Oestrogenic regulation and differential expression of WNT4 in the bonnet monkey and rodent epididymis

A role for oestrogen in regulating fluid reabsorption in the monkey epididymis was recently demonstrated. Here, these Studies are extended to identify potential oestrogen-regulated proteins in the cauda region of monkey epididymis treated with vehicle and oestrogen receptor antagonist (ICI 182780). Two-dimensional electrophoretic analysis was used to identify the proteins. The results indicated down-regulation of WNT4 in the ICI-182780-treated monkey cauda. In addition. the Wnt4f mRNA concentration was also reduced in the caput regions of ICI-182780-treated rats and oestrogen receptor knockout mice. WNT4 is a key regulator of gonadal differentiation in humans and mice and plays a pivotal role in early mouse embryogenesis. The results of the present Study establish the presence of WNT4 in the monkey epididymis and its regulation by oestrogen, and Suggest a role for WNT4 in maintaining epididymal homeostasis.

Antimycobacterial activities of novel fluoroquinolones

Fifty-one novel 1-(cyclopropyl/2,4-difluorophenyl/t-butyl)-1,4-dihydro-6-fluoro-7-(sub secondary amino)-4-oxoquinoline-3-carboxylic acids were synthesized and evaluated for their antimycobacterial in vitro and in vivo against Mycobacterium tuberculosis H37Rv (MTB), multi-drug resistant Mycobacterium tuberculosis (MDR-TB) and Mycobacterium smegmatis (MC 2) and also tested for the ability to inhibit the supercoiling activity of DNA gyrase from M. smegmatis. Among the synthesized compounds, 7-(3-(diethylcarbamoyl)piperidin-1-yl)-1-cyclopropyl-6-fluoro-1,4-dihydro-4-oxoquinoline-3-carboxylic acid (7I) was found to be the most active compound in vitro with MIC of 0.09 mu M against MTB and MDR-TB respectively. In the in vivo animal model 7I decreased the mycobacterial load in lung and spleen tissues with 2.53- and 4.88-log10 protections respectively at a dose of 50 mg/kg body weight. (C) 2007 Elsevier Masson SAS. All rights reserved.

ADAMIS: a database for medical information systems

This paper describes the design and implementation of ADAMIS (‘A database for medical information systems’). ADAMIS is a relational database management system for a general hospital environment. Apart from the usual database (DB) facilities of data definition and data manipulation, ADAMIS supports a query language called the ‘simplified medical query language’ (SMQL) which is completely end-user oriented and highly non-procedural. Other features of ADAMIS include provision of facilities for statistics collection and report generation. ADAMIS also provides adequate security and integrity features and has been designed mainly for use on interactive terminals.

Effect of human telomerase reverse transcriptase transfection on differentiation in BeWo choriocarcinoma cells

Arrest of proliferation is one of the prerequisites for differentiation of cytotrophoblasts into syncytiotrophoblasts, and thus during differentiation telomerase activity, as well as human telomerase reverse transcriptase (hTERT) expression, is down-regulated. Considering this, it is of interest to investigate whether syncytium formation can be delayed by prolonging the expression of telomerase in cytotrophoblasts. BeWo cells were transfected with pLPC-hTERT retroviral vector and the reverse transcription-polymerase chain reaction analysis for hTERT mRNA concentrations in the transfected cells revealed a several-fold increase in hTERT mRNA compared with the cells transfected with empty vector, and this confirmed that the transfection was successful. An increase in the proliferation, as assessed by bromodeoxyuridine incorporation assay, as well as an increase in mRNA and protein concentration of various cyclins and proliferating cell nuclear antigen, was noticed. The effect of hTERT transfection was also assessed after the addition of forskolin to induce differentiation and it was observed that cell–cell fusion was delayed and differentiation did not occur in hTERT-transfected cells. However, the effects seen were only transient as stable transfection was not possible and the cells were undergoing apoptosis after 72 h, which suggested that apart from hTERT other factors might be important for immortalization of BeWo cells.

