The impact of geographic unit of analysis on socioeconomic inequalities in cancer survival and distant summary stage – a population‐based study

Objective: When using area‐level disadvantage measures, size of geographic unit can have major effects on recorded socioeconomic cancer disparities. This study examined the extent of changes in recorded socioeconomic inequalities in cancer survival and distant stage when the measure of socioeconomic disadvantage was based on smaller Census Collection Districts (CDs) instead of Statistical Local Areas (SLAs). Methods: Population‐based New South Wales Cancer Registry data were used to identify cases diagnosed with primary invasive cancer in 2000–2008 (n=264,236). Logistic regression and competing risk regression modelling were performed to examine socioeconomic differences in odds of distant stage and hazard of cancer death for all sites combined and separately for breast, prostate, colorectal and lung cancers. Results: For all sites collectively, associations between socioeconomic disadvantage and cancer survival and distant stage were stronger when the CD‐based socioeconomic disadvantage measure was used compared with the SLA‐based measure. The CD‐based measure showed a more consistent socioeconomic gradient with a linear upward trend of risk of cancer death/distant stage with increasing socioeconomic disadvantage. Site‐specific analyses provided similar findings for the risk of death but less consistent results for the likelihood of distant stage. Conclusions: The use of socioeconomic disadvantage measure based on the smallest available spatial unit should be encouraged in the future. Implications for public health: Disadvantage measures based on small spatial units can more accurately identify socioeconomic cancer disparities to inform priority settings in service planning.     

Suppression of Anti-Inflammatory Mediators in Metabolic Disease May Be Driven by Overwhelming Pro-Inflammatory Drivers

Obesity is a multifactorial disease and is associated with an increased risk of developing metabolic syndrome and co-morbidities. Dysregulated expansion of the adipose tissue during obesity induces local tissue hypoxia, altered secretory profile of adipokines, cytokines and chemokines, altered profile of local tissue inflammatory cells leading to the development of low-grade chronic inflammation. Low grade chronic inflammation is considered to be the underlying mechanism that increases the risk of developing obesity associated comorbidities. The glucocorticoid induced protein annexin A1 and its N-terminal peptides are anti-inflammatory mediators involved in resolving inflammation. The aim of the current study was to investigate the role of annexin A1 in obesity and associated inflammation. To achieve this aim, the current study analysed data from two feasibility studies in clinical populations: (1) bariatric surgery patients (Pre- and 3 months post-surgery) and (2) Lipodystrophy patients. Plasma annexin A1 levels were increased at 3-months post-surgery compared to pre-surgery (1.2 ± 0.1 ng/mL, n = 19 vs. 1.6 ± 0.1 ng/mL, n = 9, p = 0.009) and positively correlated with adiponectin (p = 0.009, r = 0.468, n = 25). Plasma annexin A1 levels were decreased in patients with lipodystrophy compared to BMI matched controls (0.2 ± 0.1 ng/mL, n = 9 vs. 0.97 ± 0.1 ng/mL, n = 30, p = 0.008), whereas CRP levels were significantly elevated (3.3 ± 1.0 µg/mL, n = 9 vs. 1.4 ± 0.3 µg/mL, n = 31, p = 0.0074). The roles of annexin A1 were explored using an in vitro cell based model (SGBS cells) mimicking the inflammatory status that is observed in obesity. Acute treatment with the annexin A1 N-terminal peptide, AC2-26 differentially regulated gene expression (including PPARA (2.8 ± 0.7-fold, p = 0.0303, n = 3), ADIPOQ (2.0 ± 0.3-fold, p = 0.0073, n = 3), LEP (0.6 ± 0.2-fold, p = 0.0400, n = 3), NAMPT (0.4 ± 0.1-fold, p = 0.0039, n = 3) and RETN (0.1 ± 0.03-fold, p < 0.0001, n = 3) in mature obesogenic adipocytes indicating that annexin A1 may play a protective role in obesity and inflammation. However, this effect may be overshadowed by the continued increase in systemic inflammation associated with rapid tissue expansion in obesity.     

ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive–compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.     

The spatial chronnectome reveals a dynamic interplay between functional segregation and integration

The brain is highly dynamic, reorganizing its activity at different interacting spatial and temporal scales, including variation within and between brain networks. The chronnectome is a model of the brain in which nodal activity and connectivity patterns change in fundamental and recurring ways over time. Most literature assumes fixed spatial nodes/networks, ignoring the possibility that spatial nodes/networks may vary in time. Here, we introduce an approach to calculate a spatially fluid chronnectome (called the spatial chronnectome for clarity), which focuses on the variations of networks coupling at the voxel level, and identify a novel set of spatially dynamic features. Results reveal transient spatially fluid interactions between intra‐ and internetwork relationships in which brain networks transiently merge and separate, emphasizing dynamic segregation and integration. Brain networks also exhibit distinct spatial patterns with unique temporal characteristics, potentially explaining a broad spectrum of inconsistencies in previous studies that assumed static networks. Moreover, we show anticorrelative connections to brain networks are transient as opposed to constant across the entire scan. Preliminary assessments using a multi‐site dataset reveal the ability of the approach to obtain new information and nuanced alterations that remain undetected during static analysis. Patients with schizophrenia (SZ) display transient decreases in voxel‐wise network coupling within visual and auditory networks, and higher intradomain coupling variability. In summary, the spatial chronnectome represents a new direction of research enabling the study of functional networks which are transient at the voxel level, and the identification of mechanisms for within‐ and between‐subject spatial variability.     

BDNF Is Needed for Postnatal Maturation of Basal Forebrain and Neostriatum Cholinergic Neurons In Vivo

Neurotrophins regulate survival, neurite outgrowth, and phenotypic maturation of developing neurons. Brain-derived neurotrophic factor (BDNF) can promote the survival of developing cholinergic forebrain neurons in vitro and reduce their degeneration following injury in adult rats. We investigated the role of endogenous BDNF during postnatal development of these cholinergic neurons by analyzing homozygous BDNF-deficient (−/−) mice and their littermates (+/+, +/−). At P6, the number of choline acetyltransferase- (ChAT) positive neurons in the medial septum was 23% lower in BDNF−/− mice, although their brain and body weight was normal. At P15, control (+/+) littermates had 45% more and 45% larger ChAT-positive neurons and a much denser cholinergic hippocampal innervation than at P6, indicative of maturation of the septohippocampal system. In BDNF−/− mice, the number, size, and ChAT-immunostaining intensity of the cholinergic neurons remained the same between P6 and P15 (few mice survive longer). BDNF−/− mice had about three times more TUNEL-labeled (a marker of apoptosis) cells in the medial septum at P6, consistent with (but not proof of) the possibility that the cholinergic neurons were dying. The cholinergic hippocampal innervation in BDNF−/− mice expanded to a lesser extent than in controls and had reduced levels of acetylcholinesterase staining at P15. The developmental deficits were largely similar in the neostriatum of BDNF−/− mice. These findings suggest that BDNF is critical for postnatal development and maturation of cholinergic forebrain neurons.     

Epidemiological modelling (including economic modelling) and its role in preventive drug therapy

In contrast to curative therapies, preventive therapies are administered to largely healthy individuals over long periods. The risk-benefit and cost-benefit ratios are more likely to be unfavourable, making treatment decisions difficult. Drug trials provide insufficient information for treatment decisions, as they are conducted on highly selected populations over short durations, estimate only relative benefits of treatment and offer little information on risks and costs. Epidemiological modelling is a method of combining evidence from observational epidemiology and clinical trials to assist in clinical and health policy decision-making. It can estimate absolute benefits, risks and costs of long-term preventive strategies, and thus allow their precise targeting to individuals for whom they are safest and most cost-effective. Epidemiological modelling also allows explicit information about risks and benefits of therapy to be presented to patients, facilitating informed decision-making.     

