Reverse metabolomics for the discovery of chemical structures from humans.

Determining the structure and phenotypic context of molecules detected in untargeted metabolomics experiments remains challenging. Here we present reverse metabolomics as a discovery strategy, whereby tandem mass spectrometry spectra acquired from newly synthesized compounds are searched for in public metabolomics datasets to uncover phenotypic associations. To demonstrate the concept, we broadly synthesized and explored multiple classes of metabolites in humans, including N-acyl amides, fatty acid esters of hydroxy fatty acids, bile acid esters and conjugated bile acids. Using repository-scale analysis1,2, we discovered that some conjugated bile acids are associated with inflammatory bowel disease (IBD). Validation using four distinct human IBD cohorts showed that cholic acids conjugated to Glu, Ile/Leu, Phe, Thr, Trp or Tyr are increased in Crohn's disease. Several of these compounds and related structures affected pathways associated with IBD, such as interferon-γ production in CD4+ T cells3 and agonism of the pregnane X receptor4. Culture of bacteria belonging to the Bifidobacterium, Clostridium and Enterococcus genera produced these bile amidates. Because searching repositories with tandem mass spectrometry spectra has only recently become possible, this reverse metabolomics approach can now be used as a general strategy to discover other molecules from human and animal ecosystems.

Elucidating the role of lipid interactions in stabilizing the membrane protein KcsA.

The significant effects of lipid binding on the functionality of potassium channel KcsA have been validated by brilliant studies. However, the specific interactions between lipids and KcsA, such as binding parameters for each binding event, have not been fully elucidated. In this study, we employed native mass spectrometry to investigate the binding of lipids to KcsA and their effects on the channel. The tetrameric structure of KcsA remains intact even in the absence of lipid binding. However, the subunit architecture of the E71A mutant, which is constantly open at low pH, relies on tightly associated copurified lipids. Furthermore, we observed that lipids exhibit weak binding to KcsA at high pH when the channel is at a closed/inactivation state in the absence of permeant cation K+. This feeble interaction potentially facilitates the association of K+ ions, leading to the transition of the channel to a resting closed/open state. Interestingly, both anionic and zwitterionic lipids strongly bind to KcsA at low pH when the channel is in an open/inactivation state. We also investigated the binding patterns of KcsA with natural lipids derived from E. coli and Streptomyces lividans. Interestingly, lipids from E. coli exhibited much stronger binding affinity compared to the lipids from S. lividans. Among the natural lipids from S. lividans, free fatty acids and triacylglycerols demonstrated the tightest binding to KcsA, whereas no detectable binding events were observed with natural phosphatidic acid lipids. These findings suggest that the lipid association pattern in S. lividans, the natural host for KcsA, warrants further investigation. In conclusion, our study sheds light on the role of lipids in stabilizing KcsA and highlights the importance of specific lipid-protein interactions in modulating its conformational states.

Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer's Disease Across Distinct Brain Regions.

Alzheimer's disease (AD) is a neurodegenerative disease with a complex etiology influenced by confounding factors such as genetic polymorphisms, age, sex, and race. Traditionally, AD research has not prioritized these influences, resulting in dramatically skewed cohorts such as three times the number of Apolipoprotein E (APOE) ε4-allele carriers in AD relative to healthy cohorts. Thus, the resulting molecular changes in AD have previously been complicated by the influence of apolipoprotein E disparities. To explore how apolipoprotein E polymorphism influences AD progression, 62 post-mortem patients consisting of 33 AD and 29 controls (Ctrl) were studied to balance the number of ε4-allele carriers and facilitate a molecular comparison of the apolipoprotein E genotype. Lipid and protein perturbations were assessed across AD diagnosed brains compared to Ctrl brains, ε4 allele carriers (APOE4+ for those carrying 1 or 2 ε4s and APOE4- for non-ε4 carriers), and differences in ε3ε3 and ε3ε4 Ctrl brains across two brain regions (frontal cortex (FCX) and cerebellum (CBM)). The region-specific influences of apolipoprotein E on AD mechanisms showcased mitochondrial dysfunction and cell proteostasis at the core of AD pathophysiology in the post-mortem brains, indicating these two processes may be influenced by genotypic differences and brain morphology.

