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Children from lower socioeconomic status (SES) families are at increased risk for anxiety problems, though knowledge of the pathways by which SES predicts children's anxiety outcomes remains scant. Limited work suggests SES as a moderator of links between early development and anxiety outcomes but has not used a longitudinal framework or a multimethod approach. In this preregistered study, SES was tested as a simultaneous moderator of putatively biologically (error-related negativity [ERN]) and contextually (authoritarian parenting) based pathways of anxiety risk from ages 3 (

Islet autoantibodies can be detected prior to the onset of type 1 diabetes and are important tools for aetiologic studies, prevention trials and disease screening. Current risk stratification models rely on the positivity status of islet autoantibodies alone, but additional autoantibody characteristics may be important for understanding disease onset. This work aimed to determine if a data-driven model incorporating characteristics of islet autoantibody development, including timing, type and titre, could stratify risk for type 1 diabetes onset.Data on autoantibodies against GAD (GADA), tyrosine phosphatase islet antigen-2 (IA-2A) and insulin (IAA) were obtained for 1,415 children enrolled in The Environmental Determinants of Diabetes in the Young study with at least one positive autoantibody measurement from years 1 to 12 of life. Unsupervised machine learning algorithms were trained to identify clusters of autoantibody development based on islet autoantibody timing, type and titre. Risk for type 1 diabetes across each identified cluster was evaluated using time-to-event analysis.We identified 2-4 clusters in each year cohort that differed by autoantibody timing, titre and type. During the first 3 years of life, risk for type 1 diabetes onset was driven by membership in clusters with high titres of all three autoantibodies (1-year risk: 20.87-56.25%, 5-year risk: 67.73-69.19%). Type 1 diabetes risk transitioned to type-specific titres during ages 4 to 8, as clusters with high titres of IA-2A (1-year risk: 20.88-28.93%, 5-year risk: 62.73-78.78%) showed faster progression to diabetes compared with high titres of GADA (1-year risk: 4.38-6.11%, 5-year risk: 25.06-31.44%). The importance of high GADA titres decreased during ages 9 to 12, with clusters containing high titres of IA-2A alone (1-year risk: 14.82-30.93%) or both GADA and IA-2A (1-year risk: 8.27-25.00%) demonstrating increased risk.This unsupervised machine learning approach provides a novel tool for stratifying risk for type 1 diabetes onset using multiple autoantibody characteristics. These findings suggest that age-dependent changes in IA-2A titres modulate risk for type 1 diabetes onset across 12 years of life. Overall, this work supports incorporation of islet autoantibody timing, type and titre in risk stratification models for aetiologic studies, prevention trials and disease screening.

Sexual violence and relationship abuse are prevalent among adolescents and programs promoting gender equity, reproductive justice, and healthy relationships are key strategies for prevention. While such "gender transformative" approaches appear promising for boys, they have not been evaluated among girls. This study assessed the feasibility of this community-based program, called Sisterhood 2.0, among girls in socially disadvantaged urban neighborhoods in Pittsburgh, Pennsylvania.This quasi-experimental trial examined feasibility of Sisterhood 2.0 (n = 246), delivered through 8 weekly sessions, assessed through attendance, retention and satisfaction. Participants completed surveys at baseline and end of program assessing other relevant measures. Generalized linear mixed models estimated changes from baseline to follow up comparing intervention to control participants.Eleven neighborhoods were assigned to Sisterhood 2.0 (n = 5 neighborhoods) or job-readiness training (n = 6 neighborhoods). Girls were between the ages of 13 and 19, 8-10th graders (59%), and self-identified as Black (69%). Participants most often attended because they thought the program would be interesting (74%) and returned because of the women teaching the program (71%). Girls reported experiences with physical adolescent relationship abuse (ARA) (30% in both arms), emotional ARA (66% intervention; 56% control), or sexual ARA (11% intervention; 12% control). Physical ARA perpetration was high in both arms (intervention: 47%; control: 46%). Significant intervention effects were observed in recognition of abuse (β = 0.41, 95% confidence interval 0.03-0.78). No other significant intervention effects were observed.Community-based gender-transformative programming for girls is feasible and may be a promising approach for addressing interpersonal violence and promoting sexual health.

PURPOSE: Assess the effects of stay-at-home orders on access to services utilized by families of children with disabilities (CWD). METHODS: Cross-sectional weekly surveys were fielded over four weeks, during which western Pennsylvania was under stay-at-home orders. Respondents were divided into families of CWD (N = 233) or without CWD (N = 1582). Survey questions included measures of socio-economic status, and families of CWD answered questions regarding access to services pre and post-initiation of stay-at-home orders. Differences between families with and without CWD were analyzed using chi-square tests. RESULTS: Among families of CWD that had used services previously, 76.6% of survey respondents stated that they had decreased access, with the greatest percentage experiencing loss among those previously utilizing early intervention (75.5%), outpatient therapies (69.1%), or school-based therapies (80.7%). Compared to families without CWD, families of CWD were more likely to report lower pre-COVID-19 annual incomes (p

Context Pediatric obesity is a serious health problem in the United States. While lifestyle modification therapy with dietary changes and increased physical activity are integral for the prevention and treatment of mild to moderate obesity in youth, only a modest effect on sustained weight reduction is observed in children and young adults with severe obesity. This underscores the need for additional evidence-based interventions for children and adolescents with severe obesity, including pharmacotherapy, before considering invasive procedures such as bariatric surgery. Evidence Acquisition This publication focuses on recent advances in pharmacotherapy of obesity with an emphasis on medications approved for common and rarer monogenic forms of pediatric obesity. Evidence Synthesis We review medications currently available in the United States, both those approved for weight reduction in children and “off-label” medications that have a broad safety margin. Conclusion It is intended that this review will provide guidance for practicing clinicians and will encourage future exploration for successful pharmacotherapy and other interventions for obesity in youth.

