brainlife.io: a decentralized and open-source cloud platform to support neuroscience research.

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.

Amygdalar Excitation of Hippocampal Interneurons Can Lead to Emotion-driven Overgeneralization of Context.

Context is central to cognition: Detailed contextual representations enable flexible adjustment of behavior via comparison of the current situation with prior experience. Emotional experiences can greatly enhance contextual memory. However, sufficiently intense emotional signals can have the opposite effect, leading to weaker or less specific memories. How can emotional signals have such intensity-dependent effects? A plausible mechanistic account has emerged from recent anatomical data on the impact of the amygdala on the hippocampus in primates. In hippocampal CA3, the amygdala formed potent synapses on pyramidal neurons, calretinin (CR) interneurons, as well as parvalbumin (PV) interneurons. CR interneurons are known to disinhibit pyramidal neuron dendrites, whereas PV neurons provide strong perisomatic inhibition. This potentially counterintuitive connectivity, enabling amygdala to both enhance and inhibit CA3 activity, may provide a mechanism that can boost or suppress memory in an intensity-dependent way. To investigate this possibility, we simulated this connectivity pattern in a spiking network model. Our simulations revealed that moderate amygdala input can enrich CA3 representations of context through disinhibition via CR interneurons, but strong amygdalar input can impoverish CA3 activity through simultaneous excitation and feedforward inhibition via PV interneurons. Our model revealed an elegant circuit mechanism that mediates an affective "inverted U" phenomenonv: There is an optimal level of amygdalar input that enriches hippocampal context representations, but on either side of this zone, representations are impoverished. This circuit mechanism helps explain why excessive emotional arousal can disrupt contextual memory and lead to overgeneralization, as seen in severe anxiety and posttraumatic stress disorder.

A taxonomy of the brain's white matter: twenty-one major tracts for the 21st century.

The functional and computational properties of brain areas are determined, in large part, by their connectivity profiles. Advances in neuroimaging and network neuroscience allow us to characterize the human brain noninvasively, but a comprehensive understanding of the human brain demands an account of the anatomy of brain connections. Long-range anatomical connections are instantiated by white matter, which itself is organized into tracts. These tracts are often disrupted by central nervous system disorders, and they can be targeted by neuromodulatory interventions, such as deep brain stimulation. Here, we characterized the connections, morphology, traversal, and functions of the major white matter tracts in the brain. There are major discrepancies across different accounts of white matter tract anatomy, hindering our attempts to accurately map the connectivity of the human brain. However, we are often able to clarify the source(s) of these discrepancies through careful consideration of both histological tract-tracing and diffusion-weighted tractography studies. In combination, the advantages and disadvantages of each method permit novel insights into brain connectivity. Ultimately, our synthesis provides an essential reference for neuroscientists and clinicians interested in brain connectivity and anatomy, allowing for the study of the association of white matter's properties with behavior, development, and disorders.

Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation.

Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bundles from diffusion Magnetic Resonance Imaging (dMRI) data indirectly, by exploiting either the idea of connectivity between regions or the geometry of fiber paths obtained with tractography techniques, or, directly, through the information in volumetric data. Despite the remarkable improvement in automatic segmentation methods over the years, their segmentation quality is not yet satisfactory, especially when dealing with datasets with very diverse characteristics, such as different tracking methods, bundle sizes or data quality. In this work, we propose a novel, supervised streamline-based segmentation method, called Classifyber, which combines information from atlases, connectivity patterns, and the geometry of fiber paths into a simple linear model. With a wide range of experiments on multiple datasets that span from research to clinical domains, we show that Classifyber substantially improves the quality of segmentation as compared to other state-of-the-art methods and, more importantly, that it is robust across very diverse settings. We provide an implementation of the proposed method as open source code, as well as web service.

Simulations reveal how M-currents and memory-based inputs from CA3 enable single neuron mismatch detection for EC3 inputs to the CA1 subfield of hippocampus.

