BMC biomedical engineering最新文献

{"title":"The effect of using the hip exoskeleton assistive (HEXA) robot compared to conventional physiotherapy on clinical functional outcomes in stroke patients with hemiplegia: a pilot randomized controlled trial.","authors":"Hamed Mamipour, Seyed Ali Hoseini, Hossein Negahban, Ali Moradi, Amir Hojjati, Fariborz Rezaeitalab, Mohammadreza Torshizian, Arefeh Mehrali, Mohammad Parsa, Iman Kardan, Hamed Tabesh, Ebrahim Ghayem Hassankhani, Alireza Akbarzadeh","doi":"10.1186/s42490-024-00082-0","DOIUrl":"10.1186/s42490-024-00082-0","url":null,"abstract":"<p><strong>Trial design: </strong>This study is a pilot randomized clinical trial aimed to investigate the effect of using Hip Exoskeleton Assistive (HEXA) robot compared to conventional physiotherapy on the quality of walking, disability, and quality of life of stroke patients with hemiplegia.</p><p><strong>Methods: </strong>In this study, 24 patients were randomly assigned to the intervention group (robotic physiotherapy with HEXA robot), or control group (conventional physiotherapy). In each session, both groups received 30 min of conventional physiotherapy including electrotherapy and conventional exercises, and then the intervention group did gait training for 30 min with the HEXA robot and the control group for 30 min without the HEXA robot. The treatment program was 12 sessions, 3 times a week. Before the 1st and after the 12th sessions, both groups were evaluated for walking quality, disability, and quality of life.</p><p><strong>Results: </strong>The results showed that the main effect of time was significant (P < 0.05) in all outcomes and patients in both groups achieved significant improvement in all outcomes after the intervention. The main effect of the group was also significant in the outcomes of 6MWT (P < 0.05) and TUG (P < 0.05), and the intervention group patients experienced more distance and speed in these two tests. This study was approved by the ethics committee of Mashhad University of Medical Sciences (IR.MUMS.FHMPM.REC.1400.079 dated 28th Jan 2022). The trial was registered with the clinical trials site of www.IRCT.ir (IRCT20210730052024N1) on January 28th 2022.</p><p><strong>Conclusion: </strong>It seems that the HEXA robot can effectively improve walking capacity and speed.</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"6 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11293188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141861797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-term epileptic seizures prediction based on cepstrum analysis and signal morphology.","authors":"Bahar Tajadini, Saeid R Seydnejad, Soheila Rezakhani","doi":"10.1186/s42490-024-00081-1","DOIUrl":"10.1186/s42490-024-00081-1","url":null,"abstract":"<p><p>This article aims to provide and implement a patient-specific seizure (for Intervention Time (IT) detection) prediction algorithm using non-invasive data to develop warning devices to prevent further patient injury and reduce stress. Employing algorithms with high initial data volume and computations time to increase the accuracy is an important problem in prediction issues. Consequently, reduction of calculations is met by applying only two effective EEG signal channels without manual removal of artifacts by visual inspection as the algorithm's input. Autoregression (AR) modeling and Cepstrum detect changes due to IT period. We carry out the goal of higher accuracy by increasing sensitivity to interictal epileptiform discharges or artifacts and reduce errors caused by them, taking advantage of the discrete wavelet transform and the comparison of two channels epochs by applying the median filter. Averaging and positive envelope methods are introduced to patient-specific thresholds become more differentiated as soon as possible and can be lead to sooner prediction. We examined this method on a mathematical model of adult epilepsy as well as on 10 patients with EEG data. The results of our experiments confirm that performance of the proposed approach in accuracy and average false prediction rate is superior to other algorithms. Simulation results have been shown the robustness of our proposed method to artifacts and errors, which is a step towards the development of real-time alarm devices by non-invasive techniques.</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"6 1","pages":"6"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11215831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141473130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A handheld device for intra-cavity and ex vivo fluorescence imaging of breast conserving surgery margins with 5-aminolevulinic acid.","authors":"Christopher Gibson, Shirley C Wang, Arcturus Phoon, Nayana Thalanki Anantha, Kathryn Ottolino-Perry, Stephen Petropoulos, Zuha Qureshi, Vasanth Subramanian, Anam Shahid, Cristiana O'Brien, Steven Carcone, Suzanne Chung, Teresa Tsui, Viktor Son, Mayleen Sukhram, Fannong Meng, Susan J Done, Alexandra M Easson, Tulin Cil, Michael Reedijk, Wey L Leong, Ralph S DaCosta","doi":"10.1186/s42490-024-00079-9","DOIUrl":"10.1186/s42490-024-00079-9","url":null,"abstract":"<p><strong>Background: </strong>Visualization of cancer during breast conserving surgery (BCS) remains challenging; the BCS reoperation rate is reported to be 20-70% of patients. An urgent clinical need exists for real-time intraoperative visualization of breast carcinomas during BCS. We previously demonstrated the ability of a prototype imaging device to identify breast carcinoma in excised surgical specimens following 5-aminolevulinic acid (5-ALA) administration. However, this prototype device was not designed to image the surgical cavity for remaining carcinoma after the excised lumpectomy specimen is removed. A new handheld fluorescence (FL) imaging prototype device, designed to image both excised specimens and within the surgical cavity, was assessed in a clinical trial to evaluate its clinical utility for first-in-human, real-time intraoperative imaging during index BCS.