Correlation between genetic alterations and clinicopathological features of papillary thyroid carcinomas.

OBJECTIVE: To investigate the correlations between multigene alterations and clinicopathological features in papillary thyroid carcinoma (PTC) samples. METHODS: In this retrospective study, 111 cytological specimens of thyroid nodules, including 74 PTC samples and 37 benign samples, were analyzed using a 22-gene mutation assay employing next-generation sequencing. Clinicopathological information was retrospectively collected and analyzed. RESULTS: Gene alterations were associated with a higher rate of lymph node metastasis (LNM) and thyroid capsular invasion, a lower rate of coexisting Hashimoto's thyroiditis, the classical PTC subtype, and younger age (<45 years). Among the 22 genes tested, the BRAF mutation rates showed a significant difference between the PTC and benign groups. In the subgroup analysis, younger age (odds ratio = 12.512, 95% confidence interval: 3.126-50.087) was an independent risk factor for LNM. In further analyses, BRAF mutation was significantly associated with LNM in the older subgroup (age ≥ 45 years), suggesting that the BRAF mutation test has greater value for determining PTC prognosis in the older age group. CONCLUSIONS: Our findings will provide a more comprehensive understanding of the relationship between gene mutations and PTC and may contribute to improved PTC management.

A multi-variable predictive warning model for cervical cancer using clinical and SNPs data.

Introduction: Cervical cancer is the fourth most common cancer among female worldwide. Early detection and intervention are essential. This study aims to construct an early predictive warning model for cervical cancer and precancerous lesions utilizing clinical data and simple nucleotide polymorphisms (SNPs). Methods: Clinical data and germline SNPs were collected from 472 participants. Univariate logistic regression, least absolute shrinkage selection operator (LASSO), and stepwise regression were performed to screen variables. Logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), extreme gradient boosting(XGBoost) and neural network(NN) were applied to establish models. The receiver operating characteristic (ROC) curve was used to compare the models' efficiencies. The performance of models was validated using decision curve analysis (DCA). Results: The LR model, which included 6 SNPs and 2 clinical variables as independent risk factors for cervical carcinogenesis, was ultimately chosen as the most optimal model. The DCA showed that the LR model had a good clinical application. Discussion: The predictive model effectively foresees cervical cancer risk using clinical and SNP data, aiding in planning timely interventions. It provides a transparent tool for refining clinical decisions in cervical cancer management.

The Triterpenoids from Munronia pinnata and Their Anti-Proliferative Effects.

Six new tirucallane-type triterpenoids, named munropenes A-F (1-6), were extracted from the whole plants of Munronia pinnata using a water extraction method. Their chemical structures were determined based on detailed spectroscopic data. The relative configurations of the acyclic structures at C-17 of munropenes A-F (1-6) were established using carbon-proton spin-coupling constants (2,3JC,H) and inter-proton spin-coupling constants (3JH,H). Furthermore, the absolute configurations of munropenes A-F (1-6) were determined through high-performance liquid chromatography (HPLC), single-crystal X-ray diffraction, and electronic circular dichroism (ECD) analyses. The antiproliferative effects of munropenes A-F were evaluated in five tumor cell lines: HCT116, A549, HepG2, MCF7, and MDAMB. Munropenes A, B, D, and F (1, 2, 4, and 6) inhibited proliferation in the HCT116 cell line with IC50 values of 40.90, 19.13, 17.66, and 32.62 µM, respectively.

Sequential gene expression analysis of cervical malignant transformation identifies RFC4 as a novel diagnostic and prognostic biomarker.

