Identifying ligands directly interacting with target protein in medicinal herbs by metabolomic analysis of T2-filtered HSQC spectra.

A protocol for efficiently identifying ligands directly interacting with a target protein in complex extracts of medicinal herbs was proposed by combining an adapted 2D perfect-echo Carr-Purcell-Meiboom-Gill heteronuclear single quantum correlation (PE-CPMG HSQC) spectrum with metabolomic analysis. PE-CPMG HSQC can suppress the signal interference from the target protein, allowing more accurate peak quantification than conventional HSQC. Inspired from untargeted metabolomics, regions of interest (ROIs) are constructed and quantified for the mixture or complex extract samples with and without a target protein, and then a binding index (BI) of each ROI is determined. ROIs or corresponding peaks significantly perturbed by the presence of the target protein (BI ≥1.5) are detected as differential features, and potential binding ligands identified from the differential features can be equated with bioactive markers associated with the 'treatment' of the target protein. Quantifying ROI can inclusively report the ligand bindings to a target protein in fast, intermediate and slow exchange regimes on nuclear magnetic resonance (NMR) time scale. The approach was successfully implemented and identified Angoroside C, Cinnamic acid and Harpagoside from the extract of Scrophularia ningpoensis Hemsl. as ligands binding to peroxisome proliferator-activated receptor γ. The proposed 2D NMR-based approach saves excess steps for sample processing and has a higher chance of detecting the weaker ligands in the complex extracts of medicinal herbs. We expect that this approach can be applied as an alternative to mining the potential ligands binding to a variety of target proteins from traditional Chinese medicines and herbal extracts.

Metabolomics research on treatment of primary liver cancer with Cortex Juglandis Mandshuricae on LC-MS/MS technology.

Diethylnitrosamine (DEN) was applied to create the primary liver cancer (PLC) animal model. In the study, the normal group, model group, cyclophosphamide (CTX) group, Cortex Juglandis Mandshuricae (CJM) extract group, myricetin group and myricitrin group were divided. LC-MS/MS technology was applied to determine the metabolites of liver tissue samples from different locations (nodular and non-nodular parts of liver tissue) in each group of rats. Through metabolomics research, the connection and difference of anti-PLC induced by the CJM extract, myricetin and myricitrin was analyzed. The surface of the liver tissues of rats in the model group was rough, dimly colored, inelastic, on which there were scattered gray white cancer nodules and blood stasis points. The number of cancer nodules was significantly reduced, and the degree of cell malignancy was low, but there were some inflammatory cell infiltrations, necrosis area and karyokinesis in the CJM extract group, myricetin group, myricitrin group and CTX group. The result of metabolic research indicated that 45 potential biomarkers of the PLC were found, as gamma-aminoisobutyrate, taurochenodeoxycholate, xanthurenic acid, etc. There were 22 differential metabolites in the CTX group, 16 differential metabolites in the CJM extract group, 14 differential metabolites in the myricetin group, 14 differential metabolites in the myricitrin group.

Multi-omic applications for understanding and enhancing tropical fruit flavour.

Consumer trends towards nutrient-rich foods are contributing to global increasing demand for tropical fruit. However, commercial cultivars in the breeding pipeline that are tailored to meet market demand are at risk of possessing reduced fruit flavour qualities. This stems from recurrent prioritised selection for superior agronomic traits and not fruit flavour, which may in turn reduce consumer satisfaction. There is realisation that fruit quality traits, inclusive of flavour, must be equally selected for; but currently, there are limited tools and resources available to select for fruit flavour traits, particularly in tropical fruit species. Although sugars, acids, and volatile organic compounds are known to define fruit flavour, the specific combinations of these, that result in defined consumer preferences, remain unknown for many tropical fruit species. To define and include fruit flavour preferences in selective breeding, it is vital to determine the metabolites that underpin them. Then, objective quantitative analysis may be implemented instead of solely relying on human sensory panels. This may lead to the development of selective genetic markers through integrated omics approaches that target biosynthetic pathways of flavour active compounds. In this review, we explore progress in the development of tools to be able to strategically define and select for consumer-preferred flavour profiles in the breeding of new cultivars of tropical fruit species.

Alterations in metabolome and lipidome in patients with in-stent restenosis.

