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The dataset was normalized by applying summation and logarithmic transformations, and then proceeded to undergo a comprehensive set of statistical analyses. Principal Component Analysis (PCA) was conducted (Figure 3A), which revealed distinct separations and highlighted metabolic differences. Subsequently, an Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) model was developed, with the resulting scores depicted in Figure 3B, demonstrating the model's discriminatory effectiveness. In the evaluation of 618 metabolites, volcano plots comparing AISF and blood samples identified 146 differential metabolites, with tissue fluid exhibiting both down-regulated and up-regulated metabolites (Figure 3C). Additionally, a heatmap was created to provide a comparative overview of the top 50 differential metabolites (Figure 3D).
To assess the reliability of the sampling method, serotonin and lactic acid were utilized as positive controls representing tissue fluid components and blood, respectively. The results aligned with the established distribution patterns of these components across various body fluids, as illustrated in Figure 4. Supplementary Figure 1 shows the stability of lactate and serotonin in microdialysate aliquots stored at -80 °C.
The 146 differential metabolites were systematically classified into several categories: nucleosides, nucleotides, and their analogues; fatty acids and their derivatives; amino acids, peptides, and their analogues; carbohydrates and carbohydrate conjugates; organic acids and their derivatives; biogenic amines; purines and pyrimidines; vitamins and steroids; as well as other compounds (Figure 5A). Supplementary Table 1 shows differential metabolites detected in blood.Heatmap analyses further elucidate the enrichment patterns of biogenic amines and amino acids, peptides, and their analogues across various body fluids (Figure 5B,C). Differential metabolite enrichment analysis is presented in Figure 6. Supplementary Table 2 lists the coefficient of variation (CV) for fifteen randomly selected metabolites in three consecutive perivascular tissue-fluid samples.

Figure 1: Images of the experimental apparatus. (A) Refrigerated fraction collector. (B) Syringe pump. (C) Microsyringes. (D) Surgical instruments, including vascular scissors and tweezers, etc. (E) Anesthesia machine. (F) Microdialysis probes. (G) Microdialysis probes, tissue guide needle, and a tearable tube. (H) Tissue guide needle assemblies. Please click here to view a larger version of this figure.

Figure 2: The key steps in the study. (A) A schematic representation depicting a diagram illustrating the positioning of the surgical site and the orientation of the probe. (B) Identification of critically vascular junctions to ensure precise observation of probe placement sites. (C) Insertion of the guide needle that penetrates the skin and advances into the tissue space. (D) Retraction of the guide pin needles is withdrawn, leaving the tearable tube within the tissue. (E) The microdialysis probe is introduced into the tissue via the established channel. (F) Gentle retraction of the tearable tube. The tearable tube is gently retracted after securing the probe in place. (G) Visualization of probes positioned in the epithelium of the femoral arterial and venous vessels. (H) Separation of tissue from the jugular vein. (I) Placement of the probe in the jugular vein. (J) The microdialysis probe is fixed on the skin surface. (K) isolation of the jugular vein. (L) Insertion of the probe into the jugular vein. Please click here to view a larger version of this figure.

Figure 3: Multivariate statistical analysis of interstitial fluid (ISF) and blood. (A) The data have been downscaled to emphasize significant separations, demonstrating distinct differences between ISF and blood components. (B) The orthogonal partial least squares discriminant analysis (OPLS-DA) model scores indicate R2Y and Q2 values of 0.925 and 0.811, respectively. (C) The volcano plot depicts 146 differential metabolites, with 85 metabolites down-regulated and 61 up-regulated in ISF. (D) Correspondingly, heatmaps contrasting the top 30 metabolites in ISF and blood reveal a clear distinction between the two sets of components. Please click here to view a larger version of this figure.

Figure 4: The presentation of a series of box plots elucidated the enrichment levels of lactate and serotonin in ISF and blood. All data points represent mean ± SEM; error bars are shown for all quantitative panels. Panel (A) illustrates that ISF samples exhibit a significantly greater enrichment of lactate compared to blood samples. In contrast, panel (B) demonstrates that serotonin is more enriched in blood samples, which concurrently display lower lactate levels. Please click here to view a larger version of this figure.

Figure 5: The classification ring chart of differential metabolites and the heat map of amino acids, peptides, and analogues, as well as biogenic amines, are depicted. (A) Each color block corresponds to a distinct class of metabolites. Amino acids, peptides, and analogues represent the largest category, comprising 19.29% of the total, followed by nucleosides, nucleotides, and analogues (15%), fatty acids and derivatives (12.86%), carbohydrates and carbohydrate conjugates (7.86%), organic acids and derivatives (10%), biogenic amines (7.14%), purines/pyrimidines (5.71%), vitamins and steroids (8.57%), and other compounds, including indoles, azepines, pyridines, and benzenes, at 13.57%. (B) In interstitial fluid (ISF), the enrichment levels of compounds such as Deoxycarnitine and Spermidine within the biogenic amines category are significantly elevated compared to those in blood, whereas the levels of Serotonin (D4), Serotonin, Tryptamine, and related compounds are significantly reduced. (C) In ISF, the majority of metabolites associated with amino acids, peptides, and analogues are markedly lower than those observed in blood. Please click here to view a larger version of this figure.

Figure 6: Metabolite set enrichment analysis (MSEA) of normal interstitial fluid revealed that metabolic activity is predominantly distributed across pathways related to energy production, redox homeostasis, and amino acid turnover. The top enriched pathways include butanoate metabolism, purine metabolism, and glutathione metabolism, reflecting the maintenance of mitochondrial energy supply and antioxidant capacity under physiological conditions. Additionally, several amino acid-related pathways, such as arginine and proline metabolism, tryptophan metabolism, and cysteine and methionine metabolism, are represented, indicating active amino acid interconversion and nitrogen balance regulation in the extracellular microenvironment. These findings suggest that the normal interstitial metabolome maintains a dynamic equilibrium between bioenergetic processes, oxidative defense, and amino acid metabolism, supporting tissue homeostasis and microcirculatory stability. Please click here to view a larger version of this figure.
Supplementary Figure 1: Stability of lactate and serotonin in microdialysate aliquots stored at -80 °C. Data are mean ± SEM (n = 6 replicates per time point). No analyte deviated >5% from baseline over 72 h. Please click here to download this File.
Supplementary Table 1: Differential metabolites detected in blood and adventitial interstitial fluid microdialysate. This includes metabolite name, fold-change (FC), Student's t-test P value, and VIP (OPLS-DA). Please click here to download this File.
Supplementary Table 2: Coefficient of variation (CV) for fifteen randomly selected metabolites in three consecutive perivascular tissue-fluid samples. All CVs are <20%. Please click here to download this File.