Study of wound healing dynamics by single pseudo-particle tracking in phase contrast images acquired in time-lapse

Cellular contacts modify the way cells migrate in a cohesive group with respect to a free single cell. The resulting motion is persistent and correlated, with cells’ velocities self-aligning in time. The presence of a dense agglomerate of cells makes the application of single particle tracking techniques to define cells dynamics difficult, especially in the case of phase contrast images. Here, we propose an original pipeline for the analysis of phase contrast images of the wound healing scratch assay acquired in time-lapse, with the aim of extracting single particle trajectories describing the dynamics of the wound closure. In such an approach, the membrane of the cells at the border of the wound is taken as a unicum, i.e., the wound edge, and the dynamics is described by the stochastic motion of an ensemble of points on such a membrane, i.e., pseudo-particles. For each single frame, the pipeline of analysis includes: first, a texture classification for separating the background from the cells and for identifying the wound edge; second, the computation of the coordinates of the ensemble of pseudo-particles, chosen to be uniformly distributed along the length of the wound edge. We show the results of this method applied to a glioma cell line (T98G) performing a wound healing scratch assay without external stimuli. We discuss the efficiency of the method to assess cell motility and possible applications to other experimental layouts, such as single cell motion. The pipeline is developed in the Python language and is available upon request

Artificial intelligence-based models for reconstructing the critical current and index-value surfaces of HTS tapes

For modelling superconductors, interpolation and analytical formulas are commonly used to consider the relationship between the critical current density and other electromagnetic and physical quantities. However, look-up tables are not available in all modelling and coding environments, and interpolation methods must be manually implemented. Moreover, analytical formulas only approximate real physics of superconductors and, in many cases, lack a high level of accuracy. In this paper, we propose a new approach for addressing this problem involving artificial intelligence (AI) techniques for reconstructing the critical surface of high temperature superconducting (HTS) tapes and predicting their index value known as n-value. Different AI models were proposed and implemented, relying on a public experimental database for electromagnetic specifications of HTS tapes, including artificial neural networks (ANN), eXtreme Gradient Boosting (XGBoost), and kernel ridge regressor (KRR). The ANN model was the most accurate in predicting the critical current of HTS materials, performing goodness of fit very close to 1 and extremely low root mean squared error. The XGBoost model proved to be the fastest method, with training computational times under 1 s; whilst KRR could be used as an alternative solution with intermediate performance

Early prediction of Autism Spectrum Disorders through interaction analysis in home videos and explainable artificial intelligence

There is considerable discussion about the advantages and disadvantages of early ASD diagnosis. However, the development of easily understandable and administrable tools for teachers or caregivers in order to identify potentially alarming behaviours (red flags) is usually considered valuable even by scholars who are concerned with very early diagnosis. This study proposes an AI pre-screening tool with the aim of creating an easily administrable tool for non-competent observers useful to identify potentially alarming signs in pre-verbal interactions. The use of these features is evaluated using an explainable artificial intelligence algorithm to assess which of the proposed new interaction characteristics were more effective in classifying individuals with ASD vs. controls. We used a rating scale with three core sections - sensorimotor, behavioural, and emotional - each further divided into four items. By seeing home videos of children doing everyday activities, two experienced observers rated each of these items from 1 (highly typical interaction) to 8 (extremely atypical interaction). Then, a machine learning model based on XGBoost was developed for identifying ASD children. The classification obtained was interpreted through the use of SHAP explanations, obtaining an area under the receiver operating curve of 0.938 and 0.914 for the two observers, respectively. These results demonstrated the significance of early detection of body-related sensorimotor features

Study of Wound Healing Dynamics by Single Pseudo-Particle Tracking in Phase Contrast Images Acquired in Time-Lapse

