Deciphering a Prognostic Signature Based on Soluble Mediators Defines the Immune Landscape and Predicts Prognosis in HNSCC.

BACKGROUND: The study on Head and Neck Squamous Cell Carcinoma (HNSCC), a prevalent and aggressive form of head and neck cancer, focuses on the often-overlooked role of soluble mediators. The objective is to leverage a transcriptome-based risk analysis utilizing soluble mediator-related genes (SMRGs) to provide novel insights into prognosis and immunotherapy efficacy in HNSCC patients. METHODS: We analyzed the expression and prognostic significance of 10,859 SMRGs using 502 HNSCC and 44 normal samples from the TCGA-HNSC cohort in The Cancer Genome Atlas (TCGA). The samples were divided into training and test sets in a 7:3 ratio, with an additional external validation using 40 tumor samples from the International Cancer Genome Consortium (ICGC). Key differentially expressed genes (DEGs) with prognostic significance were identified through univariate and Lasso-Cox regression analyses. A prognostic model based on 20 SMRGs was developed using Lasso and multivariate Cox regression. We assessed the clinical outcomes and immune status in high-risk (HR) and low-risk (LR) HNSCC patients utilizing the BEST databases and single-sample Gene Set Enrichment Analysis (ssGSEA). RESULTS: The 20 SMRGs were crucial in predicting the prognosis of HNSCC, with the SMRG signature emerging as an independent prognostic indicator. Patients classified in the HR group exhibited poorer outcomes compared to those in the LR group. A nomogram, integrating clinical characteristics and risk scores, demonstrated substantial prognostic value. Immunotherapy appeared to be more effective in the LR group, possibly attributed to enhanced immune infiltration and expression of immune checkpoints. CONCLUSIONS: The model based on soluble mediator-associated genes offers a fresh perspective for assessing the pre-immune efficacy and showcases robust predictive capabilities. This innovative approach holds significant promise in advancing the field of precision immuno-oncology research, providing valuable insights for personalized treatment strategies in HNSCC.

Emergence and clonal expansion of Aeromonas hydrophila ST1172 that simultaneously produces MOX-13 and OXA-724.

BACKGROUND: Aeromonas hydrophila infections can cause gastrointestinal symptoms such as diarrhea; however, deep infections are rarely reported. Outbreaks of A. hydrophila are reported more frequently in fish, poultry, and snakes than in humans. This study aimed to track clonal relatedness of deep infections caused by A. hydrophila using whole genome sequencing (WGS). METHODS: We collected three isolates of A. hydrophila in July 19 to August 29, 2019, from patients that underwent spine surgery. Accurate species identification was performed using whole-genome average nucleotide identity (ANI). Antimicrobial susceptibility testing was performed using a VITEK 2 automated AST-N334 Gram-negative susceptibility card system. Antimicrobial resistance and virulence genes were identified using the Comprehensive Antibiotic Resistance Database and Virulence Factor Database VFanalyzer. RESULTS: All three isolates were identified as A. hydrophila based on ANI and multilocus sequence typing analysis revealed that A. hydrophila belonged to a novel sequence type (ST1172). All three isolates were susceptible to amikacin and levofloxacin; however, they were resistant to piperacillin/tazobactam, ceftriaxone, cefuroxime, cefoxitin, and imipenem. Isolate 19W05620 (patient 3) showed increased ceftazidime resistance (minimum inhibitory concentration ≥ 64 µg/mL). All three isolates possessed the same chromosomally encoded ß-lactamases, including blaOXA-724 (ß-lactamase), imiH (metallo-ß-lactamase), and blaMOX-13 (AmpC) in plasmids. CONCLUSIONS: Our study validated the transmission of a novel carbapenem-resistant A. hydrophila sequence type (ST1172) in patients that underwent spine surgery. Control measures should be developed to prevent dissemination of A. hydrophila in the hospital setting.

