BACKGROUND: Florida, which led the country in terms of its number of opioid-prescribing physicians, was unique during the height of the opioid epidemic because of its lax prescribing laws and high number of unregulated pain clinics. Here, we address differences in the distribution rates of oxycodone and hydrocodone across Florida counties during the peak years of the opioid epidemic using an under-utilized database.
METHODS: The Washington Post and the United States Drug Enforcement Administration\'s Automation of Reports and Consolidated Orders System (ARCOS) databases provided longitudinal oxycodone and hydrocodone distribution data in grams per county (2006-2014) and state (2006-2021). Grams of oxycodone and hydrocodone were converted into morphine milligram equivalents (MMEs).
RESULTS: There was a steep increase in oxycodone from 2006 to 2010, with a subsequent decline. In 2010, the average MME per person across Florida was 729.4, a 120.6% increase from 2006. The three counties with the highest MMEs per person in 2010 were Hillsborough (2271.3), Hernando (1915.3), and Broward (1726.9), and they were significantly (p < 0.05) elevated relative to the average county.
CONCLUSIONS: The data demonstrated pronounced differences in opioid distribution, particularly oxycodone, between Florida counties during the height of the opioid epidemic. Legislative action taken between 2009 and 2011 aligns with the considerable decline in opioid distribution after 2010.

Measurements of sphingolipid metabolism are most accurately performed by LC-MS. However, this technique is expensive, not widely accessible, and without the use of specific probes, it does not provide insight into metabolic flux through the pathway. Employing the fluorescent ceramide analogue NBD-C6-ceramide as a tracer in intact cells, we developed a comprehensive HPLC-based method that simultaneously measures the main nodes of ceramide metabolism in the Golgi. Hence, by quantifying the conversion of NBD-C6-ceramide to NBD-C6-sphingomyelin, NBD-C6-hexosylceramides, and NBD-C6-ceramide-1-phosphate (NBD-C1P), the activities of Golgi resident enzymes sphingomyelin synthase 1, glucosylceramide synthase, and ceramide kinase (CERK) could be measured simultaneously. Importantly, the detection of NBD-C1P allowed us to quantify CERK activity in cells, a usually difficult task. By applying this method, we evaluated the specificity of commonly used sphingolipid inhibitors and discovered that 1-phenyl-2-decanoylamino-3-morpholino-1-propanol, which targets glucosylceramide synthase, and fenretinide (4HPR), an inhibitor for dihydroceramide desaturase, also suppress CERK activity. This study demonstrates the benefit of an expanded analysis of ceramide metabolism in the Golgi, and it provides a qualitative and easy-to-implement method.

OBJECTIVE: In this study, we explored key prescription drug monitoring program-related outcomes among clinicians from a broad cohort of Massachusetts healthcare facilities following prescription drug monitoring program (PDMP) and electronic health record (EHR) data integration.
METHODS: Outcomes included seven-day rolling averages of opioids prescribed, morphine milligram equivalents (MMEs) prescribed, and PDMP queries. We employed a longitudinal study design to analyze PDMP data over a 15-month study period which allowed for six and a half months of pre- and post-integration observations surrounding a two-month integration period. We used longitudinal mixed effects models to examine the effect of EHR integration on each of the key outcomes.
RESULTS: Following EHR integration, PDMP queries increased both through the web-based portal and in total (0.037, [95% CI = 0.017, 0.057] and 0.056, [95% CI = 0.035, 0.077]). Both measures of clinician opioid prescribing declined throughout the study period; however, no significant effect following EHR integration was observed. These results were consistent when our analysis was applied to a subset consisting only of continuous PDMP users.
CONCLUSIONS: Our results support EHR integration contributing to PDMP utilization by clinicians but do not support changes in opioid prescribing behavior.

Thrombotic complications after allogeneic hematopoietic stem cell transplantation (allo-HSCT) significantly impact transplant outcomes. We focused on high mobility group box-protein (HMGB)1, one causative agent of thrombotic lesions in allo-HSCT, and investigated its association with platelets. We statistically analyzed available data from 172 patients with hematopoietic malignancies receiving allo-HSCT. A significant enhancement of monocyte-chemotactant protein-1, HMGB1, and platelet-derived microparticle (PDMP) levels was observed at day 0 after transplantation as compared to pre-transplantation. Multivariate analysis of the association among HMGB1 and 16 factors on day 0 revealed a significant correlation of HMGB1 levels with thrombin-antithrombin complex, interleukin-6, and PDMPs. High mobility group box-protein 1-induced procoagulant platelet induction and PDMP generation were performed in vitro using healthy platelets. High mobility group box-protein 1-induced PDMP generation was suppressed by toll-like receptor inhibitors and recombinant thrombomodulin. These results suggest that HMGB1 contributes to platelet activation in patients after allo-HSCT and is associated with PDMP-related thrombotic complications.

