Prediction of reaeration rates in square, stirred tanks

Experiments were conducted on the oxygen transfer coefficient, k(L)a(20), through surface aeration in geometrically similar square tanks, with a rotor of diameter D fitted with six flat blades. An optimal geometric similarity of various linear dimensions, which produced maximum k(L)a(20) for any rotational speed of rotor N by an earlier study, was maintained. A simulation equation uniquely correlating k = k(L)a(20)(nu/g(2))(1/3) (nu and g are kinematic viscosity of water and gravitational constant, respectively), and a parameter governing the theoretical power per unit volume, X = (ND2)-D-3/(g(4/3)nu(1/3)), is developed. Such a simulation equation can be used to predict maximum k for any N in any size of such geometrically similar square tanks. An example illustrating the application of results is presented. Also, it has been established that neither the Reynolds criterion nor the Froude criterion is singularly valid to simulate either k or K = k(L)a(20)/N, simultaneously in all the sizes of tanks, even through they are geometrically similar. Occurrence of "scale effects" due to the Reynolds and the Froude laws of similitude on both k and K are also evaluated.

Preincubation of cut tobacco leaf explants promotes Agrobacterium-mediated transformation by increasing vir gene induction

The effects of preincubation of cut tobacco leaf explants on Agrobacterium transformation efficiency and induction of Agrobacterium virE-lacZ fusion were evaluated. Transformation efficiency was evaluated by histochemical and fluorometric analysis of beta-glucuronidase in leaf rings transformed with Agrobacterium tumefaciens strain LBA4404(pKIWI105). The transformation efficiency increased by 2-fold, 5-fold, and 4.3-fold upon preincubation for 24, 48, and 72 h, respectively. Preincubation for 24, 48, and 72 h increased the ability of tobacco leaf segments to induce Agrobacterium virE by 2.3-fold, 3.5-fold and 4.5-fold, respectively. The requirement of preincubation for increased transformation efficiency was obviated by the addition of 100 mu M acetosyringone to the freshly cut leaf rings cocultivated with Agrobacterium. The production of vii gene inducers by the leaf rings during the preincubation period is an important factor that contributes to increased transformation efficiency of Agrobacterium upon preincubation. (C) 1999 Elsevier Science Ireland Ltd. All rights reserved.

Advantage of the ether linkage between the positive charge and the cholesteryl skeleton in cholesterol-based amphiphiles as vectors for gene delivery

Twelve novel cationic cholesterol derivatives with different linkage types between the cationic headgroup and the cholesteryl backbone have been developed. These have been tested for their efficacies as gene transfer agents as mixtures with dioleoyl phosphatidylethanolamine (DOPE). A pronounced improvement in transfection efficiency was observed when the cationic center was linked to the steroid backbone using an ether type bond. Among these, cholest-5-en-3b-oxyethane-N, N,N-trimethylammonium bromide (2a) and cholest-5-en-3b-oxyethane-N, N-dimethyl-N-2-hydroxyethylammonium bromide (3d) showed transfection efficiencies considerably greater than commercially available reagents such as Lipofectin or Lipofectamine. To achieve transfection, 3d did not require DOPE. Increasing hydration at the headgroup level for both ester- and ether-linked amphiphiles resulted in progressive loss of transfection efficiency. Transfection efficiency was also greatly reduced when a 'disorder'-inducing chain like an oleyl (cis-9-octadecenyl) segment was added to these cholesteryl amphiphiles. Importantly, the transfection ability of 2a with DOPE in the presence of serum was significantly greater than for a commercially available reagent, Lipofectamine. This suggests that these novel cholesterol-based amphiphiles might prove promising in applications involving liposome-mediated gene transfection. This investigation demonstrates the importance of structural features at the molecular level for the design of cholesterol-based gene delivery reagents that would aid the development of newer, more efficient formulations based on this class of molecules.

