Neuroscience Research Articles

Human macrophage polarisation and regulation of angiogenesis and osteogenesis is dependent on culture extracellular matrix and dimensionality

The immune system plays a crucial role in tissue repair and regeneration. Macrophages have been identified as master regulators of the early immune response and healing outcome, by orchestrating the temporal nature of the initial inflammation phase and coordinating the fate of stem/progenitor cells involved in regeneration. However, traditional in-vitro models for the study of macrophages often fail to fully replicate the complexity of the in-vivo microenvironment, therefore generating models which do not fully capture the extensive spectrum of macrophage behaviour seen in native tissues. To this end, we used a hematoma-mimetic 3D fibrin matrix characteristic of early injured tissues to generate a 3D in-vitro model mirroring the local macrophage microenvironment. Leveraging this framework, we demonstrated significant effects of extracellular matrix and dimensionality on macrophage basal signalling and polarisation, achieving more pronounced regenerative phenotypes upon stimulation with the M2a polarisation factors compared to traditional 2D tissue culture conditions. Moreover, this enhanced physiological macrophage behaviour corresponded to increased coordination of angiogenesis and osteogenesis, better mirroring the healing processes seen in-vivo. Taken together, this study demonstrates the critical importance of integrating tissue composition and 3D architecture when investigating the macrophage behaviour in-vitro, establishing a powerful tool that overcomes known limitations associated with traditional 2D culture on plastic, and can be used to identify and validate novel immunomodulation strategies to enhance tissue regeneration.

Influence of Management Systems on Severity of Heat Stress and Reproductive Performance of Rams in the Tropics – A Review

Abstract Sheep are an important source of protein for humans, and recent decades have seen a significant increase in the production of sheep-based products, thus indicating an increase in demand for this commodity. At a time when this sector is growing, sheep are exposed to various challenges. These include climate change, which can cause heat stress in sheep, including rams, which later negatively affects their growth and reproductive performance. Exposure to heat stress results in physiological and reproductive behaviour responses in rams, which could also be used to visually identify the effect of heat stress as it will affect the productivity of livestock. In addition, the year-round hot and humid climate of the tropics is expected to contribute to a higher probability of heat stress occurrences in rams reared in developing countries around the equator. Nevertheless, the adaptability of rams to heat stress varies according to their origin, whereby native breeds tend to adapt better. Despite that, native breeds still can be affected by adverse environmental conditions and rely on thermoregulation mechanisms to mitigate heat stress. This results in numerous negative physiological changes, such as sweating and increased heart rate. This review highlights the effects of heat stress on the physiology, reproductive behaviour and reproductive performance of male sheep. The review also discusses the impact of management systems on heat stress in rams, which affects sheep productivity.

Animal models for antidepressant activity assay on natural and conventional agents: A review of preclinical testing

Depression is characterized by symptoms such as insomnia, change in appetite and body weight, impaired concentration, lethargy, agitation, psychomotor retardation, anhedonia, feelings of worthlessness, and suicidal thoughts. Various methods have been applied to assess the efficacy of antidepressants and associated molecular processes. However, guidance on the selection of methods for antidepressant testing is still lacking. This article provides a comprehensive review focusing on animal models of depression and the behavioral and molecular changes. A literature search was conducted on platforms, such as PubMed, Google Scholar, Scopus, and Science Direct to find relevant articles. This review found that chronic unpredictable mild stress might be the best and most commonly used model for inducing depression and simulating human depressive states in animals. This model employs a naturalistic approach to expose animals to unpredictable stressors that disrupt homeostasis and cause somatic, physiological, neurobiological, and biochemical disorders and behaviors. The forced swim test (FST) is the most frequently used simple behavioral testing method that is consistent with antidepressant effects, reduces immobility time, and serves as the leading indicator of antidepressant effectiveness. The most commonly observed molecular changes are those related to the levels of monoamine neurotransmitters, such as 5-hydroxytryptamine, dopamine, norepinephrine, and brain-derived neurotrophic factor (BDNF), which are the main etiological contributors to depression. The findings from this review will contribute to ongoing efforts to discover and develop drug candidates for the treatment of depression.

