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Progress in Orthodontics Jun 2024Determining the right time for orthodontic treatment is one of the most important factors affecting the treatment plan and its outcome. The aim of this study is to...
INTRODUCTION
Determining the right time for orthodontic treatment is one of the most important factors affecting the treatment plan and its outcome. The aim of this study is to estimate the mandibular growth stage based on cervical vertebral maturation (CVM) in lateral cephalometric radiographs using artificial intelligence. Unlike previous studies, which use conventional CVM stage naming, our proposed method directly correlates cervical vertebrae with mandibular growth slope.
METHODS AND MATERIALS
To conduct this study, first, information of people achieved in American Association of Orthodontics Foundation (AAOF) growth centers was assessed and after considering the entry and exit criteria, a total of 200 people, 108 women and 92 men, were included in the study. Then, the length of the mandible in the lateral cephalometric radiographs that were taken serially from the patients was calculated. The corresponding graphs were labeled based on the growth rate of the mandible in 3 stages; before the growth peak of puberty (pre-pubertal), during the growth peak of puberty (pubertal) and after the growth peak of puberty (post-pubertal). A total of 663 images were selected for evaluation using artificial intelligence. These images were evaluated with different deep learning-based artificial intelligence models considering the diagnostic measures of sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). We also employed weighted kappa statistics.
RESULTS
In the diagnosis of pre-pubertal stage, the convolutional neural network (CNN) designed for this study has the higher sensitivity and NPV (0.84, 0.91 respectively) compared to ResNet-18 model. The ResNet-18 model had better performance in other diagnostic measures of the pre-pubertal stage and all measures in the pubertal and post-pubertal stages. The highest overall diagnostic accuracy was also obtained using ResNet-18 model with the amount of 87.5% compared to 81% in designed CNN.
CONCLUSION
The artificial intelligence model trained in this study can receive images of cervical vertebrae and predict mandibular growth status by classifying it into one of three groups; before the growth spurt (pre-pubertal), during the growth spurt (pubertal), and after the growth spurt (post-pubertal). The highest accuracy is in post-pubertal stage with the designed networks.
Topics: Humans; Cephalometry; Mandible; Male; Female; Cervical Vertebrae; Artificial Intelligence; Child; Adolescent; Puberty; Deep Learning
PubMed: 38910180
DOI: 10.1186/s40510-024-00527-1 -
BMC Medical Research Methodology Jun 2024Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or...
BACKGROUND
Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or intervention. We propose a highly available method which enables synthetic data generation from real patient records in a privacy preserving and compliant fashion, is interpretable and allows for expert intervention.
METHODS
Our approach ties together two established tools in medical informatics, namely OMOP as a data standard for electronic health records and Synthea as a data synthetization method. For this study, data pipelines were built which extract data from OMOP, convert them into time series format, learn temporal rules by 2 statistical algorithms (Markov chain, TARM) and 3 algorithms of causal discovery (DYNOTEARS, J-PCMCI+, LiNGAM) and map the outputs into Synthea graphs. The graphs are evaluated quantitatively by their individual and relative complexity and qualitatively by medical experts.
RESULTS
The algorithms were found to learn qualitatively and quantitatively different graph representations. Whereas the Markov chain results in extremely large graphs, TARM, DYNOTEARS, and J-PCMCI+ were found to reduce the data dimension during learning. The MultiGroupDirect LiNGAM algorithm was found to not be applicable to the problem statement at hand.
CONCLUSION
Only TARM and DYNOTEARS are practical algorithms for real-world data in this use case. As causal discovery is a method to debias purely statistical relationships, the gradient-based causal discovery algorithm DYNOTEARS was found to be most suitable.
Topics: Humans; Algorithms; Electronic Health Records; Markov Chains; Medical Informatics
PubMed: 38909216
DOI: 10.1186/s12874-024-02257-8 -
Cardiovascular Diabetology Jun 2024Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For... (Comparative Study)
Comparative Study
BACKGROUND
Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as well as anthropometric features. However, there is still no agreement on the most suitable one for predicting CAD.
METHODS
We followed a cohort of 2,000 individuals, ranging in age from 20 to 74, for a duration of 9.9 years. We utilized multivariate Cox proportional hazard models to investigate the association between TyG-index, TyG-BMI, TyG-WC, TG/HDL, plus METS-IR and the occurrence of CAD. The receiver operating curve (ROC) was employed to compare the predictive efficacy of these indices and their corresponding cutoff values for predicting CAD. We also used three distinct embedded feature selection methods: LASSO, Random Forest feature selection, and the Boruta algorithm, to evaluate and compare surrogate markers of insulin resistance in predicting CAD. In addition, we utilized the ceteris paribus profile on the Random Forest model to illustrate how the model's predictive performance is affected by variations in individual surrogate markers, while keeping all other factors consistent in a diagram.
