bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning-Based Identifications of COVID-19 Fake News Using Biomedical Information Extraction
Authors: Fifita Faizi , Smith Jordan , Hanzsek-Brill Melissa B. , Li Xiaoyin , Zhou Mengshi
Published: March 2023

The spread of fake news related to COVID-19 is an infodemic that leads to a public health crisis. Therefore, detecting fake news is crucial for an effective management of the COVID-19 pandemic response. Studies have shown that machine learning models can detect COVID-19 fake news based on the content of news articles. However, the use of biomedical information, which is often featured in COVID-19 news, has not been explored in the development of these models. We present a novel approach for predicting COVID-19 fake news by leveraging biomedical information extraction (BioIE) in combination with machine learning models. We analyzed 1164 COVID-19 news articles and used advanced BioIE algorithms to extract 158 novel features. These features were then used to train 15 machine learning classifiers to predict COVID-19 fake news. Among the 15 classifiers, the random forest model achieved the best performance with an area under the ROC curve (AUC) of 0.882, which is 12.36% to 31.05% higher compared to models trained on traditional features. Furthermore, incorporating BioIE-based features improved the performance of a state-of-the-art multi-modality model (AUC 0.914 vs. 0.887). Our study suggests that incorporating biomedical information into fake news detection models improves their performance, and thus could be a valuable tool in the fight against the COVID-19 infodemic.
Seasonal Changes in the Biochemical Composition of Dominant Macroalgal Species along the Egyptian Red Sea Shore
Authors: Kamal Marwa , Abdel-Raouf Neveen , Alwutayd Khairiah , AbdElgawad Hamada , Abdelhameed Mohamed Sayed , Hammouda Ola , Elsayed Khaled N. M.
Published: March 2023

Macroalgae are significant biological resources in coastal marine ecosystems. Seasonality influences macroalgae biochemical characteristics, which consequentially affect their ecological and economic values. Here, macroalgae were surveyed from summer 2017 to spring 2018 at three sites at 7 km (south) from El Qusier, 52 km (north) from Marsa Alam and 70 km (south) from Safaga along the Red Sea coast, Egypt. Across all the macroalgae collected, Caulerpa prolifera (green macroalgae), Acanthophora spicifera (red macroalgae) and Cystoseira myrica, Cystoseira trinodis and Turbinaria ornata (brown macroalgae) were the most dominant macroalgal species. These macroalgae were identified at morphological and molecular (18s rRNA) levels. Then, the seasonal variations in macroalgal minerals and biochemical composition were quantified to determine the apt period for harvesting based on the nutritional requirements for commercial utilizations. The chemical composition of macroalgae proved the species and seasonal variation. For instance, minerals were more accumulated in macroalgae C. prolifera, A. spicifera and T. ornata in the winter season, but they were accumulated in both C. myrica and C. trinodis in the summer season. Total sugars, amino acids, fatty acids and phenolic contents were higher in the summer season. Accordingly, macroalgae collected during the summer can be used as food and animal feed. Overall, we suggest the harvesting of macroalgae for different nutrients and metabolites in the respective seasons.
Transportan 10 Induces Perturbation and Pores Formation in Giant Plasma Membrane Vesicles Derived from Cancer Liver Cells
Authors: Anselmo Sara , Sancataldo Giuseppe , Baiamonte Concetta , Pizzolanti Giuseppe , Vetri Valeria
Published: March 2023

Continuous progress has been made in the development of new molecules for therapeutic purposes. This is driven by the need to address several challenges such as molecular instability and biocompatibility, difficulties in crossing the plasma membrane, and the development of host resistance. In this context, cell-penetrating peptides (CPPs) constitute a promising tool for the development of new therapies due to their intrinsic ability to deliver therapeutic molecules to cells and tissues. These short peptides have gained increasing attention for applications in drug delivery as well as for their antimicrobial and anticancer activity but the general rules regulating the events involved in cellular uptake and in the following processes are still unclear. Here, we use fluorescence microscopy methods to analyze the interactions between the multifunctional peptide Transportan 10 (TP10) and the giant plasma membrane vesicles (GPMVs) derived from cancer cells. This aims to highlight the molecular mechanisms underlying functional interactions which bring its translocation across the membrane or cytotoxic mechanisms leading to membrane collapse and disruption. The Fluorescence Lifetime Imaging Microscopy (FLIM) method coupled with the phasor approach analysis proved to be the winning choice for following highly dynamic spatially heterogeneous events in real-time and highlighting aspects of such complex phenomena. Thanks to the presented approach, we were able to identify and monitor TP10 translocation into the lumen, internalization, and membrane-induced modifications depending on the peptide concentration regime.
Role of Glutamatergic Projections from Lateral Habenula to Ventral Tegmental Area in Inflammatory Pain-Related Spatial Working Memory Deficits
Authors: Alemi Mobina , Pereira Ana Raquel , Cerqueira-Nunes Mariana , Monteiro Clara , Galhardo Vasco , Cardoso-Cruz Helder
Published: March 2023

