Miracle-dz/UniFAR-FTUs huggingface dataset:
Applications of transgenics in studies of bone sialoprotein

Bone sialoprotein (BSP) is a major non‐collagenous protein in mineralizing connective tissues such as dentin, cementum and calcified cartilage tissues. As a member of the Small Integrin‐Binding Ligand, N‐linked Glycoprotein (SIBLING) gene family of glycoproteins, BSP is involved in regulating hydroxyapatite crystal formation in bones and teeth, and has long been used as a marker gene for osteogenic differentiation. In the most recent decade, new discoveries in BSP gene expression and regulation, bone remodeling, bone metastasis, and bone tissue engineering have been achieved with the help of transgenic mice. In this review, we discuss these new discoveries obtained from the literatures and from our own laboratory, which were derived from the use of transgenic mouse mutants related to BSP gene or its promoter activity. J. Cell. Physiol. 220: 30–34, 2009. © 2009 Wiley‐Liss, Inc.
Inter‐Related Summer Vacation Choices by Swedish Tourists

Abstract The aim of our study was to investigate whether and how different vacation choices vary with respect to a number of attributes and whether there are differences in this respect depending on how familiar the tourist is with the destination. In a web‐based survey conducted in the fall of 2007, 681 Swedish residents (response rate 15%) retrospectively reported their vacation trips during the summer. The results warrant the conclusion that it is possible to rank choices of destination, departure date, primary activity, and travel mode according to primacy, importance, inflexibility, and impact on other choices. However, the different measures did not converge in identifying an invariant order of the choices. Individual and situational factors may play important roles for the order. A sequential decision‐making process was still identified for the majority of the respondents and the examined choices were to a large extent made before departure. Familiarity with the destination only had an effect on the importance and inflexibility the respondents experienced in their destination choice. Both managerial and practical implications of the findings are discussed.
The utility of body mass index as a measure of body fatness in children and adolescents: differences by race and gender.

OBJECTIVE To evaluate whether body mass index (BMI) is a representative equivalent measure of body fatness independent of age, race, gender, sexual maturation, and distribution of fat in children and adolescents. STUDY DESIGN Cross-sectional study of 192 healthy subjects (100 boys and 92 girls, 103 white and 89 black) age 7 to 17 years. Methods. Height and weight were measured in the standard fashion, and BMI (kg/m) was calculated from these values. Fat mass and percent body fat were determined using dual-energy x-ray absorptiometry. Sexual maturation was evaluated by physical assessment. Distribution of fat was determined by the waist:hip ratio. RESULTS There were no significant differences by gender and ethnic group for any of the demographic or anthropometric variables, except waist:hip ratio, which was higher in white compared with black boys. BMI was significantly and positively correlated with age, stage of maturation, and all of the anthropometric variables in each race-sex group. The correlation of maturation stage with BMI was stronger than the correlation between age and BMI. A multiple regression analysis showed that BMI, gender, race, sexual maturation, and distribution of fat were all significant independent correlates of the percent body fat (multiple R = .77). The percent body fat-BMI relationship was dependent on the stage of sexual maturation, gender (for an equivalent BMI, girls have greater amounts of body fat than boys), race (for equivalent BMI, whites have higher body fat than blacks), and waist:hip ratio (for equivalent BMI, those with central obesity have greater body fatness than those with peripheral obesity). CONCLUSION BMI is not an equivalent measure of the percent body fat for each race-sex group. When BMI is used as a measure of body fatness in a research or clinical setting, particularly when comparisons are made across race and gender, it may be important to consider the maturation stage, race, gender, and distribution of body fat in the interpretation of the results.
Potent In Vitro Antifungal Activities of Naturally Occurring Acetylenic Acids

