FOSL1-mediated LINC01566 negatively regulates CD4+ T-cell activation in myasthenia gravis.

BACKGROUND: Myasthenia gravis (MG) is an autoimmune disease characterized by pathogenic antibodies that target structures of the neuromuscular junction. The evidence suggests that the regulation of long noncoding RNAs (lncRNAs) that is mediated by transcription factors (TFs) plays a key role in the pathophysiology of MG. Nevertheless, the detailed molecular mechanisms of lncRNAs in MG remain largely undetermined. METHODS: Using microarray analysis, we analyzed the lncRNA levels in MG. By bioinformatics analysis, LINC01566 was found to potentially play an important role in MG. First, qRT‒PCR was performed to verify the LINC1566 expressions in MG patients. Then, fluorescence in situ hybridization was conducted to determine the localization of LINC01566 in CD4 + T cells. Finally, the impact of LINC01566 knockdown or overexpression on CD4 + T-cell function was also analyzed using flow cytometry and CCK-8 assay. A dual-luciferase reporter assay was used to validate the binding of the TF FOSL1 to the LINC01566 promoter. RESULTS: Based on the lncRNA microarray and differential expression analyses, we identified 563 differentially expressed (DE) lncRNAs, 450 DE mRNAs and 19 DE TFs in MG. We then constructed a lncRNA-TF-mRNA network. Through network analysis, we found that LINC01566 may play a crucial role in MG by regulating T-cell-related pathways. Further experiments indicated that LINC01566 is expressed at low levels in MG patients. Functionally, LINC01566 is primarily distributed in the nucleus and can facilitate CD4 + T-cell apoptosis and inhibit cell proliferation. Mechanistically, we hypothesized that LINC01566 may negatively regulate the expressions of DUSP3, CCR2, FADD, SIRPB1, LGALS3 and SIRPB1, which are involved in the T-cell activation pathway, to further influence the cellular proliferation and apoptosis in MG. Moreover, we found that the effect of LINC01566 on CD4 + T cells in MG was mediated by the TF FOSL1, and in vitro experiments indicated that FOSL1 can bind to the promoter region of LINC01566. CONCLUSIONS: In summary, our research revealed the protective roles of LINC01566 in clinical samples and cellular experiments, illustrating the potential roles and mechanism by which FOSL1/LINC01566 negatively regulates CD4 + T-cell activation in MG.

Generation of secondary microbial methane of high-rank coals: insights from the microbial community and carbon isotope.

Secondary microbial methane could provide a valuable energy source if it were better understood. Although coal seam is an ideal environment for investigating secondary microbial methane, there are few studies to trace the secondary microbial methane of high-rank coals. Here, we collected co-produced water samples from coalbeds in the Qinshui Basin (China) and analyzed the microbial community structure by 16S ribosomal RNA (16S rRNA) amplicon sequencing analysis. 16S rRNA sequencing demonstrated abundant methanogens in coalbeds including 6 orders (Methanobacteriales, Methanococcales, Methanofastidiosales, Methanomassiliicoccale, Methanomicrobiales, and Methanosarciniales) and 22 genera of methanogens. Superheavy DIC (δ13CDIC ranging from -4.2‰ to 34.8‰) and abundance of methanogenic microbes in co-produced water revealed the generation of secondary biogenic methane in high-rank coal seams in the Qingshui Basin. Hydrogenotrophic methanogenesis is the main pathway for secondary biogenic methane production. In deeply buried coal seams, biogenic methane is dominated by CO2 and H2 reduction methanogenesis, and in shallow buried coal seams, it may be produced synergistically by hydrocarbon degradation and hydrogenotrophic methanogenic microbes. The study discussed here is important for a better understanding of the generation of secondary microbial methane in high-rank coal.

A Novel Data Fusion Strategy of GC-MS and 1H NMR Spectra for the Identification of Different Vintages of Maotai-flavor Baijiu.

