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INTRODUCTION: Prior research suggests that African Americans (AAs) have more frequent, intense, and debilitating pain and functional disability compared with non-Hispanic Whites (NHWs). Potential contributing factors to this disparity are physical activity and sedentary behavior, given that AAs are less physically active, and physical activity is associated with antinociception (whereas sedentary behavior is linked to pronociception). However, impact of these factors on pain processing has largely been unexplored in AAs, especially before chronic pain onset. OBJECTIVE: This study examined relationships between physical activity, sedentary behavior (sitting time), and laboratory measures of pain and pain modulation in adult AAs. These included heat pain threshold and tolerance, temporal summation of pain (TSP, a marker of central sensitization), and conditioned pain modulation (CPM, a marker of descending pain inhibition). METHODS: Multiple regressions were conducted to examine the effects of physical activity and sitting time on heat threshold and tolerance. Multilevel models were conducted to assess the relationship between physical activity, sitting time, and temporal summation of pain. Additional multilevel models were conducted to assess the relationship between physical activity, sitting time, and conditioned pain modulation. RESULTS: Higher level of physical activity, but not sitting time, was associated with reduced TSP slopes. Neither physical activity nor sitting time was associated with CPM slopes. No significant relationships between physical activity or sitting time and heat pain threshold or tolerance were detected. CONCLUSIONS: These findings suggest that physical activity is associated with reduced TSP, an effect which may be driven by reduced spinal hyperexcitability in more active individuals. Thus, structural and individual interventions designed to increase physical activity in healthy, young AAs may be able to promote antinociceptive processes (ie, reduced TSP/reduced pain facilitation) potentially protective against chronic pain.

BackgroundDysfunction in major stress response systems during the acute aftermath of trauma may contribute to risk for developing posttraumatic stress disorder (PTSD). The current study investigated how PTSD diagnosis and symptom severity, depressive symptoms, and childhood trauma uniquely relate to diurnal neuroendocrine secretion (cortisol and alpha-amylase rhythms) in women who recently experienced interpersonal trauma compared to non-traumatized controls (NTCs).MethodUsing a longitudinal design, we examined diurnal cortisol and alpha-amylase rhythms in 98 young women (n = 57 exposed to recent interpersonal trauma, n = 41 NTCs). Participants provided saliva samples and completed symptom measures at baseline and 1-, 3-, and 6-month follow-up.ResultsMultilevel models (MLMs) revealed lower waking cortisol predicted the development of PTSD in trauma survivors and distinguished at-risk women from NTCs. Women with greater childhood trauma exposure exhibited flatter diurnal cortisol slopes. Among trauma-exposed individuals, lower waking cortisol levels were associated with higher concurrent PTSD symptom severity. Regarding alpha-amylase, MLMs revealed women with greater childhood trauma exposure exhibited higher waking alpha-amylase and slower diurnal alpha-amylase increase.ConclusionsResults suggest lower waking cortisol in the acute aftermath of trauma may be implicated in PTSD onset and maintenance. Findings also suggest childhood trauma may predict a different pattern of dysfunction in stress response systems following subsequent trauma exposure than the stress system dynamics associated with PTSD risk; childhood trauma appears to be associated with flattened diurnal cortisol and alpha-amylase slopes, as well as higher waking alpha-amylase.

A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study adopted multilevel modeling and exploratory machine learning (ML) methods to predict PTSD onset in 58 young women, ages 18 to 30, who experienced an incident of physical and/or sexual assault in the three months prior to baseline assessment. Women completed baseline assessments of theory-driven cognitive and neurobiological predictors and interview-based measures of PTSD diagnostic status and symptom severity at 1-, 3-, and 6-month follow-ups. Higher levels of self-blame, generalized anxiety disorder severity, childhood trauma exposure, and impairment across multiple domains were associated with a pattern of high and stable posttraumatic stress symptom severity over time. Predictive performance for PTSD onset was similarly strong for a gradient boosting machine learning model including all predictors and a logistic regression model including only baseline posttraumatic stress symptom severity. The present findings provide directions for future work on PTSD prediction among interpersonal violence survivors that could enhance early risk detection and potentially inform targeted prevention programs.

