Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging

In dynamic Positron Emission Tomography (PET), an estimate of the radio activity concentration is obtained from a series of frames of sinogram data taken at ranging in duration from 10 seconds to minutes under some criteria. So far, all the well-known reconstruction algorithms require known data statistical properties. It limits the speed of data acquisition, besides, it is unable to afford the separated information about the structure and the variation of shape and rate of metabolism which play a major role in improving the visualization of contrast for some requirement of the diagnosing in application. This paper presents a novel low rank-based activity map reconstruction scheme from emission sinograms of dynamic PET, termed as SLCR representing Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging. In this method, the stationary background is formulated as a low rank component while variations between successive frames are abstracted to the sparse. The resulting nuclear norm and l ₁ norm related minimization problem can also be efficiently solved by many recently developed numerical methods. In this paper, the linearized alternating direction method is applied. The effectiveness of the proposed scheme is illustrated on three data sets.     

Augmented sparse reconstruction of protein signaling networks

The problem of reconstructing and identifying intracellular protein signaling and biochemical networks is of critical importance in biology. We propose a mathematical approach called augmented sparse reconstruction for the identification of links among nodes of ordinary differential equation (ODE) networks, given a small set of observed trajectories with various initial conditions. As a test case, the method is applied to the epidermal growth factor receptor (EGFR) driven signaling cascade, a well-studied and clinically important signaling network. Our method builds a system of representation from a collection of trajectory integrals, selectively attenuating blocks of terms in the representation. The system of representation is then augmented with random vectors, and l₁ minimization is used to find sparse representations for the dynamical interactions of each node. After showing the performance of our method on a model of the EGFR protein network, we sketch briefly the potential future therapeutic applications of this approach.     

Metasample-based sparse representation for tumor classification

A reliable and accurate identification of the type of tumors is crucial to the proper treatment of cancers. In recent years, it has been shown that sparse representation (SR) by l1-norm minimization is robust to noise, outliers and even incomplete measurements, and SR has been successfully used for classification. This paper presents a new SR-based method for tumor classification using gene expression data. A set of metasamples are extracted from the training samples, and then an input testing sample is represented as the linear combination of these metasamples by l1-regularized least square method. Classification is achieved by using a discriminating function defined on the representation coefficients. Since l1-norm minimization leads to a sparse solution, the proposed method is called metasample-based SR classification (MSRC). Extensive experiments on publicly available gene expression data sets show that MSRC is efficient for tumor classification, achieving higher accuracy than many existing representative schemes.     

Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules

It is believed that energy efficiency is an important constraint in brain evolution. As synaptic transmission dominates energy consumption, energy can be saved by ensuring that only a few synapses are active. It is therefore likely that the formation of sparse codes and sparse connectivity are fundamental objectives of synaptic plasticity. In this work we study how sparse connectivity can result from a synaptic learning rule of excitatory synapses. Information is maximised when potentiation and depression are balanced according to the mean presynaptic activity level and the resulting fraction of zero-weight synapses is around 50%. However, an imbalance towards depression increases the fraction of zero-weight synapses without significantly affecting performance. We show that imbalanced plasticity corresponds to imposing a regularising constraint on the L ₁-norm of the synaptic weight vector, a procedure that is well-known to induce sparseness. Imbalanced plasticity is biophysically plausible and leads to more efficient synaptic configurations than a previously suggested approach that prunes synapses after learning. Our framework gives a novel interpretation to the high fraction of silent synapses found in brain regions like the cerebellum.     

Compression dynamics of quasi-spherical wire arrays with different linear mass profiles