The lateral habenula (LHb) and the ventral tegmental area (VTA), which form interconnected circuits, have important roles in the crucial control of sensory and cognitive motifs. Signaling in the LHb-VTA pathway can be exacerbated during pain conditions by a hyperactivity of LHb glutamatergic neurons to inhibit local VTA DAergic cells. However, it is still unclear whether and how this circuit is endogenously engaged in pain-related cognitive dysfunctions. To answer this question, we modulated this pathway by expressing halorhodopsin in LHb neurons of adult male rats, and then selectively inhibited the axonal projections from these neurons to the VTA during a working memory (WM) task. Behavioral performance was assessed after the onset of an inflammatory pain model. We evaluated the impact of the inflammatory pain in the VTA synapses by performing immunohistochemical characterization of specific markers for GABAergic (GAD65/67) and dopaminergic neurons (dopamine transporter (DAT), dopamine D2 receptor (D2r) and tyrosine hydroxylase (TH)). Our results revealed that inhibition of LHb terminals in the VTA during the WM delay-period elicits a partial recovery of the performance of pain animals (in higher complexity challenges); this performance was not accompanied by a reduction of nociceptive responses. Finally, we found evidence that the pain-affected animals exhibit VTA structural changes, namely with an upregulation of GAD65/67, and a downregulation of DAT and D2r. These results demonstrate a role of LHb neurons and highlight their responsibility in the stability of the local VTA network, which regulates signaling in frontal areas necessary to support WM processes.
3D Electrospun Polycaprolactone Scaffolds to Assess Human Periodontal Ligament Cells Mechanobiological Behaviour
Authors: Gauthier Rémy , Attik Nina , Chevalier Charlène , Salles Vincent , Grosgogeat Brigitte , Gritsch Kerstin , Trunfio-Sfarghiu Ana-Maria
Published: March 2023

While periodontal ligament cells are sensitive to their 3D biomechanical environment, only a few 3D in vitro models have been used to investigate the periodontal cells mechanobiological behavior. The objective of the current study was to assess the capability of a 3D fibrous scaffold to transmit a mechanical loading to the periodontal ligament cells. Three-dimensional fibrous polycaprolactone (PCL) scaffolds were synthetized through electrospinning. Scaffolds seeded with human periodontal cells (103 mL−1) were subjected to static (n = 9) or to a sinusoidal axial compressive loading in an in-house bioreactor (n = 9). At the end of the culture, the dynamic loading seemed to have an influence on the cells’ morphology, with a lower number of visible cells on the scaffolds surface and a lower expression of actin filament. Furthermore, the dynamic loading presented a tendency to decrease the Alkaline Phosphatase activity and the production of Interleukin-6 while these two biomolecular markers were increased after 21 days of static culture. Together, these results showed that load transmission is occurring in the 3D electrospun PCL fibrous scaffolds, suggesting that it can be used to better understand the periodontal ligament cells mechanobiology. The current study shows a relevant way to investigate periodontal mechanobiology using 3D fibrous scaffolds.
There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines
Authors: Bongard Joshua , Levin Michael
Published: March 2023

The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.
Experimental Study on Seismic Behavior of Damaged Beam-Column Joints Retrofitted by Viscoelastic Steel-Enveloped Elements
Authors: Huang Xing-Huai , Xu Zhao-Dong , Xiao Han-Jie
Published: March 2023

In order to improve the seismic performance of damaged reinforced concrete joints, a new retrofitting method using viscoelastic materials and steel plates is proposed. A reversal cyclic loading test was carried out on four T-shaped RC joints to investigate the reliability of this method. Seismic performance, including the strength, stiffness, ductility, and energy dissipation capacity of the original non-damaged joint and different repaired and retrofitted joints are then compared. The results show that this new method can significantly improve the strength of the retrofitted joints, and the joints can be loaded to a larger displacement value. After retrofitting, the energy dissipation of the joints increases, and the stiffness degradation decreases. The test results indicate that the retrofitting method is effective in repairing seismically damaged RC joints.
Preventive Measures of Alkali–Silica Reaction in Concrete Buildings: Use of Hybrid Waste Coal Ash and Steel Wire Cut Fibers
Authors: Abbas Safeer
Published: March 2023