</p><p><strong>Results: </strong>The imaging device combines consumer-grade imaging sensory technology with miniature light-emitting diodes (LEDs) and multiband optical filtering to capture high-resolution white light (WL) and FL digital images and videos. The technology allows for visualization of protoporphyrin IX (PpIX), which fluoresces red when excited by violet-blue light. To date, <math><mrow><mi>n</mi> <mo>=</mo> <mn>17</mn></mrow> </math> patients have received <math><mrow><mn>20</mn> <mfrac><mtext>mg</mtext> <mtext>kg</mtext></mfrac> </mrow> </math> bodyweight (BW) 5-ALA orally 2-4 h before imaging to facilitate the accumulation of PpIX within tumour cells. Tissue types were identified based on their colour appearance. Breast tumours in sectioned lumpectomies appeared red, which contrasted against the green connective tissues and orange-brown adipose tissues. In addition, ductal carcinoma in situ (DCIS) that was missed during intraoperative standard of care was identified at the surgical margin at <1 mm depth. In addition, artifacts due to the surgical drape, illumination, and blood within the surgical cavity were discovered.</p><p><strong>Conclusions: </strong>This study has demonstrated the detection of a grossly occult positive margin intraoperatively. Artifacts from imaging within the surgical cavity have been identified, and potential mitigations have been proposed.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov Identifier: NCT01837225 (Trial start date is September 2010. It was registered to ClinicalTrials.gov retrospectively on April 23, 2013, then later updated on April 9, 2020, to reflect the introduction of the new imaging device.).</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"6 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11143723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141186915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the role of generative artificial intelligence in the development of brain-computer interfaces","authors":"Seif Eldawlatly","doi":"10.1186/s42490-024-00080-2","DOIUrl":"https://doi.org/10.1186/s42490-024-00080-2","url":null,"abstract":"Since their inception more than 50 years ago, Brain-Computer Interfaces (BCIs) have held promise to compensate for functions lost by people with disabilities through allowing direct communication between the brain and external devices. While research throughout the past decades has demonstrated the feasibility of BCI to act as a successful assistive technology, the widespread use of BCI outside the lab is still beyond reach. This can be attributed to a number of challenges that need to be addressed for BCI to be of practical use including limited data availability, limited temporal and spatial resolutions of brain signals recorded non-invasively and inter-subject variability. In addition, for a very long time, BCI development has been mainly confined to specific simple brain patterns, while developing other BCI applications relying on complex brain patterns has been proven infeasible. Generative Artificial Intelligence (GAI) has recently emerged as an artificial intelligence domain in which trained models can be used to generate new data with properties resembling that of available data. Given the enhancements observed in other domains that possess similar challenges to BCI development, GAI has been recently employed in a multitude of BCI development applications to generate synthetic brain activity; thereby, augmenting the recorded brain activity. Here, a brief review of the recent adoption of GAI techniques to overcome the aforementioned BCI challenges is provided demonstrating the enhancements achieved using GAI techniques in augmenting limited EEG data, enhancing the spatiotemporal resolution of recorded EEG data, enhancing cross-subject performance of BCI systems and implementing end-to-end BCI applications. GAI could represent the means by which BCI would be transformed into a prevalent assistive technology, thereby improving the quality of life of people with disabilities, and helping in adopting BCI as an emerging human-computer interaction technology for general use.","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"170 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140828368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An optimized CT-dense agent perfusion and micro-CT imaging protocol for chick embryo developmental stages","authors":"Azza Naïja, O. Mutlu, Talha Khan, Thomas Daniel Seers, Huseyin C Yalcin","doi":"10.1186/s42490-024-00078-w","DOIUrl":"https://doi.org/10.1186/s42490-024-00078-w","url":null,"abstract":"","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"37 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140667357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Needle artifact reduction during interventional CT procedures using a silver filter","authors":"Carlos A. Reynoso-Mejia, Jonathan Troville, Martin G. Wagner, Bernice