Results of experimental studies of the implosion of quasi-spherical wire (or metalized fiber) arrays are presented. The goal of the experiments was to achieve synchronous three-dimensional compression of the plasma produced in different regions of a quasi-spherical array into its geometrical center. To search for optimal synchronization conditions, quasi-spherical arrays with different initial profiles of the linear mass were used. The following dependences of the linear mass on the poloidal angle were used: m _l (θ) ∝ sin^–1θ and m _l (θ) ∝ sin^–2θ. The compression dynamics of such arrays was compared with that of quasi-spherical arrays without linear mass profiling, m _l (θ) = const. To verify the experimental data, the spatiotemporal dynamics of plasma compression in quasi-spherical arrays was studied using various diagnostics. The experiments on three-dimensional implosion of quasi-spherical arrays made it possible to study how the frozen-in magnetic field of the discharge current penetrates into the array. By measuring the magnetic field in the plasma of a quasi-spherical array, information is obtained on the processes of plasma production and formation of plasma flows from the wire/fiber regions with and without an additionally deposited mass. It is found that penetration of the magnetic flux depends on the initial linear mass profile m _l (θ) of the quasi-spherical array. From space-resolved spectral measurements and frame imaging of plasma X-ray emission, information is obtained on the dimensions and shape of the X-ray source formed during the implosion of a quasi-spherical array. The intensity of this source is estimated and compared with that of the Z-pinch formed during the implosion of a cylindrical array.     

Resolution and noise performance of sparse view X-ray CT reconstruction via Lp-norm regularization

ObjectivesAdaptive steepest descent projection onto convex sets (ASD-POCS) algorithms with Lp-norm (0 < p ≤ 1) regularization have shown great promise in sparse-view X-ray CT reconstruction. However, the difference in p value selection can lead to varying algorithm performance of noise and resolution. Therefore, it is imperative to develop a reliable method to evaluate the resolution and noise properties of the ASD-POCS algorithms under different Lp-norm priors.MethodsA comparative performance evaluation of ASD-POCS algorithms under different Lp-norm (0 < p ≤ 2) priors were performed in terms of modulation transfer function (MTF), noise power spectrum (NPS) and noise equivalent quanta (NEQ). Simulation data sets from the EGSnrc/BEAMnrc Monte Carlo system and an actual mouse data set were used for algorithms comparison.ResultsA considerable MTF improvement can be achieved with the decrement of p. L1 regularization based algorithm obtains the best noise performance, and shows superiority in NEQ evaluation. The advantage of L1-norm prior is also confirmed by the reconstructions from the actual mouse data set through contrast to noise ratio (CNR) comparison.ConclusionAlthough the ASD-POCS algorithms using small Lp-norm (p ≤ 0.5) priors yield a higher MTF than do the high Lp-norms, the best noise-resolution performance is achieved when p is between 0.8 and 1. The results are expected to be a reference to the choice of p in Lp-norm (0 < p ≤ 2) regularization.     

Stable solution to <Emphasis Type="Italic">l</Emphasis><Subscript>2,1</Subscript>-based robust inductive matrix completion and its application in linking long noncoding RNAs to human diseases

Backgrounds

A large number of long intergenic non-coding RNAs (lincRNAs) are linked to a broad spectrum of human diseases. The disease association with many other lincRNAs still remain as puzzle. Validation of such links between the two entities through biological experiments are expensive. However, a plethora lincRNA-data are available now, thanks to the High Throughput Sequencing (HTS) platforms, Genome Wide Association Studies (GWAS), etc, which opens the opportunity for cutting-edge machine learning and data mining approaches to extract meaningful relationships among lincRNAs and diseases. However, there are only a few in silico lincRNA-disease association inference tools available to date, and none of them utilizes side information of both the entities simultaneously in a single framework.

Methods

The recently developed Inductive Matrix Completion (IMC) technique provides a recommendation platform among two entities considering respective side information about them. However, the formulation of IMC is incapable of handling noise and outliers that may be present in the datasets, while data sparsity consideration is another issue with the standard IMC method. Thus, a robust version of IMC is needed that can solve the two issues. As a remedy, in this paper, we propose Stable Robust Inductive Matrix Completion (SRIMC) that utilizes the l _2,1 norm based regularization to optimize the objective function with a unique 2-step stable solution approach.

Results

We applied SRIMC to the available association data between human lincRNAs and OMIM disease phenotypes as well as a diverse set of side information about the lincRNAs and the diseases. The method performs better than the state-of-the-art methods in terms of p r e c i s i o n @ k and r e c a l l @ k at the top-k disease prioritization to the subject lincRNAs. We also demonstrate that SRIMC is equally effective for querying about novel lincRNAs, as well as predicting rank of a newly known disease for a set of well-characterized lincRNAs.

