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β-Adrenergic Responses in Lymphocytes

The lymphocytes were isolated from peripheral blood obtained under identical basal conditions in all subjects, allowing results from the two studies to be pooled. Unstimulated cAMP accumulation in lymphocyte incubates was similar in the three groups (Table 1). Isoprenaline enhanced cAMP accumulation approximately fivefold, the maximum response being reached at 10-5 M in most experiments (Table 1, Fig 1). The EC50 for isoprenaline varied considerably, but was about 5 to 10xl0“8 M, on the average (Table 1). IBMX enhanced basal and isoprenaline stimulated cAMP accumulation approximately fourfold in all three groups, without changing the EC^-values for isoprenaline. The cAMP-values for the prselective antagonist atenolol were similar in the three groups and four orders of magnitude higher than the cAMP-values for the nonselective (J-adrenoceptor antagonist propranolol (Table 1). Thus, lymphocytes from all three groups of subjects seemed to have a homogenous population of 02-adrenoceptors.

Lymphocytes from EIA patients showed a depressed cAMP response to isoprenaline (p<0.05) as compared to control subjects (Fig 1), whereas the response was normal in lymphocytes from NEIA patients compared to their matched controls (Fig 2), as well as to the entire control group flable 1). The cAMP–values for isoprenaline did not differ significantly between the groups (Table 1). Only one individual in the control group and one in the NEIA group had cAMP»-values for isoprenaline above 7 x 10“8 M (5.6 X10″ and 4.5 X10“7 M, respectively). In the EIA group, six out of 16 individuals had EC^-values for isoprenaline above 7xl0~8 M. Thus, the distribution of ECso-values for isoprenaline tended to be different in the three groups. You should buy asthma ventolin inhalers online only with one purpose to stop your attacks as quick as possible.

Responses to Isoprenaline Infusions

NEIA Patients (Study 1): The NEIA patients and control subjects of study 1 did not have significant bronchoconstriction and were approximately equal with regard to most physiologic variables 30 minutes after the exercise test which was performed in study 1. In this study, isoprenaline infusions were given at two rates (0.02 and 0.1 jig X kg‘1 X min) which produced isoprenaline concentrations in plasma of 0.64 ±0.10 and 3.33±0.87 nM, respectively, in the control group and similar values in the NEIA group. There was no evidence of reduced responsiveness to isoprenaline, ventolin inhalers in vivo in the NEIA group. Thus, heart rate was increased from 77 ±4 to 133 ±2 beats per minute and diastolic blood pressure was reduced from 73 ± 4 to 39 ± 5 mm Hg in the NEIA group. The corresponding figures for their matched controls were 70 ± 4 to 129 ± 6 beats per minute and 77 ±3 to 41 ±4 mm Hg. Similarly, there were no differences between the groups with regard to plasma cAMP or glycerol responses. Since both the in vivo responses and the lymphocyte cAMP responses to isoprenaline (Fig 2) were normal in the NEIA patients, this patient group was not studied further.

EIA Patients (Study 2): The results from isoprenaline infusion tests in study 1, as well as the lymphocyte studies, had suggested that (adrenoceptor responsiveness might be reduced in EIA. Since the EIA patients were not basal at the time of the isoprenaline infusions in study 1, another eight EIA patients were recruited for farther studies of responsiveness to isoprenaline in vivo and in vitro.

Figure 3 summarizes the changes in cAMP and glycerol concentrations in plasma and in heart rate and diastolic blood pressure observed in study 2. The basal values for these and other variables were similar in the two groups, with the exception of Sgaw which was significantly lower in the EIA group (Table 2). Isoprenaline infusions enhanced the isoprenaline concentrations in plasma dose-dependently in both groups, the EIA group achieving somewhat higher concentrations at each dose level (eg, 1.91 ±0.19 vs 1.50±0.25 nM at 0.05 ^gxkg^xmin’). The interindividual variability in isoprenaline concentrations was approximately fivefold to sixfold. It may be seen that the heart rate and plasma glycerol responses to isoprenaline were virtually identical, whereas the plasma cAMP and diastolic depressor responses were significantly attenuated in the EIA group when plasma concentra-don-response curves were compared (Fig 3). If isoprenaline dose-response curves were compared, there was still a significant difference with regard to the diastolic depressor response, but not the plasma cAMP response.

