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These organizations based their recommendation by extrapolation of the studies done on atomic bomb survivors who had received higher doses of radiation. According to LNT theory a The effect of low doses or radiation can be estimated by linear extrapolation from effects observed by high doses, and b There are not any safe doses as even very low doses of ionizing radiation produce some biological effect Mortazan.

However, in reality, interpretation of results may to an extent, depend on the position of the interpreter. The frenzied debates about hormesis in radiation or global warming attest to the above assertion. Jamea Miller observed mutation following radiation of Drosophila. He assumed a linear relation between radiation and mutation though his experiments did not include very low doses of radiation. Catastrophe following nuclear war on Hiroshima and Nagasaki has resulted in radiophobia and an aversion to the concept of hormesis.

The evidence for hormesis is accumulating. And deaths due to leukemia in the sub group who received less than mSv was less than age matched controls. Nambi and Soman in have demonstrated a significantly reduced death due to cancer in high back ground areas versus areas of low background radiation in Kerala. Abbat Thus, there is no evidence of harmful effects of radiation at lower doses. Yet, most people tend to go by LNT model including regulatory authorities. It took a while to establish a link between administration of saturated oxygen and retrolenticular fibroblasia in neonates.

It was felt that life sustaining oxygen can never harm human life even at higher concentration. Thus, establishing a casual link between retrolenticular hyperplasia and saturated oxygen took considerable time by which time innumerable neonates were affected. The biphasic action of chlorpromazine as protector and senstiser at various concentrations is yet another instance of concentration dependent behavior. There are innumerable such examples of biphasic phenomenon. Hormesis also has played a crucial role in the evolution of life.

Life had to evolve despite the harsh environmental conditions, including higher cosmic radiation that is seen now. Cellular mechanism including signaling pathways responsible for adaptive pathways are emerging. Now, there is a mechanistic explanation for a possible hermetic response for a wide range of stimulants, including that for ionizing radiation.

Men are no Drosophila or cells in the Petri dish. Complex biological systems behave much differently than most people concede. Failure to acknowledge hormesis is also a failure to realize essential realities of biological complexity. There is a slow broadening of views in the area of radiobiology to where hormesis is being accepted. The new view incorporates concepts of hormesis , nonlinear systems, bioenergy field theory, uncertainty and homeodynamics.

While the mechanisms underlying these effects and responses are still far from clear, it is very apparent that their implications are much wider than the field of radiobiology. This reflection discusses the changing views and considers how they are influencing thought in environmental and medical science and systems biology. For years, voices have been raised calling for acknowledgement of the existence of radiation hormesis and for revision of the LNT linear no-threshold standards for radiation protection which state that radiation exposure at any dose is biologically damaging.

These calls have not gotten anywhere so far. Perceived harm to irradiated nuclear workers and the public is mainly reflected through calculated hypothetical increased cancers. The LNT-based system of protection employs easy-to-implement measures of radiation exposure. Such measures include the equivalent dose a biological-damage-potential-weighted measure and the effective dose equivalent dose multiplied by a tissue-specific relative sensitivity factor for stochastic effects.

These weighted doses have special units such as the sievert Sv and millisievert mSv, one thousandth of a sievert. Radiation -induced harm is controlled via enforcing exposure limits expressed as effective dose. Expected cancer cases can be easily computed based on the summed effective dose person-sievert for an irradiated group or population. Yet the current system of radiation protection needs revision because radiation -induced natural protection hormesis has been neglected.

A novel, nonlinear, hormetic relative risk model for radiation -induced cancers is discussed in the context of establishing new radiation exposure limits for nuclear workers and the public. Given that individuals may vary significantly in their hormetic responses to radiation, establishing standards to replace LNT could be a daunting task. It is unfortunate that radiation safety standards and therefore radiation hormesis seem to be so bound up with nuclear energy safety issues, issues of great public concern where most people want to be on the safe side.

It is thought by some that radiation hormesis is mainly an argument put forward by the nuclear industry to lessen the regulatory burden on it, and this may to some extent be so. However, science is science. Radiation hormesis is ancient and evolutionary but good news, providing us with layers of protection we did not know about.

It also seems clear to me that the LNT standards for radiation safety should be revised given the presence of radiation hormesis, but how much so will require further concerted study and that in turn will require a new public safety initiative. Fully acknowledging the effects of radiation hormesis conceivably could significantly reduce public concern for radiation safety from x-rays and radon as well as nuclear power plants.

Your email:. This blog is about Mitohormesis , a different form of hormesis than that discussed in the previous blog entry Radiation Hormesis. Mitohormesis has to do with cell metabolic pathways and oxidative stress, topics I have discussed in many previous blog entries. The proper functioning of mitohormesis has to do with multiple aspects of health and with extended organism longevity in many species, quite probably including our own. And the absence of proper mitohormesis functioning has been shown to be associated with certain disease processes and shortened lifespans in a range of animals including humans.

As is the case for radiation hormesis, the concept of mitohormesis has been around for some time but has not been universally accepted. It is only recently being widely acknowledged as an important biological phenomenon. And only relatively recently are its mechanisms of operation being unveiled. I am grateful for an intensive round of communication with James P Watson, a follower of this blog and stem cell researcher, which helped me to improve this blog entry.

This is not to say that Watson, clearly a very brilliant person, will necessarily agree with all I have to say. In researching this blog entry I encountered a number of interesting recent research results having to do with topics I have discussed previously including mitochondrial metabolism, the OXPHOS system in general, mitochondrial biogenesis, frataxin , the key roles of SIRT3 in controlling ROS stress in mitochondria, and the health roles of PCG1alpha.

And I started to question whether it makes sense to supplement with PQQ. And there are pathways which seem to produce health benefits independently of motohormesis, like inhibition of TOR. Because of the great complexity involved I decided to cover most of those topics in subsequent blog entries — even though they all bear on mitohormesis.

So, my intent is to keep this present blog entry focused on mitohormesis itself, what turns it on and off, and the direct health implications of mitohormesis. In particular, I deal with the important practical topic of mitohormesis and exercise, and how some antioxidants nullify the health benefits of regular exercise.

Hormesis in General. The first section of the previous blog entry Radiation Hormesis is a short introduction to the topic of hormesis in general, and I will not repeat that introduction here. What is Mitohormesis? Consistently, abrogation of this mitochondrial ROS signal by antioxidants impairs the lifespan-extending and health-promoting capabilities of glucose restriction and physical exercise, respectively.

In summary, the findings discussed in this review indicate that ROS are essential signaling molecules which are required to promote health and longevity. Hence, the concept of mitohormesis provides a common mechanistic denominator for the physiological effects of physical exercise, reduced calorie uptake, glucose restriction, and possibly beyond.

This review aims to summarize published evidence that several longevity-promoting interventions may converge by causing an activation of mitochondrial oxygen consumption to promote increased formation of reactive oxygen species ROS. These serve as molecular signals to exert downstream effects to ultimately induce endogenous defense mechanisms culminating in increased stress resistance and longevity, an adaptive response more specifically named mitochondrial hormesis or mitohormesis.

Consistently, we here summarize findings that antioxidant supplements that prevent these ROS signals interfere with the health-promoting and life-span-extending capabilities of calorie restriction and physical exercise. And, in fact, suppression of ROS by taking antioxidants can be health-damaging and life-shortening ref.

These points were also made in the publications related to radiation hormesis cited in the previous blog entry. They are also articulated in several of the publications that will be cited here as relevant to mitohormesis. Hormesis, Nrf2 and Antioxidant supplementation — a unifying framework.

Before proceeding further with specific findings reported in the literature, I would like to outline a framework for viewing these findings, findings which otherwise sometimes seem inconsistent. The major points of this framework are:. And, in reviewing the literature of hormesis I likewise find that the keap1-Nrf2 pathway is mentioned only rarely.

Yet my research suggests that everything that is known to happen associated with hormesis is completely explainable by the operation of keap1-Nrf2 pathway, without reference to other pathways normally associated with hormesis such as the heat-shock response. In stressing the role of the keap1-Nrf2 pathway in hormesis, I of course acknowledge that this is a simplification and far from tells the whole story.

L-proline catabolism can also be involved ref. HDAC inhibition and histone-dependent gene silencing can be involved. And of course there are other largely independent body stress-response pathways like the UPR unfolded protein response ref and the various kinds of DNA repair machinery. A key to understanding what is going on in hormesis is understanding how the hormetic dose-response curve works, and this can be formulated in terms of NRF2 expression.

In my interpretation, the horizontal axis depicts level of stress, say as driven by ROS load. The vertical axis represents relative risk , level of probable pathological organismic response where normal level is 1. To the left of the first axis crossing in the diagram point D the Keap1-Nrf2 pathway is progressively kicking in but not sufficiently so as to overcome the direct negative effects of ROS stress.

Phantom risk is theoretical risk for low stress levels that would apply if the linear model were extrapolated for low stress dosages. According to this model, supplementation with radical-scavenging supplements like vitamins C and E inhibits the ROS which triggers the release of Nrf2 which produces hormesis when the stress is in the hormesis range, i.

The result of such supplementation is a lower health state. That is, supplementation with such antioxidants when the stress is within the hormesis range of stress can turn off the stress that activates the keap1-Nrf2 pathway therefore turning off hormesis and can do more harm than good.

It appears, for example, that this is what happens with exercise where taking antioxidants eliminates the hormetic health benefits of the exercise. Some of the earlier research on free radicals and their damaging effects appears to be concerned with high dosages in this beyond-hormesis region. So these early anti-ROS and pro-antioxidant papers are valid in their own domains and not in fact contradicted by later papers that show positive health effects associated with lower levels of ROS stress.

I believe serious nuclear plant radiation overexposure and accidental ingestion of heavy metals are excellent reasons for taking heavy doses of radical-scavenging antioxidants. They work by activating Nrf2 and triggering a hormesis response which lowers ROS and produces a wide range of positive health effects. I discuss these and other substances which activate Nrf2 in the blog entry The pivotal role of Nrf2. Part 2 — foods, phyto-substances and other substances that turn on Nrf2.

Now, moving on to some results reported in the literature:. In some lower organisms, inducing enhanced ROS signaling can lead to mitohormesis and significantly extended lifespans. By contrast, acute impairment of daf-2 in adult C. Consistent with the concept of mitohormesis, this ROS signal causes an adaptive response by inducing ROS defense enzymes SOD, catalase , culminating in ultimately reduced ROS levels despite increased mitochondrial activity.

IIIS upregulates mitochondrial L-proline catabolism, and impairment of the latter impairs the life span-extending capacity of iIIS while L-proline supplementation extends C. Taken together, iIIS promotes L-proline metabolism to generate a ROS signal for the adaptive induction of endogenous stress defense to extend life span. Many substances can promote mitohormesis at low doses, even poisons which are highly toxic at higher doses.

An example is the highly toxic pesticide rotenone. We investigated the effects of rotenone Compared with controls, rotenone ROS production was continually increased in cells treated with rotenone. These data indicate that low concentrations of rotenone can induce mitohormesis, which may be attributed to ROS production.

