Cluster Scores Research Articles

An Analysis of Streamflow Trends in the Southern and Southeastern US from 1950–2015

In this article, the mean daily streamflow at 139 streamflow-gaging stations (sites) in the southern and southeastern United States are analyzed for spatial and temporal patterns. One hundred and thirty-nine individual time-series of mean daily streamflow were reduced to five aggregated time series of Z scores for clusters of sites with similar temporal variability. These aggregated time-series correlated significantly with a time-series of several climate indices for the period 1950–2015. The mean daily streamflow data were subset into six time periods—starting in 1950, 1960, 1970, 1980, 1990, and 2000, and each ending in 2015, to determine how streamflow trends at individual sites acted over time. During the period 1950–2015, mean monthly and seasonal streamflow decreased at many sites based on results from traditional Mann–Kendall trend analyses, as well as results from a new analysis (Quantile-Kendall) that summarizes trends across the full range of streamflows. A trend departure index used to compare results from non-reference with reference sites identified that streamflow trends at 88% of the study sites have been influenced by non-climatic factors (such as land- and water-management practices) and that the majority of these sites were located in Texas, Louisiana, and Georgia. Analysis of the results found that for sites throughout the study area that were influenced primarily by climate rather than human activities, the step increase in streamflow in 1970 documented in previous studies was offset by subsequent monotonic decreases in streamflow between 1970 and 2015.

Abstract 17285: Metabolite-Derived Network Reveals Cluster of Acylcholine Metabolites Associated With Better Diet Quality and Lower Prevalence of Type 2 Diabetes: Findings From the Boston Puerto Rican Health Study

Introduction: Puerto Rican (PR) adults living on the US mainland are at high risk for developing type 2 diabetes (T2D), and dietary factors may contribute to this increased risk. Network analysis is a data-reduction tool that can identify correlated clusters of co-regulated metabolites that reflect mechanisms underlying diet-T2D associations. Hypothesis: Diet quality will associate with T2D-associated metabolite clusters among PR adults. Methods: We used LC/MS to measure fasting plasma metabolites (>700) among Boston PR Health Study participants, aged 45-75 years, with (n=258) and without (n=421) T2D. We applied an unsupervised correlation network-based method to identify metabolite clusters within a global metabolite network and calculated a score for each cluster using a weighted sum of metabolite concentrations. To estimate diet quality, we calculated a modified version of a previously validated American Heart Association diet score (AHA-DS). Logistic regression was used to assess cross-sectional associations between metabolite clusters and prevalent T2D, and linear regression was used to assess associations between the continuous AHA-DS and T2D-associated metabolite clusters among controls, adjusting for potential confounders and correcting for multiple testing. Results: We identified 7 metabolite clusters that were associated with prevalent T2D ( p <0.05). For every 1-standard deviation (SD) increase in cluster score, the odds ratios for prevalent T2D and 95% confidence intervals were as the follows: acylcholines [0.40 (0.31, 0.50)], aromatic hydrocarbon derivatives [0.33 (0.22, 0.47)], sphingolipids [0.46 (0.33, 0.64)], tricarboxylic acid (TCA) cycle amino acids/peptides [0.39 (0.25, 0.62)], branched-chain amino acid metabolites [4.1 (2.9, 6.0)], acylcarnitines [1.8 (1.3, 2.5)], and TCA cycle/energy metabolites [2.0 (1.4, 3.0)]. The AHA-DS was only significantly associated with the acylcholine metabolites cluster [β (standard error) = 0.01 (0.004) SD increase in cluster score, p=0.02]. Conclusions: In individuals of PR descent, we identified a cluster of acylcholine metabolites where concentrations are higher among those with better diet quality and lower among those with prevalent T2D.

Yoga for warriors: An intervention for veterans with comorbid chronic pain and PTSD.

