Miracle-dz/UniFAR-FTUs huggingface dataset:
Using a quality improvement initiative to reduce acute kidney injury during on-pump coronary artery bypass grafting

Introduction: In response to a perceived high incidence of acute kidney injury following cardiopulmonary bypass at our institution, a quality improvement initiative consisting of a systematic change to a delivered oxygen (DO2) goal-directed perfusion practice was implemented. We sought to maintain DO2 > 270 mL/min/m2 to reduce the incidence of acute kidney injury. Methods: ’The study population included all patients receiving isolated, non-emergent, on-pump coronary artery bypass grafting from January 2015 through December 2018, excluding patients requiring preoperative hemodialysis. DO2 goal-directed perfusion was instituted in February 2017. Acute kidney injury was defined using Acute Kidney Injury Network criteria. Results: The pre–goal-directed perfusion cohort included 257 patients, and the post–goal-directed perfusion cohort included 226 patients. The DO2 was significantly higher in the post–goal-directed perfusion group (p < 0.001). Postoperative change in serum creatinine and incidence of acute kidney injury were significantly lower in the post–goal-directed perfusion group (p < 0.001, p = 0.001, respectively). Estimation with probit and ordered probit models support these findings. Conclusion: This initiative confirms previous assertions that DO2 is a critical intraoperative parameter and should direct perfusion intervention accordingly.
Automated classification method of lung tumor type using cytological image and clinical record

Recently, as chemotherapy has advanced, it is important to accurately diagnosis the histological type (adenocarcinoma, squamous cell carcinoma and small cell carcinoma). In previous study, automated classification method for lung cancers in cytological images using a deep convolutional neural network (DCNN) was proposed. However, its classification accuracy is approximately 70%, therefore improvement in accuracy is required. In this study, we focus on liquid-based cytology images and clinical record. In this study, we aimed to improve the classification accuracy of lung cancer type by combining cytological images and electronic medical records. We aimed to develop of classification method of lung tumor type by combining cytological images and clinical record. First, the cytological images were collected. The original microscopic images were first cropped to obtain images with resolution 256 × 256 pixels. And then, we collected personal clinical data (age, gender, smoking status, laboratory test values, tumor markers and so on) corresponding to cytological images. Next, image features were extracted from cytological images using VGG-16 model pretrained on the ImageNet dataset. 4096 features before the fully connected layer were extracted. Then, these features were reduced dimensions by PCA. Image features obtained from the DCNN and clinical data corresponding to cytological images were given to the classifier. Finally, classification result of 3 histological categories was obtained. Evaluation results showed that classification by combining cytological images and clinical record improved classification accuracy than by cytological images alone. These results indicate that the proposed method may be useful for histological classification of lung tumor.
Biochemical Characterization of Citrobacter diversus (Burkey) Werkman and Gillen and Designation of the Neotype Strain

The biochemical characteristics of 137 strains of Citrobacter diversus (Burkey) Werkman and Gillen were determined, and the resulting data are summarized. Members of this species produced indole and ornithine decarboxylase and fermented adonitol but failed to grow in KCN medium. Detectable amounts of hydrogen sulfide were not produced in triple sugar-iron-agar medium but were formed by some strains in peptone-iron-agar. The nomenclature and taxonomic position of these bacteria are discussed, and information that should be helpful for their differentiation from Citrobacter freundii and Enterobacter cloacae is included. Strain 3613–63 (ATCC 27156) is designated as the neotype strain and is described herein.
Performances Evaluation of a Low-Cost Platform for High-Resolution Plant Phenotyping

