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Background: Factors that predict attempts to discontinue drug use are clinically relevant and may inform treatment. This study investigated drug use-related consequences as a predictor of drug quit attempts and treatment seeking among two cohorts of persons who use drugs. Methods: Drug use and clinical characteristics were assessed among persons who use cocaine (N=176; urine-verified; ‘Cocaine Cohort’) and among those who use heroin (N=166; urine-verified; ‘Heroin Cohort’). Mediation analyses assessed relationships among age at initial drug use, adverse drug-specific use-related consequences, and drug-specific quit attempts, separately for each cohort. Forward conditional logistic regression models evaluated drug use and clinical symptom scores as predictors of drug-specific treatment seeking. Results: Controlling for age, mediation models showed that drug use consequences fully mediated the relationship between age at initial drug use and number of drug-specific quit attempts for the ‘Cocaine Cohort’ and ‘Heroin Cohort’ (R2=0.30, p

Introduction: Integrated care programs that prioritize comprehensive service delivery for behavioural health and medical conditions have the potential to improve patient outcomes. Few programs, however, use data-driven methods to guide program evaluation and implementation, limiting their effectiveness, as well as the scope of findings in the research literature. Purpose: To address these gaps, we describe an innovative and rigorous evaluative research framework: the Rutgers Integrated Care Evaluation (RICE) Research Framework, designed to be tailorable across conditions and care settings. Method: The RICE Research Framework is guided by two core concepts: (1) an approach built on engaging as equal partners and (2) data source triangulation. For the former, the approach relies on multiple teams (Project, Clinical Site, Evaluation, and Consumer) working in collaboration. While teams have specific roles, all teams engage frequently as equal partners to facilitate performance and advance research deliverables. For the latter, we provide a template with recommended primary and secondary data sources with areas of focus, applicable methods, and samples. These sources, when used in combination, can guide implementation, advance replicability, develop/refine health care programs, and foster dissemination of scientific findings. Conclusions: We recommend clinicians and scientists implement the RICE Research Framework to enhance their integrated care programs.

Abstract Pneumococcal pneumonia remains a significant global public health issue. Malaysia has recently added the 10 valent pneumococcal conjugate vaccine to its national immunisation programme. Data on pneumococcal serotype epidemiology is vital for informing national vaccination policy. However, there remains a lack of representative population-based pneumococcal surveillance in Malaysia to help both the assessment of vaccine effectiveness in the country and to shape future vaccine policy. This review explores the history of pneumococcal vaccination, the burden of pneumococcal disease in Malaysia, and offers an insight into the prospects for reducing pneumococcal disease in Malaysia.

Abstract Background People with severe mental illness (SMI), such as schizophrenia, have higher rates of physical long-term conditions (LTCs), poorer health outcomes, and shorter life expectancy compared with the general population. Previous research exploring SMI and diabetes highlights that people with SMI experience barriers to self-management, a key component of care in long-term conditions; however, this has not been investigated in the context of other LTCs. The aim of this study was to explore the lived experience of co-existing SMI and LTCs for service users, carers, and healthcare professionals. Methods A qualitative study with people with SMI and LTCs, their carers, and healthcare professionals, using semi-structured interviews, focused observations, and focus groups across the UK. Forty-one interviews and five focus groups were conducted between December 2018 and April 2019. Transcripts were coded by two authors and analysed thematically. Results Three themes were identified, 1) the precarious nature of living with SMI, 2) the circularity of life with SMI and LTCs, and 3) the constellation of support for self-management. People with co-existing SMI and LTCs often experience substantial difficulties with self-management of their health due to the competing demands of their psychiatric symptoms and treatment, social circumstances, and access to support. Multiple long-term conditions add to the burden of self-management. Social support, alongside person-centred professional care, is a key facilitator for managing health. An integrated approach to both mental and physical healthcare was suggested to meet service user and carer needs. Conclusion The demands of living with SMI present a substantial barrier to self-management for multiple co-existing LTCs. It is important that people with SMI can access person-centred, tailored support for their LTCs that takes into consideration individual circumstances and priorities.

