数学模型有助于干细胞的研究..

decloud2009

Go Figure: Math Model May Help Researchers With Stem Cell, Cancer Therapies
) I/ s- h* U6 s5 Z4 f" [8 tMain Category: Stem Cell Research
1 n; D4 O; h0 B5 F7 VAlso Included In: Cancer / Oncology
/ @' V  j/ N" d4 M  t1 Y# Y  `5 ~2 ?. aArticle Date: 21 Jan 2011 - 4:00 PST
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3 t1 i4 d2 Y5 }数学模型有助于干细胞的研究..9 n$ O+ j% t0 o$ C; _$ `( M4 w
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科学家一直在试着为有进行性疾病的病人寻找新的干细胞的治疗方法, 但是分类和计数干细胞及癌症相关的干细胞一直是一件非常困难的工作.8 _) J! {- b# S. D; v/ i8 j. g/ ?. g

/ U5 r3 f! _3 f; c# R- O但是让数学老师们感到高兴的是,佛罗里达大学的研究者创造了一系列的数学方法来达到这个大多数显微镜,高处理量筛选系统和蛋白质分析都做不到的目标----评估干细胞及干细胞样恶性肿瘤细胞的增长速度.7 d5 N6 J: O5 p2 l6 C
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这个方法, 在PloS ONE 的一月份杂志上出版, 有可能加快阿尔兹海默尔症, 帕金森和其他相关疾病的干细胞治疗研究. 同时也有望帮助研究肿瘤干细胞的起源----肿瘤是由极少数细胞产生的.8 G6 y( a  o6 ^% C

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“数学将成为21世纪新的观察方法,因为它可以让我们看到其他方法看不到的东西” Brent Reynolds (Ph.D., an associate professor of neurosurgery at UF's McKnight Brain Institute and a member of the UF Shands Cancer Center)  “干细胞和肿瘤干细胞是极其少数的,其数量级大概在1/(10,000~100,000). 问题是怎么去研究数量如此稀少的细胞的生理机制.”
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) 从一个2004年的描述了 数学和生物学之间的合作的短评(作者 Joel E. Cohen Ph.D., of The Rockefeller University and Columbia University)中得到灵感,  Reynolds和博士后Loic P. Deleyrolle开始试着建立一个可以将干细胞和肿瘤样干细胞分类的公式.7 z' J/ W. V8 d; Y" c& c  w/ P3 u

( U# {1 C- ?( m虽然干细胞的数量及其稀少,科学家通过组织愈合,再生,以及某些肿瘤不断的复发中得知干细胞的存在.6 _* ?3 x9 |  y1 k1 _

  ]% W( M% f2 d. m1 o* ]  y一个Queensland Brain Institute的电脑神经科学家和其他一些科学家和Geoffrey Ericksson组成了一个小组. 这个小组提出了对神经球的数学解释----一个很小的包括各个发展时期的干细胞及干细胞后代的脑细胞集合.
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他们通过在体外和小鼠中培养脑肿瘤和乳腺癌细胞,来检测这个数学模型的计算得出的期望值和肿瘤的侵袭性的相关性.* i$ ?5 t* u( C) X2 X( o0 K, p
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: ]% t2 }6 G8 V& m  t说明：由干细胞之家新闻小组成员decloud2009翻译（转帖请注明）。个人翻译，理解不准确的语句还望大家积极指出。) k9 d2 T; |0 z
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, G* T( D4 {. G; \1 |% yThe difficult task of sorting and counting prized stem cells and their cancer-causing cousins has long frustrated scientists looking for new ways to help people who have progressive diseases. 1 f, a& g% P7 b$ @3 f
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But in a development likely to delight math teachers, University of Florida researchers have devised a series of mathematical steps that accomplishes what the most powerful microscopes, high-throughput screening systems and protein assays have failed to do - assess how rapidly stem cells and their malignant, stemlike alter egos increase their numbers. $ Q, a( j2 |+ d
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The method, published in the online journal PLoS ONE in January, may rev up efforts to develop stem cell therapies for Alzheimer's, Parkinson's and other diseases. It may also help get to the root of the cancer-stem cell theory, which puts forth the idea that a tiny percentage of loner cancer cells gives rise to tumors.   w2 \; S# N3 L" O- h9 T: @
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"Math is going to be the new microscope of the 21st century because it is going to allow us to see things in biology that we cannot see any other way," said Brent Reynolds, Ph.D., an associate professor of neurosurgery at UF's McKnight Brain Institute and a member of the UF Shands Cancer Center. "Stem cells and the cells that drive cancer may be as infrequent as one in 10,000 or one in 100,000 cells. The problem is how do you understand the biology of something whose frequency is so low?" + c3 a' C" P" \6 n; c6 t# U
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Inspired by a 2004 essay by Joel E. Cohen, Ph.D., of The Rockefeller University and Columbia University that described the explosive synergy between mathematics and biology, Reynolds and postdoctoral associate Loic P. Deleyrolle set out to build an algorithm that could determine the rate stem cells and cancer stem cells divide.& a7 x- _: B' A  g
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; r3 D  N" j& Q: Z$ `/ ?& ^4 f" RHigh hopes to treat or prevent diseases have been pinned on these indistinguishable cells, which are often adrift in populations of millions of other cells. Scientists know stem cells exist mainly because their handiwork is everywhere - tissues heal and regenerate because of stem cells, and somehow cancer may reappear years after it was thought to be completely eliminated." J8 A' U  q0 s# a& |2 `/ F
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With Geoffrey Ericksson, Ph.D., a computational neuroscientist at the Queensland Brain Institute, and other scientists in Australia, the team proposed a mathematical interpretation of neurospheres - tiny collections of brain cells that include stem cells and their progeny at different stages of development.
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They tested the mathematical approach by using brain tumor and breast tumor cells in cultures and in mice, correlating the estimates generated by the mathematical model with the aggressiveness of the cells they were studying.
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( a5 G) e  e  n) p, ~3 Y# B"The unique thing about our study is we were able to do the biology," Deleyrolle said. "We took our simulation to the real world with real cells."
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: R# i4 ~1 p- x6 TBy offering a method to evaluate the effects of diseases and treatments on stem cell activity in the brain, as well as allowing the assessment of malignant stemlike cells, researchers believe they can better evaluate potential therapies for diseases. 2 j) n! k( o/ Y

