A comprehensive AI model development framework for consistent Gleason grading

Background: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. Methods: We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. Results: Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. Conclusions: This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows

Masking effects on linear regression in multi-class classification

The linear regression method belongs to the important class of linear methods for multi-class classification. Empirical evidences suggest that a masking problem occurs with the linear regression approach and it is especially prevalent when the number of classes is large. This paper provides an analytical study of this issue and explicitly explains why the linear discriminant analysis procedure removes this problem.Classifier Decision boundary Linear discriminant analysis Linear regression

Intent-aware image cloning

Currently, gradient domain methods are popular for producing seamless cloning of a source image patch into a target image. However, structure conflicts between the source image patch and the target image may generate artifacts, preventing the general practices. In this paper, we tackle the challenge by incorporating the users' intent in outlining the source patch, where the boundary drawn generally has different appearances from the objects of interest. We first reveal that artifacts exist in the over-included region, the region outside the objects of interest in the source patch. Then we use the diversity from the boundary to approximately distinguish the objects from the over-included region, and design a new algorithm to make the target image adaptively take effects in blending. So the structure conflicts can be efficiently suppressed to remove the artifacts around the objects of interest in the composite result. Moreover, we develop an interpolation measure to composite the final image rather than solving a Poisson equation, and speed up the interpolation by treating pixels in clusters and using hierarchical sampling techniques. Our method is simple to use for instant and high-quality image cloning, in which users only need to outline a region of interested objects to process. Our experimental results have demonstrated the effectiveness of our cloning method.Currently, gradient domain methods are popular for producing seamless cloning of a source image patch into a target image. However, structure conflicts between the source image patch and the target image may generate artifacts, preventing the general practices. In this paper, we tackle the challenge by incorporating the users' intent in outlining the source patch, where the boundary drawn generally has different appearances from the objects of interest. We first reveal that artifacts exist in the over-included region, the region outside the objects of interest in the source patch. Then we use the diversity from the boundary to approximately distinguish the objects from the over-included region, and design a new algorithm to make the target image adaptively take effects in blending. So the structure conflicts can be efficiently suppressed to remove the artifacts around the objects of interest in the composite result. Moreover, we develop an interpolation measure to composite the final image rather than solving a Poisson equation, and speed up the interpolation by treating pixels in clusters and using hierarchical sampling techniques. Our method is simple to use for instant and high-quality image cloning, in which users only need to outline a region of interested objects to process. Our experimental results have demonstrated the effectiveness of our cloning method

Mechanochemistry: An Efficient Way to Recycle Thermoset Polyurethanes

A recycling process of waste thermosetting polyurethane plastics was proposed based on the mechanochemical method, aiming at the three-dimensional network cross-linking structure of thermosetting polyurethane. Orthogonal experimental design was adopted to select three factors of crushing speed, crushing time, and feed amount to determine the best crushing parameters. Then, the waste polyurethane insulation boards were crushed and degraded by the mechanism of regenerative forming with the adjustable speed test machine. Accordingly, the recycled powder was obtained. Finally, nine kinds of polyurethane recycled composite plates were prepared by hot pressing process. The degradation effect of thermosetting polyurethane was analyzed by Fourier transform infrared spectroscopy, scanning electron microscope, and X-ray diffraction. Moreover, the mechanical properties and thermal insulation properties of recycled composite plates were tested and analyzed. The results show that the network cross-linking molecular structure of waste thermosetting polyurethane plastics is destroyed by the effect of mechanochemical action, and methyl and aldehyde groups are decomposed. Therefore, a recycled powder with strong reactivity and plasticity is generated, which improves the activity regeneration ability. After adding thermoplastic resin, the mechanical properties and formability of recycled composite plates are enhanced, with maximum tensile strength up to 9.913 MPa. Correspondingly, the thermal insulation performance of plates is reduced. However, the minimum thermal conductivity can also reach 0.056 W/m·K. This study provides an effective method for the recycling of thermosetting polyurethane plastics

Implications of the melting depth and temperature of the Atlantic mid-ocean ridge basalts