CONTEXT: In-stent restenosis (ISR) can lead to blood flow obstruction, insufficient blood supply to the brain, and may even result in serious complications such as stroke. Endothelial cell hyperproliferation and thrombosis are the primary etiologies, frequently resulting in alterations in intravascular metabolism. However, the metabolic changes related to this process are still undermined. OBJECTIVE: We tried to characterize the serum metabolome of patients with ISR and those with non-restenosis (NR) using metabolomics and lipidomics, exploring the key metabolic pathways of this pathological phenomenon. RESULTS: We observed that the cysteine and methionine pathways, which are associated with cell growth and oxidative homeostasis, showed the greatest increase in the ISR group compared to the NR group. Within this pathway, the levels of N-formyl-l-methionine and L-methionine significantly increased in the ISR group, along with elevated levels of downstream metabolites such as 2-ketobutyric acid, pyruvate, and taurocholate. Additionally, an increase in phosphatidylcholine (PC) and phosphatidylserine (PS), as well as a decrease in triacylglycerol in the ISR group, indicated active lipid metabolism in these patients, which could be a significant factor contributing to the recurrence of blood clots after stent placement. Importantly, phenol sulfate and PS(38:4) were identified as potential biomarkers for distinguishing ISR, with an area under the curve of more than 0.85. CONCLUSIONS: Our study revealed significant metabolic alterations in patients with ISR, particularly in the cysteine and methionine pathways, with phenol sulfate and PS(38:4) showing promise for ISR identification.

Sleep deprivation causes gut dysbiosis impacting on systemic metabolomics leading to premature ovarian insufficiency in adolescent mice.

Rationale: Currently, there are occasional reports of health problems caused by sleep deprivation (SD). However, to date, there remains a lack of in-depth research regarding the effects of SD on the growth and development of oocytes in females. The present work aimed to investigate whether SD influences ovarian folliculogenesis in adolescent female mice. Methods: Using a dedicated device, SD conditions were established in 3-week old female mice (a critical stage of follicular development) for 6 weeks and gut microbiota and systemic metabolomics were analyzed. Analyses were related to parameters of folliculogenesis and reproductive performance of SD females. Results: We found that the gut microbiota and systemic metabolomics were severely altered in SD females and that these were associated with parameters of premature ovarian insufficiency (POI). These included increased granulosa cell apoptosis, reduced numbers of primordial follicles (PmFs), correlation with decreased AMH, E2, and increased LH in blood serum, and a parallel increased number of growing follicles and changes in protein expression compatible with PmF activation. SD also reduced oocyte maturation and reproductive performance. Notably, fecal microbial transplantation from SD females into normal females induced POI parameters in the latter while niacinamide (NAM) supplementation alleviated such symptoms in SD females. Conclusion: Gut microbiota and alterations in systemic metabolomics caused by SD induced POI features in juvenile females that could be counteracted with NAM supplementation.

Changes in the serum metabolomics of polycystic ovary syndrome before and after compound oral contraceptive treatment.

Background: Polycystic ovary syndrome (PCOS) is both a common endocrine syndrome and a metabolic disorder that results in harm to the reproductive system and whole-body metabolism. This study aimed to investigate differences in the serum metabolic profiles of patients with PCOS compared with healthy controls, in addition to investigating the effects of compound oral contraceptive (COC) treatment in patients with PCOS. Materials and methods: 50 patients with PCOS and 50 sex-matched healthy controls were recruited. Patients with PCOS received three cycles of self-administered COC treatment. Clinical characteristics were recorded, and the laboratory biochemical data were detected. We utilized ultra-performance liquid chromatography-high-resolution mass spectrometry to study the serum metabolic changes between patients with PCOS, patients with PCOS following COC treatment, and healthy controls. Result: Patients with PCOS who received COC treatment showed significant improvements in serum sex hormone levels, a reduction in luteinising hormone levels, and a significant reduction in the levels of biologically active free testosterone in the blood. Differential metabolite correlation analysis revealed differences between PCOS and healthy control groups in N-tetradecanamide, hexadecanamide, 10E,12Z-octadecadienoic acid, and 13-HOTrE(r); after 3 months of COC treatment, there were significant differences in benzoic acid, organic acid, and phenolamides. Using gas chromatography-mass spectrometry to analyse blood serum in each group, the characteristic changes in PCOS were metabolic disorders of amino acids, carbohydrates, and purines, with significant changes in the levels of total cholesterol, uric acid, phenylalanine, aspartic acid, and glutamate. Conclusion: Following COC treatment, improvements in sex hormone levels, endocrine factor levels, and metabolic levels were better than in the group of PCOS patients receiving no COC treatment, indicating that COC treatment for PCOS could effectively regulate the levels of sex hormones, endocrine factors, and serum metabolic profiles.

