Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnostic and Prognostic Power of Active DNA Demethylation Pathway Intermediates in Acute Myelogenous Leukemia and Myelodysplastic Syndromes

Acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) are characterized by genomic instability, which may arise from the global hypomethylation of the DNA. The active DNA demethylation process may be linked with aberrant methylation and can be involved in leukemogenesis. The levels of 5-methylcytosine oxidation products were analyzed in minimally invasive material: the cellular DNA from peripheral blood cells and urine of patients with AML and MDS along with the control group, using isotope-dilution two-dimensional ultra-performance liquid chromatography with tandem mass spectrometry. The receiver operating characteristic curve analysis was used for the assessment of the ability to discriminate patients’ groups from the control group, and AML from MDS. The most diagnostically useful for discriminating AML patients from the control group was the urinary excretion of 5-hydroxymethylcytosine (AUC = 0.918, sensitivity: 85%, and specificity: 97%), and 5-(hydroxymethyl)-2′-deoxyuridine (0.873, 74%, and 92%), while for MDS patients 5-(hydroxymethyl)-2′-deoxycytidine in DNA (0.905, 82%, and 98%) and urinary 5-hydroxymethylcytosine (0.746, 66%, and 92%). Multi-factor models of classification trees allowed the correct classification of patients with AML and MDS in 95.7% and 94.7% of cases. The highest prognostic value of the analyzed parameters in predicting the transformation of MDS into AML was observed for 5-carboxy-2′-deoxycytidine (0.823, 80%, and 97%) and 5-(hydroxymethyl)-2′-deoxyuridine (0.872, 100%, and 75%) in DNA. The presented research proves that the intermediates of the active DNA demethylation pathway determined in the completely non-invasive (urine) or minimally invasive (blood) material can be useful in supporting the diagnostic process of patients with MDS and AML. The possibility of an early identification of a group of MDS patients with an increased risk of transformation into AML is of particular importance.
Exploring the Potential of Natural Product-Based Nanomedicine for Maintaining Oral Health

Oral diseases pose a major threat to public health across the globe. Diseases such as dental caries, periodontitis, gingivitis, halitosis, and oral cancer affect people of all age groups. Moreover, unhealthy diet practices and the presence of comorbidities aggravate the problem even further. Traditional practices such as the use of miswak for oral hygiene and cloves for toothache have been used for a long time. The present review exhaustively explains the potential of natural products obtained from different sources for the prevention and treatment of dental diseases. Additionally, natural medicine has shown activity in preventing bacterial biofilm resistance and can be one of the major forerunners in the treatment of oral infections. However, in spite of the enormous potential, it is a less explored area due to many setbacks, such as unfavorable physicochemical and pharmacokinetic properties. Nanotechnology has led to many advances in the dental industry, with various applications ranging from maintenance to restoration. However, can nanotechnology help in enhancing the safety and efficacy of natural products? The present review discusses these issues in detail.
Tracking the Spatio‐Temporal Evolution of Foreshocks Preceding the Mw 6.1 2009 L’Aquila Earthquake

How faulting processes lead to a large earthquake is a fundamental question in seismology. To better constrain this pre‐seismic stage, we create a dense seismic catalog via template matching to analyze the precursory phase of the Mw 6.1 L’Aquila earthquake that occurred in central Italy in 2009. We estimate several physical parameters in time, such as the coefficient of variation, the seismic moment release, the effective stress drop, and analyze spatio‐temporal patterns to study the evolution of the sequence and the earthquake interactions. We observe that the precursory phase experiences multiple accelerations of the seismicity rate that we divide into two main sequences with different signatures and features: the first part exhibits weak earthquake interactions, quasi‐continuous moment release, slow spatial migration patterns, and a lower effective stress drop, pointing to aseismic processes. The second sequence exhibits strong temporal clustering, fast seismicity expansion, and a larger effective stress drop typical of a stress transfer process. We interpret the differences in seismicity behaviors between the two sequences as distinct physical mechanisms that are controlled by different physical properties of the fault system. We conclude that the L’Aquila earthquake is preceded by a complex preparation, made up of different physical processes over different time scales on faults with different physical properties.
Visualizing Population Dynamics to Examine Algorithm Performance