BackgroundRacial disparities in trauma care have been reported for a range of outcomes, but the extent to which these remain after accounting for socioeconomic and environmental factors remains unclear. The objective of this study was to evaluate the unique contributions of race, health insurance, community distress, and rurality/urbanicity on trauma outcomes after carefully controlling for specific injury-related risk factors.MethodsAll adult (age, ≥18 years) trauma patients admitted to a single Level I trauma center with a statewide, largely rural, catchment area from January 2010 to December 2020 were retrospectively reviewed. Primary outcomes were mortality, rehabilitation referral, and receipt of opioids in the emergency department. Demographic, socioeconomic, and injury characteristics as well as indicators of community distress and rurality based on home address were abstracted from a trauma registry database.ResultsAnalyses revealed that Black patients (n = 13,073) were younger, more likely to be male, more likely to suffer penetrating injuries, and more likely to suffer assault-based injuries compared with White patients (n = 10,946; all p < 0.001). In adjusted analysis, insured patients had a 28% lower risk of mortality (odds ratio, 0.72; p = 0.005) and were 92% more likely to be referred for postdischarge rehabilitation than uninsured patients (odds ratio, 1.92; p = 0.005). Neither race- nor place-based factors were associated with mortality. However, post hoc analyses revealed a significant race by age interaction, with Black patients exhibiting more pronounced increases in mortality risk with increasing age.ConclusionThe present findings help disentangle the social determinants of trauma disparities by adjusting for place and person characteristics. Uninsured patients were more likely to die and those who survived were less likely to receive referrals for rehabilitation services. The expected racial disparity in mortality risk favoring White patients emerged in middle age and was more pronounced for older patients.Level of evidencePrognostic and epidemiological, Level III.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic pain are known sequelae of IPV; however, not all those who experience IPV develop chronic pain. To mitigate its development, it is critical to identify the factors that are associated with increased risk of pain after IPV. This proof-of-concept study used machine-learning strategies to predict pain severity and interference in 47 young women, ages 18 to 30, who experienced an incident of IPV (i.e., physical and/or sexual assault) within three months of their baseline assessment. Young women are more likely than men to experience IPV and to subsequently develop posttraumatic stress disorder (PTSD) and chronic pain. Women completed a comprehensive assessment of theory-driven cognitive and neurobiological predictors of pain severity and pain-related interference (e.g., pain, coping, disability, psychiatric diagnosis/symptoms, PTSD/trauma, executive function, neuroendocrine, and physiological stress response). Gradient boosting machine models were used to predict symptoms of pain severity and pain-related interference across time (Baseline, 1-,3-,6- follow-up assessments). Models showed excellent predictive performance for pain severity and adequate predictive performance for pain-related interference. This proof-of-concept study suggests that machine-learning approaches are a useful tool for identifying predictors of pain development in survivors of recent IPV. Baseline measures of pain, family life impairment, neuropsychological function, and trauma history were of greatest importance in predicting pain and pain-related interference across a 6-month follow-up period. Present findings support the use of machine-learning techniques in larger studies of post-IPV pain development and highlight theory-driven predictors that could inform the development of targeted early intervention programs. However, these results should be replicated in a larger dataset with lower levels of missing data.

