bluuebunny/crossref_metadata_2025 huggingface dataset:
Demographic Profile and Clinical Characteristics of Adults with Down Syndrome in North-Eastern Romania
Authors: Lefter Nicoleta , Abdulan Irina Mihaela , Maștaleru Alexandra , Leon Maria-Magdalena , Rusu Cristina
Published: August 2024

(1) Background: Down syndrome is characterized by physical abnormalities, intellectual disability (ID), and specific patterns of other health issues. Additionally, individuals with DS are known to experience premature aging and early onset of certain age-related medical conditions. These conditions are linked to higher incident disability and reduced survival rates compared to the general population. (2) Methods: Between July 2022 and February 2024, we conducted a prospective, observational study in the Cardiovascular Rehabilitation Clinic at Iasi Clinical Rehabilitation Hospital. The study included 28 patients diagnosed with Down Syndrome and a control group. Interdisciplinary interventions were tailored to address the needs of a complex patient, incorporating cardiological, endocrinological, genetical, biological and developmental support. Data on physical health, cognitive development, and psychosocial well-being were collected. (3) Results: Our DS group consisted of 11 (39%) females and 17 (61%) males. Their age ranged from 20 to 55 years with a mean of 28.07 ± 9.51. All patients were unmarried, living in urban areas, without a partner but with family support. In the study sample, 96.4% of participants had three or more comorbidities. (4) Conclusions: The high prevalence of multimorbidity, combined with little medication, contributes to a high level of clinical complexity, which appears to be similar to the one of the older non-trisomic population. As individuals with Down syndrome transition into adulthood, they may require a more comprehensive and holistic approach to their healthcare.
A Cost-Effective Strategy to Modify the Electrical Properties of PEDOT:PSS via Femtosecond Laser Irradiation
Authors: Zhang Chi , Zhou Jiayue , Han Rui , Chen Cheng , Jiang Han , Li Xiaopeng , Peng Yong , Wang Dasen , Wang Kehong
Published: August 2024

Poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) is a commonly used conductive polymer in organic optoelectronic devices. The conductivity and work function of the PEDOT:PSS are two important parameters that significantly determine the performance of the associated optoelectronic device. Traditionally, some solvents were doped in PEDOT:PSS solution or soaked in PEDOT:PSS film to improve its electrical conductivity, but they damaged the integrity of PEDOT:PSS and reduce the film’s work function. Herein, for the first time, we use femtosecond laser irradiation to modify the electrical conductivity and work function of PEDOT:PSS film. We proposed that the femtosecond laser irradiation could selectively remove the superficial insulative PSS, thereby improving the electrical conductivity of the film. The femtosecond laser-irradiated PEDOT:PSS film was further employed as a hole injection layer within cutting-edge perovskite light-emitting diodes (PeLEDs). A maximum luminosity of 950 cd/m2 was obtained in PeLEDs irradiated by femtosecond laser light in thin films, which is five times higher than that of the controlled device. Moreover, the external quantum efficiency of the devices was also increased from 4.6% to 6.3%. This work paved a cost-effective way to regulate the electrical properties of the PEDOT:PSS film.
Augmented Reality Navigation System (SIRIO) for Neuroprotection in Vertebral Tumoral Ablation
Authors: Faiella Eliodoro , Casati Rebecca , Pileri Matteo , Pacella Giuseppina , Altomare Carlo , Vergantino Elva , Bruno Amalia , Beomonte Zobel Bruno , Grasso Rosario Francesco
Published: August 2024

(1) This study evaluates the impact of the CT-guided SIRIO augmented reality navigation system on the procedural efficacy and clinical outcomes of neuroprotection in vertebral thermal ablation (RTA) for primary and metastatic bone tumors. (2) Methods: A retrospective non-randomized analysis of 28 vertebral RTA procedures was conducted, comparing 12 SIRIO-assisted and 16 non-SIRIO-assisted procedures. The primary outcomes included dose-length product (DLP) and epidural dissection time. The secondary outcomes included technical success, complication rates, and pain scores at procedural time (VAS Time 0) and three months post-procedure (VAS Time 1). The statistical analyses included t-tests, Mann–Whitney U tests, and multiple regression. (3) Results: SIRIO-assisted procedures significantly reduced DLP (307.42 mGycm vs. 460.31 mGycm, p = 2.23 × 10−8) and procedural epidural dissection time (13.48 min vs. 32.26 min, p = 2.61 × 10−12) compared to non-SIRIO-assisted procedures. Multiple regression confirmed these reductions were significant (DLP: β = −162.38, p < 0.001; time: β = −18.25, p < 0.001). Pain scores (VAS Time 1) did not differ significantly between groups, and tumor type did not significantly influence outcomes. (4) Conclusions: The SIRIO system enhances neuroprotection efficacy and safety, reducing radiation dose and procedural time during spine tumoral ablation while maintaining consistent pain management outcomes.
Potential Impact of Omega 6/3 Ratio and CD68+ Macrophage Infiltration on Survival in NSCLC Patients Undergoing Pulmonary Resection
Authors: Déniz Carlos , Moreno Camilo , Macía Iván , Rivas Francisco , Ureña Anna , Muñoz Anna , Serratosa Ines , Aso Samantha , García Marta , Masuet-Aumatell Cristina , Escobar Ignacio , Ramos Ricard
Published: August 2024

