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Article ; Online: Pannexin 3 deletion in mice results in knee osteoarthritis and intervertebral disc degeneration after forced treadmill running.

Wakefield, Brent / Tang, Justin / Hutchinson, Jeffrey L / Kanji, Rehanna / Brooks, Courtney / Grol, Matthew W / Séguin, Cheryle A / Penuela, Silvia / Beier, Frank

Journal of orthopaedic research : official publication of the Orthopaedic Research Society

2024

Abstract: Pannexin 3 (Panx3) is a glycoprotein that forms mechanosensitive channels expressed in chondrocytes and annulus fibrosus cells of the intervertebral disc (IVD). Evidence suggests Panx3 plays contrasting roles in traumatic versus aging osteoarthritis (OA) ...

Abstract	Pannexin 3 (Panx3) is a glycoprotein that forms mechanosensitive channels expressed in chondrocytes and annulus fibrosus cells of the intervertebral disc (IVD). Evidence suggests Panx3 plays contrasting roles in traumatic versus aging osteoarthritis (OA) and intervertebral disc degeneration (IDD). However, whether its deletion influences the response of joint tissue to forced use is unknown. The purpose of this study was to determine if Panx3 deletion in mice causes increased knee joint OA and IDD after forced treadmill running. Male and female wildtype (WT) and Panx3 knockout (KO) mice were randomized to either a no-exercise group (sedentary; SED) or daily forced treadmill running (forced exercise; FEX) from 24 to 30 weeks of age. Knee cartilage and IVD histopathology were evaluated by histology, while tibial secondary ossification centers were analyzed using microcomputed tomography (µCT). Both male and female Panx3 KO mice developed larger superficial defects of the tibial cartilage after forced treadmill running compared with SED WT mice. Additionally, Panx3 KO mice developed reduced bone volume, and female PANX3 KO mice had lengthening of the lateral tubercle at the intercondylar eminence. In the lower lumbar spine, both male and female Panx3 KO mice developed histopathological features of IDD after running compared to SED WT mice. These findings suggest that the combination of deleting Panx3 and forced treadmill running induces OA and causes histopathological changes associated with the degeneration of the IVDs in mice.
Language	English
Publishing date	2024-03-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	605542-4
ISSN	1554-527X ; 0736-0266
ISSN (online)	1554-527X
ISSN	0736-0266
DOI	10.1002/jor.25830
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Article: A spatial agent-based joint model of electric vehicle and vehicle-to-grid adoption: A case of Beijing

Liu, Junbei / Zhuge, Chengxiang / Tang, Justin Hayse Chiwing G. / Meng, Meng / Zhang, Jie

Applied energy. 2022 Mar. 15, v. 310

2022

Abstract: The potential widespread adoption of Electric Vehicles (EVs) has received considerable attention across the globe. However, as a promising technology for both EVs and smart grid, Vehicle-to-Grid (V2G) tended to receive much less attention. This paper ... ...

Abstract	The potential widespread adoption of Electric Vehicles (EVs) has received considerable attention across the globe. However, as a promising technology for both EVs and smart grid, Vehicle-to-Grid (V2G) tended to receive much less attention. This paper developed an agent-based joint EV and V2G model to simultaneously simulate how EVs and V2G might diffuse across space and over time, with empirical findings from a questionnaire survey in Beijing. In particular, random forest models were developed with the survey data to generate each agent’s preferences and attitudes towards EVs and V2G. The joint model also considered three typical levels of social influence, i.e., global influence, neighbor effect, and friendship effect, in the diffusion of EVs and V2G. Finally, the joint model was tested through several “what-if” scenarios, considering different V2G prices, EV/V2G advertisement intensities, and vehicle purchase restrictions. The survey results suggested that 67.7% of the respondents were familiar with EVs, but only 3.3% of them were familiar with V2G. However, over 70% of them would/might try V2G given that they had an EV. The model results suggested that the number of CV applicants was 6.19 times that of BEV applicants in 2030 in the baseline scenario, and only 27.8% of BEV users adopted V2G. Furthermore, V2G selling price, EV/V2G advertisement, and dedicated PHEV purchase permits were not very influential to the diffusion of V2G. The outcomes would be helpful for EV- and V2G-related stakeholders in policy making and technology investment.
Keywords	electric vehicles ; electrical equipment ; energy ; interpersonal relationships ; issues and policy ; models ; questionnaires ; stakeholders ; surveys ; China
Language	English
Dates of publication	2022-0315
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	2000772-3
ISSN	0306-2619
ISSN	0306-2619
DOI	10.1016/j.apenergy.2022.118581
Database	NAL-Catalogue (AGRICOLA)

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Article: What Are Patients Saying About Minimally Invasive Spine Surgeons Online: A Sentiment Analysis of 2,235 Physician Review Website Reviews.