Efficient removal of organic pollutants by activation of peroxydisulfate with the magnetic CoFe2O4/carbon nanotube composite.

A magnetic composite of CoFe2O4 and carbon nanotube (CNT) was prepared using the solvothermal approach and then employed for the activation of peroxydisulfate (PDS) to degrade reactive black 5 (RB5) and other organic pollutants. Characterization results of the composite catalyst revealed the successful loading of spherical CoFe2O4 particles on CNTs, possessing abundant porosity as well as magnetic separation capability. Under the degradation conditions of 0.2 g/L CoFe2O4-CNT dosage and 4 mM PDS dosage, the removal efficiencies of 10 mg/L RB5 and other pollutants were in the range of 94.5 to ~ 100%. The effects of pH, co-existing ions/humic acid, and water matrices as well as the reusability of the catalyst were also investigated in detail. Furthermore, the degradation mechanism and pathway were proposed based on quenching experiments, LC-MS analysis, and density functional theory (DFT) calculations, and the toxicity of the degradation products was evaluated in the quantitative structure-activity relationship approach.

Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy.

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

CD8 + T-cell marker genes reveal different immune subtypes of oral lichen planus by integrating single-cell RNA-seq and bulk RNA-sequencing.

BACKGROUND: Oral lichen planus (OLP) is a local autoimmune disease induced by T-cell dysfunction that frequently affects middle-aged or elderly people, with a higher prevalence in women. CD8 + T cells, also known as killer T cells, play an important role in the progression and persistence of OLP. In order to identify different OLP subtypes associated with CD8 + T cell pathogenesis, consensus clustering was used. METHODS: In this study, we preprocessed and downscaled the OLP single-cell dataset GSE211630 cohort downloaded from Gene Expression Omnibus (GEO) to finally obtain the marker genes of CD8 + T cells. Based on the expression of marker genes, we classified OLP patients into CMGs subtypes using unsupervised clustering analysis. The gene expression profiles were analyzed by WGCNA using the "WGCNA" R package based on the clinical disease traits and typing results, and 108 CD8 + T-cell related OLP pathogenicity-related genes were obtained from the intersection. Patients were once again classified into gene subtypes based on intersection gene expression using unsupervised clustering analysis. RESULTS: After obtaining the intersecting genes of CD8 + T cells related to pathogenesis, OLP patients can be precisely classified into two different subtypes based on unsupervised clustering analysis, and subtype B has better immune infiltration results, providing clinicians with a reference for personalized treatment. CONCLUSIONS: Classification of OLP into different subtypes improve our current understanding of the underlying pathogenesis of OLP and provides new insights for future studies.

Uncovering the potential role of oxidative stress in the development of periodontitis and establishing a stable diagnostic model via combining single-cell and machine learning analysis.

Background: The primary pathogenic cause of tooth loss in adults is periodontitis, although few reliable diagnostic methods are available in the early stages. One pathological factor that defines periodontitis pathology has previously been believed to be the equilibrium between inflammatory defense mechanisms and oxidative stress. Therefore, it is necessary to construct a model of oxidative stress-related periodontitis diagnostic markers through machine learning and bioinformatic analysis. Methods: We used LASSO, SVM-RFE, and Random Forest techniques to screen for periodontitis-related oxidative stress variables and construct a diagnostic model by logistic regression, followed by a biological approach to build a Protein-Protein interaction network (PPI) based on modelled genes while using modelled genes. Unsupervised clustering analysis was performed to screen for oxidative stress subtypes of periodontitis. we used WGCNA to explore the pathways correlated with oxidative stress in periodontitis patients. Networks. Finally, we used single-cell data to screen the cellular subpopulations with the highest correlation by scoring oxidative stress genes and performed a proposed temporal analysis of the subpopulations. Results: We discovered 3 periodontitis-associated genes (CASP3, IL-1ß, and TXN). A characteristic line graph based on these genes can be helpful for patients. The primary hub gene screened by the PPI was constructed, where immune-related and cellular metabolism-related pathways were significantly enriched. Consistent clustering analysis found two oxidative stress categories, with the C2 subtype showing higher immune cell infiltration and immune function ratings. Therefore, we hypothesized that the high expression of oxidative stress genes was correlated with the formation of the immune environment in patients with periodontitis. Using the WGCNA approach, we examined the co-expressed gene modules related to the various subtypes of oxidative stress. Finally, we selected monocytes for mimetic time series analysis and analyzed the expression changes of oxidative stress genes with the mimetic time series axis, in which the expression of JUN, TXN, and IL-1ß differed with the change of cell status. Conclusion: This study identifies a diagnostic model of 3-OSRGs from which patients can benefit and explores the importance of oxidative stress genes in building an immune environment in patients with periodontitis.

