Size-Selective Predation on Groundwater Bacteria by Nanoflagellates in an Organic-Contaminated Aquifer

Time series incubations were conducted to provide estimates for the size selectivities and rates of protistan grazing that may be occurring in a sandy, contaminated aquifer. The experiments involved four size classes of fluorescently labeled groundwater bacteria (FLB) and 2- to 3-μm-long nanoflagellates, primarily Spumella guttula (Ehrenberg) Kent, that were isolated from contaminated aquifer sediments (Cape Cod, Mass.). The greatest uptake and clearance rates (0.77 bacteria · flagellate⁻¹ · h⁻¹ and 1.4 nl · flagellate⁻¹ · h⁻¹, respectively) were observed for 0.8- to 1.5-μm-long FLB (0.21-μm³ average cell volume), which represent the fastest growing bacteria within the pore fluids of the contaminated aquifer sediments. The 19:1 to 67:1 volume ratios of nanoflagellate predators to preferred bacterial prey were in the lower end of the range commonly reported for other aquatic habitats. The grazing data suggest that the aquifer nanoflagellates can consume as much as 12 to 74% of the unattached bacterial community in 1 day and are likely to have a substantive effect upon bacterial degradation of organic groundwater contaminants.While heterotrophic protists have been found in pristine and contaminated aquifers (3, 29, 34, 37, 54–57), very little research has been performed to elucidate their role in the subsurface. In other environments (e.g., surface and marine waters, topsoil, and wastewater treatment plants), it is well documented that they typically consume bacteria (2, 11, 15, 41, 42, 47), although some have been observed to consume high-molecular-weight organics (48, 59) and even viruses (20, 39). Protists typically graze selectively, depending upon the size (1, 9, 17, 25, 52), growth condition (18, 53), species (16, 17, 35), and motility (18) of their prey. In carbon-limited environments, protists decrease bacterial competition, resulting in a greater bacterial uptake rate for organic substrate per unit of bacterial biomass (27). Based upon indirect field observations, it is also hypothesized that this may be the role they play in organically contaminated aquifers (31). In nutrient-limited environments, protists may release nitrogen or phosphorus needed by bacteria (10, 28, 44, 61).Studies at the U.S. Geological Survey’s (USGS) Toxic Substances Hydrology Program research site at the Massachusetts Military Reservation (MMR) on Cape Cod, Mass., have shown that sandy aquifer sediments can harbor large protistan populations even at relatively low levels (≤2 mg/liter) of dissolved organic matter (30). Protistan abundances in the MMR aquifer plume range from 1 × 10⁴ to 7 × 10⁴ g (dry weight)⁻¹ (30) and consist primarily of nanoflagellates (2 to 3 μm in length) (29) that belong to the genera Bodo, Cercomonas, Cryptaulax, Cyanthomonas, Goniomonas, and Spumella, along with some undescribed species (37). A few amoebae (63) and no ciliates (29) have been observed.Results of a principal-component factor analysis of protistan and bacterial abundances and chemical constituents in the MMR plume suggested that the flagellates were preying upon unattached bacteria (30). Additional evidence of predation was obtained from flowthrough columns of aquifer sediment from which fluorescently labeled unattached bacteria eluted at much lower rates than they did from sterile (protist-free) controls (31). However, these results provide only indirect evidence of predation because no enumerations of the bacteria within the flagellates were performed.The purpose of the research reported in this paper was to directly determine whether the MMR nanoflagellates can consume unattached bacteria in the plume and the extent to which they engage in size-selective grazing. Rates of bacterivory (grazing and clearance rates) were estimated in the laboratory by using fluorescently labeled, monodispersed bacteria (FLB) and nanoflagellates that had been isolated from the MMR aquifer plume. Although other methods exist (19, 26, 38, 43, 45, 62, 64–66), we chose to use fluorescent labeling to study flagellate bacterivory because this procedure requires shorter incubation times and relies upon direct visual observation of the prey within the predator. In addition, experiments could be designed with different sizes of FLB to determine if the nanoflagellates can discriminate between prey. This involved using FLB with cell lengths of 0.1 to 0.5, 0.5 to 0.8, 0.8 to 1.5, and >1.5 μm (average cell volumes of 0.06, 0.14, 0.21, and 0.87 μm³, respectively) in the grazing experiments.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Daytime Blue Light Enhances the Nighttime Circadian Melatonin Inhibition of Human Prostate Cancer Growth