BACKGROUND: Cervical squamous cell carcinoma (SCC) is known to arise through increasingly higher-grade squamous intraepithelial lesions (SILs) or cervical intraepithelial neoplasias (CINs). This study aimed to describe sequential molecular changes and identify biomarkers in cervical malignant transformation. METHODS: Multidimensional data from five publicly available microarray and TCGA-CESC datasets were analyzed. Immunohistochemistry was carried out on 354 cervical tissues (42 normal, 62 CIN1, 26 CIN2, 47 CIN3, and 177 SCC) to determine the potential diagnostic and prognostic value of identified biomarkers. RESULTS: We demonstrated that normal epithelium and SILs presented higher molecular homogeneity than SCC. Genes in the region (e.g., 3q, 12q13) with copy number alteration or HPV integration were more likely to lose or gain expression. The IL-17 signaling pathway was enriched throughout disease progression with downregulation of IL17C and decreased Th17 cells at late stage. Furthermore, we identified AURKA, TOP2A, RFC4, and CEP55 as potential causative genes gradually upregulated during the normal-SILs-SCC transition. For detecting high-grade SIL (HSIL), TOP2A and RFC4 showed balanced sensitivity (both 88.2%) and specificity (87.1 and 90.1%), with high AUC (0.88 and 0.89). They had equivalent diagnostic performance alone to the combination of p16INK4a and Ki-67. Meanwhile, increased expression of RFC4 significantly and independently predicted favorable outcomes in multi-institutional cohorts of SCC patients. CONCLUSIONS: Our comprehensive study of gene expression profiling has identified dysregulated genes and biological processes during cervical carcinogenesis. RFC4 is proposed as a novel surrogate biomarker for determining HSIL and HSIL+, and an independent prognostic biomarker for SCC.

[The anti-inflammatory effects of idazoxan on inflammatory mediator release in endotoxin-challenged mice in vivo and activated macrophages in vitro].

Objective: To study the anti-inflammatory effects of idazoxan (IDA) on endotoxin lipopolysaccharide (LPS) challenged mice in vivo and activated macrophages in vitro, and explore its potential molecular mechanisms. Methods: To do the experiments in vivo,30 adult male C57BL/6 mice were randomly divided into control group, model group, and low,medium and high doses IDA groups (IDA-L,IDA-M, and IDA-H groups),n =6 in each group. The inflammatory model was reproduced by intraperitoneal injection of LPS 10 mg/kg, and the control group was injected with the same amount of normal saline. The IDA groups received LPS (10 mg/kg) and IDA 0.3,1.0 and 3.0 mg/kg, respectively. The blood samples of mice in each group were collected at 6 hours after the reproduction of the model .For the in vitro experiments, primary peritoneal macrophages were collected from 20 adult male C57BL/6 mouse cells and they were divided into control group, LPS group (10 mg/L) and LPS+IDA-L,IDA-M,IDA-H groups (10 mg/L LPS + 5,25,100 µmol/L IDA, respectively).Cell culture supernatants were collected at 24 hours after the reproduction of the model. Detection methods: enzyme linked immunosorbent assay (ELISA) was used to determine the levels of serum tumor necrosis factor-α (TNF-α),interleukin-6 (IL-6),monocyte chemotactic protein-1 (MCP-1) and nitric oxide (NO).Western Blot was used to determine the effect of IDA on the expression levels of nuclear factor-κB (NF-κB) in macrophages. Results: ① For the in vivo experiment, the serum levels of TNF-α and IL-6 were significantly elevated in the model group as compared with those in the control group [TNF-o (ng/L):403.96 ± 40.98 vs.17.50 ± 8.68;IL-6 (ng/L):61 400.31 ± 7 826.61 vs.2 436.30 ± 448.89;both P ＜ 0.01].IDA treatment could inhibit the elevation of inflammatory cytokines in a dose-dependent manner, with the most significant decrease in LPS+IDA-H group [TNF-α (ng/L):170.09 ± 28.53 vs.403.96 ± 40.98,IL-6 (ng/L):16 570.81 ± 1 083.65 vs.61 400.31± 7 826.61;both P ＜ 0.01].② For the in vitro experiment, the levels of TNF-α,IL-6,MCP-1,and NO secreted by LPS-stimulated macrophages were distinctly higher in the LPS group than those in the control group [TNF-α (ng/L):7 259.14 ± 320.70 vs.28.50±27.08,IL-6 (ng/L):14809.60±5852.73 vs.1 113.47±465.53,MCP-1 (ng/L):20847.37± 1 788.33 vs.447.37± 395.69,NO (µmol/L):1 900.00 ± 144.31 vs.603.03 ± 102.18;all P ＜ 0.01]. However, IDA intervention could lower the secretion of TNF-α,IL-6,MCP-1 and NO in a dose-dependent manner, with the most notable decrease in the LPS+IDA-H group [TNF-α (ng/L):784.40±281.90 vs.7259.14±320.70,IL-6 (ng/L):1 802.96± 1 534.18 vs.14 809.60± 5 852.73,MCP-1 (ng/L):2005.26± 1 534.28 vs.20847.37 ± 1 788.33,NO (µ mol/L):654.54± 150.21 vs.1 900.00 ± 144.31;all P ＜ 0.05].In addition, IDA at the concentration of 100 µmol/L could promote the translocation of NF-κBp65 in macrophages into the nucleus 15 minutes early and lead to increased NF-κBp65 expression (gray value:18.70 ± 2.29 vs.1.09 ± 0.36,P ＜ 0.05),hut significantly reduce the expression levels of NF-κBp50 in the nucleus at 45 minutes after treatment (gray value:1.99 ± 0.14 vs.2.94 ± 0.54,P ＜ 0.05). Conclusions: IDA could significantly reduce inflammation of mice challenged with LPS and inhibit inflammatory cytokines and mediators secreted by macrophage in a dose-dependent manner. High concentration of IDA (100 µmol/L) exhibited the greatest anti-inflammatory effects. The anti-inflammatory effect of IDA may be worked through NF-κB signaling pathway.