This study aims to test the performances of a low-cost and automatic phenotyping platform, consisting of a Red-Green-Blue (RGB) commercial camera scanning objects on rotating plates and the reconstruction of main plant phenotypic traits via the structure for motion approach (SfM). The precision of this platform was tested in relation to three-dimensional (3D) models generated from images of potted maize, tomato and olive tree, acquired at a different frequency (steps of 4°, 8° and 12°) and quality (4.88, 6.52 and 9.77 µm/pixel). Plant and organs heights, angles and areas were extracted from the 3D models generated for each combination of these factors. Coefficient of determination (R2), relative Root Mean Square Error (rRMSE) and Akaike Information Criterion (AIC) were used as goodness-of-fit indexes to compare the simulated to the observed data. The results indicated that while the best performances in reproducing plant traits were obtained using 90 images at 4.88 µm/pixel (R2 = 0.81, rRMSE = 9.49% and AIC = 35.78), this corresponded to an unviable processing time (from 2.46 h to 28.25 h for herbaceous plants and olive trees, respectively). Conversely, 30 images at 4.88 µm/pixel resulted in a good compromise between a reliable reconstruction of considered traits (R2 = 0.72, rRMSE = 11.92% and AIC = 42.59) and processing time (from 0.50 h to 2.05 h for herbaceous plants and olive trees, respectively). In any case, the results pointed out that this input combination may vary based on the trait under analysis, which can be more or less demanding in terms of input images and time according to the complexity of its shape (R2 = 0.83, rRSME = 10.15% and AIC = 38.78). These findings highlight the reliability of the developed low-cost platform for plant phenotyping, further indicating the best combination of factors to speed up the acquisition and elaboration process, at the same time minimizing the bias between observed and simulated data.
A Variational Point Process Model for Social Event Sequences

Many events occur in real-world and social networks. Events are related to the past and there are patterns in the evolution of event sequences. Understanding the patterns can help us better predict the type and arriving time of the next event. In the literature, both feature-based approaches and generative approaches are utilized to model the event sequence. Feature-based approaches extract a variety of features, and train a regression or classification model to make a prediction. Yet, their performance is dependent on the experience-based feature exaction. Generative approaches usually assume the evolution of events follow a stochastic point process (e.g., Poisson process or its complexer variants). However, the true distribution of events is never known and the performance depends on the design of stochastic process in practice. To solve the above challenges, in this paper, we present a novel probabilistic generative model for event sequences. The model is termed Variational Event Point Process (VEPP). Our model introduces variational auto-encoder to event sequence modeling that can better use the latent information and capture the distribution over inter-arrival time and types of event sequences. Experiments on real-world datasets prove effectiveness of our proposed model.
Translating policy to practice: theory-based formative research to improve messaging and over-the-counter access to emergency contraception in Florence, Italy

Abstract Objectives Italy’s 2015 emergency contraception (EC) policy made EC available without prescription for individuals aged 18 years and older; however, women living in Italy continue to face barriers to accessing EC. The purposes of this study were to understand EC knowledge, attitudes and behaviours among women living in Italy and explore the impact of the 2015 policy. Methods Researchers conducted 30 interviews with women living in Florence, Italy, aged 18–50 years and using the Italian health care system. Researchers used an expanded grounded theory approach to understand women’s EC experiences, with diffusion of innovations (DOI) serving as a conceptual lens. Researchers completed open and axial coding to identify emerging themes. Results Participants had low awareness of the 2015 EC policy and suggested increased messaging in strategic locations to overcome this barrier. They held positive and negative attitudes towards EC: while some perceived the advantage of EC compared with unintended pregnancy, others expressed concerns about irresponsible behaviour and safety. Finally, conscientious objection impacted access, despite women’s desire for autonomous EC decision making. Conclusion The findings offer practical recommendations to guide EC messaging in Italy to increase women’s access to EC. Recommendations include using theory- and audience-based methods to overcome gaps in policy knowledge and real and perceived barriers to EC access. Incorporating DOI as a theoretical framework with women’s voices presents a novel opportunity to enhance policy and EC dissemination.
Diversification of the RAB Guanosine Triphosphatase Family in Dicots and Monocots

