Targeted Quantification of Glutathione/Arginine Redox Metabolism Based on a Novel Paired Mass Spectrometry Probe Approach for the Functional Assessment of Redox Status.

Glutathione (GSH) redox control and arginine metabolism are critical in regulating the physiological response to injury and oxidative stress. Quantification assessment of the GSH/arginine redox metabolism supports monitoring metabolic pathway shifts during pathological processes and their linkages to redox regulation. However, assessing the redox status of organisms with complex matrices is challenging, and single redox molecule analysis may not be accurate for interrogating the redox status in cells and in vivo. Herein, guided by a paired derivatization strategy, we present a new ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)-based approach for the functional assessment of biological redox status. Two structurally analogous probes, 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) and newly synthesized 2-methyl-6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (MeAQC), were set for paired derivatization. The developed approach was successfully applied to LPS-stimulated RAW 264.7 cells and HDM-induced asthma mice to obtain quantitative information on GSH/arginine redox metabolism. The results suggest that the redox status was remarkably altered upon LPS and HDM stimulation. We expect that this approach will be of good use in a clinical biomarker assay and potential drug screening associated with redox metabolism, oxidative damage, and redox signaling.

Prevalence, cognitive characteristics, and influencing factors of amnestic mild cognitive impairment among older adults residing in an urban community in Chengdu, China.

Objective: Dementia is a significant public health concern, and mild cognitive impairment (MCI) serves as a transitional stage between normal aging and dementia. Among the various types of MCI, amnestic MCI (aMCI) has been identified as having a higher likelihood of progressing to Alzheimer's dimension. However, limited research has been conducted on the prevalence of aMCI in China. Therefore, the objective of this study is to investigate the prevalence of aMCI, examine its cognitive characteristics, and identify associated risk factors. Methods: In this cross-sectional study, we investigated a sample of 368 older adults aged 60 years and above in the urban communities of Chengdu, China. The participants underwent a battery of neuropsychological assessments, including the Mini-Mental State Examination (MMSE), the Clinical Dementia Rating (CDR), Auditory Verbal Learning Test (AVLT), Wechsler's Logical Memory Task (LMT), Boston Naming Test (BNT) and Trail Making Test Part A (TMT-A). Social information was collected by standard questionnaire. Multiple logistic regression analysis was utilized to screen for the risk and protective factors of aMCI. Results: The data analysis included 309 subjects with normal cognitive function and 59 with aMCI, resulting in a prevalence of 16.0% for aMCI. The average age of participants was 69.06 ± 7.30 years, with 56.0% being females. After controlling for age, gender and education, the Spearman partial correlation coefficient between various cognitive assessments and aMCI ranged from -0.52 for the long-term delayed recall scores in AVLT to 0.19 for the time-usage scores in TMT-A. The results indicated that all cognitive domains, except for naming scores (after semantic cue of BNT) and error quantity (in TMT-A), showed statistically significant associations with aMCI. Furthermore, the multiple logistic regression analysis revealed that older age (OR = 1.044, 95%CI: 1.002~1.087), lower educational level, and diabetes (OR = 2.450, 95%CI: 1.246~4.818) were risk factors of aMCI. Conclusion: This study found a high prevalence of aMCI among older adults in Chengdu, China. Individuals with aMCI exhibited lower cognitive function in memory, language, and executive domains, with long-term delayed recall showing the strongest association. Clinicians should prioritize individuals with verbal learning and memory difficulties, especially long-term delayed recall, in clinical practice.

Determining food tourism consumption of wild mushrooms in Yunnan Provence, China: A projection-pursuit approach.

As the first of the six elements of tourism, food is an important part of tourism activities. As an important driving force for the economic development of tourist destinations, food tourism plays an increasingly important role in tourism and has gradually become an important hub connecting tourists, local residents, and tourist destinations. This study takes Yunnan wild mushrooms as a case, obtained data through a questionnaire survey and applied a projection pursuit model (PPM) to explore the driving factors affecting food tourism consumption. Research shows that the quality and abundance of gourmet resources are the most important factors affecting tourist consumption of gourmet foods, and the needs and experiences of tourists also promote their consumption, to a certain extent. This provides a guide for Yunnan Province to expand the source market. Second, we compared PPM with structural equation modeling (SEM) and demonstrated that the former requires less data than the latter and is immune to nonlinearities, interaction effects, and the researchers' excessive prior knowledge. This makes PPM more robust, anti-interference, accurate, and objective than SEM when dealing with problems. Finally, we put forward reasonable suggestions from four aspects of government, enterprises, local residents, and tourists, which provide an effective way for Yunnan Province to develop food tourism. In addition, PPM's advantages in data selection, data processing, and result stability fill the gaps in data processing in the tourism field.

An in-house database-driven untargeted identification strategy for deep profiling of chemicalome in Chinese medicinal formula.

