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Journal of Gastroenterology and... Jul 2024LIVERSTAT is an artificial intelligence-based noninvasive test devised to screen for and provide risk stratification for metabolic dysfunction-associated fatty liver...
BACKGROUND AND AIM
LIVERSTAT is an artificial intelligence-based noninvasive test devised to screen for and provide risk stratification for metabolic dysfunction-associated fatty liver disease (MAFLD) by using simple blood biomarkers and anthropometric measurements. We aimed to study LIVERSTAT in patients with MAFLD and to explore its role for the diagnosis of advanced fibrosis.
METHODS
This is a retrospective study of data from MAFLD patients who underwent a liver biopsy. Patients with type 2 diabetes who underwent transient elastography and had liver stiffness measurement (LSM) < 5 kPa were included as patients with no fibrosis. Among these patients, controlled attenuation parameter <248 dB/m was considered as no steatosis. The LIVERSTAT results were generated based on a proprietary algorithm, blinded to the histological and LSM data.
RESULTS
The data for 350 patients were analyzed (mean age 53 years, 45% male, advanced fibrosis 22%). The sensitivity, specificity, positive predictive value, negative predictive value, and misclassification rate of LIVERSTAT to diagnose advanced fibrosis were 90%, 50%, 30%, 95%, and 42%, respectively. The corresponding rates for Fibrosis-4 score (FIB4) were 56%, 83%, 44%, 89%, and 22%, respectively. When LSM was used as a second test, the corresponding rates for LIVERSTAT were 60%, 97%, 76%, 94%, and 8%, respectively, while the corresponding rates for FIB4 were 38%, 99%, 83%, 89%, and 11%, respectively.
CONCLUSION
LIVERSTAT had a higher negative predictive value compared with FIB4 and a lower misclassification rate compared with FIB4 when used in a two-step approach in combination with LSM for the diagnosis of advanced fibrosis.
PubMed: 38946405
DOI: 10.1111/jgh.16675 -
Pest Management Science Jul 2024The Red Imported Fire Ant (RIFA), scientifically known as Solenopsis invicta, is a destructive invasive species causing considerable harm to ecosystems and generating...
BACKGROUND
The Red Imported Fire Ant (RIFA), scientifically known as Solenopsis invicta, is a destructive invasive species causing considerable harm to ecosystems and generating substantial economic costs globally. Traditional methods for RIFA nests detection are labor-intensive and may not be scalable to larger field areas. This study aimed to develop an innovative surveillance system that leverages artificial intelligence (AI) and robotic dogs to automate the detection and geolocation of RIFA nests, thereby improving monitoring and control strategies.
RESULTS
The designed surveillance system, through integrating the CyberDog robotic platform with a YOLOX AI model, demonstrated RIFA nest detection precision rates of >90%. The YOLOX model was trained on a dataset containing 1118 images and achieved a final precision rate of 0.95, with an inference time of 20.16 ms per image, indicating real-time operational suitability. Field tests revealed that the CyberDog system identified three times more nests than trained human inspectors, with significantly lower rates of missed detections and false positives.
CONCLUSION
The findings underscore the potential of AI-driven robotic systems in advancing pest management. The CyberDog/YOLOX system not only matched human inspectors in speed, but also exceeded them in accuracy and efficiency. This study's results are significant as they highlight how technology can be harnessed to address biological invasions, offering a more effective, ecologically friendly, and scalable solution for RIFA detection. The successful implementation of this system could pave the way for broader applications in environmental monitoring and pest control, ultimately contributing to the preservation of biodiversity and economic stability. © 2024 Society of Chemical Industry.
PubMed: 38946320
DOI: 10.1002/ps.8254 -
Gynecological Endocrinology : the... Dec 2024Normal reproductive function requires adequate regulation of follicle stimulating hormone (FSH) and luteinizing hormone (LH) secretion. During ovarian stimulation for...
