Neuronal STING activation in amyotrophic lateral sclerosis and frontotemporal dementia.

The stimulator of interferon genes (STING) pathway has been implicated in neurodegenerative diseases, including Parkinson's disease and amyotrophic lateral sclerosis (ALS). While prior studies have focused on STING within immune cells, little is known about STING within neurons. Here, we document neuronal activation of the STING pathway in human postmortem cortical and spinal motor neurons from individuals affected by familial or sporadic ALS. This process takes place selectively in the most vulnerable cortical and spinal motor neurons but not in neurons that are less affected by the disease. Concordant STING activation in layer V cortical motor neurons occurs in a mouse model of C9orf72 repeat-associated ALS and frontotemporal dementia (FTD). To establish that STING activation occurs in a neuron-autonomous manner, we demonstrate the integrity of the STING signaling pathway, including both upstream activators and downstream innate immune response effectors, in dissociated mouse cortical neurons and neurons derived from control human induced pluripotent stem cells (iPSCs). Human iPSC-derived neurons harboring different familial ALS-causing mutations exhibit increased STING signaling with DNA damage as a main driver. The elevated downstream inflammatory markers present in ALS iPSC-derived neurons can be suppressed with a STING inhibitor. Our results reveal an immunophenotype that consists of innate immune signaling driven by the STING pathway and occurs specifically within vulnerable neurons in ALS/FTD.

High-throughput genetic manipulation of multicellular organisms using a machine-vision guided embryonic microinjection robot.

Microinjection is a technique used for transgenesis, mutagenesis, cell labeling, cryopreservation, and in vitro fertilization in multiple single and multicellular organisms. Microinjection requires specialized skills and involves rate-limiting and labor-intensive preparatory steps. Here, we constructed a machine-vision guided generalized robot that fully automates the process of microinjection in fruit fly (Drosophila melanogaster) and zebrafish (Danio rerio) embryos. The robot uses machine learning models trained to detect embryos in images of agar plates and identify specific anatomical locations within each embryo in 3D space using dual view microscopes. The robot then serially performs a microinjection in each detected embryo. We constructed and used three such robots to automatically microinject tens of thousands of Drosophila and zebrafish embryos. We systematically optimized robotic microinjection for each species and performed routine transgenesis with proficiency comparable to highly skilled human practitioners while achieving up to 4× increases in microinjection throughput in Drosophila. The robot was utilized to microinject pools of over 20,000 uniquely barcoded plasmids into 1,713 embryos in 2 days to rapidly generate more than 400 unique transgenic Drosophila lines. This experiment enabled a novel measurement of the number of independent germline integration events per successfully injected embryo. Finally, we showed that robotic microinjection of cryoprotective agents in zebrafish embryos significantly improves vitrification rates and survival of cryopreserved embryos post-thaw as compared to manual microinjection. We anticipate that the robot can be used to carry out microinjection for genome-wide manipulation and cryopreservation at scale in a wide range of organisms.

Conduction-Dominated Cryomesh for Organism Vitrification.

Vitrification-based cryopreservation is a promising approach to achieving long-term storage of biological systems for maintaining biodiversity, healthcare, and sustainable food production. Using the "cryomesh" system achieves rapid cooling and rewarming of biomaterials, but further improvement in cooling rates is needed to increase biosystem viability and the ability to cryopreserve new biosystems. Improved cooling rates and viability are possible by enabling conductive cooling through cryomesh. Conduction-dominated cryomesh improves cooling rates from twofold to tenfold (i.e., 0.24 to 1.2 × 105  °C min-1 ) in a variety of biosystems. Higher thermal conductivity, smaller mesh wire diameter and pore size, and minimizing the nitrogen vapor barrier (e.g., vertical plunging in liquid nitrogen) are key parameters to achieving improved vitrification. Conduction-dominated cryomesh successfully vitrifies coral larvae, Drosophila embryos, and zebrafish embryos with improved outcomes. Not only a theoretical foundation for improved vitrification in µm to mm biosystems but also the capability to scale up for biorepositories and/or agricultural, aquaculture, or scientific use are demonstrated.

iPSC motor neurons, but not other derived cell types, capture gene expression changes in postmortem sporadic ALS motor neurons.

