Integrated multi-omics analysis reveals molecular changes associated with chronic lipid accumulation following contusive spinal cord injury.

Functional and pathological recovery after spinal cord injury (SCI) is often incomplete due to the limited regenerative capacity of the central nervous system (CNS), which is further impaired by several mechanisms that sustain tissue damage. Among these, the chronic activation of immune cells can cause a persistent state of local CNS inflammation and damage. However, the mechanisms that sustain this persistent maladaptive immune response in SCI have not been fully clarified yet. In this study, we integrated histological analyses with proteomic, lipidomic, transcriptomic, and epitranscriptomic approaches to study the pathological and molecular alterations that develop in a mouse model of cervical spinal cord hemicontusion. We found significant pathological alterations of the lesion rim with myelin damage and axonal loss that persisted throughout the late chronic phase of SCI. This was coupled by a progressive lipid accumulation in myeloid cells, including resident microglia and infiltrating monocyte-derived macrophages. At tissue level, we found significant changes of proteins indicative of glycolytic, tricarboxylic acid cycle (TCA), and fatty acid metabolic pathways with an accumulation of triacylglycerides with C16:0 fatty acyl chains in chronic SCI. Following transcriptomic, proteomic, and epitranscriptomic studies identified an increase of cholesterol and m6A methylation in lipid-droplet-accumulating myeloid cells as a core feature of chronic SCI. By characterizing the multiple metabolic pathways altered in SCI, our work highlights a key role of lipid metabolism in the chronic response of the immune and central nervous system to damage.

Evaluation of analgesic and anti-inflammatory activities of Rubia cordifolia L. by spectrum-effect relationships.

The objective of the current work was to evaluate the spectrum-effect relationships between high-performance liquid chromatography fingerprints and analgesic and anti-inflammatory effects of Rubia cordifolia L. extract (RCE), and to identify active components of RCE. Chemical fingerprints of ten batches of RC from various sources were obtained by HPLC, and similarity and hierarchical clustering analyses were carried out. Pharmacodynamic assays were performed in adjuvant-induced arthritis rat model to assess the analgesic and anti-inflammatory properties of RCE. The spectrum-effect relationships between chemical fingerprints and the analgesic and anti-inflammatory effects of RCE were established by gray correlation analysis. UPLC-ESI-MS was used to identify the structures of potential active components, by reference standards comparison. The results showed that a close correlation existed between chemical fingerprints with analgesic and anti-inflammatory activities, and alizarin, 6-hydroxyrubiadin, purpurin and rubiadin might be the active constituents of RCE. In addition, RCE attenuated pathological changes in adjuvant-induced arthritis. The current findings provide a strong basis for combining chemical fingerprints with analgesic and anti-inflammatory activities in assessing the spectrum-effect relationships of RCE.

Qualitative and Quantitative Analysis of Volatile Components of Zhengtian Pills Using Gas Chromatography Mass Spectrometry and Ultra-High Performance Liquid Chromatography.

Zhengtian pills (ZTPs) are traditional Chinese medicine (TCM) which have been commonly used to treat headaches. Volatile components of ZTPs extracted by ethyl acetate with an ultrasonic method were analyzed by gas chromatography mass spectrometry (GC-MS). Twenty-two components were identified, accounting for 78.884% of the total components of volatile oil. The three main volatile components including protocatechuic acid, ferulic acid, and ligustilide were simultaneously determined using ultra-high performance liquid chromatography coupled with diode array detection (UHPLC-DAD). Baseline separation was achieved on an XB-C18 column with linear gradient elution of methanol-0.2% acetic acid aqueous solution. The UHPLC-DAD method provided good linearity (R (2) ≥ 0.9992), precision (RSD < 3%), accuracy (100.68-102.69%), and robustness. The UHPLC-DAD/GC-MS method was successfully utilized to analyze volatile components, protocatechuic acid, ferulic acid, and ligustilide, in 13 batches of ZTPs, which is suitable for discrimination and quality assessment of ZTPs.