Tracing diagnosis trajectories over millions of patients reveal an unexpected risk in schizophrenia.

The identification of novel disease associations using big-data for patient care has had limited success. In this study, we created a longitudinal disease network of traced readmissions (disease trajectories), merging data from over 10.4 million inpatients through the Healthcare Cost and Utilization Project, which allowed the representation of disease progression mapping over 300 diseases. From these disease trajectories, we discovered an interesting association between schizophrenia and rhabdomyolysis, a rare muscle disease (incidence < 1E-04) (relative risk, 2.21 [1.80-2.71, confidence interval = 0.95], P-value 9.54E-15). We validated this association by using independent electronic medical records from over 830,000 patients at the University of California, San Francisco (UCSF) medical center. A case review of 29 rhabdomyolysis incidents in schizophrenia patients at UCSF demonstrated that 62% are idiopathic, without the use of any drug known to lead to this adverse event, suggesting a warning to physicians to watch for this unexpected risk of schizophrenia. Large-scale analysis of disease trajectories can help physicians understand potential sequential events in their patients

Comprehensive analysis of normal adjacent to tumor transcriptomes.

Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies. However, little is known about the transcriptomic profile of NAT, how it is influenced by the tumor, and how the profile compares with non-tumor-bearing tissues. Here, we integrate data from the Genotype-Tissue Expression project and The Cancer Genome Atlas to comprehensively analyze the transcriptomes of healthy, NAT, and tumor tissues in 6506 samples across eight tissues and corresponding tumor types. Our analysis shows that NAT presents a unique intermediate state between healthy and tumor. Differential gene expression and protein-protein interaction analyses reveal altered pathways shared among NATs across tissue types. We characterize a set of 18 genes that are specifically activated in NATs. By applying pathway and tissue composition analyses, we suggest a pan-cancer mechanism of pro-inflammatory signals from the tumor stimulates an inflammatory response in the adjacent endothelium

Analysis of the TMT mount control system

The TMT mount control system provides telescope pointing and tracking. Requirements include wind disturbance rejection, offsetting time and accuracy, control system robustness, and the magnitude of response at structural resonances. A finite element model of the complete telescope has been developed and the transfer functions used for the control designs are presented. Wind disturbance, encoder, and wave-front-sensor models are presented that are used for the control design. A performance analysis translates the requirements to a required bandwidth. Achieving this bandwidth is important for reducing telescope image motion due to wind-buffeting. A mount control design is presented that meets the demanding requirements by maximizing low frequency gain and using structural filters to roll-off structural modes. The control system analysis includes an outer guide loop using a wave front sensor. Offsetting time and accuracy requirements are satisfied using feed-forward control architecture

Control analysis of the TMT primary segment assembly

The primary mirror control system (M1CS) stabilizes the 492 segments of the Thirty Meter Telescope primary mirror in the presence of disturbances. Each Primary Segment Assembly (PSA) has three actuators and position sensors that control the piston, tip, and tilt of the mirror segment. Requirements for the PSA position controller are presented, with the main requirements being 10 Newton per micron stiffness below one Hertz, where wind is the primary disturbance. Bandwidths of the PSA position controller of about twenty Hertz, assuming a soft actuator, are needed to meet this requirement. A finite element model of the PSA was developed and used for a preliminary control design. PSA structural modes at 40, 90, and 120 impact the control design. We have studied control designs with different actuators, sensors, and structural filters in order to assess disturbance rejection properties and interactions with the PSA structural modes. The performance requirements are achieved using voice coil actuators with modal control architecture for piston, tip, and tilt. Force interactions with the underlying mirror cell are important, and we present the status of our studies of the control structure interaction effect (CSIE). A related paper presents further analysis of the CSIE and MICS global position control loop

Organic-Matter Loading Determines Regime Shifts and Alternative States in an Aquatic Ecosystem

Slow changes in underlying state variables can lead to “tipping points,” rapid transitions between alternative states (“regime shifts”) in a wide range of complex systems. Tipping points and regime shifts routinely are documented retrospectively in long time series of observational data. Experimental induction of tipping points and regime shifts is rare, but could lead to new methods for detecting impending tipping points and forestalling regime shifts. By using controlled additions of detrital organic matter (dried, ground arthropod prey), we experimentally induced a shift from aerobic to anaerobic states in a miniature aquatic ecosystem: the self-contained pools that form in leaves of the carnivorous northern pitcher plant, Sarracenia purpurea. In unfed controls, the concentration of dissolved oxygen ($[O_2]$) in all replicates exhibited regular diurnal cycles associated with daytime photosynthesis and nocturnal plant respiration. In low prey-addition treatments, the regular diurnal cycles of $[O_2]$ were disrupted, but a regime shift was not detected. In high prey-addition treatments, the variance of the $[O_2]$ time series increased until the system tipped from an aerobic to an anaerobic state. In these treatments, replicate $[O_2]$ time series predictably crossed a tipping point at ∼45 h as $[O_2]$ was decoupled from diurnal cycles of photosynthesis and respiration. Increasing organic-matter loading led to predictable changes in $[O_2]$ dynamics, with high loading consistently driving the system past a well-defined tipping point. The Sarracenia microecosystem functions as a tractable experimental system in which to explore the forecasting and management of tipping points and alternative regimes.Organismic and Evolutionary Biolog

Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types.

Cancer cell lines are a cornerstone of cancer research but previous studies have shown that not all cell lines are equal in their ability to model primary tumors. Here we present a comprehensive pan-cancer analysis utilizing transcriptomic profiles from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia to evaluate cell lines as models of primary tumors across 22 tumor types. We perform correlation analysis and gene set enrichment analysis to understand the differences between cell lines and primary tumors. Additionally, we classify cell lines into tumor subtypes in 9 tumor types. We present our pancreatic cancer results as a case study and find that the commonly used cell line MIA PaCa-2 is transcriptionally unrepresentative of primary pancreatic adenocarcinomas. Lastly, we propose a new cell line panel, the TCGA-110-CL, for pan-cancer studies. This study provides a resource to help researchers select more representative cell line models