Hoppel, Fred T. Lee, Timothy P. Szczykutowicz","doi":"10.1186/s42490-024-00076-y","DOIUrl":"https://doi.org/10.1186/s42490-024-00076-y","url":null,"abstract":"MAR algorithms have not been productized in interventional imaging because they are too time-consuming. Application of a beam hardening filter can mitigate metal artifacts and doesn’t increase computational burden. We evaluate the ability to reduce metal artifacts of a 0.5 mm silver (Ag) additional filter in a Multidetector Computed Tomography (MDCT) scanner during CT-guided biopsy procedures. A biopsy needle was positioned inside the lung field of an anthropomorphic phantom (Lungman, Kyoto Kagaku, Kyoto, Japan). CT acquisitions were performed with beam energies of 100 kV, 120 kV, 135 kV, and 120 kV with the Ag filter and reconstructed using a filtered back projection algorithm. For each measurement, the CTDIvol was kept constant at 1 mGy. Quantitative profiles placed in three regions of the artifact (needle, needle tip, and trajectory artifacts) were used to obtain metrics (FWHM, FWTM, width at − 100 HU, and absolute error in HU) to evaluate the blooming artifact, artifact width, change in CT number, and artifact range. An image quality analysis was carried out through image noise measurement. A one-way analysis of variance (ANOVA) test was used to find significant differences between the conventional CT beam energies and the Ag filtered 120 kV beam. The 120 kV-Ag is shown to have the shortest range of artifacts compared to the other beam energies. For needle tip and trajectory artifacts, a significant reduction of − 53.6% (p < 0.001) and − 48.7% (p < 0.001) in the drop of the CT number was found, respectively, in comparison with the reference beam of 120 kV as well as a significant decrease of up to − 34.7% in the artifact width (width at − 100 HU, p < 0.001). Also, a significant reduction in the blooming artifact of − 14.2% (FWHM, p < 0.001) and − 53.3% (FWTM, p < 0.001) was found in the needle artifact. No significant changes (p > 0.05) in image noise between the conventional energies and the 120 kV-Ag were found. A 0.5 mm Ag additional MDCT filter demonstrated consistent metal artifact reduction generated by the biopsy needle. This reduction may lead to a better depiction of the target and surrounding structures while maintaining image quality.","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140099240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of the synergistic effect of antimicrobial peptides and antimicrobial agents via supervised machine learning","authors":"Basak Olcay, Gizem D. Ozdemir, Mehmet A. Ozdemir, Utku K. Ercan, Onan Guren, Ozan Karaman","doi":"10.1186/s42490-024-00075-z","DOIUrl":"https://doi.org/10.1186/s42490-024-00075-z","url":null,"abstract":"Infectious diseases not only cause severe health problems but also burden the healthcare system. Therefore, the effective treatment of those diseases is crucial. Both conventional approaches, such as antimicrobial agents, and novel approaches, like antimicrobial peptides (AMPs), are used to treat infections. However, due to the drawbacks of current approaches, new solutions are still being investigated. One recent approach is the use of AMPs and antimicrobial agents in combination, but determining synergism is with a huge variety of AMPs time-consuming and requires multiple experimental studies. Machine learning (ML) algorithms are widely used to predict biological outcomes, particularly in the field of AMPs, but no previous research reported on predicting the synergistic effects of AMPs and antimicrobial agents. Several supervised ML models were implemented to accurately predict the synergistic effect of AMPs and antimicrobial agents. The results demonstrated that the hyperparameter-optimized Light Gradient Boosted Machine Classifier (oLGBMC) yielded the best test accuracy of 76.92% for predicting the synergistic effect. Besides, the feature importance analysis reveals that the target microbial species, the minimum inhibitory concentrations (MICs) of the AMP and the antimicrobial agents, and the used antimicrobial agent were the most important features for the prediction of synergistic effect, which aligns with recent experimental studies in the literature. This study reveals that ML algorithms can predict the synergistic activity of two different antimicrobial agents without the need for complex and time-consuming experimental procedures. The implications support that the ML models may not only reduce the experimental cost but also provide validation of experimental procedures.","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139483221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A pressure monitoring approach for pressure ulcer prevention.","authors":"Bethel Osuagwu, Euan McCaughey, Mariel Purcell","doi":"10.1186/s42490-023-00074-6","DOIUrl":"10.1186/s42490-023-00074-6","url":null,"abstract":"<p><strong>Background: </strong>A pressure ulcer (PU) is a debilitating condition that disproportionately affects people with impaired mobility. PUs facilitate tissue damage due to prolonged unrelieved pressure, degrading quality of life with a considerable socio-economic impact. While rapid treatment is crucial, an effective  prevention strategy may help avoid the development of PUs altogether. While pressure monitoring is currently used in PU prevention, available monitoring approaches are not formalised and do not appropriately account for accumulation and relief of the effect of an applied pressure over a prolonged duration. The aim of this study was to define an approach that incorporates the accumulation and relief of an applied load to enable continuous pressure monitoring.