Endoscopic image analysis using Deep Convolutional GAN and traditional data

One big challenge encountered in the medical field is the availability of only limited annotated datasets for research. On the other hand, medical image annotation requires a lot of input from medical experts. It is noticed that machine learning and deep learning are producing better results in the area of image classification. However, these techniques require large training datasets, which is the major concern for medical image processing. Another issue is the unbalanced nature of the different classes of data, leading to the under-representation of some classes. Data augmentation has emerged as a good technique to deal with these challenges. In this work, we have applied traditional data augmentation and Generative Adversarial Network (GAN) on endoscopic esophagus images to increase the number of images for the training datasets. Eventually we have applied two deep learning models namely ResNet50 and VGG16 to extract and represent the relevant cancer features. The results show that the accuracy of the model increases with data augmentation and GAN. In fact, GAN has achieved the highest accuracy, that is, 94% over non-augmented training set and traditional data augmentation for VGG16

Development of Bioinformatics Infrastructure for Genomics Research in H3Africa

Background: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet’s role has evolved in response to changing needs from the consortium and the African bioinformatics community. Objectives: H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Methods and Results: Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. Conclusions: For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa

Equity, diversity, and inclusion at the Global Alliance for Genomics and Health

A lack of diversity in genomics for health continues to hinder equitable leadership and access to precision medicine approaches for underrepresented populations. To avoid perpetuating biases within the genomics workforce and genomic data collection practices, equity, diversity, and inclusion (EDI) must be addressed. This paper documents the journey taken by the Global Alliance for Genomics and Health (a genomics-based standard-setting and policy-framing organization) to create a more equitable, diverse, and inclusive environment for its standards and members. Initial steps include the creation of two groups: the Equity, Diversity, and Inclusion Advisory Group and the Regulatory and Ethics Diversity Group. Following a framework that we call "Reflected in our Teams, Reflected in our Standards," both groups address EDI at different stages in their policy development process. [Abstract copyright: © 2023 The Author(s).

Comparative Transcriptome Analysis of Bacillus subtilis Responding to Dissolved Oxygen in Adenosine Fermentation

Dissolved oxygen (DO) is an important factor for adenosine fermentation. Our previous experiments have shown that low oxygen supply in the growth period was optimal for high adenosine yield. Herein, to better understand the link between oxygen supply and adenosine productivity in B. subtilis (ATCC21616), we sought to systematically explore the effect of DO on genetic regulation and metabolism through transcriptome analysis. The microarrays representing 4,106 genes were used to study temporal transcript profiles of B. subtilis fermentation in response to high oxygen supply (agitation 700 r/min) and low oxygen supply (agitation 450 r/min). The transcriptome data analysis revealed that low oxygen supply has three major effects on metabolism: enhance carbon metabolism (glucose metabolism, pyruvate metabolism and carbon overflow), inhibit degradation of nitrogen sources (glutamate family amino acids and xanthine) and purine synthesis. Inhibition of xanthine degradation was the reason that low oxygen supply enhanced adenosine production. These provide us with potential targets, which can be modified to achieve higher adenosine yield. Expression of genes involved in energy, cell type differentiation, protein synthesis was also influenced by oxygen supply. These results provided new insights into the relationship between oxygen supply and metabolism

Comparative Transcriptional Profiling of Bacillus cereus Sensu Lato Strains during Growth in CO2-Bicarbonate and Aerobic Atmospheres

Bacillus species are spore-forming bacteria that are ubiquitous in the environment and display a range of virulent and avirulent phenotypes. This range is particularly evident in the Bacillus cereus sensu lato group; where closely related strains cause anthrax, food-borne illnesses, and pneumonia, but can also be non-pathogenic. Although much of this phenotypic range can be attributed to the presence or absence of a few key virulence factors, there are other virulence-associated loci that are conserved throughout the B. cereus group, and we hypothesized that these genes may be regulated differently in pathogenic and non-pathogenic strains.Here we report transcriptional profiles of three closely related but phenotypically unique members of the Bacillus cereus group--a pneumonia-causing B. cereus strain (G9241), an attenuated strain of B. anthracis (Sterne 34F(2)), and an avirulent B. cereus strain (10987)--during exponential growth in two distinct atmospheric environments: 14% CO(2)/bicarbonate and ambient air. We show that the disease-causing Bacillus strains undergo more distinctive transcriptional changes between the two environments, and that the expression of plasmid-encoded virulence genes was increased exclusively in the CO(2) environment. We observed a core of conserved metabolic genes that were differentially expressed in all three strains in both conditions. Additionally, the expression profiles of putative virulence genes in G9241 suggest that this strain, unlike Bacillus anthracis, may regulate gene expression with both PlcR and AtxA transcriptional regulators, each acting in a different environment.We have shown that homologous and even identical genes within the genomes of three closely related members of the B. cereus sensu lato group are in some instances regulated very differently, and that these differences can have important implications for virulence. This study provides insights into the evolution of the B. cereus group, and highlights the importance of looking beyond differences in gene content in comparative genomics studies