Altered neurological and neurobehavioral phenotypes in a mouse model of the recurrent KCNB1-p.R306C voltage-sensor variant.

Pathogenic variants in KCNB1 are associated with a neurodevelopmental disorder spectrum that includes global developmental delays, cognitive impairment, abnormal electroencephalogram (EEG) patterns, and epilepsy with variable age of onset and severity. Additionally, there are prominent behavioral disturbances, including hyperactivity, aggression, and features of autism spectrum disorder. The most frequently identified recurrent variant is KCNB1-p.R306C, a missense variant located within the S4 voltage-sensing transmembrane domain. Individuals with the R306C variant exhibit mild to severe developmental delays, behavioral disorders, and a diverse spectrum of seizures. Previous in vitro characterization of R306C described altered sensitivity and cooperativity of the voltage sensor and impaired capacity for repetitive firing of neurons. Existing Kcnb1 mouse models include dominant negative missense variants, as well as knockout and frameshifts alleles. While all models recapitulate key features of KCNB1 encephalopathy, mice with dominant negative alleles were more severely affected. In contrast to existing loss-of-function and dominant-negative variants, KCNB1-p.R306C does not affect channel expression, but rather affects voltage-sensing. Thus, modeling R306C in mice provides a novel opportunity to explore impacts of a voltage-sensing mutation in Kcnb1. Using CRISPR/Cas9 genome editing, we generated the Kcnb1R306C mouse model and characterized the molecular and phenotypic effects. Consistent with the in vitro studies, neurons from Kcnb1R306C mice showed altered excitability. Heterozygous and homozygous R306C mice exhibited hyperactivity, altered susceptibility to chemoconvulsant-induced seizures, and frequent, long runs of slow spike wave discharges on EEG, reminiscent of the slow spike and wave activity characteristic of Lennox Gastaut syndrome. This novel model of channel dysfunction in Kcnb1 provides an additional, valuable tool to study KCNB1 encephalopathies. Furthermore, this allelic series of Kcnb1 mouse models will provide a unique platform to evaluate targeted therapies.

Predicting response to neoadjuvant chemotherapy for colorectal liver metastasis using deep learning on prechemotherapy cross-sectional imaging.

BACKGROUND AND OBJECTIVES: Deep learning models (DLMs) are applied across domains of health sciences to generate meaningful predictions. DLMs make use of neural networks to generate predictions from discrete data inputs. This study employs DLM on prechemotherapy cross-sectional imaging to predict patients' response to neoadjuvant chemotherapy. METHODS: Adult patients with colorectal liver metastasis who underwent surgery after neoadjuvant chemotherapy were included. A DLM was trained on computed tomography images using attention-based multiple-instance learning. A logistic regression model incorporating clinical parameters of the Fong clinical risk score was used for comparison. Both model performances were benchmarked against the Response Evaluation Criteria in Solid Tumors criteria. A receiver operating curve was created and resulting area under the curve (AUC) was determined. RESULTS: Ninety-five patients were included, with 33,619 images available for study inclusion. Ninety-five percent of patients underwent 5-fluorouracil-based chemotherapy with oxaliplatin and/or irinotecan. Sixty percent of the patients were categorized as chemotherapy responders (30% reduction in tumor diameter). The DLM had an AUC of 0.77. The AUC for the clinical model was 0.41. CONCLUSIONS: Image-based DLM for prediction of response to neoadjuvant chemotherapy in patients with colorectal cancer liver metastases was superior to a clinical-based model. These results demonstrate potential to identify nonresponders to chemotherapy and guide select patients toward earlier curative resection.