Tang, Justin / White, Christopher A / Arvind, Varun / Cho, Samuel / Kim, Jun S / Steinberger, Jeremy

Cureus

2022 Volume 14, Issue 4, Page(s) e24113

Abstract: Objective Physician review websites are becoming increasingly popular for patients to find and review healthcare providers. The goal of this study was to utilize quantitative analyses to understand trends in ratings and written comments on physician ... ...

Abstract	Objective Physician review websites are becoming increasingly popular for patients to find and review healthcare providers. The goal of this study was to utilize quantitative analyses to understand trends in ratings and written comments on physician review websites for Society of Minimally Invasive Spine Surgery (SMISS) members. Methods This is a cross-sectional study. The reviews of SMISS surgeons were obtained from healthgrades.com, and sentiment analysis was used to obtain compound scores of each physicians' reviews. SMISS surgeons who were international or had fewer than three written reviews, often consisting of residents and fellows, were excluded. Inferential statistics were utilized, and word frequency analysis reported the phrases used to characterize reviews. Results One hundred sixty-nine surgeons met the inclusion criteria. 98.6% were males and the mean age was 51.7 years old. A total of 2,235 written reviews were analyzed. Younger surgeons were significantly more likely to receive higher star ratings (p<0.01). Positive behavioral characteristics, such as "kind" and "bedside manner," conferred significantly improved odds of receiving positive reviews (p<0.01). Ancillary "staff" conferred a 2x greater odds of receiving a positive review whereas a comment on "wait" times halved a surgeon's odds (p<0.01). Sentences describing pain drove down the odds of positive reviews whereas those describing pain relief produced greater odds of positive reviews (p<0.01). Conclusion Physicians who were younger, personable, provided sufficient pain relief, and who worked in favorable offices received the most positive reviews. This study informs SMISS members on the traits deemed important by patients who ultimately review surgeons online.
Language	English
Publishing date	2022-04-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.24113
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Article ; Online: How are Patients Describing You Online? A Natural Language Processing Driven Sentiment Analysis of Online Reviews on CSRS Surgeons.

Tang, Justin / Arvind, Varun / White, Christopher A / Dominy, Calista / Cho, Samuel / Kim, Jun S

Clinical spine surgery

2022 Volume 36, Issue 2, Page(s) E107–E113

Abstract: Study design: A quantitative analysis of written, online reviews of Cervical Spine Research Society (CSRS) surgeons.: Objective: This study quantitatively analyzes the written reviews of members of the CSRS to report biases associated with ... ...

Abstract	Study design: A quantitative analysis of written, online reviews of Cervical Spine Research Society (CSRS) surgeons. Objective: This study quantitatively analyzes the written reviews of members of the CSRS to report biases associated with demographic factors and frequently used words in reviews to help aid physician practices. Summary of background data: Physician review websites have influence on a patient's selection of a provider, but written reviews are subjective. Sentiment analysis of writing through artificial intelligence can quantify surgeon reviews to provide actionable feedback. Methods: Online written and star-rating reviews of CSRS surgeons were obtained from healthgrades.com. A sentiment analysis package was used to obtain compound scores of each physician's reviews. The relationship between demographic variables and average sentiment score of written reviews were evaluated through t -tests. Positive and negative word and bigram frequency analysis was performed to indicate trends in the reviews' language. Results: In all, 2239 CSRS surgeon's reviews were analyzed. Analysis showed a positive correlation between the sentiment scores and overall average star-rated reviews ( r2 =0.60, P <0.01). There was no difference in review sentiment by provider sex. However, the age of surgeons showed a significant difference as those <55 had more positive reviews (mean=+0.50) than surgeons >=55 (mean=+0.37) ( P <0.01). The most positive reviews focused both on pain and behavioral factors, whereas the most negative focused mainly on pain. Behavioral attributes increased the odds of receiving positive reviews while pain decreased them. Conclusion: The top-rated surgeons were described as considerate providers and effective at managing pain in their most frequently used words and bigrams. However, the worst-rated ones were mainly described as unable to relieve pain. Through quantitative analysis of physician reviews, pain is a clear factor contributing to both positive and negative reviews of surgeons, reinforcing the need for proper pain expectation management. Level of evidence: Level 4-retrospective case-control study.
MeSH term(s)	Humans ; Retrospective Studies ; Natural Language Processing ; Sentiment Analysis ; Case-Control Studies ; Artificial Intelligence ; Patient Satisfaction ; Surgeons ; Pain ; Cervical Vertebrae ; Internet
Language	English
Publishing date	2022-08-10
Publishing country	United States
Document type	Journal Article
ZDB-ID	2849646-2
ISSN	2380-0194 ; 2380-0186
ISSN (online)	2380-0194
ISSN	2380-0186
DOI	10.1097/BSD.0000000000001372
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Article ; Online: Reducing PTV margins for prostate SBRT with motion compensation and gating techniques.