Abstract Background Though methadone has been shown to effectively treat opioid use disorder, many barriers prevent individuals from accessing and maintaining treatment. Barriers are prevalent in less populated areas where treatment options are limited. This study examines barriers to retention in methadone treatment in a small Midwest community and identifies factors associated with greater endorsement of barriers. Methods Patients at an opioid treatment program (N = 267) were recruited to complete a computer-based survey onsite. Surveys assessed demographics, opioid misuse, depression and anxiety symptoms, trauma history and symptoms, social support, and barriers to retention in treatment (e.g., childcare, work, housing, transportation, legal obligations, cost, health). Descriptive statistics were used to examine individual barriers and multiple regression was calculated to identify demographic and psychosocial factors associated with greater cumulative barriers. Results Most participants reported at least one barrier to retention in treatment and more than half reported multiple barriers. Travel hardships and work conflicts were the most highly endorsed barriers. Past year return to use (B = 2.31, p = 0.004) and more severe mental health symptomology (B = 0.20, p = 0.038) were associated with greater cumulative barriers. Greater levels of social support were associated with fewer barriers (B = − 0.23, p

Background: Medications for Opioid Use Disorder (MOUD) are efficacious, however only one-third of individuals with an opioid use disorder (OUD) enter into treatment. Low rates of MOUD utilization are partially due to stigma. This study examines provider-based stigma toward MOUD and identifies factors associated with experiencing stigma related to MOUD from substance use treatment and healthcare providers among people receiving methadone. Methods: Clients receiving MOUD at an opioid treatment program (N = 247) were recruited to complete a cross-sectional computer-based survey assessing socio-demographics, substance use, depression and anxiety symptoms, self-stigma, and recovery supports/barriers. Logistic regression was used to examine factors associated with hearing negative comments about MOUD from substance use treatment and healthcare providers. Results: 27.9% and 56.7% of respondents reported they sometimes/often hear negative comments about MOUD from substance use treatment and healthcare providers, respectively. Logistic regression results indicate that individuals who experience more negative consequences resulting from their OUD (OR=1.09, p=.019) had greater odds of hearing negative comments from substance use treatment providers. Age (OR=0.966, p=.017) and treatment stigma (OR=1.42, p=.030) were associated with greater odds of hearing negative comments from healthcare providers. Conclusions: Stigma can be a deterrent to seeking substance use treatment, healthcare, and recovery support. Understanding factors associated with experiencing stigma from substance use treatment providers and healthcare providers is important as these individuals may act as advocates for those with OUD. This study highlights individual factors associated with hearing negative comments about methadone and other MOUD and point to areas for targeted education.

Abstract Background Pneumococcal pneumonia is the leading cause of under-five mortality globally. The surveillance of pneumococcal serotypes is therefore vital for informing pneumococcal vaccination policy and programmes. Pneumococcal conjugate vaccines (PCVs) have been available as an option in the private healthcare setting and beginning December 2020, PCV10 was incorporated as part of routine national immunisation programme (NIP) in Malaysia. We searched existing literature on pneumococcal serotype distribution across Malaysia to provide an overall view of this distribution before the implementation of PCV10. Methods Online databases (PubMed, Ovid MEDLINE and Scopus), reference lists of articles identified, and grey literature (Malaysian Ministry of Health website, WHO website) were systematically searched for relevant literature on pneumococcal serotype distribution across Malaysia up to 10th November 2020. No lower date limit was set to maximise the number of target reports returned. Results of serotypes were split by age categories, including ≤5 years, > 5 years and unreported for those that did not specify. Results The search returned 18 relevant results, with a total of 2040 isolates. The most common serotypes across all disease types were 19F (n = 313, 15.3% [95%CI: 13.8–17.0]), 23F (n = 166, 8.1% [95%CI: 7.0–9.4]), 14 (n = 166, 8.1% [95%CI: 7.0–9.4]), 6B (n = 163, 8.0% [95%CI: 6.9–9.2]) and 19A (n = 138, 6.8% [95%CI: 5.8–7.9]). Conclusion Four of the most common serotypes across all isolate sources in Malaysia are covered by PCV10, while PCV13 provides greater serotype coverage in comparison to PCV10. There is still a need for surveillance studies, particularly those investigating serotypes in children under 5 years of age, to monitor vaccine effectiveness and pneumococcal population dynamic following implementation of PCV10 into routine immunisation.

