bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Excitability Rate on Physiological Responses to Stress in Goats
Authors: Kannan Govind , Batchu Phaneendra , Naldurtiker Aditya , Dykes Gregory S. , Kouakou Brou , Terrill Thomas H. , Gurrapu Priyanka
Published: April 2022

This study was conducted to determine if excitability score (ES) in goats can influence their physiological responses when subjected to stress. Thirty-six intact male Spanish goats (8-mo-old) were individually weighed and scored for excitability: 1 for calm (13 goats), 2 for moderately excitable (11 goats), and 3 for highly excitable (12 goats). To impose stress, goats were assigned to one of three treatments (TRT) for 90 min: (i) isolation in an open pen with metal grill panels, (ii) isolation in a pen with side panels covered using tarp sheets, and (iii) no isolation (control). Blood samples were collected at 0, 30, 60, and 90 min of isolation and physiological data were analyzed using MIXED procedures in SAS. The data from the two isolation treatments were pooled and compared with that of the control group. Plasma cortisol and non-esterified fatty acid concentrations were the lowest in goats with ES 1 (p < 0.05). Neutrophil–lymphocyte ratios were also the lowest in goats with a calm temperament (p < 0.01). Application of full quadratic model using response surface methodology (PROC RSREG) in SAS revealed that the influence of ES on physiological stress responses over time was not the same between the TRT groups. The results indicate that physiological stress responses are greater in goats with an excitable temperament compared to goats with a calm temperament.
Plasmid-Mediated Transfer of Antibiotic Resistance Genes in Soil
Authors: Meng Miaoling , Li Yaying , Yao Huaiying
Published: April 2022

Due to selective pressure from the widespread use of antibiotics, antibiotic resistance genes (ARGs) are found in human hosts, plants, and animals and virtually all natural environments. Their migration and transmission in different environmental media are often more harmful than antibiotics themselves. ARGs mainly move between different microorganisms through a variety of mobile genetic elements (MGEs), such as plasmids and phages. The soil environment is regarded as the most microbially active biosphere on the Earth’s surface and is closely related to human activities. With the increase in human activity, soils are becoming increasingly contaminated with antibiotics and ARGs. Soil plasmids play an important role in this process. This paper reviews the current scenario of plasmid-mediated migration and transmission of ARGs in natural environments and under different antibiotic selection pressures, summarizes the current methods of plasmid extraction and analysis, and briefly introduces the mechanism of plasmid splice transfer using the F factor as an example. However, as the global spread of drug-resistant bacteria has increased and the knowledge of MGEs improves, the contribution of soil plasmids to resistance gene transmission needs to be further investigated. The prevalence of multidrug-resistant bacteria has also made the effective prevention of the transmission of resistance genes through the plasmid-bacteria pathway a major research priority.
Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications
Authors: Bracamonte Johane H. , Saunders Sarah K. , Wilson John S. , Truong Uyen T. , Soares Joao S.
Published: April 2022

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid–structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.
Uniform Accuracy Lifetime Principle and Optimal Design Methods for Measurement Systems
Authors: Cheng Zhenying , Liu Liying , Li Ruijun
Published: April 2022

The accuracy of measurement instruments, as well as that of their components, gradually declines as time goes on. Due to different loss mechanisms and the allowable accuracy loss values, the accuracy lifetimes of a whole system and its components are generally nonuniform, which lead to the waste of resources and costs. In this paper, a novel design method based on the uniform accuracy lifetime principle is presented to avoid the waste of resources. After giving and determining the uniformity and accuracy loss weights, optimal design models are established, and the sequential quadratic programming (SQP) method is employed to solve the models. A design example is presented to verify the effectiveness of the design model and the solution method. Using this method, the minimum accuracy lifetime of the whole system extends from 73.07 weeks to 200 weeks, and the uniformity improves from 0.75 to 0.96. The proposed method can be used in practice to achieve the target of uniform accuracy lifetimes for measurement systems because it is easy for manufacturers to obtain the average loss velocities of different components. The implementation of the optimization method will greatly help to save resources and improve the utilization efficiency of instruments or equipment.
Electro-Mechanical Impedance Technique for Assessing the Setting Time of Steel-Fiber-Reinforced Mortar Using Embedded Piezoelectric Sensor
Authors: Lee Jun-Cheol , Lee Chang-Joon
Published: April 2022

The electro-mechanical impedance (EMI) change in Piezoelectric (PZT) sensors embedded in steel-fiber-reinforced mortar (SFRM) was investigated to assess the material setting time. The EMI was continuously monitored for 12 h by the PZT sensor embedded in SFRM having fiber volume fraction of 0.5%, 1.5%, and 2.0%. The initial and final setting time of the SFRM were estimated using EMI signal change. The penetration resistance test, a conventional test method for the setting time of cement mortar, was also conducted. In the penetration resistance test, it was observed that the initial and the final setting time of SFRM accelerated as the volume fraction of the steel fiber increased. On the other hand, in the EMI sensing technique, the initial and the final setting time of the SFRM were consistent regardless of the fiber volume fraction.
Classification and Fast Few-Shot Learning of Steel Surface Defects with Randomized Network
Authors: Nagy Amr M. , Czúni László
Published: April 2022