Isoprenaline did not influence airways conductance in the control group, but induced significant bron-chodilatation in the EIA group at the intermediate and high dose levels (Fig 4). Plasma noradrenaline increased similarly in the two groups (to 2.77±0.33 nMin EIA patients and 2.95 ±0.18 nM in controls at the intermediate dose level; no further increase was seen at the high dose level), but adrenaline did not increase during isoprenaline infusions.

Figure 1. Isoprenaline induced accumulation of cAMP in lymphocytes from 16 EIA patients and 15 healthy matched controls. The dose-response curve obtained in the EIA group differed from that obtained in the control group (p<0.05), when compared by analysis of covariance.

Figure 2. Isoprenaline induced accumulation of cAMP in lymphocytes from eight NEIA patients and eight healthy matched control subjects.

Figure 3. Changes in plasma cAMP and glycerol, heart rate (HR) and diastolic blood pressure (DBP) in relation to venous plasma isoprenaline concentrations in eight EIA patients (from study 2) and seven matched healthy control subjects. The p2-mediated responses of plasma cAMP and diastolic blood pressure were significantly reduced in EIA (p<0.05 for both responses when concentration-effect curves were compared by analysis of covariance). The mainly Pr or mixed P^-mediated responses of heart rate and plasma glycerol did not differ between the groups.

Figure 4. Specific airway conductance (Sgaw) in the EIA group of study 2 and their matched control subjects before and during isoprenaline infusion. *p<0.Q5, **p<0.01, as compared to basal values.

Table 1—Results from Lymphocyte Studies in vitro

Control Subjects (n = 15) EIA(n = 16) NEIA (n —8) Basal cAMP (pmol x 10″* cells) 2.9 ±0.4 2.1 ±0.3 1.8±0.6 Isoprenaline stimulated cAMP (pmol x 10″® cells) 12.6±1.2 9.3±1.4 12.3 ±2.2 ECjo for isoprenaline (x 10_8M) 6.7 ±3.5 10.0 ±2.9 9.5±5.0 pAg for atenolol* 5.66 ±0.15 5.75 ±0.07 5.80 ±0.09 pAs for propranolol* 9.76 ±0.02 9.83 ±0.10 9.92 ±0.09

Table 2—Basal Physiologic Data for Subjects in Study 2 (Not Preceded bu Exercise)+

Control Subjects (n = 7) EIA(n = 8) Heart rate (beats/min) 63±3 59 ±2 Diastolic blood pressure (mm Hg) 74 ±2 78 ±2 Respiratory parameters Vital capacity (L) 5.14 ±0.28 5.00 ±0.32 FEV, (L) 4.61 ±0.25 3.80 ±0.25 Sgaw(xs ‘xcmHjO’) 0.159 ±0.018 0.098 ±0.011* Plasma variables Noradrenaline (nM) 1.81 ±0.20 1.80 ±0.36 Adrenaline (nM) 0.07 ±0.01 0.11 ±0.01 Dopamine (nM) 0.08 ±0.01 0.07 ±0.01 Glycerol (|iM) 47 ±6 61 ±11 Cyclic AMP (nM) 16.4 ±0.8 17.2± 1.9

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Monitoring of asthma patients for bronchoconstriction has often relied on the use of pulmonary function tests such as the PEFR. Noninvasive attempts to measure respiratory obstruction have included the use of ear oximetry. Although oximetry is a useful method, it is insensitive except when severe abnormalities are present. It is therefore of limited value in moderate asthma. In the present study, no patient had significant desaturation while asleep.

