Sequential graph convolutional network and DeepRNN based hybrid framework for epileptic seizure detection from EEG signal

Automated epileptic seizure detection from ectroencephalogram (EEG) signals has attracted significant attention in the recent health informatics field. The serious brain condition known as epilepsy, which is characterized by recurrent seizures, is typically described as a sudden change in behavior caused by a momentary shift in the excessive electrical discharges in a group of brain cells, and EEG signal is primarily used in most cases to identify seizure to revitalize the close loop brain. The development of various deep learning (DL) algorithms for epileptic seizure diagnosis has been driven by the EEG's non-invasiveness and capacity to provide repetitive patterns of seizure-related electrophysiological information. Existing DL models, especially in clinical contexts where irregular and unordered structures of physiological recordings make it difficult to think of them as a matrix; this has been a key disadvantage to producing a consistent and appropriate diagnosis outcome due to EEG's low amplitude and nonstationary nature. Graph neural networks have drawn significant improvement by exploiting implicit information that is present in a brain anatomical system, whereas inter-acting nodes are connected by edges whose weights can be determined by either temporal associations or anatomical connections. Considering all these aspects, a novel hybrid framework is proposed for epileptic seizure detection by combined with a sequential graph convolutional network (SGCN) and deep recurrent neural network (DeepRNN). Here, DepRNN is developed by fusing a gated recurrent unit (GRU) with a traditional RNN; its key benefit is that it solves the vanishing gradient problem and achieve this hybrid framework greater sophistication. The line length feature, auto-covariance, auto-correlation, and periodogram are applied as a feature from the raw EEG signal and then grouped the resulting matrix into time-frequency domain as inputs for the SGCN to use for seizure classification. This model extracts both spatial and temporal information, resulting in improved accuracy, precision, and recall for seizure detection. Extensive experiments conducted on the CHB-MIT and TUH datasets showed that the SGCN-DeepRNN model outperforms other deep learning models for seizure detection, achieving an accuracy of 99.007%, with high sensitivity and specificity.

Evolution of cisplatin resistance through coordinated metabolic reprogramming of the cellular reductive state

BACKGROUND

Cisplatin (CDDP) is a mainstay treatment for advanced head and neck squamous cell carcinomas (HNSCC) despite a high frequency of innate and acquired resistance. We hypothesised that tumours acquire CDDP resistance through an enhanced reductive state dependent on metabolic rewiring.

METHODS

To validate this model and understand how an adaptive metabolic programme might be imprinted, we performed an integrated analysis of CDDP-resistant HNSCC clones from multiple genomic backgrounds by whole-exome sequencing, RNA-seq, mass spectrometry, steady state and flux metabolomics.

RESULTS

Inactivating KEAP1 mutations or reductions in KEAP1 RNA correlated with Nrf2 activation in CDDP-resistant cells, which functionally contributed to resistance. Proteomics identified elevation of downstream Nrf2 targets and the enrichment of enzymes involved in generation of biomass and reducing equivalents, metabolism of glucose, glutathione, NAD(P), and oxoacids. This was accompanied by biochemical and metabolic evidence of an enhanced reductive state dependent on coordinated glucose and glutamine catabolism, associated with reduced energy production and proliferation, despite normal mitochondrial structure and function.

CONCLUSIONS

Our analysis identified coordinated metabolic changes associated with CDDP resistance that may provide new therapeutic avenues through targeting of these convergent pathways.

Identification of an integrated stress and growth response signaling switch that directs vertebrate intestinal regeneration

BACKGROUND

Snakes exhibit extreme intestinal regeneration following months-long fasts that involves unparalleled increases in metabolism, function, and tissue growth, but the specific molecular control of this process is unknown. Understanding the mechanisms that coordinate these regenerative phenotypes provides valuable opportunities to understand critical pathways that may control vertebrate regeneration and novel perspectives on vertebrate regenerative capacities.

RESULTS

Here, we integrate a comprehensive set of phenotypic, transcriptomic, proteomic, and phosphoproteomic data from boa constrictors to identify the mechanisms that orchestrate shifts in metabolism, nutrient uptake, and cellular stress to direct phases of the regenerative response. We identify specific temporal patterns of metabolic, stress response, and growth pathway activation that direct regeneration and provide evidence for multiple key central regulatory molecules kinases that integrate these signals, including major conserved pathways like mTOR signaling and the unfolded protein response.

CONCLUSION

Collectively, our results identify a novel switch-like role of stress responses in intestinal regeneration that forms a primary regulatory hub facilitating organ regeneration and could point to potential pathways to understand regenerative capacity in vertebrates.