Metabolic orchestration of cell death by AMPK-mediated phosphorylation of RIPK1.

Adenosine monophosphate-activated protein kinase (AMPK) activity is stimulated to promote metabolic adaptation upon energy stress. However, sustained metabolic stress may cause cell death. The mechanisms by which AMPK dictates cell death are not fully understood. We report that metabolic stress promoted receptor-interacting protein kinase 1 (RIPK1) activation mediated by TRAIL receptors, whereas AMPK inhibited RIPK1 by phosphorylation at Ser415 to suppress energy stress-induced cell death. Inhibiting pS415-RIPK1 by Ampk deficiency or RIPK1 S415A mutation promoted RIPK1 activation. Furthermore, genetic inactivation of RIPK1 protected against ischemic injury in myeloid Ampkα1-deficient mice. Our studies reveal that AMPK phosphorylation of RIPK1 represents a crucial metabolic checkpoint, which dictates cell fate response to metabolic stress, and highlight a previously unappreciated role for the AMPK-RIPK1 axis in integrating metabolism, cell death, and inflammation.

T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing.

Background: Hepatocellular carcinoma (HCC), the third most prevalent cause of cancer-related death, is a frequent primary liver cancer with a high rate of morbidity and mortality. T-cell depletion (TEX) is a progressive decline in T-cell function due to continuous stimulation of the TCR in the presence of sustained antigen exposure. Numerous studies have shown that TEX plays an essential role in the antitumor immune process and is significantly associated with patient prognosis. Hence, it is important to gain insight into the potential role of T cell depletion in the tumor microenvironment. The purpose of this study was to develop a trustworthy TEX-based signature using single-cell RNA-seq (scRNA-seq) and high-throughput RNA sequencing, opening up new avenues for evaluating the prognosis and immunotherapeutic response of HCC patients. Methods: The International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases were used to download RNA-seq information for HCC patients. The 10x scRNA-seq. data of HCC were downloaded from GSE166635, and UMAP was used for clustering descending, and subgroup identification. TEX-related genes were identified by gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Afterward, we established a prognostic TEX signature using LASSO-Cox analysis. External validation was performed in the ICGC cohort. Immunotherapy response was assessed by the IMvigor210, GSE78220, GSE79671, and GSE91061cohorts. In addition, differences in mutational landscape and chemotherapy sensitivity between different risk groups were investigated. Finally, the differential expression of TEX genes was verified by qRT-PCR. Result: 11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis. Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC. The predictive efficacy of columnar maps created from clinical features and risk scores was strong. Conclusion: TEX signature and column line plots showed good predictive performance, providing a new perspective for assessing pre-immune efficacy, which will be useful for future precision immuno-oncology studies.

Circadian rhythm-related genes index: A predictor for HNSCC prognosis, immunotherapy efficacy, and chemosensitivity.

