Comprehensive isoform-level analysis reveals the contribution of alternative isoforms to venom evolution and repertoire diversity.

Animal venom systems have emerged as valuable models for investigating how novel polygenic phenotypes may arise from gene evolution by varying molecular mechanisms. However, a significant portion of venom genes produce alternative mRNA isoforms that have not been extensively characterized, hindering a comprehensive understanding of venom biology. In this study, we present a full-length isoform-level profiling workflow integrating multiple RNA sequencing technologies, allowing us to reconstruct a high-resolution transcriptome landscape of venom genes in the parasitoid wasp Pteromalus puparum Our findings demonstrate that more than half of the venom genes generate multiple isoforms within the venom gland. Through mass spectrometry analysis, we confirm that alternative splicing contributes to the diversity of venom proteins, acting as a mechanism for expanding the venom repertoire. Notably, we identified seven venom genes that exhibit distinct isoform usages between the venom gland and other tissues. Furthermore, evolutionary analyses of venom serpin3 and orcokinin further reveal that the co-option of an ancient isoform and a newly evolved isoform, respectively, contributes to venom recruitment, providing valuable insights into the genetic mechanisms driving venom evolution in parasitoid wasps. Overall, our study presents a comprehensive investigation of venom genes at the isoform level, significantly advancing our understanding of alternative isoforms in venom diversity and evolution and setting the stage for further in-depth research on venoms.

A mutagenesis study of autoantigen optimization for potential T1D vaccine design.

A previously reported autoreactive antigen, termed the X-idiotype, isolated from a unique cell population in Type 1 diabetes (T1D) patients, was found to stimulate their CD4+ T cells. This antigen was previously determined to bind more favorably than insulin and its mimic (insulin superagonist) to HLA-DQ8, supporting its strong role in CD4+ T cell activation. In this work, we probed HLA-X-idiotype-TCR binding and designed enhanced-reactive pHLA-TCR antigens using an in silico mutagenesis approach which we functionally validated by cell proliferation assays and flow cytometry. From a combination of single, double, and swap mutations, we identified antigen-binding sites p4 and p6 as potential mutation sites for HLA binding affinity enhancement. Site p6 is revealed to favor smaller but more hydrophobic residues than the native tyrosine, such as valine (Y6V) and isoleucine (Y6I), indicating a steric mechanism in binding affinity improvement. Meanwhile, site p4 methionine mutation to hydrophobic residues isoleucine (M4I) or leucine (M4L) modestly increases HLA binding affinity. Select p6 mutations to cysteine (Y6C) or isoleucine (Y6I) exhibit favorable TCR binding affinities, while a swap p5-p6 tyrosine-valine double mutant (V5Y_Y6V) and a p6-p7 glutamine-glutamine double mutant (Y6Q_Y7Q) exhibit enhanced HLA binding affinity but weakened TCR affinity. This work holds relevance to potential T1D antigen-based vaccine design and optimization.

Improved reconstruction of crossing fibers in the mouse optic pathways with orientation distribution function fingerprinting.

PURPOSE: The accuracy of diffusion MRI tractography reconstruction decreases in the white matter regions with crossing fibers. The optic pathways in rodents provide a challenging structure to test new diffusion tractography approaches because of the small crossing volume within the optic chiasm and the unbalanced 9:1 proportion between the contra- and ipsilateral neural projections from the retina to the lateral geniculate nucleus, respectively. METHODS: Common approaches based on Orientation Distribution Function (ODF) peak finding or statistical inference were compared qualitatively and quantitatively to ODF Fingerprinting (ODF-FP) for reconstruction of crossing fibers within the optic chiasm using in vivo diffusion MRI ( n = 18 $$ n=18 $$ healthy C57BL/6 mice). Manganese-Enhanced MRI (MEMRI) was obtained after intravitreal injection of manganese chloride and used as a reference standard for the optic pathway anatomy. RESULTS: ODF-FP outperformed by over 100% all the tested methods in terms of the ratios between the contra- and ipsilateral segments of the reconstructed optic pathways as well as the spatial overlap between tractography and MEMRI. CONCLUSION: In this challenging model system, ODF-Fingerprinting reduced uncertainty of diffusion tractography for complex structural formations of fiber bundles.

