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Usher syndrome, the most prevalent cause of combined hereditary vision and hearing impairment, is clinically and genetically heterogeneous. Moreover, several conditions with phenotypes overlapping Usher syndrome have been described. This makes the molecular diagnosis of hereditary deaf-blindness challenging. Here, we performed exome sequencing and analysis on 7 Mexican and 52 Iranian probands with combined retinal degeneration and hearing impairment (without intellectual disability). Clinical assessment involved ophthalmological examination and hearing loss questionnaire. Usher syndrome, most frequently due to biallelic variants in MYO7A (USH1B in 16 probands), USH2A (17 probands), and ADGRV1 (USH2C in 7 probands), was diagnosed in 44 of 59 (75%) unrelated probands. Almost half of the identified variants were novel. Nine of 59 (15%) probands displayed other genetic entities with dual sensory impairment, including Alström syndrome (3 patients), cone-rod dystrophy and hearing loss 1 (2 probands), and Heimler syndrome (1 patient). Unexpected findings included one proband each with Scheie syndrome, coenzyme Q10 deficiency, and pseudoxanthoma elasticum. In four probands, including three Usher cases, dual sensory impairment was either modified/aggravated or caused by variants in distinct genes associated with retinal degeneration and/or hearing loss. The overall diagnostic yield of whole exome analysis in our deaf-blind cohort was 92%. Two (3%) probands were partially solved and only 3 (5%) remained without any molecular diagnosis. In many cases, the molecular diagnosis is important to guide genetic counseling, to support prognostic outcomes and decisions with currently available and evolving treatment modalities.
Ultrastructural analysis of wild-type and RIM1α knockout active zones in a large cortical synapse
(2022)
Rab3A-interacting molecule (RIM) is crucial for fast Ca\(^{2+}\)-triggered synaptic vesicle (SV) release in presynaptic active zones (AZs). We investigated hippocampal giant mossy fiber bouton (MFB) AZ architecture in 3D using electron tomography of rapid cryo-immobilized acute brain slices in RIM1α\(^{−/−}\) and wild-type mice. In RIM1α\(^{−/−}\), AZs are larger with increased synaptic cleft widths and a 3-fold reduced number of tightly docked SVs (0–2 nm). The distance of tightly docked SVs to the AZ center is increased from 110 to 195 nm, and the width of their electron-dense material between outer SV membrane and AZ membrane is reduced. Furthermore, the SV pool in RIM1α\(^{−/−}\) is more heterogeneous. Thus, RIM1α, besides its role in tight SV docking, is crucial for synaptic architecture and vesicle pool organization in MFBs.
Targeting the intrinsic metabolism of immune or tumor cells is a therapeutic strategy in autoimmunity, chronic inflammation or cancer. Metabolite repair enzymes may represent an alternative target class for selective metabolic inhibition, but pharmacological tools to test this concept are needed. Here, we demonstrate that phosphoglycolate phosphatase (PGP), a prototypical metabolite repair enzyme in glycolysis, is a pharmacologically actionable target. Using a combination of small molecule screening, protein crystallography, molecular dynamics simulations and NMR metabolomics, we discover and analyze a compound (CP1) that inhibits PGP with high selectivity and submicromolar potency. CP1 locks the phosphatase in a catalytically inactive conformation, dampens glycolytic flux, and phenocopies effects of cellular PGP-deficiency. This study provides key insights into effective and precise PGP targeting, at the same time validating an allosteric approach to control glycolysis that could advance discoveries of innovative therapeutic candidates.
In times of environmental change species have two options to survive: they either relocate to a new habitat or they adapt to the altered environment. Adaptation requires physiological plasticity and provides a selection benefit. In this regard, the Western honeybee (Apis mellifera) protrudes with its thermoregulatory capabilities, which enables a nearly worldwide distribution. Especially in the cold, shivering thermogenesis enables foraging as well as proper brood development and thus survival. In this study, we present octopamine signaling as a neurochemical prerequisite for honeybee thermogenesis: we were able to induce hypothermia by depleting octopamine in the flight muscles. Additionally, we could restore the ability to increase body temperature by administering octopamine. Thus, we conclude that octopamine signaling in the flight muscles is necessary for thermogenesis. Moreover, we show that these effects are mediated by β octopamine receptors. The significance of our results is highlighted by the fact the respective receptor genes underlie enormous selective pressure due to adaptation to cold climates. Finally, octopamine signaling in the service of thermogenesis might be a key strategy to survive in a changing environment.
