bluuebunny/crossref_metadata_2025 huggingface dataset:
EEG channel and feature investigation in binary and multiple motor imagery task predictions
Authors: Degirmenci Murside , Yuce Yilmaz Kemal , Perc Matjaž , Isler Yalcin
Published: December 2024

Introduction

Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high classification accuracy. Although various machine learning methods have already proven useful to that effect, the use of many features and ineffective EEG channels often leads to a complex structure of classifier algorithms. State-of-the-art studies were interested in improving classification performance with complex feature extraction and classification methods by neglecting detailed EEG channel and feature investigation in predicting MI tasks from EEGs. Here, we investigate the effects of the statistically significant feature selection method on four different feature domains (time-domain, frequency-domain, time-frequency domain, and non-linear domain) and their two different combinations to reduce the number of features and classify MI-EEG features by comparing low-dimensional matrices with well-known machine learning algorithms.

Methods

Our main goal is not to find the best classifier performance but to perform feature and channel investigation in MI task classification. Therefore, the detailed investigation of the effect of EEG channels and features is implemented using a statistically significant feature distribution on 22 EEG channels for each feature set separately. We used the BCI Competition IV Dataset IIa and 288 samples per person. A total of 1,364 MI-EEG features were analyzed in this study. We tested nine distinct classifiers: Decision tree, Discriminant analysis, Logistic regression, Naive Bayes, Support vector machine, k-Nearest neighbor, Ensemble learning, Neural networks, and Kernel approximation.

Results

Among all feature sets considered, classifications performed with non-linear and combined feature sets resulted in a maximum accuracy of 63.04% and 47.36% for binary and multiple MI task predictions, respectively. The ensemble learning classifier achieved the maximum accuracy in almost all feature sets for binary and multiple MI task classifications.

Discussion

Our research thus shows that the statistically significant feature-based feature selection method significantly improves the classification performance with fewer features in almost all feature sets, enabling detailed and effective EEG channel and feature investigation.
An all integer-based spiking neural network with dynamic threshold adaptation
Authors: Zou Chenglong , Cui Xiaoxin , Feng Shuo , Chen Guang , Zhong Yi , Dai Zhenhui , Wang Yuan
Published: December 2024

Spiking Neural Networks (SNNs) are typically regards as the third generation of neural networks due to their inherent event-driven computing capabilities and remarkable energy efficiency. However, training an SNN that possesses fast inference speed and comparable accuracy to modern artificial neural networks (ANNs) remains a considerable challenge. In this article, a sophisticated SNN modeling algorithm incorporating a novel dynamic threshold adaptation mechanism is proposed. It aims to eliminate the spiking synchronization error commonly occurred in many traditional ANN2SNN conversion works. Additionally, all variables in the proposed SNNs, including the membrane potential, threshold and synaptic weights, are quantized to integers, making them highly compatible with hardware implementation. Experimental results indicate that the proposed spiking LeNet and VGG-Net achieve accuracies exceeding 99.45% and 93.15% on the MNIST and CIFAR-10 datasets, respectively, with only 4 and 8 time steps required for simulating one sample. Due to this all integer-based quantization process, the required computational operations are significantly reduced, potentially providing a substantial energy efficiency advantage for numerous edge computing applications.
Exploring neural mechanisms of gender differences in bodily emotion recognition: a time-frequency analysis and network analysis study
Authors: Feng Tingwei , Mi Mingdi , Li Danyang , Wang Buyao , Liu Xufeng
Published: December 2024

Background

This study aimed to explore the neural mechanisms underlying gender differences in recognizing emotional expressions conveyed through body language. Utilizing electroencephalogram (EEG) recordings, we examined the impact of gender on neural responses through time-frequency analysis and network analysis to uncover gender disparities in bodily emotion recognition.

Methods

The study included 34 participants, consisting of 18 males and 16 females. A 2 × 2 mixed design was employed, with gender (male and female) and bodily emotion (happy and sad) as the independent variables. Both behavioral and EEG data were collected simultaneously.

Results

Males demonstrated more stable brain activity patterns when recognizing different bodily emotions, while females showed more intricate and highly interconnected brain activity networks, especially when identifying negative emotions like sadness. Differences based on gender were also observed in the significance of brain regions; males had greater importance in central brain areas, whereas females exhibited higher significance in the parietal lobe.

Conclusion

Gender differences do influence the recognition of bodily emotions to some extent. The primary aim of this study was to explore the neural mechanisms underlying gender differences in bodily emotion recognition, with a particular focus on time-frequency analysis and network analysis based on electroencephalogram (EEG) recordings. By elucidating the role of gender in cognitive development, this study contributes to early detection and intervention.
Prmt1-mediated histone H4R3me2a methylation regulates the proliferation, migration and invasion of laryngeal cancer cells by affecting the expression level of NCOA5
Authors: Li Linlu , Cui Jiao , Li Xiaoyu , Zhu Yuting , Wu Hongfei , Zhou Lanzhu
Published: December 2024

Background

Laryngeal cancer is a common head and neck cancer, and its occurrence and development are closely related to a variety of epigenetic modifications. protein arginine methyltransferase 1 (PRMT1) is an important type I protein arginine methyltransferase, which catalyzes the monomethylation and asymmetric dimethylation of arginine and participates in the occurrence and development of a variety of cancers. Current research has found that the expression of PRMT1 is increased in laryngeal carcinoma tissues. Histone modifications play a key role in regulating gene expression and maintaining cellular function. In particular, histone H4 arginine 3 dimethylation (H4R3me2a) has been shown to be associated with the development of a variety of cancers. Nuclear Receptor Coactivator 5 (NCOA5) is an important nuclear receptor coactivator, which regulates gene expression through the interaction between various nuclear receptors and other transcription factors. The present study aimed to investigate how PRMT1-mediated H4R3me2a methylation affects the proliferation, migration and invasion of laryngeal cancer cells and to verify the role of NCOA5 in this process.

