Integrative bioinformatic analysis identified IFIT3 as a novel regulatory factor in psoriasis.

Psoriasis is an autoimmune skin disease with poor prognosis. Currently, there is no cure for psoriasis and the pathogenic mechanism of psoriasis remains unclear. Our study aims to explore key regulators underlying psoriasis and potential targets for psoriasis treatment. RNA-seq data of psoriasis and normal tissues were extracted from Gene Expression Omnibus database to screen differentially expressed genes (DEGs). Weighted correlation network analysis (WGCNA) was conducted to identify key gene modules correlated with psoriasis. Enrichment analysis was used to characterize identified genes. The expression of identified genes was verified in a data set with various types of psoriasis lesion tissues and six psoriasis and healthy control tissues by quantitative polymerase chain reaction and immunohistochemistry assays. And the biological functions of IFIT3 in keratinocytes were determined by colony formation assays, Cell Counting Kit-8, and enzyme-linked immunosorbent assays. A total of 594 overlapped genes (370 upregulated and 224 downregulated) were selected as DEGs between psoriasis and normal tissues in three independent data sets. These genes were enriched in interferon-related pathway and cytokine-related pathway. Weighted correlation network analysis identified several gene modules that were associated with psoriasis. Overlapped genes between gene modules and DEGs were associated with interferon-related pathway and T cell activities. Among these genes, OAS1, USP18, and IFIT3 had higher expression levels in psoriasis vulgaris (PV) and nonpustular palmoplantar psoriasis (NPPP) tissues but not Palmoplantar Pustular Psoriasis (PPPP). Meanwhile, these results were confirmed in our independent psoriasis tissue cohort. And results of in vitro experiments showed that inhibition of IFIT3 significantly impaired the proliferation capacity and CXCL1, CCL20, IL-1ß, and IL-6 secretion of keratinocytes. Our study identified key genes and pathways underlying the pathogenesis of psoriasis through the conduct of integrated analysis. OAS1, USP18, and IFIT3 could be potential targets for the treatment of psoriasis. IFIT3 can promote the proliferation and immune activation of keratinocytes and facilitates the development of psoriasis.

CCL13 is upregulated in alopecia areata lesions and is correlated with disease severity.

Alopecia areata (AA) is a multi-factors disease characterized by non-scarring hair loss. AA could be classified into three main clinical phenotypes including patchy type AA (AAP), alopecia totalis (AT) and alopecia universalis (AU) based on the severity and areas of hair loss. Recent studies suggested immunological factor was critical in AA, but the precise aetiology and pathogenesis of AA still need exploration. In the work, we screened two gene expression profiles (GSE45512 and GSE68801) from Gene Expression Omnibus (GEO). Based on the two data sets, 10 upregulated genes and 107 downregulated genes in AA skin biopsies were identified. CCL13, as one of the remarkably upregulated genes, was found to have potential biological functions in aberrant immune response of AA according to the GO and KEGG analyses. The PPI network showed CCL13 was associated with multiple immune-related genes. The expression of CCL13 was increased depending on the severity of disease in AA patients. Cytotoxic lymphocytes, T cells and myeloid dendritic cells accumulated remarkably in scalp tissue depending on the severity of AA, and CCL13 was significantly correlated to cytotoxic lymphocytes, T cells and myeloid dendritic cells in AA patients. Our RT-PCR and ELISA results found CCL13 was upregulated in skin biopsy and serum of AA patients, and the immunohistochemistry (IHC) detection showed CCL13 was expressed by both the hair follicle epithelium and infiltrating immune cells. In conclusion, the upregulated of CCL13 and subsequent immune cell infiltration was related to AA, which could be a promising target for diagnosis and therapy in AA patients.

Array-based microbial identification upon extracellular aminoglycoside residue sensing.

