ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Viral spillover risk increases with climate change in High Arctic lake sediments

The host spectrum of viruses is quite diverse, as they can sustainedly infect a few species to several phyla. When confronted with a new host, a virus may even infect it and transmit sustainably in this new host, a process called 'viral spillover'. However, the risk of such events is difficult to quantify. As climate change is rapidly transforming environments, it is becoming critical to quantify the potential for spillovers. To address this issue, we resorted to a metagenomics approach and focused on two environments, soil and lake sediments from Lake Hazen, the largest High Arctic freshwater lake in the world. We used DNA and RNA sequencing to reconstruct the lake's virosphere in both its sediments and soils, as well as its range of eukaryotic hosts. We then estimated the spillover risk by measuring the congruence between the viral and the eukaryotic host phylogenetic trees, and show that spillover risk increases with runoff from glacier melt, a proxy for climate change. Should climate change also shift species range of potential viral vectors and reservoirs northwards, the High Arctic could become fertile ground for emerging pandemics.
Risk Model Development and Validation in Clinical Oncology: Lessons Learned

Reliable risk models can greatly facilitate patient-centered inferences and decisions. Herein we summarize key considerations related to risk modeling in clinical oncology. Often overlooked challenges include data quality, missing data, effective sample size estimation, and selecting the variables to be included in the risk model. The stability and quality of the model should be carefully interrogated with particular emphasis on rigorous internal validation.
Weakly Supervised Neuron Reconstruction From Optical Microscopy Images With Morphological Priors

Manually labeling neurons from high-resolution but noisy and low-contrast optical microscopy (OM) images is tedious. As a result, the lack of annotated data poses a key challenge when applying deep learning techniques for reconstructing neurons from noisy and low-contrast OM images. While traditional tracing methods provide a possible way to efficiently generate labels for supervised network training, the generated pseudo-labels contain many noisy and incorrect labels, which lead to severe performance degradation. On the other hand, the publicly available dataset, BigNeuron, provides a large number of single 3D neurons that are reconstructed using various imaging paradigms and tracing methods. Though the raw OM images are not fully available for these neurons, they convey essential morphological priors for complex 3D neuron structures. In this paper, we propose a new approach to exploit morphological priors from neurons that have been reconstructed for training a deep neural network to extract neuron signals from OM images. We integrate a deep segmentation network in a generative adversarial network (GAN), expecting the segmentation network to be weakly supervised by pseudo-labels at the pixel level while utilizing the supervision of previously reconstructed neurons at the morphology level. In our morphological-prior-guided neuron reconstruction GAN, named MP-NRGAN, the segmentation network extracts neuron signals from raw images, and the discriminator network encourages the extracted neurons to follow the morphology distribution of reconstructed neurons. Comprehensive experiments on the public VISoR-40 dataset and BigNeuron dataset demonstrate that our proposed MP-NRGAN outperforms state-of-the-art approaches with less training effort.
Near-infrared fluorescent probe with a large Stokes shift for bioimaging of β-galactosidase in living cells and zebrafish develop at different period

Overexpression of β-galactosidase (β-gal) in tumor cells may serve as a valuable biomarker for the early diagnosis of some cancers (such as ovarian cancer). In addition, abnormal accumulation of β-gal is also considered an essential marker of cell senescence. Therefore, it is important to construct fluorescent probes with excellent fluorescence properties to visualize β-gal in biological systems. Here, we designed and screened a novel fluorescent probe XM for the detection of β-gal. Spectral data show that the probe has a good affinity (Km = 2.6 μM) for β-gal, large stokes shift (190 nm), fast response speed (stable within 20 min), and low detection limit (6.7 × 10-3 U/mL). Based on the above advantages, XM can not only detect β-gal content in cancer cells but also track the changes of β-gal content in zebrafish at different developmental period. We believe XM will become a powerful tool for the early cancer diagnosis and cellular senescence.
Naturalness- and information-preserving image recoloring for red-green dichromats

More than 100 million individuals around the world suffer from color vision deficiency (CVD). Image recoloring algorithms have been proposed to compensate for CVD. This study has proposed a new recoloring algorithm to make up shortages of contrast enhancement and naturalness preservation of the state-of-the-art methods. The recoloring task is formulated as an optimization problem that is solved by using the colors in a simulated CVD color space to maximize contrast and to preserve the original color as much as possible. In addition, the dominant colors are extracted for recoloring. They are then propagated to the whole image so that the optimization problem could be solved at a reasonable cost independent of the image size. In the quantitative evaluation, the results of the proposed method are competitive with those of the best existing method. The evaluation involving subjects with CVD demonstrates that the proposed method outperforms the state-of-the-art method in preserving both the information and the naturalness of images.
Art Inheritance: An Education Course on Traditional Pattern Morphological Generation in Architecture Design Based on Digital Sculpturism

