bluuebunny/crossref_metadata_2025 huggingface dataset:
A Carpometacarpal Thumb Tracking Device for Telemanipulation of a Robotic Thumb: Development, Prototyping, and Evaluation
Authors: Abdul Rahaman Abdul Hafiz , Shiakolas Panos S.
Published: January 2025

Hand−tracking systems are widely employed for telemanipulating grippers with high degrees of freedom (DOFs) such as an anthropomorphic robotic hand (ARH). However, tracking human thumb motion is challenging due to the complex motion of the carpometacarpal (CMC) joint. Existing hand−tracking systems can track the motion of simple joints with one DOF, but most fail to track the motion of the CMC joint, or to do so, there is a need for expensive and intricately set up hardware systems. This research introduces and realizes an affordable and personalizable tracking device to capture the CMC joint Flexion/Extension and Abduction/Adduction motions. Tracked human thumb motion is mapped to a robot thumb in a hybrid approach: the proposed algorithm maps the CMC joint motion to the first two joints of the robot thumb, while joint mapping is established between the metacarpophalangeal and interphalangeal joints to the last two joints. When the tracking device is paired with a flex glove outfitted with bend sensors, the developed system provides the means to telemanipulate an ARH with a four-DOF thumb and one-DOF underactuated digits. A three-stage framework is proposed to telemanipulate the fully actuated robot thumb. The tracking device and framework were evaluated through a device operation and personalization test, as well as a framework verification test. Two volunteers successfully personalized, calibrated, and tested the device using the proposed mapping algorithm. One volunteer further evaluated the framework by performing hand poses and grasps, demonstrating effective control of the robot thumb for precision and power grasps in coordination with the other digits. The successful results support expanding the system and further evaluating it as a research platform for studying human–robot interaction in grasping tasks or in manufacturing, assistive, or medical domains.
Dietary Intake According to the Evolution of the Resting Metabolic Rate and Body Composition of an Elite Olympic Athlete over a Macrocycle: A Case Study
Authors: Saftel Mihaiță Alin , Leonte Nicoleta , Maftei Alexandru , Moanță Alina Daniela
Published: January 2025

Monitoring physiological parameters is vital for tracking swimmers’ progress and performance. This study examines an elite male swimmer’s nutrition during his preparation for the 2024 Paris Olympics, considering his metabolic rate and body composition. His resting energy needs (2905 ± 407.99 kcal/day) were measured using indirect Cosmed K5, calorimetry, and body composition determined through skinfold measurements. Nutrition plans were developed using software, varying with his training intensity—providing 2910 ± 379 kcal/day on rest days, and 4238 ± 562 kcal/day on intense days. The analysis of the correlations between key variables revealed strong and diverse interactions among anthropometric, metabolic data, and energy substrates. Thus, weight exhibited a very strong positive correlation with lean mass (FFM), indicating that higher weight is associated with increased lean mass. Conversely, the moderate correlation between weight and body fat percentage suggests a weaker association. The amount of skin folds accurately reflects the body fat percentage. Ensuring that a high-energy dietary intake aligned with his actual needs throughout the season was crucial for sustaining performance. Experimenting with fueling and recovery tactics during smaller competitions enabled the athlete to meet energy and nutrient demands at the elite level.
Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies
Authors: Alerte Zélie , Chodorowski Mateusz , Ammari Samy , Rovira Alex , Ognard Julien , Douraied Ben Salem
Published: January 2025

We evaluated the energy consumption of a 3T MRI using a central monitoring system, focusing on hospital energy costs during peak winter months from 2021 to 2023. We analyzed consumption during non-productive phases like end-of-day standby and assessed their impact. For active use, we compared standard and AI-enhanced protocols on phantoms, scheduling high-demand protocols during off-peak hours to benefit from lower energy prices. Standard protocols consumed 3.4 to 15 kWh, while optimized protocols used 2.3 to 10.6 kWh, reducing consumption by 32% on average. Savings per scan ranged from EUR 0.03 to EUR 3.7. The electrical consumption of a brain MRI protocol is equivalent to that of 3–4 knee protocols or 2–3 lumbar spine protocols. Using AI-optimized protocols and management, 41 protocols can be completed in 12 h, up from 30, reducing daily costs by EUR 2.38 to EUR 29.18. Annually, AI-optimized protocols could save 7900 to 8800 kWh per MRI unit, totaling 10,500 to 11,600 MWh across France’s MRI fleet, equivalent to the yearly consumption of about 4700 to 5300 people. Optimizing MRI resource use can expand patient access while significantly reducing the associated energy footprint. These findings support the implementation of more sustainable practices in medical imaging without compromising care quality.
Quantification Method of Driving Risks for Networked Autonomous Vehicles Based on Molecular Potential Fields
Authors: Chen Yicheng , Qu Dayi , Wang Tao , Cui Shanning , Shao Dedong
Published: January 2025