A Framework for Detecting Glaucomatous Progression in the Optic Nerve Head of an Eye Using Proper Orthogonal Decomposition

Glaucoma is the second leading cause of blindness worldwide. Often, the optic nerve head (ONH) glaucomatous damage and ONH changes occur prior to visual field loss and are observable in vivo. Thus, digital image analysis is a promising choice for detecting the onset and/or progression of glaucoma. In this paper, we present a new framework for detecting glaucomatous changes in the ONH of an eye using the method of proper orthogonal decomposition (POD). A baseline topograph subspace was constructed for each eye to describe the structure of the ONH of the eye at a reference/baseline condition using POD. Any glaucomatous changes in the ONH of the eye present during a follow-up exam were estimated by comparing the follow-up ONH topography with its baseline topograph subspace representation. Image correspondence measures of L-1-norm and L-2-norm, correlation, and image Euclidean distance (IMED) were used to quantify the ONH changes. An ONH topographic library built from the Louisiana State University Experimental Glaucoma study was used to evaluate the performance of the proposed method. The area under the receiver operating characteristic curves (AUCs) was used to compare the diagnostic performance of the POD-induced parameters with the parameters of the topographic change analysis (TCA) method. The IMED and L-2-norm parameters in the POD framework provided the highest AUC of 0.94 at 10 degrees. field of imaging and 0.91 at 15 degrees. field of imaging compared to the TCA parameters with an AUC of 0.86 and 0.88, respectively. The proposed POD framework captures the instrument measurement variability and inherent structure variability and shows promise for improving our ability to detect glaucomatous change over time in glaucoma management.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

Proteomic profiling of forskolin-induced differentiated BeWo cells: an in-vitro model of cytotrophoblast differentiation

Placental trophoblastic differentiation is characterized by the fusion of monolayer cytotrophoblasts into syncytiotrophoblasts. During this process of differentiation, several morphological and biochemical changes are known to occur, and this model has been employed to investigate the changes that occur at the gene and protein level during differentiation. Using the sensitive technique of proteomics [two-dimensional gel electrophoresis (2DGE)], changes in protein profile were evaluated in the control and forskolin-induced differentiated cells of trophoblastic choriocarcinoma BeWo cell line. Several proteins were differentially expressed in control and differentiated cells. Four major proteins were up-regulated as assessed by silver staining, and were further characterized as c-h-ras p 21 (phosphorylated), retinoblastoma susceptibility protein I and integrase interactor protein 1. These proteins are known to play an important role in growth arrest of cells, and thus may play a role in initiating the process of differentiation.

Lectin Microarrays for Glycomic Analysis

Glycomics is the study of comprehensive structural elucidation and characterization of all glycoforms found in nature and their dynamic spatiotemporal changes that are associated with biological processes. Glycocalyx of mammalian cells actively participate in cell-cell, cell-matrix, and cell-pathogen interactions, which impact embryogenesis, growth and development, homeostasis, infection and immunity, signaling, malignancy, and metabolic disorders. Relative to genomics and proteomics, glycomics is just growing out of infancy with great potential in biomedicine for biomarker discovery, diagnosis, and treatment. However, the immense diversity and complexity of glycan structures and their multiple modes of interactions with proteins pose great challenges for development of analytical tools for delineating structure function relationships and understanding glycocode. Several tools are being developed for glycan profiling based on chromatography,m mass spectrometry, glycan microarrays, and glyco-informatics. Lectins, which have long been used in glyco-immunology, printed on a microarray provide a versatile platform for rapid high throughput analysis of glycoforms of biological samples. Herein, we summarize technological advances in lectin microarrays and critically review their impact on glycomics analysis. Challenges remain in terms of expansion to include nonplant derived lectins, standardization for routine clinical use, development of recombinant lectins, and exploration of plant kingdom for discovery of novel lectins.

Computation of restoration of ligand response in the random kinetics of a prostate cancer cell signaling pathway

Mutation and/or dysfunction of signaling proteins in the mitogen activated protein kinase (MAPK) signal transduction pathway are frequently observed in various kinds of human cancer. Consistent with this fact, in the present study, we experimentally observe that the epidermal growth factor (EGF) induced activation profile of MAP kinase signaling is not straightforward dose-dependent in the PC3 prostate cancer cells. To find out what parameters and reactions in the pathway are involved in this departure from the normal dose-dependency, a model-based pathway analysis is performed. The pathway is mathematically modeled with 28 rate equations yielding those many ordinary differential equations (ODE) with kinetic rate constants that have been reported to take random values in the existing literature. This has led to us treating the ODE model of the pathways kinetics as a random differential equations (RDE) system in which the parameters are random variables. We show that our RDE model captures the uncertainty in the kinetic rate constants as seen in the behavior of the experimental data and more importantly, upon simulation, exhibits the abnormal EGF dose-dependency of the activation profile of MAP kinase signaling in PC3 prostate cancer cells. The most likely set of values of the kinetic rate constants obtained from fitting the RDE model into the experimental data is then used in a direct transcription based dynamic optimization method for computing the changes needed in these kinetic rate constant values for the restoration of the normal EGF dose response. The last computation identifies the parameters, i.e., the kinetic rate constants in the RDE model, that are the most sensitive to the change in the EGF dose response behavior in the PC3 prostate cancer cells. The reactions in which these most sensitive parameters participate emerge as candidate drug targets on the signaling pathway. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Autoregressive spectral array for graphical display of EEG data

