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Frontiers in Human Neuroscience
Brain Health and Clinical Neuroscience
Understanding the Link Between the Developing Brain and Behavior in Adolescents View all 9 Articles
Tim J. Silk
School of Psychology, Faculty of Health, Deakin University, Australia
Kelvin O. Lim
University of Minnesota Twin Cities, United States
Eileen M. Moore
Center for Behavioral Teratology, San Diego State University, United States
Fleur Warton
University of Cape Town, South Africa
Front. Hum. Neurosci., 30 June 2020 | https://doi.org/10.3389/fnhum.2020.00223
Current Socioeconomic Status Correlates With Brain Volumes in Healthy Children and Adolescents but Not in Children With Prenatal Alcohol Exposure
Kaitlyn McLachlan1*, Dongming Zhou2,3, Graham Little3, Carmen Rasmussen4, Jacqueline Pei5, Gail Andrew6, James N. Reynolds7 and Christian Beaulieu3
1Department of Psychology, College of Social & Applied Human Sciences, University of Guelph, Guelph, ON, Canada
2Department of Zoology, Kunming Medical University, Kunming, Yunnan, China
3Department of Biomedical Engineering, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
4Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
5Department of Educational Psychology, Faculty of Education, University of Alberta, Edmonton, AB, Canada
6Glenrose Rehabilitation Hospital PAE Clinic, Edmonton, AB, Canada
7Department of Biomedical and Molecular Sciences, School of Medicine, Faculty of Health Sciences, Queens University, Kingston, ON, Canada
Individuals with prenatal alcohol exposure (PAE) exhibit neurological deficits associated with brain injury including smaller brain volumes. Additional risk factors such as lower socioeconomic status (SES) may also have an impact on brain development for this population. This study examined how brain volumes are related to SES in both neurotypically developing children and adolescents, and those with PAE. 3D T1-weighted MPRAGE images were acquired from 69 participants with PAE (13.0 ± 3.2 years, range 7.1–18.8 years, 49% female) and 70 neurotypical controls (12.4 ± 2.9 years, range 7.0–18.5 years, 60% female) from four scanning sites in Canada. SES scores calculated using Hollingshead's Four-Factor Index of Social Status from current caregiver placement were not significantly different between groups, though more children with PAE had lower SES scores compared to controls. Psychometric data comprised 14 cognitive measures, including executive functioning, attention and working memory, memory, math/numerical ability, and word reading. All cognitive scores were significantly worse in children with PAE compared to controls, though SES was not correlated with cognitive scores in either group after correction for multiple comparisons. All 13 brain volumes were smaller in children with PAE compared to children in the control group. Higher SES was associated with larger hippocampus and amygdala volumes in controls, but there were no such associations in children with PAE. Direct evaluation of the interaction between SES and diagnostic group did not show a significant differential impact of SES on these structures. These findings support previous links between SES and brain volumes in neurotypically developing children, but the lack of such a relationship with SES in children with PAE may be due to the markedly smaller brain volumes resulting from the initial brain injury and postpartum brain development, regardless of later SES.
Prenatal alcohol exposure (PAE) is associated with a range of lifelong physical, cognitive, and neurological impacts, and may result in a diagnosis of fetal alcohol spectrum disorder (FASD; Cook et al., 2016; Hoyme et al., 2016; Mattson et al., 2019). PAE can impact any stage of fetal development, with studies suggesting that structural impacts are associated with the developmental timing of exposure (see reviews by Jones, 2011; Mattson et al., 2019). For instance, alcohol can impact gastrulation leading to facial dysmorphology as early as weeks 3 and 4 of pregnancy (Sulik, 2005). Alcohol also crosses the placenta and blood-brain barrier causing decreased protein synthesis, reduced DNA translation, and irreversible brain injury such as neuronal death, among other effects (West et al., 1994; Miller, 1996). PAE can also trigger a range of additional impacts such as maternal hypoxia, oxidative stress, displacement or malabsorption of essential nutrients, and altered metabolism, all of which can further alter fetal brain development (for reviews see Goodlett and Horn, 2001; Young et al., 2014; del Campo and Jones, 2017). Smaller brain volumes are commonly seen in children with PAE, as identified in autopsy (Jones and Smith, 1975; Clarren and Smith, 1978) and by several in vivo quantitative neuroimaging techniques (for reviews see Norman et al., 2009; Lebel et al., 2011). General population prevalence for FASD ranges from 2 to 5%, however, the disability is thought to occur more frequently in communities marked by socioeconomic disadvantage (May et al., 2014, 2018; Lange et al., 2017; Popova et al., 2019a,b).
Socioeconomic status (SES) has an impact on brain development and cognitive function in typically developing children (for reviews see Bradley and Corwyn, 2002; Hackman and Farah, 2009; Hackman et al., 2010; Brito and Noble, 2014). Poverty likely shapes brain development through a series of complex factors, including maternal deprivation, environmental stressors, and environmental toxins, among others. Together these factors may lead to neural changes via biological mechanisms including gene × environment interactions, epigenetic modifications, and hypothalamic pituitary adrenal (HPA) function. Ultimately this has been associated with key structural and functional changes in the brain, as well as observed neurocognitive and academic outcomes (see reviews by Brito and Noble, 2014; Johnson et al., 2016). In typically developing children, lower SES is usually associated with worse cognitive performance and academic achievement (Willms, 2004; Farah et al., 2006; Johnson et al., 2016), increased health concerns (Chen et al., 2002; Adler and Ostrove, 2006), and smaller brain volumes (Jednoróg et al., 2012; Noble et al., 2012; Cavanagh et al., 2013). Also, women and families experiencing poverty and lower SES may be at increased risk for poor maternal nutrition during pregnancy and increased maternal stress, in addition to alcohol and other substance use in the context of limited social determinants of health (Bradley and Corwyn, 2002; Lewis et al., 2011; von dem Knesebeck et al., 2013; Young et al., 2014). Lower SES has also been linked to additional mental health disorders, with generally higher levels of depression, anxiety, and psychosis (Lorant et al., 2003; Kessler et al., 2005; McLaughlin et al., 2012; Agerbo et al., 2015; Blair and Raver, 2016; Vukojević et al., 2018). Further, some studies explicitly link SES with reduced regional brain volumes, such as in adults with schizophrenia relative to controls (Takayanagi et al., 2010; Yeo et al., 2014).
Given the high rates of additional pre and postnatal experiences of adversity reported in children with FASD, coupled with higher rates of FASD in the context of health and social inequities, SES may be an important contributing factor for alterations in brain development for children and adolescents with PAE (Streissguth et al., 2004; May et al., 2005, 2008; McLachlan et al., 2015; Lebel et al., 2019; Popova et al., 2019b). While FASD can occur following an alcohol-exposed pregnancy for women and families of any SES level, lower SES is an important factor that elevates the risk of having a child with FASD, and as noted, several epidemiological studies have shown lower SES for families of children with FASD (e.g., see May et al., 2011; Popova et al., 2019b). Recently, Uban et al. (2020) reported findings from a study of SES and brain structure in a U.S. cohort of 95 children with PAE and 102 age and sex-matched controls. Their results indicated that higher SES in the current child placement was associated with larger subcortical volumes in neurotypically developing children, but not in children with PAE. To our knowledge, no other studies have evaluated SES-brain structure relationships in children with PAE or FASD. Thus, the present study aimed to identify whether current SES is associated with cognitive functioning and brain volume in children and adolescents with PAE compared to neurotypical controls.
