Cluster Scores Research Articles

Construction of cuproptosis signature based on bioinformatics and experimental validation in clear cell renal cell carcinoma.

Cuproptosis was defined as a novel nonapoptotic cell death pathway and its potential function in clear cell renal cell carcinoma (ccRCC) remains unclear. We obtained gene expression profiles, somatic mutation and corresponding clinical information of 881 ccRCC samples from 3 cohorts including the cancer genome atlas cohort, GSE29609 cohort and CheckMate 025 cohort. As described in the latest published article, we enrolled 16 genes as cuproptosis-related genes (CRGs). We explored the expression level, variants and copy number variation of the CRGs. Univariate and multi-variate regression were utilized to assess the prognostic significance of the CRGs. Non-negative matrix factorization was used to identify potential subgroup and gene set variation analysis was used to explore the potential biological functions. CIBERSORT, ESTIMATE algorithm and single sample gene set enrichment analysis were used to evaluate the tumor microenvironment. In vitro experiments including CCK-8, transwell and wound healing assays were utilized to explore the potential biological function of DLAT in ccRCC. We found that except for CDKN2A, the CRGs were positively associated with patients' OS. Cuproptosis cluster, cuproptosis gene cluster and cuproptosis score were established, respectively, and higher cuproptosis score was significantly associated with a worse OS in ccRCC (p < 0.001). The area under the receiver operating characteristic curve of the cuproptosis-related nomogram at 1 year, 3 years, 5 years was 0.858, 0.821 and 0.78, respectively. In addition, we found that the cuproptosis score was positively associated with PDCD1, CTLA4 expression level, thus the cuproptosis score may also reflect the dysfunction of tumor infiltrating immune cells. In vitro experiments indicated that overexpression of DLAT could inhibited the migration and proliferation ability of ccRCC cells. Our findings identify a novel cuproptosis-related signature and the cuproptosis characteristics may influence the anti-tumor immunity though complex regulating networks, and thus cuproptosis may play a role in developing novel therapeutic target of ccRCC.

Public Perceptions and Informational Needs Regarding Surgical Residents

Identify what topics are of most interest to patients regarding surgical residents. Survey of general public describing a hypothetical surgery and then assessing comfort level with resident involvement in surgery, reactions to disclosure statements regarding resident involvement, and desires for additional information. This data was used to produce an amended statement about surgical residents and their involvement in a hypothetical surgery to determine the impact of increased information on participant comfort. Online survey via Mechanical Turk. Our sample was broadly representative of the United States based on race and age, but with higher education level than United States census data. Using a combination of hierarchical clustering, weighted averages, and VAS scoring, questions that were most highly valued by participants were related to what the resident will be doing in the operation and the impact of resident involvement. Participants who had a past negative experience with residents assigned higher importance to all questions, even those that may be seen as not clinically relevant. Increasing the amount of proactively provided information did not have a significant effect on comfort (p = 0.219) when compared to our baseline statement, except with those who reported past negative experience with residents (p = 0.039). These results demonstrate that the majority of potential patients want to know specific details about the residents' skills, what they will be doing in their surgery, and the impact of their participation. Surgeons should be attuned to patients with past negative experiences, who may desire more information. Additional information alone may not be sufficient to comfort some patients, and future research should consider information delivery styles and interpersonal effects on patient comfort level.

Associations between soil-transmitted helminth infections and physical activity, physical fitness, and cardiovascular disease risk in primary schoolchildren from Gqeberha, South Africa.

