Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Whole-Body Operational Space Control in a Point-Foot Series Elastic Biped: Balance on Split Terrain and Undirected Walking

In this paper we present advancements in control and trajectory generation for agile behavior in bipedal robots. We demonstrate that Whole-Body Operational Space Control (WBOSC), developed a few years ago, is well suited for achieving two types of agile behaviors, namely, balancing on a high pitch split terrain and achieving undirected walking on flat terrain. The work presented here is the first implementation of WBOSC on a biped robot, and more specifically a biped robot with series elastic actuators. We present and analyze a new algorithm that dynamically balances point foot robots by choosing footstep placements. Dealing with the naturally unstable dynamics of these type of systems is a difficult problem that requires both the controller and the trajectory generation algorithm to operate quickly and efficiently. We put forth a comprehensive development and integration effort: the design and construction of the biped system and experimental infrastructure, a customization of WBOSC for the agile behaviors, and new trajectory generation algorithms. Using this custom built controller, we conduct, for first time, an experiment in which a biped robot balances in a high pitch split terrain, demonstrating our ability to precisely regulate internal forces using force sensing feedback techniques. Finally, we demonstrate the stabilizing capabilities of our online trajectory generation algorithm in the physics-based simulator and through physical experiments with a planarized locomotion setup.
Cooperative Edge Caching in User-Centric Clustered Mobile Networks

With files proactively stored at base stations (BSs), mobile edge caching enables direct content delivery without remote file fetching, which can reduce the end-to-end delay while relieving backhaul pressure. To effectively utilize the limited cache size in practice, cooperative caching can be leveraged to exploit caching diversity, by allowing users served by multiple base stations under the emerging user-centric network architecture. This paper explores delay-optimal cooperative edge caching in large-scale user-centric mobile networks, where the content placement and cluster size are optimized based on the stochastic information of network topology, traffic distribution, channel quality, and file popularity. Specifically, a greedy content placement algorithm is proposed based on the optimal bandwidth allocation, which can achieve $(1-{1/e})$ -optimality with linear computational complexity. In addition, the optimal user-centric cluster size is studied, and a condition constraining the maximal cluster size is presented in explicit form, which reflects the tradeoff between caching diversity and spectrum efficiency. Extensive simulations are conducted for analysis validation and performance evaluation. Numerical results demonstrate that the proposed greedy content placement algorithm can reduce the average file transmission delay up to 45 percent compared with the non-cooperative and hit-ratio-maximal schemes. Furthermore, the optimal clustering is also discussed considering the influences of different system parameters.
Copy Number Variants Are Enriched in Individuals With Early-Onset Obesity and Highlight Novel Pathogenic Pathways

Context Only a few genetic causes for childhood obesity have been identified to date. Copy number variants (CNVs) are known to contribute to obesity, both syndromic (15q11.2 deletions, Prader-Willi syndrome) and nonsyndromic (16p11.2 deletions) obesity. Objective To study the contribution of CNVs to early-onset obesity and evaluate the expression of candidate genes in subcutaneous adipose tissue. Design and Setting A case-control study in a tertiary academic center. Participants CNV analysis was performed on 90 subjects with early-onset obesity and 67 normal-weight controls. Subcutaneous adipose tissue from body mass index-discordant siblings was used for the gene expression analyses. Main Outcome Measures We used custom high-density array comparative genomic hybridization with exon resolution in 1989 genes, including all known obesity loci. The expression of candidate genes was assessed using microarray analysis of messenger RNA from subcutaneous adipose tissue. Results We identified rare CNVs in 17 subjects (19%) with obesity and 2 controls (3%). In three cases (3%), the identified variant involved a known syndromic lesion (22q11.21 duplication, 1q21.1 deletion, and 16p11.2 deletion, respectively), although the others were not known. Seven CNVs in 10 families were inherited and segregated with obesity. Expression analysis of 37 candidate genes showed discordant expression for 10 genes (PCM1, EFEMP1, MAMLD1, ACP6, BAZ2B, SORBS1, KLF15, MACROD2, ATR, and MBD5). Conclusions Rare CNVs contribute possibly pathogenic alleles to a substantial fraction of children with early-onset obesity. The involved genes might provide insights into pathogenic mechanisms and involved cellular pathways. These findings highlight the importance of CNV screening in children with early-onset obesity.
Cornea Differentiation Patterns of Immortalized Human Meibomian Gland Epithelial Cells in Three-Dimensional Culture

