Small molecule produced by Photorhabdus interferes with ubiquinone biosynthesis in Gram-negative bacteria.

We report the identification of 3,6-dihydroxy-1,2-benzisoxazole (DHB) in a screen of Photorhabdus and Xenorhabdus, whose symbiotic relationship with eukaryotic nematodes favors secondary metabolites that meet several requirements matching those for clinically useful antibiotics. DHB is produced by Photorhabdus laumondii and is selective against the Gram-negative species Escherichia coli, Enterobacter cloacae, Serratia marcescens, Klebsiella pneumoniae, Proteus mirabilis, and Acinetobacter baumannii. It is inactive against anaerobic gut bacteria and nontoxic to human cells. Mutants resistant to DHB map to the ubiquinone biosynthesis pathway. DHB binds to 4-hydroxybenzoate octaprenyltransferase (UbiA) and prevents the formation of 4-hydroxy-3-octaprenylbenzoate. Remarkably, DHB itself is prenylated, forming an unusable chimeric product that likely contributes to the toxic effect of this antimicrobial. DHB appears to be both a competitive enzyme inhibitor and a prodrug; this dual mode of action is unusual for an antimicrobial compound. IMPORTANCE: The spread of resistant pathogens has led to the antimicrobial resistance crisis, and the need for new compounds acting against Gram-negative pathogens is especially acute. From a screen of Photorhabdus symbionts of nematodes, we identified 3,6-dihydroxy-1,2-benzisoxazole (DHB) that acts against a range of Gram-negative bacteria, including Escherichia coli, Enterobacter cloacae, Klebsiella pneumoniae, and Acinetobacter baumannii. DHB had previously been isolated from other bacterial species, but its mechanism of action remained unknown. We show that DHB is unique among antimicrobials, with dual action as an inhibitor of an important enzyme, UbiA, in the biosynthesis pathway of ubiquinone and as a prodrug. DHB is a mimic of the natural substrate, and UbiA modifies it into a toxic product, contributing to the antimicrobial action of this unusual antibiotic. We also uncover the mechanism of DHB selectivity, which depends on a particular fold of the UbiA enzyme.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched.

Background: Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment. Results: We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD. Conclusions: visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

A Reconfigurable Proangiogenic Hydrogel Patch Enabling Minimally Invasive Drug Delivery.

Hydrogel is widely used for the sustained delivery of bioactive molecules that can treat various injuries, diseases, and tissue defects. However, inserting hydrogel implants without disrupting their functionality and microstructure often requires a large incision, leading to potential complications, such as infection, scarring, and pain. The gel implant is often manually rolled and inserted through a catheter for a minimally invasive delivery. However, success heavily depends on the user's skills, which can inadvertently damage the implant. To address this issue, we developed a reconfigurable hydrogel patch that can self-fold into a small tube and unfold spontaneously after implantation through a catheter. The hydrogel path was assembled by layering a drug-releasing poly(ethylene glycol) diacrylate (PEGDA) hydrogel sheet onto a PEGDA and polyethylenimine (PEI) hydrogel sheet, which rapidly swells and degrades homogeneously at controlled rates. The dynamics of the self-folding and unfolding process could be controlled by differences in the expansion ratio and elastic modulus between the two gel layers according to a mathematical model that closely matched experimental results. The unfolding process triggered a sustained release of the protein cargo. Specifically, the reconfigurable gel loaded with angiopoietin 1 significantly enhanced neovascularization, nearly doubling the vascular density compared to the control group following implantation through a tube with 15% smaller diameter than the original shape of the gel patch. This gel biopatch will be broadly useful for the minimally invasive delivery of a wide array of therapeutic molecules, potentially enhancing therapeutic outcomes.

Cost Offset of Dapagliflozin in the US Medicare Population with Cardio-Kidney Metabolic Syndrome.

