The Patient Is In: August 2006

Implication of Glutamate in the Kinetics of Insulin Secretion in Rat and Mouse Perfused Pancreas -- Maechler et al. 51 (Supplement 1): 99 -- Diabetes

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Diabetes 51:S99-S102, 2002
© 2002 by the American Diabetes Association, Inc.

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Section 2: Biphasic Insulin Release: Pools and Signal Modulation

Implication of Glutamate in the Kinetics of Insulin Secretion in Rat and Mouse Perfused Pancreas
Pierre Maechler, Asllan Gjinovci, and Claes B. Wollheim
From the Division of Clinical Biochemistry, Department of Internal Medicine, University Medical Center, Geneva, Switzerland

ABSTRACT
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

It is intriguing that the kinetics of glucose-stimulated insulin secretion from the in situ perfused pancreas differ between the rat and the mouse. Here we confirm that insulin release in the rat is clearly biphasic, whereas in the mouse glucose essentially elicits a transient monophasic insulin release. Glucose-derived glutamate has been suggested to participate in the full development of the secretory response. The present report shows that the expression of glutamate dehydrogenase is lower in mouse than in rat or human islets, paralleling the insulin secretion profile. Addition of glutamic acid dimethyl ester mainly enhances insulin release at an intermediate glucose concentration in the rat pancreas. In the mouse preparation, glutamic acid dimethyl ester induces a sustained secretory response, both at 7.0 and 16.7 mmol/l glucose. These results are compatible with a role for glucose-derived glutamate principally in the sustained phase of nutrient-stimulated insulin secretion.

INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

The kinetics of insulin secretion from the perfused pancreas stimulated by glucose vary according to the animal model. This is particularly evident regarding the two most widely used species, i.e., the rat and the mouse (1,2). In rats, glucose stimulation results in biphasic insulin release, with a transient first phase followed, after 4–5 min, by a gradually increasing second phase (3). In contrast, the perfused mouse pancreas exhibits a weak second phase compared with the first phase in response to glucose stimulation (1,2). Only a few studies have addressed the mechanisms underlying these species differences. Among others, it has been proposed that the divergence may reside in the cellular levels of cyclic adenosine monophosphate (cAMP) (4) or inositol phosphate (5).

In the consensus model of glucose-stimulated insulin secretion, ATP is generated by mitochondrial metabolism, promoting an increase in cytosolic Ca2+ concentration, which constitutes the main trigger initiating insulin exocytosis (6–8). Glucose generates additional factors participating in the stimulation of insulin secretion (8–11). We have previously proposed that, during glucose stimulation, glutamate is generated by the mitochondria and plays a role in stimulus-secretion coupling (12,13). Under conditions of permissive, clamped cytosolic Ca2+ levels in permeabilized cells, glutamate directly stimulates insulin exocytosis independently of mitochondrial function, suggesting that glutamate acts as an intracellular factor coupling glucose metabolism to insulin secretion (12). Glutamate can be formed in the mitochondria from the tricarboxylic acid cycle intermediate -ketoglutarate by glutamate dehydrogenase (GDH) (14). As a glucose-derived metabolic coupling factor, glutamate is postulated to participate mainly in the second phase of insulin secretion.

Glutamate does not penetrate efficiently into islet cells and is not insulinotropic (15), although induction of transient insulin release has been reported (16). Investigators have therefore used cell-permeant methyl ester derivatives. An insulinotropic action of glutamic acid dimethyl ester in the presence of intermediate glucose concentrations has been reported in the perfused rat pancreas (17). In the present study, we have examined the hypothesis that intracellular glutamate provision might be rate-limiting for full development of the second phase of insulin secretion. Deficient second phases are observed in the rat at intermediate glucose concentrations or in mice even at optimal glucose concentrations. Our results show that, in these incomplete secretory responses, glutamic acid dimethyl ester supplementation induces the development of a full, sustained phase of insulin secretion.

RESEARCH DESIGN AND METHODS
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

Insulin secretion.
Male Wistar rats and BALB/c mice were anesthetized with sodium pentothal 100 mg/kg body wt i.p. and prepared for pancreas perfusion as previously described (18). The pancreas was perfused at 37°C with modified Krebs-Ringer HEPES buffer supplemented with the indicated concentrations of glucose. The perfusion was maintained at 5 ml/min for rats and 1.5 ml/min for mice. The pancreatic effluent of the first 30 min of perfusion with basal glucose (2.8 mmol/l) was not collected. After this equilibration period, the effluent was collected in 1-min fractions from a catheter placed in the portal vein. The insulin content of each fraction was determined by radioimmunoassay (12). Where mentioned, the area under the curve (AUC) was calculated after subtraction of basal release determined by the first 15 min of fraction collection. Differences in insulin secretion between groups were analyzed by Student’s t test.

Immunoblotting.
Pancreatic islets were obtained from a human donor (12) or isolated from rats and mice by collagenase digestion as previously described (19). They were centrifuged, resuspended in lysis buffer, and sonicated before protein determination (Bradford’s assay). Immunoblotting was performed after SDS-PAGE using 5 µg proteins of islet extract per lane or standard of GDH (Roche Diagnostics, Rotkreuz, Switzerland) on 11% gel. Proteins were transferred onto nitrocellulose membrane and incubated overnight at 4°C in the presence of rabbit anti-GDH polyclonal antibody (1:5,000) raised against bovine GDH (Rockland, Gilbertsville, PA). The membrane was then incubated for 1 h at room temperature with donkey anti–rabbit IgG antibody (1:5,000) conjugated to horseradish peroxidase (ECL; Amersham, Zürich, Switzerland), and the GDH protein was revealed by chemiluminescence (Pierce, Rockford, IL).

RESULTS
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

Control in situ pancreatic perfusions.
Control experiments show the typical species-specific patterns of the dynamics of insulin secretion in the perfused pancreas stimulated with glucose (Fig. 1). In the rat, raising glucose from basal 2.8 to 16.7 mmol/l glucose induced a transient first phase followed by a sustained second phase with similar amplitudes (Fig. 1A). In the mouse, the same high glucose concentration (16.7 mmol/l) elicited a rapid first phase but only a very weak second phase (Fig. 1 B). At 7.0 mmol/l glucose, the amplitudes of insulin release were smaller but the species difference was also observed, i.e., absence of the second phase in the mouse.