Martin et al have documented the number of wheezing episodes, night and day, in hospitalized asthmatic patients. They found increased wheezing at night, using wheezing as a measure of airflow obstruction.

We have previously noted that wheeze duration (as a proportion of the respiratory cycle duration: Tw/Ttot) and frequency of the sound signal were associated with the degree of bronchospasm, but wheeze sound intensity was not. We have developed a computer algorithm to establish whether wheezes were or were not present during random samples of the breath cycle, and thus, to estimate the percentage of time in which wheezing occurs. This study demonstrates the correlation between this estimated Tw/Ttot and the level of airways obstruction observed.

Random segments of sound signal were studied to assure that there was no bias towards any portion of the respiratory cycle. A computer program was used to analyze each segment of the sound signal and determine whether a peak was present. However, analysis of sound signals must include other sounds recorded, such as those associated with body movement, speech, and external noises in the room. These noises could contain tones which could lead to mistaking a peak on sound signal analysis as a wheeze. Table 3 shows the results of varying the minimal peak associated with a wheeze. Using the most sensitive value may lead to noise being accepted as wheezing, and thus, an Est Tw/ Ttot which would be inappropriately high. The fact that a relationship is seen between the FEVi and the Est Tw/Ttot at the highest sensitivity is not surprising, since Forgacs et al have noted a correlation between noisy breathing heard at the mouth and obstructive airways disease. On the other hand, if we are too discriminating, we may reject peaks which do represent wheezes. This appears to occur when peaks are counted as wheezes only when nine or more times the baseline. Accepting as wheezes peaks which were three or more times baseline led to a good correlation with FEVX, as well as the one most sensitive to intersubject variation.

Wheezing depends on flow-rate and volume, and the five-minute sample contains breaths which vary in both of these respects. However, over a five-minute time period, this appears to even out. Different sets of 50 samples from a five-minute time period provide similar estimates of Tw/Ttot. Over 30 minutes, there was no significant change in the Est Tw/Ttot for different five-minute periods if the FE Vi remained the same. Do you need to substitute you previous ventolin inhaler? You may do it in one click with our web site – http://buy-asthma-inhalers-online.com/.

Asthma has been shown to follow a circadian pattern in some patients, with the worst obstruction occurring at around 4 am. Several possibilities have been suggested as a cause, including a rise in serum histamine levels with a fall in serum cortisol and epinephrine level.

Our studies are consistent and confirm the worsening of asthma at 4 am. This worsening of bronchospasm was demonstrated without awakening the patient, and therefore, could not be attributed to poor patient compliance in performing a test such as the PEFR.

In summary, we report a method of externally monitoring wheezes. Analysis of the lung sounds for the amount of wheezing in the breath cycle correlated with the FEVi. In the asthmatic patient, more wheezing was noted between 4:00 and 4:30 am than earlier in the evening.

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Asthma is a complex trait that is determined by both genetic and environmental factors. Evidence for genetic predisposition to asthma (and related phenotypes) is derived from family studies, twin studies, adoption studies, and segregation analyses (also see Burkart et al for a more recent review). There is also evidence that different genes influence asthma phenotypes of different racial/ethnic groups. Many candidate genes contributing to the development and expression of asthma have been proposed including gene variants associated with T-cell differentiation and related biological processes (eg, cytokine function and IgE production), genes related to drug response (eg, p-adrenergic receptor and glucocorticoid receptor), and genes important to the handling of environmental toxins (eg, cytochrome P450 and glutathione S-transferase genes). Genetic polymorphisms in the P2-adrenergic receptor have been linked to asthma severity, and the prevalence of functional polymorphisms in the p2-adrenergic receptor gene varies across race.

