bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical Properties of Metasandstone under Uniaxial Graded Cyclic Loading and Unloading
Authors: Liu Dunwen , Jiang Shulin , Tang Yu
Published: June 2022

The acoustic emission and wave velocity characteristics of metasandstone under graded cyclic loading and unloading were revealed by conducting graded cyclic loading and unloading tests. The results show that the acoustic emission signals of metasandstone samples are mainly generated in the loading phase, and almost no acoustic emission activity is generated in the unloading phase. The quiet period feature can be used to monitor and predict the destabilization of metasandstone. There is a stress threshold for wave velocity variation in metasandstone, below which wave velocity does not change significantly with increasing stress. When the stress exceeds this threshold, the wave velocity of the rock sample will decrease rapidly with the increase in stress. The phenomenon of a rapid decrease in wave velocity can be used to predict the damage instability of rock masses in engineering.
A Stray Light Detection Model for VR Head-Mounted Display Based on Visual Perception
Authors: Li Hung-Chung , Tsai Meng-Che , Lee Tsung-Xian
Published: June 2022

In recent years, the general public and the technology industry have favored stereoscopic vision, immersive experience, and real-time visual information reception of virtual reality (VR) and augmented reality (AR). The device carrier, the Head-Mounted Display (HMD), is recognized as one of the next generation’s most promising computing and communication platforms. HMD is a virtual image optical display device that combines optical lens modules and binocular displays. The visual impact it brings is much more complicated than the traditional display and also influences the performance of image quality. This research investigated the visual threshold of stray light for three kinds of VR HMD devices, and proposes a qualitative model, derived from psychophysical experiments and the measurement of images on VR devices. The recorded threshold data of the psychophysical stray light perception experiment was used as the target when training. VR display image captured by a wide-angle camera was processed, through a series of image processing procedures, to extract variables in the range of interest. The machine learning algorithm established an evaluation method for human eye-perceived stray light in the study. Four supervised learning algorithms, including K-Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machine (SVM), and Random Forest (RF), were compared. The established model’s accuracy was about 90% in all four algorithms. It also proved that different percentages of thresholds could be used to label data according to demand to predict the feasibility of various subdivision inspection specifications in the future. This research aimed to provide a fast and effective stray light qualitative evaluation method to be used as a basis for future HMD optical system design and quality control. Thus, stray light evaluation will become one of the critical indicators of image quality and will be applicable to VR or AR content design.
Ecological Characterization and Bio-Mitigation Potential of Heavy Metal Contamination in Metallurgically Affected Soil
Authors: Hovhannisyan Varuzhan , Vaseashta Ashok , Avanesyan Lyudmila , Sadoyan Ruzanna , Gasparyan Armen , Shogheryan Sirine , Harutyunova Laura , Mirumyan Lyudmila , Gevorgyan Gor
Published: June 2022

Heavy metals (HMs) remain persistent in soil for a long time and thus present a long-term threat of environmental pollution. In this study, the concentrations of some HMs (As, Cu, Zn, Pb, and Mo) in soil, potentially affected by the ex-operation of a metallurgical plant—specifically, a copper smelter in Alaverdi Town, northeastern Armenia—were measured, based on which, the HM contamination and its ecological, biological, and health effects were assessed. Concentrations of HMs (Cu, Zn, and Pb) were also measured in different plant (leaves) and invertebrate species that occur in the soil over the metallurgical factory site in order to assess the potential for the bioremoval of HMs from the soil. The results showed that the ex-operation of the metallurgical facility created such contamination in the soil that it caused a noticeable loss of invertebrate biomass in the soil and posed ecological, non-carcinogenic (for children), and carcinogenic health hazards. The investigated plant and invertebrate species were characterized by different capacities for the accumulation of HMs from the soil, based on which the plant species Fraxinus excelsior, Acer platanoides, Robinia pseudoacacia, and Aesculus hippocastanum and the invertebrate species Deroceras caucasicum, Limax flavus, and Eisenia rosea are recommended to be used for the selective removal of HMs (Cu, Zn, and Pb) from the soil.
Detecting Malignant Leukemia Cells Using Microscopic Blood Smear Images: A Deep Learning Approach
Authors: Baig Raheel , Rehman Abdur , Almuhaimeed Abdullah , Alzahrani Abdulkareem , Rauf Hafiz Tayyab
Published: June 2022

