High-parametric evaluation of human invariant natural killer T cells to delineate heterogeneity in allo- and autoimmunity.

Human invariant natural killer T (iNKT) cells are a rare innate-like lymphocyte population that recognizes glycolipids presented on CD1d. Studies in mice have shown that these cells are heterogeneous and are capable of enacting diverse functions, and the composition of iNKT cell subsets can alter disease outcomes. In contrast, far less is known about how heterogeneity in human iNKT cells relates to disease. To address this, we used a high-dimensional, data-driven approach to devise a framework for parsing human iNKT heterogeneity. Our data revealed novel and previously described iNKT cell phenotypes with distinct functions. In particular, we found 2 phenotypes of interest: (1) a population with T helper 1 function that was increased with iNKT activation characterized by HLA-II+CD161- expression, and (2) a population with enhanced cytotoxic function characterized by CD4-CD94+ expression. These populations correlate with acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation and with new onset type 1 diabetes, respectively. Our study identifies human iNKT cell phenotypes associated with human disease that could aid in the development of biomarkers or therapeutics targeting iNKT cells.

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere.

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Rationale for a Clinical Trial That Compares Acute Stroke Rehabilitation at Inpatient Rehabilitation Facilities to Skilled Nursing Facilities: Challenges and Opportunities.

In the United States, approximately 400,000 patients with acute stroke are discharged annually to inpatient rehabilitation facilities (IRFs) or skilled nursing facilities (SNFs). Typically, IRFs provide time-intensive therapy for an average of 2-3 weeks, whereas SNFs provide more moderately intensive therapy for 4-5 weeks. The factors that influence discharge to an IRF or SNF are multifactorial and poorly understood. The complexity of these factors in combination with subjective clinical indications contributes to large variations in the use of IRFs and SNFs. This has significant financial implications for health care expenditure, given that stroke rehabilitation at IRFs costs approximately double that at SNFs. To control health care spending without compromising outcomes, the Institute of Medicine has stated that policy reforms that promote more efficient use of IRFs and SNFs are critically needed. A major barrier to the formulation of such policies is the highly variable and low-quality evidence for the comparative effectiveness of IRF- vs SNF-based stroke rehabilitation. The current evidence is limited by the inability of observational data to control for residual confounding, which contributes to substantial uncertainty around any magnitude of benefit for IRF- vs SNF-based care. Furthermore, it is unclear which specific patients would receive the most benefit from each setting. A randomized controlled trial addresses these issues, because random treatment allocation facilitates an equitable distribution of measured and unmeasured confounders. We discuss several measurement, practical, and ethical issues of a trial and provide our rationale for design suggestions that overcome some of these issues.

Emulating 3 Clinical Trials That Compare Stroke Rehabilitation at Inpatient Rehabilitation Facilities With Skilled Nursing Facilities.

OBJECTIVE: To inform the design of a potential future randomized controlled trial (RCT), we emulated 3 trials where patient-level outcomes were compared after stroke rehabilitation at inpatient rehabilitation facilities (IRFs) with skilled nursing facilities (SNFs). DESIGN: Trials were emulated using a 1:1 matched propensity score analysis. The 3 trials differed because facilities from rehabilitation networks with different case volumes were compared. Rehabilitation network case volumes were based on the number of patients with stroke that each hospital discharged to each specific IRF or SNF. Trial 1 included 60,529 patients from all networks, trial 2 included 34,444 patients from networks with medium and large case volumes (ie, ≥5 patients), and trial 3 included 19,161 patients from networks with large case volumes (ie, ≥10 patients). The E values were calculated to estimate the minimum strength that an unmeasured confounder would need to be to nullify the results. SETTING: A national sample of IRFs and SNFs from across the United States. PARTICIPANTS: Fee-for-service Medicare patients with acute stroke who received IRF or SNF based rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: One-year successful community discharge (home for >30 consecutive days) and all-cause mortality. RESULTS: Overall, 29,500, 15,156, and 7450 patients were matched for trials 1, 2, and 3. For 1-year successful community discharge, absolute risk differences for IRF patients were 0.21 (95% CI, 0.20-0.22), 0.17 (95% CI, 0.16-0.19), and 0.12 (95% CI, 0.10-0.14) in trials 1, 2, and 3, respectively. For 1-year all-cause mortality, corresponding risk differences were -0.11 (95% CI, -0.12 to -0.11), -0.11 (95% CI, -0.12 to -0.09), and -0.08 (95% CI, -0.10 to -0.06). The E values indicated that a moderately sized unmeasured confounder, with a relative risk of 1.6-2.0 would nullify differences in successful community discharge. CONCLUSIONS: IRF patients had superior outcomes, but differences were attenuated when IRFs and SNFs from larger rehabilitation networks were compared. The vulnerability of the findings to unmeasured confounding supports the need for an RCT.

