This study presents a novel method for authenticating the geographical origin and cultivar of kava (Piper methysticum) by combining Fourier Transform Infrared (FTIR) spectroscopy with Artificial Neural Networks (ANN). A spectral database of kava vari...
Accumulating evidence suggests the canonical cortical circuit, consisting of excitatory (E) and diverse classes of inhibitory (I) interneurons, implements Bayesian posterior sampling. However, most of the identified circuits’ sampling algorithms are ...
Mass spectrometry imaging (MSI) provides molecularly resolved maps of metabolites and lipids across tissues, yet the lack of large-scale, unified representation learning frameworks limits its potential for generalization and downstream analysis. Here...
Despite the increasing adoption of deep neural networks (DNNs) in brain-computer interfaces (BCIs), developing high-degree-of-freedom (DOF) systems capable of decoding continuous movements, such as limb kinematics, remains a significant challenge. Th...
Stereotyped neural sequences are often exhibited in the brain, yet the neurophysiological mechanisms underlying their generation are not fully understood. Birdsong is a prominent model to study such behavior particularly because juvenile songbirds pr...
Antibodies play a central role in neutralizing pathogens through direct interference with viral entry and recruitment of effector immune cells. However, viruses employ sophisticated escape mechanisms to evade these defenses, primarily through mutatio...
Fluorescence lifetime imaging microscopy (FLIM) can probe the metabolic environment of living cells in a label-free and non-invasive manner. However, endogenous fluorophores have low absorption and quantum yields, which necessitates long integration ...
Proteins often function as part of complexes, and the specific stoichiometry of these assemblies is critical for their biological roles, but experimental determination of assembly composition remains challenging and existing computational methods for...
Machine learning approaches have advanced the identification of neural signatures of substance use, particularly through case-control comparisons and network-level analyses. However, most studies have focused on single substances in isolation, making...
Understanding the cells of origin is essential for overcoming therapy resistance in esophageal squamous cell carcinoma (ESCC). We utilized machine learning-based single-cell trajectory analysis on 4NQO-induced murine models and genetically engineered...
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