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Abstract: The skin is the largest organ in the human body and is colonized by a diverse microbiota that works in harmony to protect the skin. However, when skin damage occurs, the skin microbiota is also disrupted, and pathogens can invade the wound and cause infection. Probiotics or other beneficial microbes and their metabolites are one possible alternative treatment for combating skin pathogens via their antimicrobial effectiveness. The objective of our study was to evaluate the antimicrobial effect of seven multi-strain dietary supplements and eleven single-strain microbes that contain probiotics against 15 clinical wound pathogens using the agar spot assay, co-culturing assay, and agar well diffusion assay. We also conducted genera-specific and species-specific molecular methods to detect the DNA in the dietary supplements and single-strain beneficial microbes. We found that the multi-strain dietary supplements exhibited a statistically significant higher antagonistic effect against the challenge wound pathogens than the single-strain microbes and that lactobacilli-containing dietary supplements and single-strain microbes were significantly more efficient than the selected propionibacteria and bacilli. Differences in results between methods were also observed, possibly due to different mechanisms of action. Individual pathogens were susceptible to different dietary supplements or single-strain microbes. Perhaps an individual approach such as a ‘probiogram’ could be a possibility in the future as a method to find the most efficient targeted probiotic strains, cell-free supernatants, or neutralized cell-free supernatants that have the highest antagonistic effect against individual clinical wound pathogens.
Keywords: probiotics, beneficial microbes, wound pathogens, skin pathogens, agar spot, co-culturing, agar well diffusion, molecular methods, PCR
Published in DKUM: 23.10.2025; Views: 0; Downloads: 3
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Abstract: Aims: The aim of this study is to use generative artificial intelligence to perform bibliometric analysis on abstracts published at European Resuscitation Council (ERC) annual scientific congress and define trends in ERC guidelines topics over the last decade. Methods: In this bibliometric analysis, the WebHarvy software (SysNucleus, India) was used to download data from the Resuscitation journal’s website through the technique of web scraping. Next, the Chat Generative Pre-trained Transformer 4 (ChatGPT-4) application programming interface (Open AI, USA) was used to implement the multinomial classification of abstract titles following the ERC 2021 guidelines topics. Results: From 2012 to 2022 a total of 2491 abstracts have been published at ERC congresses. Published abstracts ranged from 88 (in 2020) to 368 (in 2015). On average, the most common ERC guidelines topics were Adult basic life support (50.1%), followed by Adult advanced life support (41.5%), while Newborn resuscitation and support of transition of infants at birth (2.1%) was the least common topic. The findings also highlight that the Basic Life Support and Adult Advanced Life Support ERC guidelines topics have the strongest co-occurrence to all ERC guidelines topics, where the Newborn resuscitation and support of transition of infants at birth (2.1%; 52/2491) ERC guidelines topic has the weakest co-occurrence. Conclusion: This study demonstrates the capabilities of generative artificial intelligence in the bibliometric analysis of abstract titles using the example of resuscitation medicine research over the last decade at ERC conferences using large language models.
Keywords: generative artificial intelligence, bibliometric analysis, congress, emergency medicine, European Resuscitation Council
Published in DKUM: 27.11.2024; Views: 0; Downloads: 2
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Published in DKUM: 19.12.2019; Views: 1748; Downloads: 455
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