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  • Frontiers Media SA  (45)
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  • Frontiers Media SA  (45)
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  • 1
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Microbiology Vol. 13 ( 2022-11-16)
    In: Frontiers in Microbiology, Frontiers Media SA, Vol. 13 ( 2022-11-16)
    Abstract: Allicin, which is generated by the catalytic reaction between alliin and alliinase extracted from garlic, has been shown to have a wide range of antimicrobial activities, but its anti- Cryptococcus efficacy and mechanism are not quite clear. Here, we have determined that the Conversion rate of allicin in the reaction product reached 97.5%. The minimal inhibitory concentration (MIC) of allicin against Cryptococcus neoformans (C. neoformans) H99 was 2 μg/ml, which is comparable to fluconazole (FLU, 1 μg/ml). Furthermore, allicin exhibited effective antifungal activity against 46 clinical isolates of C. neoformans , and the MICs ranged from 1 to 8 μg/ml, even for AmB-insensitive strains. Interestingly, allicin also exerted additive or synergistic effects when combined with amphotericin B (AmB) and FLU. Time-killing curves and long-term live cell imaging of H99 showed that 4 MIC of allicin had fungicide activity. Additionally, allicin (4 and 8 mg/kg) exerted a dose-dependent therapeutic effect on H99-infected mice by significantly reducing the wet pulmonary coefficient and Cryptococcus load and reducing lung damage. Even the efficacy of 8 mg/kg was comparable to FLU (20 mg/kg). Transcriptomics revealed that allicin may act on the cell membrane of H99. Subsequently, transmission electron microscopy (TEM) observations showed that allicin clearly breached the cell membrane and organelles of H99. Confocal laser scanning microscopy (CLSM) results further confirmed that allicin disrupted the permeability of the cell membranes of H99 in a dose-dependent manner. Allicin exhibits strong anti- C. neoformans activity in vitro and in vivo , mainly by destroying the permeability and related functions of Cryptococcus cell membranes.
    Type of Medium: Online Resource
    ISSN: 1664-302X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2587354-4
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  • 2
    In: Frontiers in Cellular and Infection Microbiology, Frontiers Media SA, Vol. 11 ( 2021-6-28)
    Abstract: Increasing attention has been directed to Talaromyces marneffei ( T. marneffei ) infection in HIV-negative patients due to its high mortality rate. However, nonspecific symptoms and biological characteristics similar to those of other common pathogenic fungi complicate the rapid and accurate diagnosis of T. marneffei infection. Sphingolipids (SPLs) are bioactive lipids involved in the regulation of various physiological and pathological processes and have been identified as serum biomarkers for several diseases. This study employed a sphingolipidomic approach established in our previous work to explore the use of serum SPLs in the diagnosis of HIV-negative patients with T. marneffei infection. Additional clinical cohorts of patients infected with other microorganisms were also recruited. We found that sphinganine (Sa) (d16:0) exhibited obvious depletion after infection; moreover, its level in patients with T. marneffei infection was significantly lower than that in patients infected with other microorganisms. Therefore, Sa (d16:0) was considered a specific diagnostic biomarker for T. marneffei infection, and 302.71 nM was selected as the optimal cutoff value with a diagnostic sensitivity of 87.5% and specificity of 100%. These results suggested that determination of serum Sa (d16:0) levels can be used as a new alternative tool for the rapid diagnosis of T. marneffei infection in HIV-negative patients.
