1
|
Wang XL, Zhao YR, Yu Y, Mao ZF, Tan SX, Yu SS. Impact of dietary nutrition regimens based on body composition analysis on bone metabolism in Alzheimer's disease patients. World J Psychiatry 2025; 15:99008. [PMID: 39974500 PMCID: PMC11758049 DOI: 10.5498/wjp.v15.i2.99008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Revised: 11/27/2024] [Accepted: 12/17/2024] [Indexed: 01/14/2025] Open
Abstract
BACKGROUND Body composition analysis (BCA) is primarily used in the management of conditions such as obesity and endocrine disorders. However, its potential in providing nutritional guidance for patients with Alzheimer's disease (AD) remains relatively unexplored. AIM To explore the clinical efficacy of BCA-based dietary nutrition scheme on bone metabolism in AD patients. METHODS This retrospective study included 96 patients with AD complicated by osteoporosis who were admitted to The Third Hospital of Quzhou between January 2023 and December 2024. Based on data from previous similar studies, the patients were randomly assigned to either a routine diet (RD) group (n = 48) or a personalized nutrition (PN) group (n = 48). The RD group received conventional dietary guidance, while the PN group received individualized diet intervention measures based on human BCA. The intervention period lasted for 12 weeks. Bone mineral density (BMD), body mass index (BMI), muscle mass, mineral content, osteocalcin, 25-hydroxyvitamin D, procollagen type I N-terminal propeptide (PINP), beta C-terminal telopeptide of type I collagen (β-CTX), and serum calcium were measured and compared between the two groups before and 12 weeks after the intervention. RESULTS No significant differences were observed between groups in terms of age, sex, height, BMI, or other baseline data (P > 0.05). In both groups, BMI did not show significant changes after the intervention (P > 0.05), whereas muscle mass and mineral content were significantly increased (P < 0.05). After the intervention, BMI in the PN group did not differ significantly from that of the RD group, but muscle mass and mineral content were significantly higher in the PN group (P < 0.05). After the intervention, a higher proportion of patients in the PN group had a T score > -1 compared to the RD group (P < 0.05). The mini-mental state examination (MMSE) score was similar in both groups before the intervention. However, 12 weeks after the intervention, the MMSE score in the PN group was significantly higher than that in the RD group (P < 0.05). In both groups, the MMSE score significantly increased 12 weeks post-intervention compared to pre-intervention levels (P < 0.05). Before the intervention, the levels of osteocalcin, serum calcium, PINP, β-CTX, and 25-hydroxyvitamin D were not significantly different between the two groups (P > 0.05). After 12 weeks of intervention, the PN group exhibited higher levels of osteocalcin, serum calcium, and 25-hydroxyvitamin D, as well as lower levels of PINP and β-CTX, compared to the RD group (P < 0.05). In both groups, osteocalcin, serum calcium, and 25-hydroxyvitamin D levels were significantly higher, while PINP and β-CTX levels were significantly lower after 12 weeks of intervention compared to baseline (P < 0.05). CONCLUSION The human BCA-based dietary nutrition regimen plays a crucial role in improving BMD and bone metabolism, with effects that surpass those of conventional nutrition strategies. The findings of this study provide strong evidence for the nutritional management of AD patients.