Citation: Asano N, Hampel U, Garreis F, et al. Differentiation patterns of immortalized human meibomian gland epithelial cells in three-dimensional culture. Invest Ophthalmol Vis Sci. 2018;59:1343–1353. https:// doi.org/10.1167/iovs.17-23266 PURPOSE. To establish a simplified three-dimensional (3D) meibomian gland culture model using a meibomian gland epithelial cell (HMGEC) line that might be a useful tool to gain deeper insights into meibomian gland dysfunction. For this purpose, 3D differentiation patterns and growth characteristics of HMGECs were studied on various membranes/scaffolds as well as in hanging drops.
A Role for Progesterone-Regulated sFRP4 Expression in Uterine Leiomyomas

Context: Despite progesterone's key role in uterine smooth muscle tumorigenesis, the mechanisms by which it promotes the growth of uterine leiomyomas remain poorly understood. Objective: The aim of this study was to identify gene products mediating the effects of progesterone in uterine leiomyomas. Design: Gene expression profiling was used to identify putative progesterone‐regulated genes differentially expressed in uterine leiomyomas, which were then studied in vitro. Methods: Gene expression was comprehensively profiled with the Illumina WG BeadChip (version 2.6) and analyzed with a bioinformatic algorithm that integrates known protein‐protein interactions. Genomic binding sites for progesterone receptor (PR) were interrogated by chromatin immunoprecipitation—quantitative polymerase chain reaction (ChIP‐qPCR). Small interfering RNA was used to study gene function in primary cell lines. Results: Our analyses identified secreted Frizzled‐related protein 4 (sFRP4) as a key gene product functionally linked to PR activation whose expression was 2.6 times higher in leiomyomas than myometrium (n = 26, P < 0.01) and 2.5 times higher during the proliferative phase of the menstrual cycle (n = 26, P < 0.01). Direct binding between PR and sFRP4 promoter was observed by ChIP‐qPCR. Robust overexpression of sFRP4 was also observed in primary cultures derived from leiomyoma. Progesterone preferentially inhibited sFRP4 expression and secretion in leiomyoma cultures in a dose‐dependent manner sensitized by estradiol. Knockdown of sFRP4 inhibited proliferation and apoptosis in primary cultures of both myometrium and leiomyoma. Conclusions: Overexpression of sFRP4 is a robust, progesterone‐regulated feature of leiomyomas that increases smooth muscle proliferation. More work is needed to elucidate how progesterone's ability to modulate sFRP4 expression contributes to uterine smooth muscle tumorigenesis.
The relationship of sit-to-stand tests with 6-minute walk test in healthy young adults

Abstract The aim of this study was to evaluate the timed sit-to-stand (STS) test performances of healthy young adults and to investigate the relationship of timed STS tests with 6-minute walk test (6MWT). A cross-sectional study was performed. A total of 40 healthy volunteers (mean age: 21.7 ± 1.2 years) were evaluated with 10, 30, and 60 seconds STS tests and 6MWT. Fatigue and shortness of breath were rated using Borg category-ratio scale (CR10) before and after each test. Weekly energy expenditures of volunteers were calculated using International Physical Activity Questionnaire. 30 and 60 seconds STS tests were moderately (r = 0.611 and r = 0.647, respectively) (P < .001) and 10 seconds STS test was weakly (r = 0.344) (P = .028) correlated with 6MWT. Among correlations of each STS test with 6MWT, none of them was statistically stronger to one another (P > .05). Borg fatigue scores after 10, 30, and 60 seconds STS tests were weakly correlated with fatigue score after 6MWT (r = 0.321, r = 0.378, and r = 0.405, respectively) (P < .05). Weekly energy expenditure (MET-min/week) was moderately correlated with 10, 30, and 60 seconds STS tests and 6MWT (r = 0.533, r = 0.598, r = 0.598, and r = 0.547, respectively) (P < .001). Considering the statistically significant relationship between timed STS tests and 6MWT, any of the timed STS tests may be used for a quick and alternative measurement of physical performance and functional capacity in healthy young adults.
A New Feature Vector Based on Gene Ontology Terms for Protein-Protein Interaction Prediction

