bluuebunny/crossref_metadata_2025 huggingface dataset:
An Adaptive Deep Ensemble Learning Method for Dynamic Evolving Diagnostic Task Scenarios
Authors: Su Kaixiang , Wu Jiao , Gu Dongxiao , Yang Shanlin , Deng Shuyuan , Khakimova Aida K.
Published: December 2021

Increasingly, machine learning methods have been applied to aid in diagnosis with good results. However, some complex models can confuse physicians because they are difficult to understand, while data differences across diagnostic tasks and institutions can cause model performance fluctuations. To address this challenge, we combined the Deep Ensemble Model (DEM) and tree-structured Parzen Estimator (TPE) and proposed an adaptive deep ensemble learning method (TPE-DEM) for dynamic evolving diagnostic task scenarios. Different from previous research that focuses on achieving better performance with a fixed structure model, our proposed model uses TPE to efficiently aggregate simple models more easily understood by physicians and require less training data. In addition, our proposed model can choose the optimal number of layers for the model and the type and number of basic learners to achieve the best performance in different diagnostic task scenarios based on the data distribution and characteristics of the current diagnostic task. We tested our model on one dataset constructed with a partner hospital and five UCI public datasets with different characteristics and volumes based on various diagnostic tasks. Our performance evaluation results show that our proposed model outperforms other baseline models on different datasets. Our study provides a novel approach for simple and understandable machine learning models in tasks with variable datasets and feature sets, and the findings have important implications for the application of machine learning models in computer-aided diagnosis.
Dynamic Doppler Ultrasound Assessment of Tissue Perfusion Is a Better Tool than a Single Vessel Doppler Examination in Differentiating Malignant and Inflammatory Pancreatic Lesions
Authors: Dyrla Przemysław , Lubas Arkadiusz , Gil Jerzy , Saracyn Marek , Gonciarz Maciej
Published: December 2021

Dynamic tissue perfusion measurement (DTPM) and single vessel flow measurement (SVFM) were assessed in differentiating inflammatory and malignant lesions of the pancreas. Sixty-nine patients (age 62.0 ± 14.7; 33 Female and 36 Men; 40 with malignant and 29 with inflammatory lesions) in whom during the endoscopic ultrasound (EUS) of focal pancreatic lesions it was possible to adequately evaluate the flow in the color Doppler, and then perform a biopsy, were qualified for the study. The assessed DTPM parameters flow velocity (TFV), perfusion intensity (TPI), and resistive index (TRI) as well as the following SVFM parameters: flow velocity (FV), volume flow (VolF), and resistive index (RI) differed significantly between the malignant and inflammatory lesions (p < 0.005). TFV and TPI have slightly better discriminatory properties than the corresponding FV and VolF parameters (p < 0.10). Considering the Doppler parameters usually evaluated in a given method, the TPI = 0.009 cm/s (sensitivity 79%, specificity 92%, AUC 0.899, p < 0.001) was significantly better (p = 0.014) in differentiating between inflammatory and malignant pancreatic lesions in comparison to FV = 2.526 cm/s (sensitivity 79%, specificity 70%, AUC 0.731, p < 0.001). Tissue perfusion has better discriminatory properties in the differentiation of solid pancreatic lesions than the Doppler blood flow examination in the single vessel within the tumor.
Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C
Authors: Stämmler Frank , Grassi Marcello , Meeusen Jeffrey , Lieske John , Dasari Surendra , Dubourg Laurence , Lemoine Sandrine , Ehrich Jochen , Schiffer Eric
Published: December 2021

Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived ‘metabolite constellation’ (GFRNMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFRNMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFRNMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (−1.0; 1.0) mL/min/1.73 m2 for GFRNMR vs. −6.0 (−7.0; −5.0) mL/min/1.73 m2 for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI2012) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFRNMR vs. 47.3% (43.2; 51.5) for CKD-EPI2012 (p < 0.010). Thus, GFRNMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.
High-Energy Ejection of Molecules and Gas-Dust Outbursts in Coal Mines
Authors: Kaim Sergii D.
Published: December 2021

In the current work, using the framework of the formalism found in the Bogolyubov–Born–Green–Kirkwood–Yvon (BBGKY) equations for the distribution functions of particle groups, the effective single-particle potential near the surface of the liquid was analyzed. The thermodynamic conditions under which a sudden opening of the liquid surface leads to high-energy ejection of atoms and molecules were found. The energies of the emitted particles were observed to be able to significantly exceed their thermal energy. Criteria of the ejection stability of the liquid surface and the self-acceleration of ejection were formulated. The developed theory was used to explain the phenomenon of the self-acceleration of gas-dust outbursts in coal mines during the explosive opening of methane traps. The results also explained the mechanisms of generating significant amounts of methane and the formation of coal nanoparticles in gas-dust outbursts. The developed approach was also used to explain the phenomenon of the self-ignition of hydrogen when it enters the atmosphere.
Assessment of Anxiety in Cognitive-Behavior Therapy in Young University Students with Autism Spectrum Disorders: A Review
Authors: Sánchez-Cueva Sarah , Alonso-Esteban Yurena , Alcantud-Marín Francisco
Published: December 2021