Sensitive and rapid identification of pathogenic microorganisms is of great importance for clinical diagnosis and treatment. In this study, we developed an ultrasensitive colorimetric sensor array (CSA) based on the interactions between aminoglycoside antibiotics (AMGs) and Ag nanoparticles decorated with ß-cyclodextrin (AgNPs@ß-CD) to discriminate microorganisms quickly and accurately. Microorganisms can absorb different amounts of AMGs after incubation. Upon the addition of AgNPs@ß-CD, the corresponding extracellular AMG residues will bind to AgNPs@ß-CD, leading to color changes due to the modifications in localized surface plasmon resonance. The array was developed using 4 AMGs as sensing elements and AgNPs@ß-CD as the colorimetric probe to generate a unique colorimetric response pattern for each microorganism. Standard chemometric methods indicated excellent discrimination among 20 microorganisms at low concentrations of 2 × 106 CFU/mL. Therefore, this ultrasensitive CSA can be used for microbial discrimination portably and efficiently. Importantly, the concentration of microbial discrimination by our array is much lower than that of prior CSAs. This method of extracellular residue sensing also provided a new strategy to improve the sensitivity of conventional CSA in the discrimination of microorganisms, to measure the amount of intercellular uptake of AMGs by microorganisms, and to screen drugs that can easily be accumulated by the pathogenic microorganisms.

Comprehensive bioinformatics analysis identifies lncRNA HCG22 as a migration inhibitor in esophageal squamous cell carcinoma.

Esophageal cancer is one of the most lethal malignancies worldwide, and esophageal squamous cell carcinoma (ESCC) is the dominant histological type. However, the long noncoding RNA (lncRNA) alterations in ESCC have not been elucidated to date. In this study, reliable databases from Gene Expression Omnibus (GEO), which analyzed lncRNA expression in ESCC tumor tissues and adjacent normal tissues were searched, and common differentially expressed lncRNAs and genes were analyzed. Next, cis- trans analysis was performed to predict the underlying relationships between altered lncRNAs and mRNAs, and the lncRNA-mRNA regulatory network was established. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of altered lncRNA-related genes were performed. The promising lncRNA HCG22 was validated by quantitative polymerase chain reaction (qPCR), and clinicopathological data were collected to identify the relationship between lncRNA HCG22 expression level and clinical features. Finally, Transwell assays were performed to explore the biological functions of lncRNA HCG22 in ESCC cells. Two hundred forty-one lncRNAs and 835 mRNAs were observed to be remarkably altered between ESCC tumor tissues and adjacent normal tissues. The lncRNA-mRNA regulatory network showed the coexpression association between lncRNA HCG22 and SPINK7 and ADAMTS12. GO and KEGG analyses showed that HCG22 and ADAMTS12 had potential biological functions in the cell migration of ESCC. The downregulation of lncRNA HCG22 in ESCC tumor tissues was validated by qPCR, and the clinicopathological data showed a noticeable correlation between lncRNA HCG22 expression level and the ESCC differentiational degree and clinical TNM stage. Kaplan-Meier analysis showed that patients with ESCC having low lncRNA HCG22 expression in ESCC tissues had considerably shorter overall survival compared with patients with ESCC having high lncRNA HCG22 expression. Following Transwell assays confirmed the migratory role of lncRNA HCG22 in ESCC cells. In conclusion, lncRNA HCG22 was downregulated in ESCC tissues and can be a migration inhibitor of ESCC cells, and SPINK7 and ADAMTS12 are promising to be the regulatory targets of lncRNA HCG22.

Tepidiphilus olei sp. nov., isolated from the production water of a water-flooded oil reservoir in PR China.

A novel, moderately thermophilic, Gram-stain-negative bacterium, designated strain J18T, was isolated from a water-flooded oil reservoir. Cells were aerobic, oxidase- and catalase-positive, with a polar flagellum. Growth occurred at 35-60 °C and at pH 6-8.5. The respiratory quinones were ubiquinone 8 and ubiquinone 9. The dominant cellular fatty acids were C16 : 0, C17 : 0 cyclo, C19 : 0 cyclo ω8c and summed feature 8 (C18 : 1 ω7c/C18 : 1 ω6c). The polar lipids consisted of phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, phosphatidylcholine, an unidentified aminolipid, an unidentified phospholipid and an unidentified aminophospholipid. The strain showed the highest 16S rRNA gene sequence similarities to Tepidiphilus margaritifer DSM 15129T (98.6 %), Tepidiphilus succinatimandens DSM 15512T (98.4 %) and Tepidiphilus thermophilus DSM 27220T (98.1 %), respectively, and the similarity to other species was lower than 93 %. In the phylogenetic trees, it constituted a unique sub-cluster within the genus Tepidiphilus. The DNA G+C content of strain J18T was 64.44 mol%. As compared with the type strains, the genome-to-genome distances of strain J18T were 34.7-40 %. These results confirmed the separate species status of J18T with its close relatives. On the basis of physiological, chemotaxonomic and phylogenetic analyses along with the low levels of identity at the whole-genome level, it can be concluded that strain J18T represents a new species of the genus Tepidiphilus, for which the name Tepidiphilus olei sp. nov. is proposed. The type strain of T. olei is J18T (=CGMCC 1.16800T=LMG 31400T).