This work assesses the efficacy of evolutionary algorithms (EAs) using an intuitive multidimensional scaling (MDS) visualization of the evolution of a population. We propose the use of landmark MDS (LMDS) to overcome computational challenges inherent to visualizing many-objective and complex problems with MDS. For the benchmark problems we tested, LMDS is akin to MDS visually, whilst requiring less than 1% of the time and memory necessary to produce an MDS visualization of the same objective space solutions, leading to the possibility of online visualizations for multi- and many-objective optimization evaluation. Using multi- and many-objective problems from the DTLZ and WFG benchmark test suites, we analyze how Landmark MDS visualizations can offer far greater insight into algorithm performance than using traditional algorithm performance metrics such as hypervolume alone, and can be used to complement explicit performance metrics. Ultimately, this visualization allows the visual identification of problem features and assists the decision maker in making intuitive recommendations for algorithm parameters/operators for creating and testing better EAs to solve multi- and many-objective problems.
Feasibility of 4D-Spatio Temporal Image Correlation (STIC) in the Comprehensive Assessment of the Fetal Heart Using FetalHQ®

Fetal Heart Quantification (FetalHQ®) is a novel speckle tracking software that permits the study of global and regional ventricular shape and function from a 2D four-chamber-view loop. The 4D-Spatio Temporal Image Correlation (STIC) modality enables the offline analysis of optimized and perfectly aligned cardiac planes. We aimed to evaluate the feasibility and reproducibility of 4D-STIC speckle tracking echocardiography (STE) using FetalHQ® and to compare it to 2D STE. We conducted a prospective study including 31 low-risk singleton pregnancies between 20 and 40 weeks of gestation. Four-chamber view volumes and 2D clips were acquired with an apex pointing at 45° and with a frame rate higher than 60 Hz. Morphometric and functional echocardiography was performed by FetalHQ®. Intra- and interobserver reproducibility were evaluated by the intraclass correlation coefficient (ICC). Our results showed excellent reproducibility (ICC > 0.900) for morphometric evaluation (biventricular area, longitudinal and transverse diameters). Reproducibility was also good (ICC > 0.800) for functional evaluation (biventricular strain, Fractional Area Change, left ventricle volumes, ejection fraction and cardiac output). On the contrary, the study of the sphericity index and shortening fraction of the different ventricular segments showed lower reproducibility (ICC < 0.800). To conclude, 4D-STIC is feasible, reproducible and comparable to 2D echocardiography for the assessment of cardiac morphometry and function.
Experimental study on the miners' emergency handling ability

Based on the characteristics of individual physiological parameter indices being closely related to individual emergency handling ability,through methods of designing and building experiment system,testing employee samples,data processing and analysis,studied the evaluation on miners' emergency handling ability.The results show that the developed experimental system can study miners' emergency handling ability in sudden events;the 7 selected physiological parameter indices can reflect miners' emergency handling ability condition to some extent;the evaluation index and determining method presented on miner emergency handling ability can exploratively solve the quantitative evaluation problem on miners' emergency handling ability.The research results can be used to distinguish employees of different emergency ability,and provide support for coal mine key post employees' selection.At the same time,the reason for emergency ability difference,targeted improving methods,etc.are still worthy of discussion.
Multiclass Skin Lesion Classification Using a Novel Lightweight Deep Learning Framework for Smart Healthcare