The university provides academic support to disabled students, however, few institutions provide academic, extra-academic or preventive support to students with Autism Spectrum Disorders High-Functioning (ASD-HF). Among the most commonly requested needs is support for coping with anxiety arising from academic and social activity itself. When planning an intervention program, it is necessary to screen those who have problems and are likely to benefit from such a program. In this article we propose a systematic search for measures of anxiety for young people and adults with ASD-HF. Of a total of 683 documents, only 7 met the selection criteria. Of these, a total of 35 tools were detected, of which only 11 mediated anxiety. Screening should be carried out for all students, so that we can detect the “risk” of anxiety disturbance in all cases and, in particular, in students with ASD-HF. However, the instruments eligible for assessing intervention outcomes should be agreed upon in order to be able to compare results from different trials.
Psychophysiological Regulation and Classroom Climate Influence First and Second Graders’ Well-Being: The Role of Body Mass Index
Authors: Scrimin Sara , Peruzza Marta , Mastromatteo Libera Ylenia , Patron Elisabetta
Published: December 2021

This study examines the associations between physical and emotional well-being and classroom climate, cardiac vagal response, and body mass index (BMI) in a sample of 6- to-8-year-olds. Specifically, we expected a direct link between classroom climate, vagal withdrawal, BMI and children’s physical and emotional comfort. Furthermore, we explored whether these individual and environmental characteristics influenced well-being in an interactive fashion. Participants were 142 (63 boys, 44%) first and second graders living in the North of Italy who were interviewed on their emotional and physical comfort. Heart rate and a measure of vagal influence on the heart (cardiac vagal tone) were recorded at rest and during an oral academic test. Height and weight were collected. Classroom climate was positively linked with physical well-being, whereas emotional well-being was negatively related with BMI. In addition, an inverted U-shaped effect of cardiac vagal withdrawal (i.e., cardiac vagal tone during stress minus resting vagal tone) on emotional well-being was found. Two regression models highlighted the role played by BMI when interacting with vagal withdrawal in predicting children’s physical and emotional well-being. The interplay between BMI and cardiac vagal withdrawal played an important role in primary school children’s well-being. From a clinical perspective, preventive training to improve autonomic regulation in concert with interventions promoting healthy eating attitudes might be critical for supporting primary school children’s emotional and physical health.
Stress Axis in the Cancer Patient: Clinical Aspects and Management
Authors: Francesco Felicetti , Alice Nervo , Filippo Gatti , Daniela Rosso , Enrico Brignardello , Emanuela Arvat
Published: December 2021

Hypothalamus–pituitary–adrenal (HPA) axis alterations are common in cancer patients, mainly due to the different antitumoral therapies, which lead to several acute and late endocrine side effects. This review summarizes the most recent evidence regarding HPA derangement, both in patients with active neoplasms and in cancer survivors, with particular attention to the impact of the different antitumoral treatments, focusing on the major clinical aspects. While acute hormone failure usually results from injury caused directly by tumor burden or surgical interventions, short- and long-term effects are generally due to chemotherapy, radiotherapy and, as more recently shown, to different types of targeted- and immuno-therapy. Adrenal insufficiency (AI) is mostly caused by pituitary or hypothalamic injury rather than a direct damage of the adrenal gland. Moreover, other treatments commonly employed as supportive therapy or in the context of palliative care (i.e., glucocorticoids, opioids) can lead to HPA dysfunction. Epidemiology and pathophysiology of stress axis alterations in cancer patients still require clarification. Since AI may represent a life-threatening condition, monitoring adrenal function in cancer patients is mandatory, especially in subjects who experience fatigue or during stress conditions, in order to promptly start replacement treatment when needed.
Properties of Plywood Made from Perforated Veneers
Authors: Fekiač Jozef , Gáborík Jozef , Vojtkuliak Marek
Published: December 2021

The paper is focused on the bending properties of beech plywood made from veneers with perforations. The modification of the plywood was done by the targeted perforations in veneers used. The perforations were rectangular in shape 5 × 30 mm. There was a gap of 10 mm between the perforations (in each direction) and the perforations in the individual rows were shifted by 10 mm relative to each other. Two structures of lightweight plywood were investigated: sheathed (lightweight type 1) with perforated inner layers sheathed with solid veneer and perforated (lightweight type 2) with perforations in each layer. Bending properties were evaluated by three-point bend testing. The results showed decreased bending strength (MOR) as well as decreased modulus of elasticity in bending (MOE) with reduction of weight. Bending strength (MOR) was reduced by 33 to 57% and modulus of elasticity (MOE) by 13 to 43% compared to standard (non-lightweight) plywood. Bendability of lightweight plywood expressed by the minimum bending radius (Rmin) and the coefficient of bendability (koh) point to a slight decrease in bendability by 1 to 35% compared to standard (non-lightweight) plywood. The benefit of the proposed plywood lightweight constructions is weight reduction by 16.5 to 24.4%.
Are Climates in Canada and the United States Suitable for the European Spruce Bark Beetle, Ips typographus, and Its Fungal Associate, Endoconidiophora polonica?
Authors: Sambaraju Kishan R. , Côté Chantal
Published: December 2021

Invasions of exotic forest insects and pathogens can devastate evolutionarily naïve habitats and could cause irreversible changes to urban and natural ecosystems. Given the ever-increasing volume of trade in wood and plant stock worldwide, establishment of non-native pests under climate change is one of the most important forest health concerns currently. The European spruce bark beetle, Ips typographus, is a damaging, phloem-feeding insect of Norway spruce, Picea abies, in Eurasia. Endoconidiophora polonica is the most virulent ophiostomatoid fungal associate of I. typographus. Spruce species native to North America are susceptible to this insect-pathogen complex. We studied the suitability of ‘current’ (1970–2000) and future climates (2021–2100) in Canada and the United States for these two species via ensemble species distribution models. We also determined overlapping regions favorable to both I. typographus and E. polonica. Our results indicate that, currently, climate is particularly suitable for I. typographus and E. polonica in western Canada and throughout the United States. Northward shifts in climatic suitability are projected to occur in Canada for both species under climate change. By the end of the 21st century, a coast-to-coast corridor of climatic suitability for I. typographus and E. polonica will occur in Canada under high-temperature regimes.
Residual Stress-Strain Relationship of Scoria Aggregate Concrete with the Addition of PP Fiber after Fire Exposure
Authors: Cai Bin , Tao Yu , Fu Feng
Published: December 2021

Scoria aggregate concrete (SAC) as new green material has been gradually used in some construction projects for its lightweight and high strength, which can reduce the environmental impact of construction materials. In this paper, the residual mechanical properties and intact compressive stress-strain relationships of polypropylene (PP) fiber-reinforced Scoria aggregate concrete after high-temperature exposure at 20, 200, 400, 600, and 800 °C were investigated. The failure modes of PP fiber-reinforced Scoria aggregate concrete specimens and the effect of high temperatures on the peak stress, secant modulus, and peak strain were obtained. The results showed that the residual compressive strength of heated concrete is significantly reduced when the temperature exceeds 400 °C. The residual strength and residual secant modulus of PP fiber-reinforced Scoria aggregate concrete are significantly higher than those of ordinary concrete. The Scoria aggregate concrete specimens with PP fibers exhibited fewer surface cracks and fewer edge bursts under high temperatures. The residual stress-strain equation of the Scoria aggregate concrete was established by regression analysis, which agreed well with the experimental results.
A Hybrid LSTM-CPS Approach for Long-Term Prediction of Train Delays in Multivariate Time Series
Authors: Wu Jianqing , Du Bo , Wu Qiang , Shen Jun , Zhou Luping , Cai Chen , Zhai Yanlong , Wei Wei , Zhou Qingguo
Published: December 2021

In many big cities, train delays are among the most complained-about events by the public. Although various models have been proposed for train delay prediction, prior studies on both primary and secondary train delay prediction are limited in number. Recent advances in deep learning approaches and increasing availability of various data sources has created new opportunities for more efficient and accurate train delay prediction. In this study, we propose a hybrid deep learning solution by integrating long short-term memory (LSTM) and Critical Point Search (CPS). LSTM deals with long-term prediction tasks of trains’ running time and dwell time, while CPS uses predicted values with a nominal timetable to identify primary and secondary delays based on the delay causes, run-time delay, and dwell time delay. To validate the model and analyse its performance, we compare the standard LSTM with the proposed hybrid model. The results demonstrate that new variants outperform the standard LSTM, based on predicting time steps of dwell time feature. The experiment results also showed many irregularities of historical trends, which draws attention for further research.
Game Awareness: A Questionnaire
Authors: Kostelić Katarina
Published: December 2021

This paper deals with one of the possible methodological approaches to an empirical examination of game awareness. Such an outline should enable the gathering of a deeper understanding of individuals’ awareness. The questionnaire is based on a scenario technique, and it is focused on game awareness in situations with possible strategic interactions. The goal is to assess the instrument regarding its reliability and validity. Internal reliability is assessed using Cronbach’s alpha coefficient. A k-nn analysis was used to estimate divergent construct validity and criterion validity, and nonparametric factor analysis was used to estimate convergent construct validity. The questionnaire satisfies the requirements of reliability and validity. Moreover, there is an indication that each of the eight scenarios may be used separately, as they also meet the criteria for reliability and validity. Possible practical and theoretical implications involve questionnaire use as a basis for educational intervention, other instruments’ development, as well as for the collection and publication of behavioral insights about game awareness. Behavioral insights should enrich the theory and incite behavioral game theory models of game awareness and its implications.
The APOE ε4 Allele Affects Cognitive Functions Differently in Carriers of APP Mutations Compared to Carriers of PSEN1 Mutations in Autosomal-Dominant Alzheimer’s Disease
Authors: Almkvist Ove , Graff Caroline
Published: December 2021

