Alterations in whole-brain dynamic functional stability during memory tasks under dexmedetomidine sedation.

Purpose: This study aimed to explore the neurological effects of dexmedetomidine-induced sedation on memory using functional stability, a whole-brain voxel-wise dynamic functional connectivity approach. Methods: A total of 16 participants (10 men) underwent auditory memory task-related fMRI in the awake state and under dexmedetomidine sedation. Explicit and implicit memory tests were conducted 4 h after ceasing dexmedetomidine administration. One-sample Wilcoxon signed rank test was applied to determine the formation of explicit and implicit memory in the two states. Functional stability was calculated and compared voxel-wise between the awake and sedated states. The association between functional stability and memory performance was also assessed. Results: In the awake baseline tests, explicit and implicit memory scores were significantly different from zero (p < 0.05). In the tests under sedation, explicit and implicit memory scores were not significantly different from zero. Compared to that at wakeful baseline, functional stability during light sedation was reduced in the medial prefrontal cortex, left angular gyrus, and right hippocampus (all clusters, p < 0.05, GRF-corrected), whereas the left superior temporal gyrus exhibited higher functional stability (cluster p < 0.05, GRF-corrected). No significant associations were observed between functional stability and memory test scores. Conclusions: The distribution and patterns of alterations in functional stability during sedation illustrate the modulation of functional architecture by dexmedetomidine from a dynamic perspective. Our findings provide novel insight into the dynamic brain functional networks underlying consciousness and memory in humans.

[Characteristics and composition of vegetation carbon storage in natural grassland in Ning-xia, China.] / 宁夏天然草地植被碳储量特征及构成.

We measured the total vegetation carbon stock in the widely distributed natural grassland of meadow steppe (MS), warm steppe (WS), steppe desert (SD) and desert steppe (DS)] in Ningxia, using survey and sampling method. The results showed that the average carbon rate of vege-tation, shrubs and root were 0.40, and that of litter was 0.39. The total vegetation carbon density of meadow steppe, warm steppe, steppe desert and desert steppe (including aboveground vegetation, litter and roots) was 470.26, 192.23, 117.17 and 83.36 g·m-2, while that of aboveground vegetation was 87.35, 68.50, 59.32 and 40.05 g·m-2, and that of roots was 344.29, 108.83, 50.65 and 30.29 g·m-2, litter carbon storage was 38.62,14.91, 7.19 and 13.03 g·m-2, respectively. The order of those grassland types ranked as MS＞WS＞SD＞DS. Root carbon storage contributed the most to carbon storage in meadow steppe and warm steppe, and aboveground vegetation carbon storage contributed the most to steppe desert and desert steppe. Root carbon storage showed a decreasing trend with the increases of soil depth within 40 cm soil layer. For the spatial distribution of total carbon stock, the southern part of meadow steppe and temperate steppe had obviously higher carbon stock than the middle and north part of desert steppe and steppe desert.

[Carbon sequestration characteristics of typical temperate natural grasslands in Ningxia, China]. / å®å¤å ¸åž‹æ¸©æ€§å¤©ç„¶è‰åœ°å›ºç¢³ç‰¹å¾.

To accurately estimate ecosystem carbon storage of natural grassland in Ningxia, we examined ecosystem carbon storage in four types of typical temperate natural grasslands, including meadow steppe, warm steppe, steppe desert, and desert steppe in Ningxia. The results showed that the total vegetation biomass of meadow steppe, warm steppe, steppe desert and desert steppe were 1178.91, 481.22, 292.80 and 209.09 g·m-2, respectively. Root biomass was the main component of total vegetation biomass of meadow steppe and warm steppe, with a contribution of 73.1% and 56.6%, respectively. Aboveground biomass was the main component of total vegetation biomass of steppe desert and desert steppe, accounting for 50.3% and 47.6%, respectively. Litter made low contribution, being 8.5%, 8.0%, 6.4% and 16.2%, respectively. Ecosystem carbon storage of four typical natural grassland was 13.90, 5.94, 2.69 and 2.37 kg·m-2, vegetation carbon storage was 470.26, 192.23, 117.17 and 83.36 g·m-2, and soil organic carbon storage in 0-40 cm layers were 13.43, 5.75, 2.58 and 2.29 kg·m-2, respectively. Soil organic carbon storage was the main body of the total carbon storage of four typical natural grassland in Ningxia, accounting for 96.6%, 96.8%, 95.6% and 96.5%, respectively. The total vegetation biomass, vegetation carbon storage, soil organic carbon storage and ecosystem carbon storage of four natural grassland types were in the order of meadow steppe＞warm steppe＞steppe desert＞desert steppe.

Diagnostic performance between CT and initial real-time RT-PCR for clinically suspected 2019 coronavirus disease (COVID-19) patients outside Wuhan, China.

INTRODUCTION: Chest CT is thought to be sensitive but less specific in diagnosing the 2019 coronavirus disease (COVID-19). The diagnostic value of CT is unclear. We aimed to compare the performance of CT and initial RT-PCR for clinically suspected COVID-19 patients outside the epicentre-Wuhan, China. MATERIALS AND METHODS: Patients clinically suspected of COVID-19 infection who underwent initial RT-PCR and chest CT at the same time were retrospectively enrolled. Two radiologists with specific training reviewed the CT images independently and final diagnoses of the presence or absence of COVID-19 was reached by consensus. With serial RT-PCR as reference standard, the performance of initial RT-PCR and chest CT was analysed. A strategy of combining initial RT-PCR and chest CT was analysed to study the additional benefit. RESULTS: 82 patients admitted to hospital between Jan 10, 2020 to Feb 28, 2020 were enrolled. 34 COVID-19 and 48 non-COVID-19 patients were identified by serial RT-PCR. The sensitivity, specificity was 79% (27/34) and 100% (48/48) for initial RT-PCR and 77% (26/34) and 96% (46/48) for chest CT. The image readers had a good interobserver agreement with Cohen's kappa of 0.69. No statistical difference was found in the diagnostic performance between initial RT-PCR and chest CT. The comprehensive strategy had a higher sensitivity of 94% (32/34). CONCLUSIONS: Initial RT-PCR and chest CT had comparable diagnostic performance in identification of suspected COVID-19 patients outside the epidemic center. To compensate potential risk of false-negative PCR, chest CT should be applied for clinically suspected patients with negative initial RT-PCR.