Causes of death among people who used illicit opioids in England, 2001–18: a matched cohort study

Background: In many countries, the average age of people who use illicit opioids, such as heroin, is increasing. This has been suggested to be a reason for increasing numbers of opioid-related deaths seen in surveillance data. We aimed to describe causes of death among people who use illicit opioids in England, how causes of death have changed over time, and how they change with age. Methods: In this matched cohort study, we studied patients in the Clinical Practice Research Datalink with recorded illicit opioid use (defined as aged 18–64 years, with prescriptions or clinical observations that indicate use of illicit opioids) in England between Jan 1, 2001, and Oct 30, 2018. We also included a comparison group, matched (1:3) for age, sex, and general practice with no records of illicit opioid use before cohort entry. Dates and causes of death were obtained from the UK Office for National Statistics. The cohort exit date was the earliest of date of death or Oct 30, 2018. We described rates of death and calculated cause-specific standardised mortality ratios. We used Poisson regression to estimate associations between age, calendar year, and cause-specific death. Findings: We collected data for 106 789 participants with a history of illicit opioid use, with a median follow-up of 8·7 years (IQR 4·3–13·5), and 320 367 matched controls with a median follow-up of 9·5 years (5·0–14·4). 13 209 (12·4%) of 106 789 participants in the exposed cohort had died, with a standardised mortality ratio of 7·72 (95% CI 7·47–7·97). The most common causes of death were drug poisoning (4375 [33·1%] of 13 209), liver disease (1272 [9·6%]), chronic obstructive pulmonary disease (COPD; 681 [5·2%]), and suicide (645 [4·9%]). Participants with a history of illicit opioid use had higher mortality rates than the comparison group for all causes of death analysed, with highest standardised mortality ratios being seen for viral hepatitis (103·5 [95% CI 61·7–242·6]), HIV (16·7 [9·5–34·9]), and COPD (14·8 [12·6–17·6]). In the exposed cohort, at age 20 years, the rate of fatal drug poisonings was 271 (95% CI 230–313) per 100 000 person-years, accounting for 59·9% of deaths at this age, whereas the mortality rate due to non-communicable diseases was 31 (16–45) per 100 000 person-years, accounting for 6·8% of deaths at this age. Deaths due to non-communicable diseases increased more rapidly with age (1155 [95% CI 880–1431] deaths per 100 000 person-years at age 50 years; accounting for 52·0% of deaths at this age) than did deaths due to drug poisoning (507 (95% CI 452–562) per 100 000 person-years at age 50 years; accounting for 22·8% of deaths at this age). Mirroring national surveillance data, the rate of fatal drug poisonings in the exposed cohort increased from 345 (95% CI 299–391) deaths per 100 000 person-years in 2010–12 to 534 (468–600) per 100 000 person-years in 2016–18; an increase of 55%, a trend that was not explained by ageing of participants. Interpretation: People who use illicit opioids have excess risk of death across all major causes of death we analysed. Our findings suggest that population ageing is unlikely to explain the increasing number of fatal drug poisonings seen in surveillance data, but is associated with many more deaths due to non-communicable diseases

Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

A survey of performance enhancement of transmission control protocol (TCP) in wireless ad hoc networks

This Article is provided by the Brunel Open Access Publishing Fund - Copyright @ 2011 Springer OpenTransmission control protocol (TCP), which provides reliable end-to-end data delivery, performs well in traditional wired network environments, while in wireless ad hoc networks, it does not perform well. Compared to wired networks, wireless ad hoc networks have some specific characteristics such as node mobility and a shared medium. Owing to these specific characteristics of wireless ad hoc networks, TCP faces particular problems with, for example, route failure, channel contention and high bit error rates. These factors are responsible for the performance degradation of TCP in wireless ad hoc networks. The research community has produced a wide range of proposals to improve the performance of TCP in wireless ad hoc networks. This article presents a survey of these proposals (approaches). A classification of TCP improvement proposals for wireless ad hoc networks is presented, which makes it easy to compare the proposals falling under the same category. Tables which summarize the approaches for quick overview are provided. Possible directions for further improvements in this area are suggested in the conclusions. The aim of the article is to enable the reader to quickly acquire an overview of the state of TCP in wireless ad hoc networks.This study is partly funded by Kohat University of Science & Technology (KUST), Pakistan, and the Higher Education Commission, Pakistan

Mechanistic interplay between ceramide and insulin resistance

Recent research adds to a growing body of literature on the essential role of ceramides in glucose homeostasis and insulin signaling, while the mechanistic interplay between various components of ceramide metabolism remains to be quantified. We present an extended model of C16:0 ceramide production through both the de novo synthesis and the salvage pathways. We verify our model with a combination of published models and independent experimental data. In silico experiments of the behavior of ceramide and related bioactive lipids in accordance with the observed transcriptomic changes in obese/diabetic murine macrophages at 5 and 16 weeks support the observation of insulin resistance only at the later phase. Our analysis suggests the pivotal role of ceramide synthase, serine palmitoyltransferase and dihydroceramide desaturase involved in the de novo synthesis and the salvage pathways in influencing insulin resistance versus its regulation