Cannabis sativa genotypes with larger leaf areas have higher potential to adjust stomatal size and density in response to water deficit: the effect on stomatal conductance and physiological stomatal behaviour

Cannabis sativa genotypes with larger leaf areas have higher potential to adjust stomatal size and density in response to water deficit: the effect on stomatal conductance and physiological stomatal behaviour

Denoising diffusion model with adversarial learning for unsupervised anomaly detection on brain MRI images

This paper proposes the Adversarial Denoising Diffusion Model (ADDM). Diffusion models excel at generating high-quality samples, outperforming other generative models. These models also achieve outstanding medical image anomaly detection (AD) results due to their strong sampling ability. However, the performance of the diffusion model-based methods is highly varied depending on the sampling frequency, and the time cost to generate good-quality samples is significantly higher than that of other generative models. We propose the ADDM, a diffusion model-based AD method trained with adversarial learning that can maintain high-quality sample generation ability and significantly reduce the number of sampling steps. The proposed adversarial learning is achieved by classifying model-based denoised samples and samples to which random Gaussian noise is added to a specific sampling step. Compared with the loss function of diffusion models, defined under the noise space to minimise the predicted noise and scheduled noise, the diffusion model can explicitly learn semantic information about the sample space since adversarial learning is defined based on the sample space. Our experiment demonstrated that adversarial learning helps achieve a data sampling performance similar to the DDPM with much fewer sampling steps. Experimental results show that the proposed ADDM outperformed existing unsupervised AD methods on Brain MRI images. In particular, in the comparison using 22 T1-weighted MRI scans provided by the Centre for Clinical Brain Sciences from the University of Edinburgh, the ADDM achieves similar performance with 50% fewer sampling steps than other DDPM-based AD methods, and it shows 6.2% better performance about the Dice metric with the same number of sampling steps.

Climatic variation and risk assessment in a highly seasonal mammal

Abstract Climate change and its resulting effects on seasonality are known to alter a variety of animal behaviors including those related to foraging, phenology, and migration. While many studies focus on the impacts of phenological changes on physiology or fitness enhancing behaviors, fewer have investigated the relationship between variation in weather and phenology on risk assessment. Fleeing from predators is an economic decision that incurs costs and benefits. As environmental conditions change, animals may face additional stressors that affect their decision to flee and influence their ability to effectively assess risk. Flight initiation distance (FID)–the distance at which animals move away from threats–is often used to study risk assessment. FID varies due to both internal and external biotic and physical factors as well as anthropogenic activities. We asked whether variation in weather and phenology is associated with risk-taking in a population of yellow-bellied marmots (Marmota flaviventer). As the air temperature increased marmots tolerated closer approaches, suggesting that they either perceived less risk or that their response to a threat was thermally compromised. The effect of temperature was relatively small and was largely dependent upon having a larger range in the full data set that permitted us to detect it. We found no effects of either the date that snow disappeared or July precipitation on marmot FID. As global temperatures continue to rise, rainfall varies more and drought becomes more common, understanding climate-related changes in how animals assess risk should be used to inform population viability models.

인공지능 로봇의 도덕감정 함양 가능성에 대한 검토 -초등 도덕과를 중심으로-

This study examined the possibility of cultivating moral emotions of artificial intelligence robots that are developing recently. The 2022 revised elementary moral curriculum provides an opportunity for thought by asking questions about the relationship between artificial intelligence robots and humans. For the study, we first investigated the nature and expression process of emotions from ancient Western philosophy to modern brain science and neuroscience. Based on this, we explored what kind of emotional view the currently developed artificial intelligence robots express emotions based on. As a result, current artificial intelligence robots showed responses to humans using information accumulated through facial movements and facial expressions, focusing on basic emotions, according to Ekman's theory. This may be seen as a passive form based on human physical characteristics. However, moral emotion has a complex and active character that combines understanding of moral problem situations, empathy for others, and appropriate responses to situations. Accordingly, it was recommended to clearly teach the status and limitations of artificial intelligence robots in the field of current moral emotions in elementary moral education and educate students to form desirable relationships with artificial intelligence robots.