Comorbid chronic pain and posttraumatic stress disorder (PTSD) is common in veterans; this comorbidity is associated with increased severity and poorer prognosis when compared to each outcome alone. Yoga has been shown to be effective for chronic pain and promising for PTSD, but yoga for comorbid pain and PTSD has not been examined. This article offers empirical support for a yoga intervention for comorbid chronic pain and PTSD in a veteran population. Results are presented from a 4-year pilot yoga intervention for comorbid chronic pain and PTSD at a large, urban Veterans Affairs Medical Center. Based on the fear avoidance model of pain, the intervention used a cross-sectional, open-trial design with pre- and postmeasures. T test analyses were conducted on program completers (N = 49; out of 87 initially enrolled, 44% attrition rate), who were primarily African American (69%) and male (61%) and had a mean age of 51.41 years (SD = 11.32). Results indicated trend-level reductions in overall PTSD symptoms, as measured by the PTSD Checklist for DSM-5 (p = .02, d = 0.38) and in symptom cluster scores of negative alterations of cognitions and mood (p = .03, d = 0.36) and arousal and reactivity (p = .03, d = 0.35). Veterans reported significant improvement in ability to participate in social activities (p < .001, d = 0.44) and significant reductions in kinesiophobia (fear of movement or physical activity; p < .001, d = 0.85). On a satisfaction measure with a range of 1 (quite dissatisfied) to 4 (extremely satisfied), the mean rating was 3.74 (SD = 0.33). Yoga is a feasible and effective intervention for veterans with comorbid chronic pain and PTSD. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Proteomics analysis of host cell proteins after immobilized metal affinity chromatography: Influence of ligand and metal ions

Different degrees of protein purity have been observed in immobilized metal affinity chromatography ranging from extremely high purity to moderate and low purity. It has been hypothesized that the host cell protein composition and the metal ligands are factors governing the purity of a protein obtained after immobilized metal affinity chromatography (IMAC). Ni nitrilotriacetic acid (NTA) has become the first choice for facile His-tagged protein purification, but alternative ligands such as iminodiacetic acid (IDA) with other immobilized metal ions such as Zn, Cu and Co are valuable options when the expected purity or binding capacity is not reached. Especially Cu and Zn are very attractive, due to their reduced environmental and safety concerns compared to Ni. Co and Zn are more selective than Ni and Cu. This increased selectivity comes at the cost of weaker binding. In this work, the influence of ligand choice on protein purity after IMAC was evaluated by several methods, including peptide mapping. His-tagged GFP was used as model protein. We found that host cell protein (HCP) content varies drastically between ligands, as IDA eluates generally showing higher HCP concentrations than NTA. The relative content of the key amino acids His, Cys and Trp in the sequence of the co-eluted protein does not suffice to explain co-eluting propensity. The co-elution of HCPs is mostly influenced by metal binding clusters on the protein surface and not by total content or surface concentration of metal interacting amino acids. Prediction of co-elution is not dependent on these clusters alone, due to protein-protein interactions, indicted by a relative low metal binding cluster score but high co-elution propensity and in a lot of cases these proteins are often part of complex such as ribosome and chaperones. The different co-eluting proteins were presented by a heatmap with a dendrogram. Ward's linkage method was used to calculate the distance between groups of co-eluting proteins. Clustering of co-eluting HCPs was observed according to ligand and by metal ions, with Zn and Co forming one cluster and Ni and Cu another. The co-elution of host cell proteins can be explained by clusters of metal interacting amino acids on the protein surface and by protein-protein interactions. While Ni NTA still appears to be highly advantageous, it might not be the cure-all for all applications.

Efficacy of the \u2018Stand and Move at Work\u2019 multicomponent workplace intervention to reduce sedentary time and improve cardiometabolic risk: a group randomized clinical trial