Quality inspection is inevitable in the steel industry so there are already benchmark datasets for the visual inspection of steel surface defects. In our work, we show, contrary to previous recent articles, that a generic state-of-art deep neural network is capable of almost-perfect classification of defects of two popular benchmark datasets. However, in real-life applications new types of errors can always appear, thus incremental learning, based on very few example shots, is challenging. In our article, we address the problems of the low number of available shots of new classes, the catastrophic forgetting of known information when tuning for new artifacts, and the long training time required for re-training or fine-tuning existing models. In the proposed new architecture we combine EfficientNet deep neural networks with randomized classifiers to aim for an efficient solution for these demanding problems. The classification outperforms all other known approaches, with an accuracy 100% or almost 100%, on the two datasets with the off-the-shelf network. The proposed few-shot learning approach shows considerably higher accuracy at a low number of shots than the different methods under testing, while its speed is significantly (at least 10 times) higher than its competitors. According to these results, the classification and few-shot learning of steel surface defects can be solved more efficiently than was possible before.
Modelling Electricity Consumption in Cambodia Based on Remote Sensing Night-Light Images
Authors: Gao Xumiao , Wu Mingquan , Gao Ju , Han Li , Niu Zheng , Chen Fang
Published: April 2022

The accurate estimation of electricity consumption and its spatial distribution are important in electricity infrastructural planning and the achievement of the United Nations Sustainable Development Goal 7 (SDG7). Electricity consumption can be estimated based on its correlation with nighttime lights observed using remote sensing imagery. Since night-light images are easily affected by cloud cover, few previous studies have estimated electricity consumption in cloudy areas. Taking Cambodia as an example, the present study proposes a method for denoising night-light images in cloudy areas and estimating electricity consumption. The results show that an exponential model is superior to linear and power function models for modelling the relationship between total night-light data and electricity consumption in Cambodia. The month-specific substitution method is best for annual night-light image synthesis in cloudy areas. Cambodia’s greatest electricity consumption occurs in its four most economically developed cities. Electricity consumption spreads outwards from these cities along the main transport routes to a large number of unelectrified areas.
Design of Model-Based and Model-Free Robust Control Strategies for Lower Limb Rehabilitation Exoskeletons
Authors: Saeed Muhammad Tallal , Gul Jahan Zeb , Kausar Zareena , Mughal Asif Mahmood , Din Zia Mohy Ud , Qin Shiyin
Published: April 2022

Rehabilitation in the form of locomotion assistance and gait training through robotic exoskeletons requires both precision and accuracy to achieve effective results. The essential challenge is to ensure robust tracking of the reference signal, i.e., of the gait or locomotion. This paper presents the design of model-based (MB) and model-free (MF) robust control strategies to achieve desired performance and robustness in terms of transient behavior and steady-state/tracking error, implementable to the locomotion assistance and gait training by exoskeletons. The dynamic responses of the exoskeleton system were investigated with both the control strategies. The study was carried out with a variety of reference signals and performance was evaluated to identify the best suited approach for rehabilitation exoskeletons. In case of the model-based control, a mathematical model of the system was developed using a bond graph modeling technique and a lead compensated H-infinity reference gain controller was designed to ensure robust tracking performance. In the model-free control strategy, however, the system function is approximated using radial basis function neural networks (RBFNNs) and an adaptive proportional-derivative RBFNN controller was designed to achieve the desired results with minimum tracking error. Both strategies make the system robust and stable. However, the MF control strategy is faster for all reference inputs as compared to the MB control strategy i.e., faster to approach the peak value and settle, and rapidly approaches the zero steady-state/tracking error. The rise time in the case of a sinusoidal input for model-free control is 0.4 s faster than the rise time in model-based control. Similarly, the settling time is 3.9 s faster in the case of model-free control, which is a prominent difference and can provide better rehabilitation results.
Production of Docosahexaenoic Acid and Odd-Chain Fatty Acids by Microalgae Schizochytrium limacinum Grown on Waste-Derived Volatile Fatty Acids
Authors: Oliver Laura , Fernández-de-Castro Laura , Dietrich Thomas , Villaran Maria Carmen , Barrio Ramón J.
Published: April 2022

Heterotrophic microalgae are recognized as a source of bioactive compounds. However, there are still some drawbacks for their use at an industrial scale associated with the high cost of glucose, the main carbon source in heterotrophic cultures. In recent years, significant efforts have been made to investigate more sustainable carbon sources to produce biomass. In this study, the capacity of Schizochytrium limacinum to grow on waste-derived volatile fatty acids and the effect that their use produces on biomass and fatty acids profiles were investigated. Acetic, propionic, butyric, valeric and caproic acid were evaluated independently, as well as in a synthetic mixture (VFA). The use of acetic and butyric resulted in a good biomass productivity, while the use of valeric and propionic acid resulted in higher content of odd-chain fatty acids (OCFA), increasingly investigated due to their potential benefits for human health. The use of industrial waste-derived VFA as a potential carbon source was validated through the utilization of biowaste derived effluents from a volatile fatty acid platform. The biomass produced was of 18.5 g/L, 54.0% lipids, 46.3% docosahexaenoic acid (DHA) and 25.0% OCFA, concluding that waste derived VFA can produce DHA and OCFA in a suitable ratio of DHA/OCFA with potential industrial applications.
Noise Characteristics Analysis of Medical Electric Leg Compression Machine Using Multibody Dynamic Simulation
Authors: Kang Sungwook , Kim Hyunsoo , Kim Jaewoong , Hwang Jong-Moon , Lee Wonhee , Kim Jungtae , Ryu Hyunsu
Published: April 2022

