Identification of ä-Spectrin Domains Susceptible to Ubiquitination

Previously, we demonstrated that alpha-spectrin is a substrate for the ubiquitin system and that this conjugation is a dynamic process (Corsi, D., Galluzzi, L., Crinelli, R., and Magnani, M. (1995) J. Biol. Chem. 270, 8928-8935). In this study, we mapped the sites of ubiquitination on erythrocyte alpha-spectrin. A peptide map of digested alpha-spectrin, previously submitted to in vitro 125I-ubiquitin conjugation, revealed the presence of four distinct labeled bands with Mr 40,000, 36,000, 29,000, and 25,500. Western blotting experiments using antibodies against each alpha-spectrin domain revealed that only IgG anti-alphaIII domain recognized the 125I-labeled ubiquitin peptide of 29 kDa, whereas the IgG anti-alphaV domain recognized the Mr 40,000 125I-ubiquitin-labeled peptide. The other two labeled bands of Mr 36,000 and Mr 25,500 were identified as tetra and tri multiubiquitin chains. Ubiquitination of the alphaIII and alphaV domains was further confirmed by anti-alpha-spectrin domain immunoaffinity chromatography. Endoprotease Lys C-digested spectrin conjugated previously to 125I-ubiquitin was incubated with antibodies against each trypsin-resistant domain of alpha-spectrin. Gamma counting of the radiolabeled antigen-antibody complexes purified by protein A chromatography showed labeling in the IgG anti-alphaIII and anti-alphaV complexes alone. Domain alphaIII is not associated with any known function, whereas domain alphaV contains the nucleation site for the association of the alpha and beta chains. Ubiquitination of the latter domain suggests a role for ubiquitin in the modulation of the stability, deformability, and viscoelastic properties of the erythrocyte membrane

Prevalence of marijuana use does not differentially increase among youth after states pass medical marijuana laws: Commentary on Stolzenberg et al. (2015) and reanalysis of US National Survey on Drug Use in Households data 2002–2011

There is considerable interest in the effects of medical marijuana laws (MML) on marijuana use in the USA, particularly among youth. The article by Stolzenberg et al. (2015) “The effect of medical cannabis laws on juvenile cannabis use” concludes that “implementation of medical cannabis laws increase juvenile cannabis use”. This result is opposite to the findings of other studies that analysed the same US National Survey on Drug Use in Households data as well as opposite to studies analysing other national data which show no increase or even a decrease in youth marijuana use after the passage of MML. We provide a replication of the Stolzenberg et al. results and demonstrate how the comparison they are making is actually driven by differences between states with and without MML rather than being driven by pre and post-MML changes within states. We show that Stolzenberg et al. do not properly control for the fact that states that pass MML during 2002–2011 tend to already have higher past-month marijuana use before passing the MML in the first place. We further show that when within-state changes are properly considered and pre-MML prevalence is properly controlled, there is no evidence of a differential increase in past-month marijuana use in youth that can be attributed to state MML

US Traffic Fatalities, 1985–2014, and Their Relationship to Medical Marijuana Laws

Objectives. To determine the association of medical marijuana laws (MMLs) with traffic fatality rates. Methods. Using data from the 1985–2014 Fatality Analysis Reporting System, we examined the association between MMLs and traffic fatalities in multilevel regression models while controlling for contemporaneous secular trends. We examined this association separately for each state enacting MMLs. We also evaluated the association between marijuana dispensaries and traffic fatalities. Results. On average, MML states had lower traffic fatality rates than non-MML states. Medical marijuana laws were associated with immediate reductions in traffic fatalities in those aged 15 to 24 and 25 to 44 years, and with additional yearly gradual reductions in those aged 25 to 44 years. However, state-specific results showed that only 7 states experienced post-MML reductions. Dispensaries were also associated with traffic fatality reductions in those aged 25 to 44 years. Conclusions. Both MMLs and dispensaries were associated with reductions in traffic fatalities, especially among those aged 25 to 44 years. State-specific analysis showed heterogeneity of the MML–traffic fatalities association, suggesting moderation by other local factors. These findings could influence policy decisions on the enactment or repealing of MMLs and how they are implemented

State Medical Marijuana Laws and the Prevalence of Opioids Detected Among Fatally Injured Drivers

Objectives. To assess the association between medical marijuana laws (MMLs) and the odds of a positive opioid test, an indicator for prior use. Methods. We analyzed 1999–2013 Fatality Analysis Reporting System (FARS) data from 18 states that tested for alcohol and other drugs in at least 80% of drivers who died within 1 hour of crashing (n = 68 394). Within-state and between-state comparisons assessed opioid positivity among drivers crashing in states with an operational MML (i.e., allowances for home cultivation or active dispensaries) versus drivers crashing in states before a future MML was operational. Results. State-specific estimates indicated a reduction in opioid positivity for most states after implementation of an operational MML, although none of these estimates were significant. When we combined states, we observed no significant overall association (odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.61, 1.03). However, age-stratified analyses indicated a significant reduction in opioid positivity for drivers aged 21 to 40 years (OR = 0.50; 95% CI = 0.37, 0.67; interaction P < .001). Conclusions. Operational MMLs are associated with reductions in opioid positivity among 21- to 40-year-old fatally injured drivers and may reduce opioid use and overdose