Collapse
Affiliation(s)
- Xue-Lian Wang
- Department of Clinical Nutrition, The Third Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
| | - Yi-Ran Zhao
- Department of Rehabilitation Treatment Group, The Third Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
| | - Ying Yu
- Department of Geriatrics, The Third Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
| | - Zhi-Fang Mao
- Department of Rehabilitation Medicine, The Third Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
| | - Su-Xian Tan
- Department of Psychiatry, The Third Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
| | - Shan-Shan Yu
- Department of Geriatric Psychiatry, The Third Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
| |
Collapse
|
2
|
Nasme F, Behera J, Tyagi P, Debnath N, Falcone JC, Tyagi N. The potential link between the development of Alzheimer's disease and osteoporosis. Biogerontology 2025; 26:43. [PMID: 39832071 DOI: 10.1007/s10522-024-10181-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Accepted: 12/28/2024] [Indexed: 01/22/2025]
Abstract
Alzheimer's disease (AD) and osteoporosis (OP) pose distinct but interconnected health challenges, both significantly impacting the aging population. AD, a neurodegenerative disorder characterized by memory impairment and cognitive decline, is primarily associated with the accumulation of abnormally folded amyloid beta (Aβ) peptides and neurofibrillary tangles in the brain. OP, a skeletal disorder marked by low bone mineral density, involves dysregulation of bone remodeling and is associated with an increased risk of fractures. Recent studies have revealed an intriguing link between AD and OP, highlighting shared pathological features indicative of common regulatory pathophysiological pathways. In this article, we elucidate the signaling mechanisms that regulate the pathology of AD and OP and offer insights into the intricate network of factors contributing to these conditions. We also examine the role of bone-derived factors in the progression of AD, underscoring the plausibility of bidirectional communication between the brain and the skeletal system. The presence of amyloid plaques in the brain of individuals with AD is akin to the accumulation of brain Aβ in vascular dementia, pointing towards the need for further investigation of shared molecular mechanisms. Moreover, we discuss the role of bone-derived microRNAs that may regulate the pathological progression of AD, providing a novel perspective on the role of skeletal factors in neurodegenerative diseases. The insights presented here should help researchers engaged in exploring innovative therapeutic approaches targeting both neurodegenerative and skeletal disorders in aging populations.
Collapse
Affiliation(s)
- Fariha Nasme
- Department of Physiology, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Jyotirmaya Behera
- Division of Immunology, Harvard Medical School, Boston Children's Hospital, Boston, MA, USA
| | - Prisha Tyagi
- Department of Physiology, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Nabendu Debnath
- Centre for Molecular Biology, Central University of Jammu, Rahya-Suchani (Bagla) Samba, Jammu, Jammu & Kashmir, 181143, India
| | - Jeff C Falcone
- Department of Physiology, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Neetu Tyagi
- Department of Physiology, School of Medicine, University of Louisville, Louisville, KY, 40202, USA.
| |
Collapse
|
3
|
Curtis EM, Miguel M, McEvoy C, Ticinesi A, Torre C, Al-Daghri N, Alokail M, Bałkowiec-Iskra E, Bruyère O, Burlet N, Cavalier E, Cerreta F, Clark P, Cherubini A, Cooper C, D'Amelio P, Fuggle N, Gregson C, Halbout P, Kanis JA, Kaufman J, Laslop A, Maggi S, Maier A, Matijevic R, McCloskey E, Ormarsdóttir S, Yerro CP, Radermecker RP, Rolland Y, Singer A, Veronese N, Rizzoli R, Reginster JY, Harvey NC. Impact of dementia and mild cognitive impairment on bone health in older people. Aging Clin Exp Res 2024; 37:5. [PMID: 39725855 PMCID: PMC11671436 DOI: 10.1007/s40520-024-02871-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 10/20/2024] [Indexed: 12/28/2024]
Abstract
Mild cognitive impairment, dementia and osteoporosis are common diseases of ageing and, with the increasingly ageing global population, are increasing in prevalence. These conditions are closely associated, with shared risk factors, common underlying biological mechanisms and potential direct causal pathways. In this review, the epidemiological and mechanistic links between mild cognitive impairment, dementia and skeletal health are explored. Discussion will focus on how changes in brain and bone signalling can underly associations between these conditions, and will consider the molecular and cellular drivers in the context of inflammation and the gut microbiome. There is a complex interplay between nutritional changes, which may precede or follow the onset of mild cognitive impairment (MCI) or dementia, and bone health. Polypharmacy is common in patients with MCI or dementia, and there are difficult prescribing decisions to be made due to the elevated risk of falls associated with many drugs used for associated problems, which can consequently increase fracture risk. Some medications prescribed for cognitive impairment may directly impact bone health. In addition, patients may have difficulty remembering medication without assistance, meaning that osteoporosis drugs may be prescribed but not taken. Cognitive impairment may be improved or delayed by physical activity and exercise, and there is evidence for the additional benefits of physical activity on falls and fractures. Research gaps and priorities with the aim of reducing the burden of osteoporosis and fractures in people with MCI or dementia will also be discussed.
Collapse
Affiliation(s)
- Elizabeth M Curtis
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton, Southampton, UK
| | - Mario Miguel
- Centro de Estudos Egas Moniz, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
| | - Claire McEvoy
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
| | - Andrea Ticinesi
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Azienda Ospedaliero-Universitaria Di Parma, Parma, Italy
| | - Carla Torre
- Faculdade de Farmácia, Universidade de Lisboa, Avenida Professor Gama Pinto, 1649-003, Lisbon, Portugal
- Laboratory of Systems Integration Pharmacology, Clinical and Regulatory Science, Research Institute for Medicines of the University of Lisbon (iMED.ULisboa), Avenida Professor Gama Pinto, 1649-003, Lisbon, Portugal
| | - Nasser Al-Daghri
- Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, 11451, Riyadh, Kingdom of Saudi Arabia
| | - Majed Alokail
- Biochemistry Department, College of Science, KSU, Riyadh, Kingdom of Saudi Arabia
| | - Ewa Bałkowiec-Iskra
- Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Warsaw, Poland
- The Office for Registration of Medicinal Products, Medical Devices and Biocidal Products & CHMP, SAWP, CNSWP, PCWP, ETF (European Medicines Agency) Member, Warsaw, Poland
| | - Olivier Bruyère
- Research Unit in Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium
- Department of Physical Activity and Rehabilitation Sciences, University of Liège, Liège, Belgium
| | - Nansa Burlet
- Research Unit in Epidemiology, University of Liege, Liège, Belgium
| | - Etienne Cavalier
- Department of Clinical Chemistry, CIRM, University of Liège, CHU de Liège, Liège, Belgium
| | - Francesca Cerreta
- Digital Health and Geriatrics, European Medicines Agency, Amsterdam, The Netherlands
| | - Patricia Clark
- Clinical Epidemiology Unit, Hospital Infantil Federico Gómez-Facultad de Medicina, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Antonio Cherubini
- Geriatria, Accettazione Geriatrica e Centro di ricerca per l'invecchiamento, IRCCS INRCA Istituto Nazionale di Ricovero e Cura per Anziani, Ancona, Italy
- Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy
| | - Cyrus Cooper
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton, Southampton, UK
| | - Patrizia D'Amelio
- Department of Medicine, Service of Geriatric Medicine & Geriatric Rehabilitation, University of Lausanne Hospital, University of Lausanne, Lausanne, Switzerland
| | - Nicholas Fuggle
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton, Southampton, UK
| | - Celia Gregson
- Musculoskeletal Research Unit, Bristol Medical School, Learning and Research Building, University of Bristol, Southmead Hospital, Bristol, BS10 5NB, UK
- The Health Research Unit of Zimbabwe (THRU ZIM), The Biomedical Research and Training Institute, Harare, Zimbabwe
| | | | - John A Kanis
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
- Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK
| | - Jean Kaufman
- Department of Endocrinology, Ghent University Hospital, Ghent, Belgium
| | - Andrea Laslop
- Scientific Office, Austrian Medicines and Medical Devices Agency, Vienna, Austria
| | | | - Andrea Maier
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117596, Singapore
- Department of Human Movement Sciences, at AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Radmila Matijevic
- Faculty of Medicine in Novi Sad, University of Novi Sad, Novi Sad, Serbia
| | - Eugene McCloskey
- Mellanby Centre for Musculoskeletal Research, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK
- MRC Versus Arthritis Centre for Integrated Research in Musculoskeletal Ageing, University of Sheffield, Sheffield, UK
| | - Sif Ormarsdóttir
- Medicine Assessment and Licencing, Icelandic Medicines Agency, Reykjavik, Iceland
| | | | - Régis P Radermecker
- Department of Diabetes, Nutrition and Metabolic Disorders, Clinical Pharmacology, University of Liege, CHU de Liège, Liège, Belgium
| | - Yves Rolland
- HealthAge, CHU Toulouse, CERPOP UMR 1295, Inserm, Université Paul Sabatier, Toulouse, France
| | - Andrea Singer
- Departments of Obstetrics & Gynecology and Medicine, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Nicola Veronese
- Department of Internal Medicine, Geriatrics Section, University of Palermo, Palermo, Italy
| | - René Rizzoli
- Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | - Jean-Yves Reginster
- Protein Research Chair, Biochemistry Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Nicholas C Harvey
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK.