Background: Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer and is highly aggressive and heterogeneous, leading to variable prognosis and immunotherapy outcomes. Circadian rhythm alterations in tumourigenesis are of equal importance to genetic factors and several biologic clock genes are considered to be prognostic biomarkers for various cancers. The aim of this study was to establish reliable markers based on biologic clock genes, thus providing a new perspective for assessing immunotherapy response and prognosis in patients with HNSCC. Methods: We used 502 HNSCC samples and 44 normal samples from the TCGA-HNSCC dataset as the training set. 97 samples from GSE41613 were used as an external validation set. Prognostic characteristics of circadian rhythm-related genes (CRRGs) were established by Lasso, random forest and stepwise multifactorial Cox. Multivariate analysis revealed that CRRGs characteristics were independent predictors of HNSCC, with patients in the high-risk group having a worse prognosis than those in the low-risk group. The relevance of CRRGs to the immune microenvironment and immunotherapy was assessed by an integrated algorithm. Results: 6-CRRGs were considered to be strongly associated with HNSCC prognosis and a good predictor of HNSCC. The riskscore established by the 6-CRRG was found to be an independent prognostic factor for HNSCC in multifactorial analysis, with patients in the low-risk group having a higher overall survival (OS) than the high-risk group. Nomogram prediction maps constructed from clinical characteristics and riskscore had good prognostic power. Patients in the low-risk group had higher levels of immune infiltration and immune checkpoint expression and were more likely to benefit from immunotherapy. Conclusion: 6-CRRGs play a key predictive role for the prognosis of HNSCC patients and can guide physicians in selecting potential responders to prioritise immunotherapy, which could facilitate further research in precision immuno-oncology.

Machine learning to construct sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with uveal melanoma.

Background: Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults and is highly metastatic, resulting in a poor patient prognosis. Sphingolipid metabolism plays an important role in tumor development, diagnosis, and prognosis. This study aimed to establish a reliable signature based on sphingolipid metabolism genes (SMGs), thus providing a new perspective for assessing immunotherapy response and prognosis in patients with UVM. Methods: In this study, SMGs were used to classify UVM from the TCGA-UVM and GEO cohorts. Genes significantly associated with prognosis in UVM patients were screened using univariate cox regression analysis. The most significantly characterized genes were obtained by machine learning, and 4-SMGs prognosis signature was constructed by stepwise multifactorial cox. External validation was performed in the GSE84976 cohort. The level of immune infiltration of 4-SMGs in high- and low-risk patients was analyzed by platforms such as CIBERSORT. The prediction of 4-SMGs on immunotherapy and immune checkpoint blockade (ICB) response in UVM patients was assessed by ImmuCellAI and TIP portals. Results: 4-SMGs were considered to be strongly associated with the prognosis of UVM and were good predictors of UVM prognosis. Multivariate analysis found that the model was an independent predictor of UVM, with patients in the low-risk group having higher overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores had good prognostic power. The high-risk group showed better results when receiving immunotherapy. Conclusions: 4-SMGs signature and nomogram showed excellent predictive performance and provided a new perspective for assessing pre-immune efficacy, which will facilitate future precision immuno-oncology studies.

Efficient degradation of organic pollutants using peroxydisulfate activated by magnetic carbon nanotube.

The magnetic composite of Fe3O4 and carbon nanotube (MCNT) was fabricated in a facile one-pot solvothermal method and employed to activate peroxydisulfate (PDS) for degradation of Rhodamine B (RhB) and other pollutants. The effects of operational factors including MCNT dosage and PDS dosage were studied, and high removal efficiencies of 84.2-99.5% were achieved for these pollutants with 0.3 g/L MCNT and 4 mM PDS. The effects of environmental factors including initial pH, inorganic cations, inorganic anions, humic acid and water matrix were also studied. Reusability test showed that the removal efficiency declined in four consecutive runs, which was attributed to the adsorbed oxidation products on the catalyst surface. Based on quenching experiments, solvent exchange (H2O to D2O), inductively coupled plasma and open circuit potential tests, it was concluded that radicals of ·OH/SO4·- and the non-radical electron-transfer pathway were involved in the MCNT/PDS system, and the contributions of O2·-, 1O2, high-valent iron-oxo species and homogenous activation were insignificant. Moreover, the orbital-weighted Fukui functions of RhB were calculated by density functional theory, and its plausible degradation pathway was proposed based on the calculation results. Finally, toxicity evaluation of the degradation products was performed in the quantitative structure-activity relationship approach.

Identification and validation of neurotrophic factor-related genes signature in HNSCC to predict survival and immune landscapes.

Background: Head and neck squamous cell carcinoma (HNSCC) is the seventh most common type of cancer worldwide. Its highly aggressive and heterogeneous nature and complex tumor microenvironment result in variable prognosis and immunotherapeutic outcomes for patients with HNSCC. Neurotrophic factor-related genes (NFRGs) play an essential role in the development of malignancies but have rarely been studied in HNSCC. The aim of this study was to develop a reliable prognostic model based on NFRGs for assessing the prognosis and immunotherapy of HNSCC patients and to provide guidance for clinical diagnosis and treatment. Methods: Based on the TCGA-HNSC cohort in the Cancer Genome Atlas (TCGA) database, expression profiles of NFRGs were obtained from 502 HNSCC samples and 44 normal samples, and the expression and prognosis of 2601 NFRGs were analyzed. TGCA-HNSC samples were randomly divided into training and test sets (7:3). GEO database of 97 tumor samples was used as the external validation set. One-way Cox regression analysis and Lasso Cox regression analysis were used to screen for differentially expressed genes significantly associated with prognosis. Based on 18 NFRGs, lasso and multivariate Cox proportional risk regression were used to construct a prognostic risk scoring system. ssGSEA was applied to analyze the immune status of patients in high- and low-risk groups. Results: The 18 NFRGs were considered to be closely associated with HNSCC prognosis and were good predictors of HNSCC. The multifactorial analysis found that the NFRGs signature was an independent prognostic factor for HNSCC, and patients in the low-risk group had higher overall survival (OS) than those in the high-risk group. The nomogram prediction map constructed from clinical characteristics and risk scores had good prognostic power. Patients in the low-risk group had higher levels of immune infiltration and expression of immune checkpoints and were more likely to benefit from immunotherapy. Conclusion: The NFRGs risk score model can well predict the prognosis of HNSCC patients. A nomogram based on this model can help clinicians classify HNSCC patients prognostically and identify specific subgroups of patients who may have better outcomes with immunotherapy and chemotherapy, and carry out personalized treatment for HNSCC patients.

Modelling the octanol-air partition coefficient of aromatic pollutants based on the solvation free energy and the dimer effect.

In this study, generalized predictive models were developed to estimate KOA of four kinds of aromatic pollutants based on the calculated solvation free energy and taking the dimer effect into account. Uncorrected log KOA values, which were directly estimated from the calculated solvation free energy of individual molecules, underestimated experimental values, and the deviation increased with increasing log KOA. Dimers were found to greatly affect the apparent KOA values of these aromatic pollutants, which were driven by π-π interactions. London dispersion and exchange-repulsion terms were identified to be dominant components of the underlying π-π interactions. It is interesting to find that the π-π interactions of polybrominated diphenyl ethers correlate with not only the molecular polarizability but also the size of opposing aromatic surfaces, which leads to a different trend of π-π interactions from other aromatic pollutants. A universal quantitative structure-activity relationship model was developed to estimate the proportion of dimers based on five molecular structural descriptors relevant to the π-π interactions. After calibration with the dimer effect, estimations of log KOA were consistent with experimental values. Therefore, the dimer effect should be taken into consideration when investigating the partition behavior of aromatic pollutants, and the solvation free energy model could be an alternative method for the prediction of KOA.

Efficient degradation of organic dyes using peroxymonosulfate activated by magnetic graphene oxide.

