BMC Neuroscience

Organisms have spent their life histories exposed to background levels of natural ionizing radiation. To document the role that radiation plays, the deprivation of these natural levels has been studied by incubating organisms in the shielded space of underground laboratories. We report here on two studies (Study I and Study II) using Aedes aegypti for the first time as a model organism incubated 655 meters underground at the Waste Isolation Pilot Plant (WIPP) outside of Carlsbad, New Mexico, U.S.A. Male mosquitos were incubated at the surface exposed to natural background radiation, and were compared to two underground treatments in which incubators were supplemented with radiation sources used to mimic background and these groups were compared to the underground, radiation-deprived treatment. In Study I, the mosquitos incubated underground in the absence of natural radiation had higher levels of mortality compared to those incubated at the surface and PCA plots of the two transcriptomes were clearly differentiated. Study II was conducted the following year and the experiment was narrowed to include only the surface control and underground, radiation-deprived treatment which allowed for four biological replicates. Again, there was a higher level of mortality in the mosquitos grown underground compared mosquitos grown at the surface. Transcriptomes were not as clearly differentiated by PCA analysis and fecundity data were similar between the two groups. Functional analysis of transcriptomic DEGs from two independent studies suggested there are stress responses in radiation deprived mosquitoes. The absence of a secondary stressor in Study II is discussed as an explanation for the transcriptome differences in the two experiments.

Optical recording from large numbers of neurons is an indispensable technique for studying neuronal ensembles. We use optical sectioning through pinhole illumination to reduce the background fluorescence (F0) and increase the optical signal ({Delta}F/F0) in ex vivo brain slices densely labeled with GCaMP6f, allowing an ordinary fluorescence microscope to capture calcium transients from over 300 individual CA1 neurons - a marked increase compared to ordinary wide field fluorescence illumination. Multiple layers of overlapping neurons can be identified by their locations and the shape in space of their {Delta}F/F0 images. A single pinhole mask was placed at the field stop of a wide field illuminator, and the image of the pinhole was projected onto the tissue by a 20X NA 0.95 water immersion objective (Olympus). This created an illuminated disk with a diameter of [~]200 m and optical sections of hippocampal CA1 pyramidal layer tissue [~]100 m thick. This illumination blocked a large fraction of the F0, which in turn increased the {Delta}F/F0 5-10-fold compared to that of wide field illumination. When putative pyramidal neurons fire sparsely in the brain slice, up to 300 partially superimposed neurons can be identified by their shape and spatial location in the thick ([~]480 m) ex vivo slice in the CA1 area surrounding the pinhole image. The signal-to-noise ratio was adequate even at a low excitation light level of [~]20k photoelectrons per pixel well on the camera, allowing for 3,000 seconds of total recording time without significant bleaching. This pinhole "half confocal" method has created a useful way to sample calcium transient signals in thick tissue with a large population of neurons densely labeled with GCaMP-6f.

Photobiomodulation (PBM) is a therapeutic approach based on illumination with red or near-infrared (NIR) light. Cytochrome c oxidase (COX), a terminal enzyme of the mitochondrial respiratory chain, contains copper centers (CuA and CuB) that absorb light within the red and NIR spectral range, making it a potential primary photoacceptor at wavelengths around 820 nm. PBM appears to be a promising strategy for the treatment and prevention of neurological disorders. Elucidating its precise molecular mechanisms may help optimize therapeutic outcomes. Using patch-clamp method, we showed that illumination with 820 nm light activates mitochondrial large-conductance calcium-activated potassium (mitoBKCa) channels in rat hippocampal mitochondria. Moreover, 820 nm light caused neuroprotective effect in NMDA-treated organotypic hippocampal cultures. Consistently, activation of mitoBKCa channel by 820 nm light illumination was observed in mitochondria isolated from glioma U-87 MG cells. To further investigate the role of mitoBKCa channel, we used CRISPR/Cas9- developed U-87 MG cells lacking the -subunit of the BKCa channel (dBK cells). Comparative transcriptomic analysis of illuminated wild-type and dBK cells revealed significant differences in gene expression profiles. In summary, our results show two types of cellular responses to the PBM. An acute effect involving activation of the mitoBKCa channel and a long-term effect associated with extensive transcriptome remodeling. Both mechanisms may contribute to the cytoprotective effect of 820 nm near-infrared light. HighlightsO_LI820 nm light activates hippocampal mitochondrial BKCa channels C_LIO_LI820 nm light induces hippocampal neuroprotection under excitotoxic conditions C_LIO_LI820 nm light causes intensive transcriptome remodeling in glioma cells C_LIO_LIBKCa channels modulate a subset of transcriptomic responses to 820 nm light C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=171 SRC="FIGDIR/small/731043v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@5a5595org.highwire.dtl.DTLVardef@a8ddb2org.highwire.dtl.DTLVardef@72ec20org.highwire.dtl.DTLVardef@ec46da_HPS_FORMAT_FIGEXP M_FIG C_FIG