Drosophila’s lateral posterior neurons (LPNs) belong to a small group of circadian clock neurons that is so far not characterized in detail. Thanks to a new highly specific split‐Gal4 line, here we describe LPNs’ morphology in fine detail, their synaptic connections, daily bimodal expression of neuropeptides, and propose a putative role of this cluster in controlling daily activity and sleep patterns. We found that the three LPNs are heterogeneous. Two of the neurons with similar morphology arborize in the superior medial and lateral protocerebrum and most likely promote sleep. One unique, possibly wakefulness‐promoting, neuron with wider arborizations extends from the superior lateral protocerebrum toward the anterior optic tubercle. Both LPN types exhibit manifold connections with the other circadian clock neurons, especially with those that control the flies’ morning and evening activity (M‐ and E‐neurons, respectively). In addition, they form synaptic connections with neurons of the mushroom bodies, the fan‐shaped body, and with many additional still unidentified neurons. We found that both LPN types rhythmically express three neuropeptides, Allostatin A, Allostatin C, and Diuretic Hormone 31 with maxima in the morning and the evening. The three LPN neuropeptides may, furthermore, signal to the insect hormonal center in the pars intercerebralis and contribute to rhythmic modulation of metabolism, feeding, and reproduction. We discuss our findings in the light of anatomical details gained by the recently published hemibrain of a single female fly on the electron microscopic level and of previous functional studies concerning the LPN.
The exponential increase in the human population in tandem with increased food demand has caused agriculture to be the global‐dominant form of land use. Afrotropical drylands are currently facing the loss of natural savannah habitats and agricultural intensification with largely unknown consequences for bees. Here we investigate the effects of agricultural intensification on bee assemblages in the Afrotropical drylands of northern Tanzania. We disentangled the direct effects of agricultural intensification and temperature on bee richness from indirect effects mediated by changes in floral resources.
We collected data from 24 study sites representing three levels of management intensity (natural savannah, moderate intensive and highly intensive agriculture) spanning an extensive gradient of mean annual temperature (MAT) in northern Tanzania. We used ordinary linear models and path analysis to test the effects of agricultural intensity and MAT on bee species richness, bee species composition and body‐size variation of bee communities.
We found that bee species richness increased with agricultural intensity and with increasing temperature. The effects of agricultural intensity and temperature on bee species richness were mediated by the positive effects of agriculture and temperature on the richness of floral resources used by bees. During the off‐growing season, agricultural land was characterized by an extensive period of fallow land holding a very high density of flowering plants with unique bee species composition. The increase in bee diversity in agricultural habitats paralleled an increasing variation of bee body sizes with agricultural intensification that, however, diminished in environments with higher temperatures.
Synthesis and applications. Our study reveals that bee assemblages in Afrotropical drylands benefit from agricultural intensification in the way it is currently practiced. However, further land‐use intensification, including year‐round irrigated crop monocultures and excessive use of agrochemicals, is likely to exert a negative impact on bee diversity and pollination services, as reported in temperate regions. Moreover, several bee species were restricted to natural savannah habitats. To conserve bee communities and guarantee pollination services in the region, a mixture of savannah and agriculture, with long periods of fallow land should be maintained.
