ABSTRACT
BACKGROUND: Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength. However, current anti-resorptive drugs carry a risk of various complications. The deep learning-based efficacy prediction system (DLEPS) is a forecasting tool that can effectively compete in drug screening and prediction based on gene expression changes. This study aimed to explore the protective effect and potential mechanisms of cinobufotalin (CB), a traditional Chinese medicine (TCM), on bone loss. METHODS: DLEPS was employed for screening anti-osteoporotic agents according to gene profile changes in primary osteoporosis. Micro-CT, histological and morphological analysis were applied for the bone protective detection of CB, and the osteogenic differentiation/function in human bone marrow mesenchymal stem cells (hBMMSCs) were also investigated. The underlying mechanism was verified using qRT-PCR, Western blot (WB), immunofluorescence (IF), etc. RESULTS: A safe concentration (0.25 mg/kg in vivo, 0.05 µM in vitro) of CB could effectively preserve bone mass in estrogen deficiency-induced bone loss and promote osteogenic differentiation/function of hBMMSCs. Both BMPs/SMAD and Wnt/ß-catenin signaling pathways participated in CB-induced osteogenic differentiation, further regulating the expression of osteogenesis-associated factors, and ultimately promoting osteogenesis. CONCLUSION: Our study demonstrated that CB could significantly reverse estrogen deficiency-induced bone loss, further promoting osteogenic differentiation/function of hBMMSCs, with BMPs/SMAD and Wnt/ß-catenin signaling pathways involved.
ABSTRACT
Cancer stem cells (CSCs) are resistant to conventional cancer therapies, permitting the repopulation of new tumor growth and driving disease progression. Models for testing prostate CSC-propagated tumor growth are presently limited yet necessary for therapeutic advancement. Utilizing the congenic nontumorigenic NRP152 and tumorigenic NRP154 rat prostate epithelial cell lines, the present study investigated the self-renewal, differentiation, and regenerative abilities of prostate stem/progenitor cells and developed a CSC-based PCa model. NRP154 cells expressed reduced levels of tumor suppressor caveolin-1 and increased p-Src as compared to NRP152 cells. Gene knockdown of caveolin-1 in NRP152 cells upregulated p-Src, implicating their role as potential oncogenic mediators in NRP154 cells. A FACS-based Hoechst exclusion assay revealed a side population of stem-like cells (0.1%) in both NRP152 and NRP154 cell lines. Using a 3D Matrigel culture system, stem cells from both cell lines established prostaspheres at a 0.1% efficiency through asymmetric self-renewal and rapid proliferation of daughter progenitor cells. Spheres derived from both cell lines contained CD117+ and CD133+ stem cell subpopulations and basal progenitor cell subpopulations (p63+ and CK5+) but were negative for luminal cell CK8 markers at day 7. While some NRP152 sphere cells were androgen receptor (AR) positive at this timepoint, NRP154 cells were AR- up to 30 days of 3D culture. The regenerative capacity of the stem/progenitor cells was demonstrated by in vivo tissue recombination with urogenital sinus mesenchyme (UGM) and renal grafting in nude mice. While stem/progenitor cells from NRP152 spheroids generated normal prostate structures, CSCs and progeny cells from NRP154 tumoroids generated tumor tissues that were characterized by immunohistochemistry. Atypical hyperplasia and prostatic intraepithelial neoplasia (PIN) lesions progressed to adenocarcinoma with kidney invasion over 4 months. This provides clear evidence that prostate CSCs can repopulate new tumor growth outside the prostate gland that rapidly progresses to poorly differentiated adenocarcinoma with invasive capabilities. The dual in vitro/in vivo CSC model system presented herein provides a novel platform for screening therapeutic agents that target prostate CSCs for effective combined treatment protocols for local and advanced disease stages.
ABSTRACT
Objective:To explore the risk factors of the incidence of arrhythmia and the prediction of baseline ventricular late potential in patients with first depression episode.Methods:The cohort study was used to observe the relationship between the baseline status of ventricular late potential, the severity of baseline depression symptoms, the extent of remission of depressive symptoms within the treatment duration and arrhythmia incidence in the 3 years progress. For the assessment of the severity of depression symptoms, 17 version of Hamilton depression scale was used to evaluate the baseline ventricular late potential, and DMS lab3.0 ECG platform late potential analysis system was used to determine the assessment (CardioScan 12 NET version). The first depression patients with positive ventricular late potential were followed up for 3 years. The changes of the severity of ventricular late potential and depression symptoms were investigated, and the correlation with the subsequent course of arrhythmia was investigated.SPSS 20.0 software package was used for statistical distraction, chi square test was used for count data, independent samples t test was used for normal distribution measurement data, Mann-Whitney U test was used for non-normal distribution count data, and logistic regression method was used to calculate relative risk( RR). Results:According to the 3-year follow-up of 400 first-episode depression patients, 22.25% (89/400) had malignant arrhythmia. The incidence of malignant arrhythmia was 39.46% (58/147) in ventricular late potential positive group and 12.25% (31/253) in ventricular late potential negative group, and the difference was statistically significant(χ 2=9.578, P<0.01). Logistic regression analysis showed that positive ventricular late potential at baseline (compared with negative ventricular late potential at baseline, RR=10.78, 95% CI=8.34-13.80), having a family history of arrhythmia (compared with no family history of arrhythmia, RR=5.23, 95% CI=2.41-9.85), had a higher severity of depression at baseline (compared with lower severity of depression at baseline, RR=1.73, 95% CI=1.25-2.85), poor first-time efficacy and more repeated hospitalizations (compared with good first-time efficacy and less hospitalizations, RR=1.11, 95% CI=1.04-1.17), and age of onset< 20 (compared with age of onset≥20, RR=1.07, 95% CI=1.02-1.93) were the risk factors of malignant arrhythmia in patients with first-episode depression(all P<0.05). Conclusion:The incidence of arrhythmia is very high in those patients with baseline positive late ventricular potential. Positive late ventricular potential, family history of arrhythmia, younger onset age and poor therapeutic effect were the relative risk of arrhythmia in the patients with depression.