Leukemia is a form of blood cancer that develops when the human body’s bone marrow contains too many white blood cells. This medical condition affects adults and is considered a prevalent form of cancer in children. Treatment for leukaemia is determined by the type and the extent to which cancer has developed across the body. It is crucial to diagnose leukaemia early in order to provide adequate care and to cure patients. Researchers have been working on advanced diagnostics systems based on Machine Learning (ML) approaches to diagnose leukaemia early. In this research, we employ deep learning (DL) based convolutional neural network (CNN) and hybridized two individual blocks of CNN named CNN-1 and CNN-2 to detect acute lymphoblastic leukaemia (ALL), acute myeloid leukaemia (AML), and multiple myeloma (MM). The proposed model detects malignant leukaemia cells using microscopic blood smear images. We construct a dataset of about 4150 images from a public directory. The main challenges were background removal, ripping out un-essential blood components of blood supplies, reduce the noise and blurriness and minimal method for image segmentation. To accomplish the pre-processing and segmentation, we transform RGB color-space into the greyscale 8-bit mode, enhancing the contrast of images using the image intensity adjustment method and adaptive histogram equalisation (AHE) method. We increase the structure and sharpness of images by multiplication of binary image with the output of enhanced images. In the next step, complement is done to get the background in black colour and nucleus of blood in white colour. Thereafter, we applied area operation and closing operation to remove background noise. Finally, we multiply the final output to source image to regenerate the images dataset in RGB colour space, and we resize dataset images to [400, 400]. After applying all methods and techniques, we have managed to get noiseless, non-blurred, sharped and segmented images of the lesion. In next step, enhanced segmented images are given as input to CNNs. Two parallel CCN models are trained, which extract deep features. The extracted features are further combined using the Canonical Correlation Analysis (CCA) fusion method to get more prominent features. We used five classification algorithms, namely, SVM, Bagging ensemble, total boosts, RUSBoost, and fine KNN, to evaluate the performance of feature extraction algorithms. Among the classification algorithms, Bagging ensemble outperformed the other algorithms by achieving the highest accuracy of 97.04%.
Investigation of Gentamicin Release from Polydopamine Nanoparticles
Authors: Batul Rahila , Khaliq Abdul , Alafnan Ahmed , Bhave Mrinal , Yu Aimin
Published: June 2022

Polydopamine (PDA), being highly reactive in nature, has acquired great attention in multi-disciplinary fields. Owing to its fascinating properties, including its biocompatible, non-toxic and readily bio-degradative nature, we investigated the drug loading and release behavior, using an aminoglycoside antibiotic gentamicin (G) as a model drug. The gentamicin was loaded into the PDA nanoparticles (NPs) via an in situ polymerization method. The release kinetics of the gentamicin was then studied in pH 3, 5 and 7.4. Two batches with varied gentamicin loadings, G-PDA NPs 1:1 (with approx. 84.1% loaded gentamicin) and G-PDA NPs 0.6:1 (with approx. 72.7% loaded gentamicin), were studied. The drug release data were analyzed by LC–MS. The PDA showed good stability in terms of gentamicin release at alkaline pH over a period of seven days. The negative surface charge of PDA at pH 7.4 makes a strong bond with gentamicin, hence preventing its release from the PDA NPs. However, at pH 5 and 3, the amine groups of PDA are more prone towards protonation, making PDA positively charged, hence the repulsive forces caused the gentamicin to detach and release from the G-PDA NPs. Consequently, approx. 40% and 55% drug release were observed at pH 5 and 3, respectively, from the G-PDA NPs 1:1. However, the drug released from G-PDA NPs 0.6:1 was found to be one half as compared to the G-PDA NPs 1:1, which is obvious to the concentration gradient. These findings suggested that the in situ loading method for gentamicin could provide drug release over a period of seven days, hence defending the drug’s efficacy and safety challenges. Furthermore, two kinetic models, namely the Ritger–Peppas and Higuchi models, were implemented to determine the drug release kinetics. Curve fitting analysis supported our findings for the drug release kinetics which are followed by PDA structural changes in response to pH.
Multi-Source Information Fusion Fault Diagnosis for Gearboxes Based on SDP and VGG
Authors: Fu Yuan , Chen Xiang , Liu Yu , Son Chan , Yang Yan
Published: June 2022

A decision-level approach using multi-sensor-based symmetry dot pattern (SDP) analysis with a Visual Geometry Group 16 network (VGG16) fault diagnosis model for multi-source information fusion was proposed to realize accurate and comprehensive fault diagnosis of gearbox gear teeth. Firstly, the SDP technique was used to perform a feature-level fusion of the fault states of gearbox gear collected by multiple sensors, which could initially visualize the vibration states of the gear teeth in different states. Secondly, the SDP images obtained were combined with the deep learning VGG16. In this way, the local diagnostic results of each sensor can be easily obtained. Finally, the local diagnostic results of each sensor were combined with the DS evidence theory to achieve decision-level fusion, which can better realize comprehensive fault detection for gearbox gear teeth. Before fusion, the accuracies of the three sensors were 96.43%, 93.97%, and 93.28%, respectively. When sensor 1 and sensor 2 were fused, the accuracy reached 99.93%, which is 3.52% and 6.34% better than when using sensors 1 and 2, respectively, alone. When sensor 1 and sensor 3 were fused, the accuracy reached 99.96%, marking an improvement of 3.36% and 6.85% over individual use of sensors 1 and 3, respectively. When sensor 2 and sensor 3 were fused, the accuracy reached 99.40%, which is 5.78% and 6.56% better than individual use of sensors 2 and 3, respectively. When the three sensors were fused simultaneously, the accuracy reached 99.98%, which is 3.68%, 6.40%, and 7.18% better than individual use of sensors 1, 2, and 3, respectively.
ANN-Based Dynamic Prediction of Daily Ground Settlement of Foundation Pit Considering Time-Dependent Influence Factors
Authors: Zhang Zhenyu , Xu Rongqiao , Wu Xi , Wang Jinchang
Published: June 2022