Connected autonomous vehicles (CAVs) face constraints from multiple traffic elements, such as the vehicle, road, and environmental factors. Accurately quantifying the vehicle’s operational status and driving risk level in complex traffic scenarios is crucial for enhancing the efficiency and safety of connected autonomous driving. To continuously and dynamically quantify the driving risks faced by CAVs in the road environment—arising from the front, rear, and lateral directions—this study focused s on the self-driving particle characteristics that enable CAVs to perceive their surrounding environment and make driving decisions. The vehicle-to-vehicle interaction behavior was analogized to the inter-molecular interaction relationship, and a molecular Morse potential model was applied, coupled with the vehicle dynamics theory. This approach considers the safety margin and the specificity of driving styles. A multi-layer decoder–encoder long short-term memory (LSTM) network was employed to predict vehicle trajectories and establish a risk quantification model for vehicle-to-vehicle interaction behavior. Using SUMO software (win64-1.11.0), three typical driving behavior scenarios—car-following, lane-changing, and yielding—were modeled. A comparative analysis was conducted between the risk field quantification method and existing risk quantification indicators such as post-encroachment time (PET), deceleration rate to avoid crash (DRAC), modified time to collision (MTTC), and safety potential fields (SPFs). The evaluation results demonstrate that the risk field quantification method has the advantage of continuously quantifying risk, addressing the limitations of traditional risk indicators, which may yield discontinuous results when conflict points disappear. Furthermore, when the half-life parameter is reasonably set, the method exhibits more stable evaluation performance. This research provides a theoretical basis for the dynamic equilibrium control of driving risks in connected autonomous vehicle fleets within mixed-traffic environments, offering insights and references for collision avoidance design.
Effect of Thermal Treatment on the Retention of Phenolic Compounds, Antioxidant Activity, and Vitamin C of Edible Plants (Mallow Leaf and Garambullo Flower)
Authors: Ramírez-Moreno Esther , Cruz-Cansino Nelly del Socorro , Olguín-Hernández Zacnicté , Baltazar-Téllez Rosa María , Sánchez-Padilla María Luisa , Palmeros-Exsome Carolina , Sandoval-Gallegos Eli Mireya , Arias-Rico José
Published: January 2025

Mexico has a wide variety of edible plants, such as mallow and garambullo flowers. Their composition is based on nutrients (carbohydrates, proteins, lipids, vitamins, minerals), as well as phytochemicals, organic or inorganic acids, etc. For the traditional consumption of these plants, they are boiled and then combined with other ingredients. However, after a thermal treatment, their nutritional and sensory qualities are affected. In this work, we study the effect of thermal treatment on the total phenolic compounds (TPC), antioxidant capacity, and vitamin C of two edible plants from Mexico. Both plants had a high amount of TPC as ferulic acid, p-coumaric acid, caffeic acid, quercetin, and apigenin. Both plants had a high amount of TPC as ferulic acid, p-coumaric acid, caffeic acid, quercetin, and apigenin. After thermal treatment, the samples showed a high antioxidant capacity analyzed by 2,2-Diphenyl-1-picrylhydrazyl (DPPH•), 2,2′-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS●+), and ferric reducing antioxidant power (FRAP), associated with a high retention (78 and 89%) of phenolic compounds in the food matrix. Coumarin and ferulic acid were identified in both samples, while apigenin was only found in the mallow leaves and quercetin in the garambullo flowers after thermal treatment. Vitamin C content was higher on mallow leaves compared to garambullo flowers after thermal treatment. Further research is needed to characterize and evaluate the effect in both plants.
Enhancing Telexistence Control Through Assistive Manipulation and Haptic Feedback
Authors: Halabi Osama , Al-Sada Mohammed , Abourajouh Hala , Hoque Myesha , Iskandar Abdullah , Nakajima Tatsuo
Published: January 2025

The COVID-19 pandemic brought telepresence systems into the spotlight, yet manually controlling remote robots often proves ineffective for handling complex manipulation tasks. To tackle this issue, we present a machine learning-based assistive manipulation approach. This method identifies target objects and computes an inverse kinematic solution for grasping them. The system integrates the generated solution with the user’s arm movements across varying inverse kinematic (IK) fusion levels. Given the importance of maintaining a sense of body ownership over the remote robot, we examine how haptic feedback and assistive functions influence ownership perception and task performance. Our findings indicate that incorporating assistance and haptic feedback significantly enhances the control of the robotic arm in telepresence environments, leading to improved precision and shorter task completion times. This research underscores the advantages of assistive manipulation techniques and haptic feedback in advancing telepresence technology.
Image Segmentation Framework for Detecting Adversarial Attacks for Autonomous Driving Cars
Authors: Sattout Ahmad Fakhr Aldeen , Chehab Ali , Mohanna Ammar , Tajeddine Razane
Published: January 2025

The widespread deployment of deep neural networks (DNNs) in critical real-time applications has spurred significant research into their security and robustness. A key vulnerability identified is that DNN decisions can be maliciously altered by introducing carefully crafted noise into the input data, leading to erroneous predictions. This is known as an adversarial attack. In this paper, we propose a novel detection framework leveraging segmentation masks and image segmentation techniques to identify adversarial attacks on DNNs, particularly in the context of autonomous driving systems. Our defense technique considers two levels of adversarial detection. The first level mainly detects adversarial inputs with large perturbations using the U-net model and one-class support vector machine (SVM). The second level of defense proposes a dynamic segmentation algorithm based on the k-means algorithm and a verifier model that controls the final prediction of the input image. To evaluate our approach, we comprehensively compare our method to the state-of-the-art feature squeeze method under a white-box attack, using eleven distinct adversarial attacks across three benchmark and heterogeneous data sets. The experimental results demonstrate the efficacy of our framework, achieving overall detection rates exceeding 96% across all adversarial techniques and data sets studied. It is worth mentioning that our method enhances the detection rates of FGSM and BIM attacks, reaching average detection rates of 95.65% as opposed to 62.63% in feature squeezing across the three data sets.
Multimodal Augmented Reality System for Real-Time Roof Type Recognition and Visualization on Mobile Devices
Authors: Kubicki Bartosz , Janowski Artur , Inglot Adam
Published: January 2025