Methods

The expression of PRMT1 and NCOA5 was inhibited by siRNA mediated gene knockdown in laryngeal cancer cells. The changes of H4R3me2a protein levels were detected by Western Blotting, and cell proliferation, migration and invasion abilities were evaluated by CCK-8, cell scratch assay, Transwell migration and invasion assay. RT-qPCR was used to detect the mRNA expression levels of related genes. The overexpression experiment of NCOA5 was carried out by constructing overexpression vector to verify its effect.

Results

After PRMT1 knockdown, the expression of H4R3me2a in laryngeal cancer cells was significantly decreased, and the cell proliferation, migration and invasion abilities were weakened. Similarly, knockdown of NCOA5 expression also resulted in decreased H4R3me2a levels and attenuated cell proliferation, migration and invasion. Overexpression of NCOA5 partially restored H4R3me2a levels and cell proliferation, migration and invasion abilities.
Digital workplace technology intensity: qualitative insights on employee wellbeing impacts of digital workplace job demands
Authors: Marsh Elizabeth , Perez Vallejos Elvira , Spence Alexa
Published: December 2024

Introduction

Digital workplace technologies are powerful enablers in modern organizations but can also threaten employee wellbeing. Drawing on the Job Demands-Resources (JD-R) model, this study explores digital workplace job demands, including hyperconnectivity and overload, and their association with health impairment.

Methods

Using a qualitative approach, semi-structured interviews were conducted with 14 employees to capture their experiences of these phenomena. A Critical Realist Reflexive Thematic Analysis was employed to investigate tendencies among digital workers and to draw theoretical links that might reveal underlying mechanisms.

Results

Five overarching themes were identified: hyperconnectivity, techno-overwhelm, digital workplace hassles, Fear of Missing Out, and techno-strain. A connecting thread between these themes is the new concept we label Digital Workplace Technology Intensity, mirroring the dynamics of the existing construct of work intensity.

Discussion

The findings extend JD-R theory by highlighting the wellbeing challenges posed by digital workplace job demands. They emphasize the need for organizations to address the mental and physical health ramifications of the dark side of digital working.
Advances and challenges of prenatal interventions for fetal tachyarrhythmias
Authors: Tang Jiao , Huang Pujue , Deng Xue , Zhao Lijuan , Zhai Yang , Wang Tao
Published: December 2024

It is estimated that 1%–2% of pregnancies are complicated by fetal arrhythmias, with most arrhythmias considered benign and not requiring further treatment or intervention. However, persistent tachyarrhythmias can lead to fetal heart failure, preterm birth, stillbirth, and increased risks during the perinatal period. Therefore, timely treatment during pregnancy is often necessary. Currently, prenatal treatment for fetal tachyarrhythmias (FTs) is primarily drug based, aiming to restore normal fetal heart rate, prevent or reverse fetal heart failure, and avoid adverse outcomes such as preterm birth and stillbirth. Despite decades of clinical experience, the lack of prospective, multicenter randomized clinical trials on the safety and efficacy of drugs means that there is still no universally accepted prenatal treatment regimen for FTs, and treatment relies on series of observational studies or clinical cases. Moreover, all drug treatments carry potential risks to the mother, fetus, and pregnancy, hence the need for more clinical diagnostic and therapeutic experience to provide more clinical evidence for prenatal treatment of FTs.
Enhanced glucose production in norepinephrine and palmitate stimulated hepatocytes following endurance training
Authors: Sumida Ken D. , Lordan Vera M. , Donovan Casey M.
Published: December 2024

Enhanced hepatic gluconeogenesis plays an important role in exercise glucose homeostasis when hepatic glycogen stores are depleted. Livers from trained animals demonstrate greater rates of gluconeogenesis in the presence of elevated substrate with and without hormonal stimulation. Training has been reported to have a particularly profound impact on norepinephrine-stimulated gluconeogenesis, but this was only demonstrated in the presence of other gluconeogenic hormones. Here we reexamine the impact of endurance training on norepinephrine-stimulated gluconeogenesis in the absence of any other hormones. Isolated hepatocytes from trained and untrained rats were incubated in 6 mM lactate with various concentrations of norepinephrine (0 nM–20 nM). Absent norepinephrine, gluconeogenic rates were significantly greater from trained hepatocytes compared to controls (97.2 ± 6.7 vs 57.6 ± 8.7 nmol/mg protein; p < 0.01). In the presence of NE (0.5–20 nM), gluconeogenesis from trained liver cells was significantly greater at all NE concentrations compared to controls. The NE-stimulated increase in gluconeogenesis above basal (0 nM NE) was also greater for trained vs control (36% vs 19%, respectively). Concomitant with the max NE-stimulated increase in gluconeogenesis, lactate uptake was significantly elevated for trained vs. control hepatocytes (307.22 ± 44.5 vs 124.5 ± 23.9 nmol/mg protein; p < 0.01), with lactate uptake quantitatively accounting for the entire increase in gluconeogenesis for trained hepatocytes. Endurance training was also observed to significantly elevate glucose production in presence of 0.6 mM palmitate, both in the absence and presence of NE. These findings confirm that hepatocytes from endurance-trained animals demonstrate enhanced rates of NE-stimulated gluconeogenesis, as well as palmitate-stimulated glucose production.
Effects of a play-based approach on psychosocial variables in federated long- and middle-distance athletes
Authors: Valero-Valenzuela Alfonso , Hoyos Cuartas Luz Amalia , Heredia-León Diego Andrés , León-Guereño Patxi
Published: December 2024