Molecular Dynamics Refinement of Open State Serotonin 5-HT3A Receptor Structures.

Pentameric ligand-gated ion channels play an important role in mediating fast neurotransmissions. As a member of this receptor family, cation-selective 5-HT3 receptors are a clinical target for treating nausea and vomiting associated with chemotherapy and radiation therapy (Thompson and Lummis, 2006). Multiple cryo-electron microscopy (cryo-EM) structures of 5-HT3 receptors have been determined in distinct functional states (e.g., open, closed, etc.) (Basak et al., 2018; Basak et al., 2018; Polovinkin et al., 2018; Zhang et al., 2015). However, recent work has shown that the transmembrane pores of the open 5-HT3 receptor structures rapidly collapse and become artificially asymmetric in molecular dynamics (MD) simulations. To avoid this hydrophobic collapse, Dämgen and Biggin developed an equilibration protocol that led to a stable open state structure of the glycine receptor in MD simulations (Dämgen and Biggin, 2020). However, the protocol failed to yield open-like structures of the 5-HT3 receptor in our simulations. Here, we present a refined equilibration protocol that involves the rearrangement of the transmembrane helices to achieve stable open state structures of the 5-HT3 receptor that allow both water and ion permeation through the channel. Notably, channel gating is mediated through collective movement of the transmembrane helices, involving not only pore lining M2 helices but also their cross-talk with the adjacent M1 and M3 helices. Thus, the successful application of our refined equilibration protocol underscores the importance of the conformational coupling between the transmembrane helices in stabilizing open-like structures of the 5-HT3 receptor.

Role of Structural, Metabolic, and Functional MRI in Monitoring Visual System Impairment and Recovery.

The visual system, consisting of the eyes and the visual pathways of the brain, receives and interprets light from the environment so that we can perceive the world around us. A wide variety of disorders can affect human vision, ranging from ocular to neurologic to systemic in nature. While other noninvasive imaging techniques such as optical coherence tomography and ultrasound can image particular sections of the visual system, magnetic resonance imaging (MRI) offers high resolution without depth limitations. MRI also gives superior soft-tissue contrast throughout the entire pathway compared to computed tomography. By leveraging different imaging sequences, MRI is uniquely capable of unveiling the intricate processes of ocular anatomy, tissue physiology, and neurological function in the human visual system from the microscopic to macroscopic levels. In this review we discuss how structural, metabolic, and functional MRI can be used in the clinical assessment of normal and pathologic states in the anatomic structures of the visual system, including the eyes, optic nerves, optic chiasm, optic tracts, visual brain nuclei, optic radiations, and visual cortical areas. We detail a selection of recent clinical applications of MRI at each position along the visual pathways, including the evaluation of pathology, plasticity, and the potential for restoration, as well as its limitations and key areas of ongoing exploration. Our discussion of the current and future developments in MR ocular and neuroimaging highlights its potential impact on our ability to understand visual function in new detail and to improve our protection and treatment of anatomic structures that are integral to this fundamental sensory system. LEVEL OF EVIDENCE 3: TECHNICAL EFFICACY STAGE 3: .

Macroscale variation in resting-state neuronal activity and connectivity assessed by simultaneous calcium imaging, hemodynamic imaging and electrophysiology.