BackgroundSedentary time is associated with chronic disease and premature mortality. We tested a multilevel workplace intervention with and without sit-stand workstations to reduce sedentary time and lower cardiometabolic risk.MethodsStand and Move at Work was a group (cluster) randomized trial conducted between January 2016 and December 2017 among full-time employees; ≥18 years; and in academic, industry/healthcare, and government worksites in Phoenix, Arizona and Minneapolis/St. Paul, Minnesota, USA. Eligible worksites were randomized to (a) MOVE+, a multilevel intervention targeting reduction in sedentary time and increases in light physical activity (LPA); or (b) STAND+, the MOVE+ intervention along with sit-stand workstations to allow employees to sit or stand while working. The primary endpoints were objectively-measured workplace sitting and LPA at 12 months. The secondary endpoint was a clustered cardiometabolic risk score (blood pressure, glucose, insulin, triglycerides, and HDL-cholesterol) at 12 months.ResultsWorksites (N = 24; academic [n = 8], industry/healthcare [n = 8], and government [n = 8] sectors) and employees (N = 630; 27 ± 8 per worksite; 45 ± 11 years of age, 74% female) were enrolled. All worksites were retained and 487 participants completed the intervention and provided data for the primary endpoint. The adjusted between arm difference in sitting at 12 months was − 59.2 (CI: − 74.6,-43.8) min per 8 h workday, favoring STAND+, and in LPA at 12 months was + 2.2 (− 0.9,5.4) min per 8 h workday. Change in the clustered metabolic risk score was small and not statistically significant, but favored STAND+. In an exploratory subgroup of 95 participants with prediabetes or diabetes, the effect sizes were larger and clinically meaningful, all favoring STAND+, including blood glucose, triglycerides, systolic blood pressure, glycated hemoglobin, LDL-cholesterol, body weight, and body fat.ConclusionsMultilevel workplace interventions that include the use of sit-stand workstations are effective for large reductions in sitting time over 12 months. Among those with prediabetes or diabetes, clinical improvements in cardiometabolic risk factors and body weight may be realized.Trial registrationClinicalTrials.gov Identifier: NCT02566317. Registered 2 October 2015, first participant enrolled 11 January 2016.

Service Dogs for Veterans and Military Members With Posttraumatic Stress Disorder: Replication With the PTSD Checklist for DSM-5.

Psychiatric service dogs are an emerging complementary intervention for veterans and military members with posttraumatic stress disorder (PTSD). Recent cross-sectional studies have documented significant, clinically relevant effects regarding service dogs and PTSD symptom severity. However, these studies were conducted using the PTSD Checklist (PCL) for the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM). The present study aimed to replicate and advance these findings using the latest version of the PCL for the fifth edition of the DSM (PCL-5). Participants included 186 military members and veterans who had received a PTSD service dog (n = 112) or who were on the waitlist to receive one in the future (n = 74). A cross-sectional design was used to investigate the association between having a service dog and PCL-5 total and symptom cluster scores. After controlling for demographic variables, there was a significant association between having a service dog and lower PTSD symptom severity both in total, B = -14.52, p < .001, d = -0.96, and with regard to each symptom cluster, ps < .001, ds = -0.78 to -0.94. The results replicated existing findings using the largest sample size to date and the most recent version of the PCL. These findings provide additional preliminary evidence for the efficacy of service dogs as a complementary intervention for military members and veterans with PTSD and add to a growing body of foundational research serving to rationalize investment in the further clinical evaluation of this emerging practice.

Feasibility Trial of an eHealth Intervention for Health-Related Quality of Life: Implications for Managing Patients with Chronic Pain during the COVID-19 Pandemic.

Purpose: This study was conducted to determine the feasibility of providing an eHealth intervention for health-related quality of life (HRQOL) to facilitate patient self-management. Methods: A randomized controlled trial was conducted from 2019–2020 within the Pain Registry for Epidemiological, Clinical, and Interventional Studies and Innovation. Eligible patients included those with chronic low back pain and a SPADE (sleep disturbance, pain interference with activities, anxiety, depression, and low energy/fatigue) cluster score ≥ 55 based on the relevant scales from the Patient-Reported Outcomes Measurement Information System instrument with 29 items (PROMIS-29). Patients were randomized to the eHealth treatment group, which received a tailored HRQOL report and interpretation guide, or to a wait-list control group. The primary outcome was change in the SPADE cluster score, including its five component scales, over 3 months. Secondary outcomes were changes in low back pain intensity and back-related disability. Treatment effects were measured using the standardized mean difference (SMD) in change scores between groups. The eHealth intervention was also assessed by a survey of the experimental treatment group 1 month following randomization. Results: A total of 102 patients were randomized, including 52 in the eHealth treatment group and 50 in the wait-list control group, and 100 (98%) completed the trial. A majority of patients agreed that the HRQOL report was easy to understand (86%), provided new information (79%), and took actions to read or learn more about self-management approaches to improve their HRQOL (77%). Although the eHealth intervention met the criteria for a small treatment effect in improving the overall SPADE cluster score (SMD = 0.24; p= 0.23) and anxiety (SMD = 0.24; p = 0.23), and for a small-to-medium treatment effect in improving depression (SMD = 0.37; p = 0.06) and back-related disability (SMD = 0.36; p = 0.07), none of these results achieved statistical significance because of limited sample size. Conclusion: Given the feasibility of rapid online deployment, low cost, and low risk of adverse events, this eHealth intervention for HRQOL may be useful for patients with chronic pain during the COVID-19 pandemic.