Accurately and dynamically predicting ground settlements during the construction of foundation pits is pivotal to the understanding of the potential risk of foundation pits and, therefore, enables constructors to take timely and effective actions to ensure the construction safety of foundation pits. Existing settlement prediction methods mainly focus on the prediction of the maximum ground settlements based on static influence factors, such as soil properties and the geometry of foundation pits. However, these methods are unable to be applied to the prediction of daily ground settlements in a direct way because daily ground settlements can be affected by many time-dependent influence factors, and an accurate prediction of daily ground settlements should take into consideration such factors. To address this problem, this paper proposes an artificial neural network-based daily ground settlement prediction method, where both static and time-dependent influence factors, as well as previous settlement monitoring data, are considered in the optimum artificial neural network. The proposed method is validated using data collected from a real cut-and-cover highway tunnel project in western Hangzhou, China. The results demonstrate that time-dependent influence factors and previous settlement monitoring data play vital roles in establishing an optimum artificial neural network for the accurate prediction of daily ground settlement.
Influence of Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) on Photosynthetic Parameters and Secondary Metabolites of Plants from Fabaceae Family
Authors: Taschina Monica , Moisa Cristian , Lupitu Andreea , Copolovici Dana Maria , Copolovici Lucian
Published: June 2022

Nonsteroidal anti-inflammatory medications (NSAIDs) are commonly used painkillers, anti-inflammatory agents, and fever reducers. They arrive in the environment from municipal wastewater and/or agriculture waste, affecting growing plants. In our study, the impact of NSAIDs, namely, diclofenac, indomethacin, naproxen, and paracetamol, on four plant species from the Fabaceae family (Cicer arietinum, Pisum sativum, Lens culinaris, and Vicia faba) was tested. The assimilation rate and stomatal conductance decreased for all plants treated with NSAIDs. Chlorophyll and carotenoid contents in the leaves of plants under stress declined by more than 15% compared with the control plants, while the flavonoids and total phenols decreased to a lesser extent. In contrast, the plants treated with NSAIDs emit terpenes and green leaf were volatile, at a level of some nmol m−2 s−1, which could influence the atmospheric reaction and ozone formation.
Early Gapping and Platoon Merging Strategies for Autonomous Vehicles using Local Controllers
Authors: Shvalb Nir , Geller Shlomo , Avrahami Idit
Published: June 2022

Autonomous vehicle merging schemes require a central control or a complex communication system between the vehicles. We suggest an alternative local traffic control method based on distance sensors and roadside units which provides the vehicles with the desired gap profile without the need for vehicle-to-vehicle communication. The gap profile aims to open gaps between the vehicles before an upcoming junction. To explore the profiles’ governing parameters, 140,000 simulation cases with varying conditions were run. Results show that, for a speed limit of 100 km/h and high inlet density (of 1–1.5 s between vehicles), the best strategy with respect to flow and merging percentage (of ~90%) is to use early gapping and platoon merging using linear profiles with long stabilization sections (>0.6 km). Moreover, the gapping process should start when the vehicle ahead attains a velocity of 75 km/h. In this way, fluent traffic can be sustained without perpetuating upstream traffic jams.
New Theorems in Solving Families of Improper Integrals
Authors: Abu Ghuwaleh Mohammad , Saadeh Rania , Burqan Aliaa
Published: June 2022

Many improper integrals appear in the classical table of integrals by I. S. Gradshteyn and I. M. Ryzhik. It is a challenge for some researchers to determine the method in which these integrations are formed or solved. In this article, we present some new theorems to solve different families of improper integrals. In addition, we establish new formulas of integrations that cannot be solved by mathematical software such as Mathematica or Maple. In this article, we present three main theorems that are essential in generating new formulas for solving improper integrals. To show the efficiency and the simplicity of the presented techniques, we present some applications and examples on integrations that cannot be solved by regular methods. Furthermore, we acquire new results for integrations and compare them to that obtained in the classical table of integrations. Some previous results, become special cases of our outcomes or generalizations to acquire new integrals.
Recent Advances in Silica-Nanomaterial-Assisted Lateral Flow Assay
Authors: Zhuang Han , Xu Chun , Gao Fang , Li Yiwei , Lei Chang , Yu Chengzhong
Published: June 2022

Lateral flow assays (LFAs) have attracted much attention as rapid and affordable point-of-care devices for medical diagnostics. The global SARS-CoV-2 pandemic has further highlighted the importance of LFAs. Many efforts have been made to enhance the sensitivity of LFAs. In recent years, silica nanomaterials have been used to either amplify the signal of label materials or provide stability, resulting in better detection performance. In this review, the recent progress of silica-nanomaterial-assisted LFAs is summarized. The impact of the structure of silica nanomaterials on LFA performance, the challenges and prospects in this research area are also discussed.
N6-Methyladenosine Methylome Profiling of Muscle and Adipose Tissues Reveals Methylase–mRNA Metabolic Regulatory Networks in Fat Deposition of Rex Rabbits
Authors: Luo Gang , Wang Shuhui , Ai Yaotian , Li Jiapeng , Ren Zhanjun
Published: June 2022

