Green chemistry principles for the synthesis of anti fungal active gum acacia-gold nanocomposite - natamycin (GA-AuNC-NT) against food spoilage fungal strain Aspergillus ochraceopealiformis and its marked Congo red dye adsorption efficacy.

In this present study, a highly stable gum acacia -gold nanocomposite fabricated with food preservative agent natamycin (GA-AuNC-NT) was prepared via green science principles under in vitro conditions. Various characterisation techniques reveal highly stable structural, functional properties of the synthesised nanocomposite with marked antifungal activity and adsorption efficacy against congo red dye. The antifungal activity was investigated against the fungal strain Aspergillus ochraceopealiformis isolated from spoiled, expired bread. The well diffusion assay, fungal hyphae fragmentation assay and spore germination inhibition assay were used to determine the antifungal activity of the synthesised nanocomposite. Potential antifungal activity of the synthesised nanocomposite was confirmed by recording zone of inhibition, high rate of hyphae fragmentation and marked spore germination inhibition against the tested fungal strain. The molecular mechanism of antifungal activity was studied by measuring oxidative stress marker genes like catalase (CAT), superoxide dismutase (SOD), peroxidase (POD) induction adopting quantitative real-time polymerase chain reaction (q RT-PCR). Among the various treatment, a notable reduction in all the tested marker genes expression was recorded in the nanocomposite treated fungal strain. Release profile studies using different solvents reveals sustained or controlled release of natamycin at the increasing periods. The synthesised nanocomposite's high safety or biocompatibility was evaluated with the Wistar animal model by determining notable changes in behavioural, biochemical, haematological and histopathological parameters. The synthesised nanocomposite did not exhibit any undesirable changes in all the tested parameters confirming the marked biosafety or biocompatibility. The nanocomposite was coated on the bread packaging material. The effect of packaging on the proximate composition, antioxidative enzymes status, and fungal growth of bread samples incubated under the incubation period were studied. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) studies reveal that the nanocomposite was effectively coated on the packaging material without changing size, shape, and functional groups. No changes in the proximate composition and antioxidative enzymes of the packaged bread samples incubated under different incubation periods reveal the nanocomposite's marked safety. The complete absence of the fungal growth also indicates the uniqueness of the nanocomposite. Further, the sorption studies revealed the utilisation of Langmuir mechanism and pseudo II order model successfully The present finding implies that the synthesised nanocomposite can be used as an effective, safe food preservative agent and adsorbent of toxic chemicals.

Clinical, Histopathological Characteristics and Immunohistochemical Findings in Lichen Planus Pigmentosus.

BACKGROUND: Lichen planus pigmentosus (LPP), a rare variant of lichen planus, is reported in various ethnic groups, more often from the Indian subcontinent and the Middle East. AIMS: Although the condition is encountered quite often by dermatologists of this region, the data on the clinical, pathological, and immunohistochemical (IHC) aspects of LPP are limited. This prospective study is aimed towards filling this lacuna. MATERIALS AND METHODS: Data were collected from thirty clinically diagnosed cases of LPP who presented to the dermatology outpatient department. Skin biopsy and blood investigations were conducted and the specimens were further analyzed for their histopathological features and IHC staining for CD4+, CD8+ T-lymphocyte subsets along with CD45RO (UCHL-1), and CD68. The results were statistically analyzed. RESULTS: The study showed a female preponderance (56.7%). Photo aggravation as a precipitating cause was seen in 40% of the individuals. The lesions with duration <4 months had a more intense inflammatory infiltrate on histology. CD4+ and CD8+ cells showed very good Pearsons correlation on statistical analysis. CD45 was seen in association with CD8+, and staining for CD68 to assess the macrophage density showed a close correlation with CD45RO. LIMITATIONS: Small sample size. CONCLUSION: LPP represents a misguided lesional immune response pattern. The intense inflammatory infiltrate seen in the early lesions necessitates prompt treatment to arrest progression which may prevent the chronic pigmentary phase of the disease.

Host-to-host variation of ecological interactions in polymicrobial infections.

Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host-microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.

Mixed Poisson distributions in exact solutions of stochastic autoregulation models.

