bluuebunny/crossref_metadata_2025 huggingface dataset:
Liver Tumor Computed Tomography Image Segmentation Based on an Improved U-Net Model
Authors: Li Hefu , Liang Binmei
Published: October 2023

An automated segmentation method for computed tomography (CT) images of liver tumors is an urgent clinical need. Tumor areas within liver cancer images are easily missed as they are small and have unclear borders. To address these issues, an improved liver tumor segmentation method based on U-Net is proposed. This involves incorporating attention mechanisms into the U-Net’s skip connections, giving higher weights to important regions. Through dynamically adjusting the attention recognition characteristics, the method achieves accurate localization that is focused on and discriminates target regions. Testing using the LiTS (liver tumor segmentation) public dataset resulted in a Dice similarity coefficient of 0.69. The experiments demonstrated that this method can accurately segment liver tumors.
Research on the Dynamic Characteristics Analysis and Power Control Method of Heat Pipe Reactors
Authors: Yin Shaoxuan , Yu Ren , Sheng Dongjie , Mao Wei , Zhao Yudong
Published: October 2023

A heat pipe reactor (HPR) is a kind of modular small reactor with broad application prospects, and its dynamic characteristics and nuclear power control are essential to the safe and stable operation of nuclear power plants. Taking the MegaPower HPR as an example, the dynamic characteristics of the HPR are analyzed, and its power control method is designed in this paper. Based on the lumped parameter idea, the equivalent processing of the structure of the HPR core is carried out, and the main parameters of the heat pipe heat exchanger are designed at first. A lightweight dynamic model of the HPR is established using a thermal resistance network, and the accuracy of the model is verified using the solution of the model under the steady-state full power condition. Then, the dynamic characteristics of the HPR without a controller are analyzed respectively with the disturbance reactivity and mass flow rate, indicating strong self-stability and self-regulation of the HPR. Finally, a reinforcement learning (RL) controller based on the twin delayed deep deterministic policy gradient (TD3) algorithm is designed for the HPR power control, and it is adjusted through appropriately setting states, network structures, reward functions, etc. To verify the performance of the controller, a step response simulation ranging from 100%FP to 90%FP, a compound conditions simulation, and a large load change simulation are carried out, respectively. The results show that the RL controller can find the optimal control strategy through training. Meanwhile, it significantly improves the dynamic and steady-state performance of nuclear power compared with uncontrolled case and PID controller case, and it has the ability of power control under all operating conditions.
Experimental Investigation of the BIPV System under Şanlıurfa Meteorological Conditions
Authors: Demir Yusuf Can , Aktacir Mehmet Azmi
Published: October 2023

In this study, under the meteorological conditions of Şanlıurfa, Turkey, some parameter studies were conducted to more efficiently utilize Building Integrated Photovoltaic BIPV systems placed on different facades of a building. For this purpose, one single-sided (monofacial) panel was placed on both the roof and the east facade. As an innovation brought about by this study, both bifacial and monofacial panels with the same production potential were compared under the same conditions on the south facade. In addition, to enhance the production performance of the rear surface of the bifacial panel, a reflector was placed on the wall surface by leaving a gap between the wall and the panel. The experimental study was conducted between February and July. In addition, the building model created experimentally was analyzed monthly using the PVsyst program for a duration of one year. According to the study results, in the 6-month BIPV experimental application, the electrical production of the bifacial panel was found to be 15.1% higher than that of the monofacial panel under the same conditions. In addition, based on the 1-year results in the PVsyst analysis, the bifacial panel demonstrated a 5.86% higher production performance compared with the monofacial panel. This demonstrates that the efficiency of the bifacial panel in the experimental setup was enhanced by placing a reflective surface on the structure wall behind it. According to the complete annual analysis results obtained from the PVsyst analysis, the bifacial panel in the south produced 401.65 kWh, the monofacial panel produced 379.41 kWh, the panel on the eastern facade produced 313.34 kWh, and the rooftop panel, where the highest production was recorded, generated 505.64 kWh of energy. Therefore, it is anticipated that the use of bifacial panels with reflective surfaces on the roof under the meteorological conditions of Şanlıurfa will demonstrate the highest performance for the BIPV system.
Developing a Static Kinematic Model for Continuum Robots Using Dual Quaternions for Efficient Attitude and Trajectory Planning
Authors: Li Yunfei , Wang Qiuhao , Liu Qian
Published: October 2023

Kinematic modeling is essential for planning and controlling continuum robot motion. The traditional Denavit Hartenberg (DH) model involves complex matrix multiplication operations, resulting in computationally intensive inverse solutions and trajectory planning. Solving position and orientation changes in continuum robots using the double quaternion rule can reduce computational complexity. However, existing dual quaternion methods are direct equational transformations of DH rules and do not give a complete modeling process. They usually require more interpretability when applying continuum robot kinematic modeling. This paper uses the dual quaternion method to establish a kinematic model of a continuum robot. It uses a two-section continuum robot model to compare the advantages of dual quaternion and traditional modeling methods. In addition, this paper proposes a five-polynomial interpolation algorithm based on the dual quaternion method for trajectory planning of continuum robots. This method accurately models spatial bending and torsional motions of singularity-free continuum robots.
Global Path Planning for Differential Drive Mobile Robots Based on Improved BSGA* Algorithm
Authors: Yao Ming , Deng Haigang , Feng Xianying , Li Peigang , Li Yanfei , Liu Haiyang
Published: October 2023