School-aged children in low- and middle-income countries carry the highest burden of intestinal helminth infections, such as soil-transmitted helminths (STH). STH infections have been associated with negative consequences for child physical and cognitive development and wellbeing. With the epidemiological transition and rise in cardiovascular disease (CVD), studies have shown that helminth infections may influence glucose metabolism by preventing obesity. Thus, the aim of this study was to determine the association of STH infections in schoolchildren from Gqeberha, focusing on physical activity, physical fitness, and clustered CVD risk score. This cross-sectional study involved 680 schoolchildren (356 girls and 324 boys; mean age 8.19 years, SD±1.4) from disadvantaged communities in Gqeberha (formerly, Port Elizabeth), South Africa. Stool samples were collected and examined for STH infections using the Kato-Katz method. Physical activity (accelerometer) and physical fitness (grip strength, 20 m shuttle run) were measured using standard procedures. Furthermore, anthropometry, blood pressure, as well as glycated haemoglobin and lipid profile from capillary blood samples were assessed. We employed one-way ANOVAs to identify the associations of STH infections in terms of species and infection intensity with physical activity, physical fitness, and clustered CVD risk score. We found a low STH infection prevalence (7.2%) in our study, with participants infected with at least one intestinal helminth species. In comparison to their non-infected peers, children infected with STH had lower mean grip strength scores, but higher mean VO2max estimation and higher levels of MVPA (p < .001). When considering type and intensity of infection, a positive association of A. lumbricoides infection and MVPA was found. In contrast, light T. trichiura-infected children had significantly lower grip strength scores compared to non and heavily-infected children. VO2max and MVPA were positively associated with light T. trichiura infection. No significant association between the clustered CVD risk score and infection with any STH species was evident. STH-infected children had lower grip strength scores than their non-infected peers, yet, achieved higher VO2max and MVPA scores. Our study highlights that the type and intensity of STH infection is relevant in understanding the disease burden of STH infections on children's health. The findings of our study must be interpreted cautiously due to the low infection rate, and more research is needed in samples with higher prevalence rates or case-control designs.

Artificial Intelligence-Assisted Methodology for Dataset Reduction Applied to the Establishment of Power Interruption Limits in Brazil

Definitions of methodologies to regulate the quality of electricity supply services are a topic under active discussion in Brazil and worldwide. There are various ways to define limits and quality service goals. In Brazil, the regulation of limit indicators for consumer unit sets is carried out by the National Electric Energy Agency. Its latest revision took place in 2014, under the framework of Public Announcement No. 29/2014. The primary contribution of this research is the proposition of an artificial intelligence-assisted methodology, specifically utilizing machine-learning techniques capable of organizing and selecting the most relevant attributes for representing similar consumer sets. Tests were conducted with real data from the 2020 system. The results demonstrated that this methodology can select attributes from different categories, achieving data representativeness and clustering scores superior to those attained with attributes selected by the current ANEEL methodology. Furthermore, the proposed methodology exhibits greater replicability compared to the current approach. These outcomes contribute to the modernization of quality regulation in the electricity distribution sector, benefiting all stakeholders in the industry.

Evaluation of procedural pain for neonates in a neonatal intensive care unit: a single-centre study

BackgroundTo evaluate the procedural pain experienced by neonates in a neonatal intensive care unit (NICU) setting and determine the corresponding pain grades.MethodsTwo experienced nurses independently used the Neonatal Infant Pain...

Biological functions and molecular subtypes regulated by miR-142-3p in colon cancer.

MicroRNA-142-3p (miR-142-3p) has been reported to be implicated in colon cancer; however, the possible regulatory mechanisms and molecular subtypes regulated by miR-142-3p have not been fully elucidated. This study aimed to investigate the biological functions and regulatory mechanism of miR-142-3p in colon cancer. The expression level of miR-142-3p in colon cancer was analyzed based on the mRNA and miRNA expression datasets of colon cancer retrieved from The Cancer Genome Atlas. Target genes of miR-142-3p were also predicted. Based on these target genes, the functions and subtypes of miR-142-3p were investigated. The metabolic and tumor-related pathways, immune microenvironment, and target gene expression between the 2 subtypes were analyzed. MiR-142-3p was upregulated in tumor tissues, and its high expression indicated a poor prognosis. A total of 39 target genes were predicted, which were significantly involved in autophagy- and metabolism-related functions and pathways. Based on these target genes, the colon cancer samples were clustered into 2 subtypes. There were 35 metabolism-related pathways that were significantly different between the 2 clusters. The immune and stromal scores in cluster 2 were higher than those in cluster 1, whereas the tumor purity of cluster 2 was significantly lower than that of cluster 1. TP53INP2 expression in cluster 2 was higher than that in cluster 1. MiR-142-3p may promote colon cancer progression via autophagy- and metabolism-related pathways. MiR-142-3p may be served as a candidate target for the treatment of colon cancer.