Motor neuron degeneration, the defining feature of amyotrophic lateral sclerosis (ALS), is a primary example of cell-type specificity in neurodegenerative diseases. Using isogenic pairs of induced pluripotent stem cells (iPSCs) harboring different familial ALS mutations, we assess the capacity of iPSC-derived lower motor neurons, sensory neurons, astrocytes, and superficial cortical neurons to capture disease features including transcriptional and splicing dysregulation observed in human postmortem neurons. At early time points, differentially regulated genes in iPSC-derived lower motor neurons, but not other cell types, overlap with one-third of the differentially regulated genes in laser-dissected motor neurons from ALS compared with control postmortem spinal cords. For genes altered in both the iPSC model and bona fide human lower motor neurons, expression changes correlate between the two populations. In iPSC-derived lower motor neurons, but not other derived cell types, we detect the downregulation of genes affected by TDP-43-dependent splicing. This reduction takes place exclusively within genotypes known to involve TDP-43 pathology.

Conservation of the Restricted Expression of Brassicaceae Bsister-Like Genes in Seeds Requires a Transposable Element in Arabidopsis thaliana.

Changes in transcription factor binding sites (TFBSs) can alter the spatiotemporal expression pattern and transcript abundance of genes. Loss and gain of TFBSs were shown to cause shifts in expression patterns in numerous cases. However, we know little about the evolution of extended regulatory sequences incorporating many TFBSs. We compare, across the crucifers (Brassicaceae, cabbage family), the sequences between the translated regions of Arabidopsis Bsister (ABS)-like MADS-box genes (including paralogous GOA-like genes) and the next gene upstream, as an example of family-wide evolution of putative upstream regulatory regions (PURRs). ABS-like genes are essential for integument development of ovules and endothelium formation in seeds of Arabidopsis thaliana. A combination of motif-based gene ontology enrichment and reporter gene analysis using A. thaliana as common trans-regulatory environment allows analysis of selected Brassicaceae Bsister gene PURRs. Comparison of TFBS of transcriptionally active ABS-like genes with those of transcriptionally largely inactive GOA-like genes shows that the number of in silico predicted TFBS) is similar between paralogs, emphasizing the importance of experimental verification for in silico characterization of TFBS activity and analysis of their evolution. Further, our data show highly conserved expression of Brassicaceae ABS-like genes almost exclusively in the chalazal region of ovules. The Arabidopsis-specific insertion of a transposable element (TE) into the ABS PURRs is required for stabilizing this spatially restricted expression, while other Brassicaceae achieve chalaza-specific expression without TE insertion. We hypothesize that the chalaza-specific expression of ABS is regulated by cis-regulatory elements provided by the TE.

Early spring onset increases carbon uptake more than late fall senescence: modeling future phenological change in a US northern deciduous forest.

In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models. Here, we optimized the phenology algorithms in a regionally developed biogeochemical model (PnET-CN) using phenology data from eight mid-latitude PhenoCam sites in eastern North America. We then performed a sensitivity analysis to determine how the optimization affected future predictions of carbon, water, and nitrogen cycling at Bartlett Experimental Forest, New Hampshire. Compared to the original PnET-CN phenology models, our new spring and fall models resulted in shorter season lengths and more abrupt transitions that were more representative of observations. The new phenology models affected daily estimates and interannual variability of modeled carbon exchange, but they did not have a large influence on the magnitude or long-term trends of annual totals. Under future climate projections, our new phenology models predict larger shifts in season length in the fall (1.1-3.2 days decade-1) compared to the spring (0.9-1.5 days decade-1). However, for every day the season was longer, spring had twice the effect on annual carbon and water exchange totals compared to the fall. These findings highlight the importance of accurately modeling season length for future projections of carbon and water cycling.

