Results in Journal Annals of Biomedical Science and Engineering: 15
(searched for: journal_id:(2016742))
Published: 20 January 2022
Annals of Biomedical Science and Engineering, Volume 6, pp 001-007; https://doi.org/10.29328/journal.abse.1001015
Throughout global efforts to defend against the spread of COVID-19 from late 2019 up until now, one of the most crucial factors that has helped combat the pandemic is the development of various screening methods to detect the presence of COVID-19 as conveniently and accurately as possible. One of such methods is the utilization of chest X-Rays (CXRs) to detect anomalies that are concurrent with a patient infected with COVID-19. While yielding results much faster than the traditional RT-PCR test, CXRs tend to be less accurate. Realizing this issue, in our research, we investigated the applications of computer vision in order to better detect COVID-19 from CXRs. Coupled with an extensive image database of CXRs of healthy patients, patients with non-COVID-19 induced pneumonia, and patients positive with COVID-19, convolutional neural networks (CNNs) prove to possess the ability to easily and accurately identify whether or not a patient is infected with COVID-19 in a matter of seconds. Borrowing and adjusting the architectures of three well-tested CNNs: VGG-16, ResNet50, and MobileNetV2, we performed transfer learning and trained three of our own models, then compared and contrasted their differing precisions, accuracies, and efficiencies in correctly labeling patients with and without COVID-19. In the end, all of our models were able to accurately categorize at least 94% of the CXRs, with some performing better than the others; these differences in performance were largely due to the contrasting architectures each of our models borrowed from the three respective CNNs.
Published: 24 June 2021
Annals of Biomedical Science and Engineering, Volume 5, pp 025-031; https://doi.org/10.29328/journal.abse.1001014
Naturally, microorganisms decompose the organic material existing in nature, both in the presence or absence of oxygen. The majority of materials such as poisonous chemical compounds, heavy metals, would prevent the treatment process from taking place, lead to the entry of these contaminants into the environment results in the emergence of numerous diseases. In the present study, using the TOXChem4.1 simulation model, attempts were made to simulate a wastewater treatment plant and then assess the dispersions of contaminants including 1,2-Dimethylnaphthalene, 1,3-Dinitropyrene, 1,6-Dimethylnaphthalene, 1,6-Dinitropyrene, and 17a-ethinylestradiol (EE2) in concentrations of a common scenario. The results of computer simulations showed that the EE2 contaminant is of the highest percentage of decomposition among others, due to its wider chemical structure. Consequently, it is clear that such contaminant is of the highest mass in the sludge exiting the treatment plant. In addition, the results of the simulations demonstrated that the highest volumes of gaseous pollutants take place in the modulation and initial sedimentation units.
Published: 9 June 2021
Annals of Biomedical Science and Engineering, Volume 5, pp 015-024; https://doi.org/10.29328/journal.abse.1001013
Due to the urgent need for water in all parts of industrial or developing societies, water supply, and transmission facilities are suitable targets for biological risks. Given that even a short interruption in water supply and water supply operations has a great impact on daily activities in the community, the deliberate contamination of urban water resources has irreparable consequences in the field of public health, and the economy of society will follow. Unfortunately, most officials in the public health control departments in our country have received limited training in detecting accidental or intentional contamination of water resources and dealing with the spread of waterborne diseases both naturally and intentionally. For this reason, there is low preparedness in the responsible agencies to deal with waterborne diseases during biological risks. In the first step of this research, a review study has been conducted on water biological risks and operational strategies to deal with them. In the following, it has studied how Escherichia coli (E. coli) bacteria spread in aqueous media. In this regard, the kinetic model of the studied microorganism was analyzed based on the implementation of (Fick Law) in polar coordinates and the combination of (Dirac Distribution) with (Legendre polynomial) distribution. Finally, after studying the factors affecting the microbial pollutant emission coefficient, the effects of all three factors of linear velocity, linear motion time period, and angle of motion on the pollutant emission flux and biofilm diffusion time in the water supply network environment were investigated. Studies have shown that the linear velocity parameter of Escherichia coli with a nonlinear relationship has the greatest effects on the release of microbial contaminants.
Published: 19 May 2021
Annals of Biomedical Science and Engineering, Volume 5, pp 013-014; https://doi.org/10.29328/journal.abse.1001012
Artificial intelligence (AI) is the emulation of human intelligence in computers that have been trained to think and behave like humans. The word may also refer to any computer that exhibits human-like characteristics like learning and problem-solving. Artificial intelligence is intelligence demonstrated by machines, as opposed to natural intelligence, which involves consciousness and emotionality and is demonstrated by humans and animals .
Published: 17 March 2021
Annals of Biomedical Science and Engineering, Volume 5, pp 006-012; https://doi.org/10.29328/journal.abse.1001011
Advances in metagenomics have facilitated population studies of associations between microbial compositions and host properties, but strategies to minimize biases in these population analyses are needed. However, the effects of storage conditions, including freezing and preservation buffer, on microbial populations in fecal samples have not been studied sufficiently. In this study, we investigated metagenomic differences between fecal samples stored in different conditions. We collected 46 fecal samples from patients with lung cancer. DNA quality and microbial composition within different storage Methods were compared throughout 16S rRNA sequencing and post analysis. DNA quality and sequencing results for two storage conditions (freezing and preservation in buffer) did not differ significantly, whereas microbial information was better preserved in buffer than by freezing. In a metagenomic analysis, we observed that the microbial compositional distance was small within the same storage condition. Taxonomic annotation revealed that many microbes differed in abundance between frozen and buffer-preserved feces. In particular, the abundances of Firmicutes and Bacteroidetes varied depending on storage conditions. Microbes belonging to these phyla differed, resulting in biases in population metagenomic analysis. We suggest that a unified storage Methods is requisite for accurate population metagenomic studies.
