Structural studies of protein unfolding

Methods for macromolecular structure determination (NMR and crystallography) are now being used to get structural information on partially folded and unfolded states of proteins. These techniques, in combination with proton hydrogen exchange studies are powerful tools to extract information on non-native states of proteins. This review discusses progress In this area of protein folding.

Hidden order in serrated flow of metallic glasses

We report results of statistical and dynamic analysis of the serrated stress-time curves obtained from compressive constant strain-rate tests on two metallic glass samples with different ductility levels in an effort to extract hidden information in the seemingly irregular serrations. Two distinct types of dynamics are detected in these two alloy samples. The stress-strain curve corresponding to the less ductile Zr65Cu15Ni10Al10 alloy is shown to exhibit a finite correlation dimension and a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. In contrast, for the more ductile Cu47.5Zr47.5Al5 alloy, the distributions of stress drop magnitudes and their time durations obey a power-law scaling reminiscent of a self-organized critical state. The exponents also satisfy the scaling relation compatible with self-organized criticality. Possible physical mechanisms contributing to the two distinct dynamic regimes are discussed by drawing on the analogy with the serrated yielding of crystalline samples. The analysis, together with some physical reasoning, suggests that plasticity in the less ductile sample can be attributed to stick-slip of a single shear band, while that of the more ductile sample could be attributed to the simultaneous nucleation of a large number of shear bands and their mutual interactions. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Progesterone receptor expression in the human placenta

The presence of progesterone receptors (PR) in the human placenta has been demonstrated using the reverse transcriptase-polymerase chain reaction technique. It was observed that the amount of PR in the human placenta is less during late gestation. Electrophoretic mobility shift assays with nuclear extract isolated from the first trimester and term placenta revealed three complexes when incubated with [P-32]dCTP-labelled progesterone response element, and, in competition with unlabelled progesterone response element, the formation of all three complexes was inhibited. When supershift analysis of these complexes was carried out using antibodies which cross-react with both the A and B types of the PR or only with the B type receptor, only the A-form of PR was detected in the human placenta.

Regulation of an 8-kDa peptide involved in testosterone production by luteinizing hormone in rat Leydig cells

Results of Western blot analysis carried out with an interstitial cell extract from male guinea pig and ovarian extract from immature female rats administered equine chorionic gonadotropin (eCG) provide supportive evidence to our earlier suggestion that an 8-kDa peptide is involved in acquisition of steroidogenic capacity by the rat Leydig cells. It was found that though the signal was observed in other tissues such as liver, kidney and lung which do not produce gonadal hormones, the peptide was modulated only by lutenizing hormone (LH) in the rat Leydig cells.

Transformations of morphine, codeine and their analogues by Bacillus sp

A bacterial strain belonging to the genus Bacillus isolated by enrichment culture technique using morphine as a sole source of carbon transforms morphine and codeine into 14-hydroxymorphinone and 14-hydroxycodeinone as major and 14-hydroxymorphine and 14-hydroxycodeine as minor metabolites, respectively. When the N-methyl group in morphine and codeine are replaced by higher alkyl groups, the organism still retains its ability to carry out 14-hydroxylation as well as oxidation of the C-6-hydroxyl group in these N-variants, although the level of metabolites formed are considerably low. The organism readily transforms dihydromorphine and dihydrocodeine into only dihydromorphinone and dihydrocodeinone, respectively; suggesting that the 7,8-double bond is a necessary structural feature to carry out 14-hydroxylation reaction. The cell free extract (20,000 x g supernatant), prepared from morphine grown cells, transforms morphine into 14-hydroxymorphinone in the presence of NAD(+), but fails to show activity against testosterone. However, the cell free extract prepared from testosterone grown cells contains significant levels of 17 beta- hydroxysteroid dehydrogenase but shows no activity against morphine.

Discovery of Application Workloads from Network File Traces

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.