BMC Neuroscience

Zebrafish (Danio rerio) are an important vertebrate model for vision and neuroscience research. In the larval stages, the aquatic species begins to elicit the optomotor response (OMR) to stabilize themselves in water -- a behaviour that may be exploited in the laboratory to measure visual acuity. However, up to now, the measurement of the OMR in juvenile and adult zebrafish has been limited due to their behavioural complexity. Here, we optimize a protocol to assay zebrafish aged between 4 and 9 weeks-post-fertilization, by displaying sinusoidal gratings parallel to the zebrafish eye to elicit a robust OMR. We assessed the visual spatial-frequency tuning function of an environmentally induced myopia model to confirm the sensitivity and robustness of the protocol. Additionally, we show the OMR is sensitive to the contrast and temporal resolution of the sinusoidal gratings. Furthermore, we found that the time between stimulus presentations impact the spatial-frequency tuning function likely as time is required for zebrafish to return to baseline swimming after eliciting the OMR. Finally, we found that the OMR after ten versus twenty seconds of stimulus onset appears comparable; indicating that robust OMR responses in zebrafish can be elicited through relatively short stimulus presentations. Through the experiments conducted, we present an optimized protocol specific to zebrafish. The protocol may be used to follow the progression or treatment efficacy of progressive neurological disorders including specific visual disorders and higher brain functions with visual endophenotypes. Ultimately, this protocol allows for high-throughput robust measures of visual and neural function in zebrafish.

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

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.

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.

SignificanceDigital Holographic Microscopy (DHM) provides label-free quantitative phase images (QPIs) of living cells and has become a powerful tool for studying cellular morphology and dynamics. While most DHM studies have focused on cell-level analysis, the quantitative characterization of neuronal network organization and maturation from DHM images remains largely unexplored, highlighting the need for dedicated computational approaches. AimWe aimed to develop an automated framework combining deep-learning-based image analysis and graph theory to quantitatively characterize the organization, connectivity, and maturation of neuronal networks in primary rat cortical cultures imaged by DHM. ApproachTwo U-Net convolutional neural networks were trained on manually annotated DHM phase images to segment neuronal cell bodies and neurites. The resulting segmentation maps were used to infer putative morphological connections between neurons and generate graph representations of neuronal networks, referred to as graph fingerprints. A panel of 18 connectomics-inspired graph features was then computed to characterize local and global properties of network organization across four stages of culture maturation. ResultsThe mean area under the receiver operating characteristic curves was 0.98 for cell-body and 0.91 for neurite segmentation, indicating near-perfect identification. Graph-theoretical analysis revealed reproducible topological changes during network maturation in vitro, including increased density, reduced modularity, and progressive network integration. Correlation analysis showed that the 18 graph features grouped into two highly correlated families. A Random Forest classifier identified density and modularity as the most informative descriptors, achieving an accuracy of 87% in classifying maturation stages of neuronal cultures. ConclusionsOur results demonstrate that combining DHM, deep-learning-based segmentation, and graphtheoretical analysis enables quantitative characterization of neuronal network organization and maturation from label-free phase images. This framework provides a foundation for future studies of pharmacological experiments, neuronal network phenotyping, and human induced pluripotent stem cell (hiPSC)-derived neuronal cultures, where quantitative assessment of network organization remains a major challenge.