The main cause of premature deterioration in concrete buildings is linked with the alkali–silica reaction (ASR) owing to the use of reactive aggregates and severe exposure conditions. This research aimed to explore the mitigation of ASR in concrete buildings using waste coal ash (CA) and steel fibers cut from long wire. CA and SF were acquired from a local market. The studied dosages of CA were 10%, 20%, 30% and 40% by cement weight and steel fibers were added at 0.5% and 1% of the total volume of the mixture. Specimens were cast and immersed in a 1N NaOH solution at 80 °C for 90 days as per ASTM C1260 guidelines. The compressive and flexural strengths of the control mixture without CA and the mixture with 10% of CA had a comparable behavior. A decrease in the compressive and flexural strengths was observed for higher dosages of CA (30% and 40%). Specimens incorporating 30% of CA showed a compressive strength of 24 MPa at 56 days compared to that of 33 MPa for the identical control specimen without CA. This strength decrease was due to the porous nature of the used CA and was compensated for by the incorporation of steel fibers. Specimens with 1% of steel fibers exhibited higher strength properties compared to those with 0.5% of steel fibers for all the tested dosages of CA. The control specimens without CA and steel fibers showed expansions higher than 0.10% and 0.20% at 14 and 28 days, respectively, demonstrating their reactive behavior. The hybrid incorporation of CA and steel fibers decreased the ASR expansion. The mortar bar specimen incorporating 10% of CA and 1% of steel fibers showed an expansion of 0.168% at 28 days compared to that of 0.321% for the control specimen without CA and steel fibers. A decrease in the compressive and flexural strengths was observed for the specimen placed in ASR exposure conditions compared to identical specimens placed in normal water. However, specimens incorporating CA and steel fibers showed relatively fewer effects under the ASR exposure conditions. The control specimens without CA and steel fibers also showed micro-cracking due to ASR exposure, as observed through scanning electron microscopy. This study will assist practitioners to construct a sustainable building using locally available waste materials with the additional advantage of mitigating the ASR-related damages.
Prognostic Significance of Esophagogastric Junction Invasion in Patients with Adenocarcinoma of the Cardia or Subcardia
Authors: Oh Sung Eun , Park Sujin , Ahn Soomin , An Ji Yeong , Lee Jun Ho , Sohn Tae Sung , Bae Jae Moon , Choi Min-Gew
Published: March 2023

Background: There has been no comparison of the prognoses of Korean patients who underwent curative surgery for cancer located at the cardia or subcardia of the stomach. We performed this comparison and further investigated the prognostic significance of esophagogastric junction (EGJ) invasion in patients. Methods: The medical records of patients (n = 511) who were diagnosed with cardia or subcardia cancer and underwent surgery between January 2010 and May 2019 were retrospectively reviewed. Patients were further categorized into four groups for analysis: subcardia gastric cancer (sGC; subcardia cancer without EGJ invasion; n = 97), AEG (adenocarcinoma of the esophagogastric junction) type III (subcardia cancer with EGJ invasion, n = 54), AEG type II without EGJ invasion (n = 158), and AEG type II with EGJ invasion (n = 202). We compared the overall survival of the four groups using a gastric cancer staging system and evaluated the prognostic significance of EGJ invasion with multivariate analysis. Results: The median follow-up of patients was 46.0 months (range: 0–124 months). There was significant difference in overall survival curves among the four groups (p < 0.001). Subgroup analysis showed a significant difference in overall survival between the groups with and without EGJ invasion (p < 0.001). Cancers with EGJ invasion were more frequently in the cardia (p < 0.001), had a larger size (p < 0.001), and showed a more advanced pathologic stage (stages II and III; 67.6% versus 33.7%, p < 0.001) than those without EGJ invasion. EGJ invasion and the pathologic stage were significant independent prognostic factors of overall survival in cardia and subcardia cancer patients (hazard ratio 2.24, 95% confidence interval 1.32–3.81, p = 0.003). Conclusion: The overall survival between patients with cardia or subcardia cancer was significantly different according to EGJ invasion. EGJ invasion was an independent prognostic factor and should be considered for staging. Additional research is needed to apply this feature to gastric and esophageal cancer classification.
Process Development of Zirconolite Ceramics for Pu Disposition: Use of a CuO Sintering Aid
Authors: Friskney Aidan A. , Aldean Ismail , Corkhill Claire L. , Blackburn Lewis R.
Published: March 2023

Zirconolite-structured ceramics are candidate wasteform materials for the immobilisation of separated Pu. Due to the refractory properties of zirconolite and other titanates, removing residual porosity remains challenging in the final wasteform product when utilising a conventional solid state sintering route. Herein, we demonstrate that the addition of CuO as a sintering aid increases densification and promotes grain growth. Moreover, zirconolite phase formation was enhanced at lower process temperatures than typically required (≥1350 °C). CuO addition allowed an equivalent density to be reached using process temperatures of 250 °C lower than the undoped composition. At 150 °C lower than the undoped zirconolite, the addition of CuO resulted in a favourable microstructure and phase assemblage, as confirmed via X-ray diffraction and scanning electron microscopy. Secondary phases of CaTiO3 and Ca0.25Cu0.75TiO3 were observed at some processing temperatures, which may prove deleterious to wasteform performance. The use of a CuO sintering aid provides an avenue for the further development of the thermal processing of ceramic wasteform materials.
Gold Clusters Immobilized by Post-Synthesis Methods on Thiol-Containing SBA-15 Mesoporous Materials for the Aerobic Oxidation of Cyclohexene: Influence of Light and Hydroperoxide
Authors: Delgado Rafael , Márquez-Álvarez Carlos , Mayoral Álvaro , de la Serna Ramón , Agúndez Javier , Pérez-Pariente Joaquín
Published: March 2023