N6-methyladenosine (m6A) is the most prevalent internal form of modification in messenger RNA in higher eukaryotes and plays an important role in cancer, immunity, reproduction, development, and fat deposition. Intramuscular fat is the main factor used to measure the meat quality of an animal. The deposition of intramuscular fat and perirenal fat increases with age. However, there is no data on m6A modification of Rex rabbits and its potential biological roles in adipose deposition and muscle growth. Here, we performed two high-throughput sequencing methods, m6A-modified RNA immunoprecipitation sequence (MeRIP-seq) and RNA sequence (RNA-seq), to identify key genes with m6A modification on fat deposition in the muscle and adipose tissues of Rex rabbits. Then, qRT-PCR was used to identify the differently methylated genes related to fat deposition. Our findings showed that there were 12,876 and 10,973 m6A peaks in the rabbit muscle and adipose tissue transcriptomes, respectively. Stop codons, 3′-untranslated regions, and coding regions were found to be mainly enriched for m6A peaks. In addition, we found 5 differential methylases and 12 key genes of methylation modification related to fat deposition between muscle and adipose tissues samples. The expression levels of six random key genes were significantly higher in the fat than that in the muscle of Rex rabbits at different stages (p < 0.01). Finally, five differential methylases were found to regulate adipogenesis by affecting the expression of screened genes in different ways. These findings provided a theoretical basis for our future research on the function of m6A modification during the growth of fat deposits.
Temporal Skin Temperature as an Indicator of Cardiorespiratory Fitness Assessed with Selected Methods
Authors: Jastrzębska Agnieszka Danuta , Hebisz Rafal , Hebisz Paulina
Published: June 2022

The aim of this study was to determine whether there are associations between cardiovascular fitness (and aerobic capacity) and changes in temporal skin temperature during and after a single bout of high-intensity exercise. Twenty-three men with varying levels of physical activity (VO2max: 59.03 ± 11.19 (mL/kg/min), body mass 71.5 ± 10.4 (kg), body height 179 ± 8 (cm)) participated in the study. Each subject performed an incremental test and, after a 48-h interval, a 110%Pmax power test combined with an analysis of the thermal parameters, heart rate recovery and heart rate variability. Thermal radiation density from the body surface (temple) was measured using a Sonel KT384 thermal imaging camera immediately after warm-up (Tb), immediately after exercise (Te) and 120 sec after the end of exercise (Tr). The differences between measurements were then calculated. The correlation analysis between the thermal and cardiovascular function parameters during the recovery period showed strong positive associations between the Tr-Te difference and measures of cardiovascular fitness (50 < r < 69, p < 0.05). For example, the correlation coefficient between Tr-Te and VO2max reached 0.55 and between Tr-Te and Pmax reached 0.68. The results obtained indicate that the measurement of temporal temperature during and after an intense 3-min bout of exercise can be used to assess aerobic physical capacity and cardiovascular fitness.
No Association of Hair Zinc Concentration with Coronary Artery Disease Severity and No Relation with Acute Coronary Syndromes
Authors: Dziedzic Ewelina A. , Gąsior Jakub S. , Tuzimek Agnieszka , Paleczny Justyna , Kwaśny Mirosław , Dąbrowski Marek , Jankowski Piotr
Published: June 2022

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Although zinc (Zn) was reported to have antioxidant, anti-inflammatory and protective properties in CVDs, its association with coronary artery disease (CAD) is still unclear. As methods commonly used to assess Zn levels in blood and urine do not show the full picture of the microelement supply, in this study, the nutritional status of Zn in patients with angiographically confirmed CAD was assessed using inductively coupled plasma optical emission spectrometry. We found no association between Zn and the severity of CAD evaluated with the Coronary Artery Surgery Study Score (p = 0.67). There were no statistically significant differences in Zn levels between patients with acute coronary syndrome and those with stable CAD (p = 0.937). A statically significant negative correlation was observed between Zn content and serum triglyceride concentration (p < 0.05). Patients with type 2 diabetes mellitus were found to have a significantly lower hair Zn content compared to non-diabetic individuals (p < 0.01). The role of Zn in the pathogenesis of CAD and its complications need further well-designed research as the moderation and supplementation of Zn dietary intake could be a simple intervention to reduce the CVDs risk.
Obesity, Bone Loss, and Periodontitis: The Interlink
Authors: Zhao Pengfei , Xu Aimin , Leung Wai Keung
Published: June 2022

Obesity and periodontitis are both common health concerns that have given rise to considerable economic and societal burden worldwide. There are established negative relationships between bone metabolism and obesity, obesity and diabetes mellitus (DM), and DM and periodontitis, to name a few, with osteoporosis being considered a long-term complication of obesity. In the oral cavity, bone metabolic disorders primarily display as increased risks for periodontitis and alveolar bone loss. Obesity-driven alveolar bone loss and mandibular osteoporosis have been observed in animal models without inoculation of periodontopathogens. Clinical reports have also indicated a possible association between obesity and periodontitis. This review systematically summarizes the clinical periodontium changes, including alveolar bone loss in obese individuals. Relevant laboratory-based reports focusing on biological interlinks in obesity-associated bone remodeling via processes like hyperinflammation, immune dysregulation, and microbial dysbiosis, were reviewed. We also discuss the potential mechanism underlying obesity-enhanced alveolar bone loss from both the systemic and periodontal perspectives, focusing on delineating the practical considerations for managing periodontal disease in obese patients.
BPC 157, L-NAME, L-Arginine, NO-Relation, in the Suited Rat Ketamine Models Resembling “Negative-Like” Symptoms of Schizophrenia
Authors: Zemba Cilic Andrea , Zemba Mladen , Cilic Matija , Strbe Sanja , Ilic Spomenko , Vukojevic Jaksa , Zoricic Zoran , Filipcic Igor , Kokot Antonio , Smoday Ivan Maria , Rukavina Iva , Boban Blagaic Alenka , Tvrdeic Ante , Duplancic Bozidar , Stambolija Vasilije , Marcinko Darko , Skrtic Anita , Seiwerth Sven , Sikiric Predrag
Published: June 2022