Light-actuated G protein-coupled receptors (optoGPCRs) are a class of opsins that act through intracellular signaling cascades. As optogenetic tools, bistable inhibitory optoGPCRs are attractive as they decouple the duration of silencing from the duration of illumination: brief light pulses drive prolonged signaling. Opsin3 from the mosquito Anopheles stephensi (MosOPN3) is a bistable Gi/o-coupled opsin that produces sustained inhibition in mammalian neurons and C. elegans, but its utility in vinegar flies, Drosophila melanogaster, remains untested. Here we tested three optoGPCRs in adult flies; MosOPN3 emerged as the most effective and was benchmarked against an established inhibitor, Guillardia theta anion channelrhodopsin 1 (GtACR1), in walking and memory assays. MosOPN3 inhibitory potency was comparable to that of GtACR1 across most neuronal classes tested, with substantially lower developmental toxicity. Rearing flies on all-trans-retinal-supplemented food throughout development improved both viability and inhibitory efficacy for both opsins. A single pulse of green light (as brief as 5 s) inhibited behavior for minutes, and was sufficient to ablate aversive olfactory learning over a one-minute training epoch. For flies, MosOPN3 is a low-toxicity optogenetic inhibitor for flies that yields minutes of silencing from brief light pulses--especially useful where continuous actuating light would be confounding. Key pointsO_LITo our knowledge, Anopheles stephensi Opsin3 (OPN3) is the first GPCR opsin that inhibits behavior in adult Drosophila melanogaster. C_LIO_LIOPN3 has inhibitory efficacy close to that of GtACR1, with superior viability. C_LIO_LIBrief light pulses drive sustained inhibition lasting minutes, eliminating the need for continuous illumination. C_LIO_LIFor both GtACR1 and OPN3, rearing flies on ATR-supplemented food enhances inhibition efficacy and improves developmental viability. C_LI

Valproic acid (VPA) is a widely used antiepileptic drug that also increases the risk of neurodevelopmental disorders in the offspring of exposed mothers. Prenatal exposure to VPA is a widely used rodent model of autism spectrum disorder (ASD). Anatomical, functional and molecular alterations in the retinas of various ASD model animals have been described in the literature, but the impact on the neural composition of the retina remains unclear. We examined whether and how the density and spatial regularity of selected retinal neurons are altered in the VPA induced model of ASD. Whole-mount retinas of 2-month-old VPA-treated and control animals were immunolabeled for S-cones, horizontal cells, AII amacrine cells, and parvalbumin-positive wide-field amacrines (PV-wfACs), and the positions of labelled cells mapped in various regions of interest (n = 39 for treated, n = 32 for control animals) across the retinas. Multivariate analysis of variance revealed a significant overall effect of VPA on cell densities (p = 6.1x10-7, 2 = 0.43), driven mainly by reduced AII amacrine density, while horizontal cells showed a modest reduction and S-cones were unaffected. After adjusting for retinal location, analysis of covariance indicated a 7% decrease in AII cells and a 15% increase in PV-wfACs. Regularity indices calculated from nearest neighbor distances or Voronoi-domain areas of cell mosaics were largely unchanged. These findings suggest that prenatal VPA exposure selectively alters inhibitory inner retinal circuitry in the rat ASD model at the time of cell differentiation, but self-organizing mechanisms responsible for spatial order are not affected. Lay SummaryValproic acid (VPA) is a medicine for epilepsy, but it can also raise the risk of autism in children when taken during pregnancy. In rats exposed to VPA before birth, we found changes in certain nerve cells of the retina: one type of cell important for night vision was reduced, while another type increased slightly, while most other cells stayed the same. This suggests that the changes in development that lead to autism may also be reflected in the structure and function of the eye.

Understanding neural correlates of brain function in neuroscience now largely involves detecting and analyzing transient signals from fluorescent sensors. Imaging technologies such as confocal and two-photon microscopy, along with onboard miniscopes, enable the visualization of neural activities and capture dynamic signals both ex vivo and in vivo. This includes monitoring Ca2+ transients via the expression of genetically encoded sensors such as GCaMP in specific brain cells. Additionally, the advent of GPCR-based neurotransmitter sensors allows for imaging the release of neurotransmitters including glutamate and GABA, as well as neuromodulators such as dopamine or noradrenaline. These approaches however generate large, high-dimensional, spatiotemporally complex datasets, presenting significant challenges for signal detection and analysis. To overcome these challenges, we developed a versatile pipeline of Dynamic Extraction and Tracking of Emitted Cellular Transients (DETECT), which combines background denoising, object segmentation, and multi-object tracking. Our user-friendly, Python-based GUI offers a low-resource platform for efficient data analysis. Validated across various imaging modalities and biological models, DETECT provides a robust and comprehensive solution for analyzing complex imaging datasets in neuroscience research.

