Misuse and mortality related to gabapentin and pregabalin are being under-estimated: a two-year post-mortem population

Due to the rise in their misuse and associated mortality, the UK government is reclassifying gabapentin (GBP) and pregabalin (PGL) to Class C controlled drugs from April 2019. However, it is impossible to gauge the extent of their use with current post-mortem toxicological screening, where GBP and PGL are only screened for if they are mentioned in the case documents. This study determines the prevalence of GBP and PGL, the potential extent of their under-reporting and poly-drug use in a post-mortem population. Between 1 January 2016 and 31 December 2017, 3,750 deceased from Coroners’ cases in London and South East England underwent a routine drugs screen and a specific screen for GBP and PGL. The prevalence of both drugs was determined in the cohort and the subcategories of heroin users and non-heroin-users. The prevalence of both drugs was compared to tramadol (Class C drug). Case documents were reviewed to investigate the under-reporting of GBP and PGL and poly-drug use. Of 3,750 samples analyzed, 118 (3.1%) were positive for GBP, 229 (6.1%) for PGL and 120 (3.2%) were positive for tramadol. If routine analysis without additional screening of GBP and PGL had been performed in this cohort, GBP would have been under-reported by 57.6% (P < 0.0001) and PGL by 53.7% (P < 0.0001) in deaths. The most common drug group observed with GBP and PGL was non-heroin-related opioids at 60.2% and 64.6%, respectively. In total 354 deceased (9.4%) were heroin users. GBP was positive in 23 (6.5%) of these cases and PGL was positive in 69 (19.5%). The prevalence of PGL in heroin users (19.5%) was 4.1 times greater than in non-heroin users (4.7%) (P < 0.0001). GBP and PGL are being significantly under reported in fatalities. Both drugs are extensively used with opioids. The prevalence of PGL in heroin users is highly significant

Hypothalamic actions of neuromedin U.

The central nervous system and gut peptide neuromedin U (NMU) inhibits feeding after intracerebroventricular injection. This study explored the hypothalamic actions of NMU on feeding and the hypothalamo-pituitary-adrenal axis. Intraparaventricular nucleus (intra-PVN) NMU dose-dependently inhibited food intake, with a minimum effective dose of 0.1 nmol and a robust effect at 0.3 nmol. Feeding inhibition was mapped by NMU injection into eight hypothalamic areas. NMU (0.3 nmol) inhibited food intake in the PVN (0-1 h, 59 ± 6.9% of the control value; P < 0.001) and arcuate nucleus (0-1 h, 76 ± 10.4% of the control value; P < 0.05). Intra-PVN NMU markedly increased grooming and locomotor behavior and dose-dependently increased plasma ACTH (0.3 nmol NMU, 24.8 ± 1.9 pg/ml; saline, 11.4 ± 1.0; P < 0.001) and corticosterone (0.3 nmol NMU, 275.4 ± 40.5 ng/ml; saline, 129.4 ± 25.0; P < 0.01). Using hypothalamic explants in vitro, NMU stimulated CRH (100 nM NMU, 5.9 ± 0.95 pmol/explant; basal, 3.8 ± 0.39; P < 0.01) and arginine vasopressin release (100 nM NMU, 124.5 ± 21.8 fmol/explant; basal, 74.5 ± 7.6; P < 0.01). Leptin stimulated NMU release (141.9 ± 20.4 fmol/explant; basal, 92.9 ± 9.4; P < 0.01). Thus, we describe a novel role for NMU in the PVN to stimulate the hypothalamo-pituitary-adrenal axis and locomotor and grooming behavior and to inhibit feeding

Neuromedin U partially mediates leptin-induced hypothalamo-pituitary adrenal (HPA) stimulation and has a physiological role in the regulation of the HPA axis in the rat.

Intracerebroventricular (ICV) administration of the hypothalamic neuropeptide neuromedin U (NMU) or the adipostat hormone leptin increases plasma ACTH and corticosterone. The relationship between leptin and NMU in the regulation of the hypothalamo-pituitary adrenal (HPA) axis is currently unknown. In this study, leptin (1 nM) significantly increased the release of CRH from ex vivo hypothalamic explants by 207 ± 8.4% (P < 0.05 vs. basal), an effect blocked by the administration of anti-NMU IgG. The ICV administration of leptin (10 μg, 0.625 nmol) increased plasma ACTH and corticosterone 20 min after injection [plasma ACTH (picograms per milliliter): vehicle, 63 ± 20, leptin, 135 ± 36, P < 0.05; plasma corticosterone (nanograms per milliliter): vehicle, 285 ± 39, leptin, 452 ± 44, P < 0.01]. These effects were partially attenuated by the prior administration of anti-NMU IgG. Peripheral leptin also stimulated ACTH release, an effect attenuated by prior ICV administration of anti-NMU IgG. We examined the diurnal pattern of hypothalamic NMU mRNA expression and peptide content, plasma leptin, and plasma corticosterone. The diurnal changes in hypothalamic NMU mRNA expression were positively correlated with hypothalamic NMU peptide content, plasma corticosterone, and plasma leptin. The ICV administration of anti-NMU IgG significantly attenuated the dark phase rise in corticosterone [corticosterone (nanograms per milliliter): vehicle, 493 ± 38; NMU IgG, 342 ± 47 (P < 0.05)]. These studies suggest that NMU may play a role in the regulation of the HPA axis and partially mediate leptin-induced HPA stimulation. Copyright © 2006 by The Endocrine Society