Again, more proof of mitohormetic dose-response curve. One of several substances that promotes mitohormesis in nematodes is the phytochemical glaucarubinone. We have found that glaucarubinone induces oxygen consumption and reduces body fat content of C. Moreover and consistent with the concept of mitohormesis, glaucarubinone extends C. Taken together, glaucarubinone is capable of reducing body fat and promoting longevity in C.

Yet another substance that appears to induce a hormetic-like effect in muscle tissues is Stanozolol. Since muscle fatigue has been related to oxidative stress caused by an exercise-linked reactive oxygen species ROS production, we investigated the potential effects of a treatment with the anabolic androgenic steroid stanozolol against oxidative damage induced on rat skeletal muscle mitochondria by an acute bout of exhaustive exercise.

Mitochondrial ROS generation with complex I- and complex II-linked substrates was increased in exercised control rats, whereas it remained unchanged in the steroid-treated animals. Stanozolol treatment markedly reduced the extent of exercise-induced oxidative damage to mitochondrial proteins, as indicated by the lower levels of the specific markers of protein oxidation, glycoxidation, and lipoxidation, and the preservation of the activity of the superoxide-sensitive enzyme aconitase.

This effect was not due to an enhancement of antioxidant enzyme activities. Acute exercise provoked changes in mitochondrial membrane fatty acid composition characterized by an increased content in docosahexaenoic acid. In contrast, the postexercise mitochondrial fatty acid composition was not altered in stanozolol-treated rats.

Our results suggest that stanozolol protects against acute exercise-induced oxidative stress by reducing mitochondrial ROS production, in association with a preservation of mitochondrial membrane properties. The aim of the study was to test whether pharmaceutical concentrations of the glycolytic inhibitor lonidamine are capable of extending lifespan in a nematodal model organism for aging processes, the roundworm Caenorhabditis elegans.

Several hundreds of adult C. Lonidamine was applied to test whether it may promote longevity by quantifying survival in the presence and absence of the compound. In addition, several biochemical and metabolic assays were performed with nematodes exposed to lonidamine. Moreover, the compound increases paraquat stress resistance, and promotes mitochondrial respiration, culminating in increased formation of reactive oxygen species ROS. Extension of lifespan requires activation of pmk-1, an orthologue of p38 MAP kinase, and is abolished by co-application of an antioxidant, indicating that increased ROS formation is required for the extension of lifespan by lonidamine.

Consistent with the concept of mitohormesis, lonidamine is capable of promoting longevity in a pmk-1 sensitive manner by increasing formation of ROS. I Mitohormesis appears to be a pathway response preserved by evolution over many species, ranging from yeast cells to nematode worms to humans. This, in turn, produces an adaptive mitochondrial ROS signal that extends worm life span.

These findings further bolster the concept of mitohormesis as a critical component of conserved aging and longevity pathways. Using the yeast chronological aging model, researchers have identified conserved signaling pathways that affect lifespan by modulating mitochondrial functions.

Caloric restriction and a genetic mimetic with reduced target of rapamycin signaling globally upregulate the mitochondrial proteome and respiratory functions. Mitohormesis involves a variety of ROS during several growth stages and extends lifespan in yeast and other organisms. Here we recap recent advances in understanding of ROS as signals that decelerate chronological aging in yeast. We also discuss parallels between yeast and worm hypoxic signaling.

In sum, this mini-review covers mitochondrial regulation by nutrient-sensing pathways and the complex underlying interactions of ROS, metabolic pathways, and chronological aging. Exploitation of mitohormesis could become an important strategy for prevention and control of heart diseases.

Reactive oxygen and nitrogen species are the most common electrophiles formed during lipid peroxidation and lead to the formation of both stable and unstable LPP. Of the LPP formed, highly reactive aldehydes are a well-recognized causative factor in ageing and age-associated diseases, including cardiovascular disease and diabetes. Numerous studies have found that there are functional consequences in the heart following exposure to specific aldehydes acrolein, transhexanal, 4-hydroxynonenal and acetaldehyde.

Because these LPP are known to form in heart failure, cardiac ischaemia-reperfusion injury and diabetes, they may have an underappreciated role in the pathophysiology of these disease processes. Lipid peroxidation products are involved in the transcriptional regulation of endogenous anti-oxidant systems. Recent evidence demonstrates that transient increases in LPP may be beneficial in cardioprotection by contributing to mitohormesis i.

Thus, exploitation of the cardioprotective actions of the LPP may represent a novel therapeutic strategy for future treatment of heart disease. Mitochondrial metabolism appears critical to sustain cardiac function to counteract aging. In this study, we generated mice transgenically over-expressing the mitochondrial protein frataxin, which promotes mitochondrial energy conversion by controlling iron-sulfur-cluster biogenesis and hereby mitochondrial electron flux.

Hearts of transgenic mice displayed increased mitochondrial energy metabolism and induced stress defense mechanisms, while overall oxidative stress was decreased. Following standardized exposure to doxorubicin to induce experimental cardiomyopathy, cardiac function and survival was significantly improved in the transgenic mice.

Activation of this cascade is markedly inhibited in the hearts of wild-type mice following induction of cardiomyopathy. Taken together, these findings suggest that increased mitochondrial metabolism elicits an adaptive response due to mildly increased oxidative stress as a consequence of increased oxidative energy conversion, previously named mitohormesis.

This in turn activates protective mechanisms which counteract cardiotoxic stress and promote survival in states of experimental cardiomyopathy. Thus, induction of mitochondrial metabolism may be considered part of a generally protective mechanism to prevent cardiomyopathy and cardiac failure.

The chemotherapy drug is a common FDA approved drug that causes cardiomyopathy when patients are treated with too much of this drug. In the frataxin-over expressed mice, there was an induction of mitochondrial metabolism and ROS defense. Statins induce mitohormesis, mitochondrial biogenesis and associated positive health effects in cardiac tissue but do not induce mitohormesis and instead induce excessive ROS stress and negative health effects in skeletal muscles.

To investigate mechanisms of statins, we tested the hypothesis that statins optimized cardiac mitochondrial function but impaired vulnerable skeletal muscle by inducing different level of reactive oxygen species ROS. However, in deltoid biopsies from patients with statin-induced muscular myopathy, oxidative capacities were decreased together with ROS increase and a collapse of PGC-1 mRNA expression.

Several animal and cell culture experiments were conducted and showed by using ROS scavengers that ROS production was the triggering factor responsible of atorvastatin-induced activation of mitochondrial biogenesis pathway and improvement of antioxidant capacities in heart. Conversely, in skeletal muscle, the large augmentation of ROS production following treatment induced mitochondrial impairments, and reduced mitochondrial biogenesis mechanisms.

Quercetin, an antioxidant molecule, was able to counteract skeletal muscle deleterious effects of atorvastatin in rat. The report highlights the importance of dosage in determining whether ROS stress is in the range where the positive effects of hormesis are realized where the hormetic response curve is above the line , or the stress is too great where the hormetic response curve is below the line , and the net health result is negative.

The dose response curve must be scaled different for cardiac and muscle tissue. Apparently, a dose of statins with a response above the line for cardiac tissue produces a result below the line for muscle tissue. A second point of the above publication is the importance of the ROS. PGC-1 signaling pathway in regulation of mitochondrial biogenesis and functions. This protein interacts with the nuclear receptor PPAR-gamma , which permits the interaction of this protein with multiple transcription factors.

It provides a direct link between external physiological stimuli and the regulation of mitochondrial biogenesis, and is a major factor that regulates muscle fiber type determination. This protein may be also involved in controlling blood pressure, regulating cellular cholesterol homoeostasis, and the development of obesity ref. Regarding this article, James P Watson had some very interesting comments which he communicated to me privately, as follow.

This is very convincing evidence of an ROS-mediated mitohormetic mechanism in the heart for statins and an opposite mitodestructive mechanism in skeletal muscles with statin therapy. Here are the results summarized:. N uclear co-activators and gene expression ;. ROS production. This study did not include anti-oxidants. It was just a skeletal muscle vs cardiac muscle biopsy study, done during open heart surgery.

My comment James P Watson, continuing on this article and diagram:. Another publication relating exercise, ROS and the impact of statins is the publication Atorvastatin treatment reduces exercise capacities in rats: involvement of mitochondrial impairments and oxidative stress.

Mitochondrial impairments may play an important role in the development of muscular symptoms following statin treatment. Our objective was to characterize mitochondrial function and reactive oxygen species ROS production in skeletal muscle after exhaustive exercise in atorvastatin-treated rats. By blocking mitohormesis, regular supplementation with antioxidants may block the beneficial effects of regular exercise.

This is a sobering revelation for those who both regularly exercise and take antioxidant supplements, believing that these interventions work synergistically. A publication Antioxidants prevent health-promoting effects of physical exercise in humans speaks as to how by blocking mitohormesis, supplementation with Vitamins C and E nullifies the health-producing effects of physical exercise.

However, exercise also increases mitochondrial formation of presumably harmful reactive oxygen species ROS. Antioxidants are widely used as supplements but whether they affect the health-promoting effects of exercise is unknown. Before and after a 4 week intervention of physical exercise, GIR was determined, and muscle biopsies for gene expression analyses as well as plasma samples were obtained to compare changes over baseline and potential influences of vitamins on exercise effects.

Molecular mediators of endogenous ROS defense superoxide dismutases 1 and 2; glutathione peroxidase were also induced by exercise, and this effect too was blocked by antioxidant supplementation. Consistent with the concept of mitohormesis, exercise-induced oxidative stress ameliorates insulin resistance and causes an adaptive response promoting endogenous antioxidant defense capacity. Supplementation with antioxidants may preclude these health-promoting effects of exercise in humans.

Notably, by blocking exercise-dependent formation of reactive oxygen species due to ingestion of antioxidant supplements, health promoting effects of physical exercise are abolished, and physical exercise fails to promote insulin sensitivity and antioxidant defense in the presence of vitamin C and vitamin E. The patterns of coupling the taking of antioxidants along with regular physical exercise in the interest of general health is, for many people, deeply entrenched, encouraged by much advertising, and only recently being seriously questioned.

The August publication Does vitamin C and e supplementation impair the favorable adaptations of regular exercise? However, controversy has risen regarding the potential outcomes associated with vitamins C and E, two popular antioxidant nutrients.

Recent evidence has been put forth suggesting that exogenous administration of these antioxidants may be harmful to performance making interpretations regarding the efficacy of antioxidants challenging. The available studies that employed both animal and human models provided conflicting outcomes regarding the efficacy of vitamin C and E supplementation, at least partly due to methodological differences in assessing oxidative stress and training adaptations.

Long-term antioxidant supplementation, specifically with Vitamin C and alpha-lipoic acid, reduces mitochondrial biogenesis in skeletal muscle tissue by interfering with ROS signaling that triggers mitohormesis. However, exercise-induced ROS may regulate beneficial skeletal muscle adaptations, such as increased mitochondrial biogenesis. METHODS: Male Wistar rats were divided into four groups: 1 sedentary control diet, 2 sedentary antioxidant diet, 3 exercise control diet, and 4 exercise antioxidant diet.

Experimental Evidence also shows absence of research support for the popular idea that antioxidant supplementation is a good thing to do associated with fitness exercising. This has provoked expansion of the supplement industry which responded by creation of a plethora of products aimed at facilitating the needs of the active individual. However, what does the experimental evidence say about the efficacy of antioxidants on skeletal muscle function?