Early infant behavioural correlates of social skills in adolescents.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder typically diagnosed after the second year of life; however, differences in brain structure and function associated with ASD have been ascertained in early infancy. Identifying behavioural markers of ASD risk in early infancy has the potential to facilitate early detection and intervention. We examined associations between infant behaviour and adolescent behaviours associated with ASD. Analyses leveraged data available on 370 participants from the New Bedford Cohort, a sociodemographically diverse prospective birth cohort of children born from 1993 to 1998 to mothers residing near the New Bedford Harbor Superfund site in Massachusetts. Longitudinal assessments were used to examine the associations between behaviours when children were approximately 2weeks old (measured by the Neonatal Behavioral Assessment Scale [NBAS]), and subsequent maladaptive behaviours associated with ASD at approximately 15years old [measured by the Behavior Assessment System for Children, 2nd Edition-Teacher Rating Scale (BASC-2 TRS) scores which are standardised to a mean (SD) of 50 (10)]. Poorer performance on select individual items and cluster scales of the NBAS was associated with an increase in behaviours associated with ASD in adolescents. Associations were strongest for neonatal measures of self-regulation, response to auditory input, and autonomic nervous system regulation. For example, in covariate-adjusted models, infants with Regulation of State NBAS cluster scores in the lowest tertile (poorest performance) compared to infants with scores in the higher two tertiles had adolescent BASC-2 TRS Developmental Social Disorders T-scores that were 2.9 points higher (95% CI: 0.8, 4.9), indicating more behaviours associated with ASD. The NBAS is an established and accessible instrument that assesses a broad range of behaviours in very young infants, and may be a useful tool for newborn assessments of developmental risk, including risk of ASD-associated behaviours.

Behavioral and Neural Correlates of Cognitive Training and Transfer Effects in Stroke Patients.

Stroke lesions are frequently followed by cognitive impairments. Cognitive training is a non-pharmacological intervention that can promote neural compensation mechanisms and strategies to remediate cognitive impairments. The aims of this study were: (1) To investigate the cognitive performance, generalization effects, and neural correlates of semantic organization strategy training (SOST) in patients with chronic left frontoparietal stroke and healthy controls (HC); and (2) to compare the behavioral effects and neural correlates of SOST with an active control psychoeducation intervention (PI). In this randomized controlled study, all participants were randomly allocated into two groups, one group received SOST, and the other received PI intervention. Participants underwent two fMRI sessions, one prior and the other, after intervention. In each fMRI session, images were obtained during memory encoding task using a list of semantically related words. We found improved post-intervention memory performance in participants that received SOST (both patients and controls), indicated by number of words recalled, word clustering scores, and performance in a generalization task. The fMRI analysis revealed negative correlation between task performance and regions of the default-mode network. These results suggest that cognitive training using semantic organization strategy can improve episodic memory performance and promote potential functional neuroplasticity in patients with ischemic stroke lesions.Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03644290.