Despite widespread acceptance that prenatal symptoms of depression in mothers are detrimental to infants' long-term emotional and cognitive development, little is known about the mechanisms that may integrate outcomes across these domains. Rooted in the integrative perspective that emotional development is grounded in developing cognitive processes, we hypothesized that prenatal symptoms of depression in mothers would be associated with delays in neural maturation that support sociocognitive function in infants, leading to more problematic behaviors. We used a prospective longitudinal study of mothers (N = 92) and their infants to test whether self-reported symptoms of depression in mothers during the second and third trimesters were associated with neural development and infant outcomes at 4 months of age. While controlling for postpartum symptoms of depression, more prenatal symptoms of depression in mothers predicted less neural maturation in the parietal region of 4-month-old infants. Less neural maturation, in turn, was associated with greater infant negativity, suggesting neural maturation as a putative mechanism linking maternal symptoms of depression with infant outcomes. Differences in neural regions and developmental timing are also discussed.

A negative breastfeeding experience is a contextual risk factor for the development of postpartum depressive symptoms among mothers. Many current interventions targeted at disrupting this association rely on the ability to make breastfeeding experiences positive. As a beginning step toward identifying alternative approaches, we investigated a potential psychological buffer of the negative relation between breastfeeding experience and symptoms of postpartum depression: feeling authentic in one's role as a parent. Authenticity appears to enhance well-being and buffer negative outcomes more generally, but has largely gone unaddressed in mothers, particularly during the critical peripartum period when depressive symptoms are at increased prevalence. We tested whether three facets of felt authenticity in the parent role (authentic living, acceptance of external influence, and self-alienation) moderated the association between satisfaction with breastfeeding experience and postpartum depressive symptoms in mothers (N = 92, 81% White, 85% non-Hispanic, college-educated, Mage = 30.49). We found that mothers who felt high in authentic living in the parent role showed fewer depressive symptoms when breastfeeding experiences were positive. In addition, we found that the association between negative breastfeeding experience and greater postpartum depression was mitigated when feelings of self-alienation in the parent role, or the sense that one is unaware of or disconnected from who “she really is” as a mother, were low. This work suggests that enhancing women's feelings of connectedness to “who they truly are” as a mother may be protective against some of the negative mental health effects linked to problems with breastfeeding.

Delta-beta coupling is increasingly used to understand early emotional development. However, little is known about the development of the coupling, limiting its utility for identifying normative or aberrant functioning. We used a prospective longitudinal sample (N = 122) to compare measures of within-person and between-person coupling between ages 3 and 5, track the developmental trajectory of coupling, identify individual differences in patterns of development, and explore emotion-related predictors and outcomes of discrete developmental patterns. Within-person measures, limited in overall utility, were most useful when (1) statistical approaches produced more homogenous groups within the overall sample (extreme groups or latent classes) or (2) the full developmental course was considered. We found two trajectories of change in frontal coupling and three trajectories of change in parietal coupling. Coupling trajectories were predicted by observed fear and approach/avoidance at age 3. In addition, high levels of frontal coupling at age 3 that declined and then levelled out through age 5 were associated with lower levels of internalizing by age 5. This work provides a foundation for understanding normative change in delta-beta coupling across the preschool years and useful insight for the use of this metric in future work.

Objective Hyperglycemia has emerged as an important clinical manifestation of coronavirus disease 2019 (COVID-19) in diabetic and nondiabetic patients. Whether these glycemic changes are specific to a subgroup of patients and persist following COVID-19 resolution remains to be elucidated. This work aimed to characterize longitudinal random blood glucose in a large cohort of nondiabetic patients diagnosed with COVID-19. Materials and Methods De-identified electronic medical records of 7502 patients diagnosed with COVID-19 without prior diagnosis of diabetes between January 1, 2020, and November 18, 2020, were accessed through the TriNetX Research Network. Glucose measurements, diagnostic codes, medication codes, laboratory values, vital signs, and demographics were extracted before, during, and after COVID-19 diagnosis. Unsupervised time-series clustering algorithms were trained to identify distinct clusters of glucose trajectories. Cluster associations were tested for demographic variables, COVID-19 severity, glucose-altering medications, glucose values, and new-onset diabetes diagnoses. Results Time-series clustering identified a low-complexity model with 3 clusters and a high-complexity model with 19 clusters as the best-performing models. In both models, cluster membership differed significantly by death status, COVID-19 severity, and glucose levels. Clusters membership in the 19 cluster model also differed significantly by age, sex, and new-onset diabetes mellitus. Discussion and Conclusion This work identified distinct longitudinal blood glucose changes associated with subclinical glucose dysfunction in the low-complexity model and increased new-onset diabetes incidence in the high-complexity model. Together, these findings highlight the utility of data-driven techniques to elucidate longitudinal glycemic dysfunction in patients with COVID-19 and provide clinical evidence for further evaluation of the role of COVID-19 in diabetes pathogenesis.