Oleiliquidispirillum nitrogeniifigens gen. nov., sp. nov., a new member of the family Rhodospirillaceae isolated from oil reservoir water.

A novel Gram-staining-negative, spiral-shaped bacterium, designated strain 64-1T, was isolated from oil reservoir water collected from Liaohe oilfield, north-eastern China. Growth occurred at 15-55 °C and pH 6.0-10.0. The sole respiratory quinone was Q-10. The predominant cellular fatty acids were summed feature 8 (C18 : 1 ω7c /C18 : 1 ω6c), C16 : 0 and C19 : 0 cyclo ω8c. The polar lipids consisted of phosphatidylethanolamine (PE), phosphatidylglycerol (PG), phosphatidylcholine (PC), an unidentified aminophospholipid (UAPL), an unidentified aminolipid (UAL) and two unidentified polar lipids (UPL). The genomic DNA G+C content of strain 64-1T was 64.5 mol%. Strain 64-1T shared the highest 16S rRNA gene sequence similarities with Phaeospirillum chandramohanii JA145T (92.0 %) and Telmatospirillum siberiense 26-4b1T (91.8 %). In the phylogenetic trees, the strain constituted a sub-cluster within the family Rhodospirillaceae. Based on the results of morphological, physiological, biochemical and phylogenetic analysis, strain 64-1T represents a new species of a novel genus within the family Rhodospirillaceae, for which the name Oleiliquidispirillum nitrogeniifigens gen. nov., sp. nov. is proposed. The type strain is 64-1T (=CGMCC 1.16798T=LMG 31399T).

MicroRNA-331-3p inhibits epithelial-mesenchymal transition by targeting ErbB2 and VAV2 through the Rac1/PAK1/ß-catenin axis in non-small-cell lung cancer.

MicroRNAs have been reported to play critical roles in the regulation of non-small-cell cancer (NSCLC) development, but the role of microRNA (miR)-331-3p in NSCLC is still unclear. In this study, the expression levels of miR-331-3p in NSCLC tumor tissues and adjacent normal tissues were examined by quantitative RT-PCR, and the relationship between miR-331-3p expression and patient clinicopathological characteristics was analyzed. The effects of miR-331-3p on epithelial-mesenchymal transition (EMT), migration, and metastasis of NSCLC cells were determined in vitro and vivo. Direct functional targets of miR-331-3p were identified by luciferase reporter assay, western blot assay, immunohistochemical staining, and rescue assay. The downstream pathway regulated by miR-331-3p was identified by immunofluorescence, immunoprecipitation, and Rac1 activity examination. Our results showed that miR-331-3p was significantly downregulated in NSCLC tumor tissues and was correlated with clinicopathological characteristics, and miR-331-3p could be an independent prognostic marker for NSCLC patients. Furthermore, miR-331-3p significantly suppressed EMT, migration and metastasis of NSCLC cells in vitro and in vivo. Both ErbB2 and VAV2 were direct functional targets of miR-331-3p. The activities of Rac1, PAK1, and ß-catenin were regulated by miR-331-3p through ErbB2 and VAV2 targeting. These results indicated that miR-331-3p suppresses EMT, migratory capacity, and metastatic ability by targeting ErbB2 and VAV2 through the Rac1/PAK1/ß-catenin axis in NSCLC.

Colorimetric Sensor Array Based on Wulff-Type Boronate Functionalized AgNPs at Various pH for Bacteria Identification.