Conventional medical equipment used for treating patients with ischemic heart disease relies on pneumatic compression to achieve intense and instantaneous compression of the legs. Because the pneumatic operation of a compressor inevitably produces noise, the treatment is given to a patient in a separate room to avoid causing discomfort to other patients. This need for a dedicated treatment room could be another source of increased medical costs. In this study, a new electrical motor-driven system was developed to address the noise problem of existing pneumatic compression devices. Additionally, the new system features a reduced footprint and weight, and can be carried by medical staff. To develop a low-noise leg compression machine, the noise level at the surface of the structure was estimated using multibody dynamics simulation. Based on the initial design of the electric leg compression machine, parameters including assembly tolerance, component material, and shape of the structure were adjusted to prepare variations of the initial design, and their noise characteristics were analyzed. It was found that by applying the design variables, the noise levels were reduced by 7.2–11.7% compared with the initial design. The most significant reduction in noise levels was 11.7% and was achieved by reinforcing the section surrounding the gearbox enclosing a noise source.
Design and Development of OECT Logic Circuits for Electrical Stimulation Applications
Authors: Kostić Miloš , Kojić Vladimir , Ičagić Savo , Andersson Ersman Peter , Mulla Mohammad Yusuf , Strandberg Jan , Herlogsson Lars , Keller Thierry , Štrbac Matija
Published: April 2022

This paper presents the first successful implementation of fully printed electronics for flexible and wearable smart multi-pad stimulation electrodes intended for use in medical, sports and lifestyle applications. The smart multi-pad electrodes with the electronic circuits based on organic electrochemical transistor (OECT)-based electronic circuits comprising the 3–8 decoder for active pad selection and high current throughput transistors for switching were produced by multi-layer screen printing. Devices with different architectures of switching transistors were tested in relevant conditions for electrical stimulation applications. An automated testbed with a configurable stimulation source and an adjustable human model equivalent circuit was developed for this purpose. Three of the proposed architectures successfully routed electrical currents of up to 15 mA at an output voltage of 30 V, while one was reliably performing even at 40 V. The presented results demonstrate feasibility of the concept in a range of conditions relevant to several applications of electrical stimulation.
Credibility Analysis of User-Designed Content Using Machine Learning Techniques
Authors: Gayakwad Milind , Patil Suhas , Kadam Amol , Joshi Shashank , Kotecha Ketan , Joshi Rahul , Pandya Sharnil , Gonge Sudhanshu , Rathod Suresh , Kadam Kalyani , Shelke Maya
Published: April 2022

Content is a user-designed form of information, for example, observation, perception, or review. This type of information is more relevant to users, as they can relate it to their experience. The research problem is to identify the credibility and the percentage of credibility as well. Assessment of such content is important to convey the right understanding of the information. Different techniques are used for content analysis, such as voting the content, Machine Learning Techniques, and manual assessment to evaluate the content and the quality of information. In this research article, content analysis is performed by collecting the Movie Review dataset from Kaggle. Features are extracted and the most relevant features are shortlisted for experimentation. The effect of these features is analyzed by using base regression algorithms, such as Linear Regression, Lasso Regression, Ridge Regression, and Decision Tree. The contribution of the research is designing a heterogeneous ensemble regression algorithm for content credibility score assessment, which combines the above baseline methods. Moreover, these factors are also toned down to obtain the values closer to Gradient Descent minimum. Different forms of Error Loss, such as Mean Absolute Error, Mean Squared Error, LogCosh, Huber, and Jacobian, and the performance is optimized by introducing the balancing bias. The accuracy of the algorithm is compared with induvial regression algorithms and ensemble regression separately; this accuracy is 96.29%.
Measurement of Photoionization Cross-Section for the Excited States of Atoms: A Review
Authors: Baig Muhammad Aslam
Published: April 2022

A review of experimental studies of the measurement of the photoionization cross-section for the excited states of the alkali atoms, alkaline earth atoms, and rare-gas atoms is presented, with emphasis on using multi-step laser excitation, ionization, and the saturation technique. The dependence of the photoionization cross-section from different intermediate states populated in the first step and ionized in the second step are discussed, including results on the photoionization cross-sections measured above the first ionization threshold. Results based on different polarizations of the exciting and the ionizing dye lasers are also discussed. Examples are provided, illustrating the photoionization cross-sections measured using thermionic diode ion detector, atomic beam apparatus in conjunction with a time-of-flight mass spectrometer and DC/RF glow discharge cell as an optogalvanic detection.
Approximate Optimal Control for a Parabolic System with Perturbations in the Coefficients on the Half-Axis
Authors: Kapustian Olena A. , Kapustyan Oleksiy V. , Ryzhov Anton , Sobchuk Valentyn
Published: April 2022