Are antioxidants actually as beneficial as the general populous believes? Or, could they in fact lead to deleterious effects on skeletal muscle function and performance? This Mini Review addresses these questions with an unbiased look at what we know about antioxidant effects on skeletal muscle, and what we still need to know before conclusions can be made. On the contrary, studies with antioxidant supplementations generally show no effect on muscle function during and after exercise. The exception is NAC treatment, which has been found to improve performance during submaximal exercise.

It appears that muscle fibers are in some way protected against deleterious effects of oxidants during exercise and fibers are generally much more sensitive to exposure to oxidants in the rested state than during fatigue. The molecular mechanisms leading to sarcopenia are not completely identified, but the increased oxidative damage occurring in muscle cells during the course of aging represents one of the most accepted underlying pathways.

In fact, skeletal muscle is a highly oxygenated tissue and the generation of reactive oxygen species is particularly enhanced in both contracting and at rest conditions. It has been suggested that oral antioxidant supplementation may contribute at reducing indices of oxidative stress both in animal and human models by reinforcing the natural endogenous defenses.

Aim of the present paper is to discuss present evidence related to possible benefits of oral antioxidants in the prevention and treatment of sarcopenia. In fact, a large body of evidence may indicate extreme cautiousness in taking antioxidant supplementation as preventive measures against aging process and age-related conditions. Further studies are needed to support the widespread practice of oral antioxidant supplementation and to determine appropriate recommendations in elderly.

Instead, seemingly puzzled, the authors suggest a need for more research to relate sarcopenia to antioxidant use. In acknowledgement of the existence of mitohormesis, metabolic researchers are beginning to think in terms not only of oxidative stress but also in terms of antioxidant stress, especially associated with the consumption of antioxidants.. ROSs were considered traditionally to be only a toxic byproduct of aerobic metabolism. However, recently, it has become apparent that ROS might control many different physiological processes such as induction of stress response, pathogen defense, and systemic signaling.

Thus, the imbalance of the increased antioxidant potential, the so-called antioxidative stress, should be as dangerous as well. Oxidative stress is not necessarily an un-wanted situation, since its consequences may be beneficial for many physiological reactions in cells.

Antioxidants can neutralize ROS and decrease oxidative stress; however, this is not always beneficial in regard to disease formation or progression of, e. The normal balance between antioxidants and free radicals in the body is offset when either of these forces prevails. The available evidence on the harmful effects of antioxidants is analyzed in this review.

Negative health effects due to inhibition of ROS and consequent inhibition of mitohormesis applies to classical antioxidants, substances like vitamins C and E that act as free radical scavengers. Regarding this point, see the blog entry The pivotal role of Nrf2. Speaking also directly to this point is the March publication Oligomerized lychee fruit extract OLFE and a mixture of vitamin C and vitamin E for endurance capacity in a double blind randomized controlled trial. The study aimed to investigate the effects of a polyphenol mixture and vitamins on exercise endurance capacity.

Seventy regularly exercising male participants were randomly assigned to receive oligomerized lychee fruit extract, a mixture of vitamin C mg and E IU , or a placebo for 30 consecutive days. The adjusted mean change was 3. Oligomerized lychee fruit extract significantly increased the anaerobic threshold by 7. On the other hand, vitamins significantly attenuated VO 2 max by Their effects on plasma free radical amount, however, were similar.

Our results suggest that a polyphenol-containing supplement and typical antioxidants may have different mechanisms of action and that the endurance-promoting effect of oligomerized lychee fruit extract may not directly come from the scavenging of free radicals but may be attributed to other non-antioxidant properties of polyphenols, which requires further investigation. Consistant with the above discussions regarding mitohormesis, researchers are continuing to discover additional important biological roles played by oxidative stress, even extending to sexual signaling.

In , von Schantz et al. Their suggestion has been enthusiastically tested, with over studies citing their paper, but most effort has concerned carotenoid-based and to a lesser extent melanin-based visual signals, predominantly in birds and fishes. Today, we know a great deal more about oxidative stress and related physiology, in both a pathological and regulatory sense, than we did in We revisit von Schantz et al. In particular, we argue that differences between individuals in their ability to regulate physiology related to oxidative stress may be an important factor influencing the production of sexual signals and the costs that are incurred from investment.

Wrapping it up. Mitohormesis, like radiation hormesis exists and is important. Here I have been able to discuss some key aspects of mitohormesis, but there is probably much more to come. My experience in writing this blog entry was the usual one of more questions being raised than answered. The leading edges of science are never neat and nicely wrapped up. James P Watson has argued with me privately, for example, that most all scientifically proven lifespan extension phenomena are due to a mitohormetic principle.

And I hope that some combination of he and I will be able to lay that argument out in a blog posting to come. Me, working up a little mitohormesis in the gym. I also benefit from blogohormesis: Working to get my mind around the subject of this blog entry initially produced a similar experience of nearly-impossible weight and stress.

This was slowly replaced by a feeling of wellbeing, one that will be good hopefully until I get deeply into the next blog entry. There appears to be a Great Divide in the world when it comes to health, manifest most clearly in Western Countries and in the US in particular.

The divide is between two major paradigms of thinking, philosophies, methods and institutions used to maintain health and treat diseases. On one side of the divide we have what today is popularly called Health Care. On the other side of the Divide we have the paradigm I will call Wellness - which is actually the current form of Folk Health.

This blog entry updates and amplifies on the theme of my May blog entry Shift to the wellness-longevity paradigm. I reiterate some of the key points in that blog entry and focus particularly on the dynamics that keep the Great Divide in place. I discuss how new scientific knowledge of certain plant-based substances can contribute to bridging the Great Divide. And I express concern about how that can happen. This is a long blog entry and if you want to go first to conclusions and suggestions you can scroll down to the final section entitled Wrapping it all up — bridging the Great Divide.

The two paradigms of Health Care and Wellness encompass behavior patterns, educational approaches, major institutions, government policies and agencies. The divide is to some extent also between old and new, between East and West, and between how a person decides on what to do about his or her wellness and health.

It involves who people trust for health advice, and between what educated people think they are supposed to do and what they actually do. Though operating in very different spheres, there is some evidence that these two paradigms are increasingly overlapping and moving together.

I believe this is a very good thing. In this blog entry I discuss the strengths and weaknesses of each paradigm. I talk about how the two paradigms complement and require each other, and how the process of bringing them together might be accelerated. My primary reference here is the situation in the US, although similar patterns exist in other advanced countries.

Health Care. First, let me outline the paradigm of Health Care as I see it. Health Care is based mainly on Allopathic Medicine and goes on to encompass vast institutions. At the periphery lie health insurance companies, nursing homes and secondary care facilities, government bureaucracies and countless university and private laboratories and research institutions.

The numbers involved in US health care are mind-numbing. And these costs do not include suffering from diseases, lost time from work for individuals and employers, loss of productivity, and care provided by unpaid caregivers. The Health Care system facilitates progress in many important dimensions. But the relationships among central players also limits progress in overall public health.

What drives or limits progress in Health Care? What is the source of innovation? What inhibits innovation? MD doctors and the medical schools and boards that train and discipline them, 2. The pharmaceutical, biotech and medical technology industries that convert research knowledge into practical drugs and educate doctors about these, and 3.

Government agencies, especially the FDA which sets the rules for how new drugs are developed and released to the public. Only doctors and a few other highly licensed practitioners can prescribe legally-sanctioned drugs. New drugs are developed typically through the course of an years period of research and development, culminating with Phase 1, Phase2 and Phase 3 clinical trials. These trials are overseen by the FDA and alone may cost from one to several hundred million dollars. No wonder that big drug companies aim new drugs at massive markets and the business model is like that for blockbuster movies.

Medical doctors are highly trained, regulated and respected in our society. They function within practice frameworks prescribed by law and by rule-setting professional associations like the American College of Cardiology, the American Association for Thoracic Surgery, the American Academy of Pediatrics, etc. Few doctors will administer or prescribe treatments that have not gone through the FDA approval process and that are not mainline in their professional subspecialty.

One reason is that straying beyond FDA and association-approved medications engenders a risk of ruinous lawsuits. If a treatment prescribed is not an established standard of medical practice and someone claims to be harmed by that treatment, the doctor is at risk of ruin.

Use of standard and government approved drugs provides badly needed legal coverage in case of such commonly-occurring lawsuits. Another reason, sadly, is that doctors, being extremely busy as they are, may simply not know about highly effective alternative treatments in Wellness which have been highly researched and found effective but which are not FDA sanctioned. Physicians get much of their drug information not from reading research journals but from pharma company representatives that are constantly calling on them.

As a result, I believe there are numerous effective alternative treatments that are locked out of medical practice. By-and-large, allopathic physicians do not know about them. They live in limbo. Health Care is basically a repair-oriented industry. The main context of Health Care has been repair rather than regular maintenance. For the most part, patients invoke Health Care to fix a problem when it manifests itself. You have a sore throat or a serious pain, you see a doctor.

The most serious problem with the repair-oriented paradigm of Health Care is that by the time a serious degenerative disease problem shows up, it is frequently too late effectively to do anything about it. And for them a diagnosis is like a death sentence.

Early-detection biomarkers for more and more of these diseases are being identified and there are a number of simple preventative maintenance interventions that can be applied to forestall actual diseases from emerging, even when there is a genetic risk factor for them. However, the concept of Preventative Medicine is only now starting to receive semi-serious attentions. For most of us, Preventative Medicine within the Health Care paradigm means relatively superficial checkups.

Blood pressure and pulse is checked at every office visit to a doctor. An annual physical exam involves a few blood and urine tests, the doctor thumping us and looking in our orifices, asking us a few questions. Once every few years there might be a cardiogram, chest x-ray, mammogram, colonoscopy or other diagnostic procedure. For seemingly healthy people however, even aging ones, predictive biomarkers for specific deadly age-related diseases are not looked for.

For airliners, healthcare is mainly about constant checkups and preventative maintenance, not about repair-after-breakdown. An airliner must be inspected before each flight and is subject to a strictly enforced schedule of preventative maintenance required by law. Imagine what it would be like if airliners were in a healthcare system like us humans are — where repairs are initiated only when a problem becomes clearly manifest.

For an airliner this could mean an engine stopping or catching fire in mid-air or a flat tire that is only discovered when taking off. The idea is very scary and our airline accident death rate would be many times what it is now. However by moving in the direction of regular preventative maintenance we could do a lot better than we are doing now.

The term Health Care itself is misleading because the paradigm of Health Care actually cares a lot more about trying to cure problems of health than it cares about maintaining individuals or a population in a healthy state. How well is Health Care doing? The answer depends on the perspective. Health care is responsible for many achievements. Sophisticated technologies have been brought to bear on a massive scale, such as the use of MRI machines for diagnosis and interventional radiology for performing surgeries without cutting.

A few formerly incurable diseases are now curable, although the treatments are sometimes draconian. More cancers are being cured. People who are walking around would have been dead without triple bypass surgeries or the use of special drugs that address certain deadly and rare diseases. Orthopedic procedures such as knee, hip and shoulder replacements keep many people functional and moving, and there is progress in developing robotic appendages.

