Mechanistic Insights from the Crystal Structure and Computational Analysis of the Radical SAM Deaminase DesII.

Radical S-adenosyl-L-methionine (SAM) enzymes couple the reductive cleavage of SAM to radical-mediated transformations that have proven to be quite broad in scope. DesII is one such enzyme from the biosynthetic pathway of TDP-desosamine where it catalyzes a radical-mediated deamination. Previous studies have suggested that this reaction proceeds via direct elimination of ammonia from an α-hydroxyalkyl radical or its conjugate base (i.e., a ketyl radical) rather than 1,2-migration of the amino group to form a carbinolamine radical intermediate. However, without a crystal structure, the active site features responsible for this chemistry have remained largely unknown. The crystallographic studies described herein help to fill this gap by providing a structural description of the DesII active site. Computational analyses based on the solved crystal structure are consistent with direct elimination and indicate that an active site glutamate residue likely serves as a general base to promote deprotonation of the α-hydroxyalkyl radical intermediate and elimination of the ammonia group.

Mobilizing data during a crisis: Building rapid evidence pipelines using multi-institutional real world data.

The COVID-19 pandemic generated tremendous interest in using real world data (RWD). Many consortia across the public and private sectors formed in 2020 with the goal of rapidly producing high-quality evidence from RWD to guide medical decision-making, public health priorities, and more. Experiences were gathered from five large consortia on rapid multi-institutional evidence generation during the COVID-19 pandemic. Insights have been compiled across five dimensions: consortium composition, governance structure and alignment of priorities, data sharing, data analysis, and evidence dissemination. The purpose of this piece is to offer guidance on building large-scale multi-institutional RWD analysis pipelines for future public health issues. The composition of each consortium was largely influenced by existing collaborations. A central set of priorities for evidence generation guided each consortium, however different approaches to governance emerged. Challenges surrounding limited access to clinical data due to various contributors were overcome in unique ways. While all consortia used different methods to construct and analyze patient cohorts ranging from centralized to federated approaches, all proved effective for generating meaningful real-world evidence. Actionable recommendations for clinical practice and public health agencies were made from translating insights from consortium analyses. Each consortium was successful in rapidly answering questions about COVID-19 diagnosis and treatment despite all taking slightly different approaches to data sharing and analysis. Leveraging RWD, leveraged in a manner that applies scientific rigor and transparency, can complement higher-level evidence and serve as an important adjunct to clinical trials to quickly guide policy and critical care, especially for a pandemic response.

Diversity, Equity, and Inclusion in Clinical Research: A Path Toward Precision Health for Everyone.

Healthcare disparities are a persistent societal problem. One of the contributing factors to this status quo is the lack of diversity and representativeness of research efforts, which result in nongeneralizable evidence that, in turn, provides suboptimal means to enable the best possible outcomes at the individual level. There are several strategies that research teams can adopt to improve the diversity, equity, and inclusion (DEI) of their efforts; these strategies span the totality of the research path, from initial design to the shepherding of clinical data through a potential regulatory process. These strategies include more intentionality and DEI-based goal-setting, more diverse research and leadership teams, better community engagement to set study goals and approaches, better tailored outreach interventions, decentralization of study procedures and incorporation of innovative technology for more flexible data collection, and self-surveillance to identify and prevent biases. Within their remit of overlooking research efforts, regulatory authorities, as stakeholders, also have the potential for a positive effect on the DEI of emerging clinical evidence. All these are implementable tools and mechanisms that can make study participation more approachable to diverse communities, and ultimately generate evidence that is more generalizable and a conduit for better outcomes. The research community has an imperative to make DEI principles key foundational aspects in study conduct in order to pursue better personalized medicine for diverse patient populations.

Byproduct formation during the biosynthesis of spinosyn A and evidence for an enzymatic interplay to prevent its formation.

