MetaboLights

application/xml

ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/m_MTBLS15192_LC-MS_alternating_reverse-phase_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/s_MTBLS15192.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/a_MTBLS15192_LC-MS_alternating_reverse-phase.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CN_QC2_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121546-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121547-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CN_QC1_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CN_blank_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CP_blank_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121543-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121538-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121543-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121548-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121545-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121550-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CP_QC1_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121544-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CP_QC3_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121540-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CN_QC3_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121537-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121542-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_1257549_CP_QC2_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121549-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121539-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121552-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121549-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121550-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121548-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121544-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121538-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121540-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121545-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121541-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121551-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121547-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121552-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121551-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121546-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121541-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CN1_FZTM220121537-1A_neg.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121539-1A_pos.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192/FILES/HF2_CP1_FZTM220121542-1A_pos.rawprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15192The identified metabolites were annotated using the KEGG database (https://www.genome.jp/kegg/pathway.html), HMDB database (https://hmdb.ca/metabolites), and LIPIDMaps database (http://www.lipidmaps.org/). For multivariate statistical analysis, the metabolomic data were normalized and processed using the metaX software [6], followed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to calculate the variable importance in the projection (VIP) value of each metabolite. For univariate analysis, the Student’s t-test was applied to evaluate the statistical significance (P value) of each metabolite between the two groups, and the fold change (FC) was calculated to reflect the differential expression level of metabolites. The default screening criteria for differentially expressed metabolites were set as VIP > 1, P < 0.05, and FC ≥ 2 or FC ≤ 0.5. Volcano plots were generated using the R package ggplot2 based on three key parameters, including the VIP value, log2(fold change), and -log10(P value), to screen candidate differential metabolites. Cluster heatmaps were plotted using the R package pheatmap, and metabolite data were standardized utilizing the z-score normalization method. The Pearson correlation analysis of differential metabolites was performed via the cor() function in R, and the statistical significance of correlation coefficients was verified using the cor.mtest() function; correlations with P < 0.05 were considered statistically significant, and the correlation network diagram was visualized using the R package corrplot. Bubble plots were drawn with the ggplot2 package for KEGG functional enrichment analysis. Metabolic pathways were regarded as enriched when the ratio of annotated metabolite numbers to background gene numbers satisfied the enrichment threshold, and pathways with P < 0.05 were defined as significantly enriched pathways.MetaboLightsPublicLiquid Chromatography MS - alternating - reverse-phaseChromatographic separation was performed using a Hypersil Gold C18 column at 40 °C with a flow rate of 0.2 mL/min. For the positive ionization mode, mobile phase A consisted of 0.1% formic acid in water and mobile phase B was pure methanol; for the negative ionization mode, mobile phase A was 5 mM ammonium acetate aqueous solution (pH 9.0) and mobile phase B was methanol. The gradient elution procedure was set as follows: 0–1.5 min, 98% A / 2% B; 1.5–3 min, linearly changed to 15% A / 85% B; 3–10 min, linearly changed to 0% A / 100% B; 10.1–12 min, maintained at 98% A / 2% B. Mass spectrometry detection was conducted with an electrospray ionization (ESI) source over a mass scan range of m/z 100–1500, with the following parameters: spray voltage of 3.5 kV, sheath gas flow rate of 35 psi, auxiliary gas flow rate of 10 L/min, capillary temperature of 320 °C, S-lens RF level of 60, auxiliary gas heater temperature of 350 °C, and both positive and negative ionization modes were applied; data-dependent MS/MS acquisition was performed for secondary scanning.Isoquercitrin alleviates subchronic high-altitude hypoxia-induced myocardial injury by regulating mitochondrial energy metabolism and maintaining immune–inflammatory homeostasis.Academy of Military SciencesZhao Jiaoblankmyocardiummass spectrometry assayPlease update the A total of 100 mg of tissue powder ground in liquid nitrogen was transferred into an EP tube, and 500 μL of 80 percent aqueous methanol solution was added.The mixture was vortexed thoroughly, incubated on ice for 5 min, and centrifuged at 15,000 g and 4 °C for 20 min.An appropriate volume of the supernatant was collected and diluted with mass spectrometry-grade water to adjust the final methanol concentration to 53 percent.The diluted solution was centrifuged again at 15,000 g and 4 °C for 20 min. The final supernatant was collected for subsequent LC-MS analysis s protocol descriptionQuality control (QC) samplesEqual volumes of all individual experimental samples were mixed thoroughly to prepare the QC sample.Blank samplesA 53 percent aqueous methanol solution was used as the blank sample, which underwent the identical pretreatment procedures as the experimental samples.blankRattus norvegicushttps://www.ebi.ac.uk/metabolights/MTBLS15192Zhao Jiao. Academy of Military Sciences. 