Goddard, Lee / Jeong, Kyoungkeun / Tang, Justin / Garg, Madhur / Tomé, Wolfgang A

Journal of applied clinical medical physics

2022 Volume 24, Issue 4, Page(s) e13861

Abstract: The purpose of this study is to investigate the dosimetric accuracy of prostate SBRT when motion is considered. To account for target movement, motion compensation and gating techniques were investigated with PTV margins reduced to 2 mm. To allow for ... ...

Abstract	The purpose of this study is to investigate the dosimetric accuracy of prostate SBRT when motion is considered. To account for target movement, motion compensation and gating techniques were investigated with PTV margins reduced to 2 mm. To allow for dosimetric measurements a Delta4 phantom, Gafchromic film, and Hexamotion motion platform were utilized. Four motion files were utilized that represent a range of motions. Analysis of measured prostate motions for fifteen patients was performed to ensure detected motions were similar to those previously reported and motion files utilized were suitable. Five patient plans were utilized to allow for the effects of MLC and target motion interplay to be investigated. For both motion compensation and gating techniques, plans were delivered to the stationary phantom and for each of four motion types with/without compensation/gating enabled. Using a 3%, 2 mm and 80% threshold gamma criteria, film measurements had an average pass rate of 80.5% for uncorrected deliveries versus 96.0% for motion compensated deliveries. For gated techniques average pass rates increased from 89.9% for uncorrected to 94.8% with gating enabled. Measurements with the Delta4 arrays were analyzed with a 3%, 2 mm and 10% threshold dose. An average pass rate of 83.8% was measured for uncorrected motions versus 94.8% with motion compensation. For the gated technique an average pass rate of 87.2% was found for uncorrected motions versus 96.9% with gating enabled. These results show that very high gamma pass rates are achievable when motion compensation or gating techniques are applied. When target motion is not accounted for shifts up to 5 mm in planned versus delivered isodose distributions were found. However, when motion compensation, or gated techniques were applied, much smaller differences between planned and delivered isodose distributions were found. With these techniques dose delivery accuracy is greatly improved, allowing for PTV margins to be reduced.
MeSH term(s)	Male ; Humans ; Prostate ; Radiosurgery/methods ; Radiotherapy, Intensity-Modulated/methods ; Radiotherapy Planning, Computer-Assisted/methods ; Motion ; Movement ; Radiometry/methods ; Radiotherapy Dosage
Language	English
Publishing date	2022-12-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2010347-5
ISSN	1526-9914 ; 1526-9914
ISSN (online)	1526-9914
ISSN	1526-9914
DOI	10.1002/acm2.13861
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Article: How Are Patients Reviewing Spine Surgeons Online? A Sentiment Analysis of Physician Review Website Written Comments.

Tang, Justin E / Arvind, Varun / Dominy, Calista / White, Christopher A / Cho, Samuel K / Kim, Jun S

Global spine journal

2022 Volume 13, Issue 8, Page(s) 2107–2114

Abstract: Study design: A Sentiment Analysis of online reviews of spine surgeons.: Objectives: Physician review websites have significant impact on a patient's provider selection. Written reviews are subjective, but sentiment analysis through machine learning ... ...

Abstract	Study design: A Sentiment Analysis of online reviews of spine surgeons. Objectives: Physician review websites have significant impact on a patient's provider selection. Written reviews are subjective, but sentiment analysis through machine learning can quantitatively analyze these reviews. This study analyzes online written reviews of spine surgeons and reports biases associated with demographic factors and trends in words utilized. Methods: Online written and star-reviews of spine surgeons were obtained from healthgrades.com. A sentiment analysis package was used to analyze the written reviews. The relationship of demographic variables to these scores was analyzed with t-tests and word and bigram frequency analyses were performed. Additionally, a multiple regression analysis was performed on key terms. Results: 8357 reviews of 480 surgeons were analyzed. There was a significant difference between the means of sentiment analysis scores and star scores for both gender and age. Younger, male surgeons were rated more highly on average ( Conclusions: The best reviews laud surgeons for their ability to manage pain and for exhibiting positive bedside manner. However, the worst reviews primarily focus on pain and its management, as exhibited by the frequency and multivariate analysis. Pain is a clear contributing factor to reviews, thus emphasizing the importance of establishing proper pain expectations prior to any intervention.
Language	English
Publishing date	2022-01-27
Publishing country	England
Document type	Journal Article
ZDB-ID	2648287-3
ISSN	2192-5690 ; 2192-5682
ISSN (online)	2192-5690
ISSN	2192-5682
DOI	10.1177/21925682211069933
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The Role of Triglyceride-Glucose Index in the Prediction of the Development of Hypertension - Findings from a Community Cohort in Singapore.

