bluuebunny/crossref_metadata_2025 huggingface dataset:
Limno-Terrestrial Tardigrada of Sub-Antarctic Islands—An Annotated Review
Authors: Degma Peter , Gábrišová Nina
Published: October 2023

Research on the limno-terrestrial Tardigrada fauna of the Sub-Antarctic zone began almost 120 years ago. Here we present an overview of the literature data on the presence of tardigrades on sub-Antarctic islands, including the substrates on which they have been found. From 32 published sources, we found original data on the occurrence of 49 currently valid species on six sub-Antarctic islands/island groups. Of these, 9 species (18%) were originally described from this zone, another 13 species (26%) were described from Continental or Maritime Antarctica, almost half of these species (22 species—45%) were originally described from European localities, and the remaining 5 species (10%) were originally described from South America, Africa, or Australia. The validity of the records of individual species is discussed. We consider the presence of 29 species in the Sub-Antarctic to be doubtful. We ascertained a total of 90 combinations of species and islands or island groups. More than half (64%) of these will require confirmation in the future because we currently consider them doubtful. We can conclude that the tardigrade fauna of the sub-Antarctic islands is only very superficially known, and the occurrence of most species in this zone must be verified.
Correction: Jobe et al. Herbivory by Geese Inhibits Tidal Freshwater Wetland Restoration Success. Diversity 2022, 14, 278
Authors: Jobe Justus , Krafft Cairn , Milton Mikaila , Gedan Keryn
Published: October 2023

In the original publication [...]
Improving the Quality of Care for Cancer Patients through Oncological Second Opinions in a Comprehensive Cancer Center: Feasibility of Patient-Initiated Second Opinions through a Health-Insurance Service Point
Authors: Schulmeyer Carla E. , Beckmann Matthias W. , Fasching Peter A. , Häberle Lothar , Golcher Henriette , Kunath Frank , Wullich Bernd , Emons Julius
Published: October 2023

Background: To improve the quality and cost-effectiveness of care, cancer patients can obtain a second medical opinion on their treatment. Validation of the diagnostic procedure (e.g., imaging), diagnosis, and treatment recommendation allows oncological therapy to be applied in a more targeted way, optimizing interdisciplinary care. This study describes patients who received second opinions at the Comprehensive Cancer Center for Erlangen–Nuremberg metropolitan area in Germany over a 6-year period, as well as the amount of time spent on second-opinion counseling. Methods: This prospective, descriptive, single-center observational study included 584 male and female cancer patients undergoing gynecological, urologic, or general surgery who sought a second medical opinion. The extent to which the first opinion complied with standard guidelines was assessed solely descriptively. Results: The first opinion was in accordance with the guidelines and complete in 54.5% of the patients, and guideline compliant but incomplete in 13.2%. The median time taken to form a second opinion was 225 min, and the cancer information service was contacted by patients an average of eight times. Conclusions: The initial opinion was guideline compliant and complete in every second case. Without a second opinion, the remaining patients would have been denied a guideline-compliant treatment recommendation. Obtaining a second opinion gives patients an opportunity to receive a guideline-compliant treatment recommendation and enables them to benefit from newer, individualized therapeutic approaches in clinical trials. Establishing patient-initiated second opinions via central contact points appears to be a feasible option for improving guideline compliance.
Remaining Useful Life Prediction of Rolling Bearings Based on Multi-scale Permutation Entropy and ISSA-LSTM
Authors: Wang Hongju , Zhang Xi , Ren Mingming , Xu Tianhao , Lu Chengkai , Zhao Zicheng
Published: October 2023

The performance of bearings plays a pivotal role in determining the dependability and security of rotating machinery. In intricate systems demanding exceptional reliability and safety, the ability to accurately forecast fault occurrences during operation holds profound significance. Such predictions serve as invaluable guides for crafting well-considered reliability strategies and executing maintenance practices aimed at enhancing reliability. In the real operational life of bearings, fault information often gets submerged within the noise. Furthermore, employing Long Short-Term Memory (LSTM) neural networks for time series prediction necessitates the configuration of appropriate parameters. Manual parameter selection is often a time-consuming process and demands substantial prior knowledge. In order to ensure the reliability of bearing operation, this article investigates the application of three advanced techniques—Maximum Correlation Kurtosis Deconvolution (MCKD), Multi-Scale Permutation Entropy (MPE), and Long Short-Term Memory (LSTM) recurrent neural networks—for the prediction of the remaining useful life (RUL) of rolling bearings. The improved sparrow search algorithm (ISSA) is employed for configuring parameters in the Long Short-Term Memory (LSTM) network. Each technique’s principles, methodologies, and applications are comprehensively reviewed, offering insights into their respective strengths and limitations. Case studies and experimental evaluations are presented to assess their performance in RUL prediction. Findings reveal that MCKD enhances fault signatures, MPE captures complexity, and LSTM excels in modeling temporal patterns. The root mean square error of the prediction results is 0.007. The fusion of these techniques offers a comprehensive approach to RUL prediction, leveraging their unique attributes for more accurate and reliable predictions.
Analysis of Control Strategy of Arc Plasma Power Supply Inverter Module
Authors: Li Yue , Yu Hailong , Jiang Chuan , Jin Yong
Published: October 2023

