Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling the Emergence of Antibiotic Resistance in the Environment: an Analytical Solution for the Minimum Selection Concentration

ABSTRACT Environmental antibiotic risk management requires an understanding of how subinhibitory antibiotic concentrations contribute to the spread of resistance. We develop a simple model of competition between sensitive and resistant bacterial strains to predict the minimum selection concentration (MSC), the lowest level of antibiotic at which resistant bacteria are selected. We present an analytical solution for the MSC based on the routinely measured MIC, the selection coefficient (sc) that expresses fitness differences between strains, the intrinsic net growth rate, and the shape of the bacterial growth dose-response curve with antibiotic or metal exposure (the Hill coefficient [κ]). We calibrated the model by optimizing the Hill coefficient to fit previously reported experimental growth rate difference data. The model fit varied among nine compound-taxon combinations examined but predicted the experimentally observed MSC/MIC ratio well (R2 ≥ 0.95). The shape of the antibiotic response curve varied among compounds (0.7 ≤ κ ≤ 10.5), with the steepest curve being found for the aminoglycosides streptomycin and kanamycin. The model was sensitive to this antibiotic response curve shape and to the sc, indicating the importance of fitness differences between strains for determining the MSC. The MSC can be >1 order of magnitude lower than the MIC, typically by the factor scκ. This study provides an initial quantitative depiction and a framework for a research agenda to examine the growing evidence of selection for resistant bacterial communities at low environmental antibiotic concentrations.
Phenotypic and Genetic Divergence among Poison Frog Populations in a Mimetic Radiation

The evolution of Müllerian mimicry is, paradoxically, associated with high levels of diversity in color and pattern. In a mimetic radiation, different populations of a species evolve to resemble different models, which can lead to speciation. Yet there are circumstances under which initial selection for divergence under mimicry may be reversed. Here we provide evidence for the evolution of extensive phenotypic divergence in a mimetic radiation in Ranitomeya imitator, the mimic poison frog, in Peru. Analyses of color hue (spectral reflectance) and pattern reveal substantial divergence between morphs. However, we also report that there is a “transition-zone” with mixed phenotypes. Analyses of genetic structure using microsatellite variation reveals some differentiation between populations, but this does not strictly correspond to color pattern divergence. Analyses of gene flow between populations suggest that, while historical levels of gene flow were low, recent levels are high in some cases, including substantial gene flow between some color pattern morphs. We discuss possible explanations for these observations.
Management of severe complications in Behçet’s disease with TNF inhibitors

ABSTRACT Introduction: The efficacy of anti-TNFα agents has been recently evaluated in many studies in Behçet’s disease (BD), particularly in ocular and life-threatening manifestations such as neurological and vascular disease. Areas covered: The following article aims to summarize the currently available efficacy and safety data of anti-TNFα agents in BD. Expert opinion: Most studies have shown dramatic and rapid efficacy with anti-TNFα agents on the main BD-associated issues including posterior uveitis, gastro-intestinal and neurological complications as well as major vessel disease. Experts in the field do recommend the use of anti-TNF agents (either infliximab or adalimumab) as a first-line therapy in severe posterior uveitis in BD and now use anti-TNFα treatment in BD-associated life threatening manifestations. However, data is mainly based on retrospective cohorts or open-label prospective studies. Controlled studies (versus conventional immunosuppressants such as azathioprine and cyclophosphamide) are warranted to properly evaluate their efficacy as first line therapeutic in life-threatening manifestations of BD.
Chapter 3 Functional architecture of posterior parietal cortex during tactile sensorimotor behavior ( in preparation )