INTRODUCTION: Cardiovascular-kidney-metabolic (CKM) syndrome is highly prevalent in the US Medicare population and is projected to increase further. Sodium-glucose co-transporter 2 inhibitors have indications in chronic kidney disease (CKD), heart failure (HF), and type 2 diabetes (T2D), providing protective efficacy across conditions within CKM syndrome. The objective of this study was to develop a model to extrapolate key outcomes observed in pivotal clinical trials to the US Medicare population, and to assess the potential direct cost offsets associated with dapagliflozin therapy. METHODS: All US 2022 Medicare beneficiaries (≥ 65 years of age) eligible to receive dapagliflozin were estimated according to drug label indication and Medicare enrollment and claims data. Incidence of key outcomes from the dapagliflozin clinical program were modelled over a 4-year time horizon based on patient-level data with CKD, HF, and T2D. Published cost data of relevant clinical outcomes were used to calculate direct medical care cost-offset associated with treatment with dapagliflozin. RESULTS: In a population of 13.1 million patients with CKM syndrome, treatment with dapagliflozin in addition to historical standard of care (hSoC) versus hSoC alone led to fewer incidents of HF-related events (hospitalization for HF, 613,545; urgent HF visit, 98,896), renal events (kidney failure, 285,041; ≥ 50% sustained decline in kidney function, 375,137), and 450,355 fewer deaths (of which 225,346 and 13,206 incidences of cardiovascular and renal death were avoided). In total this led to medical care cost offsets of $99.3 billion versus treatment with hSoC only (dapagliflozin plus hSoC, $310.3 billion; hSoC, $211.0 billion). CONCLUSION: By extrapolating data from trials across multiple indications within CKM syndrome, this broader perspective shows that considerable medical care cost offsets may result through attenuated incidence of clinical events in CKD, T2D, and HF populations if treated with dapagliflozin in addition to hSoC over a 4-year time horizon. Graphical abstract available for this article.

Neuritin 1 Drives Therapeutic Preservation of Retinal Ganglion Cells in an Ex Vivo Human Glaucoma Model.

Purpose: Glaucoma is a leading cause of irreversible blindness. Glaucomatous intraocular pressure (IOP) triggers deleterious effects, including gliosis, optic nerve (ON) axonal retraction, neurotrophic factor deprivation, inflammation, and other pathological events, leading to retinal ganglion cell (RGC) loss. Trophic factor impairment enhances RGC apoptosis susceptibility. Neuritin 1 (NRN1), a neurotrophic protein downstream of various neurotrophins, exhibited RGC protection and regeneration in axotomy models. We evaluated human recombinant NRN1's impact on human RGCs cultured in pressurized conditions within the ex vivo translaminar autonomous system to simulate glaucoma pathogenesis. Methods: Human glaucomatous and non-glaucomatous donor eyes were obtained from eye banks according to the Declaration of Helsinki. Initially, we evaluated NRN1and RGC marker expression in glaucoma and non-glaucomatous retina to determine the NRN1 level and its association with RGC loss. Further, we evaluated NRN1's therapeutic potential by treating pressurized human eyes at normal and high IOP for seven days. Retina, ON, and conditioned medium were analyzed for RGC survival (THY1, RBPMS), gliosis (GFAP), apoptosis (CASP3, CASP7), and extracellular matrix deposition (COLIV, FN) by qRT-PCR and western blotting. Paraphenylenediamine staining assessed ON axonal degeneration, whereas ex vivo electroretinogram assessed retinal activity. Results: Glaucomatous retinas exhibited significant reductions in both NRN1 (*p = 0.007, n = 5) and RGC marker expression (*p = 0.04, n = 5). NRN1 treatment reduced gliosis, extracellular matrix deposition, ON degeneration, and increased retinal activity in pressure-perfused eyes. Conclusions: Our study confirms that NRN1 enhances human RGC survival and improves retinal function in degenerative conditions, substantiating it as a promising candidate for rescuing human RGCs from degeneration.

Association Between Time From Surgery to Radiation Therapy and Multimodality Treatment Outcomes in HPV+ Head and Neck Cancer: A Multi-Institutional Cohort Experience.

