There is growing evidence that severe acute respiratory syndrome coronavirus 2 can affect the CNS. However, data on white matter and cognitive sequelae at the one-year follow-up are lacking. Therefore, we explored these characteristics in this study. We investigated 22 recovered coronavirus disease 2019 (COVID-19) patients and 21 matched healthy controls. Diffusion tensor imaging, diffusion kurtosis imaging and neurite orientation dispersion and density imaging were performed to identify white matter changes, and the subscales of the Wechsler Intelligence scale were used to assess cognitive function. Correlations between diffusion metrics, cognitive function, and other clinical characteristics were then examined. We also conducted subgroup analysis based on patient admission to the intensive care unit. The corona radiata, corpus callosum and superior longitudinal fasciculus had lower volume fraction of intracellular water in the recovered COVID-19 group than in the healthy control group. Patients who had been admitted to the intensive care unit had lower fractional anisotropy in the body of the corpus callosum than those who had not. Compared with the healthy controls, the recovered COVID-19 patients demonstrated no significant decline in cognitive function. White matter tended to present with fewer abnormalities for shorter hospital stays and longer follow-up times. Lower axonal density was detected in clinically recovered COVID-19 patients after one year. Patients who had been admitted to the intensive care unit had slightly more white matter abnormalities. No significant decline in cognitive function was found in recovered COVID-19 patients. The duration of hospital stay may be a predictor for white matter changes at the one-year follow-up.

Background: Neither a vaccine nor specific therapeutic drugs against 2019 novel coronavirus have been developed. Some studies have shown that Xuebijing injection (XBJ) can exert an anti-inflammatory effect by inhibiting the production of interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and other cytokines.This study aimed to investigate the effect of XBJ on coronavirus disease 2019 (COVID-19) and its effects on IL-6 and tumor necrosis alpha TNF-α.Methods: A total of 42 patients, who were diagnosed with COVID-19 and treated with XBJ combined with routine treatment at Chongqing University Three Gorges Hospital between January 20, 2020, and March 11, 2020, were selected as the observation group. A control group comprising 16 patients who received routine treatment was also established, and cases were matched from the observation group on a 1:1 basis according to age, comorbidities, and mild and severe disease. The clinical symptoms, laboratory test indexes, and changes in computed tomography (CT) scans of patients in the two groups were observed at the time of admission and 7 days after treatment, and the time taken for the patients to produce a negative nucleic acid test was also recorded.Results: There were no significant differences in baseline data between the two groups. After treatment, there were significant improvements in IL-6 levels and body temperature in the observation group as compared with the control group. Particularly in severe patients, the reduction in body temperature in the observation group was greater than that in the control group (P<0.05). A higher number of patients in the observation group showed improved CT imaging results compared with the control group, and the time taken to produce a negative nucleic acid test was shorter in the observation group than in the control group;

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Background: The focus of neuro-oncology research has changed from histopathologic grading to molecular characteristics, and medical imaging routinely follows this change. Purpose: To compare the diagnostic performance of amide proton transfer (APT) and four diffusion models in gliomas grading and isocitrate dehydrogenase (IDH) genotype. Study Type: Prospective. Population: A total of 62 participants (37 males, 25 females; mean age, 52 AE 13 years) whose IDH genotypes were mutant in 6 of 14 grade II gliomas, 8 of 20 of grade III gliomas, and 4 of 28 grade IV gliomas. Field Strength/Sequence: APT imaging using sampling perfection with application optimized contrasts by using different flip angle evolutions (SPACE) and DWI with q-space Cartesian grid sampling were acquired at 3 T. Assessment: The ability of diffusion kurtosis imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging (NODDI), mean apparent propagator (MAP), and APT imaging for glioma grade and IDH status were assessed, with histopathological grade and genetic testing used as a reference standard. Regions of interest (ROIs) were drawn by two neuroradiologists after consensus. Statistical Tests: T-test and Mann-Whitney U test; one-way analysis of variance (ANOVA); receiver operating curve (ROC) and area under the curve (AUC); DeLong test. P value < 0.05 was considered statistically significant. Results: Compared with IDH-mutant gliomas, IDH-wildtype gliomas showed a significantly higher mean, 5th-percentile (APT 5 ), and 95th-percentile from APTw, the 95th-percentile value of axial, mean, and radial diffusivity from DKI, and 95thpercentile value of isotropic volume fraction from NODDI, and no significantly different parameters from DTI and MAP (P = 0.075-0.998). The combined APT model showed a significantly wider area under the curve (AUC 0.870) for IDH status, when compared with DKI and NODDI. APT 5 was significantly different between two of the three groups (glioma II vs. glioma III vs. glioma IV: 1.35 AE 0.75 vs. 2.09 AE 0.93 vs. 2.71 AE 0.81). Data conclusion: APT has higher diagnostic accuracy than DTI, DKI, MAP, and NODDI in glioma IDH genotype. APT 5 can effectively identify both tumor grading and IDH genotyping, making it a promising biomarker for glioma classification.

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Introduction: Acute cerebellar ataxia (ACA) is the most common form of pediatric ataxia. Changes in gut flora can modulate the nervous system, influencing brain function via the gut-brain axis (GBA). This study aimed to illustrate the relationship between intestinal microbiota and ACA.Method: A total of 30 and 12 children were randomly sampled from history of intestinal surgery (HOIS) and no intestinal surgery groups (NHOIS), respectively. In addition, 10 healthy children who sought physical examination in Children's Hospital of Nanjing Medical University were recruited as a control group. The stool samples were 16S rRNA detected.Results: We observed that many ACA children had intestinal surgery history prior to the onset of ACA. The 16S rRNA sequencing indicated that HOIS and control groups were well-distinguished by principal component analysis. The discrepancy between HOIS and NHOIS groups were also displayed by principal component analysis score plot. However, no differences were found between NHOIS and control groups. The results of student's t-test were consistent with principal component analysis. A total of nine different genera were identified between HOIS and control groups. Five genera and a phylum showed significant differences between HOIS and NHOIS groups.Conclusion: Altered genera and phyla associated with ACA were identified. Our findings provide new insight into treating and preventing ACA.