Thermocline management of stratified tanks for heat storage

Stratified tanks are useful for maximising the thermal energy efficiency of non-continuous and semi-continuous processes. Liquid at two or more dissimilar temperatures is stored within the same tank to provide a buffer for variations in heating and cooling loads. Control of the thermocline between the hot and cold fluid regions is needed to minimise thermocline growth and maximise operation of the storage tank. An experimental programme using a scale model of an industrial stratified tank (aspect ratio 3.5) and Perspex tank (aspect ratio 8.2) is reported. The behaviour and growth of the hot-cold thermocline under various operating conditions is presented. A siphoning method to re-establish the thermocline without interrupting the use of the tank is tested. Siphoning of the thermocline region from either 20%, 50% or 80% of the tank height is an effective strategy for uninterrupted interface re-establishment. However, the rate and position of siphoning and the load balance of the exit streams are critical variables for minimising the time for effective re-establishment of the two temperature zones

Delayed evaluation of combat-related penetrating neck trauma

ObjectiveThe approach to penetrating trauma of the head and neck has undergone significant evolution and offers unique challenges during wartime. Military munitions produce complex injury patterns that challenge conventional diagnosis and management. Mass casualties may not allow for routine exploration of all stable cervical blast injuries. The objective of this study was to review the delayed evaluation of combat-related penetrating neck trauma in patients after evacuation to the United States.MethodFrom February 2003 through April 2005, a series of patients with military-associated penetrating cervical trauma were evacuated to a single institution, prospectively entered into a database, and retrospectively reviewed.ResultsSuspected vascular injury from penetrating neck trauma occurred in 63 patients. Injuries were to zone II in 33%, zone III in 33%, and zone I in 11%. The remaining injuries involved multiple zones, including the lower face or posterior neck. Explosive devices wounded 50 patients (79%), 13 (21%) had high-velocity gunshot wounds, and 19 (30%) had associated intracranial or cervical spine injury. Of the 39 patients (62%) who underwent emergent neck exploration in Iraq or Afghanistan, 21 had 24 injuries requiring ligation (18), vein interposition or primary repair (4), polytetrafluoroethylene (PTFE) graft interposition (1), or patch angioplasty (1). Injuries occurred to the carotid, vertebral, or innominate arteries, or the jugular vein. After evacuation to the United States, all patients underwent radiologic evaluation of the head and neck vasculature. Computed tomography angiography was performed in 45 patients (71%), including six zone II injuries without prior exploration. Forty (63%) underwent diagnostic arteriography that detected pseudoaneurysms (5) or occlusions (8) of the carotid and vertebral arteries. No occult venous injuries were noted. Delayed evaluation resulted in the detection of 12 additional occult injuries and one graft thrombosis in 11 patients. Management included observation (5), vein or PTFE graft repair (3), coil embolization (2), or ligation (1).ConclusionsPenetrating multiple fragment injury to the head and neck is common during wartime. Computed tomography angiography is useful in the delayed evaluation of stable patients, but retained fragments produce suboptimal imaging in the zone of injury. Arteriography remains the imaging study of choice to evaluate for cervical vascular trauma, and its use should be liberalized for combat injuries. Stable injuries may not require immediate neck exploration; however, the high prevalence of occult injuries discovered in this review underscores the need for a complete re-evaluation upon return to the United States

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures

Tyrosine 121 moves revealing a ligandable pocket that couples catalysis to ATP-binding in serine racemase

Human serine racemase (hSR) catalyses racemisation of L-serine to D-serine, the latter of which is a co-agonist of the NMDA subtype of glutamate receptors that are important in synaptic plasticity, learning and memory. In a ‘closed’ hSR structure containing the allosteric activator ATP, the inhibitor malonate is enclosed between the large and small domains while ATP is distal to the active site, residing at the dimer interface with the Tyr121 hydroxyl group contacting the α-phosphate of ATP. In contrast, in ‘open’ hSR structures, Tyr121 sits in the core of the small domain with its hydroxyl contacting the key catalytic residue Ser84. The ability to regulate SR activity by flipping Tyr121 from the core of the small domain to the dimer interface appears to have evolved in animals with a CNS. Multiple X-ray crystallographic enzyme-fragment structures show Tyr121 flipped out of its pocket in the core of the small domain. Data suggest that this ligandable pocket could be targeted by molecules that inhibit enzyme activity

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Mitochondrial Variability as a Source of Extrinsic Cellular Noise