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FIG. 1. A and B: Control in situ pancreatic perfusions. The pancreas was perfused at 5 ml/min for rat (A) and 1.5 ml/min for mouse (B). After a 30-min equilibration period at basal 2.8 mmol/l glucose, the effluent was collected in 1-min fractions from a catheter placed in the portal vein. The pancreas was perfused sequentially at different glucose concentrations, first at 2.8 mmol/l for 45 min, next at 7.0 mmol/l for 30 min, then again at 2.8 mmol/l for 15 min followed by a 30-min stimulation at 16.7 mmol/l, and finally at 2.8 mmol/l for 15 min. C: Immunoblotting for GDH. Islets from rats, mice, and a human donor were isolated and immunoblotting was performed after SDS-PAGE using 5 µg proteins of islet extract per lane or standard of GDH. The data presented in panels A–C are representative of three independent experiments each.

GDH levels in pancreatic islets.
Islets from rats, mice, and a human donor were isolated, and the equivalent of 5 µg protein was subjected to immunoblotting for quantification of GDH. Human and rat samples exhibited similar levels of GDH, whereas the signal from the mouse was noticeably weaker (Fig. (Fig. 1 C). Compared with the standards of GDH, the band from rat islet extracts was similar to the standard of 10 ng GDH. The intensity of the mouse band was situated between the standards 10 ng and 1 ng, the latter being undetectable. GDH concentration in rat islets could be estimated roughly at 0.2% of total proteins. This concentration is only indicative, since the reactivity of the antibody raised against bovine GDH may vary slightly between species, although this mitochondrial enzyme is extremely well conserved.
Effect of glutamic acid dimethyl ester on insulin secretion.
Rat pancreatic perfusion was performed at the rate of 5 ml/min and resulted in a basal insulin release of 0.54 ± 0.34 ng/ml per minute at 2.8 mmol/l glucose. Addition of 5 mmol/l L-glutamic acid dimethyl ester (dmGlut) at low glucose (2.8 mmol/l) for 15 min induced only marginal, slow-onset insulin secretion over basal release (Fig. 2). Stimulation with 7.0 mmol/l glucose for 15 min resulted in biphasic insulin secretion with an AUC of 219.2 ± 76.6 ng/ml, and supplementation with 5 mmol/l dmGlut for the next 15 min induced a 3.6-fold increase in the AUC (786.2 ± 201.2 ng/ml, P < 0.05). After a 15-min period at low glucose (2.8 mmol/l), 16.7 mmol/l glucose stimulated insulin secretion, with a pronounced first and second phase (AUC = 1,194 ± 176 ng/ml for 15 min, 5.5-fold vs. 7.0 mmol/l glucose, P < 0.05). Application of 5 mmol/l dmGlut on top of high glucose for the subsequent 15 min resulted in a further modest 1.6-fold elevation of insulin release (AUC = 1,971 ± 218 ng/ml for 15 min, P < 0.01).

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FIG. 2. Rat pancreatic perfusion. The pancreata from male Wistar rats were perfused at 5 ml/min, first for a 30-min equilibration period at basal 2.8 mmol/l glucose. The effluent was then collected in 1-min fractions from a catheter placed in the portal vein. The pancreas was perfused sequentially at different glucose concentrations without or with 5.0 mmol/l dmGlut. Each condition or combination was applied for 15 min. Values are means ± SE of three independent experiments.

In the mouse, pancreatic perfusion of 5 mmol/l dmGlut at 2.8 mmol/l glucose did not modify basal insulin release (Fig.3). In the presence of 7.0 mmol/l glucose, there was a transient, first phase–like stimulation of insulin secretion (AUC = 8.4 ± 4.0 ng/ml for 15 min), without establishment of a second phase. Addition of dmGlut (5 mmol/l) in the continuous presence of 7.0 mmol/l glucose induced biphasic, sustained insulin release (AUC = 2.5-fold compared with 7.0 mmol/l glucose alone, P < 0.05). Stimulation with 16.7 mmol/l glucose resulted in a similar pattern of insulin secretion both in the absence and the presence of dmGlut.

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FIG. 3. Mouse pancreatic perfusion. The pancreata from male BALB/c mice were perfused at 1.5 ml/min, first for a 30-min equilibration period at basal 2.8mmol/l glucose. The effluent was then collected in 1-min fractions from a catheter placed in the portal vein. The pancreas was perfused sequentially at different glucose concentrations without or with 5.0 mmol/l dmGlut. Each condition or combination was applied for 15 min. Values are means ± SE of three independent experiments.

DISCUSSION
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

The kinetics of insulin secretion from the in situ perfused pancreas were studied in rats and mice. Our control experiments confirmed the species difference in insulin release, with typical transient first and sustained second phases in rats compared with a transient first phase followed by only a very weak second phase in mice (1,2). Biphasic insulin secretion in response to stimulatory glucose is also observed in humans (20), rendering the mouse questionable as a relevant model. However, the lack of a sustained second phase in mice provides a useful tool for the dissection of mechanisms involved in the establishment of prolonged and robust insulin release. This might also be useful in the search for new treatments of impaired insulin secretion.
Studying the species difference, it has been proposed that a larger production of cAMP in rat ß-cells may account for the pronounced second phase of insulin secretion compared with mice (4). Zawalich et al. (5) have shown that the increase in inositol phosphates upon glucose stimulation was much more marked in rat compared with mouse islets, correlating with phospholipase C expression. Differences between rat and mouse pancreatic islets were also reported regarding membrane potential oscillations and changes in cytosolic Ca2+ concentration in response to glucose (21).

In the present report, we have shown that the expression of GDH is lower in islets isolated from mice compared with those of rats or humans. This mitochondrial enzyme can generate glutamate from the tricarboxylic acid cycle intermediate -ketoglutarate (14). In conditions of permissive cytosolic Ca2+ concentrations, glutamate stimulated insulin exocytosis in permeabilized insulinoma cells (12). This led to the proposal that glutamate plays a role as an intracellular factor in the ß-cell (22). Glucose-derived glutamate might participate in the potentiation of insulin secretion rather than its initiation caused by a rise in cytosolic Ca2+. In the perfused rat pancreas, in the absence of glucose, non-nutrient stimulation of insulin secretion by a sulfonylurea was defective, but it was restored by the addition of dmGlut (17). It was further proposed that dmGlut might bypass glucose metabolism to enhance the insulinotropic action of sulfonylureas (23).