Light controls pineal melatonin production and temporally coordinates circadian rhythms of metabolism and physiology in normal and neoplastic tissues. We previously showed that peak circulating nocturnal melatonin levels were 7-fold higher after daytime spectral transmittance of white light through blue-tinted (compared with clear) rodent cages. Here, we tested the hypothesis that daytime blue-light amplification of nocturnal melatonin enhances the inhibition of metabolism, signaling activity, and growth of prostate cancer xenografts. Compared with male nude rats housed in clear cages under a 12:12-h light:dark cycle, rats in blue-tinted cages (with increased transmittance of 462–484 nm and decreased red light greater than 640 nm) evinced over 6-fold higher peak plasma melatonin levels at middark phase (time, 2400), whereas midlight-phase levels (1200) were low (less than 3 pg/mL) in both groups. Circadian rhythms of arterial plasma levels of linoleic acid, glucose, lactic acid, pO₂, pCO₂, insulin, leptin, and corticosterone were disrupted in rats in blue cages as compared with the corresponding entrained rhythms in clear-caged rats. After implantation with tissue-isolated PC3 human prostate cancer xenografts, tumor latency-to-onset of growth and growth rates were markedly delayed, and tumor cAMP levels, uptake–metabolism of linoleic acid, aerobic glycolysis (Warburg effect), and growth signaling activities were reduced in rats in blue compared with clear cages. These data show that the amplification of nighttime melatonin levels by exposing nude rats to blue light during the daytime significantly reduces human prostate cancer metabolic, signaling, and proliferative activities.Abbreviations: A-V, arterial–venous difference, ipRGC, intrinsically photosensitive retinal ganglion cell, LA, linoleic acid, 13-HODE, 13-hydroxyoctadecadienoic acid, TFA, total fatty acidsLight profoundly influences circadian, neuroendocrine, and neurobehavioral regulation in all mammals and is essential to life on our planet.^{2,15,28, 40} The light–dark cycle entrains the master biologic clock, located in the suprachiasmatic nucleus of the brain, in an intensity-, duration-, and wavelength-dependent manner.^8-13 Photobiologic responses, including circadian rhythms of metabolism and physiology, are mediated by organic molecules called ‘chromophores,’ which are contained within a small subset of retinal cells, called the intrinsically sensitive retinal ganglion cells (ipRGC).^{16,29,31,36,41,49,53,59} In humans and rodents light quanta are detected by the chromophore melanopsin, which detects light quanta in principally the short-wavelength, blue-appearing portion of the spectrum (446 to 477 nm), and transmits its photic information via the retinohypothalamic tract to the ‘molecular clock’ of the suprachiasmatic nucleus. This region of the brain regulates the daily pineal gland production of the circadian neurohormone melatonin (N-acetyl-5-methoxytryptamine), which results in high levels produced at night and low levels during daytime.^38,54 The daily, rhythmic melatonin signal provides temporal coordination of normal behavioral and physiologic functions including chronobiologic rhythms of locomotor activity,² sleep-wake cycle,^2,14 dietary and water intake,^2,51 hormone secretion and metabolism.^5,44,47,61 Alterations in light intensity, duration, and spectral quality at a given time of day,^{8-13,17,19-22,24,61} such as occurs in night-shift workers exposed to light at night,^26,34,46,57 acutely suppresses endogenous melatonin levels in most mammalian species^{9,11,44,45,54,55} and may lead to various disease states, including metabolic syndrome^5,61 and carcinogenesis.