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.

Alterations of fluorescence properties in retinal pigment epithelium (RPE) cells caused by diseases such as age-related macular degeneration (AMD) highlight the need for detailed analysis of the fluorescent RPE granules at the individual level. Precise segmentation and classification of these granules remain challenging due to their limited visual separability. In this study, we present Classi4RPE, a computational algorithm designed to accurately segment RPE granules and classify them into three categories -- lipofuscin (L), melanolipofuscin (ML), and melanin (M) -- based on fluorescence lifetime imaging data, which provide distinctive contrast. The method is implemented in a custom Python framework and employs seeded watershed segmentation to isolate individual granules. Lipofuscin granules are identified as hyperfluorescent structures with longer lifetimes, while granules with shorter lifetimes are further analyzed based on their spatial lifetime distribution from the center to edge, enabling discrimination of ML from other melanin-rich granules. Our approach achieves high performance, with mean sensitivities of 0.99 for L granules and 0.90 for ML granules, and corresponding specificities of 0.93 and 0.98, respectively, compared to manually annotated ground truth. These results demonstrate the potential of Classi4RPE to surpass human visual limitations and provide a robust tool for quantitative RPE analysis.

Normal brain aging and Alzheimers disease both involve progressive structural brain alterations, making it challenging to distinguish pathological neurodegeneration from normative aging-related atrophy. This study investigated whether Alzheimers disease exhibits radiomic patterns that mimic, diverge from, or selectively perturb age-associated structural brain changes. T1-weighted magnetic resonance imaging scans from the Alzheimers Disease Neuroimaging Initiative were analyzed using a region-wise radiomics framework across 10 anatomically defined brain regions. Radiomic features were extracted following automated segmentation, bias field correction, and intensity normalization. Age-associated radiomic patterns were first identified in cognitively normal subjects using Spearman correlation analysis. Features demonstrating significant age sensitivity were subsequently compared between cognitively normal and Alzheimers disease cohorts across age bins using Welchs two-sample t-tests with permutation-based significance estimation and false discovery rate correction. Medial temporal and limbic regions, particularly the hippocampus, entorhinal cortex, and cingulum, demonstrated consistent age-aligned radiomic trajectories with systematic, statistically significant disease-related shifts across all age bins, supported by large effect sizes and bootstrap-validated confidence intervals. In contrast, several other regions demonstrated more heterogeneous and less stable patterns of group separation across age bins. Secondary analysis using late mild cognitive impairment subjects demonstrated that these radiomic divergences are detectable at the transition from normal cognition to mild cognitive impairment, with statistically significant CN-LMCI separation but no significant LMCI-AD separation, positioning the identified markers as early-stage rather than late-stage indicators of neurodegeneration. These findings indicate that Alzheimers disease does not uniformly mimic normal aging across the brain but instead selectively perturbs radiomic features associated with normative aging trajectories. The identified markers represent promising candidates for age-adjusted radiomic biomarkers, warranting validation in independent cohorts to establish their generalisability. The fully automated nature of the analytical pipeline -- spanning segmentation, feature extraction, and statistical comparison without manual annotation -- may facilitate scalable validation of these biomarkers in larger neuroimaging cohorts.