Biosynthesis of spinosyn A in Saccharopolyspora spinosa involves a 1,4-dehydration followed by an intramolecular [4 + 2]-cycloaddition catalyzed by SpnM and SpnF, respectively. The cycloaddition also takes place in the absence of SpnF leading to questions regarding its mechanism of catalysis and biosynthetic role. Substrate analogs were prepared with an unactivated dienophile or an acyclic structure and found to be unreactive consistent with the importance of these features for cyclization. The SpnM-catalyzed dehydration reaction was also found to yield a byproduct corresponding to the C11 = C12 cis isomer of the SpnF substrate. This byproduct is stable both in the presence and absence of SpnF; however, relative production of the SpnM product and byproduct could be shifted in favor of the former by including SpnF or the dehydrogenase SpnJ in the reaction. This result suggests a potential interplay between the enzymes of spinosyn A biosynthesis that may help to improve the efficiency of the pathway.

Longitudinal studies support the safety and ethics of virtual reality suicide as a research method.

Many have expressed concerns about the safety and ethics of conducting suicide research, especially intense suicide research methods that expose participants to graphic depictions of suicidality. We conducted two studies to evaluate the effects of one such method called virtual reality (VR) suicide. Study 1 tested the effects of VR suicide exposure over the course of one month in participants with (n = 56) and without a history of suicidality (n = 50). Study 2 exposed some participants to VR suicide scenarios (n = 79) and others to control scenarios (n = 80). Participants were invited to complete a follow-up assessment after an average of 2 years. For both studies, the presence of suicidality post exposure was the primary outcome, with closely related constructs (e.g., capability for suicide, agitation) as secondary outcomes. Study 1 found no pre-post increases in suicidality or related variables, but revealed several significant decreases associated with small to medium effect sizes in suicide-related constructs. In Study 2, VR suicide exposure did not cause any significant increases in suicidality or related variables. Together with prior research, these findings suggest that methods involving intense suicide stimuli appear safe and consistent with utilitarian ethics.

Relations between implicit attitudes towards eating disorder stimuli and disordered eating symptoms among at-risk college women.

This study examined implicit attitudes towards different eating disorder (ED) relevant stimuli- emaciation, hard-exercise, the self, and eating related stimuli-and their relationship with explicit ED symptoms in two symptomatic samples of college-aged women. Study 1 found that positive implicit attitudes towards eating and self-relevant images were associated with greater state body image satisfaction and self-esteem and with less ED-related intentions. Study 2 found that positive implicit attitudes towards eating and self-relevant images were associated with less trait global ED psychopathology and distress and greater self-esteem. Overall, positive implicit evaluations of eating and self-related stimuli were negatively associated with ED symptoms and related psychopathology and positively related to self-esteem. However, implicit attitudes towards emaciation and hard exercise were not associated with explicit ED symptoms in either sample. These findings suggest that implicit attitudes towards eating and self-related stimuli, in particular, may be viable targets for reconditioning in novel treatment paradigms such as therapeutic evaluative conditioning interventions.

Rapid confirmation of five non-typhoidal Salmonella (NTS) serotypes using a low-cost portable-DIY OpenPCR© thermocycler

Aims@#OpenPCR is a low cost yet accurate thermocycler which can be self-built. The aim of the study is to highlight a low-cost alternative method for rapid confirmation of five predominant non-typhoidal Salmonella (NTS) serotypes using a multiplex PCR on a portable-DIY OpenPCR© thermocycler. @*Methodology and results@# Eight multiplex polymerase chain reaction (mPCR) samples containing genomic DNA of S. Agona selectively placed on the wells of the conventional PCR and OpenPCR© thermocyclers showed uniform heating in both thermocyclers. The limit of detection was similar for both thermocyclers for all five serotypes. The limit of detection for S. Typhimurium, S. Agona and S. Weltevreden was 10 pg/µL whereas the limit of detection for S. Enteriditis and S. Heidelberg was 1 pg/µL and 100 pg/µL, respectively. This assay incorporated a panel of unique genes; STM4495, SEN1392, SeHa-C4893, SeAg-B1096 and SENTW-3241 which were previously identified to be specific for S. Typhimurium, S. Enteritidis, S. Heidelberg, S. Agona, and S. Weltevreden, respectively, as well as the pan-Salmonella gene invA as internal control (IC) and pan-bacteria gene 16S rRNA to serve as amplification control (AC). The analytical specificity of the mPCR assay was found to be 100% for all five NTS using OpenPCR© thermocyclers. @*Conclusion, significance and impact of study@#The feasibility and low cost of the OpenPCR© thermocycler makes this device an ideal alternative for mPCR assay for rapid confirmation of NTS serotypes.

