SARS-CoV-2 and its Multifaceted Impact on Bone Health: Mechanisms and Clinical Evidence

Harris, Alexander; Creecy, Amy; Awosanya, Olatundun D.; McCune, Thomas; Ozanne, Marie V.; Toepp, Angela J.; Kacena, Melissa A.; Qiao, Xian

doi:10.1007/s11914-023-00843-1

Cited by 7 publications

(3 citation statements)

References 123 publications

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“…For the AI-assisted review articles [15,18,20], ChatGPT-4 was used as outlined in the AI-only section above with the following differences. The AI-assisted article utilized the human-generated outline and all the references utilized to generate this article were provided using the AskYourPDF plugin as described above.…”

Section: Ai-assisted (Aia) Review Articlesmentioning

confidence: 99%

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The Use of Artificial Intelligence in Writing Scientific Review Articles

Kacena,

Plotkin,

Fehrenbacher

2024

Curr Osteoporos Rep

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Purpose of Review With the recent explosion in the use of artificial intelligence (AI) and specifically ChatGPT, we sought to determine whether ChatGPT could be used to assist in writing credible, peer-reviewed, scientific review articles. We also sought to assess, in a scientific study, the advantages and limitations of using ChatGPT for this purpose. To accomplish this, 3 topics of importance in musculoskeletal research were selected: (1) the intersection of Alzheimer’s disease and bone; (2) the neural regulation of fracture healing; and (3) COVID-19 and musculoskeletal health. For each of these topics, 3 approaches to write manuscript drafts were undertaken: (1) human only; (2) ChatGPT only (AI-only); and (3) combination approach of #1 and #2 (AI-assisted). Articles were extensively fact checked and edited to ensure scientific quality, resulting in final manuscripts that were significantly different from the original drafts. Numerous parameters were measured throughout the process to quantitate advantages and disadvantages of approaches. Recent Findings Overall, use of AI decreased the time spent to write the review article, but required more extensive fact checking. With the AI-only approach, up to 70% of the references cited were found to be inaccurate. Interestingly, the AI-assisted approach resulted in the highest similarity indices suggesting a higher likelihood of plagiarism. Finally, although the technology is rapidly changing, at the time of study, ChatGPT 4.0 had a cutoff date of September 2021 rendering identification of recent articles impossible. Therefore, all literature published past the cutoff date was manually provided to ChatGPT, rendering approaches #2 and #3 identical for contemporary citations. As a result, for the COVID-19 and musculoskeletal health topic, approach #2 was abandoned midstream due to the extensive overlap with approach #3. Summary The main objective of this scientific study was to see whether AI could be used in a scientifically appropriate manner to improve the scientific writing process. Indeed, AI reduced the time for writing but had significant inaccuracies. The latter necessitates that AI cannot currently be used alone but could be used with careful oversight by humans to assist in writing scientific review articles.

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Section: Ai-assisted (Aia) Review Articlesmentioning

confidence: 99%

“…(2) neural regulation of fracture healing [16][17][18]; and (3) COVID-19 and musculoskeletal health [19,20]. With this background, we hypothesized that the human paper would take the most time and require the fewest changes between the first and final drafts.…”

Section: Introductionmentioning

confidence: 99%

The Use of Artificial Intelligence in Writing Scientific Review Articles

Kacena,

Plotkin,

Fehrenbacher

2024

Curr Osteoporos Rep

Self Cite

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“…To test this possibility in scientific writing, we created an experiment to see if the current state of LLMs, and more specifically ChatGPT 4.0, would be able to increase the efficiency of writing scientific review articles. To accomplish this, we first identified 3 topics of importance to the musculoskeletal research field: (1) COVID-19 and musculoskeletal health [ 4 , 5 ]; (2) the intersection of Alzheimer’s disease and bone [ 6 – 8 ]; and (3) the neural regulation of fracture healing [ 9 – 11 ]. We then implemented 3 approaches to write the first draft of review articles on each topic: (1) human only; (2) ChatGPT 4.0 only (AI-only or AIO); and (3) a combination of approaches 1 and 2 (AI-assisted or AIA).…”

