Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of cell wall stress to characterize σ22 (AlgT/U) activation by regulated proteolysis and its regulon in Pseudomonas aeruginosa

MucA sequesters extracytoplasmic function (ECF) σ22 (algT/U encoded) from target promoters including PalgD for alginate biosynthesis. We have shown that cell wall stress (e.g. d‐cycloserine) is a potent inducer of the algD operon. Here we showed that MucB, encoded by the algT‐mucABCD operon, interacts with MucA in the sigma–sequestration complex. We hypothesized that AlgW protease (a DegS homologue) is activated by cell wall stress to cleave MucA and release σ22. When strain PAO1 was exposed to d‐cycloserine, MucA was degraded within just 10 min, and σ22 was activated. However, in an algW mutant, MucA was stable with no increased σ22 activity. Studies on a yaeL mutant, defective in an RseP/YaeL homologue, suggest that YaeL protease cleaves MucA only after cleavage by AlgW. A defect in mucD, encoding a periplasmic HtrA/DegP homologue, caused MucA instability, suggesting MucD degrades cell wall stress signals. Overall, these data indicate that cell wall stress signals release σ22 by regulated intramembrane proteolysis (RIP). Microarray analyses identified genes of the early and late cell wall stress stimulon, which included genes for alginate production. The subset of genes in the σ22 regulon was then determined, which included gene products predicted to contribute to recovery from cell wall stress.
Ensembles of exemplar-SVMs for video face recognition from a single sample per person

Recognizing the face of target individuals in a watch-list is among the most challenging applications in video surveillance, especially when enrollment is based on one reference still facial image. Besides the limited representativeness of facial models used for matching, the appearance of faces captured in videos varies due to changes in illumination, pose, scales, etc., and to camera inter-operability. A multi-classifier system is proposed in this paper for robust still-to-video face recognition (FR) based on multiple diverse face representations. An individual-specific ensemble of exemplar-SVMs (e-SVMs) classifiers is assigned to each target person, where each classifier is trained using a high-quality reference face still versus many lower-quality faces of non-target individuals captured in videos. Diverse face representations are generated from different patches isolated in facial images and face descriptors that are robust to various nuisance factors (e.g., illumination and pose) commonly encountered in surveillance environments. Discriminant feature subsets, training samples, and ensemble fusion functions are selected using faces of non-target individuals captured in videos of the scene. Experiments on videos from the Chokepoint dataset reveal that the proposed ensemble of e-SVMs outperforms state-of-the-art FR systems specialized for the single sample per person problem.
Impairment in Cytotoxicity and Expression of NK Cell- Activating Receptors on Human NK Cells following Exposure to Asbestos Fibers

Asbestos is well-known for its tumorigenic activity, but its effect on anti-tumor immunity remains unclear. Therefore, we prepared a sub-line of YT-A1 human NK cells exposed to chrysotile B (CB) asbestos (YT-CB5) as an in vitro model to analyze the effect of asbestos exposure on NK cells, and examined cytotoxicity and expressions of its related molecules. The cytotoxicity of YT-CB5 against K562 cells decreased compared with the original line of YT-A1 (YT-Org). YT-CB5 exhibited significant decreases in expressions of cell surface NKG2D, 2B4 and intracellular granzyme A. YT-CB5 also exhibited a decrease in the 2B4-dependent cytotoxicity. In addition, the degranulations stimulated via cell surface NKG2D and 2B4 also decreased in YT-CB5. Therefore, peripheral blood NK cells in patients with malignant mesothelioma (MM) were examined and compared with healthy volunteers. NK cells in patients with MM also showed decreases in cytotoxicity against K562. Although the expressions of NKG2D and 2B4 did not decrease in NK cells of MM patients, the expression of cell surface NKp46 decreased. To confirm the effect of asbestos exposure on peripheral blood NK cells, PBMCs were cultured under exposure to CB. NK cells in PBMCs exposed to CB in vitro showed a significant decrease in the expression of NKp46, whereas NK cells in PBMCs exposed to glass wool did not show such a decrease. These results indicate that exposure to asbestos has the potential to impair the cytotoxicity of NK cells and alter the expression of NK cell-activating receptors including NKG2D, 2B4 and NKp46 and intracellular perforin/granzymes.
Inflation and deflation at the steep‐sided Llaima stratovolcano (Chile) detected by using InSAR