Realizing active targeting in cancer nanomedicine with ultrasmall nanoparticles.

Ultrasmall nanoparticles (usNPs) have emerged as promising theranostic tools in cancer nanomedicine. With sizes comparable to globular proteins, usNPs exhibit unique physicochemical properties and physiological behavior distinct from larger particles, including lack of protein corona formation, efficient renal clearance, and reduced recognition and sequestration by the reticuloendothelial system. In cancer treatment, usNPs demonstrate favorable tumor penetration and intratumoral diffusion. Active targeting strategies, incorporating ligands for specific tumor receptor binding, serve to further enhance usNP tumor selectivity and therapeutic performance. Numerous preclinical studies have already demonstrated the potential of actively targeted usNPs, revealing increased tumor accumulation and retention compared to non-targeted counterparts. In this review, we explore actively targeted inorganic usNPs, highlighting their biological properties and behavior, along with applications in both preclinical and clinical settings.

Impact of rising CO2 and temperature on grass phenology, physiology, and pollen release patterns in northern latitudes

Climate change has complex effects on vegetation, including native grasses and those used as fodder plants. Like many other plant species, grasses respond to climate change by altering their phenology and physiological behavior, leading to changes e.g. in growth, reproduction and metabolic processes. Our study is the first to explore how Phleum pratense and Alopecurus pratensis respond to rising CO2 and temperatures projected for northern latitudes for two growing seasons. We investigated growth, phenology, pollen release, and physiological parameters in plants cultivated under these conditions, simulated within environmentally controlled chambers.Treatment with elevated temperature reduced the number of generative tillers and, consequently, decreased both the number of inflorescences and the season pollen integrals. Pollen release from P. pratense started up to 17 days earlier, and the daily peak concentration of released pollen was observed 1–2 h earlier in chambers with elevated temperatures when compared to the present climate conditions. Similar effects were noted in A. pratensis. Elevated CO2 (EC) increased net photosynthesis of P. pratense, but this effect was reduced under elevated temperature (ET), suggesting an antagonistic interaction. In A. pratensis, both elevated CO2 and temperature had an additive effect on increasing net photosynthesis, with the highest rate observed under the combined ETEC treatment. The elevated temperature or CO2 did not affect the plant biomass.Our findings propose that the rising temperatures in northern latitudes decrease the flowering of studied grasses and shift the seasonal and daily start of the pollen release. Changes in tiller proportions, reduced pollen integrals, and fewer inflorescences suggest that a warmer climate may negatively impact reproductive success, ecological fitness, and allergenic burden of these grasses.

Microfluidic Applications in Prostate Cancer Research.

Prostate cancer is a disease in which cells in the prostate, a gland in the male reproductive system below the bladder, grow out of control and, among men, it is the second-most frequently diagnosed cancer (other than skin cancer). In recent years, prostate cancer death rate has stabilized and, currently, it is the second-most frequent cause of cancer death in men (after lung cancer). Most deaths occur due to metastasis, as cancer cells from the original tumor establish secondary tumors in distant organs. For a long time, classical cell cultures and animal models have been utilized in basic and applied scientific research, including clinical applications for many diseases, such as prostate cancer, since no better alternatives were available. Although helpful in dissecting cellular mechanisms, these models are poor predictors of physiological behavior mainly because of the lack of appropriate microenvironments. Microfluidics has emerged in the last two decades as a technology that could lead to a paradigm shift in life sciences and, in particular, controlling cancer. Microfluidic systems, such as organ-on-chips, have been assembled to mimic the critical functions of human organs. These microphysiological systems enable the long-term maintenance of cellular co-cultures in vitro to reconstitute in vivo tissue-level microenvironments, bridging the gap between traditional cell cultures and animal models. Several reviews on microfluidics for prostate cancer studies have been published focusing on technology advancement and disease progression. As metastatic castration-resistant prostate cancer remains a clinically challenging late-stage cancer, with no curative treatments, we expanded this review to cover recent microfluidic applications related to prostate cancer research. The review includes discussions of the roles of microfluidics in modeling the human prostate, prostate cancer initiation and development, as well as prostate cancer detection and therapy, highlighting potentially major contributions of microfluidics in the continuous march toward eradicating prostate cancer.

