Background Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, prompted heightened surveillance in Shenzhen, China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control measures.Methods From Jan 14 to Feb 12, 2020, the Shenzhen Center for Disease Control and Prevention identified 391 SARS-CoV-2 cases and 1286 close contacts. We compared cases identified through symptomatic surveillance and contact tracing, and estimated the time from symptom onset to confirmation, isolation, and admission to hospital. We estimated metrics of disease transmission and analysed factors influencing transmission risk.Findings Cases were older than the general population (mean age 45 years) and balanced between males (n=187) and females (n=204). 356 (91%) of 391 cases had mild or moderate clinical severity at initial assessment. As of Feb 22, 2020, three cases had died and 225 had recovered (median time to recovery 21 days; 95% CI 20-22). Cases were isolated on average 4•6 days (95% CI 4•1-5•0) after developing symptoms; contact tracing reduced this by 1•9 days (95% CI 1•1-2•7). Household contacts and those travelling with a case were at higher risk of infection (odds ratio 6•27 [95% CI 1•49-26•33] for household contacts and 7•06 [1•43-34•91] for those travelling with a case) than other close contacts. The household secondary attack rate was 11•2% (95% CI 9•1-13•8), and children were as likely to be infected as adults (infection rate 7•4% in children <10 years vs population average of 6•6%). The observed reproductive number (R) was 0•4 (95% CI 0•3-0•5), with a mean serial interval of 6•3 days (95% CI 5•2-7•6).Interpretation Our data on cases as well as their infected and uninfected close contacts provide key insights into the epidemiology of SARS-CoV-2. This analysis shows that isolation and contact tracing reduce the time during which cases are infectious in the community, thereby reducing the R. The overall impact of isolation and contact tracing, however, is uncertain and highly dependent on the number of asymptomatic cases. Moreover, children are at a similar risk of infection to the general population, although less likely to have severe symptoms; hence they should be considered in analyses of transmission and control.

BackgroundRapid spread of SARS-CoV-2 in Wuhan prompted heightened surveillance in Shenzhen and elsewhere in China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control. MethodsThe Shenzhen CDC identified 391 SARS-CoV-2 cases from January 14 to February 12, 2020 and 1286 close contacts. We compare cases identified through symptomatic surveillance and contact tracing, and estimate the time from symptom onset to confirmation, isolation, and hospitalization. We estimate metrics of disease transmission and analyze factors influencing transmission risk. FindingsCases were older than the general population (mean age 45) and balanced between males (187) and females (204). Ninety-one percent had mild or moderate clinical severity at initial assessment. Three have died, 225 have recovered (median time to recovery is 32 days). Cases were isolated on average 4.6 days after developing symptoms; contact tracing reduced this by 1.9 days. Household contacts and those travelling with a case where at higher risk of infection (ORs 6 and 7) than other close contacts. The household secondary attack rate was 15%, and children were as likely to be infected as adults. The observed reproductive number was 0.4, with a mean serial interval of 6.3 days. InterpretationOur data on cases as well as their infected and uninfected close contacts provide key insights into SARS-CoV-2 epidemiology. This work shows that heightened surveillance and isolation, particularly contact tracing, reduces the time cases are infectious in the community, thereby reducing R . Its overall impact, however, is uncertain and highly dependent on the number of asymptomatic cases. We further show that children are at similar risk of infection as the general population, though less likely to have severe symptoms; hence should be considered in analyses of transmission and control.

Background Idiopathic rapid eye movement sleep behavior disorder is an early sign of neurodegenerative disease. This study aimed to quantitatively evaluate iron content in idiopathic rapid eye movement sleep behavior disorder patients using quantitative susceptibility mapping and to examine the potential of this technique to identify the prodromal stage of α‐synucleinopathies. Methods Twenty‐five idiopathic rapid eye movement sleep behavior disorder patients, 32 Parkinson's disease patients, and 50 healthy controls underwent quantitative susceptibility mapping. The mean magnetic susceptibility values within the bilateral substantia nigra, globus pallidus, red nucleus, head of the caudate nucleus, and putamen were calculated and compared among groups. The relationships between the values and the clinical features of idiopathic rapid eye movement sleep behavior disorder and Parkinson's disease were measured using correlation analysis. Results Idiopathic rapid eye movement sleep behavior disorder patients had elevated iron in the bilateral substantia nigra compared with healthy controls. Parkinson's disease patients had increased iron in the bilateral substantia nigra, globus pallidus, and left red nucleus compared with healthy controls and had elevated iron levels in the bilateral substantia nigra compared with idiopathic rapid eye movement sleep behavior disorder patients. Mean magnetic susceptibility values were positively correlated with disease duration in the left substantia nigra in idiopathic rapid eye movement sleep behavior disorder patients. Conclusions Quantitative susceptibility mapping can detect increased iron in the substantia nigra in idiopathic rapid eye movement sleep behavior disorder, which becomes more significant as the disorder progresses. This technique has the potential to be an early objective neuroimaging marker for detecting α‐synucleinopathies. © 2019 International Parkinson and Movement Disorder Society