Llaima volcano, Chile, is a typical basaltic‐to‐andesitic stratovolcano in the southcentral Andes. Llaima had at least four explosive eruptions in the decade 2000 – 2010, however little is known about the physical processes and magma storage at this volcano. In this study we present an InSAR deformation field at Llaima from 2003 – 2008, covering both the post‐eruptive and syn‐eruptive periods. The satellite InSAR data are significantly affected by environmental decorrelation due to steep topography, snow and vegetation; because of this, we applied a model‐assisted phase unwrapping approach. The analysis of these data suggests two main deformation episodes: subsidence associated with the post‐eruptive period, and uplift associated with the syn‐eruptive period. Maximum summit subsidence and uplift are ∼10 cm and ∼8 cm, respectively. Through inverse modeling of both periods, a deflating and inflating magma body can be inferred, located at a depth of 4 – 12 km, subject to a volume decrease of 10 – 46 × 106 m3 during the subsidence period, followed by a volume increase of 6 – 20 × 106 m3 during the uplift period. Therefore, this study presents the first evidence of magma‐driven deformation at Llaima volcano, and suggests that eruption periods are associated with the inflation and deflation of a deep magma body that can be monitored by using space geodesy.
Correctness witnesses: exchanging verification results between verifiers

Standard verification tools provide a counterexample to witness a specification violation, and, since a few years, such a witness can be validated by an independent validator using an exchangeable witness format. This way, information about the violation can be shared across verification tools and the user can use standard tools to visualize and explore witnesses. This technique is not yet established for the correctness case, where a program fulfills a specification. Even for simple programs, it is often difficult for users to comprehend why a given program is correct, and there is no way to independently check the verification result. We close this gap by complementing our earlier work on violation witnesses with correctness witnesses. While we use an extension of the established common exchange format for violation witnesses to represent correctness witnesses, the techniques for producing and validating correctness witnesses are different. The overall goal to make proofs available to engineers is probably as old as programming itself, and proof-carrying code was proposed two decades ago --- our goal is to make it practical: We consider witnesses as first-class exchangeable objects, stored independently from the source code and checked independently from the verifier that produced them, respecting the important principle of separation of concerns. At any time, the invariants from the correctness witness can be used to reconstruct a correctness proof to establish trust. We extended two state-of-the-art verifiers, CPAchecker and Ultimate Automizer, to produce and validate witnesses, and report that the approach is promising on a large set of verification tasks.
Identification of RFID tags in dynamic framed slotted Aloha

Passive RFID tags, which have no self-battery and just backscatter the energy from a reader, share a common channel. It causes a tag-to-tag collision problem when at least two or more tags communicate to the reader simultaneously. The dynamic frame slotted Aloha (DFS-Aloha) protocol is one of the well-known anti-collision algorithms to solve this problem. To maximize the system performance and enhance the reading speed of Aloha protocols, we propose a frame-size estimator which is a modified version of Q-algorithm. To maximize the system performance, the maximum system efficiency value is used by mathematical model of DFS-Aloha. Simulation results show that the proposed estimation algorithm enhances the system performance. The proposed estimation algorithm takes less identification time than DFS-Aloha with the existing Q-Algorithm based on EPC Class 1 Generation 2 protocol.
The role of three‐dimensional information in health care and medical education: The implications for anatomy and dissection

The purposes of medical education can be summarized as learning how to take an effective history, perform a physical examination, and perform diagnostic and therapeutic procedures with minimal risk and maximal benefit to patients. Because patients are three‐dimensional (3‐D) objects, health care and medical education involve learning and applying 3‐D information. The foundation begins in anatomy where students form and confirm or reform their own 3‐D ideas and images of the development and structure of the human body at all levels of organization. Students go on to understand the interdependence of structure and function in health and disease. The basic questions for those teaching anatomy are “How do we learn and use 3‐D information? ” and “How is it taught most effectively? ” These are not easy questions for teachers and are rarely asked by those who currently defend or reframe curricula. Unfortunately, there is little information on how we learn 3‐D information and no evidence‐based literature on the relative long‐term vocational effectiveness of methods for teaching it. It is clear that we learn in several distinct modalities and that our students represent a spectrum of learning styles. To support the 3‐D learning essential to both medical education and health care, anatomical societies need to provide answers to the following questions: Do the opportunities of dissection (visual, tactile, time, discovery, group process, mentoring) contribute to short‐ and long‐term learning of 3‐D information? If so, how? Does dissection offer significant advantages over other methods for learning, confirming, and using 3‐D information in anatomy? Answers to these questions will provide a rational basis for decisions about curricular changes in anatomy courses (if, where, and when dissection should occur). This, in turn, will link these changes to society's ultimate purposes for medical education and health care rather than to the fiscal concerns of the businesses of health care and medical education, which is the current practice. Clin. Anat. 13:448–452, 2000. © 2000 Wiley‐Liss, Inc.
Gene Expression and Biological Pathways in Tissue of Men with Prostate Cancer in a Randomized Clinical Trial of Lycopene and Fish Oil Supplementation