There are a number of key ideas to keep in mind when considering the genetic determinants of asthma disparities. This significant rise in asthma prevalence and severity over the past 2 to 3 decades, along with the widening disparities is too rapid to be explained by changes in genetic factors. Moreover, it needs to be kept in mind that genetic factors generally determine susceptibility to but not development of the disease. Racial-ethnic variability in the distribution of genetic polymorphisms can also modify the response to environmental exposures that are socially and economically patterned as well as the response to drug treatments. As we increasingly come to understand that the concept of “race” is not a true biological characteristic, we need to avoid simplistic interpretations of intergroup differences or genetic stratification. That is, although race/ ethnicity has been used as a proxy for biology and genetic risk in the past, researchers are increasingly viewing race as more of a social construct. Genetic studies that ignore interactions with broad environmental factors in ethnic minority populations would likely perpetuate the view of race as a biological construct. It is a known fact that you may buy ventolin inhalers online spending on it less time, money and energy.

It is unlikely then that genetic factors alone explain the rise in asthma prevalence or the observed disparities. It is more likely the case that gene-by-gene and gene-by-environment interactions are the crucial determinants of asthma occurrence and severity. Genetic variants that have causal effects but also modify the host response to social and physical environments may not be unique to minority populations and are likely to be common among the general population. Rather, differential exposure to relevant environmental exposures could explain disease disparities. The examination of the main effects of genes and interactions between genes and environmental factors will more likely inform the discernment of common final pathways to asthma disparities. From the perspective of health disparities, this means that both the environmental exposure and the genetic factor will be critical determinants in the causation pathway of the disease, Subjects who are exposed to toxins that are more highly prevalent in urban communities (eg, stress, smoking, aeroallergens, and diesel exhaust) and carry the genetic variants will have the greatest increased risk of disease, whereas subjects who are exposed to the toxins but do not have the genetic variant will have only a modestly increased risk of disease, Thus, applying genetic knowledge about asthma to reducing asthma disparities will require sophisticated strategies based on the role of both significant genetic and relevant social and physical environmental risk factors, No amount of progress in understanding the genetic factors underlying asthma etiology and response to treatment will help to reduce health disparities unless racial/ ethnic/SES disparities in exposure to risk-related social and environmental factors are concomitantly addressed.

Need for a Multilevel Perspective

The etiology of health problems is increasingly recognized as a result of the complex interplay of influences operating at several levels, including the individual, the family, and the community. As part of this growing complexity, evidence supports the notion that connections between health and economic well-being are embedded within the larger context of people’s lives,102Д03 The profound question, initially raised in the context of cancer, is, what gets asthma? Is it the cell, gene, organ, individual, household, population subgroup, or community? Indeed, the potential answers are rarely exclusive,> As reviewed above, more recently observed epidemiologic trends suggest that asthma may provide an excellent paradigm for understanding the role of community-level contextual factors in disease, Specifically, a multilevel approach that includes an ecological perspective may help to explain heterogeneities in asthma expression across socioeconomic and geographic boundaries that to date have remained largely unexplained (Fig 1).

Traditionally, asthma epidemiology has focused on individual-level risk factors and family factors, Far less attention has been given to the broader social context in which individuals live, Although it is beyond the scope of the current discussion given the space limitations, one also must consider the developmental timing of exposures over the course of a lifetime relative to specific asthma outcomes, whether individual or contextual factors are being considered. Factors leading to the onset, remission, or persistence of asthma across the course of a lifetime may be influenced by physical exposures and social experiences beginning in utero, a series of social and biological experiences initiated by early childhood exposure, or cumulative exposure to toxic biological or social factors over critical periods of development.

Could Neighborhood Context Be a Source in Producing Social Disparities in Asthma?

