Solving the chemical master equation using sliding windows

Background  

The chemical master equation (CME) is a system of ordinary differential equations that describes the evolution of a network of chemical reactions as a stochastic process. Its solution yields the probability density vector of the system at each point in time. Solving the CME numerically is in many cases computationally expensive or even infeasible as the number of reachable states can be very large or infinite. We introduce the sliding window method, which computes an approximate solution of the CME by performing a sequence of local analysis steps. In each step, only a manageable subset of states is considered, representing a "window" into the state space. In subsequent steps, the window follows the direction in which the probability mass moves, until the time period of interest has elapsed. We construct the window based on a deterministic approximation of the future behavior of the system by estimating upper and lower bounds on the populations of the chemical species.     

Structural footprinting in protein structure comparison: the impact of structural fragments

Background

One approach for speeding-up protein structure comparison is the projection approach, where a protein structure is mapped to a high-dimensional vector and structural similarity is approximated by distance between the corresponding vectors. Structural footprinting methods are projection methods that employ the same general technique to produce the mapping: first select a representative set of structural fragments as models and then map a protein structure to a vector in which each dimension corresponds to a particular model and "counts" the number of times the model appears in the structure. The main difference between any two structural footprinting methods is in the set of models they use; in fact a large number of methods can be generated by varying the type of structural fragments used and the amount of detail in their representation. How do these choices affect the ability of the method to detect various types of structural similarity?

Results

To answer this question we benchmarked three structural footprinting methods that vary significantly in their selection of models against the CATH database. In the first set of experiments we compared the methods' ability to detect structural similarity characteristic of evolutionarily related structures, i.e., structures within the same CATH superfamily. In the second set of experiments we tested the methods' agreement with the boundaries imposed by classification groups at the Class, Architecture, and Fold levels of the CATH hierarchy.

Conclusion

In both experiments we found that the method which uses secondary structure information has the best performance on average, but no one method performs consistently the best across all groups at a given classification level. We also found that combining the methods' outputs significantly improves the performance. Moreover, our new techniques to measure and visualize the methods' agreement with the CATH hierarchy, including the threshholded affinity graph, are useful beyond this work. In particular, they can be used to expose a similar composition of different classification groups in terms of structural fragments used by the method and thus provide an alternative demonstration of the continuous nature of the protein structure universe.

     

Absorbing phenomena and escaping time for Muller's ratchet in adaptive landscape

Background

The accumulation of deleterious mutations of a population directly contributes to the fate as to how long the population would exist, a process often described as Muller's ratchet with the absorbing phenomenon. The key to understand this absorbing phenomenon is to characterize the decaying time of the fittest class of the population. Adaptive landscape introduced by Wright, a re-emerging powerful concept in systems biology, is used as a tool to describe biological processes. To our knowledge, the dynamical behaviors for Muller's ratchet over the full parameter regimes are not studied from the point of the adaptive landscape. And the characterization of the absorbing phenomenon is not yet quantitatively obtained without extraneous assumptions as well.

Methods

We describe how Muller's ratchet can be mapped to the classical Wright-Fisher process in both discrete and continuous manners. Furthermore, we construct the adaptive landscape for the system analytically from the general diffusion equation. The constructed adaptive landscape is independent of the existence and normalization of the stationary distribution. We derive the formula of the single click time in finite and infinite potential barrier for all parameters regimes by mean first passage time.

Results

We describe the dynamical behavior of the population exposed to Muller's ratchet in all parameters regimes by adaptive landscape. The adaptive landscape has rich structures such as finite and infinite potential, real and imaginary fixed points. We give the formula about the single click time with finite and infinite potential. And we find the single click time increases with selection rates and population size increasing, decreases with mutation rates increasing. These results provide a new understanding of infinite potential. We analytically demonstrate the adaptive and unadaptive states for the whole parameters regimes. Interesting issues about the parameters regions with the imaginary fixed points is demonstrated. Most importantly, we find that the absorbing phenomenon is characterized by the adaptive landscape and the single click time without any extraneous assumptions. These results suggest a graphical and quantitative framework to study the absorbing phenomenon.

     

Past vegetation dynamics in the Yellowstone region highlight the vulnerability of mountain systems to climate change

Aim

Reconstruct the long‐term ecosystem dynamics of the region across an elevational gradient as they relate to climate and local controls. In particular, we (1) describe the dominant conifers' history; (2) assess changes in vegetation composition and distribution; and (3) note periods of abrupt change versus stability as means of better understanding vegetation responses to environmental variability.

Location

Greater Yellowstone Ecosystem (GYE; USA).

Time period

16.5 ka bp ‐present.

Major taxa studied

Juniperus, Picea, Abies, Pinus, Pseudotsuga.