The inverter module serves as a critical component in the conversion of electrical energy within arc plasma power sources, exerting a profound influence on the overall performance and stability of the power supply. Consequently, the meticulous design and precise control of the inverter module are of paramount importance in ensuring the effective operation and application of arc plasma power sources. This paper introduces a dual-closed-loop control system, integrating a voltage outer loop with a current inner loop, as the cornerstone of its inverter module design. It also undertook a comprehensive comparative analysis of various voltage-control strategies, encompassing four control methods (PI, PID, PR, QPR) and two modulation techniques (bipolar modulation and unipolar, carrier-based modulation) under diverse operating conditions. Additionally, simulation experiments were conducted on a prototype 10 kW inverter module using the Matlab/Simulink simulation platform, with evaluation criteria including waveform tracking performance, voltage waveform distortion rate, and steady-state error. The results indicate that in low-frequency operating conditions, the voltage-control strategy employing QPR control plus unipolar, carrier-based modulation, and in high-frequency operating conditions, the voltage-control strategy utilizing PI control plus unipolar, carrier-based modulation exhibited superior waveform tracking performance. The waveform distortion rates were measured at below 0.47% and 4.2%, respectively, aligning perfectly with the stringent standards of IEEE 519. This research provides valuable theoretical support and practical guidance for future engineering endeavors in the field of inverters.
The Design of a Wide-Dynamic-Range and High-Linearity RMS Power Detector for mm-Wave Applications in 65 nm CMOS
Authors: Wu Xi-An , Zhang Zechen , Liu Hong , Tian Tong
Published: October 2023

In this paper, a wide dynamic range RMS power detector with an operating frequency from 24 GHz to 35 GHz mm-wave frequency is presented. The power detector is fabricated in a 65 nm CMOS process. It is composed of a power detector unit, a radio frequency signal attenuator and a linear proportional voltage adder. The equalization technique is used to achieve a good linearity performance. The input dynamic range of the power detector is expanded by using one radio frequency signal attenuator and five power detector units. The simulation results show the slope of VOUT versus input power remaining constant at around 0.06 V/dBm when the input signal power varies from −10 dBm to 10 dBm. The difference in output voltage varies by only 0.03 V when the input power varies from −10 to 0 dBm and 0 to 10 dBm. These all indicate that the proposed power detector achieves a good linearity performance. The measured results also show that the proposed power detector achieves a wide dynamic range and a high linearity performance from −10 dBm to 10 dBm. The detectable dynamic range is enhanced by 3.3 times compared to that achieved when only using one single power detector unit, while it only consumes about 0.75 mW under a 1.2 V supply voltage.
Guidelines for Area Ratio between Metal Lines and Vias to Improve the Reliability of Interconnect Systems in High-Density Electronic Devices
Authors: Hong Tae Yeong , Kim Sarah Eunkyung , Park Jong Kyung , Hong Seul Ki
Published: October 2023

This research was conducted in the context of the semiconductor market, with a demand for high-performance and highly integrated semiconductor systems that simultaneously enhance performance and reduce chip size. Scaling down the metal line and via in back-end-of-line (BEOL) structures is essential to efficiently deliver power to scaling down devices. This study utilized the finite element method (FEM) simulation technique to model the heat and current distribution for enhancing the efficiency of scaled-down structures. Due to current flow bottlenecks, an increase in the area ratio of the via to metal line (as the via becomes relatively smaller) leads to a temperature rise due to Joule heating. This trend follows a second-degree polynomial form, and the point where the temperature doubles compared to when the area ratio is one is situated at an area ratio of three. The temperature increase caused by Joule heating ultimately leads to destruction of the via, which directly affects the reliability of the BEOL structure. These experimental results can provide guidelines for designing with reliability considerations in mind, particularly in today’s semiconductor systems where significant scaling down is required in interconnect structures. They can also be widely applied to research aimed at developing interconnect structures that enhance reliability.
Task-Based Visual Attention for Continually Improving the Performance of Autonomous Game Agents
Authors: Ulu Eren , Capin Tolga , Çelikkale Bora , Celikcan Ufuk
Published: October 2023

Deep Reinforcement Learning (DRL) has been effectively performed in various complex environments, such as playing video games. In many game environments, DeepMind’s baseline Deep Q-Network (DQN) game agents performed at a level comparable to that of humans. However, these DRL models require many experience samples to learn and lack the adaptability to changes in the environment and handling complexity. In this study, we propose Attention-Augmented Deep Q-Network (AADQN) by incorporating a combined top-down and bottom-up attention mechanism into the DQN game agent to highlight task-relevant features of input. Our AADQN model uses a particle-filter -based top-down attention that dynamically teaches an agent how to play a game by focusing on the most task-related information. In the evaluation of our agent’s performance across eight games in the Atari 2600 domain, which vary in complexity, we demonstrate that our model surpasses the baseline DQN agent. Notably, our model can achieve greater flexibility and higher scores at a reduced number of time steps.Across eight game environments, AADQN achieved an average relative improvement of 134.93%. Pong and Breakout games both experienced improvements of 9.32% and 56.06%, respectively. Meanwhile, SpaceInvaders and Seaquest, which are more intricate games, demonstrated even higher percentage improvements, with 130.84% and 149.95%, respectively. This study reveals that AADQN is productive for complex environments and produces slightly better results in elementary contexts.
A Review for the Euler Number Computing Problem
Authors: Yao Bin , He Haochen , Kang Shiying , Chao Yuyan , He Lifeng
Published: October 2023

