I-R-Polar-Negative-0902

The study utilized Sprague Dawley rats that were time-dated for pregnancy. These rats weighed between 180-250 g and were 6-8 weeks old. The rats were at 14 days of gestation at the time of purchase, and they were obtained from BioLASCO in Taiwan. During the pre-experimental period, the experimental rats were given food and water ad libitum and housed in a room with a temperature range of 20°C to 25°C and a relative humidity range of 40%–60% for a duration of one week. A light–dark cycle of 12:12 hours was maintained. On day 17 of gestation, general anesthesia was induced in the animals with isoflurane, and the experimental and control groups underwent bilateral uterine vessel ligation and sham surgery, respectively. It was necessary to execute a midline laparotomy to expose the uterine horns and their blood vessels. The ligation locations were chosen based on the scientific literature (12). In order to maintain blood flow from both the iliac arteries and ovaries, the uterine vessels were ligated in the midsection of each uterine horn to increase the likelihood of fetal survival and decrease the probability of a partial miscarriage. The sham surgery performed on the control group did not involve ligation. After repositioning the uterus within the abdominal cavity, lidocaine was administered at the incision site (12, 13). On day 22 of gestation, every rat offspring was born naturally. Litter size was adjusted based on recommendations for testing maternal effects on reproductive/developmental toxicity (14, 15). Within 12 hours of birth, the litters were aggregated and reassigned at random to the mothers who delivered them. After the pups were euthanized on postnatal day 0 and 7, the control and IUGR groups reduced the litter size to nine and five pups, respectively, to ensure equal access to breast milk. On the seventh postnatal day, rats of both sexes were chosen at random from each group. Removed a single kidney and dissected it by cutting it longitudinally. The kidney is then placed under a magnifying glass and the cortex of the kidney was dissected from the medulla with a sharp scalpel, and kidney tissue was obtained for Western blot and metabolomic analysis. Samples of kidney tissue were trypsinized and flushed with phosphate-buffered saline (PBS) prior to resuspension (1500 rpm, 7 minutes). After aspiration of PBS, 100 L of lysate buffer and protease inhibitor are added. After 30 minutes on ice, the sample was centrifuged for 20 minutes at 12,000 rpm and 4°C in a microcentrifuge. The centrifuge tubes were placed on ice. The pellet was discarded while the supernatant was aspirated and deposited in a separate tube on ice. 30 g of proteins were resolved by 12% sodium dodecyl sulfate–polyacrylamide gel electrophoresis, electroblotted, and transferred to polyvinylidene difluoride membranes (ImmobilonP, Millipore, Bedford, MA, USA). Following blocking with 5% nonfat dried milk, the membranes were incubated with cleaved caspase 3 (1:1000, #9664, Cell Signaling Technology), Bax (1:750, B-9 sc-7480, Santa Cruz Biotechnology, Dallas, TX, USA), Bcl-2 (1:750, C-2 sc-7382, Santa Cruz Biotechnology), and anti-β-actin (1:1,000, C4 sc-47778, Santa Cruz Biotechnology). Subsequently, the samples were subjected to incubation with horseradish peroxidase–conjugated goat anti-mouse antibodies (Pierce Biotechnology, Rockford, IL, USA). The detection of protein bands was performed utilizing the BioSpectrum AC Imaging System (UVP, Upland, CA, USA).The kidney tissue samples were obtained by utilizing a 100 μL of methanol solution (Macron Chemicals, Center Valley, PA, USA) and H2O (Cat# W4502, Sigma-Aldrich, St. Louis, MO, USA; in a ratio of 7:3 v:v). Following two freeze-thaw cycles, the samples were subjected to vortexing. Following the centrifugation of each sample at 4°C and 12,000 × g for a duration of 15 minutes, the supernatant was collected, rapidly dried under vacuum, and dissolved in 0.3 mL of 50:50 mixture of H2O and CH3CN. The process of chromatographic separation was conducted utilizing a Waters ACQUITY ultraperformance liquid chromatography (UPLC) system. A UPLC BEH C18 guard column (1.7 μm, 5 mm) was employed as the reverse-phase column. The analytical column (1.7 μm, 2.1 × 100 mm), was kept at a temperature of 45°C. The mobile phase employed for linear gradient separation comprised of two components: (A) water with 0.1% formic acid, and (B) acetonitrile supplemented with 0.1% formic acid.The SYNAPT G2 quadrupole time-of-flight mass spectrometer (Waters MS Technologies, Manchester, UK) was utilized to conduct mass spectrometry (MS) analysis. The mass spectrometer was configured as follows: negative ion mode, capillary voltage of 2 kV, source temperature of 120°C, desolvation gas N2 at 900 L/h at 550°C, cone gas N2 at 15 L/h, capillary voltage of 2.8 kV, cone voltage of 40 V, and time-of-flight mass spectrometry (TOF MS) scan range of 50 to 1000 m/z. The Waters MS acquisition mode was utilized, and