We present a study investigating the role of mitochondrial variability in generating noise in eukaryotic cells. Noise in cellular physiology plays an important role in many fundamental cellular processes, including transcription, translation, stem cell differentiation and response to medication, but the specific random influences that affect these processes have yet to be clearly elucidated. Here we present a mechanism by which variability in mitochondrial volume and functionality, along with cell cycle dynamics, is linked to variability in transcription rate and hence has a profound effect on downstream cellular processes. Our model mechanism is supported by an appreciable volume of recent experimental evidence, and we present the results of several new experiments with which our model is also consistent. We find that noise due to mitochondrial variability can sometimes dominate over other extrinsic noise sources (such as cell cycle asynchronicity) and can significantly affect large-scale observable properties such as cell cycle length and gene expression levels. We also explore two recent regulatory network-based models for stem cell differentiation, and find that extrinsic noise in transcription rate causes appreciable variability in the behaviour of these model systems. These results suggest that mitochondrial and transcriptional variability may be an important mechanism influencing a large variety of cellular processes and properties

Confidence from uncertainty - A multi-target drug screening method from robust control theory

<p>Abstract</p> <p>Background</p> <p>Robustness is a recognized feature of biological systems that evolved as a defence to environmental variability. Complex diseases such as diabetes, cancer, bacterial and viral infections, exploit the same mechanisms that allow for robust behaviour in healthy conditions to ensure their own continuance. Single drug therapies, while generally potent regulators of their specific protein/gene targets, often fail to counter the robustness of the disease in question. Multi-drug therapies offer a powerful means to restore disrupted biological networks, by targeting the subsystem of interest while preventing the diseased network from reconciling through available, redundant mechanisms. Modelling techniques are needed to manage the high number of combinatorial possibilities arising in multi-drug therapeutic design, and identify synergistic targets that are robust to system uncertainty.</p> <p>Results</p> <p>We present the application of a method from robust control theory, Structured Singular Value or μ- analysis, to identify highly effective multi-drug therapies by using robustness in the face of uncertainty as a new means of target discrimination. We illustrate the method by means of a case study of a negative feedback network motif subject to parametric uncertainty.</p> <p>Conclusions</p> <p>The paper contributes to the development of effective methods for drug screening in the context of network modelling affected by parametric uncertainty. The results have wide applicability for the analysis of different sources of uncertainty like noise experienced in the data, neglected dynamics, or intrinsic biological variability.</p

PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data.

Although the majority of bacteria are harmless or even beneficial to their host, others are highly virulent and can cause serious diseases, and even death. Due to the constantly decreasing cost of high-throughput sequencing there are now many completely sequenced genomes available from both human pathogenic and innocuous strains. The data can be used to identify gene families that correlate with pathogenicity and to develop tools to predict the pathogenicity of newly sequenced strains, investigations that previously were mainly done by means of more expensive and time consuming experimental approaches. We describe PathogenFinde

Stochastic Delay Accelerates Signaling in Gene Networks

The creation of protein from DNA is a dynamic process consisting of numerous reactions, such as transcription, translation and protein folding. Each of these reactions is further comprised of hundreds or thousands of sub-steps that must be completed before a protein is fully mature. Consequently, the time it takes to create a single protein depends on the number of steps in the reaction chain and the nature of each step. One way to account for these reactions in models of gene regulatory networks is to incorporate dynamical delay. However, the stochastic nature of the reactions necessary to produce protein leads to a waiting time that is randomly distributed. Here, we use queueing theory to examine the effects of such distributed delay on the propagation of information through transcriptionally regulated genetic networks. In an analytically tractable model we find that increasing the randomness in protein production delay can increase signaling speed in transcriptional networks. The effect is confirmed in stochastic simulations, and we demonstrate its impact in several common transcriptional motifs. In particular, we show that in feedforward loops signaling time and magnitude are significantly affected by distributed delay. In addition, delay has previously been shown to cause stable oscillations in circuits with negative feedback. We show that the period and the amplitude of the oscillations monotonically decrease as the variability of the delay time increases

‘Glocal’ Robustness Analysis and Model Discrimination for Circadian Oscillators

To characterize the behavior and robustness of cellular circuits with many unknown parameters is a major challenge for systems biology. Its difficulty rises exponentially with the number of circuit components. We here propose a novel analysis method to meet this challenge. Our method identifies the region of a high-dimensional parameter space where a circuit displays an experimentally observed behavior. It does so via a Monte Carlo approach guided by principal component analysis, in order to allow efficient sampling of this space. This ‘global’ analysis is then supplemented by a ‘local’ analysis, in which circuit robustness is determined for each of the thousands of parameter sets sampled in the global analysis. We apply this method to two prominent, recent models of the cyanobacterial circadian oscillator, an autocatalytic model, and a model centered on consecutive phosphorylation at two sites of the KaiC protein, a key circadian regulator. For these models, we find that the two-sites architecture is much more robust than the autocatalytic one, both globally and locally, based on five different quantifiers of robustness, including robustness to parameter perturbations and to molecular noise. Our ‘glocal’ combination of global and local analyses can also identify key causes of high or low robustness. In doing so, our approach helps to unravel the architectural origin of robust circuit behavior. Complementarily, identifying fragile aspects of system behavior can aid in designing perturbation experiments that may discriminate between competing mechanisms and different parameter sets