External Validation of the PediBIRN Screening Tool for Abusive Head Trauma in Pediatric Emergency Department Settings.

METHODS: We conducted a retrospective, secondary analysis of an existing, deidentified, prospective data set captured to derive a bruising CDR. Subjects were patients under 3 years with bruising and confirmed acute head trauma. An expert medical panel had previously identified patients with AHT. Measures of the CDR's AHT screening performance (sensitivity, specificity, likelihood ratios) were calculated with 95% confidence intervals (CIs). RESULTS: Expert medical panel members had classified 78 of 117 eligible patients (67%) as AHT, 38 (33%) as non-AHT, and 1 as indeterminate. Excluding the indeterminate case, the PediBIRN-4 demonstrated a sensitivity of 0.96 (95% CI, 0.88-0.99), specificity of 0.29 (95% CI, 0.16-0.46), positive likelihood ratio of 1.35 (95% CI, 1.10-1.67), and negative likelihood ratio of 0.13 (95% CI, 0.04-0.46). Close inspection of the data revealed that 1 of the CDR's predictor variables had lowered specificity without impacting sensitivity. Eliminating this variable would have increased specificity to 0.84 (95% CI, 0.68-0.93). CONCLUSIONS: The PediBIRN 4-variable CDR demonstrated AHT screening sensitivity in the pediatric ED equivalent to pediatric intensive care unit and other inpatient settings, but lower specificity. Further study of a simplified 3-variable PediBIRN AHT screening tool for the ED setting is warranted.

A Cluster Randomized Trial to Reduce Missed Abusive Head Trauma in Pediatric Intensive Care Settings.

OBJECTIVE: To estimate the impact of the PediBIRN (Pediatric Brain Injury Research Network) 4-variable clinical decision rule (CDR) on abuse evaluations and missed abusive head trauma in pediatric intensive care settings. STUDY DESIGN: This was a cluster randomized trial. Participants included 8 pediatric intensive care units (PICUs) in US academic medical centers; PICU and child abuse physicians; and consecutive patients with acute head injures <3 years (n = 183 and n = 237, intervention vs control). PICUs were stratified by patient volumes, pair-matched, and randomized equally to intervention or control conditions. Randomization was concealed from the biostatistician. Physician-directed, cluster-level interventions included initial and booster training, access to an abusive head trauma probability calculator, and information sessions. Outcomes included "higher risk" patients evaluated thoroughly for abuse (with skeletal survey and retinal examination), potential cases of missed abusive head trauma (patients lacking either evaluation), and estimates of missed abusive head trauma (among potential cases). Group comparisons were performed using generalized linear mixed-effects models. RESULTS: Intervention physicians evaluated a greater proportion of higher risk patients thoroughly (81% vs 73%, P = .11) and had fewer potential cases of missed abusive head trauma (21% vs 32%, P = .05), although estimated cases of missed abusive head trauma did not differ (7% vs 13%, P = .22). From baseline (in previous studies) to trial, the change in higher risk patients evaluated thoroughly (67%→81% vs 78%→73%, P = .01), and potential cases of missed abusive head trauma (40%→21% vs 29%→32%, P = .003), diverged significantly. We did not identify a significant divergence in the number of estimated cases of missed abusive head trauma (15%→7% vs 11%→13%, P = .22). CONCLUSIONS: PediBIRN-4 CDR application facilitated changes in abuse evaluations that reduced potential cases of missed abusive head trauma in PICU settings. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03162354.

Race/Ethnic and Stroke Subtype Differences in Poststroke Functional Recovery After Acute Rehabilitation.