Sentiments Evoked by WHO Public Health Posts During the COVID-19 Pandemic: A Neural Network-Based Machine Learning Analysis.

Introduction The World Health Organization (WHO) is a specialized agency of the United Nations responsible for international public health. Established on April 7, 1948, it has since played a pivotal role in several public health achievements and has had considerable success. But never since the establishment of the WHO has it faced a pandemic of such a huge scale. The spread of the coronavirus and the inability of the WHO to contain it has raised many questions about its efficiency and role. The present study explores the range of emotions and sentiments evoked by public health information posts of WHO over the course of the pandemic. Methods This study uses Bidirectional Encoder Representations from Transformers (BERT), which is a neural network-based technique for natural language processing. Three timeframes of five months each, starting from March 2020, were defined. A total of six posts, two posts from each timeframe, were then analysed. Comments were classified as positive, neutral and negative. The broader positive and negative classes were further subclassified into two classes each. Natural language processing was further applied to obtain results. Results The general trend of the sentiments over the period of pandemic showed a significant and dominant proportion of negative comments that overshadowed the neutral, positive and irrelevant comments over all timeframes. Specifically, the negative sentiments peaked during the second timeframe. The negativity was directed more towards the WHO, governments and people not complying with coronavirus disease 2019-appropriate norms. Positive comments were mostly expressed towards health workers. Conclusion An unusually high proportion of negative sentiment was observed in response to relatively innocuous public health posts. This may be a result of heightened anxiety, questionable credibility of the sources of information and geopolitical power play maligning the image of the WHO.

Multiscale, multi-perspective imaging assisted robotic microinjection of 3D biological structures.

Microinjection is a widely used technique employed by biologists with applications in transgenesis, cryopreservation, mutagenesis, labeling/dye injection and in-vitro fertilization. However, microinjection is an extremely laborious manual procedure, which makes it a critical bottleneck in the field and thus ripe for automation. Here, we present a computer-guided robot that automates the targeted microinjection of Drosophila melanogaster and zebrafish (Danio rerio) embryos, two important model organisms in biological research. The robot uses a series of cameras to image an agar plate containing embryos at multiple magnifications and perspectives. This imaging is combined with machine learning and computer vision algorithms to pinpoint a location on the embryo for targeted microinjection with microscale precision. We demonstrate the utility of this microinjection robot to successfully microinject Drosophila melanogaster and zebrafish embryos. Results obtained indicate that the robotic microinjection approach can significantly increase the throughput of microinjection as compared to manual microinjection while maintaining survival rates comparable to human operators. In the future, this robotic platform can be used to perform high throughput microinjection experiments and can be extended to automatically microinject a host of organisms such as roundworms (Caenorhabditis elegans), mosquito (Culicidae) embryos, sea urchins (Echinoidea) and frog (Xenopus) oocytes.

Risk Factors for Readmissions After Total Joint Replacement: A Meta-Analysis.

¼: We performed a systematic review and meta-analysis of predictive modeling studies examining the risk of readmission after total hip arthroplasty (THA) and total knee arthroplasty (TKA) in order to synthesize key risk factors and evaluate their pooled effects. Our analysis entailed 15 compliant studies for qualitative review and 17 compliant studies for quantitative meta-analysis. ¼: A qualitative review of 15 predictive modeling studies highlighted 5 key risk factors for risk of readmission after THA and/or TKA: age, length of stay, readmission reduction policy, use of peripheral nerve block, and type of joint replacement procedure. ¼: A meta-analysis of 17 studies unveiled 3 significant risk factors: discharge to a skilled nursing facility rather than to home (approximately 61% higher risk), surgery at a low- or medium-procedure-volume hospital (approximately 26% higher risk), and the presence of patient obesity (approximately 34% higher risk). We demonstrated clinically meaningful relationships between these factors and moderator variables of procedure type, source of data used for model-building, and the proportion of male patients in the cohort. ¼: We found that many studies did not adhere to gold-standard criteria for reporting and study construction based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) and NOS (Newcastle-Ottawa Scale) methodologies. ¼: We recommend that these risk factors be considered in clinical practice and future work alike as they relate to surgical, discharge, and care decision-making. Future work should also prioritize greater observance of gold-standard reporting criteria for predictive models.