Counterfeit Baijiu has been emerging because of the price variances of real-aged Chinese Baijiu. Accurate identification of different vintages is of great interest. In this study, the combination of gas chromatography-mass spectrometry (GC-MS) and proton nuclear magnetic resonance (1H NMR) spectroscopy was applied for the comprehensive analysis of chemical constituents for Maotai-flavor Baijiu. Furthermore, a novel data fusion strategy combined with machine learning algorithms has been established. The results showed that the midlevel data fusion combined with the random forest algorithm were the best and successfully applied for classification of different Baijiu vintages. A total of 14 differential compounds (belonging to fatty acid ethyl esters, alcohols, organic acids, and aldehydes) were identified, and used for evaluation of commercial Maotai-flavor Baijiu. Our results indicated that both volatiles and nonvolatiles contributed to the vintage differences. This study demonstrated that GC-MS and 1H NMR spectra combined with a data fusion strategy are practical for the classification of different vintages of Maotai-flavor Baijiu.

The role of FERMT2 in the tumor microenvironment and immunotherapy in pan-cancer using comprehensive single-cell and bulk sequencing.

FERMT2 has been identified as a participant in integrin-linked kinase signaling pathways, influencing epithelial-mesenchymal transition and thereby affecting tumor initiation, progression, and invasion. While the character of FERMT2 in the tumor microenvironment (TME) as well as its implications for immunotherapy remain unclear. Thus, we conducted a comprehensive analysis to assess the prognostic significance of FERMT2 using Kaplan-Meier analysis. In addition, we employed enrichment analysis to uncover potential underlying molecular mechanisms. Using "Immunedeconv" package, we evaluated the immune characteristics of FERMT2 within TME. Furthermore, we determined the expression levels of FERMT2 in various cell types within TME, based on single-cell sequencing data. To confirm the co-expression of FERMT2 and markers of cancer-associated fibroblasts (CAFs), we performed multiplex immunofluorescence staining on tissue paraffin sections across various cancer types. Our analysis disclosed a significant correlation between elevated FERMT2 expression and unfavorable prognosis in specific cancer types. Furthermore, we identified a strong correlation between FERMT2 expression and diverse immune-related factors, including immune checkpoint molecules, immune cell infiltration, microsatellite instability (MSI), and tumor mutational burden (TMB). Additionally, there was a significant correlation between FERMT2 expression and immune-related pathways, particularly those associated with activating, migrating, and promoting the growth of fibroblasts in diverse cancer types. Interestingly, we observed consistent co-expression of FERMT2 in both malignant tumor cells and stromal cells, particularly within CAFs. Notably, our findings also indicated that FERMT2, in particular, exhibited elevated expression levels within tumor tissues and co-expressed with α-SMA in CAFs based on the multiplex immunofluorescence staining results.

Acetylated KHSRP impairs DNA-damage-response-related mRNA decay and facilitates prostate cancer tumorigenesis.

Androgen-regulated DNA damage response (DDR) is one of the essential mechanisms in prostate cancer (PCa), a hormone-sensitive disease. The heterogeneous nuclear ribonucleoprotein K (hnRNPK)-homology splicing regulatory protein known as far upstream element-binding protein 2 (KHSRP) is an RNA-binding protein that can attach to AU-rich elements in the 3' untranslated region (3'-UTR) of messenger RNAs (mRNAs) to mediate mRNA decay and emerges as a critical regulator in the DDR to preserve genome integrity. Nevertheless, how KHSRP responds to androgen-regulated DDR in PCa development remains unclear. This study found that androgen can significantly induce acetylation of KHSRP, which intrinsically drives tumor growth in xenografted mice. Moreover, enhanced KHSRP acetylation upon androgen stimuli impedes KHSRP-regulated DDR gene expression, as seen by analyzing RNA sequencing (RNA-seq) and Gene Set Enrichment Analysis (GSEA) datasets. Additionally, NAD-dependent protein deacetylase sirtuin-7 (SIRT7) is a promising deacetylase of KHSRP, and androgen stimuli impairs its interaction with KHSRP to sustain the increased KHSRP acetylation level in PCa. We first report the acetylation of KHSRP induced by androgen, which interrupts the KHSRP-regulated mRNA decay of the DDR-related genes to promote the tumorigenesis of PCa. This study provides insight into KHSRP biology and potential therapeutic strategies for PCa treatment, particularly that of castration-resistant PCa.

