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Abstract Background Dysregulation of iron metabolism is implicated in malignant transformation, cancer progression, and therapeutic resistance. Here, we demonstrate that iron regulatory protein 2 (IRP2) preferentially regulates iron metabolism and promotes tumor growth in colorectal cancer (CRC). Methods IRP2 knockdown and knockout cells were generated using RNA interference and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 methodologies, respectively. Cell viability was evaluated using both CCK-8 assay and cell counting techniques. Furthermore, IRP2 inhibition was determined by surface plasmon resonance (SPR) and RNA immunoprecipitation (IP). The suppressive effects of IRP2 were also corroborated in both organoid and mouse xenograft models, providing a comprehensive validation of IRP2’s role. Results We have elucidated the role of IRP2 as a preferential regulator of iron metabolism, actively promoting tumorigenesis within CRC. Elevated levels of IRP2 expression in patient samples are correlated with diminished overall survival, thereby reinforcing its potential role as a prognostic biomarker. The functional suppression of IRP2 resulted in a pronounced delay in tumor growth. Building on this proof of concept, we have developed IRP2 inhibitors that significantly reduce IRP2 expression and hinder its interaction with iron-responsive elements in key iron-regulating proteins, such as ferritin heavy chain 1 (FTH1) and transferrin receptor (TFRC), culminating in iron depletion and a marked reduction in CRC cell proliferation. Furthermore, these inhibitors are shown to activate the AMPK-ULK1-Beclin1 signaling cascade, leading to cell death in CRC models. Conclusions Collectively, these findings highlight the therapeutic potential of targeting IRP2 to exploit the disruption of iron metabolism in CRC, presenting a strategic advancement in addressing a critical area of unmet clinical need.

Abstract The development of synthetic receptors capable of selectively binding guests with diverse structures and multiple functional groups poses a significant challenge. Here, we present the efficient assembly of foldamer-based receptors for monosaccharides, utilising the principles of complexation-induced equilibrium shifting and adaptive folding. Diimine 4 can be quantitatively assembled from smaller components when d-galactose is added as a guest among monosaccharides we examined. During this assembly, dual complexation-induced equilibrium shifts toward both the formation of diimine 4 and the conversion of d-galactose into α-d-galactofuranose are observed. Diimine 6 is quantitatively assembled in the presence of two different guests, methyl β-d-glucopyranoside and methyl β-d-galactopyranoside, resulting in the formation of two dimeric complexes: (6-MP)2⊃(methyl β-d-glucopyranoside)2 and (6-MM)2⊃(methyl β-d-galactopyranoside∙2H2O)2, respectively. These two complexes exhibit distinct folding structures with domain-swapping cavities depending on the bound guest and temperature. Interestingly, (6-MM)2⊃(methyl β-d-galactopyranoside∙2H2O)2 is exclusively formed at lower temperatures, while (6-MP)2⊃(methyl β-d-glucopyranoside)2 is only formed at higher temperatures.

Abstract Background and aims There are limited comparative data for infliximab and vedolizumab in inflammatory bowel disease patients. Methods We conducted a systematic review and meta-analysis to compare the efficacy and safety of infliximab and vedolizumab in adult patients with moderate-to-severe Crohn’s disease or ulcerative colitis. Results We identified six eligible Crohn’s disease and seven eligible ulcerative colitis trials that randomised over 1900 participants per disease cohort to infliximab or vedolizumab. In the Crohn’s disease and ulcerative colitis cohorts, infliximab yielded better efficacy than vedolizumab for all analysed outcomes (CDAI-70, CDAI-100 responses, and clinical remission for Crohn’s disease and clinical response and clinical remission for ulcerative colitis) during the induction phase, with non-overlapping 95% confidence intervals. In the maintenance phase, similar proportions of infliximab- or vedolizumab-treated patients achieved clinical response, clinical remission, or mucosal healing in both Crohn’s disease and ulcerative colitis. For the safety outcomes, rates of adverse events, serious adverse events, and discontinuations due to adverse events were similar in infliximab- and vedolizumab-treated patients in both diseases. The infection rate was higher in infliximab for Crohn’s disease and higher in vedolizumab when treating patients with ulcerative colitis. There was no difference between the treatments in the proportions of patients who reported serious infections in both indications. Conclusions Indirect comparison of infliximab and vedolizumab trials in adult patients with moderate-to severe Crohn’s disease or ulcerative colitis demonstrated that infliximab has better efficacy in the induction phase and comparable efficacy during the maintenance phase and overall safety profile compared to vedolizumab.