A Study on the Effects of Memory Training and Speech Processing Intervention on Children's Working Memory and Speech Skills: Based on the Perspective of Brain and Cognitive Science

The present study examined the effect of phonological processing and working memory intervention on the verbal working memory and phonological skills of children with Specific reading disorders. Ten participants between 7 to 10 years of age who met ICD 10 criteria for specific reading disorders, were assigned to an experimental group, or a control group. Intelligence screening was done using the Colored Progressive Matrices. Pre - test and post - test measures were the Test of Memory for Children (TOMC) and Informal Reading Assessment (IRA). The intervention group received 30 sessions of phonological processing intervention and working memory intervention. The control group received no intervention. Post - test assessments included TOMC and IRA. Participants who had received the intervention showed more improvement than controls. The majority of the participants in the experimental group performed higher post - intervention.

Development and evaluation of an EMP course to teach fMRI technology and brain science in handwriting for university nursing students

In traditional nursing education, brain science is often limited to physiology, anatomy, and pathology, with little emphasis on advanced diagnostic tools like fMRI or the brain’s functional processes, such as language learning and handwriting. This study developed an English for Medical Purposes (EMP) course to teach university nursing students about fMRI technology and brain science related to handwriting, highlighting the importance of interprofessional education. The study aimed to (a) assess the course’s effectiveness in enhancing students’ knowledge in fMRI, brain science, and handwriting; and (b) evaluate the students’ satisfaction and perceptions toward the course. A single-group quasi-experimental design with pre/post-tests involved 49 nursing students. Data were collected using the Brain Science Related Knowledge Test (BSKT), assignments, and a Course Satisfaction Questionnaire (CSQ). Results showed significant improvements in students’ knowledge of fMRI and brain science in handwriting, with high assignment scores and overall course satisfaction. Students also reported increased awareness of reading professional English journals and learned about fMRI safety issues. This pioneering EMP course effectively introduced nursing students to fMRI technology and brain science in handwriting, potentially enhancing their understanding of normal brain function and its contrast with brain injury cases.

Quantum logic automata generate class IV-like patterns and [formula omitted] noise

Owing to recent advancements in brain science and AI, researchers tend to focus on the concept of self-organized criticality or the edge of chaos. On the other hand, quantum cognition, which is rooted in quantum mechanics, is promising for resolving various cognitive illusions. However, until recently, no connection between criticality and quantum mechanics was proposed. Gunji et al. (2024) recently introduced a linkage termed quantum logic automata, which encompasses not only quantum logic but also criticality characterized by power-law distributions. While quantum logic automata can be derived from various structures, only one of them has been proposed and discussed. Here, we define another type of quantum logic automata involving quantum logic and demonstrate that symmetric quantum logic automata lead to complex Class IV-like patterns and power-law distributions. Our findings support the association between criticality and quantum theory.

Feed Forward Modeling: an efficient approach for mathematical modeling of the force frequency relationship in the rabbit isolated ventricular myocyte

Background and Objective. This study addresses the Force-Frequency relationship, a fundamental characteristic of cardiac muscle influenced by β 1-adrenergic stimulation. This relationship reveals that heart rate (HR) changes at the sinoatrial node lead to alterations in ventricular cell contractility, increasing the force and decreasing relaxation time for higher beat rates. Traditional models lacking this relationship offer an incomplete physiological depiction, impacting the interpretation of in silico experiment results. To improve this, we propose a new mathematical model for ventricular myocytes, named ‘Feed Forward Modeling’ (FFM). Methods. FFM adjusts model parameters like channel conductance and Ca2+ pump affinity according to stimulation frequency, in contrast to fixed parameter values. An empirical sigmoid curve guided the adaptation of each parameter, integrated into a rabbit ventricular cell electromechanical model. Model validation was achieved by comparing simulated data with experimental current–voltage (I-V) curves for L-type Calcium and slow Potassium currents. Results. FFM-enhanced simulations align more closely with physiological behaviors, accurately reflecting inotropic and lusitropic responses. For instance, action potential duration at 90% repolarization (APD90) decreased from 206 ms at 1 Hz to 173 ms at 4 Hz using FFM, contrary to the conventional model, where APD90 increased, limiting high-frequency heartbeats. Peak force also showed an increase with FFM, from 8.5 mN mm−2 at 1 Hz to 11.9 mN mm−2 at 4 Hz, while it barely changed without FFM. Relaxation time at 50% of maximum force (t50) similarly improved, dropping from 114 ms at 1 Hz to 75.9 ms at 4 Hz with FFM, a change not observed without the model. Conclusion. The FFM approach offers computational efficiency, bypassing the need to model all beta-adrenergic pathways, thus facilitating large-scale simulations. The study recommends that frequency change experiments include fractional dosing of isoproterenol to better replicate heart conditions in vivo.

Hierarchical communities in the larval Drosophila connectome: Links to cellular annotations and network topology

One of the longstanding aims of network neuroscience is to link a connectome's topological properties-i.e., features defined from connectivity alone-with an organism's neurobiology. One approach for doing so is to compare connectome properties with annotational maps. This type of analysis is popular at the meso-/macroscale, but is less common at the nano-scale, owing to a paucity of neuron-level connectome data. However, recent methodological advances have made possible the reconstruction of whole-brain connectomes at single-neuron resolution for a select set of organisms. These include the fruit fly, Drosophila melanogaster, and its developing larvae. In addition to fine-scale descriptions of connectivity, these datasets are accompanied by rich annotations. Here, we use a variant of the stochastic blockmodel to detect multilevel communities in the larval Drosophila connectome. We find that communities partition neurons based on function and cell type and that most interact assortatively, reflecting the principle of functional segregation. However, a small number of communities interact nonassortatively, forming form a "rich-club" of interneurons that receive sensory/ascending inputs and deliver outputs along descending pathways. Next, we investigate the role of community structure in shaping communication patterns. We find that polysynaptic signaling follows specific trajectories across modular hierarchies, with interneurons playing a key role in mediating communication routes between modules and hierarchical scales. Our work suggests a relationship between system-level architecture and the biological function and classification of individual neurons. We envision our study as an important step toward bridging the gap between complex systems and neurobiological lines of investigation in brain sciences.

Analysis of the nursing value of continuity care in the recovery of ureteral stone patients after Pneumatic ballistic lithotripsy: An observational study.

This study aims to assess nursing methods' effects on ureteral stone patients post-Pneumatic ballistic lithotripsy with double J-tube placement. Through comparing interventions' impact on recovery, complications, and overall quality of life, the study aims to establish a more effective nursing protocol for this patient group. This study investigates ureteral stone patients who underwent PL and subsequent double J-tube placement between January 2020 and October 2023. A total of 100 eligible subjects (n = 100), meeting the inclusion and exclusion criteria, were divided into an intervention group (n1 = 50) and a control group (n2 = 50) according to different treatments. The control group received routine in-hospital care combined with outpatient follow-up, while the intervention group underwent continuous care using the Omaha system. Nursing effects pre- and post-intervention were assessed using questionnaires, clinical indicators, and the Omaha evaluation system, evaluating aspects such as cognition, behavior, and status in terms of environment, psychosocial aspects, physiology, and health behavior. Additionally, complications during double J-tube placement and pain scores were compared among the patients. Prior to the intervention, no statistically significant differences were observed between the scores of both groups across environmental, psychosocial, physiological, and health behavioral domains. Subsequent to the nursing intervention on the first postoperative day, at discharge, and post-discharge, a statistically significant variance was evident between the groups across these domains (P < .05). Furthermore, the intervention group exhibited notably lower rates of infection, hematuria, and residual or fragmented stones, all significantly lower with a P-value of <.05, compared to the control group. While a reduction in tissue damage and acute kidney injury was observed in the intervention group compared to the control group, this difference did not reach statistical significance. Notably, 92% of patients in the intervention group reported no pain during the nursing intervention, in contrast to only 52% in the control group. Continuity care utilizing the Omaha system demonstrates favorable outcomes in managing double J stent placement post-PL among ureteral stone patients, notably leading to a significant reduction in both pain levels and the incidence of associated complications.

