Bowness R - Search Results

1

Tuberculosis bacillary load, an early marker of disease severity: the utility of tuberculosis Molecular Bacterial Load Assay.

Sabiiti W, Azam K, Farmer ECW, Kuchaka D, Mtafya B, Bowness R, Oravcova K, Honeyborne I, Evangelopoulos D, McHugh TD, Khosa C, Rachow A, Heinrich N, Kampira E, Davies G, Bhatt N, Ntinginya EN, Viegas S, Jani I, Kamdolozi M, Mdolo A, Khonga M, Boeree MJ, Phillips PPJ, Sloan D, Hoelscher M, Kibiki G, Gillespie SH. Sabiiti W, et al. Among authors: bowness r. Thorax. 2020 Jul;75(7):606-608. doi: 10.1136/thoraxjnl-2019-214238. Epub 2020 Apr 30. Thorax. 2020. PMID: 32354738 Free PMC article.

2

The relationship between Mycobacterium tuberculosis MGIT time to positivity and cfu in sputum samples demonstrates changing bacterial phenotypes potentially reflecting the impact of chemotherapy on critical sub-populations.

Bowness R, Boeree MJ, Aarnoutse R, Dawson R, Diacon A, Mangu C, Heinrich N, Ntinginya NE, Kohlenberg A, Mtafya B, Phillips PP, Rachow A, Plemper van Balen G, Gillespie SH. Bowness R, et al. J Antimicrob Chemother. 2015 Feb;70(2):448-55. doi: 10.1093/jac/dku415. Epub 2014 Oct 25. J Antimicrob Chemother. 2015. PMID: 25344806

3

Modelling the effects of bacterial cell state and spatial location on tuberculosis treatment: Insights from a hybrid multiscale cellular automaton model.

Bowness R, Chaplain MAJ, Powathil GG, Gillespie SH. Bowness R, et al. J Theor Biol. 2018 Jun 7;446:87-100. doi: 10.1016/j.jtbi.2018.03.006. Epub 2018 Mar 7. J Theor Biol. 2018. PMID: 29524441 Free PMC article.

4

A spatially heterogeneous network-based metapopulation software model applied to the simulation of a pulmonary tuberculosis infection.

Pitcher MJ, Bowness R, Dobson S, Gillespie SH. Pitcher MJ, et al. Among authors: bowness r. Appl Netw Sci. 2018;3(1):33. doi: 10.1007/s41109-018-0091-2. Epub 2018 Aug 23. Appl Netw Sci. 2018. PMID: 30839831 Free PMC article.

5

Modelling the effects of environmental heterogeneity within the lung on the tuberculosis life-cycle.

Pitcher MJ, Bowness R, Dobson S, Eftimie R, Gillespie SH. Pitcher MJ, et al. Among authors: bowness r. J Theor Biol. 2020 Dec 7;506:110381. doi: 10.1016/j.jtbi.2020.110381. Epub 2020 Aug 6. J Theor Biol. 2020. PMID: 32771534 Free PMC article.

6

How mechanistic in silico modelling can improve our understanding of TB disease and treatment.

Pitcher MJ, Dobson SA, Kelsey TW, Chaplain J, Sloan DJ, Gillespie SH, Bowness R. Pitcher MJ, et al. Among authors: bowness r. Int J Tuberc Lung Dis. 2020 Nov 1;24(11):1145-1150. doi: 10.5588/ijtld.20.0107. Int J Tuberc Lung Dis. 2020. PMID: 33172521

7

A simple label-free method reveals bacterial growth dynamics and antibiotic action in real-time.

Hammond RJH, Falconer K, Powell T, Bowness R, Gillespie SH. Hammond RJH, et al. Among authors: bowness r. Sci Rep. 2022 Nov 12;12(1):19393. doi: 10.1038/s41598-022-22671-6. Sci Rep. 2022. PMID: 36371444 Free PMC article.

8

Systems Medicine and Infection.

Bowness R. Bowness R. Methods Mol Biol. 2016;1386:107-18. doi: 10.1007/978-1-4939-3283-2_7. Methods Mol Biol. 2016. PMID: 26677182 Review.

9

Within-Host Mathematical Models of Antibiotic Resistance.

Saula AY, Knight G, Bowness R. Saula AY, et al. Among authors: bowness r. Methods Mol Biol. 2024;2833:79-91. doi: 10.1007/978-1-0716-3981-8_9. Methods Mol Biol. 2024. PMID: 38949703

10

Use of Individual-Based Mathematical Modelling to Understand More About Antibiotic Resistance Within-Host.

Saula AY, Rowlatt C, Bowness R. Saula AY, et al. Among authors: bowness r. Methods Mol Biol. 2024;2833:93-108. doi: 10.1007/978-1-0716-3981-8_10. Methods Mol Biol. 2024. PMID: 38949704

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