PubMed

Food Chem. 2024 Dec 5;468:142384. doi: 10.1016/j.foodchem.2024.142384. Online ahead of print.ABSTRACTIn this study, the bioaccessibility and bioavailability of curcumin encapsulated into different lupin protein isolate-based carriers was evaluated by coupling an in vitro gastrointestinal digestion (INFOGEST) with an in vitro co-culture absorption model, Caco-2/HT29-MTX, consisting of both absorptive and mucus producing cells. A targeted ultrahigh-performance quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) method was applied to monitor the fate of curcumin post digestion and absorption, specifically analyzing the apical, cellular, and basolateral fractions. Lupin protein nanoparticles, obtained by desolvation, protected curcumin from degradation better than oil in water (O/W) emulsions stabilized with lupin protein isolate. A recovery of 70 % of initial curcumin was found in the whole digesta of nanoparticles, whereas the emulsion systems displayed ≤35 % recovery. Interestingly, unlike in the case of emulsions, where curcumin was found in the micellar phase, most of the curcumin in the digesta of nanoparticles was recovered in the insoluble phase, highlighting the influence of the matrix structure in ensuring bioaccessibility of bioactive components. Regardless of the treatment, curcumin was not detected in the basolateral compartment, after absorption and transport through the in vitro cell monolayer model. However, a noteworthy proportion of curcumin, 54 % for protein nanoparticles and ≤ 24 % for emulsions, was retrieved within the cell monolayer. Non-targeted metabolomics analysis revealed the presence of a range of curcumin metabolites in the basolateral fraction and showed distinct profiles depending on the type (structure) of the delivery systems. The study highlights the critical need for thorough research into the behavior of bioactive compounds within the gut and emphasizes the necessity for future studies aimed at gaining a deeper understanding of the impact of the food matrix. Such insights are vital for enhancing and optimizing the delivery of bioactive compounds from complex food sources.PMID:39667234 | DOI:10.1016/j.foodchem.2024.142384

Plant J. 2024 Dec 12. doi: 10.1111/tpj.17169. Online ahead of print.ABSTRACTExtreme dryness is lethal for nearly all plants, excluding the so-called resurrection plants, which evolved vegetative desiccation tolerance (VDT) by recruiting genes common in most plants. To better understand the evolution of VDT, we generated chromosome-level assemblies and improved genome annotations of two Selaginella species with contrasting abilities to survive desiccation. We identified genomic features and critical mechanisms associated with VDT through sister-group comparative genomics integrating multi-omics data. Our findings indicate that Selaginella evolved VDT through the expansion of some stress protection-related gene families and the contraction of senescence-related genes. Comparative analyses revealed that desiccation-tolerant Selaginella species employ a combination of constitutive and inducible protection mechanisms to survive desiccation. We show that transcriptional priming of stress tolerance-related genes and accumulation of flavonoids in unstressed plants are hallmarks of VDT in Selaginella. During water loss, the resurrection Selaginella induces phospholipids and glutathione metabolism, responses that are missing in the desiccation-sensitive species. Additionally, gene regulatory network analyses indicate the suppression of growth processes as a major component of VDT. This study presents novel perspectives on how gene dosage impacts crucial protective mechanisms and the regulation of central processes to survive extreme dehydration.PMID:39666518 | DOI:10.1111/tpj.17169

