bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancement of a Single-Axis Femtosecond Laser Scanning System by Using Two Galvanometers to Improve the Telecentricity and the Effective Scanning Length on Laser Process
Authors: Nguyen Xuan-Huy , Chen Chao-Ming , Le Hien-Thanh , Lee Hsiao-Yi
Published: December 2022

The galvanometer scanning system plays a crucial role in modern laser material processing. With the development of this industry, the requirements for galvanometer scanners are getting higher and higher, especially to overcome the inherent disadvantages that still exist, such as image distortion, marking speed and accuracy in state-of-the-art scanning systems. In this paper, a single-axis optical scanner using two galvanometers in combination with one f-theta telecentric lens and a 343 nm femtosecond pulse laser source is proposed as a new approach for enhancing the precision of laser micromachining technology. The additional second galvanometer is used to manipulate the output laser beam of the first galvanometer to the path with less lens aberration to enhance the telecentricity correction and the effective scanning area. This is based on the international standard regulation ISO (the International Organization for Standardization) 11145:2018 requirements in optics and photonics, in which an important criterion is for the roundness of the focused beam spot to be greater than 87% to determine the effective working length of the proposed scanning system compared to the conventional scanning system. It is demonstrated by optical simulations and real optical experiments that the effective working length can be increased by 3.6 mm, corresponding to 8.1% of the effective scanning field, to achieve a laser material processing system with ISO standard. The damped least squares (DLS) algorithm in optical design software ZEMAX is used to optimize the deflected angle of the two galvanometers to obtain the optimal incident position of the f-theta lens.
Applying a Character-Level Model to a Short Arabic Dialect Sentence: A Saudi Dialect as a Case Study
Authors: Alqurashi Tahani
Published: December 2022

Arabic dialect identification (ADI) has recently drawn considerable interest among researchers in language recognition and natural language processing fields. This study investigated the use of a character-level model that is effectively unrestricted in its vocabulary, to identify fine-grained Arabic language dialects in the form of short written text. The Saudi dialects, particularly the four main Saudi dialects across the country, were considered in this study. The proposed ADI approach consists of five main phases, namely dialect data collection, data preprocessing and labelling, character-based feature extraction, deep learning character-based model/classical machine learning character-based models, and model evaluation performance. Several classical machine learning methods, including logistic regression, stochastic gradient descent, variations of the naive Bayes models, and support vector classification, were applied to the dataset. For the deep learning, the character convolutional neural network (CNN) model was adapted with a bidirectional long short-term memory approach. The collected data were tested under various classification tasks, including two-, three- and four-way ADI tasks. The results revealed that classical machine learning algorithms outperformed the CNN approach. Moreover, the use of the term frequency–inverse document frequency, combined with a character n-grams model ranging from unigrams to four-grams achieved the best performance among the tested parameters.
A Topology Map Generation Algorithm for Optimal Path Finding for Image-Based Maps
Authors: Kim Seon-Ho , Lee Kyung-Oh , Chae Yoon-Jae , Lee Ho-Won , Park Yoon-Yong
Published: December 2022

Algorithms that automatically search for routes have various applications, such as games, navigation, and robots, and are used to create optimal paths in the space of real and virtual worlds. This paper introduces an indoor navigation algorithm allowing rescuers to create a topology map of floor plans, given that the amount of data provided by conventional mapping constructs is limited. Traditional pathfinding algorithms include the A* algorithm, which has demonstrated excellent performance; however, its applicability is limited in the case of high-resolution images, as the number of nodes increases significantly. Here, we use the corner node algorithm (CNA) to improve pathfinding performance by preprocessing the data to create a topology map for the pathfinding algorithm. The algorithm can reduce the number of nodes required for the pathfinding process by generating topology maps in advance through two preprocessing processes: node creation and node connection. This effectively reduces the number of nodes to be processed, as well as the error rate when creating more accurate routes. Furthermore, a generated topology map can be reused by the algorithm unless its structure changes, which enhances efficiency. For the user, this means that the sought-after mapping information of the floor plan is quickly made available for navigation. With this algorithm, we created an augmented reality navigation solution to display virtual objects for rescuers, to demonstrate the enhanced performance of our approach.
Influence of Activation Parameters on the Mechanical and Microstructure Properties of an Alkali-Activated BOF Steel Slag
Authors: Nunes Vitor A. , Suraneni Prannoy , Bezerra Augusto C. S. , Thomas Carlos , Borges Paulo H. R.
Published: December 2022