Mounting evidence shows that the APOE ε4 allele interferes with cognition in sporadic Alzheimer’s disease. Less is known about APOE in autosomal-dominant Alzheimer’s disease (adAD). The present study explored the effects on cognition associated with the gene–gene interactions between the APOE gene and the APP and PSEN1 genes in adAD. This study includes mutation carriers (MC) and non-carriers (NC) from adAD families with mutations in APP (n = 28 and n = 25; MC and NC, respectively) and PSEN1 (n = 12 and n = 15; MC and NC, respectively) that represent the complete spectrum of disease: AD dementia (n = 8) and mild cognitive impairment (MCI, n = 15 and presymptomatic AD, n = 17). NC represented unimpaired normal aging. There was no significant difference in the distribution of APOE ε4 (absence vs. presence) between the APP vs. PSEN1 adAD genes and mutation status (MC vs. NC). However, episodic memory was significantly affected by the interaction between APOE and the APP vs. PSEN1 genes in MC. This was explained by favorable performance in the absence of APOE ε4 in PSEN1 compared to APP MC. Similar trends were seen in other cognitive functions. No significant associations between APOE ε4 and cognitive performance were obtained in NC. In conclusion, cognitive effects of APOE–adAD gene interaction were differentiated between the PSEN1 and APP mutation carriers, indicating epistasis.
Unschooling and Indigenous Education
Authors: Romero Noah , Yellowhorse Sandra
Published: December 2021

This article draws from autoethnography and historical analysis to examine how racialized people pursue educational justice, consent, inclusion, and enjoyment through non-hegemonic learning. A historical analysis of U.S. colonial education systems imposed upon Diné and Philippine peoples grounds a comparative study on two forms of anti-colonial pedagogy: Indigenous education and critical unschooling. These two lines of inquiry underpin autoethnographic analyses of our own experiences in non-hegemonic learning to offer direct insights into the process of experiential, and decolonial growth intimated in relational learning environments. Indigenous education and critical unschooling literature both affirm the notion that all learners are always already educators and students, regardless of their age, ability, or status. This notion reorients the processes and aspirations of education toward an understanding that everyone holds valuable knowledge and is inherently sovereign. These relational values link together to form systems of circular knowledge exchange that honour the gifts of all learners and create learning environments where every contribution is framed as vital to the whole of the community. This study shows that because these principles resonate in multiple sites of colonial contact across Philippine and Diné knowledge systems, through Indigenous education and critical unschooling, and in our own lived experiences, it is important to examine these resonant frequencies together as a syncretic whole and to consider how they can inform further subversions of hegemonic educational frameworks.
Effectiveness of BNT162b2 and ChAdOx1 Vaccines against Symptomatic COVID-19 among Healthcare Workers in Kuwait: A Retrospective Cohort Study
Authors: Alali Walid Q. , Ali Lamiaa A. , AlSeaidan Mohammad , Al-Rashidi Mohammad
Published: December 2021

Background: Estimating vaccine effectiveness (VE) against severe, acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among healthcare workers (HCWs) is necessary to demonstrate protection from the disease. Between 24 December 2020 and 15 June 2021, we determined the factors associated with vaccine coverage and estimated VE against SARS-CoV-2 infection in HCWs at a secondary hospital in Kuwait. Methods: We extracted sociodemographic, occupational, SARS-CoV-2 infection, and vaccination data for eligible HCWs from the hospital records. Vaccine coverage percentages were cross-tabulated with the HCW factors. Cox regression was used to estimate hazard ratios in vaccinated versus unvaccinated. Results: 3246 HCWs were included in the analysis, of which 82.1% received at least one vaccine dose (50.4% only one dose of ChAdOx1, 3.3% only one dose of BNT162b2, and 28.3% two doses of BNT162b2). However, 17.9% of HCWs were unvaccinated. A significantly lower vaccination coverage was reported amongst female HCWs, younger age group (20–30 years), and administrative/executive staff. The adjusted VE of fully vaccinated HCWs was 94.5% (95% CI = 89.4–97.2%), while it was 75.4% (95% CI = 67.2–81.6%) and 91.4% (95% CI = 65.1–97.9%) in partially vaccinated for ChAdOx1 and BNT162b2, respectively. Conclusions: BNT162b2 and ChAdOx1 vaccines prevented most symptomatic infections in HCWs across age groups, nationalities, and occupations.
New Targets for PET Imaging of Myeloma
Authors: Revheim Mona-Elisabeth , Stokke Caroline , Nørgaard Jakob Nordberg , Phillips Hilde Feiring , Sherwani Alexander Gul , Schjesvold Fredrik , Connelly James P.
Published: December 2021

Recent advances in the treatment of multiple myeloma (MM) have increased the need for accurate diagnosis and detection of minimal residual disease (MRD), disease characterization and localization, and response evaluation and prognostication. Positron emission tomography (PET)/computed tomography (CT) imaging combines molecular and morphological information and has been shown to be especially valuable in this disease. The most frequently used PET tracer in MM is the glucose analog 18F-fluorodeoxyglucose ([18F]FDG). [18F]FDG PET/CT has a sensitivity for detection of MM between 80% to 100% and is currently the main imaging modality for assessing treatment response and for determining MRD. However, 18F-FDG PET/CT has some limitations, and imaging with alternative tracers that may overcome these constraints should be further explored. This article discusses new targets for PET/CT imaging in the assessment of MM.
Characteristics of Mango Leaf Photosynthetic Inhibition by Enhanced UV-B Radiation
Authors: Wang Hong , Guo Yujian , Zhu Jianjun , Yue Kun , Zhou Kaibing
Published: December 2021

