Panniculitis in childhood and adolescence

Background: The purpose of the present paper was to describe the clinical manifestations and treatment of patients with panniculitis. Methods: From January 1983 to December 2002, 4294 patients were treated for pediatric rheumatological diseases at Pediatric Rheumatology Unit, University of São Paulo, Brazil. Of these, 35 children and adolescents (0.8%) presented with panniculitis: erythema nodosum (EN) or Weber–Christian disease (WCD). Clinical characteristics, laboratory exams, biopsy of the lesion, treatment and clinical course were studied. Results: Of the 35 patients, 29 presented with EN and six with WCD, one of these with cytophagic histiocytic panniculitis. Mean age at symptom onset was 85 months (6–204 months) and the mean duration of follow up was 55 months (1–144 months). All the patients presented with inflammatory subcutaneous nodules. The patients with WCD presented with systemic manifestations and cutaneous atrophy. The principal etiologies of EN were streptococcal infection (42%), undetermined (13.5%), pulmonary tuberculosis (10%), and acute rheumatic fever (10%). Biopsy of the nodules indicated septal panniculitis in 14 patients with EN and lobular panniculitis without vasculitis in the patients with WCD, one of which had cytophagic histiocytic panniculitis. There was recurrence in 11 patients (38%) with EN and in all those with WCD. Non‐steroidal anti‐inflammatory drugs were used in 15 patients with EN and corticosteroids and/or immunosuppressive drugs in the six patients with WCD. Three patients died. Conclusions: EN is the most frequent panniculitis, with a benign course and is mainly associated with infections. WCD is a severe disease, with systemic involvement, that proceeds with cutaneous atrophy and requires the use of corticosteroids and or immunosuppressive drugs.     

Childhood obesity increases duration of therapy during severe asthma exacerbations.

OBJECTIVES: Childhood obesity contributes to a wide array of medical conditions, including asthma. There is also increasing evidence in adult patients admitted to the intensive care unit (ICU) that obesity contributes to increased morbidity and to a prolonged length of stay. We hypothesized that obesity is associated with the need for increased duration of therapy in children admitted to the ICU with status asthmaticus. DESIGN: Retrospective cohort study. SETTING: A tertiary pediatric ICU in a university-affiliated children's hospital. PATIENTS: We retrospectively examined data from all children older than 2 yrs admitted to the ICU with status asthmaticus between April 1997 and June 2004. Children were classified as normal weight (<95% weight-for-age percentile) or obese (>95% weight-for-age). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of the 209 children admitted to the ICU with asthma, 45 (22%) were obese. Compared with children of normal weight, the obese children were older (9.7 +/- 4.4 vs. 8.0 +/- 4.3 yrs, p = .02), more likely to be female (60% vs. 37%, p < .01), and more likely to have been admitted to the ICU previously (40% vs. 20%, p = .01). The obese children also had a statistically significant difference in race (more likely to be Hispanic) and in baseline asthma classification (more likely to have persistent asthma). Despite similar severity of illness at ICU admission, obese children had a significantly longer ICU length of stay (116 +/- 125 hrs vs. 69 +/- 57 hrs, p = .02) and hospital length of stay (9.8 +/- 7.0 vs. 6.5 +/- 3.4 days, p < .01). Obese children also received longer courses of supplemental oxygen, continuous albuterol, and intravenous steroids. CONCLUSIONS: Childhood obesity significantly affects the health of children with asthma. Obese children with status asthmaticus recovered more slowly from an acute exacerbation, even after adjustment for baseline asthma severity and admission severity of illness.     

Positive association of farm or rural residence with acute myeloid leukemia incidence in a cohort of older women.