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.

Noise-induced hearing loss (NIHL) is a leading cause of permanent hearing impairment worldwide, yet no pharmacological therapies are currently available to prevent or treat this disorder. Although inflammation is increasingly recognized as a key contributor to cochlear degeneration, the therapeutic potential of targeting early inflammatory signaling remains poorly understood. Here, we combined phenotypic screening in zebrafish with mechanistic and functional validation in complementary mouse models to identify quinoxaline derivatives with otoprotective activity following acoustic trauma. Lead compounds preserved cochlear synapses and auditory function after moderate noise exposure, while one derivative also protected sensory hair cells in a model of permanent hearing loss. Mechanistic analyses demonstrated that this protection was associated with attenuation of early NF-{kappa}B signaling and modulation of the cochlear inflammatory response toward a reparative state, consistent with suppression of pathogenic innate immune activation before irreversible tissue damage occurred. Together, these findings identify early NF-{kappa}B-dependent inflammatory signaling as a therapeutically actionable mechanism in NIHL and establish quinoxaline derivatives as promising candidates for pharmacological intervention. More broadly, this work demonstrates the utility of a cross-species discovery platform for identifying therapies that preserve sensory function by targeting early inflammatory pathways.

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.

Digital behaviour change interventions have emerged as a promising approach for improving health, well-being, and performance, yet relatively few studies have evaluated their effects using objective biological and neurophysiological measures. The present study examined the effectiveness of Autonomic, a neuroscience-informed digital coaching platform designed to improve student well-being through personalized behavioural interventions targeting sleep, stress, mood, energy, and focus. Thirty university students engaged with the platform for ten weeks and completed behavioural assessments, biomarker collection, and electroencephalographic (EEG) testing at baseline, five weeks, and ten weeks. Behavioural outcomes included self-reported ratings of focus, energy, sleep, mood, and stress. Biological measures included salivary cortisol and tear fluid dopamine concentrations. EEG assessments included resting-state recordings, frontal theta activity during a working memory task, and N200/P300 event-related potentials during a visual oddball task. Significant improvements were observed in self-reported focus, energy, and sleep quality across the intervention. Electrophysiological measures demonstrated reduced frontal theta power during working memory and shorter P300 latencies during attentional processing, consistent with more efficient cognitive processing following the intervention. Although cortisol, dopamine, and resting-state EEG measures did not reach statistical significance, all exhibited changes in the predicted direction. Collectively, these findings provide converging behavioural, biological, and neurophysiological evidence supporting the effectiveness of Autonomic. More broadly, the study demonstrates the value of combining objective biomarkers and EEG with traditional behavioural assessments when evaluating digital behaviour change interventions and highlights the potential of neuroscience-informed coaching platforms to improve health, well-being, and cognitive functioning in university students.

While a growing number of studies have linked environmental exposures and Parkinsons disease (PD)1-3, the impact of many pesticides remains understudied4,5; for example, neonicotinoids are the most used insecticides in the world, but research into their contribution to PD is limited to a handful of studies6-8. Newer pesticides, such as the butenolide flupyradifurone (FPF), specifically developed to overcome increased pest resistance9 and spurred on by tighter restrictions on neonicotinoids such as imidacloprid (IMI)10, are even less studied. New approach methodologies (NAMs) that allow for rapid evaluation of pesticide exposures are needed to evaluate potential links between the growing number of pesticides and PD11. To this end, we exposed the model nematode Caenorhabditis elegans12 to IMI and FPF. Due to its high degree of tractability, and conservation of many genetic, neuronal, and toxic mode of action processes, C. elegans has been invaluable in both elucidating mechanisms and novel therapeutic targets for PD that can be validated in other models13, and as a complementary tool for early toxicity screening14. Along this line, we found that exposure to IMI, and to a greater extent FPF, in young adult animals causes significant dendritic blebbing, an early sign of neurodegeneration, exclusively in dopaminergic neurons. Blebbing was accompanied by impairment of dopamine-mediated behaviors, changes in neuronal mitochondrial morphology, and elevation of pathways related to reactive oxygen species (ROS). We were able to reduce the blebbing caused by IMI and FPF two ways: 1) pharmacologically via administration of the antioxidant N-acetyl cysteine (NAC); 2) genetically via knockout of a MAP kinase (MAPK) stress response pathway. This suggests that oxidative stress is a key mediator of this insecticide-induced dopaminergic neurodegeneration.

