Biology subjects

Ke, J.

Publications and source records attributed to Ke, J..

3 recordsLinked to original sources

bioRxiv2022

Long-term two-photon imaging of spinal cord in freely behaving mice

The spinal cord is critical to the perception of peripheral information under sensory-guided motor behaviors in health and disease. However, the cellular activity underlie spinal cord function in freely behaving animals is not clear. Here, we developed a new method for imaging the spinal cord at cellular and subcellular resolution over weeks under naturalistic conditions. The method involves an improved surgery to reduce spinal movement, and the installation of a miniaturized two-photon microscope to obtain high-resolution imaging in moving mice. In vivo calcium imaging demonstrated that dorsal horn neurons show a sensorimotor program-dependent synchronization and heterogeneity under distinct cutaneous stimuli in behaving mice. The long-term imaging of sensory neurons revealed that in the spinal cord, healthy mice demonstrated stereotyped responses. However, in a neuropathic pain model, plasticity changes and neuronal sensitization were observed. We provide a practical method to study the function of spinal cord on sensory perception and disorders in freely behaving mice.

neuroscience↗

bioRxiv2021

An AAV-ie based Vaccine effectively protects against SARS-CoV-2 and Circulating Variants

Prophylactic vaccines against SARS-CoV-2 have been extensively developed globally to overcome the COVID-19 pandemic. However, recently emerging SARS-CoV-2 variants B.1.1.7 and B.1.351 limit the vaccine protection effects and successfully escape antibody cocktail treatment. Herein, based on our previously engineered adeno-associated viral (AAV) vector, AAV-ie, and systematic immunogen screening, we developed an AAV-ie-S1 vaccine with thermostability, high efficiency, safety, and single-dose vaccination advantage. Importantly, the AAV-ie-S1 immune sera efficiently neutralize B.1.1.7 and B.1.351, indicating a potential to circumvent the spreading of SARS-CoV-2.

microbiology↗

bioRxiv2019

Time-dependent Canonical Correlation Analysis for Multilevel Time Series

Canonical Correlation Analysis is a technique in multivariate data analysis for finding linear projections that maximize the correlation between two groups of variables. The correlations are typically defined without accounting for the serial correlations between observations, a typical setting for time series data. To understand the coupling dynamics and temporal variations between the two time-varying sources, we introduce the time-dependent canonical correlation analysis (TDCCA), a method for inferring time-dependent canonical vectors from multilevel time series data. A convex formulation of the problem is proposed, which leverages the singular value decomposition (SVD) characterization of all solutions of the CCA problem. We use simulated datasets to validate the proposed algorithm. Moreover, we propose a novel measure, canonical correlation variation as another way to assess the dynamic pattern of brain connections and we apply it to a real resting state fMRI dataset to study the aging effects on brain connectivity. Additionally, we explore our proposed method in a task-related fMRI to detect the temporal dynamics due to different motor tasks. We show that, compared to extant methods, the TDCCA-based approach not only detect temporal changes but also improves feature extraction. Together, this paper contributes broadly to new computational methodologies in understanding multilevel time series.

neuroscience↗