BosR (BB0647) Controls the RpoN-RpoS Regulatory Pathway and Virulence Expression in Borrelia burgdorferi by a Novel DNA-Binding Mechanism

In Borrelia burgdorferi (Bb), the Lyme disease spirochete, the alternative σ factor σ54 (RpoN) directly activates transcription of another alternative σ factor, σS (RpoS) which, in turn, controls the expression of virulence-associated membrane lipoproteins. As is customary in σ54-dependent gene control, a putative NtrC-like enhancer-binding protein, Rrp2, is required to activate the RpoN-RpoS pathway. However, recently it was found that rpoS transcription in Bb also requires another regulator, BosR, which was previously designated as a Fur or PerR homolog. Given this unexpected requirement for a second activator to promote σ54-dependent gene transcription, and the fact that regulatory mechanisms among similar species of pathogenic bacteria can be strain-specific, we sought to confirm the regulatory role of BosR in a second virulent strain (strain 297) of Bb. Indeed, BosR displayed the same influence over lipoprotein expression and mammalian infectivity for strain Bb 297 that were previously noted for Bb strain B31. We subsequently found that recombinant BosR (rBosR) bound to the rpoS gene at three distinct sites, and that binding occurred despite the absence of consensus Fur or Per boxes. This led to the identification of a novel direct repeat sequence (TAAATTAAAT) critical for rBosR binding in vitro. Mutations in the repeat sequence markedly inhibited or abolished rBosR binding. Taken together, our studies provide new mechanistic insights into how BosR likely acts directly on rpoS as a positive transcriptional activator. Additional novelty is engendered by the facts that, although BosR is a Fur or PerR homolog and it contains zinc (like Fur and PerR), it has other unique features that clearly set it apart from these other regulators. Our findings also have broader implications regarding a previously unappreciated layer of control that can be involved in σ54–dependent gene regulation in bacteria

A reexamination of information theory-based methods for DNA-binding site identification

<p>Abstract</p> <p>Background</p> <p>Searching for transcription factor binding sites in genome sequences is still an open problem in bioinformatics. Despite substantial progress, search methods based on information theory remain a standard in the field, even though the full validity of their underlying assumptions has only been tested in artificial settings. Here we use newly available data on transcription factors from different bacterial genomes to make a more thorough assessment of information theory-based search methods.</p> <p>Results</p> <p>Our results reveal that conventional benchmarking against artificial sequence data leads frequently to overestimation of search efficiency. In addition, we find that sequence information by itself is often inadequate and therefore must be complemented by other cues, such as curvature, in real genomes. Furthermore, results on skewed genomes show that methods integrating skew information, such as <it>Relative Entropy</it>, are not effective because their assumptions may not hold in real genomes. The evidence suggests that binding sites tend to evolve towards genomic skew, rather than against it, and to maintain their information content through increased conservation. Based on these results, we identify several misconceptions on information theory as applied to binding sites, such as negative entropy, and we propose a revised paradigm to explain the observed results.</p> <p>Conclusion</p> <p>We conclude that, among information theory-based methods, the most unassuming search methods perform, on average, better than any other alternatives, since heuristic corrections to these methods are prone to fail when working on real data. A reexamination of information content in binding sites reveals that information content is a compound measure of search and binding affinity requirements, a fact that has important repercussions for our understanding of binding site evolution.</p

Texture Analysis of the Microscopic Structure of Wound Tissues

Deep cut or heavy blows can wound living tissues. The wounds heal but often leave a permanent scar. One aim of medical science is to find efficient treatments for wounds to reduce scarring to a minimum. However, it is not possible to judge which treatment gives a better performance unless there is an objective method for comparing tissue samples. The aim of this paper is to develop computer-based methods for making quantitative comparisons between microscopic images of wound and normal tissues. Methods have been developed, using mathematical morphology, to measure the distribution of lengths, widths and orientations of collagen fibres in the tissue images, even though they cannot be resolved as individual objects.Keywords: mathematical morphology, isotropic opening, directional opening,texture analysis