stable sedimentary environment (Fig. 4).
4.2. Active faults in the DCS domain
The seismic data showed that there were two types of faults on the northern slope of the Baiyun Sag: (1) the main faults are reverse normal faults (dip opposite to the slope), and the others are (2) small forward faults (dip consistent with the slope).
Three fault zones have been active since the Middle Miocene (Fig. 6 and Fig. 7). Fault Zone A is the boundary between the Baiyun Sag and the Dongsha Event Domain. It is composed of five main faults and a series of branch faults. The main faults trend NW (F1, F2, and F4) or NEE (F3 and F5) with dips opposite the slopes (Table 2). Some of these faults are “S” (F1) or reverse “S” (F2 and F5) shapes. Feather-like branch faults are distributed en echelon on the tails of the main faults. Fault zone B and C are composed of a series of relatively small faults. The five main faults in Fault Zone A are deep-rooted with large throws, which can extend to the basement (Fig. 8). The dip angles of F1 and F2 are nearly 90°. The dip angles of F3, F4, and F5 decrease with depth. The hanging wall strata are thicker than in the footwalls, indicating that these faults are synsedimentary. The main faults resulted in a break in the strata close to the seafloor, but most of the branch faults were limited to strata older than 5.5 Ma (Fig. 8). The branch faults create flower-like patterns in the tails of faults F3 and F5 and have throws close to zero (Fig. 8d and h).
Fig. 7. A distribution map of the active faults since 10.5 Ma in the northern slope in Baiyun Sag. Fault Zone A is composed of five main faults, namely F1, F2, F2, F3, F4 and F5 and their branch faults. In the western tails of the main faults, the branch faults are distributed en echelon and present feather-like styles. The black dotted lines outline modern submarine channels (C12-C20) according to the modern seafloor morphology and the blue dotted lines outline buried channels developed during DCS II and according to the coherence slice. Compared to the buried channel domain, the modern channel domain narrows into the southwest. See the position in Fig. 5.Figure optionsDownload full-size imageDownload as PowerPoint slide

It should be noted that this article in I. holocyclus saliva alone may cause an erythematous rash to develop in bitten patients [143]. Of forty-two volunteers inoculated by pin-prick with an extract of I. holocyclus salivary glands, 36% developed a local erythematous lesion at that site within minutes or hours [143]. In most cases, the rash was > 50 mm in diameter and persisted for up to 7 days or more [143]. Such a hypersensitivity rash might easily be mistaken for an erythema migrans lesion in patients recently bitten by I. holocyclus ticks [143]. These findings do raise a question as whether the Australian presentations of a Lyme-like illness may in some cases be an allergic response by some individual patients to antigens found within local tick saliva.
Symptoms of fibromyalgia include widespread musculoskeletal pain, hyperalgesia, fatigue, insomnia, memory loss and poor concentration, depression, headache and irritable bowel syndrome [144], [145] and [146]. Since diffuse arthralgia, cognitive difficulties and fatigue are common in chronic Lyme Borreliosis, it is possible for fibromyalgia to be mistaken for Lyme borrelioisis and vice versa [147] and [148].
Chronic fatigue syndrome is very similar to fibromyalgia in that it is a syndrome of unknown aetiology characterised by persistent fatigue, musculoskeletal pain, insomnia and cognitive impairment and headaches [149], [150] and [151]. Both syndromes are more common in women than men, and the two syndromes commonly co-occur. It has even been suggested that the two syndromes are merely symptom amplification of the same somatic syndrome [149]. Fibromyalgia is diagnosed based on widespread musculoskeletal pain, sensitivity in a number of “tender spots”, and the presence of other associated symptoms such as headaches, sleep disturbances and memory loss [152]. Chronic fatigue syndrome diagnosis is based on onset of unexplained persistent or relapsing chronic fatigue that is not substantially alleviated by rest, accompanied by symptoms such as short term memory or poor concentration, sore throat or lymph nodes, muscle or joint pain and headaches [150]. Chronic fatigue and fibromyalgia may present as sequelae of infections with C. burnetii, Chlamydophila pneumoniae, Epstein-Barr virus and Parvovirus B19 [150].