BackgroundAlterations in major stress response systems are present during the immediate aftermath of trauma and may play a role in determining risk for developing posttraumatic stress disorder (PTSD). However, the dynamics and determinants of stress responses during this acute recovery phase, and their relevance for longitudinal clinical course and prognosis, have yet to be fully examined. The objectives of the present study were to characterize stress response and habituation patterns to repeated social stressors in women who recently experienced interpersonal trauma and to determine the extent to which these stress responses were associated with PTSD during prospective follow-up.MethodThis longitudinal study examined salivary cortisol and alpha-amylase and heart rate (HR) responses to repeated stressors in 98 young women (ages 18-30). Participants included women who had experienced an incident of interpersonal trauma (i.e., physical and/or sexual assault) in the three months prior to their baseline assessment (n = 58) and a comparison group of healthy, non-traumatized women (n = 40). Women completed the Trier Social Stress Test (TSST), clinical interviews to evaluate posttraumatic stress symptom severity at the baseline assessment and again at 1-, 3-, and 6-month follow-ups.ResultsMultilevel models revealed a pattern of robust initial cortisol TSST responses and habituation across successive TSSTs; alpha-amylase and HR responses showed no evidence of habituation across TSSTs. Among interpersonal trauma survivors, current PTSD status was associated with more pronounced cortisol responses to the first TSST. Survivors exhibited similarly blunted cortisol responses across follow-up TSSTs regardless of PTSD status, suggesting habituation of cortisol responses among survivors who developed PTSD. PTSD re-experiencing symptoms were uniquely associated with blunting of cortisol TSST responses.ConclusionFindings suggest that PTSD as a diagnostic entity is meaningfully associated with cortisol responses to repeated social stressors. Social-evaluative threat is a salient form of danger for interpersonal trauma survivors. Identifying the determinants of cortisol (non)habituation to repeated social-evaluative threat among interpersonal trauma survivors could inform the development of early interventions for PTSD.

A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study adopted multilevel modeling and exploratory machine learning (ML) methods to predict PTSD onset in 58 young women, ages 18 to 30, who experienced an incident of physical and/or sexual assault in the three months prior to baseline assessment. Women completed baseline assessments of theory-driven cognitive and neurobiological predictors and interview-based measures of PTSD diagnostic status and symptom severity at 1-, 3-, and 6-month follow-ups. Higher levels of self-blame, generalized anxiety disorder severity, childhood trauma exposure, and impairment across multiple domains were associated with a pattern of high and stable posttraumatic stress symptom severity over time. Predictive performance for PTSD onset was similarly strong for a gradient boosting machine learning model including all predictors and a logistic regression model including only baseline posttraumatic stress symptom severity. The present findings provide directions for future work on PTSD prediction among interpersonal violence survivors that could enhance early risk detection and potentially inform targeted prevention programs.

Rates of substantiated child abuse and neglect vary significantly across counties. Despite strong cross-sectional support for links between social-contextual characteristics and abuse and neglect, few longitudinal studies have tested relations between these risk factors and substantiated rates of abuse/neglect. The goal of this study was to identify county-level socioeconomic and crime factors associated with substantiated abuse/neglect rates over 13 years (2004-2016). Annual county-level data for Tennessee, obtained from the KIDS COUNT Data Center, included rates of substantiated child abuse and neglect, children's race and ethnicity, births to unmarried women, teen birth rate, children in families receiving Supplemental Nutrition Assistance Program (SNAP) benefits, and children in families receiving Temporary Assistance for Needy Families. Annual county-level crime report data, obtained from the Tennessee Incident Based Reporting System, included sexual offenses, non-sexual assaults, stalking incidents, thefts, property damage, and drug-related offenses. Bayesian spatio-temporal models indicated that substantiated child abuse and neglect rates were independently and positively associated with teen birth rates, percentages of births to unmarried mothers, drug-related offenses, and percentages of children receiving SNAP benefits. In contrast, substantiated child abuse and neglect rates were negatively associated with percentages of African-American youth. The findings highlighted distinct demographic, socioeconomic, and crime factors associated with substantiated child abuse and neglect rates and have the potential to enhance identification of high-risk counties that could benefit from targeted abuse and neglect prevention efforts.