The global path planner is an important part of the navigation system for autonomous differential drive mobile robots (DDMRs). Aiming at the problems such as long calculation time, large number of search nodes, and poor smoothness of path when A* is applied to global path planning, this study proposes an improved bidirectional search Gaussian-A* (BSGA*) algorithm. First, the Gaussian function is introduced to realize the dynamic weighting of the heuristic function, which reduces the calculation time. Secondly, the bidirectional search (BS) structure is adopted to solve the problem of nodes’ repeated search when there are large obstacles between the starting point and the target point. Finally, a multi-layer turning point filter strategy is proposed to further smooth the path. In order to verify the performance of the improved BSGA* algorithm, experiments are carried out in simulation environments with the size of 15 × 15 and 30 × 30, respectively, and compared with the five common global path planning algorithms including ant colony optimization (ACO), D* lite algorithm, and genetic algorithm (GA). The results show that the improved BSGA* algorithm has the lowest calculation time and generates the shortest and smoothest path in the same environment. Finally, the program of the improved BSGA* algorithm is embedded into the LEO ROS mobile robot and two different real environments were built for experimental verification. By comparing with the A* algorithm, Dijkstra algorithm, ACO, D* lite algorithm, and GA, the results show that the improved BSGA* algorithm not only outperforms the above five algorithms in terms of calculation time, length, and total turning angle of the generated paths, but also consumes the least time when DDMR drives along the generated paths.
Bidirectional Representations for Low-Resource Spoken Language Understanding
Authors: Meeus Quentin , Moens Marie-Francine , Van hamme Hugo
Published: October 2023

Speech representation models lack the ability to efficiently store semantic information and require fine tuning to deliver decent performance. In this research, we introduce a transformer encoder–decoder framework with a multiobjective training strategy, incorporating connectionist temporal classification (CTC) and masked language modeling (MLM) objectives. This approach enables the model to learn contextual bidirectional representations. We evaluate the representations in a challenging low-resource scenario, where training data is limited, necessitating expressive speech embeddings to compensate for the scarcity of examples. Notably, we demonstrate that our model’s initial embeddings outperform comparable models on multiple datasets before fine tuning. Fine tuning the top layers of the representation model further enhances performance, particularly on the Fluent Speech Command dataset, even under low-resource conditions. Additionally, we introduce the concept of class attention as an efficient module for spoken language understanding, characterized by its speed and minimal parameter requirements. Class attention not only aids in explaining model predictions but also enhances our understanding of the underlying decision-making processes. Our experiments cover both English and Dutch languages, offering a comprehensive evaluation of our proposed approach.
Robust 3D Joint Inversion of Gravity and Magnetic Data: A High-Performance Computing Approach
Authors: Del Razo Gonzalez Abraham , Yutsis Vsevolod
Published: October 2023

One of the fundamental challenges in geophysics is the calculation of distribution models for physical properties in the subsurface that accurately reproduce the measurements obtained in the survey and are geologically plausible in the context of the study area. This is known as inverse modeling. Performing a 3D joint inversion of multimodal geophysical data is a computationally intensive task. Additionally, since it involves a modeling process, finding a solution that matches the desired characteristics requires iterative calculations, which can take days or even weeks to obtain final results. In this paper, we propose a robust numerical solution for 3D joint inversion of gravimetric and magnetic data with Gramian-based structural similarity and structural direction constraints using parallelization as a high-performance computing technique, which allows us to significantly reduce the total processing time based on the available Random-Access Memory (RAM) and Video Random-Access Memory (VRAM)and improve the efficiency of interpretation. The solution is implemented in the high-level programming languages Fortran and Compute Unified Device Architecture (CUDA) Fortran, capable of optimal resource management while being straightforward to implement. Through the analysis of performance and computational costs of serial, parallel, and hybrid implementations, we conclude that as the inversion domain expands, the processing speed could increase from 4× up to 100× times faster, rendering it particularly advantageous for applications in larger domains. We tested our algorithm with two synthetic data sets and field data, showing better results than standard separate inversion. The proposed method will be useful for joint geological and geophysical interpretation of gravimetric and magnetic data used in exploration geophysics for example minerals, ore, and petroleum search and prospecting. Its application will significantly increase the reliability of physical-geological models and accelerate the process of data processing.
Influence of Horse Age on Carcass Tissue Composition and Horsemeat Quality: Exploring Nutritional and Health Benefits for Gourmets
Authors: Stanisławczyk Renata , Żurek Jagoda , Rudy Mariusz , Gil Marian
Published: October 2023

The aim of this study was to show the influence of the age of horses currently in use in Poland on the tissue composition of carcasses and the quality of horsemeat. To conduct a detailed dissection and analysis of horsemeat quality, 12 half carcasses of foals and young horses, 14 half carcasses of adult horses, and 14 half carcasses of older horses were selected. A highly significant difference was demonstrated between the linear measurements of the carcasses of foals and young horses compared with those of adult animals. A significantly higher dressing percentage was observed in foals compared with older horses (p ≤ 0.05). Compared with the carcasses from older horses, the foal carcasses provided a significantly higher amount of meat in class I (p ≤ 0.05). Meat obtained from foal carcasses, when compared with the raw material from other age groups of animals, was characterized by a higher number of points for individual qualitative characteristics in the sensory evaluation. The physicochemical properties of horsemeat were dependent on the age of the horses. Compared with the oldest horses, foal meat was characterized by the lowest ability to bind and retain water. The significantly highest content of protein and fat was found in the meat of adult horses compared with the meat of foals. The horsemeats consumed today, compared with those from the 1980s and 1990s, are characterized by a much lower degree of fat deposition in the carcasses, and a higher dressing percentage index and carcass meatiness. This may result in a greater popularization of horsemeat, both among processors of this raw material and the consumers themselves. This can be a very important advantage, pointing to new aspects of food quantity and quality, especially for gourmets of this type of product.
Analysis and Research on Secondary LT Coding Anti-Eavesdropping Scheme Based on LT Code Degree-1
Authors: Wang Lizheng , Niu Fanglin , Jin Jingjing , Yu Ling
Published: October 2023

Fountain code can significantly increase eavesdroppers’ untranslated efficiency in the wireless communication eavesdropping channel. The secondary LT coding anti-eavesdropping scheme with fountain code degree-1 is the subject of a theoretical investigation in this paper. The fact that its channel security capacity is greater than that of traditional LT code is first deduced from an information-theoretic standpoint, and the impact of source symbol length on decoding complexity and decoding overhead is then examined. The experimental results show that, compared with the traditional anti-eavesdropping twice fountain code, selecting long source symbols for double LT coding, when the main channel is better than the eavesdropping channel, can ensure that the eavesdropper has a higher untranslated efficiency, and can effectively reduce the fountain code decoding complexity and the number of encoded symbols sent by the source to improve the efficiency of information transmission.
Closed-Form DoA Solution for Co-Centered Orthogonal Microphone Arrays Based on Multilateration Equations
Authors: Zengin Kazım , Yeşildirek Aydın
Published: October 2023

This study proposes a closed-form direction-of-arrival (DoA) solution derived from multilateration equations for microphone arrays of co-centered and orthogonal pairs. The generalized cross-correlation phase transform (GCC-Phat) algorithm is used to obtain the time-difference-of-arrival (TDoA) values. Simulation studies have shown the success of our proposed method compared to existing DoA methods in the literature by varying the sampling frequency of the sound signal, inter-microphone distances, and the source distance. The results from the simulation are validated by the measurements from our experiments. Our proposed solution gives better results than the far-field solution against the angle error, which is more pronounced at incidence angles smaller than 15°. These angle errors, which approach 3° using the far-field method, are reduced to less than 0.5 degrees using our proposed solution. Our solution also gives more stable results against TDoA measurement errors. Our proposed solution achieves a 66% improvement for azimuth angle and 5.88% improvement for elevation angle compared to the simulation results in the absence of TDoA measurement error, outperforming the far-field approach. When normally distributed sampling error is added to TDoA measurements, with a standard deviation of three samples, our proposed solution achieves a 41% improvement for azimuth angle and a 5.44% improvement for elevation angle. In our field measurements, an absolute mean error of 0.94 degrees was observed with our proposed method for azimuth angle. It is shown to be a more stable and faster solution method for real-time applications.
Research on the Strawberry Recognition Algorithm Based on Deep Learning
Authors: Zhang Yunlong , Zhang Laigang , Yu Hanwen , Guo Zhijun , Zhang Ran , Zhou Xiangyu
Published: October 2023

In view of the time-consuming and laborious manual picking and sorting of strawberries, the direct impact of image recognition accuracy on automatic picking and the rapid development of deep learning(DL), a Faster Regions with Convolutional Neural Network features (R-CNN) strawberry recognition method that combines Mixup data augmentation, a ResNet(Residual Network)50 backbone feature extraction network and a Soft-NMS (Non-Maximum Suppression) algorithm, named the MRS Faster R-CNN, is proposed. In this paper, the transfer learning backbone feature extraction network VGG (Visual Geometry Group) 16 and ResNet50 are compared, and the superior ResNet50 is selected as the backbone network of MRS Faster R-CNN. The data augmentation method of Mixup image fusion is used to improve the learning and generalization ability of the model. The redundant bboxes (bounding boxes) are removed through Soft-NMS to obtain the best region proposal. The freezing phase is added to the training process, effectively reducing the occupation of video memory and shortening the training time. After experimental verification, the optimized model improved the AP (Average Precision) values of mature and immature strawberries by 0.26% and 5.34%, respectively, and the P(Precision) values by 0.81% and 6.34%, respectively, compared to the original model (R Faster R-CNN). Therefore, the MRS Faster R-CNN model proposed in this paper has great potential in the field of strawberry recognition and maturity classification and improves the recognition rate of small fruit and overlapping occluded fruit, thus providing an excellent solution for mechanized picking and sorting.
Different Stress Paths Lead to Different Failure Envelopes: Impact on Rock Characterisation and Design
Authors: Vervoort Andre
Published: October 2023

The strength of rock is a non-intrinsic property, and this means that numerous parameters influence the strength values. In most laboratory experiments, specimens are free of stress at the start of the tests, and the load is increased systematically until failure occurs. Around excavations, the opposite path occurs, i.e., the rock is in equilibrium under a triaxial stress state and at least one stress component decreases while another component may increase. Hence, the stress paths in classic laboratory experiments are different from the in situ stress paths. In the research presented, a first step was made to evaluate with an open mind the effect of these different stress paths on the failure process and failure envelope. The research was based on distinct element models, allowing the simulation of micro-fracturing of the rock, which is essential to correctly model rock failure. The micro-fracturing when loading rock (from zero or low stress state) until failure was different from the micro-fracturing when unloading rock (from the in situ stress state) until failure. And, hence, by this difference in weakening processes, the failure envelopes were significantly different. The conventional loading resulted in the largest strength and, thus, overestimated the rock strength in comparison to the real in situ behaviour. This finding, after being confirmed by further lab experiments, will have a direct effect on how one characterises rock material and on the design of rock excavations.
Research on Flexible Traceability System of Agaricus bisporus Supply Chain
Authors: Zhang Xingguo , Liu Pingzeng , Zhang Yan , Sun Feihu , Gong Ao , Zhang Chao
Published: October 2023

The supply chain of Agaricus bisporus constitutes a complex, multi-layered production and distribution network, encompassing various stages. Challenges in information transmission and process integration between these stages often lead to reduced query efficiency, subsequently compromising the credibility of traceability results and the flexibility of the system. In traditional traceability systems, data for multiple service recipients may be stored on a single blockchain, resulting in complex data structures and making it challenging for users to conduct effective queries and analyses. To address this issue, this paper proposes a solution: a multi-chain tracing model tailored for stakeholders in the traceability process of Agaricus bisporus. This model establishes public chains, enterprise chains, and supervision chains for consumers, enterprises, and regulatory authorities, respectively, to enhance system storage and query efficiency. Additionally, leveraging the modular design of Hyperledger Fabric, the paper optimizes and upgrades the supply chain of Agaricus bisporus. The proposed multi-chain tracing model, designed for traceability for stakeholders, undergoes rigorous validation. Analysis and application results demonstrate that this approach significantly improves the query efficiency and credibility of traceability information while markedly enhancing system flexibility.
A New Research Scheme for Full-Scale/Model Test Comparison of Wind Effects on Pengcheng Cooling Tower Based on Sinusoidal Flow Field Simulations
Authors: Cheng Xiao-Xiang , Zhao Lin , Ge Yao-Jun , Wu Bai-Jian , Dong Jun , Peng Yang
Published: October 2023

When examining the history of wind engineering, it is evident that many full-scale/model test comparisons have found noticeable differences between the results. Although understanding the causes of these differences is important for practical purposes, limited numerical and experimental conditions have often resulted in subjective explanations for full-scale/model test comparisons without scientific validation. To address this issue, this article suggests the use of the computational fluid dynamics technique or the multiple-fan actively controlled wind tunnel technique to quantitatively reveal the adverse effects that impact the reliability of the traditional atmospheric boundary layer wind tunnel tests for a large cooling tower, including not only the widely acknowledged influences (Reynolds number effects and turbulent flow characteristics effects) but also the non-stationarity effects that have potential influences. Established on the novel proposition, a new research scheme for future full-scale/model test wind effects comparisons for large cooling towers has been formulated based on the numerical or physical simulations of the sinusoidal flow fields. Using the Pengcheng cooling tower as a case study, the research recognized the very significant impact of Reynolds number effects, the non-stationarity effects that cannot be ignored, and the negligible effects of turbulent flow characteristics.
Quantitative Analysis of Biodiesel Adulterants Using Raman Spectroscopy Combined with Synergy Interval Partial Least Squares (siPLS) Algorithms
Authors: Su Yuemei , Li Maogang , Yan Chunhua , Zhang Tianlong , Tang Hongsheng , Li Hua
Published: October 2023

Biodiesel has emerged as an alternative to traditional fuels with the aim of reducing the impact on the environment. It is produced by the esterification of oleaginous seeds, animal fats, etc., with short-chain alcohols in an alkaline solution, which is one of the most commonly used methods. This increases the oxygen content (from the fatty acids) and promotes the fuel to burn faster and more efficiently. The accurate quantification of biodiesel is of paramount importance to the fuel market due to the possibility of adulteration, which can result in economic losses, engine performance issues and environmental concerns related to corrosion. In response to achieving this goal, in this work, synergy interval partial least squares (siPLS) algorithms in combination with Raman spectroscopy are used for the quantification of the biodiesel content. Different pretreatment methods are discussed to eliminate a large amount of redundant information of the original spectrum. The siPLS technique for extracting feature variables is then used to optimize the input variables after pretreatment, in order to enhance the predictive performance of the calibration model. Finally, the D1-MSC-siPLS calibration model is constructed based on the preprocessed spectra, the selected input variables and the optimized model parameters. Compared with the feature variable selection methods of interval partial least squares (iPLS) and backward interval partial least squares (biPLS), results elucidate that the D1-MSC-siPLS calibration model is superior to the D1-MSC-biPLS and the D1-MSC-iPLS in the quantitative analysis of adulterated biodiesel. The D1-MSC-siPLS calibration model demonstrates better predictive performance compared to the full spectrum PLS model, with the optimal determination coefficient of prediction (R2P) being 0.9899; the mean relative error of prediction (MREP) decreased from 9.51% to 6.31% and the root--mean-squared error of prediction (RMSEP) decreased from 0.1912% (v/v) to 0.1367% (v/v), respectively. The above results indicate that Raman spectroscopy combined with the D1-MSC-siPLS calibration model is a feasible method for the quantitative analysis of biodiesel in adulterated hybrid fuels.
High-Frequency Harmonic Suppression Strategy and Modified Notch Filter-Based Active Damping for Low-Inductance HPMSM
Authors: Liu Yifeng , Du Jinhua , Zhao Xiaodong , Song Yutong , Wang Yao
Published: October 2023

The voltage inverters have the high-frequency switching characteristic, which will generate massive high-frequency harmonics in the motors. Especially, the inductance of the high-speed permanent magnet synchronous motor (HPMSM) is designed to be small, and the high-frequency harmonic content will be higher than that of ordinary motors, which adversely affects the system. To overcome this problem, this paper proposed a harmonic suppression method based on the LC filter and the adaptive notch filter for HPMSMs. The LC filter is connected between the inverter and the HPMSM to filter out high-frequency harmonics, however, at the cost of the system resonance. Therefore, the adaptive notch filter with the frequency tracking capability is designed to offset specific resonant peaks by constructing an antiresonant peak. The least mean square adaptive algorithm automatically adjusts the filter parameters according to the variation of the input signal to ensure accurate filtering in complex cases. Simulation and experiment results prove the practicability and effectiveness of the proposed scheme. The harmonic contents of HPMSM are significantly reduced, and the dynamic response performance of the control system is improved.
Assessment of Live Lactobacilli Recovery from Probiotic Products for Vaginal Application
Authors: Sousa Diana Neves , Gaspar Carlos , Rolo Joana , Donders Gilbert G. G. , Martinez-de-Oliveira José , Palmeira-de-Oliveira Rita , Palmeira-de-Oliveira Ana
Published: October 2023

The interest in the use of probiotics to treat and prevent vaginal infections is known. The new regulation of medical devices by the European Medical Agency (EMA) introduced big changes in Europe regarding probiotic products for vaginal application, as they are no longer considered as medical devices. As the future classification will be as drugs, it will stress the need to define robust and reliable pre-clinical in vitro testing in order to assess the quality, safety and efficacy of probiotics for human use. Before discussing the efficacy in human pathology, it is mandatory to evaluate the survival and multiplication potential of probiotic strains when brought into contact with vaginal fluid. In this work, our objective was to assess the recovery and stability profile of lactobacilli from six vaginal probiotic formulations brought in contact with specific culture media or vaginal fluid simulants (VFS). Overall, the recovery of viable lactobacilli cells from a modified vaginal fluid simulant (MVFS) solution was comparable to the recovery pattern obtained in standard culture medium. Therefore, we conclude that the MVFS seems to better simulate the conditions of the human vaginal fluid, in contrast with other simulants, and may be used to predict the viability of probiotics over time in the normal vaginal milieu. We discovered that each probiotic product has a unique profile that requires stand-alone studies in conditions that mimic the in vivo status in order to assess their preclinical effectiveness and promote their differential use by the medical community.
Innovative Strategy for Constructing Soft Topology
Authors: Alajlan Amlak I. , Alghamdi Ahmad M.
Published: October 2023

To address the complexity of daily problems, soft set theory has emerged as a valuable tool, providing innovative mathematical techniques to manage vast amounts of data and ambiguity. The study of soft topology involves the investigation of various properties of soft sets and functions, as well as the development of new mathematical models and techniques for addressing uncertainty. The main motivation of this paper is to delve deeper into the subject and devise new methodologies to address real-world challenges more effectively and unlock the full potential of soft sets in various applications. In this paper, we present a novel soft topology, which is constructed using soft single points on a nonempty set V in relation to a topology on V. We investigate and study the behaviors and properties associated with this particular type of soft topology. Furthermore, we shed light on the soft separation axioms with this type of soft topology and investigate whether these axioms are inherited from the corresponding ordinary topology or not. Our study is concerned with examining the connection between ordinary topologies and the soft topologies generated that arise from them, with the aim of identifying their interdependencies and potential implications. By studying the connection between soft topologies and their corresponding ordinary topologies, researchers are able to gain a deeper understanding of the properties and behaviors of these structures and develop new modeling approaches for dealing with uncertainty and complexity in data.
Autotrophic Production of the Sesquiterpene α-Humulene with Cupriavidus necator in a Controlled Bioreactor
Authors: Sydow Anne , Becker Lucas , Lombard Eric , Ulber Roland , Guillouet Stephane E. , Holtmann Dirk
Published: October 2023

Cupriavidus necator is a facultative chemolithotrophic organism that grows under both heterotrophic and autotrophic conditions. It is becoming increasingly important due to its ability to convert CO2 into industrially valuable chemicals. To translate the potential of C. necator into technical applications, it is necessary to optimize and scale up production processes. A previous proof-of-principle study showed that C. necator can be used for the de novo production of the terpene α-humulene from CO2 up to concentrations of 11 mg L−1 in septum flasks. However, an increase in final product titer and space–time yield will be necessary to establish an economically viable industrial process. To ensure optimized growth and production conditions, the application of an improved process design in a gas bioreactor with the control of pH, dissolved oxygen and temperature including a controlled gas supply was investigated. In the controlled gas bioreactor, the concentration of α-humulene was improved by a factor of 6.6 and the space–time yield was improved by a factor of 13.2. These results represent an important step toward the autotrophic production of high-value chemicals from CO2. In addition, the in situ product removal of α-humulene was investigated and important indications of the critical logP value were obtained, which was in the range of 3.0–4.2.
Reproducibility and Robustness of a Liver Microphysiological System PhysioMimix LC12 under Varying Culture Conditions and Cell Type Combinations
Authors: Lim Alicia Y. , Kato Yuki , Sakolish Courtney , Valdiviezo Alan , Han Gang , Bajaj Piyush , Stanko Jason , Ferguson Stephen S. , Villenave Remi , Hewitt Philip , Hardwick Rhiannon N. , Rusyn Ivan
Published: October 2023

The liver is one of the key organs for exogenous and endogenous metabolism and is often a target for drug- and chemical-driven toxicity. A wide range of experimental approaches has been established to model and characterize the mechanisms of drug- and chemical-induced hepatotoxicity. A number of microfluidics-enabled in vitro models of the liver have been developed, but the unclear translatability of these platforms has hindered their adoption by the pharmaceutical industry; to achieve wide use for drug and chemical safety evaluation, demonstration of reproducibility and robustness under various contexts of use is required. One of these commercially available platforms is the PhysioMimix LC12, a microfluidic device where cells are seeded into a 3D scaffold that is continuously perfused with recirculating cell culture media to mimic liver sinusoids. Previous studies demonstrated this model’s functionality and potential applicability to preclinical drug development. However, to gain confidence in PhysioMimix LC12’s robustness and reproducibility, supplementary characterization steps are needed, including the assessment of various human hepatocyte sources, contribution of non-parenchymal cells (NPCs), and comparison to other models. In this study, we performed replicate studies averaging 14 days with either primary human hepatocytes (PHHs) or induced pluripotent stem cell (iPSC)-derived hepatocytes, with and without NPCs. Albumin and urea secretion, lactate dehydrogenase, CYP3A4 activity, and metabolism were evaluated to assess basal function and metabolic capacity. Model performance was characterized by different cell combinations under intra- and inter-experimental replication and compared to multi-well plates and other liver platforms. PhysioMimix LC12 demonstrated the highest metabolic function with PHHs, with or without THP-1 or Kupffer cells, for up to 10–14 days. iPSC-derived hepatocytes and PHHs co-cultured with additional NPCs demonstrated sub-optimal performance. Power analyses based on replicate experiments and different contexts of use will inform future study designs due to the limited throughput and high cell demand. Overall, this study describes a workflow for independent testing of a complex microphysiological system for specific contexts of use, which may increase end-user adoption in drug development.
Platelet-Rich Fibrin-Conditioned Medium as an Alternative to Fetal Bovine Serum Promotes Osteogenesis of Human Dental Pulp Stem Cells
Authors: Hatori Ayano , Yamakawa Daiki , Al-Maawi Sarah , Dohle Eva , Chikira Jin , Fujii Yasuyuki , Miki Megumu , Sader Robert , Chikazu Daichi , Ghanaati Shahram , Kawase-Koga Yoko
Published: October 2023

Human dental pulp stem cells (DPSCs) exhibit multilineage differentiation capabilities and superior clonogenic and proliferative properties. However, the use of animal-derived components such as FBS raises concerns regarding the clinical application of stem-cell-based therapies. Platelet-rich fibrin (PRF) derived from human blood is rich in fibrin, platelets, and growth factors and acts as a bioactive scaffold for grafting with biomaterials. In this study, we assessed the efficacy of PRF-conditioned medium (CM) in promoting DPSCs proliferation and osteogenic differentiation compared with the standard culture medium supplemented with FBS. A comparison of DPSCs cultured in FBS and PRF-CM revealed no differences in characteristics or morphology. However, cells cultured with PRF-CM exhibited inferior proliferation rates and cell numbers during passage in comparison with those cultured with FBS. In contrast, DPSCs cultured in PRF-CM showed significantly higher levels of calcification, and RT-PCR confirmed that the gene expression levels of markers associated with osteoblast differentiation were significantly increased. The PRF-CM approach offers a convenient, straightforward, and advantageous method for culturing DPSCs, without relying on animal-derived components. In summary, this study introduces a novel application of PRF-CM for enhancing the osteogenesis of DPSCs, which provides an alternative to FBS culture medium and addresses concerns associated with the use of animal-derived components in clinical settings.
Bioactive Components in Fruit Interact with Gut Microbes
Authors: Jin Yuanyuan , Chen Ling , Yu Yufen , Hussain Muhammad , Zhong Hao
Published: October 2023