Measures of health such as longevity, diseases of all causes, infant mortality and disease incidences and cure rates have generally continued to improve year-to-year. See ref for details. Why have we dropped from being ranked 23th in ? Why are we not even in the top 20 countries when it comes to life expectancy when we ranked 7 th. And the same pattern exists for most other health statistics related to specific diseases and conditions.

Our performance ranks down with that of third-world countries while, all at the same time that we spend at least twice as much per healthcare per capita than in other countries. And as the population ages and lifespans become longer, these diseases become more and more important. Health Care is not the major factor in determining health of a population. Wellness appears to be more important. The conclusion seems inescapable.

There is great concern today in improving the efficiency of health care, controlling health care costs, speeding up the FDA approval process, eliminating unnecessary medical procedures, developing better medical records, etc.. These could be very good things to do. However, improving the efficiency of Health Care is not going to be enough. By itself the Health Care paradigm is incomplete, broken and in key respects obsolete. Unless other initiatives are taken, health care costs are likely to continue to spiral upwards and our relative health performance as a country is likely to spiral even further downwards.

We have to do something else, and I believe the place to look for that something else is in the Wellness paradigm. Wellness — Folk Health. Wellness, Folk Health, has deep historical roots and includes but is not confined to Folk Medicine. Wellness is not focused on sickness but rather on maintenance of health and longevity.

It is comparable to preventive maintenance where steps are taken to prevent debility or sickness sufficiently in advance so that actual debility or sickness becomes relatively scarce. While important aspects of wellness are captured in the traditional Health Care idea of preventative medicine , wellness-longevity goes much further in expectations for ever-enhanced longevity, personal productivity and transformed lifestyles.

As I see it, Wellness encompasses all health-oriented activities that take place outside of the health care allopathic medicine establishment. Wellness includes all the things people do as individuals to keep themselves healthy including eating healthy food, fastening seat belts, watching their weight, exercising regularly, using air and water purifiers in their homes and consuming dietary supplements.

And Wellness includes public health initiatives. Historically, the most striking gains in health and population longevity have been due to public health initiatives. In recent history for example, automobile injury deaths and rates of certain cancers have declined due to safer cars and anti-smoking campaigns. AIDS educations has been another important health-promoting factor, as is the use of mosquito netting in the third world to control malaria.

Over the last years water treatment and sewage systems have been major contributors to longevity. Some public health gains have been the results of other technological developments. The replacement of horses with automobiles eliminated fecal materials in the streets and reduced bacterial contamination in cities, and modern oil and gas furnaces eliminates the cancerous clouds of smoke from wood burning fireplaces that once hung over our cities.

Catalytic converters and other emission-control measures are reducing smog in cities that contributes to pulmonary problems. And today anti-obesity campaigns and public awareness programs about diabetes are kicking in. Folk Medicine. Folk medicine , a subset of Wellness, is still the mainly practiced form of medicine in many parts of the world, and is surprisingly vital and growing today, even in the US.

Each of these is thousands of years old and has involved the passage of knowledge from generation to generation primarily by oral means. These and other forms of folk Medicine tend to look at diseases more in terms of perturbations of whole-body systems than in Health Care which is more reductionist. Most forms of Folk Medicine practiced throughout the world are heavily focused on herbal treatments. Folk Medicine is usually passed on by an oral tradition and its practitioners may be trained or be self-declared.

They can be known by such names as healers, shamans, bush doctors and curanderos. Contemporary Chinese pharmacy. Folk Health is mainly focused on disease prevention, staying healthy and longevity, and only partially on disease repair. Folk Medicine tends to be concerned with both health maintenance and treating diseases, in most cases viewing the two as intrinsically related. Often, Folk Medicine as well as other practices of Folk Health have strong spiritual and mental wellbeing components.

In the US for example, many practitioners of yoga and meditation view themselves as being important contributors to Wellness. I believe Wellness is alive and thriving in the US and Western countries with ever-new forms of expression. Like traditional Folk Health it is largely separate and independent from Health Care.

Like traditional Folk Health the major focus is on wellbeing, general health and longevity. One major trend in wellness is that individuals increasingly are taking personal responsibility for their own health. There is no one strong group of respected healers, curanderos or bush doctors in our US society.

But there are many groups with their individual wellness-related specialties like athletic trainers, specialized non-medical therapists of all kinds, dietary advisors and TV Wellness gurus, practitioners of homeopathy and naturopathy, and teachers of yoga, tai chi, massage, meditation and acupuncture.

This is the solution as implemented in the Web which was introduced 20 years ago. Its simplicity also leaves room for improvement. Semantic technology adds tags to semistructured information as database technology adds column headings to tabular information. In a similar fashion, programs and other computational resources can be described through semantic annotations.

This is the essence of Semantic Web technology. This is investigated in more detail in the following. Logic is a 1,year-old technology to formally capture meaning. Over this long history, especially relatively recently, a large number of logics have been developed, each suitable for a specific purpose. The focus is on a small number of these languages, in particular, on those that provide insights into the overall design issues associated with logical languages and those that have been applied in a Semantic Web context.

A number of languages will be then examined that are used to express the meaning of data on the Semantic Web. Finally, there would be a discussion on open issues and problems when applying logic to the Web. From an algorithmic perspective, implementing logical-reasoning systems demonstrates clearly how complex decidability and complexity are to manage cf.

First, briefly described are logical paradigms in increasing levels of complexity, and then, how com- puter scientists identified reasonable subsets which can be handled to a certain extent. Propositional Logic is a rather simple logic language providing propositions such as A, B, C,. All interpretations are simply the enumerations of all possible false and true assignments to these propositions. Therefore, propositional logic is decidable, although, already NP-hard. First-Order Predicate Logic provides a richer means to define such propositions by providing terms such as c, f c, X ,.

Terms can make use of variables that can be existentially or all quantified i. First-order predicate logic is still semi-decidable. An important feature of first-order logic is the distinction between terms and predicates, that is, one is not allowed to apply predicates or terms to predicates. Second-Order Predicate Logic [96] and comparable languages drop this limitation cf. Here, one can apply predicates to other predicates or entire formulae and interpret variables as sets rather than as individuals of a domain of interpretation.

Unfortunately, for these languages, already unification, that is, the question of whether two terms can be substituted, is semi-decidable, which means that there is not even an approach for implementing inference in these languages. The question of how far one can make progress in simulating second-order features syntactically statements over state- ments or classes that can be instances of other classes in a semantic first-order framework has been explored in F-Logic cf.

In layman terms, propositional logic is reasoning about individuals. It is decidable but the effort grows exponentially with the number of individuals. First-order logic is rea- soning over sets of individuals each predicate is interpreted as a set , which is complete but does not guarantee a terminating decision procedure.

Second-order logic is concerned with reasoning about sets that have elements which may again be sets. The focus of computational logic is on identifying subsets of logic that can be handled by computers. Unfortunately, what one gets here is not necessarily what one would need. Most approaches in automatic theorem proving and software verification use variants of first-order logic to reason cf.

Here, based on the transformation of the general clause form, resolution and unification cf. Obviously, for this level of expressiveness, only incomplete reasoning requiring heuristic guidance can be achieved in the general case. A restriction of the pragmatic complexity can be achieved by restricting first-order logic to Horn logic and applying Selective Linear Definite resolution [99].

There are also variants that forbid or cleverly restrict the usage of function symbols creating a decidable language — propositional logic with some additional syntactical sugar. Most work on Horn logic alters the model theory of logic by not considering all models but models that are defined through certain minimality criteria this model is unique in the case where negation in the bodies of the Horn clauses is either restricted or does not exist, cf.

In layman terms, this model assumes that only facts which can be inferred are true and that all other facts are false. This is called the closed-world assumption and originates from the database area. A well-known implementation of this paradigm is Prolog cf. Interestingly enough, this paradigm extends the expressiveness of these syntactically restricted first-order languages beyond first-order logic as it becomes possible to express the transitive closure of a relationship.

Description Logics cf. Common among these languages is to restrict the formalism to unary and binary predicates concepts and properties and to restrict the usage of function symbols and logical connectors to build complex formulae. The different levels of complex- ity and the decidability of these languages follow from the precise definition of these restrictions. An obvious one is the META tag []:. In the time before the wider usage of RDF, systems such as Ontobroker cf. It is also possible to interpret the semantics of HTML documents indirectly.

Still, HTML was not designed to provide descriptions of documents beyond that of informing the browser on how to render the contents. It generalizes HTML by allowing user-defined tags. This flexibility of XML, however, reduces the possibilities for the type of semantic interpretation that was possible with the predefined tags of HTML.

Binary properties interlink terms forming a directed graph. These terms as well as the properties are described using URIs. Since a property can be a URI, it can again be used as a term interlinked to another property. That is, unlike most logical languages or databases, it is not possible to distinguish the language or schema from statements in the language or schema.

This very flexible data model is obviously suitable in the context of a free and open Web; however, it generates quite a headache for logicians who wish to layer a language on top. Specifically, it defines entities such as rdfs:class, rdfs:subclass, rdfs: subproperty, rdfs:domain, and rdfs:range, enabling one to model classes, prop- erties with domain and range restrictions, and hierarchies of classes and properties.

Mechanisms are provided to define properties to be inverse, transitive, symmetric, or functional. Frankly, OWL Lite is already quite an expressive Description Logic which makes the development of efficient implementations for large data sets quite challenging and, in practice, as difficult as implementing OWL DL. This is due to the fact that logic languages such as Descriptions Logics exclude meta statements, that is, statements over statements.

OWL Full drops these restrictions. For example, in OWL Full, a class can be treated simultaneously as a set of individuals and as an individual. Therefore, OWL Full is beyond the expressive scope of Description Logic and minimally requires a theorem prover type of inference such as first- order logic i. SKOS is a data model for knowledge organiza- tion systems that uses keywords to describe resources. OWL2 cf. This hampered the implementation of Lite reasoning based on existing semantic repository technologies and also made the layering of rules on top of the language unfeasible.

In consequence, three new sub-languages were defined. OWL2EL provides polynomial time algorithms for all the standard reasoning tasks of description logic, OWL2QL enables efficient query answering over large instance populations, and OWL2RL restricts the expressiveness with respect to extensibility toward rule languages. This is currently the route that most industrial semantic repository developers follow and will probably define together with OWL2QL the most important Semantic Web representa- tion languages from a technological point of view.

Like OWL, it does not come as a single language but as a number of sub-languages. This split is due to the fact that the W3C working group had to cover two very different paradigms which are only similar at the surface level: rules based on a declarative interpretation of logic cf.

The latter normally only have an opera- tional semantics and are used to express the dynamic aspects of processes. Production rules are in essence a kind of programming language based on a blackboard architecture and event triggers. Since these production systems are no longer called expert system shells but business rule engines suitable to implement business processes , they have gained significant commercial interest.

Creating a merger of these two different paradigms was a nontrivial task. Since RDF is a data model, it also requires a query language. Up to now formats to create metadata statements have been discussed, but not how to link these to existing Web content. Grounding or connecting metadata with documents on the Web is supported by a set of languages. A well-known microformat is hCard, which can be used for representing people, companies, organizations, and places, using vCard, a file format standard for electronic business cards.