Participants for the current study were 139 children and adolescents drawn from the larger NeuroDevNet FASD cohort (N = 239, Reynolds et al., 2011), based on their status for MRI, age, and other exclusion criteria (as outlined below). Children with PAE (n = 69) were recruited through FASD diagnostic clinics at six Canadian sites (although MRI was only at 4 sites), including Kingston, ON; Ottawa, ON; Edmonton, AB; Cold Lake, AB; Winnipeg, MB; and Vancouver, BC. Neurotypically developing children (n = 70) were recruited as a control sample from the same geographic regions, matched as closely as possible for age and sex, and were excluded if they had any neurological or psychiatric disorders.
Participants in the FASD group were predominantly assessed before their participation via a multidisciplinary team that adhered to the 2005 Canadian Diagnostic Guidelines (Chudley et al., 2005). FASD diagnosis was made by experienced multidisciplinary teams using the Canadian Guidelines from 2005 that incorporate objective methods of evaluating core clinical features of FASD, including neurodevelopmental impairment, facial dysmorphology, growth deficiency, PAE, and other pre and post natal adversity factors. As part of the diagnostic process, PAE is evaluated using a range of reliable sources of information. While detailed information regarding the pattern, timing, and volume of exposure was not available for the current study, records were reviewed to ensure that participants with PAE had confirmed exposure at the above risk thresholds following the Washington Diagnostic and Prevention Network FASD 4-digit classification system (Astley, 2004). Most children in the PAE group were diagnosed with FASD under the Canadian Guidelines1, including 26% (n = 18) with fetal alcohol syndrome (FAS) or partial fetal alcohol syndrome (pFAS), and 51% (n = 35) with alcohol-related neurodevelopmental disorder (ARND). An additional 23% (n = 16) had confirmed PAE but did not meet the criteria for formal diagnosis or were deferred for re-evaluation.
Socioeconomic Status
Socioeconomic status (SES) for the current caregiver placement at the time of scanning was calculated using Hollingshead's Four-Factor Index of Social Status, a commonly used estimate for SES based on the highest educational and current occupation for one or two caregivers in the household (Hollingshead, 1975; Adams and Weakliem, 2011). For the current study, caregivers who attended the study visit provided education and occupation data for one or both contributing adult caregivers/guardians living in the child's household, and weighted SES scores were derived based on established occupational and educational attainment scores. Occupational scores range from 1 (e.g., service workers) through 9 (e.g., higher executives and major professionals), while educational scores range from 1 (e.g., lower than 7th-grade education) through 7 (e.g., graduate-level education). The Hollingshead Index continues to be among the most widely used, brief, valid, and reliable estimate of SES in health and imaging research (e.g., Bornstein et al., 2003; Lawson et al., 2013, 2017; Cohen-Zimerman et al., 2019; Spann et al., 2019).
Cognitive Tests
Children completed a single testing session comprising a broad battery of cognitive measures spanning domains including executive functioning, attention and working memory, memory, numerical ability, and word identification (see McLachlan et al., 2017). In the current study, measures were drawn from the NEPSY-II (Korkman et al., 2007), including Animal Sorting (assessing basic concept formulation and set-shifting), Inhibition (including Naming, Inhibition, and Switching, measuring the inhibition of automatic responses in favor of novel responses and switching between response types), Memory for Names (assessing short- and long-term verbal learning and retention), and Auditory Attention and Response Set (assessing selective and sustained attention, and ability to shift and maintain information while inhibiting previously learned responses). NEPSY-II scores are age-normed as scaled scores (M = 10, and SD = 3) with higher scores indicating better cognitive performance relative to same-aged peers. Participants also completed subtests from the Working Memory Test Battery for Children (WMTB-C, Pickering and Gathercole, 2001), including Digit Recall (verbal/phonological working memory) and Block Recall (visuospatial working memory). WMTB-C age-referenced standardized scores were calculated (M = 100, and SD = 15). Participants completed the Quantitative Concepts subtest (quantitative reasoning and mathematics knowledge) from the Woodcock Johnson-III Tests of Achievement (WJ-III ACH, Woodcock et al., 2001) and the Word Identification subtest (word identification/reading ability) from the Woodcock Reading Mastery Tests-Revised (WRMT-R, Woodcock, 1998). Both tools use age-referenced standard scores (M = 100, and SD = 15).
Caregivers provided ratings of each child's executive functioning in everyday contexts via the Behavior Rating Inventory of Executive Function (BRIEF, Gioia et al., 2000). The Behavior Regulation Index (BRI, a summary score tapping one's ability to shift cognitive set and modulate appropriate behavior through effective behavioral control) and the Metacognition Index (MI, a summary of subscales tapping the ability to cognitively self-manage tasks and monitor performance) were used in analyses for the current study, specifically, age and sex referenced t-scores, where higher scores indicate greater levels of difficulty (M = 50, SD = 10). Caregivers also completed a short interview and provided basic demographic information about their child, including age, sex, handedness, ethnicity, and caregiving placement. Imaging sessions were typically conducted during a second session, within a few days or weeks of the cognitive testing session. Cognitive testing was typically completed before the MRI session.
The Human Research Ethics Boards at Queen's University, the University of Alberta, the Children's Hospital of Eastern Ontario, the University of Manitoba, and the University of British Columbia reviewed and approved all study procedures. A parent or legal guardian gave written informed consent, and children provided assent before study participation.
Image Acquisition and Processing
From the overall NeuroDevNet sample, 177 participants underwent brain MRI including 3D T1-weighted MPRAGE (1 × 1 × 1 mm3 in ~5–6 min; for acquisition details see Little and Beaulieu, 2020) at four imaging sites in Canada (University of British Columbia, UBC, 3T Philips Intera; University of Alberta, UofA, 1.5T Siemens Sonata; University of Manitoba, UofM, 3T Siemens Trio; and Queen's University, 3T Siemens Trio). In total, 20 participants were excluded after visual inspection for motion artifacts and quality control from the CIVET quality control program for segmentation and surface extraction, including eight controls and nine PAE from motion artifacts, and two controls and one PAE from segmentation errors in local areas. Another seven participants were removed owing to exclusions (e.g., neurological disorder for controls, unclear data for PAE) and 11 participants were removed owing to missing SES scores and age <7 years (several cognitive tasks are designed for children ages 7 and above), leaving a final sample of 70 neurotypically developing control children and 69 children with PAE/FASD.
An automated program (Freesurfer 5.1, Fischl et al., 2002) on the CBrain platform2 was used to yield 13 volumes of the total cerebrum, total gray matter (GM), cortical GM, and total deep subcortical GM along with its individual subregions including the hippocampus, amygdala, thalamus, caudate, putamen, and pallidum, white matter (WM), and cerebellum GM and WM. Left and right volumes were measured separately and then combined to reduce multiple comparisons.
Inter-site Correction
Given the potential for scanner differences across the four imaging sites to yield systematically differential quantitative image metrics, including volumes (e.g., vendor, model, field strength, etc., see Han et al., 2006; Wonderlick et al., 2009; Chalavi et al., 2012; Jovicich et al., 2013), volumes for the current study were corrected based on the consistency of these metrics from the same 8 healthy participants each scanned twice at each site, i.e., 64 scans total, as was done previously (Zhou et al., 2018). Effects of site, scan, and site-by-scan interactions were tested using two-way repeated-measures analysis of variance (RM-ANOVA). For a specific volume (e.g., the total cerebrum volume), if the site was significantly biased (p < 0.05), the volume was corrected for each site. A correction factor for each site was calculated as a Δ volume from the difference between the volume at each site and the mean volume across all four sites. The corrected volume was then determined for each control and PAE participant per site.