ABSTRACT Our continuing effort in antifungal natural product discovery has led to the identification of five 6-acetylenic acids with chain lengths from C16 to C20: 6-hexadecynoic acid (compound 1), 6-heptadecynoic acid (compound 2), 6-octadecynoic acid (compound 3), 6-nonadecynoic acid (compound 4), and 6-icosynoic acid (compound 5) from the plant Sommera sabiceoides. Compounds 2 and 5 represent newly isolated fatty acids. The five acetylenic acids were evaluated for their in vitro antifungal activities against Candida albicans, Candida glabrata, Candida krusei, Candida tropicalis, Candida parapsilosis, Cryptococcus neoformans, Aspergillus fumigatus, Aspergillus flavus, Aspergillus niger, Trichophyton mentagrophytes, and Trichophyton rubrum by comparison with the positive control drugs amphotericin B, fluconazole, ketoconazole, caspofungin, terbinafine, and undecylenic acid. The compounds showed various degrees of antifungal activity against the 21 tested strains. Compound 4 was the most active, in particular against the dermatophytes T. mentagrophytes and T. rubrum and the opportunistic pathogens C. albicans and A. fumigatus, with MICs comparable to several control drugs. Inclusion of two commercially available acetylenic acids, 9-octadecynoic acid (compound 6) and 5,8,11,14-eicosatetraynoic acid (compound 7), in the in vitro antifungal testing further demonstrated that the antifungal activities of the acetylenic acids were associated with their chain lengths and positional triple bonds. In vitro toxicity testing against mammalian cell lines indicated that compounds 1 to 5 were not toxic at concentrations up to 32 μM. Furthermore, compounds 3 and 4 did not produce obvious toxic effects in mice at a dose of 34 μmol/kg of body weight when administered intraperitoneally. Taking into account the low in vitro and in vivo toxicities and significant antifungal potencies, these 6-acetylenic acids may be excellent leads for further preclinical studies.
Learning from multi metrics for stereoscopic 3D image quality assessment

Quality assessment of stereoscopic 3D images is much more complex than that of 2D images. Quality assessment metrics for 3D images have achieved good performance on symmetric distorted 3D images, while given poor performance on asymmetric distorted 3D images. To further improve the perception consistency for symmetric and asymmetric distorted 3D images, this paper presents a machine learning-based full-reference 3D image quality assessment method that learns from multi IQA metrics. Considering that changes in left view, right view and depth information all impact human perception, our method considers the quality of two views and depth information. Since symmetric and asymmetric distortions impact left and right views of a 3D image differently, we propose different features for symmetric and asymmetric distorted 3D images. The experimental results show that our method has better performance than both 2D-based 3D quality assessment metrics and the state of the art specially designed 3D quality assessment metrics.
Recursively Convolutional CFS-PML in 3-D Laguerre-FDTD Scheme for Arbitrary Media

Weighted Laguerre finite-difference time-domain (Laguerre-FDTD) method is an efficient and unconditionally stable time-domain numerical method. The complex frequency-shifted perfectly matched layer (CFS-PML) is the main absorbing boundary condition in the Laguerre-FDTD method. The implementations of CFS-PML in the Laguerre-FDTD method, which have been reported, include the use of auxiliary variables and auxiliary differential equations. These implementations make CFS-PML sensitive to its parameters and timescale parameter s of weighted Laguerre polynomials and result in potential instability and poor absorption issues in numerical simulations. In this paper, we proposed an efficient and stable implementation of CFS-PML based on recursive convolution in the Laguerre-FDTD method. The accuracy of the proposed implementation is theoretically validated. Its numerical dispersion is theoretically derived for choosing the key parameters of CFS-PML in the Laguerre-FDTD scheme. The numerical dispersion demonstrates that the timescale factor s needs to match the simulated signal frequency and the CFS-PML parameter $\alpha $ is chosen as $0.5s\varepsilon _{0}$ to obtain the minimum dispersive error. Numerical examples validate the theoretical predictions and verify that the proposed implementation of CFS-PML is robust and retains the advantages of CFS-PML in classical FDTD method, such as effectively absorbing evanescent as well as guided waves. It requires nonsplits of electromagnetic field components, no auxiliary variables, and no modifications when applying it to inhomogeneous, lossy, and dispersive media. The CFS-PML formulas can directly be converted into computer codes of the Laguerre-FDTD method.
Painful Hemiplegic Shoulder