Gold nanospecies produced by a historically inspired two-liquid phase system were immobilized on plate-like mesoporous silica, SBA-15, functionalized with mercaptopropyl groups by a post-synthesis method, and the resulting materials were tested in the oxidation of cyclohexene with molecular oxygen at atmospheric pressure. The main purpose of this approach was to compare the physicochemical properties and catalytic performance of these materials with those of previously reported related materials functionalized by in situ methods during synthesis. In addition, catalytic tests under ambient lighting and darkness and also in the presence and absence of the initiator tert-butyl hydroperoxide (TBHP) were carried out. The samples were characterized by chemical analysis, N2 adsorption/desorption, TGA, SEM, HRTEM, UV-vis spectroscopy and XPS. Gold nanoclusters and isolated gold atoms but no AuNPs were found in the catalysts (0.31–2.69 wt.% of gold). The XPS shows that nearly 60% of the -SH groups (1.33 wt.% of S) were oxidized to sulphonic groups upon gold immobilization. The AuNCs and isolated gold atoms evolved in the the reaction medium to form AuNPs. The activity of the samples was lower than that of the catalysts supported on related S-bearing SBA-15 functionalized in situ, which was attributed to their different Au/S ratios, which in turn regulated the evolutionary process of the gold species during the reaction. The catalysts turned out to be inactive in darkness, which evidences that the cyclohexene oxidation carried out at ambient illumination is actually photocatalyzed by the AuNPs formed in situ during the reaction. The TBHP initiator is required to obtain the activity in order to counteract the inhibitors of cyclohexene auto-oxidation present in the commercial reagent. On the other hand, no major differences in the selectivity among the different catalysts and reactions were observed, with 2-cyclohexen-1-one and 2-cyclohexen-1-ol resulting from the allylic oxidation as main products (selectivity of (one + ol) ~80% at a conversion ≥ 35%; one/ol~2).
Conversion of Ethanol to Butadiene over Binary MgO-SiO2 Mixed Oxides Prepared by the Ammonia Evaporation Method
Authors: Samsudin Ismail Bin , Jaenicke Stephan , Chuah Gaik-Khuan
Published: March 2023

The ammonia evaporation method, originally applied for the preparation of highly dispersed silica-supported copper catalysts, was used to synthesize magnesia-silica for the one-step conversion of ethanol to 1,3-butadiene. The MgO-SiO2 catalysts obtained by this method contained a high fraction of magnesium silicate hydrates, which are associated with enhanced butadiene selectivity. These catalysts were benchmarked against those prepared by a conventional wet-kneading method. A Mg/Si molar ratio of 4 was optimal, forming butadiene with 37% yield, which is far superior to the 15% yield obtained with MgO-SiO2 formed by wet-kneading. At 475 °C and a WHSV of 3.2 h−1, a productivity of 0.612 gBD gcat−1 h−1 was measured without the catalyst suffering from deactivation, even after 52 h TOS. The catalysts were characterized by spectroscopic and thermal techniques to elucidate their physicochemical properties and explain the differences in the catalytic performance. The presence of magnesium silicate hydrates gave a balance of surface acidity and basicity, which greatly improved butadiene formation. The open morphology of MgO-SiO2 with vertically arranged platelets and the presence of large pores are proposed to contribute to the stability of the catalyst.
The Impact of Working Memory on the Development of Social Play in Japanese Preschool Children: Emotion Knowledge as a Mediator
Authors: Shimizu Hisayo
Published: March 2023

Through enriched play, children learn social-emotional skills necessary for academic achievement and interpersonal relationships with others. Further research is needed on how specific factors associated with social play, such as working memory and emotion knowledge, interact to promote it. Previous studies have examined the association of working memory and emotion knowledge with social play. However, there are no consistent results as to which abilities influence which skills first. Thus, the present study examines the impact of working memory on the development of social play and the role of emotion knowledge in the relationship between working memory and social play. Forty-seven Japanese preschoolers were tested on working memory, social play, and emotion knowledge. Regression analysis indicated that working memory was significantly related to social play. Furthermore, mediation analysis indicated that emotion recognition mediates the effects of working memory on social play. Working memory was found to contribute to social play by improving emotion recognition in children. These results indicate that the pathway from working memory to social play is mediated by emotion recognition and expands previous perspectives on the developmental mechanisms of emotion knowledge in children.
Terpene-Containing Analogues of Glitazars as Potential Therapeutic Agents for Metabolic Syndrome
Authors: Blokhin Mikhail E. , Kuranov Sergey O. , Khvostov Mikhail V. , Fomenko Vladislav V. , Luzina Olga A. , Zhukova Natalia A. , Elhajjar Cham , Tolstikova Tatiana G. , Salakhutdinov Nariman F.
Published: March 2023

Metabolic syndrome is a complex of abnormalities involving impaired glucose and lipid metabolism, which needs effective pharmacotherapy. One way to reduce lipid and glucose levels associated with this pathology is the simultaneous activation of nuclear PPAR-alpha and gamma. For this purpose, we synthesized a number of potential agonists based on the pharmacophore fragment of glitazars with the inclusion of mono- or diterpenic moiety in the molecular structure. The study of their pharmacological activity in mice with obesity and type 2 diabetes mellitus (C57Bl/6Ay) revealed one substance that was capable of reducing the triglyceride levels in the liver and adipose tissue of mice by enhancing their catabolism and expressing a hypoglycemic effect connected with the sensitization of mice tissue to insulin. It has also been shown to have no toxic effects on the liver.
A Design Concept of an Intelligent Onboard Computer Network
Authors: Pchelintsev Alexander N. , Solovyov Andrey M. , Semenov Mikhail E. , Selvesyuk Nikolay I. , Kosyanchuck Vladislav V. , Zybin Evgeniy Yu.
Published: March 2023

