Identification and Validation of TRIM25 as a Glucose Metabolism Regulator in Prostate Cancer.

Prostate cancer (PCa) malignant progression is accompanied with the reprogramming of glucose metabolism. However, the genes involved in the regulation of glucose metabolism in PCa are not fully understood. Here, we propose a new method, DMRG, which constructs a weighted differential network (W-K-DN) to define the important metabolism-related genes. Based on biological knowledge and prostate cancer transcriptome data, a tripartite motif-containing 25 (TRIM25) was defined using DMRG; TRIM25 was involved in the regulation of glucose metabolism, which was verified by overexpressing or knocking down TRIM25 in PCa cell lines. Differential expression analysis of TCA cycle enzymes revealed that TRIM25 regulated isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) expression. Moreover, a protein-RNA interaction network of TRIM25 revealed that TRIM25 interacted with RNA-binding proteins, including DExH-box helicase 9 and DEAD-box helicase 5, to play a role in regulating the RNA processing of metabolic enzymes, including IDH1 and FH. Furthermore, TRIM25 expression level was found to be positively correlated with Gleason scores in PCa patient tissues. In conclusion, this study provides a new method to define genes influencing tumor progression, and sheds light on the role of the defined TRIM25 in regulating glucose metabolism and promoting PCa malignancy.

Full Collision Energy Ramp-MS2 Spectrum in Structural Analysis Relying on MS/MS.

Albeit frequently being overlooked, MS2 spectrum variation against collision energy (CE) implies auxiliary structural clues for m/z values. Online energy-resolved MS (ER-MS) provides the opportunity to acquire the trajectory of ion intensity against CE for any fragment ion of interest, thus exactly offering the desired momentum to empower the conventional MS2 spectrum at a certain CE forward to a full-CE ramp MS2 spectrum (FCER-MS2). Efforts were made here to construct an FCER-MS2 spectrum and to evaluate its potential toward structural analysis. Flavonoids were employed as a proof of concept. MS2 spectra of 76 compounds were recorded by LC-Q-Exactive-MS, and online ER-MS was subsequently programmed using LC-Qtrap-MS to build a breakdown graph for each obvious fragment ion. After defining the greatest value amongst all regressive apices as 100%, the normalized breakdown graphs comprised an FCER-MS2 spectrum for each compound. The FCER-MS2 spectrum contained the MS2 spectrum at any CE as well as optimal CE (OCE) and maximal relative ion intensity (RIImax) of each fragment ion. Except the pronounced isomeric discrimination potential, either OCE or RIImax reflected certain structural properties, such as aglycone, glycosidic bond, and hydroxy, methoxy, and glycosyl substituents. These rules were subsequently applied for flavonoid-focused characterization of a famous herbal medicine, namely Scutellariae Radix, and high-level structural annotation was accomplished for 75 flavonoids. Above all, the FCER-MS2 spectrum includes m/z, OCEs, and RIImax features, thus facilitating confidence-advanced structural analysis.

[Isomeric discrimination of kaempferol versus luteolin by online energy-resolved mass spectrometry].

Isomers are widely distributed in Chinese herbal medicines,and can be discriminated by energy-resolved mass spectrometry( ER-MS). However,ER-MS was performed through direct injection of reference compounds with syringe pump,which encountered a significant technical barrier for high-throughput and automated measurements. Herein,online ER-MS was conducted using LC-MS platform,and a pair of isomers,kaempferol vs luteolin,were employed as a case study to illustrate and assess the utility of online ER-MS for isomeric discrimination. High-resolution tandem mass spectrometry data of both flavonoids were acquired on LC-QE-Orbitrap-MS,and the fragmentation pathways responsible for the primary fragment ions were proposed. The primary signal in MS1 occurred at m/z 285( [M-H]-),and the primary signals of either compound generated by retro-Diels-Alder fragmentation were observed at m/z 151 and 133. The spectral information was subsequently transferred onto LC-Qtrap-MS platform to carry out online ER-MS. Two precursor-to-product ion transition candidates were constructed as m/z 285>151 and 285>133,and either afterward derived a set of pseudo-ion transitions( PITs) and so forth,exactly corresponding to a series of progressive collision energies( eg-5,-8,-11 e V,and so on). All PITs were typed into the monitoring list of multiple reaction monitoring program to generate the peak area datasets. Either dataset was normalized using the highest values in the set and imported into Graph Pad Prism software to plot the Gaus-sian-shaped curve that was termed as the break-down graph. The apex of the regressive curve was termed as optimal collision energy( OCE). The OCE values corresponding to m/z 285>151 were calculated as-29. 06 e V and-35. 71 e V for kaempferol and luteolin,respectively. In the case of m/z 285>133,the OCEs were yielded as-44. 15 e V for kaempferol and-49. 01 e V for luteolin. With re-ference to their chemical structures,the location of hydroxyl group was regarded to be responsible for the differences of either m/z 285>151 or 285>133 between the isomers,attributing to their different bond properties. Above all,online ER-MS offers an eligible tool for isomeric discrimination,and provides meaningful information for the accurate chemical composition characterization based on LC-MS,which is not limited to Chinese herbal medicines.