Environmental gradients generate and maintain biodiversity on Earth. Mountain slopes are among the most pronounced terrestrial environmental gradients, and the elevational structure of species and their interactions can provide unique insight into the processes that govern community assembly and function in mountain ecosystems. We recorded bumble bee–flower interactions over 3 years along a 1400‐m elevational gradient in the German Alps. Using nonlinear modeling techniques, we analyzed elevational patterns at the levels of abundance, species richness, species β‐diversity, and interaction β‐diversity. Though floral richness exhibited a midelevation peak, bumble bee richness increased with elevation before leveling off at the highest sites, demonstrating the exceptional adaptation of these bees to cold temperatures and short growing seasons. In terms of abundance, though, bumble bees exhibited divergent species‐level responses to elevation, with a clear separation between species preferring low versus high elevations. Overall interaction β‐diversity was mainly caused by strong turnover in the floral community, which exhibited a well‐defined threshold of β‐diversity rate at the tree line ecotone. Interaction β‐diversity increased sharply at the upper extreme of the elevation gradient (1800–2000 m), an interval over which we also saw steep decline in floral richness and abundance. Turnover of bumble bees along the elevation gradient was modest, with the highest rate of β‐diversity occurring over the interval from low‐ to mid‐elevation sites. The contrast between the relative robustness bumble bee communities and sensitivity of plant communities to the elevational gradient in our study suggests that the strongest effects of climate change on mountain bumble bees may be indirect effects mediated by the responses of their floral hosts, though bumble bee species that specialize in high‐elevation habitats may also experience significant direct effects of warming.
The mechanisms by which climatic changes influence ecosystem functions, that is, by a direct climatic control of ecosystem processes or by modifying richness and trait compositions of species communities, remain unresolved.
This study is a contribution to this discourse by elucidating the linkages between climate, land use, biodiversity, body size and ecosystem functions.
We disentangled direct climatic from biodiversity‐mediated effects by using dung removal by dung beetles as a model system and by combining correlative field data and exclosure experiments along an extensive elevational gradient on Mt. Kilimanjaro, Tanzania.
Dung removal declined with increasing elevation, being associated with a strong reduction in the richness and body size traits of dung beetle communities. Climate influenced dung removal rates by modifying biodiversity rather than by direct effects. The biodiversity–ecosystem effect was driven by a change in the mean body size of dung beetles. Dung removal rates were strongly reduced when large dung beetles were experimentally excluded.
This study underscores that climate influences ecosystem functions mainly by modifying biodiversity and underpins the important role of body size for dung removal.
Arthropod dark taxa provide new insights into diversity responses to bark beetle infestations
(2022)
Natural disturbances are increasing around the globe, also impacting protected areas. Although previous studies have indicated that natural disturbances result in mainly positive effects on biodiversity, these analyses mostly focused on a few well established taxonomic groups, and thus uncertainty remains regarding the comprehensive impact of natural disturbances on biodiversity. Using Malaise traps and meta‐barcoding, we studied a broad range of arthropod taxa, including dark and cryptic taxa, along a gradient of bark beetle disturbance severities in five European national parks. We identified order‐level community thresholds of disturbance severity and classified barcode index numbers (BINs; a cluster system for DNA sequences, where each cluster corresponds to a species) as negative or positive disturbance indicators. Negative indicator BINs decreased above thresholds of low to medium disturbance severity (20%–30% of trees killed), whereas positive indicator BINs benefited from high disturbance severity (76%–98%). BINs allocated to a species name contained nearly as many positive as negative disturbance indicators, but dark and cryptic taxa, particularly Diptera and Hymenoptera in our data, contained higher numbers of negative disturbance indicator BINs. Analyses of changes in the richness of BINs showed variable responses of arthropods to disturbance severity at lower taxonomic levels, whereas no significant signal was detected at the order level due to the compensatory responses of the underlying taxa. We conclude that the analyses of dark taxa can offer new insights into biodiversity responses to disturbances. Our results suggest considerable potential for forest management to foster arthropod diversity, for example by maintaining both closed‐canopy forests (>70% cover) and open forests (<30% cover) on the landscape.
Recent reports on insect decline have highlighted the need for long‐term data on insect communities towards identifying their trends and drivers.
With the launch of many new insect monitoring schemes to investigate insect communities over large spatial and temporal scales, Malaise traps have become one of the most important tools due to the broad spectrum of species collected and reduced capture bias through passive sampling of insects day and night. However, Malaise traps can vary in size, shape, and colour, and it is unknown how these differences affect biomass, species richness, and composition of trap catch, making it difficult to compare results between studies.
