Release of PAHs from sediments to seawater under wave: Indoor microcosms and level IV fugacity models.

Estuaries and coasts are located at the land-sea interface, where sediment liquefaction due to strong wave action results in significant material exchange at the sediment-seawater system. Polycyclic aromatic hydrocarbons (PAHs), as organic pollutants, are distributed across various media. Herein, the impact of wave was studied on the release of PAHs through indoor microcosmic experiments combined with a level IV fugacity model. Comparison revealed that the release amount and rate of PAHs during static consolidation stage were minimal, whereas wave action substantially enhanced the release. Particularly the sediments in a liquefied state, the PAHs release in Stage III was 1.55-1.86 times that in Stage II, reaching 84.73 µg/L. The loss of soil strength and strong hydrodynamic effects resulted in a substantial release of PAHs into seawater along with suspended solids. Due to volatility of 2-ring PAHs and difficult desorption of 6-ring PAHs, 3-5-ring PAHs are the main contributors to releases into seawater. The model results also indicated that the three PAHs had different fates in the sediment-seawater system, with sediment serving as an important "reservoir" for benzo[a]pyrene entering seawater, while functioning as both a "sink" and a "source" for pyrene.

The effect of bioturbation on the release behavior of polycyclic aromatic hydrocarbons from sediments: A sediment-seawater microcosm experiment combined with a fugacity model.

The effects of two benthonic species, Perinereis aibuhitensis and Matuta planipes Fabricius, on the release of polycyclic aromatic hydrocarbons (PAHs) from sediments were investigated using a sediment-seawater microcosm. A Level IV fugacity model was used to simulate the behavior and fate of PAHs in the environment. This study revealed that both benthos significantly influenced the release of PAHs, and Matuta planipes Fabricius had a stronger disturbance effect than another. The final concentrations of Matuta planipes Fabricius group, Perinereis aibuhitensis group and the control group in the seawater phase reached 10.8, 9.94 and 7.90 µg/L, respectively. There were certain differences in the behaviour of the two benthonic species. Matuta planipes Fabricius caused more sediment resuspension, while Perinereis aibuhitensis increased the total organic carbon (TOC) content in the environment. The vertical concentration distribution of sediment indicated that vertical mixing was slightly stronger in the Matuta planipes Fabricius group than that in the Perinereis aibuhitensis group. The fugacity model effectively simulated the release behavior of PAHs, providing insight into PAH transport and distribution. The results demonstrated that bioturbation could promote the release of PAHs from seawater. The amount of PAHs released was significantly correlated with the biological habits of the benthos.

Removal of sulfonylurea herbicides with g-C3N4-based photocatalysts: A review.

The accumulation of agricultural chemicals in the environment has become a global concern, of which sulfonylurea herbicides (SUHs) constitute a significant category. Solar-driven photocatalysis is favored for removing organic pollutants due to its high efficiency and environmental friendliness. Graphite carbon nitride (g-C3N4)-based materials with superior catalytic activities and physicochemical stabilities are promising photocatalysts. This review describes the g-C3N4-based materials and their uses in the photocatalytic degradation of SUHs or other organic pollutants with similar structures. First, the fundamentals of g-C3N4-based materials and photocatalytic SUHs degradation are discussed to provide an in-depth understanding of the mechanism for the photocatalytic activity. The ability of different g-C3N4-based materials to photocatalytically degrade SUH-like structures is then discussed and summarized based on different modification strategies (morphology modulation, elemental doping, defect engineering, and heterojunction formations). Meanwhile, the effects of different environmental factors on the photocatalytic performance of g-C3N4-based materials are described. Finally, the major challenges and opportunities of g-C3N4-based materials for the photocatalytic degradation of SUHs are proposed. It is hoped that this review will show the feasibility of photocatalytic degradation of SUHs with g-C3N4-based materials.

Spatiotemporal variability of PAHs and their derivatives in sediments of the Laizhou Bay in the eastern China: Occurrence, source, and ecological risk assessment.