Two-photon imaging with genetically encoded sensors is widely used to monitor neurophysiology. An additional fluorescent protein can provide anatomical landmarks for cell-type identification and motion detection. However, most red fluorescent proteins require a dedicated excitation laser. We made transgenic Drosophila with a long-Stokes-shift mScarlet variant (LSSmScarlet3) to image alongside green sensors with a single 920-nm laser. We describe excitation and emission spectra of the expressed protein and show that 920 nm elicits robust in vitro and in vivo fluorescence. Channel crosstalk is minimal. This approach can reduce equipment complexity and cost while placing functional calcium dynamics in their anatomical context.

Wide-field imaging (WFI) is a mesoscopic approach for monitoring cortex-wide activity with high temporal resolution and a broad field of view. Owing to its simple optical configuration and compatibility with chronic preparations, WFI has become an important tool in systems neuroscience and disease-model research. In this chapter, we describe practical protocols for chronic transcranial WFI in mice using two complementary optical signals: genetically encoded calcium indicators (GCaMP) and endogenous flavoprotein autofluorescence. Calcium imaging provides a robust readout of neuronal population activity, whereas flavoprotein imaging reflects mitochondrial redox dynamics and cellular metabolic demand. We detail procedures for animal preparation, skull clearing, headplate implantation, macroscope assembly, synchronized sensory stimulation, triggered image acquisition, and MATLAB-based data analysis. The analysis workflow includes {Delta}F/F normalization, reference-based signal correction, and artifact reduction, followed by trial averaging, atlas registration, and region-of-interest analysis. Because imaging is performed through the intact skull, the protocol enables repeated longitudinal measurements in the same animal over extended periods. This approach is reproducible, cost-effective, and adaptable to studies of cortical physiology and neurological disorders.

BackgroundThe brainstem and its different sub-systems control essential functions such as motor agility etc. that worsen with age. The purpose of this study was: 1. To assess the impact of age-related volume loss within three brainstem sub-systems on functions supported by them. 2. To use data-driven machine learning to identify different volume loss patterns or subtypes and investigate how they are associated with function. MethodsStructural MRI and behavioral data from 674 Human Connectome Project Aging (HCA) participants was used in this project. The brainstem was extracted, internal brainstem structures segmented and the segmentations warped onto a probabilistic population atlas on which the nuclei of interest had been labeled. Jacobian deformation maps were calculated, each rois mean Jacobians extracted and converted into z-scores with and without correction for age. Linear regression analyses were used to assess volume - function (cognition, motor agility, autonomic control) associations for each roi belonging to the sub-system supporting these functions. Subtype and Stage Inference (SuStaIn) was used to identify different volume loss patterns in each sub-system. ResultsAge explained larger percentage of the variation of the behavioral variables than brainstem volumes. SuStaIn identified up to 4 subtypes, one representing typical aging and the remainder atypical aging. The subtypes did not significantly differ behaviorally with the exception of grip strength and diastolic blood pressure. ConclusionAging affects brainstem systems which contributes to the worsening of these functions with increasing age. SuStaIn detected different patterns of volume loss or subtypes within each of the brainstem systems.

Aquatic vertebrates are increasingly used in neuroscience research, yet underwater visual stimulation remains a challenge. Commonly used monochromatic stimuli have been shown to be inadequate to activate many visual neurons properly, and underwater refraction artifacts are prone to ruin stimulus designs. Here, we present MARINER - a visual stimulator, which remedies these issues and integrates concurrent behavioral and neurophysiological two-photon calcium imaging recordings. MARINERs full-field visual stimulation combined with receptive field mapping reveals that the visual field of larval zebrafish is larger than previously thought, extending almost down below the fish, and is spatially biased to better utilize motion content in naturalistic visual scenes. Using chromatic motion nulling, we further show that behavioral responses and task-associated sensory neurons are colorblind for "red" and "green" during the larvas optokinetic response. The MARINER stimulator facilitates naturalistic stimulation and faithful presentation of colored visual underwater stimuli for small aquatic species.