OBJECTIVE: Significant racial/ethnic disparities in poststroke function exist, but whether these disparities vary by stroke subtype is unknown. Study goals were to (1) determine if racial/ethnic disparities in the recovery of poststroke function varied by stroke subtype and (2) identify confounding factors associated with these racial/ethnic disparities. DESIGN: Secondary analysis of the 1-year Stroke Recovery in Underserved Populations Cohort Study. SETTING: Eleven inpatient rehabilitation facilities (IRFs) across the United States. PARTICIPANTS: A total of 1066 patients (n=868 with ischemic stroke and n=198 with hemorrhagic stroke, N=1066) who self-identified as White (n=813), Black (n=183), or Hispanic (n=70). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: FIM scores at IRF admission, discharge, 3 months, and 12 months were modeled using multivariable mixed effects longitudinal regression. RESULTS: Compared with White patients, Black (-6.1 and -4.6) and Hispanic (-10.1 and -9.9) patients had significantly lower FIM scores at 3 and 12 months, respectively. A significant (P<.01) 3-way interaction (race/ethnic*subtype*time) indicated that disparities varied by stroke subtype. The stroke subtype differences were most prominent for Black-White disparities because disparities in hemorrhagic stroke were present at IRF admission (vs 3 months for ischemic stroke). Additionally, at 12 months, the magnitude of Black-White disparities was over 3 times larger for hemorrhagic stroke (-10.4) than ischemic stroke (-3.1). Age primarily influenced Black-White disparities (especially for hemorrhagic stroke), but factors that influenced Hispanic-White disparities were not identified. Sensitivity analyses showed that there were stroke subtype differences in racial/ethnic disparities for cognitive (but not motor) function, and results were robust to adjustments for missing data because of attrition. CONCLUSIONS: There are significant differences between stroke subtypes in the timing and magnitude of Black-White disparities in poststroke function. Age was a major confounding factor for Black-White disparities (particularly for hemorrhagic stroke). Overall, Hispanic patients had the lowest levels of poststroke function, and more work is needed to identify significant factors that influence Hispanic-White disparities.

Number of musculoskeletal pain sites leads to increased long-term healthcare contacts and healthcare related costs - a Danish population-based cohort study.

BACKGROUND: People with musculoskeletal pain seek more healthcare than the general population, however little is known about the long-term effect on healthcare use. The aim of this study was to examine the consequences of number of musculoskeletal pain sites on long-term care-seeking and healthcare-related costs and explore how health anxiety influences this relationship. METHODS: We conducted a Danish population-based longitudinal cohort study of 4883 participants combining self-reported survey data from 2008 with ten-year follow-up data from national health registers. Using a causal inference framework, we examined associations between number of pain sites (range 0-7)/level of health anxiety (high/low level) and face-to-face healthcare contacts/healthcare-related costs. Data were analyzed using negative binomial regression with generalized estimating equations. Regression models were adjusted for sex, age, duration of pain, level of education, comorbidity, personality traits, risk of depression, marital status, physical job exposure, and previous healthcare utilization. RESULTS: For each additional pain site general healthcare contacts (Incidence Rate Ratio (IRR): 1.04 (95% CI: 1.03-1.05)), healthcare-related costs (IRR: 1.06 (95% CI: 1.03-1.08) and musculoskeletal healthcare contacts (IRR: 1.11 (95% CI:1.09-1.14) increased. Those with high levels of health anxiety at baseline had a slightly higher number of general healthcare contacts (IRR 1.06 (1.01-1.11), independent of number of pain sites. However, level of anxiety did not influence the effect of number of pain sites on any healthcare use or cost outcomes. CONCLUSIONS: We found evidence for a causal association between increasing number of pain sites and greater healthcare use and cost, and high levels of health anxiety did not increase the strength of this association. This suggests that number of pain sites could be a potential target for biopsychosocial interventions in order to reduce the need for future care-seeking.

Estimating the Relevance of Historical Red Flags in the Diagnosis of Abusive Head Trauma.

