BMC Neuroscience

Exposure to chemical cues released by predator or pathogen can evoke anxiety or fear responses in prey/host animals such as fight, flight or freeze both at behavioral and molecular levels. Freezing is a fundamental anxiety response when fighting or fleeing arent feasible. Despite the potential relevance of freezing as a stress-coping mechanism, its behavioral and molecular underpinnings are not understood yet. At molecular level danger cues are perceived by chemosensory receptors expressed in sensory neurons which may further regulate the animals behavioral responses(Ye et al., 2024){Citation}. 2-nonanone (2-NA) is one of the principal volatile organic compounds secreted by many pathogenic bacteria infecting Caenorhabditis elegans as well as humans and may signal danger to worms. Here, we show that olfactory exposure to threat-associated cue 2-NA induces a reversible fear-like freezing response characterized by immobility and halted feeding in C. elegans. With the application of in silico and behavioral approaches we showed that 2-NA is one of the ligands for an olfactory G-protein Coupled Receptor (GPCR) STR-211 and RNAi knockdown of the receptor leads to a defect in 2-NA induced avoidance behavior in worms. We next discovered that STR-211 is required for immediate behavioral changes in C. elegans during freezing response against 2-NA. The study proposes an environment relevant animal model to mimic human anxiety and fear-like behavior, along with the identification of one of the olfactory GPCRs mediating this behavior. The model may help in understanding the neuromolecular basis of freezing response in human anxiety, contributing towards treatment of mental health disorders.

Aging affects individuals at varying biological rates, prompting the development of the Brain Age Index (BAI) to quantify neurobiological health relative to chronological age and disease risk. While structural MRI has dominated brain age prediction, its high cost, immobility, and low temporal resolution restrict its clinical scalability and responsiveness to transient neurophysiological changes. Electroencephalography (EEG) offers a highly scalable, portable, and temporally precise alternative capable of capturing dynamic brain states. However, the transition of EEG-based models to clinical biomarkers is impeded by methodological limitations, including small or biased datasets, inconsistent preprocessing pipelines, and a distinct lack of interpretable machine learning approaches. To address these persistent challenges, this paper presents a comprehensive, open-source, end-to-end pipeline for large-scale EEG-based brain age modeling. Developed using the Temple University Hospital EEG Corpus (TUEG) the largest publicly available resting-state EEG dataset. The pipeline encompasses rigorous data engineering, reproducible preprocessing, and robust feature extraction. Following quality control and subject-level dataset partitioning to definitively prevent data leakage, exactly 41,181 recordings were successfully retained. Two independent feature sets were extracted: the Catch22 time-series characteristics and a comprehensive set of spectral, aperiodic, and non-linear dynamics from the CCS toolbox. The methodology evaluates seven regression models, optimized via Optuna for hyperparameter tuning, and integrates SHAP (SHapley Additive exPlanations) for transparent feature importance analysis. By making this infrastructure publicly available, this work lowers the barrier to entry for large-cohort studies, fostering reproducible development and clinical validation of dynamic brain age biomarkers.

Recent technological advances allow for the large-scale acquisition of genetic and morphological data: high-throughput sequencing has transformed the field of genomics while synchrotron X-ray microtomography enables rapid, noninvasive 3D imaging. However, integrating these approaches for the same specimens is challenging because X-rays can fragment DNA, and DNA extraction damages internal morphology, particularly relevant for small bodied organisms, such as insects. We systematically tested multiple extraction protocols and irradiation conditions across three model insect species. We irradiated more than 1,000 specimens under varying conditions and tested DNA quality through DNA barcoding and UCE sequencing. Our results demonstrate that high-quality DNA and high-resolution tomograms can be obtained from the same individuals, provided that the parameters are carefully optimized and rapid SR-CT scanning precedes DNA extraction. In this respect, our findings establish practical guidelines for combining genomics and phenomics, paving the way for comprehensive integrative digitization of biodiversity.

