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The fight against blood doping in sport

Blood doping benefits endurance athletes (notoriously, but not only, cyclists) by raising the red blood cell (rbc) count or haematocrit, and so increasing the oxygen supply to the muscles. It is one of the most difficult types of drug abuse to detect. Awareness of blood doping was raised in the popular press recently when comments were made about the impressive nature of China’s Ye Shiwen’s Olympic gold medal wins and with Lance Armstrong’s (cycling’s famous winner of seven Tours de France after surviving advanced testicular cancer) sudden decision to drop his fight against the US Anti-Doping Agency’s drug charges. Hematocrit levels can be raised by a variety of methods ranging from legal altitude training, to the banned use of autologous blood transfusions and erythropoietin (EPO) injections.
Detection of these banned methods is extremely difficult and the fight against them is being waged in a number of ways. The UCI’s (cycling’s governing body) lines of defence include simply demonstrating possession of banned substances and monitoring hematocrit levels, with a limit set at 50% (normal being 41–50% for men).
Some early success was had with testing urine to distinguish pharmaceutical EPO from the nearly identical natural hormone by isolectric focusing, though its accuracy has been questioned with claims that it is not possible to distinguish pharmaceutical EPO from other unrelated proteins that are present in urine after strenuous exercise or as the result of sample degradation and bacterial contamination.
At present, tests that provide indirect evidence of autologous blood transfusion (where the athlete withdraws and then re-injects his own blood) are under development and involve looking at the ratio of immature to mature red blood cells and might also include the measurement of 2,3-bisphophoglycerate (2,3-BPG). As 2,3-BPG degrades over time, stored blood used for autologous transfusions would have less than fresh blood and so levels of 2,3-BPG lower than normal may then indicate blood doping by this method. The presence of plasticizers in the blood (from the IV bags in which blood is stored) has also been used as evidence of blood doping.
While these advances in the detection of blood doping are being made it is tempting to think that we have got there, that the cheats will be caught. However, in the high-stakes world of elite athletes this would be a naive hope: the possibility of athletes subjecting themselves to EPO gene therapy – so called gene doping – has been suggested and methods for the detection of transgenic DNA following in vivo gene transfer are already being developed.

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C39 Fig1

Improving the precision of peanut allergy testing

The increasing prevalence of peanut allergy has placed a significant burden on patient waiting times in Australian allergy clinics. We hope that the use of 2-step component testing for whole peanut and Ara h2 improves the accuracy of peanut allergy diagnosis, thereby alleviating this problem. This article discusses the clinical implications for Ara h2 testing.
by Thanh D. Dang and Professor Katrina J. Allen

The current diagnosis of peanut allergy
Food allergy affects 4–6% of the western population, with the number of hospital admissions for food related reactions more than doubling in the last decade. Peanuts and tree nuts account for almost half of all food related incidences of anaphylaxis. The diagnosis of peanut allergy is relatively straightforward when there is an unequivocal history of clinical reaction to peanut ingestion [1]. However, diagnosis can be more complicated in cases where the clinical history is not clearly defined, or in children who have not yet been exposed to a food. Positive results for both the skin prick test (SPT) and the blood test for peanut-specific IgE (ImmunoCAP fluorescence enzyme immunoassay) have high sensitivity and low specificity for diagnosis of peanut allergy. Thus, the positive predictive value (PPV) of these tests (i.e. the likelihood of detecting true peanut allergy) is low. Several reports have documented that the use of 95% PPV threshold values has assisted peanut allergy diagnosis in the clinic [2,3]. Nevertheless, for the large majority of patients who have a positive SPT or ImmunoCAP result below 95% PPV, it remains uncertain whether or not there is clinical allergy, and an oral food challenge (OFC) is required to confirm or exclude a diagnosis of food allergy. Although definitive, the OFC is time consuming, costly, and is associated with a risk of anaphylaxis. Thus, new approaches that allow accurate diagnosis of peanut allergy while reducing the need for an OFC are needed.

Due to the rapid rise in rates of sensitisation to foods, allergy services are overwhelmed and food-challenge tests may be difficult to access. Clinicians faced with the difficult task of having to assess for the presence of food allergy based solely upon a positive SPT or ImmunoCAP must err on the side of caution and accept a diagnosis of ‘possible’ food allergy in these situations. This approach may lead to over-diagnosis of peanut allergy in the community, and a potentially unnecessary burden on the healthcare system. Moreover, an incorrect diagnosis of food allergy unnecessarily imposes allergen avoidance and impaired quality of life on the patient and family.

