Methods for investigating biosurfactants and bioemulsifiers: a review

Microorganisms produce biosurfactant (BS)/bioemulsifier (BE) with wide structural and functional diversity which consequently results in the adoption of different techniques to investigate these diverse amphiphilic molecules. This review aims to compile information on different microbial screening methods, surface active products extraction procedures, and analytical terminologies used in this field. Different methods for screening microbial culture broth or cell biomass for surface active compounds production are also presented and their possible advantages and disadvantages highlighted. In addition, the most common methods for purification, detection, and structure determination for a wide range of BS and BE are introduced. Simple techniques such as precipitation using acetone, ammonium sulphate, solvent extraction, ultrafiltration, ion exchange, dialysis, ultrafiltration, lyophilization, isoelectric focusing (IEF), and thin layer chromatography (TLC) are described. Other more elaborate techniques including high pressure liquid chromatography (HPLC), infra red (IR), gas chromatography-mass spectroscopy (GC-MS), nuclear magnetic resonance (NMR), and fast atom bombardment mass spectroscopy (FAB-MS), protein digestion and amino acid sequencing are also elucidated. Various experimental strategies including static light scattering and hydrodynamic characterization for micelles have been discussed. A combination of various analytical methods are often essential in this area of research and a numbers of trials and errors to isolate, purify and characterize various surface active agents are required. This review introduces the various methodologies that are indispensable for studying biosurfactants and bioemulsifiers.     

Methods of analysis of neural nets

The properties of isotropy, smoothness, minimum curvature and locality suggest the shape of filled-in contours between two boundary edges. The contours are composed of the arcs of two circles tangent to the given edges, meeting smoothly, and minimizing the total curvature. It is shown that shapes meeting all the above requirement can be generated by a network which performs simple, local computations. It is suggested that the filling-in process plays an important role in the early processing of visual information.     

Banknote recognition: investigating processing and cognition framework using competitive neural network

Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded. In a similar analogy, the robustness of intelligent systems to perform the task of banknote recognition should not collapse under some minimum level of partial occlusion. Artificial neural networks are intelligent systems which from inception have taken many important cues related to structure and learning rules from the human nervous/cognition processing system. Likewise, it has been shown that advances in artificial neural network simulations can help us understand the human nervous/cognition system even furthermore. In this paper, we investigate three cognition hypothetical frameworks to vision-based recognition of banknote denominations using competitive neural networks. In order to make the task more challenging and stress-test the investigated hypotheses, we also consider the recognition of occluded banknotes. The implemented hypothetical systems are tasked to perform fast recognition of banknotes with up to 75 % occlusion. The investigated hypothetical systems are trained on Nigeria’s Naira banknotes and several experiments are performed to demonstrate the findings presented within this work.     

Growth of food-borne pathogenic bacteria in oil-in-water emulsions: I—Methods for investigating the form of growth

Methods are presented for investigating the site and form of growth of bacteria in model oil-in-water emulsions and in dairy cream. Following growth of the bacteria, the continuous aqueous phase is gelled using agarose and the oil phase removed using a mixture of chloroform and methanol. Using this method, the authors have found that Listeria monocytogenes, Salmonella typhimurium and Yersinia enterocolitica grow in the form of colonies in concentrated oil-in-water emulsions. Colonies of L. monocytogenes and Y. enterocolitica also form in artificially-inoculated fresh and tinned dairy cream. If information about the precise site of growth is not required, the authors have discovered that intact colonies can be liberated from the model emulsions by dissolving away the oil phase with chloroform: methanol.     

Two-dimensional components and hidden dependencies provide insight into ion channel gating mechanisms

Correlations between the durations of adjacent open and shut intervals recorded from ion channels contain information about the underlying gating mechanism. This study presents an additional approach to extracting the correlation information. Detailed correlation information is obtained directly from single-channel data and quantified in a manner that can provide insight into the connections among the states underlying the gating. The information is obtained independently of any specific kinetic scheme, except for the general assumption of Markov gating. The durations of adjacent open and shut intervals are binned into two-dimensional (2-D) dwell-time distributions. The 2-D (joint) distributions are fitted with sums of 2-D exponential components to determine the number of 2-D components, their volumes, and their open and closed time constants. The dependency of each 2-D component is calculated by comparing its observed volume to the volume that would be expected if open and shut intervals paired independently. The estimated component dependencies are then used to suggest gating mechanisms and to provide a powerful means of examining whether proposed gating mechanisms have the correct connections among states. The sensitivity of the 2-D method can identify hidden components and dependencies that can go undetected by previous correlation methods.     

