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Kinematic analysis is a useful and widespread tool used in research and clinical biomechanics for the quantification of human movement. Common marker-based optical motion capture systems are time intensive and require highly trained operators to obtain kinematic data. Markerless motion capture systems offer an alternative method for the measurement of kinematic data with several practical benefits. This work compared the kinematics of human gait measured using a deep learning algorithm-based markerless motion capture system to those from a standard marker-based motion capture system. Thirty healthy adult participants walked on a treadmill while data were simultaneously recorded using eight video cameras and seven infrared optical motion capture cameras, providing synchronized markerless and marker-based data for comparison. The average root mean square distance (RMSD) between corresponding joint centers was less than 2.5 cm for all joints except the hip, which was 3.6 cm. Lower limb segment angles relative to the global coordinate system indicated the global segment pose estimates from both systems were very similar, with RMSD of less than 5.5° for all segment angles except those that represent rotations about the long axis of the segment. Lower limb joint angles captured similar patterns for flexion/extension at all joints, ab/adduction at the knee and hip, and toe-in/toe-out at the ankle. These findings indicate that the markerless system would be a suitable alternative technology in cases where the practical benefits of markerless data collection are preferred.

Abstract Kinematic analysis is a useful and widespread tool used in research and clinical biomechanics for the estimation of human pose and the quantification of human movement. Common marker-based optical motion capture systems are expensive, time intensive, and require highly trained operators to obtain kinematic data. Markerless motion capture systems offer an alternative method for the measurement of kinematic data with several practical benefits. This work compared the kinematics of human gait measured using a deep learning algorithm-based markerless motion capture system to those of a common marker-based motion capture system. Thirty healthy adult participants walked on a treadmill while data were simultaneously recorded using eight video cameras (markerless) and seven infrared optical motion capture cameras (marker-based). Video data were processed using markerless motion capture software, marker-based data were processed using marker-based capture software, and both sets of data were compared. The average root mean square distance (RMSD) between corresponding joints was less than 3 cm for all joints except the hip, which was 4.1 cm. Lower limb segment angles indicated pose estimates from both systems were very similar, with RMSD of less than 6° for all segment angles except those that represent rotations about the long axis of the segment. Lower limb joint angles captured similar patterns for flexion/extension at all joints, ab/adduction at the knee and hip, and toe-in/toe-out at the ankle. These findings demonstrate markerless motion capture can measure similar 3D kinematics to those from marker-based systems. Competing Interest Statement WSS is the President of Theia Markerless Inc. (Kingston, Ontario), the developers of Theia3D. He contributed to the conception and design of the study, critically revised the article for intellectual content, and provided final approval of the submitted version. WSS was not involved with the collection, analysis, or interpretation of data.

The volumetric quantification of brain structures is of great interest in pediatric populations because it allows the investigation of different factors influencing neurodevelopment. FreeSurfer and FSL both provide frequently used packages for automatic segmentation of brain structures. In this study, we examined the accuracy and consistency of those two automated protocols relative to manual segmentation, commonly considered as the “gold standard” technique, for estimating hippocampus and amygdala volumes in a sample of preadolescent children aged between 6 to 11years. The volumes obtained with FreeSurfer and FSL-FIRST were evaluated and compared with manual segmentations with respect to volume difference, spatial agreement and between- and within-method correlations. Results highlighted a tendency for both automated techniques to overestimate hippocampus and amygdala volumes, in comparison to manual segmentation. This was more pronounced when using FreeSurfer than FSL-FIRST and, for both techniques, the overestimation was more marked for the amygdala than the hippocampus. Pearson correlations support moderate associations between manual tracing and FreeSurfer for hippocampus (right r=0.69, p<0.001; left r=0.77, p<0.001) and amygdala (right r=0.61, p<0.001; left r=0.67, p<0.001) volumes. Correlation coefficients between manual segmentation and FSL-FIRST were statistically significant (right hippocampus r=0.59, p<0.001; left hippocampus r=0.51, p<0.001; right amygdala r=0.35, p<0.001; left amygdala r=0.31, p<0.001) but were significantly weaker, for all investigated structures. When computing intraclass correlation coefficients between manual tracing and automatic segmentation, all comparisons, except for left hippocampus volume estimated with FreeSurfer, failed to reach 0.70. When looking at each method separately, correlations between left and right hemispheric volumes showed strong associations between bilateral hippocampus and bilateral amygdala volumes when assessed using manual segmentation or FreeSurfer. These correlations were significantly weaker when volumes were assessed with FSL-FIRST. Finally, Bland–Altman plots suggest that the difference between manual and automatic segmentation might be influenced by the volume of the structure, because smaller volumes were associated with larger volume differences between techniques. These results demonstrate that, at least in a pediatric population, the agreement between amygdala and hippocampus volumes obtained with automated FSL-FIRST and FreeSurfer protocols and those obtained with manual segmentation is not strong. Visual inspection by an informed individual and, if necessary, manual correction of automated segmentation outputs are important to ensure validity of volumetric results and interpretation of related findings. •In a pediatric sample, we compare hippocampus and amygdala volumes from FSL-FIRST and FreeSurfer to manual segmentation•We examine discrepancies, associations, and biases between automatic and manual segmentation volumes•In the studied pediatric population, the agreement between manual segmentation, FreeSurfer and FSL is questionable•Associations between manual segmentation and FreeSurfer were stronger than with FSL-FIRST•Associations between manual segmentation and automatic techniques were stronger for hippocampus than amygdala volumes