The posterior parietal cortex (PPC) in rodents is reciprocally connected to primary somatosensory cortex (S1) and vibrissal motor area (M2). PPC could thus bridge incoming sensory information to motor output but the cellular activity map across PPC layers during sensorimotor whisker behavior remains largely unknown. To uncover the functional architecture in PPC during active tactile processing, we performed single unit and ensemble recordings across cytoarchitectonic layers of PPC in anaesthetized and awake, behaving rats. In urethane-anaesthetized rats, mechanical (passive) whisker stimulation for receptive field measurements reveal whisker-related somatotopy, resembling S1 architecture but at lower spatial resolution. Juxtasomal single unit and silicon probe ensemble recordings in awake, behaving rats during whisking reveal efferent copy coding in PPC, reflected as increased spiking activity in PPC during self-induced exploratory whisking. Efferent copy encoding is layer-specific since spiking activity in superficial and deep layers is increased during free whisking, but not in middle layers. Furthermore, spiking activity in superficial and deep layers is tuned to whisker protraction in contrast to middle layers, where spiking is tuned to whisker retraction. Active object touch further induces spiking activity in individual units, indicating the integration of both efferent copy and ex-afference signals, and again, this integration is restricted to superficial and deep PPC layers. The cellular activity map of PPC during active tactile behavior therefore indicates layer-specific encoding of selfgenerated whisker movements and ex-afference information. We put forward the hypothesis that superficial and deep PPC layers serve as an integrative hub bridging sensory encoding in the PPC-S1 loop and motor output in the PPC-M2 projection.
Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and Its Variance Estimate

Abstract In this article, we propose using the principle of boosting to reduce the bias of a random forest prediction in the regression setting. From the original random forest fit, we extract the residuals and then fit another random forest to these residuals. We call the sum of these two random forests a one-step boosted forest. We show with simulated and real data that the one-step boosted forest has a reduced bias compared to the original random forest. The article also provides a variance estimate of the one-step boosted forest by an extension of the infinitesimal Jackknife estimator. Using this variance estimate, we can construct prediction intervals for the boosted forest and we show that they have good coverage probabilities. Combining the bias reduction and the variance estimate, we show that the one-step boosted forest has a significant reduction in predictive mean squared error and thus an improvement in predictive performance. When applied on datasets from the UCI database, one-step boosted forest performs better than random forest and gradient boosting machine algorithms. Theoretically, we can also extend such a boosting process to more than one step and the same principles outlined in this article can be used to find variance estimates for such predictors. Such boosting will reduce bias even further but it risks over-fitting and also increases the computational burden. Supplementary materials for this article are available online.
Multifractal analysis of mercury inclusions in quartz by X-ray computed tomography

T. Shibata, T. Maruoka, and T. Echigo Geological Survey of Hokkaido, Hokkaido Research Organization, N19 W12, Kita-ku, Sapporo, Hokkaido 060-0819, Japan Institute for Geothermal Sciences, Graduate School of Science, Kyoto University, Noguchibaru 3088, Beppu, Oita 874-0903, Japan Graduate School of Life and Environmental Sciences, University of Tsukuba, Tennodai 1-1-1, Tsukuba, Ibaraki 305-8572, Japan Department of Natural Science, Faculty of Education, Shiga University, Hiratsu 2-5-1, Otsu, Shiga 520-0862, Japan
Facile fabrication of novel polycaprolactone-based electrospun fibers using in-process water exposure

ABSTRACT To overcome the problems related to the low surface enrichment of blended fibers from hydrophilic polymer, routine blend electrospinning setup was modified by exposing the polycaprolactone (PCL)–Pluronic P123 solution to water in order to attract the hydrophilic chains toward the fiber surface. Analysis of the modified fibers revealed a drastic surge of hydrophilic polymer surface enrichment value in comparison with that of the routine method which suggested homogenously positioned Pluronic on the surface and the subsequent reduction of its accumulations within fibers. The thermogram of the proposed method showed induced crystallization in the Pluronic section. Furthermore, the intensity of PCL characteristic peaks decreased for this method.
End-to-End Fingerprints Liveness Detection using Convolutional Networks with Gram module

This paper proposes an end-to-end CNN(Convolutional Neural Networks) model that uses gram modules with parameters that are approximately 1.2MB in size to detect fake fingerprints. The proposed method assumes that texture is the most appropriate characteristic in fake fingerprint detection, and implements the gram module to extract textures from the CNN. The proposed CNN structure uses the fire module as the base model and uses the gram module for texture extraction. Tensors that passed the fire module will be joined with gram modules to create a gram matrix with the same spatial size. After 3 gram matrices extracted from different layers are combined with the channel axis, it becomes the basis for categorizing fake fingerprints. The experiment results had an average detection error of 2.61% from the LivDet 2011, 2013, 2015 data, proving that an end-to-end CNN structure with few parameters that is able to be used in fake fingerprint detection can be designed.
A Minimalist Approach to Type-Agnostic Detection of Quadrics in Point Clouds