To investigate the photosynthetic change characteristics of mango leaves under enhanced UV-B radiation, adult ‘Tainong No. 1′ mango (Mangifera indica) trees were treated (N = nine individuals) with simulated enhanced UV-B radiation [24 and 96 kJ/(m2·d)] in the field, and the photochemical reactions, activities of key enzymes in carbon assimilation, and the expression of genes were observed. The results showed that compared with the control, there was a decrease in tree yield, soluble sugar, sugar–acid ratio, and vitamin C of the fruits under the 96 kJ/(m2·d) treatment, while no significant changes were observed under 24 kJ/(m2·d). After 20 or 40 days, the leaves’ net photosynthetic rate (Pn), stomatal conductance (Sc), transpiration rate (Tr), intercellular CO2 concentration (Ci), and chlorophyll a/b under exposure to 96 kJ/(m2·d) of UV-B were significantly lower than in the control, whereas chlorophyll a, chlorophyll b, carotenoids, Hill reaction activity, photochemical quenching coefficient (qP), and Rubisco activities were significantly higher. In contrast, the Hill activity and Rubisco activity under 24 kJ/(m2·d) were significantly higher than the control, and increased by 350% and 30.8%, respectively, while Pn, Sc, Tr, Ci, and the content of photosynthetic pigments were similar to the control. The expression of gene coding the Rubisco big subunit (rbcL) was inhibited by the 96 kJ/(m2·d) treatment. We conclude that stomatal limitation was directly induced by 96 kJ/(m2·d), resulting in the inhibition of photosynthesis and the reduction in yield and deterioration of the quality of mango.
Efficiency of Reductive Soil Disinfestation Affected by Soil Water Content and Organic Amendment Rate
Authors: Zhu Rui , Huang Xinqi , Zhang Jinbo , Cai Zucong , Li Xun , Wen Teng
Published: December 2021

Reductive Soil Disinfestation (RSD) is a good method which can restore degraded greenhouse soil and effectively inactivate soil-borne pathogens. However, the approach needs to be optimized in order to facilitate its practical application in various regions. In the present work, we investigated the effect of soil water content (60% water holding capacity (WHC), 100% WHC and continuous flooding) and maize straw application rates (0, 5, 10, and 20 g kg−1 soil) on the improvement of soil properties and suppression of soil-borne pathogens (Fusarium oxysporum, Pythium and Phytophthora). The results showed that increasing the soil water content and maize straw application rate accelerated the removal of excess sulfate and nitrate in the soil and elevated the soil pH. Elevating the water content and maize straw application rate also produced much more organic acids, which could strongly inhibit soil-borne pathogens. Soil properties were improved significantly after RSD treatment with a maize straw amendment rate of more than 5 g kg−1, regardless of the water content. However, RSD treatments with 60% WHC could not effectively inactivate soil-borne pathogens and even stimulated their growth by increasing the maize application rate. RSD treatments of both 100% WHC and continuous flooding could inactivate soil-borne pathogens and increase the pathogens mortality indicated by cultural cells relatively effectively. The inhibited pathogens were significantly increased with the increasing maize application rate from 5 g kg−1 to 10 g kg−1, but were not further increased from 10 g kg−1 to 20 g kg−1. A further increased mortality of F. oxysporum, indicated by gene copies, was also observed when the soil water content and maize straw application rate were increased. Therefore, RSD treatment with 60% WHC could improve soil properties significantly, whereas irrigation with 100% WHC or continuous flooding was a necessity for effective soil-borne pathogens suppression. Holding 100% WHC and applicating maize straw at 10 g kg−1 soil were optimum conditions for RSD field operation to restore degraded greenhouse soil.
Analysis of the Effect on Denture Base Metal of Cleaning with Denture Cleanser Using the Quartz Crystal Microbalance Method
Authors: Imaizumi Naoya , Sakurai Toshitsugu , Hirota Masatsugu , Hayakawa Tohru , Ohkubo Chikahiro
Published: December 2021

Denture plaque control for the prevention of aspiration pneumonia is very important. The pellicle is the major cause of denture plaque adhesion. Few basic studies have evaluated the effectiveness of denture cleansers for pellicles composed of salivary proteins. The adhesion of salivary proteins formed on denture base metal and the removal rate were quantitatively analyzed using the QCM method after denture cleanser injection. This is the first study to compare the cleaning effects of denture cleanser on denture base metal using the QCM method. Au and Ti sensors were employed as the denture base metals. Albumin was used for the adsorption of salivary proteins. The results showed that no significant difference was found between Au and Ti in the amounts of albumin adsorbed, and the rate of albumin removal from Ti was significantly higher than that of Au. In this study, the cleaning effectiveness of denture cleanser was confirmed based on the adsorbed amount and the removal rate of salivary proteins adsorbed onto denture base metals. Thus, the QCM method was suggested to be a useful tool for removing the effects of salivary proteins from denture cleaning agents on denture base metal.
Consequences of COVID-19 on Banking Sector Index: Artificial Neural Network Model
Authors: Assous Hamzeh F. , Al-Najjar Dania
Published: December 2021