Background/Aims: Accumulating evidence from a relatively small number of prospective studies indicates that exposure to prenatal stress profoundly influences the developing human fetus with consequences that persist into childhood and very likely forever. Methods: Maternal/fetal dyads are assessed at ∼20, ∼25, ∼31 and ∼36 weeks of gestation. Infant assessments begin 24 h after delivery with the collection of cortisol and behavioral responses to the painful stress of the heel-stick procedure and measures of neonatal neuromuscular maturity. Infant cognitive, neuromotor development, stress and emotional regulation are evaluated at 3, 6 12 and 24 months of age. Maternal psychosocial stress and demographic information is collected in parallel with infant assessments. Child neurodevelopment is assessed with cognitive tests, measures of adjustment and brain imaging between 5 and 8 years of age. Results:Psychobiological markers of stress during pregnancy, especially early in gestation, result in delayed fetal maturation, disrupted emotional regulation and impaired cognitive performance during infancy and decreased brain volume in areas associated with learning and memory in 6- to 8-year-old children. We review findings from our projects that maternal endocrine alterations that accompany pregnancy and influence fetal/infant/child development are associated with decreased affective responses to stress, altered memory function and increased risk for postpartum depression. Conclusions: Our findings indicate that the mother and her fetus both are influenced by exposure to psychosocial and biological stress. The findings that fetal and maternal programming occur in parallel may have important implications for long-term child development and mother/child interactions.

Pregnancy is a time of increased vulnerability to psychopathology, yet limited work has investigated the extent to which variation in psychopathology during pregnancy is shared and unshared across syndromes and symptoms. Understanding the structure of psychopathology during pregnancy, including associations with childhood experiences, may elucidate risk and resilience factors that are transdiagnostic and/or specific to particular psychopathology phenotypes. Participants were 292 pregnant individuals assessed using multiple measures of psychopathology. Confirmatory factor analyses found evidence for a structure of psychopathology consistent with the Hierarchical Taxonomy of Psychopathology (HiTOP). A common transdiagnostic factor accounted for most variation in psychopathology, and both adverse and benevolent childhood experiences (ACEs and BCEs) were associated with this transdiagnostic factor. Furthermore, pregnancy-specific anxiety symptoms most closely reflected the dimension of Fear, which may suggest shared variation with manifestations of fear that are not pregnancy-specific. ACEs and BCEs also linked to specific prenatal psychopathology involving thought problems, detachment, and internalizing, externalizing, antagonistic, and antisocial behavior. These findings extend the dimensional and hierarchical HiTOP model to pregnant individuals and show how maternal childhood risk and resilience factors relate to common and specific forms of psychopathology during pregnancy as a period of enhanced vulnerability.

The developmental origins of psychopathology begin before birth and perhaps even prior to conception. Understanding the intergenerational transmission of psychopathological risk is critical to identify sensitive windows for prevention and early intervention. Prior research demonstrates that maternal trauma history, typically assessed retrospectively, has adverse consequences for child socioemotional development. However, very few prospective studies of preconception trauma exist, and the role of preconception symptoms of posttraumatic stress disorder (PTSD) remains unknown. The current study prospectively evaluates whether maternal preconception PTSD symptoms predict early childhood negative affectivity, a key dimension of temperament and predictor of later psychopathology. One hundred and eighteen women were recruited following a birth and prior to conception of the study child and were followed until the study child was 3–5 years old. Higher maternal PTSD symptoms prior to conception predicted greater child negative affectivity, adjusting for concurrent maternal depressive symptoms and sociodemographic covariates. In exploratory analyses, we found that neither maternal prenatal nor postpartum depressive symptoms or perceived stress mediated this association. These findings add to a limited prospective literature, highlighting the importance of assessing the mental health of women prior to conception and providing interventions that can disrupt the intergenerational sequelae of trauma.