Significant evidence has accumulated to support the hypothesis that hippocampal region CA1 operates as an associative mismatch detector (e.g., Hasselmo ME, Schnell E, Barkai E. J Neurosci 15: 5249-5262, 1995; Duncan K, Curtis C, Davachi L. J Neurosci 29: 131-139, 2009; Kumaran D, Maguire EA. J Neurosci 27: 8517-8524, 2007; Lisman JE, Grace AA. Neuron 46: 703-713, 2005; Lisman JE, Otmakhova NA. Hippocampus 11: 551-568 2001; Lörincz A, Buzsáki G. Ann N Y Acad Sci 911: 83-111, 2000; Meeter M, Murre JMJ, Talamini LM. Hippocampus 14: 722-741, 2004; Schiffer AM, Ahlheim C, Wurm MF, Schubotz RI. PLoS One 7: e36445, 2012; Vinogradova OS. Hippocampus 11: 578-598 2001). CA1 compares predictive synaptic signals from CA3 with synaptic signals from EC3, which reflect actual sensory inputs. The new CA1 pyramidal model presented here shows that the distal-proximal segregation of synaptic inputs from EC3 versus CA3, along with other biophysical features, enable such pyramids to serve as comparators that switch output encoding from a brief burst, for a match, to prolonged tonic spiking, for a mismatch. By including often-overlooked features of CA1 pyramidal neurons, this new model allows simulation of pharmacological effects that can eliminate either the match (phasic mode) response or the mismatch (tonic mode) response. These simulations reveal that dysfunctions can arise from either too much or too little ACh stimulation of the muscarinic receptors that control KCNQ channels. Additionally, a dysfunction caused by administration of an N-methyl-d-aspartate antagonist could be rescued by simultaneous administration of a KCNQ channel agonist, such as retigabine.NEW & NOTEWORTHY Hippocampal region CA1 operates as an associative mismatch detector, comparing predictive signals from CA3 with signals from EC3 reflecting sensory inputs. This new CA1 pyramidal model shows that biophysical features enable these comparators to switch output between brief bursts for matches and tonic spiking for mismatches. This suggests that cognitive learning models (e.g., predictive coding) may require much less match/mismatch circuitry than commonly assumed. Additional simulations illuminate deficits seen in psychiatric disorders and drug-induced states.

Inhibition of HSP90 and Activation of HSF1 Diminish Macrophage NLRP3 Inflammasome Activity in Alcohol-Associated Liver Injury.

BACKGROUND: Activation of NLRP3 in liver macrophages contributes to alcohol-associated liver disease (ALD). Molecular chaperone heat shock protein (HSP) 90 facilitates NLRP3 inflammasome activity during infections and inflammatory diseases. We previously reported that HSP90 is induced in ALD and regulates proinflammatory cytokines, tumor necrosis factor alpha, and IL-6. Whether HSP90 affects IL-1ß and IL-18 regulated by NLRP3 inflammasome in ALD is unknown. Here, we hypothesize that HSP90 modulated NLRP3 inflammasome activity and affects IL-1ß and IL-18 secretion in ALD. METHODS: The expression of HSP90AA1 and NLRP3 inflammasome genes was evaluated in human alcoholic livers and in mouse model of ALD. The importance of HSP90 on NLRP3 inflammasome activation in ALD was evaluated by administering HSP90 inhibitor, 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG) to mice subjected to ALD, and in vitro to bone marrow-derived macrophages (BMDM) stimulated with LPS and ATP. The effect of activation of HSF1/HSPA1A axis during HSP90 inhibition or direct activation during heat shock of BMDMs on NLRP3 activity and secretion of downstream cytokines was evaluated. RESULTS: We found positive correlation between induction of HSP90 and NLRP3 inflammasome genes in human alcoholic cirrhotic livers. Administration of 17-DMAG in mouse model of ALD significantly down-regulated NLRP3 inflammasome-mediated caspase-1 (CASP-1) activity and cytokine secretion, with reduction in ALD. 17-DMAG-mediated decrease in NLRP3 was restricted to liver macrophages. Using BMDMs, we show that inhibition of HSP90 prevented CASP-1 activity, and Gasdermin D (GSDMD) cleavage, important in release of active IL-1ß and IL-18. Interestingly, activation of the heat shock factor 1 (HSF1)/HSPA1A axis, either during HSP90 inhibition or by heat shock, decreased NLRP3 inflammasome activity and reduced secretion of cytokines. CONCLUSION: Our studies indicate that inhibition of HSP90 and activation of HSF1/HSPA1A reduce IL-1ß and IL-18 via decrease in NLRP3/CASP-1 and GSDMD activity in ALD.