Functional imaging of spontaneous activity continues to play an important role in the field of connectomics. The most common imaging signal used for these experiments is the blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signal, but how this signal relates to spontaneous neuronal activity remains incompletely understood. Genetically encoded calcium indicators represent a promising tool to study this problem, as they can provide brain-wide measurements of neuronal activity compared to point measurements afforded by electrophysiological recordings. However, the relationship between the calcium signal and neurophysiological parameters at the mesoscopic scale requires further systematic characterization. Therefore, we collected simultaneous resting-state measurements of electrophysiology, along with calcium and hemodynamic imaging, in lightly anesthetized mice to investigate two aims. First, we examined the relationship between each imaging signal and the simultaneously recorded electrophysiological signal in a single brain region, finding that both signals are better correlated with multi-unit activity compared to local field potentials, with the calcium signal possessing greater signal-to-noise ratio and regional specificity. Second, we used the resting-state imaging data to model the relationship between the calcium and hemodynamic signals across the brain. We found that this relationship varied across brain regions in a way that is consistent across animals, with delays increasing by600 ms towards posterior cortical regions. Furthermore, while overall functional connectivity (FC) measured by the hemodynamic signal is significantly correlated with FC measured by calcium, the two estimates were found to be significantly different. We hypothesize that these differences arise at least in part from the observed regional variation in the hemodynamic response. In total, this work highlights some of the caveats needed in interpreting hemodynamic-based measurements of FC, as well as the need for improved modeling methods to reduce this potential source of bias.

Top-down influence on the visual cortex of the blind during sensory substitution.

Visual sensory substitution devices provide a non-surgical and flexible approach to vision rehabilitation in the blind. These devices convert images taken by a camera into cross-modal sensory signals that are presented as a surrogate for direct visual input. While previous work has demonstrated that the visual cortex of blind subjects is recruited during sensory substitution, the cognitive basis of this activation remains incompletely understood. To test the hypothesis that top-down input provides a significant contribution to this activation, we performed functional MRI scanning in 11 blind (7 acquired and 4 congenital) and 11 sighted subjects under two conditions: passive listening of image-encoded soundscapes before sensory substitution training and active interpretation of the same auditory sensory substitution signals after a 10-minute training session. We found that the modulation of visual cortex activity due to active interpretation was significantly stronger in the blind over sighted subjects. In addition, congenitally blind subjects showed stronger task-induced modulation in the visual cortex than acquired blind subjects. In a parallel experiment, we scanned 18 blind (11 acquired and 7 congenital) and 18 sighted subjects at rest to investigate alterations in functional connectivity due to visual deprivation. The results demonstrated that visual cortex connectivity of the blind shifted away from sensory networks and toward known areas of top-down input. Taken together, our data support the model of the brain, including the visual system, as a highly flexible task-based and not sensory-based machine.

Improved spatial accuracy of functional maps in the rat olfactory bulb using supervised machine learning approach.

Functional MRI (fMRI) is a popular and important tool for noninvasive mapping of neural activity. As fMRI measures the hemodynamic response, the resulting activation maps do not perfectly reflect the underlying neural activity. The purpose of this work was to design a data-driven model to improve the spatial accuracy of fMRI maps in the rat olfactory bulb. This system is an ideal choice for this investigation since the bulb circuit is well characterized, allowing for an accurate definition of activity patterns in order to train the model. We generated models for both cerebral blood volume weighted (CBVw) and blood oxygen level dependent (BOLD) fMRI data. The results indicate that the spatial accuracy of the activation maps is either significantly improved or at worst not significantly different when using the learned models compared to a conventional general linear model approach, particularly for BOLD images and activity patterns involving deep layers of the bulb. Furthermore, the activation maps computed by CBVw and BOLD data show increased agreement when using the learned models, lending more confidence to their accuracy. The models presented here could have an immediate impact on studies of the olfactory bulb, but perhaps more importantly, demonstrate the potential for similar flexible, data-driven models to improve the quality of activation maps calculated using fMRI data.

In vivo visuotopic brain mapping with manganese-enhanced MRI and resting-state functional connectivity MRI.