Microbial contribution estimated by clumped isotopologues (13CH3D and 12CH2D2) characteristics in a CO2 enhanced coal bed methane reservoir.

Carbon capture and storage (CCS) of CO2 is a key technology for substantially mitigating global greenhouse gas emissions. Determining the biogeochemical processes in host rocks after CO2 injection informs the viability of carbon storage as a long-term sink for CO2, the complexity of reservoir CH4 cycling, as well as the direct and indirect environmental impacts of this strategy. The doubly substituted ('clumped') isotopologues of methane (13CH3D and 12CH2D2) provide novel insights into methane origins and post-generation processing. Here, we report the chemical compositions of hydrocarbons (C1/C2+ molecular ratios), and methane bulk and clumped isotopes (δ13C, δD, Δ13CH3D and Δ12CH2D2) of a CO2 enhanced coal bed methane recovery (CO2-ECBM) area in Qinshui basin, China and is an analogue for carbon capture and storage. The clumped isotopologue compositions observed in the study area are generally consistent with a range of temperatures spanning 73 to 193 °C. The range in apparent temperature and correlations among clumped and bulk isotopic indices are best explained by mixing between a high maturity thermogenic methane (high in δ13C and δD, with a clumped isotope composition equilibrated near ∼249 °C) and biogenic methane formed or processed in the reservoir (low in δ13C and δD, with a clumped isotope composition equilibrated near 16-27 °C). We hypothesize that the biogenic endmember may result from slow methanogenesis and/or anaerobic oxidation of methane (AOM). This study demonstrates that the potential of methane clumped isotope approach to identify in situ microbial metabolic processes and their association with carbon cycling in CO2-ECBM area, improving our understanding of biogeochemical mechanisms in analogous geological reservoirs.

LINC02454-CCT complex interaction is essential for telomerase activity and cell proliferation in head and neck squamous cell carcinoma.

Telomerase activity is upregulated in head and neck squamous cell carcinoma (HNSCC), yet its regulatory mechanisms remain unclear. Here, we identified a cancer-specific lncRNA (LINC02454) associated with poor prognosis by using LncRNA chip of our HNSCC cohorts and external datasets. Through employing negative-stain transmission electron microscopy (NS-TEM), we discovered an interaction between LINC02454 and CCT complex which would augment telomerase activity for maintaining telomere homeostasis. Supporting this, in the telomerase repeat amplification protocol (TRAP) assay and quantitative fluorescence in situ hybridization (Q-FISH) analysis, LINC02454 depletion significantly reduced telomerase activity and shortened telomere length. Consistently, pathways related to telomerase, mitosis, and apoptosis were significantly impacted upon LINC02454 knockdown in RNAseq analysis. Functionally, LINC02454-deficient cells exhibited a more significant senescence phenotype in ß-galactosidase staining, cell cycle, and apoptosis assays. We further confirmed the role of LINC02454 in HNSCC proliferation through a combination of in vitro and in vivo experiments. The therapeutic potential of targeting LINC02454 was verified by adenovirus-shRNA approach in HNSCC patient-derived xenograft (PDX) models. In summary, our findings provided valuable insights into the molecular mechanisms of HNSCC tumorigenesis and potential targets for future treatment modalities.

Downregulation of VEGFA accelerates AGEs-mediated nucleus pulposus degeneration through inhibiting protective mitophagy in high glucose environments.