These formats not only provide a language structure to present information but additionally provide domain-specific terminologies controlled vocabularies for this purpose. Therefore, they directly interweave structure and content. RDFa cf. In contrast to Microformats, RDFa does not predefine domain-specific terminologies. Documents are, however, only one type of data source available on the Web.

In addition to being a global repository for human-readable documents, the Web is becoming more and more a platform for applications and application integration. Within the Web of Data cf. It is a way of sub-dividing a communications system into smaller parts called layers.

A layer is a collection of conceptually similar functions that provide services to the layer above it and receives services from the layer below [94]. This model is widely used in designing network architectures on a global scale. A model starts with the physical layer and ends with the application layer that provides mechanisms such as the HTTP protocol. At the lowest level, Unicode is seen as a means to encode text, URIs to refer to resources, and XML with its namespace and schema mechanisms to provide syntactic descriptions of structured objects.

This type of layering has two major functions: preventing an. Trust Rules. Data Proof Digital signature. Logic Data Self- Ontology vocabulary desc. Of course, there is no requirement for all tools to provide this functionality; the point is that this option should be enabled [2]. For example, OWL should not define a new owl:Class statement but rather reuse the already provided rdfs:Class statement.

Unfortunately, this is not the case. This also breaks the second compatibility of [2]: " Downward compatibility. Agents fully aware of a layer should also be able to interpret and use information written at lower levels. Unfortunately, this is also not the case! Even worse, these faults in layering OWL on top of RDF properly are not due to the fact that our colleagues involved in the language were incompetent. It actually reflects a fundamental problem associated with layering logic on top of the RDF.

Obviously, this creates conflict and only experience can show how this fundamental problem can be resolved in a pragmatic manner that best fits practical needs. Note that statements over statements and, e. A radical outcome could be that logic is not well suited for the Semantic Web, however; what else could play this role? Another issue of layering is internal to OWL. Here, a central design concern of OIL Light cf. Meanwhile, with the less expressive sub-language profiles in OWL2, this has now been repaired, and obviously OWL Lite will be less than a footnote in the development of the Semantic Web.

Unfortunately, this layering did not capture the essence of either Description Logics or of rule languages. Both are defined as fragments of first-order logic to reduce the computational complexity of executing inference. When simply com- bining them, this feature gets lost.

As a result, one has a syntactic restriction of first-order logic without any gain in computational terms. Only when one restricts the rules to DL- safe rules is decidability restored. You may notice in this figure that proof is no longer a proper layer, that a query language is developed as an alternative to the logic stack, and finally that there is a wish for the Holy Grail, a unifying logic. It is therefore somewhat isolated from. As already mentioned earlier, most rule languages slightly alter the semantics of first- order logic by not using all possible models but a specific minimal model.

This comes along with what is called the closed-world assumption. If a fact is not evaluated to be true in this model, it is assumed to be false. This goes beyond the expressive power of first- order logic which OWL is based on. Here, simply a truth value will not be assigned to it, since it is not restricted to a specific model.

That is, it is not inferred that a fact is false from the situation where a fact is not known to be true in a specific model. This is termed the open-world assumption. As the Web is an open world, an open-world assumption sounds like a suitable proposition. However, with the same rationale, one could also argue for reasoning based on the closed-world assumption in relation to the portion of the Web one is investigating. This difference between rule and Description Logic languages is also reflected in the way they interpret integrity constraints, such as the domain and range restrictions of properties.

When the value of a property is found and it is not known that it is a member of its range, it is assumed that there must be a mistake. The violation of a constraint is indicated over the range of the property. This is how most rule languages work. It is not known that a fact holds and one therefore assumes its negation. OWL does the opposite. OWL would infer that this value must be an element of the set defining the range of the property since the integrity constraint is requesting this.

Frankly, it is hard to tell which type of reasoning is most suitable for the Web. Therefore, the designer of RDFS took a wise decision: " For example, an RDF vocabulary might describe limitations on the types of values that are appropriate for some property, or on the classes to which it makes sense to ascribe such properties. The RDF Vocabulary Description language provides a mechanism for describing this information, but does not say whether or how an application should use it.

For example, while an RDF vocabulary can assert that an author property is used to indicate resources that are instances of the class Person, it does not say whether or how an application should act in processing that range information. Different applications will use this information in different ways. For example, data checking tools might use this to help discover errors in some data set, an interactive editor might suggest appropriate values, and a reasoning application might use it to infer additional information from instance data.

RDF vocabularies can describe relationships [9]. RIF has the fundamental problem of covering rule languages based on very different paradigms incorporating either a declarative or an operational flavor. It is of no surprise that RIF is not a single language but, within its first version, provides three languages. OWL now provides at least six different dialects.

Thus in total, one has more than ten Semantic Web languages, and RIF additionally contains a framework for defining more. This language fragmentation is quite dangerous as it may significantly hamper informa- tion interoperability between Semantic Web applications and also significantly increase the effort to implement them.

As a final example, let us examine the layering of SKOS. In the end, the Semantic Web is closer to the tower of Babel than to a coherently layered network protocol stack, and Yahweh, the enemy of global communication, may succeed again []. Maybe the wisdom of the crowd or swarm intelligence may solve this issue in terms of impact.

One may also worry a little less given the fact that holy logic also has a similar problem in that rule languages syntactically restrict and semantically extend first-order logic. What a layering! For defining machine-processable metadata, a formal language for definitional purposes is required and also for linking to content available on the Web. In addition, terms are needed to actually write down metadata statements.

The simplest technique is to support keyword lists taken from a natural language. This is often called a tag. Folksonomies as used at Web 2. Users can freely define tags, and tag clouds indicate the most popular term for a subject []. In library science, controlled vocabularies are widely used.

However, it is not enough to simply control the vocabulary; one must also control its usage. There are various studies indicating that people will choose different terms to annotate a resource and that these terms may not be necessarily useful when a user is searching for the resource and is not familiar with the vocabulary. A controlled vocabulary can be based on a thesaurus such as WordNet [85] that groups nouns, verbs, adjectives, and adverbs into sets of synonyms i.

The next step is to use a taxonomy [], which is a classification schema arranged in a hierarchical structure. Simple taxonomies can be formalized in RDFS that provides hierarchies of classes and properties. When adding formal definitions to state that a certain value of a property must be fulfilled in order to classify it as an instance of a certain class, one can use language elements of OWL or RIF.

Ontologies cf. A very common definition of ontologies attributed to Gruber [25] is that an ontology is a formal, explicit specification of a shared conceptualization. There is a design trade-off as to how much of a domain should be contained in a specification: the level of granularity how fine-grained and the level of abstraction or genericity. This is most meaningful when the target domain covers IT resources such as software components. The purpose and benefit of ontologies in a Semantic Web context is that they support interoperability between the designer or producer of a resource and the software- underpinned user.

A set of formal statements hidden on a single machine does not fulfill the definition nor the purpose of an ontology. Following from this, one thus expects ontologies to have a level of coherence and completeness with respect to a certain domain. Note that one views all the metadata formats discussed earlier as ontologies which vary in the level of formalization.

Examples of widely used ontologies are Dublin Core [65] for describing resources through properties such as title, creator, subject, publisher, etc. Each of these has in part been due to the research areas from which the communities originally came from and partly related to a particular conceptualization of what a semantically enhanced Web would look like.

It is worth reflecting on these in order to appreciate the Semantic Web as a research topic. However, it is still worth exploring some of the underlying issues. Even 10 years ago, when the Semantic Web began to take off, the Web was large 7 million unique sites [78]. From the beginning of the Semantic Web as a research project, there was a view that the key problem was how to connect with the current Web as a text resource, that is, how to transform a Web of millions or billions of text documents into a well-structured and well-defined repository of semantically described assets.

Relatively quickly a number of issues emerged. Text on the Web is not the same as text found in non-Web documents e. Because of the above, most successful NLP approaches to the Semantic Web rely on no or only shallow parsing. As well as the input to the systems being different, differences in the required output also led to a stream of research. A more general issue associated with the above is the generic way in which NLP and ontology-based-reasoning components were integrated in applications.

For the most part, these components were placed as black boxes, which were pipelined together. Only recently, in projects such as LarKC [74], has significant effort been put into combining algorithms associated with the two research areas. A final issue related to the Semantic Web and NLP has been how to relate the newly produced semantic data to the original text.

For the most part, though, the research overlap between the Semantic Web and databases was minimal. This could be seen as somewhat surprising as the Web of Data is now a widely used term, but, in the early days, the emphasis was on creating knowledge structures as a platform for agents see below.

Web and database communities. RDF stores are now seen from the academic and industrial sectors, which can be deployed in settings where performance is a key issue. Commercial successes such as mentioned above have now led to a more detailed discussion with the overall goal of bringing the logic and data close together.

Including what are the correct dimensions? For example, materialization the precomputation and storage of inferred triples is an expensive process which may not contribute to desired results. Another contribution to this debate is the Billion Triple Challenge run in conjunction with the International Semantic Web Conference see below in Related Resources [60]. Finally, Orri Erling has an interesting database-centric blog on this in [76].

From the beginning, the Semantic Web was seen as a necessary platform for supporting agents which could carry out tasks on behalf of human users. Within the seminal Semantic Web paper [6], a scenario is presented at the start where a Semantic Web agent books an important medical appointment checking the online diaries of a woman, her two grown-up children, and a number of hospitals satisfying geographic and quality constraints. The motivation for creating the Semantic Web is based on the functionality provided by software agents, which rely on the combination and exchange of content from diverse sources.

The Semantic Web would allow agents to read the content of pages because the data are coded in a machine-readable representation. The underlying ontological basis for the data supports semantic interoperability by coding meaning in a way that supports semantic mediation. Given the early motivations, however, the amount of agent research based on Semantic Web technology has been relatively small. There were two main reasons for this. Firstly, more emphasis than initially envisioned was required for creating a robust, usable, and scalable data layer.

Also the majority of agent research was founded on FIPA protocols [67] rather than the stack of Web standards. It is hard to know who first had the idea of creating a language on the World Wide Web that could be used to express the domain knowledge needed to improve Web applications.

However, by or so, it was clear that the Web was going to be around for some time, and there was a burst of energy going on. This historical event is mentioned here as it is sometimes said that the Semantic Web was created to improve search. This is partly true, but it is important to note that search as known back then, pre-Google, was not the same as the current keyword search that powers so much of the modern Web today. Around this effort, a number of tools were created within the project including a semantic annotator for HTML pages and a semantic search tool.

These two early projects looked at what is now called Web ontology languages, and were driven less by the AI-inspired push for expressive languages, and more by the needs of the emerging Web — what would now be called semantic annotation or tagging. Approximately 18 months later the OntoWeb [70] network of excellence started, which was the birthplace for the Knowledge Web project [71]. In parallel with this Web representation work, W3C had begun to explore whether some sort of Web markup language could be defined to help bring data to the Web.

There was at this time a split between XML and RDF, which we do not have space here to recount but suffice to say that this added confusion to the overall story. It is also worth noting here the dialogue that began in the late s within the Knowledge Acquisition Workshop Series in Banff [72] on the relationship between knowledge acquisition, modeling, and the Web. One of the projects that came out of this discussion was IBROW3 [4], which examined how knowledge components could be reused through the Web.