Demographic differences between groups were assessed by t-test for continuous variables (age, SES), Chi-square tests for dichotomous variables (e.g., handedness, sex), and non-parametric Wilcoxon Rank Sum tests for categorical variables (current caregiver, ethnicity, scanning site). Group comparisons for cognitive scores were made using t-tests, while brain volume comparisons were evaluated using analysis of covariance (ANCOVA), with both age and sex included as covariates. Associations between SES and cognitive scores were evaluated using Pearson correlations within each of the control and PAE groups separately. SES and brain volume associations were assessed using linear regression, controlling for age and sex, in each of the control and PAE groups separately. Exploratory hierarchical linear regressions were also conducted to directly assess the possible differential impact of SES on brain volumes in children with PAE compared to controls. Covariates (age, sex) were included in the first step of each model, followed by both group and SES (mean-centered) in the second step, and the interaction between the group and SES (mean-centered) in the third step. In all inferential analyses, p-values were considered significant at a level of 0.05. Multiple comparisons were corrected in primary analyses (e.g., between-group comparisons, bivariate associations) using the Benjamini–Hochberg false discovery rate (FDR; α = 0.05, q = 0.10 for each family of comparisons; Benjamini and Hochberg, 1995, 2000). Effect sizes for t-tests (Cohen's d), chi-square (phi, φ), and F tests (partial eta squared, ηp2) are reported. Cohen's d values range from 0.2 (small) to 0.5 (medium) to 0.8 and above (large), φ values range from 0.1 (small) to 0.3 (medium) to 0.5 and above (large), and ηp2 values range from 0.02 (small), to 0.13 (medium) to 0.26 and above (large; Cohen, 1988). Analyses were conducted using IBM SPSS Statistics 26 for Mac.
Age, sex, and handedness were similar between typically developing control participants (12.4 ± 2.9 years, range 7.0–18.5 years, 60% female, 93% right-handed) and participants with PAE (13.0 ± 3.2 years, range 7.1–18.8 years, 49% female, 91% right-handed, see Table 1). While mean SES did not differ significantly between groups, who shared comparable ranges (47 ± 9, range 13–66 in controls and 43 ± 14, range 11–66 in PAE, p = 0.06), the distributions for each group differed considerably, with only 11/70 controls (16%) having relatively lower SES scores (e.g., <40) as compared to nearly three times that number for children with PAE (30/69, 44%; see Figure 1). SES did not differ significantly across PAE subgroups, though the SES range was somewhat restricted in the PAE-only subgroup (44 ± 13, range 28–66) compared to the FAS/pFAS (44 ± 16, range 17–66) and ARND subgroups (42 ± 14, range 11–65). Differences in SES were apparent by site, F(3,135) = 2.92, p = 0.036, ηp2 = 0.06). Mean SES scores were highest at Queen's site (PAE 52 ± 11, range 32–66, Control 45 ± 5, range 32–51), followed by the UofM site (PAE 45 ± 20, range 17–66, Control 50 ± 7, range 37–58), and then the UBC (PAE 36 ± 17, range 17–66, Control 47 ± 12, range 22–66) and UofA sites (PAE 38 ± 11, range 11–61, Control 47 ± 9, range 13–63). Current caregiving arrangement differed significantly between groups, with nearly all children in the control group (n = 69, 99%) living with their biological parent(s), compared to only 9% (n = 6) of those with PAE, and the rest residing in adoptive families (n = 42, 61%), foster care placements (n = 12, 17%), or with other legal guardians (n = 7, 13%). More participants were recruited and scanned in Alberta compared to other sites (e.g., 35 controls, 50%, and 30 PAE, 43%), but there was roughly an equal number of participants in each group at each site.
Table 1. Demographic information for control and prenatal alcohol exposure (PAE) groups (N = 139).
Figure 1. Two of 13 brain volumes, (A) hippocampus, and (B) amygdala, were positively associated with socioeconomic status (SES) in neurotypically developing controls (n = 70), but not in prenatal alcohol exposure (PAE), n = 69 [displayed for different PAE/fetal alcohol spectrum disorder (FASD) subgroups, including fetal alcohol syndrome (FAS), n = 7; partial FAS (pFAS), n = 11; alcohol-related neurodevelopmental disorder (ARND), n = 35; and PAE, n = 16]. The *indicates that the p-value remained significant after correction for multiple comparisons, see Table 4. Regression lines pictured do not include covariates.
SES and Cognitive Scores
Participants with PAE performed significantly worse than control children on all cognitive test scores, including measures of executive functioning, attention and working memory, memory, numerical ability, and word identification (all p < 0.001, all significant after correction for multiple comparisons, Table 2). We examined associations between SES and cognitive test scores within each group and found no significant associations.
Table 2. Cognitive test scores and correlations with SES in control and PAE groups.
SES Correlated With Brain Volumes in Controls but not in PAE
All measured brain volumes were significantly smaller in children with PAE compared to controls after accounting for age and sex (Table 3). Most brain volumes for children with PAE were between 4 and 8% smaller compared to controls, with larger discrepancies for overall cerebellum WM and a deep gray matter structure (caudate; 10%, and 12% smaller, respectively). We examined relationships between SES and brain volumes within each of the PAE and control groups and found that SES was positively associated with subcortical structures including the hippocampus and amygdala for control children (Table 4, Figure 1). In contrast, no significant associations were observed between SES and brain volumes for children with PAE. Follow-up exploratory hierarchical linear regressions revealed no significant interactions between SES and group for any brain volumes, though diagnostic group (control vs. PAE) was significantly associated with 11 of 13 brain volumes (excluding cerebellum WM, p = 0.050, and amygdala, p = 0.051) in the overall sample (Supplementary Table S1).
Table 3. Regional brain volumes in control and PAE groups.
Table 4. Associations between regional brain volumes and SES in control and PAE groups.
SES and Brain Volumes
Complementing a range of prior studies, our findings indicated significantly smaller brain volumes across cerebrum, cerebellum, and deep gray matter volumes in children with PAE compared to neurotypically developing children (Norman et al., 2009; Lebel et al., 2011; Nardelli et al., 2011; Uban et al., 2020). Subgroup analyses showed associations between higher SES and larger volumes of specific subcortical structures including the hippocampus and amygdala in neurotypically developing children, but not in the PAE cohort; both covering the same age range of 7–18 years. Though we did not see differential patterns of association for SES by group, our findings complement results recently reported by Uban et al. (2020) in an independent cohort of similarly-aged children with PAE and controls. They found differential patterns of association for SES indicators and regional brain volumes in children with PAE vs. controls (hippocampus, nucleus accumbens, and ventral diencephalon), as well as within-group associations between SES indicators and multiple regional volumes including the amygdala in only controls, but not children with PAE.
Our results are also consistent with previous studies indicating that SES is positively correlated with brain volumes in typically developing children and adolescents (Hackman and Farah, 2009; Noble et al., 2012; Jednoróg et al., 2012; Ellwood-Lowe et al., 2018; Yu et al., 2018; McDermott et al., 2019). This includes a recent large scale longitudinal study of children ages 5–25 years (N = 623) where SES was positively associated with total brain volume, both gray and WM volume, cortical volume, in addition to subcortical structures including both the hippocampus and amygdala in a cross-sectional examination of the full sample (McDermott et al., 2019). These associations also remained stable in a subset of 344 individuals with multiple scans suggesting that intra-individual age-related change did not modify the SES-volume relationship. Our results also fit with other cross-sectional studies. For instance, lower SES has been associated with lower cortical gray matter, hippocampal, and amygdala volumes in typically developing 3–15-year-olds (Luby et al., 2013); regional volumes of the hippocampus and amygdala in 5–17-year-olds (Noble et al., 2012); regional volumes of the middle temporal gyri, left fusiform, and right inferior occipito-temporal gyri in typically developing 8–10-year-olds (Jednoróg et al., 2012); and hippocampal volume in 10–24-year-old girls (Ellwood-Lowe et al., 2018) and children aged 8–12 years (Yu et al., 2018). The negative effect on regional brain morphology in individuals from lower SES families may relate to the lack of nutrients during prenatal or postpartum development (Ivanovic et al., 2002; Pechey and Monsivais, 2015; Ranjit et al., 2015), decreased overall health (Adler and Ostrove, 2006) or raised stress levels (Bradley and Corwyn, 2002; Hackman and Farah, 2009; Hackman et al., 2010; Pagliaccio et al., 2014), all of which could have an impact on the developing brain.