This study aims to improve the detection performance of age-related macular degeneration (AMD) in low-quality retinal images. BackgroundAMD is a leading cause of vision loss among older adults globally, and accurate detection is crucial for clinical management. However, low-quality optical coherence tomography (OCT) images significantly compromise diagnostic accuracy. ObjectiveTo enhance AMD detection in low-quality images using noise-augmented data augmentation and an improved YOLO deep learning model. MethodsPublic datasets from UCSD and Duke University were utilized; the training dataset comprised 24,980 OCT images (high-quality and noise-augmented low-quality), while the testing dataset included 1,000 images (584 AMD, 416 normal). The model is based on the YOLOv8n framework, integrated with Squeeze-and-Excitation blocks (SEblock) and Adaptive Sparse Self-Attention (ASSA), with an additional 160x160 detection layer for detecting small lesions. Evaluation metrics included accuracy, sensitivity, specificity, and F2-score. ResultsThe proposed model achieved an accuracy of 99.02%, sensitivity of 98.17%, specificity of 100%, and an F2-score of 98.50% on the Duke dataset. Detection rates were significantly improved compared to traditional methods, particularly in low-quality images, with a detection rate of 89.60%, markedly superior to original YOLOv8n (55.10%) and classical models like ResNet50. ConclusionThe enhanced model, employing noise-augmented training data and improved attention mechanisms, demonstrates excellent AMD detection capabilities in low-quality OCT images, showing broad potential for clinical applications.

Environmental stress during early development can have lasting effects on reproduction and developmental plasticity in Caenorhabditis elegans. Here, we compared the consequences of two dauer-inducing stressors, high temperature and crowding, on fertility, dauer formation, and intergenerational gene expression. Entry into the dauer stage protected animals from stress-induced sterility, with high-temperatureinduced diapause (HID) providing strong preservation of reproductive capacity. Remarkably, the progeny of temperature-induced post-dauers (PD-temp) displayed a twofold increase in dauer formation upon re-exposure to heat, revealing a transient intergenerational enhancement of HID. This effect was stimulus-specific, as parental heat exposure suppressed pheromone-induced dauer formation in progeny, while parental pheromone exposure did not enhance HID. This increased dauer propensity was reset after a single stress-free generation. RNA-seq across three generations identified a transient F1-specific gene expression signature associated with enhanced dauer formation upon re-exposure to heat. Functional analyses showed that snpc-1.3, F49F1.7, and Y69A2AR.12 promote HID. In parallel, vit-3 expression was selectively reduced in F1 progeny of PD-temp animals, and vit-3 mutants exhibited increased dauer formation at 27{degrees}C, suggesting that vit-3 normally restrains HID. Consistent with previous work from our group implicating RNAi pathways in environmentally induced diapause and inherited stress responses, we find that endogenous RNAi pathways also modulate HID across generations. Multiple RNAi pathway components contributed to HID, while the nuclear RNAi factor nrde-2 was specifically required for the intergenerational increase in dauer formation. Tissue-specific rescue experiments further suggest that coordinated RNAi activity across tissues contributes differently to parental HID and progeny responses. Together, these findings identify HID as a distinct stress-induced developmental program that transiently modifies progeny responses to recurring thermal stress while preserving reproductive fitness. Our results further indicate that the physiological and intergenerational consequences of dauer entry depend on the environmental cue that induces diapause.