To help sell the US government on funding this research area, the techniques pioneered in Ontobroker and SHOE were used to build some demos showing the potential for these new languages. In fact, in a talk Web Conference, Geneva he said: " Documents on the web describe real objects and imaginary concepts, and give particular relationships between them. For example, a document might describe a person.

The title document to a house describes a house and also the ownership relation with a person. This means that machines, as well as people operating on the web of information, can do real things. For example, a program could search for a house and negotiate transfer of ownership of the house to a new owner. The land registry guarantees that the title actually represents reality. As this work grew, it was decided that an effort was needed to bring together the key players in this emerging area.

The outcome of this was a Dagstuhl Seminar held in [62]. The workshop was quite successful and led to a dramatic increase in funding especially in Europe. Knowledge and Content Unit in Luxembourg by type and funding, color coded according to the areas of semantic annotation, modeling, search, inference, and Semantic Web Services.

The change in name relates to the conference series covering topics related to the application of semantics to mobile platforms, cloud computing, sensor networks, as well as the Web. The event usually attracts around participants and includes a research and in-use track as well as workshops and tutorials.

This con- ference traditionally includes a Semantic Web track. It often includes papers though related to the Semantic Web. A number of videos and websites exist that outline the basic notions behind the Semantic Web. Pollock Wiley Inc. Moreover, a number of commercial announcements have been made recently, which indicate that one is moving from an early adopters phase to more mainstream markets for semantic technologies.

However, of interest here is the fact that. One of the main reasons for this is that as with many commercial shifts, this was a requirement from Oracle customers, particularly in the areas of pharmaceutics, life sciences, and health care, who need to integrate large amounts of data from many different sources.

This type of data integration at scale and across many heterogeneous sources which cannot be changed is one where semantic repositories cope well. Additionally, in these areas, reasoning capabilities are useful in supporting the mining and analysis of the data. Here, the focus is on the impact of the announcement. In short, the Open Graph protocol facilitates the integration of Web resources into a Facebook social graph. It is seen in the figure that three readers have expressed that they like the story.

These preferences also allow site owners to track the demographic data of users visiting their site. In the last few months, a number of commercial companies have built sites around this feature. Also, Amazon have integrated their recommendation system to use Facebook pro- files through Open Graph.

There are two main reasons for highlighting this deployment of semantic technology. The probability is that this will in the short to medium term be a major source for semantic data. In July , Google bought Metaweb, the company which maintains Freebase. Currently, Freebase has around 12 million items including movies, books, and organizations. From a linked data viewpoint, one interesting aspect of this purchase is that Google intends to maintain Freebase as a free and open resource.

The Website included over pages describing the 32 teams, 8 groups, and the associated hundreds of footballers that took part in the event. The Web pages were dynamically aggregated using a football ontology describing concepts associated with the World Cup e. One can see the page describing the England midfielder Frank Lampard. The use of semantic technology was deemed to be successful and the website proved popular dealing with several million page requests every day throughout the World Cup.

User requests, which can be typed or spoken, are given through a dialog interface customized for smart phone screens. The currently supported tasks include booking a table at a restaurant, for a movie, or for an event, and requesting a local taxi or finding local businesses. In addition to the sophisticated dialog system, domain and task models are used to support the combining of online services to fulfill the requested task.

The main benefit that Siri provides for the end user is that a simple conversation replaces the effort of combining either a sequence of Web searches or a sequence of mobile phone App interactions. It can be seen above that semantic technology is beginning to enter the mainstream. Also, by and large, it is the simpler technologies which are data-centric that have been taken up. There are a number of views that one could take on this.

One is that it should be expected that by their very nature, real-world Web applications will be dom- inated by data rather than conceptual structures. Second, even with the successes emerg- ing now, the Semantic Web is still in a preliminary phase of commercialization and it will take time to progress to Web applications, which require more complex conceptual reasoning. The acquisition of Siri runs somewhat counter to the reasoning above and indicates that there may be space for more complex forms of reasoning, as is required to deal with services and Web APIs.

Reflecting on the last decade of research into the Semantic Web, two issues seem clear. Firstly, as outlined above, at this point semantic technology is becoming mainstream and we will continue to see deployment of semantics in the commercial sector.

It is envisaged that in the near term, organizations will make significant portions of their data available on the Web using semantic technologies. Moreover, the emergence of data will grow in a way analogous to the way in which the Web grew. At the beginning of the Web, it was often asked what would motivate individuals and organizations to put resources into creating and developing websites.

Over the history of the Web, we have seen a progressive escalation in this effort. Corporations will now have entire departments dedicated to maintaining their presence on the Web. Web presence is seen as a requirement rather than a luxury, and the Google ranking of an organization can determine its success.

As a first step toward the vision outlined in the Scientific American paper [6], a semantic data presence will soon become a requirement rather than a luxury. Thus, linked data moves the effort of creating and maintaining websites and Web applications over organizational data to external parties. Secondly, the Web is changing in a number of ways.

It is expected to see a growth in platforms for Web applications based upon combinations of social networking and semantic technologies, harnessing the power of human networks and automated reasoning. A discussion is currently taking place related to which forces will dominate the way the Internet is used.

In this article, the authors saw three trends emerging. Firstly, that video and peer-to-peer network traffic are beginning to take a large proportion of Internet traffic when compared to pure Web communication. Secondly, that as predicted in several places, the number of users accessing the Internet from mobile devices will soon surpass the number who access it from PCs. A consequence of the shift to mobile devices such as the iPhone and iPad is that specialist Apps designed for a single purpose will be used more than general-purpose Web browsers.

A third trend from the commercial perspective is that the Internet will be dominated by a relatively small number of large players, such as Apple, who will act like the media empires of the third quarter of the twentieth century. These claims are not agreed by all however. One thing that can be assumed safely is that the debate will continue for some time. After a decade of research and as shown in the rest of this book, the Web is a global infrastructure that benefits significantly from the use of semantics.

Semantics supports a broad range of tasks including data sharing and data integration at scale, knowledge management, decision making, data analysis, search, and the use and management of Web applications based on Web APIs and services, as well as a variety of vertical sectors such as government, science, business, and media.

Given the success thus far, it is clear that semantic technology will also play a major role in other global network infrastructures based on, for example, mobile devices and sensor nets. Whatever form future planet-scale networks take, it has certainly been an exhilarating journey so far and we look forward to the next decade. Acknowledgments We thank Ian Horrocks and Michael Kifer from preventing mistakes in the sections of the chapter related to logic. We also thank Neil Benn for his help in the final formatting stages.

References 1. Adida, B. Accessed Aug ing Group Note Oct 6. Berners-Lee, T. Antoniou, G. Scientific American Magazine, pp. Baader, F. Bizer, C. Web Inf. Cambridge University 1—22 Press, Cambridge 8. Brachman, R. Benjamins, V. Morgan Kaufmann, Studer, R. Brickley, D. W3C world-wide web. Brin, S. ISDN Syst. Bush, V. The Atlantic Monthly, 5.

Cerf, V. Gruber, T. Accessed Aug Chen, W. Log Program 15 3 , — consumer experience on the phone. Keynote Clocksin, W. Springer, New York tomgruber. Codd, E. Addison-Wesley Halpin, H. Dean, M. Hedman, S. Horrocks, I. Feigenbaum, E. In: Proceedings of the gence: themes and case studies of knowledge Sixth International Conference on Principles of engineering. Fensel, D. Schnurr, H. Web Semant. Isaac, A. Jurafsky, D. Processing, 2nd edn. Kelly, J. Prentice Hall, Stollberg, M.

Kifer, M. Springer, 42, — Berlin , 2nd edn. Springer Lausen, H. Garcia-Molina, H. Prentice Hall, New Jersey Lloyd, J. Giarratano, J. Springer, Berlin Principles and Programming, 4th edn. PWS, Luke, S. In: Proceedings of Manning, C. Accessed University Press, Cambridge 6 Sept Manola, F. Accessed Maslow, H. Mauritius National Assembly: The constitution.

Accessed 6 Accessed 6 Sept Sept Mead, G. The Univer- Moens, M. Accessed 6 Sept rithms and Prospects in a Retrieval Context. Accessed 6 Sept Motik, B. Lutz, C. Nelson, T. In: Proceedings Accessed 6 Sept of the 20th National Conference, Association for Patel-Schneider, P. Accessed 6 Sept OWL web ontology language semantics and abtrsct syntax. Section 5. RDF-compatible Pingdom: Internet in numbers.

Accessed Jan 6 Sept Reynolds, D. Accessed 6 Sept Group Note June Robinson, A. Elsevier Science, on-building-britains-digital-future, Amsterdam Accessed 6 Sept Russell, S. Accessed 6 Sept A Modern Approach, 2nd edn. Prentice Hall, Accessed 6 Sept New Jersey Schreiber, G.

Accessed 6 Sept Hoog, R. Tomasello, M. MIT Press, Cambridge Wikipedia: Semantics. Wikipedia: Tag cloud. Wikipedia: Taxonomies. Wikipedia: Controlled vocabulary. Wikipedia: Tower of Babel. Accessed 6 Accessed 6 Sept Sept Wikipedia: Energy.

Wiktionary: Device. Wikipedia: Equipment. Accessed 6 Sept logy language reference, W3C Recommenda- Wikipedia: Idea. Idea Accessed 6 Sept Accessed 6 Sept Accessed 6 Sept Recommendation. Wikipedia: Machine. World Wide Web Consortium: The global Wikipedia: NLS computer system.

Accessed 6 Sept global. Wikipedia: OSI model. Accessed 6 Sept W3C Standard. Wikipedia: Purpose. Yeates, G. Te Ara — the encyclope- Wikipedia: Second-order logic. Maciej Janik2. Abstract: The Semantic Web extends the existing Web, adding a multitude of language standards and software components to give humans and machines direct access to data. The chapter starts with deriving the architecture of the Semantic Web as a whole from first principles, followed by a presentation of Web standards underpinning the Semantic Web that are used for data publishing, querying, and reasoning.

Further, the chapter identifies functional software components required to implement capabilities and behavior in applications that publish and consume Semantic Web content. One of the key goals of Semantic Web technologies is to provide machines with a more sapient understanding of data. Given a wider availability of quality data online, applications can leverage a common data access and integration layer for providing elaborate services to users.

The chapter derives the architecture of the Semantic Web from first principles, gives an overview of the architecture of Semantic Web applica- tions, and covers building blocks of the Semantic Web in more detail. The information required to answer these questions is available on the Web. In fact, a large amount of such information already exists in formats amenable to machine processing on the Semantic Web.

The reason that Web search engines fail at answering such questions is that they are limited to analyzing Web content — mostly documents in natural language — one page at a time, while the Semantic Web allows for combining data that are distributed across many different sources and described in a machine-interpretable manner. For example, how may one pursue answering the questions related to playlists of UK radio stations? MusicBrainz knows about band members, such as Benny Andersson, and about genre of artists and songs.