The influence of SES on brain structure seems to be a long-term effect where early years spent in a lower SES environment can affect the brain into and beyond adulthood, such as one previous study which reported that the hippocampus volume at 64 years of age was positively correlated with familial SES status at 11 years (Staff et al., 2012). Another study showed that SES in childhood at age 11 years positively correlated with cerebellum volumes (lower SES predicted less volume) at 35–64 years (Cavanagh et al., 2013). As noted above, McDermott et al. (2019) demonstrated stable associations between SES and multiple indicators of brain volume in a longitudinal model for children and young adults aged 5–25 years. However, there are exceptions, such as one study where childhood poverty was not found to be associated with brain volumes at 44–48 years, but interestingly bilateral hippocampal and amygdala volumes did correlate with the participants' current financial status (Butterworth et al., 2012). Similarly, two studies did not find correlations between current SES and brain volumes in healthy participants of ~30 years, but did show links between lower SES and reduced gray matter volumes in individuals with schizophrenia over this age range (Takayanagi et al., 2010; Yeo et al., 2014).
Although brain volume often forms the primary focus in imaging research, SES studies have also examined cortical thickness and diffusion tensor imaging (DTI) of WM. For instance, in a study of neurotypical children ages 4–18 years, the thicker cortex in the left superior frontal gyrus and right anterior cingulate gyrus was found to correlate with higher parental education (Lawson et al., 2013). Other typical development studies have addressed SES and WM volume and DTI metrics (for a review see Brito and Noble, 2014), with greater SES, linked to larger overall WM volumes over ages 3–15 years (Luby et al., 2013), and higher education to greater fractional anisotropy in the superior longitudinal fasciculus and cingulum bundle over 17–23 years (Noble et al., 2013).
In contrast to the controls, SES did not correlate with brain volumes for children with PAE in the current study. As indicated, this finding corresponds with results reported by Uban et al. (2020) in their recent U.S. cohort of similarly aged children, lending further independent support to our results. Several possible explanations may account for this outcome. The lack of association could suggest that central nervous system structures were already altered by alcohol exposure before birth and that subsequent SES conditions did not mediate brain volume. For instance, in a cohort of 28 children with PAE and 56 controls, ages 6–17 years, Nardelli et al. (2011) found the largest relative reductions in total deep gray matter volumes for children with PAE vs. controls from a range of imaging volumes, raising the possibility that the attenuation of deep gray matter brain volume in children with PAE could be overwhelming any potential SES effects, as observed in specific subcortical structures for neurotypically developing children in the current study. Uban et al. (2020) similarly suggest that reduced neuroplasticity following PAE, in addition to increased susceptibility to stress, may result in attenuation of brain-SES associations frequently observed in neurotypically developing children. PAE has many potential mechanisms of injury on fetal brain development, including disruption and impairment of cellular energetics, glucose utilization and transport, the timing of cell acquisition/dysregulation, gene expression, protein, and DNA synthesis, cell to cell interactions, growth factor signaling, or cell death, in addition to others (for reviews, see Goodlett et al., 2005; Young et al., 2014). A possible lack of association of brain volumes with SES could also be expected in the PAE population given that structural brain alterations are already seen in early neonates with PAE (Taylor et al., 2015; Donald et al., 2016). These prenatal PAE injuries could then extend throughout neurodevelopment in children and adolescents, as shown by MRI measures of cortical thickness and WM (Zhou et al., 2011; Treit et al., 2014).
Consistent with established literature, our results indicated that children with PAE performed substantially worse than neurotypically developing children across all areas of cognitive functioning assessed (Mattson et al., 2019; Uban et al., 2020). After accounting for multiple comparisons we did not find positive associations between SES and cognitive abilities including measures of executive functioning, attention and working memory, memory, mathematical/numerical ability, and word reading, for either typically developing children or children with PAE, though trends were apparent for indicators of executive functioning and math in controls. Among controls, this finding stands in contrast to an array of studies that generally demonstrate positive associations between SES and a variety of cognitive indicators (for reviews see Bradley and Corwyn, 2002; Hackman and Farah, 2009; Hackman et al., 2010; Farah, 2017). Examples include overall intellectual functioning (von Stumm and Plomin, 2015) executive functions (Ardila et al., 2005; Last et al., 2018), working memory (Engel et al., 2008; Evans and Schamberg, 2009; Evans and Fuller-Rowell, 2013), and mathematical achievement (Kobrosly et al., 2011), all being associated with SES in developmental studies. Our current findings may be the result of sampling, with our neurotypically developing subgroup being best characterized as a healthy group of children drawn largely from moderate to high socioeconomic backgrounds. As well, early vs. later childhood or adulthood socioeconomic disadvantage is more strongly associated with later cognitive achievement in neurotypically developing children, and this remains understudied in FASD (e.g., Duncan et al., 1998). As such, these findings should be interpreted in the context of future studies that take into consideration the need to assess more detailed information on child environment (e.g., adversities, other exposures, placement disruptions and care stability including shifts in SES) to best understand the impact of SES on cognitive development in children, particularly for those with PAE.
In the current study, several limitations render it premature to determine whether the absence of associations between current SES and brain volume can be conclusively interpreted. The suboptimal number of children with PAE from very low SES caregiving circumstances, coupled with fewer control children from low SES backgrounds, limits our ability to draw firm conclusions and suggests the need for further research in this vulnerable population. It warrants highlighting that there are practical challenges involved in enrolling children and families of low SES and complex disabilities into voluntary studies involving multiple visits and MRI scans. Future research should include appropriate recruitment and support strategies to ensure that research participation is accessible for a broad range of families.
The cross-sectional study also limits the ability to draw longitudinal and/or developmental conclusions about the degree of intra-individual change that could be accounted for as a result of environmental exposures or changes in SES over time. As well, we did not capture information about other relevant risk factors, including additional adverse environmental experiences or stressors, or other prenatal exposures such as drugs or cigarettes, nor could we control for additional potential covariates, such as ethnicity. As such, the current findings are best framed as exploratory and can be used to direct future methodological design and approaches to explore the impact of SES during sensitive developmental years for children with PAE.
Another important consideration centers on the nature of caregiving placement differences between our typically developing and PAE groups. Specifically, there is a greater likelihood that our assessment of current SES better reflects a stable environmental marker across development in controls given that most resided with their biological parents. This stands in contrast to the PAE group, where approximately 30% of children were living in foster care or another guardianship arrangement, with the majority (60%) living in adoptive families. This is common in PAE samples, and consistent with the Uban et al. (2020) cohort, where 74% of children with PAE were living in adoptive families compared to only 8% of control children. In our study, we did not have data concerning the stability or length of caregiving placements for participants in either group, serving as a further potential confound in any association between SES and brain volumes for children with PAE. However, Uban et al. (2020) were able to control for the length of placement specifically among adoptive families and found that most group-by-SES interactions remained significant across subcortical brain volumes. That said, there remains a clear need to consider the potential differential impact of SES on biological vs. adoptive families and other caregiving configurations in future studies.
