BMC Neuroscience

We investigated O-linked {beta}-N-acetylglucosamine (O-GlcNAc), a post-translational modification, in an in vivo Caenorhabditis elegans model of Alzheimers Disease and aging. Employing a chemoenzymatic labeling strategy combined with an automated image processing approach, we analyzed both post-hatching and adult stages of wild-type N2 and transgenic strain expressing human tau V337M under the aex-3 promoter (aex-3p::tau(V337M)). Labeled O-GlcNAc proteins were visualized using fluorescence microscopy and quantified using a region-of-interest-based image analysis pipeline. Morphometric characterization revealed an age-dependent increase in O-GlcNAcylation in wild-type worms, while the AD model showed a progressive decline. In middle-aged transgenic nematodes, O-GlcNAc-labeled regions of interest shifted from anterograde to predominantly retrograde movement, suggesting that aging and neurodegeneration alter O-GlcNAc trafficking dynamics, potentially reflecting impaired synaptic support or enhanced clearance in C. elegans. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/659071v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@10d6816org.highwire.dtl.DTLVardef@12ca2d8org.highwire.dtl.DTLVardef@17742b2org.highwire.dtl.DTLVardef@bbc33b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Motion artifacts remain a barrier to in vivo calcium imaging in Drosophila melanogaster larvae. Here, we evaluate a multimodal immobilization approach that combines a Pluronic F-127 (PF-127) hydrogel with brief diethyl ether vapor exposure (5 minutes, 25{degrees}C) and compare it against hydrogel-only immobilization using custom MATLAB-based analysis software that performs NoRMCorre rigid motion correction. In wide-field GFP recordings at 1 Hz over approximately 60 minutes (N = 15 per group), the multimodal condition significantly reduced motion across all three core metrics after FDR correction (all q < 0.001), with large effect sizes for mean speed (Hedges g = -1.18) and median step size (g = -1.36). In a secondary analysis of the first 30 minutes, uniformly large effect sizes (|g| = 1.10-1.51) were observed, consistent with stronger initial chemical immobilization that partially wanes over the recording period. We implemented a dual-flag quality control system that distinguishes motion data reliability from ROI detection eligibility. Control calcium recordings (33.33 Hz, [~]5 minutes; N = 23) yielded 368 ROIs with a mean SNR 30.4 {+/-} 16.9 and an event rate of 0.228 {+/-} 0.113 Hz. Experimental recordings (N = 21) yielded 295 ROIs with SNR 18.0 {+/-} 10.6 and event rate 0.309 {+/-} 0.188 Hz. SNR was higher in controls (Cliffs{delta} = 0.50, p < 0.001), while event rate was modestly higher in the experimental group at the ROI level ({delta} = -0.22, p < 0.001), though this difference did not reach significance at the sample level, suggesting altered but not suppressed calcium dynamics. These results support a practical, accessible immobilization workflow for larval calcium imaging. HighlightsO_LIBrief ether + hydrogel approach reduces larval motion 85-91% vs. hydrogel alone C_LIO_LIDual-flag QC system separates motion reliability from calcium ROI eligibility C_LIO_LICalcium event rates not suppressed under multimodal immobilization C_LIO_LIComplete MATLAB pipeline for motion analysis and calcium imaging provided C_LIO_LIAccessible protocol requires only standard laboratory supplies C_LI

AbstractOptogenetic tools have revolutionized the study of neuronal circuits in Caenorhabditis elegans. The expression of light-sensitive ion channels or pumps under specific promotors allows researchers to modify the behavior of excitable cells. Several optogenetic systems have been developed to spatially and temporally photoactivate light-sensitive actuators in C. elegans. Nevertheless, their high costs and low flexibility have limited wide access to optogenetics. Here, we developed an inexpensive, easy-to-build, and adjustable optogenetics device for use on different microscopes and worm trackers, called the OptoArm. The OptoArm allows for single- and multiple-worm illumination and is adaptable in terms of light intensity, lighting profiles and light-color. We demonstrate the OptoArms power in a population-based study on contributions of motor circuit cells to age-related motility decline. We find that functional decline of cholinergic neurons mirrors motor decline, while GABAergic neurons and muscle cells are relatively age-resilient, suggesting that rate-limiting cells exist and determine neuronal circuit aging.