In this paper, we use the averaging method to find an approximate solution in the optimal control problem of a parabolic system with non-linearity of the form f(t/ε,y) on an infinite time interval.
Fuzzy Multi Criteria Decision Making Model for Agritourism Location Selection: A Case Study in Vietnam
Authors: Wu Chihkang Kenny , Wang Chia-Nan , Le Thi Kim Trang
Published: April 2022

Agritourism is an increasing new trend in the global tourism industry. Vietnam has a long tradition of agricultural production combined with diverse natural resources stretching from the north to the south, bringing advantages in the development of agritourism. The study aims to choose the most appropriate agritourism location in Vietnam for long-term investment. A hybrid fuzzy multi-criteria decision model (FMCDM) is proposed to find the optimal location based on eco-nomic, social, and environmental factors. In the first stage, the fuzzy analytic hierarchy process (FAHP) is used to estimate the relative criteria rating through the evaluation process. In the second stage, the fuzzy technique for order preference using similarities to ideal solution (FTOPSIS) is applied to rank the potential alternative locations. Finally, the best alternative to tourist site investment is Can Tho (A8), which maximizes resources and enhances the local benefits. Future research can also be used to support similar site-selection processes in other regions or could be applied to other types of tourism.
Machine Learning and Regression Analysis to Model the Length of Hospital Stay in Patients with Femur Fracture
Authors: Ricciardi Carlo , Ponsiglione Alfonso Maria , Scala Arianna , Borrelli Anna , Misasi Mario , Romano Gaetano , Russo Giuseppe , Triassi Maria , Improta Giovanni
Published: April 2022

Fractures of the femur are a frequent problem in elderly people, and it has been demonstrated that treating them with a diagnostic–therapeutic–assistance path within 48 h of admission to the hospital reduces complications and shortens the length of the hospital stay (LOS). In this paper, the preoperative data of 1082 patients were used to further extend the previous research and to generate several models that are capable of predicting the overall LOS: First, the LOS, measured in days, was predicted through a regression analysis; then, it was grouped by weeks and was predicted with a classification analysis. The KNIME analytics platform was applied to divide the dataset for a hold-out cross-validation, perform a multiple linear regression and implement machine learning algorithms. The best coefficient of determination (R2) was achieved by the support vector machine (R2 = 0.617), while the mean absolute error was similar for all the algorithms, ranging between 2.00 and 2.11 days. With regard to the classification analysis, all the algorithms surpassed 80% accuracy, and the most accurate algorithm was the radial basis function network, at 83.5%. The use of these techniques could be a valuable support tool for doctors to better manage orthopaedic departments and all their resources, which would reduce both waste and costs in the context of healthcare.
Phylogeny and Metabolic Potential of the Candidate Phylum SAR324
Authors: Malfertheiner Lukas , Martínez-Pérez Clara , Zhao Zihao , Herndl Gerhard J. , Baltar Federico
Published: April 2022

The bacterial SAR324 cluster is ubiquitous and abundant in the ocean, especially around hydrothermal vents and in the deep sea, where it can account for up to 30% of the whole bacterial community. According to a new taxonomy generated using multiple universal protein-coding genes (instead of the previously used 16S rRNA single gene marker), the former Deltaproteobacteria cluster SAR324 has been classified since 2018 as its own phylum. Yet, very little is known about its phylogeny and metabolic potential. We downloaded all publicly available SAR324 genomes (65) from all natural environments and reconstructed 18 new genomes using publicly available oceanic metagenomic data and unpublished data from the waters underneath the Ross Ice Shelf. We calculated a global SAR324 phylogenetic tree and identified six clusters (namely 1A, 1B, 2A, 2B, 2C and 2D) within this clade. Genome annotation and metatranscriptome read mapping showed that SAR324 clades possess a flexible array of genes suited for survival in various environments. Clades 2A and 2C are mostly present in the surface mesopelagic layers of global oceans, while clade 2D dominates in deeper regions. Our results show that SAR324 has a very versatile and broad metabolic potential, including many heterotrophic, but also autotrophic pathways. While one surface water associated clade (2A) seems to use proteorhodopsin to gain energy from solar radiation, some deep-sea genomes from clade 2D contain the complete Calvin–Benson–Bassham cycle gene repertoire to fix carbon. This, in addition to a variety of other genes and pathways for both oxic (e.g., dimethylsulfoniopropionate degradation) and anoxic (e.g., dissimilatory sulfate reduction, anaerobic benzoate degradation) conditions, can help explain the ubiquitous presence of SAR324 in aquatic habitats.
Insulin Receptors and Insulin Action in the Heart: The Effects of Left Ventricular Assist Devices
Authors: Pantazi Konstantina , Karlafti Eleni , Bekiaridou Alexandra , Didagelos Matthaios , Ziakas Antonios , Didangelos Triantafyllos
Published: April 2022