Steel slag (SS) is a secondary material from steelmaking production with little commercial value. Its volumetric expansion and low reactivity limit the use of SS in Portland cement (PC)-based materials. This study investigated the potential use of basic oxygen furnace (BOF) slag as a single precursor in alkali-activated matrices (AAMs). Six AAM pastes were assessed by changing the silica modulus (0.75, 1.50 and 2.22) and the sodium concentration (4% or 6% Na2O—wt. SS). The early hydration was assessed using isothermal calorimetry (IC), followed by the assessment of the mechanical performance (compressive strength), apparent porosity, and structure and microstructure characterization (X-ray diffraction, thermogravimetric analysis and scanning electron microscopy). The results indicated that although the BOF slag may be considered a low-reactivity material, the alkaline environment effectively dissolved important crystalline phases to produce hydrates (reaction products). An optimized combination of activator sources was achieved with 4% Na2O and a silica modulus of 1.50–2.22, with a compressive strength up to 20 MPa, a significant amount of reaction products (C-S-H/C-A-S-H gels), and low initial and cumulative heat release. Those properties will help to promote SS recycling use in future engineering projects that do not require high-strength materials.
3DSG: A 3D LiDAR-Based Object Detection Method for Autonomous Mining Trucks Fusing Semantic and Geometric Features
Authors: Li Huazhi , Wang Zhangyu , Yu Guizhen , Gong Ziren , Zhou Bin , Chen Peng , Zhao Fei
Published: December 2022

Object detection is an essential task for autonomous vehicles to ensure safety. Due to the complexity of mining environments, it is difficult to detect objects accurately and robustly. To address these issues, this paper proposes a novel 3D LiDAR-based object detection method fusing semantic and geometric features for autonomous trucks in mining environments (3DSG). A road region extraction method is presented by establishing a semantic segmentation network with a region searching strategy to eliminate off-road point clouds. To deal with the complexity of unstructured road ground point-cloud segmentation, we propose a cascaded ground detection algorithm by performing semantic segmentation filtering and rectangular grid map filtering. A clustering method is proposed fusing adaptive distance thresholds of Euclidean clusters with semantic segmentation categories to solve the problem of the over- and undersegmentation of objects caused by the sparsity of point clouds. The performance of the proposed method is examined utilizing a real mining dataset named TG-Mine-3D. Compared with state-of-the-art methods, our method achieved higher precision of 66.39%. Moreover, for the truck and pedestrian categories, the performance of our method was significantly improved by 2.66% and 5.80%, respectively. The proposed method running at 51.35 ms achieved real-time performance.
Collaborative Detection of Black Hole and Gray Hole Attacks for Secure Data Communication in VANETs
Authors: Younas Shamim , Rehman Faisal , Maqsood Tahir , Mustafa Saad , Akhunzada Adnan , Gani Abdullah
Published: December 2022

Vehicle ad hoc networks (VANETs) are vital towards the success and comfort of self-driving as well as semi-automobile vehicles. Such vehicles rely heavily on data management and the exchange of Cooperative Awareness Messages (CAMs) for external communication with the environment. VANETs are vulnerable to a variety of attacks, including Black Hole, Gray Hole, wormhole, and rush attacks. These attacks are aimed at disrupting traffic between cars and on the roadside. The discovery of Black Hole attack has become an increasingly critical problem due to widespread adoption of autonomous and connected vehicles (ACVs). Due to the critical nature of ACVs, delay or failure of even a single packet can have disastrous effects, leading to accidents. In this work, we present a neural network-based technique for detection and prevention of rushed Black and Gray Hole attacks in vehicular networks. The work also studies novel systematic reactions protecting the vehicle against dangerous behavior. Experimental results show a superior detection rate of the proposed system in comparison with state-of-the-art techniques.
Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors
Authors: Durczak Karol , Rybacki Piotr , Sujak Agnieszka
Published: December 2022

Knowledge of the use-to-failure periods of process equipment, including agricultural vehicles, is essential for the determination of their durability and reliability. Obtaining any empirical data on this issue is difficult and sometimes impossible. Experimental studies are costly and time-consuming. Manufacturers are usually reluctant to share such data, claiming that the information is classified for the sake of their companies. The purpose of this study was to compare empirical data with data generated using adequate statistical tools. The newly generated and very similar in value pseudorandom numbers were obtained by simulations using the Monte Carlo, Latin hypercube sampling and Iman-Conover methods. Reliability function graphs obtained from the generated time-series (use-to-failure periods) with matching Weibull distribution had very similar shape and scale parameters. They were are also comparable to parameters from experimental data extracted from a Polish Zetor agricultural tractor service station. The validation of the applied methods was limited as it was carried out only on the basis of the available data. Analysis of line graphs of cumulative deviations of the values of use-to-failure periods (times-to-fail) generated against empirical times-to-fail indicated that the best method in the studied case was the Monte Carlo method.
Habituation and Behavioural Response of Confinement-Induced Anxiety Conditions in a Zebrafish Model
Authors: Wilson Alphonse Carlton Ranjith , Rajaretinam Rajesh Kannan
Published: December 2022