Background Studies suggest that micronutrients may modify the risk or delay progression of prostate cancer; however, the molecular mechanisms involved are poorly understood. We examined the effects of lycopene and fish oil on prostate gene expression in a double-blind placebo-controlled randomized clinical trial. Methods Eighty-four men with low risk prostate cancer were stratified based on self-reported dietary consumption of fish and tomatoes and then randomly assigned to a 3-month intervention of lycopene (n = 29) or fish oil (n = 27) supplementation or placebo (n = 28). Gene expression in morphologically normal prostate tissue was studied at baseline and at 3 months via cDNA microarray analysis. Differential gene expression and pathway analyses were performed to identify genes and pathways modulated by these micronutrients. Results Global gene expression analysis revealed no significant individual genes that were associated with high intake of fish or tomato at baseline or after 3 months of supplementation with lycopene or fish oil. However, exploratory pathway analyses of rank-ordered genes (based on p-values not corrected for multiple comparisons) revealed the modulation of androgen and estrogen metabolism in men who routinely consumed more fish (p = 0.029) and tomato (p = 0.008) compared to men who ate less. In addition, modulation of arachidonic acid metabolism (p = 0.01) was observed after 3 months of fish oil supplementation compared with the placebo group; and modulation of nuclear factor (erythroid derived-2) factor 2 or Nrf2-mediated oxidative stress response for either supplement versus placebo (fish oil: p = 0.01, lycopene: p = 0.001). Conclusions We did not detect significant individual genes associated with dietary intake and supplementation of lycopene and fish oil. However, exploratory analyses revealed candidate in vivo pathways that may be modulated by these micronutrients. Trial Registration ClinicalTrials.gov NCT00402285
Detecting and visualizing cell phenotype differences from microscopy images using transport-based morphometry

Significance Much of what is currently known about how cells work has been derived through visual interpretation of microscopy images. Computational methods for image analysis have emerged as quantitative alternatives to visual interpretation. We describe an analysis pipeline for cell image databases that combines statistical pattern recognition with the mathematics of optimal mass transport. The approach is fully automated and does not require the use of ad hoc numerical features. It enables the identification of discriminant phenotypic variations, or biomarkers, between sets of cells (e.g., normal vs. diseased) while at the same time allowing for the visualization of meaningful differences. The approach can be used for fully automated high content screening with a variety of microscopic image modalities. Modern microscopic imaging devices are able to extract more information regarding the subcellular organization of different molecules and proteins than can be obtained by visual inspection. Predetermined numerical features (descriptors) often used to quantify cells extracted from these images have long been shown useful for discriminating cell populations (e.g., normal vs. diseased). Direct visual or biological interpretation of results obtained, however, is often not a trivial task. We describe an approach for detecting and visualizing phenotypic differences between classes of cells based on the theory of optimal mass transport. The method is completely automated, does not require the use of predefined numerical features, and at the same time allows for easily interpretable visualizations of the most significant differences. Using this method, we demonstrate that the distribution pattern of peripheral chromatin in the nuclei of cells extracted from liver and thyroid specimens is associated with malignancy. We also show the method can correctly recover biologically interpretable and statistically significant differences in translocation imaging assays in a completely automated fashion.
Selection of Negative Samples for One-class Matrix Factorization

Many recommender systems have only implicit user feedback. The two possible ratings are positive and negative, but only part of positive entries are observed. One-class matrix factorization (MF) is a popular approach for such scenarios by treating some missing entries as negative. Two major ways to select negative entries are by sub-sampling a set with similar size to that of observed positive entries or by including all missing entries as negative. They are referred to as “subsampled” and “full” approaches in this work, respectively. Currently detailed comparisons between these two selection schemes on large-scale data are still lacking. One important reason is that the “full” approach leads to a hard optimization problem after treating all missing entries as negative. In this paper, we successfully develop efficient optimization techniques to solve this challenging problem so that the “full” approach becomes practically viable. We then compare in detail the two approaches “subsampled” and “full” for selecting negative entries. Results show that the “full” approach of including much more missing entries as negative yields better results.
Inequality in the health status of workers in small-scale enterprises.