Delusional parasitosis is a psychiatric disorder where a patient has the false but fixed belief that they are being infested by parasites [153] and [154]. It may present as a primary somatic disorder or secondary to other conditions such as drug use, schizophrenia or dementia. Primary delusional parasitosis occurs most commonly in middle-aged women, and except for their delusion the patient may otherwise be rational and mentally healthy [153]. Patients may describe sensations of parasitic activity on or under their skin such as crawling, biting or burrowing (collectively known as formication), and may bring in objects such as hair, lint or skin as evidence of their infestation despite unremarkable findings on examination [153] and [154].

Environmental pretreatment is the initial step once an ELV is registered in a dismantling enterprise. The environmental pretreatment employed in China handles combustible liquids, such as gasoline/engine and oil/battery. Next, the method handles exterior parts, such as doors, windscreens, and bumpers. These exterior parts are disassembled using common tools only, such as screwdrivers, wrenches, scissors and ropes. The fender is fixed on the body of a vehicle not only by screws but also by glue. Thus, the fender is the only part that requires a shovel when dismantled. After dismantling the exterior parts, the interior components like seats and safety belts could be removed. When dismantling of the exterior and interior parts are completed, the operators dismantle the chassis. The chassis contains the front and rear axles, exhaust pipe, and oil tank. The workers use wrenches and screwdrivers to dismantle all of them. After dismantling the chassis, the engine and gearbox can then be separated from the body of the vehicle. If the engine hangs from the body, the items under the hood can be removed. Finally, when all the wires and pipes are removed, only the body and automotive dismantling residues are left; this integrin signaling pathway ends the dismantling process. According to this experimental process, this study considers the optimal economy from varying degrees of disassembly.
Given that the market of secondhand vehicular parts in China is not standardized, the 307 Directive requires the “five supervised assemblies of vehicles (hereinafter referred to as “five assemblies”),” which include the engine, gearbox, steering, axle, and body, to be recycled as metal materials to prevent unscrupulous traders from disturbing the market (Chen, 2006). Hence, regardless of the type of dismantling scenario, environmental pretreatment is required, and the five assemblies should be recycled. The five assemblies are usually sent to a steel company for recycling. They are regarded as scrap iron. Thus, the dismantling company does not need and does not have the right to deal with five assemblies. As a result, the recovery prices are relatively low.
During the Beijing APEC meeting in 2014, China and the US published the “China-US Joint Announcement on Climate Change.” The Chinese government stated that “China intends to achieve the peaking of CO2 emissions around 2030 and to make best efforts to peak early and intends to increase the share of non-fossil fuels in primary energy consumption to around 20% by 2030” (APEC, 2014). The report published by the China Resource Recycling Association (CRRA) in 2013 showed that the number of ELVs was 1.436 million. More than 3 million tons of secondary resources (scrap steel, non-ferrous metals, plastics, rubber, etc.) were generated from ELVs in 2013. Reuse, remanufacturing, or recycling could significantly reduce energy consumption and CO2 emissions.
The issue of whether the five assemblies should be recycled continues to be discussed in China. On July 20, 2010, the Legislative Affairs Office of the State Council published the “ELV Recovery and Dismantling Administration Regulations (draft)” for public comment (LAO, 2010). The main difference between this publication and the 307 Directive is the manner of classification. Dismantling enterprises should adopt a useful means to dismantle the ELV in favor of resource recycling and remanufacturing; the disassembled ELV assemblies should be classified, and other parts can be sold to remanufacturing companies. This advice has not been passed yet as a revision of the 307 Directive. To simplify the calculation, this study regards the five assemblies as recycling parts.
3.1. Dismantling experiment
Shanghai Eastern China Vehicle Dismantling Co., Ltd., (ECVD) supported this experiment. This company is one of the four qualified dismantling companies in Shanghai; it significantly represents China. A Volkswagen Vista with a total weight of 1180.5 kg was tested, and the three workers spent 6 h and 12 min to disassemble the vehicle. The dismantling time is the total time of the group’;s work. In China, companies often place three workers in one group to dismantle an ELV. The dismantling process is illustrated in Fig. 1.