Assessing Per- and Polyfluoroalkyl Substances in Fish Fillet Using Non-Targeted Analyses.

Per- and polyfluoroalkyl substances (PFAS) are a class of thousands of man-made chemicals that are persistent and highly stable in the environment. Fish consumption has been identified as a key route of PFAS exposure for humans. However, routine fish monitoring targets only a handful of PFAS, and non-targeted analyses have largely only evaluated fish from heavily PFAS-impacted waters. Here, we evaluated PFAS in fish fillets from recreational and drinking water sources in central North Carolina to assess whether PFAS are present in these fillets that would not be detected by conventional targeted methods. We used liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) to collect full scan feature data, performed suspect screening using an in-house library of 100 PFAS for high confidence feature identification, searched for additional PFAS features using non-targeted data analyses, and quantified perfluorooctanesulfonic acid (PFOS) in the fillet samples. A total of 36 PFAS were detected in the fish fillets, including 19 that would not be detected using common targeted methods, with a minimum of 6 and a maximum of 22 in individual fish. Median fillet PFOS levels were concerningly high at 11.6 to 42.3 ppb, and no significant correlation between PFOS levels and number of PFAS per fish was observed. Future PFAS monitoring in this region should target more of these 36 PFAS, and other regions not considered heavily PFAS contaminated should consider incorporating non-targeted analyses into ongoing fish monitoring studies.

From big data to big insights: statistical and bioinformatic approaches for exploring the lipidome.

The goal of lipidomic studies is to provide a broad characterization of cellular lipids present and changing in a sample of interest. Recent lipidomic research has significantly contributed to revealing the multifaceted roles that lipids play in fundamental cellular processes, including signaling, energy storage, and structural support. Furthermore, these findings have shed light on how lipids dynamically respond to various perturbations. Continued advancement in analytical techniques has also led to improved abilities to detect and identify novel lipid species, resulting in increasingly large datasets. Statistical analysis of these datasets can be challenging not only because of their vast size, but also because of the highly correlated data structure that exists due to many lipids belonging to the same metabolic or regulatory pathways. Interpretation of these lipidomic datasets is also hindered by a lack of current biological knowledge for the individual lipids. These limitations can therefore make lipidomic data analysis a daunting task. To address these difficulties and shed light on opportunities and also weaknesses in current tools, we have assembled this review. Here, we illustrate common statistical approaches for finding patterns in lipidomic datasets, including univariate hypothesis testing, unsupervised clustering, supervised classification modeling, and deep learning approaches. We then describe various bioinformatic tools often used to biologically contextualize results of interest. Overall, this review provides a framework for guiding lipidomic data analysis to promote a greater assessment of lipidomic results, while understanding potential advantages and weaknesses along the way.

Recent additions and access to a multidimensional lipidomic database containing liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry information.

The importance of lipids in biology continues to grow with their recent linkages to more diseases and conditions, microbiome fluctuations, and environmental exposures. These associations have motivated researchers to evaluate lipidomic changes in numerous matrices and studies. Lipidomic analyses, however, present numerous challenges as lipid species have broad chemistries that require different extraction methods and instrumental analyses to evaluate and separate their many isomers and isobars. Increasing knowledge about different lipid characteristics is therefore crucial for improving their separation and identification. Here, we present a multidimensional database for lipids analyzed on a platform combining reversed-phase liquid chromatography, drift tube ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (RPLC-DTIMS-CID-MS). This platform and the different separation characteristics it provides enables more confident lipid annotations when compared to traditional tandem mass spectrometry platforms, especially when analyzing highly isomeric molecules such as lipids. This database expands on our previous publication containing only human plasma and bronchoalveolar lavage fluid lipids and provides experimental RPLC retention times, IMS collision cross section (CCS) values, and m/z information for 877 unique lipids from additional biofluids and tissues. Specifically, the database contains 1504 precursor [M + H]+, [M + NH4]+, [M + Na]+, [M-H]-, [M-2H]2-, [M + HCOO]-, and [M + CH3COO]- ion species and their associated CID fragments which are commonly targeted in clinical and environmental studies, in addition to being present in the chloroform layer of Folch extractions. Furthermore, this multidimensional RPLC-DTIMS-CID-MS database spans 5 lipid categories (fatty acids, sterols, sphingolipids, glycerolipids, and glycerophospholipids) and 24 lipid classes. We have also created a webpage (tarheels.live/bakerlab/databases/) to enhance the accessibility of this resource which will be populated regularly with new lipids as we identify additional species and integrate novel standards.