Novel pattern recognition-enhanced sensor fault detection and diagnosis for chiller plant

In building application, sensor faults in chilled water system would cause extra electricity consumption or thermal comfort problems. In the computerized building management system, it is important to automatically detect, diagnose and correct different categories of sensor faults. To realise this aim, a novel 2-stage pattern recognition-enhanced sensor fault detection and diagnosis (PRe-SFDD) was formulated. At the first-stage pattern recognition, various featuring patterns were generated through sensor reading datasets from both fault-free and different faulty test cases. At the second-stage pattern recognition, one-day featuring patterns were used to diagnose the sensor faults of positive bias, negative bias, precision degradation and general drift; while 3-day featuring patterns would allow further recognise the drift fault to be positive or negative. Hence, different categories of sensor faults could be automatically detected, diagnosed and corrected through the proposed pattern recognition strategy. For a representative chiller plant, it was found that the successful diagnosis ratio of the 2-stage PRe-SFDD were 97.9%, 100%, 96.4%, 95.4% and 98.1% for positive bias, negative bias, precision degradation, positive drift and negative drift, respectively. In addition, characteristic curves of clustering score values were constructed for correction of the extent of sensor faults.

Comparison of the PHQ9 and ImPACT symptom cluster scores in measuring depression among college athletes

Accurate identification of athletes in need of mental health services is essential. The clinical utility of the Patient Health Questionnaire − 9 (PHQ-9), a stand-alone measure of depression, was explored among Division II college athletes (n = 1,209) completing pre-participation concussion baseline assessments (mean age = 19.28), which also included Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT). ImPACT’s symptom inventory can be divided into four clusters: affective, cognitive, physical/somatic, and sleep. Most athletes (81.9%) did not endorse any items on the affective symptom cluster; however, 90 athletes (7.4%) fell above the cutoff of 5 for depression on the PHQ-9, and approximately half of all athletes endorsed one or more PHQ-9 items. Simple linear regressions revealed ImPACT’s sleep symptom cluster as the best predictor of PHQ-9 total score; however, affective, cognitive, and physical symptom clusters significantly predicted PHQ-9 total score as well. Due to relative under-endorsement of items on ImPACT’s affective symptom cluster compared to the PHQ-9, the clinical utility of incorporating a stand-alone measure of depression such as the PHQ-9 during baseline testing is supported.

Association of the TLR4 gene with depressive symptoms and antidepressant efficacy in major depressive disorder

At present, the etiology and pathogenesis of major depressive disorder(MDD) are still unclear. Some studies have shown that toll-like receptor 4 may play an important role in MDD. However, little is currently known about the association between TLR4 single gene polymorphisms (SNPs) and depressive symptoms and antidepressant efficacy.The aim of this study is to analyze whether TLR4 SNPs are associated with depressive symptoms and antidepressant efficacy. The study consisted of 438 patients with first-episode depression. We analyzed three TLR4 SNPs (rs1927911, rs11536889, and rs7873784) and obtained the baseline and 6-week scores using the 17-item Hamilton Depression Rating Scale (HAMD17) and its five-factor model. Allelic and genotypic association tests between TLR4 SNPs and HAMD17 total and cluster scores were performed with UNPHASED, while chi-square tests to analyze the association between TLR4 SNPs and response to antidepressants were performed with SPSS. Patients with the rs1927911-GG genotype exhibited higher scores of anxiety (physical symptoms) and anxiety (somatic). Patients with rs1927911-G also exhibited higher anxiety (physical symptoms) and anxiety (somatic) scores. Patients with rs11536889-GG had significantly lower suicide scores and higher psychomotor retardation scores. Patients with rs11536889-G also had significantly lower suicide scores and higher psychomotor retardation scores. Patients with rs7873784-G had higher anxiety (physical symptoms) and anxiety (psychological) scores. There was no significant difference between antidepressant efficacy and TLR4 gene polymorphisms. These findings provide evidence that TLR4 plays an important role in anxiety, suicide, and other symptoms in patients with MDD. No relationship was found between TLR4 gene polymorphisms and antidepressant efficacy in this study. Further research is needed on gene polymorphisms and the expression of TLR4 in patients with MDD.

Does retrieval potentiate new learning when retrieval stops but new learning continues?