We compared five Malaise trap types (three variations of the Townes and two variations of the Bartak Malaise trap) to determine their effects on biomass and species richness as identified by metabarcoding.
Insect biomass varied by 20%–55%, not strictly following trap size but varying with trap type. Total species richness was 20%–38% higher in the three Townes trap models compared to the Bartak traps. Bartak traps captured lower richness of highly mobile taxa but increased richness of ground‐dwelling taxa. The white roofed Townes trap captured a higher richness of pollinators.
We find that biomass, total richness, and taxa group specific richness are all sensitive to Malaise trap type. Trap type should be carefully considered and aligned to match monitoring and research questions. Additionally, our estimates of trap type effects can be used to adjust results to facilitate comparisons across studies.
Abiotic factors are generally assumed to determine whether species can exist at the extreme ends of environmental gradients, for example, at high elevations, whereas the role of biotic interactions is less clear. On temperate mountains, insect‐pollinated plant species with bilaterally symmetrical flowers exhibit a parallel elevational decline in species richness and abundance with bees. This suggests that the lack of mutualistic interaction partners sets the elevational range limits of plants via a reduction in reproductive success. We used the bee‐pollinated mountain plant Clinopodium alpinum (Lamiaceae), which blooms along a continuous 1000‐m elevational gradient and has bilaterally symmetrical flowers, as a model to test the predicted parallel elevational decline in flower visitation and seed production. Although the community of flower visitors changed with elevation, the flower visitation rate by the most frequent visitors, bumble bees (33.8% of legitimate visits), and the overall rate of flower visitation by potential pollinators did not vary significantly with elevation. However, we discovered that nectar robbing by bumble bees and nectar theft by ants, two interactions with potentially negative effects on flowers, sharply increased with elevation. Seed set depended on pollinators across elevations and followed a weak hump‐shaped pattern, peaking at mid‐elevations and decreasing by about 20% toward both elevational range edges. Considering the mid‐ and high elevations, elevational variation in seed production could not be explained by legitimate bee visitation rates but was inversely correlated with the frequency of nectar robbing. Our observations challenge the hypothesis that a decrease in the availability of pollinators limits seed production of bee‐flowered plants at high elevations but suggest that an increase in negative interactions (nectar robbing and larceny) constrains reproductive success.
Green plants are equipped with photoreceptors that are capable of sensing radiation in the ultraviolet‐to‐blue and the red‐to‐far‐red parts of the light spectrum. However, plant cells are not particularly sensitive to green light (GL), and light which lies within this part of the spectrum does not efficiently trigger the opening of stomatal pores. Here, we discuss the current knowledge of stomatal responses to light, which are either provoked via photosynthetically active radiation or by specific blue light (BL) signaling pathways. The limited impact of GL on stomatal movements provides a unique option to use this light quality to control optogenetic tools. Recently, several of these tools have been optimized for use in plant biological research, either to control gene expression, or to provoke ion fluxes. Initial studies with the BL‐activated potassium channel BLINK1 showed that this tool can speed up stomatal movements. Moreover, the GL‐sensitive anion channel GtACR1 can induce stomatal closure, even at conditions that provoke stomatal opening in wild‐type plants. Given that crop plants in controlled‐environment agriculture and horticulture are often cultivated with artificial light sources (i.e. a combination of blue and red light from light‐emitting diodes), GL signals can be used as a remote‐control signal that controls stomatal transpiration and water consumption.
Purpose
Image acquisition and subsequent manual analysis of cardiac cine MRI is time-consuming. The purpose of this study was to train and evaluate a 3D artificial neural network for semantic segmentation of radially undersampled cardiac MRI to accelerate both scan time and postprocessing.
Methods
A database of Cartesian short-axis MR images of the heart (148,500 images, 484 examinations) was assembled from an openly accessible database and radial undersampling was simulated. A 3D U-Net architecture was pretrained for segmentation of undersampled spatiotemporal cine MRI. Transfer learning was then performed using samples from a second database, comprising 108 non-Cartesian radial cine series of the midventricular myocardium to optimize the performance for authentic data. The performance was evaluated for different levels of undersampling by the Dice similarity coefficient (DSC) with respect to reference labels, as well as by deriving ventricular volumes and myocardial masses.