Nature and prevalence of PTSD as per DSM-5 and ICD-11 after natural and unnatural deaths

The death of a loved one may lead to posttraumatic stress disorder (PTSD). Although it is conceivable that unnatural losses (caused by e.g., accidents, homicide, or suicide) render people more vulnerable to PTSD than natural losses (e.g., caused by illnesses) this is an understudied issue. The current study sought to enhance knowledge about the presentation and prevalence of PTSD symptoms, in people confronted with natural, non-sudden and unnatural, sudden losses. Considering that PTSD is defined differently in DSM-5 and ICD-11, we compared PTSD severity and prevalence rates between these diagnostic systems. Self-reported data were available from a heterogeneous sample of 1064 bereaved people (Mage = 52.13 years, 86 % female). Confirmatory factor analyses supported the DSM-5-based and ICD-11-based symptom clustering. DSM-5 yielded higher prevalence rates of probable PTSD than ICD-11 criteria. PTSD cluster and total scores were significantly higher for participants confronted with unnatural losses than participants confronted with natural losses. Rates of probable PTSD (based on DSM-5 and ICD-11) were also higher in the former group. Confrontation with an unnatural loss was not associated with PTSD scores beyond other sociodemographic and loss-related variables considered. Results show that bereavement-related PTSD is assessed differently in DSM-5 and ICD-11. Cause of death affected PTSD but less strongly than anticipated.

Association Between Insomnia, Stress Events, and Other Psychosocial Factors and Incident Atrial Fibrillation in Postmenopausal Women: Insights From the Women's Health Initiative.

Background The association between psychosocial factors and atrial fibrillation (AF) is poorly understood. Methods and Results Postmenopausal women from the Women's Health Initiative were retrospectively analyzed to identify incident AF in relation to a panel of validated psychosocial exposure variables, as assessed by multivariable Cox proportional hazard regression and hierarchical cluster analysis. Among the 83 736 women included, the average age was 63.9±7.0 years. Over an average of 10.5±6.2 years follow-up, there were 23 954 cases of incident AF. Hierarchical cluster analysis generated 2 clusters of highly correlated psychosocial variables: the Stress Cluster included stressful life events, depressive symptoms, and insomnia, and the Strain Cluster included optimism, social support, social strain, cynical hostility, and emotional expressiveness. Incident AF was associated with higher values in the Stress Cluster (hazard ratio [HR], 1.07 per unit cluster score [95% CI, 1.05-1.09]) and the Strain Cluster (HR, 1.03 per unit cluster score [95% CI, 1.00-1.05]). Of the 8 individual psychosocial predictors that were tested, insomnia (HR, 1.04 [95% CI, 1.03-1.06]) and stressful life events (HR, 1.02 [95% CI, 1.01-1.04]) were most strongly associated with increased incidence of AF in Cox regression analysis after multivariate adjustment. Subgroup analyses showed that the Strain Cluster was more strongly associated with incident AF in those with lower traditional AF risks (P for interaction=0.02) as determined by the cohorts for heart and aging research in genomic epidemiology for atrial fibrillation score. Conclusions Among postmenopausal women, 2 clusters of psychosocial stressors were found to be significantly associated with incident AF. Further research is needed to validate these associations.

RETRACTED ARTICLE: Network Attribute Analysis and Competitiveness Evaluation of Auto Parts Industry Cluster for e-Commerce Platform