The utilization of augmented reality (AR) is becoming increasingly prevalent in the integration of virtual reality (VR) elements into the tangible reality of the physical world. It facilitates a more straightforward comprehension of the interconnections, interdependencies, and spatial context of data. Furthermore, the presentation of analyses and the combination of spatial data with annotated data are facilitated. This is particularly evident in the context of mobile applications, where the combination of real-world and virtual imagery facilitates enhances visualization. This paper presents a proposal for the development of a multimodal system that is capable of identifying roof types in real time and visualizing them in AR on mobile devices. The current approach to roof identification is based on data made available by public administrations in an open-source format, including orthophotos and building contours. Existing computer processing technologies have been employed to generate objects representing the shapes of building masses, and in particular, the shape of roofs, in three-dimensional (3D) space. The system integrates real-time data obtained from multiple sources and is based on a mobile application that enables the precise positioning and detection of the recipient’s viewing direction (pose estimation) in real time. The data were integrated and processed in a Docker container system, which ensured the scalability and security of the solution. The multimodality of the system is designed to enhance the user’s perception of the space and facilitate a more nuanced interpretation of its intricacies. In its present iteration, the system facilitates the extraction and classification/generalization of two categories of roof types (gable and other) from aerial imagery through the utilization of deep learning methodologies. The outcomes achieved suggest considerable promise for the advancement and deployment of the system in domains pertaining to architecture, urban planning, and civil engineering.
Capacity of the Fungi Trichoderma Koningiopsis and Talaromyces Verruculosus for Hg Leaching, Immobilization and Absorption During the Dissolution of Cinnabar
Authors: Balland Clarisse , Alphonse Vanessa , Jusselme My Dung , Abbad-Andaloussi Samir , Bousserrhine Noureddine
Published: January 2025

The present study investigates the potential capacity of fungi for the use in mercury (Hg) leaching and immobilization during the dissolution of cinnabar ore, the updated understanding of the mechanisms involved, and the evaluation of Hg absorption by these fungal strains. Two fungal strains are isolated from Hg-polluted soils in French Guiana and identified as Trichoderma koningiopsis and Talaromyces verruculosus. These fungal strains possess a high capacity for Hg resistance. The Hg concentrations causing 50% growth reduction (EC50) are 5.9 and 1.5 ppm for T. koningiopsis and T. verruculosus, respectively. The results of medium-culture-containing cinnabar ore show that these fungal strains remove over 99% of the Hg content in the culture media by the end of the experiment. Fungal biomass decreases with increasing mercury concentration. The production of organic acids by fungi is observed for both fungal strains, leading to an acidic pH in the medium culture. Oxalic and citric acids are preferentially produced to dissolve Fe from minerals, which may impact Hg leaching. The results of this study provide evidence that the two fungi seem to have potential use for the bioremediation of Hg during the dissolution of cinnabar ores through biosorption mechanisms.
Classification of Hydrometeors During a Stratiform Precipitation Event in the Rainy Season of Liupanshan
Authors: Feng Nansong , Shu Zhiliang , Qiu Yujun
Published: January 2025

This study conducted a classification analysis of hydrometeor types during a typical stratiform mixed cloud precipitation event in the rainy season using data from the Liupan Mountains micro rain radar power spectra. The primary research findings are as follows: (1) Utilizing the RaProM method synthesizes the information of particle falling velocity, equivalent radar reflection coefficient, particle scale characteristics at different stages, and the location of the bright zone in the zero-degree layer to classify hydrometeors during this precipitation process, and the results show that drizzle and raindrop distribution time periods do not match with the raindrop spectra and rain intensities observed by the DSG5 ground-based precipitation gauge. (2) Sensitivity experiments conducted on the RaProM method revealed that after modifying the discrimination thresholds for drizzle and raindrops, the distributions of drizzle and raindrops were more aligned with ground-based raindrop spectrum observations. Furthermore, these adjustments also showed better consistency with the radar reflectivity factor, Doppler velocity, and velocity spectrum width thresholds used by existing millimeter-wave cloud radars to discriminate between drizzle and raindrops. (3) Various kinds of hydrometeors show different vertical distribution characteristics in three precipitation stages: weak, strong, and weak. In the two weak precipitation stages, hydrometeors mainly existed in the form of snowflakes at altitudes above the zero-degree layer and in the form of drizzle at altitudes below the zero-degree layer. The vertical distribution disparity of hydrometeors between the mountain peak and base sites demonstrates that terrain significantly influences hydrometeors during the precipitation process.
Electrochemical Performance of Pre-Modified Birch Biochar Monolith Supercapacitors by Ferric Chloride and Ferric Citrate
Authors: Song Ziyue , Feng Tianjie , Kirk Donald W. , Jia Charles Q.
Published: January 2025