The zebrafish model is an emerging model for the study of the complex behavioural patterns noted in depression and neurological disorders. Confinement and memory loss are linked with cognition and mental health impairment, where confinement paradigms are assessed using other behavioural responses based on novel tanks or T tanks. Since zebrafish are exploratory animals, the impact during confinement cannot be evaluated using a novel tank or T tank. The present study investigates the response of the zebrafish to acute confinement and assesses its memory-based learning behaviour through parameters such as movement, swimming speed, and time spent inside the confined space. The movement and swimming speed of the fishes in confinement showed no significant difference. When confined inside a space, the fish showed their anxiety with erratic movements or bouts of freezing, which declined by 83%, during the six days of confinement and the escape time from the confinement space also decreased by 58%. The impact of anxiety, resulting in clockwise and counter-clockwise movement, also reduced after three days. Our results summarise that the decrease in anxiety can help the fish in habituating itself to a forced condition. This experiment on zebrafish behavioural biology is used to assess the cognitive behaviour against confinement, and it emphasizes the learning of behavioural adaptions under both crowded and solitary conditions.
Spin Optics for Gravitational Waves
Authors: Dahal Pravin Kumar
Published: December 2022

We present the geometric optics expansion for circularly polarized gravitational waves on a curved spacetime background, to subleading order. We call spin optics to the subleading order geometric optics expansion, which involves modifying the standard eikonal function by including a specially chosen helicity-dependent correction. We show that the techniques developed for the propagation of electromagnetic waves can also be applied to gravitational waves in the limit of spin optics. However, one needs to account for the difference in the photon and graviton helicity, which we do here.
The Geometry and Charge of the Streamer Bursts Generated by Lightning Rods under the Influence of High Electric Fields
Authors: Cooray Vernon , Jayasinghe Hasupama , Rubinstein Marcos , Rachidi Farhad
Published: December 2022

The streamer bursts generated during the initiation and propagation of leaders play an important role in the creation and maintenance of hot discharge channels in air. The most important parameters related to streamer bursts in this respect are the length of the streamer bursts, their lateral extent and the charge associated with them. The lateral extent of the streamer bursts may play a significant role in deciding the path and the tortuosity of the discharge channels of laboratory discharges and lightning. The charges associated with the streamer bursts are needed in understanding the physical processes associated with the streamer-to-leader transition. In this paper, the length, the lateral extension and the charge of the streamer regions generated by grounded conductors when exposed to external electric fields are estimated. This estimation is based on two assumptions: (i) once a streamer is incepted, the streamer head follows the direction of maximum background electric field at the location of the streamer head and (ii) the streamer continues to extend along this direction until the potential drop along the streamer channel matches the potential drop caused by the background electric field between the initial and end points of the streamer channel. The same technique could be used to estimate the streamer bursts generated in laboratory discharges and lightning stepped leaders. It is shown that in estimating the geometry of the streamer region, it is necessary to include the spread of streamers caused by branching. Moreover, the charge associated with the streamer region increases as the frequency of branching increases. The results obtained confirm that the charge in the streamer region can significantly change the potential ahead of the streamer region from the background potential and this has to be taken into account in any study that simulates the initiation and propagation of lightning leaders. Since the streamer bursts of leaders control the direction and speed of the leaders, the technique we have used here could be implemented in lightning leader progression models.
Inexact Restoration Methods for Semivectorial Bilevel Programming Problem on Riemannian Manifolds
Authors: Liao Jiagen , Wan Zhongping
Published: December 2022

For a better understanding of the bilevel programming on Riemannian manifolds, a semivectorial bilevel programming scheme is proposed in this paper. The semivectorial bilevel programming is firstly transformed into a single-level programming problem by using the Karush–Kuhn–Tucker (KKT) conditions of the lower-level problem, which is convex and satisfies the Slater constraint qualification. Then, the single-level programming is divided into two stages: restoration and minimization, based on which an Inexact Restoration algorithm is developed. Under certain conditions, the stability and convergence of the algorithm are analyzed.
Automation of Measurements for Personalized Medical Appliances by Means of CAD Software—Application in Robin Sequence Orthodontic Appliances
Authors: Aretxabaleta Maite , Roehler Ariadne , Poets Christian F. , Xepapadeas Alexander B. , Koos Bernd , Weise Christina
Published: December 2022

Measuring the dimensions of personalized devices can provide relevant information for the production of future such devices used in various medical specialties. Difficulties with standardizing such measurement and obtaining high accuracy, alongside cost-intensive measuring methodologies, has dampened interest in this practice. This study presents a methodology for automatized measurements of personalized medical appliances of variable shape, in this case an orthodontic appliance known as Tübingen Palatal Plate (TPP). Parameters such as length, width and angle could help to standardize and improve its future use. A semi-automatic and custom-made program, based on Rhinoceros 7 and Grasshopper, was developed to measure the device (via an extraoral scanner digital file). The program has a user interface that allows the import of the desired part, where the user is able to select the necessary landmarks. From there, the program is able to process the digital file, calculate the necessary dimensions automatically and directly export all measurements into a document for further processing. In this way, a solution for reducing the time for measuring multiple dimensions and parts while reducing human error can be achieved.
Mycorrhizal Colonization Modulates the Essential Oil Profile and Enzymatic and Non-Enzymatic Antioxidants to Mitigate the Adverse Effects of Water Deficit in Salvia subg. Perovskia
Authors: Afshari Mahvash , Rahimmalek Mehdi , Sabzalian Mohammad , Szumny Antoni , Matkowski Adam , Jezierska-Domaradzka Anna
Published: December 2022