The World Health Organization officially declared COVID-19 a global pandemic on 11 March 2020. In this study, we examine the effect of COVID-19 indicators and policy response on the Saudi banking index. COVID-19 variables that were applied are: new confirmed and fatal COVID-19 cases in Saudi Arabia; lockdowns; first and second decreases in interest rates; regulations, and oil prices. We implemented the analysis by running a stepwise regression analysis then building an artificial neural network (ANN) model. According to regression findings, oil prices and new confirmed cases have had a significant positive effect on the Saudi banking index. Nevertheless, the lockdown announcements in Saudi Arabia and the first decrease in interest rates had a significant negative effect on the Saudi banking index. To enhance the performance of the linear regression model, the ANN model was built. Findings showed that the ranking of the variables in terms of their importance is: oil price, number of confirmed cases, lockdown announcements, decrease in interest rates, and lastly, regulations.
Correlation between Oxidative Stress and Transforming Growth Factor-Beta in Cancers
Authors: Chung Jinwook , Huda Md Nazmul , Shin Yoonhwa , Han Sunhee , Akter Salima , Kang Insug , Ha Joohun , Choe Wonchae , Choi Tae Gyu , Kim Sung Soo
Published: December 2021

The downregulation of reactive oxygen species (ROS) facilitates precancerous tumor development, even though increasing the level of ROS can promote metastasis. The transforming growth factor-beta (TGF-β) signaling pathway plays an anti-tumorigenic role in the initial stages of cancer development but a pro-tumorigenic role in later stages that fosters cancer metastasis. TGF-β can regulate the production of ROS unambiguously or downregulate antioxidant systems. ROS can influence TGF-β signaling by enhancing its expression and activation. Thus, TGF-β signaling and ROS might significantly coordinate cellular processes that cancer cells employ to expedite their malignancy. In cancer cells, interplay between oxidative stress and TGF-β is critical for tumorigenesis and cancer progression. Thus, both TGF-β and ROS can develop a robust relationship in cancer cells to augment their malignancy. This review focuses on the appropriate interpretation of this crosstalk between TGF-β and oxidative stress in cancer, exposing new potential approaches in cancer biology.
Molecular Mechanisms of Eosinophilic Esophagitis
Authors: Zhernov Yury V. , Vysochanskaya Sonya O. , Sukhov Vitaly A. , Zaostrovtseva Olga K. , Gorshenin Denis S. , Sidorova Ekaterina A. , Mitrokhin Oleg V.
Published: December 2021

Food hypersensitivity is a group of diseases arising from a specific immune response that reproduces on exposure to a given food. The current understanding of molecular mechanisms and immunopathology of non-IgE-mediated/mixed food hypersensitivity, e.g., eosinophilic esophagitis, contains many gaps in knowledge. This review aims to provide a modern classification and identify the primary diseases of non-IgE-mediated/mixed food hypersensitivity reactions, delineate the distinctive molecular features, and discuss recent findings in the immunopathology of eosinophilic esophagitis that may become a basis to develop valid biomarkers and novel therapies for this disease. Eosinophilic esophagitis is a recently recognized allergic-mediated disease with eosinophil-predominant esophagus inflammation. Its pathogenesis is a complicated network of interactions and signaling between epithelial, mesenchymal, and immune cells on molecular and intercellular levels. Alterations produced by overactivation of some cytokine signaling pathways, e.g., IL-13 or thymic stromal lymphopoietin (TSLP), were evolved and observed in this review from the viewpoints of molecular, genetic, epigenetic, and transcriptomic changes. Despite substantial experimental data, the reliable and representative mechanism of eosinophilic esophagitis pathogenesis has yet to show itself. So, the place of esophagitis between mixed and non-IgE-mediated allergic disorders and between eosinophilic gastrointestinal disorders currently seems vague and unclear.
Selected Methods of Predicting Financial Health of Companies: Neural Networks Versus Discriminant Analysis
Authors: Horváthová Jarmila , Mokrišová Martina , Petruška Igor
Published: December 2021

This paper focuses on the financial health prediction of businesses. The issue of predicting the financial health of companies is very important in terms of their sustainability. The aim of this paper is to determine the financial health of the analyzed sample of companies and to distinguish financially healthy companies from companies which are not financially healthy. The analyzed sample, in the field of heat supply in Slovakia, consisted of 444 companies. To fulfil the aim, appropriate financial indicators were used. These indicators were selected using related empirical studies, a univariate logit model and a correlation matrix. In the paper, two main models were applied—multivariate discriminant analysis (MDA) and feed-forward neural network (NN). The classification accuracy of the constructed models was compared using the confusion matrix, error type 1 and error type 2. The performance of the models was compared applying Brier score and Somers’ D. The main conclusion of the paper is that the NN is a suitable alternative in assessing financial health. We confirmed that high indebtedness is a predictor of financial distress. The benefit and originality of the paper is the construction of an early warning model for the Slovak heating industry. From our point of view, the heating industry works in the similar way in other countries, especially in transition economies; therefore, the model is applicable in these countries as well.
TextQ—A User Friendly Tool for Exploratory Text Analysis
Authors: Edwards April , Sullivan MaryLyn , Itkowsky Ezrah , Weinberg Dana
Published: December 2021