Multidimensional profiles of head start preschoolers' moral self-concept predict subsequent, but not concurrent, aggression.

The moral self-concept (MSC) describes how children view themselves as moral agents. Research suggests that the MSC may relate to moral behavior, yet little is known about how MSC relates to moral behavior in preschoolers. One hundred six low-income children (M age = 52.78 months, SD = 6.61 months) and their teachers participated in this study. In the fall, children completed a MSC puppet task measure. In the fall and spring, teachers reported via children's survey prosocial behavior and aggressive behavior. We used a person-centered approach to identify profiles of MSC, which revealed two profiles of behavior: comforting prosocials and helpful aggressors. Comforting prosocials showed a moderate preference for comforting, a slight preference for helping, and a slight preference for avoiding aggression. Helpful aggressors had a moderate aversion to comforting, a strong preference for helping, and a slight preference for aggressive behavior. Subsequent analysis of covariance analysis revealed that MSC profiles did not differ in concurrent behavior but did differ in behavior 6 months later. The comforting prosocial group participated in more aggression than the helpful aggressors. Additionally, analysis of covariance analysis of change in aggression scores over time showed that comforting prosocials aggression increased, while helpful aggressors aggression decreased. Both groups over time decreased in prosocial behavior, but to different degrees. Overall, findings reveal that the MSC in preschoolers may relate to future not concurrent moral behavior.

Surgical microwave ablation for the treatment of hepatocellular carcinoma in 791 operations.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality and often arises in the setting of cirrhosis. The present series reviews outcomes following 791 operations. METHODS: Retrospective review surgical MWA for HCC from March 2007 through December 2022 at a high-volume institution was performed using a prospective database. Primary outcome was overall survival. RESULTS: A total of 791 operations in 623 patients and 1156 HCC tumors were treated with surgical MWA. Median tumor size was 2 cm (range 0.25-10 cm) with an average of 1 tumor ablated per operation (range 1-7 tumors). Nearly 90 % of patients had cirrhosis with a median MELD score of 8 (IQR = 6-11). Mortality within 30 days occurred in 13 patients (1.6 %). Per tumor, the rate of incomplete ablation was 2.25 % and local recurrence was 2.95 %. Previous ablation and tumor size were risk factors for recurrence. One-year overall survival was 82.0 % with a median overall survival of 36.5 months (95 % CI 15.7-93.7) and median disease-free survival of 15.9 months (range 5.7-37.3 months). CONCLUSION: Surgical MWA offers a low-morbidity approach for treatment of HCC, affording low rates of incomplete ablation and local recurrence.

Aggregated Molecular Phenotype Scores: Enhancing Assessment and Visualization of Mass Spectrometry Imaging Data for Tissue-Based Diagnostics.