SignificancePyruvate is a nodal intermediate in cellular metabolism, positioned at the crossroads between glycolysis and fermentative metabolism. It is exchanged between the intracellular and extracellular compartments through the proton-coupled monocarboxylate transporters and between the cytosol and mitochondria through the mitochondrial pyruvate carrier, where it serves as a primary carbon source for respiration. AimOur goal is to present a detailed protocol for quantifying cytosolic pyruvate concentration in neurons at single-cell resolution using a minimally invasive, two-point calibration approach with the FRET-based genetically-encoded fluorescent indicator Pyronic. ApproachThis protocol is based on a non-invasive pharmacological two-point calibration approach, where Pyronics dynamic range ({Delta}RMAX) is established by using trans-acceleration exchange to deplete intracellular pyruvate (RMIN), and by inducing Pyronic saturation (RMAX) through the combination of inhibition of pyruvate export, stimulation of its production, and blockade of its mitochondrial consumption. The protocol also incorporates the previously published KD values for Pyronic obtained from in vitro experiments. This procedure does not require the use of detergents to permeabilize the cells. ResultsImplementing this protocol enables the measurement of absolute cytosolic pyruvate concentrations. This quantitative parameter facilitates comparisons of pyruvate metabolism across different cells, samples and experimental batches, thereby enabling the comparison between a plethora of experimental conditions. ConclusionsThe FRET-based fluorescent indicator Pyronic can be reliably calibrated using a minimally invasive, pharmacology-based two-point calibration protocol in neurons, thus providing a robust and quantitative method to study pyruvate metabolism under various physiological and pathological scenarios.

Monogenic Parkinsons Disease can be caused by a mutation in the leucine-rich repeat kinase 2 (LRRK2) gene, causing a late-onset autosomal dominant inherited form of Parkinsons Disease. The function of the LRRK2 gene is incompletely understood, but several in vitro studies have reported that LRRK2-G2019S mutations affect neurite branching, calcium homeostasis and mitochondrial function, but thus far, there have been no reports of effects on electrophysiological activity. We assessed the neuronal activity of induced pluripotent stem cell derived neurons from Parkinsons Disease patients with LRRK2-G2019S mutations and isogenic controls. Neuronal activity of spontaneously firing neuronal populations was recorded with a fluorescent calcium-sensitive dye (Fluo-4) and analysed with a novel image analysis pipeline that combined semi-automated neuronal segmentation and quantification of calcium transient properties. Compared with controls, LRRK2-G2019S mutants have shortened inter-spike intervals and an increased rate of spontaneous calcium transient induction.

Insulin secretion from pancreatic {beta}-cells is integral in maintaining the delicate equilibrium of blood glucose levels. Calcium is known to be a key regulator and triggers the release of insulin. This sub-cellular process can be monitored and tracked through live-cell imaging and subsequent cell segmentation, registration, tracking, and analysis of the calcium level in each cell. Current methods of analysis typically require the manual outlining of {beta}-cells, involve multiple software packages, and necessitate multiple researchers - all of which tend to introduce biases. Utilizing deep learning algorithms, we have therefore created a pipeline to automatically segment and track thousands of cells, which greatly reduces the time required to gather and analyze a large number of sub-cellular images and improve accuracy. Tracking cells over a time-series image stack also allows researchers to isolate specific calcium spiking patterns and spatially identify those of interest, creating an efficient and user-friendly analysis tool. Using our automated pipeline, a previous dataset used to evaluate changes in calcium spiking activity in {beta}-cells post-electric field stimulation was reanalyzed. Changes in spiking activity were found to be underestimated previously with manual segmentation. Moreover, the machine learning pipeline provides a powerful and rapid computational approach to examine, for example, how calcium signaling is regulated by intracellular interactions in a cluster of {beta}-cells.