Management of Distal Femur Periprosthetic Fracture in an Elderly Patient by Open Reduction and Internal Fixation With Locking Plate Osteosynthesis -: A Case Report.

INTRODUCTION: Distal femur periprosthetic fractures are rare entityies and difficult to manage. Supracondylar femur fractures are most common amongst periprosthetic fractures. They can be managed by various modalities. These fractures are often difficult to treat because of various factors likesuch as osteoporosis, communication, female gender, and poor bone stock. Fixation of supracondylar femur fracture by locking plate provides excellent results in terms of radiological and clinical outcomes. CASE REPORT: We report a case of a 70 year -year-old female with pain and swelling in the right knee since for 1 day. She had a history of fall in bathroom 1 day back. The patient was operated with total knee replacement 6 years back for grade Grade 3 osteoarthritis of the knee. The patient was known case of hypertension and was on medication for the same. We operated the patient by open reduction and internal fixation with distal femur locking plate and it provided excellent clinical outcome. CONCLUSION: Periprosthetic supracondylar femur fractures are rare entity entities and generally difficult to manage, especially in elderly patient, due to poor bone quality. The choice of implant used to treat such fractures depends on the surgeon's choice and patient's compliance. Open reduction and internal fixation with a locking plate is a good entity as it provides excellent clinical and radiological outcome.

Quantifying uncertainty in annual runoff due to missing data.

Long-term streamflow datasets inevitably include gaps, which must be filled to allow estimates of runoff and ultimately catchment water budgets. Uncertainty introduced by filling gaps in discharge records is rarely, if ever, reported. We characterized the uncertainty due to streamflow gaps in a reference watershed at the Hubbard Brook Experimental Forest (HBEF) from 1996 to 2009 by simulating artificial gaps of varying duration and flow rate, with the objective of quantifying their contribution to uncertainty in annual streamflow. Gaps were filled using an ensemble of regressions relating discharge from nearby streams, and the predicted flow was compared to the actual flow. Differences between the predicted and actual runoff increased with both gap length and flow rate, averaging 2.8% of the runoff during the gap. At the HBEF, the sum of gaps averaged 22 days per year, with the lowest and highest annual uncertainties due to gaps ranging from 1.5 mm (95% confidence interval surrounding mean runoff) to 21.1 mm. As a percentage of annual runoff, uncertainty due to gap filling ranged from 0.2-2.1%, depending on the year. Uncertainty in annual runoff due to gaps was small at the HBEF, where infilling models are based on multiple similar catchments in close proximity to the catchment of interest. The method demonstrated here can be used to quantify uncertainty due to gaps in any long-term streamflow data set, regardless of the gap-filling model applied.

Risk Factors for Readmission After Knee Arthroplasty Based on Predictive Models: A Systematic Review.

BACKGROUND: An increase in the aging yet active US population will continue to make total knee arthroplasty (TKA) procedures routine in the coming decades. For such joint procedures, the Centers for Medicare and Medicaid Services introduced programs such as the Comprehensive Care for Joint Replacement to emphasize accountable and efficient transitions of care. Accordingly, many studies have proposed models using risk factors for predicting readmissions after the procedure. We performed a systematic review of TKA literature to identify such models and risk factors therein using a reliable appraisal tool for their quality assessment. METHODS: Five databases were searched to identify studies that examined correlations between post-TKA readmission and risk factors using multivariate models. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis criteria established for quality assessment of prognostic studies. RESULTS: Of 29 models in the final selection, 6 models reported performance using a C-statistic, ranging from 0.51 to 0.76, and 2 studies used a validation cohort for assessment. The average 30-day and 90-day readmission rates across the studies were 5.33% and 7.12%, respectively. Three new significant risk factors were discovered. CONCLUSIONS: Current models for TKA readmissions lack in performance measurement and reporting when assessed with established criteria. In addition to using new techniques for better performance, work is needed to build models that follow the systematic process of calibration, external validation, and reporting for pursuing their deployment in clinical settings.

