Inflammatory bowel disease (IBD) is a chronic inflammatory condition linked to dysregulated immune responses, gut barrier dysfunction, and oxidative stress. The African star apple, Chrysophyllum albidum peel is rich in pectin, a bioactive polysaccharide with potential anti-inflammatory and antioxidant properties, but its therapeutic role in IBD remains unexplored. This study investigated the effects of C. albidum pectin (CAP) on colitis and associated neurobehavioral and biochemical alterations in a mouse model of dextran sodium sulphate (DSS)-induced colitis in HFD-fed mice. Mice were fed either a normal diet (ND) or HFD with colitis induced by DSS administration. Treatment groups received CAP at doses of 250 and 500 mg/kg. Disease progression was assessed by the Disease Activity Index (DAI), behavioral tests for anxiety and pain sensitivity, and histological examination of colon and brain tissues. Pro-inflammatory cytokines (TNF-α, IL-6), oxidative stress markers (MDA, nitrites), antioxidant enzymes (GSH, CAT, SOD, GST), apoptotic markers (MMP-9, caspase-9), and neurotransmitter-related enzymes were analysed in the colon and brain tissues. The HFD and DSS co-treatment aggravated colitis severity, increasing DAI, pro-inflammatory cytokines, oxidative stress, apoptosis, and neurobehavioral deficits such as anxiety and hyperalgesia. The CAP treatment significantly lowered DAI scores, attenuated inflammation and oxidative damage in both colon and brain tissues, enhanced antioxidant enzyme activities, reduced apoptotic markers, and improved locomotor and pain-response behaviors. Histopathological analyses confirmed preservation of tissue integrity in CAP-treated groups. Chrysophyllum albidum pectin exerts protective effects against DSS-induced colitis exacerbated by a high-fat diet through multi-modal actions including anti-inflammatory, antioxidant, and anti-apoptotic pathways.

Introduction

Alcohol consumption is a leading risk factor for premature mortality and disability. Alcohol consumption is known to activate pro-inflammatory signalling pathways that affect the production of prostaglandins (PGs) and reactive oxygen species (ROS). The mechanisms through which alcohol can alter PG synthesis are not fully understood. Drosophila melanogaster (fruit flies) is an established model system for studying alcohol-related behaviours and neuronal responses, but limited studies have utilised this model for elucidating alcohol-related inflammatory processes. In Drosophila, the Peroxinectin-like (PXT) and Cardinal (Cd) genes are believed to encode for putative cyclo-oxygenase-like enzymes and be responsible for PG synthesis, including PGE₂. The aim of this study is to understand the effect of alcohol consumption on PGE₂ levels in relation to inflammatory processes and addictive behaviours.

Methods

The development of tolerance was measured in Drosophila by measuring the time taken by half a cohort of flies to be sedated by ethanol vapours (ST50). An increase in ST50 following repeated ethanol exposures on consecutive days indicates development of tolerance. The level of PGE₂ was measured in homogenates of fly heads and bodies using an ELISA Kit (Cayman) in wild-type, PXT and Cd mutant flies with and without exposure to 2mM aspirin (a cyclo-oxygenase inhibitor).

Results and Conclusion

All Drosophila species examined developed tolerance. but their sensitivity to ethanol varied. Ethanol caused a different effect on PGE₂ production in different fly species (wild type and mutants); additionally, aspirin had a different capacity to alter the ethanol effect on PGE₂ production and the development of tolerance. These results, thus, provide evidence that the inflammatory process and addiction-related behaviours are interlinked and support the use of Drosophila as a tool for evaluating these mechanisms.

The balance between reward and aversion is central to adaptive behavior, yet the neural mechanisms orchestrating this balance remain incompletely understood. Recent progress in behavioral neuroscience suggests that decision-making and emotional regulation are shaped by dynamic interactions between dopaminergic, glutamatergic, and peptidergic signaling systems distributed across cortico-limbic networks.

This study integrates functional neuroimaging, behavioral modeling, and molecular profiling to dissect the reward–aversion circuitry underlying motivated behavior. Using a cohort of 120 healthy adults and 40 individuals with maladaptive reward processing (subclinical addiction and anxiety traits), we applied fMRI with dynamic causal modeling (DCM) and diffusion-weighted tractography to map directed connectivity between the ventral tegmental area (VTA), amygdala, and prefrontal cortex. Concurrent saliva cortisol and blood metabolomics provided peripheral biomarkers of stress-linked modulation.