The Down syndrome brain in the presence and absence of fibrillar β-amyloidosis

People with Down syndrome (DS) have a neurodevelopmentally distinct brain and invariably developed amyloid neuropathology by age 50. This cross-sectional study aimed to provide a detailed account of DS brain morphology and the changes occuring with amyloid neuropathology. Forty-six adults with DS underwent structural and amyloid imaging-the latter using Pittsburgh compound B (PIB) to stratify the cohort into PIB-positive (n = 19) and PIB-negative (n = 27). Age-matched controls (n = 30) underwent structural imaging. Group differences in deep gray matter volumetry and cortical thickness were studied. PIB-negative people with DS have neurodevelopmentally atypical brain, characterized by disproportionately thicker frontal and occipitoparietal cortex and thinner motor cortex and temporal pole with larger putamina and smaller hippocampi than controls. In the presence of amyloid neuropathology, the DS brains demonstrated a strikingly similar pattern of posterior dominant cortical thinning and subcortical atrophy in the hippocampus, thalamus, and striatum, to that observed in non-DS Alzheimer's disease. Care must be taken to avoid underestimating amyloid-associated morphologic changes in DS due to disproportionate size of some subcortical structures and thickness of the cortex.This work was supported by the Medical Research Council (grant number: 98480 ). Additional support was received from the NIHR Cambridge Biomedical Research Centre, the NIHR Collaborations in Leadership for Applied Health Research and Care (CLAHRC) for the East of England, the NIHR Cambridge Dementia Biomedical Research Unit, the Down Syndrome Association and the Health Foundation

Control Growth Factor Release Using a Self-Assembled [polycation∶heparin] Complex

The importance of growth factors has been recognized for over five decades; however their utilization in medicine has yet to be fully realized. This is because free growth factors have short half-lives in plasma, making direct injection inefficient. Many growth factors are anchored and protected by sulfated glycosaminoglycans in the body. We set out to explore the use of heparin, a well-characterized sulfated glycosaminoglycan, for the controlled release of fibroblast growth factor-2 (FGF-2). Heparin binds a multitude of growth factors and maintains their bioactivity for an extended period of time. We used a biocompatible polycation to precipitate out the [heparin∶FGF-2] complex from neutral buffer to form a release matrix. We can control the release rate of FGF-2 from the resultant matrix by altering the molecular weight of the polycation. The FGF-2 released from the delivery complex maintained its bioactivity and initiated cellular responses that were at least as potent as fresh bolus FGF-2 and fresh heparin stabilized FGF-2. This new delivery platform is not limited to FGF-2 but applicable to the large family of heparin-binding growth factors

International Delegations and the Values of Federalism

Inland water sediments receive large quantities of terrestrial organic matter(1-5) and are globally important sites for organic carbon preservation(5,6). Sediment organic matter mineralization is positively related to temperature across a wide range of high-latitude ecosystems(6-10), but the situation in the tropics remains unclear. Here we assessed temperature effects on the biological production of CO2 and CH4 in anaerobic sediments of tropical lakes in the Amazon and boreal lakes in Sweden. On the basis of conservative regional warming projections until 2100 (ref. 11), we estimate that sediment CO2 and CH4 production will increase 9-61% above present rates. Combining the CO2 and CH4 as CO2 equivalents (CO(2)eq; ref. 11), the predicted increase is 2.4-4.5 times higher in tropical than boreal sediments. Although the estimated lake area in low latitudes is 3.2 times smaller than that of the boreal zone, we estimate that the increase in gas production from tropical lake sediments would be on average 2.4 times higher for CO2 and 2.8 times higher for CH4. The exponential temperature response of organic matter mineralization, coupled with higher increases in the proportion of CH4 relative to CO2 on warming, suggests that the production of greenhouse gases in tropical sediments will increase substantially. This represents a potential large-scale positive feedback to climate change

Plant-made polio type 3 stabilized VLPs—a candidate synthetic polio vaccine

Poliovirus (PV) is the causative agent of poliomyelitis, a crippling human disease known since antiquity. PV occurs in two distinct antigenic forms, D and C, of which only the D form elicits a robust neutralizing response. Developing a synthetically produced stabilized viruslike particle (sVLP)-based vaccine with D antigenicity, without the drawbacks of current vaccines, will be a major step towards the final eradication of poliovirus. Such a sVLP would retain the native antigenic conformation and the repetitive structure of the original virus particle, but lack infectious genomic material. In this study, we report the production of synthetically stabilized PV VLPs in plants. Mice carrying the gene for the human PV receptor are protected from wild-type PV when immunized with the plant-made PV sVLPs. Structural analysis of the stabilized mutant at 3.6 Å resolution by cryo-electron microscopy and single particle reconstruction reveals a structure almost indistinguishable from wild-type PV3

The p53HMM algorithm: using profile hidden markov models to detect p53-responsive genes

<p>Abstract</p> <p>Background</p> <p>A computational method (called p53HMM) is presented that utilizes Profile Hidden Markov Models (PHMMs) to estimate the relative binding affinities of putative p53 response elements (REs), both p53 single-sites and cluster-sites. These models incorporate a novel "Corresponded Baum-Welch" training algorithm that provides increased predictive power by exploiting the redundancy of information found in the repeated, palindromic p53-binding motif. The predictive accuracy of these new models are compared against other predictive models, including position specific score matrices (PSSMs, or weight matrices). We also present a new dynamic acceptance threshold, dependent upon a putative binding site's distance from the Transcription Start Site (TSS) and its estimated binding affinity. This new criteria for classifying putative p53-binding sites increases predictive accuracy by reducing the false positive rate.</p> <p>Results</p> <p>Training a Profile Hidden Markov Model with corresponding positions matching a combined-palindromic p53-binding motif creates the best p53-RE predictive model. The p53HMM algorithm is available on-line: <url>http://tools.csb.ias.edu</url></p> <p>Conclusion</p> <p>Using Profile Hidden Markov Models with training methods that exploit the redundant information of the homotetramer p53 binding site provides better predictive models than weight matrices (PSSMs). These methods may also boost performance when applied to other transcription factor binding sites.</p