Background: Lung cancer remains the leading cause of cancer-related mortality worldwide with non-small cell lung cancer (NSCLC) accounting for the majority of cases. The stage of detection significantly influences survival rates with early-stage diagnosis offering the best prognosis. This study investigates the prognostic impact of the omega-6/omega-3 ratio and tumor infiltration by CD8+ lymphocytes and CD68+ macrophages on overall survival (OS) and disease-free survival (DFS) in NSCLC patients undergoing pulmonary resection. Methods: We conducted a retrospective analysis of 53 patients with early-stage NSCLC who underwent pulmonary resection between September 2017 and January 2020. The omega-6/omega-3 ratio was quantified using gas chromatography and spectrometry. Tumor infiltration by CD8 and CD68 was assessed through immunohistochemistry. Survival outcomes were evaluated using Kaplan-Meier and Cox regression analyses. Results: An increased omega-6/omega-3 ratio and higher CD68+ macrophage infiltration were associated with a trend towards worse OS and DFS in NSCLC patients, though these results did not reach statistical significance. CD8+ T-cell infiltration was associated with improved survival outcomes, confirming its role as a favorable prognostic marker. Comparative analysis with existing datasets revealed similar demographic and clinical characteristics, reinforcing the generalizability of our findings. Conclusions: The omega-6/omega-3 ratio and CD68+ macrophage infiltration serve as important factors potentially influencing prognosis in NSCLC patients undergoing pulmonary resection. These findings highlight the need for further research to refine the prognostic utility of these biomarkers and to explore therapeutic strategies targeting inflammation and immune cell infiltration.
Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model
Authors: Yang Yiqing , Zhang Guoyin , Wu Yanxia , Zhao Zhixiang , Fu Yan
Published: August 2024

With advancements in computing technology and the rapid progress of data science, machine learning has been widely applied in various fields, showing great potential, especially in digital healthcare. In recent years, conversational diagnostic systems have been used to predict diseases through symptom checking. Early systems predicted the likelihood of a single disease by minimizing the number of questions asked. However, doctors typically perform differential diagnoses in real medical practice, considering multiple possible diseases to address diagnostic uncertainty. This requires systems to ask more critical questions to improve diagnostic accuracy. Nevertheless, such systems in acute medical situations need to process information quickly and accurately, but the complexity of differential diagnosis increases the system’s computational cost. To improve the efficiency and accuracy of telemedicine diagnostic systems, this study developed an optimized algorithm for the Top-K algorithm. This algorithm dynamically adjusts the number of the most likely diseases and symptoms by real-time monitoring of case progress, optimizing the diagnostic process, enhancing accuracy (99.81%), and increasing the exclusion rate of severe pathologies. Additionally, the Top-K algorithm optimizes the diagnostic model through a policy network loss function, effectively reducing the number of symptoms and diseases processed and improving the system’s response speed by 1.3–1.9 times compared to the state-of-the-art differential diagnosis systems.
A Communication-Efficient Distributed Matrix Multiplication Scheme with Privacy, Security, and Resiliency
Authors: Wang Tao , Shi Zhiping , Yang Juan , Liu Sha
Published: August 2024

Secure distributed matrix multiplication (SDMM) schemes are crucial for distributed learning algorithms where extensive data computation is distributed across multiple servers. Inspired by the application of repairing Reed–Solomon (RS) codes in distributed storage and secret sharing, we propose SDMM schemes with reduced communication overhead through the use of trace polynomials. Specifically, these schemes are designed to address three critical concerns: (i) ensuring information-theoretic privacy against collusion among servers; (ii) providing security against Byzantine servers; and (iii) offering resiliency against stragglers to mitigate computing delays. To the best of our knowledge, security and resiliency are being considered for the first time within trace polynomial-based approaches. Furthermore, our schemes offer the advantage of reduced sub-packetization and a lower server-count requirement, which diminish the computational complexity and download cost for the user.
Current and Stray Flux Combined Analysis for Sparking Detection in DC Motors/Generators Using Shannon Entropy
Authors: Salas-Robles Jorge E. , Biot-Monterde Vicente , Antonino-Daviu Jose A.
Published: August 2024

Brushed DC motors and generators (DCMs) are extensively used in various industrial applications, including the automotive industry, where they are critical for electric vehicles (EVs) due to their high torque, power, and efficiency. Despite their advantages, DCMs are prone to premature failure due to sparking between brushes and commutators, which can lead to significant economic losses. This study proposes two approaches for determining the temporal and frequency evolution of Shannon entropy in armature current and stray flux signals. One approach indirectly achieves this through prior analysis using the Short-Time Fourier Transform (STFT), while the other applies the Stockwell Transform (S-Transform) directly. Experimental results show that increased sparking activity generates significant low-frequency harmonics, which are more pronounced compared to mid and high-frequency ranges, leading to a substantial rise in system entropy. This finding enables the introduction of fault-severity indicators or Key Performance Indicators (KPIs) that relate the current condition of commutation quality to a baseline established under healthy conditions. The proposed technique can be used as a predictive maintenance tool to detect and assess sparking phenomena in DCMs, providing early warnings of component failure and performance degradation, thereby enhancing the reliability and availability of these machines.
An Unsupervised Abnormal Power Consumption Detection Method Combining Multi-Cluster Feature Selection and the Gaussian Mixture Model
Authors: Liu Danhua , Huang Dan , Chen Ximing , Dou Jian , Tang Li , Zhang Zhiqiang
Published: August 2024

