OBJECTIVE: Solar lentigo is a prevalent skin condition that affects a significant number of individuals. Fortunately, certain traditional Chinese medicines and monomers (TCMM) have proven effective in addressing these concerns. In this study, we evaluated the efficacy and underlying mechanism of TCMM, a combination of TCM and monomers in repairing solar lentigo.
METHODS: We detected and identified the main compounds of TCM using liquid chromatography-mass spectrometry (LC-MS) and through the approach of network pharmacology, we screened drug and disease targets, visualized networks with Cytoscape software, analyzed targets via Gene ontology and KEGG, clinically validated predictions. In a mouse model, UVB-induced pigmentation was assessed, and the effects of TCMM were evaluated. A clinical trial on 30 patients validated the depigmenting agent.
RESULTS: Active ingredients such as MSH, Butylated hydroxytoluen, Valerophenone, and Geranylacetone aid pigmentation treatment. One hundred and forty-three crore targets impact PI3K-Akt, MAPK signaling pathway, ect. pathways. TCMM reduced UVB-induced pigmentation, water loss, epidermal thickness, and melanin. It inhibited TYR, MITF, AKT1, VEGFA, PTGS2, TNF-α, IL-6, IL-1β. Clinical and microscopic analysis showed significant pigmentation reduction.
CONCLUSIONS: The treatment of solar lentigo can benefit from the TCMM. By targeting multiple factors and pathways, this approach offers a comprehensive and effective treatment strategy.

BACKGROUND: Asparagus species are naturally distributed worldwide and are known for their pharmacological properties that offer cures for various ailments. However, the metabolic choreography of these Asparagus species is not well characterized, and the compounds contributing to their bioactivities remain unknown.
OBJECTIVE: This study aimed to profile and compare the metabolomes of three Asparagus species cladodes using different solvent extractions.
METHODS: An ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based metabolomics and molecular networking approach was used to study the effects of different solvents (ethyl acetate, methanol, and chloroform) with varying polarity on metabolites extraction and identification of bioactive compounds from three Asparagus species cladodes (Asparagus falcatus, Asparagus plumosus, and Asparagus densiflorus \'Meyersii\').
RESULTS: Multivariate statistical analyses (mainly principal component analysis) revealed a significant separation between the three solvents and the three species, indicating notable metabolic differences. A total of 118 metabolites were identified in the three species extracted with the different solvents, with methanolic and chloroform extracts containing more metabolites compared with ethyl acetate extracts. These metabolites were identified as belonging to the flavonoids, cinnamic acids, organooxygen compounds, steroids, fatty acids, benzenes, and glycerophospholipids compound classes. Furthermore, these compounds classes were differentially distributed among the three species, indicating chemical/chemotaxis differences between the compared species. Chloroform and methanol are recommended as the optimal solvents to obtain a high content of phytochemical compounds from Asparagus species cladodes.

Blast-induced trauma is emerging as a serious threat due to its wide pathophysiology where not only the brain but also a spectrum of organs is being affected. In the present study, we aim to identify the plasma-based metabolic dysregulations along with the associated temporal changes at 5-6 h, day 1 and day 7 post-injury in a preclinical animal model for blast exposure, through liquid chromatography-mass spectrometry (LC-MS). Using significantly advanced metabolomic and statistical bioinformatic platforms, we were able to elucidate better and unravel the complex networks of blast-induced neurotrauma (BINT) and its interlinked systemic effects. Significant changes were evident at 5-6 h with maximal changes at day 1. Temporal analysis also depicted progressive changes which continued till day 7. Significant associations of metabolic markers belonging to the class of amino acids, energy-related molecules, lipids, vitamin, hormone, phenolic acid, keto and histidine derivatives, nucleic acid molecules, uremic toxins, and uronic acids were observed. Also, the present study is the first of its kind where comprehensive, detailed pathway dysregulations of amino acid metabolism and biosynthesis, perturbed nucleotides, lipid peroxidation, and nucleic acid damage followed by correlation networking and multiomics networking were explored on preclinical animal models exposed to mild blast trauma. In addition, markers for systemic changes (renal dysfunction) were also observed. Global pathway predictions of unannotated peaks also presented important insights into BINT pathophysiology. Conclusively, the present study depicts important findings that might help underpin the biological mechanisms of blast-induced brain or systemic trauma.

