Predicting the subcellular location of apoptosis proteins based on recurrence quantification analysis and the Hilbert Huang transform

Apoptosis proteins play an important role in the development and homeostasis of an organism. The elucidation of the subcellular locations and functions of these proteins is helpful for understanding the mechanism of programmed cell death. In this paper, the recurrent quantification analysis, Hilbert-Huang transform methods, the maximum relevance and minimum redundancy method and support vector machine are used to predict the subcellular location of apoptosis proteins. The validation of the jackknife test suggests that the proposed method can improve the prediction accuracy of the subcellular location of apoptosis proteins and its application may be promising in other fields.

Recurrence quantification analysis on pulse morphological changes in patients with coronary heart disease

OBJECTIVE： To show that the pulse diagnosis used in Traditional Chinese Medicine, combined with nonlinear dynamic analysis, can help identify car- diovascular diseases. METHODS： Recurrence quantification analysis （RQA） was used to study pulse morphological changes in 37 inpatients with coronary heart dis- ease （CHD） and 37 normal subjects （controls）. An in- dependent sample t-test detected significant differ- ences in RQA measures of their pulses. A support vector machine （SVM） classified the groups accord- ing to their RQA measures. Classic time-domain pa- rameters were used for comparison. RESULTS： RQA measures can be divided into two groups. One group of measures [ecurrence rate（RR）, determinism （DEL）, average diagonal line length （L）, maximum length of diagonal structures （Lmax）, Shannon entropy of the frequency distribu- tion of diagonal line lengths （ENTR）, laminarity （LAM）, average length of vertical structures （TT）, maximum length of vertical structures （Vmax）] showed significantly higher values for patients with CHD than for normal subjects （P〈0.0S）. The other measures （RR_std, L_std, Lmaxstd, TT_std, Vmax_std） showed significantly lower values for the CHD group than for normal subjects （P〈0.05）. SVM classification accuracy was higher with RQA measures： With RQA （16 parameters） accuracy was at 88.21%, and with RQA（12 parameters） accuracy was at 84.11%. In contrast, with classic time-do- main （15 parameters） accuracy was 75.73%, and with time-domain （7 parameters） accuracy was 74.7O%. CONCLUSION： Nonlinear dynamic methods such as RQA can be used to study functional and struc- tural changes in the pulse noninvasively. Pulse sig- nals of individuals with CHD have greater regulari- ty, determinism, and stability than normal subjects, and their pulse morphology displays less variabili- ty. RQA can distinguish the CHD pulse from the healthy pulse with an accuracy of 88.21%, thereby providing an early diagnosis of cardiovascular dis- eases such as CHD.

Characterization of various structures in gas-solid fluidized beds by recurrence quantification analysis

Gas-solid fluidized beds are widely considered as nonlinear and chaotic dynamic systems. Pressure fluc- tuations were measured in a fluidized bed of 0.15 m in diameter and were analyzed using multiple approaches： discrete Fourier transform （DFT）, discrete wavelet transform （DWT）, and nonlinear recur- rence quantification analysis （RQA）. Three different methods proposed that the complex dynamics of a fluidized bed system can be presented as macro, meso and micro structures. It was found from DFT and DWT that a minimum in wide band energy with an increase in the velocity corresponds to the transition between macro structures and finer structures of the fluidization system. Corresponding transition veloc- ity occurs at gas velocities of 0.3, 0.5 and 0.6 m]s for sands with mean diameters of 150, 280 and 490/~m, respectively. DFT, DWT, and RQA could determine frequency range of0-3.125 Hz for macro, 3. ! 25-50 Hz for meso, and 50-200 Hz for micro structures. The RQA showed that the micro structures have the least periodicity and consequently their determinism and laminarity are the lowest. The results show that a combination of DFT, DWT, and RQA can be used as an effective approach to characterize multi-scale flow behavior in gas-solid fluidized beds.

Hidden Sequence Repeats: Additional Evidence for the Origin of TIM-Barrel Family

Most proteins adopt an approximate structural symmetry. However, they have no symmetry detectable in their sequences and it is unclear for most of these proteins whether their structural symmetry originates from duplication. As one of the six popular folds (super-folds) possessing an approximate structural symmetry, the triosephosphate isomerase barrel (TIM-barrel) domain has been widely studied. Using modified recurrent quantification analysis of primary sequences, we identified the same 2-, 3-, and 4-fold symmetry pattern as their tertiary structures. This result indicates that the symmetry in tertiary structure is coded by symmetry in the primary sequence and that the TIM-barrel adopts a 2-, 3-, or 4-fold repeat pattern during evolution. This discovery will be useful for understanding the evolutionary mechanisms of this protein family and the symmetry pattern that may be a clue into the ancient origin of duplication of half-barrels or the β a unit.

Automatic Assessment of Expanded Disability Status Scale (EDSS) in Multiple Sclerosis Using a Decision Tree

The expanded disability status scale (EDSS) is frequently used to classify the patients with multiple sclerosis (MS). We presented in this paper a novel method to automatically assess the EDSS score from posturologic data (center of pres-sure signals) using a decision tree. Two groups of participants (one for learning and the other for test) with EDSS rang-ing from 0 to 4.5 performed our balance experiment with eyes closed. Two linear measures (the length and the surface) and twelve non-linear measures (the recurrence rate, the Shannon entropy, the averaged diagonal line length and the trapping time for the position, the instantaneous velocity and the instantaneous acceleration of the center of pressure respectively) were calculated for all the participants. Several decision trees were constructed with learning data and tested with test data. By comparing clinical and estimated EDSS scores in the test group, we selected one decision tree with five measures which revealed a 75% of agreement. The results have signified that our tree model is able to auto-matically assess the EDSS scores and that it is possible to distinguish the EDSS scores by using linear and non-linear postural sway measures.

Multiscale characterization of nanoparticles in a magnetically assisted fluidized bed

Pressure fluctuations of a fluidized bed of nanoparticles were measured during the fluidization of nanoparticles with and without a magnetic field at a frequency of 50 Hz.Recurrence quantification analysis(RQA)and wavelet transform were used to determine the frequency range of various flow structures in the bed at three scales.The frequency ranges of the macro-,meso-,and micro-structures were determined to be 0-49Hz,49-781 Hz,and 781+Hz,respectively.Comparison of the determinisms of the sub-signals with and without the external field revealed that in the presence the field,breakage of larger agglomerates occurs faster than re-agglomeration of small agglomerates into larger ones.The power spectral density function of the pressure fluctuations indicated that with an external magnetic field,the power and the frequency range of the pressure signal of macro-structures do not change noticeably.However,the power of the meso-structure signal increases and its frequency range is widened toward higher frequencies,confirming that the number of small bubbles and agglomerates increase in the bed.ln addition,the energy of signal analysis indicated that the external field significantly increases the share of meso-structures in the bed,confirming the RQA results.