Purpose: Oropharyngeal squamous cell cancers (OPSCCs) are traditionally managed with surgery and, if indicated, adjuvant radiation therapy (RT) with or without chemotherapy. NCCN recommends keeping the time from surgery to the start of RT (TSRT) within 6 weeks to avoid possibly compromising patient outcomes. HPV+ OPSCCs behave more favorably than HPV- OPSCCs. We hypothesized that TSRT beyond 6 weeks may not portend poorer outcomes for the former. Methods: We identified nonmetastatic, high-risk HPV+ OPSCCs treated with multimodal therapy at 2 institutions. Prolonged TSRT was defined as >6 weeks and was evaluated for association with recurrence-free survival (RFS). Radiation treatment time (RTT; time from the first to the last day of RT), total treatment package time (TTPT; time from surgery to the end of adjuvant treatments), de-escalated RT (dose ≤56 Gy), concurrent chemotherapy, smoking history, and treatment institution were evaluated as possible confounders. Results: In total, 96 patients were included. The median follow-up time was 62 months (4-123 months); 69 patients underwent transoral robotic surgeries, and 27 received open surgeries. The median postoperative RT dose was 60 Gy (50-70.8 Gy). The median TSRT, RTT, and TTPT were 38 days (11-208), 43 days (26-56 days), and 81 days (40-255 days), respectively. Ten patients failed treatment at a median of 8 months (4-64 months). Two locoregional and 4 distant failures occurred in the group without prolonged TSRT, whereas 2 locoregional and 2 distant failures were recorded in the prolonged TSRT group. Prolonged TTPT, de-escalated RT, chemotherapy, smoking history, and treatment institution were not associated with treatment failure. RTT was dropped from our analyses as no events appeared in the prolonged RTT group, and no reliable hazard ratio could be computed. Conclusions: TSRT > 6 weeks was not significantly associated with inferior outcomes in the postoperative management of HPV+ OPSCCs. Longer TSRT may facilitate better recovery from surgical toxicity, as needed, without compromising oncologic outcomes. The TSRT goal for these cancers should be investigated in future studies.

Fluorescein-Based SynNotch Adaptors for Regulating Gene Expression Responses to Diverse Extracellular Cues.

We introduce an adaptor-based strategy for regulating fluorescein-binding synthetic Notch (SynNotch) receptors using ligands based on conjugates of fluorescein isomers and analogs. To develop a versatile system, we evaluated the surface expression and activities of multiple constructs containing distinct extracellular fluorescein-binding domains. Using an optimized receptor, we devised ways to regulate signaling via fluorescein-based chemical transformations, including an approach based on a bio-orthogonal chemical ligation and a spatially controllable strategy via the photo-patterned uncaging of an o -nitrobenzyl-caged fluorescein conjugate. We further demonstrate that fluorescein-conjugated extracellular matrix (ECM)-binding peptides can regulate SynNotch activity depending on the folding state of collagen-based ECM networks. Treatment with these conjugates enabled cells to distinguish between folded versus denatured collagen proteins and enact dose-dependent gene expression responses depending on the nature of the signaling adaptors presented. To demonstrate the utility of these tools, we applied them to control the myogenic conversion of fibroblasts into myocytes with spatial and temporal precision and in response to denatured collagen-I, a biomarker of multiple pathological states. Overall, we introduce an optimized fluorescein-binding SynNotch as a versatile tool for regulating transcriptional responses to extracellular ligands based on the widely used and clinically-approved fluorescein dye.

Modeling of spatiotemporal dynamics of ligand-coated particle flow in targeted drug delivery processes.