A graphical display of the frequency content of background,electroencephalogram (EEG) activity is obtained by calculating the spectral estimates using autocorrelation autoregressive method and the classical Fourier transform method, Display of spectral content of consecutive data segments is made using hidden-line suppression technique so as to get a spectral array, The autoregressive spectral array (ASA) is found to be sensitive to baseline drift, Following baseline correction the autoregressive technique is found to be superior to the Fourier method of compressed spectral array (CSA) in detecting the transitions in the frequencies of the signal. The smoothed ASA gives a better picture of transitions and changes in the background activity, The ASA can be made to adapt to specific changes of dominant frequencies while eliminating unnecessary peaks in the spectrum. The utility,of the ASA for background EEG analysis is discussed,

Application of vibrational microspectroscopy to biology and medicine

Vibrational microspectroscopic (Raman and infrared (IR)) techniques are rapidly emerging as effective tools to probe the basic processes of life. This review mainly focuses on the applications of Raman and IR microspectroscopy to biology and biomedicine, ranging from studies on cellular components in single cells to advancement in techniques for in vitro to in vivo applications. These techniques have proved to be instrumental in studying the biological specimen with minimum perturbation, i.e. without the use of dyes and contrast-inducing agents. These techniques probe the vibrational modes of the molecules and provide spectra that are specific to the molecular properties and chemical nature of the species.

Computational Biology and Language

Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

NMR studies of preimplantation embryo metabolism in human assisted reproductive techniques: a new biomarker for assessment of embryo implantation potential

There has been growing interest in understanding energy metabolism in human embryos generated using assisted reproductive techniques (ART) for improving the overall success rate of the method. Using NMR spectroscopy as a noninvasive tool, we studied human embryo metabolism to identify specific biomarkers to assess the quality of embryos for their implantation potential. The study was based on estimation of pyruvate, lactate and alanine levels in the growth medium, ISM1, used in the culture of embryos. An NMR study involving 127 embryos from 48 couples revealed that embryos transferred on Day 3 (after 72 h in vitro culture) with successful implantation (pregnancy) exhibited significantly (p < 10(-5)) lower pyruvate/alanine ratios compared to those that failed to implant. Lactate levels in media were similar for all embryos. This implies that in addition to lactate production, successfully implanted embryos use pyruvate to produce alanine and other cellular functions. While pyruvate and alanine individually have been used as biomarkers, the present study highlights the potential of combining them to provide a single parameter that correlates strongly with implantation potential. Copyright (C) 2012 John Wiley & Sons, Ltd.

Biomimetic molecular organization of naphthalene diimide in the solid state: tunable (chiro-) optical, viscoelastic and nanoscale properties

The interfacing of aromatic molecules with biomolecules to design functional molecular materials is a promising area of research. Intermolecular interactions determine the performance of these materials and therefore, precise control over the molecular organization is necessary to improve functional properties. Herein we describe the tunable biomimetic molecular engineering of a promising n-type organic semiconductor, naphthalene diimide (NDI), in the solid state by introducing minute structural mutations in the form of amino acids with variable Ca-functionality. For the first time we could achieve all four possible crystal packing modes, namely cofacial, brickwork, herringbone and slipped stacks of the NDI system. Furthermore, amino acid conjugated NDIs exhibit ultrasonication induced organogels with tunable visco-elastic and temperature responsive emission properties. The amino acid-NDI conjugates self-assemble into 0D nanospheres and 1D nanofibers in their gel state while the ethylamine-NDI conjugate forms 2D sheets from its solution. Photophysical studies indicated the remarkable influence of molecular ordering on the absorption and fluorescence properties of NDIs. Interestingly, the circular dichroism (CD) and X-ray diffraction (XRD) studies revealed the existence of helical ordering of NDIs in both solution and solid state. The chiral amino acids and their conformations with respect to the central NDI core are found to influence the nature of the helical organization of NDIs. Consequently, the origin of the preferential handedness in the helical organization is attributed to transcription of chiral information from the amino acid to the NDI core. On account of these unique properties, the materials derived from NDI-conjugates might find a wide range of future interdisciplinary applications from materials to biomedicine.