In a binary image, the Euler number is a crucial topological feature that holds immense significance in image understanding and image analysis owing to its invariance under scaling, rotation, or any arbitrary rubber-sheet transformation of images. This paper focuses on the Euler number computing problem in a binary image. The state-of-the-art Euler number computing algorithms are reviewed, which obtain the Euler number through different techniques, such as definition, features of binary images, and special data structures representing forms of binary images, and we explain the main principles and strategies of the algorithms in detail. Afterwards, we present the experimental results to bring order of the prevailing Euler number computing algorithms in 8-connectivity cases. Then, we discuss both the parallel implementation and the hardware implementation of algorithms for calculating the Euler number and present the algorithm extension for 3D image Euler number computation. Lastly, we aim to outline forthcoming efforts concerning the computation of the Euler number.
Comparison of Selected Machine Learning Algorithms in the Analysis of Mental Health Indicators
Authors: Bieliński Adrian , Rojek Izabela , Mikołajewski Dariusz
Published: October 2023

Machine learning is increasingly being used to solve clinical problems in diagnosis, therapy and care. Aim: the main aim of the study was to investigate how the selected machine learning algorithms deal with the problem of determining a virtual mental health index. Material and Methods: a number of machine learning models based on Stochastic Dual Coordinate Ascent, limited-memory Broyden–Fletcher–Goldfarb–Shanno, Online Gradient Descent, etc., were built based on a clinical dataset and compared based on criteria in the form of learning time, running time during use and regression accuracy. Results: the algorithm with the highest accuracy was Stochastic Dual Coordinate Ascent, but although its performance was high, it had significantly longer training and prediction times. The fastest algorithm looking at learning and prediction time, but slightly less accurate, was the limited-memory Broyden–Fletcher–Goldfarb–Shanno. The same data set was also analyzed automatically using ML.NET. Findings from the study can be used to build larger systems that automate early mental health diagnosis and help differentiate the use of individual algorithms depending on the purpose of the system.
Advanced Examination of User Behavior Recognition via Log Dataset Analysis of Web Applications Using Data Mining Techniques
Authors: Borowiec Marcin , Rak Tomasz
Published: October 2023

As web systems based on containerization increasingly attract research interest, the need for effective analytical methods has heightened, with an emphasis on efficiency and cost reduction. Web client simulation tools have been utilized to further this aim. While applying machine learning (ML) methods for anomaly detection in requests is prevalent, predicting patterns in web datasets is still a complex task. Prior approaches incorporating elements such as URLs, content from web pages, and auxiliary features have not provided any satisfying results. Moreover, such methods have not significantly improved the understanding of client behavior and the variety of request types. To overcome these shortcomings, this study introduces an incremental approach to request categorization. This research involves an in-depth examination of various established classification techniques, assessing their performance on a selected dataset to determine the most effective model for classification tasks. The utilized dataset comprises 8 million distinct records, each defined by performance metrics. Upon conducting meticulous training and testing of multiple algorithms from the CART family, Extreme Gradient Boosting was deemed to be the best-performing model for classification tasks. This model outperforms prediction accuracy, even for unrecognized requests, reaching a remarkable accuracy of 97% across diverse datasets. These results underline the exceptional performance of Extreme Gradient Boosting against other ML techniques, providing substantial insights for efficient request categorization in web-based systems.
Analyzing Factors Affecting Micro-Mobility and Predicting Micro-Mobility Demand Using Ensemble Voting Regressor
Authors: Ko Jiyoung , Byun Yung-Cheol
Published: October 2023

Several mobility vehicle rental companies have emerged owing to the increased preference for shared mobility as a short-distance transit option. These shared-mobility vehicles must be strategically placed at different locations to enable easy access to customers. However, without prior knowledge of the occurrence of rental demand, it becomes challenging for companies to respond quickly. In this study, we analyzed the factors affecting rental demand for shared electric mobility vehicles by utilizing actual data from the company EV PASS and predicted rental demand to ensure that the vehicles were distributed effectively, allowing customers to receive timely service. We compared the performance of machine learning models such as the Extra Trees regressor, CatBoost regressor, and LightGBM (Light Gradient Boosting Machine) models in predicting the demand for shared mobility vehicles. Additionally, we explored the use of an ensemble technique called voting regressor to reduce errors with an R2 score of 0.7629, it outperformed all the individual models. The analysis revealed that factors including humidity, precipitation, and solar radiation have a significant influence on rental demand. Based on the findings of this study, companies can effectively manage equipment and personnel, providing better shared electric mobility rental services, leading to increased customer satisfaction.
Simulation Model for Sustainable Management of the Air Cargo Screening Process
Authors: Kierzkowski Artur , Kisiel Tomasz , Uchroński Piotr , Vidović Andrija
Published: October 2023