The etiology of acute myeloid leukemia (AML) is relatively unknown. Incidence rates are highest in the agricultural Midwest region compared with other regions of the United States. Many studies have examined the relationship between farming and leukemia, but most have mainly focused on men. We examined the potential association between farm or rural residence and AML in the Iowa Women's Health Study. In 1986, 37,693 women who were free of prior cancer completed a lifestyle and health questionnaire, which included a question on the place of residence. Women were subsequently followed until 2002 for cancer incidence; 79 women developed AML during the time period. Women who lived on a farm at baseline were more likely (relative risk, 1.91; 95% confidence interval, 1.19-3.05) to develop AML compared with women who did not live on a farm. Further, women who reported living on a farm or in a rural area were twice as likely (relative risk, 2.38; 95% confidence interval, 1.33-4.26) to develop AML compared with women who lived in a city with a population of >10,000 people. These results provide evidence that women who live on farms or rural areas are at an increased risk of AML.     

The cyclooxygenase-2 product prostaglandin E2 modulates cardiac contractile function in adult rat ventricular cardiomyocytes.

Prostaglandin E(2) (PGE(2)), a product of the cyclooxygenase-2 pathway, has been shown to increase cardiac output and modulate cardiac contractile function. However, whether the cardiac contractile response of PGE(2) is due to its action on single ventricular myocytes has not been elucidated. To assess the mechanical effect of PGE(2) at the cellular level, adult rat ventricular myocytes were isolated and stimulated to contract at 0.5Hz. Mechanical and intracellular Ca(2+) properties were evaluated using an IonOptix Myocam analog-to-digital optical detection system. Contractile and intracellular Ca(2+) properties were evaluated as peak shortening (PS), time-to-PS (TPS), time-to-90% relengthening (TR(90)), maximal velocity of shortening or relengthening (+/-dL/dt) and Ca(2+)-induced intracellular Ca(2+) fluorescence release (CICR), baseline intracellular Ca(2+) levels and intracellular Ca(2+) decay rate (tau). PGE(2) (10(-8) to 10(-3)M) elicited an augmentation in PS but had no effect on TPS, TR(90), +/-dL/dt, CICR and tau. High concentration of PGE(2) (10(-5)M or higher) reduced the baseline intracellular Ca(2+) levels. These data indicate that the myocardial contractile response of PGE(2) may be due to its direct cardiac contractile action at the single ventricular myocyte level, probably through a mechanism independent of intracellular Ca(2+) release.     

Mammographic density and risk of breast cancer by age and tumor characteristics

Introduction

Understanding whether mammographic density (MD) is associated with all breast tumor subtypes and whether the strength of association varies by age is important for utilizing MD in risk models.

Methods

Data were pooled from six studies including 3414 women with breast cancer and 7199 without who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2)) status by age (<55, 55–64, and ≥65 years).

Results

MD was positively associated with risk of invasive tumors across all ages, with a two-fold increased risk for high (>51%) versus average density (11-25%). Women ages <55 years with high MD had stronger increased risk of ductal carcinoma in situ (DCIS) compared to women ages 55–64 and ≥65 years (P_{age-interaction} = 0.02). Among all ages, MD had a stronger association with large (>2.1 cm) versus small tumors and positive versus negative lymph node status (P’s < 0.01). For women ages <55 years, there was a stronger association of MD with ER-negative breast cancer than ER-positive tumors compared to women ages 55–64 and ≥65 years (P_{age-interaction} = 0.04). MD was positively associated with both HER2-negative and HER2-positive tumors within each age group.

Conclusion

MD is strongly associated with all breast cancer subtypes, but particularly tumors of large size and positive lymph nodes across all ages, and ER-negative status among women ages <55 years, suggesting high MD may play an important role in tumor aggressiveness, especially in younger women.     