The development of a new integrated operant system was driven by two challenges in behavioral neuroscience: the high cost and technical complexity of commercial rigs, and their limited adaptability across experiments. We developed the NeuroHab, an integrated behavioral arena for high-fidelity operant conditioning and automated data collection in a single unified system. Food and water reward, conditioned-stimulus presentation, and event recording are tied together programmatically with easy-to-install open-source code to facilitate throughput and reproducibility. All behavioral events are processed by internal microcontrollers and logged with <1 ms latency (typical range 56-728 s). This precise timing is critical for integrating the system with two-photon imaging and electrophysiology, enabling real-time alignment of behavior with brain activity. The NeuroHab uses solenoid-actuated, capacitive-sensing Lickports that let an untethered mouse drink from an automated port, and delivers food via the Kravitz Lab FED3. Conditioned stimuli are presented by dedicated buzzer/LED modules. A central controller (the Core) coordinates all modules and logs event timestamps using TTL-low signaling between two microcontrollers, at a maximum recording rate of 16.67 Hz for single-pulse events. We have deployed the NeuroHab in over 50 behavior trials and over 20 sessions alongside a Mini two-photon microscope. At approximately $1,400, easily modified, and compatible with existing analysis tools, the NeuroHab lowers barriers to multimodal behavioral neuroscience. Significance StatementThe study of how neural activity gives rise to behavior depends on operant systems that are both temporally precise and affordable, yet commercial rigs are costly and difficult to adapt across experiments. We introduce the NeuroHab, an integrated, open-source operant platform that unifies reward delivery, conditioned-stimulus presentation, and event logging with sub-millisecond timing (typical latency 56-728 s). Built for approximately $1,400, the system forwards all behavioral timestamps to external acquisition hardware, enabling millisecond-scale alignment of behavior with two-photon imaging and electrophysiology. By lowering the cost and technical barriers to synchronized behavioral and neural recording, the NeuroHab makes multimodal, reproducible operant neuroscience accessible to a broad range of laboratories and adaptable to diverse experimental paradigms.

The widespread presence of microplastics and nanoplastics has emerged as a significant environmental concern, with increasing evidence suggesting potential adverse effects on neurological health. However, the molecular mechanisms linking polystyrene exposure to Alzheimers disease (AD) remain poorly understood. In this study, an integrative systems biology framework was employed to investigate the molecular interplay between environmental polystyrene exposure and AD pathogenesis. AD-associated genes were retrieved from the Comparative Toxicogenomics Database (CTD) and DisGeNET, while polystyrene-responsive genes were obtained from CTD. Integration of these datasets identified 16 shared genes potentially connecting polystyrene exposure with AD. Transcriptomic analysis of the hippocampal dataset GSE29378 revealed significant differential expression of several overlapping genes between AD and healthy controls. Functional enrichment analyses demonstrated that these genes are predominantly involved in oxidative stress, inflammatory signaling, apoptosis, and synaptic function, all of which are central to AD pathology. Weighted gene co-expression network analysis (WGCNA) further identified disease-associated modules containing multiple intersecting genes strongly correlated with AD clinical traits. Protein-protein interaction analysis highlighted IL1B, CASP3, BCL2, ACHE, and APOE as key hub genes, indicating their potential roles in integrating environmental stress responses with neurodegenerative pathways. Independent validation using the GSE48350 dataset confirmed the robust diagnostic performance of several hub genes in discriminating AD from control samples. Collectively, these findings suggest that environmental polystyrene exposure may promote AD progression through neuroinflammation, oxidative stress, apoptosis, and synaptic dysfunction, providing novel mechanistic insights and identifying promising molecular targets for future experimental, clinical, and epidemiological investigations.