Metabolomic profiling of upper GI malignancies in blood and tissue: a systematic review and meta-analysis.

OBJECTIVE: To conduct a systematic review and meta-analysis of case-control and cohort human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on esophageal cancer (EC), cancer of the gastroesophageal junction (GEJ), and gastric cancer (GC) in blood and tissue. BACKGROUND: Upper gastrointestinal cancers (UGC), predominantly EC, GEJ, and GC, are malignant tumour types with high morbidity and mortality rates. Numerous studies have focused on metabolomic profiling of UGC in recent years. In this systematic review and meta-analysis, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with EC, GEJ and GC. METHODS: Following the PRISMA procedure, a systematic search of four databases (Embase, PubMed, MEDLINE, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of EC, GEJ and GC was conducted and registered at PROSPERO (CRD42023486631). The Newcastle-Ottawa Scale (NOS) was used to benchmark the risk of bias for case-controlled and cohort studies. QUADOMICS, an adaptation of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy) tool, was used to rate diagnostic accuracy studies. Original articles comparing metabolite patterns between patients with and without UGC were included. Two investigators independently completed title and abstract screening, data extraction, and quality evaluation. Meta-analysis was conducted whenever possible. We used a random effects model to investigate the association between metabolite levels and UGC. RESULTS: A total of 66 original studies involving 7267 patients that met the required criteria were included for review. 169 metabolites were differentially distributed in patients with UGC compared to healthy patients among 44 GC, 9 GEJ, and 25 EC studies including metabolites involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and lipid metabolism. Phosphatidylcholines, eicosanoids, and adenosine triphosphate were among the most frequently reported lipids and metabolites of cellular respiration, while BCAA, lysine, and asparagine were among the most commonly reported amino acids. Previously identified lipid metabolites included saturated and unsaturated free fatty acids and ketones. However, the key findings across studies have been inconsistent, possibly due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group. CONCLUSION: Thus far, metabolomic studies have provided new opportunities for screening, etiological factors, and biomarkers for UGC, supporting the potential of applying metabolomic profiling in early cancer diagnosis. According to the results of our meta-analysis especially BCAA and TMAO as well as certain phosphatidylcholines should be implicated into the diagnostic procedure of patients with UGC. We envision that metabolomics will significantly enhance our understanding of the carcinogenesis and progression process of UGC and may eventually facilitate precise oncological and patient-tailored management of UGC.

Metagenomic and metabolomic analysis showing the adverse risk-benefit trade-off of the ketogenic diet.

BACKGROUND: Ketogenic diets are increasingly popular for addressing obesity, but their impacts on the gut microbiota and metabolome remain unclear. This paper aimed to investigate how a ketogenic diet affects intestinal microorganisms and metabolites in obesity. METHODS: Male mice were provided with one of the following dietary regimens: normal chow, high-fat diet, ketogenic diet, or high-fat diet converted to ketogenic diet. Body weight and fat mass were measured weekly using high-precision electronic balances and minispec body composition analyzers. Metagenomics and non-targeted metabolomics data were used to analyze differences in intestinal contents. RESULTS: Obese mice on the ketogenic diet exhibited notable improvements in weight and body fat. However, these were accompanied by a significant decrease in intestinal microbial diversity, as well as an increase in Firmicutes abundance and a 247% increase in the Firmicutes/Bacteroidetes ratio. The ketogenic diet also altered multiple metabolic pathways in the gut, including glucose, lipid, energy, carbohydrate, amino acid, ketone body, butanoate, and methane pathways, as well as bacterial secretion and colonization pathways. These changes were associated with increased intestinal inflammation and dysbiosis in obese mice. Furthermore, the ketogenic diet enhanced the secretion of bile and the synthesis of aminoglycoside antibiotics in obese mice, which may impair the gut microbiota and be associated with intestinal inflammation and immunity. CONCLUSIONS: The study suggest that the ketogenic diet had an unfavorable risk-benefit trade-off and may compromise metabolic homeostasis in obese mice.