This article presents a novel model for the management of air cargo shipment screening. Previous research has focused solely on making the air cargo screening process as efficient as possible. These scientific papers did not look at the costs generated by the improper selection of technical equipment for the cargo handled. The challenge is to be able to complete the entire screening process in the expected time with the lowest possible energy consumption. This article presents a discrete-event simulation model for the balanced planning of air cargo screening. The innovation of this solution is the parallel analysis of process performance and energy consumption. The user receives two variables (energy consumption and process execution time) in relation to the number of cargo shipments handled. The user can therefore control the process by taking these variables into account. This will allow the user to find the right system configuration for the preferences desired. It is possible to strike a balance between achieved process efficiency and energy consumption. This approach has not been considered so far. Given that energy consumption constitutes 15% of operating costs at airports, this is an important issue that needs to be addressed.
Inverted Soil Mounding as a Restoration Approach of Seismic Lines in Boreal Peatlands: Implications on Plant and Arthropod Abundance and Diversity
Authors: Echiverri Laureen , Pinzon Jaime , Dabros Anna
Published: October 2023

In northern Alberta, Canada, much of treed boreal peatlands are fragmented by seismic lines—linear disturbances where trees and shrubs are cleared for the exploration of fossil fuel reserves. Seismic lines have been shown to have slow tree regeneration, likely due to the loss of microtopography during the creation of seismic lines. Inverted soil mounding is one of the treatments commonly applied in Alberta to restore seismic lines and mitigate the use of these corridors by wildlife and humans. We assessed the effects of mounding on understory plants and arthropod assemblages three years after treatment application. We sampled five mounded and five untreated seismic lines and their adjacent treed fens (reference fens). Compared to reference fens, mounded seismic lines showed on average lower bryophyte (6.5% vs. 98.1%) and total understory cover (47.2% vs. 149.8%), ground-dwelling spider abundance (226.0 vs. 383 individuals), richness (87.2 vs. 106.4 species) and diversity (19.0 vs. 24.6 species), rove beetle abundance (35.2 vs. 84.8 individuals), and ant richness (9.0 vs. 12.9 species). In contrast, rove beetle and ground beetle richness (39.0 and 14.5 species, respectively) and diversity (16.8 and 7.8 species, respectively) were higher on mounded seismic lines compared to reference fens (richness: 18.0 and 7.5 species, respectively; diversity: 7.0 and 3.8 species, respectively). This is one of the first studies to assess arthropod responses to restoration efforts in the context of oil and gas disturbances in North America, and our results highlight the need to incorporate multiple taxa when examining the impact of such treatments.
Aerial Imaging-Based Fuel Information Acquisition for Wildfire Research in Northeastern South Korea
Authors: Kwon Kyeongnam , Kwon Chun Geun , Lee Ye-eun , Kim Sung Yong , Im Seong-kyun
Published: October 2023

Tree detection and fuel amount and distribution estimation are crucial for the investigation and risk assessment of wildfires. The demand for risk assessment is increasing due to the escalating severity of wildfires. A quick and cost-effective method is required to mitigate foreseeable disasters. In this study, a method for tree detection and fuel amount and distribution prediction using aerial images was proposed for a low-cost and efficient acquisition of fuel information. Three-dimensional (3D) fuel information (height) from light detection and ranging (LiDAR) was matched to two-dimensional (2D) fuel information (crown width) from aerial photographs to establish a statistical prediction model in northeastern South Korea. Quantile regression for 0.05, 0.5, and 0.95 quantiles was performed. Subsequently, an allometric tree model was used to predict the diameter at the breast height. The performance of the prediction model was validated using physically measured data by laser distance meter triangulation and direct measurement from a field survey. The predicted quantile, 0.5, was adequately matched to the measured quantile, 0.5, and most of the measured values lied within the predicted quantiles, 0.05 and 0.95. Therefore, in the developed prediction model, only 2D images were required to predict a few of the 3D fuel details. The proposed method can significantly reduce the cost and duration of data acquisition for the investigation and risk assessment of wildfires.
Drought Variations in the Yili Basin, Northwest China since AD 1673 Based on Tree-Ring Width
Authors: Wu Yifan , Liu Yu , Li Qiang , Cai Qiufang , Ren Meng , Song Huiming , Sun Changfeng , Zhang Tongwen , Ye Mao
Published: October 2023

The Yili Basin represents a typical region influenced by the Westerlies, and as a result of the substantial precipitation delivered by these winds, it has emerged as a significant hub for agricultural and animal husbandry activities in Central Asia. This study established a 419-year tree-ring width chronology, utilizing living Picea schrenkiana samples from two sampling sites in the Yili Basin. Correlation analysis showed that the standard tree-ring width chronology had the best correlation with the Palmer Drought Severity Index from the previous August to the current May (PDSIP8C5) (r = 0.614, n = 59, p < 0.001). Therefore, we reconstructed PDSIP8C5 variations from 1673 to 2018. The reconstruction results reveal eight wet and seven dry periods during the past 346 years. In the reconstructed series, droughts are particularly pronounced around 1770 and 1920, and the PDSI shows a significant long-term wetting trend since the 1980s. The solar activity, North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO) jointly influenced the regional moisture variation.
Potential of Incorporating a Functional Probiotic Encapsulant in Whipped Cream
Authors: Gaba Kritika , Anand Sanjeev
Published: October 2023