JAMA Netw Open. 2024 Dec 2;7(12):e2450467. doi: 10.1001/jamanetworkopen.2024.50467.ABSTRACTIMPORTANCE: Gestational diabetes (GD) is linked to health risks for the birthing parent and infant. The outcomes of GD on human milk composition are mostly unknown.OBJECTIVE: To determine associations between GD, the human milk metabolome, and infant growth and body composition.DESIGN, SETTING, AND PARTICIPANTS: Cohort study using data from the Mothers and Infants Linked for Healthy Growth and the Maternal Milk, Metabolism, and the Microbiome studies at the University of Oklahoma and University of Minnesota, large prospective US cohorts with a high proportion of exclusive breastfeeding. Participants were mother-infant dyads recruited between October 2014 and August 2019 who planned to exclusively breastfeed for 3 or more months. Data were analyzed from July 2022 to August 2024.EXPOSURE: GD diagnosed via oral glucose tolerance test.MAIN OUTCOMES AND MEASURES: The milk metabolome was assessed by untargeted liquid chromatography-gas chromatography-mass spectrometry at 1 month post partum. Infant growth (weight for length z score, length for age z score, and rapid weight gain) and body composition (percentage body fat and fat-free mass index) from 0 to 6 months were assessed. Linear regression analyses tested associations between GD and milk metabolites, with adjustment for covariates and potential confounders.RESULTS: Among 348 dyads (53 with GD), 27 (51%) of the GD-exposed infants were female and 157 (53%) of nonexposed infants were male; 10 (19%) were Asian, 2 (4%) were Black or African American, and 37 (70%) were White. The mean (SD) age was higher in the GD group (with GD, 34.0 [4.3] years; without GD, 30.7 [4.1] years). In adjusted models, GD was associated with differential levels of 9 metabolites of 458 tested (FDR<0.05); 3 were higher (2-hydroxybutyric acid, 3-methylphenylacetic acid, and pregnanolone sulfate) and 6 were lower in women with GD (4-cresyl sulfate, cresol, glycine, P-cresol sulfate, phenylacetic acid, and stearoylcarnitine). Phenylacetic acid was associated with length for age z score (β = 0.27; SE, 0.13; 95% CI, 0.02 to 0.16), 2-hydroxybutryic acid with percentage body fat (β = -1.50; SE, 0.66; 95% CI, -2.79 to -4.82), and stearoylcarnitine with greater odds of rapid weight gain (odds ratio, 1.66; 95% CI, 1.23 to 2.25). GD was associated with greater length for age z scores (β = 0.48; SE, 0.22; 95% CI, 0.04 to 0.91).CONCLUSIONS AND RELEVANCE: In this observational cohort study, GD was associated with altered concentrations of several human milk metabolites. The associations between these metabolites and infant growth suggest that milk compositional differences in mothers with GD may beneficially moderate the growth and body composition of their infants.PMID:39666338 | DOI:10.1001/jamanetworkopen.2024.50467

J Food Drug Anal. 2022 Sep 15;30(3):402-416. doi: 10.38212/2224-6614.3425.ABSTRACTTraditional Chinese medicine (TCM) has been applied to improve human health for millennia. In the TCM system, "medicinal property" ( yao xing; hot and cold properties) is a core concept used to describe the influences of medicinal materials on human physiological conditions, and metabolites are believed to be one of the major ingredients of TCMs that affect their medicinal property. However, due to a lack of comprehensive analyses of TCM metabolomes, information about the relationships between TCM metabolite composition and medicinal property remains limited. In this pilot study, a mass spectral molecular networking-based platform was established and applied to systematically profile the metabolome of 24 TCMs with various medicinal properties. The molecular networks were built based on the liquid chromatography-tandem mass spectrometry (LC-MS/MS) data from 50% EtOH extracts of 24 TCMs. The results showed that various classes of metabolites were clustered in the molecular networks, and the potential medicinal property-associated molecular families were filtered by screening the medicinal property and the diversity of TCM sources. For example, some specific types of flavonoids were identified in the representative cold-property (han xing) molecular families. In contrast, due to the limited sample size, the representative and universal hot-property (re xing) molecular family has not been well revealed. In summary, this study provides methodology and information on the potential relationships between the metabolite composition and the concept of medicinal property in TCM. Furthermore, the results can serve as a foundation for mass spectral molecular networking-based analysis of TCM metabolomes, facilitating TCM research and development.PMID:39666294 | DOI:10.38212/2224-6614.3425