Protein-protein interaction (PPI) plays a key role in understanding cellular mechanisms in different organisms. Many supervised classifiers like Random Forest (RF) and Support Vector Machine (SVM) have been used for intra or inter-species interaction prediction. For improving the prediction performance, in this paper we propose a novel set of features to represent a protein pair using their annotated Gene Ontology (GO) terms, including their ancestors. In our approach, a protein pair is treated as a document (bag of words), where the terms annotating the two proteins represent the words. Feature value of each word is calculated using information content of the corresponding term multiplied by a coefficient, which represents the weight of that term inside a document (i.e., a protein pair). We have tested the performance of the classifier using the proposed feature on different well known data sets of different species like S. cerevisiae, H. Sapiens, E. Coli, and D. melanogaster. We compare it with the other GO based feature representation technique, and demonstrate its competitive performance.
Individualized Empiric Vancomycin Dosing in Neonates Using a Model-Based Approach.

BACKGROUND Vancomycin dosing in neonates is challenging because of the large variation in pharmacokinetics. Existing empiric dosing recommendations use table-based formats, within which a neonate is categorized on the basis of underlying characteristics. The ability to individualize dosing is limited because of the small number of "dose categories," and achieving narrow exposure targets is difficult. Our objective was to evaluate a model-based dosing approach (which we designated Neo-Vanco) designed to individualize empiric vancomycin dosing in neonates. METHODS Neo-Vanco was developed on the basis of a published, externally validated population pharmacokinetic model. Using a simulation-based methodology, individualized empiric doses that maximize the probability of attaining a 24-hour area under the curve/minimum inhibitory concentration ratio (AUC24/MIC) of >400 while minimizing troughs >20 mg/L are calculated. To evaluate the Neo-Vanco strategy, retrospective data from neonates treated with vancomycin at 2 healthcare systems were used, and empiric dose recommendations from the following 4 sources were examined: Neo-Vanco, Neofax, Red Book, and Lexicomp. Predicted AUC24 and troughs were calculated and compared. RESULTS Overall, 492 neonates were evaluated (median postmenstrual age, 36 weeks [5th-95th percentiles (90% range), 25-47 weeks]; median weight, 2.4 kg [90% range, 0.6-4.8 kg]). The percentage of neonates predicted to achieve an AUC24/MIC of >400 was 94% with Neo-Vanco, 18% with Neofax, 23% with Red Book, and 55% with Lexicomp (all P < .0001 vs Neo-Vanco). Predicted troughs of >20 mg/L were infrequent and similar across the dosing approaches (Neo-Vanco, 2.8%; Neofax, 1.0% [P = . 03]; Red Book, 2.6% [P = . 99]; and Lexicomp, 4.1% [P = . 27]. CONCLUSION A model-based dosing approach that individualizes empiric vancomycin dosing was predicted to improve achievement of target exposure levels in neonates. Prospective clinical evaluation is warranted.
Coping Styles, Well-Being, and Self-Care Behaviors Among African Americans With Type 2 Diabetes