Performing retrieval practice of previously studied material can enhance subsequent learning of new material. This potentiating effect of interpolated testing has been extensively investigated in multi-list learning paradigms. However, extant studies in this literature have manipulated interpolated testing in a binary manner, such that participants either took a test after every list or they are not tested until the final list. In reality, when students prepare for an exam, they are unlikely to test themselves consistently at regular intervals. Therefore, a critical question is whether interpolated testing would potentiate new learning when interpolated testing stops but encoding continues. In four experiments, we compared memory performance across participants who received an interpolated test after every list, received no interpolated tests, or received interpolated tests during only the early lists. Results showed that retrieval enhanced new learning even when testing was terminated early, although the benefits were weakened substantially. Further, participants’ test expectancy ratings and semantic clustering scores provide support for the idea that retrieval promotes new learning by independently enhancing attentional and organizational processes.

Baseline Concussion Symptom Reporting As A Possible Screening Method For Generalized Anxiety Disorder

Athletes with previous diagnosis of a psychiatric condition, such as depression or anxiety, have been shown to experience a larger overall concussion symptom score compared to those without a previous psychiatric treatment. Anxiety rates in college students is high (42%) with student-athletes only slightly lower (37%) compared to the general the population (18%). PURPOSE: The purpose of this study was to compare concussion-related anxiety symptoms and validated anxiety disorder screeners to see if baseline concussion symptoms could be used as a screening tool for follow-up mental health assessments. METHODS: 254 club level collegiate student-athletes (18.2±1.4yrs, 150 female, 104 male) completed the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) including the 22-item Post-Concussion Symptom Scale (PCSS), the Patient Reported Outcome Measurement Information System (PROMIS-29), and the Depression Anxiety Stress Scales (DASS-21). DSM-5 Anxiety symptoms were compared to the PCSS symptoms and an anxiety-related concussion symptom score was calculated. These along with the anxiety sub-scales for both the DASS-21 and PROMIS-29 were used for analysis. RESULTS: Participants were divided into 4 anxiety level groups based on norms from the DASS-21 (normal=36; mild=76; moderate=87; severe=28). There was a significant correlation (p<0.001) between Anxiety Cluster PCSS symptom score and DASS-21 anxiety subscale (r=.41) and PROMIS-29 Anxiety Sub-score (r=.44). The DASS-21 and PROMIS-29 were also significantly correlated (r=.64, p<0.001). There were significant group differences across the 4 DASS-21 anxiety levels for Anxiety Symptom Cluster (F(4, 226)=9.27, p<0.001) and the PROMIS-29 Anxiety subscale (F(4,223)=31.01, p<0.001). CONCLUSIONS: The significance from this data shows that the proposed symptom clusters that potentially pertain to anxiety symptoms are meaningfully related to higher scores on the DASS-21 and the PROMIS-29 anxiety related questions. Participants that demonstrated a higher overall concussion-related anxiety symptom score were more likely to exhibit more severe levels of anxiety suggesting that this cluster score could potentially screen individuals at risk for anxiety disorders thus providing a pathway to refer and provide resources and support.

Combining Clustering and Factor Analysis as Complementary Techniques

The study of driver behavior and associated accidents has been of interest to researchers and insurance companies. From the perspective of insurance companies, identifying factors that contribute to traffic violations plays a significant role in providing insurance quotes as it establishes the basis for charging appropriate insurance rates to customers. This study assesses the traffic violations intensity for 64 counties in the state of Florida, USA by using the publicly available traffic violations data set. This data set consists of 3,669,796 records with 11 attributes, which include race, gender, driver's age, type of driving violation, etc. The 187 types of traffic violations are categorized into 11 broad traffic violations categories. Two machine learning algorithms, factor analysis and k-means clustering, were applied in this study. After applying factor analysis, a new comprehensive traffic violation index (TVI) was developed, which quantified the traffic violation intensity of each county. All the counties in the data set were ranked with the TVI scores, and the counties with high TVI scores were identified. K-means clustering algorithm was then applied to the same data, and four clusters of counties were derived. The counties that were grouped in each cluster were compared with the TVI scores to check if the counties in each cluster had similar TVI scores. The counties with the highest TVI scores are found to be grouped in one cluster, followed by counties with the next high TVI scores in the second cluster, and so on. Thus, it is observed that there is a perfect match in the results of both models. They serve as two techniques complementary to each other, in that the k-means clustering method groups counties with comparable traffic violation intensities and factor analysis is able to also rank individual counties according to the TVI. These techniques have identified the counties with high traffic violation intensities, which helps the policymakers to take adequate measures for traffic management.