Results
Without transfer learning, the pretrained model performed moderately on true radial data [maximum number of projections tested, P = 196; DSC = 0.87 (left ventricle), DSC = 0.76 (myocardium), and DSC =0.64 (right ventricle)]. After transfer learning with authentic data, the predictions achieved human level even for high undersampling rates (P = 33, DSC = 0.95, 0.87, and 0.93) without significant difference compared with segmentations derived from fully sampled data.
Conclusion
A 3D U-Net architecture can be used for semantic segmentation of radially undersampled cine acquisitions, achieving a performance comparable with human experts in fully sampled data. This approach can jointly accelerate time-consuming cine image acquisition and cumbersome manual image analysis.
At the beginning of their foraging careers, Cataglyphis desert ants calibrate their compass systems and learn the visual panorama surrounding the nest entrance. For that, they perform well-structured initial learning walks. During rotational body movements (pirouettes), naïve ants (novices) gaze back to the nest entrance to memorize their way back to the nest. To align their gaze directions, they rely on the geomagnetic field as a compass cue. In contrast, experienced ants (foragers) use celestial compass cues for path integration during food search. If the panorama at the nest entrance is changed, foragers perform re-learning walks prior to heading out on new foraging excursions. Here, we show that initial learning walks and re-learning walks are structurally different. During re-learning walks, foragers circle around the nest entrance before leaving the nest area to search for food. During pirouettes, they do not gaze back to the nest entrance. In addition, foragers do not use the magnetic field as a compass cue to align their gaze directions during re-learning walk pirouettes. Nevertheless, magnetic alterations during re-learning walks under manipulated panoramic conditions induce changes in nest-directed views indicating that foragers are still magnetosensitive in a cue conflict situation.
The negative impact of juvenile undernourishment on adult behavior has been well reported for vertebrates, but relatively little is known about invertebrates. In honeybees, nutrition has long been known to affect task performance and timing of behavioral transitions. Whether and how a dietary restriction during larval development affects the task performance of adult honeybees is largely unknown. We raised honeybees in-vitro, varying the amount of a standardized diet (150 µl, 160 µl, 180 µl in total). Emerging adults were marked and inserted into established colonies. Behavioral performance of nurse bees and foragers was investigated and physiological factors known to be involved in the regulation of social organization were quantified. Surprisingly, adult honeybees raised under different feeding regimes did not differ in any of the behaviors observed. No differences were observed in physiological parameters apart from weight. Honeybees were lighter when undernourished (150 µl), while they were heavier under the overfed treatment (180 µl) compared to the control group raised under a normal diet (160 µl). These data suggest that dietary restrictions during larval development do not affect task performance or physiology in this social insect despite producing clear effects on adult weight. We speculate that possible effects of larval undernourishment might be compensated during the early period of adult life.
Squamous cell carcinomas (SCC) frequently have an exceptionally high mutational burden. As consequence, they rapidly develop resistance to platinum-based chemotherapy and overall survival is limited. Novel therapeutic strategies are therefore urgently required. SCC express ∆Np63, which regulates the Fanconi Anemia (FA) DNA-damage response in cancer cells, thereby contributing to chemotherapy-resistance. Here we report that the deubiquitylase USP28 is recruited to sites of DNA damage in cisplatin-treated cells. ATR phosphorylates USP28 and increases its enzymatic activity. This phosphorylation event is required to positively regulate the DNA damage repair in SCC by stabilizing ∆Np63. Knock-down or inhibition of USP28 by a specific inhibitor weakens the ability of SCC to cope with DNA damage during platin-based chemotherapy. Hence, our study presents a novel mechanism by which ∆Np63 expressing SCC can be targeted to overcome chemotherapy resistance. Limited treatment options and low response rates to chemotherapy are particularly common in patients with squamous cancer. The SCC specific transcription factor ∆Np63 enhances the expression of Fanconi Anemia genes, thereby contributing to recombinational DNA repair and Cisplatin resistance. Targeting the USP28-∆Np63 axis in SCC tones down this DNA damage response pathways, thereby sensitizing SCC cells to cisplatin treatment.