This paper proposes a segmentation-free, automatic and efficient procedure to detect general geometric quadric forms in point clouds, where clutter and occlusions are inevitable. Our everyday world is dominated by man-made objects which are designed using 3D primitives (such as planes, cones, spheres, cylinders, etc.). These objects are also omnipresent in industrial environments. This gives rise to the possibility of abstracting 3D scenes through primitives, thereby positions these geometric forms as an integral part of perception and high level 3D scene understanding. As opposed to state-of-the-art, where a tailored algorithm treats each primitive type separately, we propose to encapsulate all types in a single robust detection procedure. At the center of our approach lies a closed form 3D quadric fit, operating in both primal & dual spaces and requiring as low as 4 oriented-points. Around this fit, we design a novel, local null-space voting strategy to reduce the 4-point case to 3. Voting is coupled with the famous RANSAC and makes our algorithm orders of magnitude faster than its conventional counterparts. This is the first method capable of performing a generic cross-type multi-object primitive detection in difficult scenes. Results on synthetic and real datasets support the validity of our method.
Crystal Structure of an Uncommon Cellulosome-Related Protein Module from Ruminococcus flavefaciens That Resembles Papain-Like Cysteine Peptidases

Background Ruminococcus flavefaciens is one of the predominant fiber-degrading bacteria found in the rumen of herbivores. Bioinformatic analysis of the recently sequenced genome indicated that this bacterium produces one of the most intricate cellulosome systems known to date. A distinct ORF, encoding for a multi-modular protein, RflaF_05439, was discovered during mining of the genome sequence. It is composed of two tandem modules of currently undefined function that share 45% identity and a C-terminal X-dockerin modular dyad. Gaining insight into the diversity, architecture and organization of different types of proteins in the cellulosome system is essential for broadening our understanding of a multi-enzyme complex, considered to be one of the most efficient systems for plant cell wall polysaccharide degradation in nature. Methodology/Principal Findings Following bioinformatic analysis, the second tandem module of RflaF_05439 was cloned and its selenium-labeled derivative was expressed and crystallized. The crystals belong to space group P21 with unit-cell parameters of a = 65.81, b = 60.61, c = 66.13 Å, β = 107.66° and contain two protein molecules in the asymmetric unit. The crystal structure was determined at 1.38-Å resolution by X-ray diffraction using the single-wavelength anomalous dispersion (SAD) method and was refined to Rfactor and Rfree of 0.127 and 0.152 respectively. The protein molecule mainly comprises a β-sheet flanked by short α-helixes, and a globular α-helical domain. The structure was found to be structurally similar to members of the NlpC/P60 superfamily of cysteine peptidases. Conclusions/Significance The 3D structure of the second repeat of the RflaF_05439 enabled us to propose a role for the currently undefined function of this protein. Its putative function as a cysteine peptidase is inferred from in silico structural homology studies. It is therefore apparent that cellulosomes integrate proteins with other functions in addition to the classic well-defined carbohydrate active enzymes.
Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices

The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important research topic. The current study proposes a mixed methodology to obtain the first classification model that is able to predict new nucleotide binding peptides, using only the amino acid sequence. Thus, the methodology uses a Star graph molecular descriptor of the peptide sequences and the Machine Learning technique for the best classifier. The best model represents a Random Forest classifier based on two features of the embedded and non‐embedded graphs. The performance of the model is excellent, considering similar models in the field, with an Area Under the Receiver Operating Characteristic Curve (AUROC) value of 0.938 and true positive rate (TPR) of 0.886 (test subset). The prediction of new nucleotide binding peptides with this model could be useful for drug target studies in drug development.
Accelerating R with high performance linear algebra libraries