INTRODUCTION: Tau pathology in Alzheimers disease preferentially afflicts excitatory neurons in the limbic and association cortices that utilize high levels of calcium signaling to perform cognitive operations. This includes the layer III pyramidal cells in the dorsolateral prefrontal cortex (dlPFC) that subserve higher cognition, which express the calcium-binding protein, calbindin, when young and healthy, but lose calbindin and develop tangles and degenerate in Alzheimers disease (AD). These data suggest that loss of calbindin may be associated with the emergence of tau pathology. However, the relationship between calbindin and early-stage, soluble tau pathology is challenging to study in human brains, as soluble pTau dephosphorylates within 15min postmortem. In contrast, the relationship between calbindin and soluble pT217-tau expression can be studied in aging macaques with naturally-occurring tau pathology, where perfusion fixation is possible to capture phosphorylation state in situ. METHODS: The current study used multiple-label-immunofluorescence to label MAP2-positive dlPFC layer III pyramidal cells for calbindin and pT217-tau in macaque brains across the adult age span (8-34.5yrs). The study employed a semi-automated CellProfiler workflow to identify labeled pyramidal cell dendrites the cellular compartment where tau pathology begins in AD. RESULTS: Calbindin expression decreased with age, while pT217Tau increased with age. Specifically, the ratio of calbindin/pT217-tau within a dendrite decreased with age, and was especially prominent in the aged macaques with long-term inflammatory disorders. DISCUSSION: These data suggest that the loss of calbindin in dendrites with advancing age, and especially with inflammation, contributes to the rise of tau pathology and the risk of AD.

In populations with well-preserved cognitive function, cognitive screening total scores tend to cluster near the ceiling, making it difficult to characterize age-group differences from total scores alone. We compared the temporal structure of word production, acoustic features, and the magnitude and timing of forehead total-hemoglobin (total-Hb) responses during a phonemic verbal fluency task in adults in their 40s and 70s. A total of 254 healthy participants (115 in their 40s, 139 in their 70s) completed a 60-s phonemic verbal fluency task requiring words beginning with the Japanese syllable /ka/, administered as part of the Japanese version of the Montreal Cognitive Assessment (MoCA-J). We derived the total word count, word counts in 10-s bins, mean inter-word pause duration, speech offset time, smoothed cepstral peak prominence (CPPS), jitter, and shimmer. Area under the curve (AUC) and time-to-peak (TTP) were computed from forehead total-Hb signals recorded with a wearable single-wavelength near-infrared spectroscopy device. MoCA-J scores clustered near the ceiling in both groups, although the age-group difference was significant. The 70s group produced fewer words (14.00 vs 17.09) and showed longer inter-word pauses (1.60 vs 0.72 s). CPPS was lower, AUC was higher, and TTP was longer (32.97 vs 15.63 s) in the 70s group, whereas jitter did not differ. Word counts across 10-s bins showed an age group time-bin interaction. Within each age group, participants who produced more words showed longer TTP. Age-group differences in TTP and AUC persisted after adjustment for speech offset time (proportions mediated, 6.7% and 0.5%) and in a subsample matched on speech offset time. Even when screening scores clustered at the ceiling, the temporal structure of word production and forehead total-Hb responses differed between age groups, and these two classes of measures dissociated. Because the sample was selectively recruited and single-wavelength total-Hb signals do not index localized neural activity, the findings are descriptive and motivate longitudinal, multi-axis characterization of speech in aging.

Light microscopy is one of the most powerful tools for understanding living systems, but the opacity of tissue prevents visualization of all but superficial layers. Several methods to clarify tissue have been developed, but most require fixed specimens. To address the challenge of improving resolution in functioning neuronal circuits, we developed a biocompatible clearing agent, iodixanol-ACSF, which is capable of increasing the transparency of living neuronal tissue. Brain-cleared mice were motile and unimpaired on a variety of behavioral tasks, and extracellular recordings showed that many cellular and circuit phenomena were well-preserved. In live iodixanol-ACSF cleared mouse brain tissue, both transmission and cellular-resolution fluorescence microscopy indicate improvements of 150-200% in penetration depth with one-third to one-half the laser intensity when compared to untreated tissue. Our results show that iodixanol-ACSF clearing will enable deeper imaging and extend our understanding of neuronal circuit function.