The rodents are an increasingly important model for understanding the mechanisms of development, plasticity, functional specialization and disease in the visual system. However, limited tools have been available for assessing the structural and functional connectivity of the visual brain network globally, in vivo and longitudinally. There are also ongoing debates on whether functional brain connectivity directly reflects structural brain connectivity. In this study, we explored the feasibility of manganese-enhanced MRI (MEMRI) via 3 different routes of Mn(2+) administration for visuotopic brain mapping and understanding of physiological transport in normal and visually deprived adult rats. In addition, resting-state functional connectivity MRI (RSfcMRI) was performed to evaluate the intrinsic functional network and structural-functional relationships in the corresponding anatomical visual brain connections traced by MEMRI. Upon intravitreal, subcortical, and intracortical Mn(2+) injection, different topographic and layer-specific Mn enhancement patterns could be revealed in the visual cortex and subcortical visual nuclei along retinal, callosal, cortico-subcortical, transsynaptic and intracortical horizontal connections. Loss of visual input upon monocular enucleation to adult rats appeared to reduce interhemispheric polysynaptic Mn(2+) transfer but not intra- or inter-hemispheric monosynaptic Mn(2+) transport after Mn(2+) injection into visual cortex. In normal adults, both structural and functional connectivity by MEMRI and RSfcMRI was stronger interhemispherically between bilateral primary/secondary visual cortex (V1/V2) transition zones (TZ) than between V1/V2 TZ and other cortical nuclei. Intrahemispherically, structural and functional connectivity was stronger between visual cortex and subcortical visual nuclei than between visual cortex and other subcortical nuclei. The current results demonstrated the sensitivity of MEMRI and RSfcMRI for assessing the neuroarchitecture, neurophysiology and structural-functional relationships of the visual brains in vivo. These may possess great potentials for effective monitoring and understanding of the basic anatomical and functional connections in the visual system during development, plasticity, disease, pharmacological interventions and genetic modifications in future studies.

In silico design of high-affinity antigenic peptides for HLA-B44.

Cancer cell-killing by CD8+ T cells demands effective tumor antigen presentation by human leukocyte antigen class I (HLA-I) molecules. Screening and designing highly immunogenic neoantigens require quantitative computations to reliably predict HLA-peptide binding affinities. Here, with all-atom molecular dynamics (MD) simulations and free energy perturbation (FEP) methods, we design a collection of antigenic peptide candidates through in silico mutagenesis studies on immunogenic neoantigens, yielding enhanced binding affinities to HLA-B*44:02. In-depth structural dissection shows that introducing positively charged residues such as arginine to position 6 or lysine to position 7 of the candidates triggers conformational shifts in both peptides and the antigen-binding groove of the HLA, following the "induced-fit" mechanism. Enhancement in binding affinities compared to the wild-type was found in three out of five mutated candidates. The HLA pocket, capable of accommodating positively charged residues in positions from 5 to 7, is designated as the "dynamic pocket". Taken together, we showcase an effective structure-based binding affinity optimization framework for antigenic peptides of HLA-B*44:02 and underscore the importance of dynamic nature of the antigen-binding groove in concert with the anchoring motifs. This work provides structural insights for rational design of favorable HLA-peptide bindings and future developments in neoantigen-based therapeutics.

Age-related effects of optineurin deficiency in the mouse eye.