ObjectivesIdentify rates and correlates of comorbid affective and substance use disorders among an understudied population, Medicaid/Medicare beneficiaries receiving care at an opioid treatment program serving patients from small urban and rural areas. Examine whether past-year non-medical opioid use status differentiates comorbidity status.MethodsA cross-sectional, venue-based design was used to recruit a convenience sample of patients treated with methadone for opioid use disorder. Measures were assessed across three domains: (1) demographic characteristics, (2) opioid use characteristics, and (3) comorbid disorders. Brief validated screeners categorized probable comorbid disorders. Bivariate analyses examined correlates of comorbid disorders and determined variable selection for multivariable analyses.ResultsIn this sample (N = 210; mean age = 38.5 years; female = 62.2%; Non-Hispanic White race/ethnicity = 86.1%), comorbid disorders were common. Rates were as follows: current anxiety (48.1%), depression (41.1%), and PTSD (33.7%), and past-year stimulant (27.6%), marijuana (19.0%), alcohol (14.9%), and sedative (7.6%). In bivariate analyses, past-year non-medical opioid use and a greater accumulation of opioid use consequences were associated with most disorders. When including demographic and opioid use characteristics in multivariable analyses, past-year non-medical opioid use was associated with anxiety, PTSD, stimulant use disorder, and sedative use disorder.ConclusionsFew studies have investigated comorbid disorders among this understudied population. This analysis highlights a high burden, especially for affective disorders. Our findings demonstrate that routine, ongoing assessment of non-medical opioid use may be a promising and feasible strategy to detect patients needing integrated care. Future research should investigate whether changes to assessment protocols at opioid treatment programs in small urban and rural settings facilitate care coordination.

Background: Opioid-overdose deaths and opioid prescriptions have increased substantially within the past decade, leading to examinations of urban-rural differences for these opioid-related outcomes, and whether annual trends differ by urban-rural status. Most investigations have examined differences using national data, whereas few studies have identified patterns in hard-hit regions. Therefore, we examined urban-rural differences for opioid-related outcomes in Michigan, a state with overdose death and prescribing rates above the national average. Methods: This study used county-level public data on opioid prescribing and opioid-overdose death rates in Michigan. Bivariate and joinpoint regression analyses tested for annual differences and annual changes in opioid-related outcomes across 2013–2017. Rural Urban Continuum Codes classified urban-rural county status. Results: Bivariate analyses demonstrated that urban counties had consistently higher opioid-overdose death rates than rural, whereas rural counties had consistently higher opioid prescribing rates than urban. Joinpoint regression (2013–2017) revealed opioid-overdose death rates increased in urban (Annual Percent Change = 25.0%, p = .001) and rural counties (Annual Percent Change = 21.7%, p = .002), though no changes for opioid prescribing rates were observed among urban or rural counties. Conclusions: Our study highlights nuanced urban-rural patterns in Michigan, a hard-hit state, compared to trends in national data. Both urban and rural counties experienced rising rates of opioid-overdose deaths, and rural counties experienced higher opioid prescribing rates than urban. Though urban counties experienced higher opioid-overdose death rates than rural, the rise in both county types was similar. Future research directions, implications for public health, and healthcare policy recommendations are discussed.

The distribution and local abundance of tree species constitute basic information about our forest ecosystems that is relevant to understanding their ecology, diversity, and relationship to people. The US Forest Service conducts a forest inventory across all forest lands in the United States. We developed geospatial models of forest attributes using this sample-based inventory which make this information available for an even wider variety of applications. From these modeled datasets, we created a series of maps for 24 US states in an effort to connect more people to trees, the datasets, and the scientific research behind them. Presenting these maps in an attractive way invites engagement. The sidebar text is presented in accessible scientific language that clearly defines terms, guides readers in interpreting the maps and histograms, and provides source details and links. The resulting maps are inviting, informative, and accessible to a broad range of people of different ages and backgrounds.