The assessment of current vs. prenatal or early perinatal SES also warrants consideration. Several studies have assessed current SES using a variety of approaches (e.g., parent income in the last year, parental education, etc.), including the Uban et al. (2020) PAE cohort, as well as in older neurotypically developing children and adolescents, with several showing SES-brain volume associations (for a review see Brito and Noble, 2014). Cavanagh et al. (2013) also studied adults aged 36–65 years and found that both early life SES (e.g., childhood poverty, paternal social class, etc.) and current SES predicted cerebellar gray matter volume, with current SES adding significantly to predictive models that already considered early-life SES, further speaking to the importance of both current SES and early life environmental impacts. These findings suggest that our assessment of current SES is consistent with approaches commonly adopted in the relevant and rapidly unfolding literature, though, there remains a research gap comparing the relative impact of SES in early vs. later developmental periods, or from a longitudinal approach, using brain imaging.
Also, in the current study, although children with PAE who were living in higher SES families may have been provided better opportunity to access the essential nutrients, interventions, and broad environmental conditions for positive development (Ivanovic et al., 2002; Pechey and Monsivais, 2015; Ranjit et al., 2015), this may not have translated into associations with brain volume in these children for the overall sample. As such, the lack of association between SES with brain volumes in children with PAE could be explained by a variety of factors, including the substantial effect of PAE, the variability of time spent, number, and quality of caregiving placements, and other factors not measured in the current study (e.g., maternal education, variability in the level and timing of alcohol exposure during pregnancy, et cetera).
This study observed that a higher current SES caregiving environment was associated with larger hippocampus and amygdala volumes in neurotypically developing children and adolescents, but not in those with PAE. Findings are consistent with an established SES literature for neurotypically developing children, and a single recent study of children with PAE. Several explanations warrant consideration, including the possibility that lack of brain volume-SES associations in children with PAE could result if the initial PAE-related injury overwhelms postpartum brain development such that later SES does not play as substantial a role. However, additional research accounting for a more comprehensive assessment of developmental trajectories for SES, as well as other pre and postnatal experiences and exposures in PAE cohorts that span the full SES spectrum, is required to inform firm conclusions. The current findings contribute to a growing body of evidence characterizing the impact of PAE on structural and cognitive brain outcomes in the context of additional pre and postnatal adversities, including SES.
The studies involving human participants were reviewed and approved by the Human Research Ethics Boards at Queen's University, the University of Alberta, the Children's Hospital of Eastern Ontario, the University of Manitoba, and the University of British Columbia. Written informed consent to participate in this study was provided by the participants' legal guardian.
KM, DZ, GL, and CB: completed the literature review, performed statistical analyses, data analysis/interpretation, and manuscript drafting and editing. DZ and GL: performed image analysis and quality assessment. All authors: study concepts/study design, data acquisition, manuscript review and revision, editing, and approval of the final manuscript.
This work was supported by Kids Brain Health Network (formerly NeuroDevNet), Network of Centres of Excellence (NCE) and Women's and Children's Health Research Institute (WCHRI) for operating and training award (KM); Canada Research Chairs salary award (CB).
^ A revised set of Canadian Diagnostic Guidelines for FASD were released subsequent to data collection, resulting in changes to diagnostic terminology and criteria.
^ http://cbrain.mcgill.ca/
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnhum.2020.00223/full#supplementary-material.
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Yu, Q., Daugherty, A. M., Anderson, D. M., Nishimura, M., Brush, D., Hardwick, A., et al. (2018). Socioeconomic status and hippocampal volume in children and young adults. Dev. Sci. 21:e12561. doi: 10.1111/desc.12561
Zhou, D., Lebel, C., Lepage, C., Rasmussen, C., Evans, A., Wyper, K., et al. (2011). Developmental cortical thinning in fetal alcohol spectrum disorders. NeuroImage 58, 16–25. doi: 10.1016/j.neuroimage.2011.06.026
Zhou, D., Rasmussen, C., Pei, J., Andrew, G., Reynolds, J. N., and Beaulieu, C. (2018). Preserved cortical asymmetry despite thinner cortex in children and adolescents with prenatal alcohol exposure and associated conditions. Hum. Brain Mapp. 39, 72–88. doi: 10.1002/hbm.23818
Keywords: brain volume, development, fetal alcohol spectrum disorder (FASD), prenatal alcohol exposure (PAE), socioeconomic status (SES)
Citation: McLachlan K, Zhou D, Little G, Rasmussen C, Pei J, Andrew G, Reynolds JN and Beaulieu C (2020) Current Socioeconomic Status Correlates With Brain Volumes in Healthy Children and Adolescents but Not in Children With Prenatal Alcohol Exposure. Front. Hum. Neurosci. 14:223. doi: 10.3389/fnhum.2020.00223
Received: 20 December 2019; Accepted: 19 May 2020;
Published: 30 June 2020.
Tim J. Silk, Deakin University, Australia
Eileen M. Moore, San Diego State University, United States
Kelvin O. Lim, University of Minnesota Twin Cities, United States
Fleur Warton, University of Cape Town, South Africa
Copyright © 2020 McLachlan, Zhou, Little, Rasmussen, Pei, Andrew, Reynolds and Beaulieu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Kaitlyn McLachlan, kmclac02@uoguelph.ca


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Dallas Cowboys roster power rankings Week 13: A Giant step in the right direction
As the playoff picture becomes clearer, you can rely on these ten names to get the Cowboys in the postseason.
By Brandon_Loree@Brandoniswrite Dec 1, 2022, 11:00am CST
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Jerome Miron-USA TODAY Sports
The Dallas Cowboys' Thanksgiving game against the New York Giants was a full-course meal. The appetizer (the first half) was as bland and disappointing as a family member who brings soup on Turkey day. It's something you don't expect and you are looking for something more.
Then what everyone came for, the turkey and stuffing (the second half), was better than expected. Everything tastes great, and there are no annual arguments between your two cousins who can't get along. Dessert (Micah Parsons' two sacks) was just a little something special to put a bow on a great family holiday.
With over 42 million people in their homes watching the Cowboys with plates of food in front of them, here are the top ten players from Dallas' win over New York.
10. Damone Clark, LB
In the absence of Anthony Barr, Damone Clark has slid right in and continues to fly all over the field. In his fourth game of the season, Clark totaled a season-best seven tackles against the Giants.
For a player who is coming back from spinal fusion surgery, Clark shows no hesitancy when it comes to tackling. There might be a few reads where he looks out of sorts, but Clark looks like a different player from his game against the Chicago Bears. If Clark can keep showing coaches he belongs in the starting lineup, Barr might be on the bench for a while, even if he's healthy.
9. Jake Ferguson, TE
Jake Ferguson had the highlight of the game, hurdling a Giants defender for a huge gain. It wasn't the play of the game, but it shows fans what to expect if Dalton Schultz isn't back next season.
Ferguson was one of the four targets Dak Prescott threw to most, totaling three catches for 57 yards. The hurdle and athleticism are impressive, but what stands out more is averaging 19 yards per reception. Ferguson was known for his run blocking coming from Wisconsin, but if he can develop his receiving skills, he might develop into one of the top tight ends in the NFL.
8. Michael Gallup, WR
Michael Gallup continues to get better and better the further removed he is from his ACL injury. He finished the game with five catches for 63 yards, averaging 12.6 yards a catch.
Dak Prescott found the sure-handed receiver whenever he needed a play on third down. When the Cowboys needed a touchdown on their third drive of the game, Gallup made some sensational third-down grabs to keep the momentum moving. Not to mention his 25-yard catch where he was bulldozing people and showed off his strength.
7. Zack Martin, OG
Whenever the Cowboys play a defense with a dominant defensive tackle, I circle that matchup to see how ZackMartin performs against them. He didn't disappoint.