Quantitative Analysis of Competency Levels in Medical Interns of a Tertiary Care Hospital in India - A Questionnaire Based Cross Sectional Study.

CONTEXT: The MCI has laid down a basic framework for interns, which it expects all prospective doctors to be well versed in. Asking students to demonstrate their understanding of the subject, ability to think critically, analyze, infer and act accordingly is imperative to the learning process. AIMS: To assess competency levels in medical interns post internship via a questionnaire developed based on MCI framework and departmental expectations of clinical capabilities. SETTINGS AND DESIGN: This descriptive cross-sectional study was done in a tertiary care hospital involving 74 interns nearing end of internship in the year 2017. METHODS AND MATERIAL: A questionnaire consisting of core competencies such as professionalism, communication skills, learning competency, clinical problem solving amongst others was provided to each and competency levels were assessed against a pre-defined scale. Answers were graded as Poor, Average, Good and Excellent with corresponding numerical equivalents 0, 1, 2 and 3 respectively. STATISTICAL ANALYSIS USED: The values obtained were analysed using Weighted Sum technique through Microsoft Excel tool. RESULTS: An ideal average competency score was initially established and overall competency of each intern was adjudged against the same. Out of 74 candidates that answered the questionnaire, a vast majority of 50 were found at below average competency. Cardio pulmonary resuscitation was known only to 13 students. Around 50 students were severely lacking with regards to knowledge about the use of preferred antibiotic in sepsis and seizures. CONCLUSION: There seems to exist significant disconnect in the expectations of MCI on one hand and actual knowledge and skill acquisition of the doctors on other. A departmental wise curriculum and exams at the end of each departmental posting which is more skill based will enable a well-trained doctor with reasonable skills and knowledge to obtain his license to practice.

Analysis of intersections of trajectories of systems of linear fractional differential equations.

This article deals with trajectorial intersections in systems of linear fractional differential equations. We propose a classification of intersections of trajectories into three classes: (a) trajectories intersecting at the same time (IST), (b) trajectories intersecting at different times (IDT), and (c) self-intersections of a trajectory. We prove a generalization of the separation theorem for the case of linear fractional systems. This result proves the existence of the IST. Based on the presence of the IST, systems are further classified into two types, Type I and Type II systems, which are analyzed further for the IDT. Self-intersections in a fractional trajectory can be regular such as constant solution or limit-cycle behavior, or they can be irregular such as cusps or nodes. We give necessary and sufficient conditions for a trajectory to be regular.

Cannabinoid CB2 Agonist AM1710 Differentially Suppresses Distinct Pathological Pain States and Attenuates Morphine Tolerance and Withdrawal.