^4-7,17,18Recent studies from our laboratory^{5,20,23-25,60,61} have demonstrated that relatively small changes in the spectral transmittance (color) of light passing through translucent amber (>590 nm), blue (>480 nm), and red-tinted (>640 nm) polycarbonate laboratory rodent cages, compared with standard polycarbonate clear cages (390 to 700 nm), during the light phase markedly influenced the normal nighttime melatonin signal and disrupted temporal coordination of metabolism and physiology.^19,24,61 Most notable was our discovery that, in both male and female pigmented nude rats maintained in blue-tinted rodent cages, nighttime melatonin levels were as much as 7 times higher than normal nighttime peak levels in animals maintained in all other cage types.¹⁹ An earlier study in human subjects diagnosed with midwinter insomnia coupled with low nighttime melatonin levels demonstrated that daily exposure to intense morning bright polychromatic light therapy for up to one week resulted in a restoration of nocturnal melatonin levels to those of control subjects.³⁵ In another study, exposure to blue-tinted (470 nm) LED light (100 lx) for approximately 20 min in the morning after 2 sleep-restricted (6 h) nights led to earlier onset of the melatonin surge at nighttime.³⁰In the United States alone this year, approximately 240,000 men will be diagnosed with prostate cancer, and nearly 30,000 will die from this disease (National Cancer Institute; www.cancer.gov/). Epidemiologic studies have shown that night shift work, which involves circadian disruption, including nocturnal melatonin suppression, markedly increases prostate cancer risk in men.^{26,34,46,57,58} Both in vitro and in vivo studies have demonstrated that melatonin inhibits human prostate cancer growth, including that of androgen-receptor–negative, castration-resistant PC3 human prostate cancer cells.^20,29,42,56 Cancer cells depend primarily on aerobic glycolysis (Warburg effect) over oxidative phosphorylation to meet their bioenergetic needs supporting biomass formation.⁵ The Warburg effect is characterized by increased cellular uptake of glucose and production of lactate despite an abundance of oxygen. Investigations have shown that signal transduction pathways that include AKT, MEK, NFκB, GS3Kβ, and PDK1 drive the Warburg effect.^5,61 In addition, cancer cells rely on increased uptake of the ω6 fatty acid linoleic acid (LA), which is prevalent in the western diet.^4-6 In most cancers, LA uptake occurs through a cAMP-dependent transport mechanism, and LA is metabolized to the mitogenic agent 13-hydroxyoctadecadienoic acid (13-HODE). In most tumors, 13-HODE plays an important role in enhancing downstream phosphorylation of ERK 1/2, AKT, and activation of the Warburg effect, thereby leading to increased cell proliferation and tumor growth.^4-6 Melatonin, the principal neurohormone of the pineal gland and whose production is regulated by the suprachiasmatic nucleus,^4,5 modulates processes of tumor initiation, progression, and growth in vivo.⁵ The circadian nocturnal melatonin signal not only inhibits LA uptake and metabolism, the Warburg effect in human cancer xenografts, and ultimately tumor growth, but it actually drives circadian rhythms in tumor metabolism, signal transduction activity, and cell proliferation. These effects are extinguished when melatonin production is suppressed by light exposure at night.⁵In the present investigation, we examined the hypothesis that the spectral transmittance (color) of short-wavelength (480 nm) bright light passing through blue-tinted standard laboratory rodent cages during the light phase not only amplifies the normal circadian nocturnal melatonin signal but also enhances the inhibition of the metabolism, signaling activity, and growth progression of human PC3 androgen-receptor–negative human prostate cancer xenografts in male nude rats.     