Auxiliary Marker-Assisted Classification in the Absence of Class Identifiers

Constructing classification rules for accurate diagnosis of a disorder is an important goal in medical practice. In many clinical applications, there is no clinically significant anatomical or physiological deviation exists to identify the gold standard disease status to inform development of classification algorithms. Despite absence of perfect disease class identifiers, there are usually one or more disease-informative auxiliary markers along with feature variables comprising known symptoms. Existing statistical learning approaches do not effectively draw information from auxiliary prognostic markers. We propose a large margin classification method, with particular emphasis on the support vector machine (SVM), assisted by available informative markers in order to classify disease without knowing a subject’s true disease status. We view this task as statistical learning in the presence of missing data, and introduce a pseudo-EM algorithm to the classification. A major distinction with a regular EM algorithm is that we do not model the distribution of missing data given the observed feature variables either parametrically or semiparametrically. We also propose a sparse variable selection method embedded in the pseudo-EM algorithm. Theoretical examination shows that the proposed classification rule is Fisher consistent, and that under a linear rule, the proposed selection has an oracle variable selection property and the estimated coefficients are asymptotically normal. We apply the methods to build decision rules for including subjects in clinical trials of a new psychiatric disorder and present four applications to data available at the UCI Machine Learning Repository

Molecular cloning and characterization of a highly selective chemokine-binding protein from the tick Rhipicephalus sanguineus.

Abstract Ticks are blood-feeding parasites that secrete a number of immuno-modulatory factors to evade the host immune response. Saliva isolated from different species of ticks has recently been shown to contain chemokine neutralizing activity. To characterize this activity, we constructed a cDNA library from the salivary glands of the common brown dog tick, Rhipicephalus sanguineus. Pools of cDNA clones from the library were transfected into HEK293 cells, and the conditioned media from the transfected cells were tested for chemokine binding activity by chemical cross-linking to radiolabeled CCL3 followed by SDS-PAGE. By de-convolution of a single positive pool of 270 clones, we identified a full-length cDNA encoding a protein of 114 amino acids, which after signal peptide cleavage was predicted to yield a mature protein of 94 amino acids that we called Evasin-1. Recombinant Evasin-1 was produced in HEK293 cells and in insect cells. Using surface plasmon resonance we were able to show that Evasin-1 was exquisitely selective for 3 CC chemokines, CCL3 and CCL4 and the closely related chemokine CCL18, with KD values of 0.16, 0.81, and 3.21 nm, respectively. The affinities for CCL3 and CCL4 were confirmed in competition receptor binding assays. Analysis by size exclusion chromatography demonstrated that Evasin-1 was monomeric and formed a 1:1 complex with CCL3. Thus, unlike the other chemokine-binding proteins identified to date from viruses and from the parasitic worm Schistosoma mansoni, Evasin-1 is highly specific for a subgroup of CC chemokines, which may reflect a specific role for these chemokines in host defense against parasites

Ticks produce highly selective chemokine binding proteins with antiinflammatory activity

Bloodsucking parasites such as ticks have evolved a wide variety of immunomodulatory proteins that are secreted in their saliva, allowing them to feed for long periods of time without being detected by the host immune system. One possible strategy used by ticks to evade the host immune response is to produce proteins that selectively bind and neutralize the chemokines that normally recruit cells of the innate immune system that protect the host from parasites. We have identified distinct cDNAs encoding novel chemokine binding proteins (CHPBs), which we have termed Evasins, using an expression cloning approach. These CHBPs have unusually stringent chemokine selectivity, differentiating them from broader spectrum viral CHBPs. Evasin-1 binds to CCL3, CCL4, and CCL18; Evasin-3 binds to CXCL8 and CXCL1; and Evasin-4 binds to CCL5 and CCL11. We report the characterization of Evasin-1 and -3, which are unrelated in primary sequence and tertiary structure, and reveal novel folds. Administration of recombinant Evasin-1 and -3 in animal models of disease demonstrates that they have potent antiinflammatory properties. These novel CHBPs designed by nature are even smaller than the recently described single-domain antibodies (Hollinger, P., and P.J. Hudson. 2005. Nat. Biotechnol. 23:1126–1136), and may be therapeutically useful as novel antiinflammatory agents in the future

Nevirapine and efavirenz elicit different changes in lipid profiles in antiretroviral-therapy-naive patients infected with HIV-1

Patients infected with HIV-1 initiating antiretroviral therapy (ART) containing a non-nucleoside reverse transcriptase inhibitor (NNRTI) show presumably fewer atherogenic lipid changes than those initiating most ARTs containing a protease inhibitor. We analyzed whether lipid changes differed between the two most commonly used NNRTIs, nevirapine (NVP) and efavirenz (EFV)

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status

The methylation status of the O6-methylguanine- DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs,