bluuebunny/crossref_metadata_2025 huggingface dataset:
Intelligent Identification of Trend Components in Singular Spectrum Analysis
Authors: Golyandina Nina , Dudnik Pavel , Shlemov Alex
Published: July 2023

Singular spectrum analysis (SSA) is a non-parametric adaptive technique used for time series analysis. It allows solving various problems related to time series without the need to define a model. In this study, we focus on the problem of trend extraction. To extract trends using SSA, a grouping of elementary components is required. However, automating this process is challenging due to the nonparametric nature of SSA. Although there are some known approaches to automated grouping in SSA, they do not work well when the signal components are mixed. In this paper, a novel approach that combines automated identification of trend components with separability improvement is proposed. We also consider a new method called EOSSA for separability improvement, along with other known methods. The automated modifications are numerically compared and applied to real-life time series. The proposed approach demonstrated its advantage in extracting trends when dealing with mixed signal components. The separability-improving method EOSSA proved to be the most accurate when the signal rank is properly detected or slightly exceeded. The automated SSA was very successfully applied to US Unemployment data to separate an annual trend from seasonal effects. The proposed approach has shown its capability to automatically extract trends without the need to determine their parametric form.
Hierarchical Reinforcement Learning for Crude Oil Supply Chain Scheduling
Authors: Ma Nan , Wang Ziyi , Ba Zeyu , Li Xinran , Yang Ning , Yang Xinyi , Zhang Haifeng
Published: July 2023

Crude oil resource scheduling is one of the critical issues upstream in the crude oil industry chain. It aims to reduce transportation and inventory costs and avoid alerts of inventory limit violations by formulating reasonable crude oil transportation and inventory strategies. Two main difficulties coexist in this problem: the large problem scale and uncertain supply and demand. Traditional operations research (OR) methods, which rely on forecasting supply and demand, face significant challenges when applied to the complicated and uncertain short-term operational process of the crude oil supply chain. To address these challenges, this paper presents a novel hierarchical optimization framework and proposes a well-designed hierarchical reinforcement learning (HRL) algorithm. Specifically, reinforcement learning (RL), as an upper-level agent, is used to select the operational operators combined by various sub-goals and solving orders, while the lower-level agent finds a viable solution and provides penalty feedback to the upper-level agent based on the chosen operator. Additionally, we deploy a simulator based on real-world data and execute comprehensive experiments. Regarding the alert number, maximum alert penalty, and overall transportation cost, our HRL method outperforms existing OR and two RL algorithms in the majority of time steps.
Monolithic PneuNets Soft Actuators for Robotic Rehabilitation: Methodologies for Design, Production and Characterization
Authors: Tiboni Monica , Loda Davide
Published: July 2023

Soft-robotics for biomedical applications, such as rehabilitation robots, is a field of intense research activity. Different actuation solutions have been proposed in the last decades, involving study and development of soft actuators of different types and materials. The purpose of the paper is to present procedures for an optimized design, and for easy and low cost production and characterization of monolithic PneuNets soft-actuators. An innovative design approach has been developed. The parameterization of the geometry, combined with FEM simulations is the basis for an optimized design of the actuator, as a function of the obtained bending and of the generated forces. Simple and cheap characterization setup and procedures have been identified for the actuator characterization and for simulation results validation. An easy and low-cost fabrication method based on lost wax core obtained through a silicone based mold has been developed for a monolithic PneuNets soft-actuator. The proposed solution performs well in bending, without the need for a strain limiting layer. Experimental results validated simulations, confirming the feasibility of adopting an optimized simulation-based design approach.
Experimental Thermohydraulic Assessment of Novel Curved Ribs for Heat Exchanger Tubes: A Machine Learning Approach
Authors: Deshmukh Prashant , Lahane Subhash , Sumant Hari , Patange Abhishek D. , Gnanasekaran Sakthivel
Published: July 2023

Heat transfer enhancement using curved ribs of different cross sections, viz., square, rectangular, triangular, and circular, is a crucial study for designing heat-exchanging devices for various applications, and their thermohydraulic performance prediction using machine learning technique is a vital part of the modern world. An experimental study on using curved ribs suitable for heat transfer enhancement for the circular tube is presented for turbulent airflow with Reynolds numbers varying from 10,000 to 50,000. The machine learning methodology is used to predict the thermohydraulic performance assessment of curved ribs. The square cross-sectioned curved ribs produce the highest performance factor R3 of 1.5 to 2.65 to the equivalent Reynolds number Rec value of 20,000. It is observed that most of the curved rib configurations show a performance ratio R3 maximum and are suitable at a low Reynolds number value. At moderate and high Reynolds number values, the performance factor values decrease due to a rise in the pressure drop values for a few curved rib configurations. An artificial neural network (ANN) model predicts with an accuracy of 95% with the present study experimental values for the heat transfer performance indicators like average heat transfer enhancement Nua/Nus, average heat transfer enhancement fa/fs, and performance ratio R3, i.e., Nua/Nuc.
First Measurement of Ambient Air Quality on the Rural Lower Eastern Shore of Maryland
Authors: Bediako Bernice , Sauder Deborah G.
Published: July 2023