Conclusions

With the experimental results and computational evaluation, we show that SRIMC is robust in handling datasets with noise and outliers as well as dealing with novel lincRNAs and disease phenotypes.

     

Biases of acoustic indices measuring biodiversity in urban areas

Urban green infrastructure, GI (e.g., parks, gardens, green roofs) are potentially important biodiversity habitats, however their full ecological capacity is poorly understood, in part due to the difficulties of monitoring urban wildlife populations. Ecoacoustic surveying is a useful way of monitoring habitats, where acoustic indices (AIs) are used to measure biodiversity by summarising the activity or diversity of biotic sounds. However, the biases introduced to AIs in acoustically complex urban habitats dominated by anthropogenic noise are not well understood. Here we measure the level of activity and diversity of the low (0–12 kHz, _l) and high (12–96 kHz, _h) frequency biotic, anthropogenic, and geophonic components of 2452 h of acoustic recordings from 15 sites across Greater London, UK from June to October 2013 based on acoustic and visual analysis of recordings. We used mixed-effects models to compare these measures to those from four commonly used AIs: Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Bioacoustic Index (BI), and Normalised Difference Soundscape Index (NDSI). We found that three AIs (ACI_l, BI_l, NDSI_l) were significantly positively correlated with our measures of biotic_l activity and diversity. However, all three were also correlated with anthropogenic_l activity, and BI_l and NDSI_l were correlated with anthropogenic_l diversity. All low frequency AIs were correlated with the presence of geophonic_l sound. Regarding the high frequency recordings, only one AI (ACI_h) was positively correlated with measured biotic_h activity, but was also positively correlated with anthropogenic_h activity, and no index was correlated with biotic_h diversity. The AIs tested here are therefore not suitable for monitoring biodiversity acoustically in anthropogenically dominated habitats without the prior removal of biasing sounds from recordings. However, with further methodological research to overcome some of the limitations identified here, ecoacoustics has enormous potential to facilitate urban biodiversity and ecosystem monitoring at the scales necessary to manage cities in the future.     

Influence of the concentrations of d-xylose and yeast extract on ethanol production by Pachysolen tannophilus

To determine the most favorable conditions for the production of ethanol by Pachysolen tannophilus, this yeast was grown in batch cultures with various initial concentrations of two of the constituents of the culture medium: d-xylose (s_o), ranging from 1 g·l⁻¹ to 200 g·l⁻¹, and yeast extract (l_o), ranging from 0 g·l⁻¹ to 8 g·l⁻¹. The most favorable conditions proved to be initial concentrations of S_o=25 g·l⁻¹ and l_o=4 g·l⁻¹, which gave a maximum specific growth rate of 0.26 h⁻¹, biomass productivity of 0.023 g·l⁻¹·h⁻¹, overall biomass yield of 0.094 g·g⁻¹, specific xylose-uptake rate (q_s) of 0.3 g·g⁻¹·h⁻¹ (for t=50 h), specific ethanol-production rate (q_E) of 0.065 g·g⁻¹·h⁻¹ and overall ethanol yield of 0.34 g·g⁻¹; q_s values decreased after the exponential growth phase while q_E remained practically constant.     

Ethanol production by Escherichia coli from detoxified lignocellulosic teak wood hydrolysates with high concentration of phenolic compounds

Teak wood residues were subjected to thermochemical pretreatment, enzymatic saccharification, and detoxification to obtain syrups with a high concentration of fermentable sugars for ethanol production with the ethanologenic Escherichia coli strain MS04. Teak is a hardwood, and thus a robust deconstructive pretreatment was applied followed by enzymatic saccharification. The resulting syrup contained 60 g l^–1 glucose, 18 g l^–1 xylose, 6 g l^–1 acetate, less than 0.1 g l^–1 of total furans, and 12 g l^–1 of soluble phenolic compounds (SPCs). This concentration of SPC is toxic to E. coli, and thus two detoxification strategies were assayed: (1) treatment with Coriolopsis gallica laccase followed by addition of activated carbon and (2) overliming with Ca(OH)₂. These reduced the phenolic compounds by 40% and 76%, respectively. The detoxified syrups were centrifuged and fermented with E. coli MS04. Cultivation with the overlimed hydrolysate showed a 60% higher volumetric productivity (0.45 g_ETOH l^–1 hr^–1). The bioethanol/sugar yield was over 90% in both strategies.     

Cell and Solution Velocity Constants for the Reaction CO + Hb → COHb at Different Temperatures in Mammals with Different Red Cell Sizes

Using a double beam stopped-flow apparatus, measurements were made of the velocity constant of the reaction CO + Hb → COHb in solution and in the red cells of human beings, rabbits, horses, and goats. The solution constant (l'') at 37°C for human beings was 362 mM ^-1 sec.^-1; in other species l'' was somewhat lower. Two rabbits, despite having apparently identical hemoglobins had significantly different values for l''. The energy of activation (E) of l'' was between 8 and 11 kcal/mole in all cases. The cell reaction constant (l''_c) at 37° was between 61 and 73 mM ^-1 sec.^-1 in all cases; at 37° the trend was for the smaller cells to have the higher l''_c. This cell size effect was much less than previously found for the faster oxygen reaction. This showed that by merely increasing the rate of chemical reaction, it was not possible to increase cell uptake rate beyond a certain level, this level being dependent on the size and membrane properties of the cell. At lower temperatures l'' was a more important factor in determining l''_c than was cell size. The cell membrane was a barrier to gas diffusion in all species. The effect of temperature on l''_c was also measured and was less than its effect on l'' at most temperatures. Temperature effect increased in small cells at low temperatures. Both these findings are in accordance with predictions based on differentiation of Roughton''s equations.     

Kinetics study of pyridine biodegradation by a novel bacterial strain,Rhizobium sp. NJUST18

Biodegradation of pyridine by a novel bacterial strain, Rhizobium sp. NJUST18, was studied in batch experiments over a wide concentration range (from 100 to 1,000 mg l^?1). Pyridine inhibited both growth of Rhizobium sp. NJUST18 and biodegradation of pyridine. The Haldane model could be fitted to the growth kinetics data well with the kinetic constants μ* = 0.1473 h^?1, K _s = 793.97 mg l^?1, K _i = 268.60 mg l^?1 and S _m = 461.80 mg l^?1. The true μ _max, calculated from μ*, was found to be 0.0332 h^?1. Yield coefficient Y _X/S depended on S _i and reached a maximum of 0.51 g g^?1 at S _i of 600 mg l^?1. V _max was calculated by fitting the pyridine consumption data with the Gompertz model. V _max increased with initial pyridine concentration up to 14.809 mg l^?1 h^?1. The q _S values, calculated from $V_{ \hbox{max} }$ , were fitted with the Haldane equation, yielding q _Smax = 0.1212 g g^?1 h^?1 and q* = 0.3874 g g^?1 h^?1 at S _m′ = 507.83 mg l^?1, K _s′ = 558.03 mg l^?1, and K _i′ = 462.15 mg l^?1. Inhibition constants for growth and degradation rate value were in the same range. Compared with other pyridine degraders, μ _max and S _m obtained for Rhizobium sp. NJUST18 were relatively high. High K _i and K _i′ values and extremely high K _s and K _s′ values indicated that NJUST18 was able to grow on pyridine within a wide concentration range, especially at relatively high concentrations.     

ECG Enhancement and QRS Detection Based on Sparse Derivatives

Electrocardiography (ECG) signals are often contaminated by various kinds of noise or artifacts, for example, morphological changes due to motion artifact, non-stationary noise due to muscular contraction (EMG), etc. Some of these contaminations severely affect the usefulness of ECG signals, especially when computer aided algorithms are utilized. In this paper, a novel ECG enhancement algorithm is proposed based on sparse derivatives. By solving a convex ?₁ optimization problem, artifacts are reduced by modeling the clean ECG signal as a sum of two signals whose second and third-order derivatives (differences) are sparse respectively. The algorithm is applied to a QRS detection system and validated using the MIT-BIH Arrhythmia database (109,452 anotations), resulting a sensitivity of Se = 99.87% and a positive prediction of +P = 99.88%.     

