Infrared spectroscopy of proteins

This review discusses the application of infrared spectroscopy to the study of proteins. The focus is on the mid-infrared spectral region and the study of protein reactions by reaction-induced infrared difference spectroscopy.     

Myosin light chain kinase binding to plastic

Methionine-81 and/or -8 of the transmembrane sialoglycoprotein, glycophorin A, have been specifically alkylated with ¹³CH₃I to produce the sulfonium ion derivatives [S-[¹³C]methylmethionine-8]glycophorin A and [S-[¹³C]methylmethionine-8 and -81]glycophorin A. ¹³C NMR spectra of these species show that the resonances of the methyl groups of the modified glycophorins occur at 26.1 ppm downfield from Me₄Si. A spin-lattice relaxation time of 0.4 was observed for the ¹³C-enriched methyl resonances of the sulfonium ion derivatives of Met-8 and -81, which corresponds to an effective correlation time of < 2× 10^?10 s. Demethylation of the 2 glycophorin A sulfonium ion species with 2-mercaptoethanol produces native glycophorin A which now has the ε-carbon of the methionine residue(s) 45% isotopically enriched. The ε-carbon of Met-8 was found to occur at 15.7 ppm downfield from Me₄Si whereas the ε-carbon of Met-81 exhibited an unusual chemical shift of 2.0 ppm downfield from Me₄Si. The spin-lattice relaxation time of both resonances was found to be ～0.3 s.     

Multiple mechanisms of cytochrome P450-catalyzed substrate hydroxylations

We have examined the 5-$\text{exo}$-hydroxylation of camphor by cytochrome P450 in [¹⁸O] water/buffer solution. In the $\text{NADH}\text{O}{}_2\text{-dependent}$ reaction of the reconstituted multienzyme system, no ¹⁸O-label is observed in the product alcohol. Similarly, in the m-chloroperbenzoic acid or cumene hydroperoxide supported reactions with ferric P450, solvent oxygen is not incorporated into hydroxycamphor. When the analagous reaction is carried out using iodosobenzene as the exogenous oxidant, however, the alcoholic oxygen of the product is derived entirely from the solvent. These results cannot be explained by equilibration of the iodosobenzene oxygen with solvent water before reacting with P450, and suggest a unique mechanism for iodosobenzene-supported P450 oxygenations. We propose two distinct mechanistic activities for cytochrome P450: a hydroxylase, and an oxene transferase, with the former encompassing the classic oxygenase as well as “peroxygenase” reactions.     

Synthesis and relative stereochemistry of the four mercapturic acids derived from styrene oxide and N-acetylcysteine

The chemical reaction between (±)-styrene oxide and N-acetylcysteine produces both positional isomers ($\text{1}$ and $\text{2}$) as a mixture of diastereoisomers with a preference for the benzylic thioether isomer $\text{1}$ (2 : 1). Synthesis of the mercapturic acid conjugates from either (+)- or (?)-styrene oxide produces only two of the four possible stereoisomers. The single diastereoisomers of $\text{1}$ and $\text{2}$ were separated by high pressure liquid chromatography (HPLC) and identified by ¹H- and ¹³C-nuclear magnetic resonance (NMR). The relative stereochemistry at the benzylic carbon center of the mercapturic acid conjugates was assigned on the basis of the established chemical correlation between optically pure styrene oxide and its precursor mandelic acid, and considerations on the mechanism of ring opening of epoxides by sulfur nucleophiles. The stereochemical definition of the isomers $\text{3}$–$\text{6}$ should prove useful in investigations of the biotransformation of the glutathione (GSH) conjugates of styrene oxide.     

A model for population regulation with density- and frequency-dependent selection

The life-cycle of a species with separate generations is divided into a reproduction phase and a growing-up phase. In the reproduction phase we assume random mating and selection due to genotype differences in fecundity of the parents and viability of the offspring. During the growing-up phase we assume a (deterministic) death process in continuous time with death rates for the genotypes which increase linearly with the genotype population sizes.In the absence of genotype differences the model gives logistic population regulation. With genotype differences the model generalizes the usual separate generations selection patterns. In addition to these we exhibit cases with three polymorphic equilibria or with a stable cycle.     

基于小波神经网络的麦蚜发生程度预测模型

【目的】建立基于小波神经网络病虫害预测预报模型,对提前采取防病防虫措施、减少农作物病虫害损失、提高农作物产量与质量具有重要意义。【方法】本研究以山西省运城市芮城县1980-2014年麦蚜发生程度和气象因子数据为基础,采用主成分分析法从40个基础气象因子中整合形成9个新的自变量输入模型,采用试凑法筛选隐含层节点数,用1980-2009年的数据进行网络训练,对2010-2014年麦蚜发生程度进行回测,建立了以Morlet小波函数为传递函数的小波神经网络模型,并与以Sigmoid函数为传递函数的BP神经网络模型进行了比较。【结果】小波和BP神经网络两种模型对训练样本的平均拟合精度均有10年以上超过80%,两者MAPE 值分别为 89.83% 和83.07%,MSE 值分别为0.0578和0.6192。【结论】两个模型都能较好地描述麦蚜发生程度;从预测精度和模型的稳定性来看,小波神经网络好于BP神经网络。     

Interactions of an anionic antimicrobial peptide with Staphylococcus aureus membranes

The antimicrobial activity of the anionic peptide, AP1 (GEQGALAQFGEWL), was investigated. AP1 was found to kill Staphylococcus aureus with an MLC of 3 mM and to induce maximal surface pressure changes of 3.8 mN m⁻¹ over 1200 s in monolayers formed from lipid extract of S. aureus membranes. FTIR spectroscopy showed the peptide to be α-helical (100%) in the presence of vesicles formed from this lipid extract and to induce increases in their fluidity (Δν circa 0.5 cm⁻¹). These combined data show that AP1 is able to function as an α-helical antimicrobial peptide against Gram-positive bacteria and suggest that the killing mechanism used by the peptide involves interactions with the membrane lipid headgroup region. Moreover, this killing mechanism differs strongly from that previously reported for AP1 against Gram-negative bacteria, indicating the importance of considering the effects of membrane lipid composition when investigating the structure/function relationships of antimicrobial peptides.     

Flexible Analytic Wavelet Transform Based Features for Physical Action Identification Using sEMG Signals

ObjectivesElectromyography (EMG) is recording of the electrical activity produced by skeletal muscles. The classification of the EMG signals for different physical actions can be useful in restoring some or all of the lost motor functionalities in these individuals. Accuracy in classifying the EMG signal indicates efficient control of prosthesis.Material and methodsThe flexible analytic wavelet transform (FAWT) is used for classification of surface electromyography (sEMG) signals for identification of physical actions. FAWT is an efficient method for decomposition of sEMG signal into eight sub-bands, features namely neg-entropy, mean absolute value (MAV), variance (VAR), modified mean absolute value type 1 (MAV1), waveform length (WL), simple square integral (SSI), Tsallis entropy, integrated EMG (IEMG) are extracted from the sub-bands. Extracted features are fed into an extreme learning machine (ELM) classifier with sigmoid activation function.ResultsComprehensive experiments are conducted on the input sEMG signals and the accuracy, sensitivity and specificity scores are used for performance measurement. Experiments showed that among all sub-bands, the seventh sub-band provided the best performance where the recorded accuracy, sensitivity and specificity values were 99.36%, 99.36% and 99.93%, respectively. The comparison results showed best efficiency of proposed method as compared to other methods on the same dataset.ConclusionThis paper investigates the usage of the FAWT and ELM on sEMG signal classification. The results show that the proposed method is quite efficient in classification of the sEMG signals. It is also observed that the seventh sub-band of the FAWT provides the best discrimination property. In the future works, recent wavelet transform methods will be used for improving the classification performance.     

ROI-Based Compression Strategy of 3D MRI Brain Datasets for Wireless Communications

ObjectivesBecause of the large amount of medical imaging data, the transmission process becomes complicated in telemedicine applications. Thus, in order to adapt the data bit streams to the constraints related to the limitation of the bandwidths a reduction of the size of the data by compression of the images is essential. Despite the improvements in the field of compression, the transmission itself can also introduce errors. For this reason, it is important to develop an adequate strategy which will help reduce this volume of data without having to introduce some distortion and resist the errors introduced by the channel noise during transmission. Thus, in this paper, we propose a ROI-based coding strategy and unequal bit stream protection to meet this dual constraint.Material and methodsThe proposed ROI-based compression strategy with unequal bit stream protection is composed of three parts: the first one allows the extraction of the ROI region, the second one consists of a ROI-based coding and the third one allows an unequal protection of the ROI bit stream.First, the Regions Of Interest (ROI) are extracted by hierarchical segmentation of these regions according to a segmentation method based on the technique of Marker-based-watershed combined with the technique of active contours by level set. The resulting regions are selectively encoded by a 3D coder based on a shape adaptive discrete wavelet transform 3D-BISK, where the compression ratio of each region depends on its relevance in diagnosis. These obtained regions of interest are protected with an error-correcting code of Reed-Solomon type with a code rate that varies according to the relevance of the region by an unequal protection strategy (UEP).ResultsThe performance of the proposed compression scheme is evaluated in several ways. First, tests are performed to study the impact of errors on the different bit streams. In the first place, these tests are carried out in order to study the effect of the variation of the compression rates on the different bit streams. Secondly, different Reed Solomon error-correcting codes of different code rates are tested at different compression rates on a BSC channel. Finally, the performances of this coding strategy are compared with those of SPIHT 3D in the case of transmission on a BSC channel.ConclusionThe obtained results show that the proposed method is quite efficient in transmission time reduction. Therefore, our proposed scheme will reduce the volume of data without having to introduce some distortion and resist the errors introduced by the channel noise in the case of telemedicine.     

Modified Fuzzy Q Learning Based Classifier for Pneumonia and Tuberculosis

This work proposes reinforcement learning for correctly identifying pneumonia and tuberculosis (TB) using a repository of X ray images. To our knowledge, this is a first attempt at employing reinforcement learning for pneumonia and TB classification. In particular, modified fuzzy Q learning (MFQL) algorithm in conjunction with wavelet based pre-processing has been used to build a classifier for identifying pneumonia and tuberculosis's severity. Proposed classifier is a self-learning one and uses pneumonia dataset (no pneumonia, mild pneumonia and severe pneumonia) and tuberculosis dataset (TB present, TB absent) samples to classify X ray images of subjects. Results indicate that MFQL based approach achieves high accuracy and fares much better over contemporary Support Vector Machine (SVM) and k-Nearest Neighbor (KNN) classifiers. Proposed classifier can be a useful tool for pneumonia and tuberculosis diagnosis in a practical setting.