Serum Metabolites Research Articles

Lonicera japonica Fermented by Lactobacillus plantarum Improve Multiple Patterns Driven Osteoporosis.

Osteoporosis (OP) represents a global health challenge. Certain functional food has the potential to mitigate OP. Honeysuckle (Lonicera japonica) solution has medicinal effects, such as anti-inflammatory and immune enhancement, and can be used in functional foods such as health drinks and functional snacks. The composition of honeysuckle changed significantly after fermentation, and 376 metabolites were enriched. In this study, we used dexamethasone to induce OP in the rat model. Research has confirmed the ability of FS (fermented Lonicera japonica solution) to enhance bone mineral density (BMD), repair bone microarchitectural damage, and increase blood calcium levels. Markers such as tartrate-resistant acid phosphatase-5b (TRACP-5b) and pro-inflammatory cytokines (TNF-α and IL-6) were notably decreased, whereas osteocalcin (OCN) levels increased after FS treatment. FS intervention in OP rats restored the abundance of 6 bacterial genera and the contents of 17 serum metabolites. The results of the Spearman correlation analysis showed that FS may alleviate OP by restoring the abundance of 6 bacterial genera and the contents of 17 serum metabolites, reducing osteoclast differentiation, promoting osteoblast differentiation, and reducing the inflammatory response. This study revealed that Lactobacillus plantarum-fermented honeysuckle alleviated OP through intestinal bacteria and serum metabolites and provided a theoretical basis for the development of related functional foods.

The toxicity of cisplatin derives from effects on renal organic ion transporters expression and serum endogenous substance levels

Acute kidney injury (AKI) is a worldwide public health problem with high morbidity and mortality. Cisplatin is a widely used chemotherapeutic agent for treating solid tumors, but the induction of AKI restricts its clinical application. In this study, the effect of cisplatin on the expression of organic ion transporters was investigated through in vivo and in vitro experiments. Targeted metabolomics techniques were used to measure the levels of selected endogenous substances in serum. Transmission electron microscopy was used to observe the microstructure of renal tubular epithelial cells. Our results show that the toxicity of cisplatin on HK-2 cells or HEK-293 cells was time- and dose-dependent. Administration of cisplatin decreased the expression of OAT1/3 and OCT2 and increased the expression of MRP2/4. Mitochondrial damage induced by cisplatin lead to renal tubular epithelial cell injury. In addition, administration of cisplatin resulted in significant changes in endogenous substance levels in serum, including amino acids, carnitine, and fatty acids. These serum amino acids and metabolites (α-aminobutyric acid, proline, and alanine), carnitines (tradecanoylcarnitine, hexanylcarnitine, octanoylcarnitine, 2-methylbutyroylcarnitine, palmitoylcarnitine, and linoleylcarnitine) and fatty acids (9E-tetradecenoic acid) represent endogenous substances with diagnostic potential for cisplatin-induced AKI.

Ningxiang Pig-Derived Microbiota Affects the Growth Performance, Gut Microbiota, and Serum Metabolome of Nursery Pigs.

The gut microbiota is crucial for maintaining the host's intestinal homeostasis and metabolism. This study investigated the effects of fecal microbiota transplantation (FMT) from Ningxiang pigs on the growth performance, fecal microbiota, and serum metabolites of the same-old DLY pigs. The results indicated that the average daily gain of FMT pigs was significantly greater than that of the control (CON) group. Compared to the CON group, the FMT group significantly improved the apparent digestibility of crude fiber, crude ash, gross energy, and calcium of the pigs. The analysis of serum antioxidant status revealed that the activities of total superoxide dismutase and catalase in the serum of pigs in the FMT group were significantly elevated, whereas the level of malondialdehyde was significantly reduced. Furthermore, 16S rRNA sequencing analysis revealed that the Ningxiang pig-derived microbiota altered the fecal microbiota structure and modulated the diversity of the gut microbiota in the DLY pigs. Untargeted LC-MS metabolomics demonstrated that pigs in the FMT group exhibited distinct metabolomic profiles compared to those in the CON group. Significant changes were observed in key metabolites involved in amino acid, lipid, and carbohydrate metabolism. Additionally, a correlation analysis between serum differential metabolites and the gut microbiota revealed that the relative abundance of Lachnospiraceae_NK4A136_group and Corynebacterium was highly correlated with lipid compounds. In conclusion, Ningxiang pig-derived microbiota can alleviate oxidative stress and enhance growth performance in DLY pigs by modulating their gut microbiota and metabolic features.

Identifying biomarkers for nasopharyngeal carcinoma diagnosis and chemoradiotherapy response using serum endogenous small molecules profiling

Changes in metabolic characteristics are important features of tumor progression and prognosis, including nasopharyngeal carcinoma (NPC). Identifying serum metabolites as potential diagnostic and chemoradiotherapy response biomarkers for NPC is therefore crucial. In this study, ultra-performance liquid chromatography coupled with linear ion trap quadrupole orbitrap high-resolution mass spectrometry (UPLC-LTQ-Orbitrap MS) was used to analyze metabolic variations among controls, NPC patients, and NPC patients undergoing chemoradiotherapy (CRT). Univariate and multivariate analyses revealed seven differential metabolites between the control and NPC groups and eleven metabolites between the CRT and NPC groups. Five common metabolites, gluconic acid, palmitic acid, LysoPC (15:0/0:0), stearic acid, and LysoPC (20:2(11Z,14Z)/0:0), were consistently altered across groups. Notably, the first four metabolites were adjusted closer to normal after chemoradiotherapy, while this change is not reflected at LysoPC (20:2(11Z,14Z)/0:0). These common metabolites were enriched in five pathways. These findings underscore the importance of serum metabolite profiling in NPC diagnosis and treatment response assessment and offer a promising foundation for further clinical research.

An Analysis of the Intestinal Microbiome Combined with Metabolomics to Explore the Mechanism of How Jasmine Tea Improves Depression in CUMS-Treated Rats.

Recently, research has confirmed that jasmine tea may help improve the depressive symptoms that are associated with psychiatric disorders. Our team previously found that jasmine tea improved the depressive-like behavior that is induced by chronic unpredictable mild stress (CUMS) in Sprague Dawley (SD) rats. We hypothesized that the metabolic disorder component of depression may be related to the gut microbiota, which may be reflected in the metabolome in plasma. The influence of jasmine tea on gut microbiota composition and the association with depressive-related indexes were explored. Furthermore, the metabolites in plasma that are related to the gut microbiota were identified. SD rats were treated with control or CUMS and administrated jasmine tea for 8 weeks. The 16S rRNA gene amplicon sequencing was used to analyze the gut microbiota in feces samples, and untargeted metabolomics was used to analyze the metabolites in plasma. The results found that jasmine tea significantly ameliorated the depressive behavior induced by CUMS, significantly improved the neurotransmitter concentration (BDNF and 5-HT), and decreased the pro-inflammation levels (TNF-α and NF-κB). The intervention of jasmine tea also alleviated the dysbiosis caused by CUMS; increased the relative abundance of Bacteroides, Blautia, Clostridium, and Lactobacillus; and decreased Ruminococcus and Butyrivibrio in the CUMS-treated rats. Furthermore, the serum metabolites of the CUMS-treated rats were reversed after the jasmine tea intervention, i.e., 22 were up-regulated and 18 were down-regulated, which may have a close relationship with glycerophospholipid metabolism pathways, glycine serine and threonine metabolism pathways, and nicotinate and nicotinamide metabolism pathways. Finally, there were 30 genera of gut microbiota related to the depressive-related indexes, and 30 metabolites in the plasma had a strong predictive ability for depressive behavior. Potentially, our research implies that the intervention of jasmine tea can ameliorate the depression induced by CUMS via controlling the gut flora and the host's metabolism, which is an innovative approach for the prevention and management of depression.