Mass spectrometry imaging (MSI) has gained increasing popularity for tissue-based diagnostics due to its ability to identify and visualize molecular characteristics unique to different phenotypes within heterogeneous samples. Data from MSI experiments are often assessed and visualized using various supervised and unsupervised statistical approaches. However, these approaches tend to fall short in identifying and concisely visualizing subtle, phenotype-relevant molecular changes. To address these shortcomings, we developed aggregated molecular phenotype (AMP) scores. AMP scores are generated using an ensemble machine learning approach to first select features differentiating phenotypes, weight the features using logistic regression, and combine the weights and feature abundances. AMP scores are then scaled between 0 and 1, with lower values generally corresponding to class 1 phenotypes (typically control) and higher scores relating to class 2 phenotypes. AMP scores, therefore, allow the evaluation of multiple features simultaneously and showcase the degree to which these features correlate with various phenotypes. Due to the ensembled approach, AMP scores are able to overcome limitations associated with individual models, leading to high diagnostic accuracy and interpretability. Here, AMP score performance was evaluated using metabolomic data collected from desorption electrospray ionization MSI. Initial comparisons of cancerous human tissues to their normal or benign counterparts illustrated that AMP scores distinguished phenotypes with high accuracy, sensitivity, and specificity. Furthermore, when combined with spatial coordinates, AMP scores allow visualization of tissue sections in one map with distinguished phenotypic borders, highlighting their diagnostic utility.

Using Multidimensional Separations to Distinguish Isomeric Amino Acid-Bile Acid Conjugates and Assess Their Presence and Perturbations in Model Systems.

Bile acids play key roles in nutrient uptake, inflammation, signaling, and microbiome composition. While previous bile acid analyses have primarily focused on profiling 5 canonical primary and secondary bile acids and their glycine and taurine amino acid-bile acid (AA-BA) conjugates, recent studies suggest that many other microbial conjugated bile acids (or MCBAs) exist. MCBAs are produced by the gut microbiota and serve as biomarkers, providing information about early disease onset and gut health. Here we analyzed 8 core bile acids synthetically conjugated with 22 proteinogenic and nonproteogenic amino acids totaling 176 MCBAs. Since many of the conjugates were isomeric and only 42 different m/z values resulted from the 176 MCBAs, a platform coupling liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) was used for their separation. Their molecular characteristics were then used to create an in-house extended bile acid library for a combined total of 182 unique compounds. Additionally, ∼250 rare bile acid extracts were also assessed to provide additional resources for bile acid profiling and identification. This library was then applied to healthy mice dosed with antibiotics and humans having fecal microbiota transplantation (FMT) to assess the MCBA presence and changes in the gut before and after each perturbation.

Impacts of Gestational FireMaster 550 Exposure on the Neonatal Cortex Are Sex Specific and Largely Attributable to the Organophosphate Esters.

INTRODUCTION: Flame retardants (FRs) are common bodily and environmental pollutants, creating concern about their potential toxicity. We and others have found that the commercial mixture FireMaster® 550 (FM 550) or its individual brominated (BFR) and organophosphate ester (OPFR) components are potential developmental neurotoxicants. Using Wistar rats, we previously reported that developmental exposure to FM 550 or its component classes produced sex- and compound-specific effects on adult socioemotional behaviors. The underlying mechanisms driving the behavioral phenotypes are unknown. METHODS: To further mechanistic understanding, here we conducted transcriptomics in parallel with a novel lipidomics approach using cortical tissues from newborn siblings of the rats in the published behavioral study. Inclusion of lipid composition is significant because it is rarely examined in developmental neurotoxicity studies. Pups were gestationally exposed via oral dosing to the dam to FM 550 or the BFR or OPFR components at environmentally relevant doses. RESULTS: The neonatal cortex was highly sexually dimorphic in lipid and transcriptome composition, and males were more significantly impacted by FR exposure. Multiple adverse modes of action for the BFRs and OPFRs on neurodevelopment were identified, with the OPFRs being more disruptive than the BFRs via multiple mechanisms including dysregulation of mitochondrial function and disruption of cholinergic and glutamatergic systems. Disrupted mitochondrial function by environmental factors has been linked to a higher risk of autism spectrum disorders and neurodegenerative disorders. Impacted lipid classes included ceramides, sphingomyelins, and triacylglycerides. Robust ceramide upregulation in the OPFR females could suggest a heightened risk of brain metabolic disease. CONCLUSIONS: This study reveals multiple mechanisms by which the components of a common FR mixture are developmentally neurotoxic and that the OPFRs may be the compounds of greatest concern.