The article suggests design principles of an advanced onboard computer network with an intelligent control system. It describes the main advantages of designing an onboard computer network based on fibre optics, which allows the implementation of an integrated intellectual system performing intelligent inference in emergency situations. The suggested principles significantly increase the reliability and fault tolerance of avionics suits, which, in turn, enhances flight safety. The suggested concept aims to solve a number of important problems including the design of a switchless computing environment, the development of the methods for dynamic reconfiguration of avionics suits with such an environment, and the implementation of a specialised multilevel intelligent avionics system within this environment.
Deep Learning for Parkinson’s Disease Diagnosis: A Short Survey
Authors: Shaban Mohamed
Published: March 2023

Parkinson’s disease (PD) is a serious movement disorder that may eventually progress to mild cognitive dysfunction (MCI) and dementia. According to the Parkinson’s foundation, one million Americans were diagnosed with PD and almost 10 million individuals suffer from the disease worldwide. An early and precise clinical diagnosis of PD will ensure an early initiation of effective therapeutic treatments, which will potentially slow down the progression of the disease and improve the quality of life for patients and their caregivers. Machine and deep learning are promising technologies that may assist and support clinicians in providing an objective and reliable diagnosis of the disease based upon significant and unique features identified from relevant medical data. In this paper, the author provides a comprehensive review of the artificial intelligence techniques that were recently proposed during the period from 2016 to 2022 for the screening and staging of PD as well as the identification of the biomarkers of the disease based on Electroencephalography (EEG), Magnetic Resonance Imaging (MRI), speech tests, handwriting exams, and sensory data. In addition, the author highlights the current and future trends for PD diagnosis based machine and deep learning and discusses the limitations, challenges, potential future solutions, and recommendations for a reliable application of machine and deep learning for PD detection and screening.
Efficacy of Bomas (Kraals) in Mitigating Livestock Depredation in Maasai Mara Conservancies, Kenya
Authors: Wakoli Elizabeth , Syallow Dorothy Masiga , Sitati Evans , Webala Paul W. , Ipara Hellen , Finch Tabitha
Published: March 2023

Livestock depredation is a major conservation challenge globally, causing significant economic losses to pastoralists and threatening large carnivore species outside protected areas. Our study investigated the temporal and spatial distribution of livestock depredation incidences, carnivore species associated with livestock depredation, and assessed mitigation measures in Maasai Mara Conservancies in Southern Kenya. Using daily monitoring of livestock depredation cases, we made comparisons between livestock attacks occurring in predator-proof bomas and those with traditional kraals. A total of 305 livestock depredation incidents were recorded between January and December 2021, translating to a total tally of 1411 livestock maimed or killed. Most livestock depredation incidents occurred during the day (59%) as opposed to night (41%), but this difference was not significant. Livestock depredation incidents in the nighttime occurred mostly inside traditional kraals (34%) and occurred the least in predator-proof kraals (2%). Lions were responsible for more livestock attacks in the grazing fields compared with leopards, hyenas, and wild dogs. Hyenas were more daring and attacked livestock inside traditional bomas relative to lions and leopards. Our study concludes that predator-proof bomas are more effective in minimizing livestock depredation and can be embraced as a sound intervention for human–carnivore co-existence in communities’ wildlife conservation areas.
Relationship between Systemic Inflammatory Markers, GLUT1 Expression, and Maximum 18F-Fluorodeoxyglucose Uptake in Non-Small Cell Lung Carcinoma and Their Prognostic Significance
Authors: Park Sonya Youngju , Cho Deog-Gon , Shim Byoung-Yong , Cho Uiju
Published: March 2023

Background: Factors involved in inflammation and cancer interact in various ways with each other, and biomarkers of systemic inflammation may have a prognostic value in cancer. Glucose transporter 1 (GLUT1) plays a pivotal role in glucose transport and metabolism and it is aberrantly expressed in various cancer types. We evaluated the differential expression of GLUT1, along with 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) in non-small-cell lung cancer (NSCLC), and then analyzed their prognostic significance. Methods: A total of 163 patients with resectable NSCLC were included in this study. Tumor sections were immunohistochemically stained for GLUT1 and GLUT3. Maximum standardized uptake value (SUVmax) was measured by preoperative FDG-PET, and neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), and lymphocyte–monocyte ratio (LMR) were derived from pretreatment blood count. Results: GLUT1 and GLUT3 was positively expressed in 74.8% and 6.1% of the NSCLC tissues, respectively. GLUT1 expression was significantly correlated with squamous cell carcinoma histology, poor differentiation, high pathologic stage, old age, male, smoking, and high SUVmax (>7) (all p < 0.05). The squamous cell carcinoma and smoker group also showed significantly higher SUVmax (both p < 0.001). Systemic inflammation markers, including NLR, PLR, and LMR, were positively correlated with high SUVmax (all p < 0.05). High GLUT1 expression, high SUVmax, high NLR, and low LMR, were significantly associated with poor overall survival in patients with NSCLC. However, in the multivariate survival analysis, LMR was an independent prognostic factor overall (HR 1.86, 95% CI 1.05–3.3) and for the stage I/II cohort (HR 2.3, 95% CI 1.24–4.3) (all p < 0.05). Conclusions: Systemic inflammatory markers—NLR, PLR, and LMR are strongly correlated with the SUVmax and are indicators of aggressive tumor behavior. Specifically, LMR is a promising prognostic biomarker in NSCLC patients.
Retrospective Analysis of the Predictive Value of 18F-FDG PET/CT Metabolic Parameters for PD-L1 Expression in Cervical Cancer
Authors: Ji Jianfeng , Pang Weiqiang , Song Jinling , Wang Xiawan , Tang Huarong , Liu Yunying , Yi Heqing , Wang Yun , Gu Qing , Li Linfa
Published: March 2023