Concerns about atmospheric ammonia have been expressed recently by some on the Lower Eastern Shore (LES) of Maryland, which lies between the Chesapeake Bay and the Atlantic Ocean on the Delmarva peninsula. Agriculture, seafood and tourism are responsible for a significant fraction of the economic activity on the LES. The USDA 2017 census reported there were ~100 Concentrated Animal Feeding Operations (CAFOs) raising nearly 63 M chickens per year across Somerset and Worcester Counties. We report air quality data collected from sites near Princess Anne, Somerset County, and near Pocomoke City, Worcester County, to address air quality concerns by examining the influence of chicken farms on ammonia in ambient air on the LES. Within a two-mile radius of the Worcester County site, CAFO operations house ~1.6 million birds. The Princess Anne site is comparable to the Pocomoke City site in agricultural use and population demographics but has only a few chicken houses within two miles. The first 33 months of LES ammonia data are presented, and their significance is discussed relative to other ammonia studies. The 33-month average concentration of ammonia in Pocomoke was 10.3 ± 0.08 ppb, more than double that in Princess Anne, which was 4.7 ± 0.04 ppb.
Screening for Antimicrobial Resistance and Genes of Exotoxins in Pseudomonas aeruginosa Isolates from Infected Dogs and Cats in Poland
Authors: Płókarz Daria , Bierowiec Karolina , Rypuła Krzysztof
Published: July 2023

Pseudomonas aeruginosa has assumed an increasingly prominent role as the aetiological agent in serious hard-to-treat infections in animals and humans. In this study, 271 P. aeruginosa strains collected from dogs and cats were investigated. The aim of the research was to screen these P. aeruginosa strains for antibiotic resistance and the presence of selected virulence factor genes. Antibiotic resistance was determined using the Kirby–Bauer method, while virulence genes were detected by polymerase chain reaction (PCR). The most frequently detected resistance was to fluoroquinolones, ranging in prevalence from 17.3% for ciprofloxacin up to 83% for enrofloxacin. The resistance to carbapenems was 14% and 4.8% for imipenem and meropenem, respectively. Almost all P. aeruginosa strains harboured the exoT (97.8%) and lasB (93.4%) genes, while the lowest prevalence was found for exoU (17.3%) and plcH (17.3%). P. aeruginosa strains isolated from dogs that harboured the toxA gene were more frequently resistant to ceftazidime (p = 0.012), while the presence of the exoU gene was found to be connected with resistance to marbofloxacin (p = 0.025) and amikacin (p = 0.056). In strains originating from cats, only the connection between the presence of the exoU gene and resistance to enrofloxacin (p = 0.054) was observed. The confirmation of associations between virulence-factor-encoding genes and antibiotic resistance indicates that problems of antibiotic resistance may not only cause complications at the level of antibiotic dosage but also lead to changes in the virulence of the bacteria; thus, further studies in this area are required.
Synthesis of Novel Quinazolinone Analogues for Quorum Sensing Inhibition
Authors: Shandil Sahil , Yu Tsz Tin , Sabir Shekh , Black David StC. , Kumar Naresh
Published: July 2023

As bacteria continue to develop resistance mechanisms against antimicrobials, an alternative method to tackle this global concern must be developed. As the pqs system is the most well-known and responsible for biofilm and pyocyanin production, quinazolinone inhibitors of the pqs system in P. aeruginosa were developed. Molecular docking following a rationalised medicinal chemistry approach was adopted to design these analogues. An analysis of docking data suggested that compound 6b could bind with the key residues in the ligand binding domain of PqsR in a similar fashion to the known antagonist M64. The modification of cyclic groups at the 3-position of the quinazolinone core, the introduction of a halogen at the aromatic core and the modification of the terminal group with aromatic and aliphatic chains were investigated to guide the synthesis of a library of 16 quinazolinone analogues. All quinazolinone analogues were tested in vitro for pqs inhibition, with the most active compounds 6b and 6e being tested for biofilm and growth inhibition in P. aeruginosa (PAO1). Compound 6b displayed the highest pqs inhibitory activity (73.4%, 72.1% and 53.7% at 100, 50 and 25 µM, respectively) with no bacterial growth inhibition. However, compounds 6b and 6e only inhibited biofilm formation by 10% and 5%, respectively.
Teneligliptin Co-Infusion Alleviates Morphine Tolerance by Inhibition of Spinal Microglial Cell Activation in Streptozotocin-Induced Diabetic Rats
Authors: Kuthati Yaswanth , Rao Vaikar Navakanth , Huang Wei-Hsiu , Busa Prabhakar , Wong Chih-Shung
Published: July 2023