The probiotic foods market is expanding; however, maintaining probiotics viability is challenging during manufacturing and storage conditions. In this study, a functional ingredient containing whey protein hydrolysate-encapsulated probiotics was standardized into whipped cream, followed by its characterization and storage stability study. The whipped cream was prepared under standard laboratory conditions, and the encapsulant was added at 0.1% and 1% w/w levels. The samples were further characterized through viable probiotic counts, physicochemical and microstructural analysis. Analyses were conducted in triplicates, and ANOVA was applied to differentiate between the mean values (p < 0.05). The whipped cream variant with 1% w/w encapsulant addition exhibited higher viability of Lactobacillus acidophilus ATCC4356 (LA5) (7.38 ± 0.26 log10CFU/g) and Bifidobacterium animalis ssp. Lactis ATCC27536 (BB12) (7.25 ± 0.56 log10CFU/g) along with enhanced physicochemical properties as compared to the LA5 (6.53 ± 0.45 log10CFU/g) and BB12 (6.41 ± 0.39 log10CFU/g) counts in the 0.1% variant. This was attributed to the thicker and uniform encapsulant deposition at the O/W interface observed in micro-images. The storage stability results did not show a substantial difference in viability for encapsulated probiotics compared to the control. The encapsulant also maintained the 1:1 ratio of LA5 and BB12. Thus, a value-added range of dairy products could be introduced with enhanced physicochemical attributes.
The 6G Ecosystem as Support for IoE and Private Networks: Vision, Requirements, and Challenges
Authors: Serôdio Carlos , Cunha José , Candela Guillermo , Rodriguez Santiago , Sousa Xosé Ramón , Branco Frederico
Published: October 2023

The emergence of the sixth generation of cellular systems (6G) signals a transformative era and ecosystem for mobile communications, driven by demands from technologies like the internet of everything (IoE), V2X communications, and factory automation. To support this connectivity, mission-critical applications are emerging with challenging network requirements. The primary goals of 6G include providing sophisticated and high-quality services, extremely reliable and further-enhanced mobile broadband (feMBB), low-latency communication (ERLLC), long-distance and high-mobility communications (LDHMC), ultra-massive machine-type communications (umMTC), extremely low-power communications (ELPC), holographic communications, and quality of experience (QoE), grounded in incorporating massive broad-bandwidth machine-type (mBBMT), mobile broad-bandwidth and low-latency (MBBLL), and massive low-latency machine-type (mLLMT) communications. In attaining its objectives, 6G faces challenges that demand inventive solutions, incorporating AI, softwarization, cloudification, virtualization, and slicing features. Technologies like network function virtualization (NFV), network slicing, and software-defined networking (SDN) play pivotal roles in this integration, which facilitates efficient resource utilization, responsive service provisioning, expanded coverage, enhanced network reliability, increased capacity, densification, heightened availability, safety, security, and reduced energy consumption. It presents innovative network infrastructure concepts, such as resource-as-a-service (RaaS) and infrastructure-as-a-service (IaaS), featuring management and service orchestration mechanisms. This includes nomadic networks, AI-aware networking strategies, and dynamic management of diverse network resources. This paper provides an in-depth survey of the wireless evolution leading to 6G networks, addressing future issues and challenges associated with 6G technology to support V2X environments considering presenting +challenges in architecture, spectrum, air interface, reliability, availability, density, flexibility, mobility, and security.
The Nephroprotective Potential of Brassica nigra Sprout Hydroalcoholic Extract against Carbon Tetrachloride-Induced Renal Toxicity in Rats
Authors: Aljutaily Thamer , Almutairi Sarah M. , Alharbi Hend F.
Published: October 2023

The nephroprotective potential of the Brassica nigra sprout (BNS) hydroalcoholic extract against carbon tetrachloride (CCl4)-induced renal toxicity in rats was the object of this study. B. nigra sprouts were prepared in the lab to monitor the bio-changes in bioactive compounds during the sprouting for up to 7 days at 17 ± 1 °C and 90% relative humidity. Subsequently, 6-day sprouts of B. nigra were selected according to their phenolics and antioxidant activity, extracted, and examined for their nephroprotective and antioxidative stress potential at 250 and 500 mg sprout extracts kg−1 bw, in vivo. Weight gain, organ weight, lipid profile, atherogenic index, kidney functions, and oxidative stress biomarkers were assessed. The results indicated that the most proficient treatment for weight gain improvement was BNS extract at 500 mg kg−1. BNS at 250 mg kg−1 was remarked as the lowest weight gain enhancer compared to the NR group. A significant increase in TG, TC, LDL-c, and VLDL-c levels in the rats with CCl4-induced renal toxicity, and a significant decrease in HDL level, was noted. The administration of the BNS extract at 250 and 500 mg kg−1 considerably attenuated TG, TC, LDL-c, and VLDL-c levels, compared to the NR group. The most efficient treatment for improving the lipid profile was the BNS extract at 500 mg kg−1, even better than 250 mg kg−1. Administrating the BNS extract substantially attenuated the alterations in the creatinine, urea, and BUN caused by the CCl4 injection. The most efficient improvement was markedly recorded with the BNS extract at 500 mg kg−1, compared to the NR group. The rats treated with the BNS extract showed significant enhancement in GSH, CAT, and SOD activities and a considerable reduction in MDA levels. Administering the BNS extract at 250 and 500 mg kg−1 can efficiently reverse CCl4 inhibition of antioxidant enzyme activities, significantly increase GSH, CAT, and SOD, and decrease the MDA levels dose-dependently. The BNS extract at 250 and 500 mg kg−1 exhibits nephroprotection and antioxidative stress in a dose-dependent matter. The total nephroprotection % was recorded at 65.18% and 99.21% for rats treated with 250 and 500 mg kg−1, respectively. These findings could prove and potentiate the nephroprotective activities of the BNS extract in the range of the given doses. Further clinical studies are highly recommended for confirming the nephroprotection efficiency of the B. nigra sprout.
Unveiling the Mysteries of RAS Signaling: A Journey of Discovery and Breakthroughs
Authors: Castellano Esther
Published: October 2023