Chemical imaging is a powerful branch of modern microscopy encumbered by a lack of flexible, high-throughput analysis tools. Bespoke analytical pipelines typically perform ratiometric analysis on two layers in a multispectral image to describe the relative composition of molecules in a sample. This strategy has been implemented across fields, spanning histopathology, cell biology, environmental science, and materials science. The commercialization of chemical imaging microscopes has facilitated the collection of large multispectral datasets, necessitating accessible ways to process them. This paper describes Multispectral Analysis Graphical User Interface (msaGUI), a desktop graphical user interface to analyze individual and batch datasets of multispectral images. Data is loaded as CSV, TSV, or TIFFs and processed through a user-defined sequence of modular image operations that can be flexibly combined, e.g. to reduce spectral crosstalk or background noise. After analysis, data is visualized as exportable images, histograms, and statistics. To yield publication-quality figures, outputted images are fully customizable. Written in Python with open-source libraries, the msaGUI program is packaged into an executable for Windows and Mac for a fully no-code application. Other operating systems are supported via the Python source code. In summary, msaGUI provides a rapid and user-friendly solution for analyzing and visualizing multispectral data.

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.

The use of meditation as a tool to improve human wellbeing is receiving considerable scientific interest. However, most existing research has focused on concentration-based practices. One powerful alternative is jhana meditation, which leads to states characterised by self-reinforcing bliss, potentially useful for a variety of clinical and scientific domains. However, our understanding of these states is limited by small amounts of data and poor access to experts. To enable new insights, here we release the largest to date and first open-access dataset of electroencephalographic and physiological recordings in expert Jhana meditators. This includes 100+ hours of data in N=26 subjects across three retreats, alongside a detailed description and example code illustrating analysis of the data. This open dataset release can enable wider collaboration and has the potential to move us closer to an understanding of endogenously generated altered states of consciousness.

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.

Automated platforms such as Chi.Bio enable simultaneous monitoring of optical density and fluorescent reporter expression in 20 ml reactor cultures with controllable pump systems. As such, they provide an appealing option for contemporary gene expression quantification, quantitative physiology, and laboratory evolution and ecology experiments. While optical density calibration for this device is well established, no equivalent calibration framework exists for fluorescence, making quantitative comparison with reference instruments unreliable. Here, we characterize Chi.Bio fluorescence capabilities using fluorescent calibration microspheres and fixed GFP-expressing S. cerevisiae and E. coli cells, compared with orthogonal plate-reader measurements. We show that microsphere fluorescence is detectable and scales linearly with concentration, whereas the GFP signal from both species falls below the device detection limit. Comparison of background-correction strategies indicates that direct subtraction of a non-fluorescent control measured within the same device yields more reliable fluorescence estimates than the commonly used on-line normalization method. Knowledge of these sensitivity boundaries of the device provides practical guidelines for experimental design of future studies.

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.