We attempted throughout the NO-system to achieve the particular counteraction of the ketamine-induced resembling “negative-like” schizophrenia symptoms in rats using pentadecapeptide BPC 157, and NO-agents, NG-nitro-L-arginine methylester (L-NAME), and/or L-arginine, triple application. This might be the find out the NO-system organized therapy (i.e., simultaneously implied NO-system blockade (L-NAME) vs. NO-system over-stimulation (L-arginine) vs. NO-system immobilization (L-NAME+L-arginine)). The ketamine regimen (intraperitoneally/kg) included: 3 mg (cognitive dysfunction, novel object recognition test), 30 mg (anxiogenic effect (open field test) and anhedonia (sucrose test)), and 8 mg/3 days (social withdrawal). Medication (mg/kg intraperitoneally) was L-NAME (5), L-arginine (100), and BPC 157 (0.01), alone and/or together, given immediately before ketamine (L-NAME, L-arginine, and combination) or given immediately after (BPC 157 and combinations). BPC 157 counteracted ketamine-cognition dysfunction, social withdrawal, and anhedonia, and exerted additional anxiolytic effect. L-NAME (antagonization, social withdrawal) and L-arginine (antagonization, cognitive dysfunction, anhedonia) both included worsening cognitive dysfunction, anhedonia, and anxiogenic effect (L-NAME), social withdrawal, and anxiogenic effect (L-arginine). Thus, ketamine-induced resembling “negative-like” schizophrenia symptoms were “L-NAME non-responsive, L-arginine responsive” (cognition dysfunction), “L-NAME responsive, L-arginine non-responsive” (social withdrawal), “L-NAME responsive, L-arginine responsive, opposite effect” (anhedonia) and “L-NAME responsive, L-arginine responsive, parallel effect” (both anxiogening). In cognition dysfunction, BPC 157 overwhelmed NO-agents effects. The mRNA expression studies in brain tissue evidenced considerable overlapping of gene overexpression in healthy rats treated with ketamine or BPC 157. With the BPC 157 therapy applied immediately after ketamine, the effect on Nos1, Nos2, Plcg1, Prkcg, and Ptgs2 (increased or decreased expression), appeared as a timely specific BPC 157 effect on ketamine-specific targets.
SOX9 Protein in Pancreatic Cancer Regulates Multiple Cellular Networks in a Cell-Specific Manner
Authors: Kopantzev Eugene , Kondratyeva Liya , Kopantseva Marina , Kashkin Kirill , Gnatenko Dmitry , Grigorieva Elizaveta , Alekseenko Irina , Safina Dina , Chernov Igor
Published: June 2022

SOX9 is upregulated in the majority of pancreatic ductal adenocarcinoma cases. It is hypothesized that the increased expression of SOX9 is necessary for the formation and maintenance of tumor phenotypes in pancreatic cancer cells. In our research, we studied six pancreatic cancer cell lines, which displayed varying levels of differentiation and a range of oncogenic mutations. We chose the method of downregulation of SOX9 expression via siRNA transfection as the main method for investigating the functional role of the SOX9 factor in pancreatic cancer cells. We discovered that the downregulation of SOX9 expression in the cell lines leads to cell-line-specific changes in the expression levels of epithelial and mesenchymal protein markers. Additionally, the downregulation of SOX9 expression had a specific effect on the expression of pancreatic developmental master genes. SOX9 downregulation had the greatest effect on the expression levels of the protein regulators of cell proliferation. In three of the four cell lines studied, the transfection of siSOX9 led to a significant decrease in proliferative activity and to the activation of proapoptotic caspases in transfected cells. The acquired results demonstrate that the SOX9 protein exerts its multiple functions as a pleiotropic regulator of differentiation and a potential promoter of tumor growth in a cell-specific manner in pancreatic cancer cells.
Chrysin Induces Apoptosis and Autophagy in Human Melanoma Cells via the mTOR/S6K Pathway
Authors: Lee Jae-Han , Yoo Eun-Seon , Han So-Hee , Jung Gi-Hwan , Han Eun-Ji , Choi Eun-Young , Jeon Su-ji , Jung Soo-Hyun , Kim BumSeok , Cho Sung-Dae , Nam Jeong-Seok , Choi Changsun , Che Jeong-Hwan , Jung Ji-Youn
Published: June 2022

Chrysin is known to exert anti-inflammatory, antioxidant, and anticancer effects. The aim of this study was to investigate the anticancer effects of chrysin in the human melanoma cells A375SM and A375P. The results obtained demonstrated successful inhibition of the viability of these cells by inducing apoptosis and autophagy. This was confirmed by the level of apoptosis-related proteins: Bax and cleaved poly (ADP-ribose) polymerase both increased, and Bcl-2 decreased. Moreover, levels of LC3 and Beclin 1, both autophagy-related proteins, increased in chrysin-treated cells. Autophagic vacuoles and acidic vesicular organelles were observed in both cell lines treated with chrysin. Both cell lines showed different tendencies during chrysin-induced autophagy inhibition, indicating that autophagy has different effects depending on the cell type. In A375SM, the early autophagy inhibitor 3-methyladenine (3-MA) was unaffected; however, cell viability decreased when treated with the late autophagy inhibitor hydroxychloroquine (HCQ). In contrast, HCQ was unaffected in A375P; however, cell viability increased when treated with 3-MA. Chrysin also decreased the phosphorylation of mTOR/S6K pathway proteins, indicating that this pathway is involved in chrysin-induced apoptosis and autophagy for A375SM and A375P. However, studies to elucidate the mechanisms of autophagy and the action of chrysin in vivo are still needed.
Applications of Neural Networks in Biomedical Data Analysis
Authors: Weiss Romano , Karimijafarbigloo Sanaz , Roggenbuck Dirk , Rödiger Stefan
Published: June 2022