This study investigated the electrochemical properties of supercapacitors by pre-modifying thick birch biochar monoliths with FeCl3 or C6H5FeO7 solutions prior to wood pyrolysis. The pre-modification introduced iron species to the surface, promoting the specific surface area, charge-stored species, and surface functionalities, which enhanced the gravimetric capacitance. X-ray diffraction confirmed the successful loading of Fe3O4 and Fe. SEM implied the wider distribution of iron-rich particulates and porous carbon via self-pyrolysis on the biochar surface modified with 1.0 M C6H5FeO7. Contact angle measurements demonstrated the enhanced wettability of the biochar surfaces following pre-modification, with the C6H5FeO7-modified samples exhibiting superior wettability compared to the other groups. The gravimetric capacitance of the supercapacitor was dramatically promoted and reached 210 F/g and 219 F/g, respectively, when modified with 1.0M C6H5FeO7 and 1.0 M FeCl3 at a 5 mA/g current density. Compared to the birch biochar modified with 1.0 M FeCl3, the 1.0 M C6H5FeO7 had a higher current response peak and capacitive behavior in the CV analysis, demonstrated better ion diffusion capacity, and had lower charge-transfer resistance in the EIS results. But, a slight irreversible process on the electrode of the 1.0 M C6H5FeO7 group led to a lower level of the supercapacitor capacitance retention. The results using ferric solution pre-impregnation show how iron species doping can improve capacitance behavior, providing a feasible scheme for the modification of thick biochar monolith.
Force-Driven Model for Automated Clear Aligner Staging Design Based on Stepwise Tooth Displacement and Rotation in 3D Space
Authors: Yang Sensen , Cheng Yumin
Published: January 2025

This study introduced a novel force-driven automated staging design method for clear aligners, aimed at enhancing treatment planning efficiency and outcomes. The method simplified the alignment process into a force-driven mechanics model that calculates forces and moments exerted on teeth while adhering to Newton’s third law, determining their displacement and rotation at each position. An optimal path was generated by iteratively moving teeth from their initial to target positions and subsequently divided into stages based on a predefined step size. The algorithm was implemented in C++ and incorporated into the WebGL-based SmarteeCheck3.0 software for visualization. In a maxillary extraction case, the automated staging method (0.25 mm step size) generated 51 stages in merely 5 s, while manual staging (>0.25 mm step size) necessitated 30 min to achieve 55 stages. In a molar distalization case, the automated method demonstrated similar efficiency advantages, generating 30 stages for the maxilla and 34 for the mandible, compared to 41 stages each in manual staging. The automated staging approach yielded shorter and more precise tooth movement paths that adhered to aligner biomechanics and physical principles, surpassing the limitations of manual staging. For cases requiring entire arch displacement, the method incorporated sequential movements with anchorage control to maintain force equilibrium. This innovative method substantially improved design efficiency and accuracy, ultimately elevating the efficacy of clear aligner therapy, although further biomechanical analyses and experimental validations are needed to refine the model parameters.
Contactless Fatigue Level Diagnosis System Through Multimodal Sensor Data
Authors: Lee Younggun , Lee Yongkyun , Kim Sungho , Kim Sitae , Yoo Seunghoon
Published: January 2025

Fatigue management is critical for high-risk professions such as pilots, firefighters, and healthcare workers, where physical and mental exhaustion can lead to catastrophic accidents and loss of life. Traditional fatigue assessment methods, including surveys and physiological measurements, are limited in real-time monitoring and user convenience. To address these issues, this study introduces a novel contactless fatigue level diagnosis system leveraging multimodal sensor data, including video, thermal imaging, and audio. The system integrates non-contact biometric data collection with an AI-driven classification model capable of diagnosing fatigue levels on a 1 to 5 scale with an average accuracy of 89%. Key features include real-time feedback, adaptive retraining for personalized accuracy improvement, and compatibility with high-stress environments. Experimental results demonstrate that retraining with user feedback enhances classification accuracy by 11 percentage points. The system’s hardware is validated for robustness under diverse operational conditions, including temperature and electromagnetic compliance. This innovation provides a practical solution for improving operational safety and performance in critical sectors by enabling precise, non-invasive, and efficient fatigue monitoring.
Mathematical Model-Based Optimization of Trace Metal Dosage in Anaerobic Batch Bioreactors
Authors: Kegl Tina , Paramasivan Balasubramanian , Maharaj Bikash Chandra
Published: January 2025