Insights Imaging. 2024 Dec 12;15(1):299. doi: 10.1186/s13244-024-01876-5.ABSTRACTOBJECTIVES: Radical prostatectomy (RP) is a common intervention in patients with localized prostate cancer (PCa), with nerve-sparing RP recommended to reduce adverse effects on patient quality of life. Accurate pre-operative detection of extraprostatic extension (EPE) remains challenging, often leading to the application of suboptimal treatment. The aim of this study was to enhance pre-operative EPE detection through multimodal data integration using explainable machine learning (ML).METHODS: Patients with newly diagnosed PCa who underwent [68Ga]Ga-PSMA-11 PET/MRI and subsequent RP were recruited retrospectively from two time ranges for training, cross-validation, and independent validation. The presence of EPE was measured from post-surgical histopathology and predicted using ML and pre-operative parameters, including PET/MRI-derived features, blood-based markers, histology-derived parameters, and demographic parameters. ML models were subsequently compared with conventional PET/MRI-based image readings.RESULTS: The study involved 107 patients, 59 (55%) of whom were affected by EPE according to postoperative findings for the initial training and cross-validation. The ML models demonstrated superior diagnostic performance over conventional PET/MRI image readings, with the explainable boosting machine model achieving an AUC of 0.88 (95% CI 0.87-0.89) during cross-validation and an AUC of 0.88 (95% CI 0.75-0.97) during independent validation. The ML approach integrating invasive features demonstrated better predictive capabilities for EPE compared to visual clinical read-outs (Cross-validation AUC 0.88 versus 0.71, p = 0.02).CONCLUSION: ML based on routinely acquired clinical data can significantly improve the pre-operative detection of EPE in PCa patients, potentially enabling more accurate clinical staging and decision-making, thereby improving patient outcomes.CRITICAL RELEVANCE STATEMENT: This study demonstrates that integrating multimodal data with machine learning significantly improves the pre-operative detection of extraprostatic extension in prostate cancer patients, outperforming conventional imaging methods and potentially leading to more accurate clinical staging and better treatment decisions.KEY POINTS: Extraprostatic extension is an important indicator guiding treatment approaches. Current assessment of extraprostatic extension is difficult and lacks accuracy. Machine learning improves detection of extraprostatic extension using PSMA-PET/MRI and histopathology.PMID:39666257 | DOI:10.1186/s13244-024-01876-5

J Gastroenterol. 2024 Dec 12. doi: 10.1007/s00535-024-02197-6. Online ahead of print.ABSTRACTBACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a formidable health challenge due to its detection at a late stage and a lack of reliable biomarkers for early detection. Although levels of carbohydrate antigen 19-9 are often used in conjunction with imaging-based tests to aid in the diagnosis of PDAC, there is still a need for more sensitive and specific biomarkers for early detection of PDAC.METHODS: We obtained serum samples from 88 subjects (patients with PDAC (n = 58) and controls (n = 30)). We carried out a multi-omics analysis to measure cytokines and related proteins using proximity extension technology and lipidomics and metabolomics using tandem mass spectrometry. Statistical analysis was carried out to find molecular alterations in patients with PDAC and a machine learning model was used to derive a molecular signature of PDAC.RESULTS: We quantified 1,462 circulatory proteins along with 873 lipids and 1,001 metabolites. A total of 505 proteins, 186 metabolites and 33 lipids including bone marrow stromal antigen 2 (BST2), keratin 18 (KRT18), and cholesteryl ester(20:5) were found to be significantly altered in patients. We identified different levels of sphingosine, sphinganine, urobilinogen and lactose indicating that glycosphingolipid and galactose metabolisms were significantly altered in patients compared to controls. In addition, elevated levels of diacylglycerols and decreased cholesteryl esters were observed in patients. Using a machine learning model, we identified a signature of 38 biomarkers for PDAC, composed of 21 proteins, 4 lipids, and 13 metabolites.CONCLUSIONS: Overall, this study identified several proteins, metabolites and lipids involved in various pathways including cholesterol and lipid metabolism to be changing in patients. In addition, we discovered a multi-analyte signature that could be further tested for detection of PDAC.PMID:39666045 | DOI:10.1007/s00535-024-02197-6

ACS Infect Dis. 2024 Dec 12. doi: 10.1021/acsinfecdis.4c00472. Online ahead of print.ABSTRACTAfrican trypanosomiasis is a widespread disease of human and veterinary importance caused by various Trypanosoma spp. with a globally devastating impact and a need for novel treatment options. We here provide a comprehensive preclinical evaluation of nucleoside analogues, 6-thioether-modified tubercidins, with curative activity against African trypanosomiasis. Promising hits were identified following in vitro screening against the most relevant trypanosome species. Selected hit compounds were extensively tested for in vitro metabolic stability, potency in in vivo mouse models for the various species, genotoxicity in an in vitro testing battery, and mode of action studies (i.e., genome-wide RNA interference library screening and metabolomics). Among the nucleoside analogues, analogue 3 was curative in mouse models with no indication of genotoxicity and a low ecotoxicological footprint. Mode-of-action studies revealed that P1-type nucleoside transporters and adenosine kinase are involved in the uptake and activation, respectively. Analogue 3 represents a potent, advanced lead fitting the preferred target product profile for a broad-spectrum trypanocide regardless of the causative species.PMID:39665421 | DOI:10.1021/acsinfecdis.4c00472