Gene Expression Profiling of Preovulatory Follicle in the Buffalo Cow: Effects of Increased IGF-I Concentration on Periovulatory Events

The preovulatory follicle in response to gonadotropin surge undergoes dramatic biochemical, and morphological changes orchestrated by expression changes in hundreds of genes. Employing well characterized bovine preovulatory follicle model, granulosa cells (GCs) and follicle wall were collected from the preovulatory follicle before, 1, 10 and 22 h post peak LH surge. Microarray analysis performed on GCs revealed that 450 and 111 genes were differentially expressed at 1 and 22 h post peak LH surge, respectively. For validation, qPCR and immunocytochemistry analyses were carried out for some of the differentially expressed genes. Expression analysis of many of these genes showed distinct expression patterns in GCs and the follicle wall. To study molecular functions and genetic networks, microarray data was analyzed using Ingenuity Pathway Analysis which revealed majority of the differentially expressed genes to cluster within processes like steroidogenesis, cell survival and cell differentiation. In the ovarian follicle, IGF-I is established to be an important regulator of the above mentioned molecular functions. Thus, further experiments were conducted to verify the effects of increased intrafollicular IGF-I levels on the expression of genes associated with the above mentioned processes. For this purpose, buffalo cows were administered with exogenous bGH to transiently increase circulating and intrafollicular concentrations of IGF-I. The results indicated that increased intrafollicular concentrations of IGF-I caused changes in expression of genes associated with steroidogenesis (StAR, SRF) and apoptosis (BCL-2, FKHR, PAWR). These results taken together suggest that onset of gonadotropin surge triggers activation of various biological pathways and that the effects of growth factors and peptides on gonadotropin actions could be examined during preovulatory follicle development.

Multivariate nonlinear ensemble prediction of daily chaotic rainfall with climate inputs

The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.

Phenobarbitone-mediated translocation of the cytosolic proteins interacting with the 5 '-proximal region of rat liver CYP2B1/B2 gene into the nucleus

The positive element (PE) (-69 to -98 bp) within the 5'-proximal region of the CYP2B1B2 gene (+1 to -179 bp) of rat liver is essential for phenobarbitone (PB) response and gives a single major complex with the rat liver cytosol in gel shift analysis. This complex corresponds to complex I (top) of the three complexes given by the nuclear extracts. PB treatment of rats leads to a decrease in complex I formation with the cytosol and PE and an increase in the same with the nuclear extract in gel shift analysis. Both the changes are counteracted by simultaneous okadaic acid administration. The nuclear protein giving rise to complex I has been isolated and has an M-r of 26 kDa. The cytosolic counterpart consists of two species, 26 and 28 kDa, as revealed by Southwestern blot analysis using labeled PE. It is concluded that PB treatment leads to the translocation accompanied by processing of the cytosolic protein species into the nucleus that requires protein dephosphorylation. It is suggested that PB may exert a global regulation on the transcription of many genes by modulating the phosphorylation status of different protein factors involved in transcriptional regulation. (C) 2002 Elsevier Science (USA).

An investigation into the feasibility of fetal lung maturity prediction using statistical textural features

Fetal lung and liver tissues were examined by ultrasound in 240 subjects during 24 to 38 weeks of gestational age in order to investigate the feasibility of predicting the maturity of the lung from the textural features of sonograms. A region of interest of 64 X 64 pixels is used for extracting textural features. Since the histological properties of the liver are claimed to remain constant with respect to gestational age, features obtained from the lung region are compared with those from liver. Though the mean values of some of the features show a specific trend with respect to gestation age, the variance is too high to guarantee definite prediction of the gestational age. Thus, we restricted our purview to an investigation into the feasibility of fetal lung maturity prediction using statistical textural features. Out of 64 features extracted, those features that are correlated with gestation age and less computationally intensive are selected. The results of our study show that the sonographic features hold some promise in determining whether the fetal lung is mature or immature.