25Background: Understanding clinical progression of COVID-19 is a key public health priority that 26 informs resource allocation during an emergency. We characterized clinical progression of 27 COVID-19 and determined important predictors for faster clinical progression to key clinical 28 events and longer use of medical resources. 29 Methods and Findings:The study is a single-center, observational study with prospectively 30 collected data from all 420 patients diagnosed with COVID-19 and hospitalized in Shenzhen 31 between January 11 th and March 10 th , 2020 regardless of clinical severity. Using competing risk 32 regressions according to the methods of Fine and Gray, we found that males had faster clinical 33 progression than females in the older age group and the difference could not be explained by 34 difference in baseline conditions or smoking history. We estimated the proportion of cases in 35 each severity stage over 80 days following symptom onset using a nonparametric method built 36 upon estimated cumulative incidence of key clinical events. Based on random survival forest 37 models, we stratified cases into risk sets with very different clinical trajectories. Those who 38 progressed to the severe stage (22%,93/420), developed acute respiratory distress syndrome 39 (9%,39/420), and were admitted to the intensive care unit (5%,19/420) progressed on average 40 9.5 days (95%CI 8.7,10.3), 11.0 days (95%CI 9.7,12.3), and 10.5 days (95%CI 8.2,13.3), 41 respectively, after symptom onset. We estimated that patients who were admitted to ICUs 42 remained there for an average of 34.4 days (95%CI 24.1,43.2). The median length of hospital 43 stay was 21.3 days (95%CI, 20.5,22.2) for cases who did not progress to the severe stage, but 44 increased to 52.1 days (95%CI, 43.3,59.5) for those who required critical care. 45 Conclusions: Our analyses provide insights into clinical progression of cases starting early in 46the course of infection. Patient characteristics near symptom onset both with and without lab 47

Multi‐institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure‐based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI—rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure‐based analysis showed widespread DTI abnormalities in FEP and rs‐fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof‐of‐concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub‐groups.

No abstract

We addressed the relationship between white matter architecture, represented by MRI fractional anisotropy (FA), and cognition in individuals with first-episode psychosis (FEP) by applying for a new methodology that allows whole brain parcellation of core and peripheral white matter in a biologically meaningful fashion. Regionally specific correlations were found in FEP between three specific domains of cognition (processing speed, attention/working memory, and executive functioning) and FA at the deep (cerebral peduncles, sagittal striatum, uncinate, internal/external capsule, cingulum) and peripheral white matter (adjacent to inferior temporal, angular, supramarginal, insula, occipital, rectus gyrus).

Aberrant differentiations of bone mesenchymal stem cells (BMSCs) have proved to be associated with the occurrence of senile osteoporosis. However, mechanisms of this phenomenon relative to abnormal lipid metabolism remain unclear. This study was conducted to characterize the lipidomics alterations during BMSC passaging, aiming at uncovering the aging-related lipid metabolism that may play an important role in aberrant differentiations of BMSCs. Principal component analysis presented the sequential lipidomics alterations during BMSC passaging. The majority of glycerophospholipids, including phosphatidylcholines, phosphatidylethanolamines, phosphatidylglycerols, as well as sphingolipids, revealed significant elevations, whereas the others, including phosphatidic acids, phosphatidylinositols, and phosphatidylserines, presented decreases in aged cells. Double-bond equivalent versus carbon number plots demonstrated that the changing trends and significances of lipids during passaging were associated with the chain length and the degree of unsaturation. In the correlation networks, the scattering patterns of lipid categories suggested the category-related metabolic independence and potential conversion among phosphatidic acids, phosphatidylinositols, and phosphatidylserines. The lipid–enzyme integrated pathway analysis indicated the activated metabolic conversion from phosphatidic acids to CDP-diacylglycerol to phosphatidylinositols and from sphingosine to ceramides to sphingomyelins with BMSC passaging. The conversions among lipid species described the lipidomics responses that potentially induced the aberrant differentiations during BMSC aging.