Fruits contain many bioactive compounds, including polysaccharides, oligosaccharides, polyphenols, anthocyanins, and flavonoids. All of these bioactives in fruit have potentially beneficial effects on gut microbiota and host health. On the one hand, fruit rich in active ingredients can act as substrates to interact with microorganisms and produce metabolites to regulate the gut microbiota. On the other hand, gut microbes could promote health effects in the host by balancing dysbiosis of gut microbiota. We have extensively analyzed significant information on bioactive components in fruits based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Although the deep mechanism of action of bioactive components in fruits on gut microbiota needs further study, these results also provide supportive information on fruits as a source of dietary active ingredients to provide support for the adjunctive role of fruits in disease prevention and treatment.
MicroRNAs: Small but Key Players in Viral Infections and Immune Responses to Viral Pathogens
Authors: Bauer Anais N. , Majumdar Niska , Williams Frank , Rajput Smit , Pokhrel Lok R. , Cook Paul P. , Akula Shaw M.
Published: October 2023

Since the discovery of microRNAs (miRNAs) in C. elegans in 1993, the field of miRNA research has grown steeply. These single-stranded non-coding RNA molecules canonically work at the post-transcriptional phase to regulate protein expression. miRNAs are known to regulate viral infection and the ensuing host immune response. Evolving research suggests miRNAs are assets in the discovery and investigation of therapeutics and diagnostics. In this review, we succinctly summarize the latest findings in (i) mechanisms underpinning miRNA regulation of viral infection, (ii) miRNA regulation of host immune response to viral pathogens, (iii) miRNA-based diagnostics and therapeutics targeting viral pathogens and challenges, and (iv) miRNA patents and the market landscape. Our findings show the differential expression of miRNA may serve as a prognostic biomarker for viral infections in regard to predicting the severity or adverse health effects associated with viral diseases. While there is huge market potential for miRNA technology, the novel approach of using miRNA mimics to enhance antiviral activity or antagonists to inhibit pro-viral miRNAs has been an ongoing research endeavor. Significant hurdles remain in terms of miRNA delivery, stability, efficacy, safety/tolerability, and specificity. Addressing these challenges may pave a path for harnessing the full potential of miRNAs in modern medicine.
Improved Stability and Manufacturability of Nucleocapsid Antigens for SARS-CoV2 Diagnostics through Protein Engineering
Authors: Shukla Esha , Choudhury Lipsa , Rastogi Saurabh , Chawla Arshmeet , Bhattacharya Sanghati , Kaushik Umesh , Mittal Manan , Rathore Anurag Singh , Pandey Gaurav
Published: October 2023

The COVID-19 pandemic has had a significant impact on human health management. A rapid diagnosis of SARS-CoV2 at the point-of-care (POC) is critical to prevent disease spread. As a POC device for remote settings, a LFIA should not require cold-chain maintenance and should be kept at normal temperatures. Antigen stability can be enhanced by addressing instability issues when dealing with fragile components, such as proteinaceous capture antigens. This study used immunologically guided protein engineering to enhance the capture nucleocapsid (NP) antigen stability of SARS-CoV2. A search of the IEDB database revealed that antibodies detecting epitopes are almost uniformly distributed over NP1-419. In contrast, N-terminal stretches of NP1-419 are theoretically more unstable than C-terminal stretches. We identified NP250-365 as a NP stretch with a low instability index and B-cell epitopes. Apart from NP1-419, two other variants (NP121-419 and NP250-365) were cloned, expressed, and purified. The degradation pattern of the proteins was observed on SDS-PAGE after three days of stability studies at −20 °C, 4 °C, and 37 °C. NP1-419 was the most degraded while NP250-365 exhibited the least degradation. Also, NP1-419, NP250-365, and NP121-419 reacted with purified antibodies from COVID-19 patient serum. Our results suggest that NP250-365 may be used as a stable capture antigen in LFIA devices to detect COVID-19.
Mechanical Responses of a Single Myelin Layer: A Molecular Simulation Study
Authors: Maliha Fairuz , Adnan Ashfaq
Published: October 2023

The myelin sheath provides insulation to the brain’s neuron cells, which aids in signal transmission and communication with the body. Degenerated myelin hampers the connection between the glial cells, which are the front row responders during traumatic brain injury mitigation. Thus, the structural integrity of the myelin layer is critical for protecting the brain tissue from traumatic injury. At the molecular level, myelin consists of a lipid bilayer, myelin basic proteins (MBP), proteolipid proteins (PLP), water and ions. Structurally, the myelin sheath is formed by repeatedly wrapping forty or more myelin layers around an axon. Here, we have used molecular dynamic simulations to model and capture the tensile response of a single myelin layer. An openly available molecular dynamic solver, LAMMPS, was used to conduct the simulations. The interatomic potentials for the interacting atoms and molecules were defined using CHARMM force fields. Following a standard equilibration process, the molecular model was stretched uniaxially at a deformation rate of 5 Å/ps. We observed that, at around 10% applied strain, the myelin started to cohesively fail via flaw formation inside the bilayers. Further stretching led to a continued expansion of the defect inside the bilayer, both radially and transversely. This study provides the cellular-level mechanisms of myelin damage due to mechanical load.
Unraveling the Link between Periodontitis and Coronavirus Disease 2019: Exploring Pathogenic Pathways and Clinical Implications
Authors: Lin En-Chin , Chiang Yi-Chun , Lin Hsuan-Yu , Tseng Shao-Yu , Hsieh Yu-Ting , Shieh Jer-An , Huang Yu-Hao , Tsai Hsiang-Tai , Feng Sheng-Wei , Peng Tzu-Yu , Lee I-Ta
Published: October 2023