Characterization of the gene encoding the envelope fusion glycoprotein GP64 from Bombyx mori nucleopolyhedrovirus

We describe here the characterization of the gene gp64 encoding the envelope fusion protein GP64 (open reading frame) ORF 105 from Bombyx mori nucleopolyhedrovirus (BmNPV). gp64 was transcribed from the early to late stages of infection and the transcripts were seen from 6 to 72 h post infection (hpi). The early transcripts initiated from a consensus CAGT motif while the late transcripts arose from three conserved TAAG motifs, all of which were located in the near upstream region of the coding sequence. Both early and late transcripts terminated at a run of T residues following the second polyadenylation signal located 31 nt downstream of the translation termination codon. BmGP64 protein was detectable from 6 hpi and was present in larger quantities throughout the infection process from 12 hpi, in BmNPV-infected BmN cells. The persistent presence of GP64 in BmN cells differed from the protein expression pattern of GP64 in Autographa californica multinucleocapsid nucleopolyhedrovirus infection, where the protein levels decreased significantly by late times (48 hpi). BmGP64 was located in the membrane and cytoplasm of the infected host cells and as a component of the budded virions. The production of infectious budded virus and the fusion activity were reduced when glycosylation of GP64 was inhibited. (C) 2003 Elsevier Science B.V. All rights reserved.

Identification of a core promoter and a novel isoform of the human TSCI gene transcript and structural comparison with mouse homolog

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder with loci on chromosome 9q34.12 (TSC1) and chromosome 16p13.3 (TSC2). Genes for both loci have been isolated and characterized. The promoters of both genes have not been characterized so far and little is known about the regulation of these genes. This study reports the characterization of the human TSC1 promoter region for the first time. We have identified a novel alternative isoform in the 5' untranslated region (UTR) of the TSC1 gene transcript involving exon 1. Alternative isoforms in the 5' UTR of the mouse Tsc1 gene transcript involving exon I and exon 2 have also been identified. We have identified three upstream open reading frames (uORFs) in the 5' UTR of the TSC1/Tsc1 gene. A comparative study of the 5' UTR of TSC1/Tsc1 gene has revealed that there is a high degree of similarity not only in the sequence but also in the splicing pattern of both human and mouse TSC1 genes. We have used PCR methodology to isolate approximately 1.6 kb genomic DNA 5' to the TSC1 cDNA. This sequence has directed a high level of expression of luciferase activity in both HeLa and HepG2 cells. Successive 5' and 3' deletion analysis has suggested that a -587 bp region, from position +77 to -510 from the transcription start site (TSS), contains the promoter activity. Interestingly, this region contains no consensus TATA box or CAAT box. However, a 521-bp fragment surrounding the TSS exhibits the characteristics of a CpG island which overlaps with the promoter region. The identification of the TSC1 promoter region will help in designing a suitable strategy to identify mutations in this region in patients who do not show any mutations in the coding regions. It will also help to study the regulation of the TSC1 gene and its role in tumorigenesis. (C) 2003 Elsevier B.V. All rights reserved.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Stress-Strain Prediction of Jointed Rocks using Artificial Neural Networks

The applicability of Artificial Neural Networks for predicting the stress-strain response of jointed rocks at varied confining pressures, strength properties and joint properties (frequency, orientation and strength of joints) has been studied in the present paper. The database is formed from the triaxial compression tests on different jointed rocks with different confining pressures and different joint properties reported by various researchers. This input data covers a wide range of rock strengths, varying from very soft to very hard. The network was trained using a 3 layered network with feed forward back propagation algorithm. About 85% of the data was used for training and remaining15% for testing the predicting capabilities of the network. Results from the analyses were very encouraging and demonstrated that the neural network approach is efficient in capturing the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different rocks, whose intact strength vary from 11.32 MPa to 123 MPa and spacing of joints vary from 10 cm to 100 cm for confining pressures ranging from 0 to 13.8 MPa.