Nanoparticles tethered with vasculature-binding epitopes have been used to deliver the drug into injured or diseased tissues via the bloodstream. However, the extent that blood flow dynamics affects nanoparticle retention at the target site after adhesion needs to be better understood. This knowledge gap potentially underlies significantly different therapeutic efficacies between animal models and humans. An experimentally validated mathematical model that accurately simulates the effects of blood flow on nanoparticle adhesion and retention, thus circumventing the limitations of conventional trial-and-error-based drug design in animal models, is lacking. This paper addresses this technical bottleneck and presents an integrated mathematical method that derives heavily from a unique combination of a mechanics-based dispersion model for nanoparticle transport and diffusion in the boundary layers, an asperity model to account for surface roughness of endothelium, and an experimentally calibrated stochastic nanoparticle-cell adhesion model to describe nanoparticle adhesion and subsequent retention at the target site under external flow. PLGA-b-HA nanoparticles tethered with VHSPNKK peptides that specifically bind to vascular cell adhesion molecules on the inflamed vascular wall were investigated. The computational model revealed that larger particles perform better in adhesion and retention at the endothelium for the particle sizes suitable for drug delivery applications and within physiologically relevant shear rates. The computational model corresponded closely to the in vitro experiments which demonstrates the impact that model-based simulations can have on optimizing nanocarriers in vascular microenvironments, thereby substantially reducing in vivo experimentation as well as the development costs.

Transcriptomic characterization of human lateral septum neurons reveals conserved and divergent marker genes across species.

The lateral septum (LS) is a midline, subcortical structure, which regulates social behaviors that are frequently impaired in neurodevelopmental disorders including schizophrenia and autism spectrum disorder. Mouse studies have identified neuronal populations within the LS that express a variety of molecular markers, including vasopressin receptor, oxytocin receptor, and corticotropin releasing hormone receptor, that control specific facets of social behavior. Despite its critical role in the regulation of social behavior and notable gene expression patterns, comprehensive molecular profiling of the human LS has not been performed. Here, we conducted single nucleus RNA-sequencing (snRNA-seq) to generate the first transcriptomic profiles of the human LS using postmortem human brain tissue samples from 3 neurotypical donors. Our analysis identified 4 transcriptionally distinct neuronal cell types within the human LS that are enriched for TRPC4, the gene encoding Trp-related protein 4. Differential expression analysis revealed a distinct LS neuronal cell type that is enriched for OPRM1, the gene encoding the µ-opioid receptor. Leveraging recently collected mouse LS snRNA-seq datasets, we also conducted a cross-species analysis. Our results demonstrate that TRPC4 enrichment in the LS is highly conserved between human and mouse, while FREM2, which encodes FRAS1 related extracellular matrix protein 2, is enriched only in the human LS. Together, these results highlight transcriptional heterogeneity of the human LS, and identify robust marker genes for the human LS.

Precocious Puberty and GnRH Analogs: Current Treatment Practices and Perspectives among US Pediatric Endocrinologists.

INTRODUCTION: Gonadotropin releasing hormone analogs (GnRHas) are used for treatment of precocious puberty. Over the last decade, several new formulations have been approved. METHODS: The Drugs and Therapeutics Subcommittee of the Pediatric Endocrine Society (PES) undertook a review to ascertain the current treatment options, prescribing behaviors, and practices of GnRHas among pediatric endocrinologists practicing within the USA. The survey consisted of four main subsections: (1) description of clinical practice; (2) self-assessment of knowledge base of pediatric and adult GnRHa formulations; (3) current practice for treating central precocious puberty (CPP); and (4) utilization of healthcare resources. RESULTS: There were 223 survey respondents. Pediatric endocrine practitioners were most familiar with the pediatric one-monthly preparation, the 3-month preparation, and the histrelin implant (Supprelin®) (88%, 96%, and 91%, respectively), with lower familiarity for 24-week triptorelin intramuscular (Triptodur®) (65%) and 6-month subcutaneous leuprolide (Fensolvi®) (45%). Only 23% of the respondents reported being extremely familiar with the availability of adult formulations, and 25% reported being completely unaware of cost differences between pediatric and adult GnRHa preparations. The implant was the most preferred therapy (44%), but in practice, respondents reported a higher percentage of patients treated with the 3-month preparation. While family preference/ease of treatment (87%) was the key determinant for using a particular GnRHa preparation, insurance coverage also played a significant role in the decision (64%). Responses regarding assessment for efficacy of treatment were inconsistent, as were practices and criteria for obtaining an MRI. CONCLUSIONS: The survey indicated there is more familiarity with older, shorter acting GnRHas, which are prescribed in greater numbers than newer, longer acting formulations. There is lack of consensus on the need for central nervous system (CNS) imaging in girls presenting with CPP between 6 and 8 years of age and use of laboratory testing to monitor response to treatment. Insurance requirements regarding CNS imaging and laboratory monitoring are highly variable. Despite having similar constituents and bioavailability, there are substantial cost differences between the pediatric and adult formulations and lack of evidence for safe use of these formulations in children. The survey-based analysis highlights the challenges faced by prescribers while reflecting on areas where further research is needed to provide evidence-based practice guidelines for pediatric endocrinologists.