Power theft and other abnormal power consumption behaviors seriously affect the safety, reliability, and stability of the power grid system. The traditional abnormal power consumption detection methods have complex models and low accuracy. In this paper, an unsupervised abnormal power consumption detection method based on multi-cluster feature selection and the Gaussian mixture model is proposed. First of all, twelve features are extracted from the load sequence to reflect the overall form, fluctuation, and change trend of the user’s electricity consumption. Then, multi-cluster feature selection algorithm is employed to select a subset of important features. Finally, based on the selected features, the Gaussian mixture model is formulated to cluster the normal power users and abnormal power users into different groups, so as to realize abnormal power consumption detection. The proposed method is evaluated through experiments based on a power load dataset from Anhui Province, China. The results show that the proposed method works well for abnormal power consumption detection, with significantly superior performance comapred to the traditional approaches in terms of the popular binary evaluation indicators like recall rate, precision rate, and F-score.
An Implementation of Communication, Computing and Control Tasks for Neuromorphic Robotics on Conventional Low-Power CPU Hardware
Authors: Russo Nicola , Madsen Thomas , Nikolic Konstantin
Published: August 2024

Bioinspired approaches tend to mimic some biological functions for the purpose of creating more efficient and robust systems. These can be implemented in both software and hardware designs. A neuromorphic software part can include, for example, Spiking Neural Networks (SNNs) or event-based representations. Regarding the hardware part, we can find different sensory systems, such as Dynamic Vision Sensors, touch sensors, and actuators, which are linked together through specific interface boards. To run real-time SNN models, specialised hardware such as SpiNNaker, Loihi, and TrueNorth have been implemented. However, neuromorphic computing is still in development, and neuromorphic platforms are still not easily accessible to researchers. In addition, for Neuromorphic Robotics, we often need specially designed and fabricated PCBs for communication with peripheral components and sensors. Therefore, we developed an all-in-one neuromorphic system that emulates neuromorphic computing by running a Virtual Machine on a conventional low-power CPU. The Virtual Machine includes Python and Brian2 simulation packages, which allow the running of SNNs, emulating neuromorphic hardware. An additional, significant advantage of using conventional hardware such as Raspberry Pi in comparison to purpose-built neuromorphic hardware is that we can utilise the built-in physical input–output (GPIO) and USB ports to directly communicate with sensors. As a proof of concept platform, a robotic goalkeeper has been implemented, using a Raspberry Pi 5 board and SNN model in Brian2. All the sensors, namely DVS128, with an infrared module as the touch sensor and Futaba S9257 as the actuator, were linked to a Raspberry Pi 5 board. We show that it is possible to simulate SNNs on a conventional low-power CPU running real-time tasks for low-latency and low-power robotic applications. Furthermore, the system excels in the goalkeeper task, achieving an overall accuracy of 84% across various environmental conditions while maintaining a maximum power consumption of 20 W. Additionally, it reaches 88% accuracy in the online controlled setup and 80% in the offline setup, marking an improvement over previous results. This work demonstrates that the combination of a conventional low-power CPU running a Virtual Machine with only selected software is a viable competitor to neuromorphic computing hardware for robotic applications.
Research on Control Strategy of Oscillating Continuous-Wave Pulse Generator Based on ILADRC
Authors: Jiang Wanlu , Chang Shangteng , Zhao Yonghui , Zhao Yang , Li Zhenbao
Published: August 2024

To achieve fast and precise position servo control in a continuous-wave pulse generator and address issues such as internal and external disturbances and significant overshoot, this paper proposes an improved linear active disturbance rejection control strategy. First, a mathematical model of the permanent magnet synchronous motor is established, and a second-order linear active disturbance rejection controller is designed based on this model. To address the issue of large errors in disturbance estimation by the traditional extended state observer, a cascaded extended state observer is introduced. By designing an additional state observer to estimate the system’s residual disturbances, the impact of disturbances on system performance is further reduced. Through an in-depth analysis of the motion characteristics of the continuous-wave pulse generator, the trade-off between system overshoot and response speed is revealed. To address this, a new adaptive law is proposed. This law, based on the system’s periodic wave response and tracking error, adjusts the parameters of the linear state error feedback control law in real time, reducing system overshoot while improving response speed. To validate the effectiveness of the proposed control strategy, a simulation model of the position servo control system for the continuous-wave pulse generator was developed. The comparative analysis of the simulation results for the different control strategies shows that the improved linear active disturbance rejection control strategy significantly enhances the system’s dynamic response performance.
Enhancing Alzheimer’s Disease Detection through Ensemble Learning of Fine-Tuned Pre-Trained Neural Networks
Authors: Topsakal Oguzhan , Lenkala Swetha
Published: August 2024