Intervertebral disc degeneration (IVDD) contributes largely to low back pain. Recent studies have highlighted the exacerbating role of diabetes mellitus (DM) in IVDD, mainly due to the influence of hyperglycemia (HG) or the accumulation of advanced glycation end products (AGEs). Vascular endothelial growth factor A (VEGFA) newly assumed a distinct impact in nonvascular tissues through mitophagy regulation. However, the combined actions of HG and AGEs on IVDD and the involved role of VEGFA remain unclear. We confirmed the potential relation between VEGFA and DM through bioinformatics and biological specimen detection. Then we observed that AGEs induced nucleus pulposus (NP) cell degeneration by upregulating cellular reactive oxygen species (ROS), and HG further aggravated ROS level through breaking AGEs-induced protective mitophagy. Furthermore, this adverse effect could be strengthened by VEGFA knockdown. Importantly, we identified that the regulation of VEGFA and mitophagy were vital mechanisms in AGEs-HG-induced NP cell degeneration through Parkin/Akt/mTOR and AMPK/mTOR pathway. Additionally, VEGFA overexpression through local injection with lentivirus carrying VEGFA plasmids significantly alleviated NP degeneration and IVDD in STZ-induced diabetes and puncture rat models. In conclusion, the findings first confirmed that VEGFA protects against AGEs-HG-induced IVDD, which may represent a therapeutic strategy for DM-related IVDD.

A novel tree shrew model of lipopolysaccharide-induced acute respiratory distress syndrome.

INTRODUCTION: Acute respiratory distress syndrome (ARDS) is a leading cause of respiratory failure, with substantial attributable morbidity and mortality. The small animal models that are currently used for ARDS do not fully manifest all of the pathological hallmarks of human patients, which hampers both the studies of disease mechanism and drug development. OBJECTIVES: To examine whether the phenotypic changes of primate-like tree shrews in response to a one-hit lipopolysaccharides (LPS) injury resemble human ARDS features. METHODS: LPS was administered to tree shrews through intratracheal instillation; then, the animals underwent CT or PET/CT imaging to examine the changes in the structure and function of the whole lung. The lung histology was analyzed by H&E staining and immunohistochemical staining of inflammatory cells. RESULTS: Results demonstrated that tree shrews exhibited an average survival time of 3-5 days after LPS insult, as well as an obvious symptom of dyspnea before death. The ratios of PaO2 to FiO2 (P/F ratio) were close to those of moderate ARDS in humans. CT imaging showed that the scope of the lung injury in tree shrews after LPS treatment were extensive. PET/CT imaging with 18F-FDG displayed an obvious inflammatory infiltration. Histological analysis detected the formation of a hyaline membrane, which is usually present in human ARDS. CONCLUSION: This study established a lung injury model with a primate-like small animal model and confirmed that they have similar features to human ARDS, which might provide a valuable tool for translational research.

Comprehensive quality control of Qingjin Yiqi granule based on UHPLC-Q-Orbitrap-MS and UPLC-QQQ-MS.

INTRODUCTION: Qingjin Yiqi granule (QYG) is a prescription medicine of traditional Chinese medicine which is widely used clinically for the recovery of coronavirus patients. However, there is currently limited research on the quality control of QYG. OBJECTIVE: To evaluate the quality of QYG qualitatively and quantitatively by making full use of advanced chromatography-mass spectrometry techniques. METHODS: Firstly, a multicomponent characterisation of QYG was performed by ultrahigh-performance liquid chromatography coupled with a Q Exactive™ hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q-Orbitrap-MS) system using a rapid negative/positive switching mode. Secondly, the co-condition fingerprint analysis of constituted herbal medicines of QYG was performed to unveil active ingredients as the quality markers of QYG. Thirdly, the marker compounds in 10 batches of QYG were quantified by ultrahigh-performance liquid chromatography coupled with a Waters Xevo TQ-S triple quadrupole mass spectrometry (UPLC-QQQ-MS) system. RESULTS: A comprehensive method that combined the inclusion list and data-dependent acquisition (DDA) to achieve a systematic characterisation of QYG was established by UHPLC-Q-Orbitrap-MS. After analysis based on Compound Discoverer software and Global Natural Products Social (GNPS) platform, a total of 332 compounds were detected. Eleven Q-markers were determined for the quality evaluation of QYG by comparison with the fingerprint of nine constituted herbal medicines. An adjusted multiple reaction monitoring (MRM) quantification method was further established to simultaneously determine the 11 Q-markers for holistic quality evaluation of QYG. CONCLUSION: This is the first study to report comprehensive multicomponent characterisation, identification, and quality assessment of QYG, which could be used for effective guarantee of the quality of QYG.