Cannabis may be a substitute for opioids but previous studies have found conflicting results when using data from more recent years. Most studies have examined the relationship using state-level data, missing important sub-state variation in cannabis access.
To examine cannabis legalization on opioid use at the county level, using Colorado as a case study. Colorado allowed recreational cannabis stores in January 2014. Local communities could decide whether to allow dispensaries, creating variation in the level of exposure to cannabis outlets.
Observational, quasi-experimental design exploiting county-level variation in allowance of recreational dispensaries.
Colorado residents MEASURES: We use licensing information from the Colorado Department of Revenue to measure county-level exposure to cannabis outlets. We use the state\'s Prescription Drug Monitoring Program (2013-2018) to construct opioid-prescribing measures of number of 30-day fills and total morphine equivalents, both per county resident per quarter. We construct outcomes of opioid-related inpatient visits (2011-2018) and emergency department visits (2013-2018) with Colorado Hospital Association data. We use linear models in a differences-in-differences framework that accounts for the varying exposure to medical and recreational cannabis over time. There are 2048 county-quarter observations used in the analysis.
We find mixed evidence of cannabis exposure on opioid-related outcomes at the county level. We find increasing exposure to recreational cannabis is associated with a statistically significant decrease in number of 30-day fills (coefficient: -117.6, p-value<0.01) and inpatient visits (coefficient: -0.8, p-value: 0.03), but not total MME nor ED visits. Counties with no medical exposure prior to recreational legalization experience greater reductions in the number of 30-day fills and MME than counties with prior medical exposure (p=0.02 for both).
Our mixed findings suggest that further increases in cannabis beyond medical access may not always reduce opioid prescribing or opioid-related hospital visits at a population level.

Prescription opioids (POs) have had a devastating effect on people and public health systems in the U.S. Due to the urgency and complexity of the opioid crisis, there is a need to expand qualitative research on the medical community\'s perspectives on opioid prescribing practices and the role that prescription drug monitoring programs (PDMPs) have played in mitigating this crisis.
We conducted qualitative interviews with clinicians (n = 23) across specialties and a range of overdose hotspot and coldspot locations in Massachusetts during 2019. We aimed to capture their perspectives on the opioid crisis, changes in clinical practice, and experiences with opioid prescribing and PDMPs.
Respondents consistently recognized the role clinicians played in the opioid crisis and reported reductions in their opioid prescribing, which were motivated by the crisis itself. The limitations of opioids in pain management were frequently discussed. While clinicians appreciated having greater awareness of their opioid prescribing and increased access to patient prescription histories, they also expressed concerns about surveillance of their prescribing and other unintended consequences. We observed that clinicians in opioid prescribing hotspots had more detailed and specific reflections on their experiences with the Massachusetts PDMP, MassPAT.
Clinician perceptions of the severity of the opioid crisis in Massachusetts and thoughts on their role as prescribers were consistent across specialty, prescribing level, and practice location. Many clinicians in our sample cited use of the PDMP as an influence on their prescribing. Those practicing in opioid overdose hotspots had the most nuanced reflections about the system.

BACKGROUND: Prescription opioids remain an important contributor to the United States opioid crisis and to the development of opioid use disorder for opioid-naïve individuals. Recent legislative actions, such as the implementation of state prescription drug monitoring programs (PDMPs), aim to reduce opioid morbidity and mortality through enhanced tracking and reporting of prescription data. The primary objective of our study was to describe the opioid prescribing trends in the state of Pennsylvania (PA) as recorded by the PA PDMP following legislative changes in reporting guidelines, and discuss the PDMP\'s role in a multifactorial approach to opioid harm reduction.
METHODS: State-level opioid prescription data summaries recorded by the PA PDMP for each calendar quarter from August 2016 through March 2020 were collected from the PA Department of Health. Data for oxycodone, hydrocodone, and morphine were analyzed by quarter for total prescription numbers and refills. Prescription lengths, pill quantities, and average morphine milliequivalents (MMEs) were analyzed by quarter for all 14 opioid prescription variants recorded by the PA PDMP. Linear regression was conducted for each group of variables to identify significant differences in prescribing trends.
RESULTS: For total prescriptions dispensed, the number of oxycodone, hydrocodone, and morphine prescriptions decreased by 34.4, 44.6, and 22.3% respectively (p < 0.0001). Refills fluctuated less consistently with general peaks in Q3 of 2017 and Q3 of 2018 (p = 0.2878). The rate of prescribing for all opioid prescription lengths decreased, ranging in frequency from 22 to 30 days (47.5% of prescriptions) to 31+ days of opioids (0.8% of prescriptions) (p < 0.0001). Similarly, decreased prescribing was observed for all prescription amounts, ranging in frequency from 22 to 60 pills (36.6% of prescriptions) to 60-90 pills (14.2% of prescriptions) (p < 0.0001). Overall, the average MME per opioid prescription decreased by 18.9%.
CONCLUSIONS: Per the PA PDMP database, opioid prescribing has decreased significantly in PA from 2016 to 2020. The PDMP database is an important tool for tracking opioid prescribing trends in PA, and PDMPs structured similarly in other states may enhance our ability to understand and influence the trajectory of the U.S. opioid crisis. Further research is needed to determine optimal PDMP policies and practices nationwide.