The automotive parts industry cluster is a complex operating system, and it is no longer possible to use a simple theory to make a scientific and reasonable explanation for the parts industry cluster. In view of this, the study takes the automotive parts industry cluster as the research object, innovatively invokes the theory of organizational ecology and constructs a competitiveness analysis mechanism based on population co-evolution. The study conducts performance analysis and simulation tests on the constructed model, integrating the CS–AHP evaluation method to evaluate the competitiveness of the parts industry cluster. The performance comparison results show that the research method has a minimum training error of 0.0108, when the number of iterations of the system is 69th. This method has a stable loss function value at the fifth iteration, which is a stable convergence state earlier than the GA algorithm, differential evolution and distribution estimation algorithm. The A-level index score of the off-line platform auto parts industry cluster is 0.5174, which is significantly greater than 0.5. The competitive cooperation effect, technological innovation effect and cluster culture scores of the e-commerce platform are 0.5885, 0.6899 and 0.5329, respectively, which are significantly higher than those of the off-line. The above results show that the accuracy of the research algorithm is higher than that of the off-line industry. The above results show that the accuracy of the research algorithm is better, which can make a reasonable scientific basis for the auto parts industry and carry out competitiveness evaluation. To a certain extent, it can provide technical reference for the future development of the auto field industry.

Associations of inflammation with neuropsychological symptom cluster in patients with Head and neck cancer: A longitudinal study

PurposeHead and neck cancer (HNC) patients may experience multiple co-occurring neuropsychological symptoms (NPS) cluster, including fatigue, depression, pain, sleep disturbance, and cognitive impairment. While inflammation has been attributed as a key mechanism for some of these symptoms, its association with the NPS as a cluster of symptoms is unknown. Thus, the aim of this study was to examine the association between peripheral inflammation and NPS cluster among HNC patients over cancer treatment (radiotherapy with or without chemotherapy). MethodsHNC patients were recruited and followed at pre-treatment, end of treatment, three months and one-year post-treatment. Plasma inflammatory markers, including C-reactive protein (CRP), tumor necrosis factor-alpha (TNFA), soluble tumor necrosis factor receptor-2 (sTNFR2), interleukin-1 beta (IL1-β), interleukin-6 (IL-6), interleukin-10 (IL-10), monocyte chemotactic protein-1 (MCP-1), and interleukin-1 receptor antagonist (IL-1RA) and patient-reported NPS cluster were collected at the 4 time points. Associations between inflammatory markers and the NPS cluster were analyzed using linear mixed-effects models and generalized estimating equations (GEE) models controlling covariates. Results147 HNC patients were eligible for analysis. 56% of the patients received chemoradiotherapy as treatment. The highest NPS cluster score was reported at the end of treatment, which gradually decreased over time. An increase in inflammatory markers including CRP, sTNFR2, IL-6 and IL-1RA was associated with higher continuous NPS cluster scores (p<0.001, p = 0.003, p<0.001, p<0.001; respectively). GEE further confirmed that patients with at least two moderate symptoms had elevated sTNFR2, IL-6, and IL-1RA (p = 0.017, p = 0.038, p = 0.008; respectively). Notably, this positive association between NPS cluster and inflammatory markers was still significant at one-year post-treatment for CRP (p = 0.001), sTNFR2 (p = 0.006), and IL-1RA (p = 0.043). ConclusionsMost HNC patients experienced NPS clusters over time, especially immediately after the end of treatment. Elevated inflammation, as represented by inflammatory markers, was strongly associated with worse NPS cluster over time; this trend was also notable at one-year post-treatment. Our findings suggest that peripheral inflammation plays a pivotal role in the NPS cluster over cancer treatment, including long-term follow-ups. Interventions on reducing peripheral inflammation may contribute to alleviating the NPS cluster in cancer patients.

Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies

ObjectivesDue to the heterogeneity of PCa, the clinical indicators used for PCa can't satisfy risk prognostication and personalized treatment. It is imperative to develop novel biomarkers for prognosis prediction and therapy response in PCa. Accumulating evidence shows that non-mutational epigenetic reprogramming, independent from genomic instability and mutation, serves as a newly added hallmark in cancer progression.MethodsIn this study, we integrated multi-center cohorts (N > 1300) to develop a RNA 5-methylcytosine regulator-based signature, the m5C score. We performed unsupervised clustering and LASSO regression to identify novel m5C-related subtypes and calculate the m5C score. Then we assessed the role of m5C cluster and m5C score in several clinical aspects such as prognosis in various molecular subtypes, responses to chemotherapy, androgen receptor signaling inhibitor (ARSI) therapy and immunotherapy in PCa. Finally, we validated the cancer-promoting performance of ALYREF through clinical data analysis and experiments in vivo and in vitro.ResultsThe investigation revealed that the m5C score could accurately predict the biochemical recurrence (BCR) in different subtypes (the PAM50 subtypes and immunophenotypes) and the responses to chemotherapy, ARSI therapy, and immunotherapy (PD1/PD-L1). A high m5C score indicated a poor BCR prognosis in every subtype of PCa, unfavorable responses in ARSI therapy and immunotherapy (PD1/PD-L1). Moreover, the m5C reader gene termed ALYREF, yielding the highest weighed coefficient, promoted PCa progression through in silico analysis and experimental validations (in vivo and in vitro).ConclusionsThe m5C signature can function in many aspects of PCa, such as the development and prognosis of the disease, and multiple therapy responses. Further, the m5C reader, ALYREF, was identified as a prognostic biomarker and a potential therapeutic target for PCa. The m5C signature could act as a brand-new tool for predicting the prognosis of patients in different molecular subtypes and patients’ therapy responses and promoting customized treatments.

0759 Multidimensional Sleep Health is Associated with Emotional Well-being in Adolescents

Abstract Introduction Multidimensional sleep health (MSH) is a population-based approach to capture the 24-hour experience of sleep by incorporating measures of nighttime sleep and daytime functioning that promote physical and mental well-being. We have updated the existing adolescent MSH model to incorporate objective and subjective sleep measures and, in the present study, examined its utility in identifying associations between MSH and behavioral and emotional well-being. Methods We studied 377 adolescents (16.4 ± 2.3 yr; 46.4% female; 21.5% racial/ethnic minority) from the Penn State Child Cohort, a randomly-selected population-based sample. Using the RU-SATED framework – regularity, satisfaction, alertness, timing, efficiency, and duration – we derived an MSH composite score based on actigraphy-measured and self-reported sleep data. We examined the associations between MSH and scores on both the adolescent version of the Child Behavior Checklist (CBCL) and on the Pediatric Behavior Scale (PBS). CBCL’s internalizing, externalizing, thought and attention problems scores were self-reported, while similar behavioral and emotional cluster scores on the PBS were parent-reported. Results Higher MSH scores were associated with lower thought (r=-0.21, p&amp;lt; 0.001), externalizing (r=-0.18, p&amp;lt; 0.001), attention (r=-0.16, p&amp;lt; 0.01) or internalizing (r=-0.12, p&amp;lt; 0.05) problems. Higher MSH scores were associated with lower scores on the rule-breaking (r=-0.27, p&amp;lt; 0.001) and aggressive (r=-0.21, p&amp;lt; 0.001) externalizing subscales. For the internalizing subscales, higher MSH scores were associated with lower anxious-depressed (r = -0.17, p&amp;lt; 0.01), withdrawn-depressed (r=-0.14, p&amp;lt; 0.01), and somatic complaints (r=-0.12, p&amp;lt; 0.05) scores. Analyses based on parent reports on the more fine-grained PBS cluster scores replicated CBCL’s associations; for example, higher MSH scores were associated with lower depression (r=-0.19, p&amp;lt; 0.01) and inattention (r=-0.12, p&amp;lt; 0.05) as observed by parents. Conclusion Optimal sleep health, when considered as a multidimensional construct, is associated with emotional well-being and better behavioral outcomes in adolescents. Our MSH model, derived from objective and subjective sleep metrics, is able to capture similar trends from self-report and parent-report measures of emotion and behavior. Support (if any) National Institutes of Health (R01HL136587, UL1TR000127)

Multi-Modal Neurorehabilitation for Persisting Post-Concussion Symptoms.

