Impact of Opioid-Free Anesthesia Versus Opioid-Based Anesthesia on Time to Extubation: A Scoping Review

Purpose/Background Opioids during surgery have been clinically proven to lengthen the time between intubation and post-op extubation. Increased time to extubation is associated with negative patient outcomes. This scoping review aims to evaluate the use of ketamine with opioid free analgesia (OFA) versus traditional opioid usage and its outcomes on extubation times. Methods From September 2021 to November 2021, we conducted a literature search using the University of Tennessee Health Science Center’s (UTHSC) online library. Through the PubMed, CINAHL, Medline, and Cochrane databases, we identified seventy-one articles that matched our criteria. Of those articles, we selected twenty-five to undergo rapid critical appraisal (RCA). We then chose ten articles that were critically appraised and were from peer-reviewed sources. Finally, we constructed an outcome synthesis table and level of evidence table to synthesize the results of those ten articles. Results Ten articles were chosen for this scoping review. Nine articles show that the use of ketamine decreases the time to extubation, with five proving to be statistically significant. Four articles demonstrated a decrease in ICU length of stay in days with the ketamine-based anesthesia group. Five articles found a significant decrease in postoperative opioid consumption in the ketamine-based anesthesia group. The results demonstrate that there is evidence favoring the use of ketamine and opioid free anesthesia to decrease extubation times, decrease ICU lengths of stay, and decrease postoperative opioid consumption. Implications for Nursing Practice This scoping review has demonstrated that ketamine, when used as a perioperative adjunct for pain control, will reduce opioid usage and times to extubation. Implementation of routine ketamine administration should be considered in populations that may have prolonged intubation times

B cell and/or autoantibody deficiency do not prevent neuropsychiatric disease in murine systemic lupus erythematosus

Background: Neuropsychiatric lupus (NPSLE) can be one of the earliest clinical manifestations in human lupus. However, its mechanisms are not fully understood. In lupus, a compromised blood-brain barrier may allow for the passage of circulating autoantibodies into the brain, where they can induce neuropsychiatric abnormalities including depression-like behavior and cognitive abnormalities. The purpose of this study was to determine the role of B cells and/or autoantibodies in the pathogenesis of murine NPSLE. Methods: We evaluated neuropsychiatric manifestations, brain pathology, and cytokine expression in constitutively (JhD/MRL/lpr) and conditionally (hCD20-DTA/MRL/lpr, inducible by tamoxifen) B cell-depleted mice as compared to MRL/lpr lupus mice. Results: We found that autoantibody levels were negligible (JhD/MRL/lpr) or significantly reduced (hCD20-DTA/MRL/lpr) in the serum and cerebrospinal fluid, respectively. Nevertheless, both JhD/MRL/lpr and hCD20-DTA/MRL/lpr mice showed profound depression-like behavior, which was no different from MRL/lpr mice. Cognitive deficits were also observed in both JhD/MRL/lpr and hCD20-DTA/MRL/lpr mice, similar to those exhibited by MRL/lpr mice. Furthermore, although some differences were dependent on the timing of depletion, central features of NPSLE in the MRL/lpr strain including increased blood-brain barrier permeability, brain cell apoptosis, and upregulated cytokine expression persisted in B cell-deficient and B cell-depleted mice. Conclusions: Our study surprisingly found that B cells and/or autoantibodies are not required for key features of neuropsychiatric disease in murine NPSLE

Knowledge-Driven Analysis Identifies a Gene–Gene Interaction Affecting High-Density Lipoprotein Cholesterol Levels in Multi-Ethnic Populations

Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected Pc = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (Pc = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; Pc = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (Pc = 0.004) and in the Hispanic American sample from MESA (Pc = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations

Resolution of inflammation: a new therapeutic frontier

Dysregulated inflammation is a central pathological process in diverse disease states. Traditionally, therapeutic approaches have sought to modulate the pro- or anti-inflammatory limbs of inflammation, with mixed success. However, insight into the pathways by which inflammation is resolved has highlighted novel opportunities to pharmacologically manipulate these processes — a strategy that might represent a complementary (and perhaps even superior) therapeutic approach. This Review discusses the state of the art in the biology of resolution of inflammation, highlighting the opportunities and challenges for translational research in this field

Whole genome identification of Mycobacterium tuberculosis vaccine candidates by comprehensive data mining and bioinformatic analyses

<p>Abstract</p> <p>Background</p> <p><it>Mycobacterium tuberculosis</it>, the causative agent of tuberculosis (TB), infects ~8 million annually culminating in ~2 million deaths. Moreover, about one third of the population is latently infected, 10% of which develop disease during lifetime. Current approved prophylactic TB vaccines (BCG and derivatives thereof) are of variable efficiency in adult protection against pulmonary TB (0%–80%), and directed essentially against early phase infection.</p> <p>Methods</p> <p>A genome-scale dataset was constructed by analyzing published data of: (1) global gene expression studies under conditions which simulate intra-macrophage stress, dormancy, persistence and/or reactivation; (2) cellular and humoral immunity, and vaccine potential. This information was compiled along with revised annotation/bioinformatic characterization of selected gene products and <it>in silico </it>mapping of T-cell epitopes. Protocols for scoring, ranking and prioritization of the antigens were developed and applied.</p> <p>Results</p> <p>Cross-matching of literature and <it>in silico</it>-derived data, in conjunction with the prioritization scheme and biological rationale, allowed for selection of 189 putative vaccine candidates from the entire genome. Within the 189 set, the relative distribution of antigens in 3 functional categories differs significantly from their distribution in the whole genome, with reduction in the Conserved hypothetical category (due to improved annotation) and enrichment in Lipid and in Virulence categories. Other prominent representatives in the 189 set are the PE/PPE proteins; iron sequestration, nitroreductases and proteases, all within the Intermediary metabolism and respiration category; ESX secretion systems, resuscitation promoting factors and lipoproteins, all within the Cell wall category. Application of a ranking scheme based on qualitative and quantitative scores, resulted in a list of 45 best-scoring antigens, of which: 74% belong to the dormancy/reactivation/resuscitation classes; 30% belong to the Cell wall category; 13% are classical vaccine candidates; 9% are categorized Conserved hypotheticals, all potentially very potent T-cell antigens.</p> <p>Conclusion</p> <p>The comprehensive literature and <it>in silico</it>-based analyses allowed for the selection of a repertoire of 189 vaccine candidates, out of the whole-genome 3989 ORF products. This repertoire, which was ranked to generate a list of 45 top-hits antigens, is a platform for selection of genes covering all stages of <it>M. tuberculosis </it>infection, to be incorporated in rBCG or subunit-based vaccines.</p