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. We defined molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and infer the expression of these patterns in the SRT data. With this approach, we leveraged existing rodent datasets that feature information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

Prospective Trial of Functional Lung Avoidance Radiation Therapy for Lung Cancer: Quality of Life Report.

PURPOSE: A novel form of lung function imaging has been developed that uses 4-dimensional computed tomography (4DCT) data to generate lung ventilation images (4DCT-ventilation). Functional avoidance uses 4DCT-ventilation to reduce doses to functional lung with the aim of reducing pulmonary side effects. A phase 2, multicenter 4DCT-ventilation functional avoidance clinical trial was completed. The purpose of this work was to quantify changes in patient-reported outcomes (PROs) for patients treated with functional avoidance and determine which metrics are predictive of PRO changes. MATERIALS AND METHODS: Patients with locally advanced lung cancer receiving curative-intent radiation therapy were accrued. Each patient had a 4DCT-ventilation image generated using 4DCT data and image processing. PRO instruments included the Functional Assessment of Cancer Therapy-Lung (FACT-L) questionnaire administered pretreatment; at the end of treatment; and at 3, 6, and 12 months posttreatment. Using the FACT-Trial Outcome Index and the FACT-Lung Cancer Subscale results, the percentage of clinically meaningful declines (CMDs) were determined. A linear mixed-effects model was used to determine which patient, clinical, dose, and dose-function metrics were predictive of PRO decline. RESULTS: Of the 59 patients who completed baseline PRO surveys. 83% had non-small cell lung cancer, with 75% having stage 3 disease. The median dose was 60 Gy in 30 fractions. CMD FACT-Trial Outcome Index decline was 46.3%, 38.5%, and 26.8%, at 3, 6, and 12 months, respectively. CMD FACT-Lung Cancer Subscale decline was 33.3%, 33.3%, and 29.3%, at 3, 6, and 12 months, respectively. Although an increase in most dose and dose-function parameters was associated with a modest decline in PROs, none of the results were significant (all P > .053). CONCLUSIONS: The current work presents an innovative combination of use of functional avoidance and PRO assessment and is the first report of PROs for patients treated with prospective 4DCT-ventilation functional avoidance. Approximately 30% of patients had clinically significant decline in PROs at 12 months posttreatment. The study provides additional data on outcomes with 4DCT-ventilation functional avoidance.

PMechDB: A Public Database of Elementary Polar Reaction Steps.

Most online chemical reaction databases are not publicly accessible or are fully downloadable. These databases tend to contain reactions in noncanonicalized formats and often lack comprehensive information regarding reaction pathways, intermediates, and byproducts. Within the few publicly available databases, reactions are typically stored in the form of unbalanced, overall transformations with minimal interpretability of the underlying chemistry. These limitations present significant obstacles to data-driven applications including the development of machine learning models. As an effort to overcome these challenges, we introduce PMechDB, a publicly accessible platform designed to curate, aggregate, and share polar chemical reaction data in the form of elementary reaction steps. Our initial version of PMechDB consists of over 100,000 such steps. In the PMechDB, all reactions are stored as canonicalized and balanced elementary steps, featuring accurate atom mapping and arrow-pushing mechanisms. As an online interactive database, PMechDB provides multiple interfaces that enable users to search, download, and upload chemical reactions. We anticipate that the public availability of PMechDB and its standardized data representation will prove beneficial for chemoinformatics research and education and the development of data-driven, interpretable models for predicting reactions and pathways. PMechDB platform is accessible online at https://deeprxn.ics.uci.edu/pmechdb.