Maternal depression is one of the most common prenatal complications, and prenatal maternal depression predicts many child psychopathologies. Here, we apply the fetal programming hypothesis as an organizational framework to address the possibility that fetal exposure to maternal depressive symptoms during pregnancy affects fetal development of vulnerabilities and risk mechanisms, which enhance risk for subsequent psychopathology. We consider four candidate pathways through which maternal prenatal depression may affect the propensity of offspring to develop later psychopathology across the life span: brain development, physiological stress regulation (hypothalamic–pituitary–adrenocortical axis), negative emotionality, and cognitive (effortful) control. The majority of past research has been correlational, so potential causal conclusions have been limited. We describe an ongoing experimental test of the fetal programming influence of prenatal maternal depressive symptoms using a randomized controlled trial design. In this randomized controlled trial, interpersonal psychotherapy is compared to enhanced usual care among distressed pregnant women to evaluate whether reducing prenatal maternal depressive symptoms has a salutary impact on child ontogenetic vulnerabilities and thereby reduces offspring's risk for emergence of later psychopathology.

Prenatal maternal stress predicts subsequent elevations in youth depressive symptoms, but the neural processes associated with these links are unclear. This study evaluated whether prenatal maternal stress is associated with child brain development, and adolescent depressive symptoms using a prospective design with 74 mother child pairs (40 boys). Maternal stress was assessed during pregnancy, child cortical thickness at age 7, and depressive symptoms at age 12. Prenatal maternal stress was associated with less cortical thickness primarily in frontal and temporal regions and with elevated depressive symptoms; child cortical thickness additionally correlated with adolescent depressive symptoms. The observed associations are consistent with the possibility that cortical thickness in superior frontal regions links associations between prenatal maternal stress and adolescent depressive symptoms.

Increasing evidence indicates that, in addition to poverty, maternal depression, and other well-established factors, unpredictability of maternal and environmental signals early in life influences trajectories of brain development, determining risk for subsequent mental illness. However, whereas most risk factors for later vulnerability to mental illness are readily measured using existing, clinically available tools, there are no similar measures for assessing early-life unpredictability. Here we validate the Questionnaire of Unpredictability in Childhood (QUIC) and examine its associations with mental health in the context of other indicators of childhood adversity (e.g., traumatic life events, socioeconomic status, and parenting quality). The QUIC was initially validated through administration to a cohort of adult females (N = 116) and then further refined in two additional independent cohorts (male Veterans, N = 95, and male and female adolescents, N = 175). The QUIC demonstrated excellent internal (α = 0.89) and test–retest reliability (r = 92). Scores on the QUIC were positively correlated with other prospective indicators of exposures to unpredictable maternal inputs in infancy and childhood (unpredictable maternal mood and sensory signals), and accuracy of recall also was confirmed with prospective data. Importantly, the QUIC predicted symptoms of anxiety, depression, and anhedonia in the three study cohorts, and these effects persisted after adjusting for other previously established risk factors. The QUIC, a reliable and valid self-report assessment of exposure to unpredictability in the social, emotional, and physical domains during early life, is a brief, comprehensive, and promising instrument for predicting risk for mental illness.

Preconception and prenatal stress impact fetal and infant development, and women of color are disproportionately exposed to sociocultural stressors like discrimination and acculturative stress. However, few studies examine links between mothers’ exposure to these stressors and offspring mental health, or possible mitigating factors. Using linear regression, we tested associations between prenatally assessed maternal acculturative stress and discrimination on infant negative emotionality among 113 Latinx/Hispanic, Asian American, Black, and Multiethnic mothers and their children. Additionally, we tested interactions between stressors and potential pre- and postnatal resilience-promoting factors: community cohesion, social support, communalism, and parenting self-efficacy. Discrimination and acculturative stress were related to more infant negative emotionality at approximately 12 months old ( M = 12.6, SD = .75). In contrast, maternal report of parenting self-efficacy when infants were 6 months old was related to lower levels of infant negative emotionality. Further, higher levels of parenting self-efficacy mitigated the relation between acculturative stress and negative emotionality. Preconception and prenatal exposure to sociocultural stress may be a risk factor for poor offspring mental health. Maternal and child health researchers, policymakers, and practitioners should prioritize further understanding these relations, reducing exposure to sociocultural stressors, and promoting resilience.