Abstract This paper takes the form of a discussion relating to a smarter knowledge commons, having come about due to implications arising from research into the development of a pragmatic pedagogical ‘guide to learning’ for smart learning environments. The paper does not discuss any research findings (which have not yet been established), but rather is about attempting to discover through examination of early adopter use cases the underlying challenge for smart learning design in relation to the delivery of personalised geo-spatially relevant knowledge. Solutions for the mapping and delivery of the knowledge web are tentatively suggested, making use of an existing meta-property framework, the Open Graph. Smart learning environments focus on learning in geo-spatially relevant learning locations, with tutors or learners engaged in tasks that may frequently require the searching and selecting of knowledge content to contribute to learning or in the further production of new digital knowledge content. This has led to considerations regarding where and how knowledge content is obtained, provided, produced or shared, and this paper examines issues related to the producing, searching and finding of knowledge content in these learning contexts. Practical examples are provided to illustrate how digital knowledge content plays a pivotal role in learning design and learner interactions taking place in smart learning, both for the content of learning and as part of the process for learning. Emphasis is on open access smart learning in relation to connected and collaborative pedagogical approaches. Considering the future development and pedagogies of open-access smart learning environments, we must ask how the knowledge commons, an integral part of this learning, can become ‘smarter’ for learning and teaching.

The extent to which the quality and yield of plant varieties are influenced by the environment is important for their successful uptake by end users particularly as climatic fluctuations are resulting in environments that are highly variable from one growing season to another. The genotype-by-environment interaction (GEI) of milling quality and yield was studied using four winter oat varieties in multi-locational trials over 4 years in the U.K. Significant differences across the 22 environments were found between physical grain quality and composition as well as grain yield, with the environment having a significant effect on all of the traits measured. Grain yield was closely related to grain number m−2 whereas milling quality traits were related to grain size attributes. Considerable genotype by environment interaction was obtained for all grain quality traits and stability analysis revealed that the variety Mascani was the least sensitive to the environment for all milling quality traits measured whereas the variety Balado was the most sensitive. Examination of environmental conditions at specific within-year stages of crop development indicated that both temperature and rainfall during grain development were correlated with grain yield and β-glucan content and with the ease of removing the hull (hullability).

Ruminant methane production is a significant energy loss to the animal and major contributor to global greenhouse gas emissions. However, it also seems necessary for effective rumen function, so studies of anti-methanogenic treatments must also consider implications for feed efficiency. Between-animal variation in feed efficiency represents an alternative approach to reducing overall methane emissions intensity. Here we assess the effects of dietary additives designed to reduce methane emissions on the rumen microbiota, and explore relationships with feed efficiency within dietary treatment groups. Seventy-nine finishing steers were offered one of four diets (a forage/concentrate mixture supplemented with nitrate (NIT), lipid (MDDG) or a combination (COMB) compared to the control (CTL)). Rumen fluid samples were collected at the end of a 56 d feed efficiency measurement period. DNA was extracted, multiplexed 16s rRNA libraries sequenced (Illumina MiSeq) and taxonomic profiles were generated. The effect of dietary treatments and feed efficiency (within treatment groups) was conducted both overall (using non-metric multidimensional scaling (NMDS) and diversity indexes) and for individual taxa. Diet affected overall microbial populations but no overall difference in beta-diversity was observed. The relative abundance of Methanobacteriales (Methanobrevibacter and Methanosphaera) increased in MDDG relative to CTL, whilst VadinCA11 (Methanomassiliicoccales) was decreased. Trimethylamine precursors from rapeseed meal (only present in CTL) probably explain the differences in relative abundance of Methanomassiliicoccales. There were no differences in Shannon indexes between nominal low or high feed efficiency groups (expressed as feed conversion ratio or residual feed intake) within treatment groups. Relationships between the relative abundance of individual taxa and feed efficiency measures were observed, but were not consistent across dietary treatments.