Background: Immunotherapy targeting PD-1/PD-L1 has been proven to be effective for cervical cancer treatment. To explore non-invasive examinations for assessing the PD-L1 status in cervical cancer, we performed a retrospective study to investigate the predictive value of 18F-FDG PET/CT. Methods: The correlations between PD-L1 expression, clinicopathological characteristics and 18F-FDG PET/CT metabolic parameters were evaluated in 74 cervical cancer patients. The clinicopathological characteristics included age, histologic type, tumor differentiation, FIGO stage and tumor size. The metabolic parameters included maximum standard uptake (SUVmax), mean standard uptake (SUVmean), total lesion glycolysis (TLG) and tumor metabolic volume (MTV). Results: In univariate analysis, SUVmax, SUVmean, TLG, tumor size and tumor differentiation were obviously associated with PD-L1 status. SUVmax (rs = 0.42) and SUVmean (rs = 0.40) were moderately positively correlated with the combined positive score (CPS) for PD-L1 in Spearman correlation analysis. The results of multivariable analysis showed that the higher SUVmax (odds ratio = 2.849) and the lower degree of differentiation (Odds Ratio = 0.168), the greater probability of being PD-L1 positive. The ROC curve analysis demonstrated that when the cut-off values of SUVmax, SUVmean and TLG were 10.45, 6.75 and 143.4, respectively, the highest accuracy for predicting PD-L1 expression was 77.0%, 71.6% and 62.2%, respectively. The comprehensive predictive ability of PD-L1 expression, assessed by combining SUVmax with tumor differentiation, showed that the PD-L1-negative rate was 100% in the low probability group, whereas the PD-L1-positive rate was 84.6% in the high probability group. In addition, we also found that the H-score of HIF-1α was moderately positively correlated with PD-L1 CPS (rs = 0.51). Conclusions: The SUVmax and differentiation of the primary lesion were the optimum predictors for PD-L1 expression in cervical cancer. There was a great potential for 18F-FDG PET/CT in predicting PD-L1 status and selecting cervical cancer candidates for PD1/PD-L1 immune checkpoint therapy.
Impact of Omicron Variant Infection on Assessment of Spike-Specific Immune Responses Using the EUROIMMUN Quan-T-Cell SARS-CoV-2 Assay and Roche Elecsys Anti-SARS-CoV-2-S
Authors: Ahmed Mohamed I. M. , Plank Michael , Castelletti Noemi , Diepers Paulina , Eser Tabea M. , Rubio-Acero Raquel , Noreña Ivan , Reinkemeyer Christina , Zapf Dorinja , Hoelscher Michael , Janke Christian , Wieser Andreas , Geldmacher Christof ,   on behalf of the KoCo19/ORCHESTRA Study Group
Published: March 2023

The currently prevailing variants of SARS-CoV-2 are subvariants of the Omicron variant. The aim of this study was to analyze the effect of mutations in the Spike protein of Omicron on the results Quan-T-Cell SARS-CoV-2 assays and Roche Elecsys anti-SARS-CoV-2 anti-S1. Omicron infected subjects ((n = 37), vaccinated (n = 20) and unvaccinated (n = 17)) were recruited approximately 3 weeks after a positive PCR test. The Quan-T-Cell SARS-CoV-2 assays (EUROIMMUN) using Wuhan and the Omicron adapted antigen assay and a serological test (Roche Elecsys anti-SARS-CoV-2 anti-S1) were performed. Using the original Wuhan SARS-CoV-2 IGRA TUBE, in 19 of 21 tested Omicron infected subjects, a positive IFNy response was detected, while 2 non-vaccinated but infected subjects did not respond. The Omicron adapted antigen tube resulted in comparable results. In contrast, the serological assay detected a factor 100-fold lower median Spike-specific RBD antibody concentration in non-vaccinated Omicron infected patients (n = 12) compared to patients from the pre Omicron era (n = 12) at matched time points, and eight individuals remained below the detection threshold for positivity. For vaccinated subjects, the Roche assay detected antibodies in all subjects and showed a 400 times higher median specific antibody concentration compared to non-vaccinated infected subjects in the pre-Omicron era. Our results suggest that Omicron antigen adapted IGRA stimulator tubes did not improve detection of SARS-CoV-2-specific T-cell responses in the Quant-T-Cell-SARS-CoV-2 assay. In non-vaccinated Omicron infected individuals, the Wuhan based Elecsys anti-SARS-CoV-2 anti-S1 serological assay results in many negative results at 3 weeks after diagnosis.
Hybrid Techniques for the Diagnosis of Acute Lymphoblastic Leukemia Based on Fusion of CNN Features
Authors: Ahmed Ibrahim Abdulrab , Senan Ebrahim Mohammed , Shatnawi Hamzeh Salameh Ahmad , Alkhraisha Ziad Mohammad , Al-Azzam Mamoun Mohammad Ali
Published: March 2023