Liraglutide ameliorates diabetic kidney disease by modulating gut microbiota and L-5-Oxoproline

The gut microbiome-metabolites-kidney axis is a potential target for treating diabetic kidney disease (DKD). Our previous study found that Liraglutide attenuated DKD in rats by decreasing renal tubular ectopic lipid deposition (ELD) and serum metabolites levels, including L-5-Oxoproline (5-OP). However, the response of gut microbiome-metabolites-kidney axis to Liraglutide in DKD rats and the effect of 5-OP on ELD remain unknown. In this study, Sprague-Dawley rats were used as an animal model of DKD. They were subjected to a high fat diet, streptozotocin and uninephrectomy, followed by Liraglutide treatment (0.4 mg/kg d). Additionally, HK-2 cells were incubated with 30 mM glucose and 200 μM palmitate for 24h, and exposed to different concentrations of 5-OP. In DKD rats, Liraglutide dramatically improved the renal tubule structure. It increased the Simpson index (F = 4.487, p = 0.035) and reduced the Actinobacteria-to-Bacteroidetes ratio (F = 6.189, p = 0.014). At the genus level, Liraglutide increased the relative abundance of Clostridium, Oscillospira, Sarcina, SMB53, and 02d06 while decreasing that of Allobaculum. Meanwhile, 13 metabolites were significantly altered after Liraglutide treatment. Multi-omics analysis found that 5-OP levels were positively correlated with Clostridium abundance but negatively correlated with renal injury related indicators. In HK-2 cells, 5-OP significantly reduced the ELD in a dose-dependent manner through inhibiting the expression of SREBP1 and FAS. Overall, the renoprotective effect of Liraglutide in DKD rats is linked to the improvement of the gut microbiota composition and increased serum 5-OP levels, which may reduce ELD in renal tubular cells by lowering lipid synthesis.

Identification of serum metabolites associated with polybrominated diphenyl ethers (PBDEs) exposure in papillary thyroid carcinoma: a case–control study

As the most common endocrine cancer, thyroid cancer (TC) has sharply increased globally over the past three decades. The growing incidence of TC might be counted by genetics, radiation, iodine, autoimmune disease, and exposure to environmental endocrine–disrupting chemicals (EDCs). Polybrominated diphenyl ethers (PBDEs), being typical EDCs, have been widely utilized in plastics, electronics, furniture, and textiles as flame retardants since the 1980s, and research has indicated a significant correlation between their exposure and the risk of TC. Even so, PBDEs exposure impact on the metabolic signature for TC remains unexplored. In this study, eight congeners of PBDEs were determined in serum from 111 patents with papillary thyroid cancer (PTC) and 111 healthy participants based on case–control epidemiology using gas chromatography–atmospheric pressure chemical ionization–tandem mass spectrometry (GC-APCI–MS/MS). Based on the tertile distribution of total PBDEs concentrations in 59 participants, metabolomics analysis was further performed by ultra-high performance liquid chromatography coupled to hybrid quadrupole–Orbitrap MS. In the partial correlation analysis, the 29 identified metabolites were correlated with PBDEs exposure (P < 0.05). In addition, PBDEs disrupted the metabolism of glycerophospholipids, sphingolipids, taurine, and hypotaurine, indicating that neurotransmitters, oxidative stress, and inflammation are the vulnerable pathways affected in PTC. Furthermore, (±)-octopamine and 5-hydroxyindole, both of which modulate the actions of neurotransmitters, emerged as potential disturbed metabolite markers for TC following exposure to PBDEs. This study analyzed the impact of PBDEs on PTC in terms of the metabolic changes and further explored possible biomarkers, which helped us have a deep understanding of the possible mechanism of the effects of PBDEs on TC.

Explore key genes of Crohn’s disease based on glycerophospholipid metabolism: A comprehensive analysis Utilizing Mendelian Randomization, Multi-Omics integration, Machine Learning, and SHAP methodology