BACKGROUND Small-scale enterprises (SSEs) usually share poorer resources for promoting occupational health. AIM To investigate inequality of health status among SSEs in Japan. METHOD A cross-sectional, multiple-centred study was carried out using the periodical health check-up data for the fiscal year 2000 to compare the age-adjusted proportions of workers with hypertension (HT), hyperlipidaemia, impaired glucose tolerance (IGT) and obesity and of current smokers by size of enterprise, i.e. <or=29, 30-49, 50-99, 100-299, 300-999 and >or=1000 employees in Japan. RESULTS From five leading occupational health organizations, data were collected for 9833 enterprises with a total of 436 729 subjects, 302 383 males and 134 346 females. The proportions of workers in SSEs with <or=49 employees with HT, IGT and obesity were 8.5, 5.0 and 3.5%, respectively, higher than those in enterprises with >or=50 male employees. The prevalence of smokers in SSEs with <or=49 employees was 61%, 2-6% higher than in enterprises with >or=50 male employees. These proportions showed a significantly increasing tendency with decreasing size of male workforce. CONCLUSION Despite the cross-sectional design and only adjusting age as a potential confounder, higher proportions of HT, IGT, obesity and smoking in male workers were found in SSEs compared to larger organizations.
Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty

Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists' classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.
Effects of pneumothorax or pleural effusion on pulmonary function.

The effects of pneumothorax or pleural effusion on respiratory function as measured by the commonly applied tests were investigated by studying 13 patients (six with pneumothorax, seven with effusion) with and, as far as possible, without air or fluid in the pleural cavity. Measurements included spirometric volumes, carbon monoxide transfer factor (TLCO), and KCO by the single breath method, maximum expiratory flow-volume curves, and subdivisions of lung volume estimated by both inert gas dilution and body plethysmography. In patients with pneumothorax "pleural volume" was estimated as the difference between lung volumes measured by dilution and thoracic gas volume measured by plethysmography. In patients with effusion the change in "pleural volume" was equated with the volume of fluid subsequently aspirated. "Total thoracic capacity" (TTC) was estimated by adding total lung capacity (TLC) measured by dilution and "pleural volume. " Both effusion and pneumothorax produced a restrictive ventilatory defect with reductions of vital capacity, functional residual capacity, and TLC. In the patients with effusion TTC fell after aspiration, suggesting that the pleural fluid produced relative expansion of the chest wall as well as compression of the lung. In patients with pneumothorax, however, there was no difference in TTC with and without air in the pleural space. In the presence of pleural air or fluid there was a slight decrease in TLCO and increase in KCO, with a small but significant increase in the rate of lung emptying during forced expiration.
Estimating Impacts of Agricultural Subsurface Drainage on Evapotranspiration Using the Landsat Imagery-Based METRIC Model

Agricultural subsurface drainage changes the field hydrology and potentially the amount of water available to the crop by altering the flow path and the rate and timing of water removal. Evapotranspiration (ET) is normally among the largest components of the field water budget, and the changes in ET from the introduction of subsurface drainage are likely to have a greater influence on the overall water yield (surface runoff plus subsurface drainage) from subsurface drained (TD) fields compared to fields without subsurface drainage (UD). To test this hypothesis, we examined the impact of subsurface drainage on ET at two sites located in the Upper Midwest (North Dakota-Site 1 and South Dakota-Site 2) using the Landsat imagery-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. Site 1 was planted with corn (Zea mays L.) and soybean (Glycine max L.) during the 2009 and 2010 growing seasons, respectively. Site 2 was planted with corn for the 2013 growing season. During the corn growing seasons (2009 and 2013), differences between the total ET from TD and UD fields were less than 5 mm. For the soybean year (2010), ET from the UD field was 10% (53 mm) greater than that from the TD field. During the peak ET period from June to September for all study years, ET differences from TD and UD fields were within 15 mm ( 0.05) and showed no consistent relationship.