Shoulder pain resulting from hemiplegia is a common clinical consequence of a focal cerebral insult resulting from a vascular lesion (ie. hemorrhagic or ischemic stroke). Painful hemiplegic shoulder can occur as early as 2 weeks post stroke but an onset time of 2-3 months post stroke is more typical. Shoulder pain can negatively affect rehabilitation outcomes as good shoulder function is a prerequisite for successful transfers, maintaining balance, performing activities of daily living and for effective hand function. Similarly, complex regional pain syndrome is pervasive in hemiplegic patients and can lead to significant medical complications. This review summarizes the existing literature with regard to hemiplegic shoulder pain after stroke. Topics include causes and management of hemiplegic shoulder pain with in-depth discussion of shoulder subluxation, spasticity, contractures, and rotator cuff disorders. Management techniques including shoulder positioning, slings and aids, surgical interventions, injections, and electrical stimulation along with other miscellaneous treatments are addressed. Finally, a full discussion of the physiology, incidence, and treatment of shoulder hand syndrome is included.
Exploration of the Conformational Dynamics of Major Histocompatibility Complex Molecules

Major histocompatibility complex (MHC) molecules are loaded with a wide variety of self- and non-self-peptides in their binding grooves and present these to T cell receptors (TCRs) in order to activate the adaptive immune system. A large number of crystal structures of different MHC alleles with different bound peptides have been determined, and they have been found to be quite similar to one another regardless of the bound peptide sequence. The structures do not change markedly even when forming complexes with TCRs. Nonetheless, the degree of TCR activation does differ markedly depending on the peptide presented by the MHC. Recent structural studies in solution rather than as crystals have suggested that the conformational dynamics of MHC molecules may be responsible for the MHC stability differences. Furthermore, it was shown that the conformational dynamics of MHC molecules is important for peptide loading and presentation to TCR. Here, we describe the static and dynamic structures of MHC molecules and appropriate methods to analyze them. We focus particularly on nuclear magnetic resonance (NMR), one of the most powerful tools to study dynamic properties of proteins. The number of such studies in the literature is limited, but in this review, we show that NMR is valuable for elucidating the structural dynamics of MHC molecules.
Domination Cover Number of Graphs

A set [Formula: see text] for the graph [Formula: see text] is called a dominating set if any vertex [Formula: see text] has at least one neighbor in [Formula: see text]. Fomin et al. [Combinatorial bounds via measure and conquer: Bounding minimal dominating sets and applications, ACM Transactions on Algorithms (TALG) 5(1) (2008) 9] gave an algorithm for enumerating all minimal dominating sets with [Formula: see text] vertices in [Formula: see text] time. It is known that the number of minimal dominating sets for interval graphs and trees on [Formula: see text] vertices is at most [Formula: see text]. In this paper, we introduce the domination cover number as a new criterion for evaluating the dominating sets in graphs. The domination cover number of a dominating set [Formula: see text], denoted by [Formula: see text], is the summation of the degrees of the vertices in [Formula: see text]. Maximizing or minimizing this parameter among all minimal dominating sets has interesting applications in many real-world problems, such as the art gallery problem. Moreover, we investigate this concept for different graph classes and propose some algorithms for finding the domination cover number in trees and block graphs.
Chlamydial pneumonitis induced in newborn guinea pigs

One- to three-day-old guinea pigs were inoculated intranasally with the chlamydial agent of guinea pig inclusion conjunctivitis. Physical signs of infection included a marked increase in respiration rate on days 5 to 10 of infection and radiographic evidence of pneumonia on day 6. When animals were killed at various times after infection and lung tissue was examined by histopathology, evidence of pneumonia was found beginning on day 4 and lasting as long as day 12, with maximal pathological changes on days 6 to 8. The pneumonia was generally unilateral and consisted of an acute inflammatory component in the bronchioles with granulocytes in both the lumen and the wall of the bronchioles and an interstitial and intra-alveolar mononuclear infiltrate in the parenchyma of the lung. Chlamydial antigen was detected in the bronchial epithelial cells by immunoperoxidase staining, and the guinea pig inclusion conjunctivitis organism was isolated from lung tissue on days 6 to 9. No other significant bacteria were isolated from lung tissue or seen on gram stains of lung sections. Both immunoglobulin M and immunoglobulin G serum antibodies to the guinea pig inclusion conjunctivitis agent were detected as early as day 8 and reached peak levels on day 12. The infection was apparently self-limiting. This model presents the opportunity to investigate pathophysiological and immunological aspects of chlamydial respiratory infections in a neonatal animal.
Word Spotting in Silent Lip Videos