We have shown here that the incomplete second phase of insulin secretion observed in the perfused rat pancreas at intermediate glucose concentration was overcome by dmGlut supplementation. In mice, insulin secretion upon glucose stimulation was essentially transient, with a very weak second phase even at optimal glucose concentrations. Addition of dmGlut caused a biphasic release pattern at permissive glucose concentrations but had no effect at basal glucose. The reason for the biphasic response induced by dmGlut in the mouse, contrasting with the monophasic profile in the rat, is unclear. It could be speculated that the readily releasable pool of insulin granules accumulates and is larger in the mouse than in the rat because of the marked difference in the glucose-induced insulin secretion rate.

The present results are in accordance with a role for glutamate as a metabolic coupling factor potentiating rather than initiating insulin secretion. Conflicting data about the glutamate levels in insulin-secreting cells stimulated by glucose exist in the literature (22). Therefore, future work should attempt to clarify the role of intracellular glutamate in the rat and mouse ß-cell.

ACKNOWLEDGMENTS

The authors thank C. Bartley and G. Chaffard for their skilled technical assistance and Drs. P. Morel and J. Oberholzer (Department of Surgery, University Hospital of Geneva) for providing human islets. This study was supported by the Paul Langerhans Research Fellowship from the European Association for the Study of Diabetes (to P.M.) and the Swiss National Science Foundation (grant no. 32-49755.96 to C.B.W.).

FOOTNOTES

Address correspondence and reprint requests to pierre.maechler@medecine.unige.ch.

Accepted for publication 11 May 2001.

AUC, area under the curve; dmGlut, L-glutamic acid dimethylester; GDH, glutamate dehydrogenase.

The symposium and the publication of this article have been made possible by an unrestricted educational grant from Servier, Paris.

REFERENCES
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ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

Lenzen S: Insulin secretion by isolated perfused rat and mouse pancreas. Am J Physiol 236:E391–E400, 1979[Abstract/Free Full Text]
Berglund O: Different dynamics of insulin secretion in the perfused pancreas of mouse and rat. Acta Endocrinol (Copenh) 93:54–60, 1980[Medline]
Curry DL, Bennett LL, Grodsky GM: Dynamics of insulin secretion by the perfused rat pancreas. Endocrinology 83:572–584, 1968[Medline]
Ma YH, Wang J, Rodd GG, Bolaffi JL, Grodsky GM: Differences in insulin secretion between the rat and mouse: role of cAMP. Eur J Endocrinol 132:370–376, 1995[Medline]
Zawalich WS, Bonnet-Eymard M, Zawalich KC: Insulin secretion, inositol phosphate levels, and phospholipase C isozymes in rodent pancreatic islets. Metabolism 49:1156–1163, 2000[Medline]
Rorsman P: The pancreatic beta-cell as a fuel sensor: an electrophysiologist’s viewpoint. Diabetologia 40:487–495, 1997[Medline]
Lang J: Molecular mechanisms and regulation of insulin exocytosis as a paradigm of endocrine secretion. Eur J Endocrinol 259:3–17, 1999
Wollheim CB: Beta-cell mitochondria in the regulation of insulin secretion: a new culprit in Type II diabetes. Diabetologia 43:265–277, 2000[Medline]
Matschinsky FM: A lesson in metabolic regulation inspired by the glucokinase glucose sensor paradigm. Diabetes 45:223–241, 1996[Abstract]
Prentki M: New insights into pancreatic ß-cell metabolic signaling in insulin secretion. Eur J Endocrinol 134:272–286, 1996[Medline]
Henquin JC: Triggering and amplifying pathways of regulation of insulin secretion by glucose. Diabetes 49:1751–1760, 2000[Abstract]
Maechler P, Wollheim CB: Glutamate acts as a mitochondrially derived messenger in glucose-induced insulin exocytosis. Nature 402:685–689, 1999[Medline]
Maechler P, Antinozzi PA, Wollheim CB: Modulation of glutamate generation in the mitochondria affects hormone secretion in INS-1E beta cells. IUBMB Life 50:27–31, 2000[Medline]
Hudson RC, Daniel RM: L-GDHs: distribution, properties and mechanism. Comp Biochem Physiol B 106:767–792, 1993[Medline]
Malaisse WJ, Sener A, Carpinelli AR, Anjaneyulu K, Lebrun P, Herchuelz A, Christophe J: The stimulus-secretion coupling of glucose-induced insulin release. XLVI. Physiological role of L-glutamine as a fuel for pancreatic islets. Mol Cell Endocrinol 20:171–189, 1980[Medline]
Bertrand G, Gross R, Puech R, Loubatieres-Mariani MM, Bockaert J: Evidence for a glutamate receptor of the AMPA subtype which mediates insulin release from rat perfused pancreas. Br J Pharmacol 106:354–359, 1992[Abstract]
Sener A, Conget I, Rasschaert J, Leclercq-Meyer V, Villanueva-Penacarrillo ML, Valverde I, Malaisse WJ: Insulinotropic action of glutamic acid dimethyl ester. Am J Physiol 267:E573–E584, 1994[Abstract/Free Full Text]
Trimble ER, Bruzzone R, Gjinovci A, Renold AE: Activity of the insulo-acinar axis in the isolated perfused rat pancreas. Endocrinology 117:1246–1252, 1985[Abstract]
Pralong WF, Spat A, Wollheim CB: Dynamic pacing of cell metabolism by intracellular Ca2+ transients. J Biol Chem 269:27310–27314, 1994[Abstract/Free Full Text]
van Haeften TW, Boonstra E, Veneman TF, Gerich JE, van der Veen EA: Dose-response characteristics for glucose-stimulated insulin release in man and assessment of influence of glucose on arginine-stimulated insulin release. Metabolism 39:1292–1299, 1990[Medline]
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Vicent D, Garcia-Martinez JA, Villanueva-Penacarrillo ML, Valverde I, Malaisse WJ: Stimulation of insulin secretion and potentiation of glibenclamide-induced insulin release by the dimethyl ester of glutamic acid in anaesthetized rats. Diabetes Res Clin Pract 27:27–30, 1995[Medline]

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It’s all about location and balance,” says Dr. Smith. If glutamate accumulates outside of the cell, it can over-stimulate the cell by binding to a glutamate receptor. One such receptor, the NMDA receptor, is particularly sensitive to excessive levels of glutamate. Over-stimulation of NMDA receptors allows too much calcium to enter the cells where it triggers formerly dormant cell-death pathways.