- NIHR Southampton Biomedical Research Centre, University of Southampton, Southampton, UK.
| |
Collapse
|
4
|
Lin X, Zuo Y, Hu H, Zhou J. Causal relationship between reproductive factors and female bone density: a univariate and multivariate mendelian randomization study. Front Genet 2024; 15:1393106. [PMID: 39346779 PMCID: PMC11427258 DOI: 10.3389/fgene.2024.1393106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 08/23/2024] [Indexed: 10/01/2024] Open
Abstract
Objective Observational studies have found associations between reproductive factors and bone density in women. However, the causal relationships are not well understood. This study aims to investigate whether various reproductive factors are causally related to bone density at different skeletal sites using both univariable and multivariable Mendelian randomization (MR) methods. Methods The study incorporated four reproductive factors, namely, age at menarche (AAM), age at first live birth (AFB), age at menopause (ANM), and age at last live birth (ALB), as well as five distinct skeletal sites, including bone mineral density (BMD), heel calcaneus BMD, ultradistal forearm bone mineral density (FA-BMD), lumbar spine bone mineral density (LS-BMD), and femoral neck bone mineral density (FN-BMD). Univariable two-sample MR and multivariable MR analyses were conducted using data from published genome-wide association studies (GWASs). A total of 150 single nucleotide polymorphisms (SNPs) associated with the four reproductive factors were extracted from GWAS databases. The primary statistical analysis method utilized in this study was the inverse variance weighted (IVW) method. Results In the univariate MR analysis, we observed causal connections between four reproductive factors and bone density. Specifically, AAM had a significant impact on BMD and heel calcaneus BMD. Age at first live birth was negatively associated with FA-BMD. Age at last live birth showed a negative correlation with BMD and heel calcaneus BMD. ANM exhibited positive associations with BMD, heel calcaneus BMD, FA-BMD, and LS-BMD. Subsequently, we performed a multivariable MR analysis to examine the combined effects of multiple variables, which confirmed the persistence of associations between age at menopause and bone density at various sites. Additionally, we found a negative correlation between age at last live birth and heel calcaneus BMD. Conclusion This study offers a fresh perspective on the prevention of osteoporosis in women, explicitly stating that reproductive factors such as early menopause and late childbirth play a significant predictive role in individual bone density decline. Therefore, when developing osteoporosis screening and management protocols, reproductive factors should be included for a more comprehensive guidance of clinical practice.
Collapse
Affiliation(s)
| | - Yaqi Zuo
- Guangdong Medical University, Zhanjiang, China
| | - Hongbo Hu
- Yuebei People's Hospital, Guangdong Medical University, Shaoguan, China
| | - Jie Zhou
- Yuebei People's Hospital, Shaoguan, China
| |
Collapse
|
5
|
Rishabh, Rohilla M, Bansal S, Bansal N, Chauhan S, Sharma S, Goyal N, Gupta S. Estrogen signalling and Alzheimer's disease: Decoding molecular mechanisms for therapeutic breakthrough. Eur J Neurosci 2024; 60:3466-3490. [PMID: 38726764 DOI: 10.1111/ejn.16360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/19/2024] [Accepted: 04/02/2024] [Indexed: 07/06/2024]
Abstract
In females, Alzheimer's disease (AD) incidences increases as compared to males due to estrogen deficiency after menopause. Estrogen therapy is the mainstay therapy for menopause and associated complications. Estrogen, a hormone with multifaceted physiological functions, has been implicated in AD pathophysiology. Estrogen plays a crucial role in amyloid precursor protein (APP) processing and overall neuronal health by regulating various factors such as brain-derived neurotrophic factor (BDNF), intracellular calcium signalling, death domain-associated protein (Daxx) translocation, glutamatergic excitotoxicity, Voltage-Dependent Anion Channel, Insulin-Like Growth Factor 1 Receptor, estrogen-metabolising enzymes and apolipoprotein E (ApoE) protein polymorphisms. All these factors impact the physiology of postmenopausal women. Estrogen replacement therapies play an important treatment strategy to prevent AD after menopause. However, use of these therapies may lead to increased risks of breast cancer, venous thromboembolism and cardiovascular disease. Various therapeutic approaches have been used to mitigate the effects of estrogen on AD. These include hormone replacement therapy, Selective Estrogen Receptor Modulators (SERMs), Estrogen Receptor Beta (ERβ)-Selective Agonists, Transdermal Estrogen Delivery, Localised Estrogen Delivery, Combination Therapies, Estrogen Metabolism Modulation and Alternative Estrogenic Compounds like genistein from soy, a notable phytoestrogen from plant sources. However, mechanism via which these approaches modulate AD in postmenopausal women has not been explained earlier thoroughly. Present review will enlighten all the molecular mechanisms of estrogen and estrogen replacement therapies in AD. Along-with this, the association between estrogen, estrogen-metabolising enzymes and ApoE protein polymorphisms will also be discussed in postmenopausal AD.