UNASSIGNED: Parkinson\'s disease (PD) is a common neurodegenerative disease that severely affects patients\' daily lives and places a significant burden on the global economy. There are currently no specific biomarkers for distinguishing between the different stages of PD.
UNASSIGNED: We divided 78 mice into six equal groups, including five model PD groups (W1-W5; based on the PD stage induced by length of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/propofol induction time) and a control group. Then, we used metabolomics technology to detect the serum small-molecule metabolites present in each group. Ultimately, we screened for potential biomarkers using the variable importance in the projection of the orthogonal partial least squares discriminant analysis and the coefficient value of LASSO ordinal logistic regression.
UNASSIGNED: We identified 12 potential biomarkers, including dehydroepiandrosterone sulfate, pipecolic acid, N-acetylleucine, 2-aminoadipic acid, L-tyrosine, uric acid, and 5-hydroxyindoleacetaldehyde. Pathway analysis revealed their involvement in amino acid metabolism, caffeine metabolism, steroid hormone biosynthesis, and purine metabolism. Additionally, the receiver operating characteristic curve indicated that a biomarker panel comprising the 12 biomarkers could differentiate between the different PD stages.
UNASSIGNED: Different PD stages are characterized by different metabolites. The biomarkers identified in this study are helpful to understand the PD process.

BACKGROUND: This study aimed to examine the differential variations in the metabolic composition of follicular fluid (FF) among normal-weight patients with polycystic ovary syndrome (PCOS) and controls and to identify potential biomarkers that may offer insights into the early identification and management of these patients.
METHODS: We collected FF samples from 45 normal-weight women with PCOS and 36 normal-weight controls without PCOS who were undergoing in vitro fertilization-embryo transfer. An untargeted metabolomic study of collected FF from infertile women was performed using high-performance liquid chromatography-tandem spectrometry (LC-MS). The tendency of the two groups to separate was demonstrated through multivariate analysis. Univariate analysis and variable importance in projection were used to screen out differential metabolites. Metabolic pathway analysis was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG), and a diagnostic model was established using the random forest algorithm.
RESULTS: The metabolomics analysis revealed an increase in the expression of 23 metabolites and a decrease in that of 10 metabolites in the FF of normal-weight women with PCOS. According to the KEGG pathway analysis, these differential metabolites primarily participated in the metabolism of glycerophospholipids and the biosynthesis of steroid hormones. Based on the biomarker combination of the top 10 metabolites, the area under the curve value was 0.805. The concentrations of prostaglandin E2 in the FF of individuals with PCOS exhibited an inverse association with the proportion of high-quality embryos (p < 0.05).
CONCLUSIONS: Our research identified a distinct metabolic profile of the FF from normal-weight women with PCOS. The results offer a broader comprehension of the pathogenesis and advancement of PCOS, and the detected differential metabolites could be potential biomarkers and targets for the treatment of PCOS.

Both experimental and clinical liver fibrosis leave a metabolic footprint that can be uncovered and defined using metabolomic approaches. Metabolomics combines pattern recognition algorithms with analytical chemistry, in particular, 1H and 13C nuclear magnetic resonance spectroscopy (NMR), gas chromatography-mass spectrometry (GC-MS) and various liquid chromatography-mass spectrometry (LC-MS) platforms. The analysis of liver fibrosis by each of these methodologies is reviewed separately. Surprisingly, there was little general agreement between studies within each of these three groups and also between groups. The metabolomic footprint determined by NMR (two or more hits between studies) comprised elevated lactate, acetate, choline, 3-hydroxybutyrate, glucose, histidine, methionine, glutamine, phenylalanine, tyrosine and citrate. For GC-MS, succinate, fumarate, malate, ascorbate, glutamate, glycine, serine and, in agreement with NMR, glutamine, phenylalanine, tyrosine and citrate were delineated. For LC-MS, only β-muricholic acid, tryptophan, acylcarnitine, p-cresol, valine and, in agreement with NMR, phosphocholine were identified. The metabolomic footprint of liver fibrosis was upregulated as regards glutamine, phenylalanine, tyrosine, citrate and phosphocholine. Several investigators employed traditional Chinese medicine (TCM) treatments to reverse experimental liver fibrosis, and a commentary is given on the chemical constituents that may possess fibrolytic activity. It is proposed that molecular docking procedures using these TCM constituents may lead to novel therapies for liver fibrosis affecting at least one-in-twenty persons globally, for which there is currently no pharmaceutical cure. This in-depth review summarizes the relevant literature on metabolomics and its implications in addressing the clinical problem of liver fibrosis, cirrhosis and its sequelae.