</p><p><strong>Results: </strong>A tunable continuous pressure magnitude and duration monitoring approach that can account for accumulated damaging effect of an applied pressure and pressure relief over a prolonged period is proposed. Unlike classic pressure monitoring approaches, the presented method provides ongoing indication of the net impact of a load during and after loading.</p><p><strong>Conclusions: </strong>The tunable continuous pressure magnitude and duration monitoring approach proposed here may further development towards formalised pressure monitoring approaches that aim to provide information on the risk of PU formation in real-time.</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"5 1","pages":"8"},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9986790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel wearable device for automated real-time detection of epileptic seizures.","authors":"Mikael Habtamu,&nbsp;Keneni Tolosa,&nbsp;Kidus Abera,&nbsp;Lamesgin Demissie,&nbsp;Samrawit Samuel,&nbsp;Yeabsera Temesgen,&nbsp;Elbetel Taye Zewde,&nbsp;Ahmed Ali Dawud","doi":"10.1186/s42490-023-00073-7","DOIUrl":"https://doi.org/10.1186/s42490-023-00073-7","url":null,"abstract":"<p><strong>Background: </strong>Epilepsy is a neurological disorder that has a variety of origins. It is caused by hyperexcitability and an imbalance between excitation and inhibition, which results in seizures. The World Health Organization (WHO) and its partners have classified epilepsy as a major public health concern. Over 50 million individuals globally are affected by epilepsy which shows that the patient's family, social, educational, and vocational activities are severely limited if seizures are not controlled. Patients who suffer from epileptic seizures have emotional, behavioral, and neurological issues. Alerting systems using a wearable sensor are commonly used to detect epileptic seizures. However, most of the devices have no multimodal systems that increase sensitivity and lower the false discovery rate for screening and intervention of epileptic seizures. Therefore, the objective of this project was, to design and develop an efficient, economical, and automatically detecting epileptic seizure device in real-time.</p><p><strong>Methods: </strong>Our design incorporates different sensors to assess the patient's condition such as an accelerometer, pulsoxymeter and vibration sensor which process body movement, heart rate variability, oxygen denaturation, and jerky movement respectively. The algorithm for real-time detection of epileptic seizures is based on the following: acceleration increases to a higher value of 23.4 m/s² or decreases to a lower value of 10 m/s² as energy is absorbed by the body, the heart rate increases by 10 bpm from the normal heart rate, oxygen denaturation is below 90% and vibration should be out of the range of 3 Hz -17 Hz. Then, a pulsoxymeter device was used as a gold standard to compare the heart rate variability and oxygen saturation sensor readings. The accuracy of the accelerometer and vibration sensor was also tested by a fast-moving and vibrating normal person's hand.</p><p><strong>Results: </strong>The prototype was built and subjected to different tests and iterations. The proposed device was tested for accuracy, cost-effectiveness and ease of use. An acceptable accuracy was achieved for the accelerometer, pulsoxymeter, and vibration sensor measurements, and the prototype was built only with a component cost of less than 40 USD excluding design, manufacturing, and other costs. The design is tested to see if it fits the design criteria; the results of the tests reveal that a large portion of the scientific procedures utilized in this study to identify epileptic seizures is effective.</p><p><strong>Conclusion: </strong>This project is objectively targeted to design a medical device with multimodal systems that enable us to accurately detect epileptic seizures by detecting symptoms commonly associated with an episode of epileptic seizure and notifying a caregiver for immediate assistance. The proposed device has a great impact on reducing epileptic seizer mortality, especially in lo","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"5 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10353099/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9839295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assistive technology: opportunities for societal inclusion of persons with disabilities and independence of the elderly.","authors":"Aliaa Rehan Youssef,&nbsp;Ahmed Morsy","doi":"10.1186/s42490-023-00072-8","DOIUrl":"https://doi.org/10.1186/s42490-023-00072-8","url":null,"abstract":"<p><p>Assistive technology (AT) development worldwide aims to enhance the quality of life for persons with disabilities and elderly, yet its development and commercialization may face challenges. This collection aims at obtaining a better understanding of the hurdles that various stakeholders may face in the successful development and commercialization of AT.</p>","PeriodicalId":72425,"journal":{"name":"BMC biomedical engineering","volume":"5 1","pages":"6"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10316604/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10127429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}