The data reveal that reward expectancy enhances VTA–prefrontal coupling via dopamine-mediated glutamatergic pathways, while aversive cues increase amygdaloid inhibition of orbitofrontal regions, attenuating behavioral flexibility. Elevated peptide signaling (notably neuropeptide Y and dynorphin) correlated with impaired decision speed and heightened emotional reactivity. Machine learning classifiers achieved 88% accuracy in distinguishing adaptive versus maladaptive responders based on neural–biochemical signatures.

These findings delineate a multi-scale model of behavioral regulation, in which cross-talk between reward and aversion networks predicts individual differences in emotional control and cognitive bias. Targeting neuromodulatory peptides and stress circuits could thus inform new interventions for compulsive and affective disorders.

Introduction: Major depressive disorder (MDD) is a disorder strongly linked to childhood stress, amplified by a lack of social support later in life. Rodent models like maternal deprivation (MD) and social isolation (SI) mimic these traumas, highlighting how early-life stress can alter the hypothalamic–pituitary–adrenal (HPA) axis and be transmitted to offspring. Objective: The objective of this study is to evaluate depressive-like behaviors and HPA axis protein in rats subjected to MD and SI and in the stressed female offspring, as well as the therapeutic potential of Centella asiatica and its active compound, madecassic acid. Methods: The animals were male and female Wistar rats. MD consisted of depriving the pups three hours per day for ten days. SI consisted of keeping the animals in individual cages, starting at 50 days of age. Forced swimming and gene expression of the HPA axis proteins NR3C1 and FKBP5 in the Nucleus Accumbens (NAc) were evaluated in both animals that suffered stress and in offspring of mothers who experienced stress (second-generation). After 30 days of IS, the hydroalcoholic extract of Centella asiatica (30 mg/kg) and madecassic acid (10 mg/kg) were administered for fourteen days. Results: Stress from PM and IS resulted in depressive-like behavior in adulthood of the first-generation and in offspring (second-generation) from stressed mothers. Treatments with Centella asiática and madecassic acid reduced depressive-like behavior. These compounds also reversed the reduction of NR3C1 and FKBP5 in the NAc of the stressed first-generation animals, although without corresponding changes in NAc gene expression. Conclusion: Centella asiatica extract and the active compound madecassic acid have antidepressant potential, modulating the effects of chronic childhood stress in animals that experienced stress and in their offspring who were not subjected to MD and SI protocols. This potential is further supported by the observed modulation of the HPA axis changes.

Background: Amyotrophic lateral sclerosis (ALS) and traumatic brain injury (TBI) are distinct neurological disorders that share overlapping molecular and cellular mechanisms, including neuroinflammation, oxidative stress, and synaptic dysfunction.

Methods: This study employs a systems biology approach to identify common genes and pathways linking ALS and TBI. Differentially expressed genes (DEGs) from publicly available transcriptomic datasets (GSE89866 for TBI and GSE153960 for ALS) were integrated and analyzed through network-based and enrichment analyses. Protein–protein interaction (PPI) networks were constructed to highlight key hub genes and regulatory modules shared between both conditions.

Results: A total of 3885 DEGs were identified in ALS (GSE153960) whereas 449 DEGs were obtained in TBI (GSE89866). Total number of common overlapping DEGs between the two datasets were 20, out of which 13 common DEGs were upregulated in both the cases, while 7 DEGs were downregulated. Important upregulated genes were MAFB, IL13RA1, PLBD1, CYP1B1, FBP1, TLR5, and RAB20. Similarly, key downregulated genes were ZNF541, DNAI2, NYAP1, TRIM17, and TRPV6. The functional enrichment analysis indicated that these key genes are involved largely in the innate immune system, muscle contraction, aldosterone synthesis and secretion, cellular responses to stimuli, cytosolic DNA-sensing pathway and cellular senescence.

Conclusion: These findings provide novel insights into shared molecular mechanisms and may contribute to identifying potential therapeutic targets for neuroprotection and disease modification in ALS and TBI.