Component resolved diagnosis

Recent progress in molecular biology and biochemistry has led to recombinant production of individual allergenic proteins for peanut. A total of 11 peanut components (Ara h1–11) have been identified with Ara h1–3 considered to be the major peanut allergens [4]. In recent times, the use of Ara h allergens has been suggested to be a more accurate diagnostic tool for the assessment of peanut allergy. Ara h2-specific immunoglobulin-E (Ara h2-sIgE) has been detected in 90–100% of peanut allergic patients and, although these results have been based on small study cohorts, it has been suggested that the sensitivity and specificity of Ara h2-sIgE testing is higher when compared to the current tests used to diagnose peanut allergy [5–7]. In a study of 29 peanut allergic patients, Nicolaou et al. reported a 93% sensitivity and a 100% specificity for Ara h2-sIgE at level of 0.55 kUA/L (UA = allergen specific unit) [8]. However, this small study was carried out on a patient population selected from the clinic and negative controls were not used.

In this study, we assessed whether Ara h2-sIgE could accurately identify peanut allergic status using subjects recruited into the population-based HealthNuts study, where an OFC was performed in all infants with positive peanut SPT irrespective of wheal size or history of previous reaction [9]. This design allows validation of the ability of Ara h2 to predict peanut allergy in a population-based setting.