BackgroundThe continuous rise in life expectancy introduces a central challenge of new longevity, ensuring that the additional years gained are accompanied by the preservation of cognitive function and quality. MethodsWe propose a modeling framework for multi-domain brain age derived from a repertoire of digital cognitive metrics. The model, based on Ridge regression with Leave-One-Out cross-validation, was trained in a cohort of 394 healthy controls (HC; 307 women and 87 men; mean age 30.0 {+/-} 12.5 years; range 17-64). ResultsThe model achieved a correlation between chronological age and predicted age of r = 0.942 with a mean absolute error of 3.05 years. When applied to three additional clinical cohorts, multiple sclerosis (N = 70), traumatic brain injury (N = 23), and depression (N = 18), the model detected significant accelerated cognitive aging across all conditions, with processing speed emerging as the dominant contributor to accelerated aging, albeit with varying degrees of concentration across pathologies. ConclusionsDigital cognitive metrics provide an accessible, non-invasive, and scalable biomarker for tracking brain aging, with strong potential for informing personalized neuropsychological interventions and for integration into active aging frameworks within the context of modern longevity.

Myelin is a highly complex membranous structure wrapped around axons by oligodendrocytes or Schwann cells in the central and peripheral nervous system, respectively. Fluorescent labeling is widely used to study the structure and dynamics of myelin. Combining structural with functional imaging requires labeling of myelin with red fluorescence, as many functional sensors, including Ca2+ indicators and genetically encoded metabolite sensors, fluoresce in the green spectral range. However, in vivo tools enabling red fluorescent labeling of myelinating cells and their myelin sheaths remain limited. Here, we generated a set of seven transgenic mouse lines expressing a membrane-targeted variant of the red fluorescent protein tdTomato in myelinating oligodendrocytes and Schwann cells throughout the nervous system. The mouse lines provide a variety of expression patterns ranging from wide-spread labeling of myelin to a rather sparse expression, the latter enabling visualization of individual oligodendrocytes and their associated myelin sheaths. In the peripheral nervous system, the pattern of fluorescence in sciatic nerves indicates predominant localization of tdTomato to non-compact myelin compartments including the inner and outer tongues, paranodal loops and Schmidt-Lanterman incisures. In summary, our work provides a set of novel mouse lines with myelin labeled by red fluorescence, which are compatible with diverse imaging modalities in the green spectral range enabling integrated structural and functional imaging. Main PointsO_LITransgenic mouse lines expressing membrane-targeted tdTomato in myelin enable imaging of myelin in the red spectral range C_LIO_LIDistinct expression patterns range from wide-spread labeling to sparse single-cell resolution, supporting diverse imaging applications C_LI

Animals sleep more when they are sick. In C. elegans, stress-induced sleep (SIS) follows cellular injury such as exposure to ultraviolet (UV) light. The genetic regulators of SIS remain incompletely defined. Using a worm-picking robot, multi-well WorMotel imaging, and association analysis we performed a semi-automated screen of 941 whole-genome-sequenced Million Mutation Project (MMP) strains. We quantified behavioral activity and quiescence before and after ultraviolet (UV) radiation. We applied the Sequence Kernel Association Test (SKAT) to this behavioral data to prioritize 6,663 genes and observed significant enrichment of known SIS genetic regulators. Based on these results, we conducted a candidate validation screen for additional genes regulating SIS. We identified three genes (strd-1, egl-8, cla-1), mutations in which reproducibly influence SIS. Further exploration of these genes holds potential for enhancing our understanding of the molecular basis of SIS. These findings establish a pipeline for automated behavioral phenotyping coupled with gene-based association to accelerate studies of C. elegans neurogenetics.