RESULTS
The TyG-index was the only surrogate marker of insulin resistance that demonstrated an association with CAD in fully adjusted model (HR: 2.54, CI: 1.34-4.81). The association was more prominent in females. Moreover, it demonstrated the highest area under the ROC curve (0.67 [0.63-0.7]) in comparison to other surrogate indices for insulin resistance. All feature selection approaches concur that the TyG-index is the most reliable surrogate insulin resistance marker for predicting CAD. Based on the Ceteris paribus profile of Random Forest the predictive ability of the TyG-index increased steadily after 9 with a positive slope, without any decline or leveling off.
CONCLUSION
Due to the simplicity of assessing the TyG-index with routine biochemical assays and given that the TyG-index was the most effective surrogate insulin resistance index for predicting CAD based on our results, it seems suitable for inclusion in future CAD prevention strategies.
Topics: Humans; Insulin Resistance; Coronary Artery Disease; Female; Male; Middle Aged; Predictive Value of Tests; Biomarkers; Machine Learning; Aged; Risk Assessment; Adult; Prognosis; Young Adult; Risk Factors; Time Factors; Insulin; Blood Glucose
PubMed: 38907271
DOI: 10.1186/s12933-024-02306-y -
BMC Anesthesiology Jun 2024We used transcatheter aortic valve implantation (TAVI) procedure time to investigate the association between surgical team maturity and outcome.
BACKGROUND
We used transcatheter aortic valve implantation (TAVI) procedure time to investigate the association between surgical team maturity and outcome.
METHODS
Among patients who underwent TAVI between October 2015 and November 2019, those who had Sapien™ implanted with the transfemoral artery approach were included in the analysis. We used TAVI procedure time and surgery number to draw a learning curve. Then, we divided the patients into two groups before and after the number of cases where the sigmoid curve reaches a plateau. We compared the two groups regarding the surveyed factors and investigated the correlation between the TAVI procedure time and survey factors.
RESULTS
Ninety-nine of 149 patients were analysed. The sigmoid curve had an inflection point in 23.2 cases and reached a plateau in 43.0 cases. Patients in the Late group had a shorter operating time, less contrast media, less radiation exposure, and less myocardial escape enzymes than the Early group. Surgical procedure time showed the strongest correlation with the surgical case number.
CONCLUSION
The number of cases required for surgeon proficiency for isolated Sapien™ valve implantation was 43. This number may serve as a guideline for switching the anesthesia management of TAVI from general to local anesthesia.
Topics: Humans; Transcatheter Aortic Valve Replacement; Retrospective Studies; Male; Female; Aged, 80 and over; Operative Time; Aged; Learning Curve; Clinical Competence; Treatment Outcome; Aortic Valve Stenosis
PubMed: 38907200
DOI: 10.1186/s12871-024-02594-7 -
Acta Psychologica Jun 2024As various contextual and individual difference factors determine how and when mindsets may influence learning outcomes, burgeoning L2 research has recently addressed...
As various contextual and individual difference factors determine how and when mindsets may influence learning outcomes, burgeoning L2 research has recently addressed the role of growth language mindset (GLM) in different learning outcomes such as L2 Willingness to Communicate (WTC). Since little is known about the underlying mechanism through which GLM may contribute to WTC, a highly desirable goal of L2 education and an important criterion for assessing its efficiency and success, the present study addresses this gap by investigating the possible mediating and moderating roles of linguistic risk taking and L2 learning experience, respectively. The participants were 392 Iranian L2 students chosen by multi-stage cluster sampling. Findings showed that GLM predicted WTC directly and positively, and their association was mediated and moderated by linguistic risk taking (an important affective factor) and L2 learning experience (an essential motivational factor), respectively. Suggestions for future studies and implications for promoting learners' GLM, linguistic risk taking, and L2 learning experience are presented.
PubMed: 38905950
DOI: 10.1016/j.actpsy.2024.104367 -
Frontiers in Research Metrics and... 2024The relevance of science diplomacy and open science in today's world is undeniable. Science diplomacy enables countries to jointly address pressing global challenges,...