Methods
The methods for study recruitment, skin prick testing and oral food challenges used in the Melbourne, Australia, based HealthNuts study have been detailed previously [9]. For an estimated sensitivity or specificity of 95% from Nicolaou’s study Ara h2-sIgE data [5], a sample size of 100 allergic and 100 non-allergic participants randomly selected from the HealthNuts study is sufficient to provide a lower limit of 92% for the corresponding 95% confidence interval. Of the 200 subjects analysed, 100 were peanut allergic, confirmed with a positive SPT and peanut food challenge. The remaining 100 peanut tolerant infants, confirmed by a peanut food challenge, consisted of 58 peanut-sensitised and 42 non-peanut sensitised infants, who were randomly selected as negative controls. Allergen-sIgE was measured with the ImmunoCAP System FEIA (Phadia AB, Uppsala, Sweden). Plasma samples were analysed for IgE to whole peanut and Ara h2.
Samples with Ara h2 IgE <0.35 kUA/L were tested for the presence of allergen specific IgE to the other major peanut allergens Ara h 1, 3, 8 and 9. Ara h2 testing compared to other tests
Compared to both skin prick testing and whole peanut sIgE, measurement of Ara h2-sIgE correctly identified more true peanut allergic subjects, when 95% specificity or 95% PPV were applied. If the previously reported 15 kUA/L for peanut sIgE threshold is adopted, which provides the 95% PPV and 98% specificity [Figure 1], the sensitivity of the whole peanut-sIgE test is 26% [95% CI: 18%–36%]. At a comparative specificity of 97%, provided by an Ara h2-sIgE level of 1.00 kUA/L, Ara h2-sIgE testing detects 60% [95% CI: 50%–70%, p<0.001]. How Ara h2 testing can improve peanut allergy diagnoses and outcomes of our study
Figure 2 shows two strategies which incorporate the use of peanut-sIgE or SPT as the first line test followed by Ara h2-sIgE as a second line of testing to help improve the accuracy of distinguishing peanut allergic from peanut tolerant subjects. In the first model, Ara h2 testing of the 95 infants with peanut-sIgE levels between 0.35 and 14.9 kUA/L successfully identified an additional 22 infants as peanut tolerant and 35 infants as peanut allergic [Figure 2a]. Hence incorporating Ara h2-sIgE in combination with peanut-sIgE testing would reduce the number of oral food challenges by almost two-thirds from 95 (47.5%) down to 32 (16%, P<0.001). In the second model, Ara h2 testing of the 50 infants with SPT between 3-8mm identified an additional 6 infants as peanut tolerant and 21 as peanut allergic [Figure 2b], reducing the number of oral food challenges from 50 (25%) to 21 (10.5%, P=0.007). We found that Ara h2-sIgE testing is more accurate in determining peanut allergy compared to either peanut SPT or whole peanut sIgE alone using the gold standard OFC to confirm presence of true food allergy. Although we demonstrated that the performance of both SPT and Ara h2-sIgE testing to correctly identify peanut allergic and peanut tolerant infants were similar, a SPT is usually performed in a specialist setting. The patient waiting times are at present significant exceeding 18 months in many centres in Australia. By comparison, blood testing for Ara h2 and whole peanut sIgE can be easily be accessed in the community by primary and secondary healthcare professionals with access to diagnostic laboratories. Using our cohort, testing with peanut sIgE followed by Ara h2-sIgE could substantially reduce the number of OFCs required to diagnose peanut allergy by almost two-thirds. Given that the cut-off of ≤0.1 kUA/L for Ara h2 can identify 87% of peanut tolerant infants while only having a 5% false negative rate, this would support the gradual introduction of peanuts into the diet if the child has not already eaten the food. Conversely, a cut-off of 1.00 kUA/L for Ara h2 detects 60% of peanut allergics with a false positive rate of 2%; and can be used to diagnose the presence of peanut allergy. The remainder of subjects that fall between these thresholds would require an OFC to confirm peanut allergy status. While the use of Ara h2 in the diagnosis of peanut allergy in the community has significant advantages, in an allergy clinic setting, peanut SPT still provides a rapid and accurate method for determining peanut allergy, and Ara h2-sIgE could be used as a subsequent test to reduce the number of patients requiring an oral food challenge. One limitation of our results is that our tested population were all 12 month old infants. However, in the absence of data from populations including older age groups, these results are the best available and likely to be reasonably robust for other ages. Where will Ara h2 testing be applicable?
Ara h2 has been identified as the predominant peanut allergen in a number of countries from Europe, North America, south-east Asia and Australia and may be considered in the diagnosis of peanut allergy [6,8,10–13]. However, the use of Ara h2 sIgE testing may not by applicable to all populations – for example Ara h9 is reported to be the dominant allergen in Spain. In the Australian population, other recombinant allergens tested may not improve detection of peanut allergy amongst subjects with Ara h2-sIgE levels <0.35 kUA/L. In our study, only 9 of the 100 peanut allergic patients had Ara h2-sIgE concentrations <0.35 kUA/L, and only 5 of these 9 subjects had detectable Ara h1, Ara h3, Ara h8, or Ara h9 sIgE levels. Further additional testing of the other peanut allergens on all subjects would be required to identify if there are other allergens that are dominant in our region. Our 2-step testing algorithm ensures that targeted testing of these Ara h allergens can be undertaken in a cost-effective way. That is to say that those children with a positive whole peanut sIgE but negative Arah2 would then require testing for the other Ara h allergens depending on the region of testing and the second most predominant allergen in that region. Conclusion
Whole peanut IgE followed by Ara h2-sIgE testing should be considered as the preferred 2-step diagnostic tool for determining peanut allergy, as we have shown greater diagnostic accuracy with this method than by either whole peanut sIgE or peanut SPT alone. This will reduce the need for an oral food challenge and ultimately may reduce the strain and demand on clinical allergy services.