Among traditional Iranian herbs, Perovskia species (a subgenus of Salvia), while being valued ornamentals, are also studied for numerous potential pharmacological and therapeutic aspects. The current study was conducted to assess the effectiveness of two species of arbuscular mycorrhizal fungi (AMF), Funneliformis mosseae and Rhizophagus intraradices, separately and in combination, in terms of the essential oil content and compositions along with the enzymatic and non-enzymatic antioxidants in Salvia abrotanoides and S. yangii in response to three levels of irrigation, including 100% FC as well-watered, 75% FC (moderate irrigation deficit), and 50% FC (severe irrigation deficit). In both species, essential oil content, enzyme antioxidant activities, total phenolics, and flavonoids were increased significantly with the severity of stress; this increase was more pronounced in mycorrhizal inoculated herbs. Furthermore, leaf phosphorus concentration, relative water content, chlorophylls a and b, and total carotenoids decreased in parallel with reducing soil moisture; albeit, AMF inoculation improved the stress symptoms under increasing severity of water restriction compared with their control conditions. In addition, the percentage of root colonization was positively correlated with the relative water content (RWC) and leaf phosphorus concentration. Taking into account the essential oil groups, AMF colonization elevated some essential oil components, such as oxygenated monoterpenes, 1,8-cineol, camphor, and borneol, whereas the main sesquiterpenes, including E-β-caryophyllene and α-humulene, remarkably decreased. Taken together, these findings highlighted the role of symbiosis with AMFs in increasing the tolerance of water deficit stress in S. abrotanoides and S. yangii and improving their essential oil composition.
Nitrogen and Carbon Mineralization from Green and Senesced Leaf Litter Differ between Cycad and Angiosperm Trees
Authors: Paulino Charles A. , Marler Thomas E.
Published: December 2022

Plant leaf litter decomposition is directly influenced by the identity of the source plants and the leaf age. Defoliation of forests by tropical cyclones (TC) transfers copious amounts of high-quality green leaf litter to soils. We used a soil amendment approach with the incubated buried bag method to compare carbon (C) and nitrogen (N) mineralization dynamics of green and senesced leaf litter from cycad Cycas micronesica and angiosperm Morinda citrifolia trees on the island of Guam. Soil priming increased the decomposition of pre-existing organic C, and were greater for green leaf litter additions than senesced leaf litter additions. Available N content increased by day 14 and remained elevated for the entire 117-d incubation for soils amended with green M. citrifolia litter. In contrast, available N content increased above those in control soils by day 90 and above those in soils amended with senesced litter by day 117 for green C. micronesica litter. The net N mineralization rate was higher than control soils by 120% for the senesced litter treatments and 420% for the green litter treatments. The results reveal a complex but predictable interplay between TC defoliation and litter quality as defined by tree identity. We have illuminated one means by which increased frequency of intense TCs due to climate change may alter the global C and N cycles.
Term and Preterm Birth Initiation Is Associated with the Macrophages Shifting to M1 Polarization in Gestational Tissues in Mice
Authors: Shan Yali , Shen Shiping , Long Jing , Tang Zhengshan , Wu Cichun , Ni Xin
Published: December 2022

Inflammation in gestational tissues plays critical role in parturition initiation. We sought to investigate the leukocyte infiltration and cytokine profile in uterine tissues to understand the inflammation during term and preterm labor in the mouse model. Preterm birth was induced by the administration of lipopolysaccharide (LPS) or RU38486. The populations of leukocytes were determined by flow cytometry. Macrophages were the largest population in the myometrium and decidua in late gestation. The macrophage population was significantly changed in the myometrium and decidua from late pregnancy to term labor and significantly changed at LPS- and RU386-induced preterm labor. Neutrophils, T cells, and NKT cells were increased in LPS- and RU38486-induced preterm labor. The above changes were accompanied by the increased expression of cytokines and chemokines. In late gestation, M2 macrophages were the predominant phenotype in gestational tissues. M1 macrophages significantly increased in these tissues at term and preterm labor. IL-6 and NLRP3 expression was significantly increased in macrophages at labor, supporting that macrophages exhibit proinflammatory phenotypes. NLRP3 inflammasome inhibitor MCC950 mainly suppressed macrophage infiltration in the myometrium at term labor and preterm labor. Our data suggest that the M1 polarization of macrophages contributes to inflammation linked to term and preterm labor initiation in gestational tissues.
A Structure-Based Mechanism for the Denaturing Action of Urea, Guanidinium Ion and Thiocyanate Ion
Authors: Paladino Antonella , Balasco Nicole , Vitagliano Luigi , Graziano Giuseppe
Published: December 2022