The efficient identification of bacteria is of considerable significance in clinical diagnosis. Herein, a novel colorimetric sensor array was developed for the detection and identification of bacteria based on the specific affinity and electrostatic interaction between Wulff-type 4-mercaptophenylboronic acid (MPBA)-mercaptoethylamine (MA) cofunctionalized AgNPs (MPBA-MA@AgNPs) and bacteria at various pH. In the neutral and alkaline conditions, AgNPs tended to be dispersed due to the specific affinity between cis-diol residues contained in carbohydrate-rich compositions on the bacterial cell surface and MPBA. Bacterial cells have different carbohydrate compositions on their surface. The differential binding affinity of MPBA on the surface of AgNPs to cis-diol residues of various carbohydrates resulted in a different color change of AgNPs, which could be tuned by pH. On the contrary, AgNPs tended to be aggregated due to the electrostatic interaction between positively charged MA and negatively charged bacteria under acidic conditions. Therefore, using various pH buffer solutions as the sensing elements and MPBA-MA@AgNPs as the indicator, bacteria could be differentiated from each other by their own color response patterns. Moreover, the complex bacteria mixtures could be well discriminated. The method is simple, efficient, and visual and has a potential application in pathogen diagnosis.

A pH-based sensor array for the detection and identification of proteins using CdSe/ZnS quantum dots as an indicator.

Protein identification is very important in the field of clinical medicine and diagnosis. Here, we report a novel and simple sensor array for the detection and identification of proteins using pH buffer solutions as sensing elements. Different proteins in various pH solutions have different net surface charges including positive, negative or no charge. Such differences may allow a pattern recognition-based sensor array for protein identification. When using negatively charged CdSe/ZnS quantum dots as an indicator, the interactions between a charged protein and quantum dots result in fluorescence changes, generating a differential response pattern for the protein. The result shows that proteins with pI > 7, pI = 7 or pI < 7 can be differentiated successfully. Moreover, complex protein mixtures are also able to be identified and the results demonstrate that surface charge may play an important role in protein sensing. The HSA of different concentrations in water and human urine can also be detected by using the sensor array. It is demonstrated that the proposed sensor array has potential applications in clinical diagnosis and proteomics.

Colorimetric Sensor Array Based on Gold Nanoparticles with Diverse Surface Charges for Microorganisms Identification.

We report a simple and novel colorimetric sensor array for rapid identification of microorganisms. In this study, four gold nanoparticles (AuNPs) with diverse surface charges were used as sensing elements. The interactions between AuNPs and microorganisms led to obvious color shifts, which could be observed by the naked eye. A total of 15 microorganisms had their own response patterns and were differentiated by linear discriminant analysis (LDA) successfully. Moreover, microorganism mixtures could also be well discerned. The method is simple, fast (within 5 s), effective, and visual, showing the potential applications in pathogen diagnosis and environmental monitoring.

Impacts of Kinematic Information on Action Anticipation and the Related Neurophysiological Associations in Volleyball Experts.

In this study, we investigated the cognitive mechanisms underlying action anticipation in volleyball players, especially concerned with the differences between experts and amateurs. Participants included both expert (male, N = 26) and amateur (male, N = 23) volleyball players, who were asked to predict spiking movements containing high, medium, and low levels of kinematic information while their electrophysiological activities were recorded. The high-information stimuli included the whole spiking action, the medium-information stimuli ended at 120 ms, and the low-information stimuli ended at 160 ms before hand-ball contact. The results showed that experts significantly outperformed amateurs in both prediction accuracy (68% in experts vs. 55% in amateurs) and reaction time (475.09 ms in experts vs. 725.81 ms in amateurs) under the medium-information condition. Analysis of alpha rhythm activity revealed that experts exhibited the strongest desynchronization under the low-information condition, suggesting increased attentional engagement. In contrast, amateurs showed the weakest desynchronization under the medium-information condition. Furthermore, mu rhythm activity analysis showed greater desynchronization in the duration of 100-300 ms before hand-ball contact for experts, correlating with their higher anticipation accuracy. These findings highlight the significant kinematic information-processing abilities of volleyball experts and elucidate the neural mechanisms underlying efficient attentional engagement and mirroring. Therefore, this study provides valuable insights for the development of targeted training programs through which to enhance athletic performance.