[Identification of active components in Longxue Tongluo Capsules against ischemic brain injury based on component-activity relationship].

Ten fractions(A-J) were prepared by separation of Longxue Tongluo Capsules(LTC) by using silica gel column chromatography and orthogonal experimental design,showing similar chemical profiles with different abundances of peaks.These ten samples were assessed with UHPLC-QE OrbitrapHRMS for 97 common peaks.For the pharmacological activity experiment,three kinds of in vitro cell models including lipopolysaccharide(LPS)-induced BV-2 microglial cells NO release model,oxygen-glucose deprivation/reoxygenation(OGD/R)-treated HUVEC vascular endothelial cells injury model,and OGD/R-treated PC-12 nerve cells injury model were employed to evaluated the bioactivity of each fraction.Based on the contribution of each identified component,grey relation analysis and partial least squares(PLS) analysis were performed to establish component-activity relationship of LTC,identify the potential active components.After that,validation of the potential active components in LTC was carried out by using the same models.The results indicated that 4 phenolic compounds including 7,4'-dihydroxyhomoisoflavanone,loureirin C,4,4'-dihydroxy-2,6-dimethoxydihydrochalcone,and homoisosocotrin-4'-ol,might be the active components for anti-neuroinflammation effect;five phenolic compounds such as 3,5,7,4'-tetrahydroxyhomoisoflavanone,loureirin D,7,4'-dihydroxyhomoisoflavane,and 5,7-dihydroxy-4'-methoxy-8-methyflavane,might have positive effects on the vascular endothelial injury;three phenolic compounds including 5,7,4'-trihydroxyflavanone,7,4'-dihydroxy-5-methoxyhomoisoflavane,and loureirin D,might be the active components in LTC against neuronal injury.

[Risk analysis of serum chemical residues for metabolic associated fatty liver disease based on exposome-lipidome wide association study].

Metabolic associated fatty liver disease (MAFLD) is a common liver disease with a prevalence of up to 25%; it not only adversely affects human health but also aggravates the economic burden of society. An increasing number of studies have suggested that the occurrence of chronic noncommunicable diseases is affected by both environmental exposures and genetic factors. Research has also shown that environmental pollution may increase the risk of MAFLD and promote its occurrence and development. However, the relationship between these concepts, as well as the underlying exposure effects and mechanism, remains incompletely understood. Lipidomics, a branch of metabolomics that studies lipid disorders, can help researchers investigate abnormal lipid metabolites in various disease states. Lipidome-exposome wide association studies are a promising paradigm for investigating the health effects of cumulative environmental exposures on biological responses, and could provide new ideas for determining the associations between metabolic and lipid changes and disease risk caused by chemical-pollutant exposure. Hence, in this study, targeted exposomics and nontargeted lipidomics studies based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) were used to characterize exogenous chemical pollutants and endogenous lipid metabolites in the sera of patients with MAFLD and healthy subjects. The results demonstrated that fipronil sulfone, malathion dicarboxylic acid, and monocyclohexyl phthalate may be positively associated with the disease risk of patients diagnosed as simple fatty liver disease (hereafter referred to as MAFLD(0)). Moreover, fipronil sulfone, acesulfame potassium, perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluoroundecanoic acid (PFUnDA), 4-hydroxybenzophenone, and 3,5-di-tert-butyl-4-hydroxybenzoic acid (DBPOB) may be positively associated with the disease risk of patients diagnosed as fatty liver complicated by single or multiple metabolic disorders. Association analysis was carried out to explore the lipid metabolites induced by chemical residues. Triglyceride (TG) and diglyceride (DG) were significantly increased in MAFLD and MAFLD(0). The numbers of carbons of significantly changed DGs and TGs were mainly in the ranges of 32-40 and 35-60, respectively, and both were mainly characterized by changes in polyunsaturated lipids. Most of the lipid-effect markers were positively correlated with chemical residues and associated with increased disease risk. Our research provides a scientific basis for studies on the association and mechanism between serum chemical-pollutant residues and disease outcomes.

ALBI score combined with FIB-4 index to predict post-hepatectomy liver failure in patients with hepatocellular carcinoma.