Skin lesion classification has recently attracted significant attention. Regularly, physicians take much time to analyze the skin lesions because of the high similarity between these skin lesions. An automated classification system using deep learning can assist physicians in detecting the skin lesion type and enhance the patient’s health. The skin lesion classification has become a hot research area with the evolution of deep learning architecture. In this study, we propose a novel method using a new segmentation approach and wide-ShuffleNet for skin lesion classification. First, we calculate the entropy-based weighting and first-order cumulative moment (EW-FCM) of the skin image. These values are used to separate the lesion from the background. Then, we input the segmentation result into a new deep learning structure wide-ShuffleNet and determine the skin lesion type. We evaluated the proposed method on two large datasets: HAM10000 and ISIC2019. Based on our numerical results, EW-FCM and wide-ShuffleNet achieve more accuracy than state-of-the-art approaches. Additionally, the proposed method is superior lightweight and suitable with a small system like a mobile healthcare system.
Perceptually Optimal Color Representation of Fully Polarimetric SAR Imagery

The four bands of fully polarimetric SAR data convey scattering characteristics of the Earth’s background, but perceptually are not very easy for an observer to use. In this work, the four different channels of fully polarimetric SAR images, namely HH, HV, VH, and VV, are combined so that a color image of the Earth’s background is derived that is perceptually excellent for the human eye and at the same time provides accurate information regarding the scattering mechanisms in each pixel. Most of the elementary scattering mechanisms are related to specific color and land cover types. The innovative nature of the proposed approach is due to the two different consecutive coloring procedures. The first one is a fusion procedure that moves all the information contained in the four polarimetric channels into three derived RGB bands. This is achieved by means of Cholesky decomposition and brings to the RGB output the correlation properties of a natural color image. The second procedure moves the color information of the RGB image to the CIELab color space, which is perceptually uniform. The color information is then evenly distributed by means of color equalization in the CIELab color space. After that, the inverse procedure to obtain the final RGB image is performed. These two procedures bring the PolSAR information regarding the scattering mechanisms on the Earth’s surface onto a meaningful color image, the appearance of which is close to Google Earth maps. Simultaneously, they give better color correspondence to various land cover types compared with existing SAR color representation methods.
Exploring factors affecting mobile-banking app adoption: a perspective from adaptive structuration theory

PurposeThe study has two aims: first, it aimed to investigate the impact of contextual factors (such as information quality, service quality, system quality, trust in applications (app) and COVID-19 health anxiety) on the intention to use the Mobile Payment (MP) app, and subsequently, the actual use of the app. Second, the aim of this study is whether the COVID-19 threat has a moderating influence on the relationship between customers' intent to use MP app and the actual use of MP app.Design/methodology/approachThe data are collected through an online survey from 341 Mobile Banking (MB) app users from Pakistan to empirically analyze the relationship between service quality, system quality, information quality, trust in the app, COVID-19 health anxiety and COVID-19 threat, intentions to use MB-app and actual use of MB-app.FindingsThe empirical analysis of the data collected from MB-app users from Pakistan shows that service quality, system quality, information quality, trust in the app and COVID-19 health anxiety positively related to intentions to use MB-app, consequently affect the actual use of MB-app. Furthermore, the results demonstrate that the COVID-19 threat positively moderates the relationship between intentions to use MB-app and actual use of MB-app.Originality/valueAlthough, prior research established a positive impact of mobile apps on customer service and consumer satisfaction. Yet, it is not clear which factors influence customers to adopt MB-app. This study contributes to the research on MB-apps based on adaptive structuration theory and examines the technological factors and contextual factors that collectively explain when and how individuals decide to adopt MB-app.
Mechanistic Investigation of GHS-R Mediated Glucose-Stimulated Insulin Secretion in Pancreatic Islets