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BBC NEWS | Health | Sticky DNA helps spot leukaemia

Sticky DNA helps spot leukaemia
By Louisa Cheung

Researchers use fluorescence to identify cells
US researchers have developed a new technique to distinguish leukaemia cells from healthy ones.
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The miracle worker - Sunday Times - Times Online

Feature

The miracle worker
This is p53. The gene keeps cancer at bay, and scientists are racing to find a wonder drug to harness its power. If they get it right, we’ll live longer, healthier, cancer-free lives. If they get it wrong — well, you don’t want to know. Sue Armstrong reports

::nobreak::In 2002 some scientists in Texas who were working with genetically engineered mice made a mistake and got a mighty surprise. In investigating a gene known to be crucial in protecting us from cancer, they created some mice without the gene (so-called “null mice”). The creatures proved highly prone to cancer and developed tumours at an early age, exactly as expected. In another group of mice, the researchers modified the gene, but it turned out rather more active than they intended.

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People have known for a long time that ageing and cancer are related, in that the chances of getting cancer increase with age. But nobody suspected they might be two sides of the same coin, sharing a common mechanism in which the scales can be tipped either way. In other words, that wrinkled skin, thinning bones and failing organs may be the price we pay in the long run for holding cancer at bay. “We don’t know the full picture yet,” says Professor Sir David Lane of Dundee University, a superstar in the field of cancer genetics, “but it certainly seems there’s a balance to be struck here.”

This discovery has hugely excited scientists studying both cancer and ageing, who have begun to collaborate seriously for the first time. “The clinical implications are clear,” says Lane. “People are beginning to ask, ‘Can I manipulate the system to get the best of both worlds?’” But the discovery raises other, more immediate – and alarming – questions. Could existing treatments for cancer, which often stimulate the activity of this important gene, accelerate ageing in the patient and lead to age-related disorders, such as dementia, later on? Or, conversely, could the use of drugs to try to slow the effects of ageing in people put them at higher risk of cancer? In meddling with genes without fully appreciating what might result, are we playing with fire? Nobody yet knows.

The gene at the centre of this flurry of interest is known simply as p53, because 53,000 is the molecular weight of the protein the gene produces when it is active. (Genes are, in effect, just recipes for proteins, which do all the work in our cells. The proteins are made only when and where they are needed, at which point the relevant gene is “switched on”.) P53 functions as a tumour suppressor. It senses when the DNA of a cell – the material inside the cell’s nucleus that carries all the genetic information – has been damaged. It can either stop the unnatural cell from reproducing itself – as it’s programmed to do in the normal course of body maintenance – until the DNA is repaired, or it may induce “cell suicide”. Nicknamed by Lane “the guardian of the genome”, because of its vital role in seeing that cells with scrambled DNA aren’t allowed to replicate and set off on the road towards cancer, the gene is found to be mutant and useless in more than half of all human tumours. Thus, while all cancers are caused by faulty genes, mutant p53 is the single most common genetic fault of all (see the graph on page 21).

Once the role of p53 was recognised, hundreds of molecular biologists worldwide dropped their own projects and took up with this little gene, beguiled by the prospect of conquering cancer – a disease you and I have a one-in-three chance of suffering from at some point in our lives, and a one-in-four chance of being killed by it. P53 has become the most widely studied single gene in history, generating nearly 36,000 published papers to date and bringing together every two years an ever-widening community of scientists working on the frontiers of cancer research to share their latest findings on the gene.

Like so many great scientific discoveries, p53 was found by accident in the late 1970s. When the protein made by the active gene cropped up unexpectedly in laboratory experiments looking at the activity of a monkey virus that causes tumours, most researchers dismissed it as an irritating contaminant. However, David Lane, then doing a post-doctoral fellowship in cancer research in London, was intrigued. The “rogue” protein appeared so regularly in his experiments, and he was so sure he had avoided contamination, that he felt compelled to find out what it was. His discovery that the “rogue” protein was a key player in the cancerous cells he was investigating was the cover story in Nature in 1979. Papers from other researchers, most notably Arnold Levine of Princeton University, New Jersey – who made the same discovery of a protein active in tumour cells – followed quickly. Scientists have learnt a great deal about how p53 works, which is essentially to orchestrate a cascade of events in response to cellular stress.

Conditions such as low oxygen or nutrient levels within cells, overexposure to sunlight and radiation, as well as DNA damage, send out alarm signals that switch on p53. The p53 then activates a series of genes “downstream” that put the brake on cell division, or induce cell suicide – a process known as “apoptosis”, from the Greek meaning “to drop out” and used poetically to describe the shedding of autumn leaves. (Researchers say this is what the dead cells scattered among the living in human tissue look like under the microscope.)

In 1992, impatient to find out whether what scientists were learning in the lab is what actually happens in us, Lane and Peter Hall, a cancer specialist and fellow p53 researcher, cooked up a maverick experiment over a pint in a Dundee pub, using Hall as the guinea pig. The experiment involved subjecting Hall’s arm to radiation from a sun lamp – “equivalent to 20 minutes on a Greek beach” – and taking a series of time-staggered skin biopsies to watch the activity of p53. “We reckoned that if this gene does respond to stress in living organisms, we should see the accumulation of p53 protein in the cells in my radiated skin. And that’s exactly what we did see,” says Hall, rolling up his sleeve to reveal nine neat scars. “We did the experiment on me because we wanted quick results. It would have taken months to get a licence for animal experiments. The scars all got infected,” he laughs, “but the experiment worked brilliantly, and it moved the field on considerably.”