Question Processing and Clustering in INDOC: A Biomedical Question Answering System

The exponential growth in the volume of publications in the biomedical domain has made it impossible for an individual to keep pace with the advances. Even though evidence-based medicine has gained wide acceptance, the physicians are unable to access the relevant information in the required time, leaving most of the questions unanswered. This accentuates the need for fast and accurate biomedical question answering systems. In this paper we introduce INDOC—a biomedical question answering system based on novel ideas of indexing and extracting the answer to the questions posed. INDOC displays the results in clusters to help the user arrive the most relevant set of documents quickly. Evaluation was done against the standard OHSUMED test collection. Our system achieves high accuracy and minimizes user effort.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24]     

Comparison of Gas Chromatography and Mineralization Experiments for Measuring Loss of Selected Polychlorinated Biphenyl Congeners in Cultures of White Rot Fungi

Two methods were used to compare the biodegradation of six polychlorinated biphenyl (PCB) congeners by 12 white rot fungi. Four fungi were found to be more active than Phanerochaete chrysosporium ATCC 24725. Biodegradation of the following congeners was monitored by gas chromatography: 2,3-dichlorobiphenyl, 4,4′-dichlorobiphenyl, 2,4′,5-trichlorobiphenyl (2,4′,5-TCB), 2,2′,4,4′-tetrachlorobiphenyl, 2,2′,5,5′-tetrachlorobiphenyl, and 2,2′,4,4′,5,5′-hexachlorobiphenyl. The congener tested for mineralization was 2,4′,5-[U-¹⁴C]TCB. Culture supernatants were also assayed for lignin peroxidase and manganese peroxidase activities. Of the fungi tested, two strains of Bjerkandera adusta (UAMH 8258 and UAMH 7308), one strain of Pleurotus ostreatus (UAMH 7964), and Trametes versicolor UAMH 8272 gave the highest biodegradation and mineralization. P. chrysosporium ATCC 24725, a strain frequently used in studies of PCB degradation, gave the lowest mineralization and biodegradation activities of the 12 fungi reported here. Low but detectable levels of lignin peroxidase and manganese peroxidase activity were present in culture supernatants, but no correlation was observed among any combination of PCB congener biodegradation, mineralization, and lignin peroxidase or manganese peroxidase activity. With the exception of P. chrysosporium, congener loss ranged from 40 to 96%; however, these values varied due to nonspecific congener binding to fungal biomass and glassware. Mineralization was much lower, ≤11%, because it measures a complete oxidation of at least part of the congener molecule but the results were more consistent and therefore more reliable in assessment of PCB biodegradation.

Polychlorinated biphenyls (PCBs) are produced by chlorination of biphenyl, resulting in up to 209 different congeners. Commercial mixtures range from light oily fluids to waxes, and their physical properties make them useful as heat transfer fluids, hydraulic fluids, solvent extenders, plasticizers, flame retardants, organic diluents, and dielectric fluids (1, 21). Approximately 24 million lb are in the North American environment (19). The stability and hydrophobic nature of these compounds make them a persistent environmental hazard.To date, bacterial transformations have been the main focus of PCB degradation research. Aerobic bacteria use a biphenyl-induced dioxygenase enzyme system to attack less-chlorinated congeners (mono- to hexachlorobiphenyls) (1, 5, 7, 8, 22). Although more-chlorinated congeners are recalcitrant to aerobic bacterial degradation, microorganisms in anaerobic river sediments reductively dechlorinate these compounds, mainly removing the meta and para chlorines (1, 6, 10, 33, 34).The degradation of PCBs by white rot fungi has been known since 1985 (11, 18). Many fungi have been tested for their ability to degrade PCBs, including the white rot fungi Coriolus versicolor (18), Coriolopsis polysona (41), Funalia gallica (18), Hirneola nigricans (35), Lentinus edodes (35), Phanerochaete chrysosporium (3, 11, 14, 17, 18, 35, 39, 41–43), Phlebia brevispora (18), Pleurotus ostreatus (35, 43), Poria cinerescens (18), Px strain (possibly Lentinus tigrinus) (35), and Trametes versicolor (41, 43). There have also been studies of PCB metabolism by ectomycorrhizal fungi (17) and other fungi such as Aspergillus flavus (32), Aspergillus niger (15), Aureobasidium pullulans (18), Candida boidinii (35), Candida lipolytica (35), Cunninghamella elegans (16), and Saccharomyces cerevisiae (18, 38). The mechanism of PCB biodegradation has not been definitively determined for any fungi. White rot fungi produce several nonspecific extracellular enzymes which have been the subject of extensive research. These nonspecific peroxidases are normally involved in lignin degradation but can oxidize a wide range of aromatic compounds including polycyclic aromatic hydrocarbons (37). Two peroxidases, lignin peroxidase (LiP) and Mn peroxidase (MnP), are secreted into the environment of the fungus under conditions of nitrogen limitation in P. chrysosporium (23, 25, 27, 29) but are not stress related in fungi such as Bjerkandera adusta or T. versicolor (12, 30).Two approaches have been used to determine the biodegradability of PCBs by fungi: (i) loss of the parent congener analyzed by gas chromatography (GC) (17, 32, 35, 42, 43) and (ii) mineralization experiments in which the ¹⁴C of the universally labeled ¹⁴C parent congener is recovered as ¹⁴CO₂ (11, 14, 18, 39, 41). In the first method, the loss of a peak on a chromatogram makes it difficult to decide whether the PCB is being partly degraded, mineralized, adsorbed to the fungal biomass, or bound to glassware, soil particles, or wood chips. Even when experiments with killed-cell and abiotic controls are performed, the extraction efficiency and standard error can make data difficult to interpret. For example, recoveries can range anywhere from 40 to 100% depending on the congener used and the fungus being investigated (17). On the other hand, recovery of significant amounts of ¹⁴CO₂ from the cultures incubated with a ¹⁴C substrate provides definitive proof of fungal metabolism. There appears to be only one report relating data from these two techniques (18), and in that study, [U-¹⁴C]Aroclor 1254, rather than an individual congener, was used.In this study, we examined the ability of 12 white rot fungal strains to metabolize selected PCB congeners to determine which strains were the most active degraders. Included in this group was P. chrysosporium ATCC 24725, a strain used extensively in PCB studies (3, 14, 18, 35, 39, 41–43). Six PCB congeners were selected to give a range of chlorine substitutions and therefore a range of potential biodegradability which was monitored by GC. One of the chosen congeners was ¹⁴C labeled and used in studies to compare the results from a mineralization method with those from the GC method.     