MusicBrainz aligns its information with Wikipedia, for example, to be able to include the biography of an artist, or to add facts from DBpedia [2], a version of Wikipedia in Semantic Web formats. The meaning of such relationships are explained online, too, using a set of ontologies available on the Web, such as Dublin Core, for describing general properties of information resources, SKOS for covering taxonomic descriptions, and specialized ontologies covering the music domain.

Given the available data, one may answer questions such as the frequency of certain music genres played on UK radio stations, radio stations playing Swedish composers, and many many more. However, having access to and leveraging such data does not come for free. The outlined scenario and likewise other use cases require generic software components, languages, and protocols that must interact in a seamless manner to be able to satisfy such requests.

The chapter investigates the construction of the required infrastructure at large, that is, the Semantic Web architecture, and analyzes the requirements that come from the technical need to identify and relate data, and the organizational needs to maintain the Semantic Web as a whole — even if single compo- nents shake or break. Achieving such functional capabilities requires an unprecedented growth of openly available data covering a wide range of domains and involving large amounts of people and organizations.

Such phenomenal and fast growth is a nonfunctional i. Thus, the first consideration is the architec- ture of the Web, to be able to learn from its design considerations, and to derive additional nonfunctional requirements later on. Its explosive growth is tightly associated with its underlying software architecture.

The fact that each individual system has been coupled only very loosely with the other one and that document creation, document delivery, and document browsing could happen in isolation in each of the many individual nodes was of key importance for enabling the fast adoption of the early Web.

The lesson to be learned is that a state-of-the-art system that produces higher quality output e. Furthermore, a distributed system without the need for a central coordinator is inherently robust. While there are many potential problems that may affect individual nodes in the World Wide Web, the only problem leading to brittleness in the World Wide Web as a whole is the hierarchical control of the IP addresses and the Domain Name System of the Internet.

Many requirements were derived from the design decisions that worked well for the World Wide Web and led to its phenomenal growth, but which had yet to be realized for data and knowledge systems. In fact, traditional knowledge systems have already exhibited some of the functional requirements sought from the Semantic Web. However, traditional knowledge systems exhibited a lack of flexibility, robustness, and scalability.

To quite some extent the problem had been a lack of maturity in the face of algorithmic methods with high computational complexity. For instance, description logics systems, which are now the backbone of Web Ontologies, were severely limited in scale, typically capable of handling not more than a few hundred concepts in the mids cf.

Such problems have been assuaged using much increased computational power and better understood and optimized algorithms. However, several bottlenecks remain, which are akin to the problems that the architecture solved for the domain of hypertext documents.

Remaining barriers for managing data and semantics revolve around issues concerning the large number of data sources with varying 1 underlying technologies, 2 geographically dispersed locations, 3 authorities, 4 service quality, and 5 adop- tion rate. These are exactly the dimensions that had and have to be considered for the design of the World Wide Web.

Thus, in analogy to the World Wide Web, the Semantic Web requires a computing mega system with the following five characteristics: 1. Explicit, Simple Data Representation: A common data representation should hide the underlying technologies and only capture the gist of the underlying data representa- tions. Here, the analogy may be drawn with HTML documents that have served as simple, yet effective representations of what constitutes a document.

Distributed System: The system should be fully distributed, comprising of data sources without a centralized instance that controls who owns what type of information. Distrib- uted ownership and control, if done properly, facilitates adoption and scalability, which is in analogy to websites and Web pages that are under full control of their producers.

Cross-referencing: In order to benefit from the network beyond the mere sum of its parts, the data must be cross-linked, allowing for reuse of existing data and existing data definitions from different authorities, analogous to hyperlinks allowing for the reuse of text in the hypertext space. Loose Coupling with Common Language Layers: In a mega system, the components have to be only loosely coupled.

The loose coupling is achieved by communicating in standardized languages. The standardized languages must come with great flexibility such that they may be customized for specific systems, but the overall communication must not be jeopardized by such specialization. The requirement should be seen in analogy to the coupling between different Web clients and servers, where dependency is reduced to understanding HTTP as transport protocol and producing and interpreting HTML content.

Ease of Publishing and Consumption: The mega system should allow for easy publishing and consumption of simple data and for comprehensive publishing and consumption of complex data. The requirement is in analogy to the Web page description language HTML that provides a simple means of conveying textual information, but that can be viewed, managed, and composed using elaborate browsers and powerful content man- agement systems. Given these requirements, two points of view for a Semantic Web architecture emerge.

One viewpoint is focused on the Semantic Web languages and protocols and is mentioned several times in the above list. Another viewpoint concentrates on the functionalities to be contributed by Semantic Web components. Requirements for a Semantic Web Language Architecture. At high level of abstraction, Semantic Web languages must address the listed requirements.

Below, mandatory objec- tives are presented, accompanied by examples and, in parenthesis, the requirement they refer to. Second, such a data model must be serializable in a standardized manner such that data become easily exchangeable between different computing nodes 1, 2, 4. Wikipedia or DBpedia cannot be easily joined. A merge of such datasets may lead into forming interesting connections between playlists, music groups, artists, and their origin that span across datasets.

While combining data is possible in conventional systems, such as relational databases, the emphasis on the Semantic Web is on the ease of joining such separate pieces of information. Third, individual entities must be referable in such a data model across borders of ownership or computing systems, thus allowing also for the cross-linking of data 1, 2, 3, 4. Fourth, the data model should have an expressive, machine-understandable data description language.

In a global data space, having an expressive data description language is of major concern because users and developers can no longer manually inspect and make use of data descriptions due to the sheer size and heterogeneity of data on the Web 1, 5. Furthermore, such a data description language also allows for a refinement of the basic data model, providing levels of specialization needed in the application domains 4. For instance, the richness of BBC program descriptions is hard to understand given long chains of data leading from radio stations, over shows, versions of shows, to the songs which are connected to artists.

Fifth, such a data model requires a query and manipulation language allowing for selections of data or aggregations of data, such as the number of Swedish composers being broadcasted on specific programs 5. Sixth, reasoning is desirable to facilitate querying, as it provides shortcuts for complex data situations, for example, turning the chain of relationships between a program and a song into a direct relationship using inference rules 5.

Seventh, the transport of data and the transport of queries and results need commonly agreed-upon protocols. While many protocol details are still under discussion, the usage of HTTP is agreed and even refined, for example, for the transport of queries.

Eighth, such a transport requirement may also include encrypted data requests and data transport. Security of data transmission is typically addressed by encrypting the data transmission channel. Beyond the increased security of transport, further security functionality is required, for example, for signing data items. Such features call for a completely distrib- uted authentication system to establish the authenticity of a user request and control access to resources.

All require- ments for Semantic Web languages imply corresponding requirements on functionality to be delivered by software components. However, some software components are not standardized and should not be , but should be customizable to every individual user needs — up to a point where the community may recognize new chores to be carried out in the stack of software components that should be moved out into a joint language or joint computational model or structure.

Core requirements that are not yet included in the language architecture comprise the following. First, versatile means for user interaction.

72 HOLE GROUP BETTING EXPLAINED MEANING

Professor Jose Zubizarreta, Harvard University. Chunaram Choudhary University of Copenhagen. Wednesday 10 April , - Tuesday 09 April , - Thomas Jaki, Lancaster University. Monday 08 April , - Friday 05 April , - Professor Michael Duszenko. Thursday 04 April , - Wednesday 03 April , - Friday 29 March , - Thursday 28 March , - Wednesday 27 March , - Tuesday 26 March , - Professor Francesca D.

Monday 25 March , - Len Seymor, Oxford University. Friday 22 March , - Thursday 21 March , - Wednesday 20 March , - Monday 18 March , - Friday 15 March , - Thursday 14 March , - Mary-Claire King, human geneticist professor, University of Washington. Lecture Cancelled. Cambridge University Biological Society. Wednesday 13 March , - Professor Mike Cates.

Tuesday 12 March , - Dr Yaser Hashem. Monday 11 March , - Friday 08 March , - Thursday 07 March , - Wednesday 06 March , - Dr Ingo Ringshausen, Department of Haematology. Dr Anne Corcoran. Tuesday 05 March , - Dr Rachel Simmonds. Professor Alison Murdoch. Friday 01 March , - Thursday 28 February , - Dr Julie Aspden. Chris Boutell, University of Glasgow. Professor Jonathan Hill.

Wednesday 27 February , - Clifford Albutt Lecture theatre, Clinical School. Professor Danny Dorling. Tuesday 26 February , - Graeme King — Vrije Universiteit Amsterdam. Dr Konstantina Pallas, Microsoft. Professor Julian Hibberd. Friday 22 February , - Prof Steven Julious, University of Sheffield. Thursday 21 February , - Dr Elena M. Ribe, Department of Psychiatry, University of Oxford. Wednesday 20 February , - Dr Luke Kemp. Tuesday 19 February , - Professor Lynne Regan.

Monday 18 February , - Friday 15 February , - Dr James Hudson. Alfredo Castello, University of Oxford. Thursday 14 February , - Wednesday 13 February , - Dr Daniel Hodson, Department of Haematology. Professor Ann Copestake. Tuesday 12 February , - Professor Florian Heyd. Friday 08 February , - Isaia Barbieri, Dept. James Lee, University of Cambridge. Louisa Bellis University of Cambridge. Thursday 07 February , - Wednesday 06 February , - Colin Walters.

Tuesday 05 February , - Dr Nicholas Stroustrup. Priyanka Jamwal. Monday 04 February , - Naomi Moris, Dept. Friday 01 February , - Thursday 31 January , - Rachel Edgar, Imperial College London. Professor Naomi Lamoreaux - Stanley B.

Wednesday 30 January , - Professor Sheila Rowan. Tuesday 29 January , - Dr Kok-Iung Chan. Monday 28 January , - Sarah Caddy, LMB. Friday 25 January , - Dr Francisco Lobo, Belo Horizonte. Thursday 24 January , - Dr Melanie Stefan. Wednesday 23 January , - Dr Oliver Dukes, Ghent University. Tuesday 22 January , - Professor Gabriel Waksman. John Marioni, EBI. Friday 18 January , - Professor Agnieszka Chacinska.

Thursday 17 January , - Wednesday 16 January , - Dr Ben Collins. Tuesday 15 January , - Friday 11 January , - Thursday 03 January , - Monday 17 December , - Dr John M. Wednesday 12 December , - Tuesday 11 December , - Dr Natalia Riobo-Del Gardo. Mark Cronan, Duke University. Friday 07 December , - Thursday 06 December , - David Rueda - Imperial College London.

Tuesday 04 December , - Dr Maryse Lebrun. Speakers to be confirmed. Monday 03 December , - Martin Beck. Neil Henderson, University of Edinburgh. Friday 30 November , - Eric Gouaux. Thursday 29 November , - Dr Peter Kimani, University of Warwick. Jonathan Ball, University of Nottingham. Wednesday 28 November , - Antonio Torroni, University of Pavia. Professor Stephen Tait, University of Glasgow. Axel Behrens. Tuesday 27 November , - Monday 26 November , - Professor Adrian R Krainer.