Interventions for suicide and self-injury: A meta-analysis of randomized controlled trials across nearly 50 years of research.

Self-injurious thoughts and behaviors (SITBs) are major public health concerns impacting a wide range of individuals and communities. Despite major efforts to develop and refine treatments to reduce SITBs, the efficacy of SITB interventions remains unclear. To provide a comprehensive summary of SITB treatment efficacy, we conducted a meta-analysis of published randomized controlled trials (RCTs) that have attempted to reduce SITBs. A total of 591 published articles from 1,125 unique RCTs with 3,458 effect sizes from the past 50 years were included. The random-effects meta-analysis yielded surprising findings: The overall intervention effects were small across all SITB outcomes; despite a near-exponential increase in the number of RCTs across five decades, intervention efficacy has not improved; all SITB interventions produced similarly small effects, and no intervention appeared significantly and consistently stronger than others; the overall small intervention effects were largely maintained at follow-up assessments; efficacy was similar across age groups, though effects were slightly weaker for child/adolescent populations and few studies focused on older adults; and major sample and study characteristics (e.g., control group type, treatment target, sample size, intervention length) did not consistently moderate treatment efficacy. This meta-analysis suggests that fundamental changes are needed to facilitate progress in SITB intervention efficacy. In particular, powerful interventions target the necessary causes of pathology, but little is known about SITB causes (vs. SITB correlates and risk factors). The field would accordingly benefit from the prioritization of research that aims to identify and target common necessary causes of SITBs. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Anticipated consequences as the primary causes of suicidal behavior: Evidence from a laboratory study.

Due to the limitations of conducting experimental studies on suicide, little is known about its causes. Based on basic behavioral research, we hypothesized that the anticipated consequences of suicidal behavior (e.g., stress relief) are the primary causes of suicidal behavior, and experienced antecedents (e.g., stress) are secondary causes. We evaluated this general hypothesis by testing the causal effects of these two broad phenomena on virtual reality (VR) suicide in 497 participants across five groups. On their own, experienced antecedent manipulations (i.e., stress and rejection) did not significantly increase VR suicide rates relative to the control group. On its own, the anticipated consequence manipulation (i.e., instruction that engaging in VR suicide would allow one to avoid a future stressor) caused a large increase in the VR suicide rate. In the context of an experienced antecedent manipulation (i.e., stress), this anticipated consequence manipulation caused an even larger increase in the VR suicide rate. These findings suggest that the anticipated consequences of suicidal behavior (e.g., avoidance or escape from something unpleasant, attaining something pleasant) are the primary causes of suicidal behavior, and that experienced antecedents (e.g., stress) serve as secondary causes when they make an anticipated consequence of suicidal behavior seem more appealing.

The Differences Between Individuals Engaging in Nonsuicidal Self-Injury and Suicide Attempt Are Complex (vs. Complicated or Simple).

BACKGROUND: Why do some people engage in nonsuicidal self-injury (NSSI) while others attempt suicide? One way to advance knowledge about this question is to shed light on the differences between people who engage in NSSI and people who attempt suicide. These groups could differ in three broad ways. First, these two groups may differ in a simple way, such that one or a small set of factors is both necessary and sufficient to accurately distinguish the two groups. Second, they might differ in a complicated way, meaning that a specific set of a large number of factors is both necessary and sufficient to accurately classify them. Third, they might differ in a complex way, with no necessary factor combinations and potentially no sufficient factor combinations. In this scenario, at the group level, complicated algorithms would either be insufficient (i.e., no complicated algorithm produces good accuracy) or unnecessary (i.e., many complicated algorithms produce good accuracy) to distinguish between groups. This study directly tested these three possibilities in a sample of people with a history of NSSI and/or suicide attempt. METHOD: A total of 954 participants who have either engaged in NSSI and/or suicide attempt in their lifetime were recruited from online forums. Participants completed a series of measures on factors commonly associated with NSSI and suicide attempt. To test for simple differences, univariate logistic regressions were conducted. One theoretically informed multiple logistic regression model with suicidal desire, capability for suicide, and their interaction term was considered as well. To examine complicated and complex differences, multiple logistic regression and machine learning analyses were conducted. RESULTS: No simple algorithm (i.e., single factor or small set of factors) accurately distinguished between groups. Complicated algorithms constructed with cross-validation methods produced fair accuracy; complicated algorithms constructed with bootstrap optimism methods produced good accuracy, but multiple different algorithms with this method produced similar results. CONCLUSIONS: Findings were consistent with complex differences between people who engage in NSSI and suicide attempts. Specific complicated algorithms were either insufficient (cross-validation results) or unnecessary (bootstrap optimism results) to distinguish between these groups with high accuracy.