Background and AimsCrohn’s disease (CD) is a chronic, complex inflammatory condition with increasing incidence and prevalence worldwide. However, the causes of CD remain incompletely understood. We identified CD-related metabolites, inflammatory factors, and key genes by Mendelian randomization (MR), multi-omics integration, machine learning (ML), and SHAP. MethodsWe first performed a mediation MR analysis on 1400 serum metabolites, 91 inflammatory factors, and CD. We found that certain phospholipids are causally related to CD. In the scRNA-seq data, monocytes were categorized into high and low metabolism groups based on their glycerophospholipid metabolism scores. The differentially expressed genes of these two groups of cells were extracted, and transcription factor prediction, cell communication analysis, and GSEA analysis were performed. After further screening of differentially expressed genes (FDR<0.05, log2FC>1), least absolute shrinkage and selection operator (LASSO) regression was performed to obtain hub genes. Models for hub genes were built using the Catboost, XGboost, and NGboost methods. Further, we used the SHAP method to interpret the models and obtain the gene with the highest contribution to each model. Finally, qRT-PCR was used to verify the expression of these genes in the peripheral blood mononuclear cells (PBMC) of CD patients and healthy subjects. ResultMR results showed 1-palmitoyl-2-stearoyl-gpc (16:0/18:0) levels, 1-stearoyl-2-arachidonoyl-GPI (18:0/20:4) levels, 1-arachidonoyl-gpc (20:4n6) levels, 1-palmitoyl-2-arachidonoyl-gpc (16:0/20:4n6) levels, and 1-arachidonoyl-GPE (20:4n6) levels were significantly associated with CD risk reduction (FDR<0.05), with CXCL9 acting as a mediation between these phospholipids and CD. The analysis identified 19 hub genes, with Catboost, XGboost, and NGboost achieving AUC of 0.91, 0.88, and 0.85, respectively. The SHAP methodology obtained the three genes with the highest model contribution: G0S2, S100A8, and PLAUR. The qRT-PCR results showed that the expression levels of S100A8 (p = 0.0003), G0S2 (p < 0.0001), and PLAUR (p = 0.0141) in the PBMC of CD patients were higher than healthy subjects. ConclusionMR findings suggest that certain phospholipids may lower CD risk. G0S2, S100A8, and PLAUR may be potential pathogenic genes in CD. These phospholipids and genes could serve as novel diagnostic and therapeutic targets for CD.

Integrated metabolomic and transcriptomic analysis reveals the effects and mechanisms of Jinqi Jiangtang tablets on type 2 diabetes

BackgroundType 2 diabetes (T2DM) is one of the major metabolic diseases and poses a serious challenge to human life and global economic development. Jinqi Jiangtang Tablets (JQJT) is effective in ameliorating the effects of T2DM, but the mechanism of JQJT is unclear. PurposeThis study integrated metabolomics and transcriptomics to reveal the mechanism by which JQJT improves T2DM. MethodsThe T2DM mouse model was established, and the effects of JQJT on improving T2DM were evaluated by determining the levels of blood lipids, fasting blood glucose (FBG), insulin metabolism and hepatic lipid accumulation in mice after JQJT administration for 8 weeks. Serum metabolites were detected using ultra-performance liquid chromatography/quadrupole time-of-flight-tandem mass spectrometry (UPLC-Q-TOF-MS) technology, and mouse liver differential genes were detected using transcriptomic technology. Correlation analysis was used to extract metabolites and RNA with correlations, and potential pathways were enriched and constructed using the common pathway analysis function of MetaboAnalyst 5.0. Finally, the expression of key target proteins and genes was verified by Western blot (WB) and Polymerase Chain Reaction (PCR) to further elucidate the mechanism by which JQJT improves T2DM. ResultsJQJT reduced FBG and lipid levels, improved insulin resistance (IR) and hepatic lipoatrophy in mice. A total of 35 differentially abundant metabolites were identified by metabolomics, and 328 differential genes were detected by transcriptomics. The integrated metabolomics and transcriptomics results suggested that JQJT may ameliorate T2DM mainly by regulating glucose and lipid metabolic pathways. WB and PCR results showed that JQJT regulates the insulin signaling pathway, involved in fatty acid metabolism, glycogen synthesis and catabolism. ConclusionsJQJT improved IR in T2DM mice by regulating the insulin signaling pathway, improving glycogen synthesis and glycolysis, and increasing hepatic triglyceride and fatty acid metabolism.

Causal relationship of inflammatory cytokines and serum metabolites in cerebral small vessel disease: a two-step Mendelian randomization study.