Bilayer Asymmetry Influences Integrin Sequestering in Raft-Mimicking Lipid Mixtures

There is growing recognition that lipid heterogeneities in cellular membranes play an important role in the distribution and functionality of membrane proteins. However, the detection and characterization of such heterogeneities at the cellular level remains challenging. Here we report on the poorly understood relationship between lipid bilayer asymmetry and membrane protein sequestering in raft-mimicking model membrane mixtures using a powerful experimental platform comprised of confocal spectroscopy XY-scan and photon-counting histogram analyses. This experimental approach is utilized to probe the domain-specific sequestering and oligomerization state of α_vβ₃ and α₅β₁ integrins in bilayers, which contain coexisting liquid-disordered/liquid-ordered (l_d/l_o) phase regions exclusively in the top leaflet of the bilayer (bottom leaflet contains l_d phase). Comparison with previously reported integrin sequestering data in bilayer-spanning l_o-l_d phase separations demonstrates that bilayer asymmetry has a profound influence on α_vβ₃ and α₅β₁ sequestering behavior. For example, both integrins sequester preferentially to the l_o phase in asymmetric bilayers, but to the l_d phase in their symmetric counterparts. Furthermore, our data show that bilayer asymmetry significantly influences the role of native ligands in integrin sequestering.     

Prodigiosin formation by Serratia marcescens in a chemostat

In a study of the control of metabolite formation, prodigiosin production by Serratia marcescens was used as a model. Specific production rates of prodigiosin formation were determined using batch culture technique. Sucrose as carbon source and NH₄NO₃ as nitrogen source resulted in a specific production rate of 0.476 mg prodigiosin (g cell dry weight)⁻¹ h⁻¹. Prodigiosin formation and productivity was inversely correlated to growth rate when the bacterium was grown under carbon limitation on a defined medium in a chemostat culture. The maximum specific growth rate (μ_max) was 0.54 h⁻¹ and prodigiosin was formed in amounts over 1 mg l⁻¹ up to a growth rate (μ) of 0.3 h⁻¹ at steady state conditions. At a dilution rate of 0.1 h⁻¹ growth at steady state with carbon and phosphate limitation supported prodigiosin formation giving a similar specific yield [1.17 mg prodigiosin (g cell dry weight)⁻¹ and 0.94 mg g⁻¹, respectively], however, cells grown with nitrogen limitation [(NH₄)₂SO₄] did not form prodigiosin. Productivity in batch culture was 1.33 mg l⁻¹ h⁻¹ as compared to 0.57 mg l⁻¹ h⁻¹ in the chemostat.     

Purification and characterization of four key enzymes from a feather-degrading Bacillus subtilis from the gut of tarantula Chilobrachys guangxiensis

A feather-degrading bacterium was isolated from the gut of the tarantula Chilobrachys guangxiensis, and was classified as Bacillus subtilis (named Bacillus subtilis CH-1) according to both the phenotypic characteristics and 16S rRNA profile. The improved culture conditions for feather-degrading were 10.0 g l⁻¹ mannitol, 10.0 g l⁻¹ tryptone, 0.1 g l⁻¹ MgCl₂, 0.4 g l⁻¹ KH₂PO₄, 0.3 g l⁻¹ K₂HPO₄, 0.5 g l⁻¹ NaCl, and 2.0 g l⁻¹ intact feather, with pH 8.5 and 37 °C. In the optimized medium, the intact black feather was completely degraded by Bacillus subtilis CH-1 in 24 h. Furthermore, four kinds of enzymes which include extracellular protease Vpr, peptidase T, γ-glutamyl transpeptidase and glyoxalmethylglyoxal reductase were identified as having principal roles. Simultaneously, the relationship between the disulfide bond reducing activity (DRT) and the keratinase activity (KT) in B. subtilis CH-1 fermentation system was discussed. This is the first report for a feather-degrading enteric bacterium from tarantula. The identification of the enzymes shines a light on further understanding the molecular mechanism of feather-degrading by microbes.     