The differences between suicide ideators and suicide attempters: Simple, complicated, or complex?

OBJECTIVE: Suicide ideators and suicide attempters might differ in 3 possible ways. First, they might differ in a simple way such that one or a small set of factors are both necessary and sufficient to distinguish between the 2 groups. Second, ideators and attempters might differ in a complicated way such that a specific combination of a large set of factors is necessary and sufficient for the distinction. Third, complex differences might exist: many possible combinations of a large set of factors may be sufficient to distinguish the 2 groups, but no combination may be necessary. This study empirically examined these possibilities. METHOD: Across 5 samples (total N = 3,869), univariate logistic regressions were conducted to test for simple differences. To test for complicated and complex differences, machine learning (ML) methods were used to identify the optimized algorithm with all variables. Subsequently, the same methods were repeated after removing the top 5 most important or discriminative variables, and a randomly selected 10% subset of variables. Multiple logistic regressions were conducted with all variables. RESULTS: Results were consistent across samples. Univariate logistic regressions on average yielded chance-level accuracy. ML algorithms with all variables showed good accuracy; substantial deviation from the optimized algorithms through the removal of variables did not result in significantly poorer performance. Multiple logistic regressions produced poor to fair accuracy. CONCLUSIONS: Differences between suicide ideators and attempters are complex. Findings suggest that their differences may be better understood on a psychological primitive level than a biopsychosocial factor level. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Brain Differences Associated with Self-Injurious Thoughts and Behaviors: A Meta-Analysis of Neuroimaging Studies.

This meta-analysis aims to evaluate whether the extant literature justifies any definitive conclusions about whether and how SITBs may be associated with brain differences. A total of 77 papers (N = 4,903) published through January 1, 2019 that compared individuals with and without SITBs were included, resulting in 882 coordinates. A pooled meta-analysis assessing for general risk for SITBs indicated a lack of convergence on structural differences. When all types of control groups were considered, functional differences in the left posterior cingulate cortex (PCC), right amygdala, left hippocampus, and right thalamus were significant using multi-level kernel density analysis (pcorrected < 0.05) but nonsignificant using activation-likelihood estimation. These results suggest that a propensity for internally-oriented, emotional processing coupled with under-active pain processing could potentially underlie SITBs, but additional research is needed to test this possibility. Separate analyses for types of SITBs suggested that the brain differences associated with deliberate self-harm were consistent with the overall findings. Checkered moderator effects were detected. Overall, the meta-analytic evidence was not robust. More studies are needed to reach definitive conclusions about whether SITBs are associated with brain differences.

Water adsorption on vanadium oxide thin films in ambient relative humidity.

In this work, ambient pressure x-ray photoelectron spectroscopy (APXPS) is used to study the initial stages of water adsorption on vanadium oxide surfaces. V 2p, O 1s, C 1s, and valence band XPS spectra were collected as a function of relative humidity in a series of isotherm and isobar experiments. Experiments were carried out on two VO2 thin films on TiO2 (100) substrates, prepared with different surface cleaning procedures. Hydroxyl and molecular water surface species were identified, with up to 0.5 ML hydroxide present at the minimum relative humidity, and a consistent molecular water adsorption onset occurring around 0.01% relative humidity. The work function was found to increase with increasing relative humidity, suggesting that surface water and hydroxyl species are oriented with the hydrogen atoms directed away from the surface. Changes in the valence band were also observed as a function of relative humidity. The results were similar to those observed in APXPS experiments on other transition metal oxide surfaces, suggesting that H2O-OH and H2O-H2O surface complex formation plays an important role in the oxide wetting process and water dissociation. Compared to polycrystalline vanadium metal, these vanadium oxide films generate less hydroxide and appear to be more favorable for molecular water adsorption.