African swine fever at the wildlife-livestock interface: challenges for management and outbreak response within invasive wild pigs in the United States.

African swine fever (ASF) causes significant morbidity and mortality in both domestic and wild suids (Sus scrofa), and disease outbreaks convey profound economic costs to impacted industries due to death loss, the cost of culling exposed/infected animals as the primary disease control measure, and trade restrictions. The co-occurrence of domestic and wild suids significantly complicates ASF management given the potential for wild populations to serve as persistent sources for spillover. We describe the unique threat of African swine fever virus (ASFV) introduction to the United States from epidemiological and ecological perspectives with a specific focus on disease management at the wild-domestic swine interface. The introduction of ASF into domestic herds would require a response focused on containment, culling, and contact tracing. However, detection of ASF among invasive wild pigs would require a far more complex and intensive response given the challenges of detection, containment, and ultimately elimination among wild populations. We describe the state of the science available to inform preparations for an ASF response among invasive wild pigs, describe knowledge gaps and the associated studies needed to fill those gaps, and call for an integrated approach for preparedness that incorporates the best available science and acknowledges sociological attributes and the policy context needed for an integrated disease response.

Seeking arrangements: cell contact as a cleavage-stage biomarker.

RESEARCH QUESTION: What can three-dimensional cell contact networks tell us about the developmental potential of cleavage-stage human embryos? DESIGN: This pilot study was a retrospective analysis of two Embryoscope imaging datasets from two clinics. An artificial intelligence system was used to reconstruct the three-dimensional structure of embryos from 11-plane focal stacks. Networks of cell contacts were extracted from the resulting embryo three-dimensional models and each embryo's mean contacts per cell was computed. Unpaired t-tests and receiver operating characteristic curve analysis were used to statistically analyse mean cell contact outcomes. Cell contact networks from different embryos were compared with identical embryos with similar cell arrangements. RESULTS: At t4, a higher mean number of contacts per cell was associated with greater rates of blastulation and blastocyst quality. No associations were found with biochemical pregnancy, live birth, miscarriage or ploidy. At t8, a higher mean number of contacts was associated with increased blastocyst quality, biochemical pregnancy and live birth. No associations were found with miscarriage or aneuploidy. Mean contacts at t4 weakly correlated with those at t8. Four-cell embryos fell into nine distinct cell arrangements; the five most common accounted for 97% of embryos. Eight-cell embryos, however, displayed a greater degree of variation with 59 distinct cell arrangements. CONCLUSIONS: Evidence is provided for the clinical relevance of cleavage-stage cell arrangement in the human preimplantation embryo beyond the four-cell stage, which may improve selection techniques for day-3 transfers. This pilot study provides a strong case for further investigation into spatial biomarkers and three-dimensional morphokinetics.

Genome-Wide Association Studies of ARIA From the Aducanumab Phase 3 ENGAGE and EMERGE Studies.