An exhaustive analysis of all the protein structures deposited in the Protein Data Bank, here performed, has allowed the identification of hundredths of protein-bound urea molecules and the structural characterization of such binding sites. It emerged that, even though urea molecules are largely involved in hydrogen bonds with both backbone and side chains, they are also able to make van der Waals contacts with nonpolar moieties. As similar findings have also been previously reported for guanidinium and thiocyanate, this observation suggests that promiscuity is a general property of protein denaturants. Present data provide strong support for a mechanism based on the protein-denaturant direct interactions with a denaturant binding model to equal and independent sites. In this general framework, our investigations also highlight some interesting insights into the different denaturing power of urea compared to guanidinium/thiocyanate.
Considerations for the Use of Photobiomodulation in the Treatment of Retinal Diseases
Authors: Zhang Chun-Xia , Lou Yan , Chi Jing , Bao Xiao-Li , Fan Bin , Li Guang-Yu
Published: December 2022

Photobiomodulation (PBM) refers to the beneficial effect produced from low-energy light irradiation on target cells or tissues. Increasing evidence in the literature suggests that PBM plays a positive role in the treatment of retinal diseases. However, there is great variation in the light sources and illumination parameters used in different studies, resulting in significantly different conclusions regarding PBM’s therapeutic effects. In addition, the mechanism by which PBM improves retinal function has not been fully elucidated. In this study, we conducted a narrative review of the published literature on PBM for treating retinal diseases and summarized the key illumination parameters used in PBM. Furthermore, we explored the potential molecular mechanisms of PBM at the retinal cellular level with the goal of providing evidence for the improved utilization of PBM in the treatment of retinal diseases.
Establishment of a Cell Line Stably Expressing the Growth Hormone Secretagogue Receptor to Identify Crocin as a Ghrelin Agonist
Authors: Wang Chia-Hao , Tseng Ching-Yu , Hsu Wei-Li , Tzen Jason T. C.
Published: December 2022

The growth hormone secretagogue receptor-1a (GHSR1a) is the endogenous receptor for ghrelin. Activation of GHSR1a participates in many physiological processes including energy homeostasis and eating behavior. Due to its transitory half-life, the efficacy of ghrelin treatment in patients is restricted; hence the development of new adjuvant therapy is an urgent need. This study aimed to establish a cell line stably expressing GHSR1a, which could be employed to screen potential ghrelin agonists from natural compounds. First, by means of lentiviral transduction, the genome of a human HEK293T cell was modified, and a cell platform stably overexpressing GHSR1a was successfully established. In this platform, GHSR1a was expressed as a fusion protein tagged with mCherry, which allowed the monitoring of the dynamic cellular distribution of GHSR1a by fluorescent microscopy. Subsequently, the authenticity of the GHSR1a mediated signaling was further characterized by using ghrelin and teaghrelin, two molecules known to stimulate GHSR1a. The results indicated that both ghrelin and teaghrelin readily activated GHSR1a mediated signaling pathways, presumably via increasing phosphorylation levels of ERK. The specific GHSR1a signaling was further validated by using SP-analog, an antagonist of GHSR1a as well as using a cell model with the knockdown expression of GHSR1a. Molecular modeling predicted that crocin might be a potential ghrelin agonist, and this prediction was further confirmed by the established platform.
Advances in Gene Therapy Techniques to Treat LRRK2 Gene Mutation
Authors: Chung Sun-Ku , Lee Seo-Young
Published: December 2022

Leucine-rich repeat kinase 2 (LRRK2) gene mutation is an autosomal dominant mutation associated with Parkinson’s disease (PD). Among LRRK2 gene mutations, the LRRK2 G2019S mutation is frequently involved in PD onset. Currently, diverse gene correction tools such as zinc finger nucleases (ZFNs), helper-dependent adenoviral vector (HDAdV), the bacterial artificial chromosome-based homologous recombination (BAC-based HR) system, and CRISPR/Cas9-homology-directed repair (HDR) or adenine base editor (ABE) are used in genome editing. Gene correction of the LRRK2 G2019S mutation has been applied whenever new gene therapy tools emerge, being mainly applied to induced pluripotent stem cells (LRRK2 G2019S-mutant iPSCs). Here, we comprehensively introduce the principles and methods of each programmable nuclease such as ZFN, CRISPR/Cas9-HDR or ABE applied to LRRK2 G2019S, as well as those of HDAdV or BAC-based HR systems used as nonprogrammable nuclease systems.
The Role of Membrane Affinity and Binding Modes in Alpha-Synuclein Regulation of Vesicle Release and Trafficking
Authors: Das Tapojyoti , Ramezani Meraj , Snead David , Follmer Cristian , Chung Peter , Lee Ka Yee , Holowka David A. , Baird Barbara A. , Eliezer David
Published: December 2022