Wheat proteomics: proteome modulation and abiotic stress acclimation

Cellular mechanisms of stress sensing and signaling represent the initial plant responses to adverse conditions. The development of high-throughput "Omics" techniques has initiated a new era of the study of plant molecular strategies for adapting to environmental changes. However, the elucidation of stress adaptation mechanisms in plants requires the accurate isolation and characterization of stress-responsive proteins. Because the functional part of the genome, namely the proteins and their post-translational modifications, are critical for plant stress responses, proteomic studies provide comprehensive information about the fine-tuning of cellular pathways that primarily involved in stress mitigation. This review summarizes the major proteomic findings related to alterations in the wheat proteomic profile in response to abiotic stresses. Moreover, the strengths and weaknesses of different sample preparation techniques, including subcellular protein extraction protocols, are discussed in detail. The continued development of proteomic approaches in combination with rapidly evolving bioinformatics tools and interactive databases will facilitate understanding of the plant mechanisms underlying stress tolerance.

Genetic characterization of highly pathogenic H5N1 avian influenza virus from live migratory birds in Bangladesh

Since the first outbreak of highly pathogenic avian influenza virus (HPAIV) subtype H5N1 in Bangladesh in 2007, the virus has been circulating among domestic poultry causing severe economic losses. To investigate the presence of HPAIV H5N1 in migratory birds and their potential role in virus spread, 205 pools of fecal samples from live migratory birds were analyzed. Here, the first virus isolation and genome characterization of two HPAIV H5N1 isolates from migratory birds (A/migratory bird/Bangladesh/P18/2010 and A/migratory bird/Bangladesh/P29/2010)are described. Full-length amplification, sequencing, and a comprehensive phylogenetic analysis were performed for HA, NA, M, NS, NP, PA, PB1, and PB2 gene segments. The selected migratory bird isolates belong to clade 2.3.2.1 along with recent Bangladeshi isolates from chickens, ducks, and crows which grouped in the same cluster with contemporary South and South-East Asian isolates. The studied isolates were genetically similar to other H5N1 isolates from different species within the respective clade although some unique amino acid substitutions were observed among them. Migratory birds remain a real threat for spreading pathogenic avian influenza viruses across the continent and introduction of new strains into Bangladesh.

Facilitating and securing offline e-medicine service through image steganography

E-medicine is a process to provide health care services to people using the Internet or any networking technology. In this Letter, a new idea is proposed to model the physical structure of the e-medicine system to better provide offline health care services. Smart cards are used to authenticate the user singly. A very unique technique is also suggested to verify the card owner's identity and to embed secret data to the card while providing patients' reports either at booths or at the e-medicine server system. The simulation results of card authentication and embedding procedure justify the proposed implementation.

First outbreak of dengue hemorrhagic fever, Bangladesh

During the first countrywide outbreak of dengue hemorrhagic fever in Bangladesh, we conducted surveillance for dengue at a hospital in Dhaka. Of 176 patients, primarily adults, found positive for dengue, 60.2% had dengue fever, 39.2% dengue hemorrhagic fever, and 0.6% dengue shock syndrome. The Dengue virus 3 serotype was detected in eight patients.

Quality assessment of sputum for Acid Fast Bacilli(AFB) test in microbiology laboratories before and after implementation of Standard Operating Procedure (SOP): a comparative study

Aims: To evaluate the present status of microbiology laboratory by comparing the test results of investigator with that of laboratory staff for sputum for Acid Fast Bacilli (AFB) withZiehl-NeelsenStaining (Z-N Staining) at primary and secondary level andto assess the present status of a microbiology laboratory for sputum for Acid Fast Bacilli (AFB) withZiehl-NeelsenStaining (Z-N Staining) at tertiary level. Material and Methods: Type of study : Cross sectional, descriptive type of study. Place of study: Department of Microbiology of Dhaka Medical College,Narsingdi Sadar Hospital,Narsingdi,PolashUpzilla Health Complex ,Polash, Narsingdi andDOTS centers. Duration of study: From July, 2007 to June,2008 Method of sampling: Non probability, purposive and convenient sampling Sample Size: Sputum for AFB: 300 sputum samples were collected for detection of AFB by direct Z-N staining, Z-N staining after bleach centrifugation and Auramine phenol staining before implementing SOP. After following SOP 150 sputum samples were collected and tested in direct Z-N method. Results: In the present study, before SOP out of 100 sputum smear at each level, discrepancy was found in 3% cases at primary level, 2% cases at secondary level and 1% case at tertiary level.After following SOP out of 50 sputum smear at each level, discrepancy was reduced to 2% cases at primary level and no discrepancy was found at secondary and tertiary level. Conclusion: Each laboratory must have SOP for laboratory testing to set the minimum acceptable standard for every test in order to improve and maintain the quality of laboratory services. DOI: http://dx.doi.org/10.3329/bjms.v11i1.9824 BJMS 2012; 11(1): 51-56