Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are used to help diagnose heart disease by recording the heart’s activity. However, automated medical-aided diagnosis with computers usually requires a large volume of labeled clinical data without patients' privacy to train the model, which is an empirical problem that still needs to be solved. To address this problem, we propose a generative adversarial network (GAN), which is composed of a bidirectional long short-term memory(LSTM) and convolutional neural network(CNN), referred as BiLSTM-CNN,to generate synthetic ECG data that agree with existing clinical data so that the features of patients with heart disease can be retained. The model includes a generator and a discriminator, where the generator employs the two layers of the BiLSTM networks and the discriminator is based on convolutional neural networks. The 48 ECG records from individuals of the MIT-BIH database were used to train the model. We compared the performance of our model with two other generative models, the recurrent neural network autoencoder(RNN-AE) and the recurrent neural network variational autoencoder (RNN-VAE). The results showed that the loss function of our model converged to zero the fastest. We also evaluated the loss of the discriminator of GANs with different combinations of generator and discriminator. The results indicated that BiLSTM-CNN GAN could generate ECG data with high morphological similarity to real ECG recordings.

The carbonic anhydrase (CA) gene family has been reported to consist of at least 11 enzymatically active members and a few inactive homologous proteins. Recent analyses of human and mouse databases provided evidence that human and mouse genomes contain genes for still another novel CA isozyme hereby named CA XIII. In the present study, we modeled the structure of human CA XIII. This model revealed a globular molecule with high structural similarity to cytosolic isozymes, CA I, II, and III. Recombinant mouse CA XIII showed catalytic activity similar to those of mitochondrial CA V and cytosolic CA I, with k_cat/K_m of 4.3 × 10⁷m^–1 s^–1, and k_cat of 8.3 × 10⁴ s^–1. It is very susceptible to inhibition by sulfonamide and anionic inhibitors, with inhibition constants of 17 nm for acetazolamide, a clinically used sulfonamide, and of 0.25 μm, for cyanate, respectively. Using panels of cDNAs we evaluated human and mouse CA13 gene expression in a number of different tissues. In human tissues, positive signals were identified in the thymus, small intestine, spleen, prostate, ovary, colon, and testis. In mouse, positive tissues included the spleen, lung, kidney, heart, brain, skeletal muscle, and testis. We also investigated the cellular and subcellular localization of CA XIII in human and mouse tissues using an antibody raised against a polypeptide of 14 amino acids common for both human and mouse orthologues. Immunohistochemical staining showed a unique and widespread distribution pattern for CA XIII compared with the other cytosolic CA isozymes. In conclusion, the predicted amino acid sequence, structural model, distribution, and activity data suggest that CA XIII represents a novel enzyme, which may play important physiological roles in several organs.

The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.

The main function of CAs (carbonic anhydrases) is to participate in the regulation of acid–base balance. Although 12 active isoenzymes of this family had already been described, analyses of genomic databases suggested that there still exists another isoenzyme, CA XV. Sequence analyses were performed to identify those species that are likely to have an active form of this enzyme. Eight species had genomic sequences encoding CA XV, in which all the amino acid residues critical for CA activity are present. However, based on the sequence data, it was apparent that CA XV has become a non-processed pseudogene in humans and chimpanzees. RT-PCR (reverse transcriptase PCR) confirmed that humans do not express CA XV. In contrast, RT-PCR and in situ hybridization performed in mice showed positive expression in the kidney, brain and testis. A prediction of the mouse CA XV structure was performed. Phylogenetic analysis showed that mouse CA XV is related to CA IV. Therefore both of these enzymes were expressed in COS-7 cells and studied in parallel experiments. The results showed that CA XV shares several properties with CA IV, i.e. it is a glycosylated glycosylphosphatidylinositol-anchored membrane protein, and it binds CA inhibitor. The catalytic activity of CA XV is low, and the correct formation of disulphide bridges is important for the activity. Both specific and non-specific chaperones increase the production of active enzyme. The results suggest that CA XV is the first member of the α-CA gene family that is expressed in several species, but not in humans and chimpanzees.

With the development of next-generation sequencing (NGS) techniques, many software tools have emerged for the discovery of novel microRNAs (miRNAs) and for analyzing the miRNAs expression profiles. An overall evaluation of these diverse software tools is lacking. In this study, we evaluated eight software tools based on their common feature and key algorithms. Three deep-sequencing data sets were collected from different species and used to assess the computational time, sensitivity and accuracy of detecting known miRNAs as well as their capacity for predicting novel miRNAs. Our results provide useful information for researchers to facilitate their selection of the optimal software tools for miRNA analysis depending on their specific requirements, i.e. novel miRNAs discovery or miRNA expression profile analysis of sequencing data sets.