Treatment of the chronic sequela that persist after a mild traumatic brain injury has been challenging with limited efficacy. The aim of this work was to report outcomes obtained from persons who met the criteria of persisting post-concussive symptoms (PPCS), utilizing a novel combination of modalities in a structured neurorehabilitation program. This work was designed as a retrospective, pre-post chart review of objective and subjective measures collected from 62 outpatients with PPCS a mean of 2.2 years post-injury, before and after a multi-modal 5-day treatment protocol. The subjective outcome measure was the 27-item modified Graded Symptom Checklist (mGSC). Objective outcome measures were motor speed/reaction time, coordination, cognitive processing, visual acuity, and vestibular function. Interventions included non-invasive neuromodulation, neuromuscular re-education exercises, gaze stabilization exercises, orthoptic exercises, cognitive training, therapeutic exercises, and single/multi-axis rotation therapy. Pre-post differences in measures were analyzed using the Wilcoxon signed-rank test, with effect size determined by the rank-biserial correlation coefficient. Pre-post treatment comparisons for the subjective mGSC overall, combined symptom measures, individual components of the mGSC, and cluster scores significantly improved for all items. Moderate strength relationships were observed for the mGSC composite score, number of symptoms, average symptom score, feeling in a "fog," "don't feel right," irritability, and physical, cognitive, and affective cluster scores. Objective symptom assessment significantly improved for trail making, processing speed, reaction time, visual acuity, and Standardized Assessment of Concussion. Patients suffering from PPCS ∼2 years after injury may have significant benefits with some moderate effect sizes from an intensive, multi-modal neurorehabilitation program.

Lymph node metastasis‐dependent molecular classification in papillary thyroid carcinoma defines aggressive metastatic outgrowth

Lymph node metastasis‐dependent molecular classification in papillary thyroid carcinoma defines aggressive metastatic outgrowth

EEG CORRELATES OF SOMATIC DISORDERS IN DEPRESSIVE PATIENTS WHO SURVIVED AND HAVE NOT BEEN ILL WITH COVID-19

IntroductionCoronavirus infection is accompanied by the development of a wide range of neuropsychiatric and somatic complications.ObjectivesThe aim of the study is to assess the severity of somatic disorders and to identify their EEG correlates in depressive patients who had and did not have COVID-19.MethodsThe study involved 30 female depressive patients (F31.3-4, F21.3-4 + F34.0, according to ICD-10), aged 16-25 years, who previously had a mild or asymptomatic coronavirus infection (group "COVID”), and 40 depressive patients matched in gender, age and syndrome structure to patients of the “COVID” group, but who did not have COVID-19 (“non-COVID” group). The pre-treatment severity of depressive symptoms was assessed by the total sum, and by sums of clusters: depression (items 1, 2, 3, 7, 8), anxiety (items 9, 10, 11), sleep disorders (items 4, 5 , 6) and somatic disorders (items 12, 13, 14) of HDRS-17 scale. All patients underwent pre-treatment multichannel (16 leads) recordings of the background EEG followed by analysis of the absolute EEG spectral power (SP) in 8 narrow frequency sub-bands. Statistical analysis of the data was carried out using the methods of descriptive statistics and correlation analysis of the IBM SPSS Statistics, v.22 software package.ResultsThe values of the total sums of scores of individual clusters (depression, anxiety, sleep disorders) of the HDRS-17 scale in the “COVID” and “non-COVID” groups did not differ statistically. The exception was a significantly higher (p&gt;0.01) number of complaints of somatic disorders (weakness, heaviness and pain in the muscles, a feeling of loss of energy, loss of strength, decreased libido) in patients who had COVID compared to those who did not (2.4±1.0 and 1.4±1.1 points, respectively). In the “non-COVID” group, the HDRS-17 somatic disorder cluster scores positively correlated with SP values of beta2 EEG (20–30 Hz) in leads F3, F8, and P3. which reflects the increased activation of brain stem structures, characteristic for depressive conditions. In the “COVID” group, these scores correlated with the SP values of alpha3 (11-13 Hz, in leads F4, F8, C4 and T4) and beta2 (20-30 Hz, in C4) not positively, but negatively. Thus, the severity of somatic complaints in patients of this group is associated not with greater, but with less activation of the brain (in particular, of the right hemisphere), which, presumably, may be associated with the “exhaustion” of the central mechanisms of regulation of autonomic functions after suffering COVID disease.ConclusionsCOVID (in a mild or asymptomatic form) did not show a significant effect on the overall severity of depression of the studied group of patients who recovered from COVID, with the exception of a significantly greater severity of their somatic complaints compared to the group of patients who had not been ill with COVID. The study supported by the RSF grant No. 21-18-00129.Disclosure of InterestNone Declared

Associations Between Social Determinants of Health and Psychoneurologic Symptom Clusters in Women With Gynecologic Cancers: A Longitudinal Study.