Optineurin (OPTN) is a gene associated with familial normal tension glaucoma (NTG). While NTG involves intraocular pressure (IOP)-independent neurodegeneration of the visual pathway that progresses with age, how OPTN dysfunction leads to NTG remains unclear. Here, we generated an OPTN knockout mouse (Optn-/-) model to test the hypothesis that a loss-of-function mechanism induces structural and functional eye deterioration with aging. Eye anatomy, visual function, IOP, retinal histology, and retinal ganglion cell survival were compared to littermate wild-type (WT) control mice. Consistent with OPTN's role in NTG, loss of OPTN did not increase IOP or alter gross eye anatomy in young (2-3 months) or aged (12 months) mice. When retinal layers were quantitated, young Optn-/- mice had thinner retina in the peripheral regions than young WT mice, primarily due to thinner ganglion cell-inner plexiform layers. Despite this, visual function in Optn-/- mice was not severely impaired, even with aging. We also assessed relative abundance of retinal cell subtypes, including amacrine cells, bipolar cells, cone photoreceptors, microglia, and astrocytes. While many of these cellular subtypes were unaffected by Optn deletion, more dopaminergic amacrine cells were observed in aged Optn-/- mice. Taken together, our findings showed that complete loss of Optn resulted in mild retinal changes and less visual function impairment, supporting the possibility that OPTN-associated glaucoma does not result from a loss-of-function disease mechanism. Further research using these Optn mice will elucidate detailed molecular pathways involved in NTG and identify clinical or environmental risk factors that can be targeted for glaucoma treatment.

Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development.

Goal: Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. Methods: We tested five smartphone-based distance-estimation approaches in the image center and periphery at 1-3 meters, including machine learning (CoreML), infrared grid distortion (IR_self), light detection and ranging (LiDAR_back), and augmented reality room-tracking on the front (ARKit_self) and back-facing cameras (ARKit_back). Results: For accuracy in the image center, all approaches had <±2.5 cm average error, except CoreML which had ±5.2-6.2 cm average error at 2-3 meters. In the periphery, all approaches were more inaccurate, with CoreML and IR_self having the highest average errors at ±41 cm and ±32 cm respectively. For usability, CoreML fared favorably with the lowest central processing unit usage, second lowest battery usage, highest field-of-view, and no specialized sensor requirements. Conclusions: We provide key information that helps design reliable smartphone-based visual assistive technologies to enhance the functionality of PBLV.

NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis improves brain activity detection across rodent and human functional MRI contexts.

NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve the temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve data quality for rodent fMRI using NORDIC PCA remains uncertain. NORDIC PCA may also be particularly beneficial for improving topological brain mapping, as conventional mapping requires precise spatiotemporal signals from large datasets (ideally ~1 hour acquisition) for individual representations. In this study, we evaluated the effects of NORDIC PCA compared with "Standard" processing in various rodent fMRI contexts that range from task-evoked optogenetic fMRI to resting-state fMRI. We also evaluated the effects of NORDIC PCA on human resting-state and retinotopic mapping fMRI via population receptive field (pRF) modeling. In rodent optogenetic fMRI, apart from doubling the tSNR, NORDIC PCA resulted in a larger number of activated voxels and a significant decrease in the variance of evoked brain responses without altering brain morphology. In rodent resting-state fMRI, we found that NORDIC PCA induced a nearly threefold increase in tSNR and preserved task-free relative cerebrovascular reactivity (rCVR) across cortical depth. NORDIC PCA further improved the detection of TGN020-induced aquaporin-4 inhibition on rCVR compared with Standard processing without NORDIC PCA. NORDIC PCA also increased the tSNR for both human resting-state and pRF fMRI, and for the latter also increased activation cluster sizes while retaining retinotopic organization. This suggests that NORDIC PCA preserves the spatiotemporal precision of fMRI signals needed for pRF analysis, and effectively captures small activity changes with high sensitivity. Taken together, these results broadly demonstrate the value of NORDIC PCA for the enhanced detection of neural dynamics across various rodent and human fMRI contexts. This can in turn play an important role in improving fMRI image quality and sensitivity for translational and preclinical neuroimaging research.

Contributions of Brain Microstructures and Metabolism to Visual Field Loss Patterns in Glaucoma Using Archetypal and Information Gain Analyses.