TCM in post stroke brain remodeling: Research advances

Brain functional remodeling is fundamental to the recovery from stroke and is one of the hot topics in modern brain science research, involving various factors such as neurophysiology, neurochemistry, and neuroimaging. Traditional Chinese Medicine (TCM), with its multi-target and multi-stage effects on the body, has unique advantages in improving neurological functions and promoting brain functional remodeling. Current research mainly focuses on monotherapy with Chinese herbs, compound prescriptions, and acupuncture, among other aspects. This paper summarizes their effects and related mechanisms, aiming to provide theoretical support for the clinical application of TCM in promoting brain function recovery after stroke.

Assessment of Sleep Quality and Duration of Medical Students in Enugu State College of Medicine

Sleep is a physiological behaviour that occurs in all animal species forming about one – third of human life and is essential for survival. Prolonged sleep deprivation leads to severe physical impairment usually accompanied by cognitive loss and can even lead to death. Sleep is a naturally recurring state of mind and body, characterized by relatively inhibited sensory activity and reduced interactions with surroundings, altered consciousness, reduced muscle activity and inhibition of nearly all voluntary eye muscles. Therefore, this study is aimed at investigating the impact of various sleep duration among students and the effect on their academic performance. Using a simple random method of sampling, questionnaires were physically distributed among medicine and surgery students of ESUT College of medicine and 265 students participated. Statistical analysis was done using the Statistical Package for the Social Sciences (SPSS) version 23 (SPSS Inc., Chicago, IL) with a value of &lt;0.05 considered significant. From the analysis of the data retrieved from the questionnaire, it was observed that during a regular school week, majority of students (27.5%) obtained 6 hours of sleep, while the night prior to an examination, of students (27.9%) obtained 4 hours of sleep. Also, 68.7% of students believe that insufficient sleep has a negative impact on memory consolidation, while 31.3% believes otherwise. In conclusion from the results, the study suggests that students should be educated regarding good sleep hygiene practices as this has a positive effect on their academic performance. Keywords: Sleep Quality, Duration and Medical Students

Environmental fluoxetine promotes skin cell proliferation and wound healing

This study investigates the effects of environmentally-relevant concentrations of fluoxetine (FLX, commercial name: Prozac) on wound healing. Pollution of water systems with pharmaceutical and personal care products, including antidepressants such as FLX and other selective serotonin reuptake inhibitors, is a growing environmental concern. Environmentally-relevant FLX concentrations are known to impact physiological functions and behaviour of aquatic animals, however, the effects of exposure on humans are currently unknown. Using a combination of human skin biopsies and a human keratinocyte cell line, we show that exposure to environmental FLX promotes wound closure. We show dose-dependent increases in wound closure with FLX concentrations from 125 ng/l. Using several –omics and pharmaceutical approaches, we demonstrate that the mechanisms underlying enhanced wound closure are increased cell proliferation and serotonin signalling. Transcriptomic analysis revealed 350 differentially expressed genes after exposure. Downregulated genes were enriched in pathways related to mitochondrial function and metabolism, while upregulated genes were associated with cell proliferation and tissue morphogenesis. Kinase profiling showed altered phosphorylation of kinases linked to the MAPK pathway. Consistent with this, phosphoproteomic analyses identified 235 differentially phosphorylated proteins after exposure, with enriched GO terms related to cell cycle, division, and protein biosynthesis. Treatment of skin biopsies and keratinocytes with ketanserin, a serotonin receptor antagonist, reversed the increase in wound closure observed upon exposure. These findings collectively show that exposure to environmental FLX promotes wound healing through modulating serotonin signalling, gene expression and protein phosphorylation, leading to enhanced cell proliferation. Our results justify a transition from the study of behavioural effects of environmental FLX in aquatic animals to the investigation of effects of exposure on wound healing in aquatic and terrestrial animals, including direct impacts on human health.

On the Special Issue “Soft-nanotechnology for Brain Science and Biological Systems”

On the Special Issue “Soft-nanotechnology for Brain Science and Biological Systems”