Major hepatectomy in elderly patients: possible benefit from robotic platform utilization.

INTRODUCTION: Robotic surgery has been increasingly utilized, yet its application for hepato-pancreato-biliary (HPB) procedures remains low due to technical complexity, perceived financial burden, and unproven clinical benefits. We hypothesized that the robotic approach would be associated with improved clinical outcomes following major hepatectomy compared with the laparoscopic approach among elderly patients who would benefit from the advantages of minimally invasive surgery. METHODS: A retrospective review of consecutive patients who underwent major hepatectomy between January 2010 and December 2021 at Carolinas Medical Center was performed. Inclusion criteria were age ≥ 65 years and major hepatectomy of three segments or more. Patients who underwent multiple liver resections, vascular/biliary reconstruction, or concomitant extrahepatic procedures (except cholecystectomy) were excluded. Categorical variables were compared using Chi-square or Fisher's exact test when more than 20% of cells had expected frequencies less than five, and Wilcoxon two-sample or Kruskal-Wallis tests were used for continuous or ordinal variables. Results are described as median and interquartile range (IQR). Multivariate analyses were used on postoperative admission days. RESULTS: There were 399 major hepatectomies performed during this time period, of which 125 met the criteria and were included. There were no differences in perioperative demographics among patients who underwent robotic hepatectomy (RH, n = 39) and laparoscopic hepatectomy (LH, n = 32). There was no difference in operative time, blood loss, or major complication rates. However, RH had lower rates of conversion to an open procedure (2.6% versus 31.3%, p = 0.002), shorter length of hospital stay [LOS, 4 (3-7) versus 6 (4-8.5) days, p ≤ 0.0001], cumulative LOS [4 (3-7) versus 6 (4.5-9) days, p ≤ 0.0001], and lower rates of intensive care unit (ICU) admission (7.7% versus 75%, p ≤ 0.001), with a trend toward fewer rehabilitation requirements. CONCLUSIONS: Robot major hepatectomy shows clinical advantages in elderly patients, including shorter hospital and ICU stays. These advantages, as well as reduced rehabilitation requirements associated with minimally invasive surgery, could overcome the current perceived financial disadvantages of robotic hepatectomy.

Textbook outcomes and benchmarks of minimally invasive left lateral sectionectomy across North America.

BACKGROUND: Minimally invasive approach represents the gold standard for the resection of the left lateral section of the liver. Recently, the American Minimally Invasive Liver Resection (AMILES) registry has become available to track outcomes of laparoscopic and robotic liver resection in the Americas. The aim of the present study is to determine the benchmark performance of MILLS throughout the AMILES database. METHODS: The AMILES registry was interrogated for cases of minimally invasive left lateral sectionectomies (MILLS). Centers with best practices according to the achievement of textbook outcomes (TOs) were identified and were used to define benchmark performances. RESULTS: Seven institutions from US and Canada entered 1665 minimally invasive liver resections, encompassing 203 MILLS. Overall, 49% of cases of MILLS satisfied contemporarily all textbook outcomes. While all centers obtained TOs with different rates of success, the outcomes of the top-ranking centers were used for benchmarking. Benchmark performance metrics of MILLS across North America are: conversion rate ≤ 3.7%, blood loss ≤ 200 ml, OR time ≤ 199 min, transfusion rate ≤ 4.5%, complication rate ≤ 7.9%, LOS ≤ 4 days. CONCLUSION: Benchmark performances of MILLS have been defined on a large multi-institutional database in North America. As more institutions join the collaboration and more prospective cases accrue, benchmark for additional procedures and approaches will be defined.

Executive function skills account for a bilingual advantage in English novel word learning among low-income preschoolers.