To understand the pollution status and risk levels in the Laizhou Bay, the spatiotemporal distribution, source, and ecological risk of 16 polycyclic aromatic hydrocarbons (PAHs) and 20 substituted PAHs (SPAHs) were studied in surface sediments in 2022. The findings indicated significant seasonal differences in the concentrations of PAHs and SPAHs under the influences of precipitation, temperature, light, and human activities, with higher storage levels in summer than in spring, and there was also a spatial distribution trend of estuary > coast > offshore. 2-Nitrofluorene (2-NF) and 2-methylnaphthalene (2-MN) were the most abundant components of SPAHs in both spring and summer, with levels of 21.44 ng/g and 17.89 ng/g in spring, 43.22 ng/g and 25.51 ng/g in summer, respectively. The results of the diagnostic ratio and principal component analysis - multiple linear regression identified sources of PAHs and SPAHs as combustion sources, including petroleum, coal, and biomass. The risk level of PAHs was low-to-moderate according to the toxicity equivalent quotient (TEQ) and risk quotient. A novel calculation method based on TEQ was proposed to assess the ecological risk of SPAHs, and the results indicated that the risk level of SPAHs was moderate-to-high.

Research Progress on the Mechanism of Nanoparticles Crossing the Intestinal Epithelial Cell Membrane.

Improving the stability of drugs in the gastrointestinal tract and their penetration ability in the mucosal layer by implementing a nanoparticle delivery strategy is currently a research focus in the pharmaceutical field. However, for most drugs, nanoparticles failed in enhancing their oral absorption on a large scale (4 folds or above), which hinders their clinical application. Recently, several researchers have proved that the intestinal epithelial cell membrane crossing behaviors of nanoparticles deeply influenced their oral absorption, and relevant reviews were rare. In this paper, we systematically review the behaviors of nanoparticles in the intestinal epithelial cell membrane and mainly focus on their intracellular mechanism. The three key complex intracellular processes of nanoparticles are described: uptake by intestinal epithelial cells on the apical side, intracellular transport and basal side exocytosis. We believe that this review will help scientists understand the in vivo performance of nanoparticles in the intestinal epithelial cell membrane and assist in the design of novel strategies for further improving the bioavailability of nanoparticles.

Cometabolic degradation of pyrene with phenanthrene as substrate: assisted by halophilic Pseudomonas stutzeri DJP1.

At present, cometabolic degradation is an extensive method for the biological removal of high molecular weight polycyclic aromatic hydrocarbons (HMW-PAHs) in the marine environment. However, due to the refractory to degradation and high toxicity, there are few studies on pyrene (PYR) cometabolic degradation with phenanthrene (PHE) as substrate. In this study, a Pseudomonas stutzeri DJP1 strain isolated from sediments was used in the cometabolic system of PHE and PYR. The biomass and the activity of key enzymes such as dehydrogenase and catechol 12 dioxygenase of strain were improved, but the enhancement of biotoxicity resulted in the inhibition of cometabolism simultaneously. Seven metabolites were identified respectively in PYR, PHE degradation cultures. It was speculated that the cometabolism of PHE and PYR had a common phthalic acid pathway, and the degradation pathway of PHE was included in the downstream pathway of PYR. The functional genes such as PhdF, NidD and CatA involved in DJP1 degradation were revealed by Genome analysis. This study provides a reference for the biodegradation of PYR and PHE in real marine environment.

A study combining a sediment-seawater microcosm with multimedia fugacity model to evaluate the effect of tidal cycles on polycyclic aromatic hydrocarbon release from sediments.