Anaerobic digestion (AD) is a promising and yet a complex waste-to-energy technology. To optimize such a process, precise modeling is essential. Developing complex, mechanistically inspired AD models can result in an overwhelming number of parameters that require calibration. This study presents a novel approach that considers the role of trace metals (Ca, K, Mg, Na, Co, Cr, Cu, Fe, Ni, Pb, and Zn) in the modeling, numerical simulation, and optimization of the AD process in a batch bioreactor. In this context, BioModel is enhanced by incorporating the influence of metal activities on chemical, biochemical, and physicochemical processes. Trace metal-related parameters are also included in the calibration of all model parameters. The model’s reliability is rigorously validated by comparing simulation results with experimental data. The study reveals that perturbations of 5% in model parameter values significantly increase the discrepancy between simulated and experimental results up to threefold. Additionally, the study highlights how precise optimization of metal additives can enhance both the quantity and quality of biogas production. The optimal concentrations of trace metals increased biogas and CH4 production by 5.4% and 13.5%, respectively, while H2, H2S, and NH3 decreased by 28.2%, 43.6%, and 42.5%, respectively.
Regional Gene Therapy for Bone Tissue Engineering: A Current Concepts Review
Authors: Gallo Matthew C. , Elias Aura , Reynolds Julius , Ball Jacob R. , Lieberman Jay R.
Published: January 2025

The management of segmental bone defects presents a complex reconstruction challenge for orthopedic surgeons. Current treatment options are limited by efficacy across the spectrum of injury, morbidity, and cost. Regional gene therapy is a promising tissue engineering strategy for bone repair, as it allows for local implantation of nucleic acids or genetically modified cells to direct specific protein expression. In cell-based gene therapy approaches, a variety of different cell types have been described including mesenchymal stem cells (MSCs) derived from multiple sources—bone marrow, adipose, skeletal muscle, and umbilical cord tissue, among others. MSCs, in particular, have been well studied, as they serve as a source of osteoprogenitor cells in addition to providing a vehicle for transgene delivery. Furthermore, MSCs possess immunomodulatory properties, which may support the development of an allogeneic “off-the-shelf” gene therapy product. Identifying an optimal cell type is paramount to the successful clinical translation of cell-based gene therapy approaches. Here, we review current strategies for the management of segmental bone loss in orthopedic surgery, including bone grafting, bone graft substitutes, and operative techniques. We also highlight regional gene therapy as a tissue engineering strategy for bone repair, with a focus on cell types and cell sources suitable for this application.
Predicting the Impact of Climate Change on the Distribution of North China Leopards (Panthera pardus japonensis) in Gansu Province Using MaxEnt Modeling
Authors: Yang Yongqiang , Gao Wenjie , Han Yapeng , Zhou Tianlin
Published: January 2025

Climate change has a profound impact on the phenology and growth of vegetation, which in turn influences the distribution and behavior of animal communities, including prey species. This dynamic shift significantly affects predator survival and activities. This study utilizes the MaxEnt model to explore how climate change impacts the distribution of the North China leopard (Panthera pardus japonensis) in the Ziwuling region of Gansu Province, China. As an endemic subspecies and apex predator, the North China leopard is vital for maintaining the structure and function of local ecosystems. Unfortunately, its population faces several threats, including habitat change, interspecies competition, and human encroachment, all of which are compounded by the ongoing effects of climate change. To assess the requirement and quality of habitat for this species, we conducted a population survey in the Ziwuling area from May 2020 to June 2022, utilizing 240 infrared cameras, which identified 46 active leopard sites. Using the MaxEnt model, we simulated habitat suitability and future distribution under different climate change scenarios based on nine environmental variables. Our results indicate that the population distribution of North China leopards is primarily influenced by the mean diurnal range (Bio2), with additional sensitivity to isothermal conditions (Bio3), temperature seasonality (Bio4), maximum temperature of the warmest month (Bio5), and annual temperature range (Bio7). We also evaluated habitat suitability across three socioeconomic pathways (SSP126, SSP245, and SSP585) for three time intervals: the 2050s (2041–2060), the 2070s (2061–2080), and the 2090s (2081–2100). The findings suggest a significant decline in high-suitability habitat for North China leopards, while areas of medium and low suitability are projected to increase. Understanding these distributional changes in North China leopards will enhance our comprehension of the region’s biogeography and inform conservation strategies aimed at mitigating the impacts of climate change.
Reference Data for a Treadmill-Based Peak Oxygen Uptake (VO2peak) in Older Adults
Authors: Sagat Peter
Published: January 2025

Background: Although the level of cardiorespiratory fitness (CRF) in older adults has been well documented, little evidence has been provided regarding sex- and age-specific reference standards. Therefore, the main purpose of the study was to examine objectively measured CRF in older adults based on sex and age. Methods: This observational study included 450 men (N = 170) and women (N = 280) aged ≥60 years with mean ± standard deviation (SD) for age (67.4 ± 5.4), height (165.7 ± 8.6 cm), weight (75.1 ± 13.3 kg) and body mass index (BMI, 27.1 ± 3.9 kg/m2). Participants performed an incremental exercise ramp test until exhaustion on a treadmill, and the outcome of CRF was presented as peak oxygen uptake (VO2peak) in milliliters per kilogram of body mass per minute (ml/kg/min). Results: Relative VO2peak values were 37.3 ± 7.1, 30.3 ± 6.6, 24.8 ± 5.4 and 21.7 ± 5.8 mL/kg/min for men aged 60–64 years, 65–69 years, 70–74 years and ≥75 years. For the same age groups in women, values were 30.5 ± 4.8, 27.1 ± 5.4, 22.4 ± 3.4 and 18.9 ± 4.7 mL/kg/min. Age-related declines were observed in both men and women (p < 0.001). In a sex–age interaction term, significant main effects occurred, where men in every age group exhibited higher VO2peak values, compared to women in the same age groups. Conclusions: This study shows that CRF needs to be assessed by considering sex and age as significant predictors. Thus, sex- and age-specific reference findings may serve as an avenue to monitor, track and compare between older adults of different nationalities.
Investigation of the Influence of Hypercapnia on the Physiology of Ovigerous West Coast Rock Lobsters, Jasus lalandii, and Their Embryonic Development
Authors: Ritter Annika , Bridges Christopher R. , Auerswald Lutz
Published: January 2025