In this study, the vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was developed using ferritin complexes with the immunogenic sequences screened against the SARS-CoV-2 spike protein (SP) from the Fv-antibody library. The Fv-antibody library was prepared on the outer membrane of E. coli by the expression of the VH region of immunoglobulin G (IgG) with a randomized complementarity-determining region 3 (CDR3). Four Fv-antibodies to the receptor-binding domain (RBD) were screened from the Fv-antibody library, which had a comparable binding constant (KD) between SARS-CoV-2 SP and the angiotensin-converting enzyme 2 (ACE2) receptor. The binding sites of screened Fv-antibodies on the RBD were analyzed using a docking analysis, and these binding sites were used as immunogenic sequences for the vaccine. The four immunogenic sequences were modified and co-expressed as a part of ferritin which was assembled into a ferritin complex. After the vaccination of ferritin complexes to mice, the anti-sera were analyzed to have a high enough titer. Additionally, the immune responses were found to be activated by vaccination, such as the expression of IgG subclasses and the increased level of cytokines. The neutralizing activity of the anti-sera was estimated using a cell-based infection assay based on pseudo-virus expressing the SP of SARS-CoV-2 variants. [ABSTRACT FROM AUTHOR]

In this study, we introduce a novel training algorithm specifically designed to overcome the limitations of GPU memory on a single DGX-A100 system. By utilizing the CPU and main memory in the training process and applying a strategy of division and parallelization, our algorithm enhances the size of the trainable language model and the batch size. In addition, we developed a comprehensive management system to effectively manage the execution of the algorithm. This system systematically controls the training process and resource usage, while also enabling the asynchronous deployment of tasks. Finally, we proposed a scheduling technique integrated into the management system, promoting efficient task scheduling in a complex, heterogeneous training environment. These advancements equip researchers with the ability to work with larger models and batch sizes, even when faced with limited GPU memory.

Recently, language models based on the Transformer architecture have been predominantly used in AI natural language processing. These models, which have been proven to perform better with more parameters, have led to a significant increase in model size and computational load. ALBERT solves this problem by significantly reducing the number of parameters it retains by repeatedly reusing parameters. Although ALBERT significantly reduces the parameters it maintains, it requires a computational load similar to the original language model due to the reuse process. In this study, we develop a distillation system that decreases the number of times the ALBERT model reuses parameters and progressively reduces the parameters being reused. We propose a representation in this distillation system that can effectively distill the knowledge of the original model and develop a new architecture with reduced computation. Through this system, F-ALBERT, which had about half the computational load compared to the ALBERT model, restored about 98% of the performance of the original model on the GLUE benchmark.

With the increase in intelligent voice phishing and the increasing reliance on open banking systems, there has been a rise in cases where individuals’ personal information has been exposed, resulting in significant financial losses for the victims. Non-face-to-face transactions in the financial sector face challenges such as customer identification, ensuring transaction integrity and preventing transaction rejection. Blockchain-based distributed ledgers have been proposed as a solution but their adoption is limited due to the difficulty of managing private keys and the burden of gas fees management. This paper proposes a non-face-to-face P2P real-time token payment system that minimizes the risk of key loss by storing private keys in a keystore file and database through a server-based key management module. The proposed system simplifies token creation and management through a server-based token management module and implements an automatic gas-charging function for smooth token transactions. Transaction integrity and non-repudiation are ensured through a transaction confirmation module that uses transaction IDs without exposing personal information. Furthermore, advanced security measures such as blocking foreign IP access and DDoS defense are implemented to securely protect user data. The proposed system aims to provide a convenient, secure and accessible online payment solution to the public by implementing a self-authentication function using a web application that is not limited to smartphones or application platforms.

Abstract The use of kidneys from donation after brain death (DBD) donors with acute kidney injury (AKI) is a strategy to expand the donor pool. The aim of this study was to evaluate how kidney transplantation (KT) from a donor with AKI affects long-term graft survival in various situations. All patients who underwent KT from DBD donors between June 2003 and April 2016 were retrospectively reviewed. The KDIGO (Kidney Disease: Improving Global Outcomes) criteria were used to classify donor AKI. The cohort included 376 donors (no AKI group, n = 117 [31.1%]; AKI group n = 259 [68.9%]). Death-censored graft survival was similar according to the presence of AKI, AKI severity, and the AKI trend (p = 0.929, p = 0.077, and p = 0.658, respectively). Patients whose donors had AKI who received using low dose (1.5 mg/kg for three days) rabbit anti-thymocyte globulin (r-ATG) as the induction agent had significantly superior death-censored graft survival compared with patients in that group who received basiliximab (p = 0.039). AKI in DBD donors did not affect long-term death-censored graft survival. Low-dose r-ATG may be considered as an induction immunosuppression in recipients receiving kidneys with AKI because it showed better graft survival than basiliximab.