In this paper we study the interplay between stochastic gene expression and system design using simple stochastic models of autoactivation and autoinhibition. Using the Poisson representation, a technique whose particular usefulness in the context of nonlinear gene regulation models we elucidate, we find exact results for these feedback models in the steady state. Further, we exploit this representation to analyze the parameter spaces of each model, determine which dimensionless combinations of rates are the shape determinants for each distribution, and thus demarcate where in the parameter space qualitatively different behaviors arise. These behaviors include power-law-tailed distributions, bimodal distributions, and sub-Poisson distributions. We also show how these distribution shapes change when the strength of the feedback is tuned. Using our results, we reexamine how well the autoinhibition and autoactivation models serve their conventionally assumed roles as paradigms for noise suppression and noise exploitation, respectively.

Mutual information and the fidelity of response of gene regulatory models.

We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κB network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology.

Model of influenza A virus infection: dynamics of viral antagonism and innate immune response.

Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses.

Unusual presentation of rare case of papillary adenofibroma of cervix in a young woman.

Adenofibroma is an extremely rare benign biphasic neoplasm that is classified into the mixed epithelial and mesenchymal tumor group. These tumors tend to occur in postmenopausal and elderly women. We report the case of a large polypoidal mass per vagina occupying the whole pelvis in a young woman. Preoperative biopsy showed benign epithelial and mullerian mesenchymal components suggestive of mullerian adenofibroma. Total hysterectomy with bilateral salpingectomy was done. The diagnosis of papillary adenofibroma of cervix was made. The total surgery assured complete excision and permitted adequate sampling to exclude malignancy.

Regulating Brownian fluctuations with tunable microscopic magnetic traps.

A major challenge to achieving positional control of fluid borne submicron sized objects is regulating their Brownian fluctuations. We present a magnetic-field-based trap that regulates the thermal fluctuations of superparamagnetic beads in suspension. Local domain-wall fields originating from patterned magnetic wires, whose strength and profile are tuned by weak external fields, enable the bead trajectories within the trap to be managed and easily varied between strong confinements and delocalized spatial excursions that are described remarkably well by simulations.

Power-laws in interferon-B mRNA distribution in virus-infected dendritic cells.

Interferon-beta (IFNB1) mRNA shows very large cell-to-cell variability in primary human dendritic cells infected by Newcastle disease virus, with copy numbers varying from a few to several thousands. Analysis of data from the direct measurement of the expression of this gene in its natural chromatin environment in primary human cells shows that the distribution of mRNA across cells follows a power law with an exponent close to -1, and thus encompasses a range of variation much more extensive than a Gaussian. We also investigate the single cell levels of IFNB1 mRNA induced by infection with Texas influenza A mutant viruses, which vary in their capacity to inhibit the signaling pathways responsible for activation of this gene. Here as well we observe power-law behavior for the distribution of IFNB1 mRNA, albeit over a truncated range of values, with exponents similar to the one for cells infected by Newcastle disease virus. We propose a model of stochastic enhanceosome and preinitiation complex formation that incorporates transcriptional pulsing. Analytical and numerical results show good agreement with the observed power laws, and thus support the existence of transcriptional pulsing of an unmodified, intact gene regulated by a natural stimulus.

Stochasticity of gene products from transcriptional pulsing.

Transcriptional pulsing has been observed in both prokaryotes and eukaryotes and plays a crucial role in cell-to-cell variability of protein and mRNA numbers. An important issue is how the time constants associated with episodes of transcriptional bursting and mRNA and protein degradation rates lead to different cellular mRNA and protein distributions, starting from the transient regime leading to the steady state. We address this by deriving and then investigating the exact time-dependent solution of the master equation for a transcriptional pulsing model of mRNA distributions. We find a plethora of results. We show that, among others, bimodal and long-tailed (power-law) distributions occur in the steady state as the rate constants are varied over biologically significant time scales. Since steady state may not be reached experimentally we present results for the time evolution of the distributions. Because cellular behavior is determined by proteins, we also investigate the effect of the different mRNA distributions on the corresponding protein distributions using numerical simulations.

Cytodiagnosis of actinomycetoma.