Alzheimer’s Disease, a progressive brain disorder that impairs memory, thinking, and behavior, has started to benefit from advancements in deep learning. However, the application of deep learning in medicine faces the challenge of limited data resources for training models. Transfer learning offers a solution by leveraging pre-trained models from similar tasks, reducing the data and computational requirements to achieve high performance. Additionally, data augmentation techniques, such as rotation and scaling, help increase the dataset size. In this study, we worked with magnetic resonance imaging (MRI) datasets and applied various pre-processing and augmentation techniques including include intensity normalization, affine registration, skull stripping, entropy-based slicing, flipping, zooming, shifting, and rotating to clean and expand the dataset. We applied transfer learning to high-performing pre-trained models—ResNet-50, DenseNet-201, Xception, EfficientNetB0, and Inception V3, originally trained on ImageNet. We fine-tuned these models using the feature extraction technique on augmented data. Furthermore, we implemented ensemble learning techniques, such as stacking and boosting, to enhance the final prediction performance. The novel methodology we applied achieved high precision (95%), recall (94%), F1 score (95%), and accuracy (95%) for Alzheimer’s disease detection. Overall, this study establishes a robust framework for applying machine learning to diagnose Alzheimer’s using MRI scans. The combination of transfer learning, via pre-trained neural networks fine-tuned on a processed and augmented dataset, with ensemble learning, has proven highly effective, marking a significant advancement in medical diagnostics.
Failure-Distribution-Dependent H∞ Fuzzy Fault-Tolerant Control for Nonlinear Multilateral Teleoperation System with Communication Delays
Authors: Han Antai , Yang Qiyao , Chen Yangjie , Li Jianning
Published: August 2024

In practice, the time-varying communication delays and actuator failures are the main inevitable issues in nonlinear multilateral teleoperation systems, which can reduce the performance and stability of the considered systems. This article proposed a novel failure-distribution-dependent H∞ fuzzy fault-tolerant control scheme to realize position synchronization and force tracking simultaneously for multilateral teleoperation systems. Firstly, the nonlinear multilateral systems were modeled as a kind of T-S fuzzy systems with multiple time-varying delays. Then, based on the distribution characteristic of failures, by introducing a series of tradeoff coefficients, a novel failure-distribution-dependent fault-tolerant control algorithm was provided to ensure force tracking in spite of failures, and the purpose of position synchronization was achieved (not only the master and slave robot position synchronization but also the position synchronization between each slave robot). Finally, a numerical simulation example was given to show the effectiveness of the proposed method.
Analysis of Underground Distribution System Models for Secondary Substations
Authors: Shin Boohyun , Lee Hyeseon , Choi Sungyun
Published: August 2024

In Korea, the demand for complete underground installation of power distribution equipment installed on roads and green areas is increasing. In addition, KEPCO is making efforts to build a more reliable system for the underground distribution system. To meet these needs, this paper proposes the S-substation. In the S-substation, an RMU, a large power transformer, and an LV-Board (including ATCB and MCCB) are installed within the underground structure. This paper proposes three models to apply the S-substation to the underground distribution system. Power flow analysis is conducted for each model by simulating a variety of loads and DERs, and the frequency fluctuations are also examined under different distribution system events. An economic analysis is also conducted to select the optimal model. The economic analysis focuses on VOLL and construction costs. Based on power flow and economic analysis, one model is selected, and the underground distribution system that the model is applied is presented.
Variable Delayed Time Control for Dual Three-Phase Permanent Magnet Synchronous Motor with Double Central Symmetry Space Vector Pulse Width Modulation
Authors: Tao Tao , Liu Sen
Published: August 2024

To address the harmonic issues associated with the pulse width modulation (PWM) method, this article introduces variable delayed time (VDT) space vector pulse width modulation (SVPWM) with double central symmetry for dual three-phase permanent magnet synchronous machines (DTP-PMSMs). Firstly, the switching sequence of four traditional vectors undergoes double central symmetry, resulting in the doubling of the frequency of the phase voltage. This alteration eliminates harmonics occurring at odd multiples of carrier frequency. Additionally, the adopting of a single null vector minimizes the additional switching times introduced by the double central symmetry. Subsequently, VDT-SVPWM is employed to further suppress the harmonics at the even multiples of carrier frequency. The implementation of the proposed double central symmetry method involves directly utilizing the calculated duty cycle of the traditional four vectors. Moreover, integrating VDT-SVPWM with the double central symmetry method is straightforward. Simulation and experimental results validate the efficacy of the proposed method in suppressing harmonics and mitigating vibrations in the DTP-PMSM.
Remote-Sensing-Based Estimation of Rooftop Photovoltaic Power Production Using Physical Conversion Models and Weather Data
Authors: Kasmi Gabriel , Touron Augustin , Blanc Philippe , Saint-Drenan Yves-Marie , Fortin Maxime , Dubus Laurent
Published: August 2024