PurposePupil diameter in daily life depends on both the light reaching the eye and the observers age, but established prediction formulas require laboratory quantities that are rarely measured in natural environments. We developed a compact age-corrected model that predicts pupil diameter from melanopic equivalent daylight illuminance (mEDI). MethodsWe used an existing field dataset in which binocular pupil diameter and near-corneal spectral irradiance were recorded while 83 adults aged 18-87 years moved through indoor and outdoor environments. The analysis included 10,082 valid paired observations. We fitted a bounded sigmoid relating pupil diameter to mEDI and age, with each participant given equal influence, and assessed prediction in participants excluded from model fitting. Performance was compared with simpler models, a flexible generalised additive model (GAM), and Watson-Yellott predictions based on assumed field geometry. ResultsPupil diameter decreased smoothly as mEDI increased. Age primarily reduced the difference between pupils in dim and bright conditions, by 0.768 mm per decade, while the predicted bright-light diameter changed little with age. In held-out participants, the bounded model had a participant-balanced root mean squared error (RMSE) of 0.630 mm and mean absolute error of 0.537 mm. The GAM had a slightly lower point-estimate RMSE of 0.610 mm, but the difference was small and uncertain. The bounded model outperformed the tested log-linear, reduced, age-only, and Watson-Yellott alternatives. ConclusionAge and mEDI are sufficient to provide useful population-average pupil predictions across the observed adult age and real-world light range. The model is transparent, physiologically bounded, and nearly as accurate as a flexible GAM, but predictions approaching darkness remain uncertain because valid mEDI measurements were not available in that range. Key pointsO_LIA compact equation predicts population-average pupil diameter from age and mEDI alone. C_LIO_LIAge mainly compresses the pupils response range by reducing pupil diameter under dimmer conditions. C_LIO_LIPrediction error in unseen participants was close to that of a flexible GAM, without requiring a fitted smooth object. C_LIO_LIThe model is intended for the observed adult age and field-light range, not for extrapolation into darkness. C_LI

Accurately determining the mating status of the agricultural fruit fly pest Ceratitis capitata, commonly known as Medfly, is essential for timely and effective eradication efforts. To overcome the limitations of subjective DAPI-based staining assessments of females captured in Jackson dry traps and Multilure liquid traps, we developed a multi-tier molecular diagnostic method that unequivocally detects mating status using DNA probes targeting the male-specific Y114 locus on the Y-chromosome of the species. Our protocol integrates morphological evaluation with increasingly sensitive molecular assays through the following steps: 1) A preliminary quality assessment of the specimens physical condition, DNA preservation, and mating status using conventional PCR followed by agarose electrophoresis (cPCR); 2) Quantification and real-time detection of sperm presence via quantitative PCR (qPCR); and 3) Detection of trace sperm amounts through droplet digital PCR (ddPCR). This PCR-based framework is designed for samples collected in the field, enabling accurate analysis of specimens exposed to adverse environmental conditions and varying levels of preservation after 2- and 3-weeks weathering times in traps. It allows quantitative determination of mating status even when sperm concentrations are extremely low, such as during transient copulation, and achieves detection limits down to approximately 14 spermatozoa in a mated female. By accounting for variable specimen quality and the performance characteristics of each molecular platform, this tiered approach ensures highly sensitive and unequivocal detection of mated females. The methodology can be used to assist eradication efforts across the C. capitata geographic range through the timely detection of mated females, halting their expansion and establishment into novel regions reducing control and eradication costs.