Introduction

Considering the theory of self-determination and its relationship with human motivation and the play-based approach (PBA), a training program is implemented in young middle and long-distance running athletes with play activities (simple tasks with rules in a ludic mood). The objectives were (1) to analyze the effects of a PBA on the autonomy support interpersonal teaching style (ASITS) perceived by athletes, the psychological variables of satisfaction of basic psychological needs, motivation, enjoyment and intention to continue practicing athletics and depending on sex, and (2) know the athletes' perception of this methodology after the intervention.

Method

Quasi- experimental design with a sample of 50 athletes (27 women and 23 men) with 17.22 average of age and federated at the regional level.

Instruments

Autonomy Support Scale (ASS), Psychological Need Satisfaction in Exercise Scale (PNSE), Behavior Regulation in Sports Questionnaire (BRSQ), Measure of Intention to be Physically Active (MIPA) and Intrinsic Satisfaction in Sports Questionnaire (ISSQ).

Results

Significant changes were identified in favor of the experimental group compared to the control group in ASITS and autonomous motivation. Over time, only the experimental group showed positive changes in the ASITS variable, self-determination index, autonomous motivation, and intention to continue practicing athletics. The women in the experimental group presented higher values in the self-determination index, autonomous motivation and intention to continue practicing athletics, while the women in the control group only in the ASITS variable in the pre-test. The young people who practiced playing during the warm-up reported high levels of fun and motivation, and interest in the activity, as well as concern about being prepared for the main part of the session.

Discussion

It is suggested to athletic trainers to use a PBA in athletics groups at a regional level to promote an ASITS and its positive consequences at both a psychosocial and cognitive level, although new studies are required, and of longer duration to be able to contrast these findings and their effects on athletic performance.
“When in Rome…”: structural determinants impacting healthcare access, health outcomes, and well-being of South Asian older adults in Ontario using a multilingual qualitative approach
Authors: Chowdhury Diya , Tong Catherine , Lopez Kimberly , Neiterman Elena , Stolee Paul
Published: December 2024

With the increase in international migration, the need for an equitable healthcare system in Canada is increasing. The current biomedical model of healthcare is constructed largely in the Eurocentric tradition of medicine, which often disregards the diverse health perspectives of Canada’s racialized immigrant older adults. As a result, current healthcare approaches (adopted in the US and Canada) fall short in addressing the health needs of a considerable segment of the population, impeding their ability to access healthcare services. This study aimed to identify and understand the structural and systemic factors that influence healthcare experiences and well-being among South Asian older adults in Ontario, addressing a significant gap in empirical and theoretical knowledge in the Canadian context. We conducted in-depth individual and dyadic interviews (n = 28) utilizing a descriptive multilingual cross-cultural qualitative approach. Through this research, participants expressed that their understanding of well-being does not align with that of their healthcare providers, resulting in unmet health needs. Our study uses an intersectional lens to demonstrate participants’ perceptions of virtual access to care and systemic factors, such as mandatory assimilation and whiteness as a taken-for-granted norm impacting the health and well-being of South Asian older adults. The findings of this research can offer valuable insights to healthcare providers and policymakers in developing culturally competent practices, guidelines, and training policies that effectively address the healthcare needs of the South Asian population in Canada.
Predicting depressive symptoms in employees through life stressors: subgroup analysis by gender, age, working hours, and income level
Authors: Moon Jiwan , An Yoosuk , Jeon Sang Won , Cho Sung Joon
Published: December 2024

Background

Although evidence has accumulated regarding the association between various stressors and depression, few studies have considered the context in which multiple stressors coexist simultaneously. Thus, this study aimed to evaluate the relative importance of seven major life stressors on depressive symptoms: workplace stress, family relationships, interpersonal conflicts, health problems, financial strains, traumatic events, and mannerisms, and analyzed its variation in subgroups.

Methods

Data from 12,541 Korean employees were analyzed. Sociodemographic data such as gender, age, education, marital status, working hours, and income level were collected from the study participants, and the Center for Epidemiologic Studies Depression Scale (CES-D) was employed to assess depressive symptoms. Additionally, life stressors experienced during the previous month and their severity were investigated via a questionnaire. Multiple regression analysis was performed to assess the independent effects of seven major life stressors on depressive symptoms, while controlling for sociodemographic factors. Subgroup analysis was also conducted to determine whether the effect of stressors varied by gender, age, working hours, and income level.

