Molecular features driving cellular complexity of human brain evolution.

Human-specific genomic changes contribute to the unique functionalities of the human brain1-5. The cellular heterogeneity of the human brain6,7 and the complex regulation of gene expression highlight the need to characterize human-specific molecular features at cellular resolution. Here we analysed single-nucleus RNA-sequencing and single-nucleus assay for transposase-accessible chromatin with sequencing datasets for human, chimpanzee and rhesus macaque brain tissue from posterior cingulate cortex. We show a human-specific increase of oligodendrocyte progenitor cells and a decrease of mature oligodendrocytes across cortical tissues. Human-specific regulatory changes were accelerated in oligodendrocyte progenitor cells, and we highlight key biological pathways that may be associated with the proportional changes. We also identify human-specific regulatory changes in neuronal subtypes, which reveal human-specific upregulation of FOXP2 in only two of the neuronal subtypes. We additionally identify hundreds of new human accelerated genomic regions associated with human-specific chromatin accessibility changes. Our data also reveal that FOS::JUN and FOX motifs are enriched in the human-specifically accessible chromatin regions of excitatory neuronal subtypes. Together, our results reveal several new mechanisms underlying the evolutionary innovation of human brain at cell-type resolution.

Singular Value Decomposition Quantum Algorithm for Quantum Biology.

There has been a recent interest in quantum algorithms for the modeling and prediction of nonunitary quantum dynamics using current quantum computers. The field of quantum biology is one area where these algorithms could prove to be useful as biological systems are generally intractable to treat in their complete form but amenable to an open quantum systems approach. Here, we present the application of a recently developed singular value decomposition (SVD) algorithm to two systems in quantum biology: excitonic energy transport through the Fenna-Matthews-Olson complex and the radical pair mechanism for avian navigation. We demonstrate that the SVD algorithm is capable of capturing accurate short- and long-time dynamics for these systems through implementation on a quantum simulator and conclude that while the implementation of this algorithm is beyond the reach of current quantum computers, it has the potential to be an effective tool for the future study of systems relevant to quantum biology.

Compensation between FOXP transcription factors maintains proper striatal function.

Spiny projection neurons (SPNs) of the striatum are critical in integrating neurochemical information to coordinate motor and reward-based behavior. Mutations in the regulatory transcription factors expressed in SPNs can result in neurodevelopmental disorders (NDDs). Paralogous transcription factors Foxp1 and Foxp2, which are both expressed in the dopamine receptor 1 (D1) expressing SPNs, are known to have variants implicated in NDDs. Utilizing mice with a D1-SPN-specific loss of Foxp1, Foxp2, or both and a combination of behavior, electrophysiology, and cell-type-specific genomic analysis, loss of both genes results in impaired motor and social behavior as well as increased firing of the D1-SPNs. Differential gene expression analysis implicates genes involved in autism risk, electrophysiological properties, and neuronal development and function. Viral-mediated re-expression of Foxp1 into the double knockouts is sufficient to restore electrophysiological and behavioral deficits. These data indicate complementary roles between Foxp1 and Foxp2 in the D1-SPNs.

Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research.

Most research using digital technologies builds on existing methods for staff-administered evaluation, requiring a large investment of time, effort, and resources. Widespread use of personal mobile devices provides opportunities for continuous health monitoring without active participant engagement. Home-based sensors show promise in evaluating behavioral features in near real time. Digital technologies across these methodologies can detect precise measures of cognition, mood, sleep, gait, speech, motor activity, behavior patterns, and additional features relevant to health. As a neurodegenerative condition with insidious onset, Alzheimer disease and other dementias (AD/D) represent a key target for advances in monitoring disease symptoms. Studies to date evaluating the predictive power of digital measures use inconsistent approaches to characterize these measures. Comparison between different digital collection methods supports the use of passive collection methods in settings in which active participant engagement approaches are not feasible. Additional studies that analyze how digital measures across multiple data streams can together improve prediction of cognitive impairment and early-stage AD are needed. Given the long timeline of progression from normal to diagnosis, digital monitoring will more easily make extended longitudinal follow-up possible. Through the American Heart Association-funded Strategically Focused Research Network, the Boston University investigative team deployed a platform involving a wide range of technologies to address these gaps in research practice. Much more research is needed to thoroughly evaluate limitations of passive monitoring. Multidisciplinary collaborations are needed to establish legal and ethical frameworks for ensuring passive monitoring can be conducted at scale while protecting privacy and security, especially in vulnerable populations.

Increased glycine contributes to synaptic dysfunction and early mortality in Nprl2 seizure model.

Targeted therapies for epilepsies associated with the mTORC1 signaling negative regulator GATOR1 are lacking. NPRL2 is a subunit of the GATOR1 complex and mutations in GATOR1 subunits, including NPRL2, are associated with epilepsy. To delineate the mechanisms underlying NPRL2-related epilepsies, we created a mouse (Mus musculus) model with neocortical loss of Nprl2. Mutant mice have increased mTORC1 signaling and exhibit spontaneous seizures. They also display abnormal synaptic function characterized by increased evoked and spontaneous EPSC and decreased evoked and spontaneous IPSC frequencies, respectively. Proteomic and metabolomics studies of Nprl2 mutants revealed alterations in known epilepsy-implicated proteins and metabolic pathways, including increases in the neurotransmitter, glycine. Furthermore, glycine actions on the NMDA receptor contribute to the electrophysiological and survival phenotypes of these mice. Taken together, in this neuronal Nprl2 model, we delineate underlying molecular, metabolic, and electrophysiological mechanisms contributing to mTORC1-related epilepsy, providing potential therapeutic targets for epilepsy.