Gene expression profile of epithelial cells and mesenchymal cells derived from limbal explant culture

Purpose: Limbal stem cell deficiency is a challenging clinical problem and the current treatment involves replenishing the depleted limbal stem cell (LSC) pool by either limbal tissue transplantation or use of cultivated limbal epithelial cells (LEC). Our experience of cultivating the LEC on denuded human amniotic membrane using a feeder cell free method, led to identification of mesenchymal cells of limbus (MC-L), which showed phenotypic resemblance to bone marrow derived mesenchymal stem cells (MSC-BM). To understand the transcriptional profile of these cells, microarray experiments were carried out.Methods: RNA was isolated from cultured LEC, MC-L and MSC-BM and microarray experiments were carried out by using Agilent chip (4x44 k). The microarray data was validated by using Realtime and semiquntitative reverse transcription polymerase chain reaction. Results: The microarray analysis revealed specific gene signature of LEC and MC-L, and also their complementary role related to cytokine and growth factor profile, thus supporting the nurturing roles of the MC-L. We have also observed similar and differential gene expression between MC-L and MSC-BM.Conclusions: This study represents the first extensive gene expression analysis of limbal explant culture derived epithelial and mesenchymal cells and as such reveals new insight into the biology, ontogeny, and in vivo function of these cells.

Artificial database for character recognition research

This paper describes a technique for artificial generation of learning and test sample sets suitable for character recognition research. Sample sets of English (Latin), Malayalam, Kannada and Tamil characters are generated easily through their prototype specifications by the endpoint co-ordinates, nature of segments and connectivity.

Maturation of a transient outward potassium current in mouse fetal hypothalamic neurons in culture

The whole-cell voltage clamp technique was used to record potassium currents in mouse fetal hypothalamic neurons developing in culture medium from days 1 to 17. The neurons were derived from fetuses of IOPS/OF1 mice on the 14th day of gestation. The mature neurons (>six days in culture) showed both a transient potassium current and a non-inactivating delayed rectifier potassium current. These were identified pharmacologically by using the potassium channel blockers tetraethyl ammonium chloride and 4-aminopyridine, and on the basis of their kinetics and voltage sensitivities. The delayed rectifier potassium current had a threshold of −20 mV, a slow time-course of activation, and was sustained during the voltage pulse. The 4-aminopyridine-sensitive current was transient, and was activated from a holding potential more negative (−80 mV) than that required for evoking the delayed rectifier potassium current (−40 mV). The delayed rectifier potassium current was detectable from day 1 onwards, while the transient potassium current showed a distinct developmental trend. The time-constant of inactivation became faster with age in culture. The half steady-state inactivation potential showed a shift towards less negative membrane potentials with age, and the relationship was best described by a logarithmic regression equation.The developmental trend of the transient potassium current may relate functionally to the progressive morphological changes, and the appearance of synaptic connections during ontogenesis.

Character recognition — A review

The machine replication of human reading has been the subject of intensive research for more than three decades. A large number of research papers and reports have already been published on this topic. Many commercial establishments have manufactured recognizers of varying capabilities. Handheld, desk-top, medium-size and large systems costing as high as half a million dollars are available, and are in use for various applications. However, the ultimate goal of developing a reading machine having the same reading capabilities of humans still remains unachieved. So, there still is a great gap between human reading and machine reading capabilities, and a great amount of further effort is required to narrow-down this gap, if not bridge it. This review is organized into six major sections covering a general overview (an introduction), applications of character recognition techniques, methodologies in character recognition, research work in character recognition, some practical OCRs and the conclusions.

Supermacroporous Polymer-Based Cryogel Bioreactor for Monoclonal Antibody Production in Continuous Culture Using Hybridoma Cells

Cryogel matrices composed of different polymeric blends were synthesized, yielding a unique combination of hydrophilicity and hydrophobicity with the presence or absence of charged surface. Four such cryogel matrices composed of polyacrylamide-chitosan (PAAC), poly(N-isopropylacrylamide)-chitosan, polyacrylonitrile (PAN), and poly(N-isopropylacrylamide) were tested for growth of different hybridoma cell lines and production of antibody in static culture. All the matrices were capable for the adherence of hybridoma cell lines 6A4D7, B7B10, and H9E10 to the polymeric surfaces as well as for the efficient monoclonal antibody (mAb) production. PAAC proved to be relatively better in terms of both mAb production and cell growth. Further, PAAC cryogel was designed into three different formats, monolith, disks, and beads, and used as packing material for packed-bed bioreactor. Longterm cultivation of 6A4D7 cell line on PAAC cryogel scaffold in all the three formats could be successfully done for a period of 6 weeks under static conditions. Continuous packed-bed bioreactor was setup using 6A4D7 hybridoma cell line in the three reactor formats. The reactors ran continuously for a period of 60 days during which mAb production and metabolism of cells in the bioreactors were monitored periodically. The monolith bioreactor performed most efficiently over a period of 60 days and produced a total of 57.5 mg of antibody in the first 30 days (in 500 mL) with a highest concentration of 115 mu g mL(-1), which is fourfold higher than t-flask culture. The results demonstrate that appropriate chemistry and geometry of the bioreactor matrix for cell growth and immobilization can enhance the reactor productivity. (C) 2010 American Institute of Chemical Engineers Biotechnol. Prog., 27: 170-180, 2011