Background: Brain banks usually provide small tissue blocks fixed by immersion in neutral-buffered formalin (NBF). While still underexploited for research, gross anatomy laboratories could provide full brains fixed by perfusion with solutions better suited for gross anatomy dissection. However, the chemicals in these solutions might have a different impact on histology protocols for cell quantification than in NBF-fixed brains. The main goal of this study is to compare the effects on the number and size of labeled neurons of the primary motor cortex (PMC) of mouse brains fixed with three different solutions: (1) NBF, typical of brain banks, (2) a saturated salt solution (SSS), and (3) an alcohol-formaldehyde solution (AFS), both used in human anatomy laboratories. Methods: 27 C57BL/6J mouse brains were perfused with the NBF (N=9), SSS (N=9) or AFS (N=9), then cut in 40-m slices and processed with immunohistochemistry to target neurons. Various quantitative variables were assessed manually and automatically on photomicrographs of 3 regions of interest (ROIs) of the PMC per specimen, namely the total and individual neuronal profile areas, number and diameters. The effects of the three fixatives on these variables were compared using ANOVA or Kruskal-Wallis, depending on the distribution. For measures on individual cells, a generalized linear mixed model was applied. Dice coefficients and correlations were applied to evaluate the agreement of the manual and automatic methods. Results: There was no significant difference between the brains fixed by the three fixatives for the total and individual cell areas, the total cell count and the cell diameters. The values obtained from manual and automatic measures had an overall good agreement (Dice coefficients > 0.79). Conclusion: It was found that the SSS and AFS had similar impacts on the quantitative variables in the tissue as the NBF. These results are promising for neuroscientists interested in using brains from anatomy laboratories for quantitative research on neurons from the PMC.

Chimpanzees share a number of age-related brain changes with humans, such as reductions in neurons and increases in neuropathology. To date, there are no published studies of peripheral biomarkers related to Alzheimers pathology and their associations with age and cortical atrophy in chimpanzees. Here we examined cross-sectional differences and longitudinal changes in biomarkers of pathological protein aggregation, neuroinflammation, and microglial function measured in serum. We examined the relationships between biomarkers and clinically relevant biomarker ratios with both age and cortical atrophy. We found linear and quadratic relationships between age and several biomarkers and ratios. Most biomarkers increased with age. While controlling for sex, we found significant negative associations between age and sulci surface area, mean depth, and gray matter thickness and a positive association with fold opening. A{beta}42 and A{beta}40 showed higher biomarker values associated with lower surface area, mean depth, and gray matter thickness and higher fold opening values. The clinically relevant biomarker ratios were also associated with cortical atrophy - A{beta}42/A{beta}40 was negatively associated with gray matter thickness, and pTau217/A{beta}42 (both total and brain-derived) was positively associated with surface area and gray matter thickness and negatively associated with fold opening. Consistent with our hypotheses and previous findings in humans, many peripheral biomarkers associated with neurodegeneration and Alzheimers disease increase as chimpanzees age. We believe this is the first evidence demonstrating an association between these clinically relevant biomarkers of Alzheimers disease and phenotypes of brain aging in nonhuman primates, underscoring their importance as models of aging and neurodegenerative disease.

Recognizing others emotions is central to social interaction. Traditional biological psychology infers emotional responding via laboratory measures, whereas contemporary computer vision algorithms claim to identify emotions unobtrusively from facial video. However, the validity of such algorithms for classifying spontaneous emotional responses occurring without explicit communicative intent remains debated. We compared established psychophysiological measures (EEG, facial EMG, EDA activity) with the open-source facial behavior toolkit OpenFace for classifying participants spontaneous responses during free viewing of happiness-inducing, disgust-inducing, and neutral pictures. Participants provided valence and arousal ratings and later selected the basic emotion that best matched their reaction which served as the classification criterion. Using within-participants single-trial support vector machine (SVM) classification, EEG achieved the highest accuracy (40%), followed by facial EMG (37%); OpenFace reached 36%. All methods except EDA exceeded chance performance (33.3%) and were lower compared to human raters (48%). Predictions declined slightly for across-participants SVMs, being at chance for OpenFace and EDA. The results indicate that in principle both, psychophysiological measures and video-derived facial action units, can capture diagnostically relevant aspects of emotional responding during picture viewing, but that their performance is limited when expressions are spontaneous and not produced for communicative purposes. Inter-individual variability in expressivity and physiological responding likely contributes to these limitations and should be considered when deploying automatic emotion recognition in research or applied settings.