Morphine (MOR) is a commonly prescribed drug for the treatment of moderate to severe diabetic neuropathic pain (DNP). However, long-term MOR treatment is limited by morphine analgesic tolerance (MAT). The activation of microglial cells and the release of glia-derived proinflammatory cytokines are known to play an important role in the development of MAT. In this study, we aimed to investigate the effects of the dipeptidyl peptidase-4 inhibitor (DPP-4i) teneligliptin (TEN) on MOR-induced microglial cell activation and MAT in DNP rats. DNP was induced in four groups of male Wistar rats through a single intraperitoneal injection of streptozotocin (STZ) (50 mg/kg, freshly dissolved in 5 mmol/L citrate buffer, pH 4.5). Sham rats were administered with the vehicle. Seven days after STZ injection, all rats were implanted with an intrathecal (i.t) catheter connected to a mini-osmotic pump, divided into five groups, and infused with the following combinations: sham + saline (1 µL/h, i.t), DNP + saline (1 µL/h, i.t), DNP + MOR (15 µg/h, i.t), DNP + TEN (2 µg/h, i.t), and DNP + MOR (15 µg/h, i.t) + TEN (2 µg/h, i.t) for 7 days at a rate of 1 μL/h. The MAT was confirmed through the measurement of mechanical paw withdrawal threshold and tail-flick tests. The mRNA expression of neuroprotective proteins nuclear factor erythroid 2-related factor (Nrf2) and heme oxygenase-1 (HO-1) in the dorsal horn was evaluated by quantitative PCR (qPCR). Microglial cell activation and mononucleate cell infiltration in the spinal cord dorsal horn were assessed by immunofluorescence assay (IFA) and Western blotting (WB). The results showed that co-infusion of TEN with MOR significantly attenuated MAT in DNP rats through the restoration of neuroprotective proteins Nrf2 and HO-1 and suppression of microglial cell activation in the dorsal horn. Though TEN at a dose of 2 μg has mild antinociceptive effects, it is highly effective in limiting MAT.
Astaxanthin as a Potent Antioxidant for Promoting Bone Health: An Up-to-Date Review
Authors: Davan Iswari , Fakurazi Sharida , Alias Ekram , Ibrahim Nurul ‘Izzah , Hwei Ng Min , Hassan Haniza
Published: July 2023

In recent years, bone loss and its associated diseases have become a significant public health concern due to increased disability, morbidity, and mortality. Oxidative stress and bone loss are correlated, where oxidative stress suppresses osteoblast activity, resulting in compromised homeostasis between bone formation and resorption. This event causes upregulation of bone remodeling turnover rate with an increased risk of fractures and bone loss. Therefore, supplementation of antioxidants can be proposed to reduce oxidative stress, facilitate the bone remodeling process, suppress the initiation of bone diseases, and improve bone health. Astaxanthin (3,3′-dihydroxy-4-4′-diketo-β-β carotene), a potent antioxidant belonging to the xanthophylls family, is a potential ROS scavenger and could be a promising therapeutic nutraceutical possessing various pharmacological properties. In bone, astaxanthin enhances osteoblast differentiation, osteocytes numbers, and/or differentiation, inhibits osteoclast differentiation, cartilage degradation markers, and increases bone mineral density, expression of osteogenic markers, while reducing bone loss. In this review, we presented the up-to-date findings of the potential anabolic effects of astaxanthin on bone health in vitro, animal, and human studies by providing comprehensive evidence for its future clinical application, especially in treating bone diseases.
Poplar Propolis Improves Insulin Homeostasis in Non-Diabetic Insulin-Resistant Volunteers with Obesity: A Crossover Randomized Controlled Trial
Authors: Sani Lea , Cardinault Nicolas , Astier Julien , Darmon Patrice , Landrier Jean François
Published: July 2023

Propolis, a natural resinous mixture rich in polyphenols, produced by bees from a variety of plant sources, has shown significant therapeutic effects and may prevent the development of certain chronic diseases like type 2 diabetes mellitus (T2DM). The objective of this study was to evaluate the effect of supplementation with standardized poplar propolis extract powder (PPEP) on insulin homeostasis in non-diabetic insulin-resistant volunteers with obesity. In this randomized, controlled, crossover trial, nine non-diabetic insulin-resistant volunteers with obesity, aged 49 ± 7 years, were subjected to two periods of supplementation (placebo and PPEP) for 3 months. Blood samples and anthropomorphic data were collected at baseline and at the end of each phase of the intervention. PPEP supplementation improved insulin sensitivity by significantly decreasing the percentage of insulin-resistant subjects and the insulin sensitivity Matsuda index (ISI-M). According to this study, supplementation with standardized PPEP for 3 months in non-diabetic insulin-resistant volunteers with obesity led to an improvement in insulin homeostasis by its effect on insulin resistance and secretion. This study suggests that poplar propolis has a preventive effect on the physiopathological mechanisms of T2DM and, therefore, that it can help to prevent the development of the disease.
Prediction of Internal Temperature in Greenhouses Using the Supervised Learning Techniques: Linear and Support Vector Regressions
Authors: García-Vázquez Fabián , Ponce-González Jesús R. , Guerrero-Osuna Héctor A. , Carrasco-Navarro Rocío , Luque-Vega Luis F. , Mata-Romero Marcela E. , Martínez-Blanco Ma. del Rosario , Castañeda-Miranda Celina Lizeth , Díaz-Flórez Germán
Published: July 2023

