ABSTRACT
Rapid and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is one of the most effective measures to control the coronavirus disease 2019 (COVID-19) pandemic. However, there is still lack of an ideal detection platform capable of high sample throughput, portability, and multiplicity. Herein, by combining Hive-Chip (capillary microarray) and reverse transcriptional loop-mediated isothermal amplification (RT-LAMP), we developed an iPad-controlled, high-throughput (48 samples at one run), portable (smaller than a backpack), multiplex (monitoring 8 gene fragments in one reaction), and real-time detection platform for SARS-CoV-2 detection. This platform is composed of a portable Hive-Chip device (HiCube; 32.7 × 29.7 × 20 cm, 5 kg), custom-designed software, and optimized Hive-Chips. RT-LAMP primers targeting seven SARS-CoV-2 genes (S, E, M, N, ORF1ab, ORF3a, and ORF7a) and one positive control (human RNase P) were designed and prefixed in the Hive-Chip. On-chip RT-LAMP showed that the limit of detection (LOD) of SARS-CoV-2 synthetic RNAs is 1 copy/µL, and there is no cross-reaction among different target genes. The platform was validated by 100 clinical samples of SARS-CoV-2, and the results were highly consistent with those of the traditional real-time PCR assay. In addition, on-chip detection of 6 other respiratory pathogens showed no cross-reactivity. Overall, our platform has great potential for fast, accurate, and on-site detection of SARS-CoV-2.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , COVID-19 Testing , Limit of Detection , RNA, Viral/genetics , RNA, Viral/analysisABSTRACT
The long-term effects of COVID-19 on brain structure remain unclear. A prospective study was conducted to explore the changes in brain structure in COVID-19 survivors at one and two years after discharge (COVID-19one, COVID-19two). The difference in gray matter volume (GMV) was analyzed using the voxel-based morphometry method, and correlation analyses were conducted. The dynamic changes in clinical sequelae varied. The GMVs in the cerebellum and vermis were reduced in COVID-19one and COVID-19two, positively correlated with lymphocyte count, and negatively correlated with neutrophil count, neutrophil/lymphocyte ratio (COVID-19one), and systemic immune-inflammation index (COVID-19two). The decreased GMVs in the left middle frontal gyrus, inferior frontal gyrus of the operculum, right middle temporal gyrus, and inferior temporal gyrus returned to normal in COVID-19two. The decreased GMV in the left frontal lobe was negatively correlated with the Athens Insomnia Scale (AIS). The GMV in the left temporal lobe was aggravated in COVID-19two and positively correlated with C-reactive protein. In conclusion, GMV recovery coexisted with injury, which was associated with AIS and inflammatory factors. This may shed some light on the dynamic changes in brain structure and the possible predictors that may be related to GMV changes in COVID-19two.
ABSTRACT
Background and purpose: Long COVID with regard to the neurological system deserves more attention, as a surge of treated patients are being discharged from the hospital. As the dynamic changes in white matter after two years remain unknown, this characteristic was the focus of this study. Methods: We investigated 17 recovered COVID-19 patients at two years after discharge. Diffusion tensor imaging, neurite orientation dispersion and density imaging were performed to identify white matter integrity and changes from one to two years after discharge. Data for 13 revisited healthy controls were collected as a reference. Subscales of the Wechsler Intelligence scale were used to assess cognitive function. Repeated-measures ANOVA was used to detect longitudinal changes in 17 recovered COVID-19 patients and 13 healthy controls after one-year follow-up. Correlations between diffusion metrics, cognitive function, and other clinical characteristics (i.e., inflammatory factors) were also analyzed. Results: Longitudinal analysis showed the recovery trends of large-scale brain regions, with small-scale brain region deterioration from one year to two years after SARS-CoV-2 infection. However, persistent white matter abnormalities were noted at two years after discharge. Longitudinal changes of cognitive function showed no group difference. But cross-sectional cognitive difference between recovered COVID-19 patients and revisited HCs was detected. Inflammation levels in the acute stage correlated positively with white matter abnormalities and negatively with cognitive function. Moreover, the more abnormal the white matter was at two years, the greater was the cognitive deficit present. Conclusion: Recovered COVID-19 patients showed longitudinal recovery trends of white matter. But also had persistent white matter abnormalities at two years after discharge. Inflammation levels in the acute stage may be considered predictors of cognition and white matter integrity, and the white matter microstructure acts as a biomarker of cognitive function in recovered COVID-19 patients. These findings provide an objective basis for early clinical intervention.