Background and Objectives: Tracking of the tumor progression by MSCs-based therapy is being increasingly important in evaluating relative therapy effectively. Herein, Bioluminescence imaging (BLI) technology was used to dynamically and quantitatively track the hepatocellular carcinoma suppressive effects by human umbilical cord mesenchymal stem cells (UC-MSCs). Methods: and Results: The stem cells present typical phenotypic characteristics and differentiation ability by morphology and flow cytometry analysis of marker expression. Then, the growth inhibition effect of conditioned medium and UC-MSC on H7402 cells was studied. It is found both the conditioned medium and UC-MSC can effectively decrease the proliferation of H7402 cells compared with the control group. Meanwhile, the relative migration of UC-MSC to H7402 is also increased through the transwell migration assay. In addition, a mice hepatoma tumor model was built by H7402 cells which can express a pLenti-6.3/DEST-CMV-luciferase 2-mKate2 gene. The effect of stem cells on growth inhibition of tumor in a mice transplantation model was dynamically monitored by bioluminescence imaging within 5 weeks. It has shown the bioluminescence signal intensity of the tumor model was significantly higher than that of the UC-MSC co-acting tumor model, indicating that the inhibition of UC-MSC on liver cancer resulted in low expression of bioluminescent signals. Conclusions The microenvironment of UC-MSCs can effectively inhibit the growth of liver cancer cells, and this therapeutic effect can be dynamically and quantitatively monitored in vivo by BLI. This is of great significance for the imaging research and application of stem cells in anticancer therapy.

Purpose: Prostate cancer (PCa) is an epithelial malignancy that originates in the prostate gland and is generally categorized into low, intermediate, and high-risk groups. The primary diagnostic indicator for PCa is the measurement of serum prostate-specific antigen (PSA) values. However, reliance on PSA levels can result in false positives, leading to unnecessary biopsies and an increased risk of invasive injuries. Therefore, it is imperative to develop an efficient and accurate method for PCa risk stratification. Many recent studies on PCa risk stratification based on clinical data have employed a binary classification, distinguishing between low to intermediate and high risk. In this paper, we propose a novel machine learning (ML) approach utilizing a stacking learning strategy for predicting the tripartite risk stratification of PCa. Methods: Clinical records, featuring attributes selected using the lasso method, were utilized with 5 ML classifiers. The outputs of these classifiers underwent transformation by various nonlinear transformers and were then concatenated with the lasso-selected features, resulting in a set of new features. A stacking learning strategy, integrating different ML classifiers, was developed based on these new features. Results: Our proposed approach demonstrated superior performance, achieving an accuracy of 0.83 and an area under the receiver operating characteristic curve value of 0.88 in a dataset comprising 197 PCa patients with 42 clinical characteristics. Conclusions This study aimed to improve clinicians’ ability to rapidly assess PCa risk stratification while reducing the burden on patients. This was achieved by using artificial intelligence-related technologies as an auxiliary method for diagnosing PCa.

The obstacle to successful remyelination in demyelinating diseases, such as multiple sclerosis, mainly lies in the inability of oligodendrocyte precursor cells (OPCs) to differentiate, since OPCs and oligodendrocyte-lineage cells that are unable to fully differentiate are found in the areas of demyelination. Thus, promoting the differentiation of OPCs is vital for the treatment of demyelinating diseases. Shikimic acid (SA) is mainly derived from star anise, and is reported to have anti-influenza, anti-oxidation, and anti-tumor effects. In the present study, we found that SA significantly promoted the differentiation of cultured rat OPCs without affecting their proliferation and apoptosis. In mice, SA exerted therapeutic effects on experimental autoimmune encephalomyelitis (EAE), such as alleviating clinical EAE scores, inhibiting inflammation, and reducing demyelination in the CNS. SA also promoted the differentiation of OPCs as well as their remyelination after lysolecithin-induced demyelination. Furthermore, we showed that the promotion effect of SA on OPC differentiation was associated with the up-regulation of phosphorylated mTOR. Taken together, our results demonstrated that SA could act as a potential drug candidate for the treatment of demyelinating diseases.
Animals ; Apoptosis ; drug effects ; Cell Differentiation ; drug effects ; Cell Proliferation ; drug effects ; Cells, Cultured ; Demyelinating Diseases ; prevention & control ; Encephalitis ; prevention & control ; Encephalomyelitis, Autoimmune, Experimental ; prevention & control ; Female ; Mice, Inbred C57BL ; Myelin Basic Protein ; metabolism ; Neuroprotective Agents ; administration & dosage ; Oligodendrocyte Precursor Cells ; drug effects ; metabolism ; Rats ; Remyelination ; drug effects ; Shikimic Acid ; administration & dosage ; TOR Serine-Threonine Kinases ; metabolism

The correct differentiation of oligodendrocyte precursor cells (OPCs) is essential for the myelination and remyelination processes in the central nervous system. Determining the regulatory mechanism is fundamental to the treatment of demyelinating diseases. By analyzing the RNA sequencing data of different neural cells, we found that cyclin-dependent kinase 18 (CDK18) is exclusively expressed in oligodendrocytes. In vivo studies showed that the expression level of CDK18 gradually increased along with myelin formation during development and in the remyelination phase in a lysophosphatidylcholine-induced demyelination model, and was distinctively highly expressed in oligodendrocytes. In vitro overexpression and interference experiments revealed that CDK18 directly promotes the differentiation of OPCs, without affecting their proliferation or apoptosis. Mechanistically, CDK18 activated the RAS/mitogen-activated protein kinase kinase 1/extracellular signal-regulated kinase pathway, thus promoting OPC differentiation. The results of the present study suggest that CDK18 is a promising cell-type specific target to treat demyelinating disease.

The differentiation and maturation of oligodendrocyte precursor cells (OPCs) is essential for myelination and remyelination in the CNS. The failure of OPCs to achieve terminal differentiation in demyelinating lesions often results in unsuccessful remyelination in a variety of human demyelinating diseases. However, the molecular mechanisms controlling OPC differentiation under pathological conditions remain largely unknown. Myt1L (myelin transcription factor 1-like), mainly expressed in neurons, has been associated with intellectual disability, schizophrenia, and depression. In the present study, we found that Myt1L was expressed in oligodendrocyte lineage cells during myelination and remyelination. The expression level of Myt1L in neuron/glia antigen 2-positive (NG2) OPCs was significantly higher than that in mature CC1 oligodendrocytes. In primary cultured OPCs, overexpression of Myt1L promoted, while knockdown inhibited OPC differentiation. Moreover, Myt1L was potently involved in promoting remyelination after lysolecithin-induced demyelination in vivo. ChIP assays showed that Myt1L bound to the promoter of Olig1 and transcriptionally regulated Olig1 expression. Taken together, our findings demonstrate that Myt1L is an essential regulator of OPC differentiation, thereby supporting Myt1L as a potential therapeutic target for demyelinating diseases.
Animals ; Cell Differentiation ; physiology ; Demyelinating Diseases ; chemically induced ; Lysophosphatidylcholines ; toxicity ; Mice ; Mice, Inbred C57BL ; Nerve Tissue Proteins ; metabolism ; Oligodendrocyte Precursor Cells ; cytology ; metabolism ; Oligodendroglia ; cytology ; metabolism ; Remyelination ; physiology ; Transcription Factors ; metabolism