The global photovoltaic (PV) installed capacity, vital for the electric sector’s decarbonation, reached 1552.3 GWp in 2023. In France, the capacity stood at 19.9 GWp in April 2024. The growth of the PV installed capacity over a year was nearly 32% worldwide and 15.7% in France. However, integrating PV electricity into grids is hindered by poor knowledge of rooftop PV systems, constituting 20% of France’s installed capacity, and the lack of measurements of the production stemming from these systems. This problem of lack of measurements of the rooftop PV power production is referred to as the lack of observability. Using ground-truth measurements of individual PV systems, available at an unprecedented temporal and spatial scale, we show that by estimating the PV power production of an individual rooftop system by combining solar irradiance and temperature data, the characteristics of the PV system inferred from remote sensing methods and an irradiation-to-electric power conversion model provides accurate estimations of the PV power production. We report an average estimation error (measured with the pRMSE) of 10% relative to the system size. Our study shows that we can improve rooftop PV observability, and thus its integration into the electric grid, using little information on these systems, a simple model of the PV system, and weather data. More broadly, this study shows that limited information is sufficient to derive a reasonably good estimation of the PV power production of small-scale systems.
Thermal Performance Evaluation of a Single-Mouth Improved Cookstove: Theoretical Approach Compared with Experimental Data
Authors: Atajafari Hamed , Pathak Birendra Raj , Bhandari Ramchandra
Published: August 2024

This work aims to address the knowledge gap in the thermal efficiency performance of a locally made cookstove in Mali. Despite the fact that the thermal efficiency of cookstoves is a crucial aspect of cooking, the performance of commercially produced cookstoves in Mali has not been thoroughly studied. In this context, the thermal efficiency of a single-mouth biomass stove has been investigated using a theoretical and experimental approach. First, the fundamental principles of physics for the three forms of heat transfer were applied. Then, the theoretical thermal efficiency of the stove was calculated based on the percentage share of energy gains and losses for the respective heat transfer modes. This analysis shows that the highest energy gain is achieved by radiation heat transfer from the flame and the fuel bed, followed by convection heat transfer to the bottom and sides of the pot, respectively. In order to validate the findings, the theoretical results have been compared with the experimental data at a case study site in Katibougou, Mali. Accordingly, the experimental thermal efficiency is slightly lower than the theoretical value, with a measured value of 27% compared to the theoretical value of 31.45%. The theoretical thermal efficiency can be closer to the experimental efficiency if the combustion losses caused by incomplete combustion of the fuel are taken into account.
Evolution of Vegetation Growth Season on the Loess Plateau under Future Climate Scenarios
Authors: Han Hongzhu , Ma Gao , Ta Zhijie , Zhao Ting , Li Peilin , Li Xiaofeng
Published: August 2024

In recent decades, vegetation phenology, as one of the most sensitive and easily observed features under climate change, has changed significantly under the influence of the global warming as a result of the green house effect. Vegetation phenological change is not only highly related to temperature change, but also to precipitation, a key factor affecting vegetation phenological change. However, the response of vegetation phenology to climate change is different in different regions, and the current research still does not fully understand the climate drivers that control phenological change. The study focuses on the Loess Plateau, utilizing the GIMMS NDVI3g dataset to extract vegetation phenology parameters from 1982 to 2015 and analyzing their spatial–temporal variations and responses to climate change. Furthermore, by incorporating emission scenarios of RCP4.5 (medium and low emission) and RCP8.5 (high emission), the study predicts and analyzes the changes in vegetation phenology on the Loess Plateau from 2030 to 2100. The long-term dynamic response of vegetation phenology to climate change and extreme climate is explored, so as to provide a scientific basis for the sustainable development of the fragile Loess Plateau. The key findings are as follows: (1) From 1982 to 2015, the start of the growing season (SOS) on the Loess Plateau shows a non-significant delay (0.06 d/year, p > 0.05), while the end of the growing season (EOS) is significantly delayed at a rate of 0.1 d/year (p < 0.05). (2) In the southeastern part of the Loess Plateau, temperature increases led to a significant advancement of SOS. Conversely, in the Maowusu Desert in the northwest, increased autumn precipitation caused a significant delay in EOS. (3) From 2030 to 2100, under the RCP4.5 and RCP8.5 scenarios, temperatures are projected to rise significantly at rates of 0.018 °C/year and 0.06 °C/year, respectively. Meanwhile, precipitation will either decrease insignificantly at −0.009 mm/year under RCP4.5 or increase significantly at 0.799 mm/year under RCP8.5. In this context, SOS is projected to advance by 19 days and 28 days, respectively, under RCP4.5 and RCP8.5, with advancement rates of 0.049 days/year and 0.228 days/year. EOS is projected to be delayed by 14 days and 27 days (p < 0.05), respectively, with delay rates of 0.084 d/year and 0.2 d/year.
Evaluation of Shoot Collection Timing and Hormonal Treatment on Seedling Rooting and Growth in Four Poplar Genomic Groups
Authors: Varnagirytė-Kabašinskienė Iveta , Suchockas Vytautas , Urbaitis Gintautas , Žemaitis Povilas , Muraškienė Milda , Čiuldienė Dovilė , Černiauskas Valentinas , Armoška Emilis , Vigricas Egidijus
Published: August 2024