Collapse
Affiliation(s)
- Rishabh
- Department of Pharmacology, M. M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, India
| | - Manni Rohilla
- Department of Pharmacology, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India
| | - Seema Bansal
- Department of Pharmacology, M. M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, India
| | - Nitin Bansal
- Department of Pharmacy, Chaudhary Bansilal University, Bhiwani, India
| | - Samrat Chauhan
- Department of Pharmacology, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India
| | - Sheenam Sharma
- Department of Pharmacology, M. M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, India
| | - Navjyoti Goyal
- Department of Pharmacology, M. M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, India
| | - Sumeet Gupta
- Department of Pharmacology, M. M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, India
| |
Collapse
|
6
|
Nazzal MK, Morris AJ, Parker RS, White FA, Natoli RM, Fehrenbacher JC, Kacena MA. Using AI to Write a Review Article Examining the Role of the Nervous System on Skeletal Homeostasis and Fracture Healing. Curr Osteoporos Rep 2024; 22:217-221. [PMID: 38217755 PMCID: PMC10912134 DOI: 10.1007/s11914-023-00854-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 01/15/2024]
Abstract
PURPOSE OF REVIEW Three review articles have been written that discuss the roles of the central and peripheral nervous systems in fracture healing. While content among the articles is overlapping, there is a key difference between them: the use of artificial intelligence (AI). In one paper, the first draft was written solely by humans. In the second paper, the first draft was written solely by AI using ChatGPT 4.0 (AI-only or AIO). In the third paper, the first draft was written using ChatGPT 4.0 but the literature references were supplied from the human-written paper (AI-assisted or AIA). This project was done to evaluate the capacity of AI to conduct scientific writing. Importantly, all manuscripts were fact checked and extensively edited by all co-authors rendering the final manuscript drafts significantly different from the first drafts. RECENT FINDINGS Unsurprisingly, the use of AI decreased the time spent to write a review. The two AI-written reviews took less time to write than the human-written paper; however, the changes and editing required in all three manuscripts were extensive. The human-written paper was edited the most. On the other hand, the AI-only paper was the most inaccurate with inappropriate reference usage and the AI-assisted paper had the greatest incidence of plagiarism. These findings show that each style of writing presents its own unique set of challenges and advantages. While AI can theoretically write scientific reviews, from these findings, the extent of editing done subsequently, the inaccuracy of the claims it makes, and the plagiarism by AI are all factors to be considered and a primary reason why it may be several years into the future before AI can present itself as a viable alternative for traditional scientific writing.
Collapse
Affiliation(s)
- Murad K Nazzal
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ashlyn J Morris
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Reginald S Parker
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Fletcher A White
- Department of Anesthesia, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA
| | - Roman M Natoli
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jill C Fehrenbacher
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA.
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Melissa A Kacena
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Anesthesia, Indiana University School of Medicine, Indianapolis, IN, USA.