Objective and Aims: Overweight/obese children are at risk of developing type 2 diabetes mellitus. Random glucose elevations provide early warning signs of glycemic dysregulation. To assess random blood glucose (RBG) concentrations and risk factors associated with prediabetes in children aged 3-18 years from six Indian regions. Method: Multicenter, cross sectional, observational school-based study; multi-stage stratified random sampling was carried out. Height and weight measured; body mass index (BMI) was computed. RBG measured using a glucometer. National sample survey was used for dietary patterns. Data were analyzed using SPSS 25.0 for Windows. Setting: Study centers were from Maharashtra, Gujarat, Chhattisgarh, Assam, Tamil Nadu and Punjab from 40 selected schools. Participant: Children aged 3-18 years were measured. Results: Data on 14339 subjects (7413 boys) were analyzed. Prevalence of obesity was 5.8% and overweight-10.6%. Overall, 1% had low (7.2 mmol/L). With increasing mean BMI, there was increase in RBG concentrations. Children from Tamil Nadu were more likely to have RBG outside reference range compared to other regions (P < 0.05). Assam and Punjab had highest prevalence of RBG and BMI within reference range. Energy intake partly explained regional variations. Multivariate analysis showed male gender, urban residency, age >10 yrs (girls) and 13 yrs (boys), and overweight or obesity were predictive of prediabetes. Conclusion: Increased prevalence of overweight, obesity and prediabetes in Indian children are a matter of concern. Regional differences suggest that strategies to prevent obesity and combat perturbations in blood sugar may have to be customized.

Background Characterizing the complexities of the tumor microenvironment is fundamental to understanding cancer. Spatial relationships between infiltrating immune cells and the existing cellular matrix are now recognized as key determinants of tumor heterogeneity. Nevertheless, most available technologies for studying cells within the context of their tissue microenvironment, like traditional immunofluorescence (IF) and immunohistochemistry (IHC), are limited—allowing the visualization of only a few markers at a time. Materials and Methods CO-Detection by indEXing (CODEX®) technology has overcome this limitation through a DNA-based labeling strategy, involving the sequential addition and removal of dye-labeled oligonucleotide reporters to antibodies equipped with complementary oligonucleotide tags. In this manner, it is possible to visualize tens of antibodies in the same tissue, in situ and at cellular resolution. Additionally, CODEX® interfaces with existing inverted microscopes and provides a cost-effective, fully automated platform for ultra-high plex immunofluorescence imaging. We have expanded the CODEX® platform to include Tyramide Signal Amplification of weak fluorescent signals, i.e. from low-expression biomarkers. This approach was tested with key biomarkers used in routine analyses of the tumor microenvironment, including PD-L1, PD-1 and FOXP3. Results We demonstrate >50X amplification of PD-L1, PD-1 and FOXP3 signals when compared to control tissues. Moreover, we successfully included our amplification step in the CODEX® labeling/imaging workflow, so that it was possible to analyze amplified PD-L1, PD-1 and FOXP3 signals concurrently with a panel of 20+ additional antibodies. Analysis of our data also generated unique biological insights, including increased PD-L1 expression in Treg cells and other tumor and stromal regions. Conclusions Our findings demonstrate the feasibility of amplifying weak biomarker signals in the CODEX® workflow. Furthermore, our experiments were conducted on human formalin fixed paraffin embedded tumor tissues, thereby demonstrating the applicability of CODEX® analyses for clinical and translational research agendas. Disclosure Information O. Braubach: A. Employment (full or part-time); Significant; Akoya Biosciences. S. Mistry: A. Employment (full or part-time); Significant; Akoya Biosciences. G. Dakshinamoorthy: A. Employment (full or part-time); Significant; Akoya Biosciences. J. Yuan: A. Employment (full or part-time); Significant; Akoya Biosciences. P. Noordam: A. Employment (full or part-time); Significant; Akoya Biosciences. J. Kim: A. Employment (full or part-time); Significant; Akoya Biosciences. W. Lee: A. Employment (full or part-time); Significant; Akoya Biosciences. J. Kennedy-Darling: A. Employment (full or part-time); Significant; Akoya Biosciences.

Reactivity to emotional information, measurable at the level of neural activity using event-related potentials, is linked to symptoms of affective disorders. Behavioral evidence suggests that contextual factors, such as social support, can alter emotional reactivity such that affective responding is normalized when social support is high. This possibility remains largely untested at the neural level, specifically through approaches that can offer insight into the mechanistic processes contributing to individual differences in emotional reactivity. Yet, such knowledge could be useful for prevention and intervention efforts, particularly with groups at risk for increased emotional reactivity, such as pregnant mothers for whom emotional distress predicts both maternal and child outcomes. Expectant mothers took part in a longitudinal study that tested whether the late positive potential (LPP), a neural index of reactivity to emotional information, was moderated by maternal perceptions of social support. In the third trimester of pregnancy, lower perceived social support was associated with an absence of a traditional LPP effect, which differentiates valenced from neutral stimuli. Findings suggest that perceptions of social support may normalize emotional processing at the neural level and highlight the potential importance of social support modulation of emotional reactivity during times of known biological change.

