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joi, 15 decembrie 2011

Biochemical Signature Predicts Progression To Alzheimer's Disease

Main Category: Alzheimer's / Dementia
Also Included In: Biology / Biochemistry
Article Date: 15 Dec 2011 - 1:00 PST

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A study led by Research Professor Matej Oresic from VTT Technical Research Centre of Finland suggests that Alzheimer's disease is preceded by a molecular signature indicative of hypoxia and up-regulated pentose phosphate pathway. This indicator can be analysed as a simple biochemical assay from a serum sample months or even years before the first symptoms of the disease occur. In a healthcare setting, the application of such an assay could therefore complement the neurocognitive assessment by the medical doctor and could be applied to identify the at-risk patients in need of further comprehensive follow-up.

Alzheimer's disease (AD) is a growing challenge to the health care systems and economies of developed countries with millions of patients suffering from this disease and increasing numbers of new cases diagnosed annually with the increasing ageing of populations.

The progression of Alzheimer's disease (AD) is gradual, with the subclinical stage of illness believed to span several decades. The pre-dementia stage, also termed mild cognitive impairment (MCI), is characterised by subtle symptoms that may affect complex daily activities. MCI is considered as a transition phase between normal aging and AD. MCI confers an increased risk of developing AD, although the state is heterogeneous with several possible outcomes, including even improvement back to normal cognition.

What are the molecular changes and processes which define those MCI patients who are at high risk of developing AD? The teams led by Matej Orešic from VTT and Hilkka Soininen from the University of Eastern Finland set out to address this question, and the results were published on 13th Dec. 2011 in Translational Psychiatry.

The team used metabolomics, a high-throughput method for detecting small metabolites, to produce profiles of the serum metabolites associated with progression to AD. Serum samples were collected at baseline when the patients were diagnosed with AD, MCI, or identified as healthy controls. 52 out of 143 MCI patients progressed to AD during the follow-up period of 27 months on average. A molecular signature comprising three metabolites measured at baseline was derived which was predictive of progression to AD. Furthermore, analysis of data in the context of metabolic pathways revealed that pentose phosphate pathway was associated with progression to AD, also implicating the role of hypoxia and oxidative stress as early disease processes.

The unique study setting allowed the researchers to identify the patients diagnosed with MCI at baseline who later progressed to AD and to derive the molecular signature which can identify such patients at baseline.

Though there is no current therapy to prevent AD, early disease detection is vital both for delaying the onset of the disease through pharmacological treatment and/or lifestyle changes and for assessing the efficacy of potential AD therapeutic agents. The elucidation of early metabolic pathways associated with progression to Alzheimer's disease may also help in identifying new therapeutic avenues.

Article adapted by Medical News Today from original press release. Source: Technical Research Centre of Finland
Visit our alzheimer's / dementia section for the latest news on this subject. Technical Research Centre of Finland Please use one of the following formats to cite this article in your essay, paper or report:

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vineri, 9 decembrie 2011

Cellular Automaton Model Predicts How Hair Follicle Stem Cells Regenerate

Main Category: Dermatology
Also Included In: Stem Cell Research
Article Date: 09 Dec 2011 - 0:00 PST

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Your hair -- or lack of hair -- is the result of a lifelong tug-of-war between activators that wake up, and inhibitors that calm, stem cells in every hair follicle on your body, according to Cheng-Ming Chuong, M.D., Ph.D., of the University of Southern California (USC).

Chuong presented the findings at the American Society for Cell Biology 2011 Annual Meeting in Denver.

Building on research reported last April in Science, Chuong and his colleagues teamed with Oxford University mathematicians Philip Maini, Ph.D., and Ruth E. Baker, Ph.D., to use a "cellular automaton" model to describe the population behavior of hair follicles.

Using the predictive model, the researchers found that each adult human hair follicle could count only on its intrinsic growth-promoting signals, without the help of adjacent follicles in the macro-environment. In contrast, the growth of both rabbit and mice hair follicles depended on signals from neighboring follicles.

The cellular automaton model consists of a regular mathematical grid of automata, each of which represents one hair follicle in one of its four functional cyclic stages. Surrounding each automaton are eight automata, the hair follicle's neighbors.

The state of each automaton changes according to rules that dictate whether hair on a human scalp or in an animal's fur coat will be caught up in waves of growth called the anagen phase, or remain in the resting or telogen phase. Under the right conditions -- winter season or a new physiological stage in an organism's life such as puberty -- a collective regeneration wave can sweep through the skin, activating hair stem cells in individual follicles and those in front of them, by the tens of thousands.

In other seasons or life stages, individual follicles may remain locked in telogen by the inhibitors in their macro-environment. Inhibitor levels are modulated in part by intradermal adipose tissue and the central endocrine system. These multiple layers of control create a balance between inhibitory BMP (bone morphogenic protein) signaling that keeps hair stem cells in quiescent state and activating Wnt signaling that wakes them up.

Chuong reported robust wave spreading in rabbits, gradual spreading in mice, and random growth with loss of follicle coupling in human skin. The data suggest a new approach to androgenic alopecia, the most common form of alopecia in aging males: It may be easier to get hair follicles growing again by improving their environment, rather than implanting stem cells.

The success of the cellular automaton method could be applied to a broad range of biological pattern formation situations, including the spread of infectious diseases or neural networking in the developing brain, said Chuong.

Chuong and his colleagues determined that spacing between hair stem cell clusters was critical. Because rabbits have compound follicles (multiple hairs from one follicle), their stem cells were tightly coupled, and their coats regenerated so rapidly that the patterns resembled rapidly changing fractals. In humans, coupling of hair follicles was much lower, probably as a result of human evolution, Chuong said.

Article adapted by Medical News Today from original press release. Click 'references' tab above for source.
Visit our dermatology section for the latest news on this subject. Minisymposium: Collective Cell Behavior and Morphogenesis in Development Presentation 184
The research is funded in part by the National Institute of Arthritis, Musculoskeletal, and Skin Diseases. M. Plikus was supported by a training grant from the California Institute of Regenerative Medicine. C. Chen was supported by funding from Taipei VA Hospital and Yang Ming University. Collaborators at Oxford University, UK, were supported by EPSRC first grant and Royal Society Wolfson Research merit award.
American Society for Cell Biology Please use one of the following formats to cite this article in your essay, paper or report:

MLA

American Society for Cell Biology. "Cellular Automaton Model Predicts How Hair Follicle Stem Cells Regenerate." Medical News Today. MediLexicon, Intl., 9 Dec. 2011. Web.
9 Dec. 2011. APA

Please note: If no author information is provided, the source is cited instead.


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View the original article here