The West Coast rock lobster, Jasus lalandii, is a key ecological species and provides an important fishery resource in South Africa and Namibia. It is found along the west coast of southern Africa in the dynamic Benguela Current upwelling system. The low seawater pH of this system is expected to decline further due to ocean acidification and increase in upwelling in terms of frequency and severity. The lobster has therefore to respond to frequent and rapid changes in pH and other environmental impacts that are predicted to become more adverse in future. Although responses to such conditions are known for mature male and juvenile lobsters, there is a lack of information on mature females and later embryonic development. We addressed this by analysing the sensitivity of ovigerous (“berried”) female WCRLs and their eggs/embryos to hypercapnia (high pCO2, low pH) and formulated the following research questions: (1) Can berried female WCRLs respond swiftly to large changes in pH? (2) What physiological mechanisms facilitate a potential response to a rapidly declining pH, i.e., acute hypercapnia? (3) Does a potential response persist during prolonged hypercapnia? (4) Are eggs/embryos impacted by hypercapnia? To investigate this, we exposed berried WCRLs to acute (pH 7.5) and chronic (up to 60 days at pH 7.5 and 7.8) hypercapnia. We applied extracellular acid–base analysis, microscopic examination of egg growth and development, and SEM of female exoskeleton structure and egg membranes. The results revealed that berried females efficiently respond to acute and chronic hypercapnia by means of increasing bicarbonate concentrations in the haemolymph. Moreover, embryo growth and development are not impacted by chronic hypercapnia, but growth shows geographical area-specific differences. We conclude that females and embryos of J. lalandii are as resilient to hypercapnia as previously shown for males and juveniles.
Gintonin Binds to Reduced LPA4 Receptor Subtype in Human Cortical Neurons in Alzheimer’s Disease Brains
Authors: Kim Kyu-Sung , Lee Rami , Park Inyeong , Hwang Sung-Hee , Kim Yeshin , Jang Jae-Won , Kim Hyung-Seok , Choi Seong-Min , Kim Sang Jin , Cho Hwa Jin , Cho Ik-Hyun , Kim Jong-Hoon , Kim Do-Geun , Nah Seung-Yeol
Published: January 2025

Ginseng, a traditional herbal medicine with a long history of use, is known to support human health, particularly by influencing brain function. Recent studies have identified gintonin, a lysophosphatidic acid (LPA) receptor ligand derived from ginseng, as a key bioactive. However, the specific LPA receptor subtypes targeted by gintonin in the human brain to exert its anti-Alzheimer’s (AD) effects remain unclear. This study aimed to elucidate the LPA receptor subtype targeted by gintonin in the human cortex. Using a fluorescent gintonin conjugate, we investigated receptor binding in cortical samples from healthy individuals (n = 4) and AD patients (n = 4). Our results demonstrated that fluorescent gintonin selectively binds to human cortical neurons rather than glial cells and that gintonin-binding sites are co-localized with the LPA4 receptor subtype. Furthermore, the expression of LPA4 receptors was significantly reduced in the cortical neurons of AD patients. These results suggest that the LPA4 receptor may serve as a novel histopathological marker for AD and represent a promising therapeutic target for gintonin-based prevention and treatment strategies.
Possible Involvement of Lysophospholipids in Severe Asthma as Novel Lipid Mediators
Authors: Kume Hiroaki , Kazama Kentaro , Sato Riko , Sato Yuki
Published: January 2025

In severe asthma, symptoms are unstable despite intensive treatment based on high doses of inhaled corticosteroids and on-demand use of oral corticosteroids. Although, recently, various biological agents related to Th2 cytokines have been added to intensive controller medications for severe asthma, a significant progress has not been observed in the management for symptoms (dyspnea, wheezing and cough). Medical treatment focused on Type 2 inflammation is probably insufficient to maintain good long-term management for severe asthma. Airway eosinophilia and decreased reversibility in forced expiratory volume in 1 second (FEV1) are listed as major predictors for exacerbation-prone asthma. However, it is generally considered that asthma is complex and heterogeneous. It is necessary to establish precision medicine using treatable traits based on a multidimensional approach related to asthma. Since phospholipids generate lysophospholipids and arachidonic acid by phospholipases, lysophospholipids can be associated with the pathogenesis of this disease via action on smooth muscle, endothelium, and epithelium in the airways. Lysophosphatidic acid (LPA), lysophosphatidylcholine (LPC), and sphingosine 1-phosphate (S1P) are increased in bronchoalveolar fluid after allergen challenge. LPA, LPC, and S1P recruit eosinophils to the lungs and cause β2-adrenergic desensitization. LAP and S1P cause contraction and hyperresponsiveness in airway smooth muscle. Moreover, lysophosphatidylserine and S1P are associated with the allergic reaction related to IgE/FcεRI in mast cells. Lysophospholipid action is probably comprised of corticosteroid resistance and is independent of Type 2 inflammation, and may be corelated with oxidative stress. Lysophospholipids may be a novel molecular target in advancing the management and treatment of asthma. This review discusses the clinical relevance of lysophospholipids in asthma.
Mitochondrial Transplantation in Animal Models of Psychiatric Disorders: A Novel Approach to Psychiatric Treatment
Authors: Iwata Keiko , Noguchi Masafumi , Shintani Norihito
Published: January 2025