LncPCD: a manually curated database of experimentally supported associations between lncRNA-mediated programmed cell death and diseases.

Programmed cell death (PCD) refers to controlled cell death that is conducted to keep the internal environment stable. Long noncoding RNAs (lncRNAs) participate in the progression of PCD in a variety of diseases. However, no specialized online repository is available to collect and store the associations between lncRNA-mediated PCD and diseases. Here, we developed LncPCD, a comprehensive database that provides information on experimentally supported associations of lncRNA-mediated PCD with diseases. The current version of LncPCD documents 6666 associations between five common types of PCD (apoptosis, autophagy, ferroptosis, necroptosis and pyroptosis) and 1222 lncRNAs in 331 diseases. We also manually curated a wealth of information: (1) 7 important lncRNA regulatory mechanisms, (2) 310 PCD-associated cell types in three species, (3) detailed information on lncRNA subcellular locations and (4) clinical applications for lncRNA-mediated PCD in diseases. Additionally, 10 single-cell sequencing datasets were integrated into LncPCD to characterize the dynamics of lncRNAs in diseases. Overall, LncPCD is an extremely useful resource for understanding the functions and mechanisms of lncRNA-mediated PCD in diseases. Database URL:  http://spare4.hospital.studio:9000/lncPCD/Home.jsp.

RT-Ensemble Pred: A tool for retention time prediction of metabolites on different LC-MS systems.

Liquid chromatography-mass spectrometry (LC-MS) could provide a large amount of information to assist in metabolites identification. Different liquid chromatographic methods (CMs) could produce different retention times to the same metabolite. To predict the retention time of local dataset by online datasets has become a trend, but the datasets downloaded from different databases were differences in quantity levels. And the imbalanced data could produce bad influence in model prediction. Thus, based on quantitative structure-retention relationships (QSRRs), an ensemble model, named RT-Ensemble Pred, has been successfully built to predict retention time of different LC-MS systems in this study. A total of 76, 807 metabolites (76, 909 retention times) have been collected across 9 CMs, and 19 natural products and 1 antifungal drug (20 retention times) have been collected to test the model applicability. An ensemble sampling was applied for the preprocessing procedure to solve the problem of imbalanced data. Based on the ensemble sampling, RT-Ensemble Pred could better utilize online datasets for the prediction of retention time. RT-Ensemble Pred was built based on the online datasets and tested by local dataset. The predictive accuracy of RT-Ensemble Pred was higher than the models without any sampling methods. The results showed that RT-Ensemble Pred could predict the metabolites which was not included in the database and the metabolites which were from new CMs. It could also be used for the prediction of other compounds beside metabolites. Furthermore, a tool of RT-Ensemble Pred was packed and can be freely downloaded at https://gitlab.com/mikic93/rt-ensemble-pred. It provides convenience for the users who need to predict the retention time of metabolites.

Integration of UHPLC/Q-OrbitrapMS-based metabolomics and activities evaluation to rapidly explore the anti-inflammatory components from lasianthus.