Estuarine sediments are key storage sites for persistent organic pollutants (POPs), and estuaries are strongly influenced by tides throughout the year. Although much work has been done concerning on POPs release, related questions on tidal action have not been considered in the release process. Herein, polycyclic aromatic hydrocarbons (PAHs) release from sediment to seawater was investigated under tidal action by combining a tidal microcosm with level IV fugacity model. The results showed that PAHs release with tidal action was 2.0-3.5 times the accumulation of that without tidal action. Tidal action was confirmed to influence strongly PAHs release from sediment to seawater. We also quantified suspended substance (SS) in the overlying water, and an obvious positive correlation between the PAHs concentration and SS content was found. In addition, an increase in seawater depth enhanced the intensity of tidal action, and more PAHs were released, especially dissolved PAHs. Moreover, the fugacity model results showed a good fit with the experimental results. The simulated values demonstrated that the PAHs release was accomplished via two processes, "rapid release" and "slow release". And the sediment played a key role in the fate of PAHs and was a major sink in the sediment-seawater system.

Two-Stage Self-Supervised Cycle-Consistency Transformer Network for Reducing Slice Gap in MR Images.

Magnetic resonance (MR) images are usually acquired with large slice gap in clinical practice, i.e., low resolution (LR) along the through-plane direction. It is feasible to reduce the slice gap and reconstruct high-resolution (HR) images with the deep learning (DL) methods. To this end, the paired LR and HR images are generally required to train a DL model in a popular fully supervised manner. However, since the HR images are hardly acquired in clinical routine, it is difficult to get sufficient paired samples to train a robust model. Moreover, the widely used convolutional Neural Network (CNN) still cannot capture long-range image dependencies to combine useful information of similar contents, which are often spatially far away from each other across neighboring slices. To this end, a Two-stage Self-supervised Cycle-consistency Transformer Network (TSCTNet) is proposed to reduce the slice gap for MR images in this work. A novel self-supervised learning (SSL) strategy is designed with two stages respectively for robust network pre-training and specialized network refinement based on a cycle-consistency constraint. A hybrid Transformer and CNN structure is utilized to build an interpolation model, which explores both local and global slice representations. The experimental results on two public MR image datasets indicate that TSCTNet achieves superior performance over other compared SSL-based algorithms.

Magnetically separable laccase-biochar composite enable highly efficient adsorption-degradation of quinolone antibiotics: Immobilization, removal performance and mechanisms.

The tremendous potential of hybrid technologies for the elimination of quinolone antibiotics has recently attracted considerable attention. This current work prepared a magnetically modified biochar (MBC) immobilized laccase product named LC-MBC through response surface methodology (RSM), and LC-MBC showed an excellent capacity in the removal of norfloxacin (NOR), enrofloxacin (ENR) and moxifloxacin (MFX) from aqueous solution. The superior pH, thermal, storage and operational stability demonstrated by LC-MBC revealed its potential for sustainable application. The removal efficiencies of LC-MBC in the presence of 1 mM 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) for NOR, ENR and MFX were 93.7 %, 65.4 % and 77.0 % at pH 4 and 40 °C after 48 h reaction, respectively, which were 1.2, 1.3 and 1.3 times higher than those of MBC under the same conditions. The synergistic effect of adsorption by MBC and degradation by laccase dominated the removal of quinolone antibiotics by LC-MBC. Pore-filling, electrostatic, hydrophobic, π-π interactions, surface complexation and hydrogen bonding contributed in the adsorption process. The attacks on the quinolone core and piperazine moiety were involved in the degradation process. This study underscored the possibility of immobilization of laccase on biochar for enhanced remediation of quinolone antibiotics-contaminated wastewater. The proposed physical adsorption-biodegradation system (LC-MBC-ABTS) provided a novel perspective for the efficient and sustainable removal of antibiotics in actual wastewater through combined multi-methods.

Time-restricted feeding affects transcriptomic profiling of hypothalamus in pigs through regulating aromatic amino acids metabolism.