Use and misuse of antibiotics have driven the evolution of serine β-lactamases to better recognize new generations of β-lactam drugs, but the selective pressures driving evolution of metallo-β-lactamases are less clear. Here, we present evidence that New Delhi metallo-β-lactamase (NDM) is evolving to overcome the selective pressure of zinc(II) scarcity. Studies of NDM-1, NDM-4 (M154L), and NDM-12 (M154L, G222D) demonstrate that the point mutant M154L, contained in 50% of clinical NDM variants, selectively enhances resistance to the penam ampicillin at low zinc(II) concentrations relevant to infection sites. Each of the clinical variants is shown to be progressively more thermostable and to bind zinc(II) more tightly than NDM-1, but a selective enhancement of penam turnover at low zinc(II) concentrations indicates that most of the improvement derives from catalysis rather than stability. X-ray crystallography of NDM-4 and NDM-12, as well as bioinorganic spectroscopy of dizinc(II), zinc(II)/cobalt(II), and dicobalt(II) metalloforms probe the mechanism of enhanced resistance and reveal perturbations of the dinuclear metal cluster that underlie improved catalysis. These studies support the proposal that zinc(II) scarcity, rather than changes in antibiotic structure, is driving the evolution of new NDM variants in clinical settings.

Childhood trauma (CT) is associated with long-lasting alterations of the hypothalamic-pituitary-adrenal (HPA) axis and elevated risk for stress exposure in adulthood. Although HPA alterations are present in the early aftermath of trauma, it remains unclear how initial HPA activity is associated with subsequent stress exposure and whether CT exposure influences the strength and direction of this association. The present study examined prospective associations between hair cortisol content (HCC) and stress exposure from baseline to 3-month follow-up in young adult women with recent (i.e. past 3 months) exposure to interpersonal violence (IPV; i.e. physical or sexual assault) and non-traumatized controls. History of significant CT abuse or neglect was determined based on clinical cutoffs for a self-report CT measure: 12 women had abuse or neglect and recent IPV exposure (CT + IPV); 7 women had abuse or neglect but no IPV exposure (CT); 15 women had no history of trauma (NTC). HCC was computed for 3 cm sections reflecting cortisol secretion during the 3 months preceding the baseline assessment. The interaction of cumulative trauma and HCC predicted stress exposure over 3-month follow-up, controlling for baseline stress exposure and depressive symptoms. Simple slopes analyses revealed that lower baseline HCC predicted greater stress exposure in the CT + IPV group compared to the CT group; HCC was not associated with stress exposure in the NTC group. The present findings highlight the potential utility of HCC as a predictor of stress exposure for women with a history of childhood abuse or neglect, particularly in the context of recent IPV. Lay summary Adults with a history of CT show long-lasting alterations in major stress response systems, including the HPA axis. They are also more likely to experience stressful life events in adulthood. However, it is not clear how altered HPA activity influences risk for stress exposure and whether CT affects their relationship. The results from this study show that lower HPA activity (measured with hair cortisol) predicted greater stress exposure in women with CT - particularly for women who also experienced recent incidents involving physical or sexual assault.

Carassius gibelio (Prussian carp) is the latest invader of Canada's fresh waters, with reports of its presence in Alberta and Saskatchewan. Morphological similarities with introduced C. auratus (goldfish) and the putatively introduced (but likely misidentified) C. carassius (crucian carp) make it difficult to distinguish these species without careful examination. DNA barcoding of the mitochondrial cytochrome c oxidase I (COI) gene is a potential tool to identify Carassius individuals to species, but incorrect annotations of publicly-available sequences can confound attempts at species identification. Here we use morphology and DNA barcoding to identify putative C. gibelio specimens collected from two Alberta locations that constituted new records for the province. Morphologically, specimens were consistent with C. gibelio but were in the range for both C. gibelio and C. auratus. Genetically, our samples could not be identified to species level, being a 100% match with multiple Carassius species. Haplotype networks, however, supported the identification of Alberta carp as C. gibelio, in agreement with statistical analysis. Furthermore, the Alberta haplotype was shared with a fish reported from the seafood trade, suggesting a possible source of entry into Alberta. Therefore, although the BOLD algorithm would suggest the COI gene is not a strong candidate for species-level identification of Carassius species, a haplotype network approach and statistical examination of variability among haplotypes can be used to make reasonable inferences as to species identity. Early detection and management of Carassius species are of critical importance due to their projected ecological impact in Canada; DNA barcoding is one important tool for species identification, especially when specimens are within the phenotypic range expected for multiple species. [ABSTRACT FROM AUTHOR]