Lasianthus, belonging to Rubiaceae, has been verified to improve clinical syndrome in immune diseases (e.g., hepatitis, nephritis, and rheumatoid arthritis). Both the anti-inflammatory function and chemical composition of Lasianthus vary considerably between different species but few studies focus. So essential it is to explore lasianthus and further search for anti-inflammatory substances. The target of this artical is to analyze the anti-inflammatory activity and chemical composition of lasianthus of different species. And the subsequent active compounds were explored. Primary, the anti-inflammatory activity among seven species of lasianthus (e.g., L. fordii., L. wallichii., L. hookeri C., L. verticillatus., L. sikkimensis., L. appressihirtus., and L. hookeri var) were evaluated by vitro experiments (RAW 264.7 cells). Next, UHPLC/Q-Orbitrap-MS-based metabolomics and the mass defect filter (MDF) algorithm were performed to explore metabolites. In addition, principal component analysis (PCA) was to screen out differential compounds in seven species. Finally, the correlation analysis between activities and composition to rapidly discover the active compounds (compounds were verified pharmacologically). Among the 7 species of lasianthus, the L. fordii. and L. hookeri C indicated the best anti-inflammatory activity. Untargeted metabolomics and MDF show 112 compounds, classified into six dominant types (e.g., flavonoids, phenolic acids, alkaloids, iridoids, coumarins, and anthraquinones). Furthermore, 33 differential metabolites were confirmed by PCA. Then according to correlation analysis and pharmacological validation, 7 compounds IC50＜100 (e.g., scopoletin, asperulosidic acid, chlorogenic acid, ferulic acid, betaine, syringic acid, and emodin) were verified as anti-inflammatory compounds and conduct quantitative analysis. Metabolomics integrated with activities evaluation might be a rapid and effective strategy to explore the active compounds from natural products.

Association between early ambulation exercise and short-term postoperative recovery after open transforaminal lumbar interbody fusion: a single center retrospective analysis.

BACKGROUND: Early ambulation in patients undergoing transforaminal lumbar interbody fusion (TLIF) surgery is recommended, however, the precise time interval after open surgery has never been specified. Current retrospective analysis was conducted aiming to clarify an accurate time interval. METHODS: A retrospective analysis of eligible patients was conducted using the databases of the Bone Surgery Department, Third Affiliated Hospital of Sun Yat-sen University from 2016 to 2021. Data pertaining to postoperative hospital stay length, expenses, incidence of complications were extracted and compared using Pearson's χ2 or Student's t-tests. A multivariate linear regression model was conducted to identify the relationship between length of hospital stay (LOS) and other outcomes of interest. A propensity analysis was conducted to minimize bias and to evaluate the reliability of results. RESULTS: A total of 303 patients met the criteria and were included for the data analysis. Multivariate linear regression results demonstrated that a high ASA grade (p = 0.016), increased blood loss (p = 0.003), cardiac disease (p < 0.001), occurrence of postoperative complications(p < 0.001) and longer ambulatory interval (p < 0.001) was significantly associated with an increased LOS. The cut-off analysis manifested that patients should start mobilization within 3 days after open TLIF surgery (B = 2.843, [1.395-4.292], p = 0.0001). Further comparative analysis indicated that patients who start ambulatory exercise within 3 days have shorter LOS (8.52 ± 3.28d vs 12.24 ± 5.88d, p < 0.001), total expenses ( 9398.12 ± 2790.82vs 10701.03 ± 2994.03 [USD], p = 0.002). Propensity analysis revealed such superiority was stable along with lower incidence of postoperative complications (2/61 vs 8/61, p = 0.0048). CONCLUSIONS: The current analysis suggested that ambulatory exercise within 3 days for patients who underwent open TLIF surgery was significantly associated with reduced LOS, total hospital expenses, and postoperative complications. Further causal relationship would be confirmed by future randomized controlled trials.

Integrated metabolic and transcriptomic profiles reveal the germination-associated dynamic changes for the seeds of Cassia obtusifolia L.