RAB guanosine triphosphatases (GTPases) are key regulators of vesicle trafficking and are essential to the growth and development of all eukaryotic cells. During evolution, the RAB family has expanded in different patterns to facilitate distinct cellular, developmental and physiological adaptations. Yeast has only 11 family members, whereas mammalian RABs have expanded to 18 RAB subfamilies. Plant RABs have diversified primarily by duplicating members within a single subfamily. Plant RABs are divided into eight subfamilies, corresponding to mammalian RAB1, RAB2, RAB5, RAB6, RAB7, RAB8, RAB11 and RAB18. Functional diversification of these is exemplified by the RAB11s, orthologs of which are partitioned into unique cell compartments in plants where they function to transport vesicles during localized tip growth. Similarly, the RAB2 family in grasses is likely involved in vesicle secretion associated with wall expansion, as determined by analysis of over-expression mutants. We propose that dicots and monocots have also diverged in their RAB profiles to accommodate unique cellular functions between the two groups. Here we present a bioinformatics analysis comparing the RAB sub-families of rice, maize and Arabidopsis. These results will guide future functional studies to test for the role of diversification of subfamilies unique to monocots compared to dicots.
Biodiversity of Dioxin-Degrading Microorganisms and Potential Utilization in Bioremediation

Dioxins are a group of chloroaromatic compounds known to be toxic and carcinogenic, and persistent environmental pollutants. How to remedy dioxin-polluted environments is one of the most challenging problems in environmental technology. From ecological and economical viewpoints, biological methods using particular microorganisms and microbial consortia capable of dioxin transformation and degradation have greater appeal than physicochemical methods in their application for environmental remediation. Large numbers of microorganisms capable of degrading dioxins and dioxin-like compounds have been isolated and characterized. Information about the biodiversity, ecophysiology and molecular biology of dioxin-degrading microorganisms has accumulated particularly during the past decade. There are three major modes of microbial degradation and transformation of dioxins; that is, oxidative degradation by aerobic bacteria containing aromatic hydrocarbon dioxygenases, reductive dechlorination by anaerobic microorganisms and fungal oxidation with cytochrome P-450, lignin peroxidases and laccases. This article overviews the current knowledge of microbial degradation and transformation of dioxins as well as the biodiversity of microorganisms involved. Strategies directed towards the bioremediation of dioxin-polluted environments are discussed.
Draft Genome Sequence of Streptomyces aureoverticillatus HN6, a Strain Antagonistic against Fusarium oxysporum f. sp. cubense Race 4

Streptomyces aureoverticillatus HN6 was isolated in Hainan, China. It is highly inhibitory to Fusarium oxysporum f. sp. cubense race 4 (FOC4), which causes banana Fusarium wilt. The HN6 genome was fully sequenced and assembled. Bionformatic analysis shows that the HN6 genome contains at least 208 genes involved in antibiotic biosynthesis. ABSTRACT Streptomyces aureoverticillatus HN6 was isolated in Hainan, China. It is highly inhibitory to Fusarium oxysporum f. sp. cubense race 4 (FOC4), which causes banana Fusarium wilt. The HN6 genome was fully sequenced and assembled. Bionformatic analysis shows that the HN6 genome contains at least 208 genes involved in antibiotic biosynthesis.
Water- and acid-stable self-passivated dihafnium sulfide electride and its persistent electrocatalytic reaction

Water- and acid-stable electride realizes a sustainable electrocatalytic reaction as an efficient solid-state electron source. Electrides have emerged as promising materials with exotic properties, such as extraordinary electron-donating ability. However, the inevitable instability of electrides, which is caused by inherent excess electrons, has hampered their widespread applications. We report that a self-passivated dihafnium sulfide electride ([Hf2S]2+∙2e−) by double amorphous layers exhibits a strong oxidation resistance in water and acid solutions, enabling a persistent electrocatalytic hydrogen evolution reaction. The naturally formed amorphous Hf2S layer on the cleaved [Hf2S]2+∙2e− surface reacts with oxygen to form an outermost amorphous HfO2 layer with ~10-nm thickness, passivating the [Hf2S]2+∙2e− electride. The excess electrons in the [Hf2S]2+∙2e− electride are transferred through the thin HfO2 passivation layer to water molecules under applied electric fields, demonstrating the first electrocatalytic reaction with excellent long-term sustainability and no degradation in performance. This self-passivation mechanism in reactive conditions can advance the development of stable electrides for energy-efficient applications.
GAN-based single-image reflectance removal using depth of field guidance