As the amount of textual data available on the Internet grows substantially each year, there is a need for tools to assist with exploratory data analysis. Furthermore, to democratize the process of text analytics, tools must be usable for those with a non-technical background and those who do not have the financial resources to outsource their data analysis needs. To that end, we developed TextQ, which provides a simple, intuitive interface for exploratory analysis of textual data. We also tested the efficacy of TextQ using two case studies performed by subject matter experts—one related to a project on the detection of cyberbullying communication and another related to the user of Twitter for influence operations. TextQ was able to efficiently process over a million social media messages and provide valuable insights that directly assisted in our research efforts on these topics. TextQ is built using an open access platform and object-oriented architecture for ease of use and installation. Additional features will continue to be added to TextQ, based on the needs and interests of the installed base.
Distribution of Two Strains of Leptoglossus zonatus (Dallas) (Hemiptera: Coreidae) in the Western Hemisphere: Is L. zonatus a Potential Invasive Species in California?
Authors: Joyce Andrea L. , Parolini Hannah , Brailovsky Harry
Published: December 2021

The leaffooted plant bug, Leptoglossus zonatus (Dallas) (Hemiptera: Coreidae) is polyphagous and widely distributed in the Western Hemisphere. Although it has been recorded in California since around 1900, it has become a more common pest in almonds in the last decade. Other studies have shown that an established insect can become a pest when a new genotype is introduced. This study investigated the distribution of two lineages (strains) of L. zonatus in the Western Hemisphere. Specimens from the Leptoglossus collection in the national insect collection in Mexico were used to extract DNA and sequence the mitochondrial DNA cytochrome oxidase I (mtDNA COI) gene, for use in population genetic and phylogenetic analyses. New sequences from Mexico, Central and South America were combined with those available in GenBank, from California and Brazil. Two lineages (strains) of L. zonatus were uncovered. One lineage occurs in California, Mexico and Ecuador. The second lineage is more widespread and found in California, Mexico, Guatemala, Nicaragua, Bolivia and Brazil. The haplotype number and diversity, and nucleotide diversity, were found for samples from California, Mexico, and Brazil, for the two lineages, and for all 118 sequences combined. All sequences combined produced five haplotypes, and a haplotype diversity of 0.54. California and Brazil had 3 haplotypes each, with one haplotype shared (5 total). Haplotype diversity in California and in Brazil were 0.526 and 0.505, respectively. A haplotype network found that one haplotype was most abundant and widespread. The small number of haplotypes, a range expansion, and economic pest status of L. zonatus in California, all contribute to this insect being a potentially invasive insect pest.
Preventing Breast Cancer-Related Lymphedema: Feasibility of Axillary Reverse Mapping Technique
Authors: Caziuc Alexandra , Schlanger Diana , Amarinei Giorgiana , Fagarasan Vlad , Andras David , Dindelegan George Calin
Published: December 2021

Introduction. Our study aimed to determine the feasibility of axillary reverse mapping (ARM) technique, the identification rate of ARM nodes and their metastatic involvement, as well as to identify the factors that influence the identification and metastatic involvement. Material and methods. In total, 30 breast cancer patients scheduled for axillary lymph node dissection were enrolled in our study. The lymphatic nodes that drain the arm were identified by injecting 1 mL of blue dye in the ipsilateral upper arm; then, the ARM nodes were resected along with the other lymph nodes and sent for histological evaluation. Results. Identification of ARM node was successful in 18 patients (60%) and 22.22% of the identified ARM lymph nodes had metastatic involvement. Patients with identified ARM nodes had a significant lower BMI and a statistically significant relationship between axillary lymph node status and ARM node metastases was proven. Most of ARM lymph nodes (96.3%) were found above the intercostobrachial nerve, under the axillary vein and lateral to the thoracodorsal bundle. Conclusions. The ARM procedure is easy to reproduce but might not be appropriate for patients with a high BMI. The rate of metastatic involvement of ARM nodes is significant and no factor can predict it, showing that the preservation of these nodes cannot be considered.
Artificial Intelligence: A Shifting Paradigm in Cardio-Cerebrovascular Medicine
Authors: Abedi Vida , Razavi Seyed-Mostafa , Khan Ayesha , Avula Venkatesh , Tompe Aparna , Poursoroush Asma , Vafaei Sadr Alireza , Li Jiang , Zand Ramin
Published: December 2021