BACKGROUND AND OBJECTIVES: Amyloid-related imaging abnormalities (ARIA) were the most common adverse events reported in the phase 3 ENGAGE and EMERGE trials of aducanumab, an anti-amyloid monoclonal antibody. APOE ε4 carrier status has been shown to increase risk of ARIA in prior trials of aducanumab and other anti-amyloid therapies; however, the remainder of the human genome has not been evaluated for ARIA risk factors. Therefore, we sought to determine in a hypothesis-free manner whether genetic variants beyond APOE influence risk of ARIA in aducanumab-treated patients. METHODS: We performed genome-wide association studies (GWAS) of ARIA in participants in the ENGAGE and EMERGE trials. Participants had mild cognitive impairment due to Alzheimer disease or mild Alzheimer disease dementia and were amyloid-positive on PET scans. All participants underwent regular MRI monitoring to detect and diagnose ARIA. RESULTS: Of the 3,285 participants in the intent-to-treat population, this analysis included 1,691 with genotyping array data who received at least one dose of aducanumab with at least one post-baseline MRI. All participants in the study cohort were of European ancestry; 51% were female. The mean age was 70.3 years. 31% had ARIA-E, 19% had ARIA-H microhemorrhage, and 14% had ARIA-H superficial siderosis. We identified one genome-wide significant (p < 5.0 × 10-8) association at the chromosome 19 locus encompassing APOE. The APOE association with ARIA was stronger in ε4/ε4 homozygotes (OR = 4.28, 4.58, 7.84; p < 2.9 × 10-14 for ARIA-E, ARIA-H microhemorrhage, and ARIA-H superficial siderosis, respectively) than in ε3/ε4 heterozygotes (OR = 1.74, 1.46, 3.14; p ≤ 0.03). We found greater odds of radiographically severe ARIA (OR = 7.04-24.64, p ≤ 2.72 × 10-5) than radiographically mild ARIA (OR = 3.19-5.00, p ≤ 1.37 × 10-5) among ε4/ε4 homozygotes. APOE ε4 was also significantly associated with both symptomatic (ε4/ε4 OR = 3.64-9.52; p < 0.004) and asymptomatic (ε4/ε4 OR = 4.20-7.94, p < 1.7 × 10-11) cases, although among ARIA cases, APOE did not appear to modulate symptomatic status. No other genome-wide significant associations were found. DISCUSSION: We identified a strong, genome-wide significant association between APOE and risk of ARIA. Future, larger studies may be better powered to detect associations beyond APOE. These findings indicate that APOE is the strongest genetic risk factor of ARIA incidence, with implications for patient management and risk-benefit treatment decisions. TRIAL REGISTRATION INFORMATION: Both trials (ENGAGE [221AD301]: NCT02477800 and EMERGE [221AD302]: NCT02484547) were registered in June 2015 at clinicaltrials.gov and enrolled patients from August 2015 to July 2018.

Predicting changes in driving performance in individuals who use cannabis following acute use based on self-reported readiness to drive.

OBJECTIVE: It is unclear to what extent individuals who use cannabis can accurately assess their ability to drive safely following cannabis use, and lack of understanding as to what factors influence changes in driving performance following cannabis use. This research explores whether self-reported readiness to drive (RTD) and previous experience (PE) using cannabis within 2 h of driving can predict observed changes in driving performance following acute cannabis use. METHODS: Individuals who used cannabis at least monthly completed a baseline simulated drive, were dosed with cannabis of approximately 6.18% THC, then drove at approximately 30-minutes, 90-minutes, and 180-minutes post-dose. Before each drive, participants were asked if they felt safe to drive (on real roadways, not the simulator), a yes/no question (RTD-yes/RTD-no). Venous blood was drawn at baseline and approximately 15-minutes post-dose. Cannabis use history was obtained and included whether the participant had ever driven within 2 h of use (PE-yes/PE-no) and how many days out of the past 30 they had done so (NPD). Drives were segmented into events delineated by changes in the driving environment. Within events, standard deviation of lateral position (SDLP), average speed, and number of lane departures were calculated, and differences from baseline were modeled using mixed-effects regression. Models considered covariates of time, event, and speed, and used RTD-yes/RTD-no, PE-yes/PE-no, NPD, and their interactions as potential predictors. Conditional R2 was used to compare the predictive ability of RTD versus change in Delta-9-THC. DATA SOURCES: Data were collected from 30 individuals who use cannabis and included cannabis use patterns, driving behaviors after use, self-reported RTD, measures of driving performance, and cannabinoid blood levels. RESULTS: RTD-no predicted a 2.60 cm increase in SDLP relative to baseline (95 % CI: 0.43, 4.73, p = 0.018). Average speeds generally decreased relative to baseline, except for RTD-yes with PE-yes (+1.08 mph, 95 % CI: 0.05, 2.11). NPD predicted increased speed among RTD-yes (+0.11 mph per additional day, 95 % CI: 0.01, 0.22) and decreased speed among RTD-no (-0.06 mph per additional day, 95 % CI: -0.18, 0.32). The difference in these effects was statistically significant (p = 0.038). RTD, PE, and NPD were not significant predictors of changes in number of lane departures. For all outcomes, models using RTD achieved higher conditional R2 than models that replaced this variable with change in Delta-9-THC. Differences were most prominent when modeling change in speed with NPD (R2=0.544 with RTD vs. R2=0.481 with change in Delta-9-THC). SIGNIFICANCE OF RESULTS: These results suggest individuals who use cannabis can somewhat self-identify when they are likely to exhibit greater degraded lateral control, although RTD does not fully explain observed degradation in performance. Past research suggests drivers may reduce speed to compensate for recognized impairment following acute cannabis use. Our findings suggest this to be true for those who reported never having previously driven within 2 h of cannabis use or reported RTD-no, but not for those who had previously driven within 2 h of cannabis use and reported RTD-yes. This indicates compensatory behavior is not uniform and helps focus public health outreach efforts.