PURPOSE The purpose of this study was to describe how coping styles among African Americans with type 2 diabetes relate to diabetes appraisals, self-care behaviors, and health-related quality of life or well-being. METHODS This cross-sectional analysis of baseline measures from 185 African Americans with type 2 diabetes enrolled in a church-based randomized controlled trial uses the theoretical framework of the transactional model of stress and coping to describe bivariate and multivariate associations among coping styles, psychosocial factors, self-care behaviors, and well-being, as measured by validated questionnaires. RESULTS Among participants who were on average 59 years of age with 9 years of diagnosed diabetes, passive and emotive styles of coping were used most frequently, with older and less educated participants using more often passive forms of coping. Emotive styles of coping were significantly associated with greater perceived stress, problem areas in diabetes, and negative appraisals of diabetes control. Both passive and active styles of coping were associated with better diabetes self-efficacy and competence in bivariate analysis. In multivariate analysis, significant proportions of the variance in dietary behaviors and mental well-being outcomes (general and diabetes specific) were explained, with coping styles among the independent predictors. A positive role for church involvement in the psychological adaptation to living with diabetes was also observed. CONCLUSIONS In this sample of older African Americans with diabetes, coping styles were important factors in diabetes appraisals, self-care behaviors, and psychological outcomes. These findings suggest potential benefits in emphasizing cognitive and behavioral strategies to promote healthy coping outcomes in persons living with diabetes.
The CARINA data synthesis project: introduction and overview

Abstract. The original goal of the CARINA (Carbon in Atlantic Ocean) data synthesis project was to create a merged calibrated data set from open ocean subsurface measurements by European scientists that would be generally useful for biogeochemical investigations in the North Atlantic and in particular, studies involving the carbon system. Over time the geographic extent expanded to include the entire Atlantic, the Arctic and the Southern Ocean and the international collaboration broadened significantly. In this paper we give a brief history of the project, a general overview of data included and an outline of the procedures used during the synthesis. The end result of this project was a set of 3 data products, one for each of the listed ocean regions. It is critical that anyone who uses any of the CARINA data products recognize that the data products are not simply concatenations of the originally measured values. Rather, the data have been through an extensive calibration procedure designed to remove measurement bias and bad data. Also a significant fraction of the individual values in the data products were derived either by direct calculation or some means of approximation. These data products were constructed for basin scale biogeochemical investigations and may be inappropriate for investigations involving small areal extent or similar detailed analyses. More information on specific parts of this project can be found in companion articles in this issue. In particular, Tanhua et al. (2010) and Tanhua (2009) describe the procedures and software used to remove measurement bias from the original data. The three data products and a significant volume of supporting information are available from the CARINA web site hosted by the Carbon Dioxide Information Analysis Center (CDIAC: http://cdiac.esd.ornl.gov/oceans/CARINA/Carina_inv.html ). Anyone wanting to use the data is advised to get the highest version number of each data product. Incremental versions represent either corrections or additions. The web site documents specifics of the changes.
Feasibility of a Memory Clinic-Based Physical Activity Prescription Program.

BACKGROUND Effective programs for promoting physical activity are needed for those with cognitive impairment. OBJECTIVE To test the feasibility of mobile Health (mHealth) technology-supported physical activity prescription from a tertiary care memory clinic. METHODS This feasibility study was designed as a 16-week randomized, crossover trial of a physical activity prescription: 8 weeks of intervention, 8 weeks of baseline or maintenance phase data collection. We recruited 2 cohorts: 21 individuals with Alzheimer-related cognitive impairment (mean age 72.3 (5.2), 9 females), and 9 individuals with normal cognition (mean age 69.6 (5.8), 8 females). We gave each cohort an mHealth accelerometer-based physical activity prescription to double number of steps taken. Our primary outcomes were feasibility and safety. Our secondary outcomes were change in weekly steps taken, Dementia Quality of Life Scale, Self-efficacy Scale, 6-minute Walk, and mini-Physical Performance Test. RESULTS Set-up and use of the device was not a barrier to participation. However, only 62% of participants with cognitive impairment completed the intervention. The cohort with cognitive impairment did not change their weekly step count above Week 1. All participants in the cohort with normal cognition were able to set up and use their device and increased their weekly step count above Week 1. There were no differences between Week 1 and Week 8 for any secondary measures in either cohort. CONCLUSIONS Setup and daily use of mHealth technology appears to be feasible for a person with cognitive impairment with the help of a partner, but increasing daily step counts over 8 weeks was not achieved. Future work needs to assess alternative activity prescription goals or additional support for patients and their partners.
Distamycin A Inhibits HMGA1-Binding to the P-Selectin Promoter and Attenuates Lung and Liver Inflammation during Murine Endotoxemia