The Emotional Gatekeeper: A Computational Model of Attentional Selection and Suppression through the Pathway from the Amygdala to the Inhibitory Thalamic Reticular Nucleus.

In a complex environment that contains both opportunities and threats, it is important for an organism to flexibly direct attention based on current events and prior plans. The amygdala, the hub of the brain's emotional system, is involved in forming and signaling affective associations between stimuli and their consequences. The inhibitory thalamic reticular nucleus (TRN) is a hub of the attentional system that gates thalamo-cortical signaling. In the primate brain, a recently discovered pathway from the amygdala sends robust projections to TRN. Here we used computational modeling to demonstrate how the amygdala-TRN pathway, embedded in a wider neural circuit, can mediate selective attention guided by emotions. Our Emotional Gatekeeper model demonstrates how this circuit enables focused top-down, and flexible bottom-up, allocation of attention. The model suggests that the amygdala-TRN projection can serve as a unique mechanism for emotion-guided selection of signals sent to cortex for further processing. This inhibitory selection mechanism can mediate a powerful affective 'framing' effect that may lead to biased decision-making in highly charged emotional situations. The model also supports the idea that the amygdala can serve as a relevance detection system. Further, the model demonstrates how abnormal top-down drive and dysregulated local inhibition in the amygdala and in the cortex can contribute to the attentional symptoms that accompany several neuropsychiatric disorders.

Quantification of stimulus-evoked tactile allodynia in free moving mice by the chainmail sensitivity test.

Chronic pain occurs at epidemic levels throughout the population. Hypersensitivity to touch, is a cardinal symptom of chronic pain. Despite dedicated research for over a century, quantifying this hypersensitivity has remained impossible at scale. To address these issues, we developed the Chainmail Sensitivity Test (CST). Our results show that control mice spend significantly more time on the chainmail portion of the device than mice subject to neuropathy. Treatment with gabapentin abolishes this difference. CST-derived data correlate well with von Frey measurements and quantify hypersensitivity due to inflammation. Our study demonstrates the potential of the CST as a standardized tool for assessing mechanical hypersensitivity in mice with minimal operator input.

The use of chemogenetic actuator ligands in nonhuman primate DREADDs-fMRI.

Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are engineered receptors that allow for genetically targeted, reversible manipulation of cellular activity via systemic drug administration. DREADD induced manipulations are initiated via the binding of an actuator ligand. Therefore, the use of DREADDs is contingent on the availability of actuator ligands. Actuator ligands low-dose clozapine (CLZ) and deschloroclozapine (DCZ) are highly selective for DREADDs, and, upon binding, induce physiological and behavioral changes in rodents and nonhuman primates (NHPs). Despite this reported specificity, both CLZ and DCZ have partial affinity for a variety of endogenous receptors and can induce dose-specific changes even in naïve animals. As such, this study aimed to examine the effects of CLZ and DCZ on resting-state functional connectivity (rs-FC) and intrinsic neural timescales (INTs) in naïve NHPs. In doing so, we evaluated whether CLZ and DCZ - in the absence of DREADDs - are inert by examining these ligands' effects on the intrinsic functional properties of the brain. Low-dose DCZ did not induce consistent changes in rs-FC or INTs prior to the expression of DREADDs; however, a high dose resulted in subject-specific changes in rs-FC and INTs. In contrast, CLZ administration induced consistent changes in rs-FC and INTs prior to DREADD expression in our subjects. Our results caution against the use of CLZ by explicitly demonstrating the impact of off-target effects that can confound experimental results. Altogether, these data endorse the use of low dose DCZ for future DREADD-based experiments.

brainlife.io: A decentralized and open source cloud platform to support neuroscience research.

Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research.

Comparison of 4 femoral tunnel drilling techniques in anterior cruciate ligament reconstruction.