/ s7 V7 I: v) U% R' d* ?% J9 a3 }"Estimating the numbers of stem cells one has in a particular tissue or culture has important implications in the development of therapeutics, including those for brain tumors," said Harley Kornblum, M.D., Ph.D., professor in residence at the Broad Center of Regenerative Medicine and Stem Cell Research at the University of California, Los Angeles, who was not involved with the study. "This method provides a mathematical model that will enable researchers to do just that. Certainly, it will help my own research in these areas a great deal." ! e" H( {4 [5 H
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Source:
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tpwang

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; }; d( o7 Q4 S  G& O$ r! I回复 decloud2009 的帖子8 p- ^# F, b; j2 G6 T
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提个认真的建议。这类新闻稿的翻译，不必像翻译研究文章的摘要等严格文体那样拘泥。首先多读文字，吃透了，翻过来，自己读，然后抛开原文用中文顺，再回头对照原文，以求不要太走样。( A6 ]0 q' Q& w0 E& a- `

6 D2 ]4 E& E2 |$ v不少的翻译，首先没有从全局通读原文，而是一句一段照着英文句型翻。这样的翻法，更适用于严格的研究报告。如果要硬翻，那就一定翻准确。常见的问题是句型死扣，但意思反而没有死扣，这反而搞反了。" `5 l6 x% s% \; V; S' @

6 T6 W% k9 L7 z  z/ Z其次，不少译文一看就没有经过事后抛开原文的修饰，翻完直接就上来了。这个习惯非常不利于提高自己。其中不少不同的语句，多出来少出去的字，标点符号等细节都没有纠正。这样的文字如果用在将来的发文章上，编辑是最不喜欢的。因为你连应该搞定的小节都没有办到，他是不会相信你对待科学认真的。一个类似的情况是很常见学生拿来文章要改，编辑软件可以很方便自动改正的语法与错拼都没有做，没人愿意看。所谓细节决定成败，此之谓也。如果你写一篇文章写的不上心不认真，不如不写，因为不写不会养成坏习惯。翻译也是如此，其实上网上帖都是如此。这是题外话。" @# F' c% B/ L5 U, f
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说说这篇稿子的翻译。* D( m* j" b7 p0 g3 h: z9 r
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新闻稿有它的基本模式。其中直接间接引用人物话语，穿插在记者的理解与描述之中，如何把握这个交互配合模式的说话口气和逻辑关系，是信达雅中“信与达”的要点。就这篇文稿来说，首先搞清楚本文所说的研究的“主人公”是谁，又和那些人相关（学术思想和方法的继承关系，联合研究机构和人物等）。6 l) p: |6 I' d9 o
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这篇文稿里有几处提到本项研究相关的人物，分别是Joel Cohen及同事，Reynolds & postdoc, Geoffrey Ericksson & Australian scientists，分别把这三组人物关系理顺，找出本文提到的研究的“主人翁”，然后在翻译的时候把这个关系说清楚，故事框架读起来就顺了。上面的翻译文字这个人物关系没有说清楚，读过不好判断“谁是谁”（who's who），谁干的，干了啥。
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4 a$ K  R2 {" l/ u. \一般这类科学文宣稿习惯最后找一个没有利益相关的本行专家做一个“客观”点评，这个翻译漏掉了这一段，一是感觉虎头蛇尾，二是失去了新闻稿力图“公正”的味道。
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因为是“科学”，所以不揣冒昧，直言了，仅供参考。也是自勉。1 G. a' f$ e  w& Q; `* p
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另外，估计不少网友习惯直接在上帖栏里翻译。翻完发出后，有十分钟的时间可以“编辑”帖子。可以上帖后马上打开编辑，通读一下，把明显的误写误打等小处修改一下，很方便的。
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novodavid

一直认为当生物学发展到一定程度，也会和物理化学之类学科一样，需要靠数学的帮助才能从根本上解决，毕竟是宇宙的规律，万物之始啊。当然可能道路很长，几百几千年也不一定，但是随着计算机的发展，终有一天我们会用数字模拟这个世界！

tpwang

回复 novodavid 的帖子* {/ c2 O  m% e

: Z8 R: N* l- L  ?( c到那时候，也就不是谁靠谁了。世间万物，殊途同归。自然现象放在那里，怎么去看，也没一定。但最终的方向，是不断趋合。分科是为了方便。也许到那时候分出来新的杂交学科。话说天下大势，合久必分，分久必合。