OBJECTIVE: To replicate the previously published finding that the absence of a history of trauma in a child with obvious traumatic head injuries demonstrates high specificity and high positive predictive value (PPV) for abusive head trauma. STUDY DESIGN: This was a secondary analysis of a deidentified, cross-sectional dataset containing prospective data on 346 young children with acute head injury hospitalized for intensive care across 18 sites between 2010 and 2013, to estimate the diagnostic relevance of a caregiver's specific denial of any trauma, changing history of accidental trauma, or history of accidental trauma inconsistent with the child's gross motor skills. Cases were categorized as definite or not definite abusive head trauma based solely on patients' clinical and radiologic findings. For each presumptive historical "red flag," we calculated sensitivity, specificity, predictive values, and likelihood ratio (LR) with 95% CI for definite abusive head trauma in all patients and also in cohorts with normal, abnormal, or persistent abnormal neurologic status. RESULTS: A caregiver's specific denial of any trauma demonstrated a specificity of 0.90 (95% CI, 0.84-0.94), PPV of 0.81 (95% CI, 0.71-0.88), and a positive LR (LR+) of 4.83 (95% CI, 3.07-7.61) for definite abusive head trauma in all patients. Specificity and LR+ were lowest-not highest-in patients with persistent neurologic abnormalities. The 2 other historical red flags showed similar trends. CONCLUSIONS: A caregiver's specific denial of any trauma, changing history of accidental trauma, or history of accidental trauma that is developmentally inconsistent are each highly specific (>0.90) but may provide weaker support than previously reported for a diagnosis of abusive head trauma in patients with persistent neurologic abnormalities.

Weak effects of geolocators on small birds: A meta-analysis controlled for phylogeny and publication bias.

Currently, the deployment of tracking devices is one of the most frequently used approaches to study movement ecology of birds. Recent miniaturization of light-level geolocators enabled studying small bird species whose migratory patterns were widely unknown. However, geolocators may reduce vital rates in tagged birds and may bias obtained movement data. There is a need for a thorough assessment of the potential tag effects on small birds, as previous meta-analyses did not evaluate unpublished data and impact of multiple life-history traits, focused mainly on large species and the number of published studies tagging small birds has increased substantially. We quantitatively reviewed 549 records extracted from 74 published and 48 unpublished studies on over 7,800 tagged and 17,800 control individuals to examine the effects of geolocator tagging on small bird species (body mass <100 g). We calculated the effect of tagging on apparent survival, condition, phenology and breeding performance and identified the most important predictors of the magnitude of effect sizes. Even though the effects were not statistically significant in phylogenetically controlled models, we found a weak negative impact of geolocators on apparent survival. The negative effect on apparent survival was stronger with increasing relative load of the device and with geolocators attached using elastic harnesses. Moreover, tagging effects were stronger in smaller species. In conclusion, we found a weak effect on apparent survival of tagged birds and managed to pinpoint key aspects and drivers of tagging effects. We provide recommendations for establishing matched control group for proper effect size assessment in future studies and outline various aspects of tagging that need further investigation. Finally, our results encourage further use of geolocators on small bird species but the ethical aspects and scientific benefits should always be considered.

QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo.

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing unit (GPU) support. These scaling and memory reductions greatly increase the number of orbitals that can practically be included in AFQMC calculations, increasing the accuracy. Advances in real space methods include techniques for accurate computation of bandgaps and for systematically improving the nodal surface of ground state wavefunctions. Results of these calculations can be used to validate application of more approximate electronic structure methods, including GW and density functional based techniques. To provide an improved foundation for these calculations, we utilize a new set of correlation-consistent effective core potentials (pseudopotentials) that are more accurate than previous sets; these can also be applied in quantum-chemical and other many-body applications, not only QMC. These advances increase the efficiency, accuracy, and range of properties that can be studied in both molecules and materials with QMC and QMCPACK.

Patterns of blood mercury variation in two long-distance migratory thrushes on Mount Mansfield, Vermont.