A New Evaluation Method of Recoverable Reserves and Its Application in Carbonate Gas Reservoirs.

The propagation pattern of pressure drawdown effectively reflects the recoverable reserves range around the gas well and serves as a crucial basis for development strategies. However, it is not easy to detect the pressure propagation boundary near the producing well, especially in low-permeability reservoirs where the drainage radius is small. Physical simulation experiments can serve as a crucial method as the whole pressure profile and gas rate can be obtained in real time. Using long core plugs with permeabilities of 2.300 mD, 0.486 mD, and 0.046 mD, physical simulation experiments were carried out under varying initial water saturation (Swi) conditions of 0%, 20%, 40%, and 55% to observe the dynamic variations in pressure profiles of the core plugs during pressure depletion. Based on the material balance equation and pressure profile characteristics of the core plugs, a method for evaluating recoverable reserves within a well-spacing radius through laboratory experiments was proposed and performed. Mechanism analysis was conducted based on mercury injection tests, and suggestions for enhancing gas recovery were presented. Research findings indicate that lower permeability, higher initial water saturation, and higher abandonment gas rates result in reduced reserve utilization range and degree. Under abandoned gas rate conditions, for type I and II rocks, the pore radius is primarily distributed between 0.1 and 1 µm, the pressure drawdown can reach the well-spacing radius of 600 m, and the ultimate recovery efficiencies are more than 70.6%. For type III rocks, the pore radius mainly falls below 0.1 µm, the drainage radius is smaller than 10 m with Swi greater than 40%, and the ultimate recovery is below 10%. This paper provides an experimental method for recoverable reserves evaluation while formulating gas reservoir development strategies before well testing.

Mechanism and application of gas phase trapping by spontaneous imbibition.

For fractured gas reservoirs with strong water drive, gas phase trapping affects the gas recovery significantly. The recovery may be less than 50% for some reservoirs while it is only 12% for Beaver River gas field. The gas phase trapping mechanism has been revealed by the results of depletion experimental test. The residual pressure of the trapped gas is as high as 11.75 MPa with a 12.8 cm imbibition layer resulting in gas recovery deceased 49.5% compared with that without imbibition layer. A mathematical model is built to calculate the imbibition thickness based on capillary pressure and relative permeability of the matrix. The gas phase trapping are analyzed by two representative wells in Weiyuan gas field, the intermittent production reinforces the imbibition thickness and result in gas trapped in the matrix block with high residual pressure for the low performace gas wells, the extremely low gas recovery can be explained more rationally. That lays a foundation of improving the gas recovery for fractured reservoirs.

Array-based specific classification of bacterial species via ligands with dimethylamino/amino groups.

The early detection of bacterial species plays a crucial role in patient prognosis and the development of effective therapeutic regimens. This study introduces an accessible and promising colorimetric sensor array designed to classify gram-positive (G+) and gram-negative (G-) bacterial species. The classification relies on 6 chemical ligands with dimethylamino/amino groups as sensing elements and silver nanotriangles as colorimetric probes. Using these specific sensor arrays, we successfully differentiated G- and G+ bacterial species and discriminated individual bacterial strains, and the sensors exhibited remarkable reproducibility and high sensitivity. Moreover, the sensor array can identify bacterial mixtures and bacteria at varying concentrations, underscoring its versatility. In summary, this sensor array offers an effective tool for bacterial analysis with promising applications in the field of biomedical diagnostics.

Cuproptosis Depicts Immunophenotype and Predicts Immunotherapy Response in Lung Adenocarcinoma.

BACKGROUND: Although significant progress has been made in immunotherapy for lung adenocarcinoma (LUAD), there is an urgent need to identify effective indicators to screen patients who are suitable for immunotherapy. Systematically investigating the cuproptosis-related genes (CRGs) in LUAD may provide new ideas for patients' immunotherapy stratification. METHOD: We comprehensively analyzed the landscape of 12 CRGs in a merged TCGA and GEO LUAD cohort. We investigated the associations between tumor microenvironment and immunophenotypes. We utilized a risk score to predict the prognosis and immunotherapy response for an individual patient. Additionally, we conducted CCK-8 experiments to evaluate the impact of DLGAP5 knockdown on A549 cell proliferation. RESULT: We utilized an integrative approach to analyze 12 CRGs and differentially expressed genes (DEGs) in LUAD samples, resulting in the identification of two distinct CRG clusters and two gene clusters. Based on these clusters, we generated immunophenotypes and observed that the inflamed phenotype had the most abundant immune infiltrations, while the desert phenotype showed the poorest immune infiltrations. We then developed a risk score model for individual patient prognosis and immunotherapy response prediction. Patients in the low-risk group had higher immune scores and ESTIMATE scores, indicating an active immune state with richer immune cell infiltrations and higher expression of immune checkpoint genes. Moreover, the low-risk group exhibited better immunotherapy response according to IPS, TIDE scores, and Imvigor210 cohort validation results. In addition, our in vitro wet experiments demonstrated that DLGAP5 knockdown could suppress the cell proliferation of A549. CONCLUSION: Novel cuproptosis molecular patterns reflected the distinct immunophenotypes in LUAD patients. The risk model might pave the way to stratify patients suitable for immunotherapy and predict immunotherapy response.

Bioinformatics construction and experimental validation of a cuproptosis-related lncRNA prognostic model in lung adenocarcinoma for immunotherapy response prediction.

Cuproptosis is a newly form of cell death. Cuproptosis related lncRNA in lung adenocarcinoma (LUAD) has also not been fully elucidated. In the present study, we aimed to construct a prognostic signature based on cuproptosis-related lncRNA in LUAD and investigate its association with immunotherapy response. The RNA-sequencing data, clinical information and simple nucleotide variation of LUAD patients were obtained from TCGA database. The LASSO Cox regression was used to construct a prognostic signature. The CIBERSORT, ESTIMATE and ssGSEA algorithms were applied to assess the association between risk score and TME. TIDE score was applied to reflect the efficiency of immunotherapy response. The influence of overexpression of lncRNA TMPO-AS1 on A549 cell was also assessed by in vitro experiments. The lncRNA prognostic signature included AL606834.1, AL138778.1, AP000302.1, AC007384.1, AL161431.1, TMPO-AS1 and KIAA1671-AS1. Low-risk group exhibited much higher immune score, stromal score and ESTIMATE score, but lower tumor purity compared with high-risk groups. Also, low-risk group was associated with a much higher score of immune cells and immune related function sets, indicating an immune activation state. Low-risk patients had relative higher TIDE score and lower TMB. External validation using IMvigor210 immunotherapy cohort demonstrated that low-risk group had a better prognosis and might more easily benefit from immunotherapy. Overexpression of lncRNA TMPO-AS1 promoted the proliferation, migration and invasion of A549 cell line. The novel cuproptosis-related lncRNA signature could predict the prognosis of LUAD patients, and helped clinicians stratify patients appropriate for immunotherapy and determine individual therapeutic strategies.

An artificial intelligence network-guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms.

The immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes-based model remains largely unknown. In the current study, by analysing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data, the tumour-infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and-most significantly-immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification.

Reprogramming Macrophage Metabolism and its Effect on NLRP3 Inflammasome Activation in Sepsis.

Sepsis, the most common life-threatening multi-organ dysfunction syndrome secondary to infection, lacks specific therapeutic strategy due to the limited understanding of underlying mechanisms. It is currently believed that inflammasomes play critical roles in the development of sepsis, among which NLRP3 inflammasome is involved to most extent. Recent studies have revealed that dramatic reprogramming of macrophage metabolism is commonly occurred in sepsis, and this dysregulation is closely related with the activation of NLRP3 inflammasome. In view of the fact that increasing evidence demonstrates the mechanism of metabolism reprogramming regulating NLRP3 activation in macrophages, the key enzymes and metabolites participated in this regulation should be clearer for better interpreting the relationship of NLRP3 inflammasome and sepsis. In this review, we thus summarized the detail mechanism of the metabolic reprogramming process and its important role in the NLRP3 inflammasome activation of macrophages in sepsis. This mechanism summarization will reveal the applicational potential of metabolic regulatory molecules in the treatment of sepsis.