The future of healthcare is an organic blend of technology, innovation, and human connection. As artificial intelligence (AI) is gradually becoming a go-to technology in healthcare to improve efficiency and outcomes, we must understand our limitations. We should realize that our goal is not only to provide faster and more efficient care, but also to deliver an integrated solution to ensure that the care is fair and not biased to a group of sub-population. In this context, the field of cardio-cerebrovascular diseases, which encompasses a wide range of conditions—from heart failure to stroke—has made some advances to provide assistive tools to care providers. This article aimed to provide an overall thematic review of recent development focusing on various AI applications in cardio-cerebrovascular diseases to identify gaps and potential areas of improvement. If well designed, technological engines have the potential to improve healthcare access and equitability while reducing overall costs, diagnostic errors, and disparity in a system that affects patients and providers and strives for efficiency.
Diagnostic, Prognostic, and Therapeutic Value of Droplet Digital PCR (ddPCR) in COVID-19 Patients: A Systematic Review
Authors: Ishak Angela , AlRawashdeh Mousa M. , Esagian Stepan M. , Nikas Ilias P.
Published: December 2021

Accurate detection of SARS-CoV-2, the pathogen causing the global pandemic of COVID-19, is essential for disease surveillance and control. Quantitative reverse transcription PCR (RT-qPCR) is considered the reference standard test for the diagnosis of SARS-CoV-2 by the World Health Organization and Centers for Disease Control and Prevention. However, its limitations are a prompt for a more accurate assay to detect SARS-CoV-2, quantify its levels, and assess the prognosis. This article aimed to systematically review the literature and assess the diagnostic performance of droplet digital PCR (ddPCR), also to evaluate its potential role in prognosis and management of COVID-19 patients. PubMed and Scopus databases were searched to identify relevant articles published until 13 July 2021. An additional PubMed search was performed on 21 October 2021. Data from the 39 eligible studies were extracted and an overall 3651 samples from 2825 patients and 145 controls were used for our qualitative analysis. Most studies reported ddPCR was more accurate than RT-qPCR in detecting and quantifying SARS-CoV-2 levels, especially in patients with low viral loads. ddPCR was also found highly effective in quantifying SARS-CoV-2 RNAemia levels in hospitalized patients, monitoring their disease course, and predicting their response to therapy. These findings suggest ddPCR could serve as a complement or alternative SARS-CoV-2 tool with emerging diagnostic, prognostic, and therapeutic value, especially in hospital settings. Additional research is still needed to standardize its laboratory protocols, also to accurately assess its role in monitoring COVID-19 therapy response and in identifying SARS-CoV-2 emerging variants.
Three-Dimensional-Printed Scaffolds for Meniscus Tissue Engineering: Opportunity for the Future in the Orthopaedic World
Authors: Vasiliadis Angelo V. , Koukoulias Nikolaos , Katakalos Konstantinos
Published: December 2021

The meniscus is a critical component of a healthy knee joint. It is a complex and vital fibrocartilaginous tissue that maintains appropriate biomechanics. Injuries of the meniscus, particularly in the inner region, rarely heal and usually progress into structural breakdown, followed by meniscus deterioration and initiation of osteoarthritis. Conventional therapies range from conservative treatment, to partial meniscectomy and even meniscus transplantation. All the above have high long-term failure rates, with recurrence of symptoms. This communication presents a brief account of in vitro and in vivo studies and describes recent developments in the field of 3D-printed scaffolds for meniscus tissue engineering. Current research in meniscal tissue engineering tries to combine polymeric biomaterials, cell-based therapy, growth factors, and 3D-printed scaffolds to promote the healing of meniscal defects. Today, 3D-printing technology represents a big opportunity in the orthopaedic world to create more specific implants, enabling the rapid production of meniscal scaffolds and changing the way that orthopaedic surgeons plan procedures. In the future, 3D-printed meniscal scaffolds are likely to be available and will also be suitable substitutes in clinical applications, in an attempt to imitate the complexity of the native meniscus.
Using Inertial Sensors to Determine Head Motion—A Review
Authors: Ionut-Cristian Severin , Dan-Marius Dobrea
Published: December 2021

Human activity recognition and classification are some of the most interesting research fields, especially due to the rising popularity of wearable devices, such as mobile phones and smartwatches, which are present in our daily lives. Determining head motion and activities through wearable devices has applications in different domains, such as medicine, entertainment, health monitoring, and sports training. In addition, understanding head motion is important for modern-day topics, such as metaverse systems, virtual reality, and touchless systems. The wearability and usability of head motion systems are more technologically advanced than those which use information from a sensor connected to other parts of the human body. The current paper presents an overview of the technical literature from the last decade on state-of-the-art head motion monitoring systems based on inertial sensors. This study provides an overview of the existing solutions used to monitor head motion using inertial sensors. The focus of this study was on determining the acquisition methods, prototype structures, preprocessing steps, computational methods, and techniques used to validate these systems. From a preliminary inspection of the technical literature, we observed that this was the first work which looks specifically at head motion systems based on inertial sensors and their techniques. The research was conducted using four internet databases—IEEE Xplore, Elsevier, MDPI, and Springer. According to this survey, most of the studies focused on analyzing general human activity, and less on a specific activity. In addition, this paper provides a thorough overview of the last decade of approaches and machine learning algorithms used to monitor head motion using inertial sensors. For each method, concept, and final solution, this study provides a comprehensive number of references which help prove the advantages and disadvantages of the inertial sensors used to read head motion. The results of this study help to contextualize emerging inertial sensor technology in relation to broader goals to help people suffering from partial or total paralysis of the body.