Khoo, Jonathon Kc / Low, Serena / Irwan, Bastari / Tang, Justin Is / Sum, Chee Fang / Subramaniam, Tavintharan / Lim, Su Chi

Journal of the ASEAN Federation of Endocrine Societies

2023 Volume 38, Issue 1, Page(s) 62–67

Abstract: Objectives: Triglyceride-glucose index (TyGI) is an emerging surrogate marker of insulin resistance. We aim to explore the role of triglyceride-glucose index in the prediction of the development of hypertension.: Methodology: We conducted a ... ...

Abstract	Objectives: Triglyceride-glucose index (TyGI) is an emerging surrogate marker of insulin resistance. We aim to explore the role of triglyceride-glucose index in the prediction of the development of hypertension. Methodology: We conducted a retrospective cohort study that included 3,183 study participants identified from a community health screening programme who had no baseline hypertension and were then followed up after an average of 1.7 years. Cox proportional-hazard model was used to assess the association between risk of incident hypertension and TyGI in quartiles, while adjusting for demographics and clinical characteristics. Results: Hypertension occurred in 363 study participants (11.4%). Those who developed hypertension had higher TyGI [8.6 (IQR 8.2-9.0)] than those who did not [8.2 (IQR 8.0-8.7)] ( Conclusion: Triglyceride-glucose index was an independent predictor of the development of hypertension. It may potentially be used as an inexpensive indicator to predict the development of hypertension and risk-stratify individuals to aid management in clinical practice.
MeSH term(s)	Humans ; Triglycerides ; Risk Factors ; Glucose ; Retrospective Studies ; Singapore/epidemiology ; Hypertension/diagnosis
Chemical Substances	Triglycerides ; Glucose (IY9XDZ35W2)
Language	English
Publishing date	2023-01-16
Publishing country	Philippines
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2893162-2
ISSN	2308-118X ; 0857-1074
ISSN (online)	2308-118X
ISSN	0857-1074
DOI	10.15605/jafes.038.01.09
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Article: ChatGPT and its Role in the Decision-Making for the Diagnosis and Treatment of Lumbar Spinal Stenosis: A Comparative Analysis and Narrative Review.

Rajjoub, Rami / Arroyave, Juan Sebastian / Zaidat, Bashar / Ahmed, Wasil / Mejia, Mateo Restrepo / Tang, Justin / Kim, Jun S / Cho, Samuel K

Global spine journal

2023 Volume 14, Issue 3, Page(s) 998–1017

Abstract: Study design: Comparative Analysis and Narrative Review.: Objective: To assess and compare ChatGPT's responses to the clinical questions and recommendations proposed by The 2011 North American Spine Society (NASS) Clinical Guideline for the Diagnosis ...

Abstract	Study design: Comparative Analysis and Narrative Review. Objective: To assess and compare ChatGPT's responses to the clinical questions and recommendations proposed by The 2011 North American Spine Society (NASS) Clinical Guideline for the Diagnosis and Treatment of Degenerative Lumbar Spinal Stenosis (LSS). We explore the advantages and disadvantages of ChatGPT's responses through an updated literature review on spinal stenosis. Methods: We prompted ChatGPT with questions from the NASS Evidence-based Clinical Guidelines for LSS and compared its generated responses with the recommendations provided by the guidelines. A review of the literature was performed via PubMed, OVID, and Cochrane on the diagnosis and treatment of lumbar spinal stenosis between January 2012 and April 2023. Results: 14 questions proposed by the NASS guidelines for LSS were uploaded into ChatGPT and directly compared to the responses offered by NASS. Three questions were on the definition and history of LSS, one on diagnostic tests, seven on non-surgical interventions and three on surgical interventions. The review process found 40 articles that were selected for inclusion that helped corroborate or contradict the responses that were generated by ChatGPT. Conclusions: ChatGPT's responses were similar to findings in the current literature on LSS. These results demonstrate the potential for implementing ChatGPT into the spine surgeon's workplace as a means of supporting the decision-making process for LSS diagnosis and treatment. However, our narrative summary only provides a limited literature review and additional research is needed to standardize our findings as means of validating ChatGPT's use in the clinical space.
Language	English
Publishing date	2023-08-10
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2648287-3
ISSN	2192-5690 ; 2192-5682
ISSN (online)	2192-5690
ISSN	2192-5682
DOI	10.1177/21925682231195783
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Can generative artificial intelligence pass the orthopaedic board examination?