Measurements of Drosophila fecundity are used in a wide variety of studies, such as investigations of stem cell biology, nutrition, behavior, and toxicology. In addition, because fecundity assays are performed on live flies, they are suitable for longitudinal studies such as investigations of aging or prolonged chemical exposure. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another; the RoboCam, a low-cost, custom built robotic camera to capture images of the wells automatically; and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period; and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r2 = 0.98 for the correlation between the automated egg counts and the ground truth) In addition, we show that this method can be used to efficiently detect the effects on fecundity induced by dietary exposure to chemicals. Taken together, this strategy substantially increases the efficiency and reproducibility of high throughput egg laying assays that require exposing flies to multiple different media conditions.

Honey bees (Apis mellifera) offer an alternative model for investigating magnetoreception, exhibiting reliable navigation and behavioral responses to magnetic fields. Thanks to their compact brains, well-matched to the penetration depth of modern optical imaging techniques, they may offer insights into the neural and biochemical mechanisms underlying this sense, something that standard models, like migrating birds, have not so far provided. But also in honeybees, this progress requires tools capable of resolving weak, magnetically induced neural activity with high spatio-temporal precision. The approach, presented here, bridges quantum biology and neuroscience, allowing for testing the radical pair mechanism (RPM) as a potential basis for magnetic sensing. As the RPM predicts that magnetoreception is coupled to the visual system, we developed an in vivo two-photon calcium imaging approach to measure neural activity in the anterior optic tubercle, a higher-order visual center involved in chromatic processing and potentially navigation. Bees were prepared using a minimally invasive technique, in which this neuropil was retrogradely labelled with a fluorescent calcium indicator, enabling stable recording conditions over several hours. Controlled blue-light stimuli were provided by the scattered output of a fiber laser, and weak magnetic-field stimuli were applied by a shielded, three-axis Helmholtz coil system that allowed precise modulation of field strength and polarity while minimizing electromagnetic interference. Visual stimulation evoked consistent and reproducible calcium responses, validating the preparation and imaging stability. Magnetic stimulation produced small fluorescence decreases, suggesting field-dependent modulation of neural activity. The developed imaging framework shows the feasibility of detecting magnetic modulation in vision- and navigation-related brain regions, suggesting neural amplification of weak magnetic cues and providing a platform for controlled tests of RPM-specific predictions, including light dependence, polarity independence, and radiofrequency perturbation.

Rapid and reproducible optical transitions of a fluorescent protein (FP) can be achieved with a Genetically Encoded Voltage Indicator (GEVI) via manipulation of the membrane potential. These transitions revealed novel effects of internal mutations near the chromophore that would not be detected under steady state conditions. Mutating an internal threonine (T203) affected the speed of the voltage-dependent fluorescence transition suggesting a conformational change inside the protein. These optical transitions also demonstrated interplay between internal and externally oriented sidechains of the {beta}-can structure. Replacing the steric hindrance of a phenylalanine near the chromophore with threonine (F165T) did not alter the resting fluorescence but resulted in a more complex fluorescent transition providing evidence for a flexible chromophore undergoing conformational changes. F165T orientation was influenced by the flanking external amino acids at positions 164 and 166 with 164F/165T/166T exacerbating the complexity of the voltage-dependent transition while 164T/165T/166F reduced the flexibility of the chromophore resembling the transition pattern of the original F165 version. Alphafold predictions reveal a threonine switch with different orientations of the F165T internal side chain depending on the direction of the offset in polarity at external positions 164 and 166. The crystal structures of the pH-sensitive FP, Super Ecliptic pHluorin and two derivatives solved in varying pH conditions also indicate interactions between the external protein surface and the internal environment providing another example of a threonine switch near the chromophore at T203. This ability to orient internal sidechains has led to the development of a novel GEVI that gets brighter upon depolarization of the plasma membrane, works at low light levels, is less susceptible to physiological pH, and provides in vivo signals. These observations affecting fluorescent transitions should also prove valuable to the development of any FP-based biosensor.