Results

Workplace stress (β = 0.411, p < 0.001) had the greatest effect on depressive symptoms, followed by mannerisms (β = 0.191, p < 0.001), family relationships (β = 0.120, p < 0.001), interpersonal conflicts (β = 0.077, p < 0.001), health problems (β = 0.054, p < 0.001), financial strains (β = 0.046, p < 0.001), and traumatic events (β = 0.021, p = 0.002). Moreover, significant variance in the rank order of effects of stressors across gender, age, working hours, and income level was observed, as revealed by subgroup analysis.

Conclusion

This study identified the effects of seven major life stressors on depressive symptoms and suggests that the rank order of these effects varies depending on sociodemographic factors. These findings expand the understanding of the complex relationship between concurrent life stressors and depression, and highlight the need for personalized interventions to prevent and manage depression among Korean employees.
A Google Trends analysis of people's sense of seasons in Hokkaido
Authors: Shin Nagai , Nakagawa Hiromi , Morimoto Hiroshi , Kotani Ayumi
Published: December 2024

Accurate evaluation of the spatiotemporal variability of people's interest in seasons (i.e., their “sense of seasons”) is required to deeply understand temporal changes in the relationship between people and landscape under climate and societal changes. To this end, it is useful to analyze the time series of relative search volume (RSV) for relevant search terms extracted from Google Trends (GT) for any target period and target area. We examined the presence and absence of 12-month seasonality of the time series of RSV for about 300 representative search terms for Hokkaido in Japan, which has vast natural resources and is visited year-round by many tourists from Japan and abroad. In the case of searchers in both all of Japan and Hokkaido alone, search terms categorized into the foods, leisure, natural scenic spots, and seafood fields showed a strong trend toward 12-month seasonality of the time series of RSV, whereas those categorized into the Ainu (indigenous people) and people fields had weak trends for 12-month seasonality. People's sense of seasons in all of Japan or Hokkaido alone was likely associated with tourism (search terms in the animals, festivals, foods, leisure, natural scenic spots, seafood, tourist spots, and vegetation fields), as well as with animal and plant phenology (terms in the animals and vegetation fields), provisioning ecosystem services (terms in the foods and seafood fields), climate (terms in the climate field), and cultural ecosystem services (terms in the animals, festival, foods, leisure, natural scenic spots, seafoods, and vegetation fields). However, search terms with no 12-month seasonality were included in the tourist spots fields: they included many tourist spots visited by tourists all year around. Despite the need to appropriately select a huge number of representative search terms to reduce the effect of GT limitations and the uncertainty caused by unexpected and rapid temporal changes in RSV, the GT analysis allowed us to evaluate the spatiotemporal variability of people's sense of seasons regarding various objects in the landscape, including those related to tourism, under climate and societal changes.
Longitudinal volumetric analysis of in ovo compartments in chicken eggs using ultra-high-field magnetic resonance imaging
Authors: Streckenbach Felix , Schön Hanna , König Julia , Frank Marcus , Langner Inga , Stachs Oliver , Jonitz-Heincke Anika , Langner Sönke , Lindner Tobias , Schätzel Jana
Published: December 2024

Introduction

The chicken egg, with its in ovo compartments, is a widely used and popular animal model in experimental studies. This study aimed to quantify the volumes of the yolk/yolk sac, amniotic fluid, and chicken embryo in ovo using non-invasive ultra-high-field magnetic resonance imaging (UHF-MRI).

Materials and methods

In total, 64 chicken eggs were examined using a 7 T UHF-MRI scanner, acquiring T2-weighted anatomical images of the entire egg from developmental day 1 to 16 (D1-D16). Four eggs were scanned each developmental day, and the volumes of the yolk/yolk sac, amniotic fluid, and embryo were quantitatively assessed.

Results

UHF-MRI facilitated the in ovo quantitative assessment of the yolk/yolk sac starting from D1 and the embryo from D5 onward. The yolk/yolk sac volume increased from D1 to D6 before progressively decreasing until D14. The amniotic cavity could be detected on D6, with its fluid volume increasing steadily until D14. The embryo’s volume increased consistently throughout the developmental period, reaching its peak at D16.

Discussion

UHF-MRI allows in vivo assessment of embryonic development, providing non-invasive, longitudinal insights into the volumes of the yolk/yolk sac, amniotic fluid, and chicken embryo. The investigation method described in this study may provide a standardized model for biomedical research in the developing chicken embryo, supporting various experimental applications.
Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm
Authors: Xu Anqi , Li Hui , Hong Yun , Liu Guoji
Published: December 2024

As the complexity of air gaming scenarios continues to escalate, the demands for heightened decision-making efficiency and precision are becoming increasingly stringent. To further improve decision-making efficiency, a particle swarm optimization algorithm based on positional weights (PW-PSO) is proposed. First, important parameters, such as the aircraft in the scenario, are modeled and abstracted into a multi-objective optimization problem. Next, the problem is adapted into a single-objective optimization problem using hierarchical analysis and linear weighting. Finally, considering a problem where the convergence of the particle swarm optimization (PSO) is not enough to meet the demands of a particular scenario, the PW-PSO algorithm is proposed, introducing position weight information and optimizing the speed update strategy. To verify the effectiveness of the optimization, a 6v6 aircraft gaming simulation example is provided for comparison, and the experimental results show that the convergence speed of the optimized PW-PSO algorithm is 56.34% higher than that of the traditional PSO; therefore, the algorithm can improve the speed of decision-making while meeting the performance requirements.
Normalized Difference Vegetation Index Prediction for Blueberry Plant Health from RGB Images: A Clustering and Deep Learning Approach
Authors: Zaman A. G. M. , Roy Kallol , Olt Jüri
Published: December 2024