PURPOSE: The purpose of this study was to determine which femoral tunnel drilling technique most closely reproduces the anatomic femoral footprint and has acceptable tunnel length and tunnel orientation. METHODS: We divided 20 cadaveric knees into 4 equal groups. Arthroscopically, the anatomic femoral footprint was marked with an awl as the tunnel starting point. In group 1 the femoral tunnel was drilled through a tibial tunnel. In groups 2 and 3 the femoral tunnel was drilled through the anteromedial arthroscopy portal, with a rigid drill and flexible drill, respectively. In group 4 the femoral tunnel was drilled with the outside-in technique over a pin positioned with an arthroscopic femoral guide. Measurements of the tunnel length, aperture, and placement were taken from 3-dimensional computed tomography scans. RESULTS: Tunnel length for groups 1, 2, 3, and 4 averaged 42.08 mm, 37.73 mm, 28.92 mm, and 31.96 mm (P = .039). The mean coronal angle of the tunnels as measured from the line tangent to the posterior femoral condyles was 63.30°, 61.22°, 51.77°, and 45.00° (P = .007), and the mean distance from the inferior articular surface to the edge of the tunnel was 5.60 mm, 4.36 mm, 2.42 mm, and -0.63 mm (P = .008) for groups 1, 2, 3, and 4, respectively. There was no statistical difference in footprint length, width, area, or distance from the posterior articular margin. CONCLUSION: Drilling by the transtibial technique produces the most vertical and longest tunnels. Independent drilling techniques produce the most anatomic tunnels but at the expense of tunnel length. CLINICAL RELEVANCE: When the orthopaedic surgeon is performing ACL reconstruction, it is critical to achieve anatomic placement of the graft, as well as maintain appropriate tunnel length.

Effect of Perioperative Tranexamic Acid on Allogeneic Blood Transfusions for Total Knee Arthroplasty Patients at a Community Hospital.

Introduction Tranexamic acid (TXA) has been shown to be a cost-effective method for reducing blood loss and postoperative transfusions in patients undergoing total knee arthroplasty (TKA) at tertiary care centers. However, the efficacy of TXA has not been studied in community hospitals, and the potential cost savings may be especially beneficial for these institutions. The purpose of this study was to assess the effectiveness of TXA in reducing postoperative transfusions and blood loss following TKA at a community hospital. Methods Institutional approval was obtained for the retrospective review of a consecutive series of patients that underwent a total knee arthroplasty procedure between January 1, 2019, and December 31, 2019. Patients undergoing bilateral TKA were excluded from the analysis, yielding a total of 190 TKA procedures of which 131 patients received TXA. Fisher's exact test was conducted to compare rates of transfusion between the groups. A difference in difference analysis was conducted to assess TXA's effect on patient hemoglobin levels (Hgb) on postoperative Days 1 and 2. All analyses were conducted using R studio (Vienna, Austria). A p-value of 0.05 was set as the threshold for statistical significance. Results There was no difference in group characteristics in terms of age (70 years vs 68 years, p=0.17; no-TXA vs TXA, respectively). Fisher's exact test revealed no difference in the rates of allogeneic transfusion between TKA patients who did not receive a TXA and TKA patients who received a TXA (3.4% vs 0.8%; p=0.228). However, our difference in differences analysis revealed that TXA patients had a mean reduction in hemoglobin (Hgb)-related blood loss of 0.876 Hgb/dl (95% CI: 0.56 to 1.19; p<0.001) between the preoperative period and postoperative Day 1. Similarly, our difference in differences analysis revealed a mean reduction in Hgb-related blood loss of 0.972 Hgb/dl (95% CI: 0.593 to 1.349; p<0.001) between the preoperative period and postoperative Day 2. Conclusion The present study shows TXA to be effective for reducing blood loss and transfusions following TKAs performed at a small community hospital. Given the cost-savings previously reported with TXA use, as well as the medical benefits reported in this study, TXA may have a niche in small community hospitals where cost savings from reduced transfusions and shorter hospital stays are important. Further studies should assess the exact amount of financial savings from TXA utilization in small community hospitals.

The human endogenous attentional control network includes a ventro-temporal cortical node.