Mid-ocean ridge basalts (MORBs) are characterized by large variations in trace element compositions and isotopic ratios, which are difficult to be interpreted solely by using magmatic process such as partial melting of a peridotitic mantle and subsequently fractional crystallization. Geochemical diversity of MORBs have been attributed to large-scale heterogeneity within the underlying mantle, and the heterogeneity might have been caused by addition of recycled crustal component, subcontinental lithosphere, metasomatized lithosphere and outer core contribution. In this study, we investigated the MORBs along the Mid-Atlantic Ridge (MAR) by estimating the temperature and pressure of partial melting, and comprehensively comparing trace element and isotope ratios. The data for MORBs from areas close to mantle plumes show large variations. Mantle plumes can affect mid-oceanic ridges 1 400 km away, but plume effects did not cover all of the ridge segments, and those segments without plume effects did not have any abnormalities in temperature, trace element or isotope ratios. We ascribed the above phenomena to result from the shapes of the plume flow, which we categorized as "pipelike channels" and "pancake-like channels". The "pancake-like channels" plumes affected the ambient mantle nondirectionally, but the range of the mantle affected by the "pipe-like channels" plumes were selective. Element ratios of MORBs reveal that the mantle source of the MORBs along the MAR is highly heterogeneous. We suggest that most of source heterogeneities of the MORBs may be due to the presence of subducted slab and delaminated lower crust in the source. In addition, the plume that carried materials from the core-mantle boundary may affect some of the segments

An overview of meta-analyses on radiomics: more evidence is needed to support clinical translation

Abstract Objective To conduct an overview of meta-analyses of radiomics studies assessing their study quality and evidence level. Methods A systematical search was updated via peer-reviewed electronic databases, preprint servers, and systematic review protocol registers until 15 November 2022. Systematic reviews with meta-analysis of primary radiomics studies were included. Their reporting transparency, methodological quality, and risk of bias were assessed by PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 2020 checklist, AMSTAR-2 (A MeaSurement Tool to Assess systematic Reviews, version 2) tool, and ROBIS (Risk Of Bias In Systematic reviews) tool, respectively. The evidence level supporting the radiomics for clinical use was rated. Results We identified 44 systematic reviews with meta-analyses on radiomics research. The mean ± standard deviation of PRISMA adherence rate was 65 ± 9%. The AMSTAR-2 tool rated 5 and 39 systematic reviews as low and critically low confidence, respectively. The ROBIS assessment resulted low, unclear and high risk in 5, 11, and 28 systematic reviews, respectively. We reperformed 53 meta-analyses in 38 included systematic reviews. There were 3, 7, and 43 meta-analyses rated as convincing, highly suggestive, and weak levels of evidence, respectively. The convincing level of evidence was rated in (1) T2-FLAIR radiomics for IDH-mutant vs IDH-wide type differentiation in low-grade glioma, (2) CT radiomics for COVID-19 vs other viral pneumonia differentiation, and (3) MRI radiomics for high-grade glioma vs brain metastasis differentiation. Conclusions The systematic reviews on radiomics were with suboptimal quality. A limited number of radiomics approaches were supported by convincing level of evidence. Clinical relevance statement The evidence supporting the clinical application of radiomics are insufficient, calling for researches translating radiomics from an academic tool to a practicable adjunct towards clinical deployment. Graphical Abstrac

Oncogenic mutations within the β3‐αC loop of EGFR

Abstract Background β3‐αC loop is a highly conserved structural domain across oncogene families, which is a switch for kinase activity. There have been numerous researches on mutations within β3‐αC loop in EGFR, but relatively less in ERBB2, BRAF, and MAP2K1. In addition, previous studies mainly focus on β3‐αC deletion in EGFR, which is the most common type affecting kinase activity and driving lung cancer. Other mutation types are not well studied. Methods Here we analyzed the profile of β3‐αC loop mutations in a total of 10,000 tumor biopsy and/or ctDNA patient samples using hybridization capture‐based next‐generation sequencing. Results We identified 1616 mutations within β3‐αC loop in this cohort. Most mutations were located in EGFR, with less percentage in ERBB2, BRAF, and MAP2K1. EGFR β3‐αC deletions occurred at a high percentage of 96.7% and were all drug‐relevant. We also detected rare EGFR β3‐αC insertions and point mutations, most of which were related to EGFR TKIs resistance. ERBB2 β3‐αC deletions were only found in breast cancers and sensitive to EGFR/ERBB2 inhibitor. Moreover, BRAF and MAP2K1 mutations within β3‐αC loop also demonstrated drugs relevance. Conclusion Our study showed that oncogenic mutations within the β3‐αC loop of ERBB2, MAP2K1, and BRAF are analogous to that of EGFR, which have profound effect on drug response. Understanding the mutation profile within the β3‐αC loop is critical for targeted therapies