Alpha-synuclein is a presynaptic protein linked to Parkinson’s disease with a poorly characterized physiological role in regulating the synaptic vesicle cycle. Using RBL-2H3 cells as a model system, we earlier reported that wild-type alpha-synuclein can act as both an inhibitor and a potentiator of stimulated exocytosis in a concentration-dependent manner. The inhibitory function is constitutive and depends on membrane binding by the helix-2 region of the lipid-binding domain, while potentiation becomes apparent only at high concentrations. Using structural and functional characterization of conformationally selective mutants via a combination of spectroscopic and cellular assays, we show here that binding affinity for isolated vesicles similar in size to synaptic vesicles is a primary determinant of alpha-synuclein-mediated potentiation of vesicle release. Inhibition of release is sensitive to changes in the region linking the helix-1 and helix-2 regions of the N-terminal lipid-binding domain and may require some degree of coupling between these regions. Potentiation of release likely occurs as a result of alpha-synuclein interactions with undocked vesicles isolated away from the active zone in internal pools. Consistent with this, we observe that alpha-synuclein can disperse vesicles from in vitro clusters organized by condensates of the presynaptic protein synapsin-1.
Prescriptions of Antipsychotics in Younger and Older Geriatric Patients with Polypharmacy, Their Safety, and the Impact of a Pharmaceutical-Medical Dialogue on Antipsychotic Use
Authors: Gebauer Eva-Maria , Lukas Albert
Published: December 2022

Geriatric patients are a particularly vulnerable and, at the same time, very heterogeneous group due to their multimorbidity and polypharmacy. Antipsychotics are often prescribed in their complex drug regimens, whereby the prescription of antipsychotics is not without controversy. To date, questions remain as to whether there are differences in the prescribing pattern, safety, and impact of a consultant pharmacist regarding antipsychotic use between younger and older geriatric patients in the heterogenic geriatric group. This monocentric study of 744 patients was based on the analysis of routine data collected from January 2018 to June 2020 in a geriatric department during a weekly pharmaceutical and medical consultation. The frequency of the prescription of antipsychotics in our study was 30.7%. Regarding antipsychotic safety and/or adverse drug reaction (ADR) antipsychotics, only a difference in terms of overuse in younger geriatric patients was found. The binary logistic regression analyses of geriatric patients with antipsychotics revealed that ADRs and drug–drug interactions (DDIs) were particularly related to the number of medications prescribed. The higher the number of prescribed drugs, the higher the risk of ADRs and DDIs. In 26.7% of geriatric patients on antipsychotics, the pharmacist made recommendations that were almost exclusively implemented by the physician, with no difference made between the two age groups. The prescriptions of antipsychotics in geriatric patients with polypharmacy, their safety, and the impact of a pharmaceutical-medical dialogue on the use of antipsychotics seem comparable between younger and older geriatric patients in the geriatric setting. Antipsychotics should always be critically considered and used cautiously, whereby a regular pharmaceutical-medical dialogue is recommended in geriatric settings.
Methylenetetrahydrofolate Reductase C677T Gene Variant in Relation to Body Mass Index and Folate Concentration in a Polish Population
Authors: Wrzosek Małgorzata , Ślusarczyk Klaudia
Published: December 2022

Background: Methylenetetrahydrofolate reductase (MTHFR) is an enzyme responsible for producing an active form of folate. The MTHFR T677T genotype may have adverse health effects associated with weight gain and a reduction in folate availability. Aim: In this study, we examined the influence of the MTHFR C677T variant on BMI and determined its role as a risk factor for obesity. We also assessed the relationships between the MTHFR C677T genotype and folate and vitamin B12 concentrations in subjects before and after radical weight loss. Methods: The study group consisted of 1712 Caucasian adults of Polish nationality with a wide range of body mass indexes (BMIs). DNA was extracted from the blood, and the C677T variant was tested with RFLP-PCR and real-time-PCR. Results: There was no significant influence found for the MTHFR 677 TT genotype on BMI or the obesity risk in codominant, dominant or recessive inheritance models. Individuals with obesity and the TT genotype had significantly lower folate concentrations. After radical weight reduction, the impact of the risk genotype, as well as homeostasis between folate and vitamin B12 in TT homozygotes, seems to be attenuated. Conclusion: Although the MTHFR 677TT genotype is not directly related to a higher BMI in Polish adults, it has a detrimental effect on folate concentrations in individuals with high BMI values.
Changes in and Recognition of Electrochemical Fingerprints of Acer spp. in Different Seasons
Authors: Zhang Pengchong , Li Xiaolong , Zheng Yuhong , Fu Li
Published: December 2022

Electroanalytical chemistry is a metrological analysis technique that provides information feedback by measuring the voltammetric signal that changes when a molecule is involved in an electrochemical reaction. There is variability in the type and content of electrochemically active substances among different plants, and the signal differences presented by such differences in electrochemical reactions can be used for plant identification and physiological monitoring. This work used electroanalytical chemistry to monitor the growth of three Acer spp. This work explores the feasibility of the electrochemical analysis technique for the physiological monitoring of highly differentiated plants within the genus and further validates the technique. Changes in the electrochemical fingerprints of A. cinnamomifolium, A. sinopurpurascens and A. palmatum ‘Matsumurae’ were recorded during the one-year developmental cycle. The results show that the differences in the electrochemical fingerprint profiles of Acer spp. can be used to distinguish different species and identify the growth status in each season. This work also concludes with an identification flowchart based on electrochemical fingerprinting.
GLAD Based Advanced Nanostructures for Diversified Biosensing Applications: Recent Progress
Authors: Yadav Sarjana , Senapati Sneha , Kumar Samir , Gahlaut Shashank K. , Singh Jitendra P.
Published: December 2022