To evaluate the associations between social determinants of health (SDOH) and psychoneurologic symptom (PNS) clusters in women with gynecologic cancers during cancer treatment. 67 women with gynecologic cancers who received radiation therapy were assessed at baseline, six to eight weeks after treatment, and six months after treatment at oncology clinics in Georgia. Fatigue, pain, sleep disturbances, cognitive impairment, and depressive symptoms were measured to determine a PNS cluster score. Associations between SDOH and PNS cluster scores were assessed using mixed-effect models. Larger mean PNS cluster scores were reported in individuals with less education, lower income, and unemployment, as well as in those living in more disadvantaged neighborhoods. Individual- and community-level SDOH and their interactions were associated with more PNS clusters. Studying SDOH at multiple levels depicts how various social disadvantages can exacerbate poor health outcomes.

Rank Based Iterative Clustering (RBIC) for indoor localization

In the current era, technological advancements have resulted in a spike in various sensor data-intensive applications including indoor localization services. WiFi fingerprint-based localization for large indoor areas is primarily contingent on laborious site surveys. To ease the flow of research, grossly labeled data collected using a crowd-sourced method could be clustered. However, for a real-time localization approach, the challenge is to generate the clusters containing data samples that are really physically close. In this paper, a two-phase semi-supervised localization approach has been proposed, which is general enough to be applied to indoor localization datasets. In the offline phase, a Rank-Based Iterative Clustering (RBIC) algorithm has been proposed that generates a clustered dataset with a negligible chance of containing physically apart location points within a common cluster. RBIC can be viewed as a clustering ensemble model. Different clustering algorithms are selected as baseline algorithms and assigned unique ranks depending on well-known clustering scores to be fed as input to RBIC. In the online phase, the users’ location is estimated using machine learning (ML) classifiers based on the dynamic received signal strength indicator (RSSI) vector received through its handheld device transceiver. The system is evaluated with three benchmark datasets for WiFi based indoor localization. For the first dataset, JUIndoorLoc, 94% to 99% localization accuracy is achieved for individual supervised classifiers. For the second and third datasets, the ranges of obtained localization accuracies are 96% to 99% and 95% to 98% respectively.

LRT-CLUSTER: A New Clustering Algorithm Based on Likelihood Ratio Test to Identify Driving Genes.

Somatic mutations often occur at high relapse sites in protein sequences, which indicates that the location clustering of somatic missense mutations can be used to identify driving genes. However, the traditional clustering algorithm has such problems as the background signal over-fitting, the clustering algorithm is not suitable for mutation data, and the performance of identifying low-frequency mutation genes needs to be improved. In this paper, we propose a linear clustering algorithm based on likelihood ratio test knowledge to identify driver genes. In this experiment, firstly, the polynucleotide mutation rate is calculated based on the prior knowledge of likelihood ratio test. Then, the simulation data set is obtained through the background mutation rate model. Finally, the unsupervised peak clustering algorithm is used to, respectively, evaluate the somatic mutation data and the simulation data to identify the driver genes. The experimental results show that our method achieves a better balance of precision and sensitivity. It can also identify the driver genes missed by other methods, making it an effective supplement to other methods. We also discover some potential linkages between genes and between genes and mutation sites, which is of great value to target drug therapy research. Method framework: Our proposed model framework is as follows. a. Counting mutation sites and the number of mutations in tumor gene elements. b. The nucleotide context mutation frequency is counted based on the likelihood ratio test knowledge, and the background mutation rate model is obtained. c. Based on Monte Carlo simulation method, data sets with the same number of mutations as gene elements are randomly sampled to obtain simulated mutation data, and the sampling frequency of each mutation site is related to the mutation rate of polynucleotide. d. The original mutation data and the simulated mutation data after random reconstruction are clustered by peak density, respectively, and the corresponding clustering scores are obtained. e. We can obtain the clustering information statistics in each gene segment and score of each gene segment from the original single nucleotide mutation data through step d. f. According to the observed score and the simulated clustering score, the p-value of the corresponding gene fragment is calculated. g. We can obtain the clustering information statistics in each gene segment and score of each gene segment from the simulated single nucleotide mutation data through step d.

