Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration

Chudobová, Dagmar; Číhalová, Kristýna; Guráň, Roman; Dostálová, Simona; Šmerková, Kristýna; Veselý, Radek; Gumulec, Jaromír; Masařík, Michal; Heger, Zbyněk; Adam, Vojtěch; Kizek, René

doi:10.1016/j.bjid.2015.08.013

Cited by 11 publications

(8 citation statements)

References 42 publications

(44 reference statements)

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“…Neural network uses for classifying phenotype from the microbial composition are just beginning. A simple multilayer perceptron (MLP) was able to classify wound severity from microbial species present in the wound [335]. Recently, Ditzler et al [336] associated soil samples with pH level using MLPs, DBNs and RNNs.…”

Section: Metagenomicsmentioning

confidence: 99%

Opportunities and obstacles for deep learning in biology and medicine

Ching

Himmelstein

Beaulieu‐Jones

et al. 2018

J. R. Soc. Interface.

1,421

929

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Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems—patient classification, fundamental biological processes and treatment of patients—and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine.

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Section: Metagenomicsmentioning

confidence: 99%

Opportunities and obstacles for deep learning in biology and medicine

Ching

Himmelstein

Beaulieu‐Jones

et al. 2018

J. R. Soc. Interface.

1,421

929

View full text Add to dashboard Cite

show abstract

“…Surface morphology, topography and chemical composition of the synthesized TiO 2 (8)(9)(10)(11)(12)(13)(14) had been recorded using field emission scanning electron microscope (FESEM-JSM-7600F). The examined nanoparticles powder deposited on carbon tripe and demonstrated high 3-dimensional resolution images of materials.…”

Section: Nanoparticles Morphological Featuresmentioning

confidence: 99%

Titanium Oxide (TiO2) Nanoparticles for Treatment of Wound Infection

Alhadrami¹,

Shoudri²

2021

J Pure Appl Microbiol

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Wound infections is one of the major problems worldwide. Millions of people around the world require several medical treatments for wound infections. The extensive use of antibiotics to treat wound infection leads to emerging new microbial strains that are resistant to many antibiotics. There is a growing concern on the emergence and re-emergence of drug-resistant pathogens such as multi-resistant bacterial strains. Hence, the development of new antimicrobial compounds or the modification of those that already exist to improve antibacterial activity is a high research priority. Metallic nanoparticles (NPs) are considered as new alternative treatment for wound infection with superior antibacterial activity. In this study, new formulation of titanium oxide (TiO2) NPs with different sizes were synthesized and characterized. Genotoxicity, mutagenicity and antibacterial activities of TiO2 NPs against the causative agents of wound infection were investigated. Antibacterial activity of TiO2 NPs was conducted against three ATCC® bacterial strains: methicillin-resistant Staphylococcus aureus (MRSA), Escherichia coli and Pseudomonas aeruginosa. The results clearly illustrate a superior antibacterial activity of all newly formulated TiO2 NPs against the most causative agents of wound infection. Most of our TiO2 NPs showed non-genotoxic and non-mutagenic results at the maximum concentrations. Findings of this study will enhance the future of the therapeutic strategies against the resistant pathogenic strains that cause wound infections.

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“…We previously believed that elimination of microorganisms was key to effective treatment and that a broad-spectrum antibiotic was truly necessary. 61,62 However, we now postulate that extensive elimination of microorganisms may not be the best treatment option. 63,64 Grice et al 65 proposed that targeted therapies are the future direction in the treatment of human skin conditions.…”

Section: Are Microbes Really Bad?mentioning

confidence: 99%

Microbiome Imbalances: An Overlooked Potential Mechanism in Chronic Nonhealing Wounds

Pang

Zhu

Lei

et al. 2019

The International Journal of Lower Extremity Wounds

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Chronic nonhealing wounds are a severe burden to health care systems worldwide, causing millions of patients to have lengthy hospital stays, high health care costs, periods of unemployment, and reduced quality of life. Moreover, treating chronic nonhealing wounds effectively and reasonably in countries with limited medical resources can be extremely challenging. With many outstanding questions surrounding chronic nonhealing wounds, in this review, we offer changes to the microbiome as a potentially ignored mechanism important in the formation and treatment of chronic wounds. Our analysis helps bring a whole new understanding to wound formation and healing and provides a potential breakthrough in the treatment of chronic nonhealing wounds in the future.

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Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration

Abstract: In all of 50 patients tested bacterial infections were identified. Based on the proposed artificial neuronal network we were able to predict the severity of the infection and length of the treatment.

Cited by 11 publications

References 42 publications

Opportunities and obstacles for deep learning in biology and medicine

Opportunities and obstacles for deep learning in biology and medicine

Titanium Oxide (TiO2) Nanoparticles for Treatment of Wound Infection

Microbiome Imbalances: An Overlooked Potential Mechanism in Chronic Nonhealing Wounds

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