Mol Nutr Food Res. 2024 Dec 12:e202400583. doi: 10.1002/mnfr.202400583. Online ahead of print.ABSTRACTSCOPE: Cow's milk allergy (CMA) is one of the most prevalent food allergies in early childhood, often treated via elimination diets including standard amino acid-based formula or amino acid-based formula supplemented with synbiotics (AAF or AAF-S). This work aimed to assess the effect of cow's milk (CM) tolerance acquisition and synbiotic (inulin, oligofructose, Bifidobacterium breve M-16 V) supplementation on the fecal metabolome in infants with IgE-mediated CMA.METHODS AND RESULTS: The CMA-allergic infants received AAF or AAF-S for a year during which fecal samples were collected. The samples were subjected to metabolomics analyses covering gut microbial metabolites including SCFAs, tryptophan metabolites, and bile acids (BAs). Longitudinal data analysis suggested amino acids, BAs, and branched SCFAs alterations in infants who outgrew CMA during the intervention. Synbiotic supplementation significantly modified the fecal metabolome after 6 months of intervention, including altered purine, BA, and unsaturated fatty acid levels, and increased metabolites of infant-type Bifidobacterium species: indolelactic acid and 4-hydroxyphenyllactic acid.CONCLUSION: This study offers no clear conclusion on the impact of CM-tolerance acquisition on the fecal metabolome. However, our results show that 6 months of synbiotic supplementation successfully altered fecal metabolome and suggest induced bifidobacteria activity, which subsequently declined after 12 months of intervention.PMID:39665335 | DOI:10.1002/mnfr.202400583

Adv Sci (Weinh). 2024 Dec 12:e2406562. doi: 10.1002/advs.202406562. Online ahead of print.ABSTRACTLiver metastasis is a common cause of death in colorectal cancer (CRC) patients, but epigenetic remodeling and metabolic reprogramming for CRC liver metastasis remain unclear. The study revealed that the Lyn/RUVBL1 complex is highly expressed in CRC and is closely correlated with liver metastasis. On the one hand, ATAC-seq and HiCut suggested that Lyn/RUVBL1 regulates the expression of TRIB3 through the POL II-mediated chromatin conformation of TRIB3 and thus the expression of β-catenin. This promotes the proliferation and migration of CRC through β-catenin-mediated upregulation of MMP9 and VEGF. On the other hand, metabolomics revealed that Lyn/RUVBL1 regulates the expression of PGE2 through the enzyme COX2, thereby promoting arachidonic acid (AA) metabolism. CUT-Tag showed that Lyn/RUVBL1 silencing reduces the H3K27ac level in the COX2 promoter. Then, it is found that COX2 is regulated by the transcription factor FOXA1. Lyn/RUVBL1 modulates AA metabolism by regulating the chromatin accessibility of FOXA1. AA metabolism promotes the metastasis of CRC by affecting β-catenin nuclear translocation and upregulating MMP9 and VEGF. These findings suggest that the Lyn/RUVBL1 complex mediates epigenetic remodeling to regulate the metabolic reprogramming of AA, highlighting its role in promoting the metastasis of CRC.PMID:39665272 | DOI:10.1002/advs.202406562

Adv Sci (Weinh). 2024 Dec 12:e2410506. doi: 10.1002/advs.202410506. Online ahead of print.ABSTRACTSingle-cell MALDI mass spectrometry imaging (MSI) of lipids and metabolites >200 Da has recently come to the forefront of biomedical research and chemical biology. However, cell-targeting and metabolome-preserving methods for analysis of low mass, hydrophilic metabolites (<200 Da) in large cell populations are lacking. Here, the PRISM-MS (PRescan Imaging for Small Molecule - Mass Spectrometry) mass-guided MSI workflow is presented, which enables space-efficient single cell lipid and metabolite analysis. In conjunction with giant unilamellar vesicles (GUVs) as MSI ground truth for cell-sized objects and Monte Carlo reference-based consensus clustering for data-dependent identification of cell subpopulations, PRISM-MS enables MSI and on-cell MS2-based identification of low-mass metabolites like amino acids or Krebs cycle intermediates involved in stimulus-dependent cell activation. The utility of PRISM-MS is demonstrated through the characterization of complex metabolome changes in lipopolysaccharide (LPS)-stimulated microglial cells and human-induced pluripotent stem cell-derived microglia. Translation of single cell results to endogenous microglia in organotypic hippocampal slice cultures indicates that LPS-activation involves changes of the itaconate-to-taurine ratio and alterations in neuron-to-glia glutamine-glutamate shuttling. The data suggests that PRISM-MS can serve as a standard method in single cell metabolomics, given its capability to characterize larger cell populations and low-mass metabolites.PMID:39665230 | DOI:10.1002/advs.202410506