Quantifying blood-brain barrier (BBB) integrity from fluorescence microscopy remains limited by subjective scoring and categorical classification methods that lack reproducibility. For objective and consistent BBB phenotyping, we present two semi-automated image-analysis pipelines that replace manual scoring with quantitative, continuous-variable measurements. Our in vitro pipeline, implemented in Python, quantifies the connectivity of tight junction structures by measuring discrete ZO-1 fragment objects within manually traced junction regions. It outputs continuous metrics including average fragment area, total junctional area, and a junctional fragmentation ratio that captures degree of ZO-1 continuity versus discontinuity. In human brain microvascular endothelial cells subjected to glycocalyx component knockdown, the pipeline detected significantly reduced fragment area (37% decrease for both CD44 and syndecan-1 (SDC1) knockdown, p = 0.0148 and 0.0084) and junctional fragmentation ratio (p = 0.0061 and 0.0137). Our in vivo pipeline integrates ilastik-based pixel classification with FIJI macro automation to quantify vascular marker colocalization and to separate vessel signal from microglial contamination within a single fluorescence channel, eliminating the need for dedicated counterstains. Applied across four mouse cohorts [young, aged, Alzheimer's, traumatic brain injury (TBI)] and three brain regions [prefrontal cortex (PFC), hippocampus, midbrain], the pipeline revealed concurrent ZO-1 loss and ICAM-1 elevation in the PFC and hippocampus of aged and Alzheimer's mice, with Alzheimer's-specific doubling of eNOS occurring in the PFC (p = 0.0013). TBI mice showed persistent ZO-1 loss with transient ICAM-1 and eNOS changes. Both deterministic pipelines are available on GitHub and designed for adoption beyond the specific markers and systems analyzed here.

Octopamine is involved in a variety of different physiological and behavioral mecha-nisms in Drosophila melanogaster. Throughout the life cycle of the fruit fly, from the larva to the adult, octopaminergic neurons in both the central and the peripheral nerv-ous system target a multitude of neurons and even non-neuronal tissues, making it challenging to analyze individual mechanisms of octopamine function. One approach to deconstructing this complex system is to examine the postsynaptic components of signal transmission. In Drosophila, octopamine interacts with six distinct G-protein-coupled receptors. For some of these receptors, expression maps and functional im-plications have been described. In contrast, other receptors have been neglected, partly due to the lack of suitable genetic tools. Here, for the first time, we compiled a complete set of mutant lines of all known octopamine receptors, all generated using the same genetic tool, the recently established Trojan Exon system. It integrates the Gal4/UAS binary expression strategy while simultaneously impairing receptor func-tion. This enabled us to generate a comprehensive anatomical map of receptor ex-pression in the larva and, at the same time, analyze the function of individual octopa-mine receptors during larval development, chemosensory perception and locomotion. All octopamine receptors (Oamb, Oct2R, Oct{beta}1R, Oct{beta}2R, Oct{beta}3R, and Oct-TyrR) showed extensive signal in the central nervous system. The same was found for the peripheral nervous system, with the exception of Oct{beta}2R, which showed pronounced expression in the somatic muscles. We also observed a previously undescribed role of Oct{beta}1R, Oct{beta}3R, and Oct-TyrR in larval hatching and in the survival of larvae and pupae. Molecular evaluation of the Trojan Exon octopamine lines supports our analy-sis. In addition, we combined the experimental results with gene expression data from the different development stages of Drosophila melanogaster and from different tis-sues and cell populations throughout the body. Overall, we compiled, analyzed and validated a complete set of octopamine lines which, together with gene expression analysis, provides a basis for further functional studies on the larval octopaminergic system.