Cultural communication and art heritage represent a repository of highly condensed information of past time that depends not only on the expansion of emerging digital media but also on the transformation of language and knowledge. In this course, students try to extract single elements from the traditional Chinese cultural patterns and redesign them, then combine them into existing buildings, attempting to balance the coherence, heterogeneity of space, and the uniqueness of projects. It provides favorable conditions in the new era for the traditional patterns to be re-activated. It is a combination of technology and art. The purpose of this course is not to discover new theories or new technologies but to provide morphological possibilities under the existing digital techniques in cultural symbols. We try to build new ideas and innovative digital expressions for traditional Chinese patterns, realize the collision of culture and technology from experimental trials on the existing architectures in other unimagined forms. It is not only the research reproduction of traditional patterns but also brings new vitality and fresh ideas for architecture design.
Dual Learning-Based Graph Neural Network for Remote Sensing Image Super-Resolution

High-resolution (HR) remote sensing imagery plays a critical role in remote sensing image interpretation, and single image super-resolution (SISR) reconstruction technology is becoming increasingly valuable and significant. The state-of-the-art deep-learning-based SISR methods have demonstrated remarkable advantages while reconstructing complex texture details still remains a big challenge. Besides, as a typical ill-posed inverse problem, how to determine the optimal solution is another important topic. To address these problems, in this work, a dual learning-based graph neural network (DLGNN) is proposed, in which the graph neural network (GNN) is utilized to consider the self-similarity patches in remote sensing imagery by aggregating cross-scale neighboring feature patches, and dual learning strategy is adopted to refine the reconstruction results by constraining the mapping process in terms of the loss function, transferring the typical ill-posed problem to a well-posed one. Abundant experiments on 3K VEHICLE_SR datasets and Massachusetts Roads demonstrate the validity and outstanding performance for remote sensing image super-resolution (SR) tasks compared with other state-of-the-art SR construction methods. Code is available at https://github.com/CUG-RS/DLGNN
Association of Probiotic Treatment With Antibiotics in Male Accessory Gland Infections

Male accessory gland infection (MAGI) represents a frequent disease, commonly treated with antibiotics alone. However, in approximately 40% to 50% of patients, persistent infection is detected. Intestinal dysbiosis is involved in the pathogenesis of prostatitis. We aimed to evaluate the efficacy of antibiotic treatment in association with a specific probiotic supplementation. A total of 104 infertile patients, with microbiological analysis on semen and/or prostatic secretions positive for Gram-negative bacteria, have been enrolled. All patients received antibiotic treatment with fluoroquinolones. In total, 84 patients received a commercial association of Enterococcus faecium and Saccharomyces boulardii during antibiotic treatment, followed by treatment with Lactobacilli. After the treatment, a complete microbiological analysis was repeated. Polymicrobial infections have been observed in 11% of patients, while infections due to a single germ were reported in 89% of the patients. After the treatment was performed, a complete eradication with negative semen culture and microbiological analysis on prostatic secretion was observed in 64 of 84 patients (76.2%), while only 10 of 20 patients receiving antibiotics alone (50%; p < .05) reported negative microbiological analysis. Persistent infections have been observed only in patients with infections due to Enterococcus faecalis and Escherichia coli. This study represents the first approach demonstrating the efficacy of a specific probiotic treatment in reducing the rate of persistent infections in patients with MAGI.
Pfeature: A Tool for Computing Wide Range of Protein Features and Building Prediction Models

In the last three decades, a wide range of protein features have been discovered to annotate a protein. Numerous attempts have been made to integrate these features in a software package/platform so that the user may compute a wide range of features from a single source. To complement the existing methods, we developed a method, Pfeature, for computing a wide range of protein features. Pfeature allows to compute more than 200,000 features required for predicting the overall function of a protein, residue-level annotation of a protein, and function of chemically modified peptides. It has six major modules, namely, composition, binary profiles, evolutionary information, structural features, patterns, and model building. Composition module facilitates to compute most of the existing compositional features, plus novel features. The binary profile of amino acid sequences allows to compute the fraction of each type of residue as well as its position. The evolutionary information module allows to compute evolutionary information of a protein in the form of a position-specific scoring matrix profile generated using Position-Specific Iterative Basic Local Alignment Search Tool (PSI-BLAST); fit for annotation of a protein and its residues. A structural module was developed for computing of structural features/descriptors from a tertiary structure of a protein. These features are suitable to predict the therapeutic potential of a protein containing non-natural or chemically modified residues. The model-building module allows to implement various machine learning techniques for developing classification and regression models as well as feature selection. Pfeature also allows the generation of overlapping patterns and features from a protein. A user-friendly Pfeature is available as a web server python library and stand-alone package.
Sustainability in the Opera Sector: Main Drivers and Limitations to Improve the Environmental Performance of Scenography