The sun-lamp session was enough to trigger p53 but not damage the DNA and, as anticipated, Hall and Lane saw the protein level subside in time without causing cell arrest or apoptosis. They observed the normal functioning of p53 as it surveys our cells for signs of trouble. When the gene is unable to do its policing job, cells are at risk of becoming cancerous. Most often this is because p53 is damaged by mutation. There is a rare condition, for instance, called Li-Fraumeni syndrome, where people are born with mutant p53 in all their cells. Affected individuals are extremely vulnerable to cancer, tending to develop tumours – perhaps even in babyhood – and often several different types of cancer across their lives. (Among the rest of us, the proportion of patients who develop more than one of the 200-plus types of cancer is vanishingly small.)

Being inherited rather than acquired, Li-Fraumeni syndrome runs in families, explains Rosalind Eeles, who has a specialist clinic at the Royal Marsden hospital in London for people with the syndrome. “But because the cancers are so devastating and they occur at such a young age, the families are generally not very big.”

However, the gene can be disabled by means other than mutation – which helps explain what’s happening in the roughly half of all cancers in which this vital tumour-suppressor appears to be intact. When p53 was first seen in the experiments with the monkey virus, for example, the protein had been trapped and crippled by the virus (though of course nobody realised it at the time). Researchers have discovered, too, that in cervical-cancer cases caused by the human papilloma virus (HPV) – a sexually transmitted infection that can also cause genital warts – p53 is chopped up and devoured by the virus so that the cancer cells have none of the tumour-suppressor at all.

Very recently, Levine’s laboratory at Princeton uncovered a mechanism that explains why healthy p53 cannot prevent breast cancer developing in some cases. Researchers had already found that because it’s such a powerful gene, able to kill or arrest cells, p53 is kept under tight control by another gene called mdm2 that switches it on and off. “It’s like a policeman and his guard dog,” explains one scientist of the relationship between mdm2 and p53. “The policeman decides when to let the dog off the leash to fight a threat, and when to pull it in. If the policeman loses his grip, the dog can cause havoc.” So too with p53: “Mdm2 is what stops p53 killing all our cells – killing us!”

Now Levine and his colleagues discovered that in some people the mdm2 gene is more active than in others, holding p53 on a tighter leash and thus heightening the risk of developing cancer. “What surprised us,” says Levine of the breast-cancer study, “was that this [variant of mdm2] has its largest effect in pre-menopausal women, who have high levels of oestrogen.” So the “policeman” is influenced by the hormone, which amplifies its curbing effect on p53.

Having an overactive version of mdm2 is also bad news for smokers, says Levine. “Tobacco is a stress signal, a carcinogen in the lungs, and smoking alone might double or treble the risk for lung cancer. But two studies make it quite clear that, if you have this genetic risk factor plus tobacco, you have a tenfold increase in the odds of developing cancer.” Lung cancer is the most common cause of death in the UK, with one person newly diagnosed every 15 minutes, according to Action on Smoking and Health. For decades the tobacco industry sought to undermine the case against smoking by claiming that evidence of a link between tobacco and lung cancer, first mooted in the 1950s, was purely circumstantial – there was no physical proof that smoking caused the disease. But p53 has finally nailed the case against tobacco. Since the early 1990s, the International Agency for Research on Cancer (IARC) in Lyons, France, has kept a database of the mutations found in p53 in different tumour types. In the lung cancer of smokers, p53 is overwhelmingly mutated at a particular “hot spot” on the gene. In other words, the gene carries the fingerprint of the cancer-causing agent. Scientists found benzo(a)pyrene, a component of tobacco smoke, is the culprit.

The first paper pinning it down was published in 1996, followed closely by another presenting the evidence from the database. But Big Tobacco had been waiting in the wings. When the papers appeared, it launched an attack questioning the science and challenging the scientists via learned journals. “We’re used to trust within the scientific community, and you expect people to be fair,” says Pierre Hainaut of the IARC. “So the first reaction when you see a paper attacking your work is: ‘Oh my God, I’ve missed something important; I’ve made a big mistake!’”

But when he set out to answer his critics, Hainaut discovered a network of scientists and journal editors not only being paid by the tobacco industry to do their own research on p53, but colluding with the industry to hide the source of their funding and frustrate the scientific debate. They used their contacts to alert tobacco companies to forthcoming publications and helped to prepare papers challenging the data and get them into print as quickly and prominently as possible.

Hainaut followed the trail to secretive institutes set up by the tobacco industry, into the boardrooms of key journals and even the labs of some eminent scientists, and he was shocked. “It may seem very naive, but I had no idea something like this could happen,” he says. “It was like falling into a detective story.”

However, the battle, which turned nasty and personal at times and is well documented in a Lancet article of 2005, did have some positive spin-offs. The rules about declaring conflicts of interest when publishing scientific papers have been tightened. And Hainaut and his colleagues acknowledged the weakness of some data they used to make their original case, and started again from scratch to generate watertight data on the effect of tobacco on p53. Their paper was published in 2005.

Tobacco isn’t the only cancer-causing agent to leave a fingerprint on p53. Many cases of skin cancer have p53 mutations characteristic of ultraviolet radiation from sunlight. And most liver cancers in tropical countries are caused by aflatoxin, a poison secreted by a fungus that infects grains and peanuts, and leave a clear fingerprint on p53.

“Liver cancer is absolutely impossible to treat when it reaches a late stage, so the challenge is to have early detection,” says Hainaut. “The liver releases DNA into the bloodstream, and we can identify the presence of the mutation in it.

Two recent papers demonstrate that we have a very, very strong correlation between the presence of the mutation and cancer. “The feasibility of screening for liver cancer in high-prevalence tropical countries is currently being tested by the IARC and the UK Medical Research Council in west Africa.

Similar studies are under way in the US to see if screening heavy smokers with chronic bronchitis and other “cancer-predisposing symptoms” for mutant p53 in blood or spit samples could be used to identify people likely to develop cancer or to detect early tumours. And Levine believes screening younger women for the higher-acting version of mdm2 that stops p53 working properly might be used to single out those at risk from breast cancer who would benefit from regular mammograms well before their fifties. At the Royal Marsden, Eeles awaits new guidelines from the National Institute for Clinical Excellence (Nice) any day now “that will suggest breast-screening for women under 30 if they have the inherited p53 mutation”.