Linear algebra routines are basic building blocks for the statistical software. In this paper we analyzed how can we can improve R performance for matrix computations. We benchmarked few matrix operations using the standard linear algebra libraries included in the R distribution and high performance libraries like OpenBLAS, GotoBLAS and MKL. Our tests showed the the best results are obtained with the MKL library, the other two libraries having similar performances, but lower than MKL
Solubility and dissolution enhancement of quercetin via preparation of spray dried microstructured solid dispersions

Quercetin (QC) is a bioflavonoid characterized with poor water solubility that limits its oral bioavailability and hence its therapeutic applications. In an attempt to enhance its solubility and dissolution rate, both binary and ternary microstructured solid dispersions (MSDs) of QC with different ratios of polyvinylpyrrolidone K30 (PVP K30) and pluronic F 127 (PF 127) were prepared by spray drying. Solubility and dissolution characteristics of the prepared solid dispersions were evaluated and compared with that of the corresponding physical mixtures and the drug powder. The obtained results revealed that the solubility and the dissolution rate of QC were greatly improved in binary microstructured solid dispersions (MBSD), as well as in ternary microstructured solid dispersions (MTSD). MTSD, made up of 5% w/w PF 127, and 95% w/w QC/PVP K30 in 1:1 weight ratio, showed enhanced QC solubility and dissolution. The percent of QC dissolved after 60 minutes (%D 60min ) was 95.1, and the time required for 90% of QC to be dissolved (T 90% ) was 50 minutes Physical characterization of MTSD by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) spectroscopy, differential scanning calorimetry (DSC), and X-ray powder diffraction (XRPD), in comparison with corresponding physical mixtures, revealed changes in solid state of QC during the formation of solid dispersion that indicate the formation of high-energy amorphous phase.
Effects of Lateral Eye Displacement on Comfort While Reading from a Video Display Terminal

Some small field-of-view (FOV) head worn displays (HWD), like Epson's Moverio BT-300, are mounted directly in the user's line of sight. In contrast, Google Glass is mounted “out of the way” and above the line of sight. Other displays like the Vuzix M100 or Optinvent ORA-1 allow the user to adjust the display position, and some users have expressed a desire for the display to be laterally displaced toward the ear, out of the main line of sight. How far toward the ear can a small FOV display be mounted and still be used comfortably? Using a 30-minute reading task and an emulated display with the FOV of a typical smart phone (9.2°x 16.3°), we study a user's perceived comfort level while reading at four horizontally displaced positions. We ask participants to rate their comfort every five minutes using a 5-point Likert scale knob (5 being most comfortable), for a total of seven measurements. Scores are summed over the seven measurements to form a summed comfort score. We find that 0° (Md = 34.0; p«0.001), 10° (Md = 33.5; p«c0.001), and 20° (Md = 33.5; p«c0.001) are more comfortable than 30° (Md = 29.5) and that 0° (p<0.01) and 10° (p<0.01) are more comfortable than 20°. Reading performance and workload measures were numerically similar across all conditions. Given the main results of the experiment, post-hoc analysis on other measurements such as preference and asthenopia, and participant comments, we suggest that small FOV displays should be mounted at lateral displacement angles of 20° and less for sustained use.
Hierarchic Interaction of Factors Associated With Liver Decompensation After Resection for Hepatocellular Carcinoma.