Cellular contacts modify the way cells migrate in a cohesive group with respect to a free single cell. The resulting motion is persistent and correlated, with cells’ velocities self-aligning in time. The presence of a dense agglomerate of cells makes the application of single particle tracking techniques to define cells dynamics difficult, especially in the case of phase contrast images. Here, we propose an original pipeline for the analysis of phase contrast images of the wound healing scratch assay acquired in time-lapse, with the aim of extracting single particle trajectories describing the dynamics of the wound closure. In such an approach, the membrane of the cells at the border of the wound is taken as a unicum, i.e., the wound edge, and the dynamics is described by the stochastic motion of an ensemble of points on such a membrane, i.e., pseudo-particles. For each single frame, the pipeline of analysis includes: first, a texture classification for separating the background from the cells and for identifying the wound edge; second, the computation of the coordinates of the ensemble of pseudo-particles, chosen to be uniformly distributed along the length of the wound edge. We show the results of this method applied to a glioma cell line (T98G) performing a wound healing scratch assay without external stimuli. We discuss the efficiency of the method to assess cell motility and possible applications to other experimental layouts, such as single cell motion. The pipeline is developed in the Python language and is available upon request.Basque Government BERC 2018– 2021 Spanish Ministry of Economy and Competitiveness MINECO via the BCAM Severo Ochoa SEV-2017-0718 accreditatio

Effect of data leakage in brain MRI classification using 2D convolutional neural networks

In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high performances reported in numerous studies, developing CNN models with good generalization abilities is still a challenging task due to possible data leakage introduced during cross-validation (CV). In this study, we quantitatively assessed the effect of a data leakage caused by 3D MRI data splitting based on a 2D slice-level using three 2D CNN models to classify patients with Alzheimer’s disease (AD) and Parkinson’s disease (PD). Our experiments showed that slice-level CV erroneously boosted the average slice level accuracy on the test set by 30% on Open Access Series of Imaging Studies (OASIS), 29% on Alzheimer’s Disease Neuroimaging Initiative (ADNI), 48% on Parkinson’s Progression Markers Initiative (PPMI) and 55% on a local de-novo PD Versilia dataset. Further tests on a randomly labeled OASIS-derived dataset produced about 96% of (erroneous) accuracy (slice-level split) and 50% accuracy (subject-level split), as expected from a randomized experiment. Overall, the extent of the effect of an erroneous slice-based CV is severe, especially for small datasets

The first archaeological case of permanent teeth fusion in Europe

Abstract Teeth fusion is a developmental anomaly characterized by the union of two and, more rarely, three adjacent teeth. The fusion is caused by the physical pressure between two adjacent teeth during their development due to congenital, inherited, acquired or idiopathic factors. Nowadays, fused teeth occur with a frequency ratio between 0.1% and 1% in permanent dentition and 0.5% and 2.5% in primary dentition, and with an equal distribution between males and females. Fused teeth are a rare clinical finding, so there are not standardized clinical protocols and each case should be treated independently. This condition is rare in archaeological populations, likely due to taphonomic processes that cause the lack of information, as well as for the general low occurrence of the defect itself. In the European archaeological literature, there are no reports of two permanent fused teeth so far. Therefore, the present paper represents the first case study of two fused permanent incisors in the past Europe populations as this anomaly has been recognized in an adult man buried in the Longobard cemetery of Guidizzolo (VI?VII century A.D., northern Italy)

Efficacy of different regimens of adjuvant radiochemotherapy for treatment of glioblastoma

Aims and background: We retrospectively analyzed the impact of different adjuvant chemotherapy regimens in a group of patients treated for glioblastoma compared to patients receiving only postoperative radiotherapy. Material and methods: Eighty-six consecutive patients underwent radiotherapy between January 2000 and December 2003: 52 patients received radiotherapy alone, 17 patients radiochemotherapy with low-dose temozolomide (20 mg/m(2)) + cyclooxygenase-2-inhibitors (200 mg), 6 patients radiochemotherapy with high-dose temozolomide (50 mg/m(2)). Eleven patients, with unfavorable prognostic factors, were treated with imatinib and 55/2.5 Gy. Results: The groups treated with high-and low-dose temozolomide showed the longest overall survival (median, 21 months and 17 months, respectively). Median overall survival was 9 months for radiation alone and 4 months for the imatinib-treated group. The same positive trend of temozolomide on prolonged overall survival was confirmed when only patients submitted to maximally radical resection or patients with KPS >70 were considered. Differences in progression-free survival were not statistically significant. Conclusions: Patients treated with adjuvant temozolomide either inside or outside of study protocols had survival times similar to other reports or randomized studies. The absence of a significant influence of temozolomide on progression-free survival could depend on the unavoidable drawbacks and biases of retrospective investigations or on the definition of relapse used. The unsatisfactory results of radiotherapy plus imatinib may have been due to a high prevalence of unfavorable prognostic factors in the respective patients. The ongoing controlled trial will further define the efficacy of adjuvant/concomitant imatinib