Differentiation of reprogrammed human adipose mesenchymal stem cells toward neural cells with defined transcription factors.

Somatic cell reprogramming may become a powerful approach to generate specific human cell types for cell-fate determination studies and potential transplantation therapies of neurological diseases. Here we report a reprogramming methodology with which human adipose stem cells (hADSCs) can be differentiated into neural cells. After being reprogrammed with polycistronic plasmid carrying defined factor OCT3/4, SOX2, KLF4 and c-MYC, and further treated with neural induce medium, the hADSCs switched to differentiate toward neural cell lineages. The generated cells had normal karyotypes and exogenous vector sequences were not inserted in the genomes. Therefore, this cell lineage conversion methodology bypasses the risk of mutation and gene instability, and provides a novel strategy to obtain patient-specific neural cells for basic research and therapeutic application.

[Stimulation of sphingosine-1-phosphate on cardiomyogenic differentiation of mesenchymal stem cells].

To study the effect of sphingosine-1-phosphate (S1P) on the cardiomyogenic differentiation of human umbilical cord mesenchymal stem cells (UC-MSCs) and human adipose-derived mesenchymal stem cells (AD-MSCs), we seeded the cells in the culture plates and used cardiomyocyte culture medium (CMCM) combining with different concentration of S1P to induce UC-MSCs and AD-MSCs in vitro for 7, 14 and 28 days. Cardiomyogenic differentiations were identified through immunofluorescence staining, and the results were observed with fluorescence microscopy and confocal microscopy. The effects of S1P and CMCM on cell activity were evaluated by the methyl thiazolyl tetrazolium assay. The functional characteristic similar to cardiomyocytes was evaluated through detecting calcium transient. Our results showed that cardiomyogenic differentiation of UC-MSCs or AD-MSCs were enhanced with S1P concentration increasing, but cell activities declined. Results showed that the suitable differentiation time was 14 days, and the optimal concentration of S1P was 0.5 micromol/L. When working together with CMCM, S1P could promote the differentiation of UC-MSCs or AD-MSCs into functional cardiomyocytes, giving rise to specific electrophysiological properties (the calcium transient). Taken together, our results suggested that S1P could promote the differentiation of UC-MSCs or AD-MSCs into functional cardiomyocytes when being cultured in CMCM.

Induced pluripotent stem cells generated from human adipose-derived stem cells using a non-viral polycistronic plasmid in feeder-free conditions.