A model for tool-use traditions in primates: implications for the coevolution of culture and cognition

Inspired by the demonstration that tool-use variants among wild chimpanzees and orangutans qualify as traditions (or cultures), we developed a formal model to predict the incidence of these acquired specializations among wild primates and to examine the evolution of their underlying abilities. We assumed that the acquisition of the skill by an individual in a social unit is crucially controlled by three main factors, namely probability of innovation, probability of socially biased learning, and the prevailing social conditions (sociability, or number of potential experts at close proximity). The model reconfirms the restriction of customary tool use in wild primates to the most intelligent radiation, great apes; the greater incidence of tool use in more sociable populations of orangutans and chimpanzees; and tendencies toward tool manufacture among the most sociable monkeys. However, it also indicates that sociable gregariousness is far more likely to produce the maintenance of invented skills in a population than solitary life, where the mother is the only accessible expert. We therefore used the model to explore the evolution of the three key parameters. The most likely evolutionary scenario is that where complex skills contribute to fitness, sociability and/or the capacity for socially biased learning increase, whereas innovative abilities (i.e., intelligence) follow indirectly. We suggest that the evolution of high intelligence will often be a byproduct of selection on abilities for socially biased learning that are needed to acquire important skills, and hence that high intelligence should be most common in sociable rather than solitary organisms. Evidence for increased sociability during hominin evolution is consistent with this new hypothesis. (C) 2003 Elsevier Science Ltd. All rights reserved.

Two Dimensional Principal Component Analysis for Online Tamil Character Recognition

This paper presents a new application of two dimensional Principal Component Analysis (2DPCA) to the problem of online character recognition in Tamil Script. A novel set of features employing polynomial fits and quartiles in combination with conventional features are derived for each sample point of the Tamil character obtained after smoothing and resampling. These are stacked to form a matrix, using which a covariance matrix is constructed. A subset of the eigenvectors of the covariance matrix is employed to get the features in the reduced sub space. Each character is modeled as a separate subspace and a modified form of the Mahalanobis distance is derived to classify a given test character. Results indicate that the recognition accuracy using the 2DPCA scheme shows an approximate 3% improvement over the conventional PCA technique.

Online character recognition using regression techniques

This paper introduces a scheme for classification of online handwritten characters based on polynomial regression of the sampled points of the sub-strokes in a character. The segmentation is done based on the velocity profile of the written character and this requires a smoothening of the velocity profile. We propose a novel scheme for smoothening the velocity profile curve and identification of the critical points to segment the character. We also porpose another method for segmentation based on the human eye perception. We then extract two sets of features for recognition of handwritten characters. Each sub-stroke is a simple curve, a part of the character, and is represented by the distance measure of each point from the first point. This forms the first set of feature vector for each character. The second feature vector are the coeficients obtained from the B-splines fitted to the control knots obtained from the segmentation algorithm. The feature vector is fed to the SVM classifier and it indicates an efficiency of 68% using the polynomial regression technique and 74% using the spline fitting method.

Texture and grain boundary character distribution during Equal Channel Angular Extrusion of some two-phase copper alloys

In the present work, a thorough investigation of evolution of microstructure and texture has been carried out to elucidate the evolution of texture and grain boundary character distribution (GBCD) during Equal Channel Angular Extrusion (ECAE) of some model two-phase materials, namely Cu-0.3Cr and Cu-40Zn. Texture of Cu-0.3Cr alloy is similar to that reported for pure copper. On the other hand, in Cu-40Zn alloy, texture evolution in α and β (B2) phases are interdependent. In Cu-0.3Cr alloy, there is a considerable decreases in volume fraction of low angle boundaries (LAGBs), only a slight increase in CSL boundaries, but increase in high angle grain boundaries (HAGBs) from 1 pass to 4 passes for both the routes. In the case of Cu-40Zn alloy, there is an appreciable increase in CSL volume fraction.