Though not many places are doing so yet, Hainaut believes the potential to use p53 for the detection and management of cancer is “huge and very important”. P53 research promises novel ways of treating cancer too. Several drugs currently being developed and tested make a virtue of the way viruses invade cells and take over the machinery for their own purposes. In one approach, a common-cold virus, genetically engineered so it cannot cause harm, is used to carry good copies of p53 into cancer cells where it is mutant and useless, thereby reactivating the stress-response machinery. In another, a the virus is engineered so it can infect only cells with dysfunctional p53 – cancer cells – where it grows and multiplies until the cells literally burst.

Besides gene therapy, researchers are looking for small molecules that can be used as tiny tools to tinker with the stress response at various points upstream or downstream of p53. Chemical compounds called “nutlins”, for example – developed by the pharmaceutical giant Hoffman-La Roche, and which interfere with the interaction between p53 and mdm2 – are causing a lot of excitement. Finding a molecule that would “cut the leash between the policeman and his dog”, enabling scientists to switch p53 on and off at will, has become a holy grail.

“I’m very excited about the results with nutlin,” says Lane, who set up a biotech company in the late 1990s to search for such a molecule. “It works very well in tissue culture and animal models, and appears to have good activity in the half of tumours where p53 is not mutant.” That is the case in most leukaemias, half of colon cancer, two-thirds of breast cancer, half of prostate cancer, “so very big numbers”.

Lane stresses, however, that nutlin is still a long way from the marketplace. “It’s not sufficiently drug-like yet to be in clinical trials. But what we call ‘target validation’ – that is, being certain that if we get a drug like this, it will work – is looking very good.”

Drugs to manipulate the p53 system to protect against cancer and slow down ageing at the same time are even further over the horizon, but scientists working to understand this relationship are making some sensational discoveries. Judith Campisi, a p53 and age researcher from Berkeley, California, studies a process called cell senescence. This means cells that lose the ability to divide but remain alive and active, which is one of the options that p53 can choose in responding to stress. “Inability to divide is good news if it means a damaged cell can’t form a tumour,” says Campisi. “But as these non-dividing cells accumulate over time, it’s not such good news, because we’ve seen they’re dysfunctional.”

During normal metabolism, senescent cells produce large amounts of waste material that seep from the cell and begins “to chew up the extra-cellular matrix – the stuff that keeps cells glued together”, explains Campisi. “The major extra-cellular molecule that keeps your skin looking young is collagen. Sure enough, senescent cells produce molecules that destroy collagen.” Hence, wrinkles.

Another theory about how tumour suppression might drive ageing is that, over time, we may simply run out of the stem cells we need to replenish our tissues and organs, as the cells are killed off or stopped from dividing by the stress-response mechanism. “The simplest model would be that you’re born with a limited number of stem cells,” explains Lane. “Those cells are very easily killed off by DNA damage, so they’re the ones most tightly controlled by p53. If you set a [stress-response] threshold where they’re too easily killed, you don’t get cancer but you run out of stem cells more quickly. If you set the threshold where they’re hard to kill, you could live a long time but you’re likely to get cancer.”

With compounds such as nutlins, scientists can manipulate p53 in ways that were once impossible – and for all kinds of therapeutic effects, says Lane, whose belief in the promise of the gene he discovered 27 years ago remains undiminished. “I think one can imagine really quite extraordinary results in the next few years as we begin to be able to control this system,” he says.

Even the idea of resetting our bodies’ stress response to suppress both cancer and ageing does not seem wacky to Lane. But the stakes are high: get the balance right and we will be on the way to longer and healthier lives; get it wrong and we could expire fast and messily in an orgy of apoptosis, as p53, like a guard dog out of control, runs riot in every cell of our bodies.

LIVING WITH CANCER

Natasha Dean has a rare inherited condition that leaves her highly susceptible to cancer. But she is determined to lead a normal life

Natasha Dean’s mother had her first mastectomy at the age of 15, following breast cancer. She had her other breast removed at 19, when cancer recurred, and died from secondaries in the bones at 39, when her daughter was 11. “I was always told by my father and my aunts that I should be careful,” she says. “So I was vigilant from an early age.”

She was on holiday in Australia in 2000 when she went for a routine checkup and discovered a lump in her breast. She was 24. After surgery, chemo- and radiotherapy, she returned to England, where she was referred to the cancer-genetics clinic of the Royal Marsden, London, for a p53 test. “The specialists in Sydney told me I fitted three of the five criteria that would classify someone as having Li-Fraumeni [syndrome],” says Dean. The Royal Marsden confirmed the diagnosis. She and her boyfriend looked it up on the internet, “but it was all quite scary, so I stopped,”she says.“They were very supportive at the hospital and made sure we were aware of the implications. Apparently, there are patients who don’t cope with it very well.” Dean has done so by carrying on with her everyday life.

In January 2004, a routine scan picked up secondary tumours in her liver. She asked to postpone chemotherapy for a few weeks while she married her boyfriend and visited her family in Australia. Treatment with Herceptin and tamoxifen while she was away kept cancer at bay. “The tumours shrank right down till you couldn’t see them any more,” she says. “But after 18 months they started to pop back up. So I had another four cycles of chemotherapy.” With each cycle she returned to her job with an investment bank for two weeks out of three. “Being able to work made it a lot easier getting through it,” she says.

Recently Dean has undergone radio-ablation, a new treatment that involves burning the cancer cells away with radio waves delivered through fine needles directly into the tumour. She is now recovering from a repeat of the procedure after new growth appeared at the edge of the scar.

The mutation in p53 can occur spontaneously in a sperm or egg at any point in a family’s history. Dean believes it began with her grandparents. She and her mother, both only children, are so far the only people affected. “My maternal grandmother passed away at 80, with no cancer. Her mother, my great-grandmother, had breast cancer, but post-menopausal.”

Dean knows she could pass the Li-Fraumeni on to her children. She and her husband have discussed their options with the oncologists. “Until I got the recurrence it was nice to know those options were there. But that’s not something I’m thinking about now,” she says.

Thursday, August 03, 2006

IL4 and IL10 and Pain

Health briefs

August1 2006

CHRONIC PAIN: Lack of proteins could be culprit

Low blood levels of two anti-inflammatory proteins could be key to chronic pain, researchers report.

