Association between recent overdose and chronic pain among individuals in treatment for opioid use disorder

Chronic pain increases risk for opioid overdose among individuals with opioid use disorder. The purpose of this study is to evaluate the relationship between recent overdose and whether or not chronic pain is active. 3,577 individuals in treatment for opioid use disorder in 2017 or 2018 were surveyed regarding recent overdoses and chronic pain. Demographics from the 2017 Treatment Episode Data Set, which includes all U.S. facilities licensed or certified to provide substance use care, were used to evaluate the generalizability of the sample. χ2 tests and logistic regression models were used to compare associations between recent overdoses and chronic pain. Specifically, active chronic pain was associated with opioid overdose among people in treatment for opioid use disorder. Individuals with active chronic pain were more likely to have had a past month opioid overdose than those with no history chronic pain (adjusted OR = 1.55, 95% CI 1.16-2.08, p = 0.0003). In contrast, individuals with prior chronic pain, but no symptoms in the past 30 days, had a risk of past month opioid overdose similar to those with no history of chronic pain (adjusted OR = 0.88, 95% CI 0.66-1.17, p = 0.38). This suggests that the incorporation of treatment for chronic pain into treatment for opioid use disorder may reduce opioid overdoses

Management of Orofacial Manifestations of Juvenile Idiopathic Arthritis: Interdisciplinary Consensus-Based Recommendations

Involvement of the temporomandibular joint (TMJ) is common in juvenile idiopathic arthritis (JIA). TMJ arthritis can lead to orofacial symptoms, orofacial dysfunction, and dentofacial deformity with negative impact on quality of life. Management involves interdisciplinary collaboration. No current recommendations exist to guide clinical management. We undertook this study to develop consensus-based interdisciplinary recommendations for management of orofacial manifestations of JIA, and to create a future research agenda related to management of TMJ arthritis in children with JIA. Recommendations were developed using online surveying of relevant stakeholders, systematic literature review, evidence-informed generation of recommendations during 2 consensus meetings, and Delphi study iterations involving external experts. The process included disciplines involved in the care of orofacial manifestations of JIA: pediatric rheumatology, radiology, orthodontics, oral and maxillofacial surgery, orofacial pain specialists, and pediatric dentistry. Recommendations were accepted if agreement was >80% during a final Delphi study. Three overarching management principles and 12 recommendations for interdisciplinary management of orofacial manifestations of JIA were outlined. The 12 recommendations pertained to diagnosis (n = 4), treatment of TMJ arthritis (active TMJ inflammation) (n = 2), treatment of TMJ dysfunction and symptoms (n = 3), treatment of arthritis-related dentofacial deformity (n = 2), and other aspects related to JIA (n = 1). Additionally, a future interdisciplinary research agenda was developed. These are the first interdisciplinary recommendations to guide clinical management of TMJ JIA. The 3 overarching principles and 12 recommendations fill an important gap in current clinical practice. They emphasize the importance of an interdisciplinary approach to diagnosis and management of orofacial manifestations of JIA

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

Shifting pathways of stimulant use among individuals with opioid use disorder: a retrospective analysis of the last thirty years.

Stimulant use among individuals with opioid use disorder has recently increased, driven by changes in drug distribution channels. However, our understanding of polysubstance use is often limited by a need to provide targeted treatment to a primary drug of addiction. Yet there is a crucial need to better understand pathways to addiction, and how the use of multiple substances may differ between populations, as well as time periods. Using a national opioid surveillance system, we analyzed survey data from new entrants to 124 opioid use disorder treatment centers from 2017 to 2020. Age of first use was collected for prescription opioids, illicit opioids, prescription stimulants, crack/cocaine, and methamphetamines. Year of initial use of an opioid or stimulant was calculated and grouped by 5 year blocs, inclusive of initial use starting from 1991 and ending in 2020 ( = 6,048). Lifetime exposure to stimulants was 82.5% among individuals with opioid use disorder. Mean age of initiation increased for all drugs in 2016-2020, in particular prescription opioids (22.3 to 31.8). Stimulants were initiating drugs for a substantial proportion of individuals with opioid use throughout the analyzed time period. Those initiating opioid/stimulant use from 1991 to 1995 had a mean average of 6.8 years between first and second drug exposure, which steadily decreased to 1.5 years between exposures in 2016-2020. Sankey plots depict significantly more drug transitions in those initiating use from 1991 to 2000 (65.1% had at least two drug transitions) compared to 2010-2020 (16.0%). Opioid-stimulant use increased over time among racial/ethnic minorities, sexual minorities, and those with an educational attainment of high school or less. These data highlight not only the substantial prevalence of stimulant use among individuals who develop opioid use disorder, but also the variability through which pathways of use occur. Prevention and intervention efforts need to take into account increasing ages of initial drug exposures, demographic shifts in stimulant-using populations, and more rapid drug transitions between opioid and stimulants. But at a broader level, prevention, harm reduction ideology, and addiction medicine needs to take into account the ubiquity of polysubstance use among individuals with substance use disorders

Opioid Dosage Levels, Concurrent Risk Factors and Self-Perceptions among Chronic Pain, Opioid-Managed Individuals at Elevated Risk for Opioid Overdose

While current opioid prescribing guidelines highlight a dose-response relationship between therapeutic management and overdose risk, other concurrent risk factors have also been identified. However, there is little data in assessing the relationship between risk factor prevalence, associated provider communication, and subsequent perceptions of overdose risk among chronic pain, opioid-managed (CPOM) patients. An online questionnaire was distributed in June 2020 to a sample of CPOM individuals (n = 190) treated with an opioid prescription at or above 50 daily MME, or any dosage alongside benzodiazepines. CPOM individuals reported a mean daily MME of 470, with half (52.6%) receiving a concurrent benzodiazepine prescription. All patients reported past month alcohol use, and 67.4% indicated a risk-elevating diagnosed medical condition. In assessing provider communication, 41.6% reported no discussion focusing on the risks of one’s opioid therapy. Subsequently, 62.1% perceived themselves as having “no risk”, and 60.0% were “not at all concerned” (60.0%) about experiencing an opioid overdose. Organizational policies should focus on implementing consistent methods of patient education regarding overdose risk, as well as assessments of behaviors or characteristics that my increase an individual’s risk of opioid overdose. These policies should also include other forms of evidence-based overdose risk prevention such as co-prescriptions of naloxone

Femtosecond X-ray Spectroscopy Directly Quantifies Transient Excited-State Mixed Valency.

Quantifying charge delocalization associated with short-lived photoexcited states of molecular complexes in solution remains experimentally challenging, requiring local element specific femtosecond experimental probes of time-evolving electron transfer. In this study, we quantify the evolving valence hole charge distribution in the photoexcited charge transfer state of a prototypical mixed valence bimetallic iron-ruthenium complex, [(CN)5FeIICNRuIII(NH3)5]-, in water by combining femtosecond X-ray spectroscopy measurements with time-dependent density functional theory calculations of the excited-state dynamics. We estimate the valence hole charge that accumulated at the Fe atom to be 0.6 ± 0.2, resulting from excited-state metal-to-metal charge transfer, on an ∼60 fs time scale. Our combined experimental and computational approach provides a spectroscopic ruler for quantifying excited-state valency in solvated complexes