In precision agriculture (PA), monitoring individual plant health is crucial for optimizing yields and minimizing resources. The normalized difference vegetation index (NDVI), a widely used health indicator, typically relies on expensive multispectral cameras. This study introduces a method for predicting the NDVI of blueberry plants using RGB images and deep learning, offering a cost-effective alternative. To identify individual plant bushes, K-means and Gaussian Mixture Model (GMM) clustering were applied. RGB images were transformed into the HSL (hue, saturation, lightness) color space, and the hue channel was constrained using percentiles to exclude extreme values while preserving relevant plant hues. Further refinement was achieved through adaptive pixel-to-pixel distance filtering combined with the Davies–Bouldin Index (DBI) to eliminate pixels deviating from the compact cluster structure. This enhanced clustering accuracy and enabled precise NDVI calculations. A convolutional neural network (CNN) was trained and tested to predict NDVI-based health indices. The model achieved strong performance with mean squared losses of 0.0074, 0.0044, and 0.0021 for training, validation, and test datasets, respectively. The test dataset also yielded a mean absolute error of 0.0369 and a mean percentage error of 4.5851. These results demonstrate the NDVI prediction method’s potential for cost-effective, real-time plant health assessment, particularly in agrobotics.
Evolution of Precipitates and Microhardness of L-PBF Inconel 625 Through Relevant Thermal Treatment
Authors: Keya Tahmina , Fischer Ralf D. , Andurkar Mohanish , Thompson Scott M. , O’Donnell Valentina , Gahl John , Prorok Barton C.
Published: December 2024

Laser powder bed fusion (L-PBF) is a metal additive manufacturing (AM) technique that produces a unique microstructure significantly different from wrought microstructure. Inconel 625 (IN625) is an alloy widely used to manufacture complex parts, but it comes with its own unique challenges. The alloy is prone to precipitation under elevated temperatures, which makes designing suitable heat treatment to tailor the desired microstructure and mechanical properties critical. Traditional heat treatment for wrought IN625 cannot be applied to L-PBF IN625; therefore, it is vital to understand the evolution of precipitates on the way to complete recrystallization. This study focuses on these precipitates in IN625 produced by the L-PBF technique. Heat treatments at 700 °C, 900 °C, and 1050 °C were performed separately to encourage the precipitation of strengthening γ″, the detrimental δ phase, and the dissolution of precipitates, respectively. γ″ precipitates were found in the as-printed condition and at 700 °C. δ precipitates were detected at 700 and 900 °C. Carbides and Al-rich oxides were observed in all conditions of L-PBF IN625. Texture analysis showed grain growth along the build direction with strong (100) texture at temperatures up to 900 °C. Weak and random texture with equiaxed grains was observed at 1050 °C, which is similar to wrought IN625.
Research Challenges Relating to Immune-Related Patient Outcomes During Blood Transfusion for Spine Surgery
Authors: Michelle Roets , Sturgess David , Dean Melinda , Van Zundert Andre , Waters Jonathen H.
Published: December 2024

Background: In this manuscript, the challenges encountered during research into patient outcomes following transfusion during spine surgery are explored. Method: A narrative review of transfusion research over decades. Results: An estimated 310 million major surgeries occur in the world each year, and 15% of these patients experience serious adverse outcomes (the United States of America, n 5,880,829). Many adverse outcomes are associated with allogeneic blood transfusion (ABT) and are potentially avoided by intraoperative cell salvage (ICS). The incidence of perioperative transfusion in patients who undergo spine surgery varies between 8 and 36%. Conclusions: Knowledge gaps remain due to the complexity of the field of study, confounding factors, the inability to define optimal transfusion triggers, challenges countered in study design, requirements for large sample sizes, and the inability to conduct randomised controlled trials (RCTs). The surgical complexity, subtle patient factors, and differences in policies and procedures across hospitals and countries are difficult to define and add further complexity. Solutions demand well-designed prospective collaborative research projects.
The Effect of Gut Microbiome, Neurotransmitters, and Digital Insights in Autism
Authors: Bamicha Victoria , Pergantis Pantelis , Drigas Athanasios
Published: December 2024