Mycetoma is a late clinical manifestation of a subcutaneous infection produced by bacteria (actinomycetoma) or fungi (eumycetoma). The distinction between eumycetoma and actinomycetoma in Fine Needle Aspiration Cytology (FNAC) is as accurate as histopathology. A 55 year old man presented with a slow growing swelling on the plantar aspect of the right foot which was present for the last 10 years. A clinical diagnosis of soft tissue tumor was made and FNAC was advised. Smears revealed mixed inflammatory infiltrate and foreign body type of giant cells along with clumps of fibrillar organisms. Gram stain done later demonstrated gram positive thin branching filaments. A diagnosis of actinomycetoma was rendered. Histopathology of the excised specimen confirmed the cytologic diagnosis of actinomycetoma. Mycetoma can be accurately diagnosed by FNAC, which is a simple, inexpensive technique for rapid diagnosis.

Shared kinase fluctuations between two enzymatic reactions.

Kinases serve crucial roles in many cellular signaling pathways that process and transfer information. When signaling kinases phosphorylate two targets, these can serve as branch points that distribute information among two pathways. Responses to stimuli transmitted by activated kinases show high levels of cell-to-cell variation that influence cellular function. We ask how fluctuations around a steady state, due to kinase fluctuations and intrinsic noise, are distributed between two reactions with substrates phosphorylated by a shared kinase. We develop the formalism to answer this question and, for a realistic set of biological constants, we illustrate various features of fluctuations and relaxation times to a steady state. We find that the steady-state response determines the size and range in enzyme concentration of phosphorylated substrate fluctuations, and that the choice of an operating point can have a large impact on how shared kinase noise is distributed among two available pathways.

Intraoperative consultation and smear cytology in the diagnosis of brain tumours.

BACKGROUND: Intraoperative smear cytology provides a rapid and reliable intraoperative diagnosis and guidance to the neurosurgeon during surgical resection and lesion targeting. It also helps the surgeon to monitor and modify the approach at surgery. OBJECTIVES: 1) To assess the utility of intraoperative smear cytology and correlate with the final histopathological diagnosis. 2) To describe the cytomorphological features of common brain tumours in smear preparation. MATERIALS AND METHODS: The material for this study was obtained from 100 consecutive biopsies of central nervous system neoplasms sent for intraoperative consultation. Smears were prepared from the biopsy samples sent in isotonic saline for immediate processing. The smears were stained by the rapid Haematoxylin and Eosin method. The cytomorphological features were noted and correlated with paraffin section findings. RESULTS: Of the total 100 cases, 86 showed accuracy when compared with histopathological diagnosis. This was comparable with other studies. Of the remaining, two cases were frank errors, 12 cases showed partial correlation, with five cases showed incomplete typing of the cell type and seven, discrepancy in grading of tumours. The error percentage was 14%. Correlation with clinical details and radiological findings were helpful in improving the accuracy rate. CONCLUSIONS: Smear technique is a fairly accurate, relatively safe, rapid, simple, easily reproducible and cost effective tool to diagnose brain tumours. Smear cytology is of great value in intraoperative consultation of central nervous system pathology.

Self-organization and productivity in semi-arid ecosystems: implications of seasonality in rainfall.

Spatial self-organization including striking vegetation patterns observed in arid ecosystems has been studied in models with uniform rainfall. In this paper, we present a fully seasonal rainfall model that produces vegetation patterns found in nature by including the natural adaptation of plants to scarcity of water and the consequent seasonal variation in their growth and metabolic rate. We present results for the mean-field and spatially extended versions of the model. We find that the patterns depend on the duration of the wet season even with fixed total annual precipitation (PPT) showing how seasonality affects spatial self-organization. We observe that the productivity can vary for fixed PPT as a function of the duration thereby providing another source of observed variations. We compute the maximum vegetation cover as function of PPT and find that the behavior is consistent with observations. We comment on the implications for regime shifts due to increased interannual fluctuations caused by climatic changes. Our specific model calculations provide more general conclusions for ecosystems with competition for scarce resources due to seasonal variations in the resource, especially for self-organization and productivity.

NF-kappaB oscillations and cell-to-cell variability.