Multipattern Consensus Regions in Multiple Aligned Protein Sequences and Their Segmentation

Decomposing a biological sequence into its functional regions is an important prerequisite to understand the molecule. Using the multiple alignments of the sequences, we evaluate a segmentation based on the type of statistical variation pattern from each of the aligned sites. To describe such a more general pattern, we introduce multipattern consensus regions as segmented regions based on conserved as well as interdependent patterns. Thus the proposed consensus region considers patterns that are statistically significant and extends a local neighborhood. To show its relevance in protein sequence analysis, a cancer suppressor gene called p53 is examined. The results show significant associations between the detected regions and tendency of mutations, location on the 3D structure, and cancer hereditable factors that can be inferred from human twin studies.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]     

Double-Stranded RNA-Independent Dimerization of Interferon-Induced Protein Kinase PKR and Inhibition of Dimerization by the Cellular P58IPK Inhibitor

The interferon (IFN)-induced, double-stranded RNA-activated protein kinase (PKR) mediates the antiviral and antiproliferative actions of IFN, in part, via its translational inhibitory properties. Previous studies have demonstrated that PKR forms dimers and that dimerization is likely to be required for activation and/or function. In the present study we used multiple approaches to examine the modulation of PKR dimerization. Deletion analysis with the λ repressor fusion system identified a previously unrecognized site involved in PKR dimerization. This site comprised amino acids (aa) 244 to 296, which span part of the third basic region of PKR and the catalytic subdomains I and II. Using the yeast two-hybrid system and far-Western analysis, we verified the importance of this region for dimerization. Furthermore, coexpression of the 52-aa region alone inhibited the formation of full-length PKR dimers in the λ repressor fusion and two-hybrid systems. Importantly, coexpression of aa 244 to 296 exerted a dominant-negative effect on wild-type kinase activity in a functional assay. Due to its role as a mediator of IFN-induced antiviral resistance, PKR is a target of viral and cellular inhibitors. Curiously, PKR aa 244 to 296 contain the binding site for a select group of specific inhibitors, including the cellular protein P58^IPK. We demonstrated, utilizing both the yeast and λ systems, that P58^IPK, a member of the tetratricopeptide repeat protein family, can block kinase activity by preventing PKR dimerization. In contrast, a nonfunctional form of P58^IPK lacking a TPR motif did not inhibit kinase activity or perturb PKR dimers. These results highlight a potential mechanism of PKR inhibition and define a novel class of PKR inhibitors. Finally, the data document the first known example of inhibition of protein kinase dimerization by a cellular protein inhibitor. On the basis of these results we propose a model for the regulation of PKR dimerization.Cellular protein kinases play crucial roles in propagating, regulating, and coordinating signals necessary for many seminal biological processes, including metabolism, gene expression, cell growth, differentiation, and development. As a result, protein kinases are subjected to elaborate control mechanisms, including association with domains or subunits that inhibit kinase activity by an autoregulatory process (40, 44) or domains that target the kinase to different subcellular localizations and/or substrates (23, 36). In addition, association with activating or inhibitory proteins (21, 86), reversible protein phosphorylation (19, 32), and multimerization (31, 76) also may regulate kinase activity. While dimerization is a common regulatory mechanism for receptor protein kinases, it is less so for cytosolic nonreceptor protein kinases. The latter class of protein kinases, whose dimerization is implicated in their activation and/or function, includes the cGMP- and cAMP-dependent kinases (81), casein kinase 2 (9), Mst1 kinase (17), Raf-1 kinase (22), and the interferon (IFN)-induced, double-stranded (ds)-RNA-activated kinase (PKR) (60). PKR is novel in that it also regulates its own protein synthesis at the translational level (7, 82).PKR is a pivotal component of the host antiviral defense system because of its translational inhibitory properties (58, 74). Viral replication produces dsRNA that can bind PKR via two dsRNA-binding motifs (DSRMs) located in the N-terminal portion of the kinase, resulting in autophosphorylation and consequently activation of the enzyme. Activated PKR, in turn, phosphorylates the α subunit of eukaryotic initiation factor-2 (eIF-2α), leading to a complex series of biochemical events that culminate in a dramatic decrease in the initiation of protein synthesis (15, 59). This disables the use of the translational machinery for the production of viral proteins, and hence restricts viral replication within the cell. Due to its function in antiviral defense, PKR is a target of viral and cellular inhibitors (42, 51). The best-characterized cellular protein inhibitor of PKR is P58^IPK, which is activated upon influenza virus infection (53, 54). P58^IPK appears to be a member of a potential new class of molecular chaperones containing tetratricopeptide repeat motifs and the “J region” of the DnaJ family (52, 62). The non-enzymatic P58^IPK protein inhibits both the auto- and trans-phosphorylation activities of PKR (53, 54). However, the exact mode of P58^IPK action is not fully understood, although it likely involves direct physical interaction with PKR (25, 69).In addition to its role in interferon-induced antiviral resistance, there is growing evidence that PKR is involved in the control of cell growth and proliferation. Overexpression of PKR in mouse (46), insect (4), and yeast (14) cells results in severe inhibition of growth due to increased eIF-2α phosphorylation. Furthermore, expression of catalytically inactive mutants of PKR elicits fibroblast transformation and tumor formation upon injection of the cells into nude mice, suggesting that PKR has tumor suppressor properties (6, 46, 61). In support of this view, the P58^IPK protein exhibits oncogenic potential; overexpression of the cellular PKR inhibitor causes a transformed phenotype and rapid tumor formation in nude mice (3).The mechanism(s) by which the functionally defective PKR mutants or wild-type P58^IPK induce malignant transformation is not known. One hypothesis is that the PKR mutants inhibit kinase function by forming inactive heterodimers with endogenous wild-type PKR (6, 46). This also raises a fundamental question concerning the role of dimerization on PKR function. Indeed, evidence for PKR dimerization dependent on the DSRMs has been reported (16, 67), although its role in activation and/or function remains unclear (71, 85). Moreover, the role of P58^IPK in modulating PKR dimer formation has not been investigated.Recent efforts to identify the region and mechanism responsible for PKR dimerization have led to conflicting results (16, 66, 67). This controversy can be explained, at least in part, by our demonstration herein that PKR can dimerize through a previously unrecognized region independent of the DSRMs. In addition, we show that P58^IPK, but not a nonfunctional form of the protein, prevents PKR dimer formation, suggesting that P58^IPK inhibits PKR by converting PKR dimers into stable monomers. To our knowledge, our findings present the first known example of a cytosolic kinase whose activity may be modulated at the level of dimerization through association with a nonenzymatic cellular protein inhibitor.     

An Improved Algorithm for the Piecewise-Smooth Mumford and Shah Model in Image Segmentation

An improved algorithm for the piecewise-smooth Mumford and Shah functional is presented. Compared to the previous work of Chan and Vese, and Choi et al., extensions of the key functions are replaced by updating the level set function based on an artificial image that is composed of the diffused image and the original image. The low convergence problem of the classical algorithm is efficiently solved in the proposed approach. The resulting algorithm has also been demonstrated by several cases.[1,2,3,4,5,6,7,8,9,10,11]