References
1. Allen KJ, Hill DJ, Heine RG. Food allergy in childhood. Medical Journal of Australia 2006; 185: 394–400.
2. Sporik R, et al. Specificity of allergen skin testing in predicting positive open food challenges to milk, egg and peanut in children. Clinical and experimental allergy 2000; 30: 1540–1546.
3. Sampson HA. Utility of food–specific IgE concentrations in predicting symptomatic food allergy. The Journal of allergy and clinical immunology 2001; 107: 891–896.
4. Allergen Nomenclature. The Official ‘‘List of Allergens.’’ W.H.O./I.U.I.S. Allergen Nomenclature Sub–Committee. 2010. Available at: http://www.allergen.org. Accessed May 15, 2011.
5. Nicolaou N, Poorafshar M, Murray C, Simpson A, Winell H, Kerry G, et al. Allergy or tolerance in children sensitized to peanut: prevalence and differentiation using component–resolved diagnostics. The Journal of allergy and clinical immunology 2010; 125: 191–197.
6. Knol EF, Knulst AC, Bruijnzeel-Koomen CA, Hoekstra MO, Pasmans SG, Koppelman S, et al. Children with peanut allergy recognize predominantly Ara h2 and Ara h6, which remains stable over time. Clinical and experimental allergy 2007; 37: 1221–1228.
7. Astier C, Morisset M, Roitel O, Codreanu F, Jacquenet S, Franck P, et al. Predictive value of skin prick tests using recombinant allergens for diagnosis of peanut allergy. Journal of Allergy and Clinical Immunology 2006; 118: 250–256.
8. Nicolaou N, Murray C, Belgrave D, Poorafshar M, Simpson A, Custovic A. Quantification of specific IgE to whole peanut extract and peanut components in prediction of peanut allergy. Journal of Allergy and Clinical Immunology 2011; 127: 684–685.
9. Osborne NJ, Koplin JJ, Martin PE, Gurrin LC, Thiele L, Tang ML, et al. The HealthNuts population–based study of paediatric food allergy: validity, safety and acceptability. Clinical & Experimental Allergy 2010; 40: 1516–1522.
10. Vereda A, van Hage M, Ahlstedt S, et al. Peanut allergy: Clinical and immunologic differences among patients from 3 different geographic regions. The Journal of allergy and clinical immunology 2011; 127: 603–607.
11. Flinterman AE, Knol EF, Lencer DA, Bardina L, den Hartog Jager CF, Lin J, et al. Peanut epitopes for IgE and IgG4 in peanut–sensitized children in relation to severity of peanut allergy. Journal of Allergy and Clinical Immunology 2008; 121: 737–743.
12. Chiang WC, Pons L, Kidon MI, Liew WK, Goh A, Wesley Burks A. Serological and clinical characteristics of children with peanut sensitization in an Asian community. Pediatric Allergy and Immunology 2010; 21: e429–e38.
13. Codreanu F, Collignon O, Roitel O, Thouvenot B, Sauvage C, Vilain AC et al. A novel immunoassay using recombinant allergens simplifies peanut allergy diagnosis. International Archives of Allergy & Immunology 2011; 154: 216–26.

The authors
Thanh D Dang, BBiomedSc and
Katrina J. Allen*, BMedSc, MBBS, FRACP, PhD
MCRI, Royal Children’s Hospital
Flemington Road, PARKVILLE   VIC  3052, Australia
*Corresponding author:
email: katie.allen@rch.org.au

C41a

Diagnosing asthma in smokers

Asthma patients who smoke report more pronounced symptoms, an attenuated response to inhaled corticosteroids and more frequent attacks. Furthermore, diagnosing asthma in smokers can be difficult, as smoking impacts on the results of frequently used diagnostic and monitoring tools for asthma, including exhaled NO (eNO) and airway challenges.

by Dr Christian G. Westergaard, Professor Vibeke Backer and Dr Celeste Porsbjerg

Clinical background
Asthma is one of the most frequent chronic diseases worldwide, with an estimated global prevalence of 300 million people. The disease is characterised by respiratory symptoms, airway hyperresponsiveness (AHR) and bronchopulmonary inflammation. Asthma symptoms can be triggered by different agents, including exposure to allergens, physical activity and unspecific irritants such as air pollution, perfume, air humidity and tobacco smoke. The prevalence of asthma varies considerably between countries, however, in general, the prevalence  has been increasing during recent decades, and ranges from a few percent to more than 15% in some countries [1].

It is estimated by the WHO that 1.25 billion people in the world are smokers. The global tobacco consumption was in 2000 estimated to be 15 billion cigarettes per day. This number is not expected to decrease until 2030, because the total number of smokers will become higher due to a larger world population [2].

Tobacco smoking has very damaging impacts on the asthmatic disease. Asthma patients who smoke report more pronounced symptoms, an attenuated response to inhaled corticosteroids, more frequent exacerbations and a higher mortality rate from asthma. Furthermore, these patients suffer from an accelerated decline in lung function, where both the highly reactive tobacco smoke and the chronic asthmatic inflammation in combination contribute to airway tissue destruction. Unfortunately, tobacco smoking is common among asthma patients, with a frequency of smokers at least as high as found in the rest of the population. In most countries, smokers constitute 15–40% of the population.