The aim was to investigate the causal relationships of inflammatory cytokines and serum metabolites in cerebral small vessel disease (CSVD). Bidirectional Mendelian randomization was first conducted to screen inflammatory cytokines and serum metabolites that were associated with imaging features of CSVD, including white matter hyperintensities, recent small subcortical infarcts, cortical cerebral microinfarcts, cerebral microbleeds, lacunes and enlarged perivascular spaces. Sensitivity analyses were performed to evaluate the robustness and pleiotropy of these results. Subsequently, inflammatory cytokines and serum metabolites that were associated with CSVD were subjected to functional enrichment. Finally, mediation analysis was employed to investigate whether inflammatory cytokines or serum metabolites acted as an intermediary for the other in their causal relationship with CSVD. Of the inflammatory cytokines, five were risk factors (e.g., tumour-necrosis-factor-related apoptosis-inducing ligand) and five (e.g., fibroblast growth factor 19) were protective factors for CSVD. Eleven serum metabolites that increased CSVD risk and 13 metabolites that decreased CSVD risk were also identified. The majority of these markers of CSVD susceptibility were lipid metabolites. Natural killer cell receptor sub-type 2B4 was determined to act as a mediating factor of an unidentified metabolite for the enlargement of perivascular spaces. Several inflammatory cytokines and serum metabolites had causal relationships with imaging features of CSVD. A natural killer cell receptor mediated in part the promotional effect of a metabolite on perivascular space enlargement.

Treatment response of venlafaxine induced alterations of gut microbiota and metabolites in a mouse model of depression.

Antidepressants remain the first-line treatment for depression. However, the factors influencing medication response are still unclear. Accumulating evidence implicates an association between alterations in gut microbiota and antidepressant response. Therefore, the aim of this study is to investigate the role of the gut microbiota-brain axis in the treatment response of venlafaxine. After chronic social defeat stress and venlafaxine treatment, mice were divided into responders and non-responders groups. We compared the composition of gut microbiota using 16S ribosomal RNA sequencing. Meanwhile, we quantified metabolomic alterations in serum and hippocampus, as well as hippocampal neurotransmitter levels using liquid chromatography-mass spectrometry. We found that the abundances of 29 amplicon sequence variants (ASVs) were significantly altered between the responders and non-responders groups. These ASVs belonged to 8 different families, particularly Muribaculaceae. Additionally, we identified 38 and 39 differential metabolites in serum and hippocampus between the responders and non-responders groups, respectively. Lipid, amino acid, and purine metabolisms were enriched in both serum and hippocampus. In hippocampus, the concentrations of tryptophan, phenylalanine, gamma-aminobutyric acid, glutamic acid, and glutamine were increased, while the level of succinic acid was decreased in the responders group, compared with the non-responders group. Our findings suggest that the gut microbiota may play a role in the antidepressant effect of venlafaxine by modulating metabolic processes in the central and peripheral tissues. This provides a novel microbial and metabolic framework for understanding the impact of the gut microbiota-brain axis on antidepressant response.

Cocaine-derived hippuric acid activates mtDNA-STING signaling in alcoholic liver disease: Implications for alcohol and cocaine co-abuse

The simultaneous abuse of alcohol-cocaine is known to cause stronger and more unpredictable cellular damage in the liver, heart, and brain. However, the mechanistic crosstalk between cocaine and alcohol in liver injury remains unclear. The findings revealed cocaine-induced liver injury and inflammation in both marmosets and mice. Of note, co-administration of cocaine and ethanol in mice causes more severe liver damage than individual treatment. The metabolomic analysis confirmed that hippuric acid (HA) is the most abundant metabolite in marmoset serum after cocaine consumption and that is formed in primary marmoset hepatocytes. HA, a metabolite of cocaine, increases mitochondrial DNA leakage and subsequently increases the production of proinflammatory factors via STING signaling in Kupffer cells (KCs). In addition, conditioned media of cocaine-treated KC induced hepatocellular necrosis via alcohol-induced TNFR1. Finally, disruption of STING signaling in vivo ameliorated co-administration of alcohol- and cocaine-induced liver damage and inflammation. These findings postulate intervention of HA-STING-TNFR1 axis as a novel strategy for treatment of alcohol- and cocaine-induced excessive liver damage.Graphical

Effects of Dietary Energy Levels on Growth Performance, Serum Metabolites, and Meat Quality of Jersey Cattle-Yaks.

