Three dimensional reconstruction of brain tumor along with space occupying in lesions

Multimedia Tools and Applications - The three-dimensional models of brain tumors serve as diagnostic assistance for physicians, surgeons, and radiologists. The proposed system establishes an...     

Role of Zinc (Zn) in Human Reproduction: A Journey from Initial Spermatogenesis to Childbirth

Zinc (Zn), the second-most necessary trace element, is abundant in the human body. The human body lacks the capacity to store Zn; hence, the dietary intake of Zn is essential for various functions and metabolism. The uptake of Zn during its transport through the body is important for proper development of the three major accessory sex glands: the testis, epididymis, and prostate. It plays key roles in the initial stages of germ cell development and spermatogenesis, sperm cell development and maturation, ejaculation, liquefaction, the binding of spermatozoa and prostasomes, capacitation, and fertilization. The prostate releases more Zn into the seminal plasma during ejaculation, and it plays a significant role in sperm release and motility. During the maternal, labor, perinatal, and neonatal periods, the part of Zn is vital. The average dietary intake of Zn is in the range of 8–12 mg/day in developing countries during the maternal period. Globally, the dietary intake of Zn varies for pregnant and lactating mothers, but the average Zn intake is in the range of 9.6–11.2 mg/day. The absence of Zn and the consequences of this have been discussed using critical evidence. The events and functions of Zn related to successful fertilization have been summarized in detail. Briefly, our current review emphasizes the role of Zn at each stage of human reproduction, from the spermatogenesis process to childbirth. The role of Zn and its supplementation in in vitro fertilization (IVF) opens opportunities for future studies on reproductive biology.     

Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

Simple schemes for parallel acquisition of spreading sequences inDS/SS systems

Suboptimal parallel schemes for the acquisition of spreading sequences in chip-asynchronous spread-spectrum systems are considered. These acquisition schemes estimate the unknown delay of the received signal with respect to a locally generated spreading code. Two schemes are presented which are considerably easier to implement than the optimal estimator. An analytical expression is given for the error probability of the simpler of the two schemes, and it is shown that the average error probability of this scheme decreases exponentially with the signal-to-noise ratio. Numerical results show that the performance of both suboptimal estimators is comparable to that of the optimal estimator     

Sulfated zirconia catalysts: Are Brønsted acid sites the source of the activity?

The thermal decomposition products of pyridinium sulfate differ from those of pyridinium sulfate supported on zirconia which in turn differs from that of pyridine adsorbed on a sulfated zirconia. Unsupported pyridinium sulfate decomposes to produce pyridine and sulfuric acid, and these subsequently react to produce oxides of carbon and sulfur. Zirconia that is sulfated and then exposed to pyridine does not release detectable amount of pyridine during heating in an inert gas; rather the pyridine undergoes oxidation reduction reactions simultaneously to release CO₂ and sulfur compounds. Pyridinium sulfate supported on zirconia decomposes upon heating to release pyridine and sulfuric acid, which reacts with the zirconia. The desorption of pyridine in one case and only CO₂/SO_x in the other case suggests that sulfated zirconia does not contain Brønsted acidity that can form pyridinium sulfate.     

High char‐yielding poly[acrylonitrile‐co‐(itaconic acid)‐co‐(methyl acrylate)]: synthesis and properties

Polyacrylonitrile terpolymers of various compositions consisting of acrylonitrile (AN), itaconic acid (IA) and methyl acrylate (MA) were synthesized by solution polymerization in dimethylsulfoxide. Increase in concentration of either IA or MA retarded the overall polymerization rate and the polymer molecular weight. The system consisting of AN + MA and varying IA concentration was more prone to retardation in comparison with the system composed of AN + IA with variable MA concentration. The retardation factors were quantified. Minor quantities of MA boost the reactivity of IA in the terpolymer system. The terpolymer was richer in MA vis‐à‐vis the feed. The thermal characteristics of the terpolymer were examined as a function of its composition. In contrast to the copolymer of AN and IA requiring 1–1.5 mol% IA, the terpolymer required an IA content of approximately 2.5 mol% for optimum thermal stability. The polymer with 90 mol% AN, 2.5 mol% IA and 7.5 mol% MA exhibited reasonably good char‐forming characteristics and thermal stability. The overall crystallinity and crystallite size of the polymers were found to decrease on incorporation of the comonomers. The ‘aromatization index’ of the copolymer increased with the temperature of pyrolysis through re‐organization of the tetrahydropyridine ladder structure. Copyright © 2005 Society of Chemical Industry     

Development of the human fetal visceral pleura. An ultrastructural study

OBJECTIVE: To develop a method to predict long-term outcome after head injury and determine if outcome can be accurately predicted 24 hours after injury. DESIGN: A retrospective review was performed on a study cohort of 672 head-injured patients admitted in coma (Glascow Coma Scale score < or = 8) who remained comatose for at least 6 hours, survived more than 24 hours, and had 6-month outcome data available. Stepwise logistic regression analysis was used to determine which clinical variables predicted 6-month outcome. Statistically significant clinical predictors were combined into a single examination variable (MPX score), which reflected a rank-ordering of examinations from worst to best, which was then further weighted by patient age. The relation between 6-month outcome and MPX score at admission and 24 hours was plotted and analyzed. MEASUREMENT AND MAIN RESULTS: Age, best motor score, and pupillary reactivity at admission and 24 hours were significant predictors of outcome; extraocular motility was predictive at 24 hours only. Age was the most important independent predictor, followed by best motor score, pupillary reactivity, and extraocular motility. Combining these predictors into MPX score resulted in a set of graphs that reliably predicted long-term outcome. The 24-hour MPX data were better predictors of 6-month outcome and were more specific in predicting negative outcomes than admission data. CONCLUSIONS: The method is simple to use, relying on bedside neurologic examination and a single graph, but appears to predict long-term outcome accurately as early as 24 hours after head injury. If validated on other large series of patients, this method could provide an objective and practical basis for terminating care in patients unlikely to survive a head injury.     

Cytoplasmic tail deletion of T cell receptor (TCR) beta-chain results in its surface expression as glycosylphosphatidylinositol-anchored polypeptide on mature T cells in the absence of TCR-alpha

Surface expression of the T cell antigen receptor (TCR) in mature T cells requires the association of a variable heterodimer (alpha.beta or gamma.delta) with six invariant CD3 polypeptides (gamma, delta, epsilon-epsilon, zeta-zeta, or zeta-eta). We described here that deletion of the cytoplasmic tail polypeptide sequence (Lys-Lys-Lys-Asn-Ser) of TCR beta-chain (beta CT) results in expression of the truncated beta-chain on the surface of a mature T cell hybridoma line, in the absence of TCR-alpha, as a glycophosphatidylinositol (GPI)-anchored monomeric polypeptide. The GPI-anchored TCR-beta CT is not associated with CD3-epsilon and is incapable of conventional signal transduction. Association with TCR-alpha prevents beta CT from GPI-linkage formation. The alpha beta CT heterodimer binds the CD3 polypeptides, and the resultant TCR alpha beta CT/CD3 complex is capable of signal transduction. Our data show that a signal sequence for GPI-linkage formation is present in TCR-beta, and this alternative membrane anchoring mechanism can be utilized by beta-chain polypeptide lacking the CT sequence. We conclude therefore that in the absence of TCR-alpha expression, the beta-chain CT sequence plays an essential function in hindering GPI-linkage formation, thereby preventing escape of incompletely assembled TCR beta-chain to the cell surface of mature T cells.