More than seventy-five isotypes of α-1-antitrypsin (AAT) have been described. To assess risks associated with AAT deficiency, isotype identification is necessary. Isoelectric focusing (IEF) is traditionally used for isotype differentiation, however, IEF has limited scope since it is a manual procedure that is not suitable for automation, and antitrypsin variants must differ in net charge in order to be resolved. In comparison, mass spectrometric assays are easily automated and offer a more complete solution for characterization of proteins. To capitalize on these advantages, we have developed a qualitative top-down liquid chromatography-mass spectrometry (LC-MS) method for selective phenotyping of AAT. This technique requires no sample pretreatment, and has the potential for use in routine clinical diagnostics. We have validated our LC-MS results against both DNA sequencing and IEF. Thus far, this method has identified the AAT variants PLowell, S and Z, as well as unique fragments shared by different M alleles. Its high selectivity is indirectly illustrated by the detection of a variant carrying the amino acid substitution p.Ala308Ser, which cannot be visualized by IEF.

Liquid chromatography-mass spectrometry (LC-MS) has emerged as a powerful analytical technique for analyzing complex biological samples. Among various chromatographic stationary phases, porous graphitic carbon (PGC) columns have attracted significant attention due to their unique properties-such as the ability to separate both polar and non-polar compounds and their stability through all pH ranges and to high temperatures-besides the compatibility with LC-MS. This review discusses the applicability of PGC for SPE and separation in LC-MS-based analyses of human biological samples, highlighting the diverse applications of PGC-LC-MS in analyzing endogenous metabolites, pharmaceuticals, and biomarkers, such as glycans, proteins, oligosaccharides, sugar phosphates, and nucleotides. Additionally, the fundamental principles underlying PGC column chemistry and its advantages, challenges, and advances in method development are explored. This comprehensive review aims to provide researchers and practitioners with a valuable resource for understanding the capabilities and limitations of PGC columns in LC-MS-based analysis of human biological samples, thereby facilitating advancements in analytical methodologies and biomedical research.

Solanaceous plants, such as Solanum dulcamara, produce steroidal glycosides (SGs). Leaf SG profiles vary among S. dulcamara individuals, leading to distinct phytochemical phenotypes (\'chemotypes\') and intraspecific phytochemical diversity (\'chemodiversity\'). However, if and how SG chemodiversity varies among organs and across ontogeny, and how this relates to SG metabolism gene expression is unknown. Among organs and across ontogeny, S. dulcamara plants with saturated (S) and unsaturated (U) SG leaf chemotypes were selected and clonally propagated. Roots, stems and leaves were harvested from vegetative and flowering plants. Extracts were analysed using untargeted LC-MS. Expression of candidate genes in SG metabolism (SdGAME9, SdGAME4, SdGAME25, SdS5αR2 and SdDPS) was analysed using RT-qPCRs. Our analyses showed that SG chemodiversity varies among organs and across ontogeny in S. dulcamara; SG richness (Dmg) was higher in flowering than vegetative plants. In vegetative plants, Dmg was higher for leaves than for roots. Lack of SdGAME25 expression in U-chemotype leaves, while readily expressed in roots and stems, suggests a pivotal role for SdGAME25 in differentiation of leaf chemotypes in vegetative and flowering plants. By acting as an ontogeny-dependent chemotypic switch, differential regulation of SdGAME25 enables adaptive allocation of SGs, thereby increasing SG chemodiversity in leaves. This indicates that differential expression and/or regulation of glycoalkaloid metabolism genes, rather than their presence or absence, explains observed chemotypic variation in SG chemodiversity among organs and across ontogeny.

Tryptophan (an essential amino acid) and its clinically important metabolite-kynurenine contribute to several fundamental biological processes and methods that allow their determination in biological samples are in demand. The novelty of the work was a demonstration of the utility of two polymers: 4-vinylpyridine crosslinked with trimethylolpropane trimethacrylate (poly(4VP-co-TRIM)) or 1,4-dimethacryloyloxybenzene (poly(4VP-co-14DMB))-in terms of human serum clean-up for simultaneous LC-MS determination of tryptophan and kynurenine. The goal was to achieve a reduction of the matrix effect, which is responsible for signal suppression, with minimal capture of analytes. The adsorption properties of the polymeric beads were studied by evaluating the adsorption kinetics and isotherms in model matrices. Therefore, the adsorption capacities of both molecules were not efficient, the tested 4-vinylpyridine-based copolymers have shown great promise (especially poly(4VP-co-TRIM)) as sorbents for serum clean-up. In the model human serum matrix, poly(4VP-co-TRIM) provided good recoveries of tryptophan and kynurenine (76% and 87%, respectively) and allowed for the reduction of the matrix effect. Performances of both copolymers were compared to those of commercially available sorbents (octadecylsilane, activated charcoal, and primary secondary amine).