Low concentrations of two cytokines, IL-4 and IL-10, were found in patients with chronic widespread pain, according to a German study published in the August issue of Arthritis & Rheumatism.

Cytokines are proteins that act as messengers between cells.

The study included 40 patients who'd received intravenous immunoglobulin (IVIG) as a novel treatment for pain that hadn't responded to standard therapy and another 15 patients who did not receive IVIG. The study also included a control group of 40 healthy people.

Compared with the control group, the 40 pain patients had significantly lower levels of IL-4 and IL-10. The 15 patients in the second group had similar results, although the difference in their levels of IL-10 compared to people in the control group was not statistically significant.

Several factors may be involved in low levels of these cytokines and how they influence pain, the study authors said. They noted that previous studies have shown that IL-10 reduces sensitivity to pain and that IL-4 can also dull pain response.

Genetic variations in different cytokine genes are associated with certain diseases. For example, IL-4 gene variations are associated with asthma, Crohn's disease and chronic polyarthritis, the researchers said.

the honda case

Case Name:

EVALUATING DISABILITY A MEDICAL LEGAL DILEMMA

Jumping Through Hoops

Disability Law Guide - Bayda Ludwar Law Firm

HRDC - Evaluation of the National Vocational Rehabilitation Project

eMJA: Management of chronic low back pain

eMJA: Management of chronic low back pain

They are correct in stating that reductionist procedures performed to the required standard are available in only a few centres. However, this does not invalidate these procedures; it reflects only a political and ideological problem in healthcare delivery. They also fail to reveal that in many places where these procedures are available, they are not performed according to best-practice standards. It is not the procedures, but misguided and unscrupulous practitioners, who render patients bewildered and dysfunctional

eMJA: Management of chronic low back pain

Multidisciplinary rehabilitation for chronic low back pain: systematic review -- Guzm�n et al. 322 (7301): 1511 -- BMJ

NEJM -- The Promise and Problems of Meta-Analysis

NEJM -- The Promise and Problems of Meta-Analysis

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The Promise and Problems of Meta-Analysis

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Meta-analysis has acquired a substantial following among both statisticians and clinicians. The technique was developed as a way to summarize the results of different research studies of related problems. Meta-analysis may be applied even when the studies are small and there is substantial variation in the specific issues studied, the research methods applied, the source and nature of the study subjects, and other factors that may have an important bearing on the findings. In this issue of the Journal, LeLorier et al.1 compare the findings of 12 large randomized, controlled trials with the results of meta-analyses of the same problems. They find important discrepancies. When a large randomized, controlled trial — commonly considered the gold standard for determining the effects of medical interventions — disagrees with a meta-analysis, what should the reader conclude? Perhaps more important, when only one of the two tools is used, how much uncertainty should the reader add to the confidence limits and other statistical measures of uncertainty reported by the author?

The core of meta-analysis is its systematic approach to the identification and abstracting of critical information from research reports. Doing a meta-analysis correctly demands expertise in both the method and the substance and hence almost always requires collaboration between clinicians and an experienced statistician. The questions must be defined carefully to maximize the relevance of the reports to be included and to reduce uncertainties about procedures. The investigators must then try to find every relevant report by searching data bases, reviewing bibliographies, and asking widely about unpublished work. The collected reports are then winnowed to the few (often less than 10 percent) that meet the requirements for the meta-analysis. The reports must be searched carefully to identify problems and validate the quantitative findings of interest. These findings must be expressed on a common scale (often as odds ratios), and some reports may have to be dropped for lack of information. Those doing a meta-analysis may also abstract information from each report to produce a quantitative measure of research quality. Each of the individual quantitative estimates must be scrutinized for problems, and this may require the efforts of a range of specialists. When the analysis is completed and submitted for publication, the editor and the reviewers must assure themselves of its quality. A rigorous technical review of a meta-analysis requires the reviewer to identify, reabstract, and interpret a fair sample of the original papers. Very few editors and reviewers will do this, which may be one reason why there are so many poor meta-analyses in the literature.

Although some meta-analyses stop with the presentation and discussion of the results of the individual studies, many others proceed further and combine the results into a single, comprehensive "best" estimate, generally with statistical confidence bounds, that is meant to summarize what is known about the clinical problem. This last step — preparing and presenting a single estimate as the distillation of all that is known — is the one that has drawn the most criticism. This is because there are often biologic reasons, statistical evidence, or both, showing that the studies included in the meta-analysis have in fact measured somewhat different things, so that a combined estimate cannot be meaningful unless additional, doubtful assumptions are made. One such assumption is that the effects reported in the studies actually performed can be seen as a random sample of the effects observed in all possible studies that might have met the author's criteria. Unfortunately, there is little evidence to support an assumption such as this.

LeLorier et al.1 searched four leading general medical journals to identify all the large randomized, controlled trials (those with 1000 subjects or more) whose results were published from 1991 through 1994, then searched for meta-analyses of similar topics that were published before each trial. Twelve large randomized, controlled trials and 19 meta-analyses met their criteria. Because some of the trials and meta-analyses reported on more than 1 outcome, they studied a total of 40 outcomes. Overall, there was somewhat better than chance agreement between these meta-analyses and the subsequent large randomized, controlled trials, with kappa values in a range commonly considered to represent "fair-to-slight agreement." In terms of an ordinary diagnostic test, the results could be described as average. The results obtained with the two approaches usually pointed in the same direction, and there were no cases in which they gave statistically significant results in opposite directions. However, the discrepancies with regard to the estimated size of an effect were sometimes quite substantial, and occasionally they differed significantly despite their agreement in direction. Stewart and Parmar2 have shown how some such differences can arise.

