EIKEN嗜肺軍團菌檢測試劑盒

廣州健侖生物科技有限公司

主要用途：用于檢測尿樣中嗜肺軍團菌血清型1抗原，以支持軍團菌感染的診斷。

產品規格：20T/盒

存儲條件：2-30℃

EIKEN嗜肺軍團菌檢測試劑盒

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【產品介紹】

EIKEN

二維碼掃一掃

【公司名稱】 廣州健侖生物科技有限公司
【】    楊永漢 
【】 
【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101-3室
【企業文化】

研究人員表示，這項新發現明確了多種不同腦部疾病的共同機理，并為延緩那些已經表征癡呆癥狀的患者的治療指明了道路。
膜蛋白對于光合作用、視覺等功能至關重要。它們還是細胞的看門人，能決定什么可能會通過細胞膜，也幫助從細胞膜外部輸入養料和將內部垃圾輸出。由于這些多重角色，它們構成了很大一部分的藥物靶點。雖然它們的功能很明確，但是關于它們如何折疊的信息卻遠遠落后于球狀蛋白質。
Wolynes及其同事使用原始的基因組信息，來預測氨基酸鏈將如何通過遵循阻力zui小的途徑(取決于鏈上每個殘基相關的能量)，折疊成為功能蛋白質。一個蛋白質越接近于其功能性“原始”狀態，它就會越穩定。Wolynes的開創性理論生動地將這種能量描繪成一個漏斗。
為了檢測他們的計算機模型，研究人員將它們與X射線晶體學獲得的真實蛋白質結構進行比較。大量的結構對球狀折疊的蛋白質是可用的，這些蛋白漂浮在體內，執行生命*的任務。
但直到zui近幾年，我們已經很難獲得跨膜蛋白的相似結構，因為要提取它們用于成像，同時又不會破壞它們，難度非常的大。zui近有研究人員利用一種去垢劑洗掉目的蛋白上的大多數膜，Wolynes稱：“它在蛋白質周圍留下一個脂肪層，但是卻給出一種涂層，可使整個分子在后來形成晶格。”
當Wolynes注意到，兩種廣泛使用的細胞生物學教材對于跨膜蛋白如何折疊有*不同的意見時，受到啟發研究膜蛋白。他說：“其中一本教材，列出所有規則，說：‘這是證據表明，它是動力學控制的。’另外一本教材指出：‘這是證據表明，它是熱力學控制的。’它們以那種方式被寫入教材，好像是確定。我想說我仍然不確定，但我認為我們的工作更多地指出，折疊是熱力學(平衡)控制的，至少一次蛋白質是停留在膜中。”
Kim和Schafer修改了Wolynes實驗室使用的一種蛋白質折疊算法，被稱為聯想記憶、水介導的結構和能量模型(AWSEM)，來解釋膜蛋白所*的外界影響，包括將部分折疊蛋白質插入膜的易位子機制和膜本身。
利用這種算法，他們成功地確定，熱力學漏斗在膜蛋白折疊中似乎仍然占據上風，如同它們為球狀蛋白質所做的。
Kim稱：“我們有來自許多不同實驗室的膜蛋白結構數據庫，我們能了解在它們之間轉換的參數。這些參數兩個殘基(珠)應該相互作用的多么強烈，并考慮周圍的環境。這可讓我們能夠從原始序列做出預測。”

The researchers said the new findings pinpoint common causes of many different brain diseases and point the way to delaying the treatment of those who already have symptoms of dementia.
Membrane proteins are essential for photosynthesis, vision and other functions. They are also gatekeepers to cells that determine what may pass through the cell membrane and also help to input nourishment from the exterior of the cell membrane and to export internal junk. Due to these multiple roles, they constitute a large part of the drug target. Although their function is clear, the information about how they fold is far behind globular proteins.
Wolynes and colleagues use the raw genomic information to predict how amino acid chains will fold into functional proteins by following the pathway of least resistance (depending on the energy associated with each residue on the chain). The closer a protein is to its functional "primitive" state, the more stable it will be. Wolynes' pioneering theory vividly portrays this energy as a funnel.
To test their computer models, the researchers compared them to the actual protein structures obtained by X-ray crystallography. Numerous structures are available for globularly folded proteins that float in the body and perform essential tasks of life.
However, it has been very difficult to obtain similar structures of transmembrane proteins in recent years because it is extremely difficult to extract them for imaging without damaging them. Recently, researchers have used a detergent to wash away most of the membrane on the protein of interest, Wolynes said: "It leaves a layer of fat around the protein, but gives a coating that allows the entire molecule to form later Lattice. "
Wolynes was inspired to study membrane proteins when he noted that the two widely used textbooks on cell biology have compley different opinions about how the transmembrane proteins fold. He said: "One of the textbooks lists all the rules, saying: 'This is evidence that it is kinetically controlled.'" Another textbook states: 'This is evidence that it is thermodynamically controlled.' ' It seems to be absoluy certain that the text was written in that way, and I would like to say that I am still not sure, but I think our work more often states that the folding is thermodynamically (equilibrium) controlled, at least once the protein is stuck in the film "
Kim and Schafer modified a protein folding algorithm used by Wolynes Lab called associative memory, water-mediated structure and energy model (AWSEM) to account for the external effects unique to membrane proteins, including the insertion of partially folded proteins Membrane translocation mechanism and membrane itself.
Using this algorithm, they succeeded in determining that the thermodynamic funnels still seem to hold the upper hand in membrane protein folding as they do for globular proteins.
"We have a database of membrane protein structures from many different laboratories and we know the parameters that switch between them." These parameters specify how strongly two residues (beads) should interact and take into account the surrounding environment This allows us to make predictions from the original sequence. "