We investigated mercury (Hg) blood concentrations in Bicknell's thrush (Catharus bicknelli) and Swainson's thrush (C. ustulatus), congeneric long-distance migratory songbirds, from 2000-2017 at a montane forest site in north-central Vermont. We analyzed variation in blood Hg of both species using mixed-effects models, incorporating atmospheric wet Hg deposition data from a nearby sampling location. Although Hg deposition varied among years and seasonally, we detected no temporal trend in either atmospheric deposition or blood Hg, nor evidence of a relationship between the two. Sampling date had the strongest effect on blood Hg concentration, which declined seasonally, followed by age and sex of the individual. The data did not support an effect of species. We believe that the absence of a clear relationship between local atmospheric deposition and thrush blood Hg concentrations suggests that Hg cycling dynamics, mechanisms of transfer, and timing of uptake by montane forest biota are complex and poorly understood. The blood Hg concentrations of ~0.07-0.1 µg/g we documented in Bicknell's and Swainson's thrush are below those found to negatively impact physiological or reproductive endpoints in other invertivorous terrestrial passerines. To better evaluate the validity of Bicknell's thrush as a bioindicator of MeHg availability in montane forest ecosystems, we recommend (1) effects-based investigations, (2) a more robust understanding of Hg and MeHg cycling, (3) more clear geospatial and temporal links between Hg deposition and biotic uptake, and (4) more thorough documentation of Hg burdens across the species' annual cycle.

Brain 18F-FDG-PET: Utility in the Diagnosis of Dementia and Epilepsy.

BACKGROUND: The authors reviewed the two most common current uses of brain 18F-labeled fluoro-2-deoxyglucose positron emission tomography (FDG-PET) at a large academic medical center. For epilepsy patients considering surgical management, FDG-PET can help localize epileptogenic lesions, discriminate between multiple or discordant EEG or MRI findings, and predict prognosis for post-surgical seizure control. In elderly patients with cognitive impairment, FDG-PET often demonstrates lobar-specific patterns of hypometabolism that suggest particular underlying neurodegenerative pathologies, such as Alzheimer's disease. FDG-PET of the brain can be a key diagnostic modality and contribute to improved patient care.

Deep Immune Profiling of an Arginine-Enriched Nutritional Intervention in Patients Undergoing Surgery.

Application of high-content immune profiling technologies has enormous potential to advance medicine. Whether these technologies reveal pertinent biology when implemented in interventional clinical trials is an important question. The beneficial effects of preoperative arginine-enriched dietary supplements (AES) are highly context specific, as they reduce infection rates in elective surgery, but possibly increase morbidity in critically ill patients. This study combined single-cell mass cytometry with the multiplex analysis of relevant plasma cytokines to comprehensively profile the immune-modifying effects of this much-debated intervention in patients undergoing surgery. An elastic net algorithm applied to the high-dimensional mass cytometry dataset identified a cross-validated model consisting of 20 interrelated immune features that separated patients assigned to AES from controls. The model revealed wide-ranging effects of AES on innate and adaptive immune compartments. Notably, AES increased STAT1 and STAT3 signaling responses in lymphoid cell subsets after surgery, consistent with enhanced adaptive mechanisms that may protect against postsurgical infection. Unexpectedly, AES also increased ERK and P38 MAPK signaling responses in monocytic myeloid-derived suppressor cells, which was paired with their pronounced expansion. These results provide novel mechanistic arguments as to why AES may exert context-specific beneficial or adverse effects in patients with critical illness. This study lays out an analytical framework to distill high-dimensional datasets gathered in an interventional clinical trial into a fairly simple model that converges with known biology and provides insight into novel and clinically relevant cellular mechanisms.

Racial and Ethnic Disparities and Bias in the Evaluation and Reporting of Abusive Head Trauma.

OBJECTIVE: To characterize racial and ethnic disparities in the evaluation and reporting of suspected abusive head trauma (AHT) across the 18 participating sites of the Pediatric Brain Injury Research Network (PediBIRN). We hypothesized that such disparities would be confirmed at multiple sites and occur more frequently in patients with a lower risk for AHT. STUDY DESIGN: Aggregate and site-specific analysis of the cross-sectional PediBIRN dataset, comparing AHT evaluation and reporting frequencies in subpopulations of white/non-Hispanic and minority race/ethnicity patients with lower vs higher risk for AHT. RESULTS: In the PediBIRN study sample of 500 young, acutely head-injured patients hospitalized for intensive care, minority race/ethnicity patients (n = 229) were more frequently evaluated (P < .001; aOR, 2.2) and reported (P = .001; aOR, 1.9) for suspected AHT than white/non-Hispanic patients (n = 271). These disparities occurred almost exclusively in lower risk patients, including those ultimately categorized as non-AHT (P = .001 [aOR, 2.4] and P = .003 [aOR, 2.1]) or with an estimated AHT probability of ≤25% (P <.001 [aOR, 4.1] and P <.001 [aOR, 2.8]). Similar site-specific analyses revealed that these results reflected more extreme disparities at only 2 of 18 sites, and were not explained by local confounders. CONCLUSION: Significant race/ethnicity-based disparities in AHT evaluation and reporting were observed at only 2 of 18 sites and occurred almost exclusively in lower risk patients. In the absence of local confounders, these disparities likely represent the impact of local physicians' implicit bias.