Private and public organizations are becoming increasingly involved in achieving the Sustainable Development Goals. This includes organizations within the cultural sector, with a central role in the progress of society. This study presents a state-of-the-art analysis of actions towards sustainability of the opera sector with a life cycle perspective and focusing on the impact of opera sets' scenery. Our research is based on a review of literature and experiences, the results of interviews, a survey, and an experts' forum to analyze the related systems, standards, and practices. The study contributes with novel research that provides an understanding of the factors that determine the environmental performance which are synthesized with a sustainability SWOT analysis. Findings are relevant for academic researchers analyzing the potential conflicts among organizational strategic goals and sustainability and for scenic arts' practitioners and managers who aim to develop a roadmap towards improving the sustainability of their sector.
Effects of increasing levels of whole Black Soldier Fly (Hermetia illucens) larvae in broiler rations on acceptance, nutrient and energy intakes and utilization, and growth performance of broilers

Meal of black soldier fly larvae (BSFL), which requires extraction of protein and fat, is a novel protein source for poultry, while unprocessed whole BSFL could even directly be fed to chickens. Newly hatched Ross-308 chicks (n = 252) received whole BSFL at 10% (L10), 20% (L20), or 30% (L30) of voluntary feed intake (FI) of control chickens (CON) that received no BSFL but only age-specific diets (n = 63 birds / group) for 42 days (d). Acceptance and nutrient and energy intake of birds by BSFL and FI were calculated. Plasma metabolites were measured using an automatic enzymatic analyzer and immunoglobulins with ELISA. Depending on the variable, data were analyzed using ANOVA or repeated measures ANOVA to address treatment, time and interaction effects. Birds consumed all offered larvae. With the exception of d1, time spent by birds eating their daily portion of larvae (TSL, min/pen) did not differ among the larvae supply groups (P = 0.982). The L10 had a higher larvae eating rate (LER) that is, speed of larvae intake than did L20 and L30 (P < 0.05), implying increased competition for less available BSFL. The ratio of LER to feed eating rate (FER) was greater than 50 fold change difference (FCD), indicating a strong interest of chickens in BSFL over regular feed. Whole BSFL intake up to 30% of voluntary FI did not adversely affect broiler growth (P > 0.05). The L30 had lower total dry matter and metabolizable energy intakes (P < 0.05), although total fat intake was higher in L30 than in CON (P < 0.05). Compared with CON, 30% whole BSFL increased dietary protein-to-energy ratios, plasma uric acid and serum alkaline phosphatase concentrations (P < 0.05). We conclude that whole BSFL can be included in broiler rations up to 20% without negatively affecting growth performance and nutrient conversion efficiency, whereas a higher proportion is associated with lower protein utilization efficiency, possibly due to lower total energy intake.
Endoscopic Findings of Enteropathy-Associated T-Cell Lymphoma Type II: A Case Series

Enteropathy-associated T-cell lymphoma (EATL) is a rare extranodal T-cell lymphoma arising from the intestine. Two types of EATL have been reported. In contrast to the classic EATL type I, EATL type II occurs sporadically, is unrelated to celiac disease, and comprises 10% to 20% of all EATL cases. A total of five cases of EATL type II were diagnosed at our clinic from January 2009 to September 2012. Four of the five patients were diagnosed with the help of endoscopy. Among the four patients, two of the cases involved both the small and large intestines, whereas in the other two patients, EATL was limited to the small intestine. Common endoscopic findings included innumerable fine granularities (also called mosaic mucosal patterns) and diffuse thickening of the mucosa with a semicircular shallow ulceration in the lesions of the small bowel. In contrast, the endoscopic findings of the colon were nonspecific and could not distinguish EATL type II from other diseases. There are only few published reports regarding the representative endoscopic findings of EATL. Here, we present the clinical and endoscopic findings of four cases of EATL type II diagnosed by endoscopy.
Street vending, vulnerability and exclusion during the COVID-19 pandemic: the case of Cali, Colombia

The COVID-19 pandemic has had a profound effect on livelihoods everywhere, but especially in the informal economy where crucial forms of protection and security are often absent. A detailed understanding of the impacts for informal workers, the public policy approaches that could most effectively respond to their needs, and the barriers to such policy, is urgently needed. This paper discusses the results of a 2021 street vendor survey in Cali, Colombia, focusing on (1) vendors' socioeconomic circumstances and (2) their political engagement and attitudes on key policy and governance issues. It argues that while the pandemic and the government responses to it negatively impacted street vendors, there are steps that government could have taken, and can still take, to address vendors' needs and priorities. To ensure a just, equitable, sustainable recovery, and to protect economically marginalized groups from future crises, informal workers must be more meaningfully included in decision-making processes.
The Effects of a Professor's Professionalism and Diversity on the Perception and Satisfaction of Education in the Liberal Arts Curriculum