Front Nutr. 2024 Nov 27;11:1479607. doi: 10.3389/fnut.2024.1479607. eCollection 2024.ABSTRACTINTRODUCTION: Black-bone chicken meat is rich in nutritional substances and bioactive compounds. Stewing is a traditional and healthy cooking style for black-bone chicken meat. However, the alteration of metabolites in chicken meat during stewing is still unknown.METHODS: A comprehensive analysis of Lueyang black-bone chicken meat metabolites was performed in fresh chicken meat (FM), short-term heat-pretreated meat (PM), fully cooked meat (CM) and chicken soup (CS) via untargeted metabolomics.RESULTS: By comparison, 200, 992 and 891 significantly differentially metabolites (DMs) were identified in the PM vs. FM, CM vs. FM and CS vs. FM comparisons, respectively. These DMs mainly included amino acids, peptides, carbohydrates and lipids. During the heating process, the abundances of Ser, Ala, Tyr, niacinamide, galactose, guanosine 3'-monophosphate and inosine 5'-monophosphate in chicken meat significantly decreased and were partially dissolved in the soup. Due to the hydrolysis of phospholipids, the relative contents of unsaturated lipids, especially a range of lysophosphatidylcholines, lysophosphatidylethanolamines, arachidonic acid and derivatives, increased in fully cooked meat.DISCUSSION: Pretreatment had little impact on the changes in metabolites in chicken meat. During stewing, the dissolved amino acids, carbohydrates and nucleic acids could enhance the taste quality of chicken soup, and the high abundance of unsaturated lipids could promote the nutritional quality of black-bone chicken meat. In summary, these data provide helpful information for nutritional quality studies on the metabolite profiles of black-bone chicken meat.PMID:39664908 | PMC:PMC11631612 | DOI:10.3389/fnut.2024.1479607

Hortic Res. 2024 Sep 5;11(12):uhae253. doi: 10.1093/hr/uhae253. eCollection 2024 Dec.ABSTRACTThe target of rapamycin (TOR) kinase is a central signaling hub that plays a crucial role in precisely orchestrating plant growth, development, and stress responses. This suggests that TOR is intricately involved in maintaining the balance between plant growth and stress responses. Nevertheless, despite the observed effects, the specific mechanisms through which TOR operates in these processes remain obscure. In this study, we investigated how the tomato (Solanum lycopersicum) TOR (SlTOR) affects plant growth and cold responses. We demonstrated that SlTOR inhibition transcriptionally primes cold stress responses, consequently enhancing tomato cold tolerance. A widely targeted metabolomics analysis revealed the disruption of amino acid metabolism homeostasis under cold stress upon SlTOR inhibition, which led to the accumulation of two important cryoprotective metabolites: salicylic acid (SA) and putrescine (Put). Next, we discovered SlPGH1 (2-PHOSPHO-D-GLYCERATE HYDRO-LYASE 1) as a direct substrate of SlTOR. Inhibiting SlTOR led to increased SlCBF1 (C-REPEAT-BINDING FACTOR 1) expression via SlPGH1, potentially triggering the activation of cold-responsive genes and subsequent metabolic alterations. Our study provides a mechanistic framework that elucidates how SlTOR modulates amino acid-related metabolism to enhance tomato cold tolerance, which sheds light on the complex interplay between growth and stress responses orchestrated by TOR.PMID:39664689 | PMC:PMC11630258 | DOI:10.1093/hr/uhae253