BACKGROUND: Time-restricted feeding (TRF) is an effective means that can efficiently regulate the metabolism and health of animals and humans. However, the effect of TRF on hypothalamic function remains unclear. RESULTS: Results showed that TRF significantly increased the activities of digestive enzymes lipase, maltase in the duodenum and lipase, trypsin in the pancreas whereas significantly decreased serum gastrointestinal hormones gastrin, glucagon-like peptide-1, cholecystokinin, peptide YY, and ghrelin. Metabolites related to amino acid metabolism, including citrulline, kynurenine, N-acetylleucine, l-tryptophan, and l-tyrosine, significantly increased in the TRF group. Differential metabolites were mainly enriched in phenylalanine, tyrosine, and tryptophan biosynthesis and tryptophan metabolism. Transcriptomic analysis of hypothalamus showed that a total of 462 differentially expressed genes (DEGs) were significantly changed by TRF. In particular, DEGs such as DDC, TH, GOT2, and DBH involved in aromatic amino acid metabolism pathways were significantly downregulated, whereas the expression of CYP1B1 was significantly upregulated. Moreover, DEGs (PDYN and PPP3CA) involved in amphetamine addiction and cocaine addiction were also downregulated in the TRF group. CONCLUSION: Taken together, these results suggested that TRF improved the digestion and absorption of nutrients and thus increased the accessibilities of aromatic amino acids. The increasing of circulating aromatic amino acids might mediate the regulatory neuroendocrine effects of TRF regimes on the hypothalamus functions, especially on drug addictions. This study reveals a possible mechanism underlying the effects of regulating feeding patterns on the function of the hypothalamus by altering aromatic amino acids metabolism. © 2022 Society of Chemical Industry.

A simple and feasible fluorescent approach for rapid detection of hexavalent chromium based on gold nanoclusters.

Hexavalent chromium (Cr6+) owns hypertoxicity, non-biodegradability, and carcinogenicity, thus the detection of Cr6+ is of paramount significance for environmental monitoring and human health maintenance. Herein, a simple, rapid, and feasible fluorescent method based on gold nanoclusters (AuNCs) was established for determination of Cr6+. The AuNCs was coated by a simple and fast one-pot method using d-histidine (d-His) and polylysine (P-Lys) as stabilizers and reductants, which could be quenched by the addition of Cr6+ owing to the aggregation of AuNCs and fluorescence resonance energy transfer (FRET) between AuNCs and Cr6+. Under the optimal conditions, the fluorescent sensor exhibited good linearity within 10-10000 µg/L with limit of detection of 7.2 µg/L. The developed sensor possessed favorable sensitivity and selectivity. Additionally, the proposed method also had favorable recovery with good precision and accuracy within the actual sample, including celery cabbage, rice, capsule shell, and river water.

Multi-functional chitosan copolymer modified nanocrystals as oral andrographolide delivery systems for enhanced bioavailability and anti-inflammatory efficacy.

Modifying nanocrystals with functional materials have been common strategy to enlarge the enhancing ability on oral absorption via nanocrystals; however, whether the functional materials have played their full enhancing ability in oral absorption is still unknown. In this study, we synthetized a novel chitosan-based copolymer (the copolymer of sodium dodecyl sulfate (SDS), chitosan (CS) and D-α-Tocopherol polyethylene glycol 1000 succinate, SDS-CS-TPGS), and modified nanocrystals with this copolymer, aiming to enhance the oral absorption of polymer andrographolide (ADR). In real-time distribution study, we found the distribution of ADR, SDS, CS and TPGS varies in gastrointestinal tract, while the distribution of ADR and SDS-CS-TPGS was similar, revealing the SDS-CS-TPGS could able to participate in the absorption process of andrographolide timely. To explore the oral absorption enhancing ability of SDS-CS-TPGS, we prepared a series of nanocrystals modified with different materials and explored their pharmacokinetic performances on SD rats. The results showed the nanocrystals modified with SDS-CS-TPGS (S-C-TANs) exhibited the highest bioavailability, which could enhance the AUC0-∞ of ADR from 1.291 mg/L*h to 5.275 mg/L*h (enhanced for about 4.09-folds). The enhanced anti- inflammatory efficacy was also found on ICR mice by employing ear swelling rate, TNF-α, IL-1ß and IL-6 and pharmacodynamic index. These results indicated that modified with synthesized copolymer containing different functional stabilizers is an efficient strategy to enlarge the enhancing ability on oral absorption of nanocrystals.