    Type of Medium: Online Resource
    ISSN: 2235-2988
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2619676-1
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  • 3
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Endocrinology Vol. 13 ( 2022-6-15)
    In: Frontiers in Endocrinology, Frontiers Media SA, Vol. 13 ( 2022-6-15)
    Abstract: Endometriosis (EMS), an endocrine-related inflammatory disease, is characterized by estrogen and progesterone imbalance in ectopic lesions. However, its pathogenic mechanism has not been fully elucidated. While SCM-198 is the synthetic form of leonurine and has multiple pharmacological activities such as antioxidation and anti-inflammation, it remains unknown whether it could inhibit the progress of EMS by regulating estrogen signaling and inflammation. Methods The therapeutic effects of SCM-198 on EMS and its potential mechanism were analyzed by establishing EMS mouse models and performing an RNA sequencing (RNA-seq) assay. ELISA was performed to detect estrogen and tumor necrosis factor (TNF) -α concentrations in normal endometrial stromal cells (nESCs) and ectopic endometrial stromal cells (eESCs) with or without SCM-198 treatment. Western blotting, RNA silencing, and plasmid overexpression were used to analyze the relationship between inflammation, endocrine factors, and autophagy and the regulatory activity of SCM-198 on the inflammation-endocrine-autophagy axis. Results Increased estrogen-estrogen receptor (ER) α signaling and decreased progesterone receptor isoform B (PRB) expression synergistically led to a hypo-autophagy state in eESCs, which further inhibited the apoptosis of eESCs. The high expression of TNF-α in eESCs enhanced the antiapoptotic effect mediated by low autophagy through the activation of the aromatase-estrogen-ERα signaling pathway. SCM-198 inhibited the growth of ectopic lesions in EMS mice and promoted the apoptosis of eESCs both in vivo and in vitro. The apoptotic effect of SCM-198 on eESCs was attained by upregulating the autophagy level via the inhibition of the TNF-α-activated aromatase-estrogen-ERα signal and the increase in PRB expression. Conclusion Inflammation facilitated the progress of EMS by disrupting the estrogen regulatory axis. SCM-198 inhibited EMS progression by regulating the inflammation-endocrine-autophagy axis.
    Type of Medium: Online Resource
    ISSN: 1664-2392
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2592084-4
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  • 4
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Chemistry Vol. 10 ( 2022-7-1)
    In: Frontiers in Chemistry, Frontiers Media SA, Vol. 10 ( 2022-7-1)
    Abstract: Florfenicol was widely used as antibiotic in the livestock and poultry breeding industry, resulting in a serious problem of drug resistance. In order to solve the resistance of florfenicol, this study designed and synthesized a new series of florfenicol-polyarginine conjugates and tested for antimicrobial activities. Drug-sensitive bacteria, gram-negative bacteria Escherichia coli ( E. coli ) and gram-positive Staphylococcus aureus ( S. aureus ), were sensitive to several of the compounds tested. These conjugates also showed excellent activity against drug-resistant strains such as methicillin-resistant S. aureus (MRSA) and florfenicol resistant Escherichia coli strains (2017XJ30, 2019XJ20), one of which as E6 had a minimum inhibitory concentration of 12.5 μmol/L. These conjugates did not allow bacteria to develop resistance and also decreased bacterial growth by membrane depolarization and disruption. Additionally, florfenicol succinate (C1) showed certain activity after coupling with arginine. This suggested that conjugating arginine to florfenicol succinate effectively modulated the properties of prodrugs. These new conjugates may provide useful insights for expanding the pool of antibiotics.
    Type of Medium: Online Resource
    ISSN: 2296-2646
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2711776-5
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  • 5
    In: Frontiers in Bioengineering and Biotechnology, Frontiers Media SA, Vol. 10 ( 2022-3-21)
    Abstract: The prediction of protein–protein interactions (PPIs) in plants is vital for probing the cell function. Although multiple high-throughput approaches in the biological domain have been developed to identify PPIs, with the increasing complexity of PPI network, these methods fall into laborious and time-consuming situations. Thus, it is essential to develop an effective and feasible computational method for the prediction of PPIs in plants. In this study, we present a network embedding-based method, called DWPPI, for predicting the interactions between different plant proteins based on multi-source information and combined with deep neural networks (DNN). The DWPPI model fuses the protein natural language sequence information (attribute information) and protein behavior information to represent plant proteins as feature vectors and finally sends these features to a deep learning–based classifier for prediction. To validate the prediction performance of DWPPI, we performed it on three model plant datasets: Arabidopsis thaliana ( A. thaliana ), mazie ( Zea mays ), and rice ( Oryza sativa ). The experimental results with the fivefold cross-validation technique demonstrated that DWPPI obtains great performance with the AUC (area under ROC curves) values of 0.9548, 0.9867, and 0.9213, respectively. To further verify the predictive capacity of DWPPI, we compared it with some different state-of-the-art machine learning classifiers. Moreover, case studies were performed with the AC149810.2_FGP003 protein. As a result, 14 of the top 20 PPI pairs identified by DWPPI with the highest scores were confirmed by the literature. These excellent results suggest that the DWPPI model can act as a promising tool for related plant molecular biology.