Ghrelin receptor, a growth hormone secretagogue receptor (GHS-R), is expressed in the pancreas. Emerging evidence indicates that GHS-R is involved in the regulation of glucose-stimulated insulin secretion (GSIS), but the mechanism by which GHS-R regulates GSIS in the pancreas is unclear. In this study, we investigated the role of GHS-R on GSIS in detail using global Ghsr−/− mice (in vivo) and Ghsr-ablated pancreatic islets (ex vivo). GSIS was attenuated in both Ghsr−/− mice and Ghsr-ablated islets, while the islet morphology was similar between WT and Ghsr−/− mice. To elucidate the mechanism underpinning Ghsr-mediated GSIS, we investigated the key steps of the GSIS signaling cascade. The gene expression of glucose transporter 2 (Glut2) and the glucose-metabolic intermediate—glucose-6-phosphate (G6P) were reduced in Ghsr-ablated islets, supporting decreased glucose uptake. There was no difference in mitochondrial DNA content in the islets of WT and Ghsr−/− mice, but the ATP/ADP ratio in Ghsr−/− islets was significantly lower than that of WT islets. Moreover, the expression of pancreatic and duodenal homeobox 1 (Pdx1), as well as insulin signaling genes of insulin receptor (IR) and insulin receptor substrates 1 and 2 (IRS1/IRS2), was downregulated in Ghsr−/− islets. Akt is the key mediator of the insulin signaling cascade. Concurrently, Akt phosphorylation was reduced in the pancreas of Ghsr−/− mice under both insulin-stimulated and homeostatic conditions. These findings demonstrate that GHS-R ablation affects key components of the insulin signaling pathway in the pancreas, suggesting the existence of a cross-talk between GHS-R and the insulin signaling pathway in pancreatic islets, and GHS-R likely regulates GSIS via the Akt-Pdx1-GLUT2 pathway.
Liver Stiffness Is Markedly Decreased After Chronic Hepatitis C Treatment

Aim The aim of the study was to demonstrate the liver stiffness (LS) change in chronic hepatitis C (CHC) patients obtained by elastography point quantification technique in before and after antiviral treatment (AVT). Material and Methods This prospective study included 84 patients diagnosed with CHC who had not previously received treatment for CHC and who had an indication for using direct-acting AVT. Necessary measurements were recorded with noninvasive liver fibrosis (LF) examinations. Posttreatment control of patients was carried out (ombitasvir + paritaprevir + ritonavir) + 3 months after the start of treatment for those treated with dasabuvir and 6 months after the start of treatment for patients treated with sofosbuvir + ribavirin. Liver stiffness changed after AVT is accepted as (Δ-LS), LS before AVT–LS after AVT. Results Basal LS was found to decrease significantly after AVT (8.00 ± 2.56 kPa vs 6.95 ± 2.86 kPa, P < 0.05). Similar aspartate aminotransferase–to–platelet ratio index and platelet number fibrosis 4 indices were observed before and after AVT (P > 0.05). It was observed that Δ-LS value after AVT was lower in patients with Child-Pugh class A cirrhosis than patients without cirrhosis (P < 0.05). In the comparison between Δ-LS value after AVT and LF score determined by liver biopsy, it was seen that the greatest Δ-LS value was in patients with fibrosis score of 3. An independent relationship was found between Δ-LS after AVT and LF score determined by biopsy (P < 0.05). Conclusions The LS value determined by the elastography point quantification technique is more effective than other noninvasive laboratory methods in demonstrating the CHC treatment response in clinical practice.
A Comprehensive Study on Provesicular Drug Delivery System: Proniosomal Gel

: Provesicular Drug Delivery System Vesicular approaches are novel techniques for transporting the drug that reinforces the availability of drugs and gives an action for a prolonged time. Besides, it has definite advantages over traditional drug delivery systems. Liposomes and niosomes comprising vesicles demonstrate the stability issues such as aggregation, leakage, fusion and sedimentation of vesicles due to the aqueous nature of the system. The provesicular system developed to overcome these problems for a unique novel approach includes proliposomes and proniosomes. Provesicles are dry, anhydrous formulations, coated with a non-ionic surfactant, acts as a carrier mixed with water when needed. This article reviews provesicular drug delivery systems with a focus on composition, preparation, the mechanism of drug delivery, encapsulation of the drug into provesicles and characterization techniques. Likewise, this review details the summary of research findings and patent reports on proniosomal investigations. As supported by the literature study, the proniosomes are a leading carrier for the delivery of various drugs over different routes of administration. (dehydrated forms of niosomes), vesicles formed by non-ionic surfactants, which have a better penetration capability than other vesicles. The use of boswellic acids may be potentially useful for the prevention or treatment of vascular calcification.
3D Printing for Cartilage Replacement: A Preliminary Study to Explore New Polymers