Background The architectural transcription factor High Mobility Group-A1 (HMGA1) binds to the minor groove of AT-rich DNA and forms transcription factor complexes (“enhanceosomes”) that upregulate expression of select genes within the inflammatory cascade during critical illness syndromes such as acute lung injury (ALI). AT-rich regions of DNA surround transcription factor binding sites in genes critical for the inflammatory response. Minor groove binding drugs (MGBs), such as Distamycin A (Dist A), interfere with AT-rich region DNA binding in a sequence and conformation-specific manner, and HMGA1 is one of the few transcription factors whose binding is inhibited by MGBs. Objectives To determine whether MGBs exert beneficial effects during endotoxemia through attenuating tissue inflammation via interfering with HMGA1-DNA binding and modulating expression of adhesion molecules. Methodology/Principal Findings Administration of Dist A significantly decreased lung and liver inflammation during murine endotoxemia. In intravital microscopy studies, Dist A attenuated neutrophil-endothelial interactions in vivo following an inflammatory stimulus. Endotoxin induction of P-selectin expression in lung and liver tissue and promoter activity in endothelial cells was significantly reduced by Dist A, while E-selectin induction was not significantly affected. Moreover, Dist A disrupted formation of an inducible complex containing NF-κB that binds an AT-rich region of the P-selectin promoter. Transfection studies demonstrated a critical role for HMGA1 in facilitating cytokine and NF-κB induction of P-selectin promoter activity, and Dist A inhibited binding of HMGA1 to this AT-rich region of the P-selectin promoter in vivo. Conclusions/Significance We describe a novel targeted approach in modulating lung and liver inflammation in vivo during murine endotoxemia through decreasing binding of HMGA1 to a distinct AT-rich region of the P-selectin promoter. These studies highlight the ability of MGBs to function as molecular tools for dissecting transcriptional mechanisms in vivo and suggest alternative treatment approaches for critical illness.
Age‐associated B cells expanded in autoimmune mice are memory cells sharing H‐CDR3‐selected repertoires

Age‐associated B cells (ABCs) represent a distinct cell population expressing low levels of CD21 (CD21−/low). The Ig repertoire expressed by ABCs in aged mice is diverse and exhibits signs of somatic hypermutation (SHM). A CD21−/low B‐cell population is expanded in autoimmune diseases, e.g. systemic lupus erythematosus, as well as in lupus‐prone NZB/W mice and in mice lacking a pre‐B cell receptor (SLC−/−). However, the nature of the CD21−/low B cells (hereafter ABCs) in autoimmunity is not well understood. Here we show that in young SLC−/− mice, the vast majority of the ABCs express memory B‐cell (MBC) markers in contrast to wild‐type controls. A similar population is present in lupus‐prone MRL mice before and at disease onset. In SLC−/− mice, a majority of the ABCs are IgM+, their VH genes have undergone SHM, show clonal diversification and clonal restriction at the H‐CDR3 level. ABC hybridomas, established from SLC−/− mice, secrete typical lupus autoantibodies, e.g. anti‐Smith antigen, and some of those that bind to DNA comprise a H‐CDR3 that is identical to previously described IgM anti‐DNA antibodies from lupus‐prone mice. Together, these results reveal that ABCs in autoimmune mice are comprised of autoreactive MBCs expressing highly restricted H‐CDR3 repertoires.
WiHACS: Leveraging WiFi for human activity classification using OFDM subcarriers' correlation

Human Activity Classification using Wi-Fi Channel characteristics serve a diverse range of applications such as monitoring hospital patients and promoting independent living of elderly people. Current systems' key limitation is performance degradation when detecting activities across multiple walls or under non-line-of-sight (NLOS). Although their performance can be improved by engaging multiple transmitters/receivers, it creates an overhead in practical scenarios. We propose WiHACS: A Wi-Fi based Human Activity Classification based on OFDM Subcarriers' correlation, which engages a single AP and laptop. We employ correlation patterns across a particular range of subcarriers as our salient feature to detect human activities in different environments. Preliminary evaluations show WiHACS can correctly classify human activities with an average accuracy of 97%, 92%, and 75% in LOS, across one-wall and across two-walls respectively.