Agricultural greenhouses must accurately predict environmental factors to ensure optimal crop growth and energy management efficiency. However, the existing predictors have limitations when dealing with dynamic, non-linear, and massive temporal data. This study proposes four supervised learning techniques focused on linear regression (LR) and Support Vector Regression (SVR) to predict the internal temperature of a greenhouse. A meteorological station is installed in the greenhouse to collect internal data (temperature, humidity, and dew point) and external data (temperature, humidity, and solar radiation). The data comprises a one year, and is divided into seasons for better analysis and modeling of the internal temperature. The study involves sixteen experiments corresponding to the four models and the four seasons and evaluating the models’ performance using R2, RMSE, MAE, and MAPE metrics, considering an acceptability interval of ±2 °C. The results show that LR models had difficulty maintaining the acceptability interval, while the SVR models adapted to temperature outliers, presenting the highest forecast accuracy among the proposed algorithms.
Bioactive Substances and Microbiological Quality of Milk Thistle Fruits from Organic and Conventional Farming
Authors: Sadowska Katarzyna , Andrzejewska Jadwiga , Ligocka Anna , Korczyk-Szabo Joanna , Haban Miroslav
Published: July 2023

The agricultural policy of the European Union is currently focused on increasing the area of organic farming. Medicinal plants, including milk thistle (Silybum marianum [L.] Gaertn.), are particularly suitable for this type of cultivation. The aim of this study was to compare milk thistle fruits from organic and conventional farming in terms of the content of silymarin and individual flavonolignans, oil content, microbiological purity, as well as antimicrobial activity of the silymarin extract, mainly in relation to microorganisms responsible for skin infections. The raw material of Silybi mariani fructus obtained from organic farming did not differ in terms of silymarin and oil content compared to the raw material from conventional cultivation. However, it differed in the composition of silymarin and the level of microbiological contamination. Raw material from organic farming was mostly characterized by a higher proportion of the sum of silydianin and silychristin in the silymarin complex than the sum of silybinin A and silybinin B. In the samples from conventional cultivation, only genotypes with a predominance of silybinins were present. Although the total number of microorganisms (TAMC) and yeasts and molds (TYMC) on fruit from organic farming were several times higher than on fruit from conventional farming, it was still within the standards set for food products. All raw materials were free of Escherichia coli, Salmonella spp. and Listeria monocytogenes. In addition, it was shown that the silymarin extract from organic farming was generally characterized by greater antimicrobial activity, especially in relation to Staphylococcus aureus, which is resistant and troublesome in skin infections.
MHA-ConvLSTM Dam Deformation Prediction Model Considering Environmental Volume Lag Effect
Authors: Liu Hepeng , Li Denghua , Ding Yong
Published: July 2023

The construction of a reasonable and reliable deformation prediction model is of great practical significance for dam safety assessment and risk decision-making. Traditional dam deformation prediction models are susceptible to interference from redundant features, weak generalization ability, and a lack of model interpretation. Based on this, a deformation prediction model that considers the lag effect of environmental quantities is proposed. The model first constructs a new deformation lag influence factor based on the plain HST model through the lag quantization algorithm. Secondly, the attention and memory capacity of the model is improved by introducing a multi-head attention mechanism to the features of the long-time domain deformation influence factor, and finally, the extracted dynamic features are transferred to the ConvLSTM model for learning, training, and prediction. The results of the simulation tests based on the measured deformation data of an active dam show that the introduction of the deformation lag factor not only improves the interpretation of the prediction model for deformation but also makes the prediction of deformation more accurate, and it can improve the evaluation indexes such as RMSE by 50%, the nMAPE by 40%, and R2 by 10% compared with the traditional prediction model. The combined prediction model is more capable of mining the hidden features of the data and has a deeper picture of the overall peak and local extremes of the deformation data, which provides a new way of thinking for the dam deformation prediction model.
Comparison of the Tribological Behaviour of Various Graphene Nano-Coatings as a Solid Lubricant for Copper
Authors: Goti Edoardo , Mura Andrea , Wang Haozhe , Ji Xiang , Kong Jing
Published: July 2023

Among the amazing properties of graphene, superlubricity is one of the most promising properties. This property can be used in industrial field components to reduce friction without using liquid lubricants, and therefore, improve machines’ efficiency and reliability with low environmental impact thanks to the elimination of oil or grease lubricants. In this paper, copper alloy samples for electrical purposes were coated with graphene by four different deposition processes. The investigated synthesis processes are direct grown graphene on bulk Cu, transferred graphene, and self-assembled graphene from graphene flakes. Ball-on-disk tests were performed to evaluate the tribological performance of samples. The aim was to compare the effect on the tribological performance given by different types of coatings, taking also into consideration industrial scalability. Interestingly, not all graphene nano-coatings being compared proved effective in reducing friction and wear in gross sliding conditions. The results show that the cost-effective self-assembled graphene is the longer-lasting nano-coating among those investigated in this work, and can reduce both friction and wear. Tests revealed that graphene coatings can be applied as a solid lubricant, reducing friction up to 78%, and reducing the average wear volume up to 40%.
Special Issue on Innovative Food Products and Processing
Authors: Mamat Hasmadi , Bhandari Bhesh R.
Published: July 2023

The food industry is experiencing a significant transformation, driven by evolving consumer preferences, sustainability concerns, and technological advancements [...]
Spiking Neural P Systems for Basic Arithmetic Operations
Authors: Chen Xiong , Guo Ping
Published: July 2023