In the realm of molecular biology, few terms evoke as much curiosity, fascination, and determination as RAS [...]
Complete Mitochondrial DNA Genome Variation in the Swedish Population
Authors: Sturk-Andreaggi Kimberly , Bodner Martin , Ring Joseph D. , Ameur Adam , Gyllensten Ulf , Parson Walther , Marshall Charla , Allen Marie
Published: October 2023

The development of complete mitochondrial genome (mitogenome) reference data for inclusion in publicly available population databases is currently underway, and the generation of more high-quality mitogenomes will only enhance the statistical power of this forensically useful locus. To characterize mitogenome variation in Sweden, the mitochondrial DNA (mtDNA) reads from the SweGen whole genome sequencing (WGS) dataset were analyzed. To overcome the interference from low-frequency nuclear mtDNA segments (NUMTs), a 10% variant frequency threshold was applied for the analysis. In total, 934 forensic-quality mitogenome haplotypes were characterized. Almost 45% of the SweGen haplotypes belonged to haplogroup H. Nearly all mitogenome haplotypes (99.1%) were assigned to European haplogroups, which was expected based on previous mtDNA studies of the Swedish population. There were signature northern Swedish and Finnish haplogroups observed in the dataset (e.g., U5b1, W1a), consistent with the nuclear DNA analyses of the SweGen data. The complete mitogenome analysis resulted in high haplotype diversity (0.9996) with a random match probability of 0.15%. Overall, the SweGen mitogenomes provide a large mtDNA reference dataset for the Swedish population and also contribute to the effort to estimate global mitogenome haplotype frequencies.
Challenges in the Definitive Diagnosis of Niemann–Pick Type C—Leaky Variants and Alternative Transcripts
Authors: Encarnação Marisa , Ribeiro Isaura , David Hugo , Coutinho Maria Francisca , Quelhas Dulce , Alves Sandra
Published: October 2023

Niemann–Pick type C (NPC, ORPHA: 646) is a neuro-visceral, psychiatric disease caused predominantly by pathogenic variants in the NPC1 gene or seldom in NPC2. The rarity of the disease, and its wide range of clinical phenotypes and ages of onset, turn the diagnosis into a significant challenge. Other than the detailed clinical history, the typical diagnostic work-up for NPC includes the quantification of pathognomonic metabolites. However, the molecular basis diagnosis is still of utmost importance to fully characterize the disorder. Here, the authors provide an overview of splicing variants in the NPC1 and NPC2 genes and propose a new workflow for NPC diagnosis. Splicing variants cover a significant part of the disease-causing variants in NPC. The authors used cDNA analysis to study the impact of such variants, including the collection of data to classify them as leaky or non-leaky pathogenic variants. However, the presence of naturally occurring spliced transcripts can misdiagnose or mask a pathogenic variant and make the analysis even more difficult. Analysis of the NPC1 cDNA in NPC patients in parallel with controls is vital to assess and detect alternatively spliced forms. Moreover, nonsense-mediated mRNA decay (NMD) analysis plays an essential role in evaluating the naturally occurring transcripts during cDNA analysis and distinguishing them from other pathogenic variants’ associated transcripts.
Detection Rate and Spectrum of Pathogenic Variations in a Cohort of 83 Patients with Suspected Hereditary Risk of Kidney Cancer
Authors: Ouedraogo Zangbéwendé Guy , Ceruti Florian , Lepage Mathis , Gay-Bellile Mathilde , Uhrhammer Nancy , Ponelle-Chachuat Flora , Bidet Yannick , Privat Maud , Cavaillé Mathias
Published: October 2023

Hereditary predisposition to cancer affects about 3–5% of renal cancers. Testing criteria have been proposed in France for genetic testing of non-syndromic renal cancer. Our study explores the detection rates associated with our testing criteria. Using a comprehensive gene panel including 8 genes related to renal cancer and 50 genes related to hereditary predisposition to other cancers, we evaluated the detection rate of pathogenic variants in a cohort of 83 patients with suspected renal cancer predisposition. The detection rate was 7.2% for the renal cancer genes, which was 2.41-fold higher than the estimated 3% proportion of unselected kidney cases with inherited risk. Pathogenic variants in renal cancer genes were observed in 44.5% of syndromic cases, and in 2.7% of non-syndromic cases. Incidental findings were observed in CHEK2, MSH2, MUTYH and WRN. CHEK2 was associated with renal cancer (OR at 7.14; 95% CI 1.74–29.6; p < 0.003) in our study in comparison to the gnomAD control population. The detection rate in renal cancer genes was low in non-syndromic cases. Additional causal mechanisms are probably involved, and further research is required to find them. A study of the management of renal cancer risk for CHEK2 pathogenic variant carriers is needed.
Editorial on Genetic Diversity of Plant Tolerance to Environmental Restraints
Authors: Dolferus Rudy , Onyemaobi Olive
Published: October 2023