Drosophila melanogaster serves as a powerful model for studying neurodegenerative diseases, often employing the GAL4-UAS system for targeted gene expression. Electroretinograms (ERGs) provide a robust in vivo functional readout of neuronal integrity and are increasingly used to assess disease progression and therapeutic interventions in these models. However, the genetic background upon which these models are built, particularly the widely used w1118 white-eyed mutant, can significantly influence baseline ERG characteristics. This study systematically characterizes ERG responses in wild-type Canton S (CS), w1118, and a w1118line carrying a UAS-hPLD1 construct (which includes a mini-white gene). We demonstrate profound differences in ERG amplitudes, waveforms, and responses to varying light stimuli (intensity and duration) between these genotypes, as well as significant sex-specific variations. Notably, w1118 flies exhibit markedly larger ERG amplitudes compared to CS, while the hPLD1 line shows partial compensation. We also introduce a novel quadrant-based analysis of the receptor potential, revealing distinct "fingerprints" for each genotype. These findings underscore that the w1118 background is not electrophysiologically neutral and can intrinsically alter neuronal responses. This has critical implications for interpreting ERG data from neurodegeneration models, as these background effects could mask or mimic disease-related changes. Researchers must consider these baseline differences and potential sex-specific effects to accurately attribute observed ERG phenotypes to the gene or condition under investigation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/626125v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1b655f0org.highwire.dtl.DTLVardef@1c412e7org.highwire.dtl.DTLVardef@1b52fe3org.highwire.dtl.DTLVardef@5af680_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIERG profiles differ significantly between CS, w1118, and w1118; UAS-hPLD1 flies. C_LIO_LIThe w1118 background, common in GAL4-UAS studies, exhibits distinct ERG features. C_LIO_LISex-specific differences in ERG responses are prominent and genotype-dependent. C_LIO_LIUAS-hPLD1 insertion (with mini-white) partially alters the w1118 ERG phenotype. C_LIO_LIResults caution the interpretation of ERG data in w1118 neurodegeneration models. C_LI

Understanding how organisms detect environmental humidity remains a fundamental problem in sensory biology. While specialized sensory neurons in insect antennae can detect changes in humidity, the mechanism underlying this ability is not fully understood. Here, we present an integrated approach combining precise humidity control, rapid cryo-preservation, and serial block-face scanning electron microscopy (SBF-SEM) to investigate the ultrastructure of hygrosensilla in the vinegar fly Drosophila melanogaster. We developed a deep learning-based segmentation pipeline to analyze three-dimensional structural features of sensilla exposed to different humidity conditions at stable temperature. Our analysis reveals consistent differences in sensilla width between high (80% RH) and low (26% RH) humidity conditions across all chambers of the sacculus. Additionally, we identified chamber-specific patterns in sensilla tapering, indicating specialized structural adaptations across different sensilla populations. The observed structural changes suggest a potential role for mechanical transduction in humidity sensing. This study establishes a technical framework for high-resolution analysis of sensory organs while providing new insights into the structural basis of humidity detection. Our findings advance our understanding of how specialized sensory organs might transduce environmental signals into neural responses.