AM1710 (3-(1,1-dimethyl-heptyl)-1-hydroxy-9-methoxy-benzo(c) chromen-6-one), a cannabilactone cannabinoid receptor 2 (CB2) agonist, suppresses chemotherapy-induced neuropathic pain in rodents without producing tolerance or unwanted side effects associated with CB1 receptors; however, the signaling profile of AM1710 remains incompletely characterized. It is not known whether AM1710 behaves as a broad-spectrum analgesic and/or suppresses the development of opioid tolerance and physical dependence. In vitro, AM1710 inhibited forskolin-stimulated cAMP production and produced enduring activation of extracellular signal-regulated kinases 1/2 phosphorylation in human embryonic kidney (HEK) cells stably expressing mCB2. Only modest species differences in the signaling profile of AM1710 were observed between HEK cells stably expressing mCB2 and hCB2. In vivo, AM1710 produced a sustained inhibition of paclitaxel-induced allodynia in mice. In paclitaxel-treated mice, a history of AM1710 treatment (5 mg/kg per day × 12 day, i.p.) delayed the development of antinociceptive tolerance to morphine and attenuated morphine-induced physical dependence. AM1710 (10 mg/kg, i.p.) did not precipitate CB1 receptor-mediated withdrawal in mice rendered tolerant to Δ9-tetrahydrocannabinol, suggesting that AM1710 is not a functional CB1 antagonist in vivo. Furthermore, AM1710 (1, 3, 10 mg/kg, i.p.) did not suppress established mechanical allodynia induced by complete Freund's adjuvant (CFA) or by partial sciatic nerve ligation (PSNL). Similarly, prophylactic and chronic dosing with AM1710 (10 mg/kg, i.p.) did not produce antiallodynic efficacy in the CFA model. By contrast, gabapentin suppressed allodynia in both CFA and PSNL models. Our results indicate that AM1710 is not a broad-spectrum analgesic agent in mice and suggest the need to identify signaling pathways underlying CB2 therapeutic efficacy to identify appropriate indications for clinical translation.

A Dead Gene Walking: Convergent Degeneration of a Clade of MADS-Box Genes in Crucifers.

Genes are "born," and eventually they "die." These processes shape the phenotypic evolution of organisms and are hence of great biological interest. If genes die in plants, they generally do so quite rapidly. Here, we describe the fate of GOA-like genes that evolve in a dramatically different manner. GOA-like genes belong to the subfamily of Bsister genes of MIKC-type MADS-box genes. Typical MIKC-type genes encode conserved transcription factors controlling plant development. We show that ABS-like genes, a clade of Bsister genes, are indeed highly conserved in crucifers (Brassicaceae) maintaining the ancestral function of Bsister genes in ovule and seed development. In contrast, their closest paralogs, the GOA-like genes, have been undergoing convergent gene death in Brassicaceae. Intriguingly, erosion of GOA-like genes occurred after millions of years of coexistence with ABS-like genes. We thus describe Delayed Convergent Asymmetric Degeneration, a so far neglected but possibly frequent pattern of duplicate gene evolution that does not fit classical scenarios. Delayed Convergent Asymmetric Degeneration of GOA-like genes may have been initiated by a reduction in the expression of an ancestral GOA-like gene in the stem group of Brassicaceae and driven by dosage subfunctionalization. Our findings have profound implications for gene annotations in genomics, interpreting patterns of gene evolution and using genes in phylogeny reconstructions of species.

Regional Differences in Predicting Risk of 30-Day Readmissions for Heart Failure.

Many researchers are working toward the goal of data-driven care by predicting the risk of 30-day readmissions for patients with heart failure. Most published predictive models have used only patient level data from either single-center studies or secondary data analysis of randomized control trials. This study describes a hierarchical model that captures regional differences in addition to patient-level data from 1778 unique patients across 31 geographically distributed hospitals from one health system. The model was developed using Bayesian techniques operating on a large set of predictors. It provided Area Under Curve (AUC) of 0.64 for the validation cohort. We confirmed that the regional differences indeed exist in the observed data and verified that our model was able to capture the regional variances in predicting the risk of 30-day readmission for patients in our cohort.

Predicting Risk of 30-Day Readmissions Using Two Emerging Machine Learning Methods.

Decades-long research efforts have shown that Heart Failure (HF) is the most expensive diagnosis for hospitalizations and the most frequent diagnosis for 30-day readmissions. If risk stratification for readmission of HF patients could be carried out at the time of discharge from the index hospitalization, corresponding appropriate post-discharge interventions could be arranged to avoid potential readmission. We, therefore, sought to explore and compare two newer machine learning methods of risk prediction using 56 predictors from electronic health records data of 1778 unique HF patients from 31 hospitals across the United States. We used two approaches boosted trees and spike-and-slab regression for analysis and found that boosted trees provided better predictive results (AUC: 0.719) as compared to spike-and-slab regression (AUC: 0.621) in our dataset.

