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In patients with high-level radiation exposure, gastrointestinal injury is the main cause of death. Despite the severity of damage to the gastrointestinal tract, no specific therapeutic option is available. Tauroursodeoxycholic acid (TUDCA) is a conjugated form of ursodeoxycholic acid that suppresses endoplasmic reticulum (ER) stress and regulates various cell-signaling pathways. We investigated the effect of TUDCA premedication in alleviating intestinal damage and enhancing the survival of C57BL/6 mice administered a lethal dose (15Gy) of focal abdominal irradiation. TUDCA was administered to mice 1 h before radiation exposure, and reduced apoptosis of the jejunal crypts 12 h after irradiation. At later timepoint (3.5 days), irradiated mice manifested intestinal morphological changes that were detected via histological examination. TUDCA decreased the inflammatory cytokine levels and attenuated the decrease in serum citrulline levels after radiation exposure. Although radiation induced ER stress, TUDCA pretreatment decreased ER stress in the irradiated intestinal cells. The effect of TUDCA indicates the possibility of radiation therapy for cancer in tumor cells. TUDCA did not affect cell proliferation and apoptosis in the intestinal epithelium. TUDCA decreased the invasive ability of the CT26 metastatic colon cancer cell line. Reduced invasion after TUDCA treatment was associated with decreased matrix metalloproteinase (MMP)-7 and MMP-13 expression, which play important roles in invasion and metastasis. This study shows a potential role of TUDCA in protecting against radiation-induced intestinal damage and inhibiting tumor cell migration without any radiation and radiation therapy effect., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Joong Sun Kim reports financial support was provided by National Research Foundation of Korea. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Although there are several types of radiation exposure, it is debated whether low‑dose‑rate (LDR) irradiation (IR) affects the body. Since the small intestine is a radiation‑sensitive organ, the present study aimed to evaluate how it changes when exposed to LDR IR and identify the genes sensitive to these doses. After undergoing LDR (6.0 mGy/h) γ radiation exposure, intestinal RNA from BALB/c mice was extracted 1 and 24 h later. Mouse whole genome microarrays were used to explore radiation‑induced transcriptional alterations. Reverse transcription‑quantitative (RT‑q) PCR was used to examine time‑ and dose‑dependent radiation responses. The histopathological status of the jejunum in the radiated mouse was not changed by 10 mGy of LDR IR; however, 23 genes were upregulated in response to LDR IR of the jejunum in mice after 1 and 24 h of exposure. Upregulated genes were selected to validate the results of the RNA sequencing analysis for RT‑qPCR detection and results showed that only Na + /K + transporting subunit α4, glucose‑6‑phosphatase catalytic subunit 2 (G6PC2), mucin 6 (MUC6) and transient receptor potential cation channel subfamily V member 6 levels significantly increased after 24 h of LDR IR. Furthermore, G6PC2 and MUC6 were notable genes induced by LDR IR exposure according to protein expression via western blot analysis. The mRNA levels of G6PC2 and MUC6 were significantly elevated within 24 h under three conditions: i) Exposure to LDR IR, ii) repeated exposure to LDR IR and iii) exposure to LDR IR in the presence of inflammatory bowel disease. These results could contribute to an improved understanding of immediate radiation reactions and biomarker development to identify radiation‑susceptible individuals before histopathological changes become noticeable. However, further investigation into the specific mechanisms involving G6PC2 and MUC6 is required to accomplish this.