As a novel biological computing device, the Spiking Neural P system (SNPS) has powerful computing potential. The application of SNPS in the field of arithmetic operation has been a hot research topic in recent years. Researchers have proposed methods and systems for implementing basic arithmetic operations using SNPS. This paper studies four basic arithmetic operations, improves the parallelization of addition and multiplication methods, and designs more effective natural number addition and multiplication SNPS, as well as SNPS for subtraction and for division of natural numbers based on multiple subtractions. The effectiveness of the proposed SNPS is verified by example. Compared with the same kind of SNPS, for the addition operation the number of neurons used in our system is reduced by 50% and the time overhead is reduced by 33%, while for the multiplication operation the number of neurons is reduced by 40%.
Impacts of UHI on Heating and Cooling Loads in Residential Buildings in Cities of Different Sizes in Beijing–Tianjin–Hebei Region in China
Authors: Meng Fanchao , Ren Guoyu , Zhang Ruixue
Published: July 2023

The heating and cooling energy consumption levels of urban buildings account for a large and rapidly growing proportion of the total end-use energy consumption of society. The urban heat island (UHI) effect is an important factor influencing the spatiotemporal variations in the heating and cooling energy consumption levels of buildings. However, there is a lack of research on the impact of the UHI on the heating and cooling energy consumption of buildings in cities of different sizes in the Beijing–Tianjin–Hebei urban agglomeration, which is the most urbanized region in northern China. We selected rural reference stations using the remote sensing method, and applied an hourly data set from automatic weather stations, to examine the impact of the UHI on the typical residential building heating and cooling loads in three cities of varied sizes in the Beijing–Tianjin–Hebei urban agglomeration through building energy simulation. The main conclusions were as follows. As the UHI intensity (UHII) increased, the heating load difference between urban and rural areas decreased, while the cooling load difference between urban and rural areas increased in the cities. The average daily heating loads in the urban areas of Beijing, Tianjin, and Shijiazhuang were 8.14, 10.71, and 2.79% lower than those in their rural areas, respectively, while the average daily cooling loads in the urban areas were 6.88, 6.70, and 0.27% higher than those in their rural areas, respectively. Moreover, the absolute hourly load differences between urban and rural areas were significantly larger during the heating periods than during the cooling periods, with the former characterized by being strong at night and weak during the day. During the peak energy load period, the contribution of the UHI to the peak load of residential buildings varied between the cities. During the stable high-load period, from 18:00 to 07:00 the next day in the heating periods (from 18:00 to 05:00 the next day in the cooling periods), the hourly loads in the urban areas of Beijing, Tianjin, and Shijiazhuang were 3.15 (2.48), 3.88 (1.51), and 1.07% (1.09%) lower (higher) than those in their rural areas, respectively. Our analysis highlights the necessity to differentiate the energy supplies for the heating and cooling of urban buildings in different sized cities in the region.
Setup for the Ionic Lifetime Measurement of the 229mTh3+ Nuclear Clock Isomer
Authors: Scharl Kevin , Ding Shiqian , Holthoff Georg , Hussain Mahmood Irtiza , Kraemer Sandro , Löbell Lilli , Moritz Daniel , Rozibakieva Tamila , Seiferle Benedict , Zacherl Florian , Thirolf Peter G.
Published: July 2023

For the realization of an optical nuclear clock, the first isomeric excited state of thorium-229 (229mTh) is currently the only candidate due to its exceptionally low-lying excitation energy (8.338±0.024 eV). Such a nuclear clock holds promise not only to be a very precise metrological device but also to extend the knowledge of fundamental physics studies, such as dark matter research or variations in fundamental constants. Considerable progress was achieved in recent years in characterizing 229mTh from its first direct identification in 2016 to the only recent observation of the long-sought-after radiative decay channel. So far, nuclear resonance as the crucial parameter of a nuclear frequency standard has not yet been determined with laser-spectroscopic precision. To determine another yet unknown basic property of the thorium isomer and to further specify the linewidth of its ground-state transition, a measurement of the ionic lifetime of the isomer is in preparation. Theory and experimental investigations predict the lifetime to be 103–104 s. To precisely target this property using hyperfine structure spectroscopy, an experimental setup is currently being commissioned at LMU Munich. It is based on a cryogenic Paul trap providing long-enough storage times for 229mTh ions, that will be sympathetically cooled with 88Sr+. This article presents a concept for an ionic lifetime measurement and discusses the laser-optical part of a setup specifically developed for this purpose.
In Vivo Assessment of High-Strength and Corrosion-Controlled Magnesium-Based Bone Implants
Authors: Ibrahim Hamdy , Billings Caroline , Abdalla Moataz , Korra Ahmed , Anderson David Edger
Published: July 2023