Quantitative approaches to energy and glucose homeostasis: machine learning and modelling for precision understanding and prediction

Obesity is a major global public health problem. Understanding how energy homeostasis is regulated, and can become dysregulated, is crucial for developing new treatments for obesity. Detailed recording of individual behaviour and new imaging modalities offer the prospect of medically relevant models of energy homeostasis that are both understandable and individually predictive. The profusion of data from these sources has led to an interest in applying machine learning techniques to gain insight from these large, relatively unstructured datasets. We review both physiological models and machine learning results across a diverse range of applications in energy homeostasis, and highlight how modelling and machine learning can work together to improve predictive ability. We collect quantitative details in a comprehensive mathematical supplement. We also discuss the prospects of forecasting homeostatic behaviour and stress the importance of characterizing stochasticity within and between individuals in order to provide practical, tailored forecasts and guidance to combat the spread of obesity

L-Arginine promotes gut hormone release and reduces food intake in rodents

Aims: To investigate the anorectic effect of L‐arginine (L‐Arg) in rodents. Methods: We investigated the effects of L‐Arg on food intake, and the role of the anorectic gut hormones glucagon‐like peptide‐1 (GLP‐1) and peptide YY (PYY), the G‐protein‐coupled receptor family C group 6 member A (GPRC6A) and the vagus nerve in mediating these effects in rodents. Results: Oral gavage of L‐Arg reduced food intake in rodents, and chronically reduced cumulative food intake in diet‐induced obese mice. Lack of the GPRC6A in mice and subdiaphragmatic vagal deafferentation in rats did not influence these anorectic effects. L‐Arg stimulated GLP‐1 and PYY release in vitro and in vivo. Pharmacological blockade of GLP‐1 and PYY receptors did not influence the anorectic effect of L‐Arg. L‐Arg‐mediated PYY release modulated net ion transport across the gut mucosa. Intracerebroventricular (i.c.v.) and intraperitoneal (i.p.) administration of L‐Arg suppressed food intake in rats. Conclusions: L‐Arg reduced food intake and stimulated gut hormone release in rodents. The anorectic effect of L‐Arg is unlikely to be mediated by GLP‐1 and PYY, does not require GPRC6A signalling and is not mediated via the vagus. I.c.v. and i.p. administration of L‐Arg suppressed food intake in rats, suggesting that L‐Arg may act on the brain to influence food intake. Further work is required to determine the mechanisms by which L‐Arg suppresses food intake and its utility in the treatment of obesity

A framework for power analysis using a structural equation modelling procedure

BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres

Detailed characterization of a long-term rodent model of critical illness and recovery

Objective: To characterize a long-term model of recovery from critical illness, with particular emphasis on cardiorespiratory, metabolic, and muscle function. Design: Randomized controlled animal study. Setting: University research laboratory. Subjects: Male Wistar rats. Interventions: Intraperitoneal injection of the fungal cell wall constituent, zymosan or n-saline. Measurements and Main Results: Following intervention, rats were followed for up to 2 weeks. Animals with zymosan peritonitis reached a clinical and biochemical nadir on day 2. Initial reductions were seen in body weight, total body protein and fat, and muscle mass. Leg muscle fiber diameter remained subnormal at 14 days with evidence of persisting myonecrosis, even though gene expression of regulators of muscle mass (e.g., MAFbx, MURF1, and myostatin) had peaked on days 2–4 but normalized by day 7. Treadmill exercise capacity, forelimb grip strength, and in vivo maximum tetanic force were also reduced. Food intake was minimal until day 4 but increased thereafter. This did not relate to appetite hormone levels with early (6 hr) rises in plasma insulin and leptin followed by persisting subnormal levels; ghrelin levels did not change. Serum interleukin-6 level peaked at 6 hours but had normalized by day 2, whereas interleukin-10 remained persistently elevated and high-density lipoprotein cholesterol persistently depressed. There was an early myocardial depression and rise in core temperature, yet reduced oxygen consumption and respiratory exchange ratio with a loss of diurnal rhythmicity that showed a gradual but incomplete recovery by day 7. Conclusions: This detailed physiological, metabolic, hormonal, functional, and histological muscle characterization of a model of critical illness and recovery reproduces many of the findings reported in human critical illness. It can be used to assess putative therapies that may attenuate loss, or enhance recovery, of muscle mass and function