Saturday 24 November , - Friday 23 November , - Judith Allen, University of Manchester. Thursday 22 November , - Wednesday 21 November , - Professor Walter Reith, University of Geneva. David Baulcombe. Tuesday 20 November , - Prof Wojcieh Bal. Carrie Partch. Monday 19 November , - Friday 16 November , - Thursday 15 November , - Sarah Teichmann. Dr Ruth Morgan, University of Edinburgh. Wednesday 14 November , - Tuesday 13 November , - Dr Hayley Sharpe.

Paola Scaffidi; Bas van Steensel. Monday 12 November , - You must email Anna. Toporska cruk. Friday 09 November , - Dr Simon Rogers, University of Glasgow. Thursday 08 November , - Jonathan Heeney, University of Cambridge. Wednesday 07 November , - Professor Wayne Potts, University of Utah.

Professor Daniela Bortoletto. Tuesday 06 November , - Dr Lionel Mourey. Aubrey de Grey. Saturday 03 November , - Friday 02 November , - Peng Li, Tsinghua University. Max Gutierrez. Thursday 01 November , - Wednesday 31 October , - Tuesday 30 October , - Professor Jernej Ule. Monday 29 October , - Dr Joshua Ramsay, Curtin University. Friday 26 October , - Berna Sozen, Dept. Joachim Schultze, University of Bonn. Thursday 25 October , - Wednesday 24 October , - Dr Andreas Schlitzer,University of Bonn.

Gero Miesenboeck. Dr Emmanuel Derivery. Tuesday 23 October , - Monday 22 October , - Friday 19 October , - Wayne Potts, University of Utah. Thursday 18 October , - Caroline Tapparel, University of Geneva, Switzerland. Wednesday 17 October , - Alpha Lee. Tuesday 16 October , - Professor Simon Newstead, University of Oxford. Professor Monika Fuxreiter. Monday 15 October , - Raphael Margueron; Caroline Dean. Dr Lew Cantley. Gavin Screaton, University of Oxford,. Friday 12 October , - Thursday 11 October , - Wednesday 10 October , - Andrea Crisanti.

Tuesday 09 October , - Monday 08 October , - Friday 05 October , - Thursday 04 October , - Wednesday 03 October , - Manuela Zucknick, University of Oslo. Tuesday 02 October , - Roser Vento-Tormo, Sanger Institute. Friday 28 September , - This talk will be rescheduled in Apologies for any incovenience this has caused. Thursday 27 September , - Wednesday 26 September , - Tuesday 25 September , - Refreshments after. Please contact Sophie Palmer sap71 medschl.

Monday 24 September , - Musa Mhlanga, University of Cape Town. Friday 21 September , - Jordan Raff. Thursday 20 September , - Rozbeh Baradaran, Sloan Kettering Institute. Tuesday 18 September , - Seminar room 3. Monday 17 September , - Thursday 13 September , - Wednesday 12 September , - Monday 10 September , - Ferric Fang, University of Washington.

Professor Soren Brunak from University of Copenhagen. Glenn King University of Queensland, Australia. Monday 03 September , - Wednesday 01 August , - Professor Rita Horvath, Newcastle University. Friday 27 July , - Dr Matthew Murray, Department of Pathology. Thursday 26 July , - Dr Tobias Janowitz, Department of Oncology. Thursday 19 July , - Wednesday 18 July , - Magnus Rattray, University of Manchester. Tuesday 17 July , - Thomas Schulz, Medizinische Hochschule Hannover.

Friday 13 July , - Thursday 12 July , - Tuesday 10 July , - Friday 06 July , - Ravindra Gupta, UCL. Thursday 05 July , - These talks are aimed at first year PhD students but all are welcome to attend. Wednesday 04 July , - Monday 02 July , - Friday 29 June , - Steve Harrison. Thursday 28 June , - David Sabatini, Whitehead Institute.

Tuesday 26 June , - Adrian Liston, Univ. Friday 22 June , - Kasturi Haldar, University of Notre Dame. Tamara Tilburgs, Harvard University. Thursday 21 June , - Dr Suzanne Turner, Department of Pathology. Wednesday 20 June , - Dr Laura Spagnolo University of Glasgow. Tuesday 19 June , - Amit Singhal, A. Star Singapore. Friday 15 June , - Professor Andrew Dowsey, University of Bristol.

Thursday 14 June , - Michael Malim, King's College London. Wednesday 13 June , - Friday 08 June , - Dr Laurent Gatto, University of Cambridge. Thursday 07 June , - Wednesday 06 June , - Tuesday 05 June , - Monday 04 June , - Friday 01 June , - Andreas Lundqvist, Karolinska Institute.

Thursday 31 May , - Professor Shana Kelly, University of Toronto. Wednesday 30 May , - Dr Martin Davey, University of Birmingham. Michael Hall. Tuesday 29 May , - Friday 25 May , - Victor Tybulewicz, Francis Crick Institute. Thursday 24 May , - Wednesday 23 May , - Cambridge Cell Biology Seminar Series.

Joel Swanson, University of Michigan. Dr Virginia Pedicord, Sanger Institute. Titia De Lange Rockefeller. Refreshments provided. Maxwell Centre, Cavendish Laboratory. Monday 21 May , - Friday 18 May , - Ziad Mallat, University of Cambridge. Thursday 17 May , - Robert Mahen - Imperial College, London. Wednesday 16 May , - Dr Paul Brear Hyvonen Group. Dr Abderrahmane Kaidi, University of Bristol. Tuesday 15 May , - Friday 11 May , - Martin Turner, Babraham Institute. Dr Guido Sanguinetti, University of Edinburgh.

Thursday 10 May , - Nicole Zitzmann, University of Oxford. Wednesday 09 May , - Dr Joanna Andrecka Lumicks. Friday 04 May , - Harry Sokol, Paris, France. Thursday 03 May , - Dr Andy Pierce, AstraZeneca. Wednesday 02 May , - Professor Chris Dobson. Monday 30 April , - Friday 27 April , - Jacques Dubochet. Thursday 26 April , - Wednesday 25 April , - Dr Pablo Martinez-Lozano Sinues. Tuesday 24 April , - Thursday 19 April , - Dr Vicki Gold.

Wednesday 18 April , - Tuesday 17 April , - Monday 16 April , - Thursday 12 April , - Liz Ryan, University of Warwick. Thursday 05 April , - Thursday 29 March , - Dr Luay Joudeh Pellegrini Group. Biochemistry Seminar Room, Sanger Building. Wednesday 28 March , - Tuesday 27 March , - Dietmar Zaiss, University of Edinburgh. Friday 23 March , - Wednesday 21 March , - Dr Pedro Torres. Tuesday 20 March , - Monday 19 March , - Matthew Hepworth, University of Manchester.

Friday 16 March , - Anita Ramanan, Microsoft. Thursday 15 March , - Lukas Kapitein. Stephen Polyak, University of Washington. Dr Paul Smith, AstraZeneca. Professor David Pritchard, University of Nottingham. Wednesday 14 March , - Tuesday 13 March , - Stephen Cusack.

Monday 12 March , - Friday 09 March , - Thursday 08 March , - Dr Francesco Aprile. Ellen Rothenberg, CalTech. Wednesday 07 March , - David Christianson. Tuesday 06 March , - Monday 05 March , - Karam Teixeira, Dept. Friday 02 March , - Thursday 01 March , - Wednesday 28 February , - Tuesday 27 February , - Monday 26 February , - Professor W.

Friday 23 February , - Thursday 22 February , - Wednesday 21 February , - Professor Jonathan Clayden, University of Bristol. Tuesday 20 February , - Ben Calderhead, Imperial College London. Steve Kelly. Friday 16 February , - Rupert Beale, University of Cambridge. Professor John Walker. Thursday 15 February , - Wednesday 14 February , - Professor Jon Slate, University of Sheffield. Tuesday 13 February , - Ulrich Schwarz-Linek.

Friday 09 February , - Thursday 08 February , - Wednesday 07 February , - Professor Andrew Sewell, Cardiff University. Tuesday 06 February , - John Briggs. Carla F. Dr Neda Farahi, Baraa Kwieder. Monday 05 February , - Professor Lawrence Hunter. Saturday 03 February , - Friday 02 February , - Thursday 01 February , - Professor George Lomonossoff. Professor Andreas Wagner, Dept.

Peter Stockley, University of Leeds. Wednesday 31 January , - Dr Omer Dushek, University of Oxford. Jerrard Hayes. Tuesday 30 January , - Rahul Roychoudhuri, Babraham Institute. Friday 26 January , - Professor Russell Foster. Thursday 25 January , - Wednesday 24 January , - Islam Department of Biochemistry, University of Cambridge.

Tuesday 23 January , - Matt Higgins. Richard Kitching, Monash University. Dr Merlin Wilcox. Monday 22 January , - Friday 19 January , - Thursday 18 January , - Dr Phil Spence, University of Edinburgh. Wednesday 17 January , - Yanlan Mao. Tuesday 16 January , - Jesper V. Dr Ana-Maria Lennon-Dumenil. Xiaowei Zhuang. Monday 15 January , - Thursday 14 December , - Wednesday 13 December , - Professor Martin Ott, Stockholm University.

Tuesday 12 December , - Monday 11 December , - Friday 08 December , - Dr Nicola McCarthy. Tuesday 05 December , - Please contact Kamila at least 24 hours prior the talk. Thank you. Monday 04 December , - Christine Holt. Brian Ferguson, University of Cambridge. Friday 01 December , - Professor Christina Smolke. Thursday 30 November , - Wednesday 29 November , - Professor Roland Nilsson, Karolinska Institute.

Professor Dame Sally Davies. Tuesday 28 November , - Franck Perez. Sjors Sheres. Professor Nick Lane. Monday 27 November , - Friday 24 November , - Graham Pawelec, University Of Tuebingen. Sir Mark Walport. Thursday 23 November , - Dr Darren Naish. Fisher Buidling, St John's College. Wednesday 22 November , - Dr David Vermijlen, Universite libre de Bruxelles. Dr Ben Taylor, University of Lancaster. Tuesday 21 November , - Nathalie Juge. Monday 20 November , - Friday 17 November , - Dr Julija Krupic.

Lightfoot Room - St John's College. Thursday 16 November , - Wednesday 15 November , - Professor Grahame Hardie, University of Dundee. Professor Graham Anderson, Universitiy of Birmingham. Professor Llyod Peck. Tuesday 14 November , - Kristijan Ramadan. Matthew Shoulders - MIT. Monday 13 November , - Dr Nancy R. Friday 10 November , - Thursday 09 November , - Ian Goodfellow, University of Cambridge. Wednesday 08 November , - Professor Sir Nigel Shadbolt.

Tuesday 07 November , - Mike Olsen. Monday 06 November , - Friday 03 November , - Ervin Fodor, University of Oxford. John McCutcheon. Thursday 02 November , - Wednesday 01 November , - Professor Malcolm Longair. Tuesday 31 October , - Peter Becker. Caitlin Black and Derek Murphy. Castlereagh room - St John's College. Contents Search. Resource Description Framework. Reference work entry First Online: 07 December How to cite.

Synonyms RDF. This is a preview of subscription content, log in to check access. RDF 1. W3C recommendation. Schreiber G, Raimond Y. Berners-Lee T. Semantic web road map. Heath T, Bizer. Linked data: evolving the web into a global data space.

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