Classifying Injuries in Young Children as Abusive or Accidental: Reliability and Accuracy of an Expert Panel Approach.

OBJECTIVE: To assess interrater reliability and accuracy of an expert panel in classifying injuries of patients as abusive or accidental based on comprehensive case information. STUDY DESIGN: Data came from a prospective, observational, multicenter study investigating bruising characteristics of children younger than 4 years. We enrolled 2166 patients with broad ranges of illnesses and injuries presenting to one of 5 pediatric emergency departments in whom bruises were identified during examination. We collected comprehensive data regarding current and past injuries and illnesses, and provided deidentified, standardized case information to a 9-member multidisciplinary panel of experts with extensive experience in pediatric injury. Each panelist classified cases using a 5-level ordinal scale ranging from definite abuse to definite accident. Panelists also assessed whether report to child protective services (CPS) was warranted. We calculated reliability coefficients for likelihood of abuse and decision to report to CPS. RESULTS: The interrater reliability of the panelists was high. The Kendall coefficient (95% CI) for the likelihood of abuse was 0.89 (0.87, 0.91) and the kappa coefficient for the decision to report to CPS was 0.91 (0.87, 0.94). Reliability of pairs and subgroups of panelists were similarly high. A panel composite classification was nearly perfectly accurate in a subset of cases having definitive, corroborated injury status. CONCLUSIONS: A panel of experts with different backgrounds but common expertise in pediatric injury is a reliable and accurate criterion standard for classifying pediatric injuries as abusive or accidental in a sample of children presenting to a pediatric emergency department.

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures.

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factor reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10-100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.

Tracking dragons: stable isotopes reveal the annual cycle of a long-distance migratory insect.

Insect migration is globally ubiquitous and can involve continental-scale movements and complex life histories. Apart from select species of migratory moths and butterflies, little is known about the structure of the annual cycle for migratory insects. Using stable-hydrogen isotope analysis of 852 wing samples from eight countries spanning 140 years, combined with 21 years of citizen science data, we determined the full annual cycle of a large migratory dragonfly, the common green darner ( Anax junius). We demonstrate that darners undertake complex long-distance annual migrations governed largely by temperature that involve at least three generations. In spring, the first generation makes a long-distance northbound movement (further than 650 km) from southern to northern range limits, lays eggs and dies. A second generation emerges and returns south (further than 680 km), where they lay eggs and die. Finally, a third resident generation emerges, reproducing locally and giving rise to the cohort that migrates north the following spring. Since migration timing and nymph development are highly dependent on temperature, continued climate change could lead to fundamental changes in the biology for this and similar migratory insects.

Gaussian process based optimization of molecular geometries using statistically sampled energy surfaces from quantum Monte Carlo.

Optimization of atomic coordinates and lattice parameters remains a significant challenge to the wide use of stochastic electronic structure methods such as quantum Monte Carlo (QMC). Measurements of the forces and stress tensor by these methods contain statistical errors, challenging conventional gradient-based numerical optimization methods that assume deterministic results. Additionally, forces are not yet available for some methods, wavefunctions, and basis sets and when available may be expensive to compute to sufficiently high statistical accuracy near energy minima, where the energy surfaces are flat. Here, we explore the use of Gaussian process based techniques to sample the energy surfaces and reduce sensitivity to the statistical nature of the problem. We utilize Latin hypercube sampling, with the number of sampled energy points scaling quadratically with the number of optimized parameters. We show these techniques may be successfully applied to systems consisting of tens of parameters, demonstrating QMC optimization of a benzene molecule starting from a randomly perturbed, broken symmetry geometry.