INTRODUCTION: The seeds of Cassia obtusifolia L. (Cassiae [C.] semen) have been widely used as both food and traditional Chinese medicine in China. OBJECTIVES: We aimed to analyze the metabolic mechanisms underlying C. semen germination. MATERIALS AND METHODS: Different samples of C. semen at various germination stages were collected. These samples were subjected to 1 H-NMR and UHPLC/Q-Orbitrap-MS-based untargeted metabolomics analysis together with transcriptomics analysis. RESULTS: A total of 50 differential metabolites (mainly amino acids and sugars) and 20 key genes involved in multiple pathways were identified in two comparisons of different groups (36 h vs 12 h and 84 h vs 36 h). The metabolite-gene network for seed germination was depicted. In the germination of C. semen, fructose and mannose metabolism was activated in the testa rupture period, indicating more energy was needed (36 h). In the embryonic axis elongation period (84 h), the pentose and glucuronate interconversions pathway and the phenylpropanoid biosynthesis pathway were activated, which suggested some nutrient sources (nitrogen and sugar) were in demand. Furthermore, oxygen, energy, and nutrition should be supplied throughout the whole germination process. These global views open up an integrated perspective for understanding the complex biological regulatory mechanisms during the germination process of C. semen.

Identification of a pyroptosis-based model for predicting clinical outcomes from immunotherapy in patients with metastatic melanoma.

Immunotherapy has greatly improved outcomes for patients with advanced melanoma, but good predictive biomarkers remain lacking in clinical practice. Although increasing evidence has revealed a vital role of pyroptosis in the tumor microenvironment (TME), it remains unclear for pyroptosis as a predictive biomarker for immunotherapy in melanoma. RNA sequencing data and annotated clinical information of melanoma patients were obtained from four published immunotherapy datasets. LASSO regression analysis was conducted to develop a pyroptosis-based model for quantifying a pyroptosis score in each tumor. Based on four clinical cohorts, we evaluated the predictive capability of the model using multiple immunotherapeutic outcomes, including clinical benefits, overall survival (OS), and progression-free survival (PFS). Furthermore, we depicted the distinctive TME features associated with pyroptosis. Compared with the group with low pyroptosis scores, the group with high pyroptosis scores consistently achieved better durable clinical benefits in four independent cohorts and the meta-cohort. ROC analysis validated that the pyroptosis-based model was a reliable biomarker for predicting clinical benefits from immunotherapy in melanoma. Survival analyses showed that the group with high pyroptosis scores harbored more favorable OS and PFS than those with low pyroptosis scores. Molecular analysis revealed that tumors with high pyroptosis scores displayed a typical immune-inflamed phenotype in TME, including enrichment of immunostimulatory pathways, increased level of tumor-infiltrating lymphocytes, upregulation of immune effectors, and activation of the antitumor immune response. Our findings suggested that the pyroptosis-related model associated with multiple immune-inflamed characteristics might be a reliable tool for predicting clinical benefit and survival outcomes from immunotherapy in melanoma.

A multiple-metabolites model to predict preliminary renal injury induced by iodixanol based on UHPLC/Q-Orbitrap-MS and 1H-NMR.

BACKGROUND & AIMS: There are some problems, such as unclear pathological mechanism, delayed diagnosis, and inaccurate therapeutic target of Contrast-induced acute kidney injury (CI-AKI). It is significantly important to find biomarkers and therapeutic targets that can indicate renal injury in the early stage of CI-AKI. This study aims to establish a multiple-metabolites model to predict preliminary renal injury induced by iodixanol and explore its pathogenesis. METHODS: Both UHPLC/Q-Orbitrap-MS and 1H-NMR methods were applied for urine metabolomics studies on two independent cohorts who suffered from a preliminary renal injury caused by iodixanol, and the multivariate statistical analysis and random forest (RF) algorithm were used to process the related date. RESULTS: In the discovery cohort (n = 169), 6 metabolic markers (leucine, indole, 5-hydroxy-L-tryptophan, N-acetylvaline, hydroxyhexanoycarnine, and kynurenic acid) were obtained by the cross-validation between the RF and liquid chromatography-mass spectrometry (LC-MS). Secondly, the 6 differential metabolites were confirmed by comparison of standard substance and structural identification of 1H-NMR. Subsequently, the multiple-metabolites model composed of the 6 biomarkers was validated in a validation cohort (n = 165). CONCLUSIONS: The concentrations of leucine, indole, N-acetylvaline, 5-hydroxy-L-tryptophan, hydroxyhexanoycarnitine and kynurenic acid in urine were proven to be positively correlated with the degree of renal injury induced by iodixanol. The multiple-metabolites model based on these 6 biomarkers has a good predictive ability to predict early renal injury caused by iodixanol, provides treatment direction for injury intervention and a reference for reducing the incidence of clinical CI-AKI further.

