青春之泉：科學(xué)家表示激活睡眠狀態(tài)中的皮膚干細(xì)胞將抵御人體皮膚衰老，使人們?nèi)蓊伇３智啻河礼v
據(jù)英國每日郵報報道,，目前，科學(xué)家最新研究表明,，容貌青春永駐的秘密在于喚醒皮膚中“睡眠狀態(tài)干細(xì)胞”,。
一項計算機模型實驗發(fā)現(xiàn)，伴隨著人類逐漸衰老,，我們將失去引發(fā)這些“萬能細(xì)胞”再生受損皮膚的能力,。英國和美國科學(xué)家稱，這項創(chuàng)新性研究將有助于研制更好的美容治療方法,，使人們保持青春容顏,。
科學(xué)家進(jìn)行了一項復(fù)雜的虛擬仿真實驗，測試了三種最易于接受的假設(shè)理論,，驗證人類皮膚在3年時間里如何再生,。李新山(音譯)博士說：“最佳解釋理論是皮膚具有一定數(shù)量的‘睡眠狀態(tài)干細(xì)胞’，它們位于皮膚最淺層,，并不會經(jīng)常分裂形成新的細(xì)胞,。”
然而，如果皮膚受損,，這些睡眠細(xì)胞將被喚醒修復(fù)皮膚受損部分,，如果其它類型更成熟的皮膚細(xì)胞數(shù)量也持續(xù)減少，皮膚組織將在任何情況下持續(xù)再生,。干細(xì)胞是人體的“萬能細(xì)胞”,，它將潛在成為許多不同類型的細(xì)胞。
李新山博士稱,，每次我們喚醒這些細(xì)胞,，用于治療傷口或者補充其它細(xì)胞，大量干細(xì)胞并不能返回進(jìn)入睡眠模式,，因此這種細(xì)胞的數(shù)量逐漸下降,。這將解釋為什么老年人皮膚傷口愈合緩慢，從某種程度上講,，伴隨著我們年齡的增長,，皮膚也將發(fā)生變化。通過更好地理解這種機制,，很可能發(fā)現(xiàn)有效抵御人體皮膚衰老的方法,。
人的一生之中不斷地生長新的皮膚,，同時脫落衰老皮膚組織，直到目前科學(xué)家們?nèi)晕催_(dá)成一致觀點解釋其中的運行原理,。這項英國謝菲爾德大學(xué)和寶潔公司玉蘭油研發(fā)中心的研究人員共同完成這項實驗,，研究結(jié)果發(fā)布在近期出版的《自然科學(xué)報告》上。他們可能發(fā)現(xiàn)抵御皮膚衰老甚至是皮膚癌的有效方法,。 （生物谷Bioon.com）
生物谷推薦英文摘要：
Scientific Reports doi:10.1038/srep01904
Skin Stem Cell Hypotheses and Long Term Clone Survival – Explored Using Agent-based Modelling
X. Li, A. K. Upadhyay, A. J. Bullock, T. Dicolandrea, J. Xu, R. L. Binder, M. K. Robinson, D. R. Finlay, K. J. Mills, C. C. Bascom, C. K. Kelling, R. J. Isfort, J. W. Haycock, S. MacNeil & R. H. Smallwood
Skin is the body's first line of defense against environmental hazards, forming a protective barrier for the surface of the body. It consists of an epidermis and a dermis separated by a basement membrane. Keratinocytes are the main building blocks of the epidermis. Under normal conditions, cells on the skin surface are continuously replaced by new cells generated in the basal layer. Cells leave the basal layer and differentiate upwards to comprise the stratum spinosum, stratum granulosum and stratum corneum. These upper layers mediate skin barrier function. The lifespan of keratinocytes and their differentiation into a barrier to prevent water loss and infection are precisely regulated in order to achieve coordinated self-renewal by a process called homeostasis.
Due to the dynamic nature of skin and the importance of its structural integrity, it is difficult to study the development of the tissue in vivo, as any disturbance in the epidermis (such as tape stripping or sodium dodecyl sulphate treatment) compromises the barrier function immediately and many of the experimental techniques used to study cell biology cannot ethically be carried out in man. Therefore, animal models and in vitro tissue engineered skin are commonly used as alternatives. Although these experiments provide a good representation of the human in vivo equivalent, the results are usually qualitative and difficult to interpret on a continuum basis, which hinders integrating new discoveries with previous research. Computer models on the other hand, are ideal tools for investigating individual cell behaviour by combining laboratory data and the existing literature. Agent-based models have been frequently used for studying a group of entities (or agents)1, 2, 3, such as keratinocytes, each with their unique properties4, 5. The behaviour of each agent is defined using a set of rules based on the experimental literature. Previous models of epithelial cells have been used in studying a wide range of applications, such as cell culture morphogenesis6, hierarchy of cells within the intestinal crypts7, 8, activation of hematopoietic stem cells9, the behaviour of sperm in the oviduct10, and modelling metabolic process in liver cells11. In particular, epithelial cells in the intestinal crypts are famous for their monoclonality, where a single stem cell lineage is thought to sustain the entire population in each crypt7, 8. This has been shown by Loeffler et al. (1997) through their 2D models by applying a stochastic symmetric division pattern to stem cells7. The model was later extended by Van Leeuwen et al. (1997) to investigate the process of mitosis and clonal expansion in the crypt8. In addition, agent-based models have also been used extensively to simulate tissue regeneration under pathological conditions, such as the remodelling of airway epithelium in asthma12, the acute inflammatory response13, elucidating possible mechanisms for psoriasis14, cancer cell invasion and tumour behaviour15, as well as a range of multi-scaled models aimed at bridging between changes at the cellular level with behaviours at the tissue and the organ levels1, 8, 12, 16, 17. These models allow one to explore alternative hypotheses inexpensively and for longer periods than are possible for in vitro experiments making them very useful for studying the dynamics of biological organisation.
In skin biology, epithelial homeostasis and self-renewal supported by regenerative cells is one of the most studied areas. As new data emerge hypotheses behind the behaviour of regenerative cells have also evolved over the past years. In particular, a series of recent publications18, 19 challenged the traditional view of a stem-transit amplifying (TA) cell population leading to the generation of an epithelial proliferation unit (EPU), which in turn sustains the renewal process in the tissue. By employing genetic labelling techniques, these studies followed colonies of regenerative cells over one year, and suggested an alternative hypothesis of division in the basal layer (see Figure 1). This hypothesis, described in Clayton et al. (2007)18, is in favour of a single proliferative progenitor cell population that sustains epithelial renewal by producing post mitotic basal cells in a stochastic process. The experiments however, provided insufficient evidence for slow-cycling stem cells as had previously been suggested. However, recent evidence20 suggests the existence of a hierarchical organisation consisting of both fast-cycling progenitor cells and slow-cycling stem cells in an attempt to consolidate the traditional stem-TA hypothesis with stochastic fate decision (hereon referred to as the “PAS” hypothesis, short for populational asymmetry with stem cells). All three hypotheses have been derived based on the observation of the dynamics of biological tissues over a steady state period of typically one year. Individually, each provides a sound mechanism that ensures the continuous regeneration during homeostasis. However, these hypotheses are derived from a collection of static snap-shots of tissues at regular intervals and hence provide a limited window of information within the lifespan of the tissue. A similar problem lies with the in vitro experiments, from which data can only be obtained over a few weeks. In contrast, these hypotheses can be used to generate rule sets which can run inexpensively using computer models, which can: (1) monitor the entire population over any numerical period; and (2) trace the development of individual lineages over years within the equivalent of days in computational time.