Glancing angle deposition (GLAD) is a technique for the fabrication of sculpted micro- and nanostructures under the conditions of oblique vapor flux incident and limited adatom diffusion. GLAD-based nanostructures are emerging platforms with broad sensing applications due to their high sensitivity, enhanced optical and catalytic properties, periodicity, and controlled morphology. GLAD-fabricated nanochips and substrates for chemical and biosensing applications are replacing conventionally used nanomaterials due to their broad scope, ease of fabrication, controlled growth parameters, and hence, sensing abilities. This review focuses on recent advances in the diverse nanostructures fabricated via GLAD and their applications in the biomedical field. The effects of morphology and deposition conditions on GLAD structures, their biosensing capability, and the use of these nanostructures for various biosensing applications such as surface plasmon resonance (SPR), fluorescence, surface-enhanced Raman spectroscopy (SERS), and colorimetric- and wettability-based bio-detection will be discussed in detail. GLAD has also found diverse applications in the case of molecular imaging techniques such as fluorescence, super-resolution, and photoacoustic imaging. In addition, some in vivo applications, such as drug delivery, have been discussed. Furthermore, we will also provide an overview of the status of GLAD technology as well as future challenges associated with GLAD-based nanostructures in the mentioned areas.
Role of Estradiol Hormone in Human Life and Electrochemical Aptasensing of 17β-Estradiol: A Review
Authors: Waifalkar P. P. , Noh Daegwon , Derashri Poorva , Barage Sagar , Oh Eunsoon
Published: December 2022

Estradiol is known as one of the most potent estrogenic endocrine-disrupting chemicals (EDCs) that may cause various health implications on human growth, metabolism regulation, the reproduction system, and possibly cancers. The detection of these EDCs in our surroundings, such as in foods and beverages, is important to prevent such harmful effects on humans. Aptamers are a promising class of bio-receptors for estradiol detection due to their chemical stability and high affinity. With the development of aptamer technology, electrochemical aptasensing became an important tool for estradiol detection. This review provides detailed information on various technological interventions in electrochemical estradiol detection in solutions and categorized the aptasensing mechanisms, aptamer immobilization strategies, and electrode materials. Moreover, we also discussed the role of estradiol in human physiology and signaling mechanisms. The level of estradiol in circulation is associated with normal and diseased conditions. The aptamer-based electrochemical sensing techniques are powerful and sensitive for estradiol detection.
Design and Engineering of a Palm-Sized Optical Immunosensing Device for the Detection of a Kidney Dysfunction Biomarker
Authors: Divya  , Mahapatra Supratim , Chandra Pranjal
Published: December 2022

Creatinine is one of the most common and specific biomarkers for renal diseases, usually found in the serum and urine of humans. Its level is extremely important and critical to know, not only in the case of renal diseases, but also for various other pathological conditions. Hence, detecting creatinine in clinically relevant ranges in a simplistic and personalized manner is interesting and important. In this direction, an optical sensing device has been developed for the simple, point-of-care detection of creatinine. The developed biosensor was able to detect creatinine quantitatively based on optical signals measured through a change in color. The sensor has been integrated with a smartphone to develop a palm-sized device for creatinine analysis in personalized settings. The sensor has been developed following facile chemical modification steps to anchor the creatinine-selective antibody to generate a sensing probe. The fabricated sensor has been thoroughly characterized by FTIR, AFM, and controlled optical analyses. The quantitative analysis is mediated through the reaction between picric acid and creatinine which was detected by the antibody-functionalized sensor probe. The differences in color intensity and creatinine concentrations show an excellent dose-dependent correlation in two different dynamic ranges from 5 to 20 μM and 35 to 400 μM, with a detection limit of 15.37 (±0.79) nM. Several interfering molecules, such as albumin, glucose, ascorbic acid, citric acid, glycine, uric acid, Na+, K+, and Cl−, were tested using the biosensor, in which no cross-reactivity was observed. The utility of the developed system to quantify creatinine in spiked serum samples was validated and the obtained percentage recoveries were found within the range of 89.71–97.30%. The fabricated biosensor was found to be highly reproducible and stable, and it retains its original signal for up to 28 days.
Label-Free Bound-States-in-the-Continuum Biosensors
Authors: Luo Man , Zhou Yi , Zhao Xuyang , Li Yuxiang , Guo Zhihe , Yang Xi , Zhang Meng , Wang You , Wu Xiang
Published: December 2022

Bound states in the continuum (BICs) have attracted considerable attentions for biological and chemical sensing due to their infinite quality (Q)-factors in theory. Such high-Q devices with enhanced light-matter interaction ability are very sensitive to the local refractive index changes, opening a new horizon for advanced biosensing. In this review, we focus on the latest developments of label-free optical biosensors governed by BICs. These BICs biosensors are summarized from the perspective of constituent materials (i.e., dielectric, metal, and hybrid) and structures (i.e., grating, metasurfaces, and photonic crystals). Finally, the current challenges are discussed and an outlook is also presented for BICs inspired biosensors.
Recent Development in Plasmonic Nanobiosensors for Viral DNA/RNA Biomarkers
Authors: Park Dong Hyeok , Choi Min Yu , Choi Jin-Ha
Published: December 2022

