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Abstract: The shielding performance and activation susceptibility of a sandwich wall in the proton therapy facility of China Medical University Hospital were investigated in an integrated manner using FLUKA Monte Carlo simulations. The 2-m-thick partition wall between two adjoining treatment rooms had a three-layered structure, which comprised a 0.2-m-thick iron layer sandwiched between two layers of 0.9-m-thick concrete. In comparison with that of a concrete wall of the same thickness, the shielding performance of the concrete-iron-concrete wall was marginally better, further reducing the transmitted dose rate by approximately a factor of 2 against secondary neutrons generated through proton bombardment. This study also investigated radioactivity levels from long-lived radionuclides (3H, 22Na, 54Mn, 55Fe, 60Co, 134Cs, 152Eu, and 154Eu) that are primarily induced in concrete or iron by neutrons. The specific activities of 54Mn, 55Fe, and 60Co in the middle iron layer were considerably higher (by factors of 75, 25, and 5, respectively) than those in the neighboring concrete. However, as for clearance levels, the index value of the iron layer was lower than that of the neighboring concrete because of the presence of fewer types of long-lived radionuclides in iron. Under irradiation scenarios considered in this study, the residual activity levels of the sandwich wall do not exceed those of a full-concrete wall, and the indexes at various depths estimated at 5 years cooling following a 20-y operational period comply with clearance criteria., (Copyright © 2025 Health Physics Society.)

The use of a Monte Carlo code in the assessment of residual radioactivity for decommissioning of a medical cyclotron facility requires a reasonable approximation to the facility's history of operations. A periodic irradiation scenario simulating the cyclotron's daily operation for radioisotope production is generally considered reasonable, but its implementation in the code's input file can be cumbersome because more than thousands of irradiation cycles must be modeled. In practice, two simplified scenarios with continuous irradiation are commonly used instead: (i) omitting the downtime between two irradiation periods and (ii) extending the irradiation duration across the entire operational lifespan of the facility, albeit with a reduced beam current to maintain workload consistency. A systematic comparison of residual radionuclide productions across various half-lives under these three scenarios was performed. This technical note presents the resulting correction factors for the two simplified continuous irradiation models, enhancing their applicability in estimating radioactive inventories under a range of circumstances., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

In sum, 11 (p,xn) related nuclear reactions with 9 target materials, namely 18O(p,n)18F, 15N(p,n)15O, 68Zn(p,n)68Ga, 68Zn(p,2n)67Ga, 69Ga(p,2n)68Ge, 89Y(p,n)89Zr, 100Mo(p,pn)99Mo, 100Mo(p,2n)99mTc, 112Cd(p,2n)111In, 124Xe(p,2n)123Cs and 203Tl(p,3n)201Pb, are involved in the operation of 13 radionuclide-production cyclotrons in Taiwan. The secondary neutrons accompanying these production routes could induce varying degrees of material activation in the cyclotron facility. Accordingly, this study compared the effects of various (p,xn) production routes on the neutron-induced long-lived radioactivity in the concrete walls of a hypothetical cyclotron vault. In addition, an activation-reduction approach involving the addition of a layer of neutron-absorbing material to the surface of inner concrete walls was evaluated., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Interstitial fibrosis assessment by renal pathologists lacks good agreement, and we aimed to investigate its hidden properties and infer possible clinical impact. Fifty kidney biopsies were assessed by 9 renal pathologists and evaluated by intraclass correlation coefficients (ICCs) and kappa statistics. Probabilities of pathologists' assessments that would deviate far from true values were derived from quadratic regression and multilayer perceptron nonlinear regression. Likely causes of variation in interstitial fibrosis assessment were investigated. Possible misclassification rates were inferred on reported large cohorts. We found inter-rater reliabilities ranged from poor to good (ICCs 0.48 to 0.90), and pathologists' assessments had the worst agreements when the extent of interstitial fibrosis was moderate. 33.5% of pathologists' assessments were expected to deviate far from the true values. Variation in interstitial fibrosis assessment was found to be correlated with variation in interstitial inflammation assessment (r 2  = 32.1%). Taking IgA nephropathy as an example, the Oxford T scores for interstitial fibrosis were expected to be misclassified in 21.9% of patients. This study demonstrated the complexity of the inter-rater reliability of interstitial fibrosis assessment, and our proposed approaches discovered previously unknown properties in pathologists' practice and inferred a possible clinical impact on patients., (© 2023. Springer Nature Limited.)