BackgroundThere is growing consensus that spatial biology is the key to unlocking the underlying mechanisms of cancer immunotherapy and to predicting patient outcomes. Indeed, a recent example using the Akoya Phenoptics technology revealed a unique phenotypic signature of CD8/Foxp3 positive cells embedded within the tumor microenvironment of patients that responded favorably to PD-1 checkpoint inhibition.1 In this case, the combination of both multiparameter and spatial readouts was required to correlate significantly with outcome. As the number of treatment options expands and knowledge regarding cell types that contribute to treatment mechanisms improves, so too do the number of markers required to analyze responses that enable discovery of new signatures.MethodsHere, we present data from the analysis of human FFPE cancer tissues using an expanded CODEX antibody catalog targeting a variety of immune, immune checkpoint and transcription factors. CODEX enables the highly multiplexed detection of more than 40 targets within the same tissue sample, with single cell resolution and without degradation of the sample.ResultsOur expanded target list enables detection of key macrophage populations, T and B cell subtypes, granulocytes, dendritic cells, natural killer cells, stromal, tumor and epithelial cells. Additionally, the activation state of these immune and tumor cell types can be measured through detection of key immune checkpoints, including PD-1 and PD-L1. Through the addition of these critical markers, both cells known to contribute to treatment outcome and new biomarker signatures can be identified.ConclusionsContinued expansion of spatial biology discovery capabilities will be critical to continuing to improve patient outcomes and to develop new treatment options of solid tumors using cancer immunotherapies.ReferenceBerry S, Taube J, et al. Analysis of multispectral imaging with the AstroPath platform informs efficacy of PD-1 blockade. Science. 2021; 372: 6547.

The research-grade ADOS is a broadly used instrument that informs and steers much of the science of Autism. Despite its broad use, little is known about the empirical variability inherently present in the scores of the ADOS scale, or their appropriateness to define change, to repeatedly use this test to characterize neurodevelopmental trajectories. Here we examine the empirical distributions of research-grade ADOS scores from 1,324 records in a cross-section of the population comprising participants with autism between 5-65 years of age. We find that these empirical distributions violate the theoretical requirements of normality and homogeneous variance, essential for independence between bias and sensitivity. Further, we assess a subset of 52 typical controls vs. those with autism and find lack of proper elements to characterize neurodevelopmental trajectories in a coping nervous system changing at non-uniform, non-linear rates. Lastly, longitudinally repeating the assessments over 4 visits in a subset of the participants with autism for whom verbal criteria kept the same appropriate ADOS modules over the timespan of the 4 visits, reveals that switching the clinician, changes the cutoff scores, and consequently, influences the diagnosis, despite maintaining fidelity in the same test’s modules, room conditions and tasks’ fluidity per visit. Given the changes in probability distribution shape and dispersion of these ADOS scores, the lack of appropriate metric spaces, and the impact that these elements have on sensitivity-bias co-dependencies, and on longitudinal tracking of autism, we invite a discussion on the use of this test for scientific purposes.

IMPACT: Understanding the longitudinal glucose changes following SARS-CoV-2 infection can inform point-of-care guidelines and elucidate the viral hypothesis of diabetes mellitus pathogenesis. OBJECTIVES/GOALS: Hyperglycemia has emerged as an important manifestation of SARS-CoV-2 infection in both diabetic and non-diabetic patients. Whether clinically-detectable glycemic changes persist following SARS-CoV-2 infection remain to be elucidated. This work aims to characterize temporal patterns in glucose dysregulation following SARS-CoV-2 infection. METHODS/STUDY POPULATION: Electronic health records of patients with a diagnosis of COVID-19, positive laboratory test for SARS-CoV-2, and negative history of Diabetes Mellitus prior to infection were extracted from the TriNetX database. 7,502 patients with at least one blood glucose value 2 years to 2 weeks before, 2 weeks before to 2 weeks after, and 2 weeks after to 1 year after COVID-19 diagnosis were used for analysis. Temporal patterns are characterized by training state-of-the-art clustering algorithms, including fuzzy short time-series clustering, k-means for longitudinal data, and spectral clustering. Clustering performance is evaluated using internal evaluation metrics of the Silhouette coefficient, Calinski-Harabasz score, and Davies Bouldin index. RESULTS/ANTICIPATED RESULTS: Based on the success of prior clustering methods with random blood glucose measurements, we anticipate that the proposed time-series clustering algorithms will appropriately characterize temporal patterns of glycemic dysregulation. The best performing algorithm based on interval evaluation metrics will be selected for further analysis. Associations between blood glucose values and cluster membership will be evaluated using Kruskal-Wallis one-way ANOVA and effect size will be calculated using unbiased Cohen’s d. Clinical phenotypes for each cluster will be characterized in terms of current diagnoses, prior medication use, pertinent laboratory tests, and vital signs. DISCUSSION/SIGNIFICANCE OF FINDINGS: A clearer understanding of the longitudinal glucose changes following SARS-CoV-2 infection can elucidate clinically-detectable patterns of glycemic dysregulation, identify sub-phenotypes of patients who are more susceptive to glycemic dysregulation, and inform appropriate point-of-care guidelines.