Expectation effects in working memory training

There is a growing body of research focused on developing and evaluating behavioral training paradigms meant to induce enhancements in cognitive function. It has recently been proposed that one mechanism through which such performance gains could be induced involves participants’ expectations of improvement. However, no work to date has evaluated whether it is possible to cause changes in cognitive function in a long-term behavioral training study by manipulating expectations. In this study, positive or negative expectations about cognitive training were both explicitly and associatively induced before either a working memory training intervention or a control intervention. Consistent with previous work, a main effect of the training condition was found, with individuals trained on the working memory task showing larger gains in cognitive function than those trained on the control task. Interestingly, a main effect of expectation was also found, with individuals given positive expectations showing larger cognitive gains than those who were given negative expectations (regardless of training condition). No interaction effect between training and expectations was found. Exploratory analyses suggest that certain individual characteristics (e.g., personality, motivation) moderate the size of the expectation effect. These results highlight aspects of methodology that can inform future behavioral interventions and suggest that participant expectations could be capitalized on to maximize training outcomes.

There is a great deal of current scientific interest as to whether and/or how basic cognitive skills can be improved via dedicated behavioral training (1–3). This potential, if realized, could lead to substantial real-world impact. Indeed, effective training paradigms would have significant value not only for populations that show deficits in cognitive skills (e.g., individuals diagnosed with Attention Deficit Hyperactivity Disorder [ADHD] or Alzheimer’s disease and related dementias) but also, for the general public, where core cognitive capacities underpin success in both academic and professional contexts (4–6). These possible translational applications, paired with an emerging understanding of how to best unlock neuroplastic change across the life span (7, 8), have spurred hundreds of behavioral intervention studies over the past few decades. While the results have not been uniformly positive (perhaps not surprising given the massive heterogeneity in theoretical approach, methods, etc.), multiple meta-analyses suggest that it is possible for cognitive functions to be improved via some forms of dedicated behavioral training (9–11). However, while these basic science results provide optimism that real-world gains could be realized [and in fact, real-world gain is already being realized in some spheres, such as a Food and Drug Administration (FDA)–cleared video game–based treatment supplement for ADHD (12, 13)], concerns have been raised as to whether those interventions that have produced positive outcomes are truly working via the proposed mechanisms or through other nonspecific third-variable mechanisms. Several factors have been proposed to explain improvements in behavioral interventions, including selective attrition, contextual factors, regression to the mean, and practice effects to name a few (14). Here, we focus on whether expectation-based (i.e., placebo) mechanisms can explain improvements in cognitive training (15–17).In other domains, such as in clinical trials in the pharmaceutical domain for instance, expectation-based mechanisms are typically controlled for by making the experimental treatment and the control treatment perceptually indistinguishable (e.g., both might be clear fluids in an intravenous bag or a white unmarked pill). Because perceptual characteristics cannot be used to infer condition, this methodology is meant to ensure that expectations are matched between the experimental and control groups (both in terms of the expectations that the participants have and in terms of the expectations that the research team members who interact with the participants have). Under ideal circumstances, the use of such a “double-unaware” design ensures that expectations cannot be an explanatory mechanism underlying any differences between the groups’ outcomes [note that we use the double-unaware terminology in lieu of the more common “double-blind” terminology, which can be seen as ableist (18)].It is unclear whether most pharmaceutical trials do, in fact, truly meet the double-unaware standard (e.g., despite being perceptually identical, active and control treatments nonetheless often produce different patterns of side effects that could be used to infer condition) (19, 20). Yet, meeting the double-unaware standard is particularly difficult in the case of cognitive training interventions (16). Here, there is simply no way to make the experimental and control interventions perceptually indistinguishable while at the same time, ensuring that the experimental condition contains an “active ingredient” that the control condition lacks. In behavioral interventions, no matter what the active ingredient may be, it will necessarily produce a difference in look and feel as compared with a training condition that lacks the ingredient.Researchers designing cognitive training trials, therefore, typically attempt to utilize experimental and control conditions that, while differing in the proposed active ingredient, will nonetheless produce similar expectations about the likely outcomes (16, 21–24). This type of matching process, however, is inherently difficult as it is not always