Neural networks for deep-learning applications, also called artificial neural networks, are important tools in science and industry. While their widespread use was limited because of inadequate hardware in the past, their popularity increased dramatically starting in the early 2000s when it became possible to train increasingly large and complex networks. Today, deep learning is widely used in biomedicine from image analysis to diagnostics. This also includes special topics, such as forensics. In this review, we discuss the latest networks and how they work, with a focus on the analysis of biomedical data, particularly biomarkers in bioimage data. We provide a summary on numerous technical aspects, such as activation functions and frameworks. We also present a data analysis of publications about neural networks to provide a quantitative insight into the use of network types and the number of journals per year to determine the usage in different scientific fields.
An Oral 3D Printed PLGA-Tocopherol PEG Succinate Nanocomposite Hydrogel for High-Dose Methotrexate Delivery in Maintenance Chemotherapy
Authors: Kondiah Pierre P. D. , Rants’o Thankhoe A. , Makhathini Sifiso S. , Mdanda Sipho , Choonara Yahya E.
Published: June 2022

High-dose methotrexate (HDMTX) is one of the chemotherapeutic agents used to treat a variety of cancers in both adults and children. However, the toxicity associated with HDMTX has resulted in the spread of infections and treatment interruption. Further, poor bioavailability due to efflux pump activities mediated by P-glycoprotein has also been linked to poor therapeutic effects of methotrexate following oral administrations. D-α-Tocopheryl poly-ethylene glycol 1000 succinate (TPGS) is known to improve the bioavailability of poorly soluble drugs by inhibiting P-gp efflux activities, thus enhancing cellular uptake. Therefore, to achieve improved bioavailability for MTX, this study aimed to design and develop a novel drug delivery system employing TPGS and a biodegradable polymer, i.e., PLGA, to construct methotrexate-loaded nanoparticles fixated in alginate-gelatine 3D printable hydrogel ink to form a solid 3D printed tablet for oral delivery. The results indicated that high accuracy (>95%) of the 3D printed tablets was achieved using a 25 G needle. In vitro, drug release profiles were investigated at pH 1.2 and pH 7.4 to simulate the gastrointestinal environment. The in vitro release profile displayed a controlled and prolonged release of methotrexate over 24 h. The in silico modeling study displayed P-gp ATPase inhibition, suggesting enhanced MTX absorption from the gastrointestinal site. The 3D-printed hydrogel-based tablet has the potential to overcome the chemotherapeutic challenges that are experienced with conventional therapies.
Silent Antibodies Start Talking: Enhanced Lateral Flow Serodiagnosis with Two-Stage Incorporation of Labels into Immune Complexes
Authors: Sotnikov Dmitriy V. , Byzova Nadezhda A. , Zherdev Anatoly V. , Xu Youchun , Dzantiev Boris B.
Published: June 2022

The presence of pathogen-specific antibodies in the blood is widely controlled by a serodiagnostic technique based on the lateral flow immunoassay (LFIA). However, its common one-stage format with an antigen immobilized in the binding zone of a test strip and a nanodispersed label conjugated with immunoglobulin-binding proteins is associated with risks of very low analytical signals. In this study, the first stage of the immunochromatographic serodiagnosis was carried out in its traditional format using a conjugate of gold nanoparticles with staphylococcal immunoglobulin-binding protein A and an antigen immobilized on a working membrane. At the second stage, a labeled immunoglobulin-binding protein was added, which enhanced the coloration of the bound immune complexes. The use of two separated steps, binding of specific antibodies, and further coloration of the formed complexes, allowed for a significant reduction of the influence of non-specific immunoglobulins on the assay results. The proposed approach was applied for the serodiagnosis using a recombinant RBD protein of SARS-CoV-2. As a result, an increase in the intensity of test zone coloration by more than two orders of magnitude was demonstrated, which enabled the significant reduction of false-negative results. The diagnostic sensitivity of the LFIA was 62.5% for the common format and 100% for the enhanced format. Moreover, the diagnostic specificity of both variants was 100%.
A Fast and Non-Destructive Prediction Model for Remaining Life of Rigid Pavement with or without Asphalt Overlay
Authors: Hong Xuan , Tan Weilin , Xiong Chunlong , Qiu Zhixiong , Yu Jiangmiao , Wang Duanyi , Wei Xiaopeng , Li Weixiong , Wang Zhaodong
Published: June 2022