BackgroundTransient pentylenetetrazol (PTZ) treatment on zebrafish larvae has been widely accepted a promising animal model for human epilepsy. However, this model is not ideal due to its acuteness and lack of recurrent seizures, which are the key feature of epilepsy in human disease. It is important to develop a more sensitive zebrafish model for epilepsy with well-controlled, predictable, recurrent seizures.\n\nNew MethodThe new method includes an experimental setup and a treatment protocol. The setup tracks the locomotion activity of up to 48 larvae simultaneously, while a visual stimulus can be presented to each of the 48 animals individually. The protocol treated the larvae through a water bath in 5 mM PTZ while being stimulated with rotating grating stimuli for 1 hour/day from 5 to 7 days postfertilization.\n\nResultsThe setup captured the locomotion activity of zebrafish larvae during visual stimulation. The new protocol generated recurrent responses after flashing lights 4 hours post PTZ treatment. The effects could be suppressed by the anti-epileptic drug valproic acid. The characteristics of the visual stimulus play a major role in this kindling model.\n\nComparisons with Existing MethodsWe compared the proposed method with the transient PTZ model and confirmed that the flashing-light-evoked recurrent seizure is a new feature in addition to the transient changes.\n\nConclusionsThe new method generated non-drug-triggered predictable recurrent seizures in response to intermittent photic stimulation in zebrafish larvae and may serve as a sensitive method for anti-epileptic drug screening or a new research protocol in epilepsy research.

Visually evoked steady-state potentials (SSVEPs) are neural responses elicited by visual stimuli oscillating at specific frequencies. In this study, we introduce a novel LED display system designed specifically for steady-state visual stimulation, offering precise control over visual stimulus parameters, including frequency resolution, luminance, and the ability to control the phase at the end of the stimulation. The LED display provides a personalized, modular, and affordable option for experimental setups. Based on the Teensy 3.2 board, the display utilizes Direct Digital Synthesis and Pulse Width Modulation techniques to control the LEDs. Its performance is validated through four experiments: the first two measure LED light intensities directly, while the last two assess the displays impact on EEG recordings. The results demonstrate that the display can deliver a stimulus suitable for generating SSVEPs with the desired frequency and phase resolution. We provide comprehensive documentation, including all necessary codes and electrical diagrams, as an open-source resource. This facilitates the replication and adaptation of the system for specific experimental requirements, enhancing its potential for widespread use in the field of neuroscience.

Alzheimers disease (AD) is characterized not only by tau and amyloid-{beta} aggregation but also by systemic disruptions in circadian rhythms, metabolism, and gut-brain communication that exacerbate neuroinflammation and neurodegeneration. While glial cells play central roles in inflammatory signaling and proteostasis, the contribution of the gut microbiome to glia-driven AD pathology remains poorly understood. Here, we used Drosophila models with glial-specific expressions of human tau and amyloid-associated transgenes to investigate how microbiome integrity influences disease progression. AD models exhibited significant shifts in gut microbial composition, particularly in Lactobacillus and Acetobacter species, suggesting an adaptive microbial response to pathological stress. Strikingly, microbiome depletion (axenic condition) markedly worsened behavioral and physiological outcomes, including disrupted sleep-circadian rhythms, impaired memory, and reduced locomotor function. These deficits were accompanied by amplified neuroinflammatory signaling (Upd-Dome-Hop-Stat92e axis), increased apoptotic gene expression, lipid dysregulation, and altered synaptic markers. Moreover, microbiome loss induced energy stress marked by elevated phospho-AMPK (p-AMPK), yet failed to restore proteostasis, as evidenced by accumulation of ubiquitinated proteins and the autophagy adaptor Ref2p, indicating impaired autophagic flux. This dysfunction correlated with increased tau, phospho-tau, and A{beta}42 accumulation. Together, our findings demonstrate that microbiome depletion exacerbates glial-mediated inflammation, disrupts circadian and metabolic homeostasis, impairs, and accelerates cognitive and motor decline. This work highlights a previously underappreciated role of the gut microbiome in restraining glial dysfunction and mitigating AD-like pathology, positioning microbial homeostasis as a critical modulator of neurodegenerative disease progression.