Plant Tissue Culture and Metabolite Profiling for High-Value Natural Product Synthesis.

The engineering of plant cell cultures to produce high-value natural products is suggested to be a safe, low-cost, and environmentally friendly route to produce a wide range of chemicals. Given that the expression of heterologous biosynthetic pathways in plant tissue culture is limited by a lack of detailed protocols, the biosynthesis of high-value metabolites in plant cell culture is constrained compared with that in microbes. However, both Arabidopsis thaliana and Nicotiana benthamiana can be efficiently transformed with multigene constructs to produce high-value natural products in stable plant cell cultures. This chapter provides a detailed protocol as to how to engineer the plant cell culture as bio-factories for metabolite biosynthesis.

Sepsis Research Using Omics Technology in the European Union and the United Kingdom: Maps, Trends, and Future Implications.

High-throughput omics technologies have become valuable tools for systems science research and clinical management of sepsis. This article analyzes sepsis research using omics technologies in the European Union (EU) and the United Kingdom from 1990 to May 2023 using bibliometric data from the Web of Science database. Using VOSviewer for network analysis, we examined the distribution patterns, funding characteristics, and collaborations among the states, noting trends of convergence and divergence. The analysis included 2078 articles, revealing an increasing rate of publications on sepsis research using omics approaches. The United Kingdom's research output is notably high, contributing 28.3% of the total research from the EU and United Kingdom combined. Germany, France, the Netherlands, and Italy together account for 56.9% of the publications from the EU member states. The United States is the leading international collaborator, particularly with the United Kingdom, followed by Germany and France. The EU-15 countries have significantly more publication outputs in this domain with growing but limited inclusion of the newer members of the EU. We suggest that the role of EU member states and the United Kingdom in sepsis research using omics technologies can be advanced by facilitating high-value, technology-driven health research, fostering collaboration, convergence, and equity in global health and biomedical research.

Untargeted metabolomic profiling of Prinsepia utilis Royle leaves by Ultra-Performance Liquid Chromatography-Quadrupole-Time of Flight-Mass Spectrometry.

Prinsepia utilis Royle, native to the Himalayas, is esteemed in Chinese and Indian folk medicine for its diverse medicinal benefits, targeting arthritis, pain relief, bone disorders, and joint discomfort. This study examined the 25% aqueous methanol extract of P. utilis leaves using UPLC-Q-TOF-MS/MS, identifying 78 metabolites, 76 of which were reported for the first time in P. utilis. These included 64 phenolics represented by 56 flavonoids, 5 phenolic acids, 3 phenolic glycosides, 4 terpenoids, 2 lignan glycosides, and 8 other compounds, expanding the knowledge of its chemical composition. These findings lay a foundation for further research, providing insights into potential bioactive compounds and opening avenues for applications in natural product drug discovery, traditional medicine, and nutraceutical development, leveraging the plant's established traditional uses.

Opportunities and Challenges in Advancing Plant Research with Single-cell Omics.

Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of nature. Various strategies have been employed to study cell types and their developmental progressions, including single-cell sequencing methods which provide high-dimensional catalogs to address biological concerns. In recent years, single-cell sequencing technologies in transcriptomics, epigenomics, proteomics, metabolomics, and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell level. However, the application of single-cell technologies to plants is more limited due to the challenges posed by cell structure. This review outlines the advancements in single-cell omics technologies, their implications in plant systems, future research applications, and the challenges of single-cell omics in plant systems.

Plasma metabolites are altered before and after diagnosis of preeclampsia or fetal growth restriction.