User-Centered Design of a Machine Learning Intervention for Suicide Risk Prediction in a Military Setting.

Primary care represents a major opportunity for suicide prevention in the military. Significant advances have been made in using electronic health record data to predict suicide attempts in patient populations. With a user-centered design approach, we are developing an intervention that uses predictive analytics to inform care teams about their patients' risk of suicide attempt. We present our experience working with clinicians and staff in a military primary care setting to create preliminary designs and a context-specific usability testing plan for the deployment of the suicide risk indicator.

Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide.

Suicide accounts for nearly 800,000 deaths per year worldwide with rates of both deaths and attempts rising. Family studies have estimated substantial heritability of suicidal behavior; however, collecting the sample sizes necessary for successful genetic studies has remained a challenge. We utilized two different approaches in independent datasets to characterize the contribution of common genetic variation to suicide attempt. The first is a patient reported suicide attempt phenotype asked as part of an online mental health survey taken by a subset of participants (n = 157,366) in the UK Biobank. After quality control, we leveraged a genotyped set of unrelated, white British ancestry participants including 2433 cases and 334,766 controls that included those that did not participate in the survey or were not explicitly asked about attempting suicide. The second leveraged electronic health record (EHR) data from the Vanderbilt University Medical Center (VUMC, 2.8 million patients, 3250 cases) and machine learning to derive probabilities of attempting suicide in 24,546 genotyped patients. We identified significant and comparable heritability estimates of suicide attempt from both the patient reported phenotype in the UK Biobank (h2SNP = 0.035, p = 7.12 × 10-4) and the clinically predicted phenotype from VUMC (h2SNP = 0.046, p = 1.51 × 10-2). A significant genetic overlap was demonstrated between the two measures of suicide attempt in these independent samples through polygenic risk score analysis (t = 4.02, p = 5.75 × 10-5) and genetic correlation (rg = 1.073, SE = 0.36, p = 0.003). Finally, we show significant but incomplete genetic correlation of suicide attempt with insomnia (rg = 0.34-0.81) as well as several psychiatric disorders (rg = 0.26-0.79). This work demonstrates the contribution of common genetic variation to suicide attempt. It points to a genetic underpinning to clinically predicted risk of attempting suicide that is similar to the genetic profile from a patient reported outcome. Lastly, it presents an approach for using EHR data and clinical prediction to generate quantitative measures from binary phenotypes that can improve power for genetic studies.

Psychological primitives can make sense of biopsychosocial factor complexity in psychopathology.

BACKGROUND: Many agree that the biopsychosocial contributions to psychopathology are complex, yet it is unclear how we can make sense of this complexity. One approach is to reduce this complexity to a few necessary and sufficient biopsychosocial factors; although this approach is easy to understand, it has little explanatory power. Another approach is to fully embrace complexity, proposing that each instance of psychopathology is caused by a partially unique set of biopsychosocial factors; this approach has high explanatory power, but is impossible to comprehend. Due to deficits in either explanatory power or comprehensibility, both approaches limit our ability to make substantial advances in understanding, predicting, and preventing psychopathology. Thus, how can we make sense of biopsychosocial factor complexity? MAIN TEXT: There is a third possible approach that can resolve this dilemma, with high explanatory power and high comprehensibility. This approach involves understanding, predicting, and preventing psychopathology in terms of a small set of psychological primitives rather than biopsychosocial factors. Psychological primitives are the fundamental and irreducible elements of the mind, mediating all biopsychosocial factor influences on psychopathology. All psychological phenomena emerge from these primitives. Over the past decade, this approach has been successfully applied within basic psychological science, most notably affective science. It explains the sum of the evidence in affective science and has generated several novel research directions. This approach is equally applicable to psychopathology. The primitive-based approach does not eliminate the role of biopsychosocial factors, but rather recasts them as indeterminate causal influences on psychological primitives. In doing so, it reframes research away from factor-based questions (e.g., which situations cause suicide?) and toward primitive-based questions (e.g., how are suicidality concepts formed, altered, activated, and implemented?). This is a valuable shift because factor-based questions have indeterminate answers (e.g., infinite situations could cause suicide) whereas primitive-based questions have determinate answers (e.g., there are specific processes that undergird all concepts). CONCLUSION: The primitive-based approach accounts for biopsychosocial complexity, ties clinical science more directly to basic psychological science, and could facilitate progress in understanding, predicting, and preventing psychopathology.

