PubMed

Sci Adv. 2023 Jun 16;9(24):eadh4299. doi: 10.1126/sciadv.adh4299. Epub 2023 Jun 14.ABSTRACTNature has evolved eight different pathways for the capture and conversion of CO2, including the Calvin-Benson-Bassham cycle of photosynthesis. Yet, these pathways underlie constrains and only represent a fraction of the thousands of theoretically possible solutions. To overcome the limitations of natural evolution, we introduce the HydrOxyPropionyl-CoA/Acrylyl-CoA (HOPAC) cycle, a new-to-nature CO2-fixation pathway that was designed through metabolic retrosynthesis around the reductive carboxylation of acrylyl-CoA, a highly efficient principle of CO2 fixation. We realized the HOPAC cycle in a step-wise fashion and used rational engineering approaches and machine learning-guided workflows to further optimize its output by more than one order of magnitude. Version 4.0 of the HOPAC cycle encompasses 11 enzymes from six different organisms, converting ~3.0 mM CO2 into glycolate within 2 hours. Our work moves the hypothetical HOPAC cycle from a theoretical design into an established in vitro system that forms the basis for different potential applications.PMID:37315145 | DOI:10.1126/sciadv.adh4299

Anal Chem. 2023 Jun 14. doi: 10.1021/acs.analchem.3c00764. Online ahead of print.ABSTRACTPeak-detection algorithms currently used to process untargeted metabolomics data were designed to maximize sensitivity at the sacrifice of selectively. Peak lists returned by conventional software tools therefore contain a high density of artifacts that do not represent real chemical analytes, which, in turn, hinder downstream analyses. Although some innovative approaches to remove artifacts have recently been introduced, they involve extensive user intervention due to the diversity of peak shapes present within and across metabolomics data sets. To address this bottleneck in metabolomics data processing, we developed a semisupervised deep learning-based approach, PeakDetective, for classification of detected peaks as artifacts or true peaks. Our approach utilizes two techniques for artifact removal. First, an unsupervised autoencoder is used to extract a low-dimensional, latent representation of each peak. Second, a classifier is trained with active learning to discriminate between artifacts and true peaks. Through active learning, the classifier is trained with less than 100 user-labeled peaks in a matter of minutes. Given the speed of its training, PeakDetective can be rapidly tailored to specific LC/MS methods and sample types to maximize performance on each type of data set. In addition to curation, the trained models can also be utilized for peak detection to immediately detect peaks with both high sensitivity and selectivity. We validated PeakDetective on five diverse LC/MS data sets, where PeakDetective showed greater accuracy compared to current approaches. When applied to a SARS-CoV-2 data set, PeakDetective enabled more statistically significant metabolites to be detected. PeakDetective is open source and available as a Python package at https://github.com/pattilab/PeakDetective.PMID:37314824 | DOI:10.1021/acs.analchem.3c00764

Probiotics Antimicrob Proteins. 2023 Jun 14. doi: 10.1007/s12602-023-10101-6. Online ahead of print.ABSTRACTProbiotics are used to prevent antibiotic-associated diarrhea (AAD) via the restoration of the gut microbiota. However, the precise effects of Akkermansia muciniphila (Akk), which is a promising probiotics, on AAD are unknown. Here, AAD models were established via the administration of lincomycin and ampicillin with or without pasteurized Akk or Amuc_1100 treatment. A diffusion test revealed that Akk was susceptible to the majority of the antibiotics, such as ampicillin. These effects were confirmed by the reduced Akk abundance in AAD model mice. Pasteurized Akk or Amuc_1100 significantly decreased the diarrhea status score and colon injury of AAD model mice. Additionally, these treatments significantly decreased the relative abundance of Citrobacter at genus level and reshaped the metabolic function of gut microbiota. Notably, pasteurized Akk or Amuc_1100 significantly changed the serum metabolome of AAD model mice. In addition, pasteurized Akk or Amuc_1100 suppressed intestinal inflammation by upregulating the expression of GPR109A and SLC5A8 and downregulating the expression of TNFα, IFNγ, IL1β, and IL6. Furthermore, they enhanced water and electrolyte absorption by upregulating AQP4, SLC26A3, and NHE3. Pasteurized Akk or Amuc_1100 also restored intestinal barrier function by ameliorating the downregulation of ZO-1, OCLN, CLDN4, and Muc2 in AAD model mice. In summary, optimizing intestinal health with pasteurized Akk or Amuc_1100 may serve as an approach for preventing AAD.PMID:37314693 | DOI:10.1007/s12602-023-10101-6