In the clinical setting, spotting the asthma patients among smokers can be challenging, due to the overlap of airway symptoms between true asthma and smoking-induced manifestations such as productive cough as well as breathlessness during exercise. In patients with a significant smoking history, an element of early chronic obstructive pulmonary disease (COPD) can also blur the clinical picture.

The diagnosing and monitoring of asthma has traditionally been based on the evaluation of symptoms in combination with spirometric measurements, which to date remain key elements in the clinical handling of asthma patients. However, as asthma is basically an inflammatory disease, many new diagnostic approaches focusing on airway inflammation have emerged, such as exhaled nitric oxide (eNO), sputum induction and airway challenges, of which the most recently approved is the mannitol test. All of these newer tests contribute to the understanding of the underlying pathophysiological mechanisms of the disease as well as expanding our diagnostic possibilities.

However, it appears that tobacco smoke may attenuate the clinical utility of many of the tests. In the following section, the focus will be on the effect of smoking on inflammation markers, AHR and spirometry, respectively.

Inflammation markers: eNO and induced sputum
Smoking has a considerable impact on the measurement of eNO. Several studies have reported a pronounced reduction of eNO in smokers compared to non-smokers, as much as 40–60% in current smokers [3]. Even passive smoking seems to have an effect on eNO values. Moreover, in a study from 2009 it was shown that eNO could only discriminate asthmatics from healthy controls in never-smokers, and not in either current or former smokers [4]. However, we have recently reported data from large sample, demonstrating that in adults with symptoms suggestive of asthma, eNO was equally good at differentiating between asthma and non-asthma, albeit with a lower cut-off for an abnormal eNO in smokers than in ex- and never smokers [5].

An eNO value of 17–22 ppb has been proposed for diagnosing asthma in current smokers [5, 6], supported by others who suggested 18 ppb as a cut-off for smokers without allergic rhinitis [6]. These similar cut-off values represent quite different sensitivity values, from about 40 to 100 %, when preserving a high specificity of at least 90%.

It would seem that eNO can also be applied in disease monitoring of the smokers when used in sequential measurements, because even in smokers, relative changes in eNO have been shown to reflect the dynamics of disease activity [7]. It has been demonstrated that, similar to non-smokers, a decrease in eNO of <20% precludes asthma control improvement, and that an increase in eNO of <30% is not associated with loss of control [7]. An important issue is the lack of knowledge regarding cut-off values for predicting steroid-response. In non-smokers, the effect of treatment with steroids has been found to be associated with airway eosinophilia, which again correlates well with eNO. Hence, a cut-off value for eNO predicting a sputum eosinophil count >3% and a high likelihood of a positive steroid response has been investigated. In smokers, this value was 28 ppb, ranging from 15 to 33 ppb, depending on atopy and high dose ICS usage [8], compared to 24 to 58 ppb in non-smokers. Such cut-off values are, however, not easy to determine, due to many factors of importance for the level of eNO, including atopy with rhinitis, life tobacco consumption and respiratory tract infections.
Several underlying mechanisms for the decreased eNO in smokers have been demonstrated, including increased arginase expression leading to reduced amounts of iNOS substrate, attenuated eosinophilic and enhanced neutrophilic inflammation as well as the impact on exogenous NO from cigarette smoke leading impairment of NO synthesis.

Another way of characterising the inflammation in the airway tissue is through sputum induction. This technique is rarely used in the diagnosis of asthma. In smoking asthmatics, it seems that the cell distribution is altered into a less eosinophilic and more neutrophilic direction. This may partially explain why smokers are less responsive to steroids.