The current study compared economically disadvantaged bilingual and monolingual preschoolers' performance on an English novel word learning task and examined whether children's executive function (EF) skills account for differences in novel word learning performance across groups. In total, 39 English monolinguals and 35 Spanish-English bilingual preschoolers from low-income homes completed a battery of EF measures and the Quick Interactive Language Screener to gauge English novel word learning ability. Within a poverty context, bilingual preschoolers performed significantly better on measures of English novel word learning as compared with their monolingual peers. This bilingual advantage in novel word learning ability was mediated by short-term memory, but not inhibition or attention shifting, which indicates that gains in short-term memory may facilitate word learning in English for bilingual preschoolers from economically disadvantaged backgrounds. These findings have important practical implications for interventions designed to promote English vocabulary growth for low-income bilingual children.

Multidimensional profiles of Head Start children's social behaviors predict their interpretations of physical aggression.

Preschool children's reasoning regarding moral events differs according to adversity and relates to aggression. Understanding morality in young children is paramount for understanding their aggressive behaviors. The study aims to identify patterns of aggression and prosocial behavior using Latent Class Analysis (LCA) and investigate how patterns of aggression and prosocial behavior relate to reasoning about prototypic moral events. One hundred six children (Mage = 4.40 years old, SD = 0.55 years old, Range: 3.08-5.33 years old, 51% boys) enrolled in Head Start programs and their caregivers participated. In the fall caregivers completed surveys on forms (i.e., the manifestation of behavior) and functions of aggression (i.e., motivation of behavior), and prosocial behavior. The following spring children completed two moral reasoning tasks that measured children's judgment and reasoning of harm, and their attributions of transgressors' reasoning. The LCA revealed a 3-class solution: (1) high levels of relational aggression and moderate levels of prosocial behavior (bistrategic controllers), (2) low levels of both aggression and average prosocial behavior (uninvolved), (3) high levels of all types of aggression and low levels of prosocial behavior (high aggression). Subsequent analyses suggest that uninvolved children prioritize adhering to authority over other concerns, and bistrategic controllers focused on goal-oriented reasoning. Overall, our findings support that recognizing patterns of behavior may be useful in understanding children's moral reasoning.

Evaluating trunnionosis in modular anatomic shoulder arthroplasties: a retrieval study.

BACKGROUND: Shoulder arthroplasty procedures are widely indicated, and the number of shoulder arthroplasty procedures has drastically increased over the years. Rapid expansion of the utilization of reverse total shoulder arthroplasty has outpaced the more modest growth of anatomic total shoulder arthroplasty (aTSA) while shoulder hemiarthroplasty (HA) has trended down. Recently, shoulder prostheses have transitioned to increasingly modular systems offering more individualized options with the potential for decreased pain and increased range of motion. However, increased primary procedures has resulted in increased revision surgeries, with one potential cause being fretting and corrosion damage within these modular systems. METHODS: Following institutional review board approval, 130 retrieved aTSA and 135 HA explants were identified through database query. Humeral stem and head components were included in all 265 explants, whereas 108 included polyethylene glenoid liner components. All explanted components were macroscopically evaluated for standard damage modes, and taper junctions were microscopically examined for fretting/corrosion using a modified Goldberg-Cusick classification system that was 4-quadrant graded for both the male and female component. Medical records were reviewed for patient demographics and surgical information. RESULTS: In this series, 158 of explants were from female patients (male = 107), and 162 explants were from the right shoulder. Average age at implantation was 61 years (range: 24-83), average age at explanation was 66 years (range, 32-90), and average duration of implantation was 61.4 months (range, 0.5-240). Scratching, edge deformation, and burnishing were the most commonly observed standard damage modes. Of the 265 explants, 146 had a male stem component vs. 118 with a female stem component. Average summed fretting grades on male and female stem components were 8.3 and 5.9, respectively (P < .001). Average summed corrosion grades for male and female stem components were 8.2 and 6.2, respectively (P < .001). Wider male tapers (>11 mm) showed significantly less fretting and corrosion (P < .001). Lastly, mismatched metal compositions between the head and stem components showed greater fretting and corrosion damage (P = .002). CONCLUSION: In this series of 265 aTSA and HA explants, there was substantial damage present on the explanted components. All components demonstrated macroscopic damage. In this retrieval study, small-tapered male stems with small, thin female heads and mismatched metal composition between components were risk factors for increased implant wear. As shoulder arthroplasty volume increases, optimizing design is paramount for long-term success. Additional work could determine the clinical significance of these findings.