Environmental restraints like cold, drought and heat adversely affect growth and development in different ways and at different plant developmental stages, leading to reduced crop yield [...]
Mapping of a Stripe Rust Resistance Gene Yr72 in the Common Wheat Landraces AUS27506 and AUS27894 from the Watkins Collection
Authors: Chhetri Mumta , Miah Hanif , Wong Debbie , Hayden Matthew , Bansal Urmil , Bariana Harbans
Published: October 2023

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is among the major threats to global wheat production. The common wheat landraces AUS27506 and AUS27894 displayed stripe rust resistance against several commercially prevailing Pst pathotypes. These genotypes were crossed with a stripe-rust-susceptible landrace AUS27229 to understand the inheritance of resistance and to determine the genomic location(s) of underlying gene(s). F3 generations of crosses AUS27506/AUS27229 and AUS27894/AUS27229 showed monogenic segregation for stripe rust resistance under greenhouse conditions. The absence of segregation for stripe rust response among the AUS27506/AUS27894-derived F3 population suggested that both genotypes carry the same gene. The stripe rust resistance gene carried by AUS27506 and AUS27894 was tentatively named YrAW4. A bulked segregant analysis placed YrAW4 in the long arm of chromosome 2B. The AUS27506/AUS27229 F3 population was enhanced to develop an F6 recombinant inbred line (RIL) population for detailed mapping of chromosome 2BL. DArT-based SSR, STS and SNP markers were employed to enrich the 2BL map. DArT-based STS markers sun481 and SNP marker IWB12294 flanked YrAW4 proximally (1.8 cM) and distally (1.2 cM), respectively. Deletion mapping placed sun481 in the deletion bin 2BL-5. All stripe rust resistance genes, previously located on chromosome 2BL, neither express an infection type like YrAW4, nor are they mapped in the deletion bin 2BL-5. Hence, YrAW4 represented a new locus and was formally named Yr72. The usefulness of the markers IWB12294 and sun481 in marker-assisted selection was demonstrated by the amplification of alleles that are different to that linked with Yr72 in 19 common wheat and two durum wheat cultivars.
Development, Objectives and Operation of Return-of-Service Bursary Schemes as an Investment to Build Health Workforce Capacity in South Africa: A Multi-Methods Study
Authors: Mabunda Sikhumbuzo , Durbach Andrea , Chitha Wezile , Bodzo Paidamoyo , Angell Blake , Joshi Rohina
Published: October 2023

Background: South Africa uses government-funded return-of-service (RoS) schemes to train, recruit and retain skilled health professionals in underserved areas. These educate health professionals locally or internationally in return for a commitment to serve in a specified area for an agreed period. While such schemes are used widely and are funded by substantial public funds, their exact makeup differs across jurisdictions, and little is known about why these differences have emerged or how they influence their effectiveness or impact on the health system. We aimed to fill these gaps through an analysis of the origins, architecture, and evolution of RoS schemes in South Africa. Methods: A multimethod research study including a policy review, a literature review, and semi-structured interviews of policymakers was undertaken between October 2020 and August 2022. The included policy documents and literature were analysed using the Walt and Gilson framework and narrative synthesis. Qualitative data were analysed using inductive, thematic analysis in NVIVO 12. Results: RoS schemes are used as a recruitment and retention strategy and a mechanism to address equity in access to medical education. Whilst there is evidence of RoS schemes existing in 1950, no evidence of beneficiaries was found in databases until 1989. The impact of these schemes is likely being limited by sub-optimal institutional arrangements and poor transparency in their design and implementation. Conclusion: Despite rigorous research methods, the origins of RoS policies in South Africa could not be established due to poor preservation of institutional memory. Opportunities to monitor the value of public investment into RoS programs are being missed and often the underlying objective of the programs has not been well-specified. Policies were found to have been developed and operate in isolation from other health workforce planning activities and thus may not be maximising their impact as a retention and training tool.
Digital Device Use, Risk of Cognitive Impairment, and Cognition in Healthy Older Adults: The Role of Cognitive Reserve
Authors: Liang Carolyn , Subramaniam Ponnusamy , Mohd Ridzwan Goh Nurul Syasya , Kok Wai Tay , Moustafa Ahmed A.
Published: October 2023