The purpose of this study was to investigate the awareness of the necessity and importance of liberal arts education and to examine the satisfaction of college students with their liberal arts courses. This study was conducted from June 1-15, 2018, for college students who are taking liberal arts courses. The collected data were analyzed using the SPSS 24.0 and AMOS 24.0 statistical package programs. To understand the general characteristics of the survey subjects, a frequency analysis, exploratory factor analysis, correlation analysis, and reliability analysis were performed to measure the reliability and validity of the measurement tools, and a structural model analysis was conducted to verify the proposed research model. The result shows that a professor's professionalism has a positive influence on the perception of a subject's importance and necessity after the course, diversity has a positive influence on satisfaction in liberal arts education. Favorable changes in the perception of importance and necessity have a positive effect on satisfaction level. Our findings imply that colleges should operate an integrated student-selective education course that allows all students to select and take liberal arts courses. It should be organized to secure full-time professors who will be exclusively responsible for liberal arts curriculums.
A qualitative meta-synthesis of the caregiving experiences of adult children providing care for cancer patients in China: Implications for multidisciplinary healthcare teams

Qualitative meta-synthesis is a coherent approach to answering an overarching research question by synthesising past qualitative studies so as to create new meanings from their results. We conducted a qualitative meta-synthesis to systematically evaluate and integrate the caregiving experiences of adult children providing care for an elderly parent with cancer. The search was conducted in the databases Web of Science, PubMed, Embase, MEDLINE, Cochrane Library, Grew Literature in the Health Sciences, CNKI, WanFang Data, VIP, SINOMED and China Academic Journals as well as Chinese grey literature databases (China Academic Conference Literature Database/, National Science and Technology Library) from inception to June 9, 2021. Thirteen studies were included in the final synthesis. The caregiver experiences they describe are synthesised into three primary themes: care needs, care burden and care gains, with numerous secondary themes. Besides our findings that seem to align with those from studies focused on other cultures, we have highlighted three main discoveries from the synthesis that stand out in the Chinese context: (1) many sub-themes related to specific caregiving skills; (2) a strong expectation for health professionals to improve their communication skills with family caregivers; (3) the negative and positive influences of filial piety in caregiving experiences. Our findings can help multidisciplinary healthcare teams in China support adult children as caregivers in their emphasis on improving caregiver education and training, ways of making the most of potential care gains, and ways of easing care burdens.
Wettability-based ultrasensitive detection of amphiphiles through directed concentration at disordered regions in self-assembled monolayers

Various forms of ecological monitoring and disease diagnosis rely upon the detection of amphiphiles, including lipids, lipopolysaccharides, and lipoproteins, at ultralow concentrations in small droplets. Although assays based on droplets' wettability provide promising options in some cases, their reliance on the measurements of surface and bulk properties of whole droplets (e.g., contact angles, surface tensions) makes it difficult to monitor trace amounts of these amphiphiles within small-volume samples. Here, we report a design principle in which self-assembled monolayer-functionalized microstructured surfaces coated with silicone oil create locally disordered regions within a droplet's contact lines to effectively concentrate amphiphiles within the areas that dominate the droplet static friction. Remarkably, such surfaces enable the ultrasensitive, naked-eye detection of amphiphiles through changes in the droplets' sliding angles, even when the concentration is four to five orders of magnitude below their critical micelle concentration. We develop a thermodynamic model to explain the partitioning of amphiphiles at the contact line by their cooperative association within the disordered, loosely packed regions of the self-assembled monolayer. Based on this local analyte concentrating effect, we showcase laboratory-on-a-chip surfaces with positionally dependent pinning forces capable of both detecting industrially and biologically relevant amphiphiles (e.g., bacterial endotoxins), as well as sorting aqueous droplets into discrete groups based on their amphiphile concentrations. Furthermore, we demonstrate that the sliding behavior of amphiphile-laden aqueous droplets provides insight into the amphiphile's effective length, thereby allowing these surfaces to discriminate between analytes with highly disparate molecular sizes.
Prediction of Human Eye Fixation by a Single Filter

Saliency modeling has played an important part in computer vision studies over the past 30 years. Many state-of-the-art models adopted complex mathematical and machine learning theories. In this paper, a simple and effective visual attention model is proposed. We find that a single fixed template is enough for saliency map generation; this idea is inspired by the receptive field of the human visual system. All that is needed is to convolve the input image with this template with additional post-processing. Experiments show that our model is extremely fast and performs better than state-of-the-art models in human eye fixation prediction.