Recently, due to the coronavirus pandemic, the need for early diagnosis of infectious diseases, including viruses, is emerging. Though early diagnosis is essential to prevent infection and progression to severe illness, there are few technologies that accurately measure low concentrations of biomarkers. Plasmonic nanomaterials are attracting materials that can effectively amplify various signals, including fluorescence, Raman, and other optical and electromagnetic output. In this review, we introduce recently developed plasmonic nanobiosensors for measuring viral DNA/RNA as potential biomarkers of viral diseases. In addition, we discuss the future perspective of plasmonic nanobiosensors for DNA/RNA detection. This review is expected to help the early diagnosis and pathological interpretation of viruses and other diseases.
Adaptive Triboelectric Nanogenerators for Long-Term Self-Treatment: A Review
Authors: Zhao Zequan , Lu Yin , Mi Yajun , Meng Jiajing , Wang Xueqing , Cao Xia , Wang Ning
Published: December 2022

Triboelectric nanogenerators (TENGs) were initially invented as an innovative energy−harvesting technology for scavenging mechanical energy from our bodies or the ambient environment. Through adaptive customization design, TENGs have also become a promising player in the self-powered wearable medical market for improving physical fitness and sustaining a healthy lifestyle. In addition to simultaneously harvesting our body’s mechanical energy and actively detecting our physiological parameters and metabolic status, TENGs can also provide personalized medical treatment solutions in a self-powered modality. This review aims to cover the recent advances in TENG-based electronics in clinical applications, beginning from the basic working principles of TENGs and their general operation modes, continuing to the harvesting of bioenergy from the human body, and arriving at their adaptive design toward applications in chronic disease diagnosis and long-term clinical treatment. Considering the highly personalized usage scenarios, special attention is paid to customized modules that are based on TENGs and support complex medical treatments, where sustainability, biodegradability, compliance, and bio-friendliness may be critical for the operation of clinical systems. While this review provides a comprehensive understanding of TENG-based clinical devices that aims to reach a high level of technological readiness, the challenges and shortcomings of TENG-based clinical devices are also highlighted, with the expectation of providing a useful reference for the further development of such customized healthcare systems and the transfer of their technical capabilities into real-life patient care.
Gold Nanoclusters Dispersed on Gold Dendrite-Based Carbon Fibre Microelectrodes for the Sensitive Detection of Nitric Oxide in Human Serum
Authors: Arivazhagan Mani , Kannan Palanisamy , Maduraiveeran Govindhan
Published: December 2022

Herein, gold nanoclusters (Au NC) dispersed on gold dendrite (Au DS)-based flexible carbon fibre (AuNC@AuDS|CF) microelectrodes are developed using a one-step electrochemical approach. The as-fabricated AuNC@AuDS|CF microelectrodes work as the prospective electrode materials for the sensitive detection of nitric oxide (NO) in a 0.1 M phosphate buffer (PB) solution. Carbon microfibre acts as an efficient matrix for the direct growth of AuNC@AuDS without any binder/extra reductant. The AuNC@AuDS|CF microelectrodes exhibit outstanding electrocatalytic activity towards NO oxidation, which is ascribed to their large electrochemical active surface area (ECSA), high electrical conductivity, and high dispersion of Au nanoclusters. As a result, the AuNC@AuDS|CF microelectrodes attain a rapid response time (3 s), a low limit of detection (LOD) (0.11 nM), high sensitivity (66.32 µA µM cm−2), a wide linear range (2 nM–7.7 µM), long-term stability, good reproducibility, and a strong anti-interference capability. Moreover, the present microsensor successfully tested for the discriminating detection of NO in real human serum samples, revealing its potential practicability.
Reading: From the Simple to the Complex
Authors: Sigmundsson Hermundur , Thórsdóttir Helga S. , Njálsdóttir Herdís R. , Hjaltalín Svava Th.
Published: December 2022

The aim of this article was to present an important perspective on reading skill development. The perspective ‘READ’ builds on the phonics approach which has been found to be most important in relation to reading achievement i.e., to teach children to break the reading code. In addition, READ builds on theories within learning and skill development. The Ericsson concept of ‘deliberate practice’ refer to baseline measurements that provide a basis for follow-up and deliberate practice. The concept of ‘flow’ is also of great importance where challenges are always in relation to the skills. It means that each child will be able to experience ‘flow’ where mastery is the key word, feeling I CAN! When mastery is experienced, the dopamine hormone gives the feeling of reward. Stimuli, experience, and repetition is also a key word in the ‘training hour’ where children get the possibility to strengthen the neural network that is used for specific skills which are trained. In this respect, the letter-sound knowledge is trained until the child has broken the reading code. The results from the first year in the school in Vestmannaeyjar in Iceland indicates that all the children were able to break the reading code or read simple words. In addition, 96% of the children were able to read sentences, and 88% where able to read text. These promising results are discussed in relation to Ericsson’s and Csikszentmihalyi’s important theories.