Discovery of metabolic markers for the discrimination of Helwingia species based on bioactivity evaluation, plant metabolomics, and network pharmacology.

RATIONALE: Helwingia japonica (HJ), a traditional medicinal plant, is commonly used for the treatment of dysentery, blood in the stool, and scald burns. Three major HJ species, Helwingia japonica (Thunb.) Dietr. (QJY), Helwingia himalaica Hook. f. et Thoms. ex C. B. Clarke, and Helwingia chinensis Batal., share great similarities in both morphology and chemical constituents. The discrimination of medicinal plants directly affects their pharmacological and clinical effects. Here, we solved the taxonomy uncertainty of these three HJ species and explored the discrimination and study of other traditional medicines (TMs). METHODS: First, the anti-inflammatory effects of the three HJ species were compared using lipopolysaccharide (LPS)-induced inflammatory responses in mouse leukemia cells of monocyte macrophage (RAW) 264.7 cells. Then, plant metabolomics were performed in 48 batches of samples to discover chemical markers for discriminating different HJ species. Finally, network pharmacology was applied to explore the linkages among constituents, targets, and signaling pathways. RESULTS: In vitro experiments showed that the QJY exhibited the most potential anti-inflammatory activities. Meanwhile, 172 compounds were tentatively identified and eight metabolites with higher relative content in QJY were designated as chemical markers to distinguish QJY and the other two species. According to the property of absorbed in vivo, threonic acid, arginine, and tyrosine were selected to construct a component-target-pathway network. The network pharmacology analysis confirmed that the chemotaxonomy differentiation was consistent with the bioactive assessment. CONCLUSIONS: The present study demonstrates that bioactivity evaluation integrated with plant metabolomics and network pharmacology could be used as an effective approach to discriminate different TMs and discover the active compounds.

Identification of circulating immune landscape in ischemic stroke based on bioinformatics methods.

Ischemic stroke (IS) is a high-incidence disease that seriously threatens human life and health. Neuroinflammation and immune responses are key players in the pathophysiological processes of IS. However, the underlying immune mechanisms are not fully understood. In this study, we attempted to identify several immune biomarkers associated with IS. We first retrospectively collected validated human IS immune-related genes (IS-IRGs) as seed genes. Afterward, potential IS-IRGs were discovered by applying random walk with restart on the PPI network and the permutation test as a screening strategy. Doing so, the validated and potential sets of IS-IRGs were merged together as an IS-IRG catalog. Two microarray profiles were subsequently used to explore the expression patterns of the IS-IRG catalog, and only IS-IRGs that were differentially expressed between IS patients and controls in both profiles were retained for biomarker selection by the Random Forest rankings. CLEC4D and CD163 were finally identified as immune biomarkers of IS, and a classification model was constructed and verified based on the weights of two biomarkers obtained from the Neural Network algorithm. Furthermore, the CIBERSORT algorithm helped us determine the proportions of circulating immune cells. Correlation analyses between IS immune biomarkers and immune cell proportions demonstrated that CLEC4D was strongly correlated with the proportion of neutrophils (r = 0.72). These results may provide potential targets for further studies on immuno-neuroprotection therapies against reperfusion injury.