Post-hepatectomy liver failure (PHLF) is a potentially life-threatening complication following liver resection. Hepatocellular carcinoma (HCC) often occurs in patients with chronic liver disease, which increases the risk of PHLF. This study aimed to investigate the ability of the combination of liver function and fibrosis markers (ALBI score and FIB-4 index) to predict PHLF in patients with HCC. Patients who underwent hepatectomy for HCC between August 2012 and September 2022 were considered for inclusion. Multivariable logistic regression analysis was used to identify factors associated with PHLF, and ALBI score and FIB-4 index were combined based on their regression coefficients. The performance of the combined ALBI-FIB4 score in predicting PHLF and postoperative mortality was compared with Child-Pugh score, MELD score, ALBI score, and FIB-4 index. A total of 215 patients were enrolled in this study. PHLF occurred in 35 patients (16.3%). The incidence of severe PHLF (grade B and grade C PHLF) was 9.3%. Postoperative 90-d mortality was 2.8%. ALBI score, FIB-4 index, prothrombin time, and extent of liver resection were identified as independent factors for predicting PHLF. The AUC of the ALBI-FIB4 score in predicting PHLF was 0.783(95%CI: 0.694-0.872), higher than other models. The ALBI-FIB4 score could divide patients into two risk groups based on a cut-off value of - 1.82. High-risk patients had a high incidence of PHLF of 39.1%, while PHLF just occurred in 6.6% of low-risk patients. Similarly, the AUCs of the ALBI-FIB4 score in predicting severe PHLF and postoperative 90-d mortality were also higher than other models. Preoperative ALBI-FIB4 score showed good performance in predicting PHLF and postoperative mortality in patients undergoing hepatectomy for HCC, superior to the currently commonly used liver function and fibrosis scoring systems.

Metabolomics acts as a powerful tool for comprehensively evaluating vaccines approved under emergency: a CoronaVac retrospective study.

Introduction: To control the COVID-19 pandemic, great efforts have been made to realize herd immunity by vaccination since 2020. Unfortunately, most of the vaccines against COVID-19 were approved in emergency without a full-cycle and comprehensive evaluation process as recommended to the previous vaccines. Metabolome has a close tie with the phenotype and can sensitively reflect the responses to stimuli, rendering metabolomic analysis have the potential to appraise and monitor vaccine effects authentically. Methods: In this study, a retrospective study was carried out for 330 Chinese volunteers receiving recommended two-dose CoronaVac, a vaccine approved in emergency in 2020. Venous blood was sampled before and after vaccination at 5 separate time points for all the recipients. Routine clinical laboratory analysis, metabolomic and lipidomic analysis data were collected. Results and discussion: It was found that the serum antibody-positive rate of this population was around 81.82%. Most of the laboratory parameters were slightly perturbated within the relevant reference intervals after vaccination. The metabolomic and lipidomic analyses showed that the metabolic shift after inoculation was mainly in the glycolysis, tricarboxylic acid cycle, amino acid metabolism, urea cycle, as well as microbe-related metabolism (bile acid metabolism, tryptophan metabolism and phenylalanine metabolism). Time-course metabolome changes were found in parallel with the progress of immunity establishment and peripheral immune cell counting fluctuation, proving metabolomics analysis was an applicable solution to evaluate immune effects complementary to traditional antibody detection. Taurocholic acid, lysophosphatidylcholine 16:0 sn-1, glutamic acid, and phenylalanine were defined as valuable metabolite markers to indicate the establishment of immunity after vaccination. Integrated with the traditional laboratory analysis, this study provided a feasible metabolomics-based solution to relatively comprehensively evaluate vaccines approved under emergency.

Benzophenone glycosides from the pericarps of Aquilaria yunnanensis S. C. Huang.

Two new benzophenone glycosides, aquilarisides A (1) and B (2), together with six known analogues (3-8) were isolated from the pericarps of Aquilaria yunnanensis S. C. Huang. Their structures were elucidated on the basis of 1D and 2D NMR and mass spectroscopic analyses, and the absolute configuration of compound 1 was determined by experimental and calculated electronic circular dichroism (ECD) spectra. Anti-inflammatory activities of all compounds 1-8 were evaluated for their inhibitory activities against lipopolysaccharide (LPS)-stimulated induced nitric oxide (NO) production in RAW 264.7 cells using the Griess assay. Compound 2 indicated a weak inhibition of NO production.

LC-MS-guided isolation of anti-inflammatory 2-(2-phenylethyl)chromone dimers from Chinese agarwood (Aquilaria sinensis).

Fifteen previously undescribed 2-(2-phenylethyl)chromone dimers, along with two known analogues were isolated from Chinese agarwood (Aquilaria sinensis) by a LC-MS-guided fractionation procedure. Their structures were elucidated on the basis of spectroscopic and spectrometric data (1D and 2D NMR, IR, and HRESIMS). The isolated compounds exhibited significant inhibition of nitric oxide production in lipopolysaccharide-stimulated RAW264.7 cells with IC50 values in the range 0.6-37.1 µM.