Analysis of FFPE human tumor tissues using CODEX with signal amplification Characterizing the complexities of the tumor microenvironment is fundamental to understanding disease mechanisms. The spatial relationships between infiltrating immune cells and the remodeling of the cellular matrix is widely recognized as a key component to defining tumor heterogeneity. Current methodologies for studying cells within the context of tissue architecture, like traditional immunofluorescence (IF) and immunohistochemistry (IHC), are limiting–allowing the assessment of only a few parameters at a time. The CODEX technology has overcome this limitation through a DNA-based labeling strategy, involving adding and removing dye-labeled oligonucleotides (reporters) across multiple cycles to oligonucleotide-labeled antibodies. In this manner, tens of markers can be analyzed on the same tissue. Additionally, CODEX interfaces with existing inverted microscopes and provides a cost-effective, fully automated platform for highly multiplexed imaging. Recently, we expanded our workflow to amplify the fluorescent signal intensities of low expressing biomarkers by combining Tyramide Signal Amplification (TSA) with CODEX. This approach is associated with key markers used to analyze the tumor microenvironment, including PD-L1 and PD-1. We demonstrated signal amplification of more than 50X compared with non-amplified signal. Here, we present the analysis of CODEX data for a panel of over 20 biomarkers on human FFPE tissue including signal amplification of PD-L1, PD-1 and foxp3. Through amplification of key markers as the final cycle of a CODEX experiment, low expression can be measured and used to identify key cell types, including Treg cells and PD-L1 positive tumor and stromal regions. Citation Format: Sejal Mistry, Gajalakshmi Dakshinamoorthy, Jessica Yuan, Pieter Noordam, Joseph Kim, Won-Mean Lee, Julia Kennedy-Darling. Analysis of FFPE human tumor tissues using CODEX with signal amplification [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 387.

Autism has been largely portrayed as a psychiatric and childhood disorder. However, autism is a lifelong neurological condition that evolves over time through highly heterogeneous trajectories. These trends have not been studied in relation to normative aging trajectories, so we know very little about aging with autism. One aspect that seems to develop differently is the sense of movement, inclusive of sensory kinesthetic-reafference emerging from continuously sensed self-generated motions. These include involuntary micro-motions eluding observation, yet routinely obtainable in fMRI studies to rid images of motor artifacts. Open-access repositories offer thousands of imaging records, covering 5&ndash, 65 years of age for both neurotypical and autistic individuals to ascertain the trajectories of involuntary motions. Here we introduce new computational techniques that automatically stratify different age groups in autism according to probability distance in different representational spaces. Further, we show that autistic cross-sectional population trajectories in probability space fundamentally differ from those of neurotypical controls and that after 40 years of age, there is an inflection point in autism, signaling a monotonically increasing difference away from age-matched normative involuntary motion signatures. Our work offers new age-appropriate stochastic analyses amenable to redefine basic research and provide dynamic diagnoses as the person&rsquo, s nervous systems age.

The objectives of this study were to: 1) Determine the impact of varying baseline serum 25OHD on increase in vitamin D concentrations after daily supplementation with vitamin D and calcium (1000 IU + 500 mg respectively) for six months in school-children from a semi-rural setting 2) Test the efficacy of daily vitamin D-calcium supplementation on improvement in serum vitamin D concentrations to ≥75 nmol/L. Data collected from 106 subjects (58 boys, 48 girls), aged 6-12 years, included anthropometric measures like height and weight, body composition analysis, three one-day dietary recalls and sunlight exposure (by questionnaire). Blood was collected at baseline and endline and estimated for serum vitamin D by ELISA technique using standard kits. Classification of Vitamin D status was performed according to the 2011 Endocrine Society Practice Guidelines: vitamin D deficiency - 50 nmol/L; insufficiency - 50.0-74.9 nmol/L; sufficiency - ≥75 nmol/L. Statistical analysis was performed using SPSS software. Mean baseline serum vitamin D concentration was 59.7 ± 11.2 nmol/L; this rose to 79.8 ± 23.3 nmol/L with no significant differences between genders at the two time-points. Inverse relationship was obtained between baseline serum 25(OH)D concentrations and change in serum concentrations after supplementation, implying that with increasing baseline serum concentrations of 25(OH)D, increase in vitamin D levels post supplementation were significantly lower (r = - 0.96, p 0.0001). Greatest benefit of change in serum vitamin D concentrations after supplementation was experienced by children with basal concentrations of45 nmol/L. Daily vitamin D supplementation was effective in improving serum 25(OH)D to ≥75 nmol/L in 44% of children. Significantly higher percentage of children who were deficient at baseline (64%) were able to attain serum concentrations of ≥75 nmol/L as compared to children who were vitamin D insufficient (43%) (p 0.001). Thus, daily supplementation with 1000 IU of vitamin D along with 500 mg of calcium helped in improving serum vitamin D concentrations to ≥75 nmol/L. Children who were vitamin D deficient particularly experienced these benefits.

The current rise of neurodevelopmental disorders poses a critical need to detect risk early in order to rapidly intervene. One of the tools pediatricians use to track development is the standard growth chart. The growth charts are somewhat limited in predicting possible neurodevelopmental issues. They rely on linear models and assumptions of normality for physical growth data - obscuring key statistical information about possible neurodevelopmental risk in growth data that actually has accelerated, non-linear rates-of-change and variability encompassing skewed distributions. Here, we use new analytics to profile growth data from 36 newborn babies that were tracked longitudinally for 5 months. By switching to incremental (velocity-based) growth charts and combining these dynamic changes with underlying fluctuations in motor performance - as the transition from spontaneous random noise to a systematic signal - we demonstrate a method to detect very early stunting in the development of voluntary neuromotor control and to flag risk of neurodevelopmental derail.