Background: Autism spectrum disorder is a multifactorial phenomenon whose genetic, biological, environmental, and nutritional factors outline the heterogeneous phenotype of the disease. A limitation in social connections with others, stereotyped reactions, and specific interests and preferences characterize the behavioral manifestations of a person with autism. Also, weaknesses are found in emotional, cognitive, and metacognitive development, significantly burdening the individual’s quality of life. Lately, it has gained widespread acceptance that the gut microbiome and neurotransmission constitute two decisive etiological factors of autism both in the prenatal period and postnatally. This study aims to investigate data on the interaction between the quantitative and qualitative composition of the gut flora and neurotransmission in humans, as well as their influences on the appearance and progression of the symptoms of autism spectrum disorder. At the same time, it captures the role of digital technology in diagnosing and intervening in autism, which is mainly related to the individual subjects under study. Methods: The current research employs an exploratory review to provide a concise overview of the complex neuronal functions associated with neurotransmitter action and the homeostasis mechanisms that allow the brain and the human body to survive and perform optimally. Results: A review of 111 sources highlighted the connection of dietary habits with synthesizing and releasing neurotransmitters and their influence on the emergence of autism-related behaviors. Conclusions: The literature review’s findings revealed the importance and influence of nutritional factors on neurotransmission performance and behavioral, social, and cognitive development among individuals with autism. Moreover, it is noteworthy that combining a healthy lifestyle and the targeted use of digital tools can improve the intensity of autism symptoms.
Evaluating the Health Implications of Kombucha Fermented with Gardenia jasminoides Teas: A Comprehensive Analysis of Antioxidant, Antimicrobial, and Cytotoxic Properties
Authors: Thenuwara Gayathree , Cui Xu , Yao Zhen , Javed Bilal , Naik Azza Silotry , Tian Furong
Published: December 2024

Background/Objectives: Plant-derived compounds are increasingly valued in drug discovery for their therapeutic potential. This study aims to examine the antimicrobial, antioxidant, and anticancer properties of kombucha beverages fermented with Gardenia jasminoides (GJ) and various types of Camellia sinensis teas: matcha green tea (MGT), organic green tea (OGT), and decaffeinated green tea (DGT). Methods: Two experimental designs were employed: (1) using black tea as a base substrate, infusing the four teas post-fermentation over 0–14 days, and (2) directly fermenting tea–herb combinations over 0–21 days. Antioxidant activity was assessed via the DPPH assay. Microbial dynamics were analyzed through total mesophilic bacteria and Lactobacillus counts. Antimicrobial potential was evaluated against E. coli, S. aureus, and S. enteritidis over 24 h. Cytotoxicity assays were conducted on Caco-2 and U251 cell lines to assess anticancer effects, with pH-adjusted controls used to differentiate bioactivity from acidity. Results: In the first experiment, GJ kombucha displayed the highest antioxidant potential (IC50: 14.04 µg/mL), followed by MGT (IC50: 32.85 µg/mL) and OGT (IC50: 98.21 µg/mL). In the second setup, unfermented GJ kombucha initially showed high antioxidant activity (IC50: 12.94 µg/mL), improving during fermentation to reach an IC50 of 18.26 µg/mL by day 21. Microbial analysis indicated moderate increases in total mesophilic bacteria and Lactobacillus in GJ kombucha after 14 days, while MGT, OGT, and DGT exhibited higher increments. GJ kombucha consistently demonstrated the highest antimicrobial activity against E. coli, S. aureus, and S. enteritidis, with significant inhibitory effects observed by 24 h. Cytotoxicity assays showed that GJ kombucha reduced Caco-2 cell viability to 20% at 800 µg/mL after 14 days, while U251 cells maintained 50% viability at the same concentration. Conclusions: This study highlights the antimicrobial, antioxidant, and anticancer potential of GJ kombucha, with fermentation enhancing bioactive metabolite production. Optimizing fermentation conditions, identifying specific bioactive compounds, expanding cytotoxicity testing, and exploring broader therapeutic applications of kombucha could maximize its health benefits and establish it as a natural antimicrobial and anticancer agent.
Mesenchymal Stem Cell Plasticity: What Role Do Culture Conditions and Substrates Play in Shaping Biomechanical Signatures?
Authors: Danalache Marina , Gaa Lena Karin , Burgun Charline , Umrath Felix , Naros Andreas , Alexander Dorothea
Published: December 2024

Cell functionality, driven by remarkable plasticity, is strongly influenced by mechanical forces that regulate mesenchymal stem cell (MSC) fate. This study explores the biomechanical properties of jaw periosteal cells (JPCs) and induced mesenchymal stem cells (iMSCs) under different culture conditions. We cultured both JPCs and iMSCs (n = 3) under normoxic and hypoxic environments, with and without osteogenic differentiation, and on laminin- or gelatin-coated substrates. Using atomic force microscopy, we measured cellular elasticity and Young’s modulus of calcium phosphate precipitates (CaPPs) formed under osteogenic conditions. Correlation analyses between cellular stiffness, quantity of CaPP deposition, and stiffness of formed CaPPs were evaluated. The results showed that iMSCs, despite their softer cellular consistency, tended to form CaPPs of higher elastic moduli than osteogenically differentiated JPCs. Particularly under normoxic conditions, JPCs formed stronger CaPPs with lower cellular stiffness profiles. Conversely, iMSCs cultivated under hypoxic conditions on laminin-coated surfaces produced stronger CaPPs while maintaining lower cellular stiffness. We conclude that JPCs and iMSCs display distinct biomechanical responses to culture conditions. While JPCs increase cellular stiffness during osteogenic differentiation, in particular under hypoxic conditions, iMSCs exhibit a decrease in stiffness, indicating a higher resistance to lower oxygen levels. In both cell types, a lower cellular stiffness profile correlates with enhanced mineralization, indicating that this biomechanical fingerprint serves as a critical marker for osteogenic differentiation.
Development of a Wearable Electromyographic Sensor with Aerosol Jet Printing Technology
Authors: Perilli Stefano , Di Pietro Massimo , Mantini Emanuele , Regazzetti Martina , Kiper Pawel , Galliani Francesco , Panella Massimo , Mantini Dante
Published: December 2024