Metabolomics is the study of small molecules (metabolites), within cells, tissues and biofluids. Maternal metabolites can provide important insight into the health and development of both mother and fetus throughout pregnancy. This study assessed metabolic profiles in the maternal circulation prior to and at the time of diagnosis of preeclampsia and fetal growth restriction. Maternal plasma samples were collected from two independent cohorts: (1) Established disease cohort: 50 participants diagnosed with early-onset preeclampsia (< 34 weeks' gestation), 14 with early-onset fetal growth restriction, and 25 gestation-matched controls. (2) Prospective cohort, collected at 36 weeks' gestation before diagnosis: 17 participants later developed preeclampsia, 49 delivered infants with fetal growth restriction (birthweight < 5th centile), and 72 randomly selected controls. Metabolic evaluation was performed by Metabolomics Australia on the Agilent 6545 QTOF Mass Spectrometer. In the established disease cohort, 77 metabolites were altered in circulation from participants with preeclampsia - increased L-cysteine (3.73-fold), L-cystine (3.28-fold), L-acetylcarnitine (2.57-fold), and carnitine (1.53-fold) (p < 0.05). There were 53 metabolites dysregulated in participants who delivered a fetal growth restriction infant-including increased levulinic acid, citric acid (1.93-fold), and creatine (1.14-fold) (p < 0.05). In the prospective cohort, 30 metabolites were altered in participants who later developed preeclampsia at term - reduced glutaric acid (0.85-fold), porphobilinogen (0.77-fold) and amininohippuric acid (0.82-fold) (p < 0.05) was observed. There were 5 metabolites altered in participants who later delivered a fetal growth restriction infant - including reduced 3-methoxybenzenepropanoic acid (p < 0.05). Downstream pathway analysis revealed aminoacyl-tRNA biosynthesis to be most significantly altered in the established cohort in preeclampsia (13/48 hits, p < 0.001) and fetal growth restriction (7/48 hits, p < 0.001). The predictive cohort showed no significant pathway alterations. This study observed altered metabolites in maternal plasma collected before and after diagnosis of a preeclampsia or fetal growth restriction. While a significant number of metabolites were altered with established disease, few changes were observed in the predictive cohort. Thus, metabolites measured in this study may not be useful as predictors of preeclampsia or fetal growth restriction.

Plasma metabolomics identifies differing endotypes of recurrent wheezing in preschool children differentiated by symptoms and social disadvantage.

Preschool children with recurrent wheezing are a heterogeneous population with many underlying biological pathways that contribute to clinical presentations. Although the morbidity of recurrent wheezing in preschool children is significant, biological studies in this population remain quite limited. To address this gap, this study performed untargeted plasma metabolomic analyses in 68 preschool children with recurrent wheezing to identify metabolomic endotypes of wheezing. K-means cluster analysis was performed on metabolomic dataset including a total of 1382 named and unnamed metabolites. We identified three metabolomic clusters which differed in symptom severity, exacerbation occurrence, and variables associated with social disadvantage. Metabolites that distinguished the clusters included those involved in fatty acid metabolism, fatty acids (long chain monounsaturated fatty acids, long chain polyunsaturated fatty acids, and long chain saturated fatty acids), lysophospholipids, phosphatidylcholines, and phosphatidylethanolamines. Pathway analyses identified pathways of interest in each cluster, including steroid metabolism, histidine metabolism, sphingomyelins, and sphingosines, among others. This study highlights the biologic complexity of recurrent wheezing in preschool children and offers novel metabolites and pathways that may be amenable to future study and intervention.

Biliary atresia and cholestasis plasma non-targeted metabolomics unravels perturbed metabolic pathways and unveils a diagnostic model for biliary atresia.

The clinical diagnosis of biliary atresia (BA) poses challenges, particularly in distinguishing it from cholestasis (CS). Moreover, the prognosis for BA is unfavorable and there is a dearth of effective non-invasive diagnostic models for detection. Therefore, the aim of this study is to elucidate the metabolic disparities among children with BA, CS, and normal controls (NC) without any hepatic abnormalities through comprehensive metabolomics analysis. Additionally, our objective is to develop an advanced diagnostic model that enables identification of BA. The plasma samples from 90 children with BA, 48 children with CS, and 47 NC without any liver abnormalities children were subjected to metabolomics analysis, revealing significant differences in metabolite profiles among the 3 groups, particularly between BA and CS. A total of 238 differential metabolites were identified in the positive mode, while 89 differential metabolites were detected in the negative mode. Enrichment analysis revealed 10 distinct metabolic pathways that differed, such as lysine degradation, bile acid biosynthesis. A total of 18 biomarkers were identified through biomarker analysis, and in combination with the exploration of 3 additional biomarkers (LysoPC(18:2(9Z,12Z)), PC (22:5(7Z,10Z,13Z,16Z,19Z)/14:0), and Biliverdin-IX-α), a diagnostic model for BA was constructed using logistic regression analysis. The resulting ROC area under the curve was determined to be 0.968. This study presents an innovative and pioneering approach that utilizes metabolomics analysis to develop a diagnostic model for BA, thereby reducing the need for unnecessary invasive examinations and contributing to advancements in diagnosis and prognosis for patients with BA.