Methods

The vegetation reconstruction was developed from 15 pollen records. Results were interpreted based on modern pollen–vegetation relationships estimated from a suite of regression‐based approaches.

Results

Calibrated pollen data suggest that late‐glacial vegetation, dominated by shrubs and Juniperus, lacks a modern counterpart in the area. Picea, Abies and Pinus expanded at 16 ka bp in association with postglacial warming and co‐occurred in mixed‐conifer parkland/forest after 12 ka bp . This association along with Pinus contorta forest, which was present after 9 ka bp , has persisted with little change at middle and high elevations to the present day. This stability contrasts with the dynamic history of plant communities at low elevations, where shifts between parkland, steppe and forest over the last 8,000 years were likely driven by variations in effective moisture and fire.

Main conclusions

The postglacial vegetation history of the GYE highlights the dynamic nature of mountain ecosystems and informs on their vulnerability to future climate change: (1) most of the conifers have been present in the area for >12,000 years and survived climate change by adjusting their elevational ranges; (2) some plant associations have exhibited stability over millennia as a result of nonclimatic controls; and (3) present‐day forest cover is elevationally more compressed than at any time in history, probably due to the legacy of the Medieval Climate Anomaly and the Little Ice Age.     

Evolutionary origins of insulin resistance: a behavioral switch hypothesis

Background  

Insulin resistance, which can lead to a number of diseases including type 2 diabetes and coronary heart disease, is believed to have evolved as an adaptation to periodic starvation. The "thrifty gene" and "thrifty phenotype" hypotheses constitute the dominant paradigm for over four decades. With an increasing understanding of the diverse effects of impairment of the insulin signaling pathway, the existing hypotheses are proving inadequate.     

Developmental dynamics of cone photoreceptors in the eel

Background  

Many fish alter their expressed visual pigments during development. The number of retinal opsins expressed and their type is normally related to the environment in which they live. Eels are known to change the expression of their rod opsins as they mature, but might they also change the expression of their cone opsins?     

Contraction-induced injury to the extensor digitorum longus muscles of rats: the role of vitamin E

Van der Meulen, Jack H., Anne McArdle, Malcolm J. Jackson,and John A. Faulkner. Contraction-induced injury to the extensordigitorum longus muscles of rats: the role of vitamin E. J. Appl. Physiol. 83(3): 817-823, 1997.Three days after a protocol of 225 pliometric (lengthening)contractions was administered to in situ extensor digitorum longusmuscles of rats, the force deficit was 64 ± 7% and the percentageof damaged muscle fibers was 38 ± 5% of the control values. Wethen tested the hypothesis that at 3 h and 3 days after the protocol anelevation in the muscle vitamin E content would decrease the forcedeficit, the percentage of damaged muscle fibers, and the serumactivities of creatine kinase and pyruvate kinase. The 5-8 days ofintravenous injections of -tocopherol increased muscle vitamin Econtent threefold compared with vehicle (ethanol)-treated rats. Despite the difference in vitamin E content, the force deficit and number ofdamaged fibers were not different. After the contractionprotocol, the serum creatine kinase and pyruvate kinase activities ofthe vehicle-treated rats increased fourfold at 3 h and twofold at 3 days, whereas the vitamin E-treated rats showed no change. We concludethat vitamin E treatment did not ameliorate either the induction of theinjury or the more severe secondary injury at 3 days.Despite the absence of evidence for an antioxidant function, the lackof any increase in serum enzyme activities for vitamin E-treated ratsat 3 h and 3 days supported a role for vitamin E in the prevention ofenzyme loss after muscle damage.

     

Conceptualising attributional LCA is necessary for resolving methodological issues such as the appropriate form of land use baseline

Purpose

The purposes of this commentary are to further an on-going debate concerning the appropriate form of land use baseline for attributional life cycle assessment (LCA) and to respond to a number of arguments advanced by Soimakallio (Int J Life Cycle Assess 20:1364–1375, 2016). The commentary also seeks to clarify the conceptual nature of attributional LCA.

Methods

The overarching approach for resolving the question of the appropriate form of land use baseline for attributional LCA is to clarify what attributional LCA is seeking to represent, i.e. methodological questions can only be resolved if it is clear what the method is seeking to do. An illustrative example is used to explore the different results produced by ‘natural regeneration’ and ‘natural’ baselines.

Results and discussion

It is proposed that attributional LCA should be conceptualised as an inventory of anthropogenic impacts, conceptually akin to other forms of environmental inventory, such as national GHG inventories. The use of natural regeneration baselines is not consistent with this conceptualisation of attributional LCA, and such baselines necessitate further ad hoc or arbitrary adjustments, such as arbitrary temporal windows or the inconsistent treatment of natural emissions.