clear what expectations will be induced by a given type of experience. Consistent with this, there is reason to believe that expectations have not always been successfully matched. In multiple cases, despite attempts to match expectations across conditions, participants in behavioral intervention studies have nonetheless indicated the belief that the true active training task will produce more cognitive gains than the control task (25–27). Critically, the data as to whether differential expectations in these cases actually, in turn, influence the observed outcomes are decidedly mixed. In some cases, participant expectations differed between training and control conditions, and these expectations were at least partially related to differences in behavior (25). In other cases, participants expected to improve but did not show any actual improvements in cognitive skill (28), or the degree to which they improved was unrelated to their stated expectations (29).Regardless of the mixed nature of the data thus far, there is increasing consensus that training studies should 1) attempt to match the expectations generated by their experimental and control treatment conditions, 2) measure the extent to which this matching is successful and if the matching was not successful, and 3) evaluate the extent to which differential expectations explain differences in outcome (16, 30). Yet, such methods are not ideal with respect to getting to the core question of whether expectation-based mechanisms can, in fact, alter performance on cognitive tasks in the context of cognitive intervention studies in the first place. Indeed, there is a growing body of work suggesting that self-reported expectations do not necessarily fully reflect the types of predictions being generated by the brain (e.g., it is possible to produce placebo analgesia effects even in the absence of self-reported expectation of pain relief) (31, 32). Instead, addressing this question would entail purposefully maximizing the differences in expectations between groups (i.e., rather than attempting to minimize differential expectations and then, measuring the possible impact if the differences were not eliminated, as is done in most cognitive training studies).One key question then is how to maximize such expectations. In general, in those domains that have closely examined placebo effects, expectations are typically induced through two broad routes: an explicit route and an associative route. In the explicit route, as given by the name, participants are explicitly told what behavioral changes they should expect (e.g., “this pill will improve your symptoms” or “this cognitive training will improve your cognition”) (33). In the associative learning route, participants are made to experience a behavioral change associated with expected outcomes (e.g., feeling improvements of symptoms or gains in cognition) through some form of deception (34). For example, in an explicit expectation induction study, participants may first have a hot temperature probe applied to their skin, after which they are asked to rate their pain level. An inert cream is then applied that is explicitly described as an analgesic before the hot temperature probe is reapplied. If participants indicate less pain after the cream is applied, this is taken as evidence of an explicit expectation effect. In the associative expectation version, the study progresses identically as above except that when the hot temperature probe is applied the second time, it is at a physically lower temperature than it was initially (participants are not made aware of this fact). This is meant to create an associative pairing between the cream and a reduction in experienced pain (i.e., not only are they told that the cream will reduce their pain, they are provided “evidence” that the cream works as described). If then, after reapplying the cream and applying the hot temperature probe a third time (this time at the same temperature setting as the first application), if participants indicate even less pain than in the explicit condition, this is taken as evidence of an associative expectation effect. It remains to be clarified how associative learning approaches may be best applied to cognitive training; however, we suggest here that a reasonable approach to this would be to provide test sessions where test items are manipulated to provide participants with an experience where they perceive that they are performing better, or worse in the case of a nocebo, than they did at the initial test session. Notably, while there are cases where strong placebo effects have been induced via only explicit (35) or only associative methods (36), in general, the most consistent and robust effects have been induced when a combination of these methods has been utilized (37–39).Within the cognitive training field, the corresponding literature is quite sparse. Few studies have deliberately attempted to create differences in participant expectations, and of those, all have used the explicit expectation route alone, have implemented the manipulation in the context of rather short interventions (e.g., utilizing 20 min of “training” within a single session rather than the multiple hours that are typically implemented in actual training studies), or both. Of these, the results are again at best mixed, with one study suggesting that expectations alone can result in a positive impact on cognitive measures (40), while others have found no such effects (33, 41, 42). Given this critical gap in knowledge, here we examined the impact of manipulations deliberately designed to maximize the presence of differential expectations in the context of a long-term cognitive training study.