Oscillations in the transcriptional activator NF-kappaB localized in the nucleus have been observed when a cell is stimulated by an external agent. A negative feedback based on the protein IkappaB whose expression is controlled by NF-kappaB is known to be responsible for these oscillations. We study NF-kappaB oscillations, which have been observed both for cell populations by Hoffmann et al. [2002. The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation. Science 298, 1241-1245] and for single cells by Nelson et al. [2004. Oscillations in NF-kappaB signaling control the dynamics of gene expression. Science 306, 704-708]. In order to study cell-to-cell variability we use Gillespie's algorithm, applied to a simplified version of the model proposed by Hoffmann et al. (2002). We consider the amounts of cellular NF-kappaB and activated IKK as external parameters. When these are fixed, we show that intrinsic fluctuations are small in a model with strong transcription, as is the case of the Hoffmann et al. (2002) model, whether transcription is quadratic or linear in the number of NF-kappaB molecules. Intrinsic fluctuations can however be large when transcription is weak, as we illustrate in a model variant. The effect of extrinsic fluctuations can be significant: cell-to-cell fluctuations of the initial amount of cellular NF-kappaB affect mainly the amplitude of nuclear NF-kappaB oscillations, at least when transcription is linear in the number of NF-kappaB molecules, while fluctuations in the amount of activated IKK affect both their amplitude and period, whatever the mode of transcription. In this case model results are in qualitative agreement with the considerable cell-to-cell variability of NF-kappaB oscillations observed by Nelson et al. (2004).

A feedforward loop motif in transcriptional regulation: induction and repression.

We study the dynamical behavior of a unit of three positive transcriptional regulators which occurs frequently in biological networks of yeast and bacteria as a feedforward loop. We investigate numerically a set of reactions incorporating the basic features of transcription and translation. We determine (i) how the feedforward loop motif functions as a computational element such as an AND gate in the presence of stochastic fluctuations, and (ii) the robustness of the motif when transcription at the primary level is suddenly repressed. We highlight the effective time-scales which underlie both of these aspects of the feedforward loop motif. We show how threshold behavior of the motif output arises as a function of the number of external inducers as well as the time over which the inducer acts. We discuss how individual cell behavior can deviate significantly from average behavior, due to intrinsic fluctuations in the small number of molecules present in a cell.

Synchronization rates in classes of relaxation oscillators.

Relaxation oscillators arise frequently in physics, electronics, mathematics, and biology. Their mathematical definitions possess a high degree of flexibility in the sense that through appropriate parameter choices relaxation oscillators can be made to exhibit qualitatively different kinds of oscillations. We study numerically four different classes of relaxation oscillators through their synchronization rates in one-dimensional chains with a Heaviside step function interaction and obtain the following results. Relaxation oscillators in the sinusoidal and relaxation regime both exhibit an average time to synchrony, approximately n, where n is the chain length. Relaxation oscillators in the singular limit exhibit approximately n(p), where p is a numerically obtained value less than 0.5. Relaxation oscillators in the singular limit with parameters modified so that they resemble spike oscillations exhibit approximately log(n) in chains and approximately log(L) in two-dimensional square networks of length L. Finally, using a sigmoid interaction results in approximately n(2), for relaxation oscillators in the sinusoidal and relaxation regimes, indicating that the form of the coupling is a controlling factor in the synchronization rate.

The linear noise approximation for molecular fluctuations within cells.

We study the applicability of Van Kampen's linear noise approximation to the calculation of fluctuations in cells due to small number of molecules for simple genetic systems not previously considered. These systems include dimer formation and feedback. We explain why the linear noise approximation can be surprisingly effective, but also illustrate how it fails in a simple example when a protein probability distribution is not purely Gaussian.

Fluctuations and slow variables in genetic networks.

Computer simulations of large genetic networks are often extremely time consuming because, in addition to the biologically interesting translation and transcription reactions, many less interesting reactions like DNA binding and dimerizations have to be simulated. It is desirable to use the fact that the latter occur on much faster timescales than the former to eliminate the fast and uninteresting reactions and to obtain effective models of the slow reactions only. We use three examples of self-regulatory networks to show that the usual reduction methods where one obtains a system of equations of the Hill type fail to capture the fluctuations that these networks exhibit due to the small number of molecules; moreover, they may even miss describing the behavior of the average number of proteins. We identify the inclusion of fast-varying variables in the effective description as the cause for the failure of the traditional schemes. We suggest a different effective description, which entails the introduction of an additional species, not present in the original networks, that is slowly varying. We show that this description allows for a very efficient simulation of the reduced system while retaining the correct fluctuations and behavior of the full system. This approach ought to be applicable to a wide range of genetic networks.