An error-bounded median filter for correcting ECG baseline wander.

The baseline wander (BLW) in electrocardiogram (ECG) is a common disturbance that has a significant influence on the ECG wave pattern recognition. Many methods, such as IIR filter, mean filter, etc., can be used to correct BLW; However, most of them work on the original ECG signals. Compressed ECG data are economic for data storage and transmission, and if the baseline correction can be processed on them, it will be more efficient than we decompress them first and then do such correction. In this paper, we propose a new type of median filter CM_Filter, which works on the synopses of straight lines achieved from ECG by piecewise linear approximation (PLA) under maximum error bound. In CM_Filter, a heuristic strategy "Quick-Finding" is deduced by a property of straight lines in order to get the quality-assured median values from the synopses. The extended experimental tests demonstrate that the proposed filter is very efficient in execution time, and effective for correcting both slow and abrupt ECG baseline wander.

Microstate feature fusion for distinguishing AD from MCI.

Electroencephalogram (EEG) microstates provide powerful tools for identifying EEG features due to their rich temporal information. In this study, we tested whether microstates can measure the severity of Alzheimer's disease (AD) and mild cognitive impairment (MCI) in patients and effectively distinguish AD from MCI. We defined two features using transition probabilities (TPs), and one was used to evaluate between-group differences in microstate parameters to assess the within-group consistency of TPs and MMSE scores. Another feature was used to distinguish AD from MCI in machine learning models. Tests showed that there were between-group differences in the temporal characteristics of microstates, and some kinds of TPs were significantly correlated with MMSE scores within groups. Based on our newly defined time-factor transition probabilities (TTPs) feature and partial accumulation strategy, we obtained promising scores for accuracy, sensitivity, and specificity of 0.938, 0.923, and 0.947, respectively. These results provide evidence for microstates as a neurobiological marker of AD.

Medical image enhancement in F-shift transformation domain.

Image enhancement technology plays an important role in the diagnosis and treatment of medical diseases. In this paper, we propose a method to automatically enhance medical images. The proposed method could be used to support clinical medical diagnosis, adjuvant therapy and curative effect diagnosis. This scheme uses contrast limited adaptive histogram equalization (CLAHE) method in F-shift transformation domain. Firstly, we adjust the overall brightness of the underexposed or overexposed image. Secondly, we perform CLAHE to enhance the low-frequency components obtained by one-level two-dimensional F-shift transformation (TDFS) on the adjusted images. At this stage, most of the coefficients in the high-frequency component can be changed to zero through properly setting the error bound. We then use inverse transformation to reconstruct image which is further enhanced with CLAHE. Compared to previous work, this approach takes into account not only the image enhancement, but also the data compression. Experimental results and comparison with state-of-the-art methods show that our proposed method has a better enhancement performance. Moreover, it has a certain data compression ability.

A new marine bacterial laccase with chloride-enhancing, alkaline-dependent activity and dye decolorization ability.

A bacterial laccase gene designated as lac21 was screened from a marine microbial metagenomic library of the South China Sea based on sequence screening strategy. The protein encoded by lac21 shared less than 40% sequence identities with all of the laccases found. Lac21, which was recombinantly expressed in Escherichia coli, showed high activity toward syringaldazine at an optimum pH of 7.5 and temperature of 45°C. Lac21 was stable at pH values ranging from 5.5 to 9.0 and temperatures lower than 40°C. Interestingly, chloride enhanced the laccase activity, with concomitant increase in substrate affinity. Furthermore, Lac21 has high decolorization capability toward azo dyes in the absence of redox mediators, with 80% of Reactive Deep Blue M-2GE (50mg/L) being decolorized by 15U/L enzyme after 24h incubation at 20°C. These unusual properties demonstrate that the new bacterial laccase Lac21 has potentials in specific industrial or environmental applications.

A bacterial laccase from marine microbial metagenome exhibiting chloride tolerance and dye decolorization ability.

Laccases are blue multicopper oxidases with potential applications in environmental and industrial biotechnology. In this study, a new bacterial laccase gene of 1.32 kb was obtained from a marine microbial metagenome of the South China Sea by using a sequence screening strategy. The protein (named as Lac15) of 439 amino acids encoded by the gene contains three conserved Cu(2+)-binding domains, but shares less than 40% of sequence identities with all of the bacterial multicopper oxidases characterized. Lac15, recombinantly expressed in Escherichia coli, showed high activity towards syringaldazine at pH 6.5-9.0 with an optimum pH of 7.5 and with the highest activity occurring at 45 °C. Lac15 was stable at pH ranging from 5.5 to 9.0 and at temperatures from 15 to 45 °C. Distinguished from fungal laccases, the activity of Lac15 was enhanced twofold by chloride at concentrations lower than 700 mM, and kept the original level even at 1,000 mM chloride. Furthermore, Lac15 showed an ability to decolorize several industrial dyes of reactive azo class under alkalescent conditions. The properties of alkalescence-dependent activity, high chloride tolerance, and dye decolorization ability make the new laccase Lac15 an alternative for specific industrial applications.