The relevance of science diplomacy and open science in today's world is undeniable. Science diplomacy enables countries to jointly address pressing global challenges, such as climate change, pandemics, and food security. Open science, promoting accessible and transparent research, plays a pivotal role in this context. Nevertheless, the degree of openness is subject to specific circumstances, contingent upon varying factors, including local knowledge and resources. Latin America has not only been at the forefront of pioneering open access strategies, making it an interesting case to study, but it has also shown a tangible interest in using science diplomacy. Our research employs a mixed-methods approach, incorporating a quantitative survey involving 50 organizations and initiatives dedicated to promoting open science in Latin America, along with two qualitative focus group studies. Our primary objective is to assess if and how these entities use science diplomacy to achieve their objectives. Non-policy entities were prioritized due to their institutional stability in the region. We highlight successful strategies and delve into the existing barriers hindering the full implementation of open science principles. Our research aims to enhance collaboration between these organizations and policy and decision-makers by providing a set of recommendations in that direction. By shedding light on the current landscape and dynamics of open science in Latin America, we aspire to focus on science diplomacy, facilitate informed decision-making, and formulate policies that further propel the region along the path of openness, collaboration, and innovation in scientific research.
PubMed: 38903656
DOI: 10.3389/frma.2024.1355393 -
Journal of Psychopharmacology (Oxford,... Jun 2024The human stress response is characterized by increases in neuromodulators, including norepinephrine (NE) and cortisol. Both neuromodulators can enter the brain and...
BACKGROUND
The human stress response is characterized by increases in neuromodulators, including norepinephrine (NE) and cortisol. Both neuromodulators can enter the brain and affect neurofunctional responses. Two brain areas associated with stress are the amygdala and the hippocampus. The precise influence of NE and cortisol on the amygdala and hippocampal resting state functional connectivity (RSFC) is poorly understood.
AIMS
To investigate the influence of NE and cortisol on the amygdala and hippocampal RSFC.
METHODS
We recruited 165 participants who received 10 mg yohimbine and/or 10 mg hydrocortisone in a randomized, placebo-controlled design. With seed-based analyses, we compared RSFC of the hippocampus and amygdala separately between the three groups that received medication versus placebo.
RESULTS
We found no differences between yohimbine and placebo condition or between hydrocortisone and placebo condition regarding amygdala or hippocampal FC. Compared with placebo, the yohimbine/hydrocortisone condition showed increased amygdala and hippocampal RSFC with the cerebellum. Also, they had increased hippocampal RSFC with the amygdala and cerebral white matter.
DISCUSSION
The group with elevated NE and cortisol showed significantly increased RSFC between the amygdala, hippocampus, and cerebellum compared to placebo. These three brain areas are involved in associative learning and emotional memory, suggesting a critical role for this network in the human stress response. Our results show that NE and cortisol together may influence the strength of this association. Compared to placebo, we found no differences in the groups receiving only one medication, suggesting that increasing one neuromodulator alone may not induce differences in neurofunctional responses. The study procedure has been registered at clinicaltrials.gov (ID: NCT04359147).
PubMed: 38902928
DOI: 10.1177/02698811241260972 -
BMC Medicine Jun 2024IMCY-0098, a synthetic peptide developed to halt disease progression via elimination of key immune cells in the autoimmune cascade, has shown a promising safety profile... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
IMCY-0098, a synthetic peptide developed to halt disease progression via elimination of key immune cells in the autoimmune cascade, has shown a promising safety profile for the treatment of type 1 diabetes (T1D) in a recent phase 1b trial. This exploratory analysis of data from that trial aimed to identify the patient biomarkers at baseline associated with a positive response to treatment and examined the associations between immune response parameters and clinical efficacy endpoints (as surrogates for mechanism of action endpoints) using an artificial intelligence-based approach of unsupervised explainable machine learning.
METHODS
We conducted an exploratory analysis of data from a phase 1b, dose-escalation, randomized, placebo-controlled study of IMCY-0098 in patients with recent-onset T1D. Here, a panel of markers of T cell activation, memory T cells, and effector T cell response were analyzed via descriptive statistics. Artificial intelligence-based analyses of associations between all variables, including immune responses and clinical responses, were performed using the Knowledge Extraction and Management (KEM) v 3.6.2 analytical platform.