The rare holding call against Martin wasn't even a hold. It was just him beating Leonard Williams and both falling to the ground. Williams was matched up with Martin for most of the game and is one of the best defensive tackles in football. Martin neutralized him from the game and showed great strength in his pass sets and run blocking.
6. Leighton Vander Esch, LB
After the Green Bay Packers loss, Micah Parsons spoke to the media about how the defense would have to come together and fix the run defense. There's no better way to start seeing results than with the middle linebacker.
Leighton Vander Esch has found the fountain of youth two games in a row. He's had a good season overall, but limiting Dalvin Cook and Saquon Barkley to under 100 yards rushing is no small task. Not only does he now lead the team in tackles with 75, but he has missed just four tackles on the season, which is only 5.3 percent. That's the lowest of his career, according to PFF.
Mike McCarthy said a few weeks ago that he feels Dalton Schultz looks like the player he was before the knee injury against the Bengals. It certainly looked like it on Thanksgiving.
Schultz finished the night with four catches for 31 yards but had the Cowboys' two biggest touchdowns.
It started rocky for Dak Prescott with two interceptions in the first half, but he became lights out when the game needed to be put away. Prescott threw for 261 yards and two touchdowns, but his best throws of the night came when he was under pressure.
Prescott is known to be great against the blitz, but he was under much more pressure than he is used to seeing. The Giants' defense registered 23 total pressures, which is the most Prescott has seen all season, and it showed. His throws to CeeDee Lamb on the sideline and the touchdown throw to Dalton Schultz are reasons why he can be in the top-five quarterback conversation. If he can find a way to run a little more with his legs, then he will undoubtedly be in that category.
3. CeeDee Lamb, WR
The Cowboys' offense needs more explosive plays, but from other players besides CeeDee Lamb. There should be no debating that Lamb is Dallas' No. 1 receiver. Ever since Amari Cooper left, he's had big shoes to fill. It took a while to come around, but Lamb is becoming a dynamic playmaker for the Cowboys.
His one-handed catch was the best of the night, but his almost-touchdown was even better. Lamb had over 100 yards for the second time in three weeks and is now second in the NFC in receiving yards behind Justin Jefferson. Even if Odell Beckham Jr. comes to Dallas, Lamb will remain the team's No. 1 target.
2. Ezekiel Elliott, RB
One of Mike McCarthy's underrated traits as head coach is knowing the health of his team. When Ezekiel Elliott injured his knee against the Detroit Lions, McCarthy talked about how it's a 20-game season, and Elliott needed rest to be himself come Thanksgiving onward. McCarthy was right again.
After Elliott was able to rest for three weeks, he looked like his old self against the Giants. When the offense struggled in the first half, Elliott was the only one to bring some juice. He had his old burst back, and the touchdown run was reminiscent of his 2016 self. It was only fitting that the player who has "feed me" as his trademark had himself a game on turkey day.
Along with Elliott, the Lion, Micah Parsons, is another player that likes to be fed. In baseball, a team can only have true postseason success if they have a strong closer. The position doesn't exist in football, but Parsons has undoubtedly become that for the Cowboys.
After Dallas took the lead coming out of halftime to make it 14-13, New York's offense was looking to respond with points of their own. On second and five from the Giants' 41-yard line, Parsons breaks through for his first sack. That knocked the Giants back, and they turned the ball over on downs when they couldn't convert on fourth down.
His second sack of the game was more impressive going against left tackle Andrew Thomas, who's regarded as one of the best in the NFL. It looked like Thomas jumped early to try and defend Parsons, but it was no match for his speed. The Giants tried to go for it on fourth down again and couldn't convert. If he can be this dominant down the final six games of the season, Parsons should be able to run away with Defensive Player of the Year honors.
Dallas Cowboys vs. New York Giants, 2022 NFL Week 12
Grading the Cowboys Week 12 win over the New York Giants

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Malaria continues to kill hundreds of thousands of young children each year and is a significant risk for travelers and visitors in large areas of Africa, South America, and Asia. This session will review the risks of malaria, the clinical presentations of malaria, diagnostic methods, treatment options, and preventive interventions. This information will help participants protect themselves from malaria while also preventing and treating malaria in the populations they serve.
Dr. Jason O'Grady will be joining the speaker for this presentation.


Received 2018 July 24; Revised 2018 August 10; Accepted 2018 August 17.
The purpose of this study was to investigate the effects of wild ginseng pharmacopuncture on melanin production in B16/F10 murine melanoma cells.
To determine the effect of wild ginseng pharmacopuncture solution on B16/F10 cells, cytotoxicity was evaluated using the 3-(4,5-dimethylthiazol-2-yl)- 2,5-diphenyl-tetrazolium bromide (MTT) method. To observe B16/F10 cell growth, death, and morphological changes, Trypan blue solution was used. The Hosoi method was used to investigate the effect of wild ginseng pharmacopuncture solution on melanin production. The Martinez-Esparza method was used to investigate the effect of wild ginseng pharmacopuncture solution on tyrosinase activity. To determine the pathway involved in the melanogenesis in cells exposed to wild ginseng pharmacopuncture solution, a cell-free tyrosinase was used.
Following treatment with 200 μL of wild ginseng solution, the cell survival rate was 76.32 ± 2.45% which significantly decreased with higher concentrations (μL) of wild ginseng (up to 200 μL). When 100 μL of wild ginseng was used, the cell survival rate was 89.95 ± 2.07%. No morphological changes or abnormalities were observed in the B16/F10 murine melanoma cells as observed in the Trypan blue test. Melanin production was significantly reduced to 72.17 ± 3.74% at 100 μL. Using 100 μL of wild ginseng solution, tyrosinase activity was significantly decreased to 80.15 ± 1.05%. Wild ginseng pharmacopuncture solution reduced melanin production both directly and indirectly.
This study suggests that wild ginseng pharmacopuncture solution may be effective in inhibiting melanin production. Further studies are needed to determine safe and effective clinical applications.
Human skin color depends on the amount of melanin contained within each epidermal unit. Melanocytes function in association with keratinocytes and Langerhans cells. The functional units associated with melanocytes, keratinocytes, and Langerhans cells are called epidermal melanin units . Melanin is produced by a tyrosinase enzymatic reaction in melanocytes. The resulting melanin protects the skin from external stimuli, such as ultraviolet (UV) rays . Melanin causes pigmentation. This prevents photoaging caused by UV rays , however, the precursor of melanin promotes apoptosis and has a negative function in terms of cosmetic appearance [4,5]. Therefore, studies have been performed to investigate ways to prevent or reduce hyperpigmentation in the skin. Cosmetics and traditional Korean medicines containing hydroquinone, arbutin, kojic acid, vitamin C, and others are sold based on their effects on hyperpigmentation [6-8]. However, research is ongoing to discover raw materials that exhibit better properties for preventing hyperpigmentation effects. Recently, there have been studies published on the effects of Pueraria , Siberian Sibiricum , and Hyssopus officinalis  on melanogenesis.
Wild ginseng is grown naturally in the wild and is used to supplement energy in Korean medicine. It is a typical drug to treat physical decline, fatigue, and burnout . Wild ginseng has almost the same active ingredient composition as ginseng and high active ingredient content, so it exhibits excellent effects for symptom treatment .
Wild ginseng pharmacopuncture is a traditional Korean medication. The wild ginseng used for pharmacopuncture solution is extracted by distillation and injected directly into acupuncture points, pressure points, tender points, muscles, and blood vessels. It is an accepted acupuncture treatment in Korean medicine, and the acupuncture and medicinal effects of wild ginseng can be used in parallel .
In Korean medicine, hyperpigmentation is known to occur more in people with a lack of physiologically active substances, energy incompatibility, and emotional stress . Therefore, there has been research to reduce pigmentation mainly through treatment with herbal medicine [16-18]. In previous studies, the whitening effect using hominis placenta has been studied . To date there have been very few studies on the effects of wild ginseng pharmacopuncture solution on reducing dermal hyperpigmentation.