The biodegradable nature of magnesium in aqueous mediums makes it an attractive material for various biomedical applications when it is not recommended that the material stay permanently in the body. Some of the main challenges that hinder the use of magnesium for bone fracture repair are its limited mechanical strength and fast corrosion rates. To this end, we developed a novel Mg-Zn-Ca-Mn-based alloy and post-fabrication methods that can deliver high-strength and corrosion-controlled implant materials to address these challenges. This study is focused on assessing the in vitro corrosion and in vivo biocompatibility of the developed magnesium-based alloy and post-fabrication processes. The developed heat treatment process resulted in an increase in the microhardness from 71.9 ± 5.4 HV for the as-cast Mg alloy to as high as 98.1 ± 6.5 HV for the heat-treated Mg alloy, and the ceramic coating resulted in a significant reduction in the corrosion rate from 10.37 mm/yr for the uncoated alloy to 0.03 mm/yr after coating. The in vivo assessments showed positive levels of biocompatibility in terms of degradation rates and integration of the implants in a rabbit model. In the rabbit studies, the implants became integrated into the bone defect and showed minimal evidence of an immune response. The results of this study show that it is possible to produce biocompatible Mg-based implants with stronger and more corrosion-controlled properties based on the developed Mg-Zn-Ca-Mn-based alloy and post-fabrication methods.
Evaluation of Mutual Information and Feature Selection for SARS-CoV-2 Respiratory Infection
Authors: Kidambi Raju Sekar , Ramaswamy Seethalakshmi , Eid Marwa M. , Gopalan Sathiamoorthy , Karim Faten Khalid , Marappan Raja , Khafaga Doaa Sami
Published: July 2023

This study aims to develop a predictive model for SARS-CoV-2 using machine-learning techniques and to explore various feature selection methods to enhance the accuracy of predictions. A precise forecast of the SARS-CoV-2 respiratory infections spread can help with efficient planning and resource allocation. The proposed model utilizes stochastic regression to capture the virus transmission’s stochastic nature, considering data uncertainties. Feature selection techniques are employed to identify the most relevant and informative features contributing to prediction accuracy. Furthermore, the study explores the use of neighbor embedding and Sammon mapping algorithms to visualize high-dimensional SARS-CoV-2 respiratory infection data in a lower-dimensional space, enabling better interpretation and understanding of the underlying patterns. The application of machine-learning techniques for predicting SARS-CoV-2 respiratory infections, the use of statistical measures in healthcare, including confirmed cases, deaths, and recoveries, and an analysis of country-wise dynamics of the pandemic using machine-learning models are used. Our analysis involves the performance of various algorithms, including neural networks (NN), decision trees (DT), random forests (RF), the Adam optimizer (AD), hyperparameters (HP), stochastic regression (SR), neighbor embedding (NE), and Sammon mapping (SM). A pre-processed and feature-extracted SARS-CoV-2 respiratory infection dataset is combined with ADHPSRNESM to form a new orchestration in the proposed model for a perfect prediction to increase the precision of accuracy. The findings of this research can contribute to public health efforts by enabling policymakers and healthcare professionals to make informed decisions based on accurate predictions, ultimately aiding in managing and controlling the SARS-CoV-2 pandemic.
Current Understanding of Polyphenols to Enhance Bioavailability for Better Therapies
Authors: Aatif Mohammad
Published: July 2023

In recent years, plant polyphenols have become a popular focus for the development of novel functional foods. Polyphenols, a class of bioactive compounds, including flavonoids, phenolic acids, and lignans, are commonly found in plant-based diets with a variety of biological actions, including antioxidant, anti-inflammatory, and anticancer effects. Unfortunately, polyphenols are not widely used in nutraceuticals since many of the chemicals in polyphenols possess poor oral bioavailability. Thankfully, polyphenols can be encapsulated and transported using bio-based nanocarriers, thereby increasing their bioavailability. Polyphenols’ limited water solubility and low bioavailability are limiting factors for their practical usage, but this issue can be resolved if suitable delivery vehicles are developed for encapsulating and delivering polyphenolic compounds. This paper provides an overview of the study of nanocarriers for the enhancement of polyphenol oral bioavailability, as well as a summary of the health advantages of polyphenols in the prevention and treatment of several diseases.
CASZ1: Current Implications in Cardiovascular Diseases and Cancers
Authors: Jian Heng , Poetsch Ansgar
Published: July 2023

Castor zinc finger 1 (CASZ1) is a C2H2 zinc finger family protein that has two splicing variants, CASZ1a and CASZ1b. It is involved in multiple physiological processes, such as tissue differentiation and aldosterone antagonism. Genetic and epigenetic alternations of CASZ1 have been characterized in multiple cardiovascular disorders, such as congenital heart diseases, chronic venous diseases, and hypertension. However, little is known about how CASZ1 mechanically participates in the pathogenesis of these diseases. Over the past decades, at first glance, paradoxical influences on cell behaviors and progressions of different cancer types have been discovered for CASZ1, which may be explained by a “double-agent” role for CASZ1. In this review, we discuss the physiological function of CASZ1, and focus on the association of CASZ1 aberrations with the pathogenesis of cardiovascular diseases and cancers.
Tumor-Associated Macrophages Affect the Tumor Microenvironment and Radioresistance via the Upregulation of CXCL6/CXCR2 in Hepatocellular Carcinoma
Authors: Lee Hsin-Lun , Tsai Yi-Chieh , Pikatan Narpati Wesa , Yeh Chi-Tai , Yadav Vijesh Kumar , Chen Ming-Yao , Tsai Jo-Ting
Published: July 2023