IMPORTANCE Liver resection is the treatment of choice for hepatocellular carcinoma (HCC) in well-compensated liver cirrhosis. Postoperative liver decompensation (LD) is the most representative and least predictable cause of morbidity and mortality. OBJECTIVES To determine the hierarchy and interaction of factors associated with the risk for LD and to define applicable risk classes among surgical candidates. DESIGN, SETTING, AND PARTICIPANTS This retrospective review collected data from 543 patients with chronic liver disease who underwent hepatic resection for HCC from January 1, 2000, through December 31, 2013, in a tertiary comprehensive cancer center. Final follow-up was completed on January 31, 2015, and data were assessed from February 1 to 28, 2015. MAJOR OUTCOMES AND MEASURES Preoperative prognostic factors and risk stratification for postoperative LD. Multivariate logistic regression was performed, and the independent risk factors for LD were included in a recursive partitioning analysis model. Results were validated by means of 10-fold cross-validation. RESULTS The analysis included 543 patients, of whom 411 (75.7%) were male, 132 (24.3%) were female, and the median age was 68 (interquartile range, 62-73) years. An independent association with LD was found for major hepatectomy (odds ratio [OR], 2.41; 95% CI, 1.17-4.30; P = .01), portal hypertension (OR, 2.20; 95% CI, 1.13-4.30; P = .01), and Model for End-Stage Liver Disease (MELD) score greater than 9 (OR, 2.26; 95% CI, 1.10-4.58; P = .02). Recursive partitioning analysis confirmed portal hypertension as the most important factor (OR, 2.99; 95% CI, 1.93-4.62; P < .001), followed by extension of hepatectomy with (OR, 2.76; 95% CI, 1.85-4.77; P = .03) and without (OR, 2.98; 95% CI, 1.97-4.52; P < .001) portal hypertension, and MELD score (OR, 1.79; 95% CI, 1.23-2.13; P < .001). Low-risk patients (LD rate, 4.9% [11 of 226]) without portal hypertension underwent minor resection with a MELD score of 9 or less; intermediate-risk patients (LD rate, 28.6% [85 of 297]) had no portal hypertension and underwent major resections or, in case of minor resections, had portal hypertension or a MELD score greater than 9; and high-risk patients (LD rate, 60.0% [12 of 20]) underwent major resection with portal hypertension. Risk-class progression paralleled median length of stay (7, 8, and 11 days, respectively; P < .001) and liver-related mortality (4.4% [10 of 226], 9.0% [27 of 297], and 25.0% [5 of 20], respectively; P = .001). A 10-fold cross-validation of the model resulted in a C index of 0.78 (95% CI, 0.74-0.82) and an overall error rate of 0.06. CONCLUSIONS AND RELEVANCE The risk for postoperative LD after resection for HCC in chronic liver disease is associated with preoperative hierarchic interaction of portal hypertension, planned extension of hepatectomy, and the MELD score.
Effectiveness of three mouthwashes – Manuka honey, Raw honey, and Chlorhexidine on plaque and gingival scores of 12–15-year-old school children: A randomized controlled field trial

Objectives: The aim of this study is to compare the effectiveness of three types of mouthwashes manuka honey (MH), raw honey (RH), and chlorhexidine (CHX) on plaque and gingival scores of 12–15-year-old government school children. Study Design: This study was a double-blind, randomized controlled field trial conducted in Belagavi city, India. Materials and Methods: One hundred and thirty-five government school children aged 12–15 years were randomly selected and allocated into three groups, RH, MH, and CHX mouthwash groups. Ten milliliters each of honey-based mouthwash formulation and CHX mouthwashes (0.2%) were administered according to the group allocation twice daily for 21 days. All the children were examined at baseline, 22nd day (after discontinuation of mouthwash) and 28th day (1 week after discontinuation of mouthwash) for Gingival (Loe and silness 1963) and Plaque Index (Silness and Loe, 1964). Results: Descriptive statistics was applied for distribution of study participants according to age and gender. One-way ANOVA followed by Tukey's post hoc test and repeated measures ANOVA test followed by Bonferroni's post hoc were applied for inter- and intragroup comparison, respectively. Statistically significant reductions (P < 0.001) in plaque and gingival scores were observed in all the three types of mouthwash groups at the end of the 22nd day and 28th day. MH and RH mouthwash demonstrated equal effectiveness, whereas CHX mouthwash showed the maximum reduction in clinical parameters. Conclusion: Honey-based mouthwash showed a promising antimicrobial effect on dental caries and plaque and gingival scores.
Dynamic Vertical Mapping with Crowdsourced Smartphone Sensor Data

In this paper, we present our novel approach for the crowdsourced dynamic vertical mapping of buildings. For achieving this, we use the barometric sensor of smartphones to estimate altitude differences and the moment of the outdoor to indoor transition to extract reference pressure. We have identified the outdoor–indoor transition (OITransition) via the fusion of four different sensors. Our approach has been evaluated extensively over a period of 6 months in different humidity, temperature, and cloud-coverage situations, as well as over different hours of the day, and it is found that it can always predict the correct number of floors, while it can approximate the altitude with an average error of 0.5 m.