Anal Chem. 2023 Jun 14. doi: 10.1021/acs.analchem.3c01072. Online ahead of print.ABSTRACTUntargeted mass spectrometry is a robust tool for biology, but it usually requires a large amount of time on data analysis, especially for system biology. A framework called Multiple-Chemical nebula (MCnebula) was developed herein to facilitate the LC-MS data analysis process by focusing on critical chemical classes and visualization in multiple dimensions. This framework consists of three vital steps as follows: (1) abundance-based classes (ABC) selection algorithm, (2) critical chemical classes to classify "features" (corresponding to compounds), and (3) visualization as multiple Child-Nebulae (network graph) with annotation, chemical classification, and structure. Notably, MCnebula can be used to explore the classification and structural characteristic of unknown compounds beyond the limit of the spectral library. Moreover, it is intuitive and convenient for pathway analysis and biomarker discovery because of its function of ABC selection and visualization. MCnebula was implemented in the R language. A series of tools in R packages were provided to facilitate downstream analysis in an MCnebula-featured way, including feature selection, homology tracing of top features, pathway enrichment analysis, heat map clustering analysis, spectral visualization analysis, chemical information query, and output analysis reports. The broad utility of MCnebula was illustrated by a human-derived serum data set for metabolomics analysis. The results indicated that "Acyl carnitines" were screened out by tracing structural classes of biomarkers, which was consistent with the reference. A plant-derived data set was investigated to achieve a rapid annotation and discovery of compounds in E. ulmoides.PMID:37314081 | DOI:10.1021/acs.analchem.3c01072

Am J Sports Med. 2023 Jun 14:3635465231177890. doi: 10.1177/03635465231177890. Online ahead of print.ABSTRACTBACKGROUND: An Achilles tendon rupture (ATR) is a frequent injury and results in the activation of tendon cells and collagen expression, but it is unknown to what extent turnover of the tendon matrix is altered before or after a rupture.PURPOSE/HYPOTHESIS: The purpose of this study was to characterize tendon tissue turnover before and immediately after an acute rupture in patients. It was hypothesized that a rupture would result in pronounced collagen synthesis in the early phase (first 2 weeks) after the injury.STUDY DESIGN: Cross-sectional study; Level of evidence, 3.METHODS: The study included patients (N = 18) eligible for surgery after an ATR. At the time of inclusion, the patients ingested deuterium oxide (2H2O) orally, and on the day of surgery (within 14 days of the injury), they received a 3-hour flood-primed infusion of an 15N-proline tracer. During surgery, the patients had 1 biopsy specimen taken from the ruptured part of the Achilles tendon and 1 that was 3 to 5 cm proximal to the rupture as a control. The biopsy specimens were analyzed for carbon-14 (14C) levels in the tissue to calculate long-term turnover (years), incorporation of 2H-alanine (from 2H2O) into the tissue to calculate the fractional synthesis rate (FSR) of proteins in the short term (days), and incorporation of 15N-proline into the tissue to calculate the acute FSR (hours).RESULTS: Both the rupture and the control samples showed consistently lower levels of 14C compared with the predicted level of 14C in a healthy tendon, which indicated increased tendon turnover in a fraction (48% newly synthesized) of the Achilles tendon already for a prolonged period before the rupture. Over the first days after the rupture, the synthesis rate for collagen was relatively constant, and the average synthesis rate on the day of surgery (2-14 days after the rupture) was 0.025% per hour, irrespective of the length of time after a rupture and the site of sampling (rupture vs control). No differences were found in the FSR between the rupture and control samples in the days after the rupture.CONCLUSION: Higher than normal tissue turnover in the Achilles tendon before a rupture indicated that changes in the tendon tissue preceded the injury. In addition, we observed no increase in tendon collagen tissue turnover in the first 2 weeks after an ATR. This favors the view that an increase in the formation of new tendon collagen is not an immediate phenomenon during the regeneration of ruptured tendons in patients.REGISTRATION: NCT03931486 (ClinicalTrials.gov identifier).PMID:37313851 | DOI:10.1177/03635465231177890

Ann Neurosci. 2023 Jan;30(1):11-19. doi: 10.1177/09727531221117634. Epub 2022 Aug 27.ABSTRACTBACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder that mainly affects the aged population. Transcranial magnetic field (MF) stimulation has shown to provide temporary motor recovery in neurological disorders.PURPOSE: The aim of this study was to understand the cellular and molecular mechanism of low-intensity MF stimulation (17.96 µT; 50Hz; 2 h/day, four weeks) in a rat model of severe PD.METHODS: A clinically relevant, bilateral striatal 6-hydroxydopamine (6-OHDA) lesioned rat model of severe PD was employed to test the efficacy of low-intensity MF stimulation in the management of motor symptoms. The mechanism of action of MF was dissected by assessing the microglial activation, tissue ultrastructure, and cerebrospinal fluid (CSF) metabolomics using microdialysis.RESULTS: We observed a significant improvement in the postural balance and gait after MF exposure with a significant reduction in the number of activated microglia. There was an improvement in striatal dopaminergic innervation and glutamate levels but it did not reach a level of statistical significance.CONCLUSION: MF stimulation helped ameliorate the motor deficits and reduced inflammation but was unable to provide a significant change in terms of dopaminergic innervation and metabolic profile in the severe 6-OHDA PD rat model.PMID:37313335 | PMC:PMC10259148 | DOI:10.1177/09727531221117634

Mol Breed. 2023 Mar 2;43(3):16. doi: 10.1007/s11032-023-01361-9. eCollection 2023 Mar.ABSTRACTBreeding crop varieties with high yield and ideal plant architecture is a desirable goal of agricultural science. The success of "Green Revolution" in cereal crops provides opportunities to incorporate phytohormones in crop breeding. Auxin is a critical phytohormone to determine nearly all the aspects of plant development. Despite the current knowledge regarding auxin biosynthesis, auxin transport and auxin signaling have been well characterized in model Arabidopsis (Arabidopsis thaliana) plants, how auxin regulates crop architecture is far from being understood, and the introduction of auxin biology in crop breeding stays in the theoretical stage. Here, we give an overview on molecular mechanisms of auxin biology in Arabidopsis, and mainly summarize auxin contributions for crop plant development. Furthermore, we propose potential opportunities to integrate auxin biology in soybean (Glycine max) breeding.PMID:37313296 | PMC:PMC10248601 | DOI:10.1007/s11032-023-01361-9

Front Plant Sci. 2023 May 29;14:1208218. doi: 10.3389/fpls.2023.1208218. eCollection 2023.NO ABSTRACTPMID:37313256 | PMC:PMC10258335 | DOI:10.3389/fpls.2023.1208218

Heliyon. 2023 May 27;9(6):e16774. doi: 10.1016/j.heliyon.2023.e16774. eCollection 2023 Jun.ABSTRACTPomegranate (Punica granatum L.) fruits are a historical agricultural product of the Mediterranean basin that became increasingly popular in the latest years for being rich in antioxidants and other micronutrients, and are extensively commercialized as fruits, juice, jams and, in some Eastern countries, as a fermented alcoholic beverage. In this work, four different pomegranate wines specifically designed using combinations of two cultivars (Jolly Red and Smith) and two yeast starters with markedly different characteristics (Saccharomyces cerevisiae Clos and Saccharomyces cerevisiae ex-bayanus EC1118) were analyzed. The chemical characterization of the wines together with the originating unfermented juices was performed by 1H NMR spectroscopy metabolomic analysis. The full spectra were used for unsupervised and supervised statistical multivariate analysis (MVA), namely Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), and sparse PCA (SPCA). The MVA of the wines showed a clear discrimination between the cultivars, and a smaller, yet significant, discrimination between the yeasts used. In particular, a higher content of citrate and gallate was observed for the Smith cv. and, on the contrary, a statistically significant higher content of fructose, malate, glycerol, 2,3 butanediol, trigonelline, aromatic amino acids and 4-hydrophenylacetate was observed in Jolly Red pomegranate wines samples. Significant interaction among the pomegranate cultivar and the fermenting yeast was also observed. Sensorial analysis was performed by a panel of testing experts. MVA of tasting data showed that the cultivar significantly affected the organoleptic parameters considered, while the yeast had a minor impact. Correlation analysis between NMR-detected metabolites and organoleptic descriptors identified several potential sensorially-active molecules as those significantly impacting the characteristics of the pomegranate wines.PMID:37313136 | PMC:PMC10258421 | DOI:10.1016/j.heliyon.2023.e16774

Digit Health. 2023 May 31;9:20552076231179007. doi: 10.1177/20552076231179007. eCollection 2023 Jan-Dec.ABSTRACTBACKGROUND: Diagnosis of pancreatic ductal adenocarcinoma (PDAC) is difficult due to the lack of specific symptoms and screening methods. Only less than 10% of PDAC patients are candidates for surgery at the time of diagnosis. Thus, there is a great global unmet need for valuable biomarkers that could improve the opportunity to detect PDAC at the resectable stage. This study aimed to develop a potential biomarker model for the detection of resectable PDAC by tissue and serum metabolomics.METHODS: Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS) was performed for metabolome quantification in 98 serum samples (49 PDAC patients and 49 healthy controls (HCs)) and 20 pairs of matched pancreatic cancer tissues (PCTs) and adjacent noncancerous tissues (ANTs) from PDAC patients. Univariate and multivariate analyses were used to profile the differential metabolites between PDAC and HC.RESULTS: A total of 12 differential metabolites were present in both serum and tissue samples of PDAC. Among them, a total of eight differential metabolites showed the same expressional levels, including four upregulated and four downregulated metabolites. Finally, a panel of three metabolites including 16-hydroxypalmitic acid, phenylalanine, and norleucine was constructed by logistic regression analysis. Notably, the panel was capable of distinguishing resectable PDAC from HC with an AUC value of 0.942. Additionally, a multimarker model based on the 3-metabolites-based panel and CA19-9 showed a better performance than the metabolites panel or CA19-9 alone (AUC: 0.968 vs. 0.942, 0.850).CONCLUSIONS: Taken together, the resectable early-stage PDAC has unique metabolic features in serum and tissue samples. The defined panel of three metabolites has the potential value for early screening of PDAC at the resectable stage.PMID:37312938 | PMC:PMC10259126 | DOI:10.1177/20552076231179007

Mol Breed. 2023 Apr 21;43(5):33. doi: 10.1007/s11032-023-01380-6. eCollection 2023 May.ABSTRACTSoybean is one of the most versatile crops for oil production, human diets, and feedstocks. The vegetative biomass of soybean is an important determinant of seed yield and is crucial for the forage usages. However, the genetic control of soybean biomass is not well explained. In this work, we used a soybean germplasm population, including 231 improved cultivars, 207 landraces, and 121 wild soybeans, to investigate the genetic basis of biomass accumulation of soybean plants at the V6 stage. We found that biomass-related traits, including NDW (nodule dry weight), RDW (root dry weight), SDW (shoot dry weight), and TDW (total dry weight), were domesticated during soybean evolution. In total, 10 loci, encompassing 47 putative candidate genes, were detected for all biomass-related traits by a genome-wide association study. Among these loci, seven domestication sweeps and six improvement sweeps were identified. Glyma.05G047900, a purple acid phosphatase, was a strong candidate gene to improve biomass for future soybean breeding. This study provided new insights into the genetic basis of biomass accumulation during soybean evolution.SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11032-023-01380-6.PMID:37312748 | PMC:PMC10248709 | DOI:10.1007/s11032-023-01380-6