This year, 2022, marks the 100th anniversary of the isolation of human insulin and its administration to patients suffering from diabetes mellitus (DM). Insulin exerts many effects on the human body, including the cardiac tissue. The pathways implicated include the PKB/Akt signaling pathway, the Janus kinase, and the mitogen-activated protein kinase pathway and lead to normal cardiac growth, vascular smooth muscle regulation, and cardiac contractility. This review aims to summarize the existing knowledge and provide new insights on insulin pathways of cardiac tissue, along with the role of left ventricular assist devices on insulin regulation and cardiac function.
Potential Wound Healing Effect of Gel Based on Chicha Gum, Chitosan, and Mauritia flexuosa Oil
Authors: Ferreira Maria Onaira Gonçalves , Ribeiro Alessandra Braga , Rizzo Marcia S. , de Jesus Oliveira Antonia Carla , Osajima Josy Anteveli , Estevinho Leticia M. , Silva-Filho Edson C.
Published: April 2022

Wounds are considered a clinically critical issue, and effective treatment will decrease complications, prevent chronic wound formation, and allow rapid healing. The development of products based on naturally occurring materials is an efficient approach to wound healing. Natural polysaccharides can mimic the extracellular matrix and promote cell growth, thus making them attractive for wound healing. In this context, the aim of this work was to produce a gel based on chicha gum, chitosan, and Mauritia flexuosa oil (CGCHO) for wound treatment. TG and DTG analyzed the thermal behavior of the materials, and SEM investigated the surface roughness. The percentages of total phenolic compounds, flavonoids, and antioxidants were determined, presenting a value of 81.811 ± 7.257 µmol gallic acid/g Mauritia flexuosa oil, 57.915 ± 0.305 µmol quercetin/g Mauritia flexuosa oil, and 0.379 mg/mL, respectively. The anti-inflammatory was determined, presenting a value of 10.35 ± 1.46% chicha gum, 16.86 ± 1.00% Mauritia flexuosa oil, 10.17 ± 1.05% CGCHO, and 15.53 ± 0.65% chitosan, respectively. The materials were tested against Gram-negative (Klebsiella pneumoniae) and Gram-positive (Staphylococcus aureus) bacteria and a fungus (Candida albicans). The CGCHO formulation showed better antimicrobial activity against Gram-positive bacteria. In addition, an in vivo wound healing study was also performed. After 21 days of treatment, the epidermal re-epithelialization process was observed. CGCHO showed good thermal stability and roughness that can help in cell growth and promote the tissue healing process. In addition to the good results observed for the antimicrobial, antioxidant, anti-inflammatory activities and providing wound healing, they provided the necessary support for the healing process, thus representing a new approach to the wound healing process.
Graphene-Based Biosensors for Molecular Chronic Inflammatory Disease Biomarker Detection
Authors: Badillo-Ramírez Isidro , Carreón Yojana J. P. , Rodríguez-Almazán Claudia , Medina-Durán Claudia M. , Islas Selene R. , Saniger José M.
Published: April 2022

Chronic inflammatory diseases, such as cancer, diabetes mellitus, stroke, ischemic heart diseases, neurodegenerative conditions, and COVID-19 have had a high number of deaths worldwide in recent years. The accurate detection of the biomarkers for chronic inflammatory diseases can significantly improve diagnosis, as well as therapy and clinical care in patients. Graphene derivative materials (GDMs), such as pristine graphene (G), graphene oxide (GO), and reduced graphene oxide (rGO), have shown tremendous benefits for biosensing and in the development of novel biosensor devices. GDMs exhibit excellent chemical, electrical and mechanical properties, good biocompatibility, and the facility of surface modification for biomolecular recognition, opening new opportunities for simple, accurate, and sensitive detection of biomarkers. This review shows the recent advances, properties, and potentialities of GDMs for developing robust biosensors. We show the main electrochemical and optical-sensing methods based on GDMs, as well as their design and manufacture in order to integrate them into robust, wearable, remote, and smart biosensors devices. We also describe the current application of such methods and technologies for the biosensing of chronic disease biomarkers. We also describe the current application of such methods and technologies for the biosensing of chronic disease biomarkers with improved sensitivity, reaching limits of detection from the nano to atto range concentration.
The Capitalization of School Quality in Rents in the Beijing Housing Market: A Propensity Score Matching Method
Authors: Song Zisheng
Published: April 2022

In China, the capitalization of education resources in housing prices has been widely discussed. However, insufficient attention is paid to it in rents. Thus, this paper mainly aims to identify the capitalization of school quality in rents. It estimates a hedonic treatment effects model by introducing the propensity score matching (PSM) method. The empirical analysis is based on 49,438 rental transaction data of 2016–2018 in Beijing, China. It finds that school quality can be significantly capitalized in rents across different school quality (ranked as 1st-class, 2nd-class, and popular-class), space, and time. Besides, quality school density (the number of quality schools) within neighborhoods can significantly moderate the nearest school’s capitalization, promoting a 3.5% capitalization increase in outer municipal districts but a 3% decrease in inner districts. The popular-class schools can be capitalized into the rent of inner districts, probably because of other exogenous factors (e.g., housing prices, public transit). In addition, the equitable housing policy might show a potential risk in worsening social inequality between homeowners and renters in the municipal areas with high competition for 1st-class schools. In contrast, it may remedy such inequality in outer districts with less competition for quality schools.
Selection of Low-Carbon Building Materials in Construction Projects: Construction Professionals’ Perspectives
Authors: Chan Melissa , Masrom Md. Asrul Nasid , Yasin Suleiman Said
Published: April 2022

