ABSTRACT
Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.
ABSTRACT
Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.
ABSTRACT
<p><b>OBJECTIVE</b>To investigate the changes in the membrane properties and synaptic stability of the rat retinal ganglion cells (RGCs) during postnatal development.</p><p><b>METHODS</b>Whole-cell patch-clamp technique was used to record the action potentials (AP) and miniature excitatory postsynaptic currents (mEPSC) of SD rat RGCs at postnatal days 7, 14 and 40. The active and passive membrane properties and the synaptic stability (measured by the amplitude, frequency, rise time and decay time of mEPSC) of the RGCs were analyzed using Patchmaster software.</p><p><b>RESULTS</b>Comparison of the RGCs in SD rats across different postnatal ages revealed significant changes in the electrophysiological characteristics of the RGCs during postnatal development. The discharge rate was significantly greater while the AP half-peak width was significantly smaller at postnatal day 15 (P15) than at P7 ( < 0.01), but were both similar between P15 and P40 (=0.086); in terms of the passive membrane properties, the membrane time constant gradually decreased during the development. The frequency of mEPSCs increased significantly over time during postnatal development ( < 0.01), but was similar between P15 and P40 rats.</p><p><b>CONCLUSIONS</b>In SD rats, the membrane properties and synaptic stability of the RGCs undergo alterations following a specific pattern, which highlights a critical period where distinct changes occur in the electrophysiological characteristics of RGCs, followed by gradual stabilization over time. Such changes in the electrophysiological characteristics represent the basic characteristics of RGCs for visual signal processing, and understanding of this mechanism may provide insights into the exact role of the RGC in visual information processing.</p>