Published: 13 January 2021
Annals of Biomedical Science and Engineering, Volume 5, pp 001-005; https://doi.org/10.29328/journal.abse.1001010
The Human three-dimensional (3D) musculoskeletal model is based on motion analysis methods and can be obtained by particular motion capture systems that export 3D data with coordinate 3D (C3D) format. Unique cameras and specific software are essential for analyzing the data. This equipment is quite expensive, and using them is time-consuming. This research intends to use ordinary video cameras and open source systems to get 3D data and create a C3D format due to these problems. By capturing movements with two video cameras, marker coordination is obtainable using Skill-Spector. To create C3D data from 3D coordinates of the body points, MATLAB functions were used. The subject was captured simultaneously with both the Cortex system and two video cameras during each validation test. The mean correlation coefficient of datasets is 0.7. This method can be used as an alternative method for motion analysis due to a more detailed comparison. The C3D data collection, which we presented in this research, is more accessible and cost-efficient than other systems. In this method, only two cameras have been used.
Published: 9 April 2020
Annals of Biomedical Science and Engineering, Volume 4, pp 020-027; https://doi.org/10.29328/journal.abse.1001009
The global virome: The viruses have a global distribution, phylogenetic diversity and host specificity. They are obligate intracellular parasites with single- or double-stranded DNA or RNA genomes, and afflict bacteria, plants, animals and human population. The viral infection begins when surface proteins bind to receptor proteins on the host cell surface, followed by internalisation, replication and lysis. Further, trans-species interactions of viruses with bacteria, small eukaryotes and host are associated with various zoonotic viral diseases and disease progression. Virome interface and transmission: The cross-species transmission from their natural reservoir, usually mammalian or avian, hosts to infect human-being is a rare probability, but occurs leading to the zoonotic human viral infection. The factors like increased human settlements and encroachments, expanded travel and trade networks, altered wildlife and livestock practices, modernised and mass-farming practices, compromised ecosystems and habitat destruction, and global climate change have impact on the interactions between virome and its hosts and other species and act as drivers of trans-species viral spill-over and human transmission. Zoonotic viral diseases and epidemics: The zoonotic viruses have caused various deadly pandemics in human history. They can be further characterized as either newly emerging or re-emerging infectious diseases, caused by pathogens that historically have infected the same host species, but continue to appear in new locations or in drug-resistant forms, or reappear after apparent control or elimination. The prevalence of zoonoses underlines importance of the animal–human–ecosystem interface in disease transmission. The present COVID-19 infection has certain distinct features which suppress the host immune response and promote the disease potential. Treatment for epidemics like covid-19: It appears that certain nutraceuticals may provide relief in clinical symptoms to patients infected with encapsulated RNA viruses such as influenza and coronavirus. These nutraceuticals appear to reduce the inflammation in the lungs and help to boost type 1 interferon response to these viral infections. The human intestinal microbiota acting in tandem with the host’s defence and immune system, is vital for homeostasis and preservation of health. The integrity and balanced activity of the gut microbes is responsible for the protection from disease states including viral infections. Certain probiotics may help in improving the sensitivity and effectivity of immune system against viral infections. Currently, antiviral therapy is available only for a limited number of zoonotic viral infections. Because viruses are intracellular parasites, antiviral drugs are not able to deactivate or destroy the virus but can reduce the viral load by inhibiting replication and facilitating the host’s innate immune mechanisms to neutralize the virus. Conclusion: Lessons from recent viral epidemics - Considering that certain nutraceuticals have demonstrated antiviral effects in both clinical and animal studies, further studies are required to establish their therapeutic efficacy. The components of nutraceuticals such as luteolin, apigenin, quercetin and chlorogenic acid may be useful for developing a combo-therapy. The use of probiotics to enhance immunity and immune response against viral infections is a novel possibility. The available antiviral therapy is inefficient in deactivating or destroying the infecting viruses, may help in reducing the viral load by inhibiting replication. The novel efficient antiviral agents are being explored.
Published: 11 March 2020
Annals of Biomedical Science and Engineering, Volume 4, pp 009-019; https://doi.org/10.29328/journal.abse.1001008
Published: 14 February 2020
Annals of Biomedical Science and Engineering, Volume 4, pp 001-008; https://doi.org/10.29328/journal.abse.1001007
Published: 12 October 2019
Annals of Biomedical Science and Engineering, Volume 3, pp 013-019; https://doi.org/10.29328/journal.abse.1001006
Published: 28 June 2019
Annals of Biomedical Science and Engineering, Volume 3, pp 010-012; https://doi.org/10.29328/journal.abse.1001005
Published: 1 February 2019
Annals of Biomedical Science and Engineering, Volume 3, pp 001-009; https://doi.org/10.29328/journal.abse.1001004
Published: 1 January 2017
Annals of Biomedical Science and Engineering, Volume 2, pp 001-006; https://doi.org/10.29328/journal.abse.1001003
Published: 12 October 2017
Annals of Biomedical Science and Engineering, Volume 1, pp 012-022; https://doi.org/10.29328/journal.hbse.1001002
Published: 18 May 2017
Annals of Biomedical Science and Engineering, Volume 1, pp 001-011; https://doi.org/10.29328/journal.hbse.1001001