Discrimination of Colon Cancer Stem Cells Using Noncanonical Amino Acid

Cancer stem cells (CSCs) may be responsible for tumor recurrence. Metabolic labelling of newly synthesized proteins with non-canonical amino acids allows us to discriminate CSCs in mixed populations due to the quiescent nature of these cells

Breast Tumour Initiating Cell Fate Is Regulated by Microenvironmental Cues from an Extracellular Matrix

Cancer stem cells, also known as tumour-initiating cells (TICs), are identified as highly tumorigenic population within tumours and hypothesized to be main regulators in tumour growth, metastasis and relapse. Evidence also suggests that a tumour microenvironment plays a critical role in the development and progression of cancer, by constantly modulating cell–matrix interactions. Scientists have tried to characterize and identify the TIC population but the actual combination of extracellular components in deciphering the fate of TICs has not been explored. The basic unanswered question is the phenotypic stability of this TIC population in a tissue extracellular matrix setting. The in vivo complexity makes it difficult to identify parameters in a diverse milieu that affect TICs behaviour. Herein we studied how the TIC population would respond when subjected to a unique microenvironment composed of different extracellularproteins. The TIC-enriched population isolated from a Her2/neu-induced mouse mammary tumour was cultured on collagen, fibronectin and laminin coated substrates for one to two weeks. Our observations indicate that a laminin substrate can maintain the majority of the self-renewing and tumorigenic TIC population, whereas collagen induced a more differentiated phenotype of the cells. Also interestingly, fibronectin substrates dictated an invasive phenotype of TICs as evidenced from the EMT-related gene expression pattern. The results of this study signify that the microenvironmental cues play a considerable role in tumour relapse and progression by altering the cancer stem cell behaviour and thus this knowledge could be used to design novel cancer therapeutics

Short-term PV power prediction based on the 24 traditional Chinese solar terms and adaboost-GA-BP model

High-precision, short-term power forecasting for photovoltaic systems not only reduces unnecessary energy consumption but also provides power grid security. To this end, in this paper we propose a photovoltaic short-term power forecasting model based on the division of data of the 24 traditional Chinese solar terms and the Adaboost-GA-BP model. The 24 solar terms were condensed from the laws of meteorology, phenology, and seasonal changes to adapt to agricultural times in ancient China and have become intangible cultural heritage. This article first analyzes the numerical characteristics of meteorological factors and demonstrates their close correlation with the turning points of the 24 solar terms. Second, using Standardized Euclidean Distance and Spearman’s Correlation Coefficients to analyze data similarity between the Gregorian half-months and the 24 solar terms divisions for comparative analysis purposes, it is shown that the intragroup data under the division of the 24 solar terms have a higher similarity, leading to an average decrease of 15.68%, 40.57%, 14.68%, and 14.64% in the MAE, MSE, RMSE, and WMAPE of the predicted results, respectively. Finally, based on the data derived from the 24 solar terms, the combined algorithm was compared with the Adaboost-GA-BP model and then was verified. The genetic algorithm and Adaboost were used to optimize the BP neural network algorithm in initial value assignment and neural network structure, resulting in a 23.42%, 18.12%, and 22.28% reduction in the mean values of the MAE, RMSE, and WMAPE of the predicted results, respectively. Analysis of the results show that using the Adaboost-GA-BP model based on the 24 solar terms for short-term photovoltaic power forecasting can improve the accuracy of photovoltaic power forecasting and significantly improve the predictive performance of the model

Effects of aging and macrophages on mice stem Leydig cell proliferation and differentiation in vitro

BackgroundTestosterone plays a critical role in maintaining reproductive functions and well-beings of the males. Adult testicular Leydig cells (LCs) produce testosterone and are generated from stem Leydig cells (SLCs) during puberty through adulthood. In addition, macrophages are critical in the SLC regulatory niche for normal testicular function. Age-related reduction in serum testosterone contributes to a number of metabolic and quality-of-life changes in males, as well as age-related changes in immunological functions. How aging and testicular macrophages may affect SLC function is still unclear.MethodsSLCs and macrophages were purified from adult and aged mice via FACS using CD51 as a marker protein. The sorted cells were first characterized and then co-cultured in vitro to examine how aging and macrophages may affect SLC proliferation and differentiation. To elucidate specific aging effects on both cell types, co-culture of sorted SLCs and macrophages were also carried out across two ages.ResultsCD51+ (weakly positive) and CD51++ (strongly positive) cells expressed typical SLC and macrophage markers, respectively. However, with aging, both cell types increased expression of multiple cytokine genes, such as IL-1b, IL-6 and IL-8. Moreover, old CD51+ SLCs reduced their proliferation and differentiation, with a more significant reduction in differentiation (2X) than proliferation (30%). Age matched CD51++ macrophages inhibited CD51+ SLC development, with a more significant reduction in old cells (60%) than young (40%). Crossed-age co-culture experiments indicated that the age of CD51+ SLCs plays a more significant role in determining age-related inhibitory effects. In LC lineage formation, CD51+ SLC had both reduced LC lineage markers and increased myoid cell lineage markers, suggesting an age-related lineage shift for SLCs.ConclusionThe results suggest that aging affected both SLC function and their regulatory niche cell, macrophages