Fatty acid (FA) concentration and composition of forage has recently gained interest due to potential opportunities for improving FA profile of ruminant products (meat and milk). Twenty perennial ryegrass genotypes from an experimental breeding population and four genotypes from an experimental mapping population were used to assess (1) genotypic variation, and (2) associations between FAs and other important chemical constituents (i.e., protein, carbohydrate and fibre). Mean total FA (TFA) concentration was 23.8 g kg−1 DM, ranging from 14.5 to 33.8 g kg−1 DM; 89% to 95% of which was comprised of six individual FAs, namely, palmitic acid (C16:0), trans-3-hexadecenoic acid (C16:1Δt3), stearic acid (C18:0), oleic acid (C18:1Δc9), linoleic acid (C18:2Δc9,12) and α-linolenic acid (C18:3Δc9,12,15). Mean crude protein (CP), water-soluble carbohydrate (WSC), neutral detergent fibre (NDF) and acid detergent fibre (ADF) concentrations were: 133, 188, 447 and 240 g kg−1 DM, respectively. Genotypes from the mapping population differed for: WSC (p = 0.015), C16:0 (p = 0.034), C18:0 (p < 0.001), C18:3Δc9,12,15 (p = 0.012) and TFA (p = 0.025). Genotypes from the breeding population differed (p < 0.001) for all measured components except CP (p = 0.078). Higher FA concentration was generally associated with higher CP concentration and lower WSC, NDF and ADF. Selectively breeding for higher FA concentrations may alter the overall feed value of perennial ryegrass, however further investigation is needed to fully understand the relationship between FA concentration and feed value and the possible implications for ruminant nutrition.

Rumen microbiota plays an important role in animal productivity, methane production and health. Several different locations have been used to obtain rumen samples (i.e., liquid-phase samples, solid-phase samples, buccal swabs) in previous studies. Here we assess differences in the rumen microbiota between solid- and liquid-phases of the rumen under differing dietary conditions (white clover vs. perennial ryegrass); there were 4 sample types: liquid-associated/grass (LG), solid-associated/grass (SG), liquid-associated/clover (LC), and solid-associated/clover (SC). Four Holstein-Friesian cows were strip grazed on pure stands of perennial ryegrass or white clover in a change-over design experiment with 3 periods (each lasting for 3 weeks). Solid- and liquid- phase microbes were obtained following total rumen evacuation on the penultimate day of each period. DNA was extracted and multiplexed libraries sequenced using 16S next generation sequencing (Illumina MiSeq). Demultiplexed sequences underwent quality control and taxonomic profiles were generated for each sample. Statistical analysis for the effects of diet and phase was conducted both overall [using non-metric multidimensional scaling (NMDS) and diversity indices] and for individual taxa. Separation of both diet and phase was observed NMDS, with significant effects of diet (P < 0.001) and phase (P < 0.001) being observed. Regardless of diet, Prevotella was most abundant in the liquid samples. When assessing differences between phases, the majority of statistically significant taxa (predominantly from Archaea and the order Clostridiales) were found at higher relative abundances in solid-phase samples. Diversity (Shannon Index) was lower in the liquid-phase samples, possibly because of the higher relative abundance of Prevotella. A presence vs. absence approach, followed by Chi-squared testing, was adopted. Differences between phases (LG vs. LC, LC vs. LG, SG vs. SC, and SC vs. SG) and differences between phases for the clover diet (LC vs. SC and SC vs. LC) were significant (P < 0.001); differences between phases for the grass diet were non-significant. Sampling technique has a profound impact on reported microbial communities, which must be taken into consideration, particularly as archaea may be underestimated in the liquid-phase.

Auditory cognitive training (ACT) improves attention in older adults; however, the underlying neurophysiological mechanisms are still unknown. The present study examined the effects of ACT on the P3b event-related potential reflecting attention allocation (amplitude) and speed of processing (latency) during stimulus categorization and the P1-N1-P2 complex reflecting perceptual processing (amplitude and latency). Participants completed an auditory oddball task before and after 10 weeks of ACT (n = 9) or a no contact control period (n = 15). Parietal P3b amplitudes to oddball stimuli decreased at post-test in the trained group as compared to those in the control group, and frontal P3b amplitudes show a similar trend, potentially reflecting more efficient attentional allocation after ACT. No advantages for the ACT group were evident for auditory perceptual processing or speed of processing in this small sample. Our results provide preliminary evidence that ACT may enhance the efficiency of attention allocation, which may account for the positive impact of ACT on the everyday functioning of older adults.