Eliminating reflections on a single-image has been a challenging issue in image processing and computer vision, because defining an elaborate physical model to separate irregular reflections is almost impossible. In fact, while human vision can automatically focus on the transmitted object, basic deep neural networks even have a limitation to learn the attentive mechanism. In this paper, to solve this problem, a Generative Adversarial Networks guided by using Depth of Field (DoF) is proposed. The DoF is formulated by using image statistics and indicates the focused region of image. Thus, by adding this information to both generative and discriminative networks, the generator focuses on the transmitted layer and the discriminator will be able to estimate the local consistency of the restored areas. Since it is intractable to obtain the ground-truth transmitted layer in real images, a dataset with synthetic reflection is considered for quantitative evaluation. The experimental results demonstrate that the proposed method outperforms the existing approaches in both PSNR and SSIM. The visual outputs indicate that the proposed network convincingly eliminates the reflection and produce sufficient transmitted layers as compared to the previous methods.
VapBC22 toxin-antitoxin system from Mycobacterium tuberculosis is required for pathogenesis and modulation of host immune response

The VapBC22 toxin-antitoxin system regulates adaptation to oxidative stress and virulence in Mycobacterium tuberculosis. Virulence-associated protein B and C toxin-antitoxin (TA) systems are widespread in prokaryotes, but their precise role in physiology is poorly understood. We have functionally characterized the VapBC22 TA system from Mycobacterium tuberculosis. Transcriptome analysis revealed that overexpression of VapC22 toxin in M. tuberculosis results in reduced levels of metabolic enzymes and increased levels of ribosomal proteins. Proteomics studies showed reduced expression of virulence-associated proteins and increased levels of cognate antitoxin, VapB22 in the ΔvapC22 mutant strain. Furthermore, both the ΔvapC22 mutant and VapB22 overexpression strains of M. tuberculosis were susceptible to killing upon exposure to oxidative stress and showed attenuated growth in guinea pigs and mice. Host transcriptome analysis suggests upregulation of the transcripts involved in innate immune responses and tissue remodeling in mice infected with the ΔvapC22 mutant strain. Together, we demonstrate that the VapBC22 TA system belongs to a key regulatory network and is essential for M. tuberculosis pathogenesis.
Analysis of Co-authorship Network and the Correlation between Academic Performance and Social Network Measures

: This project conducted link analysis and graph cluster analysis to analyze the co-authorship network of 166 researchers, mainly from three top universities in Shanghai, China. The publication data of researchers in the area of social science between 2014 and 2016 were collected from Scopus, and the g index was calculated as their performance indicator. For this project, the centrality measures, the efficiency of the egocentric network were calculated as well as authorities and hubs were identified in the link analysis. In addition, clustering algorithms based on betweenness centrality were used to conduct the graph cluster analysis. Finally, in order to identify productive researchers, this project employed the Spearman correlation test to analyze the correlation between a researcher's performance and social network measures. Results from this test indicate that except for closeness centrality and degree centrality, the correlation between g-index and betweenness centrality, eigenvector centrality and efficiency is significant.
Floral trait differentiation in Anacamptis coriophora: phenotypic selection on scents, but not on colour.