Anal Chem. 2023 Jun 13. doi: 10.1021/acs.analchem.3c00516. Online ahead of print.ABSTRACTDendritic cells (DCs) actively sample and present antigen to cells of the adaptive immune system and are thus vital for successful immune control and memory formation. Immune cell metabolism and function are tightly interlinked, and a better understanding of this interaction offers potential to develop immunomodulatory strategies. However, current approaches for assessing the immune cell metabolome are often limited by end-point measurements, may involve laborious sample preparation, and may lack unbiased, temporal resolution of the metabolome. In this study, we present a novel setup coupled to a secondary electrospray ionization-high resolution mass spectrometric (SESI-HRMS) platform allowing headspace analysis of immature and activated DCs in real-time with minimal sample preparation and intervention, with high technical reproducibility and potential for automation. Distinct metabolic signatures of DCs treated with different supernatants (SNs) of bacterial cultures were detected during real-time analyses over 6 h compared to their respective controls (SN only). Furthermore, the technique allowed for the detection of 13C-incorporation into volatile metabolites, opening the possibility for real-time tracing of metabolic pathways in DCs. Moreover, differences in the metabolic profile of naı̈ve and activated DCs were discovered, and pathway-enrichment analysis revealed three significantly altered pathways, including the TCA cycle, α-linolenic acid metabolism, and valine, leucine, and isoleucine degradation.PMID:37311562 | DOI:10.1021/acs.analchem.3c00516

J Ethnopharmacol. 2023 Jun 11:116780. doi: 10.1016/j.jep.2023.116780. Online ahead of print.ABSTRACTETHNOPHARMACOLOGICAL RELEVANCE: Shuganzhi Tablet (SGZT) originates from a famous traditional Chinese herbal formula Chaihu Decoction which can be applied to treat liver diseases, however, the pharmacodynamic mechanism of SGZT needs to be evaluated.AIM OF THIS STUDY: To study the mechanism of SGZT in the treatment of non-alcoholic fatty liver disease (NAFLD), and screen out its effective ingredients.MATERIALS AND METHODS: In this study, firstly, the main components of SGZT were analyzed qualitatively. And a rat model of NAFLD was established by feeding high-fat diet. Serum biochemical indexes and liver pathological analysis were used to evaluate the pharmacodynamic effect of SGZT in the treatment of NAFLD. In order to explore the pharmacodynamic mechanism, proteomics and metabolomics analysis were used. Western blotting was used to verify the expression of important differential proteins. And L02 cells were treated with free fatty acids (FFA) and the main substances of SGZT to establish the cell model of NAFLD in vitro and to reveal the pharmacodynamic substance of SGZT.RESULTS: Twelve components were detected in SGZT, and according to the results of serum biochemical indexes and liver pathological analysis, SGZT could effectively treat NAFLD. Combined with the results of bioinformatics analysis, we found that 133 differentially expressed proteins were reversed in liver samples of rats treated with SGZT. The important proteins in PPAR signaling pathway, steroid biosynthesis, cholesterol metabolism and fatty acid metabolism were mainly regulated to maintain cholesterol homeostasis and improve lipid metabolism. SGZT also affected various metabolites in rat liver, including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and taurine. In addition, the main components contained in SGZT (hesperidin, polydatin, naringin, emodin, specnuezhenide, saikosaponin A) and a metabolite (resveratrol) could significantly reduce FFA-induced intracellular lipid accumulation.CONCLUSION: SGZT effectively treated NAFLD, and PPAR-γ, Acsl4, Plin2 and Fads1 may be the main targets of SGZT. And Fads1-EPA/DHA-PPAR-γ may be the potential pharmacodynamic pathway. Cell experiments in vitro revealed that the main components of SGZT and their metabolites, such as hesperidin, polydatin, naringin, emodin, specnuezhenide, saikosaponin A and resveratrol may be the main components of its efficacy. Further research is needed to reveal and validate the pharmacodynamic mechanism.PMID:37311504 | DOI:10.1016/j.jep.2023.116780