Remaining life is an important indicator of pavement residual effective service time and is directly related to maintenance decision-making with limited funds. This paper proposes a fast and non-destructive model to predict the remaining life of rigid PCC (Portland cement concrete) pavement, with or without asphalt overlay. Firstly, a model was constructed according to the current Chinese design specifications for concrete pavement integrating an inverse design concept. Secondly, the prediction model was applied to three typical pavement sections with 1430, 1250 and 1000 slabs, respectively. Ground penetrating radar (GPR) was utilized to determine the geometric parameters in the predictive model and the physical state of the pavement. A falling weight detector (FWD) was utilized for determination of the mechanical parameters. A more reasonable equivalent elastic modulus of foundation was back-calculated instead of using the limited model in the design specification. Thirdly, the remaining life was predicted based on the current mechanical and geometric parameters. The distributions of the remaining life of the three pavement sections was statistically analyzed. Finally, a decision-making system to inform maintenance strategy was proposed based on the remaining life and the technical condition of each slab. The results showed that the relationship between the remaining life and the mechanical parameters, geometric parameters and the physical state of the pavement was highly consistent with engineering experience. The success rate of the prediction model was as high as 96%. The proposed fast and non-destructive prediction model showed good engineering applicability and feasibility. The decision-making system was shown to be feasible in terms of economic benefits.
Evaluation of Park Accessibility Based on Improved Gaussian Two-Step Floating Catchment Area Method: A Case Study of Xi’an City
Authors: Li Yunmei , Xie Yuanli , Sun Shaoqi , Hu Lifa
Published: June 2022

Park accessibility plays a critical role in evaluating the quality of park construction. However, the conventional accessibility model ignores non-spatial factors, so it is crucial to use more complex methods for evaluating park accessibility. This study aims to establish an improved Gaussian-based two-step floating catchment area method (iG2SFCA) based on Point of Interest (POI), population data and Baidu map, to measure the park accessibility of various travel modes (walking, riding and driving modes) in 5-min, 15-min and 30-min scenarios, and location quotient is used to assess spatial equity of parks. The results show that: (1) There are clear disparities between park supply and population demand at the street level. (2) iG2SFCA evaluates the level and attractiveness of the park comprehensively. It is more sensitive to identifying accessibility, which can lead to a more realistic assessment of Park accessibility. (3) Under the three modes of transportation, the accessible area of the park increases with time, and the accessibility difference between residential areas is the smallest under the 30-min scenario. Overall, accessibility of park is relatively high; however, there is an obvious tendency for the accessibility level to decrease from the park as the center. The areas with poor accessibility appear in the north and southeast of the research area. (4) There are regional variances in the spatial equity of parks within Xi’an 3 City, and the park configuration needs to be optimized. These findings can provide theoretical support for further optimizing the layout of park in Xi’an in order to improve the spatial equity of urban parks.
Development and Characterization of an Anti-Cancer Monoclonal Antibody for Treatment of Human Carcinomas
Authors: Tsang Kwong yok , Fantini Massimo , Mavroukakis Sharon A. , Zaki Anjum , Annunziata Christina M. , Arlen Philip M.
Published: June 2022

NEO-201 is an IgG1 humanized monoclonal antibody (mAb) that binds to tumor-associated variants of carcinoembryonic antigen-related cell adhesion molecule (CEACAM)-5 and CEACAM-6. NEO-201 reacts to colon, ovarian, pancreatic, non-small cell lung, head and neck, cervical, uterine and breast cancers, but is not reactive against most normal tissues. NEO-201 can kill tumor cells via antibody-dependent cell-mediated cytotoxicity (ADCC) and complement dependent cytotoxicity (CDC) to directly kill tumor cells expressing its target. We explored indirect mechanisms of its action that may enhance immune tumor killing. NEO-201 can block the interaction between CEACAM-5 expressed on tumor cells and CEACAM-1 expressed on natural killer (NK) cells to reverse CEACAM-1-dependent inhibition of NK cytotoxicity. Previous studies have demonstrated safety/tolerability in non-human primates, and in a first in human phase 1 clinical trial at the National Cancer Institute (NCI). In addition, preclinical studies have demonstrated that NEO-201 can bind to human regulatory T (Treg) cells. The specificity of NEO-201 in recognizing suppressive Treg cells provides the basis for combination cancer immunotherapy with checkpoint inhibitors targeting the PD-1/PD-L1 pathway.
Proteases and HPV-Induced Carcinogenesis
Authors: Vieira Gabriel Viliod , Somera dos Santos Fernanda , Lepique Ana Paula , da Fonseca Carol Kobori , Innocentini Lara Maria Alencar Ramos , Braz-Silva Paulo Henrique , Quintana Silvana Maria , Sales Katiuchia Uzzun
Published: June 2022

Persistent infection with Human papillomavirus (HPV) is the main etiologic factor for pre-malignant and malignant cervical lesions. Moreover, HPV is also associated with oropharynx and other anogenital carcinomas. Cancer-causing HPV viruses classified as group 1 carcinogens include 12 HPV types, with HPV 16 and 18 being the most prevalent. High-risk HPVs express two oncoproteins, E6 and E7, the products of which are responsible for the inhibition of p53 and pRB proteins, respectively, in human keratinocytes and cellular immortalization. p53 and pRB are pleiotropic proteins that regulate the activity of several signaling pathways and gene expression. Among the important factors that are augmented in HPV-mediated carcinogenesis, proteases not only control processes involved in cellular carcinogenesis but also control the microenvironment. For instance, genetic polymorphisms of matrix metalloproteinase 1 (MMP-1) are associated with carcinoma invasiveness. Similarly, the serine protease inhibitors hepatocyte growth factor activator inhibitor-1 (HAI-1) and -2 (HAI-2) have been identified as prognostic markers for HPV-dependent cervical carcinomas. This review highlights the most crucial mechanisms involved in HPV-dependent carcinogenesis, and includes a section on the proteolytic cascades that are important for the progression of this disease and their impact on patient health, treatment, and survival.
Association of Allostatic Load and All Cancer Risk in the SWAN Cohort
Authors: Shen Jie , Fuemmeler Bernard F. , Guan Yufan , Zhao Hua
Published: June 2022