Model complexity improves the prediction of nonsuicidal self-injury.

OBJECTIVE: Efforts to predict nonsuicidal self-injury (NSSI; intentional self-injury enacted without suicidal intent) to date have resulted in near-chance accuracy. Incongruence between theoretical understanding of NSSI and the traditional statistical methods to predict these behaviors may explain this poor prediction. Whereas theoretical models of NSSI assume that the decision to engage in NSSI is relatively complex, statistical models used in NSSI prediction tend to involve simple models with only a few theoretically informed variables. The present study tested whether more complex statistical models would improve NSSI prediction. METHOD: Within a sample of 1,021 high-risk self-injurious and/or suicidal individuals, we examined the accuracy of three different model types, of increasing complexity, in predicting NSSI across 3, 14, and 28 days. Univariate logistic regressions of each predictor and multiple logistic regression with all predictors were conducted for each timepoint and compared with machine learning algorithms derived from all predictors. RESULTS: Results demonstrated that model complexity was associated with predictive accuracy. Multiple logistic regression models (AUCs 0.70-0.72) outperformed univariate logistic models (average AUCs 0.56). Machine learning models that produced algorithms modeling complex associations across variables produced the strongest NSSI prediction across all time points (AUCs 0.87-0.90). These models outperformed all multiple logistic regression models, including those involving identical study variables. Machine learning algorithm performance remained strong even after the most important factor across algorithms was removed. CONCLUSIONS: Results parallel recent findings in suicide research and highlight the complexity that underlies NSSI. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Virtual reality suicide: Development of a translational approach for studying suicide causes.

Causal knowledge is crucial for understanding and preventing suicide. Unfortunately, we have little direct knowledge about suicide causes because we cannot conduct experiments that seek to make suicide more likely. In such situations, translational approaches can provide valuable, though tentative, information. We sought to establish a new translational approach by developing a laboratory approximation of suicide with new virtual reality (VR) technologies. Such an approach would allow researchers to tentatively investigate the causes of suicide by conducting experiments that introduce purported causes of suicide and observe their effects on VR suicide rates. Across three studies (total N = 498), results indicated that our two VR suicide scenarios (jumping from heights; shooting oneself) were safe; rated as unpleasant, realistic, and suicide-relevant; associated with several relevant predictors of VR suicide completion, including male sex, suicidal desire, suicidal capability, agitation, and prior suicidality; associated with reasons for not engaging in VR suicide that are similar to the reasons people give for not engaging in actual suicide; and produced 5% completion rates under neutral conditions and 25% completion rates after reward/avoid manipulations. We hope that future work further improves this approach and applies it to more directly test ideas about suicide causes and suicide prevention.

Are Eating Disorders and Related Symptoms Risk Factors for Suicidal Thoughts and Behaviors? A Meta-analysis.

This meta-analysis addressed whether eating disorders (EDs) are risk factors (i.e., longitudinal predictors) for suicidal thoughts and behaviors. We identified 2,611 longitudinal studies published through August 1, 2017. Inclusion required studies include at least one longitudinal analysis predicting suicide ideation, attempt, or death using an ED diagnosis and/or symptom. Fourteen studies (42 prediction cases) met criteria. Results indicated that clinically diagnosed EDs and disordered eating symptoms were significant but weak predictors of suicide attempts but not death. Effects remained weak when moderators were considered. By reviewing the methodological limitations of previous research, these results highlight avenues for future research.

What suicide interventions should target.

Recent reviews and national statistics indicate that, so far, our field has made limited progress on fulfilling its central mission of preventing future suicidal thoughts and behaviors (STBs). We posit that a fundamental reason for our lack of progress is the way in which our field tends to think about and select STB intervention targets. Specifically, the vast majority of our intervention targets are derived from untested theoretical assertions, moderate correlates of STBs, or weak risk factors for STBs. None of these forms of evidence permits causal inferences, which is problematic because successful STB interventions must target the causes of STBs. To develop effective interventions, we must employ experimental designs to identify targets that are causal, necessary, and viable.