Manufacturing of Metal Frameworks for Full-Arch Dental Restoration on Implants: A Comparison between Milling and a Novel Hybrid Technology

Purpose: To determine the trueness and precision of frameworks manufactured with a selective laser melting/milling hybrid technique (SLM/m) and conventional milling by comparing the implant-platform/framework interface with those of the original computer-aided design (CAD). Materials and Methods: Using a virtual 6-implant-supported full-arch framework CAD drawing, 27 titanium replicas were manufactured by 3 independent manufacturing centers (n = 9/center) using a hybrid SLM/m technology (labs 1 and 2) or the conventional milling technique (lab 3). Using an opto-mechanical coordinate measuring machine, the frameworks\u2019 misfit distribution and patterns were analyzed, and the position error between paired platform positions within each framework was evaluated to calculate the misfit tendency for each group. A multilevel analysis using a mixed-effects model was conducted (\u3b1 = 0.05). The trueness was evaluated as the dimensional difference from the original, while the precision as the dimensional difference from a repeated scan. Results: The 3 dimensional misfits differed significantly among the 3 groups, with the milled group exhibiting the least accurate outcome (p = 0.005). The mean 3D positioning errors ranged from 8 to 16 \ub5m and from 9 to 22 \ub5m for the SLM/m technique (labs 1 and 2, respectively), and from 20 to 35 \ub5m for conventional milling (lab 3). Regarding the misfit distribution pattern, the misfit increased with the distance between paired platform positions in all groups. Conclusions: All groups had 3D misfits well within the error limits reported in the literature. The 3D misfits of new hybrid (SLM/milling) and conventional (milling) procedures differed significantly among them, with the milling technique the less accurate and precise. The largest errors in all groups were found between the most distant implants, resulting in a correlation between the framework span and the inaccuracies

Manufacturing of Metal Frameworks for Full-Arch Dental Restoration on Implants: A Comparison between Milling and a Novel Hybrid Technology

Purpose: To determine the trueness and precision of frameworks manufactured with a selective laser melting/milling hybrid technique (SLM/m) and conventional milling by comparing the implant-platform/framework interface with those of the original computer-aided design (CAD). Materials and Methods: Using a virtual 6-implant-supported full-arch framework CAD drawing, 27 titanium replicas were manufactured by 3 independent manufacturing centers (n = 9/center) using a hybrid SLM/m technology (labs 1 and 2) or the conventional milling technique (lab 3). Using an opto-mechanical coordinate measuring machine, the frameworks\u2019 misfit distribution and patterns were analyzed, and the position error between paired platform positions within each framework was evaluated to calculate the misfit tendency for each group. A multilevel analysis using a mixed-effects model was conducted (\u3b1 = 0.05). The trueness was evaluated as the dimensional difference from the original, while the precision as the dimensional difference from a repeated scan. Results: The 3 dimensional misfits differed significantly among the 3 groups, with the milled group exhibiting the least accurate outcome (p = 0.005). The mean 3D positioning errors ranged from 8 to 16 \ub5m and from 9 to 22 \ub5m for the SLM/m technique (labs 1 and 2, respectively), and from 20 to 35 \ub5m for conventional milling (lab 3). Regarding the misfit distribution pattern, the misfit increased with the distance between paired platform positions in all groups. Conclusions: All groups had 3D misfits well within the error limits reported in the literature. The 3D misfits of new hybrid (SLM/milling) and conventional (milling) procedures differed significantly among them, with the milling technique the less accurate and precise. The largest errors in all groups were found between the most distant implants, resulting in a correlation between the framework span and the inaccuracies