Introduction Implicit motor adaptation is widely described as having a fixed ceiling of 12–15° that does not scale with perturbation size when explicit strategies are suppressed. We examined how this ceiling changes when participants experience two different visuomotor rotation magnitudes (24° and 48°) under gradual versus error-clamped schedules.

Methods Forty-one participants adapted to 24° and 48° rotations in counterbalanced order across two sessions. Perturbations were introduced either gradually (stepped increments designed to minimize the awareness of the visuomotor perturbation) or via error-clamp (constant clamped feedback that eliminates explicit aiming). Immediate aftereffects were measured during the first four no-feedback trials after each exposure.

Results In the gradual groups, aftereffects scaled strongly with the perturbation size (first exposure: 12.7° after 24° vs. 24.8° after 48°, t(19)=6.06, p<0.001; second exposure: 24.4° vs. 16.3°). In the error-clamped groups, aftereffects remained ∼11–14° regardless of whether participants had just experienced a 24° or 48° clamp (all ps>0.18).

Conclusions When visuomotor adaptation occurs gradually, implicit aftereffects are flexibly modulated based on the rotation size. When the adaptation occurs under the error-clamped condition, aftereffects are fixed at approximately 13° irrespective of the rotation size. These results indicate that the “fixed ceiling” effect known to follow implicit adaptation may be task dependent.

Understanding how brain activity changes across neurological and neurodevelopmental disorders requires tools that can reveal patterns hidden in complex EEG data. Conditions such as epilepsy, Alzheimer’s disease, dementia, and autism often produce distinct alterations in neural oscillations and connectivity, but these signatures can be difficult to interpret in real time. In this work, we present an interactive brain interface designed to visually explore disease-specific EEG dynamics through integrated spectrograms, topographic maps, and connectivity graphs.

Our system combines classical signal-processing techniques with computational modeling to generate a multi-layer representation of ongoing brain activity. EEG segments are analyzed to extract spectral features, inter-electrode coherence, and spatial activation patterns. The interface simulates key biomarkers for each condition, including epileptic spike–wave discharges, Alzheimer-related reductions in alpha power, dementia-associated slowing, and atypical connectivity profiles observed in autism. A dedicated seizure module models the rapid synchronization that occurs during ictal events, highlighting propagation pathways across the scalp. All visual components, EEG waveforms, frequency-band power, scalp topomaps, and graph-based networks, update continuously, allowing users to observe how brain states evolve over time.

Initial results demonstrate that the interface effectively captures meaningful differences between disorders, making high-dimensional EEG patterns easier to understand and compare. Epileptic simulations display strong bursts and dense network coupling, while neurodegenerative modes show weakened connectivity and spectral slowing. These visualizations offer an intuitive yet rigorous way to explore neural dynamics.

Overall, the project illustrates how computational neuroscience, mathematical modeling, and interactive visualization can be combined to create an accessible tool for research, education, and potential clinical support. This interface provides a flexible platform for studying how neural circuits behave across diverse brain conditions and how their dynamics relate to cognition and behavior.

Introduction: Major Depressive Disorder (MDD) is one of the most prevalent and severe mental health condition, affecting millions of individuals worldwide and often leading to significant cognitive and emotional dysfunction. MDD is characterized by persistent low mood, loss of interest or pleasure, and impaired cognitive and physical functioning. Our objective is to apply advanced complexity and recurrence network analysis approaches to investigate underlying changes in functional brain connectivity using electroencephalographic (EEG) signals.

Methods: We used the multi-modal open dataset for mental-disorder analysis (MODMA), consisting of 128-channel resting-state EEG recordings of individuals with MDD and those of healthy controls. We have particularly focussed on channels in the frontal brain region as it is known to play a crucial role in emotional and cognitive processing. After pre-processing, power spectral density (PSD) and Lempel–Ziv (LZ) complexity analysis were applied to distinguish MDD subjects from healthy controls. We performed t-tests to identify significant channels. We then constructed recurrence networks to capture the nonlinear temporal dynamics of EEG activity in these significant frontal channels. Then, we computed various network measures, including Recurrence Quantification Analysis (RQA), recurrence rate (RR), determinism (DET), and laminarity (LAM), to characterize the resulting recurrence network. Further, we performed functional cartography of nodes based on modularity to quantify network hubs.