Populus spp. is an economically valuable tree worldwide, known for its adaptability, fast growth, and versatile wood, often cultivated in short-rotation plantations. Effective propagation is crucial for rapid genetic improvement and global demand for forest products and biomass energy. This study focused on the rooting and growth of poplar cuttings, examining shoot collection timing and growth stimulant treatments across four hybrids: Populus deltoides × P. nigra (Agathe F), P. maximowiczii × P. trichocarpa (Arges), P. deltoides × P. trichocarpa (Donk), and an interspecific hybrid Populus × canadensis (F-448). The experiment used hybrid poplar cuttings collected in spring 2022 and 2023, planted in controlled climates with a randomized block design. Cuttings were soaked for 24 h in growth stimulants, namely indole-3-butyric acid, cinnamic acid, and indole-3-acetic acid. After 12 weeks, rooting percentage and seedling height were assessed. The study found that the optimal time for collecting poplar cuttings for best rooting is late winter to early spring, specifically from March to early April, with shoots collected after early April showing the lowest rooting potential. The growth stimulants significantly influenced the growth of poplar seedlings. There was a tendency for lower concentrations to increase root formation and seedling height, while higher concentrations had adverse effects. Despite variations in growth rates, a consistent growth pattern was observed across different shoot collection dates for all genomic groups.
Long-Read MDM4 Sequencing Reveals Aberrant Isoform Landscape in Metastatic Melanomas
Authors: Patrick Nehaal , Markey Michael
Published: August 2024

MDM4 is upregulated in the majority of melanoma cases and has been described as a “key therapeutic target in cutaneous melanoma”. Numerous isoforms of MDM4 exist, with few studies examining their specific expression in human tissues. The changes in splicing of MDM4 during human melanomagenesis are critical to p53 activity and represent potential therapeutic targets. Compounding this, studies relying on short reads lose “connectivity” data, so full transcripts are frequently only inferred from the presence of splice junction reads. To address this problem, long-read nanopore sequencing was utilized to read the entire length of transcripts. Here, MDM4 transcripts, both alternative and canonical, are characterized in a pilot cohort of human melanoma specimens. RT-PCR was first used to identify the presence of novel splice junctions in these specimens. RT-qPCR then quantified the expression of major MDM4 isoforms observed during sequencing. The current study both identifies and quantifies MDM4 isoforms present in melanoma tumor samples. In the current study, we observed high expression levels of MDM4-S, MDM4-FL, MDM4-A, and the previously undescribed Ensembl transcript MDM4-209. A novel transcript lacking both exons 6 and 9 is observed and named MDM4-A/S for its resemblance to both MDM4-A and MDM4-S isoforms.
A Butyrate-Yielding Dietary Supplement Prevents Acute Alcoholic Liver Injury by Modulating Nrf2-Mediated Hepatic Oxidative Stress and Gut Microbiota
Authors: Xu Qi , Guo Mei , Wang Haidi , Liu Haitao , Wei Yunbo , Wang Xiao , Mackay Charles R. , Wang Quanbo
Published: August 2024

Alcoholic liver disease (ALD) is a globally prevalent form of liver disease for which there is no effective treatment. Recent studies have found that a significant decrease in butyrate was closely associated with ALD development. Given the low compliance and delivery efficiency associated with oral-route butyrate administration, a highly effective butyrate-yielding dietary supplement, butyrylated high-amylose maize starch (HAMSB), is a good alternative approach. Here, we synthesized HAMSB, evaluated the effect of HAMSB on acute ALD in mice, compared its effect with that of oral administration of butyrate, and further studied the potential mechanism of action. The results showed HAMSB alleviated acute ALD in mice, as evidenced by the inhibition of hepatic-function impairment and the improvement in liver steatosis and lipid metabolism; in these respects, HAMSB supplementation was superior to oral sodium butyrate administration. These improvements can be attributed to the reduction of oxidative stress though the regulation of Nrf2-mediated antioxidant signaling in the liver and the improvement in the composition and function of microbiota in the intestine. In conclusion, HAMSB is a safe and effective dietary supplement for preventing acute ALD that could be useful as a disease-modifying functional food or candidate medicine.
aMMP-8 POCT vs. Other Potential Biomarkers in Chair-Side Diagnostics and Treatment Monitoring of Severe Periodontitis
Authors: Aji Nur Rahman Ahmad Seno , Räisänen Ismo T. , Rathnayake Nilminie , Lundy Fionnuala T. , Mc Crudden Maelíosa T. C. , Goyal Lata , Sorsa Timo , Gupta Shipra
Published: August 2024

This study aimed to compare several potential mouthrinse biomarkers for periodontitis including active matrix-metalloproteinase-8 (aMMP-8), total MMP-8, and other inflammatory biomarkers in diagnosing and monitoring the effects of nonsurgical periodontal therapy. Thirteen patients with stage III/IV periodontitis were recruited, along with thirteen periodontally and systemically healthy controls. These 13 patients were representative of the number of outpatients visiting any dentist in a single day. Full-mouth clinical periodontal parameters and biomarkers (the aMMP-8 point-of-care-test [POCT], total MMP-8, tissue inhibitor of MMPs (TIMP)-1, the aMMP-8 RFU activity assay, Myeloperoxidase, PMN elastase, calprotectin, and interleukin-6) were recorded at baseline and after nonsurgical therapy at 6 weeks. The aMMP-8 POCT was the most efficient and precise discriminator, with a cut-off of 20 ng/mL found to be optimal. Myeloperoxidase, MMP-8’s oxidative activator, was also efficient. Following closely in precision was the aMMP-8 RFU activity assay and PMN elastase. In contrast, the total MMP-8 assay and the other biomarkers were less efficient and precise in distinguishing patients with periodontitis from healthy controls. aMMP-8, MPO, and PMN elastase may form a proteolytic and pro-oxidative tissue destruction cascade in periodontitis, potentially representing a therapeutic target. The aMMP-8 chair-side test with a cut-off of 20 ng/mL was the most efficient and precise discriminator between periodontal health and disease. The aMMP-8 POC test can be effectively used by dental professionals in their dental practices in online and real-time diagnoses as well as in monitoring periodontal disease and educating and encouraging good oral practices among patients.
Envelope Protein-Targeting Zika Virus Entry Inhibitors
Authors: Roy Abhijeet , Liu Qian , Yang Yang , Debnath Asim K. , Du Lanying
Published: August 2024