Due to the sharp increase in household waste, its separate collection is essential in order to reduce the huge amount of household waste, since it is difficult to recycle trash without separate collection. However, since it is costly and time-consuming to separate trash manually, it is crucial to develop an automatic system for separate collection using deep learning and computer vision. In this paper, we propose two Anchor-free-based Recyclable Trash Detection Networks (ARTD-Net) which can recognize overlapped multiple wastes of different types efficiently by using edgeless modules: ARTD-Net1 and ARTD-Net2. The former is an anchor-free based one-stage deep learning model which consists of three modules: centralized feature extraction, multiscale feature extraction and prediction. The centralized feature extraction module in backbone architecture focuses on extracting features around the center of the input image to improve detection accuracy. The multiscale feature extraction module provides feature maps of different scales through bottom-up and top-down pathways. The prediction module improves classification accuracy of multiple objects based on edge weights adjustments for each instance. The latter is an anchor-free based multi-stage deep learning model which can efficiently finds each of waste regions by additionally exploiting region proposal network and RoIAlign. It sequentially performs classification and regression to improve accuracy. Therefore, ARTD-Net2 is more accurate than ARTD-Net1, while ARTD-Net1 is faster than ARTD-Net2. We shall show that our proposed ARTD-Net1 and ARTD-Net2 methods achieve competitive performance in mean average precision and F1 score compared to other deep learning models. The existing datasets have several problems that do not deal with the important class of wastes produced commonly in the real world, and they also do not consider the complex arrangement of multiple wastes with different types. Moreover, most of the existing datasets have an insufficient number of images with low resolution. We shall present a new recyclables dataset which is composed of a large number of high-resolution waste images with additional essential classes. We shall show that waste detection performance is improved by providing various images with the complex arrangement of overlapped multiple wastes with different types.

Background : Graft survival rate of kidney transplantation recipients improves after induction therapy. However, there is no conclusive evidence on which regimen is superior for deceased donor kidney transplantation (DDKT). This study aims at discussing effective induction therapy in DDKT. Methods : Between 2003 and 2016, 395 DDKT recipients were divided into three groups following induction therapy. Recipients of the basiliximab group (n=184) received basiliximab (20 mg/kg) on days 0 and 4. Recipients of the low-dose rabbit anti-thymocyte globulin (rATG) group (n=113) received rATG (1.5 mg/kg) on days 0, 1, and 2, while those of the high-dose rATG group (n=98) received it for more than 4 days. We retrospectively reviewed and analyzed the clinical outcomes and adverse effects of induction therapy.Results : Compared to other groups, the low-dose rATG group donors were older (P

This study researched the current occurrence status of viral diseases of solanaceous crops in the main production areas of Gangwon region, for four years from 2014 to 2018. From 2014 to 2018, in eight cities and counties including Chuncheon, Cucumber mosaic virus (CMV), Broad bean wilt virus 2 (BBWV2), Pepper mild mottle virus (PMMoV), Tomato spotted wilt virus (TSWV), and Potato virus Y occurred in chilli peppers. In case of tomato, the research was performed in 2017 and 2018 while TSWV and Tomato yellow leaf curl virus (TYLCV) were verified in Chuncheon, Hoengseong, and Cheorwon. Especially, TYLCV occurred in Chuncheon region for the first time in 2017, which was verified in 2018. Lastly, the current occurrence status of viral diseases of bell peppers was researched in seven cities and counties like Gangneung, Hoengseong, and Cheorwon from 2015 to 2018. In the results, CMV, BBWV2, PMMoV, Pepper mottle virus, and TSWV were verified in bell peppers of Gangwon region. During the research period, there were no crops suspected or infected by Beet western yellows virus, so that it is judged that there is no villiferous or infected aphid by this virus in Gangwon-do. Such results of this study could be used as the basic data for the stable production of crops through the early prevention of plant diseases occurring in the solanaceous crops of Gangwon region.