It is impossible to say, on the basis of present evidence alone, whether the results of a large randomized, controlled trial or those of a meta-analysis of many smaller studies are more likely to be close to the truth. Much depends on the details of both the research studies and the analyses. When both the trial and the meta-analysis seem to be of good quality, however, I tend to believe the results of the trial. A history of 40 years of generally successful use of randomized, controlled trials that have made important contributions to progress in many branches of medicine must not be overlooked. In addition, major problems with the implementation of meta-analyses have been common.3,4,5,6 There have been a wide variety of these, including failure of the investigator performing the meta-analysis to understand the basic issues, carelessness in abstracting and summarizing appropriate papers, failure to consider important covariates, bias on the part of the meta-analyst, and, perhaps most often, overstatements of the strength and precision of the results. It is not uncommon to find that two or more meta-analyses done at about the same time by investigators with the same access to the literature reach incompatible or even contradictory conclusions.7,8,9,10 Such disagreement argues powerfully against any notion that meta-analysis offers an assured way to distill the "truth" from a collection of research reports.

Other observers, including policy makers, also have reservations about meta-analyses, and there is some general concern about the credibility of the findings of meta-analysis. I know of no instance in medicine in which a meta-analysis led to a major change in policy before the time when a careful, conventional review of the literature led to the same change. Showing that a sequence of meta-analyses performed over time converged to have some value as published findings accumulated does not mean that it was the meta-analyses that gave a convincing answer to the particular clinical question.

In my own review of selected meta-analyses,3 problems were so frequent and so serious, including bias on the part of the meta-analyst, that it was difficult to trust the overall "best estimates" that the method often produces. On present evidence, we can generally accept the results of a well-done meta-analysis as a way to present the results of disparate studies on a common scale (as is shown by the two figures in the article by LeLorier et al.), but any attempt to reduce the results to a single value, with confidence bounds, is likely to lead to conclusions that are wrong, perhaps seriously so. I still prefer conventional narrative reviews of the literature, a type of summary familiar to readers of the countless review articles on important medical issues.

Meta-analysis may still be improved, by a combination of experience and theory, to the point at which its findings can be taken as sufficiently reliable when there is no other analysis or confirmation available, but that day seems to be well ahead of us. LeLorier et al. also imply, however, that large randomized, controlled trials should be regarded more circumspectly than published reports commonly suggest. We never know as much as we think we know.

John C. Bailar III, M.D., Ph.D.
University of Chicago
Chicago, IL 60637

References

LeLorier J, Grégoire G, Benhaddad A, Lapierre J, Derderian F. Discrepancies between meta-analyses and subsequent large randomized, controlled trials. N Engl J Med 1997;337:536-542.[Abstract/Full Text]
Stewart LA, Parmar MK. Meta-analysis of the literature or of individual patient data: is there a difference? Lancet 1993;341:418-422.[Medline]
Bailar JC III. The practice of meta-analysis. J Clin Epidemiol 1995;48:149-157.[CrossRef][Medline]
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Shapiro S. Meta-analysis shmeta-analysis. Am J Epidemiol 1994;140:771-778.[Medline]
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Kerlikowske K, Grady D, Rubin SM, Sandrock C, Ernster VL. Efficacy of screening mammography: a meta-analysis. JAMA 1995;273:149-154.[Abstract]
Smart CR, Hendrick RE, Rutledge JH III, Smith RA. Benefit of mammography screening in women ages 40 to 49 years: current evidence from randomized controlled trials. Cancer 1995;75:1619-1626.[Medline]
Rosenfeld RM, Post JC. Meta-analysis of antibiotics for the treatment of otitis media with effusion. Otolaryngol Head Neck Surg 1992;106:378-386.[Medline]
Williams RL, Chalmers TC, Stange KC, Chalmers FT, Bowlin SJ. Use of antibiotics in preventing recurrent acute otitis media and in treating otitis media with effusion: a meta-analytic attempt to resolve the brouhaha. JAMA 1993;270:1344-1351. [Erratum, JAMA 1994;271:430.][Abstract]

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N Engl J Med 1998; 338:59-62, Jan 1, 1998. Correspondence

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Anderson, J. W, Johnstone, B. M, Remley, D. T (1999). Breast-feeding and cognitive development: a meta-analysis. Am. J. Clin. Nutr. 70: 525-535 [Abstract] [Full Text]
Freudenheim, J. L (1999). Study design and hypothesis testing: issues in the evaluation of evidence from research in nutritional epidemiology. Am. J. Clin. Nutr. 69: 1315S-1321 [Abstract] [Full Text]
Arditi, M., Mason Jr, E. O., Bradley, J. S., Tan, T. Q., Barson, W. J., Schutze, G. E., Wald, E. R., Givner, L. B., Kim, K. S., Yogev, R., Kaplan, S. L. (1998). Three-Year Multicenter Surveillance of Pneumococcal Meningitis in Children: Clinical Characteristics, and Outcome Related to Penicillin Susceptibility and Dexamethasone Use. Pediatrics 102: 1087-1097 [Abstract] [Full Text]
GIANNINI, E. H (1998). Can non-fundable trials be conducted anyway? The case for open, randomised, actively controlled trials in rheumatology. Ann Rheum Dis 57: 128-130 [Full Text]

Wednesday, August 02, 2006

Tuesday, August 01, 2006

How to caulk around a tub from AverageGuyDIY.com

Caulk Like a Professional

Ancestral Pile: let's talk caulk

Text Savvy

: Name: Impatient Patient; Location: Martha and Henry's World, Canada

"Westley: Life is pain, Highness. Anyone who says differently is selling something. " (The Princess Bride) I'm a bitch I'm a lover I'm a child, I'm a mother.... and I am a stuck on the wonders of science and I am incensed by alternative medicine and the misuse and manipulation of data. I am NOT a scientist, I am NOT an expert on anything, so please know that any mistakes on this blog are failures of mine, and if they need to be corrected (scientifically speaking ONLY) please feel free to let me know.

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The Patient Is In

Thursday, August 17, 2006

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Tuesday, August 15, 2006

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Thursday, August 03, 2006

eMJA: Management of chronic low back pain

eMJA: Management of chronic low back pain

Multidisciplinary rehabilitation for chronic low back pain: systematic review -- Guzm�n et al. 322 (7301): 1511 -- BMJ

NEJM -- The Promise and Problems of Meta-Analysis

Wednesday, August 02, 2006

Untitled Document

Celebrity Mercury OV Stateroom And Veranadah

Checking Out: A Boycott

Tuesday, August 01, 2006

How to caulk around a tub from AverageGuyDIY.com

Caulk Like a Professional

Ancestral Pile: let's talk caulk

Text Savvy

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