Mitochondria are essential for brain function, and accumulating evidence from postmortem brain studies, neuroimaging, and basic research indicates mitochondrial impairments in patients with psychiatric disorders. Restoring mitochondrial function therefore represents a promising therapeutic strategy for these conditions. Mitochondrial transplantation, an innovative approach that uses functional mitochondria to repair damaged cells, has demonstrated efficacy through various delivery methods in cell, animal, and animal disease models. This review explores the critical link between mitochondria and psychiatric disorders and provides an overview of mitochondrial transplantation as a therapeutic intervention. It highlights recent advances in mitochondrial transplantation in animal models of psychiatric disorders, focusing on delivery methods, the timing of administration, and the integration of exogenous mitochondria into brain cells. The potential therapeutic effects and the mechanisms that underlie these effects are discussed. Additionally, this review evaluates the clinical relevance, challenges, and future strategies for the application of mitochondrial transplantation in the treatment of psychiatric disorders.
The Causal Relationships and Therapeutic Targets of Plasma Proteins in Ankylosing Spondylitis
Authors: Wen Pengfei , Yang Mingyi , Wang Yidian , Niu Yuyu , Yang Peng , Hu Shouye , Liu Lin , Yang Zhi
Published: January 2025

Objective: The purpose of this study was to assess the causal effects of circulating plasma proteins on ankylosing spondylitis (AS) and to explore potential therapeutic targets. Methods: The study used protein quantitative trait loci (pQTLs) for thousands of plasma proteins from nine genome-wide association studies (GWAS) as instrumental variables. The relationship between genetically predicted plasma proteins and AS was assessed through Mendelian randomization (MR) analysis. Further analyses, including colocalization analysis, Steiger filtering analysis, protein-altering variant assessment, protein–protein interaction (PPI), and pathway enrichment analysis, were conducted to validate the robustness and causal direction of the results, as well as to investigate the protein functions and potential drug targets. Results: Nine unique proteins were found to have strong causal associations with AS. Steiger filtering analysis confirmed that all associations identified by MR analysis have a direct causal link from the proteins to AS. Colocalization analysis identified four unique proteins—Interleukin-6 receptor alpha (IL-6Rα), Interleukin-23 receptor (IL-23R), Thrombospondin-2 (THBS2), and Interleukin-1 receptor type 2 (IL-1R2)—that share the same causal variants with AS. PPI and pathway enrichment analysis revealed the potential roles of these proteins in inflammatory responses and immune regulation. Moreover, these proteins were valuable drug targets or considered druggable. Conclusions: This study has identified multiple plasma proteins associated with AS, revealing the important roles of these proteins in the pathogenesis of AS and providing potential therapeutic targets for AS.
Italian Coma Recovery Scale for Pediatrics (CRS-P): Preliminary Validation in a Sample of Young Children with Typical Development
Authors: Colombo Katia , Corti Claudia , Porro Chiara , Fedeli Claudia , Beschi Monica , Reverberi Cristina , Strazzer Sandra
Published: January 2025

Background/Objectives: Guidelines for the diagnosis of children with disorder of consciousness (DoC) in pediatric age have not been defined yet. Assessment tools designed for adults have generally not been standardized for pediatrics, which could lead to misdiagnosis due to the limited behavioral repertoire of children. This study aims at examining the basic psychometric properties of the Italian Coma Recovery Scale for Pediatrics (CRS-P) in typically developing children. Methods: A total of 64 typically developing children aged 3 months to 5:7 years were administered the CRS-P. Performance was examined across the age range, and for the two behaviors indicating emergence to a conscious state, namely functional object use (FOU) and functional communication (FC). Results: Inter-rater reliability ranged from 0.95 to 1 for subscale and total scores. All children aged ≥34 months scored at the CRS-P ceiling. All children ≥ 14 months met the criteria for FOU and all children ≥ 34 months met those for FC. Children as early as 3 months of age displayed behaviors discriminating between vegetative state (VS) and minimally conscious state (MCS) in the Visual and Motor subscales. Language-based behaviors of MCS in other subscales were consistently displayed by older children. Conclusions: Typically developing children met the criteria for all items of the Italian CRS-P by 34 months, which suggests caution in adopting the scale at a younger age. However, the features of the distinct stages of DoC could be captured earlier, based on the various subscales. Modifications should be made to some items to improve diagnostic accuracy.
The Patients’ Long-Term Insight into Day-to-Day Functioning After Establishing the Functional Seizures Diagnosis
Authors: Lazovic Jelena , Radojicic Ognjen , Bozovic Ivo , Pejovic Aleksa , Sokic Dragoslav
Published: January 2025

