The interactions between proteins, DNA, and RNA in living cells constitute molecular networks that govern various cellular functions. To investigate the global dynamical properties and stabilities of such networks, we studied the cell-cycle regulatory network of the budding yeast. With the use of a simple dynamical model, it was demonstrated that the cell-cycle network is extremely stable and robust for its function. The biological stationary state, the G1 state, is a global attractor of the dynamics. The biological pathway, the cell-cycle sequence of protein states, is a globally attracting trajectory of the dynamics. These properties are largely preserved with respect to small perturbations to the network. These results suggest that cellular regulatory networks are robustly designed for their functions. Despite the complex environment in and outside of the cell, various cellular functions are carried out reliably by the underlying biomolecular networks. How is the stability of a cell state achieved? How can a biological pathway take the cell from one state to another reliably? Evolution must have played a crucial role in the selection of the architectures of these networks for them to have such a remarkable property. Much attention has recently been focused on the ''topological'' properties of largescale networks (1-5). It was argued that a power-law distribution of connectivity, which is apparent for some bionetworks (2, 4), is more tolerable against random failure (1). Here we address this question from a dynamic systems point of view. We study the network regulating the cell cycle of the budding yeast, investigating its global dynamical property and stability. We find that the stationary states of the cell, or states at the checkpoints in general, correspond to global attractors of the dynamics: almost all initial protein states flow to these biological stationary states. Furthermore, the biological pathway of the cell-cycle sequence, which is a particular trajectory in the state space, is a globally stable and attracting trajectory of the dynamics. These dynamic properties, arising from the underlying network connection, are also robust against small perturbations to the network. They are directly responsible for the robustness of the cellular process. The Yeast Cell-Cycle NetworkThe cell-cycle process, by which one cell grows and divides into two daughter cells, is a vital biological process the regulation of which is highly conserved among the eukaryotes (6). The process consists of four phases: G 1 (in which the cell grows and, under appropriate conditions, commits to division), S (in which the DNA is synthesized and chromosomes replicated), G 2 (a ''gap'' between S and M), and M (in which chromosomes are separated and the cell is divided into two). After the M phase, the cell enters the G 1 phase, hence completing a ''cycle.'' The process has been studied in great detail in the budding yeast Saccharomyces cerevisiae, a single-cell model eukaryotic organism (see supporting information, which is publishe...

The WORMS method described in this report provides multi-feature, whole-organ assessment of the knee in OA using conventional MR images, and shows high inter-observer agreement among trained readers. This method may be useful in epidemiological studies and clinical trials of OA.

SignificanceA high-quality genome assembly of Camellia sinensis var. sinensis facilitates genomic, transcriptomic, and metabolomic analyses of the quality traits that make tea one of the world’s most-consumed beverages. The specific gene family members critical for biosynthesis of key tea metabolites, monomeric galloylated catechins and theanine, are indicated and found to have evolved specifically for these functions in the tea plant lineage. Two whole-genome duplications, critical to gene family evolution for these two metabolites, are identified and dated, but are shown to account for less amplification than subsequent paralogous duplications. These studies lay the foundation for future research to understand and utilize the genes that determine tea quality and its diversity within tea germplasm.

Information technology is generally considered an enabler of a firm's agility. A typical premise is that greater IT investment enables a firm to be more agile. However, it is not uncommon that IT can also hinder and sometimes even impede organizational agility. We propose and theorize this frequently observed but understudied IT-agility contradiction by which IT may enable or impede agility. We develop the premise that organizations need to develop superior firm-wide IT capability to successfully manage their IT resources to realize agility. We refine the conceptualization and measurement of IT capability as a latent construct reflected in its three dimensions: IT infrastructure capability, IT business spanning capability, and IT proactive stance. We also conceptualize two types of organizational agility: market capitalizing agility and operational adjustment agility. We then conduct a matched-pair field survey of business and information systems executives in 128 organizations to empirically examine the link between a firm's IT capability and agility. Business executives responded to measurement scales of the two types of agility and organizational context variables, and IS executives responded to measurement scales of IT capabilities and IS context variables. The results show a significant positive relationship between IT capability and the two types of organizational agility. We also find a significant positive joint effect of IT capability and IT spending on operational adjustment agility but not on market capitalizing agility. The findings suggest a possible resolution to the contradictory effect of IT on agility: while more IT spending does not lead to greater agility, spending it in such a way as to enhance and foster IT capabilities does. Our study provides initial empirical evidence to better understand essential IT capabilities and their relationship with organizational agility. Our findings provide a number of useful implications for research and managerial practices.

S. Chatrchyan et al. * (CMS Collaboration)

Assessment of precision errors in bone mineral densitometry is important for characterization of a technique's ability to detect longitudinal skeletal changes. Short-term and long-term precision errors should be calculated as root-mean-square (RMS) averages of standard deviations of repeated measurements (SD) and standard errors of the estimate of changes in bone density with time (SEE), respectively. Inadequate adjustment for degrees of freedom and use of arithmetic means instead of RMS averages may cause underestimation of true imprecision by up to 41% and 25% (for duplicate measurements), respectively. Calculation of confidence intervals of precision errors based on the number of repeated measurements and the number of subjects assessed serves to characterize limitations of precision error assessments. Provided that precision error are comparable across subjects, examinations with a total of 27 degrees of freedom result in an upper 90% confidence limit of +30% of the mean precision error, a level considered sufficient for characterizing technique imprecision. We recommend three (or four) repeated measurements per individual in a subject group of at least 14 individuals to characterize short-term (or long-term) precision of a technique.