The construction sector in Malaysia has been facing challenges in productivity due to the increase in greenhouse gas (GHG) emissions. This study aims to enhance the usage of low-carbon building materials among construction professionals so that the carbon emission and GHG can be reduced during the early stage of construction. The scope of this research involved main parties in the Malaysian construction industry, represented by fifty professionals including contractors, consultants, and architects with a focus on low-carbon building materials. Procedures in this study involved a literature review on low-carbon building materials in the construction industry followed by a questionnaire survey with analysis using One-way Analysis of Variance (ANOVA). Major study findings indicated that there is a significant need for increasing the awareness of low-carbon building materials, as this is vital to introduce the concept of sustainable development and consequently cutting down carbon emissions to all parties working in construction. The study also suggested that barriers in adoption also prevent alternative material choices as a means of mitigating embodied carbon emissions. Many of these barriers are common across materials with uptake restricted by lack of demonstration projects, regulation, high costs, shortage of skilled labor, lack of design knowledge, time constraints, and lack of knowledge on LCA. The results are significant as the construction industry can seek to overcome these barriers by providing more information on material performance, design training on alternative materials, cost reduction on low-carbon materials, and more demonstration projects as well as case studies. From the work in this study, the industry must also share the knowledge on embodied carbon and implement regulations that will limit embodied carbon. The industry must adopt a business case strategy in encouraging greater value in assessment schemes to adopt low carbon building materials.
SRPX Emerges as a Potential Tumor Marker in the Extracellular Vesicles of Glioblastoma
Authors: Ampudia-Mesias Elisabet , El-Hadad Samia , Cameron Charles Scott , Wöhrer Adelheid , Ströbel Thomas , Saydam Nurten , Saydam Okay
Published: April 2022

Extracellular vesicles (EVs) may be used as a non-invasive screening platform to discover markers associated with early diagnosis, prognosis, and treatment response. Such an approach is invaluable for diseases such as glioblastoma, for which only a few non-invasive diagnostic or prognostic markers are available. We used mass spectrometry to analyze proteomics profiles of EVs derived from four glioblastoma cell lines and human primary astrocytes (HPAs) and found that SRPX is the only protein enriched in the majority of glioblastoma EVs that was absent in the HPA-derived EVs. Then, we evaluated the relationship between SRPX protein expression and tumor grade using immunohistochemical staining (IHC) and performed colony formation and viability assays to analyze the possible function of SRPX in glioblastoma. SRPX mRNA and protein expression were associated with tumor grade. Moreover, temozolomide (TMZ)-resistant tumor tissues showed highly positive SRPX staining, compared to all other tumor grades. Additionally, glioblastoma cells displayed enhanced SRPX gene expression when exposed to TMZ. Knockdown of SRPX gene expression via siRNA inhibited cell viability. Taken together, the results of this study suggest that SRPX can be used as a novel tumor marker for diagnostic and prognostic purposes and can also be a therapeutic target for glioblastomas.
Effects of Multimodal Bundle with Remote Ischemic Preconditioning and Intrathecal Analgesia on Early Recovery of Estimated Glomerular Filtration Rate after Robot-Assisted Laparoscopic Partial Nephrectomy for Renal Cell Carcinoma
Authors: Chae Min Suk , Shim Jung-Woo , Choi Hoon , Hong Sung Hoo , Lee Ji Youl , Jeong Woohyung , Lee Bongsung , Kim Eunji , Hong Sang Hyun
Published: April 2022

We investigated the effects of multimodal combined bundle therapy, consisting of remote ischemic preconditioning (RIPC) and intrathecal morphine block (ITMB), on the early recovery of kidney function after robot-assisted laparoscopic partial nephrectomy (RALPN) in patients with renal cell carcinoma (RCC). In addition, we compared the surgical and analgesic outcomes between patients with and without bundle treatment. This prospective randomized double-blind controlled trial was performed in a cohort of 80 patients with RCC, who were divided into two groups: a bundle group (n = 40) and non-bundle group (n = 40). The primary outcome was postoperative kidney function, defined as the lowest estimated glomerular filtration rate (eGFR) on postoperative day (POD) 2. Surgical complications, pain, and length of hospital stay were assessed as secondary outcomes. The eGFR immediately after surgery was significantly lower in the bundle group compared to the preoperative baseline, but serial levels on PODs 1 and 2 and at three and six months after surgery were comparable to the preoperative baseline. The eGFR level immediately after surgery was lower in the non-bundle than bundle group, and serial levels on PODs 1 and 2 and at three months after surgery remained below the baseline. The eGFR level immediately after surgery was higher in the bundle group than in the non-bundle group. The eGFR changes immediately after surgery, and on POD 1, were smaller in the bundle than in the non-bundle group. The non-bundle group had longer hospital stays and more severe pain than the bundle group, but there were no severe surgical complications in either group. The combined RIPC and ITMB bundle may relieve ischemia–reperfusion- and pain-induced stress, as a safe and efficient means of improving renal outcomes following RALPN in patients with RCC.
Next-Generation DNA Sequencing-Based Gene Panel for Diagnosis and Genetic Risk Stratification in Onco-Hematology
Authors: Gargallo Pablo , Molero Merche , Bilbao Cristina , Stuckey Ruth , Carrillo-Cruz Estrella , Hermosín Lourdes , Pérez-López Olga , Jiménez-Velasco Antonio , Soria Elena , Lázaro Marián , Carbonell Paula , Yáñez Yania , Gómez Iria , Izquierdo-García Marta , Valero-García Jennifer , Ruiz Carlos , Such Esperanza , Calabria Inés
Published: April 2022