the data acquisition rate and interscan latency were 1.2 and 0.02 s, respectively. Simultaneous recording of the exact masses of all molecules was accomplished by rapidly cycling between two functions. The first function gathered data with a low impact energy of 4 eV for the collision cell trap and 2 eV for the collision cell transfer, while the second function gathered data with a modulated transfer collision energy of 15 to 25 eV. All analyses were conducted with a lockspray to guarantee precision and reproducibility. As the lockmass, we utilized leucine-enkephalin (m/z = 556.2771) at a concentration of 1 ng/L and a flow rate of 5 L/min. The data was collected in continuous mode with a 20-second lockspray interval. For all data collection, Waters MassLynx MS software (version 4.1) was employed.Progenesis QI software (Waters, Milford, MA, USA) was used to analyze the raw mass data generated using a Waters SYNAPT G2 for peak detection, extraction, alignment, and integration; the parameters were adjusted for each processing step. We regarded a difference of at least 1.2 fold between the median intensities of the two sample groups to indicate differential metabolite levels. The compounds associated with the pathway were compared to those listed in the Human Metabolome Database. Compound identification was performed using Progenesis QI, resulting in an overall score of 40 based on mass accuracy and isotope patterns for compound prediction. A minimum score of 36 or higher was utilized. The compounds were subjected to pathway enrichment analysis using MetaboAnalyst 5.0 and were afterwards compared with the Kyoto Encyclopedia of Genes and Genomes (KEGG). The quality control pool referencing method was applied to all intact MS samples, and it was seen that they aligned with the reference at a minimum of 90%, indicating the dependability of the 1.7-m ACQUITY Premier CSH Phenyl-Hexyl Column. The retention time and m/z pairs of distinct ions were combined through the use of adducts and isotope deconvolution techniques. This process allowed for the aggregation of the abundance of unique ions and the creation of distinctive characteristics, characterized by their retention time and m/z pairs, which are representative of unidentified metabolites. The data underwent normalization using Progenesis QI for all the characteristics. The abundance ratio of feature ions in a specific run to their corresponding value in the normalized reference was calculated by measuring each feature ion in every run. The data underwent Log10 transformations using Progenesis QI software in order to achieve normal distributions for each procedure and sample. Scalar estimation was then applied to change the Log10 distributions for the purpose of normalizing the reference data.The data is presented in the form of mean ± standard deviation. Statistical significance was determined when the p value was less than 0.05. One-way analysis of variance (ANOVA) was conducted using Progenesis QI to determine if there were any statistically significant differences between the IUGR and control groups. The pooled abundance data was analyzed using Progenesis QI to generate the fold change (FC) criterion, with a FC ≥1.2 being considered significant (16-18). Volcano plots were employed as a graphical representation to depict dysregulated metabolites, with the log2 fold change plotted against the negative logarithm of the p-value. Tentative and putative annotations in Progenesis QI were established by considering accurate mass measurements with an error of less than 5 ppm, similarity in isotope distribution, and manual matching of fragmentation spectra (if applicable) with databases such as the Human Metabolome Database, Metlin, MassBank, and the National Institute of Standards and Technology database. The MS data were subsequently employed for relative quantification through the utilization of the mixOmics package in R programming language. To reduce the dimensionality of the data, they were exported for unsupervised principal component analysis (PCA). To visualize data clustering and identify substantially different metabolites, we performed a supervised analysis, namely partial least-squares discriminant analysis (PLS-DA), and obtained variable importance in projection (VIP) scores. Each metabolite was compared between the groups using a univariate Student t test in MetaboAnalyst 5.0, and the Benjamini–Hochberg method was performed to adjust the p values for multiple testing with consideration of a 5% false discovery rate (q value). The metabolites with a VIP >1 and q <0.05 were considered significantly differing metabolites. Threefold cross-validation was performed to evaluate the goodness of fit of the PLS-DA model on the basis of R2 and Q2 values. Pathway analysis in MetaboAnalyst was performed using Fisher’s exact test to calculate the probability of finding a certain number of metabolites of a biological term of interest in a given list of compounds based on the KEGG.