The methylene amidogen radical (HCN) plays a role in high-energy material combustion and extraterresterial atmospheres. Recent theoretical work has struggled to match experimental assignments for its CN and antisymmetric CH stretching frequencies (ν and ν), which were reported to occur at 1725 and 3103 cm. Herein, we compute the vibrational energy levels of this molecule by extrapolating quadruples-level coupled-cluster theory to the complete basis limit and adding corrections for vibrational anharmonicity. This level of theory predicts that ν and ν should occur at 1646 and 2892 cm, at odds with the experimental assignments. To investigate the possibility of defects in our theoretical treatment, we analyze the sensitivity of our approach to each of its contributing approximations. Our analysis suggests that the observed deviation from experiment is too large to be explained as an accumulation of errors, leading us to conclude that these transitions were misassigned. To help resolve this discrepancy, we investigate possible byproducts of the H + HCN reaction, which was the source of HCN in the original experiment. In particular, we predict vibrational spectra for cis-HCNH, trans-HCNH, and HCNH using high-level coupled-cluster computations. Based on these results, we reassign the transition at 1725 cm to ν of trans-HCNH, yielding excellent agreement. Supporting this identification, we assign a known contaminant peak at 886 cm to ν of the same conformer. Our computations suggest that the peak observed at 3103 cm, however, does not belong to any of the aforementioned species. To facilitate further investigation, we use structure and bonding arguments to narrow the range of possible candidates. These arguments lead us to tentatively put forth formaldazine [(HCN)] as a suggestion for further study, which we support with additional computations.

Reluctance to undergo lumbar puncture (LP) is a barrier to neurological disease biomarker research. We assessed whether an educational intervention increased willingness to consider research LP and whether message framing modified intervention effectiveness. We randomly assigned 851 recruitment registry enrollees who had previously indicated they were unwilling to be contacted about studies requiring LP to gain or loss framed video educational interventions describing the procedure and the probability of experiencing adverse events. The gain framed intervention emphasized the proportion of individuals free of adverse events; the loss frame emphasized the proportion experiencing adverse events. The primary outcome for the study was the participant's post-intervention agreement to be contacted about studies requiring LP. Participants were mean (SD) age 60.1 years (15.7), 69% female (n = 591), and mostly college educated and white. Among the 699 participants who completed the study, 43% (95% CI: 0.39, 0.47; n = 301) changed their response to agree to be contacted about studies requiring LP. We estimated that participants randomized to the gain framed intervention had 67% higher odds of changing their response compared to those randomized to the loss frame (Odds Ratio = 1.67; 95% CI: 1.24, 2.26; p < 0.001). A classification and regression tree model identified participants' pre-intervention willingness as the strongest predictor of changing response. Education, in particular education that alerts participants to the probability of not experiencing adverse events, may be an effective tool to increase participation rates in research requiring LP.

Background Early study exit is detrimental to statistical power and increases the risk for bias in Alzheimer’s disease clinical trials. Previous analyses in early phase academic trials demonstrated associations between rates of trial incompletion and participants’ study partner type, with participants enrolling with non-spouse study partners being at greater risk. Methods We conducted secondary analyses of two multinational phase III trials of semagacestat, an oral gamma secretase inhibitor, for mild-to-moderate AD dementia. Cox’s proportional hazards regression model was used to estimate the relationship between study partner type and the risk of early exit from the trial after adjustment for a priori identified potential confounding factors. Additionally, we used a random forest model to identify top predictors of dropout. Results Among participants with spousal, adult child, and other study partners, respectively, 35%, 38%, and 36% dropped out or died prior to protocol-defined study completion, respectively. In unadjusted models, the risk of trial incompletion differed by study partner type (unadjusted p value = 0.027 for test of differences by partner type), but in models adjusting for potential confounding factors, the differences were not statistically significant (p value = 0.928). In exploratory modeling, participant age was identified as the primary characteristic to explain the relationship between study partner type and the risk of failing to complete the trial. Participant age was also the strongest predictor of trial incompletion in the random forest model. Conclusions After adjustment for age, no differences in the risk of incompletion were observed when comparing participants with different study partner types in these trials. Differences between our findings and the findings of previous studies may be explained by differences in trial phase, size, geographic regions, or the composition of academic and non-academic sites.

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