Magnetic graphene oxide (MGO) was prepared and used as a catalyst to activate peroxymonosulfate (PMS) for degradation of Coomassie brilliant blue G250 (CBB). The effects of operation conditions including MGO dosage, PMS dosage and initial concentration of CBB were studied. CBB removal could reach 99.5% under optimum conditions, and high removals of 98.4-99.9% were also achieved for other organic dyes with varied structures, verifying the high efficiency and wide applicability of the MGO/PMS catalytic system. The effects of environmental factors including solution pH, inorganic ions and water matrices were also investigated. Reusability test showed that CBB removals maintained above 90% in five consecutive runs, indicating the acceptable recyclability of MGO. Based on quenching experiments, solvent exchange (H2O to D2O) and in situ open circuit potential (OCP) test, it was found that ˙OH, SO4˙- and high-valent iron species were responsible for the efficient degradation of CBB in the MGO/PMS system, while the contributions of O2˙-, 1O2 and the non-radical electron-transfer pathway were limited. Furthermore, the plausible degradation pathway of CBB was proposed based on density functional theory (DFT) calculations and liquid chromatography-mass spectrometry (LC-MS) results, and toxicity variation in the degradation process was evaluated by computerized structure-activity relationships (SARs) using green algae, daphnia, and fish as indicator species.

Single-Molecule Force Spectroscopy Reveals Stability of mitoNEET and its [2Fe2Se] Cluster in Weakly Acidic and Basic Solutions.

The outer mitochondrial membrane protein mitoNEET (mNT) is a recently identified iron-sulfur protein containing a unique Fe2 S2 (His)1 (Cys)3 metal cluster with a single Fe-N(His87) coordinating bond. This labile Fe-N bond led to multiple unfolding/rupture pathways of mNT and its cluster by atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS), one of most common tools for characterizing the molecular mechanics. Although previous ensemble studies showed that this labile Fe-N(His) bond is essential for protein function, they also indicated that the protein and its [2Fe2S] cluster are stable under acidic conditions. Thus, we applied AFM-SMFS to measure the stability of mNT and its cluster at pH values of 6, 7, and 8. Indeed, all previous multiple unfolding pathways of mNT were still observed. Moreover, single-molecule measurements revealed that the stabilities of the protein and the [2Fe2S] cluster are consistent at these pH values with only ≈20 pN force differences. Thus, we found that the behavior of the protein is consistent in both weakly acidic and basic solutions despite a labile Fe-N bond.

The neuroprotective effects and transdifferentiation of astrocytes into dopaminergic neurons of Ginkgolide K on Parkinson' disease mice.

Parkinson's disease (PD) is a chronic and progressive movement disorder caused by the selective loss of midbrain dopaminergic neurons of unknown etiology. Up to now, although there is a great development on treatments of PD, cures with neuroprotective or nerve regenerative effects are underway for PD patients. Here we reported neuroprotective effects of Ginkgolide K (GK) when mice were upon acute MPTP exposure, in which GK ameliorated the gait dysfunction and dopaminergic neuron loss. GK exhibits its ability in immunomodulation, including switching microglia to M2 phenotype and decreasing the microglia-mediated inflammation, inhibiting peripheral CD4+IFN-γ+ and CD4+IL-17+ T cells and α-synuclein specific autoantibodies. The expression of neurotrophic factors BDNF, GDNF and NT-3 was promoted with a treatment of GK in MPTP mice brains. Notably, GK enhanced the expression of nestin in GFAP+ astrocytes followed by the transdifferentiation of astrocyte-to-neuron independent on the Wnt signaling although GK induced the expression of Wnt signaling on astrocytes. Based on these results, our work implicates a therapeutic potential of GK for protecting TH+ neurons by multiple and intercellular pathways to modify nerve regeneration in MPTP mice. However, its exactly cellular and molecular mechanisms need to be further explored and confirmed.

Comparative evaluation of Sensititre YeastOne and VITEK 2 against the Clinical and Laboratory Standards Institute M27-E4 reference broth microdilution method for the antifungal susceptibility testing of Cryptococcus neoformans and Cryptococcus gattii.