1256132920@qq.com.Wang Xinxing. Academy of Military Sciences. wxxemail@sina.cn.he acquired raw data (.raw) were imported into Compound Discoverer 3.1 for data processing. Simple parameter screening of each metabolite was performed based on retention time, mass-to-charge ratio (m/z), and other indices. Peak alignment across different samples was conducted with a retention time deviation of 0.2 min and a mass tolerance of 5 ppm to improve the accuracy of metabolite identification. Subsequently, peak picking and peak area quantification were performed by setting a mass tolerance of 5 ppm, a signal intensity deviation of 30%, a signal-to-noise ratio of 3, minimum signal intensity, and adduct ion parameters, followed by target ion integration. Molecular formula prediction was implemented based on molecular ion peaks and fragment ions. The predicted molecular formulas were further matched against the mzCloud (https://www.mzcloud.org/), mzVault, and Masslist databases. Blank samples were used to remove background ions, and the original quantitative results were standardized to obtain final metabolite identification and relative quantification results. All data processing procedures were performed on the Linux operating system (CentOS 6.6) using R and Python programming languages. Detailed information on specific program packages and software versions is provided in the readme file of the results.TreatmentHypoxia exposureBiological replicate1256132920@qq.comAll animal experiments were carried out in accordance with the Guide for the Care and Use of Laboratory Animals (8th edition, 2011), issued by the National Institutes of Health and approved by the Laboratory Animal Welfare Ethics Committee of the Institute of Environmental and Occupational Medicine. Healthy SPF-grade male Wistar rats (240–280 g, 7–8 weeks old) were purchased from Charles River Laboratory Animal Technology Co., Ltd. (Beijing, China). The rats were acclimatized for one week to an environment with a 12-h light/dark cycle, temperature of 20°C–23°C, and humidity of 50%–80%, with ad libitum access to food and water.Rats were randomly assigned to the following three groups (n = 10 per group): normoxic control (Control), hypoxic control (HC), and IQ-treated hypoxia (SH). A hypobaric hypoxic environment simulating 6,000 m in altitude was established using an animal high-altitude hypobaric chamber (Tianjin Weisi Instrument Co., Ltd., China), with ambient oxygen concentration maintained at 10.8%–9.7%. Rats in the Control and HC groups were intragastrically administered 0.5% sodium carboxymethyl cellulose (CMC-Na; Yuanye, R27342), whereas those in the SH group received 60 mg/kg IQ (Yuanye, B21529). After 15 days of acclimation and gavage under normoxic conditions, rats in the HC and SH groups were transferred to the hypobaric chamber for daily hypoxic exposure (20 h/day). During the 4 h/day out-of-chamber period, gavage administration, feeding, water replacement, and cage bedding changes were conducted. This protocol was maintained for 30 consecutive days. Rats in the Control group were housed under identical normoxic conditions without hypoxic exposure. At the end of the experiment, body weight was measured. The rats were anesthetized with isoflurane, and blood was collected via the abdominal aorta for serum separation and storage at −80°C. The heart was excised and weighed. One portion was fixed for paraffin embedding, another was preserved in electron microscopy fixative at 4°C for ultrastructural analysis, and the remainder was snap-frozen in liquid nitrogen for subsequent assays.Metabolomicspooled quality control sampleMetabolomicsnormalProteoWizard msconvertMyocardial fibrosisblankuntargeted analysissolvent blankRattus norvegicusmyocardiummyocardium hypertrophyexperimental sampleThermo Scientific Vanquish UHPLC SystemThermo Scientific Q Exactive HFpooled quality control sampleMetabolomicsnormalProteoWizard msconvertMyocardial fibrosisblankuntargeted analysissolvent blankRattus norvegicusmyocardiummyocardium hypertrophyexperimental sampleThermo Scientific Vanquish UHPLC SystemThermo Scientific Q Exactive HFThe scanning range is selected as m/z 100-1500; the settings for the ESI source are as follows: Spray Voltage: 3.5kV; Sheath gas flow rate: 35psi; Aux Gas flow rate: 10L/min; Capillary Temp: 320°C; S-lens RF level: 60; Aux gas heater temp: 350°C; Polarity: positive, negative; MS/MS secondary scanning is data-dependent scanningfalseIsoquercitrin alleviates subchronic high-altitude hypoxia-induced myocardial injury by regulating mitochondrial energy metabolism and maintaining immune–inflammatory homeostasisHigh-altitude hypoxia induces myocardial metabolic disorders, structural remodeling, and functional impairment, which threaten the health of highland populations. The interventional effects and molecular mechanisms of isoquercitrin (IQ), a natural flavonoid with cardiovascular protective activity, against high-altitude hypoxic cardiac injury are unclear. Taken together, the results indicate that IQ mitigates subchronic high-altitude hypoxia-induced myocardial metabolic reprogramming and functional injury through multitarget synergistic regulation of the hematopoietic–immune–energy metabolic network, thus offering a novel therapeutic strategy for preventing and treating high-altitude heart disease.2026-07-292026-07-29MTBLS15192