RESULTS
The relationship between all available patient data was investigated using unsupervised machine learning implemented in the KEM environment. Of 15 associations found for the dose C group (450 μg subcutaneously followed by 3 × 225 μg subcutaneously), seven involved human leukocyte antigen (HLA) type, all of which identified improvement/absence of worsening of disease parameters in DR4 patients and worsening/absence of improvement in DR4 patients. This association with DR4 and non-DR3 was confirmed using the endpoints normalized area under the curve C-peptide from mixed meal tolerance tests where presence of DR4 HLA haplotype was associated with an improvement in both endpoints. Exploratory immune analysis showed that IMCY-0098 dose B (150 μg subcutaneously followed by 3 × 75 μg subcutaneously) and dose C led to an increase in presumed/potentially protective antigen-specific cytolytic CD4 T cells and a decrease in pathogenic CD8 T cells, consistent with the expected mechanism of action of IMCY-0098. The analysis identified significant associations between immune and clinical responses to IMCY-0098.
CONCLUSIONS
Promising preliminary efficacy results support the design of a phase 2 study of IMCY-0098 in patients with recent-onset T1D.
TRIAL REGISTRATION
ClinicalTrials.gov NCT03272269; EudraCT: 2016-003514-27.
Topics: Humans; Diabetes Mellitus, Type 1; Double-Blind Method; Biomarkers; Male; Female; Adult; Immunotherapy; Young Adult; Adolescent; Treatment Outcome; Peptides; Middle Aged
PubMed: 38902652
DOI: 10.1186/s12916-024-03476-y -
Nature Communications Jun 2024The ability to establish associations between environmental stimuli is fundamental for higher-order brain functions like state inference and generalization. Both the...
The ability to establish associations between environmental stimuli is fundamental for higher-order brain functions like state inference and generalization. Both the hippocampus and orbitofrontal cortex (OFC) play pivotal roles in this, demonstrating complex neural activity changes after associative learning. However, how precisely they contribute to representing learned associations remains unclear. Here, we train head-restrained mice to learn four 'odor-outcome' sequence pairs composed of several task variables-the past and current odor cues, sequence structure of 'cue-outcome' arrangement, and the expected outcome; and perform calcium imaging from these mice throughout learning. Sequence-splitting signals that distinguish between paired sequences are detected in both brain regions, reflecting associative memory formation. Critically, we uncover differential contents in represented associations by examining, in each area, how these task variables affect splitting signal generalization between sequence pairs. Specifically, the hippocampal splitting signals are influenced by the combination of past and current cues that define a particular sensory experience. In contrast, the OFC splitting signals are similar between sequence pairs that share the same sequence structure and expected outcome. These findings suggest that the hippocampus and OFC uniquely and complementarily organize the acquired associative structure.
Topics: Animals; Hippocampus; Prefrontal Cortex; Neurons; Mice; Male; Mice, Inbred C57BL; Association Learning; Cues; Odorants; Memory
PubMed: 38902232
DOI: 10.1038/s41467-024-49652-9 -
Experimental Gerontology Jun 2024Lifelong learning facilitates active ageing, and intragenerational learning-the process by which older adults learn from their peers-is an effective means of achieving...
OBJECTIVES
Lifelong learning facilitates active ageing, and intragenerational learning-the process by which older adults learn from their peers-is an effective means of achieving this goal. The present research aims to elucidate the mechanisms and differences between intergenerational and intragenerational learning models for older adults as evidenced by brain-to-brain synchrony.
METHODS
Fifty-six instructor-learner dyads completed a study comparing intergenerational and intragenerational learning models, as well as task difficulty. The study utilized a block puzzle task and functional near-infrared spectroscopy (fNIRS) for hyperscanning.
RESULTS
The instructor-learner dyads showed greater interpersonal neural synchrony (INS) and learning acquisition in the intragenerational learning model in the difficult task condition (t (54) = 3.49, p < 0.01), whereas the two learning models yielded similar results in the easy condition (t (54) = 1.96, p = 0.06). In addition, INS and self-efficacy mediated the association between learning models and learning acquisition in older adults (b = 0.14, SEM = 0.04, 95 % CI [0.01 0.16]).
DISCUSSION
This study is the first to provide evidence of interbrain synchrony in an investigation of the intragenerational learning model in older adults. Our findings suggest that intra-learning is as effective as traditional inter-learning and may be more effective in certain contexts, such as difficult tasks. Encouraging intra-learning in community service or educational activities can effectively mitigate the challenge of limited volunteers and enhance learning acquisition among older adults.
PubMed: 38901772
DOI: 10.1016/j.exger.2024.112499