Cell-free fat extract protects septic lethality via restraining NLRP3 inflammasome activation.

BACKGROUND: Sepsis is a dysregulated host response to infection with high mortality and current management cannot reach optimal remission. Previous studies have shown that cell-free fat extract (CEFFE) is a kind of bioactive extraction from adipose tissues and exhibits a potent anti-inflammatory effect on wound healing and inflammatory diseases. However, the potential role of CEFFE in sepsis remains unclear. METHODS: CEFFE was extracted from healthy donors and was intraperitoneally injected into septic mice. The septic mice models were constructed using lipopolysaccharide (LPS), E. coli, and cecal ligation and puncture (CLP). The survival of septic mice was detected for 96 h and Kaplan-Meier analysis was used to analyze the differences of survival rates. Lung tissues that were collected from septic mice were subjected to HE staining to evaluate the extent of lung injury, and the mice serum was obtained for inflammasome-related cytokines detection. Moreover, peritoneal macrophages were extracted from C57 mice and treated with CEFFE and/or inflammasome activators. The level of IL-1ß, IL-18, IL-6, and TNF-α was detected by ELISA, and the activation of NLRP3 were evaluated by Western Blot. Total mtDNA and mitochondrial permeability transition pore were determined to explore the mitochondrial dysfunction in the activation of NLRP3 inflammasome with or without CEFEE. Coimmunoprecipitation (Co-IP) assays were performed to confirm the mechanism of NLRP3 activation induced by CEFFE. RESULTS: CEFFE significantly improved the survival of sepsis mice and alleviate sepsis-induced lung injury. Moreover, CEFFE significantly decreased the level of inflammasome-cytokines (IL-1ß and IL-18) but not the pro-inflammatory cytokines such as IL-6 and TNF-α. Moreover, CEFFE markedly suppressed the canonical activation of NLRP3 inflammasome without affecting inflammasomes NLRC4 and AIM2. Additionally, the non-canonical activation of NLRP3 inflammasome was significantly inhibited by CEFFE. CEFFE treatment attenuated the mtDNA outflow and the increase of mitochondrial permeability induced by both canonical and non-canonical pathway of NLRP3 inflammasome activation. The results of Co-IP assays revealed that CEFFE remarkably attenuated the oligomerization of ASC and inhibited the association between NLRP3 and ASC. CONCLUSION: Our study revealed that CEFFE could significantly alleviate sepsis-related injuries possibly by suppressing NLRP3 inflammasome activation. CEFFE was a promising approach for sepsis treatment.

Study on the Pore Structure and Fractal Characteristics of Different Lithofacies of Wufeng-Longmaxi Formation Shale in Southern Sichuan Basin, China.

Gas content and flow characteristics are closely related to shale lithofacies, and significant differences exist in the pore structure and fractal characteristics among lithofacies. In this study, X-ray diffractometer (XRD), field-emission scanning electron microscopy (FE-SEM), gas adsorption (N2 and CO2), and fractal theory were employed to systematically characterize the pore attributes of the marine Wufeng-Longmaxi formation shales. The information of various pores and microfractures among lithofacies was extracted and quantified via high-resolution FE-SEM image stitching technology. Shales were classified into four types based on mineral compositions, and siliceous shales possess the largest SEM-based surface porosity (2.84%) and the largest pore volume (PV) (average 0.0243 cm3/g) as well as specific surface area (SSA) (average 28.06 m2/g). The effect of lithofacies variation on the PV of shale is minor. In contrast, the lithofacies variation has a significant impact on the SSA, and the SSA of siliceous shale is 39.11% higher than that of argillaceous shale. PV and SSA show strong positive correlation with the total organic carbon (TOC) content but negative correlation with clay minerals. Siliceous shales have the greatest fractal dimension D1 (pore surface roughness) (average 2.6821), which is contributed by abundant organic matter pores with more complicated boundaries. The largest fractal dimension D2 (pore structure complexity) (average 2.8263) is found in mixed shales, which is attributed to well-developed intraparticle (intraP) pores associated with carbonate mineral dissolution. This indicates that siliceous shales have the highest methane adsorption capacity and that shale gas desorption, diffusion, and seepage are more difficult in mixed shales.