Electromyographic (EMG) sensors are essential tools for analyzing muscle activity, but traditional designs often face challenges such as motion artifacts, signal variability, and limited wearability. This study introduces a novel EMG sensor fabricated using Aerosol Jet Printing (AJP) technology that addresses these limitations with a focus on precision, flexibility, and stability. The innovative sensor design minimizes air interposition at the skin–electrode interface, thereby reducing variability and improving signal quality. AJP enables the precise deposition of conductive materials onto flexible substrates, achieving a thinner and more conformable sensor that enhances user comfort and wearability. Performance testing compared the novel sensor to commercially available alternatives, highlighting its superior impedance stability across frequencies, even under mechanical stress. Physiological validation on a human participant confirmed the sensor’s ability to accurately capture muscle activity during rest and voluntary contractions, with clear differentiation between low and high activity states. The findings highlight the sensor’s potential for diverse applications, such as clinical diagnostics, rehabilitation, and sports performance monitoring. This work establishes AJP technology as a novel approach for designing wearable EMG sensors, providing a pathway for further advancements in miniaturization, strain-insensitive designs, and real-world deployment. Future research will explore optimization for broader applications and larger populations.
ZFP36L2 Is a Potential Prognostic Marker of IL1β+ Osteosarcoma
Authors: Hao Peiyao , Luo Piaopiao , Xu Shenglin , Ren Zhenhua , Zhao Hong , Nan Xiang
Published: December 2024

Background: Osteosarcoma stands as the predominant bone malignancy afflicting children and young adults. Despite strides in treatment, the enduring reality is that the long-term survival rates for patients grappling with recurrences and metastases linger at a mere 30%. This underscores the pressing demand for novel prognostic markers and therapeutic avenues to improve outcomes and offer hope to those battling this formidable disease. ZFP36L2, a member of the tristetraprolin family of CCCH zinc finger proteins, stands out for its pivotal role in posttranscriptional modifications and its ability to modify tumor microenvironments. Methods: We obtained RNA-seq data from TCGA and GTEx cohorts to investigate the expression of ZFP36L2 in tumor and normal tissues. We also utilized GO/KEGG analysis and immune infiltration analysis to verify the relationship between ZFP36L2 and immune cells. A Kaplan–Meier survival curve was used to study the relationship between ZFP36L2 and IL1β in osteosarcoma. Single-cell data analysis and cell–cell communication analysis were used to discover the therapeutic potential of ZFP36L2 in osteosarcoma. Results: This study elucidates the specific expression pattern of ZFP36L2 in tumors. ZFP36L2 is associated with metastasis in sarcoma, but has no statistically significant correlation with survival rate. ZFP36L2 has been shown to be associated with T cells and macrophages in the tumor microenvironment through GO/KEGG analysis and immune infiltration analysis. The survival analysis results show that ZFP36L2 can serve as a biomarker in IL1β+ osteosarcoma. Single-cell sequencing analysis shows that ZFP36L2 is present in IL1β+ macrophages. Cell–cell communication analysis indicates that ZFP36L2 targets TNF in IL1β+ osteosarcoma, thereby improving prognosis. Conclusions: ZFP36L2 has potential as a prognostic marker in IL1β+ osteosarcoma patients.
Investigating the Potential of Extracellular Vesicles as Delivery Systems for Chemotherapeutics
Authors: Brancolini Alessia , Vago Riccardo
Published: December 2024

Background/Objectives: Standard chemotherapy is generally considered the best approach to treat many solid cancers, even accounting for severe side effects. Therefore, the development of a drug delivery system for chemotherapeutic administration could significantly improve standard chemotherapy by maintaining the cytotoxic effects of the drugs while decreasing the inherent side effects of the treatment. The aim of our study is the optimization of a loading strategy that conjugates the use of extracellular vesicles (EVs) as drug delivery carriers, by preserving their integrity, with the loading efficiency and activity maintenance of chemotherapeutics. Methods: We compared the EV loading of the chemotherapeutics epirubicin, mitomycin, methotrexate and mitoxantrone by co-incubation. Once loaded, the activity of drug-carrying EVs was tested on cancer cells and compared to that of free chemotherapeutics. Results: We defined a linear correlation between chemotherapeutics’ concentration and their absorbance at the drug-specific wavelength, which allowed the definition of a highly sensitive absorbance-based spectrophotometric quantification system, enabling the assessment of drug loading efficiency. Co-incubation of EVs and chemotherapeutics was sufficient to obtain quantifiable drug loading, and the efficacy of EV loading was drug-dependent. Epirubicin-loaded vesicles showed increased toxicity to bladder cancer cells with respect to the free chemotherapeutic. The cytotoxicity was maintained even upon 6-month storage at −80 °C of loaded EVs. Conclusion: We established an absorbance-based spectrophotometric quantification system that enables a straightforward measure of drug loading efficiency into EVs, and we demonstrated that chemotherapeutic-carrying EVs can be obtained by co-incubation, preserving and increasing drug cytotoxicity.
Navigating Hemorrhagic Shock: Biomarkers, Therapies, and Challenges in Clinical Care
Authors: Meza Monge Kenneth , Rosa Caleb , Sublette Christopher , Pratap Akshay , Kovacs Elizabeth J. , Idrovo Juan-Pablo
Published: December 2024