J Ethnopharmacol. 2023 Jun 11:116775. doi: 10.1016/j.jep.2023.116775. Online ahead of print.ABSTRACTETHNOPHARMACOLOGICAL RELEVANCE: Wendan Decoction (WDD) is one of the classic traditional Chinese prescriptions that has been used in the treatment of type 2 diabetes mellitus (T2DM), metabolic syndrome, obstructive sleep apnea-hypopnea syndrome (OSAHS) and so on. The therapeutic effects and mechanism of WDD remain to be explored, especially from the perspective of metabolomics, oxidative stress and inflammation.AIM OF THE STUDY: To investigate the therapeutic and metabolic regulatory effects and the underlying mechanism of WDD in OSAHS with T2DM patients.MATERIALS AND METHODS: All included patients were from Rudong Hospital of Traditional Chinese Medicine, Nantong, Jiangsu Province, China. Both groups received lifestyle interventions; at the same time, all of them were administered metformin (1500 mg/day) and dapagliflozin (10 mg/day), and the treatment group was administered WDD orally. All patients were treated for two months. Before and after treatment, the changes in clinical symptoms and signs of the two groups of patients were evaluated, and the detection indicators such as body mass index (BMI), apnea-hypopnea index (AHI), lowest arterial oxygen saturation (LSaO2), Epworth sleepiness scale (ESS), percentage of total sleep time with oxygen saturation <90% (TST90), fasting plasma glucose (FPG), 2-h post-load glucose(2h-PG), fasting insulin (FINS), homeostasis model assessment of insulin resistance (HOMA-IR)，hemoglobin A1c (HbA1c), blood lipid levels, as well as the adverse reactions and compliance of the patients were observed and detection of serum metabolites in patients to screen out specific biomarkers. The serum metabolic profile of WDD in OSAHS with T2DM patients was explored using ultra-high-performance liquid chromatography-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry (UPLC-Q Orbitrap HRMS).RESULTS: After treatment with WDD for 8 weeks, biochemical indicators, including BMI, FPG, 2h-PG, blood lipid, FINS, HbA1c, AHI, ESS, LSaO2, TST90, and HOMA-IR, were significantly improved. Serum metabolomic analysis showed that metabolites were differentially expressed before and after WDD-treated patients. Metabolomics results revealed that WDD regulated the biomarkers, such as DL-arginine, guaiacol sulfate, azelaic acid, phloroglucinol, uracil, L-tyrosine, cascarillin, Cortisol and L-alpha-lysophosphatidylcholine. Pathway enrichment analysis showed that the metabolites were associated with oxidative stress and inflammation.CONCLUSION: The study based on clinical research and metabolomics indicated that WDD can improve OSAHS with T2DM through multiple targets and pathways, and it may be a useful alternative therapy for the treatment of OSAHS with T2DM patients.PMID:37311503 | DOI:10.1016/j.jep.2023.116775

J Nutr Biochem. 2023 Jun 11:109405. doi: 10.1016/j.jnutbio.2023.109405. Online ahead of print.ABSTRACTInfancy and childhood represent a high-risk period for developing iron deficiency (ID) and is a period of increased susceptibility to infectious disease. Antibiotic use is high in children from low-, middle-, and high-income countries, and thus we sought to determine the impact of antibiotics in the context of ID. In this study, a piglet model was used to assess the impact of ID and antibiotics on systemic metabolism. ID was induced by withholding a ferrous sulfate injection after birth to piglets in the ID group and providing an iron deficient diet upon weaning on postnatal day (PD) 25. Antibiotics (gentamicin and spectinomycin) were administered on PD34-36 to a set of control (Con*+Abx) and ID piglets (ID+Abx) after weaning. Blood was analyzed on PD30 (before antibiotic administration) and PD43 (7 days after antibiotic administration). All ID piglets exhibited growth faltering and had lower hemoglobin and hematocrit compared to control (Con) and Con*+Abx throughout. The metabolome of ID piglets at weaning and sacrifice exhibited elevated markers of oxidative stress, ketosis, and ureagenesis compared to Con. The impact of antibiotics on Con*+Abx piglets did not result in significant changes to the serum metabolome 7-days after treatment; however, the impact of antibiotics on ID+Abx piglets resulted in the same metabolic changes observed in ID piglets, but with a greater magnitude when compared to Con. These results suggest that antibiotic administration in the context of ID exacerbates the negative metabolic impacts of ID and may have long lasting impacts on development.PMID:37311489 | DOI:10.1016/j.jnutbio.2023.109405