Estimating the Treatment and Prophylactic Economic Value of New Antimicrobials in Managing Antibiotic Resistance and Serious Infections for Common Pathogens in the USA: A Population Modelling Study.

BACKGROUND: Antimicrobial resistance is a growing public health concern. There is a global need to estimate the population-level value of developing new antimicrobials and to ensure the effective use of existing antimicrobials as strategies to counteract antimicrobial resistance. To this aim, population-level value criteria need to be considered alongside conventional value measures. OBJECTIVE: The objective of this study was to develop a novel modelling approach to estimate the value of new antimicrobials, considering the transmission, diversity and enablement elements of STEDI value. METHODS: We developed a population-based mathematical model for the assessment of antimicrobial value considering both prophylactic use of antimicrobials and the treatment of selected serious hospital-acquired infections in hospitals in the USA at a population level. Large-scale clinical and population healthcare data were used to inform a modelling-based analysis assessing the impact of introducing a new antimicrobial compared with continuing with no new antimicrobial, accounting for the transmission, diversity and enablement value of antimicrobial agents. RESULTS: Over a 10-year period, the addition of a new antimicrobial as part of an antimicrobial stewardship strategy in the USA was estimated to result in a proportional reduction of 9.03% in projected antimicrobial resistance levels. This yielded an estimated reduction of $64.3 million in hospitalization costs and a gain of over 153,000 quality-adjusted life-years at an economic value of over $15.4 billion over 10 years. Considering input uncertainty, the estimate of monetary benefit ranged from $11.1 to $21.4 billion. CONCLUSIONS: The use of a new antimicrobial for treatment and prophylactic indications yields considerable clinical and economic benefits including transmission diversity and enablement value. These findings may provide decision makers with important evidence to support investment in new antimicrobials and antimicrobial stewardship policy that address the patient, population and system burden associated with antimicrobial resistance.

Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population.

OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarboxylase deficiency (AADCd), an autosomal recessive disease caused by pathogenic variants in the dopa decarboxylase gene. Deficiency of the AADC enzyme results in combined severe reductions in monoamine neurotransmitters: dopamine, serotonin, epinephrine, and norepinephrine. This leads to widespread neurological complications affecting motor, behavioral, and autonomic function. The goal of this study was to use EHR data to identify previously undiagnosed patients who may have AADCd without available training cases for the disease. MATERIALS AND METHODS: A multiple symptom and related disease annotated dataset was created and used to train individual concept classifiers on annotated sentence data. A multistep algorithm was then used to combine concept predictions into a single patient rank value. RESULTS: Using an 8000-patient dataset that the algorithms had not seen before ranking, the top and bottom 200 ranked patients were manually reviewed for clinical indications of performing an AADCd diagnostic screening test. The top-ranked patients were 22.5% positively assessed for diagnostic screening, with 0% for the bottom-ranked patients. This result is statistically significant at P < .0001. CONCLUSION: This work validates the approach that large-scale rare-disease screening can be accomplished by combining predictions for relevant individual symptoms and related conditions which are much more common and for which training data is easier to create.