Conclusions

The use of natural regeneration baselines may be motivated by the impulse to make attributional LCA both an inventory-type method and an assessment of system-wide change. Pulling attributional LCA in two different directions at once results in a conceptually and methodologically incoherent method. The solution is to recognise attributional LCA as an inventory-type method, which therefore has distinct but complementary uses to consequential LCA, which is an assessment of system-wide change.

     

Identification of gene expression patterns using planned linear contrasts

Background  

In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With the same timing of the initial change, genes which share similar patterns of expression for any number of sampling intervals from the beginning should be considered co-expressed at certain level(s) in the gene networks. In addition, multiple testing problems are complicated in experiments with multi-level treatments when thousands of genes are involved.     

Frequent occurrence of recognition Site-like sequences in the restriction endonucleases

Background  

There are two different theories about the development of the genetic code. Woese suggested that it was developed in connection with the amino acid repertoire, while Crick argued that any connection between codons and amino acids is only the result of an "accident". This question is fundamental to understand the nature of specific protein-nucleic acid interactions.     

Birdcage volume coils and magnetic resonance imaging: a simple experiment for students

Background

This article explains some simple experiments that can be used in undergraduate or graduate physics or biomedical engineering laboratory classes to learn how birdcage volume radiofrequency (RF) coils and magnetic resonance imaging (MRI) work. For a clear picture, and to do any quantitative MRI analysis, acquiring images with a high signal-to-noise ratio (SNR) is required. With a given MRI system at a given field strength, the only means to change the SNR using hardware is to change the RF coil used to collect the image. RF coils can be designed in many different ways including birdcage volume RF coil designs. The choice of RF coil to give the best SNR for any MRI study is based on the sample being imaged.

Results

The data collected in the simple experiments show that the SNR varies as inverse diameter for the birdcage volume RF coils used in these experiments. The experiments were easily performed by a high school student, an undergraduate student, and a graduate student, in less than 3 h, the time typically allotted for a university laboratory course.

Conclusions

The article describes experiments that students in undergraduate or graduate laboratories can perform to observe how birdcage volume RF coils influence MRI measurements. It is designed for students interested in pursuing careers in the imaging field.

     

Medical ethnobotany of the Albanian Alps in Kosovo

Background

The boreal forest of Canada is home to several hundred thousands Aboriginal people who have been using medicinal plants in traditional health care systems for thousands of years. This knowledge, transmitted by oral tradition from generation to generation, has been eroding in recent decades due to rapid cultural change. Until now, published reviews about traditional uses of medicinal plants in boreal Canada have focused either on particular Aboriginal groups or on restricted regions. Here, we present a review of traditional uses of medicinal plants by the Aboriginal people of the entire Canadian boreal forest in order to provide comprehensive documentation, identify research gaps, and suggest perspectives for future research.

Methods

A review of the literature published in scientific journals, books, theses and reports.

Results

A total of 546 medicinal plant taxa used by the Aboriginal people of the Canadian boreal forest were reported in the reviewed literature. These plants were used to treat 28 disease and disorder categories, with the highest number of species being used for gastro-intestinal disorders, followed by musculoskeletal disorders. Herbs were the primary source of medicinal plants, followed by shrubs. The medicinal knowledge of Aboriginal peoples of the western Canadian boreal forest has been given considerably less attention by researchers. Canada is lacking comprehensive policy on harvesting, conservation and use of medicinal plants. This could be explained by the illusion of an infinite boreal forest, or by the fact that many boreal medicinal plant species are widely distributed.

Conclusion

To our knowledge, this review is the most comprehensive to date to reveal the rich traditional medicinal knowledge of Aboriginal peoples of the Canadian boreal forest. Future ethnobotanical research endeavours should focus on documenting the knowledge held by Aboriginal groups that have so far received less attention, particularly those of the western boreal forest. In addition, several critical issues need to be addressed regarding the legal, ethical and cultural aspects of the conservation of medicinal plant species and the protection of the associated traditional knowledge.     

Applying unmixing to gene expression data for tumor phylogeny inference

Background  

While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall into a relatively small number of "sub-types," each characterized a roughly equivalent sequence of mutations by which it progresses in different patients. There is currently great interest in identifying the common sub-types and applying them to the development of diagnostics or therapeutics. Phylogenetic methods have shown great promise for inferring common patterns of tumor progression, but suffer from limits of the technologies available for assaying differences between and within tumors. One approach to tumor phylogenetics uses differences between single cells within tumors, gaining valuable information about intra-tumor heterogeneity but allowing only a few markers per cell. An alternative approach uses tissue-wide measures of whole tumors to provide a detailed picture of averaged tumor state but at the cost of losing information about intra-tumor heterogeneity.     