Induced pluripotent stem cells (iPSCs) can be generated from somatic cells by ectopic expression of defined transcription factors (TFs). However, the optimal cell type and the easy reprogramming approaches that minimize genetic aberrations of parent cells must be considered before generating the iPSCs. This paper reports a method to generate iPSCs from adult human adipose-derived stem cells (hADSCs) without the use of a feeder layer, by ectopic expression of the defined transcription factors OCT4, SOX2, KLF4 and C-MYC using a polycistronic plasmid. The results, based on the expression of pluripotent marker, demonstrated that the iPSCs have the characteristics similar to those of embryonic stem cells (ESCs). The iPSCs differentiated into three embryonic germ layers both in vitro by embryoid body generation and in vivo by teratoma formation after being injected into immunodeficient mice. More importantly, the plasmid DNA does not integrate into the genome of human iPSCs as revealed by Southern blotting experiments. Karyotypic analysis also demonstrated that the reprogramming of hADSCs by the defined factors did not induce chromosomal abnormalities. Therefore, this technology provides a platform for studying the biology of iPSCs without viral vectors, and can hopefully overcome immune rejection and ethical concerns, which are the two important barriers of ESC applications.

Effect of neural stem cells on apoptosis of PC12 cells induced by serum deprivation.

Neural stem cells (NSCs) have a bright application prospect to be used to treat neurodegenerative diseases due to their capacity to give rise to the appropriate cell types when they are grafted. At present, however, the function of NSCs after transplantation is not quite ensured, whether to replace the degenerative cells or to secrete nutrient factors. On the other hand, pheochromocytoma cell line 12 (PC12) cells have been widely used for investigating Parkinson's disease (PD) since their apoptosis is similar to that of dopaminergic neuron cells. Therefore, the possible cytoprotective effects of NSCs on the apoptosis of PC12 cells induced by serum deprivation were investigated in this paper. PC12 cells were cocultured with NSCs in DMEM/F12 medium free of serum, and their morphologies, viabilities, and survival were observed with an inverted microscope and assessed with a CCK-8 assay. In addition, the concentrations of glial derived neurotrophic factor (GDNF) in different medium were detected with a GDNF Elisa kit, and the mechanism of NSC's protective effect on PC12 cell apoptosis induced by serum deprivation was analyzed. The results showed that (1) PC12 cell apoptosis induced by serum deprivation increased with time, and only about 44.25% PC12 cells survived after 72 h; (2) NSCs culture medium protected against PC12 cell apoptosis insignificantly; (3) NSCs' supernatant and NSCs mildly prevented PC12 cells from apoptosis; (4) the amount of GDNF secreted by NSCs increased after the coculture with the apoptotic PC12 cells induced by serum deprivation. It can be concluded that there exists clear interaction between NSCs and apoptotic PC12 cells, and that GDNF secretion from NSCs is one of the important mechanisms to prevent the apoptosis of PC12 cells.

Neural network analysis of ex-vivo expansion of hematopoietic stem cells.

The shortage of hematopoietic stem cells (HSCs) greatly limits their widespread clinical applications. Few studies however, investigated the relationship between the cellular expansion and the influencing factors although wide variety results of the ex-vivo expansion of HSCs existed in literature. Here, a back-propagation (BP) neural network model was employed to evaluate the ex-vivo expansions of nuclear cells (NCs), CD34(+) cells, and colony-forming units (CFU-Cs), where the output was the cellular expansion folds and the inputs include inoculated density, cytokines, resources, serum, stroma, culture time, and bioreactor types. Around 124, 86, and 90 samples were used to train the neural network for the expansion evaluations of NCs, CD34(+ )cells, and CFU-Cs, respectively, while 17, 14, and 10 samples were applied to predict respectively. The results show that for the training of network, the interval accuracy of the expansion folds for the different cells is 85.5, 86.1, and 86.7%, respectively, while the truth-value accuracy is still up to 59.7, 50.0, and 62.2%, respectively within a relative error (RE) of +/-20%. For the prediction of network, the interval accuracy can be up to 82.4, 71.4, and 70%, respectively, while the truth-value accuracy is only 29.4, 14.3, and 50.0%, respectively (RE = +/-20%). Moreover, six verification experiments were carried out based on our interval predicted values and the results proved that the five group predicted conditions lead to the correct expansion of the HSCs with the accuracy more than 80%. Considering the complexity of HSC expansion and complicated wide range of the experimental data, such relatively high interval accuracy for training and prediction as well as verification are satisfied. Therefore this nonlinear modeling makes it possible to describe quantitatively the effects of the culture conditions on the HSC expansion and to predict the optimal culture conditions for higher ex-vivo expansion of HSCs.