Prenatal Predictors of Performance on the Brazelton Neonatal Behavioral Assessment Scale

The present study presents a prospective analysis of the interrelationships among prenatal medical, nutritional (dietary and biochemical) and behavioral determinants of Brazelton performance. Previous researchers (Scanlon 1984, Lester and Brazelton 1984) have raised questions regarding the relative roles of medical factors, nutrition, ponderal index and other behavioral factors in neonatal performance on the BNBAS. Four hundred sixty-seven predominantly Black nulliparous women and their neonates in Washington, D.C. who were enrolled in the study by the 20th week of gestation were subjects. Results of univariate tests of significant (P < 0.01) association between independent variables and Brazelton clusters from scores measured on day 2 are presented. The 26 behavioral items were summarized into 6 clusters as done in similar studies by linearizing measures made on a curvilinear scale and taking the mean. The 6 behavioral clusters are habituation, motor, orientation, range of states, regulation of states, and autonomic. Results of 16 reflex tests are used to define a seventh reflex cluster. Independent variables included demographic, lifestyle, nutritional, medical, ponderal index, and psychosocial measures. Several psychosocial variables, including stress, anxiety and partner interaction were associated with the behavioral clusters. Nutritional variables were associated with BNBAS habituation, motor, orientation, reflex score and autonomic responses. An analysis of co-variance was performed to determine the joint effect of the above variables on the variation in the Brazelton performance on the seven cluster scores. Five of the seven models (orientation, motor, range of states, autonomic, and reflex scores) were significant predictors of the outcome variables.

Moderate-to-vigorous physical activity, but not sedentary time, predicts changes in cardiometabolic risk factors in 10-y-old children: the Active Smarter Kids Study

Background: Cross-sectional data have suggested an inverse relation between physical activity and cardiometabolic risk factors that is independent of sedentary time. However, little is known about which subcomponent of physical activity may predict cardiometabolic risk factors in youths. Objective: We examined the independent prospective associations between objectively measured sedentary time and subcomponents of physical activity with individual and clustered cardiometabolic risk factors in healthy children aged 10 y. Design: We included 700 children (49.1% males; 50.9% females) in which sedentary time and physical activity were measured with the use of accelerometry. Systolic blood pressure, waist circumference (WC), and fasting blood sample (total cholesterol, high-density lipoprotein cholesterol, triglycerides, glucose, fasting insulin) were measured with the use of standard clinical methods and analyzed individually and as a clustered cardiometabolic risk score standardized by age and sex (z score). Exposure and outcome variables were measured at baseline and at follow-up 7 mo later. Results: Sedentary time was not associated with any of the individual cardiometabolic risk factors or clustered cardiometabolic risk in prospective analyses. Moderate physical activity at baseline predicted lower concentrations of triglycerides (P = 0.021) and homeostatic model assessment for insulin resistance (P = 0.027) at follow-up independent of sex, socioeconomic status, Tanner stage, monitor wear time, or WC. Moderate-to-vigorous physical activity (P = 0.043) and vigorous physical activity (P = 0.028) predicted clustered cardiometabolic risk at follow-up, but these associations were attenuated after adjusting for WC. Conclusions: Physical activity, but not sedentary time, is prospectively associated with cardiometabolic risk in healthy children. Public health strategies aimed at improving children’s cardiometabolic profile should strive for increasing physical activity of at least moderate intensity rather than reducing sedentary time. This trial was registered at clinicaltrials.gov as NCT02132494.