Bronchial challenges: mannitol and methacholine
Another important approach in asthma diagnostics is measurement of airway hyperresponsiveness (AHR) using the mannitol challenge, which is an indirect bronchial provocation. In non-smokers, this test can be successfully applied for both diagnostic and monitoring purposes. It has been shown that the mannitol challenge is useful in confirming a diagnosis of asthma (specificity close to 100%), unfortunately, however, the sensitivity is considerably more moderate, around 60% [9] and thereby lower than that of the methacholine challenge [9]. Being a relative recent invention, the diagnostic properties of the mannitol test have not yet been evaluated in a smoking asthmatic population. However, in non-asthmatic smokers, a study has indicated that as much as one quarter of the subjects expressed a positive mannitol test [10]. Thus, until investigated properly in smoking asthma patients, the mannitol challenge test should be interpreted with caution and be accompanied with other tests in order to account for false positives.
AHR can also be assessed through direct challenges such as inhaled methacholine. The higher sensitivity for the methacholine test (69%) compared to the mannitol test is, unfortunately, not accompanied by an equivalently higher specificity, which has been reported to be 80% [9]. In non-asthmatics, previous studies have indicated increased AHR to methacholine in smokers. But as is the case with the mannitol test, the diagnostic properties of the methacholine test have not yet been investigated in a smoking asthmatic population, which is surprising considering that the test has been applied for decades. However, a few studies have documented that smoking does appear to affect AHR to both direct and indirect challenges. In COPD patients, it has been shown that one year of smoking cessation is associated with improvement in AHR to methacholine as well as to AMP; this finding has been supported later in a study primarily of healthy subjects, but also a few asthma patients. 
 
Spirometry with reversibility test

Increased bronchial muscular tonus is a key feature in persistent asthma, which is the reason that measurements of lung function, including the reversibility test, have been widely used in asthma diagnostics and monitoring for decades. For some smoking asthma patients, this will continue to be a corner stone in confirming the diagnosis, but in smoking asthmatic subjects with a baseline normal FEV1 or patients with very severe asthma and hence attenuated airway compliance, reversibility testing may not be the best diagnostic test. Many studies of asthma and COPD patients have shown improvement in FEV1 after smoking cessation, indicating an airway narrowing effect of tobacco smoke. However, a study of 134 asthma patients with airway reversibility showed no difference in baseline FEV1 between smokers and non-smokers, and the salbutamol reversibility was similar [11]. This latter finding has also been confirmed in a few other studies, but, in general, our knowledge of the effect of smoking on the β2-agonist reversibility of airway resistance is sparse.

Conclusion
Smoking affects the results of most of the different clinical asthma tests available, and test results should be interpreted with smoking status in mind. Clinicians should be aware of potential limitations of each test, especially eNO, which decreases in smokers but remains useful, and the mannitol test, which may give false positive in smokers. It remains crucial to obtain an explorative anamnestic interview, involving clarification of symptom triggers, seasonal variation, presence of wheezing, concomitant rhinitis, night symptoms, familiar dispositions, symptom debut, allergies and of course, smoking history.

References
1. Masoli M, Fabian D, Holt S, Beasley R. Allergy. 2004; 59(5): 469-478.
2. Annual global cigarette consumption. http://www.who.int/tobacco/en/atlas8.pdf
3. Alving K, Malinovschi A. Eur Respir Mon 2010; 49: 1-31.
4. Malinovschi A, Janson C, Högman M, Rolla G, Torén K, Norbäck D, Olin AC. Allergy. 2009; 64(1): 55-61.
5. Malinovschi A, Backer V, Harving H, Porsbjerg C. Respir Med. 2012; 106(6): 794–801.
6. Matsunaga K, Hirano T, Akamatsu K, Koarai A, Sugiura H, Minakata Y, Ichinose M. Allergol Int. 2011; 60(3): 331-337.
7. Michils A, Louis R, Peché R, Baldassarre S, Van Muylem A. Eur Respir J. 2009; 33(6): 1295–301.
8. Schleich FN, Seidel L, Sele J, Manise M, Quaedvlieg V, Michils A, Louis R. Thorax. 2010; 65(12): 1039-1044.
9. Sverrild A, Porsbjerg C, Thomsen SF, Backer V. J Allergy Clin Immunol. 2010; 126(5): 952–958.
10. Stolz D, Anderson SD, Gysin C, Miedinger D, Surber C, Tamm M, Leuppi JD. Respir Med. 2007; 101(7): 1470-1476.
11. Chaudhuri R, McSharry C, McCoard A, Livingston E, Hothersall E, Spears M, Lafferty J, Thomson NC. Allergy. 2008; 63(1): 132-135.

The authors
Christian G. Westergaard MD*,
Vibeke Backer MD, DMSc and
Celeste Porsbjerg MD, PhD

Bispebjerg Hospital
Respiratory Research Unit
Bispebjerg Bakke 23, Entrance 66
DK-2400 Copenhagen NV, Denmark
*Corresponding author:
e-mail: cgwestergaard@hotmail.com