A-11 Comparison of the PHQ-9 and ImPACT Affective Symptom Cluster Scores in Measuring Depression at Baseline Among College Athletes

Abstract Objective Previous research has suggested that the affective symptom cluster in ImPACT can be used to screen for mood-related depressive symptoms in college athletes in place of a standalone mood measure (Riegler, Guty &amp; Arnett, 2019). However, examining the clinical utility of a mood measure that additionally assesses for non-affective depression symptoms should be explored. Method Division II college athletes (n = 1,209) completed ImPACT and the Patient Health Questionnaire (PHQ-9) at their first annual pre-participation baseline assessment (mean age = 19.28, 37% female). ImPACT symptoms were divided into four symptom clusters: physical, sleep, cognitive, and affective. Results Mean affective symptom cluster score was 0.51 while mean PHQ-9 total score was 1.32. Ninety (7.44%) of the 1,209 athletes fell above the cutoff for mild depression on the PHQ-9. The sleep symptom cluster was the best individual predictor of PHQ-9 total score (R2 = .202, p &amp;lt; .001) compared to the affective symptom cluster (R2 = .147, p &amp;lt; .001), physical symptom cluster (R2 = .124, p &amp;lt; .001) and cognitive symptom cluster (R2 = .145, p &amp;lt; .001). The individual ImPACT symptom of “fatigue” accounted for the most individual variance in PHQ-9 total score (R2 = .158, p &amp;lt; .001). Conclusions These results suggest there is clinical utility in utilizing a stand-alone mood measure to assess dysphoria that presents in a sleep-related manner as opposed to a purely affective manner.

Identification of potential inhibitors of three key enzymes of SARS-CoV2 using computational approach

The recent outbreak of coronavirus disease-19 (COVID-19) continues to drastically affect healthcare throughout the world. To date, no approved treatment regimen or vaccine is available to effectively attenuate or prevent the infection. Therefore, collective and multidisciplinary efforts are needed to identify new therapeutics or to explore effectiveness of existing drugs and drug-like small molecules against SARS-CoV-2 for lead identification and repurposing prospects. This study addresses the identification of small molecules that specifically bind to any of the three essential proteins (RdRp, 3CL-protease and helicase) of SARS-CoV-2. By applying computational approaches we screened a library of 4574 compounds also containing FDA-approved drugs against these viral proteins. Shortlisted hits from initial screening were subjected to iterative docking with the respective proteins. Ranking score on the basis of binding energy, clustering score, shape complementarity and functional significance of the binding pocket was applied to identify the binding compounds. Finally, to minimize chances of false positives, we performed docking of the identified molecules with 100 irrelevant proteins of diverse classes thereby ruling out the non-specific binding. Three FDA-approved drugs showed binding to 3CL-protease either at the catalytic pocket or at an allosteric site related to functionally important dimer formation. A drug-like molecule showed binding to RdRp in its catalytic pocket blocking the key catalytic residues. Two other drug-like molecules showed specific interactions with helicase at a key domain involved in catalysis. This study provides lead drugs or drug-like molecules for further in vitro and clinical investigation for drug repurposing and new drug development prospects.