Section: Introductionmentioning

confidence: 99%

The Utility of AI in Writing a Scientific Review Article on the Impacts of COVID-19 on Musculoskeletal Health

Awosanya,

Harris,

Creecy

et al. 2024

Curr Osteoporos Rep

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Purpose of Review There were two primary purposes to our reviews. First, to provide an update to the scientific community about the impacts of COVID-19 on musculoskeletal health. Second, was to determine the value of using a large language model, ChatGPT 4.0, in the process of writing a scientific review article. To accomplish these objectives, we originally set out to write three review articles on the topic using different methods to produce the initial drafts of the review articles. The first review article was written in the traditional manner by humans, the second was to be written exclusively using ChatGPT (AI-only or AIO), and the third approach was to input the outline and references selected by humans from approach 1 into ChatGPT, using the AI to assist in completing the writing (AI-assisted or AIA). All review articles were extensively fact-checked and edited by all co-authors leading to the final drafts of the manuscripts, which were significantly different from the initial drafts. Recent Findings Unfortunately, during this process, it became clear that approach 2 was not feasible for a very recent topic like COVID-19 as at the time, ChatGPT 4.0 had a cutoff date of September 2021 and all articles published after this date had to be provided to ChatGPT, making approaches 2 and 3 virtually identical. Therefore, only two approaches and two review articles were written (human and AI-assisted). Here we found that the human-only approach took less time to complete than the AI-assisted approach. This was largely due to the number of hours required to fact-check and edit the AI-assisted manuscript. Of note, the AI-assisted approach resulted in inaccurate attributions of references (about 20%) and had a higher similarity index suggesting an increased risk of plagiarism. Summary The main aim of this project was to determine whether the use of AI could improve the process of writing a scientific review article. Based on our experience, with the current state of technology, it would not be advised to solely use AI to write a scientific review article, especially on a recent topic.

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The abortive SARS‐CoV‐2 infection of osteoclast precursors promotes their differentiation into osteoclasts

Sviercz,

Jarmoluk,

Godoy Coto

et al. 2024

Journal of Medical Virology

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The Coronavirus Disease 2019 (COVID‐19) pandemic has resulted in the loss of millions of lives, although a majority of those infected have managed to survive. Consequently, a set of outcomes, identified as long COVID, is now emerging. While the primary target of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is the respiratory system, the impact of COVID‐19 extends to various body parts, including the bone. This study aims to investigate the effects of acute SARS‐CoV‐2 infection on osteoclastogenesis, utilizing both ancestral and Omicron viral strains. Monocyte‐derived macrophages, which serve as precursors to osteoclasts, were exposed to both viral variants. However, the infection proved abortive, even though ACE2 receptor expression increased postinfection, with no significant impact on cellular viability and redox balance. Both SARS‐CoV‐2 strains heightened osteoclast formation in a dose‐dependent manner, as well as CD51/61 expression and bone resorptive ability. Notably, SARS‐CoV‐2 induced early pro‐inflammatory M1 macrophage polarization, shifting toward an M2‐like profile. Osteoclastogenesis‐related genes (RANK, NFATc1, DC‐STAMP, MMP9) were upregulated, and surprisingly, SARS‐CoV‐2 variants promoted RANKL‐independent osteoclast formation. This thorough investigation illuminates the intricate interplay between SARS‐CoV‐2 and osteoclast precursors, suggesting potential implications for bone homeostasis and opening new avenues for therapeutic exploration in COVID‐19.

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SARS-CoV-2 and its Multifaceted Impact on Bone Health: Mechanisms and Clinical Evidence

Cited by 7 publications

References 123 publications

The Use of Artificial Intelligence in Writing Scientific Review Articles

The Use of Artificial Intelligence in Writing Scientific Review Articles

The Utility of AI in Writing a Scientific Review Article on the Impacts of COVID-19 on Musculoskeletal Health

The abortive SARS‐CoV‐2 infection of osteoclast precursors promotes their differentiation into osteoclasts

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