A Self-Supervised Learning Based Channel Attention MLP-Mixer Network for Motor Imagery Decoding.

Convolutional Neural Network (CNN) is commonly used for the Electroencephalogram (EEG) based motor-imagery (MI) decoding. However, its performance is generally limited due to the small size sample problem. An alternative way to address such issue is to segment EEG trials into small slices for data augmentation, but this approach usually inevitably loses the valuable long-range dependencies of temporal information in EEG signals. To this end, we propose a novel self-supervised learning (SSL) based channel attention MLP-Mixer network (S-CAMLP-Net) for MI decoding with EEG. Specifically, a new EEG slice prediction task is designed as the pretext task to capture the long-range information of EEG trials in the time domain. In the downstream task, a newly proposed MLP-Mixer is applied to the classification task for signals rather than for images. Moreover, in order to effectively learn the discriminative spatial representations in EEG slices, an attention mechanism is integrated into MLP-Mixer to adaptively estimate the importance of each EEG channel without any prior information. Thus, the proposed S-CAMLP-Net can effectively learn more long-range temporal information and global spatial features of EEG signals. Extensive experiments are conducted on the public MI-2 dataset and the BCI Competition IV Dataset 2A. The experimental results indicate that our proposed S-CAMLP-Net achieves superior classification performance over all the compared algorithms.

A comprehensive review of capacitive deionization technology with biochar-based electrodes: Biochar-based electrode preparation, deionization mechanism and applications.

The recently developed techniques for desalination and wastewater treatment are costly and unsustainable. Therefore, a cost-effective and sustainable approach is essential to achieve desalination through wastewater treatment. Capacitive deionization (CDI), an electrochemical desalination technology, has been developed as a novel water treatment technology with great potential. The electrode material is one of the key factors that promotes the development of CDI technology and broadens the scope of CDI applications. Biochar-based electrode materials have attracted increasing attention from researchers because of their advantages, such as environmentally friendly, economical, and renewable properties. This paper reviews the methods for preparing biochar-based electrode materials and elaborates on the mechanism of CDI ion storage. We then summarize the applications of CDI technology in water treatment, analyze the mechanism of pollutant removal and resource recovery, and discuss the applicability of different CDI configurations, including hybrid CDI systems. In addition, the paper notes that environmentally friendly green activators that facilitate the development of pore structure should be developed more often to avoid the adverse environmental impact. The development of ion-selective electrode materials should be enhanced and it is necessary to comprehensively assess the impact of heteroatoms on selective ion removal and CDI performance. Electrooxidation of organic pollutants should be further promoted to achieve organic degradation by extending to redox reactions.

S2Q-Net: Mining the High-Pass Filtered Phase Data in Susceptibility Weighted Imaging for Quantitative Susceptibility Mapping.

Susceptibility weighted imaging (SWI) is a routine magnetic resonance imaging (MRI) sequence that combines the magnitude and high-pass filtered phase images to qualitatively enhance the image contrasts related to tissue susceptibility. Tremendous amounts of the high-pass filtered phase data with low signal to noise ratio and incomplete background field removal have thus been collected under default clinical settings. Since SWI cannot quantitatively estimate the susceptibility, it is thus non-trivial to derive quantitative susceptibility mapping (QSM) directly from these redundant phase data, which effectively promotes the mining of the SWI data collected previously. To this end, a novel deep learning based SWI-to-QSM-Net (S2Q-Net) is proposed for QSM reconstruction from SWI high-pass filtered phase data. S2Q-Net firstly estimates the edge maps of QSM to integrate edge prior into features, which benefits the network to reconstruct QSM with realistic and clear tissue boundaries. Furthermore, a novel Second-order Cross Dense Block is proposed in S2Q-Net, which can capture rich inter-region interactions to provide more non-local phase information related to local tissue susceptibility. Experimental results on both simulated and in-vivo data indicate its superiority over all the compared deep learning based QSM reconstruction methods.

A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images.