Background Despite WHO grade and IDH status, significant survival differences remain in diffuse gliomas. We hypothesized that a brain-aging transcriptomic signature, reflecting neuroinflammation, myeloid infiltration, and synaptic loss, would independently predict survival and allow for molecular reclassification. Methods A neurodegeneration score was derived via PCA of brain MRI volumes from 1,057 OASIS-3 subjects and projected onto 888 TCGA-LGG/GBM (discovery) and 693 CGGA gliomas (validation). A 14-gene signature of glial/myeloid (GFAP, AQP4, TYROBP, TREM2, C1QA, CD68, ITGAM) and neuronal (SYP, DLG4, GRIN1, GRIA1, SNAP25, SYN1, RBFOX3) genes were computed. Elastic-net Cox regression identified a 3-gene panel (C1QA, CD68, GRIA1). Kaplan-Meier, multivariate Cox, decision curve, and single-cell RNA-seq analyses were performed. Results High brain-aging scores predicted poorer overall survival (p < 0.0001) and remained an independent prognostic factor after adjusting for WHO grade and IDH status (z = 4.72, p < 0.001); chronological age was non-significant (p = 0.231). In IDH-mutant gliomas, significance was confirmed in both cohorts (TCGA p = 0.027; CGGA p < 0.0001). Bidirectional reclassification showed high-risk Grade 2 tumors with Grade 3-like survival (p = 0.00089), and indolent Grade 3 tumors resembling Grade 2 by Ki-67. Single-cell RNA-seq confirmed macrophage localization of signature genes; DCA demonstrated net benefit over grade alone at 5-30% probability thresholds. Conclusions A brain-aging transcriptomic signature independently predicts glioma survival beyond WHO grade and IDH status, validated in an independent Chinese cohort, with clinical utility for identifying high-risk Grade 2 and sparing over-treatment of indolent Grade 3 tumors.

INTRODUCTION: Brain age gap (BAG) is the difference between a person's chronological age and the age predicted from the structural appearance of their brain on MRI. A higher BAG indicates an older-appearing brain and provides a global marker of structural brain aging across the Alzheimer's disease continuum. Prior studies suggest that females may show greater Alzheimer's disease-related pathology or faster late-stage neurodegeneration than males. We tested whether sex was associated with baseline BAG or longitudinal BAG change after accounting for APOE {epsilon}4 genetic risk, amyloid positivity, cognitive severity, and disease stage. METHODS: We developed a domain-adaptive deep learning model to estimate BAG from T1-weighted MRIs, training it on 26,512 neurologically healthy UK Biobank data and fine-tuning it on 2,974 amyloid-negative cognitively normal samples from Mayo Clinic Study of Aging and OASIS-3 cohorts. We applied the model to ADNI and used hierarchical mixed-effects models to test whether sex was associated with BAG trajectories after adjusting for Alzheimer's disease risk factors. RESULTS: After adjustment for Alzheimer's disease risk factors, there was no baseline sex differences in BAG. Longitudinally, females showed greater BAG acceleration than males, but this effect was moderated by APOE {epsilon}4 status. APOE {epsilon}4 accelerated brain aging in a dose-dependent manner, independent of amyloid burden. DISCUSSION: Sex differences in BAG across the AD continuum were largely explained by APOE {epsilon}4-related acceleration rather than by an independent effect of sex alone. These findings suggest that females may be more vulnerable to APOE {epsilon}4-associated structural brain aging over time.

BackgroundWe previously demonstrated that 1,10-phenanthroline-5-amine (PAA) significantly reduced the number and size of amyloid plaques in one-year-old APP/TAU mice. The primary objective of the present study was to validate these findings in the APP/PS1 mouse model using a larger cohort of animals. A second objective was to determine whether PAA binds directly to amyloid plaques in brain tissue sections. MethodsFor the in vivo studies, APP/PS1 mice received daily oral PAA or vehicle treatment and were euthanized at one year of age. Brains were collected, fixed, cryosectioned, and stained with hydroxyquinoline oxalate (HQ-O) to visualize amyloid plaques. For the in vitro studies, brain tissue sections were incubated in a PAA solution. Double labeling with PAA and HQ-O was performed on the same tissue sections to compare plaque labeling patterns. ResultsDaily oral administration of PAA produced a significant reduction in both the number and size of amyloid plaques compared with untreated control mice. In vitro incubation of tissue sections with PAA resulted in red fluorescent labeling of all amyloid plaques. Double-labeling studies showed that PAA labeled plaques are more extensive than HQ-O in frozen tissue sections, whereas no such difference was observed in paraffin-embedded sections. ConclusionsThese findings extend our previous observation that chronic oral administration of PAA significantly reduces amyloid plaque burden in vivo. In addition, the in vitro studies demonstrate that PAA binds directly to amyloid plaques. The mechanism of PAA binding may involve interactions with transition metals incorporated within amyloid plaques and/or the sialic acid moieties of plaque-associated gangliosides.