A diverse proteome is present and enzymatically active in metabolite extracts.

Metabolite extraction is the critical first-step in metabolomics experiments, where it is generally regarded to inactivate and remove proteins. Here, arising from efforts to improve extraction conditions for polar metabolomics, we discover a proteomic landscape of over 1000 proteins within metabolite extracts. This is a ubiquitous feature across several common extraction and sample types. By combining post-resuspension stable isotope addition and enzyme inhibitors, we demonstrate in-extract metabolite interconversions due to residual transaminase activity. We extend these findings with untargeted metabolomics where we observe extensive protein-mediated metabolite changes, including in-extract formation of glutamate dipeptide and depletion of total glutathione. Finally, we present a simple extraction workflow that integrates 3 kDa filtration for protein removal as a superior method for polar metabolomics. In this work, we uncover a previously unrecognized, protein-mediated source of observer effects in metabolomics experiments with broad-reaching implications across all research fields using metabolomics and molecular metabolism.

Plasma metabolomics of immune-related adverse events for patients with lung cancer treated with PD-1/PD-L1 inhibitors.

BACKGROUND: Metabolomics has the characteristics of terminal effects and reflects the physiological state of biological diseases more directly. Several current biomarkers of multiple omics were revealed to be associated with immune-related adverse events (irAEs) occurrence. However, there is a lack of reliable metabolic biomarkers to predict irAEs. This study aims to explore the potential metabolic biomarkers to predict risk of irAEs and to investigate the association of plasma metabolites level with survival in patients with lung cancer receiving PD-1/PD-L1 inhibitor treatment. METHODS: The study collected 170 plasmas of 85 patients with lung cancer who received immune checkpoint inhibitors (ICIs) treatment. 58 plasma samples of 29 patients with irAEs were collected before ICIs treatment and at the onset of irAEs. 112 plasma samples of 56 patients who did not develop irAEs were collected before ICIs treatment and plasma matched by treatment cycles to onset of irAEs patients. Untargeted metabolomics analysis was used to identify the differential metabolites before initiating ICIs treatment and during the process that development of irAEs. Kaplan-Meier curves analysis was used to detect the associations of plasma metabolites level with survival of patients with lung cancer. RESULTS: A total of 24 differential metabolites were identified to predict the occurrence of irAEs. Baseline acylcarnitines and steroids levels are significantly higher in patients with irAEs, and the model of eight acylcarnitine and six steroid metabolites baseline level predicts irAEs occurrence with area under the curve of 0.91. Patients with lower concentration of baseline decenoylcarnitine(AcCa(10:1) 2, decenoylcarnitine(AcCa(10:1) 3 and hexanoylcarnitine(AcCa(6:0) in plasma would have better overall survival (OS). Moreover, 52 differential metabolites were identified related to irAEs during ICIs treatment, dehydroepiandrosterone sulfate, corticoserone, cortisol, thyroxine and sphinganine 1-phaosphate were significantly decreased in irAEs group while oxoglutaric acid and taurocholic acid were significantly increased in irAEs group. CONCLUSIONS: High levels of acylcarnitines and steroid hormone metabolites might be risk factor to development of irAEs, and levels of decenoylcarnitine (AcCa(10:1) 2, decenoylcarnitine (AcCa(10:1) 3 and hexanoylcarnitine (AcCa(6:0) could be used to predict OS for patients with lung cancer received ICIs treatment.

GC-MS based metabolomic profiling of Aporosa cardiosperma (Gaertn.) Merr. leaf extracts and evaluating its therapeutic potential.