There is evidence that the risk factors associated with asthma, which were outlined earlier, are unevenly distributed across communities and neighborhoods. The failure to view these risk factors within its context can be limiting. Neighborhood contexts, defined by their characteristics related to socioeconomic disadvantage, physical conditions, and social processes, may play a critical role in accounting for the social disparities in asthma. Indeed, each of the risk factors (eg, exposure to indoor allergens, outdoor pollution, and smoking) that were discussed in the previous sections is likely to be distributed disproportionately across populations as well as communities and neighborhoods. At the same time, there has been growing interest in the potential role of the social environment in both health and psychological processes. This is a useful way to conceptualize environmental influences on health whether one operationalizes the environment as a social or a physical construct. Both physical and social factors can be a source of environmental demands that contribute to the stress experienced by populations living in a particular area. Bridging such theoretical constructs with research into asthma disparities is timely, given the convergence with advances in understanding the influences of psychological stress on the development and expression of asthma. Structurally disadvantaged neighborhoods may not only generate clustering of physical risk factors but may also act as a stressor inducing, for instance, individuals to smoke. Neighborhood structural disadvantage may also contribute to the level of sociophysical disorder in the community, including violence, which may, in turn, influence asthma, as reviewed in more detail below.

The potential import of such a framework stems from a number of observations. Notably, asthma trends are consistent with an inverse association between SES and adverse health outcomes found for many diseases. Explanations of such a ubiquitous socioeconomic gradient in health together with the observation that it is capable of replicating itself on new disease processes as they emerge in society calls for an understanding of how humans can become generally vulnerable or resilient to disease over time. This argues for the consideration of not only physical factors that alter biological processes but also how psychosocial conditions get into the body. Chronic stress may be a pervasive environmental factor imposed on already vulnerable popu-lations, resulting in an enhanced biological response to known physical environmental exposures. Mechanisms linking psychological stress, personality, and emotion to atopic disease continue to be elucidated and have been reviewed elsewhere. Moreover, the effects of environmental toxins (ie, air pollution and tobacco smoke) on atopy and asthma may be mediated by the common pathway of oxidative stress, a process that may be potentiated by chronic psychological stress. Further research is needed to examine these relationships.

Ecological views on health recognize that individual-level health risks and behaviors have multilevel determinants, which are in part influenced by the social context within which subjects live. Emerging scholarship on how social environments “get under the skin” to influence health suggests that psychological factors play a key role. That is, the degree of chronic stress is significantly influenced by the characteristics of the families, homes, and communities in which we live. Indicators of neighborhood disadvantage (ND) that may lead to chronic stress have been investigated in relation to urban children’s development. ND, characterized by the presence of a number of area-level stressors including poverty, unemployment/underemployment, percentage of unskilled laborers, limited social capital or social cohesion, substandard housing, and high crime/violence exposure rates. Such stress is chronic and can affect all subjects in a given environment regardless of their individual-level risks. In the United States, many urban communities are characterized by high ND levels. Evidence from social epidemiology on the determinants of health disparities among racial and ethnic minorities and low-SES populations points to the powerful influence of community characteristics in promoting health and well-being. One potential mediating feature of community life that has generated considerable attention is the concept of “social capital.” Social capital, and related constructs such as social cohesion, have been to linked to economic development, investment in public goods such as education, and crime/violence rates in a community.

Our previous work has identified violence exposure as a prevalent factor that concerns residents of Boston communities and, in turn, has linked violence exposure to asthma morbidity.> Violence serves as a good example of these social processes that may be impacting health. Social capital is strongly correlated with violent crime rates, which impacts community resilience by undermining social cohesion. Thus, crime and violence (or the lack of it) can be used as indicators of collective well-being, social relations, or social cohesion within a community and society. Violent victimization is a major cause of childhood morbidity in urban America. The rates of experiencing and witnessing serious and lethal violence among inner-city youth are also high.135 A prevalence study in a pediatric primary care clinic at Boston City Hospital found that 10% of children had witnessed a knifing or shooting before the age of 6 years; 18% had witnessed shoving, kicking, or punching; and 47% had reported hearing gunshots in their neighborhood. In a preadolescent sample in Boston, our group found that 61% had witnessed shoving, kicking, or punching; 8% had witnessed a stabbing or shooting; and 21% reported hearing gunshots in their communities.

Figure 1. A multilevel approach including an ecological perspective to explain heterogeneities in asthma expression across socioeconomic and geographic boundaries.