Acute lymphoblastic leukemia (ALL) is one of the deadliest forms of leukemia due to the bone marrow producing many white blood cells (WBC). ALL is one of the most common types of cancer in children and adults. Doctors determine the treatment of leukemia according to its stages and its spread in the body. Doctors rely on analyzing blood samples under a microscope. Pathologists face challenges, such as the similarity between infected and normal WBC in the early stages. Manual diagnosis is prone to errors, differences of opinion, and the lack of experienced pathologists compared to the number of patients. Thus, computer-assisted systems play an essential role in assisting pathologists in the early detection of ALL. In this study, systems with high efficiency and high accuracy were developed to analyze the images of C-NMC 2019 and ALL-IDB2 datasets. In all proposed systems, blood micrographs were improved and then fed to the active contour method to extract WBC-only regions for further analysis by three CNN models (DenseNet121, ResNet50, and MobileNet). The first strategy for analyzing ALL images of the two datasets is the hybrid technique of CNN-RF and CNN-XGBoost. DenseNet121, ResNet50, and MobileNet models extract deep feature maps. CNN models produce high features with redundant and non-significant features. So, CNN deep feature maps were fed to the Principal Component Analysis (PCA) method to select highly representative features and sent to RF and XGBoost classifiers for classification due to the high similarity between infected and normal WBC in early stages. Thus, the strategy for analyzing ALL images using serially fused features of CNN models. The deep feature maps of DenseNet121-ResNet50, ResNet50-MobileNet, DenseNet121-MobileNet, and DenseNet121-ResNet50-MobileNet were merged and then classified by RF classifiers and XGBoost. The RF classifier with fused features for DenseNet121-ResNet50-MobileNet reached an AUC of 99.1%, accuracy of 98.8%, sensitivity of 98.45%, precision of 98.7%, and specificity of 98.85% for the C-NMC 2019 dataset. With the ALL-IDB2 dataset, hybrid systems achieved 100% results for AUC, accuracy, sensitivity, precision, and specificity.
Developing Automated Computer Algorithms to Track Periodontal Disease Change from Longitudinal Electronic Dental Records
Authors: Patel Jay S. , Kumar Krishna , Zai Ahad , Shin Daniel , Willis Lisa , Thyvalikakath Thankam P.
Published: March 2023

Objective: To develop two automated computer algorithms to extract information from clinical notes, and to generate three cohorts of patients (disease improvement, disease progression, and no disease change) to track periodontal disease (PD) change over time using longitudinal electronic dental records (EDR). Methods: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between 1 January 2009, and 31 December 2014, at Indiana University School of Dentistry (IUSD) clinics. We utilized various Python libraries, such as Pandas, TensorFlow, and PyTorch, and a natural language tool kit to develop and test computer algorithms. We tested the performance through a manual review process by generating a confusion matrix. We calculated precision, recall, sensitivity, specificity, and accuracy to evaluate the performances of the algorithms. Finally, we evaluated the density of longitudinal EDR data for the following follow-up times: (1) None; (2) Up to 5 years; (3) > 5 and ≤ 10 years; and (4) >10 and ≤ 15 years. Results: Thirty-four percent (n = 9954) of the study cohort had up to five years of follow-up visits, with an average of 2.78 visits with periodontal charting information. For clinician-documented diagnoses from clinical notes, 42% of patients (n = 5562) had at least two PD diagnoses to determine their disease change. In this cohort, with clinician-documented diagnoses, 72% percent of patients (n = 3919) did not have a disease status change between their first and last visits, 669 (13%) patients’ disease status progressed, and 589 (11%) patients’ disease improved. Conclusions: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We provided detailed steps and computer algorithms to clean and preprocess the EDR data and generated three cohorts of patients. This information can now be utilized for studying clinical courses using artificial intelligence and machine learning methods.
Feasibility Study of Detection of Ochre Spot on Almonds Aimed at Very Low-Cost Cameras Onboard a Drone
Authors: Martínez-Heredia Juana M. , Gálvez Ana I. , Colodro Francisco , Mora-Jiménez José Luis , Sassi Ons E.
Published: March 2023