The observation of thioester-mediated acyl transfer processes in nature has inspired the development of novel protein synthesis and functionalization methodologies. The chemoselective transfer of an acyl group from S -to- N is the basis of several powerful ligation strategies. In this work, we sought to apply the reverse process, the transfer of an acyl group from N -to- S , as a method to convert stable chiral amides into more reactive thioesters. To this end, we developed a novel cysteine-derived oxazolidinone that serves as both a chiral imide auxiliary and an acyl transfer agent. This auxiliary combines the desirable features of rigid chiral imides as templates for asymmetric transformations with the synthetic applicability of thioesters. We demonstrate that the auxiliary can be applied in a range of highly selective asymmetric transformations. Subsequent intramolecular N -to- S acyl transfer of the chiral product and in situ trapping of the resulting thioester provides access to diverse carboxylic acid derivatives under mild conditions. The oxazolidinone thioester products can also be isolated and used in Pd-mediated transformations to furnish highly valuable chiral scaffolds, such as noncanonical amino acids, cyclic ketones, tetrahydropyrones, and dihydroquinolinones. Finally, we demonstrate that the oxazolidinone thioesters can also serve as a surrogate for SNAC-thioesters, enabling their seamless use as non-native substrates in biocatalytic transformations., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Purpose: Networking with other biodosimetry laboratories is necessary to assess the radiation exposure of many individuals in large-scale radiological accidents. The Korea biodosimetry network, K-BioDos, prepared harmonized scoring guidelines for dicentric chromosome assay to obtain homogeneous results within the network and investigated the efficiency of the guidelines., Materials and Methods: Three laboratories in K-BioDos harmonized the scoring guidelines for dicentric chromosome assay. The results of scoring dicentric chromosomes using the harmonized scoring guidelines were compared with the laboratories' results using their own methods. Feedback was collected from the scorers following the three intercomparison exercises in 3 consecutive years., Results: K-BioDos members showed comparable capacity to score dicentrics in the three exercises. However, the results of the K-BioDos guidelines showed no significant improvement over those of the scorers' own methods. According to the scorers, our harmonized guidelines led to more rejected metaphases and ultimately decreased the number of scorable metaphases compared with their own methods. Moreover, the scoring time was sometimes longer with the K-BioDos protocol because some scorers were not yet familiar with the guidelines, though most scorers reported that the time decreased or was unchanged. These challenges may cause low adherence to the guidelines. Most scorers expressed willingness to use the guidelines to select scorable metaphases or identify dicentrics for other biodosimetry works, whereas one did not want to use it due to the difference from their calibration curves., Conclusions: We identified potential resistance to following the harmonized guidelines and received requests for more detailed methods. Our findings suggest that the harmonized criteria should be continually updated, and education and training should be provided for all scorers. These changes could allow members within the biodosimetry network to successfully collaborate and support each other in large-scale radiological accidents.

Purpose: The dicentric chromosome assay (DCA), often referred to as the 'gold standard' in radiation dose estimation, exhibits significant challenges as a consequence of its labor-intensive nature and dependency on expert knowledge. Existing automated technologies face limitations in accurately identifying dicentric chromosomes (DCs), resulting in decreased precision for radiation dose estimation. Furthermore, in the process of identifying DCs through automatic or semi-automatic methods, the resulting distribution could demonstrate under-dispersion or over-dispersion, which results in significant deviations from the Poisson distribution. In response to these issues, we developed an algorithm that employs deep learning to automatically identify chromosomes and perform fully automatic and accurate estimation of diverse radiation doses, adhering to a Poisson distribution., Materials and Methods: The dataset utilized for the dose estimation algorithm was generated from 30 healthy donors, with samples created across seven doses, ranging from 0 to 4 Gy. The procedure encompasses several steps: extracting images for dose estimation, counting chromosomes, and detecting DC and fragments. To accomplish these tasks, we utilize a diverse array of artificial neural networks (ANNs). The identification of DCs was accomplished using a detection mechanism that integrates both deep learning-based object detection and classification methods. Based on these detection results, dose-response curves were constructed. A dose estimation was carried out by combining a regression-based ANN with the Monte-Carlo method., Results: In the process of extracting images for dose analysis and identifying DCs, an under-dispersion tendency was observed. To rectify the discrepancy, classification ANN was employed to identify the results of DC detection. This approach led to satisfaction of Poisson distribution criteria by 32 out of the initial pool of 35 data points. In the subsequent stage, dose-response curves were constructed using data from 25 donors. Data provided by the remaining five donors served in performing dose estimations, which were subsequently calibrated by incorporating a regression-based ANN. Of the 23 points, 22 fell within their respective confidence intervals at p < .05 (95%), except for those associated with doses at levels below 0.5 Gy, where accurate calculation was obstructed by numerical issues. The accuracy of dose estimation has been improved for all radiation levels, with the exception of 1 Gy., Conclusions: This study successfully demonstrates a high-precision dose estimation method across a general range up to 4 Gy through fully automated detection of DCs, adhering strictly to Poisson distribution. Incorporating multiple ANNs confirms the ability to perform fully automated radiation dose estimation. This approach is particularly advantageous in scenarios such as large-scale radiological incidents, improving operational efficiency and speeding up procedures while maintaining consistency in assessments. Moreover, it reduces potential human error and enhances the reliability of results.