Hemorrhagic shock remains a leading cause of preventable death worldwide, with mortality patterns varying significantly based on injury mechanisms and severity. This comprehensive review examines the complex pathophysiology of hemorrhagic shock, focusing on the temporal evolution of inflammatory responses, biomarker utility, and evidence-based therapeutic interventions. The inflammatory cascade progresses through distinct phases, beginning with tissue injury and endothelial activation, followed by a systemic inflammatory response that can transition to devastating immunosuppression. Recent advances have revealed pattern-specific responses between penetrating and blunt trauma, necessitating tailored therapeutic approaches. While damage control resuscitation principles and balanced blood product administration have improved outcomes, many molecular targeted therapies remain investigational. Current evidence supports early hemorrhage control, appropriate blood product ratios, and time-sensitive interventions like tranexamic acid administration. However, challenges persist in biomarker validation, therapeutic timing, and implementation of personalized treatment strategies. Future directions include developing precision medicine approaches, real-time monitoring systems, and novel therapeutic modalities while addressing practical implementation barriers across different healthcare settings. Success in hemorrhagic shock management increasingly depends on integrating multiple interventions across different time points while maintaining focus on patient-centered outcomes.
Prediction of Bacterial Etiology in Pediatric Patients with Acute Epididymitis: A Comparison of C-Reactive Protein and Urinalysis in Terms of Diagnostic Accuracy
Authors: Liu Kang , Tseng Chi-Shin , Wong Shin-Mei , Huang Kuo-How , Chiang I-Ni , Huang Chao-Yuan , Chiang Chih-Hung
Published: December 2024

Background/Objectives: We aimed to determine the proportion of bacterial etiology in pediatric acute epididymitis (AE) and to compare the predictive accuracy of C-reactive protein (CRP) and urinalysis. Methods: Pediatric patients diagnosed with AE in National Taiwan University Hospital from 2009 to 2018 were retrospectively identified. Patient profiles, including clinical symptoms, physical findings, laboratory data, and treatment types, were collected. Patients were categorized into acute bacterial epididymitis (ABE) or acute non-bacterial epididymitis (ANBE) groups based on the presence or absence of bacterial growth in urine cultures. The primary endpoints were the proportion of patients with ABE and those who received antibiotic therapy. The secondary endpoint was to assess the diagnostic accuracy of CRP and urinalysis for ABE. Results: The final cohort comprised of 289 patients, of whom 216 (74.7%) received antibiotics. Urine culture was obtained for 167 (57.8%) patients, and 52 (31.1%) were positive for a bacterial source. The median CRP and positive rate for urinalysis were significantly higher in the ABE group compared to the ANBE group (CRP: 3.68 vs. 0.25 mg/dL; p < 0.001; urinalysis: 41% vs. 23%; p = 0.005). Multivariate analysis revealed that elevated CRP was significantly associated with AE (odds ratio [OR], 61.96; p < 0.001), whereas positive urinalysis was not (OR, 2.09; p = 0.33). The area under the receiver operating characteristic curves for CRP was higher than that for urinalysis (0.82 vs. 0.72). Conclusions: Serum CRP proved to be a more accurate and reliable tool than urinalysis for predicting pediatric ABE. This could provide guidance to practitioners when prescribing antibiotics in the future.
Mossy Fiber Sprouting in Temporal Lobe Epilepsy: The Impact of Netrin-1, DCC, and Gene Expression Changes
Authors: Onay Melis , Harter Patrick N. , Weber Katherina , Piiper Albrecht , Czabanka Marcus , Plate Karl H. , Freiman Thomas M. , Gessler Florian , Puhahn-Schmeiser Barbara
Published: December 2024

Background: Temporal lobe epilepsy (TLE) is the most common form of drug-resistant epilepsy, often associated with hippocampal sclerosis (HS), which involves selective neuronal loss in the Cornu Ammonis subregion 1 CA1 and CA4 regions of the hippocampus. Granule cells show migration and mossy fiber sprouting, though the mechanisms remain unclear. Microglia play a role in neurogenesis and synaptic modulation, suggesting they may contribute to epilepsy. This study examines the role of microglia and axonal guidance molecules in neuronal reorganization in TLE. Methods: Nineteen hippocampal samples from patients with TLE undergoing epilepsy surgery were analyzed. Microglial activity (M1/M2-like microglia) and neuronal guidance molecules were assessed using microscopy and semi-automated techniques. Gene expression was evaluated using the nCounter Expression Profiling method. Results: Neuronal cell loss was correlated with decreased activity of the M1 microglial phenotype. In the CA2 region, neuronal preservation was linked to increased mossy fiber sprouting and microglial presence. Neuronal markers such as Deleted in Colorectal Cancer (DCC) and Synaptopodin were reduced in areas of cell death, while Netrin-1 was elevated in the granule cell layer, potentially influencing mossy fiber sprouting. The nCounter analysis revealed downregulation of genes involved in neuronal activity (e.g., NPAS4, BCL-2, GRIA1) and upregulation of IκB, indicating reduced neuroinflammation. Conclusions: This study suggests reduced neuroinflammation in areas of neuronal loss, while regions with preserved neurons showed mossy fiber sprouting associated with microglia, Netrin-1, and DCC.