Endogenous attention is the cognitive function that selects the relevant pieces of sensory information to achieve goals and it is known to be controlled by dorsal fronto-parietal brain areas. Here we expand this notion by identifying a control attention area located in the temporal lobe. By combining a demanding behavioral paradigm with functional neuroimaging and diffusion tractography, we show that like fronto-parietal attentional areas, the human posterior inferotemporal cortex exhibits significant attentional modulatory activity. This area is functionally distinct from surrounding cortical areas, and is directly connected to parietal and frontal attentional regions. These results show that attentional control spans three cortical lobes and overarches large distances through fiber pathways that run orthogonally to the dominant anterior-posterior axes of sensory processing, thus suggesting a different organizing principle for cognitive control.

Collegiate athlete brain data for white matter mapping and network neuroscience.

We describe a dataset of processed data with associated reproducible preprocessing pipeline collected from two collegiate athlete groups and one non-athlete group. The dataset shares minimally processed diffusion-weighted magnetic resonance imaging (dMRI) data, three models of the diffusion signal in the voxel, full-brain tractograms, segmentation of the major white matter tracts as well as structural connectivity matrices. There is currently a paucity of similar datasets openly shared. Furthermore, major challenges are associated with collecting this type of data. The data and derivatives shared here can be used as a reference to study the effects of long-term exposure to collegiate athletics, such as the effects of repetitive head impacts. We use advanced anatomical and dMRI data processing methods publicly available as reproducible web services at brainlife.io.

Expanding the Reach of an Evidence-Based, System-Level, Racial Equity Intervention: Translating ACCURE to the Maternal Healthcare and Education Systems.

The abundance of literature documenting the impact of racism on health disparities requires additional theoretical, statistical, and conceptual contributions to illustrate how anti-racist interventions can be an important strategy to reduce racial inequities and improve population health. Accountability for Cancer Care through Undoing Racism and Equity (ACCURE) was an NIH-funded intervention that utilized an antiracism lens and community-based participatory research (CBPR) approaches to address Black-White disparities in cancer treatment completion. ACCURE emphasized change at the institutional level of healthcare systems through two primary principles of antiracism organizing: transparency and accountability. ACCURE was successful in eliminating the treatment completion disparity and improved completion rates for breast and lung cancer for all participants in the study. The structural nature of the ACCURE intervention creates an opportunity for applications in other health outcomes, as well as within educational institutions that represent social determinants of health. We are focusing on the maternal healthcare and K-12 education systems in particular because of the dire racial inequities faced by pregnant people and school-aged children. In this article, we hypothesize cross-systems translation of a system-level intervention exploring how key characteristics of ACCURE can be implemented in different institutions. Using core elements of ACCURE (i.e., community partners, milestone tracker, navigator, champion, and racial equity training), we present a framework that extends ACCURE's approach to the maternal healthcare and K-12 school systems. This framework provides practical, evidence-based antiracism strategies that can be applied and evaluated in other systems to address widespread structural inequities.

Neural representations and mechanisms for the performance of simple speech sequences.

Speakers plan the phonological content of their utterances before their release as speech motor acts. Using a finite alphabet of learned phonemes and a relatively small number of syllable structures, speakers are able to rapidly plan and produce arbitrary syllable sequences that fall within the rules of their language. The class of computational models of sequence planning and performance termed competitive queuing models have followed K. S. Lashley [The problem of serial order in behavior. In L. A. Jeffress (Ed.), Cerebral mechanisms in behavior (pp. 112-136). New York: Wiley, 1951] in assuming that inherently parallel neural representations underlie serial action, and this idea is increasingly supported by experimental evidence. In this article, we developed a neural model that extends the existing DIVA model of speech production in two complementary ways. The new model includes paired structure and content subsystems [cf. MacNeilage, P. F. The frame/content theory of evolution of speech production. Behavioral and Brain Sciences, 21, 499-511, 1998 ] that provide parallel representations of a forthcoming speech plan as well as mechanisms for interfacing these phonological planning representations with learned sensorimotor programs to enable stepping through multisyllabic speech plans. On the basis of previous reports, the model's components are hypothesized to be localized to specific cortical and subcortical structures, including the left inferior frontal sulcus, the medial premotor cortex, the basal ganglia, and the thalamus. The new model, called gradient order DIVA, thus fills a void in current speech research by providing formal mechanistic hypotheses about both phonological and phonetic processes that are grounded by neuroanatomy and physiology. This framework also generates predictions that can be tested in future neuroimaging and clinical case studies.

Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations.

Tractography has created new horizons for researchers to study brain connectivity in vivo. However, tractography is an advanced and challenging method that has not been used so far for medical data analysis at a large scale in comparison to other traditional brain imaging methods. This work allows tractography to be used for large scale and high-quality medical analytics. BUndle ANalytics (BUAN) is a fast, robust, and flexible computational framework for real-world tractometric studies. BUAN combines tractography and anatomical information to analyze the challenging datasets and identifies significant group differences in specific locations of the white matter bundles. Additionally, BUAN takes the shape of the bundles into consideration for the analysis. BUAN compares the shapes of the bundles using a metric called bundle adjacency which calculates shape similarity between two given bundles. BUAN builds networks of bundle shape similarities that can be paramount for automating quality control. BUAN is freely available in DIPY. Results are presented using publicly available Parkinson's Progression Markers Initiative data.

A local circuit model of learned striatal and dopamine cell responses under probabilistic schedules of reward.

Recently, dopamine (DA) neurons of the substantia nigra pars compacta (SNc) were found to exhibit sustained responses related to reward uncertainty, in addition to the phasic responses related to reward-prediction errors (RPEs). Thus, cue-dependent anticipations of the timing, magnitude, and uncertainty of rewards are learned and reflected in components of DA signals. Here we simulate a local circuit model to show how learned uncertainty responses are generated, along with phasic RPE responses, on single trials. Both types of simulated DA responses exhibit the empirically observed dependencies on conditional probability, expected value of reward, and time since onset of the reward-predicting cue. The model's three major pathways compute expected values of cues, timed predictions of reward magnitudes, and uncertainties associated with these predictions. The first two pathways' computations refine those modeled by Brown et al. (1999). The third, newly modeled, pathway involves medium spiny projection neurons (MSPNs) of the striatal matrix, whose axons corelease GABA and substance P, both at synapses with GABAergic neurons in the substantia nigra pars reticulata (SNr) and with distal dendrites (in SNr) of DA neurons whose somas are located in ventral SNc. Corelease enables efficient computation of uncertainty responses that are a nonmonotonic function of the conditional probability of reward, and variability in striatal cholinergic transmission can explain observed individual differences in the amplitudes of uncertainty responses. The involvement of matricial MSPNs and cholinergic transmission within the striatum implies a relation between uncertainty in cue-reward contingencies and action-selection functions of the basal ganglia.

Hospitalized cases of child abuse in America: who, what, when, and where.

BACKGROUND: Orthopaedic surgeons need to recognize features of child abuse. The purpose of this study was to identify common characteristics of child abuse and to delineate features of physical injury cases that would raise concern for child abuse. METHODS: A nationally representative sample of all pediatric inpatient discharges for calendar years 1997, 2000, and 2003 was queried for physical injury diagnoses. Cases were identified as those with a diagnosis of child abuse and controls were those without the diagnosis of child abuse. Incidence of coded child abuse and a comparison of rates across time, demographics, and injury pattern were determined. Cases were compared with controls, and relative risks for coded child abuse were computed using the generalized linear model specifying the Poisson distribution and a log link. RESULTS: There were 665,195 physical injury cases identified. Of these, 11,554 (1.74%) had a diagnosis of child abuse. Fracture requiring orthopaedic management was present in 28% of the child abuse cases. The 3 strongest demographic predictors of coded child abuse were age younger than 1 year, age 1 to younger than 2 years, and Medicaid as primary payer with adjusted relative risks of 11.46, 3.07, and 1.99, respectively. Winter and weekday presentation were significantly higher for coded child abuse. Fractures with the greatest adjusted relative risks for coded child abuse were rib or sternum (5.34) and scapula (3.22). Pelvic fracture was the only fracture significant for lowered adjusted relative risk of coded child abuse. CONCLUSIONS: This study shows that young age continues to be a strong predictor of child abuse in the setting of physical injury. Supporting features include Medicaid as primary payer and winter or weekday presentation. Orthopaedists should be particularly aware of child abuse as 28% of cases had a fracture requiring orthopaedic management. LEVEL OF EVIDENCE: Prognostic Study, Level III (case-control study).