GPI-anchored folate receptor α (FRα) is an attractive anticancer drug target and diagnosis marker in fundamental biology and medical research due to its significant expression on many cancer cells. Currently, analyses of FRα expression levels are usually achieved using immunological methods. Due to the continual FRα synthesis and degradation, immunological methods are not suitable for studying real-time dynamic activities of FRα in living cells. In this paper, we introduce a rapid and specific FRα protein-labeling fluorescent probe, FR1 , to facilitate the study of the dynamics of expression and degradation processes of endogenous FRα in living cells. With this labeling probe, insights on FRα protein lifetime and shedding from the cell surface can be obtained using fluorescence live-cell imaging and electrophoresis techniques. We revealed that FRα undergoes soluble domain release and endocytosis degradation simultaneously. Imaging results showed that most of the membrane FRα are transported to the lysosomes after 2 h of incubation. Furthermore, we also showed that the secretion of a FRα soluble domain into the environment is most likely accomplished by phospholipase. We believe that this protein-labeling approach can be an important tool for analyzing various dynamic processes involving FRα.

Interstitial inflammation scoring is incorporated into the Banff Classification of Renal Allograft Pathology and is essential for the diagnosis of T-cell mediated rejection. However, its reproducibility, including inter-rater and intra-rater reliabilities, has not been carefully investigated. In this study, eight renal pathologists from different hospitals independently scored 45 kidney allograft biopsies with varying extents of interstitial inflammation. Inter-rater reliabilities and intra-rater reliabilities were investigated by kappa statistics and conditional agreement probabilities. Individual pathologists' scoring patterns were examined by chi-squared tests and proportions tests. The mean pairwise kappa values for inter-rater reliability were 0.27, 0.30, and 0.26 for the Banff i score, ti score, and i-IFTA, respectively. No rater pair performed consistently better or worse than others on all three scorings. After dichotomizing the scores into two groups (none/mild and moderate/severe inflammation), the averaged conditional agreements ranged from 47.1% to 50.0%. The distributions of the scores differed, but some pathologists persistently scored higher or lower than others. Given the important role of interstitial inflammation scoring in the diagnosis of T-cell mediated rejection, transplant practitioners should be aware of the possible clinical implications of the far-from-optimal reproducibility., (© 2023. The Author(s).)

Ectodomain shedding is a form of limited proteolysis in which a protease cleaves a transmembrane protein, releasing the extracellular domain from the cell surface. Cells use this process to regulate a wide variety of biological events. Typically, immunological detection methods are employed for the analysis of ectodomains secreted into the cultured media. In this paper, we describe a new strategy using an affinity-based protein-labeling fluorescent probe to study ectodomain shedding. We analyzed the ectodomain shedding of cell surface carbonic anhydrases (CAIX and CAXII), which are important biomarkers for tumor hypoxia. Using both chemical and genetic approaches, we identified that the ADAM17 metalloprotease is responsible for the shedding of carbonic anhydrases. Compared to current immunological methods, this protein-labeling approach not only detects ectodomain released into the culture media but also allows real-time living cell tracking and quantitative analysis of remnant proteins on the cell surface, thereby providing a more detailed insight into the mechanism of ectodomain shedding as well as protein lifetime on the cell surface.

A novel chiral P,Se-heterodonor ligand has been designed and prepared through an efficient and simple operation. This ligand can be successfully applied to Pd-catalyzed asymmetric allylic substitution with C- and N-nucleophiles, producing a diverse range of chiral allylic products in high yields and enantioselectivities (up to 99% yield and 95% ee).