Int J Biol Sci. 2024 Nov 4;20(15):5979-5998. doi: 10.7150/ijbs.100607. eCollection 2024.ABSTRACTMacrophages play a crucial role in malignant pleural effusion (MPE), a frequent complication of advanced cancer. While C1q+ macrophages have been identified as a pro-tumoral cluster, direct evidence supporting the role of C1q-mediated macrophages remains to be elucidated. This study employed global and macrophage-specific knockout mice to investigate the role of C1q in MPE. The data demonstrated that C1q deficiency in macrophages suppressed MPE and prolonged mouse survival. scRNA-seq analysis of the C1qa-/- mouse MPE model revealed that C1q deficiency significantly decreased the proportion of M2 macrophages in MPE. In vitro experiments suggested that C1q expression was gradually upregulated during M2 polarization, which was C1q-dependent, as was antigen presentation. Deficiency of C1q in macrophages rescued the exhausted status of CD8+ T cells and enhanced the immune activity of CD8+ T cells and NK cells in both MPE and pleural tumors. Cell-to-cell interaction analysis demonstrated that C1q deficiency attenuated the immunoinhibitory effects of macrophages on NK cells by downregulating the CCR2-CCL2 signaling axis. Metabolomic analysis revealed significantly elevated hippuric acid levels in C1q-deficient mouse MPE. Treatment with either hippuric acid or a CCR2 antagonist inhibited MPE and tumor growth, with an even more pronounced effect observed when both treatments were combined.PMID:39664577 | PMC:PMC11628339 | DOI:10.7150/ijbs.100607

Int J Biol Sci. 2024 Nov 11;20(15):6038-6055. doi: 10.7150/ijbs.103977. eCollection 2024.ABSTRACTThyroid eye disease (TED) is an organ-specific autoimmune disorder that significantly impacts patients' visual function, appearance, and well-being. Despite existing clinical evaluation methods, there remains a need for objective biomarkers to facilitate clinical management and pathogenesis investigation. Rapid advances in multi-omics technologies have enabled the discovery and development of more informative biomarkers for clinical use. This systematic review synthesizes the current landscape of multi-omics approaches in TED research, highlighting the potential of genomics, transcriptomics, proteomics, metabolomics, and microbiomics to uncover novel biomarkers. Our review encompasses 69 studies involving 1,363 TED patients and 1,504 controls, revealing a wealth of biomarker candidates across various biological matrices. The identified biomarkers reflect alterations in gene expression, protein profiles, metabolic pathways, and microbial compositions, underscoring the systemic nature of TED. Notably, the integration of multi-omics data has been pivotal in enhancing our understanding of TED's molecular mechanisms and identifying diagnostic and prognostic markers with clinical potential.PMID:39664569 | PMC:PMC11628329 | DOI:10.7150/ijbs.103977

Indian J Orthop. 2024 Nov 5;58(12):1871-1882. doi: 10.1007/s43465-024-01284-3. eCollection 2024 Dec.ABSTRACTBACKGROUND: Bone regeneration following a fracture is dependent on multiple factors including skeletal stem cells (SSCs). Recruitment, proliferation, and differentiation of the SSCs is guided by the proteins and metabolites found within the fracture microenvironment. Understanding how intrinsic factors affect the fracture microenvironment has been a topic of ongoing investigation. This study sought to determine whether the levels of select proteins and metabolites within the fracture hematoma would be differentially expressed depending on the age of the patient. We hypothesized that a distinct set of proteins and metabolites found within the fracture hematoma microenvironment would be present at varying levels depending on patient age.METHODS: The research study was reviewed and approved by an Institutional Review Board. Hematomas were collected from subjects aged 18 years old or older undergoing surgical intervention for a fracture. Hematoma samples were selected from the biorepository and assigned to one of two fracture groups including young ankle/hindfoot and aged ankle/hindfoot. Protein and metabolite levels within each hematoma were analyzed by liquid chromatography-mass spectrometry.RESULTS: A total of seven hematomas were included in each the young ankle/hindfoot and aged ankle/hindfoot groups. From the global metabolomic analysis, creatine, 2-methylindoline, and acetyl-L-carnitine were identified as being differentially expressed between both groups. An untargeted metabolomic analysis of the two groups identified significant differences in the levels of an additional 66 metabolites. Proteomic analysis identified 34 proteins that were expressed at significantly different levels.CONCLUSIONS: The level of metabolites and proteins found within the local fracture environment vary by patient age. Future investigations will focus on identifying a role for these proteins and metabolites in bone homeostasis and fracture healing.LEVEL OF EVIDENCE: N/A, basic science investigation.SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43465-024-01284-3.PMID:39664353 | PMC:PMC11628468 | DOI:10.1007/s43465-024-01284-3