Energy feed can provide animals with balanced nutrition, thereby enhancing their growth performance. This study aimed to evaluate the effects of dietary energy levels on the growth performance, serum metabolites, and meat quality of Jersey cattle-yaks. A total of 24 male Jersey cattle-yaks were randomly divided into three groups. Each group was fed diets with metabolizable energy levels of 8.21 MJ/kg (LE), 9.50 MJ/kg (ME), and 10.65 MJ/kg (HE), respectively. The HE and ME groups showed significantly higher final body weight, average daily gain (ADG), and feed efficiency compared to the LE group (p < 0.05). The glucose (GLU) and total cholesterol (TC) concentrations were significantly increased in the serum of the ME and HE groups (p < 0.05). The low-density lipoprotein cholesterol (LDL-C) and alanine aminotransferase (ALT) levels were significantly higher in the serum of the HE group than in the ME group (p < 0.05). Blood urea nitrogen (BUN) levels exhibited a significant decrease with increasing metabolizable energy levels in the diet (p < 0.05). Increasing dietary energy levels enhances the eye muscle area and intramuscular fat content of Jersey cattle-yaks (p < 0.05), with no effect on pH45 min, pH24 h, and shear force. In the HE group, the levels of heneicosanoic acid (C21:0), palmitoleic acid (C16:1), elaidic acid (C18:1n9t), and eicosadienoic acid (C20:2n6) were notably elevated (p < 0.05) when compared to the LE group. We concluded that a higher dietary energy level enhanced the growth performance and meat quality traits of male Jersey cattle-yaks.

Characteristics of dietary patterns, and serum metabolites during the low-gluten diet among Chinese young adults

The number of gluten-restricted dieters is growing, yet its impact on healthy diets and serum profiles is unclear. This study investigated the effects of a 2-week low-gluten diet (LGD) on the dietary patterns, serum metabolic profiles, and health status of 61 young individuals from a university in southeastern China. Data on food intake, serum metabolomics, blood biochemistry, and fecal SCFA were collected. This population was divided into four dietary patterns by k-means method:1 Processed food group (PB, n = 17), 2 Rice group (RB, n = 10), 3 Fish/shrimp-based group (SB, n = 4), and 4 Vegetable group (VB, n = 30). Serum metabolites and fecal SCFA were measured using HPLC-MS and GC-MS, respectively. After 2-week of LGD, the SB group had the highest diet diversity. There were remarked differences in nutrient intake among the four dietary patterns, but no differences in health indices or fecal SCFA. WGCNA method revealed the differences in metabolite metabolite modules 4 and 5, and 3-hydroxybutyric acid, hydrolyzed fumonisin（HFB1）, and palmitoleic acid were the different metabolites among clusters. Following a 2-week LGD, different dietary patterns lead to different nutrient intakes and serum metabolite profiles.

Impact of Partial Body Shielding from Very High Dose Rates on Untargeted Metabolomics in Biodosimetry.

A realistic exposure to ionizing radiation (IR) from an improvised nuclear device will likely include individuals who are partially shielded from the initial blast delivered at a very high dose rate (VHDR). As different tissues have varying levels of radiosensitivity, e.g., hematopoietic vs gastrointestinal tissues, the effects of shielding on radiation biomarkers need to be addressed. Here, we explore how biofluid (urine and serum) metabolite signatures from male and female C57BL/6 mice exposed to VHDR (5-10 Gy/s) total body irradiation (TBI, 0, 4, and 8 Gy) compare to individuals exposed to partial body irradiation (PBI) (lower body irradiated [LBI] or upper body irradiated [UBI] at an 8 Gy dose) using a data-independent acquisition untargeted metabolomics approach. Although sex differences were observed in the spatial groupings of urine signatures from TBI and PBI mice, a metabolite signature (N6,N6,N6-trimethyllysine, carnitine, propionylcarnitine, hexosamine-valine-isoleucine, taurine, and creatine) previously developed from variable dose rate experiments was able to identify individuals with high sensitivity and specificity, irrespective of radiation shielding. A panel of serum metabolites composed from previous untargeted studies on nonhuman primates had excellent performance for separating irradiated cohorts; however, a multiomic approach to complement the metabolome could increase dose estimation confidence intervals. Overall, these results support the inclusion of small-molecule markers in biodosimetry assays without substantial interference from the upper or lower body shielding.

