University School

Distinguishing non-epileptic events from epileptic seizures remains a clinical challenge, particularly when occurring exclusively during sleep. Sleep-related rhythmical movement disorder (SRRMD) is a benign condition typically seen in early childhood, characterised by stereotyped, rhythmical repetitive movements involving large muscle groups, predominantly during Stage II of non-REM sleep. These movements can closely mimic features of sleep parasomnias, hypermotor seizures or psychogenic non-epileptic seizures (PNES), complicating the diagnostic approach. We present a case of an adolescent female with comorbid SRRMD and PNES and a clinical approach to distinguish between them.

Mitochondrial dysfunction and dysregulated proteolysis drive Huntington's disease (HD), tauopathy, and related neurodegenerative disorders. Calpain-2, a Ca2+-activated protease restrained by calpastatin (CAST), is pathologically overactivated, yet no therapies directly target this axis. We identify A36, a brain-penetrant small molecule derived from CHIR99021 that selectively stabilizes the CAST-calpain-2 complex without inhibiting GSK3. A36 acts as a protein-protein interaction stabilizer, enhancing CAST-calpain-2 binding, preventing CAST degradation, and thereby limiting calpain-2 activation and mitochondrial damage. In patients with HD induced pluripotent stem cell-derived neurons and mutant mouse striatal neurons, A36 normalized mitochondrial morphology and membrane potential, reduced oxidative stress, and improved survival. In vivo, A36 displayed favorable pharmacokinetics and central nervous system exposure; treatment reduced striatal neurodegeneration, mutant huntingtin aggregation, and motor deficits in HD R6/2 mice, and lowered phosphorylated tau, neuroinflammation, and cognitive decline in tauopathy PS19 mice. These findings establish pharmacological stabilization of CAST-calpain-2 as a therapeutic strategy and position A36 as a mechanism-selective modulator with broad neurodegenerative disease potential.

Despite effective antiretroviral therapy (ART) in suppressing HIV replication and reducing viral loads, latent reservoirs within the central nervous system (CNS) may contribute to persistent immune dysfunction, inflammation, and neurocognitive impairment in people living with HIV. Extracellular vesicles (EVs) isolated from serum and cerebrospinal fluid have been reported to contain HIV-1 RNAs, with their abundance associated with neurocognitive outcomes in ART-treated individuals. However, the mechanistic contribution of HIV-associated EVs in CNS pathology remains incompletely understood. In this study, we characterized EVs derived from latently HIV-1-infected T cells and microglial cells and identified HIV RNAs, including transactivation response element (TAR) RNA, Nef, and Tat RNA, within these particles. These EVs disrupted the integrity of a triple-cell blood–brain barrier (BBB) model by inducing apoptosis in BBB-associated cells. HIV-associated EVs were also able to traverse the BBB and promote apoptosis in cultured neuronal cells. In cerebral organoids derived from human induced pluripotent stem cells, these EVs induce production of pro-inflammatory cytokines, including IL-1β and TNF-α. Single-cell RNA sequencing of cerebral organoids exposed to microglial cell-derived EVs revealed upregulation of genes involved in double-stranded RNA signaling, apoptosis, inflammation, and microglial activation in response to HIV-associated EVs. Additionally, these EVs induced increased expression and phosphorylation of protein kinase R (PKR) in cerebral organoids. Plasma-derived EVs containing HIV RNA from individuals with HIV, but not control EVs from uninfected donors, induced apoptosis in both cerebral organoids and neuronal cells. These findings suggest that HIV-associated EVs may contribute to neuroinflammatory processes and cellular injury in CNS models, potentially informing mechanisms underlying HIV-related neurocognitive impairment that persist despite ART.

Reciprocal innovation, a model of sustained, multidirectional exchange in which health strategies are adapted, revisited, and refined across contexts, offers a compelling framework to rethink how implementation science can support global health equity by enabling dynamic, multidirectional learning across different contexts. Drawing on the EXTRA-CVD trial, a nurse-led cardiovascular disease prevention intervention designed to extend the HIV treatment cascade in United States (U.S.) HIV clinics, which adapted strategies informed by implementation research in Kenya and the U.S. Veterans Affairs health system, this perspective examines how reciprocal innovation can begin to emerge within existing research structures, as well as where opportunities for deeper exchange remain limited. We identify four operational domains of reciprocal innovation: care delivery strategies, end-user engagement, research methodologies, and research leadership and partnership. Across these domains, we describe how cross-context learning shaped intervention adaptation and site-level implementation in EXTRA-CVD, as well as missed opportunities where more intentional feedback, shared leadership, and methodological exchange could have strengthened multidirectional learning. Taken together, this work highlights both the potential and the practical challenges of reciprocal innovation in implementation research, emphasizing its role in moving beyond unidirectional knowledge transfer toward iterative, context-responsive learning. By embedding structures for iterative feedback, equity-centered governance, and multidirectional learning systems within research and implementation systems, future global partnerships can foster more inclusive, responsive, and sustainable health interventions.

V-domain immunoglobulin suppressor of T cell activation (VISTA) is an immune checkpoint protein that impairs antitumor T cell responses. While broadly expressed on myeloid cells and T cells, the specific contribution of T cell–intrinsic VISTA to antitumor immunity remains undefined. This study investigated the phenotypic and functional consequences of T cell–specific VISTA deletion in tumor-specific CD8+ T cells. Single-cell transcriptomic analysis, TCR repertoire profiling, and flow cytometry revealed that loss of T cell–intrinsic VISTA enhanced early priming and short-term expansion of CD8+ T cells, yet this initial advantage failed to confer durable tumor control. Persistent dysfunction in VISTA-deficient T cells was in part driven by trans-VISTA on myeloid cells, while CTLA-4 upregulation further constrained T cell responses. T cell–intrinsic VISTA deficiency cooperated with CTLA-4 blockade to improve T cell survival and broaden TCR repertoire diversity, resulting in more robust tumor regression than CTLA-4 inhibition alone. A transcriptional signature enriched in VISTA-deficient cytotoxic T cells correlated with favorable outcomes in cancer patients treated with existing immune checkpoint inhibitors. These findings collectively define T cell–intrinsic mechanisms by which VISTA enforces T cell dysfunction and underscore its potential as both a therapeutic target and a biomarker of resistance to current immunotherapies.

Degenerative eye diseases are major causes of irreversible vision loss worldwide, but effective treatments remain limited, partly due to the lack of effective human models. Retinal organoids derived from stem cells can recapitulate key structural and physiological features of the human retina, offering powerful tools to study disease mechanisms and develop new therapies. Here, we review recent progress in engineering retinal organoids and eye-on-a-chip models for modeling degenerative eye diseases, with a focus on engineering innovations. We first describe conventional methods for organoid differentiation and characterization along with current outstanding challenges. To better engineer retinal organoids, new strategies that leverage microfluidics and biomaterials have emerged to regulate dynamic and physiologically relevant environments for organoid differentiation. Moreover, the integration of artificial intelligence, multimodal sensing, and data analytics improves the monitoring and prediction of retinal function and therapeutic outcomes. Finally, we discuss future directions in innovating next-generation retinal organoid and eye-on-a-chip models for disease modeling, drug discovery, and vision restoration, highlighting their potential for precision ophthalmology.