Drones can be very helpful in precision agriculture. Currently, most drone-based solutions for plant disease detection incorporate multispectral, hyperspectral, or thermal cameras, which are expensive. In addition, there is a trend nowadays to apply machine learning techniques to precision agriculture, which are computationally complex and intensive. In this work, we explore the feasibility of detecting ochre spot disease in almond plantations based on conventional techniques of computer vision and images from a very low-cost RGB camera that is placed on board a drone. Such an approach will allow the detection system to be simple and inexpensive. First, we made a study of color on the ochre spot disease. Second, we developed a specific algorithm that was capable of processing and analyzing limited-quality images from a very low-cost camera. In addition, it can estimate the percentage of healthy and unhealthy parts of the plant. Thanks to the GPS on board the drone, the system can provide the location of every sick almond tree. Third, we checked the operation of the algorithm with a variety of photographs of ochre spot disease in almonds. The study demonstrates that the efficiency of the algorithm depends to a great extent on environmental conditions, but, despite the limitations, the results obtained with the analyzed photographs show a maximum discrepancy of 10% between the estimated percentage and the ground truth percentage of the unhealthy area. This approach shows great potential for extension to other crops by making previous studies of color and adaptations.
Composite Attention Residual U-Net for Rib Fracture Detection
Authors: Wang Xiaoming , Wang Yongxiong
Published: March 2023

Computed tomography (CT) images play a vital role in diagnosing rib fractures and determining the severity of chest trauma. However, quickly and accurately identifying rib fractures in a large number of CT images is an arduous task for radiologists. We propose a U-net-based detection method designed to extract rib fracture features at the pixel level to find rib fractures rapidly and precisely. Two modules are applied to the segmentation network—a combined attention module (CAM) and a hybrid dense dilated convolution module (HDDC). The features of the same layer of the encoder and the decoder are fused through CAM, strengthening the local features of the subtle fracture area and increasing the edge features. HDDC is used between the encoder and decoder to obtain sufficient semantic information. Experiments show that on the public dataset, the model test brings the effects of Recall (81.71%), F1 (81.86%), and Dice (53.28%). Experienced radiologists reach lower false positives for each scan, whereas they have underperforming neural network models in terms of detection sensitivities with a long time diagnosis. With the aid of our model, radiologists can achieve higher detection sensitivities than computer-only or human-only diagnosis.
Nonlinear Dynamics of Heart Rate Variability after Acutely Induced Myocardial Ischemia by Percutaneous Transluminal Coronary Angioplasty
Authors: Calderón-Juárez Martín , Cruz-Vega Itayetzin Beurini , González-Gómez Gertrudis Hortensia , Lerma Claudia
Published: March 2023

Several heart rate variability (HRV) characteristics of patients with myocardial ischemia are associated with a higher mortality risk. However, the immediate effect of acute ischemia on the HRV nonlinear dynamical behavior is unknown. The objective of this work is to explore the presence of nonlinearity through surrogate data testing and describe the dynamical behavior of HRV in acutely induced ischemia by percutaneous transluminal coronary angioplasty (PTCA) with linear and recurrence quantification analysis (RQA). Short-term electrocardiographic recordings from 68 patients before and after being treated with elective PTCA were selected from a publicly available database. The presence of nonlinear behavior was confirmed by determinism and laminarity in a relevant proportion of HRV time series, in up to 29.4% during baseline conditions and 30.9% after PTCA without statistical difference between these scenarios. After PTCA, the mean value and standard deviation of HRV time series decreased, while determinism and laminarity values increased. Here, the diminishment in overall variability caused by PTCA is not accompanied by a change in nonlinearity detection. Therefore, the presence of nonlinear behavior in HRV time series is not necessarily in agreement with the change of traditional and RQA measures.
Closed Formula for Transport across Constrictions
Authors: Malgaretti Paolo , Harting Jens
Published: March 2023

In the last decade, the Fick–Jacobs approximation has been exploited to capture transport across constrictions. Here, we review the derivation of the Fick–Jacobs equation with particular emphasis on its linear response regime. We show that, for fore-aft symmetric channels, the flux of noninteracting systems is fully captured by its linear response regime. For this case, we derive a very simple formula that captures the correct trends and can be exploited as a simple tool to design experiments or simulations. Lastly, we show that higher-order corrections in the flux may appear for nonsymmetric channels.
Functional Analysis Diagrams in Science and Technology Education
Authors: Michalakoudis Ioannis , Dimitriou Pavlos , Koutlidis Apollon , Childs Peter
Published: March 2023

With the world currently facing an escalating environmental crisis and major virus disease outbreaks, the need to significantly grow the STEM workforce ranks has never been more urgent. The authors propose a novel teaching methodology involving functional analysis diagrams (FADs) as an educational aid. The paper presents a method to quantitatively assess the effects of the proposed intervention in an educational setting alongside a pilot study conducted in a South Korean secondary school with non-native English-speaking students (n = 39). The written assessment results indicate that the FAD-assisted method can have a measurable effect and have the potential to assist students with lower scores in English. This pilot study’s results suggest that FAD models of engineering systems can enhance knowledge transfers in technology and engineering education. Experimental validation using the proposed method was shown to be feasible and would require a moderate-sized sample (n ≥ 168) for a future full-scale study.