Sleep abnormalities and dysfunction of gamma band (30-80 Hz) activity generated by parvalbumin (PV) interneurons are early characteristics of Alzheimers disease (AD) which correlate with the severity of amyloid-{beta} deposition (A{beta}) and cognitive impairment. However, the timing of these alterations in vivo with respect to disease progression is unclear. Here, in longitudinal recordings from APP/PS1/PV-cre (AD mice) from 3-6 months, we found reduced sleep slow-wave power (0.5-4 Hz) in hippocampus and medial prefrontal cortex in AD mice as young as 3 months old, compared to non-AD (PV-cre) mice, well before overt pathology. This finding was primarily due to reductions in the NREM delta range (1.5-4 Hz), a hallmark of restorative functions of sleep. In contrast, beta (15-30 Hz) power linked to insomnia was significantly higher across all sleep-wake states. Loss of deep NREM sleep was not compensated by an increase in NREM sleep time, instead NREM sleep during the dark (active) phase was slightly but significantly lower in AD mice. 40-Hz auditory steady-state responses and associated evoked calcium responses of hippocampal PV neurons recorded using fiber photometry were also impaired by 3 months old. However, Y-maze performance in 3- and 6-month-old AD mice was not significantly different from non-AD mice. These results reveal reduced deep sleep and PV-associated 40-Hz activity as very early changes amenable to early intervention occurring prior to cognitive deficits. Furthermore, they establish APP/PS1 mice as a good model to causally test the relationship between sleep, PV neuronal activity and amyloid-mediated pathology.

Cellular stress responses are often characterized as conserved, cell-autonomous processes. However, it remains unclear whether stress responses are coordinated uniformly across tissues within complex organisms, particularly during ecologically relevant conditions. We investigated tissue- and stage-specific transcriptional responses to cold stress in Drosophila melanogaster. Adults and larvae were independently exposed to a gradual cooling and recovery time series, and three adult tissues (gut, ovary, brain) and one larval tissue (gut) were sampled at baseline, at two time points that spanned the critical thermal minimum (before and during chill coma), and after recovery to rearing temperature. Transcriptomic analyses revealed strongly tissue- and stage-specific responses to cold stress, with limited overlap in differentially expressed genes or functional enrichment across tissues. These results indicate that the organismal response to thermal stress at the transcriptional level is not coordinated by a unified transcriptional program, but rather by largely distinct, tissue-specific regulatory processes.

Investigating neural circuit dynamics across distributed brain regions in awake, behaving animals is crucial for understanding complex behavior. Genetically encoded voltage indicators (GEVIs) offer a powerful approach to tracking transmembrane voltage with high temporal and cellular specificity. However, scaling high-sensitivity GEVI recordings across multiple brain regions and multiple animals simultaneously remains a major technical challenge. Furthermore, it is unclear whether soma-targeted GEVIs - typically used for single-cell resolution imaging - can be effectively adapted for fiber photometry. Here, we show that a sCMOS-based widefield imaging system achieves sensitive dual-color multi-site fiber photometry using soma-targeted GEVI indicators with high temporal resolution. We validated this approach in the mouse hippocampal CA1, capturing theta (3-10Hz) and gamma (30-80Hz) rhythms and theta-gamma cross-frequency coupling. Additionally, we recorded high-frequency neural entrainment (>100 Hz) and somatic depolarization induced by electrical stimulation in CA1. Lastly, we tracked synchronized neural activity between the bilateral CA1s as well as multi-site dual-color imaging across CA1 and cortex simultaneously in three freely running mice. This work provides a scalable, accessible platform for high-speed optical electrophysiology in distributed neural circuits. Key points- Implementation of a sCMOS-based widefield imaging setup for sensitive and scalable fiber photometry and cellular imaging. - Demonstration of population multi-site and inter-animal voltage imaging with soma-targeted genetically encoded voltage indicators. - Tracking of high-frequency gamma and high-gamma (>100Hz) neural entrainment