西班牙Certest滅活沙門氏菌副傷寒A抗原（天然提取物）

廣州健侖生物科技有限公司

廣州健侖長期供應各種生物原料，主要代理品牌：西班牙Certest。

主要產品包括各種生物單克隆抗原抗體、重組蛋白。

西班牙Certest滅活沙門氏菌副傷寒A抗原（天然提取物）

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細胞環境有著超越基因組的影響，正因如此，大規模“組學”數據將是未來細胞重編程的一個重要方面。雖然我們認為iPSC和ESC在功能上是相同的，但轉錄組、蛋白質組和表觀基因組水平的深入研究將有助于闡明環境對重編程的影響。另外，在單個細胞中同時檢測多個“組學”，將能鑒定那些造成iPSC多能性差異的基礎元件。
目前，細胞重編程領域普遍缺乏定量數據。實際上，文獻中的重編程效率差異，可能更多的是由體細胞內部異質性造成的，而不是方法學上的問題。定量理解這樣的異質性，可以幫助我們從細胞群體中區分出想要的細胞。
Buganim等人通過細胞重編程的兩個狀態，描述了異質性產生的基礎。首先，OSKM轉基因激活一系列隨機事件，當這些事件達到“適當”條件時，細胞轉變為第二個狀態。這個狀態會出現決定性的基因表達，此時轉基因被沉默，細胞被重塑為多能性狀態。在Buganim這個模型中，轉基因激活與沉默之間的平衡，是細胞重編程效率低的重要原因。我們可以換一種途徑進行重編程，激活或沉默非基因組的因子，將有望顯著提高重編程效率。“組學”數據無疑能加深我們對這些因子的認識，幫助我們理解細胞重編程的必要條件和非必要條件。
在這些信息的基礎上，我們可以同步細胞動態，在引入轉基因時讓大多數細胞處于抗原抗體狀態。已經有前期工作表明，重編程動態受到一些限速步驟的調控。比如，去除組蛋白乙?；囊粋€抑制子，可以使體外重編程的效率達到幾乎100%。此外，引入OSKM也會刺激甲基化等細胞過程，以維持內穩態。對于研究這些過程的動態而言，定量技術將特別有優勢。FACS和拉曼光譜才剛開始用于細胞重編程的定量研究，就已經表現出了很大的潛力。
細胞重編程受到公眾關注，主要是因為它在疾病模擬和醫療保健中的應用。神經退行性疾病的患者特別能從這一技術中獲益，因為生成神經元的iPS方案要優于其他細胞類型，而且患者神經元通常很難獲取。目前，細胞重編程技術研究特定基因組突變引起的疾病，因為重編程會重設表觀基因組。盡管有證據表明，iPS技術也能用來研究復雜基因組改變引起的疾病，但目前的模型一般不足以研究異常細胞網絡或動態引發的疾病。
近年來，iPS研究發表的數量和速度都很驚人，但這些研究還局限于檢測相對簡單的系統。對于復雜網絡引發的問題或疾病，就需要采用能描述網絡互作的定量技術或者轉基因動物模型。這些方面的進步將加深我們對重編程機制的理解，有助于早日實現人們對這一技術的期望。

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【公司名稱】 廣州健侖生物科技有限公司
【市場部】    楊永漢

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【騰訊  】 2042552662
【公司地址】 廣州清華科技園創新基地番禺石樓鎮創啟路63號二期2幢101-103室

The cellular environment has the effect of transcending the genome, and as such, large-scale "omics" data will be an important aspect of future cell reprogramming. Although we believe that iPSCs and ESC are functionally identical, further studies of transcriptome, proteome, and epigenome levels will help elucidate the impact of the environment on reprogramming. In addition, the simultaneous detection of multiple "omics" in a single cell will identify those basic elements that contribute to the pluripotency of iPSCs.
Currently, there is a general lack of quantitative data in the field of cell reprogramming. In fact, the differences in reprogramming efficiency in the literature may be due more to the internal heterogeneity of somatic cells than to methodological problems. Quantitative understanding of this heterogeneity can help us to distinguish the cells we want from the cell population.
Buganim et al. Describe the basis for heterogeneity through the two states of cellular reprogramming. First, OSKM transgenics activate a series of random events, and when these events reach the "appropriate" condition, the cells switch to the second state. This state will appear decisive gene expression, when the transgene is silenced, the cells are remodeled into pluripotent state. In the Buganim model, the balance between transactivation and silencing is a major cause of inefficient cell reprogramming. We can reprogram, activate or silence non-genomic factors in a different way, and we expect to significantly improve reprogramming efficiency. "Omics" data undoubtedly deepen our understanding of these factors and help us to understand the necessary and non-essential conditions for cell reprogramming.
Based on this information, we can synchronize cellular dynamics, allowing most cells to be in an antigen-antibody state upon introduction of the transgene. Preliminary work has shown that reprogramming is dynamically limited by some rate-limiting steps. For example, removing a suppressor of histone acetylation can make reprogramming nearly 100% efficient in vitro. In addition, the introduction of OSKM also stimulates cellular processes such as methylation to maintain homeostasis. Quantitative techniques will be particularly advantageous for studying the dynamics of these processes. FACS and Raman spectroscopy have just begun to be used in quantitative studies of cell reprogramming and have shown great potential.
Cell reprogramming has received public attention primarily because of its use in disease simulation and healthcare. In particular, patients with neurodegenerative diseases benefit from this technique because the iPS regimen that produces neurons is superior to other cell types and is often difficult to obtain in patient neurons. Currently, cell reprogramming is best suited to study diseases caused by specific genomic mutations because reprogramming resets the epigenome. Although there is evidence that iPS technology can also be used to study diseases caused by complex genome changes, current models are generally not adequate for studying abnormal cell networks or dynamically induced diseases.
In recent years, the number and speed of iPS research publications have been staggering, but these studies have also been limited to the detection of relatively simple systems. For problems or diseases caused by complex networks, quantitative techniques or transgenic animal models that describe network interactions are needed. Advances in these areas will deepen our understanding of the reprogramming mechanism and help to bring about the early realization of this technology.