Purpose: To investigate the contributions of the microstructural and metabolic brain environment to glaucoma and their association with visual field (VF) loss patterns by using advanced diffusion magnetic resonance imaging (dMRI), proton magnetic resonance spectroscopy (MRS), and clinical ophthalmic measures. Methods: Sixty-nine glaucoma and healthy subjects underwent dMRI and/or MRS at 3 Tesla. Ophthalmic data were collected from VF perimetry and optical coherence tomography. dMRI parameters of microstructural integrity in the optic radiation and MRS-derived neurochemical levels in the visual cortex were compared among early glaucoma, advanced glaucoma, and healthy controls. Multivariate regression was used to correlate neuroimaging metrics with 16 archetypal VF loss patterns. We also ranked neuroimaging, ophthalmic, and demographic attributes in terms of their information gain to determine their importance to glaucoma. Results: In dMRI, decreasing fractional anisotropy, radial kurtosis, and tortuosity and increasing radial diffusivity correlated with greater overall VF loss bilaterally. Regionally, decreasing intra-axonal space and extra-axonal space diffusivities correlated with greater VF loss in the superior-altitudinal area of the right eye and the inferior-altitudinal area of the left eye. In MRS, both early and advanced glaucoma patients had lower gamma-aminobutyric acid (GABA), glutamate, and choline levels than healthy controls. GABA appeared to associate more with superonasal VF loss, and glutamate and choline more with inferior VF loss. Choline ranked third for importance to early glaucoma, whereas radial kurtosis and GABA ranked fourth and fifth for advanced glaucoma. Conclusions: Our findings highlight the importance of non-invasive neuroimaging biomarkers and analytical modeling for unveiling glaucomatous neurodegeneration and how they reflect complementary VF loss patterns.

Early inner plexiform layer thinning and retinal nerve fiber layer thickening in excitotoxic retinal injury using deep learning-assisted optical coherence tomography.

Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer's, multiple sclerosis, and Parkinson's disease. Within the eye, excitotoxicity is thought to play a critical role in retinal ganglion cell death in glaucoma, diabetic retinopathy, retinal ischemia, and optic nerve injury, yet how excitotoxic injury impacts different retinal layers is not well understood. Here, we investigated the longitudinal effects of N-methyl-D-aspartate (NMDA)-induced excitotoxic retinal injury in a rat model using deep learning-assisted retinal layer thickness estimation. Before and after unilateral intravitreal NMDA injection in nine adult Long Evans rats, spectral-domain optical coherence tomography (OCT) was used to acquire volumetric retinal images in both eyes over 4 weeks. Ten retinal layers were automatically segmented from the OCT data using our deep learning-based algorithm. Retinal degeneration was evaluated using layer-specific retinal thickness changes at each time point (before, and at 3, 7, and 28 days after NMDA injection). Within the inner retina, our OCT results showed that retinal thinning occurred first in the inner plexiform layer at 3 days after NMDA injection, followed by the inner nuclear layer at 7 days post-injury. In contrast, the retinal nerve fiber layer exhibited an initial thickening 3 days after NMDA injection, followed by normalization and thinning up to 4 weeks post-injury. Our results demonstrated the pathological cascades of NMDA-induced neurotoxicity across different layers of the retina. The early inner plexiform layer thinning suggests early dendritic shrinkage, whereas the initial retinal nerve fiber layer thickening before subsequent normalization and thinning indicates early inflammation before axonal loss and cell death. These findings implicate the inner plexiform layer as an early imaging biomarker of excitotoxic retinal degeneration, whereas caution is warranted when interpreting the ganglion cell complex combining retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses in conventional OCT measures. Deep learning-assisted retinal layer segmentation and longitudinal OCT monitoring can help evaluate the different phases of retinal layer damage upon excitotoxicity.

Novel Inhibitory Role of Fenofibric Acid by Targeting Cryptic Site on the RBD of SARS-CoV-2.