Environmental temperature strongly influences muscle contractile mechanics and locomotor performance in ectotherms, yet animals routinely develop across a range of temperatures while maintaining effective movement. We tested the hypothesis that developmental temperature induces compensatory changes in the intrinsic mechanical properties of the muscles that power the fast-start escape response in larval zebrafish (Danio rerio). Larvae were reared at 25{degrees}C, 28{degrees}C, or 32{degrees}C, and contractile properties of intact tail myotomal muscles were measured across experimental temperatures. Acute changes in experimental temperature strongly affected twitch kinetics, particularly relaxation rate (Q10 = 2.1), resulting in substantial changes in twitch duration. In contrast, rearing temperature produced adaptive changes that opposed these acute thermal effects. At a common experimental temperature, muscles from cold-reared larvae exhibited faster intrinsic relaxation and greater force production during shortening at a physiologically relevant velocity, whereas warm-reared larvae showed slower relaxation and reduced shortening force. As a result, twitch kinetics were largely normalized when measurements were made at each group's rearing temperature, reducing the apparent thermal sensitivity of relaxation rate (Q10 = 1.1). To identify molecular correlates of these functional adaptations, we performed label-free quantitative LCMS proteomic analysis. Cold rearing increased the abundance of Sarco/Endoplasmic Reticulum Calcium-ATPase (SERCA) proteins, driven primarily by elevated atp2a1 expression, while warm rearing reduced the abundance of the major parvalbumin isoforms pvalb1 and pvalb2. These changes implicate remodeling of intracellular calcium handling as a mechanism underlying thermal compensation of muscle function. Together, our results demonstrate that developmental temperature modifies the intrinsic mechanical properties of larval zebrafish muscle in ways that counteract the direct effects of environmental temperature, thereby preserving the timing and power-generating capacity required for fast-start escape performance.

Heterozygous pathogenic variants in CSNK2A1 or CSNK2B encoding the Casein Kinase 2 (CK2) protein complex, lead to pediatric neurodevelopmental disorders, Okur-Chung Neurodevelopmental Syndrome (OCNDS) and Poirier-Bienvenu Neurodevelopmental Syndrome (POBINDS). OCNDS and POBINDS are characterized by a range of symptoms, including developmental delay, intellectual disability, facial dysmorphism, and seizures. Despite over 250 reported cases of OCNDS and POBINDS, we do not fully understand how specific alterations in CK2 relate to the heterogeneity observed in patients. To investigate this, we used the fruit fly, Drosophila melanogaster, as a model system. To assess variant impact, we co-expressed human CSNK2A1 and CSNK2B reference or disease-causing variants in flies. In parallel, we determined the role of Drosophila CkII in the developing and mature nervous system, specifically in neurons and glia. We found that 12/13 variants tested act as full or partial loss-of-function with one CSNK2A1 variant showing gain-of-function. Phospho-proteomic studies in neurons revealed separate signatures for loss- and gain-of-function variants. We found that neuronal and glial CkII is critical for organismal development. Reduction of neuronal CkII in the adult nervous system causes motor and seizure-like phenotypes. Finally, given the known role of CK2 in potentiating Wnt/{beta}-catenin signalling, we show that Wnt agonists partially rescue phenotypes associated with adult-specific neuronal reduction of CkII. This work generates Drosophila models of CSNK2A1 and CSNK2B expression to functionally assess variant impact, as well as an adult-specific neuronal loss-of-function model for drug screening and mechanistic studies.

AO_SCPLOWBSTRACTC_SCPLOWElectroencephalography (EEG) is a promising tool for automated detection of mild cognitive impairment (MCI) and dementia, but comparisons across studies are limited by inconsistent datasets and evaluation protocols. This study benchmarks ten deep learning models across four resting-state EEG datasets and eight binary classification tasks using a unified preprocessing pipeline and five-fold subject-wise cross-validation. Each experiment was repeated ten times. SCCNet obtained the highest mean subject-level accuracy, sensitivity, and F1 score, while ShallowConvNet achieved the highest mean segment-level accuracy, specificity, and precision. Subject-level aggregation improved mean accuracy for all evaluated models, and performance varied substantially across datasets and diagnostic tasks. Higher computational cost did not consistently correspond to better classification performance, with several compact architectures remaining competitive with substantially larger models. The results provide a reproducible reference for comparing EEG-based dementia classification models under consistent subject-independent evaluation conditions.