Current divergent selection may promote floral trait differentiation among conspecific populations in flowering plants. However, whether this applies to complex traits such as colour or scents has been little studied, even though these traits often vary within species. In this study, we compared floral colour and odour as well as selective pressures imposed upon these traits among seven populations belonging to three subspecies of the widespread, generalist orchid Anacamptis coriophora. Colour was characterised using calibrated photographs and scents were sampled using dynamic headspace extraction and analysed using gas chromatography-mass spectrometry. We then quantified phenotypic selection exerted on these traits by regressing fruit set values on floral trait values. We showed that the three studied subspecies were characterised by different floral colour and odour, with one of the two predominant floral volatiles emitted by each subspecies being taxon-specific. Plant size was positively correlated with fruit set in most populations, while we found no apparent link between floral colour and female reproductive success. We detected positive selection on several taxon-specific compounds in A. coriophora subsp. fragrans, whereas no selection was found on floral volatiles of A. coriophora subsp. coriophora and A. coriophora subsp. martrinii. This study is one of the first to document variation in phenotypic selection exerted on floral scents among conspecific populations. Our results suggest that selection could contribute to ongoing chemical divergence among A. coriophora subspecies.
Thermal ramping rate influences evolutionary potential and species differences for upper thermal limits in Drosophila

Summary 1. Thermal tolerance is a key factor limiting insect distributions, but there is limited information on the ability of species to evolve different thermal limits. Recent studies indicate that the experimental protocol influences upper limits, with slower but ecologically relevant rates of warming lowering estimates of tolerance. These effects could also influence genetic and environmental variances that define evolutionary potential. 2. To determine the influence of experimental protocol on estimates of narrow sense heritability (h2n) and other measures of evolutionary potential in Drosophila melanogaster, we conducted family studies on knockdown time when flies were immediately exposed to a high temperature (static) or when temperature was increased to an upper limit (ramping). 3. Estimates of variance components in two populations were obtained using the animal model approach that incorporates information from all relationships among relatives. Coefficients of variation were higher when flies were exposed to a static stress, as were estimates of additive genetic variance and measures of evolvability where genetic variances were standardized by trait means. In contrast, levels of environmental variance were higher under ramping conditions. These effects mean that the narrow sense heritability of thermal resistance was low under slow ramping and did not differ significantly from zero. 4. Differences in thermal limits under both methods were detected among Drosophila species. There was a significant positive relationship between the fast and slow ramping estimates of thermal resistance across species after correction for phylogeny, suggesting similar underlying mechanisms or a history of correlated evolution. However, this result was caused by the strong influence of two taxa. 5. These results suggest that natural populations exhibit lower adaptive potential for upper thermal limits under ramping than estimated from traditional (static) estimates of heat resistance. Even the highly adaptable Drosophila melanogaster appears to have little evolutionary potential to extend its upper thermal range under ramping conditions although species have diverged for this measure.
Selection on fruit traits is mediated by the interplay between frugivorous birds, fruit flies, parasitoid wasps and seed‐dispersing ants

Every organism on Earth must cope with a multitude of species interactions both directly and indirectly throughout its life cycle. However, how selection from multiple species occupying different trophic levels affects diffuse mutualisms has received little attention. As a result, how a given species amalgamates the combined effects of selection from multiple mutualists and antagonists to enhance its own fitness remains little understood. We investigated how multispecies interactions (frugivorous birds, ants, fruit flies and parasitoid wasps) generate selection on fruit traits in a seed dispersal mutualism. We used structural equation models to assess whether seed dispersers (frugivorous birds and ants) exerted phenotypic selection on fruit and seed traits in the spiny hackberry (Celtis ehrenbergiana), a fleshy‐fruited tree, and how these selection regimes were influenced by fruit fly infestation and wasp parasitoidism levels. Birds exerted negative correlational selection on the combination of fruit crop size and mean seed weight, favouring either large crops with small seeds or small crops with large seeds. Parasitoids selected plants with higher fruit fly infestation levels, and fruit flies exerted positive directional selection on fruit size, which was positively correlated with seed weight. Therefore, higher parasitoidism indirectly correlated with higher plant fitness through increased bird fruit removal. In addition, ants exerted negative directional selection on mean seed weight. Our results show that strong selection on phenotypic traits may still arise in perceived diffuse species interactions. Overall, we emphasize the need to consider diverse direct and indirect partners to achieve a better understanding of the mechanisms driving phenotypic trait evolution in multispecies interactions.