Background:The outbreak of coronavirus-disease-2019 (COVID-19) has rapidly spread to many places outside Wuhan. Previous studies on COVID-19 mostly included older hospitalized-adults. Little information on infectivity among and characteristics of youngsters with COVID-19 is available. Methods: A cluster of 22 close-contacts of a 22-year-old male (Patient-Index) including youngsters with laboratory-confirmed COVID-19 and hospitalized close-contacts testing negative for severe-acuterespiratory-syndrome-coronavirus-2 (SARS-CoV-2) in Anhui Province, China was prospectively-traced. Results: Since January 23, 2020, we enrolled a cluster of eight youngsters with COVID-19 (median age [range], 22 [16-23] years; six males) originating from Patient-Index returning from Wuhan to Hefei on January 19. Patient-Index visited his 16-year-old female cousin in the evening on his return, and met 15 previous classmates in a get-together on January 21. He reported being totally asymptomatic and were described by all his contacts as healthy on January 19-21. His very first symptoms were itchy eyes and fever developed at noon and in the afternoon on January 22, respectively. Seven youngsters (his cousin and six classmates) became infected with COVID-19 after a-few-hour-contact with Patient-Index. None of the patients and contacts had visited Wuhan (except Patient-Index), or had any exposure to wet-markets, wild-animals, or medical-institutes within three months. For affected youngsters, the median incubationperiod was 2 days (range, 1-4). The median serial-interval was 1 day (range, 0-4). Half or more of the eight COVID-19-infected youngsters had fever, cough, sputum production, nasal congestion, and fatigue on admission. All patients had mild conditions. Six patients developed pneumonia (all mild; one bilateral) on admission. As of February 20, four patients were discharged. Conclusions: SARS-CoV-2-infection presented strong infectivity during the incubation-period with rapid transmission in this cluster of youngsters outside Wuhan. COVID-19 developed in these youngsters had fast onset and various nonspecific atypical manifestations, and were much milder than in older patients as previously reported.

Spinal cord injury (SCI), for which there currently is no cure, is a heavy burden on patient physiology and psychology. The microenvironment of the injured spinal cord is complicated. According to our previous work and the advancements in SCI research, ‘microenvironment imbalance’ is the main cause of the poor regeneration and recovery of SCI. Microenvironment imbalance is defined as an increase in inhibitory factors and decrease in promoting factors for tissues, cells and molecules at different times and spaces. There are imbalance of hemorrhage and ischemia, glial scar formation, demyelination and re-myelination at the tissue’s level. The cellular level imbalance involves an imbalance in the differentiation of endogenous stem cells and the transformation phenotypes of microglia and macrophages. The molecular level includes an imbalance of neurotrophic factors and their pro-peptides, cytokines, and chemokines. The imbalanced microenvironment of the spinal cord impairs regeneration and functional recovery. This review will aid in the understanding of the pathological processes involved in and the development of comprehensive treatments for SCI.

Study design: A literature review of worldwide epidemiology of spinal cord injury (SCI). Objectives: To review the epidemiological indicators of SCI, such as incidence, prevalence, demographic characteristics, etiology, level and severity of injury, complications and mortality.

We develop a statistical tool SNVer for calling common and rare variants in analysis of pooled or individual next-generation sequencing (NGS) data. We formulate variant calling as a hypothesis testing problem and employ a binomial–binomial model to test the significance of observed allele frequency against sequencing error. SNVer reports one single overall P-value for evaluating the significance of a candidate locus being a variant based on which multiplicity control can be obtained. This is particularly desirable because tens of thousands loci are simultaneously examined in typical NGS experiments. Each user can choose the false-positive error rate threshold he or she considers appropriate, instead of just the dichotomous decisions of whether to ‘accept or reject the candidates’ provided by most existing methods. We use both simulated data and real data to demonstrate the superior performance of our program in comparison with existing methods. SNVer runs very fast and can complete testing 300 K loci within an hour. This excellent scalability makes it feasible for analysis of whole-exome sequencing data, or even whole-genome sequencing data using high performance computing cluster. SNVer is freely available at http://snver.sourceforge.net/.