The emergence of the recent pandemic causing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created an alarming situation worldwide. It also prompted extensive research on drug repurposing to find a potential treatment for SARS-CoV-2 infection. An active metabolite of the hyperlipidemic drug fenofibrate (also called fenofibric acid or FA) was found to destabilize the receptor-binding domain (RBD) of the viral spike protein and therefore inhibit its binding to human angiotensin-converting enzyme 2 (hACE2) receptor. Despite being considered as a potential drug candidate for SARS-CoV-2, FA's inhibitory mechanism remains to be elucidated. We used molecular dynamics (MD) simulations to investigate the binding of FA to the RBD of the SARS-CoV-2 spike protein and revealed a potential cryptic FA binding site. Free energy calculations were performed for different FA-bound RBD complexes. The results suggest that the interaction of FA with the cryptic binding site of RBD alters the conformation of the binding loop of RBD and effectively reduces its binding affinity towards ACE2. Our study provides new insights for the design of SARS-CoV-2 inhibitors targeting cryptic sites on the RBD of SARS-CoV-2.

Visual Plasticity in Adulthood: Perspectives from Hebbian and Homeostatic Plasticity.

The visual system retains profound plastic potential in adulthood. In the current review, we summarize the evidence of preserved plasticity in the adult visual system during visual perceptual learning as well as both monocular and binocular visual deprivation. In each condition, we discuss how such evidence reflects two major cellular mechanisms of plasticity: Hebbian and homeostatic processes. We focus on how these two mechanisms work together to shape plasticity in the visual system. In addition, we discuss how these two mechanisms could be further revealed in future studies investigating cross-modal plasticity in the visual system.

GABA decrease is associated with degraded neural specificity in the visual cortex of glaucoma patients.

Glaucoma is an age-related neurodegenerative disease of the visual system, affecting both the eye and the brain. Yet its underlying metabolic mechanisms and neurobehavioral relevance remain largely unclear. Here, using proton magnetic resonance spectroscopy and functional magnetic resonance imaging, we investigated the GABAergic and glutamatergic systems in the visual cortex of glaucoma patients, as well as neural specificity, which is shaped by GABA and glutamate signals and underlies efficient sensory and cognitive functions. Our study shows that among the older adults, both GABA and glutamate levels decrease with increasing glaucoma severity regardless of age. Further, our study shows that the reduction of GABA but not glutamate predicts the neural specificity. This association is independent of the impairments on the retina structure, age, and the gray matter volume of the visual cortex. Our results suggest that glaucoma-specific decline of GABA undermines neural specificity in the visual cortex and that targeting GABA could improve the neural specificity in glaucoma.

Training AI to Recognize Objects of Interest to the Blind and Low Vision Community.

Recent object detection models show promising advances in their architecture and performance, expanding potential applications for the benefit of persons with blindness or low vision (pBLV). However, object detection models are usually trained on generic data rather than datasets that focus on the needs of pBLV. Hence, for applications that locate objects of interest to pBLV, object detection models need to be trained specifically for this purpose. Informed by prior interviews, questionnaires, and Microsoft's ORBIT research, we identified thirty-five objects pertinent to pBLV. We employed this user-centric feedback to gather images of these objects from the Google Open Images V6 dataset. We subsequently trained a YOLOv5x model with this dataset to recognize these objects of interest. We demonstrate that the model can identify objects that previous generic models could not, such as those related to tasks of daily functioning - e.g., coffee mug, knife, fork, and glass. Crucially, we show that careful pruning of a dataset with severe class imbalances leads to a rapid, noticeable improvement in the overall performance of the model by two-fold, as measured using the mean average precision at the intersection over union thresholds from 0.5 to 0.95 (mAP50-95). Specifically, mAP50-95 improved from 0.14 to 0.36 on the seven least prevalent classes in the training dataset. Overall, we show that careful curation of training data can improve training speed and object detection outcomes. We show clear directions on effectively customizing training data to create models that focus on the desires and needs of pBLV.Clinical Relevance- This work demonstrated the benefits of developing assistive AI technology customized to individual users or the wider BLV community.