The present study collected 280 isolates of Cryptococcus neoformans and 22 isolates of Cryptococcus gattii and evaluated the consistencies between Sensititre YeastOne (SYO), VITEK 2, and the reference broth microdilution (BMD) method for the antifungal susceptibility testing of fluconazole, voriconazole, and flucytosine. For amphotericin B, SYO was replaced with the BIO KONT amphotericin B microbroth dilution kit. The essential agreements (EAs) by SYO and VITEK 2 for C. neoformans var. grubii and C. neoformans var. neoformans were 98.15-99.63% and 88.89-100%, respectively, with fluconazole, voriconazole, and flucytosine. The EA for C. gattii VG â…  against fluconazole was 29.41% by VITEK 2, while the other EAs for C. gattii strains were 100% by SYO and VITEK 2. The categorical agreements (CAs) by SYO and VITEK 2 for C. neoformans and C. gattii were 94.12-100%, while VITEK 2 failed to distinguish 5/6 fluconazole-resistant non-wild-type C. neoformans var. grubii isolates; this finding confirmed the limitation of testing fluconazole against C. neoformans as documented in the manufacturer's package insert. The EAs for amphotericin B were 97.42-100% for C. neoformans and C. gattii, but the CAs were 17.65-60% by BIO KONT and VITEK 2. Thus, SYO can be used for susceptibility testing of C. neoformans and C. gattii against fluconazole, voriconazole, and flucytosine, and VITEK 2 can be used for susceptibility testing of C. neoformans against voriconazole and flucytosine. Further studies using amphotericin B-resistant isolates are required to assess the agreement between VITEK 2, BIO KONT, and BMD. LAY SUMMARY: Sensititre YeastOne showed a good agreement with the CLSI broth microdilution method for C. neoformans and C. gattii against voriconazole and flucytosine. The limitation regarding fluconazole testing against C. neoformans documented in VITEK 2 manufacturer's package insert was confirmed.

Magnetic graphene oxide for methylene blue removal: adsorption performance and comparison of regeneration methods.

A series of Fe3O4-graphene oxide (GO) composite materials (MGOs) with abundant surface area, rich oxygen-containing functional groups, and magnetic properties were prepared in a facile coprecipitation method and then employed for the adsorptive removal of methylene blue (MB) from water. The kinetic data were better fitted in the pseudo-second-order model than in the pseudo-first-order model, and the intraparticle diffusion model revealed the two-step diffusion process including diffusion in the boundary layer and in the porous structures. The maximum adsorption amounts of MB were calculated to be 37.5-108 mg/g at 25 °C and pH 9 using the Langmuir isotherm model. Thermodynamic study showed that the adsorption process was spontaneous, with ΔH° of 23.0-49.6 kJ/mol and ΔS° of 131-249 J∙mol-1∙K-1. The adsorption amount of MB increased with pH in the range of 4-10. Inorganic ions including Na+ and Ca2+ suppressed the adsorption of MB, and the more pronounced impact of Ca2+ was ascribed to its higher valence state. The cetyltrimethylammonium bromide (CTAB) surfactant showed a stronger inhibitory effect than Ca2+. The adsorption mechanism was proposed to be a combination of electrostatic interactions, hydrophobic adsorption, and electron donor-acceptor interactions. Two methods were used for the regeneration of spent MGO, and the results showed that the peroxomonosulfate (PMS) oxidation method was more favorable than the acid washing method, considering the better regeneration ability and lower amount of washing water used. Finally, the reaction mechanism of PMS oxidation was analyzed based on quenching tests and in situ open circuit potential measurements, which proved that OH and 1O2 played dominant roles and that the fine adsorption ability of MGO promoted the reaction between them and MB.

Mdivi-1 Modulates Macrophage/Microglial Polarization in Mice with EAE via the Inhibition of the TLR2/4-GSK3ß-NF-κB Inflammatory Signaling Axis.