The use of additive manufacturing technologies for biomedical applications must begin with the knowledge of the material to be used, by envisaging a very specific application rather than a more general aim. In this work, the preliminary study was focused on considering the cartilaginous tissue. This biological tissue exhibits different characteristics, such as thickness and mechanical properties, depending on its specific function in the body. Due to the lack of vascularization, cartilage is a supporting connective tissue with limited capacity for recovery and regeneration. For this reason, any approach, whether to repair/regenerate or as a total replacement, needs to fulfill the adequate mechanical and chemical properties of the surrounding native cartilage to be successful. This work aims to explore the possibility of using new polymers for cartilage total replacement approaches with polymeric materials processed with the specific 3D printing technique of fused filament fabrication (FFF). The materials studied were Nylon® 12 (PA12), already described for this purpose, and LAY-FOMM® 60 (FOMM). FOMM has not been described in the literature for biomedical purposes. Therefore, the chemical, thermal, swelling capacity, and mechanical properties of the filaments were thoroughly characterized to better understand the structure–properties–application relationships of this new polymer. In addition, as the FFF technology is temperature based, the properties were also evaluated in the printed specimens. Due to the envisaged application, the specimens were also characterized in the wet state. When comparing the obtained results with the properties of native cartilage, it was possible to conclude that: (i) PA12 exhibits low swelling capacity, while FOMM, in its dry and wet forms, has a higher swelling capacity, closer to that of native cartilage; (ii) the mechanical properties of the polymeric materials, especially PA12, are higher than those of native cartilage; and (iii) from the mechanical properties evaluated by ultra-micro hardness tests, the values for FOMM indicate that this material could be a good alternative for cartilage replacement in older patients. This preliminary study, essentially devoted to expanding the frontiers of the current state of the art of new polymeric materials, provides valuable indications for future work targeting the envisaged applications.
Influence of Uneven Lighting on Quantitative Indicators of Surface Defects

The impact of the illumination level on the quantitative indicators of mechanical damage of the rolled strip is investigated. To do so, a physical model experiment was conducted in the laboratory. The obtained images of defects at light levels in the range of 2–800 lx were recognized by a neural network model based on the U-net architecture with a decoder based on ResNet152. Two levels of illumination were identified, at which the total area of recognized defects increased: 50 lx and 300 lx. A quantitative assessment of the overall accuracy of defect recognition was conducted on the basis of comparison with data from images marked by an expert. The best recognition result (with Dice similarity coefficient DSC = 0.89) was obtained for the illumination of 300 lx. At lower light levels (less than 200 lx), some of the damage remained unrecognized. At high light levels (higher than 500 lx), a decrease in DSC was observed, mainly due to the fact that the surface objects are better visible and the recognized fragments become wider. In addition, more false-positives fragments were recognized. The obtained results are valuable for further adjustment of industrial systems for diagnosing technological defects on rolled metal strips.
Classification of Chemicals Based on Structured Toxicity Information

Matthew T. Martin Classification of Chemicals Based on Structured Toxicity Information “Under the direction of Drs. David J. Dix and Ivan Rusyn” Thirty years and millions of dollars worth of pesticide registration toxicity studies, historically stored as hardcopy and scanned documents, have been digitized into highly standardized and structured toxicity data within the Toxicity Reference Database (ToxRefDB). Toxicity-based classifications of chemicals were performed as a model application of ToxRefDB. These endpoints will ultimately provide the anchoring toxicity information for the development of predictive models and biological signatures utilizing in vitro assay data. Utilizing query and structured data mining approaches, toxicity profiles were uniformly generated for greater than 300 chemicals. Based on observation rate, species concordance and regulatory relevance, individual and aggregated effects have been selected to classify the chemicals providing a set of predictable endpoints. ToxRefDB exhibits the utility of transforming unstructured toxicity data into structured data and, furthermore, into computable outputs, and serves as a model for applying such data to address modern toxicological problems.