Aporosa cardiosperma is a plant species majorly found in the Indian Western Ghats that belongs to the phyllanthaceae family with ethnobotanical importance. Using a Fourier Transform-Infrared Spectrometer (FT-IR) and Gas Chromatography-Mass Spectrometry (GC-MS) for evaluating leaf extracts of A. cardiosperma, significant functional groups and metabolite constituents were determined, and its total flavonoid, phenol, and tannin content were quantified. Further, its antibacterial efficacy was investigated against microorganisms that cause fish and human disease and are resistant to common antibiotics, including Staphylococcus aureus, Bacillus subtilis, Mycobacterium tuberculosis, Klebsiella pneumoniae, Aeromonas hydrophila, and Pseudomonas aeruginosa. Regarding the outcomes of GC-MS analysis, the primary metabolites in the A. cardiosperma leaf extracts were heneicosane (57.06%), silane (13.60%), 1-heptadecene (10.09%), 3-hexadecene (9.99%), and pentadecane (9.54%). In comparison to other solvents, methanolic extract of A. cardiosperma leaves had increased phenolic, flavonoid, and tannin content; these findings are consistent with in vitro antioxidant potential and obtained that the methanolic extract (100 µg/mL) exhibited the higher percentage of inhibition in DPPH (82.35%), FRAP (86.20%), metal chelating (72.32%), and ABTS (86.06%) antioxidant assays respectively. Similar findings were found regarding the antibacterial efficacy against pathogenic bacteria. Comparatively, to other extracts, methanolic extracts showed more significant antibacterial activity at a lower minimum inhibitory concentration (MIC) value (250 µg/mL), whilst ethyl acetate and hexane solvent extracts of A. cardiosperma leaves had higher MIC values 500 µg/mL and 1000 µg/mL respectively. The antimicrobial potential was validated by investigating bacterial growth through the extracts acquired MICs and sub-MICs range. Bacterial growth was completely inhibited at the determined MIC range. In conclusion, A. cardiosperma leaf extract's phytochemical fingerprint has been determined, and its potent antibacterial and antioxidant activities were discovered. These findings of the current study will pave the way for developing herbal treatments from A. cardiosperma for various fish and human diseases.

Progress and perspectives of metabolic biomarkers in human aortic dissection.

BACKGROUND: Aortic dissection (AD) significantly threated human cardiovascular health, extensive clinical-scientific research programs have been executed to uncover the pathogenesis and prevention. Unfortunately, no specific biomarker was identified for the causality or development of human AD. AIM OF REVIEW: Metabolomics, a high-throughput technique capable of quantitatively detecting metabolites, holds considerable promise in discovering specific biomarkers and unraveling the underlying pathways involved. Aiming to provide a metabolite prediction in human AD, we collected the metabolomics data from 2003 to 2023, and diligently scrutinized with the online system MetaboAnalyst 6.0. KEY SCIENTIFIC CONCEPTS OF REVIEW: Based on the data obtained, we have concluded the metabolic dynamics were highly correlated with human AD. Such metabolites (choline, serine and uridine) were frequently involved in the AD. Besides, the pathways, including amino acids metabolism and lipids metabolism, were also dysregulated in the disease. Due to the current limitation of metabolism analysis, the integrative omics data including genomics, transcriptomics, and proteomics were required for developing the specific biomarker for AD.

Follicular Fluid and Blood Monitorization of Infertility Biomarkers in Women with Endometriosis.

Infertility is recognized globally as a social disease and a growing medical condition, posing a significant challenge to modern reproductive health. Endometriosis, the third-most frequent gynecologic disorder, is one of the most common and intricate conditions that can lead to female infertility. Despite extensive research, the etiology, malignant transformation, and biological therapy of endometriosis remain unknown. Blood and follicular fluid are two matrices that have been carefully studied and can provide insights into women's health. These matrices are clinically significant because they contain metabolites closely associated with women's illness stage and reproductive outcomes. Nowadays, the application of metabolomic analysis in biological matrices may be able to predict the outcome of assisted reproductive technologies with greater precision. From a molecular viewpoint on reproductive health, we evaluate and compare the utilization of human follicular fluid and blood as matrices in analysis for diagnostic and assisted reproductive technology (ART) predictors of success for endometriosis patients. In the follicular fluid (FF), plasma, and serum of endometriosis-affected women, researchers identified dysregulations of oxidative stress, upregulation of several immune factors, and aberrations in energy metabolic pathways. The altered signatures negatively correlate with the overall oocyte and embryo quality and fertilization rate.