Larger-diameter trunnions and bolt-reinforced taper junctions are associated with less tribocorrosion in reverse total shoulder arthroplasty.

BACKGROUND: Morse taper junction tribocorrosion is recognized as an important failure mode in total hip arthroplasty. Although taper junctions are used in almost all shoulder arthroplasty systems currently available in the United States, with large variation in design, limited literature has described comparable analyses of taper damage in these implants. In this study, taper junction damage in retrieved reverse total shoulder arthroplasty (RTSA) implants was assessed and analyzed. METHODS: Fifty-seven retrieved RTSAs with paired baseplate and glenosphere components with Morse taper junctions were identified via database query; 19 of these also included paired humeral stems and trays or spacers with taper junctions. Components were graded for standard damage modes and for fretting and corrosion with a modified Goldberg-Cusick classification system. Medical records and preoperative radiographs were reviewed. Comparative analyses were performed assessing the impact of various implant, radiographic, and patient factors on taper damage. RESULTS: Standard damage modes were commonly found at the evaluated trunnion junctions, with scratching and edge deformation damage on 76% and 46% of all components, respectively. Fretting and corrosion damage was also common, observed on 86% and 72% of baseplates, respectively, and 23% and 40% of glenospheres, respectively. Baseplates showed greater moderate to severe (grade ≥ 3) fretting (43%) and corrosion (27%) damage than matched glenospheres (fretting, 9%; corrosion, 13%). Humeral stems showed moderate to severe fretting and corrosion on 28% and 30% of implants, respectively; matched humeral trays or spacers showed both less fretting (14%) and less corrosion (17%). On subgroup analysis, large-tapered implants had significantly lower summed fretting and corrosion grades than small-tapered implants (P < .001 for both) on glenospheres; paired baseplate corrosion grades were also significantly lower (P = .031) on large-tapered implants. Factorial analysis showed that bolt reinforcement of the taper junction was also associated with less fretting and corrosion damage on both baseplates and glenospheres. Summed fretting and corrosion grades on glenospheres with trunnions (male) were significantly greater than on glenospheres with bores (female) (P < .001 for both). CONCLUSIONS: Damage to the taper junction is commonly found in retrieved RTSAs and can occur after only months of being implanted. In this study, tribocorrosion predominantly occurred on the taper surface of the baseplate (vs. glenosphere) and on the humeral stem (vs. tray or spacer), which may relate to the flexural rigidity difference between the titanium and cobalt-chrome components. Bolt reinforcement and the use of large-diameter trunnions led to less tribocorrosion of the taper junction. The findings of this study provide evidence for the improved design of RTSA prostheses to decrease tribocorrosion.

Assessing How Chemical Exposures Affect Human Health.

Measuring chemical exposure is extremely challenging due to the range and number of anthropogenic molecules encountered in our daily lives, as well as their complex transformations throughout the body. To broadly characterize how chemical exposures influence human health, a combination of genomic, transcriptomic, proteomic, endogenous metabolomic, and xenobiotic measurements must be performed. However, while genomic, transcriptomic, and proteomic analyses have rapidly progressed over the last two decades, advancements in instrumentation and computations for nontargeted xenobiotic and endogenous small molecule measurements are still greatly needed.