Neuroprotective factors are essential to successful ageing. As such, digital device use was proposed as an easily accessible and stimulating available cognitive activity to enhance brain function. Nonetheless, there was a lack of studies inspecting the connection between digital device use and cognitive reserve, the risk of cognitive impairment, and cognition. This study aims to investigate the potential mediator and moderator of the association between digital device use, cognitive reserve, the risk of cognitive impairment, and cognition among healthy older adults. A quantitative cross-sectional study was conducted to investigate the relationship between digital device use and cognitive reserve, the risk of cognitive impairment, and cognition. A total of 210 healthy older adults were recruited through purposive sampling. The results obtained from this study revealed that there was a significant difference in cognitive reserve and cognition between healthy older adults who use a digital device for communication purpose only and who use a digital device for multiple purposes. A significant relationship was also found between cognitive reserve, the risk of cognitive impairment, and cognition. Although digital device use was found to be significantly associated with cognitive reserve and cognition, it was not significantly associated with the risk of cognitive impairment. Cognitive reserve partially mediated the relationship between digital device use and cognition, supporting the notion that cognitive reserve acts as an underlying mechanism in the relationship between digital device use and cognition. Hence, digital device use was suggested to be a good daily intervention for healthy older adults to build on their cognitive reserve and potentially protect their cognition from declining. Nevertheless, relying on digital device use alone is not sufficient, and other activities should be explored to enhance cognitive reserve among healthy older adults.
Insight on HBIM for Conservation of Cultural Heritage: The Galleria dell’Accademia di Firenze
Authors: Monchetti Silvia , Betti Michele , Borri Claudio , Gerola Claudia , Matta Carlotta , Francalanci Barbara
Published: October 2023

The application of Building Information Modeling (BIM) on historic constructions is investigated in this paper by discussing, as a representative case study, the Galleria dell’Accademia di Firenze (Italy), thus showing as this tool can be used effectively for the management and maintenance activities of a historic museum. In fact, while BIM is already well-known as a powerful tool for the design and management of new buildings, its development in the field of historical construction is currently growing and attracting increasing interest in the scientific community. This paper proposes, in particular, an Information Model (IM) aimed to collect the structural information to be subsequently employed for numerical modeling of the building, thus representing the link between the real world and the computational models. The possibility to handle different types of information to be used for the management, maintenance, and modeling of existing constructions, as shown in this paper, encourages the popularization of this approach as an effective method to support cultural heritage (CH) conservation.
Emerging and Re-Emerging Parasitic Infections of the Central Nervous System (CNS) in Europe
Authors: Tunali Varol , Korkmaz Metin
Published: October 2023

In a rapidly evolving global landscape characterized by increased international travel, migration, and ecological shifts, this study sheds light on the emergence of protozoal and helminthic infections targeting the central nervous system (CNS) within Europe. Despite being traditionally associated with tropical regions, these infections are progressively becoming more prevalent in non-endemic areas. By scrutinizing the inherent risks, potential outcomes, and attendant challenges, this study underscores the intricate interplay between diagnostic limitations, susceptibility of specific population subsets, and the profound influence of climate fluctuations. The contemporary interconnectedness of societies serves as a conduit for introducing and establishing these infections, warranting comprehensive assessment. This study emphasizes the pivotal role of heightened clinician vigilance, judicious public health interventions, and synergistic research collaborations to mitigate the potential consequences of these infections. Though rare, their profound impact on morbidity and mortality underscores the collective urgency required to safeguard the neurological well-being of the European populace. Through this multifaceted approach, Europe can effectively navigate the complex terrain posed with these emergent infections.
Circular RNA circIGF2BP3 Promotes the Proliferation and Differentiation of Chicken Primary Myoblasts
Authors: Wang Xiaotong , Lin Junyuan , Jiao Zhenhai , Zhang Li , Guo Dongxue , An Lilong , Xie Tingting , Lin Shudai
Published: October 2023

The quality and quantity of animal meat are closely related to the development of skeletal muscle, which, in turn, is determined by myogenic cells, including myoblasts and skeletal muscle satellite cells (SMSCs). Circular RNA, an endogenous RNA derivative formed through specific reverse splicing in mRNA precursors, has the potential to influence muscle development by binding to miRNAs or regulating gene expression involved in muscular growth at the transcriptional level. Previous high-throughput sequencing of circRNA in chicken liver tissue revealed a circular transcript, circIGF2BP3, derived from the gene encoding insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3). In this study, we confirmed the presence of the natural circular molecule of circIGF2BP3 through an RNase R enzyme tolerance assay. RT-qPCR results showed high circIGF2BP3 expression in the pectoral and thigh muscles of Yuexi frizzled feather chickens at embryonic ages 14 and 18, as well as at 7 weeks post-hatch. Notably, its expression increased during embryonic development, followed by a rapid decrease after birth. As well as using RT-qPCR, Edu, CCK-8, immunofluorescence, and Western blot techniques, we demonstrated that overexpressing circIGF2BP3 could promote the proliferation and differentiation of chicken primary myoblasts through upregulating genes such as proliferating cell nuclear antigen (PCNA), cyclin D1 (CCND1), cyclin E1 (CCNE1), cyclin dependent kinase 2 (CDK2), myosin heavy chain (MyHC), myoblast-determining 1 (MyoD1), myogenin (MyoG), and Myomaker. In conclusion, circIGF2BP3 promotes the proliferation and differentiation of myoblasts in chickens. This study establishes a foundation for further investigation into the biological functions and mechanisms of circIGF2BP3 in myoblasts proliferation and differentiation.