ADHD and cannabis use in young adults examined using fMRI of a Go/NoGo task

Children diagnosed with attention-deficit/hyperactivity disorder (ADHD) are at increased risk for substance abuse. Response inhibition is a hallmark of ADHD, yet the combined effects of ADHD and regular substance use on neural networks associated with response inhibition are unknown. Task-based functional Magnetic Resonance Imaging (fMRI) data from young adults with childhood ADHD with (n?=?25) and without (n?=?25) cannabis use ≥ monthly in the past year were compared with a local normative comparison group (LNCG) with (n?=?11) and without (n?=?12) cannabis use. Go/NoGo behavioral and fMRI data were evaluated for main and interaction effects of ADHD diagnosis and cannabis use. ADHD participants made significantly more commission errors on NoGo trials than controls. ADHD participants also had less frontoparietal and frontostriatal activity, independent of cannabis use. No main effects of cannabis use on response inhibition or functional brain activation were observed. An interaction of ADHD diagnosis and cannabis use was found in the right hippocampus and cerebellar vermis, with increased recruitment of these regions in cannabis-using controls during correct response inhibition. ADHD participants had impaired response inhibition combined with less fronto-parietal/striatal activity, regardless of cannabis use history. Cannabis use did not impact behavioral response inhibition. Cannabis use was associated with hippocampal and cerebellar activation, areas rich in cannabinoid receptors, in LNCG but not ADHD participants. This may reflect recruitment of compensatory circuitry in cannabis using controls but not ADHD participants. Future studies targeting hippocampal and cerebellar-dependent function in these groups may provide further insight into how this circuitry is altered by ADHD and cannabis use.     

One enzyme for the 5′-deiodination of 3,3′,5′-triiodothyronine and 3′,5′-diiodothyronine in rat liver

Many studies suggest that one enzyme is involved in the phenolic ring deiodination of iodothyronines in rat liver and kidney and another one in the tyrosyl ring deiodination. This study describes some characteristics of the phenolic ring (5′-) deiodination of rT₃ and 3′,5′-T₂ by rat liver microsomes. At pH 7.2 the K_m values of the 5′-deiodination of rT₃ and 3′,5′-T₂ were 0.103 and 0.77 μM, respectively. 3′,5′-T₂ and rT₃ inhibited the respective 5′-deiodination reactions competitively, the K_i values being 1.05 and 0.134 μM, respectively. Several radiographic contrast agents markedly inhibit the 5′-monodeiodination of rT₃ and 3′,5′T-₂, the type of inhibition being competitive. Of these compounds iopanoic acid, ipodic acid and iophenoxic acid are the most potent inhibitors with K_i values of approximately 2 μM for both reactions. The non-iodine containing compound 8-anilino-1-naphthalene sulphonic acid (ANS) appeared to be a very strong competitive inhibitor of both 5′-deiodinations (K_i 4.3–4.7 μM), whereas salicylic acid, which as ANS inhibits the binding of iodothyronines to T₄-binding globulin, inhibited these reactions to a much lesser extent (K_i 300–500 μM). On the other hand, diiodosalicylic acid was a very strong inhibitor. The β-adrenergic blocker d,l-propranolol was a weak noncompetitive inhibitor of both 5′-deiodinations (K_i 0.4–0.7 mM). These reactions were also inhibited by various 2,6-diiodophenol derivatives, triiodophenol being the strongest and diiodotyrosine the weakest inhibitor tested. Comparing the K_i values of various inhibitors for the 5′-deiodination of rT₃ and 3′,5′-T₂, a positive correlation between these values was found (r = 0.97). It was concluded that rT₃ (to 3,3′-T₂) and 3′,5′-T₂ (to 3′-T₁) monodeiodinating activities are very similar to each other and that there may just be one monodeiodinase catalyzing the 5′-deiodination of iodothyronines in rat liver.