Effect of BCG on Concanavalin A-induced Suppressor Cell Activity and Lymphocyte Stimulation in Stage I Melanoma

Suppressor cell activity was determined in 14 patients with stage I melanoma, treated with or without adjuvant Bacillus Calmette-Guerin (BCG) immunotherapy, and in 27 normal healthy volunteers. An in vitro test system was used in which peripheral blood mononuclear cells when stimulated with concanavalin A (ConA) significantly suppress proliferative responses of fresh autologous mononuclear cells. In addition, lymphocyte stimulation capacity to optimal and suboptimal concentrations of phytohemagglutinin (PHA) was determined in 44 BCG treated or not BCG treated melanoma patients and in 40 normal individuals.ConA induced suppressor cell activity was significantly (p < 0.02) impaired in BCG treated melanoma patients (21.3 ± 3.1% suppression) when compared to not BCG treated patients (39.8 ± 5.6%) or to normals (38.3 ± 9.3%). Lymphocyte stimulation capacity was depressed in all melanoma patients when suboptimal concentrations of PHA were used but was found to be not significantly altered at optimal concentration of PHA.The present study reveals that BCG immunotherapy impairs ConA induced suppressor cell activity in melanoma patients but does not influence lymphocyte stimulation capacity

Not a Matter of Interpretation

This Article explores the basic question of statutory interpretation. The disagreement among scholars is a theoretical one - it is a dispute about what the proper object of interpretation should be, about whether it should be what Scalia calls the objective indication of the words (what the authors said), or whether it should be the intent of the legislature (what the authors meant)

Recent advances in anion–π interactions

Over the past 10 years, anion–π interaction has been recognized as an important weak force that may occur between anionic systems and electron- deficient aromatics. Lately, this supramolecular contact has experienced a rapidly growing interest, as reflected by numerous recent literature reports. The present paper highlights the tremendous progress achieved in the field by emphasizing three important studies involving anion–π interactions published in 2010. In addition, a pioneering search of the Protein Data Bank (PDB) reveals short anion–π contacts in some protein structures

Prediction using step-wise L1, L2 regularization and feature selection for small data sets with large number of features

<p>Abstract</p> <p>Background</p> <p>Machine learning methods are nowadays used for many biological prediction problems involving drugs, ligands or polypeptide segments of a protein. In order to build a prediction model a so called training data set of molecules with measured target properties is needed. For many such problems the size of the training data set is limited as measurements have to be performed in a wet lab. Furthermore, the considered problems are often complex, such that it is not clear which molecular descriptors (features) may be suitable to establish a strong correlation with the target property. In many applications all available descriptors are used. This can lead to difficult machine learning problems, when thousands of descriptors are considered and only few (e.g. below hundred) molecules are available for training.</p> <p>Results</p> <p>The CoEPrA contest provides four data sets, which are typical for biological regression problems (few molecules in the training data set and thousands of descriptors). We applied the same two-step training procedure for all four regression tasks. In the first stage, we used optimized L1 regularization to select the most relevant features. Thus, the initial set of more than 6,000 features was reduced to about 50. In the second stage, we used only the selected features from the preceding stage applying a milder L2 regularization, which generally yielded further improvement of prediction performance. Our linear model employed a soft loss function which minimizes the influence of outliers.</p> <p>Conclusions</p> <p>The proposed two-step method showed good results on all four CoEPrA regression tasks. Thus, it may be useful for many other biological prediction problems where for training only a small number of molecules are available, which are described by thousands of descriptors.</p

Connectivity independent protein-structure alignment: a hierarchical approach

BACKGROUND: Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most of them ignore that structurally similar proteins can share the same spatial arrangement of secondary structure elements (SSE) but differ in the underlying polypeptide chain connectivity (non-sequential SSE connectivity). RESULTS: We perform protein-structure alignment using a two-level hierarchical approach implemented in the program GANGSTA. On the first level, pair contacts and relative orientations between SSEs (i.e. α-helices and β-strands) are maximized with a genetic algorithm (GA). On the second level residue pair contacts from the best SSE alignments are optimized. We have tested the method on visually optimized structure alignments of protein pairs (pairwise mode) and for database scans. For a given protein structure, our method is able to detect significant structural similarity of functionally important folds with non-sequential SSE connectivity. The performance for structure alignments with strictly sequential SSE connectivity is comparable to that of other structure alignment methods. CONCLUSION: As demonstrated for several applications, GANGSTA finds meaningful protein-structure alignments independent of the SSE connectivity. GANGSTA is able to detect structural similarity of protein folds that are assigned to different superfamilies but nevertheless possess similar structures and perform related functions, even if these proteins differ in SSE connectivity

Influence of Complex Exciton-Phonon Coupling on Optical Absorption and Energy Transfer of Quantum Aggregates

We present a theory that efficiently describes the quantum dynamics of an electronic excitation that is coupled to a continuous, highly structured phonon environment. Based on a stochastic approach to non-Markovian open quantum systems, we develop a dynamical framework that allows us to handle realistic systems where a fully quantum treatment is desired yet the usual approximation schemes fail. The capability of the method is demonstrated by calculating spectra and energy transfer dynamics of mesoscopic molecular aggregates, elucidating the transition from fully coherent to incoherent transfer

Protonation State-Dependent Communication in Cytochrome c Oxidase

Proton transfer in cytochrome c oxidase from the cellular inside to the binuclear redox center (BNC) can occur through two distinct pathways, the D- and K-channels. For the protein to function as both a redox enzyme and a proton pump, proton transfer into the protein toward the BNC or toward a proton loading site (and ultimately through the membrane) must be highly regulated. The PR → F transition is the first step in a catalytic cycle that requires proton transfer from the bulk at the N-side to the BNC. Molecular dynamics simulations of the PR → F intermediate of this transition, with 16 different combinations of protonation states of key residues in the D- and K-channel, show the impact of the K-channel on the D-channel to be protonation-state dependent. Strength as well as means of communication, correlations in positions, or communication along the hydrogen-bonded network depends on the protonation state of the K-channel residue K362. The conformational and hydrogen-bond dynamics of the D-channel residue N139 is regulated by an interplay of protonation in the D-channel and K362. N139 thus assumes a gating function by which proton passage through the D-channel toward E286 is likely facilitated for states with protonated K362 and unprotonated E286. In contrast, proton passage through the D-channel is hindered by N139’s preference for a closed conformation in situations with protonated E286

Insights from surface enhanced resonance Raman spectroscopy and QM/MM calculations

Understanding the coupling between heme reduction and proton translocation in cytochrome c oxidase (CcO) is still an open problem. The propionic acids of heme a3 have been proposed to act as a proton loading site (PLS) in the proton pumping pathway, yet this proposal could not be verified by experimental data so far. We have set up an experiment where the redox states of the two hemes in CcO can be controlled via external electrical potential. Surface enhanced resonance Raman (SERR) spectroscopy was applied to simultaneously monitor the redox state of the hemes and the protonation state of the heme propionates. Simulated spectra based on QM/MM calculations were used to assign the resonant enhanced CH2 twisting modes of the propionates to the protonation state of the individual heme a and heme a3 propionates respectively. The comparison between calculated and measured H2OD2O difference spectra allowed a sound band assignment. In the fully reduced enzyme at least three of the four heme propionates were found to be protonated whereas in the presence of a reduced heme a and an oxidized heme a3 only protonation of one heme a3 propionates was observed. Our data supports the postulated scenario where the heme a3 propionates are involved in the proton pathway