Our goal is to spot words in silent speech videos without explicitly recognizing the spoken words, where the lip motion of the speaker is clearly visible and audio is absent. Existing work in this domain has mainly focused on recognizing a fixed set of words in word-segmented lip videos, which limits the applicability of the learned model due to limited vocabulary and high dependency on the model's recognition performance. Our contribution is two-fold: 1) we develop a pipeline for recognition-free retrieval, and show its performance against recognition-based retrieval on a large-scale dataset and another set of out-of-vocabulary words. 2) We introduce a query expansion technique using pseudo-relevant feedback and propose a novel re-ranking method based on maximizing the correlation between spatio-temporal landmarks of the query and the top retrieval candidates. Our word spotting method achieves 35% higher mean average precision over recognition-based method on large-scale LRWdataset. Finally, we demonstrate the application of the method by word spotting in a popular speech video ("The great dictator" by Charlie Chaplin) where we show that the word retrieval can be used to understand what was spoken perhaps in the silent movies.
Evolutionary forces affecting synonymous variations in plant genomes

Base composition is highly variable among and within plant genomes, especially at third codon positions, ranging from GC-poor and homogeneous species to GC-rich and highly heterogeneous ones (particularly Monocots). Consequently, synonymous codon usage is biased in most species, even when base composition is relatively homogeneous. The causes of these variations are still under debate, with three main forces being possibly involved: mutational bias, selection and GC-biased gene conversion (gBGC). So far, both selection and gBGC have been detected in some species but how their relative strength varies among and within species remains unclear. Population genetics approaches allow to jointly estimating the intensity of selection, gBGC and mutational bias. We extended a recently developed method and applied it to a large population genomic datasets based on transcriptome sequencing of 11 angiosperm species spread across the phylogeny. We found that base composition is far from mutation-drift equilibrium in most genomes and that gBGC is a widespread and stronger process than selection. gBGC could strongly contribute to base composition variation among plant species, implying that it should be taken into account in plant genome analyses, especially for GC-rich ones.
Preoperative hemoglobin-platelet ratio can significantly predict progression and mortality outcomes in patients with T1G3 bladder cancer undergoing transurethral resection of bladder tumor

Objective To investigate the prognostic role of hematological biomarkers, especially hemoglobin-platelet ratio (HPR) in the oncological outcomes in stage 1 and grade 3 (T1G3) bladder cancer. Materials and Methods We identified 457 T1G3 bladder cancer patients who underwent transurethral resection of the bladder (TURB) between 2009 and 2014. Based on hematological parameters (hemoglobin-platelet ratio (HPR), hemoglobin, and platelet counts), recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS) and cancer-specific survival (CSS) were analyzed by using Kaplan-Meier analysis. Multivariate Cox regression model was adopted to identify the predictors of oncological outcomes. Results Kaplan-Meier survival analysis showed that low HPR (< 0.615), low hemoglobin (< 125g/l) and elevated platelet counts (> 240 × 103/μl) were correlated with poor OS. Low HPR, but not low hemoglobin and high platelet counts, is associated with worse PFS. Low HPR and low hemoglobin, but not elevated platelet counts, are associated with worse CSS. However, no significant difference was observed in RFS according to any of these hematological markers. On multivariate analysis, low HPR (HR = 1.27, 95% CI = 0.81–1.75, P = 0.030), low hemoglobin (HR = 1.20, 95% CI = 0.79–1.84, P = 0.028) and elevated platelet counts (HR = 1.07, 95% CI = 0.72–1.32, P = 0.038) were significantly associated with OS. Low hemoglobin (HR = 1.08, 95% CI = 0.68–1.82, P = 0.041) was significantly linked with CSS. Particularly, low HPR was identified as an independent predictor of PFS (HR = 1.16, 95% CI = 0.97–1.49, P = 0.033) and CSS (HR = 1.14, 95% CI = 0.87–1.78, P = 0.029). Conclusions Preoperative HPR can be taken into account as a factor predictive of oncological outcomes for T1G3 bladder cancer, particularly disease progression and mortality outcomes.
MODELING FARMERS PREFENCES FOR AGRIENVIRONMENTAL SCHEME DESIGN: A SPANISH CASE STUDY