Introduction Characterising complexities of the tumour microenvironment is elemental to understanding disease mechanisms. The spatial relationships between infiltrating immune cells and the remodelling of the cellular matrix is widely recognised as a key component to defining tumour heterogeneity. Current methodologies for analysing the spatial dimension in tissues, like traditional immunofluorescence (IF) and immunohistochemistry (IHC), are limited to a few parameters at a time, restricting the scope of identifiable cells. Conversely, single-cell technologies like mass cytometry and NGS-based tools provide multiplexing capabilities, but at the expense of the associated spatial information. Here we present a novel multiplexed imaging technology, termed CODEX, (CO-Detection by indEXing) that combines the high-parameter space of single-cell methodologies with the spatial analysis. Material and methods The CODEX technology involves labelling antibodies with oligonucleotide-based tags followed by a single staining step. Over 50 parameters are simultaneously measured in a single specimen in Akoya’s novel, fully automated process. Unlike other cyclic IF approaches involving multiple antibody staining and stripping steps, the CODEX platform involves a single initial staining step and subsequent gentle manipulation of the tissue thereafter. This provides a faster workflow and prevents tissue degradation due to the harsh conditions used to remove adhered antibody. Other multiplexed imaging technologies, including imaging cytometry and MIBI, require expensive equipment precluding their routine use across various labs. The CODEX technology developed by Akoya is comprised of a fluidics instrument that interfaces with existing microscope hardware as well as a suite of associated specialised reagent offerings. Results and discussions Here we present the results of an analysis of human tissue samples, including both fresh-frozen (FF) and formalin-fixed paraffin embedded (FFPE) specimens using the CODEX platform. Panels of antibodies were validated against a variety of markers and used to stain human tonsil, lymph node and tumour tissues. These data were processed using a custom analysis pipeline from image registration through cell segmentation. Single-cell data was analysed using clustering algorithms to define cell types. Conclusion This CODEX study showcases the impact of high-parameter spatially resolved analysis of clinically relevant tissues enables the detection of unique cell types and cell niches within the tumour microenvironment.

Characterizing the complexities of the tumor microenvironment is elemental to understanding disease mechanisms. The spatial relationships between infiltrating immune cells and the remodeling of the cellular matrix is widely recognized as a key component to defining tumor heterogeneity. Current methodologies for analyzing the spatial dimension in tissues, like traditional immunofluorescence (IF) and immunohistochemistry (IHC), are limited to a few parameters at a time, restricting the scope of identifiable cells. Conversely, single-cell technologies like mass cytometry and NGS-based tools provide multiplexing capabilities, but at the expense of the associated spatial information. Here, we present a novel multiplexed imaging technology, termed CODEX, (CO-Detection by indEXing) that combines the high parameter capabilities of single-cell methodologies with the associated spatial dimension. The CODEX technology involves labeling antibodies with oligonucleotide-based Barcodes followed by a single staining step. Over 50 parameters are measured within a single tissue through fully-automated, iterative cycles of adding and removing corresponding dye-conjugated Reporters. Unlike other cyclic IF approaches involving multiple antibody staining and stripping steps, the CODEX platform involves a single initial staining step and subsequent gentle and relatively fast manipulation of the tissue thereafter. This provides a faster workflow and prevents tissue degradation. Other multiplexed imaging technologies, including imaging cytometry and MIBI, require expensive equipment precluding their routine use across various labs. The CODEX technology, developed by Akoya, is comprised of a fluidics instrument that interfaces with existing microscope hardware, as suite of reagents and associated control and analysis software. Over 100 antibody clones have been validated for this platform with more than ten tissue types analyzed, including both FFPE and fresh-frozen from human and mouse samples. The CODEX technology can be used to ascertain complex cellular niches and spatial associations between multiple cell types based on the staining pattern of more than 50 parameters. The CODEX viewer software package enables users to interact with both raw data and cell annotated tissue maps to determine the underlying spatial relationships within each dataset. CODEX data from various normal and cancer tissue types is shown here with corresponding single-cell analysis of key tissue features. Overall, the CODEX platform is an accessible and versatile technology for high parameter, spatial profiling of tissue specimens. Citation Format: Gajalakshmi Dakshinamoorthy, Jaskirat Singh, Joseph Kim, Nadya Nikulina, Roya Bashier, Sejal Mistry, Maria E. Gallina, Atri Choksi, Meenu Perera, Ashley Wilson, Julia Kennedy-Darling. Highly multiplexed single-cell spatial analysis of tissue specimens using CODEX [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 490.