    Type of Medium: Online Resource
    ISSN: 2296-4185
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2719493-0
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  • 6
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 13 ( 2022-8-16)
    Abstract: Emerging evidence has revealed that circular RNA (circRNA) is widely distributed in mammalian cells and functions as microRNA (miRNA) sponges involved in transcriptional and posttranscriptional regulation of gene expression. Recognizing the circRNA–miRNA interaction provides a new perspective for the detection and treatment of human complex diseases. Compared with the traditional biological experimental methods used to predict the association of molecules, which are limited to the small-scale and are time-consuming and laborious, computing models can provide a basis for biological experiments at low cost. Considering that the proposed calculation model is limited, it is necessary to develop an effective computational method to predict the circRNA–miRNA interaction. This study thus proposed a novel computing method, named KGDCMI, to predict the interactions between circRNA and miRNA based on multi-source information extraction and fusion. The KGDCMI obtains RNA attribute information from sequence and similarity, capturing the behavior information in RNA association through a graph-embedding algorithm. Then, the obtained feature vector is extracted further by principal component analysis and sent to the deep neural network for information fusion and prediction. At last, KGDCMI obtains the prediction accuracy (area under the curve [AUC] = 89.30% and area under the precision–recall curve [AUPR] = 87.67%). Meanwhile, with the same dataset, KGDCMI is 2.37% and 3.08%, respectively, higher than the only existing model, and we conducted three groups of comparative experiments, obtaining the best classification strategy, feature extraction parameters, and dimensions. In addition, in the performed case study, 7 of the top 10 interaction pairs were confirmed in PubMed. These results suggest that KGDCMI is a feasible and useful method to predict the circRNA–miRNA interaction and can act as a reliable candidate for related RNA biological experiments.
    Type of Medium: Online Resource
    ISSN: 1664-8021
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2606823-0
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  • 7
    Online Resource
    Online Resource
    Frontiers Media SA ; 2021
    In:  Frontiers in Pharmacology Vol. 12 ( 2021-8-26)
    In: Frontiers in Pharmacology, Frontiers Media SA, Vol. 12 ( 2021-8-26)
    Abstract: Pulmonary fibrosis is a known sequela of severe or persistent lung damage. Existing clinical, imaging and autopsy studies have shown that the lungs exhibit a pathological pulmonary fibrosis phenotype after infection with coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pulmonary fibrosis may be one of the most serious sequelae associated with coronavirus disease 2019 (COVID-19). In this study, we aimed to examine the preventative effects of the antiviral drug remdesivir on pulmonary fibrosis. We used a mouse model of bleomycin-induced pulmonary fibrosis to evaluate the effects of remdesivir on pulmonary fibrosis in vivo and further explored the potential pharmacological mechanisms of remdesivir in lung fibroblasts and alveolar epithelial cells in vitro . The preventive remdesivir treatment was started on the day of bleomycin installation, and the results showed that remdesivir significantly alleviated bleomycin-induced collagen deposition and improved pulmonary function. In vitro experiments showed that remdesivir dose-dependently suppressed TGF-β1-induced lung fibroblast activation and improved TGF-β1-induced alveolar epithelial to mesenchymal transition. Our results indicate that remdesivir can preventatively alleviate the severity of pulmonary fibrosis and provide some reference for the prevention of pulmonary fibrosis in patients with COVID-19.