Nat Sci Sleep. 2024 Dec 7;16:1959-1972. doi: 10.2147/NSS.S472675. eCollection 2024.ABSTRACTPURPOSE: Despite recent findings suggesting an altered gut microbiota in those suffering from insomnia disorder (ID), research into the gut microbiota, oral microbiota, serum metabolites, and their interactions in patients with ID is sparse.PATIENTS AND METHODS: We collected a total of 114 fecal samples, 133 oral cavity samples and 20 serum samples to characterize the gut microbiota, oral microbiota and serum metabolites in a cohort of 76 ID patients (IDs) and 59 well-matched healthy controls (HCs). We assessed the microbiota as potentially biomarkers for ID for ID by 16S rDNA sequencing and elucidated the interactions involving gut microbiota, oral microbiota and serum metabolites in ID in conjunction with untargeted metabolomics.RESULTS: Gut and oral microbiota of IDs were dysbiotic. Gut and oral microbial biomarkers could be used to differentiate IDs from HCs. Eleven significantly altered serum metabolites, including adenosine, phenol, and phenol sulfate, differed significantly between groups. In multi-omics analyses, adenosine showed a positive correlation with genus_Lachnospira (p=0.029) and total sleep time (p=0.016). Additionally, phenol and phenol sulphate had a negative correlation with genus_Coprococcus (p=0.0059; p=0.0059) and a positive correlation with Pittsburgh Sleep Quality Index (p=0.006; p=0.006) and Insomnia Severity Index (p=0.021; p=0.021).CONCLUSION: Microbiota and serum metabolite changes in IDs are strongly correlated with clinical parameters, implying mechanistic links between altered bacteria, serum metabolites and ID. This study offers novel perspective into the interaction among gut microbiota, oral microbiota, and serum metabolites for ID.PMID:39664229 | PMC:PMC11633293 | DOI:10.2147/NSS.S472675

Front Microbiol. 2024 Nov 27;15:1476429. doi: 10.3389/fmicb.2024.1476429. eCollection 2024.ABSTRACTINTRODUCTION: Candida albicans gastrointestinal (GI) colonization is crucial for the onset of invasive disease. This research encompassed 31 patients diagnosed with Candida spp. bloodstream infections during their admission to a university hospital in China.METHODS: We explored risk factors associated with C. albicans GI colonization and ensuing translocated infection. Animal models were established via gavage with clinical isolates of C. albicans to induce GI tract colonization and subsequent kidney translocation infection. Our analysis is focused on 16S rRNA gene sequencing, metabolomics of colon contents, and transcriptomics of colon tissues, examining the intestinal barrier, inflammatory responses, and immune cell infiltration.RESULTS: This study observed that down-regulation of programmed cell death 1 (PD-1) in colon tissues is likely linked to the progression from C. albicans colonization to translocated infection. Notably, reductions in Dubosiella abundance and Short-chain fatty acids (SCFA) levels, coupled with increases in Mucispirillum and D-erythro-imidazolylglycerol phosphate, were indicator features during the advancement to translocated invasive infection in hosts with rectal colonization by C. albicans and lower serum protein levels.CONCLUSION: Given the similarity in intestinal bacterial communities and metabolome profiles, antifungal treatment may not be necessary for patients with nonpathogenic C. albicans colonization. The reduced expression of PD-1 in colon tissues may contribute to the transition from colonized C. albicans to subsequent translocated infection. The indicator features of decreased Dubosiella abundance and SCFA levels, coupled with increased Mucispirillum and D-erythro-imidazolylglycerol phosphate, are likely linked to the development of translocated invasive infection in hosts colonized rectally by C. albicans with lower serum protein levels.IMPORTANCE: Candida albicans invasive infections pose a significant challenge to contemporary medicine, with mortality rates from such fungal infections remaining high despite antifungal treatment. Gastrointestinal colonization by potential pathogens is a critical precursor to the development of translocated infections. Consequently, there is an increasing demand to identify clinical risk factors, multi-omics profiles, and key indicators to prevent the progression to translocated invasive infections in patients colonized rectally by C. albicans.PMID:39664059 | PMC:PMC11632224 | DOI:10.3389/fmicb.2024.1476429