ACS Appl Mater Interfaces. 2023 Jun 13. doi: 10.1021/acsami.3c07248. Online ahead of print.ABSTRACTProstate malignancy represents the second leading cause of cancer-specific death among the male population worldwide. Herein, enhanced intracellular magnetic fluid hyperthermia is applied in vitro to treat prostate cancer (PCa) cells with minimum invasiveness and toxicity and highly specific targeting. We designed and optimized novel shape-anisotropic magnetic core-shell-shell nanoparticles (i.e., trimagnetic nanoparticles - TMNPs) with significant magnetothermal conversion following an exchange coupling effect to an external alternating magnetic field (AMF). The functional properties of the best candidate in terms of heating efficiency (i.e., Fe3O4@Mn0.5Zn0.5Fe2O4@CoFe2O4) were exploited following surface decoration with PCa cell membranes (CM) and/or LN1 cell-penetrating peptide (CPP). We demonstrated that the combination of biomimetic dual CM-CPP targeting and AMF responsiveness significantly induces caspase 9-mediated apoptosis of PCa cells. Furthermore, a downregulation of the cell cycle progression markers and a decrease of the migration rate in surviving cells were observed in response to the TMNP-assisted magnetic hyperthermia, suggesting a reduction in cancer cell aggressiveness.PMID:37312240 | DOI:10.1021/acsami.3c07248

BMC Complement Med Ther. 2023 Jun 13;23(1):195. doi: 10.1186/s12906-023-04017-5.ABSTRACTOBJECTIVE: Sjögren's syndrome (SS) is an inflammatory autoimmune disease characterized by high levels of chronic lymphocyte infiltration. Differences and dysfunction in the gut microbiota and metabolites may be closely related to the pathogenesis of SS. The purpose of this study was to reveal the relationship between the gut microbiota and metabolome in NOD mice as a model of SS and the role of FuFang Runzaoling (FRZ), which is a clinically effective in treating SS.METHODS: NOD mice were gavaged with FRZ for 10 weeks. The ingested volume of drinking water, submandibular gland index, pathologic changes of the submandibular glands, and serum cytokines interleukin (IL)-6, IL-10, IL-17 A, and tumor necrosis factor-alpha (TNF-α) were determined. The roles of FRZ on gut microbiota and fecal metabolites were explored by 16 S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MC), respectively. The correlation between them was determined by Pearson correlation analysis.RESULTS: Compared with the model group, the drinking water volume of NOD mice treated with FRZ increased and the submandibular gland index decreased. FRZ effectively ameliorated lymphocyte infiltration in the small submandibular glands in mice. Serum levels of IL-6, TNF-α, and IL-17 A decreased, and IL-10 increased. The Firmicutes/Bacteroidetes ratio in the FRZ treatment group was higher. FRZ significantly downregulated the relative abundance of the family Bacteroidaceae and genus Bacteroides, and significantly upregulated the relative abundance of genus Lachnospiraceae_UCG-001. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) revealed the significant change in fecal metabolites after FRZ treatment. Based on criteria of OPLS-DA variable influence on projection > 1, P < 0.05, and fragmentation score > 50, a total of 109 metabolites in the FRZ-H group were differentially regulated (47 downregulated and 62 upregulated) compared to their expressions in the model group. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed enriched metabolic of sphingolipid metabolism, retrograde endocannabinoid signaling, GABAergic synapse, necroptosis, arginine biosynthesis, and metabolism of histidine, alanine, aspartate, and glutamate. Correlation analysis between gut microbiota and fecal metabolites suggested that the enriched bacteria were related to many key metabolites.CONCLUSIONS: Taken together, we found FRZ could reduce the inflammatory responses in NOD mice by regulating the gut microbiota, fecal metabolites, and their correlation to emerge a therapeutic effect on mice with SS. This will lay the foundation for the further studies and applications of FRZ, and the use of gut microbiotas as drug targets to treat SS.PMID:37312184 | DOI:10.1186/s12906-023-04017-5