We measured cortical and trabecular bone loss using QCT of the spine and hip in 14 crewmembers making 4-to 6-month flights on the International Space Station. There was no compartmentspecific loss of bone in the spine. Cortical bone mineral loss in the hip occurred primarily by endocortical thinning. Introduction:In an earlier study, areal BMD (aBMD) measurements by DXA showed that cosmonauts making flights of 4-to 12-month duration on the Soviet/Russian MIR spacecraft lost bone at an average rate of 1%/month from the spine and 1.5%/month from the hip. However, because DXA measurements represent the sum of the cortical and trabecular compartments, there is no direct information on how these bone envelopes are affected by spaceflight. Materials and Methods: To address this, we performed a study of crewmembers (13 males and 1 female; age range, 40 -55 years) on long-duration missions (4 -6 months) on the International Space Station (ISS). We used DXA to obtain aBMD of the hip and spine and volumetric QCT (vQCT) to assess integral, cortical, and trabecular volumetric BMD (vBMD) in the hip and spine. In the heel, DXA was used to measure aBMD, and quantitative ultrasound (QUS) was used to measure speed of sound (SOS) and broadband ultrasound attenuation (BUA). Results and Conclusions: aBMD was lost at rates of 0.9%/month at the spine (p Ͻ 0.001) and 1.4 -1.5%/month at the hip (p Ͻ 0.001). Spinal integral vBMD was lost at a rate of 0.9%/month (p Ͻ 0.001), and trabecular vBMD was lost at 0.7%/month (p Ͻ 0.05). In contrast to earlier reports, these changes were generalized across the vertebrae and not focused in the posterior elements. In the hip, integral, cortical, and trabecular vBMD was lost at rates of 1.2-1.5%/month (p Ͻ 0.0001), 0.4 -0.5%/month (p Ͻ 0.01), and 2.2-2.7%/month (p Ͻ 0.001), respectively. The cortical bone loss in the hip occurred primarily by cortical thinning. Calcaneal aBMD measurements by DXA showed smaller mean losses (0.4%/month) than hip or spine measurements, with SOS and BUA showing no change. In summary, our results show that ISS crewmembers, on average, experience substantial loss of both trabecular and cortical bone in the hip and somewhat smaller losses in the spine. These results do not support the use of calcaneal aBMD or QUS measurements as surrogate measures to estimate changes in the central skeleton.

Background As of June 8, 2020, the global reported number of COVID-19 cases had reached more than 7 million with over 400 000 deaths. The household transmissibility of the causative pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains unclear. We aimed to estimate the secondary attack rate of SARS-CoV-2 among household and non-household close contacts in Guangzhou, China, using a statistical transmission model. Methods In this retrospective cohort study, we used a comprehensive contact tracing dataset from the Guangzhou Center for Disease Control and Prevention to estimate the secondary attack rate of COVID-19 (defined as the probability that an infected individual will transmit the disease to a susceptible individual) among household and non-household contacts, using a statistical transmission model. We considered two alternative definitions of household contacts in the analysis: individuals who were either family members or close relatives, such as parents and parents-in-law, regardless of residential address, and individuals living at the same address regardless of relationship. We assessed the demographic determinants of transmissibility and the infectivity of COVID-19 cases during their incubation period. Findings Between Jan 7, 2020, and Feb 18, 2020, we traced 195 unrelated close contact groups (215 primary cases, 134 secondary or tertiary cases, and 1964 uninfected close contacts). By identifying households from these groups, assuming a mean incubation period of 5 days, a maximum infectious period of 13 days, and no case isolation, the estimated secondary attack rate among household contacts was 12·4% (95% CI 9·8–15·4) when household contacts were defined on the basis of close relatives and 17·1% (13·3–21·8) when household contacts were defined on the basis of residential address. Compared with the oldest age group (≥60 years), the risk of household infection was lower in the youngest age group (<20 years; odds ratio [OR] 0·23 [95% CI 0·11–0·46]) and among adults aged 20–59 years (OR 0·64 [95% CI 0·43–0·97]). Our results suggest greater infectivity during the incubation period than during the symptomatic period, although differences were not statistically significant (OR 0·61 [95% CI 0·27–1·38]). The estimated local reproductive number ( R ) based on observed contact frequencies of primary cases was 0·5 (95% CI 0·41–0·62) in Guangzhou. The projected local R , had there been no isolation of cases or quarantine of their contacts, was 0·6 (95% CI 0·49–0·74) when household was defined on the basis of close relatives. Interpretation SARS-CoV-2 is more transmissible in households than SARS-CoV and Middle East respiratory syndrome coronavirus. Older individuals (aged ≥60 years) are the most susceptible to household transmission of SARS-CoV-2. In addition to case finding and isolation, timely tracing and quarantine of close contac...