Zika virus (ZIKV; family, Flaviviridae), which causes congenital Zika syndrome, Guillain-Barré Syndrome, and other severe diseases, is transmitted mainly by mosquitoes; however, the virus can be transmitted through other routes. Among the three structural and seven nonstructural proteins, the surface envelope (E) protein of ZIKV plays a critical role in viral entry and pathogenesis, making it a key target for the development of effective entry inhibitors. This review article describes the life cycle, genome, and encoded proteins of ZIKV, illustrates the structure and function of the ZIKV E protein, summarizes E protein-targeting entry inhibitors (with a focus on those based on natural products and small molecules), and highlights challenges that may potentially hinder the development of effective inhibitors of ZIKV infection. Overall, the article will provide useful guidance for further development of safe and potent ZIKV entry inhibitors targeting the viral E protein.
The Enigmatic Interplay of Interleukin-10 in the Synergy of HIV Infection Comorbid with Preeclampsia
Authors: Naidoo Shirelle Janine , Naicker Thajasvarie
Published: August 2024

Cytokines coordinate the intricate choreography of the immune system, directing cellular activities that mediate inflammation, pathogen defense, pathology and tissue repair. Within this spectrum, the anti-inflammatory prowess of interleukin-10 (IL-10) predominates in immune homeostasis. In normal pregnancy, the dynamic shift of IL-10 across trimesters maintains maternal immune tolerance ensuring fetal development and pregnancy success. Unravelling the dysregulation of IL-10 in pregnancy complications is vital, particularly in the heightened inflammatory condition of preeclampsia. Of note, a reduction in IL-10 levels contributes to endothelial dysfunction. In human immunodeficiency virus (HIV) infection, a complex interplay of IL-10 occurs, displaying a paradoxical paradigm of being immune-protective yet aiding viral persistence. Genetic variations in the IL-10 gene further modulate susceptibility to HIV infection and preeclampsia, albeit with nuanced effects across populations. This review outlines the conceptual framework underlying the role of IL-10 in the duality of normal pregnancy and preeclampsia together with HIV infection, thus highlighting its regulatory mechanisms and genetic influences. Synthesizing these findings in immune modulation presents avenues for therapeutic interventions in pregnancy complications comorbid with HIV infection.
Molecular Characterization of Odorant-Binding Protein Genes Associated with Host-Seeking Behavior in Oides leucomelaena
Authors: Zhao Ning , Li Kai , Ma Huifen , Hu Lianrong , Yang Yingxue , Liu Ling
Published: August 2024

The identification of odorant-binding proteins (OBPs) involved in host location by Oides leucomelaena (O. leucomelaena Weise, 1922, Coleoptera, Galerucinae) is significant for its biological control. Tools in the NCBI database were used to compare and analyze the transcriptome sequences of O. leucomelaena with OBP and other chemosensory-related proteins of other Coleoptera insects. Subsequently, MEGA7 was utilized for OBP sequence alignment and the construction of a phylogenetic tree, combined with expression profiling to screen for candidate antennae-specific OBPs. In addition, fumigation experiments with star anise volatiles were conducted to assess the antennae specificity of the candidate OBPs. Finally, molecular docking was employed to speculate on the binding potential of antennae-specific OBPs with star anise volatiles. The study identified 42 candidate OBPs, 8 chemosensory proteins and 27 receptors. OleuOBP3, OleuOBP5, and OleuOBP6 were identified as classic OBP family members specific to the antennae, which was confirmed by volatile fumigation experiments. Molecular docking ultimately clarified that OleuOBP3, OleuOBP5, and OleuOBP6 all exhibit a high affinity for β-caryophyllene among the star anise volatiles. We successfully obtained three antennae-specific OBPs from O. leucomelaena and determined their high-affinity volatiles, providing a theoretical basis for the development of attractants in subsequent stages.
Cyclic Adenosine Monophosphate Signaling in Chronic Kidney Disease: Molecular Targets and Therapeutic Potentials
Authors: Delrue Charlotte , Speeckaert Reinhart , Moresco Rafael Noal , Speeckaert Marijn M.
Published: August 2024