Isleem, Ula N / Zaidat, Bashar / Ren, Renee / Geng, Eric A / Burapachaisri, Aonnicha / Tang, Justin E / Kim, Jun S / Cho, Samuel K

Journal of orthopaedics

2023 Volume 53, Page(s) 27–33

Abstract: Background: Resident training programs in the US use the Orthopaedic In-Training Examination (OITE) developed by the American Academy of Orthopaedic Surgeons (AAOS) to assess the current knowledge of their residents and to identify the residents at risk ...

Abstract	Background: Resident training programs in the US use the Orthopaedic In-Training Examination (OITE) developed by the American Academy of Orthopaedic Surgeons (AAOS) to assess the current knowledge of their residents and to identify the residents at risk of failing the Amerian Board of Orthopaedic Surgery (ABOS) examination. Optimal strategies for OITE preparation are constantly being explored. There may be a role for Large Language Models (LLMs) in orthopaedic resident education. ChatGPT, an LLM launched in late 2022 has demonstrated the ability to produce accurate, detailed answers, potentially enabling it to aid in medical education and clinical decision-making. The purpose of this study is to evaluate the performance of ChatGPT on Orthopaedic In-Training Examinations using Self-Assessment Exams from the AAOS database and approved literature as a proxy for the Orthopaedic Board Examination. Methods: 301 SAE questions from the AAOS database and associated AAOS literature were input into ChatGPT's interface in a question and multiple-choice format and the answers were then analyzed to determine which answer choice was selected. A new chat was used for every question. All answers were recorded, categorized, and compared to the answer given by the OITE and SAE exams, noting whether the answer was right or wrong. Results: Of the 301 questions asked, ChatGPT was able to correctly answer 183 (60.8%) of them. The subjects with the highest percentage of correct questions were basic science (81%), oncology (72.7%, shoulder and elbow (71.9%), and sports (71.4%). The questions were further subdivided into 3 groups: those about management, diagnosis, or knowledge recall. There were 86 management questions and 47 were correct (54.7%), 45 diagnosis questions with 32 correct (71.7%), and 168 knowledge recall questions with 102 correct (60.7%). Conclusions: ChatGPT has the potential to provide orthopedic educators and trainees with accurate clinical conclusions for the majority of board-style questions, although its reasoning should be carefully analyzed for accuracy and clinical validity. As such, its usefulness in a clinical educational context is currently limited but rapidly evolving. Clinical relevance: ChatGPT can access a multitude of medical data and may help provide accurate answers to clinical questions.
Language	English
Publishing date	2023-11-05
Publishing country	India
Document type	Journal Article
ZDB-ID	2240839-3
ISSN	0972-978X
ISSN	0972-978X
DOI	10.1016/j.jor.2023.10.026
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Book ; Online: FinEntity

Tang, Yixuan / Yang, Yi / Huang, Allen H / Tam, Andy / Tang, Justin Z

Entity-level Sentiment Classification for Financial Texts

2023

Abstract: In the financial domain, conducting entity-level sentiment analysis is crucial for accurately assessing the sentiment directed toward a specific financial entity. To our knowledge, no publicly available dataset currently exists for this purpose. In this ... ...

Abstract	In the financial domain, conducting entity-level sentiment analysis is crucial for accurately assessing the sentiment directed toward a specific financial entity. To our knowledge, no publicly available dataset currently exists for this purpose. In this work, we introduce an entity-level sentiment classification dataset, called \textbf{FinEntity}, that annotates financial entity spans and their sentiment (positive, neutral, and negative) in financial news. We document the dataset construction process in the paper. Additionally, we benchmark several pre-trained models (BERT, FinBERT, etc.) and ChatGPT on entity-level sentiment classification. In a case study, we demonstrate the practical utility of using FinEntity in monitoring cryptocurrency markets. The data and code of FinEntity is available at \url{https://github.com/yixuantt/FinEntity} Comment: EMNLP'23 Main Conference Short Paper
Keywords	Computer Science - Computation and Language
Subject code	332
Publishing date	2023-10-18
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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