Therefore, we performed this study to investigate the effect of wild ginseng pharmacopuncture solution on potentially inhibiting hyperpigmentation of the skin, by measuring the changes in cell number, the amount of melanin, cell morphology, tyrosinase activity, and cell-free tyrosinase in B16/F10 murine melanoma cells.
Sanyangsansam wild ginseng pharmacopuncture solution was used in the experiments (Korean Pharmacopuncture Research Institute, Wonju, Korea).
B16/F10 murine melanoma cells (Korean Cell Line Bank) were cultured in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum and penicillin-streptomycin at 37°C, 5% CO2.
The B16/F10 melanoma cells were cultured at 37°C, 5% CO2 using serum-free DMEM medium. Cell viability was measured using Mosmann's method . 1 × 105 B16/F10 melanoma cells were placed in each well of a 96-well plate and cultured for 24 hours. The cells were treated with wild ginseng pharmacopuncture solution at different concentrations (μL) and cultured for 72 hours. After incubation, 0.05% 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) solution was added and cultured at 37°C for 2 hours. The supernatant was removed, 1 mL of dimethyl sulfoxide (DMSO) was added to the formazan precipitate, and it was allowed to stand at room temperature for approximately 15 minutes. The absorbance was measured at a wavelength of 540 nm, and cell viability was calculated.
B16/F10 melanoma cells were cultivated at 5 × 105/well in a 6-well plate. Cells were cultured for 24 hours at 37°C, 5% CO2. Cells were separated from each well using trypsin. The separated cells were washed twice with phosphate-buffered saline (PBS). A total of 2 mL of 0.4% (w/v) trypan blue solution was added to each well. A hemocytometer was used to count the number of living cells (cells without trypan blue staining are living).
The amount of melanin was measured by applying the Hosoi  method. The cultured cells were centrifuged at 5,000x g, for 5 minutes. A total of 200 μL of 1 N NaOH solution was added, to which 10% DMSO was also added. Following 1 hour at 80°C the absorbance was measured at 405 nm. The amount of melanin contained in the sample was calculated using a melanin standard curve.
The tyrosinase activity was measured by the Martinez-Esparza  method. The cells in each well were centrifuged (5,000x g, 5 minutes) to precipitate the cells. A total of 100 mL of lysis buffer was added to the cell pellet and placed in ice. The supernatant was separated by centrifugation (5,000x g, 5 minutes) again. A total of 100 mL of 100 mM sodium phosphate was added to 100 μL of the sample. It was reacted at 37°C for 5 minutes. A total of 50 μL of 100 mM catechol solution was added. Absorbance was measured at 405 nm.
The tyrosinase activity was determined by measuring the absorbance at 475 nm using 3,4 Dihydroxy-L-phehylalanine (L-DOPA) as a substrate. A total of 160 μL of 0.1 mM potassium phosphate buffer and 20 μL of 0.01% L-DOPA were added, and 10 μL of each sample and enzyme solution (mushroom tyrosinase) were added, followed by reaction at 37°C for 1 hour. After the reaction, the absorbance at 475 nm was measured and the tyrosinase activity was calculated as a percentage based on the absorbance of the control group.
The results were expressed using averages ± SD with the SPSS Windows program (Ver. 21.0). Statistical significance was confirmed using the Student's t test. The level of significance was p < 0.05.
Cells were treated with varying concentrations of 0, 10, 20, 50, 100, and 200 μL/mL of cell suspension to determine the optimum treatment concentration (μL) of wild ginseng pharmacopuncture solution on B16/F10 melanoma cells. After 72 hours, cell viability was examined by MTT assay. The cell viabilities were 100.00 ± 0.14%, 98.49 ± 1.75%, 97.87 ± 1.84%, 94.29 ± 1.93%, 89.95 ± 2.07%, and 76.32 ± 2.45% of the negative control at the wild ginseng pharmacopuncture solution concentrations of 0, 10, 20, 50, 100, and 200 μL/mL of cell suspension, respectively.
The MTT assay showed a significant decrease in cell viability using 200 μL wild ginseng pharmacopuncture solution/mL of cell culture (Fig. 1).
Effect of wild ginseng pharmacopuncture solution on cell viability.
The cell cytotoxicity of the B16/F10 murine melanoma cells was measured by MTT assay. Results were expressed as % of untreated control. *p < 0.05.
Trypan blue uptake was used to examine the number of living and dead cells. With higher concentrations of wild ginseng the number of living cells decreased significantly. The cell viabilities were 100.00 ± 0.22%, 98.14 ± 2.16%, 95.17 ± 1.78%, 91.67 ± 2.97%, 89.74 ± 1.74%, and 84.11 ± 3.78% at the wild ginseng pharmacopuncture solution concentrations of 0, 10, 20, 50, 100, and 200 μL/mL, respectively. The number of viable cells decreased in a dose-dependent manner. These results showed similar results to the MTT measurements. The morphological abnormality of the cells was not examined (Fig. 2).
Effect of wild ginseng pharmacopuncture solution on cell viability by trypan blue test.
The cell viability of the B16/F10 murine melanoma cells was measured by trypan blue test. Results were expressed as % of untreated control. *p < 0.05.
To investigate the effect of wild ginseng pharmacopuncture solution on the melanin synthesis in B16/F10 melanoma cells, the total melanin levels were measured after culturing wild ginseng at 0, 10, 20, 50, and 100 μL/mL for 3 days. The results showed that melanin production in B16/F10 melanoma cells after treatment with wild ginseng pharmacopuncture solution was 100.00 ± 0.59%, 92.44 ± 2.72%, 90.26 ± 3.17%, 87.47 ± 4.91%, and 72.17 ± 3.74% compared with the negative untreated control cells after treatment with 0, 10, 20, 50, and 100 μL/mL of wild ginseng pharmacopuncture solution, respectively. Wild ginseng pharmacopuncture solution significantly decreased melanin synthesis at 100 μL/mL (Fig. 3).
Effect of wild ginseng pharmacopuncture solution on melanin content.
The melanin content of the B16/F10 murine melanoma cells was measured by Hosoi method. Results were expressed as % of untreated control containing no ginseng pharmacopuncture solution. **p < 0.01.
The effect of wild ginseng pharmacopuncture solution on the tyrosinase activity in B16/F10 melanoma cells was 100.00 ± 0.57%, 95.11 ± 3.69%, 91.84 ± 1.95%, 89.65 ± 2.74%, and 80.15 ± 1.05% compared with the untreated control cells treated with 0, 10, 20, 50, and 100 μL/mL wild ginseng pharmacopuncture solution, respectively. Wild ginseng pharmacopuncture solution significant decreased tyrosinase activity at 100 μL/mL (Fig. 4).
Effect of wild ginseng pharmacopuncture solution on cell tyrosinase activity.
The Tyrosinase activity of the B16/F10 murine melanoma cells was measured by Martines Esparza method. Results were expressed as % of untreated control. *p < 0.05.
The inhibition of tyrosinase activity by mushroom tyrosinase can be regulated by controlling the oxidation and reduction of tyrosinase by changing the state of copper ions at an active tyrosinase site. Therefore, the inhibition of in vitro tyrosinase activity by mushroom tyrosinase provides a useful experimental assessment. The effect of wild ginseng pharmacopuncture solution on the tyrosinase activity of B16/F10 melanoma cells was 100.00 ± 2.81%, 98.16 ± 1.26%, 97.12 ± 2.18%, 83.15 ± 2.75%, and 92.66 ± 3.17% compared with untreated controls when incubated with 0, 10, 20, 50, and 100 μL/mL of wild ginseng pharmacopuncture solution, respectively. However, these results were not statistically significant. In this experiment, the direct tyrosinase-inhibitory effect of wild ginseng pharmacopuncture solution was tested using mushroom tyrosinase. As a result, wild ginseng pharmacopuncture solution directly inhibited concentration-dependent activity of the mushroom tyrosinase enzyme (Fig. 5).
