Lidocaine and Ketamine Infusions as Adjunctive Pain Management Therapy: A Retrospective Analysis of Clinical Outcomes in Hospitalized Patients Admitted for Pain Related to Sickle Cell Disease.

Objective: In this study, we aim to evaluate the efficacy of adjunctive lidocaine and ketamine infusions for opioid reduction in the treatment of sickle cell disease in patients with vaso-occlusive crisis (VOC). Design: We retrospectively reviewed a cohort of 330 adult sickle-cell crisis hospital encounters with 68 patients admitted to our institution from July 2017 to August 2018. Methods: Upon institutional IRB approval, we obtained initial data from billing records and performed chart reviews to obtain pain scores and confirm total opioid consumption. If provided by the acute pain consultation service, the patients received either a lidocaine or a ketamine infusion of 0.5-2 mg/min or 2-3 mcg/kg, respectively, for a maximum of 24-48 h. We compared the change in opioid consumption before and after infusion therapy to patients that did not receive ketamine or lidocaine. Results: Compared to patients that did not receive infusion therapy, ketamine and lidocaine accounted for respective relative decreases of 28 and 23% in average daily morphine consumption (p = 0.02). Patients that received either infusion were 3 to 4 times more likely to decrease their opioid consumption independent of treatment length or baseline opioid doses (p < 0.01). Ketamine and lidocaine therapies were not associated with change in pain scores. When a patient had multiple admissions, opioid reduction was strongly correlated with initiation of infusions in the later visits. Conclusion: Both ketamine and lidocaine infusion therapies are effective in reducing opioid consumption for patients with vaso-occlusive crisis. Lidocaine infusion is emerging as an agent for stabilizing opioid doses in VOC for patients with high daily MME.

Mitonuclear mismatch alters performance and reproductive success in naturally introgressed populations of a montane leaf beetle.

Coordination between nuclear and mitochondrial genomes is critical to metabolic processes underlying animals' ability to adapt to local environments, yet consequences of mitonuclear interactions have rarely been investigated in populations where individuals with divergent mitochondrial and nuclear genomes naturally interbreed. Genetic variation in the leaf beetle Chrysomela aeneicollis was assessed along a latitudinal thermal gradient in California's Sierra Nevada. Variation at mitochondrial cytochrome oxidase II (COII) and the nuclear gene phosphoglucose isomerase (PGI) shows concordance and was significantly greater along a 65 km transect than 10 other loci. STRUCTURE analyses using neutral loci identified a southern and northern subpopulation, which interbreed in the central drainage Bishop Creek. COII and PGI were used as indicators of mitochondrial and nuclear genetic variation in field and laboratory experiments conducted on beetles from this admixed population. Fecundity, larval development rate, running speed and male mating frequency were higher for beetles with geographically "matched" than "mismatched" mitonuclear genotypes. Effects of mitonuclear mismatch were largest for individuals with northern nuclear genotypes possessing southern mitochondria and were most pronounced after heat treatment or at high elevation. These findings suggest that mitonuclear incompatibility diminishes performance and reproductive success in nature, effects that could intensify at environmental extremes.

Allele-specific copy number profiling by next-generation DNA sequencing.

The progression and clonal development of tumors often involve amplifications and deletions of genomic DNA. Estimation of allele-specific copy number, which quantifies the number of copies of each allele at each variant loci rather than the total number of chromosome copies, is an important step in the characterization of tumor genomes and the inference of their clonal history. We describe a new method, falcon, for finding somatic allele-specific copy number changes by next generation sequencing of tumors with matched normals. falcon is based on a change-point model on a bivariate mixed Binomial process, which explicitly models the copy numbers of the two chromosome haplotypes and corrects for local allele-specific coverage biases. By using the Binomial distribution rather than a normal approximation, falcon more effectively pools evidence from sites with low coverage. A modified Bayesian information criterion is used to guide model selection for determining the number of copy number events. Falcon is evaluated on in silico spike-in data and applied to the analysis of a pre-malignant colon tumor sample and late-stage colorectal adenocarcinoma from the same individual. The allele-specific copy number estimates obtained by falcon allows us to draw detailed conclusions regarding the clonal history of the individual's colon cancer.