The spatial correlation among different tissue components is an essential characteristic for diagnosis of breast cancers based on histopathological images. Graph convolutional network (GCN) can effectively capture this spatial feature representation, and has been successfully applied to the histopathological image based computer-aided diagnosis (CAD). However, the current GCN-based approaches need complicated image preprocessing for graph construction. In this work, we propose a novel CAD framework for classification of breast histopathological images, which integrates both convolutional neural network (CNN) and GCN (named CNN-GCN) into a unified framework, where CNN learns high-level features from histopathological images for further adaptive graph construction, and the generated graph is then fed to GCN to learn the spatial features of histopathological images for the classification task. In particular, a novel clique GCN (cGCN) is proposed to learn more effective graph representation, which can arrange both forward and backward connections between any two graph convolution layers. Moreover, a new group graph convolution is further developed to replace the classical graph convolution of each layer in cGCN, so as to reduce redundant information and implicitly select superior fused feature representation. The proposed clique group GCN (cgGCN) is then embedded in the CNN-GCN framework (named CNN-cgGCN) to promote the learned spatial representation for diagnosis of breast cancers. The experimental results on two public breast histopathological image datasets indicate the effectiveness of the proposed CNN-cgGCN with superior performance to all the compared algorithms.

Metabolome-Microbiome Responses of Growing Pigs Induced by Time-Restricted Feeding.

Time-restricted feeding (TRF) mode is a potential strategy in improving the health and production of farm animals. However, the effect of TRF on microbiota and their metabolism in the large intestine of the host remains unclear. Therefore, the present study aimed to investigate the responses of microbiome and metabolome induced by TRF based on a growing-pig model. Twelve crossbred growing barrows were randomly allotted into two groups with six replicates (1 pig/pen), namely, the free-access feeding group (FA) and TRF group. Pigs in the FA group were fed free access while the TRF group were fed free access within a regular time three times per day at 07:00-08:00, 12:00-13:00, and 18:00-19:00, respectively. Results showed that the concentrations of NH4-N, putrescine, cadaverine, spermidine, spermine, total biogenic amines, isobutyrate, butyrate, isovalerate, total SCFA, and lactate were increased while the pH value in the colonic digesta and the concentration of acetate was decreased in the TRF group. The Shannon index was significantly increased in the TRF group; however, no significant effects were found in the Fisher index, Simpson index, ACE index, Chao1 index, and observed species between the two groups. In the TRF group, the relative abundances of Prevotella 1 and Eubacterium ruminantium group were significantly increased while the relative abundances of Clostridium sensu sticto 1, Lactobacillus, and Eubacterium coprostanoligenes group were decreased compared with the FA group. PLS-DA analysis revealed an obvious and regular variation between the FA and TRF groups, further pathway enrichment analysis showed that these differential features were mainly enriched in pyrimidine metabolism, nicotinate and nicotinamide metabolism, glycerolipid metabolism, and fructose and mannose metabolism. In addition, Pearson's correlation analysis indicated that the changes in the microbial genera were correlated with the colonic metabolites. In conclusion, these results together indicated that although the overall microbial composition in the colon was not changed, TRF induced the gradient changes of the nutrients and metabolites which were correlated with certain microbial genera including Lactobacillus, Eubacterium_ruminantium group, Eubacterium coprostanoligenes group, Prevotella 1, and Clostridium sensu sticto 1. However, more studies are needed to understand the impacts of TRF on the health and metabolism of growing pigs.

Key role of different levels of dissolved oxygen in hydrolyzed polyacrylamide bioconversion: Focusing on metabolic products, key enzymes and functional microorganisms.