Macrophage/microglial modulation plays a critical role in the pathogenesis of multiple sclerosis (MS), which is an inflammatory disorder of the central nervous system. Dynamin-related protein 1 is a cytoplasmic molecule that regulates mitochondrial fission. It has been proven that mitochondrial fission inhibitor 1 (Mdivi-1), a small molecule inhibitor of Drp1, can relieve experimental autoimmune encephalomyelitis (EAE), a preclinical animal model of MS. Whether macrophages/microglia are involved in the pathological process of Mdivi-1-treated EAE remains to be determined. Here, we studied the anti-inflammatory effect of Mdivi-1 on mice with oligodendrocyte glycoprotein peptide35-55 (MOG35-55)-induced EAE. We found that Drp1 phosphorylation at serine 616 in macrophages/microglia was decreased with Mdivi-1 treatment, which was accompanied by decreased antigen presentation capacity of the macrophages/microglia in the EAE mouse spinal cord. The Mdivi-1 treatment caused macrophage/microglia to produce low levels of proinflammatory molecules, such as CD16/32, iNOS, and TNF-α, and high levels of anti-inflammatory molecules, such as CD206, IL-10, and Arginase-1, suggesting that Mdivi-1 promoted the macrophage/microglia shift from the inflammatory M1 phenotype to the anti-inflammatory M2 phenotype. Moreover, Mdivi-1 was able to downregulate the expression of TRL2, TRL4, GSK-3ß, and phosphorylated NF-κB-p65 and prevent NF-κB-mediated IL-1ß and IL-6 production. In conclusion, these results indicate that Mdivi-1 significantly alleviates inflammation in mice with EAE by promoting M2 polarization by inhibiting TLR2/4- and GSK3ß-mediated NF-κB activation.

A Rapid Antimicrobial Susceptibility Test for Klebsiella pneumoniae Using a Broth Micro-Dilution Combined with MALDI TOF MS.

BACKGROUND: Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a novel method that can be used to identify pathogens and has potential applications in the detection of drug-resistant bacteria. PURPOSE: To evaluate the ability of a MALDI-TOF MS-based broth micro-dilution method in detecting the minimum inhibitory concentration (MIC) values of Klebsiella pneumoniae to ceftriaxone and imipenem. MATERIALS AND METHODS: Sixty strains of K. pneumoniae with different levels of resistance to carbapenems and cephalosporins were randomly collected. The 0.5 McFarland (Mc) concentration of the bacterial suspension was inoculated in cation-adjusted Mueller-Hinton broth (CAMHB) with a final cell turbidity of 5×105 CFU/mL. The broth was incubated with serial concentrations of antibiotics. After centrifuging the bacterial suspensions, the lysed cells were analyzed by MALDI-TOF MS to identify the growth-promoting or inhibitory effects on K. pneumoniae. The molecular mechanisms of resistance were investigated by PCR and DNA sequencing analysis. RESULTS: The expression of known resistance genes (blaKPC, blaFOX, blaDHA, blaCTX-M and blaTEM) was detected in the 30 carbapenems-resistant strains. The agreement between the MIC values derived from the MALDI-TOF MS analysis and from the broth micro-dilution method was 61.7% for ceftriaxone and 71.7% for imipenem. According to the Clinical and Laboratory Standards Institute (CLSI) breakpoint of resistance to ceftriaxone and imipenem, the 60 isolates were accurately classified as resistant or susceptible isolates with 100% sensitivity and 100% specificity. CONCLUSION: The transmission and infection of multidrug-resistant bacteria could be better managed and treated with the rapid identification of strains and antimicrobial susceptibility. A MALDI-TOF MS-based susceptibility test could be used to identify resistance of K. pneumoniae within a short time-frame. This approach could potentially be used as a supplementary antimicrobial susceptibility test that could be investigated on more bacterial species combined with different antibiotics.