Normal reproductive function requires adequate regulation of follicle stimulating hormone (FSH) and luteinizing hormone (LH) secretion. During ovarian stimulation for in-vitro fertilization (IVF), some patients will demonstrate an early rise in LH despite being treated with a gonadotropin releasing-hormone (GnRH) antagonist, sometimes necessitating cycle cancellation. Previous studies have demonstrated a possible link between a premature LH rise with ovarian response to gonadotropins. We sought to determine what clinical parameters can predict this premature LH rise and their relative contribution. A retrospective study of 382 patients who underwent IVF treatment at Rambam Medical Center. The patients were stratified into age groups. A model predicting premature LH rise based on clinical and demographic parameters was developed using both multiple linear regression and a machine-learning-based algorithm. LH rise was defined as the difference between pre-trigger and basal LH levels. The clinical parameters that significantly predicted an LH rise were patient age, BMI, LH levels at stimulation outset, LH levels on day of antagonist administration, and total number of stimulation days. Importantly, when analyzing the data of specific age groups, the model's prediction was strongest in young patients (age 25-30 years, = 0.88, < .001) and weakest in older patients (age > 41 years, = 0.23, = .003). Using both multiple linear regression and a machine-learning-based algorithm of patient data from IVF cycles, we were able to predict patients at risk for premature LH rise and/or LH surge. Utilizing this model may help prevent IVF cycle cancellation and better timing of ovulation triggering.
Topics: Humans; Female; Ovulation Induction; Fertilization in Vitro; Adult; Luteinizing Hormone; Retrospective Studies; Gonadotropin-Releasing Hormone; Machine Learning; Age Factors
PubMed: 38946245
DOI: 10.1080/09513590.2024.2365913 -
Biophysical Journal Jun 2024Raf kinases play key roles in signal transduction in cells for regulating proliferation, differentiation, and survival. Despite decades of research into functions and...
Raf kinases play key roles in signal transduction in cells for regulating proliferation, differentiation, and survival. Despite decades of research into functions and dynamics of Raf kinases with respect to other cytosolic proteins, understanding Raf kinases is limited by the lack of their full-length structures at the atomic resolution. Here, we present the first model of the full-length CRaf kinase obtained from Artificial Intelligence/Machine Learning (AI/ML) algorithms with a converging ensemble of structures simulated by large-scale temperature replica exchange simulations. Our model is validated by comparing simulated structures with the latest Cryo-EM structure detailing close contacts among three key domains and regions of the CRaf. Our simulations reveal potentially new epitopes of intra-molecule interactions within the CRaf and reveal a dynamical nature of CRaf kinases, in which the three domains can move back and forth relative to each other for regulatory dynamics. The dynamical conformations are then used in a docking algorithm to shed insight into the paradoxical effect caused by Vemurafenib in comparison with a paradox breaker PLX7904. We propose a model of Raf-heterodimer/KRas-dimer as a signalosome based on the dynamics of the full-length CRaf.
PubMed: 38946141
DOI: 10.1016/j.bpj.2024.06.028 -
Magnetic Resonance in Chemistry : MRC Jun 2024The defect models of the orthorhombical and tetragonal Cu centers in Pb[ZrTi]O are attributed to Cu ions occupying the sixfold coordinated octahedral Ti site with and...
The defect models of the orthorhombical and tetragonal Cu centers in Pb[ZrTi]O are attributed to Cu ions occupying the sixfold coordinated octahedral Ti site with and without charge compensation, respectively. The electron paramagnetic resonance (EPR) g factors g (i = x, y, z) of the Cu centers in Pb[ZrTi]O are theoretically studied by using the perturbation formulas of a 3d ion under orthorhombically and tetragonally elongated octahedra. Based on the calculation, the impurity off-center displacements are about 0.253 and 0.162 Å for the orthorhombical and tetragonal Cu centers, respectively. Meanwhile, the planar Cu-O bonds are found to experience the relative variation ΔR (≈0.102 Å) along the a- and b-axes for the orthorhombical Cu center due to the Jahn-Teller (JT) effect. The theoretical EPR g factors based on the above local structures agree well with the observed values.
PubMed: 38946056
DOI: 10.1002/mrc.5472 -
European Radiology Experimental Jul 2024Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high... (Review)
Review
Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in artificial intelligence (AI) and robot-assisted neurosurgery. The potential of submillimetre fMRI mapping can help better appreciate uncertainty on resection margins, though geometric distortions at UHF might lessen the accuracy of fMRI maps. A useful trade-off for UHF fMRI is to collect data with 1-mm isotropic resolution to ensure high sensitivity and subsequently a low risk of false negatives. Scanning at UHF might yield a revival interest in slow event-related fMRI, thereby offering a richer depiction of the dynamics of fMRI responses. The potential applications of AI concern denoising and artefact removal, generation of super-resolution fMRI maps, and accurate fusion or coregistration between anatomical and fMRI maps. The latter can benefit from the use of T1-weighted echo-planar imaging for better visualization of brain activations. Such AI-augmented fMRI maps would provide high-quality input data to robotic surgery systems, thereby improving the accuracy and reliability of robot-assisted neurosurgery. Ultimately, the advancement in fMRI at UHF would promote clinically useful synergies between fMRI, AI, and robotic neurosurgery.Relevance statement This review highlights the potential synergies between fMRI at UHF, AI, and robotic neurosurgery in improving the accuracy and reliability of fMRI-based presurgical mapping.Key points• Presurgical fMRI mapping at UHF improves spatial resolution and sensitivity.• Slow event-related designs offer a richer depiction of fMRI responses dynamics.• AI can support denoising, artefact removal, and generation of super-resolution fMRI maps.• AI-augmented fMRI maps can provide high-quality input data to robotic surgery systems.