Background: Hepatocellular carcinoma is the sixth most diagnosed malignancy and the fourth most common cause of cancer-related mortality globally. Despite progress in the treatment of liver cancer, nonsurgical treatments remain unsatisfactory, and only 15% of early-stage cases are surgically operable. Radiotherapy (RT) is a non-surgical treatment option for liver cancer when other traditional treatment methods are ineffective. However, RT has certain limitations, including eliciting poor therapeutic effects in patients with advanced and recurrent tumors. Tumor-associated macrophages (TAMs) are major inflammatory cells in the tumor microenvironment that are key to tumor development, angiogenesis, invasion, and metastasis, and they play an essential role in RT responses. Methods: We used big data analysis to determine the potential of targeting CXCL6/CXCR2. We enrolled 50 patients with liver cancer who received RT at our hospital. Tumor tissue samples were examined for any relationship between CXCL6/CXCR2 activity and patient prognosis. Using a cell coculture system (Transwell), we cocultured Huh7 liver cancer cells and THP-1 monocytes with and without CXCL6/CXCR2 small interfering RNA for 72 h. Results: The overexpression of CXCL6/CXCR2 was highly correlated with mortality. Our tissue study indicated a positive correlation between CXCL6/CXCR2 and M2-TAMs subsets. The coculture study demonstrated that THP-1 monocytes can secrete CXCL6, which acts on the CXCR2 receptor on the surface of Huh7 cells and activates IFN-g/p38 MAPK/NF-κB signals to promote the epithelial–mesenchymal transition and radio-resistance. Conclusions: Modulating the TAM/CXCL6/CXCR2 tumor immune signaling axis may be a new treatment strategy for the effective eradication of radiotherapy-resistant hepatocellular carcinoma cells.
When Size Really Matters: The Eccentricities of Dystrophin Transcription and the Hazards of Quantifying mRNA from Very Long Genes
Authors: Hildyard John C. W. , Piercy Richard J.
Published: July 2023

At 2.3 megabases in length, the dystrophin gene is enormous: transcription of a single mRNA requires approximately 16 h. Principally expressed in skeletal muscle, the dystrophin protein product protects the muscle sarcolemma against contraction-induced injury, and dystrophin deficiency results in the fatal muscle-wasting disease, Duchenne muscular dystrophy. This gene is thus of key clinical interest, and therapeutic strategies aimed at eliciting dystrophin restoration require quantitative analysis of its expression. Approaches for quantifying dystrophin at the protein level are well-established, however study at the mRNA level warrants closer scrutiny: measured expression values differ in a sequence-dependent fashion, with significant consequences for data interpretation. In this manuscript, we discuss these nuances of expression and present evidence to support a transcriptional model whereby the long transcription time is coupled to a short mature mRNA half-life, with dystrophin transcripts being predominantly nascent as a consequence. We explore the effects of such a model on cellular transcriptional dynamics and then discuss key implications for the study of dystrophin gene expression, focusing on both conventional (qPCR) and next-gen (RNAseq) approaches.
Therapeutic Targets of Monoclonal Antibodies Used in the Treatment of Cancer: Current and Emerging
Authors: Effer Brian , Perez Isabela , Ulloa Daniel , Mayer Carolyn , Muñoz Francisca , Bustos Diego , Rojas Claudio , Manterola Carlos , Vergara-Gómez Luis , Dappolonnio Camila , Weber Helga , Leal Pamela
Published: July 2023

Cancer is one of the leading global causes of death and disease, and treatment options are constantly evolving. In this sense, the use of monoclonal antibodies (mAbs) in immunotherapy has been considered a fundamental aspect of modern cancer therapy. In order to avoid collateral damage, it is indispensable to identify specific molecular targets or biomarkers of therapy and/or diagnosis (theragnostic) when designing an appropriate immunotherapeutic regimen for any type of cancer. Furthermore, it is important to understand the currently employed mAbs in immunotherapy and their mechanisms of action in combating cancer. To achieve this, a comprehensive understanding of the biology of cancer cell antigens, domains, and functions is necessary, including both those presently utilized and those emerging as potential targets for the design of new mAbs in cancer treatment. This review aims to provide a description of the therapeutic targets utilized in cancer immunotherapy over the past 5 years, as well as emerging targets that hold promise as potential therapeutic options in the application of mAbs for immunotherapy. Additionally, the review explores the mechanisms of actin of the currently employed mAbs in immunotherapy.
Breaking through Multiple Myeloma: A Paradigm for a Comprehensive Tumor Ecosystem Targeting
Authors: Solimando Antonio G. , Krebs Markus , Desantis Vanessa , Marziliano Donatello , Caradonna Ingrid Catalina , Morizio Arcangelo , Argentiero Antonella , Shahini Endrit , Bittrich Max
Published: July 2023

Multiple myeloma (MM) is a cancerous condition characterized by the proliferation of plasma cells within the hematopoietic marrow, resulting in multiple osteolytic lesions. MM patients typically experience bone pain, kidney damage, fatigue due to anemia, and infections. Historically, MM was an incurable disease with a life expectancy of around three years after diagnosis. However, over the past two decades, the development of novel therapeutics has significantly improved patient outcomes, including response to treatment, remission duration, quality of life, and overall survival. These advancements include thalidomide and its derivatives, lenalidomide and pomalidomide, which exhibit diverse mechanisms of action against the plasma cell clone. Additionally, proteasome inhibitors such as bortezomib, ixazomib, and carfilzomib disrupt protein degradation, proving specifically toxic to cancerous plasma cells. Recent advancements also involve monoclonal antibodies targeting surface antigens, such as elotuzumab (anti-CS1) and daratumumab (anti-CD38), bispecific t-cell engagers such as teclistamab (anti-BCMA/CD3) and Chimeric antigen receptor T (CAR-T)-based strategies, with a growing focus on drugs that exhibit increasingly targeted action against neoplastic plasma cells and relevant effects on the tumor microenvironment.
The Poly-Arginine Peptide R18D Interferes with the Internalisation of α-Synuclein Pre-Formed Fibrils in STC-1 Enteroendocrine Cells
Authors: Gorecki Anastazja M. , Spencer Holly , Meloni Bruno P. , Anderton Ryan S.
Published: July 2023