Results: The results revealed frontal asymmetry with several frontal channels exhibiting significant variations in oscillatory power and signal complexity in MDD. The recurrence networks represent the complex interrelationships among recurring patterns of EEG brain activity over time. We observed that functional cartography applied for hub classification in the constructed recurrence networks provides a powerful framework for quantitative analysis and unveiling network-based signatures underlying the nonlinear dynamics of EEG signals.

Conclusions: The identification of such EEG-based network markers could facilitate early detection and prediction of MDD severity.

Introduction. Endothelial dysfunction (ED) is a key pathogenetic mechanism underlying cardiovascular and cerebrovascular diseases and is increasingly recognized as a common link between ischemic heart pathology and cerebral vascular impairment. In addition to postnatal risk factors, adverse intrauterine conditions, particularly prenatal hypoxia (PH), may program long-term endothelial alterations. The aim of this study was to investigate the structural and molecular features of ED in the myocardial and cerebral vessels in experimental chronic heart failure (CHF) and PH, as well as to evaluate the endothelioprotective potential of pharmacological agents targeting the nitric oxide system.

Methods. This study was conducted on Wistar rats using experimental models of CHF (doxorubicin administration, cumulative dose 15 mg/kg) and PH (sodium nitrite 50 mg/kg administered to pregnant females on gestational days 16–21). The endothelial status of cerebral and myocardial vessels was assessed using immunohistochemistry, ELISA, morphometric analysis, and real-time PCR. Key markers of endothelial function, inflammation, nitric oxide metabolism, oxidative stress, and angiogenesis were evaluated. The endothelioprotective potential of nitric oxide-modulating pharmacological agents was also evaluated.

Results. CHF and PH induced pronounced structural and functional endothelial alterations in the microcirculatory and muscular-type vessels of the heart and brain. These changes were characterized by reduced endothelial cell density, suppressed eNOS expression, increased iNOS expression, nitric oxide deficiency, elevated nitrotyrosine levels, and activation of proinflammatory cytokines. VEGF levels were significantly decreased, while apoptotic features of endothelial cells were intensified. Angiolin and Hypertril demonstrated the most pronounced endothelioprotective effects among the tested agents.

Conclusions. CHF and PH induce persistent ED in cerebral and myocardial vessels through disruption of the nitric oxide system, oxidative stress, and inflammatory activation. PH may act as an early trigger increasing susceptibility to cardiovascular and cerebrovascular diseases later in life. These findings support the rationale for targeted endothelioprotective therapy in ischemic cardiovascular pathology.

Introduction: It has been established that the cognitive style of field dependence/field independence (FD/FI) significantly influences sensory reliance in postural control. Individuals with FD appear to rely more on vision, whereas those with FI prioritize vestibular and proprioceptive inputs. The current study aims to investigate the impact of this cognitive style on postural adaptation in complex tasks involving sensory deprivation and virtual reality.
Methods: A total of 41 participants aged 19–26 years were classified as either FD or FI based on the Gottschaldt Figures Test. Their postural stability was assessed using stabilometry (Stabilan-01-2) under various conditions: eyes open (EO), eyes closed (EC), virtual reality goggles (VR), hard surface (HS), and soft surface (SS).
Results: All participants showed impaired postural control during complex tasks. Individuals with FI showed enhanced stability when faced with either simple visual deprivation or proprioceptive limitation. In contrast, individuals with FD demonstrated increased destabilization in response to virtual reality on a firm surface, with a prolonged recovery time after visual deprivation. However, when virtual reality was combined with a soft surface, both groups exhibited immediate destabilization. Interestingly, FI individuals showed a slower recovery after the test, while FD individuals displayed a faster adaptation rate.
Conclusion: It has been shown that FI individuals use more effective strategies in sensory-deprived conditions. However, their strong reliance on internal cues makes them more susceptible to the combined effects of VR and proprioceptive deficits. It is crucial to consider a patient's cognitive style when prescribing VR-based therapy, as this can be critical in minimizing fall risks and optimizing rehabilitation protocols.
This study was supported by the Russian Science Foundation (grant №25-15-20048).