Methods for investigating patterns of mortality and quantifying cause-specific mortality in sea-farmed Atlantic salmon Salmo salar

Methods for investigating patterns of mortality and quantifying cause-specific mortality in Atlantic salmon Salmo salar farming were developed. The methods were further used to investigate mortality and patterns of mortality for the first 3 mo after sea transfer in the 2006 year-class autumn smolts (SO) of Norwegian farmed Atlantic salmon. In the study population, which consisted of 20 pens at 10 sites, cause-specific mortality was examined by 11 fish health professionals during 8 visits to each pen. Cause-specific mortality proportions were used to convert crude mortality into cause-specific mortality. Cumulative mortality in the study period was 2.1% in the study population compared with 3.7% for the 2006 year-class SOs in the national database. Of this cumulative mortality, 73 and 59% took place in 20% of the pens in the study and the reference population, respectively. Daily mortality rates in the study population showed a variation from 0 to 2376 per 100,000 fish where the majority of mortality was observed during disease outbreaks. All study pens had periods of low baseline mortality and some pens had no increased mortality during the study period. Of 2088 dead fish examined, 92% (1929 fish) were assigned a specific cause of death, and in 97% of these 1929 fish the investigators reported the given cause of death to be likely or very likely. Ulcers were the main cause of death, accounting for 43% of the assigned mortality, and infectious agents were involved in 64% of the total mortality. The study shows that probable causes of death can be established in Atlantic salmon farming and their contribution to total mortality measured.     

Two strategies for investigating the evolution of behavior

In this paper I distinguish and characterize two strategies, both prominent in contemporary biology, for investigating the evolution of behavior. The ‘Lorenzian Strategy’ is taxon-focused, holistic, and particularistic, and relies heavily on naturalistic observation as well as careful experimental manipulation of target systems; it tends to produce detailed knowledge of concrete historical instances of the evolution of behavior in particular lineages. The ‘Analytic Strategy’ is principle-focused, generative, and taxonomically universal; it relies on the development of mathematical principles (simple analytic models) of the evolution of behavior at an abstract level, and uses experimentation to garner support for the empirical relevance for these. The strategies hence employ different methods and produce different sorts of knowledge, hence they are neither inconsistent nor redundant, but complementary, and indeed they both play important roles in the contemporary biology of animal behavior.     

Methods for comparison of parameters from longitudinal rhythmometric models with multiple components

Multiple components linear least-squares methods have been proposed for the detection of periodic components in nonsinusoidal longitudinal time series. However, a proper test for comparison of parameters obtained from this method for two or more time series is not yet available. Accordingly, we propose two methods, one parametric and one nonparametric, to compare parameters from rhythmometric models with multiple components. The parametric method is based on techniques commonly and generally employed in linear regression analysis. The comparison of parameters among two or more time series is accomplished by the use of so-called dummy variables. The nonparametric method is based on bootstrap techniques. This approach basically tests if the difference in any given parameter obtained by fitting a model with the same periods to two different longitudinal time series differs from zero. This method calculates a confidence interval for the difference in the tested parameter. If this interval does not contain zero, it can be concluded that the parameters obtained from the two time series are different with high probability. An estimation of the p-value for the corresponding test can also be calculated. By the use of similar bootstrap techniques, confidence intervals can also be obtained for any parameter derived from the multiple component fit of several periods to nonsinusoidal longitudinal time series, including the orthophase (peak time), bathyphase (trough time), and global amplitude (difference between the maximum and the minimum) of the fitted model waveform. These methods represent a valuable tool for the comparison of rhythm parameters obtained by multiple component analysis, and they render this approach as a generally applicable one for waveform representation and detection of periodicities in nonsinusoidal, sparse, and noisy longitudinal time series sampled with either equidistant or unequidistant observations.     

人脸感知中的事件相关电位早期成份反映了顺序性神经活动

事件相关电位(event.related potential,ERa)的研究证实了ERP的早期成份正电位P120、负电位N170和顶正波(vertexpositive potential,VPP)都与人脸感知活动有关.还有研究进一步表明,VPP是N170的正性配对成份,它们由同一大脑源活动产生.然而,P120是否也拥有...     

The neural cell adhesion molecule is associated with major components of the cytoskeleton

The neural cell adhesion molecule (NCAM) is a member of the immunoglobulin superfamily. Two of the three major isoforms (NCAM 140 and NCAM 180) are transmembrane glycoproteins, which differ in their intracellular domains. The present study is concerned with the identification of novel intracellular binding partners of NCAM. We expressed and purified both cytoplasmic domains of NCAM. Using ligand affinity chromatography followed by peptide mass fingerprinting, we could identify several novel binding partners of the cytoplasmic domains of NCAM 140 and 180. We present data that alpha- and beta-tubulin as well as alpha-actinin 1 are associated with both NCAM 140 and 180. In contrast, beta-actin, tropomyosin, microtubuli-associated protein MAP 1A, and rhoA-binding kinase-alpha preferentially bind to NCAM 180. Furthermore, we demonstrate that inhibition of rhoA-binding kinase-alpha stimulates neurite outgrowth independently from NCAM.     

Destruction of components of the neural induction system of the amphibian egg with ultraviolet irradiation

Ultraviolet irradiation of the vegetal hemisphere of the fertilized amphibian (Xenopus laevis) egg prior to first cleavage results in the embryo developing an incomplete set of neural structures. The effects of irradiation on various morphogenetic processes, including cell division, formation of the dorsal lip, invagination at gastrulation, and neural induction by the primary organizer, were examined. A decrease in the capacity for invagination during gastrulation and a diminution in the neural inducing capacity of the primary organizer were found to account for defective neurulation in irradiated embryos. Consequently, irradiation of the uncleaved egg leads to interference with the events of both gastrulation and neurulation.