Deep profiling of chemicalome in Chinese medicinal formulas is vital for disclosing the secret underlying their effectiveness. To address this issue, an in-house database-driven untargeted identification strategy was proposed with the use of ultra-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry. Firstly, an in-house mass spectral database for the analyzed herbs was constructed, and database querying was performed for rapid recognition of known compounds. Secondly, a chemical diagnostic characteristics algorithm was originally developed for deep mining unrecorded ions, and thus expanding coverage of components beyond the database. Additionally, we proposed evaluation criteria for the untargeted identification of compounds with different confidence levels. As a case study, the integrated strategy was applied to comprehensively characterize complex multi-type components in Gegen-Qinlian Decoction. A total of 381 compounds were characterized and annotated with four different confidence levels, and 88.40% of these annotated compounds were successfully re-identified in triplicate analyses with a different instrument. The integrated strategy was demonstrated powerful in deep profiling of chemicalome in Chinese medicinal formulas with higher throughput, analytical sharpness, and lower omission ratios.

Targeting tryptophan metabolism reveals Clematichinenoside AR alleviates triptolide-induced hepatotoxicity.

Liver toxicity induced by Triptolide (TP) has limited its clinical application on rheumatoid arthritis (RA). Saponins have been proved as an efficacious remedy to mitigate hepatotoxicity. However, the mechanism of reducing hepatotoxicity by saponins intervention remains incompletely characterized. Tryptophan (Trp) metabolites activate transcriptional regulators to mediate host detoxification responses. Our study aimed to investigate whether Clematichinenoside AR (C-AR) could attenuate TP-induced liver damage by regulating Trp metabolism. We used targeted metabolomics to quantify Trp metabolites in the serum and liver samples of collagen-induced arthritis rats treated by TP. Multiple comparison analyses helped the evaluation of promising biomarkers. The pronounced changed levels of Trp, indole acetic acid, and indole-3-carboxaldehyde in the serum and indole acetic acid, indole, and tryptamine in the liver are relevant to TP-induced liver injury. Intervention with C-AR could relieve TP-induced hepatotoxicity evidenced by ameliorative serum parameters and hepatic histology. In addition, C-AR regulated the levels of these indoles biomarker candidates to normal. Therapeutic modulation with natural compounds might be a useful clinical strategy to ameliorate toxicity induced by TP. Deciphering Trp metabolism will facilitate a better understanding of the pathogenesis of diseases and drug responding.

Measurement of Intracellular Nitric Oxide with a Quantitative Mass Spectrometry Probe Approach.

Nitric oxide (NO) is a molecule of physiological importance, and the function of NO depends on its concentration in biological systems, particularly in cells. Concentration-based analysis of intracellular NO can provide insight into its precise role in health and disease. However, current methods for detecting intracellular NO are still inadequate for quantitative analysis. In this study, we report a quantitative mass spectrometry probe approach to measure NO levels in cells. The probe, Amlodipine (AML), comprises a Hantzsch ester group that reacts with NO to form a pyridine, Dehydro Amlodipine (DAM). Quantification of DAM by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) allows specific measurement of intracellular NO levels. Notably, the AML/NO reaction proceeds rapidly (within 1 s), which is favorable for NO detection considering its large diffusivity and short half-life. Meanwhile, studies under simulated physiological conditions revealed that the AML response to NO is proportional and selective. The presented UPLC-MS/MS method showed high sensitivity (LLOQ = 0.24 nM) and low matrix interference (less than 15%) in DAM quantification. Furthermore, the mass spectrometry probe approach was demonstrated by enabling the measurement of endogenous and exogenous NO in cells. Hence, the quantitative UPLC-MS/MS method developed using AML as a probe is expected to be a new method for intracellular NO analysis.

Enhancing enrichment ability of ZIF-8 mixed matrix membrane microextraction by reverse micelle strategy for analysis of multiple ionizable bioactive components in biological samples.

Recent research aimed at the design of mixed-matrix membrane (MMM) to be used for microextraction emphasized on membrane extraction phase with high surface area and porosity. This study explored the influence that surfactants have on MMM extraction efficiency for the first time. The zeolitic imidazolate framework 8-based MMM (ZIF-8-MMM) was synthesized by in situ self-assembly of ZIF-8 on the inner wall of a hollow fiber membrane with the aim of fabricating a microextraction device. By prompting the encapsulation of ionizable analytes in the polar core of reverse micelles, the presence of surfactants in extraction solvent assisted the dissolution of analytes in the fiber membrane lumen and enhanced their adsorption onto ZIF-8. Notably, hereby a microextraction method based on the novel ZIF-8-MMM-reverse micelle (ZIF-8-MMM-RM) system was developed and employed for the extraction and quantitation of two alkaloids (berberine and jatrorrhizine) and two flavonoids (wogonin and wogonoside) in biological samples. The main factors affecting microextraction performance, identity of the extraction solvent, surfactant concentration, sample solution pH and extraction time, were investigated in detail. The method showed good linearity (r2 > 0.99) and repeatability (RSD < 10%), low limits of detection (0.10-0.31 ng mL-1) and high relative recoveries (90.03-98.84%). The enrichment factor values ranged between 48.47 and 54.96. Reverse micelle formation prompted by surfactant addition was demonstrated to effectively assist the extraction of multiple ionizable analytes from biological samples, resulting in a marked improvement of ZIF-8-MMM extraction performance.