The opioid crisis in the United States has had devastating effects on communities across the country, leading many states to pass legislation that limits the prescription of opioid medications in an effort to reduce the number of overdose deaths. This study evaluates the impact of two categories of PDMP and Pill Mill regulations on the supply of opioid prescriptions at the level of dispensers and distributors (excluding manufacturers) using ARCOS data. The study uses a difference-in-difference method with a two-way fixed design to analyze the data. The study finds that both of the regulations are associated with reductions in the volume of opioid distribution. However, the study reveals that these regulations may have unintended consequences, such as shifting the distribution of controlled substances to neighboring states. For example, in Tennessee, the implementation of Operational PDMP regulations reduces the in-state distribution of opioid drugs by 3.36% (95% CI, 2.37 to 4.3), while the out-of-state distribution to Georgia, which did not have effective PDMP regulations in place, increases by 16.93% (95% CI, 16.42 to 17.44). Our studies emphasize that policymakers should consider the potential for unintended distribution shifts of opioid drugs to neighboring states with laxer regulations as well as varying impacts on different dispenser types.

Artificial intelligence-based (AI) technologies such as machine learning (ML) systems are playing an increasingly relevant role in medicine and healthcare, bringing about novel ethical and epistemological issues that need to be timely addressed. Even though ethical questions connected to epistemic concerns have been at the center of the debate, it is going unnoticed how epistemic forms of injustice can be ML-induced, specifically in healthcare. I analyze the shortcomings of an ML system currently deployed in the USA to predict patients\' likelihood of opioid addiction and misuse (PDMP algorithmic platforms). Drawing on this analysis, I aim to show that the wrong inflicted on epistemic agents involved in and affected by these systems\' decision-making processes can be captured through the lenses of Miranda Fricker\'s account of hermeneutical injustice. I further argue that ML-induced hermeneutical injustice is particularly harmful due to what I define as an automated hermeneutical appropriation from the side of the ML system. The latter occurs if the ML system establishes meanings and shared hermeneutical resources without allowing for human oversight, impairing understanding and communication practices among stakeholders involved in medical decision-making. Furthermore and very much crucially, an automated hermeneutical appropriation can be recognized if physicians are strongly limited in their possibilities to safeguard patients from ML-induced hermeneutical injustice. Overall, my paper should expand the analysis of ethical issues raised by ML systems that are to be considered epistemic in nature, thus contributing to bridging the gap between these two dimensions in the ongoing debate.

UDP-glucose ceramide glucosyltransferase (UGCG) is the first key enzyme in glycosphingolipid (GSL) metabolism that produces glucosylceramide (GlcCer). Increased UGCG synthesis is associated with cell proliferation, invasion and multidrug resistance in human cancers. In this study we investigated the role of UGCG in the pathogenesis of hepatic fibrosis. We first found that UGCG was over-expressed in fibrotic livers and activated hepatic stellate cells (HSCs). In human HSC-LX2 cells, inhibition of UGCG with PDMP or knockdown of UGCG suppressed the expression of the biomarkers of HSC activation (α-SMA and collagen I). Furthermore, pretreatment with PDMP (40 μM) impaired lysosomal homeostasis and blocked the process of autophagy, leading to activation of retinoic acid signaling pathway and accumulation of lipid droplets. After exploring the structure and key catalytic residues of UGCG in the activation of HSCs, we conducted virtual screening, molecular interaction and molecular docking experiments, and demonstrated salvianolic acid B (SAB) from the traditional Chinese medicine Salvia miltiorrhiza as an UGCG inhibitor with an IC50 value of 159 μM. In CCl4-induced mouse liver fibrosis, intraperitoneal administration of SAB (30 mg · kg-1 · d-1, for 4 weeks) significantly alleviated hepatic fibrogenesis by inhibiting the activation of HSCs and collagen deposition. In addition, SAB displayed better anti-inflammatory effects in CCl4-induced liver fibrosis. These results suggest that UGCG may represent a therapeutic target for liver fibrosis; SAB could act as an inhibitor of UGCG, which is expected to be a candidate drug for the treatment of liver fibrosis.