Chronic kidney disease (CKD) is characterized by a steady decline in kidney function and affects roughly 10% of the world’s population. This review focuses on the critical function of cyclic adenosine monophosphate (cAMP) signaling in CKD, specifically how it influences both protective and pathogenic processes in the kidney. cAMP, a critical secondary messenger, controls a variety of cellular functions, including transcription, metabolism, mitochondrial homeostasis, cell proliferation, and apoptosis. Its compartmentalization inside cellular microdomains ensures accurate signaling. In kidney physiology, cAMP is required for hormone-regulated activities, particularly in the collecting duct, where it promotes water reabsorption through vasopressin signaling. Several illnesses, including Fabry disease, renal cell carcinoma, nephrogenic diabetes insipidus, Bartter syndrome, Liddle syndrome, diabetic nephropathy, autosomal dominant polycystic kidney disease, and renal tubular acidosis, have been linked to dysfunction in the cAMP system. Both cAMP analogs and phosphodiesterase inhibitors have the potential to improve kidney function and reduce kidney damage. Future research should focus on developing targeted PDE inhibitors for the treatment of CKD.
Hypoxia Abrogates Tumor-Suppressive Activities of C/EBPδ in Pancreatic Cancer
Authors: Hartl Leonie , ten Brink Marieke S. , Aberson Hella L. , Koster Jan , Zwijnenburg Danny A. , Duitman JanWillem , Bijlsma Maarten F. , Spek C. Arnold
Published: August 2024

Pancreatic ductal adenocarcinoma (PDAC) is a dismal disease with a low 5-year survival rate of only 13%. Despite intense research efforts, PDAC remains insufficiently understood. In part, this is attributed to opposing effects of key players being unraveled, including the stroma but also molecules that act in a context-dependent manner. One such molecule is the transcription factor C/EBPδ, where we recently showed that C/EBPδ exerts tumor-suppressive effects in PDAC cells in vitro. To better understand the role of C/EBPδ in different contexts and the development of PDAC, we here build on these findings and assess the effect of C/EBPδ in a PDAC model in mice. We establish that the lack of oxygen in vivo—hypoxia—counteracts the tumor-suppressive effects of C/EBPδ, and identify a reciprocal feedback loop between C/EBPδ and HIF-1α. RNA sequencing of C/EBPδ-induced cells under hypoxia also suggests that the growth-limiting effects of C/EBPδ decrease with oxygen tension. Consequently, in vitro proliferation assays reveal that the tumor-suppressive activities of C/EBPδ are abrogated due to hypoxia. This study demonstrates the importance of considering major physiological parameters in preclinical approaches.
An Interplay between Transcription Factors and Recombinant Protein Synthesis in Yarrowia lipolytica at Transcriptional and Functional Levels—The Global View
Authors: Gorczyca Maria , Korpys-Woźniak Paulina , Celińska Ewelina
Published: August 2024

Transcriptional regulatory networks (TRNs) associated with recombinant protein (rProt) synthesis in Yarrowia lipolytica are still under-described. Yet, it is foreseen that skillful manipulation with TRNs would enable global fine-tuning of the host strain’s metabolism towards a high-level-producing phenotype. Our previous studies investigated the transcriptomes of Y. lipolytica strains overproducing biochemically different rProts and the functional impact of transcription factors (TFs) overexpression (OE) on rProt synthesis capacity in this species. Hence, much knowledge has been accumulated and deposited in public repositories. In this study, we combined both biological datasets and enriched them with further experimental data to investigate an interplay between TFs and rProts synthesis in Y. lipolytica at transcriptional and functional levels. Technically, the RNAseq datasets were extracted and re-analyzed for the TFs’ expression profiles. Of the 140 TFs in Y. lipolytica, 87 TF-encoding genes were significantly deregulated in at least one of the strains. The expression profiles were juxtaposed against the rProt amounts from 125 strains co-overexpressing TF and rProt. In addition, several strains bearing knock-outs (KOs) in the TF loci were analyzed to get more insight into their actual involvement in rProt synthesis. Different profiles of the TFs’ transcriptional deregulation and the impact of their OE or KO on rProts synthesis were observed, and new engineering targets were pointed.
The Spectrum of Coronary Artery Disease in Elite Endurance Athletes—A Long-Standing Debate: State-of-the-Art Review
Authors: Celeski Mihail , Di Gioia Giuseppe , Nusca Annunziata , Segreti Andrea , Squeo Maria Rosaria , Lemme Erika , Mango Federica , Ferrera Armando , Ussia Gian Paolo , Grigioni Francesco
Published: August 2024

Physical activity is recommended for the prevention of primary and secondary cardiovascular (CV) disease as it is linked to a number of health benefits, especially CV. However, recent research suggests that high-volume, long-term endurance exercise may hasten rather than slow the coronary atherosclerosis progression. This contentious theory has generated a great discussion and is still a major source of doubt when it comes to the clinical treatment of coronary artery disease (CAD) in athletes. CAD is the primary cause of sudden cardiac death in athletes over 35 years. Thus, recent studies evaluated the prevalence of CAD in athletes and its clinical and prognostic implications. Indeed, many studies have shown a relationship between endurance sports and higher volumes of coronary calcified plaque as determined by computed tomography. However, the precise pathogenetic substrate for the existence of an increased coronary calcification burden among endurance athletes remains unclear. Moreover, the idea that coronary plaques in elite athletes present a benign morphology has been cast into doubt by some recent studies showing potential association with adverse cardiovascular events. This review aims to analyze the association between physical activity and CAD, explaining possible underlying mechanisms of atherosclerotic progression and non-ischemic coronary lesions, focusing primarily on clinical and prognostic implications, multimodal evaluation, and management of CAD in endurance athletes.