Periodontitis involves the inflammation of the periodontal tissue, leading to tissue loss, while coronavirus disease 2019 (COVID-19) is a highly transmissible respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is amplified by poor systemic health. Key facilitators of SARS-CoV-2’s entry into host cells are angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). This review reveals that periodontal pockets can serve as a hotspot for virus accumulation, rendering surrounding epithelia more susceptible to infection. Given that ACE2 is expressed in oral mucosa, it is reasonable to suggest that poor periodontal health could increase the risk of COVID-19 infection. However, recent studies have not provided sufficient evidence to imply a significant effect of COVID-19 on periodontal health, necessitating further and more long-term investigations. Nevertheless, there are hypotheses linking the mechanisms of the two diseases, such as the involvement of interleukin-17 (IL-17). Elevated IL-17 levels are observed in both COVID-19 and periodontitis, leading to increased osteoclast activity and bone resorption. Lastly, bidirectional relationships between periodontitis and systemic diseases like diabetes are acknowledged. Given that COVID-19 symptoms may worsen with these conditions, maintaining good oral health and managing systemic diseases are suggested as potential ways to protect against COVID-19.
A Review of Cyclic Phosphatidic Acid and Other Potential Therapeutic Targets for Treating Osteoarthritis
Authors: Tsukahara Tamotsu , Imamura Shigeyuki , Morohoshi Toshiro
Published: October 2023

Osteoarthritis (OA), a chronic degenerative joint disease, is the most common form of arthritis. OA occurs when the protective cartilage that cushions the ends of bones gradually breaks down. This leads to the rubbing of bones against each other, resulting in pain and stiffness. Cyclic phosphatidic acid (cPA) shows promise as a treatment for OA. In this article, we review the most recent findings regarding the biological functions of cPA signaling in mammalian systems, specifically in relation to OA. cPA is a naturally occurring phospholipid mediator with unique cyclic phosphate rings at the sn-2 and sn-3 positions in the glycerol backbone. cPA promotes various responses, including cell proliferation, migration, and survival. cPA possesses physiological activities that are distinct from those elicited by lysophosphatidic acid; however, its biochemical origin has rarely been studied. Although there is currently no cure for OA, advances in medical research may lead to new therapies or strategies in the future, and cPA has potential therapeutic applications.
Inflammatory and Anti-Inflammatory Parameters in PCOS Patients Depending on Body Mass Index: A Case-Control Study
Authors: Vasyukova Elena , Zaikova Ekaterina , Kalinina Olga , Gorelova Inga , Pyanova Irina , Bogatyreva Elena , Vasilieva Elena , Grineva Elena , Popova Polina
Published: October 2023

Background: it has been suggested that chronic low-grade inflammation plays an important role in the pathogenesis of polycystic ovary syndrome (PCOS). According to previous studies, it remains unclear which cytokines influence the development of this syndrome and whether their increase is associated with the presence of excess weight/obesity or is an independent factor. The aim of our research was to determine the parameters of chronic inflammation in women with PCOS in comparison with healthy women in the normal weight and the overweight subgroups. Methods: This case-control study included 44 patients with PCOS (19 women with a body mass index (BMI) < 25 kg/m² and 25 women with a BMI ≥ 25 kg/m²) and 45 women without symptoms of PCOS (22 women with a BMI < 25 kg/m² and 23 women with a BMI ≥ 25 kg/m²). Thirty-two cytokines were analyzed in the plasma of the participants using Immunology multiplex assay HCYTA-60K-PX48 (Merck Life Science, LLC, Germany). Results: Cytokines: interleukin-1 receptor antagonist (IL-1 RA), IL-2, IL-6, IL-17 E, IL-17 A, IL-18, and macrophage inflammatory protein-1 alpha (MIP-1 α) were increased in women with PCOS compared to controls, both in lean and overweight/obese subgroups (p < 0.05). Moreover, only lean women with PCOS had higher levels of IL-1 alpha, IL-4, IL-9, IL-12, IL-13, IL-15, tumor necrosis factor (TNF- α) alpha and beta, soluble CD40 and its ligand (SCD40L), fractalkine (FKN), monocyte-chemotactic protein 3 (MCP-3), and MIP-1 β compared to the control group (p < 0.05). IL-22 was increased in the combined group of women with PCOS (lean and overweight/obese) compared to the control group (p = 0.012). Conclusion: Chronic low-grade inflammation is an independent factor affecting the occurrence of PCOS and does not depend on the presence of excess weight/obesity. For the first time, we obtained data on the increase in such inflammatory parameters as IL-9, MCP-3, and MIP-1α in women with PCOS.