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA.
| |
Collapse
|
7
|
Awosanya OD, Harris A, Creecy A, Qiao X, Toepp AJ, McCune T, Kacena MA, Ozanne MV. The Utility of AI in Writing a Scientific Review Article on the Impacts of COVID-19 on Musculoskeletal Health. Curr Osteoporos Rep 2024; 22:146-151. [PMID: 38216806 PMCID: PMC10912275 DOI: 10.1007/s11914-023-00855-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 01/14/2024]
Abstract
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. 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.
Collapse
Affiliation(s)
- Olatundun D Awosanya
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alexander Harris
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Amy Creecy
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xian Qiao
- Critical Care, and Sleep Specialists, SMG Pulmonary, Norfolk, VA, USA
- Division of Pulmonary and Critical Care Medicine, Eastern Virginia Medical School, Norfolk, VA, USA
- Department of Internal Medicine, Eastern Virginia Medical School, Norfolk, VA, USA
| | - Angela J Toepp
- Department of Internal Medicine, Eastern Virginia Medical School, Norfolk, VA, USA
- Sentara Health, Enterprise Analytics, Norfolk, VA, USA
| | - Thomas McCune
- Department of Internal Medicine, Eastern Virginia Medical School, Norfolk, VA, USA
- Division of Nephrology, Eastern Virginia Medical School, Norfolk, VA, USA
| | - Melissa A Kacena
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, USA.
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA.
| | - Marie V Ozanne
- Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA, USA.
| |
Collapse
|
8
|
Margetts TJ, Karnik SJ, Wang HS, Plotkin LI, Oblak AL, Fehrenbacher JC, Kacena MA, Movila A. Use of AI Language Engine ChatGPT 4.0 to Write a Scientific Review Article Examining the Intersection of Alzheimer's Disease and Bone. Curr Osteoporos Rep 2024; 22:177-181. [PMID: 38225472 PMCID: PMC10912103 DOI: 10.1007/s11914-023-00853-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 01/17/2024]
Abstract
PURPOSE OF REVIEW This Comment represents three review articles on the relationship between Alzheimer's disease, osteoporosis, and fracture in an exploration of the benefits that AI can provide in scientific writing. The first drafts of the articles were written (1) entirely by humans; (2) entirely by ChatGPT 4.0 (AI-only or AIO); and (3) by humans and ChatGPT 4.0 whereby humans selected literature references, but ChatGPT 4.0 completed the writing (AI-assisted or AIA). Importantly, each review article was edited and carefully checked for accuracy by all co-authors resulting in a final manuscript which was significantly different from the original draft. RECENT FINDINGS The human-written article took the most time from start to finish, the AI-only article took the least time, and the AI-assisted article fell between the two. When comparing first drafts to final drafts, the AI-only and AI-assisted articles had higher percentages of different text than the human article. The AI-only paper had a higher percentage of incorrect references in the first draft than the AI-assisted paper. The first draft of the AI-assisted article had a higher similarity score than the other two articles when examined by plagiarism identification software. This writing experiment used time tracking, human editing, and comparison software to examine the benefits and risks of using AI to assist in scientific writing. It showed that while AI may reduce total writing time, hallucinations and plagiarism were prevalent issues with this method and human editing was still necessary to ensure accuracy.
Collapse
Affiliation(s)
- Tyler J Margetts
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Sonali J Karnik
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Hannah S Wang
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Lilian I Plotkin
- Department of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, 46202, USA
| | - Adrian L Oblak
- Department of Radiology & Imaging Sciences, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Jill C Fehrenbacher
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Melissa A Kacena
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Department of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA.
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, 46202, USA.
| | - Alexandru Movila
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Biomedical Sciences and Comprehensive Care, Indiana University School of Dentistry, Indianapolis, IN, 46202, USA.
| |
Collapse
|
9
|
Kacena MA, Plotkin LI, Fehrenbacher JC. The Use of Artificial Intelligence in Writing Scientific Review Articles. Curr Osteoporos Rep 2024; 22:115-121. [PMID: 38227177 PMCID: PMC10912250 DOI: 10.1007/s11914-023-00852-0] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 01/17/2024]
Abstract
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. 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.
Collapse
Affiliation(s)
- Melissa A Kacena
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Department of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, 46202, USA.
| | - Lilian I Plotkin
- Department of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, 46202, USA
| | - Jill C Fehrenbacher
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
| |
Collapse
|