Studies in humans and murine models have pointed towards a possible link between metabolic syndrome, which shows insulin resistance and metabolic dysregulation, and Alzheimer's disease (AD) pathology marked by amyloid-beta (A{beta}) accumulation and hypometabolism in the brain. Yet, the underlying biological mechanisms by which metabolic syndrome affects these pathological changes in AD brain remain unknown. We hypothesized that insulin resistance is responsible for alterations in blood-brain barrier (BBB) transport of A{beta} peptides and glucose. This hypothesis was tested by employing radiolabeled ligands (125I-A{beta}40, 125I-A{beta}42, and 18F-FDG) in high-fat diet (HFD)-fed mouse models that manifest metabolic syndrome. Further, we assessed alterations in the expression of various molecular mediators within the brain microcapillaries harvested from both low-fat diet (LFD)-fed and HFD-fed mice. Our findings show that HFD-fed mice developed peripheral insulin resistance and obesity. In addition, HFD-fed mice demonstrated an increase in the influx rate of A{beta} peptides and a reduction in 18F-FDG (a glucose surrogate) influx rate compared to LFD-fed mice. These transport changes are associated with the increase in the BBB endothelial expression of RAGE (receptor to traffic A{beta} from plasma-to-brain) and reduction of GLUT1 (glucose transporter) expression in HFD-fed mice compared to LFD-fed mice. Moreover, disruption in insulin signaling, as indicated by reduced pAKT and pERK expression, was observed in HFD-fed mice. Inhibiting AKT or ERK phosphorylation resulted in similar changes in A{beta} and glucose uptake in polarized BBB endothelial cell monolayers in vitro. These results indicate that high-fat diet induced metabolic syndrome may lead to BBB dysfunction, characterized by increased plasma-to-brain A{beta} trafficking and diminished glucose transport at the BBB, thereby aggravating the expression of AD pathological hallmarks.

Insects solve complex behavioural tasks with remarkable efficiency, using minimal neural hardware tuned to the specific requirements of their ecological niches. To truly understand or replicate these behaviours, it is insufficient to model the brain in isolation: one must account for the dynamic, closed-loop interactions between the environment, the physical organisation of the sensory periphery, and internal biophysical dynamics. To address these issues for visually controlled behaviours, we present RhabdoForge, a modular, hardware-agnostic and high-performance rendering framework specifically designed for insect neuroethology and neuromorphic research. Designed for seamless integration into Python-based workflows, RhabdoForge implements both real-time ray-tracing and stochastic path-tracing using hardware-agnostic GPU pipelines. Crucially, the engine moves beyond the static "ommatidium-as-a-pixel" paradigm by introducing a fully parametrisable model where every layer of the compound eye (from the geometric shape and the topological lattice to the internal rhabdomere blueprint) is a discrete, swappable component. The engine is capable of simulating the high-frequency, sub-ommatidial rhabdomere photomechanical actuation, allowing for the investigation of a variety of active sensing phenomena within a real-time closed-loop environment. The framework also includes an automated morphological pipeline that allows transforming 2D anatomical data into faithful 3D sensory models. We validate the engine through two case studies: a closed-loop optic-flow centring response in a virtual tunnel, and the recovery of spatial hyperacuity via rhabdomere microsaccades. By providing a bridge between high-fidelity visual ecology and neuromorphic modelling, RhabdoForge enables researchers to explore how the interplay of sensory optics and neural processing can generate complex behaviour in both biological and artificial agents.