Metabolomics Profiling of Serum and Urine from Chuanzang Black Pigs with Different Residual Feed Intake.

This study was conducted to evaluate associations of blood variables and urine variables with different residual feed intakes (RFIs) in growing Chuanzang black (CB) pigs. A total of 228 growing CB boars from 99 days were used. The same basal diet was offered ad libitum and individual feed intake and body weight were measured over a period of 181 d. The CB pigs were categorized based on their residual feed intake values, with six individuals each from the high and low ends selected and divided into two groups: the low residual feed intake group (LS) and the high residual feed intake group (HS). Serum and urine samples were collected at the end of the experiment for determination of metabolomics profiling. Results showed that there were significantly different metabolites in serum and urine of different RFI groups (fold-change, FC > 2.0 or FC < 0.5, and p < 0.05), and 21 metabolites were identified in serum and 61 in urine. Cluster analysis showed that 20 metabolites were up-regulated and one metabolite was down-regulated in serum; 44 metabolites were up-regulated and 17 metabolites were down-regulated in urine. Kyoto Encyclopedia of Genes and Genomes analysis showed that the differential metabolites of serum were enriched in linoleic acid metabolism, and the differential metabolites of urine were enriched in steroid hormone biosynthesis, taurine and hypotaurine metabolism, and primary bile acid biosynthesis. The correlations between serum metabolites and urine metabolites indicated a significant positive correlation between all fatty acyls in serum metabolites and L-glutamate in urine. However, no compelling genetic or blood biomarkers have been found to explain the differences in RFI, suggesting multiple approaches to effective feed use in pigs. This study provides new insights into the subsequent assessment of RFI by metabolomics profiling, as well as the development of novel feed additives for the factors that will facilitate future research directions in CB pigs.

Comparison of lipidome profiles in serum from lactating dairy cows supplemented with Acremonium terrestris culture based on UPLC-QTRAP-MS/MS

This study evaluated the effects of supplementing the diet of lactating cows with Acremonium terrestris culture (ATC) on milk production, serum antioxidant capacity, inflammatory indices, and serum lipid metabolomics. Over 90 days, 24 multiparous Chinese Holstein cows in mid-lactation (108 ± 10.4 days in milk, 637 ± 25 kg body weight, 30.23 ± 3.7 kg/d milk yield) were divided into either a control diet (CON) or a diet supplemented with 30 g of ATC daily. All the data were analyzed using Student’s t test with SPSS 20.0 software. The results showed that compared with CON feeding, ATC feeding significantly increased milk yield, antioxidant capacity, and immune function. Lipidome screening identified 143 lipid metabolites that differed between the two groups. Further analysis using “random forest” machine learning revealed three glycerophospholipid serum metabolites that could serve as lipid markers with a predictive accuracy of 91.67%. This study suggests that ATC can be a useful dietary supplement for improving lactational performance in dairy cows and provides valuable insights into developing nutritional strategies to maintain metabolic homeostasis in ruminants.

Voice-based depression assessment in patients with gynecological cancer.