General anesthesia (GA) has been under scientific scrutiny since its discovery more than a century ago, resulting in conceptually different proposed mechanisms to explain its origin and operation. Two mechanisms stand out: the lipid and the protein hypothesis. The Meyer-Overton rule (the more anesthetics dissolve in octanol, the greater their action) backups the first hypothesis, while the ligand-receptor interaction, specifically on ion channels, sustains the second. A recent study on Drosophila melanogaster draws attention to the possibility that both paradigms come together to explain GA synergistically, with the important caveat that this hybrid mechanism lies in the existence of lipid rafts in which cholesterol plays an essential role. Using two model organisms, the water flea (D. magna) and the nematode C. elegans, we give a further step to clarify this puzzle by carrying out anesthetic experiments with xenon and nitrous oxide. First, the obtained dose-response curves are very steep, implying that Hill coefficients greater than one are needed to describe them correctly, supporting an unspecific action mechanism. Second, we show that the animals response to both gases is influenced by a cholesterol diet modification, thus proving that this lipid promotes anesthetic induction. Our findings reenforce the idea that GA is driven by an allosteric induction rather than selective actions on single-target receptors.

SignificanceThe firefly enzyme luciferase has been used in a wide range of biological assays, including bioluminescence imaging of ATP. The biosensor Syn-ATP utilizes subcellular targeting of luciferase to nerve terminals for optical measurement of ATP in this compartment. Manual analysis of Syn-ATP signals is challenging due to signal heterogeneity and cellular motion in long imaging sessions. Here, we have leveraged machine learning tools to develop a method for analysis of bioluminescence images. AimOur goal was to create a semi-automated pipeline for analysis of bioluminescence imaging to improve measurements of ATP content in nerve terminals. ApproachWe developed an image analysis pipeline that applies machine learning toolkits to distinguish neurons from background signals, and excludes neural cell bodies, while also incorporating user input. ResultsSide-by-side comparison of manual and semi-automated image analysis demonstrated that the latter improves precision and accuracy of ATP measurements. ConclusionsOur method streamlines data analysis and reduces user-introduced bias, thus enhancing the reproducibility and reliability of quantitative ATP imaging in nerve terminals.

Social interaction, a pivotal aspect of human and animal behavior, involves a dynamic exchange of information that shapes behavioral responses, emotional states, and cognitive processes. To gain insights into the neural mechanisms underlying these processes, it is necessary to simultaneously investigate the brain activity of socially interacting subjects. Commonly, the simultaneous study of behavior and brain activity during the execution of social tasks is conducted through Hyperscanning in humans which limits the availability of interventions. Here we describe a new experimental platform that combines the development of a new miniaturized optical system, the "MiCe-Scope", to monitor neural activity across the entire cortical mantle with a behavioral paradigm to perform a Hyperscanning study in freely moving mice engaged in social interaction. Our results revealed inter-brain synchrony across different frequency bands widespread over the entire cortical mantle, modulated by social behavior. This finding suggests that synchronization reflects the mutual prediction performed by the entire cortex in mice of interacting dyads. The presence of different synchronization maps in these frequency bands suggests a multiscale nature of interaction, extending the predictive nature of interaction to cortical areas beyond the medial prefrontal cortex. Our work provides an experimental framework to conduct Hyperscanning studies in an animal model that mirrors findings from human studies.