Background/Objectives: Functional seizures (FSs) are paroxysmal, time-limited events with motor, sensory, autonomic, or cognitive manifestations related to pathophysiological processes other than abnormal electric discharges in the brain. However, these seizures are often followed by different psychiatric comorbidities. Their impact on the overall quality of life and the cofounding factors, especially the ones that can be treated, were the main investigation aims of this study. Methods: This study comprised 76 patients who were diagnosed with FSs. This study included patients who were diagnosed with FSs via video-EEG telemetry. We used the “Likert scale” from the QOLIE 31 questionnaire to evaluate patients’ subjective perception of their quality of life. We researched the association of various clinical factors with the subjective QoL score. Results: A statistically significant marginal association was shown for seven variables, four of them with a positive association (subjective perception of disease severity, belief in treatments’ positive effects, functional seizure cessation, and not being afraid of next seizure) and three of them with a negative association (age at FS onset, depression symptoms, and current age of life). After Bonferroni correction for multiple testing only symptoms of depression stayed statistically significantly associated with outcome. Multivariable logistic regression following variable selection identified that six variables (age at FS onset, absence of psychiatric testing, perceiving oneself as mentally changed due to the disease, seizure severity, depressive symptoms, and fear of therapy side effects) were statistically significantly negatively associated with the outcome. Conclusions: It seems that patients who have FSs coexisting with depressive symptoms and also those with worse disease perception have less chances to be satisfied with their overall quality of life.
Ouabain Counteracts Retinal Ganglion Cell Death Through Modulation of BDNF and IL-1 Signaling Pathways
Authors: Oliveira Amanda Candida da Rocha , Figueiredo Camila Saggioro , Raony Ícaro , Von-Held-Ventura Juliana Salles , Granja Marcelo Gomes , Mázala-de-Oliveira Thalita , Pedrosa-Soares Vinícius Henrique , dos Santos Aline Araujo , Giestal-de-Araujo Elizabeth
Published: January 2025

Background: Ouabain is a steroid hormone that binds to the sodium pump (Na+, K+-ATPase) at physiological (nanomolar) concentrations, activating different signaling pathways. This interaction has been shown to prevent the axotomy-induced death of retinal ganglion cells (RGCs), although the underlying mechanisms remain unclear. Objective: In this study, we investigated potential mechanisms by which ouabain promotes RGC survival using primary cultures of rat neural retina. Results: Our findings indicate that ouabain regulates brain-derived neurotrophic factor (BDNF) signaling in retinal cells via matrix metalloproteinase-9-mediated processing of proBDNF to mature BDNF (mBDNF) and by increasing the phosphorylation of the mBDNF receptor, tropomyosin-related receptor kinase B. Ouabain also enhances the maturation of interleukin (IL)-1β through the increased activation of caspase-1, which mediates the processing of proIL-1β into IL-1β, and transiently upregulates both IL-1 receptor and IL-1 receptor antagonist (IL-1Ra). Treatment using either IL-1β or IL-1Ra alone is sufficient to enhance RGC survival similarly to that achieved with ouabain. Finally, we further show that ouabain prevents RGC death through a complex signaling mechanism shared by BDNF and IL-1β, which includes the activation of the Src and protein kinase C pathways. Conclusions: Collectively, these results suggest that ouabain stimulates the maturation and signaling of both BDNF and IL-1β, which act as key mediators of RGC survival.
Effectiveness of Adding a Pain Neuroscience Education Program to a Multimodal Physiotherapy Intervention in Patients with Chronic Shoulder Pain: A Randomized Clinical Trial
Authors: Delgado-Gil Jose Angel , Prado-Robles Eva , Muñoz-Alcaraz María Nieves , Seco-Calvo Jesús
Published: January 2025

Objectives: The purpose of this study was to assess the efficacy of a pain neuroscience education program completed by patients with shoulder pain. Methods: A randomized, controlled trial was performed. Fifty-five patients satisfied the eligibility criteria, agreed to participate, and were randomized into an experimental group (n = 27) or control group (n = 28). A manual therapy and exercises program was administered for both groups. The experimental group also received a 4-week pain neuroscience education protocol (1 session/week, 75 min per session). The measurements taken included the active range of motion, pain, disability, catastrophizing, kinesiophobia, and therapeutic alliance. The outcomes were assessed at baseline and 5 weeks after completion of treatment. The primary outcome analyzed was the group × time interaction. Results: The 2 × 2 analysis of variance revealed a significant group × time interaction for the active range of motion (F = 15.27; p = 0.011), disability (F = 6.14; p = 0.01), catastrophizing (F = 8.79; p = 0.01), kinesiophobia (F = 7.62; p = 0.008), and therapeutic alliance (p = 0.03) in favor of the experimental group. Conclusions: This study showed that the patients with shoulder pain who completed the pain neuroscience program achieved significantly better results in terms of their active range of motion, disability, catastrophizing, kinesiophobia, and therapeutic alliance compared to those achieved by the control group. Therefore, pain neuroscience education may be beneficial in the treatment of patients with shoulder pain.