Reductions in atmospheric concentrations of greenhouse gases are urgently needed to avoid the most catastrophic consequences of warming. Reducing deforestation and forest degradation presents a climate change mitigation opportunity critical to meeting Paris Agreement goals. One strategy for decreasing carbon emissions from forests is to provide developing countries with results-based financial incentives for reducing deforestation: nearly two billion dollars are currently committed to finance such programs, referred to as REDD+ (Reducing Emissions from Deforestation and forest Degradation, conservation, sustainable management of forests, and enhancement of forest carbon stocks). Countries participating in these programs must document the uncertainty in their estimates of emissions and emission reductions, and payments are reduced if uncertainties are high. Our examination of documentation submitted to date to the United Nations Framework Convention on Climate Change (UNFCCC) and the Forest Carbon Partnership Facility (FCPF) reveals that uncertainties are commonly underestimated, both by omitting important sources of uncertainty and by incorrectly combining uncertainties. Here, we offer recommendations for addressing common problems in estimating uncertainty in emissions and emission reductions. Better uncertainty estimates will enable countries to improve forest carbon accounting, contribute to better informed forest management, and support efforts to track global greenhouse gas emissions. It will also strengthen confidence in markets for climate mitigation efforts. Demand by companies for nature-based carbon credits is growing and if such credits are used for offsets, in exchange for fossil fuel emissions, it is essential that they represent accurately quantified emissions reductions.

ETC-1002 is an investigational drug currently in Phase 2 development for treatment of dyslipidemia and other cardiometabolic risk factors. In dyslipidemic subjects, ETC-1002 not only reduces plasma LDL cholesterol but also significantly attenuates levels of hsCRP, a clinical biomarker of inflammation. Anti-inflammatory properties of ETC-1002 were further investigated in primary human monocyte-derived macrophages and in in vivo models of inflammation. In cells treated with ETC-1002, increased levels of AMP-activated protein kinase (AMPK) phosphorylation coincided with reduced activity of MAP kinases and decreased production of proinflammatory cytokines and chemokines. AMPK phosphorylation and inhibitory effects of ETC-1002 on soluble mediators of inflammation were significantly abrogated by siRNA-mediated silencing of macrophage liver kinase B1 (LKB1), indicating that ETC-1002 activates AMPK and exerts its anti-inflammatory effects via an LKB1-dependent mechanism. In vivo, ETC-1002 suppressed thioglycollate-induced homing of leukocytes into mouse peritoneal cavity. Similarly, in a mouse model of diet-induced obesity, ETC-1002 restored adipose AMPK activity, reduced JNK phosphorylation, and diminished expression of macrophage-specific marker 4F/80. These data were consistent with decreased epididymal fat-pad mass and interleukin (IL)-6 release by inflamed adipose tissue. Thus, ETC-1002 may provide further clinical benefits for patients with cardiometabolic risk factors by reducing systemic inflammation linked to insulin resistance and vascular complications of metabolic syndrome.

Obesity is an important modifiable risk factor for chronic diseases. While there is increasing focus on the role of dietary sugars, there remains a paucity of data establishing the association between sugar intake and obesity in the general public. The objective of this study was to investigate associations of estimated sugar intake with odds for obesity in a representative sample of English adults. We used data from 434 participants of the 2005 Health Survey of England. Biomarkers for total sugar intake were measured in 24 h urine samples and used to estimate intake. Linear and logistic regression analyses were used to investigate associations between biomarker-based estimated intake and measures of obesity (body mass intake (BMI), waist circumference and waist-to-hip ratio) and obesity risk, respectively. Estimated sugar intake was significantly associated with BMI, waist circumference and waist-to-hip ratio; these associations remained significant after adjustment for estimated protein intake as a marker of non-sugar energy intake. Estimated sugar intake was also associated with increased odds for obesity based on BMI (OR 1.02; 95%CI 1.00-1.04 per 10g), waist-circumference (1.03; 1.01-1.05) and waist-to-hip ratio (1.04; 1.02-1.06); all OR estimates remained significant after adjusting for estimated protein intake. Our results strongly support positive associations between total sugar intake, measures of obesity and likelihood of being obese. It is the first time that such an association has been shown in a nationally-representative sample of the general population using a validated biomarker. This biomarker could be used to monitor the efficacy of public health interventions to reduce sugar intake.