Agri-environmental schemes (AES) have had a limited effect on European agriculture due to farmer’s reluctance to participate in them. Information on the role that AES design can have on encouraging farmers to participate can be an important input into the design of such policies. This paper investigates farmers’ preferences for different design options related to a specific AES in Spain using a mixed logit error component choice experiment approach allowing for preference heterogeneity and correlation amongst the non status quo alternatives. In particular, findings show farmers preference for greater flexibility in scheme implementation, presence of a fixed-rate payment per contract and additional advisory services. However, heterogeneity in the value of the AES attributes across regions and farmers is significant. The results show that there is room for improvement in current AES design that will lead to higher adoption rates however, farmer reluctance to AES sign-up is still substantial.
Time- and coefficient- selective diffusion strategies for distributed parameter estimation

We present an innovative approach to distributed estimation, featuring selective update of parameter estimates. In distributed parameter estimation, sensor nodes consume energy not only in processing data, but most costly, in communicating and diffusing updated parameter estimates. Reducing the number of parameters to be updated and reducing the frequency of updates are thus effective ways to save in energy consumption. The approach presented in this paper features advantages of set-membership adaptive filtering (SMAF) and those of partial updates in adaptive filtering. Simulation results show that the proposed algorithm offers substantial reduction in energy consumption without much, if any, performance degradation.
Characterization of Subgrid-Scale Variability in Particulate Matter with Respect to Satellite Aerosol Observations

Recent use of satellite observations of aerosol optical depth (AOD) to characterize surface concentrations of particulate matter (PM) air pollution has proven extremely valuable in estimating exposures for health effects studies. While the spatial resolutions of satellite data provide far better coverage than existing fixed site surface monitoring stations, they are not able to capture atmospheric processes such as dilution of primary pollutants that vary at small spatial scales. As a result, small-scale variability due to highly localized sources such as traffic may be poorly represented, which in turn may lead to exposure measurement error in epidemiological analyses. Using a fixed spatial grid representing 4.4 km Multiangle Imaging SpectroRadiometer (MISR) aerosol observations, we examined the spatial variability in fine and coarse mode PM (PM2.5 and PM2.5–10 respectively) measured at ground monitors from a unique spatially-dense sampling campaign in Southern California. We found that while the variance in measured PM2.5 differed seasonally (warm 6.82 μg2/m6 and cool 24.5 μg2/m6) across the study region, the average subgrid (<4.4 km) variance did not (warm 2.03 μg2/m6 and cool 2.43 μg2/m6) and was significantly smaller. On the other hand, ground monitor PM2.5–10 concentrations showed large variance in warm (18.6 μg2/m6) and cool (20.6 μg2/m6) seasons, as well as seasonal differences in subgrid variance (warm 8.90 μg2/m6 and cool 3.28 μg2/m6). Geostatistical analysis of the semivariance as a function of distance indicated that variability in measured PM2.5 and PM2.5–10 concentrations was relatively constant for spatial scales of one to five kilometers, but there was evidence of small-scale (~500 m) variability in PM2.5–10 concentrations in the cool season. The lack of small-scale spatial variability in the warm season was likely due to large photochemical contributions to regional PM2.5, and greater regional contributions to PM2.5–10 from windblown dust. In contrast, in the cool season there tends to be greater localized concentrations from primary traffic sources due to stronger nocturnal inversions and delayed morning winds reducing dilution that contribute to greater spatial heterogeneity. Overall, these results suggest that regional contributions tend to dominate PM2.5, and spatial resolutions of satellite observations including the 4.4 km MISR and 3 km MODIS aerosol products aptly capture relevant spatial variability. Coarse PM2.5–10 can have seasonally dependent localized contributions, leading to small-scale variability below current satellite aerosol product resolutions.