Medical Sciences Commons^™

Refining Aicardi Syndrome Diagnostic Criteria: An Expert-Based Consensus Using A Modified Delphi Approach, Silvia Masnada, Valentina De Giorgis, Umberto Carugo, Nadia Bahi-Buisson, Mara Cavallin, Mark Corbett, Manuela Formica, Jozef Gecz, Natalia Petros, Emilio Perucca, Anna Pichiecchio, Paolo Fusar Poli, Elliott H Sherr, Ignatia B Van Den Veyver, Federico Zara, Martin Geroldinger, Pierangelo Veggiotti, Alexis Arzimanoglou

Duncan NRI Faculty and Staff Publications

Background and objectives: Aicardi syndrome (AIC) is a rare neurodevelopmental disorder historically characterised by the presence of chorioretinal lacunae, corpus callosum agenesis, infantile spasms and several supporting features that aid in diagnosis. However, the unclear aetiology and evolving diagnostic tools have led to ongoing reconsideration of the criteria, based on individual approaches. Our study aimed to establish, for the first time, an expert-based consensus on diagnostic criteria for AIC by integrating both existing and novel ones.

Methods: A geographically diverse and multidisciplinary group of expert physicians was invited to participate in a modified Delphi study, to achieve consensus on major, …

Chromnet: A Multi-Task Learning Framework For Cross-Cell Type Prediction Of 3d Chromatin Interactions Using Epigenetic Signals, Bin Wang, Shaokai Wang, Liqing Ding, Hongdong Li, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

The 3D organization of chromatin plays a fundamental role in gene regulation, cellular function, and disease mechanisms. However, current experimental techniques, such as Hi-C, remain costly and labor-intensive, limiting their application in large-scale and disease-related studies. To address this challenge, ChromNet is presented, a multi-task learning framework that integrates epigenetic signals across diverse cell types to enable high-precision prediction of chromatin architecture. By incorporating noise perturbation and auxiliary classification tasks, ChromNet improves the identification of topologically associating domains (TADs) and cell-type-specific chromatin structures, demonstrating superior generalization performance. Notably, ChromNet accurately predicts chromatin interactions in acute myeloid leukemia (AML) samples by …

A Comprehensive Overview Of Neurophysiological Correlates Of Cognitive Impairment In Amyotrophic Lateral Sclerosis, Seyyed Bahram Borgheai, Brie E. Achorn, Alyssa H. Zisk, Sarah M. Hosni, Karl E. G. Richter, Frank S. Menniti, Yalda Shahriari

Computer Science Faculty Publications

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that leads to the gradual loss of motor control, typically resulting in paralysis and death within 3 to 5 years of diagnosis. ALS shares neuropathological and genetic associations with fronto-temporal dementia (FTD), a neurodegenerative condition primarily impacting cognitive functions. These two conditions are increasingly viewed as manifestations of a single molecular disease process that affects distinct brain systems, impacting motor neuronal pathways in ALS and fronto-cortical functions in FTD. However, this simple dichotomy belies the complexity of these conditions. In particular, patients with primary motor ALS can also experience significant cognitive …

Sage: Spatially Aware Gene Selection And Dual-View Embedding Fusion For Domain Identification In Spatial Transcriptomics, Yi He, Yunpei Xu, Liqing Ding, Hong-Dong Li, Yaohang Li, Shaokai Wang

Computer Science Faculty Publications

Despite enabling high-resolution mapping of gene expression within tissues, spatial transcriptomics (ST) still faces challenges in accurately segmenting spatial domains due to complex tissue architecture and limitations of current methods. Most approaches rely on local spatial priors, lack gene-level interpretability, and fall short in capturing structure-discriminative genes or long-range functional relationships, limiting their ability to resolve biologically meaningful architectures. We present Spatially Aware Gene selection and dual-view Embedding fusion (SAGE), a unified and reproducible framework for domain identification in spatial transcriptomics that combines topic-driven gene selection with dual-view embedding fusion to address these gaps. SAGE integrates non-negative matrix factorization (NMF)-based …

Cb1 Allosteric Modulation: Preclinical Insights Into Therapeutic Potential And Misuse Liability, Mohammed A. Mustafa

Theses and Dissertations

Cannabinoid type-1 (CB1) allosteric modulators represent a promising approach to modulate CB1 receptor signaling by binding to distinct receptor sites, without producing adverse cannabimimetic and dependence-related effects associated with Δ9-tetrahydrocannabinol (THC) and other CB1 agonists. This dissertation investigates the pharmacological, behavioral, and dependence-related profiles of CB1 allosteric modulators for their therapeutic potential and misuse liability. Presented here, the chiral CB1 positive allosteric modulator (PAM) ZCZ011 was resolved into its R- and S-enantiomers and characterized across in vitro and in vivo assays. Both enantiomers enhance CB1 agonist activity and produce intrinsic effects in vitro. Behaviorally, they produce antinociceptive effects in the …