In Parkinson’s disease (PD), gut inflammation is hypothesised to contribute to α-synuclein aggregation, but gastrointestinal α-synuclein expression is poorly characterised. Cationic arginine-rich peptides (CARPs) are an emerging therapeutic option that exerts various neuroprotective effects and may target the transmission of protein aggregates. This study aimed to investigate endogenous α-synuclein expression in enteroendocrine STC-1 cells and the potential of the CARP, R18D (18-mer of D-arginine), to prevent internalisation of pre-formed α-synuclein fibrils (PFFs) in enteroendocrine cells in vitro. Through confocal microscopy, the immunoreactivity of full-length α-synuclein and the serine-129 phosphorylated form (pS129) was investigated in STC-1 (mouse enteroendocrine) cells. Thereafter, STC-1 cells were exposed to PFFs tagged with Alexa-Fluor 488 (PFF-488) for 2 and 24 h and R18D-FITC for 10 min. After confirming the uptake of both PFFs and R18D-FITC through fluorescent microscopy, STC-1 cells were pre-treated with R18D (5 or 10 μM) for 10 min prior to 2 h of PFF-488 exposure. Immunoreactivity for endogenous α-synuclein and pS129 was evident in STC-1 cells, with prominent pS129 staining along cytoplasmic processes and in perinuclear areas. STC-1 cells internalised PFFs, confirmed through co-localisation of PFF-488 and human-specific α-synuclein immunoreactivity. R18D-FITC entered STC-1 cells within 10 min and pre-treatment of STC-1 cells with R18D interfered with PFF uptake. The endogenous presence of α-synuclein in enteroendocrine cells, coupled with their rapid uptake of PFFs, demonstrates a potential for pathogenic spread of α-synuclein aggregates in the gut. R18D is a novel therapeutic approach to reduce the intercellular transmission of α-synuclein pathology.
Machine Learning Identifies a Signature of Nine Exosomal RNAs That Predicts Hepatocellular Carcinoma
Authors: Yap Josephine Yu Yan , Goh Laura Shih Hui , Lim Ashley Jun Wei , Chong Samuel S. , Lim Lee Jin , Lee Caroline G.
Published: July 2023

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Although alpha fetoprotein (AFP) remains a commonly used serological marker of HCC, the sensitivity and specificity of AFP in detecting HCC is often limited. Exosomal RNA has emerged as a promising diagnostic tool for various cancers, but its use in HCC detection has yet to be fully explored. Here, we employed Machine Learning on 114,602 exosomal RNAs to identify a signature that can predict HCC. The exosomal expression data of 118 HCC patients and 112 healthy individuals were stratified split into Training, Validation and Unseen Test datasets. Feature selection was then performed on the initial training dataset using permutation importance, and the predictive performance of the selected features were tested on the validation dataset using Support Vector Machine (SVM) Classifier. A minimum of nine features were identified to be predictive of HCC and these nine features were then evaluated across six different models in an unseen test set. These features, mainly in the immune, platelet/neutrophil and cytoskeletal pathways, exhibited good predictive performance with ROC-AUC from 0.79–0.88 in the unseen test set. Hence, these nine exosomal RNAs have potential to be clinically useful minimally invasive biomarkers for HCC.
Non-Coding RNAs in Oral Cancer: Emerging Roles and Clinical Applications
Authors: Dey Saurabh , Biswas Bini , Manoj Appadan Angela , Shah Jaladhi , Pal Jayanta , Basu Soumya , Sur Subhayan
Published: July 2023

Oral cancer (OC) is among the most prevalent cancers in the world. Certain geographical areas are disproportionately affected by OC cases due to the regional differences in dietary habits, tobacco and alcohol consumption. However, conventional therapeutic methods do not yield satisfying treatment outcomes. Thus, there is an urgent need to understand the disease process and to develop diagnostic and therapeutic strategies for OC. In this review, we discuss the role of various types of ncRNAs in OC, and their promising clinical implications as prognostic or diagnostic markers and therapeutic targets. MicroRNA (miRNA), long ncRNA (lncRNA), circular RNA (circRNA), PIWI-interacting RNA (piRNA), and small nucleolar RNA (snoRNA) are the major ncRNA types whose involvement in OC are emerging. Dysregulated expression of ncRNAs, particularly miRNAs, lncRNAs, and circRNAs, are linked with the initiation, progression, as well as therapy resistance of OC via modulation in a series of cellular pathways through epigenetic, transcriptional, post-transcriptional, and translational modifications. Differential expressions of miRNAs and lncRNAs in blood, saliva or extracellular vesicles have indicated potential diagnostic and prognostic importance. In this review, we have summarized all the promising aspects of ncRNAs in the management of OC.