Dissolved oxygen (DO) played a short board effect on nitrogen biotransformation and pollutant metabolism. This study for the first time explored the key role of different levels of DO (covering anaerobic, anoxic and aerobic) on hydrolyzed polyacrylamide (HPAM) bioconversion. HPAM was metabolized to intermediates with different chain length. Volatile fatty acid (VFA) production rose first and then descended with DO concentration (0-2 mg·L-1), and the maximum reached 92.5 mg·L-1 when DO was 0.5 mg·L-1. Total nitrogen (TN) removal increased first and then dropped with DO concentration, and the maximum (61.4%) occurred at 0.5 mg·L-1 DO. NH4+-N dipped from 42.8 to 0 mg·L-1 and NO3--N rose from 0 to 32.8 mg·L-1 with DO concentration. The changes of enzyme activities were consistent with those of VFA production and TN removal, which were related to HPAM metabolism and N bioconversion. Microbial function was correlated to HPAM metabolism, N bioconversion and key enzyme.

[Screening of biomarkers related with leukocyte responses early after burn injury in mice by differential gene expression profiling].

OBJECTIVE: To screen the genes related with leukocyte responses in mice early after burn injury by bioinformatic analysis of the gene expression profiling data. METHODS: The gene expression profiles were obtained from GEO (GSE7404, Mouse musculus, 25% TBSA, full-thickness) database. T test, fold changes and GO functional enrichment analysis were used to identify the differentially expressed genes (DEGs) related to leukocyte responses to burns; the interacting genes were transferred to STRING to construct the protein-protein interaction (PPI) network. Biological annotation of the sub-networks was executed using the software Cytoscape. Real-time PCR and Western blotting were used to verify the DEGs in mice. RESULTS: In mice at 1 day post-burn, a total of 658 genes were up-regulated and 1167 were down-regulated. PPI network and module analysis suggested that some of the genes (Stat1, Cdk1, Cd19, Lck and Jun) may play critical roles in the PPI network post-burn. Real-time PCR and Western blotting results in mice were consistent with those of bioinformatic analysis of Stat1, Cdk1 and Jun. CONCLUSION: Stat1, Cdk1 and Jun might be critical players in the development of leukocyte response in mice early after burn injury. Our finding provides new insights into the pathogenesis of leukocyte response to burn injury and identifies several biomarkers as potential targets for burn treatment.

Construction of an immunorelated protein-protein interaction network for clarifying the mechanism of burn.

BACKGROUND AND AIM: Severe burn is known to induce a series of pathological responses resulting in increased susceptibility to systemic inflammatory response and multiple organ failure, but the underlying molecular mechanism remains unclear at present. The main aim of this study was to expand our understanding of the events leading to circulating leukocyte response after burn by subjecting the gene expression profiles to a bioinformatic analysis. MATERIALS AND METHODS: Comprehensive gene expression analysis was performed to identify differentially expressed genes (DEGs) using the expression profile GSE7404 (Mus musculus, circulating leukocyte, 25% of total body surface area (TBSA), full thickness) downloaded from the Gene Expression Omnibus, followed by the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, a postburn protein-protein interaction (PPI) network was constructed to identify potential biomarkers. RESULTS: Maximum changes in the gene expression profile were detected 1 day post burn. Separate Gene Ontology (GO) functional enrichment analysis for upregulated and downregulated DEGs revealed significant alterations of genes related to biological process such as "response to stimuli," "metabolic," "cellular and immune system processes," "biological regulation," and "death" in the leukocyte transcriptome after the burn. The KEGG pathway enrichment analysis showed that the upregulated DEGs were significantly enriched in the nodes of immunorelated and signal transduction-related pathways, and the downregulated genes were significantly enriched for the immunorelated pathways. The PPI network and module analysis revealed that, 1 day after the burn, lymphocyte-specific protein tyrosine kinase (Lck) (downregulated), Jun (upregulated), Cd19 (downregulated), Stat1 (downregulated), and Cdk1 (upregulated) were located centrally in both the PPI network and modules. CONCLUSIONS: Based on an integrated bioinformatic analysis, we concluded that Lck, Jun, Cd19, Stat1, and Cdk1 may be critical 1 day after the burn. These findings expand our understanding of the molecular mechanisms of this important pathological process. Further studies are needed to support our work, focused on identifying candidate biomarkers with sufficient predictive power to act as prognostic and therapeutic biomarkers for burn injury.