    Type of Medium: Online Resource
    ISSN: 1663-9812
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2587355-6
    SSG: 15,3
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  • 8
    Online Resource
    Online Resource
    Frontiers Media SA ; 2020
    In:  Frontiers in Genetics Vol. 11 ( 2020-8-4)
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 11 ( 2020-8-4)
    Type of Medium: Online Resource
    ISSN: 1664-8021
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2020
    detail.hit.zdb_id: 2606823-0
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  • 9
    Online Resource
    Online Resource
    Frontiers Media SA ; 2021
    In:  Frontiers in Molecular Neuroscience Vol. 14 ( 2021-11-1)
    In: Frontiers in Molecular Neuroscience, Frontiers Media SA, Vol. 14 ( 2021-11-1)
    Abstract: This research aimed to investigate the role of glyoxalase 1 (Glo-1) polymorphisms in the susceptibility of schizophrenia. Using the real-time polymerase chain reaction (PCR) and spectrophotometric assays technology, significant differences in Glo-1 messenger ribonucleic acid (mRNA) expression ( P = 3.98 × 10 −5 ) and enzymatic activity ( P = 1.40 × 10 −6 ) were found in peripheral blood of first-onset antipsychotic-naïve patients with schizophrenia and controls. The following receiver operating characteristic (ROC) curves analysis showed that Glo-1 could predict the schizophrenia risk ( P = 4.75 × 10 −6 in mRNA, P = 1.43 × 10 −7 in enzymatic activity, respectively). To identify the genetic source of Glo-1 risk in schizophrenia, Glo-1 polymorphisms (rs1781735, rs1130534, rs4746, and rs9470916) were genotyped with SNaPshot technology in 1,069 patients with schizophrenia and 1,023 healthy individuals. Then, the impact of risk polymorphism on the promoter activity, mRNA expression, and enzymatic activity was analyzed. The results revealed significant differences in the distributions of genotype ( P = 0.020, false discovery rate (FDR) correction) and allele ( P = 0.020, FDR correction) in rs1781735, in which G & gt; T mutation significantly showed reduction in the promoter activity ( P = 0.016), mRNA expression, and enzymatic activity (P = 0.001 and P = 0.015, respectively, GG vs. TT, in peripheral blood of patients with schizophrenia) of Glo-1. The expression quantitative trait locus (eQTL) findings were followed up with the resting-state functional magnetic resonance imaging (fMRI) analysis. The TT genotype of rs1781735, associated with lower RNA expression in the brain ( P & lt; 0.05), showed decreased neuronal activation in the left middle frontal gyrus in schizophrenia ( P & lt; 0.001). In aggregate, this study for the first time demonstrates how the genetic and biochemical basis of Glo-1 polymorphism culminates in the brain function changes associated with increased schizophrenia risk. Thus, establishing a combination of multiple levels of changes ranging from genetic variants, transcription, protein function, and brain function changes is a better predictor of schizophrenia risk.
    Type of Medium: Online Resource
    ISSN: 1662-5099
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2452967-9
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  • 10
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 12 ( 2022-7-29)
    Abstract: To explore the value of PET/MRI, including diffusion kurtosis imaging (DKI), diffusion weighted imaging (DWI) and positron emission tomography (PET), for distinguishing between benign and malignant solitary pulmonary lesions (SPLs) and predicting the histopathological grading of malignant SPLs. Material and methods Chest PET, DKI and DWI scans of 73 patients with SPL were performed by PET/MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), maximum standard uptake value (SUV max ), metabolic total volume (MTV) and total lesion glycolysis (TLG) were calculated. Student’s t test or the Mann–Whitney U test was used to analyze the differences in parameters between groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy. Logistic regression analysis was used to evaluate independent predictors. Results The MK and SUV max were significantly higher, and the MD and ADC were significantly lower in the malignant group (0.59 ± 0.13, 10.25 ± 4.20, 2.27 ± 0.51[×10 -3 mm 2 /s] and 1.35 ± 0.33 [×10 -3 mm 2 /s]) compared to the benign group (0.47 ± 0.08, 5.49 ± 4.05, 2.85 ± 0.60 [×10 -3 mm 2 /s] and 1.67 ± 0.33 [×10 -3 mm 2 /s]). The MD and ADC were significantly lower, and the MTV and TLG were significantly higher in the high-grade malignant SPLs group (2.11 ± 0.51 [×10 -3 mm 2 /s], 1.35 ± 0.33 [×10 -3 mm 2 /s], 35.87 ± 42.24 and 119.58 ± 163.65) than in the non-high-grade malignant SPLs group (2.46 ± 0.46 [×10 -3 mm 2 /s], 1.67 ± 0.33[×10 -3 mm 2 /s], 20.17 ± 32.34 and 114.20 ± 178.68). In the identification of benign and malignant SPLs, the SUV max and MK were independent predictors, the AUCs of the combination of SUV max and MK, SUV max , MK, MD, and ADC were 0.875, 0.787, 0.848, 0.769, and 0.822, respectively. In the identification of high-grade and non-high-grade malignant SPLs, the AUCs of MD, ADC, MTV, and TLG were 0.729, 0.680, 0.693, and 0.711, respectively. Conclusion DWI, DKI, and PET in PET/MRI are all effective methods to distinguish benign from malignant SPLs, and are also helpful in evaluating the pathological grading of malignant SPLs.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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