Elevated chronic stress is thought to increase cancer risk, though the results so far have been inconsistent. In this study, we assessed the relationship between allostatic load (AL), a biological indicator of chronic stress, and overall cancer risk in 3015 women who participated in the Study of Women’s Health Across the Nation (SWAN). Based on the distribution of AL, the study population was categorized into four groups, from the lowest (1st category) to the highest AL group (4th category). At baseline, African American and Hispanic women were more likely to be in the higher AL categories than White women (p < 0.001). In addition, women who smoked regularly, drank alcohol regularly, had no leisure physical activity, and had restless sleep were also more likely to be in the higher AL categories than their relative counterparts (p < 0.001). We also observed that women in the lower-income category with no health insurance were more likely to be in the higher AL category (p < 0.001). The study then found that women in the 4th category of AL (the highest AL group) had a 1.64-fold increased risk of overall cancer (Hazard ratio (HR): 1.64, 95% confidence interval (CI): 1.04, 2.59). The risk association was further strengthened after adjusting demographics, healthy behaviors, and socioeconomic factors with an HR of 2.08. In further analysis of individual biomarkers of AL score, we found that higher levels of triglyceride and CRP were associated with increased risk of cancer, highlighting the role of metabolic dysfunction and inflammation in the etiology of cancer development. In summary, we report that higher AL is associated with increased cancer risk.
Theranostic Potentials of Gold Nanomaterials in Hematological Malignancies
Authors: Shakil Md Salman , Niloy Mahruba Sultana , Mahmud Kazi Mustafa , Kamal Mohammad Amjad , Islam Md Asiful
Published: June 2022

Hematological malignancies (HMs) are a heterogeneous group of blood neoplasia generally characterized by abnormal blood-cell production. Detection of HMs-specific molecular biomarkers (e.g., surface antigens, nucleic acid, and proteomic biomarkers) is crucial in determining clinical states and monitoring disease progression. Early diagnosis of HMs, followed by an effective treatment, can remarkably extend overall survival of patients. However, traditional and advanced HMs’ diagnostic strategies still lack selectivity and sensitivity. More importantly, commercially available chemotherapeutic drugs are losing their efficacy due to adverse effects, and many patients develop resistance against these drugs. To overcome these limitations, the development of novel potent and reliable theranostic agents is urgently needed to diagnose and combat HMs at an early stage. Recently, gold nanomaterials (GNMs) have shown promise in the diagnosis and treatment of HMs. Magnetic resonance and the surface-plasmon-resonance properties of GNMs have made them a suitable candidate in the diagnosis of HMs via magnetic-resonance imaging and colorimetric or electrochemical sensing of cancer-specific biomarkers. Furthermore, GNMs-based photodynamic therapy, photothermal therapy, radiation therapy, and targeted drug delivery enhanced the selectivity and efficacy of anticancer drugs or drug candidates. Therefore, surface-tuned GNMs could be used as sensitive, reliable, and accurate early HMs, metastatic HMs, and MRD-detection tools, as well as selective, potent anticancer agents. However, GNMs may induce endothelial leakage to exacerbate cancer metastasis. Studies using clinical patient samples, patient-derived HMs models, or healthy-animal models could give a precise idea about their theranostic potential as well as biocompatibility. The present review will investigate the theranostic potential of vectorized GNMs in HMs and future challenges before clinical theranostic applications in HMs.
The New Face of a Well-Known Antibiotic: A Review of the Anticancer Activity of Enoxacin and Its Derivatives
Authors: Jałbrzykowska Karolina , Chrzanowska Alicja , Roszkowski Piotr , Struga Marta
Published: June 2022

Enoxacin as a second-generation synthetic quinolone is known for its antibacterial action; however, in recent years there have been studies focusing on its anticancer potential. Interestingly, it turns out that compared to other fluoroquinolones, enoxacin exhibits uncommon cytotoxic properties. Besides its influence on apoptosis, the cell cycle and cell growth, it exhibits a regulatory action on microRNA biogenesis. It was revealed that the molecular targets of the enoxacin-mediated inhibition of osteoclastogenesis are vacuolar H+-ATPase subunits and the c-Jun N-terminal kinase signaling pathway, causing a decrease in cell invasiveness. Interestingly, the prooxidative nature of the subjected fluoroquinolone enhanced the cytotoxic effect. Crucial for the anticancer activity were the carboxyl group at the third carbon atom, fluorine at the seventh carbon atom and nitrogen at the eighth position of naphyridine. Modifications of the parent drug improved the induction of oxidative stress, cell cycle arrest and the dysregulation of microRNA. The inhibition of V-ATPase–microfilament binding was also observed. Enoxacin strongly affected various cancer but not normal cells, excluding keratinocytes, which suffered from phototoxicity. It seems to be an underestimated anticancer drug with pleiotropic action. Furthermore, its usage as a safe antibiotic with well-known pharmacokinetics and selectivity will enhance the development of anticancer treatment strategies. This review covers articles published within the years 2000–2021, with a strong focus on the recent years (2016–2021). However, some canonical papers published in twentieth century are also mentioned.