BMC Med Inform Decis Mak. 2023 Jun 13;23(1):107. doi: 10.1186/s12911-023-02171-x.ABSTRACTBACKGROUND: Lung cancer is a malignant tumour, and early diagnosis has been shown to improve the survival rate of lung cancer patients. In this study, we assessed the use of plasma metabolites as biomarkers for lung cancer diagnosis. In this work, we used a novel interdisciplinary mechanism, applied for the first time to lung cancer, to detect biomarkers for early lung cancer diagnosis by combining metabolomics and machine learning approaches.RESULTS: In total, 478 lung cancer patients and 370 subjects with benign lung nodules were enrolled from a hospital in Dalian, Liaoning Province. We selected 47 serum amino acid and carnitine indicators from targeted metabolomics studies using LC‒MS/MS and age and sex demographic indicators of the subjects. After screening by a stepwise regression algorithm, 16 metrics were included. The XGBoost model in the machine learning algorithm showed superior predictive power (AUC = 0.81, accuracy = 75.29%, sensitivity = 74%), with the metabolic biomarkers ornithine and palmitoylcarnitine being potential biomarkers to screen for lung cancer. The machine learning model XGBoost is proposed as an tool for early lung cancer prediction. This study provides strong support for the feasibility of blood-based screening for metabolites and provide a safer, faster and more accurate tool for early diagnosis of lung cancer.CONCLUSIONS: This study proposes an interdisciplinary approach combining metabolomics with a machine learning model (XGBoost) to predict early the occurrence of lung cancer. The metabolic biomarkers ornithine and palmitoylcarnitine showed significant power for early lung cancer diagnosis.PMID:37312179 | DOI:10.1186/s12911-023-02171-x

Nat Commun. 2023 Jun 13;14(1):3493. doi: 10.1038/s41467-023-39275-x.NO ABSTRACTPMID:37311773 | DOI:10.1038/s41467-023-39275-x

Environ Microbiol Rep. 2023 Jun 13. doi: 10.1111/1758-2229.13184. Online ahead of print.ABSTRACTGlyphosate (GS) specifically inhibits the 5-enolpyruvyl-shikimate-3-phosphate (EPSP) synthase that converts phosphoenolpyruvate (PEP) and shikimate-3-phosphate to EPSP in the shikimate pathway of bacteria and other organisms. The inhibition of the EPSP synthase depletes the cell of the EPSP-derived aromatic amino acids as well as of folate and quinones. A variety of mechanisms (e.g., EPSP synthase modification) has been described that confer GS resistance to bacteria. Here, we show that the Burkholderia anthina strain DSM 16086 quickly evolves GS resistance by the acquisition of mutations in the ppsR gene. ppsR codes for the pyruvate/ortho-Pi dikinase PpsR that physically interacts and regulates the activity of the PEP synthetase PpsA. The mutational inactivation of ppsR causes an increase in the cellular PEP concentration, thereby abolishing the inhibition of the EPSP synthase by GS that competes with PEP for binding to the enzyme. Since the overexpression of the Escherichia coli ppsA gene in Bacillus subtilis and E. coli did not increase GS resistance in these organisms, the mutational inactivation of the ppsR gene resulting in PpsA overactivity is a GS resistance mechanism that is probably unique to B. anthina.PMID:37311711 | DOI:10.1111/1758-2229.13184