1644-P: High Throughput Approach Enables Expanded Clustering of Type 2 Diabetes Genetic Loci Informed by Phenotypic Associations

Improved understanding of disease-causing pathways for type 2 diabetes (T2D) may lead to novel therapeutic targets and individualized treatment. Rapid expansion in the number of T2D genetic loci over the past few years can be leveraged to identify pathways via cluster analysis. We developed an automated pipeline to enable clustering of T2D genetic loci starting with genome-wide association study (GWAS) summary statistics from 6 European T2D studies. The pipeline 1) extracts variants reaching genome-wide significance, 2) replaces multi-allelic, ambiguous (A/T, C/G), or low-trait count SNPs with appropriate proxies, and 3) filters for independent signals using r2=0. Traits in the T2D Knowledge Portal with summary GWAS data in European populations were included if they met a minimum Bonferroni p-value across the selected variants. This pipeline generated a matrix of associations for 259 independent T2D variants and 32 traits to which we applied Bayesian Non-negative Matrix Factorization (bNMF) clustering. We identified 6 robust clusters of T2D loci, 5 of which overlapped with a previously published analysis of 94 loci. Three clusters indicated variant-trait associations related to insulin deficiency, while the other three clusters displayed insulin resistance-related features including: obesity, lipodystrophy, and liver-lipid metabolism. The new cluster identified in this analysis is related to beta cell function. Increased polygenic scores for clusters were associated with distinct clinical outcomes in GWAS, including coronary artery disease (UK BioBank CARDIoGRAM), ischemic stroke (MEGASTROKE), chronic kidney disease (CKDGen). Clusters also displayed tissue-specific epigenomic enrichment. Our approach expands upon previous clustering work of T2D loci and allows for efficient updating as additional GWAS results become available. This method can also be readily applied to other diseases beyond T2D to identify key pathways. Disclosure H. Kim: None. M. von Grotthuss: None. J.M. Mercader: None. J. Chiou: None. K.J. Gaulton: Consultant; Self; Genentech, Inc. Employee; Spouse/Partner; Vertex Pharmaceuticals. A. Manning: None. J.C. Florez: Advisory Panel; Self; Doris Duke Charitable Foundation. Other Relationship; Self; Novo Nordisk Inc., Park Street School. M. Udler: None. Funding National Institutes of Health

Therapeutic Atmosphere in Psychotherapy Sessions.

There is uncertainty concerning what the active ingredients in psychotherapy are. The First Experimental Study of Transference interpretations (FEST) was a randomized controlled trial of the effects of transference work (TW) in psychodynamic psychotherapy. Women with low quality of object relations (QOR) showed a large positive effect of transference work, while men with high QOR showed a slight negative effect. The present study aimed to expand the knowledge from the FEST by investigating the therapeutic atmosphere with Structural Analysis of Social Behavior (SASB). Two-way ANOVAs were conducted to investigate differences between SASB cluster scores between subgroups. The therapeutic atmosphere was characterized by Protect–Trust, Affirm–Disclose and Control–Submit. Multilevel modeling was used to assess the relationship between a therapist variable and outcomes for men and women. Contrary to expectations, no significant differences in therapeutic atmosphere between subgroups (with or without TW in women with low QOR and men with high QOR) were observed using the process measure SASB.

Clinical evaluation of biological rhythm domains in patients with major depression.

Objective:Sleep, physical activity, and social domains of biological rhythm disruptions may have specific effects on the symptom cluster and severity of depression. However, there is a lack of structured clinical evaluation to specify the domains of biological rhythms in patients with depression.Methods:Ninety drug-naïve subjects with depression and 91 matched healthy controls were recruited for the study. The severity of depression was examined with the Hamilton Rating Scale for Depression (HRSD), while biological rhythm was evaluated using the Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN).Results:Patients with depression showed significantly greater biological rhythm disturbances than healthy controls in all domains of BRIAN (sleep, activity, social, and eating). BRIAN-Total correlated positively with HRSD-Total and HRSD-Total without sleep cluster. The sleep and activity domains correlated significantly with HRSD-Total score. Additionally, the sleep, activity, and social domains correlated significantly with HRSD-Total without the sleep cluster score. Regression analysis revealed the activity (β = 0.476, t = 5.07, p<0.001) and sleep (β = 0.209, t = 2.056, p = 0.043) domains may predict HRSD-Total score.Conclusion:Consideration of biological rhythm domains in clinical examination and focusing on the sleep and activity domains may hold promise for the management of depression.