Go Figure: Math Model May Help Researchers With Stem Cell, Cancer Therapies / ~6 l: B8 c: x% ?, o. SMain Category: Stem Cell Research 5 z, ]* y3 Q2 H- ~ q9 J6 KAlso Included In: Cancer / Oncology* ]7 Y* g& [/ B7 l9 F
Article Date: 21 Jan 2011 - 4:00 PST( N8 h+ x5 Q: @. Q0 `) [8 h I5 F
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数学模型有助于干细胞的研究..) ?! y2 K. \1 ?9 |: L6 H
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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.* H2 d! d( ~: _& v0 M8 ]) z
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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. " G7 J" j, V/ l; h 1 S/ |! W4 m, V& J" D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 ?+ B& b" A# l6 }+ B
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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.”, v& v) K/ r$ l& ?& w
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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. 1 d: U/ v* f7 w) A; v+ I8 p 6 G @* N/ a6 i& O$ u" |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. 5 [3 P$ W/ Y. ^* N) r* N6 \; i9 ?* F; ^2 a% f) f" d* D+ F: K/ [' G
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. 0 [0 Z; O; g# a% |& d# z , m8 P9 E" }5 x, w+ t2 [- C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. 0 P A$ S3 g/ e* \3 M / [. L, E- R% t% b) E, ]: D7 t6 I: o. v2 x
9 b; D! E) O' C, ?' k& j" x 1 z" a |8 A; ~2 E( Z' ? % I8 \8 q9 d: B: E( D# E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。 2 g( ?0 e5 _! K 6 j7 t8 J' D0 f) v+ q + J$ L z6 ] B/ r4 \' V+ ^ Y4 S; s% i( Z, O0 W5 I, g. r7 m8 m) W1 }* O/ G9 A
The 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. 5 v1 `! A: i9 F# Y- ^- ^7 G6 @
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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. 4 x( q6 U+ k: I4 D" e2 k : J' l( s1 d6 a! v& D6 m3 MThe 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. # y( i& _8 i4 `3 C' a* {
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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?" 6 r3 _+ g/ }- K0 l0 O8 W
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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. $ g5 D( w5 Z p9 K( @, J3 v0 A4 G! A9 E- n4 b/ O3 K
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High 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.3 G- H1 @1 N+ M5 F( ]# Q
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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. 6 U6 m) f( S& h. @
9 q% L, _: e, K; Z, \: D1 V8 uThey 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. 2 g6 r1 ?- i- J+ t5 g ' p& l* |, Z- V4 Y" w 1 `" q- E1 x; 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." 7 i, H; \3 x ~3 @. @; B: j/ ~/ D# N% j
By 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. - q- E1 I: t5 G7 o9 V. E" W8 F7 Z7 r1 o) X) D" U( L
"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." 3 M7 @4 Z& f# v5 k5 V% A
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UF Health Science Center 6 ~! w- C, x+ U3 |4 b1 J/ Q8 O+ x% }+ V# j$ d. y& p) @ 作者: tpwang 时间: 2011-1-23 08:21
本帖最后由 tpwang 于 2011-1-23 08:25 编辑 " R- Y" P! [% G* h3 O( x0 b5 o, i" D: a( [0 O# V 回复 decloud2009 的帖子 {: Y k1 c2 b- l+ s0 W 2 a6 S# t$ _& r1 N$ I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。2 M* p, s. S; ^- x& M9 U
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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。- A$ r. N" h8 _- S; K+ P
$ c- a% y, x$ X' O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。1 Y3 R/ h! F* P# W3 u3 I& U1 ^* G6 d