Characterizing the complexities of the tumor microenvironment is elemental to understanding disease mechanisms. The spatial relationships between infiltrating immune cells and the remodeling of the cellular matrix is widely recognized as a key component to defining tumor heterogeneity. Here, we present a novel multiplexed imaging technology, termed CODEX, (CO-Detection by indEXing) that combines the high parameter capabilities of single-cell methodologies with the associated spatial dimension. Over 50 parameters are measured within a single tissue through fully-automated, iterative cycles of adding and removing dye-conjugated Reporters to corresponding nucleic acid based Barcodes. The CODEX technology, developed by Akoya, is comprised of a fluidics instrument that interfaces with existing microscope hardware, a suite of reagents and associated control and analysis software. Over 100 antibody clones have been validated for this platform with more than ten tissue types analyzed, including both FFPE and fresh-frozen from human and mouse samples. The CODEX technology can be used to ascertain complex cellular niches and spatial associations between multiple cell types based on their staining pattern. CODEX data from various normal and cancer tissue types are shown here with corresponding single-cell analysis of key tissue features. Overall, the CODEX platform is an accessible and versatile technology for high parameter, spatial profiling of tissue specimens.

Spatially resolved, deep antigen profiling of tissue specimens is crucial for investigating the architecture and cell diversity in complex matrices, such as the tumor microenvironment (TME). The correlation of these two parameters with the progression of a variety of pathologies, ranging from cancer to autoimmune diseases, is still vastly unknown due to the lack of technologies that enable the detection of both high content and spatial resolution. Formalin-fixed, paraffin-embedded (FFPE) tissues constitute the ideal sample for these investigations as they retain tissue morphology at room temperature for long periods of time, which is convenient and cost-effective, and are available in vast specimen archives. Akoya Biosciences, Inc., is commercializing CODEXTM (CO-Detection by indEXing), a multiparameteric imaging platform that performs the concurrent detection and quantification of dozens of antigens with single cell resolution within a tissue specimen. The CODEX platform uses a DNA-based barcode library to label antibodies and iterative cycles of adding and removing cognate dye-labeled oligonucleotides to reveal the staining pattern for a subset of the target markers per cycle. The entire data acquisition process is fully automated using the CODEX instrument, which integrates with existing microscopes. To support high-multiplexing capabilities, more than 45 different antibody clones have been screened and validated for the detection of target epitopes in human FFPE secondary lymphoid tissues for both healthy and cancerous specimens using the CODEX platform. Proof-of-concept data have also been obtained for different cancer types, including melanoma and head and neck cancer in both normal and TMA formats. Analysis software has been developed to extract meaning from CODEX datasets and is included as part of the CODEX platform. The analysis pipeline includes image drift compensation, deconvolution and segmentation to measure integrated fluorescence intensity for each cell across tens of parameters. In this manner, infiltrating lymphocytes and other immune cells have been identified within the TME. With the high multiplexing capabilities, a variety of T-cells can be identified to detect the ratios of both immunosuppressive and immune-activating subtypes. Analysis of FFPE tissues using the CODEX platform demonstrates the unparalleled opportunities for simultaneously detecting tens of antigens with single-cell resolution within a tissue specimen. Citation Format: Maria Elena Gallina, Atri Choksi, Nadya Nikulina, Jaskirat Singh, Gajalakshmi Dakshinamoorthy, Joseph Kim, Sejal Mistry, Julia Kennedy-Darling. Spatially resolved deep antigen profiling of single cells in FFPE tissue samples through CODEXTM [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr A074.

The tumor microenvironment (TME) comprises a multitude of cell types that collectively create an immunosuppressive environment, enabling tumor growth. Understanding the spatial organization of these tissues requires a technology that can identify the presence of multiple markers and correlate it to their specific spatial location within the same tissue. Characteristics of the TME including infiltrating immune cells, angiogenesis and the presence of other nonmalignant cells influence important phenomena like drug delivery, treatment effectiveness and, ultimately, clinical outcomes. Current methodologies for analyzing the spatial dimension of tissues, e.g., traditional immunofluorescence (IF) and immunohistochemistry (IHC), are limited to measuring a few parameters simultaneously, thereby restricting the number of phenotypes that can be identified. Conversely, single-cell technologies like mass cytometry and next-generation sequencing-based tools provide multiplexing capabilities, but at the expense of the associated spatial information. Akoya Biosciences, Inc., is commercializing CODEXTM (CO-Detection by indEXing), a multiparameteric imaging platform that allows the simultaneous detection and quantification of dozens of target epitopes in single cells within a single tissue section. This innovative platform is an end-to-end solution that comprises three components: 1) the CODEX fluidics instrument, 2) a suite of specialized CODEX reagents, and 3) an analysis pipeline. The CODEX workflow involves a barcoding system such that each antibody moiety is conjugated to a proprietary tag. Panels of CODEX antibodies are used to stain tissue specimens en masse in a single step. Staining data for sets of antibodies are revealed across iterative cycles using corresponding dye-labeled barcodes. The CODEX fluidics instrument integrates with existing microscope units for a fully automated data collection process. CODEX data are processed to achieve noise reduction and analyzed at the single-cell level through a segmentation algorithm based on nuclear staining.More than 80 antibodies have been validated on the CODEX platform for analysis of human and mouse fresh-frozen and FFPE tissues. Preliminary studies on fresh-frozen tissues with developed antibodies demonstrate an unprecedented capability for revealing the spatial correlation between a variety of target epitopes. These results demonstrate the enormous potential of the CODEX technology to identify spatial correlations in the TME through highly multiplexed detection with single-cell resolution. Citation Format: Maria Elena Gallina, Atri Choksi, Nadya Nikulina, Jaskirat Singh, Gajalakshmi Dakshinamoorthy, Joseph Kim, Sejal Mistry, Julia Kennedy-Darling. CODEXTM: A novel platform for spatially resolved deep antigen profiling of single cells in tissue samples [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr A073.