Downsizing a long-term precipitation network: Using a quantitative approach to inform difficult decisions.

The design of a precipitation monitoring network must balance the demand for accurate estimates with the resources needed to build and maintain the network. If there are changes in the objectives of the monitoring or the availability of resources, network designs should be adjusted. At the Hubbard Brook Experimental Forest in New Hampshire, USA, precipitation has been monitored with a network established in 1955 that has grown to 23 gauges distributed across nine small catchments. This high sampling intensity allowed us to simulate reduced sampling schemes and thereby evaluate the effect of decommissioning gauges on the quality of precipitation estimates. We considered all possible scenarios of sampling intensity for the catchments on the south-facing slope (2047 combinations) and the north-facing slope (4095 combinations), from the current scenario with 11 or 12 gauges to only 1 gauge remaining. Gauge scenarios differed by as much as 6.0% from the best estimate (based on all the gauges), depending on the catchment, but 95% of the scenarios gave estimates within 2% of the long-term average annual precipitation. The insensitivity of precipitation estimates and the catchment fluxes that depend on them under many reduced monitoring scenarios allowed us to base our reduction decision on other factors such as technician safety, the time required for monitoring, and co-location with other hydrometeorological measurements (snow, air temperature). At Hubbard Brook, precipitation gauges could be reduced from 23 to 10 with a change of <2% in the long-term precipitation estimates. The decision-making approach illustrated in this case study is applicable to the redesign of monitoring networks when reduction of effort seems warranted.

Slowly Signaling G Protein-Biased CB2 Cannabinoid Receptor Agonist LY2828360 Suppresses Neuropathic Pain with Sustained Efficacy and Attenuates Morphine Tolerance and Dependence.

The CB2 cannabinoid agonist LY2828360 lacked both toxicity and efficacy in a clinical trial for osteoarthritis. Whether LY2828360 suppresses neuropathic pain has not been reported, and its signaling profile is unknown. In vitro, LY2828360 was a slowly acting but efficacious G protein-biased CB2 agonist, inhibiting cAMP accumulation and activating extracellular signal-regulated kinase 1/2 signaling while failing to recruit arrestin, activate inositol phosphate signaling, or internalize CB2 receptors. In wild-type (WT) mice, LY2828360 (3 mg/kg per day i.p. × 12 days) suppressed chemotherapy-induced neuropathic pain produced by paclitaxel without producing tolerance. Antiallodynic efficacy of LY2828360 was absent in CB2 knockout (KO) mice. Morphine (10 mg/kg per day i.p. × 12 days) tolerance developed in CB2KO mice but not in WT mice with a history of LY2828360 treatment (3 mg/kg per day i.p. × 12 days). LY2828360-induced antiallodynic efficacy was preserved in WT mice previously rendered tolerant to morphine (10 mg/kg per day i.p. × 12 days), but it was absent in morphine-tolerant CB2KO mice. Coadministration of LY2828360 (0.1 mg/kg per day i.p. × 12 days) with morphine (10 mg/kg per day × 12 days) blocked morphine tolerance in WT but not in CB2KO mice. WT mice that received LY2828360 coadministered with morphine exhibited a trend (P = 0.055) toward fewer naloxone-precipitated jumps compared with CB2KO mice. In conclusion, LY2828360 is a slowly signaling, G protein-biased CB2 agonist that attenuates chemotherapy-induced neuropathic pain without producing tolerance and may prolong effective opioid analgesia while reducing opioid dependence. LY2828360 may be useful as a first-line treatment in chemotherapy-induced neuropathic pain and may be highly efficacious in neuropathic pain states that are refractive to opioid analgesics.