Front Microbiol. 2024 Nov 27;15:1470054. doi: 10.3389/fmicb.2024.1470054. eCollection 2024.ABSTRACTThe terrestrial green alga Chromochloris zofingiensis is an emerging model species with potential applications including production of triacylglycerol or astaxanthin. How C. zofingiensis interacts with the diverse substrates during trophic transitions is unknown. To characterize its substrate utilization and secretion dynamics, we cultivated the alga in a soil-based defined medium in transition between conditions with and without glucose supplementation. Then, we examined its exometabolite and endometabolite profiles. This analysis revealed that regardless of trophic modes, C. zofingiensis preferentially uptakes exogenous lysine, arginine, and purines, while secreting orotic acid. Here, we obtained metabolomic evidences that C. zofingiensis may use arginine for putrescine synthesis when in transition to heterotrophy, and for the TCA cycle during transition to photoautotrophy. We also report that glucose and fructose most effectively inhibited photosynthesis among thirteen different sugars. The utilized or secreted metabolites identified in this study provide important information to improve C. zofingiensis cultivation, and to expand its potential industrial and pharmaceutical applications.PMID:39664052 | PMC:PMC11631937 | DOI:10.3389/fmicb.2024.1470054

Aging Cell. 2024 Dec 12:e14435. doi: 10.1111/acel.14435. Online ahead of print.ABSTRACTThis study aims to investigate the association between metabolomic aging acceleration and body mass index (BMI) phenotypes with mortality and obesity-related morbidities (ORMs). 85,458 participants were included from the UK Biobank. Metabolomic age was determined using 168 metabolites. The Chronological Age-Adjusted Gap was used to define metabolomically younger (MY) or older (MO) status. BMI categories were defined as normal weight, overweight, and obese. Participants were categorized into MY normal weight (MY-NW, reference), MY overweight (MY-OW), MY obesity (MY-OB), MO normal weight (MO-NW), MO overweight (MO-OW), and MO obesity (MO-OB). Mortality and 43 ORMs were identified through death registries and hospitalization records. Compared with MY-NW phenotype, MO-OB phenotype yielded increased risk of mortality and 32 ORMs, followed by MO-OW with mortality and 27 ORMs, MY-OB with mortality and 26 ORMs, MY-OW with 21 ORMs, and MO-NW with mortality and 14 ORMs. Consistently, MO-OB phenotype showed the highest risk of developing obesity-related multimorbidities, followed by MY-OB phenotype, MO-OW phenotype, MY-OW phenotype, and MO-NW phenotype. Additive interactions were found between metabolomic aging acceleration and obesity on CVD-specific mortality and 10 ORMs. Additionally, individuals with metabolomic aging acceleration had higher mortality and cardiovascular risk, even within the same BMI category. These findings suggest that metabolomic aging acceleration could help stratify mortality and ORMs risk across different BMI categories. Weight management should also be extended to individuals with overweight or obesity even in the absence of accelerated metabolomic aging, as they face increased healthy risk compared with MY-NW individuals. Additionally, delaying metabolic aging acceleration is needed for all metabolomically older groups, including those with normal weight.PMID:39663904 | DOI:10.1111/acel.14435

Mov Disord. 2024 Dec 11. doi: 10.1002/mds.30074. Online ahead of print.ABSTRACTBACKGROUND: Patients with Parkinson's disease (PD) present progressive deterioration in both motor and non-motor manifestations. However, the absence of clinical biomarkers for disease progression hinders clinicians from tailoring treatment strategies effectively.OBJECTIVES: To identify electroencephalography (EEG) biomarker that can track disease progression in PD.METHODS: A total of 116 patients with PD were initially enrolled, whereas 63 completed 2-year follow-up evaluation. Fifty-eight age- and sex-matched healthy individuals were recruited as the control group. All participants underwent EEG and clinical assessments. Long-range temporal correlations (LRTC) of EEG data were analyzed using the detrended fluctuation analysis.RESULTS: Patients with PD exhibited higher LRTC in left parietal θ oscillations (P = 0.0175) and lower LRTC in centro-parietal γ oscillations (P = 0.0258) compared to controls. LRTC in parietal γ oscillations inversely correlated with changes in Unified Parkinson's Disease Rating Scale (UPDRS) part III scores over 2 years (Spearman ρ = -0.34, P = 0.0082). Increased LRTC in left parietal θ oscillations were associated with rapid motor progression (P = 0.0107), defined as an annual increase in UPDRS part III score ≥3. In cognitive assessments, LRTC in parieto-occipital α oscillations exhibited a positive correlation with changes in Mini-Mental State Examination and Montreal Cognitive Assessment scores over 2 years (Spearman ρ = 0.27-0.38, P = 0.0037-0.0452).CONCLUSIONS: LRTC patterns in EEG potentially predict rapid progression of both motor and non-motor manifestations in PD patients, enhancing clinical assessment and understanding of the disease. © 2024 International Parkinson and Movement Disorder Society.PMID:39663783 | DOI:10.1002/mds.30074