Topics: Humans; Magnetic Resonance Imaging; Artificial Intelligence; Robotic Surgical Procedures; Brain Mapping; Neurosurgical Procedures; Magnetic Fields; Preoperative Care; Brain Neoplasms
PubMed: 38945979
DOI: 10.1186/s41747-024-00472-y -
Magnetic Resonance in Medical Sciences... 2024This special issue of Magnetic Resonance in Medical Sciences is dedicated to "Advanced Techniques for MR Neuroimaging," featuring nine review articles authored by...
This special issue of Magnetic Resonance in Medical Sciences is dedicated to "Advanced Techniques for MR Neuroimaging," featuring nine review articles authored by leading experts. The reviews cover advancements in reproducible research practices, diffusion tensor imaging along the perivascular space, myelin imaging using magnetic susceptibility source separation, spinal cord quantitative MRI analysis, tractometry of visual white matter pathways, deep learning-based image enhancement, arterial spin labeling, the potential of radiomics, and MRI-based quantification of brain oxygen metabolism. These articles provide a comprehensive update on cutting-edge technologies and their applications in clinical and research settings, highlighting their impact on improving diagnostic accuracy and understanding of neurological disorders.
Topics: Humans; Neuroimaging; Magnetic Resonance Imaging; Brain; Diffusion Tensor Imaging; Image Processing, Computer-Assisted; Nervous System Diseases; Deep Learning
PubMed: 38945942
DOI: 10.2463/mrms.e.2024-1000 -
The Journal of Prosthetic Dentistry Jun 2024Artificial intelligence has been used to enhance the digitalized workflow, especially when undergoing complex oral rehabilitations. However, the reliability of real-time...
STATEMENT OF PROBLEM
Artificial intelligence has been used to enhance the digitalized workflow, especially when undergoing complex oral rehabilitations. However, the reliability of real-time jaw motion registration devices is unclear, and no standard measurement method of the sagittal condylar inclination (SCI) and Bennett angle (BA) has been established.
PURPOSE
The purpose of this clinical study was to compare and evaluate the reliability of the SCI and BA values recorded by using 2 different digital devices.
MATERIAL AND METHODS
A total of 17 participants, aged between 20 and 30 years (10 women and 7 men) were included in the study. For each participant, the Cadiax Compact 2 and MODJAW tracking devices were used to measure the SCI and BA values at 3 mm and 5 mm of condylar displacement during 3 separate recording sessions. The intraclass correlation coefficient (ICC) was used to assess the reliability of the recordings. Comparisons between the devices were performed with the Wilcoxson rank-sum test (α=.05). The Bland-Altman plot was used to evaluate the quantitative agreement between the 2 devices.
RESULTS
All ICC intrarater reliability values for Cadiax and MODJAW were higher than 0.90. Both at 3 and 5 mm, the SCI measurements were higher for MODJAW registrations than for those recorded by Cadiax. The Bland-Altman plot showed that the SCI values were higher for MODJAW than for Cadiax by 5.9 (95% CI 3.9 to 8.2) and that the BA differences between the MODJAW and the Cadiax were not consistent with the measured value.
CONCLUSIONS
Excellent reliability was found with the MODJAW and Cadiax recordings. The SCI and BA values for MODJAW measurements were higher at 3 mm and 5 mm than those acquired with Cadiax. MODJAW showed higher values than Cadiax, and the discrepancies were more pronounced for 3 mm than for 5 mm of condylar displacement, highlighting the need for precision in measurements at lower ranges of motion.
PubMed: 38945794
DOI: 10.1016/j.prosdent.2024.05.014 -
European Journal of Surgical Oncology :... Jun 2024
PubMed: 38945784
DOI: 10.1016/j.ejso.2024.108492 -
Otolaryngologic Clinics of North America Jun 2024
PubMed: 38945727
DOI: 10.1016/j.otc.2024.06.001