GeneOrder3.0: Software for comparing the order of genes in pairs of small bacterial genomes

Background  

An increasing number of whole viral and bacterial genomes are being sequenced and deposited in public databases. In parallel to the mounting interest in whole genomes, the number of whole genome analyses software tools is also increasing. GeneOrder was originally developed to provide an analysis of genes between two genomes, allowing visualization of gene order and synteny comparisons of any small genomes. It was originally developed for comparing virus, mitochondrion and chloroplast genomes. This is now extended to small bacterial genomes of sizes less than 2 Mb.     

CNAReporter: a GenePattern pipeline for the generation of clinical reports of genomic alterations

Background

Genomic copy number alterations are widely associated with a broad range of human tumors and offer the potential to be used as a diagnostic tool. Especially in the emerging era of personalized medicine medical informatics tools that allow the fast visualization and analysis of genomic alterations of a patient's genomic profile for diagnostic and potential treatment purposes increasingly gain importance.

Results

We developed CNAReporter, a software tool that allows users to visualize SNP-specific data obtained from Affymetrix arrays and generate PDF-reports as output. We combined standard algorithms for the analysis of chromosomal alterations, utilizing the widely applied GenePattern framework. As an example, we show genome analyses of two patients with distinctly different CNA profiles using the tool.

Conclusions

Glioma subtypes, characterized by different genomic alterations, are often treated differently but can be difficult to differentiate pathologically. CNAReporter offers a user-friendly way to visualize and analyse genomic changes of any given tumor genomic profile, thereby leading to an accurate diagnosis and patient-specific treatment.     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

Modeling and correct the GC bias of tumor and normal WGS data for SCNA based tumor subclonal population inferring

Background

Somatic copy number alternations (SCNAs) can be utilized to infer tumor subclonal populations in whole genome seuqncing studies, where usually their read count ratios between tumor-normal paired samples serve as the inferring proxy. Existing SCNA based subclonal population inferring tools consider the GC bias of tumor and normal sample is of the same fature, and could be fully offset by read count ratio. However, we found that, the read count ratio on SCNA segments presents a Log linear biased pattern, which influence existing read count ratios based subclonal inferring tools performance. Currently no correction tools take into account the read ratio bias.

Results

We present Pre-SCNAClonal, a tool that improving tumor subclonal population inferring by correcting GC-bias at SCNAs level. Pre-SCNAClonal first corrects GC bias using Markov chain Monte Carlo probability model, then accurately locates baseline DNA segments (not containing any SCNAs) with a hierarchy clustering model. We show Pre-SCNAClonal’s superiority to exsiting GC-bias correction methods at any level of subclonal population.

Conclusions

Pre-SCNAClonal could be run independently as well as serving as pre-processing/gc-correction step in conjuntion with exsiting SCNA-based subclonal inferring tools.

     

Forecasting the combined effects of climate and land use change on Mexican bats

Aim

Climate and land use change are among the most important threatening processes driving biodiversity loss, especially in the tropics. Although the potential impacts of each threat have been widely studied in isolation, few studies have assessed the impacts of climate and land cover change in combination. Here, we evaluate the exposure of a large mammalian clade, bats, to multiple scenarios of environmental change and dispersal to understand potential consequences for biodiversity conservation.

Location

Mexico.

Methods

We used ensemble species distribution models to forecast changes in environmental suitability for 130 bat species that occur in Mexico by 2050s under four dispersal assumptions and four combined climate and land use change scenarios. We identified regions with the strongest projected impacts for each scenario and assessed the overlap across scenarios.

Results

The combined effects of climate and land use change will cause an average reduction in environmental suitability for 51% of the species across their range, regardless of scenario. Overall, species show a mean decrease in environmental suitability in at least 46% of their current range in all scenarios of change and dispersal. Climate scenarios had a higher impact on species environmental suitability than land use scenarios. There was a spatial overlap of 43% across the four environmental change scenarios for the regions projected to have the strongest impacts.

Main conclusions

Combined effects of future environmental change may result in substantial declines in environmental suitability for Mexican bats even under optimistic scenarios. This study highlights the vulnerability of megadiverse regions and an indicator taxon to human disturbance. The consideration of combined threats can make an important difference in how we react to changes to conserve our biodiversity as they pose different challenges.

     

Random subwindows and extremely randomized trees for image classification in cell biology

Background

With the improvements in biosensors and high-throughput image acquisition technologies, life science laboratories are able to perform an increasing number of experiments that involve the generation of a large amount of images at different imaging modalities/scales. It stresses the need for computer vision methods that automate image classification tasks.

Results

We illustrate the potential of our image classification method in cell biology by evaluating it on four datasets of images related to protein distributions or subcellular localizations, and red-blood cell shapes. Accuracy results are quite good without any specific pre-processing neither domain knowledge incorporation. The method is implemented in Java and available upon request for evaluation and research purpose.

Conclusion

Our method is directly applicable to any image classification problems. We foresee the use of this automatic approach as a baseline method and first try on various biological image classification problems.