Improvement of imaging quality has the potential to visualize previously unseen building blocks of the brain and is therefore one of the great challenges in neuroscience. Rapid development of new tissue clearing techniques in recent years have attempted to solve imaging compromises in thick brain samples, particularly for high resolution optical microscopy, where the clearing medium needs to match the refractive index of the objective immersion medium. These problems are exacerbated in insect tissue, where numerous (initially air-filled) tracheal tubes branching throughout the brain increase the scattering of light. To date, surprisingly few studies have systematically quantified the benefits of such clearing methods using objective transparency and tissue shrinkage measurements. In this study we compare a traditional and widely used insect clearing medium, methyl salicylate combined with permanent mounting in Permount ( MS/P) with several more recently applied clearing media that offer tunable refractive index (n): 2,2-thiodiethanol (TDE), SeeDB2 (in variants SeeDB2S & SeeDB2G matched to oil and glycerol immersion, n=1.52 & 1.47 respectively) and Rapiclear (also with n=1.52 & 1.47). We measured transparency and tissue shrinkage by comparing freshly dissected brains with cleared brains from dipteran flies, with or without addition of vacuum or ethanol pre-treatments (dehydration and rehydration) to evacuate air from the tracheal system. The results show that ethanol pre-treatment is very effective for improving transparency, regardless of the subsequent clearing medium, while vacuum treatment offers little measurable benefit. Ethanol pre-treated SeeDB2G and Rapiclear brains show much less shrinkage than using the traditional MS/P method. Furthermore, these newly developed media offer outstanding transparency compared to TDE and MS/P. Rapiclear protocols were less laborious compared to SeeDB2, but both offer sufficient transparency and refractive index tunability to permit super-resolution imaging of local volumes in whole mount brains from large insects, and even light-sheet microscopy. Although long-term permanency of Rapiclear stored samples remains to be established, our samples still showed good preservation of fluorescence after storage for more than a year at room temperature.

Drosophila has long served as a powerful model for investigating locomotor behavior, and geotaxis assays have generated valuable insights into genetics, aging, and neurobiology. Nonetheless, their use can be constrained by subjective scoring, modest throughput, and challenges in reproducibility. To complement and extend these classical approaches, we developed and validated an integrated hardware-software platform that enables automated, high-resolution locomotor analysis across 12 vials in parallel. The system integrates 3D-printed mechanical components, Raspberry Pi-based video acquisition, and programmable environmental controls to ensure standardized conditions. A deep learning pipeline segments vials with near-perfect accuracy (IoU > 0.95), while computer vision algorithms quantify climbing trajectories, velocity, and positional zone occupancy at 60 frames per second. The end-to-end workflow converts raw video into time-resolved metrics, supports sex-specific aggregation, and incorporates advanced statistical analyses, including Linear Mixed Effects regression, harmonic mean p-values, and Mann-Whitney U tests. Relative to manual scoring, this automated pipeline yields 2.8-fold faster processing and nearly 800-fold higher data density. Application of the platform uncovered reproducible phenotypes of multiple genotypes. For example, a circadian mutant known as Clockout, males displayed progressive climbing deficits with age, whereas females-maintained age-resilient trajectories. Moreover, male Clockout exhibited a reduced performance compared to age-matched control (w1118), however, female Clockout showed subtle reduction in performance. Additionally, glial-specific knockdown of PolG, encoding the DNA polymerase gamma catalytic subunit, revealed striking sex-dimorphic aging patterns: females outperformed controls at older age, while males exhibited marked decline. To promote broad adoption, a user-friendly Python interface (Tkinter GUI) enables accessibility independent of computational expertise. Collectively, this standardized, high-throughput framework advances the resolution of genotype-, age-, and sex-dependent locomotor dynamics, offering new opportunities in aging, circadian biology, and neurodegeneration research.

The quantitative analysis of dynamic cellular events from time-lapse microscopy is critical for understanding biological processes but is often hindered by low signal-to-signal ratios and subjective manual parameter 1,2.To address these limitations, TransiScope was developed as an open-source tool built on Python and the napari viewer, offering a seamless workflow within a single graphical user interface2-4. Its key innovation is a data driven, interactive approach to parameter optimization, where the software analyzes user defined regions of interest (ROIs) to propose optimal settings for algorithms like the Difference of Gaussians (DoG) filter5,6, ensuring consistency by averaging signals from multiple ROIs. The platforms performance, validated using open-resource .avi files from published studies, demonstrates high specificity and a low false-positive rate, accurately quantifying events in signal-positive regions while correctly identifying zero events in background areas7-11. By replacing manual trial-and-error with a guided workflow, TransiScope enhances the objectivity, speed, and reproducibility of transient event analysis, providing an accessible solution for robust quantitative imaging12.