Stochastic convex sparse principal component analysis

Principal component analysis (PCA) is a dimensionality reduction and data analysis tool commonly used in many areas. The main idea of PCA is to represent high-dimensional data with a few representative components that capture most of the variance present in the data. However, there is an obvious disadvantage of traditional PCA when it is applied to analyze data where interpretability is important. In applications, where the features have some physical meanings, we lose the ability to interpret the principal components extracted by conventional PCA because each principal component is a linear combination of all the original features. For this reason, sparse PCA has been proposed to improve the interpretability of traditional PCA by introducing sparsity to the loading vectors of principal components. The sparse PCA can be formulated as an ? ₁ regularized optimization problem, which can be solved by proximal gradient methods. However, these methods do not scale well because computation of the exact gradient is generally required at each iteration. Stochastic gradient framework addresses this challenge by computing an expected gradient at each iteration. Nevertheless, stochastic approaches typically have low convergence rates due to the high variance. In this paper, we propose a convex sparse principal component analysis (Cvx-SPCA), which leverages a proximal variance reduced stochastic scheme to achieve a geometric convergence rate. We further show that the convergence analysis can be significantly simplified by using a weak condition which allows a broader class of objectives to be applied. The efficiency and effectiveness of the proposed method are demonstrated on a large-scale electronic medical record cohort.     

Extracellular production of menaquinone-4 by a mutant of Flavobacterium sp. 238-7 with a detergent-supplemented culture

Culture conditions for the extracellular production of menaquinone (MK) by a mutant strain, K₃-15, of Flavobacterium sp. 238-7 were investigated. A detergent-supplemented culture medium consisted of 60 g of glycerol, 23 g of peptone, 3 g of yeast extract, 7 g of K₂HPO₄, 5 g of NaCl, 0.8 g of MgSO₄ · 7H₂O, and 0.5 g of Rikanon UA 5012 in 1 l of tap water, pH 7.0, was constructed. Amounts of MK-4, MK-6, and total MK in 1 l of the medium were 101 mg, 39 mg, and 140 mg, respectively, after 7 d of cultivation at 28°C. Further studies with some additives showed that the addition of cedar wood oil increased the productivity of MK, especially MK-4. In the presence of 0.1% Rikanon UA 5012 and 0.1% cedar wood oil, mutant strain K₃-15 produced 155 mg/l intracellularly and 105 mg/l extracellularly) of MK-4 and 27 mg/l (16 mg/l intracellularly and 11 mg/l extracellularly) of MK-6, and the total amount of MK reached 182 mg/l.     

Bacteriocin Protein BacL1 of Enterococcus faecalis Targets Cell Division Loci and Specifically Recognizes l-Ala2-Cross-Bridged Peptidoglycan

Bacteriocin 41 (Bac41) is produced from clinical isolates of Enterococcus faecalis and consists of two extracellular proteins, BacL₁ and BacA. We previously reported that BacL₁ protein (595 amino acids, 64.5 kDa) is a bacteriolytic peptidoglycan d-isoglutamyl-l-lysine endopeptidase that induces cell lysis of E. faecalis when an accessory factor, BacA, is copresent. However, the target of BacL₁ remains unknown. In this study, we investigated the targeting specificity of BacL₁. Fluorescence microscopy analysis using fluorescent dye-conjugated recombinant protein demonstrated that BacL₁ specifically localized at the cell division-associated site, including the equatorial ring, division septum, and nascent cell wall, on the cell surface of target E. faecalis cells. This specific targeting was dependent on the triple repeat of the SH3 domain located in the region from amino acid 329 to 590 of BacL₁. Repression of cell growth due to the stationary state of the growth phase or to treatment with bacteriostatic antibiotics rescued bacteria from the bacteriolytic activity of BacL₁ and BacA. The static growth state also abolished the binding and targeting of BacL₁ to the cell division-associated site. Furthermore, the targeting of BacL₁ was detectable among Gram-positive bacteria with an l-Ala-l-Ala-cross-bridging peptidoglycan, including E. faecalis, Streptococcus pyogenes, or Streptococcus pneumoniae, but not among bacteria with alternate peptidoglycan structures, such as Enterococcus faecium, Enterococcus hirae, Staphylococcus aureus, or Listeria monocytogenes. These data suggest that BacL₁ specifically targets the l-Ala-l-Ala-cross-bridged peptidoglycan and potentially lyses the E. faecalis cells during cell division.