Background: There is a critical need for precision phenotyping across neurodevelopmental disorders, especially in individuals who receive a clinical diagnosis of autism spectrum disorder (ASD). Phelan-McDermid deletion syndrome (PMS) is one such example, as it has a high penetrance of ASD. At present, no biometric characterization of the behavioral phenotype within PMS exists. Methods: We introduce a data-type and statistical framework that permits the personalized profiling of naturalistic behaviors. Walking patterns were assessed in 30 participants (16 PMS, 3 idiopathic-ASD and 11 age- and sex-matched controls). Each individual's micro-movement signatures were recorded at 240 Hz. We empirically estimated the parameters of the continuous Gamma family of probability distributions and calculated their ranges. These estimated stochastic signatures were then mapped on the Gamma plane to obtain several statistical indexes for each child. To help visualize complex patterns across the cohort, we introduce new tools that enable the assessment of connectivity and modularity indexes across the peripheral network of rotational joints. Results: Typical walking signatures are absent in all children with PMS as well as in the children with idiopathic-ASD (iASD). Underlying these patterns are atypical leg rotational acceleration signatures that render participants with PMS unstable with rotations that are much faster than controls. The median values of the estimated Gamma parameters serve as a cutoff to automatically separate children with PMS 5–7 years old from adolescents with PMS 12–16 years old, the former displaying more randomness and larger noise. The fluctuations in the arm's motions during the walking also have atypical statistics that separate males from females in PMS and show higher rates of noise accumulation in idiopathic ASD (iASD) children. Despite high heterogeneity, all iASD children have excess noise, a narrow range of probability-distribution shapes across the body joints and a distinct joint network connectivity pattern. Both PMS and iASD have systemic issues with noise in micro-motions across the body with specific signatures for each child that, as a cohort, selectively deviates from controls. Conclusions: We provide a new methodology for precision behavioral phenotyping with the potential to use micro-movement output noise as a natural classifier of neurodevelopmental disorders of known etiology. This approach may help us better understand idiopathic neurodevelopmental disorders and personalize the assessments of natural movements in these populations.

Background Major depressive disorder (MDD) has been associated with adverse medical consequences, including cardiovascular disease and osteoporosis. Patients with MDD may be classified as having melancholic, atypical, or undifferentiated features. The goal of the present study was to assess whether these clinical subtypes of depression have different endocrine and metabolic features and consequently, varying medical outcomes. Methods Premenopausal women, ages 21 to 45 years, with MDD (N = 89) and healthy controls (N = 44) were recruited for a prospective study of bone turnover. Women with MDD were classified as having melancholic (N = 51), atypical (N = 16), or undifferentiated (N = 22) features. Outcome measures included: metabolic parameters, body composition, bone mineral density (BMD), and 24 hourly sampling of plasma adrenocorticotropin (ACTH), cortisol, and leptin. Results Compared with control subjects, women with undifferentiated and atypical features of MDD exhibited greater BMI, waist/hip ratio, and whole body and abdominal fat mass. Women with undifferentiated MDD characteristics also had higher lipid and fasting glucose levels in addition to a greater prevalence of low BMD at the femoral neck compared to controls. Elevated ACTH levels were demonstrated in women with atypical features of depression, whereas higher mean 24-hour leptin levels were observed in the melancholic subgroup. Conclusions Pre-menopausal women with various features of MDD exhibit metabolic, endocrine, and BMD features that may be associated with different health consequences. Trial Registration ClinicalTrials.gov NCT00006180

Background An increased prevalence of low bone mineral density (BMD) has been reported in patients with major depressive disorder (MDD), mostly women. Methods Study recruitment was conducted from July 1, 2001, to February 29, 2003. We report baseline BMD measurements in 89 premenopausal women with MDD and 44 healthy control women enrolled in a prospective study of bone turnover. The BMD was measured by dual-energy x-ray absorptiometry at the spine, hip, and forearm. Mean hourly levels of plasma 24-hour cytokines, 24-hour urinary free cortisol, and catecholamine excretion were measured in a subset of women. We defined MDD according to the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition). Results The prevalence of low BMD, defined as a T score of less than −1, was greater in women with MDD vs controls at the femoral neck (17% vs 2%; P = .02) and total hip (15% vs 2%; P = .03) and tended to be greater at the lumbar spine (20% vs 9%; P = .14). The mean ± SD BMD, expressed as grams per square centimeters, was lower in women with MDD at the femoral neck (0.849 ± 0.121 vs 0.866 ± 0.094; P = .05) and at the lumbar spine (1.024 ± 0.117 vs 1.043 ± 0.092; P = .05) and tended to be lower at the radius (0.696 ± 0.049 vs 0.710 ± 0.055; P = .07). Women with MDD had increased mean levels of 24-hour proinflammatory cytokines and decreased levels of anti-inflammatory cytokines. Conclusions Low BMD is more prevalent in premenopausal women with MDD. The BMD deficits are of clinical significance and comparable in magnitude to those resulting from established risk factors for osteoporosis, such as smoking and reduced calcium intake. The possible contribution of immune or inflammatory imbalance to low BMD in premenopausal women with MDD remains to be clarified. Trial Registration clinicaltrials.gov Identifier:NCT00006180