A suitable diagnostic classification of myeloid neoplasms and acute leukemias requires testing for a large number of molecular biomarkers. Next-generation sequencing is a technology able to integrate identification of the vast majority of them in a single test. This manuscript includes the design, analytical validation and clinical feasibility evaluation of a molecular diagnostic kit for onco-hematological diseases. It is based on sequencing of the coding regions of 76 genes (seeking single-nucleotide variants, small insertions or deletions and CNVs), as well as the search for fusions in 27 target genes. The kit has also been designed to detect large CNVs throughout the genome by including specific probes and employing a custom bioinformatics approach. The analytical and clinical feasibility validation of the Haematology OncoKitDx panel has been carried out from the sequencing of 170 patient samples from 6 hospitals (in addition to the use of commercial reference samples). The analytical validation showed sensitivity and specificity close to 100% for all the parameters evaluated, with a detection limit of 2% for SNVs and SVs, and 20% for CNVs. Clinically relevant mutations were detected in 94% of all patients. An analysis of the correlation between the genetic risk classification of AML (according to ELN 2017) established by the hospitals and that obtained by the Haematology OncoKitDx panel showed an almost perfect correlation (K = 0.94). Among the AML samples with a molecular diagnosis, established by the centers according to the WHO, the Haematology OncoKitDx analysis showed the same result in 97% of them. The panel was able to adequately differentiate between MPN subtypes and also detected alterations that modified the diagnosis (FIP1L1-PDGFRA). Likewise, the cytogenetic risk derived from the CNV plot generated by the NGS panel correlated substantially with the results of the conventional karyotype (K = 0.71) among MDS samples. In addition, the panel detected the main biomarkers of prognostic value among patients with ALL. This validated solution enables a reliable analysis of a large number of molecular biomarkers from a DNA sample in a single assay.
Importance of and Satisfaction with Domains of Health-Related Quality of Life in Cancer Rehabilitation
Authors: Hinz Andreas , Schulte Thomas , Ernst Jochen , Mehnert-Theuerkauf Anja
Published: April 2022

Instruments for measuring health-related quality of life (HRQoL) generally do not consider the subjective importance of the dimensions they comprise. The aims of this study were to analyze the subjectively perceived importance of the dimension of HRQoL and to investigate their relationship to the satisfaction ratings with these dimensions. A total of 1108 participants enrolled in a cancer rehabilitation program were surveyed. Patients rated eight dimensions of HRQoL (physical functioning, autonomy, emotional stability, cognitive functioning, social relationships, vitality, absence of pain, and sleep quality), as well as global health in terms of how important those dimensions are to them, and how satisfied they are with them. The dimensions with the highest importance ratings were autonomy and social relationships. There were only small sex differences in the importance ratings, but younger patients rated health as being more important than older patients did. The correlations between the importance ratings and the satisfaction ratings of the specific HRQoL dimensions ranged from −0.06 to 0.40, and the correlation between importance and satisfaction for global health was 0.01. Importance ratings provide relevant information for health care professionals in addition to the HRQoL assessments in the context of cancer rehabilitation.
MBP-11901 Inhibits Tumor Growth of Hepatocellular Carcinoma through Multitargeted Inhibition of Receptor Tyrosine Kinases
Authors: Park Hyun Jin , Choi Garam , Ha Seongmin , Kim Yesl , Choi Min-Jin , Kim Minsup , Islam Md. Kamrul , Chang Yongmin , Kwon Tae-Jun , Kim Dongkyu , Jang Eunbee , Kim Tae Hwan , Chang Sha Joung , Kim Yeoun-Hee
Published: April 2022

