Major depressive disorder (MDD) exhibits significant heterogeneity whose neurobiological mechanisms remain elusive. Alterations in morphological-functional coupling (MFC) have been observed in MDD. This study aims to investigate MDD subtypes based on...
One of the fundamental goals of behavioural science is to explain seemingly complex human and animal behaviour in terms of simple mechanistic principles. Ji-An, Benna, & Mattar1 (henceforth, JBM) recently proposed a novel analytic and interpretative ...
Spatial transcriptomics offers detailed molecular insights but struggles to capture continuous tissue dynamics due to experimental constraints and destructive sampling. Traditional optimal transport (OT) methods attempt to link time points but often ...
During development, neural circuits are shaped continuously as we learn to control our bodies. The ultimate goal of this process is to produce neural dynamics that enable the rich repertoire of behaviors we perform. What begins as a series of “babble...
Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in the U.S., and the stimulant and nonstimulant medications used to treat ADHD are among the most widely prescribed treatments in youth. Stimulants—includi...
All life relies on proteins to function, yet accurately modeling protein structures that exceed ≈ 10, 000 amino acids or have higher-order geometries remains difficult. Existing solutions are limited to specific scenarios, require considerable comput...
Polymerase Chain Reaction (PCR) is a widely used molecular biology technique to amplify DNA sequences. PCR amplification is affected by factors such as binding dynamics and primer-template interactions. This study aims to reduce the time and cost of ...
B7-H3 (CD276), an immunoregulatory checkpoint molecule overexpressed in numerous cancers, is a promising therapeutic target. Nanobodies possess unique advantages for targeting B7-H3, such as small size, high stability, and the ability to bind cryptic...
Tertiary lymphoid structures (TLS) have been observed in solid tumors and have been associated with better outcomes in patients treated with immunotherapy, but their dynamic nature makes identifying TLS in clinical samples challenging. Recently, path...
Deep learning has revolutionized biomolecular modeling, enabling the prediction of diverse structures with atomic accuracy. However, leveraging the atomic-level precision of the structure prediction model for de novo design remains challenging. Here,...
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