Cuticular hydrocarbons (CHC) are known to serve as discrimination cues and will trigger defence behaviour in a plethora of eusocial insects. However, little is known how about nestmate recognition ability selects for CHC diversification. In this study we investigate differences in CHC composition of four major honey bee species with respect to the differences in their nesting behavior. In contrast to A. mellifera, A. cerana and A. florea, the giant honey bee A. dorsata prefers to build their nests in aggregations with very small spatial distances between nests, which increases the probability of intrusions. Thus, A. dorsata exhibits a particularly challenging nesting behavior which we hypothesize should be accompanied with an improved nestmate recognition system. Comparative analyses of the worker CHC profiles indicate that A. dorsata workers exhibit a unique and more complex CHC profile than the other three honey bee species. This increased complexity is likely based on a developmental process that retains the capability to synthesize methyl-branched hydrocarbons as adults. Furthermore, two sets of behavioral experiments provide evidence that A. dorsata shows an improved nestmate discrimination ability compared to the phylogenetically ancestral A. florea, which is also open-nesting but does not form nest aggregations. The results of our study suggest that ecological traits like nesting in aggregation might be able to drive CHC profile diversification even in closely related insect species.
Background
Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method.
Results
Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality.
Conclusions
Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.
Robotic-assisted colon surgery may contain advantages over the laparoscopic approach, but clear evidence is sparse. This study aimed to analyze postoperative inflammation status, short-term outcome and cost-effectiveness of robotic-assisted versus laparoscopic left hemicolectomy. All consecutive patients who received minimal-invasive left hemicolectomy at the Department of Surgery I at the University Hospital of Wuerzburg in 2021 were prospectively included. Importantly, no patient selection for either procedure was carried out. The robotic-assisted versus laparoscopic approaches were compared head to head for postoperative short-term outcomes as well as cost-effectiveness. A total of 61 patients were included, with 26 patients having received a robotic-assisted approach. Baseline characteristics did not differ among the groups. Patients receiving a robotic-assisted approach had a significantly decreased length of hospital stay as well as lower rates of complications in comparison to patients who received laparoscopic surgery (n = 35). In addition, C-reactive protein as a marker of systemic stress response was significantly reduced postoperatively in patients who were operated on in a robotic-assisted manner. Consequently, robotic-assisted surgery could be performed in a cost-effective manner. Thus, robotic-assisted left hemicolectomy represents a safe and cost-effective procedure and might improve patient outcomes in comparison to laparoscopic surgery.
Introduction
Neurotransmitter release at presynaptic active zones (AZs) requires concerted protein interactions within a dense 3D nano-hemisphere. Among the complex protein meshwork the (M)unc-13 family member Unc-13 of Drosophila melanogaster is essential for docking of synaptic vesicles and transmitter release.
Methods
We employ minos-mediated integration cassette (MiMIC)-based gene editing using GFSTF (EGFP-FlAsH-StrepII-TEV-3xFlag) to endogenously tag all annotated Drosophila Unc-13 isoforms enabling visualization of endogenous Unc-13 expression within the central and peripheral nervous system.
Results and discussion
Electrophysiological characterization using two-electrode voltage clamp (TEVC) reveals that evoked and spontaneous synaptic transmission remain unaffected in unc-13\(^{GFSTF}\) 3rd instar larvae and acute presynaptic homeostatic potentiation (PHP) can be induced at control levels. Furthermore, multi-color structured-illumination shows precise co-localization of Unc-13\(^{GFSTF}\), Bruchpilot, and GluRIIA-receptor subunits within the synaptic mesoscale. Localization microscopy in combination with HDBSCAN algorithms detect Unc-13\(^{GFSTF}\) subclusters that move toward the AZ center during PHP with unaltered Unc-13\(^{GFSTF}\) protein levels.