161 Background: Although depression in patients with cancer can lead to a deterioration of treatment adherence and quality of life (QOL), diagnosis of depression in patients with cancer is difficult due to symptoms overlapping with side effects of cancer treatment such as fatigue. Traditional screening tools like the PHQ-9 questionnaire are underutilized in clinical practice. Recently, interest has grown in utilizing patients' voices to assess their mental well-being. This study aims to evaluate depression in patients with gynecological cancer and explore the usefulness of voice analysis as a depression detection tool. Methods: PHQ-9 scores were collected from 197 patients with gynecological cancer, with 28 cases undergoing longitudinal assessments at diagnosis, postoperatively, and during chemotherapy. Voice recordings were obtained from 70 patients at diagnosis, alongside serum samples from 22 patients. The PHQ-9 scores were compared across different treatment periods, with a specific focus on patients exhibiting a PHQ score of ≧10, who can be diagnosed with Major Depressive Disorder (MDD). The provision of supportive care for MDD patients was also verified. A random forest model was developed from voice features obtained from 70 patients, with hyperparameter tuning and cross-validation to predict mild depression. Serum metabolites were comprehensively analyzed between depression prediction group and normal prediction group by the depression prediction model. Results: Mean PHQ-9 scores decreased over time since diagnosis; initially 6.50 ± 4.99 (mean ±SD), post-operatively 6.18 ± 4.25, and during chemotherapy 4.88 ± 4.29. The frequencies of MDD also decreased over the clinical course; at diagnosis 24.3%, post-operatively 15.5%, and during chemotherapy 15.4%. Out of 17 cases of MDD during chemotherapy, only one (6.25%) received psychiatric intervention. All MDD cases during chemotherapy had PHQ-9 scores of 5 or higher, representing mild depression at diagnosis. Mild depression at diagnosis could be predicted with an AUC of 0.89 using voice features. Metabolites identified by the voice-based depression prediction model were associated with depression, such as xanthine, methionine, and taurocholic acid. Conclusions: Depression during chemotherapy is often not intervened. Patients with mild depression at diagnosis tend to develop MDD during chemotherapy. Voice-based mental health assessment at diagnosis is possibly a promising screening tool for depression during subsequent cancer treatment. Clinical trial information: UMIN000044266 .

Galacto-oligosaccharides modified whey protein isolate ameliorates cyclophosphamide-induced immunosuppression

The effect of whey protein isolate (WPI)- galacto-oligosaccharides (GOS)/fructo-oligosaccharides (FOS) conjugates on RAW264.7 cells, and further the effect of WPI-GOS conjugates on CTX-induced immunosuppressed mice were investigated. Compared to WPI-FOS conjugates, WPI-GOS conjugates exhibited deeper glycation extent, more pronounced structural unfolding and helix-destabilizing, and obviously improved functional indicators of RAW264.7 macrophages. In addition, WPI-GOS conjugates also repaired immune organ and intestinal barrier and increased IL-1β and IFN-γ levels in immunosuppressed mice. The alteration of gut microbiota induced by WPI-GOS conjugates changed the serum metabolites, causing the activation of NFκB pathway, which strengthens the immune system. The activation of NFκB pathway maybe associated with the mTOR signal pathway and ABC transporters. However, the precise mechanisms by which NFκB pathway interacts with mTOR signal pathway and ABC transporters to modulate the immune response need for further research.

Metabolic profiling of idiopathic pulmonary fibrosis in a mouse model: implications for pathogenesis and biomarker discovery.

Alterations in metabolites and metabolic pathways are thought to be important triggers of idiopathic pulmonary fibrosis (IPF), but our lack of a comprehensive understanding of this process has hampered the development of IPF-targeted drugs. To fully understand the metabolic profile of IPF, C57BL/6 J male mice were injected intratracheally with bleomycin so that it could be used to construct a mouse model of IPF, and lung tissues from 28-day and control IPF mice were analyzed by pathology and immunohistochemistry. In addition, serum metabolites from IPF mice were examined using LC-ESI-MS/MS, and the differential metabolites were analyzed for KEGG metabolic pathways and screened for biomarkers using machine learning algorithms. In total, the levels of 1465 metabolites were detected, of which 104 metabolites were significantly altered after IPF formation. In IPF mouse serum, 52% of metabolite expression was downregulated, with lipids (e.g., GP, FA) and organic acids and their derivatives together accounting for more than 70% of the downregulated differentially expressed metabolites. In contrast, FA and oxidised lipids together accounted for 60% of the up-regulated differentially expressed metabolites. KEGG pathway enrichment analyses of differential metabolites were mainly enriched in the biosynthesis of unsaturated fatty acids, pentose phosphate pathway, and alanine, aspartate, and glutamate metabolism. Seven metabolites were screened by machine learning LASSO models and evaluated as ideal diagnostic tools by receiver operating characteristic curves (ROCs). In conclusion, the serum metabolic disorders found to be associated with pulmonary fibrosis formation will help to deepen our understanding of the pathogenesis of pulmonary fibrosis.