Evaluation of genetic response of mesenchymal stem cells to nanosecond pulsed electric fields by whole transcriptome sequencing.

BACKGROUND: Mesenchymal stem cells (MSCs) modulated by various exogenous signals have been applied extensively in regenerative medicine research. Notably, nanosecond pulsed electric fields (nsPEFs), characterized by short duration and high strength, significantly influence cell phenotypes and regulate MSCs differentiation via multiple pathways. Consequently, we used transcriptomics to study changes in messenger RNA (mRNA), long noncoding RNA (lncRNA), microRNA (miRNA), and circular RNA expression during nsPEFs application. AIM: To explore gene expression profiles and potential transcriptional regulatory mechanisms in MSCs pretreated with nsPEFs. METHODS: The impact of nsPEFs on the MSCs transcriptome was investigated through whole transcriptome sequencing. MSCs were pretreated with 5-pulse nsPEFs (100 ns at 10 kV/cm, 1 Hz), followed by total RNA isolation. Each transcript was normalized by fragments per kilobase per million. Fold change and difference significance were applied to screen the differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to elucidate gene functions, complemented by quantitative polymerase chain reaction verification. RESULTS: In total, 263 DEGs were discovered, with 92 upregulated and 171 downregulated. DEGs were predominantly enriched in epithelial cell proliferation, osteoblast differentiation, mesenchymal cell differentiation, nuclear division, and wound healing. Regarding cellular components, DEGs are primarily involved in condensed chromosome, chromosomal region, actin cytoskeleton, and kinetochore. From aspect of molecular functions, DEGs are mainly involved in glycosaminoglycan binding, integrin binding, nuclear steroid receptor activity, cytoskeletal motor activity, and steroid binding. Quantitative real-time polymerase chain reaction confirmed targeted transcript regulation. CONCLUSION: Our systematic investigation of the wide-ranging transcriptional pattern modulated by nsPEFs revealed the differential expression of 263 mRNAs, 2 miRNAs, and 65 lncRNAs. Our study demonstrates that nsPEFs may affect stem cells through several signaling pathways, which are involved in vesicular transport, calcium ion transport, cytoskeleton, and cell differentiation.

Metabolomics investigation of cutaneous T cell lymphoma based on UHPLC-QTOF/MS.

OBJECTIVES: The identification of cutaneous T cell lymphoma (CTCL) biomarkers may serve as a predictor of disease progression and treatment response. The aim of this study was to map potential biomarkers in CTCL plasma. DESIGN AND METHODS: Plasma metabolic perturbations between CTCL cases and healthy individuals were investigated using metabolomics and ultrahigh performance liquid chromatography­quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS). RESULTS: Principal component analysis (PCA) of the spectra showed clear metabolic changes between the two groups. Thirty six potential biomarkers associated with CTCL were found. CONCLUSIONS: Based on PCA, several biomarkers were determined and further identified by LC/MS/MS analysis. All of these could be potential early markers of CTCL. In addition, we established that heparin as anticoagulant has better pre-treatment results than EDTA with the UHPLC-QTOF/MS approach.

[Quantitative calculation of drugs distribution parameter in the brain extracellular space by using MRI tracer].

OBJECTIVE: To build a mathematical model to simulate the drug distribution accompanying with diffusion, distribution and clearance in the brain extracellular space (ECS). METHODS: Magnetic resonance imaging (MRI) technology was used to monitor changes in the signal-intensity-related tracer gadolinium-diethylene triamine pentaacetic acidm(Gd-DTPA), as an external drug which was injected into the rat brain, and then the mathematical model was built by using the data to establish the diffusion, distribution and clearance process of Gd-DTPA in the brain ECS. The model equation was resolved by Laplace transform. In the sphere coordinates, the linear regressive model was adopted to obtain the estimation method of diffusion coefficient, clearance rate of drugs distribution in the brain ECS. RESULTS: The diffusion coefficient D and the clearance rate k were obtained as (2.73±0.364)×10(-4) mm(2)/s and (1.40±0.206)×10(-5) /s, respectively. CONCLUSION: The proposed method can accurately reflect the isotropic drug distribution in the brain ECS, and can serve as the foundation to further solve problems about the orthotropic distribution in the brain ECS.