Gastrointestinal stromal tumors (GIST) are common mesenchymal tumors, and their effective treatment depends upon the mutational subtype of the KIT/PDGFRA genes. We established deep convolutional neural network (DCNN) models to rapidly predict drug-sensitive mutation subtypes from images of pathological tissue. A total of 5153 pathological images of 365 different GISTs from three different laboratories were collected and divided into training and validation sets. A transfer learning mechanism based on DCNN was used with four different network architectures, to identify cases with drug-sensitive mutations. The accuracy ranged from 87% to 75%. Cross-institutional inconsistency, however, was observed. Using gray-scale images resulted in a 7% drop in accuracy (accuracy 80%, sensitivity 87%, specificity 73%). Using images containing only nuclei (accuracy 81%, sensitivity 87%, specificity 73%) or cytoplasm (accuracy 79%, sensitivity 88%, specificity 67%) produced 6% and 8% drops in accuracy rate, respectively, suggesting buffering effects across subcellular components in DCNN interpretation. The proposed DCNN model successfully inferred cases with drug-sensitive mutations with high accuracy. The contribution of image color and subcellular components was also revealed. These results will help to generate a cheaper and quicker screening method for tumor gene testing.

Background: Accurate and precise alignment of histopathology tissue sections is a key step for the interpretation of the proteome topology and cell level three-dimensional (3D) reconstruction of diseased tissues. However, the realization of an automated and robust method for aligning nonglobally stained immunohistochemical (IHC) sections is still challenging. In this study, we aim to assess the feasibility of multidimensional graph-based image registration on aligning serial-section and whole-slide IHC section images., Materials and Methods: An automated, patch graph-based registration method was established and applied to align serial, whole-slide IHC sections at ×10 magnification (average 32,947 × 27,054 pixels). The alignment began with the initial alignment of high-resolution reference and translated images (object segmentation and rigid registration) and nonlinear registration of low-resolution reference and translated images, followed by the multidimensional graph-based image registration of the segmented patches, and finally, the fusion of deformed patches for inspection. The performance of the proposed method was formulated and evaluated by the Hausdorff distance between continuous image slices., Results: Sets of average 315 patches from five serial whole slide, IHC section images were tested using 21 different IHC antibodies across five different tissue types (skin, breast, stomach, prostate, and soft tissue). The proposed method was successfully automated to align most of the images. The average Hausdorff distance was 48.93 μm with a standard deviation of 14.94 μm, showing a significant improvement from the previously published patch-based nonlinear image registration method (average Hausdorff distance of 93.89 μm with 50.85 μm standard deviation)., Conclusions: Our method was effective in aligning whole-slide tissue sections at the cell-level resolution. Further advancements in the screening of the proteome topology and 3D tissue reconstruction could be expected., Competing Interests: None declared., (Copyright: © 2021 Journal of Pathology Informatics.)

Purpose: Prostate cancer (PCa) is a major health concern in aging males, and proper management of the disease depends on accurately interpreting pathology specimens. However, reading prostatectomy histopathology slides, which is basically for staging, is usually time consuming and differs from reading small biopsy specimens, which is mainly used for diagnosis. Generally, each prostatectomy specimen generates tens of large tissue sections and for each section, the malignant region needs to be delineated to assess the amount of tumor and its burden. With the aim of reducing the workload of pathologists, in this study, we focus on developing a computer-aided diagnosis (CAD) system based on a densely connected convolutional neural network (DenseNet) for whole-slide histopathology images to outline the malignant regions., Methods: We use an efficient color normalization process based on ranklet transformation to automatically correct the intensity of the images. Additionally, we use spatial probability to segment the tissue structure regions for different tissue recognition patterns. Based on the segmentation, we incorporate a multidimensional structure into DenseNet to determine if a particular prostatic region is benign or malignant., Results: As demonstrated by the experimental results with a test set of 2,663 images from 32 whole-slide prostate histopathology images, our proposed system achieved 0.726, 0.6306, and 0.5209 in the average of the Dice coefficient, Jaccard similarity coefficient, and Boundary F1 score measures, respectively. Then, the accuracy, sensitivity, specificity, and the area under the ROC curve (AUC) of the proposed classification method were observed to be 95.0% (2544/2663), 96.7% (1210/1251), 93.9% (1334/1412), and 0.9831, respectively., Discussions: We provide a detailed discussion on how our proposed system demonstrates considerable improvement compared with similar methods considered in previous researches as well as how it can be used for delineating malignant regions., (© 2019 American Association of Physicists in Medicine.)