Effect of wild ginseng pharmacopuncture solution on cell free tyrosinase activity.
The Tyrosinase activity on cell free was measured by Mushroom tyrosinase. Results were expressed as % of control.
Melanin, hemoglobin, and carotene are the 3 factors that determine skin color. The most important of these is melanin. The main function of melanin is removing reactive oxygen species or free radicals from the skin, and protecting skin by blocking UV transmission .
Melanin is a polymeric substance of phenols released by melanocytes, which are distributed in the skin, hair follicles, eyes, ears, and cerebrum in the human body. Melanin cells, fibroblasts, keratinocytes, and inflammatory cells are activated due to external stresses such as UV rays, and pigmentation is controlled by prostaglandin, various cytokines, and changes in α-Melanocyte-stimulating hormone (α-MSH). In particular, several factors, such as α-MSH, adrenocorticotropic hormone, and β-endorphin secreted from keratinocytes, affect melanocyte growth, morphology, and differentiation. Ultimately, melanin is transmitted to keratinocytes through dendrites, thereby inhibiting cytotoxicity from the cells .
Tyrosinase is an important enzyme in the melanin synthesis process. It is involved in the oxidation of tyrosine, an in vivo amino acid, to L-DOPA. In eumelanogenesis, which produces brownish eumelanin, DOPA quinone is converted to DOPA chrome, and DOPA chrome becomes 5,6- di hydroxy indole-2-carboxylic acid (DHICA) due to tyrosinase-related protein-2, and DHICA eumelanin due to tyrosinase-related protein-1. On the other hand, DOPA chrome is converted to indole-5, 6-quinone by tyrosinase oxidase and DHI eumelanin is finally produced by reduction and decarboxylation. When the concentrations of sulfur-containing amino acids, such as cysteine and glutathione, are high, DOPA quinone forms cysteinyl DOPA and is converted into pheomelanin after several transitions. In general, melanin refers to the eumelanin produced by eumelanogenesis. Melanin produced from the melanin body is transferred to the keratinized cells of the epidermis through the dendritic processes and transferred to the surface by turn-over and eventually separated and eliminated .
Skin color and pigmentation are determined by the amount and distribution of melanin in keratinocytes. It is important to inhibit the production of melanin by inhibiting tyrosinase activity. To date, known inhibitors of tyrosinase activity include hydroquinone, kojic acid, and arbutin. They inhibit tyrosine oxidation and melanin production, including vitamin C and glutathione. In addition, salicylic acid has the effect of promoting the removal of the stratum corneum. Research studies on the effects of retinoic acid, alpha hydroxy acid, UV barrier material, cytotoxic inhibition, and active oxygen removal have been performed [6-8].
In this study, we first examined the cell viability following exposure to wild ginseng pharmacopuncture solution and found that the cell viability was reduced to 76.32% up to concentrations of 200 μL/mL. These results show similar trends to the trypan blue measurements. There was also statistically significant cell loss at the 200 μL/mL concentration in the trypan test.
Wild ginseng pharmacopuncture solution reduced tyrosinase activity to 89.65% and 80.15% at concentrations of 50 and 100 μL/mL, respectively. Thus, wild ginseng pharmacopuncture solution concentration decreased tyrosinase activity in B16/F10 melanoma cells. In the total melanin test, melanin synthesis was reduced to 87.47% and 72.17% compared with the control group at 50 and 100 μL/mL, respectively, which was similar to that of tyrosinase activity. In previous experiments, tyrosinase activity and total melanin level was very closely related .
To examine whether wild ginseng pharmacopuncture solution directly inhibits tyrosinase activity, the key enzyme of melanogenesis, mushroom tyrosinase was not directly inhibited by mushroom tyrosinase enzyme activity in a cell-free system. As a result, it was found that wild ginseng pharmacopuncture solution also inhibits tyrosinase activity directly through the signal transduction pathway of B16/F10 melanoma cells.
In conclusion, it was found that wild ginseng pharmacopuncture solution inhibits melanin production in B16/F10 melanoma cells and may play a role in as a drug substance for the treatment of skin blemishes and freckles, and for cosmetic skin whitening. Further research should be conducted to investigate its possibility for stable and efficient clinical use.
1. The cell viability of wild ginseng pharmacopuncture solution was decreased to 76% at a concentration of 200 μL/mL.
2. Wild ginseng pharmacopuncture solution did not cause morphological changes in the B16/F10 cells.
3. Wild ginseng pharmacopuncture solution resulted in a statistically significant decrease in the total amount of melanin produced in the B16/F10 cells at 100 μL/mLmL.
4. Wild ginseng pharmacopuncture solution produced a statistically significant decrease in tyrosinase activity in the B16/F10 cells at 100 μL/mL.
6. Wild ginseng pharmacopuncture solution directly and indirectly inhibited the activity of the mushroom tyrosinase enzyme. Direct inhibition pathways were statistically significant.
7. Wild ginseng pharmacopuncture solution may reduce melanin synthesis by inhibiting the tyrosinase biosynthesis of melanocytes, thus decreasing the expression of tyrosinase which is involved in melanin production.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP; Ministry of Science, ICT & Future Planning) (No. NRF-2017R1C1B5017799).
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9. Moon JS, Lee JH, Kim YB. Study of antioxidation activity and melanocyte effect of Pueraria Lobata Root Extract. J Korean Oil Chem Soc 2017;34:418–425. [in Korean].
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13. Jeong HS, Lim CS, Cha BC, Choi SH, Kwon KR. Component analysis of cultivated ginseng, cultivated wild ginseng, and wild ginseng and the change of ginsenoside components in the process of red ginseng. J Korean Pharmacopuncture Institute 2010;13:63–77. [in Korean].
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 Wedding in Provence, organize your wedding in the most beautiful venues of Provence.
Plan your wedding in Provence is above all choosing a magical landscape and a different atmosphere.
A sunny region, with soft colors and varied landscapes.
The perfect area to enjoy the long summer nights and a wedding dinner under the stars.
We are both born in Provence and we will guide you through the most beautiful places of reception of the area.
Your wedding planner will organize for you a discovery tour allowing you to travel with pleasure and serenity and discover the best wedding venues of the region.
You will be able to project in real condition and start to visualize the day of your wedding.
Getting married in Provence, it's may be to choose a wedding decoration with local colors.
Lavender, its deep color and its unmistakable smell.
It will sublimate your bridal bouquet or become the perfect gift for your guests.
The olive tree, a symbol of peace and love, its perfect green, neither too bright nor too bland.
In all its forms, it will bring elegance to your wedding decoration.
Olive leaves at the end of ceremony, a vial of olive oil on the table or a touch on your wedding table.
Noble and local products that will sublimate the decoration of your wedding.
For more information, do not hesitate to contact us, we will answer you as soon as possible.
Sea, Bride and Sun is first of all a girly duo passionate about love and beautiful encounters.
Two complementary personalities, eager to organize for you and with you one of the most beautiful day of your life.
We organize tailor-made weddings according to your desires and personalities, wherever you want!
The south of France is our favorite playground, but it is also in Portugal and Majorca that we have established our offices to organize your events.
All in a relaxed, benevolent and professional atmosphere where rigor and pleasure coexist daily.
Because our job is above all in our ability to make you happy.
Entrust us your precious day and embraque with us for the sun!