Hepatocellular carcinomas (HCCs) are aggressive tumors with a poor prognosis. Approved first-line treatments include sorafenib, lenvatinib, and a combination of atezolizumab and bevacizumab; however, they do not cure HCC. We investigated MBP-11901 as a drug candidate for HCC. Cell proliferation and cytotoxicity were evaluated using normal and cancer human liver cell lines, while Western blotting and flow cytometry evaluated apoptosis. The anticancer effect of MBP-11901 was verified in vitro through migration, invasion, colony formation, and JC-1 MMP assays. In mouse models, the tumor volume, tumor weight, and bodyweight were measured, and cancer cell proliferation and apoptosis were analyzed. The toxicity of MBP-11901 was investigated through GOT/GPT and histological analyses in the liver and kidney. The signaling mechanism of MBP-11901 was investigated through kinase assays, phosphorylation analysis, and in silico docking simulations. Results. MBP-11901 was effective against various human HCC cell lines, leading to the disappearance of most tumors when administered orally in animal models. This effect was dose-dependent, with no differences in efficacy according to administration intervals. MBP-11901 induced anticancer effects by targeting the signaling mechanisms of FLT3, VEGFR2, c-KIT, and PDGFRβ. MBP-11901 is suggested as a novel therapeutic agent for the treatment of advanced or unresectable liver cancer.
Development and Functional Characterization of a Versatile Radio-/Immunotheranostic Tool for Prostate Cancer Management
Authors: Arndt Claudia , Bergmann Ralf , Striese Franziska , Merkel Keresztély , Máthé Domokos , Loureiro Liliana R. , Mitwasi Nicola , Kegler Alexandra , Fasslrinner Frederick , González Soto Karla Elizabeth , Neuber Christin , Berndt Nicole , Kovács Noemi , Szöllősi David , Hegedűs Nikolett , Tóth Gyula , Emmermann Jan-Philipp , Harikumar Kuzhuvelil B. , Kovacs Tibor , Bachmann Michael , Feldmann Anja
Published: April 2022

Due to its overexpression on the surface of prostate cancer (PCa) cells, the prostate stem cell antigen (PSCA) is a potential target for PCa diagnosis and therapy. Here we describe the development and functional characterization of a novel IgG4-based anti-PSCA antibody (Ab) derivative (anti-PSCA IgG4-TM) that is conjugated with the chelator DOTAGA. The anti-PSCA IgG4-TM represents a multimodal immunotheranostic compound that can be used (i) as a target module (TM) for UniCAR T cell-based immunotherapy, (ii) for diagnostic positron emission tomography (PET) imaging, and (iii) targeted alpha therapy. Cross-linkage of UniCAR T cells and PSCA-positive tumor cells via the anti-PSCA IgG4-TM results in efficient tumor cell lysis both in vitro and in vivo. After radiolabeling with 64Cu2+, the anti-PSCA IgG4-TM was successfully applied for high contrast PET imaging. In a PCa mouse model, it showed specific accumulation in PSCA-expressing tumors, while no uptake in other organs was observed. Additionally, the DOTAGA-conjugated anti-PSCA IgG4-TM was radiolabeled with 225Ac3+ and applied for targeted alpha therapy. A single injection of the 225Ac-labeled anti-PSCA IgG4-TM was able to significantly control tumor growth in experimental mice. Overall, the novel anti-PSCA IgG4-TM represents an attractive first member of a novel group of radio-/immunotheranostics that allows diagnostic imaging, endoradiotherapy, and CAR T cell immunotherapy.
Prognostic Value of Systemic Inflammatory Response Markers in Patients Undergoing Neoadjuvant Chemotherapy and Gastrectomy for Advanced Gastric Cancer in the Eastern European Population
Authors: Pikuła Agnieszka , Skórzewska Magdalena , Pelc Zuzanna , Mlak Radosław , Gęca Katarzyna , Sędłak Katarzyna , Ciseł Bogumiła , Kwietniewska Magdalena , Rawicz-Pruszyński Karol , Polkowski Wojciech P.
Published: April 2022

The prognostic value of the systemic inflammatory response markers, namely neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) has not yet been clarified in patients undergoing neoadjuvant chemotherapy (NAC) and gastrectomy for advanced gastric cancer (GC) in the Eastern European population. This study aimed to verify the prognostic value of NLR, PLR, and LMR in GC patients undergoing multimodal treatment. One hundred six GC patients undergoing NAC and gastrectomy between 2012 and 2020 were included. Analysed blood samples were obtained prior to NAC (pre-NAC group) and before surgical treatment (post-NAC group). To evaluate the prognostic value of the NLR, LMR, and PLR, univariable and multivariable overall survival (OS) analyses were performed. In the pre-NAC group, elevated NLR and PLR were associated with significantly higher risk of death (mOS: 36 vs. 87 months; HR = 2.21; p = 0.0255 and mOS: 30 vs. 87 months; HR = 2.89; p = 0.0034, respectively). Additionally, a significantly higher risk of death was observed in patients with elevated NLR in the post-NAC group (mOS: 35 vs. 87 months; HR = 1.94; p = 0.0368). Selected systemic inflammatory response markers (NLR, PLR) are significant prognostic factors in patients with advanced GC treated with NAC and gastrectomy, as shown in the Eastern European population.
EGFR Signaling in Non-Small Cell Lung Cancer: From Molecular Mechanisms to Therapeutic Opportunities
Authors: La Monica Silvia
Published: April 2022

Lung cancer is the leading cause of cancer death worldwide [...]