Parental mental health, socioeconomic position and the risk of asthma in children-a nationwide Danish register study

BACKGROUND: Parental mental illness affects child health. However, less is known about the impact of different severities of maternal depression and anxiety as well as other mental health conditions. The objective of this study was to examine the impact of different severities of maternal and paternal mental health conditions on child asthma. METHODS: This nationwide, register-based cohort study included all children in Denmark born from 2000 to 2014. Exposure was parental mental health conditions categorized in three severities: minor (treated at primary care settings), moderate (all ICD-10 F-diagnoses given at psychiatric hospital) and severe (diagnoses of severe mental illness). The children were followed from their third to sixth birthday. Child asthma was identified by prescribed medication and hospital-based diagnoses. Incidence rate ratios were calculated using negative binomial regression analyses. RESULTS: The analyses included 925 288 children; 26% of the mothers and 16% of the fathers were classified with a mental health condition. Exposed children were more likely to have asthma (10.6-12.0%) compared with unexposed children (8.5-9.0%). The three severities of mental health conditions of the mother and the father increased the risk of child asthma, most evident for maternal exposure. Additive interaction between maternal mental health conditions and disadvantaged socioeconomic position was found. CONCLUSION: We found an increased risk of asthma in exposed children, highest for maternal exposure. Not only moderate and severe, but also minor mental health conditions increased the risk of child asthma. The combination of mental health condition and disadvantaged socioeconomic position for mothers revealed a relative excess risk

Lung function indices for predicting mortality in COPD

Chronic obstructive pulmonary disease (COPD) is characterised by high morbidity and mortality. It remains unknown which aspect of lung function carries the most prognostic information and if simple spirometry is sufficient. Survival was assessed in COPD outpatients whose data had been added prospectively to a clinical audit database from the point of first full lung function testing including spirometry, lung volumes, gas transfer and arterial blood gases. Variables univariately associated with survival were entered into a multivariate Cox proportional hazard model. 604 patients were included (mean±sd age 61.9±9.7 years; forced expiratory volume in 1 s 37±18.1% predicted; 62.9% males); 229 (37.9%) died during a median follow-up of 83 months. Median survival was 91.9 (95% CI 80.8–103) months with survival rates at 3 and 5 years 0.83 and 0.66, respectively. Carbon monoxide transfer factor % pred quartiles (best quartile (>51%): HR 0.33, 95% CI 0.172–0.639; and second quartile (51–37.3%): HR 0.52, 95% CI 0.322–0.825; versus lowest quartile (<27.9%)), age (HR 1.04, 95% CI 1.02–1.06) and arterial oxygen partial pressure (HR 0.85, 95% CI 0.77–0.94) were the only parameters independently associated with mortality. Measurement of gas transfer provides additional prognostic information compared to spirometry in patients under hospital follow-up and could be considered routinely

Dynamic regulation of the endocannabinoid system: implications for analgesia

The analgesic effects of cannabinoids are well documented, but these are often limited by psychoactive side-effects. Recent studies indicate that the endocannabinoid system is dynamic and altered under different pathological conditions, including pain states. Changes in this receptor system include altered expression of receptors, differential synthetic pathways for endocannabinoids are expressed by various cell types, multiple pathways of catabolism and the generation of biologically active metabolites, which may be engaged under different conditions. This review discusses the evidence that pain states alter the endocannabinoid receptor system at key sites involved in pain processing and how these changes may inform the development of cannabinoid-based analgesics

Emergent dynamic chirality in a thermally driven artificial spin ratchet

Modern nanofabrication techniques have opened the possibility to create novel functional materials, whose properties transcend those of their constituent elements. In particular, tuning the magnetostatic interactions in geometrically frustrated arrangements of nanoelements called artificial spin ice1, 2 can lead to specific collective behaviour3, including emergent magnetic monopoles4, 5, charge screening6, 7 and transport8, 9, as well as magnonic response10, 11, 12. Here, we demonstrate a spin-ice-based active material in which energy is converted into unidirectional dynamics. Using X-ray photoemission electron microscopy we show that the collective rotation of the average magnetization proceeds in a unique sense during thermal relaxation. Our simulations demonstrate that this emergent chiral behaviour is driven by the topology of the magnetostatic field at the edges of the nanomagnet array, resulting in an asymmetric energy landscape. In addition, a bias field can be used to modify the sense of rotation of the average magnetization. This opens the possibility of implementing a magnetic Brownian ratchet13, 14, which may find applications in novel nanoscale devices, such as magnetic nanomotors, actuators, sensors or memory cells

Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches